In this post I will pre-process, explore, transform, and model data from baseball team seasons from 1871-2006 inclusive (stats adjusted to match 162-game season). Feature additions and transformations can improve the predictive power of created models and in this post I’ll employ a Box-Cox transformation to acheive this. The goal is to create a model that can predict baseball team wins based on the performance metrics captured in the training dataset moneyball-training-data.