Tristan Stubbs’ T20 numbers tell a confusing story. There’s a weird pattern of him alternating between good and bad years. And this year, he’s made it even weirder by becoming an elite anchor with a 50+ average. So is it a good year because he was elite at something? Or is it a bad year because anchoring is irrelevant to the modern game?

I recently joked on Twitter about how Stubbs and Brevis seem to alternate years on who the real ‘Baby AB’ is. ‘Baby AB’ was the title given to Dewald Brevis when he initially broke out at the 2022 U19 World Cup. Although his strokeplay isn’t as close to the great AB de Villiers, Stubbs fans - who were also growing in numbers at that time - pushed back, arguing he was the superior batter and more deserving of the title. It was a healthy rivalry between two youngsters who could become future superstars for South Africa. Fast forward four years and both fanbases are now frustrated with their respective heroes.

The very fact that people consider Stubbs worthy of being the successor to AB de Villiers, one of the greatest white ball batters the game has seen, is a testament to his skills. Nobody doubts his ability. Maybe bad form just strikes him in a strange pattern, you might think. The numbers reveal a more interesting story.

Over the last two years, during which he has transformed into a complete anchor with a modest strike rate of 132.49 while the rest of the T20 world is racing on an Autobahn, Stubbs has the second-best dot%. This is a list that is typically dominated by the likes of Kohli and Gill with their low 30s value. At 28.35%, Stubbs comfortably clears them as well as KL Rahul, Shreyas Iyer, and Sai Sudharsan, all of whom you’d also expect to feature near the top.

Another related metric is the rotate% which indicates the percentage of balls resulting in a single, double or triple. This metric adds crucial context to dot%. A lower dot% can be achieved both by scoring boundaries and by rotating strike. The former is the more desirable T20 trait while the latter is what defines a typical anchor.

Stubbs ranks at the top here and the gap between him and the second place is significant enough to crown him the undisputed strike-rotation champion. While this isn’t the sexiest T20 skill, achieving a super-elite dot% of 28.35% alongside a rotate% of 60.76% is no easy feat and requires incredible batting skills.

Form slumps can manifest in different ways and it’s not impossible for it to affect one facet of a player’s game more than the others. But it’s hard to imagine a form dip where the player remains the absolute best in the world at one specific skill. So perhaps it’s not right to put his poor numbers down to bad form.

It’s clear then that boundary-hitting is where he falls short during his down years. A closer look into his boundary numbers reveals more.

Barring his peak year in 2024, his balls per four hasn’t really fluctuated all that much. There’s little to suggest his four-hitting declines during his down years. It’s the balls per six figure, which shows a clear distinction between his good and bad years.

Again, it’s hard to imagine a form fluctuation that affects only a batter’s six-hitting ability while leaving his strike rotation and four-hitting untouched. A lack of six-hitting can be attributed to two things: either he strangely loses power in certain years or it’s a matter of intent.

‘South African Thala clones’ is the term I’ve been using to refer to Stubbs and Miller in recent times. It’s a nod to how their gameplay has become increasingly similar to MS Dhoni of late: consolidate at the top, take it deep and blast at the end. That formula made Dhoni a top-tier T20 player in his prime. But the T20 landscape has shifted.

We now live in a world where ‘balls won’t come back’ is a prevailing mantra and teams are actively strategising to maximise every single ball. So the question begs: is taking it deep still a winning strategy in 2026?

One common theme across all of Stubbs’ years is how he scores slowly in both the powerplay and in the 7-11 overs phase.

The 12-16 overs phase, when batters typically begin to accelerate, is where his good and bad years diverge. In 2022 and 2024, he accelerated here. In other years, he was fairly slow.

Even at the death, where he always scores fast, 2022 and 2024 are the only two years where his death strike rate has crossed 200. Six-hitting is again the culprit at the death.

In the 12-16 overs phase though, he simply refuses to accelerate during his down years as his four-hitting numbers also deteriorate.

We saw earlier that 2026 has been a weird year, ruining the tidy pattern of good year, bad year, good year. But pattern enthusiasts, take heart. There’s one place where that pattern still holds - his numbers against pace.

And as you might have guessed, it means his 2026 numbers have been dragged down by spin.

There’s no clear explanation for why he went full ODI mode against spin this year. Perhaps it’s because he doesn’t have as many high-average years against spin as he does against pace and chose to sacrifice fast-scoring for survival.

But one thing that is clear is that he doesn’t suddenly develop different weaknesses in different years.

Fuller and shorter lengths are consistently his strongest zones against spin while yorker and good lengths are his weaker zones. Only the magnitude differs. In his good year, he’s excellent against his strengths and passable against his weaknesses. That likely comes down to intent.

His pace numbers tell the same story. Stronger against fullish and short lengths. Weaker vs good and short of a length deliveries. 2023 is an outlier year where he struggled against fuller lengths too but the broader pattern holds.

The intent argument is further strengthened by shot data. His staple shots vs pace - the on drive, flick, and pull - have a higher strike rate in his good years and a lower one in his bad years.

These shots can either be used as a rotating shot or an attacking shot. A higher strike rate suggests they were played with boundary-hitting intent more often than not.

There’s a clearer indication against spin where shots that signal a clear attacking intent made up a larger share of his total shots in his peak year. The sweep, slog sweep, reverse sweep, paddle sweep, slog shot and pull usually have higher strike rates against spin and in 2024, his good year against spin, Stubbs played them more frequently.

This is further evidence that his slow scoring is more a choice than bad form.

When Stubbs dropped a blockbuster 54/190.90 season in IPL 2024, it was the stuff of dreams. He got the cricketing world excited and fans expected him to be the next big thing. Two years later, he’s only left them disappointed. Nobody calls him Baby AB anymore. He’s neither AB nor a baby. But he’s still Stubbs, the man who sold us dreams back in 2024 with his immense talent. He chose to be a different player but those skills are still there. Whether the Stubbs of our dreams comes back is now entirely up to him.

All stats presented in this article are accurate as of August 11, 2026.

Stats & Data credit: Adithya Balagoni (@TechRadar9 on Twitter) and Himanish Ganjoo

A career that has been marred by injuries yet every time Archer makes a comeback, the hype is real. Back in 2018, ECB brought in changes to their eligibility rules which enabled England to pick Archer for the 2019 World Cup. The hype around Archer would make you think he should be in the company of the Bumrahs, Cummins and Rabadas of the world but when you look at his numbers, he sits among all rounders and imperfect bowlers. Among the 38 seamers who have taken more than 50 wickets since his Test debut, Archer has the 11th-worst bowling average.

This is not to fault those who hype him. He obviously has the skills and anyone who has watched him bowl can attest that the hype around him is justified. He averaged 22.81 even in the recently concluded series vs New Zealand. But this is only the second time he has averaged below 25 in a Test series, the first being his famous debut series.

One striking revelation from his stats is that he has an excellent average against left-handed batters while seemingly struggling against right-handers. Not only does this deviate from the global trend – where right-arm seamers typically fare better against right-handers – but the difference is also significant.

His economy is fine against right-handers but his lack of wicket-taking is what inflates his average. There’s a sense that Archer’s lengths are too short and that isn’t ideal for wicket-taking. Data does support that he bowls shorter more often than others.

But you would be wrong if you think these shorter lengths are what is holding him back. His good length deliveries perform massively worse than those of an average right-arm seamer when bowling to right-handed batters.

Breaking it down further makes it more interesting. The good-length outside-off delivery, which is the most effective line-length combination for a right-arm seamer vs right-handed batters with an average of 14.77, performs almost 2.5 times worse for Archer in terms of balls per wicket. But when he bowls his good length deliveries on a stump line, his balls per wicket is noticeably better than the global average.

The lack of wickets from outside-off deliveries is likely because Archer is not primarily an outswing bowler and hence challenges the outside edge less than a typical right-arm seamer. Similarly the inward movement he gets could make his stump-line deliveries more threatening. This is reflected in the fact that an overwhelming majority of Archer’s wickets off a good length are bowled or LBW.

This stump-line advantage disappears when he bowls short of a length because stump-line deliveries from that length would either bounce above the stumps or move too much and miss the leg stump. This is borne out by the fact that Archer has picked only one wicket from 208 short of a length stump-line balls bowled to right-handers. Meanwhile, because the outswinger is less threatening from this length, his balls per wicket ratio from outside off deliveries is comparable to the average right-arm seamer.

But what about the short-pitched deliveries? Surely this has to be a strength for Archer, right?

Glenn Phillips lay still on the Oval surface for a few seconds before tilting his sunglasses-shaded head forward and giving a thumbs up. He had fallen on his back trying to sway away from an Archer bouncer. It was an intense duel where Archer kept delivering bouncer after bouncer, flooring Phillips multiple times in the process. The article started with a description of how Archer floored Smith and Labuschagne with his bouncers, so it’s natural to assume that his short balls are his strength.

Data shows that Archer’s short-pitched deliveries have a worse average than those of an average right-arm seamer, but only marginally. Look closer and you’ll see that the heavy lifting is done by his economy while his wicket-taking threat lags significantly behind.

