You're making six and seven-figure decisions off this data. So here's the whole stack, plain English: two named research providers (Hotspotting + HtAG) feed one 5-axis composite, refreshed at the most recent available data. Every threshold cited. Every score traceable back to a source line.
The scoring model was built for James's private buyers agent work. The same 5-axis rubric he applies when pricing a $2M portfolio. It's now every report you see in StratMap.
Beyond the 5 axes, each LGA carries 8 additional classification inputs that determine its archetype (growth-lean, yield-lean, defensive, cyclical) so it can be matched to your strategy brief automatically.
StratMap doesn't produce first-hand market research. What we do is combine two respected Australian research houses into a single composite view, then score it against a locked rubric so every LGA and every suburb reads on the same scale.
What we add on top: a locked composite rubric (5 axes, published bands, all cited below) that normalises signals from all three inputs into a single 1-5 score per axis per area. You see the composite; you can also see each provider's raw figure on any suburb or LGA card.
What we don't do: no scraped agent listings, no anecdotes, no social-media signals, no "we heard from a mate" data. If it's on a report, it traces to one of the three sources above.
Every report carries a "last updated" stamp so you always know how fresh the data is. There's no guessing, no chasing a moving target mid-decision, no numbers silently shifting on the report you're reading.
Refresh is free once you've unlocked a suburb report. If the data updates during your 30-day window, you see the fresh pull at no extra cost.
Almost every axis on every report is derived directly from published data (HtAG, ABS, state feeds) against locked bands. One editorial layer sits on top of the LGA Resilience axis, and we disclose it on the LGA card + here.
Why the bonus? Ryder's team publishes the Top-100 quarterly. It blends signals we don't otherwise weight (population growth, infrastructure spend, industry diversification, transaction momentum) into an editorial call about market resilience. We treat it as one supporting signal, hence +1, not +2.
Where it's visible. Every LGA card that receives the bonus shows a "★ Hotspotting Top-100 · Resilience +1" chip so you can see when the bonus fires. Turn the chip off (personal preference) via the LGA settings when we ship them.
Every 1-5 score on every axis lives against a fixed threshold. We list every threshold below with either an external citation or an honest "v1 lock, no external benchmark yet" flag. If a threshold has no citation, it will get one, or the axis will go. Nothing invented ships forever.
scripts/derive_tags.js)| Axis | Threshold for 5/5 | Source |
|---|---|---|
| Growth (5Y CAGR) | ≥ 7% annualised | RBA / CoreLogic long-run AU house-price growth ~6-7% p.a. Anything above long-run average = top band. External citation. |
| Days on market | < 25 days | National median DOM ~35-45 days per CoreLogic monthly indices. <25 = roughly top-quartile market speed. External citation. |
| Vacancy | < 1.5% | REIA-cited "balanced" market is 3%. <1.5% = tight (rental scarcity). External citation (REIA). |
| Building approvals % | < 0.5% of dwellings | V1 lock, no external benchmark yet. Chosen to identify supply-tight suburbs where approvals in the last 12 months are less than half a percent of existing stock. Will be validated against ABS Building Approvals trends in v2. |
| Gentrification composite | ≥ 3.5 points | Explicitly weak, flagged as estimate in derive_tags.js comments. IRSAD decile band + 5Y growth threshold + population size band. No single external source combines these; we surface the composite score with a "weak signal" warning on the report page. |
AREA_BANDS in compare.html + decision_engine.js)| Axis | Threshold for 5/5 | Source |
|---|---|---|
| Growth (5Y avg) | > 6% avg 5Y growth | Same rationale as suburb Growth. RBA / CoreLogic long-run average. External citation. |
| Yield | > 5% gross | Aligned with strategy_stage_matrix stage cutoffs (Retirement stage requires yield ≥ 5%). Internal doc, cross-linked. |
| Rental Demand (inverted vacancy) | < 1% vacancy | Same REIA "balanced = 3%" reference. Bands cascade [1, 2, 3, 3.5] to give 5-tier scores. External citation (REIA). |
| Resilience (unemployment inverted) | < 4% | ABS Labour Force AU average is ~3.5-4%. Below AU average = above-median resilience. External citation (ABS). |
| Resilience +1 editorial signal | Hotspotting Top-100 | See section 3.5 above: Terry Ryder's Hotspotting Top-100 published quarterly. External signal, editorially disclosed. |
| Liquidity | > 900 annual sales | V1 lock, no external benchmark yet. Bands [100, 300, 600, 900] chosen to distinguish thin-turnover LGAs (~100/yr) from deep-liquidity capital-city LGAs (~1000+/yr). Will be validated against ABS Weekly Sales Transactions series in v2. |
| Affordability (median house price) | ≤ $600K | National median house is ~$800K per CoreLogic Home Value Index. ≤ $600K sits ~25% below national median. Bands [600K, 750K, 900K, 1.2M] mirror the strategy_stage_matrix Foundation/Balance/Consolidation ranges. Cross-linked with locked stage doc. |
memory/strategy_stage_matrix_v1.md)All 5 stage tests (Foundation / Acceleration / Balance / Consolidation / Retirement) are sourced to the Feb 2026 Australian Portfolio Growth session + Hotspotting's investment-grade brackets. Full test-per-stage table is in the locked memory doc. Internal doc, but each threshold sits in a documented range for its investor profile.
memory/strategy_matrix_research_20260624.md)All 8 strategy tests (bh-growth, bh-cashflow, equity-recycling, rent-vesting, smsf, brr, dual-occ, new-build-2026) are sourced to the research doc citing industry rules, BuyersNet buyers-agent conventions, and NG-reform Treasury factsheet where relevant. BRR + dual-occ marked UNSURE (missing housing-era + block-size data). New-build-2026 uses hotspottingTop as proxy signal, labelled MEDIUM confidence in matrix.
Three thresholds currently land here (all queued for a proper source in v2 methodology):
These are honest: the numbers you see today are the ones we've locked at v1. When they get external citations, we bump the version + re-derive every score. You'll see the version stamp on every report.
The research tells you where the data points. It doesn't tell you the future. Growth cycles vary. Interest rates change. Reforms happen (2026 Federal Budget, for one). What the model does do is make your assumptions visible and adjustable.
Every covered LGA and suburb, every measured axis, refreshed against the most recent available data. 8,000+ suburbs carry investment-grade data; thin markets are deliberately excluded. Free to browse. Deep-dive reports on your token spend.