In Major League Baseball (MLB), pitchers frequently sustain injuries that require rehabilitation following placement on the injured list (IL). In some cases, pitchers return to competition before fully recovering, increasing the risk of reinjury and multiple IL stints. Early identification of incomplete rehabilitation is therefore critical for protecting player health and maintaining team performance. Although advanced statistical learning methods have been proposed to detect changes in pitcher performance, such approaches typically require large amounts of training data for each individual, limiting their practical applicability. Given the objective of efficiently detecting changes in performance over time, statistical process control charting methods provide a natural alternative. This study proposes a control chart that integrates a process capability index with a cumulative summation (CUSUM) framework to monitor changes in an individual pitcher's game-by-game Walks and Hits Per Inning Pitched (WHIP) statistic. Results indicate that the proposed method effectively identifies elevated reinjury risk, signalling potential issues between four and nine games earlier than current practices, with sensitivity ranging from 72% to 99%. These findings highlight the potential of process monitoring techniques to enhance injury management in professional baseball.
Keywords: Injury management; injury prediction; player performance; quality control.