Measuring Skill and Chance in Games

Online and offline gaming has become a multi-billion dollar industry. However, games of chance are prohibited or tightly regulated in many jurisdictions. Thus, the question whether a game predominantly depends on skill or chance has important legal and regulatory implications. In this paper, we suggest a new empirical criterion for distinguishing games of skill from games of chance: All players are ranked according to a "best-fit" Elo algorithm. The wider the distribution of player ratings are in a game, the more important is the role of skill. Most importantly, we provide a new benchmark ("50%-chess") that allows to decide whether games predominantly (more than 50%) depend on chance, as this criterion is often used by courts. We apply the method to large datasets of various two-player games (e.g. chess, poker, backgammon, tetris). Our findings indicate that most popular online games, including poker, are below the threshold of 50% skill and thus depend pre- dominantly on chance. In fact, poker contains about as much skill as chess when 3 out of 4 chess games are replaced by a coin flip.