Beginner Guide

Compare Prediction Market Prices

How to read and compare quoted prices across different prediction market apps

By Top Prediction Markets EditorialReviewed September 7, 20265 min read

Answer first

Compare prediction market prices by converting quoted prices into implied probabilities and adjusting for fees, spreads, and liquidity. Look at whether a platform shows mid-market quotes, posted orders, or uses an automated market maker, and use a simple numeric example to compare effective cost and potential payout.

How quoted prices translate to implied probability and real cost

A quoted price on a prediction market is the amount you would pay to buy a contract that pays $1 if a specific event happens. A Yes contract — an event contract that pays $1 if the event happens — priced at $0.62 implies a 62% probability according to that market.

That raw quote is only the starting point. For any trade you need to convert the quoted number into the implied probability and then adjust for the costs you will actually face: the executable price (not just a midpoint), fees (on trade value or on realized profit), and the available quantity at that price (liquidity). For example:

If a Yes contract costs 62¢ and pays $1 if the event happens, buying one contract costs $0.62. If the event happens, the contract pays $1, so the gain before fees is $0.38. If the event does not happen, the contract expires at $0, so the loss is $0.62.

Use implied-probability conversion and then apply expected fees and slippage to compare effective costs across platforms.

Why identical events show different prices on different platforms

Several concrete mechanics cause two platforms to display different numbers for the same underlying event.

Quote type. Some apps show the mid-price (midpoint between best buy and sell). Others show the best available order (the price at which someone will sell or buy now). The mid-price is a convenience; the executable price may be the ask (more expensive) or the bid (cheaper).
Fees and rebates. Platforms charge fees in different ways: a fee on realized profits (a percentage of gains) or a taker fee added to the trade price. A quoted price typically doesn’t incorporate a profit fee: you must apply that afterwards.
Liquidity and market structure. Some apps use an order book with discrete buy and sell orders; others use an automated market maker (AMM) that quotes prices from a bonding curve and widens quotes as one side is bought. Low liquidity on either structure means a small trade can move the price.
Participant pool and information. Different user bases have different knowledge, incentives, and risk tolerances. That means prices reflect different information.
Settlement and resolution rules. Platforms may resolve questions differently or have different resolution criteria; check settlement rules so you are truly comparing the same event outcome.

When you compare prices across apps, verify the quoted type (mid vs executable), convert prices to implied probabilities, estimate fees you will pay, and check the available quantity at the quoted price. Use those adjusted numbers, not raw quotes, to decide which platform is cheaper for your intended trade size.

Side-by-side comparison of three example platforms

The worked example below keeps the original numbers and shows the same one-contract comparison in tabular form so you can compare fields at a glance.

Platform	Displayed quote	Executable price	Fee type & rate	Visible liquidity	Total cost for 1 contract	Net gain if event happens
Platform A	shows executable ask $0.62	$0.62	1% taker fee on trade value	visible ask size 100 contracts	$0.62 + 1%×$0.62 = $0.6262 ≈ $0.6262	$1 − $0.6262 = $0.3738
Platform B	displays mid-price $0.61 (best ask $0.64)	$0.64	0% taker fee; 5% fee on realized profits	best ask size 10 contracts	buy at $0.64; fee on profit if it resolves true = 5%×($1 − $0.64) = $0.018 → effective cost ≈ $0.64 (profit reduced instead)	gross gain $0.36 − $0.018 ≈ $0.342
Platform C	AMM price $0.63 (would move to $0.67 buying 200)	$0.63	2% taker fee	liquidity such that buying 200 moves price to $0.67	$0.63 + 2%×$0.63 = $0.6426 ≈ $0.6426	$1 − $0.6426 = $0.3574

From the table for buying one contract: Platform A effective cost ≈ $0.6262, Platform B effective cost ≈ $0.64 (after accounting for profit fee), Platform C effective cost ≈ $0.6426. Platform A is cheapest for this single-contract example. If you wanted 100 contracts, Platform A and Platform C’s visible liquidity and AMM slippage would change the comparison.

The central point: raw quoted numbers (0.61 vs 0.62 vs 0.63) are only the start. Convert to full effective cost after fees and slippage before deciding which is truly cheaper.

Common comparison mistakes to avoid

Comparing prices across platforms is useful, but avoid these frequent errors.

Comparing mid-prices as if they are executable. Mid-prices don’t tell you the price you will actually pay; the executable ask or bid matters for cost.
Ignoring fees or applying them incorrectly. Fees can be on trade value or on realized profit. Applying the wrong formula understates your true cost.
Overlooking liquidity and trade size. A price that looks attractive for a tiny quantity can change radically for larger orders because of visible order sizes or AMM curvature.
Treating all platforms as identical markets. Different resolution rules, question wording, and participant pools mean prices reflect different information. Confirm the event definition matches across platforms.

Follow the checklist: identify whether the displayed number is mid or executable, translate to implied probability, apply the specific fee model, and check how much is available at that price.

Which platform fits which reader

If you mostly place small trades and prefer predictable executable prices, platforms that display executable asks with reasonable visible sizes (like Platform A in the example) usually fit better.

If you prefer lower up-front cost and are comfortable with profit-based fees and small available sizes, platforms with low taker fees but profit fees (like Platform B) can be attractive for tiny bets, but be careful: the mid-price can be misleading.

If you plan to place larger trades or want continuous pricing that scales with quantity, AMMs (like Platform C) are useful — but you must model how much the price moves as you buy and include taker fees.

Use this short rubric:

You want predictable small trades → favor executable-quote platforms with visible size.
You want to minimize up-front trade fees for tiny bets → consider profit-fee platforms, but apply the fee to expected profit.
You plan larger orders and need continuous liquidity → consider AMMs but model slippage.

Further reading on prediction market pricing

Frequently asked questions

How do I convert a quoted price into probability?

A contract priced at $0.62 implies a 62% probability because the contract pays $1 if the event happens. Price expressed as a decimal or percentage maps directly to implied probability.

Should I compare mid-price or best ask when shopping for a contract?

Compare the executable price you'll face. Mid-price is a reference; the best ask is what you would pay to buy immediately. Check both and note fees and available size.

Do fees always make a platform effectively more expensive?

Not always. Some platforms charge fees on profits rather than trade value, which can be cheaper for small or losing trades. Adjust each platform's fees into the effective cost before comparing.

Are price differences evidence of a mistake on one platform?

Not necessarily. Price differences can reflect different liquidity, participant information, or resolution definitions. Investigate quote type, fees, and event wording before concluding an error.

Are prediction markets legal?

Rules vary by location and platform. See our dedicated guide on whether prediction markets are legal in the US.