A Bellingcat analysis reveals that football fans bet more than $14 billion on the FIFA World Cup through Polymarket and Kalshi, with a small percentage of users capturing most of the winnings.
Key facts
- •Users traded on nearly 60,000 outcomes, ranging from match results to specific player actions.
- •The Spain vs. Argentina final was the largest individual market on Polymarket, totaling $212 million in trades.
- •The top-performing Polymarket account earned over $13 million in profit, while the largest loss was $11.6 million.
- •Prediction markets have faced criticism regarding potential market manipulation and vulnerability to insider trading.
- •The World Cup was held across the US, Canada, and Mexico during June and July.
Football fans wagered more than $14 billion on the FIFA World Cup via prediction markets Polymarket and Kalshi. The tournament, which took place in the US, Canada, and Mexico during June and July, featured nearly 60,000 trading outcomes. While the event was projected to reach $50 billion in total wagers, the analysis focused on the activity across these two specific platforms.
By the numbers
Market Performance and Winnings
On Polymarket, users traded $10 billion, while Kalshi saw over $4.3 billion in activity. Analysis of Polymarket accounts showed that 1% of users collected 86% of all winnings, while the bottom 50% of winners shared only 0.1% of profits. The median winning account on Polymarket made $21, whereas the median losing account lost $32. More than 14,500 traders who bet on two or more games lost every wager.
Trading Volume and Methodology
The highest trading volumes by team were recorded for Argentina at $1.068 billion, Spain at $876 million, and France at $836 million. Among players, Lionel Messi led with $40 million in volume, followed by Kylian Mbappé at $36 million and Erling Haaland at $16 million. Because Kalshi does not display actual traded volume, Bellingcat used a heuristic formula based on daily average prices and contract counts to reconstruct the data for comparison.
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This article was independently rewritten by ManyPress editorial AI from reporting originally published by Bellingcat.
