Polymarket Faked Bets to Rack Up 140 Million Views

Opening

Hello, subscribers. This is OZ Talking. Sadly, the World Cup talk has wrapped up here in Korea, but there’s a market that boomed thanks to it: prediction markets. Prediction markets like Polymarket and Kalshi topped nearly $2 billion (~₩3.1 trillion) in trading volume around this World Cup.(Source)

But the World Cup isn’t why I’m bringing up prediction markets. This January, a college student posted a TikTok video: they’d bet $100,000 on whether President Trump would say the word “McDonald’s,” and when he actually said it, they cheered. Over five months, this student posted 145 betting videos worth a combined $410,000.

But when the Wall Street Journal (WSJ) analyzed more than 1,100 such videos, it found that not a single one of these trades was real. Meanwhile, more than 50 accounts that placed the same McDonald’s bet on the actual site all lost money.

A prediction market¹ platform that brands itself as a “market of transparent probability” racked up 140 million views by filming fake trades on a fake site. Let me give you the conclusion up front: this isn’t just a marketing scandal. It’s a structural event in which a market whose product is trust burned that very trust for the sake of growth.

🔍 What 1,100 Videos Concealed

Let’s walk through the core findings of the WSJ investigation.

The prediction market platform Polymarket paid dozens of college-student creators $2,000 to $3,000 a month to produce fake trading videos. The screens where they placed their bets weren’t real Polymarket. They were filmed on a dummy site Polymarket itself had built, poiymarket.com (with a lowercase “i” swapped in for the “l”). It had nearly the same layout as the real site, but was a simulation environment where trade amounts and outcomes could be manipulated at will.

About 70% of the 1,105 videos WSJ analyzed contained betting scenes, featuring a combined $1.9 million in trades. In 118 of those videos, creators appeared to have made roughly $900,000 in combined profit—but had they placed the same bets on the real site, they would have lost more than $166,000. Behind the staged screen showing $900,000 in gains was a hidden reality of $166,000 in losses.

What’s even more troubling is the distribution structure. Polymarket hired thousands of “clippers” through the marketing agency Virality. Clippers copy creators’ videos and repost them on their own accounts. They were given two instructions: first, make the content look “personal and natural.” Second, never put the words “Polymarket” or “Poly” in the account name. It was an explicit directive to disguise paid content as organic.

Creators submitted finished videos to Polymarket for review. If a video lacked appeal or the staging was too obvious, they were told to reshoot. This wasn’t a handful of influencers voluntarily exaggerating—it was an organized marketing campaign designed and managed by the company itself.

The result of this campaign? More than 140 million combined views across TikTok, YouTube, and Instagram. And the target audience was explicit: clippers only got paid if at least 60% of a video’s viewers were U.S. users. By that measure, it was wildly successful. The problem is that Polymarket has been banned from operating in the U.S. since 2022. U.S. federal advertising law requires disclosure of paid promotion, and commodities law bars misleading trade promotion.

One message repeated throughout the videos. The phrase “Is this just free money?” appeared in roughly a quarter of the videos analyzed. That single line was the core hook behind the 140 million views—and, at the same time, the biggest lie.

📊 What Happens When “Growth Is Survival” Outside Regulation

Why did Polymarket go this far? Looking at the backstory, you can read the desperation.

In 2022, Polymarket settled with the U.S. Commodity Futures Trading Commission (CFTC)², paying a $1.4 million fine over charges of operating an unregistered options exchange and halting crypto-based trading within the U.S. The company relocated its corporate entity to Panama. But reporting has shown that if you actually go looking for that Panama headquarters, it turns out to be nothing more than a law office shared with a dozen other crypto companies.

During the 2024 U.S. presidential election, Polymarket grew explosively, drawing attention as a “real-time barometer of public opinion.” But rival Kalshi caught up quickly, and by 2026 the tables had turned. According to data from The Block, Kalshi’s monthly trading volume in May 2026 was roughly double Polymarket’s. Kalshi is a legal platform regulated by the CFTC within the U.S., and through a partnership with Robinhood, it had secured a user base of 23 million.

