A probability feed delivers live updates from prediction markets, making it easy to track how expectations shift in real time. Instead of refreshing a market manually, the feed provides an ongoing flow of probability data that reflects current sentiment, new information, and evolving trader activity. This creates a clear, dynamic view of how the market’s forecast is forming.
Platforms such as Polymarket, Kalshi, Myriad, and Manifold generate rich probability streams as users trade outcome shares. These feeds capture early reactions, information shocks, liquidity-driven shifts, and slow sentiment changes. Over time, the feed offers a detailed record of belief formation, turning raw prediction market activity into structured prediction markets data suitable for analysis, automation, and visualization.
Probability feeds are especially valuable for analysts, developers, and tools that need real-time forecasting signals—such as alert systems, research dashboards, or automated trading/analytics models.
Probability feeds convert prediction market activity into immediate, actionable insights. They allow faster interpretation of crowd expectations and improve the usefulness of prediction markets data across applications.
They are important because probabilities can change rapidly as new information appears. A probability feed captures every update in real time, enabling analysts to react faster, identify meaningful shifts, and avoid relying on outdated forecasts. This makes prediction markets data more responsive and accurate for decision-making.
Probability feeds allow dashboards and models to update automatically, showing live probability curves and immediate reactions to news. Tools can highlight sudden movements, trigger alerts, or analyze patterns without delay. This enhances situational awareness and helps users distinguish real signals from noise. The result is prediction markets data that fuels more precise forecasting workflows.
Analysts can observe how quickly markets process information, identify volatility spikes, detect information latency, and compare reactions across different event types. They can also evaluate whether markets adjust smoothly or show signs of mispricing or manipulation attempts. These insights make prediction markets data easier to interpret and more valuable for research.
A forecasting team monitoring a Polymarket probability feed sees a sharp, sudden move during a major political announcement. The feed captures the jump instantly, allowing analysts to flag the update as an information shock and review the underlying news within seconds.
Probability feeds depend on consistent, time-stamped forecast updates. FinFeed's Prediction Markets API provides prediction markets data developers can use to build live feeds, alert systems, visual dashboards, and analytical tools that track probabilities as they evolve.
