Abstract
Electronic Sports (eSports) is a fast-growing domain within the entertainment sector and becomes economically relevant in terms of a paying audience, merchandise, and major tournaments with highly endowed prize money. First-person shooter (FPS) games represent a dominant discipline. Professional training methodologies such as post-match analyses and tactics discussions are becoming essential in training sessions besides pure mechanical-oriented exercises such as aiming and movement. Furthermore, professional sports coaches are involved in the training of players. In this paper, we are investigating this newly developing profession, specifically, how multimedia systems can be built to support coaches and players in analyzing data of previous matches for preparing for future ones. In the example of Counter-Strike: Global Offensive (CS:GO), we identified a set of six criteria that can be incorporated into tools to support the analysis of FPS matches. We describe user interface functionalities that allow to interactively analyze the highly multivariate data of FPS matches. We show our concepts’ technical feasibility by implementing them within a tool – CS:Show. Within an expert user study, evaluate our concepts with professionals. We conclude that our proposed eSports analysis tool was preferred over analysis functionalities built in in CS:GO. Supported by statistically significant evidence, our participants rated our tool more efficient, more usable, and assigned the tool with higher analytical ability than an average tool for analyzing FPS eSports matches.
The work is supported by the Federal Ministry of Education and Research of Germany in the project Innovative Hochschule (funding number: 03IHS071).
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Horst, R., Zander, S.M., Dörner, R. (2021). CS:Show – An Interactive Visual Analysis Tool for First-Person Shooter eSports Match Data. In: Baalsrud Hauge, J., C. S. Cardoso, J., Roque, L., Gonzalez-Calero, P.A. (eds) Entertainment Computing – ICEC 2021. ICEC 2021. Lecture Notes in Computer Science(), vol 13056. Springer, Cham. https://doi.org/10.1007/978-3-030-89394-1_2
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