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Edge

Edge is the measurable advantage a trader holds over the market price of a contract, arising when an independent probability estimate differs favorably from the [[implied-probability]] reflected in the current price.

Updated June 24, 2026Strategy & Analysis
TL;DR
Edge is the gap between what you think the true probability is and what the market is pricing. Positive edge means the market is wrong in your favor.

Key Points

Edge is expressed as the difference between your estimated true probability and market implied probability: edge = p_true minus p_market.
Positive edge exists when you believe an event is more likely than the market price implies, making the contract underpriced relative to your estimate.
Edge does not guarantee profit on any single trade; it is a statistical expectation that plays out over many trades.
Edge can be informational (you know something the market does not), analytical (you model outcomes more accurately), or structural (you exploit systematic biases like [[longshot-bias]]).
Without positive edge, trading against the [[vig]] is a losing proposition in the long run.

What Creates Edge in Prediction Markets

Edge originates from an information or analytical advantage over the aggregate market. Informational edge comes from accessing data or expertise that is not yet reflected in prices: a domain expert in electoral politics may model precinct-level voting patterns with more precision than the typical participant. Analytical edge arises from superior probability estimation methods, such as applying rigorous Base Rate analysis or Calibration techniques that most traders ignore. Structural edge exploits known market biases: Longshot Bias creates systematic overpricing of unlikely events, so fading those contracts carries positive Expected Value on average. Market Efficiency theory suggests edge erodes as more informed traders enter a market, which is why identifying underexplored markets and niche events is often the most durable source of advantage.

Measuring and Preserving Edge

Quantifying edge requires honest probability estimation independent of the market price. Traders often track results using Brier Score or Log Score to assess whether their forecasts are genuinely better than the market over time. Edge is also dynamic: prices adjust as new information arrives, so a trade that carried positive edge at entry may become neutral or negative before resolution. Position sizing via the Kelly Criterion scales stakes in proportion to estimated edge, preventing large bets on small advantages. Trading Fees and Bid-Ask Spread both consume a portion of edge on each trade, so the minimum detectable edge threshold must exceed combined transaction costs for a trade to be worth taking.

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