The Poll.ai

2025 season · through week 13

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.

Just WinALTERNATE LENS. The same games, ranked on different beliefs.
  1. 1Indiana11-011-0Gap +35.81 in 253key 2.40Ranked 1. The model replayed this schedule 1,000 times, and this team finished between 1 and 36 of 136 in 90% of them.
  2. 2Ohio State11-011-0Gap +35.21 in 87key 1.94Ranked 2. The model replayed this schedule 1,000 times, and this team finished between 1 and 29 of 136 in 90% of them.
  3. 3Texas A&M11-011-0Gap +39.71 in 428key 2.63Ranked 3. The model replayed this schedule 1,000 times, and this team finished between 2 and 48 of 136 in 90% of them.
  4. 4BYU10-110-1Gap +16.51 in 65key 1.81Ranked 4. The model replayed this schedule 1,000 times, and this team finished between 3 and 64 of 136 in 90% of them.
  5. 5Oregon10-110-1Gap +9.81 in 34key 1.53Ranked 5. The model replayed this schedule 1,000 times, and this team finished between 2 and 40 of 136 in 90% of them.
  6. 6Georgia10-110-1Gap +12.61 in 39key 1.59Ranked 6. The model replayed this schedule 1,000 times, and this team finished between 2 and 50 of 136 in 90% of them.
  7. 7Texas Tech10-110-1Gap +5.11 in 20key 1.30Ranked 7. The model replayed this schedule 1,000 times, and this team finished between 1 and 27 of 136 in 90% of them.
  8. 8Ole Miss10-110-1Gap +16.91 in 19key 1.29Ranked 8. The model replayed this schedule 1,000 times, and this team finished between 8 and 82 of 136 in 90% of them.
  9. 9Oklahoma9-29-2Gap +8.71 in 15key 1.19Ranked 9. The model replayed this schedule 1,000 times, and this team finished between 3 and 59 of 136 in 90% of them.
  10. 10James Madison10-110-1Gap +9.41 in 8key 0.88Ranked 10. The model replayed this schedule 1,000 times, and this team finished between 3 and 69 of 136 in 90% of them.
  11. 11Alabama9-29-2Gap +5.91 in 13key 1.11Ranked 11. The model replayed this schedule 1,000 times, and this team finished between 2 and 60 of 136 in 90% of them.
  12. 12North Texas10-110-1Gap +8.01 in 7key 0.85Ranked 12. The model replayed this schedule 1,000 times, and this team finished between 1 and 57 of 136 in 90% of them.
  13. 13Notre Dame9-29-2Gap +0.71 in 9key 0.94Ranked 13. The model replayed this schedule 1,000 times, and this team finished between 1 and 34 of 136 in 90% of them.
  14. 14Michigan9-29-2Gap +6.81 in 7key 0.83Ranked 14. The model replayed this schedule 1,000 times, and this team finished between 4 and 59 of 136 in 90% of them.
  15. 15Vanderbilt9-29-2Gap +2.81 in 6key 0.74Ranked 15. The model replayed this schedule 1,000 times, and this team finished between 2 and 45 of 136 in 90% of them.
  16. 16Utah9-29-2Gap +2.01 in 6key 0.75Ranked 16. The model replayed this schedule 1,000 times, and this team finished between 2 and 44 of 136 in 90% of them.
  17. 17Miami9-29-2Gap +1.81 in 5key 0.72Ranked 17. The model replayed this schedule 1,000 times, and this team finished between 2 and 44 of 136 in 90% of them.
  18. 18Texas8-38-3Gap +6.41 in 5key 0.68Ranked 18. The model replayed this schedule 1,000 times, and this team finished between 5 and 84 of 136 in 90% of them.
  19. 19Tulane9-29-2Gap +12.51 in 5key 0.66Ranked 19. The model replayed this schedule 1,000 times, and this team finished between 14 and 99 of 136 in 90% of them.
  20. 20Navy8-28-2Gap +11.91 in 3key 0.49Ranked 20. The model replayed this schedule 1,000 times, and this team finished between 12 and 108 of 136 in 90% of them.
  21. 21Virginia9-29-2Gap +7.01 in 4key 0.56Ranked 21. The model replayed this schedule 1,000 times, and this team finished between 6 and 82 of 136 in 90% of them.
  22. 22USC8-38-3Gap +0.61 in 4key 0.56Ranked 22. The model replayed this schedule 1,000 times, and this team finished between 2 and 49 of 136 in 90% of them.
  23. 23Arizona State8-38-3Gap +7.61 in 3key 0.53Ranked 23. The model replayed this schedule 1,000 times, and this team finished between 11 and 89 of 136 in 90% of them.
  24. 24South Florida8-38-3Gap +2.21 in 3key 0.50Ranked 24. The model replayed this schedule 1,000 times, and this team finished between 3 and 69 of 136 in 90% of them.
  25. 25Georgia Tech9-29-2Gap +9.41 in 3key 0.41Ranked 25. The model replayed this schedule 1,000 times, and this team finished between 17 and 98 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 253 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 79 places.

