  Game theory is the study of tractable games which may be used to model more
complex systems. Board games, video games and sports, however, are intractable
by design, so "ludological" theories about these games as complex phenomena
should be grounded in empiricism. A first "ludometric" concern is the empirical
measurement of the amount of luck in various games. We argue against a narrow
view of luck which includes only factors outside any player's control, and
advocate for a holistic definition of luck as complementary to the variation in
effective skill within a population of players. We introduce two metrics for
luck in a game for a given population - one information theoretical, and one
Bayesian, and discuss the estimation of these metrics using sparse,
high-dimensional regression techniques. Finally, we apply these techniques to
compare the amount of luck between various professional sports, between Chess
and Go, and between two hobby board games: Race for the Galaxy and Seasons.
