From a sold price to a defensible decision

See the source-linked audit of three actual Jordan auction records →

A worked comp audit: why the highest result can be wrong

Teaching example only. Every price and sale below is fictional. They demonstrate arithmetic and selection decisions, not the market value of a real card. No transaction database was queried.

Suppose you own a raw base card in a particular set. Your research identity includes the year, manufacturer, set, player, checklist number and base version. You are comparing single-card sales in USD. The card has no autograph or serial stamp. You have checked the front and back against the set checklist, but you are not assigning a professional grade.

Step 1: write exclusions before computing the range

The six search results are not six comparable sales. D changes grading status; E changes quantity; F changes the card version. Dividing a mixed lot by its card count is not a reliable substitute for a single-card sale, because buyers may pay a premium or discount for the bundle. A high price alone is not a reason to exclude a sale: the reason must be an identity, condition, quantity or transaction mismatch.

Step 2: calculate only the matching observations

The included prices are 20, 22 and 24. Sorted median: 22. Average: (20 + 22 + 24) ÷ 3 = 22. Observed range: 20–24. Including all six would produce an average of approximately 55.17, a misleading result for this raw base card. The worksheet deliberately does not remove an unusual price automatically; research must establish whether it belongs.

Step 3: handle shipping consistently

If buyers paid an additional 5, 0 and 3 in shipping, their total outlays become 25, 22 and 27. The median becomes 25 and the observed range becomes 22–27. Neither summary is universally correct: state whether your comparison measures item prices or buyer outlay. Taxes, import duties and currency conversion need separate treatment. Do not record unknown shipping as a confirmed zero.

Step 4: record what the evidence cannot establish

Three records do not establish a guaranteed sale price. If they are old, from one seller, or photographed too poorly to compare condition, say so. Keep sale dates and listing references. A relisted item can appear to be a new sale even when the earlier transaction failed; investigate repeated photos and certification numbers. An accepted best offer with a hidden final amount is not evidence for the crossed-out asking price.

A worked grading decision

Another fictional example: a raw copy could sell for 40, all-in grading would cost 30, and the effective selling fee is 10%. Assuming the other selling costs stay equal, selling raw leaves 36 before those shared costs. Grading and selling at 70 leaves 63 minus 30, or 33. The higher headline sale price still produces less.

The graded break-even sale price is 40 + 30 ÷ 0.90 = 73.33 recurring. A sale above that level beats the raw alternative under these assumptions; a sale below it does not. Round up to the next cent when setting a strict threshold. A hypothetical grade result is not a forecast. Compare several plausible grades independently, and do not invent probabilities to make a submission appear profitable.

A repeatable research record

1. Write the exact identity and visible condition before searching.
2. Choose one currency and a consistent shipping treatment.
3. Save dates, references and the actual confirmed sold amount.
4. Explain each exclusion; keep it visible in your exported worksheet.
5. Report the number of included observations and the date window.
6. Separate observed value, sale proceeds and profit.

Apply this process in the sales worksheet or read the research methodology. If you cannot find enough matching records, keep the result unresolved rather than using unrelated expensive cards.

Published November 4, 2026 · WhatsMyCardWorth editorial team · Arithmetic examples, not market quotations.