In my first Scout Note last week, I took a retrospective look at transfers. More specifically, I revisited a group of Scandinavian breakout players who had previously been identified through data and explored how their careers have developed since.

In this second post, we stay with the topic of transfers, but broaden the perspective by adding a layer of club-level strategy through a concept I refer to as “The Domino Effect.”

A quick internet search defines the domino effect as “a chain reaction where one initial event triggers a series of similar or related events.”

In football transfers, that initial event might simply be one club wanting to sign a player from another.

If that player is an important starter, however, the selling club may be reluctant to let him leave until they have identified and secured a suitable replacement. That replacement may then be an important player for another club, which suddenly faces exactly the same problem.

This is where the domino effect begins.

One transfer creates the need for another, which creates the need for another, and so on. What initially looks like an isolated player transaction can therefore develop into a chain of interconnected recruitment decisions across several clubs and leagues.

This Scout Note follows one such chain, involving a particular type of player:
the flying full-back.

Daniel Muñoz

The initial event triggering the chain reaction in this analysis was the potential transfer of Daniel Muñoz to Nottingham Forrest.

Since joining Crystal Palace, the Colombian has consistently performed at a high level as what we would describe as a “Flyer” archetype fullback. Primarily deployed as a right wing-back in Oliver Glasner’s system, Muñoz contributed four goals and three assists during the 2025/26 campaign, while also scoring twice at the 2026 World Cup.

His numbers were even stronger the season before, when he recorded four goals and five assists. The underlying data from that campaign also reinforced his profile, placing him among the most threatening attacking fullbacks across Europe’s top five leagues:

With Glasner moving to Nottingham Forest, it is therefore perhaps no surprise that he wants to bring Muñoz with him, particularly as Forest appear to be adopting a very similar structure to the one he used at Palace. So far this season, they have predominantly lined up in a 3-4-3.

For that transfer to happen, however, Crystal Palace first needed to find a replacement.

And you may have noticed that a relatively unknown player started at right wing-back for Palace against Manchester City last weekend, while Daniel Muñoz remained on the bench.

Anan Khalaili

That player was Anan Khalaili, who made his debut at right wing-back against Manchester City. After the game, Opta highlighted an interesting statistic:

From this stat alone, Khalaili already looks well suited to the Premier League, matching N’Golo Kanté’s tally of tackles on his debut.

But there is more to his profile than defensive intensity. Khalaili has also produced a strong attacking output from right wing-back in the Belgian Pro League with Union Saint-Gilloise, contributing regularly with both goals and assists, similar to Munoz.

Given USG’s ownership connection with Brighton, it is hardly surprising anymore when another relatively unknown talent emerges from their recruitment network. The club has built an impressive track record of identifying hidden gems across different markets.

In Khalaili’s case, USG signed the Israeli from Maccabi Haifa for €6.5 million shortly after his 20th birthday. Since then, he has scored 15 goals in Belgium before being sold for around $24.5 million roughly two years later, generating a profit of close to €20 million.

So, while Crystal Palace may have found their replacement for Muñoz, the domino effect does not stop there.

It simply moves on to USG.

If Khalaili is the player Palace have identified to replace Muñoz, then USG are suddenly faced with the same question: where do they find their next Flyer?

And crucially, that is a question they likely needed to answer before allowing Khalaili to leave.

Denzel De Roeve

In my previous Scout Note, I highlighted why Scandinavia has become such an attractive recruitment market. One of the factors was the high number of defensive engagements across the region, which could suggest that players are relatively well prepared for the physical demands of other high-intensity leagues.

The Norwegian Eliteserien could therefore be an interesting market for USG when searching for Khalaili’s replacement.

More interestingly, in another SCOUTED article, they looked at fullback “nests” across different European leagues, identifying teams and environments that consistently develop or deploy certain stylistic profiles.

The graph below shows which teams across the selected European leagues make the most overlap and underlap runs per 30 minutes of possession.

Notably, SK Brann, our close partner club at PlayIQ, are among the teams in Europe that use these movements most frequently in attack.

From this type of team profiling, the next step becomes relatively intuitive: scout and look at the full backs who play in these teams.

For Brann, that leads us to Denzel De Roeve, a young right-sided Flyer.

And, as fate would have it for USG, De Roeve is Belgian himself. That potentially makes the transition even more natural, with fewer cultural and environmental barriers to adaptation. A graduate of the Club Brugge NXT academy, De Roeve was signed by Brann for just €400k ahead of the 2025 season.

There is also more evidence to support De Roeve as a promising Flyer for the future.

I previously highlighted him in How Strategy Can Beat Spending, where I was scouting for attacking fullbacks suited to an imaginary back-three system:

At the time, I highlighted De Roeve and Kodou as they were among the youngest fullbacks in the sample who also appeared attainable for MLS clubs. Looking back at the initial shortlist, however, I could just as easily have highlighted Anan Khalaili, who also featured here.

De Roeve had been linked with USG throughout the summer as a potential replacement for Khalaili. But with Brann relying on him during their European qualifiers, they were reluctant to let him leave before their qualification campaign had been decided.

De Roeve ultimately helped Brann secure a place in the Conference League. Shortly after the final qualifier, he was on his way to Belgium.

And that brings us to the next and last domino.

Who should Brann bring in as their replacement to De Roeve?

Leo Cornic

The final domino in this recruitment chain is Leo Cornic’s move from Tromsø IL to Brann.

As the chart below shows, Cornic profiles very similarly to his predecessor as a Flyer. De Roeve, however, had a broader profile in the data, also scoring above average as a Pathfinder.

The chart shows how full-backs in the 2026 Eliteserien season are distributed across the Flyer and Pathfinder archetypes in our archetype models:

Looking more closely at the underlying movements, Cornic stands out particularly for runs in behind and cross-receiver runs. He performs fewer of the overlap and underlap movements that are also strongly associated with the Flyer archetype, but this likely reflects the tactical environment he currently operates in.

Cornic is therefore asked to perform fewer of the overlap and underlap movements that feature prominently in Brann’s Flyer profile. Brann use their full-backs differently, asking them to move beyond or inside the winger far more frequently.

In that sense, Cornic’s data at Tromsø may reflect the role he has been asked to perform just as much as the type of full-back he can become at Brann.

That does not mean he has lacked attacking output. Last season, Cornic contributed five goals and three assists, showing that he can still provide significant offensive value. The heatmap below reinforces that picture.

Cornic holds a consistently high position on the right side, with frequent touches in advanced areas and repeated presence in and around the opposition box. So even if Tromsø’s structure does not generate the same volume of classic overlap and underlap runs, the underlying behaviour still points towards an aggressive, attack-minded fullback profile.

This makes the translation particularly interesting. Based on the stylistic differences between the two teams, I would expect his number of overlap and underlap runs to increase significantly at Brann. However, it could take some time to adjust although his previous experience across different clubs and systems can suggest a quick adaptation and good fit.

And that points towards one of the more interesting questions in recruitment: can we identify players whose underlying characteristics might become even more valuable when placed in a different team, role or tactical environment?

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Sources:

SCOUTED. (2025). An Introduction To Full Back Archetypes. URL: https://scoutedftbl.com/an-introduction-to-full-back-archetypes/

SCOUTED. (2025). Finding a nest for Full-back Flyers. URL: https://scoutedftbl.com/finding-a-nest-for-full-back-flyers-data-scouting/

What fascinated me most was how tracking data could measure counterfactuals: not just what happened, but what could have happened. For example, identifying which players consistently made themselves available as passing options between the lines.

This inspired the first Modern Playmaker article and later helped us identify potential breakout players across different markets.

Scandinavia in particular proved to be, and still is, a booming market for emerging talent. So I wanted to revisit some of the players we identified there, what happened next, where they are now, and which signals in the data made them stand out in the first place.

Wonderkid

Sverre Nypan was one of the hottest young players on the market in 2024, and he also topped the data charts for both playmaking and pressing at the time.

After earning his big move to Manchester City, he has since gone through a loan spell at Middlesborough and beginning his second one in Belgium club, SK Lommel, as he continues his development. Here is a quote from Nypan at the Man City Podcast earlier this year:

It is a reminder that progression is rarely linear, especially for young players moving early to the very highest level. It's a journey reminiscent of Martin Ødegaard's: after joining Real Madrid at 16, he spent years out on loan at Heerenveen, Vitesse, Real Sociedad and Arsenal before the move to north London was made permanent. At only 19, I still think there is plenty more to come from Nypan.

French Connection

Two other players highlighted in the breakout shortlist were Noah Nartey and Thomas Jørgensen, both playing in the Danish Superliga at the time and until recently.

Nartey stood out particularly for his progressive ability and has since moved to a young and exciting Lyon side, which looks like a strong environment for his development. Check out these clips for a quick look at how he’s settling in so far.

Jørgensen, on the other hand, just recently moved to Toulouse for around €9 million as the total package. His off-ball profile was especially interesting, showing the early potential of a very complete midfielder who could drop deeper to support build-up while also influencing the game as a playmaker higher up the pitch. Both are players I'm excited to follow this season. And the timing could hardly have been better: they met in the Ligue 1 opener the past weekend, both in the starting XI.

First blood went to Nartey as Lyon won 2-0. He got on the scoresheet and was FotMob's man of the match with a rating of 8.0. It was an efficient performance from Nartey: 0.07 xG converted into 0.47 xGOT tells you everything about the quality of the finish.

However, Jørgensen won the xG battle and really should have scored after a fantastic run in which he glided past several defenders, only to finish wide - also confirmed in the data through his xGOT at 0.00! Check out the highlights here.

Honorable Mentions

Jens Hjertø-Dahl is another player which stood out for his playmaking and pressing profile before moving to Hull. His 1.93m frame also makes him particularly well suited to the increasingly physical demands of the modern game, perhaps making him better equipped than most for the step straight into a newly promoted Premier League side.

Felix Horn Myhre, meanwhile, made the move to West Brom in the Championship. A technical and advanced #8, his profile aligned particularly well with the developer archetype described with my eyes below.

Fun fact: Myhre is a player I know particularly well from watching him live multiple times at Brann Stadium in Bergen. His low centre of gravity, quick turns after receiving the ball in tight spaces, and constant runs into the half-spaces between the opposition full-back and centre-back are some of his standout traits.

We also saw some Scandinavian players move to Portugal. Physicality is again a keyword here. Silas Andersen joined Sporting, while Victor Froholdt moved to FC Porto. Both stood out for their physical capabilities, fitting what we described as ground eaters, or in more traditional football terms, box-to-box midfielders.

Speaking of ground eaters, that might actually be one of the reasons Scandinavia has become such an attractive market for clubs in England and France. The chart below shows that the Scandinavian leagues have some of the highest volumes of defensive engagements.

Not only has Scandinavia become an attractive market, clubs are now competing to get there as early as possible, increasingly forcing them to operate with smaller sample sizes.

In a previous LinkedIn post, I mentioned Zadok Yohanna, who was picked up by Brighton after only having played seven games in the Swedish Allsvenskan this season. He stood out particularly in 1v1 attacking situations and has already earned his first minutes against Aston Villa at the weekend.

Porto also signed Eirik Granaas at 16 years old and only 15 first team games for Fredrikstad, another example of how early clubs are now moving for Scandinavian talent. He is also the little brother of Sondre Granaas at Molde FK, another promising playmaker.

And the talent pipeline shows no sign of slowing down.

15-year-old Gabriel Rajkovic recently scored his first Eliteserien goal against Bodø/Glimt, while another 15-year-old, Isaiah Skovsgaard, debuted with an assist for KFUM.

Scandinavia is clearly booming, but the same principle applies elsewhere.

Data and smart modeling can help identify players before they become obvious to the wider market.

Everyone has data now. The real advantage is knowing what to look for, building models that capture it, and identifying talent early enough to act on it.

One successful signing, and the long-term value or profit generated from it, could in theory fund an entire data department.

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Today’s article is a collaboration with Samuel Villalta, from our Football Intelligence team at PlayIQ. In the second of two articles on Japan, we examine their offensive structure and consider whether they had the attacking tools to go further in the tournament. Enjoy!

Japan’s 2026 World Cup campaign ended in the Round of 32, but their patient attacking structure, built around width, overloads and combinations in tight spaces, revealed a clear tactical identity.

Attack vs Medium Block

One of Japan’s important build-up ideas was to drop one of the number sixes into the back line when they had possession. This gave them an extra player in the first line of build-up and allowed one of the outside centre-backs, usually the left-sided defender Hiroki Ito, to move higher. By doing this, Japan could create better control on the side of the pitch, support their wide attacks and ultimately stretch the opponent horizontally.

However, this movement also had a weakness. When one midfielder dropped into the back line, Japan often had fewer players in the middle of the pitch. This meant they could lose some central control, especially against teams that pressed well or had strong midfield players. But this was part of their game plan. Japan was not always trying to dominate the centre. Instead, they wanted to create advantages on the sides.

Patience and Wide Overloads

Japan were comfortable moving the ball from side to side being patient in possession. Their attacking plan was based on strong relationships between the wing-back, outside centre-back, number ten, and striker. These players combined in small spaces, especially near the touchline, because of Japan’s many technical players who are comfortable under pressure.

They often tried to bring several players toward the strong side, where the ball was. This helped them create overloads, short passing options, and quick combinations. At the same time, Japan kept players ready on the weak side. When the opponent shifted across to defend the ball side, Japan could switch play quickly and attack the opposite side.

This was clear in their 4-0 win over Tunisia. Japan dominated the game with aggressive pressing, quick transitions, and patient possession. In fact, they operated with an average width of almost 60 meters when attacking against the medium block of Tunisia.

In the second half, they kept the ball, switched play from side to side, and looked for openings before scoring two more goals. That result became Japan’s highest-ever goal tally in a World Cup match. Their goal below is a great example of how they used patience through switches to open up space inside centrally.

Their wide relationships also appeared against Sweden. Japan’s best first-half chance came from a combination down the left between Kamada, Maeda, and Nakamura. Later, Japan took the lead through a well-worked move involving Sugawara, Doan, Ueda, and Maeda attacking the space behind the defensive line.

Attacking vs High Block

Another observation from Japan’s offensive performance at the 2026 World Cup was how their build-up improved after the first game. Against the Netherlands, Japan had some problems progressing the ball from the back. They drew 2-2, but in possession they did not always have clean solutions when the Netherlands pressed them. Japan built up in a 4-2-4 structure, with the double pivot in front of the back line, but their rotations in the first phase were not always effective.

One of the main issues was the movement of the forwards who came low to receive. In the Netherlands game, the player dropping toward the ball was often the strong-side forward. This gave Japan one short option, but it did not really change the opponent’s defensive shape. Because the support was coming from the same side, the Netherlands defense could anticipate the action and step up to prevent them from progressing.

Japan found solutions to this problem in the following games. Instead of only using the strong-side forward to come short, they started bringing the weak-side forward across to the strong side. This was a small but important adjustment. By moving the weak-side forward toward the ball, Japan created a numerical advantage around the strong side. Furthermore, it created a marking problem for the opponent. The weak-side forward gave Japan an extra passing option between the lines, and it also created better angles for third-man combinations. The adjustment also helped Japan stay true to their main attacking idea. They still wanted to overload the strong side, combine in tight spaces, and attract pressure.

At the same time, Japan did not completely abandon the weak side. Even when one weak-side forward moved across to help the build-up, Japan still kept width on the opposite side through the wing-back or another attacking player. This meant that if the opponent shifted too aggressively toward the ball, Japan could still switch play and attack the far side.

This improvement was clear in the next matches. Japan beat Tunisia 4-0 in their second group game, their biggest World Cup win, by scoring a goal which came through a beautiful buildup.

What Happened vs Brazil?

The problem against Brazil was that Japan did not trust their offensive structure enough in the second half. After taking the lead through Kaishu Sano, they became too passive and stopped pushing up and controlling the ball. Their high block moments disappeared and Brazil gained more territory and control. This is reflected in Japan’s 30 per cent pitch control throughout the game and 26 minutes defending in the low block, equal to 63 per cent of their out of possession time.

For large parts of the game, Japan held control within their own block, reflected in their block-relative pitch control, but they gradually gave up more of the field and were pushed deeper as a result, which shows up in their overall pitch control.

This was a missed opportunity because Japan had already shown they could solve pressure in different ways. Their build-up improved after the Netherlands game, especially when they started bringing the weak-side forward across to the strong side to create numerical advantages and better passing angles.

Summary

Japan were not eliminated because they lacked an attacking identity. Throughout the tournament, they had a clear structure: building patiently, using wide overloads, combining in tight spaces, and keeping the option to switch play and attack behind the last line. Their 3-4-2-1 gave them good relationships between the wing-back, wide centre-back, number ten, and striker, which helped them progress through the sides.

For Japan to go deeper in the competition, one can argue that more offensive bravery is needed in knockout games. With a clear attacking idea, they appeared to have the necessary tools to get past Brazil, even when the game became difficult.

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Japan’s 2026 World Cup campaign ended in the Round of 32, but their compact and adaptable defensive block revealed a clear tactical identity and made them extremely difficult to break down.

Defensive Structure

Japan set up in a 3-4-2-1 formation in possession. Out of possession, however, the structure became a compact block where the two No. 10s dropped in alongside the central midfielders, and the wing-backs tucked into the back line to make a back five. The priority was staying compact and outnumbering the opposition centrally, pressing only when the right triggers appeared.

Low Block

Japan’s defensive block changed height depending on the opponent, but its purpose stayed the same: protect the centre and force play wide. Against presumed stronger teams, Japan defended deeper, using a low block for 62% (19m 38s) of their defensive time against the Netherlands and 63% against Brazil. Against weaker teams like Tunisia and Sweden, they spent more time defending in a medium block, respectively 53% and 52%. Independent of the block height, Japan stayed narrow and compact, with short distances between players, making it difficult for opponents to progress through the middle. Japan wanted to lead the Netherlands towards the wide areas, where they could press aggressively and win the ball back.

The insight below shows Japan’s average width/depth in a low block, and the Netherlands’ average attacking structure against it.

Medium Block

Japan did not simply sit back and wait. From within their compact block, they pressed selectively, using specific triggers such as a heavy touch, a pass into a tightly marked player, or a backwards pass as cues to step out and challenge for possession. Rather than pressing continuously, they remained disciplined until the right moment emerged. A clear example came during a medium block phase against the Netherlands, when Japan held their shape before collectively stepping out to regain the ball.

The insight below shows Japan’s average width/depth in a medium block, and the Netherlands’ average attacking structure against it.

High Block

At times, Japan chose to press high, for example on the opponent’s goal kicks. Against the Netherlands, Tunisia and Sweden the effect was often the same: with the short pass cut off, the goalkeeper was forced to go long. This seemed to be a clear strategy from Japan, as they were well set up to deal with the long ball: a centre-back moving up to the intended target, with players close by to collect the second ball.

The insight below shows Japan’s average width/depth in a high block, and Brazil’s average attacking structure against it.

Unlike Japan’s previous opponents, Brazil were willing to take greater risks in their build-up rather than accept the long ball. Japan responded by pressing aggressively, going man-to-man across the pitch and forcing mistakes deep inside Brazil’s own half.

Disciplined or Passive?

There is a fine line between remaining disciplined in a low block and allowing that discipline to turn into passivity. The chart below shows the change in pitch control between the first and second half when they were defending in the low block. Notably, they lost control in crucial zones in and around the box.

For 45 minutes against Brazil, Japan were arguably the better team. They led through Kaishu Sano, and PlayIQ’s block control had them ahead 45 per cent to 40 in the first half, matching Brazil around the ball while sitting deep. Japan also showed occasional spells of keeping possession, frustrating Brazil at the end of the first half. At half-time, however, Brazil made changes to their shape, and the second half looked very different.

With Endrick coming on, this meant that Vinicius Junior moved wider towards the left. This gave Brazil greater width and stretched Japan’s compact block horizontally, creating more time and space to deliver crosses into the box. It became their main solution against the low block, and led directly to the equaliser.

The greater risk was not simply that Japan defended deep, but that they stayed there for too long. Defending in a low block demands constant concentration and significant physical effort, especially when the team offers little threat in transition or gets a hold of possession. Japan’s block control fell from 45 per cent in the first half to 31 in the second, reflecting how much less they competed around the ball after the break. With no sustained pressure of their own, Brazil could keep attacking, recycle possession, and return the ball into the box. Japan were unfortunate to concede so late in added time, but once they stopped posing a threat, the equaliser increasingly felt like a matter of time.

Summary

Our analysis of Japan’s defensive structure revealed a highly drilled team, capable of shifting between all three block heights while maintaining their compactness and aggression. However, Japan also demonstrated how a disciplined low block can gradually become passive, particularly when protecting a lead in the knockout stages.

In the next article, we turn our attention to Japan’s attacking structure and examine how they looked to create chances.

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Today’s article is a collaboration with Maxi Luedy, Head of Football Intelligence at PlayIQ. Maxi went deep into one phase of the game where we believe Norway are vulnerable - but it might also be their strength. Enjoy!

Before every major tournament, there is one question that always comes up: who will be this year’s “dark horse”? In essence, this means who will be the surprise performer besides the big teams.

