TLDR; On-chain prediction markets are booming, and oracles are the best infra-related opportunity. As the core of the settlement mechanism, oracles determine what topics prediction markets can support and whether they can operate accurately and efficiently. Currently, Polymarket's oracle is led by UMA, supporting subjective prediction markets, which account for 80% of the market. Chainlink has been introduced to settle the remaining 20%. Python was introduced to solve the problem of on-chain data for the Kalshi prediction market, while other oracle solutions focus primarily on AI. As the only subjective settlement solution, UMA has established a strong barrier to entry through its products and operational experience. However, issues such as long settlement times and manipulation by large investors still exist, which fundamentally limit the development of new market types for prediction markets like Polymarket. This creates space for new solutions, including the introduction of AI agents, solutions to manipulation issues, continuous/combinatorial market oracles, permissionless/long-tail market oracles, and event-driven DeFi integration for prediction markets. Background Crypto has entered the era of applications. In the previous era, infra projects were driven by enabling applications. Memecoin drove Dex infra, AI agents drove Tee infra, and Yield drove DeFi infra. The burgeoning prediction market may drive oracle infra. Prediction markets have become a new growth engine for Crypto. The period from 2024 to 2025 saw a qualitative shift from niche experimentation to mainstream product-market fit (PMF) applications: During the 2024 US presidential election, Polymarket's trading volume skyrocketed from $73 million to $2.63 billion (a 48-fold increase), while Kalshi's reached $1.97 billion (a 10-fold increase). The prediction market as a whole has reached $15.7 billion in cumulative trading volume. ICE, the parent company of the New York Stock Exchange, invested $2 billion in Polymarket, and many well-known hedge funds have already entered prediction market trading or are exploring ways to participate. On the regulatory front, the CFTC approved Kalshi's election contract. Meanwhile, Polymarket, through its acquisition of QCEX, will re-enter the US market in a legally binding manner via a mobile app. Polymarket has repeatedly hinted at the potential of its token and crypto ecosystem. These various factors will serve as catalysts, and the explosion of the prediction market is undeniable. Prediction markets are specifically categorized into two types. The first is subjective questions, which often focus on news events related to politics, culture, economics, and sports, such as the presidential election and the World Cup. Questions and outcomes are defined using natural language, and some conclusions are subjective, such as the question "Is Zelensky wearing a suit?" - what constitutes a suit. Another type is price markets, similar to binary options products for cryptocurrencies and stocks, but with a simpler and more accessible model. For example, "Will the price of BTC reach $XXX at a certain time?" Currently, UMA and its optimistic oracle are the only settlement providers for subjective markets. For any decentralized, unstructured data market, or one that requires subjective judgment, there is currently no other solution. UMA addresses this problem through an optimistic approach similar to optimistic rollup (with results presented, accepted by default if undisputed, and further adjudication and penalties if disputed). Structured data oracle services are primarily price data markets. These markets, such as "Will the price of BTC reach $XXX at a certain time," can be better resolved directly through price oracles like Chainlink. In fact, Chainlink's routing for resolving price disputes already existed within UMA's existing escalation manager. Polymarket's direct collaboration with Chainlink enables faster resolution. Currently, prediction market oracles still require numerous improvements in mechanisms and user experience, including settlement time, incentive models, data continuity, and permissionless settlement. Prediction markets will bring new opportunities for oracle product and architectural innovation. Why Oracles Are Important: Settlement can be categorized as centralized or decentralized. Most early prediction markets adopted centralized solutions. Decentralized solutions are costly and difficult to implement. However, to protect prediction markets from a single point of control and to ensure their value as a "media of truth," decentralized settlement solutions are necessary, which in turn rely on oracles. This bottleneck technology determines whether an on-chain prediction market can sustainably operate independently and support a large market. This is why BSC needs to first solve the oracle problem if it wants to develop a prediction market project. At the same time, oracles are also needed to generate value from prediction market data and circulate it on-chain. Oracles can use prediction market results as a data source for on-chain use. The collaboration between Kalshi and Pyth focuses on this. Prediction market data serves as a primitive, allowing on-chain application developers to create