Toy Catcher
Market price
€0,87
Price history · RAW
2026-04-28 · €0,13
€1,11 · 2026-07-17
Price per print
🇬🇧
Normal · EN
n=4
€0,87
How is this value calculated?
Ladder estimate · English
· ~€0,87
gruen
| Evidence path | Sales | Age | Value vᵢ | Weight gᵢ |
|---|---|---|---|---|
| eigene rohe NM-Verkäufe | 3 | 40 d | €0,87 | 24.49 |
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = €0,87 · Σ g = 24.49
Measured error for this era×language (backtest): ±17 %
Ladder estimate · Deutsch
· ~€0,77
gruen
| Evidence path | Sales | Age | Value vᵢ | Weight gᵢ |
|---|---|---|---|---|
| en roh NM × 0.8873 (Sprach-Faktor aus 34 Karten) | 3 | 40 d | €0,77 | 2.81 |
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = €0,77 · Σ g = 2.81
Measured error for this era×language (backtest): ±22 %
Ladder estimate · Français
· ~€0,91
gelb
| Evidence path | Sales | Age | Value vᵢ | Weight gᵢ |
|---|---|---|---|---|
| en roh NM × 1.0428 (Sprach-Faktor aus 17 Karten) | 3 | 40 d | €0,91 | 7.47 |
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = €0,91 · Σ g = 7.47
Measured error for this era×language (backtest): ±20 %
Gate not green — shown only here, never as the price.
Ladder estimate · Italiano
· ~€0,89
gruen
| Evidence path | Sales | Age | Value vᵢ | Weight gᵢ |
|---|---|---|---|---|
| en roh NM × 1.0279 (Sprach-Faktor aus 29 Karten) | 3 | 40 d | €0,89 | 7.57 |
value = exp( Σ gᵢ·ln vᵢ ⁄ Σ gᵢ ) = €0,89 · Σ g = 7.57
Measured error for this era×language (backtest): ±18 %
PSA Population
No PSA numbers for this print yet — in any language.
Recent sales · 4
| 2026-07-17 | EN | RAW NM | Toy Catcher - 163/203 - Uncommon - Near Mint | €0,87 |
| 2026-06-25 | EN | RAW NM | Toy Catcher 163/203 Uncommon Evolving Skies Pokemon Near Min | €0,87 |
| 2026-05-31 | EN | RAW UNKNOWN | [Error] [M*] Alignment Dots Toy Catcher 163/203 Uncommon Evo | €1,11 |
| 2026-04-28 | EN | RAW UNKNOWN | SWSH07: Evolving Skies #163/203 Toy Catcher | €0,13 |
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.
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