We examine three topics related to experimental design in this dissertation. Two are related to the analysis of experimental data and the other focuses on the design of paired comparison experiments, in this case knockout tournaments. The two analysis topics are motivated by how to estimate and test causal effects when the assignment mechanism fails to create balanced treatment groups. In Chapter 2, we apply conditional randomization tests to experiments where, through random chance, the treatment groups differ in their covariate distributions. In Chapter 4, we apply principal stratification to factorial experiments where the subjects fail to comply with their assigned treatment. The sources of imbalance differ, but, in both cases, ignoring the imbalance can lead to incorrect conclusions. In Chapter 3, we consider designing knockout tournaments to maximize different objectives given a prior distribution on the strengths of the players. These objectives include maximizing the probability the best player wins the tournament. Our emphasis on balance in the other two chapters comes from a desire to create a fair comparison between treatments. However, in this case, the design uses the prior information to intentionally bias the tournament in favor of the better players. / Statistics

This dissertation consists of five articles about economics of sports. The first three articles investigate various types of outcome uncertainty and how they relate to match attendance demand, while the remaining two articles test the efficiency of sports betting markets. The first article presents a new method of calculating match importance. Unlike the previous approaches in the literature, it does not require ex-post information and can be used for any type of season outcome. The second article shows that the additional playoff stage in the Czech ice hockey "Extraliga" lowers the probability of the strongest team becoming a champion and thus increases seasonal uncertainty. The third article demonstrates that the inconsistent findings in the literature about the link between match uncertainty and attendance could be explained by wrongly specified regressions, proposes a new approach to analyzing the effect of match uncertainty and shows that attendance demand is maximized if teams of the same quality play against each other. The fourth article examines the favorite-longshot bias in the context of betting on tennis matches. It shows that the favorite-longshot bias pattern is consistent with bookmakers protecting themselves against both better informed insiders and the general public exploiting new information. The fifth article investigates the supposedly profitable strategy of betting on soccer draws using the Fibonacci sequence. The strategy is tested both in a simulated market and on a real data set and found to lose money.