How to Read Prediction Market Odds

Learn to interpret prediction market odds and convert them to probabilities. Understand implied probability, edge calculation, and value betting.

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Understanding Prediction Market Prices

Prediction market prices directly represent the market's estimated probability of an outcome. Unlike traditional betting odds, these prices are intuitive: a price of $0.65 means the market thinks there's a 65% chance of that outcome occurring.

Price = Probability

The key insight: A share trading at $0.70 pays out $1.00 if correct, nothing if wrong. The market price of $0.70 implies a 70% probability.

Price	Implied Probability	Potential Return
$0.10	10%	+900% if correct
$0.25	25%	+300% if correct
$0.50	50%	+100% if correct
$0.75	75%	+33% if correct
$0.90	90%	+11% if correct

Yes/No Share Relationship

In a binary market, Yes and No shares always sum to $1.00 (before fees).

Example: If Yes is trading at $0.65, No is trading at $0.35. Buying No at $0.35 means you get $1.00 if the event doesn't happen (65% implied probability against).

Converting from Traditional Odds

American Odds → Probability

Positive odds (+200): Probability = 100 / (odds + 100) = 33%
Negative odds (-200): Probability = |odds| / (|odds| + 100) = 67%

Decimal Odds → Probability

Probability = 1 / decimal odds

Example: 2.50 decimal = 1/2.50 = 40%

Fractional Odds → Probability

Probability = denominator / (numerator + denominator)

Example: 3/1 = 1/(3+1) = 25%

Finding Value Bets

A value bet exists when you believe the true probability differs from the market price.

Example: The market prices an event at $0.40 (40% probability). You believe the true probability is 55%. This is a value bet because you're buying something underpriced relative to your assessment.

Learn more about finding mispriced markets in our mispriced markets guide.

Multi-Outcome Markets

In markets with multiple outcomes (like "Who will win the election?"), prices should sum to approximately $1.00 across all options. Small deviations occur due to fees and market inefficiencies.

Example: Candidate A: $0.45, Candidate B: $0.40, Candidate C: $0.10, Other: $0.05. Total = $1.00. Each price represents that candidate's probability.