Archer hit and floored Phillips multiple times at the Oval but didn’t get him out in that innings. Archer hit Labuschagne on the helmet with the first legal ball he bowled to him but didn’t get him out in that innings. Archer hit Smith’s head so hard that he suffered a concussion but he has never dismissed Smith in Test cricket.

Somehow Archer’s bouncers are good enough to floor even the best batters, yet they can’t buy him wickets. It seems counterintuitive, given that he possesses one of the most lethal bouncers in the game. But before you doubt the data, let me tell you that data also has some evidence for this.

When right-handed batters play the pull shot to Archer’s short balls, he picks up a wicket every 10.17 balls - twice as frequently as a typical right-arm seamer (20.41). But here’s the catch: 30.90% of short-pitched deliveries from right-arm seamers are pulled by right-handers while against Archer, the pull shot is played to less than half that proportion (12.73%).

Also, the proportion of leaves off Archer’s short balls is well above that of an average right-arm seamer. The steep bounce he generates, while threatening, may actually be counterproductive. It could be making it easier for batters to decide to duck or sway rather than forcing indecision.

This pattern is consistent against left-handers too.

But what’s different against left-handers is that short length is the only length that doesn’t work.

As with right-handers, the stump line is Archer’s most productive line against left-handers as well. The dynamic here is that when he bowls from round the wicket, which accounts for 80.57% of his deliveries to left-handers, he keeps all modes of dismissal in play by angling the ball in and using his ability to move it away.

But the key difference here is that the outside off deliveries don’t undo the good work done by the stump line deliveries. Although they are still worse than those of an average right-arm seamer, the difference isn’t as pronounced as it was against right-handers. The away movement likely helps.

That said, Archer did average 21.8 vs right-handers in the recent series against New Zealand - almost two runs better than his average against left-handers (23.67). But it’s also important to note that the heavy lifting was done by short and full lengths, which is not sustainable. The staple good and short of a good length deliveries were still found wanting. He got only one wicket off 79 short of a good length deliveries and no wickets from good length.

Although Archer has an outstanding record against left-handers, he has to bowl the majority of his deliveries to right-handers. It’s fascinating how Archer’s ability to move the ball inwards and to extract steep bounce, which are supposed to be his USPs, is what hurts his Test credentials. Cricket does tend to behave in such mysterious ways. Regardless, Archer’s immense ability is undeniable and his Test numbers could still get better. But for now, where are Jofra’s Test wickets? Well, they’ve been consumed by his own strengths.

All stats presented in this article are accurate as of June 30, 2026.

Stats & Data credit: Adithya Balagoni (@TechRadar9 on Twitter) and Himanish Ganjoo, Statsguru, Cricmetric

Ever since pairing Bhuvneshwar and Hazlewood together, RCB have been on an upward curve. Critics are praising them for structuring their team around maximising powerplay impact which is a strong factor for success in T20 cricket. But while that holds generally, this really has been a one-off game for Hazlewood, who has otherwise had his worst IPL season. Bhuvneshwar, meanwhile, is enjoying a late-career renaissance after two middling seasons in the IPL.

Bhuvi has had more economical seasons in the past, but IPL has entered a different era since 2024 and we have to recalibrate how we look at stats. After going over 9 in 2024 and 2025, his economy rate has dropped to 8 in 2026, which puts him in an elite category (second best for a seamer this season) in this new age of T20 cricket. Another notable aspect is his improved wicket-taking.

Hazlewood, on the other hand, had his worst IPL season in terms of both economy and balls per wicket (excluding 2020 where he played just 3 games). Having missed the 2024 season, he had played only one season prior to this in the post-2024 run boom era. But his economy rate had been rising and it has tipped above 9 for the first time this season.

A closer look at the phase-wise stats shows that powerplay has been the most damaging phase. In fact, he has actually gotten better in the back half of the innings. But in the powerplay phase, where he’s supposed to be the most impactful, he has lost his effectiveness.

Bhuvi’s phase-wise numbers show across-the-board improvement. He has always been a low-usage middle overs bowler but both his economy and wicket-taking ability have shown noticeable improvement in the powerplay and the death.

There is a slight increase in the percentage of good length deliveries Bhuvi bowls in the powerplay.

But we cannot attribute his improved numbers entirely to that. His numbers have improved across all lengths, not just on good length balls. The improvement in balls per wicket across lengths is particularly impressive.

And what did Hazlewood do in the powerplay?

Surprise, surprise! He’s also bowling a higher percentage of good length deliveries. In fact even more heavily than Bhuvi, while moving away from his staple hard length.

You might think moving away from his trademark hard length was the mistake. Surprise again, the good length was actually his most productive length last year. This year, both good and hard lengths, which used to be his strong zones, have failed to deliver.

Both have increased the proportion of good length deliveries they are bowling in the powerplay. While Bhuvi’s numbers have improved across lengths, Hazlewood’s numbers have gotten worse. More notably, there’s a significant drop in Bhuvi’s balls per wicket when hitting the dominant good and hard lengths while there’s a significant rise in Hazlewood’s balls per wicket for those lengths. It is remarkable how essentially the same adjustment has resulted in two diametrically opposite outcomes for each.

Maybe Hazlewood has been more wayward, missing his lines more often?

There definitely is a decrease in the proportion of balls pitching on a stump line and an increase in wider lines. So there is some merit to this argument. But all that merit falls flat when you discover that the wider lines have been more rewarding for him and the tighter lines have failed him.

Maybe the swing king is swinging the new ball more? And Hazlewood is not known to be a big swinger of the ball. That could explain the contrasting outcomes right?

Fair point, Bhuvi has indeed got more balls swinging big while Hazlewood hasn’t.

But come on, what even is the point of continuing in this article if there aren’t any more surprises? While Bhuvi is swinging the ball more, those swinging deliveries haven’t been the primary drivers of his success. His most productive balls have been the ones swinging less than 0.5 degrees, where there is no noticeable swing. Basically the balls which are not swinging have been the heaviest contributors to his success.

While not the major contributors, the big swinging balls are still yielding good results for Bhuvi. For Hazlewood, however, even on the rare occasions where he gets the ball to swing, those balls haven’t fetched him any wickets and are travelling at an absurd economy rate.

To summarise: Bhuvi’s big-swinging balls are performing normally while his non-swinging balls are giving him extraordinarily good results. Hazlewood’s non-swinging balls are performing normally but his big-swinging ones are giving him extraordinarily bad results.

As with swing, Bhuvi is getting more balls to seam big than Hazlewood. And as one would expect, the seaming balls are bringing Bhuvi better returns. But for Hazlewood - you can probably guess the pattern by now - non-seaming deliveries are going for more runs and seaming deliveries are not fetching him wickets.

The pace at which they are bowling also follows a similar pattern to their lengths. Both have increased their pace. As has been the norm in this article, all speeds work for Bhuvi while for Hazlewood only 140+ kph balls are proving effective. The 135-140 kph speed band, which used to be Hazlewood’s best in 2025, is now travelling at an economy rate 2.5 times as high.

One remarkable finding is how a bowler has been able to maintain a low economy rate across every length, line, speed and degree of movement, all while operating with just two fielders outside the circle and when the scoring rates are at an all-time high. One possible explanation is that his high wicket-taking ability is feeding into that economy.

As Bhuvi takes more wickets, he gets to bowl more at new batters. 68.75% of his powerplay deliveries were bowled to batters who had faced five balls or fewer. These new batters score at a slower rate than settled ones and since he has also been dismissing them more often, he gets to bowl even more to these slow-scoring batters.

Interestingly, this dynamic didn’t work out for Hazlewood even though he’s the one bowling from the other end. He has bowled 30% fewer deliveries to these fresh batters than his opening partner. You could make a case that he doesn’t help himself by not dismissing them as often enough when he gets the chance to bowl to them. Perhaps it’s in Hazlewood’s overs that these batters are crossing the 5-ball mark.

So the high wicket-taking threat could possibly explain Bhuvi’s improved economy but we still don’t have an explanation for the wicket-taking threat itself.

Fortunately, the secret to Bhuvi’s death-overs improvement is less hazy. A standout feature is how he has been able to nail his yorkers this season. But quantifying that with data makes it look even more impressive.

There has been a significant shift in his death bowling strategy. He has gone more yorker-heavy while abandoning the good and hard lengths at the death.

But a yorker-heavy approach is not new to T20 cricket. What’s rare is executing them consistently and that’s where Bhuvi shines. Counting full tosses and half volleys as missed yorkers, Bhuvi’s yorker success rate is a striking 49.09%.

To put this into perspective, the yorker success rate at the death for all seamers is 32.69% in the IPL since 2022. Anything above 40% is considered elite and Bhuvi’s figure ranks second best this season, only behind yorker-specialist Natarajan.

It gets more impressive when you consider that when he errs, he errs on the shorter side more often than full. Surprisingly, the half volley has consistently been the second most economical length at the death while the full toss has been the second worst in the IPL since 2022. So he has ensured that even when he misses his yorkers, he concedes fewer runs.

But again, this alone cannot explain his success at the death because all lengths have fared better than in previous years.

