Prediction markets explained: how they work, what they predict, and why they matter in 2026

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Last updated: May 27, 2026

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As of May 27, 2026, US prediction-market volume runs around $21 billion a month, Polymarket alone clears roughly $9 billion of that on the back of its December 2025 CFTC clearance through QCEX, and the New York Times now quotes Kalshi probabilities the way it used to quote analyst consensus. Here’s the mechanic that makes the prices work, the legal status that made the mainstream news, and the catch nobody mentions about state-level sports contracts — sourced from the December 2025 CFTC filing, current platform documentation, and the 2024 federal court rulings on event contracts.

The short answers

  • What is a prediction market? An exchange where you trade binary contracts on whether a specified future event will happen — each pays $1 if it does, $0 if it doesn’t.
  • How do prediction markets work? Two-sided order books match YES and NO traders; the price between $0 and $1 is read as the market’s collective probability estimate.
  • How do prediction markets make money? Trading fees, maker rebates, interest on customer float, and small payment-rail margins — they’re exchanges, not sportsbooks.
  • Are prediction markets legal? Yes on CFTC-regulated platforms (Kalshi, Polymarket US, Robinhood Event Contracts); state-availability varies for sports contracts.
  • Are prediction markets gambling? Federally no (classified as swaps); some state regulators dispute that for sports event contracts.
  • The biggest US platforms in 2026: Kalshi (cleanest legal story), Polymarket (deepest liquidity, ~$9B/month), Robinhood Event Contracts (easiest on-ramp).

TL;DR

A prediction market is an exchange where you trade contracts on whether something will happen. Each contract pays $1 if the predicted event happens and $0 if it doesn’t. The current price sits between those two outcomes — and because traders compete to buy and sell, that price ends up reflecting the market’s collective probability estimate. A contract trading at $0.65 means the market is implying a 65% chance.

Prediction markets are not new — they trace back to the Iowa Electronic Markets in 1988 — but 2026 is the year they crossed into the financial mainstream. Total US monthly trading volume across the category sits around $21 billion, with Polymarket alone clearing roughly $9 billion a month and Kalshi growing fast on the CFTC-regulated side. Robinhood added Event Contracts in 2025. The New York Times, the Wall Street Journal, USA Today, and Nieman Lab now cover market-implied probabilities the way they used to quote Vegas lines or analyst consensus.

This guide explains how prediction markets actually work, who runs them, where they make their money, what you can predict on them, how US law treats them (short version: yes, they’re legal under CFTC oversight; the state-level fight is mostly about sports contracts), and how to think about the difference between trading event contracts and gambling. Read it once, and most of the news coverage you encounter for the rest of the year will make a lot more sense.

What is a prediction market?

A prediction market is a marketplace where people trade financial contracts whose value depends on whether a specific future event happens. The contracts are usually binary: they pay $1 if the event happens, and $0 if it doesn’t.

The simplest analogy is a coupon. Imagine someone offers you a slip of paper that says: “This coupon is worth exactly one dollar if the Federal Reserve cuts interest rates at its December 2026 meeting. Otherwise, it is worth nothing.” How much would you pay for that coupon today?

If you think a December cut is almost certain, you might pay $0.90. If you think it’s a coin flip, you’d pay around $0.50. If you think it’s nearly impossible, maybe $0.05. Now imagine thousands of people are answering that same question with their wallets at the same time, on a public exchange where they can buy and sell the coupon from one another whenever they like. The price they collectively settle on is the market’s implied probability of the event happening.

That is a prediction market. The fancy term for the coupon is an event contract, and the price of a contract is interpreted as a probability. Everything else — the platforms, the fees, the regulators, the controversies — is plumbing built around that single, surprisingly powerful idea.

How do prediction markets work?

The mechanism has four moving parts: the binary contract, the price, the order book, and the resolution.

1. The binary contract

Every prediction-market contract is tied to a precisely-worded question with a clear yes-or-no answer. The wording matters a lot, because it determines exactly what counts as a “yes.” A market called “Will the Fed cut rates in December 2026?” has to specify:

  • Which Fed decision? (e.g., the FOMC meeting concluding December 16, 2026)
  • What counts as a cut? (a decrease in the federal funds target rate from the prior meeting)
  • What’s the resolution source? (the official FOMC statement, as published on federalreserve.gov)

Once the rules are set, you can buy either side. Buy YES if you think the Fed will cut; buy NO if you think they won’t. Both sides exist for every contract — for every YES buyer, there’s a NO buyer on the other end of the trade. That two-sided structure is what makes a prediction market a market, not a sportsbook.

2. The price

Prices on a prediction market live between $0.00 and $1.00. A YES contract priced at $0.65 means:

  • Buy it for $0.65 today
  • If the event happens, you collect $1.00 (profit: $0.35)
  • If the event doesn’t happen, you collect $0.00 (loss: $0.65)

And here’s the elegant part: the YES price and the NO price always add up to $1.00. If YES is $0.65, then NO must be $0.35, because the two outcomes are mutually exclusive and exhaustive. (If they ever didn’t add up to a dollar, traders would arbitrage the gap away in seconds.)

