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Leiden bachelor students analyse data EC soccer

Leiden bachelor students analyse data EC soccer Students are now familiar with something sports journalists already knew: summer holidays can be a time of hard labour. Everybody else is lying on the beach, but for you, it is the busiest time of the year. Leiden bachelor students collected the data of the European Football Championship for women. By now, as the championship is over, they are making a start with analyzing the data. The big question: what made the difference for the Dutch Lionesses to become champions?

Soccer shirt

Bachelor students Patrick Bergman, Lucie Kuiper, Jody Liu and Lars Suanet are telling about their summer job in their blue socces shirts. Although, job. Volunteer work. Study project. Call it as you like, but they did this for fun. They see the possibilities of data-analysis for top sport. Valorisation of your studies. Be able to work with real data. Except for this T-shirt, the only thing they received for al those weeks of data collection and analysis: a ticket to the EC’s openings match.

Leiden Computer science students analyse the data of the EC women's soccer. Fltr supervisor Niek van Ulzen, Lucie Kuiper, Lars Suanet, Patrick Bergman, supervisor Arie-Willem de Leeuw en Jody Liu.

Two types of data

During the EC, the students team received a wide range of data, the day after a match. Patrick Bergman: ‘There are two types of data. In the first place, there are the positional data: which player was standing where at what moment. That was recorded automatically with cameras, 10 times per second. Apart from that, a specialized company sent us the event data: what kinds of actions were happening in the field. There are about 100 different sorts of events. Event 1, for example, is a pass.’


The team actually exists of five students. Erik Weenk could not make it this morning. ‘With the five of us, we have written a piece of software to be able to analyse the data now, right after the EC’, says Patrick. ‘Everybody has his own topic. That is how we gain insight into all matches of the Dutch team.’ Jody Liu: ‘I for example look at the lengths and numbers of ball possession during a match.’

Not just counting numbers

And with this selfmade software, Lars Suanet analyses the duals within all matches of the Dutch team. ‘With this, I mean the duals between individuals. How often did a certain person win a dual? Apart from that, I am looking at throw-ins. Did players throw the ball forward or backward? And when were the most or least successful? During the EC, most of our job was to transform all these data into information that can be understood. It is more complicated than just counting the numbers. You will have to decide how to visualize the information. There are 101 different graphs to choose from.’

Learn to code

The only one in the group who loves soccer, is Lucie Kuiper. She is the only one who doesn’t study computer science, but she is a soccer player. ‘I am a third year Chemistry student and I indeed play soccer. I have done a minor in data science. At this moment, I am learning how to code, as I may start a master in computer science. I know Lars from the honours programme of Leiden University. That is how I heard about the project.’

Golden Standard

When Lucie starts talking about the insights that she hopes data science will give her about the excellent results of the OrangeLionesses during the EC, you can see that she is enjoying herself. ‘Wouldn’t it be great to know whether you should perform a short corner or a long one?’ And about her own role in the project: ‘It is my job within the team to look for the Golden Standard. We are now, with the independent data, trying to understand what made The Netherlands the champion.’ Lars is adding: ‘But of course creative play is the most important thing. You cannot formalize that.’


IT-service company Qualogy, specialized in data-driven technologies and partner of Leiden University, helped the students develop the software. The company has developed a analysis-app that provides trainers and technical support staff with insights into the achievements of individual players and the team as a whole, based on positional data and event data. Apart from that, the research team receives help on an international level: universities in Porto, Leuven and the German Lüneburg are advising them on the analysis of the soccer data.

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