2025 season · through week 8

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. 1BYU7-07-0Gap +47.71 in 22key 1.35Ranked 1. The model replayed this schedule 1,000 times, and this team finished between 4 and 94 of 136 in 90% of them.
  2. 2Indiana7-07-0Gap +40.71 in 54key 1.73Ranked 2. The model replayed this schedule 1,000 times, and this team finished between 1 and 56 of 136 in 90% of them.
  3. 3Ohio State7-07-0Gap +40.21 in 23key 1.36Ranked 3. The model replayed this schedule 1,000 times, and this team finished between 1 and 58 of 136 in 90% of them.
  4. 4Texas A&M7-07-0Gap +47.11 in 31key 1.50Ranked 4. The model replayed this schedule 1,000 times, and this team finished between 5 and 87 of 136 in 90% of them.
  5. 5Georgia Tech7-07-0Gap +50.91 in 19key 1.28Ranked 5. The model replayed this schedule 1,000 times, and this team finished between 9 and 98 of 136 in 90% of them.
  6. 6Navypoll has it 126-06-0Gap +52.21 in 5key 0.66Ranked 6. The model replayed this schedule 1,000 times, and this team finished between 2 and 108 of 136 in 90% of them.
  7. 7Alabama6-16-1Gap +12.71 in 10key 1.02Ranked 7. The model replayed this schedule 1,000 times, and this team finished between 3 and 75 of 136 in 90% of them.
  8. 8Texas Tech6-16-1Gap +5.11 in 6key 0.75Ranked 8. The model replayed this schedule 1,000 times, and this team finished between 2 and 57 of 136 in 90% of them.
  9. 9South Florida6-16-1Gap +14.01 in 6key 0.77Ranked 9. The model replayed this schedule 1,000 times, and this team finished between 5 and 89 of 136 in 90% of them.
  10. 10Georgia6-16-1Gap +14.41 in 6key 0.80Ranked 10. The model replayed this schedule 1,000 times, and this team finished between 5 and 103 of 136 in 90% of them.
  11. 11Louisville5-15-1Gap +11.01 in 4key 0.62Ranked 11. The model replayed this schedule 1,000 times, and this team finished between 4 and 103 of 136 in 90% of them.
  12. 12Oregon6-16-1Gap +3.31 in 5key 0.68Ranked 12. The model replayed this schedule 1,000 times, and this team finished between 2 and 55 of 136 in 90% of them.
  13. 13Oklahoma6-16-1Gap +10.51 in 5key 0.66Ranked 13. The model replayed this schedule 1,000 times, and this team finished between 4 and 88 of 136 in 90% of them.
  14. 14Miami5-15-1Gap +8.51 in 4key 0.59Ranked 14. The model replayed this schedule 1,000 times, and this team finished between 2 and 95 of 136 in 90% of them.
  15. 15Vanderbilt6-16-1Gap +4.31 in 4key 0.56Ranked 15. The model replayed this schedule 1,000 times, and this team finished between 2 and 66 of 136 in 90% of them.
  16. 16Virginia6-16-1Gap +12.91 in 4key 0.56Ranked 16. The model replayed this schedule 1,000 times, and this team finished between 9 and 100 of 136 in 90% of them.
  17. 17James Madisonpoll has it 226-16-1Gap +10.31 in 3key 0.50Ranked 17. The model replayed this schedule 1,000 times, and this team finished between 5 and 102 of 136 in 90% of them.
  18. 18Ole Miss6-16-1Gap +15.31 in 3key 0.53Ranked 18. The model replayed this schedule 1,000 times, and this team finished between 12 and 117 of 136 in 90% of them.
  19. 19Houston6-16-1Gap +14.71 in 3key 0.51Ranked 19. The model replayed this schedule 1,000 times, and this team finished between 12 and 117 of 136 in 90% of them.
  20. 20Tulane6-16-1Gap +16.11 in 3key 0.51Ranked 20. The model replayed this schedule 1,000 times, and this team finished between 14 and 118 of 136 in 90% of them.
  21. 21UNLV6-16-1Gap +20.71 in 3key 0.45Ranked 21. The model replayed this schedule 1,000 times, and this team finished between 37 and 130 of 136 in 90% of them.
  22. 22Missouri6-16-1Gap +9.91 in 3key 0.43Ranked 22. The model replayed this schedule 1,000 times, and this team finished between 4 and 104 of 136 in 90% of them.
  23. 23North Texas6-16-1Gap +8.31 in 3key 0.45Ranked 23. The model replayed this schedule 1,000 times, and this team finished between 3 and 97 of 136 in 90% of them.
  24. 24Illinoispoll has it 185-25-2Gap +11.21 in 3key 0.51Ranked 24. The model replayed this schedule 1,000 times, and this team finished between 10 and 106 of 136 in 90% of them.
  25. 25Cincinnati6-16-1Gap +11.51 in 2key 0.39Ranked 25. The model replayed this schedule 1,000 times, and this team finished between 12 and 111 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 22 put BYU on top. One in 2 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 97.5 places.

