We extract live event schedules, dynamic ticket prices, Deal Scores, and venue topologies from SeatGeek. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery 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 seatgeek.com. All fields typed and schema-versioned.
"event_id": "5492810", "title": "New York Knicks at Boston Celtics", "datetime_local": "2026-11-12T19:30:00", "venue_name": "TD Garden", "event_type": "nba", "status": "normal", "lowest_price": 145.0, "highest_price": 4200.0
| # | event_id | title | datetime_local | datetime_utc | venue_id | venue_name |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Ticket Inventory objects from seatgeek.com. All fields typed and schema-versioned.
"listing_id": "lg-849201", "section": "Loge 12", "row": "C", "quantity": 2, "price": 350.0, "currency": "USD", "deal_score": 8.4, "is_obstructed_view": false
| # | listing_id | event_id | section | row | quantity | price |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Venue Data objects from seatgeek.com. All fields typed and schema-versioned.
"venue_id": "84", "name": "TD Garden", "city": "Boston", "state": "MA", "postal_code": "02114", "capacity": 19580, "location_lat": 42.3662, "timezone": "America/New_York"
| # | venue_id | name | city | state | country | postal_code |
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Complete list of extractable fields for Performers objects from seatgeek.com. All fields typed and schema-versioned.
"performer_id": "2094", "name": "Boston Celtics", "type": "nba", "slug": "boston-celtics", "upcoming_events_count": 42, "popularity_score": 0.94, "genre": "sports"
| # | performer_id | name | type | genre | slug | image_url |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Market Trends objects from seatgeek.com. All fields typed and schema-versioned.
"event_id": "5492810", "timestamp": "2026-10-01T14:30:00Z", "average_price": 284.5, "median_price": 210.0, "listing_count": 342, "total_tickets": 1204, "cheapest_ticket": 145.0
| # | event_id | timestamp | average_price | median_price | listing_count | total_tickets |
|---|---|---|---|---|---|---|
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Our SeatGeek scraper handles the entire secondary market stack: event schedules, dynamic ticket pricing, Deal Scores, and venue topologies. Built with anti-bot circumvention and rapid polling.
Extract all upcoming sports, concerts, and theater events categorised by date, venue, and performer.
Track secondary market price fluctuations at the section and row level across millions of listings.
Capture SeatGeek's proprietary 0 to 10 Deal Score metrics and associated colour codes for every ticket.
Map sections, rows, capacities, and geographic coordinates for stadiums and arenas globally.
Monitor specific artists, teams, or comedians to capture tour dates and aggregated popularity scores.
Identify obstructed views, aisle seats, electronic transfer status, and seller types.
Track how quickly tickets sell out or listing volumes drop to calculate demand curves.
Normalise event data across US, CA, and global markets using standard currency conversions.
Run daily market snapshots or continuous polling at 5-minute intervals for volatile events.
Brief in. Clean data out.
Provide performer lists, venue IDs, or regional parameters. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and anti-bot handling for seatgeek.com.
Schema validation, null-rate checks, price outlier detection, and sample payloads before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or BigQuery dataset on agreed cadence.
Ticketing platforms invest heavily in scraping detection. Here is how we stay resilient and why teams choose managed infrastructure over DIY.
SeatGeek uses advanced bot protection. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full TLS session management trained on real user behaviour.
SeatGeek loads ticket inventory dynamically. We intercept internal JSON API responses directly from the network tab, bypassing the need to parse complex DOM structures and SVG seating charts.
Ticketing platforms change their response structures frequently. Our extraction strategy uses multiple fallback chains per field so an API version bump does not break your data pipeline overnight.
For massive event inventories, we maintain a hash index of last-seen values per listing. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, and coverage drops. SLA uptime is contractual.
Brokers monitor secondary market pricing, Deal Scores, and inventory drops to identify mispriced tickets.
Teams track secondary market premiums for their own games to optimise primary box office pricing.
Analysts correlate ticket velocity and median price movements to predict total event attendance.
Investors track total listing volumes and average transaction values to gauge ticketing market health.
Stadium operators use historical seating chart data and sell-through rates to optimise staffing.
Aggregator apps ingest SeatGeek inventory to display comparative pricing against other exchanges.
"SeatGeek aggregates the most volatile secondary ticket market data available, but mapping those price fluctuations to specific seat topology requires dedicated extraction infrastructure."
Event ticketing operates on extreme supply and demand curves. To capture real-time secondary market prices, Deal Scores, and vanishing inventory, your pipeline must handle strict anti-bot measures, complex SVG seating charts, and rapid data expiration. DataFlirt manages this complexity entirely, delivering clean, normalised market signals directly to your warehouse.
Everything supported by our seatgeek.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 handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across US regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda and ECS. 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 seatgeek.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from SeatGeek is generally permissible. DataFlirt targets only public, non-authenticated event, pricing, and venue data. We do not extract personal data or circumvent authentication walls. Clients should review SeatGeek ToS and consult legal counsel.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for 403 or CAPTCHA rate spikes in real time and trigger pool rotation automatically.
Yes. We capture the numeric Deal Score from 0 to 10, the qualitative label, and the UI colour code associated with the listing.
Real-time streaming pipelines can achieve 5-minute polling latency for specific high-profile events. Full catalogue refreshes typically run at a daily cadence.
Yes. We extract all seat-level metadata, including obstructed view flags, aisle seat indicators, and electronic transfer requirements.
Yes. You can provide a list of performer IDs, team slugs, or venue IDs. The pipeline will automatically discover and monitor all events matching your parameters.
Our smallest packages start at a defined list of 500 events or 50 venues with daily delivery. For larger catalogues, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off venue catalogue dump or a continuous price-monitoring feed across 10,000 live events. We scope, build, and operate the pipeline. Tell us what you need.
