How a Google Employee Used Secret Search Data to Win a Million Dollars in Bets

A 36-year-old Google software engineer named Michele Spagnuolo has been charged with fraud and money laundering. Federal prosecutors say he used secret information from inside Google's search engine to place bets on a prediction website called Polymarket, where he made more than a million dollars.

The alleged scheme involved using access to Google's internal search data—information about what millions of people are searching for—to bet on which celebrity would be the most-searched person in 2025. Spagnuolo reportedly wagered that a musician named D4vd would come out on top, using real search numbers that weren't available to the public or other bettors.

How the Scheme Allegedly Worked

Spagnuolo has worked at Google since 2014 and had legitimate access to internal data about search habits. But prosecutors say he crossed a line when he started using that information to place bets on Polymarket.

Think of it like this: imagine if you worked at a movie studio and had access to advance information showing which films would be box office hits. If you then used that private knowledge to bet against other people who only had rumors and guesses, you would have an unfair advantage. That is essentially what prosecutors say Spagnuolo did.

On Polymarket, most people who bet on what will be searched or what will happen have only public information and their own hunches. Spagnuolo had something they did not: actual, real-time numbers showing what people were really searching for. That gave him an enormous edge.

Why This Matters Legally

This case involves something relatively new: using a company's private information to bet on outcomes through a prediction market. Most insider trading cases have historically involved stock prices or information about mergers and company earnings.

Prediction markets like Polymarket are built on the idea that when many people make bets based on different information and opinions, their collective guesses can forecast real-world events fairly accurately. But that only works if everyone is playing by the same rules and has access to roughly the same kind of information.

When someone uses secret company data to bet in these markets, it is similar to the kind of insider trading that has been illegal in stock markets for decades. The underlying principle is the same: if you have privileged access to information that others do not have, you cannot use it to profit unfairly in any kind of market.

The federal authorities view this as serious fraud, not just a workplace rule violation.

A Pattern Emerging

About a month before Spagnuolo was charged, the government brought similar charges against a U.S. Army Special Forces officer who allegedly used classified military intelligence to make profitable bets on Polymarket. That case involved betting on whether Venezuelan President Nicolas Maduro would be captured, and the officer made about $400,000.

These two cases in quick succession suggest that federal prosecutors are paying close attention to how people are using prediction markets. Both defendants had legitimate jobs that gave them access to valuable inside information, but prosecutors say they crossed the line into crime by using that access to make bets.

Prediction markets are relatively new as mainstream platforms. They do not have as many rules and monitoring systems as stock exchanges, which have been around for a long time and have sophisticated systems to catch unfair trading. As prediction markets grow bigger and attract more money, regulators are still figuring out what should and should not be allowed.

What Happens Now

This case will test whether existing fraud laws apply to prediction markets. If Spagnuolo is convicted, it will send a clear message that the rules against insider trading and market manipulation apply to these newer platforms too, even though they use blockchain technology and are not traditional stock markets.

The broader picture here is that prediction markets are no longer a gray area where anything goes. The same legal principles that protect fairness in stock markets—rules against using private information to gain unfair advantages—now extend to these newer platforms. As more people use them and more money flows through them, the government is taking the same approach it takes with traditional financial markets: preventing people with inside information from using it to profit unfairly.

For Google and other tech companies, this case highlights a gap in their policies. Most large companies have rules about when employees can trade company stock, but fewer have clear policies about what employees can do with private company information on prediction markets. That is likely to change as companies see the legal risks.

The bottom line is straightforward: when you have access to secret information as part of your job, you cannot use it to make money through bets or trades, whether in stock markets, prediction markets, or anywhere else. That is the law, and federal prosecutors are enforcing it.