The Poll.ai

2025 season · through week 7

Nobody voted on this.

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.

  1. 1Indiana6-06-0Gap +40.01 in 41key 1.62Ranked 1. The model replayed this schedule 1,000 times, and this team finished between 1 and 62 of 136 in 90% of them.
  2. 2Ohio State6-06-0Gap +42.21 in 21key 1.31Ranked 2. The model replayed this schedule 1,000 times, and this team finished between 2 and 71 of 136 in 90% of them.
  3. 3Texas Tech6-06-0Gap +36.21 in 20key 1.30Ranked 3. The model replayed this schedule 1,000 times, and this team finished between 1 and 47 of 136 in 90% of them.
  4. 4Texas A&M6-06-0Gap +47.11 in 16key 1.20Ranked 4. The model replayed this schedule 1,000 times, and this team finished between 3 and 101 of 136 in 90% of them.
  5. 5Miami5-05-0Gap +43.41 in 15key 1.19Ranked 5. The model replayed this schedule 1,000 times, and this team finished between 2 and 79 of 136 in 90% of them.
  6. 6BYU6-06-0Gap +47.51 in 10key 1.01Ranked 6. The model replayed this schedule 1,000 times, and this team finished between 4 and 90 of 136 in 90% of them.
  7. 7Georgia Tech6-06-0Gap +52.51 in 9key 0.97Ranked 7. The model replayed this schedule 1,000 times, and this team finished between 7 and 114 of 136 in 90% of them.
  8. 8Alabama5-15-1Gap +11.81 in 9key 0.94Ranked 8. The model replayed this schedule 1,000 times, and this team finished between 1 and 89 of 136 in 90% of them.
  9. 9Memphis6-06-0Gap +46.71 in 7key 0.86Ranked 9. The model replayed this schedule 1,000 times, and this team finished between 5 and 93 of 136 in 90% of them.
  10. 10Ole Miss6-06-0Gap +55.41 in 6key 0.77Ranked 10. The model replayed this schedule 1,000 times, and this team finished between 20 and 119 of 136 in 90% of them.
  11. 11South Florida5-15-1Gap +15.11 in 6key 0.77Ranked 11. The model replayed this schedule 1,000 times, and this team finished between 4 and 100 of 136 in 90% of them.
  12. 12UNLV6-06-0Gap +60.81 in 6key 0.76Ranked 12. The model replayed this schedule 1,000 times, and this team finished between 30 and 132 of 136 in 90% of them.
  13. 13Georgia5-15-1Gap +13.71 in 5key 0.73Ranked 13. The model replayed this schedule 1,000 times, and this team finished between 4 and 94 of 136 in 90% of them.
  14. 14Navy6-06-0Gap +52.41 in 5key 0.67Ranked 14. The model replayed this schedule 1,000 times, and this team finished between 9 and 111 of 136 in 90% of them.
  15. 15Utah5-15-1Gap +5.01 in 4key 0.60Ranked 15. The model replayed this schedule 1,000 times, and this team finished between 1 and 64 of 136 in 90% of them.
  16. 16Illinois5-25-2Gap +11.71 in 3key 0.54Ranked 16. The model replayed this schedule 1,000 times, and this team finished between 6 and 102 of 136 in 90% of them.
  17. 17Virginia5-15-1Gap +11.01 in 3key 0.52Ranked 17. The model replayed this schedule 1,000 times, and this team finished between 3 and 85 of 136 in 90% of them.
  18. 18Vanderbilt5-15-1Gap +1.81 in 3key 0.51Ranked 18. The model replayed this schedule 1,000 times, and this team finished between 1 and 74 of 136 in 90% of them.
  19. 19Oregon5-15-1Gap +5.11 in 3key 0.51Ranked 19. The model replayed this schedule 1,000 times, and this team finished between 2 and 75 of 136 in 90% of them.
  20. 20Washington5-15-1Gap +9.81 in 3key 0.50Ranked 20. The model replayed this schedule 1,000 times, and this team finished between 3 and 103 of 136 in 90% of them.
  21. 21LSU5-15-1Gap +14.21 in 3key 0.49Ranked 21. The model replayed this schedule 1,000 times, and this team finished between 12 and 105 of 136 in 90% of them.
  22. 22Oklahoma5-15-1Gap +10.91 in 3key 0.49Ranked 22. The model replayed this schedule 1,000 times, and this team finished between 5 and 105 of 136 in 90% of them.
  23. 23Houston5-15-1Gap +13.91 in 3key 0.46Ranked 23. The model replayed this schedule 1,000 times, and this team finished between 14 and 110 of 136 in 90% of them.
  24. 24Tulane5-15-1Gap +15.61 in 3key 0.45Ranked 24. The model replayed this schedule 1,000 times, and this team finished between 14 and 124 of 136 in 90% of them.
  25. 25USC5-15-1Gap +3.51 in 3key 0.41Ranked 25. The model replayed this schedule 1,000 times, and this team finished between 3 and 82 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 41 put Indiana on top. One in 3 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 100 places.

