Journal article
Examining the game-specific practice behaviors of professional and semi-professional esports players: A 52-week longitudinal study
Computers in Human Behavior, Vol.137, pp.1-6
12/2022
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Source: InCites
Abstract
This study followed a longitudinal design to objectively monitor practice behaviors of professional and semi-professional esports players over a year. Publicly available data were collected from 30 male Counter-Strike: Global Offensive players (age: 23.76 ± 2.88y). Players were classified into two groups: professional (n = 18) or semi-professional (n = 12). The total hours of practice (all game-specific practice) and the competitive hours of practice (time spent in competitive modes only) were collected weekly. Generalised Estimating Equations were used to compare the practice behaviors of the two groups. Professional and semi-professional esports players completed an average of 30.9 ± 8.2 h and 24.7 ± 3.6 h per week of total game-specific practice, respectively, and 19.6 ± 6.9 and 15.0 ± 2.7 h of competitive practice, respectively. A significant week∗group interaction was observed for total practice time (Wald χ2 = 9.48, p = 0.002) and total competition practice time (Wald χ2 = 7.54, p = 0.006). Specifically, professional esports players completed 6.6 (SE = 2.2) hr per week more of total practice hours than semi-professional players, of which 4.8 (SE = 1.8) hr were competitive practice. This sample of expert esports performers complete high volumes of practice which can be monitored via publicly accessible repositories.
Details
- Title
- Examining the game-specific practice behaviors of professional and semi-professional esports players: A 52-week longitudinal study
- Creators
- Matthew A. Pluss - University of Technology SydneyAndrew R. Novak - University of Technology SydneyKyle J.M. Bennett - Southern Cross UniversityIgnatius McBride - University of Technology SydneyDerek Panchuk - Victoria UniversityAaron J. Coutts - University of Technology SydneyJob Fransen - University of Technology Sydney
- Publication Details
- Computers in Human Behavior, Vol.137, pp.1-6
- Publisher
- Elsevier Ltd
- Identifiers
- 991013044512502368
- Copyright
- © 2022 Elsevier Ltd. All rights reserved.
- Academic Unit
- Human Sciences; Faculty of Health
- Language
- English
- Resource Type
- Journal article