A Quantitative Analysis of the Effect of Pitch Sports on Players’ Potential Energy - Tang, Weiyu; Yi, Xuanzeng; Zhao, Huimin (Transactions on Computer Science and Intelligent Systems Research, 2024)
This paper introduces a research framework for sports science, particularly in competitive tennis, focusing on momentum as a crucial factor impacting match outcomes. It addresses controversies surrounding momentum’s definition, quantification methods, and its influence on results, highlighting the lack of research on momentum strategies. The study proposes a paradigm for calculating potential energy and employs the XGBOOST model optimized with DA to predict players’ potential energy values with high accuracy (R2=0.9836). Through SHAP analysis, it delves into potential energy fluctuations, identifying factors such as continuous court running, winning shot execution frequency, stroke distance, intensity, and ball speed as significant influencers, varying among players. Furthermore, the paper utilizes GA for potential energy optimization, offering tailored training strategies. It concludes by discussing the model’s universality, emphasizing its research significance. This framework aids in pinpointing match shortcomings in individual players and devising personalized training plans accordingly.