Connectivity report · 2025 week 16

What this ranking is standing on.

The poll opened in Week 5. This is week 16; 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 16 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 played1637
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.75 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.88

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 75how unlikely1 in this many
1IndianaBig Ten13-0·Power 30.00 (2)·Gap +30.00Ranked 1. The model replayed this schedule 1,000 times, and this team finished between 1 and 24 of 136 in 90% of them.3.2401 in 1,736
2OregonBig Ten11-1·Power 26.23 (5)·Gap +10.80Ranked 2. The model replayed this schedule 1,000 times, and this team finished between 1 and 35 of 136 in 90% of them.1.9631 in 92
3GeorgiaSEC12-1·Power 22.56 (10)·Gap +13.00·1Ranked 3. The model replayed this schedule 1,000 times, and this team finished between 2 and 44 of 136 in 90% of them.1.9321 in 86
4Ohio StateBig Ten12-1·Power 29.40 (3)·Gap +7.33·1Ranked 4. The model replayed this schedule 1,000 times, and this team finished between 1 and 24 of 136 in 90% of them.1.9141 in 82
5Texas A&MSEC11-1·Power 22.72 (9)·Gap +13.80Ranked 5. The model replayed this schedule 1,000 times, and this team finished between 2 and 44 of 136 in 90% of them.1.8351 in 68
6BYUBig 1211-2·Power 19.72 (15)·Gap +12.89·1Ranked 6. The model replayed this schedule 1,000 times, and this team finished between 4 and 62 of 136 in 90% of them.1.6571 in 45
7Texas TechBig 1212-1·Power 31.03 (1)·Gap +4.41·1Ranked 7. The model replayed this schedule 1,000 times, and this team finished between 1 and 22 of 136 in 90% of them.1.6511 in 45
8Ole MissSEC11-1·Power 17.83 (19)·Gap +15.94Ranked 8. The model replayed this schedule 1,000 times, and this team finished between 5 and 68 of 136 in 90% of them.1.4431 in 28
9OklahomaSEC10-2·Power 20.23 (13)·Gap +8.21Ranked 9. The model replayed this schedule 1,000 times, and this team finished between 3 and 51 of 136 in 90% of them.1.1951 in 16
10AlabamaSEC10-3·Power 20.14 (14)·Gap +6.12Ranked 10. The model replayed this schedule 1,000 times, and this team finished between 3 and 58 of 136 in 90% of them.1.0401 in 11
11Notre DameFBS Independents10-2·Power 27.96 (4)·Gap -0.76Ranked 11. The model replayed this schedule 1,000 times, and this team finished between 1 and 29 of 136 in 90% of them.0.9791 in 10
12MiamiACC10-2·Power 24.41 (7)·Gap +2.29Ranked 12. The model replayed this schedule 1,000 times, and this team finished between 2 and 42 of 136 in 90% of them.0.9191 in 8
13VanderbiltSEC10-2·Power 23.02 (8)·Gap +3.68Ranked 13. The model replayed this schedule 1,000 times, and this team finished between 2 and 44 of 136 in 90% of them.0.9141 in 8
14James MadisonSun Belt12-1·Power 18.69 (17)·Gap +9.54Ranked 14. The model replayed this schedule 1,000 times, and this team finished between 3 and 57 of 136 in 90% of them.0.8641 in 7
15TexasSEC9-3·Power 17.17 (22)·Gap +8.18Ranked 15. The model replayed this schedule 1,000 times, and this team finished between 6 and 71 of 136 in 90% of them.0.8351 in 7
16UtahBig 1210-2·Power 24.49 (6)·Gap +1.37Ranked 16. The model replayed this schedule 1,000 times, and this team finished between 2 and 39 of 136 in 90% of them.0.8281 in 7
17NavyAmerican Athletic10-2·Power 11.19 (46)·Gap +14.81·1Ranked 17. The model replayed this schedule 1,000 times, and this team finished between 16 and 94 of 136 in 90% of them.0.7461 in 6
18TulaneAmerican Athletic11-2·Power 10.87 (48)·Gap +13.67·1Ranked 18. The model replayed this schedule 1,000 times, and this team finished between 17 and 99 of 136 in 90% of them.0.7331 in 5
19MichiganBig Ten9-3·Power 17.45 (20)·Gap +5.02·1Ranked 19. The model replayed this schedule 1,000 times, and this team finished between 6 and 74 of 136 in 90% of them.0.5931 in 4
20USCBig Ten9-3·Power 21.23 (11)·Gap +1.23·1Ranked 20. The model replayed this schedule 1,000 times, and this team finished between 3 and 58 of 136 in 90% of them.0.5651 in 4
21North TexasAmerican Athletic11-2·Power 19.42 (16)·Gap +3.04Ranked 21. The model replayed this schedule 1,000 times, and this team finished between 4 and 55 of 136 in 90% of them.0.5561 in 4
22South FloridaAmerican Athletic9-3·Power 20.40 (12)·Gap +0.23Ranked 22. The model replayed this schedule 1,000 times, and this team finished between 3 and 51 of 136 in 90% of them.0.4361 in 3
23ArizonaBig 129-3·Power 15.64 (25)·Gap +3.32·2Ranked 23. The model replayed this schedule 1,000 times, and this team finished between 8 and 74 of 136 in 90% of them.0.3491 in 2
24VirginiaACC10-3·Power 15.49 (26)·Gap +2.91Ranked 24. The model replayed this schedule 1,000 times, and this team finished between 7 and 73 of 136 in 90% of them.0.3231 in 2
25Arizona StateBig 128-4·Power 11.80 (44)·Gap +6.29·2Ranked 25. The model replayed this schedule 1,000 times, and this team finished between 13 and 94 of 136 in 90% of them.0.3121 in 2

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

run 61a5fd2c · published 2026-08-19 23:18:03 UTC · code e215160 · config 1ef7cf23…
q_ref 15.64 (Arizona) · β_w 7 · C 32 · h 3.706 · σ 15.884 · λ₁ 200 · λ₂ 0.5 · k 72.96 · w₁ 0.5184 · w₂ 0.3169