The Poll.ai

2025 season · through week 1

Too early to call this a ranking.

Ranked by how hard each record was to get against the schedule that produced it. No preseason poll, no reputation, no conference name.

Switch below and watch which teams move.

ProvisionalPROVISIONAL. THE POLL OPENS IN WEEK 5. SEE docs/constraints.md.
  1. 1Central Michigan1-01-0Gap +47.71 in 2key 0.18Ranked 1. The model replayed this schedule 1,000 times, and this team finished between 2 and 118 of 136 in 90% of them.
  2. 2Rice1-01-0Gap +47.01 in 1key 0.17Ranked 2. The model replayed this schedule 1,000 times, and this team finished between 2 and 119 of 136 in 90% of them.
  3. 3LSU1-01-0Gap +45.41 in 1key 0.15Ranked 3. The model replayed this schedule 1,000 times, and this team finished between 2 and 118 of 136 in 90% of them.
  4. 4Georgia Tech1-01-0Gap +45.01 in 1key 0.14Ranked 4. The model replayed this schedule 1,000 times, and this team finished between 3 and 119 of 136 in 90% of them.
  5. 5Auburn1-01-0Gap +44.11 in 1key 0.13Ranked 5. The model replayed this schedule 1,000 times, and this team finished between 2 and 117 of 136 in 90% of them.
  6. 6Wyoming1-01-0Gap +42.91 in 1key 0.12Ranked 6. The model replayed this schedule 1,000 times, and this team finished between 3 and 120 of 136 in 90% of them.
  7. 7Mississippi State1-01-0Gap +39.51 in 1key 0.08Ranked 7. The model replayed this schedule 1,000 times, and this team finished between 5 and 116 of 136 in 90% of them.
  8. 8California1-01-0Gap +39.11 in 1key 0.08Ranked 8. The model replayed this schedule 1,000 times, and this team finished between 5 and 117 of 136 in 90% of them.
  9. 9Iowa State2-02-0Gap +47.81 in 1key 0.08Ranked 9. The model replayed this schedule 1,000 times, and this team finished between 5 and 88 of 136 in 90% of them.
  10. 10Nebraska1-01-0Gap +55.31 in 1key 0.07Ranked 10. The model replayed this schedule 1,000 times, and this team finished between 9 and 127 of 136 in 90% of them.
  11. 11Utah1-01-0Gap +36.51 in 1key 0.06Ranked 11. The model replayed this schedule 1,000 times, and this team finished between 5 and 16 of 136 in 90% of them.
  12. 12Temple1-01-0Gap +35.41 in 1key 0.05Ranked 12. The model replayed this schedule 1,000 times, and this team finished between 7 and 17 of 136 in 90% of them.
  13. 13UNLV2-02-0Gap +53.81 in 1key 0.05Ranked 13. The model replayed this schedule 1,000 times, and this team finished between 11 and 87 of 136 in 90% of them.
  14. 14TCU1-01-0Gap +33.31 in 1key 0.04Ranked 14. The model replayed this schedule 1,000 times, and this team finished between 9 and 18 of 136 in 90% of them.
  15. 15South Carolina1-01-0Gap +50.51 in 1key 0.04Ranked 15. The model replayed this schedule 1,000 times, and this team finished between 11 and 127 of 136 in 90% of them.
  16. 16Tennessee1-01-0Gap +47.81 in 1key 0.03Ranked 16. The model replayed this schedule 1,000 times, and this team finished between 13 and 29 of 136 in 90% of them.
  17. 17Miami1-01-0Gap +64.71 in 1key 0.03Ranked 17. The model replayed this schedule 1,000 times, and this team finished between 17 and 135 of 136 in 90% of them.
  18. 18Washington State1-01-0Gap +64.41 in 1key 0.02Ranked 18. The model replayed this schedule 1,000 times, and this team finished between 18 and 134 of 136 in 90% of them.
  19. 19Wake Forest1-01-0Gap +64.21 in 1key 0.02Ranked 19. The model replayed this schedule 1,000 times, and this team finished between 20 and 135 of 136 in 90% of them.
  20. 20Kent State1-01-0Gap +64.11 in 1key 0.02Ranked 20. The model replayed this schedule 1,000 times, and this team finished between 18 and 134 of 136 in 90% of them.
  21. 21Rutgers1-01-0Gap +64.11 in 1key 0.02Ranked 21. The model replayed this schedule 1,000 times, and this team finished between 18 and 134 of 136 in 90% of them.
  22. 22Northern Illinois1-01-0Gap +64.11 in 1key 0.02Ranked 22. The model replayed this schedule 1,000 times, and this team finished between 19 and 135 of 136 in 90% of them.
  23. 23App State1-01-0Gap +46.21 in 1key 0.02Ranked 23. The model replayed this schedule 1,000 times, and this team finished between 14 and 31 of 136 in 90% of them.
  24. 24Ohio State1-01-0Gap +63.41 in 1key 0.02Ranked 24. The model replayed this schedule 1,000 times, and this team finished between 18 and 134 of 136 in 90% of them.
  25. 25Kansas2-02-0Gap +45.01 in 1key 0.02Ranked 25. The model replayed this schedule 1,000 times, and this team finished between 16 and 53 of 136 in 90% of them.

