CS2 Trade-Up Guide

How to Calculate CS2 Trade-Up Probabilities (With Examples)

What determines the odds in a CS2 trade-up contract?

Two facts determine the output odds: how many inputs came from each collection, and how many eligible skins sit one rarity above those inputs in each collection. Price, float, weapon type, and the order in which you place the inputs do not make a particular skin more likely.

The clean way to calculate an individual output is:

Collection probability = inputs from collection / total inputs
Skin probability = collection probability / eligible outputs in collection

Standard contracts use 10 inputs. The newer Covert-to-special-item route uses 5 inputs, so use 5 as the denominator there and verify the eligible knife or glove pool shown for the selected collections.

How do you calculate a single-collection contract?

Suppose all 10 Restricted inputs come from one collection and that collection has two Classified outputs. The collection is selected 100% of the time, and that probability is split between two eligible skins:

100% / 2 outputs = 50% per output

If the same collection has four eligible outputs, each output is 25%. Adding more copies of the same input skin does not favor a matching weapon; every input is simply another vote for its collection.

How do mixed-collection trade-up odds work?

Consider a contract with seven inputs from Collection A and three from Collection B. Collection A has three eligible outputs; Collection B has one.

The individual Collection B skin is the most likely single result even though Collection B supplies only three inputs. This is why counting the visible output skins without preserving collection weights produces the wrong answer.

Why is dividing by the total number of outputs wrong?

In the example above, there are four possible skins. Assigning 25% to each would erase the 7/3 input mix. The correct probabilities are 23.33%, 23.33%, 23.33%, and 30%. They still sum to 100%, but retain the collection weight created by the inputs.

This distinction changes expected value. A high-priced output in a collection with one input does not receive the same probability as an output in a collection with nine inputs.

How do probabilities connect to expected value?

Once every output has a probability, multiply that probability by the output's realistic net sale value. Add the products to get expected value:

EV = Σ (output probability × output value after fees)

Do not average prices first. A $100 skin at 5% contributes $5 to EV; a $12 skin at 50% contributes $6. The less expensive skin matters more to the contract because it is much more likely.

Our complete EV and ROI guide covers fees, profit probability, and the difference between positive EV and a likely win.

Does float change the probability of an output?

No. Input float changes the output float, wear tier, and therefore price—not which eligible skin is selected. Run the odds calculation and the output-float calculation as two separate steps, then combine them when pricing each outcome.

What probability mistakes should you check before submitting?

• Confirm the rarity step. Only skins one quality above the inputs belong in the normal output pool.
• Keep StatTrak pools separate. A StatTrak contract returns an eligible StatTrak result; do not price it as a normal skin.
• Count outcomes per collection. Different collections can have different numbers of eligible outputs.
• Make the total equal 100%. If it does not, a collection weight or divisor is wrong.
• Recalculate after replacing one input. Moving from 7/3 to 6/4 changes every affected probability.

Frequently Asked Questions