Basketball analytics

Basketball analytics applies statistical and computational methods to evaluate player performance, team strategy, and decision-making in basketball.

Basketball possession: A team’s period of control of the ball, ending when the opponent gains control or a period ends. Possessions provide the denominator for comparing teams that play at different tempos.
Player tracking data: Spatial and movement records for players and the ball, captured over time during play. Tracking reveals positioning and movement that box-score totals cannot describe.
Three-point revolution: The strategic shift toward taking more three-point shots in professional basketball. Shot-value analysis helped explain why many teams increased three-point volume.
Box score: A record of basic game statistics such as points, rebounds, assists, and turnovers. Box scores count visible events but omit much of the context analytics attempts to model.
Pace factor: An estimate of the number of possessions a team uses per game. Pace separates scoring volume from the number of chances a team creates.
Shot chart: A visual display of shot locations and outcomes on a basketball court. Location patterns expose where a player or team shoots efficiently.
Lineup optimization: The selection of player combinations to maximize a team’s expected performance. Player-impact estimates and matchup data can guide which five players share the floor.
Wins above replacement: An estimate of a player’s added wins compared with a readily available replacement. It converts player impact into a season-level contribution, unlike per-possession ratings.
Offensive rating: Points scored per 100 possessions by a team or player. It measures scoring efficiency while controlling for differences in tempo.
Shot quality: An estimate of how likely a shot is to be made, given its circumstances. Shot quality distinguishes a good attempt from a favorable or unfavorable result.

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