ML models for baseball pitch speed prediction show poor cross-individual generalizability, with R-squared falling from 0.91 within individuals to 0.38 across individuals, and trunk/pivot leg kinematics providing the strongest transfer.
The GNN-GRU model showed the best predictive performance in a previous study on ball speed prediction (Yang et al., 2025)
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Cross-individual generalizability of machine learning models for ball speed prediction in baseball pitching
ML models for baseball pitch speed prediction show poor cross-individual generalizability, with R-squared falling from 0.91 within individuals to 0.38 across individuals, and trunk/pivot leg kinematics providing the strongest transfer.