Guide: Property Price Percentiles

TL;DR

Price segments in a property market don't always move in sync. Lower-priced, mid-market, and higher-priced properties rise and fall at different rates and respond differently to market conditions. The percentiles that we derive from the Distribution Model let us separate these segments and track them individually to give a more precise view than headline indices can offer.

NOTE: This article uses data from March 2026. To see the most up-to-date data, please see our most recent monthly update.

Where Do Percentiles Sit On a Price Distribution?

Most indices report a single headline number to represent the centre of a market. Percentiles give you the rest of the picture, breaking the full distribution into 100 equal parts to see how different price segments compare. For example, if the 25th percentile is $200k, it means that 25% of properties are valued at or below $200k, and 75% are valued above $200k.

We can visualise these percentiles by overlaying a subset of them onto the property distribution. This is Greater Sydney houses, a particularly broad market:

Before looking at how percentiles change over time, a few are worth knowing by name. The median serves as the best-known example; it represents the 50th percentile, with half of properties valued at or below the median and half above. The 25th and 75th percentiles mark the boundaries of the interquartile range (IQR)^*The IQR is the gap between the 25th and 75th percentiles. It captures the middle 50% of the market. A widening IQR indicates growing price dispersion; a narrowing IQR indicates prices are converging. . The 25th, 50th, and 75th percentiles are also called the first, second, and third quartiles^*The quartiles divide a distribution into four equal parts. The first quartile (Q1) is the 25th percentile, the second quartile (Q2) is the median, and the third quartile (Q3) is the 75th percentile. . At the top end, the 90th percentile can be used to monitor the most costly segment of the market. Likewise the 10th percentile tracks the lowest priced segment.

Tracking Segments Over Time

Growth Rates

Once we can identify price segments using the distribution, the natural next step is to track how each one moves over time. As an example, we can look at the percentiles for Melbourne and Brisbane houses. Both regions showed a peak in median price in early 2022, followed by a decline. The recovery from this decline hasn't been the same for each percentile.

In both cities, the 10th percentile has performed better than the 50th and 90th percentiles. In Brisbane, the 10th percentile is up 66% compared to the 50th percentile's 44% and 90th percentile's 34%. Relying only on the median growth would have overlooked the lower market's strength by 22 percentage points. It would also have overstated the upper market's growth by 10 percentage points. The difference is Melbourne is striking as well. While the 10th percentile is up 9%, and the median is up 5%, the 90th percentile is yet to recover^*As of February 2026 to its 2022 peak, down 1%.

Market Timing

The timing differences between percentile segments stand out when we measure how many months each took to return to the 2022 peak. In Brisbane, Sydney, and Melbourne, a clear trend emerges: lower percentiles, which represent more affordable properties, recovered faster than higher percentiles. The gap between the 10th and 90th percentiles was seven months in Brisbane, five months in Sydney, and over a year in Melbourne.

This pattern won't hold for every market or every cycle, but it illustrates how different price segments can display different dynamics. These timing and magnitude differences are important; they impact anyone using an index to make decisions.

Finding Your Percentile

Matching a percentile to a particular property is analogous to having access to local indices. If you are looking to track the growth of a property in a particular suburb, you would want to use the index for that suburb, not the index for the whole city. You would also want to use an index specific to your property type (houses or units). The same logic applies for price segments. Using an index that doesn't match your segment risks misrepresenting the growth.

Suburb Comparison for Buyers

Buyers with a particular budget often look to compare suburbs based on property availability. A $600k budget might be the 50th percentile in one suburb (half the market within reach) but the 90th in another (only 10% accessible). Same budget, but you'd expect very different numbers of listings in reach, and very different levels of competition.

Investment Benchmarking

The cost of using too general an index for tracking growth can compound for an investor looking to benchmark a portfolio of properties. With a portfolio of five properties in separate cities and price segments, the growth of the portfolio could be very different to the growth suggested by a median index for each city.

Affordability Analysis

Given a particular deposit size, or a fraction of income devoted to housing costs, the matching percentile indicates what proportion of the dwellings in a region remains affordable. Tracking this over time shows how housing affordability is changing. Do the bottom 30% of income earners have access to 30% of the housing stock? Are they losing access over time? Percentiles give us a way to answer these questions.

Percentiles, drawn from our Distribution Index, gives us the precision to address all these use cases. This is something headline indices just aren't designed to do. Our core index set captures the differences between cities, towns, and submarkets. Percentiles add the missing dimension: differences within those markets, across the price spectrum.