Pythagorean Expectation in College Football: Turning Points Into Expected Wins
Points scored and allowed predict a team's record better than the record itself. How Pythagorean wins work in college football, with the 2.37 exponent.
Stat Explainers
The advanced numbers, built from scratch. What each metric measures, how it's actually computed, and where it misleads.
This is the section the rest of the site leans on. Each piece takes one advanced number — success rate, EPA, adjusted efficiency, havoc, field position, an Elo rating — and rebuilds it from public data: what it is actually counting, the formula in full, a worked example with real games, and an honest account of the sample size at which it stops meaning anything. Several pieces are season-long censuses rather than explainers: 877 cached 2024 games replayed to measure home field, the fourth-quarter comeback, the bye week, the letdown game. Read the explainer for a metric before you read an argument built on it, and treat the limits section at the bottom of each one as part of the finding, not a disclaimer.
Is a Great Record in Close Games Skill, or Just Luck?
A team that goes 7-1 in one-score games gets called 'clutch' — but from first half to second half of a season, close-game records correlate at just r=0.11.
How Fast Do Results Beat the Preseason Poll?
A preseason ranking is a prior; each game is evidence. Bayesian updating says results outweigh the poll after about 5 games under moderate trust.
From Point Spread to Win Probability: The Math of a College Football Favorite
A point spread converts cleanly to win probability under the normal model. A 3-point favorite wins about 57% of the time; a touchdown favorite, about 67%.
The Transitivity Trap: Why “We Beat the Team That Beat Them” Means So Little
If your team beat the team that beat the playoff team, are you better? Model it: 'A beat B beat C' implies 'A beats C' just 51% of the time between even teams.
The K-Factor: How Fast Should a Rating System React?
Every rating system has one dial — the K-factor — deciding how much one game moves a rating. Crank it up and ratings chase flukes; turn it down and they lag.
Why Underdogs Slow the Game Down: Pace, Variance, and the March Upset
Slowing a college basketball game doesn't make the underdog better — it makes the favorite's edge matter less. The random-walk math behind 'shorten the game.'
How Many Carries Until a Rushing Average Is Real? Sample Size, Explained
A 7.2 yards-per-carry start is a mirage with an error bar. Uncertainty shrinks with the square root of carries, so a 20-carry sample is ±2.6 yards.
When Is a College Football Lead Safe? The Math of Comebacks
"Two-score game" isn't a category — it's a probability that depends on the clock. Modeled as a random walk, an 8-point lead is 81% safe early, 99% safe late.
How Far Is Too Far? The Math of Field Goal Range
A kicker's "range" isn't a yard line — it's where the expected points of a try fall below punting. Why a 52-yarder (≈1.0 EP) is a genuine coin-flip decision.
Kick or Go for Two? The Expected-Value Math Behind the Extra Point
Convert two-point tries just under half the time and expected points says always go for two. The break-even is 47%; the average college team sits on it.
How College Football Win Probability Models Work (and Why They Swing So Hard)
A live win-probability graph that lurches 40 points on one snap isn't broken — that's leverage. Build the logistic model and see where the swings come from.
Passing Efficiency Beyond Passer Rating: YPA, ANY/A, CPOE, and EPA
Yards per attempt, adjusted net yards per attempt, completion over expected, and EPA per dropback — what each adds beyond NCAA passer rating.
Line Yards and Highlight Yards: Splitting the Run Game's Credit
Yards per carry can't tell you whether the line or the back earned the run. How line yards, opportunity rate, highlight yards, and stuff rate split the credit.
Points Per Drive: Why Possessions Beat Per-Game Scoring
Points per game is contaminated by pace. Why points per drive, available yards, and drive-finishing rank offenses and defenses fairly — and how to read them.
Run-Stuff Rate and the Defensive Front: Measuring Disruption at the Line
Stuff rate counts the runs a defense stops at or behind the line. What it measures, how it relates to havoc, and how front-seven play shows up in the numbers.
Red-Zone Defense: How to Measure the Bend-Don't-Break Side
Red-zone defense is its own skill: holding offenses to field goals, the field-shrinks dynamic, and why TD% allowed and points-per-trip beat scoring percentage.
Fourth-Down Decisions: When the Math Says Go For It
Go, punt, or kick on fourth down — by field position and distance. The win-probability framing, and why analytics pushes toward going for it.
Pass Protection and Sack Rate: Line, Quarterback, or Scheme?
Sack rate allowed versus created, why pressure and sacks aren't the same thing, and how much credit belongs to the line, the quarterback, and the scheme.
Red-Zone Efficiency in College Football: TD Rate vs. Points Per Trip
Red-zone scoring percentage flatters teams that settle for field goals. Why touchdown rate and points per trip tell the truth about red-zone offense.
Third-Down Conversion: Why Distance-to-Go Decides the Down
Third-down conversion rate is a headline efficiency stat — but third-and-1 and third-and-12 are different games. How distance-to-go ties it to success rate.
The NCAA Passer Rating Formula, Explained
The exact NCAA passer rating formula, worked term by term, how it differs from the NFL's capped rating, and the real limitations of a single quarterback number.
Standard Downs and Passing Downs: Reading Efficiency by Situation
Third-and-1 and third-and-12 aren't the same game. How splitting plays into standard downs and passing downs sharpens every efficiency number.
Turnover Margin and Turnover Luck: The Noisiest Stat in Football
Turnover margin decides games but barely predicts them. Why fumble recoveries are close to a coin flip, how turnover luck regresses, and what's actually skill.
Havoc Rate: The Advanced Defensive Stat That Measures Disruption
Havoc rate counts the plays a defense blows up — tackles for loss, forced fumbles, and passes defensed — as a share of snaps. How it's built and what it shows.
Field Position and Expected Points: The Hidden-Yardage Battle
Not all yards are equal. How expected points turns a spot on the field into a scoring value, and why field position quietly decides close games.
FEI and Drive Efficiency: Rating College Football by Possessions, Not Plays
The Fremeau Efficiency Index grades whole possessions, not single plays. How drive-based, opponent-adjusted efficiency complements SP+ and explosiveness.
Explosiveness and Yards Per Play: The Other Half of College Football Efficiency
Success rate measures how often you stay on schedule; explosiveness measures the big plays. How yards per play and marginal explosiveness complete the picture.
Why College Stats Need Adjusting: Strength of Schedule, Explained with Data
A worked strength-of-schedule calculation from a real schedule, and why unadjusted stats reward the soft slate.
Adjusted Tempo and Efficiency in College Basketball: A Practical Guide
Possessions, points per 100, and opponent adjustment — the tempo-free framework that makes basketball stats comparable.
How the NET Ranking Works (And What It Gets Right and Wrong)
The NCAA's NET, quadrants, and the selection committee: what the metric rewards, what it ignores, and how to read a team sheet.
Success Rate and EPA in College Football, Explained from Scratch
Compute success rate and expected points added by hand from a real drive, and see why down-and-distance beats raw yards.
SP+ and Adjusted Efficiency: How Advanced College Football Ratings Work
What SP+ actually measures, why opponent adjustment matters more than raw stats, and how a tempo-free efficiency rating is built.