Prediction market profits show 67% go to just 0.1% of traders

A new analysis shows that prediction markets are dominated by a small cohort of sophisticated traders, with just 0.1% of accounts on the Polymarket platform taking home 67% of all profits. The investigation by the Wall Street Journal reveals a stark divide between a vast number of casual users who consistently lose money and the professional traders using algorithmic strategies to secure the gains.

For most users, the reality of these markets is a far cry from the advertised promise of monetizing their knowledge. “They have no chance. Systematically,” said Michael Boss, a former professional poker player and statistician who now trades on Kalshi, in an interview with the Journal. On Kalshi, there are 2.9 unprofitable users for every profitable one, according to a company spokeswoman.

The concentration of winnings is extreme. The Journal’s analysis of 1.6 million Polymarket accounts found that less than 2,000 accounts netted a total of nearly half a billion dollars. More than 70% of all users lose money, with the least successful 10% losing an average of $4,000 each. This wealth transfer comes as total trading volume on Polymarket and Kalshi surged to $24.2 billion in April, a dramatic increase from $1.8 billion a year prior, according to data from The Block.

The findings suggest these platforms have become a new frontier for quantitative trading firms, which are deploying capital and technology to systematically extract profits from recreational users. Major firms like Susquehanna International Group and Jump Trading are now active on the platforms, with Citadel Securities confirming it is “absolutely keeping an eye” on the space. These players are turning prediction markets into a battleground similar to traditional financial markets, where retail traders often face a significant disadvantage.

The Algorithmic Arms Race

The gap between winners and losers is driven by a technological and informational arms race. Professional traders and dedicated firms are paying upwards of $200,000 a year for access to big-data streams, AI coding agents, and high-speed servers. One firm run by college students, among the top-five traders by volume on Kalshi, reportedly turned an initial $1,000 stake into seven-figure profits by executing tens of thousands of algorithmic trades per day. Michael Boss, the professional trader, modifies his bids and asks 30 times a second.

This professionalized approach stands in sharp contrast to the experience of casual traders. John Pederson, a 33-year-old former line cook, lost $41,000 on a single bet on what a celebrity would say on TV, a high-risk category known as a "mention market." After turning an initial $2,000 into $41,000, he lost it all on one wager and is now living in a homeless shelter. The Journal's analysis found that these mention markets, popular with retail users, pay out far less often than their odds imply, with returns often worse than Las Vegas slot machines.

Regulatory Scrutiny and Insider Trading

The market’s structure and the potential for misuse are drawing increased attention from regulators. The Commodity Futures Trading Commission (CFTC) has asserted its federal authority over the sites, filing lawsuits against several states attempting their own regulation. While the CFTC has defended the markets' potential for economic forecasting, it has also signaled a crackdown on illicit activities.

Concerns are mounting over insider trading. In one case, a U.S. Army Special Forces Master Sgt. was charged with making $400,000 on Polymarket by allegedly using classified information about a U.S. mission in Venezuela. In another, a staffer for the YouTube creator MrBeast was fired for using inside knowledge to bet on contest outcomes. These events have prompted bipartisan action in Congress, with the Senate voting to bar its members and staff from betting in prediction markets.

For investors, the analysis serves as a warning. While prediction markets are promoted as a democratized tool for forecasting, the data shows they function as highly efficient wealth extractors, where a small number of technologically advanced "sharks" prey on a large pool of retail "fish." The involvement of major quantitative firms like Susquehanna, which is believed to trade hundreds of millions of dollars weekly on Kalshi, solidifies this dynamic, making it a perilous environment for the average user.

This article is for informational purposes only and does not constitute investment advice.