Breaking down success Game-related statistical analysis in tennis grand slams
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The data-driven insights and examination of key performance indicators (KPI) in professional tennis is becoming increasingly popular and are now deemed important for player development and coaching strategies. The aim of the study was to analyse game-related KPIs differentiating winners from losers in the 2023 US Open and French Open tournaments. A total of 253 matches (127 men’s singles matches from US Open and 126 men’s singles matches from Roland Garros tournament) were included in the study. An independent t-test was employed to compare the differences between winners and losers for all indicators in 2023 French Open and US Open Grand Slams. For the variables that did not follow a normal distribution, the Mann–Whitney U test was used. Variables that showed significant differences between two groups were selected for discriminant analysis. It was found that winners outperformed losers in several key indicators, including Aces, Break Points Won %, First Serve % In, Net Points Won %, Receiving Points Won %, Second Serves In, Win % First Serve, and Win % Second Serve (p < .01, Cohen’s d: 0.06-0.1, r: 0.02–0.85). In the context of the French Open, winners demonstrated a significantly higher percentage of win on First Serve (mean- 73.02, p < .01, Cohen’s d:1.272), as compared to their counterparts who did not succeed and recorded a lesser percentage of win on First Serve (mean- 63.25, p < .01, Cohen’s d:1.272). In conclusion, Serve quality, return performance, and error minimization are critical KPIs for success in Grand Slams. Surface dynamics play a significant role in shaping match strategies.
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