We extract product listings, release calendars, raffle statuses, and SKU-level inventory from Overkillshop. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Sneaker Releases objects from overkillshop.com. All fields typed and schema-versioned.
"release_id": "OK-99214", "title": "Air Jordan 4 Retro 'Bred Reimagined'", "brand": "Nike", "style_code": "FV5029-006", "release_date": "2026-02-17T09:00:00Z", "price": 219.99, "currency": "EUR", "raffle_status": "upcoming"
| # | release_id | title | brand | style_code | release_date | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Product Catalogue objects from overkillshop.com. All fields typed and schema-versioned.
"product_id": "OK-11029", "title": "Asics Gel-Kayano 14", "brand": "Asics", "category": "Sneakers", "colourway": "Cream/Black", "price": 159.0, "in_stock": true, "discount_pct": 0
| # | product_id | title | brand | category | colourway | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inventory & Sizes objects from overkillshop.com. All fields typed and schema-versioned.
"product_id": "OK-11029", "sku": "1201A019-108-43", "size_eu": "43", "size_us": "9.5", "size_uk": "8.5", "stock_status": "in_stock", "price": 159.0, "last_checked": "2026-05-12T10:15:00Z"
| # | product_id | sku | size_eu | size_us | size_uk | stock_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Brands & Collections objects from overkillshop.com. All fields typed and schema-versioned.
"brand_name": "New Balance", "collection_name": "Made in USA", "item_count": 42, "category_url": "https://www.overkillshop.com/en/brands/new-balance.html", "min_price": 119.0, "max_price": 239.0, "new_arrivals": 5, "scraped_at": "2026-05-12T10:15:00Z"
| # | brand_name | collection_name | item_count | category_url | min_price | max_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Raffles & Drops objects from overkillshop.com. All fields typed and schema-versioned.
"raffle_id": "RAF-8821", "product_name": "Yeezy Boost 350 V2", "brand": "adidas", "style_code": "CP9652", "start_time": "2026-05-10T12:00:00Z", "end_time": "2026-05-12T12:00:00Z", "status": "closed", "draw_date": "2026-05-13T09:00:00Z"
| # | raffle_id | product_name | brand | style_code | start_time | end_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper handles the complexities of sneaker retail: limited drops, anti-bot protection, dynamic size grids, and real-time inventory changes.
Title, brand, description, colourway, style code, and high-resolution images scraped for every sneaker and apparel item.
Monitor upcoming drops, release dates, and countdown timers to maintain an accurate sneaker release calendar.
Extract stock availability mapped across EU, US, and UK size charts for every SKU.
Track open, upcoming, and closed raffles including entry windows and draw dates.
Extract and normalise manufacturer style codes to match Overkillshop inventory with secondary market databases.
High-frequency polling during release windows to capture rapid stock depletion and restocks.
Capture current price, original price, and discount percentages across all sale items.
Track total item counts, new arrivals, and price ranges per brand or streetwear collection.
Run daily catalogue exports or configure continuous pipelines for real-time drop monitoring.
Brief in. Clean data out.
Provide target brands, release URLs, or category paths. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and bot-protection bypass for overkillshop.com.
Schema validation, null-rate checks, and size-grid mapping verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Sneaker sites deploy aggressive bot protection during drops. Here is how we maintain extraction stability.
Sneaker retailers use strict bot protection (like Cloudflare or Datadome) to block automated traffic. Our crawlers use German residential ISP proxies with realistic TLS fingerprints and cookie session management to blend in with legitimate sneakerheads.
Stock levels and size availability on Overkillshop are often loaded dynamically via JavaScript. We run full Playwright browser sessions to ensure every size variant and stock status is accurately captured.
During hyped releases, Overkillshop may route traffic through waiting rooms. Our pipeline detects queue states, maintains session persistence, and extracts data as soon as access is granted.
For large apparel catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
High-traffic drops often cause site latency or 503 errors. We monitor response times and adjust concurrency dynamically to ensure data capture without triggering IP bans.
Sneaker news sites and release platforms ingest drop dates and raffle links to keep their audiences updated.
Resellers and trading platforms track retail stock and style codes to identify arbitrage opportunities against StockX or GOAT.
Competing streetwear retailers monitor Overkillshop sale sections and discount depths to adjust their own pricing strategies.
Footwear brands audit retailer compliance, checking if product descriptions, release embargoes, and pricing align with brand guidelines.
Analysts track how quickly specific sizes sell out during drops to model consumer demand for future colourways.
Retailers analyse brand mixes and new arrival velocity to optimise their own seasonal procurement.
"Overkillshop holds critical release data for the European sneaker market, but high-traffic drops make it notoriously difficult to query reliably."
Most teams underestimate the investment required for sneaker site extraction. Reliable Overkillshop scraping requires residential proxies, full JavaScript rendering for size grids, WAF bypass, and anomaly monitoring during high-traffic drops. DataFlirt absorbs that complexity so your engineers can focus on the analysis.
Everything supported by our overkillshop.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright handles JavaScript rendering, cookie sessions, and interaction flows required for dynamic sneaker grids.
We maintain pools of residential ISP proxies across European regions. Rotation happens per-request with sticky sessions for queue management.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About overkillshop.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Overkillshop is generally permissible. DataFlirt targets only public, non-authenticated product, release, and pricing data. We do not extract personal data or circumvent authentication walls. Clients should review terms of service and consult legal counsel for specific use cases.
We use German residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour to navigate WAFs and waiting rooms during high-traffic releases.
Yes. We extract availability status mapped to specific EU, US, and UK sizes for every SKU on the product page.
For targeted drops, we configure high-frequency polling to capture stock changes in near real-time, delivering updates via Webhook to your systems.
Yes. We capture style codes (e.g., Nike SKU formats) to allow seamless mapping between Overkillshop data and secondary market platforms like StockX.
Absolutely. We provide a sample run of up to 500 products or recent releases as part of the pre-engagement scoping process.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full catalogue dump or continuous release monitoring — we scope, build, and operate the pipeline. Tell us what you need.
