rebrowser/gametime-dataset

Gametime Last-Minute Tickets & Event Listings Dataset

Daily snapshots of Gametime's last-minute ticket marketplace with events, listings, deal badges, venues, and performers across sports, concerts, and theater.

This dataset is a preview sample of the Gametime dataset published by Rebrowser. If you're doing academic research, you may be eligible for free access to a much larger slice — see Free Datasets for Research.

This dataset contains 4 entities, each in its own folder: Event Listings (event-listings), Events (events), Performers (performers), Venues (venues). See below for a full field breakdown, sample counts, and data distributions for each.

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Event Listings

Per-event ticket listings from Gametime with section, row, seat group, delivery type, transfer type, ticket type, deal badges, available lot sizes, and ticket disclosures.

19,949,585 total records from 2025-11-16 to 2026-04-19, up to 30,000 rows in this sample (0.15% of full dataset). Exported as one file per day, up to 1,000 rows each, last 30 days retained.

Field	Type	Fill Rate	Description
_primaryKey	string	100%	Unique identifier for this record
_firstSeenAt	datetime	100%	First time this record was seen
_lastSeenAt	datetime	100%	Last time this record was updated
listingId	string	100%	Unique listing ID (e.g., 6908fe8a9c1370439bc948a4)
eventId	string	100%	Event ID this listing belongs to (join with gametime_events)
pricePrefee 🔒	float	100%	Ticket price in cents before fees
priceTotal 🔒	float	100%	Total ticket price in cents (with fees)
priceFaceValue 🔒	float	56%	Face value of ticket in cents (original printed price)
salesTax 🔒	float	100%	Sales tax amount in cents
preTaxTotal 🔒	float	100%	Pre-tax total price in cents
availableLots	array	100%	Available ticket quantities (e.g., [1,2,3,4] means you can buy 1, 2, 3, or 4 tickets)
section	string	100%	Venue section number/name (e.g., 317, 106, 438)
row	string	100%	Row within section (e.g., 8, 3, GA)
sectionGroup	string	84%	Section group/tier (e.g., Club Corner, Lower Corner, Upper, Dream Seat)
seats	array	100%	Seat numbers (* indicates unassigned/GA)
deliveryType	string	100%	Ticket delivery method (mobile, electronic, direct, hard, instant)
transferType	string	75%	Ticket transfer type (tm, paciolan, sg, axs, mlb, text)
ticketType	string	100%	Ticket type (tmqr, tm, tm-web, tdc, gtlew, url, tm-official)
deal	string	32%	Deal indicator (great, amazing, cheapest, super, zone)
savingsAmount 🔒	float	100%	Displayed savings amount in cents
savingsPercent 🔒	float	100%	Displayed savings percentage
disclosures	array	3%	Ticket disclosures (club_access, first_row, aisle, limited_view, standing_room, zone_deal, etc.)
inHandDate	datetime	83%	Date when tickets will be in hand for delivery
eventName	string	—	Event name (from events table)
eventCategory	string	—	Event category (from events table)
eventDatetimeUtc	datetime	—	Event datetime UTC (from events table)
eventVenueId	string	—	Event venue ID (from events table)

🔒 Premium fields are included in the data files but their values are replaced with [PREMIUM]. To access real values, use our website.

Field Distributions

Deal Badge Distribution (deal)

Value	Count	Share
great	2,802,202	█████████░░░░░░░░░░░ 43.8%
amazing	2,277,255	███████░░░░░░░░░░░░░ 35.6%
cheapest	847,600	███░░░░░░░░░░░░░░░░░ 13.3%
super	450,258	█░░░░░░░░░░░░░░░░░░░ 7.0%
zone	17,931	░░░░░░░░░░░░░░░░░░░░ 0.3%

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Events

Gametime events with category, local/UTC datetime, deal indicators, venue and performer references across sports, music, theater, and comedy.

