Prediction of Tennis Match Momentum Based on PCA and LGBM Models
Year: 2024
Type: article
Abstract: This study investigated the impact of momentum on the situation in sports based on data from the 2023 Wimbledon final. Using a BP neural network to interpolate missing values and screening the data by Principal Component Analysis (PCA), the best performing LGBM model was selected to achieve accurate quantification and real-time visualization of momentum using the classic match between Carlos Alcaraz and Novak Djokovic as an example. It is found that our model is highly accurate and performs well. In addition, we summarize the role of momentum in matches and provide professional strategy suggestions, which will provide valuable information for coaches and players, and we hope that this study will provide useful references for the development of sports.
DOI: 10.54097/zz435k83
Authors: Xiyihan Cao, Yuchen Li, Yongxu Liu
Institution: Jilin University
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4401667067