Prediction Market Depth Survey: Polymarket's Mysterious Account's Precise Bets on Iran Incident Spark Controversy

In March 2026, a blockchain analytics report disclosed the trading activity of a mysterious trader on Polymarket: since 2024, the account has achieved a 93% win rate on large trades in bets related to events connected to Iran, netting nearly $967,000. The trading records show that the trader repeatedly opened positions within a few hours before major military actions by Israel and the United States—hours before Israel’s retaliatory strike against Iran in October 2024, hours before the U.S. airstrike on Iran’s nuclear facilities in June 2025, and hours before the joint U.S.-Israeli raid in February 2026, with precise timing in each case.

Most high-frequency traders’ win rates are only slightly above 50%, while this account’s overall win rate is 83% and its win rate on large trades is 93%—“too good to be real.” Judging from the four dimensions of profit size, bet timing, trade success rate, and on-chain account linkage, these features “strongly indicate the existence of insider trading activity.”

These bets are not isolated cases. Of six Polymarket accounts created newly in February 2026, all placed bets only on the single question of “whether the U.S. will launch an attack on Iran,” with total profits of about $1 million. In an earlier Venezuela-related incident, an account that was created only in December 2025 precisely bet on Maduro stepping down a few hours before the event erupted, with an ROI exceeding 13 times. New accounts, large sums of money, and precisely timed predictions—within an unregulated, non-transparent market, this trade bears all the hallmarks of insider trading.

When the economic incentive system of “collective intelligence” intertwines with the asymmetric gains of “information advantage,” the prediction market faces a fundamental challenge: are these astonishingly accurate bets the product of insider trading, or do they reflect what a prediction market as an “information aggregator” is supposed to do?

The platform’s dual role: from information aggregation to information arbitrage

The core logic of prediction markets is simple yet profound: participants use real money to price the probabilities of future events. The more supporters there are, the higher the contract price, which also reflects a higher implied likelihood of occurrence. This mechanism depends on two key elements: the diversity of participants and the reduction of information asymmetry. In an ideal state, the collective judgments of many independent decision-makers converge on the true probability of the event.

However, a series of anomalous betting incidents Polymarket has faced in recent years reveals a more complex reality: when participants with non-public information enter the market, market prices no longer reflect “collective intelligence,” but instead become an arbitrage tool for “information advantage.” The Iran-related trader placed bets hours before Israel’s retaliatory action in October 2024, hours before the U.S. airstrike on Iran’s nuclear facilities in June 2025, and hours before the joint U.S.-Israeli raid in February 2026—each time before the military action was announced.

Behavior in prediction markets—coordinated wallets establishing positions before major news, and exiting immediately after placing a single bet with high confidence—is highly similar to market manipulation as defined in traditional financial markets. In January and February 2026, four wallets turned roughly $40,000 into $872,000 by betting on U.S. military action against Iran.

The fundamental problem with this phenomenon lies in the fact that, in prediction markets, the boundary between being “in the know” and being “an insider” is extremely blurry. The platform’s core value is to incentivize informed parties to release information through betting, but when that information comes from government secrets or operational planning for military actions, this “release” crosses the boundary of law and ethics.

The logic of rule evolution: from a “open posture” to proactive compliance

Polymarket’s stance on “insider trading” has undergone a notable shift. In November 2025, the CFTC approved Polymarket’s return to the U.S. market, allowing it to operate under a federal regulatory framework as a designated contract market. Before that, Polymarket exited the U.S. market because it previously violated rules by serving U.S. users in 2022; in July 2025, a criminal investigation during the Biden administration was terminated, clearing the way for the platform’s return to compliance.

However, the regulatory environment tightened rapidly in 2026. On March 27, the governor of California signed an order banning administrative officials from profiting from prediction-platform bets using government insider information. The reason was that authorities found that some officials who could access federal sensitive information had bet at unusually precise times. At the federal level, senators jointly proposed bipartisan legislation to prohibit prediction markets from “contracts for transactions similar to sports or casino games.” The CFTC also issued guidance requiring prediction-market platforms to adopt specific measures to prevent insider trading.

In the face of this regulatory crackdown, on March 23, 2026, Polymarket officially updated its Market Integrity Rules, clearly banning three core types of insider trading: trading based on stolen confidential information, trading based on illegal sources of messages, and trading by those who could influence the outcome. At the same time, the platform upgraded to a multi-layer monitoring architecture—on the DeFi side, partnering with world-class monitoring institutions and relying on transparent on-chain records on the Polygon network; on the U.S. exchange side, building a three-layer defense system consisting of external technical monitoring, a real-time monitoring command center, and an NFA partnership.

Platform management had previously said that “it’s a good thing for insiders to have an advantage in the market.” The shift from a “competitive advantage” stance to a “ban” stance reflects a structural tension in the prediction market industry between explosive growth and regulatory compliance. In 2025, Polymarket’s cumulative trading volume reached $21.5 billion, accounting for nearly half of the total global prediction market trading volume; in January 2026, monthly trading volume also broke a record, exceeding $12 billion. By the end of February 2026, the global prediction markets’ cumulative notional trading volume had already reached $127.5 billion, with Polymarket leading at $56.07 billion.

