Tennis Momentum: An Analytical Study of Tennis Performance Based on the CNN-LSTM-RF Model

In this study, we introduce an innovative CNN-LSTM-RF model to analyze and predict momentum shifts in tennis, using the 2023 Wimbledon Men's Singles Final as a case study. Our approach processes match data to identify key factors affecting momentum, such as serve effectiveness, player psychology, and match dynamics, employing factor analysis and the AHP-TOPSIS method for a comprehensive performance evaluation. Findings indicate a significant correlation between momentum and winning streaks, highlighting momentum's importance in influencing match outcomes. Despite its predictive success, we recognize the model's limitations and the complexity of accurately forecasting momentum shifts. This concise analysis not only demonstrates the model's utility in tennis strategy but also suggests areas for future research and model enhancement.