new products based on it. Examples cited by Pyth include: Developing futures markets based on real-world events. These protocols can use Kalshi's real-time odds as a baseline, automatically adjusting prices as the source market fluctuates. DeFi protocols can build conditional products that react to real-world probabilities. Insurance products tied to political outcomes; NFT series that evolve based on election results; and gaming tournaments that unlock prize pools when specific events occur. To understand UMA's current monopoly position, we can measure it by TVS in the prediction market. TVS (total value secured) measures the total value secured by the oracle. Currently, Polymarket holds 80% of the market share, while Chainlink is used for the remaining 20% of the price market. ▲ source: Defilamma In its business model, Stable prioritizes market share expansion over revenue in the near term, leveraging gas-free USDT payments to acquire users and build payment traffic. Long-term profitability will primarily come from within its consumer applications, supplemented by select on-chain mechanisms. Beyond USDT, Stable also sees significant opportunities in other stablecoins. As part of PayPal Ventures' investment in Stable in late September 2025, Stable will natively support PayPal's stablecoin, PYUSD, and promote its distribution, enabling PayPal users to pay "directly with PYUSD" and pay gas fees in PYUSD. This means that PYUSD will also be gas-free on the Stable chain—extending the ease of use of the USDT payment rail that attracted PSPs to it to PYUSD as well. Polymarket currently uses UMA's MOOV2 (Managed Optimistic Oracle V2) to settle markets. When a market matures and requires settlement, the market closes, and the proposer submits the result. This result is considered correct if it remains unchallenged within the dispute window. If challenged, UMA's decentralized arbitration mechanism intervenes to render a verdict. The UMA optimistic oracle has gone through four versions, evolving from an initial focus on synthetic assets to a continuous evolutionary adaptation to prediction markets: Polymarket currently supports MOOV2 contracts. This change follows the approval of the UMIP-189 governance proposal by UMA on August 6. Previously, a problem with OOV2 was that many proposals were submitted prematurely and inexperienced, which often led to disputes and delayed market settlement for up to several days. Risk Labs, the entity behind UMA, has released an initial whitelist of 37 addresses. This list includes employees from Risk Labs and Polymarket, as well as users with over 20 proposals and an accuracy rate exceeding 95%. This is the current prototype of UMA's "meritocratic" governance. As the most widely used oracle, UMA's multiple version iterations demonstrate its deep understanding of prediction market use cases and its robust ecosystem and infrastructure. However, UMA's current performance is not perfect, primarily due to two issues: The risk of manipulation by large investors and the long time it takes for results to be finalized. Regarding manipulation risk, UMA's Data Verification Mechanism (DVM) relies on token holders voting to determine data results. While a minimum vote amount (GAT, approximately 5 million UMA) and a voting consensus threshold (SPAT, 65% consensus) are implemented to ensure security, the token's low market capitalization and highly concentrated distribution make it easy for large investors to influence voting results. In 2024, on the Polymarket platform, a market question about whether Ukraine would sign a mining agreement with the United States was ruled "YES" by UMA, despite the fact that this was not the case in the real world. On-chain data shows that a single large investor, through multiple addresses, staked approximately 5 million UMA, accounting for approximately 25% of the total votes; just two large investors controlled over half of the effective voting power. This centralized structure encourages small voters to "follow the large investors" to avoid penalties. UMA's penalty rate for incorrect voting is only approximately 0.1%, which is extremely low, significantly increasing the actual risk of manipulation by large investors. Currently, UMA's MC is 100 million, but the OI of the polymarket it supports is >200 million. This reflects the asymmetry of economic relations and creates opportunities for malicious manipulation. Secondly, UMA's dispute resolution process is lengthy in terms of result confirmation speed. After submission, any data request undergoes an "active period," automatically confirming only if no challenge is received. If challenged, it enters a DVM voting phase, typically lasting 48 to 96 hours. If the threshold is not met, a new round of voting is required, potentially extending settlement to several days. This delay is particularly pronounced in scenarios requiring rapid settlement, such as prediction markets and leveraged products. User funds are locked up and cannot be reused, increasing arbitrage opportunities caused by information lags. While UMA offers advantages in decentralization and censorship resistance, its high token concentration and long settlement cycles present manipulation risks and efficiency bottlenecks. To serve as a