Predicting Injury in Professional Baseball Pitchers From Delivery Mechanics: A Statistical Model Using Quantitative Video Analysis

摘要

Baseball pitching imposes significant stress on the upper extremity and can lead to injury. Many studies have attempted to predict injury through pitching mechanics, most of which have used laboratory setups that are often not practical for population-based analysis. This study sought to predict injury risk in professional baseball pitchers using a statistical model based on video analysis evaluating delivery mechanics in a large population. Career data were collected and video analysis was performed on a random sample of former and current professional pitchers. Delivery mechanics were analyzed using 6 categories: mass and momentum, arm swing, posture, position at foot strike, path of arm acceleration, and finish. Effects of demographics and delivery scores on injury were determined using a survival analysis, and model validity was assessed. A total of 449 professional pitchers were analyzed. Risk of injury significantly increased with later birth date, role as reliever vs starter, and previous major injury. Risk of injury significantly decreased with increase in overall delivery score (7.8%) and independently with increase in score of the mass and momentum (16.5%), arm swing (12.0%), and position at foot strike (22.8%) categories. The accuracy of the model in predicting injury was significantly better when including total delivery score compared with demographic factors alone. This study presents a model that evaluates delivery mechanics and predicts injury risk of professional pitchers based on video analysis and demographic variables. This model can be used to assess injury risk of professional pitchers and can be potentially expanded to assess injury risk in pitchers at other levels.