2025 week 7 · 06f93f3a · 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
1Indiana6-01 in 413.6+2.420.0 (3)+40.01 to 620.0
2Ohio State6-01 in 213.9+2.117.8 (5)+42.22 to 71-2.0
3Texas Tech6-01 in 204.0+2.023.8 (1)+36.21 to 47-2.0
4Texas A&M6-01 in 163.9+2.112.9 (16)+47.13 to 101+2.0
5Miami5-01 in 153.1+1.916.6 (9)+43.42 to 79+2.0
6BYU6-01 in 104.2+1.812.5 (17)+47.54 to 900.0
7Georgia Tech6-01 in 94.2+1.87.5 (44)+52.57 to 114-4.0
8Alabama5-11 in 93.2+1.817.2 (6)+11.81 to 89+1.0
9Memphis6-01 in 74.4+1.613.3 (14)+46.75 to 93-9.0
10Ole Miss6-01 in 64.5+1.54.6 (63)+55.420 to 119+2.0
11South Florida5-11 in 63.5+1.511.7 (22)+15.14 to 100+2.0
12UNLV6-01 in 64.5+1.5-0.8 (101)+60.830 to 132-4.0
13Georgia5-11 in 53.5+1.511.9 (20)+13.74 to 94+1.0
14Navy6-01 in 54.7+1.37.6 (43)+52.49 to 111-9.0
15Utah5-11 in 43.7+1.318.2 (4)+5.01 to 64-5.0
16Illinois5-21 in 33.8+1.28.3 (41)+11.76 to 102+3.0
17Virginia5-11 in 34.0+1.011.8 (21)+11.03 to 85-5.0
18Vanderbilt5-11 in 34.0+1.021.2 (2)+1.81 to 74-7.0
19Oregon5-11 in 34.0+1.017.0 (7)+5.12 to 75+9.0
20Washington5-11 in 33.9+1.111.7 (23)+9.83 to 103+5.0
21LSU5-11 in 33.9+1.17.0 (51)+14.212 to 105+7.0
22Oklahoma5-11 in 34.0+1.010.7 (27)+10.95 to 105+5.0
23Houston5-11 in 34.0+1.07.1 (49)+13.914 to 110-5.0
24Tulane5-11 in 34.0+1.04.7 (61)+15.614 to 124+5.0
25USC5-11 in 34.2+0.816.3 (10)+3.53 to 82+1.0
Show the full table: top 25 of 136, every columnthe published poll
#teamunderline: 90% rank interval · league median width 100how unlikely1 in this many
1IndianaBig Ten6-0·Power 20.04 (3)·Gap +39.96Ranked 1. The model replayed this schedule 1,000 times, and this team finished between 1 and 62 of 136 in 90% of them.1.6161 in 41
2Ohio StateBig Ten6-0·Power 17.81 (5)·Gap +42.19·▼2Ranked 2. The model replayed this schedule 1,000 times, and this team finished between 2 and 71 of 136 in 90% of them.1.3121 in 21
3Texas TechBig 126-0·Power 23.80 (1)·Gap +36.20·▼2Ranked 3. The model replayed this schedule 1,000 times, and this team finished between 1 and 47 of 136 in 90% of them.1.3041 in 20
4Texas A&MSEC6-0·Power 12.86 (16)·Gap +47.14·▲2Ranked 4. The model replayed this schedule 1,000 times, and this team finished between 3 and 101 of 136 in 90% of them.1.1991 in 16
5MiamiACC5-0·Power 16.63 (9)·Gap +43.37·▲2Ranked 5. The model replayed this schedule 1,000 times, and this team finished between 2 and 79 of 136 in 90% of them.1.1861 in 15
6BYUBig 126-0·Power 12.53 (17)·Gap +47.47Ranked 6. The model replayed this schedule 1,000 times, and this team finished between 4 and 90 of 136 in 90% of them.1.0101 in 10
7Georgia TechACC6-0·Power 7.53 (44)·Gap +52.47·▼4Ranked 7. The model replayed this schedule 1,000 times, and this team finished between 7 and 114 of 136 in 90% of them.0.9671 in 9
8AlabamaSEC5-1·Power 17.16 (6)·Gap +11.82·▲1Ranked 8. The model replayed this schedule 1,000 times, and this team finished between 1 and 89 of 136 in 90% of them.0.9441 in 9
9MemphisAmerican Athletic6-0·Power 13.29 (14)·Gap +46.71·▼9Ranked 9. The model replayed this schedule 1,000 times, and this team finished between 5 and 93 of 136 in 90% of them.0.8581 in 7
10Ole MissSEC6-0·Power 4.60 (63)·Gap +55.40·▲2Ranked 10. The model replayed this schedule 1,000 times, and this team finished between 20 and 119 of 136 in 90% of them.0.7691 in 6
11South FloridaAmerican Athletic5-1·Power 11.74 (22)·Gap +15.13·▲2Ranked 11. The model replayed this schedule 1,000 times, and this team finished between 4 and 100 of 136 in 90% of them.0.7681 in 6
12UNLVMountain West6-0·Power -0.77 (101)·Gap +60.77·▼4Ranked 12. The model replayed this schedule 1,000 times, and this team finished between 30 and 132 of 136 in 90% of them.0.7611 in 6
