Sports Athletes’ Performance Prediction Model Based on Machine Learning Algorithm

Abstract

In order to accurately predict the athletes’ performance, combined with the specific changes of athletes’ performance, a performance prediction model based on machine learning algorithm is proposed. The current research status of sports athletes’ performance modeling and prediction is analyzed, and the current athletes’ performance prediction model is found. The shortcomings of the model are analyzed. The reason for the low prediction accuracy of the model is analyzed. Then the chaotic theory is used to process the historical data of the athletes, and the hidden rules are found. Finally, using the machine-learning algorithm supporting vector machine to design athlete performance prediction-model is adopted, and the particle swarm is adopted. The algorithm accelerates and optimizes the training of the model. The results on the test set show that compared with the current athlete performance prediction-model, the athletes’ performance prediction results of the designed model are more reliable, and the athletes’ prediction accuracy is higher, which can be applied to the development of sports science training plan.