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Found 5 papers, 5 papers with code
AI-enabled Prediction of eSports Player Performance Using the Data from Heterogeneous Sensors
For this reason, we collected the physiological, environmental, and the game chair data from Pro and amateur players.
Detecting Video Game Player Burnout with the Use of Sensor Data and Machine Learning
In this article, we propose the methods based on the sensor data analysis for predicting whether a player will win the future encounter.
BIG-bench Machine Learning
Interpretable Machine Learning
+8
Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset
An important feature of the dataset is simultaneous data collection from five players, which facilitates the analysis of sensor data on a team level.
Ranked #1 on
Skills Evaluation
on eSports Sensors Dataset
eSports Pro-Players Behavior During the Game Events: Statistical Analysis of Data Obtained Using the Smart Chair
Today's competition between the professional eSports teams is so strong that in-depth analysis of players' performance literally crucial for creating a powerful team.
Understanding Cyber Athletes Behaviour Through a Smart Chair: CS:GO and Monolith Team Scenario
eSports is the rapidly developing multidisciplinary domain.
