This week we will work with event data. Here we assume you have watched the setting up for the course video at the bottom of 'week 0' and have set up an environment where you can program in Python. Please work through this webpage, doing the exercises as you go. It is good if you can work with sections 1.1 - 1.3 before the first lecture on Tuesday 1st September at 10:15.

1.1 Handling Event Data

In this lecture I go through the basics of loading in event data from Statsbomb.

Learning goals for this video are:

Downloading code and data
Organising working folder
Loading in data in a json file?
Using ‘for’ loops and ‘if’ statements
Identifying specific matches in Statsbomb data

The code you need for todays lecture is available in https://github.com/Friends-of-Trackin...

1.2 Plotting actions on a pitch

We now look at how to plot actions on a pitch.

Learning goals for this video are:

1, Loading match data and finding all the shots

2, Plotting shots on the pitch and highlighting goals.

3, Plotting expected goals

4, Plotting passes

The code you need for todays lecture is available in: https://github.com/Friends-of-Trackin...

1.3 Mini-challenge: plotting actions

1, Think of a player who you enjoyed watching at the recent Men’s or Women’s World Cups.

2, What actions did they perform that were important and why?

3, Plot the actions and describe how the data supports or contradicts your own analysis.

4, Write a short text using at most two figures that illustrate your point.

Go in to the Discussion group for this mini-challenge and post your answers. You are very welcome to use methods discussed in later lectures here.

Deadline is the evening of Wednesday 9th, before the tutorial in course week 2.

1.4 Live lecture: insights from data.

This lecture will take place on the 1st of September at 10:15.

Lecture note from this lecture can be downloaded here.

1.5 More advanced visualisations and data analysis

Luca Pappalardo talks us through the Wyscout data set.

In this video he covers:

The Wyscout data set, how it is collected, from players to events.
Basic statistics on events and distributions.
Plotting events on the field, match evolution and spatial stats.
Advanced statistics: passing networks, flow centrality and playerRank

You should download the code at https://github.com/Friends-of-Trackin.. and work through the data set together with the video.

1.6 Guest lecture: good practice in visualisation.

Opta's Peter McKeever gives us insight in to how to make better data visualisations. This lecture will take place on the 3rd of September at 15:15.

Peter's notes are here. Peter has an excellent blog with code and further examples. He also mentioned the blog by Lisa Charlotte Rost.

Time progress: You should have watched this material by Friday 4th September and posted your analysis of World Cup data by Wednesday 9th.