College Football Power Rankings
Every team Kalshi prices for the College Football Playoff, ranked by one 0–100 score built from market prices and on-field results. 74% of each score is what traders are paying right now for a team to make the playoff or win the title; the rest is what the team has actually done, measured against who it did it against.
2026 · after Week 2Updated Friday, Sep 18, 2026 · 1:30 AM ET
Ranking method: Every team is scored before any are shown. Prices are scaled across the whole field to sum to twelve playoff places, and the on-field and market-strength ratings are scaled against it too, so a shorter board would be a different board.
Market-implied ranking
2026 College Football Power Rankings after Week 2
25 of 51 teams
| Score and its inputs | ||||||
|---|---|---|---|---|---|---|
| 1 | TexasSEC | 2-0 | 63.39 | 77% | 89.2 | 83.6 |
| 2 | Notre DameIndependent | 2-0 | 62.82 | 70% | 98.0 | 100.0 |
| 3 | GeorgiaSEC | 2-0 | 62.23 | 77% | 83.6 | 83.6 |
| 4 | IndianaBig Ten | 2-0 | 61.10 | 74% | 89.3 | 81.4 |
| 5 | Miami (FL)ACC | 2-0 | 60.55 | 70% | 87.2 | 100.0 |
| 6 | Ohio StateBig Ten | 1-1 | 57.06 | 71% | 69.3 | 86.0 |
| 7 | LSUSEC | 2-0 | 53.65 | 63% | 98.2 | 56.0 |
| 8 | Mississippi StateSEC | 2-0 | 48.48 | 58% | 97.1 | 44.7 |
| 9 | AlabamaSEC | 2-0 | 47.84 | 52% | 96.6 | 58.9 |
| 10 | USCBig Ten | 3-0 | 42.42 | 40% | 94.8 | 73.2 |
| 11 | Texas A&MSEC | 2-0 | 41.97 | 40% | 97.5 | 61.3 |
| 12 | Texas TechBig 12 | 2-0 | 39.90 | 42% | 76.4 | 70.0 |
| 13 | Penn StateBig Ten | 2-0 | 39.61 | 34% | 95.7 | 75.5 |
| 14 | Ole MissSEC | 2-0 | 37.88 | 39% | 84.3 | 44.1 |
| 15 | TennesseeSEC | 2-0 | 37.77 | 37% | 84.5 | 58.3 |
| 16 | OregonBig Ten | 1-1 | 35.63 | 38% | 50.5 | 82.0 |
| 17 | FloridaSEC | 2-0 | 34.11 | 31% | 86.8 | 47.5 |
| 18 | UtahBig 12 | 2-0 | 31.41 | 19% | 85.6 | 85.3 |
| 19 | MissouriSEC | 2-0 | 31.33 | 21% | 84.0 | 76.1 |
| 20 | BYUBig 12 | 2-0 | 30.98 | 21% | 81.0 | 76.5 |
| 21 | MichiganBig Ten | 2-0 | 30.02 | 22% | 77.8 | 65.5 |
| 22 | IowaBig Ten | 2-0 | 29.34 | 16% | 86.5 | 76.1 |
| 23 | South CarolinaSEC | 2-0 | 28.88 | 22% | 86.6 | 39.9 |
| 24 | SMUACC | 2-0 | 27.39 | 15% | 80.6 | 72.2 |
| 25 | OklahomaSEC | 1-1 | 27.26 | 21% | 66.7 | 62.5 |
Kalshi market viewThe book's own midpoint, and the conference adjustment between that and the number the Power Score used. Tap any price to trade the market it came from.