Ahead of the 2026 World Cup, Norway featured prominently in that conversation. An unbeaten qualifying campaign, combined with a golden generation led by Erling Haaland and Martin Ødegaard, made them one of the tournament’s most intriguing outsiders.

So far, they have lived up to the expectations. Norway progressed to the knockout stage with an energetic, front-foot approach and moments of individual brilliance from their biggest stars. Furthermore, head coach Ståle Solbakken decided to rest the entire starting lineup for the last group game against France, prioritising the freshness in the round of 32 against Ivory Coast. This is a testament to the ambitions of the team.

But how far can they really go? And despite the quality throughout the squad, are they still too dependent on individual players?

We analysed Norway’s performances throughout the group stage and found a team with clear strengths but also collective issues that could ultimately limit how far they can go in this tournament.

We will be analysing Norway’s build-up play in particular. Using our analytical layers within PlayIQ Edge, we examine how they approach the first phase of possession against a high block, and why this phase of the game can become overly dependent on individual quality and improvisation.

Attacking vs High Block

Firstly, we can take a look at Norway’s average positions and pass networks when attacking against a high block.

Norway typically line up in a 4-3-3 formation, with Erling Haaland as the focal point of the attack. Antonio Nusa (RB Leipzig) operates from the left, providing pace, directness, and excellent 1v1 ability, while Alexander Sørloth (Atlético Madrid) starts on the right despite not being a natural winger. Deploying Sørloth on the flank has been Ståle Solbakken’s solution to fitting both strikers into the same starting XI.

As we will see later in this analysis, Sørloth has adapted remarkably well to the role, allowing Norway to maximise his strengths within their attacking structure. His physical presence and aerial ability give Norway an important outlet under pressure, whether by targeting him with long balls, using him to hold up play, or simply giving the team a reliable option when opponents press aggressively. One of the clearest examples came in the build-up to Norway’s opening goal against Iraq.

Sørloth’s role in the goal cannot be overstated. His ability to hold up the ball and attract multiple defenders creates the conditions for Norway to progress, switch play and attack the weak side. Without his individual quality, the move simply does not develop in the same way.

The sequence ultimately ends in an excellent team goal, but it also highlights an important contrast. While Norway possess the individual quality to solve difficult situations, the build-up itself does not always provide the best conditions for progressing the ball cleanly. Throughout the group stage, Norway struggled at times to play through the high blocks of both Iraq and Senegal, often relying on moments of individual brilliance rather than collective solutions. Against Senegal, the contrast was particularly clear: Senegal completed twice as many progressions through the first line as Norway. More interestingly, 52 per cent of Norway’s progressions behind the 1st and 2nd line came on Sørloth’s right side.

Let’s take a closer look at why through the video examples below.

Missing Collective Tools?

In the first clip above, Iraq gradually shift from a medium block into an aggressive high block. Rather than manipulating the opposition through their own positioning and circulation, Norway allow Iraq’s press to dictate the build-up. As a result, the attack becomes rushed and ultimately ends with a long ball towards Sørloth.

The second example is a similar situation from the Senegal game. Again, we see a similar decision from Norway. Ajer chooses to play into the right-back rather than finding Ødegaard centrally, despite Ødegaard having both the technical quality to receive under pressure and the surrounding conditions to connect the next pass. From that central position, Norway would have had several options to progress the attack. Instead, the ball is played wide, the full-back is immediately pressed, and Norway are once again forced into a longer pass towards Sørloth. This is exactly why the touchline is so often used as a pressing trap: once the ball travels wide under pressure, the receiver’s options become limited by the sideline.

There are several moments in the build-up where simple collective tools and agreements could have created clean solutions to play through the press centrally, which in turn could create more solutions in the next phase of play.

So, is the tendency to progress wide a deliberate strategy from Norway or is it actually a lack of collective tools and agreements in build-up?

We now examine another sequence which highlights the center backs’ decisions in build-up.

Early in the game against Senegal, we can see another example of Norway playing out to the right-back, Ryerson, rather than progressing centrally. A collective tool, often referred to as the “third-man principle”, is available once again, with Ødegaard dropping towards the ball and Berge positioned to receive the lay-off. Instead, Norway play wide, and as a result Ryerson immediately comes under pressure. Torbjørn Heggem, the left-sided center back, also had the opportunity to progress centrally earlier in the move.

The sequence also highlights a lack of communication between Ryerson and Sørloth. Sørloth initially makes a movement towards the ball before spinning in behind, while Ryerson expects him to come short. At the same time, Ajer has not provided a supporting option in depth, leaving Ryerson without a viable passing solution.

Although the examples in this section focus on small details, together they reveal a consistent pattern. Norway often lack the collective mechanisms needed to play through medium and high presses, instead allowing opponents to dictate their build-up. Against stronger teams, such as France in the final group match, these situations can quickly become costly.

Interestingly, when Norway fielded their B-team against France, we saw a team that attempted to progress centrally at times. In the clip below, they were nearly punished after a ball loss in their own half.

On the other hand, we did actually see some signs of Norway utilizing collective tools in their build-up.

Deliberate strategy or improvisation?

Whether these sequences were intentional remains somewhat unclear, particularly as Norway were without Sørloth as their usual outlet on the right side. At the same time, the variety of build-up patterns suggests that the players are not always fully aligned on the intended approach; whether to play short, wide, through the centre, or more directly. As a result, Norway often appear to rely on individual quality and improvisation when attacking against a high block. That said, the risks associated with progressing centrally become much more apparent against stronger opposition, which may explain a more cautious approach in build-up.

Norway can still progress the ball by bypassing the build-up altogether, often by playing directly into Sørloth. That approach can certainly be effective, but relying on it too heavily makes the team predictable. If Norway are to make a deep run in this tournament, they will likely need more solutions than simply going direct.

Outcome

In this analysis, we have identified a phase of the game where Norway can look vulnerable. However, it is important to acknowledge that we do not know the team’s exact tactical instructions. The patterns we have highlighted may therefore not simply reflect poor decision-making, but instead a deliberate strategy: accepting less control in the build-up phase in exchange for reduced risk and more favourable opportunities to play directly into Sørloth or Haaland, thereby exploiting some of the squad’s greatest strengths.

There have already been several examples at this World Cup of teams being punished for trying to progress centrally under pressure. With that in mind, Norway may deliberately avoid taking unnecessary risks in central areas. Instead, they invite the opposition higher up the pitch before playing directly into Sørloth, allowing them to bypass the press and attack the spaces left behind.

If that is indeed the intention, then this becomes less of a weakness and more of a calculated tactical trade-off. As discussed earlier, getting the ball into Sørloth solves many problems. His ability to compete physically, secure possession, and connect the next action allows Norway to bypass large parts of the build-up phase altogether. Combined with Haaland’s pace and finishing ability, it gives Norway a direct route from defence to attack that few teams can replicate.

Whether this approach will be enough against the tournament’s strongest opponents remains to be seen.

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Today’s article is a guest post from Mads Storebø, one of our interns in the Football Intelligence team at PlayIQ. Mads has done a great job with the analysis, and I’ve been happy to support the process with feedback along the way. Enjoy!

South Korea impressed in their World Cup opener versus Czech Republic with a 2-1 win. While Korea struggled with Czech Republic’s set-pieces, creating a tight and hard-fought game, they dominated in open-play sequences.

In this article we will showcase some of South Korea’s main attacking characteristics, and how they were able to punish Czech Republic with a combination of tactical discipline, relational movements and individual excellence.

The match dashboard above shows the average position and passing network of players in both teams when faced with a medium block. Our first observation is how similar the two structures are in possession: both sides set up with wingbacks as their primary width holders and kept relatively compact, central passing networks that broadly reflect their on-paper shapes. That said, South Korea’s shape does look a touch more expansive: their wingbacks held a noticeably higher position on the pitch than the Czech’s, stretching the network further up the field and giving it slightly more width and depth overall.

Another observation is that a couple of players stood out as especially involved for each side. Both teams leaned heavily on their right wing-back in build-up — Vladimír Coufal for Czech Republic and Seol Young-Woo for South Korea. Tomáš Souček was the other key connector in the Czech midfield, while for South Korea much of the play ran through right-sided attacking midfielder Lee Kang-In and the no. 6 Hwang In-Beom.

Regarding territory, the Korean team controlled both pitch control (43.8% to 40.7%) and relevant pitch control (46.4% to 35.0%). This means that the Korean team controlled the most space overall but also the most important spaces near and around the ball.

In the next section, we will analyse South Korea in possession, by looking at their attacking structures and how they managed to progress through lines. Later, we will show how Lee Kang-In held a central role within the Korean team.

Attacking Structure

South Korea’s 3-4-3 structure is characterised by a combination of positional and fluid movements. Wingbacks Lee Tae-Seok and Seol Young-Woo repeatedly moved high and wide to stretch the Czech back five vertically and horizontally. Furthermore, they looked to keep a “box”-shape intact centrally, where attacking players could move in and between lines.

The image above showcases how South Korea often operated in attack against a medium block. The initial 3-4-3 shape quickly develops into a 4-2-4 shape in this phase in front of the first line of pressure. A key feature is that one of the central midfielders, in this case Paik Seung-Ho, drops into the defensive line to create a back four, initiating play outside of the Czech defensive block.

We also see that the box-shape centrally remains intact, with attacking midfielder Lee Jae-Sung dropping into the pocket Paik Seung-Ho has left, and striker Son Heung-Min filling his previous position. The result of this setup is that South Korea has numerical superiority in midfield. This was a key feature of South Korea’s attacking structure and a major factor in breaking down Czech Republic, who spent long periods without the ball, as shown in the phase distribution chart below.

More interestingly, South Korea consistently progressed from building against a high block (9 minutes) to attacking against medium (11 minutes) and low blocks (8 minutes), demonstrating both control and progression through the thirds. But how exactly do they do this?

Positional Rotations

South Korea’s positional rotations created the foundation for more fluid, relational movements. They consistently looked to combine through central areas and exploit their numerical superiority in midfield.

In the clip above, South Korea’s box midfield is positioned between the Czech defensive lines, creating multiple options for combination play. As the Czech block shifts towards wing back Seol Young-Woo, he spots Lee Jae-Sung between the lines and finds him with a lofted pass.

From there, South Korea transitioned from positional occupation to quick relational play. Lee Jae-Sung immediately combines with Lee Kang-In, whose ability to receive under pressure destabilises the Czech shape. After evading several defenders, Kang-In exploited the space created by the Czech block’s narrowness to progress the attack into wider areas.

This sequence highlights South Korea’s tendency to look for Kang-In in decisive moments. His freedom within the attacking structure is a key mechanism for breaking down opposition defences, as the next section will further demonstrate.

The Individual Within the System: Lee Kang-In

Lee Kang-In stood out as the player in the Korean team who brought unpredictability to the system. Kang-In’s positional freedom is especially evident when South Korea find themselves in attacking sequences higher in the pitch, as South Korea often search for him to initiate relational combinations over the positional movement patterns.

The progression chart highlights South Korea’s ability to break lines across different areas of the pitch. They most frequently bypassed the first line of pressure on the left side (27 passes), often drawing the Czech block across before switching play. Once through the initial press, attacks were commonly directed towards the right side, where they recorded the most line-breaking passes through the second defensive line (8).

This pattern frequently brought Lee Kang-In into play. Operating as the right-sided attacking midfielder, he regularly drifted in and out of Czech Republic’s narrow block, making him difficult to track without disrupting the defensive structure. His teammates complemented these movements by exploiting the spaces and passing angles he created.

The clips below highlight how Kang-In’s movement and positioning consistently caused problems for the Czech defence.

The Creator

In this sequence, Kang-In drops deeper to receive possession. Rather than following him, Ladislav Krejčí holds his position to protect the last line, aware of the space that could open behind him as Seol Young-Woo stretches the Czech defensive structure horizontally.

Kang-In’s technical quality is evident in his first touch, using the momentum of the pressing defender to turn into space and face the back line. From there, he quickly spots Jae-Sung Lee’s run beyond a flat Czech defence and clips a pass into his path.

The Decoy

In this attack, Lee Kang-In moves as a decoy alongside Seol Young-Woo, drawing defenders away and creating a large gap in the inside channel. South Korea then exploits the space with a well-timed run from midfield, highlighting how Lee Kang-In’s influence extends beyond his involvement on the ball.

The Collective

South Korea’s opening goal encapsulated many of the attacking principles highlighted throughout this analysis: coordinated positional rotations, intelligent occupation of space, and Lee Kang-In’s creative freedom.

In the build-up, the Korean wingbacks pinned the Czech wingbacks on the last line, while Kang-In occupied a central position within South Korea’s narrow box structure. As centre-back Gi-Hyuk received possession, Kang-In dropped deeper to offer a passing option. Simultaneously, left wingback Tae-Seok moved towards the ball, pulling Vladimír Coufal out of position.

These movements created uncertainty within the Czech defence. With several South Korean players occupying central spaces, the Czech centre-backs were forced into difficult marking decisions. As Kang-In received, Hwang In-Beom immediately attacked the space vacated by Coufal. At the same time, Robin Hranáč was drawn towards Son Heung-Min, further opening the passing lane.

Kang-In identified the opportunity and threaded a pass into Hwang’s path. Hwang then bypassed both the recovering Hranáč and goalkeeper Matěj Kovář with a clever feint before finishing calmly.

The goal illustrates how South Korea combine collective structure with individual freedom. Their use of wingbacks, central rotations, and coordinated movements consistently generated space, while Kang-In’s awareness and creativity allowed them to capitalise on it.

Summary

South Korea’s 2–1 victory over Czech Republic showcased a possession model that effectively balances positional structure with individual freedom. Through coordinated rotations, a well-functioning box midfield, and aggressive wingback positioning, they consistently manipulated the Czech defensive block and progressed the ball into dangerous areas.

At the heart of this approach was Lee Kang-In. His movement, creativity, and ability to exploit space gave South Korea a constant attacking reference point, whether receiving the ball himself or creating opportunities for others through his clever movements and positioning.

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Welcome to the PlayIQ World Cup series.

Throughout the tournament, we will deliver tactical analysis supported by PlayIQ’s analytical layers and models, allowing us to go deeper into key moments and provide context beyond the eye test.

For our first article, we have analysed Brazil vs Morocco: a game shaped by tactical trade-offs, high-level decision-making, and fine margins.

Here is how the teams set up:

The dashboard above uses PlayIQ’s deep tracking data to illustrate the average positions of both teams when attacking against an opponent in a medium block. Several interesting patterns emerge:

The first is Vinícius Júnior’s high and wide positioning for Brazil. Given that he is one of their most dangerous attacking players, Brazil appears to deliberately isolate him in wide areas to maximise his one-versus-one opportunities. In contrast, the right side of Brazil’s attack provides relatively little width. Their passing network is also notably congested, with most connections concentrated in central areas, reflecting what was effectively a 4-2-3-1 structure in possession.

Morocco, by comparison, displays a much more decentralised passing network. More player nodes remain connected to one another, and the strength of the connections is distributed more evenly across the team. This type of network structure is often indicative of a well-coordinated and cohesive collective, where ball progression and possession responsibilities are shared across multiple players rather than concentrated in a few key individuals.

As we can see in the chart below, Morocco produced slightly more line breaks than Brazil — particularly behind the first and second line on the right-hand side, a detail that will make more sense later in the article.

Territorially, the match was quite balanced. Brazil controlled slightly more of the pitch overall (43.1% to 39.6%). The picture shifts, however, when we narrow the lens to relevant pitch control — control measured only within the active zone surrounding the ball. There, Morocco led 46.0% to 37.5%, suggesting they were generally better positioned around the ball even as Brazil held more of the pitch as a whole.

In the next section, we will analyse the goals using pitch control and passing option models. This will allow us to examine the tactical decisions behind each scoring sequence and assess the trade-offs made by both teams throughout the match.

Communication is Key

Brazil initially built their attack down the right side, but lost possession as they tried to progress. From there, their reaction after the turnover was too passive, which gave Mazraoui time to receive and lift his head at left-back.

As a right-footed player on the left side, Mazraoui is naturally positioned to play inside or diagonally across the pitch, allowing Morocco to escape the pressure and attack the space Brazil have left open.

Using our probability-based model, we can assess his passing options in real time. The data shows that both Brahim and Saibari are viable options, highlighted by the green lines. However, Brahim’s pitch control value of 2.5%, combined with his positioning, indicates that he is the passing option most likely to increase the team’s probability of scoring.

Isolating the pitch control of the most relevant players, we can see that Brahim has attracted three Brazilian defenders but still has enough space to receive and play forward. Hakimi’s run on the right wing also increases Brazil’s defensive uncertainty, while Vinícius’ higher positioning appears connected to the team’s tactical organisation and communication rather than an individual defensive error. This leaves Gabriel caught between stepping out to protect the space Hakimi is attacking, or closing the space in front of Saibari.

A perfectly weighted pass and a well-timed run allow Saibari to maintain relevant pitch control in behind Brazil’s defensive line. Marquinhos should adjust across earlier to cover Saibari’s run, as there is no immediate danger on his outside. This allows Saibari to attack the space with momentum and receive in a high-value area.

By analysing both the attacking and defensive perspectives, we can better understand the relationship between communication, tactics, and individual decision-making. At the highest level, the margins are incredibly small — a defensive recovery or a clean line break can hinge on a few metres of space and a split-second read. This is where pitch control and probability models help us quantify what the eye can easily miss.

Vini’s Tactical Advantage

Brazil’s equalising goal starts with a long goal kick from Bounou. Interestingly, Hakimi is the player who steps forward to attack the duel, which he eventually loses against Douglas Santos. By doing so, he risks leaving space behind him.

The second frame shows the ball dropping to Paquetá, who can immediately look for Vinícius. This time, Vinícius is able to take advantage of the high tactical position he has been occupying, especially with Hakimi now late to recover. We can also see that Morocco’s back line is disorganised, keeping Vinícius onside.

Vinícius thrives in these 1v1 situations, especially when he has space to attack in front of him. El Aynaoui fills in as a temporary right-back and initially recovers well, but then rushes out towards Bruno Guimarães unnecessarily. This opens a new gap for Vinícius to exploit, also marked as the most ideal passing option based on scoring probability.

The pass is played between El Aynaoui and the centre-back. As El Aynaoui rushes back again, Vinícius can easily move inside and finish.

This sequence shows another example of tactical trade-offs. In the first goal, Vinícius’ high position created potential vulnerability for Brazil defensively. However, in the equaliser, we see how that same positioning may have been an intentional choice by Brazil and Ancelotti to exploit the space behind Hakimi.

Fine Margins

Across both goals, the same theme holds: at this level the difference between a successful attack and a defensive recovery often comes down to a few metres of space and a fraction of a second. Brazil’s decision to keep Vinícius high and wide carried a defensive cost on Morocco’s opener, yet created the exact advantage they needed to equalise.

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We use repositioning to examine an offensive case from the Norwegian Cup Final and a defensive breakdown from Brann’s defeat to Sarpsborg 08.

Pitch control helps us understand who controls space, while probability models reveal passing options. But combined, can they also tell us where a player should have been, or where he should move next?

In the first article, we defined pitch control and showed how to identify relevant space. The second went even deeper, using different analytical layers and passing option models for pre- and post-match analysis, and hinted that the same logic could drive individual player development. This is the use case we want to explore further in this article.

As before, we examine specific examples and game scenarios. This time, we will show how repositioning can increase the value of a passing option and, with it, the team’s scoring chances. We look at an offensive case from the Norwegian Cup Final between Brann and Bodø/Glimt, and a defensive case from Brann’s last home game against Sarpsborg 08, where they lost 1–2, exploring how positional adjustments could have changed the outcome.

Offensive Case

Possession Won in the Final Third

The sequence begins with a Brann counter-press which leads to a dangerous break. A loose ball falls to attacker Ulrik Mathisen, who suddenly finds himself behind Bodø/Glimt’s defensive line, with possession inside the box.

Although Mathisen is through on goal, the angle favours the defenders. As a right-footed player, he struggles to create a clear shooting opportunity for himself. At the same time, striker Kristian Eriksen is arriving in the box and appears to be a potential passing option.

Mathisen elects to play a lofted pass across the face of the goal, targeting Eriksen. However, the pass bypasses both Eriksen and the recovering Bodø/Glimt defenders before running through the penalty area.

Insight #1 – Evaluating Eriksen’s Positioning

The first frame evaluates Eriksen as a passing option through the probability-based lens introduced in Applied Pitch Control #2, where options are ranked by their likelihood of increasing the team’s scoring chances. Viewed through an availability-based lens, however, the option shifts from green to yellow. This suggests that while Eriksen occupies a dangerous position, he may be difficult to reach at that exact location.

So, could he have positioned himself differently to become more available and increase the scoring probability?

Insight #2 – What If Eriksen Had Made a Different Run?

The images above explore an alternative scenario using our repositioning tool to analyse the change in values and availability if Eriksen had positioned himself differently. Instead of maintaining his original run, we have repositioned Eriksen towards the back-post area. This is the exact zone where Mathisen’s pass eventually travelled.

By moving into this space, Eriksen’s availability score increases due to an improved passing angle and fewer defenders in the way of the pass. The movement not only increases the likelihood of a successful reception but also places Eriksen in a significantly more dangerous area should he receive the ball. In other words, the area targeted by Mathisen’s pass represents the most dangerous attacking space available to Brann at that moment, and precisely where our repositioning analysis suggests he should have been.

