Connectivity report · 2025 week 12

What this ranking is standing on.

The poll opened in Week 5. This is week 12; the schedule graph below is what the ranking is standing on.

The schedule graph

Abilene ChristianAdrianAir ForceAkronAlabamaAlabama A&MAlabama StateAlbany State GAAlcorn StateAllenAmerican InternationalApp StateArizonaArizona StateArkansasArkansas StateArkansas-Pine BluffArmyAuburnAustin PeayBLUEFIELDBYUBall StateBaylorBentleyBethune-CookmanBoise StateBoston CollegeBowie StateBowling GreenBrownBryantBucknellBuffaloButlerCal PolyCaliforniaCampbellCentral ArkansasCentral ConnecticutCentral MichiganCentral State (OH)Central WashingtonChadron StCharleston SouthernCharlotteChattanoogaCincinnatiClemsonCoastal CarolinaColgateColoradoColorado StateColumbiaCornellCumberland (TN)DartmouthDavidsonDaytonDelawareDelaware StateDrakeDukeDuquesneERSKINEEast CarolinaEast Tennessee StateEast Texas A&MEastern IllinoisEastern KentuckyEastern MichiganEastern WashingtonEdward WatersElizabeth City StateElonFayetteville StateFerrumFloridaFlorida A&MFlorida AtlanticFlorida InternationalFlorida StateFordhamFresno StateFurmanGardner-WebbGeorgetownGeorgiaGeorgia SouthernGeorgia StateGeorgia TechGramblingGreensboro CollegeHamptonHanover CollegeHarvardHawai'iHoly CrossHoustonHouston ChristianHowardIdahoIdaho StateIllinoisIllinois StateIncarnate WordIndianaIndiana StateIowaIowa StateJackson StateJacksonville StateJames MadisonKansasKansas StateKennesaw StateKent StateKentuckyKentucky ChristianKentucky StateLSULafayetteLamarLane CollegeLangston UniversityLehighLibertyLincoln (CA)Lincoln (PA)LindenwoodLittle RockLong Island UniversityLouisianaLouisiana CollegeLouisiana TechLouisvilleMaineMaristMarshallMarylandMassachusettsMcKendreeMcNeeseMemphisMercerMercyhurstMerrimackMiamiMiami (OH)MichiganMichigan StateMiddle TennesseeMiles CollegeMinnesotaMississippi StateMississippi Valley StateMissouriMissouri StateMonmouthMontanaMontana StateMorehead StateMorehouse CollegeMorgan StateMurray StateNC StateNavyNebraskaNevadaNew HampshireNew HavenNew MexicoNew Mexico StateNichollsNorfolk StateNorth AlabamaNorth CarolinaNorth Carolina A&TNorth Carolina CentralNorth DakotaNorth Dakota StateNorth TexasNortheastern StateNorthern ArizonaNorthern ColoradoNorthern IllinoisNorthern IowaNorthern MichiganNorthwesternNorthwestern StateNotre DameOhioOhio StateOklahomaOklahoma StateOld DominionOle MissOregonOregon StatePacePenn StatePennsylvaniaPittsburghPortland StatePrairie View A&MPresbyterianPrincetonPurdueRhode IslandRiceRichmondRobert MorrisRutgersSE LouisianaSMUSacramento StateSacred HeartSaginaw Valley StateSam HoustonSamfordSan DiegoSan Diego StateSan José StateSavannah StSouth AlabamaSouth CarolinaSouth Carolina StateSouth DakotaSouth Dakota StateSouth FloridaSoutheast Missouri StateSouthernSouthern Connecticut StateSouthern IllinoisSouthern MissSouthern UtahSt. AnselmSt. Francis (PA)St. Thomas (MN)StanfordStephen F. AustinStetsonStonehillStony BrookSul Ross StateSyracuseTCUTarleton StateTempleTennesseeTennessee StateTennessee TechTexasTexas A&MTexas SouthernTexas StateTexas TechTexas WesleyanThe CitadelThomas More CollegeToledoTowsonTroyTruman StateTulaneTulsaTuskegeeUABUAlbanyUC DavisUCFUCLAUConnUL MonroeUNLVUSCUT MartinUT Rio Grande ValleyUTEPUTSAUpper Iowa UniversityUtahUtah StateUtah TechVMIValdosta StateValparaisoVanderbiltVillanovaVirginiaVirginia StVirginia TechVirginia University Of LynchburgWagnerWake ForestWarner UniversityWashingtonWashington StateWebber InternationalWeber StateWest GeorgiaWest LibertyWest VirginiaWestern CarolinaWestern Connecticut StWestern IllinoisWestern KentuckyWestern MichiganWestern OregonWilliam & MaryWisconsinWoffordWyomingYaleYoungstown State
Every team in the fit is a node; every game played through week 12 is an edge. Teams in different components have no chain of results connecting them at all. Not through a common opponent, not through anyone’s common opponent, not at any length. The graph is welded into one component, all 315 teams mutually comparable. That is the condition under which a ranking is a measurement rather than an extrapolation. Watching this knit together, week by week, is the content.

