2026 World Cup tailwind fades: what challenges are expected to follow the trading-volume frenzy in the forecast?

The 2026 World Cup across the US, Canada, and Mexico is not only a football spectacle, but also a window period with the highest concentration of trading volume in the history of crypto prediction markets. From the tournament kickoff on June 11 to the final on July 19, prediction platforms such as Polymarket experienced an unprecedented surge of capital inflows. However, only a few days after the event ended, daily trading volume and fee revenue dropped sharply. So is this round of event-driven growth a prelude to prediction markets going mainstream—or a one-off pulse that’s hard to replicate?

What scale of trading did prediction markets create during the World Cup?

To understand the scale of this growth, we need to look at it from two dimensions: total volume and market structure. As of mid-July, Polymarket and Kalshi together handled about $5.81 billion in trading volume across 52 major and minor 2026 FIFA World Cup prediction markets. Of this, Polymarket led with about $4.21 billion, while Kalshi contributed about $1.17 billion.

Looking only at World Cup-related event trading volume, Kalshi recorded $13.59B, while Polymarket reached $10.36B; the gap narrowed to about 1.3 times. If all-platform total trading volume is included, Kalshi’s total trading volume during the World Cup was $54.34B, about 2.6 times that of Polymarket ($20.99B). predict.fun, a new platform launched for just over half a year, saw total platform trading volume of $1.09B during the period, with World Cup-related markets contributing $886M.

This scale of capital inflow suggests that prediction markets have evolved from a niche experiment in the crypto circle into a trading venue capable of carrying large amounts of capital. Polymarket’s World Cup champion prediction contract saw cumulative trading volume exceed $4 billion, surpassing the $3.69 billion record set by the 2024 US election. From $138k during the 2022 Qatar World Cup to $4.1 billion in 2026, growth over four years amounts to more than 40kx.

Where does nearly $100 million in quarterly fees sit in the industry cycle?

The surge in trading volume directly translated into platform revenue. According to data disclosed by crypto venture firm 1kx, in 2026 Q2, on-chain protocol fees fell 33% year over year, showing a typical bearish-market pattern. DEX fees saw the biggest decline, down 57% year over year, reducing by about $625 million. However, perpetual contracts and prediction market fees grew against the trend, up 22%—and Polymarket’s quarterly fees approached $100 million. Canton Network and Polymarket both made their first entry into the top 20 list of on-chain protocol fee rankings.

Focusing on fee income during the World Cup period, Kalshi’s cumulative fee revenue across the entire event totaled $473.2 million, with the highest weekly figure exceeding $100 million. Polymarket’s cumulative revenue was $111.4 million, with weekly revenue steady at around $20 million. During the World Cup, predict.fun generated income of nearly $3.5 million.

Putting these figures into a broader industry context: Polymarket’s quarterly fee revenue approaching $100 million looks especially striking amid an environment where total on-chain protocol fees were down year over year. But this income is highly concentrated in the World Cup window period—the combination of high-frequency trading during the event and a sharp drop in trading volume after the event ends creates a clear revenue volatility curve.

Why didn’t user growth during the event translate into long-term retention?

The explosive growth in trading volume came alongside a rapid expansion of the user base. During the World Cup, around 60% of Polymarket’s betting users had never previously interacted with crypto. This data highlights the unique value of the event as a crypto adoption accelerator—it successfully brought a large number of out-of-circle users into prediction markets.

However, the “quantity” of user growth did not become “quality” in terms of retention. Post-event data shows this growth was a short-term event-driven tailwind and did not translate into long-term activity or capital consolidation across the three major platforms. The overlap between predict.fun’s data showing 120k weekly independent users and the World Cup match schedule is high, with a clear event-driven characteristic. Once the event ended, how to maintain user stickiness became the core challenge.

From the user structure perspective: among Polymarket’s 2.5 million accounts, about 84% are in a losing state; 82.3% of users have quarterly trading volume below $10k; and the median per-trade amount is between $2 and $3. This structure of “long-tail retail plus a small number of big winners” is particularly fragile in event-driven growth—when the event hype fades, retail users who lack ongoing trading motivation quickly churn, while professional traders cannot sustain high-frequency trading in markets with low liquidity.

Why did retention performance diverge significantly across different platforms?

The post-event drop in data was not evenly distributed. During the World Cup, Kalshi’s daily nominal trading volume rose from $580 million in May to $138k during the event, an increase of about 140%. On July 22, trading volume fell back to $494.4 million, already below May’s daily average level. Polymarket’s volatility was similar: from May’s daily average of $228 million, rising to about $538 million during the event.

In terms of post-event fee revenue performance, the divergence was even more pronounced. Kalshi’s post-event fee revenue fell only 9.3% to $11 million per day, the smallest decline; while Polymarket and predict.fun dropped sharply by 40.5% and 36.1%, respectively.

This divergence is rooted in differences in each platform’s trading structure. Kalshi’s trading structure is more diversified—besides the World Cup, other sports events, politics, and macro markets can still continuously contribute trading volume, providing more carryover scenarios for activity after the event ends. Polymarket’s representative markets are more concentrated in US elections, crypto assets, and geopolitical events; while adding the World Cup increases the weight of sports-type markets, after the event ends there is a lack of alternative events of the same scale to fill the gap. Polymarket’s TVL did not rise in sync with trading volume during the event, and continued to decline after the event, reaching about $340 million.