But unlike the powerplay numbers, there is an explanation here. This could possibly be tied back to his powerplay wicket-taking. As he helps his team pick more wickets in the powerplay, he gets to bowl more often to less accomplished batters at the death. Over 30% of his deliveries at the death were bowled to bowlers and bowling all-rounders, a stark contrast to the previous two years where he didn’t bowl even half as many such deliveries.

This logic might also explain Hazlewood’s improved death numbers. Bhuvi’s powerplay wickets explain a lot of things we’ve looked at in this article. But as mentioned earlier, we still don’t have an explanation for Bhuvi’s powerplay wickets. Or for Hazlewood’s lack of powerplay wickets for that matter.

At least Hazlewood has been drawing less false shots than in previous seasons but Bhuvi hasn’t even been drawing more false shots.

Remember Hazlewood’s one-off game we talked about in the beginning of the article? You know what he did differently that day compared to the rest of his season? He bowled a lower percentage of deliveries in his most economical length (good length) and a significantly higher percentage of deliveries in his most expensive length (full length).

T20 cricket has the tendency to troll you like that. You can’t even make the argument that he should’ve just stuck to what worked for him that day.

It is fascinating how the wicket-taking threat of a bowler in the powerplay dominoes into so many things. It’s equally fascinating how another bowler has become less of a wicket-taking threat while making similar changes to his methods. Both Bhuvi and Hazlewood have been bowling a higher proportion of their balls on a good length and both have been bowling at an increased pace. But one has started taking more wickets in the powerplay at a reduced economy while the other is taking fewer wickets at an increased economy. The tale of these two RCB bowlers reveals the inherent idiosyncrasies within cricket. This chaos is what keeps T20 alive. This chaos is what keeps cricket alive.

All stats presented in this article are accurate as of May 28, 2026.

Stats & Data credit: ESPN Cricinfo, Cricmetric, iplt20.com, Adithya Balagoni (@TechRadar9 on Twitter) and Himanish Ganjoo

I expected this to be the season where Sunil Narine would finally be taken down by batters and his stock would start falling. My rationale was simple: he’s aging, the margin for error has been consistently shrinking for spinners and T20 batting standards are at an all-time high. I couldn’t have been more wrong about Narine though.

Narine’s T20 record has always felt like an aberration. Although he isn’t as much of a wicket-taker as he was in the early part of his career, his economy rate consistently remained elite. There has been only one year where his T20 economy rate went above 7 and even then, it didn’t cross 7.5. Even in the IPL, the toughest T20 league, his economy never touched 8 in any season.

T20 has evolved a lot since the start of his career. Strategies changed, power hitting evolved, phase specialists emerged, quick spinners took over, analytics advanced, batting went through another stage of evolution and bowlers are now left with little margin for error. Even Rashid Khan, who took the T20 world by storm and emerged as the world’s best spinner, couldn’t escape the tide. But Narine keeps going.

What’s remarkable is that his economy rate holds up across all phases.

Yes, his powerplay and death economy rates have crossed 8 in recent years but that’s simply an effect of batters levelling up. He’s still better than other spinners.

Among spinners who have bowled at least 15 overs at the death in the IPL, Narine has the best economy rate. It would be safe to say that Narine is the best-ever defensive spinner in T20 cricket. That is reflected in how teams are willing to bowl him at the death and in super overs. He maintains his exceptional record after bowling 127 overs at the death while no other spinner has bowled even half that many. We often see newer cricket stats enthusiasts bringing up the fact that spinners have better death over records. Narine’s contribution to that record is significant.

Modern day T20 cricket has made the equation simple for spinners. Simple, for us viewers, but difficult for the spinners themselves. One non-negotiable to maintain a good economy rate is to land the ball in the 5 to 7 metre length. The defensive-good-length and short-of-good-length are the only two lengths where spinners aren’t travelling.

Maintaining such a high level of accuracy is not easy but Narine has been doing it for years. His length distribution curve looks exceptional and shows how incredibly consistent he has been at landing the ball on those defensive lengths.

Since 2022, at least 65% of Narine’s deliveries have landed in the defensive-good-length or short-of-good-length zones every IPL season. Even when he misses those lengths, he predominantly hits the next-best length - the attacking-good-length, which is also optimal for wicket taking. Only in the 2024 season did more than 20% of his deliveries land outside the good and short-of-good-length zones.

His elite accuracy isn’t just limited to the lengths he bowls. His line distribution curve shows how consistently tight his lines are.

Consistency is not the only thing Narine excels at. He can also turn to variations when needed. Although Narine isn’t a big turner of the ball, it’s well known that he can turn the ball both ways.

The ability to turn the ball both ways has become a vital weapon for spinners in T20 cricket. A smart enough spinner can use that ability to be unpredictable. 91.86% of Narine’s overs contained balls turning both ways - fifth highest for a spinner in the IPL since 2022.

But this metric isn’t perfect. What if he bowls five balls turning one way and only one the other way? He’d still be fairly predictable right?

Entropy is a measure that can be used to capture how well a spinner mixes up his turn directions. It measures how evenly spread out the turn directions are in an over. A bowler who turns only one ball in a different direction will have low entropy. A bowler who turns three balls one way and three the other will have high entropy. Narine is among the best by this metric too.

Further evidence of his unpredictability is how frequently he varies his turn direction between deliveries. Change frequency measures how often the bowler changes direction from one ball to the next within an over. A higher value indicates better mixing.

The variations don’t end with turn directions. Narine is also good at varying his pace.

Narine has bowled at least 20% of his balls in three different speed buckets in three of the last five IPL seasons (2022, 2023, and 2026). Apart from him, only two other spinners have achieved this - Rashid Khan and Axar Patel.

Narine doesn’t just vary his revs and release speed, he also varies his release point. When bowling from over the wicket, his release lines span a wide range.

Coefficient of variation quantifies how much a bowler’s release point typically deviates from his mean release point. Narine has the highest coefficient of variation among all spinners when bowling from the left side of the stumps.

Another metric where Narine shines is the bounce angle ratio, which I touched on in my previous article (I’m not explaining it, go read the full article hehe). Narine has the lowest bounce angle ratio among spinners in the IPL.

This matters because a lower bounce angle ratio correlates with a lower economy.

All of this points to how much of a master craftsman Narine is. Some bowlers excel at consistency. Some bowlers excel at variations. Narine is consistent in the attributes that reward consistency and varied in the attributes that reward variation. And he’s among the best in each.

Having said all that, I cannot conclude this article without talking about the elephant in the room - his action.

Narine’s bowling action has been a subject of controversy for a long time now. He has been reported for illegal action in the past and has even remodelled his action multiple times, yet the doubts still persist among the masses. While I have my own opinions, I feel it wouldn’t be fair to take any side without presenting data and evidence to support my stance. But the disregard of this matter by those who have the data has been intriguing.

Like how quickly the MCC jumps in with an explanation every time there’s a controversy surrounding the laws of the game, it shouldn’t be too difficult for the administrators to provide evidence and settle the debate, whichever way the evidence points. It would be a shame if a career as extraordinary as Narine’s is always remembered with an asterisk. But regardless of where you stand, you cannot deny how incredibly skillful Narine is. Legal or illegal, nobody else could replicate what he has done over a long career. The air will clear at some point. Until then, Sunil Narine is a T20 legend. Sunil Narine is the IPL MVP.

All stats presented in this article are accurate as of May 14, 2026.

Stats & Data credit: Statsguru, Cricmetric, iplt20.com, Adithya Balagoni (@TechRadar9 on Twitter) and Himanish Ganjoo

This is the dipping Ngidi cutter that has been flummoxing batters for a while now. Ngidi is a slow ball merchant. 55.41% of his deliveries in IPL 2026 have been clocked below 128 kph. But is that enough to call him a slow ball merchant?

The term has had an interesting journey in T20 cricket. Initially it was used for a niche variety of seamers who were slow ball specialists, using the slower delivery as a weapon. Later it took on a derogatory connotation when some bowlers started overusing it to the point where it was no longer a weapon and became easy for batters to hit. Still, the tag belonged to only a small subset of bowlers.

Today, T20 cricket has entered a different age. Plotting the pace distributions of seamers and identifying those with a bimodal graph was a thing a few years ago. Now we live in a bimodal world. All seamers in the IPL have a bimodal pace distribution curve. It’s no longer a specialist skill, every seamer bowls a slower delivery. So how do you define a slow ball merchant these days?

I’ll leave that part to you because all these semantics don’t really matter. What matters in today’s T20 world is how effective your slower ball is.

Slower balls are interesting. Although the unpredictability of a slower ball can surprise batters, it remains effective only as long as it is unpredictable. If the batter knows it’s coming, it’s just another ball with an added advantage of more time to react.

Data shows that the slower you bowl, the higher the scoring rate.

In an increasingly fast-scoring T20 era, effective bowlers are those who can deliver a slower ball yet still manage to keep the run rate in check.

For this analysis, we’ll define a slower ball as any delivery bowled by a seamer at less than 128 kph*.

In IPL 2026, five bowlers have an economy rate below 9 while bowling slower balls: Eshan Malinga, Jasprit Bumrah, Mohsin Khan, Lungi Ngidi and Marco Jansen.

