Browse this week's slate
How the model works, and whether it does
See where every team stands, replay 2025
Who makes the twelve-team field
What we said, what happened, and where we split from the market
Your call against the projected margin
Saturday rates every team in points. That rating starts as a preseason projection and moves with the games actually played, and any matchup is then run thousands of times, which gives back a range of outcomes rather than one score. No game is ever priced using anything that happened after kickoff. That restraint is the only reason the record on the second tab is worth reading. Start with how it works.
Home strength minus away strength, plus home field. That is the projection. Every team carries exactly one number, and the distance between two of them is the margin Saturday expects. The rating itself starts in the spring, built off last year's team, the recruiting class, the portal haul, who came back and who is coaching. Then the season takes over and each week of results moves it. The one game a rating never sees is the one it is being asked to project.
Saturday rated Ohio State about 12.5 points stronger than Penn State on a neutral field. Add 3.3 for playing in Columbus and you get Ohio State by 15.8. Both of those ratings were fit on games those teams had already played, and nothing else.
A real, worked example from a completed game (week 10, 2025), fixed for illustration, not this week's projection.
There is a real formula underneath all of this, with real coefficients, and it is published. See what goes into a rating.
“Ohio State by 15.8” is the middle of a range, not a call on the final score. Play that game a thousand times and it lands everywhere from a rout to a Penn State win, because that is what this sport does on a given Saturday. So the answer is a curve. The win probability is the share of it sitting on the winning side of zero.
The curve is about 16 points wide, and it has to be. Good teams lose games they have no business losing, often enough that a model shrugging it off would be overstating what it knows. The percentage on screen carries that risk instead of rounding it away.
On opening weekend the model has watched none of this season. It is working off last year, a recruiting class and a portal cycle, so it widens the curve to say so. Results narrow it. By midseason the ratings are built on real games and the range settles near its floor, where it stays. Uncertainty is a number here, not a disclaimer at the bottom of the page.
Chart's y-axis is σThe Greek letter sigma (σ), used here for how wide the range of likely outcomes is, in points. A bigger number means more uncertainty; it shrinks as the season goes on and Saturday sees more games., in points.
That is what the “early season · high uncertainty” flag on a game page is telling you. Fewer games behind a rating, wider range in front of it. Through those opening weeks Saturday also leans on per-play efficiency, which reads a team better than four final scores do, then fades it back out as real margins pile up.
Saturday prices games off its own ratings and never looks at a betting line to do it, which is what makes the market a fair scorekeeper. There is one exception, disclosed on purpose: preseason market win totals help set each team's opening rating, an influence that washes out as real games get played. Across four seasons (2022 through 2025), Saturday finishes within about half a point of where the market closed from week 5 on, and on plenty of games it had the better number. Everything below was priced before kickoff.
The market sided with the visitor. Saturday took the home team.
Florida was favored at home by nearly a touchdown. Saturday called it a coin flip.
Saturday rated the gap at under two touchdowns, not three.
Saturday had the favorite by nearly two touchdowns, not a field goal.
Those are the wins. The market still beats Saturday more often than not in September. The whole record, calibration and all, including where it trails, is on the .
The toggles on a game page are not sliders somebody eyeballed. Each one moves the margin by what that factor is actually worth, measured. A few of them barely move it at all, because that is all the data supports.
Fit stadium by stadium out of the margins themselves, from 2.3 at the quiet venues to 4.3 at the loudest
Per net giveaway. The biggest single swing any toggle can apply
Scaled to what the starter is worth per play. An elite quarterback costs far more than a replacement
What a shanked kick costs, on average
Per net sack, backtested
Per degree away from 60°F, and only on the projected points. Real, but small
No game is priced off what a sportsbook has posted. Every projection on this site comes out of Saturday's own ratings. The single exception is preseason market win totals, which help set the opening ratings in August and fade to nothing once real results arrive.
These are probabilities. A 75% favorite is supposed to lose one Saturday in four, and across a season it will. That is the model working, not failing.
This is here to help you understand a game. Beating a sportsbook was never the point, and nothing on this site promises it.
Every setting and every constant behind Saturday is written out: the preseason projections, the weekly rating fit, how the curve gets built and taken apart, the simulations, the scenario adjustments, and the four-season validation. Enough detail to rebuild the model from scratch.
→ THE SATURDAY MODEL · TECHNICAL SPECIFICATION (PDF)