This means the single most important thing I build all year is my ownership model, a forecast of what the crowd will do before they do it. If I know the field is going to pile 40 percent of itself onto one team, I know what surviving that week is actually worth. If I know a team everyone should want is going to get ignored, I know where the free equity is. Every EV number I publish, every tier, every pick I make sits downstream of one question: how well can I project the crowd?

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Projecting one week of ownership is maybe kinda easy (ish). But projecting eighteen weeks of it, including six (or even eight) double-pick weeks, while the field shrinks, burns teams it can never use again, and reacts to its own carnage, is genuinely really really hard. Which teams are still available to which entries, who is saving what for which week, how the whole thing cascades when a big favorite loses.

When I finished my first version of my 2026 model, it passed every sniff test I threw at it. It matched a couple of independent industry sources decently well. It reproduced last season's actual ownership within a couple points in the near weeks. I was genuinely happy with it, and so I did what a normally do in this situation. Attack it from ever single angle, assume something is wrong until it proves to me that its right.

I came up with a list of 43 different beliefs about how survivor crowds could behave. Then, I tested them against sixteen seasons of pick history across three very different crowds. The public pool data on Survivor Grid (4 different sources), the sharp player pool data from the Circa Survivor Contest, and last year’s $2.5m Big Splash contest on Splash Sports.

Speaking of Splash Sports, I’ve partnered with them for the 2026 season. Promo code JBB gets you a 50% deposit match and a 100% QuickPicks payout boost. I’m also running my own survivor contest built to mirror the structure of their larger ones. Sign up here.

Here is the final score: only sixteen of the 43 survived. These earned their keep and changed my process for the better. A few of these are candidates I am considering living inside the model itself, and the rest became rules I will now run every single week when I settle up my ownership projection numbers. Another twelve came back real but too small to act on yet, so they sit on a bench and I will keep grading them this season. The last fifteen died outright. The full card for all 43 is at the bottom of this article, since I know some of you nerds will want all the details. The stories worth telling in full are below, and a few of the survivors genuinely surprised me.

The Crowd is Two Different Animals

The Myths: Everybody fades a favorite after a loss, they fade them harder after a bad loss (2+ TDs). They also fade a favorite on a losing streak. They definitely fade a favorite who just busted a bunch of the field.

Show Me The Data: The public absolutely does this. Across sixteen seasons of public pools, favorites coming off a loss run one to two points below what their price says they should. Favorites on losing streaks run more than two points light, and a team that recently busted a big chunk of the field gets avoided by about two points the next time it is chalk. My instincts were right…BUT

They were right about the wrong crowd!

I compared this to the $1,000 entry contest and the exact same situations leaned the opposite direction. The sharp field does not fade the team that just lost, it buys the dip. Nearly every loss-related habit I believed in flipped in the big money pool. And when I ran last season’s large-field Splash Sports contest through the same tests, expecting something in between, it came back sharp on five signatures out of seven and public on zero. The fields I am mostly going to be writing about this year are the sharp animal.

Chalk Runs on Fear

The myths: The crowd treats big chalk the same every week. The crowd is flatter at the top than win probability says, meaning mega chalk comes in lighter and mid chalk comes in hotter. A string of quiet weeks makes the crowd comfortable to drift away from the chalk. Then, a massacre herds everyone back to the top chalk.

Show Me The Data: The sharp crowd’s relationship with chalk is a cycle, and the fuel is fear. In a normal week, the field is actually flatter at the top than pure win probability says it should be. Mid-sized favorites run a couple points hotter than my model projected, and the monster favorites, the 35-percent-of-the-field type, runs five to six points lighter than my model. The crowd diversifies off the biggest name more than the math alone predicts.

The above chart shows what happens as the season breathes. Every quiet week that passes without a bloodbath, the crowd drifts a little further off the top pick, up to about six points of underweight after three calm weeks in a row. Then the massacre hits (a quarter or more of the field dies) and everyone snaps right back. Survivors jam the top choice about five points beyond what the pricing justifies, and I can tell you exactly where that panic money comes from: the middle of the board, the fourth through tenth best options, which get abandoned. The tail longshots barely move. Fear does not make people crazy, it makes them obedient to the chalk.

Habits Sharp Money Can’t Shake

Four beliefs survived contact with the sharp data, and one of them I had confidently called wrong.

The myth: Everyone piles onto a favorite playing a truly awful team, beyond what the line already says.

Show Me The Data: Confirmed everywhere, and it is the only habit in this whole project that every crowd shares. Favorites facing a bottom-quartile opponent run about four points over-owned in the sharp field, over two points in the public pools across every era, and about two points in last season’s large-field Splash Sports data.

The Myth: A bad loss in primetime lingers longer than a bad loss at 1pm.

Show Me The Data: This was my best call of the entire project. Favorites coming off a nationally televised loss run about five points under-owned in the sharp field, in every season I can test. Meanwhile favorites off a nationally televised win barely move. Losses get burned into memory in a way wins never do, and forty million witnesses make it worse.

The Myth: Last year’s playoff teams get extra love from the field.

Show Me The Data: Backwards, at least among sharps. I assumed this one was going to be neutral and the data disagreed with me. Prior-season playoff teams, as favorites at identical prices, run about two and a half points under-owned in both sharp datasets. The sharp field fades the pedigree. My best guess is that experienced players assume everyone else will be on the brand name and route around it, which means the brand name quietly becomes the value.

The Myth: A spread is a spread. A favorite at -10 is just a slightly bigger favorite than one at -9.5.

Show Me The Data: The human brain likes round numbers. Favorites at exactly -10 run about two points over-owned compared to teams at -9.5 and -10.5, in both the sharp and public data, in every era, and I checked hard to make sure the prices themselves were not the explanation. The same pull shows up at -14 in the public pools. It does not exist at -7 or -3. Round double-digit numbers just look safer, and the crowd pays for the optics.

Your Pool has Fewer Brains than Entries

The Myth: a 20,000-entry contest is 20,000 independent decisions.

Show Me The Data: Not even close. In Part 4 of the intro series we talked about how multi-entry players consolidate their picks and build their own internal chalk. The per-entry data proved it beyond any doubt. Entries under the same account pick together at rates far beyond chance, and the cleanest evidence is week one, before anyone has burned a single team, where blocks of entries match each other at nearly three times the rate random strangers do. Run the math on how much independent decision-making is actually in these fields and the number is brutal: last year’s biggest sharp contest had almost 19,000 entries and roughly 10,800 independent minds. The large-field Splash Sports contest I tested carried about half as many brains as entries.

And the structure goes deeper. Entries that have burned through their good teams pick measurably chalkier than entries sitting on full menus. In double-pick weeks, the crowd pairs a big favorite with another strong favorite far more often than chance, almost never the big favorite plus a longshot. Even trauma shows up in the data: entries whose team survived by a field goal or less get a little braver, not a little safer, the following week.

The Myths That Died

The graveyard matters as much as the survivors in my opinion. I put together a substantial list, logged my own hypotheses and then ran the numbers. There were plenty of claims I expected to be nothing, and if this data dive had proven otherwise, I would have folded it it. It found nothing, almost every time.

Here’s the quick hitter list: Momentum is not real in ownership. Teams off blowout wins do not get chased. Win streaks get a shrug. Thursday night has no consistent effect once you account for price. Road favorites are owned exactly like home favorites at the same number. Bad weather does not scare the crowd off favorites, and while I was in there, weather favorites also win at exactly the rate the closing line implies, which will not surprise anyone who read article one. The idea that big fields start out playing like the public and sharpen up as they shrink, which I believed strongly enough to design a whole test around, is false. The sharp fields are sharp from the jump, they don’t need a ramp up period.

The Full 43

Every test I ran with a quick one line summary. SURVIVED means it changed my process or model. BENCHED means the data says it is real, but it is too small, too one-sided, or measured on too little data to act on yet, so it stays on my ledger and gets re-graded as 2026 rolls in. DIED means it is folklore, at least at any size worth caring about. Point values are ownership versus what price alone predicts, positive means the crowd avoided the team.

The crowd is two different animals

1. Public crowds fade a favorite off a loss. SURVIVED, about a point, every era since 2010.

2. Public crowds fade a favorite off a bad loss even harder. SURVIVED, and it is the one loss habit that also shows a trace in the sharp field.

3. Public crowds fade favorites on losing streaks. SURVIVED, over two points, the strongest of the family.

4. Public crowds avoid a team that recently busted the field. SURVIVED, about two points.

5. “Off any loss” as one combined rule. BENCHED, it adds nothing beyond the pieces above.

6. Sharp crowds share the same loss aversion. DIED, they lean the opposite way on every one of these.

7. Big cheap-entry fields behave like the public. DIED, last year’s largest field tested sharp on five signatures out of seven, public on zero.

Chalk runs on fear

8. The crowd treats big chalk the same every week. DIED, and this one dying is the biggest finding of the project.

9. The crowd is flatter at the top than win probability says, mid chalk hot, mega chalk light. SURVIVED, five to six points at the extreme.

10. Quiet weeks make the crowd drift further off top chalk. SURVIVED, up to six points after three calm weeks.

11. The week after a massacre, survivors herd into top chalk. SURVIVED, about five points, every season tested.

12. The panic money comes from the middle of the board, not the longshots. SURVIVED, ranks four through ten pay for the herd.

13. Fields sharpen as they shrink, public early, sharp late. DIED, sharp from week two. I believed this one strongly and built a whole test around it.

14. The sharp field has gotten measurably sharper year over year. DIED, no trend worth the name.

Habits sharp money can’t shake

15. Everyone over-picks favorites playing terrible teams. SURVIVED, the only habit every crowd on earth shares, two to four points.

16. A primetime loss lingers in the crowd’s memory. SURVIVED, five points, my best call of the project.

17. A primetime win gets chased the same way. DIED, a fifth of the size I called, losses stick and wins do not.

18. Last year’s playoff teams get extra love. DIED, and reversed, sharps fade the pedigree by about two and a half points.

19. A spread is a spread, minus 10 is nothing special. DIED, favorites at exactly minus 10 run two points over-owned versus their neighbors.

20. The same pull exists at minus 14. BENCHED, it shows in the public data, the sharp sample is too thin to grade.

21. The same pull exists at minus 7 and minus 3. DIED, clean zeros, the illusion is a double-digit thing.

22. Some teams get picked against far more than price explains. SURVIVED, the fade-magnet cohort is real in every crowd I can measure.

23. That cohort is explained by teams simply having bad records. BENCHED, obvious victims carry part of it, the rest is not explained yet.

Your pool has fewer brains than entries

24. Multi-entry players consolidate picks and build their own chalk. SURVIVED, blocks match each other at nearly three times the stranger rate in week one, before shared history can explain anything.

25. Entries running low on good teams pick chalkier than their menus require. SURVIVED, one to two win-probability points, a clean gradient.

26. Double-pick weeks pair chalk with chalk rather than barbell. BENCHED, clearly real in the one season of data that can show it, one season is not a verdict.

27. Surviving by a hair changes next week’s behavior. BENCHED, a small consistent shift, and toward brave rather than safe, which I did not expect.

28. Heavily-owned teams that win keep drawing extra attention the next week. DIED, could not be separated from price and availability at any usable sample.

Following the leader

29. The public crowd lands wherever the big public projection tool says it will. BENCHED, the pull is enormous, but the data cannot separate the crowd copying the tool from the tool simply knowing its audience.

