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Market price
£0.77
Price history · RAW
2026-04-27 · £0.11 £1.06 · 2026-07-27
Price per print
🇬🇧 Normal · EN n=7 £0.77
How is this value calculated?
Ladder estimate · English · ~£0.77 gruen
Evidence pathSalesAgeValue vᵢWeight gᵢ
eigene rohe NM-Verkäufe5 2 mo £0.7740.82
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = £0.77 · Σ g = 40.82

Measured error for this era×language (backtest): ±16 %

Ladder estimate · Deutsch · ~£0.68 gruen
Evidence pathSalesAgeValue vᵢWeight gᵢ
en roh NM × 0.8832 (Sprach-Faktor aus 64 Karten)5 2 mo £0.683.37
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = £0.68 · Σ g = 3.37

Measured error for this era×language (backtest): ±19 %

Ladder estimate · Français · ~£1.03 gelb
Evidence pathSalesAgeValue vᵢWeight gᵢ
en roh NM × 1.251 (Sprach-Faktor aus 40 Karten) · Set +10% nachgeführt5 2 mo £1.033.6
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = £1.03 · Σ g = 3.6

Measured error for this era×language (backtest): ±25 %

Gate not green — shown only here, never as the price.

Ladder estimate · Italiano · ~£0.86 gruen
Evidence pathSalesAgeValue vᵢWeight gᵢ
en roh NM × 1.1051 (Sprach-Faktor aus 30 Karten)5 2 mo £0.862.03
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = £0.86 · Σ g = 2.03

Measured error for this era×language (backtest): ±17 %

PSA Population

No PSA numbers for this print yet — in any language.

Recent sales · 7
2026-07-27 EN RAW NM Darumaka 034/197 ~ Common English Near Mint · eBay £0.78
2026-06-30 EN RAW NM Darumaka Common SV03: Obsidian Flames 034/197 NM · eBay £1.06
2026-06-12 EN RAW NM Darumaka 034/197 Common Obsidian Flames Pokemon Near Mint · eBay £0.73
2026-05-09 EN RAW NM Darumaka (034/197) [Scarlet & Violet: Obsidian Flames] Near · eBay £0.51
2026-05-05 EN RAW UNKNOWN SV03: Obsidian Flames #034/197 Darumaka £0.11
2026-05-04 EN RAW UNKNOWN SV03: Obsidian Flames #034/197 Darumaka £0.11
2026-04-27 EN RAW NM 🔥Pokemon TCG - Darumaka - 034/197 - Common - Obsidian Flames £0.65
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FAQ

Frequently asked questions

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.