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Activity Number: 159 - SPEED: Sports and Business
Type: Contributed
Date/Time: Monday, July 31, 2017 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Sports
Abstract #324121 View Presentation
Title: Operations Research on NCAA Football Re-Injury Prevention
Author(s): Nelson Chung*
Companies: U. S. Census Bureau
Keywords: sports analytics ; injury prevention ; football ; data science ; probability

Beane (Lemire 2015) identified injury prevention as the next frontier in sports analytics. In this study, I demonstrate that statistics is essential by examining re-injury prevention, through testing whether NCAA coaches and players, facing the need to limit repetitions as key players recover from injury, allocate those repetitions in a manner that maximizes win probability. I calculate in-game win probabilities using the methodology of Stern (1991) and Winston (2009), NCAA historical point spread data from, and NCAA expected points of each down-distance-position state from Knowlton (2015). As a test case, I consider Brigham Young University's use of dual-threat quarterback Taysom Hill in his 2016 return from a prior-year Lisfranc injury. I extract play-by-play data from using R's rvest package and regular expression functions. I determine the situations in which Hill's rushing, based on his yards per carry prior to the game on standard and passing downs, maximizes changes in win probability.

Authors who are presenting talks have a * after their name.

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