It's rare that we get to tackle applying statistical techniques to a new sport, but that has been occurring in soccer/football in the past decade. What follows is an overview of progress in the field of soccer analytics that also details the application of various statistical techniques along the way. Much of the knowledge of how the game operates at a statistical level had to be built from the ground up. Research started with basic correlations and regressions, and then progressed through Generalized Additive Models, Generalized Linear Mixed Models, and Bayesian Inference. In addition to discussing the various uses of different approaches in soccer analysis, we will discuss the research and application of these techniques while inside football clubs where they are often influencing decisions worth hundreds of millions of pounds a year.