Each of the nine dimensions is scored from 0 to 100. Every score starts with a short, plain-language summary of what it tells you; open “How it’s calculated” under any dimension for the full method, data sources, and formulas. Everything is built from public data and documented so the numbers can be checked.
What this tells you: how much damage the home is likely to suffer from floods, tornadoes, earthquakes, and fire in a typical year — and how much its construction (age, materials, and upgrades like a reinforced roof) lowers or raises that risk. A higher score means less expected damage.
The resilience score uses an Expected Annual Loss (EAL) framework — the standard approach used by FEMA's National Risk Index, Hazus, and the insurance catastrophe-modeling industry.
Disaster Resilience covers four perils — flood, tornado, earthquake, and fire. (It does not measure general wear-out or longevity; that is the separate Durability dimension.)
Flood: FEMA NFHL zone codes map to annual exceedance probabilities. Zone AE = 1% annual chance × 28% damage ratio = 0.28% EAL rate. Zone X (minimal) = 0.04% × 5% = 0.002% EAL rate.
Tornado: SPC historical tornado data (1950–2023) provides frequency near the address. Point-strike probability = tornado path width ÷ 25-mile circle area. EF-based damage ratios: EF0=2%, EF1=10%, EF2=30%, EF3=60%, EF4=90%.
Seismic: the USGS National Seismic Hazard Model supplies the local peak ground acceleration (PGA) for any U.S. address, run through simplified fragility curves. High-seismic regions (the West Coast, and the New Madrid zone in the Mid-South) get proportionally higher seismic loss than the low-hazard interior.
Fire: two contributions summed as one EAL rate. A structural/electrical base rate (≈0.02%/yr, from NFPA home-fire loss data) plus the location's wildfire EAL rate from the FEMA National Risk Index (WFIR_AFREQ × WFIR_HLRB), resolved at the census tract (county/national fallback) from a bundled national crosswalk. Both are scaled by a fire-specific modifier: wiring era (pre-1950 knob-and-tube = 1.5×, NEC 2002+ AFCI = 0.85×), construction combustibility (wood frame = 1.10×, masonry/concrete = 0.80×), and condition (same factor as the other perils). Residential sprinklers cut the peril ~60% (0.40×) in the simulator. The wildfire term makes fire genuinely location-aware — near-zero across much of the country, but the dominant peril in the fire-prone West (e.g. Los Angeles County, “Very High”).
Raw EAL is adjusted by a construction-quality multiplier based on four factors:
Code era (year built): Pre-1940 = 1.6× (balloon framing, no engineered connections), Pre-1970 = 1.3×, 2003+ post-IBC = 0.85×
Construction type: Wood frame = 1.2×, ICF = 0.25× PCA racking data FEMA MAT Joplin/Moore
Foundation (flood only): Full basement = 1.4×, Slab = 0.7×
Condition: Unsound = 1.5×, Excellent = 0.8×
There is no upper cap on the BRM, so old, poorly-built, and poor-condition stock can compound well above the code-current baseline (a pre-1940 unsound frame house can exceed 2.5×). Construction-type-specific floors still prevent over-crediting: wood frame floor = 0.50, ICF floor = 0.15 (85% max EAL reduction).
When a building is a multi-unit building — detected by the National Structure Inventory, or declared by entering its unit count together with its material and height (useful when detection misses a garden-apartment complex NSI models as single-family structures) — two things change. First, the building's actual structural material — reinforced concrete or steel for a mid-rise, load-bearing masonry otherwise — drives the construction factor instead of the (often defaulted) single-family type, because a concrete or steel frame is far more wind-, seismic-, and fire-resistant than wood. Second, flood exposure becomes floor-aware: flood damage concentrates on the lowest floors (FEMA P-259 depth-damage), so a representative unit averaged over the building's height carries roughly 1/stories of the ground-floor exposure, floored at 0.15 (lobbies, parking, and mechanicals never reach zero). A wood-framed multi-family keeps the single-family factors. FEMA Hazus building types FEMA P-259
20+ toggleable features with literature-backed multipliers:
Wind: Hurricane straps (0.70), hip roof (0.55), impact garage door (0.75), sealed roof deck (0.80), metal roof (0.75) IBHS research
FORTIFIED: Roof tier (0.35), Silver (0.25), Gold (0.20) 73–76% claim reduction, Hurricane Sally actuarial data
Seismic: Cripple wall bracing (0.45), seismic retrofit (0.75) PEER-CEA research
Flood: Elevation +1ft above BFE (0.15), +2ft (0.08), +3ft (0.04) FEMA depth-damage curves
Total EAL rate maps to 0–100 via log-linear interpolation: score 100 at EAL ≤ 0.001%, score 80 at 0.02%, score 60 at 0.1%, score 40 at 0.3%, score 20 at 1%, score 0 at ≥ 2%.