The right-hand number is how hard that season was to pull off against that exact schedule. One in 2 put Central Michigan on top. One in 1 was enough for 25th. Below about 1 in 5 it stops separating teams, which is what the smaller key underneath is for. The bar under each name is where the model kept landing that team out of 136, every bar on one scale. A typical bar this week spans 52 places.

2025 week 1 · 8d6a6e80 · code e215160 · The House Poll · method 061a6d4e · 136 teams ranked

Every column

The board above is the thirty-second version. Below it is everything the run published: the résumé, the power rating, the gap, the rank interval, and where the finished season puts each team.

Every figure the cards carry, for the 25 on the board, with nothing to click.
#teamrecordhow unlikely1 in this manyexpectedwins this schedule asked forbeat that bypowerrating (rank)gapplaces from the pollrangein 90% of replayshindsight
1Central Michigan1-01 in 20.7+0.312.3 (19)+47.72 to 118-33.0
2Rice1-01 in 10.7+0.313.0 (15)+47.02 to 119-20.0
3LSU1-01 in 10.7+0.314.6 (10)+45.42 to 118-2.0
4Georgia Tech1-01 in 10.7+0.315.0 (9)+45.03 to 119-15.0
5Auburn1-01 in 10.7+0.315.9 (7)+44.12 to 117-5.0
6Wyoming1-01 in 10.8+0.217.1 (6)+42.93 to 120-30.0
7Mississippi State1-01 in 10.8+0.220.5 (5)+39.55 to 116-6.0
8California1-01 in 10.8+0.220.9 (4)+39.15 to 117-25.0
9Iowa State2-01 in 11.8+0.212.2 (21)+47.85 to 88+7.0
10Nebraska1-01 in 10.9+0.14.7 (60)+55.39 to 127+1.0
11Utah1-01 in 10.9+0.123.5 (3)+36.55 to 16-9.0
12Temple1-01 in 10.9+0.124.6 (2)+35.47 to 17-71.0
13UNLV2-01 in 11.9+0.16.2 (53)+53.811 to 87-14.0
14TCU1-01 in 10.9+0.126.7 (1)+33.39 to 18-11.0
15South Carolina1-01 in 10.9+0.19.5 (40)+50.511 to 127-22.0
16Tennessee1-01 in 10.9+0.112.2 (20)+47.813 to 29-25.0
17Miami1-01 in 10.9+0.1-4.7 (105)+64.717 to 135+16.0
18Washington State1-01 in 10.9+0.1-4.4 (104)+64.418 to 134-29.0
19Wake Forest1-01 in 10.9+0.1-4.2 (103)+64.220 to 135-4.0
20Kent State1-01 in 10.9+0.1-4.1 (102)+64.118 to 134-38.0
21Rutgers1-01 in 10.9+0.1-4.1 (100)+64.118 to 134-5.0
22Northern Illinois1-01 in 10.9+0.1-4.1 (99)+64.119 to 135-37.0
23App State1-01 in 10.9+0.113.8 (13)+46.214 to 31-48.0
24Ohio State1-01 in 11.0+0.0-3.4 (96)+63.418 to 134+18.0
25Kansas2-01 in 12.0+0.015.0 (8)+45.016 to 53-3.0
Show the full table: top 25 of 136, every columnthe published poll
ProvisionalPROVISIONAL. THE POLL OPENS IN WEEK 5. SEE docs/constraints.md.
#teamunderline: 90% rank interval · league median width 52how unlikely1 in this many
1Central MichiganMid-American1-0·Power 12.25 (19)·Gap +47.75·▼33Ranked 1. The model replayed this schedule 1,000 times, and this team finished between 2 and 118 of 136 in 90% of them.0.1841 in 2
2RiceAmerican Athletic1-0·Power 12.99 (15)·Gap +47.01·▼20Ranked 2. The model replayed this schedule 1,000 times, and this team finished between 2 and 119 of 136 in 90% of them.0.1721 in 1
3LSUSEC1-0·Power 14.62 (10)·Gap +45.38·▼2Ranked 3. The model replayed this schedule 1,000 times, and this team finished between 2 and 118 of 136 in 90% of them.0.1491 in 1
4Georgia TechACC1-0·Power 14.96 (9)·Gap +45.04·▼15Ranked 4. The model replayed this schedule 1,000 times, and this team finished between 3 and 119 of 136 in 90% of them.0.1441 in 1
5AuburnSEC1-0·Power 15.92 (7)·Gap +44.08·▼5Ranked 5. The model replayed this schedule 1,000 times, and this team finished between 2 and 117 of 136 in 90% of them.0.1321 in 1
6WyomingMountain West1-0·Power 17.08 (6)·Gap +42.92·▼30Ranked 6. The model replayed this schedule 1,000 times, and this team finished between 3 and 120 of 136 in 90% of them.0.1181 in 1