It’s fascinating where the two platforms’ paths diverged. After winning its 2024 legal dispute with the CFTC, Kalshi charged straight ahead within the regulatory framework, and by 2026 it had closed a $1 billion funding round at a $22 billion valuation. Polymarket, by contrast, chose the path of starting outside regulation and trying to legalize later. It only launched a CFTC-regulated, U.S.-only app late last year, but that app’s trading volume is a tiny fraction of the offshore crypto version’s. As of April 2026, the U.S. app’s volume was $1.3 billion versus $9 billion for the offshore version. The shift to a legal channel simply hasn’t happened yet.

A situation where volume was being siphoned off by a regulated rival. On top of that, growth pressure was extreme, coming right after Polymarket had raised $1.6 billion from ICE, the NYSE’s parent company. WSJ published internal testimony that Polymarket founder Shayne Coplan told his growth team to “become impossible to ignore online.”

What’s interesting is the political backdrop. President Trump’s son, Donald Trump Jr., is both an investor in Polymarket and a paid advisor to rival Kalshi. Under the Trump administration, the CFTC cut roughly a quarter of its staff, and a climate favorable to prediction markets took shape. President Trump recently wrote on social media that “the CFTC should have exclusive authority so that prediction markets can flourish.” In an environment where the regulator is on the industry’s side, it’s questionable whether there’s any real drive to catch and punish potentially unlawful marketing.

Grow outside regulation, then try to legalize afterward—a pattern that recurs throughout the crypto industry. This time, the strategy led straight into more aggressive marketing the moment the company started losing the competitive race. I’ve actually covered this dynamic once before.

A Market Where Crimes Are Recorded but No One Is PunishedPrediction markets welcomed insiders in the name of “accurate forecasting.” Now the bill is coming due.oztalking.com

There’s one more thing worth noting. What stands out about this case is that Polymarket, a platform banned in the U.S., ran marketing specifically targeting Americans. Because it’s a Panamanian entity, U.S. law is hard to apply; because U.S. regulators’ jurisdiction is ambiguous; and because the creators acted in a personal capacity, accountability gets blurred at every level. It’s a textbook problem of a growth strategy built on regulatory arbitrage. In a structure where no one is accountable, the harm falls on individual users.

💰 The Real Scorecard on “Easy Money”

How wide is the gap between the “easy money” narrative spread by the fake videos and reality?

According to a separate WSJ analysis, 67% of Polymarket’s total profits are concentrated in the top 0.1% of accounts. Fewer than 2,000 accounts out of 1.6 million took home roughly $500 million. On the flip side, more than 70% of all users recorded losses, and the average loss for the bottom 10% of users was $4,000. So… most people lose money.

An academic paper by French and Canadian researchers reaches the same conclusion. Prediction market profits go “almost entirely to skilled, professional traders, while casual bettors and one-off participants absorb the losses.” In a joint study by London Business School and Yale, only 3.14% of 1.72 million accounts were classified as “skilled winners.”

Kalshi’s “mention markets” — bets on whether a celebrity will say a specific word — tell an even starker story. WSJ analyzed more than 35,000 mention markets and found that the average user betting “yes” lost 11% of their stake. That’s worse than the average house edge on a Las Vegas slot machine. In precisely the category of bet most aggressively promoted by the “free money” videos, ordinary users were structurally losing money.

Who’s making money on the other side of this profit structure? Quant trading firms like Susquehanna International Group act as market makers³, trading hundreds of millions of dollars a week, and Jump Trading is also active on both platforms. They have data infrastructure and algorithms that ordinary users simply can’t match. Structurally, the losses of retail users who came in believing in “easy money” become the revenue source for these professional traders. (This part looks a lot like crypto.)

Insider trading problems are also surfacing. A Google security engineer was charged with using internal search data to make $1.2 million on Polymarket, and a U.S. special forces sergeant was charged with pocketing more than $400,000 using classified information about an operation to capture Venezuela’s Maduro. As prediction markets create a new category of trading, they’ve also opened a new channel for cashing in on insider information that previously had no way to be monetized.

Most of the users lured in by 140 million views’ worth of “easy money” videos were, structurally, always going to lose.

