Predicting Multiple Injuries to Major League Baseball Pitchers: A Logistic Regression Analysis over the 2009 - 2019 Regular Seasons

Department

School of Data Science and Analytics

Document Type

Article

Publication Date

3-16-2022

Abstract

In Major League Baseball (MLB), player injuries requiring injured list (IL) stints are common occurrences during the regular season. Injuries to pitchers may be of specific interest to prevent and detect as they may have a detrimental effect on team performance. In the present study, the effect between team wins and frequency of pitcher injuries is assessed over the 2009-2019 regular seasons (a total of n = 2,584 pitcher injuries were analysed). The study further aimed to determine if changes in pitcher performance, as quantified by changes in common pitching statistics, including strikeout and walk percentage, can predict whether a pitcher, who has already incurred an IL stint, will require a second IL stint over the same time period. Results suggest that while only a weak relationship exists between team wins and frequency of pitcher injuries, that a decrease in strikeout percentage for a pitcher returning from the IL is associated with an increased likelihood of a second IL stint. Future research should take into consideration a player's value or contribution to their team's success when assessing the effect injuries have on team performance as well as the type of injury sustained.

Journal Title

Research in Sports Medicine

Journal ISSN

1543-8627

First Page

1

Last Page

7

Digital Object Identifier (DOI)

10.1080/15438627.2022.2052067

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