Accuracy Tracking
In prediction markets, forecasts are expressed as probabilities before events resolve. Accuracy tracking compares these probabilities with confirmed outcomes after resolution.
This process goes beyond counting correct or incorrect predictions. It considers confidence levels, timing, and how close probabilities were to the final result. Accuracy tracking can be applied at different stages. Early forecasts, final forecasts, or full probability paths can each be evaluated separately.
Patterns in accuracy reveal strengths and weaknesses. Consistent overconfidence, late learning, or systematic bias become visible when many events are tracked together.
For analysts, accuracy tracking turns prediction markets data into performance metrics. It enables objective evaluation of how well markets forecast reality.
Why It Matters
Accuracy tracking shows whether prediction markets are reliable forecasting tools. It helps users understand trust, limits, and improvement areas.
How is accuracy tracked in prediction markets?
Accuracy is tracked by comparing forecast probabilities with resolved outcomes. Analysts use scoring methods that penalize confident errors more than uncertain ones. Tracking can focus on final forecasts or multiple points in time. This approach captures both correctness and calibration.
What is the difference between accuracy tracking and forecast error?
Accuracy tracking is the ongoing process of evaluation across many events. Forecast error is the result for a specific forecast or moment. Tracking looks for patterns, while error measures individual outcomes. Both are used together in prediction markets data analysis.
How does accuracy tracking improve prediction markets analysis?
Accuracy tracking identifies systematic issues like bias or delayed learning. Analysts use it to refine models, weight forecasts, and filter unreliable markets. Over time, it improves interpretation and confidence assessment. This makes prediction markets data more actionable.
Real-World Example
On Polymarket, analysts may track how often high-probability outcomes resolve as true across many markets. Repeated misses at high confidence reveal accuracy problems.
Accuracy Tracking and FinFeedAPI
FinFeedAPI’s Prediction Markets API provides prediction markets data required for accuracy tracking. Analysts can combine historical probability streams with resolution data to evaluate performance across events and time horizons. This supports calibration studies, backtesting, and reliability analysis. The API enables systematic accuracy tracking across prediction markets.