Research On Tennis Match Results Prediction Model Based On BP Neural Networ

Performance prediction is of great value and significance to professional sports,such as event broadcasting,sports guessing,news reporting and so on.In today’s sports environment,prediction has a significant effect on athletes to achieve good results and improve training efficiency.In the context of big data,all sports indicators have been decomposed and refined.After the sports event,there will be the results of technical data statistics.With the development of tennis and its increasing popularity all over the world,the decomposition and statistics of its technical indicators have been relatively mature.According to the characteristics of tennis,this paper introduces BP neural network method and applies it to the performance prediction of tennis events.Taking the four Grand Slam competitions from 2019 to 2021 as a typical example,the performance prediction model of tennis project is established.The whole process of index system establishment,BP network prediction model construction,sample database establishment,network training evaluation and prediction is studied in detail in Matlab.The main research contents include:1.This paper introduces the characteristics and calculation method of BP neural network algorithm,and analyzes the feasibility of its application in tennis performance prediction based on the characteristics of tennis technical indexes.2.During the establishment of tennis match performance prediction model based on BP network,the collection and processing of match data,the decomposition of index system,quantitative methods and the establishment of sample set.Using the processed data,the prediction models are built and trained under different eigenvalues and training sample sets.3.The prediction accuracy of BP neural network prediction model under different eigenvalue clusters,input sample size and site type is analyzed and discussed.While verifying the effectiveness of network prediction,the key parameters affecting the accuracy of network prediction are deeply analyzed,and the value of technical parameters is optimized.The research shows that the prediction model of tennis four Grand Slams based on BP neural network principle and Matlab software is feasible.The calculation results also show that the number of effective training data samples collected needs to reach a certain degree to ensure the prediction accuracy of the model..Under the condition of comparing the characteristic value of 10 and the training sample size of 7 Grand Slam events,the overall prediction accuracy of the BP neural network prediction model can reach78.125%.Combined with the prediction results,it is found that the key parameters of ACE ball,double error,active score and unforced error are more sensitive to the changes of network prediction results in Grand Slam events..The results of this paper and the prediction method established will provide a new direction for the prediction and data analysis of tennis events.