30. The crowd hoards the teams public tools rate as save-worthy. BENCHED, real in the sharp field at about four points, but it depends on someone else’s product, so it stays a weekly note rather than a model term.

31. Marquee names get hoarded beyond their actual value. DIED, unstable, no verdict either way.

32. The loss-fade habits are amplified in the season’s first weeks. DIED, mixed everywhere I looked.

The graveyard proper

33. Momentum, a blowout win gets chased. DIED.

34. Win streaks get chased. DIED, whatever trace existed a decade ago is gone.

35. Thursday night changes ownership. DIED, no consistent signal, and pick deadlines would muddy it anyway.

36. Short weeks off Monday night matter. DIED, clean zero, and it was one of my planted tripwires.

37. Road favorites get discounted. DIED, another tripwire, another clean zero.

38. Divisional favorites get discounted. BENCHED, a whisper in the public data, under half a point.

39. The crowd chases line movement during the week. BENCHED, and backwards, the public actually lags steam by nearly three points, which is worth knowing even though my contests are not that crowd.

40. Quarterback changes scare the crowd off a favorite. BENCHED, real in the public pools, fading over the years, nothing at the sharp tables.

41. Cold and wind scare the crowd off late-season favorites. DIED, twice, once with a crude test and once with actual temperature and wind readings.

42. Weather favorites also lose more than the line implies. DIED, they win at exactly the rate the closing line says, which regular readers saw coming.

43. Bad-weather ownership matters at all late in the year. DIED, the sharp data cannot even reach a usable sample in those weeks, and the public data shows nothing.

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Not many people are winning that money on one entry. Serious players (like yourself if you’ve made it here to Part 4) are buying five, eight, ten entries in September and trying to steer the whole group all season long. Now with the plethora of Splash Sports contests available these entry books are easily clearing 150 maxers in many of the contests. We’ll refer to your entire group of entries as your book.

This article is about the discovery waiting at the end of this series: managing a book is not the same game as managing ten separate entries. A book has its own leak, the data can measure it, and the fix comes from the same place every other answer in this series has come from.

Here is the short version before we dive into the data This whole series has been about one opponent, the field. It turns out your own book is a field too. And you are its chalk.

Need to catch up on our strategy series?
Part 1 - Nobody is Wrong About the Games
Part 2 - Three Piles: What Joining the Crowd Actually Costs
Part 3 - The Price of Later: Auditing the Vault

Show Me The Data!

One last piece that we can derive from the per-entry level ledger. Entry names in the contest carry a numbered suffix, which is the owner’s entry number, and that means every multi-entry book in six seasons can be grouped back together. All 53,714 entries resolve cleanly: about 6,800 single entries, thousands of small books of two to seven, and a wall of 1,710 books sitting exactly at the ten-entry maximum, which is where the serious money lived. So for the first time in this series, we can grade portfolios instead of picks.

Size Buys Survival, at a Discount

Start with the obvious question: does buying more entries actually work?

The answer: Sort of? At Week 9, a single entry is alive 12.1% of the time. A book of eight or more entries has at least one entry alive 40.3% of the time. So size clearly buys book survival, and nobody should be surprised, since more tickets cover more outcomes.

The interesting number is the one next to it. If a big book’s entries lived and died independently, like strangers, the math says an 8+ book should be alive 50.9% of the time. The actual books come in ten points short. Every big book in the data is paying a tax, and the tax is paid is pretty pricey in the grand scheme of things.

Two things cause the shortfall, and they are worth separating.

The first is that big books’ entries are individually worse. Entries inside 8+ books survive to Week 9 at 7.6%, against 12.1% for singles. That is not because large-book owners pick badly. It is structural. Ten entries cannot all take the best trade every week, so spreading a book means some entries are deliberately buying the second-best and third-best trades. Part 2 & 3 priced those trades. A big book pays the near-best dime and sometimes the full dodge toll across its roster, week after week, and the bill shows up as individual survival.

The second cause is the one that surprised me, and it gets its own section.

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You Are Your Own Crowd

Take two entries from the same book. How often do they make the same pick in the same week? Now take two random strangers from the field and ask the same question.

Strangers agree 23% to 29% of the time, which is just chalk being chalk. Entries in the same book agree 38% to 43% of the time. People correlate with themselves about one and a half times more than the field correlates with itself, in every phase of the season.

Think about what that means for the thing a book is supposed to be. The whole reason to own ten entries is to own ten different fates. Instead, the average book’s entries move together: same reads, same leans, same Sunday sweat on the same game. Ten entries picking like this behave like six entries wearing ten hats. Bad thing here is you had to pay for all 10!

This isn’t really a new phenomenon. It is the funnel from Part 2, one level down. The field converges because survivors share constraints and share instincts. Your book converges for the same reason, except now every shared instinct is yours, so whatever bias you have (even if small) shows up ten times. Your own book piles onto your own favorite reads, which makes you the chalk of your own private field, and when your chalk loses, no entry in your book is standing anywhere else.

So the fix for this seems obvious right? Spread the book out as far as it will go. Maximize the differences in your portfolio each week.

That is what I assumed too, but the data said something much more useful.

I’ve partnered with Splash Sports for the 2026 season. Promo code JBB gets you a 50% deposit match and a 100% QuickPicks payout boost. I’m also running my own survivor contest built to mirror the structure of their larger ones. Sign up here.

The Inverted U

I took every book of four or more entries, which is nearly five thousand across six seasons, and I measured how much each one spread its picks over the first six weeks. Then I checked which books still had a live entry at Week 10.

The most stacked books, the ones whose entries move in lockstep, reached Week 10 at 29%. That is the correlation tax at full price: one bad Sunday takes the whole book with it.

But look at the other end, because it is the end that most multi-entry guides and tools will try to tell you to live on. The most spread books, the ones that maximized their differences, reached Week 10 at 24% to 35% depending on size band. They were also losers!

The winners are in the middle. Books with moderate spread reached Week 10 at 38% to 44%, and the pattern holds inside each size band separately, so it is not an artifact of big books clustering in one bucket. Both extremes lose and the middle actually comes out victorious.

I hope that by this point in the series you can explain this phenomenon yourself. Spreading is not free, because most weeks there is one best trade, and forcing ten entries onto ten different teams means some of your entries are buying the dodge at 0.95. The maximum-spread books were not diversifying. They were paying Part 2’s worst toll across half their roster every week. The maximum-stacked books were not confident. They were uninsured. The middle books did the only thing this series has ever recommended, applied at portfolio scale: concentrate on quality, and buy your differences at the same price.

This is also where I pay off a promise from Part 2. I told you the fourth pile, the near-best pile that takes the second-best team at basically the same price, would matter a lot in Part 4, so here’s why. The “near-best” dime discount is the correct price of buying a difference. A book that splits across near-best teams buys real independence for eight to eleven cents per entry. A book that manufactures difference by reaching down the board pays fifteen to twenty. The inverted U is what those two prices look like after ten weeks of compounding: spread across near-bests, stack when quality is singular, and never buy your differences in the dodge aisle.

Now the caveat, and it is the biggest one in the series. Nobody randomized these books. The owners of them chose their own spread, which means moderate-spread owners might simply be sharper players whose sharpness is being double counted, once in how they spread and once in what they pick. The pattern is consistent with everything else this series measured, it holds in both size bands, and I still cannot hand you a controlled experiment. So the inverted U goes on the same pile as every other claim here: graded live on this season’s data.

The Whole Series in One Idea

Going to try and tie things together neatly here, because as I’m hoping you are seeing here that all 4 of our articles were really making one argument.

The games are priced and they are priced well. Sixteen seasons and four pools showed nobody beats the closing line, so the only thing you are ever trading is position against the field (Part 1). Each week, that trade has an exact price: join the pile when it sits on the best team, pay a dime to be different at the same price, and never pay the dodge (Part 2). Across weeks, do the exact same math: don’t buy December with September EV, because survival is the only account in this game that compounds (Part 3). And across your own entries, do the math one more time: your book is a field, you are its chalk, and the right portfolio concentrates on quality while buying its differences at the same price (Part 4).

One idea, four scales. Every decision in survivor is an EV trade against a crowd. The crowd is sometimes the field, sometimes your own future self, and sometimes ten entries with your name on them.

Starting Week 1, the doctrine stops being retrospective. Every Friday this season, I’ll publish an ownership projection for the week. I’ll also include share-of-holders numbers and DIES Score like we discussed from Part 2. Thanks to our work in Part 3, it will also include our spend labels and maybe some form of lookahead EV map. Every Sunday morning I will update it with any late breaking news/trends. Every Tuesday I’ll grade it in public. Here in Part 4, I think I’ve talked myself into some sort of contest-by-contest analysis as well, which will help us keep tabs on how sharp these fields are trending.

That makes some sense to me, so I audited six years of those investments using the same per-entry level data we used in Part 2.

Eighty percent of the dodgers died before they ever got to spend the team they were saving.

The bigger slap in the face is the twenty percent of people who were able to eventually use their dodge, cashed in on it at an average EV of 1.07 against an EV of 1.13 in the week they chose to pass on it. Survival to the end of the contest was essentially identical between the two groups: 3.3% for the entries that cashed immediately, 3.7% for the savers.

So across 27 dodge weeks and six seasons, the vault looks like this: most of the deposits into it never get withdrawn, the withdrawals that do happen come out below their deposit price, and the vault users finish in the same place as everyone else.

This article is about why that happens, and about the one version of “later” that actually is worth something.

Need to catch up on our strategy series?
Part 1 - Nobody is Wrong About the Games
Part 2 - Three Piles: What Joining the Crowd Actually Costs

Show Me The Data!

We will start with the same entry-level data as Part 2 (53,714 entries across six seasons, courtesy of the PoolGenius pick histories). Then in order to assess future value, I added in one new dataset: sixteen years of lookahead lines from Survivor Grid, saved weekly exactly as they stood at the time. This give us over 75,000 forward prices, covering every team and every future week, captured at the moment people were actually making save decisions with them. That last part really matters for this analysis. To judge whether saving works, you can’t use what we know now, you have to use what the field knew then.

The Plan Outlives the Book

Let’s revisit the uncomfortable truth that we discussed in Part 1. The thing nobody really wants to talk about: your entry is probably going to die. In pretty much every scenario of every season ever, it dies. This same concept translates to one of the first problems of saving a team, you have to be alive to spend it later!

Across six seasons, an average of 1.8% of the starting field is still alive at Week 13. In four of the last five seasons it was the same decay curve. The 2025 contest opened with 18,694 entries and by mid-December only 49 remained.

Now apply that to a save decision in late September. When you dodge a team in Week 3 to protect them for a Week 15 matchup, you are planning for a week that more than 98% of entries never reach. If you run a ten-entry book, your expected number of entries alive at Week 13 is about one-fifth of one entry. On top of that, the save plan isn’t even free since you pay for it in this week’s EV, which as we’ve established is the one thing that determines whether you get there at all!

The Asset Doesn't Rot. You Do.

This is the part where I assumed something different than what the data actually shows.

An additional argument against saving is that team dominance decays just like a participants entry book. Maybe the big favorite you’re saving for Week 15 won’t still be a big favorite by Week 15. With sixteen years of saved lookahead lines, I can test that directly: how often does a projected 80% favorite still close at 80%?