Pitch control models can move beyond describing who controls space and begin to identify where players should position themselves.

This example demonstrates how execution and decision-making interact. Mathisen selected the optimal passing location, but the opportunity broke down because no attackers occupied the intended space. While the outcome was influenced by luck and the unpredictable nature of football, it is also shaped by a series of small decisions made in real time.

Defensive Case

A Sequence of Costly Decisions

The sequence culminates in a Sarpsborg goal, but the decisive moment is not a single defensive mistake. The goal emerges from a chain of interconnected errors that progressively weaken Brann’s defensive structure and increase Sarpsborg’s control of space.

Insight #1 – A Stretched Defensive Structure

The move begins with Sarpsborg’s aggressive high press. Under pressure, Brann are forced to play a long ball towards striker Kristian Eriksen, who is isolated against two Sarpsborg defenders.

The long pass immediately creates a structural problem for Brann. With the attacking players positioned far ahead of the midfield and defensive units, the team becomes stretched vertically. When the initial duel is lost, Sarpsborg are better positioned to compete for the second ball.

The first frame shows Sarpsborg retaining control, with the ball eventually played to Claus Niyukuri, who can receive in space. The failed attempts to press the loose ball have effectively removed five Brann players from the defensive phase, leaving a significant gap between the midfield and defensive lines. The second frame shows how this space could be compressed by repositioning the defensive line higher up the pitch.

Insight #2 – Soltvedt Steps Out of the Defensive Line

As Niyukuri receives the ball, defender Joachim Soltvedt leaves the defensive line to apply pressure. Although the intention is understandable, the timing and distance of the press create a difficult situation. Soltvedt engages from a position where he is neither close enough to make an immediate challenge nor deep enough to protect the space behind him.

Niyukuri quickly recognises this and exploits the situation. Using his forward momentum against Soltvedt’s relatively static position, he bypasses the defender and continues his run. The consequence is not only that Soltvedt is eliminated from the play. His movement also opens additional space for winger Sondre Sørli, reflected in the pitch control, effectively creating a dangerous attacking opportunity.

The second frame shows the impact of repositioning Soltvedt back into the defensive line. In doing so, he retains relevant pitch control. This is a trade-off that prioritises the threat of the opposing winger over the space the full-back could run into.

Insight #3 – Insufficient Cover Defence

At the same time, midfielder Niklas Wassberg is in a position where he could potentially step in and slow down Niyukuri’s progression. However, Wassberg is also responsible for tracking the run of midfielder Victor Halvorsen, who is advancing in support of the attack. Faced with two competing threats, he hesitates between protecting the passing lane and engaging the ball carrier.

This moment of indecision allows Niyukuri to continue his run unchallenged. Rather than forcing the attacker sideways or backwards, Niyukuri is allowed to carry the ball directly towards the defensive line.

By the time Niyukuri reaches the final defensive line, Brann’s earlier mistakes have created a difficult numerical and spatial dilemma. Defender Vetle Dragsnes is forced to make a choice: stay connected to Sørli and protect the wide threat, or step across to confront Niyukuri’s central penetration. With Niyukuri driving directly at goal, Dragsnes chooses to engage the ball carrier. While understandable, this leaves Sørli unmarked. Niyukuri exploits the newly created space by playing the ball wide, and Sørli finishes to score.

A goal is often remembered as the final pass and finish, but the analysis shows that the decisive moments occurred much earlier.

The initial long ball stretches Brann’s structure. The inability to compete for the second ball creates excessive distances between the lines. Soltvedt’s attempt to step out opens additional space, while the lack of effective cover pressure allows Niyukuri to continue advancing. The other individual decisions appear relatively minor in isolation. Together, however, they create a cascading effect that progressively increases Sarpsborg’s attacking options while reducing Brann’s defensive control.

Summary

In this article, we have highlighted how the outlook of a situation changes when players are repositioned in decisive moments, and how this affects both pitch control and passing options.

By comparing a player’s actual position with alternative positions, we can identify movements that create more attacking opportunities or improve defensive coverage. Beyond post-match analysis, the same approach has clear applications for individual player development, helping players better understand which positional decisions give their team the greatest advantage.

In the first article, we introduced relevant pitch control and the idea that not all controlled space is equal. In this second installment of the applied pitch control series, we go a step deeper by showcasing how different layers and models can be combined in analysis workflows. As before, we examine specific examples and game scenarios — this time from the Norwegian cup final between SK Brann and Bodø/Glimt.

In the situation above, Bodø/Glimt is sitting in a medium block focused on controlling the central spaces of the pitch. The block spans 26.5 metres in width and 18.5 metres in depth. Its compact shape has left space on the outside, and Brann’s far-side winger Ulrik Mathisen has recognised this, signalling his availability. Would a switch of play be viable here?

With analysis layers and performance value models, we can compare and assess exactly that.

Passing Options by Space

The image below shows the same situation, now with the defensive block layer removed and our pitch control layers and passing option model applied instead.

The passing option model highlights all viable passing options based purely on how much space each player owns and controls if the ball were played into their area. In this instance, the model identifies five viable options for the ball carrier, while the faded red lines toward Brann players inside Bodø/Glimt’s block indicate far less available space.

We can also view the same situation on a 2D pitch map, this time switching to our vectorised model, which accounts for each player’s direction, speed, and ball speed.

The pitch map displays a Voronoi diagram of the entire pitch, making it straightforward to see the complete zones each player controls. The arrows at each player’s node indicate their facing direction at every frame (referee shown as the yellow node). Direction combined with velocity and ball speed influences each player’s pitch control and, in turn, the perception of the best passing options at any given moment. Looking at this image, for example, Brann’s left attacking midfielder appears positioned to receive based on his body orientation, even though the static pitch control in the first image suggested otherwise.

Passing Options by Probability

Pitch control and space provide a strong foundation for reading game situations, but the option with the most space is not necessarily the best one, nor the one most likely to increase a team’s scoring chances. To address this, passing options can also be assessed through a probability-based lens, closely related to Expected Threat frameworks.

In the image below, we have switched to a passing option model based on probability: which passing option increases the team’s chances of scoring the most from this exact moment?

The situation is the same as before, but the decision insight has shifted. The probability model now aligns with Brann’s right winger: a switch of play is the most viable option, and if executed well, it will do the most to improve the team’s scoring prospects. Several factors drive the model’s assessment here. Mathisen has a large area of space to run into and a considerable distance to his nearest defender, making the wide option particularly attractive given where opponents are positioned.

How It Played Out

In the sequence above, Soltvedt’s ball-striking ability allowed him to pick out Mathisen perfectly into space. Mathisen drove into the opponents’ box and set up a clear cutback chance. Only strong recovery defending from Bodø/Glimt prevented it from becoming a goal for Brann.

Gaining an Edge

In this article, we have used block structure, pitch control, and probability to analyse a game situation from multiple angles. By layering different models on top of each other, we can assess and evaluate the viability of passing options in a structured way, useful for both pre- and post-match analysis. More interestingly, the same approach holds potential for individual player development: helping teams align on prioritised spaces and improving the decisions that give them the best chance of scoring.

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But more data doesn’t automatically lead to better decisions. The real challenge is identifying what actually matters; turning data into actionable insight rather than noise.

So what kinds of models and insights actually move the needle?

One of the most interesting approaches in this space is pitch control. At PlayIQ, we use pitch control to support both performance analysis and recruitment: whether it’s preparing for opponents pre-match, evaluating team behaviour and sequences post-match, or identifying players who consistently create and exploit valuable space.

This article marks the first in a series where we apply our models to real game situations. The aim is simple: to show how pitch control translates from theory into practical insight. In this edition, I will analyse the recent derby between SK Brann and the Norwegian champions Viking.

Defining Pitch Control

First, it’s important to note that pitch control is not a new concept. Models describing control of space have been around for years, and were notably applied and developed further when Liverpool hired William Spearman in 2018 as lead data scientist within Ian Graham’s research team.

With that in mind, it makes sense to refer to Spearman’s definition:

Pitch control (at a particular location) is the probability that a player could control the ball, assuming it were at that location.

— William Spearman

In essence, we are trying to explain and anticipate events in the game based on how players control space. Pitch control assigns a dynamic probability to different areas of the pitch, representing the likelihood that a given player will reach the ball first based on their positioning relative to opponents.

In other words, it all comes down to one question: given the game context in a specific moment, who will get to the ball first?

Example 1: Aerial Duel

In the situation below, a long ball is about to be played from the Viking centre-back. Based on the pitch control model, the most likely outcome is that Brann will recover possession comfortably since they dominate the central areas (marked in red).

However, the ball drops into a small central pocket controlled by a Viking player. He wins the duel against two Brann midfielders, and with both the striker and a supporting midfielder positioned to attack the second ball, Viking’s pitch control shifts decisively in their favour.

Although Brann managed to regain possession in the following phase, Viking came close to establishing control and launching a dangerous attack.

Voronoi Diagrams

As we’ve seen, pitch control divides the pitch into regions based on which player is most likely to control a given space at any moment. In its simplest form, this can be understood through what is known as a Voronoi diagram.

A Voronoi diagram is a mathematical method used to partition space into regions, where each region contains all points closest to a specific reference point (a player, in this case). Applied to football, this means assigning each area of the pitch to the nearest player. These regions can then be interpreted as the areas a player is most likely to control if the ball is played there.

However, this is a simplified view. Football is dynamic, and the player closest to the ball is not always the one who will reach it first.

To account for this, modern pitch control models incorporate ball and player movement; variables such as velocity, direction, and physical capabilities like speed and acceleration. This shifts the model from a purely distance-based approach to one based on time to arrival: estimating which player can reach the ball first given the full dynamics of the situation.

This is what Spearman refers to as a Temporal Voronoi model, a more realistic representation of how players compete for space and possession.

With more realistic models, we have a strong foundation for analysing the game contextually. In the next section, we assess what we refer to as relevant pitch control as some spaces and game situations are more important than others.

Relevant Pitch Control

In the introduction, we highlighted the challenge of deciding what truly matters in an ocean of data. The same applies to pitch control models.

Not all areas of the pitch are equally valuable. A goalkeeper, for instance, may control a large amount of space (as seen in the Voronoi diagram above), but much of it carries limited threat or impact. In contrast, a striker can control highly valuable space in behind the defense with relatively little coverage or percentage of the pitch.

This perspective allows us to move beyond pitch control as a general concept and instead focus on relevant pitch control: specific game situations where control of space has the potential to be decisive, often also referred to as key moments or turning points.

Example 2: Goal

Let’s look at the situation where Brann scored their equaliser.

In the first phase, Brann and Viking have an equal number of players in a compact area of the pitch. However, it is the positioning and movement of these players that ultimately determines pitch control and the potential to resolve the situation.

Although the right-back, De Roeve, holds the highest level of pitch control at this moment, it is less valuable than control in more advanced and dangerous areas.

Felix Horn Myhre has the lowest pitch control (0.3%) and is tightly marked by two Viking players. However, a closer look reveals that he is already scanning towards Eriksen anticipating the next phase of play. When the ball is eventually played to Eriksen, he quickly combines with Myhre, who exploits the situation with a smart third-man run. This movement allows Myhre to break into a dangerous half-space and increase his pitch control (0.6%) before receiving.

At the same time, Brann’s striker Noah Holm recognises the opportunity and initiates a run in behind Viking’s defence. What stands out is the amount of space Holm is already controlling in depth while still remaining onside. Myhre opts to play him in and Holm finishes clinically with a powerful strike at the near post.

Summary

In this article, we have explored the concept of pitch control and how it builds on the mathematical foundation of Voronoi diagrams. We applied our models to two specific use cases: a goal-kick situation leading to a duel, and a passing sequence culminating in a goal.

The aim was to move closer to the idea of relevant pitch control recognising that some areas of the pitch carry greater strategic importance than others.

Going forward, I will explore these concepts and models in more detail through more case studies, with a particular focus on how vectorised approaches can provide even deeper insight into performance and spatial control.

References

Austin, S. (2020). Training Ground Guru: William Spearman, How Liverpool Create Pitch Control Models. Link

Spearman, W. (2020). Friends of Tracking: Liverpool FC data scientist William Spearman’s masterclass in pitch control. YouTube

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In the first installment of complimentary squad building, we focused on identifying suitable defenders and midfielders.‍

‍In this second part, we will complete the squad by scouting attacking players.

Scouting for Wingers

The first wide attacker we’re looking for is the explosive winger. Our recent case study, Scouting Wingers with Physical Data, revealed that many elite wingers don’t stand out in the data when using traditional volume or high-intensity metrics. What sets them apart is instead explosivity and the ability to change direction quickly. Using explosivity as a proxy, we can identify wingers who thrive in 1v1 situations and create real impact on the flanks.

Below, we highlight several wide attackers (U25) from the 24/25 season who scored above average in explosivity-related metrics last season:

Many of the players we’ve highlighted have already moved clubs after last season, with a few promising talents remaining on our shortlist. We will continue to monitor two right wide attackers in particular: Montadar Madjed (Hammarby) and Jeremy Sebas (SC Bastia).

We have now identified wingers based on their physical profiles - an effective tool of identifying them in the first place. However, we are also interested in seeing which wide attackers excel in creating shots for their teams.

Viewing the two charts together, we have identified Montader Madjed as an option for our right wing. He ranks highly for explosiveness and sits among the top 20 shot creating wingers in our sample. Stylistically, he produces 1.55 shots per 30 TIP from carries that end in individual shots, underlining his ability to turn possessions into direct shots.

On the opposite flank, we are targeting Edwin Austbø (21 in December) and recently named Young Player of the Year in the NOR1 Eliteserien, winning the league with his boyhood club. His profile is more geared towards shot creation through carries ending in passes and crosses (team sequence), which complements our left side dynamic of a shot creating winger, a flying full back, and a developing midfielder.

Given the competition for profiles like these, we are also monitoring Marius Broholm, now at Lille, and Hugo Bolin, now at Borussia Monchengladbach. Should they struggle for consistent playing time, a loan move could be realistic, particularly since we can offer a clear pathway and guaranteed minutes.

Finally, we will also try to join the race of signing Aral Simsir at FC Midtjylland. With 8 goals and 13 assists this season, he offers both end product and versatility in our attacking lineup.

Scouting for Strikers

The final position we are looking to strengthen is centre forward, and we are targeting two distinct striker archetypes.

First, a direct runner who consistently threatens in behind, stretches the back line and creates depth in our attacking play. Second, a traditional target man who can offer a strong physical presence in the box, attack crosses and provide a focal point against low blocks when space is limited.

For the first profile, we are revisiting SCOUTED’s earlier piece where they profiled the Power Forward - inspired by Viktor Gyökeres. This is an archetype that combines a majority share of runs in behind as their main off ball run type with pure speed and athleticism which we can measure with PSV-99 (peak speed velocity):

The chart highlights several promising center forwards. The fastest is Adam Daghim, currently on loan at Wolfsburg. Further to the right, we find two young Norwegian strikers: Henrik Skogvold (Fredrikstad) and Daniel Karlsbakk (Sarpsborg 08). At the far right, a small group of players stand out for their tendency to make runs in behind, with over 30 per cent of their runs falling into this category.

Next, we want to find out which players fall into the target man category. In this case, we are simply going to rank the players by their share of cross receiver runs.

Leading the target man list, Alie Conteh (21) stands out, with almost 40 per cent of his total runs being cross-receiver runs. Following Stromsgodset’s relegation from the NOR1 Eliteserien, Conteh joined Finnish side Inter Turku on loan, with an option to buy. We can also take note of Kasper Høgh (25), who impressed as the focal point of Bodø/Glimt’s incredible run in the Champions League this season.

Another intriguing target man is Anosike Ementa, towering at 202 cm. Signed by Zulte Waregem in the BEL1 Pro League, Ementa combines extreme physicality with a surprising movement profile - his most frequent off-ball run is Pulling Half-Space Runs, and he ranks in the 96th percentile for Dangerous Passes among Belgian centre forwards in the current season.

It’s also worth noting that several Power Forwards from our previous chart appear in the Target Man list. To refine our striker shortlist further, we want to focus on those who contribute to generating the most shots for their teams through their runs.

One of the first names that stands out is El Junior Kroupi from his time at Lorient last season. He has since made a strong start in the ENG1 Premier League with Bournemouth. We also find David Strelec, who moved to Middlesbrough from Slovan Bratislava.

Topping the ranking for runs in behind leading to shots, however, is Matej Trusa, who still plays in the SLK1 Nike Liga.

As we are leaning towards a slightly younger profile, Daniel Karlsbakk emerges as a particularly interesting option. He leads all players for cross-receiver runs leading to shots and has featured in our two previous charts both as a Power Forward and as a Target Man. After returning to Sarpsborg 08 in Norway following his first move abroad to the NED1 Eredivisie, he scored 18 goals and finished as the top scorer in Norway’s first division last season.

Another profile worth highlighting is Tawfik Bentayeb. He ranked highest in our Box Crashing metric among centre forwards, averaging 3.1 one-touch shots in the penalty area per 30 TIP. The Moroccan appears to have maintained that level this season, already recording 12 goals in 18 games, with only 14 starts, for Troyes in FRA2 Ligue 2.

Let’s have a look at the off ball profiles of our shortlisted striker prospects:

Daniel Karlsbakk will be our main target, as he ranks highly for the two most central run types; runs in behind and cross receiver runs.

The second profile we would like to add to our squad is Anosike Ementa because of his unique profile, reminiscent of Nick Woltemade and the rare Gravitar Archetype developed by SCOUTED. He can give us something different as an option at center forward, either through general hold-up play or as a weapon against aggressive sides, targeting his teammates in behind.

Lastly, we also wanted to show Eli Junior Kroupi’s off ball profile, which is that of a much more dynamic striker, but we already have a similar profile in Ota Yamamoto here with experience as a center forward too (although lacking a bit when it comes to runs in behind).

The Shadow Team

Having reviewed all the main position groups, we can now assemble a shadow team, a structure commonly used in scouting to visualize how potential signings might fit together on the pitch. This allows us to place each player in their intended position and role, giving a clearer picture of how the profiles could function as a collective.

Our preferred starting lineup is highlighted below in the shadow team, while the alternative options, potential substitutions or “gamechangers”, are shown in a more faded tone:

One of the most noticeable aspects of our squad and the profiles we have selected is the tactical flexibility they provide. The team is capable of operating in several different structures depending on the situation.

For example, we can line up in a traditional back four while also shifting into a situational back three thanks to the Flyer archetype on the left side. This allows the fullback to push higher while the rest of the defensive line adjusts behind him.

If we want to take even greater control of possession and dominate games, Silas Andersen can step into midfield, effectively creating a box midfield giving us numerical superiority in central areas. Midfield superiority can also be achieved by selecting a center forward who drops deeper to receive the ball, such as Ementa or Yamamoto.

A third way of creating superiority comes on the left side through local combinations between the Flyer, the Developer and the left winger. This dynamic can overload the flank and create confusion for the opponent. It can also emerge through a simpler movement pattern, with the Flyer pushing high while the left winger drifts into the half space to receive between the lines.

Contextual Scouting: From Data to Decision

Throughout the process, the aim has been to identify a range of complementary profiles. While some players share certain qualities, others bring contrasting strengths and characteristics. This variety provides tactical flexibility and allows the team to adapt depending on specific game situations, strategic priorities, or the way opponents choose to defend.

At the same time, the squad has been assembled with a relatively low average age, aligning with a strategy focused on player development and long term resale potential. Because of this, we need to stay patient and allow the signings time to adjust and grow into their roles and get integrated in the club and new environment.

Scouting players through data is not always straightforward. This is where archetypes and clearly defined profiles, grounded in football concepts and language, become particularly valuable. Context also plays a crucial role, as football is a complex and dynamic game where the same metric can carry different meanings depending on the role or tactical environment.

For that reason, we applied different methodologies and selected different metrics for each position on the pitch. Our hope is that this approach can inspire your own data driven scouting and serve as a starting point for the first stage of the recruitment process: identifying players who fit your tactical ideas and squad building strategy.

Get an overview of all the SCOUTED Archetypes here

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Modern recruitment is no longer about identifying the best individual players in isolation. It is about understanding how different profiles interact, overlap, and amplify each other within a collective structure. A high-level individual can struggle when placed in the wrong role or system, while a more modest profile can thrive when the environment allows his strengths to surface and his weaknesses to be protected.

This article explores how clubs can build squads based on complementary skills by combining position-specific profiles with SCOUTED Archetypes. Using Game Intelligence and Physical data, the aim is to move from isolated player evaluation toward intentional squad design where the collective output or the whole is greater than the sum of its parts.

Rather than asking “Is this player good?”, we shift the question to “What type of synergies can this player unlock when paired with others?”

Scenario: Club with A Development-Focused Recruitment Model

Imagine a club operating in the “next five” leagues with a clear development mandate.

The recruitment strategy prioritises young, high-upside players from emerging markets, offering them a platform to develop, gain exposure and playing time, which eventually can generate meaningful resale value. The objective is not short-term optimisation, but sustainable squad evolution.

This club targets an average starting XI age under 25, builds around learning environments rather than fixed hierarchies, and accepts squad churn as part of its competitive model. In this context, recruitment success depends less on star profiles and more on how well individual skill sets complement each other across units and phases of play.

