Data & Methodology

Everything on this site is computed from public government records and licensed industry data. Rather than one feed, each page blends several kinds of input, each used for what it is best at:

Listing-market data (June 2026) — metro-, county- and ZIP-level asking-side figures: median listing price, price per square foot, days on market, active and new listings, and the share of listings with price reductions. Refreshed monthly. Listing prices describe what sellers ask.

Closed-sales data — median sale price, its year-over-year change and the average sale-to-list ratio. Closed-sale figures describe what buyers actually paid, so the two views are labeled separately wherever both appear.

A long-run house price index — a quarterly, all-transactions price index published for roughly 400 large metros. From it we compute each metro's 1-, 5- and 10-year appreciation and how far its latest level sits above or below the metro's own 2000–2019 log-linear trend. Smaller markets ship without these fields.

Published fair market rents — the government's 2-bedroom fair market rent for each metro area (county rows population-weighted within a metro). From it we derive gross rental yield = 2BR rent × 12 ÷ median listing price — a gross cap-rate proxy, before taxes, insurance, vacancy and management.

Mortgage rates — the national weekly average 30-year fixed rate, shown as context and used to prefill payment scenarios.

Growth and risk statistics — public federal records aggregated to each metro: housing units permitted in the latest full year (the 1–3 year supply pipeline, also shown per 1,000 residents); net migration from tax-return records (inflow minus outflow summed across the metro's counties, so intra-metro moves cancel — filers only, so students and some retirees are undercounted); total-nonfarm employment and its year-over-year change (published for roughly 390 of our markets); and a county-level natural-hazard risk index, population-weighted per metro, with the top expected-loss hazard named. The hazard index is a relative, national-percentile measure — larger metros skew higher because more value is exposed.

Demographics — median household income, population, median gross rent and rental vacancy from the latest 5-year government survey, used for price-to-income and deal-analyzer defaults.

Where a source doesn't cover a metro we ship without that field and mark it n/a rather than estimate it. Every page shows its data-as-of date.

Every score is a percentile rank (0–100) across all covered U.S. metros — 50 means the metro is at the median of the country, not that it earned '50%' on some test. Scores are data-derived opinions for research and are not investment advice. The five subscores:

Momentum — the mean of six percentile ranks: listing-price change year-over-year (+), month-over-month (+), days-on-market change YoY (−, faster = stronger), active-inventory change YoY (−), price-reduced share of listings (−), and total-nonfarm employment change YoY (+). Where no metro employment series is published (about 550 of 949 markets) momentum stays the five-part mean.

Value — the percentile rank of minus the house-price-index deviation from the metro's own 2000–2019 log-linear trend: metros priced furthest below their own long-run trend score highest. Where income data is available, price-to-income joins this subscore as an equal-weight component.

Rental yield — the percentile rank of gross yield (published 2-bedroom fair market rent × 12 ÷ median listing price).

Supply risk — the percentile rank of active inventory versus the same month of 2019, the last normal pre-pandemic year. A high score means inventory has rebuilt far past pre-pandemic levels — more supply risk.

Market heat — the mean of three percentile ranks: average sale-to-list ratio (+), median days on market (−), and the pending-to-active ratio (+).

Composite Investor Score = weighted mean of the available subscores — momentum 25%, value 20%, yield 20%, supply stability (100 − supply risk) 20%, heat 15% — with weights renormalized when a subscore's source doesn't cover the metro; a composite requires at least three subscores.

Price volatility — for index-covered metros, the standard deviation of quarterly year-over-year house-price-index changes over the last 20 years (minimum 40 observations), labeled Low / Medium / High by terciles. It describes historical swing size and is display-only — it is not part of the Investor Score.

Market news — headlines on curated metro pages come from public news feeds and link to the original publisher. The one-line takeaway under them is AI-generated from those headlines only, is labeled as such, and should be checked against the linked coverage.

The investor dashboards re-rank the same metro dataset through different lenses; no dashboard introduces new data beyond the inputs above.

Cash flow — rent-covered metros ranked by gross yield (2BR fair market rent × 12 ÷ median listing price), filtered to a median list price of at least $100,000, at least 100 active listings and a yield of at least 4% to exclude thin or distressed samples. A gross screening ratio, not a pro-forma.

Undervalued / overvalued — for metros with both a long-run price index and income data, the mean of two percentile ranks: deviation from the metro's own 2000–2019 log-linear trend (further below = higher) and price-to-income (lower = higher). The 20 highest and 20 lowest blends are shown, with the formula printed on the page.

Momentum — risers are the mean of three percentile ranks (listing-price YoY +, pending-to-active +, days-on-market YoY −); coolers the mean of two (active-inventory YoY +, price-reduced share +). Metros with fewer than 100 active listings are excluded.

