We extract upcoming releases, global raffle lists, SKU metadata, and restock signals from Sole Retriever. 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 soleretriever.com. All fields typed and schema-versioned.
"sku": "DZ5485-042", "brand": "Jordan", "model": "Air Jordan 1 Retro High OG", "colorway": "Black/Royal Blue-White", "retail_price": 180.0, "release_date": "2026-11-04T14:00:00Z", "release_status": "upcoming", "family_sizing": true
| # | sku | brand | model | silhouette | colorway | release_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Raffle Data objects from soleretriever.com. All fields typed and schema-versioned.
"raffle_id": "RF-994812", "sku": "DZ5485-042", "store_name": "END. Clothing", "raffle_type": "online", "entry_method": "app", "end_date": "2026-11-03T08:00:00Z", "regions_allowed": "['US', 'UK', 'EU']", "status": "open"
| # | raffle_id | sku | store_name | raffle_type | entry_method | start_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Stockists objects from soleretriever.com. All fields typed and schema-versioned.
"store_id": "ST-104", "store_name": "Sneaker Politics", "region": "US", "release_type": "FCFS", "allocation_type": "online", "release_time": "2026-11-04T14:00:00Z", "bot_protection": "Shopify Protection", "shipping_methods": "['domestic']"
| # | store_id | store_name | region | shipping_methods | release_type | allocation_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Restock Alerts objects from soleretriever.com. All fields typed and schema-versioned.
"alert_id": "RS-88219", "sku": "DD1391-100", "store_name": "Nike US", "restock_time": "2026-05-12T09:14:00Z", "price": 115.0, "currency": "USD", "size_availability": "['8.5', '9', '10', '11']", "stock_level": "low"
| # | alert_id | sku | store_name | restock_time | size_availability | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Sneaker News objects from soleretriever.com. All fields typed and schema-versioned.
"article_id": "NW-4412", "title": "Travis Scott x Jordan Jumpman Jack TR 'Sail' Release Details", "author": "Sole Retriever Staff", "published_at": "2026-04-18T10:30:00Z", "related_skus": "['FZ8117-100']", "category": "Release News", "tags": "['Travis Scott', 'Jordan Brand', 'Collaborations']"
| # | article_id | title | author | published_at | updated_at | related_skus |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Sole Retriever aggregates highly sought-after drop data. Our infrastructure handles the heavy lifting of bypassing anti-bot systems, rendering dynamic lists, and normalising SKU metadata across thousands of releases.
Extract upcoming, past, and delayed sneaker releases. Capture exact SKUs, colorways, retail pricing, and high-resolution image URLs.
Monitor open and closed raffles across Tier 0 boutiques and global stockists. Extract entry URLs, region restrictions, and collection methods.
Capture restock alerts with timestamp precision. Stream data via Webhook for integration into secondary market pricing models.
Extract lists of confirmed retailers for specific drops, including release mechanisms (FCFS vs Raffle) and exact drop times.
Sneaker data platforms use aggressive Cloudflare and Datadome rules. We use residential proxies and TLS fingerprinting to maintain access.
Extract metadata for releases marked as exclusive to the Sole Retriever mobile app or specific brand applications.
Map inconsistent naming conventions to standard manufacturer SKUs and style codes for accurate downstream joining.
Raffle lists update constantly. We run high-frequency polling and emit only changed records to reduce your ingest load.
Filter and extract release dates and pricing specific to US, EU, UK, and Asian markets.
Brief in. Clean data out.
Provide target brands, silhouettes, or specific date ranges. We map the required data points and delivery frequency.
We configure Scrapy / Playwright crawlers, proxy rotation, and TLS spoofing to bypass Sole Retriever's protections.
Schema validation, null-rate checks, and SKU verification before pushing data to production.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or via Webhook on agreed cadence.
Platforms aggregating hype drops employ strict rate limits and bot mitigation. Here is how we ensure reliable data delivery.
