In the shadowy no-man’s-land between high-frequency trading and online sportsbooks, a new kind of white-collar crime has emerged: insider trading prediction markets. It doesn’t involve stock tickers or quarterly earnings reports. Instead, it hinges on the kind of trivial—yet wildly popular—data that powers the internet itself: the list of things people searched for most in a given year.
Earlier this week, federal prosecutors in New York charged Michele Spagnuolo, a 36-year-old Google software engineer based in Switzerland, with fraud, wire fraud, and money laundering. The crux of the case? He allegedly used his access to internal Google data to make a series of highly profitable bets on Polymarket, a decentralized prediction market, totaling more than $1.2 million in winnings.
According to the criminal complaint, Spagnuolo—who operated under the username AlphaRaccoon—wagered roughly $2.75 million on markets tied to the results of Google’s 2025 “Year in Search” list. The bets included a successful prediction that the indie pop artist d4vd would top the “most-searched-for person” category. Prosecutors allege that Spagnuolo accessed the confidential data mere hours before placing the bets.
As an Italian citizen living abroad, Spagnuolo likely never imagined his virtual gambling hobby would land him in a federal courtroom in the Southern District of New York. But U.S. Attorney Jay Clayton made clear during the announcement that the charge follows a familiar script: “Corporate insiders cannot use confidential business information to turn a profit in our markets.”
Prediction Markets: The New Frontier of Insider Trading Prediction Markets?
The Polymarket case represents a growing legal frontier. Unlike traditional stock or commodities markets, prediction platforms allow users to bet on the outcomes of virtually anything—election results, viral moments, even the capture of a foreign leader. That last example is not hypothetical: last month, a U.S. soldier named Gannon Ken Van Dyke was charged with using classified military intelligence to bet on Polymarket regarding the abduction of Venezuelan President Nicolás Maduro. He reportedly pocketed more than $400,000 on that single operation.
These cases underscore a fundamental tension. While platforms like Polymarket market themselves as tools for aggregating public sentiment—a sort of democratized forecasting engine—they also create perverse incentives for anyone with a non-public piece of information. In the case of Google’s search data, the information is commercially sensitive but not considered a “traditional” security under U.S. securities law. That’s where the charges become more creative: prosecutors are using commodities fraud and wire fraud statutes to cover the gap.
But is this really insider trading in the classic sense? Securities law expert Dr. Lena Choi, who teaches at Columbia Law School but was not involved in the case, points out a key nuance: “In a traditional stock market, insider trading involves a breach of a duty owed to shareholders or the company itself. Here, the ‘duty’ is more ambiguous. Spagnuolo owed his employer a duty of confidentiality, certainly—but he didn’t trade stocks. He made bets on a sports-like platform. It’s a gray area that regulators are eager to paint black.”
Indeed, the PolyMarket spokesperson was quick to note that the company proactively cooperated with the U.S. Attorney’s Office, adding that the platform is “the only prediction platform to date whose cooperation has led to insider trading charges in the United States.” That language suggests a deliberate strategy: in exchange for regulatory goodwill, Polymarket positions itself as a compliant, law-abiding player rather than a rogue betting site.
What This Means for the Average Person
You might ask: Why should I care about a software engineer in Switzerland and his bets on pop singers? The answer is that this case signals a broader shift in how both corporations and regulators view information asymmetry in the digital age.
Consider the sheer volume of non-public data held by employees at tech giants like Google, Meta, or Amazon. They know what we’re searching for, what we’re buying, what we’re watching. As prediction markets grow in popularity—and as more aspects of life become ‘bet-able’—the temptation to exploit that data will only increase. The line between a harmless “office pool” and a federal crime is razor-thin, measured by the distance between a computer screen and a blockchain wallet.
Google itself has placed Spagnuolo on leave and issued a statement declaring that using confidential information to place bets is a “serious breach of company policy.” Yet the company is also part of the machinery that made the data valuable in the first place. It’s a reminder that every list, every algorithm, every internal trend report is a potential goldmine—and a potential trap.
For now, the case against Spagnuolo serves as a cautionary tale for any employee tempted to monetize their insider knowledge on a prediction market. It also raises an uncomfortable question for the rest of us: as more of our lives are quantified and aggregated, who gets to profit from the clues we leave behind?
Spagnuolo’s next court appearance is set for mid-June. If convicted, he faces up to 20 years in prison on the most serious charges. His lawyer has declined to comment, but the judge in the case made a pointed remark during the bail hearing: “The integrity of markets—any market—depends on a level playing field. This defendant allegedly tilted the field in his own favor using stolen secrets. That’s not innovation. That’s theft.”
For more on how prediction markets are reshaping finance, read our analysis on global tensions stress-testing the system. Also, check out this SEC resource on insider trading for official guidelines.
