Loss aversion under pressure Analyzing decision-making in high-stakes tennis through Grand Slam big data

Abstract

This study examines loss aversion behaviour in professional tennis, with a focus on players’ responses to high-stakes situations such as game points and break points. While prior research has provided valuable insights, it has predominantly relied on limited match samples, often confined to select tournaments or individual players. To address this limitation and enhance the generalizability of findings, the present study employs a comprehensive dataset comprising ten years (2010–2020) of five-set matches from all four Grand Slam tournaments. Anchored in Prospect Theory—which suggests that individuals are more motivated to avoid losses than to acquire equivalent gains—the analysis investigates key performance indicators including scoring success rate, serve ace rate, and double fault frequency. The results indicate that players exhibit loss-averse behaviour in specific contexts, notably by reducing double faults during break points. However, other performance metrics, such as ace rates and serve accuracy, do not consistently reflect loss-averse tendencies. A post-hoc analysis based on point differentials further elucidates the nuanced manifestations of loss aversion across varying match contexts. These findings contribute to a more robust understanding of risk-related decision-making in elite sports and offer implications for performance optimization and athlete management.