Prediction markets have surged in popularity, shifting from a niche concept to a significant player in the betting landscape. A major turning point came with the U.S. election in late 2024, which propelled these markets into public discourse. Following this event, the growth trajectory of prediction markets has been steep.
H2 Gambling Capital reports that prediction markets generated $16 million during March Madness in 2025, with projections suggesting a skyrocketing to $530 million for the tournament in 2026.
Yurii Berest, CEO of DATA.BET, attributes this rapid rise to several factors. He points out the expansion of events available for betting, beyond traditional sports, into areas like politics, technology, economics, and entertainment. "Historically, betting has been concentrated around sports," Berest remarks. "Prediction markets extend that behavior into subjects people already follow closely in everyday life, significantly broadening the potential audience."
Moreover, these markets have become more intuitive and engaging. Participants now bet not just on outcomes but also on the shifting probabilities as new information emerges, transforming the market into a type of real-time content.
This focus on presentation and accessibility influenced DATA.BET's prediction market launch in April. The company adopted a "sportsbook logic," aiming to simplify the user interface by offering clear pricing and fiat transaction options, thus creating an enjoyable experience.
Although integrated into the existing sportsbook setting, prediction markets stand alone within the DATA.BET solution. Users can place bets on a diverse range of topics like politics and finance without facing the usual complexities of cryptocurrency or intricate mechanics. “We see it as a separate category,” Berest says, noting that it still connects to the familiar user experience.
In terms of user interaction, DATA.BET's platform remains designed for sportsbook participants rather than traditional traders. This means users encounter a recognizable betting interface using standard decimal odds alongside their existing balance in both fiat and crypto.
Since its initial rollout, DATA.BET has expanded with more market types and enriched data, reflecting the broader dynamism seen in prediction markets, evidenced by platforms like Polymarket.
Berest believes that the betting product holds significant potential for further evolution. He notes, “The rise of platforms like Polymarket shows that users are interested not only in traditional sports betting, but also in new types of content and new ways to engage with events they already follow closely.”
The iGaming sector should look towards new formats and mechanics rather than strictly adopting the exchange model, he adds. Prediction markets illustrate how a mature industry can remain engaging by rethinking user interactions.
Distinct differences exist among prediction market models, which vary from peer-to-peer exchanges to fixed odds. Each model has unique advantages; exchange-based markets excel in price discovery due to their reflection of market activity. However, they can introduce complexity that may alienate standard sportsbook users.
DATA.BET seeks to merge these models, maintaining a user-friendly experience while adopting market-driven pricing based on exchanges and liquidity dynamics. This approach allows for a familiar interaction without forcing users to navigate trading interfaces.
Real-time data and automation are essential for scaling prediction markets effectively. “Markets can move quickly, so pricing and settlement workflows need to operate with minimal manual intervention,” Berest explains. He elaborates on the growing need for automated event monitoring to adapt to real-world developments, leveraging AI for classification and anomaly detection while keeping pricing processes transparent.
Trust in prediction markets hinges on clearly defined and consistent settlement rules established prior to market launch. This clarity minimizes ambiguity during resolution, promoting user confidence in the betting process. Berest emphasizes, "Users need to understand how a market will be resolved and have confidence that the pricing process is consistent."
Looking to the future, Berest anticipates a decline in the significance of the prediction market label itself, as betting on real-world events continues to expand as a category alongside sports and esports. He envisions shorter-duration markets and more frequent resolutions leading to consistent engagement patterns.
"Most users will not care whether the pricing comes from an exchange or a liquidity model," Berest notes. "They will care about how easy it is to understand the market and whether they can bet immediately with their existing balance. That is where I see the category heading: a wider array of real-world events, faster market cycles, and increasingly sophisticated mechanics wrapped in a simpler user experience."