This is why prediction-market prices are read as probabilities. A $0.65 YES price is the market saying: “the collective wisdom of everyone willing to put money on this question says there’s a 65% chance the event happens.”

3. The order book

You don’t buy contracts from the platform — you buy them from another trader who is willing to sell. Every prediction market runs an order book: a real-time list of all the bids (people willing to buy at a given price) and asks (people willing to sell at a given price). When a bid and an ask match, a trade happens.

Two roles emerge:

  • Makers post limit orders that sit on the book waiting for someone to take them. They add liquidity, and most platforms pay them a small rebate for doing so.
  • Takers hit existing orders on the book, executing immediately at the available price. They remove liquidity, and they usually pay the fee.

The deeper the book, the tighter the spread between the best bid and the best ask, and the easier it is to enter or exit a position without moving the price. Liquidity is the single biggest difference between a serious prediction-market platform and a thin one — and it’s the main reason Polymarket and Kalshi dominate the US category.

4. Resolution

Once the underlying event happens (or doesn’t), the contract resolves. Every YES holder for the correct outcome receives $1.00 per contract from the platform’s escrow. Every YES holder for the wrong outcome receives $0.00. Same on the NO side, mirrored.

Resolution is automatic on most platforms. Disputes — when the resolution source is ambiguous — are handled by a published rulebook that traders can read before they take a position. On Polymarket’s decentralized side, a decentralized oracle network (UMA) handles disputed resolutions through community vote. On Kalshi, every market has a designated resolution authority written into the CFTC-approved contract specification.

What r/PredictionMarkets actually says:

“Took me a couple of weeks to stop thinking of it as betting and start thinking of it as a probability marketplace. Once that flipped, the whole thing made sense — the price isn’t the bookmaker’s line, it’s literally the crowd’s best guess.”

— Synthesis of three r/PredictionMarkets posts, Q1 2026

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Worked example: a real trade, step by step

Let’s run the math on a single contract from start to finish.

Suppose it’s October 2026. The FOMC’s December meeting is two months out. The Kalshi market for “Will the Fed cut rates in December 2026?” is trading with the following prices:

  • YES = $0.45
  • NO = $0.55
  • (Add up to $1.00 — checks out.)

The market is implying a 45% probability of a rate cut.

You disagree. You’ve read the September inflation print, watched a couple of FOMC press conferences, and you think a cut is more like 60% likely. The market is too cheap on YES, in your view. You decide to buy.

You enter an order to buy 100 YES contracts at $0.45 each. That costs you:

100 × $0.45 = $45

You now hold 100 YES contracts. Your maximum payout if the Fed cuts is:

100 × $1.00 = $100

Your potential profit is $100 − $45 = $55. Your maximum loss, if the Fed holds, is your full $45 stake. (You cannot lose more than you put in on a binary event contract — the maximum loss is always exactly what you paid for the contracts. This is a meaningful difference from, say, shorting a stock or selling a naked option, where losses can exceed your initial outlay.)

Now suppose the November jobs report comes in unexpectedly weak. The market starts pricing in a higher probability of a cut. The YES price moves up to $0.62.

You have a choice:

  • Hold to resolution — wait for the December FOMC decision. If the Fed cuts, you collect $100. If not, you lose $45.
  • Sell early — close your position by selling your 100 YES contracts at $0.62 each, locking in:

    100 × $0.62 = $62 Profit: $62 − $45 = $17

The ability to sell into a moving price is what makes a prediction market a market, not a bet. Most retail traders underestimate this. You are never forced to wait for resolution — as long as there’s liquidity, you can exit. That continuous price discovery is also what makes the implied probability meaningful: it updates in real time as new information comes in.

Why prices equal probabilities

The claim that prediction-market prices reflect the actual probability of an event is not a guess. It’s a consequence of a few well-studied properties of efficient markets.

The basic argument, sometimes attributed to Friedrich Hayek’s writings on the price system and elaborated in academic work by Robin Hanson at George Mason and Justin Wolfers at Wharton, runs like this:

  1. Many small pieces of information are distributed across many traders. No single person knows everything about whether the Fed will cut rates — but in aggregate, traders collectively hold enormous amounts of relevant information (employment data, prior Fed signaling, political pressure, market reactions).
  2. Each trader expresses their information by trading. Someone who has read every FOMC statement carefully and believes a cut is 70% likely will buy YES if the market is trading below $0.70 and sell if it’s trading above.
  3. The market price aggregates all this information into a single number. As traders buy and sell, the price adjusts until further trading isn’t profitable in expectation. That equilibrium price is the market’s best collective estimate of the probability.
  4. Mispricings get corrected by money. A trader who spots a market priced wrong has a direct profit incentive to fix it. That incentive is much stronger than the incentive a pundit has to issue an accurate prediction on TV.

The empirical record largely supports the theory. The Iowa Electronic Markets, which has run since 1988, has consistently outperformed traditional polling on US presidential election outcomes. Polymarket’s 2024 election markets called the result hours before the major news networks did, on the strength of trader bets rather than exit poll data. A 2008 paper by Wolfers and Zitzewitz in the Journal of Economic Perspectives documented similar accuracy advantages across a wide range of political and economic events.

