2025 season · through week 10

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. 1BYU8-08-0Gap +45.31 in 41key 1.61Ranked 1. The model replayed this schedule 1,000 times, and this team finished between 3 and 71 of 136 in 90% of them.
  2. 2Indiana9-09-0Gap +36.31 in 93key 1.97Ranked 2. The model replayed this schedule 1,000 times, and this team finished between 1 and 32 of 136 in 90% of them.
  3. 3Ohio State8-08-0Gap +38.91 in 31key 1.49Ranked 3. The model replayed this schedule 1,000 times, and this team finished between 1 and 44 of 136 in 90% of them.
  4. 4Texas A&M8-08-0Gap +44.51 in 56key 1.75Ranked 4. The model replayed this schedule 1,000 times, and this team finished between 3 and 66 of 136 in 90% of them.
  5. 5Alabama7-17-1Gap +12.31 in 15key 1.17Ranked 5. The model replayed this schedule 1,000 times, and this team finished between 2 and 79 of 136 in 90% of them.
  6. 6Texas Tech8-18-1Gap +4.81 in 9key 0.94Ranked 6. The model replayed this schedule 1,000 times, and this team finished between 2 and 39 of 136 in 90% of them.
  7. 7Georgia7-17-1Gap +14.41 in 9key 0.93Ranked 7. The model replayed this schedule 1,000 times, and this team finished between 5 and 88 of 136 in 90% of them.
  8. 8Louisville7-17-1Gap +12.11 in 6key 0.75Ranked 8. The model replayed this schedule 1,000 times, and this team finished between 5 and 83 of 136 in 90% of them.
  9. 9Ole Miss8-18-1Gap +17.11 in 7key 0.85Ranked 9. The model replayed this schedule 1,000 times, and this team finished between 11 and 105 of 136 in 90% of them.
  10. 10Virginia8-18-1Gap +14.01 in 6key 0.81Ranked 10. The model replayed this schedule 1,000 times, and this team finished between 7 and 90 of 136 in 90% of them.
  11. 11Oregon7-17-1Gap +5.41 in 5key 0.72Ranked 11. The model replayed this schedule 1,000 times, and this team finished between 1 and 50 of 136 in 90% of them.
  12. 12James Madison7-17-1Gap +9.41 in 4key 0.63Ranked 12. The model replayed this schedule 1,000 times, and this team finished between 2 and 79 of 136 in 90% of them.
  13. 13Georgia Tech8-18-1Gap +13.01 in 5key 0.67Ranked 13. The model replayed this schedule 1,000 times, and this team finished between 8 and 93 of 136 in 90% of them.
  14. 14North Texas8-18-1Gap +10.11 in 4key 0.61Ranked 14. The model replayed this schedule 1,000 times, and this team finished between 4 and 88 of 136 in 90% of them.
  15. 15Texas7-27-2Gap +8.71 in 5key 0.70Ranked 15. The model replayed this schedule 1,000 times, and this team finished between 5 and 75 of 136 in 90% of them.
  16. 16Memphis8-18-1Gap +7.31 in 3key 0.52Ranked 16. The model replayed this schedule 1,000 times, and this team finished between 1 and 76 of 136 in 90% of them.
  17. 17South Florida6-26-2Gap +7.01 in 3key 0.50Ranked 17. The model replayed this schedule 1,000 times, and this team finished between 3 and 91 of 136 in 90% of them.
  18. 18Michigan7-27-2Gap +6.21 in 3key 0.53Ranked 18. The model replayed this schedule 1,000 times, and this team finished between 4 and 81 of 136 in 90% of them.
  19. 19Navypoll has it 287-17-1Gap +9.91 in 2key 0.38Ranked 19. The model replayed this schedule 1,000 times, and this team finished between 6 and 99 of 136 in 90% of them.
  20. 20Utah7-27-2Gap -0.51 in 3key 0.53Ranked 20. The model replayed this schedule 1,000 times, and this team finished between 2 and 52 of 136 in 90% of them.
  21. 21Oklahoma7-27-2Gap +5.61 in 3key 0.52Ranked 21. The model replayed this schedule 1,000 times, and this team finished between 5 and 80 of 136 in 90% of them.
  22. 22Notre Dame6-26-2Gap +3.61 in 3key 0.48Ranked 22. The model replayed this schedule 1,000 times, and this team finished between 3 and 62 of 136 in 90% of them.
  23. 23Washington6-26-2Gap +5.41 in 3key 0.45Ranked 23. The model replayed this schedule 1,000 times, and this team finished between 4 and 88 of 136 in 90% of them.
  24. 24San Diego Statepoll has it 307-17-1Gap +3.71 in 2key 0.35Ranked 24. The model replayed this schedule 1,000 times, and this team finished between 1 and 70 of 136 in 90% of them.
  25. 25Miami6-26-2Gap +1.31 in 3key 0.44Ranked 25. The model replayed this schedule 1,000 times, and this team finished between 2 and 63 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 BYU 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 92 places.

