Soccer’s Big Data Dilemma: Who Owns the Data Behind the Beautiful Game?

Behind the scenes of the 2026 FIFA World Cup, a match based in data is racking up points. It is estimated that the tournament's 104 matches will generate more than 90 petabytes of data, representing a staggering 45-fold increase over the volume produced during the 2022 games. So who owns all that data? The answer sits at the intersection of intellectual property (IP) law, contractual rights, privacy and biometric regulations, antitrust law, and emerging AI governance frameworks. As data becomes one of soccer's most valuable assets, stakeholders throughout the ecosystem need to confront increasingly complex legal and commercial challenges.

Key Takeaways

• Sports data has become one of the industry's most valuable commercial assets, but legal rights to that data are often determined by contract rather than ownership.
• Wearable technologies, AI-assisted analytics, and biometric data are creating new IP, privacy, and governance challenges across the sports ecosystem.
• Clubs, leagues, technology providers, and athletes should proactively define rights to collect, use, share, and commercialize sports data.
• As major sporting events become increasingly data driven, organizations should review their data governance frameworks alongside their technology and commercial agreements.

The Expanding Universe of Soccer Data

Data has become attached to modern professional soccer, quite literally. Elite clubs deploy wearable technologies that measure player workload, recovery, and physiological performance. AI-assisted scouting platforms analyze thousands of matches to identify transfer targets. Computer vision systems track player movement in real time, anchored by connected match equipment like the official 2026 match ball, which contains an inertial measurement unit sensor transmitting telemetry 500 times per second. Broadcasters, betting companies, fantasy sports operators, and technology vendors increasingly rely on the vast datasets generated during training sessions and matches.

This information ecosystem generates multiple categories of data, each with distinct legal considerations, such as the following:

• Match-event data, including passes, shots, tackles, possession statistics, and expected goals metrics
• Tracking data generated through optical tracking systems and GPS devices
• Wearable-device data measuring heart rate, acceleration, fatigue, sleep patterns, hydration, and recovery
• Biometric data consisting of sensitive physiological or health-related information
• Video and image data used to train AI-powered analytics platforms
• Fan engagement and betting-related data generated through digital ticketing, fantasy sports, streaming applications, and other digital platforms

This commercialization of these datasets is reflected in the growing ecosystem of sports data providers, including Opta, StatsBomb, Wyscout, Catapult, and others that supply analytics to clubs, leagues, scouts, broadcasters, and media organizations.

However, the legal rights associated with these datasets often remain fragmented and uncertain.

The Ownership Question: A Bundle of Rights Rather Than a Single Answer

Unlike tangible property, data itself is not universally recognized as an owned asset under most legal systems. Instead, stakeholders rely on a combination of legal protections, including trade secret law, copyright, database rights in certain jurisdictions, and, perhaps most importantly, contractual agreements.

For example, a single sprint by a World Cup player could generate data that implicates multiple parties:

• The player whose body generated the information
• The club or national team that deployed the technology
• The wearable-device manufacturer
• The analytics provider processing the data
• The competition organizer
• The broadcaster capturing the event

As a result, disputes often turn less on "ownership" than on contractual allocation of rights to access, use, license, and commercialize the data.

A partnership between FIFPRO and Sports Data Lab illustrates one emerging approach by enabling players to store, manage, and monetize their own performance data while establishing permissions and revenue-sharing arrangements with third parties.

For clubs and federations, carefully drafted agreements with players, technology providers, and analytics companies are increasingly the primary mechanism for allocating these rights.

Wearables and Biometric Data: Privacy Risks Move to the Forefront

Commonly used wearable technologies such as GPS trackers, smart garments, heart-rate monitors, and recovery platforms generate some of the most legally sensitive forms of sports data.

Many jurisdictions classify biometric and health-related information as protected personal data subject to heightened regulatory requirements. Under the European Union's General Data Protection Regulation (GDPR), for example, player data may qualify as special-category personal data, with similar protections emerging in other jurisdictions.

Organizations should consider the following:

• Whether player consent is truly voluntary in an employment context
• How long biometric data may be retained
• Whether data may be shared with third-party analytics providers
• The extent to which players may access, correct, or delete their information
• How to manage cross-border data transfers involving multinational clubs and competitions

International tournaments magnify these questions of privacy because player data routinely moves across multiple jurisdictions.