Prediction markets aren’t infallible — they can be manipulated on thin markets, and they sometimes price in narrative more than fundamentals — but on liquid, well-defined questions, the price is usually the best probability estimate available anywhere. For the deeper how-to on reading those numbers, see our companion guide on how to read prediction-market prices.

How do prediction markets make money?

Prediction markets are exchanges. They don’t take the other side of your trade the way a sportsbook does. Their revenue comes from being the venue where trades happen — which they monetize through fees and, in some cases, listing-and-licensing economics. There are five main revenue streams.

1. Trading fees

The biggest line item. Every time a trade executes, the platform takes a small cut. The shape of the fee varies:

  • Kalshi charges a variable per-contract fee that depends on the contract’s price. The fee curve peaks near $0.50 (where uncertainty is highest) and drops near $0.01 or $0.99 (where the outcome is nearly settled). Typical fee on a $100 trade at fair value: around $1.75.
  • Polymarket uses a dynamic taker-fee model with category-specific caps. Effective March 30, 2026, peak taker fees run 0.75% on Sports, 1.00% on Politics/Finance/Tech, and 1.80% on Crypto. The US designated-contract-market product separately publishes a flat 0.30% taker fee with a 0.20% maker rebate.
  • Robinhood Event Contracts charges per-contract fees that vary by event category, broadly competitive with both Kalshi and Polymarket on retail-sized trades.

2. Maker rebates (a negative fee that’s still revenue)

Both Polymarket and Kalshi pay market makers a small rebate for posting limit orders that get filled. This sounds like a cost — and it is — but it generates more taker-fee revenue than it pays out in rebates, because every rebated maker order eventually gets crossed by a fee-paying taker.

The net result: serious market-makers can run effectively-negative fee structures on prediction markets, getting paid to provide liquidity. The platform makes its margin on the wider taker side.

3. Withdrawal and funding fees

A smaller revenue source, but real. Kalshi charges a 2% fee on debit-card deposits and withdrawals (ACH is free). Polymarket US uses similar payment-rail pricing. On-chain USDC withdrawals on Polymarket’s global product cost only Polygon network gas, which is fractions of a cent.

4. Interest on float

This is the one most users miss. Both Kalshi and Polymarket hold significant customer deposits — billions of dollars in aggregate across the category — and earn interest on that float. Kalshi, unusually, passes some of this through to users (~3.50% APY on cash balances and open positions as of early 2026). Most platforms keep more of the spread.

5. Liquidity incentive programs (LIPs)

Several platforms run formal programs that pay tokens or cash bonuses to market makers who meet uptime and spread requirements. From the platform’s perspective, this is a marketing expense that pays for itself by making the order books look deeper, which attracts retail flow, which pays taker fees.

The honest summary: prediction-market platforms are exchanges, and they make exchange money — small fees on lots of volume. Polymarket clearing $9B/month at an average effective taker rate of around 0.5% generates roughly $45 million in monthly trading-fee revenue, plus interest, plus payment-rail margin. Kalshi’s economics are smaller in absolute volume but boosted by the 3.50% APY arrangement on customer cash. These are real financial businesses, not house-banked betting operations. (See our Kalshi fee schedule deep-dive for the full per-contract math.)

A brief history of prediction markets

Prediction markets are roughly 40 years old as a formal idea, and several centuries old as an informal one. Insurance contracts at Lloyd’s of London in the 1700s, betting markets on British elections in the 1800s, and the famous “bucket shops” of late-19th-century America all expressed a similar logic: people putting money behind their beliefs about uncertain future events.

The modern era starts in 1988.

1988 — The Iowa Electronic Markets

The University of Iowa Tippie College of Business launched the Iowa Electronic Markets (IEM) as an academic experiment. It was a small-stakes prediction market (maximum $500 per trader) that let participants trade contracts on the US presidential election. The IEM consistently beat traditional pre-election polling on accuracy, often by wide margins, and it kept running through every US presidential cycle thereafter. It’s still running in 2026.

The IEM’s contribution wasn’t size — it was credibility. It proved, in peer-reviewed academic settings, that prediction markets work.

2000s — Intrade

Intrade, an Ireland-based platform, brought the IEM concept to a global retail audience in the 2000s. At its peak it had real liquidity on US elections, geopolitical events, and economic milestones. The 2008 US presidential election was a high-water mark — Intrade markets called the Obama vs. McCain result with striking accuracy long before mainstream coverage caught up.

Intrade’s end was regulatory and operational. In 2012 the CFTC sued it for offering unregistered commodity options to US persons; in March 2013 the platform halted all trading after discovering “financial irregularities” in customer funds. It never reopened. Intrade’s failure became the cautionary tale that shaped every later platform’s regulatory strategy.

2014 — PredictIt

After Intrade collapsed, PredictIt launched in 2014 as a US-based academic-style platform operated by Victoria University of Wellington in partnership with US academic researchers, under a CFTC no-action letter that allowed limited operation. Small position limits ($850 per market per user), high effective fees (10% on profits + 5% on withdrawals), and a narrow market menu kept it small — but it became the de facto home of US political prediction markets for almost a decade.

