Why Consensus Beats
Any Single Market

Checking one prediction market gives you one data point. Aggregating across all of them gives you the signal.

⚠️ Single Prediction Market

  • ✗ One pool of participants with shared biases
  • ✗ Liquidity varies — thin markets are easily moved
  • ✗ Platform-specific regulatory constraints distort prices
  • ✗ Must check multiple sites manually to get full picture
  • ✗ No divergence signal — no way to know if this market is an outlier

✅ Meridian Edge Consensus

  • ✓ Aggregated across multiple independent participant pools
  • ✓ Volume-weighted — deeper markets have more influence
  • ✓ Aggregated view reduces structural biases
  • ✓ One dashboard covers everything
  • ✓ Divergence signal shows when markets disagree

Feature Comparison

Feature Single Market Meridian Edge
Live probability data ✓ ✓
Cross-market consensus ✗ ✓
Divergence signal ✗ ✓
Multi-sport coverage Varies ✓ NBA/NFL/MLB/NHL/boxing/politics
Historical data Varies ✓ (Starter+)
API access Varies ✓ (Pro+)
Starter tier Some ✓ Live dashboard
Volume-weighted aggregation ✗ ✓
Single unified view ✗ (one platform only) ✓

The Problem with Checking One Market

Suppose you want to know the market probability for a major NBA game. You check one platform and see 61%. That's a useful data point — but how do you know if 61% is representative?

Maybe that platform's user base is particularly bullish on the home team. Maybe a large position was placed an hour ago that hasn't been corrected yet. Maybe another platform shows 54% because they have different liquidity dynamics.

A single market's price is a signal with noise. Consensus across multiple markets reduces that noise — the same way averaging multiple sensor readings gives a more accurate measurement than relying on one sensor.

This isn't just intuition. Research on prediction market accuracy consistently shows that aggregation improves calibration. The wisdom of crowds effect is well-documented — and aggregating across crowds tends to work even better than aggregating within one crowd.

Who Uses Consensus Data

Prediction Market Analysts

Quick consensus view before entering a position. Spot potential mispricings when markets diverge.

Sports Analysts

Data-driven probability estimates for game outcomes, without relying on a single platform's biases.

Political Researchers

Aggregated election and political event probabilities. More stable than any single market.

Fantasy Sports Players

Consensus probabilities for game outcomes that inform lineup decisions with multiple data points.

Data Journalists

Authoritative consensus figure to cite, rather than a single platform that may have thin liquidity.

Developers & Data Teams

REST API for integrating consensus probabilities into applications, models, or dashboards.

See the Consensus in Action

Free live dashboard required. Starter plan provides access to the full opportunity feed.

Open Dashboard → How It Works