Player-Driven Game Analytics: The Case of Guild Wars 2
Johannes Pfau, Magy Seif El‐Nasr
Abstract
Video game analytics are widely adopted within academia and industrial development – yet, the player’s perspective is rarely considered as a driving factor, even though vast communities are interested in self-regulated learning, cross-comparisons and empirical trends or insights. In this work, we propose to empower the role of the player as the central impulse for analytics, collect requirements and data from the community of one of the most popular MMORPGs (Guild Wars 2), establish a tool over a 18-month period of participatory development and discuss the co-created features. With analytics for in-game logs from (n = 175, 099) unique players and atomic game actions of over 2 million hours played, we contribute a large-scale, long-term iterative implementation and evaluation of a player-driven instrument to quantify popularity, viability and hierarchical inspection between classes or individual performances. This tool found frequent usage among the actual game community, delivering game data science to the very player.