How to Use Graph Theory to Scout Soccer Posted on : Nov 21 - 2022

Not all networks are social! Graph theory flexed its muscles with the rise of social networks. But what can it do for sports analytics? What if we model soccer passes as a network? Can we learn which team is more likely to win? Can we identify critical players to pressure the opposing team? Can we identify opportunities to improve our team’s performance?

To find out, we can use the Statsbomb API to access free data on every pass in the 2018 World Cup.

What is Graph Theory for Soccer?

 A ‘network’ is the everyday word for what data science calls a graph. In analytics, a graph is a formal way to represent a group of interconnected objects. This is borrowed from math where graphs are defined as ordered pairs that include a set of nodes and a set of edges.

The terminology makes more sense with an example. Let’s see what a graph of soccer passes might look like:

For us, a team passing graph is the combination of these attributes for all matches played by a given team in the 2018 World Cup.

Now let’s see what kind of graph analytics come out-of-the-box. These are the common metrics we can use to investigate the pass network properties of a given team or player: View More