Unlike other strategies, there’s no optimal way to execute a slower ball. You can really customize it to your strengths and still be effective. The fascinating part is how diverse the characteristics of slower balls are, even among its best exponents.

A quick look at the balls per wicket of these five bowlers shows how their slower balls provide varying levels of wicket-taking threat.

The dipping Ngidi cutter is what we started the article with. But he’s the odd one out here. None of the other four bowlers have needed any dip for their slower balls to be effective.

Dip has a negligible effect on economy rate but slower balls with higher dip pose a greater wicket-taking threat. That could explain why Ngidi’s slower balls have a good balls per wicket ratio, even though his economy rate is not as low as some of the others.

It might surprise you that Ngidi doesn’t get the highest dip among all seamers but it’s important to note that the ones ahead of him bowl a back-of-the-hand slower ball, which dips naturally due to forward spin. Ngidi achieves his high dip with an off cutter. Whatever the dip value may be, the surprise element is what troubles batters. A back-of-the-hand slower ball can be picked easily and batters know what trajectory to expect but they aren’t trained to expect that amount of dip from an off cutter.

This is clearly reflected in how his slower balls draw the highest percentage of false shots.

Mohsin Khan also ranks higher in this list, which explains his staggering numbers.

Another area where Ngidi is attacking is in his lengths.

Ngidi is the only one among these five who bowls a higher percentage of his slower balls at fullish lengths.

Slower balls, when bowled fuller, tend to be more expensive but increase the wicket-taking threat as well - a characteristic reflected in Ngidi’s numbers.

On the other hand, Eshan Malinga and Bumrah opt for a more defensive shorter lengths when bowling slower. This explains their lower economy rates.

Mohsin and Jansen are interesting in that they don’t have an exclusive length for their slower balls. The length distribution is similar to their stock balls, so there’s no unique characteristic.

The similarity between the two doesn’t end there. The two tall left-armers also don’t get much grip on their slower balls.

Consequently, they don’t get much turn. Though Mohsin appears slightly better in this regard, he’s still below average.

They fail to extract movement not just off the pitch but also in the air.

By this point, you would have already noticed Eshan Malinga topping these lists. While he was roughly average for dip and false shots drawn, deviation is his forte. He has been a master at extracting movement - both off the pitch and in the air.

Higher grip is associated with a higher wicket-taking threat and higher drift is associated with a better economy - Eshan gets the best of both worlds. Hence the elite economy rate and balls per wicket on his slower balls.

In contrast, Mohsin and Jansen’s lower drift should give them a higher economy and a greater wicket-taking threat. But then the lower grip should balance out that wicket-taking ability. This is visible in Jansen’s record. Mohsin perhaps benefits from being slightly better than Jansen in most metrics and from his insanely disciplined line and length, as his pitch map showed.

Mohsin has the most tightly grouped pitch map of the five. A probability density curve of lengths shows how he’s just been hitting the good and hard lengths like a robot. It’s also amazing how his lines are so tight that he doesn’t even need to change them while bowling to different handed batters.

Jansen is an interesting case though. He ranks among the lowest in almost every metric we considered and doesn’t have any of the generally desired characteristics in his slower balls - doesn’t get dip, draws less false shots, doesn’t get grip, doesn’t move the ball in the air or off the pitch. He doesn’t have a dominant length for his slower balls either, which could have maximised either his economy or his balls per wicket.

But if there’s one metric where he shines, it’s the bounce he gets (you might have expected this) - or the lack of it (I bet you didn’t expect this).

For measuring bounce, we use the ratio between the ball’s angle with the ground after pitching and its angle before pitching. A higher ratio means the ball left the ground at a steeper angle, a lower ratio means a shallower angle.

Data shows that shallower bounce is associated with lower economy while steeper bounce is associated with lower balls per wicket.

Jansen, with the lowest bounce ratio on his slower balls, possibly gets his lower economy rate from here. This should also introduce a surprise element to batters who wouldn’t expect such low bounce from a tall bowler, which could further improve his numbers.

There’s still one bowler we haven’t extensively talked about. Perhaps he’s the one who everyone wants to talk about. Jasprit Bumrah, who is considered an outlier in every sense, is not an outlier in any of the metrics we considered, which in turn made him an outlier in terms of his overall numbers. How poetic!

Bumrah has the weirdest balls per wicket among the five. If you’ve been paying close attention, you would have noticed that he’s about average in everything. He hasn’t got enough dip this season, bowls a defensive length with his slower balls, doesn’t draw enough false shots, doesn’t get enough grip or turn and doesn’t get steep bounce - all of which could have given him a better wicket-taking threat if he possessed them. The only metric where he’s considerably above average is the drift he gets, which also doesn’t help with wicket taking.

An even closer look at the graphs reveals that he’s been below average in metrics where being above average increases your wicket-taking threat. And he’s been above average in metrics where being below average increases your wicket-taking threat. Crazy stuff. No wonder his numbers are crazy too.

In an era where bowlers come up with all sorts of fancy slower ball variations, the ones with the five best economy rates are those who use the most basic version of slower ball variation - the off cutter - as their primary slower ball. Jansen does have a knuckle ball but it is ironic that he manages to release even that as a cutter. You can have all varieties of slower balls but in the end, if you are skilful enough you can be effective even with the most basic version. It doesn’t matter if your definition of slow ball merchants includes them, but they are the ones who really matter because they are the ones who are really effective.

*David Payne, Sandeep Sharma and Shashank Singh were excluded from the analysis their stock balls themselves were already below 128 kph.

All stats presented in this article are accurate as of April 26, 2026.

Data credit: iplt20.com

This is the kind of doom theory that dominated every field in the wake of the AI revolution. But in cricket, AI is nowhere near. Hailing Chahal’s extreme pace, calling Unadkat a T20 specialist and referring to CSK-RCB rivalry with a ‘famous’ moniker that no living being on Earth uses - that’s all AI has managed to do so far in cricket.

But on April 1, 2026, in the middle of an IPL match, Google Gemini touched upon an interesting subject: left-right combos.

This is particularly interesting because this is a question the cricket analyst community has gone back and forth on. Once seen as a must-have ingredient in T20s, and even adopted by teams to the point of overusing it, there has been a pushback in recent times from a section of that same analyst community claiming it offers no real advantage.

For a strategy that has had differing opinions on it, what really is the truth? Do left-right partnerships actually offer an advantage? Is Gemini right in supporting it?

SPOILER - Gemini is right. I might already be losing fans with my support for AI slop but stay with me. This is going to be a nuanced cricket conversation and this is not Gemini prop. Gemini is still crap for the most part (Note to Sundar Pichai: I’ll edit this part out once my account shows the deposit).

A quick look at the surface level stats shows left-right partnerships to be better across formats.

Case closed. End of debate. Thanks for coming!

But if you are a naysayer, you probably aren’t convinced yet. You may say overall surface level stats lack nuance. If we dig deeper, it might tell a different story. After all, with the special treatment left-right partnerships receive from teams, perhaps they are always set up to succeed and these overall stats are just a reflection of that?

Fair. Let’s run some endurance tests to see how it holds up.

Let’s break these numbers down further and see how different partnership types perform against each bowling type.

Left-right partnerships still look better than others even when we break down by bowling types. The only matchup where any other partnership type is at a comparable level is right-right partnerships vs off spin in ODIs and Tests, which it should absolutely be. The more interesting finding is that left-right partnerships outperform even 100% positively matched up partnerships.

In fact, as a fun aside, left-right partnerships outperform others even against mixture spinners - Sunil Narine, Mujeeb Ur Rahman, Maheesh Theekshana, Varun Chakravarthy, Usman Tariq.

Maybe you still aren’t convinced. Maybe you think this only further proves that left-right partnerships receive special treatment. You may argue special treatment doesn’t just mean making left-right partnerships face the bowling types they desire, rather it’s a larger structural advantage that makes them succeed against all bowling types.

You would say left-right combos benefit from the fact that they don’t naturally occur among tailenders and they are only manufactured in top-order partnerships. Same-handed partnership numbers might be pulled down by less accomplished batters.

Ok, let’s apply a minimum balls filter that would reasonably exclude most tailenders and recalculate these numbers.

And the trend still holds. And it holds against different bowling types too. I won’t tire you now with all those graphs here because there’s more coming!

You may still think T20 numbers are corrupted. There are a lot of T20s played among lower rung sides and you don’t expect those teams to be using advanced analytics. Those lower quality leagues may be affecting the stats of naturally occurring same-handed partnerships.

Let’s settle this too by considering only T20Is involving top 10 teams (Afg, Aus, Ban, Eng, Ind, NZ, Pak, SA, SL, WI) and T20s played in top leagues (BBL, CPL, IPL, Hundred, PSL, SA20).

Surprise surprise! The trend still holds.

This should be enough to show that left-right partnerships have consistently better numbers across formats. But you still may not want to adopt it. You might think the gap is not big enough to matter and a tinge of randomness is sufficient to bridge it on enough occasions.

So far, we’ve run endurance tests to establish that left-right advantage holds under varied circumstances. You know what we are gonna do next? We are going to find out what’s actually holding them back.

