Written by: Caitlin Ostroff, Katherine Long, and Neil Mehta, WSJ

Translated by: AididiaoJP, Foresight News

33-year-old John Pederson is currently unable to work; the former Outback Steakhouse chef is recovering from a car accident, and his savings are quickly running out. The prediction market platform Kalshi may quickly solve his problems, so he took out a variable rate loan and started betting.

Initially, everything went smoothly. Pederson turned approximately $2,000 into nearly $8,000 by betting on the daily snowfall in Detroit (his city). He then invested the funds in sports event trading, using AI-assisted strategies, and according to a review of his account records by The Wall Street Journal, it eventually reached $41,000.

Then he made his boldest bet yet: wagering the entire $41,000 that a certain celebrity would say a specific word on television, which ended up costing him everything.

Pederson is not the only one walking away empty-handed from a market where “anything can be bet on,” covering various topics including sports, celebrities, and news.

Kalshi and its competitor Polymarket promote themselves as tools that can change the fortunes of ordinary people—implying that everyone has a fair opportunity to make a fortune. “I almost couldn’t pay my rent, but through predictions on Kalshi, I made two years’ worth of rent,” a woman excitedly said in a TikTok advertisement for Kalshi.

But for most users, the reality is quite different.

On the contrary, according to an analysis of platform data and interviews with traders by The Wall Street Journal, regular traders are consistently losing money, while a small group of experienced professional players—including trading firms with vast data resources—are taking their funds.

The Wall Street Journal found that on Polymarket, 67% of the profits flow to just 0.1% of accounts. This means that fewer than 2,000 accounts have netted nearly $500 million altogether. The Wall Street Journal analyzed 1.6 million accounts trading on Polymarket since November 2022. The platform has at least 2.3 million total accounts.

Kalshi is similar, with far more losers than winners. Spokesperson Elizabeth Diana stated that based on data from the past month, for every profitable user, there are 2.9 losing users. She said this ratio may change as the platform grows. The company does not publicly release comprehensive user profit data nor disclose total user numbers.

According to data from the analytics firm The Block, the total trading volume on both platforms skyrocketed to $24.2 billion in April, up from just $1.8 billion a year ago.

Supporters claim these markets are not gambling, but rather a way to leverage collective intelligence to accurately predict future events. Research from the Federal Reserve shows that Kalshi is an effective tool for predicting economic trends.

Traders are paying for large data streams provided by third parties to gain an advantage. Computers use data and algorithms to predict price movements and manage risk far more quickly than any human. Professional players also leverage economies of scale to engage in frequent, strategic trading—sometimes executing tens of thousands of trades in a single day—and make profits from tiny fluctuations, requiring rare focus and discipline from ordinary users.

Former professional poker player and statistics-trained Michael Boss said, “Retail traders have no chance.” He places 60 trades per minute on Kalshi and adjusts buy and sell quotes 30 times per second.

Diana stated that many financial markets exhibit similar wealth concentration phenomena, and that users making money on Kalshi outnumber those in day trading or traditional sports betting. She noted that Kalshi no longer places ads saying, “Help me pay my rent.”

Polymarket spokespeople declined to comment on The Wall Street Journal’s analysis.

Polymarket has a data partnership with Dow Jones, the publisher of The Wall Street Journal, and this analysis only used publicly available data.

Take Pederson, the unemployed chef who lost everything, as an example; he fell into the category of “sucker bets”: mention markets (betting on whether someone will say a specific word).

Professional traders say they avoid these types of bets because they are unpredictable, and even with millions of dollars in data, a reliable edge cannot be provided.

According to The Wall Street Journal’s analysis, the actual payout rates for mention market bets are far lower than expected by bettors based on listed odds. Retail bettors carry greater risks than they realize, partly due to the “long shot bias”—bettors overestimate low-probability events due to excitement.

Kalshi’s mention market monthly trading volume far exceeds Polymarket and has exploded since mid-2025. These bets are especially popular among the young users that the platform is trying to attract—promoted by influencers showcasing winning moments on social media live streams and other platforms.

John Pederson stands outside a homeless shelter in Detroit, where he has been living since losing money on Kalshi investments. © Emily Rose Bennett for The Wall Street Journal

“Smarter Than You”

For all types of bets, Kalshi and Polymarket’s promotion is straightforward—users can monetize known information for quick profits—a claim that has swept the world.

However, analysis by The Wall Street Journal found that more than 70% of Polymarket users are losing. A working paper from researchers in France and Canada last month reached a similar conclusion. They found that the gains from prediction markets primarily flow to seasoned traders, while gamblers and retail traders bear the losses.

