We extract event listings, dynamic ticket prices, seat map availability, and venue metadata from StubHub. 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 Event Listings objects from stubhub.com. All fields typed and schema-versioned.
"event_id": "151283940", "title": "Taylor Swift - The Eras Tour", "performer_name": "Taylor Swift", "event_date": "2025-08-15", "venue_name": "Wembley Stadium", "city": "London", "status": "Active", "min_price": 350.0
| # | event_id | title | performer_name | event_date | event_time | venue_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Ticket Pricing objects from stubhub.com. All fields typed and schema-versioned.
"ticket_id": "98471239", "event_id": "151283940", "section": "112", "row": "14", "quantity": 2, "price": 450.0, "currency": "GBP", "delivery_method": "Mobile Transfer"
| # | ticket_id | event_id | section | row | quantity | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Venue Details objects from stubhub.com. All fields typed and schema-versioned.
"venue_id": "7483", "name": "Wembley Stadium", "city": "London", "postal_code": "HA9 0WS", "country": "UK", "capacity": 90000, "timezone": "Europe/London"
| # | venue_id | name | address | city | state | postal_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Performer Data objects from stubhub.com. All fields typed and schema-versioned.
"performer_id": "28374", "name": "Taylor Swift", "genre": "Pop", "popularity_score": 99, "upcoming_events_count": 42, "image_url": "https://example.com/tswift.jpg", "similar_artists": "['Sabrina Carpenter', 'Olivia Rodrigo']"
| # | performer_id | name | genre | popularity_score | upcoming_events_count | image_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Seat Availability objects from stubhub.com. All fields typed and schema-versioned.
"event_id": "151283940", "section": "112", "total_seats_listed": 45, "min_price": 450.0, "max_price": 1200.0, "median_price": 650.0, "currency": "GBP", "last_updated": "2025-01-14T08:30:00Z"
| # | event_id | section | total_seats_listed | min_price | max_price | median_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our StubHub scraper handles complex interactive seat maps, dynamic pricing updates, and aggressive anti-bot systems. We deliver clean, structured event data directly to your infrastructure.
Extract event titles, dates, venues, categories, and performer details across all global StubHub domains.
Monitor ticket prices, currencies, and fees across sections and rows. Track secondary market fluctuations in real time.
Extract section and row availability data directly from interactive venue maps and SVG components.
Capture venue names, addresses, capacities, coordinates, and timezone configurations for spatial analysis.
Extract delivery methods, split ticket options, and seller rating indicators for every listing.
Scrape stubhub.com, stubhub.co.uk, and stubhub.ie with region-specific proxies to bypass geo-restrictions.
Configure pipelines to poll high-demand events every few minutes to capture rapid price changes.
Receive only updated ticket prices and new listings to minimise storage bloat and processing overhead.
Bypass Akamai and Datadome protections using residential proxies and realistic browser fingerprints.
Brief in. Clean data out.
Provide event URLs, performer names, or venue IDs. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and CAPTCHA handling specifically for StubHub.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
StubHub employs aggressive bot mitigation and complex frontend rendering. Here is how we extract data reliably at scale.
StubHub uses enterprise-grade bot protection. Our infrastructure rotates residential ISP proxies and mimics human interaction patterns to maintain high success rates without triggering blocks.
Seat availability is often rendered via complex JavaScript and SVGs. We use Playwright to execute the frontend code and extract structured section and row data directly from the DOM.
Secondary market prices change constantly. Our pipelines support high-frequency polling for specific high-demand events, capturing price drops and spikes in near real time.
StubHub displays different inventory based on the user location. We route requests through region-specific proxy pools to ensure you see the exact data presented to local buyers.
Events across different international domains use various currencies and date formats. We clean and normalise all fields before delivery to ensure immediate usability in your warehouse.
Ticket brokers monitor price fluctuations across sections to identify underpriced inventory for immediate purchase.
Event organisers track secondary market premiums to optimise face-value pricing for future tours.
Analysts use ticket velocity and price trends to predict overall event attendance and regional popularity.
Rival ticketing platforms monitor StubHub inventory levels to understand competitor market share.
Hotels and airlines correlate major event ticket sales with expected travel demand spikes.
Agencies track secondary market demand as a proxy for artist or team popularity over time.
"StubHub holds the pulse of live event demand and secondary market pricing, but accessing it at scale requires bypassing aggressive bot mitigation."
Extracting ticket data from StubHub involves more than simple HTTP requests. It requires rendering complex interactive seat maps, circumventing Akamai bot protection, and managing high-frequency pricing updates. DataFlirt handles this infrastructure so your team can focus on arbitrage and market analysis.
Everything supported by our stubhub.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, interactive seat maps, and Akamai bypass flows.
We maintain pools of residential ISP proxies across global regions. Rotation happens per-request to avoid IP bans and view localised inventory.
Pipelines run on AWS Lambda and Kubernetes. Airflow handles scheduling, dependency management, and high-frequency polling triggers.
Data delivered to where your team already works — no new tooling required.
About stubhub.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available ticket data is generally permissible. DataFlirt extracts only public event and pricing information. We do not bypass authentication walls to access private user accounts or extract personal data. Clients must ensure their specific use case complies with local regulations.
We utilise residential ISP proxies, full Playwright browser sessions, and realistic interaction patterns to bypass Akamai and Datadome. Our infrastructure automatically rotates IPs and solves CAPTCHAs when challenged.
Yes. Our pipelines render the JavaScript required to load seat maps and parse the underlying DOM or SVG elements to extract section, row, and specific seat availability.
For high-priority events, we can configure pipelines to poll for price updates every few minutes. Standard event catalogues are typically refreshed daily or hourly based on your requirements.
Yes. We support stubhub.com, stubhub.co.uk, stubhub.ie, and other regional variants. We use geo-targeted proxies to ensure accurate local pricing and inventory extraction.
Engagements typically start with a defined list of performers, venues, or specific events. We price based on the volume of URLs tracked and the required refresh frequency. Contact us for a precise quote.
We begin tracking historical data from the moment your pipeline is commissioned. We do not maintain a retroactive database of past event prices prior to pipeline setup.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need to monitor a specific tour or track secondary market trends across thousands of venues, we build and operate the pipeline. Tell us your requirements.
