How We Score Suburbs
Every PropNinja suburb score is computed from publicly available data using a weighted, rules-based model. Here is exactly how it works.
The Three Scores
Every suburb gets three scores, each on a 0–100 scale:
Boom
Growth momentum. How likely is this suburb to see price appreciation in the near term?
Risk
Investment safety. Higher = riskier. Factors in vacancy, supply, economic concentration.
Stability
Market consistency. How predictable are returns? Low volatility = high stability.
The 9 Input Metrics
Each score is derived from a weighted combination of these data points:
| Metric | What It Measures | Source |
|---|---|---|
| Median Price | Current market value | Sales data |
| Median Rent | Weekly rental price | Rental listings |
| Yield | Annual rent / price ratio | Computed |
| 12-Month Growth | Price change over 12 months | Sales data |
| Vacancy Rate | Percentage of unlet properties | Rental data |
| Days on Market | Average selling speed | Sales data |
| Supply Index | New stock relative to existing | Development approvals |
| Demand Index | Buyer activity and enquiry volume | Market activity |
| Affordability Index | Price relative to income | ABS income data |
Weighting and Computation
Each metric is normalised to a 0–100 scale based on national distribution. The three scores use different weightings:
- Boom Score weights growth, demand, and days on market most heavily
- Risk Score weights vacancy, supply pipeline, and economic concentration
- Stability Score weights price variance, yield consistency, and affordability
Exact weights are proprietary but the model is transparent in its inputs and methodology.
Data Freshness
Metrics are updated monthly from the most recent available data. Some indicators (vacancy, days on market) update more frequently than others (median price, which requires sufficient sales volume).
Limitations
- Scores are backward-looking indicators derived from historical data
- They do not predict future performance with certainty
- Low-volume suburbs may have less reliable metrics
- Local factors (flooding, specific developments) may not be captured
How to Use the Scores
The scores are designed to be a starting point for research, not a buy/sell signal. Use them to:
- Shortlist suburbs that match your investment criteria
- Compare suburbs across states on a consistent basis
- Identify trends and momentum before they hit mainstream media
- Supplement (not replace) your own due diligence
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