Abstract
League of Legends is one of the most popular online games today, with a competitive scenario and a solid and constantly growing player base. This work aims to explore a solution that identifies game events and strategies from the convergence of different psychophysiological metrics from seasoned players in order to create tools to reduce the learning curve of these strategies for beginner and intermediate players. To achieve this, experiments with five participants have been conducted that extract, process, and synthesize data from player profiling, Electrodermal Activity (EDA), Interbeat Interval (IBI), facial expressions, and player perception of the match. The EDA and HR data (derived from the IBI metric) proved to be complementary and correspond with game events and strategies, while facial expression data had inconclusive results in all experiments.
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Available at https://blitz.gg.
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Available at https://mobalytics.gg.
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Available at https://obsproject.com/.
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Bandeira, I.N., Castanho, C.D., e Silva, T.B.P., Sarmet, M.M., Jacobi, R.P. (2023). Applicability of Psychophysiological and Perception Data for Mapping Strategies in League of Legends – An Exploratory Study. In: Fang, X. (eds) HCI in Games. HCII 2023. Lecture Notes in Computer Science, vol 14047. Springer, Cham. https://doi.org/10.1007/978-3-031-35979-8_10
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