Abstract

Although player performance in online games has been widely studied, few studies have considered the behavioral preferences of players and how they impact performance. In a competitive setting where players must cooperate with temporary teammates, it is even more crucial to understand how differences in playing style contribute to teamwork. Drawing on theories of individual behavior in teams, we describe a methodology to empirically profile players based on the diversity and conformity of their gameplay styles. Applying this approach to a League of Legends dataset, we find three distinct types of players that align with our theoretical framework: generalists, specialists, and mavericks. Importantly, the behavior of each player type remains stable despite players becoming more experienced. Additionally, we extensively investigate the benefits and drawbacks of each type of player by evaluating their individual …

Date

April 22, 2021

Authors

Julie Jiang, Danaja Maldeniya, Kristina Lerman, Emilio Ferrara

Journal

Proceedings of the ACM on Human-Computer Interaction

Volume

5

Issue

CSCW1

Pages

1-26

Publisher

ACM