Gaming machine data by SA4, Queensland
liveOne row per ABS Statistical Area 4 region per month from July 2004, with the venues approved and operating electronic gaming machines, the machines approved and operating on the last day of the month, and the metered win in dollars. Regions are ASGS 2011 SA4 names.
Also called: Queensland pokies data by region, Queensland gaming machine metered win by SA4, OLGR gaming machine data by statistical area 4.
Part of Gaming machine and gambling data from Queensland, 7 tables the publisher releases together: Gaming machine data by SA2, Queensland, Gaming machine data for clubs, Queensland, Gaming machine data for hotels, Queensland, Gaming machine data, Queensland totals, Gambling expenditure by stream, Queensland, Gaming venues by number of machines, Queensland.
- What is in each row?
- One ABS Statistical Area 4 region in one month, with the number of venues approved and operating, the number of gaming machines approved and operating, and the metered win, which is the amount players lost on the machines.
- Which SA4 boundaries are used?
- The publisher says it uses the areas of the Australian Statistical Geography Standard 2011. Regions are named, with no code.
Made for agents
Connect your AI agent
Any agent that connects to publicdata.au/mcp can find this dataset, read its 7 fields, count and filter across all 5,054 rows and diff its versions. Every answer names the version and carries OLGR's attribution. No key.
Then ask it: What does Gaming machine data by SA4, Queensland hold, and what changed in the newest version?
claude mcp add --transport http publicdata https://publicdata.au/mcpOne command. No key, no account, no sign-up.
Settings, then Connectors, then Add custom connector, and paste https://publicdata.au/mcp.
On the web and in the desktop app.
https://publicdata.au/mcpStreamable HTTP. Cursor, VS Code or any client that connects to a remote MCP server.
Using https://publicdata.au/llms.txt, how many people died on Queensland roads in 2025, by month?For an assistant that reads the web and has no connector.
The dashboard above, live. Click to filter, add panels, share a link or embed a frame.
Query APIFilter and count from a URLaggregate?group=sa4_region&metric=sum.metered_win&month=eq.2026-08-01
Amount players lost on gaming machines in each region in the newest month, in dollars: 50,098,457 GOLD COAST, 28,345,694 LOGAN - BEAUDESERT, 27,661,691 IPSWICH, 26,344,468 BRISBANE - SOUTH.
Download it as Excel, CSV, JSON and 6 more formats
Pick a format and a version. Excel is picked first because it opens in the tools most offices have. The URL is yours to keep. A dated version never changes.
In your own tools
Use it in Excel, R, Python and more
Excel and Power BI read the CSV from its address and refresh from it. The R and Python packages take any dataset on this site by its slug, so a new dataset needs no new release. The DuckDB file attaches read-only over HTTPS, and a query reads only the blocks it touches.
The dated URL in the code never changes. https://publicdata.au/d/qld-gaming-machines-by-sa4/latest/ redirects to the newest version.
https://publicdata.au/d/qld-gaming-machines-by-sa4/latest/data.csvIn Excel choose Data, then From Web, and paste this address. Excel keeps it, so Refresh All reads the newest version. A sheet holds about a million rows; past that, load the query to the Data Model.
https://publicdata.au/d/qld-gaming-machines-by-sa4/latest/data.csvIn Power BI Desktop choose Get data, then Web, paste this address and choose Anonymous when asked how to sign in. A scheduled refresh reads the same address, so the report follows each new version.
library(publicdataau)
df <- pd_read("qld-gaming-machines-by-sa4")
pd_attribution(df)install.packages("publicdataau"). pd_read() fetches the version's Parquet file; pd_rows() and pd_aggregate() ask the query API instead, and pd_connect() attaches the DuckDB file.
import publicdata_au as pd_au
df = pd_au.read("qld-gaming-machines-by-sa4")
df.attrs["publicdata"]["attribution"]pip install "publicdata-au[pandas]". read() fetches the version's Parquet file; rows() and aggregate() ask the query API, and connect() attaches the DuckDB file.
INSTALL httpfs; LOAD httpfs;
ATTACH 'https://publicdata.au/d/qld-gaming-machines-by-sa4/v/2026-09-16/data.duckdb' AS qld_gaming_machines_by_sa4 (READ_ONLY);
SELECT sa4_region, count(*) FROM qld_gaming_machines_by_sa4.records GROUP BY 1 ORDER BY 2 DESC;The DuckDB file attaches read-only over HTTPS and only the blocks a query touches are read. Parquet works the same way: FROM read_parquet(url).
const res = await fetch("https://publicdata.au/api/v1/datasets/qld-gaming-machines-by-sa4/aggregate?group=sa4_region&metric=sum.metered_win&month=eq.2026-08-01");
const { rows, publicdata } = await res.json();
console.log(rows, publicdata.attribution);The query API answers a page on any site as well as Node, with no key. It returns the rows and the attribution the licence asks for.