7Mississippi StateSEC1-0·Power 20.45 (5)·Gap +39.55·▼6Ranked 7. The model replayed this schedule 1,000 times, and this team finished between 5 and 116 of 136 in 90% of them.0.0841 in 1
8CaliforniaACC1-0·Power 20.89 (4)·Gap +39.11·▼25Ranked 8. The model replayed this schedule 1,000 times, and this team finished between 5 and 117 of 136 in 90% of them.0.0801 in 1
9Iowa StateBig 122-0·Power 12.20 (21)·Gap +47.80·▲7Ranked 9. The model replayed this schedule 1,000 times, and this team finished between 5 and 88 of 136 in 90% of them.0.0761 in 1
10NebraskaBig Ten1-0·Power 4.75 (60)·Gap +55.25·▲1Ranked 10. The model replayed this schedule 1,000 times, and this team finished between 9 and 127 of 136 in 90% of them.0.0691 in 1
11UtahBig 121-0·Power 23.50 (3)·Gap +36.50·▼9Ranked 11. The model replayed this schedule 1,000 times, and this team finished between 5 and 16 of 136 in 90% of them.0.0601 in 1
12TempleAmerican Athletic1-0·Power 24.59 (2)·Gap +35.41·▼71Ranked 12. The model replayed this schedule 1,000 times, and this team finished between 7 and 17 of 136 in 90% of them.0.0531 in 1
13UNLVMountain West2-0·Power 6.23 (53)·Gap +53.77·▼14Ranked 13. The model replayed this schedule 1,000 times, and this team finished between 11 and 87 of 136 in 90% of them.0.0461 in 1
14TCUBig 121-0·Power 26.68 (1)·Gap +33.32·▼11Ranked 14. The model replayed this schedule 1,000 times, and this team finished between 9 and 18 of 136 in 90% of them.0.0411 in 1
15South CarolinaSEC1-0·Power 9.49 (40)·Gap +50.51·▼22Ranked 15. The model replayed this schedule 1,000 times, and this team finished between 11 and 127 of 136 in 90% of them.0.0401 in 1
16TennesseeSEC1-0·Power 12.22 (20)·Gap +47.78·▼25Ranked 16. The model replayed this schedule 1,000 times, and this team finished between 13 and 29 of 136 in 90% of them.0.0281 in 1
17MiamiACC1-0·Power -4.65 (105)·Gap +64.65·▲16Ranked 17. The model replayed this schedule 1,000 times, and this team finished between 17 and 135 of 136 in 90% of them.0.0261 in 1
18Washington StatePac-121-0·Power -4.44 (104)·Gap +64.44·▼29Ranked 18. The model replayed this schedule 1,000 times, and this team finished between 18 and 134 of 136 in 90% of them.0.0251 in 1
19Wake ForestACC1-0·Power -4.16 (103)·Gap +64.16·▼4Ranked 19. The model replayed this schedule 1,000 times, and this team finished between 20 and 135 of 136 in 90% of them.0.0241 in 1
20Kent StateMid-American1-0·Power -4.14 (102)·Gap +64.14·▼38Ranked 20. The model replayed this schedule 1,000 times, and this team finished between 18 and 134 of 136 in 90% of them.0.0241 in 1
21RutgersBig Ten1-0·Power -4.07 (100)·Gap +64.07·▼5Ranked 21. The model replayed this schedule 1,000 times, and this team finished between 18 and 134 of 136 in 90% of them.0.0241 in 1
22Northern IllinoisMid-American1-0·Power -4.06 (99)·Gap +64.06·▼37Ranked 22. The model replayed this schedule 1,000 times, and this team finished between 19 and 135 of 136 in 90% of them.0.0241 in 1
23App StateSun Belt1-0·Power 13.79 (13)·Gap +46.21·▼48Ranked 23. The model replayed this schedule 1,000 times, and this team finished between 14 and 31 of 136 in 90% of them.0.0221 in 1
24Ohio StateBig Ten1-0·Power -3.39 (96)·Gap +63.39·▲18Ranked 24. The model replayed this schedule 1,000 times, and this team finished between 18 and 134 of 136 in 90% of them.0.0221 in 1
25KansasBig 122-0·Power 14.98 (8)·Gap +45.02·▼3Ranked 25. The model replayed this schedule 1,000 times, and this team finished between 16 and 53 of 136 in 90% of them.0.0191 in 1

