Topic-Contributed Paper Session

Statistical Methods for Estimating Player Performance Across Ages and Leagues

Mon, Aug 3, 2:00 PM - 3:50 PM Room CC-258A Thomas M. Menino Convention & Exhibition Center

Michael SchuckersOrganizerMonnie McGeeChair

Section on Statistics in Sports co: Section on Statistical Learning and Data Scienceco: Stats. Partnerships Among Academe Indust. & Govt. Committee Applied

4 Presentations

A Hierarchical Bayesian approach to Player Aging Curves accounting for different leagues.

2:05 PM - 2:25 PM

Michael Schuckers (UNC Charlotte)

sports analytics player aging Bayesian hierarchical

A multiple imputation approach to estimating aging curves in baseball

2:25 PM - 2:45 PM

Gregory Matthews (Loyola University Chicago)

Sports Multiple Imputation Aging

Does Age Shape How Athletes Move? Extending the Quantile Cube Framework to Detect Age Effects in Movement Distribution Profiles

2:45 PM - 3:05 PM

Kendall Thomas (UNC Chapel Hill)

sports analytics player aging Generalized Fiducial Inference GPS tracking

Player Aging Curves Across Sports, Metrics, and Eras

3:05 PM - 3:25 PM

Brian Macdonald (Yale University)

sports aging

Discussant

Josh Pohlkamp-Hartt (Boston Bruins)