What is in it
Column names are made snake_case and the publisher's original header is kept beside each one. Blank cells are null. Nothing is added, removed, ranked or summarised.
| Field | Type | Publisher's header | Note |
|---|---|---|---|
| month | date | Month Year | First day of the month the figures are for. |
| sa4_region | string | SA4 Region | ABS Statistical Area 4 name (ASGS 2011), in capitals as published. |
| approved_sites | integer | Approved Sites | Venues approved to operate electronic gaming machines. |
| operational_sites | integer | Operational Sites | Venues operating gaming machines on the last day of the month. |
| approved_egms | integer | Approved EGMs | The most electronic gaming machines the venues are approved to operate. |
| operational_egms | integer | Operational EGMs | Electronic gaming machines operating on the last day of the month. |
| metered_win | number | Metered Win $ | The amount players lost on the machines in the month, in dollars. |
Download this table as a data dictionary (Excel), or read it as a Frictionless Table Schema at schema.json. The key is month, sa4_region.
A sample of 10 rows
From the latest version, newest first by month, each SA4 region in turn, then in the publisher's order, with every field. A blank cell is shown as null.
| month | sa4_region | approved_sites | operational_sites | approved_egms | operational_egms | metered_win |
|---|---|---|---|---|---|---|
| 2026-08-01 | BRISBANE - EAST | 41 | 39 | 2026 | 1764 | 14199897.39 |
| 2026-08-01 | BRISBANE - NORTH | 31 | 31 | 1736 | 1640 | 15305756.52 |
| 2026-08-01 | BRISBANE - SOUTH | 33 | 33 | 2333 | 2228 | 26344468.09 |
| 2026-08-01 | BRISBANE - WEST | 15 | 14 | 997 | 765 | 5767330.89 |
| 2026-08-01 | BRISBANE INNER CITY | 53 | 52 | 1816 | 1652 | 14561821.98 |
| 2026-08-01 | CAIRNS | 71 | 66 | 2922 | 2586 | 21977755.55 |
| 2026-08-01 | CENTRAL QUEENSLAND | 85 | 81 | 2710 | 2306 | 19677148.87 |
| 2026-08-01 | DARLING DOWNS - MARANOA | 69 | 66 | 1433 | 1200 | 7791459.5 |
| 2026-08-01 | GOLD COAST | 125 | 123 | 5943 | 5502 | 50098457.43 |
| 2026-08-01 | IPSWICH | 57 | 55 | 2803 | 2403 | 27661690.67 |
The first row as JSON
As it appears in data.json.
GET https://publicdata.au/d/qld-gaming-machines-by-sa4/latest/data.json
{
"month": "2004-07-01",
"sa4_region": "BRISBANE - EAST",
"approved_sites": 46,
"operational_sites": 46,
"approved_egms": 1829,
"operational_egms": 1813,
"metered_win": 7215675.17
}
Query it without downloading
The query API returns only the rows you ask for, as JSON, NDJSON or CSV, from the same typed rows as the files. It needs no key. Build a query here and run it, then copy the URL or the code into your own work.
How filters work
Each filter is field=operator.value in the query string, and every filter must match. A number or date field compares as a number or date, and a text field compares as text. Values are case-sensitive except with ilike. Prefix not. to negate a filter, as not.eq.value.
| Operator | What it matches |
|---|---|
| eq.value | Equal to the value. |
| neq.value | Not equal to the value. A blank cell does not match. |
| gt.value | Greater than the value. |
| gte.value | Greater than or equal to the value. |
| lt.value | Less than the value. |
| lte.value | Less than or equal to the value. |
| like.*text* | Matches a pattern where * stands for any run of characters. Case-sensitive. |
| ilike.*text* | The same as like, ignoring case. |
| in.(a,b,c) | Equal to any value in the list. A value cannot contain a comma. |
| is.null | Blank in the source, or suppressed by the publisher. |
| Parameter | What it does |
|---|---|
| select | Fields to return, comma-separated. Every field when absent. |
| order | field.asc or field.desc, comma-separated. The publisher's row order when absent. |
| limit | Rows per page, 1 to 10,000. 100 when absent. |
| offset | Rows to skip. The next URL in each answer sets it for you. |
| group | On aggregate, fields to group by, comma-separated. |
| metric | On aggregate, count, sum.field, avg.field, min.field or max.field, comma-separated. count when absent. |
| format | json, ndjson or csv. JSON carries the provenance header, and the others carry it in response headers. |
Without a version the API answers from the newest loaded version, and that answer changes when the publisher releases again. Put versions/<date>/ before rows or aggregate for an answer that never changes. /api/v1/datasets/<slug>/versions lists the loaded versions. The 1 newest version is loaded; versions lists them.
