A Prediction Model for Tennis Match Fluctuations Based on the BP Neural Network

Tennis is a global sport, with Wimbledon being one of the most historic and prestigious international tennis opens. The concept of "momentum" in tennis matches, defined as "strength or force gained by motion or by a series of events," plays a critical role in influencing the course of a match. This paper selects specific indicators combined with the scoring situations in matches for correlation analysis using Kendall's tau-b method. Reasonable indicators are chosen for classification through a backpropagation neural network to predict the match process and analyze fluctuations in the match flow, which are then visualized. The analysis identifies various turning points within the match proceedings. This model is a good way to analyze and predict fluctuations in tennis matches.This research is anticipated to contribute to the prediction of scores in sports events.