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Live Feedback for Training Through Real-Time Data Visualizations: A Study with League of Legends

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Abstract

With competitive gaming on the rise, players have developed an increased interest in data-driven feedback of their in-game performance. In many cases, this feedback is presented visually post-play but live companions that provide real-time analytics are gaining more and more attention. However, the design of such systems poses different requirements which have been little explored from a scholarly point of view. In this paper, we report on a study of two visualizations - a physical and digital one - providing live feedback to League of Legends players designed based on a community survey (N= 175) and expert input. We further discuss results of a qualitative evaluation with 13 players and an expert, touch upon potential benefits and drawbacks of physical and digital implementations, and present derived design considerations and challenges for such real-time data visualizations, revolving around issues of information density, contextualization, representation, and a diverse range of user needs.

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