| ebay.es | n=6 | £1.43 | +98% |
| ebay.com | n=7 | £0.72 | — |
How is this value calculated?
Recency-weighted trimmed median of 8 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 | 8 | 3 mo | £0.68 | 65.31 |
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) | 8 | 3 mo | £0.64 | 2.82 |
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) | 8 | 3 mo | £0.75 | 1.28 |
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 | 8 | 3 mo | £0.72 | 1.91 |
Measured error for this era×language (backtest): ±17 %
No PSA numbers for this print yet — in any language.
#052 · U
#050 · C
#104 · IR
#41 · U
#25 · U
#34 · U
#116 · C
#35 · U
#23 · U
#020 · C
#32 · U
#223 · SIR
#202 · IR
#199 · IRFrequently asked questions
What will I get for Palpitoad Obsidian Flames 051/197 if I want to sell quickly?
Half of all sales fell between £0.72 and £1.29, with a median of £0.98. 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 Palpitoad Obsidian Flames 051/197 unrealistic?
The cheapest genuine sales were around £0.72. Offers well below £0.43 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.