What this board believes football results are for

The House Poll, in its own words

This is the poll this project publishes and this recipe changes nothing about it. Margin counts, and it counts less and less as it grows: the response is C*tanh(m/C) with C at 32 points plus a 7 point win premium, so the gap between a 3 point win and a 24 point win is large and the gap between a 45 point win and a 70 point win is almost nothing. There is no cliff anywhere for a coach to aim at, which is what tanh buys over a hard cap. Then the headline does not read margin at all. Teams are ordered by schedule odds, the probability that a team of published reference quality would have gone at least this well against this exact schedule, and the harder it was to do what you did the higher you go. Margin is in the engine because it carries real information about how good a team is. It is out of the headline because the headline is about what a team earned, and those are two different questions that deserve two different columns.

what it costs

  • An unbeaten team can finish behind a one loss team, and that will need explaining every single year. It is the direct consequence of the promise. The explanation is on the page: the tail probability, the reference team it was measured against by name, and the Power column beside it.
  • One published constant the wins based resume did not need. q_ref is the Power rating of the 25th ranked team that week, the least flattering defensible reading of ESPN's average Top-25 team. The study measured the ordering across a 16 point swing in it: Kendall's tau never fell below 0.985 and at most one team entered or left the top 25.
  • It loses forward ordering accuracy to Full Merit by about two points. Accepted, and for a stated reason: forward accuracy is a prediction metric and the headline poll is not the instrument this project ships for prediction. L3 Power is, and it beats all three orderings on that axis.
  • It is a compromise and it will satisfy neither end of the argument completely. Someone who believes margin is the only honest measurement will find the compression arbitrary, and someone who believes point differential should never pay will find 32 points of it far too generous. Both are reading the position correctly.

what it changed

Nothing at all. This is the poll this project publishes and this recipe changes none of it.

configs/recipes/house.toml

same evidence, different valuesEvery board on this page was fitted on the same 141 games, and the digest of that exact frame is 814cc4abdee3 under all three. Switching lens changes the constants above and nothing else. Method digest for this one: 061a6d4eda23.

Where next

  • Tune it yourself Move one setting and watch the board move.
  • The revision What this week looked like once the season ended.
  • Connectivity How much of the field was comparable, and what held it together.
  • Methodology Every constant, every baseline, and the lines that say FAIL.
run 8d6a6e80 · published 2026-08-19 23:10:36 UTC · code e215160 · config 1ef7cf23…
q_ref 11.31 (James Madison) · β_w 7 · C 32 · h 17.467 · σ 15.300 · λ₁ 325 · λ₂ 8.0 · k 211.93 · w₁ 0.3486 · w₂ 3.6402
reproduce: uv run cfbpoll rank --season 2025 --through-week 1 --out out/
Close

rank 5

Auburn

1-0 · SEC. The model never reads conference names.

1 in 1how hard that record waskey 0.13
0.7wins this schedule asked for
+0.3how far past it they came

where the model can honestly pin this team, out of 136

Ranked 5. The model replayed this schedule 1,000 times, and this team finished between 2 and 117 of 136 in 90% of them.

2 to 117 · 115 places wide

power15.9, ranked 7
gap+44.1
resume60.0, ranked 7
hindsight10 · -5.0 against this rank

This team’s wins-based resume hit the bound the model puts on how much one result can be worth, so the figure above understates it.