Dune and Keyrock teamed up to release a study of prediction markets. As explained in the detailed update shared by Dune, prediction markets may feel like somewhat of a modern invention or fairly recent development, but their roots stretch back for a long time actually. Dune also mentioned that the so-called renaissance merchants speculated on papal succession. London coffeehouses in the 1700s traded odds “on political outcomes and shipping routes, markets so influential that they eventually helped shape modern insurance.”
So basically, Dune Analytics pointed out that the idea has always been the same: use markets “to aggregate dispersed knowledge and express it through prices.”
The report from Dune Analytics further explained that blockchain rails, mobile distribution, “real-time data feeds, and a digitally native population have allowed prediction markets to finally reach the scale required to unlock their full potential.”
And scale is everything: the more participants, the “deeper the liquidity, and the more diverse the information, the more accurate prediction markets become.”
Now, prediction markets are evolving “from historical curiosities into a new layer of global financial and information infrastructure.:
Traditional forecasting tools like polls, pundits, and “surveys rely on sentiment or expertise.”
Prediction markets “work differently.”
The report also stated that they use financial incentives “to reward accuracy and penalize errors, forcing participants to reveal what they truly believe.”
Prices update continuously as new “information arrives, transforming scattered insights into a single, real-time probability estimate.”
This mechanism is why prediction markets often “outperform expert models, political polling, and sentiment-derived analysis.”
Across thousands of resolved markets, prediction platforms “exhibit Brier scores around 0.09, placing them among the most accurate large-scale forecasting systems ever measured.”
Importantly, these forecasts remain “well-calibrated far from resolution, often surfacing shifts in sentiment well before headlines or official data releases.”
Modern prediction markets “differ in architecture, design, and regulatory approach, but they all revolve around the same four layers: how markets are created, how trading works, how collateral is managed, and how outcomes are resolved.”
Modern prediction markets span “a wide design spectrum.”
On market creation, approaches now reportedly range from Kalshi’s fully permissioned, regulator-approved contracts, through Crypto.com’s controlled listings and Polymarket’s curated model, “to fully permissionless systems like MYRIAD, Limitless, and Opinion, where anyone can spin up markets tied to media content, short-interval crypto moves, or macroeconomic releases.”
Trading and liquidity architectures are “just as diverse.”
At one end of it all, Kalshi and Polymarket now “operate order-book markets, with Polymarket blending offchain matching and onchain settlement.
Limitless sits in the middle, combining a CLOB “with onchain AMMs to support faster, higher-frequency trading, while MYRIAD and Opinion lean fully onchain, using AMMs and shared liquidity pools designed for composability and capital efficiency.”
Across all models, custody and settlement, “whether centralized clearinghouses or onchain escrows, shape how capital is held and how liquidity scales.”
Markets remain active across “sports, politics, and crypto, with Sports driving daily trading flow and politics anchoring large open interest, especially during major election cycles.”
But growth is “no longer sports-led.”
In 2025, non-sports categories are driving expansion “across both volume and open interest: Economics and Tech & Science lead volume growth, while Economics and Social & Culture dominate open interest growth.”
As a result, prediction markets are “broadening from entertainment-driven speculation into tools for macro, policy, and financial insight.”
Notably, this momentum is not actually the result of a single platform.
It reflects a category-wide shift: more visibility, “more liquidity, better forecasting accuracy, and an expanding user base across the entire ecosystem.”
The scale of prediction markets point “to clear product–market fit.”
But growth alone does not explain “why institutions, corporations, and platforms are increasingly paying attention.”
The more important question is “what these markets can actually be used for.”
A core argument of this report is that prediction markets function “as a class of derivative that provides clean exposure to discrete events rather than the noisy proxies traditional finance relies on.”
While existing markets can hedge rates, currencies, and equities, they cannot directly “hedge the events that drive those variables.”
Prediction markets close that gap, “enabling risk to be managed at its source.”
Institutions can use event contracts to “hedge elections, policy decisions, inflation releases, or geopolitical outcomes.”
Corporations can run internal prediction markets “to forecast product launches, sales cycles, or operational risks, a method that has repeatedly outperformed standard forecasting approaches.”
Crypto protocols can use prediction markets to “price TGEs, estimate future valuations, and hedge token listing outcomes long before a token actually trades.”
The long-term trajectory of prediction markets depends “on structural dimensions: liquidity, retention, regulation and integration.”
As clarified in the update from Dune, the core function of prediction markets is to “aggregate dispersed knowledge into a single signal—a price—that often surfaces what matters in society well before headlines or expert commentary.”
Event contracts allow individuals, institutions, and corporations “to hedge real exposure, from elections and macro releases to product launches and governance decisions, demonstrating utility far beyond speculation.”
Their flexibility make prediction markets easy to “embed across domains, from media and finance to sports, education, and consumer applications.”
As these markets continue to mature, Dune’s report concluded that they expect an accelerating wave of “adoption from institutions, media platforms, fintechs, and consumer applications that recognize prediction markets as powerful engines for hedging, forecasting, and engagement.”