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Academic Journal of Mathematical Sciences, 2024, 5(2); doi: 10.25236/AJMS.2024.050211.

A Study on the Influence Factors of Momentum Based on Random Forest and XGBoost Algorithm

Author(s)

Ruiting Zhao1, Rui Li2, Jingrui Cai2

Corresponding Author:
Ruiting Zhao
Affiliation(s)

1School of Mathematics Statistics and Mechanics, Beijing University of Technology, Beijing, China

2School of Economics and Management, Beijing University of Technology, Beijing, China

Abstract

This study examines the effect of momentum on the outcome of tennis matches by analyzing data from the 2023 Wimbledon men's singles final. A momentum computational model was established and run test, random forest and XGBoost machine learning methods were applied, and the results showed that momentum has a non-random effect on the match results. It was found that the speed of serve was the most important factor affecting the outcome of the final match. In this match, veteran Novak Djokovic lost to rising star Carlos Alcaraz, demonstrating the latter's potential as the first men's Grand Slam singles champion born in the 2000s. This study fills a gap in research on the factors influencing momentum and provides a new perspective on understanding the mechanisms behind tennis match outcomes.

Keywords

Random Forest, XGBoost, CUMSUM Algorithm

Cite This Paper

Ruiting Zhao, Rui Li, Jingrui Cai. A Study on the Influence Factors of Momentum Based on Random Forest and XGBoost Algorithm. Academic Journal of Mathematical Sciences (2024) Vol. 5, Issue 2: 76-83. https://doi.org/10.25236/AJMS.2024.050211.

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