The competitive esports physiological, affective, and video dataset

Area of Science:

• Sports Science
• Psychology
• Data Science

Background:

• Esports, or competitive video gaming, is a rapidly growing industry with significant prize pools.
• Understanding the psychological and physiological factors influencing esports performance is crucial for player well-being and optimization.
• Existing research often lacks comprehensive, multi-modal data capturing the esports experience.

Purpose of the Study:

• To introduce and describe the Competitive Esports Physiological, Affective, and Video (CEPAV) dataset.
• To provide a rich resource for investigating the interplay of physiological, affective, and behavioral factors in esports.
• To facilitate research aimed at optimizing player affect and performance in competitive gaming.

Main Methods:

• Collected physiological data (cardiovascular responses) from 300 male Counter-Strike: Global Offensive gamers across over 3000 matches.
• Gathered self-reported affective data, including natural language descriptions of gaming situations, before gameplay.
• Acquired video data from 552 in-laboratory gaming sessions and collected affect-related individual differences over six weeks.

Main Results:

• The CEPAV dataset comprises multi-modal data streams essential for esports research.
• It includes detailed physiological, affective, and behavioral metrics linked to competitive gaming.
• Longitudinal individual differences data provides context for affective states.

Conclusions:

• The CEPAV dataset is a valuable, comprehensive resource for the esports research community.
• It enables in-depth analysis of performance-related factors in competitive gaming.
• Researchers can utilize this dataset to explore strategies for enhancing player well-being and optimizing performance.