Most of the statistical techniques we use weren't invented for football — they came from basketball, baseball, tennis, and American football. Here's what each sport contributed and how we've adapted those ideas.
Behind the scenes
What football can learn from other sports
Summary + sample · full document is 1,192 words
Summary
Sample
Basketball (NBA) — the player-rating template
The NBA's analytics revolution is roughly 15 years ahead of football's because the data was easier (fewer players per side, more discrete possessions, free public play-by-play) and the league embraced it institutionally.
- Plus-Minus / RAPM (Sill, 2010 and later): the best-validated "absolute player quality" rating in any team sport. Solves the linear-system problem with ridge regression and an informative prior. Football's RAPM analogues (see
player-quality.md) are a direct port; the data and lineup-rotation conditions are harder, but the template is the same. - Box-score plus-minus (BPM, RAPTOR, EPM, LEBRON): regress RAPM ratings on per-minute box-score features, giving a player rating computable from box scores alone. Football's vendor-specific composite ratings (StatsBomb player ratings, FBref Goals Created) follow the same pattern.
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