mainstream data oracle in a wider range of prediction scenarios, UMA needs further optimization. UMA is currently exploring new disruptive architectures. It is collaborating with EigenLayer to research and explore leveraging EigenLayer's staking system to develop next-generation oracles. It is also undertaking new AI initiatives. The Optimistic Truth Bot is a proposer agent in prediction markets. It listens to Polymarket questions 24/7, immediately proposing the most likely answer and waiting for challenge, significantly reducing settlement times. You can find specific markets through the @OOTruthBot Twitter account. Chainlink is a long-established DeFi oracle service provider. Its product capabilities proactively acquire and aggregate off-chain data (such as prices) from multiple sources, delivering it on-chain through a network of nodes. Polymarket is currently collaborating with Chainlink to serve the price data prediction market. Chainlink routing was previously involved in UMA's escalation manager dispute escalation system. This means that Polymarket has long been a Chainlink user, and the current integration with Chainlink makes this even more direct. Pyth is currently collaborating with Kalshi, primarily to disseminate Kalshi data. Kalshi data is regulated by the CFTC, so its value lies in disseminating compliant data, primarily sports and economic data, as a data source. This is similar to a compliant casino selling its real-time sports event data to downstream players. New Players primarily focus on providing verification services through AI. Currently, the agent's role is more focused on submitting settlement intent. However, since AI is available 24/7, it can ensure efficient settlement in any market, especially high-frequency markets created without permission. As mentioned earlier, UAM is exploring solutions resulting from AI participation through OO Agent. Solana's XO Market is a good example. It uses AI models to extract and analyze data from trusted APIs (such as real-time news and sports data sources) and rapidly resolve yes/no questions through pattern recognition, achieving a relatively high success rate. Some of the oracle projects on BSC, which CZ recently mentioned, are also exploring this direction. What opportunities remain for oracles? The explosion of prediction markets has placed higher demands on oracles' support scope, intelligence, real-time performance, and incentive design. Currently, mainstream oracles still face bottlenecks: UMA's settlement time is 24-48 hours, the average dispute resolution cycle takes several days, settlement dispute rates are high, and voting power is concentrated among large investors. There is still room for optimization of centralization and efficiency, and the types of markets it can support are still limited by its architecture, which may be the biggest obstacle to Polymarket's market innovation. AI-assisted AI can understand natural language, making it highly suitable for markets such as politics, sports, and social events. Previously, human judgment led to numerous semantic differences and subjective factors, leading to frequent disputes. AI oracles can significantly improve this problem through multi-source verification and neutral language models. Anti-manipulation: UMA token holders are both voters and stakeholders, creating a structural conflict. A single large holder can sway the voting outcome with just 5 million UMA. Regarding token design, how can we ensure sufficient economic security? Beyond token design, how can we establish anti-manipulation mechanisms (such as real-time flagging of malicious addresses and detection of group malicious behavior)? Multi-stage and subjective predictions, real-time data and continuous price feeds. The prediction market has long focused on binary settlement, resulting in a significant reduction in information dimensionality. Future socially aware oracles will need to access a wider range of data sources and employ dynamic models for comprehensive evaluation of diverse data. After discussing DeFi projects related to Polymarket, I realized there's significant design potential for dynamic settlement data during market operations. Supporting more sustained prediction markets, such as real-time, in-game trading for sports events, presents significant opportunities in continuous price markets or combinatorial markets like parlay, but currently, oracles don't support this. Permissionless Scaling and Long-Tail Markets In the future, permissionless prediction markets will reach asset creation rates similar to those of PumpFun. The massive market settlement demands will render UMA's current manual review and upgrade model unworkable. How to quickly address the creation, settlement, and liquidity fragmentation issues of long-tail markets may be addressed from a top-down perspective using oracles. Event-driven DeFi Integration: When prediction markets are integrated with DeFi, on-chain event probabilities can directly impact lending and derivative pricing. For example, when the probability of an interest rate hike exceeds 90%, lending leverage can be automatically reduced. This combination of oracles and prediction markets may lead to innovation in DeFi.
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