Real-Time Dashboards to Support eSports Spectating

Abstract

eSports matches offer fast-paced entertainment for millions of viewers worldwide, but little is known about how to support a positive viewer experience. One of the key challenges related to popular real-time eSports games (e.g., multiplayer online battle arena games or first-person shooters) is empowering viewers to effectively follow rapid gameplay. In our paper, we address this challenge through the design of dashboards to improve spectator insight and experience in League of Legends, and Counter Strike: Global Offensive. Based on surveys that received a total of 788 responses, we designed information dashboards that we evaluated with 18 experienced eSports viewers. Our results indicate that dashboards contribute to spectator insight and experience, but that careful consideration is necessary to adequately manage in-game complexity and cognitive load of viewers, and establish spectator trust in information dashboards through transparent design. Based on these findings, our paper formulates design goals for spectator dashboards, and outlines key opportunities for future work. CCS Concepts •Human-centered computing → Information visualization; Graphical user interfaces;

Social motivations of live-streaming viewer engagement on Twitch

“…Constructing esport as a mediated spectator experience is challenging, as there is a wealth of information that is generated by the games being played. As such, initial efforts have looked at improving the spectator experience through assisted systems such as dashboards (Charleer et al, 2018), and conceptual developments such as the technical segmentation of various parts of the game (Schubert et al, 2016). From the perspective of building a wider understanding, the consumption of esports is not something that has been previously investigated to any great extent.…”

“…Broadcast sports commonly feature a large amount of information not necessarily available through live attendance, such as highlights, replays, commentary, and modern modes of digital augmentation (Hutchins and Rowe, 2013;Trail, 2018). In the realm of esports research, tools have also been developed to facilitate the spectating experience (Charleer et al, 2018;Schubert et al, 2016). Thus, while the live experience might be important for other reasons, for cognitive motivations such as learning, it might not necessarily be the optimal mode of spectating.…”

“…The findings regarding the acquisition of knowledge within esports spectating also point to the importance of being able to convey relevant information such as statistics and team-specific strategies, during matches. Thus, practitioners should look towards expanding already existing methods of showing information to spectators in meaningful ways, and perhaps look to develop new tools for doing so (Charleer et al, 2018;Schubert et al, 2016). As shown in Publication 5, live attendees do not rate these cognitive motivations as highly, and thus an effort could be made to improve their facilitation during live events.…”

Towards an Open Standard for Gameplay Metrics

“…Such player focused solutions can reach beyond just "casual information visualisation" [17]. Charleer et al [3] visualise League of Legends and Counter-Strike: Global Offensive eSports match data in order to support "expert spectators"; in the context of this work it was revealed that many games are often viewed to improve one's own game, outlining the importance of easy accessibility of Gameplay Metrics to support players. However, extracting the data required for such applications is not straightforward.…”

“…However, extracting the data required for such applications is not straightforward. A common way for data scientists and hobbyists to attain the data is through replay files [18,3], log files [14], and Application Programming Interfaces (APIs) [3]. API data are often limited to high level aggregated statistics regarding player and team performance.…”