Despite running separate order books, liquidity pools and user bases, Polymarket and Kalshi priced Spain’s chances of winning the World Cup at roughly the same probability ahead of Sunday’s final.
Polymarket has priced Spain at approximately a 59% chance of lifting the trophy before kick-off, while Argentina traded at approximately 40%. The Calcio market independently arrived at roughly the same assessment, pricing Spain at 59.6% and Argentina at 40.4%.
Different markets, identical possibilities
The close alignment provided a rare example of the extent of independence Prediction markets With separate liquidity pools and user bases similar probability estimates can be reached through trading alone.
This consensus was demonstrated during the largest sporting event in the history of the prediction market, with Polymarket World Cup winner Processing contracts worth $4.28 billion in volume and everythingA market equivalent to another $1.29 billion.
The trading volume makes the similarity in pricing particularly notable, although the outcome of a single football match cannot determine whether these odds are perfectly calibrated.
Although the two markets arrived at almost identical odds, the trader’s situation looked somewhat different. While traders were chasing value on the underdog rather than backing the favourite, which resulted in more capital flowing towards Argentina despite Spain’s higher implied probability, both platforms ultimately reflected almost identical pre-match market forecasts.
No widespread profits
Blockchain analyst defioasis.eth has scanned over 194,000 Polymarket Governor and found that nearly two-thirds finished the tournament with losses. Only five portfolios achieved profits exceeding $1 million, while the vast majority of gains and losses remained below $100.
The World Cup has come to an end. Congratulations again to Spain. I don’t know of any friend who has successfully bet on Polymarket’s prediction of the World Cup champion’s ownership market. Out of more than 194,000 independent trading addresses, losses: – Nearly 130,000 addresses experienced losses due to wrong predictions, accounting for about 66.7% of losses – Most participants’ losses were not significant, with 114,000 addresses losing less than $100, and the average loss was less than 10… pic.twitter.com/z3kKImxnlZ
— DiffiWaces (@DiffiWaces) July 20, 2026
One notable victim was an Argentina fan who lost a $1.23 million position in the final after previously receiving more than $5 million in unrealized winnings.
Record trading volumes were large, but also largely predictable. The tournament provided one of the clearest, large-scale demonstrations to date of how prediction markets accumulate information through independent trading.
This article was written by Tanya Chipkova at www.financemagnates.com.
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