The Poll.ai

Connectivity report · 2025 week 5

What this ranking is standing on.

The poll opened in Week 5. This is week 5; 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 StatePenn StatePennsylvaniaPittsburghPortland StatePrairie View A&MPresbyterianPrincetonPurdueRhode IslandRiceRichmondRobert MorrisRutgersSE LouisianaSMUSacramento StateSacred HeartSaginaw Valley StateSam HoustonSamfordSan DiegoSan Diego StateSan José StateSouth AlabamaSouth CarolinaSouth Carolina StateSouth DakotaSouth Dakota StateSouth FloridaSoutheast Missouri StateSouthernSouthern 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 TechVMIValparaisoVanderbiltVillanovaVirginiaVirginia StVirginia TechVirginia University Of LynchburgWagnerWake ForestWarner UniversityWashingtonWashington StateWebber InternationalWeber StateWest GeorgiaWest LibertyWest VirginiaWestern CarolinaWestern IllinoisWestern KentuckyWestern MichiganWestern OregonWilliam & MaryWisconsinWoffordWyomingYaleYoungstown State
Every team in the fit is a node; every game played through week 5 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 310 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.310
games played620
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.310 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.2.000
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.109 places
teams whose interval spans the league90% interval at least 90% as wide as the whole field.4
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.173

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 109how unlikely1 in this many
1IndianaBig Ten5-0·Power 15.97 (8)·Gap +44.03·▼3Ranked 1. The model replayed this schedule 1,000 times, and this team finished between 2 and 101 of 136 in 90% of them.0.9621 in 9
2MemphisAmerican Athletic5-0·Power 13.98 (12)·Gap +46.02·▼14Ranked 2. The model replayed this schedule 1,000 times, and this team finished between 5 and 101 of 136 in 90% of them.0.9181 in 8
3OklahomaSEC4-0·Power 9.61 (25)·Gap +50.39·▼5Ranked 3. The model replayed this schedule 1,000 times, and this team finished between 4 and 105 of 136 in 90% of them.0.8791 in 8
4Texas A&MSEC4-0·Power 8.18 (33)·Gap +51.82·▲3Ranked 4. The model replayed this schedule 1,000 times, and this team finished between 4 and 112 of 136 in 90% of them.0.8611 in 7
5OregonBig Ten5-0·Power 19.07 (3)·Gap +40.93·▲2Ranked 5. The model replayed this schedule 1,000 times, and this team finished between 5 and 78 of 136 in 90% of them.0.8251 in 7
6Texas TechBig 124-0·Power 25.20 (1)·Gap +34.80·▼1Ranked 6. The model replayed this schedule 1,000 times, and this team finished between 1 and 97 of 136 in 90% of them.0.8191 in 7
7Georgia TechACC5-0·Power 4.29 (60)·Gap +55.71·▼6Ranked 7. The model replayed this schedule 1,000 times, and this team finished between 8 and 127 of 136 in 90% of them.0.8021 in 6
8Ole MissSEC5-0·Power 4.31 (58)·Gap +55.69·▼3Ranked 8. The model replayed this schedule 1,000 times, and this team finished between 9 and 125 of 136 in 90% of them.0.7921 in 6
9Ohio StateBig Ten4-0·Power 12.91 (17)·Gap +47.09·▲3Ranked 9. The model replayed this schedule 1,000 times, and this team finished between 4 and 113 of 136 in 90% of them.0.7891 in 6
10HoustonBig 124-0·Power 6.29 (46)·Gap +53.71·▼9Ranked 10. The model replayed this schedule 1,000 times, and this team finished between 8 and 114 of 136 in 90% of them.0.7651 in 6
11VanderbiltSEC5-0·Power 24.31 (2)·Gap +35.69·▼4Ranked 11. The model replayed this schedule 1,000 times, and this team finished between 6 and 74 of 136 in 90% of them.0.7631 in 6
12Iowa StateBig 125-0·Power 7.57 (38)·Gap +52.43·▲7Ranked 12. The model replayed this schedule 1,000 times, and this team finished between 9 and 112 of 136 in 90% of them.0.7621 in 6
13North TexasAmerican Athletic5-0·Power 13.02 (15)·Gap +46.98·▲3Ranked 13. The model replayed this schedule 1,000 times, and this team finished between 8 and 108 of 136 in 90% of them.0.7281 in 5
14LouisvilleACC4-0·Power 12.01 (19)·Gap +47.99·▲2Ranked 14. The model replayed this schedule 1,000 times, and this team finished between 6 and 121 of 136 in 90% of them.0.7141 in 5
15BYUBig 124-0·Power 14.42 (10)·Gap +45.58·▲1Ranked 15. The model replayed this schedule 1,000 times, and this team finished between 6 and 95 of 136 in 90% of them.0.7031 in 5
16MiamiACC4-0·Power 11.28 (20)·Gap +48.72·▲14Ranked 16. The model replayed this schedule 1,000 times, and this team finished between 9 and 114 of 136 in 90% of them.0.6181 in 4
17IllinoisBig Ten4-1·Power 7.05 (39)·Gap +18.58·▲8Ranked 17. The model replayed this schedule 1,000 times, and this team finished between 6 and 121 of 136 in 90% of them.0.5951 in 4
18UNLVMountain West4-0·Power 0.24 (83)·Gap +59.76·▼2Ranked 18. The model replayed this schedule 1,000 times, and this team finished between 14 and 128 of 136 in 90% of them.0.5771 in 4
19UtahBig 124-1·Power 17.75 (5)·Gap +5.88·▼7Ranked 19. The model replayed this schedule 1,000 times, and this team finished between 1 and 80 of 136 in 90% of them.0.5441 in 4
20MissouriSEC5-0·Power 7.69 (37)·Gap +52.31·▼1Ranked 20. The model replayed this schedule 1,000 times, and this team finished between 14 and 124 of 136 in 90% of them.0.4961 in 3
21MarylandBig Ten4-0·Power 10.14 (23)·Gap +49.86·▼8Ranked 21. The model replayed this schedule 1,000 times, and this team finished between 14 and 121 of 136 in 90% of them.0.4891 in 3
22NavyAmerican Athletic4-0·Power 11.21 (21)·Gap +48.79·▼18Ranked 22. The model replayed this schedule 1,000 times, and this team finished between 14 and 106 of 136 in 90% of them.0.4811 in 3
23GeorgiaSEC3-1·Power 8.47 (32)·Gap +14.41·▲1Ranked 23. The model replayed this schedule 1,000 times, and this team finished between 3 and 102 of 136 in 90% of them.0.4631 in 3
24Arizona StateBig 124-1·Power 8.15 (34)·Gap +13.53·▼4Ranked 24. The model replayed this schedule 1,000 times, and this team finished between 4 and 118 of 136 in 90% of them.0.4581 in 3
25MichiganBig Ten3-1·Power 12.76 (18)·Gap +8.35·▼2Ranked 25. The model replayed this schedule 1,000 times, and this team finished between 1 and 100 of 136 in 90% of them.0.3991 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.

How this works, and where it is weak →

run fe62b1d9 · published 2026-08-19 23:11:47 UTC · code e215160 · config 1ef7cf23…
q_ref 9.61 (Oklahoma) · β_w 7 · C 32 · h 5.865 · σ 20.081 · λ₁ 200 · λ₂ 2.0 · k 95.58 · w₁ 0.7248 · w₂ -0.1838
reproduce: uv run cfbpoll rank --season 2025 --through-week 5 --out out/