CS2 Trade-Up Calculator

The TradeUpBot CS2 trade-up calculator helps players estimate contract cost, expected value, output float, and potential profit before buying 10 inputs. Use it to compare rarity tiers, understand condition boundaries, and avoid contracts where marketplace fees erase the expected return.

Trade-up math depends on input skin prices, output probabilities, collection weighting, and the adjusted float formula. TradeUpBot pairs calculator logic with live listings from CSFloat, DMarket, and Skinport so you can move from theory to real buyable opportunities.

Browse live trade-ups or research CS2 skin prices and float ranges.

What the calculator does

Search a skin into each slot. The calculator fills each slot with the cheapest current buy-now listing's own float and price. A skin with no listings shows "No listings for this skin right now". The result is a starting estimate. The calculator shows cost, expected value after fees, expected P/L, the share of outcomes above cost, and each output skin's price, probability, and predicted float. Cost is the listed price with no buyer fee added; outcome values are after CSFloat's 2% seller fee.

Calculator, simulator, or generator?

Whether you call it a CS2 trade-up calculator, trade-up simulator, or trade-up generator, the tool does the same job: model a contract before you spend money. TradeUpBot uses all three terms because players search for each one — the underlying math (collection weighting, adjusted float formula, fee-adjusted profit) is identical regardless of the label.

How to use it

1. Choose a rarity tier. Inputs can be any rarity from Consumer Grade to Covert. The calculator detects the rarity from your first resolved input. Standard contracts take 10 same-rarity inputs; Covert inputs feed knife/glove contracts which take 5 inputs instead.
2. Fill each slot from a listing. Search a skin into each slot. The calculator fills that slot with the cheapest current buy-now listing's own float and price. A skin with no listings shows "No listings for this skin right now". Cost is the listed price with no buyer fee added; outcome values are after CSFloat's 2% seller fee. Average prices do not tell you what a specific low-float listing costs.
3. Review the output pool and float. The calculator shows every possible output skin with its probability and estimated value at the predicted float. Check that profitable outputs land safely inside the condition boundary you need (e.g., under 0.07 for Factory New).
4. Compare expected value and outcomes above cost. Positive expected value (after fees) means the probability-weighted value of the outcomes is above your cost; it does not mean a single trade-up will return more than it costs. A higher share of outcomes above cost means fewer possible outcomes are worth less than your inputs. Outcomes are random, so only buy inputs you can afford to lose on one trade-up.

Why most CS2 trade-up calculators are wrong

A trade-up's output float is a single deterministic number — the average of the ten inputs' adjusted floats mapped onto the output skin's range. Most calculators then price that output at its condition average: the blended price of every Field-Tested (or Minimal Wear, etc.) sale. But a 0.16 Field-Tested and a 0.37 Field-Tested are both "Field-Tested" and rarely sell for the same price — the cleaner-looking float trades higher. Pricing the output at a condition average ignores the exact float the contract actually produces.

TradeUpBot prices the exact predicted output float instead. It finds real sales at floats near the contract's deterministic output and prices from those, not from a condition midpoint. Example: a contract predicts a 0.16 output float. A condition-average model values it at the Field-Tested blend; nearest real sales around 0.16 can trade noticeably higher because the skin reads as near-Minimal-Wear. That gap is often the difference between a contract that looks break-even and one whose expected value after fees is above cost — which is why a float-exact calculator and a condition-average calculator can disagree on the very same ten inputs.

See this on live trade-ups, compare the highest expected P/L right now, read how each rarity is drawn, research a skin's float-to-price curve on skin price pages, or read theory vs reality.