How we score eviction risk
A 1-to-10 landlord-risk percentile, built from nine sub-factors. Computed across every routable US city, with the underlying data and weighting documented in full below.
The 1-to-10 score
A national percentile rank of landlord-side eviction exposure. Lower is more landlord-friendly; higher is more tenant-protective.
Each city carries a primary landlord-risk score on a 1-to-10 scale. The score is a national percentile ranking where 1 represents the most landlord-friendly markets — fast eviction process, low rent burden, conservative court culture, low organizing strength — and 10 represents the most tenant-protective: slow eviction process, severe rent burden, strong tenant-defense infrastructure, active rent-control or just-cause regimes.
The score is computed as a weighted average of nine sub-factors plus a state-law multiplier. Sub-factors are themselves percentile ranks derived from ACS and political data; the state-law multiplier captures statutory differences that produce structural differences in operator-side experience.
The nine sub-factors
Each percentile-ranked nationally, then weighted into the composite. Tag colors group the inputs: political, economic, legal, organizing.
Local political climate
Derived from 2020 county presidential margin, weighted to the city's census tract distribution where available. Higher Democratic margin produces a higher score reflecting stronger structural support for tenant protections at the local level.
Regional political climate
The same 2020 presidential data computed at the surrounding multi-county metro level. Captures the broader political pressure environment that affects state legislative votes and regional court appointments.
State political climate
Statewide 2020 presidential margin and trifecta status (governor + both chambers same party). Single-party trifecta states produce predictable legislative dynamics; divided-government states produce stalemate that often locks in the status quo.
Economic stress
Composite of local poverty rate, unemployment rate, and median household income trajectory, all from ACS 2023 5-year estimates. Higher economic stress correlates with higher eviction filing rates.
Supply constraint
Derived from vacancy rate, building age distribution, and the ratio of renter-occupied to owner-occupied units. Tighter supply produces stronger rent growth, which translates into rent-burden pressure and elevated eviction filings.
Rent-control risk
Current rent-control coverage (city, county, and state ordinances) combined with the political-climate probability of new tenant-protective legislation in the next 12–24 months. Cities with active ballot campaigns or pending legislation score higher.
Eviction process difficulty
The procedural framework: state filing fee, predicate-notice period, time-to-trial, post-judgment writ delay, mandatory mediation, right-to-counsel availability. Faster and more landlord-favorable processes score lower; slower, more contested processes score higher.
Tenant organizing strength
The practical capacity of local tenant-defense networks. Cities with funded right-to-counsel programs, active legal-aid presence, and organized tenant unions score higher because contested-case rates are higher and procedural defects more frequently produce dismissals.
Housing court bias
The procedural orientation of the local court. Courts with specialized housing dockets, mediation referral practices, and judges with published opinions interpreting tenant-protection statutes strictly score higher. Courts running pure default-judgment dockets score lower.
Data sources
Everything is computed from publicly available primary sources. No proprietary scraping, no paid-API black boxes.
US Census Bureau. Rent burden, median gross rent, renter share, poverty rate, unemployment, building age, vacancy.
2020 county presidential election results, used for local, regional, and statewide political climate sub-factors.
California (codes.ca.gov), Texas (statutes.capitol.texas.gov), New York (nysenate.gov/legislation), and equivalent primary sources for every state.
State-level tenant-protection inventory used as a cross-reference against our primary statute reads.
Filing-rate data where available and verifiable against state administrative-office statistics.
Update cadence
Every individual page carries a visible last-updated timestamp on the prose block.
Known limitations
Three structural limitations consumers of this data should understand.
Judge-level variance. The eviction-process-difficulty sub-factor captures statutory framework cleanly but cannot fully capture variation in judge-level behavior within a single jurisdiction. Two judges in the same county can produce materially different timelines on the same fact pattern. We document court-level dynamics narratively in the prose where our research team has direct operator experience; the score itself cannot.
ACS lag. ACS 2023 5-year estimates lag actual market conditions by roughly 18 to 30 months. Post-pandemic rent-burden estimates reflect 2018–2022 income data against 2018–2022 rent data, which may understate the rent-burden severity in the fastest-growing markets where 2024 rents diverged sharply from 2022 baselines.
Not legal advice. The score is a market-research signal. Acquisition and operational decisions should incorporate jurisdiction-specific legal review by a licensed attorney admitted in the relevant state.
Reproducibility
The methodology is open. Underlying data is publicly available from the cited sources. Sub-factor weighting is documented above. If you need access to the raw scoring tables for academic or journalistic use, contact us at the address below.
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