The special treatment that left-right partnerships receive is real, especially in T20s. Teams go out of their way to pair up a left and right hander to the extent of influencing selections and batting order decisions. Teams are not hesitant to even demote an obvious top quality batter just to maintain the left-right combo at the crease. What if this special treatment is not all that advantageous?

The graph above shows the percentage of partnerships where at least one batter was low quality. For this exercise, any batter who averaged below 25 or had a strike rate of below 130 in the prior two years was considered low quality. For a cleaner sample space, only batters who faced at least 100 balls in each two year period were considered. Due to data availability constraints, data from 2017 onwards was used.

Although the difference isn’t huge, it can be seen that left-right combos are more likely to include low quality batters. The urge to pair left and right handed batters at all times leads teams to compromise on quality. All that special treatment is not benefitting left-right combos, in fact it’s only been detrimental to them.

The important takeaway here is that left-right partnerships have better numbers despite having more low quality partnerships. One would only expect those numbers to improve further if teams use them more diligently.

You know what else is holding them back?

Strike rotation.

The traditional argument for left-right partnerships was simple - they force bowlers to constantly adjust their lines. Pair a left and right hander, rotate the strike heavily and the bowler has to reset almost every ball. But that’s not why left-right partnerships are being widely adopted by teams in recent years.

While forcing the bowler to adjust to different handed batters does offer an advantage, it can’t be huge. It is heavily dependent on the bowler’s control. You wouldn’t expect a bowler with elite control to stray too much just because the batter at the crease has changed. The target spot moves, their control does not.

When left-right combos became vogue in the wake of the T20 revolution, they were primarily seen as a way to counter matchups. Specifically against spin, they prevented bowling teams from spamming a negatively matched-up bowler and ensured there was always a batter in the middle with a positive matchup. This taps into the universal, inherent advantage batters have when facing in-spin and it doesn’t depend on external factors.

When you know facing in-spin offers you an advantage, what do you do?

For left-right partnerships that faced at least 10 spin deliveries, a clear trend emerges: strike rate rises with the percentage of in-spin balls faced. Pairing a left and right hander is only half the job, the batters must also ensure they actually face more in-spin.

So the way to realise the advantage offered by left-right partnerships is not by rotating the strike more. Rather, the actual way to maximise it is by strategically not rotating strike and letting the advantaged batter face the entire over against a positively matched up bowler.

Cricket isn’t there yet. Moises Henriques revealed it took a couple of days for Babar Azam to get over it when Steve Smith denied him a single in a BBL game. Conventional cricketers still take it as an insult when they are denied strike.

77.94% of left-right partnerships in our analysis had faced less than 60% of in-spin deliveries. But remember, left-right partnerships still outperform same-handed partnerships despite this taboo. Imagine how much the gap would widen if teams unlocked their full potential.

The last two trends we discussed don’t quite hold for ODIs and Tests. And that’s understandable considering how survival takes precedence in the longer formats and the ball turning away is less of a concern when you’re not chasing quick runs. But it’s important to note that even in those formats, left-right partnerships do offer an advantage as the overall stats showed.

In fact, the overall average of left-right partnerships keeps increasing with the percentage of in-spin balls faced until the 60% mark in Tests and ODIs too. This indicates that even in formats where survival is key, it’s not desirable for batters to only face away-spin. Manipulating strike to keep the advantaged batter on strike still has merit to a certain extent.

Perhaps this is what I should’ve shown first. If facing in-spin is always better than facing away-spin, why would left-right partnerships, which can ensure more of that, not be beneficial?

Left-right combos certainly offer an advantage. But we also see teams overusing it. They are neither irrelevant nor are the only relevant stuff. We need to have a more nuanced look at them. It’s up to the teams now to do due diligence and use them in a way that would benefit them. The more interesting findings that could spark further discussions are why left-right partnerships are better than same-handed partnerships against 100% positively matched up bowling types and against pace. But for now, Gemini was right. That left-right combo is not really shite.

All stats presented in this article are accurate as of April 1, 2026.

Stats credit: Adithya Balagoni (@TechRadar9 on Twitter) and Himanish Ganjoo

Thanks to @Flighted_Leggie for the conversations around this topic. One such conversation birthed this article.

Abhishek Sharma is no conventionalist and he went on to destroy Rashid’s bowling for the rest of the series. He faced 25 balls of Rashid and scored at a strike rate of 248, shattering any notion of a mental edge.

By now it’s common knowledge that Abhishek specializes in destroying spinners. He is comfortably ahead of the rest of the world when it comes to spin hitting.

While spin matchups are almost irrelevant when you are bowling to such a spin monster, Abhishek ascends to a different dimension when he’s up against his positive matchup.

Jarrod Kimber believes that a strike rate of 240 is the ceiling at which a T20 batter can consistently score. He bases this on the strike rate batters achieve against a free hit. That’s the level Abhishek operates at. In essence, he bats as if every ball is a free hit when he faces bowlers who spin the ball into him.

There is no length, line, speed, or amount of turn that he cannot attack.

‘Anchors’ are fast becoming a concept of the past in T20s but middle overs slowdown can still be a problem for many teams. It intuitively makes sense that a batter cannot score at the same rate against a spread-out field as they can under the powerplay’s fielding restrictions.

But as we established earlier, Abhishek Sharma is no conventionalist. Interestingly, despite his rise as an explosive opener, he has a higher strike rate in the middle overs (216.09) than in the powerplay (180.82) and is the best middle overs batter in the game.

Of course it’s natural for a spin monster to dominate the middle overs you’d think.

Stacking the middle order with spin hitters is a strategy teams adopted as T20 cricket revolutionized. The counter that bowling teams employed was the introduction of middle overs enforcers. Since most of these spin-hitters were easily contained by pace, the damage was reduced. So bowling pace in the middle overs should keep Abhishek quiet, right?...RIGHT?

Well, Abhishek is no conventionalist. Here’s the twist - in the middle overs, he is even more effective against pace (83.67 avg, 212.71 SR) than against spin (34.78 avg, 218.88 SR), placing him in a tier of his own as a pace-hitter.

After all, he would never be batting in the powerplay as an opener if he wasn’t good against pace. And that brings us to one of the least surprising aspects about Abhishek, that he’s one of the most explosive powerplay batters out there. He’s one of only two batters to have a strike rate above 180 in the powerplay (min. 250 balls).

He also has carved out a reputation for scoring boundaries from the very first ball. His first 10 ball strike rate of 172.65 is the second best in T20s (Fun fact: No.1 is a certain 44-year-old strawberry farmer who plays cricket as a pastime during his 2-month off-season). In a list dominated by lower order hitters, Abhishek firmly stands out at the top.

The way we’ve been talking about his hitting skills so far, I wouldn’t blame you if you thought he was the newest T20 power hitter in town. The kind that personified the early West Indies dynasties. The kind who swing for the hills every ball. However when that swing misses, these batters unfortunately run the risk of dotting up. These archetypal power hitters often struggle to rotate the strike.

Well, by now you should know what’s coming - of course Abhishek is no conventionalist. What if I told you he’s also one of the top strike rotators in the game? He ranks among the best in dot ball percentage - in the powerplay, in the middle overs and against in-spin.

The ability to rotate strike also implies that Abhishek isn’t the prototypical power hitter who strikes at 180+ but averages in the 20s. Abhishek maintains a healthy average above 30 - against both pace and spin, and in both the powerplay and middle overs.

The concoction of all these supernatural skills means Abhishek is in a league of his own as an overall T20 batter.

Abhishek isn’t your typical spin hitter, he can smash pace too. Abhishek isn’t your typical powerplay batter, he’s a dominant middle overs bat too. Abhishek isn’t your typical power hitter, he’s a proficient strike-rotator too. Abhishek is no conventionalist. Abhi loves to shake things up a little.

All stats are from T20Is involving full member nations and from matches in top franchise T20 leagues (IPL, SA20, PSL, Hundred, MLC, BBL, CPL, ILT20, BBL) since 2023.

All stats presented in this article are accurate as of October 2, 2025.

Stats credit: Cricmetric, iplt20.com, bcci.tv, Adithya Balagoni (@TechRadar9 on Twitter)

Prasidh Krishna has been around for quite a while now. He made his First Class debut in 2015 and has always been highly rated by those who’ve watched him bowl but he has failed to deliver on the big stage. Not once in his IPL career has he finished a season with an economy rate below 8. Teams repeatedly splurged cash at auctions hoping he’d eventually arrive but he never arrived.

2022 was his best IPL season - the only time his economy dipped below 9. He primarily operated as a powerplay bowler in that season, bowling 54.3% of his deliveries in that phase. But it was also the only season where he had reasonable powerplay success.

Fast forward to 2025, Prasidh has become the quintessential middle overs enforcer for Gujarat Titans, bowling 58.06% of his overs in the middle overs phase. He’s terrorising batters with an economy rate of 7.29 and a wicket every 11.6 deliveries.

He could just be a better bowler now, does usage matter that much? Usage does seem to matter as his powerplay and death-over numbers haven’t shown any improvements compared to 2022. It’s the middle overs where he’s thrived. Had Gujarat Titans deployed him primarily in the powerplay again, his numbers might not have been this good.

