Every metric in a SuburbIQ report, explained.

HTAG's national-suburb ranking on a 0–100 scale across three pillars: capital growth, cashflow, and risk. 80+ is top quintile nationally; 90+ is top decile. We use it as the "is this even a quality suburb" filter — but it doesn't say anything about timing.When the report says "Beecroft is a solid suburb — RCS overall 73/100", that 73 is the composite score across all three pillars.

How strongly the suburb has grown historically and how favourably it scores on forward-growth indicators (cycle position, supply pipeline, demand momentum). High score = better long-run price appreciation outlook.

How well the suburb performs as an income asset — gross yield, vacancy tightness, rent growth. High score = better cashflow stack. Inverse correlation with capital growth is common (high-growth areas often have weak yields).

Volatility, environmental risk (flood, bushfire), economic diversity, and price stability. High score = fewer boom-bust swings. Useful for buyers prioritising stability over upside.

Buyer search activity in this suburb relative to listings volume. Under 3 = "under the radar, no crowd yet". Over 8 = "crowded — everyone's looking, expect premium pricing". We treat low HAPI in a strong suburb as a positive signal (room before the crowd arrives).

How variable past price growth has been. 0–3 = steady (often older established suburbs with consistent demand). 7–10 = boom/bust (mining towns, speculative pockets). Lower volatility = more defensible long-term hold.

Stated as a percentage. Doesn't account for vacancy, agent fees, maintenance, or interest costs. Useful as a relative comparison across suburbs but never as a real return number on its own.

HTAG's modelled median for the suburb at the same property type. This is the suburb-average number — NOT what your specific property is worth. We use it to sanity-check the address-level estimate (if the two diverge by more than 20%, we flag it).

How many properties of this type sold in the suburb in the last 12 months. Higher count = thicker market, more reliable valuation. Low count (under 30 per year) = thin market — pricing wobbles more, comp pool gets sparse.

Trough · Recovery · Mid · Late · Peak. We derive this from GRC bracket + direction tag rather than printing the raw 0–100 number on its own — the label is what most buyers actually want to know.

How much we trust the suburb-level data for this read. HIGH = ample sales volume + recent comps + full HTAG coverage. MEDIUM = some thinning. LOW = sparse sales or partial coverage — we shift to a directional read rather than a precise call.

Where the suburb sits in its current cycle on a 0–100 scale. <30 = early, recovery. 30–65 = mid, accelerating. 65–80 = late, decelerating. >80 = peak. Very hot suburbs occasionally overshoot 100 — we cap the display at 100 and tag "(extreme)".

HTAG's tag for where the rate of growth is heading. (+) Increasing = growth still accelerating. (+) Decreasing = positive but rolling over (late cycle). (−) Decreasing = correction. We use the direction tag more than the GRC number when calling cycle stage.

How recent price growth compares to the suburb's own long-term pattern, computed at 3-year, 5-year, and 10-year windows. Positive = running hot relative to history → ceiling risk. Negative = below long-term pattern → potential catch-up. We surface GPD-3, GPD-5, and GPD-10 because the windows often disagree.

Median days from listing to sale, this suburb, this property type. <20 days = urgent buyer side, sellers winning. 20–40 = normal. >60 = slow, buyer side has time. Worth comparing to 12-month rolling average — direction matters more than absolute.

How many months of sales the current listings stock would absorb at current sales velocity. <2 months = tight, sellers' market. 2–5 = balanced. >5 = oversupply. We combine inventory direction with DOM direction to read the bull-bear tide signal.

Active listings as a percentage of total dwelling stock in the suburb. Below 0.5% is unusually tight; above 2% is unusually loose. Tracks against the suburb's own long-term baseline.

9-metric scorecard validated for 1-year forward price growth — momentum status (PRESENT / ABSENT / WEAK), affordability, scoring, vacancy/DOM/inventory, popularity. Output 0–100 with a tier label (Strong / Mixed / Weak). Pairs with DDI: STGS handles momentum, DDI handles structural demand.

