Bayesian network learning for winning structure and losing structure in basketball games

Ziyang Zhang; Lei Zhang; Chengchen Wang; Zengfanxiang Wei

doi:10.1117/12.2578956

10 November 2020 Bayesian network learning for winning structure and losing structure in basketball games

Ziyang Zhang, Lei Zhang, Chengchen Wang, Zengfanxiang Wei

Proceedings Volume 11584, 2020 International Conference on Image, Video Processing and Artificial Intelligence; 115841H (2020) https://doi.org/10.1117/12.2578956
Event: Third International Conference on Image, Video Processing and Artificial Intelligence, 2020, Shanghai, China

Abstract

This paper proposes a learning model of basketball players structure based on the Bayesian network. By analyzing the data of NBA 's players, we complete the structural learning of basketball players network based on the +/- values of 5 resident players in the Portland Trail Blazers team. We finally obtain a winning and losing models for the five resident players of the Portland Trail Blazers team, and we make suggestions for coaches about player rotation based on the analysis of the models.

Citation Download Citation

Ziyang Zhang, Lei Zhang, Chengchen Wang, and Zengfanxiang Wei "Bayesian network learning for winning structure and losing structure in basketball games", Proc. SPIE 11584, 2020 International Conference on Image, Video Processing and Artificial Intelligence, 115841H (10 November 2020); https://doi.org/10.1117/12.2578956

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