2025 week 10 · 6e790350 · code b61a958 · Just Win · method cadaeb94 · 136 teams ranked

The tinted rows are the teams this lens moves at least five places, and each one carries both ranks.

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
1BYU8-01 in 415.3+2.714.7 (12)+45.33 to 710.0
2Indiana9-01 in 935.9+3.123.7 (1)+36.31 to 320.0
3Ohio State8-01 in 315.4+2.621.1 (3)+38.91 to 440.0
4Texas A&M8-01 in 565.0+3.015.5 (10)+44.53 to 660.0
5Alabama7-11 in 154.7+2.316.1 (9)+12.32 to 790.0
6Texas Tech8-11 in 96.1+1.922.3 (2)+4.82 to 39-2.0
7Georgia7-11 in 95.0+2.011.5 (26)+14.45 to 88-3.0
8Louisville7-11 in 65.5+1.512.9 (20)+12.15 to 83-1.0
9Ole Miss8-11 in 76.1+1.97.9 (42)+17.111 to 105+2.0
10Virginia8-11 in 66.2+1.810.5 (29)+14.07 to 90-2.0
11Oregon7-11 in 55.5+1.518.9 (5)+5.41 to 50+5.0
12James Madison7-11 in 45.6+1.413.4 (15)+9.42 to 79-2.0
13Georgia Tech8-11 in 56.5+1.59.7 (33)+13.08 to 930.0
14North Texas8-11 in 46.6+1.411.6 (25)+10.14 to 88+3.0
15Texas7-21 in 55.4+1.612.6 (22)+8.75 to 750.0
16Memphis8-11 in 36.8+1.213.0 (18)+7.31 to 76-5.0
17South Florida6-21 in 34.9+1.112.2 (24)+7.03 to 91+1.0
18Michigan7-21 in 35.8+1.212.7 (21)+6.24 to 81-2.0
19Navy7-11 in 26.2+0.89.0 (35)+9.96 to 99-4.0
20Utah7-21 in 35.8+1.219.2 (4)-0.52 to 52-6.0
21Oklahoma7-21 in 35.8+1.212.9 (19)+5.65 to 80+4.0
22Notre Dame6-21 in 34.9+1.114.8 (11)+3.63 to 62+4.0
23Washington6-21 in 35.0+1.012.4 (23)+5.44 to 88-1.0
24San Diego State7-11 in 26.3+0.714.1 (14)+3.71 to 70-4.0
25Miami6-21 in 35.0+1.016.3 (7)+1.32 to 63+6.0
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 92how unlikely1 in this many
1BYUBig 128-0·Power 14.72 (12)·Gap +45.28Ranked 1. The model replayed this schedule 1,000 times, and this team finished between 3 and 71 of 136 in 90% of them.1.6091 in 41
2IndianaBig Ten9-0·Power 23.68 (1)·Gap +36.32Ranked 2. The model replayed this schedule 1,000 times, and this team finished between 1 and 32 of 136 in 90% of them.1.9701 in 93
3Ohio StateBig Ten8-0·Power 21.08 (3)·Gap +38.92Ranked 3. The model replayed this schedule 1,000 times, and this team finished between 1 and 44 of 136 in 90% of them.1.4931 in 31
4Texas A&MSEC8-0·Power 15.49 (10)·Gap +44.51Ranked 4. The model replayed this schedule 1,000 times, and this team finished between 3 and 66 of 136 in 90% of them.1.7511 in 56
5AlabamaSEC7-1·Power 16.14 (9)·Gap +12.32Ranked 5. The model replayed this schedule 1,000 times, and this team finished between 2 and 79 of 136 in 90% of them.1.1651 in 15
6Texas TechBig 128-1·Power 22.32 (2)·Gap +4.83·2Ranked 6. The model replayed this schedule 1,000 times, and this team finished between 2 and 39 of 136 in 90% of them.0.9371 in 9
7GeorgiaSEC7-1·Power 11.45 (26)·Gap +14.42·3Ranked 7. The model replayed this schedule 1,000 times, and this team finished between 5 and 88 of 136 in 90% of them.0.9301 in 9
8LouisvilleACC7-1·Power 12.92 (20)·Gap +12.08·1Ranked 8. The model replayed this schedule 1,000 times, and this team finished between 5 and 83 of 136 in 90% of them.0.7501 in 6
9Ole MissSEC8-1·Power 7.93 (42)·Gap +17.06·2Ranked 9. The model replayed this schedule 1,000 times, and this team finished between 11 and 105 of 136 in 90% of them.0.8531 in 7
10VirginiaACC8-1·Power 10.55 (29)·Gap +13.98·2Ranked 10. The model replayed this schedule 1,000 times, and this team finished between 7 and 90 of 136 in 90% of them.0.8131 in 6
11OregonBig Ten7-1·Power 18.94 (5)·Gap +5.35·5Ranked 11. The model replayed this schedule 1,000 times, and this team finished between 1 and 50 of 136 in 90% of them.0.7221 in 5
