Sports Betting: Risks & Ripple Effects Teach-Out

University of Michigan professors Chris Brooks and Tom Finholt trace the rise of sports analytics and consider how machine learning, wearable technology, and sports betting are changing the game for teams and fans.

Takeaways: Evolution of Data Analytics

We have prepared a list of key points from the Evolution of Data Analytics and Online Sports Betting interview for your reference:

1. Sports analytics has shifted from elite expertise to mass participation, without equal access. Sports analytics long predates legalization, but the 2018 Supreme Court decision dramatically accelerated its spread. What was once the domain of professional teams and analysts is now widely accessible to the public through hundreds of analytics platforms aimed at bettors. However, this democratization is incomplete. While bettors can access surface-level statistics and models, sportsbooks retain access to richer, faster, and proprietary data streams. This creates a structural imbalance where bettors are encouraged to believe analytics can help them “beat the house,” even though the house consistently holds a deeper informational advantage.

2. Machine learning and predictive models now shape betting markets—but data quality determines power. Modern sportsbooks rely heavily on machine learning models trained on massive historical datasets to forecast outcomes, set odds, and manage risk. These models are only as good as the data they ingest—and sportsbooks control the most comprehensive, high-frequency, and real-time datasets. While emerging tools like large language models may further lower technical barriers to analytics, unequal data access means predictive sophistication does not translate into equal opportunity for bettors.

3. Wearable and biometric technologies raise new ethical and integrity concerns. Athlete monitoring has expanded rapidly through wearables that track a variety of parameters, including physical load, sleep, hydration, and performance metrics. Future developments may include ingestible or implantable sensors capable of real-time internal analysis. While these technologies can improve training and injury prevention, they also raise serious concerns about privacy, consent, data ownership, and potential manipulation—especially when athlete-level data intersects with betting markets and commercial incentives.

4. Data now flows in multiple directions, blurring surveillance, protection, and control. Sportsbooks collect extensive bettor data—such as geolocation, betting frequency, timing, and wager types—largely for regulatory compliance and integrity monitoring. Increasingly, this data is shared with organizations like the NCAA to detect match-fixing, insider betting, or suspicious patterns. While this can enhance integrity, it also normalizes continuous surveillance of bettors and athletes, raising questions about transparency, proportionality, and who ultimately benefits from data sharing.

5. Analytics-driven betting reshapes how competition is perceived and experienced. The proliferation of prop bets and micro-betting introduces countless points of potential manipulation and fundamentally alters how fans interpret sport. Outcomes once celebrated as improbable upsets may now be met with suspicion. At the same time, betting has become culturally normalized yet remains socially hidden, particularly among young people, reinforcing stigma and discouraging help-seeking. As analytics extend into officiating, youth sports, and fan engagement, trust in both sport and technology becomes increasingly fragile.

Reflection Questions

In your daily life, you may have one or more than one of the following roles. Think about the questions that we have posed here. How can you use the Evolution of Data Analytics and Online Sports Betting interview to respond to these questions?

• Public health professionals:
  • How might the data asymmetry between sportsbooks and individual bettors inform public health messaging about the realistic odds of “winning” through sports betting?
• Young adult casual bettors:
  • How might limited understanding of betting algorithms and personalized promotions affect your ability to make informed decisions or recognize risk in online sports betting?
  • When sportsbooks have access to better and faster data than you do, what does that tell you about who is likely to come out ahead over time?
  • If betting apps can track your location and share that information with sports organizations, what other personal data might they be collecting about your betting behavior?
• Athlete:
  • What concerns do you have about how your performance data might be collected, shared, or monetized within betting and media ecosystems?
• High school athletics professional:
  • As analytics tools become more accessible, how might you help student-athletes understand that the sophisticated systems sportsbooks use are designed to ensure the house wins?
• Educator or higher education administrator:
  • How can institutions build data literacy and protective environments that help students understand the hidden influence of analytics in sports betting platforms?
• Parent or guardian:
  • What conversations might you have with your teen about the hidden nature of sports betting and why someone struggling might not feel comfortable asking for help?

Additional Resources

1. Have the Nerds Ruined Basketball?
2. NCAA Reaches Deal with Sportsbooks for Data, Logos, Reuters.