2025 week 13 · 8e117187 · code b61a958 · Just Win · method b4343205 · 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
1Indiana11-01 in 2537.2+3.824.2 (3)+35.81 to 360.0
2Ohio State11-01 in 877.6+3.424.8 (1)+35.21 to 290.0
3Texas A&M11-01 in 4286.9+4.120.3 (6)+39.72 to 480.0
4BYU10-11 in 656.6+3.416.3 (15)+16.53 to 640.0
5Oregon10-11 in 346.9+3.120.7 (5)+9.82 to 400.0
6Georgia10-11 in 396.7+3.317.8 (12)+12.62 to 500.0
7Texas Tech10-11 in 207.4+2.624.7 (2)+5.11 to 270.0
8Ole Miss10-11 in 197.3+2.712.2 (24)+16.98 to 820.0
9Oklahoma9-21 in 156.3+2.716.3 (14)+8.73 to 59-2.0
10James Madison10-11 in 88.0+2.015.5 (19)+9.43 to 690.0
11Alabama9-21 in 136.5+2.518.8 (9)+5.92 to 60-1.0
12North Texas10-11 in 78.0+2.016.3 (16)+8.01 to 57+3.0
13Notre Dame9-21 in 96.8+2.222.5 (4)+0.71 to 340.0
14Michigan9-21 in 77.0+2.015.5 (20)+6.84 to 590.0
15Vanderbilt9-21 in 67.2+1.818.7 (10)+2.82 to 45-2.0
16Utah9-21 in 67.2+1.819.3 (7)+2.02 to 440.0
17Miami9-21 in 57.3+1.719.2 (8)+1.82 to 44+2.0
18Texas8-31 in 56.4+1.613.7 (22)+6.45 to 84-2.0
19Tulane9-21 in 57.3+1.77.6 (47)+12.514 to 99+1.0
20Navy8-21 in 36.9+1.17.6 (48)+11.912 to 108+1.0
21Virginia9-21 in 47.6+1.412.0 (26)+7.06 to 820.0
22USC8-31 in 46.6+1.418.0 (11)+0.62 to 490.0
23Arizona State8-31 in 36.7+1.310.4 (37)+7.611 to 89-1.0
24South Florida8-31 in 36.8+1.215.6 (18)+2.23 to 69+1.0
25Georgia Tech9-21 in 38.0+1.07.7 (46)+9.417 to 980.0
Show the full table: top 25 of 136, every columnALTERNATE LENS. The same games, ranked on different beliefs.
#teamunderline: 90% rank interval · league median width 79how unlikely1 in this many
1IndianaBig Ten11-0·Power 24.22 (3)·Gap +35.78Ranked 1. The model replayed this schedule 1,000 times, and this team finished between 1 and 36 of 136 in 90% of them.2.4031 in 253
2Ohio StateBig Ten11-0·Power 24.78 (1)·Gap +35.22Ranked 2. The model replayed this schedule 1,000 times, and this team finished between 1 and 29 of 136 in 90% of them.1.9391 in 87
3Texas A&MSEC11-0·Power 20.26 (6)·Gap +39.74Ranked 3. The model replayed this schedule 1,000 times, and this team finished between 2 and 48 of 136 in 90% of them.2.6311 in 428
4BYUBig 1210-1·Power 16.27 (15)·Gap +16.46Ranked 4. The model replayed this schedule 1,000 times, and this team finished between 3 and 64 of 136 in 90% of them.1.8121 in 65
5OregonBig Ten10-1·Power 20.75 (5)·Gap +9.75Ranked 5. The model replayed this schedule 1,000 times, and this team finished between 2 and 40 of 136 in 90% of them.1.5301 in 34
6GeorgiaSEC10-1·Power 17.84 (12)·Gap +12.63Ranked 6. The model replayed this schedule 1,000 times, and this team finished between 2 and 50 of 136 in 90% of them.1.5941 in 39
7Texas TechBig 1210-1·Power 24.65 (2)·Gap +5.10Ranked 7. The model replayed this schedule 1,000 times, and this team finished between 1 and 27 of 136 in 90% of them.1.3001 in 20
8Ole MissSEC10-1·Power 12.16 (24)·Gap +16.92Ranked 8. The model replayed this schedule 1,000 times, and this team finished between 8 and 82 of 136 in 90% of them.1.2901 in 19
