Betby Launches “Betby Predictions”: A Fixed-Odds Revolution for Prediction Markets

by Dimitri Dimitrov Published on April 3, 2026
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Betby Predictions offers 24/7 engagement on global events, including finance and tech, using a fixed-odds model.

Leading sportsbook provider Betby has officially entered the prediction market sector with the launch of Betby Predictions.

Unlike traditional exchange-based models that require peer-to-peer liquidity, this new vertical offers a fully managed, fixed-odds experience integrated directly into the standard sportsbook interface.

Betby Predictions allows operators to offer markets on non-sporting events including cryptocurrency fluctuations, technological breakthroughs, and major entertainment awards. By removing the complexity of liquidity pools, the product enables a “simple, scalable, and familiar” format for traditional sports bettors who wish to engage with global news cycles.

Kirill Nekrasov, Head of Innovation and R&D at Betby, explained the vision:

“Betby Predictions represents a natural evolution of the sportsbook experience. We’re taking the core principles of betting and applying them to the world beyond sports. This is about turning global moments into interactive opportunities for players, in a way that’s both scalable and responsible.”

AI-Driven Markets with Human Oversight

The platform generates hundreds of new markets weekly using AI-driven content generation, which identifies trending topics in real time. However, Betby has implemented strict ethical safeguards.

Betby Predictions explicitly excludes sensitive topics such as active conflicts, geopolitics, or events involving human suffering. All AI-generated content is subject to human review to ensure market integrity and appropriateness.

Dimitri Dimitrov

Dimitri is an iGaming expert with nearly a decade of experience and a knack for crafting content that speaks directly to the iGaming crowd. He understands affiliate marketing, player psychology, and search algorithms, which enables him to write engaging, data-driven articles.

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