Real vs. Implied Edge Scanner

Overview

This pillar compares your historical prediction accuracy against current market-implied probabilities. It pinpoints markets where your personal expertise gives you a quantifiable edge over the crowd.

What It Does

The scanner analyzes your entire prediction history to calculate an accuracy score, like a Brier score, for each market category. It then continuously scans live markets to find the largest discrepancies between your proven skill and the market's current odds. This process highlights opportunities where the market may be under or overvaluing an outcome relative to your personal forecasting ability.

Why It Matters

It transforms betting from a gut feeling into a data-driven strategy focused on your unique strengths. By quantifying your personal 'alpha', it helps you allocate capital more effectively to markets where you have a demonstrable advantage, improving long-term profitability.

How It Works

First, the system aggregates all your resolved predictions and groups them by market category. It then calculates your historical accuracy score for each category. Finally, it compares this personal score against the live implied probabilities of active markets, flagging any with a significant positive or negative gap for your review.

Methodology

The core calculation compares a user's historical accuracy, often measured by their Brier Score `(1/N) * Σ(p - o)^2` where p is prediction and o is outcome, against a market's implied probability. The 'edge' is calculated as `(1 - Personal Brier Score) - Market Implied Probability`. The analysis typically uses a rolling window of the last 50 to 100 resolved markets within a specific category to ensure relevancy.

Edge & Advantage

This pillar provides a systematic way to exploit your specific knowledge gaps against the general market, ensuring you position biggest where your edge is statistically proven.

Key Indicators

• Personal Category Brier Score

  high

  A measure of a user's historical prediction accuracy in a specific market category, where lower is better.

• Market Implied Probability

  high

  The current probability of an outcome as derived from real-time market prices.

• Discrepancy Magnitude

  medium

  The absolute difference between the user's implied accuracy and the market's probability, highlighting potential value.

Data Sources

• User Prediction History

  The user's own historical trades and outcomes on the platform, used to calculate personal accuracy.

• Live Market Odds

  Real-time pricing data from all active prediction markets on the platform.

Example Questions This Pillar Answers

• → In which categories do I have the biggest statistical edge over the market right now?
• → Is the current market price for the election consistent with my proven accuracy in political forecasting?
• → Does my historical data suggest I should fade the public sentiment on this crypto market?

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