This Week in Sports Analytics:
Nathan Sandholtz and Jacob Mortensen introduce lineup points lost and lineup point lost contributions to measure efficiency in shot allocation in their Sloan paper titled “Chuckers: Measuring Lineup Shot Distribution Optimality Using Spatial Allocative Efficiency Models”.
The NFL Big Data Bowl concluded on Wednesday and there was a lot of great work. I was particularly interested in the Expected Hypothetical Catch Probability model that Katherine Evans and Sameer Deshpande put together. Katherine has put together an explanation of the work in part 1 of a planned 4 part series.
Prashanth Iyer put together an RShiny App to visualize RAPM data from Evolving Hockey. While baseball has had WAR for over a decade, it is fun to see other sports work on developing their own public versions.
Javier Fernandez, Luke Bornn, and Dan Cervone “Decompose the Immeasurable Sport” by constructing a model that quantifies the expected value of any soccer possession at a frame-by-frame level. Luke Bornn and his lab have consistently put out great work at the Sloan Analytics Conference and he put together a twitter thread on all 11 papers over the last 5 years.
Richard McElreath’s Statistical Rethinking is a must read for anyone looking to learn Bayesian statistics. He recently finished posting his 2019 course lectures here.