CS2 Float Values: Ranges, Conditions & Trade-Ups

CS2 float values are permanent wear numbers from 0 to 1 that determine skin condition and trade-up output quality. In trade-up contracts, adjusted float maps each input to its own float range, then projects the average onto the output skin.

After learning the ranges, test exact inputs in the CS2 trade-up calculator or compare active opportunities on the live trade-up table.

Float Values Explained

Every CS2 skin has a float value between 0 and 1 that determines its visual wear. A lower float means less wear. The float is set permanently when the skin is unboxed or dropped, and it never changes afterward.

Not every skin uses the full 0 to 1 range. Each skin has a defined minimum and maximum float. An AK-47 Redline runs from 0.10 to 0.70, so it can never be Factory New or Battle-Scarred. A Desert Eagle Blaze runs from 0.00 to 0.08, so it can only be Factory New or Minimal Wear.

These float ranges matter enormously for trade-ups, because the output float calculation uses the output skin's range, not the ranges of your inputs.

The Adjusted Float Formula

When calculating the output float, the game first normalizes each input float to a 0 to 1 scale relative to that input skin's float range. This is the adjusted float:

adjusted = (float - min_float) / (max_float - min_float)

For a skin with range 0.00 to 1.00 and float 0.05, the adjusted float is simply 0.05. For a skin with range 0.00 to 0.08 and the same float 0.05, the adjusted float is 0.05 divided by 0.08, which is 0.625. The same 0.05 float represents very different things depending on the skin's range.

The game averages all 10 adjusted floats, then maps the result back to the output skin's range:

output_float = (avg_adjusted * (out_max - out_min)) + out_min

This two-step normalization is why the same input skins can produce very different output floats depending on which output skin you are targeting. It is also why some input skins are far more valuable for trade-ups than others, even at the same condition and price.

Why Different Skins With the Same Condition Have Different Trade-Up Value

Take two Factory New skins, both at float 0.03, both costing $5. Skin A has a float range of 0.00 to 1.00. Skin B has a float range of 0.00 to 0.08.

Skin A contributes a very low adjusted float to the average, which helps produce a Factory New output. Skin B contributes a much higher adjusted float, pulling the output toward Minimal Wear or worse, despite being Factory New itself.

This is counterintuitive. A Factory New input seems like it should always help produce a Factory New output. It does not. A Factory New skin with a narrow float range, such as 0.00 to 0.08, has a high adjusted float relative to its range and pushes the output float higher than expected.

The best trade-up inputs are skins with wide float ranges and low actual floats. A skin with range 0.00 to 1.00 and float 0.01 has an adjusted float of just 0.01, pulling the output hard toward the minimum.

Condition Boundaries: Where the Money Is

The five wear conditions have specific float boundaries. The bands below are drawn to scale, which shows how much of the range Field-Tested and Battle-Scarred actually occupy.

The price jump at each boundary is where trade-up profits come from. A skin at float 0.0699 is Factory New, while the same skin at 0.0701 is Minimal Wear. The visual difference is invisible, yet the price difference can be large. On popular skins, Factory New can be worth two, five, or even ten times the Minimal Wear price.

The FN to MW boundary at 0.07 is the most profitable. The MW to FT boundary at 0.15 is the second most important. The FT to WW and WW to BS boundaries matter less because the price jumps are usually smaller.

Float Targeting Strategies

Given the formula, you work backward from the output float you want. If you need the output under 0.07 for Factory New, you calculate what average adjusted float is required, then find inputs that achieve it.

For an output skin with range 0.00-1.00, you need avg_adjusted under 0.07. For a skin with range 0.00-0.50, you need avg_adjusted under 0.14 (because 0.14 * 0.50 = 0.07). The narrower the output skin's range, the more forgiving the trade-up is.

The best targets for profitable trade-ups are output skins where:

• The Factory New version is worth significantly more than Minimal Wear
• The output skin's float range starts at or near 0.00
• Cheap input skins with wide float ranges exist in the same collection or compatible collections

CSAlpha's discovery engine tests 45+ float targets per combination, densely clustered around condition boundaries. Instead of checking one float and hoping for the best, it finds the exact crossing point where an output flips from one condition to another. This is how it identifies opportunities that manual calculations miss.

Practical Considerations

You need exact floats, not conditions. Two "Factory New" skins can have floats of 0.001 and 0.069. Their trade-up value is completely different. Never select inputs based on condition alone, always check the exact float value.

Mixed collections add outcome variance. When your inputs span multiple collections, you're introducing randomness in which output skin you receive. Each possible output may have different float ranges, meaning the same average adjusted float produces different output floats (and different conditions) depending on which skin you get. Plan for every possible outcome, not just the best one.

Small float differences in inputs compound. Replacing one input skin with a float 0.02 lower reduces the average adjusted float by 0.002 (in a 10-input trade-up). That might not sound like much, but when you're right at the 0.07 boundary, 0.002 is the difference between FN and MW, and potentially hundreds of dollars in output value.

Check input float ranges before buying. A "cheap" input that looks like a great deal might have a narrow float range that gives it a high adjusted float, dragging your output toward a worse condition. Always calculate the adjusted float, not just the raw float.

FAQ

What are CS2 float values?

CS2 float values are permanent wear numbers from 0 to 1 that determine whether a skin is Factory New (0.00 to 0.07), Minimal Wear (0.07 to 0.15), Field-Tested (0.15 to 0.38), Well-Worn (0.38 to 0.45), or Battle-Scarred (0.45 to 1.00).

What float is Factory New in CS2?

Factory New covers floats from 0.00 up to 0.07. Minimal Wear starts at 0.07, so tiny float differences near that boundary can create large price changes.

What is adjusted float in CS2 trade-ups?

Adjusted float normalizes each input skin's float within its own min to max range: adjusted = (float minus min) divided by (max minus min). The 10 adjusted floats are averaged, then mapped onto the output skin's range to produce the output float.

How does adjusted float affect trade-ups?

Adjusted float normalizes each input within its own min and max range, averages those values, and maps the average onto the output skin range.

Published 2026-03-17 by CSAlpha Team.