Forecasting markets allow traders to buy and sell outcome shares based on what they believe will happen in the future. As participants act on news, research, and personal insights, the market probability adjusts, creating a live forecast of the event’s likelihood. Unlike polls or expert opinions, forecasting markets rely on incentives—traders profit when they’re right—which helps produce reliable signals.
Platforms like Polymarket, Kalshi, Myriad, and Manifold run forecasting markets across politics, economics, technology, sports, and more. These markets capture evolving beliefs, reacting instantly when new information appears. Over time, forecasting markets produce rich prediction markets data that shows how expectations change and how crowds interpret uncertainty.
Forecasting markets are used by individuals, researchers, and institutions to understand sentiment, model scenarios, and track real-time expectations for fast-moving events.
Forecasting markets turn collective knowledge into actionable probabilities. They generate high-quality prediction markets data that helps analysts interpret trends, evaluate uncertainty, and understand how events are expected to unfold.
They are effective because they aggregate diverse information from many independent traders. Participants react to news and signals in real time, and their trades encode that information into probabilities. These incentives-driven forecasts often outperform traditional models, making prediction markets data a powerful tool for understanding what the crowd truly expects.
Forecasting markets provide clear, continuously updated probabilities instead of vague sentiment or qualitative analysis. Organizations can use these probabilities to assess risk, compare scenarios, and make data-driven decisions. The detailed prediction markets data—price paths, volatility patterns, and liquidity signals—helps users understand not just what the market believes, but how confidently those beliefs are held.
Analysts can study how probabilities react to new information, identify periods of uncertainty, compare forecasts across event types, and evaluate accuracy after events resolve. Forecasting markets also reveal behavioral patterns—such as information shocks, lagging reactions, or mispricing signals—embedded in prediction markets data.
A widely traded Polymarket market forecasting the outcome of a regulatory decision tracks sentiment over days or weeks. As lawmakers release statements or relevant news breaks, traders adjust their positions, producing a continuously updated forecast that analysts follow closely.
Forecasting markets generate time-sensitive probability data ideal for modeling and analysis. FinFeed's Prediction Markets API provides structured prediction markets data— latest probabilities, historical paths, resolution outcomes, and liquidity metrics—making it easy for developers to build tools that analyze, visualize, or integrate forecasting markets.
