CS2 Trade-Up Profit Check: Expected Value After Fees

Price every result, take the selling fee off and know your worst case before you buy the inputs.

A CS2 trade-up pays off only when the expected value of all its results, after selling fees, is higher than what the inputs cost. Price every possible result, not just the one you want, and know how much the worst one loses. The contract rules are in the trade-up guide; this page is the check to run before you buy inputs.

Which recipe you are using

CS2 trade-up recipes
RecipeInputsResult
Ten-skin contract10 weapon skins of the same rarity, all normal or all StatTrak™One skin of the next rarity from a collection among the inputs
Covert contract5 Covert skinsA knife or gloves from the inputs’ collections
StatTrak™ Covert contract5 StatTrak™ Covert skinsA StatTrak™ knife from the inputs’ collections

Valve’s Trade Up Contract article covers the ten-skin recipe: Souvenir weapons can go in, the result is not Souvenir, and a skin that is already the rarest in its collection can’t be used. Valve’s 22 October 2025 update added the five-Covert recipes, which the support article does not list yet. Souvenir inputs came with the 21 May 2026 update.

FIG. 1
Ten cosmetic weapon cards combine into one higher-tier output with uncertain outcome.
A trade-up exchanges inputs for one output; check eligibility, float and outcome probabilities first.

Step 1: list every result and its chance

Our calculator gives each collection a share equal to its number of inputs divided by the contract size, then splits that share evenly among the collection’s possible results. Example: seven inputs from collection A, which has two possible results, and three from collection B, which has three.

Odds in the example contract
ResultCalculationChance
A1(7 ÷ 10) ÷ 235%
A2(7 ÷ 10) ÷ 235%
B1(3 ÷ 10) ÷ 310%
B2(3 ÷ 10) ÷ 310%
B3(3 ÷ 10) ÷ 310%

A cheap filler from a third collection adds that collection’s results to the pool, so price them too. Five-Covert contracts use a different weighting for knife and glove finishes; the methodology explains both models.

FIG. 2
Collection weighting in a ten-item contract
Ten-input contract: our calculator gives eight inputs from collection A and two from B weights of 80% and 20%, then splits each weight between that collection’s possible results.
FIG. 3
A worked output-float example
Our calculator’s float model: an input at 0.12 in a 0.10–0.20 range sits at position 0.20. If all inputs share that position and the result’s range is 0–0.80, the result’s float is 0.16.

Step 2: put a sale price on every result

Use what each result sells for at its predicted wear, not the cheapest listing. The predicted wear comes from the input floats; the float guide shows how. If the calculator shows $0.00 for a result, its price is missing, not zero: look the skin up in the price table before you trust the expected value.

Step 3: take the fee off and compare with the input cost

Example: the ten inputs cost $100. There is a 25% chance of a result that sells for $200 and a 75% chance of one that sells for $80. The marketplace takes 10% of each sale.

Expected value of the example contract after a 10% fee
ResultChanceSale priceAfter feeWeighted
High25%$200$180$45
Low75%$80$72$54

Before fees the expected value is 0.25 × $200 + 0.75 × $80 = $110, which looks like a $10 profit. After the fee it is $45 + $54 = $99: an expected loss of $1 on every $100 contract. The inputs would have to cost less than $99 to break even, and every dollar of checkout or withdrawal cost moves that line down.

Our calculator’s expected value uses its price estimates before selling fees, so take your marketplace’s fee off yourself. The fee comparison calculator shows the fee for each marketplace, and the marketplace fee guide lists them side by side.

Step 4: decide what you can afford to lose

  • Worst result. In the example the low result returns $72 on $100: a $28 loss on that contract.
  • One contract, one result. Expected value is the average over many contracts. A single contract pays one result.
  • Time to sell. Check how many copies of each result sell on Steam per month on its skin page before you count on a quick sale.

Checklist before you buy the inputs

  • Every input: exact name, normal or StatTrak™, collection, float and price.
  • Every result: chance, predicted wear and a realistic sale price.
  • Expected value after fees against the total input cost.
  • The loss on the worst result.

Build the contract in the trade-up calculator, or start from a ready contract in the trade-up finder.