The API allows 60 requests in 10 seconds from one address. Above that it answers 429 for 10 seconds with a Retry-After header, a RateLimit-Policy header and a JSON body that gives the limit. Every API answer carries the same RateLimit-Policy. A client should wait the Retry-After seconds, or read the files, which have no limit. openapi.json describes this dataset's query paths for client generators and agents.
https://publicdata.au/mcp is a remote MCP server over Streamable HTTP with the same tools, defined in the same place, so a tool added to the pages is added here too. It needs no key and no account. The row tools are held to the query API's limit of 60 queries in 10 seconds from one address, and each call is two queries because it also counts the matching rows. Add it to Claude Code with claude mcp add --transport http publicdata https://publicdata.au/mcp, add the URL in Claude as a custom connector, or give it to any client that connects to remote MCP servers. Each queryable dataset is also a resource at https://publicdata.au/d/<slug>/fields.json, which lists its fields with their types, the publisher's descriptions, their ranges and the values they hold, so an agent can read a dataset's shape before it writes a query.
By sa4 region
One page for each sa4 region, with its own count, chart and files. The rows are the same rows as this table.
- BRISBANE - EAST266
- BRISBANE - NORTH266
- BRISBANE - SOUTH266
- BRISBANE - WEST266
- BRISBANE INNER CITY266
- CAIRNS266
- CENTRAL QUEENSLAND266
- DARLING DOWNS - MARANOA266
- GOLD COAST266
- IPSWICH266
- LOGAN - BEAUDESERT266
- MACKAY - ISAAC - WHITSUNDAY266
- MORETON BAY - NORTH266
- MORETON BAY - SOUTH266
- QUEENSLAND - OUTBACK266
- SUNSHINE COAST266
- TOOWOOMBA266
- TOWNSVILLE266
- WIDE BAY266
What changed
One version for every release the publisher has made since this site started following the dataset. The date is the day the file changed on the portal.
- 2026-09-16 5,054 rows7 fieldsutf-8-sigf0cdbf6b3325
versions.json · changes.json · history.tar.zst (76 KB, every version's Parquet and manifest)
Questions
How do I download Gaming machine data by SA4 as a CSV file?
Open https://publicdata.au/d/qld-gaming-machines-by-sa4/latest/data.csv. It redirects to the newest dated version, which is https://publicdata.au/d/qld-gaming-machines-by-sa4/v/2026-09-16/data.csv today. The same path serves Excel, JSON, Parquet, SQLite, DuckDB, NDJSON, Arrow. A dated URL never changes, so use it when the file must stay the same.
Can I open Gaming machine data by SA4 in Excel?
Yes. https://publicdata.au/d/qld-gaming-machines-by-sa4/v/2026-09-16/data.xlsx is a workbook with the 5,054 rows on a records sheet, the field list on a second sheet and the provenance on a third. The CSV also opens in Excel. https://publicdata.au/d/qld-gaming-machines-by-sa4/v/2026-09-16/data.csv.gz is the CSV at about a tenth of the size.
What years does Gaming machine data by SA4 cover?
The current version covers 2004 to 2025. Each release from OLGR becomes a new dated version here, and earlier versions stay online.
How often is Gaming machine data by SA4 updated?
OLGR releases it monthly. This site checks the portal every week and adds a dated version when the file changes.
Can I use Gaming machine data by SA4 commercially?
Yes. CC BY 3.0 AU allows commercial use, redistribution and derived works as long as the attribution is kept. The attribution string is in this page's side column and inside every file.
Is this the official source for Gaming machine data by SA4?
No. The publisher is Office of Liquor and Gaming Regulation, and its page is https://www.data.qld.gov.au/dataset/gaming-machine-data-by-statistical-area-4. This site republishes the publisher's file without changing its content. The original sits beside every version as source.csv with its SHA-256, so the two can be compared.
How do I get only the rows for one sa4 region?
Every version has one JSON file per value of sa4_region, 19 files in the current version, listed with row counts at https://publicdata.au/d/qld-gaming-machines-by-sa4/v/2026-09-16/by/sa4_region/index.json. For example https://publicdata.au/d/qld-gaming-machines-by-sa4/v/2026-09-16/by/sa4_region/brisbane-east.json holds the 266 rows where sa4_region is BRISBANE - EAST.
What this site did to the data. Cells were typed, headers were renamed and the encoding was made UTF-8. Rows were left alone. The publisher's file sits beside every version as source.csv so the change can be checked.
The publisher releases Gaming machine and gambling data from Queensland as 7 files at once, so all 7 tables here share a version date.