What happens when you take the logic of a prediction market and put it on crypto infrastructure?

When I was little, I used to play a game with my older sister.

I would tell her that Mum was coming home from work while she was rummaging through her wardrobe - something that always made her nervous because she was afraid Mum would catch her. Eventually, my sister came up with a way to stop me from lying. If I really had seen Mum coming home, she said, Mum would be friendly when she arrived. If I was lying, she would come in angry. For a while, I stopped tricking her. Then I realised what her little game was doing: she had turned my claim into a bet. There was something at stake, and suddenly my incentive to tell the truth had changed.

That little game captures something fundamental about prediction markets. Instead of simply saying what we think will happen, participants trade contracts whose value depends on the outcome of a future event. The resulting price can be read as a market-based estimate of the probability of that event occurring. The idea itself is not new, nor is it inherently tied to crypto. But crypto infrastructure offers a new set of rails on which these markets can operate - with 24/7 trading, programmable settlement, and blockchain-based transparency.

And this is where the story gets more interesting.

For the last two years at The Paypers, we've been trying to bridge the knowledge gap between TradFi and DeFi. Somewhere along that journey, prediction markets led me back to a much older idea: Friedrich Hayek's 1945 essay, The Use of Knowledge in Society.

Hayek's argument was, in essence, that economically useful knowledge is dispersed. A trader may know something about a local shortage; a shipper may know which routes have spare capacity; an individual may have information about a particular circumstance that nobody else sees. No central authority can collect all of this knowledge in real time. Yet markets have a way of bringing fragments of that information together. Prices act as signals, compressing countless pieces of dispersed knowledge into something that other participants can use without necessarily knowing where that information came from.

Prediction markets echo this idea in a particularly direct way. Their prices attempt to turn the dispersed, partial knowledge and expectations of many participants into a single, continuously updated signal about what might happen.

This is part of what drew me to the subject in the first place. But then another question emerged: if prediction markets can exist perfectly well without crypto, what changes when they are built on crypto rails?

Platforms such as Kalshi and Polymarket offer two very different ways of approaching that question - one rooted in a centralised, regulated market structure, the other built around crypto-native infrastructure. So before getting into Polymarket, its architecture, and what crypto brings to prediction markets, let's start with the basics.

What are prediction markets?

A prediction market - also called a betting market, information market, decision market, idea futures, or event derivatives market - is a market where participants trade contracts tied to the outcome of a real-world event, using what they know or believe to bet on that outcome. Financial incentives reward those who predict correctly, while market prices serve as an aggregated, real-time estimate of the event's probability.

For a simple binary question - Will X happen? - a contract might pay USD 1 if X happens and USD 0 if it doesn't. If that contract trades at USD 0.65, the market is roughly expressing a 65% probability that X will happen.

But a market price is not automatically an objective probability. It is only as good as the information feeding into it - and that depends on who is trading, how much capital they are willing to risk, how liquid the market is, and whether participants have an incentive to reveal or distort what they know.

How do prediction markets work?

Prediction markets turn real-world events into tradable contracts. An event with a clearly defined, verifiable outcome - typically a yes/no question - is listed as a contract. Participants buy and sell it based on their expectations, with the price shifting as demand changes. Once the outcome is known, winning contracts settle at a fixed value, usually USD 1, while losing ones expire worthless.

This makes event contracts fundamentally different from stocks or bonds: their value isn't tied to earnings, growth, or the performance of an underlying company, but to whether a specific event occurs.

Markets have sprung up around sports and entertainment, economics, politics, and business and technology. The common requirement is that each event has a clearly defined outcome and a pre-specified source for verifying it - whether that's a league record, certified election result, or recognised authority's statement.

That clarity is what allows the market to settle objectively.

Why should anyone care?

This brings us back to Friedrich Hayek's 1945 essay The Use of Knowledge in Society, which I mentioned earlier. Hayek argued that economically useful knowledge is dispersed across individuals, much of it local, practical, and difficult to centralise. No single authority can gather all of it in real time. The price system, he argued, provides a way to aggregate this dispersed knowledge into signals that allow people to coordinate without needing to understand the entire picture.

Prediction markets echo this idea by asking whether the price of a contract can turn the dispersed information, expectations, and judgments of many participants into a single, continuously updated signal about what might happen.

The catch is that the signal is only as good as the market producing it. Thin liquidity, manipulation, skewed participation, and weak incentives to reveal information can all affect the price.

Prediction markets existed even before crypto

The concept is far from new. Early forms appeared as political betting, including wagers on papal succession dating back to 1503, while organised election betting on Wall Street was recorded as early as 1884. The modern electronic era began with the University of Iowa's Iowa Electronic Markets in 1988, followed by corporate forecasting experiments and, eventually, commercial platforms such as Polymarket and Kalshi.

What's changed is the scale - and, increasingly, the infrastructure. The 2026 FIFA World Cup offers a striking example. According to Chainalysis, blockchain-based prediction markets tied to the tournament generated USD 20 billion in volume from January 2026 through the end of the tournament, with nearly 400,000 wallets participating. During the five-week tournament, these markets generated USD 5.7 billion in trading volume.

The numbers illustrate how far prediction markets have moved beyond small forecasting experiments. They are now attracting hundreds of thousands of participants and billions of dollars in trading activity.

What does putting a prediction market on-chain change?

A prediction market doesn't need crypto to exist. But putting one on blockchain infrastructure could change how it is accessed, traded, and settled. Crypto rails can offer global, 24/7 access, stablecoin-based settlement, transparent on-chain transactions, and programmability. At the same time, they introduce a new set of questions around liquidity, oracle design, governance, regulation, and manipulation.

