John Pederson, 33, is currently unable to work. The former Outback Steakhouse chef is recovering from a car accident, and his savings are running out. The prediction market platform Kalshi seemed like a quick fix, so he took out a variable-rate loan and started placing bets.
It started well. Pederson turned around $2,000 into nearly $8,000 by betting on the daily snowfall in Detroit (his hometown). He then reinvested the funds in sports event trading, using an AI-assisted strategy, and according to The Wall Street Journal's review of his account records, he eventually reached $41,000.
Then he made his boldest bet yet: putting all $41,000 on a celebrity saying a specific word on TV, and he lost it all.
Pederson is not alone in leaving empty-handed in the "anything goes" markets that cover sports, celebrities, news, and more.
Kalshi and its competitor Polymarket have marketed themselves as tools that can change the fate of ordinary people—implying everyone has a fair chance to make a big profit. "I was almost unable to pay my rent, but through Kalshi's predictions, I earned two years' worth of rent," a woman excitedly said in a Kalshi ad on TikTok.
However, for most users, this is far from reality.
Instead, according to The Wall Street Journal's analysis of platform data and interviews with traders, regular traders are consistently losing money, while a small group of experienced professional players—including trading firms with massive data resources—are eating up their funds.
The Wall Street Journal found that on Polymarket, 67% of profits went to merely 0.1% of accounts. This means that less than 2,000 accounts collectively netted nearly $500 million. The Wall Street Journal analyzed 1.6 million accounts traded on Polymarket since November 2022. The platform has a total of at least 2.3 million accounts.
Kalshi, too, has many more losers than winners. Spokesperson Elizabeth Diana said that based on data from the past month, every profitable user corresponds to 2.9 losing users. She mentioned that this ratio may change as the platform grows. The company does not disclose comprehensive data on user profits or the total number of users.
According to data from the analytics firm The Block, the total trading volume on both platforms surged to $24.2 billion in April, up from just $1.8 billion a year ago.
Supporters argue that these markets are not gambling but leverage collective intelligence to accurately predict future events. Federal Reserve research shows that Kalshi is an effective tool for forecasting economic trends.
Traders are paying for third-party big data feeds to gain an edge. Computers use data and algorithms to predict price movements and manage risk faster than any human. Pro traders also take advantage of economies of scale to engage in high-frequency, strategic trading—sometimes executing tens of thousands of trades in a day—and profit from small fluctuations, requiring rare levels of focus and discipline from the average user.
Former professional poker player and statistically trained Michael Bos said, "Retail traders don't stand a chance." He executes 60 trades per minute on Kalshi, modifying buy and sell quotes 30 times per second.
Diana noted that many financial markets exhibit similar wealth concentration, and more users make money on Kalshi than in day trading or traditional sports betting. She mentioned that Kalshi has stopped running ads featuring "help me pay rent."
A Polymarket spokesperson 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 solely uses publicly available data.
Using the example of the unemployed cook Pedersen, who lost all, he fell into the category of those often referred to in the market as "sucker bets" (betting on whether someone will say a specific word).
Professional traders say they steer clear of such bets as they are unpredictable, and even with millions of data points, provide no reliable edge.
According to The Wall Street Journal's analysis, the actual payout rate for such bets is much lower than expected. Retail bettors face greater risks than they realize, partially due to the phenomenon of "long shot bias"—betters overestimate small-probability events due to excitement.
Kalshi's monthly trading volume for these kinds of bets far surpasses Polymarket's, exploding since mid-2025. These bets are embraced by the platform's sought-after young users—including influencers who promote them in livestreams and other victory-bragging videos on social media.
「Smarter Than You」
For all types of bets, the promotion of Polymarket and Kalshi has been straightforward—users can monetize known knowledge, make money quickly—a claim that has swept the globe.
However, a Wall Street Journal analysis found that over 70% of Polymarket users are at a loss. A working paper by researchers in France and Canada last month reached a similar conclusion. They found that the profits from prediction markets mostly go to seasoned traders, while high-risk and retail traders incur losses.
The Wall Street Journal's analysis of Polymarket trading data shows that the average ordinary user loses between 1 and 100 dollars, while the worst-performing 10% of users lose an average of $4,000 each.