146,021 total records from 2025-11-16 to 2026-04-19, up to 30,000 rows in this sample (20.5% of full dataset). Exported as one file per day, up to 1,000 rows each, last 30 days retained.

Field	Type	Fill Rate	Description
_primaryKey	string	100%	Unique identifier for this record
_firstSeenAt	datetime	100%	First time this record was seen
_lastSeenAt	datetime	100%	Last time this record was updated
eventId	string	100%	Unique event ID (e.g., 672a9e0be4da09717f007c8b)
name	string	100%	Event name/title (e.g., Daniel O Donnell, Elf The Musical)
category	string	100%	Event category (music, theater, sports)
datetimeLocal	datetime	100%	Event local datetime
datetimeUtc	datetime	100%	Event UTC datetime
salesCutOff	datetime	100%	Sales cutoff datetime (when ticket sales end)
tbd	bool	100%	Event is TBD (to be determined)
timeTbd	bool	100%	Event time is TBD
dateTbd	bool	100%	Event date is TBD
minPriceTotal 🔒	float	100%	Minimum ticket price in cents (total with fees)
minPricePrefee 🔒	float	100%	Minimum ticket price in cents (before fees)
maxPriceTotal 🔒	float	100%	Maximum ticket price in cents (total with fees)
maxPricePrefee 🔒	float	100%	Maximum ticket price in cents (before fees)
zoneDealPriceTotal 🔒	float	100%	Zone deal price in cents (total)
flashDealPriceTotal 🔒	float	100%	Flash deal price in cents (total)
hasExclusives	bool	100%	Event has exclusive listings
mapless	bool	100%	Event has no seat map
venueId	string	100%	Venue ID (join with gametime_venues for details)
performerIds	array	100%	Performer IDs (join with gametime_performers for details)
popularityScore 🔒	float	100%	Event popularity score
trendingScore 🔒	float	98%	Event trending score

🔒 Premium fields are included in the data files but their values are replaced with [PREMIUM]. To access real values, use our website.

Field Distributions

Event Categories (category)

Value	Count	Share
music	49,874	████████░░░░░░░░░░░░ 37.8%
theater	39,907	██████░░░░░░░░░░░░░░ 30.2%
comedy	19,567	███░░░░░░░░░░░░░░░░░ 14.8%
milb	6,567	█░░░░░░░░░░░░░░░░░░░ 5.0%
cbb	3,913	█░░░░░░░░░░░░░░░░░░░ 3.0%
wcbb	3,098	░░░░░░░░░░░░░░░░░░░░ 2.3%
cbs	2,590	░░░░░░░░░░░░░░░░░░░░ 2.0%
other	2,474	░░░░░░░░░░░░░░░░░░░░ 1.9%
echl	2,047	░░░░░░░░░░░░░░░░░░░░ 1.6%
mlb	1,909	░░░░░░░░░░░░░░░░░░░░ 1.4%

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Performers

Gametime performers with name, abbreviation, slug, category, category group, primary genre, and genre tags across sports teams, music artists, theater acts, and comedy.

8,873 total records from 2025-11-16 to 2026-04-19, 1,000 rows in this sample (11.3% of full dataset). Exported as a single file, overwritten daily.

Field	Type	Fill Rate	Description
_primaryKey	string	100%	Unique identifier for this record
_firstSeenAt	datetime	100%	First time this record was seen
_lastSeenAt	datetime	100%	Last time this record was updated
performerId	string	100%	Unique performer ID (e.g., 59dbed9825f2c567c037f20b)
name	string	100%	Performer full name (e.g., Sam Smith)
shortName	string	100%	Performer short name (e.g., Sam Smith)
mediumName	string	100%	Performer medium name (e.g., Sam Smith)
abbrev	string	100%	Performer abbreviation (e.g., SMITH)
slug	string	100%	URL-friendly performer slug (e.g., musicsamsmith)
category	string	100%	Performer category (e.g., music, sports)
categoryGroup	string	100%	Category group (e.g., concert, nfl, nba)
primaryGenre	string	62%	Primary genre slug (e.g., pop)
genres	array	62%	Array of genre slugs (e.g., pop, rock)
primaryColor	string	100%	Primary brand color hex (e.g., 637079FF)
heroImageUrl 🔒	string	100%	Hero image URL
headerImageUrl 🔒	string	100%	Header image URL
logoImageUrl 🔒	string	100%	Logo image URL