How does insider trading undermine the price discovery function of prediction markets?

The impact of insider trading on prediction markets goes far beyond moral questions about the profitability of a single account. Its deeper effect is systematic erosion of the market’s core function—price discovery.

One key trend is that geopolitical events, macroeconomic outcomes, and developments in U.S. politics have already come to dominate trading activity in prediction markets, surpassing the crypto-native markets that once dominated these platforms. Specifically for Iran-related contracts, total trading volume has already exceeded $529 million, and highly sought-after prediction contracts tightly tied to geopolitics—such as whether “Supreme Leader of Iran, Khamenei, will step down soon”—have drawn significant interest. More than $74 million is betting that crude oil will break above $100, and more than $50 million is wagering whether U.S. ground forces will enter Iran within the year.

When markets involving national security and major economic interests are distorted by insider information, the consequences go far beyond losses to individual investors. From a macro perspective, there are at least three layers of impact.

First, the distortion of price signals. The core value of prediction markets is that their prices can be viewed as real-time estimates of the probability of events occurring. This function has been widely adopted by Wall Street institutions and mainstream media as a reference for decision-making. If market prices are dominated by insider trading, ordinary participants’ willingness to place bets will drop significantly, and the “collective intelligence” effect of the market will gradually be replaced by the “information advantage” effect.

Second, shrinking market liquidity and a structural split in participation willingness. Insider trading erodes the foundation of trust among market participants. When many users believe market prices are being manipulated by a small group with access to non-public information, real trading demand will shift to other information channels, and liquidity will drain away accordingly.

Third, a reverse catalyst for industry regulation. Polymarket’s repeated clouds of suspicion around insider trading have directly driven stricter regulatory responses. From California banning administrative officials from participating in prediction markets, to legislators proposing comprehensive bans, to the CFTC requiring platforms to establish mechanisms to prevent insider trading—these regulatory actions aim to maintain market fairness, but excessive regulation may also suppress the industry’s ability to innovate as an information aggregation tool.

A structural contradiction in the industry: the dilemma of information incentives versus market integrity

The core structural contradiction facing prediction markets can be summarized with a simple question: if insiders don’t release information through betting, how can market prices reflect true probabilities? If insiders profit through betting, does this “monetization of information advantage” equate to insider trading?

There is no black-and-white answer to this contradiction. In traditional financial markets, the definition of “insider trading” is built on two core elements—“material non-public information” and the trader’s duty of trust. Only when the information originates from within the company and the trader has a confidentiality obligation does it constitute illegal conduct. In prediction markets, information sources are extremely diverse: it may be public data analysis, signals aggregated from social media, satellite image interpretation, or it may be genuine internal confidential information.

This is the central tension in the design of prediction-market institutions: the pursuit of information transparency versus the constraints of regulatory compliance; the need for commercial growth versus the bottom line of market integrity; the decentralization ideal versus the reality of centralized regulation. These are not pairs of binary options that can be simply reconciled—they are structural contradictions the prediction market industry must face as it moves toward mainstream adoption.

One detail in the report may offer some form of answer: the tracked trader had dozens of small bets on sporting events, with some bets completed days or even weeks before the events occurred, meaning their insider-trading suspicion is relatively lower. This suggests that high win rate alone cannot directly prove the existence of insider trading. The key is not “knowing more” itself, but the information source, how it was obtained, and the legal boundaries around how it is used.

Future evolution paths and potential risks

The future evolution of prediction markets will depend on how the industry resolves three core problems it currently faces.

A differentiated compliance path: Polymarket has chosen a compliance route under the CFTC regulatory framework—by acquiring a derivatives exchange with a CFTC license to obtain compliance credentials, and it plans to introduce at least $1 billion in initial liquidity through introducing firms via a futures commission merchant. Another platform has taken a different route, seeking court approval to list White House election contracts. The differences between these two compliance paths will continue to affect each platform’s business model, user base, and growth ceiling.

Technological evolution in insider trading detection: on-chain data analytics has become a core tool for detecting anomalous bets. By tracking account creation time, concentration of bets, flow of funds, and on-chain linkages, it can successfully identify multiple suspicious accounts. As on-chain monitoring technology further develops, prediction market platforms are expected to build more intelligent real-time detection systems that intervene at the stage when suspicious trades occur.

A systematic assessment of “reflexivity” risk: prediction markets have grown large enough to potentially influence real-world events in a reflexive way—when large amounts of money bet on a particular outcome, do bettors have the motivation and ability to intervene in the direction of events? This concern is not unfounded. There have been incidents in the past where users issued death threats to journalists and tried to influence media coverage through intimidation to change prediction market outcomes. After wars, regime changes, and other major events are “financialized,” the industry must face a fundamental question: is a prediction market merely “predicting” the future, or has it begun “creating” the future?

Risks and limitations

When assessing insider trading issues in prediction markets, the following risks are worth continuous attention.

