A Study of Momentum Change in Sports Competitions Based on Evaluation and Correlation Analysis

In sports competitions, momentum has an important impact on the outcome of the game, and how to accurately capture and analyze momentum changes has become a key issue in research. But traditional methods often lack comprehensiveness and objectivity, so a new assessment model is needed to better understand and predict momentum changes. In this paper, an assessment model of momentum change is proposed, aiming to establish a comprehensive and objective momentum assessment model through data transformation, correlation analysis and weight calculation. The assessment model of momentum change is based on the data transformation technique, which converts score data into game data and generates 17 indicators to reflect various factors in the game. Meanwhile, using Spearman correlation coefficient and the Criteria Importance Through Intercriteria Correlation (CRITIC) algorithm, the weights of these indicators were assigned and correlation analysis was carried out to establish the Momentum Assessment Model (MAM). This paper takes the 2023 Wimbledon Men's Singles Final as an example to demonstrate the effectiveness of MAM in analyzing momentum changes in the match flow. The results show that the model can help to understand and predict the relationship between player performance and match results during a match, providing an important research tool for the field of sports and athletics.