Original | Odaily Planet Daily (@OdailyChina)
Author | Azuma (@azuma_eth)
On the evening of April 2, Polymarket, the leading prediction market platform, officially announced the integration of the Pyth Network oracle service, which will serve as the data source for settling a new batch of prediction events related to traditional assets on Polymarket.
According to statements from Polymarket and Pyth Network, this initial rollout will cover commodities such as gold, silver, WTI crude oil, and natural gas; over a dozen U.S. stocks including NVIDIA, Apple, Tesla, Coinbase, and Palantir; as well as major stock indices and select exchange-traded funds (ETFs)—such as “Will gold rise or fall in the next hour?” or “Will silver be above or below a target price by a certain time?”
The Pyth Network will provide real-time price data via WebSocket, and Polymarket will sample this data every second to publish live charts, enabling traders to continuously see their position relative to the market.
Mustafa Aljadery, Product Lead at Polymarket, stated in a statement: “Millions of dollars in predictions often hinge on a single price point, so absolute data accuracy is essential—Pyth Network provides this assurance, enabling Polymarket to further expand into high-risk financial markets.”
Polymarket's journey toward oracle expansion
This is not the Polymarket extended oracle service.
Polymarket initially relied primarily on UMA's Optimistic Oracle mechanism. UMA’s logic is essentially a “social consensus oracle” — proposers submit outcomes, challengers initiate disputes, and voters make the final ruling. This mechanism is well-suited for subjective, unstructured events without a single definitive answer, such as political elections, policy changes, and social trends.
However, subjective judgment often also implies room for controversy. Historically, Polymarket has sparked community discussions about manipulation risks and fairness multiple times due to settlement disputes involving UMA.
In September 2025, as Polymarket began prominently featuring cryptocurrency price movement markets, it urgently needed to introduce a more deterministic data source to minimize the potential for human intervention. To this end, Polymarket partnered with Chainlink at the time, combining Chainlink Data Streams (providing low-latency, timestamped market prices) with Chainlink Automation (executing on-chain result settlement at predefined times), enabling automatic and rapid settlement of BTC, ETH, and other cryptocurrency price movement markets on Polymarket, while allowing users to view low-latency, verifiable prices for related assets in real time.
In a sense, the integration with Chainlink marks Polymarket’s first expansion beyond “socialized consensus forecasting” to “automated price determination,” but Polymarket’s goals clearly extend beyond the cryptocurrency market.
Unlike Chainlink, Pyth Network’s data is provided directly by global trading firms, exchanges, market makers, and banks that actively participate in pricing across global markets. Pyth Pro sources data from the highest-quality publishers on the network, including Jump Trading, Blue Ocean, LMAX, and Jane Street. Perhaps due to its global market orientation, Polymarket ultimately selected Pyth Network as its data source for traditional financial assets.
Polymarket's ambitions revealed
With the partnership with Pyth Network finalized, Polymarket has established a clear multi-layered oracle architecture:
- UMA: The non-standard events layer, responsible for political, social, breaking news, and macro events;
- Chainlink: A crypto asset layer responsible for on-chain price feeds for assets like BTC and ETH, as well as automated price settlement;
- Pyth Network: A traditional finance layer providing high-frequency price data for traditional assets such as U.S. stocks, commodities, and indices, supplied by institutions.
From UMA, representing non-fungible events, to Chainlink, focused on crypto-native markets, and now Pyth Network, which targets global financial markets, each time Polymarket integrates a new oracle service, it pushes the platform further into broader markets. Expanding the oracles is essentially expanding the scope of “tradeable futures”—the more data sources, the more dimensions of the real world become available for betting.
If this logic continues to evolve, the potential markets Polymarket could incorporate are nearly limitless—macroeconomic data, corporate earnings reports, sporting events, weather changes, and even AI model releases could all be integrated through various oracles, as long as verifiable data sources exist. The uncertainties of the real world will be continuously broken down into bettable events.
From this perspective, Polymarket’s ultimate potential may extend far beyond a simple prediction market—it could become a “future trading platform” capable of encompassing all forms of uncertainty. When all kinds of uncertain events can be uniformly integrated into a single mechanism, everything becomes bettable and everything becomes priceable. Oracles are merely a technical extension, but what they point to is a one-stop super-platform taking shape, one that far exceeds everyone’s expectations.