Insights Blog

DataXpresso blog: how integrated is AI in the beautiful game?

AI in football

This week, DataXpresso hosts Eva and Helena welcome Pascal Bauer to the podcast. He is the Manager for Loading...Data Science and Loading...Machine Learning at the DFB Academy, the place where innovation starts in German football. This blog shines a light on how prevalent the technology is and the way it’s accelerating data analytics in football.

Listen to DataXpresso episode 18 here.

Data analytics in football has come a long way from the days when a manager would peer from the sideline jotting notes and observations in a little black book. Today, even teams like Stockport, in the fifth tier of English football, are able to access pro-level tools used by the likes of Barcelona, Villareal and Nice.

There’s been an explosion of sports tech companies offering analytics services, so clubs from the lower leagues to the global stage are spoilt for choice. We recently spoke with Exasol partner Stats Perform about its offering, but there’s also the likes of Acronis, Metrica, IBM’s Watson and many more.

Among the analytics providers, you’ll find video tools that zero-in on the mechanics of the game, such as how players act in set-piece scenarios or what they do upon receiving the ball. There’s those using statistical analysis to comb through huge volumes of information – from sensors to self-reporting surveys – hunting for patterns and tell-tale signs of, say, player stress or fatigue. Beyond that, there’s a plethora of fan engagement tools, scout-assistance apps and nutrition analysis platforms.  

The next frontier

Now, AI is slowly being introduced to the sport, as clubs look to gain an advantage by going beyond statistical analysis and delving into predictive models and even Loading...machine learning.

This is the realm of Pascal Bauer, who heads up Loading...Data Science and Loading...Machine Learning at the DFB Academy, this week’s guest on DataXpresso. Listen to the episode to hear how the Academy is pioneering the use of Loading...machine learning in football or keep reading for examples of some of the businesses using AI to help clubs and national teams get ahead. 

“We are a long way from where a machine makes decisions about what formation to use, what player to sign and who to pick – and we shouldn’t aim to get there anyway.”

Richard Battle Founder, Left Field Football Consulting

SciSports

Dutch business SciSports has three core offerings. Its player recruitment tool provides statistical insights on more than 180,000 players across 250 leagues and 3,700 clubs. It also offers a range of data delivery APIs that easily be integrated with BI-platforms like Tableau and Power BI to create easy to digest dashboards and interfaces for a whole range of information. But it’s SciSports’ AI-driven match and player analysis software that allows clubs to combine multiple tracking and event data streams with custom parameters to create what it calls “AI-driven actionable insights”. Learn more here. 

Scoutastic

Working with a number of smaller clubs in Germany, Scoutastic – a subdivision of Just Add Ai – is bringing AI to player recruitment. It uses Loading...artificial intelligence to automate the generation of forward-looking performance data and development indicators from video recordings of training sessions, matches and TV broadcasting. This has the potential to save scouts a huge amount of time. The platform uses similar technology to automatically create match reports and the tagging of points of interest – even in club-specific terminology. Read about the technology here.

Olocip 

Working across basketball, tennis and football, Olocip has a suite of solutions for clubs to use on and off the pitch. It uses Loading...predictive analytics to help forecast a range of data points around fan engagement, sponsorship and marketing. Olocip also offers pre-match analysis and real-time in-game analysis backed by Loading...artificial intelligence algorithms. Its injury prevention tool also uses both predictive and prescriptive AI to analyze player data for health indicators, performance mapping and signs of fatigue. Finally, Olocip’s scouting tools are able to predict future performance gains and season-planning assistance. Check out the tools here.

Noteworthy articles & books

Football was slow to embrace data. Now AI is eating the beautiful game

“Most of the top groups have dedicated teams, they have data scientists. But we were surprised by how rudimentary it still is, and that only a few clubs are actually excelling in this area”, says Jan-Jaap Jager from Acronis. The technology company provides storage solutions for video footage and is working with clubs on using this data more extensively via AI solutions to gain insights that can improve performance.

Can AI help Leatherhead FC raise their game?

This video shows how IBM Watson’s AI capabilities are used by Leatherhead FC to help them improve their game through pattern analysis as well as performance analysis. Identifying weaknesses of the club and addressing them, while also finding the strengths and how to build those out further is important for the grassroots football club in their journey to higher leagues.

Metrica Sports: Meet the tech company which works with FC Barcelona, giving away its football analytics software to amateurs

When it comes to data analytics in football, clubs below the top level struggle with the resources that allow them to obtain and use data effectively to improve their game and their chances to move up the ranks. Metrica Sports has given amateur sports teams access to the same tools as the top teams, albeit with less automation, through their free version. 

Book tip: Football Hackers: The Science and Art of a Data Revolution

Football’s data revolution has only just begun. The arrival of advanced metrics and detailed analysis is already reshaping the modern game. We can now fully assess player performance, analyse the role of luck and measure what really leads to victory. There is no turning back.

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