How to Calculate ARV (After Repair Value) for a Fix and Flip
After Repair Value (ARV) is the single most leverage-sensitive number in a fix & flip underwrite. Every downstream metric — projected profit, ROI, maximum allowable offer, hard-money loan amount, refinance proceeds on a BRRRR — flows directly from it. A 5% miss on ARV typically wipes 20–40% off projected profit. There is no other input where small errors compound this aggressively.
This is the method an institutional underwriter uses. It is not glamorous, but it is repeatable.
1. Define the subject property precisely
Before pulling a single comp, write down exactly what the post-renovation property will be. Square footage, bedroom and bathroom count, lot size, garage configuration, finish tier (builder-grade, mid-range, designer), and any structural changes (added bedroom, removed wall, opened kitchen). The comp set must match this finished state — not the current distressed state.
2. Pull comparable sales — three filters, in order
Quality of comps beats quantity. Apply these filters in order:
- Recency: closed sales within the last 90 days, preferred. Extend to 180 if the market is thin, never beyond 365.
- Distance: within 0.5 miles when in a uniform neighborhood. Within 1.0 mile when crossing into a different school district or HOA materially changes value.
- Parity: renovated, similar finish tier, within 10% of subject square footage, same bed and bath count where possible. A 4-bed comp for a 3-bed subject is not a comp — it is a distraction.
Five high-parity comps produce a tight, defensible ARV band. One or two comps produce a guess dressed up as a number.
3. Compute price per square foot on the comp set
For each qualifying comp, divide the sold price by finished living square footage. Discard the highest and lowest if the comp set has 5+ entries. Take the median (not the mean) of the remaining. The median is more robust to a single outlier comp that snuck through the filters.
4. Apply parity adjustments
Subject and comps will never be identical. Standard adjustments, applied to the median per-sqft figure:
- Lot: +5% for a usable lot 50%+ larger than comp median; -5% for a flag lot or steep slope.
- View / location quality: +3–10% for a defensible view (ocean, canyon, downtown); -3–7% for backing a freeway or commercial.
- Garage: +2% per additional bay vs comps; -3% if subject has carport vs garage comps.
- Pool: +2% if subject has a pool in a market where pools sell; 0 in markets where they don't.
- Finish tier: +5–10% for designer finishes above comp median; -5% if finishes will be builder-grade.
Multiply adjusted price per sqft by subject finished square footage. This is the base ARV.
5. Confidence-weight the result
A base ARV with no confidence score is dangerous. Score the comp set itself:
- High confidence: 5+ comps, all within 90 days and 0.5 miles, range of per-sqft values within 8%. Trust the ARV.
- Medium confidence: 3–4 comps, mix of 90–180 days, range within 15%. Underwrite the deal at 95% of base ARV.
- Low confidence: 1–2 comps, or per-sqft range wider than 20%. Underwrite at 90% of base ARV — or kill the deal until more sales close.
This is the part most retail spreadsheets skip. It is also where most fix & flip losses originate: a confident-looking number backed by a thin or incomparable comp set.
The three most common ARV mistakes
- Using listing prices. Listings are wishes. Only closed sales count.
- Using comps that have not been renovated. A distressed-condition comp tells you nothing about post-renovation value. Filter ruthlessly.
- Stretching distance to find more comps. A comp 1.5 miles away in a different school district is worse than no comp. Better to flag low confidence and underwrite conservatively.
How DealIntel does this automatically
DealIntel runs the comp-engine version of this method on every deal — confidence-weighted, with per-comp recency, distance, size, and renovation-parity scoring exposed in the UI. Every ARV figure carries a confidence score so the user sees the inference layer behind the number. Low-confidence comp sets trigger a Kill List flag so the deal is reviewed before an offer is drafted.
See the ARV glossary entry for the underlying definition, or comparable sales for more on comp-set construction.
Related reading
- Why ARV fails (and the methodology that survives bad comps)
- How to analyze a fix and flip deal — the institutional workflow
- Fix & flip red flags checklist
- 5 deals the DealIntel kill list would reject
- Free ARV calculator
Keep reading
- Holding Costs: The Silent Math That Turns a Profitable Flip Into a LossEvery flipper budgets purchase, rehab, and ARV. The number that quietly eats the margin is holding cost — loan interest, taxes, insurance, and utilities that accrue every single day you own the property. Here is the full holding-cost stack, the per-day burn rate math, and why a 60-day timeline slip is far more expensive than it looks.
- How to Estimate Rehab Costs on a Fix and Flip (Without Guessing)The rehab number is where most flip projections break. A 15% miss on a $90k rehab erases a thin deal entirely. Here is the line-item method professional flippers use to build a defensible rehab budget — square-foot baselines, scope tiers, the 10–20% contingency rule, and the line items beginners forget.
- How to Analyze a Fix and Flip Deal (The Institutional Workflow)A step-by-step workflow for underwriting a fix and flip deal the way an institutional capital allocator would — ARV from a confidence-weighted comp set, MAO from the 70% rule, stress-tested rehab budget, full carry math, and a pre-mortem before the offer goes in.
Matt Abadi is the founder of DealIntel. He leads the development of the platform's six-strategy underwriting engine, 25-point Kill List, and Monte-Carlo financial model — the institutional analysis stack DealIntel applies to every fix and flip deal. DealIntel was founded in 2025 with the central thesis that knowing when not to invest is the most valuable number on the page.