ICOTS8: Scientific Programme: Paper 7B2

This paper is from Session 7B: Statistics and sports

Full topic list

which comes under Topic 7: Statistics education and the wider society

(Wednesday 14th, 11:00-13:00)

Statistical models for student projects with sports themes

Presenter

Robin Lock (St. Lawrence University, United States)

Abstract

We describe several types of student project assignments that involve applications of statistical models to address questions arising from sports data. Although we illustrate these ideas with examples from specific sports, our goal is to provide sufficiently general guidelines to allow instructors to adapt and extend the topics to different sports, teams, leagues or levels of play. Some of the projects are accessible to students at the introductory levels while others are more appropriate for a second course or even an undergraduate capstone/thesis. Topics include Bill James’ so-called “Pythagorean law” for estimating team winning percentages, investigations of home field advantage, logistic regressions on the chance of winning a match based on boxscore statistics, the use of empirical Bayesian Stein estimators to project player performance over a full season based on early season results, and methods for modeling outcomes in seeded tournaments.