What Are Prediction Markets Like Polymarket and How Do They Work?

Prediction markets have surged from niche experiments to high-volume platforms where prices act as live probabilities for real-world events. By combining trading mechanics with blockchain infrastructure, they turn collective belief into a liquid, always-on forecast market.

TLDR On-chain prediction markets like Polymarket, Kalshi, Opinion, and Myriad let users trade event outcomes as $0–$1 shares, where price reflects implied probability and winning shares pay out $1 at resolution. Unlike traditional betting, positions can usually be bought and sold before events conclude, making them tradeable forecasts. On-chain platforms rely on AMMs and oracles to price and settle markets, while centralized venues manage markets more directly. The sector has grown rapidly in volume and mainstream relevance, but faces regulatory scrutiny, integrity risks (like wash trading), and ongoing legal uncertainty across jurisdictions.

On-chain prediction markets have gone from a niche corner of crypto to a mainstream talking point, especially as platforms like Myriad, Polymarket, and Kalshi expanded what people can bet on—from crypto price milestones to elections and geopolitics. At a high level, these markets take a simple idea (price = probability) and wrap it in an interface where you can buy and sell outcomes like assets.

If you’ve never used one before, it helps to think of them as a mix of betting markets and financial markets. You’re not just “placing a bet” and waiting—you can often enter and exit at any time, and the market price updates constantly based on crowd positioning. The result is a live, tradeable forecast, built either on traditional infrastructure or on blockchain rails that allow anyone, anywhere, to participate using cryptocurrencies.

In brief

• Prediction markets like Polymarket, Kalshi, and Myriad let you speculate on the outcome of future events by buying and selling outcome shares.

• Each share typically trades between $0.00 and $1.00, where the price loosely reflects the market’s implied probability of that outcome happening.

• When the event is over, the market resolves and the winning outcome pays out at $1.00 per share (while losing outcomes go to $0.00).

Prediction markets have existed in some form for centuries, but the recent wave is defined by scale, distribution, and product design. On-chain markets, in particular, can pull liquidity from a wider pool of participants, and they can be composed with other crypto tools. That’s a big part of why this sector has been growing so quickly.

What prediction markets are (and why they keep coming back)

Prediction markets are mechanisms that let people trade on the outcome of events—as long as the outcome can be clearly determined. The concept has existed since at least the 16th century in various informal forms, but modern platforms make it accessible, liquid, and continuously priced.

You’ll see markets built around sports results, elections, court decisions, macroeconomic releases, product launches, and sometimes very specific “yes/no” events that can be verified. The premise is brutally simple: if you’re right, you make money; if you’re wrong, you lose the money you put up.

Where prediction markets become more than “bets” is in how they aggregate information. When lots of participants are buying and selling outcomes, the market price becomes a live signal of what the crowd believes, adjusted by how confident they are (and how much capital they’re willing to deploy).

How pricing works: shares, probabilities, and payouts

The standard model is that each outcome has shares that trade between $0.00 and $1.00. You can think of each share as a claim on $1.00 if that outcome wins. If an outcome is priced at $0.63, the market is implying roughly a 63% chance of that outcome occurring (at least according to that specific market’s participants).

That price isn’t static. It moves as new information arrives and as traders reposition. A debate performance, a court ruling, a sudden injury in a sports match—anything that changes expectations can shift the price. In other words, these markets can experience real volatility, especially when the event is high-profile and the narrative is moving fast.

When the event concludes, the market resolves. The winning outcome pays out at $1.00 per share, and losing outcomes drop to $0.00. If you bought the winning side at $0.63 and held through resolution, your profit is $0.37 per share (before any platform costs). If you bought the losing side, you lose what you paid per share.

One crucial detail: you’re usually not forced to hold until the end. In many markets you can sell whenever you want. That means you can trade the changing odds rather than only trading the final result.

Different market types you’ll run into

Not every prediction market is a simple “yes/no.” Platforms generally support a few core formats, and understanding them helps you avoid confusion when you’re scanning markets quickly.

• Binary markets: Two outcomes that resolve to $1 or $0 (Yes/No). Example: “Will it rain next Monday?”

• Categorical markets: Multiple outcomes, where only one wins. Example: “Who will win an election?”

• Scalar markets: Outcomes tied to a numeric value or range. Example: “Will the next census show the population above or below a certain number?”

