随意的
游戏设计
博弈机制
筛选游戏
计算机科学
电子游戏
认知
主题分析
情感(语言学)
心理学
游戏开发者
认知心理学
定性性质
非合作博弈
过程(计算)
控制感
电子游戏设计
博弈论
人机交互
游戏设计文档
游戏测试
重复博弈
元游戏
序贯博弈
控制(管理)
游戏
经济教育中的模拟与游戏
定性研究
社会心理学
同时博弈
功能可见性
电子游戏开发
作者
Amon Rapp,Arianna Boldi
标识
DOI:10.1016/j.chb.2025.108826
摘要
In contemporary gaming, players increasingly rely on numerical data to guide in-game decisions, interact with others, and enhance performance. Especially with the rise of esports and streaming practices, game “numbers” have become central to player development. This study aims to explore how game metrics affect the gaming experience of different kinds of players, investigating whether and how game data influence their performance and shape their sense of agency. With this aim, we adopted an interpretive qualitative approach and conducted forty semi-structured interviews with casual players, esports players, and streamers, asking participants to recount how they use and interpret game data. We then interpreted the collected material through the lens of the extended mind theory and analyzed it using thematic analysis. Study findings reveal that different types of players vary in how they track, understand, and trust game metrics, and that such metrics may extend their cognitive processes. Moreover, the findings show that a player's level of game knowledge influences how players process game data and adjust their behavior accordingly. These findings also suggest that an overemphasis on the “objectivity” of game metrics may lead players to rely excessively on external numerical validation, potentially diminishing their performance and sense of agency. By contrast, players who develop an in-depth understanding of game mechanics and refine their game sense retain greater control over their in-game decisions and behavior. In sum, this study contributes to the understanding of self-tracking in gaming and its implications for player agency, cognition, and performance. • We explore how 40 players use game metrics and track their game performance. • We compare casual players', esports players', and streamers' tracking practices. • We show that casual players may rely heavily on game metrics. • We highlight that esports players use their “game sense” to interpret game data. • We point out that streamers prioritize spectatorship over performance.
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