Why is the incremental growth driven by the event hard to solidify into a platform’s base?

What the World Cup brings to prediction markets is fundamentally “event-driven liquidity”—users come because of a specific event, then leave when the event ends. This liquidity has three structural features:

First, the time window is highly concentrated. 104 matches take place over roughly 40 days. Average daily trading volume reaches a peak during the event, but then drops quickly after the event ends to pre-event levels or even lower. This “pulse-like” growth cannot be smoothed into a stable month-over-month or year-over-year growth curve.

Second, the trading instruments are one-off. Contracts such as the World Cup champion, single-match outcomes, and player performance lose their trading value once the event ends. The platform then needs to continuously find the next event with the same level of appeal to maintain liquidity. And from US elections to the World Cup, events that can drive trading volumes on the order of tens of billions of dollars are extremely rare in themselves.

Third, user behavior is “task-oriented.” About 60% of first-time crypto users come because they bet on the World Cup. Their understanding of prediction markets stays at the level of an “event betting tool,” not “financial infrastructure.” When the event ends, these users lack functional reasons to stay on the platform—they will not proactively shift to political predictions or macroeconomic contracts because those areas lack the narrative frameworks and emotional connections they are familiar with.

Has the long-term value of prediction markets been proven by this round of growth?

Even though the post-event data shows a clear “spike then drop” pattern, it’s undeniable that the 2026 World Cup changed the industry landscape for prediction markets in multiple dimensions.

At the market recognition level, prediction markets completed a cognitive shift from an “experiment by crypto niche enthusiasts” to mainstream financial infrastructure. Trading volume of $4 billion-plus for a single event contract means that market makers, quant trading teams, and institutional capital have already deeply participated. This maturity at the infrastructure layer won’t reverse just because a single event ends.

At the product level, sports contracts moved from a supplemental category to a core trading segment, opening a brand-new asset-class space for prediction markets. While World Cup hype can’t last, the product paradigm of “sports events + prediction markets” has been validated—Super Bowl created $1.4 billion in trading volume, and the World Cup pushed that figure to the tens of billions level.

At the competitive landscape level, new platforms like predict.fun leveraged the event window to jump from 0 to nearly $900 million in trading volume. Although the event tailwind is short-lived, for platforms in an early stage, it provides a rare opportunity to cross the cold-start barrier.

Summary

The 2026 World Cup brought $5.8 billion in total trading volume to prediction markets, nearly $100 million in quarterly fee revenue, and user additions in the millions. But the rapid post-event drop in trading volume, the differentiated decline in fee revenue, and the structural difficulties in user retention indicate that this growth was a typical short-term event-driven tailwind, and has not yet turned into long-term platform activity or capital consolidation.

The differences in post-event performance across platforms reveal that long-term competitiveness in prediction markets depends not on the explosiveness of any single event, but on diversification of trading structure and continuity of event coverage. Kalshi’s more diversified trading structure has given it stronger resilience to volatility, while Polymarket needs to find the next event capable of carrying tens of billions of dollars in trading volume after the World Cup to fill the gap.

The long-term value of prediction markets will not be negated by the end of a single event, but the industry needs to be clear: event tailwinds are amplifiers, not engines. The real growth engine lies in whether millions of event-driven users can be converted into long-term users who participate habitually in predictions across many categories—this requires systemic evolution in product format, market coverage, and user education.

FAQ

Q: What was the total trading volume of prediction markets during the 2026 World Cup?

Polymarket and Kalshi together handled about $5.81 billion in trading volume across 52 World Cup-related prediction markets. If all trading across the entire platforms is included, Kalshi’s total trading volume during the World Cup reached $40k, and Polymarket’s was $120k.

Q: What exactly was Polymarket’s fee revenue in Q2?

According to data disclosed by crypto venture firm 1kx, Polymarket’s quarterly fees in Q2 2026 approached $100 million. Against the backdrop of an overall 33% year-over-year decline in on-chain protocol fees, fees for perpetual contracts and prediction markets grew against the trend, up 22%.

Q: How much did trading volume in prediction markets decline after the World Cup ended?

After the event ended, daily average trading volume across platforms fell back to or below pre-event levels. Polymarket’s sports-related trading volume dropped from nearly $2.3 billion to $740 million, a decline of nearly 70%. Kalshi’s trading volume on July 22 was already below May’s daily average.

Q: How do user retention results differ across platforms?

Kalshi’s post-event fee revenue fell by only 9.3%, the smallest decline; Polymarket and predict.fun fell by 40.5% and 36.1%, respectively. This difference mainly comes from Kalshi’s more diversified trading structure—besides the World Cup, other sports, politics, and macro markets still continuously contribute trading volume.

Q: Does this round of growth prove the long-term value of prediction markets?

The World Cup demonstrated prediction markets’ ability to support large-scale capital and the commercial potential of sports-related contracts, but post-event data shows that event tailwinds have not yet translated into long-term user retention or capital consolidation. The long-term value of prediction markets depends on whether platforms can convert event-driven users into sustained participants across categories and across cycles.