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Title

Psychological predictors of long-term esports success: A Registered Reportuse asterix (*) to get italics

Authors

Marcel Martončik, Veli-Matti Karhulahti, Yaewon Jin, Matúš AdamkovičPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"

Year

2023

Picture

Abstract

The competitive play of digital games, esports, has attracted worldwide attention of hundreds of millions of young people. Although esports players are known to practice in similar ways to other athletes, it remains largely unknown what factors contribute to high performance and to what degree. In the present confirmatory study, our goal was to test whether deliberate practice theory, which has successfully been applied to other sports earlier, can predict high esports performance with other psychologically relevant variables. The study was carried out with participants from Counter-Strike: Global Offensive (CSGO, N = 186) and League of Legends (LoL, N = 411). In both esports, we found evidence for deliberate practice not having a meaningful effect on performance (null: r > .3 in CSGO and r > .2 in LoL, observed: .02 in CSGO and -.01 in LoL). On the other hand, the results confirmed younger age predicting better performance (-.33 and -.22, respectively). Additionally, we were able to confirm two game-specific findings: attention (-.30, CSGO) and non-deliberate practice hours (.26, LoL) meaningfully predicted performance in one but not both esports. The effects of all other variables—including intelligence, reaction time, and persistence—were confirmed to be null or inconclusive in both esports. We discuss the results against game design and hypothesize esports-specific information density as a potential explanation to differences in performance prediction. The findings can be useful for esports teams, coaches, and all individuals pursuing success in esports.

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Keywords

esports; gaming; performance; expertise; competitive

Methods that require specific expertise (optional)

NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).

Thematic fields

Social sciences

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Submission date

2023-09-26 07:15:41

Recommender

Zhang Chen

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