The CFTC withdrew PredictIt’s no-action letter in 2022, triggering a multi-year legal fight. Court rulings kept PredictIt operating through 2026, but the platform’s relevance has been overtaken by Kalshi and Polymarket on volume and market diversity.

2018 — Augur

Augur was the first serious attempt to build a fully decentralized prediction market on a public blockchain (Ethereum). The technology worked, in the narrow sense that the smart contracts executed as designed. The user experience did not — gas fees, slow resolution, low liquidity, and a clunky interface meant Augur never crossed into mainstream adoption. It remains a milestone for what’s possible on-chain, but its commercial significance has been small.

2020 — Polymarket

Polymarket launched in 2020, founded by Shayne Coplan. The product combined on-chain settlement on Polygon (cheaper and faster than Ethereum mainnet) with a slick web interface and aggressive global market-listing strategy. Within four years it became the world’s largest prediction market by volume — particularly dominant on political and geopolitical markets.

Polymarket’s regulatory arc was rocky. In January 2022 the CFTC fined the company $1.4 million and ordered it to wind down US access. The company complied formally but US traders continued to access the platform through VPNs (which Polymarket’s own terms of service forbade) for nearly four years. The legal limbo ended in December 2025 when Polymarket acquired QCEX (QC Exchange LLC) — a small CFTC-licensed designated contract market — for $112 million, giving it legitimate US infrastructure to relaunch. The US version went live in early 2026 with KYC, fiat funding (Apple Pay, Google Pay, ACH, debit, wire), and CFTC oversight.

2021 — Kalshi

Kalshi, founded in 2018 by MIT graduates Tarek Mansour and Luana Lopes Lara, took the opposite regulatory approach. The team spent two years working with the CFTC before launching anything. In November 2020 the agency approved Kalshi as the first-ever designated contract market dedicated to event contracts; the platform officially went live in June 2021.

Kalshi’s early product was deliberately wonky — CPI prints, jobless claims, Fed decisions, GDP. The bet was that macro nerds and institutional traders would form a credible user base before the consumer market arrived. It worked. Sequoia led a $30 million Series A in early 2021. By 2024 Kalshi had won a landmark federal court ruling permitting election contracts — the first US platform legally cleared to offer them. Sports event contracts followed in 2024–25.

Kalshi is the cleanest US legal story in prediction markets: CFTC-regulated since launch, no offshore baggage, no enforcement actions.

2025 — Robinhood Event Contracts

In 2025 Robinhood added Event Contracts to its main brokerage app, partnering with CFTC-regulated infrastructure to bring prediction-market exposure to its tens of millions of US retail brokerage users. The product is smaller in market selection than Kalshi or Polymarket, but the distribution is enormous — Event Contracts inside an app most retail traders already have was an inflection point for category awareness.

That’s the lineage. IEM → Intrade → PredictIt → Augur → Polymarket → Kalshi → Robinhood. Each generation learned from the failures of the prior one. The 2026 ecosystem is more regulated, better funded, and more liquid than anything that came before — but the basic idea, that prices reveal probabilities, hasn’t changed since 1988.

The major US prediction-market platforms today (2026)

A short tour of the platforms that matter in the US market right now.

Kalshi

The most institutionally credible US prediction-market platform. CFTC-regulated DCM since 2020, US-dollar funding via ACH, debit, and wire, and a market menu that spans economics, politics, sports, climate, culture, and crypto. Kalshi pays roughly 3.50% APY on cash and open positions — unique in the category. Best for traders who want the cleanest US legal story and an interface that feels like a brokerage app.

Polymarket

The global volume leader, with roughly $9 billion in monthly trading volume in 2026 and the deepest order books on marquee political and geopolitical markets. The US version launched in early 2026 through the QCEX acquisition and offers fiat funding plus native USDC settlement on Polygon. Best for traders who want the widest market menu, the deepest global liquidity, and the option to use crypto-native settlement.

Robinhood Event Contracts

Event contracts inside the Robinhood brokerage app. Curated set of markets (smaller than Kalshi or Polymarket), retail-friendly interface, and access for any existing Robinhood user. Best for retail traders who already use Robinhood and want a simple on-ramp.

PredictIt

The original academic US prediction market. Position limits of $850 per market, narrow market menu (mostly US politics), and high effective fees. Still trading in 2026 under court protection, but largely overtaken on volume and breadth. Best for academic and research use, or for nostalgic political-prediction traders who started here.

ProphetX

A newer sports-focused prediction-market app, structured around peer-to-peer matched bets rather than traditional sportsbook lines. Smaller user base than the big three, but a growing fixture in US sports prediction trading.

If you’re choosing one to start with, Kalshi has the lowest learning curve, Polymarket has the deepest liquidity, and Robinhood Event Contracts has the easiest on-ramp if you’re already a Robinhood user.

Learn more: Our full Kalshi vs Polymarket on fees, liquidity, and state availability walks through every dimension side by side. For deeper dives, see Kalshi’s fee structure and CFTC posture explained, Polymarket’s US-relaunch details, and our Robinhood Event Contracts overview.

What can you actually predict?

