A study on modeling the association between students’ psychological changes and athletic performance in physical education based on numerical computational methods

Mining the dynamic association between psychological state changes and sports performance is one of the core tasks of physical education towards scientific teaching.In this paper, the data of psychological change indexes of student athletes were collected by scales and the indexes variability was tested.Combined with the principal component analysis to extract the principal component factors of the psychological change index data, construct the correlation coefficient matrix, and calculate the multiple linear regression equations of psychological change and sports performance.The gray correlation model based on the whitening weight function was used to analyze the gray correlation between psychological change and athletic performance, and calculate the influence of the two.Among the 9 psychological indicators, 4 dimensions, such as social evaluation anxiety, had a significant difference with P<0.01.P<0.05 for 2 dimensions such as competition preparation anxiety, there was a difference.In the principal component analysis, the negative and positive psychological dimensions were extracted as principal components, including the 7 psychological indicator components excluding the 2 dimensions.Judging from the regression coefficients and gray correlation calculation results, the 3 psychological indicators of cognitive state anxiety, state self-efficacy, and injury anxiety had the greatest influence on sports performance.Targeted alleviation of cognitive and injury anxiety and improvement of self-confidence can optimize students' sports performance.