Are Prediction Markets Just Restarting Sports Betting’s Regulatory Process?

In the US, regulators are edging toward formal oversight of event-based trading, but the debate is starting to mirror one that sports betting has already spent decades working through.

From insider information and market manipulation to protection from harm, several papers have hit the headlines this week, creating a flurry of excitement over this new frontier.

A Clean Framework for a Messy Problem

A working paper by Eliezer Mishory sets out a structured approach to prediction market regulation. The core argument is that ‘insider trading’ is not all the same.

Instead, Mishory separates two distinct risks:

• Informational asymmetry (who knows what)
• Event manipulation (who can influence the outcome)

From there, he builds a hierarchy of what should be allowed, disclosed, or prohibited, distinguishing between stolen information, relationship-based access, and legitimate analytical edge.

It’s a logical framework, and one that reflects how financial markets already operate, but it assumes those distinctions can be identified both clearly and quickly.

The Problem Sports Betting Already Faced

In response to Mishory’s paper, industry veteran Jon Russell argued that defining categories of behaviour is only half the job. The harder part is finding them in the first place.

Markets don’t label trades as ‘insider’ or ‘legitimate.’ Instead, they show price movements, and volume spikes which have to be interpreted - often imperfectly. That inference problem is exactly what sports betting has spent years addressing through monitoring systems, data partnerships, and integrity frameworks.

Prediction markets are still building that infrastructure.

The concern isn’t so much that bad actors exist, it’s that the systems needed to detect them at scale might not even exist yet.

The Science Paper that Changes the Scope

A new peer-reviewed article published in Science pushes the conversation beyond enforcement altogether.

The authors here argue that modern prediction markets are no longer comparable to their academic predecessors. Instead of small, controlled forecasting environments, today’s platforms are global, continuous, and increasingly gamified. They’re processing billions in weekly transactions and that change has introduced three broader risks.

• Democratic manipulation: Where thin liquidity allows relatively small trades to shift perceived probabilities and with that influence public opinion.
• Gambling-like design: With engagement mechanics such as streak rewards, prompts, and continuous event streams.
• Public health impact: As participation scales without the safeguards typically associated with regulated betting environments.

Crucially, these platforms are often framed as ‘forecasting tools’ rather than gambling products. This sort of distinction can shape how users understand their own behaviour.

The Consensus

While the papers all discuss the same core subject, they come at it from different angles. We’ve got a framework for regulation, the challenge of enforcing the rules, and whether focusing on market integrity misses the most important part of the picture entirely.

For regulators, the key question is whether this is a familiar cycle or something more complex. If it’s familiar, we can use lessons from sports betting to make positive changes, but if it isn’t, then defining the rules will likely be a lot easier than implementing them.