Diagnostics

teams in the fitEvery team with at least one game against an FBS or FCS opponent.315
games played1412
connected componentsSeparate islands of the schedule graph. Two teams in different components have no chain of results connecting them at all, at any length.1
largest componentShare of the field that is mutually comparable through played games.315 teams (100.0%)
bridge gamesSingle games whose removal would split the graph in two, each holding at least two teams on. Every rating on the far side rests on that one result.0
fitted λ₂ (results core)Chosen by cross-validation every week. λ is a ratio of variances, a statement about how much the model does not know, containing no team-specific information whatsoever. It is large when the data is thin and falls as the season accumulates. Regularization stays a statement about variance and never becomes a reputation prior.0.500
median 90% rank-interval widthOut of 136 ranked teams, from 1,000 replays of this exact schedule. This is the number that says whether the season has settled.86 places
teams whose interval spans the league90% interval at least 90% as wide as the whole field.0
teams no closer than three hops to the top tenThey have not played a top-ten team and share no opponent with one. Their position relative to the top of the poll is an extrapolation.97

These are the measures for the weeks before the poll opens, published whether or not they are flattering. The one worth understanding is the penalty the model puts on itself: chosen fresh every week by testing, identical for every team, and carrying nothing about any particular one. Pulling an unknown team toward the middle is a statement about the model’s own ignorance, which is why it can produce a number in week 2 without being told which conferences are supposed to be good.

Bridge games

No bridge games this week. Every link in the graph has a second path around it, which means no single result is load-bearing for a whole cluster of ratings. That is a good week, and it is the first thing that stops being true when you go looking at week 2.

What would have to be true

The graph is welded: every team is connected to every other through some chain of results. That is the condition under which a ranking is a measurement rather than an extrapolation, and it is why the opening week is week 5 and not week 1.

Every one of these is worth more to this poll than its television slot suggests. They are the games that turn two separate islands of results into one comparable field, and no ranking that exists today will tell you which they are.

The provisional table

The estimator runs from week 1. The headline poll does not. What is behind this click is real output from the real model on the real schedule, and it is not the poll. It is labelled provisional on every row, on purpose, because the difference between computing something and being willing to publish it as a ranking is the entire point of this page.

