"Learn to play, noob!": The identification of ability profiles for different roles in an online multiplayer video game in order to improve the overal quality of the new player experience

Abstract

Being a new player in a multiplayer game is not an easy experience. If the game requires coordinated team play for success, an inexperienced player can receive a high amount of abuse because of what others view as bad plays. While the companies try to alleviate this problem by focusing on the offenders, we present another approach that can also help in decreasing toxic behavior. In our paper we introduce the first steps at researching what it requires to perform well in any given role in a popular multi player game, League of Legends. Using focus groups and online questionnaires we narrow down the list of abilities to 6, in which different profiles would predict different most successful playstyles. Based on these ability profiles the game itself should give more customized tutorial sessions and recommendations to new players who in turn will have an overall improved first impression. Through having better performance, we believe, that some of the toxic behavior experienced by new players can be extinguished.