9OklahomaSEC9-2·Power 16.34 (14)·Gap +8.67·▼2Ranked 9. The model replayed this schedule 1,000 times, and this team finished between 3 and 59 of 136 in 90% of them.1.1861 in 15
10James MadisonSun Belt10-1·Power 15.52 (19)·Gap +9.44Ranked 10. The model replayed this schedule 1,000 times, and this team finished between 3 and 69 of 136 in 90% of them.0.8841 in 8
11AlabamaSEC9-2·Power 18.78 (9)·Gap +5.90·▼1Ranked 11. The model replayed this schedule 1,000 times, and this team finished between 2 and 60 of 136 in 90% of them.1.1081 in 13
12North TexasAmerican Athletic10-1·Power 16.26 (16)·Gap +7.96·▲3Ranked 12. The model replayed this schedule 1,000 times, and this team finished between 1 and 57 of 136 in 90% of them.0.8481 in 7
13Notre DameFBS Independents9-2·Power 22.51 (4)·Gap +0.74Ranked 13. The model replayed this schedule 1,000 times, and this team finished between 1 and 34 of 136 in 90% of them.0.9381 in 9
14MichiganBig Ten9-2·Power 15.45 (20)·Gap +6.83Ranked 14. The model replayed this schedule 1,000 times, and this team finished between 4 and 59 of 136 in 90% of them.0.8331 in 7
15VanderbiltSEC9-2·Power 18.68 (10)·Gap +2.84·▼2Ranked 15. The model replayed this schedule 1,000 times, and this team finished between 2 and 45 of 136 in 90% of them.0.7431 in 6
16UtahBig 129-2·Power 19.31 (7)·Gap +2.01Ranked 16. The model replayed this schedule 1,000 times, and this team finished between 2 and 44 of 136 in 90% of them.0.7471 in 6
17MiamiACC9-2·Power 19.25 (8)·Gap +1.83·▲2Ranked 17. The model replayed this schedule 1,000 times, and this team finished between 2 and 44 of 136 in 90% of them.0.7161 in 5
18TexasSEC8-3·Power 13.73 (22)·Gap +6.44·▼2Ranked 18. The model replayed this schedule 1,000 times, and this team finished between 5 and 84 of 136 in 90% of them.0.6771 in 5
19TulaneAmerican Athletic9-2·Power 7.63 (47)·Gap +12.51·▲1Ranked 19. The model replayed this schedule 1,000 times, and this team finished between 14 and 99 of 136 in 90% of them.0.6571 in 5
20NavyAmerican Athletic8-2·Power 7.59 (48)·Gap +11.95·▲1Ranked 20. The model replayed this schedule 1,000 times, and this team finished between 12 and 108 of 136 in 90% of them.0.4941 in 3
21VirginiaACC9-2·Power 12.01 (26)·Gap +6.96Ranked 21. The model replayed this schedule 1,000 times, and this team finished between 6 and 82 of 136 in 90% of them.0.5561 in 4
22USCBig Ten8-3·Power 18.03 (11)·Gap +0.63Ranked 22. The model replayed this schedule 1,000 times, and this team finished between 2 and 49 of 136 in 90% of them.0.5591 in 4
23Arizona StateBig 128-3·Power 10.37 (37)·Gap +7.63·▼1Ranked 23. The model replayed this schedule 1,000 times, and this team finished between 11 and 89 of 136 in 90% of them.0.5281 in 3
24South FloridaAmerican Athletic8-3·Power 15.57 (18)·Gap +2.20·▲1Ranked 24. The model replayed this schedule 1,000 times, and this team finished between 3 and 69 of 136 in 90% of them.0.4961 in 3
25Georgia TechACC9-2·Power 7.67 (46)·Gap +9.43Ranked 25. The model replayed this schedule 1,000 times, and this team finished between 17 and 98 of 136 in 90% of them.0.4141 in 3