The Wall Street Journal’s analysis of Polymarket trading data shows that regular users typically lose between $1 and $100, while the bottom 10% of users lose an average of $4,000 each.

Some people make emotional decisions—betting based on feelings or information obtained from public channels.

A Connecticut man claiming to have a gambling problem bet $2,000 on the Super Bowl on Kalshi in one day—all lost in a tense fourth quarter. A 31-year-old man from Indiana described the trading as “like a drug,” stating he had nearly daily bets on sports events on Kalshi in the first few months of this year, losing about $5,000.

In contrast, prediction markets are increasingly attracting companies with dozens of employees that spend millions on professional sports and financial data and run trading algorithms. Their goal is to outperform the students, recreational gamblers, and other low-volume traders that make up the majority of the platform’s users.

In traditional gambling, the house sets the odds, takes bets, and pays winners. In prediction markets, there is no “house”; users trade with each other. The platform only charges transaction fees, which vary based on contract prices, market types, and other factors.

In an office in Soho, a college dropout stares at a computer screen, watching millions of dollars flow as retail traders bet on Bitcoin prices.

Samuel Wood-Solov, who dropped out of Princeton University this year, received a $500,000 check from Alliance Capital, a crypto startup accelerator backed by well-known Silicon Valley investors (including crypto entrepreneur Balaji Srinivasan). He had taken a year off before attending Princeton to trade cryptocurrencies after taking a math class at UC Berkeley in high school. Now he and four friends have moved to New York to full-time trade prediction markets, betting on the future prices of sports, politics, and cryptocurrencies.

In an interview, he said, “Our only competitors are the market makers.” He refers to other firms like theirs that continuously provide buy and sell quotes. He declined to disclose the firm's profits and losses but stated that they have deployed between $500,000 and $1 million across Polymarket, Kalshi, and other small prediction markets.

Former professional poker player Boss has made over $668,000 on Kalshi, mainly from sports betting, since he began serious trading about three months ago. Aside from trading speed, he is extremely meticulous with pricing buy and sell quotes.

He said, “You’ll find that the easiest money to make is in sports. “Sports attract all the 'pathological' young men, I think.” He clarified that “pathological” refers to gambling addicts.

He observed on Kalshi that many retail traders simply place “Yes” bets on what they hope will happen. “This is very different from how people trade securities on crypto or stock exchanges.”

Jonathan Stall-Ryan, a college student from Charlottesville, Virginia, runs a company that trades cryptocurrency prices on Kalshi, among the top five by volume. © Laura Thompson for WSJ

Stall-Ryan's company pays to acquire real-time data from third parties and uses algorithms to execute tens of thousands of trades daily. © Laura Thompson for WSJ

Another company founded by around 12 employees (like himself all college students) has founder Jonathan Stall-Ryan, who is one of the top five traders in cryptocurrency price betting on Kalshi. The company spends over $200,000 annually on real-time data sources, AI-coded agents, and servers, executing tens of thousands of real-time trades daily using algorithms.

Stall-Ryan, when he was at the University of Virginia and with fraternity brothers, saw them betting on Bitcoin prices on Kalshi casually. He recalled thinking, “That guy is going to lose money.”

These professional traders mostly serve as market makers. Kalshi and Polymarket state they return part of the market maker fees and sometimes even pay them to provide liquidity.

The quantitative trading firm Susquehanna International Group became Kalshi's first major institutional market maker in 2024. According to professional traders monitoring Kalshi’s order book, the firm trades hundreds of millions of dollars weekly through Kalshi. Its accounts are private, so specific earnings are unknown. Susquehanna declined to comment.

Another quantitative trading firm, Jump Trading, is very active on both Polymarket and Kalshi. In mid-April, Citadel Securities President Jim Esposito said at a Semafor event that the company is “watching the development” of prediction markets closely. Some traders purchasing high-risk options contracts are now flocking to prediction markets.

Jeff Yass, co-founder of Susquehanna, said on a sports betting podcast in 2020: “All sports betting, all poker, all options trading are essentially betting against someone dumber than you.” He described his role in supporting the development of prediction markets as “a mission from God.”

On one hand, he believes that Americans should have the legal right to bet on sports, even if banned in certain states; on the other hand: “I expect to make a lot of money.”