What this tells you: roughly how much energy the home uses and what that costs each month at local utility rates — driven by its age, size, construction, and heating/cooling system. A higher score means it uses less energy.
Score based on Energy Use Intensity (EUI) in kBTU/sqft/yr, using DOE Building America and EIA RECS 2020 benchmarks, adjusted for the property's IECC climate zone (looked up nationally by county; e.g. 4A mixed-humid, 5B cool-dry).
Each home maps to an archetype via year built (vintage bin), square footage (size bin), construction type, and heating/cooling system from the property record.
Published EUI benchmarks by vintage (for a mixed-humid baseline, then scaled by the local climate zone): Pre-1950 = 75 kBTU/sqft/yr, 1950–1979 = 55, 1980–1999 = 40, 2000–2009 = 30, 2010+ = 25, Passive House = 12.
Construction modifiers applied to the energy-use estimate: ICF = 0.92× and SIP = 0.95× (tighter, higher-mass envelopes), and Passive House = 0.55×. For a home in a multi-unit building, a shared-wall credit lowers the estimate — a unit attached to or stacked with others exposes far less exterior surface, so it loses less heat: roughly 10% for a duplex up to ~27% for a large (20+ unit) building, tracking EIA RECS (apartments use ~30% less energy than detached homes of similar size). The building's unit count comes from the detected structure (or the units you enter). Rooftop solar is credited to the Environmental footprint's operational-carbon leg, not to the energy-use score.
Monthly cost uses the property's state residential utility rates (EIA averages for electricity and natural gas), so the estimate reflects local prices — roughly $0.10/kWh in the lowest-cost states to $0.20–$0.30/kWh in the highest. The electricity/gas split follows the home's heating-system type.
What this tells you: how much useful life the home's major systems — structure, roof, HVAC, plumbing, and so on — have left, adjusted for the home's observed condition. A higher score means more life left before big repairs.
A component-lifespan / effective-age model — how much usable service life the building has left, tempered by the assessor's observed condition. (Distinct from Disaster Resilience, which measures hazard loss rather than wear-out.)
Eight major systems each carry a typical service life and a replacement-cost weight; the long-lived shell dominates and short-cycle systems contribute less:
Structural shell 100 yr (0.30) · plumbing 55 yr (0.10) · electrical 35 yr (0.10) · roof covering 25 yr (0.15) · windows 25 yr (0.08) · interior finishes 20 yr (0.10) · HVAC 18 yr (0.12) · water heater 12 yr (0.05).
Each system's remaining-life fraction is clamp((service_life − effective_age) / service_life, 0..1), using the assessor's effective year built (which folds in major renovations) rather than the original year. The age score is the weighted mean × 100.
Condition comes from the assessor's condition rating (Excellent = 100, Average = 60, Unsound = 0) and is weighted slightly above pure age because an inspector's observation captures real-world maintenance. The base is then scaled by exterior-wall material and by construction grade (clamped to 0.90–1.12×).
Homes with neither a build year nor a condition rating — vacant / non-residential land — are left unscored and excluded from the composite rather than guessed.
For a multi-unit building (detected by the National Structure Inventory, or entered with its material), the structural shell is a shared, building-level element rather than one house's wood frame. A reinforced-concrete or steel mid-rise frame — or a load-bearing masonry shell — is a fundamentally longer-lived building element, so the representative unit's shell decays more slowly: its service life is lengthened to 110–120 yr (concrete/steel 120, masonry 110) from the 100 yr wood-frame baseline. Only the shared shell changes; the shorter-cycle unit-level systems (roof covering, interior finishes, in-unit HVAC and water heater) keep their per-unit schedules, and a wood-framed multi-family keeps the baseline. ISO 15686 / CIRIA design service lives InterNACHI / Fannie Mae structural schedules
What this tells you: the home's yearly climate impact — from the energy it uses day to day, the carbon built into its materials, and its water use. A higher score means a smaller footprint.
A life-cycle CO₂e score blending three components — 0.50 operational + 0.30 embodied + 0.20 water — each normalized 0–100 against published good-vs-poor benchmarks (log-linear; higher score = lower footprint).
The grid factor is the property's EPA eGRID2022 subregion emission rate (looked up nationally by county, with a US-average fallback), so a home on a coal-heavy grid carries more operational carbon than one on a clean grid. Energy use is the same model the Energy dimension produces; the gas factor is from the EPA GHG Emission Factors Hub.