Cross-border challenges in regulatory enforcement: Polymarket’s international version is not directly governed by U.S. regulations, and U.S. users can access it easily via VPN. While the CFTC can bring civil enforcement lawsuits, in practice it faces dual challenges of jurisdiction and technical barriers. This means that even if platforms strengthen compliance measures, the most severe violations may still occur in regulatory blind spots.

A gap between technology and law: on-chain data is transparent and immutable, but “transparent” does not mean “provable.” Metrics such as high win rates, precise timing, and newly created accounts can only form “strong signals,” which are difficult to qualify as conclusive evidence at the legal level. The tracked accounts are anonymous and cannot be publicly traced back to specific individuals. This means that even if on-chain evidence is highly suspicious, legal accountability still faces major obstacles.

Conflicts between commercial growth and integrity-building: in October 2025, Polymarket sought financing at a valuation of $12 billion to $15 billion, more than 10 times higher than the valuation just four months earlier. Rapid growth in user scale and trading volume has created significant revenue pressure for the platform— in January 2026, Polymarket formally introduced fees for high-frequency trading products, and weekly revenue broke above $1.08 million. As the platform pursues commercial growth, whether market integrity-building will be placed as a secondary priority is a focus that investors and regulators will continue to monitor.

Summary

The 93% win-rate accounts on Polymarket, the six newly created accounts with precise bets, and the Venezuela incident with a 13x return on investment—these cases point in the same direction. They are not a flaw in the operations of any single platform, but rather a structural challenge for this emerging prediction market industry.

The core paradox of prediction markets is that they must incentivize informed parties to release information to achieve price discovery, yet they must also constrain those insiders from profiting by using insider information to maintain market fairness. There is no ultimate answer to this paradox—only an ever-adjusted institutional balance. From November 2025, when the CFTC approved the platform’s return to the U.S., to March 2026, when Polymarket comprehensively updated its integrity rules, Polymarket is transforming from a “crypto-native prediction experiment” into a “regulated financial infrastructure.” Whether this transformation succeeds or fails will not only determine the business fate of a single platform, but will also decide whether prediction markets can truly become an information pricing mechanism that goes beyond traditional polling—or whether they will devolve into a gray zone where information-advantaged actors arbitrage.

For participants in the crypto industry, the evolution of prediction markets provides a typical case for observing how a Web3 application can coexist with traditional regulatory frameworks. When decentralization’s technological ideals meet centralized compliance requirements, when transparent on-chain data conflicts with privacy protections, and when the line between “information arbitrage” and “insider trading” becomes blurred—these contradictions won’t disappear automatically; they will keep reappearing in new forms as the industry develops.

FAQ

Q: Do high win-rate accounts on Polymarket necessarily involve insider trading?

They can’t be directly equated. Some high win-rate accounts’ trading behavior does show “strong insider activity signals,” but the tracked accounts are anonymous, so their real identities cannot be confirmed. High win rates could come from a variety of legitimate methods, such as data-driven complex analysis models, aggregation of social media signals, and satellite image interpretation. Only when the information source is material non-public information and the trader has a confidentiality obligation does it constitute insider trading in the legal sense. All related accounts currently remain under investigation, and there is no official investigation conclusion yet.

Q: How does Polymarket prevent insider trading?

On March 23, 2026, Polymarket updated its Market Integrity Rules, clearly banning three types of insider trading: trades based on stolen confidential information, trades based on illegal sources of messages, and trades by those who can influence the outcome. The platform has built a multi-layer monitoring architecture—on the DeFi side, it performs anomaly detection using transparent on-chain records on the Polygon network combined with world-class monitoring institutions; on the U.S. exchange side, it has established a three-layer defense system consisting of external technical monitoring, a real-time monitoring command center, and cooperation with the NFA.

Q: Why do prediction markets repeatedly show anomalous bets on geopolitical events?

Geopolitical events attract massive bet sizes—trading volume for Iran-related contracts has already exceeded $529 million. Bets on such events naturally face an “information asymmetry” problem: participants’ information advantage may come from data analysis based on public sources, or it may come from confidential information. Because the confidentiality level of geopolitical events is often high, people who truly possess internal information often have a very strong information advantage, which leads to anomalous “return outliers” from betting compared with other types of markets.

Q: How can ordinary users identify abnormal behavior in prediction markets?

Ordinary users can watch for the following abnormal signals: newly created accounts establish large positions within a short time; bets concentrate on a single event and the timing is extremely precise; and an account’s betting history is extremely narrow with a lack of diversification. On-chain data analytics tools and visual analysis provided by third-party monitoring platforms can also help users identify potentially concentrated betting behavior.

Q: How is the regulatory environment for prediction markets evolving?

At present, there is a dual-track pattern: Polymarket has chosen a compliance route under the CFTC regulatory framework and has been approved to return to the U.S. market. On the other hand, multiple U.S. states have taken legal action against prediction platforms on the grounds of “unlicensed gambling.” At the federal level, in December 2025 the CFTC issued “no-action letters” to Polymarket and other platforms, exempting them from certain reporting and record-keeping requirements, provided that contracts are fully collateralized and transaction data is published on the website. Meanwhile, Congress is considering new legislation planned to prohibit federal officials from placing bets on prediction platforms using non-public information.