Gameplay Analysis of Multiplayer Games with Verified Action-Costs

Abstract

Measuring player skill cannot be done by considering their historical success alone as the relative skill of their opponents must be considered along with confounding factors such as luck and circumstance. With a specifically designed game, every possible player action can be attributed a cost, the value by which a player reduces their maximum probability of winning. By considering the costs of the actions made by a player we can obtain a more accurate representation of how skilful they are. We developed such a game, the mobile game RPGLite, and compared the actions players made with the cost values we had calculated. Through this analysis we made several observations about RPGLite which we share here to demonstrate the utility of action-costs for gameplay analysis. We show how they can be used to identify game states which players have difficulty making the best moves from, to measure how players learn over time and to compare the strengths and complexity of the characters of RPGLite. Commercial titles could benefit from similar tools—we discuss the feasibility of applying our approach to more complex games.