Visual Fixations Duration as an Indicator of Skill Level in eSports
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Abstract (arXiv)
Using highly interactive systems like computer games requires a lot of visual activity and eye movements. Eye movements are best characterized by visual fixation - periods of time when the eyes stay relatively still over an object. We analyzed the distributions of fixation duration of professional athletes, amateur and newbie players. We show that the analysis of fixation durations can be used to deduce the skill level in computer game players. Highly skilled gaming performance is characterized by more variability in fixation durations and by bimodal fixation duration distributions suggesting the presence of two fixation types in high skill gamers. These fixation types were identified as ambient (automatic spatial processing) and focal (conscious visual processing). The analysis of computer gamers' skill level via the analysis of fixation durations may be used in developing adaptive interfaces and in interface design.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 4 Jun 2019.
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Citing papers per year: 2024: 1; 2025: 0; 2026: 1.
2 papers.
- 2024An efficient machine learning approach for extracting eSports players distinguishing features and classifying their skill levels using symbolic transfer entropy and consensus nested cross validationcited by 1
- 2026Signals of Success and Struggle: Early Prediction and Physiological Signatures of Human Performance across Task Complexitycited by 0
- 2026Signals of Success and Struggle: Early Prediction and Physiological Signatures of Human Performance across Task Complexity19 Mar 2026
- 2024An efficient machine learning approach for extracting eSports players distinguishing features and classifying their skill levels using symbolic transfer entropy and consensus nested cross validation8 May 2024