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
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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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