  Computational Social Choice (ComSoc) is a rapidly developing field at the
intersection of computer science, economics, social choice, and political
science. The study of tournaments is fundamental to ComSoc and many results
have been published about tournament solution sets and reasoning in
tournaments. Theoretical results in ComSoc tend to be worst case and tell us
little about performance in practice. To this end we detail some experiments on
tournaments using real wold data from soccer and tennis. We make three main
contributions to the understanding of tournaments using real world data from
English Premier League, the German Bundesliga, and the ATP World Tour: (1) we
find that the NP-hard question of finding a seeding for which a given team can
win a tournament is easily solvable in real world instances, (2) using detailed
and principled methodology from statistical physics we show that our real world
data obeys a log-normal distribution; and (3) leveraging our log-normal
distribution result and using robust statistical methods, we show that the
popular Condorcet Random (CR) tournament model does not generate realistic
tournament data.