Directional regime detector using the within-suburb relationship between Days on Market and Inventory. Bull = DOM rising while Inventory falls (vendor patience). Bear = Inventory rising while DOM falls (seller flood). Historical edge: Bull +0.25pp forward growth, Bear −0.32pp. Wired but not active in current build.

SuburbIQ's hybrid 1–100 score combining affordability (Years to Own) and socio-economic profile (IRSAD) with price-tier-aware weights. Distinguishes "cheap because real buyers can afford it" from "cheap because the buyer pool is thin". 80+ = excellent depth, structural support. 30–60 = mid. <30 = hollow — the cheapness is the problem, not the opportunity.

ABS census composite of income, education, employment, and occupation. Decile 1–10 where higher = more advantaged. Predictive of buyer-pool depth: decile-9-10 suburbs have wealthier buyers who hold through downturns, decile-1-3 suburbs are more rate-sensitive.

Sister index to IRSAD but measuring disadvantage only (no advantage offset). Useful when comparing two suburbs that score similarly on IRSAD — the one with higher IRSD has less structural disadvantage even if advantage is similar.

SEIFA index focused purely on economic indicators (income, mortgage stress, employment). Decile 1–10. Useful for spotting cashflow-sensitive pockets where rate rises bite first.

SEIFA index focused on education levels and occupation prestige. Decile 1–10. Higher = better future income trajectory of residents → more durable long-term demand.

How many years of the median household income it would take to buy the median property in this suburb, ignoring interest, deposit, and tax. Above 30 years = affordability is stretched, real ceiling on near-term growth without income gains. Below 15 years = unusually affordable for the area.

Renters divided by owner-occupiers in the suburb. <0.30 = owner-occupier dominant (stable demand, less rate-sensitive). >0.60 = renter-heavy (more transient, demand swings with rental yields).

Units divided by detached houses in the suburb. <0.20 = house-dominant. >0.80 = unit-dominant. Different markets — comp pools should match the subject's category, not blend.

Median unit price divided by median house price in the same suburb. Below 0.40 means units are heavily discounted (often opportunity); above 0.70 means units are nearly house-priced (less discount available, watch out).

An estimate of what THIS specific property is worth based on third-party data — NOT a formal valuation. Hybrid: by default we use the size-adjusted comps median; when the comp pool is unreliable (lot mismatch, missing specs), we swap to HTAG's hedonic or hedge to "Insufficient evidence" so you don't get a misleading number.

Recent transactions used to triangulate the estimated value. We pull progressively wider (180 days / 1.5km → 540 days / 5km) until we have 5+ comps. Each one is size-adjusted to your subject's exact bed/bath/car/lot via HTAG's CMA structural-adjustment model.

Per-comp normalisation that asks: "what would this comp have sold for if it had the SAME beds, baths, car spaces, lot, and floor area as the subject?" Signed dollar adjustment for bed/bath/car deltas + multiplicative factor for land/floor area. The "size-adjusted" column on the comps page is post-adjustment.

HTAG's address-level hedonic — takes the property's last sale price and grows it by the suburb-wide price index since then. Strong when last sale is recent (under 5 years) and the property hasn't been altered. Brittle when last sale is >5 years old (anchor is stale) or the property has been renovated.

HTAG's modelled median for the suburb at the same property type. Used as a sanity check — if our address-level estimate is more than 20% away from suburb typical, we flag the estimate as unreliable. Used as the rough anchor when comps and IA-CMA both fail.

HIGH = 5+ comps with strong similarity. MEDIUM = 3–4 comps, or hybrid swapped to IA-CMA. LOW = 1–2 comps, poor pool match, or raw-comp-median fallback (subject specs missing). MISSING = no comps at all → refunds the report. LOW forces REVIEW verdict — we will never call BUY or WALK on shaky data.

The price above which recent comparable sales no longer support the asking price. Set ~1% above the estimated value. Treat as a data-driven boundary, not financial advice — your in-person inspection may justify going higher if the property's condition or features exceed what the data captures.

