▮ The source of record across all of gaming
GGR Data is one standardized dataset of gaming revenue, built from the regulators' own monthly filings. It covers 38 U.S. jurisdictions, route and tribal gaming, and 16 international markets. Every property is mapped to the operator and brand that own it, with M&A history and earnings-call context alongside.
▮ The problem
Gaming data is scattered across dozens of regulator websites, published in formats and on timelines that never agree — genuinely difficult to track. All of it lives together in one place: one interactive dashboard to monitor the data and understand the trends.
▮ Capabilities
01–04
A live map of the U.S. — 38 jurisdictions carrying 101 live market feeds — plus separate route-gaming, tribal and 16-market international views, with drill-downs from state to property to operator across 250+ tracked properties and counting.
Land-based, iGaming, and online sports betting standardized into a single comparable structure — ~$88.0B of trailing-twelve-month revenue in one place.
Every iGaming and online sports betting skin rolled up to its ultimate parent — so digital revenue reads the way it's actually owned.
Every figure is sourced from a primary filing or left deliberately blank — cross-validated, never modelled. Where a value is derived, such as an even monthly split of a quarterly filing, it is labelled as derived.
▮ What is actually covered
Five areas
| What we track | Markets | Notes |
|---|---|---|
| Land-based casinos | 29 | states with commercial casino floors |
| Online sports betting | 27 | 26 states + Washington, D.C. |
| In-person sportsbooks | 24 | 23 states + Washington, D.C. |
| Online casino | 7 | states with real-money slots and tables |
| Route and video lottery machines | 9 | across 8 states — bars, taverns, truck stops, racinos |
| Historical horse racing | 3 | Kentucky, Virginia, Wyoming |
| Card rooms | 1 | Florida |
| Sports betting, one combined figure | 1 | Virginia, where the state prints a single total |
U.S. properties with physical capacity on file — slot floors, table counts, hotel rooms. Each one is a dated, cited snapshot taken from a 10-K, a regulator filing or the operator's own site, so revenue can be read against a floor rather than just against a name. Capacity is stated as of a date and never interpolated between them, and where a count is not sourced we leave it blank rather than guess.
▮ Freshness
Current through the latest published filings — new figures added the day a regulator posts them.
▮ Reconciliation proof
Alt-data vendors estimate a number, then argue its accuracy. Every total here reconciles to the regulator's own published figure — the same number the state itself reports.
▮ Built for
Investors
Monthly operator and brand revenue between earnings — see what each name has already reported, weeks ahead of the print.
Investment banks
Market sizing, comps, and precedent transactions with SEC citations.
Consultants & market studies
State-by-state TAM, growth, and share data — as far back as each regulator publishes.
Regulators & executives
Cross-state benchmarking from the same filings they publish.
▮ The underwriting funnel
The same drill the terminal runs: start national, filter the vertical, land on a state, resolve to the operator of record.
▮ Inside the terminal
▮ The API
v1.0.0
Seven documented endpoints. Every row carries its value and unit, the period it covers, the serving tier it was drawn at, and the URL of the regulator document it came from — so a row that lands in your model still knows where it came from.
The catalog endpoint lists exactly what the product publishes, quotas are per key, and the interactive documentation is public, so you can read the whole contract before asking for a key.
▮ The gravity model
Premium
Give it a location, a slot and table count, and an opening year. It returns an annual revenue band for that site, built on a gravity model that measures drive times on real roads across 139,000 census block groups.
The band comes from how 18 real forecasts of this kind actually landed, not from the model's confidence in itself. The calibration record, the misses we measured and left in, and the Illinois blind spot are all in the specification.
▮ What a run looks like
▮ Context and data consolidated in one place
Weekly → AnnualTo underwrite trends
Weekend-day counts, holidays, and the local sporting-event calendar, period over period — so a swing is explained, not just reported. Know whether a month moved on real demand or on the calendar it happened to fall on.
20,637Tagged snippets
852 earnings call transcripts, tagged — what management actually said, by topic, operator, and quarter. Updated on a rolling basis.
%Reported to date
Operator-by-operator tracking of what has already been published between earnings — so you can see what share of the period's revenue is confirmed and what is still to come.
as far back as each regulator publishes
When a casino changes hands mid-year, the data knows — revenue maps to the owner of record at the time it was earned.
NextOn the roadmap
A single page per operator heading into the print — everything the states have already published for the quarter, next to what management said last time. The narrative to watch, before the call.
▮ Why this exists
Built by an underwriter who spent nine years rebuilding this market by hand, deal by deal. Independent by construction: no operator relationships, no modelled numbers, no promotional agenda.
Methodology
Private preview
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