# Sensors and Game Synchronization for Data Analysis in eSports

## TL;DR

This paper presents a system for collecting and synchronizing diverse data types in eSports training, achieving high accuracy to enhance skill analysis and training methods.

## Contribution

It introduces a novel synchronization system for heterogeneous sensors and game data, with demonstrated 10 ms accuracy in eSports environments.

## Key findings

- Synchronization accuracy up to 3 ms in CS:GO
- Effective integration of physiological, environmental, video, and telemetry data
- Potential to improve training and skill assessment in eSports

## Abstract

eSports industry has greatly progressed within the last decade in terms of audience and fund rising, broadcasting, networking and hardware. Since the number and quality of professional team has evolved too, there is a reasonable need in improving skills and training process of professional eSports athletes. In this work, we demonstrate a system able to collect heterogeneous data (physiological, environmental, video, telemetry) and guarantying synchronization with 10 ms accuracy. In particular, we demonstrate how to synchronize various sensors and ensure post synchronization, i.e. logged video, a so-called demo file, with the sensors data. Our experimental results achieved on the CS:GO game discipline show up to 3 ms accuracy of the time synchronization of the gaming computer.