🔒 Premium fields are included in the data files but their values are replaced with [PREMIUM]. To access real values, use our website.

Field Distributions

Performer Categories (category)

Value	Count	Share
music	4,410	████████████░░░░░░░░ 58.3%
comedy	762	██░░░░░░░░░░░░░░░░░░ 10.1%
cbb	550	█░░░░░░░░░░░░░░░░░░░ 7.3%
wcbb	457	█░░░░░░░░░░░░░░░░░░░ 6.0%
theater	393	█░░░░░░░░░░░░░░░░░░░ 5.2%
cbs	302	█░░░░░░░░░░░░░░░░░░░ 4.0%
cfb	223	█░░░░░░░░░░░░░░░░░░░ 2.9%
milb	169	░░░░░░░░░░░░░░░░░░░░ 2.2%
csoft	163	░░░░░░░░░░░░░░░░░░░░ 2.2%
soccer	136	░░░░░░░░░░░░░░░░░░░░ 1.8%

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Venues

Gametime venues with name, city, state, metro area, timezone, geo-coordinates, and full street address across the US.

3,970 total records from 2025-11-16 to 2026-04-19, 1,000 rows in this sample (25.2% of full dataset). Exported as a single file, overwritten daily.

Field	Type	Fill Rate	Description
_primaryKey	string	100%	Unique identifier for this record
_firstSeenAt	datetime	100%	First time this record was seen
_lastSeenAt	datetime	100%	Last time this record was updated
venueId	string	100%	Unique venue ID (e.g., 61fc67e3b1776e00011716d3)
name	string	100%	Venue name (e.g., New Orleans Fairgrounds)
slug	string	100%	URL-friendly venue slug (e.g., new_orleans_fairgrounds)
city	string	100%	City name (e.g., New Orleans)
state	string	97%	State abbreviation (e.g., LA)
metro	string	100%	Metro area identifier (e.g., neworleans)
timezone	string	100%	IANA timezone (e.g., America/Chicago)
latitude	float	100%	Venue latitude coordinate
longitude	float	100%	Venue longitude coordinate
addressCountryCode	string	100%	Address country code (e.g., US)
addressCity	string	100%	Address city (e.g., New Orleans)
addressState	string	97%	Address state (e.g., LA)
addressPostalCode	string	100%	Address postal/ZIP code (e.g., 70116)
addressStreet	string	100%	Street address (e.g., 1751 Gentilly Boulevard)
addressExtended	string	96%	Extended address (e.g., New Orleans, LA 70116)
imageUrl 🔒	string	100%	Venue image URL

🔒 Premium fields are included in the data files but their values are replaced with [PREMIUM]. To access real values, use our website.

Field Distributions

Venues by State (state)

Value	Count	Share
CA	406	████░░░░░░░░░░░░░░░░ 22.4%
TX	265	███░░░░░░░░░░░░░░░░░ 14.6%
NY	245	███░░░░░░░░░░░░░░░░░ 13.5%
FL	195	██░░░░░░░░░░░░░░░░░░ 10.8%
IL	133	█░░░░░░░░░░░░░░░░░░░ 7.3%
PA	133	█░░░░░░░░░░░░░░░░░░░ 7.3%
OH	130	█░░░░░░░░░░░░░░░░░░░ 7.2%
NC	110	█░░░░░░░░░░░░░░░░░░░ 6.1%
NV	106	█░░░░░░░░░░░░░░░░░░░ 5.8%
CO	90	█░░░░░░░░░░░░░░░░░░░ 5.0%

