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A Polymarket bot should compare its own probability estimate with the price it can actually trade at—not simply with the probability displayed on a market page. For a binary YES share bought at price p, the basic gross expected profit per share is q − p, where q is the bot’s estimated chance that YES resolves true. Fees, spread, available depth, partial fills, and settlement all affect whether that apparent edge survives. A positive estimate is not proof of arbitrage or profitability.
What a Polymarket price tells your bot
Polymarket’s FAQ describes outcome prices from $0.00 to $1.00 USDC as market-derived probabilities, with winning shares paying $1 USDC at resolution. That makes a share price a useful probability-like signal, but it is not the same thing as your model’s fair value or a guaranteed execution price.
Polymarket Help Center’s “How Are Prices Calculated?” article, dated March 13, 2026, says the displayed probability is ordinarily the midpoint of the bid-ask spread. If the spread is wider than $0.10, the last traded price is displayed instead. Neither a midpoint nor a last trade guarantees that the bot can buy or sell its intended quantity at that price.
How to calculate fair value and expected value
Start with the payoff identity
Let q be the bot’s estimated probability that YES resolves true, and p the price per YES share it can obtain. Under the binary payout described above, a YES share bought at p pays $1 if YES resolves true and $0 otherwise. Its simple gross expected profit per share is:
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Gross expected profit per share = q − p
For example, if the bot estimates q at 0.60 and can buy at an executable price of 0.54, the gross estimate is $0.06 per share before fees and other trading costs. This arithmetic is a payoff identity, not evidence that the probability estimate is accurate.
Use a tradeable quote, not a page display
For a buy decision, inspect the ask-side prices and quantities available for the intended size; for a sell decision, inspect the bid side. A best quote may cover only part of the order. If the remainder would have to execute at worse prices, calculate the effective average price across the intended quantity rather than using the top-of-book quote alone.
A practical expected-value calculation should use the expected fill price and subtract applicable fees and other costs:
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Estimated net EV per share = q − expected fill price − fee per share − other per-share costs
“Other costs” can include the effect of crossing the spread, market impact, and losses from partial or delayed execution where relevant. Keep the components separate in the bot’s calculations so that a displayed edge cannot conceal its actual cost assumptions.
Treat uncertainty in q as a separate risk
The equation takes q as an input; it does not validate the model that produced it. A model can be miscalibrated, use stale information, or be wrong about how a market’s resolution criteria apply. Record the probability estimate and timestamp, and evaluate the model against outcomes using a reproducible backtest or live record before treating an apparent edge as evidence of performance. No validated calibration result or profitability statistic for a particular Polymarket bot is established here.
How fees change the trade threshold
Polymarket Help Center’s “Trading Fees” article, dated July 10, 2026, says taker fees apply to certain markets, rates vary by category, and makers are not charged fees. The article gives this fee formula:
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Fee = C × feeRate × p × (1 − p)
Here, C is the number of shares traded, feeRate is the applicable market rate, and p is the share price. For a per-share EV calculation, divide the resulting fee by C. The article says fees are collected at match time and identifies geopolitical and world-events markets as fee-free. Because eligibility and rates can vary by market and may change, retrieve the current fee data for the specific market when making a decision instead of hard-coding a category rate into a general strategy.
A useful buy threshold is therefore not simply “buy when q exceeds the displayed probability.” It is “consider a buy only when the model’s expected value exceeds the expected fill price plus the applicable fee and other estimated costs,” with an additional margin if the model’s uncertainty warrants one. This is a decision rule, not a guarantee of a positive realized return.
Choose an order based on price, urgency, and depth
Polymarket’s order documentation distinguishes market orders, which take available liquidity, from limit orders, which specify a price and can wait on the book for a match. A limit order gives price control but may not fill; a market order interacts with available liquidity but does not ensure the displayed midpoint or a particular average price.
| Decision factor | Market order | Limit order |
|---|---|---|
| Price control | Takes available liquidity; the effective price depends on the book and order size. | Sets a price constraint; execution occurs only if matched at an acceptable price. |
| Urgency and fill | Designed to interact with available liquidity immediately, subject to what is available. | May rest until filled, expired, or canceled; there is no guarantee of a fill. |
| Depth and size | Check multiple book levels to estimate the average execution price for the full size. | Check whether enough counterparties may trade at the limit; a partial fill can leave the rest open. |
| Constraints | Account for available book liquidity and market-specific order constraints. | Follow the market’s minimum price increment and minimum order size. |
Polymarket’s documentation also describes GTC and GTD order lifetimes and order responses such as live, matched, and delayed. Market metadata can include tick size, minimum order size, and bid/ask levels; its market stream includes a tick-size-change event. A bot should use current market metadata rather than assume that constraints remain fixed.
Build the bot around the full order lifecycle
- Estimate: produce the model probability for the exact event and outcome, and store the estimate with its timestamp and model version.
- Read the market: retrieve the current order book, market-specific tick size and minimum order size, and applicable fee information. Use book levels to estimate the fill price for the intended quantity.
- Decide: calculate expected value using the executable price, expected fees, and other relevant costs. Apply the model’s own uncertainty controls before submitting an order.
- Submit: choose a market or limit order and its supported lifetime based on the desired price control and urgency. Validate the price increment and minimum quantity first.
- Track the response: distinguish an accepted or live order from a matched one; handle delayed, partial, and canceled states rather than recording every submission as a completed trade.
- Reconcile settlement: track matched trades separately from on-chain settled positions. The official quickstart demonstrates placing an order and waiting for settlement before checking positions, so bot accounting should handle the interval between matching and settlement.
For each decision, preserve the model probability, quote and depth snapshot, fee inputs, order type and limit, fill quantities and prices, and eventual settlement status. This audit trail lets you distinguish a forecasting error from a stale quote, an execution shortfall, a fee assumption, or a settlement delay.
Best Value
What “arbitrage” can—and cannot—mean here
A strategy that buys YES when its model estimate is above the market price is usually making a probabilistic value judgment, not locking in a risk-free arbitrage. The position still depends on the event outcome, the accuracy of q, the actual fill, and the market’s resolution. Even a positive estimated net EV can produce a loss on an individual trade or across a strategy if the model is biased or execution costs are understated.
Claims that a named bot reliably earns money require evidence such as reproducible evaluation with realistic execution assumptions or a verifiable live record. Polymarket’s venue documentation explains pricing, fees, and order mechanics; it does not establish the reliability or profitability of a forecasting model.
Check whether you are allowed to use the platform
Polymarket’s transparency information says users in restricted jurisdictions, including the United States, may not trade on Polymarket International or use tools intended to circumvent geographic restrictions. Availability and eligibility can vary and change; consult Polymarket’s current official access information for your location. This article does not determine an individual user’s eligibility.
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