Prediction of Collegiate Pitching Performance from Longitudinal Neuromuscular Performance Testing Data

BACKGROUND: Objective performance testing has become central to baseball, offering insights into force production, neuromuscular readiness, and joint-specific strength that are often invisible through observation. Despite advances in pitch tracking, no study has examined the relationship between these testing outcomes and advanced in-game metrics such as Stuff+. PURPOSE: The purpose of this study was to evaluate the predictive accuracy of neuromuscular performance testing metrics in forecasting pitching performance defined by Stuff+. METHODS: NCAA Division II pitchers were monitored during the 2025 season using countermovement jump (CMJ) and isometric strength testing, paired with in-game ball flight data. Each outing was matched to the nearest testing session within three days. A level-based Stuff+ model was developed to quantify performance, and multivariate stepwise linear regression was performed to identify predictors. RESULTS: Seventeen outings across eight pitchers were analyzed. The final model explained 61.5% of the variance in Stuff+ (96.16 ± 5.74; AIC = 100.4; p = 0.0153) and retained four predictors: dominant grip strength (DGS), eccentric rate of force development (ERFD), dominant shoulder external rotation strength (DSERS), and dominant hip adduction strength (DHADS). Among these, DGS (432.97N ± 138.94N; p = 0.017) and ERFD (6454.94N/s ± 2351.13N/s; p = 0.033) were statistically significant. CONCLUSION: Neuromuscular qualities including grip strength and eccentric force absorption emerged as key contributors to pitching performance. These findings support integrating CMJ and isometric strength testing with advanced analytics to inform individualized training, workload management, and talent identification in baseball.