An anonymous prediction market trader netted $316,346 by correctly betting on five of President Biden‘s last-minute pardons in the final hours of his presidency, according to a forensic analysis by Bubblemaps shared exclusively with NPR. The trader placed approximately $64,000 in bets across four pardon contracts when the odds on each were near zero, and every bet paid off. Columbia Law School professor Joshua Mitts, who advises the DOJ on insider trading, described the probability of these trades occurring by chance as “virtually zero.”
Five Perfect Bets on Names Nobody Expected
The trader bet that Biden would issue pre-emptive pardons to four political figures: Jim Biden (the president’s brother), former Rep. Liz Cheney, Sen. Adam Schiff, and former Rep. Adam Kinzinger. None of the four had been charged with crimes. All received pardons to shield them from potential prosecution under Trump’s second term.
A month earlier, the same bettor placed a well-timed wager that Biden’s son Hunter Biden would receive a pardon over gun and tax charges. That bet also paid. Across all five positions, the trader invested roughly $64,000 and walked away with over $316,000 in profit.
Pardon Bet Breakdown
| Pardon Recipient | Status at Time of Bet | Outcome |
|---|---|---|
| Hunter Biden | Facing gun and tax charges | Pardoned |
| Jim Biden | No charges | Pre-emptive pardon |
| Liz Cheney | No charges | Pre-emptive pardon |
| Adam Schiff | No charges | Pre-emptive pardon |
| Adam Kinzinger | No charges | Pre-emptive pardon |
Two Accounts, One Wallet: How Bubblemaps Connected the Dots
Bubblemaps, a Paris-based blockchain analytics firm, used pattern-matching AI software to examine all accounts trading on the pardon-related prediction markets. The investigation uncovered two accounts with a perfect track record on Biden pardon bets. Both accounts funneled their profits to the same deposit wallet on a US-based crypto platform, indicating they were controlled by the same person or entity.
Bubblemaps founder Nick Vaiman said the firm attempted to obtain account holder information from the platform but was unsuccessful. The trader’s identity remains unknown.
$143M in Estimated Insider Profits Across Prediction Markets
The Biden pardon trades are part of a broader pattern. Professor Mitts published a paper last month estimating that $143 million in total profits have been earned on prediction markets by traders with apparent access to insider information. The research suggests that confidential government information may have been used for profit on prediction platforms both before and after the transition of power.
Mitts noted that proving insider trading on prediction markets is legally complex. Even when a blockchain wallet is linked to a specific individual, prosecutors must demonstrate who misappropriated the information and under what conditions it was obtained. The pseudonymous nature of blockchain transactions adds another layer of difficulty.
A $1 Trillion Industry With an Integrity Problem
Prediction markets have grown rapidly, with monthly volumes climbing to $21 billion in 2026 from $1.2 billion in early 2025. Investment firm Bernstein projects the sector could become a $1 trillion annual industry within four years. The current administration has embraced the industry, and major platforms are competing aggressively for market share.
But the Biden pardon case illustrates the fundamental tension at the heart of the sector: prediction markets are designed to aggregate information efficiently, but without robust surveillance mechanisms, that same efficiency can reward those who trade on confidential government intelligence. As the industry scales toward the $1 trillion mark, the gap between market growth and market integrity enforcement is becoming harder to ignore.
