Prediction markets have surged in popularity, evolving from a niche idea to a significant player in the betting industry in just a few years. The pivotal moment for this escalation came with the U.S. election in late 2024, which brought prediction markets into wider public awareness. Since then, their growth has been nothing short of phenomenal.
Data from H2 Gambling Capital reveals that the amount wagered in prediction markets during March Madness reached $16 million in 2025, with projections for 2026 suggesting a staggering escalation to an estimated $530 million.
Several factors contribute to this growth, according to Yurii Berest, CEO of sportsbook solution provider DATA.BET. He points out a wider range of events for bettors to engage with and the enhanced presentation of these markets. "Historically, betting has been concentrated around sports. Prediction markets extend that behavior into areas people already follow closely in everyday life, including politics, technology, economics, entertainment, and other major real-world events," he explains. "Those subjects are at least as familiar as traditional sports markets, broadening the potential audience immensely."
Berest emphasizes that prediction markets have also become more engaging and user-friendly. Users aren’t just betting on outcomes; they're able to track how the market's implied probability shifts as new information comes in, turning the market into a real-time content experience. "I think the combination of a much broader range of relevant events and a more accessible way of interacting with them is what has pushed prediction markets from a relatively niche format into mainstream conversation," he adds.
DATA.BET’s foray into prediction markets started in April, focusing on ease of use and clear presentation. The platform applies a "sportsbook logic" to simplify the structural complexities commonly associated with prediction markets, utilizing clear pricing and fiat transactions to enhance the user experience. This approach allows players to place bets on a variety of events, from politics to weather, without diving into complicated systems or needing cryptocurrency.
Berest clarifies, "Prediction markets are a separate category, even though they sit within the sportsbook experience. Users interact with it through a familiar interface, while integration for operators can be achieved via API, requiring no new integrations. However, we built an entirely new subsystem for it, including different pricing logic and risk management."
DATA.BET’s solution, available through iFrame and API integration, caters specifically to sportsbook users rather than experienced traders. This design means bettors can use standard decimal odds and their existing accounts without disruption, whether in fiat or cryptocurrency. Following the vertical's launch, DATA.BET has added more market types and comprehensive market data, riding a wave of broader interest in prediction markets reminiscent of platforms like Polymarket.
Berest observes, "The growth of platforms like Polymarket shows that users are interested not only in traditional sports betting but also in innovative content and ways to interact with events they follow closely. The market itself can enhance the experience, allowing users to monitor changes in probability and market sentiment before betting."
For the iGaming industry, the focus shouldn't solely be on mimicking the exchange model but on identifying new formats and mechanics relevant to users, presented in a familiar experience. "Prediction markets demonstrate that a mature industry can still innovate in user engagement by rethinking what they can bet on and how they interact with that content," Berest notes.
The varied design of prediction market products highlights the ongoing evolution within the industry. From peer-to-peer exchanges to fixed-odds approaches, each model has its advantages. Berest explains that exchange-based markets excel at price discovery due to the reflection of market activity and liquidity, allowing users to feel active in the market rather than just betting against a bookmaker. At the same time, he warns that the complexity of order books and trading execution can present barriers for the average sportsbook user.
DATA.BET incorporates elements from both models. The user experience remains straightforward while maintaining market-driven pricing informed by exchanges and liquidity. "Users don't need to engage with order books or learn trading interfaces, yet the pricing adapts to liquidity and market actions," Berest says, thus allowing operators to introduce prediction markets without confusing their current sportsbook audience.
Automation and real-time data are crucial for scaling prediction markets, not just for pricing but for general management. "Market fluctuations require that pricing, exposure management, market suspension, and settlement workflows operate with minimal manual input," Berest highlights. Event monitoring is particularly vital for fast-paced markets, necessitating timely identification of when conditions change significantly.
To build long-term trust, prediction markets must establish clear rules and consistent settlement processes before opening. Berest asserts that this forthrightness removes ambiguity and builds confidence in pricing and outcomes. "It's essential users understand how a market will resolve and trust that the pricing process is consistent."
Looking toward the future, Berest anticipates a shift where prediction markets are less about their label and more about integrating real-world events as another category of "bettable" content, sitting alongside sports and esports. "As this category develops, I foresee shorter-duration markets and quicker resolutions, leading to a repeated engagement cycle," he states. As user interfaces simplify, the emphasis will be on whether the betting process is straightforward and the pricing is competitive.