Oswald’s Lens

Honestly, watching this unfold gave me a bitter sense of déjà vu.

There’s a pattern I’ve run into often while building GTM strategy. Cases where a product’s core value is “trust,” but growth pressure pushes the company to burn that trust as marketing fuel. The numbers go up in the short term. But a user base built this way isn’t an asset—it’s a liability. The moment users who came in expecting “easy money” take a loss, they walk away with a hostile memory of the platform.

Polymarket’s core value proposition is “transparent trading on the blockchain.” Every trade being recorded on the Polygon chain, auditable by anyone, was its differentiator from competitors. But this same platform filmed trades on a fake site that never touched the blockchain. When what a product promises and what its marketing actually does contradict each other this directly, the brand’s foundation of trust is structurally damaged.

To my mind, there’s an even more fundamental problem. The reason prediction markets exist is “accurate probability discovery through the wisdom of crowds.” Prices only become accurate when informed traders participate. But when FOMO-driven bettors flood in en masse, the price discovery function itself gets distorted. A paradox emerges: the very users viral marketing attracts end up undermining the market’s reason for existing.

Closing

Let me sum up.

Polymarket filmed fake trades on a fake site to manufacture a 140-million-view “easy money” narrative. Behind this marketing was structural pressure from an unregulated platform watching its trading volume get overtaken by a legal rival. More than 70% of the users who believed in “easy money” are actually losing money, and 67% of the profits are concentrated in the top 0.1%.

In a market where transparency is the product, pursuing growth through opaque means will eventually eat away at that growth itself. This isn’t a lesson unique to prediction markets—it’s a structural lesson for any business that sells trust.

If you’ve ever personally used a platform that promises “easy profits,” tell me in the comments where the gap between expectation and reality was widest. I’ll try to reflect it in the next issue.

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References & Further Reading

Primary sources

• Katherine Long, Caitlin Ostroff, Neil Mehta, Brenna T. Smith, “They Looked Like They Were Getting Rich on Polymarket, but None of It Was Real,” Wall Street Journal, June 20, 2026. This is the original WSJ investigative report analyzing more than 1,100 videos. (Paywalled)
• Wall Street Journal, “0.1% of Polymarket Accounts Take Home 67% of All Profits,” Wall Street Journal, May 4, 2026. A separate investigation analyzing profit distribution across 1.6 million accounts, showing the reality behind the “easy money” narrative in numbers.
• Gómez-Cram, Guo, Jensen & Kung, “Prediction Market Accuracy,” London Business School & Yale, April 2026. Provides academic evidence, based on an analysis of 1.72 million accounts, that only 3.14% qualify as “skilled winners.”

Background

• Pew Research Center, “Trading Volume on Prediction Markets Has Soared in Recent Months,” May 27, 2026. A neutral overview of overall prediction market trading volume trends and a Kalshi/Polymarket comparison.
• CNBC, “Google employee charged with $1M Polymarket insider trading bet on search term,” May 27, 2026. A detailed report on the circumstances of the Google employee insider trading charges.

The author, Kwangseob Ahn, is a professor of business administration at Sejong University and lead consultant at OBF (Oswarld Boutique Consulting Firm). He teaches statistics and data analysis — business data management and business analytics — while leading GTM and AI strategy consulting in the field, designing the seam between technology and business. He has published academic research on a memory architecture for AI dialogue systems (HEMA) and runs Daily Arxiv, a daily curation of global AI papers. He holds a master’s from Korea University’s Graduate School of Technology Management and a KMBA. He is the author of Homo Brainless: The People Who Outsource Their Thinking.

Footnotes

1. Prediction market: A platform where people trade on the outcomes of future events. It works on the principle that participants’ betting prices reflect the probability of the event occurring. Like stocks, you can buy and sell “yes” or “no” contracts. ↩

2. CFTC (Commodity Futures Trading Commission): The U.S. federal agency that regulates derivatives and futures markets. Prediction markets also fall under its jurisdiction. ↩

3. Market maker: A professional trader who supplies liquidity to a market. By quoting both buy and sell prices simultaneously, they enable other participants to trade, earning profit from the spread (the price difference) in the process. ↩