How aggregated probabilities from multiple regulated prediction markets produce a single, more accurate number.
See Plans →Summary: How aggregated prediction market probabilities work. Consensus combines prices from multiple regulated markets into one probability per event.
Every prediction market platform has its own participant pool, its own liquidity profile, and its own biases. A probability on one platform might differ by several percentage points from the same event on another. Which one do you trust?
The answer is: none of them individually. You trust the consensus — the volume-weighted average across all available sources.
Meridian Edge computes consensus probabilities through a three-step process:
The result is a single probability that reflects the collective intelligence of all market participants across all venues.
Academic research on prediction markets consistently shows that aggregated forecasts outperform individual sources. This is the same principle behind ensemble methods in machine learning — combining multiple imperfect estimators produces a better estimator than any one alone.
Consensus data also reveals divergence: when platforms disagree significantly, it often indicates new information entering the market or a structural inefficiency. Meridian Edge flags these divergences automatically through the opportunities endpoint.
Meridian Edge currently tracks 27,000+ active markets across NBA, NHL, NFL, MLB, politics, economics, and more. Data updates every 10 minutes during active market hours, with a 14-second pipeline refresh cycle.
Access consensus data through the REST API, Python SDK, Node.js SDK, or MCP server for AI assistants.
Consensus is the volume-weighted average probability of an event, calculated by aggregating prices from multiple regulated prediction markets and removing platform spreads. It reflects the collective view of all participants across all venues.
No single platform captures all available information. Consensus combines data from multiple independent sources, reducing noise and platform-specific biases — the same principle behind ensemble methods in machine learning.
No. Consensus data is for informational purposes only. It reflects aggregated market participant views and does not constitute financial, trading, or investment advice. Participation in prediction markets involves risk of loss.
Starter plan includes API access, the live dashboard, divergence alerts, and email digests.
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