What this board believes football results are for

Just Win, in its own words

If point differential pays, teams will run up the score on an opponent who cannot stop them. Everybody has seen it happen and nobody enjoyed it. This recipe takes the incentive off the table the only way a poll actually can, by refusing to look: the compression scale drops to a single point against a 7 point win premium, so margin can move a game's contribution by at most 1 point in 8 and beating someone by 70 is worth almost exactly what beating them by 1 is worth. There is nothing left to chase in the fourth quarter. The table is then ordered by the wins based resume, which asks one question and only one, what quality of team would have been expected to produce this record against this schedule. That is Colley's principle arrived at from the other direction, and the cost of it is written down below in full, because this recipe throws away real information on purpose and a reader is owed the size of what it threw away.

what it costs

  • It throws away information that is genuinely there. A 70 point win and a 1 point win are not the same event and this recipe values them within about 15 percent of each other. That is the whole objection to Colley and it lands.
  • It cannot move an unbeaten team, at all, ever. Expected wins approaches n from below, so an undefeated team has no finite root and every one of them lands on exactly the published bracket of +60, which is not a function of the schedule. The retroactive re-ranking that is this project's most differentiated product therefore cannot move an unbeaten team by a single place, in any week, in any direction. If September turns out to have been harder than it looked, this recipe cannot say so.
  • No team with a loss can ever be ranked above an unbeaten team. Not rarely. Never, by construction, in every season measured. In 2021 that forced a 13-0 Cincinnati to number one ahead of Alabama, Georgia and Michigan, a position no independent judge reached.
  • THE TIE-BREAK DOES NOT WORK AT THIS COMPRESSION, and the consequence is visible on the first four lines of the board. Under the house constants the margin aware resume separates teams sitting on the saturation bound, which is the one job it is kept for. At C = 1 that variant compresses too, so every unbeaten team saturates on BOTH columns and the order among them falls through to the last key in the sort, which is the team name. In 2023 the top four under this recipe is Florida State, Liberty, Michigan, Washington, in alphabetical order. That is not a ranking of those four teams. It is the absence of one, and the recipe has no way to produce a ranking of them because it has thrown away the only information that would distinguish them.
  • Compressing to a single point is far outside anything the tuning campaigns searched. Campaign 1's grid opened at C = 18 and campaign 2 only widened it upward. This constant is a value judgement taken to its logical end, not a fitted number, and nothing in this repository claims it predicts well.

what it changed

  • margin.beta_w7
  • margin.c1
  • publication.headline_orderingL4_resume

configs/recipes/just-win.toml

Full MeritMargin counts for exactly what it is worth. Nothing is protected.alternate lensThe House PollMargin in the engine, schedule odds in the headline. The published poll.the published poll

same evidence, different valuesEvery board on this page was fitted on the same 1,536 games, and the digest of that exact frame is 40e2482025f3 under all three. Switching lens changes the constants above and nothing else. Method digest for this one: b43432059de8.

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 8e117187 · published 2026-08-15 17:20:49 UTC · code b61a958 · config dfc23153…
q_ref 12.05 (Auburn) · β_w 7 · C 1 · h 4.281 · σ 15.461 · λ₁ 175 · λ₂ 2.0 · k 72.21 · w₁ 0.6502 · w₂ 0.3952
reproduce: uv run cfbpoll rank --season 2025 --through-week 13 --out out/
Close

rank 1

Indiana

11-0 · Big Ten. The model never reads conference names.

1 in 253how hard that record waskey 2.40
7.2wins this schedule asked for
+3.8how far past it they came

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

Ranked 1. The model replayed this schedule 1,000 times, and this team finished between 1 and 36 of 136 in 90% of them.

1 to 36 · 35 places wide

power24.2, ranked 3
gap+35.8
resume60.0, ranked 1
hindsight1 · 0.0 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.