Binary markets are the most common because they’re easy to verify and easy to price. Categorical markets can become more complex because the liquidity is split across multiple outcomes. Scalar markets often require extra care in how they define resolution—because the data source and the exact boundary conditions matter a lot.

Trading mechanics: you’re not locked in

The “betting” framing can be misleading because most modern prediction markets behave more like trading venues. If you buy shares of one outcome, you can usually sell them later—even if the event hasn’t happened yet. That’s how traders express changing convictions without waiting for resolution.

For example, imagine you expect a candidate to perform far better than expected in a debate. You might buy shares before the debate, anticipating that the implied probability will rise afterward. If it does, you can sell immediately after the debate and lock in gains without caring how the election ultimately resolves. You’re trading the change in odds.

This also means prediction markets can be used as hedges. If you have exposure to an outcome in the real world—business, investing, operational planning—you can sometimes offset that exposure by buying the opposite outcome as insurance. Whether that hedge is efficient depends on spreads, liquidity, and platform design.

Because these are markets, pricing is driven by supply and demand. That’s why you’ll often see them act like mini- exchanges for outcomes: order flow pushes prices, and prices then influence new order flow.

Why on-chain prediction markets use oracles

On-chain prediction markets need a way to connect real-world outcomes to on-chain settlement. That’s what oracles do: they take off-chain information (like election results, weather data, sports scores, legal outcomes) and make it usable for smart contracts to resolve payouts.

In many decentralized designs, resolution involves a combination of oracle submission and dispute processes. Someone proposes an outcome, others can challenge it, and the system relies on predefined rules to determine which data source is authoritative. Some ecosystems use well-known oracle providers like Chainlink for certain types of feeds, while other markets rely on governance-based or community-verification approaches depending on what’s being measured.

The core point is this: the market is only as credible as its resolution mechanism. If “who decides the outcome” is fuzzy, that fuzziness becomes a pricing discount, especially in high-stakes markets where disputes are likely.

The biggest names: Kalshi, Polymarket, Opinion, and Myriad

Even though the mechanics are similar, the platforms are not interchangeable. Some are centralized and operate like regulated venues; others settle markets on-chain and lean into crypto-native liquidity and composability. The differences matter when you’re thinking about access, market coverage, and settlement trust.

Kalshi

Kalshi launched in 2018 and, as of February 2026, is described as the top prediction market by volume according to DeFiLlama data. It reportedly reached an $11 billion valuation after a $1 billion funding round in November 2025.

Kalshi is often discussed as a more traditional, centralized venue compared with on-chain alternatives. That centralized structure can simplify user experience and liquidity provisioning, but it also means the platform itself plays a larger operational role in how markets are listed, managed, and resolved.

Polymarket

Polymarket launched in 2020 under founder Shayne Coplan and became one of the most recognizable names in crypto prediction markets. It made headlines after its founder was reportedly raided by the FBI in November 2024—an event Coplan characterized as politically motivated after the platform called the U.S. presidential election for Donald Trump.

Unlike centralized venues, Polymarket settles markets on-chain, which is a major part of its identity. In October 2025, it was valued at $9 billion following a $2 billion investment from Intercontinental Exchange. In February 2026, the company filed trademark applications for POLY and $POLY, fueling speculation about a potential native token launch.

On-chain settlement can make markets more transparent and easier to audit, but it also increases the importance of oracle design, dispute resolution rules, and the overall integrity of the system.

Opinion

Opinion is an on-chain prediction market that launched in Q4 2025 on BNB Chain, backed by Binance founder CZ’s family office YZi Labs. In February 2026, it raised $20 million in a pre-Series A round, with backers including Hack VC and Jump Crypto.

Being built in the BNB ecosystem can influence user acquisition and liquidity pathways, especially when the product design is aligned with how retail crypto users already move capital around. It also tends to bring increased attention—and scrutiny—when market growth accelerates.

Myriad

Myriad launched in January 2025 from Dastan, the parent company of Decrypt and Rug Radio, and it positions itself as more than a betting venue. The idea is that prediction markets can reshape how information is produced and consumed.

By integrating with media outlets, Myriad aims to turn forecasting into a participatory layer of the news cycle. Dastan President Farokh Sarmad described the goal as realigning incentives “from the bottom back up.” Dastan CEO Loxley Fernandes framed it as letting users participate in the creation of the news cycle, help identify sources of truth, and be rewarded for doing so.