The answer is clear, they are almost always still big favorites, at every distance. Projected one to two weeks out, 88.5% still close as big favorites. Three to five weeks out, 84.5%. Six or more weeks out, with a month and a half of football between the projection and the game, 83.4%. So there is no safe window for saving and no dangerous one, because the top teams barely decay. Kansas City in December, projected from October, is still Kansas City. The saved asset holds its value. The problem really does circle back to the saver.

So here’s where we stand when it comes to a save, it’s a pure multiplication problem. Your expected final equity is your stake times the product of your weekly EV multipliers. When you decide on a dodge it means you are taking roughly a 0.95 this week instead of the 1.13 that’s available on the board, and that ratio, about a 16% haircut, carries through to every future dollar, including December’s. The payoff comes later, in the week the saved team finally binds: the saver genuinely picks better that week, about 1.03 against the 0.96 that entries who burned the team are stuck with, a one-time edge of about 7%. Multiply it out: 0.95 times 1.07, against 1.13. The save nets out around ten points of expected equity lost. The asset held its value the whole time but the trade still loses, because the price was bigger than the payback.

Doing this math and staring hard at the chart above (trust me I had to stare pretty hard) actually spells out the break-even point for the whole saving question. If the payback is worth about seven points, then protecting a team is fine (a typical dodge costs ten to eighteen). Cheap saves are real. Expensive ones are not worth it. The realized data agrees on both ends: savers and cashers finished within half a point of each other, and the savers who finally spent the team got 1.07 instead of the 1.13 they passed up, because everyone who saved it tends to spend it the same week. The funnel from Part 2 takes a cut at deposit and again at withdrawal.

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December Is Part 2 With the Volume Turned Up

Another myth floating around about the saving strategy is about what the late-season boards actually look like. The theory is everything good is burned by December, everyone's picking coin flips, so you'd better have planned ahead. In this case, the data says close to the opposite.

The board never collapses. The best available price sits between .82 and .91 all season, because the NFL produces new big favorites every week faster than any field can use them up. The field’s actual picks hold between .73 and .79 from September to January. The average Week 16 pick is priced about the same as the average Week 3 pick. And the crowding never really breaks either, even in December, the biggest pile still takes 39-45% of the live field, and the top three piles take about three-quarters of it.

Sure JBB, but only a few teams make up that best price every week and once I used them, I’ve used them! That’s spot on observation, nice catch. Whether you can still take the top team on the board swings a lot late in the season: some weeks 90% of survivors still hold it, where some weeks only 30% do. But here’s the number that ends the whole coin-flip discussion: even the 25th-percentile survivor, an entry with one of the worst remaining boards in the field, still has a best option around .76 to .80 late in the season. Nobody is ever actually reduced to coin flips. This means every week, all season long you have to answer this question: which good team do I pick, against a field that never stops clustering.

(One note if you are in smaller home league pools: this is a sharp-field result. The free public pools do flatten late, with the top pile sometimes decaying toward 25% by Week 17. The sharp contest never does. I flagged in Part 1 that late-season dynamics depend on which pool you’re in.)

So if the board is the same and the clustering is the same, what actually changes in December? The stakes baby the stakes!

Equity Share: The Number Behind Every Number

This is the concept the whole series has been circling, so let’s finally put it on the table.

Your equity is your slice of the prize pool, the pot divided by the number of survivors. If a $100,000 pool has 100 entries alive and you’re one of them, your seat is worth about $1,000 right now. A more sophisticated version adjusts that for the risk still in front of you, since a survivor in Week 3 has a lot more dying left to do than a survivor in Week 15. But the simple version is close enough for now, and it explains something important: every EV number in Parts 1 and 2 was really a statement about equity.

Let’s walk through what making a pick every week actually does. When you survive a week, two things move your equity at once: 1) your survival keeps your seat alive and 2) everyone else’s eliminations shrink the number of people splitting the pot. That’s why a 1.20 EV pick means your equity grows 20% on average, and a 0.95 pick means it shrinks. The EV was never about winning that week in front of you, it’s always about what your slice of the pot looks like after the week settles.

Here’s why this matters for the saving question we’ve been discussing in this article. The multiplier on your equity is roughly the same all season. A good differentiated week in September is a 1.2x, and a good differentiated week in December is a 1.2x. But the equity share that multiplier lands on changes drastically throughout the season.

In 2025, a surviving entry was worth $1,000 after Week 1. After Week 9 it was worth $9,088. After Week 13 it was worth $381,510. The same ordinary 1.2x week that moved your position by a couple hundred dollars in September moves it by thirty-four thousand in December. And with 40% of fifty entries stacked on one pile, a single differentiated pick in December can double a six-figure position in one week.

That’s why the late season feels different even though it’s the same game. It isn’t a coin-flip lottery, and it doesn’t require teams you hoarded in September. It’s simply Part 2 with every decision worth a thousand times more, and the entries collecting those December multipliers are simply the ones that survived to be there.

Stop Planning December

Let’s summarize where we stand after all of the above deep dives.

The crowd’s mistake is not that it wants leverage in December. The leverage is real, and we measured that it’s worth about seven cents of EV per week for entries that arrive holding a fresh top team. The mistake is trying to buy that leverage in September with EV that compounds against you every week you wait. You don’t often bank December leverage by dodging down teams, you bank it by simply not dying. The schedule produces new heavy favorites every single week, and it will hand December’s survivors plenty to work with. It always has.

In my own weekly process, every team on the board gets a spend label. NOW: the best trade is today, take it. HOLD: a visibly better spot exists within the next few weeks, close enough that the plan barely decays. LATE and HAMMER: real value deep in the season, with HAMMER reserved for the rare team that is clearly the best use of a specific future week.

So, designate your hammers. The data says the designation holds. But the day you take a meaningfully worse team to protect them, you’ve joined the dodge pile, and Part 2 already priced that trade. Be different at the same price when you can; since that costs about a dime. And the easy way to gut check this is if you are honoring a save labelled team and it costs more than a nickel of this week’s EV, the label is wrong. Don’t do it. If you’re still tempted to put a team in the vault, remember what the audit found in there, a lot of bones hanging around.

We’re coming to the part of the article again where everything we summarized seems like a lot. And it is, this survivor stuff isn’t easy. But that’s why I’m here! Every Friday this season, I’ll publish an ownership projection for the week. I’ll also include share-of-holders numbers and DIES Score like we discussed from Part 2. Now that we’ve finished off Part 3, I can reveal that it will also include our spend labels. Every Sunday morning I will update it with any late breaking news/trends. Every Tuesday I’ll grade it in public, so we can get ready to do it all again.

Tomorrow, the is Part 4 of the series, and I think it builds well on the equity share stuff we hit on at the end today. Many of you are not just playing one entry, you’re playing a full book. Your ten or twenty or 100 entries have a crowd problem of their own, and when one December seat is worth $381,000, how you built the ten in September is the whole ballgame.

Let’s think about this for a second, we learned in Part 1 that the closing line is the best number anyone has. We proved that in sixteen seasons of data that nobody beat it. Yet every week during the course of a survivor contest, the public walks away from that number. Not randomly. Not in reaction to anything that actually happened that year. On a schedule, like clockwork.

This isn’t just a free-pool thing either. The blue line on that chart is the Circa field where every seat costs $1,000. It mirrors the same walk.

Price can’t explain the crowd abandoning price. Something is steering this phenomenon, it gets stronger every single week, and by January it’s the only thing left driving.

This article is about figuring out what that something is, and why the answer splits “chalk” into three different things that die at three different rates.

Show Me The Data!

In order to figure out what the field does, we need per-entry level data. This is where the folks at PoolGenius come into play, as they have made this data available for the last six years of the Circa Survivor contest:

• Every entry in the contest from 2020 through 2025, all 53,714 of them

• Over one million pick-slots: every selection per user, in the order it was made

• Every elimination, datable to the exact week it happened

• The 2025 field alone: 18,694 entries at kickoff, 49 alive by mid-December

Important to note that six seasons is only six seasons. The ownership numbers in this article are exact counts, but anything about weekly outcomes rides on roughly a hundred contest-weeks. Second, this is only one contest, and it’s generally a really sharp one. Back in Part 1, I warned you the free pools skew softer than the contests I write about. This should align much better: $1,000 a seat, no re-entry, full of people who do this seriously. Third, this contest forces special Thanksgiving and Christmas picks which are distant cousins to the double pick weeks we are going to see on Splash Sports, but not the same animal, and both deserve real treatment. I've set holiday slates and multi-pick strategy aside for their own article outside this intro series, because they'll matter a lot for us this season.

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Two Suspects

There are really only two forces that could drag a crowd off of the best team on the board, and they both live in the one main rule of survivor: you can only use a team once.

The first is the more obvious one. The board shrinks. Every week, the field burns their best option, and by midseason the slate you’re actually choosing from looks nothing like the slate being talked about on TV. Which leads us to the hypothesis that maybe the crowd isn’t actually abandoning the best team, they just can’t have it anymore.

The second is a little sneakier and much more psychological. People hoard teams. They see Kansas City at -9 this week and they’re already thinking about Week 15. They’re not picking from this week’s board, they’re picking from an imaginary board three or six or nine weeks out.

Combining these two forces, produces three different kinds of piles:

Quality chalk. The pile is on the best team on the board. The crowd and the market agree.

Forced chalk. The pile is on the best team the field can still use. The crowd would love the best team, but they already burned it in September.

The dodge. The pile skipped a best team most of the field could still use, on purpose, to save it for later.

So the same word “chalk” can really be describing three totally different situations. And here’s the callback to Part 1 that they don’t behave the same: remember that 65-70% band, the one row in the price chart that flirted with being real? Split those teams by ownership and the entire miss lived in the popular ones. Price didn’t kill those teams. Something about why they were popular did.

To sort quality chalk from forced chalk from a dodge, you have to know what every surviving entry already burned. That’s where the per-entry ledger comes into play, let’s put it to work.

The Hidden Denominator

Raw ownership is just a fraction wearing a deceptive little trench coat. When a pick projection page says a team is at 20%, that’s only the numerator talking. The denominator, who can still actually pick this team, is nowhere on the page, and by the middle of the season it’s doing all of the work.

Now that we have every entry’s full history, we can finally ask the question the right way. Not what share of the field picked this team. What share of the entries that still had it available picked it. I’m calling this the share-of-holders. Here’s what it shows, on favorites at comparable prices:

Check out that bottom row. A favorite that fewer than 15% of entries can still use draws 7.6% of the field. On the surface that looks like the crowd shrugged and moved on. But, look at the red bar: 72.7% of the entries that could still take it, took it. Nearly three of every four. At the top of the chart, fresh teams at the same price get used by one in every four. Pretty massive difference.

That’s the funnel, and once you see it you can’t unsee it. Scarcity drains a team’s raw ownership about half as fast as it drains the team’s availability, because the survivors who still hold it pile in harder the scarcer it gets.

This serves as a great preview of where this blog is headed during the regular season. Every ownership number you've ever seen published is using share-of-field, because share-of-field is the easiest thing to compute from public data. The funnel we just displayed lives in share-of-holders, and you just witnessed what it hides: a 7% team that's actually a 73% team underneath. My plan for this season is to publish share-of-holders data for the all of the main Splash Sports survivor contests, alongside my ownership numbers. You'll be able to see this denominator all season long.

