Liquidity, Spreads and Slippage in Prediction Markets: What Traders Actually Pay

While the concept of prediction markets is anything but new, rapidly growing digital platforms like Polymarket or Kalshi have completely transformed it over the past few years, introducing the next generation of highly accessible, compliant, or decentralized trading platforms. One of the most transformative features they are popularizing is an alternative way to discover odds and probabilities — purely through transparent and democratic market forces rather than traditional bookmakers’ unilateral decisions.

As with most innovations, however, there are slight frustrations that might come with the territory. On the surface, the relative price of each “Yes” and “No” contract could be indicative of the general market sentiment toward the probability of their respective outcomes. For instance, if “Yes” is currently priced at $0.65, this could be viewed as a 65% chance of that outcome actually occurring since each “Yes/No” pair technically amounts to $1 in total. Meanwhile, actual order prices deviate from such quoted figures most of the time.

For instance, a prediction market may show “Yes” at $0.62, but when the trade fills, the average price will add up to $0.67, incurring a hidden 5-cent cost increase for a trader. As a result, the number people see quoted as the “price” or “probability” is almost never the price they actually pay or receive. 

While the current mid-price — the calculated average of the best ask and the best bid — can act as a weighted probability forecast, there is often a gap between it and the real, actual execution price when factors like slippage, spreads, and liquidity depth come into play.

In this article, we will examine how the order book structure, the bid-ask spread, market depth, slippage, and fees affect the actual price traders pay when their orders are executed — and why it’s almost always worse than the mid-price everyone sees.

“Yes/No” Contracts and Order Books

While platforms like Polymarket and Kalshi are not limited to them, binary contracts amount to the lion’s share of their offerings. The total price of one such contract usually amounts to $1 (or very close to it), split into two counterparts — “Yes” and “No.” When an event occurs, traders holding the “correct” shares will receive $1 per each, while people who bet on the opposite outcome will receive nothing. The market price of “Yes” and “No” shares is commonly interpreted as the probability of the respective outcome.

When a trader wants to buy a “Yes” or “No” share, they are buying a claim from someone else (or from the order book). Notably, they don’t get to buy at the last traded price or at some ideal “fair” price — only at whatever price is currently offered.

Also similar to traditional exchanges, prediction markets employ order books — live lists of all the outstanding buy and sell orders for “Yes” and “No” shares. People who want to buy a share post the highest price they are willing to pay (bids) while those who want to sell post the lowest price they are willing to accept (asks). 

From a trader’s point of view, bids are stacked from the highest price to the lowest. In reverse, asks are stacked from the lowest price to the highest. In this example, the key visible numbers are as follows:

• Best bid = the highest price anyone is currently willing to pay for “Yes”.
• Best ask = the lowest price anyone is currently willing to sell “Yes” for.
• Mid-price = the simple average of best bids and best asks, and this is usually the number people treat as “the probability”.

Here is a simple example of a “Yes” order book:

In this example, if someone wants to buy right now, the cheapest “Yes” shares available will cost $0.64, and there are only 150 of them at that price. To buy more, a trader will have to pay $0.65 for the next 200, then $0.67, and so on. This is called “walking the book” — a process where traders move through multiple levels of an order book, filling orders across progressively worse price tiers to accumulate or liquidate a position. There is always a corresponding order book for “No” shares, and on well-functioning platforms the prices are kept consistent, i.e. buying “Yes” is economically similar to selling “No” shares.

Bid/Ask Spread: The Immediate Cost of Trading

This difference between the best buy/sell prices is called the spread, and in the table above it amounts to $0.02 — $0.64 vs. $0.62. Partially, this spread also exists because people posting their orders need compensation for the risk they take and for tying up their money.

This is essentially the first “tax” a buyer pays on a prediction market. With the mid-price of $0.63 — (0.64 + 0.62) / 2 — buying 100 shares at the best ask of $0.64 already resulted in paying one more cent above it, even on a tiny trade.

On very active markets the spread might add up to 1–3 cents while on quieter platforms it can easily reach 5–15 cents or more. In practice, this means that the moment a trade takes place, traders are already “down” relative to the mid-price by roughly half the spread.

Depth, Liquidity and Slippage

An order book’s depth is another major factor contributing to price differences, representing the total amount of shares available to buy and sell at each price level at any given moment. Thus, a book with only 50 shares at the best ask can be considered shallow while a book with 2,000 shares is much deeper in comparison.

Similarly, liquidity affects the overall ease of buying or selling shares in meaningful quantities without forcing traders to push the price against themselves. Finally, slippage is the difference between the price traders expected (usually the best ask or the mid) and the average price they actually receive when their order is filled.

For instance, buying 500 “Yes”  shares at once (based on the book example above) will look like this: ($0.64 x 150) + ($0.65 x 200) + ($0.67 x 150) = $326.5, with the trade order constantly moving to higher price tiers as previous ones are exhausted. 

In this example, the average execution price will amount to $0.653 (326.5 / 500) — compared to the mid-price of $0.63, this results in $0.023 (or $0.013 vs the best ask at $0.64) slippage. Notably, the larger an order relative to the available depth is, the more slippage a trader will pay.

