In this webinar, Rob Mastrodomenico will look at the fundamental principles behind the beautiful game, specifically how you can characterise what is important and not important in a match between two sides.
Rob will introduce a machine learning approach applied to football. The method assumes goals scored by each team can be modelled allowing us to obtain ability parameters for each team. The method will be demonstrated via a first principles approach building up from a very simple model to the final model. Rob will demonstrate how the output can be used to make predictions of upcoming games via a number of real life examples including the English Premier League.
- Introduction to how machine learning can be applied to real life problems
- Understanding of the application of machine learning models
Robert Mastrodomenico, Owner, Global Sports Statistics
Robs background is in Data Science and Machine Learning (ML) having completed a degree in Mathematics and Statistics and a PhD in Applied Statistics. His research interests are in the application of ML techniques to sports applications. He is also a keen Python programmer and has been teaching the subject for a number of years and will have his first book on the subject in 2021. Rob runs his own consultancy company specialising in Data Science applications and has also taken on CTO roles in various companies. Outside of work Rob has done lots in the area of communicating data driven stories and has made appearances of BBC TV, as well as other major print media and radio.