Embodied: a material/size estimator keyed on exterior wall and construction grade, calibrated to the verified US single-family band of ~39–121 kg CO₂e/m², then amortized over the shell's expected service life (EN 15978 / RICS 60-year reference study period) — so more durable construction spreads its upfront carbon over more years.
Water: EPA WaterSense usage benchmarks, with a national-average estimate for the energy embedded in water supply and wastewater treatment. Indoor use scales with occupancy and fixtures; outdoor use is modeled from the irrigable lot area (lot minus building footprint).
Multi-unit buildings: a unit in a stacked or attached multi-unit building (detected from the National Structure Inventory, or from a unit count you enter) carries no private-yard irrigation — any shared landscaping is common area, not the unit's own load — so its water footprint is indoor-only, which is why an apartment or condo unit scores greener on water than a detached home of the same size.
Homes with no living area (vacant / non-residential) are left unscored.
What this tells you: whether the home pays its own way for the city services it needs — roads, water, sewer, fire, and police. Denser housing shares those costs across more homes, so it scores better. A higher score means more of its cost is covered by the taxes it generates.
Models the annual municipal cost to serve each parcel using a density-based cost allocation approach, inspired by the Halifax cost-of-sprawl study, Strong Towns fiscal analysis, and municipal density-budget research.
The shared, linear-network services (roads, water/sewer) fall with density (dwelling units per acre) along a continuous log-log cost curve — the published band costs placed at each band's geometric-mean density and extended past 12 DU/acre, so per-household cost keeps amortizing as the same frontage and mains are shared across more homes (rather than flooring at a triplex). Per-household services (trash, parks) stay flat; fire and police scale by a distance/density modifier:
Roads: ~$2,400/yr at <1 DU/ac → ~$700 at 8 → ~$400 at 12 → ~$150 at 48 DU/ac
Water/sewer: ~$1,500/yr at <1 DU/ac → ~$500 at 8 → ~$350 at 12 → ~$135 at 48 DU/ac
Fire/EMS: ~$800 base × distance modifier
Police: ~$1,200 base × density modifier (most efficient at 16+ DU/ac)
Sanitation: ~$500/unit (a representative municipal fee)
Parks: $300/unit
These per-household figures set the cost-to-serve shape (how cost falls with density). The cost level is then scaled to each county's actual local-government spending using the U.S. Census of Governments — per-capita direct expenditure by function (roads, water/sewer, fire, police, sanitation, parks). So a county that spends 2× the reference per-capita rate on roads gets 2× the road cost. Los Angeles County, for example, runs ~2.0× on roads and ~2.6× on water/sewer (2022 census). Counties not in the crosswalk fall back to the national average.
A ratio > 1.0 = net contributor to the city. Both sides are localized per county and put on a like-for-like non-school basis. The cost side is the Census of Governments municipal spending (schools excluded). The revenue side starts from each county's effective property-tax rate (median real-estate taxes ÷ median home value, U.S. Census ACS), then nets out the school-district share of property tax (~41% nationally) so it matches the school-excluded cost side — and where a county funds schools through its general government (a “dependent” system with no separate district), the national-average share is used instead. The home value defaults to the county median when you don't enter one, so the revenue estimate reflects the local market. These remain county-level estimates (a county median, not a parcel's actual millage or value).
These breakpoints are anchored to the national distribution of fiscal ratios — a population-weighted reference over U.S. counties × residential-density archetypes — so the score tracks national percentile rank (A = top ~20%, B = 60–80th, C = 40–60th, D = 20–40th, F = bottom ~20%). On the non-school basis the national median fiscal ratio is ~0.31 (the typical U.S. home covers only about a third of its non-school municipal cost from non-school property tax), so a typical home scores around 50 (C).
Because the cost model is density-driven, the same lot scores very differently as a single-family home, a duplex, a triplex, or a quadplex. The density comparison holds the location and lot fixed and varies the number of dwelling units, keeping the per-unit value constant (so total value scales with units). As units increase, the same land and services are shared across more homes, so per-unit cost-to-serve falls and the fiscal ratio — and Infrastructure Burden grade — improve. That gap is the density dividend.
The per-unit fiscal ratio understates the case for infill, though, because the headline gain is on the revenue side. So the comparison also reports value per acre: on a fixed lot at constant per-unit value, a quadplex generates roughly 4× the property-tax revenue per acre on the same road frontage and water main — the lens that makes small-scale infill's productivity visible even when each individual unit still doesn't fully cover its cost. Try it with the “What if this parcel were denser?” button under the address search on the home and examples pages.
