Intelligent Assessment of Athletes' Physical Fitness Data and Optimization of Physical Education Teaching and Training Strategies in the Framework of Multivariate Statistical Analysis

Authors

  • Yefei Zhang College of Physical Education, Shanghai University of Electric Power, Shanghai, 200090, China
  • Chunlin Qin Foundation Department, Nantong Health College of Jiangsu Province, Nantong, Jiangsu, 226000, China

DOI:

https://doi.org/10.70917/ijcisim-2026-0207

Keywords:

correlation analysis; regression model; physical education training; athletes

Abstract

Athletes' physical fitness evaluation is not only an important part of sports work, but also an important part of school education evaluation system. This study carries out a multivariate statistical analysis between the various scores of athletes' sports test and the total score, establishes the regression equation between the total score and the physical form and function, and carries out an intelligent evaluation of athletes' physical quality through the regression model. At the same time, the factors affecting athletes' physical quality were explored based on the regression equation. After analyzing, athletes' physical quality can be assessed based on Athletes' physical quality=67.632+0.163×T1-0.263×T2+0.063×T3. Athletes' physical quality is mainly affected by individual factors and school factors. In this regard, this paper puts forward the optimization strategy of sports teaching and training from three aspects: cultivation mode, teaching method and evaluation mechanism. This is of great practical significance to improve athletes' health and physical quality.

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Published

2026-02-08

How to Cite

Yefei Zhang, & Chunlin Qin. (2026). Intelligent Assessment of Athletes’ Physical Fitness Data and Optimization of Physical Education Teaching and Training Strategies in the Framework of Multivariate Statistical Analysis. International Journal of Computer Information Systems and Industrial Management Applications, 18, 13. https://doi.org/10.70917/ijcisim-2026-0207

Issue

Section

Original Articles