In fact there’s evidence to suggest that he enjoys bowling in the middle overs more. Before his near-breakthorugh 2022 season, his middle-overs numbers in his first four years with Kolkata Knight Riders outperformed his returns in other phases. Even general cricketing logic would suggest his attributes are more suited to the middle overs.

But the key thing to be noticed is that he’s not just a decent middle overs bowler now, he has refined his niche relentlessly and turned into a middle overs monster now. Comparing his 2025 season to 2022 (the only other year with ball tracking data) gives us valuable insights.

HTD - this three letter abbreviation is now a popular meme on Cricket Twitter. Trace its origins and you'll arrive at Prasidh Krishna. Prasidh was always rated for his ability to hit the deck hard and his tall frame naturally complements that style. And this season, he’s hitting the deck harder than ever.

His approach now shows slight variations between overs 7-11 and 12-16, but the common thread is that he’s bowling significantly more hard length and short deliveries in the middle overs. While the hard length was effective for him even during 2022, he’s now having much better returns with it and the short ball - which reinforces the earlier point that he has refined his niche further.

The strategic shift to bowling 70%+ deliveries in the hard length and short length zones in overs 7 -11 has been essential given his struggles elsewhere. His non-hard/short deliveries went for 31 runs off just 10 balls in this phase. 12-16 is a rather interesting phase because he dominates across all lengths, with no single length conceding more than 6 runs per over.

One obvious factor for the increased success that immediately comes to mind is line control.

A look at his pitch maps suggest that his lines have been tighter, especially in the 7-11 overs phase. While his 12-16 over lines are a little spread out, he still maintains a higher percentage of balls pitching outside off than in 2022.

Over 75% of his deliveries now pitch in the outside off stump line which has always been a productive line for him. This also means that he’s pitching lesser balls in the wide outside off line where he conceded 13.33 RPO in 2022.

But we cannot put it all down to the improved line control, there are other changes in his game which could explain his enhanced success with the hard length this season.

A quick revisit to the pitch maps and you might notice that there are more green dots this year, especially in the 8-10 metre zone. His hard length balls have been much quicker this season.

Off the four hard length deliveries bowled above 140 kph in 2022, he conceded just one run. Now he has doubled down and more than half of his hard length deliveries in overs 7-11 exceed 140 kph. As mentioned earlier, he has adopted a slightly different approach in overs 12-16 but he still bowls nearly twice as many 140+ deliveries in this phase as compared to the middle overs in 2022.

Hard length effectiveness in 12-16 revolves around using pace variations as a weapon. When he’s not bowling at full tilt, his deliveries are kinda evenly distributed across speed ranges - a tactic reminiscent of Pathirana’s approach last season (Yes I’m bringing in an unrelated topic to shamelessly gain views for my earlier article). He lacked this variation in 2022.

Saliva has been a topic of discussion this IPL season. Probably not very hygienic of people to talk about someone else’s spit but the resurgence of reverse swing has made it a hot topic of discussion. Whether saliva has been responsible for the reverse swing or not, there’s no denying that reverse swing is back in business.

While you'd typically expect this to increase the effectiveness of fuller deliveries, such has been this season that even hard length deliveries are swinging enough to trouble the batters. Average swing Prasidh got off his hard length deliveries in the middle overs was 0.44° in 2022, which is effectively no movement. It has gone up to 0.63° this season.

Even in 2022, the six hard length balls that swung more than 0.5° in this phase went for only 3 runs. The increase in swing has definitely helped.

Same factors have contributed to another aspect that we briefly touched upon earlier - that his economy is sub-6 across all lengths in overs 12-16. Even while bowling fuller lengths, which travel in overs 7-11, he is mixing up his pace expertly and obviously is getting more swing now. 66.66% of his fuller deliveries swung more than 0.5° in this phase while it was 50% in 2022.

But he also undoes some of this good work done in the middle overs with his ineffectiveness in other phases. It was mentioned earlier that he hasn’t improved his record in the powerplay and death, in fact his economy has been a touch worse in these phases.

But not to worry, he compensates for this by conquering an older beast.

Left handers dominated Prasidh in 2022. This season, he’s giving it back to them not by just dominating them but [some verb that is 10x stronger but I’m not sure what it is]-ing them.

There’s indeed a change in approach in how he bowls to them. Obviously he’s bowling a higher proportion of hard lengths and bouncers, combined with pitching the ball more on their blind side.

Yet none of this conclusively explains his improved success against left handers because the same lengths and lines travelled in 2022. In fact against left handers, he travelled on all lengths and all lines in 2022 and is dominating them on all lengths and all lines now. It wouldn’t be wrong to suggest there’s mean reversion at play. Whatever it is, it has helped him and his team massively.

Everyone believed Prasidh Krishna would become this beast one day. Some lost hope along the way but everyone at some point thought it was a matter of time. Mega auction after mega auction, owners splurged cash at him hoping their franchise would be the station where the Prasidh Express finally arrived. After 7 years of delays, it has finally arrived now. The HTD Hero Prasihtd is here. Enjoy the ride for we never know how long it lasts.

All stats presented in this article are accurate as of April 25, 2025.

Stats credit: iplt20.com

‘White Hot’ is the title of the book by Tim Wigmore and Matt Roller which, in the words of Nathan Leamon, takes you into the heart of England’s white-ball revolution. While the England team of that era was not the greatest of all time and their achievements were overstated at times, they did go through an ODI batting revolution rising from their humiliating 2015 World Cup exit to the dramatic heights of their 2019 World Cup victory.

So what really happened? How did we go from ODIs defining them as ‘White Hot’ to them redefining the format as just ‘White Noise’. Let’s take a phase-wise look at their batting through a data lens to see what’s missing now compared to their peak.

A high level look at the data lets us identify three distinct periods:

• 2016-19 - their batting peak

• 2020-21 - signs of decline begin to emerge

• 2022-now - the period where, in Rob Key’s words, their batting fell off a cliff

The rest of the piece will compare their numbers across these three periods.

Aggressive openers were identified as the first key element of an ideal ODI batting lineup in the book Hitting Against the Spin by Nathan Leamon and Ben Jones as they found that the powerplay is the easiest phase to score quickly.

England have consistently produced aggressive openers ever since they realised this but at their peak, they were able to combine this aggression with wicket preservation skills which they seem to have lost since then.

This is likely because they took the aggression part too seriously, becoming overaggressive and losing wickets as a result. There’s a clear tendency to go for more sixes in the powerplay than during their peak.

They used to have openers who were masters at striking the right balance. More than 50% of their powerplay deliveries were faced by Jason Roy and Jonny Bairstow during 2016-19 who had balls-per-six ratio of 68.14 and 59.5. In contrast Phil Salt, who has faced the most powerplay deliveries since 2022, hits a six every 32.12 balls - nearly twice as often as Roy and Bairstow.

England have shifted from a risk-free, high-scoring powerplay approach to relying on overaggressive openers. Since 2022, Salt has an attacking shot percentage of 73.81% in the powerplay, compared to 61.11% for Roy and 61.25% for Bairstow during 2016-19.

‘Middle-over cruisers’ was the second facet of an ideal ODI batting lineup as identified in Hitting Against the Spin. And funnily enough, hitting against spin is what characterised these middle over cruisers. At their peak England were incredible at milking spin, displaying wicket preservation skills of the highest order while scoring at a sustainable pace. Since then, their spin game has undergone a massive decline.

During 2016-19, the monstrous engine room of Root, Morgan, Stokes along with Bairstow dominated spin in the middle overs. All four averaged above 65 against spin in overs 11-30. Even Roy, who was known to be weak against spin, provided solid support when he survived the powerplay. Together, these five faced 78% of spin deliveries England faced in overs 11-30 during this period.

It’s quite fitting Root was named as he is because he’s essentially the root on which the tree of English ODI batting grew. England’s batting fortunes in the middle overs totally hinged on his form. He went through a rough patch during 2020-21 and the knock-on effects dictated what happened in the following overs.

Root averaged 28.5 against spin in overs 11-30 during that period and the rest of the batting crumbled. While Bairstow and Stokes held their own, Morgan was also in the twilight of his career and the others couldn’t compensate.

The knock-on effect was the lower order being exposed far earlier than desired. Stokes and Buttler missing half the games during this period didn’t help either. Nearly 40% of deliveries in overs 31-40 were faced by Sam Billings, Chris Woakes, Lewis Gregory and Sam Curran. By the death overs, the tail was often already in.

Their problems have been different since 2022 though. By then, their struggles against spin were well known and teams started introducing spinners earlier. In overs 21-30, 57.2% of deliveries they faced were against spin - the only period where they faced more spin overs than pace in this phase - and they average just 34.37 off them.

Also, the early wickets lost in the powerplay and a slight shift in Buttler’s role have forced him to bat earlier. Since 2022, he has faced the most spin deliveries in overs 21-30 - a stark contrast from their peak years where his delayed entry meant he rarely featured in the first 30 overs.

