Polymarket Probability Calculator
Convert Polymarket share prices to implied probabilities and true odds, or find the fair market price for any probability estimate
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How Polymarket Prices Represent Probabilities
On Polymarket, every event has YES and NO shares that trade between $0.01 and $0.99. The price of a YES share directly reflects the market's collective estimate of the probability that an event will occur. If YES shares for an event are trading at $0.65, the market is saying there is approximately a 65% chance that event happens. This is because each share pays out exactly $1.00 if the event resolves YES, and $0.00 if it resolves NO. So at $0.65, you are paying 65 cents for the chance to win a dollar, implying the market believes the chance of winning is around 65%.
The relationship is elegantly simple: price equals implied probability (when expressed as a decimal). A $0.80 share implies 80% probability. A $0.15 share implies 15%. This one-to-one mapping makes prediction markets remarkably intuitive once you understand the basic concept. The market price aggregates the beliefs of all participants, each putting real money behind their estimates, which tends to produce surprisingly well-calibrated probabilities over time.
The complementary NO side always exists as well. If YES is at $0.65, then NO shares represent a bet that the event will not happen. In a perfectly efficient market, YES plus NO would equal exactly $1.00. In practice, the combined cost may be slightly above $1.00 due to the spread or market-making fees, which introduces a small overround. Understanding both sides of a market is essential for finding the best entry points for your positions.
Market Efficiency and When Prices Diverge from True Probability
Prediction markets are often praised for their accuracy, but they are not infallible. Market prices can diverge from true probabilities for several reasons. Thin liquidity is one of the most common causes: when few participants are trading a market, a single large order can push the price significantly without reflecting a genuine change in the underlying probability. Low-volume markets are particularly susceptible to this kind of distortion, so it is important to check trading volume before treating a price as a reliable probability estimate.
Behavioral biases also play a role. Participants tend to overweight dramatic or emotionally charged outcomes, which can push prices on sensational events higher than the true probability warrants. Conversely, boring or slowly unfolding events may be underpriced because they attract less attention and trading activity. Recency bias is another factor: if an event recently seemed more likely due to a news cycle, the market price may overshoot and take time to correct even after the temporary catalyst fades.
Time value and opportunity cost can also cause divergence. Even if a market is correctly priced at $0.92, holding that position ties up capital for potentially months waiting for resolution. Some traders demand a discount for that illiquidity, which can keep prices slightly below their true implied probability. Recognizing these structural factors helps you identify situations where the market price may not perfectly reflect the actual probability, creating potential opportunities for informed participants.
Using Implied Probability to Find Value
The core skill in prediction market trading is comparing the market's implied probability to your own estimate of the true probability. If you believe an event has a 75% chance of occurring but the market prices it at $0.60 (implying 60%), you have identified what traders call positive expected value. Your edge is the 15 percentage point gap between your estimate and the market price. Over many such bets, consistently finding and exploiting these gaps is how skilled participants generate returns.
Converting prices to probabilities using this calculator is the first step in that analysis. Once you have the implied probability, you can compare it against base rates, polling data, historical precedent, or your own domain expertise. The key is to be honest with yourself about the precision of your own estimates. If the market says 60% and you think 62%, that is probably not a meaningful edge. But if you have strong reasons to believe the true probability is 75% or higher, that gap may represent a genuine opportunity.
It is equally important to consider the NO side. If YES shares at $0.85 imply an 85% probability, then NO shares at around $0.15 imply a 15% chance the event does not happen. If you believe the true probability of failure is closer to 25%, buying NO shares may offer better expected value than buying YES in a market where you agree the event is likely. Always evaluate both sides of a market before committing capital.
The Overround: When YES + NO Exceeds $1.00
In a theoretically perfect market, the price of YES shares plus the price of NO shares would equal exactly $1.00. In reality, the combined cost often exceeds $1.00 by a small amount. This excess is called the overround (also known as the vig or vigorish in traditional betting). If YES trades at $0.65 and NO at $0.37, the combined cost is $1.02, meaning there is a 2-cent overround. This represents the implicit cost of trading in that market.
The overround exists because of bid-ask spreads and the mechanics of how market makers profit. It means that the raw share prices slightly overstate the probabilities when added together. The true implied probabilities should be normalized by dividing each price by the total combined price. In the example above, the true implied YES probability would be $0.65 / $1.02 = 63.7%, not 65%. For most practical purposes the difference is small, but for precise analysis or when comparing across markets, normalizing for the overround gives you more accurate probability estimates.
When the overround is large, it signals either an illiquid market or one with high uncertainty where market makers are demanding wider spreads for protection. A tight overround close to $1.00 indicates an efficient, well-traded market. Monitoring the overround can itself be informative: a suddenly widening spread might indicate that new information is arriving and the market is uncertain about the correct price, while a tightening spread suggests consensus is forming.