Taipan Value Engine

Keyboard Resale Estimator

Tell it the brand, model, condition, and what the keyboard cost new, and it gives you a range. Open the advanced options to add the box, the accessories, the lowest listing you can find right now, and how good your listing looks. In the background it mixes a set of fixed adjustments with a model fitted on my own sales, shows you the closest sales it found, and points out what’s helping the price, what’s hurting it, and what to fix in the listing.

Based on my own sales and listings I checked by hand|Not a price guarantee (see About)

01 · Keyboard Identity

Brand

Model

Limited collaboration or drop

02 · Condition & Retail Price

Condition grade

Launch price (what it sold for new at release)

The original launch/MSRP price, not today's sale price. The engine anchors on this and applies modifiers for condition, packaging, collab status, and platform.

Lowest current listing you can find (optional)

Check active listings for the same model in similar condition (eBay, StockX, r/mechmarket). If the board is still sold new, include the cheapest brand-new price you can find; retailer sales count. Optional for keyboards the dataset covers; required when nothing matches your model, because it becomes the main market anchor.

Hidden fields use defaults: no box, no accessories, stock build, eBay, decent listing presentation (7/10).

Complete the form and click Estimate Value to see results.

How the Engine Works

1. Condition multiplier

Condition matters most. It’s applied to the price when new: Mint = 100% of retail. Excellent ≈ 87%. Good ≈ 72%. Fair ≈ 53%. Poor ≈ 35%. The gaps between grades come from what I’ve seen in my own sales (see About).

2. Structural modifiers

Box (+12%), accessories (+4–8%), limited collab (+15–100%), then a bump or cut for the platform and for stock status. These stack on top of the condition price, so a mint, boxed, complete collab can come out above what it cost new. A plain stock board is capped at retail. Only a scarce collab, custom work, or a recorded sale pushes past that.

3. Listing quality range

Good photos and a careful description narrow the range and push it toward the high end. A sloppy listing widens it and drags it down. Whether the title is honest counts separately.

4. Statistical cross-signal

A regression fitted on my own 150+ sales and listings makes its own prediction from retail price, accessories, collab tier, and brand. If you give it the lowest listing you can find, you also get a second, clearly labeled market-adjusted range (70% estimate, 30% floor) and a note on how the two compare. For keyboards the dataset covers, the main estimate never changes because of it.