Back to the problem in front of us, because the funnel just proved something with teeth: the ownership number on the page can't be trusted to mean one thing. Time to show what that breaks.

Speaking of Splash Sports, I’ve partnered with them for the 2026 season. Promo code JBB gets you a 50% deposit match and a 100% QuickPicks payout boost. I’m also running my own survivor contest built to mirror the structure of their larger ones. Sign up here.

Let’s Grade the Piles How Part 1 Taught Us

Here's exactly what the funnel breaks. If the same 20% can be a fresh team the crowd likes or a cornered team the survivors got funneled into, then any rule built on ownership alone is hard to trust. So let's stress-test the oldest ownership rule in the sport with a phrase you’ll hear constantly this season: “fade the chalk.”

If fading the chalk works, heavily-owned teams should die more often than their price says. That’s the whole theory. So before you look at the next numbers, ask yourself what you’d expect the penalty to be. Five points? Three?

Here it is, across every favorite in six seasons, by ownership band:

1-5% owned, died 0.8 points more than priced

5-15% owned, died 2.3 points less than priced

15-30% owned, died 0.4 points less than priced

Over 30% owned, the true chalk, died 0.9 points less than priced

Every one of those gaps is inside the noise. Zero signal. And notice the punchline hiding in the list: if anything, the most-owned teams died slightly less than expected, and the least-owned died slightly more. "Fade the chalk" as an ownership rule simply isn't well supported.

Which is exactly what the funnel predicted, by the way. Ownership can't grade a pile because ownership doesn't know why the pile exists. But we do. We named the three whys at the top of this article: quality (the pile is on the best team), forced (the best team the field has left), and the dodge (skipped a better team to save it). The why is where the money is, and now we can finally put a price tag on each one.

The right question is what the pile costs. Part 1 gave you the metric for that, EV, and with every entry’s actual position I can compute it exactly. No projections, no hindsight. Just an answer to this simple question: at the moment of purchase, was joining the pile a good trade?

Quality chalk is the trade. When the crowd’s pile sits on the best team on the board, the pile’s EV averages 1.063 against 1.049 for the best alternative. The pile is the board’s best buy, and it’s within a nickel of the best in 82.5% of those weeks. Joining it costs you nothing. Fading it costs you real money.

Forced chalk surrenders about 15 cents on the dollar. When the field is cornered onto the best team it has left, that pile averages 1.001 while the board’s best sits at 1.149. Not because the team is secretly bad but because a better trade existed and the pile isn’t on it.

The dodge is below break-even. When the crowd skips a fresh, better team on purpose, its pile averages 0.954, a losing trade before a single game kicks off, while a 1.143 sits right there on the board. In only 5% of dodge weeks was the pile anywhere close to the best buy.

This pattern seemed a little too good to be true, so I pushed on it from a few different angles before trusting it. Instead of just looking at the biggest pile each week, I classified the top three and it still held. I moved the ownership cutoff around from 10% to 15% to 20% and the numbers barely nudged. The reason for the pile is everything. Its actual size does almost nothing.

There’s technically a fourth pile hiding in that cut, and it’s an honest one: piles that took the second-best team at basically the same price. This decision costs a small toll, eight to eleven cents, but getting different has to come with it’s costs. We’ll revisit this in more detail during Part 4 of our series.

Don't hear something I'm not saying. I am not claiming forced chalk and dodge piles lose more often than they should. They lose about as often as their prices say, which is the whole point of Part 1. What separates the three piles isn't the losing. It's that two of them were visibly worse trades before kickoff, and you didn't need hindsight to see it.

The Anatomy of a Dodge

Of the three piles, the dodge is the one that deserves an autopsy, because it's the only one the crowd chooses on purpose. Forced chalk happens to you, but the dodge is a decision. So let's take one apart and dissect what they took, what they skipped, and what each choice was worth at the moment they made it.

And that's the anatomy in one line: the eyes are on a future week, the hands take a worse team now, and the wallet pays twice, once in price and once in the company of everyone else doing the same thing.

Week 15 of 2022 is the poster child. Washington sat at .66, and 53% of the field took them at an EV of 0.87. Meanwhile, Kansas City was on the board at .86, available to almost everyone, at an EV of 1.43. Seven percent took it. The crowd chose a below-break-even trade over the best trade of the entire season, on purpose, to save a star rating.

Across the 40 dodge weeks in the record, the skipped team was broadly available 72% of the time, had more future value than the pile in 85% of cases, and the price paid to preserve it averaged 10.4 points of win probability. The crowd hoards. Everywhere, always.

Remember the exchange rate from Part 1: one point of ownership is worth about four-tenths of a point of win probability. The dodge pays ten points of price to stand in a different crowd, and the crowd it joins is convergent leftovers. It’s the worst trade in survivor, and it happens on a schedule.

Whether all that saving ever pays itself back is the entire subject of my Part 3 article that posts tomorrow. Spoiler: bring your popcorn.

DIES: The Board's Warning Light

Everything so far grades individual piles. I went a step further and created a one-number read on the entire board, and it’s probably the most practical thing in this whole article.

A team’s DIES score is its ownership times its chance of losing. In other words, how much of the field it would take down with it. Sum that across every team drawing real ownership (5% or more) and you get the board’s DIES score: how much of the field is standing on trapdoors this week, priced at the market’s own numbers.

Here’s how it graded out across six seasons of the contest. When DIES came in under 15, a massacre (a quarter or more of the live field eliminated in one week) happened zero times. Between 15 and 20: 22% of weeks. Between 20 and 25: 43%. And over 25: 71% of those weeks turned into massacres, with a median kill of 41% of everyone still alive.

The best part: we will compute DIES score every single week, before anything locks. When it’s over 25, that alarms us that it is not the week to get clever. That’s the week to spend quality.

That’s A Lot, How Is This Actionable?

Start here: ask why it’s chalk before you ask how big it is.

Popular because it’s the best team? Join it, at any size. Popular because it’s the best team left? That’s a 15-cent toll. Pay it when you’re genuinely cornered, and know that you’re paying it. Popular because the crowd is saving something better? That pile is below break-even and you should never, ever be standing in it. Want to be different? Be different at the same price. The second-best team at a similar number costs a nickel or a dime; the dodge costs the farm. And most importantly when the board’s DIES score runs hot, spend your best available team and let everyone else get clever.

One rule above all, and it’s the one the receipts scream over and over: never dodge downward. Taking a worse team to save a better one is paying twice. Once in price, once in company.

I agree with you, it is a lot. But that’s why I’m here! Every Friday this season, I’ll publish an ownership projection for the week. As you see here in Part 2, that will include share-of-holders numbers and DIES Score. Every Sunday morning I will update it with any late breaking news/trends. Every Tuesday I’ll grade it in public, so we can get ready to do it all again.

In Part 3, the saving itself goes on trial. The crowd pays real money to put teams in the vault. Part 3 opens the vault and counts what’s actually in there. Most of it is bones that never see the light of day.

It's all about how you play the field baby!

Show Me The Data!

Shoutout to Survivor Grid which is a treasure trove of historical data about survivor pools. Here’s what I’ve compiled:

• Historical Ownership Data from 2010-2025 across four public pools (Yahoo, ESPN, OfficeFootballPool, and RunYourPool)

• 18,499 team-weeks the public actually picked a team more than 0%

• Over 75,000 spreads frozen as they stood each week, at every lookahead horizon from that week to 17 weeks out

• Total count of 777 pool-weeks graded

Now of course, there are some drawbacks to this data that I’ll bubble up now so we can work through it later. First, Survivor Grid publishes percentages not field sizes, so nothing counts active survivors or computes equity share. As we’ll see in a future article of this series, late-season dynamics swing hard depending on the pool you’re in, which is a nuance worth diving into. Second, these are free and low-stakes pools, whereas most of the contests I'll be writing about on Splash Sports skew toward a sharper crowd.

Speaking of Splash Sports, I’ve partnered with them for the 2026 season. Promo code JBB gets you a 50% deposit match and a 100% QuickPicks payout boost. I’m also running my own survivor contest built to mirror the structure of their larger ones. Sign up here.

The above chart highlights how often the public actually died compared to how often the closing line said they should. Left of the line means the public survived more than expected, right means they got wrecked more than expected. Anything whose whisker crosses zero is a pool where the market nailed it.

They all cross zero.

Yahoo is the longest run here, sixteen straight seasons, and it lands at less than half a point off. RunYourPool comes in at +0.03, which is pretty much dead-on perfect. ESPN is the worst of the bunch at -1.14 and it still isn’t close to meaning anything. Pool it all together and you get 18,499 team-weeks where the public died at 25.62% against an implied 26.07%. That’s a gap of 0.45 percentage points over sixteen years of NFL football.

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Averages are cool, but I’m grinding edges…

Sure, on average the market’s fine, but the easy answer is survivor isn’t about averages. It’s about those weeks you’re staring at a board with no good options and you talk yourself into a 68% favorite. Everyone knows those picks are where you go to die and there’s a reason some people draw a hard line at 70% and refuse to go below it.

So I dug even deeper and broke it out by price. Every team-week, sorted by how strong a favorite it was and the actual death rate against implied.

Nothing. The 70–75% band, the one right on top of that famous line in the sand, died 0.92 points less often than its price implied, across 1,715 team-weeks. The bands above and below it flip in both directions and land nowhere. I'll flag the one row that looks like something: the 65–70% band died 5.67 points more often than implied, and its interval barely touches zero. On its own that's the closest thing to a real effect in this entire article. Neither neighbor shows a similar pattern, which means we're likely reaching if we draw a conclusion here. But I'll leave a hint: we're going to develop a way to spot bad chalk on a near-weekly basis, and it's not all about the price.

So that leaves the cost of a cheap pick exactly what it looks like: the actual gap in win probability between that team and the best team on the board. Nothing more, there’s no hidden tax underneath it. We see the same story play out across time.

Fifteen of sixteen seasons land on zero. The one that doesn’t is 2016, but one out of sixteen is about what you would expect at this confidence level. So there’s really no drift, no era effect, and no point where the public figured something out or forgot it.

Staring at those whiskers does tell you something, a single season of survivor picks swings about ten points in either direction, which tells you something worth carrying into the rest of this series: one season of anything is almost never enough to know what you’re looking at.

So if the market’s right about the games, what’s left?

There are a few different sites that actually try to tell you this every week, I just don't think enough people read it. Expected Value is the name of the game, and optimizing your equity share in the prize pool is how you give yourself a shot at making money. EV isn't a power rating, it's a calculation about the field that week.

Let’s start with the thing nobody really wants to talk about: your entry is probably going to die. In pretty much every scenario of every season ever, it dies. Once you get comfortable with this, the question stops being how do I survive every week and starts being how much company do I take with me as I go.

Think of your entry as being worth exactly 1.00 at the start of the week. EV is what it's worth when the week ends. Above 1.00 you gained ground, below 1.00 you lost it, and zero means you're out.

Every line on that chart climbs, because better teams are better teams. But look at the vertical gaps. In the 80–85% band, a team almost nobody picked carries a median EV of 1.16. Same odds, same week, over 30% ownership: 1.01. Fifteen points of expected value, and not one point of it has anything to do with the game on the field.

Week 13 of 2023 is about as clean an example as you’ll find. Jacksonville was priced at 79.0% and Dallas at 78.6%, functionally the same football game. Jacksonville drew 31.9% of the field while Dallas drew 0.8%. Same price but an EV of 1.10 versus 1.37.

