Trust & Authority
Trust & Authority Center
How we produce every study, score, and recommendation on the platform — and what we don’t do.
Editorial Standards
Every article, study and dashboard is written by investor-operators and reviewed against a four-step editorial checklist before publication: source verification, math verification, plain-language clarity, and disclosure review.
- No undisclosed sponsored content.
- Affiliate relationships are labeled inline.
- Forward-looking statements are flagged as such.
- We do not sell leads to lenders, agents, or property managers.
Research Standards
Studies follow a documented protocol covering data scope, normalization, weighting, sensitivity testing, and reproducibility. Every study is timestamped and versioned so prior conclusions can be audited.
- Inputs are normalized to 0–100 before any composite score.
- Weights are published with each study.
- Sensitivity tables disclose how rankings shift under alternative weights.
- Prior versions remain accessible via the Research Library.
Methodology Center
All scoring engines on the platform are documented end-to-end. Operators can reproduce every score using the published inputs and weights.
- Each engine has a dedicated methodology page.
- Component scores are exportable to Premium Reports for audit.
- Formula version numbers are tracked across updates.
Data Sources
Inputs combine public-domain federal datasets (Census, BLS), state-level tax and insurance disclosures, and platform-derived signals from our own calculator usage. We never use scraped credit-bureau or tenant data.
- Census ACS for population and migration.
- BLS for employment and wage growth.
- State DOR / DOI for property tax and insurance.
- MSA-level multiple-listing data, aggregated and de-identified.
Transparency
We disclose our scoring boundaries, what we don’t model, and which calculations depend on user inputs vs. platform defaults.
- Tax effects of depreciation are not modeled in base calculators.
- Refinance opportunities mid-hold are not modeled in the base BRRRR engine.
- Capex events beyond reserves are user-supplied.
- See the disclaimer for limitations.
Citation Standards
When referencing external research, we link to primary sources and avoid summary aggregators. Internal cross-references link to the underlying methodology page rather than restate it.
- Primary sources only.
- Internal links point to the canonical methodology, not duplicates.
- Publication dates are disclosed on every study.
Methodology Library
Every scoring engine on the platform, documented.
Institutional Score Methodology
The Institutional Score (0–100) compresses seven portfolio dimensions into a single, comparable grade. It is calibrated to mirror how institutional investment committees evaluate a portfolio.
Market Cycle Methodology
Our Market Cycle Analyzer assigns every MSA to one of four phases — Expansion, Peak, Contraction, Recovery — using a composite of price growth, rent growth, inventory, population, employment, and migration indicators.
Portfolio Benchmarking Methodology
The Portfolio Benchmark Engine compares your portfolio against four archetypes — Conservative, Income, Growth, Diversified — across cash flow, LTV, property count, and market count.
Capital Allocation Methodology
Capital Allocation scores efficiency on a 0–100 scale by comparing market yield to your target cap rate and assessing portfolio LTV, reserves, and risk tolerance.
Risk-Adjusted Return Methodology
The Risk-Adjusted Return Engine adapts Sharpe-style logic to residential real estate: returns are scored relative to deal-level risk (volatility, vacancy, leverage).