Behind $10.8 Billion in Weekly Trading Volume: Why Did Prediction Markets Boom During the World Cup?

In June 2026, on-chain prediction markets reached a historic moment. Data disclosed by a16z crypto shows that weekly trading volume in prediction markets hit $10.8 billion for the first time, setting an all-time record. This figure not only easily surpassed the previous weekly record of $8.7 billion, but also marked the first time prediction markets broke the $10 billion weekly threshold.

More striking are the structural numbers: after the World Cup kicked off, Polymarket’s football category day trading volume jumped from about $53 million to $220 million, an increase of roughly 315%; Kalshi’s open interest first broke $1 billion, reaching $1.16 billion, up 350% year to date; and total open interest in prediction markets reached $1.8 billion in June, up 54.3% from the previous month.

These figures point to a clear conclusion: prediction markets are undergoing a structural revaluation of value.

Where does $10.8 billion weekly trading volume rank in industry history?

To understand the weight of $10.8 billion, you need to look at it across a longer timeline.

In 2024, the total trading volume across the entire prediction market sector was only $15.8 billion. In 2025, that number soared to $63.5 billion—about a fourfold increase year over year. Entering 2026, the growth curve steepened further: global prediction market trading volume in Q1 jumped to $75 billion, versus just $440 million in the same period of 2024.

On a monthly basis, in January 2026 industry monthly trading volume exceeded $21 billion—more than 170 times the same period in 2025. Monthly trading volume reached $29.4 billion in May. The combined monthly trading volume of Kalshi and Polymarket surged from under $5 billion in September 2025 to about $24 billion in April 2026—nearly a fivefold increase in seven months.

Against this backdrop of growth, $10.8 billion in weekly trading volume is not an isolated peak, but a natural point along a steadily steepening upward curve. Analysts at investment bank Bernstein estimate that total volume in 2026 will reach $240 billion, up 370% from 2025. If calculated using an approximately 80% compound annual growth rate between 2025 and 2030, the annual trading volume of prediction markets could exceed $1 trillion by 2030.

How did the World Cup become the core catalyst for a prediction market breakout?

The 2026 FIFA World Cup is the most direct catalyst for current prediction market growth, but its role goes far beyond simply “bringing in traffic.”

Polymarket’s World Cup winner contract was launched in July 2025. Trading volume rose from $368 million on March 25, 2026 to over $1.2 billion in May. After June arrived, as team rosters were finalized, friendly match results rolled in, and the group stage officially began, trading momentum accelerated noticeably—trading volume reached $342 million in the past week and $881 million in the past month. As of June, Polymarket’s World Cup winner contract trading volume had already surpassed $3 billion.

In the World Cup’s first week, the overall sports notional trading volume for prediction markets reached $7.18 billion, setting a new all-time high. Bernstein analysts estimate that just the World Cup events themselves could generate an additional $5 billion to $10 billion in prediction market trading volume. Since Polymarket launched its World Cup markets in July 2025, cumulative trading volume has reached $2.5 billion, making it one of the platform’s largest single markets.

The fundamental reason the World Cup generates such a massive catalytic effect lies in the strong fit between the structure of the event itself and the product form of prediction markets. 48 teams, more than 100 matches, continuous real-time information updates—this kind of high-frequency, multi-variable information environment is naturally suited to a “money votes” pricing mechanism. Each match result changes the probability distribution of subsequent events, requiring market participants to continuously adjust positions to reflect new information. This ongoing repricing process is the internal driver that amplifies prediction market trading volume like a snowball.

What market-structure changes are reflected by the football category’s daily trading volume rising from $53 million to $220 million?

Polymarket’s football category daily trading volume surged from $53 million to $220 million (+315%). The significance of this data goes far beyond a simple percentage increase.

First, it indicates a fundamental shift in users’ trading behavior patterns in prediction markets. Historically, the bulk of trading volume in prediction markets concentrated on political events such as elections, with a clear “pulse” characteristic—bursts before events and then a rapid drop after. But the sustained high trading volume in football during the World Cup shows that sports events can generate more stable, more sustainable trading flows than political events. By the end of 2025, sports markets had already accounted for 85% of Kalshi’s trading volume.

Second, a daily trading volume of $220 million means prediction markets have achieved systemic importance in pricing sports information. At this scale, they are enough to compete with traditional sports betting. Mainstream finance media such as Bloomberg have begun citing Polymarket odds as indicators of market sentiment.

