Mathematical Modelling of Football

This course gives the required set of tools to work as a data scientist within a professional football club, national body or the media. It covers the technical knowledge anyone working in this area should have to contribute to a football organisation: * statistical methods and visualisation * data sources and relevant cloud computing * standards for handling and storing data * classification and regression * expected goals and action value models * logistic regression * neural networks and other machine learning methods applied to football * basic analysis methods for tracking data * simulation methods; and * pitch control. The examples in the course are primarily from football, with a focus on practical applications found within footballing organisations, focusing on creating key performance indexes for players and teams. It shows how data and models can be used to communicate with coaches, scouts, sporting directors, players and fans. **Outline for distance course:** This is a web-based course, completely without physical meetings (including the examination). Reading instructions and other communication are handled through the course home page and email. Internet access is a requirement for this course. The teaching language is English, which is required for all the individual work. Contact with the teacher can be made in Swedish.