Ordus › Methodology

Methodology

Ordus is built on primary data — NSW Valuer General bulk sales records and SQM Research listings — not aggregator estimates. This page explains exactly how every number on the site is derived, so you can judge it for yourself.

Last updated 2026-06-02.

Data sources

Median prices

Each suburb’s monthly median is estimated from VG sales using nearest-month estimation: for a target month we take qualifying sales within a 6-month window, require at least 3 sales (single-sale months are skipped to avoid outliers), smooth across the 3 closest qualifying values, and reject values more than 3× off the trailing-12-month baseline. The headline “current median” shown across the terminal is a trailing-12-month rolling median, which is more stable than any single calendar month.

House vs unit split

VG records a unit/strata number when a sale is a unit. Sales with a unit number are classed as units; the rest as houses. Every median, growth rate and screener metric can be viewed for houses, units, or all sales.

Settlement-lag handling

VG records appear after settlement, so the most recent months are always under-counted and can look like a sudden price cliff. Ordus nulls the trailing months of each series when the sale count falls below a noise floor (roughly the lower of 3 sales or 30% of the trailing-12-month average), and the charts draw a “data settling” band over that region. This removes artefacts that affected ~13% of suburbs in raw published data. See the insights write-up for the full story.

Growth rates (CAGR)

1, 3, 5 and 10-year compound annual growth rates are computed from the trailing-12-month median at each anchor point (not single-month figures), so they reflect sustained movement rather than monthly noise. Growth is reported per suburb across all sales; very thin suburbs (fewer than ~1 sale/year) are excluded from ranked surfaces.

Opportunity score (screener)

The 0–100 score in the Market Screener is a weighted blend of momentum and supply signals, normalised to each metric’s sensible range:

A suburb with no usable price history, or with less than 40% of the total signal weight available, is left unscored rather than flattered by a partial signal.

Property value estimate (My Property)

Given a property’s last sale, Ordus estimates today’s value as:

estimate = individual-factor × current class median × street premium × land adjustment

The individual factor is how the last sale compared to its suburb’s house/unit median at the time, on the same street. As the prior sale ages, that factor is decayed toward 1.0 (so a decade-old premium regresses to the suburb mean) and clamped to a sane range so outlier priors can’t dominate. The street premium is how that street historically trades versus the suburb median; the land adjustment nudges houses up or down for unusually large or small blocks (capped at ±30%).

Each estimate carries a confidence band based on how recent and how typical the prior sale is. Backtested against ~660 fresh NSW sales, the median absolute error is ~12% and the mean absolute percentage error ~15–16%. VG data carries no bedroom, bathroom or floor-area information, which is the main ceiling on estimate accuracy — the estimate is a market-data model, not a physical inspection.

Listing age (days-on-market proxy)

SQM publishes listing counts bucketed by age. Ordus collapses those buckets (using their midpoints) into a single median listing age per postcode — a proxy for days-on-market. It is postcode-level, not per-suburb.

Coverage & limitations

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