2025 week 8 · c417348f · 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
1BYU7-01 in 224.7+2.312.3 (17)+47.74 to 940.0
2Indiana7-01 in 544.4+2.619.3 (4)+40.71 to 560.0
3Ohio State7-01 in 234.7+2.319.8 (3)+40.21 to 580.0
4Texas A&M7-01 in 314.5+2.512.9 (15)+47.15 to 870.0
5Georgia Tech7-01 in 194.8+2.29.1 (35)+50.99 to 980.0
6Navy6-01 in 54.8+1.27.8 (47)+52.22 to 1080.0
7Alabama6-11 in 104.0+2.015.5 (8)+12.73 to 750.0
8Texas Tech6-11 in 64.5+1.520.9 (1)+5.12 to 57-5.0
9South Florida6-11 in 64.5+1.511.7 (18)+14.05 to 890.0
10Georgia6-11 in 64.3+1.710.9 (26)+14.45 to 103-1.0
11Louisville5-11 in 43.8+1.213.1 (13)+11.04 to 103+1.0
12Oregon6-11 in 54.6+1.420.5 (2)+3.32 to 55+4.0
13Oklahoma6-11 in 54.6+1.412.8 (16)+10.54 to 88-1.0
14Miami5-11 in 43.7+1.314.3 (9)+8.52 to 95+2.0
15Vanderbilt6-11 in 44.8+1.218.3 (6)+4.32 to 66-6.0
16Virginia6-11 in 44.8+1.29.5 (33)+12.99 to 100-4.0
17James Madison6-11 in 34.9+1.111.2 (24)+10.35 to 102-7.0
18Ole Miss6-11 in 34.8+1.26.1 (54)+15.312 to 117+3.0
19Houston6-11 in 34.9+1.16.4 (52)+14.712 to 117+1.0
20Tulane6-11 in 34.9+1.14.5 (63)+16.114 to 118+1.0
21UNLV6-11 in 35.0+1.0-0.7 (98)+20.737 to 130-7.0
22Missouri6-11 in 35.1+0.910.1 (29)+9.94 to 104-1.0
23North Texas6-11 in 35.0+1.011.5 (20)+8.33 to 97+6.0
24Illinois5-21 in 33.9+1.18.0 (46)+11.210 to 106+8.0
25Cincinnati6-11 in 25.2+0.87.7 (49)+11.512 to 111-10.0
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 97.5how unlikely1 in this many
1BYUBig 127-0·Power 12.35 (17)·Gap +47.65Ranked 1. The model replayed this schedule 1,000 times, and this team finished between 4 and 94 of 136 in 90% of them.1.3491 in 22
2IndianaBig Ten7-0·Power 19.33 (4)·Gap +40.67Ranked 2. The model replayed this schedule 1,000 times, and this team finished between 1 and 56 of 136 in 90% of them.1.7301 in 54
3Ohio StateBig Ten7-0·Power 19.82 (3)·Gap +40.18Ranked 3. The model replayed this schedule 1,000 times, and this team finished between 1 and 58 of 136 in 90% of them.1.3571 in 23
4Texas A&MSEC7-0·Power 12.92 (15)·Gap +47.08Ranked 4. The model replayed this schedule 1,000 times, and this team finished between 5 and 87 of 136 in 90% of them.1.4981 in 31
5Georgia TechACC7-0·Power 9.14 (35)·Gap +50.86Ranked 5. The model replayed this schedule 1,000 times, and this team finished between 9 and 98 of 136 in 90% of them.1.2831 in 19
6NavyAmerican Athletic6-0·Power 7.78 (47)·Gap +52.22Ranked 6. The model replayed this schedule 1,000 times, and this team finished between 2 and 108 of 136 in 90% of them.0.6601 in 5
7AlabamaSEC6-1·Power 15.49 (8)·Gap +12.67Ranked 7. The model replayed this schedule 1,000 times, and this team finished between 3 and 75 of 136 in 90% of them.1.0181 in 10
8Texas TechBig 126-1·Power 20.95 (1)·Gap +5.08·5Ranked 8. The model replayed this schedule 1,000 times, and this team finished between 2 and 57 of 136 in 90% of them.0.7541 in 6
9South FloridaAmerican Athletic6-1·Power 11.65 (18)·Gap +13.98Ranked 9. The model replayed this schedule 1,000 times, and this team finished between 5 and 89 of 136 in 90% of them.0.7661 in 6
10GeorgiaSEC6-1·Power 10.87 (26)·Gap +14.43·1Ranked 10. The model replayed this schedule 1,000 times, and this team finished between 5 and 103 of 136 in 90% of them.0.7961 in 6
11LouisvilleACC5-1·Power 13.09 (13)·Gap +11.02·1Ranked 11. The model replayed this schedule 1,000 times, and this team finished between 4 and 103 of 136 in 90% of them.0.6241 in 4