From the quote to the score
| Team | Playoff mid | Conf. value | Score used | Title mid |
|---|---|---|---|---|
| 1TexasSEC | 73% | +5.02 | 77%+6.6 pts | 15% |
| 2Notre DameIndependent | 86% | +1.65 | 70%−12.3 pts | 13% |
| 3GeorgiaSEC | 74% | +5.02 | 77%+6.3 pts | 12% |
| 4IndianaBig Ten | 75% | +4.25 | 74%+2.1 pts | 11% |
| 5Miami (FL)ACC | 85% | +1.65 | 70%−12.5 pts | 12% |
| 6Ohio StateBig Ten | 71% | +4.25 | 71%+2.4 pts | 12% |
| 7LSUSEC | 55% | +5.02 | 63%+9.3 pts | 8% |
| 8Mississippi StateSEC | 50% | +5.02 | 58%+9.6 pts | <1% |
| 9AlabamaSEC | 44% | +5.02 | 52%+9.9 pts | 4% |
| 10USCBig Ten | 38% | +4.25 | 40%+3.8 pts | 2% |
| 11Texas A&MSEC | 32% | +5.02 | 40%+9.3 pts | 3% |
| 12Texas TechBig 12 | 55% | +2.31 | 42%−11.1 pts | 2% |
| 13Penn StateBig Ten | 32% | +4.25 | 34%+3.6 pts | <1% |
| 14Ole MissSEC | 31% | +5.02 | 39%+9.2 pts | 4% |
| 15TennesseeSEC | 29% | +5.02 | 37%+9.0 pts | 2% |
| 16OregonBig Ten | 36% | +4.25 | 38%+3.9 pts | 4% |
| 17FloridaSEC | 24% | +5.02 | 31%+8.1 pts | <1% |
| 18UtahBig 12 | 28% | +2.31 | 19%−7.6 pts | <1% |
| 19MissouriSEC | 16% | +5.02 | 21%+6.1 pts | <1% |
| 20BYUBig 12 | 31% | +2.31 | 21%−8.2 pts | <1% |
| 21MichiganBig Ten | 20% | +4.25 | 22%+2.8 pts | 3% |
| 22IowaBig Ten | 15% | +4.25 | 16%+2.3 pts | <1% |
| 23South CarolinaSEC | 17% | +5.02 | 22%+6.4 pts | <1% |
| 24SMUACC | 26% | +1.65 | 15%−10.1 pts | <1% |
| 25OklahomaSEC | 16% | +5.02 | 21%+6.1 pts | <1% |
A team is credited or docked against the board's reference point of +3.59, which is itself weighted by playoff price so the forty teams with no realistic chance don't drag it. Above that line a team's price rises; below it, falls. The two market columns are book midpoints rather than fillable prices; the ask is what you would pay, and the ticket shows it. Tap any price to trade the market it came from.
MethodologyFour inputs: 49% playoff price, 25% title price, 16% on-field results and 10% market-implied strength on this update. The weights are computed from how much football has been played and how much of the playoff race is still undecided. They are a property of today's date, not of any team.
How the Kalshi Power Score works
49%Playoff priceKalshi's price on this team making the twelve-team playoff, scaled so the whole board sums to 12 places, then adjusted for how hard its conference road is.Shrinks as the playoff race resolves; still wide open, so it carries the most weight.
25%Championship priceIts price to win it all, scaled so the board sums to one champion. The one market with no path in it: winning the title means beating everyone, whatever the route.
16%On-field resultsOpponent-adjusted margin, win percentage corrected for schedule, and the Pythagorean win rate, blended 45/35/20 across all 138 FBS teams.At 2.1 games a team it carries 52% of its full weight, reaching all of it at 4.
10%Market strengthA strength rating fitted to Kalshi's individual game prices, so it reads quality with no route to the playoff mixed into it. That is the thing a qualification price cannot separate.Phases in on the same ramp as the on-field leg.
1 · The market prices49% playoff + 25% titleBoth are de-vigged first, with playoff prices scaled so the board sums to 12 places and title prices to one champion, because a futures field always prices to more than the outcomes that exist. That step couples every team together: a team's score can move when its own market did not, because someone else's did and 12 places is a fixed pool.
2 · What happened on the field0.45 adj. win% + 0.35 SRS + 0.2 PythagoreanSRS solves one rating per team such that every game's margin is explained at once, after stripping 4.53 points of home field and capping the margin at 28, so beating an FCS team by 50 cannot outscore winning a real game. The Pythagorean term runs at an exponent of 2.22. All three are scaled across the FBS field and floored at 12.
3 · The conference handicaplog-odds shift of 0.3146 × (conference − +3.59)A playoff price answers "will this team get in", which blends how good a team is with how easy its road is. The handicap subtracts an estimate of the road, measured as each conference's mean rating last season. Applied in log-odds so no price can be pushed past 0 or 100, then rescaled back to 12 places. The reference point is price-weighted, so teams with no realistic chance don't drag it; on this board it sits at +3.59.
The conference adjustmentMeasured as each conference's mean opponent-adjusted rating over last season, and applied to the playoff price only. Static: recomputed after realignment, never mid-season.
What each conference is worth
| Conference | Value | On board |
|---|---|---|
| SEC | +5.02 | 16 |
| Big Ten | +4.25 | 9 |
| Big 12 | +2.31 | 10 |
| ACC | +1.65 | 11 |
| Notre Dame | +1.65 | 1 |
| American Athletic | −1.37 | 2 |
| Mountain West | −2.45 | – |
| Pac-12 | −2.45 | – |
| Sun Belt | −3.26 | 1 |
| Conference USA | −5.05 | – |
| Mid-American | −5.88 | 1 |
A ranking made of prices, not opinions
A poll asks a few dozen people who they think is best. This asks everyone who is willing to put money behind an answer. 74% of each score is Kalshi's own price: what it costs, right now, to back this team to make the playoff or to win the championship. Those prices update continuously against real money rather than once a week against a deadline.The other 26% is what a price cannot tell you: what has already happened. Two teams can be priced identically because one has a soft road and the other is genuinely better, so the board measures results directly. Every game's margin is solved against every other team's, adjusted for venue and capped so a blowout of an overmatched opponent cannot masquerade as a win over a good one. It then subtracts an estimate of road difficulty from the playoff price itself, which is the one adjustment a market price alone will not make for you.Expect this board to move, including on days nobody plays. 0.57 points separate first from second right now, and a normal day's trading is easily worth more than that. That is the board reporting that the market cannot currently separate those two teams, which is information rather than instability.Week 3The next slate Kalshi prices, led by the 8 involving a ranked team. These game prices are also what the market-strength leg is fitted to, so a result here moves the board twice: once through the score, and once through every price that re-prints around it.
