Wang Jingya, Guo Sihang, Zhou Yuanyun
School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, Shenzhen, Guangdong, China.
School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Shenzhen, Guangdong, China.
PLoS One. 2024 Dec 31;19(12):e0316542. doi: 10.1371/journal.pone.0316542. eCollection 2024.
In the process of pushing the limits of human performance, competitive sports are dedicated to the pursuit of excellence. In this context, the concept of "momentum" has gained significant attention, as it is widely acknowledged to influence the outcomes of competitions. The question of whether momentum affects sports psychology and the mechanisms underlying its generation and influence merits thorough investigation. In this paper, taking the 7,284 scoring points in the men's singles tennis match at Wimbledon 2023 as an example, we expand upon traditional momentum research by integrating diverse algorithms, including statistical analysis and linear weighting, to construct a multidimensional momentum chain model predicated on difference equations, which aims to quantify the momentum dynamics for athletes in a match. To enhance the authenticity of our model, we incorporate a forgetting curve to modulate the momentum fluctuations. The results show that dominant players have significantly shorter running distances and higher success rates in net strokes than disadvantaged players, indicating that positive events markedly enhance players' psychological and behavioral performance. Furthermore, the likelihood of scoring is substantially greater for players possessing higher momentum, with data suggesting that the serving side has an 84% chance of securing a match victory. When applied to 6,870 tennis matches, our model achieves a prediction accuracy exceeding 80%. Accordingly, we have proposed tennis training suggestions based on the mechanisms of momentum and developed strategies to effectively harness the "hot hand" phenomenon in matches.
在挑战人类表现极限的过程中，竞技体育致力于追求卓越。在此背景下，“动量”概念备受关注，因为人们普遍认为它会影响比赛结果。动量是否影响运动心理学以及其产生和影响的潜在机制值得深入研究。本文以2023年温布尔登网球锦标赛男子单打比赛中的7284个得分点为例，通过整合包括统计分析和线性加权在内的多种算法，扩展了传统的动量研究，构建了一个基于差分方程的多维动量链模型，旨在量化运动员在比赛中的动量动态变化。为提高模型的真实性，我们引入遗忘曲线来调节动量波动。结果表明，优势球员在网前击球时的跑动距离明显短于劣势球员，成功率更高，这表明积极事件显著提升了球员的心理和行为表现。此外，动量较高的球员得分的可能性显著更大，数据显示发球方赢得比赛的概率为84%。当将我们的模型应用于6870场网球比赛时，预测准确率超过80%。因此，我们基于动量机制提出了网球训练建议，并制定了有效利用比赛中“热手”现象的策略。
