Browse sets
Market price
£1.11
based on 1 sales
How is this value calculated?
Ladder estimate · English · ~£1.43 gelb
Evidence pathSalesAgeValue vᵢWeight gᵢ
eigene rohe NM-Verkäufe413 3 d £1.433371.43
de roh NM × 0.8223 (Sprach-Faktor aus 102 Karten)7 1 d £0.693.87
fr roh NM × 0.6654 (Sprach-Faktor aus 90 Karten)4 16 d £1.743.51
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = £1.43 · Σ g = 3378.81

Measured error for this era×language (backtest): ±20 %

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

Ladder estimate · Deutsch · ~£0.92 rot
Evidence pathSalesAgeValue vᵢWeight gᵢ
eigene rohe NM-Verkäufe7 1 d £0.8557.14
en roh NM × 1.2162 (Sprach-Faktor aus 102 Karten)413 3 d £1.743.74
fr roh NM × 0.8181 (Sprach-Faktor aus 78 Karten)4 16 d £2.142.8
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = £0.92 · Σ g = 63.68

Measured error for this era×language (backtest): ±28 %

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

Ladder estimate · Français · ~£2.36 rot
Evidence pathSalesAgeValue vᵢWeight gᵢ
eigene rohe NM-Verkäufe4 16 d £2.6232.65
en roh NM × 1.503 (Sprach-Faktor aus 90 Karten)413 3 d £2.154.64
de roh NM × 1.2224 (Sprach-Faktor aus 78 Karten)7 1 d £1.033.46
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = £2.36 · Σ g = 40.75

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

Ladder estimate · Italiano · ~£1.41 rot
Evidence pathSalesAgeValue vᵢWeight gᵢ
fr roh NM × 0.8009 (Sprach-Faktor aus 18 Karten)4 16 d £2.094.39
de roh NM × 1.0715 (Sprach-Faktor aus 20 Karten)7 1 d £0.913.93
en roh NM × 1.0066 (Sprach-Faktor aus 20 Karten)413 3 d £1.442.57
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = £1.41 · Σ g = 10.89

Measured error for this era×language (backtest): ±169 %

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

PSA Population

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

Recent sales · 1
2026-09-23 EN RAW NM Jirachi EX 30th Anniversary stamped 102/128 £1.11
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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.