Evaluating the League of Legends Tutorial Based on a Theoretical Skill Model
Summary
Multiplayer Online Battle Arena (MOBA) games have become extremely complex. Getting into them as a new player becomes a harder task every day as the amount of knowledge you would have to know and skills you have to possess in advance keeps growing. New player inexperience could lead to them being the target of abuse from other players since they will view their mistakes as bad plays. Modern methods such as chat detection or reporting systems, tend to focus on the perpetrator of toxic behaviour to reduce the negativity of online communications. I present a new approach to help decrease it. In this paper, I focus on bridging the skill gap between new players and veteran players by researching what it takes to play League of Legends optimally. Using an established skill model for esports games, I have applied it to League and have defined the skills that fit within the model. With the help of an online questionnaire, I asked veteran players to narrow down the most important skills within League. Based on their feedback and the skill model, I have evaluated how well the current League tutorial matches their expectations. This approach shows that the current tutorial introduces a skill gap between what is expected of new players to know and what they should know to play League optimally. Through optimizing the tutorial content based on this model I believe that the new player experience can be improved, the toxic behaviour towards new players can be alleviated and potentially this approach can be applied to other complex (MOBA) games