Run these calcs across 276 weeks and the exchange rate comes out remarkably stable. One point of ownership costs you about what four-tenths of a point of win probability buys. Which means if a team is 10 points more popular, it needs to be roughly 4 points better just to break even.

Here's the best part about this whole exercise. Across those 276 weeks, the highest-EV pick on the board was also the highest win-probability pick only 55% of the time. Basically a coin flip. Nearly half the weeks of your season, the best team available is simply the wrong answer.

Which brings us back to that 65–70% band, the one row in the price chart that looked like it might be something. Split those teams by how many people picked them and the whole miss lives in the popular ones. That's not enough to hang anything on yet, but it's the thread I’m going to pull on in Part 2 of this series.

Now Comes The Fun Part

Your equity was never about how likely you are to advance. It’s how likely you are to advance while other people don’t.

That’s the whole reason I’m writing this series instead of another column telling you to take the Chiefs in Week 4. We’ve proven that the games are priced well. Sixteen seasons, four pools, and the public died within half a point of what the market said. To be clear, that doesn’t mean price doesn’t matter. It’s the input to everything I’m going to write about from here on out.

A 70% team still loses 30% of the time. The point isn’t that odds are unimportant, it’s that they’re correct which means there’s nothing left to extract from them. What’s left is the field, and the field is not priced by anyone. There’s almost no market on how many people are about to take the same team you are. That’s where the information gap lives.

Here’s my plan for the next week or so:

Part 2 takes on the biggest myth in this game, which is that you should fade the chalk. You shouldn’t, at least not all of it. There are three completely different kinds of chalk. One is basically free money, one is a toll you sometimes have to pay, and one is a losing trade before a single game kicks off. The difference has nothing to do with price, and that 65–70% thread is where it starts.

Part 3 is about saving teams for later, and why most of what you believe about it is a story you’re telling yourself rather than a number you can defend. I audited six years of saved teams. Most of them died in the vault, and I’ll show you exactly what the vault paid out when they didn’t.

Part 4 is about running more than one entry, which is a genuinely different game than running one, and most of the advice out there quietly assumes you’re doing the other thing. It turns out your own book has a crowd problem, and the data on what winning books did differently surprised me.

And then the season starts, and I start putting my money where my mouth is. Every Friday I’ll publish an ownership projection for the week. Every Sunday morning I will update it with any late breaking news/trends. Every Tuesday I’ll grade it in public, including the weeks I get it wrong, which will be plenty of them.

Show me the freakin’ data baby!

My current obsession: NFL Survivor Pools. With this one, I honestly think I’ve dove deeper than any project I’ve ever worked on here. Sixteen seasons of data from 4 different public pools. Then, to get even more granular I looked at six years of entry-by-entry picks from a $1,000 contest. Total of 53,714 entries and over a million weekly picks. There’s not a huge industry that is talking about survivor pools and strategy yet, and I am aiming to be a leading voice here.

Starting tomorrow, a four-part series:

Part 1: Nobody Is Wrong About the Games. Sixteen seasons say nobody beats the closing line. Everyone is focused on finding an edge in a place where it’s not.

Part 2: Three Piles. “Fade the chalk” is wrong. There are three kinds of chalk. One is free money, one is a 15-cent tax you sometimes pay, and one is a losing proposition before kickoff even happens.

Part 3: The Price of Later. I audited every “saved” team in six years. 80% died in the vault. The other 20% would have been better spent earlier.

Part 4: Books, Not Entries. Why your ten entries are really six, and what winning books actually did differently. This one is important for those of you mass entering survivor contests this season.

Then, when the 2026 NFL Season starts, my new content cadence takes over. My projections and analysis will be posted every Friday, updated bright and early on Sunday mornings, and graded in public every Tuesday. By now you know that transparency is one of my gold standards, and that transparency will continue with NFL Survivor.

If you’re playing this season, I’ve partnered with Splash Sports. Code JBB gets you a deposit match. They’ve also given me my own $10k contest to run this season, which you can sign up for here!

Not into survivor? Stick around anyway, I am sure you will enjoy some of my future obsessions. However, if the inbox clutter doesn’t work for you, no hard feelings, I don’t take the unsubscribe button personally!

Hope you’re along for the ride.

Jon (@JonBoyBeats)

Preseason Week 2 is upon us, and we only have 3 weeks left until the NFL season kicks off! Now is the time to lock into Underdog Fantasy and fire off as many Best Ball contests as you can. Each Friday I send out a newsletter recapping the different tools I use to define how the Best Ball landscape is evolving. Let’s dive into this week in review. (Apologies for missing last week, I was whitewater rafting the Lower Kern river…highly recommend!)

New Puppy? Same Puppy…and DK is Firing!

Underdog dropped the Puppy 3 this week, which has the same exact structure as The Fast Puppy. It doesn’t grade out the highest, but that 6 figure top prize has my interest peaked so I’ll be firing away a few entries I’m sure. BREAKING NEWS! The Chow Chow just dropped and it grades out as one of the best contests UD has dropped all summer. I think I’m gonna max this bad boy!

DraftKings is really ramping up their contest entries. Their SE, 3-Max, and 5-Max contests have historically graded out the best on my sheet. The Button Hook 2 scores a whooping 79.9 for the highest score of the season. I am not playing any action on DK this year (ain’t nobody got time for that), but if there’s any contests I am missing feel free to let me know!

“Scroll the Eff Down” Friday

I introduced this concept earlier this summer, so if you missed that article please feel free to read it here. Generally speaking, we are trying to identify the low-owned players who will help provide us leverage on the field. We can combine Establish the Run’s BBM ownership projections with Hayden Winks Percent Drafted optimization curves to help us solve for this.

With Best Ball Mania 5 being over 70% full at the time of writing this, the STFD list is really starting to head towards it’s final form. It’s actually super important at this stage that we can try and project out where ownership will land and we can do that based on ADP. I’ll spend some extra time on this section today.

Remove from your Ranks - These players are likely to land in the “Over-Owned” or “You’ve Scrolled Too Far!” bucket when the season kicks off.

RB - Roschon Johnson, Dylan Laube, AJ Dillon

WR - Darius Slayton, Treylon Burks, AT Perry

TE - Mike Gesicki, Colby Parkinson

Headed in the Wrong Direction - These players may land in the Sweet Spot, but it’s because of really negative movement towards end of summer, we want to avoid.

RB - Clyde Edwards-Helaire, D’Onta Foreman, Keaton Mitchell

WR - Devontez Walker, Zay Jones. Need positive news quick: Troy Franklin, Roman Wilson, Luke McCaffrey, Javon Baker

TE - Chig Okonkwo, Jelani Woods, Ja’Tavion Sanders

Start ABSOLUTELY FIRING - These players are going to land in the sweet spot and are coupling that up with positive movement at the right time.

RB - Will Shipley, Justice Hill, Jordan Mason, Eric Gray (maybe)

WR - Andrei Iosivas, Jalin Hyatt, Jauan Jennings (maybe), Jordan Whittington (maybe)

TE - Tucker Kraft, Dawson Knox, Theo Johnson, Greg Dulcich

ADP Velocity - We’ve got Movement!

Since training camp started, I have been utilizing this tool on a daily basis. I honestly cannot emphasize enough how useful it has been. As I introduced in mid-June, I think there’s a lot of nuance to be had in deciphering the ADP Risers and Fallers, and this provides the important context that we need.

You can see that the lists are getting longer, which is what we would expect at this point of summer.

When looking at the Topped Out category, I am generally trying to convince myself whether I am in or out on these players at their new cost. Here’s my current breakdown:

IN: James Conner & Chase Brown - Even though they’ve moved up, they are still in the right RB cohorts, so I don’t mind buying. Tyler Allgeier, Chuba Hubbard, Khalil Herbert - The later rounds RB group is getting pretty jumbled up but these guys are very solid.

OUT: JK Dobbins - If a guy with two torn Achilles buries me, he buries me. Jalen Tolbert - Just not sold the WR3 on Cowboys actually matters, plenty of cheaper options at WR later. Justin Fields - I get the upside, but I think he gets cheaper before summer is over.

The Still Rising and Still Falling categories are fun because it’s all about trying to be dynamic in your drafts. I’ll try and identify angles on how I’m playing these situations each week.

The Chiefs - I never though Isiah Pacheco was gonna be a guy who would bury me in the 4th round, so I certainly don’t think he’s gonna do it in the 3rd round. I have been trying to grab Mahomes doubles when I can, and that’s getting increasingly harder so I’m not prioritizing Chiefs WRs at the moment. The sweet spot was probably 2-3 weeks ago.

Tyler Lockett - Feels like a great target as he gets cheaper. Never really disappoints and still has a high ceiling. Not probably gonna win you BBM, but will definitely help you get thru the regular season.

Braelon Allen - Still way to damn cheap.

Greg Dortch - I think I’d rather take shots on Michael Wilson at his elevated cost than Dortch, preferred Dortch way later.

When looking at the Bottomed Out category, I want to look for players who I have been previously underweight on and see if their new cost makes sense.

Jonathan Brooks - I am absolutely gobbling this up. We have not gotten any new news on Brooks. Buy the dip!

Josh Downs & Xavier Legette - I still want Downs paired with Anthony Richardson whenever I can, but I’m not taking him unstacked anymore. High ankle sprain scares me. Legette has been a major target for me, I want to keep betting on 1st round draft capital at a cheaper price.

Drake Maye - Does not make sense. Keep buying. He’s still live to start Week 1 in my opinion.

Adjust The Ranks!

Every night, I cruise through the Coachspeak Index Twitter account and the 32BeatWriters.com Daily Article. I am looking for information that makes me want to adjust my ranks vs. information that is noise/double counting etc. Here’s a sample of the actionable items I picked up on this week:

1. Is this year’s Puka on the same team as Puka?

2. Buy the Jahmyr Gibbs dip. Also buy the Tyrone Tracy dip.

3. Hollywood’s ADP probably needs to drop some more

4. I don’t have enough Tank Bigsby

5. Justin Watson is the 1:1 replacement for Hollywood?

Ready for the Jordan Love talk?

One of the more common things that I’ve heard this summer (may or may not be tied to me being very high on all Packers) is “Can all the Packers even pay off their ADP?” I’m not really claiming to know the answer here since the entire idea of paying off ADP is a bit of a muddy conversation to begin with, but enough talking let’s look at some numbers.

Below is a chart showing the where teams rank when you add up the Draft Capital associated with their Top “X” Players.

RANK: Top 3 - Packers 21st, Top 4 - Packers 18th, Top 5 - Packers 16th, Top 6 - Packers 15th, Top 7 - Packers 13th, Top 8 - Packers 12th, Top 9 - Packers 12th

As you can see they are generally being priced as a below-average NFL offense, which just doesn’t make sense to me. I want to highlight the 12 teams ranked above Green Bay when looking at the Top 7 Players by Draft Capital.

Elite QBs - KC, PHI, BUF, BAL, & HOU - These 5 teams have high priced weapons and QBs. Theoretically, when we are talking about paying off ADP it will be hardest for multiple weapons AND the QB from these teams to do it. Now the flip side is they also likely have the highest ceilings.

