Hanbyeol Lee
Yonsei University, Seoul, Korea, Republic of
To achieve high performance in esports, players must be able to effectively and efficiently control input devices such as a computer mouse and keyboard (i.e., input skills). Characterizing and quantifying a player’s input skills can provide useful insights, but collecting and analyzing sufficient amounts of data in ecologically valid settings remains a challenge. Targeting the popular esports game, League of Legends, we go beyond the limitations of previous studies and demonstrate a holistic pipeline of input behavior analysis: from quantifying the quality of players’ input behavior (i.e., input skill) to training players based on the analysis. Based on interviews with five top-tier professionals and analysis of input behavior logs from 4,835 matches played freely at home collected from 193 players (including 18 professionals), we confirmed that players with higher ranks in the game implement eight different input skills with higher quality. In a three-week follow-up study using a training aid that visualizes a player’s input skill levels, we found that the analysis provided players with actionable lessons, potentially leading to meaningful changes in their input behavior.
doi.org/10.1145/3613904.3642588
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)