Lionel Messi and Cristiano Ronaldo have spent much of their careers being compared through goals, trophies, and individual awards. During the 2026 World Cup, another measure emerged: how much money traders were willing to put behind predictions involving the two soccer icons.
Prediction markets Polymarket and Kalshi handled more than $14 billion in World Cup trading, according to a Bellingcat analysis. Player-specific markets attracted substantial activity as well, with Messi generating more than $40 million in combined prop-market volume and Ronaldo around $13.6 million.
Those figures do not settle soccer's long-running Messi versus Ronaldo debate, but they show how prediction markets are creating a new way to measure expectations around the world's biggest athletes.
Messi Was the World Cup's Most-Traded Player
Messi attracted more prediction-market activity than any other individual player during the tournament.
Bellingcat calculated approximately $40.46 million in combined Messi prop-market volume across Polymarket and Kalshi. Around $30.87 million came through Kalshi, while another $9.60 million was traded on Polymarket.
That placed Messi ahead of Kylian Mbappé, who generated roughly $36.23 million, and comfortably above every other player. Erling Haaland attracted about $16.23 million, while Ronaldo generated $13.63 million.
The growth of these markets also reflects a broader convergence between cryptocurrency, online gambling and sports speculation. Some users who follow prediction platforms may also be familiar with Bitcoin casinos in the UK, but the two products operate differently. Crypto casinos offer conventional gambling products funded with digital assets, while prediction markets allow participants to trade contracts based on whether specific real-world events occur.
That distinction also matters from a regulatory perspective. Using Bitcoin does not remove the need for an online gambling operator serving British consumers to comply with applicable UK gambling rules, while prediction markets can fall under different regulatory frameworks depending on their structure and where they operate.
Argentina was also the most heavily traded national team across the two prediction platforms, generating more than $1.06 billion in combined match volume during the World Cup.
Ronaldo Still Generated Millions in Prediction Markets
Ronaldo may have trailed Messi in total player-market volume, but interest surrounding the Portugal star remained substantial.
His markets generated approximately $3.45 million on Polymarket and $10.18 million on Kalshi. Combined volume of $13.63 million placed him among the most heavily traded players at the tournament despite being in the later stages of his international career.
Portugal also generated more than $403 million in combined trading volume across its World Cup matches, illustrating the continued attention surrounding Ronaldo and the national team.
Some markets went considerably further than predicting goals or match results. Traders could even take positions on whether Ronaldo would cry during a Portugal match, demonstrating how prediction platforms can turn cultural moments surrounding major players into tradable events.
Prediction Markets Are Different From Traditional Sportsbooks
Prediction markets resemble financial exchanges more closely than conventional fixed-odds sportsbooks.
Users generally trade contracts based on whether a particular event will happen. A contract trading at $0.70, for example, can be interpreted as the market assigning approximately a 70% probability to that outcome. If the event occurs, a winning contract typically settles at $1, while an unsuccessful position settles at zero.
Prices can move continuously as traders buy and sell. A goal, injury, lineup announcement or unexpected result can therefore change the market's assessment almost immediately.
That makes prediction markets useful for observing collective expectations, although market prices should not be treated as guarantees. Liquidity, trader behavior and the information available at any given moment can all influence the probability reflected in the price.
The World Cup Became a Massive Prediction-Market Event
The scale of World Cup activity shows how quickly sports have become important to prediction-market platforms.
Across Polymarket and Kalshi, users traded on almost 60,000 outcomes during the competition. Polymarket recorded approximately $10 billion in World Cup trading, including $5.7 billion on individual games and another $4.3 billion on the tournament winner.
Kalshi added more than $4.3 billion, according to Bellingcat's calculations. The Spain versus Argentina final was the largest individual game on Polymarket, attracting around $212 million in volume, followed by the France versus Spain semifinal at $165 million and England versus Argentina at $142 million.
Argentina led all countries with approximately $1.068 billion in combined trading volume. Spain followed with about $877 million, while France generated approximately $836 million.
Popularity Does Not Mean Prediction Markets Are Easy to Beat
The billions flowing through World Cup markets might suggest plenty of opportunities for ordinary traders, but the distribution of profits tells a different story.
Bellingcat found that just 1% of Polymarket accounts collected 86% of all winnings during the tournament. The bottom half of winning accounts shared only 0.1% of profits.
The median winning account made $21, while the median losing account lost $32. More than 14,500 traders who participated in at least two games lost every wager they made.
At the extremes, one Polymarket account reportedly generated more than $13 million in profit across the tournament, while the biggest loser dropped $11.6 million. The figures underline an important limitation of prediction markets: correctly understanding soccer does not necessarily translate into consistently profitable trading.
Messi and Ronaldo Markets Reflect More Than soccer Ability
The difference between Messi's $40.46 million and Ronaldo's $13.63 million in player-market volume should not be interpreted as a direct ranking of the two players.
Trading volume measures how much activity a market attracts, not how highly traders rate a player. Messi's involvement with Argentina and the country's run through the tournament created more opportunities for traders to take positions connected to him.
Ronaldo's markets illustrate another side of the prediction-market phenomenon. Interest can extend beyond goals and victories into questions surrounding individual behavior and moments likely to attract attention online.
That combination of sport, celebrity and speculation helps explain why Messi and Ronaldo remained two of the tournament's biggest names from a trading perspective.
soccer News Can Change Market Expectations Quickly
Prediction markets are constantly repriced as new information becomes available. Team selection, injuries, suspensions and comments from managers can all affect how traders assess an upcoming event.
Following current soccer news can therefore provide context for why a contract suddenly moves from one probability to another. Markets involving players such as Messi and Ronaldo can be particularly sensitive because developments involving either star attract immediate global attention.
The important distinction is between learning something new and identifying information the market has already absorbed. Once thousands of traders have reacted, the contract price may already reflect the latest development.
What Prediction Markets Actually Tell Us About Messi and Ronaldo
If prediction-market volume is treated as a measure of attention, Messi emerged as the clear leader during the 2026 World Cup. His $40.46 million in player-related trading was nearly three times Ronaldo's $13.63 million and made him the tournament's most-traded player.
But the figures say more about the growth of prediction markets than they do about which soccerer is greater.
Nearly 60,000 World Cup outcomes were available across Polymarket and Kalshi, ranging from major match results to highly specific player events. With more than $14 billion traded during the tournament, soccer became a demonstration of how prediction markets can transform fan expectations into continuously changing prices.
Messi and Ronaldo have been compared using almost every soccer statistic imaginable. Prediction markets have now added another one, not goals or trophies, but millions of dollars in trading activity attached to what fans think they will do next.