USP-S | Black Lotus
Maximum float is 0.90.
Market Prices
Market prices are volatile and subject to rapid change. Verify current listings before buying inputs or executing a trade-up.
| Wear | Float Range | Normal Price | Volume | StatTrak Price | ST Volume |
|---|---|---|---|---|---|
| FN Factory New | 0.00 – 0.07 | €47.69 | — | €43.13 | — |
| MW Minimal Wear | 0.07 – 0.15 | €3.58 | — | €9.79 | — |
| FT Field-Tested | 0.15 – 0.38 | €1.66 | — | €5.01 | — |
| WW Well-Worn | 0.38 – 0.45 | €1.24 | — | €4.17 | — |
| BS Battle-Scarred | 0.45 – 1.00 | €1.01 | — | €3.89 | — |
Buy USP-S | Black Lotus
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Trade-Up Relevance
This skin can be used as <strong>input</strong> in Mil-Spec Grade → Restricted trade-up contracts from the The Operation Riptide Collection. Why it matters: In CS2 trade-ups, this skin's float range dictates the average float target required. If used as an input, its collection determines output odds. If targeted as an output, its profitability depends on the input cost and current market price.
Possible Outputs (Restricted)
Why Float, Rarity and Collection Matter for Trade-Ups
In CS2 trade-up contracts, the output skin's wear is determined by a mathematical formula using each input skin's float value and float range. Lower input floats produce better output conditions, which often means significantly higher output prices.
The collection determines which skins can appear as output, and the rarity determines the tier. Understanding these mechanics is the key to finding profitable contracts.
Float Value Details
Trade-Up Float Formula
adjusted_float = (input_float - 0.00) / (0.90 - 0.00)
When USP-S | Black Lotus is used as a trade-up input, its float value is first normalized to the skin's specific float range (0.00 – 0.90). The adjusted float contributes to the average that determines output float.
Output Float Prediction
With 10× USP-S | Black Lotus inputs at the same float, the output float for Restricted skins in the The Operation Riptide Collection would be:
output_float = out_min + avg_adjusted_float × (out_max - out_min)