“Cheap QBs” but Multiple Weapons in first 3 Rounds - DET, SF, MIA, LAR, & ATL - These 5 teams have QBs going late, who should probably be viewed as good values, and they also have 2-3 guys going super early in drafts. Through this lens, it makes a lot of sense that the QBs could pay off ADP, but it will be harder for multiple weapons to do it.

“One Elite with a Good QB” - ARI, CIN - Both of these teams have a WR getting drafted in the first round and QBs that are outside of the Elite QB grouping. If you expand the early rounds a bit further, we can add in Higgins and McBride in R4. I view these teams as a nice sweet spot. Relative to the teams above, these teams have a better chance at QB + Multiple Weapons paying off ADP.

The Packers - The first players for the Packers come off the board in Round 5 (Josh Jacobs and Jayden Reed), and their QB Jordan Love gets drafted after 7 of the above listed QBs. Cheap Weapons + a Cheaper QB = a very clear path for lots of folks to pay off ADP.

Insert really cool line tying all of this back to the click bait headline and telling you to bet on Jordan Love for MVP.

Reviewing the balance of the list, there aren’t many teams that mimic Green Bay, but the Jacksonville Jaguars and Seattle Seahawks come pretty close.

For context, here’s the same chart but only looking at WRs. Here’s how the the Packers rank: Top 2 - 17th, Top 3 - 12th, Top 4 - 10th, Top 5 - 9th.

Peace, Love, and Best Ball

PS: Come hang with me tonight on Friends of Best Ball with Megan Shoup!

Each Friday (sometimes Saturdays) I send out a newsletter recapping the different tools I use to define how the Best Ball landscape is evolving. Let’s dive into the week in review.

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A Rottweiler and a Dachsund walk into a bar…

Underdog released The Rottweiler and The Dachsund, two more contests that nuke out the min cash and make you get to Round 3 before tasting any of the winnings. The Rottweiler is a $25 contest with a 4 entry max that is a 2/12 → 2/10 → 2/10 advancement. The Dachsund is an $8 contest with a 4 entry max that is a 2/12 → 1/5 → 1/6 advancement. These are the 3rd and 4th best graded smaller entry contests on Underdog this season, and it seems like they are really centering in on the sweet spot for this new structure style. These are fun ones to hop into if you are trying to save your BBM bullets for later.

“Scroll the Eff Down” Friday

I introduced this concept about a month ago, so if you missed that article please feel free to read it here. Generally speaking, we are trying to identify the low-owned players who will help provide us leverage on the field. We can combine Establish the Run’s BBM ownership projections with Hayden Winks Percent Drafted optimization curves to help us solve for this.

Welcome to the bright lights of the STFD club Tank Bigsby! In this case Tank is entering the Sweet Spot from the negative direction, being more highlight drafted earlier in the summer, but now the market is cooling after seemingly lack of news out of training camp. I highlighted Tank today, because I think it’s important to distinguish the slight differences in players who make this list.

We can take a look at some of the ADPs listed for the WR group and make some assumptions for how long guys are going to be stating on this list. DJ Chark has caught some steam after being the reported WR3 in Chargers camp, so he’s quickly not even going to be showing up on this list anymore. Greg Dortch is another example of a guy who is going to be moving up into and then straight through the “overdrafted” territory. The guy I want to spend my time focusing on this week is Andrei Iosivas from the Bengals. You can see right now he’s only a 7% drafted player in BBM, but his ADP rise is going to lead him to being in the sweet spot for the better part of the next two weeks. I want a lot of him.

No huge updates to the TE group. I’d still rather be done with the position by here, however there continues to be positive news out of early camp reports on Michael Mayer, Dawson Knox, and Greg Dulcich.

ADP Velocity - We’ve got Movement!

Since training camp started, I have been utilizing this tool on a daily basis. I honestly cannot emphasize enough how useful it has been. As I introduced in mid-June, I think there’s a lot of nuance to be had in deciphering the ADP Risers and Fallers, and this provides the important context that we need.

You can see that the lists are getting longer, which is what we would expect at this point of summer.

When looking at the Topped Out category, I am generally trying to convince myself whether I am in or out on these players at their new cost. Here’s my current breakdown:

IN: Chase Brown - I think this represents a good time to try and get overweight on the Bengals seeming RB1 if you have previously been underweight. The highlights and reports out of camp continue to be super positive but he’s stalled out in ADP. I would be willing to bet that Brown’s ADP flips Zack Moss by the time summer is over, so use this as a good signal to start loading up.

OUT: Everyone else - I am largely underweight on every other player on this list and don’t envision myself starting to draft them more now that they are all more expensive. JK Dobbins gives me the most FOMO on this list, but not really.

The Still Rising and Still Falling categories are fun because it’s all about trying to be dynamic in your drafts. I’ll try and identify angles on how I’m playing these situations each week.

Tyler Allgeier & Deneric Prince - The price delta between these two is pretty steep, however both share the similarity of seemingly great standalone value as RB2s in explosive offenses. Of course they both have pretty big contingent upside. I am focusing mostly on Prince since I don’t have much, but I will keep adding to my Allgeier bags at these new prices.

Jermaine Burton and Andrei Iosivas - I would be targeting both of these players, but approaching them differently. Reaching for Yoshi in R17 is perfectly fine, while pushing Burton as much as possible past his ADP is a great opportunity as well. At the end of the day, Burton is still an untapped rookie in a good offense so we want to take shots on him in our lineups.

DeAndre Hopkins - I’m a little bit biased here because I love Hopkins and have a lot of Titans, however I would expect that he’s going to fall farther than he should due to this knee sprain. His ADP being shaken up for what could end up being only 2 weeks of drafting time could be really beneficial to gather some unique combos of him. I still think he belongs at the end of the “good” WR tier (Jamo, Samuel, Addison, Coleman, JSN) and he has already been falling past that.

Nick Chubb - Funny how the PUP listing overrode the squatting videos in the markets. The reality is that nothing about Chubb’s situation has changed, so if he’s starting to fall again now is a good time to start drafting again.

When looking at the Bottomed Out category, I want to look for players who I have been previously underweight on and see if their new cost makes sense.

I still believe that Kendre Miller is undraftable. If the market is giving him a 2.5 round discount and calling it good enough, I think we just let our competitors keep hopping on that grenade.

Mike Williams is probably too cheap right now. The de facto WR2 in an Aaron Rodgers offense and a guy who might end up being fully ramped up by Weeks 4 thru 6? Sign me up. (I’ve already been signed up since ADP of 99).

Luke McCaffey and Devontez Walker seem like two more rookies we should be buying regardless of what offense they are currently practicing with in Week 1 of training camp. Long summer ahead to prove themselves as rookies, and the exact kind of bets that we want to make.

Adjust The Ranks!

Every night, I cruise through the Coachspeak Index Twitter account and the 32BeatWriters.com Daily Article. I am looking for information that makes me want to adjust my ranks vs. information that is noise/double counting etc. Here’s a sample of the actionable items I picked up on this week:

1. If Marshawn Lloyd starts falling because of the Rotoworld blurb, start buying

2. Seems like Justice Hill should definitely be getting drafted

3. The drumbeat for Jameson Williams is starting to get pretty loud

4. I’m not yet ready to do the Alec Pierce thing again, but I’m closely monitoring

5. I’m too low on Rashid Shaheed

6. Last year I was promised Jalin-Hyatt-the-explosive-play-guy, maybe this year?

That’s all!

Peace, Love, and Best Ball

Each Friday I send out a newsletter recapping the different tools I use to define how the Best Ball landscape is evolving. Ideally, as time permits (an 8-month old baby who is anti-sleep doesn’t help here), I’ll toss out a few longer form articles throughout the week as well.

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New Contest Alert!

Underdog released The Bulldog and The Corgi, two contests that are slightly unique in their structures. Both of these do not have min cashes, which I love. The Corgi is $5 contest that is a 2/12 → 1/10 → 1/5 advancement that doesn’t pay out until you make the Finals. Week 17 is truly all the matters. The Bulldog is a $75 contest is a 2/12 → 2/10 → 2/10 with a nice small 20 person final. Gotta make it to the 2nd round to make money here. Both do not grade well in the tool (because they take zeroes in categories being graded), however I love both of these structures and am excited to see UD switching it up every now and then!

“Scroll the Eff Down” Friday

I introduced this concept about a month ago, so if you missed that article please feel free to read it here. Generally speaking, we are trying to identify the low-owned players who will help provide us leverage on the field. We can combine Establish the Run’s BBM ownership projections with Hayden Winks Percent Drafted optimization curves to help us solve for this.

Last week I talked about Audric Estime being on the Braelon Allen timeline, and this week he’s up 16 spots in ADP and has the same ADP as Allen. Get on board while you can.

The WR group has still been pretty consistent throughout the offseason so far. I’ve noticed QBs being less available in R18 than usual, so I am trying to find stacking options here more and more. Jalin Hyatt is still the guy I say I want to click a lot and then don’t end up clicking enough. Click him!

I’m still pretty out on this TE group, I’d rather be done with the position by here, however there has been positive news out of early camp reports on Michael Mayer, Dawson Knox, and Greg Dulcich.

ADP Velocity - Risers be Rising

Checking the ADP Velocity tool every day has been one of the most helpful things that I’ve added to my routine. As I introduced in mid-June, I think there’s a lot of nuance to be had in deciphering the ADP Risers and Fallers, and I think this tool does a really good job of providing context.

We’re definitely starting to get some action here, so let’s dive in a little bit further into each category.

When looking at the Topped Out category, I am generally trying to convince myself whether I am in or out on these players at their new cost. Here’s my current breakdown:

IN: Will Levis & Tyler Boyd - Gimme all the Titans possible, still too cheap. Nick Chubb - Squat Video makes ADP go brrrr, PUP list hopefully makes it drop again soon? I still want to have a lot of Chubb.

OUT: Dontayvion Wicks - I’m only writing him here so I can try and convince myself to stop clicking him at his new cost. He’s my highest owned player, I will probably still be drafting him a lot.

The Still Rising and Still Falling categories are fun because it’s all about trying to be dynamic in your drafts. I’ll try and identify angles on how I’m playing these situations each week.

Daniel Jones - Probably still underpriced by a couple rounds even if he doesn’t make it to Week 17. Definitely still underpriced by a couple of couple rounds if he plays Week 17.

Antonio Gibson, Troy Franklin, Malachi Corley, Braelon Allen, Javon Baker - These are all players I am very excited to see getting cheaper in price. Since ADP is a zero sum game, in order for some people to move up, it means some people need to move down (for no real reason). Important to be aware of that dynamic.

Jordan Addison, Ricky Pearsall, Kendre Miller - No real reason to target hurt (or probably suspended) guys if they are still falling. Just wait it out.

Josh Palmer & Rashod Bateman - Already wasn’t planning on drafting a lot of these guys, and now their cost is going up. No thanks!

When looking at the Bottomed Out category, I want to look for players who I have been previously underweight on and see if their new cost makes sense. I am in on all of these WRs, except for QJ.

Fun little caveat seeing the course correction on Christian Watson and Javonte Williams. I’m still buying both of them.

As you can see this week, the Rising/Falling categories are way bigger than the Topped/Bottomed categories. This makes sense, we are starting to get real news and ADP is definitely moving and shaking. Fun little validation for me that this tool works as intended!

Adjust The Ranks!