Stall-Ryan on the campus of the University of Virginia. His company employs about a dozen college students. © Laura Thompson for WSJ

Looking for Easy Money

The platform designs contracts for users to ask "yes/no" questions about future events. Contracts are typically set to pay $1 when correct and zero when incorrect. The contract price reflects traders' assessment of the probability of an event occurring. For example, if a contract for a certain event trades at 41 cents, the prediction market believes that event has a 41% chance of occurring. If you win, the contract purchased at 41 cents will pay $1; if you lose, you lose your principal.

Contract prices fluctuate continuously based on the market forces of buyers and sellers until settlement. Traders profit off of tiny price movements, just like Wall Street traders.

Many naïve prediction market participants are repeating the mistakes of speculators seeking easy money in financial markets. Decades of research indicate that day traders rarely make a profit. In recent years, many retail traders, spurred by social media, have lost substantial amounts on highly volatile meme stocks.

Kalshi and Polymarket's U.S. operations (recently launched to a small number of early users) are regulated by the Commodity Futures Trading Commission (CFTC) and state that trading on their platforms is similar to that in other regulated financial markets. The vast majority of Polymarket’s activity occurs on its offshore platform, which technically prohibits U.S. access but can be easily circumvented using a VPN.

Critics say these markets are prone to problems like insider trading. Recent examples include alleged insider trading regarding U.S. military operations in Venezuela, Google announcements, and congressional campaigns.

CFTC Chairman Michael Selig defended prediction markets, clarifying the federal agency's jurisdiction over these platforms. The agency has cracked down on suspected insider trading and hinted at increasing government enforcement.

Polymarket said it has worked with the Department of Justice to combat insider trading. Kalshi prohibits insider trading on its platform and has penalized several violators in recent months.

Former Kalshi employee Adi Rajaprabakaran referred to retail traders as “fish” (gambling jargon for novice bettors likely to lose) on Substack last year. In an interview, he stated that while he still believes this is generally true, he also believes the presence of uninformed traders in prediction markets strongly incentivizes more seasoned traders to enter, resulting in more accurate predictions.

“Everyone thinks they are the informed party when they place a bet,” he said. “In the long run, the more accurate will earn more money. No one is forced to do this.”

$41,000 Bet

Before engaging with mention markets, Pederson's experience on Kalshi was relatively smooth. “I have broad interests in finance,” he said. “I’ve been looking for ways to hone my sharpness, if you want to put it that way.”

Trading volume in mention markets

The core question in mention market betting is simple: will a public figure say a certain word? This year, Kalshi users wagered over $28 million on whether Trump would say words like “cartel,” “Somali,” or “hockey” during his State of the Union address. According to data from The Block, Kalshi users placed nearly $181 million in total on mention markets in February.

Analysis by The Wall Street Journal of Kalshi data shows that the actual payout rates in mention markets are far below the levels bettors expect based on listed odds.

The Wall Street Journal analyzed over 35,000 completed mention markets on Kalshi and found that on average, “Yes” trades priced at a 50% win rate have an actual payout rate of about 40%. Since contract prices should match probabilities, these bettors are effectively paying more.

Analysis revealed that these market trades often exhibit long shot bias, resulting in frequent losses. On average, traders who place “Yes” bets upon seeing the first price in mention markets (a common pattern among retail traders) lose 11% of the amount they wagered. According to research from the University of Nevada, Las Vegas, this return is worse than that of most Las Vegas slot machines.

Kalshi spokesperson Diana acknowledged the expected bias in mention markets, but stated that mention markets do not represent the overall pricing of the platform and are not suitable for such pricing analysis. She added that Kalshi's analysis shows that the pricing in mention markets is more accurate within four hours of the event occurring.

Kalshi encourages mention market traders to live stream their trading processes during events; two streamers stated this is to enhance market engagement. A Bank of America analyst wrote in an April prediction market report: “Mention market live streams on social media often go viral, enhancing Kalshi’s brand visibility.”

In January, Pederson bet all of his $41,000 that rapper A$AP Rocky would say the word “rapper” on The Tonight Show Starring Jimmy Fallon— the star recently played a rapper in a movie. He had a chance to win over $168,000.

But the version aired by NBC cut that segment. According to Kalshi’s market rules, only what is spoken in the televised version counts.

Pederson stated in a video he shared that this rule on the platform was not clear, and he did not see it. (Kalshi later updated the interface to make market rules more prominent.)

Pederson lost everything and has almost no other resources to rely on. He is currently staying in a homeless shelter in downtown Detroit but mentioned he's recently received a job offer selling mortgages.

He said once he gets back on his feet, his goal is to enter the financial industry to support his music career. Will he return to trading in prediction markets? “Maybe,” he said. “I would prefer to spend my time in more regulated markets.”

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