Almost anything that has a verifiable outcome and a defined resolution date. The active 2026 categories on US platforms:

  • Politics. Election outcomes, primary winners, control of Congress, Cabinet appointments, Supreme Court confirmations, leadership changes abroad.
  • Economics. Fed rate decisions, CPI prints, PCE prints, jobless claims, GDP growth, payroll reports, unemployment rates.
  • Sports. NFL game outcomes, NBA Finals matchups, MLB season records, golf majors, college football and basketball championships, World Cup, Olympics.
  • Crypto. Bitcoin price targets, Ethereum price ranges, ETF flows, regulatory decisions, exchange events.
  • Climate and weather. Annual high-temperature records, hurricane counts, snowfall thresholds, named storms.
  • Culture. Oscars, Emmys, Grammys, box-office milestones, music chart positions, viral cultural events.
  • Geopolitics. Wars, treaties, sanctions, leadership transitions, regulatory rulings, treaty ratifications.
  • Tech and science. Product launches, AI benchmark milestones, space-mission outcomes, FDA approvals, scientific milestones.
  • Health. Disease counts, public-health milestones, regulatory approvals.

The constraint is almost always resolution clarity. A market on “Will the Fed cut rates in December 2026?” is easy: there’s one published FOMC statement on a known date. A market on “Will the economy be strong in 2027?” is hard: there’s no single authoritative source for “strong.” Good prediction markets specify the resolution source in the contract rulebook so traders know exactly what they’re betting on.

Examples of prediction markets that mattered

A few cases where prediction markets meaningfully shaped public understanding of an event before traditional media caught up.

2008 US presidential election. Intrade markets called Barack Obama’s win with high confidence weeks before Election Day, and the final price moved sharply toward Obama during the September 2008 financial-crisis weeks — a real-time read on the political consequence of the crash that was sharper than most polling.

2016 Brexit vote. Prediction markets famously got Brexit wrong on the day — pricing Remain heavily — but the post-mortem became a foundational case in the discipline. The lesson: prediction markets reflect the beliefs of the people trading, and if those traders share systematic biases (e.g., London-financial-services Remain orientation), the market can be wrong in correlated ways. Trader composition matters.

2020 US presidential election. Polymarket called the Biden vs. Trump result with significant accuracy in the hours after polls closed, ahead of formal network calls. By the morning after Election Day, the market-implied probability of a Biden win had risen above 95% — well before any major network officially called the race.

2021 GameStop short-squeeze. Prediction markets quickly listed contracts on whether GameStop would close above various price levels by specific dates, and the markets reflected the unfolding short-squeeze dynamics in real time. Traders watching the markets had a better-than-CNBC view of the probabilities.

2024 US presidential election. The most-traded political prediction-market event in history. Polymarket’s market-implied odds tracked the campaign far more sensitively than weekly polling, and the final result was reflected in market prices hours before formal news network calls.

Fed rate decisions, 2022–2026. The CME’s federal-funds-futures market and prediction-market platforms (Kalshi, Polymarket) all run live markets on every FOMC meeting. These markets have become the single most-cited probability estimates in financial coverage of Fed decisions — frequently quoted in WSJ, FT, and Bloomberg ahead of meetings.

Russia-Ukraine war, 2022–2026. Polymarket has run continuously updated markets on cease-fire timing, territorial-control outcomes, and treaty negotiations throughout the war. These markets have become a real-time barometer of consensus expectations about the conflict.

COVID variant emergence, 2021–2022. Prediction markets listed contracts on case-count thresholds, variant-classification timing, and policy responses with continuous price updates that often led news coverage by days.

The pattern across these examples: when a question has a clear resolution date and meaningful trading liquidity, prediction-market prices tend to lead — not follow — traditional media coverage.

How are prediction markets different from gambling?

This is one of the most-Googled questions in the category, and it deserves an honest answer rather than a marketing one.

Legally, in the United States, prediction markets and gambling are distinct. Under federal law, CFTC-regulated event contracts are classified as swaps — a category of derivative financial instrument — not as bets. That classification is what allows platforms like Kalshi and Polymarket US to operate across all 50 states under federal preemption, the same way the CFTC’s jurisdiction over commodity futures preempts state gambling laws for those markets. The CFTC’s authority here is rooted in the Commodity Exchange Act, and a series of court rulings in 2024–25 reaffirmed it.

Functionally, prediction markets share characteristics with both gambling and traditional financial markets. Like gambling, they involve risk of loss and uncertain outcomes; like financial markets, they operate as two-sided exchanges with continuous pricing, transparent order books, and standardized contracts that settle on objective resolution sources.

The key structural differences from a sportsbook:

  • No house edge. A traditional sportsbook makes money by setting lines that include an embedded vig (typically 4.5%–10%) — you’re betting against the house. A prediction market matches your trade against another trader, and the platform takes a small fee from both sides. The economic structure is closer to a stock exchange than a casino.
  • Two-sided pricing. You can buy YES or buy NO on every contract, at independent prices that must add up to $1.00. On a sportsbook, you can only “bet on” one side at the price the book offers.
  • Continuous exit. You can sell your position back into the market anytime there’s liquidity. On most sportsbooks, you’re locked in until the event resolves (cash-out features are a partial exception, at heavily-discounted prices).
  • Transparent order book. You can see other traders’ bids and asks. On a sportsbook, you only see the line the book is offering you.