12OregonBig Ten6-1·Power 20.54 (2)·Gap +3.31·4Ranked 12. The model replayed this schedule 1,000 times, and this team finished between 2 and 55 of 136 in 90% of them.0.6791 in 5
13OklahomaSEC6-1·Power 12.82 (16)·Gap +10.53·1Ranked 13. The model replayed this schedule 1,000 times, and this team finished between 4 and 88 of 136 in 90% of them.0.6581 in 5
14MiamiACC5-1·Power 14.34 (9)·Gap +8.47·2Ranked 14. The model replayed this schedule 1,000 times, and this team finished between 2 and 95 of 136 in 90% of them.0.5921 in 4
15VanderbiltSEC6-1·Power 18.26 (6)·Gap +4.28·6Ranked 15. The model replayed this schedule 1,000 times, and this team finished between 2 and 66 of 136 in 90% of them.0.5571 in 4
16VirginiaACC6-1·Power 9.54 (33)·Gap +12.91·4Ranked 16. The model replayed this schedule 1,000 times, and this team finished between 9 and 100 of 136 in 90% of them.0.5591 in 4
17James MadisonSun Belt6-1·Power 11.17 (24)·Gap +10.29·7Ranked 17. The model replayed this schedule 1,000 times, and this team finished between 5 and 102 of 136 in 90% of them.0.5041 in 3
18Ole MissSEC6-1·Power 6.12 (54)·Gap +15.30·3Ranked 18. The model replayed this schedule 1,000 times, and this team finished between 12 and 117 of 136 in 90% of them.0.5311 in 3
19HoustonBig 126-1·Power 6.39 (52)·Gap +14.68·1Ranked 19. The model replayed this schedule 1,000 times, and this team finished between 12 and 117 of 136 in 90% of them.0.5151 in 3
20TulaneAmerican Athletic6-1·Power 4.55 (63)·Gap +16.08·1Ranked 20. The model replayed this schedule 1,000 times, and this team finished between 14 and 118 of 136 in 90% of them.0.5081 in 3
21UNLVMountain West6-1·Power -0.70 (98)·Gap +20.74·7Ranked 21. The model replayed this schedule 1,000 times, and this team finished between 37 and 130 of 136 in 90% of them.0.4531 in 3
22MissouriSEC6-1·Power 10.09 (29)·Gap +9.86·1Ranked 22. The model replayed this schedule 1,000 times, and this team finished between 4 and 104 of 136 in 90% of them.0.4321 in 3
23North TexasAmerican Athletic6-1·Power 11.54 (20)·Gap +8.33·6Ranked 23. The model replayed this schedule 1,000 times, and this team finished between 3 and 97 of 136 in 90% of them.0.4531 in 3
24IllinoisBig Ten5-2·Power 8.00 (46)·Gap +11.24·8Ranked 24. The model replayed this schedule 1,000 times, and this team finished between 10 and 106 of 136 in 90% of them.0.5071 in 3
25CincinnatiBig 126-1·Power 7.68 (49)·Gap +11.48·10Ranked 25. The model replayed this schedule 1,000 times, and this team finished between 12 and 111 of 136 in 90% of them.0.3921 in 2

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 952 games, and the digest of that exact frame is d2ed101a0fca 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 c417348f · published 2026-08-15 17:17:50 UTC · code b61a958 · config bf0fa1a3…
q_ref 10.98 (Michigan) · β_w 7 · C 1 · h 5.136 · σ 16.534 · λ₁ 150 · λ₂ 2.0 · k 76.66 · w₁ 0.6350 · w₂ -0.0997
Close

rank 16

Virginia

6-1 · ACC. The model never reads conference names.

1 in 4how hard that record waskey 0.56
4.8wins this schedule asked for
+1.2how far past it they came

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

Ranked 16. The model replayed this schedule 1,000 times, and this team finished between 9 and 100 of 136 in 90% of them.

9 to 100 · 91 places wide

power9.5, ranked 33
gap+12.9
resume22.4, ranked 16
hindsight20 · -4.0 against this rank