In this paper, we aimed to test whether we could predict sport type (badminton or running) and marathon proficiency from the valence, form, and content of the athletes’ self-reported inner speech. Additionally, we wanted to assess the difference between self-talk during high intensity and low intensity exercise. The present study corroborated existing research – we were able to predict both sport type in Study 1 and intensity level as well as marathon proficiency in Study 2 from questionnaire data using machine learning models. In Study 1, we found that badminton players engage more in worry and anxiety-control while runners are more prone to task disengagement. Interestingly, it seemed in Study 2 that the more participants engaged in condensed, positive, and repetitive self-talk when not pushing themselves, the slower their fastest marathons and half marathons were. We discuss potential explanations for these findings and make suggestions for future research.

在本文中，我们旨在测试我们是否可以从运动员自我报告的内心语言的效价、形式和内容来预测运动类型（羽毛球或跑步）和马拉松熟练程度。此外，我们想评估高强度和低强度运动期间自言自语之间的差异。本研究证实了现有研究——我们能够使用机器学习模型从问卷数据中预测研究 1 中的运动类型和强度水平以及研究 2 中的马拉松熟练程度。在研究 1 中，我们发现羽毛球运动员更多地参与焦虑和焦虑控制，而跑步者更容易脱离任务。有趣的是，在研究 2 中，似乎越多的参与者在不强迫自己的情况下，越多地进行凝练、积极和重复的自我对话，他们最快的马拉松和半程马拉松跑得越慢。我们讨论对这些发现的潜在解释，并为未来的研究提出建议。