Games that can move the board
#5 Miami at Wake ForestWeek 3 · Sep 18 · 7:30 PM ET8%Wake Forest win#3 Georgia at #51 ArkansasWeek 3 · Sep 19 · 12:00 PM ET5%Arkansas winKent State at #6 Ohio StateWeek 3 · Sep 19 · 12:00 PM ET>99%Ohio State winWestern Kentucky at #4 IndianaWeek 3 · Sep 19 · 4:00 PM ET>99%Indiana winMichigan State at #2 Notre DameWeek 3 · Sep 19 · 7:30 PM ET98%Notre Dame win#7 LSU at #14 Ole MissWeek 3 · Sep 19 · 7:30 PM ET42%Ole Miss winUTSA at #1 TexasWeek 3 · Sep 19 · 8:00 PM ET98%Texas winNorthwestern at #4 IndianaWeek 4 · Sep 25 · 8:00 PM ET92%Indiana win
FAQ
College football power ranking questions
How is the Kalshi Power Score calculated?
Each team gets a score from 0 to 100 built from four inputs on this update: 49% playoff price, 25% title price, 16% on-field results and 10% market-implied strength. The weights are recomputed every time the board is built, from how much football has been played and how much of the playoff race is still undecided.
Why is Texas ranked first?
Texas scores 63.39. Kalshi prices it at 73% to make the playoff (77% after de-vigging and the conference adjustment), 15% to win the championship, an on-field rating of 89.2 out of 100 from a 2-0 start, and 83.6 on market-implied strength.
Why are only 51 teams ranked and not all 138?
The board is every team Kalshi lists a playoff market for, which is currently 51. A team with no playoff market cannot be scored, because two of the four inputs would be empty. All 51 are scored before anything is shown: the de-vig sums across the whole board, both on-field measures are scaled against the field's own best and worst, and the handicap's reference point is an average over every team, so slicing to a top 25 before scoring would change every number that survived.
What is the conference adjustment, and why does Notre Dame get the ACC number?
A playoff price answers "will this team get in", which mixes how good a team is with how easy its road is, and two teams can sit at 55% for opposite reasons. So each team's price is shifted by its conference's mean rating from last season, in log-odds, and the board is rescaled back to 12 places. Notre Dame is an independent, so there is no conference value to look up and a rule had to be chosen: it takes the ACC's +1.65, because six of its twelve games are against ACC teams, ten are against Power Four opposition, and every ACC team receives that number regardless of its own schedule. That is a judgment call rather than a measurement, and it is stated as one.
Why did a team move when nobody played?
Because the market moved. Around 12,000 contracts have traded in a single 24-hour window with no games on it, and the top of this board is separated by well under a point, and a mean price move of about one cent has been enough to swap first and second. The de-vig amplifies it: the playoff prices are rescaled so the board sums to 12 places, so when other teams rise, a team's own score falls without its own market having moved at all.
Is the board reliable this early in the season?
Less so than it will be, and it says so in its own weights: at 2.1 games a team the two on-field measures carry 52% of their full weight, reaching all of it at 4 games. There is a known early-season bias in the on-field leg: the Pythagorean term has no opponent adjustment at all and the schedule correction is still phasing in, so a lopsided win over a weak opponent is rewarded more than it should be. It washes out by October, and quality of win is read more sharply by the market-strength leg in the meantime.
Does the conference adjustment make the ranking more accurate?
Not in the sense of picking more games correctly. That has never been shown, and back-testing puts the with-and-without versions inside each other’s margin of error. What it does do is what it was built for: it removes the easy-road bias in a qualification price, which had the board over-ranking Group of Five teams by around six places against the AP. That is a different claim, and it is the only one being made for it.
Can I trade these markets?
Yes. Every price on this page is a live Kalshi market, and tapping one opens an order ticket on that exact contract. The prices shown next to a team in the ranking are the model’s: de-vigged, and for the playoff column adjusted for conference. The market table shows the book’s own midpoint: halfway between the bid and the ask, and a half-price where only one side is quoted, so it is a fair-value read rather than a number you can fill at. What you would actually pay is the ask, which the order ticket and the championship rail both show in cents.