Fair value starts with power ratings and ends with a probability a trader can read off a screen. The model treats a power rating as a measure of team strength, simulates the paths to a championship, and outputs a raw title probability for each contender. That number is then checked against what the market itself is pricing, and the reconciled figure is published as fair value. Ohio State currently tops the board at 11.4%, with Notre Dame at 11.2% and Oregon at 10.2%.
How do power ratings become a title probability?
A power rating on its own does not answer the question that matters: what are the odds this team ends the season holding the trophy. To get there, the model runs the schedule forward many times, letting stronger ratings win more often and accounting for the bracket a team must survive. The frequency of simulated titles becomes the raw probability.
That step is why the top of the board is compressed rather than dominated by one name. Ohio State at 11.4%, Notre Dame at 11.2%, Oregon at 10.2%, Texas at 9.8%, Indiana at 9%, and Georgia at 8.7% sit inside a narrow band. The ratings separate these teams only slightly, and the simulation reflects that a single path to a title is fragile even for the strongest rating.
Why de-vig market prices at all?
A raw contract price is not a clean probability. Every venue builds in a margin, so the full field of title contracts adds up to more than 100%. De-vigging rescales those prices to strip the margin out, which lets a cent price be read directly as an implied chance.
The model uses that de-vigged read as a market anchor and blends it with the simulation output. When the two disagree, the gap is the signal: a contract priced well above its de-vigged fair value is expensive, and one trading near or below it is where value tends to sit. This is why fair value is not simply the raw price divided by 100.
Where do model and price line up now?
At the top of the board, price and fair value are close, which is typical for liquid favorites. Ohio State's best price is 13c on Kalshi against an 11.4% fair value. Notre Dame trades 13c on Polymarket versus 11.2%. Oregon is 11c on Kalshi against 10.2%, and Indiana is 10c on Kalshi against 9%.
The spread between a best price in cents and a fair value in percent is the cost of entry above the model's estimate. That gap is narrow for the favorites and tends to widen down the board, which is the structural reason longshots often screen as expensive once the margin is removed.
How does the cheapest venue get chosen?
Because the same team prices differently across venues, the consensus draws from both Polymarket and Kalshi and then points each team to the cheapest place to enter. Kalshi holds the best price on Ohio State, Oregon, Indiana, and Miami, while Polymarket owns Notre Dame, Texas, Georgia, and the tail names such as LSU and Alabama.
Routing to the lower price matters most when the model and market already agree, since the entry cost is the only variable left to control. For traders comparing venues, Kalshi's code FADE and Polymarket's code TGSWC are the promotions attached to those two books.
Prices and the model can both be wrong, and none of this is financial advice. The point is process: ratings to simulated probability, market price to de-vigged probability, and the reconciled figure as the fair value the rest of the board is measured against.
