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Prediction markets work like financial exchanges for future events. Instead of trading stocks or commodities, people trade contracts whose value depends on whether an event happens. They buy and sell contracts whose prices reflect collective expectations about real-world outcomes.
These contracts are priced to reflect participants’ beliefs about the likelihood of a particular event occurring. So, if a majority of people believe an event is likely, they will buy contracts that cover that outcome. This drives its price higher. An example of this is people using platforms such as PredictIt to buy contracts on potential US election outcomes. The popularity of these platforms demonstrates how this model is evolving into a hybrid system that blends elements of finance, information markets, and speculation.
A Hybrid Between Fintech Innovation and Event-Driven Trading
Prediction markets function similarly to financial exchanges. The major players in the industry, such as Kalshi and Polymarket, structure tradeable contracts that involve a Yes/No question about a future event, for example, “Will the Seattle Seahawks win the NFL?” In this situation, yes-or-no contracts exist, each typically settling at $1 if correct and $0 if incorrect.
The price of a contract reflects the perceived probability of the situation occurring. So, a price of $0.68 reflects a perceived probability of 68%. Participants trade based on information, analysis, and sentiment. They can enter and exit positions until the outcome of an event is known.
This structure resembles derivatives or options markets, where traders speculate on future conditions rather than owning the underlying asset.
Information Aggregation Mechanisms
In academic research, prediction markets are often described as information aggregation mechanisms. As such, experts have long argued that these markets can be better predictors than polls or expert forecasts. This idea relates to the concept of the “wisdom of crowds,” popularized by James Surowiecki.
Surowiecki’s theory suggests that aggregating individual estimates means that any errors are cancelled out. This, in turn, provides superior outcomes in forecasting and decision-making.
In addition, research in Behavioral Economics suggests that markets incentivize individuals to reveal information, and any new information causes prices to change rapidly. This high volume of real-time information is a major reason why many people believe the markets outperform individual thoughts and decisions.
Why Sports and Events Are Natural Entry Points
Sports outcomes are particularly well-suited to prediction markets because events occur frequently and outcomes are easily measured. Sports events are also widely followed. According to the S&P Global Market Intelligence Kagan US first-quarter 2025 Consumer Insights survey, nearly three-quarters of adults surveyed in the US watch sports, with most watching at least one of the top four sports leagues: the NFL, MLB, NBA, and NHL.
The outcomes of sporting events are also resolved quickly, which makes them ideal for event-driven trading environments. In this sense, prediction markets are similar to sports betting, but with a structural difference: traders interact with market prices rather than fixed bookmaker odds.
Regulatory and Financial Evolution
The biggest barrier to mainstream adoption of prediction markets remains regulation. In the United States, platforms like Kalshi operate under oversight from the Commodity Futures Trading Commission, framing event contracts as financial derivatives rather than wagers. Decentralized platforms such as Polymarket operate using blockchain infrastructure, pushing the model toward decentralized finance (DeFi). The tension between financial innovation and gambling regulation, when predictions involve sporting event outcomes, will likely shape the industry’s future.
If regulatory acceptance expands, prediction markets could evolve into a new category of financial products. Rather than replacing gambling or traditional finance, they may sit between them, creating a market where information itself becomes the tradable asset.
