Evaluation of Competitive Performance Ability of Basketball Players Based on Hybrid Model

Author:

Li Lin1,Zhang Wei2ORCID

Affiliation:

1. Faculty of Chinese Medicine Science, Guangxi University of Chinese Medicine, Guangxi, Nanning 530222, China

2. Zhengzhou University, Institute of Physical Education (School Headquarters), Henan, Zhengzhou 450000, China

Abstract

Competitive performance ability is the on-the-spot performance of basketball players’ comprehensive use of technical and tactical, physical, and psychological abilities. Because basketball players’ competitive performance includes many evaluation contents and influencing factors, it is difficult to comprehensively and objectively use a single qualitative analysis or quantitative statistics for evaluation and measurement. Based on the analytic hierarchy process (AHP) and intelligent fuzzy comprehensive evaluation, this research establishes a hybrid model, which is applied to evaluate the performance of basketball players. Based on the actual needs, this research uses the relevant theories in the discipline of sports training, with abundant empirical data materials, combined with the specific practice of basketball players’ training and competition, starting from the concept of clear sports intelligence, to further determine the indicators of the basketball players’ sports intelligence evaluation system and weights, construct a set of evaluation system about basketball players, and use this as a standard to evaluate and judge the current situation of basketball players’ sports intelligence.

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Reference19 articles.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Residual Connection Based Deep Neural Network for Evaluation of Athlete Competitive Ability;2024 Third International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE);2024-04-26

2. Determining the key performance indicators on game outcomes in NBA based on quantile regression analysis;International Journal of Performance Analysis in Sport;2024-03-04

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