Research on Tennis Score Based on Momentum Quantization Model

The paper goal is to investigate the significance, logic, and effects of momentum in tennis matches in order to offer logical advice to athletes and tennis coaches. the paper created a quantitative momentum model and mostly finished three tasks based on the research objectives. Firstly, the paper develop a momentum quantification model and set four essential indicators to quantify the momentum. By adding together these indicators, the paper may determine a player's momentum score at a given scoring point. And a shift curve of momentum scores is shown using the momentum scores acquired at each scoring point, providing the groundwork for determining the competition's turning point in the future. Secondly, the randomness of momentum is assessed by us. To evaluate coaches' skepticism about the impact of momentum, the paper conducted two randomized experiments to investigate this issue. The first test is a randomness test based on outcome correlation. The paper calculate the correlation between the winner and the player with the highest score on the final score. The second test is the permutation test, which involves generating a large number of random permutations by redistributing the labels of the data points. It then calculates the consistent distribution between the highest momentum scorer and the competition winner under these random permutations. The test results all indicate that the player with the highest momentum score is the winner of the game. The paper proves that momentum plays a crucial role in the matches, and predicting momentum can be utilized to anticipate pivotal moments in the game.

Authors

Publication Details

Journal
Highlights in Science Engineering and Technology
Published
2024-10-28
DOI
https://doi.org/10.54097/q1w0d773
Primary Topic
Sports Analytics and Performance
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on Tennis Score Based on Momentum Quantization Model

Y. Yi, Haitang Yang, K. Zheng
Highlights in Science Engineering and Technology
Sports Analytics and Performance
article

Research on Tennis Score Based on Momentum Quantization Model

Y. Yi, Haitang Yang, K. Zheng
article en

Abstract

The paper goal is to investigate the significance, logic, and effects of momentum in tennis matches in order to offer logical advice to athletes and tennis coaches. the paper created a quantitative momentum model and mostly finished three tasks based on the research objectives. Firstly, the paper develop a momentum quantification model and set four essential indicators to quantify the momentum. By adding together these indicators, the paper may determine a player's momentum score at a given scoring point. And a shift curve of momentum scores is shown using the momentum scores acquired at each scoring point, providing the groundwork for determining the competition's turning point in the future. Secondly, the randomness of momentum is assessed by us. To evaluate coaches' skepticism about the impact of momentum, the paper conducted two randomized experiments to investigate this issue. The first test is a randomness test based on outcome correlation. The paper calculate the correlation between the winner and the player with the highest score on the final score. The second test is the permutation test, which involves generating a large number of random permutations by redistributing the labels of the data points. It then calculates the consistent distribution between the highest momentum scorer and the competition winner under these random permutations. The test results all indicate that the player with the highest momentum score is the winner of the game. The paper proves that momentum plays a crucial role in the matches, and predicting momentum can be utilized to anticipate pivotal moments in the game.

Highlights in Science Engineering and TechnologyVol. 115
Openalex Percentile: Top 76%
Sports Analytics and Performance
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Research on Tennis Score Based on Momentum Quantization Model — Y. Yi, Haitang Yang, et al. · Highlights in Science Engineering and Technology (2024) | TGRS Research Map | TGRS