Three puzzles in the prediction market: When collective consensus is rewritten

Market prediction has become incredibly popular, and Polymarket has emerged as a new gambling scene in the crypto world. But behind every price fluctuation, there are deep struggles involving information, power, and rules. Let’s examine three real cases to see how this so-called “collective intelligence” market is gradually being manipulated.

Narrative vs. Facts: When Emotional Preferences Consume Rationality

In October 2024, around the release of HBO’s documentary Money Electric: The Bitcoin Mystery, a contract on Polymarket became the best textbook—“Who will HBO identify as Satoshi Nakamoto.”

The contract seemed simple: traders bet on who the documentary would identify as Bitcoin’s creator. Candidates included the late Len Sassaman, Hal Finney, Adam Back, and Peter Todd. The crypto community widely believed HBO would choose Len Sassaman—because his background matched Satoshi’s traits, and his tragic, legendary story fit the documentary’s aesthetic.

Sassaman’s odds (Yes) soared to 68%-70%.

But then came the twist. Some journalists and industry insiders who had early access to the media screening began leaking clips on Twitter and dark web forums. These leaks clearly pointed to director Cullen Hoback questioning Peter Todd, aiming to portray him as Satoshi. Peter Todd even mocked the director on social media. Several media outlets had already published articles stating “The documentary identifies Peter Todd as Satoshi.”

Strangely, despite the evidence being in front of everyone, Sassaman’s price on Polymarket did not plummet; it remained high at 40%-50%.

The community collectively refused to believe it. Repeated comments in the discussion area echoed the same sentiment: “This is HBO’s smoke screen,” “Peter Todd is just a side character, the big twist will be Len.”

So opportunity arose. The odds for Peter Todd and other options became ridiculously cheap—once as low as 10%-20%. It was like finding gold in a trash heap.

Only when facts conflict with desires does arbitrage have the greatest room to operate. People desperately wanted it to be Sassaman—dead men won’t dump Bitcoin, and the story was emotionally compelling. This emotional obsession blinded rational judgment. The contract explicitly states “who HBO will identify,” not “who is actually Satoshi.” But the market chose to ignore the rules and embrace emotion.

The combination of media narrative and emotional resonance is powerful: as long as the market is given a touching story, prices will automatically deviate from facts.

Feast of Asymmetry: Hardcoded Data vs. Social Opinion

The second case is even more subtle. The NORAD Santa tracking project—every Christmas, NORAD displays on its official website the “number of gifts delivered by Santa.” In 2025, this playful project was moved onto Polymarket: “How many gifts will Santa deliver in 2025?”

Then someone opened developer tools in their browser.

Tech-savvy traders found a string of hardcoded numbers in the front-end code of noradsanta.org: 8,246,713,529. This number is close to previous years’ logic but clearly below the reasonable range calculated based on historical growth (8.4-8.5 billion), appearing to be a placeholder inserted by developers rushing to meet deadlines.

The market reacted instantly. The contract price corresponding to the “8.2-8.3B” range jumped from 60% to over 90%. Large sums interpreted this hardcoded value as the “ultimate answer,” and the remaining percentage points became arbitrage opportunities.

But the subtlety is: Once this leak is exploited by large traders, the hardcoded number itself becomes a trigger variable. NORAD’s website is maintained by a centralized team, and developers have full authority to change the value at the last moment. When “developer laziness or fakery” becomes a social media focus, the maintainers are motivated to modify that number—to prove they are not amateurs.

This means that traders betting heavily at 0.93 price on “8.2-8.3B=Yes” are not really betting on “how many gifts Santa will deliver,” but on “whether the developers will change the code at the last second.”

Prediction markets suddenly turn into something else: they are no longer about predicting objective random events but about providing derivatives for a few who control the system switches—betting on how their actions will be interpreted externally.

Tech players who deploy crawlers in advance can build positions before the public reacts; media or influencers can amplify the “hardcoded scandal” narrative, indirectly influencing whether the maintainers adjust the code. The flow and speed of information dissemination directly determine who profits.

End-of-Day Kill: The Complete Script of Price Manipulation

The third case is the most shocking, involving a contract on whether Israel will carry out an airstrike on Gaza before the deadline.

For a long time, the market widely believed that the probability of a large-scale military action before the deadline was limited. The “No” price remained stable between 60%-80%. As the deadline approached, the idea that “nothing will happen” seemed to reinforce the legitimacy of “No.”

Then the familiar routine played out:

Late-night + media pressure + panic selling.

In the platform’s comment section, the “Yes” side began releasing unverified screenshots, local media links, and old news, creating an atmosphere of “airstrike has already happened, only mainstream media is slow to report.” Meanwhile, large sell orders suddenly appeared, aggressively breaking through the “No” support level, pushing the price down to 1%-2%.

For traders relying on emotional judgment, this sequence was enough to create a “false sense of conclusion”: since someone is dumping the market and the comments say it happened, they think they missed the news.

But a minority committed to fact-checking drew a completely different conclusion:

• There is no clear, authoritative, contract-accepted evidence of an “airstrike” within the specified deadline.
• According to the contract terms, “No” still has a far higher than 1% legitimate settlement probability.

A structural asymmetry emerged: the market price treats “No” as a 1% low-probability event, but the rules and evidence point to a very different reality.

After the close, someone proposed settling as “Yes,” and the contract entered a limited dispute period. Due to technical factors or participant resources, this settlement direction was ultimately not overturned. The contract was locked in as “Yes,” and those who adhered to the rule-based interpretation could only debate afterward whether this was consistent with the original design, but could not change the flow of funds.

The Fusion of Three Powers: Narrative, Capital, and Rules

These three cases reveal the true face of prediction markets—they are no longer arenas of collective wisdom but layered manipulations of narrative, capital, and rule interpretation.

For content creators and media: Each prediction market becomes a real-time thermometer of narrative influence. Documentary directors, PR teams, and topic creators can adjust their pacing based on market reactions— which candidates to hype, which plots to add. In extreme cases, content creators can even “reverse engineer” the market to feed their story.

For project teams and platforms: Ambiguity in rules, choice of settlement data sources, dispute mechanisms—all directly impact “who profits from late-stage events.” Vague oracles, broad decision rights leave a “gray space” for organized forces to exploit. In this space, prediction markets are no longer passive recorders of outcomes but active tools for liquidity manipulation.

For participants: Comment sections, social media, and secondary interpretations form a psychological leverage system. By concentrating on releasing “seemingly authoritative” screenshots, links, and headlines, actors can quickly push prices into panic or euphoria. Those with stronger voice (KOLs, influencers, research accounts) inherently possess the ability to manipulate narratives.

For tech players: Monitoring front-end code, data source updates, news APIs, and oracle mechanisms can become systematic strategies. Detecting hardcoded values, configuration errors, or rule loopholes in advance allows for high-leverage “structured arbitrage.” More aggressive players may even study how to legally or “edge” influence settlement data sources, making the world appear aligned with their positions in the short term.

The most dangerous aspect of prediction markets is that the truthfulness of information no longer matters—people are willing to pay for the “appearance of truth.” In this era, the pricing of information and how the underlying information interacts with the market may be the most critical issue.