The Wide, the Deep, and the Maverick: Types of Players in Team-based Online Games

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Although player performance in online games has been widely studied, few studies have considered the behavioral preferences of players and how that impacts 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 performance, contribution to the team, and adaptation to changes in the game environment. We find that, overall, specialists tend to outperform others, while mavericks bear high risk but also potentially reap great rewards. Generalists are the most resilient to instability in the environment (game patches). We discuss the implications of these findings in terms of game design and community management, as well as team building in environments with varying levels of stability.