What Will Football of the Future Look Like?

Statistical Modelling, Artificial Intelligence and Particle Physics: What Will Football of the Future Look Like?

Our team recently sat down with Mark Thompson from The Set Pieces to discuss how technology—AI in particular—is transforming soccer/football and what that means for the future of the sport. They chatted about the kinds of insights we provide here at SPORTLOGiQ, event data (passes and shots) as well as tracking data (the movement of players), and how teams are using that information to improve their game. They also touched on the types of actionable insights coaches and players are looking for, such as pressing, which is an important part of the modern football game.

Canadian company SPORTLOGiQ have used a similar approach. Pressing is an important part of the modern game and feedback from coaches and analysts helped SPORTLOGiQ refine their definitions.

 

“If you only look at movement towards the ball-carrier then you might have people too far away,” says Daniel Nahmias-Léonard, listing situations that could fall in the grey area between ‘pressing’ and ‘not pressing’.

“You might have a centre-back stepping up to close down the space to a forward who receives the ball with their back to the goal. Or containment, where you’re going to get forward and then stop and kind of leave the ball-carrier. If it doesn’t speak the football language then it’s not doing the job properly.”

The company, began life in another sport – hockey – before recently moving to football.

“I was just very clear about ‘I don’t care what technology exists today’,” says co-founder Craig Buntin, a former Olympic figure skater. “’I don’t care what’s possible [or] what’s not possible, let’s talk about what needs to exist in the long run and let’s put together a long-term plan to invest in research, to bring in as many researchers as we need to actually build that.”

Build it they did. SPORTLOGiQ now have a system that can gather ‘event data’ (think passes and shots in football) as well as ‘tracking data’ (the movement of players) from video. And it doesn’t stop there. The model can recognize the position of players’ hands, feet, torsos and heads at any stage of the match.

“We’re really only starting to skim the surface of what we can actually do,” says Buntin. “But at the end of the day, what we have built is essentially a 3D motion capture system for the entire pitch at any time.”

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