A prediction market can display 52% while offering no opportunity to transact at 52 cents. That distinction matters for a podcast discussing probabilities, a researcher evaluating historical forecasts, and a developer building a market dashboard. The visible number may summarize trading interest without describing the price available for a particular quantity. Liquidity connects the headline probability to the practical conditions of exchanging a contract.
This guide uses fictional order books to explain that connection. Every price, quantity, and calculation below is hypothetical unless explicitly identified as a description of documentation. There are no live quotes or participation recommendations. If event contracts are new to you, begin with our prediction markets overview. Here the focus is how to read a quoted price without assuming more certainty or available capacity than the data supports.
Distinguish the bid, ask, and displayed probability
The best bid is the highest displayed buying price; the best ask is the lowest displayed selling price. Their difference is the quoted spread. In a fictional order book with a 49-cent bid and a 55-cent ask, the spread is 6 cents and the midpoint is 52 cents. The midpoint is an arithmetic summary. It does not, by itself, identify a willing counterparty at that price.
Polymarket's Prices & Orderbook documentation describes a central limit order book and explains that its displayed price generally uses the midpoint, with the last traded price used when the spread exceeds 10 cents. It also distinguishes an immediate transaction at available prices from a limit order's specified price constraint. These are platform-specific display and order mechanics, so another venue's interface should be checked separately.
For an analyst, the practical consequence is to label the number. “The midpoint was 52 cents at the observation time” communicates more than “the probability was 52%.” The Polymarket explainer provides broader platform context. A price can be interpreted as a market-implied probability while remaining affected by trading conditions, participation, and the exact event definition. It is not a guarantee about the outcome.
A small spread can conceal a shallow book
Suppose a fictional market shows a bid of 50 cents and an ask of 51 cents. The one-cent spread appears narrow. But imagine only 10 contracts are offered at 51 cents, followed by 40 at 54 cents and 150 at 59 cents. A displayed top quote describes the first available quantity, not every quantity someone might request. The rest of the book determines how quickly the average acquisition price changes with size.
Under a deliberately simplified static-book assumption, acquiring 100 contracts would cost 10 × $0.51, plus 40 × $0.54, plus 50 × $0.59: a total of $56.20, or 56.2 cents per contract. Fees are excluded. The average is 5.2 cents above the original best ask. In practice, available orders can change before or during execution, so this arithmetic is a snapshot calculation, not a promise of a fill.
This example separates spread from depth. Spread describes the gap at the top of the book. Depth describes the quantities available at successive prices. A useful liquidity description needs both. Two markets with identical spreads can support very different hypothetical order sizes before the average price moves materially. Calling either market “liquid” without stating quantity and observation time leaves out essential context.
Understand the cost of an immediate round trip
Return to the hypothetical 49-cent bid and 55-cent ask. Assume enough quantity exists at both prices and the book stays unchanged. Buying 100 contracts at the ask costs $55. Selling the same quantity immediately at the bid returns $49. The difference is $6 before fees. No new information, probability change, or adverse event outcome is required to produce that gap; it follows from crossing the quoted spread twice.
The wording matters. Relative to the 52-cent midpoint, the purchase occurs 3 cents above and the sale 3 cents below, totaling the 6-cent spread per contract. Describing the full round-trip cost as “two spreads” would double-count this particular example. Different paths through time and changes in quotes produce different realized costs. A static illustration explains the mechanism without predicting what any future round trip will cost.
Separate a forecasting advantage from execution assumptions
Imagine an analyst assigns a 58% probability to a hypothetical contract that pays $1 if the event occurs and $0 otherwise. Under that model, the expected payout is 58 cents. The depth example's 50-cent bid and 51-cent ask give a midpoint of 50.5 cents, suggesting a 7.5-cent difference. Comparing the expected payout with its 56.2-cent average purchase price leaves only 1.8 cents before fees and other assumptions. Changing the execution model changes the calculation.
Neither calculation establishes that the analyst's 58% estimate is correct. A two-percentage-point forecasting error would already be larger than the second difference. Contract interpretation, settlement conditions, and the timing of information also matter. Expected value is a calculation conditional on a probability model, not a guaranteed gain on one event. These examples illustrate why forecast evaluation and trading simulation should be reported separately.
Do not use past volume as a substitute for current depth
Historical volume records completed activity over a period. An order-book snapshot describes displayed interest at an observation time. The two answer different questions. A fictional market could record substantial activity during yesterday's announcement and have little quantity available today. Another could show modest historical activity while currently displaying several deep price levels. Neither scenario is contradictory once the time dimension is made explicit.
For a comparison table, show the observation timestamp, best bid, best ask, and quantities near those prices. If historical volume is included, label its period. Avoid turning these fields into a single universal quality score without explaining the weighting. A researcher studying collective beliefs may care about participation over weeks, while an execution simulation needs assumptions about a particular moment and size. Those are different analytical tasks.
Limit prices control one variable, not the entire outcome
A hypothetical buyer might specify a maximum price of 54 cents. Using the earlier book, the displayed quantities at 51 and 54 cents total 50 contracts. A 100-contract request constrained to 54 cents cannot be assumed to acquire the remaining quantity at 59 cents while respecting that limit. Depending on the chosen order instructions and venue behavior, the remainder may wait or be canceled. The simulation must state its rule.
A pending order also does not guarantee future execution. If the available market changes, the requested price may never attract a counterparty. If only a portion fills, the resulting position differs from the intended quantity. Researchers should preserve unfilled and partially filled observations rather than discarding them. Otherwise a historical simulation can quietly keep favorable fills and erase decisions that failed to obtain the assumed exposure.
Record enough data to make a chart honest
When building a dashboard, distinguish last trade, midpoint, and side-specific quotes in both field names and visible labels. Preserve missing observations as gaps rather than drawing a continuous line that implies uninterrupted data. A large change after a long gap does not reveal exactly when the move occurred. The prediction market API guide explains why timestamps and identifiers belong alongside the numeric values.
For an educational execution calculator, let readers choose a hypothetical quantity and show the price levels consumed by the calculation. State that orders are assumed unchanged and list excluded costs. That makes the output inspectable: a reader can recompute the average and see which assumptions drive it. A precise-looking number without its inputs can create more confidence than the underlying snapshot deserves.
Read liquidity as part of the forecast's context
A meaningful market update can be brief: the observed midpoint, the spread, the nearby depth, the timestamp, and the event being priced. These details help a listener understand whether a dramatic probability move reflects substantial displayed interest or a sparse set of quotes. They also make comparisons across venues more careful, especially when supposedly similar contracts have different wording or deadlines.
Liquidity does not tell you whether a forecast is correct. It tells you something about the conditions under which prices are available and how much a transaction assumption may matter. For the separate question of whether probabilities are reliable, see our guide to forecasting calibration. A strong analysis keeps both questions visible: what the estimate means, and what the market data actually supports.