12James MadisonSun Belt7-1·Power 13.44 (15)·Gap +9.35·2Ranked 12. The model replayed this schedule 1,000 times, and this team finished between 2 and 79 of 136 in 90% of them.0.6271 in 4
13Georgia TechACC8-1·Power 9.70 (33)·Gap +12.99Ranked 13. The model replayed this schedule 1,000 times, and this team finished between 8 and 93 of 136 in 90% of them.0.6661 in 5
14North TexasAmerican Athletic8-1·Power 11.59 (25)·Gap +10.07·3Ranked 14. The model replayed this schedule 1,000 times, and this team finished between 4 and 88 of 136 in 90% of them.0.6091 in 4
15TexasSEC7-2·Power 12.62 (22)·Gap +8.74Ranked 15. The model replayed this schedule 1,000 times, and this team finished between 5 and 75 of 136 in 90% of them.0.6961 in 5
16MemphisAmerican Athletic8-1·Power 12.97 (18)·Gap +7.32·5Ranked 16. The model replayed this schedule 1,000 times, and this team finished between 1 and 76 of 136 in 90% of them.0.5181 in 3
17South FloridaAmerican Athletic6-2·Power 12.15 (24)·Gap +6.96·1Ranked 17. The model replayed this schedule 1,000 times, and this team finished between 3 and 91 of 136 in 90% of them.0.5051 in 3
18MichiganBig Ten7-2·Power 12.74 (21)·Gap +6.22·2Ranked 18. The model replayed this schedule 1,000 times, and this team finished between 4 and 81 of 136 in 90% of them.0.5271 in 3
19NavyAmerican Athletic7-1·Power 9.01 (35)·Gap +9.93·4Ranked 19. The model replayed this schedule 1,000 times, and this team finished between 6 and 99 of 136 in 90% of them.0.3801 in 2
20UtahBig 127-2·Power 19.22 (4)·Gap -0.46·6Ranked 20. The model replayed this schedule 1,000 times, and this team finished between 2 and 52 of 136 in 90% of them.0.5251 in 3
21OklahomaSEC7-2·Power 12.95 (19)·Gap +5.61·4Ranked 21. The model replayed this schedule 1,000 times, and this team finished between 5 and 80 of 136 in 90% of them.0.5181 in 3
22Notre DameFBS Independents6-2·Power 14.79 (11)·Gap +3.59·4Ranked 22. The model replayed this schedule 1,000 times, and this team finished between 3 and 62 of 136 in 90% of them.0.4821 in 3
23WashingtonBig Ten6-2·Power 12.41 (23)·Gap +5.45·1Ranked 23. The model replayed this schedule 1,000 times, and this team finished between 4 and 88 of 136 in 90% of them.0.4481 in 3
24San Diego StateMountain West7-1·Power 14.06 (14)·Gap +3.69·4Ranked 24. The model replayed this schedule 1,000 times, and this team finished between 1 and 70 of 136 in 90% of them.0.3511 in 2
25MiamiACC6-2·Power 16.33 (7)·Gap +1.31·6Ranked 25. The model replayed this schedule 1,000 times, and this team finished between 2 and 63 of 136 in 90% of them.0.4371 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

same evidence, different valuesEvery board on this page was fitted on the same 1,175 games, and the digest of that exact frame is 38ccfa886779 under all three. Switching lens changes the constants above and nothing else. Method digest for this one: cadaeb945e90.

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 6e790350 · published 2026-08-15 17:18:53 UTC · code b61a958 · config 9fa6713c…
q_ref 11.59 (North Texas) · β_w 7 · C 1 · h 4.346 · σ 15.592 · λ₁ 175 · λ₂ 2.0 · k 75.65 · w₁ 0.6469 · w₂ 0.0923
Close

rank 1

BYU

8-0 · Big 12. The model never reads conference names.

1 in 41how hard that record waskey 1.61
5.3wins this schedule asked for
+2.7how 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 3 and 71 of 136 in 90% of them.

3 to 71 · 68 places wide

power14.7, ranked 12
gap+45.3
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.