Who Really Wins the Bet?

Prediction markets promise something almost irresistible: turn your knowledge of politics, sports, economics or popular culture into cash. Pick the future correctly, the sales pitch suggests, and you can profit before everyone else catches up.

But behind the billions of dollars in reported trading volume lies a less glamorous reality. Prediction markets do not manufacture money. They primarily move it from participants who are wrong—or sell at the wrong time—to participants who are right. Meanwhile, the platform collects fees for arranging the exchange.

The future may be uncertain, but the transaction fee is remarkably punctual.

A typical contract asks a yes-or-no question. Suppose a “Yes” contract costs 60 cents and the corresponding “No” position costs 40 cents. Together, the opposing positions represent $1. If the event happens, the winning Yes contract pays $1. Its owner earns 40 cents before fees, while the losing side supplies the corresponding loss.

Contracts can also be resold before the event is decided. If public sentiment changes, a contract purchased for 30 cents might be sold later for 55 cents. That ability to trade in and out distinguishes prediction exchanges from many traditional wagers, but it does not eliminate the underlying financial transfer.

It also explains why trading volume can be misleading. A single contract may be bought and sold repeatedly, with every transaction added to the reported volume. Therefore, $1 billion in trading does not mean $1 billion was deposited, won or lost. It means contracts with that total reported value changed hands during the measured period.

For traders collectively, prediction markets are largely a zero-sum system before fees and incentives: one side’s profit is matched by losses or surrendered value elsewhere. After transaction costs, the participants as a group are left with less money than they brought to the table.

The platform occupies a more comfortable seat.

Kalshi says it generally acts as an intermediary matching buyers and sellers rather than taking the opposing side of every trade like a traditional sportsbook. Its revenue comes principally from transaction fees calculated according to the contract price and potential payout. That means the company does not necessarily care whether Yes or No wins. It benefits when people continue trading.

The most dependable winner, therefore, may not be the person predicting the future. It is the business charging admission to the argument.

Professional market makers can also profit. These firms continuously offer to buy and sell contracts, providing the liquidity that allows customers to trade quickly. They seek to earn the difference between buying and selling prices and may receive incentives or rebates from platforms.

Market making is not risk-free. A firm can lose when prices move suddenly or better-informed traders take advantage of its offers. Nevertheless, sophisticated operations possess major advantages over casual users: algorithms, automated trading systems, enormous datasets and the ability to respond to new information within seconds.

A detailed analysis of Polymarket accounts found that more than 70% of users lost money. Approximately 0.1% of accounts captured 67% of the profits. Those statistics apply specifically to the accounts examined on Polymarket and should not automatically be treated as the performance record of every prediction platform. But they illustrate how dramatically profits can concentrate among a small number of skilled, well-financed or better-informed participants.

Information itself may be the most valuable currency. Someone who possesses confidential knowledge about a government announcement, corporate decision, awards result or public speech may hold an enormous advantage over ordinary traders.

That risk became strikingly clear when the Commodity Futures Trading Commission took action against former White House teleprompter operator Gabriel Perez. Regulators said Perez used advance access to President Donald Trump’s prepared remarks to trade contracts predicting which words and subjects the president would mention. Perez agreed to surrender approximately $107,539 in profits, pay a $65,000 penalty and accept a three-year trading ban.

Kalshi detected and reported the suspicious activity, demonstrating that regulated platforms can identify misconduct. But the case also exposed the fundamental temptation created by markets built around events that some participants may know about before the public does.

Does the public receive anything valuable in return?

Prediction markets can produce useful information. Prices combine the judgments of many participants and can provide constantly updated estimates of an event’s probability. Businesses may also use certain contracts to offset genuine risks. A farmer could hedge against damaging weather, for example, while a company might protect itself against an economic indicator moving in an unfavorable direction.

Those functions resemble legitimate financial risk management. A person wagering on a football score, however, generally is not protecting an existing asset or business. The participant is creating a new risk in hopes of earning money.

Sports now account for most activity on Kalshi. More than 90% of the platform’s trades during 2025 were sports-related and generated approximately 95% of its revenue. That makes the industry’s claim to be primarily an economic forecasting tool more difficult to maintain. A contract predicting inflation may offer information to businesses. A four-part football parlay mostly offers excitement.

There is also a public-revenue question. Licensed sportsbooks pay gaming taxes and licensing fees to states, with some of that money directed toward public programs and gambling-addiction services. Prediction exchanges operating under federal commodities regulation may not be subject to those same state obligations. That is one reason states are fighting to classify sports event contracts as gambling.

None of this means that every prediction-market participant will lose or that the markets have no value. Successful traders can earn substantial profits, businesses may find legitimate hedging opportunities and the resulting probability estimates can occasionally inform the public.

But the financial hierarchy is becoming clear. Platforms collect fees. Market makers and highly sophisticated traders can exploit speed and expertise. A small group of exceptionally informed participants may earn enormous returns. Most ordinary customers compete for what remains—and many lose.

Prediction markets sell the democratic idea that everyone’s knowledge has value. In practice, however, knowledge is not distributed equally, technology is not available equally and luck eventually sends an invoice.

The public may gain another forecasting tool. The platforms and their investors may gain a powerful new industry. But for the average person hoping to make easy money by predicting tomorrow, the oldest gambling warning still applies: if you cannot identify who has the advantage, it probably is not you.