CEPAV Dataset: The Competitive Esports Physiological, Affective, and Video Dataset

Esports refers to competitive video gaming where individuals compete against each other in organized tournaments for prize money. Here, we present the Competitive Esports Physiological, Affective, and Video (CEPAV) dataset, in which 300 male Counter Strike: Global Offensive gamers participated in a study aimed at optimizing affect during esports tournament1. The CEPAV dataset includes (1) physiological data, capturing the player’s cardiovascular responses from before, during, and after over 3000 CS: GO matches; (2) self-reported affective data, detailing the affective states experienced before gameplay; and (3) video data, providing a visual record of 552 in-laboratory gaming sessions. We also collected (affect-related) individual differences measures (e.g., well-being, ill-being) across six weeks in three waves. The self-reported affective data also includes gamers’ natural language descriptions of gaming affective situations. The CEPAV dataset provides a comprehensive resource for researchers and analysts seeking to understand the complex interplay of physiological, affective, and behavioral factors in esports and other performance contexts.

电子竞技（Esports）指选手通过有组织的赛事同台竞技并争夺奖金的竞技性电子游戏活动。本研究公开了竞技电竞生理、情感与视频数据集（Competitive Esports Physiological, Affective, and Video, CEPAV），该数据集依托一项旨在优化电子竞技赛事1中选手情感状态的研究构建，共有300名男性《反恐精英：全球攻势》（Counter Strike: Global Offensive, CS:GO）玩家参与其中。CEPAV数据集包含三类核心内容：(1) 生理数据：采集了3000余场CS:GO对局前后及对局过程中选手的心血管反应数据；(2) 自我报告情感数据：详细记录了玩家在游戏开始前的主观情感状态；(3) 视频数据：提供了552场实验室对局的全程视觉记录。研究团队还分三轮、历时六周完成了与情感相关的个体差异测量指标采集，涵盖幸福感、不良心理状态等维度。此外，自我报告情感数据还包含玩家对游戏中情感场景的自然语言描述文本。本CEPAV数据集可为致力于探究电子竞技及其他竞技场景中生理、情感与行为因素间复杂交互关系的研究人员与分析师提供全面的研究资源。