Third, this growth is not driven solely by retail investors. On Polymarket, there have been individual bets exceeding $1 million. Kalshi, which is regulated by the U.S. Commodity Futures Trading Commission and supports direct USD deposits, is attracting more U.S. institutions and high-net-worth users to hold positions long term. The institutionalization of capital structure is an important sign that the market is maturing.

Why did institutional capital concentrate into prediction markets in 2026?

If prediction markets used to be more like a retail game, the most notable change in 2026 is that institutional capital is accelerating into the market.

In March 2026, Intercontinental Exchange, the parent company of the New York Stock Exchange, completed a $600 million investment in Polymarket. Cboe launched Cboe Predicts, offering options products with the S&P 500 as the underlying; Nasdaq obtained product approval; and the parent company of the New York Stock Exchange directly invested $2 billion into Polymarket. All three Wall Street exchange operators entered prediction markets in the same month.

The logic behind the influx of institutional capital is not purely speculative arbitrage, but recognition of prediction markets’ long-term value as “information infrastructure.” A report recently released by the Korean venture capital firm Hashed notes that prediction markets are evolving from simple betting platforms into “next-generation information infrastructure” that can aggregate collective intelligence. In 2026, prediction markets are no longer defined as “gambling” or “derivatives”; they are being redefined as: decentralized information aggregation and pricing systems.

From the standpoint of business-model sustainability, Polymarket’s 24-hour revenue rose to $1.26 million on June 16, ranking sixth among all crypto protocol revenue. The platform reported annualized revenue between $700 million and $880 million, and cumulative revenue had already exceeded $1.15 billion as of mid-2026. For a sector that has existed only for a few years, being able to switch revenue momentum across different types of events—from a smooth transition from the 2024 U.S. presidential election to major sports IP—is itself a testament to business-model resilience.

How do prediction markets’ pricing mechanisms differ fundamentally from traditional financial instruments?

To grasp the deeper meaning of $10.8 billion in trading volume, you first need to understand the core pricing logic of prediction markets.

The mechanism of crypto prediction markets is not complicated: users buy and sell contracts linked to the outcome of future events. For each contract, if the event occurs the payout is $1, and if it does not occur the payout is $0. Contract prices float between $0 and $1, directly corresponding to the market’s pricing of the event’s probability.

Unlike traditional sports betting where bookmakers set the odds, prediction markets’ prices are determined entirely by participants’ trading behavior. This “money votes” mechanism naturally aggregates fragmented market information—anyone can express their judgment by buying or selling contracts. When Germany beat Curacao 7-1, the market’s expected win probability for Germany in the subsequent match was often revised upward by about 5 to 10 percentage points. This adjustment is not an analyst’s subjective judgment; it happens through new capital entering the relevant contracts and pushing contract prices higher.

The advantage of this mechanism is that it enables faster information transmission, more timely pricing, and broader coverage. In today’s fast-changing information economy, this dynamic is becoming increasingly valuable. Every trade represents a view backed by capital, making prediction markets a more and more valuable market-sentiment indicator.

However, this mechanism also comes with its own risks. During the World Cup group stage, the rare scenario in which all 4 group matches ended in draws caused both to be fully losing bets: a $8.6 million position betting on Belgium defeating Egypt, and a nearly $1 million position betting on Spain defeating Cape Verde. The discrepancy between probability pricing and the actual results is exactly what leads traders to profit or lose.

What structural risks and regulatory challenges are prediction markets facing?

Rapid growth always needs to be viewed with balance.

Regulatory clarity remains one of the biggest challenges in the field. Total open interest in prediction markets reached $1.8 billion in June; this scale is large enough to draw the attention of policymakers. Market manipulation, responsible participation, and platform governance will continue to shape the industry’s credibility.

Another structural risk worth noting is liquidity sustainability. Some analysts point out that any situation where daily trading volume after the World Cup continues to fall and sustains below $100 million would indicate that the liquidity “escape velocity” threshold is being tested from below. Whether prediction markets can maintain sufficient trading depth outside major events is the key test for moving from an “event-driven” model to “continuous operation.”

In addition, the composition of prediction markets’ participants is also worth paying attention to. A Q1 2026 report jointly disclosed by Bitget Wallet and Polymarket shows that among 2.5 million accounts, 84% are losing money. High volatility means most participants struggle to keep making profits consistently, which could affect user retention and long-term liquidity.