These structural differences are real — and they’re why the CFTC classifies event contracts the way it does. But the underlying activity (paying money in exchange for a contingent claim on a future event) is similar enough that the line is genuinely contested.

State gaming regulators in Nevada, Massachusetts, and New Jersey have argued, particularly with respect to sports event contracts on Kalshi, that the economic substance is sports betting regardless of the federal swap label. The federal-vs-state preemption question is being litigated in 2026 and will likely keep moving through 2027.

The pragmatic answer for an individual trader: regardless of the legal classification, treat the money you put into prediction markets as risk capital — money you can afford to lose. The legal label doesn’t change the financial exposure. (For the platform-specific version of this debate, see Is Kalshi gambling?.)

Are prediction markets gambling?

Same question, slightly different framing — and worth answering separately because both phrasings get searched heavily.

Under federal law, no. CFTC-regulated event contracts are swaps, not bets, and the platforms offering them (Kalshi, Polymarket US, Robinhood Event Contracts) are designated contract markets, not sportsbooks. The legal category is the same one that contains commodity futures and interest-rate swaps — financial derivatives traded on regulated exchanges, not gambling products.

Under some state laws and in cultural perception, the answer is more complicated. Several state gaming regulators have argued that sports event contracts in particular are functionally equivalent to sportsbook bets and should be regulated as such. Kalshi’s response, supported by federal court rulings to date, is that federal CFTC jurisdiction over swap contracts preempts state gambling law. The legal question is being actively litigated.

If you want a one-line summary you can give to a friend who asks: “Federally regulated as a financial product, not a gambling product. Some state regulators disagree about specific categories. Functionally, you’re trading binary contracts with other people on an exchange — it’s structurally different from a sportsbook, but it shares the risk-of-loss feature of gambling.”

Most prediction-market platforms — including Kalshi and Polymarket — avoid the word “betting” in their own marketing and use “trading event contracts” instead. That’s not just legal hygiene; it reflects the real structural difference between an exchange and a sportsbook. But the colloquial overlap is real, and you should treat the activity as financially risky regardless of how it’s labeled.

Are prediction markets legal?

For US-based, CFTC-regulated platforms: yes.

The relevant federal regulator is the Commodity Futures Trading Commission (CFTC), which has jurisdiction over event contracts as a category of swap. Two key platform classifications:

  • Designated Contract Market (DCM). A CFTC-registered exchange permitted to list standardized contracts. Kalshi has been a DCM since November 2020. QCEX, the entity Polymarket acquired in December 2025, is a DCM whose contracts are now offered under the Polymarket US brand.
  • No-action letter. A more limited form of CFTC tolerance, granted to specific products on specific terms. PredictIt historically operated under a no-action letter; that letter was withdrawn in 2022 and the matter is ongoing in court.

For users:

  • US residents can legally trade on CFTC-regulated DCMs (Kalshi, Polymarket US, Robinhood Event Contracts) subject to state-availability restrictions. Industry partner pages currently list Polymarket US as unavailable in AZ, IL, MA, MD, MI, MT, NV, and OH; Kalshi officially operates in all 50 states + DC, though sports contracts face active state-level challenges in NV, MA, and NJ.
  • Non-US residents generally cannot access the US-regulated platforms (KYC restrictions), but can access Polymarket’s global product where local law permits. US residents accessing Polymarket’s global product (rather than Polymarket US) via VPN violates Polymarket’s terms of service.

The state-availability picture is the part changing fastest. Always check the platform’s own state-availability page before depositing. A guide we wrote last week may be out of date by the time you read this.

Learn more: Our state-by-state legality guides cover California, Texas, Florida, and New York, among other states where the regulatory picture has moved in 2026.

Who uses prediction markets?

The user base has shifted dramatically in 2026. Five rough groups:

Retail traders. The largest group by user count. People with $500 to $25,000 in disposable trading capital who use prediction markets for some combination of intellectual interest, hedging exposure to known events (e.g., taking the other side of an outcome they’re personally invested in), and entertainment.

Quants and prop traders. Smaller in number but large in trading volume. Specialist traders who use prediction markets to express views on macro events, run cross-platform arbitrage, or hedge other positions. The CFTC’s regulatory clarity has attracted a measurable wave of institutional flow since 2024.

Journalists and policy analysts. A new and growing user category. Reporters at NYT, WSJ, USA Today, Bloomberg, and FT now routinely cite prediction-market prices in coverage of elections, Fed decisions, and geopolitical events. Some maintain personal accounts to monitor markets in real time; others rely on aggregator dashboards.

Hedge funds (selectively). Larger institutional players have begun using prediction markets as one input among many for macro positioning, though regulatory uncertainty and contract-size limits have kept positions modest by hedge-fund standards.

Academics. The longest-standing user community, often working with Iowa Electronic Markets or PredictIt for research on market-aggregation theory, electoral forecasting, and information economics. Several major universities now run prediction-market research programs.

Sports bettors. A growing user category since Kalshi launched sports event contracts in 2024–25. Many users came over from traditional sportsbooks attracted by the no-vig structure, the ability to sell positions before resolution, and the federal-legal cover under CFTC oversight.

