The US Open, one of the four Grand Slam tennis tournaments, is played on hard courts alongside the Australian Open, while the US Open typically takes place in August or September during the summer in New York. This study employs literature review and statistical methods such as SPSS to analyze 10 data points from 125 men's singles matches announced on the official website of the 2024 US Open. First, each indicator is coded for preprocessing. Then, KMO test and Bartlett's test for sphericity are used, along with total variance, rotated component matrix, and coefficient matrix, to derive the predictive model. The run test is conducted to check if the data meets randomness, and the selected data undergoes Shapiro-Wilk and Spearman correlation tests. The data are then analyzed in conjunction with the previously obtained model, and finally, the prediction results are tested. This study clarifies that winning break points and the probability of winning the second service point significantly impact actual match scenarios, emphasizing the importance of stability throughout a game.

Fuqian Wang, Zhuojian Li. Construction of prediction results for men's singles tennis at the US Open. Frontiers in Sport Research (2025), Vol. 7, Issue 2: 33-39. https://doi.org/10.25236/FSR.2025.070206.

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