Prediction markets have experienced a remarkable surge in popularity, quickly evolving from a niche idea into one of the hottest topics in betting today. A significant turning point was the 2024 US elections, which propelled prediction markets into the spotlight and has since fueled rampant growth.
Data from H2 Gambling Capital indicates that prediction markets related to the NCAA March Madness event handled approximately $16 million in 2025, with projections suggesting this number could skyrocket to around $530 million for the college basketball tournament in 2026.
Yurii Berest, the CEO of sportsbook solution provider DATA.BET, cites multiple reasons behind the rapid adoption of prediction markets. These include an expanded variety of events for bettors to engage with and an enhanced presentation of those markets. "Historically, betting has been concentrated around sports," Berest explains. "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. For many users, those subjects are at least as familiar as traditional sports markets, which significantly broadens the potential audience."
He adds that prediction markets have become easier to understand and more engaging for users. Participants can track how the implied probability of outcomes adjusts with new information, transforming the market into a source of real-time content. "I think the combination of a much broader range of relevant events and a more accessible way to engage with them has pushed prediction markets from a relatively niche format into mainstream conversation," Berest comments.
Accessibility and presentation were pivotal when DATA.BET launched its own prediction markets in April. They adopted a "sportsbook logic," aiming to simplify the structure of exchanges by featuring clear pricing, fiat transactions, and an intuitive user experience.
"Operationally, it’s a new vertical; experientially, it’s designed to feel like a natural extension," Berest notes. Users can bet on a wide range of events—from politics and finance to culture and weather—without needing to understand complex mechanics or deal with cryptocurrency.
"We see it as a separate category, even though it sits within the sportsbook experience," Berest clarifies. The familiar interface allows users to engage through the same user experience they already know, and integration for operators is straightforward via API, negating the need for additional configurations.
Since launching this vertical, DATA.BET has also added new market types and richer live and historical data, aligning with the broader trend in prediction market growth, as observed with platforms like Polymarket. "Prediction markets are a good example of how a mature industry can still create new engagement," Berest adds.
He emphasizes that the evolution of the betting product is ongoing, highlighting users' interest in not just traditional sports betting, but also fresh content and novel engagement methods. Users have the opportunity to follow market developments such as changes in probability and volume even before placing a bet.
For the iGaming sector, Berest emphasizes the importance of prioritizing new formats and mechanics over copying existing models. "Prediction markets are a good example of how the industry can still create new engagement by rethinking what users can bet on and how they interact with that content," he explains.
Different prediction market products employ varying underlying models, ranging from peer-to-peer exchanges to fixed-odds approaches. Each has its advantages. Exchange-based markets offer effective price discovery since prices reflect active market behavior and liquidity. However, they tend to add complexity that could deter casual sportsbook users.
DATA.BET merges aspects from both models, ensuring user experience remains intuitive, while maintaining market-driven pricing that responds to liquidity and market dynamics. "This means users do not need to engage with an order book or learn a trading interface, while pricing still reflects market activity," Berest states.
Additionally, real-time data and automation are vital for the scalability of prediction markets. Rapid shifts in markets necessitate that pricing, exposure management, and settlement workflows function with minimal manual input. Berest underlines the growing need for event monitoring, especially for markets linked to fast-changing real-world situations. Furthermore, AI can assist in monitoring and automating operational tasks, but the core pricing and settlement logic must remain transparent and clear.
Trust is paramount for the long-term viability of prediction markets. Settlement rules should be predetermined, ensuring no ambiguity exists during resolution. Automated and auditable processes will confirm that the rules are followed consistently, fostering confidence in the pricing mechanism. "Ultimately, consistency is what builds trust," Berest explains.
Looking forward, Berest envisions prediction markets becoming less defined by their label and integrating seamlessly with other “bettable” content like sports and esports. He anticipates an increase in short-duration markets that resolve frequently, enhancing user engagement patterns. Simplifying the user experience will be key, allowing users to easily comprehend market mechanics regardless of the underlying pricing model. "What matters is that the market is easy to understand and users can bet immediately using their existing balance," he concludes, indicating a future where real-world events become an integrated part of the betting experience.
