# Towards Understanding of eSports Athletes' Potentialities: The Sensing System for Data Collection and Analysis

## TL;DR

This paper introduces a sensing system for collecting and analyzing data from professional eSports athletes, demonstrated through a case study on gaze data from a CS:GO team, aiding in player assessment and scouting.

## Contribution

It presents a novel sensing platform for real-time data collection from eSports athletes and provides a case study comparing amateur and professional gaze behavior.

## Key findings

- Gaze data collected from professional and amateur players shows distinct patterns.
- The sensing system enables detailed analysis of athlete performance.
- Results support improved scouting and training methods in eSports.

## Abstract

eSports is a developing multidisciplinary research area. At present, there is a lack of relevant data collected from real eSports athletes and lack of platforms which could be used for the data collection and further analysis. In this paper, we present a sensing system for enabling the data collection from professional athletes. Also, we report on the case study about collecting and analyzing the gaze data from Monolith professional eSports team specializing in Counter-Strike: Global Offensive (CS:GO) discipline. We perform a comparative study on assessing the gaze of amateur players and professional athletes. The results of our work are vital for ensuring eSports data collection and the following analysis in the scope of scouting or assessing the eSports players and athletes.