Tennis Data

Forecasting professional tennis players winning matches has a wide range of practical applications. We introduced a new approach to measure and combine strategic and psychological momentum using the entropy weight method and the analytic hierarchy process, and test its effectiveness. Using data from Wimbledon Championship 2023, we then constructed a support vector machine (SVM) model to predict the turning point and winner of each point, and we optimized it using particle swarm optimization (PSO). Our model achieved a significant level of accuracy (96.09\% turning point and 83.52\% predicting winner) and performs well in different courts and players. Furthermore, we compare its performance with commonly utilized predictive models, including ARIMA, LSTM and BP network, and find that our model exhibits higher accuracy than other existing models on predicting the point winner. Our research can be used to calculate odds in tennis matches and provide advice to coaches.