Obstacles and Regulation Deconstruction of Athletes’ Psychological Training Based on Machine Learning Algorithm in Physical Education Teaching

Abstract

In sports, players had differences in psychological training principles, sports characteristics, and personal athletic ability due to differences in sports plans. At the same time, the winning and losing rules of various competitions would also limit the psychological training and tactical ability of players. The current problem with mental training for athletes was that it is impossible to accurately understand the mentality of athletes and make a reasonable adjustment plan. Therefore, this paper adopted a machine learning algorithm and used the methods of psychological testing and questionnaire research to carry out extensive research on the training and regulation of remote sports psychology. The possible psychological barriers and adjustment methods of athletes are supplemented, focusing on the comparison of four aspects: psychological endurance before training, control accuracy, anxiety score before psychological training, and the effects of before and after adjustment. And after in-depth research on the problem of athletes’ psychological training, the conclusion showed that the psychological tolerance value of athletes has increased by 18.9%, the accuracy of control of athletes’ psychological problems had increased by 13%, the psychological anxiety of students had also been alleviated and improved, and the overall score had increased by 12.5%. A more systematic mental training program for athletes was introduced in order to provide a basis for improving the effectiveness of mental training for athletes.