Abstract
Scientific sports training plans are only possible if you can accurately predict a player's performance. Accurate prediction of sporting performance not only is useful for athletes, but also helps to guide the development of sports. Research methods used in traditional forecasting include the time series method, analogy method, regression analysis, and other methods of analysis. Most of the data used to make these projections are derived from a relatively small set of static problems. A sports performance prediction model based on deep learning is proposed to address the current model's low prediction accuracy. Deep learning models are more accurate at predicting sports performance than traditional methods, and the difference between the two is greater in this study. Also, it performs well when it comes to both convergence and robustness.
Highlights
Sports performance prediction can help schools, sports teams, and sports training institutions develop scientific training methods that reflect the changing trends in sports performance [1]. us, athletes and coaches will be able to use these opinions as a basis for reforming physical education and training. e level of sports training is reflected in a person’s ability to perform well in sports
This paper puts forward a sports achievement prediction model based on deep learning. e quantitative evaluation system of special movement techniques has been established. is system can scientifically monitor and evaluate the development level of each athlete’s athletic ability so that athletes can get scientific training. e performance test of the model proposed in this paper shows that the model improves the accuracy of sports performance prediction, and the prediction error can meet the requirements of practical application
Sports performance and related factors must be studied quantitatively, using interdisciplinary approaches, as soon as possible. e multivariate and multiparameter statistical analysis is used to build a model for sports achievement prediction
Summary
Sports performance prediction can help schools, sports teams, and sports training institutions develop scientific training methods that reflect the changing trends in sports performance [1]. us, athletes and coaches will be able to use these opinions as a basis for reforming physical education and training. e level of sports training is reflected in a person’s ability to perform well in sports. It is of great significance to study the prediction model of sports performance in promoting scientific training and improving sports performance [4]. In light of the growing interest in sports development, this paper proposes a method for accurately predicting sports performance based on deep neural networks (DNN) [6,7,8]. A sports performance prediction model based on DNN is proposed in order to improve the Scientific Programming scientific guidance of sports training and predict sports performance. Neural network (NN) is generally used in uncertain input-output function mapping, which can determine the linear correspondence It has stable effectiveness and adaptability, forward propagation signal, and backward propagation error, and is often used in various fields [9]. This paper puts forward a sports achievement prediction model based on deep learning. e quantitative evaluation system of special movement techniques has been established. is system can scientifically monitor and evaluate the development level of each athlete’s athletic ability so that athletes can get scientific training. e performance test of the model proposed in this paper shows that the model improves the accuracy of sports performance prediction, and the prediction error can meet the requirements of practical application
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