This “media-native” angle is one of the clearest ways Myriad differentiates itself. Instead of treating markets as purely financial instruments, it treats them as feedback mechanisms that can surface what participants collectively believe to be true—or likely to become true.

How Myriad works under the hood

Myriad is an on-chain prediction market, and like other decentralized designs, it needs a reliable method for pricing outcomes and ensuring there is enough liquidity for people to trade. In general, on-chain markets lean on two major approaches: order books and automated market makers (AMMs).

Order books match buyers and sellers based on posted orders, similar to a traditional exchange model. AMMs use formulas to price outcomes based on the balance of assets in liquidity pools. Myriad uses an AMM approach, which matters because AMMs can continue functioning even when liquidity is thin—there doesn’t need to be a perfect counterparty at the moment you want to trade.

Another defining feature is that liquidity can come from anywhere. In centralized prediction markets, the platform (or its designated market maker) typically provides most liquidity. In an AMM-based design, any user can contribute liquidity to a market. That can help scale liquidity faster, although it also introduces new dynamics around incentives and liquidity-provider exposure.

On-chain prediction markets like Myriad use incentive structures to attract liquidity and keep markets tradeable over long time horizons. When you participate in a market, you receive shares in the outcomes, and those shares can often be traded while the market remains open. That flexibility is important for markets that resolve weeks or months in the future.

Myriad’s constant function design keeps the total number of shares in a market’s pool consistent. When trading activity creates imbalances—by adding or removing shares from one side—prices adjust, and shares are redistributed between the trader or liquidity provider and the pool. That’s the AMM doing its job: pushing price to reflect the new distribution of belief (and capital) in the market.

Why prediction markets are growing so fast

One of the most telling signals is volume growth. According to a February 2026 report from blockchain security firm CertiK, prediction market volume jumped from $15.8 billion in 2024 to $63.5 billion in 2025. Growth at that pace tends to attract both mainstream attention and regulatory focus.

Media treatment has also shifted. Mainstream outlets have increasingly referenced prediction market odds alongside traditional polling, including mentions from publications like the Wall Street Journal and Newsweek. That doesn’t mean prediction markets are always “right,” but it does show they’re being treated as a meaningful signal rather than a fringe curiosity.

Decentralized markets argue they can be more efficient because fewer intermediaries can mean fewer fees. They also highlight global accessibility: if you can access crypto rails, you can access markets. Some users also value the privacy characteristics that can come with crypto-based participation, depending on how the platform is designed.

At the same time, that global accessibility creates friction with regulation, because gambling law, securities law, and derivatives law vary widely across jurisdictions. What is permitted in one place can be restricted in another, and the compliance burden grows as platforms become more visible.

Regulatory pressure and operational challenges

Prediction markets sit in a complicated legal zone, and crypto prediction markets have attracted meaningful scrutiny. A U.S. Commodity Futures Trading Commission (CFTC) spokesperson has previously noted (in response to questions about Augur) that publishing code onto a blockchain does not remove an entity’s obligation to comply with relevant laws and CFTC regulations.

In 2022, Polymarket received a $1.4 million fine from the CFTC, which accused the platform of facilitating unregistered bets. Later developments suggested a shift in the regulatory arc: in July 2025, both the DOJ and CFTC reportedly wound down investigations into Polymarket. Shortly after, the platform acquired a U.S. options exchange, described as a meaningful step toward expanding and potentially returning to the U.S. market.

International pushback continued into early 2026, with Polymarket facing bans in Portugal and Hungary. In the U.S., state-level actions also created obstacles: Kalshi was temporarily banned in Massachusetts following a preliminary injunction in January 2026 (an action later challenged in federal court), and Polymarket received a temporary restraining order from a Nevada state court in February 2026.

Beyond regulation, the sector also faces structural and integrity concerns. CertiK’s February 2026 report warned about issues including wash trading and hybrid security threats—problems that can emerge when growth accelerates faster than market structure and monitoring tools can keep up. These are not theoretical concerns; they directly affect liquidity quality, pricing credibility, and user trust.

Even with those headwinds, adoption appears supported by a broader cultural shift. A January 2026 survey found that nearly a third of Americans expect online betting to become a bigger and more important part of culture, with younger consumers showing higher awareness of prediction market platforms like Polymarket and Kalshi.