Suggested opening offer is median − 1 SD. Data anchor is the median. Late-cycle suburbs (GRC ≥75) get a −0.5% to −1.5% conservative shading on the upper bound. Final offer depends on factors only visible in person — this is the data-supported envelope, not an instruction.

Loan ÷ purchase price. A 20% deposit means 80% LVR. Above 80% LVR you'll typically pay Lenders Mortgage Insurance (LMI). Above 95% LVR is hard to source in most major lenders' core products.

Total loan ÷ gross annual household income. APRA recommends lenders cap at 6× without exception. Banks vary in how strictly they enforce — broker can advise on which lenders are flexible at higher DTIs.

A fully-amortising loan where each repayment covers both interest and principal. The standard 30-year structure for owner-occupied loans. Compare to Interest-Only (I/O) which doesn't reduce the principal during the I/O period.

Australian banking regulator requires lenders to qualify borrowers at the contracted rate +1.5pp. So if your contracted rate is 6.55%, you must service repayments at 8.05% to qualify. Used as the "qualify-for-refi" rate when we project your refinance headroom in the stress test.

The Reserve Bank's target overnight cash rate. Owner-occupied P&I rates run roughly +2.0–2.4pp above cash. We pull the current cash rate from HTAG live so the stress test reflects today's pricing, not last quarter's.

State-imposed transfer tax on the purchase price. Owner-occupier (PPOR) rates are generally lower than investor rates — and first-home-buyer concessions further reduce PPOR rates below certain thresholds. We compute stamp duty using the correct state's 2025–26 slabs (NSW, VIC, QLD, WA, SA, TAS, ACT, NT all supported).

P&I repayments + council rates + water rates + insurance + 0.5%/year maintenance. Excludes stamp duty (one-off, separate). For an investment property, subtract net rent to get the cash drag.

Higher = safer. Composite of historical flood events, modelled flood-prone area percentage, and proximity to waterways. >90 = insurance available at standard rates. <60 = expect insurance load or specific flood-zone exclusions.

Higher = safer. Composite of vegetation interface, fire weather frequency, and historical events. >90 = no BAL (Bushfire Attack Level) impact expected. <60 = BAL-rated construction may apply at the property level.

Address-level rating (BAL-LOW through BAL-FZ) that dictates construction standards for new builds and major renovations. Higher BAL = stricter construction = higher build costs. Confirm at property level via council planning portal.

How spread the suburb's employment base is across sectors. >60 = diversified, low single-sector shock risk. <40 = concentrated, vulnerable if the dominant sector contracts (mining towns, single-industry coastal pockets).

How heavily the suburb's economy leans on mining or agriculture. Higher MAD score = less single-sector dependence (counter-intuitively scored: 100 = minimal mining/ag, 0 = entirely mining/ag). >80 = safe from commodity cycles. <30 = boom/bust risk.

Percentage of dwellings within the address's micro-area that are public/social housing. Above 10% compresses local prices 5–15 points on RCS vs the broader suburb average. We surface this at address level — it's a block-level signal that suburb averages mask.

Property is on a heritage register (state or local). Alterations require heritage approval; external changes are often restricted; permits add 4–12 weeks. Confirm scope (interior vs exterior) with the council heritage office before purchase if you have any reno plans.

The named area you'd put on an envelope (Forrestfield, Fitzroy North, Ashfield). All our reports are anchored at this level. HTAG covers 15,000+ Australian suburbs.

The council area that governs planning, rates, and local services. Often (but not always) larger than a single suburb. Stamp duty, council rates, and planning overlays operate at LGA level.

ABS statistical area covering a whole metropolitan region (Greater Sydney, Greater Melbourne, etc.). Used for cross-metro comparisons and where the suburb's economic gravity sits.

ABS census aggregation level — typically 3,000–25,000 residents per SA2. Often used as a fallback when suburb-level data is too thin. Many demographics layers (income, occupation) only publish reliably at SA2 or above.

Hexagonal grid system used by HTAG for spatial layers (price heatmaps, flood risk overlays). Resolution 7 hexes are roughly 5 km²; resolution 8 around 0.7 km². Cleaner than suburbs for geographic gradients because hexes are uniform shape and size.