In this week’s Film Room, we provide perspective on recent news regarding:
- high stakes prediction market and sports betting litigation
- leveraging AI and data in sports
High stakes prediction market and sports betting litigation
Courts across the country are actively considering the regulatory structure applicable to prediction market companies. Sophisticated technological elements and a patchwork of state-specific gambling and sports betting laws make outcomes difficult to predict!
This detailed article by Bill King in Sports Business Journal does a great job of framing the complex legal issues at play. At bottom, the question is whether prediction market companies should be subject to the same regulatory—and tax—framework as sports betting companies. The stakes here are enormous—the article notes that Kalshi had a trading volume of about $5.8 billion last month and that its latest capital raise was priced at an assumed $11 billion valuation. In other news that exemplifies the size of the market, iGaming Business recently reported that online sports betting revenue in New York reached an all-time high of $280.6 million in November (just one state, just one month).
Leveraging AI and data in sports
Data is at the core of both sports betting company operations and related integrity measures put in place by regulators, monitors, and leagues. Enterprising sports organizations and teams are also utilizing data in various ways. For example, this December 8 article in PYMNTS.com describes ways in which leagues are deploying artificial intelligence platforms and video-based tools to “widen the funnel and allow athletes from around the world to get measured, benchmarked and considered, even if they never attended a formal trial or academy.” Such platforms can further shrink the world for recruiters, including college coaches, who can obtain actionable information from a broader pool of athletes while utilizing fewer resources.
This December 5 article from the BBC highlights the English Football Association’s use of AI in a different context. The report notes the club’s use of AI in synthesizing data and informing tactical decisions—like specific athlete approaches to penalties. The note also describes how athlete health and well-being data—like sleep, nutritional and performance information—is being incorporated to optimize athlete and team performance.
Such athlete performance data can serve as a difference-maker in the college space as well, and for the same reasons. Whose data is it? Many pro leagues account for the uses of and rights relating to athlete data in collectively bargained agreements. Conferences, institutions and student-athletes operate within a less-defined framework for athlete data, providing more flexibility for entities interested in cultivating this valuable asset.
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