Signs of adaptability of cybersportsmen to the virtual environment

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PhD, Associate Professor E.A. Kosmina1
Dr. Hab., Professor Yu.M. Makarov1
PhD, Associate Professor A.I. Chernaya1
O.N. Gural2
1Lesgaft National State University of Physical Education, Sports and Health, St. Petersburg
2Russian Esports Federation, Moscow]

Objective of the study was to determine the dominant features that affect the adaptability of cybersportsmen aged 18-25 to the virtual environment.
Methods and structure of the study. As a result of the theoretical analysis, 125 features (characteristics) of e-sportsmen have been identified that affect the adaptability to the virtual environment. An online survey of 55 experts in the field of computer sports was conducted on the basis of the Yandex Forms service, where respondents evaluated each of the 125 features. To reduce the number of variables and determine the structure of relationships between variables, the data obtained were subjected to factor analysis, which made it possible to identify seven factors, including from three to 14 features.
Results and conclusions. The dominant features that affect the adaptability of a cybersportsman in the digital environment are determined: the ability to synthesize, concentration of attention, switching of attention, quickness of thinking, competition, strength of the nervous system, working capacity, emotional biorhythms, lack of need for acquiring knowledge. The results of the study can be used in the development of training programs for those involved in various disciplines of computer sports.

Keywords: computer sports, e-sportsmen, signs of adaptability, virtual environment, meta.

References

  1. Kosmina E.A., Makarov Yu.M. Soderzhaniye razlichnykh vidov sportivnoy podgotovki v kompyuternom sporte [The content of various types of sports training in computer sports]. Lesgaft National State University of Physical Education, Sports and Health, St. Petersburg. St. Petersburg: LEMA publ., 2022. 185 p.
  2. Aung M. et al. Predicting skill learning in a large, longitudinal moba dataset. 2018 IEEE conference on computational intelligence and games (CIG). IEEE, 2018. pp. 1-7.