Open Access
Journal Article
Analysis of Tennis Competition Situation Based on Adboost-BP Neural Network
by
Yida Ding
, Heyuan Zhang
, Mengyuan An
, Jinxiao Chu
, Zihao Zhang
and
Chenglu Miao
Abstract
In this study, we analyzed tennis match data to answer various questions related to tennis. Firstly, we constructed a model to capture the process of the game and evaluate the performance of players. By preprocessing and analyzing the data, including eliminating outliers, filling in missing values, and standardizing the data, we obtained prepared analytical data. Subsequently,
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style="text-align: justify;">style="font-size: 14pt;">style="font-family: 'Times New Roman', serif;">In this study, we analyzed tennis match data to answer various questions related to tennis. Firstly, we constructed a model to capture the process of the game and evaluate the performance of players. By preprocessing and analyzing the data, including eliminating outliers, filling in missing values, and standardizing the data, we obtained prepared analytical data. Subsequently, using principal component analysis, three representative principal components were identified. In addition, by using the entropy weight method, we calculated the weights, enabling us to derive a momentum formula for visualizing the temporal changes during the competition process. Secondly, we explored whether there is a correlation between match results and momentum. By using the momentum model we established, we used Pearson correlation analysis to calculate the correlation coefficient, thereby determining the relationship between momentum and game results.