Prediction Models with Sports Data

This course will teach you how to forecast professional sports game results using Python. The course focuses on the use of logistic regression to model game results using data about team expenditures. Learners are guided through the process of modeling past results and using the model to predict the outcome of any games yet to be played. This course will teach the learner how they can evaluate the reliability and validity of a model by using data about betting odds. This analysis is first applied to the English Premier League, then to the NBA and NHL. This course provides an overview of data analytics and gambling, their history, and the social issues surrounding sports betting.