Performance Analytics and Pitch Metrics as Predictors of Ulnar Collateral Ligament Injury in Major League Baseball Pitchers (128). Issue 10 (31st October 2021) - Fury, Matthew; Scarborough, Donna; Oh, Luke; Wright-Chisem, Joshua; Fury, Jacob; Berkson, Eric
Objectives: Ulnar collateral ligament (UCL) injury is a significant concern in elite throwers, and it is associated with prolonged time away from competition in Major League Baseball (MLB) pitchers. Identifying athletes at higher risk of injury, with the subsequent goal of injury prevention, may positively impact pitcher health while mitigating the significant economic impact of this injury on professional organizations. As technology continues to advance, more granular assessments of performance are becoming possible. In 2015, Major League Baseball introduced StatCast, a spatiotemporal data tracking system that uses a standardized camera system and radar technology, to optically track player and ball movement to measure and quantify game events. This technology allows for further investigation of the science of pitching and provides new frontiers for injury research. Understanding UCL injuries in MLB pitchers may also provide insight into youth pitching injuries. To date, there is a paucity of evidence regarding risk factors of UCL injury in MLB pitchers. Methods: All MLB pitchers who underwent primary UCLR between 2015 and 2019 were identified from publicly available reports. This date range was selected to capture the seasons in which Statcast data was available. Advanced analytics and pitch metrics from the injury season—including velocity, spin rates, and pitch movement from MLB StatCast data—were collected as well as the seasonal data of an uninjured control group. Binomial logistic regression analysis was performed to determine risk factors for UCL injury. Results: Seventy-six MLB pitchers undergoing primary UCL reconstruction were included, and a control group of 95 uninjured pitchers was identified. There was no significant difference in age, height, weight, or BMI between the two cohorts. A logistic regression model was created using the following variables: 4-seam fastball velocity, 4-seam fastball spin rate, slider spin rate, curveball spin rate, strikeout percentage, and wins above replacement (WAR). The model explained 18.4% of the variance and predicted 70.4% of UCL injuries. Increasing WAR was associated with increasing likelihood of subsequent UCL injury (odds ratio [OR] 2.34; 95% CI, 1.08–5.07; p = 0.031). Conclusions: When controlling for fastball velocity and pitch spin rates, MLB pitchers who are more valuable, as indicated by WAR, may be at an elevated risk of UCL injury. While velocity is a known risk factor for UCL injury, this model indicates that other factors, including performance or pitch metrics, may influence single-season injury risk and warrant future investigation in multi-year studies.