As a development-focused club, our game model is built around ball dominance and positional control. However, modern football trends have made it clear that technical security alone is no longer sufficient. The game has become increasingly transitional, placing greater demands on physical capacity, robustness, and the ability to repeatedly perform in high-intensity moments on both sides of the ball.

Therefore, we look to identify players who can contribute to a proactive, ball-dominant style of play while also possessing the athletic tools required to survive and exploit transitional moments.

Based on this game model, we have constructed a shadow team composed of positional profiles and SCOUTED Archetypes. This serves as a strategic blueprint for our data-driven scouting process, helping narrow the search toward players whose skill sets align not only with individual roles, but with the collective demands of the team.

Scouting for Defenders

Center backs are arguably the most complex position group to evaluate because they are highly dependent on team context and defensive structure. Furthermore, high engagement volumes in defensive metrics can often introduce noise. Strong defenders may therefore appear almost invisible in the data, as intelligent positioning frequently prevents situations from occurring in the first place.

By dissecting the data more carefully, however, we can still separate profiles and highlight the traits that truly distinguish them. We can also use on ball engagement outcomes for this purpose. This approach was explored effectively in a recent piece by SCOUTED, which introduced a useful spear and shield analogy when analysing defenders through data. Some centre backs operate as spears, characterised by high engagement volumes and proactive interventions, while others function as shields, preserving structure and reducing danger through positioning rather than frequent defensive events.

Our objective is to identify at least one player from each profile. Our method of separating the defenders in the sample is by creating two performance indices, one for spears and one for shields. We visualize the two archetypes in a scatter plot further down.

The scouting pool that we are operating with consists of CZE1 First league, DEN1 Superliga, SWE1 Allsvenskan, NOR1 Eliteserien, SUI1 Super League, AUT1 Bundesliga, POL1 Ekstraklasa, SRB1 Superliga, SVK1 Nike Liga and FRA2 Ligue 2 from the 24/25 season:

* “Spear and Shield” performance indices created and plotted in the Web App Lab (WAL)

Ranking highest for “spears”, we find Modou Keba Cissé at Lask Linz. He embodies this aggressive archetype as he sits inside the 98th and 99th percentile for On Ball Engagements P30 OTIP and Direct Disruption and Regain Percentage. By researching Cissé more closely, we found that he has already been signed by Aston Villa on a pre-deal agreement before next season - a testament to his potential and a validating sign for our data scouting. Just behind him, we also find two RB Salzburg defenders, Samson Baidoo (now at Lens) and Joane Gadou. This leaves us with three candidates for this role; Adama Drame (now at Wolfsberger), Sedi Kinteh (Tromsø IL) and Junior Ligue, a Swiss youth international who was just recently signed by Venezia and loaned out to Mantova in Serie B. Being left-footed and previously having experience as a center forward, we believe he can fit into our left center back position as a front foot defender and potentially even cover the offensive left back role if needed.

Moving to the center of our defence and focusing, we find Ange Ahoussou with the highest average performance for our “shield” metrics. He ranks within the 98th percentile for both indirect disruption and regain percentage and stop or reduce danger percentage. Nehemiah Fernandez, now at Nancy and previously in the PSG academy profiles somewhere in between a spear and a shield. The same can be said for Silas Andersen (BK Hacken) who we profiled as a rare hybrid defender/midfielder in our previous analysis, How Strategy Can Beat Spending. Not only that, he is extremely proficient on the ball as well - ranking in the 100th percentile for our “Ball Playing Central Defender” index. Therefore, Andersen will be our choice for the ball-playing centre back role on the right side of our back three.

The final defender we aim to sign is the ‘Flyer’ archetype, a flying full-back which we also searched for in the mentioned article above. Here, we found several interesting options for both right-back and left-back.

Our chosen player is the 21-year-old South African, Samukelo Kabini, who currently plays left-back for Molde FK in the NOR1 Eliteserien. Kabini is an explosive talent, averaging 5.52 Overlap Runs P30 Tip well within the 90th percentile of young full backs, fulfilling a specific skillset we need for the synergies we want to leverage on the left side of our attack.

Scouting for Playmakers

Our shadow team includes several positional profiles we have previously explored in depth, allowing us to apply earlier findings directly to specific roles.

Last year, we published two extensive pieces on profiling The Modern Playmaker and Pressing Playmakers. The combination of these profiles evolved into a more holistic data profile which we called The Dynamic Playmaker - inspired by the Japanese market and the increased trends and focus on transitions and vertical football.

* Scatter plot created in our Web App Lab (WAL): U27 Midfielders in J1, J2, K1 (2025 season)

When merging the two performance indices, our top ranked player was Sota Kitano, who earned a move to RB Salzburg last summer.

However, another profile stood out to us in the J2 League: Ota Yamamoto.

Not only did Yamamoto (21) rank inside the top ten of our overall Total Index Score (IP and OOP), he also featured in our recent collaboration with SCOUTED when they went “shopping” in Asia for the Championship. Yamamoto ranks well above average in both Carries at Speed per 30 TIP and High Intensity Activities per 90 when compared to Championship midfielders, suggesting that his profile translates well to a more transitional and physically demanding environment which is a tick for our recruitment strategy and game model.

Chart retrieved from SCOUTED: Scouting Asia For The Championship

Perhaps most importantly, Yamamoto offers tactical flexibility. He can operate as a dynamic advanced midfielder but also as a centre forward, giving us optionality within squad construction.

Now on a new loan in the J2-league at Red Bull owned Omiya Ardija, Yamamoto is likely to feature on several shortlists heading into the 2026 season. As a result, he is the first name on our team sheet. A Dynamic Playmaker from Japan.

Scouting for Midfielders

Moving forward with our recruitment, we will remain focused on the midfield for our next signings. Having already identified a dynamic playmaker capable of pressing and creating chances, our goal is to find complementary profiles to complete a “staggered” double pivot.

We believe we can identify different profiles through a single, unified scouting search by looking for distinct skill sets that, when paired, create an asymmetrical yet flexible partnership (if one goes, the other one must stay).

Midfield Archetypes

• The “Developer”: A more attack-minded midfielder who contributes directly to goal-scoring and chance creation. We lean on the “Developer” archetype here. This is a player who affects play through continuous off the ball movements in attack.
  

• The “Controller”: A more balanced, defensive-minded presence closer to a traditional “number six” or holding midfielder. This profile is similar to the Platformer Archetype.
  

• The “Line Breaker”: Similar to the controller in terms of role and positioning but must be able to break the lines. This profile is similar to the Pathfinder Archetype.

To find these players, we have designed a performance index that aggregates both offensive and defensive metrics, effectively modeling a comprehensive “box-to-box” midfielder role.

Our approach is to generate a broad shortlist using this index and then decompose the data for individual players. This allows us to see which specific combinations of talent will best fulfill our tactical role requirements.

* Performance Index created in our Web App Lab (WAL)

Our scouting pool consists of CZE1 First league, DEN1 Superliga, SUI1 Super League, AUT1 Bundesliga, POL1 Ekstraklasa, SRB1 Superliga, SVK1 Nike Liga and FRA2 Ligue 2 from the current 25/26 season.

The bar chart below highlights the 15 top midfielders identified by our performance index:

At the top of the ranking, we have Noah Nartey who recently signed for Olympique Lyon. Nartey has taken big steps since we first profiled him as a Scandinavian Breakout Star, now much more involved in the Finish Phase. This is reflected in the breakdown below, ranking within the 92nd percentile for “P-Finish”. Still, he also shows up in the Build Up Phase when needed, shown in his 59th percentile score for possessions in this phase.

Besides Nartey being a reference profile for the complete Box-to-Box role, we have picked out four other profiles from our list that we believe can be potential candidates for playing across our two positions. The first candidate is Mike Themsen (note: low sample size of 5 games) who profiles close to the Developer Archetype as he is a willing runner both offensively (R-Ahead) and defensively (HI Distance + OBE + Recovery). He would be the perfect pick to help create space and combine with our winger and flying full back. We can support this by visualizing his output for underlaps and overlaps as well.

‍

* Scatter plot created in our Web App Lab (WAL)

As we can see, Themsen has a high underlap frequency with 2.46 runs per 30 TIP, and he is an outlier when it comes to runs ahead of the ball. Gulliksen leads all players in overlap volume averaging 1.88 runs per 30 TIP. We believe that the combination of underlaps and runs ahead of the ball is the most relevant combination for the developer archetype.

Another option worth considering for our midfield composition is Gassou Diakhité - a technical and versatile profile who receives the ball a whole lot more averaging around 25 possessions P30 Tip in the Finish phase. However, Diakhité has also featured 8 games as a center forward and is very much a threat in attack while he also possesses the skill to set up teammates from midfield position. This is reflected by his 6 goals and 6 assists so far this season for Lausanne in the Swiss Super League. Although Diakité seems like quite the offensive profile, he does rank in the 94th percentile for OBE as well which makes us confident that he can fit well within our team.

For our Controller Profile, we have picked out David Pech and Rok Storman. Pech is a high volume midfielder who gives us the control we need in build up and he can also perform the same function in the finish phase. Storman, on the other hand, does not average as high possession counts across phases, but he will more often attempt to break the second last line:

As we can see, when given the option, Storman attempts 42 per cent of his passes through the second last line - an important skill for a deeper midfielder. Pech is not included in the scatter plot due to a smaller sample size, but even after lowering the match threshold he remains below average with just 19 per cent.

Pech may provide the control we need in the build up phase, while Storman offers greater verticality through his line breaking. Viewed together, they could potentially form a well balanced double pivot. For now, we will include both on the shortlist and in the shadow team for further monitoring. In theory, we could utilize three different profiles depending on the game context; Themsen as our developer, Pech as a controller and Storman as a line-breaker. Diakhité becomes our second option in the playmaker role along with Yamamoto.

So far, we have focused on building the spine of the team, scouting central defenders and different midfield archetypes. In part two of this squad building exercise, we move further up the pitch and turn our attention to the attacking line, where wide attackers and center forwards will complete the picture.

Get an overview of all the SCOUTED Archetypes here.

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We Can’t Replace Him

When your best player leaves, many clubs instinctively look for the next star or a like-for-like replacement. It is an understandable reaction, but it often becomes an expensive and uncertain pursuit, as almost 50 per cent of ‘big transfers’ don’t deliver the expected impact (‘How To Win The Premier League’, 2023). Clubs are not only betting on one player to adapt quickly, but they are also entering a market where every team is competing for the same “next big thing”, which inevitably drives prices up.
This raises a broader strategic question: is there a smarter way to replace departing stars and reduce the risk built into recruitment?

The image above recalls one of the most iconic scenes from the movie Moneyball, where Oakland A’s scouts debate how to replace Jason Giambi. Billy Beane cuts through by arguing that they cannot replace Giambi directly, but they might be able to re-create his value in the aggregate. Instead of chasing one expensive superstar, they focused on the key performance indicator (KPI) that contributed most to winning baseball games, On-Base Percentage (OBP). The idea was to distribute Giambi’s total OBP across several undervalued players, allowing the A’s to compete in an uneven market. No single signing was a perfect match, but collectively they managed to replace Giambi’s OBP value.

Translating this idea to football is less straightforward. Baseball is a highly structured sport with isolated events, while football is a dynamic invasion game with constant interactions. However, the underlying Moneyball principle remains the same. If we can identify a metric or a set of metrics that consistently correlates with increasing scoring probability and ultimately winning matches, then we can break down a player’s impact and examine whether that value can be reproduced across multiple roles rather than through a single high-risk signing.

Expected Threat as KPI

This is where expected threat becomes an interesting starting point. By analysing how a player advances the ball into dangerous areas, we can quantify the part of their game most closely tied to creating goal-scoring opportunities or increased danger. Since football is a low-scoring sport, the most valuable contribution to the target is a player’s role in generating chances. Once we understand the components of their xT profile, we can explore whether several targeted, cost-efficient signings can collectively reproduce that influence.

In order to not make the calculations overly complicated, we will focus on finding metrics that we believe represent progression and chance creation (essentially xT). This can also make it easier to scout and pick the metrics that certain positions should excel in inside our squad composition.

Re-Creating A ‘Star’ Playmaker

The scenario we are imagining is that our star creator leaves. This is a player who receives the ball both in the Create phase and the Finish phase. In practice, that means we’re trying to replace someone who helps progress play after the initial Build Up phase and someone who is central to our chance creation in the final third. Players who influence multiple phases like this are hard to replace. They don’t appear often, and when they do, they come with heavy price tags.

To approach this problem, we will break creative impact into clear components. The idea is to separate their progressive qualities through Forward Momentum actions, their ability to advance play through 8-metre Carries at Speed, and their Pass Attempt Share to Runs Ahead of the Ball. We then combine this with their Avg Expected Threat (xT) Per Pass Attempt into Off Ball Runs to assess which players that picks out the most dangerous passing options on average. By isolating these elements, we can understand which parts of the profile can be reproduced by different players. Later, we will also look at how we can replace their impact in the final third or the Finish phase.

Performance Index for Progression

• Count Forward Momentum Possessions In Create

• Count 8M Carries Above Running Speed (all phases)

• (Share, %) Pass Attempts to Runs Ahead of the Ball / Pass Opportunities to Runs Ahead of the Ball In Create

• Avg xThreat Per Pass Attempt to Off Ball Runs

‍Below are the results of our index ranking filtered for U23 Midfielders in the top five leagues from the 24/25 season.

At the top of our ranking is Florian Wirtz, a player many would say has struggled to make an immediate impact at his new club. Last season he was arguably the best creator in Europe for Bayer Leverkusen, something we also highlighted in our previous Contextual Scouting piece on The Modern Playmaker. In second place is Nico Paz, a breakout performer for Como in Serie A. Real Madrid still owns his rights and there has already been plenty of speculation about a return to the Spanish capital.

This gives us a useful starting point. How do you replace a star creator like Wirtz or Paz?

Staying true to our initial argument about comparing players Expected Threat, we have ranked our progressive list by their Avg xT Per Pass Attempt To Off Ball Runs below:

At the top of the ranking we find Cole Palmer, averaging 4 per cent threat per pass attempt to off ball runs. In practical terms, this implies that if 100 passes were completed, around 4 would be expected to result in a goal within ten seconds. In terms of pass selection, Palmer averaged 2.1 pass attempts to runs in behind (85th percentile) and 1.1 pass attempts to cross receivers (89th percentile) in the English Premier League.

In second place is Habib Diarra, who moved to Sunderland ahead of the season. His strong xT per attempt is largely explained by a distinctive movement and passing profile. During his time in France, he ranked in the 95th percentile for overlap runs, the 87th percentile for underlap runs, and the 96th percentile for pass attempts to cross receivers, averaging 1.45 such passes per 30 TIP. These passes are particularly valuable because cross receiver runs typically generate higher xT, as they target teammates attacking the most dangerous areas inside the box. Diarra’s profile therefore illustrates why xT should not be assessed in isolation. His output is driven by a specific combination of movement and pass selection that consistently funnels the ball into high threat zones.

A similar pattern can be observed for Florian Wirtz, who ranked in the 98th percentile for both pass attempts to runs in behind and to cross receivers in the Bundesliga prior to his move to Liverpool.

The rest of the xT ranking mixes established elite players at major clubs with more under the radar talents who were on the move ahead of this season. With that in mind, we will focus on a selection of profiles that remain at their clubs and examine how they perform across the different components of our Progression Index.

When we break their profiles into percentile scores, we get a clearer picture of where each player stands out. Both Wirtz and Paz are exceptional across most metrics that make up the Progression Index. The question becomes whether we can split their combined contribution across two midfielders instead of one.

An Experimental Approach

Take Ilaix Moriba and Luka Sučić as an example. Moriba ranks fairly high for Forward Momentum In Create but averages a higher pass attempt percentage to runs ahead of the ball than Wirtz and Paz.

Sučić, meanwhile, ranks above both Wirtz and Paz for Carries Above Running Speed across all phases of play, and his xT from Passes to Off Ball Runs is close to their level.

This sets up an interesting comparison. If we combine Moriba’s strengths with Sučić’s, can their profiles collectively match the overall output of the elite playmakers at the top of the ranking?

Above, we have handpicked a group of midfielders and pulled their raw metric counts to explore how different pairings might complement each other on the pitch. The idea is simple: instead of looking at players in isolation, we assess how two profiles can combine their progressive skillsets and behaviours.

As a reference point, we use the Wirtz and Xhaka partnership from last season. Their distribution of strengths is a useful template. While Wirtz stands out in almost every creative metric, his impact is unlocked by having someone who can feed him the ball consistently. That is exactly what Xhaka provided him in Leverkusen. His high Pass Attempt Percentage (57 %) to Runs Ahead of the Ball in Create shows how Wirtz was given the platform to receive up the pitch.

The question is whether we can construct something similar, or even deliberately different, by combining complementary profiles.

The first example is Sučić and Moriba, of Real Sociedad and Celta Vigo, respectively. Moriba is an aggressive passer (98th percentile), even exceeding Xhaka’s pass attempt percentage to Runs Ahead of the Ball in Create. Sučić brings the ball-carrying ability (93rd percentile) and dangerous passes to off-ball runs (85th percentile for xThreat per Pass Attempt). Together, they recreate a similar division of labour: Moriba acting as the deeper distributor and Sučić as the dynamic carrier who accelerates play.

The second example is Danois (AJ Auxerre) and Guerra (Valencia), who form a more direct and high-impact pairing. Guerra excels in Forward Momentum In Create and brings a willingness to drive possessions forward rather than sitting as a fixed six. Danois adds strong carrying output (94th percentile) of his own, and both score well in xThreat per pass attempt, particularly Guerra.

None of this is perfect science, but it gives us a structured way to think about how to build a midfield based on complementary strengths and skillsets using data. It also helps clarify what kind of behaviours we want: do we prioritise carrying, passing aggression, or the ability to generate threat from fewer passes? And in which positions do we deem the different characteristics important?

For example, If we wanted a steadier number six profile in a 4-3-3, someone like Hugo Sotelo would enter the conversation. He ranks highly for Forward Momentum but has a much lower threat per pass attempt, suggesting he prioritises keeping possession and distributing balls to his teammates from his No. 6 position. Threat levels will also be lower for players operating closer to their own goal, and increase closer to the opponents goal which aligns with this positional profile.

These scenarios and comparisons help us map out the trade offs and build a midfield that fits the desired game model rather than chasing one direct player replacement.

Up to this point, our scouting has focused on players with strong progression qualities and high xThreat output. Those metrics help us identify profiles that move the ball into valuable zones and consistently create danger for teammates. What they do not capture is the final step, which is whether those actions actually translate into shots. And since football is a low scoring sport, understanding who regularly drives their team into shooting positions becomes essential.

Re-Creating Output: Shot Creating Actions

To identify players who reliably create or arrive in shooting situations, we break their contributions into three distinct buckets of actions that results in shots in the Finish Phase:

1. Carry Ending in Shot (In Finish Phase)

2. One Touch Shot (in the Penalty Area)

3. Carry and Pass Leading to Shot (In Finish Phase)

In the bar chart below, we rank midfielders by their combined distributions across the different shot buckets on a p30 TIP level (adjusted for teams’ possession):

The bar chart above ranks U25 midfielders from Europe’s top five leagues based on their combined Shot-Creating Actions (SCA) from last season.

Topping the list is Jamal Musiala, who recorded 3.3 SCA per 30 minutes of Team In Possession (P30 TIP). He is closely followed by Florian Wirtz and Nico Paz, the only other midfielders to average more than 3.0 shot-creating actions.

What distinguishes this trio is their balanced creative profiles. Their output is relatively evenly distributed across the three key categories:

• Individual Shots: Individual carries and shots (Black).

• Box Crashing: Arriving in the box for one-touch finishes (Green).

• Team Sequence: Carry and pass leading to a shot within 10 seconds (Light Green).

Notably, Nico Paz led the top 20 for “box crashing,” averaging 1.1 one-touch shots in the penalty area P30 TIP, highlighting his tendency to arrive in the box from midfield.

Specialisation vs. Versatility

As we move down the rankings, players tend to show more specialised, uneven distributions. For many, passing within the finish phase accounts for the vast majority of their shot creating contributions. One example is Kevin Danois, who also featured in our earlier progression index.

However, since players who excel across all three creative “buckets” are rare, recruitment strategies could involve pairing specialized players to share the creative load. To explore alternatives to central creators, we will now shift our focus to Wide Attackers, who naturally find themselves in high-value chance-creation zones more frequently.

The following charts analyze the shot-creation distributions for U25 Left and Right Wingers from the 24/25 season:

Leading the rankings for Left Wide Attackers, Khvicha Kvaratskhelia stands out with 4.3 shot-creating actions (SCA). His profile is skewed toward individual brilliance, with 44% of his output generated from direct carries followed by his own shots while playing for Napoli.

In contrast, Jérémy Doku displays a different tactical utility; 79% of his actions stem from carries that culminate in a pass or cross. Finally, Abde Ezzalzouli represents a more balanced profile across all three creative “buckets.” However, he notably leads this group in “box crashing,” recording 1.36 one-touch shots in the penalty area P30 TIP.

