| ebay.es | n=8 | £1.58 | +102% |
| ebay.de | n=2 | £1.57 | +101% |
| ebay.com | n=6 | £0.78 | — |
How is this value calculated?
Recency-weighted trimmed median of 7 NM sales (RAW; outliers trimmed against the median, newer sales weigh more, dynamic half-life).
| Evidence path | Sales | Age | Value vᵢ | Weight gᵢ |
|---|---|---|---|---|
| eigene rohe NM-Verkäufe · Set -12% nachgeführt | 7 | 2 mo | £1.32 | 57.14 |
Measured error for this era×language (backtest): ±16 %
| Evidence path | Sales | Age | Value vᵢ | Weight gᵢ |
|---|---|---|---|---|
| en roh NM × 0.8701 (Sprach-Faktor aus 64 Karten) | 7 | 2 mo | £1.25 | 2.52 |
Measured error for this era×language (backtest): ±19 %
| Evidence path | Sales | Age | Value vᵢ | Weight gᵢ |
|---|---|---|---|---|
| en roh NM × 1.0231 (Sprach-Faktor aus 41 Karten) | 7 | 2 mo | £1.47 | 1.25 |
Measured error for this era×language (backtest): ±25 %
Gate not green — shown only here, never as the price.
| Evidence path | Sales | Age | Value vᵢ | Weight gᵢ |
|---|---|---|---|---|
| en roh NM × 1.0927 (Sprach-Faktor aus 30 Karten) · Set -15% nachgeführt | 7 | 2 mo | £1.42 | 1.91 |
Measured error for this era×language (backtest): ±17 %
No PSA numbers for this print yet — in any language.
#104 · U
#11
#50 · C
#106 · C
#50 · C
#9
#61 · C
#58 · C
#122 · C
#121 · C
#38 · C
#85 · C
#52 · C
#67 · CFrequently asked questions
What will I get for Diglett Obsidian Flames 103/197 if I want to sell quickly?
Half of all sales fell between £0.78 and £1.61, with a median of £1.32. Selling fast lands you nearer the lower end; with patience, good photos and a complete title the upper end is achievable.
Below which price is an offer for Diglett Obsidian Flames 103/197 unrealistic?
The cheapest genuine sales were around £0.78. Offers well below £0.47 are typically fakes, mislabelled cards or a different variant — ask for photos of all four borders and a close-up of the surface.
How does lastsold determine the market value?
lastsold uses only real sales — eBay plus auction houses like Goldin & Fanatics — recent sales count more (recency weighting), outliers and fakes are removed. It's not an estimate but actual sold prices, separated by condition, language and grading.