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Pre-built Views on Rebrowser

Rebrowser web viewer lets you filter, sort, and export any slice of this dataset interactively. These pre-built views are ready to open:

Event Listings

Listings with Deal Badge — 6,395,246 records

↳ [{"field":"deal","op":"isNotEmpty"},{"sort":"priceTotal ASC"}]

Instant Delivery Listings — 61,849 records

↳ [{"field":"deliveryType","op":"is","value":"instant"},{"sort":"priceTotal ASC"}]

Listings with Savings — 19,949,585 records

↳ [{"field":"savingsAmount","op":"gt","value":0},{"sort":"savingsPercent DESC"}]

Cheapest Deal Listings — 847,600 records

↳ [{"field":"deal","op":"is","value":"cheapest"},{"sort":"priceTotal ASC"}]

Listings by Price (Low to High) — 19,949,585 records

↳ [{"sort":"priceTotal ASC"}]

See all 18 views →

Events

Events with Flash Deals — 146,021 records

↳ [{"field":"flashDealPriceTotal","op":"gt","value":0},{"sort":"datetimeUtc ASC"}]

NBA Events — 1,397 records

↳ [{"field":"category","op":"is","value":"nba"},{"sort":"datetimeUtc ASC"}]

Music & Concert Events — 49,874 records

↳ [{"field":"category","op":"is","value":"music"},{"sort":"datetimeUtc ASC"}]

Events with Zone Deals — 146,021 records

↳ [{"field":"zoneDealPriceTotal","op":"gt","value":0},{"sort":"datetimeUtc ASC"}]

Events with Exclusive Listings — 52,151 records

↳ [{"field":"hasExclusives","op":"isTrue","value":true},{"sort":"datetimeUtc ASC"}]

See all 19 views →

Performers

Music Performers — 4,410 records

↳ [{"field":"category","op":"is","value":"music"},{"sort":"name ASC"}]

College Basketball Performers — 550 records

↳ [{"field":"category","op":"is","value":"cbb"},{"sort":"name ASC"}]

Theater Performers — 393 records

↳ [{"field":"category","op":"is","value":"theater"},{"sort":"name ASC"}]

NBA Performers — 36 records

↳ [{"field":"category","op":"is","value":"nba"},{"sort":"name ASC"}]

NFL Performers — 36 records

↳ [{"field":"category","op":"is","value":"nfl"},{"sort":"name ASC"}]

See all 17 views →

Venues

Venues in California — 406 records

↳ [{"field":"state","op":"is","value":"CA"},{"sort":"name ASC"}]

Venues in Texas — 265 records

↳ [{"field":"state","op":"is","value":"TX"},{"sort":"name ASC"}]

Venues in New York — 245 records

↳ [{"field":"state","op":"is","value":"NY"},{"sort":"name ASC"}]

Venues in Florida — 195 records

↳ [{"field":"state","op":"is","value":"FL"},{"sort":"name ASC"}]

Venues in Illinois — 133 records

↳ [{"field":"state","op":"is","value":"IL"},{"sort":"name ASC"}]

See all 19 views →

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Code Examples

import pandas as pd
from pathlib import Path

# ── Venues (reference table) ────────────────────────────────────────────────
venues = pd.read_parquet('rebrowser/gametime-dataset/venues/data.parquet')

# Top 10 states by venue count
print(venues['state'].value_counts().head(10).to_string())

# Venues in a specific metro area
print(venues[venues['metro'] == 'newyork'][['name', 'city', 'state']]
      .to_string(index=False))

# ── Performers (reference table) ────────────────────────────────────────────
performers = pd.read_parquet('rebrowser/gametime-dataset/performers/data.parquet')

# Count performers by category (nba, nfl, music, theater, etc.)
print(performers['category'].value_counts().head(15).to_string())

