A Google software engineer has been charged in New York over an alleged prediction-market trading scheme that federal authorities say turned confidential Google search data into more than $1.2 million in profits.
Michele Spagnuolo, a 36-year-old Italian citizen living in Switzerland, is accused of using nonpublic Google information to place trades on Polymarket, the prediction-market platform where users can wager on event outcomes. Prosecutors say he traded under the name AlphaRaccoon and used internal data connected to Google’s 2025 Year in Search results before those results were public.
Spagnuolo has been charged with commodities fraud, wire fraud, and money laundering. The Commodity Futures Trading Commission has also filed a parallel civil complaint accusing him of insider trading in event contracts tied to Google search results.
The case is still at the allegation stage. A criminal complaint is not a conviction, and prosecutors will have to prove their claims in court. But the charges are already important because they show how U.S. authorities are starting to treat prediction-market abuse more like traditional market misconduct, especially when confidential corporate information is involved.
What Prosecutors Say Happened
According to federal authorities, Spagnuolo worked at Google and had access to internal information about search trends. Prosecutors allege that between roughly October and December 2025, he used that access to place Google-related wagers on Polymarket before the relevant information was publicly released.
The central claim is straightforward: prosecutors say Spagnuolo was not merely making educated guesses. They allege he knew, or had access to information showing, how Google’s Year in Search rankings were shaping up and used that knowledge to buy positions before other traders could reasonably know the outcome.
One major example involved a market about who would be Google’s most-searched person of 2025. Authorities say Spagnuolo correctly backed singer D4vd, who had become the subject of intense public attention after being accused in a murder case and later charged. At the time of the wager, prosecutors say the market gave that outcome very low odds.
The complaint describes the information as confidential and commercially valuable. That language matters. Prosecutors are framing the alleged conduct not as clever research or fast trading, but as misuse of employer information for personal gain.
The Charges at a Glance
The criminal and civil cases involve several overlapping claims. The table below summarizes the main pieces without assuming guilt.
| Action | What authorities allege | Why it matters |
|---|---|---|
| Accessing internal data | Spagnuolo allegedly viewed confidential Google search information before public release. | The case turns on whether the information was nonpublic and improperly used. |
| Trading on Polymarket | He allegedly placed Google-related prediction-market trades under the name AlphaRaccoon. | Authorities say the trades were based on inside knowledge, not public analysis. |
| Profits | Prosecutors say the trades generated more than $1.2 million. | The profit figure helps explain the scale of the alleged scheme. |
| Money movement | The complaint includes a money laundering charge tied to the handling of funds. | That charge focuses on what allegedly happened after the profitable trades. |
| CFTC complaint | The regulator filed a civil insider-trading case over event contracts. | It signals regulatory attention on prediction markets, not just criminal prosecution. |
Why This Is Being Treated as Insider Trading
Prediction markets can look different from stock markets, but the basic concern is familiar. If one trader has confidential information that other participants do not, and uses it to trade for profit, authorities may view that as market abuse.
In traditional finance, insider-trading cases often involve corporate earnings, merger talks, or other confidential business information. Here, the alleged information was different: internal data about Google search trends and a planned public ranking. The market was also different: event contracts on Polymarket rather than stocks or options.
The legal theory still has a recognizable shape. Prosecutors allege that Spagnuolo misappropriated confidential information from his employer and used it in a market where counterparties did not have the same access. In plain terms, they say he was betting on outcomes he already knew or had an unfair basis to know.
That is why the case matters beyond Google. Many companies hold data that could move prediction markets if it became public: search trends, sales numbers, internal polling, unreleased product plans, platform metrics, or media rankings. Employees with access to that information may face legal risk if they use it to trade, even when the market is not a conventional securities exchange.
What Google and Polymarket Said
Google said it was working with law enforcement and described the alleged use of confidential information to place bets as a serious breach of company policy. The company said the employee had been placed on leave and that it would take appropriate action.
Polymarket said it worked with the U.S. Attorney’s Office for the Southern District of New York and pointed to the traceability of blockchain-based trading activity. The platform has also said the case followed a referral it made to authorities.
Those statements point to a broader issue for prediction markets: surveillance and enforcement are becoming part of the product’s credibility problem. Public blockchain records can make some activity easier to trace after the fact, but they do not automatically prevent insider trading, market manipulation, or improper access to information before trades are placed.
Why Prediction Markets Are Under More Scrutiny
Prediction markets have grown quickly because they offer a direct way to trade on politics, culture, sports, business outcomes, and public events. Supporters argue that prices can reflect collective expectations. Critics argue that the same markets can reward people who have privileged access, manipulate public narratives, or profit from sensitive events.
This case arrived during a period of rising government attention. Lawmakers have questioned how prediction-market platforms screen users, detect suspicious activity, and prevent abuse. Regulators have also signaled that they are looking more closely at event contracts, especially where crypto rails and offshore trading structures are involved.
Some reporting has described Polymarket as operating through separate U.S.-accessible and offshore-facing experiences, with the larger crypto-based market restricted for U.S. users. Because platform availability and legal access can depend on jurisdiction and product structure, readers should treat broad descriptions of Polymarket’s setup as a moving regulatory issue rather than a settled fact.
The CFTC’s involvement is especially important. By filing a civil complaint, the agency is making clear that it views at least some prediction-market contracts as within its enforcement reach. That does not settle every legal question around the industry, but it does show that regulators are willing to pursue alleged insider trading in event markets.
How Companies Should Read the Case
For companies, the lesson is not limited to Google or search data. Any organization with valuable internal information should assume that prediction markets create new ways for employees, contractors, or partners to misuse access.
Practical controls should focus on the data most likely to have trading value. That can include unreleased rankings, traffic dashboards, product launch information, internal forecasts, customer metrics, election or polling data, and business performance signals.
Companies should consider several safeguards:
- Clearly define which internal data is confidential and commercially sensitive.
- Update employee trading policies so they cover prediction markets and crypto-based event contracts, not just stocks.
- Log access to sensitive dashboards, reports, and pre-release marketing materials.
- Limit access to data that could influence public markets or event contracts.
- Train employees that using internal information to trade can create legal exposure, even outside securities markets.
These controls do not need to be theatrical. They need to be specific enough that employees understand the boundary and investigators can reconstruct access if something goes wrong.
How Traders Should Read the Case
For individual traders, the case is a warning about the difference between public research and privileged information. Reading public documents, watching market odds, following news, and analyzing open data are ordinary trading behaviors. Using confidential employer information is different.
The risk is especially high when a trader’s edge comes from workplace access. If the information is not public, belongs to an employer or client, and is being used to profit in a market, the trader may be creating a legal problem even if the market itself is easy to access.
A simple test helps clarify the issue: could another ordinary market participant obtain the same information through public channels at the same time? If the answer is no, and the information comes from work access or a confidential relationship, trading on it can be dangerous.
What Happens Next
The criminal case will now move through federal court, while the CFTC’s civil complaint proceeds separately. Prosecutors may seek to prove that Spagnuolo knowingly used confidential Google information to place profitable trades. The defense may challenge the facts, the legal theory, or the interpretation of the trades and data access.
Whatever the outcome, the case has already changed the conversation around prediction markets. It shows that federal authorities are willing to pursue alleged insider trading when event contracts intersect with confidential corporate data. It also shows that employers may need to treat prediction markets as part of their compliance and data-security planning.
The central takeaway is simple: prediction markets may be new in form, but the old rule still applies. Confidential information cannot be turned into a private trading advantage without serious legal risk.