3. Simulating football matches

This week you should primarily focus your attention on the Evaluating passes assignment. Make sure you have it finished before the deadline on the 20th.

3.1 Randomness and prediction in football

In this live lecture (Tuesday 15th September) David explains how much randomness is football, introduces the Poisson distribution and Poisson regression for modelling football.

Code for todays lecture is are files numbered 9,10 and 11 in the Github directory Links to an external site.. Lecture notes available for download here.

3.2 Ranking players using regression models

This video provides a methodology for ranking players based on regression. It also starts with an excellent history of player ranking systems. 

This video goes slightly deeper in to rankings than is required for this course, but 

Garry and Lars talk through this article as well as giving an excellent background on ranking models. https://content.iospress.com/articles... Download https://content.iospress.com/articles...

See also Garry's blog: http://business-analytic.co.uk/blog/l... Links to an external site.

Garry passed away a few months after this presentation. He is sorely missed by the analytics community.

3.3 How IT is used within clubs.

Sayed Farook, former Manchester United FC Deputy Head of Technology & Operations Manager, and current Football Technology Consultant, outlines tells us more about how a data scientist work will fit in to a club. Lecture live at 16:15, Thursday 17th September. 

Notes from the lecture are available here Download here