If you’re reading this guide, you’re almost certainly in the first or last group. Welcome.

What the news media now does with prediction markets

The single biggest 2026 development for the category isn’t a new platform — it’s the legitimization of prediction-market prices in mainstream news coverage.

  • The New York Times began citing Polymarket and Kalshi prices in election coverage in 2024 and now uses them as standard reference points in political reporting.
  • The Wall Street Journal routinely quotes market-implied probabilities from Kalshi for Fed decision coverage, including in editorial and op-ed pages.
  • USA Today integrated prediction-market data into its election coverage in 2024 and expanded that integration in 2026 midterm reporting.
  • Nieman Lab has covered prediction markets as a standalone news beat, examining how journalists use and misuse market-implied probabilities.
  • Dow Jones × Polymarket announced an exclusive partnership in 2026 to feed prediction-market data directly into Wall Street Journal and Barron’s reporting workflows.

This matters for a simple reason: a probability that gets quoted in the New York Times is a probability that has crossed into the mainstream financial vocabulary. The lay reader who would have shrugged at “Kalshi prices imply a 62% probability of a December Fed cut” in 2022 now understands the sentence. That cultural shift, more than any single platform launch, is what 2026 will be remembered for in the category.

It also creates a feedback loop. As news coverage cites prediction-market prices, more readers become aware of the markets. Some of those readers become traders. More traders means more liquidity. More liquidity means more reliable prices. More reliable prices means more news coverage. The bell rings louder.

What new traders actually say:

“Spent the first month just watching prices and reading resolution rules before I put a dollar down. Best advice anyone gave me — by the time I placed my first trade, I actually knew what I was buying.”

— Composite of r/Kalshi and r/Polymarket new-trader threads, April–May 2026

The risks

A complete guide owes you the downsides. Five real risks worth understanding before you fund an account.

1. Capital loss. Every trade can go to zero. There is no FDIC-style protection for prediction-market positions. If you buy YES at $0.45 and the event doesn’t happen, you lose the full $0.45 per contract. Treat the money you put in as risk capital.

2. Illiquidity on niche markets. Marquee markets (US presidential, NFL Sunday games, Fed decisions) are deeply liquid. Long-tail markets — obscure political races, niche climate predictions, narrow-window contracts — can have spreads so wide that even a small position moves the price. Check the order book depth before you trade.

3. Manipulation potential. Small markets with thin order books can be manipulated by individual traders willing to spend money to move the price. Regulated platforms (Kalshi, Polymarket US) have surveillance and position limits that reduce this risk, but it doesn’t go to zero. Polymarket’s UMA oracle resolution system has occasionally been the subject of disputes when contested resolutions had economic incentives attached.

4. Regulatory uncertainty. The federal-vs-state preemption fight over sports event contracts (Nevada, Massachusetts, New Jersey) is unresolved and could change platform availability in those states. The CFTC’s stance on certain contract categories could also shift under a new administration. Always check state availability before depositing.

5. Resolution disputes. Most resolutions are clean. A small percentage are not — usually because the underlying event has ambiguous facts (e.g., “Did the candidate concede by X date?” when the candidate gave a partial concession on day X+1). Read the contract rulebook before you trade, and understand the resolution source.

None of these risks should stop you from using prediction markets if the underlying activity interests you. They should stop you from putting in money you can’t afford to lose.

How to start trading on a prediction market today

A short, practical on-ramp.

1. Pick a platform. If you want the simplest US experience, start with Kalshi. If you want the widest market menu and deepest liquidity, start with Polymarket US. If you’re already a Robinhood user, Robinhood Event Contracts is the lowest-friction option.

2. Check state availability. Before signing up, confirm the platform operates in your state. Kalshi is officially nationwide; Polymarket US has a list of currently-restricted states (AZ, IL, MA, MD, MI, MT, NV, OH as of mid-2026, subject to change).

3. Complete KYC. All CFTC-regulated platforms require identity verification — name, date of birth, address, Social Security number. The process takes a few minutes and is standard for any US financial account.

4. Fund the account. ACH is the easiest method on Kalshi (free, instant up to $250 on first deposits). Polymarket US accepts ACH, debit, wire, Apple Pay, and Google Pay. Start small — $50 to $200 is enough to learn.

5. Place a small first trade. Find a market on a topic you actually know something about. Buy 5 to 20 contracts. Watch how the price moves. Sell into a profit if it goes your way, or hold to resolution to learn what that feels like.

6. Read the resolution rules. Before every trade, read the contract rulebook. Know exactly what counts as a YES outcome and what the resolution source is.

7. Keep trade size proportional to capital. A common rookie mistake is putting 50% of your balance into a single conviction trade. Even a 70%-likely event loses 30% of the time. Size positions so that any single loss is recoverable.

The first month of trading is mostly a learning curve. The second month is when the patterns start clicking — you’ll start recognizing what tight markets look like, where the fee curves matter, which categories have the most thoughtful trader communities. Be patient. The traders making consistent edges have all been at this for years.

What’s next for you

If you’ve read this far, you’re past “what is this?” and into “how should I actually use it?” Here’s where to go next:

Frequently asked questions

Are prediction markets legal in the United States?

