Abstract
This study aims to quantify momentum changes in tennis matches by building a machine learning model and investigate their impact on match outcomes. Firstly, a momentum model is established to quantify the momentum value of players by defining basic points, break points, guaranteed points and continuous points. Then, the momentum curve of players is calculated using real match data, and its high match with the match trend is verified. Then, the correlation between momentum value and match result is tested by statistical test method. The results show that there is a significant correlation between momentum value and match victory. Further, the displacement test verifies that the change of momentum value is not random, but reflects the actual trend of the game. This study proves that momentum plays an important role in tennis matches, and its change has a significant impact on match results, which provides an important reference for further research and application of momentum.
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