13GeorgiaSEC5-1·Power 11.88 (20)·Gap +13.69·▲1Ranked 13. The model replayed this schedule 1,000 times, and this team finished between 4 and 94 of 136 in 90% of them.0.7251 in 5
14NavyAmerican Athletic6-0·Power 7.57 (43)·Gap +52.43·▼9Ranked 14. The model replayed this schedule 1,000 times, and this team finished between 9 and 111 of 136 in 90% of them.0.6651 in 5
15UtahBig 125-1·Power 18.19 (4)·Gap +5.03·▼5Ranked 15. The model replayed this schedule 1,000 times, and this team finished between 1 and 64 of 136 in 90% of them.0.5961 in 4
16IllinoisBig Ten5-2·Power 8.31 (41)·Gap +11.71·▲3Ranked 16. The model replayed this schedule 1,000 times, and this team finished between 6 and 102 of 136 in 90% of them.0.5391 in 3
17VirginiaACC5-1·Power 11.75 (21)·Gap +10.95·▼5Ranked 17. The model replayed this schedule 1,000 times, and this team finished between 3 and 85 of 136 in 90% of them.0.5221 in 3
18VanderbiltSEC5-1·Power 21.18 (2)·Gap +1.78·▼7Ranked 18. The model replayed this schedule 1,000 times, and this team finished between 1 and 74 of 136 in 90% of them.0.5111 in 3
19OregonBig Ten5-1·Power 16.99 (7)·Gap +5.10·▲9Ranked 19. The model replayed this schedule 1,000 times, and this team finished between 2 and 75 of 136 in 90% of them.0.5071 in 3
20WashingtonBig Ten5-1·Power 11.69 (23)·Gap +9.85·▲5Ranked 20. The model replayed this schedule 1,000 times, and this team finished between 3 and 103 of 136 in 90% of them.0.5011 in 3
21LSUSEC5-1·Power 7.03 (51)·Gap +14.18·▲7Ranked 21. The model replayed this schedule 1,000 times, and this team finished between 12 and 105 of 136 in 90% of them.0.4941 in 3
22OklahomaSEC5-1·Power 10.69 (27)·Gap +10.91·▲5Ranked 22. The model replayed this schedule 1,000 times, and this team finished between 5 and 105 of 136 in 90% of them.0.4921 in 3
23HoustonBig 125-1·Power 7.13 (49)·Gap +13.86·▼5Ranked 23. The model replayed this schedule 1,000 times, and this team finished between 14 and 110 of 136 in 90% of them.0.4571 in 3
24TulaneAmerican Athletic5-1·Power 4.72 (61)·Gap +15.65·▲5Ranked 24. The model replayed this schedule 1,000 times, and this team finished between 14 and 124 of 136 in 90% of them.0.4551 in 3
25USCBig Ten5-1·Power 16.31 (10)·Gap +3.49·▲1Ranked 25. The model replayed this schedule 1,000 times, and this team finished between 3 and 82 of 136 in 90% of them.0.4091 in 3

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

Full MeritMargin counts for exactly what it is worth. Nothing is protected.alternate lensJust WinWin the game. Running the score up buys you nothing here.alternate lens

same evidence, different valuesEvery board on this page was fitted on the same 840 games, and the digest of that exact frame is 8834d28d912e 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 06f93f3a · published 2026-08-19 23:12:37 UTC · code e215160 · config 1ef7cf23…
q_ref 10.84 (San Diego State) · β_w 7 · C 32 · h 5.517 · σ 17.319 · λ₁ 125 · λ₂ 1.0 · k 74.78 · w₁ 0.6672 · w₂ -0.0854
reproduce: uv run cfbpoll rank --season 2025 --through-week 7 --out out/
Close

rank 2

Ohio State

6-0 · Big Ten. The model never reads conference names.

1 in 21how hard that record waskey 1.31
3.9wins this schedule asked for
+2.1how far past it they came

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

Ranked 2. The model replayed this schedule 1,000 times, and this team finished between 2 and 71 of 136 in 90% of them.

2 to 71 · 69 places wide

power17.8, ranked 5
gap+42.2
resume60.0, ranked 7
hindsight4 · -2.0 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.