Mike Wolff

Practical founder/product leader constantly striving to create products that are elegant in their simplicity. Occasionally succeeding, but always learning.

[Mike Wolff @mrwolff369]

Nice work finishing 1st and 2nd in your survivor pool. Curious to hear how you approached making picks across your 5 entries to land both spots.

BTW, I built SurvivorPulse (https://t.co/CQVLqLeyQk) for people who play multiple pools and entries and want a better way to manage, coordinate, and game plan out picks across all of them to maximize overall survival probability, minimize correlated risk exposure, and better avoid wipeout weeks. Free access currently.

Given your success, would love to get your feedback.

[Mike Wolff @mrwolff369]

Ran the numbers on saving good teams for a better matchup down the line. Doesn't help you win, at any pool size we tested. Full thread: https://t.co/OjJBQe2UTa

[SurvivorPulse @survivor_pulse]

Post 3 of 6. Post 1 showed that Chalk survives longest but rarely wins. Post 2 showed that leaning slightly off the crowd beats Chalk. Today we're looking at whether adding future value to your picks actually helps.

The idea: instead of only weighing win probability and field exposure, also account for a team's future matchup quality, saving a good team now if a better matchup is coming for it later. We call this the 65/25/10 Future Value Blend: 65% win probability, 25% field exposure, 10% future value.

On survival, this is exact math, not a model. The Future Value Blend reaches week 9 alive about 9% of the time. Chalk is 15%, the Mild Lean is 12%, so the Future Value Blend is behind both. It does narrowly beat a heavier 70/30 blend, which sits around 8%.

There's a common worry behind wanting to plan ahead: you'll run out of good teams late in the season and get stuck with a bad one. We checked that directly, across all 10 seasons, using real schedules and betting lines. It never happens. Not one strategy was ever forced into a pick below a 55% win probability, and the single worst late-season pick in the entire dataset still cleared 58%. That's not the real risk.

On winning, the Future Value Blend is flat. We ran it against Chalk across all 10 real seasons, every pool size we track, and no pool size showed a real difference.

We went further this time and ran the Future Value Blend head to head against Chalk, the Mild Lean, and the 70/30 blend, all against each other directly, same seasons, same simulated pools, every possible pair. None of them separates from any other by a margin that clears season-to-season noise, at any pool size. That includes the Mild Lean against the other three, checked directly this time instead of inferred from separate comparisons against Chalk.

So the honest read: on survival, don't go further than the Mild Lean, it costs you real ground. On winning, we don't have evidence that any of these four approaches beats the others, Mild Lean included.

We're not done testing this. Next post, we look at what happens when you push field exposure a lot further, all the way to weighing it as heavily as win probability itself (aka the Heavy Contrarian approach).

This is direction and statistical significance, not a dollar figure. Payoff numbers from this kind of modeling are inflated by construction, so we don't quote them, and you shouldn't trust anyone else's either.

Full methodology, plus links to Post 1 and Post 2, in the reply below.

[Mike Wolff @mrwolff369]

Wrote up our latest survivor pool backtest. This one tests fading the field as hard as possible, and it backfires badly. Full thread: https://t.co/0lo4AAufCb

[SurvivorPulse @survivor_pulse]

Post 4 of 6. Post 1 showed that Chalk survives longest but rarely wins. Post 2 showed that leaning slightly off the crowd beats Chalk. Post 3 showed that adding future value to your picks doesn't help either. Today we push field exposure a lot further, all the way to weighing it as heavily as win probability itself.

We call this the Heavy Contrarian approach: 50% win probability, 50% field exposure. We ran it through the same 10-season backtest we've used for every strategy in this series.

On survival, it's the worst one we've tested. Heavy Contrarian's chance of reaching week 9 alive is 4.0%. Every other template we've run, Chalk, Mild Lean, the 65/25/10 Blend, Max Equity, survives longer. Chalk alone reaches week 9 at 14.9%, nearly four times as often.

On winning, it doesn't make up for that. We ran a comprehensive head-to-head across all five strategies, same 10 seasons, same bootstrapped opponent fields, three pool sizes. Zero of 30 pairwise comparisons reached statistical significance. Heavy Contrarian specifically didn't separate from any of the other four strategies, at any pool size, on wins.

So pushing field exposure all the way to parity with win probability doesn't buy you anything on the winning side, and it costs you real ground on survival. Fading the crowd that hard just means fading good teams along with bad ones.

This closes out the strategy-by-strategy piece of this series. Next post, we look at how running multiple entries, and buybacks, changes things.

This is direction and statistical significance, not a dollar figure. Payoff numbers from this kind of modeling are inflated by construction, so we don't quote them, and you shouldn't trust anyone else's either.

Full methodology, plus links to Post 1, Post 2, and Post 3, in the reply below.

[Mike Wolff @mrwolff369]

Hey, your pool sounds cool. $875k pot is no joke. Do you usually get that many entries? Curious if a lot of players buy multiple entries? I built SurvivorPulse (https://t.co/dsXlp3opDr) to manage, coordinate, and game plan out picks across multiple pools and entries to maximize overall survival probability, minimize correlated risk exposure, and better avoid wipeout weeks.

Free access currently.

[Mike Wolff @mrwolff369]

@PlayThePools Hey, curious if you allow the same person to run multiple entries in your pool? I built a tool called SurvivorPulse (https://t.co/a2h2ZsJEYT) for managing picks across multiple entries if that's ever useful for you or your entrants. Free right now in early access.

[Mike Wolff @mrwolff369]

@Buffalo88888 @survivorgrid Hey, we track pick popularity & crowd exposure by team/week at SurvivorPulse (https://t.co/a2h2ZsJEYT) if you want a look while waiting on the grid. Free right now in early access.

[Mike Wolff @mrwolff369]

@survivor_pulse Built this because I was tired of guessing in my own pools. Ran the actual numbers on 5 seasons instead of trusting gut feel. The chalk-wins-zero part surprised me too. Curious what you're seeing in yours.

[Mike Wolff @mrwolff369]

@RingerRundown Nice, good luck running it. If you end up allowing multiple entries, I built SurvivorPulse for managing picks across entries, worth a look if that comes up: https://t.co/a2h2ZsJEYT

[Mike Wolff @mrwolff369]

@SurvivorSweat @CircaSports Congrats on the track record. Been studying how multi-entry survivor picks correlate in ways most players don't see. Built a back-tester that replays 2021-2025 seasons across entry portfolios with real field data. Would love to share what we found with your team.

[Mike Wolff @mrwolff369]

#NFLSurvivor #SurvivorPool

[Mike Wolff @mrwolff369]

To all serious multiple-entry NFL Survivor players...

Differentiating your picks across teams doesn't mean you're actually diversified.

Two picks can look different and still carry the same correlated risk.

Do you actively account for this, or is it pick-by-pick?

[Mike Wolff @mrwolff369]

@SurvivorSweat @CircaSports #CircaSurvivor

[Mike Wolff @mrwolff369]

Question for folks who run multiple entries in NFL Survivor pools.
Beyond avoiding the same team across entries, do you actively coordinate your picks as a portfolio -- or just take the best pick for each entry independently?
Curious how people actually handle this in practice.

[Mike Wolff @mrwolff369]

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