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Dutch tech firm transforms real-life football through video game concept

Tech company that helped the Belgian football team in the last World Cup is changing the way footballers are scouted and teams are trained

A Dutch company that was created when gamers thought the Football Manager computer game concept could work in real life helped to support the Belgian national team at the last World Cup in 2018.

Now, with the European Championship finals coming up this summer, countries are looking for ways to optimise their team’s performance – and data can play an important role.

During the 2018 World Cup, Dutch tech firm SciSports, which specialises in the analysis of football data, helped the Belgian team by providing analyses of its opponents. Giels Brouwer, CIO at SciSports, said: “It can be very interesting to see where the weaknesses lie in the team you have to play against, because then you can respond to them.”

But it is even more interesting for coaches to see their own team’s weaknesses, said Brouwer.

The concept for SciSports originated seven years ago at the Netherlands’ University of Twente, where Brouwer and two fellow students noticed that footballers were often scouted purely on the basis of a gut feeling by scouts. “We thought that could be done more efficiently, so we started to focus on data that could be used to support decisions,” said Brouwer.

The students were inspired by the video game Football Manager, in which the gamer takes on the role of technical director of a football club, making selections, buying players and playing matches with the right tactics. “I thought it would be nice to be able to do that in real life,” said Brouwer.

After an internship at Dutch football club FC Twente, where he analysed players and matches based on various datasets, Brouwer completed his studies in industrial engineering. Then, with two fellow students, he built a platform with the vision that data would become indispensable in analysing players and enriching the recruitment strategy.

The SciSports platform, Insight, contains data on 90,000 football players worldwide, which helps clubs and countries to find the right footballers for their team much more efficiently.

Brouwer said: “If you, as a club, want to have the greatest talents from Slovenia, for example, then a scout has to go there for at least two months to watch all kinds of matches and players. As a result, they see a lot of players who are quite good at playing soccer, but are not good enough for what the club is looking for. By looking at our database, you can focus on only those players that are good enough. That focus offers a lot of efficiency.”

Read more about data science in sport

Scouts, clubs and national teams can search the database using all kinds of variables, said Brouwer. “Suppose I am from FC Utrecht and I am looking for a striker who has the same qualities as Klaas-Jan Huntelaar. Then, on the Insight platform, I can set a search query for players similar to Huntelaar, with, for example, EU nationality and for under €5m. Then the players who meet these criteria roll out of the system.”

The platform is powered by data that SciSports buys from an Italian data provider, which employs countless people who manually collect data from almost all the professional matches played. “That is what they call a click farm,” said Brouwer. “These people record from where to where a pass is made, how a cross is made, what movement leads to a goal attempt, and so on.”

SciSports builds algorithms on top of that data so that users of the platform do not have to plough through all the data themselves, but can easily gain insights.

“For example, we measure the influence of a player on a team, and the influence of actions leading up to goals,” said Brouwer. Machine learning plays a major role in this, he added: “That’s the basis of everything.”

Three years ago, one machine learning expert started work at SciSports; now there is a whole team working there predicting the potential of players. The influence of an individual pass on a game and a team’s scoring ability is compared to 100 million similar passes in the system, said Brouwer. “We can see how many of those passes ultimately resulted in a goal, and therefore say something about the probability that a particular pass will contribute to a goal.”

Although a lot of the platform’s data comes from the click farm in Italy, in 2015, Brouwer set up another company, BallJames. This is a camera system that converts video into 3D data automatically, reducing the need for a click farm. “For the time being, this is not yet fully operational for us, because for BallJames we are still dependent on our own camera images and do not, for example, have cameras in stadiums in Colombia,” he said.

Deep learning technology

The deep learning technology used at BallJames is extremely advanced, said Brouwer. “The system not only has to be able to recognise who a player is and who the referee is, but also has to know, for example, which team a footballer belongs to, how and where he moves across the pitch, how he creates space and what his acceleration is like.”

This kind of information is crucial in the world of football. In the past, for example, possession of the ball or the total distance covered by a player during a match were seen as important criteria for determining success.

New insights from real data now offer more and more information, and Brouwer is convinced that this will develop even further. “However, I don’t know whether data will become a real game-changer in competitions in the next two years,” he said.

So, data allows football to be dissected more and more, but isn’t there a risk that the game will soon be analysed to death? “On the contrary, I think it’s very cool that all this is possible.” said Brouwer.

He draws a comparison with basketball, where statistics and analyses have a big impact on the game. “But in soccer, only three substitutions are allowed and 22 people still walk onto the pitch with a ball – and there’s nothing as unpredictable as a human being,” he said.

Brouwer pointed to Liverpool as a club that uses a lot of data but still plays very attractive football. “In the end, in my opinion, data can add only 1% and the other 99 % is still the emotions on the field, whether a player has slept well, how his mood is,” he said. “Those are things that can’t be captured in an algorithm. That is why I think the game isn’t going to be over-analysed, but I do think that because more and more relevant information is available, the game is going to change.”

Brouwer suggested that technology might one day produce a competition between holograms. “How cool would it be to be able to buy tickets for a World Cup game in Qatar in 2022 to see the game live in 3D at the Arena or the Grolsch Veste?” he said. “Technically, it’s possible, but not yet in real time.”

That will change in the coming years, Brouwer expects. For his own company, his dream is to help a team win the Champions League, the European Championship or the World Cup.

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