Sneaker platforms use advanced WAF rules to block scrapers. We bypass these using residential IP proxies, HTTP/2 multiplexing, and JA3/JA4 TLS fingerprint spoofing to mimic genuine browser traffic perfectly.
Release calendars and raffle lists load dynamically via API calls. We use Playwright to execute JavaScript, intercept API payloads, and extract clean JSON data directly from the network layer.
Sneaker data is highly time-sensitive. We deploy distributed, high-concurrency crawlers that poll endpoints at sub-minute intervals, ensuring you capture shock drops and restocks instantly.
Brands frequently use overlapping or inconsistent naming conventions. Our pipeline normalises colorways, silhouettes, and style codes against a master database, ensuring clean joins in your warehouse.
We maintain state across runs. When a new stockist is added to a release, or a raffle deadline shifts, we emit only the delta. This reduces noise and processing costs for downstream systems.
Resale platforms and authentication services ingest release calendars and retail pricing to establish baseline market values and track supply signals.
Retailers and consignment stores monitor global raffle volumes and stockist counts to gauge hype and forecast secondary market demand.
Automation tool developers ingest real-time release URLs and restock signals to trigger automated checkout tasks.
Hedge funds and retail analysts track release frequency, brand collaboration volume, and retail price inflation across major footwear brands.
Sneaker news outlets and community forums syndicate release dates and raffle lists to drive traffic and affiliate revenue.
Data science teams train predictive pricing models using historical release data, colorway popularity, and retail-to-resale price spreads.
"Sneaker drop data is highly volatile and heavily guarded. Building an internal scraper for it usually means fighting Cloudflare full-time instead of building your product."
Extracting data from platforms like Sole Retriever requires constant maintenance. Bot protection rules change weekly, API endpoints shift, and DOM structures are intentionally obfuscated. DataFlirt manages this entire infrastructure layer, delivering structured release and raffle data directly to your warehouse so your engineers can focus on core business logic.
Everything supported by our soleretriever.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 retry logic. Playwright executes JavaScript and intercepts API payloads to extract clean data from dynamic Next.js/React frontends.
We utilise residential ISP proxies, HTTP/2 multiplexing, and strict TLS fingerprint matching to consistently bypass Cloudflare and other bot mitigation layers.
Pipelines run on AWS Lambda for burst concurrency. Airflow schedules high-frequency polling tasks, ensuring restock signals hit your webhook in milliseconds.
Data delivered to where your team already works — no new tooling required.
About soleretriever.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available factual data, such as sneaker release dates, retail prices, and stockist lists, is generally permissible. DataFlirt extracts only public, non-authenticated information. We do not bypass authentication walls to access user-specific data. Clients must review platform Terms of Service and consult legal counsel for their specific use case.
Sneaker platforms use aggressive bot mitigation. We deploy ISP-grade residential proxies, realistic browser fingerprints, and HTTP/2 layer spoofing. Our system automatically detects blocks and rotates connection parameters instantly to maintain pipeline uptime.
Yes. We configure dedicated high-frequency polling pipelines for target SKUs or brands. Data is pushed via Webhook the millisecond a restock is detected, enabling downstream automation or pricing updates.
Yes. We can extract global release calendars or filter raffles and stockists specifically for US, UK, EU, or Asian markets based on your requirements.
Our extraction pipeline includes a normalisation layer. We map extracted style codes against a master database to ensure consistent brand, silhouette, and SKU formatting across all delivered records.
Most clients opt for daily or hourly syncs for upcoming release calendars and raffle lists. Restock monitoring requires custom sub-minute polling configurations.
Yes. We provide a sample extraction of recent releases and active raffles during the scoping phase. This allows your engineering team to validate the schema, SKU formatting, and data fidelity before committing to a production pipeline.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a historical database of Jordan releases or a real-time feed of Tier 0 raffles — we scope, build, and operate the pipeline. Tell us your requirements.
