In this post, we will learn how to use statistical learning to build models for classifying pass outcomes. Classification is the operation of labeling a set of data into different classes, for example whether a pass from a player will be a successful or an unsuccessful pass depending on a set of particular features.
In our last tutorial, we studied how to visualize a pass network for the teams from a particular match and how to analyse the networks using knowledge from complex network analysis literature.
In our last tutorial we studied how to draw a pass map, a shot map and their corresponding heat maps. We used statsbomb’s open even data from the match between Real Madrid and Barcelona, which Real Madrid ended up winning 2-0.
In this post, we will learn how to draw simple pass maps and shot maps and visualize their corresponding heat maps. We will study use the event data from the Real Madrid vs.
This is the first of all the blog posts that are to be published further. In this tutorial we will learn how to download open access event data from statsbomb using the Python package statsbombpy.