Analyzing the Impact of Momentum on Tennis Matches Using Decision Tree Classification: A Case Study of Wimbledon

Abstract

In this paper, a Momentum Scoring Model is developed to quantify the abstract concept of Momentum through a set of important factors such as the base point, the hold point, and the break point. The model has the flexibility to capture player's in-game scoring changes with high accuracy and has a visualization process that is easy for tennis coaches and tennis players to understand. In order to statistically test whether momentum score changes are beyond random fluctuations, this paper validates the data by using the permutation test and shows that momentum plays a role in tennis matches. The paper also extracted several key metrics affecting momentum shifts, such as server, p2_score, etc., through an inductive learning algorithm like decision tree. Based on the above model, this article provides some preparation methods for tennis players. Such as analyzing the opponent's playing patterns, enhancing individual psychological preparation, optimizing serving and receiving strategies, etc.