Show the provisional table: 136 teams, ranked by schedule oddsThis week is past the start line: this is the published poll.
#teamunderline: 90% rank interval · league median width 86how unlikely1 in this many
1Texas A&MSEC10-0·Power 20.99 (8)·Gap +39.01·1Ranked 1. The model replayed this schedule 1,000 times, and this team finished between 1 and 53 of 136 in 90% of them.2.5331 in 341
2IndianaBig Ten11-0·Power 25.57 (2)·Gap +34.43·1Ranked 2. The model replayed this schedule 1,000 times, and this team finished between 1 and 38 of 136 in 90% of them.2.4261 in 267
3Ohio StateBig Ten10-0·Power 25.51 (3)·Gap +34.49Ranked 3. The model replayed this schedule 1,000 times, and this team finished between 1 and 34 of 136 in 90% of them.1.8271 in 67
4BYUBig 129-1·Power 17.75 (13)·Gap +16.40Ranked 4. The model replayed this schedule 1,000 times, and this team finished between 2 and 59 of 136 in 90% of them.1.6281 in 43
5GeorgiaSEC9-1·Power 18.79 (11)·Gap +12.85·1Ranked 5. The model replayed this schedule 1,000 times, and this team finished between 2 and 54 of 136 in 90% of them.1.4901 in 31
6Texas TechBig 1210-1·Power 25.97 (1)·Gap +5.88·2Ranked 6. The model replayed this schedule 1,000 times, and this team finished between 1 and 29 of 136 in 90% of them.1.3031 in 20
7Ole MissSEC10-1·Power 13.66 (24)·Gap +17.20Ranked 7. The model replayed this schedule 1,000 times, and this team finished between 8 and 87 of 136 in 90% of them.1.2871 in 19
8OregonBig Ten9-1·Power 22.03 (6)·Gap +8.69·3Ranked 8. The model replayed this schedule 1,000 times, and this team finished between 2 and 46 of 136 in 90% of them.1.2301 in 17
9AlabamaSEC8-2·Power 18.99 (10)·Gap +6.83Ranked 9. The model replayed this schedule 1,000 times, and this team finished between 2 and 68 of 136 in 90% of them.1.0161 in 10
10OklahomaSEC8-2·Power 17.31 (14)·Gap +7.59Ranked 10. The model replayed this schedule 1,000 times, and this team finished between 3 and 71 of 136 in 90% of them.0.9171 in 8
11Notre DameFBS Independents8-2·Power 22.52 (5)·Gap +1.99Ranked 11. The model replayed this schedule 1,000 times, and this team finished between 1 and 41 of 136 in 90% of them.0.8661 in 7
12James MadisonSun Belt9-1·Power 16.87 (15)·Gap +8.78·5Ranked 12. The model replayed this schedule 1,000 times, and this team finished between 3 and 64 of 136 in 90% of them.0.7391 in 5
13Georgia TechACC9-1·Power 10.67 (40)·Gap +14.55·2Ranked 13. The model replayed this schedule 1,000 times, and this team finished between 9 and 102 of 136 in 90% of them.0.7311 in 5
14North TexasAmerican Athletic9-1·Power 15.37 (19)·Gap +9.26·2Ranked 14. The model replayed this schedule 1,000 times, and this team finished between 4 and 68 of 136 in 90% of them.0.6981 in 5
15UtahBig 128-2·Power 23.29 (4)·Gap -0.76·5Ranked 15. The model replayed this schedule 1,000 times, and this team finished between 1 and 42 of 136 in 90% of them.0.6811 in 5
16USCBig Ten8-2·Power 19.27 (9)·Gap +3.30·2Ranked 16. The model replayed this schedule 1,000 times, and this team finished between 2 and 61 of 136 in 90% of them.0.6641 in 5
17MichiganBig Ten8-2·Power 14.32 (22)·Gap +8.16·1Ranked 17. The model replayed this schedule 1,000 times, and this team finished between 5 and 86 of 136 in 90% of them.0.6551 in 5
18MiamiACC8-2·Power 21.23 (7)·Gap +0.69·5Ranked 18. The model replayed this schedule 1,000 times, and this team finished between 2 and 46 of 136 in 90% of them.0.6221 in 4
19VanderbiltSEC8-2·Power 18.47 (12)·Gap +3.35·1Ranked 19. The model replayed this schedule 1,000 times, and this team finished between 3 and 65 of 136 in 90% of them.0.6001 in 4
20TexasSEC7-3·Power 14.67 (20)·Gap +6.29·1Ranked 20. The model replayed this schedule 1,000 times, and this team finished between 5 and 77 of 136 in 90% of them.0.5851 in 4
21VirginiaACC9-2·Power 13.26 (28)·Gap +7.64·1Ranked 21. The model replayed this schedule 1,000 times, and this team finished between 6 and 87 of 136 in 90% of them.0.5751 in 4
22TulaneAmerican Athletic8-2·Power 7.62 (60)·Gap +12.73·1Ranked 22. The model replayed this schedule 1,000 times, and this team finished between 16 and 112 of 136 in 90% of them.0.5181 in 3
23IllinoisBig Ten7-3·Power 11.60 (36)·Gap +8.07·4Ranked 23. The model replayed this schedule 1,000 times, and this team finished between 7 and 96 of 136 in 90% of them.0.4871 in 3
24Arizona StateBig 127-3·Power 10.36 (42)·Gap +8.76·1Ranked 24. The model replayed this schedule 1,000 times, and this team finished between 14 and 98 of 136 in 90% of them.0.4701 in 3
25HoustonBig 128-2·Power 10.63 (41)·Gap +9.09·1Ranked 25. The model replayed this schedule 1,000 times, and this team finished between 8 and 98 of 136 in 90% of them.0.4641 in 3

Top 25 of 136. The full table, the résumé column, the schedule receipts and the sort controls arrive with the week 5 launch.

run 2e15f1cc · published 2026-08-19 23:15:20 UTC · code e215160 · config 1ef7cf23…
q_ref 13.54 (Louisville) · β_w 7 · C 32 · h 4.362 · σ 15.819 · λ₁ 150 · λ₂ 0.5 · k 70.79 · w₁ 0.5523 · w₂ 0.1862