Yes, on CFTC-regulated platforms. Kalshi has been a CFTC-designated contract market since November 2020. Polymarket US operates as a designated contract market through its December 2025 acquisition of QCEX. Robinhood Event Contracts runs on CFTC-regulated infrastructure. State-level availability varies, particularly for sports contracts in Nevada, Massachusetts, and New Jersey. Always check the platform’s own state page before funding.

Are prediction markets gambling?

Legally, no — federally regulated event contracts are classified as swaps under CFTC jurisdiction, not as bets. Functionally, they share some characteristics with gambling (risk of loss, uncertain outcomes) but operate as two-sided exchanges rather than house-banked sportsbooks. State regulators in some jurisdictions argue sports event contracts in particular are functionally equivalent to sports betting, and that question is being litigated in 2026.

How are prediction markets different from sportsbooks?

Four structural differences: (1) no house edge — your counterparty is another trader, not the platform; (2) two-sided pricing — you can buy YES or NO at independent prices that must sum to $1.00; (3) continuous exit — you can sell your position anytime there’s liquidity, not only at event resolution; (4) transparent order books — you can see other traders’ bids and asks. Sportsbooks have none of these features.

What’s the difference between Kalshi and Polymarket?

Kalshi is CFTC-regulated since 2020, US-dollar-funded, pays ~3.50% APY on cash, and has the simplest US legal story. Polymarket is the global volume leader at ~$9 billion/month, with deeper order books on marquee political and geopolitical markets, native USDC settlement on Polygon, and a US version (launched 2026 via QCEX) that adds fiat funding. Many serious traders use both. See our verdict on Kalshi vs Polymarket for fees, payments, and state availability side by side.

What’s the minimum trade size?

There’s typically no formal minimum trade size on Kalshi or Polymarket beyond the per-contract price (which can be as low as $0.01). Practical minimums are driven by what’s worth the time — most retail traders start with $20 to $100 positions. Kalshi’s first ACH deposit has an instant-funding cap of $150.

Can I lose more than I put in?

No, not on a standard binary event contract. Your maximum loss is always exactly what you paid for the contracts — you cannot owe additional money. This is structurally different from short-selling stocks or selling naked options, where losses can exceed initial outlay.

Are winnings taxable?

Yes. In the US, prediction-market gains are generally taxable income. The exact treatment varies — some traders report gains as ordinary income on Form 1099-MISC (Kalshi reports this way), others as capital gains, and a few as Section 1256 contracts depending on platform classification. Talk to a tax professional. Don’t take tax advice from a guide on the internet, including this one.

How do prediction markets make money if they don’t take the other side of trades?

Trading fees on every executed trade, maker rebates that net out to positive exchange revenue, interest on customer float (Kalshi passes 3.50% APY back to users; most platforms keep more), and small fees on certain payment methods (e.g., 2% on debit cards). Polymarket clearing $9B/month at an average effective taker rate of around 0.5% generates roughly $45 million in monthly trading-fee revenue, plus the other lines.

How accurate are prediction-market prices?

Empirically, very accurate on liquid markets with well-defined resolution criteria. The Iowa Electronic Markets has outperformed traditional polling on US presidential elections since 1988. Polymarket called the 2024 US presidential result with high confidence before major networks did. Accuracy degrades on thin markets, on markets with ambiguous resolution criteria, and on markets where trader composition is systematically biased (the 2016 Brexit case being the famous example).

Can I trade prediction markets without using crypto?

Yes. Kalshi is entirely US-dollar-funded — no crypto involved at any stage. Polymarket US offers fiat funding via Apple Pay, Google Pay, ACH, debit, and wire; you never need to touch USDC if you don’t want to. Robinhood Event Contracts uses standard Robinhood brokerage funding. Crypto-native funding (USDC on Polygon) is only required if you’re using Polymarket’s global product rather than Polymarket US.

What happens if a market’s resolution is disputed?

Every contract has a published rulebook that specifies the resolution source. On Kalshi and Polymarket US, the platform’s compliance team handles disputes per the CFTC-approved rulebook. On Polymarket’s global product, the UMA oracle handles disputed resolutions through a decentralized token-vote process. Read the rulebook before you trade. Most resolutions are clean; the rare contested ones are usually a function of edge-case wording.

How do I get started if I’ve never traded before?

Pick one platform, complete KYC, fund with a small amount ($50–$200), and place a small first trade on a topic you actually know something about. Read the contract rulebook before each trade. Watch how the price moves. Sell into a profit or hold to resolution to feel both outcomes. The first month is mostly a learning curve; patterns start clicking in the second. Don’t put in money you can’t afford to lose.

Stay ahead of the markets

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By Avery Chen · Markets Editor, Bellwether · Last updated: May 27, 2026 — we update this page when regulations change, platform terms shift, or significant news breaks in the prediction-market category.

Where to go next

If you’ve made it this far, you have the conceptual foundation. From here, the most useful next steps depend on what you want to do:

The category is moving fast in 2026. We update this guide as platform mechanics, regulatory positions, and market structure evolve. If you spot something out of date, write to us — we’d rather fix it than be wrong on the internet.

Next: How to use Polymarket in the US — the post-QCEX walkthrough

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