To address these challenges, player unions and governing bodies are increasingly pursuing common standards. The FIFPRO Charter of Player Data Rights, developed in collaboration with FIFA, establishes principles that recognize performance metrics as personal data while promoting rights such as access, portability, and greater control over how player data is processed.

AI-Assisted Scouting and Coaching: Who Owns the Insights?

AI is rapidly transforming talent identification and tactical analysis. Modern scouting platforms leverage machine learning models trained on extensive collections of match footage, event data, and player tracking information. Coaches increasingly use AI-powered tools to analyze opponents, generate tactical recommendations, and model substitutions and formations.

These developments raise several important legal questions:

• Who owns AI-generated outputs produced through proprietary analytics platforms?
• What rights exist in the underlying data used to train AI models?
• Can proprietary algorithms themselves become protectable competitive assets?

Trade secret law often provides the strongest protection for proprietary algorithmic models, but maintaining that protection requires robust confidentiality measures and carefully structured vendor relationships. Patent protection may be available for certain AI-enabled technologies, although recent decisions such as Recentive Analytics, Inc. v. Fox Corp. illustrate the continuing challenges of obtaining patent protection for machine learning innovations under US patent eligibility standards. Under current law, AI-generated outputs are generally not protectable copyrights because they do not contain human authorship. The extent to which the outputs must be adjusted or revised by human authors to be eligible for copyright protection is still being litigated.

As AI adoption accelerates throughout professional soccer, these questions are likely to become central issues in technology procurement and licensing agreements.

Commercializing Match Data

Historically, media rights have been the financial engine of global sports. Increasingly, however, data rights are emerging as a distinct and valuable asset class.

Official match statistics, tracking feeds, and real-time event data are licensed to broadcasters, fantasy sports operators, betting companies, media platforms, and analytics providers. Every pass, shot, and movement on the field may be captured, processed, packaged, and monetized through multiple downstream products.

This commercialization raises important legal questions regarding the below:

• The extent to which live sports data is protectable
• Contractual restrictions on data scraping and unauthorized collection
• Competition and antitrust issues arising from exclusive data licensing arrangements
• The relationship between official data providers and independent analytics companies

These tensions are reflected in initiatives such as Project Red Card, through which hundreds of professional players in the United Kingdom have challenged the commercial exploitation of performance data without consent or compensation. By framing performance metrics as personal data rather than unprotected public facts, Project Red Card illustrates the increasingly blurred boundaries between privacy rights and traditional IP principles. Furthermore, in the United States, players may attempt to argue that their right of publicity protections under state law should include their performance data as part of their commercial persona.

Protecting Sports Analytics

Traditional IP rights remain important tools for protecting investments in sports technology, although each has limitations.

Patent protection may be available for certain wearable technologies, sensor systems, and AI-enabled innovations, while copyright protects software, visualizations, and audiovisual content, as well as the arrangement and selection of materials contained in databases rather than the underlying facts or figures. Trade secret law often provides the strongest protection for proprietary scouting methodologies, performance models, and injury prediction systems, provided organizations maintain appropriate confidentiality measures.

For sports technology companies, effective protection increasingly depends on coordinated patent, copyright, trade secret, right of publicity and privacy, and contractual strategies rather than reliance on any single form of intellectual property.

Looking Ahead

The legal framework governing sports data continues to evolve rapidly. Clubs, leagues, federations, broadcasters, technology providers, and athletes are all seeking greater clarity regarding data access, ownership, portability, and commercialization, while regulators continue expanding oversight of biometric information, AI systems, and data-driven decision-making.

The risks of inadequate governance are already apparent. Spain's Data Protection Agency imposed a €250,000 fine on LaLiga after determining that its mobile application's use of smartphone microphones and location data to identify unauthorized commercial broadcasts violated core GDPR principles of transparency and consent. The enforcement action serves as a reminder that aggressive efforts to protect valuable data assets can themselves create significant regulatory exposure.

Conclusion

The 2026 FIFA World Cup highlights both the opportunities and challenges of this transformation. Every match generates enormous volumes of information that can improve performance, enhance fan engagement, and create new revenue streams. Yet the same data can also create significant legal exposure if rights and responsibilities are not clearly defined.

The future of soccer may still be decided on the field. Increasingly, however, competitive advantage and commercial value will also depend on how effectively organizations govern, protect, and commercialize the data generated behind the game. Organizations that establish clear contractual frameworks, implement thoughtful data governance policies, and anticipate evolving regulatory requirements will be best positioned to capitalize on one of sport's fastest-growing assets.