Lets also have a look at the Right Wide Attackers from last season:

On the right flank, Bukayo Saka recorded the highest average score with 4.6 SCA, closely followed by Noni Madueke and Antoine Semenyo. It is worth highlighting that Semenyo ranked in the top five in both charts, underscoring his rare output and making him a versatile target for elite clubs. When compared to Doku and Cherki, whose profiles are more heavily skewed towards passing and chance creation, Semenyo stands out as a more direct goal threat. This helps explain why he offers Manchester City a different attacking dimension and an additional source of goals alongside Haaland. His unpredictability further strengthens his profile, as he is comfortable attacking on both sides and finishing with either foot, scoring six goals with his right and five with his left last season.

Further down the rankings, Brennan Johnson recorded the highest “box crashing” score. This aligns with the “eye test,” as he frequently arrived at the back post for tap-ins last season (a trait and movement that secured his team the trophy in the Europa League Final as well). Other profiles, such as Antony or Gustav Isaksen, post higher total SCA scores than Johnson but rely more on ball-carrying and individual shooting rather than off-the-ball movement into the box.

The “Mix and Match” Strategy

Rather than pursuing rare, “all-in-one” playmakers who command substantial transfer fees, we can adopt a “mix and match” strategy: distributing creative responsibilities across multiple positions.

By breaking down shot creating actions, we can distinguish players by how they help create shots for their team. This allows us to scout more precisely, targeting players based on the specific types of actions we want to increase in our own attack.

Based on the analysis so far, we now aim to assemble a complementary set of players that, collectively, could replace the output of a departing star playmaker.

For shots generated from carries, both Ezzalzouli and Isaksen cover this bucket well. In box crashing actions, Ezzalzouli stands out with the highest output, while for passes leading to shots within a team sequence, all three replacements record relatively high averages. This aligns with the idea of a more distributed approach to chance creation in the final third.

Notably, Ezzalzouli on his own produces a higher average shot creation score than both Wirtz and Paz. That comes with the important context that his contribution is shaped by his role as an attacker, but it further underlines how different profiles and positions can collectively replicate elite creative output.

The Rebuild

By integrating the analyzed profiles, we can reconstruct the output of a “departing star” through a diversified attack. This not only makes the team less reliant on a single individual but also makes the offensive structure harder for opponents to defend, as threats now emerge from multiple zones and varying action types. Below, we have created a projected line-up with our chosen profiles:

With Hugo Sotelo operating as the No. 6, we secure a stable distributor at the base of midfield. He underpins our progression through an elite volume of forward momentum actions in the Create phase, ranking in the 99th percentile. In addition, he averaged 4.55 pass attempts through the second last line (98th percentile) just in front of Granit Xhaka and Adam Wharton last season. Alongside Sotelo, we have selected Ilaix Moriba, also from Celta Vigo, to add a more aggressive edge in possession. Moriba is willing to take even greater risk with his pass attempts to runs ahead of the ball, and contributing across multiple phases as a dynamic No. 8 profile.

Completing the midfield is Kevin Danois, primarily chosen for his carrying ability but also because he features strongly in both our progression index and our ranking of shot-creating midfielders. Danois profiles somewhere between a No. 8 and a No. 10, with greater responsibility for joining attacks and combining with our isolated right winger, Gustav Isaksen.

On the right, Isaksen provides width and variation. He can carry inside to shoot himself, or create opportunities for others through passes and crosses. On the opposite flank, Abde Ezzalzouli offers a more balanced winger profile based on his shot-creation distribution (perhaps paired with a lapping fullback). The intention is for him to be a consistent goal threat alongside the centre forward while remaining unpredictable in his movement and decision making. He can engage fullbacks 1v1, step into the half space to combine, or crash the box when play develops on the opposite side.

Let’s now look at the total cost of acquiring these players based on their current market values:

Although it would be unrealistic to sign all of these players, a combined market value of roughly €70 million illustrates how assembling a set of complementary profiles can collectively replace the influence of a departing “star” playmaker, while also spreading responsibility across the team and reducing risk in recruitment compared to pursuing a single like for like replacement. More interestingly, trying this scouting approach in lesser known markets could reveal undervalued players with the skills and characteristics you need in your team.

Outthinking, Not Outspending

Across world football, financial constraints define reality for most clubs. Many clubs operate within tightly controlled budgets, revenue-based salary caps, or league regulations that restrict contracts and wage bills. The context varies by competition, but the fundamental challenge remains the same: how do you build a competitive squad when you cannot outspend your rivals? To explore this question, we examine a league where league-wide salary structures create a relatively level playing field and force clubs to find competitive advantages beyond pure spending power.

Major League Soccer is unique in world football as the only major league that operates under a league-wide salary cap (as opposed to restrictions based on salaries to turnover ratio, for example). As with the other major American sports leagues, this structure is designed to create a more balanced and competitive environment, and thus a more compelling ‘product’ for the audience.

In MLS, the salary cap prevents clubs from outspending their rivals on player salaries, forcing teams to compete on smarter roster construction rather than financial dominance. Every club begins from a relatively similar financial baseline, which raises a fascinating strategic question: How can teams find a competitive advantage in squad building and on-field performance within the constraints of the cap?‍

Before answering that, we first need to understand how the MLS salary cap actually works and the mechanisms that shape how teams build their squads.

How “The Salary Cap” Works

First of all, the total salary (budget) cap for the 2025 season for each team’s senior roster (20 players) is around $5.95 million. If we were to divide this evenly across the entire roster, it would amount to an average cap hit of $297 000 per player. However, clubs rarely do this as they want to afford better players on higher wages in key positions and there are certain mechanisms that allow teams to “buy down” some salaries and overspend strategically on others.

The salary cap is what’s known as a “soft” cap, i.e. there are some exceptions that enable the clubs to spend beyond it. The first, and most influential of these exceptions is the Designated Player (DP) rule - sometimes known colloquially as the “David Beckham rule”. Each club gets 3 DP slots for players whose total salary and transfer fee can exceed the max budget charge per player (≈ $743k in 2025). These players often earn far more than the cap allows, as club owners are free to pay them as much as they can afford. So, although these players have high salaries, only the maximum budget charge “hits” the team’s salary cap.

This system allows teams to attract global stars while maintaining overall parity across the league. It’s how Inter Miami can afford Lionel Messi’s wages and how LAFC could bring in a player like Son Heung-min straight from the Premier League.

The bar chart above highlights Inter Miami, LAFC and Atlanta United as the league’s top spenders. However, what truly differentiates them is how they spend. Inter Miami, for instance, allocates roughly 72 % of its total roster budget to their three Designated Players: Lionel Messi, Sergio Busquets and Jordi Alba (Wright, 2025). Their salaries are more than any other MLS team’s entire roster combined. However, Philadelphia Union has shown (by winning their conference this year despite having the third lowest spending) that it is possible to ‘outperform’ spending on player salaries.

The second key mechanism influencing the salary cap is Targeted Allocation Money (TAM), which allows clubs to “buy down” the budget charge of specific players. In 2025, each team had roughly $2.7 million in TAM available. For example, if a player earns $1 million per year, the club can apply $257,000 of TAM to reduce his cap hit to the maximum budget charge, allowing him to fit under the cap as a non-Designated Player.

Clubs also have General Allocation Money (GAM), which functions as an in-league currency. It allows teams to acquire other MLS players or their rights using GAM, while the receiving club can use that amount to reduce its own salary cap charges.

There are also mechanisms such as the U22 Initiative, which allows clubs to limit and minimize cap hits for up to three U22 players. In addition, if a club signs a Young Designated Player (aged 23 or younger), it does not reduce the number of available U22 Initiative slots - effectively giving that team an extra U22 spot compared to if all three DPs were senior players.

The TAM/GAM mechanism enables clubs to sign high-quality players alongside their stars without exceeding the cap, and it’s often where the biggest opportunity lies. By identifying undervalued players who perform at near-DP levels, clubs can potentially raise their overall roster quality and efficiency.

However, finding and acquiring players who deliver DP-level impact on TAM-level contracts is far from easy. These signings often come with meaningful salaries or transfer fees, which naturally limit how much flexibility a club has elsewhere on the roster. This begs the question: could clubs achieve better overall efficiency by spreading their TAM investments across multiple positions, rather than concentrating so heavily on attacking talent?

Shifting Positional Focus

In their article on Maximising Roster Efficiency in the MLS, Daboo and Birnham (2025) tried to answer this exact question where they compared teams’ spending represented by a forward-to-defense spend ratio. The intention was to evaluate teams’ spending efficiency relative to the goal probability added (G+) per $10k of salary wages. One of their findings was that teams who spend a greater proportion of their salary on attacking players perform less efficiently. The downward slope of the regression line below illustrates this relationship:

‍While the difference in team efficiency isn’t dramatic, the analysis suggests a clear direction: investing more heavily in defense could be a smarter approach to roster building, particularly for teams with a lower budget (Daboo & Birnham, 2025). This argument becomes even stronger when we consider that the G+ model is based on event-data, and therefore naturally biased toward attacking contributions. Defensive actions and structural balance are harder to capture in such models, meaning the true impact of a stronger defensive unit might be even greater than the data in that study suggests.

To conclude, the research suggests that clubs may be overvaluing attacking contributions and undervaluing defensive ones. This bias is reflected in the higher G+ values typically assigned to attackers. As a result, defenders tend to earn significantly less than attacking players, which creates an opportunity for clubs to build more cost-efficient rosters. For example, attacking midfielders in MLS earn on average $354,967 dollars more than full-backs.

These insights point us toward an alternative approach to roster construction. What if a team invested in one attacking full-back capable of producing winger-like G+ output, paired with a dominant center back to maintain balance? Our potential center-back should be able to defend the wide channels in a back four, providing cover behind an advanced full-back, and also slot into a back three in possession. Such a structure could enhance both squad composition and tactical flexibility within the constraints of the salary cap. Let’s go scouting.

Methodology

Based on our analysis, we will focus our scouting on an attacking full-back who makes a lot of attacking runs and is capable of staying high and wide within our in-possession structure. Ideally, this player operates alongside a winger or attacking midfielder who moves inside, allowing the full-back to provide width and stretch the opposition. The player should be comfortable functioning either as a wing-back in a 3-4-3 or as a full-back in a back-four system, with a natural sense of when to join the attack and when to hold position as the team’s width provider.

The second profile we are targeting is a dominant, ball-playing center-back. The ideal profile combines physical presence and athleticism with the ability to defend transitions effectively, while also being composed and progressive on the ball. Below are the key metrics we have selected to identify and evaluate players for the two roles.

Attacking full back:

• High Intensity Distance P90

• Count Explosive Acceleration To Sprint P90

• Avg Time To Sprint

• Runs Ahead Of The Ball P30 Tip

• Overlaps Runs P30 Tip

• Underlap Runs P30 Tip

• Pass Attempts To Cross Receivers P30 Tip

• Dangerous Passes P30 Tip

Dominant CB:

• Avg Psv-99

• Avg Time To Hsr

• Pass Attempts Through First Line P30 Tip

• Pass Attempts Through Second Last Line P30 Tip

• Carries At Speed P30 Tip

• Recovery Press Engagements P30 Otip

• On Ball Engagements In Transition P30 Otip

• Stop Or Reduce Danger %

• Direct Disruption Or Regain %

We are focusing our scouting on seven European leagues in the 2025/26 season: NOR1 Eliteserien, SWE1 Allsvenskan, DEN1 Superliga, CZE1 First League, BEL1 Pro League, ESP2 La Liga 2 and the GER2 Bundesliga 2. Note that all of the leagues except Scandinavia have smaller sample sizes since we are still early in the season.

Undervalued Attacking Left Back

After applying our performance index, these are the results of the top 15 attacking left backs across the leagues:

‍Timo Stavitski (26) tops our performance index and is an obvious option for our roster considering his market value of only €400k, albeit we may have to pay a little more than that, given Stavitski just won the Allsvenskan with Mjallby. He has operated as a left wing back in a 3-4-2-1, covering the flank in an expansive, fluid attacking setup. That experience aligns with our requirements for an attacking full back who can provide width, vertical running, and goal contributions. This is a huge plus as he ticks our core boxes for role fit and price efficiency.

One key detail with Stavitski is that he is a right-footer operating on the left, meaning he regularly attacks inside against the fullback instead of overlapping wide like a traditional wing-back. This inverted tendency makes him a flexible option who could also play on the right side. He excels in transition moments as he is in the top one percent for both possession counts and off ball-runs in transition, combined with general high off-ball running volume. He is also an active ball carrier, averaging 9.1 carries at speed per 30 TIP (99th percentile), and ranks inside the top five percent for dangerous pass attempts.

In the table below, we estimate the potential cost of signing Timo Stavitski on a four-year contract and how each scenario would impact the salary cap. We have outlined two versions: a cheaper option that aligns closely with his current market value, and a more expensive option that reflects a possible increase in both market value and transfer fee. The cap hit, also referred to as the budget charge, is the sum of the player’s annual amorticed transfer fee and his guaranteed yearly salary.

‍If we manage to sign Stavitski at his current market value, the table shows that his annual budget charge would remain well below the maximum budget charge. As a result, he could be registered as a standard senior player on our roster without the need to use Targeted Allocation Money (TAM).

If we prefer a naturally left-footed option on the left side, Adam Sørensen (24) from Odense BK emerges as a compelling alternative. The data shows that he profiles more as a traditional overlapping fullback who consistently joins attacks and delivers from wide areas, ranking in the top 10% of all fullbacks in our sample for overlap runs per 30 TIP.

What makes him particularly interesting, however, is the versatility in his movement. Sørensen is also in the top five percent for cross-receiver runs and pulling half-space runs. In practice, this means he not only overlaps but also steps inside to occupy pockets between the lines. In addition, when play develops on the opposite side, he will often position himself just outside the penalty area to capitalize on potential rebounds or second balls. Like Stavitski, Sørensen is financially attainable and can fit as a standard senior player, especially under a five-year deal that keeps his cap hit below the max charge.

Young Attacking Right Back

Below are the results of the same full back search, this time for right backs:

‍Thérence Kodou and Denzel De Roeve are both young right-backs who qualify for the U22 Initiative, making them particularly attractive from a roster-building perspective. Under this mechanism, players aged 22 or younger can be signed on competitive salaries or even with significant transfer fees, yet their budget charge remains fixed at around $200,000.

We are going for Denzel De Roeve (21) from SK Brann, as he represents the most affordable option between the two with a market value of around $900k. Originally from Belgium, De Roeve came through the Club Brugge academy before joining Brann, where he has featured in the Europa League this season. Brann plays an aggressive, high-pressing, and vertical brand of football, which aligns well with our desired playing style and the type of profiles we aim to recruit.

Having identified the full-backs we want to recruit, we will now turn our focus to analyzing center-backs. We are looking for a player who is fast, dominant, and capable of providing defensive cover for at least one of our attacking full-backs.

Fast and Dominant Center Back

‍The list above includes the 15 most dominant center-backs identified in our data search. Many of them meet our criteria for disrupting opposition attacks while also demonstrating composure and quality in possession. However, one of the key traits we are prioritizing is speed and the ability to cover wide channels and stop counter attacks. This role is somewhat comparable to how Kyle Walker operated for Manchester City during his peak years, covering the space in behind a high line using his pace and explosiveness.

Therefore, let’s find out which ones are the fastest and most explosive. The scatter plot below shows each player’s Peak Sprint Velocity and Average Time to Sprint.

‍Abdoulaye Sylla is the fastest center-back in our dataset with a peak speed of 31.49 km/h, but he also ranks within the top 10% for average time to reach sprint speed. Sylla currently plays in the Czech First League and is valued at around $800,000. From a roster-building perspective, he represents an excellent opportunity as we could potentially integrate him into the squad in a similar way to Timo Stavitski, keeping his budget charge well below the cap and avoiding the need to use additional allocation funds.

‍After confirming that Sylla checks the physical box, we also wanted to assess his composure and quality on the ball. While the chart below doesn’t directly measure progression, it provides some signal (which we can confirm with video scouting) of his on-ball ability, ranking inside the top five in our sample for ball retention under pressure.

Wildcard (Young DP)

Since we have identified several affordable and undervalued options, we now have additional funds available to strengthen other areas of the squad.

One player who has particularly caught our attention in the center-back section is Silas Andersen, a 21-year-old who has played both as a midfielder and center-back for BK Häcken in Sweden. Andersen represents a rare profile - a hybrid midfielder/defender who could provide defensive balance while contributing to build-up play and progression. Both data and video analysis confirm his versatility, as he has operated effectively in both roles. This also shows itself in his off-ball-run profile when played as a midfielder, with his high volume of dropping off runs and coming short runs:

‍Standing at 1.90 meters, he combines physical presence with composure and technical quality on the ball. It is especially noteworthy that he ranks first in our Dominant Center-Back Index, despite being primarily a midfielder.

However, Andersen is likely to command a significant transfer fee, with reports indicating that BK Häcken rejected a $4 million offer from FC Copenhagen earlier this year. Andersen came through Copenhagen’s academy before earning a move to Inter Milan at just 17. After a spell in the Netherlands with Utrecht, he made his way to Sweden, where he has now completed a full season at the top level with more than 2000 minutes played.

Given his age and potential, we could consider acquiring him as a Young Designated Player (Young DP). This would minimize his cap impact while also unlocking an additional U22 Initiative slot, maintaining roster flexibility for future signings. This feels like a rare opportunity to secure a player that will improve our starting XI immediately, as well as having long-term upside and strong resale value. Let’s break down the financial impact of signing Sylla for our defense and adding Andersen as a Young Designated Player:

‍As we can see, the big advantage with signing Anderson on as a young DP is that it only hits our cap with $200 000.

Contextual Scouting: From Data to Decision

Our analysis revealed that MLS teams often allocate a disproportionate share of their salary budget toward attacking players, leaving defensive positions relatively undervalued. Recognizing this inefficiency, we set out to identify defensive profiles that could deliver impact both offensively and defensively - players who provide structure, balance, and attacking depth in modern, transition-oriented systems. The second factor was how well these players complemented each other, evaluating them within the context of our potential team setup and how their individual strengths could interact to enhance the collective structure.

Through our contextual scouting framework, we identified four such players: Timo Stavitski, Denzel De Roeve, Abdoulaye Sylla, and Silas Andersen. Each fits a clear tactical purpose: from Stavitski’s offensive runs to Sylla’s recovery pace and Andersen’s hybrid defensive-midfield role. This is how our projected line-up looks so far:

‍Crucially, these signings also reflect financial discipline. By leveraging MLS mechanisms like the U22 Initiative and Young Designated Player rule, we’ve minimized our cap impact while integrating young, high-upside players into the roster. The result is a recruitment strategy that aligns on-field needs with financial efficiency. Below is a breakdown of our projected cap hits and the remaining allocation available to complete the roster:

‍In a league designed for parity, where every team starts with similar financial constraints, success depends on how efficiently resources are used. Few leagues in the world offer smaller clubs such an opportunity to compete on even terms. With intelligent roster building and targeted investments, it’s entirely possible to construct a team capable of challenging for trophies, without breaking the cap.

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Sources:

MLS Rules and Regulations. URL: https://www.mlssoccer.com/about/roster-rules-and-regulations

Daboo & Birnham, 2025. Maximizing Roster Efficiency. URL: https://www.stat.cmu.edu/cmsac/sure/2025/showcase/soccer_roster/report.html

Salary Guide. URL: https://mlsplayers.org/resources/salary-guide

Talent alone isn’t enough. To succeed, a player needs to match a team’s style, system, and role expectations - in possession and out of possession. That’s where Contextual Scouting comes in.

With this approach, the goal is simple: help clubs find players who match specific tactical and stylistic needs both in and out of possession. Not just “good” players, but the right ones - increasing the certainty around these key investments. The second part of effective scouting, and what we want to focus on here, is identifying hidden talent in emerging and ‘untapped’ leagues and markets that can generate high resale value.

Our next stop is Asia, using data from the current 2025 season.

Exploring the Japanese Market

The next market we aim to explore is Asia, with a particular focus on the Japanese J1-League. In recent years, Japan has emerged as a highly attractive talent pool, thanks to a well-organized youth development system and a clear national footballing philosophy. These long-term structural investments are now bearing fruit, producing technically gifted and tactically disciplined players.

Japanese exports have consistently adapted well to a variety of competitive environments, from the English Championship and Scottish Premiership to the German Bundesliga. On top of that, five Japanese players are now playing for teams in the English Premier League. Below is a snapshot of recent transfer flows from Asia to European leagues:

Benchmarking Japan

An analysis conducted by SCOUTED in 2024 found that players in the J1 League not only cover a high volume of ground, but also possess a technical proficiency that translates well to European football. For instance, their ball retention under high pressure stands at 72.5%, comparable to the top five leagues’ average of 74.6%.

We can further support these findings with recent physical data. In the bar charts below, we benchmarked physical metrics from the current 2025 season in Japan against the averages from Europe’s top five leagues in 2024/25.

