Research on state volatility of tennis players based on sliding window technique

This paper aims to study the state volatility of players in tennis matches and proposes a conceptual model of "momentum" based on sliding window technology. Firstly, Pearson correlation analysis is used to screen out the indicators that are highly relevant to the victory of the match, and the index system including point advantage, service advantage, break point, unforced error, ace, game won and distance run is constructed. Then, a formula for calculating "momentum" is proposed, and the sliding window algorithm is used to calculate the "momentum" value of each athlete. Finally, the change of "momentum" during the game is demonstrated visually, and the correlation between "momentum" and the outcome of the game is verified. In addition, the "momentum" transition point is defined, the "momentum" difference series is calculated by moving average method, and the randomness of the "momentum" transition point is analyzed by Run test. The results show that the change of "momentum" has a significant impact on the outcome of the match, and the change of "momentum" is not random.