Prediction Markets Expand Rapidly as Operators Face New User Profiles

Prediction Markets Process Tens of Billions in Volume – iGaming Operators Confront a Distinct New User Base

Key Takeaways

• Kalshi processed 43 billion dollars in trades in 2025, with monthly volumes rising from under 100 million dollars in early 2024 to more than 20 billion dollars by early 2026.
• On Super Bowl Sunday 2026, 871 million dollars were traded on a single prediction market platform in one day.
• The average prediction market bet is 185 dollars, compared to 55 dollars on a sportsbook.
• About 2 percent of users account for roughly 90 percent of total trading volume.
• Between September 2025 and February 2026, two major sportsbook platforms recorded a 13 to 18 percent year over year drop in new app installs, while Kalshi added 6.3 million new users.

Trading Volumes Show Rapid Growth in Prediction Markets

Prediction markets, long considered a niche segment, have recorded sharp increases in trading activity. According to the figures cited, Kalshi processed 43 billion dollars in trades in 2025 alone. Monthly volumes expanded from less than 100 million dollars at the beginning of 2024 to more than 20 billion dollars by early 2026.

Single event activity has also reached levels comparable to major sports betting days. On Super Bowl Sunday 2026, 871 million dollars moved through one prediction market platform within 24 hours. These figures indicate that the vertical has moved beyond experimental status and now operates at a scale that places it alongside established online betting segments.

Regulatory and infrastructure developments have accompanied this expansion. Gibraltar issued its first prediction market operator license, and business to business infrastructure providers have started to enter the space. This combination of licensing activity and service development suggests that parts of the regulated gambling ecosystem are beginning to integrate prediction style products into their planning.

User Demographics Differ from Traditional Sportsbook Profiles

Data referenced by Turbo Stars shows that prediction market users do not align with the standard sportsbook or casino customer profile. The core demographic falls into the 25 to 34 age group, skews male, and reports above average income and education levels. Around 26 percent hold graduate degrees, and 30 percent earn between 100,000 and 150,000 dollars annually.

This group is described as competitive, status conscious, and highly engaged with current affairs. Rather than focusing on team lineups or casino promotions, they follow news, macroeconomic developments, and geopolitical events. For these users, the surrounding information environment is central, and the platform functions primarily as a venue to act on their views.

Acquisition channels reflect this difference. Traffic to prediction markets comes mainly from news outlets, financial tools, and social media platforms. Traditional sportsbook affiliate networks or casino review sites play a lesser role. For operators, this means that established marketing funnels may not reach this audience effectively.

Higher Average Stakes and Concentrated Volume

Bet sizing and frequency also diverge from typical sportsbook patterns. The average prediction market bet stands at 185 dollars, compared to 55 dollars for a sportsbook wager. Engagement levels are correspondingly high. Around 21 percent of users trade daily, and another 29 percent trade several times per week.

At the same time, trading volume is heavily concentrated. Approximately 2 percent of users account for about 90 percent of total volume. This concentration resembles the high value player dynamic seen in casinos and sportsbooks, but the underlying profile differs. Instead of jackpot oriented high rollers, these users are characterized as individuals placing significant capital behind specific economic or geopolitical theses.

For operators evaluating entry into the segment, this concentration implies that a relatively small group of high frequency participants can drive a large share of revenue, while a broader base of occasional traders contributes lower volumes.

Limited Direct Cannibalization but Shifts in New User Growth

Leading sportsbook operators have publicly stated that prediction markets are not materially cannibalizing their existing business. The data cited indicates that only around 5 percent of legal sportsbook handle has shifted to prediction markets, suggesting limited direct substitution among current customers.

However, new user trends point to a structural change in acquisition. Between September 2025 and February 2026, the two largest sportsbook platforms saw new app installs decline by 13 to 18 percent year over year. During the same period, Kalshi added 6.3 million new users.

According to the analysis, prediction markets are attracting users who may not yet have engaged with traditional sportsbooks. Users active on both platforms reportedly underperform on each compared to single platform users, indicating limited overlap in core customer value.

For comparison platform users, this distinction matters. A prediction market account may not function as a direct substitute for a sportsbook account, and vice versa. The products differ in structure, event selection, and user motivation.

Implications for Product Design and Retention Models

The structural differences extend to product mechanics. Retention tools commonly used in sportsbooks, such as odds boosts, may not resonate with users who place larger stakes on macro or political outcomes. Engagement appears tied more closely to news cycles and real time developments than to traditional betting promotions.

As prediction markets move from peripheral experiments to formal roadmap items for operators, the focus has shifted toward understanding user behavior before integrating similar products. Turbo Stars reports that operators across multiple markets are assessing how to design acquisition and engagement strategies that match this specific audience profile.

The emphasis, according to the data cited, lies on observation and iteration. Operators considering entry into prediction markets must account for distinct acquisition channels, higher average stakes, concentrated volume distribution, and user motivations centered on information rather than entertainment alone.

Our Assessment

The figures presented show that prediction markets have reached substantial trading volumes and attracted millions of new users within a short timeframe. User demographics, acquisition channels, stake sizes, and volume concentration differ significantly from traditional sportsbook patterns. While direct cannibalization appears limited, shifts in new user growth indicate that prediction markets are engaging a separate and growing segment of the online wagering audience. For operators and comparison platform users, the data highlights structural differences between the two models rather than simple substitution.