Data Analytics Transforms Soccer Tactics, Led by KU Leuven Lab
Professor Jesse Davis, head of the Sports Analytics Lab at KU Leuven in Belgium, is at the forefront of a data-driven revolution in soccer. His team utilizes advanced machine-learning models and data analytics to uncover new tactical insights, influencing professional clubs' decision-making. The lab's research, which is often made openly available, helps teams evaluate rosters, assess strategies, and identify hidden tactical patterns previously unseen by traditional analysis. Their work is considered highly influential within the sport's analytics community.
The Sports Analytics Lab at KU Leuven in Belgium, led by Professor Jesse Davis, has been instrumental in a decade-long data transformation within soccer. While the research group applies machine-learning models to various sports, its most significant impact is observed on the soccer pitch.
Davis and his team employ advanced data analytics to generate findings that are changing professional clubs' strategies. Their contributions include helping teams evaluate rosters, assess strategy efficiency, and develop algorithms to identify hidden tactical patterns. Hugo Rios-Neto, data recruitment lead for Royal Sporting Club Anderlecht, describes Davis's lab as the most influential sports analytics lab in soccer.
One example of their research involves a seemingly counter-intuitive tactic: intentionally kicking the ball out of bounds near the opponent's goal. To support this, Davis's group compiled a training data set of over 1.4 million passes and approximately 60,000 throw-ins, including data from the 2022 World Cup. Using tree ensemble models, they simulated the tactic and presented their findings in a 2024 paper titled “Boot it.” The research concluded that kicking the ball out of bounds from the middle third of the pitch on the opponent’s side can lead to a goal within 10 actions.
Beyond providing specific game-day insights, Davis also makes much of his research freely available through open-source analytics tools. His academic role allows him to address complex issues, such as standardizing in-game data, which aims to simplify the analysis of game footage and facilitate the development of winning strategies.
Davis, 45, developed an interest in soccer after watching the 2002 World Cup, despite a childhood focus on basketball and American football. His doctoral studies in computer science at the University of Wisconsin–Madison involved analyzing mammography reports. He joined KU Leuven in October 2010, initially researching AI's intersection with healthcare and athletic performance. The focus shifted to the tactical and technical aspects of soccer after he hired Jan Van Haaren, an engineering student and AI enthusiast, who prompted the application of data analysis to aspects like passing, shooting, and ball progression.
(Source: MIT Technology Review)
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