Free sandbox: try any request below on the sample suburbs, no signup. For every suburb, create an API key.

Microburbs Property Data API

Suburb - Market

Chance of a sale within two years (by suburb)

GET/v1/suburbs/{suburb_name}/mesh-blocks/sale-probability20¢ per call

Modelled chance that a home in a suburb or city block sells within the next two years, as a percentage, for every block and suburb in Australia we score. Modelled estimates.

Coverage: About 262,000 mesh blocks and 12,100 suburbs across every state and territory; blocks we did not score return no data. Current to 2026-05-22. Full description, field list and method: /v1/datasets/sale-probability.

One call returns every mesh block in the suburb.

Exact suburb identifier required. Exact official suburb name (SAL), e.g. Burwood (NSW) — many suburbs carry a state suffix. If starting from free text or an unverified bare name, first call GET /v1/geocode/suburb?q=<text>, then use the exact data[].area_name it returns. Suburb data endpoints do not guess a state or typo-correct names.

Authorization

Bearer tokentest

Sandbox key test works for the allowlisted GNAF + SAL — no signup.

Request

The only values you send. Fields under Responses below are what comes back — you never pass those.

Path parameters

suburb_namestringrequired

Exact official suburb name (SAL), e.g. `Burwood (NSW)` — many suburbs carry a state suffix. If starting from free text or an unverified bare name, first call `GET /v1/geocode/suburb?q=<text>`, then use the exact `data[].area_name` it returns. Suburb data endpoints do not guess a state or typo-correct names.

Query parameters

None — this endpoint accepts no query parameters. Call the path above with your bearer token and nothing else.

Responses

Successful Response

application/json

DatasetBlocksfields returned to you

datasetstringalways returned

Dataset slug.

suburbstringalways returned

Canonical suburb name.

as_ofstring · datealways returned

Date the dataset is current to.

modelledbooleanalways returned

True when the figures are modelled estimates.

blocksintegeralways returned

Number of mesh blocks with data.

rowsarray of DatasetBlockRowalways returned

One row per block, field and period.

GET/v1/suburbs/{suburb_name}/mesh-blocks/sale-probability

cURL

curl --request GET \
  --url 'https://api.microburbs.com.au/v1/suburbs/Belmont%20North/mesh-blocks/sale-probability' \
  --header 'Authorization: Bearer test'

Example Responses

Show schema

{
  "data": {
    "dataset": "sale-probability",
    "suburb": "Belmont North",
    "as_of": "2026-05-22",
    "modelled": true,
    "blocks": 60,
    "rows": [
      {
        "mb_code": "10431160000",
        "field": "sale_probability_2y_pct",
        "period": "2026-05-22",
        "value": 13.65084
      },
      {
        "mb_code": "10431170000",
        "field": "sale_probability_2y_pct",
        "period": "2026-05-22",
        "value": 13.70266
      },
      {
        "mb_code": "10431200000",
        "field": "sale_probability_2y_pct",
        "period": "2026-05-22",
        "value": 11.60449
      }
    ]
  }
}

Successful Response200

application/json

About this dataset

About 262,000 mesh blocks and 12,100 suburbs across every state and territory; blocks we did not score return no data. Current to 2026-05-22; refreshed yearly. These figures are modelled estimates.

What it is

A modelled estimate of how likely a home is to change hands in the next 24 months, given for each mesh block (a city block of roughly 30 to 60 homes) and rolled up to a suburb average. A value of 12 means we expect about 12 in every 100 homes in that block to sell within two years.

What it shows

One number per block: the expected share of its homes that sell over the next two years, in percent. The suburb figure is the average of its blocks weighted by the number of homes in each, plus the number of homes it covers. Across Australia the typical block scores about 12.5, the lowest under 1 and the highest above 60, with 99 in 100 blocks between about 6 and 20.

Why use it

Agents prospecting for listings, buyers hunting for quiet off-market approaches, lenders and developers all need to know where homes are most likely to come up. Turnover differs a lot from street to street: long-held family blocks sit near 5, while blocks of rentals and new apartments run well above 20. A suburb average hides that.

How it is built

This is a model output, not a count of sales, and it was last refreshed on 22 May 2026. We back-tested it against the sales we recorded in the two years to that date in two large regions (Brisbane Inner City and Sydney - Parramatta). The model's average (12.5 and 10.0 in 100 homes) sits above the sales we recorded (8.8 and 7.2 in 100), which is expected because our sales record is not complete. Between blocks the signal is real but modest: the tenth of blocks the model rates highest recorded about 1.2 to 1.6 times the sales of the tenth it rates lowest, and the order mostly rises from low to high. Nationally the average of 12.5 over two years is about 6 per 100 homes a year, in line with typical annual turnover of Australian homes. Use it to rank where a sale is likelier and as a rough guide to the level, not as a forecast for one home. Blocks with no score are not returned.

Fields

Field	Unit	Description
`sale_probability_2y_pct` Chance of a sale within two years	%	Modelled expected share of homes that sell in the next 24 months, in percent (12 = about 12 in 100 homes). Block level, and the dwelling-weighted average of its blocks at suburb level.
`dwellings_scored` Homes covered by the score	count	Suburb level only: number of homes in the blocks that carry a score, the weight behind the suburb average.