And this is where Polymarket and Kalshi become particularly interesting.

Enter Polymarket and Kalshi

Two platforms have come to define the prediction market space, and they represent different answers to the same underlying question: how should these markets be built and regulated?

Polymarket is the crypto-native example. Built on Polygon, an Ethereum layer-2 blockchain, it uses an on-chain architecture in which positions are represented by tokens and settlement is executed through smart contracts. Its current collateral token, pUSD, is an ERC-20 token on Polygon backed 1:1 by USDC.

This architecture gives Polymarket some of the characteristics that make crypto infrastructure attractive: crypto-native access, transparent on-chain transactions, and programmable settlement. But it also brings its own friction, from wallets and gas fees to the complexities of resolving events that happen in the real world.

That last point is particularly important. A blockchain can execute the settlement of a contract automatically, but it cannot know whether an election was won, a team won a game, or a particular event happened. Polymarket uses the UMA Optimistic Oracle and a predefined dispute process to bring that external information into the market. In other words, the blockchain can guarantee payout execution, but not the correctness of the real-world ‘truth’ feeding into it.

Kalshi took a different path. It is a US-based, CFTC-regulated Designated Contract Market built within the traditional financial system. Unlike Polymarket's crypto-native infrastructure, users can trade through conventional financial rails, without managing a crypto wallet, paying blockchain gas fees, or holding an on-chain settlement token.

That regulatory structure has helped Kalshi build a significant US presence, but it has not eliminated the regulatory debate. The company has faced state-level challenges over whether sports-related event contracts should be treated as financial derivatives or gambling. The legal question remains unsettled: in August 2026, the Ninth Circuit ruled that Nevada could regulate Kalshi's sports contracts under state gambling law, while a separate Third Circuit case involving New Jersey had reached the opposite conclusion.

The two platforms therefore represent different bets on how prediction markets should go mainstream. Polymarket started with crypto-native infrastructure and built around global, on-chain markets; Kalshi built within the US regulatory and financial system.

But that distinction is already beginning to blur. Polymarket has been moving toward a US-regulated presence, while Kalshi has been expanding beyond traditional event contracts. The more interesting question may therefore be less ‘crypto or traditional finance?’ and more which parts of each model are worth keeping.

The uncomfortable problems

Prediction markets sit in an awkward place between financial markets and gambling. Their supporters argue that putting money behind a forecast can make information more useful: if participants have something at stake, they have an incentive to bring their knowledge to the market and to price events they believe others have misjudged.

The same mechanism, however, can look remarkably similar to betting.

That tension becomes particularly important when we move from speculation to hedging. A company may use an event contract to protect itself against a specific operational or regulatory risk, much as it might use an insurance policy, option, or other derivative. For smaller businesses, prediction markets could potentially fill gaps that traditional financial institutions are unwilling or unable to serve.

The difficulty is drawing a clean line between using a market to manage risk and using it simply to speculate. The same contract can look very different depending on who is trading it and why.

That ambiguity is already playing out in regulation. In the US, federally regulated prediction markets can operate as derivatives markets, while states have challenged some sports-related contracts as gambling. Outside the US, the regulatory picture is even more fragmented, with some jurisdictions restricting or blocking access to platforms such as Polymarket.

The problem isn't only legal. It is also about whether these markets produce reliable information in the first place.

A price may look like a probability, but it is still the product of a particular group of traders, operating with different amounts of information, capital, and incentives. Thin liquidity can make prices easier to move; concentrated positions can distort the signal; and participants with privileged information can potentially profit before the wider market catches up.

This creates a paradox at the heart of prediction markets. Their greatest promise is that they can aggregate information that no individual possesses in full. But the same openness that allows information to enter the market also creates opportunities for speculation and manipulation. There is another problem: markets don't always just predict events. They can influence them. (e.g. Polymarket was under fire after a bet about a US-Ukraine rare earth mineral deal with President Donald Trump was resolved as ‘yes’ despite no such deal occurring.)

Once a public event is assigned a price, that price can become part of the information environment surrounding the event. Participants may react to the market's forecast, while people with privileged information may have an incentive to trade on it. Prediction markets therefore don't simply observe uncertainty; at sufficient scale, they can become part of the system that produces the outcome they are trying to predict.

The challenge for the industry is to capture the information and risk-management benefits of these markets without allowing speculation, manipulation, and consumer harm to overwhelm them.

Why financial readers should care

Zoom out, and prediction markets sit at an unusual intersection of information markets, financial markets, derivatives, and crypto infrastructure. Their potential applications extend beyond betting on elections or sports. They could be used for risk management, event hedging, corporate decision-making and insurance-like products, while blockchain infrastructure adds the possibility of programmable, 24/7 settlement. That makes prediction markets interesting not simply as a new form of speculation, but as an experiment in how financial markets might price uncertainty.

The question is whether they will remain primarily a new venue for betting - or evolve into another layer of financial infrastructure.

About author

Mirela Ciobanu is Lead Editor at The Paypers, bridging the knowledge gap between TradFi and DeFi. With a keen eye for industry trends, she is constantly on the lookout for the latest developments in crypto and blockchain. Closely connected with subject-matter experts in the digital assets space, Mirela amplifies your voice through compelling interviews, webinars, reports, and articles.

To share more ideas and get inspired, connect with Mirela on LinkedIn or reach out via email at mirelac@thepaypers.com.