FIFA World Cup AI: The data workers powering football analytics - Rest of World

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By Rina Chandran and Michael Beltran

23 June 2026

Football increasingly relies on advanced data analytics and AI tools to power team tactics, broadcasting, and the sports betting industry.<br>A global workforce of human annotators manually logs thousands of match actions to generate structured data and train computer vision algorithms.<br>With growing U.S. investment, the multibillion-dollar industry relies heavily on these behind-the-scenes workers.

The current edition of the FIFA World Cup features a sensor-fitted ball, real-time tracking, artificial intelligence-assisted offside calls, and an AI assistant for each of the 48 teams. Behind these innovations are data workers in countries including India, Cambodia, and the Philippines, who are essential for the many AI tools in play.

Football embraced data analytics more than two decades ago, and nearly every national team and major club now uses it for recruitment, training, game tactics, injury prevention, player management, and more. The data analytics also feed broadcasters, and the video-game and betting industries.

Teams today may have in-house data analysts and scientists with doctorates in physics, mathematics, or machine learning and AI experience; data vendors whose workers specialize in player tracking and turning raw video into data; and video platforms that record and tag matches, Rafael Grohmann, assistant professor of media studies at the University of Toronto, told Rest of World.

“Football has been relying on this kind of work far longer than the current AI excitement,” he said. “The workers in data value chains are essential to football … and the data value chain has a geography: The high-value data analytic work is located in a handful of wealthy centers, while the data annotation is concentrated in cities across Eastern Europe, Africa, South Asia, and Southeast Asia.”

Side gig for players

The data annotation workers — who are often football players themselves, or have extensive knowledge of the game — are largely in cities such as Manila, Cairo, Chennai, and Ternopil. They include independent contractors hired match by match, and annotators who spend three to four hours on a single game, turning every pass, tackle, and shot into structured data, said Grohmann, who is mapping the workforce in football’s data value chains.

Data work is a popular side gig for many Philippine football league players looking for additional income, according to a player who annotated data for about a year at Packing Sports, the Manila-based unit of German data analysis company Impect. He asked not to be named, as he is not authorized to speak to the media.

Greater American investment “will likely translate into greater investment in data analytics.” Scott Powers, Rice University

The player told Rest of World he watched European league matches and tagged passes, shots, tackles, and other player actions. During major tournaments like the FIFA World Cup and the UEFA European Championship, “the workload is heavier because of higher demand for fast data from teams, analysts, and the media,” he said.

As a player, the tasks also gave him a deeper understanding of the game, he said. “My work helps me notice tactical details and player movements that many people might miss,” he said. “It also makes watching football more interesting.”

Follow the money

Football is big business. The top teams in the English Premier League, Italy’s Serie A, Germany’s Bundesliga, and Spain’s La Liga generate billions of dollars in revenue. American fans — and investors — are increasingly taking an interest.

More than half the clubs in the Premier League are majority-owned by wealthy American individuals or U.S.-based firms. Americans and Canadians control nearly half the Serie A teams, as well as a handful of clubs in La Liga, according to the Forbes ranking of the world’s most valuable football teams. U.S. investors are also buying up teams in lower divisions, and in countries such as Mexico.

Greater American investment “will likely translate into greater investment in data analytics,” Scott Powers, assistant professor of sport analytics at Rice University, told Rest of World. “After all, the Moneyball revolution came from the U.S.,” he said, referring to the book and movie that detail the Oakland Athletics’ effective use of data analytics to build a competitive baseball team on a small budget — a strategy that was quickly adopted by other sports teams.

Today, a small number of companies control the data most football clubs rely on. Advanced technologies enable data generation in real time through a combination of human annotation, computer vision, and AI modeling. Data workers can capture up to 3,000 actions per match.

There is now greater emphasis on the analysis of player tracking data, said Powers, a former data scientist at sports data firm Zelus...