What Are Prediction Markets? A Data-Driven Explainer

A contract trading at $0.65 on a prediction market means the market collectively estimates a 65% probability that the underlying event will occur. If the event happens, the contract pays $1.00. If it does not, it pays $0. This price-as-probability mechanism is the core innovation that makes prediction markets useful as forecasting tools.

How Do Prediction Markets Work?

Prediction markets are exchanges where participants buy and sell contracts tied to future events. Each contract resolves to either $1 (event occurred) or $0 (event did not occur). The current trading price represents the market’s real-time probability estimate, derived from the aggregate information and beliefs of all participants.

The mechanism is straightforward: participants who believe an event is more likely than the current price indicates will buy contracts, pushing the price up. Those who believe the probability is overstated will sell. The resulting price represents a dynamic equilibrium of all available information.

This differs fundamentally from polls (which sample opinions) and expert forecasts (which rely on individual judgment). Prediction markets create a financial incentive for participants to incorporate all relevant information, including information they might not share in a survey.

What Types of Prediction Markets Exist?

Three distinct models operate today:

Regulated real-money exchanges like Kalshi operate under CFTC oversight. Users deposit US dollars, trade event contracts on a central order book, and receive regulated settlement. These platforms function like any other derivatives exchange.

Blockchain-based platforms like Polymarket use cryptocurrency infrastructure. Users deposit stablecoins (typically USDC), trade through automated market makers or order books on-chain, and resolution is handled by decentralized oracles. Liquidity tends to be deeper on high-profile markets.

Community forecasting platforms like Metaculus use no real money. Forecasters stake their reputation on probability estimates, and accuracy is tracked through scoring rules. Despite the absence of financial incentives, these platforms have demonstrated strong calibration in academic studies.

Each model has tradeoffs. Regulated exchanges offer legal certainty but geographic restrictions. Blockchain platforms offer global access but require crypto knowledge. Community platforms are free and accessible but lack the financial incentives that theory suggests should improve accuracy.

Why Are Prediction Markets Useful?

The core utility is information aggregation. A prediction market price synthesizes the beliefs of hundreds or thousands of participants — each with different expertise, data sources, and analytical frameworks — into a single number.

Academic evidence supports their effectiveness. Research from the Iowa Electronic Markets, operating since 1988, demonstrated that election prediction markets outperformed major polls in 74% of head-to-head comparisons. The theoretical basis draws from Hayek’s insight that market prices aggregate dispersed information more efficiently than any central planner.

Our analysis across platforms tracks this accuracy in real time. The Odds Reference dashboard displays current prices across multiple platforms, allowing direct comparison of how different markets price the same event.

What Can You Predict on a Prediction Market?

Markets cover a broad range of categories:

• Politics and elections — the highest-volume category, covering everything from presidential races to congressional seats and policy outcomes
• Economics — Federal Reserve rate decisions, GDP growth, inflation, recession probability
• Technology and AI — AI benchmark milestones, product launches, company valuations
• Science and health — FDA approvals, clinical trial outcomes, space exploration milestones
• Sports and entertainment — Award shows, box office performance, championship outcomes
• Geopolitics — International conflicts, trade agreements, diplomatic outcomes

Platform coverage varies. Kalshi focuses on economics, politics, and climate. Polymarket offers the broadest selection. See our platform comparison for a full breakdown of what each platform covers.

How Reliable Is Prediction Market Data?

Reliability scales with liquidity. Markets with hundreds of active traders and significant volume produce prices that closely track actual outcome frequencies. Thin markets — those with few participants and low volume — are noisy and should be interpreted with caution.

Our dataset shows that markets with daily trading volume above $10,000 demonstrate meaningfully better calibration than markets below that threshold. The price on a deep Kalshi or Polymarket market reflects genuine information aggregation. The price on a market with three participants and $50 in total volume is closer to noise.

This is why cross-platform comparison matters. When the same event trades on multiple platforms, price convergence (or divergence) signals how confident the market collectively is. The Odds Reference dashboard tracks these cross-platform spreads automatically.

Key Takeaways

• Prediction market prices directly represent probability estimates: $0.65 = 65% implied probability
• Three models operate today: regulated exchanges (Kalshi), blockchain platforms (Polymarket), and community forecasting (Metaculus)
• Academic research spanning decades shows prediction markets outperform polls and expert panels in most binary forecasting contexts
• Reliability correlates strongly with liquidity — deep markets produce accurate prices, thin markets produce noise
• Cross-platform price comparison reveals where the market is confident and where genuine uncertainty exists