Prediction Market Users Lose More Than Sports Bettors, New Data Reveals

As courts weigh whether prediction markets are financial instruments or gambling products, new and earlier data from Citizens data provide insight into consumer outcomes and whether users are at a disadvantage on these platforms compared to traditional sportsbooks.

From Cannibalization Fears to Consumer Outcomes

At the start of 2026, the debate centered on market impact. A January Citizens report suggested mid-single-digit cannibalization, with roughly 5% of legal sportsbook handle shifting to prediction markets.

At the time, the report noted that companies like DraftKings, FanDuel, and Fanatics, which all launched prediction market products, would not be impacted. Operators that have not entered the sector would face greater downside risk.

Both Flutter and DraftKings CEOs said during their fourth-quarter earnings calls that prediction markets have not affected sports betting. Still, both companies reported results that fell short of expectations.

The impact narrative now looks incomplete. As newer data has emerged, the question shifts from how much is going to prediction markets to what is happening to users there.

Prediction Market Users See Greater Losses

The January report found that prediction market users experienced higher losses than users of other gambling products.

According to the analysis, prediction market users experienced a median loss of 7%, compared to 1% across other gambling products.

At the extremes:

• Bottom 25%: -28% vs -11% elsewhere
• Bottom 10%: -44% vs -22%

The report noted that sharper bettors were consistently taking advantage of retail players — a dynamic more pronounced than in traditional betting.

A newer March report — which tracks user activity from July 2025 onward — confirms that this is a persistent trend. It found that the median loss for prediction markets now stood at 8%, while for sportsbooks it was 5%.

However, the more telling insight comes from cohort segmentation. Users of prediction markets who traded more than $500,000 had a median ROI of 2.6%. Meanwhile, even the highest-volume sportsbook users remained unprofitable at approximately -0.6%.

Below the top tier, however, returns deteriorate sharply:

• $100K–$500K: -1.5% ROI
• $10K–$100K: -2.4% ROI
• $1K–$10K: -7.2% ROI
• Sub-$100 users: losses exceeding -25% to -30%

The report also highlights that ROI declines almost linearly as wallet size decreases — a clear indication that less experienced, lower-volume users are disproportionately bearing losses.

By contrast, sportsbook users show a similar downward trend by volume, but no cohort achieves profitability. That reinforces a key structural difference between the two ecosystems.

Across users that are active on both sportsbooks and prediction markets, the disparity becomes more pronounced:

• Sportsbooks: +1% ROI
• Prediction markets: -6% ROI

The report concludes that crossover users are lower-quality customers for sportsbooks and simultaneously underperformers in prediction markets.

Taken together, the data suggest that prediction market losses are concentrated among less informed participants, with high-volume, informed users being more profitable than on sportsbooks.

Efficiency or Information Asymmetry?

That gap has raised a more fundamental question: what explains the performance difference between informed and retail participants?

Recent events in which individual users have generated significant profits (in some cases reportedly reaching six figures) have raised questions about potential insider trading in prediction markets. According to one Truist survey, even participants in these markets believe insider trading may be occurring.

State regulators and lawmakers at both the state and federal levels are increasingly focusing on insider trading and market manipulation in prediction markets amid concerns that “informed” traders could profit from non-public or difficult-to-access information.

Additionally, sports leagues and collegiate organizations, such as the NFL and NCAA, have urged prediction markets to halt certain contracts they say are easily manipulable. They’ve warned that certain markets could be influenced or even rigged in advance.

Taken together, these developments reinforce a broader concern: that performance gaps in prediction markets may not be driven solely by skill, but also by structural advantages in information and execution.

Bigger Bets, Sharper Competition

The January report found average prediction market bets of $185, compared to $55 on sportsbooks.

Higher bet sizes increase volatility and accelerate losses — particularly in a system where users are betting against each other rather than a house.

Prediction markets replace the traditional house edge with market-driven competition, where skilled participants act as liquidity providers and retail users absorb pricing inefficiencies.

A Crowded Market and a Familiar Outcome

The March report notes that the prediction market sector is rapidly expanding. More than two dozen platforms have licenses already or are seeking approval.

However, it suggests that many of these platforms may be short-lived. The report draws comparisons to the online sports betting sector, where 33 out of 68 operators that have entered the U.S. since 2018 have already shut down. Meanwhile, the eight leading operators control 98% of the market.

Prediction markets may follow a similar path, particularly as new entrants compete for a limited pool of users.

Implications for the Regulatory Debate

For regulators, the immediate question remains classification: are prediction markets derivatives or gambling products?

If the courts rule or Congress clarifies through legislation that they fall under federal oversight, data like the Citizens reports could introduce a new dimension, pointing to consumer outcomes.

If prediction markets consistently produce larger losses for retail users and greater advantages for informed participants, the debate may shift toward consumer protection.

The Bottom Line

Prediction markets are not simply a new betting product — they represent a structural shift.

Early data suggested they were taking share from sportsbooks. New data suggests they may also be taking more from bettors.

As courts, regulators, and operators grapple with the space, that reality may prove just as important as the platforms’ ultimately definition.