The spin weakness continues to haunt them in overs 31-40 as well. It’s only logical to choke them with more spin overs once you identify there’s a weakness. Expectedly, they average only 26.45 against spin in this phase while they averaged 65.52 during their peak.

If that’s not enough, they are making things worse for themselves with their six-obsession. Overagression isn’t confined to the powerplay, it has been a general issue for them throughout this period. The newer players lack patience and haven’t mastered the art of pacing an ODI innings. There’s a tendency for them to go explosive too early.

This used to be the phase where Buttler came in and shattered the souls of the opposition with solid support from Stokes and Root at the other end. Now, Buttler is a different player and Livingstone, tasked with filling that role, has struggled to match the lofty standards set by peak Buttler.

Death overs are the only phase where their numbers look decent. With their six-obsession, you’d expect them to fare better at the death but their strike rate is still 6 points lower than at their peak. This is largely due to poor wicket preservation early on, leaving few main batters to capitalize at the death.

Not long ago, England boasted of building a white ball dynasty and possessed both the white ball world trophies. Now they have neither and the dynasty has been destroyed even before it was built. The primary reasons seem to be a glaring spin weakness and overaggression - likely due to reduced List A exposure and their first-choice players’ involvement in a shortened version of T20 over it. Players like Harry Brook and Jamie Smith show England aren’t short of talent but the system must also support their development for them to succeed. England were white hot once. It’s all white noise now. Perhaps it’s time for a whiteboard reset.

All stats presented in this article are accurate as of March 7, 2025.

Stats credit: Himanish Ganjoo

He loves the gap. He loves smashing the cricket ball through the gap. By now it’s well known that Duckett doesn’t believe in the concept of leaving balls. In the Bazball era, for every 100 balls he faces in Test cricket, he leaves just about 2.

Duckett absolutely loves scoring and that probably explains why he has the best strike rate in Test cricket since 2022.

And obviously, that means he must be hitting a lot of fours and sixes to maintain such a high strike rate, right?

Well, yes and no. His four-hitting is elite - since 2022, Duckett comfortably has the best balls-per-four ratio, taking one fewer ball per four than the second-best. But he ranks 53rd in balls-per-six. He uniquely maintains a high strike rate by hitting plenty of fours but very few sixes.

This is a direct result of the types of shots he plays - shots that are more likely to produce fours than sixes. One such important shot and also the one he is most famous for, is the sweep, which brings us to his spin game.

Duckett boasts an impressive strike rate of 100 against spin. Only madman Pant is ahead of him. Nobody except these two have a strike rate above 90. 

And as you would expect, these two also stand out from the rest in terms of balls-per-four ratio. 

What sets them apart is that Pant is a proper boundary hitter who also hits plenty of sixes whereas Duckett doesn’t. Pant hits a six every 18 balls against spin while Duckett hits one every 18 overs. And as we touched upon earlier, this comes down to Duckett’s shot selection.

Shot type data records four different types of sweeps. Duckett plays all of them. Three of these sweeps - the conventional sweep, reverse sweep and paddle sweep - are primarily four-hitting shots. Even when he plays the more aggressive slog sweep, he hits fewer sixes and more fours than the average batter does with that shot. This obsession with the sweep explains his unique ability to achieve a high strike rate primarily through fours.

He doesn’t just play all four types of sweeps, he plays them at a higher frequency than the average batter. His obsession with sweeps is so much that he plays them 3.2 times more often than the average player.

He isn’t spamming the sweep just because it is his favourite shot, he is simply too good at it.

And that doesn't mean he's a dud against pace. He’s equally proficient, having the second-best strike rate and balls-per-four ratio against pace as well.

The other standout feature of his pace game is his low dot ball percentage - the lowest, in fact. Once again, this comes down to his shot selection.

Duckett loves playing off the back foot. He plays a higher proportion of cuts and pulls which helps minimise dot balls. He plays nearly three times as many cuts and twice as many pulls against pace as the average batter.

He also plays a slightly higher percentage of cover drives which contributes to his four hitting.

His tendency to play more sweeps and backfoot shots is clearly represented in his wagon wheel, which shows that he has scored majority of his runs square of the wicket.

Duckett is a unique and interesting character, both on and off the field. Off field, he’s seen as someone who provides meme-worthy entertaining content. But don’t let that overshadow his equally entertaining on-field play. “It almost feels like we should take some credit” is what Duckett said when Yashasvi Jaiswal played an aggressive knock against his team. Perhaps Duckett should take some credit – not for others’ performances, but for his own unique and captivating batsmanship.

All stats presented in this article are accurate as of October 14, 2024.

Stats credit: Himanish Ganjoo

This was the title of a video from the Bumble & Kimber series on talkSPORT Cricket. “Yes” is Bumble’s first word in the video. And at the time, Harry Brook was just 15 Tests into his career.

Absolute bonkers, yes. But it does make you wonder: how is a 15-Test old youngster already being mentioned in GOAT conversations by sane people?

You already know Brook’s record, his upside and his style of play. His career took off right as Bazball was taking over and he became one of the key pillars of its success. It wouldn’t be wrong to call him the face of Bazball.

One standout feature of his game is his ability to score off good length deliveries, particularly against seam bowling despite playing most of his matches in helpful English conditions. Brook’s strike rate of 58.6 is the 11th best in Test cricket against good length seam bowling.

But 11th best doesn’t sound like someone who should be in GOAT conversations, right? Maybe people have gone mad. Or maybe only two players ahead of him on this list have a higher average.

He averages 31.5 against good length off seam bowlers. Of the players who strike higher than him, only two have a higher average (de Kock - 38.68, Perera - 34.38). Half of them average in the 20s. So, not only does Brook score faster against good-length deliveries, but he also does so without getting dismissed often.

How does he maintain a higher survival rate despite being more attacking against the ideal length? The answer lies in his method of scoring. He has the best dot% against good length seam bowling in Test cricket since records began.

He doesn’t achieve a higher strike rate by blindly slogging at good length deliveries. Instead, he employs a risk-free approach by minimising his dot%. While others boost their strike rate through boundary hitting, Brook achieves it through strike rotation. To confirm this further, let’s look at his rotate%, which measures the percentage of balls he faced on which he scored 1, 2, or 3 runs.

He’s so far ahead of everyone else in terms of rotate%. 

It’s possible that he’s just a lucky lad and bowlers start straying in line when Brook’s at the crease making it easier for him to rotate the strike.

Good length outside off deliveries are considered the gold standard for pace bowlers. Data backs this up. Since records began, batters average just 18.36 and strike at 31.76 against seamers bowling good length outside off deliveries. Only yorkers are more effective and you obviously cannot keep bowling yorkers. It’s the most threatening line-length combination. As a batter, you can’t even rotate off these deliveries (dot% - 83.97%, rotate% - 12.17%)...unless you are Harry Brook who manages to score off these deliveries as well. 

So the luck theory doesn’t hold up, he has been scoring off the ideal line-length combination of fast bowlers. And how does he do it? Oh, you know it - by minimising his dot% and increasing his rotate%.

Brook only has the third best dot% against good length outside off deliveries but the two players above him are tailenders who slog for their lives. Both of them average below 25 while Brook maintains a healthy average of 33 against these deliveries. Again this is because of his risk-free approach to scoring quick runs. When we look at his rotate%, Brook stands comfortably ahead of the rest.

His ability to rotate strike against pacers' best deliveries is miles ahead of everyone else. He scores most of his runs through the point and cover regions as shown by his wagon wheel.

And shot type data confirms that he drives and pushes a lot against these deliveries.

He additionally plays a flick when the line is straighter as illustrated by the wagon wheel and shot type data.

The ability to put away bad balls is a fundamental trait of any good batter. But excelling against good deliveries is what separates the best from the rest. In his young career, Harry Brook has already found a way to score off bowlers’ best deliveries. Your good balls aren’t enough to keep Brook quiet. You have nowhere to hide. No wonder he’s already featuring in GOAT conversations.

All stats presented in this article are accurate as of July 12, 2024.

Stats credit: Himanish Ganjoo

This is what Phil Tufnell said after Root attempted to reverse scoop Bumrah. In fact, this is what everyone has been saying since Root played that dreaded reverse scoop. But what does the data say? Has Bazball really spoiled Root?

large section of cricket fans agrees with Tufnell that Bazball doesn’t suit Root, arguing he should stick to his old conventional style. Bazball enthusiasts counter this by highlighting Root’s higher average during the Bazball era. He indeed averages 53.19 in the Bazball era compared to 49.19 previously.

In fact, during the Bazball era, Root has a higher average in innings where he has a higher strike rate. His average in innings with a strike rate above 55 is 65.45, while it drops to just 22.54 in innings with a strike rate below 55.

However, strike rate may not be the best metric. Instead, let’s use attack% which helps us accurately determine how attacking he was in each innings based on shot type data.

But guess what, the observations show no noticeable difference. Root has certainly performed better in innings where he attacked more.

You could argue that the final attack% is also not a reliable measure, as he might have started slow and then accelerated after reaching a milestone, as batters often do. To verify this, let’s just consider Root’s attack% in the first 50 balls of all his innings during the Bazball era.

Sorry Bazball-naysayers, but here’s more bad news: he still has a better record when he attacks more. 

