A free Google Sheets template that returns what items actually sold for on eBay. Type the item into a cell, get the real median back. No code, no scraping, no browser extension.
Since eBay put sold listings behind a login, checking what something really sold for means signing in and clicking through one item at a time, capped at 90 days of history. That does not scale when you are pricing a lot of forty items or keeping an inventory sheet current.
This template fixes that inside the spreadsheet you already use. It adds four formulas to Google Sheets, each one backed by real completed eBay sales.
| Formula | What you get |
|---|---|
=COMPS_MEDIAN("iphone 14 pro 256gb") | Median price of real completed sales, last 90 days |
=COMPS_MEDIAN("charizard psa 10", 365) | The same over any window, up to 1,095 days |
=COMPS_MEDIAN("switch oled", 90, "used") | Filtered by condition: new, used, open box, refurbished or parts |
=COMPS_COUNT("lego 75192") | How many sales actually matched |
=COMPS_RANGE("rolex submariner date") | The typical band, 25th to 75th percentile |
=COMPS_LAST("ps5 disc edition", 5) | A table of the newest sales with dates and prices |
Drag a formula down a column and you price a whole list in one pass. Minus words work the same as on eBay, so iphone 15 -case -box prices the phone and not the accessories.
What Best Offers actually closed at. When a sale goes through as an accepted offer, eBay keeps showing the asking price with a line through it. The real figure is hidden. In offer heavy categories like watches, cards and anything expensive, pricing from those asking prices means buying high. The sheet uses the amount the sale closed at.
More than 90 days. The sold filter stops at roughly three months, which is enough to answer what something went for last week and useless for seasonality. Pass a second argument and the same formula looks back up to three years, so you can see that golf clubs peak in spring and consoles spike in December before you commit to stock.
A cleaned median. Lots, bundles, parts listings and the wrong model are filtered out, and outliers are dropped, before the median is worked out. A raw average across a keyword search is usually wrong by a wide margin for exactly these reasons.
Three steps, about a minute. Copy the sheet with the button above, which puts your own editable version in your Google Drive. Get a free API key at app.compsapi.com, which takes an email and no card. Then open the CompsAPI menu in the sheet, choose Set API key, and paste it in. Google will ask you to authorise the script the first time, which is standard for any sheet that uses formulas like these.
After that, type any item into the Item column and the numbers fill themselves in.
The free tier is 100 searches a month with every filter enabled and no card. Each unique lookup is one search, and results are cached for six hours, so a sheet recalculating does not quietly drain your allowance. If you price at volume, paid plans start at $9 a month for 5,000 searches.
The spreadsheet and the API are the same data and the same key. If you are building a repricer, a collection tracker or a valuation model, skip the sheet and call /v1/sold directly: up to 240 sales per request as JSON, with Python and Node clients, or read the API reference.
100 free requests a month · every filter on · no card
Get a free key