Some people make emotional decisions—following their gut or betting based on information obtained through public channels.
A Connecticut man who claims to have a gambling problem wagered on the Super Bowl on Kalshi and lost $2,000 in a single day—all in the tense fourth quarter. A 31-year-old man from Indiana described this type of trading as "like a drug," betting on sports almost every day in the early months of this year on Kalshi and losing around $5,000.
In contrast, prediction markets are increasingly attracting companies with dozens of employees, spending millions of dollars on professional sports and financial data, and running trading algorithms. They aim to outsmart the students, recreational gamblers, and other low-volume traders who make up the majority of the platform's users.
In traditional gambling, the house sets the odds, takes the bets, and pays the winners. In prediction markets, there is no "house"; users trade with each other. The platform only charges a transaction fee, which varies based on factors such as contract prices and market type.
In an office in SoHo, a college dropout stares at a computer screen, watching millions of dollars in funds from retail traders flow on bets on the price of Bitcoin.
Samuel Wood-Soloff dropped out of Princeton University this year and received a $500,000 check from the crypto startup accelerator Alliance Capital, backed by Silicon Valley notable investors, including crypto entrepreneur Balaji Srinivasan.
He took a math class at the University of California, Berkeley in high school, took a year off to trade cryptocurrency before going to Princeton. Now, he and four friends have moved to New York, trading full-time in the prediction markets, betting on the future prices of sports, politics, and cryptocurrency.
In an interview, he said, "Our only competitor is the market maker." He referred to other companies that continuously provide buy and sell quotes like them. He refused to disclose the company's profit and loss but mentioned that they have deployed $500,000 to $1 million on Polymarket, Kalshi, and other small prediction markets.
Former professional poker player Boss has earned over $668,000 on Kalshi, mainly from sports betting, since he started trading seriously about three months ago. Besides the speed of trading, he is also very precise in pricing the quotes.
He said, "You'll find that the easiest way to make money is through sports." "Sports attract all the 'sick' young men, I think." He clarified that by "sick," he meant gambling addicts.
He observed on Kalshi that many retail traders only bet "Yes" on what they hope will happen. "This is completely different from people trading securities on cryptocurrency or stock trading platforms."
Another company founded by about 12 employees (all university students like him) sees Jonathan Stall-Ryan as 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 coding agents, and servers, executing tens of thousands of real-time trades daily using algorithms.
Stall-Ryan once saw fellow fraternity brothers casually betting on the price of Bitcoin on Kalshi while at the University of Virginia and thought to himself at the time, "That guy is about to lose money."
These professional traders mostly serve as market makers. Kalshi and Polymarket have indicated that they will refund a portion of the market maker fees and sometimes even pay them to provide liquidity.
Quantitative trading firm Susquehanna International Group became Kalshi's first major institutional market maker in 2024. Professional traders monitoring Kalshi's order book claim that the firm trades hundreds of millions of dollars through Kalshi weekly. Its accounts are private, and specific profits are undisclosed. Susquehanna declined to comment.
Another quantitative trading firm, Jump Trading, is active on both Polymarket and Kalshi. In mid-April, Citadel Securities CEO Jim Esposito stated at the Semafor event that the company is "closely watching" the development of prediction markets. Some traders who used to buy high-risk options contracts are now flocking to prediction markets.
Susquehanna co-founder Jeff Yass said in a 2020 sports betting podcast: "All sports betting, all poker, all option trading, is essentially gambling against people dumber than you." He described his role in supporting the development of prediction markets in the same podcast as a "mission from God."
On one hand, he believes that Americans should be able to legally bet on sports even if it is prohibited in some states; on the other hand: "I expect to make a lot of money."
Looking for Easy Money
The platform is designed for users to ask "yes/no" questions about future events through contracts. Contracts are usually structured to pay $1 if correct and $0 if incorrect. The contract price reflects traders' assessment of the probability of the event occurring.
For example, if an event contract is trading at 41 cents, the prediction market believes the event has a 41% probability of occurring. If you win, the contract bought at 41 cents will pay $1; if you lose, you lose your stake.
