Confidence Score Feed
In prediction markets, a probability alone does not explain how trustworthy a forecast is. A confidence score feed tracks additional indicators that reflect reliability, such as liquidity depth, participation consistency, and volatility.
The feed updates as market conditions change. When trading is deep and prices are stable, confidence scores tend to rise. When markets are thin, volatile, or fragmented, confidence scores usually fall.
Confidence score feeds are especially useful during periods of rapid price movement. They help distinguish strong belief updates from fragile, short-lived reactions. Over time, these feeds reveal patterns in market behavior. Some markets maintain high confidence for long periods, while others fluctuate frequently despite similar probability levels.
For analysts, a confidence score feed adds a second dimension to prediction markets data. It enables better weighting of forecasts, improves filtering, and reduces reliance on raw probabilities alone.
Why It Matters
Confidence scores help users judge whether a forecast should be trusted. They reduce the risk of overreacting to weak or unstable prediction markets signals.
What is a confidence score feed in prediction markets?
In prediction markets, a confidence score feed is a time-series signal that estimates forecast reliability. It reflects how well-supported a probability is by market activity. High scores indicate strong consensus and stability. Low scores signal uncertainty or weak participation.
How does a confidence score feed improve prediction markets data analysis?
A confidence score feed helps analysts separate meaningful probability changes from noise. It adds context around liquidity, volatility, and participation strength. Analysts can weight forecasts based on confidence rather than treating all probabilities equally. This leads to more robust models and interpretations.
Why is a confidence score feed important for prediction markets APIs?
Prediction markets APIs deliver the raw data needed to compute confidence scores, such as prices, volume, and trade frequency. A confidence score feed built on top of API data allows real-time reliability tracking. Analysts can automate filtering, alerts, and model adjustments. APIs make confidence scoring scalable across many markets.
Real-World Example
On Polymarket, two outcomes may show the same probability at a given moment. A confidence score feed can highlight which one is backed by deeper liquidity and steadier trading, making it the more reliable forecast.
Confidence Score Feed and FinFeedAPI
FinFeedAPI’s Prediction Markets API provides prediction markets data suitable for building confidence score feeds. Analysts can combine liquidity metrics, volatility measures, and participation signals into continuous confidence indicators. This supports forecast weighting, monitoring, and model validation. The API enables consistent confidence score tracking across prediction markets.