We extract sneaker listings, size-specific pricing, release calendars, and brand catalogues from Flight Club. 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 Listings objects from flightclub.com. All fields typed and schema-versioned.
"id": "fc-89241", "name": "Air Jordan 4 Retro 'Military Black'", "brand": "Air Jordan", "sku": "DH6927 111", "release_date": "2022-05-21", "retail_price": 210.0, "colourway": "White/Black/Neutral Grey"
| # | id | name | brand | silhouette | colourway | sku |
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Complete list of extractable fields for Size & Pricing objects from flightclub.com. All fields typed and schema-versioned.
"sku": "DH6927 111", "size": "10.5", "size_type": "US Men", "price": 435.0, "currency": "USD", "availability": true, "condition": "New"
| # | sku | size | size_type | price | currency | availability |
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Complete list of extractable fields for Market Trends objects from flightclub.com. All fields typed and schema-versioned.
"sku": "DH6927 111", "date": "2023-10-14", "average_sale_price": 420.5, "price_premium": 100.2, "volatility": 4.5, "sales_volume": 124, "price_trend_30d": 2.1
| # | sku | date | average_sale_price | price_premium | volatility | sales_volume |
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Complete list of extractable fields for Streetwear & Apparel objects from flightclub.com. All fields typed and schema-versioned.
"product_id": "sup-fw23-104", "title": "Supreme Box Logo Hooded Sweatshirt", "brand": "Supreme", "season": "FW23", "retail_price": 168.0, "resell_price": 350.0, "sizes_available": "['M', 'L', 'XL']"
| # | product_id | title | brand | season | release_date | retail_price |
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Complete list of extractable fields for Search Results objects from flightclub.com. All fields typed and schema-versioned.
"keyword": "yeezy boost 350", "position": 1, "sku": "CP9652", "title": "Yeezy Boost 350 V2 'Core Black Red'", "brand": "adidas", "min_price": 280.0, "is_new_release": false
| # | keyword | position | sku | title | brand | min_price |
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Our Flight Club scraper navigates the complexities of sneaker market data: dynamic size pricing, release calendars, and infinite scrolling catalogues, with anti-bot circumvention built in.
Extract SKU, colourway, release date, retail price, and silhouette details across the entire catalogue.
Capture the exact price for every half-size variation, as sneaker values fluctuate drastically based on size.
Monitor availability and stock status for specific sizes to gauge market supply and demand.
Track apparel releases from Supreme, Bape, Palace, and other streetwear brands featured on the platform.
Index entire brand pages, specific silhouettes, or custom search queries to build comprehensive datasets.
Run intraday pipelines to capture rapidly changing secondary market prices for arbitrage opportunities.
Monitor upcoming drops and new additions to the catalogue to stay ahead of market trends.
Download high-resolution product photography for machine learning models or internal catalogues.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences.
Brief in. Clean data out.
Provide SKU lists, brand URLs, or search terms. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for flightclub.com.
Schema validation, null-rate checks, price-outlier detection, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Sneaker marketplaces actively block scraping to protect pricing data. Here is how we maintain access and deliver reliable datasets.
Flight Club uses advanced bot mitigation to block automated traffic. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management to blend in with legitimate sneaker shoppers.
Sneaker prices do not exist as static HTML. They load dynamically based on size selection. We use Playwright to execute the JavaScript, interacting with the size selection matrix to extract the exact price for every variant.
Category pages use infinite scroll, making traditional pagination scraping impossible. We intercept the underlying XHR requests to paginate through the entire catalogue efficiently without rendering unnecessary DOM elements.
We extract and normalise the manufacturer style codes (SKUs) so you can easily join Flight Club data with your existing inventory databases or cross-reference prices with other marketplaces.
For large catalogues, we maintain a hash index of last-seen values per SKU and size. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Traders compare size-specific prices across Flight Club, StockX, and GOAT to identify cross-platform arbitrage opportunities.
Primary retailers monitor secondary market premiums to inform pricing strategies for future releases and restocks.
Authentication services and insurers use historical price data and image assets to value collections accurately.
Analysts track silhouette popularity, brand dominance, and colourway trends over time to identify shifts in consumer demand.
Alternative asset funds track sneaker market caps and price volatility to build quantitative investment models.
Computer vision teams use scraped product images and metadata to train sneaker recognition and authentication models.
"Flight Club dictates the secondary market for sneakers, but their pricing data is fragmented across thousands of dynamic size variations."
Extracting sneaker data requires more than a simple HTTP GET. Prices fluctuate intraday based on consignment inventory, and anti-bot systems block aggressive polling. DataFlirt manages the residential proxies, JavaScript execution, and schema normalisation so your quantitative teams receive clean, structured market data ready for analysis.
Everything supported by our flightclub.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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across US/UK/EU regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About flightclub.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and product information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated market data. We do not extract personal data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for block rate spikes in real time and trigger pool rotation automatically.
Yes. Our pipeline interacts with the size selection matrix on every product page to extract the exact price and availability for every single size variant.
Real-time streaming pipelines achieve sub-60-minute latency for price signals on a defined SKU set. Full catalogue refreshes complete within a 6-12 hour window depending on the total size.
Flight Club primarily shows current asking prices. However, by running continuous pipelines, we build a historical time-series dataset of prices for you from the day your pipeline is commissioned.
Yes. We extract standard manufacturer SKUs and style codes, allowing you to easily join the Flight Club dataset with data from other sneaker marketplaces.
Our smallest packages start at a defined SKU list with weekly delivery. For full catalogue tracking or high-frequency intraday updates, we price based on volume and compute requirements. Contact us for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily catalogue sync or high-frequency price updates across 100K SKUs, we scope, build, and operate the pipeline. Tell us what you need.
