Psychophysiological factors determining the success of elite Greco-Roman wrestlers using artificial intelligence methods

Authors

DOI:

https://doi.org/10.47197/retos.v83.119484

Keywords:

Elite athletes, Greco-Roman wrestling, psychophysiological indicators, multivariate analysis, artificial intelligence

Abstract

Introduction: The application of artificial intelligence methods to the analysis of psychophysiological indicators enables the identification of the most informative markers and the construction of profiles of preparedness in elite athletes within the framework of sports monitoring.

Objective: To identify the psychophysiological determinants that characterize the preparedness profile of elite Greco-Roman wrestlers using multivariate analysis methods and artificial intelligence tools.

Methodology: The study involved 44 Greco-Roman wrestlers: youth elite wrestlers (n = 21) and elite wrestlers (n = 23). A set of psychophysiological tests was used for the measurements. An algorithm for investigating psychophysiological indicators using artificial intelligence tools was applied, which included the stages of data collection, statistical processing of the results in the RStudio environment, and interpretation of the findings using the large language model GPT-5.2 (OpenAI).

Results: Psychophysiological determinants characterizing the wrestlers’ preparedness profile were identified. No statistically significant differences were found between the Youth U-17 and Seniors groups across 10 key indicators. Latent components of wrestlers’ psychophysiological functions and integral indices (LPI) were determined, making it possible to construct individual athlete profiles and to monitor psychophysiological functions during the training process. The application of artificial intelligence methods to the analysis of psychophysiological indicators enables the identification of the most informative markers and the construction of generalized profiles of preparedness in qualified combat sports athletes within the framework of sports monitoring.

Conclusions: The added value of a hybrid approach was confirmed, in which AI enhances the analytical process without compromising its scientific reproducibility.

Author Biographies

  • Georgiy Korobeynikov, National University of Ukraine on Physical Education and Sport

    Professor of the Department of Combat Sports and Power Sports, National University of Ukraine on Physical Education and Sport, Kyiv, Ukraine;

    Professor of the Department of Theory and Methodology of Physical Education and Sport, Uzbek University of Physical Education and Sport, Cherchik, Uzbekistan

  • Vyacheslav Romanenko, Kharkiv State Academy of Physical Culture

    Associate Professor, Kharkiv State Academy of Physical Culture, Rharkiv, Ukraine

  • Yrui Tropin, Kharkiv State Academy of Physical Culture

    Head of Department of Combat Sport, Kharkiv State Academy of Physical Culture, Kharkiv, Ukraine

  • Leonid Podrigalo, Kharkiv State Academy of Physical Culture

    Professor, Department of Sport Medicine, Kharkiv State Academy of Physical Culture, Kharkiv, Ukraine

  • Volodymyr Shatskykh, Pridniprovsk State Academy of Physical Culture and Sports

    Associate Professor, Educational and Scientific Institute, Pridniprovsk State Academy of Physical Culture and Sports, Dnipro, Ukraine

  • Markus Raab, German Sport University Cologne

    Professor of Psychology. Lead a department of performance psychology at the German Sport University. Main research interests are within sport, exercise, performance, and decision-making.

  • Oleksandr Pryimakov, University of Szczecin

    Professor, Faculty of Physical Culture and Health Promotion, University of Szczecin, Szczecin, Poland

  • Lesia Korobeinikova, National University of Ukraine on Physical Education and Sport

     Professor, National  University of Ukraine on Physical Education and Sport, Kyiv, Ukraine;

    Professor, Uzbek  State University of Physical Education and Sport, Chirchik, Uzbekistan

  • Denis Volsky, National University of Ukraine on Physical Education and Sport

    As. Professor, National University of Ukraine on Physical Education and Sport, Kyiv, Ukraine

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30-05-2026

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Vol. 83 (2026)

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Copyright (c) 2026 Georgiy Korobeynikov, Vyacheslav Romanenko, Yrui Tropin, Leonid Podrigalo, Volodymyr Shatskykh, Markus Raab, Oleksandr Pryimakov, Lesia Korobeinikova, Denis Volsky

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Korobeynikov, G., Romanenko, V., Tropin, Y., Podrigalo, L., Shatskykh, V., Raab, M., Pryimakov, O., Korobeinikova, L., & Volsky, D. (2026). Psychophysiological factors determining the success of elite Greco-Roman wrestlers using artificial intelligence methods. Retos, 83, 352-370. https://doi.org/10.47197/retos.v83.119484