When a building is a multi-unit building (detected by the National Structure Inventory, or from a unit count you enter), the number of units drives the density calculation, so the building's shared land and services are amortized across its actual units rather than scored as a single detached home on the lot. The value side is also building-aware: instead of the single-family owner-occupied median (wrong for a rental building or condo), the per-unit value is an income-based “value-per-door” estimate — the way apartments are actually valued — from local rent: value_per_door = annual rent × occupancy × (1 − operating expense ratio) / cap rate. Rent is the county median gross rent (ACS B25064); occupancy (0.93), operating-expense ratio (0.40), and cap rate (~5.5%) are national constants. This is a neighborhood-average estimate, not an appraisal, so the fiscal and dollar figures remain approximate for a specific apartment or condo. ACS B25064 rent CBRE / Statista cap rate Census HVS occupancy
What this tells you: how healthy the surrounding neighborhood is, based on local rates of conditions like obesity, diabetes, high blood pressure, and asthma. A higher score means a healthier area. (This describes the neighborhood, not the building.)
Uses CDC PLACES census-tract-level health estimates. Seven measures: obesity, diabetes, high blood pressure, asthma, coronary heart disease, mental distress, and physical inactivity.
Each address is assigned to its census tract, and the health index is the average of the seven measures' inverted percentile ranks against the full national distribution of US census tracts (population-weighted) — lower prevalence = higher score. Because it is a national percentile rather than a within-county rank, a score means the same thing in every metro, so neighborhoods are comparable across cities. The reference distribution is bundled and versioned (CDC PLACES 2023).
What this tells you: the economic profile of the neighborhood — income, poverty, education, and jobs. A higher score means stronger local economic opportunity. (Like Health, this describes the area, not the building.)
Census ACS 5-year estimates at the census tract level: poverty rate, median household income, and housing-cost burden. Scored against the full national distribution of US census tracts (household-weighted) — higher income, lower poverty and cost burden = higher score — so a score is comparable across locations rather than ranked within the address's own county. Sourced from the keyless ACS 5-year Summary File (2023), so the live scoring path needs no Census API key.
What this tells you: how easy it is to get around from this address on foot, by transit, or by bike. A higher score means more of daily life is reachable without a car.
Uses the EPA National Walkability Index (NWI) — a public-domain national index covering every US census block group, built from three built-environment measures: street-intersection density, proximity to transit, and diversity of land use. Its 1–20 index is scaled to 0–100 (higher = more walkable) and aggregated from block groups to the census tract (household-weighted).
Because the NWI is a national index (0 = car-dependent, 100 = highly walkable), the national grade is directly comparable across cities, and no per-address API call is made — the value is a bundled, storable lookup. This replaces the Walk Score API, whose Terms of Use prohibit storing scores and whose free tier caps at ~5,000 calls/day; an optional Walk Score enrichment (0.60 × Walk + 0.25 × Transit + 0.15 × Bike) is still honoured when one has been supplied.
What this tells you: how the local climate is projected to change by mid-century — more extreme heat, heavier rain and flooding, and drought. A higher score means less projected climate hazard. The label shows a range, because how much it changes depends on future emissions.
Sub-county downscaled climate-hazard projections from the USGS CMIP6-LOCA2 threshold/extreme-event metrics — the Weighted Multi-Model Mean (an ensemble mean over CMIP6 LOCA2-downscaled models, ~6 km), sampled at each census tract's internal point (county = the mean of its tracts). Three hazard legs are blended equally into a 0–100 score (higher = less projected hazard): extreme heat (annual days > 95°F and > 100°F), heavy precipitation & flood (days > 1″ and the annual max 5-day total), and drought (max consecutive dry days). Each metric is scored against national breakpoints anchored to the SSP2-4.5 mid-century distribution. The dimension is reported as a low/high band from SSP2-4.5 → SSP5-8.5 (a lower- vs higher-emissions future) at mid-century (2040–2069), with the SSP2-4.5 value as the headline.
Every dimension gets two grades. The national grade says how the home compares to the whole country. The local grade says how it compares to its own neighbors — useful when you're choosing between homes in the same area.
National absolute grade: A ≥ 80, B ≥ 60, C ≥ 40, D ≥ 20, F < 20. Calibrated for national comparison — a Grade B means the same thing anywhere in the country.
Local percentile grade: A = top 10%, B = next 25% (65th–90th percentile), C = next 30% (35th–65th), D = next 25% (10th–35th), F = bottom 10%, ranked against nearby properties.
Composite score: the average of the dimensions that could be scored. Dimensions with no data (for example, a location dimension whose census tract can't be resolved) are left out rather than counted as zero, so a strong home isn't dragged down by a missing input.