Methodology

Built on data, not opinion.

Every score is a national percentile. Every signal has a published definition. Every location carries a confidence tier. When data is sparse, we tell you — we never hide it behind an inflated score.

You rank the signals

The Combined Signal Score

Each location receives a single Combined Signal Score between 0 and 100. A score of 87 means that location is in the top 13% nationally, on the signals you ranked, in the most recent month. Higher means tighter supply and stronger rental demand as you have defined it.

The score is calculated by re-normalized exponential decay across the signals you ranked. Your top-ranked signal carries the most weight; each subsequent rank carries 60% of the rank above it. Signals you toggle off contribute zero. The remaining weights are renormalized to sum to 1.0 — so the score is always comparable across users with different rankings, even though each person's ranking is their own.

weight(rank n) = 0.6^(n - 1)
base     = Σ ( normalized_signal × weight ) / Σ present weights
coverage = Σ present weights / Σ available weights
score    = base × √coverage × 100

Two refinements keep that number honest. Coverage weighting:the score is multiplied by the square root of the location's coverage — the share of your ranked signal weight it actually has data for. A location missing your top-ranked signal is dampened accordingly, so complete markets out-rank sparse ones and a thin-data ZIP can never top the list on two lucky signals. Per-month signal universe:a signal only counts toward coverage in months where it existed at all — a signal launched mid-series (like Days on Market, first data June 2026) is excluded from earlier months' denominators, so historical scores stay directly comparable to current ones. Locations must also carry data for at least two ranked signals, including at least one market (non-Census) signal, to appear in results at all.

Each signal is converted to a 0–100 percentile using all valid US locations in the current month. That means every score is grounded in a national context — not a local one. A 90 in Spokane and a 90 in Austin are directly comparable.

What we measure

The 12 leading signals

The signals were chosen because they lead price, not lag it. They reflect the buying, listing, and renting decisions that move markets — captured at the location level for every US location with sufficient data.

What to buy, not just where

Property Standouts

The Combined Signal Score tells you where demand is strongest. Property Standouts goes one level deeper — what to look at within a location. When you expand any ZIP, alongside its Trend card you'll see the standout asset type:

An "asset type" is a property type × bedroom count segment — for example, a 3-bedroom single-family home, or a 1-bedroom condo. The card shows that segment's median price, typical rent, dwelling size, typical age, lot size, Days on Market (cumulative list-to-contract), Days to Close (list-to-close), sale-to-list ratio, price-cut rate, and its headline appreciation.

How the figures are derived:

• Source: medians pooled from roughly the last 18 months of recorded home sales in each location.
• Appreciation: the annualized growth between the two most recent sale prices of the same property (a repeat-sales method, the principle behind the Case-Shiller index), taken as a median across qualifying homes — so it reflects real buyer-to-buyer price changes, not a model estimate.
• Minimum-sample gating: a segment must have enough recent sales to qualify, and appreciation requires enough repeat-sale pairs. A thin, lucky cell can never win — if the data is too sparse, the cards simply do not appear for that ZIP.
• Coverage honesty: Property Standouts are shown only where the sales record supports them. They are naturally absent in non-disclosure states and very thin rural markets — we would rather show nothing than something unreliable.

Property Standouts describe past, recorded sales for information only. They are not a recommendation to buy or sell any property, and not investment advice — see the note at the bottom of this page.

Data quality

Confidence tiers

Each location carries a confidence tier reflecting two things: how much underlying data sits behind its score, and how stableits signals are month to month. A location with full data coverage but signals that swing wildly between months (for example, days-on-market jumping from 30 to 105) is downgraded — volatile inputs make a single month's score less dependable, and we would rather say so than present false certainty. Locations with too little signal coverage are excluded entirely — we will not invent a score where one cannot be supported.

By default the app shows Very High and High tiers only. You can expand the filter to include Medium or Low — but we recommend treating those scores with corresponding caution.

Where the data comes from

Our data principles

Raw data is aggregated from a mix of free public sources and paid commercial feeds, then transformed into the leading indicators above. We do not rely on a single source for any signal — every metric is cross-checked or derived from at least two independent inputs where possible.

• Transparency: The full formula above is the entire formula. There are no hidden adjustments, no editorial overrides, no "trust us" layers.
• Coverage honesty: Locations with insufficient data are excluded from results. Their absence is reported in the footer along with the eligible count.
• Comparability: Every signal is normalized against the full US universe of locations in the current month. Local rankings are derivative of national context, not independent of it.
• Reproducibility: Given the same inputs, the same ranking produces the same scores every time. No randomness, no machine-learning black boxes.

Cadence

Updates and history

Scores update monthly. When you expand a location, its trajectory — a sparkline of the Combined Signal Score across recent months plus a sentence explaining the largest drivers of month-over-month change — is computed under your current ranking: prior months re-score live as you re-rank signals, so every point in the series is apples-to-apples with today. The number of historical months available may grow over time.

If a core signal was missing in the previous month for more than 95% of locations, the month-over-month delta is suppressed to avoid a misleading comparison. Newly launched signals are handled separately: they are excluded from months before their launch (see the coverage rule above), so adding a signal never suppresses deltas or distorts historical scores.

Important

Abunsh is a data and analytics tool. The Combined Signal Score is a ranking, not a recommendation. Past performance is not indicative of future results. Abunsh does not provide investment, legal, tax, or financial advice. Always do your own due diligence and consult appropriate licensed advisors before making real-estate investment decisions.