Outcome Likelihood Curve
An outcome likelihood curve is a time-based view of probability. Instead of looking at a single number, it traces how confidence rises, falls, or stabilizes throughout a market’s life. Each point on the curve reflects the market’s belief at that moment.
In prediction markets, these curves are built from continuous price updates. As traders react to news, delays, confirmations, or uncertainty, the curve bends accordingly. On platforms like Polymarket, Kalshi, Myriad, and Manifold, outcome likelihood curves often show early volatility, mid-period adjustments, and late-stage convergence. This pattern is clearly visible in prediction markets data.
The curve helps distinguish different behaviors. Sharp jumps suggest information shocks, slow slopes suggest gradual learning, and flat sections suggest consensus or inattention.
Why It Matters
Outcome likelihood curves reveal how beliefs change, not just where they end. They add depth to prediction markets data by showing the full forecasting process.
How is an outcome likelihood curve different from a single probability?
A single probability is a snapshot. An outcome likelihood curve shows the full path of belief over time. This makes it easier to understand momentum, reversals, and confidence changes within prediction markets data.
What can analysts learn from the shape of an outcome likelihood curve?
Analysts can identify overreactions, anchoring, information shocks, and correction phases. The curve’s slope and smoothness reveal how quickly and confidently the market processes information. These insights help interpret prediction markets data beyond final outcomes.
How are outcome likelihood curves used in analysis?
They are used to compare events, evaluate forecast stability, and measure learning speed. Analysts often align curves from similar events to study patterns. This makes outcome likelihood curves a core tool for working with prediction markets data.
Real-World Example
A Kalshi market tracking a regulatory deadline shows a volatile curve early on, with sharp moves after rumors. As official confirmations arrive, the curve smooths and trends steadily upward, reflecting growing confidence before resolution.
Outcome Likelihood Curve and FinFeedAPI
Analyzing outcome likelihood curves requires clean, time-stamped probability histories. FinFeed's Prediction Markets API provides structured prediction markets data: orderbooks, prices, trades and OHLCV, allowing developers and analysts to build curves, compare belief evolution, and study forecasting behavior over time.