Beyond the Meta: Leveraging Game Design Parameters for Patch-Agnostic Esport Analytics

Esport games comprise a sizeable fraction of the global games market, and is the fastest growing segment in games. This has given rise to the domain of esports analytics, which uses telemetry data from games to inform players, coaches, broadcasters and other stakeholders. Compared to traditional sports, esport titles change rapidly, in terms of mechanics as well as rules. Due to these frequent changes to the parameters of the game, esport analytics models can have a short life-spam, a problem which is largely ignored within the literature. As a case study, a neural network model is trained to predict the number of kills in a Dota 2 match utilising this novel character representation technique. The performance of this model is then evaluated against two distinct baselines, including conventional techniques. Not only did the model significantly outperform the baselines in terms of accuracy (85% AUC), but the model also maintains the accuracy in two newer iterations of the game that introduced one new character and a brand new character type. These changes introduced to the design of the game would typically break conventional techniques that are commonly used within the literature. Therefore, the proposed methodology for representing characters can increase the life-spam of machine learning models as well as contribute to a higher performance when compared to traditional techniques typically employed within the literature. Beyond the Meta: Leveraging Game Design Parameters for Patch-Agnostic Esport Analitics Introduction Esport titles, such as League of Legends and Dota 2, have amassed both large audiences and player-bases (Newzoo, 2022; Petrovskaya and Zendle, 2020). Due to the competitive nature of the genre, the player community often develop so called "metas" as explained by Kokkinakis et al. (2021). According to the author, metas are naturally discovered and developed strategies for optimum ways of playing the game that are focused in determining competitive advantage available within the current parameters of the game design.