Fees: The Final Layer of Cost

Even after accounting for the bid/ask spread and slippage, most prediction market platforms will also charge additional fees — the last factor that separates the quoted mid-price from the real money that leaves a trader’s account.

The main categories of fees traders encounter are:

• Trading fees: Charged when an order is filled. Many platforms distinguish between makers (orders that rest on the book and add liquidity) and takers (orders that cross the spread and take liquidity immediately). Takers usually pay higher rates while makers often pay little or nothing, and on some platforms they even receive small rebates.
• Settlement or resolution fees: Rare on major platforms today, but still present on a few older or specialized venues.
• Deposit and withdrawal fees: The platform itself may charge nothing, yet payment processors, banks, or blockchain networks can add costs when moving money in or out.

Fee formulas differ by platform and sometimes by market category. A common structure is a fee that peaks when the contract price is near $0.5 and shrinks toward the extremes — near $0 or $1. In practice this means the dollar cost of trading a coin-flip market is higher than the cost of trading a market that is already 90% decided.

Returning to the earlier 500-share example where a trade order produced $0.023 of slippage versus the mid-price, it will also include a trading fee on top of it. Suppose the platform charges a taker fee that, at this price level, equals roughly $0.008–0.012 per share (a range consistent with current schedules on major venues). For simplicity, let’s use $0.01 per share:

• Slippage versus the mid-price: $0.023
• Trading fee: $0.01
• Total extra cost on the buy side: $0.033 per share

If the trader later sells the position (a round-trip), a similar cost can appear on the exit. Even if the exit is cleaner, a conservative round-trip friction of 4–6 cents per share is common once spread, slippage, and fees are combined.

The useful way to think about these costs is to translate them back into probability points. In the example, the mid-price suggested a 63% probability. After paying the average execution price plus fees, the trader’s true break-even probability is higher: 

• Effective purchase price including fees: $0.653 + $0.01 = $0.663 
• The forecast must therefore clear roughly 66.3% (instead of the quoted 63%) just to break even on the capital committed, before any profit.

In other words, a trader needs several extra percentage points of edge simply to cover the market’s microstructure costs. If their true edge over the mid-price is smaller than this hurdle, the trade has a negative expected value even if the directional view is correct. 

This is why experienced participants always calculate the full round-trip cost — spread + expected slippage + fees — before sizing a position. The headline probability is only the starting point, and the effective probability after costs is what actually determines whether the trade is worth taking.

Here is a short, actionable checklist to follow when deciding on a trade:

• Always examine the full order book, not just the displayed mid-price or last trade.
• Check how many shares are available near the best prices before deciding size.
• Calculate rough round-trip cost in advance.
• Prefer markets where the spread and depth make the friction small relative to your edge.
• Remember that liquidity often worsens as the event gets closer to resolution.
• Most importantly, avoid treating the quoted probability as the price you can trade at — this is the most common and expensive mistake.

What to Check Before Buying on Dexsport

In general, the above examples of order books, bid/ask spreads, “walking the book,” and maker/taker fees illustrate how many exchange-style prediction markets work, including Polymarket and Kalshi. Meanwhile, Dexsport’s prediction markets operate a bit differently when it comes to a few key points.

Dexsport’s particular traits:

• Early (secondary-market) sales of positions are not available yet. Once you buy, the position is held until the market resolves.
• Ahead of the final confirmation, Dexsport’s interface will show the exact amount you will pay and the potential payout if the outcome is correct.
• Settlement is facilitated in stablecoins and follows the resolution rules published on each market’s page.

Because there are no intermediate exits, the main costs you face are the purchase price itself plus any platform fees that apply at the time of the trade. Slippage from “walking the book” and round-trip spread costs do not apply in the same way. 

When you click any open market on Dexsport — for instance, a Yes/No market on a sports outcome, crypto price target, or election — focus on these elements:

• Purchase price/implied probability: The live “Yes” or “No” price shown for the side you want. This is the price you will actually pay per share/unit once you press “Confirm.”
• Amounts to pay and potential payouts: Enter the amount of shares you intend to buy. The confirmation screen/order panel displays the total cost in stablecoins and the payout you will receive if that side wins. Compare these two numbers to see your break-even probability and potential return.
• Settlement/resolution rules: The market page lists its period, closing date, resolution deadline, and how the outcome is determined. Read this before buying so you know exactly when and how the position will be settled.
• Fees: Note whether a trading fee is deducted from the stake or the payout, this is usually visible before confirmation.

A quick pre-buy checklist for Dexsport:

• Confirm the displayed purchase price (not just a mid-price or last trade).
• Verify the total cost and the potential payout shown before you sign the transaction.
• Read the resolution rules on that specific market.
• Remember that positions stay open until settlement — size the trade accordingly.
• Treat the headline probability as the starting point and calculate your true break-even after the actual purchase price and any fees.

Conclusion

Overall, while a prediction market can be highly accurate in its mid-prices, it can still remain a costly place to trade. In practice, what traders actually pay is heavily influenced by the order book, the spread, the available depth, slippage, and fees — not by the headline probability.