Source: ~700 listings from Vinted API across France, Germany, Spain, Italy, Netherlands, and Belgium (February 2026). 20-50 listings per country per product category, querying average sale prices for each item.
Tool: Python + matplotlib for visualization. Data collected via a custom MCP server I built that queries Vinted’s search API across multiple country domains simultaneously.
Some notes on the data:
– iPhone 14 has the wildest spread (162%) likely because of different listing conditions and accessories across markets
– Luxury items (LV bags, Canada Goose) show consistent 30-60% spreads
– Commodity items like Nike Air Max 90 are nearly flat (7%) — the market is efficient for mass-produced sneakers
– Cross-border shipping within Western EU is €2-5, so many of these spreads represent real arbitrage opportunities
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Source: ~700 listings from Vinted API across France, Germany, Spain, Italy, Netherlands, and Belgium (February 2026). 20-50 listings per country per product category, querying average sale prices for each item.
Tool: Python + matplotlib for visualization. Data collected via a custom MCP server I built that queries Vinted’s search API across multiple country domains simultaneously.
Some notes on the data:
– iPhone 14 has the wildest spread (162%) likely because of different listing conditions and accessories across markets
– Luxury items (LV bags, Canada Goose) show consistent 30-60% spreads
– Commodity items like Nike Air Max 90 are nearly flat (7%) — the market is efficient for mass-produced sneakers
– Cross-border shipping within Western EU is €2-5, so many of these spreads represent real arbitrage opportunities