The paper presents a comprehensive overview of the current state of research in the field of performance and training in esports. The authors aim to address the gap in scientific research in the area of skill and performance improvement in esports by conducting an empirical study. The theory of performance structure in esports combines insights from both game and sport science to propose a unified framework for esports. This framework highlights the importance of tactical-cognitive abilities, coordination and skill, and the role of different sensory systems in contributing to performance in esports. The authors conducted a systematic literature search and analyzed 46 articles, which showed that the players’ mean engagement in training was 14 hours per week, with some elite players training up to 37 hours a week. The main contents of training were game-mechanics, tactics, communication, and movement precision. The study selected 5 esports games for analysis: Starcraft II, League of Legends, Rocket League, FIFA, and Counter Strike, to determine the importance of specific competencies, training areas, and training engagement in various esports games.

The integrative model of esports performance combines elements from the competence model of games and the performance model of sports to create a model specifically for esports. According to this model, tactical-cognitive abilities are essential components of esports performance. These abilities include things like strategic thinking, decision making, and memory and concentration. The ability to process information, analyze situations, and plan actions is also important. The model also highlights the role of coordination and skill in esports. The specific physical interaction with input devices, such as mouse and keyboard, is a crucial aspect of performance in esports. Spatial abilities, such as perception of position and anticipation, are also important components. In addition, the visual, acoustic, and haptic systems play an important role in contributing to performance in esports. These systems help the player to perceive information about other players, avatars, and game conditions. Finally, the model also takes into consideration pressure conditions such as time pressure, precision pressure, situational pressure, complexity pressure, and stress-strain pressure which are important demands in esports.

The study aimed to investigate the relationship between skill level, playing time, motivation, and training engagement in esports. The results showed that the importance of competencies varies between different esports and that different esports have different levels of importance for specific training areas. For example, accuracy was found to be more important in Rocket League (RL) and Counter-Strike (CS) compared to other esports, while spatial orientation was found to be of great importance in RL. The results confirmed that the technique, movement accuracy, and strategy were the most important training areas across all esports, while physical training was considered the least important. The study also found that a positive correlation between motivation and training effort exists and a positive correlation between skill level and training engagement exists. The results showed that different levels of players (beginners, advanced, and professional) have different levels of training effort, motivation, and skill level.

1. Esports training is different from traditional sports and requires a unique approach to performance optimization.
2. The importance and type of competencies and training areas vary among different esports.
3. Time management and break behaviour are important factors in the training and performance of esports players.
4. Performance factors from sports can also be significant in esports.
5. Training for esports should be grounded in a thorough understanding of the specific structure of the game.
6. The study can serve as a foundation for future research in the field of esports training.
7. As a coach or performance professional, it’s important to consider the findings of this study and tailor your training approach to the specific needs of the esports player you are working with.

Source:

Nagorsky E, Wiemeyer J. The structure of performance and training in esports. PLoS One. 2020 Aug 25;15(8):e0237584. doi: 10.1371/journal.pone.0237584. Erratum in: PLoS One. 2021 Apr 13;16(4):e0250316. PMID: 32841263; PMCID: PMC7447068.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7447068/

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