# Music performers with a primary genre
music = performers[(performers['category'] == 'music') & (performers['primaryGenre'].notna())]
print(music.groupby('primaryGenre').size().sort_values(ascending=False).head(10).to_string())

# ── Events (daily files) ────────────────────────────────────────────────────
files = sorted(Path('rebrowser/gametime-dataset/events/data').glob('*.parquet'))[-7:]
events = pd.concat([pd.read_parquet(f) for f in files])

# Events per category
print(events['category'].value_counts().to_string())

# Upcoming confirmed events (date not TBD)
confirmed = events[events['dateTbd'] == False].sort_values('datetimeUtc')
print(confirmed[['name', 'category', 'datetimeUtc']].head(20).to_string(index=False))

# ── Event Listings (daily files) ────────────────────────────────────────────
files = sorted(Path('rebrowser/gametime-dataset/event-listings/data').glob('*.parquet'))[-7:]
listings = pd.concat([pd.read_parquet(f) for f in files])

# Deal badge distribution
print(listings['deal'].value_counts().to_string())

# Listings by delivery type
print(listings['deliveryType'].value_counts().to_string())

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Use Cases

Last-Minute Pricing Analysis

Study how deal badges (great, amazing, cheapest, super, zone) distribute across event categories and delivery types. Identify which sports and concert segments see the most deal activity.

Venue Market Mapping

Map venue density by state and metro area using geo-coordinates. Identify which regions have the highest event concentration and compare venue coverage across markets.

Performer Demand Research

Analyze which performer categories and genres generate the most events. Track how leagues like NFL, NBA, and MLB compare in event volume over time.

Delivery & Inventory Patterns

Examine distribution of ticket delivery types (mobile, electronic, instant, direct) and available lot sizes across event categories to understand marketplace fulfillment dynamics.

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Full Dataset on Rebrowser

This is a 1,000-row preview sample. The full dataset is at rebrowser.net/products/datasets/gametime

Doing academic research? You may qualify for free access to a larger slice. See Free Datasets for Research.

On Rebrowser you can:

• Filter before you buy — use the web UI to apply filters on any field and sort by any column. Preview results before purchasing. You only pay for records that match your criteria.
• Export in your format — CSV, JSON, JSONL, or Parquet depending on your plan.
• Access via API — integrate dataset queries into your pipelines and workflows.
• Choose your freshness — plans range from a 14-day lag to real-time data with no delay.
• Select only the fields you need — keep exports lean. Premium fields with richer data are available on higher plans.

Pricing starts at $2 per 1,000 rows with volume discounts.

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License & Terms

Free for research and non-commercial use with attribution. See license terms and how to cite.

@misc{rebrowser_gametime,
  author       = {Rebrowser},
  title        = {Gametime Last-Minute Tickets & Event Listings Dataset},
  year         = {2026},
  howpublished = {\url{https://rebrowser.net/products/datasets/gametime}},
  note         = {Accessed: YYYY-MM-DD}
}

Commercial use requires a paid license — see pricing. Use of this data is governed by the Rebrowser Terms of Use, which may be updated at any time independently of this dataset.

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Disclaimer

Rebrowser is an independent data provider and is not affiliated with, endorsed by, or sponsored by Gametime. Any trademarks are the property of their respective owners. This dataset is compiled from publicly available information; we do not request or collect Gametime user credentials. By using this dataset, you agree to comply with Gametime's Terms of Service and all applicable laws and regulations. Images, logos, descriptions, and other materials included in this dataset remain the intellectual property of their respective owners and are provided solely for informational purposes. Rebrowser makes no warranties regarding the accuracy, completeness, or legality of the data and assumes no liability for how the data is used. You are solely responsible for ensuring that your use of this dataset does not infringe on the rights of any third party.

You can also find this data on GitHub, Kaggle, Zenodo.