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As soccer clubs increasingly turn to advanced analytics, a Belgian professor’s research is providing game-changing insights that are influencing strategies on and off the pitch.
Imagine tuning into the opening kickoff of a World Cup match and seeing a player intentionally send the ball all the way down the pitch and right out of bounds. To casual fans, it might seem like an odd move. But to Jesse Davis, a professor of computer science at KU Leuven in Belgium, this play is a strategic setup that could lead to a goal.
Davis heads the Sports Analytics Lab at KU Leuven, which has been at the forefront of a data renaissance in soccer for over a decade. His team uses machine learning and advanced data analytics to provide insights that are transforming how professional clubs make decisions. "His lab is the most influential sports analytics lab in soccer," says Hugo Rios-Neto, data recruitment lead for Royal Sporting Club Anderlecht in Belgium.
Davis and his researchers have developed algorithms that uncover hidden tactical patterns, helping teams better evaluate their rosters and assess strategy efficiency. One notable finding is the value of kicking the ball out of bounds near the opponent's goal-a move that has gained traction in top leagues over recent years.
To make a statistical case for this counterintuitive play, Davis’s team built a training data set comprising over 1.4 million passes and some 60,000 throw-ins, partly from the 2022 World Cup. Using tree ensemble models, they simulated the tactic. The results, published in a 2024 paper titled "Boot it," showed that when the ball is in the middle third of the pitch, kicking it out of bounds on the opponent's side can position the team within 10 actions (such as passes and dribbles) of scoring a goal. In a game with over 1,500 actions per match and limited scoring opportunities, this can be a significant advantage.

The lab’s research extends beyond tactical insights. Davis also focuses on standardizing in-game data, making it easier to analyze game footage and derive meaningful statistics. This work is crucial as many clubs now have their own internal data teams, seeking a competitive edge through analytics.
Davis's contributions to sports analytics are not just theoretical; they are being applied by top-tier soccer clubs around the world. By providing freely available open-source tools and tackling complex problems, his lab continues to push the boundaries of what is possible in the realm of data-driven decision-making.
As the sport evolves, the integration of advanced analytics will likely become even more prevalent. For investors and stakeholders in the soccer industry, staying informed about these developments can offer valuable insights into team performance and market trends. The future of soccer is being shaped by data, and Davis’s work is at the heart of this transformation.
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Original Sources
Inside soccer’s data renaissance
↗ https://www.technologyreview.com/2026/06/11/1138506/inside-soccer-data-renaissance-jesse-davis
Inside soccer's data renaissance - MIT Technology Review
↗ https://www.technologyreview.com/2026/06/11/1138506/inside-soccer-data-renaissance-jesse-davis/amp
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Marcus began tracking AI's market implications in 2016, noticing AI-related patent filings accelerating ahead of earnings upgrades before most of the sell-side had caught on. A former fixed-income quantitative analyst, he spent two decades building models that priced risk across emerging markets before pivoting to cover the economic impact of AI full-time. His writing translates opaque technical developments into clear risk/reward terms — and he's rarely diplomatic about the gap between AI valuations and underlying fundamentals. He believes most market participants still underestimate AI's long-run deflationary effect on knowledge work.
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15 June 2026
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