One number for how hot a deal is
The HOT Score is a 0–100 rating that summarizes how strong an investment property is at a glance. It blends four factors so you can compare very different listings on the same scale — now powered by live AVM data and explained for you in plain English.
Yield
Net cap rate from rent vs price, net of ~50% operating expenses (the 50% rule). Higher cash flow scores higher, with diminishing returns — no hard ceiling.
Equity upside
Net profit after repairs (ARV − price − repairs) as a share of ARV. Meeting the 70% rule (~30% margin) scores high; underwater deals score low.
Freshness
Days on market — a minor liquidity signal. Fresh listings score a little higher; it decays smoothly and never hits zero.
Condition
Property age as a proxy for capital-expense risk. Newer carries less near-term risk; older but renovatable stock keeps a floor.
Color tiers
How it's calculated
Each factor maps to a 0–100 sub-score through a smooth curve (so there are no flat spots or cliffs). The sub-scores are combined with the weights above using a blend of a weighted average and a weighted geometric mean — the geometric term penalizes lopsided deals, so a listing that's fatally weak on one financial factor can't hide behind a strong one:
weights = 40% Yield · 35% Equity · 10% Freshness · 15% Condition arithmetic = Σ weightᵢ × sub-scoreᵢ geometric = exp( Σ weightᵢ × ln(sub-scoreᵢ) ) HOT Score = round( 0.6 × arithmetic + 0.4 × geometric )
Equity upside is figured net of estimated repairs, and missing inputs (e.g. no rent or ARV) lower a deal's confidence rather than inflating its score. The HOT Score is an informational estimate, not investment advice. Always perform your own due diligence before making an offer.
Real data, and a reason
Yield and equity upside are only as good as the rent and value behind them. When a listing is enriched, the HOT Score uses an independent automated valuation (AVM) for both its rent estimate and its market value — an outside valuation instead of a rule-of-thumb — and tightens or loosens the score's confidence based on how narrow those estimates are. Every score also comes with a short, plain-English explanation of its biggest driver and its biggest risk, generated by AI from the same numbers shown here.