STATISTICS COLLOQUIUM
Brian Macdonald
Director of Sports Analytics
ESPN
A Bayesian hierarchical regression-based metric for NBA players
Abstract
We present a Bayesian hierarchical regression model that estimates the value of box score statistics and player coefficients simultaneously, and provides an estimate of a player’s contribution to his team’s on-court performance. We discuss how our approach differs from other regression-based metrics, provide visualizations of those differences over time as a way to highlight the characteristics of each, and discuss how this approach could be used in hockey, soccer, football, or eSports.
Brian Macdonald is currently the Director of Sports Analytics in the Stats & Information Group at ESPN. He was previously the Director of Hockey Analytics with the Florida Panthers Hockey Club, and an Associate Professor in the Department of Mathematical Sciences at West Point. He received a Bachelor of Science in Electrical Engineering from Lafayette College, Easton, PA, and a Master of Arts and a Ph.D. in Mathematics from Johns Hopkins University, Baltimore, MD.
DATE: Friday, November 22, 2019
TIME: 11:00 am
PLACE: Philip E. Austin Bldg., Rm. 344
Coffee will be served at 10:30 am in the Noether Lounge (AUST 326)
For more information, contact: Tracy Burke at tracy.burke@uconn.edu