The contract price constantly changes before settlement based on market forces from both buyers and sellers. Traders profit from small price fluctuations, much like Wall Street traders.
Many naive market participants are now following in the footsteps of easy money seekers in the financial markets. Decades of research have shown that day traders rarely make money. In recent years, many retail traders have been left empty-handed on highly volatile meme stocks, driven by social media hype.
Kalshi and Polymarket's U.S. operations (recently launched to a small group of early users) are regulated by the Commodity Futures Trading Commission (CFTC) and claim that their platform operates similarly to other regulated financial markets. The majority of Polymarket's activity takes place on its offshore platform, which is technically inaccessible to Americans but can be easily circumvented using a VPN.
Critics argue that these markets are prone to issues such as insider trading. Recent examples include alleged insider trading on U.S. military action in Venezuela, Google announcements, and congressional elections.
CFTC Chairman Michael Selig has defended prediction markets and clarified the federal agency's jurisdiction over these platforms. The agency has cracked down on suspected insider trading and hinted at ramping up government enforcement.
Polymarket has stated that it is working 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 Rajaprabhakaran referred to retail traders as "fish" (a gambler slang, meaning inexperienced players) in a Substack last year. In an interview, he stated that while he still believes this to be true overall, he also believes that the presence of uninformed traders in prediction markets will strongly incentivize more seasoned traders to participate, leading to more accurate predictions.
"Everyone placing a bet believes that they are the more informed party," he said. "In the long run, the more accurate person will make more money. No one is being forced to do this."
A $41,000 Bet
Pedersen's experience on Kalshi was somewhat smooth sailing before diving into the mention market. "I have a broad interest in finance," he said. "I've always been looking for ways to sharpen my acuity, if you will."
The crux of the mention market bet lies in one question: Will a public figure say a certain word? This year, Kalshi users wagered over $28 million on whether certain words such as "cartel," "Somali," or "hockey" would be mentioned in Trump's State of the Union address. According to The Block data, Kalshi users placed nearly $181 million in bets in the mention market in February.
The Wall Street Journal's analysis of Kalshi data shows that the actual settlement rate in referenced markets is much lower than what bettors would expect based on the listed odds.
The Wall Street Journal analyzed over 35,000 completed referenced markets on Kalshi and found that on average, "Yes" trades priced at a 50% win probability had an actual settlement rate of around 40%. These bettors ended up overpaying as the contract prices should align with probabilities.
The analysis revealed that these market trades often exhibit a long shot bias and frequently result in losses. On average, traders who bet "Yes" upon seeing the initial price in a referenced market (a common pattern among retail traders) lost 11% of their wagered amount. According to research from the University of Nevada, Las Vegas, this return is worse than most Las Vegas slot machines.
Kalshi spokesperson Diana acknowledged an expectation discrepancy in referenced markets but stated that these markets do not represent the platform's overall pricing and are not the appropriate subject for such pricing analyses. She added that Kalshi's analysis shows that pricing in referenced markets is more accurate within four hours before an event.
Kalshi encourages referenced market traders to live-stream their trading during events, with two live streamers stating that this is to boost market participation. In an April market forecast report, a Bank of America analyst wrote, "Referenced market live streams on social media often go viral and enhance Kalshi's brand recognition."
In January this year, Peterson wagered his entire $41,000 earnings on a bet that rapper A$AP Rocky would say the word "rapper" on "The Tonight Show Starring Jimmy Fallon"—the celebrity recently portrayed a rapper in a movie. He had the opportunity to win over $168,000.
However, the segment was cut from the version aired on NBC. According to Kalshi's market rules, only the content said in the TV-aired version counts.
In a video he posted, Peterson expressed that this rule was not clearly visible on the platform's website, and he did not see it. (Kalshi later updated the interface to make the market rules more prominent.)
Peterson incurred a total loss and has almost no other resources to fall back on. He currently resides in a homeless shelter in downtown Detroit, but says he recently received a job offer to sell mortgages.
He mentioned that once he gets back on his feet, his goal is to enter the finance industry to support his music career. Will he return to prediction market trading? "Maybe," he said. "I'd prefer to spend time in more regulated markets."
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