The data confirms that Japanese players run a lot from the Total Distance P60 BIP bar chart (top middle). However, the top five leagues score higher for Sprint Distance P60 BIP (top right), but this is boosted by the Premier League being a physical outlier as well. Further, when we look at the three bar charts on the second row, we can note that J1-league players average higher numbers for High Intensity Activities and High Accelerations P60 BIP. So, although the overall sprinting distance is higher in the top 5, the frequency of high intensity activities are higher in the J-League when the ball is in play. Let’s explore this further on a league level:

As seen above, the Premier League is a league on its own regarding sprint output. More interestingly, the data tell us that J-league players record above average numbers of high intensity accelerations each game, and we start to see why they adapt quickly in Germany and the Netherlands - matching the sprinting distance in those leagues (J2 League included).

A research paper we did on tactical trends across leagues for the 2024/25 season found that successful teams in Japan typically play direct transition-based football. We can break this down by looking at the different team styles within the league from the current season. Below, we have highlighted the teams that finished in the top four in the J1-league last season:

The direct teams we’ve highlighted all finished in the top four last season, with Vissel Kobe securing their second consecutive league title. What these sides have in common is a clear tendency toward directness - all of them score above average (green scores) in either Direct Play or Transitions. A few teams, however, have sought to deviate from this trend. Kashiwa Reysol, led by Spanish manager Ricardo Rodriguez, stands out as a notable example. They currently sit inside the top three and have just reached the Japanese league cup final, where they will face Sanfrecce Hiroshima, who ranks highly for direct play and quick breaks. An exciting watch for sure!

Revisiting our research on tactical trends, we also found that the Bundesliga was the most direct league amongst the top five - favouring directness over the progression to build up. This supports the idea that Japanese players are naturally well-suited to the Bundesliga’s direct playing style.

In summary, Japanese players adapt well to the technical and physical demands of Europe’s highest level, making them attractive targets at affordable prices.
In the next section, we will pick a specific scenario and look for the next breakout stars in Japan and South Korea.

Club Context: Bundesliga Club Targeting A Dynamic and Robust Playmaker in Asia

In this scenario, we take on the role of a Bundesliga club searching for a dynamic and robust playmaker from Asia, with a primary focus on Japan. Our scouting scope includes the ongoing 2025 season of the Japanese J1 and J2 Leagues and the South Korean K1 League.

The target profile thrives as a central attacking midfielder (CAM) in a 4-2-3-1 system, but can also operate as a right or left attacking midfielder, rotating positions within the trio to receive both centrally and wide. The player can also fit naturally into a 3-4-2-1 structure, occupying one of the two advanced playmaking roles behind the striker.

We’re looking for a player who is dynamic, mobile, and capable of influencing the game through off-ball movements and sharp decision-making in transitions. The ideal candidate blends technical quality with tempo and verticality, aligning with a Bundesliga style built on intensity and direct attacking play.

Methodology

We are going to apply The Playmaker Index and The Pressing Index, similar to our previous pieces on Scandinavia and South America. In those pieces, we experimented with different weightings for the indices. But this time, we are going to change some of the Game Intelligence metrics inside the Playmaker Index to suit more of a transitional and direct style of play, in line with our analysis of the J-League. The pressing index remains unchanged as we believe it mirrors the modern pressing game quite well. Below is our new combination of metrics to make up the “vertical” playmaker index:

In the Movement category, we continue to use passing options to represent how players position themselves to receive between the lines, but we’ve now added a vertical layer with runs ahead of the ball and off-ball runs in transition. Together, these indicators aim to identify players who combine intelligent positioning to receive between lines (high technical proficiency) with the ability to target and exploit space when it opens up.

In the Progression category, we’ve shifted the focus toward the transitional phase, emphasizing players who move the ball forward with speed and intent. The phase now combines 8-meter carries in transition and quick passes in transition to capture progression through both carries and playmaking tempo. We’ve kept the forward momentum metric - measured as the share of FM retention relative to all possessions, to ensure we still identify players who consistently advance play across all phases, not only in transition.

Since we are not focusing solely on players that can break down a low block, we have removed the finish phase here as well. Furthermore, measuring pass attempts to runs in behind can reveal more impact across multiple phases - particularly in moments with more space to attack (which would be from Build-Up or Create) . In addition, we’ve chosen not to isolate all metrics solely within the transition phase, since transitions still occur far less frequently (only 4-6 % of game phases) than sustained periods of controlled possession.

With this setup, the index is intended to surface players who carry vertical threat without only depending on counterattacks - the kind of dynamic playmakers suited for high-tempo leagues like the Bundesliga.

With the adjustments complete, it’s time to see the results. Which players are emerging as the next breakout stars in Asia/Japan?

Our shortlist features several exciting young players. At the top is Sota Kitano (21), who recorded the highest Total Index Score. He’s joined by other rising talents like Sang-Yun Kang (21) from the K1-League and Kota Tawaratsumida (19) from FC Tokyo. The players highlighted in dark green are slightly older but remain intriguing options - their experience could help them adapt and break out in new environments.

Breakdown of Breakout Stars

Let’s take a closer look at how they perform across the different categories, both in and out of possession.

The first thing that stands out is how all of our players excel in the Movement category, each scoring at least in the 83rd percentile. When we move to Progression and Finish, scores are more modest with the exception of Shibayama who looks like a complete playmaker based on our index.

On the defensive side, four players stand out in the Volume category, while another four appear notably more intense and explosive than the rest.

It will be interesting to explore and compare the players’ movement profiles in more detail, as this seems to be the area where they truly distinguish themselves. Let’s explore this further.

Playmaker Analysis

Returning to our initial target profile, we aimed for a dynamic and robust playmaker capable of influencing the game through intelligent off-ball movement, quick combinations, and sharp decision-making in transitions.

Below is a scatter plot of our players ability to move between the lines, represented by their passing options through the second last line (x-axis) and around the second last line (y-axis) per 30 Tip:

As expected, all of our shortlisted players rank above average for both movements. However, four players clearly stand out across both metrics: Kitano, who records the highest total of passing options, followed closely by Tawaratsumida, Sumi and Hiraoka who most often drifts out wide. Notably, Koshiro Sumi has been playing in the J2 League this season, yet still ranks among the top three in our Total Index Score.

Since all of our players display strong numbers and demonstrate intelligent movement to receive the ball in advantageous areas, we have to distinguish them by their ability to move forward into space.

Consequently, our visualization below highlights the players runs ahead of the ball (x-axis) and off-ball runs in transition (y-axis) Per 30 Tip:

While Shibayama ranked slightly lower than the top group in the previous chart, he stands out here as a clear outlier. His exceptional score for off-ball runs in transition sets him apart, making him a player worth keeping a close eye on as we move forward in our analysis.

We’ve now established that all of our players are above-average movers, each meeting our criteria for being dynamic and mobile. But how do they help their team progress the ball and create chances?

First, let’s look at how the players rank in terms of carries (x-axis) and quick passes (y-axis) in transition Per 30 Tip:

All of our players rank above average for carries, with Shibayama leading the way at nearly four carries per 30 TIP. On the other hand, Miyashiro and Hiraoka record the highest numbers for quick passes - a stronger indicator of playmaking ability and decision-making speed, as these actions require receiving and releasing the ball within one second.

Next, we want to look at how our players perform for our most important direct chance creation metrics: pass attempts to runs in behind (x-axis) and cross receiver runs (yaxis).

In terms of chance creation, Shibayama stands out once again - this time for his high frequency of passes played to runs in behind. On the opposite side of the plot, Sota Nakamura emerges as one of the most active crossers, which aligns with his six assists so far this season for Sanfrecce Hiroshima. The remaining players fall somewhere in between, displaying a balanced mix of both passing profiles.

At this stage, it remains challenging to clearly separate the players from one another. To build a more complete picture, we’ll now shift our focus to the Pressing Index, comparing their defensive contributions and physical profiles. The next steps will help us determine which players look most promising overall based on the data.

Pressing Analysis

Let’s find out how our players rank in terms of their on ball engagements (defensive output) in the high and medium block:

Six of our players rank above average for on-ball engagements in both the high and medium blocks. Among them, Shibayama and Kitano stand out - which makes sense given that they both play for Cerezo Osaka. A closer look at the data confirms that Cerezo spend most of their out of possession time in the high block. A similar pattern appears with Miyashiro and Sumi, whose teams (Vissel Kobe and Júbilo Iwata) also operate higher up the pitch, suggesting that team style plays a key role in shaping these metrics.

Interestingly, Hiraoka’s team, Shonan Bellmare, spends the most time in a low block when out of possession - yet he still ranks highly in the other pressing zones. This suggests that Hiraoka could fit into multiple pressing systems effectively.

Physical Analysis

To complete our analysis, we turn to physicality. Earlier in this piece, we noted that Japanese players tend to cover large distances, although their total sprinting distance is slightly lower compared to some of the top European leagues. We now want to examine how our selected players perform in terms of sprinting activities and sprinting distance, to assess whether they can meet the physical demands of the Bundesliga.

The scatter plot below benchmarks each player’s sprint output against the average values for Bundesliga midfielders from the 2024/25 season - dotted lines mark the Bundesliga average. The background sample includes all midfielders in the J1 and J2 league this season.

Interestingly, all of our players appear capable of coping with the sprinting demands of the Bundesliga. Kota Tawaratsumida stands out as the clear leader - while Sumi, Nakamura, Kitano, and Hiraoka also record high scores. It’s also worth noting that Nakamura has the highest Peak Speed Velocity (PSV-99) and the fastest time to sprint, reflected in his 95th percentile score for our Intensity category from the breakdown.

We can also complement the sprint data with high-intensity actions p90, which include all movements above 20 km/h. In this category, Kitano and Hiraoka emerge as the standout performers.

It’s time to narrow down our shortlist of potential targets, as we now have enough information from our analysis. The decision on which players to scout further comes down to a holistic assessment of their qualities both in and out of possession.

The Shortlist

After combining all our insights, we’ve identified four players to focus on: Sota Kitano, Taisei Miyashiro, Taiyo Hiraoka, and Masaya Shibayama. However, upon reviewing each player more closely, we found that Sota Kitano has already completed a transfer to Red Bull Salzburg in Austria. This narrows our list down to three remaining candidates.

Below are the off ball profiles of our final candidates, allowing us to analyze the main differences between them off the ball:

We’re now left with three dynamic playmakers who move well between the lines. All three also meet our criteria of being direct and vertical, reflected in their frequent runs in behind and runs ahead of the ball per 30 Tip.

Contextual Scouting: From Data to Decision

Masaya Shibayama (23) clearly distinguishes himself from the others through his greater involvement in build-up play, as shown by his dropping off runs and coming short runs. His high score for support runs is also a great asset for aiding ball circulation and helping his team up the pitch. From video scouting, he comes across as an exceptional left-footed technician, combining low centre of gravity with tight close control. However, his small stature (1.61 m) means he could be physically challenged in more demanding environments. Another factor is sample size - he has only five full games in our dataset, although his playing time has increased since Kitano’s transfer to RB Salzburg. His data profile is very promising, and he’s certainly a player to keep monitoring as he continues to develop and gain influence in the J1 League.

Moving on to Taisei Miyashiro (25) of Vissel Kobe, who ranks fourth in our Total Index Score. What sets him apart from the other two is his strong output for cross-receiver runs, averaging 9.1 runs per 30 TIP as a midfielder.

If we were specifically targeting a more goal-scoring attacking midfielder, he would be a standout candidate - registering 11 goals and 3 assists this season for the reigning champions. This attacking instinct is also reflected in his positional split, featuring in 11 games as a center forward and 15 as a midfielder in our dataset. His high score for on-ball engagement in the high block further suggests he could thrive in a direct pressing system, combining experience as a forward leading the press with the ability to arrive late in the box as a number eight. Clubs with a direct and aggressive playing style should definitely keep Miyashiro on their radar.

Lastly, we have Taiyo Hiraoka (23), who ranks second in our Total Index Score and displays strong, consistent numbers across all categories - including the physical robustness required for the Bundesliga. It’s important to note that Hiraoka plays for Shonan Bellmare currently sitting in one of the relegation spots. The team has underperformed their expected goals (for and against), but should still be considered a mid-to-lower-table side in terms of underlying performance. Hiraoka’s off ball profile shows the offensive qualities we are after as he moves well between the lines, and combines this with vertical runs scoring in the 99th percentile for both runs ahead of the ball and underlap runs per 30 Tip. He demonstrates these qualities despite playing in a more possession-oriented team, in contrast to Miyashiro, who operates in a more direct system. Below, we have visualized Hiraoka’s receptions in space and runs ahead of the ball:

From watching him play, it’s clear that Hiraoka fits the profile we’re looking for. He constantly seeks space, alternating between finding pockets in the left half-space and drifting wide when needed. He looks like a natural fit for the left-sided attacking midfielder role in a 4-2-3-1, ideally paired with an overlapping fullback - but could potentially be even more effective as an inside forward, drifting and dropping deeper to link play and attack central spaces. His ability to combine in tight areas also makes him a strong candidate for the left number 10 role in a 3-4-2-1 system.

One area for improvement is his direct goal contribution as he only has 3 goals and 1 assist this season. However, one could argue that Hiraoka might perform even better in a stronger team.

Hiraoka’s value lies in his intelligent movement, high pressing volume, and physical output (explosivity included). He offers constant availability in possession and relentless work out of it - qualities that often translate well to higher-intensity leagues. With a market value of just €550k, he could represent excellent value for a Bundesliga club seeking a dynamic and robust number playmaker, capable of adjusting to different team styles and systems.

Talent alone isn’t enough. To succeed, a player needs to match a team’s style, system, and role expectations - in possession and out of possession. That’s where Contextual Scouting comes in.

The Contextual Scouting series is where I use advanced tracking data from SkillCorner, known as Game Intelligence, to try and find undervalued players in developing markets. We combine the two frameworks introduced in our earlier articles - the Playmaker Index and the Pressing Index - to create a Total Index Score. This score captures a player’s overall impact on the game by evaluating their attacking and defensive contributions in tandem, offering a more complete scouting lens. On top of that, we are putting ourselves in the shoes of club, scouting within a specific scenario.

Last time we applied the frameworks in Scandinavia, and our next stop is South America, using data from the 2024 season.

Club Context: A Mid-Table La Liga Side Operating on a Budget

In our second scenario, we take on the role of a mid-table La Liga club searching for a new midfielder - with a specific focus on the LATAM market. The player must be Spanish-speaking, making South America a natural scouting ground. Operating on a limited budget, the club follows a “buy low, sell high” policy aiming to identify undervalued talent with strong resale potential.

We’re looking for a versatile midfield profile: one that combines strong ball progression with defensive reliability. The player offers tactical flexibility, being comfortable as one of the two in a 4-2-3-1 double pivot while also able to operate as a number 8 in a three-man midfield.

The LATAM market is especially appealing since many of the world’s best players, particularly from Brazil and Argentina, have emerged from this region and seen rapid rises in value. One clear example is the growing demand for Brazilian centre-backs, something SCOUTED explored in their “centre-back goldmine” analysis earlier this year.

Clubs across Europe are already tapping into this market. Brighton hit gold with Moisés Caicedo (€5m + 20% sell-on clause), selling him to Chelsea for €116 million, and with Alexis Mac Allister (€8m), sold to Liverpool for €65 million - a combined profit of €168 million (excluding sell-on clauses). Below is a snapshot of recent and similar transfers emerging from the LATAM market:

In short, South America offers exciting opportunities for uncovering hidden talent, developing them on a bigger stage, and eventually securing major profits through smart resale.

Methodology

For our search, we’ve applied the same Total Index Score methodology as in our previous scenario in Scandinavia, but with the adjusted weighting to favour defensive output. In practice, this means that the Pressing Index now carries 60% of the score and the Playmaker Index 40%, rather than distributing weight across each category individually.

Our shortlist comes from the Argentine Primera División, Brazilian Série A, Colombian Categoría Primera A, Ecuadorian Serie A, and Uruguayan Primera División, targeting versatile midfielders who combine strong ball progression with high volume and intensity out of possession - players who can anchor our style and deliver future profit potential.

In the top three of midfielders under 26, we can find the technically gifted Ecuadorian midfielder, Kendry Páez. Chelsea recently secured the 18-year-old for just €10 million. Instead of integrating him straight into the first team, they’ve opted to loan him to their partner club, RC Strasbourg, for the upcoming season - a move that underlines their long-term development strategy which mirrors similar models seen at clubs like Manchester City and Red Bull.

Chelsea also won the race for the highly sought-after Estevão - and yes, he too appeared in our Total Index Score when we filtered for wide attackers. Looking ahead to the 2025 season, Franco Mastantuono (now signed by Real Madrid) ranked inside the top five of our Total Index Score. Both players are already earning regular minutes at the top level and stand out as clear examples of the rising stars category.

Another player we highlight as a potential rising stars is Augustín Soría, a 20-year-old recently signed by Al-Sadd in the Qatar Stars League.

Lastly, we want to highlight “hidden gems” Hércules and Richard Ríos (maybe not so hidden anymore). Hércules earned a move to Fluminense and impressed at the Club World Cup, while Ríos, a Colombian international, joined Benfica this summer - a club renowned for buying smart, developing talent, and securing high resale value.

The other midfielders on our list are relatively unknown names, and perhaps this is where the real value lies for a La Liga club operating on a limited budget?

Breakdown of Breakout Stars

Let’s take a closer look at how they perform across the different categories, both in and out of possession. In this comparison, we’ve ranked our selected players in descending order by their Pressing Index.

Remember, we’re looking for a versatile midfield profile: one that combines strong ball progression with defensive reliability. In our context, the ideal data profile must excel in both Progression and Volume, offering value on and off the ball.

One player that caught our eye in the data is Alejandro García, a 24-year-old attacking midfielder from Once Caldas in Colombia’s top division. García ranks highly across four of our six index categories, suggesting he can contribute effectively in and out of possession. Notably, he also appeared in our Index Score for the ongoing 2025 season, highlighting his consistency.

In the following section, we will take a closer look at García and compare him with Hércules and Ríos, who both made moves following the 2024 season.

Scouting Alejandro García

We have already established that García’s profile is exciting based on his strong index score. However, for our sporting director we want to deliver a more detailed report, supported by intuitive visualizations and metrics connected to our playing style. A natural starting point is to break down García’s events using heatmaps to better understand the areas of the pitch he most frequently operates in.

In the top-left heatmap, we see García’s passing options. The darker areas indicate where he most frequently moves to get open and receive the ball. He tends to drift toward the left side of the pitch while still operating centrally, though there are also movements toward the right. The top-right heatmap, which illustrates his on-ball engagements (defensive actions), shows that these actions are concentrated mainly on the left side. Taken together, this makes it clear that his positioning is primarily oriented to the left. The same applies to his possessions, although his off-ball movements display greater variety when progressing into the final third. In summary, García demonstrates strong spatial coverage, influencing large areas of the pitch with contributions on both sides of the ball.

We can further contextualize the heatmap by incorporating physical metrics. The scatter plot below illustrates this by comparing our shortlisted players’ explosive accelerations to HSR and Sprints per 90 (x-axis) with their total sprinting distance per 90:

Erick Mendoza stands out as our most explosive player averaging 7 explosive accelerations (to above 20 km/h) per game, something also reflected in his intensity score from the breakdown. However, his high index score is largely driven by his playmaking qualities (see breakdown), which are also reflected in his goal contributions. So far this season, he has recorded 8 goals and 2 assists in 18 appearances for Delfín in the Ecuadorian Serie A.

García and Ríos both score strongly on explosiveness and sprinting distance, which reinforces our initial impression of García’s physical profile from the heatmaps.

Tactical Context - Will The Player Fit Our System?

To determine if García is a good fit for our club and style of play, we can use scatter plots to handpick metrics that are important for us.

Our tactical context matters: as a mid-table side, we’re unlikely to defend a lot in a high block like the top teams. Instead, we’ll spend much of our time in a medium block, looking to progress the ball from deeper areas and transition quickly when we win the ball.

This means we need to search for players who are not just high pressers, but who are accustomed to defending in a more compact structure, while still showing the progressive qualities we prioritise in possession.

Below, we’ve highlighted our shortlisted players based on two key metrics: their On-Ball Engagements in the Medium Block per 30 OTIP (x-axis) and their On-Ball Engagements in the High Block (y-axis).

The scatter plot provides further context to the players pressing volume, showing that García averages more than 30 on-ball engagements in the medium block per 30 OTIP, which so far suggests a strong fit with our style of play. We can also observe that Kendry Páez ranks highly for on-ball engagements in the high block, a trait that likely makes him well-suited to Chelsea’s high-pressing approach.

The next step is to assess the effectiveness of García’s engagements. In the following scatter plot, we visualize the percentage of actions where players force the ball backwards or affect the opponent’s line-breaking passes:

Players in the top-right corner perform well in both metrics, hindering progression in two ways. The data suggests that García and Hércules will help our team to be defensively solid and stop the opposition from carrying or playing through our lines.

For the final part of our tactical context analysis, we shift focus to an offensive metric. We have already verified that García meets our requirements for defending in a medium block, but our aim is to spring quick counterattacks and punish opponents in transition. To capture this, we now look at which players recorded the highest number of eight-meter carries at above running speed in transition:

The bar chart highlights the top 15 players in our selected South American leagues, with García ranking in the top five with 2.2 carries in transition per 30 TIP. When focusing on carry retentions at above running speed, Agustín Soría also appeared alongside García and Paez.

In summary, García profiles as a strong fit for our style of play, which is built on defending in a mid block and launching quick counterattacks.