Supply risk — active inventory as a percentage of the same month in 2019, extremes on both ends (minimum 100 active listings).

Appreciation — house-price-index change over 1, 5 and 10 years; leaders, laggards and 10-year compounders.

Screener — an interactive table of every scored metro (median price, YoY, days on market, gross yield, price-to-income, Investor Score, volatility). The data is embedded in the page and all filtering runs in the browser; no tracking, no external requests.

Compare — the metro comparison tool puts any two scored metros side by side from the same embedded dataset, highlights the stronger reading per row, and summarizes the differences in plain English. Fully client-side.

ZIP drill-down — curated metro pages link to a ZIP-level table: every ZIP matched to the metro by place name with at least 10 active listings, ranked by median listing price. Small ZIP samples are volatile month to month.

Monthly movers — the movers page re-ranks metros (≥100 active listings) on raw month-over-month and year-over-year listing-price change and inventory change. MoM medians in small metros are noisy; the page says so.

Annual rankings — the 'Best markets of 2026' pages are point-in-time editorial cuts of the same dataset: cash flow ranks by gross yield with the cash-flow dashboard's guardrails; appreciation ranks by 5-year index change; the first-rental list requires a median price below the national metro median and blends three equal percentiles (gross yield, lower price, supply stability). Each formula is printed on its page.

Deal analyzer — the rental deal analyzer prefills each metro's median listing price, market rent (2-bedroom fair market rent, else median gross rent), effective property-tax rate (median real-estate taxes paid ÷ median home value), rental vacancy rate and the current national mortgage rate. Insurance (0.5%/yr), maintenance (1%/yr), management (8% of rent) and closing costs (3%) are labeled editable assumptions, not local data. All math runs in the browser; outputs are models, not advice or quotes.

Rate scenarios — metro pages and the deal analyzer show the principal-and-interest payment on the median-priced home (20% down, 30-year fixed) at the current national rate and one point either side. Taxes, insurance and HOA are excluded and the payment is a build-time computation, not a lender quote.

The market map — /map paints the same dataset across public cartographic boundary files (metro, county and ZIP, generalized for display, not legal use). Metro view carries all 19 metrics; the county and ZIP views recolor by listing price, YoY change, days on market, $/sqft and (county) price-cut share, loading ZIP boundaries one state at a time. Colors are quantile bins recomputed per metric across the areas that have it; clicking opens the matching market page where one exists. County and ZIP medians come from small samples and are volatile month to month. Basemap © OpenStreetMap contributors © CARTO.

Every dashboard states its thresholds in a data note, and every ranking is a data-derived opinion — not investment advice.

Scored metro pages and the comparison tool show a 12-month listing-price outlook. It is a deliberately simple, fully transparent linear blend of three of our percentile subscores — published here in full so there is no black box:

Each subscore (0–100) is first centered: z = (subscore − 50) / 50, giving a value between −1 and +1. Supply risk is inverted (z = (50 − supply_risk) / 50) because rebuilt inventory weighs on prices.

outlook = clamp(10 × (0.5 × momentum_z + 0.3 × inverted_supply_z + 0.2 × value_z), −10%, +10%) — weights renormalized when a subscore is unavailable for a metro. Labels: Rising at +2% or above, Cooling at −2% or below, otherwise Flat.

This is a heuristic model output for research context — it is not a prediction service and not investment advice. It has no error bars, no macro inputs beyond those described above, and no track record; treat it as a compact restatement of the momentum, supply and value data on the page.

Agent directories — public agent profiles collected in July 2026: recent and career sales counts, price ranges and client ratings. Sales counts can include full-team production; directories are informational, not endorsements.

Licensing requirements — compiled from each state real-estate commission's public requirements, with the regulating authority linked on every page. As an ongoing verification program, pre-license hour figures for 25 of 51 jurisdictions — Arkansas, California, Colorado, Connecticut, Delaware, the District of Columbia, Georgia, Hawaii, Iowa, Louisiana, Massachusetts, Minnesota, Mississippi, Missouri, Montana, New Jersey, New York, North Carolina, North Dakota, Oklahoma, Pennsylvania, Utah, Virginia, Washington and West Virginia — are confirmed against those primary sources to date, with the remaining states in progress.

Salaries — official U.S. government occupational wage statistics for real estate sales agents: state annual median and 90th-percentile wages from the May 2025 estimates, rounded to the nearest $1,000. The statistics are suppressed for Iowa, Massachusetts and Vermont, where we show clearly-labeled estimates instead.

What is illustrative — the two sample market reports, calculator defaults and national directory rankings are demonstrations and labeled as such on-page.

Verify any figure with a local agent, MLS or the relevant authority before relying on it. Data errors? Tell us via the contact page.

Portions of market data courtesy of Realtor.com and Redfin; additional statistics from U.S. government sources.