Every night, I cruise through the Coachspeak Index Twitter account and the 32BeatWriters.com Daily Article. I am looking for information that makes me want to adjust my ranks vs. information that is noise/double counting etc. Here’s a sample of the actionable items I picked up on this week:

1. Kendre Miller might be undraftable until further notice

2. Andrei Iosivas should be in your ranks and getting clicked

3. So should Mack Hollins…

4. We’re all probably way too underexposed to Anthony Richardson

5. I need to draft way more JK Dobbins

Portfolio Review - Running Back Rooms

As the NFL trends towards more and more Running Back By Committees (RBBC), I think it probably means that we need to be a little bit more cognizant of our exposures across the team RB rooms. Here’s where I’m currently at across all 32 teams and how I want to keep approaching them to finish out the summer.

Exactly where I want to be

Need to get my numbers up on both

Need to Pump the Brakes on both

Lot of the Late Round Guy, Need more of the Early Round Guy

Lot of the Early Round Guy, Need more of the Late Round Guy

At the Field or Fading

Have a good weekend peeps!

Peace, Love, and Best Ball

Each Friday I send out a newsletter recapping the different tools I use to define how the Best Ball landscape is evolving. Ideally, as time permits (an 8-month old baby who is anti-sleep doesn’t help here), I’ll toss out a few longer form articles throughout the week as well.

Subscribe now

“Scroll the Eff Down” Friday

I introduced this concept about a month ago, so if you missed that article please feel free to read it here. Generally speaking, we are trying to identify the low-owned players who will help provide us leverage on the field. We can combine Establish the Run’s BBM ownership projections with Hayden Winks Percent Drafted optimization curves to help us solve for this.

My favorite STFD clicks lately at the RB positions have been Audric Estime and Will Shipley. Unfortunately, Estime feels like he’s starting to gain some steam and will likely make his way into the Braelon Allen category (old STFD candidate, but now 72% owned).

As you can see, the WR group has been pretty consistent throughout the offseason so far. I would be trying to add these guys on as R18 stack options if possible. Jalin Hyatt and Greg Dortch have been my preferred clicks.

The Tight End group is a pretty fun one for STFD. The ADP chasing guys talked late round TE on their show last week, and hit on a lot of these guys. I am personally usually done at TE by R17/R18 but if you need an emegency click, this is the list you should be targetting.

ADP Velocity - The Storms a Brewin’

Checking the ADP Velocity tool every day has been one of the most helpful things that I’ve added to my routine. As I introduced in mid-June, I think there’s a lot of nuance to be had in deciphering the ADP Risers and Fallers, and I think this tool does a really good job of providing context.

We’re definitely starting to get some action here, so let’s dive in a little bit further into each category.

When looking at the Topped Out category, I am generally trying to convince myself whether I am in or out on these players at their new cost. Here’s my current breakdown:

IN: James Conner & Gus Edwards - still in parts of drafts I am heavily targetting RBs. Ja’Lynn Polk & Tyler Boyd - both emergency stack candidates for me. Juwan Johnson - still too cheap for a guy who’s supposed to be ready by start of the season,

OUT: Isiah Pacheco - As long as he’s being drafted near the first QBs and TEs on the board, I will be fading. DeMario Douglas & Demarcus Robinson - steam doesn’t appear to be based on anything?

The Still Rising and Still Falling categories are fun because it’s all about trying to be dynamic in your drafts. I’ll try and identify angles on how I’m playing these situations each week.

Christian Watson & Dontayvion Wicks - two of my highest owned players. I won’t be rushing to take ahead of ADP, but will still select when they fall.

Nick Chubb - have been at the field (7%) so far, and want to try and build an overweight position. Seems like a guy who could potentially be a 7th round pick with the right news.

CJ Stroud - I am always trying to push him since I think he should be closer to the Joe Burrow ADP.

Jordan Addison - no real reason to take him now. Risk seems too high and he’s going to keep falling.

When looking at the Bottomed Out category, I want to look for players who I have been previously underweight on and see if their new cost makes sense. Here’s my current breakdown:

Trey Benson & Blake Corum - similar situations (elite handcuffs), makes sense for me to start buying now.

Mike Williams - I’m pretty backwards on Big Mike, I took him a lot early on and all he’s done is drop. I expect with the PUP news he’s not actually bottomed out and will fall again.

Roman Wilson & Malachi Corley - We want to draft Rookie WRs. We want to draft late round WRs. We really want to draft late round Rookie WRs.

Exploitation Exploration

There’s enough discussion around drafting exploitatively. I think it’s one of my biggest edges during the summer. The reason it’s oftentimes hard to do, is because it requires you to have strong opinions, loosely held. My favorite spots to look for exploitative opportunities are within teams or within tiers. Today, we’ll focus on some team dynamics.

Generally speaking, these opportunities will present themselves because of new news. However, when things are changing based on no news, that’s really when we want to pounce.

Pretty easy opportunity to start taking some Trey Benson, if you’ve previously been underweight.

Opposite viewpoint here, seems like Javonte Williams would be the correct click right now.

Great time to start taking Anthony Richardson because his pass-catchers are getting cheaper.

If Jordan Addison misses some time, you would think it benefits one or all of Justin Jefferson, Aaron Jones, and TJ Hockenson. None of them have moved yet.

The market appears to be getting pretty confident about the Patriots pass-catcher situation after *checks notes* no new news.

Evidently, the beneficiary of Mike Williams starting camp on PUP is only Tyler Conklin, not Garrett Wilson and DEFINITELY not Malachi Corley.

If by some crazy chance the 49ers decide not to trade one of the best WR talents on their team who helped get them to a super bowl, now would be the time to buy Brandon Aiyuk.

That’s it for this week! I’ll see you in the Slow Puppy streets.

Peace, Love, and Best Ball.

Rookies report to NFL training camps in less than one week. We know that news is going to hit fast and ADP is going to start moving, so I wanted to make sure that Show Me The Data is ready for all the action.

Moving forward, I’ll be sending out a newsletter every Friday helping to recap some of the different tools that I use to get a feel for how the Best Ball landscape is evolving. Ideally, as time permits (a 8 month old baby who is anti-sleep doesn’t help here) I’ll toss out a few longer form articles throughout the week as well.

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Wen Puppy? Now Puppy

The Contest Comparison tool is probably the thing that I get asked the most about on Twitter. If you aren’t super familiar with the concept, I will be sending out an article later this summer trying to build what I think would be a perfect contest. In the interim, the quick explainer is that this is a tool that I use to try to determine how a contest ranks up against some of it’s peers. This can help for bankroll management throughout the summer.

Just this morning, Underdog released the Slow and Fast Puppy. For many different reasons, The Slow Puppy is one of my favorite contests that they have ever created. Ok, it’s actually mainly just one reason.

They took the top-heavy prize structure approach to both of these this season. While it’s hard to not love 6 figure prizes to first place, these contests are never going to grade out super well in my tool, since I weight “21st to 1st prize ratio” so highly.

These contests are very similar. Both follow the 2/12 → 1/10 → 1/10 advancement structure. The Fast Puppt (20 sec clock) is double the size and the ratio of the 5th and 21st place payouts relative to first place are both a little worse than the Slow Puppy. The big positive is that making the Finals in either of these guarantees that you make your money back, which is a fun addition UD has been adding this year.

“Scroll the Eff Down” Friday

I introduced this concept about a month ago, so if you missed that article please feel free to read it here. Generally speaking, what we are trying to identify is the low-owned players who will help provide us leverage on the field. We can combine Establish the Run’s BBM ownership projections with Hayden Winks Percent Drafted optimization curves to help us solve for this.

There’s been a lot of consistency with these charts over the past few weeks which is why I haven’t been tweeting them out a bunch, however with the upcoming ADP movement, this list should ebb and flow a lot too. For now, best to just familiarize yourself with the concept and try to target drafting a couple of the players in the Sweet Spot.

ADP Velocity - The Storms a Brewin’

Checking my ADP Velocity tool every day has been one of the most helpful things that I’ve added to my routine. As I introduced in mid-June, I think there’s a lot of nuance to be had in deciphering the ADP Risers and Fallers, and I think this tool does a really good job of providing context.

It’s honestly a pretty boring list right now, so I’m not going to spend too much time diving into it. Again, this is a good week to help get the fundamentals of the ADP Velocity report under your belt so when the big swings start happening, we know how best to assess them.

Diving into the Bookmark Bin

I am a big fan of the Jonathan Bales method (can’t find the actual quote/article) of trying to identify who the smartest/most reliable people are about certain topics and just following them blindly (almost). This allows you to spend more time on other things (like the above three tools). Of course with Fantasy Football, there’s pretty much no one that you can follow blindly, however here are some of the accounts that I have been getting the most value out of lately. Moving forward, I’ll try to include some data-driven tweets that I’ve bookmarked over the past week for any of my fellow SMTD who nerds want to dive in.

The Coachspeak Index - Incredible insight into whether we can take action based on what the coaches are saying, or whether we should proceed with caution.

32 Beat Writers - I subscribed to these guys a few weeks ago and have been absolutely loving the summary posts they put together outlining all of the actionable takeaways from beat writers for all 32 teams.

Majesstik1 - Jess is the creator of The Workbook over at One Week Season and he’s been dropping some really fun spreadsheets on Twitter looking at historical scoring data for all positions. Below is his WR tweet, but he’s got similar ones for all positions. I’m as big of a fan as anyone of spreadsheet screenshots posted to twitter that make you double tap, scroll around, and zoom in!

Happy Friday people. Enjoy the weekend, hopefully these Puppy contests don’t fill before Monday.

Peace, Love, and Best Ball!

One of my core tenants of best ball is exploitative drafting. This is especially important if you are going to be drafting consistently for the next 2.5 months. We want to be attacking ADP spots that may be short term, and avoiding new ADP spots that are gaining in market efficiency. Generally speaking, when there’s ADP movement, we want to determine what that means the market is doing, and then figure out the right way to try and exploit it.

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I created a new tool that I’m calling “ADP Velocity” which is geared at trying to categorize the player ADP movement and measure whether it is still moving or if it has plateaued out. It tracks the ADP delta over the last two weeks, and then measures the daily movement over the last one week, to help determine these categories.

Players who have Topped Out

These are all players who have seen their ADP rise over the past 2 weeks, but have started to taper off and likely have settled in on their current price. Most of these names are likely tied to “positive” news. The “Topped Out” category should identify that the current ADP is real. If you feel like you don’t want to pay the new price, feel free to push these players a few picks and see if they fall to you at closer to their old price.

Players who are Still Rising

Similar to the first category, a lot of these players will likely have “positive” news surrounding them. What’s important to delineate here is that the price is still going up. The “Still Rising” category should identify players who you will likely have to take before the current ADP if you want to get them in drafts. It can also identify a spot where you want to hold on until you see where ADP settles.

Players who are Still Falling

This is the exact opposite of the previous category. There has likely been some “negative” buzz around these players, and the ADP drop off has begun. It’s too early to call their new ADP efficient, and they should likely keep moving down draft boards. The “Still Falling” category should identify players who you can likely push to after their current ADP if you want to get them in drafts. It can also identify a spot where you want to keep holding on until you see where ADP settles.

Players who have Bottomed Out

These are all players who have seen their ADP fall over the past 2 weeks, but have started to taper off and likely have settled in on their current price. Most of these names are likely tied to “negative” news. The “Bottomed Out” category should identify that the current ADP is real. If you feel like you don’t want to pay the new price, feel free to push these players a few picks and see if you can squeeze a couple extra spots of value out of them.

