  The popularity of online gaming has grown dramatically, driven in part by
streaming and the billion-dollar e-sports industry. Online games regularly
update their software to fix bugs, add functionality that improve the game's
look and feel, and change the game mechanics to keep the games fun and
challenging. An open question, however, is the impact of these changes on
player performance and game balance, as well as how players adapt to these
sudden changes. To address these questions, we use causal inference to measure
the impact of software patches to League of Legends, a popular team-based
multiplayer online game. We show that game patches have substantially different
impacts on players depending on their skill level and whether they take breaks
between games. We find that the gap between good and bad players increases
after a patch, despite efforts to make gameplay more equal. Moreover, longer
between-game breaks tend to improve player performance after patches. Overall,
our results highlight the utility of causal inference, and specifically
heterogeneous treatment effect estimation, as a tool to quantify the complex
mechanisms of game balance and its interplay with players' performance.