Off-Ball Profile

We have now confirmed that García meets our requirements for both defensive and progressive qualities. Looking back at the percentile breakdowns, however, he stands out as the weakest in the finish category, which mainly covers pass attempts to runners in behind and cross receivers. Since it is rare to find players who excel in every area, we want to examine his off-ball profile to gain further context and assess whether qualities there might compensate for his limited direct goal contributions and chance creation volume.

Below, we compare García’s radar with those of Hércules and Ríos, who also rank within the top three of the pressing index.

From the off-ball radar, it is clear that García is a runner. He ranks above the 90th percentile in several offensive run types, and few players can match his output on underlaps, where he averages 2.4 runs per 30 TIP. Our head coach particularly values midfielders who make these movements consistently, as underlaps demonstrate game understanding and a willingness to create space for teammates. It is often a selfless act, since the runner does not always receive the ball. Video scouting confirms that García makes these runs deliberately: after carrying the ball and releasing it to a winger, he frequently follows up with an underlap, at times even gesturing with his hand to signal the space he intends to attack.

When comparing his profile with the other two midfielders, García’s run distribution most closely resembles that of Richard Ríos, now at Benfica. The key distinction is that Ríos seems to contribute more in build-up, reflected in his higher scores for dropping off and coming short runs. Hércules, by contrast, is more involved in direct chance creation, leading the trio in cross-receiver runs and runs in behind - reinforced by his 75th percentile score in the Finish category.

Contextual Scouting: From Data to Decision

We’ve now done the groundwork of data scouting by identifying a player whose profile aligns with our playing style. The next step is to validate these findings through video analysis, confirming that the traits highlighted in the data translate to the pitch.

At this end of the market we cannot expect to find a complete midfielder who excels in every aspect of the game. Instead, we have prioritised qualities that are central to our style of play. García’s biggest strengths lies in the preceding phase, progressing the ball up the pitch and opening up space for his teammates, as well as covering a lot of ground both offensively and defensively. With that in mind, he could be deployed as a space-eater or runner in midfield, complemented by another more advanced playmaker (8/10) more specialized in goals and assists. At a market value of just €900k (Source: TransferMarkt 20.06.2025), García could represent excellent value for a club within our budget, provided we platform his strengths effectively within the team environment.

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Talent alone isn’t enough. To succeed, a player needs to match a team’s style, system, and role expectations - in possession and out of possession. That’s where Contextual Scouting comes in.

With this approach, the goal is simple: help clubs find players who match specific tactical and stylistic needs both in and out of possession. Not just “good” players, but the right ones - increasing the certainty around these key investments. The second part of effective scouting, and what we want to focus on here, is identifying hidden talent in emerging and ‘untapped’ leagues and markets that can generate high resale value.

In this piece, we combine the two frameworks introduced in our earlier articles - the Playmaker Index and the Pressing Index - to create a Total Index Score. This score captures a player’s overall impact on the game by evaluating their creative and defensive contributions in tandem, offering a more complete scouting lens.

We’ll go through some realistic scenarios for clubs in different situations to show how these scores can add precision and more certainty in recruiting for key positions.

We’re focusing on emerging markets; places where quality often goes unnoticed, and where value can be found before prices skyrocket. Our first stop is Scandinavia, using data from the 2024/25 season, before expanding to Asia and South America.

Club Context: Champions League Club with a Possession-Dominant Style

We are a title-chasing club in one of Europe’s “Next Three” leagues, which have become a launchpad for players on their way to the very top of European football:

• 🇧🇪 BEL1 Pro League

• 🇳🇱 NED1 Eredivisie

• 🇵🇹 POR1 Primeira Liga

We occasionally compete in the Champions League, but remain vulnerable to our best players being signed by clubs from Europe’s top five leagues. Our ambition is clear: compete for trophies every season while developing players capable of making the leap to Europe’s elite, and generating substantial profit for the club in the process.

We are a club that plays a possession-oriented game, dominating the ball and dictating tempo, while also pressing with intensity and organisation in both high and medium blocks.

For our style of play, we’re targeting a young playmaker capable of operating as both a No. 10 and a No. 8. In short, we’re after a two-way midfielder with the creativity to unlock defenses and the work rate to contribute both in and out of possession.

So, where might we uncover a player like this?

In recent years, Scandinavia has emerged as a breeding ground for top-tier talent, producing technically refined and tactically intelligent profiles. A common thread in many of these players’ journeys is the step-by-step nature of their development. Rather than jumping straight to a top-five league, they often take an intermediate step, typically to leagues like the Netherlands, Belgium or Portugal - where they can secure consistent minutes, grow in a competitive but supportive environment, and prove themselves before making the leap to a major European club. However, some clubs from the ‘Big Five’ leagues have already started to take notice, securing talent early in this market before prices increase.

Below is a snapshot of the development pathways some Scandinavian players have taken in recent years:

The chart showcases a selection of players - some who have already established themselves, and others identified as high-potential prospects - and the region continues to produce exciting young talent beyond those highlighted here.

In the following section, we narrow our focus to young midfielders or playmakers, using data from last season in Scandinavia to highlight those who stand out statistically and show high potential.

Methodology

To make our analysis and player filtering as detailed as possible, we have combined the Playmaker Index and the Pressing Index into a single Total Index Score. The visual below serves as a reminder of the metrics that make up each index.

As part of our analysis, we have manipulated the weightings to see how each category shapes the overall score and influences the ranking of players.

Our weighting reflects the dual demands we place on an 8/10 hybrid in a modern pressing team. In possession, Movement (40%) and Finish (40%) are prioritised because our playmaker must constantly find space between lines and then turn those positions into decisive actions in the final third. Progression (20%) remains important, but in our structure Forward Momentum and Carries are more evenly distributed across the team, so we value the connective role of the playmaker more than raw progression volume.

Out of possession, we mirror that distribution by giving equal weight to pressing Volume (40%) and Effectiveness (40%). The player must repeatedly join pressing chains and actively disrupt opposition build-up and progression, not just run for running’s sake. Intensity (20%) adds value through explosiveness and burst, but is secondary to overall pressing output and end outcomes.

This distribution ensures the Total Index Score highlights profiles who can dictate tempo and unlock defences while also sustaining our pressing identity. It builds directly on the insights from the Modern Playmaker and Pressing Playmakers analyses, where availability, final-third decision making, and pressing impact were identified as the defining qualities of the role we are targeting.

The outcome is a ranking of midfielders best suited to our tactical demands; breaking down teams who deploy a low block and win the ball back by applying effective pressure in the high block.

The bar chart below ranks midfielders in Scandinavia under 26 years old by their Total Index Score:

The top performer in our Total Index Score is 18-year-old Sverre Nypan. Manchester City secured one of Europe’s most promising young talents before his price tag and market value skyrockets. Nypan has now joined Middlesbrough on loan, a move that should expose him to the physicality of English football, and the minutes needed to prepare for a future role in City’s first team. If he succeeds, the upside is significant - both in terms of potential long-term integration into the senior squad, but also with limited risk with good potential resale value as well.

Scouting Sverre Nypan

To gain deeper insight into a player identified through our data, we can turn to heatmaps from the 2024 Norwegian Eliteserien season to help illustrate his playing style and movement patterns.

While traditional heatmaps focus on event-based stats like passes in possession or tackles and interceptions out of possession, we’ve gone a step further by splitting Nypan’s actions into four distinct heatmaps based on SkillCorner event types. This allows us to paint a picture of Nypan’s off the ball actions as well:

Nearly half of Nypan’s total events come from making himself available as a Passing Option, while only 14.1% fall under traditional ‘In Possession’ metrics like touches or passes.

The On Ball Engagement heatmap is particularly interesting, showing that Nypan defends deeper in his own half, ticking our boxes as a hybrid 8/10 profile rather than a ‘luxury’ #10.

As seen in the heatmaps, the left half-space is where Nypan mainly operates - It’s the zone where he most often picks up possession and creates danger, underlining his role as a connector and creator in that channel. Regarding Nypan’s passing options, the touch map (below left) highlights all instances where he received the ball in space (at least 3 meters to the closest opponent at reception).

Building on this, we can also isolate his off-ball runs. Nypan’s off-ball runs heatmap (15% of his events) show a clear tendency to push into the penalty area, suggesting a box-crasher profile. Within this, he often targets the cut-back space, as highlighted by his high number of cross-receiver runs around the penalty area.

As Scouted summed up in a previous piece about Secrets of Scandinavia: He makes a lot of runs, a lot of those runs are dangerous and they result in shots and goals for his team.

Breakdown of Next Breakout Stars

We can take our analysis of Nypan and the other young profiles a step further by breaking down their percentile scores in each category within the two indices.

The category breakdown tells us even more. Nypan’s all-round profile fits perfectly with our game model: he is the only player who excels across all categories, with the one exception being Effectiveness, where he falls just below the 80th percentile. That said, a score above the 70th percentile in Effectiveness is already quite strong, especially considering how demanding this category is. It combines four distinct metric components: on ball engagements in high block which force opponents backwards, affect line break, leads to disruption, and leads to regains - which makes it harder for most playmakers to get a high percentile score here.

Other players ranked highly in our index have already made the move to the ‘Next Five’ leagues. Håkon Evjen moved early to AZ Alkmaar before returning to Bodø/Glimt, where he played a key role in their run to the Europa League semi-final. In fact, the Norwegian serial winners will play in the Champions League for the first time this season.

Albert Grønbæk earned a move to Rennes, had a short loan in the Premier League, and will play for Genoa in Serie A this season. Same goes for Yuito Suzuki who delivered goals and assists at Brøndby which earned him a move to Freiburg in the Bundesliga.

Of the younger prospects in the top positions, Mario Dorgeles has moved to Braga, Malick Yalcouye has joined Brighton (loaned to Swansea), and Victor Froholdt has been snapped up by Porto.

The Shortlist

Of the players still available, we’ve picked out exciting youngsters, Thomas Jørgensen and Noah Nartey (both 19 years old). Below, we have visualized and compared their run profiles using our off-the-ball radar charts, alongside Nypan for reference.

Jørgensen’s off-the-ball profile stands out, as he shows a wide variety in his run types, with relatively high values across all categories. The most interesting insight here is that Jørgensen actually scores higher than Nypan for cross receiver runs P30 TIP, while also registering strong numbers for dropping-off runs and coming-short runs, which are more prominent in build-up play for midfielders. This can suggest that Jørgensen takes on greater responsibility in his team's build-up, while also showing the capacity and intent to get into the opponent’s box.

When we link this with his pressing volume - as a proxy for work rate - we begin to see promising signs of a true two-way midfielder emerging, which fits the profile we are looking for.

Contextual Scouting: From Data to Decision

Ultimately, who we target depends on our needs and who we see as having the highest potential. Jørgensen leads our shortlist for Pressing Volume, while Nartey sits joint-top with Nypan for Progression. Whichever route we take, our aim would be to develop the player’s other qualities to create a more complete profile and eventually sell him on for a profit.

If we were to choose one based purely on the data, we would be inclined towards Jørgensen, as he ranks highly in more categories than Nartey and fits the creative profile we’re looking for. His high pressing volume is a major plus, helping offset his weaker explosiveness score. That said, we know that our scouts and sporting director will want to take a look at both players on video (or perhaps in person) to get a full picture and come to our decision.

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The era of accommodating luxury playmakers or midfield “passengers” who contribute little out of possession is, for the most part, a thing of the past at the elite level. Today’s attacking midfielder is expected to be more than just a creator; they must play their part in the team’s defensive gameplan like everyone else.

The problem is that we’ve lacked the tools to properly measure this side of the game. Traditional defensive stats like blocks, tackles, and duels capture isolated moments but miss the broader context.

If a player applies pressure to the ball carrier and forces them backwards or sideways, prevents a counterattack, or blocks off a dangerous passing option, they’ve done their job for the team, but they haven’t won a duel or made an interception.

In fact, less than 3% of defensive engagements result in a direct regain (SkillCorner, 2023), and most “pressure” stats are still based on proximity to the ball, with no insight into pressing quality or effectiveness.

Until recently, this additional defensive context was largely invisible in the data. But with Game Intelligence, we can finally evaluate the quality of a player’s defensive output beyond challenging for the ball and define the best pressing players.

In our previous Contextual Scouting report, we explored how the Modern Playmaker unlocks defences through movement, progression, and decision-making on the ball. In this follow-up, we flip the perspective to evaluate which of these players gives us what we need out of possession.

As before, we apply a role-specific scouting framework, starting with the player profile we’re looking for and translating those football traits into measurable metrics. With that foundation, our goal is to identify the attacking midfielders who defend with the same purpose they create.

The profile we’re looking for is:

"...A pressing midfielder who defends actively, with speed and intensity, in the high block and disrupts opposition build-up by forcing them backwards and cutting off passing lanes.…"

We’ll analyse midfielders from the ‘Big Five’ European leagues; however, as we’re switching from in-possession to out-of-possession, we’re exploring a new set of metrics from Game Intelligence: On Ball Engagements (OBE).

On Ball Engagement consists of a variety of defensive events:

We also capture the phase of play in which these defensive metrics occur, putting these defensive actions in context - for example, how a centre-back engages in a high line vs. in a low block, or a centre-forward’s ability to lead a high press vs quickly retreat into defensive shape.

We’ll also combine these defensive metrics with Physical Data so we can identify dynamic athletes who really impact the game with the speed and intensity of their pressing.

Volume: "...defends actively in the high block ...”

In this analysis we aim to identify midfielders who are active out of possession in the team’s first line of defence. Specifically, we're looking for players who consistently press from the front, while also maintaining defensive discipline in a medium block.

To find this versatile profile in the data, we’ve isolated midfielders’ on ball engagements in both high and medium blocks. In the scatter plot below, we’ve mapped players based on two key metrics: their pressing engagements p30 in a high block (as part of a pressing chain) on the y-axis, and their combined total of pressing and pressure actions p30 in the medium block on the x-axis:

Phil Foden stands out as one of the most active pressers, ranking first for pressing engagements in the high block and third for combined pressures in the medium block. In the medium block, Unaí Gómez (Athletic Club) leads the way in combined pressing and pressure actions. Familiar names like Martin Ødegaard, Cole Palmer, and Kevin De Bruyne also appear prominently. All three play for teams that frequently defend high up the pitch, so their presence here is no surprise.

More unexpected but noteworthy names include Johann Lepenant (Nantes), Juanlu Sánchez (Sevilla), and Omari Hutchinson (Ipswich), who also show strong pressing tendencies despite playing for teams with different defensive setups.

To provide context around team styles of play, we've highlighted a selection of the teams above to show which defensive phases they spend the most time in:

Effectiveness: “...disrupts opposition build-up by forcing them backwards and cutting off passing lanes...”

We now have a sense of which players frequently engage in pressing actions in the high and medium block, but quantity doesn’t necessarily lead to quality. With Game Intelligence, we can go a step further and use pressing outcomes as a measure of quality and effectiveness.

There are two primary ways in which we can measure how On Ball Engagements affect the ball carrier. One goal of pressing in a high block can be to hinder progression, with intense pressure on the ball carrier to force them to play backwards or sideways. Some clubs, on the other hand, prefer their #10 to play more of a containing role cutting off the ball carrier’s ability to play line-breaking passes.

In the scatter plot below, we highlight midfielders with the highest share of On-Ball Engagements in the high block that force the opponent backwards (x-axis) and affect potential line breaks (y-axis).

Note that total on-ball engagements include not only pressing and pressure engagements, but also counter-press and recovery press engagements, giving us a more complete picture of their overall defensive engagements.

We’ve also applied a filter threshold of at least 10 OBE Engagements in High Block Per 30mins OTIP (“Other Team In Possession”) to avoid players with low counts skewing the sample:

The visualisation above highlights the midfielders in our sample that are most effective at forcing opponents backwards or affecting line-breaking passing options.

Players in the top left, top right and bottom left quadrants are all recording high percentages of success in their On Ball Engagements, but the outcomes they’re achieving are different. Warren Zaire-Emery, for example, in the bottom right ,excels at forcing the play backwards while Juanlu Sanchez is the most effective player in our sample when it comes to affecting potential line breaking passing options. Finally, midfielders positioned in the top-right quadrant record high percentages for both outcomes.

The vertical dotted line represents the average percentage of high block engagements that force the opponent backwards. As our profile calls for more aggressive, direct pressure, we’ve highlighted the players ranking above average for this metric - let’s call them “hunters”.

The bar chart below refines our list of hunters by including only midfielders with at least 10% of their high block on-ball engagements resulting in the opponent being forced to play backwards:

Interestingly, this metric highlights players from less prominent clubs. Our leading hunter is Isi Palazón (Rayo Vallecano) with 15.2%, and just below him are two players from Bologna, which could point to a well-coordinated pressing system at the club. Other standouts are Yann Gboho (Toulouse), Paul Nebel (Mainz) and Bilal El Khannouss (Leicester City), who also ranked highly in our Playmaker Index, showing their impact on both sides of the ball.

While disrupting progression may be the main priority for our profile, others may prioritise winning the ball back in the opposition half.

With that in mind, our next bar chart focuses on identifying which of our hunters that also excel as Ball Winners or “stealers”. We do this by measuring the share of on-ball engagements in high block that lead to direct regains of possession or clear disruption of the opponent’s play:

Eren Dinkçi, the 23-year-old attacking midfielder from Freiburg, stands out as the most effective ball-winner among our hunters - with 19% of his on-ball engagements resulting in either a regain or disruption of the opponent’s play. Next on the list, ranking highly again, is top-10 Playmaker Bilal El Khannouss.

So far, we’ve added an important layer of context to pressing by identifying players who press effectively, but pressing isn't just about structure or awareness; it’s also about intensity. We’re looking for a player with the physical profile to close down opponents at speed, to deny opponents time and space and force mistakes.

Intensity: "...defends actively with speed and intensity…”

How can we further differentiate between our pack of hunters to identify who engages the ball carrier with the intensity we’re looking for?

We can measure pressing intensity by benchmarking players based on their ability to perform pressing and pressure engagements at HSR and Sprint speed.

The bar chart below ranks our hunters by their total pressing and pressure actions performed at HSR and Sprint speed:

Martin Ødegaard stands out as a relentless presser in our analysis, recording 148 pressing/pressure engagements at HSR speed and 38 at sprint speed over the 2024/25 season. Only Justin Kluivert comes close to matching him in terms of total high-intensity volume, underlining Ødegaard’s exceptional work rate off the ball.

We can convert these numbers into percentages, revealing:

22.7% of Ødegaard’s pressing and pressure actions were performed at high-speed running or at sprinting intensity - the highest share among all midfielders in the top 5 leagues with over 500 recorded pressing and pressure events throughout the season.

The bar chart below ranks our selected hunters by their share of pressing and pressure events performed at high intensity. This is more representative as minutes played affects the count chart above - with more playing time allowing more opportunities to press.

While Ødegaard still ranks on top for share of high-intensity pressing and pressure engagements, we can notice that Justin Kluivert moves down the list where 15% of his pressing activities are performed at HSR and Sprint Speed.

The final element of our physicality profile is explosiveness. With so many physical actions taking place within tight spaces, this short area quickness is just as important as top line speed. We can assess our hunters’ explosiveness by looking at the unique acceleration metrics available within SkillCorner Physical Data: Explosive Accelerations:

The ‘Count’ metrics will give an indication of our hunters’ ability to perform explosive actions repeatedly, enabling us to identify the hunters with the physical capacity to press relentlessly. We chose to place the hunters in the same scatter plot as other advanced midfielders that scored above the 80th percentile for On ball engagements in the high block:

The ‘Time to’ metrics, on the other hand, show the ability to reach those speeds quicker than other players, giving us the hunters with the burst to close down opponents quickly in tight spaces:

Among our hunters, three players stand out: Yann Gboho, Justin Kluivert, and Bilal El Khanouss. They all demonstrate high totals of explosive accelerations per 90, showcasing their ability to perform repeated sprints. On top of that, Gboho and Kluivert rank among the top five in our sample for time to reach sprint speed – in company with elite playmakers such as Florian Wirtz, Cole Palmer, and Jude Bellingham.

The big outlier, however, is Omari Hutchinson. Despite playing for Ipswich, a team that spends most of its time in a low block, he still ranks top for total explosive accelerations and within the top five in our sample for sprint count per 90. Not only that, Hutchinson is the joint second most explosive player in our sample, together with Xavi Simons, averaging just 1.36 seconds to reach sprint speed.

While different clubs may prioritise these physical elements differently within their versions of this profile - perhaps depending on the level within their league competitions - we can certainly use them as a reference point for our hunters’ ability to impact the game with their physicality.

Contextual Scouting: Combining Data-Driven Profiles In and Out of Possession

This exploration of the hunter profile is another example of how Game Intelligence enables scouts and analysts to move beyond generic metrics to find exactly what they’re looking for.

With the flexibility to combine and tailor metrics, clubs can craft precise, role-specific profiles and gain greater confidence that the players identified will meet both the tactical and physical demands of their system.

If you read our previous analysis on The Modern Playmaker, some of the names in this analysis will be familiar from the Playmaker Index. Players that rank highly in both analyses excel both in and out of possession, and may have the complete profile we’re looking for.

