PART 4 — Biometric Data, Wearables & AI Performance Analytics: Legal Risks and Athlete Protection

Athletes today are using more technology than ever to track performance, prevent injury, and optimize training. From smart watches to AI-driven wearable devices, your biometric and performance data are constantly being collected, analyzed, and stored. But in the age of AI, this data is potentially valuable intellectual property and a source of legal exposure.

1. The Rise of Biometric and Performance Data

Wearables and training platforms collect a wide range of athlete data, including:

• Heart rate, blood oxygen, and sleep patterns

• Motion tracking and biomechanics

• GPS and location data

• Stress and recovery metrics

AI systems use this data to create predictive performance models, simulate injury risks, and even generate recommendations for contract valuation or scouting reports.

2. Legal Risks for Athletes

Even though this data is generated from your body and your performance, several legal questions arise:

• Ownership: Who owns the data collected by wearables or team-provided devices—the athlete, the team, or the platform?

• Consent: Are athletes fully informed about how their data will be used, shared, or sold?

• Privacy: Unauthorized sharing of biometric data may violate state privacy laws, such as Illinois’ Biometric Information Privacy Act (BIPA). See Illinois General Assembly, Biometric Information Privacy Act:

• NIL and likeness intersections: AI models can combine biometric data with video and images to simulate or generate content featuring the athlete. The legal status of these “digital twins” remains uncertain.

These gaps leave athletes exposed to potential misuse of their data for commercial purposes without compensation or control.

3. Documented Incidents and Expert Warnings

• The FBI has noted that cyber attacks targeting biometric and health data are rising, particularly in sectors that include elite sports teams.

• Researchers have demonstrated that publicly available motion and performance data could be used to train AI models to predict athlete movements with high accuracy, showing that even non-sensitive data can be exploited. See Artificial intelligence in sport: A narrative review of applications, challenges and future trends https://www.tandfonline.com/doi/full/10.1080/02640414.2025.2518694

These examples show that even seemingly routine training data can be legally and commercially consequential.

4. Mitigation and Legal Protections

Athletes and their teams can take steps to reduce exposure:

• Data Ownership Agreements: Clarify in writing who owns wearable and performance data.

• Consent Protocols: Ensure all data collection is transparent and includes clear, written consent for any AI use.

• Secure Storage: Use encrypted devices and platforms with strong privacy policies.

• Monitoring & Auditing: Regularly review who accesses your data and for what purposes.

• Legal Review: Include language in contracts with teams, brands, and AI platforms addressing the use of biometric data, AI simulations, and digital twins.

By combining operational safeguards with contractual protections, athletes can maintain control over their most sensitive performance information.

5. Why This Matters

As AI adoption in sports accelerates, your biometric data is increasingly a tradeable asset. Teams, brands, and even third-party developers may want to use it for predictive modeling, endorsements, or synthetic content. Without clear legal protections, athletes risk:

• Loss of control over personal performance data

• Unauthorized monetization of their likeness

• Breach of privacy laws

• Potential misuse affecting contracts or NIL agreements

Next in the Series

Part 5 will explore AI in Betting, Game Integrity, and Behavioral Manipulation—showing how predictive AI models and synthetic content can impact fair play, contract negotiations, and even athlete reputations.

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