A study on momentum in sports based on entropy weight-fuzzy evaluation and stacking model

Haoxiang Luo; Xianglan Liu; Keqing Zhang; Tao Liu

doi:10.1117/12.3035183

21 July 2024 A study on momentum in sports based on entropy weight-fuzzy evaluation and stacking model

Haoxiang Luo, Xianglan Liu, Keqing Zhang, Tao Liu

Proceedings Volume 13219, Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024); 132192S (2024) https://doi.org/10.1117/12.3035183
Event: 4th International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2024), 2024, Kaifeng, China

Abstract

This study proposes entropy weight-fuzzy evaluation and stacking model to quantify and predict momentum in sports competitions. While many traditional studies have explained the existence of momentum from psychological and statistical perspectives, this study focuses on analyzing momentum in sports based on mathematical model and machine learning. Taking 2023 Wimbledon Men’s Singles Final as an example, this study conducted corresponding data processing. Next, the study employed the entropy-weighted fuzzy evaluation model to quantify momentum and utilized stacking models to predict momentum fluctuations with high precision, aiding coaches in providing targeted guidance for athletes to enhance performance and strategic planning. Furthermore, this study also conducted a generalizability test on the model, applying it to various sports events including other matches in the Wimbledon tennis championship and the Olympic badminton finals. The results show that the model can effectively capture the momentum of athletes and predict fluctuations in moments in matches across different sports events.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Haoxiang Luo, Xianglan Liu, Keqing Zhang, and Tao Liu "A study on momentum in sports based on entropy weight-fuzzy evaluation and stacking model", Proc. SPIE 13219, Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024), 132192S (21 July 2024); https://doi.org/10.1117/12.3035183

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