While analyzing only the first 25 balls adds an interesting perspective, it still doesn’t provide any support to the argument that Bazball has diminished Root’s returns.

Alright, now let’s talk about something which I’ve deliberately set aside but have clearly presented for you all to see - his control%. Notice how his control% remains remarkably consistent regardless of how attacking he is. Even during his pre-Bazball days, when his overall attack rate was 39.17%, his control rate was 85.68%, which isn’t significantly different from the numbers mentioned above. Conventional knowledge suggests that you have to compromise your control% to achieve a higher attack%. So, how does Root manage to maintain his control% while being more attacking? It could potentially explain why Bazball hasn’t affected his record.

To find out, let’s break down shot type data further and examine the shots Root has played. The key observations are presented in the table below: 

The above table helps us understand the changes in Root's shot selection when he adopts a more attacking approach. You can see that he defends and leaves the ball less, while he has started flicking, pushing, steering, pulling, and reverse sweeping more in the Bazball era. Some shots, like the cut, sweep, and square drive, remain at similar percentages as before. But what you’re about to see next is what’s going to explain Root’s genius.

You'll notice that most of the shots Root plays more in the Bazball era are ones that have given him good returns in the past. The shots he plays less are those that didn’t yield good returns, while the shots he plays the same amount provided moderate returns.

Bazball is often associated with reckless hitting among the general public but Root has been fantastic with his shot selection. Yes, he has been more attacking but he achieves this by playing his most productive shots more often and his less productive shots less often. This could also explain how he maintains his control% despite being more aggressive. He only plays his comfortable shots more often and isn’t really trying to do something he can’t. In fact, the reverse scoop, which has drawn a lot of criticism, accounts for only 0.17% of his shots during the Bazball era.

His shot selection has changed similarly in his first 50 balls and first 25 balls.

Now that Bazballians have enough to be over the moon, let’s bring them back to earth by asking the important question - Is Bazball solely responsible for Root’s improved record?

Yes, Root has a better record during the Bazball era but it would be too simplistic to conclude that his better record is solely because of Bazball.

There was a one-and-a-half year period, just before Bazball, when Root significantly upped his game. During this period, his average was 54.36, compared to 47.99 before. His attack% also increased to 42.57% from 38.22%. To provide more context, his attack% during the Bazball era is 45.97%. The increase in his attack% was more pronounced in this interim period than after Bazball took over.

And the way his shot preferences changed during this transformative period looks familiar.

Notice how there is a progressive increase or decrease in each shot he plays. Root had already begun to adopt a more attacking style before Bazball. Although he became even more aggressive during the Bazball era, it wasn’t a sudden shift as often portrayed. He had identified his most productive shots even before Bazball and had started playing them more frequently.

The article started by discussing Root’s reverse scoop against Bumrah. That one dismissal influenced perceptions so much that people began believing that’s how he plays in the Bazball era. In reality, he’s been very clever in choosing which shots to play more aggressively. On the other hand, it would be disrespectful to someone of Root’s class to simply attribute his improved record to Bazball. He started becoming more aggressive before Bazball, and Bazball just acted as a catalyst to accelerate this further. Bazball neither spoiled him nor deserves sole credit for his success. Instead, Root should be celebrated for finding a way to make such an extreme approach work for him.

All stats presented in this article are accurate as of July 12, 2024.

Stats credit: Himanish Ganjoo

Let’s keep that aside for a moment and now imagine seeing this on your TV screen:

Unreal isn’t it? Now you might think the bowler described in the first paragraph is the same guy in the picture above as this article is indeed about Bumrah. If that was your guess, haha I tricked you. It isn’t Bumrah, it’s Rasikh Salam.

But I’ll admit I tricked you for the sake of it because Bumrah isn’t far off. In fact he has bowled the second highest percentage of full tosses in the last three seasons of the IPL. He has bowled a whopping 63 full tosses (third highest for any bowler in the last three seasons) despite missing an entire season.

But as you may already know he has a remarkably low economy rate on his full tosses. The non-extras economy rate of Bumrah’s full tosses is just 5.74 despite the huge sample size.

Throughout this article, we will only use the non-extras economy rate of full tosses. Henceforth, any mention of economy rate will specifically denote the runs scored off the bat per over.

“Yeah yeah, we know. It’s because of the insane lift he gets, right?”

While the lift plays a role it can’t be the sole reason. 

For people who are unfamiliar with the concept of lift, here’s an excerpt from my previous article: 

“The natural vertical acceleration due to gravity is -9.8 m/s² (the negative sign indicates downward acceleration). When backspin is imparted, it creates an upward force that counteracts some of this downward acceleration. This slows down the downward acceleration and that’s what causes the ball to land fuller.”

It’s now well known that Bumrah’s wrist snap helps him impart a large backspin resulting in a higher lift. Bumrah gets an average vertical acceleration of -5.87 m/s² on his full tosses, which is the third highest among seamers who have bowled at least 10 full tosses in the IPL since 2022.

But a higher lift doesn’t guarantee a lower economy rate. After all, it’s still a full toss. The economy rate for full tosses bowled with a vertical acceleration below -6 m/s² is 12.45. If it’s above -6 m/s², the economy drops to 10.5.

A difference of just 2 RPO isn’t what we see for Bumrah’s full tosses. So a higher lift alone can’t be the only magic behind Bumrah’s full tosses.

Another commonly cited reason is his delayed release point which implies that the ball has to travel a shorter distance and consequently loses less pace before reaching the batter. This can be quantified using the reaction time to crease.

Another contributing factor to the reduced reaction time is the pace at which Bumrah bowls his full tosses. Since 2022, only 4 of Bumrah’s 63 full tosses in the IPL were delivered at a pace of <135 kph.

The delayed release point also explains why Bumrah’s full tosses have a reduced reaction time despite bowling at a lower speed compared to bowlers like Pathirana and Nortje. 

Now remember, a lift of below -6 m/s² didn’t have a significant effect on the economy rate of full tosses. Now if we combine that with a pace of >140 kph and a reaction time of < 0.49 seconds, the economy rate drops further to 8.42. You see where this is going, right? 

                                                                       *****

Four - That’s how many wickets Bumrah has picked up off his 63 full tosses in the IPL since 2022. Three of those wickets (Hetmyer, Porel, du Plessis) follow a similar pattern - batters trying to put away full tosses but failing to get enough elevation and distance. In a traditional sense, they were unable to get under the ball.

Of course, we can’t attribute all these wickets solely to Bumrah’s magic. There were batting errors as well but batters not being able to get under the ball is one common characteristic of Bumrah’s full tosses. 

Obviously, the lift and the high pace play a role but there’s another factor at play - Bumrah bowls a lot of low full tosses which are often said to be as difficult to score off as yorkers. If we consider the average height from the ground when the ball passes parallel to the crease, Bumrah has bowled the second lowest full tosses in the IPL since 2022.

You know what we are gonna do next. Adding another filter for the ball height at the crease being below 40 centimetres, in addition to the previous filters, further reduces the economy rate of full tosses to 7.09.

By the way, we have only covered three of Bumrah’s four wickets off full tosses. What about the fourth? Well, it’s a sad-looking dismissal of Washington Sundar completely missing a full toss and getting cleaned up. 

“Who gets bowled on a full toss?” you’d ask but this ain’t no ordinary full toss. He was certainly deceived by the lift as we could clearly see the batter misjudging the trajectory and swinging his bat below the ball. Of course, the lift caused the ball to hit the stumps higher but let’s not overlook one super-obvious thing that led to the dismissal - the ball was directed at the stumps.

The beehive above not only shows how low Bumrah’s full tosses are but also shows that he’s always at the stumps. And this indeed is the final piece of the Bumrah full toss puzzle. When we further filter the full tosses derived earlier, considering only deliveries within 35 centimetres either side of the middle stump line (when ball passes parallel to the crease), the economy rate drops down to an unbelievable 5.88.

A full toss that exhibits all the attributes discussed above is essentially the 'perfect full toss' (for convenience, we'll refer to it as such from now on), which every bowler wants to bowl to avoid punishment even when they miss their length. 

And we are already in Bumrah territory. Since 2022, there have been 48 perfect full tosses in the IPL and Bumrah has bowled 41.67% of them despite missing an entire season. Cummins and Nortje, tied for second place, have only managed 8.33% each. They have managed to bowl only 4 perfect full tosses each while Bumrah has bowled 20 such balls in the same time period. 

The perfect full toss accounts for 31.75% of Bumrah’s full tosses and it should be quite obvious that the remaining deliveries share similar attributes, with slight variations in one or two attributes that just miss the cutoff we used in our analysis.

Bumrah’s full tosses are akin to a perfectly prepared dish with each added ingredient enhancing the taste further. Bumrah combines various attributes that each slightly improves the economy rate of a full toss and delivers a killer full toss that produces an unbelievable economy drop. If you are a batter facing Bumrah and you wish he errs and bowls a full toss so that you can score off him, think again. You are not going to get a regular full toss that you can hit for a six but a full toss that won’t even let you score six in an over. It’s the perfect full toss. It’s the Bumrah full toss.