%0 Generic
%A Duersch, Peter
%A Lambrecht, Marco
%A Oechssler, Joerg
%A Universität Heidelberg,
%C Heidelberg
%D 2017
%F heidok:23867
%R 10.11588/heidok.00023867
%T Measuring Skill and Chance in Games
%U https://archiv.ub.uni-heidelberg.de/volltextserver/23867/
%V 0643
%X 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.