Can prediction markets become the next-generation financial infrastructure?

Prediction markets are gradually evolving from edge-of-the-market event trading tools into financial infrastructure that prices uncertainty in the real world.

The logic behind this evolution is that markets able to efficiently aggregate information tend to become more valuable over time. Whether stocks, commodities, derivatives, or digital assets, liquidity and reliable price discovery are always the foundation for long-term adoption.

The unique value of prediction markets lies in the breadth of their application scenarios. During the 2024 U.S. presidential election, Polymarket users accurately predicted Trump’s victory a month in advance, demonstrating clear advantages over traditional polling in forecasting swing states. During the 2026 World Cup, sports events demonstrated the efficiency of prediction markets in real-time information pricing. Contracts such as those tied to the shipping status in the Strait of Hormuz also show prediction markets’ potential for pricing geopolitical risks.

In the long run, companies may use prediction markets to gauge consumer expectations, investors may incorporate them into risk analysis, and researchers may rely on them to better understand collective market wisdom. What once appeared to be experimental blockchain applications is steadily developing into an ecosystem that can influence information pricing and interpretation across multiple industries.

From the technical layer, prediction markets are a typical use case for blockchain. Transparency, settlement speed, and permissionless access—these are precisely the capabilities that blockchain technology itself provides. Every dollar of trading volume flowing through prediction markets is demonstrating that decentralized financial infrastructure is indeed usable in the real world.

Summary

In June 2026, prediction markets’ weekly trading volume exceeded $10.8 billion; Polymarket’s football daily trading volume surged from $53 million to $220 million (+315%); and Kalshi’s open interest first broke $1 billion. Taken together, these data point to a clear trend: prediction markets are transforming from a niche crypto experiment into an emerging financial sector with systemic importance.

The World Cup is a direct catalyst, but the deeper drivers are: institutional capital accelerating into the market, validation of the efficiency of pricing mechanisms, and a broad expansion of application scenarios from elections to sports, geopolitics, macroeconomics, and beyond. Regulatory uncertainty, liquidity sustainability, and the structure of user participation remain key challenges for the sector. In any case, prediction markets have already proven they are not just “another crypto narrative”—they are becoming a new type of financial infrastructure for pricing uncertainty in the real world.

FAQ

Q1: What does the $10.8 billion weekly trading volume in prediction markets mean?

This is the first time prediction markets have broken the $10 billion weekly threshold. In 2024, the total annual trading volume of the sector was only $15.8 billion, while in 2026 a single week already reached $10.8 billion. This data marks prediction markets’ move from a small “event-driven” niche into a large-scale trading ecosystem that runs continuously.

Q2: Why did Polymarket’s football daily trading volume grow from $53 million to $220 million?

The core catalyst is the 2026 FIFA World Cup. The number of participating teams increased from 32 to 48, and the number of matches rose by 40. The high-frequency, multi-variable nature of the tournament structure is naturally suited to prediction markets’ pricing mechanism—each match result changes the probability distribution of subsequent events, driving continuous trading activity.

Q3: What is the difference between prediction markets and traditional sports betting?

The core difference lies in the pricing mechanism. Traditional sports betting sets odds through bookmakers, while prediction markets’ prices are determined entirely by participants’ trading behavior. Anyone can express judgment by buying or selling contracts, and the market aggregates dispersed information through a “money votes” approach. In addition, prediction markets operate on blockchain, offering transparency, permissionless access, and real-time settlement.

Q4: Is the growth of prediction markets sustainable?

Sustainability faces multiple tests. Regulatory clarity remains one of the biggest challenges. Whether liquidity can maintain sufficient depth outside major events is a key factor for the sector’s transition from “event-driven” to “continuous operation.” However, institutional capital is accelerating into the market—including the New York Stock Exchange parent company’s $600 million investment in Polymarket—which indicates that long-term capital is betting on sustained growth for this sector.

Q5: How can ordinary investors participate in prediction markets?

Prediction market trading has high volatility and high-risk characteristics. Participants need to fully understand the contracts’ binary payout structure—$1 if the event occurs, and $0 if it does not. It is recommended to thoroughly understand the platform’s mechanism, the background of each event, and one’s own risk tolerance before participating, to avoid making trading decisions based on a single piece of information.