Recently, Hayden Winks from Underdog Fantasy tweeted out some graphics that can really help quantify when and how far we should be scrolling down.

As I will end up doing very often here at Show Me The Data, I am now going to try and combine the work put forward by two very smart people and help quantify and make it actionable for the current draft landscape.

This is the STFD x SMTD collab you didn’t know that you needed!

Based on the information that Hayden provided in his graphics from the last 3 seasons of Best Ball Mania, I created 4 buckets for each position group.

• Over-owned: Based on Points Added data, these players are likely too owned given their potential range of outcomes. Better to just skip and focus on less owned guys.

• Sweet Spot: This is who you want to try and hammer in drafts.

• Also Good: These players are less good then the Sweet Spot, but also good still. Just not as good.

• You’ve Scrolled Too Far!: Jon would probably argue that there’s no limit to how far you can scroll, but based on the data, there surely is. These are the guys who are likely not adding any additional upside to your lineup.

Now that we’ve outlined the buckets, we can then utilize Establish The Run’s projected ownership data (updated daily) to figure out which players fall into which buckets.

Notes:

1. The Ownership data early in the summer will be a lot more swingy (and to a degree less impactful) then it will be once there are more drafts in the system, but it is still useful information.

2. I wouldn’t utilize the buckets as hard and fast rules (due to the spreadsheet nerd in me I need to organize it like that), but players in and around the fringes of the green buckets are still probably ok.

3. I am planning on compiling player trends over the next couple of weeks, so I would just view this as a good primer. Tracking this data over the next few weeks will really help us understand who are the best targets as we continue into summer.

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The first series of articles I am writing is going to include an overview of each of the 4 main positions in fantasy football. We are starting with QB, but RB, WR, and TE articles will closely follow. As always, I will be tailoring my content for Underdog Fantasy (Promo Code: JBB), and I’ll be reviewing all of the players based on tiers given their current Average Draft Position (ADP). The goal is to identify valuable draft targets based on historical performance data combined with 2024 projections (shoutout Mike Clay).

The Elite QBs (Tier 1)

Since the Elite QB tier is such an even playing field, I’ll spend this first section talking through some of the different metrics I include in these charts. First to the left is the ADP, Round, and associated Draft Capital which helps identify where the market believes there to be tier breaks.

Next up, are Points per Game metrics for Average, Ceiling, and Floor fantasy results. In all of these calcs, outliers are removed and they are slightly differentiated based on number of games played. Then, we have the frequency at which players scored above certain fantasy point thresholds (for QB this is 26, 28, 30, and 32 fantasy points).

Finally, we have the Weekly Percentile finishes, which compares a player’s weekly fantasy score to the average of the top 2 fantasy scores at their position and indicates how close to that top end range of outcomes they achieved in a given week. These numbers are then weighted and normalized against players within 1-2 adjacent tiers and we come up with the “Score” (workshopping this name still).

As you can see, one chart is based on historical data from the last 4 seasons, and the other chart is based on a very simple simulation (ppg projection randomized w/ historical player specific standard deviation) of 200 games (seems good enough?) from the upcoming season. We can review both of these data sets within tiers to see who separates themselves from the pack.

Historically speaking, Josh Allen has been a slight tier above this group in regards to fantasy output, so it makes a lot of sense why he is being drafted as the QB1. However, Jalen Hurts, Lamar Jackson, and Patrick Mahomes are really not that far behind in many of the metrics. All three are great consolation prizes.

CJ Stroud and Anthony Richardson don’t look as good historically #SmallSampleSize but they both possess elite simulation results. I really do not think there is a bad pick in this tier. I personally am trying to push Elite QB as late as possible (preferably 4th round or later), but am going to be loading up on all of these guys.

The Probably Over-Priced Guys (Tier 2)

While the Elite QBs are priced up in Rounds 3-5 based on past results, this tier of QBs is a bit more falsely propped up in large part due to stacking partners who are being drafted early. This is generally a cohort that I want to be cognizant of, and likely come in underweight.

Joe Burrow (Chase R1, Higgins R4), Kyler Murray (Harrison R1, McBride R4), and Dak Prescott (Lamb R1) all definitely have shown the ceiling outcomes in the past that we want from our QB1. However all of them score a bit lower then the Tier 1 group we just reviewed, and are likely being priced up due to their stacking partners. Dak is probably my favorite of this bunch, but I would highly recommend pushing him as far as possible down the draft boards once you draft CeeDee Lamb. He tends to slip quite a bit.

Jordan Love (Jacobs R4, Reed R5, Watson R8) and Brock Purdy (CMC R1, Aiyuk R2, Deebo R2, Kittle R6) are both in the historical #SmallSampleSize group and clearly both getting priced up based on their stacking partners. I have high hopes for these guys this season, however I would imagine their price is not very efficient.

As you’ll see throughout this series, I am largely going to be a *shrugs shoulders* guy when it comes to Rookies. There are plenty of other smarter people out there with better player takes. However, I would say that the sims data for Jayden Daniels and Caleb Williams is encouraging. However, it does feel like these guys are almost a tier too far ahead of the other rookies though.

The Likely League Winners (Tier 3)

We likely aren’t seeing a lot of 30+ point performances from this group, however they provide some really good metrics at a 4-7 round discount from the Tier 2 QBs.

The bull case for Tua Tagovailoa is pretty clear, Tyreek Hill + Jaylen Waddle = high ceiling outcomes. This is evident when comparing him to Trevor Lawrence and Jared Goff. All three have very similar points per game numbers, however Tua’s 28pt scoring threshold and 85%+ percentile outcome numbers are a tier above.

Justin Herbert might be the steal of the draft if we are only looking at the numbers. It wasn’t long ago (like literally 9 months), where he was routinely included in the Tier 1 conversation and ADP range. His historical numbers jump off the page within this group. However, he did lose Keenan Allen and Mike Williams, Quentin Johnston is #bad, and Jim Harbaugh is a very vocal proponent of #EstablishTheRun. I still want to be willing to swing for the fences by drafting Herbert.

Kirk Cousins, Matthew Stafford, and Aaron Rodgers bring up the rear in a very fitting cohort of old veterans with no mobility (and now much less healthy Achilles), but really strong floor outputs. Stafford grades our as the worst of this group and is likely being dragged up by the three stacking partners on his team that go in the first three rounds. Of course, Cousins and Rodgers are both essentially playing in brand new situations (unless you gained a lot of info from the Jets first 4 plays last year), so I assume there’s some uncertainty being weighed in to the ADP. I am very willing and eager to draft a lot of these two.

Unfortunately Watson is also looking like a pretty good value, but obviously significantly less fun to talk about him.

This group feels safe. They feel cheap. They feel comfortable. They are probably going to be the league winners. I would try to draft a lot of these guys.

If You Squint Hard Enough… (Tier 4)

It’s round 14, you’ve got a nice 1-4-7-1 build going and BAM you just got sniped on two straight QBs from Tier 3…you know what time it is. EMERGENCY BACKSTACK TIME!

I think it’s more fun to talk about these guys through the lens of…”what magic can I make happen over these next 4 rounds”, so here’s my current rankings:

• Drake Maye R17 + Ja’Lynn Polk R13 + Antonio Gibson R14 or Hunter Henry R14 + Demario Douglas R16 or Javon Baker R16 + Kendrick Bourne R18 or DJ Chark R18 or Brendan Rice R18 - I’m sure this is the first piece of content you are consuming that likes the optionality of a Patriots late round backstack. Just kidding, at least 34 other fantasy analysts are also talking about this, so I’ll save the word count.

• Daniel Jones R17 + Wan’Dale Robinson R15 + Darius Slayton R18 or Jalin Hyatt R18 or (Insert Giants TE here) R18 or Jelani Woods R18 - Everybody in the world things the Giants are going to suck this year from a fantasy standpoint, and what if they just don’t? Jones is not that far removed from a QB9 finish in 2022. I know a lot of people think he won’t finish the season as QB due to contract something yada yada, but a lot of people also thought Jalen Hurts job was in jeopardy going into the 2021 season. This isn’t a Jalen Hurts comp, this is a “we don’t know shit” comp.

• Bo Nix R18 + Jaleel McLaughlin R15 + Troy Franklin R16 or Marvin Mims R16 + Mike Gesicki R18 - Everyone is talking about Maye, but not many people are talking about the other rookie who is all but a lock to start football games in Week 1 of the 2024 season. Other options: Greg Dulcich R18 or Andrei Iosivas R18

• Will Levis R16 + Chig Okonkwo R17 + Tank Bigsby R18 or Tyler Boyd R18 - Reports are that the Titans are gonna toss the rock around the yard quite a bit this year and we know Levis has a gunslinger mentality. As long as you don’t care about interceptions (you shouldn’t), I think it’s wise to have Levis as a priority target this season. Of course, I much prefer him paired with multiple of Calvin Ridley R6, DeAndre Hopkins R7, Tony Pollard R9, or Tyjae Spears R10.

• Bryce Young R17 + Adam Thielen R16 + Bucky Irving or Cade Otton R15 - I am definitely buying the Dave Canales and Brad Idzik hype coming out of OTAs. The only problem is Bryce Young was just so bad last year. Other options: Chubba Hubbard R16, Ja’Tavion Sanders R18

• Baker Mayfield R14 + Bucky Irving R15 or Cade Otton R15 + Adam Theilen R16 - Obviously this becomes much better if you happened to land Mike Evans in R2 or Chris Godwin in R6. Other options: Jalen McMillan R18

• Geno Smith R15 + Khalil Herbert R16 + Noah Fant R17 - I really don’t think this is worth chasing if you miss out on all three of DK Metcalf R2, JSN R6, and Tyler Lockett R9. However, if you have some of the early Seattle WRs, I really like Geno a lot this year. Khalil Herbert W17 bring back is really the only reason I like this emergency stack (I’m big on Herbert).

• Derek Carr R17 + Juwan Johnson R14 + AT Perry R18 - This is the second year in a row where I’m not sure that Carr exists. Like I know he is in the player pool, I just never see him in my queue or on my teams. I would probably skip the AT Perry shot and instead grab Tre Tucker or Michael Gallup (or whoever emerges) as a Raiders bring back in R18.

• Justin Fields/Russell Wilson R17 + Calvin Austin R18 or Van Jefferson R18 - Uncertainty rules the day here with the Steelers QB position. Whenever we get more clarity and/or idea on potential number of games played, one of these guys will rise in ADP. I’m not so sure I care that much about trying to capture this value now. RBs or ‘Muth and move on for me.

• JJ McCarthy R16 - There is no viable emergency backstack partners at this time. We also do not know how many games he will start. I’m okay waiting until we have less unknowns later in summer.

• Gardner Minshew R18 - Another guy who we are not sure who the lat round options are at this point. Minshew doesn’t get drafted often, and doesn’t possess much of a ceiling, but it is worth noting that only 4 raiders get drafted in 100% of drafts right now. There is likely at least one or two more players that emerge as draftable before summer is over.

Well that wraps up the first article in the Show Me The Data rebrand. Please be on the lookout for the rest of the position groups over the next couple of weeks. If you made it this far ready through every viable emergency backstack option in drafts you should probably just click this button.

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