In our next piece of the contextual scouting series, we will look to combine both profiles to find complete players in other markets and team-specific scenarios and contexts.

Thank you for reading Expected Insights! 💡
It’s been so fun to see the continued growth of the channel and just how many of you that are interested in data-driven insights from the beautiful game.

Going forward, I hope to spark even more discussion and interaction within this community here on Substack 🚀

Looking forward to seeing your responses in the poll!

Excited to share what I've been working on this past month: I’ve joined SkillCorner as a football insights writer! ⚽️🚀

Whether you’ve been following my work for a while or just joined - thank you for being here. It’s incredibly rewarding to see so many people interested in the future of data-driven scouting.

Now, grab a coffee and dive into why Liverpool were willing to break the bank for Florian Wirtz, and which under-the-radar talents that are showing similar traits.

Hope you enjoy reading it as much as I enjoyed putting it together.

- Trym

Transfer spending may be restricted to the summer and January windows, but planning happens year-round. Recruitment is now a long-term game: complex, competitive, and difficult to master.

History has shown this to be the case, with approximately 50% of signings failing to meet expectations ('How to win the Premier League', Graham 2023) and many struggling to secure consistent playing time during their first two seasons.

The majority of clubs are now using data in one form or another to reduce the risk of costly mistakes, with forward-thinking clubs looking for more and more specificity in their profiling to find exactly what they need.

SkillCorner’s Game Intelligence data provides unprecedented granularity and depth, helping clubs pinpoint specific player profiles that deliver the technical and tactical elements they’re looking for - on and off the ball, in and out of possession.

In this new series, we'll adopt the approach of a club, identifying and analysing specific player roles using the most unique metrics available from our Game Intelligence data.

Our first target is a creative attacking midfielder, or number #10.

The profile we’re looking for is:

“... an attacking midfielder who operates between the lines, links play effectively in tight areas, receives on the half-turn, plays forward, and creates chances and goal-scoring opportunities.”

Who are these midfielders that unlock games from the half-space, and how can Game Intelligence help to find them in less obvious places?

For this case study, we’ll analyse players based on their ability to find space, impact the game and create opportunities in the Finish phase, with the opponent positioned in a low block.

(Click here for a video explainer of our unique Phase of Play model)

Movement: "...operates between the lines…”

We’re looking for players who position themselves in the ‘half-spaces’ between the opposition’s midfield and defensive lines to receive the ball, create dangerous situations and tempt opposing defenders out of position.

We can identify this by looking at options for line break receptions through and around the second last line.

Looking at options and not just touches means players are credited for being in the right position, regardless of whether their teammate plays the pass.

The image below illustrates the two types of line-breaking passes we aim to analyse. The first option goes through the block, while the second goes around it. We’ll refer to the space between the opponent’s defence and midfield as the area played through or around the second-last line:

In the scatter plot below, we highlight the players in the “Big Five” European leagues who most frequently position themselves to receive line-breaking passes through or around the second last line:

On the x-axis, we show the number of times a player is available for a pass through the opponent’s second last line. Dani Olmo ranks highest in this metric, closely followed by his teammate Fermín López. On the y-axis, we measure availability for passes around the second line, where Florian Wirtz leads the way.

Wirtz’s positioning indicates his tendency to drift out wide to receive the ball, but his high score for through-the-line availability suggests he also varies his movement to find pockets of space in central areas.

As The Athletic’s Michael Cox observed earlier this season after watching Wirtz’s Bayer Leverkusen draw 0-0 with Bayern:

“...As usual, everything revolved around Wirtz. He is a brilliant player in possession, capable of dribbling past opponents, playing clever through-balls, and scoring goals. But he’s also a truly outstanding player in terms of his movement before receiving the ball. He might be the best player in the world at finding space between the lines, away from the opposition midfielders.”

Other notable names appearing prominently in both metrics include Oihan Sancet (Athletic Club), Weston McKennie (Juventus), and Phil Foden (Manchester City), all players who frequently operate between the lines.

So far, we’ve identified who gets into the right spaces. But what happens once they receive the ball?

The next question we want to answer is: which players link play efficiently and drive their teams forward?

Progression: “...receives on the half-turn, and plays forward…”

To answer this question, we can rank midfielders using a brand-new on-ball metric: Forward Momentum, which captures how effectively a player plays forward after receiving the ball.

Forward Momentum is recorded when a player receives a pass from the back or from the side with an opponent less than 6 metres away and executes a progressive action, for example:

- Receiving on the half-turn and playing forward
- Progressing the ball with a turn or drop of shoulder
- Turning up the pitch and carrying the ball

This metric helps us identify midfielders that find space between the lines and use those moments to accelerate play, break structure, and move their team up the pitch with purpose.

In the scatter plot, we have highlighted the players with the most possessions in the Finish phase (x-axis) and players with the highest counts for Forward Momentum (y-axis):

Florian Wirtz has the highest share of possessions in the Finish phase. However, Cole Palmer, Jamal Musiala, Dani Olmo and Phil Foden all averaged more than 1.3 forward momentum actions per 30 TIP. These are midfielders who consistently drive play forward in decisive moments and act as key link-up players in their teams' final-third progression.

A sharp eye may have spotted Aston Villa’s Morgan Rogers in the previous chart. In the visualisation below, his impact becomes even clearer. Rogers leads all players in Forward Momentum actions as a share of total possessions:

While that figure might initially seem modest, it’s important to consider the context: these actions are taking place in Finish phase, i.e. against a settled low block, where space is at a premium. That makes Rogers' ability to consistently receive the ball with Forward Momentum even more impressive.

It's also interesting to note that the top three players are all products of Manchester City's academy.

To further our analysis, we can also rank players by their ability to carry the ball in the Finish phase:

In this bar chart, we rank midfielders based on the number of carries covering at least 8 meters. Florian Wirtz ranks first with an average of 9 carries per game, and he’s in strong company alongside other well-known attacking midfielders such as Martin Ødegaard and Isco. There are also some less high-profile names at the top of the list: Yann Gboho (Toulouse), Dwight McNeil (Everton) and Paul Nebel (Mainz 05).

So far, we’ve identified which players consistently operate between the lines and those who help their teams progress the ball from these spaces. But this still doesn't tell us who turns these moments into real value for the team.

To complete the picture, our final requirement shifts the focus closer to the goal, to understand which players are the most effective at converting these situations into actual chances and scoring opportunities.

Finish "...creates chances and goal-scoring opportunities.”

In the scatter plot below, we show how often midfielders attempt passes to runs in behind (x-axis) and to cross receiver runs (y-axis) during the Finish phase:

Florian Wirtz stands out as one of the most complete playmakers in our sample. He has ranked among the best across nearly every metric in our analysis, from his movement between the lines to his progressive actions in the final third.

This final chart is no different, with Wirtz leading the way in combined pass attempts to both runs in behind and cross receiver runs.

Other standouts include Rodrigo de Paul (Atletico Madrid) who ranks second for pass attempts to runs in behind, and 21-year-old Gvidas Gineitis (Torino) - the only player ranking above Wirtz in pass attempts to cross-receivers.

Lastly, Yann Gboho (Toulouse), a 24 year old attacking midfielder, who has recorded 5 goals and 4 assists this season, ranking highly for both metrics.

Elite creators like Wirtz and De Bruyne attempt many passes, but they also get more opportunities playing in possession dominant teams. This raises an important question: how do we evaluate risk-taking midfielders in lesser-known teams who don’t get as many opportunities?

We can start to answer that question by examining the percentage of pass attempts relative to a player's total opportunities.

In the bar chart below, we highlight the players with the highest pass attempt rates, using a minimum threshold of 1.5 opportunities per 30 TIP to focus on players who are regularly involved in chance creation:

Gineitis is the clear outlier here, attempting 90 per cent of his opportunities. The previous scatter plot showed that the vast majority of his passes are directed toward cross-receivers, indicating that he tends to identify those opportunities and targets them aggressively.

Interestingly, of the 30 games Gineitis played for Torino last season, only 15 were starts, showing how data can surface intriguing profiles that might otherwise fly under the radar.

Just below Gineitis is another aggressive passer: Paul Wanner, a 19-year-old Bayern Munich youth product that spent last season on loan at Heidenheim in the Bundesliga.

Wanner attempts 70% of his available passes, but with a more balanced distribution; averaging 0.52 to cross-receiver runs and 0.69 in behind, highlighting his potential as a Modern Playmaker.

So far, we’ve demonstrated how Game Intelligence can be used to profile these midfielders - from their movements before receiving the ball to their impact in the final third - all while factoring in key match context.

In the final part of our analysis, we bring it all together to identify the most complete Modern Playmakers in European football.

Building The Modern #10: The Playmaker Index

The Playmaker Index score captures the complete playmaker profile by blending performance across the three key requirements we've focused on:

In order to create a shortlist of interesting prospects, we’ve calculated percentiles and assigned value based on the metrics above. The Modern Playmaker will score above average in all metrics.

Below, we have the top 15 players across the “Big Five” European leagues, ranked by their overall Playmaker Index:

Florian Wirtz tops the Playmaker Index, narrowly edging out Phil Foden and Xavi Simons. What sets Wirtz apart is his consistency as he ranks among the top two across all key requirements.

He is only surpassed by Oihan Sancet for movement between the lines and by Phil Foden for progressive actions, but ranks first for chance creation in the Finish phase.

The ranking includes a variety of lesser-known names that may be options for elite clubs looking to identify the next generation of playmakers.

While the standout performers in Europe’s “Big Five” leagues are likely to carry premium price tags, the same Playmaker Index framework can be applied to identify talent in emerging markets.

Below, we highlight top-performing midfielders from the “Next Five” leagues: the Eredivisie, Belgian Pro League, Primeira Liga, Turkey’s Süper Lig, and the Czech First League:

This chart highlights several lesser-known young players.

Just below two experienced playmakers, Dusan Tadic and Dries Mertens, we find 17-year-old Konstantinos Karetsas, who has already recorded 3 goals and 2 assists in his 20 starts for Genk this season.

It’s no surprise to find another promising young player in the Belgian Pro League; our partners at Scouted highlighted the consistent flow of young talent from the Pro League in a recent piece.

Just below Karetsas is Levi Smans, a 22-year-old attacking midfielder playing for Herenveen. Smans scored highly for all of our requirements, excelling in movement, progression and chance creation in the finish phase.

A bit further down the list, we find Luciano Valente, a 21-year-old attacking midfielder at FC Groningen. Now in his third straight season of regular first-team football, Valente has tallied 7 assists and 2 goals this campaign and recently earned a call-up to the Netherlands U21 squad.

His standout trait is progression: ranking first for Forward Momentum Actions per 30 TIP and trailing only Kacper Kozłowski in Forward Momentum possession share during the Finish phase. Standing at 189 cm, Valente blends physical presence with technical quality, also ranking in the top five for 8M carries in the finish phase.

Finally, 18-year-old Rodrigo Mora (FC Porto) excels at finding space between the lines, ranking first for combined line break opportunities through and around the second last line. He’s also proving clinical in front of goal, with 10 goals and 4 assists in just 16 starts (23 total appearances).

Contextual Scouting: From Data to Decision

In this article, we’ve shown how scouts and analysts can use SkillCorner’s Game Intelligence data to perform detailed, role-specific player profiling.

As a reminder, here’s the profile we’re looking for:

“... an attacking midfielder who operates between the lines, links play effectively in tight areas, receives on the half-turn, plays forward, and creates chances and goal-scoring opportunities.”

By systematically translating these football requirements into clearly-defined metrics, we've captured the actions and movements identified in the profile, and narrowed our focus to the Finish phase.

Our exploration of the modern playmaker serves as just one example of how Game Intelligence data empowers scouts and analysts. With the flexibility to combine and tailor metrics, clubs can craft targeted, precise player profiles and be more confident that the players flagged by the data can deliver what the team needs from a technical and tactical perspective.

Find out more about SkillCorner Game Intelligence Data

📧 If you enjoyed this post, I’d appreciate it if you would share it with a friend 🌟

🔗 I post regularly on my LinkedIn as well, so feel free to connect with me there 🤝

What is ‘Vibe Coding’ ?

You may have heard about Vibe Coding by now. If not, here’s how Andrej Karpathy, a leading figure in the AI space, defines it:

“There's a new kind of coding I call "vibe coding", where you fully give in to the vibes, embrace exponentials, and forget that the code even exists” (X, 2024)
- Andrej Karpathy

This approach transforms the developer’s role from writing code line by line to guiding, testing, and refining code generated by an AI model. Put simply, you’re having a conversation with a tool like ChatGPT: asking questions or giving prompts that trigger code execution in the background.

The key is clarity: the more specific your prompts, the better the results. And like any good collaboration, it often requires iteration and refinement to reach the output you’re aiming for.

Building on the philosophy of vibe coding, I thought it would be cool to adapt it to football and see how it could help me identify standout players.

Hence, I present to you: Vibe Scouting 😎

In the following section, I will show you the prompt I wrote to ChatGPT and the strategy we made in uncovering outliers from the 24/25 season in the Top 5 leagues. Enjoy being a fly on the wall!

Writing the Perfect Prompt

To support a data-driven scouting piece, I collaborated with ChatGPT to identify standout players under the age of 27 using Z-scores: a statistical method that highlights outliers.

👨‍💻 I started with the following prompt:

I want you to scout for me based on weighted Z-scores to find outliers in the data.
Some requirements are:

• Players must have played equal or more than 700 minutes

• Age filter < 27 to find relatively young and promising players with high market value

• For each position, you must make an evaluation of what metrics are suitable to measure high performance in that position (for instance, you should make different profiles for a deep lying midfielder, often called #6 and an attacking midfielder, often referred to as a #10). Pass completion is more important for a #6 for instance, while attacking players should take more risk. The same goes for differentiating between wingers and strikers although they both go under the same category of "FW".

Output:

The output I want is the top 20 players for each position. The positions I want are:

• Full backs (DF)

• Center Backs (DF)

• Deep Lying midfielder #6 (MF)

• Box to Box midfielder #8 (MF)

• Creative attacking midfielder #10 (MF)

• Advanced Striker #9 (FW)

• Playmaking Winger (FW)

• Inverted Winger (FW)

Before you start the analysis, ask me a question to clarify potential questions or suggestions.

ChatGPT followed up with clarifying questions on how roles should be assigned, how to normalize stats, and how I wanted the output structured. I clarified:

• Roles should be inferred using clustering

• Z-scores should be calculated and compared within each role group (e.g. full backs with full backs)

• Missing data should be handled carefully — no artificial values

• Output should include rankings together with the metrics used
  

  *Important: You need to feed ChatGPT with a dataset (excel file or a csv) together with the prompt. My data was event data from FBref: Top 5 Leagues 24/25*

Results

In the following section, I will go through the result from three different player roles. Let’s begin with strikers.

Our first bar chart ranks strikers using z-scores, a statistical measure that shows how far a player deviates from the average 💡

A z-score of 0 means average, while anything above 2 signals a clear outlier; someone performing significantly above their peers.

There is no need to discuss Kylian Mbappe in first place, but it’s worth noticing Mika Biereth in second place as his output for Monaco this season has been nothing short of extraordinary. What’s especially impressive is that he only broke into the team in October, yet still managed to score 13 goals and provide 2 assists in just 16 league games.

Notable mentions for scouts and analysts include the other players highlighted in red. While not quite at Biereth’s level, these relatively under-the-radar talents also score above average across key metrics.

🚀 For example, Luca Stassin and Emmanuel Emegha have quietly put together strong seasons in Ligue 1, consistently contributing with goals and promising underlying numbers.

Further up the table, we have Rodrigo Muniz and Myron Boadu who scores well above average due to the fact that they have really high output (goals) in the relatively few games they have played.

Now, we will look at the top “Box-to-Box” midfielders according to ChatGPT.

For midfielders in Europe, Pedri is the clear outlier averaging 11.2 progressive passes per 90 and 10.3 passes into the final third per 90 (ranking above the rest in both of these metrics).

On top of that, Pedri has the highest total of Shot Creating Actions (5.2 per 90), and he also ranked as number #1 when I looked at the deep-playmaker role which tells us what a complete player he is and how he excels between both boxes!

📊 For reference; here are the metrics and weights that ChatGPT used to evaluate box-to-box midfielders:

• Progressive Carries (15 %)

• Progressive Passes (15 %)

• Shot Creating Actions (15 %)

• Tackles (10 %)

• Interceptions (10 %)

• Assist P90 (15 %)

• Goals P90 (10 %)

• Passes into Final Third (15 %)

  ---

There are some other standouts here as well; Tijani Rijnders who have been linked to Manchester City lately, Angelo Stiller playing fantastically in Stuttgart, and Lamine Camara who I talked about earlier this season when I was scouting for elite midfielders in Europe 🔎

Fun fact: Ryan Gravenberch is the king of Interceptions (in this group) with 1.7 int per 90, while Alexis Mac Allister tops the chart for tackles at 3.3 tackles per 90 💥

🔗 Together, they form a midfield pivot duo that complements each other defensively; one breaking up passing lanes (Gravenberch), the other disrupting play directly (MacAllister). It’s a dynamic pairing that’s particularly exciting from a Moneyball and squad-building perspective.

Apparently, Slot made MacAllister rest for the last couple of games this season because of his “Argentinian mentality”, translated into tackles by the data.

The last role we will analyze is Defenders.

Because both full-backs and center-backs are grouped under “Defenders” in FBref data, I’ve chosen to label this player cluster as Attacking Defenders.

While the majority of the chart is dominated by full-backs, we also see center-backs who excel going forward; a profile I like to call Hybrid Defenders. The standout here is Joško Gvardiol, who ranks an incredible 3 standard deviations above the mean. His ability to operate in multiple roles makes him a uniquely versatile defender.

In fact, Gvardiol has the highest number of total carries into the final third, and only Nuno Tavares beats him on a per-90 basis in that metric. Let’s not forget that Gvardiol has scored five goals this season as a defender, and last season he had four!

Other center-backs like Jan Paul van Hecke, Alessandro Bastoni, and Nico Schlotterbeck also show up well, reflecting their progressive passing styles.

On the full-back side, we find several familiar names: Trent Alexander-Arnold, Milos Kerkez, and Achraf Hakimi. But there are also some pleasant surprises — particularly Dodô (Fiorentina) and Andrei Rațiu (Rayo Vallecano), with the highest totals of progressive carries over the season.

Lastly, shout-out to Nuno Tavares, Juan Miranda, and Pedro Porro for leading the way in crosses into the penalty area per 90, offering real value in final-third delivery.

Lastly, let’s look at the center back cluster. I think this is a really interesting list that the AI has given us, since we can see the likes of Dean Huijsen and Nathan Collins in the middle of the chart, both ranking above average for this role.

Both of them had great seasons, Huijsen on his way to Madrid, and Collins is the only player this season who have played every minute in the Premier League! Someone who deserves a proper vacation 🌴

However, the profile that stands out for me is 21 year old, Diego Coppola, who plays for Hellas Verona.

Coppola stands tall at 192 cm and boasts an impressive aerial duel win rate of 64.9%, averaging 4.1 aerials won per 90 minutes. He also leads his peers in interceptions with 2.2 int per 90, placing him in the 96th percentile for that metric❗️

This is somewhat reminiscent of Virgil Van Dijk’s data profile; dominating duels and reading the game through intercepting a lot. The only minus I can find is that he seems to love a tackle (2 tackles per 90) 😅 If you’ve read my Van Dijk series, you know what I mean.

That said, context matters. Coppola plays for Hellas Verona, a mid-table team where defenders are naturally more “active” due to their team setup. At first glance, Coppola’s possession numbers makes him look like a bad player. But after digging deeper, it turns out Hellas Verona averages just 38.8% possession – the lowest in Serie A and the fewest attempted passes in the league. So the low passing and on-ball stats say more about the system than the player.

On a final note, his defensive mindset seems elite and just what we would expect from an Italian defender. In fact, Coppola is expected to make his debut for the Italian national team in the upcoming World Cup qualifiers. Take a look at Coppola in action below 👇

The Power of AI

In this piece, I’ve shown how AI agents — specifically ChatGPT — can act as a powerful assistant for data-driven scouting. Even if you don’t have a coding background, this approach is highly accessible. Remember, all I did was upload the data and have a nice back-and-forth conversation with Chat 🤝

By understanding a few core statistical concepts like clustering and z-scores, you can guide the AI to perform complex analysis through simple, conversational prompts. And if you still don’t quite grasp these statistical concepts, don’t worry, I think I know someone you could ask 🤖

Of course, it’s not completely effortless. The results aren’t always perfect, and getting high-quality output requires iteration, domain knowledge, and a critical eye. The AI is powerful, but not flawless, and still depends on how clearly and specifically you define the task.

That said, it’s an incredibly useful tool for saving time, generating player shortlists, and surfacing overlooked talent, especially if you already have structured data at hand, and a understanding for metrics. The key lies in crafting thoughtful prompts and knowing what you’re looking for.

So what do you think: could vibe scouting be a viable tool in your scouting workflow?
I’d love to hear your thoughts.

Oh I almost forgot, don’t forget to say thank you.

📧 If you enjoyed this post, I’d appreciate it if you would share it with a friend 🌟

🔗 I post regularly on my LinkedIn as well, so feel free to connect with me there 🤝