SkinMerge organizes trade-up inputs, float behavior, and outcome distributions into a single analysis view. Compare scenarios across multiple price sources in a single workspace.
Analysis is based on recent price snapshots and item metadata. Values and availability can change over time.
Scan large sets of trade-up combinations and narrow them with structured filters for cost, rarity, and liquidity.
Review the same trade-up scenario against multiple price sources to understand how source selection changes the analysis.
Track adjusted float behavior with the same normalized float math used by the internal trade-up engine.
Inspect how each eligible output contributes to the overall distribution for a given set of trade-up inputs.
Choose collections, rarity bands, and input assumptions to focus the scenario space you want to review.
See projected value, value ratio, and float context side by side for each scenario returned by the engine.
Open the builder to examine input composition, output distribution, and custom assumption changes in one place.
Start with your own inputs, apply custom price assumptions, and inspect how each change shifts the output distribution.
Assemble a scenario with exact skins, collections, and rarity combinations.
Adjust float assumptions at the slot level and keep the normalized float math intact.
Override input and output price assumptions to match the scenario you want to inspect.
Review eligible outputs, float-adjusted value estimates, and distribution weights in one screen.
