How Output Float Changes Trade-Up Profit

Most explanations of CS2 trade-ups treat output float as a detail you check at the end. It is not a detail. For boundary-hugging contracts — which is where almost all the profit lives — the output float is the single biggest lever on what your result is worth. A change too small to see can multiply or erase your profit.

This post puts real numbers on that claim. To follow along on live contracts, browse current trade-ups or test inputs in the calculator.

Float decides condition, condition decides price

A trade-up's output float is deterministic. You can compute it before you buy anything:

output_float = avg_adjusted_input_float * (output_max - output_min) + output_min

That float lands the output in exactly one wear condition, and CS2's condition cutoffs are hard. The Factory New / Minimal Wear line sits at 0.07. An output at 0.069 is Factory New; at 0.071 it is Minimal Wear. Nothing about the skin looks different. The price is a different story.

The data: one boundary, huge price gaps

We compared Factory New and Minimal Wear for real CS2 skins using marketplace data captured in June 2026. The table keeps the two sides of the 0.07 boundary and the FN ÷ MW ratio from that comparison:

The float columns are the two sides of the 0.07 boundary: 0.069 is Factory New and 0.071 is Minimal Wear. Every one of these crosses a 10x value line there. The FN ÷ MW column is that gap. The M4A1-S | Nightmare ratio is 10.6x across a float change you could not detect by looking at the weapon.

Why this breaks naive profit estimates

The condition itself is computable: the deterministic float tells you whether the output is Factory New or Minimal Wear before you buy. The problem is the price you attach to it. A model that values the output at a blended condition price throws away exactly the information that matters most near 0.07, where value jumps. Price a boundary output as a blended average and your profit estimate is off by the multipliers above, not by a few percent. The contracts most worth doing are the ones engineered to sit closest to a boundary, which is precisely where a blended price is least trustworthy.

It is not only the boundary, either. Within a single condition, price still drifts with float: a 0.16 Field-Tested generally outsells a 0.37 Field-Tested. The boundary effect is the dramatic one, but intra-condition float still moves money on the margin.

How the float actually gets calculated

You control the output float through your input selection. Each input contributes its adjusted float — its position within its own min-to-max range — and the average of those adjusted values maps onto the output skin's range. Swap one high-float input for a lower one and the predicted output float drops, sometimes just enough to cross a boundary in your favor. That is the whole game on boundary contracts: nudging the average until the deterministic output lands one tick inside the better condition.

How to use this

Before buying inputs, predict the exact output float and check which condition it lands in — and how close it is to the next boundary. A contract that lands at 0.068 is fragile: a single slightly-worse input can tip it into Minimal Wear and collapse the value. A contract that lands at 0.045 has margin to spare. Price the output at that exact float, not at a blended condition average, and your profit estimate will be far closer to the actual sale range — and far less likely to be distorted near a boundary.

Run your inputs through the calculator to see the predicted output float and value, compare live contracts, or read why CS2 trade-up calculators disagree for the pricing mechanics behind these numbers.

Method: per-condition prices captured from TradeUpBot's live marketplace data (CSFloat sales, with reference pricing as fallback) on 2026-06-24. Prices move with the market; the ratios are a dated snapshot of the boundary effect, not a fixed quote.

FAQ

How much does output float affect CS2 trade-up profit?

On boundary-hugging contracts, enormously. Crossing the 0.07 Factory New / Minimal Wear line changes an output's value by roughly 10x to 17x on real skins — for example a USP-S | Black Lotus at 14.4x. Within a single condition, price still drifts with float but less dramatically.

Why does such a tiny float change matter so much?

Because CS2 wear conditions have hard cutoffs. An output at 0.069 is Factory New and one at 0.071 is Minimal Wear, and the market prices those two conditions very differently even though the skins look identical. The float change is invisible; the condition change is not.

Can I predict the output float before buying inputs?

Yes. The output float is deterministic: it is the average of each input's adjusted float mapped onto the output skin's float range. A calculator computes it exactly from your ten inputs, so you can see which condition the output lands in and how close it is to the next boundary before spending anything.

Are these ratios exact?

They are a dated snapshot. The FN ÷ MW ratios were captured from live marketplace data (CSFloat sales) on 2026-06-24 and move with the market. The point is the size of the boundary effect — a roughly 10x-plus value change at float 0.07 — which holds even as absolute prices shift.

Published 2026-06-24 by TradeUpBot Team.