Browse sets
Market price
€10,07
How is this value calculated?
Ladder estimate · English · ~€10,07 gruen
Evidence pathSalesAgeValue vᵢWeight gᵢ
eigene rohe NM-Verkäufe6 2 mo €10,0748.98
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = €10,07 · Σ g = 48.98

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

Ladder estimate · Deutsch · ~€9,78 gelb
Evidence pathSalesAgeValue vᵢWeight gᵢ
en roh NM × 0.9714 (Sprach-Faktor aus 9 Karten)6 2 mo €9,780.29
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = €9,78 · Σ g = 0.29

Measured error for this era×language (backtest): ±34 %

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

Ladder estimate · Français · ~€11,98 rot
Evidence pathSalesAgeValue vᵢWeight gᵢ
en roh NM × 1.1893 (Sprach-Faktor aus 36 Karten)6 2 mo €11,983.67
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = €11,98 · Σ g = 3.67

Measured error for this era×language (backtest): ±9 %

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

Ladder estimate · Italiano · ~€11,92 gelb
Evidence pathSalesAgeValue vᵢWeight gᵢ
en roh NM × 1.1836 (Sprach-Faktor aus 28 Karten)6 2 mo €11,925.72
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = €11,92 · Σ g = 5.72

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

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

PSA Population EN Σ 58
PSA 10
1 2%
PSA 9
6 10%
PSA 8
32 55%
PSA ≤7
19 33%
PSA · Burning Shadows Prerelease-Staff · as of 2026-08-13
Recent sales · 1
2026-06-14 EN RAW LP Seviper - SM46 - Black Star Promo - Pokemon Card - LP €6,01
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FAQ

Frequently asked questions

Is it worth grading Seviper SM Black Star Promos SM46/248?

A PSA 10 currently sells for about €497,22, raw the card sits at €10,46 — 47,5× as much. Mathematically, submitting returns €497,22 on average, before fees and shipping. Rule of thumb: submit when the value at a realistic grade is at least double the raw value — which is the case here. Centering decides it: an off-centre card will not get a 10.

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.