Process Mining Meets Football

17:09Recorded on 20 June 2019 at TU Eindhoven

Hadi Sotudeh(JADS, Netherlands)

Hadi brought his enthusiasm for football and his love for data together when he analyzed the 2018 World Cup data with process mining. He realized that the key to finding patterns is to make the right assumptions when preparing the data.

Synopsis

Sometimes, an application of process mining comes along that nobody thought of before. Hadi Sotudeh, PDEng student at JADS, had such an example when he applied process mining to data from the 2018 World Cup in football.

After transforming the data into an event log suitable for process mining, he was especially interested in how a football team possesses the ball on the pitch. This would give coaching staff great insights into interesting patterns of play to develop counter strategies for an opponent, or for a team to learn from mistakes.

The challenge is that the football interactions do not follow a typical (standard) process. Therefore, finding the right perspective is not easy. Hadi shows that there is not just one perspective, but that the same data can be molded to explore many different angles. Each of these perspectives can give different insights. For example, next to sequences of types of actions, he also looked at interactions between individual players, zones in the field, and patterns for particular outcomes (e.g., goal or throw-in).

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