A spatial analysis of basketball shot chart data

Brian J. Reich, James S Hodges, Brad Carlin, Adam M. Reich

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Basketball coaches at all levels use shot charts to study shot locations and outcomes for their own teams as well as upcoming opponents. Shot charts are simple plots of the location and result of each shot taken during a game. Although shot chart data are rapidly increasing in richness and availability, most coaches still use them purely as descriptive summaries. However, a team's ability to defend a certain player could potentially be improved by using shot data to make inferences about the player's tendencies and abilities. This article develops hierarchical spatial models for shot-chart data, which allow for spatially varying effects of covariates. Our spatial models permit differential smoothing of the fitted surface in two spatial directions, which naturally correspond to polar coordinates: distance to the basket and angle from the line connecting the two baskets. We illustrate our approach using the 2003-2004 shot chart data for Minnesota Timberwolves guard Sam Cassell.

Original languageEnglish (US)
Pages (from-to)3-12
Number of pages10
JournalAmerican Statistician
Volume60
Issue number1
DOIs
StatePublished - Feb 1 2006

Keywords

  • Bayesian
  • Conditionally autoregressive prior
  • Sports

Fingerprint Dive into the research topics of 'A spatial analysis of basketball shot chart data'. Together they form a unique fingerprint.

Cite this