# Eye Movement Feature Classification for Soccer Goalkeeper Expertise Identification in Virtual Reality

arXiv: https://arxiv.org/abs/2009.11676 · HTML: https://mlsanity.com/paper/2009.11676/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Sep 2020.

## Built on by (most cited first, 2 of 2)

- [Evaluating Deep Networks for Detecting User Familiarity with VR from Hand Interactions](https://mlsanity.com/paper/2401.16443/) (2024)
- [Differentiating Surgeon Expertise Solely by Eye Movement Features](https://mlsanity.com/paper/2102.08155/) (2021)

## Abstract (arXiv)

The latest research in expertise assessment of soccer players has affirmed the importance of perceptual skills (especially for decision making) by focusing either on high experimental control or on a realistic presentation. To assess the perceptual skills of athletes in an optimized manner, we captured omnidirectional in-field scenes and showed these to 12 expert, 10 intermediate and 13 novice soccer goalkeepers on virtual reality glasses. All scenes were shown from the same natural goalkeeper perspective and ended after the return pass to the goalkeeper. Based on their gaze behavior we classified their expertise with common machine learning techniques. This pilot study shows promising results for objective classification of goalkeepers expertise based on their gaze behaviour and provided valuable insight to inform the design of training systems to enhance perceptual skills of athletes.