ARV is the price a property should sell for once repairs are done. Every flip, wholesale, and BRRRR deal depends on it, and most bad deals trace back to a bad ARV.
The good news is that calculating ARV is a learnable skill, not a black box. Once you understand the method, you can run it on any property and explain every number to a partner, lender, or skeptical buyer.
What ARV is not
ARV is not the Zestimate. It's not the listing price of a similar house down the street. It's not what your contractor thinks the house "should be worth" after renovation. And it's definitely not what you need it to be for the deal to work.
ARV is your data-driven estimate of what a ready, retail buyer would pay for this specific property in its fully renovated condition, based on what similar properties have actually sold for recently. The word "sold" is the operative word. You're building your case from completed transactions, not wishes.
Step 1: Start with sold comps, not listings
Active listings tell you what sellers hope for. Sold prices tell you what buyers paid. Those are often very different numbers, especially in markets where sellers are optimistic or where the market is softening.
Go straight to the sold data. In MLS-connected tools, filter for "sold" status. In public data sources, look for recorded sales — deeds that have been filed with the county.
Your default filter: sold in the last 90 days, within half a mile of your subject. That's your starting point. You'll adjust if the market is thin.
Step 2: Stay inside the market
Location matters more than any other comp filter. A house that looks like a perfect match for your subject is useless if it's on the other side of a school district line, a highway, or a railroad track.
These invisible boundaries create real price differences because buyers sort by them. Parents paying for school quality won't cross a district line. Buyers who don't want highway noise won't look in your comp's neighborhood. Same city, different markets.
When you're not local, map the sale prices of all recent sales in the area and look for where prices cluster differently. The boundaries usually become visible when you look at enough data.
Half a mile is a good default for dense urban and suburban markets. Rural markets, where properties are more spread out, might require a one to two mile radius — but you'll need to be more careful about adjustments.
Step 3: Match the condition accurately
For ARV, you want to know what similar homes sell for after renovation, not before. That means filtering for comps that sold in finished condition, not distressed sales, not as-is estate sales, not "investor-to-investor" deals.
If your subject will have:
- New kitchen with granite and stainless appliances
- Renovated bathrooms
- New flooring and fresh paint
- Updated HVAC
Then your comps should also have those things. A house that sold at $160,000 because it hadn't been touched since 1985 doesn't tell you what your renovated version will bring.
The one exception: if you're estimating current as-is value (for a baseline or for a rental hold calculation), you'd want as-is comps. Know which value you're solving for before you pull the data.
Step 4: Narrow to the best 3-5 comps
More comps aren't always better. Ten mediocre comps are worse than four excellent ones. Prioritize:
- Closest in location — same street or block if possible
- Most recent — 30-60 days beats 80-90 days
- Best property match — similar beds, baths, square footage (within 15-20%), and age
- Arm's-length sales — exclude family sales, LLC-to-LLC transfers, outlier prices that suggest non-market conditions
When you have 3-5 strong comps, look at the range of prices and where most of them cluster. If 4 out of 5 cluster around $215,000-$225,000 and one is $185,000 (probably a distressed sale that slipped through), discard the outlier and work with the cluster.
Step 5: Adjust for differences
No comp is identical to your subject. Adjustments move a comp's sale price closer to what it would have been if it were identical to your property.
The direction of the adjustment: if the comp has something your subject doesn't, the comp's price is higher, so you subtract. If your subject has something the comp doesn't, add.
Common adjustments used by investors:
- Extra bedroom: subtract $10,000-$20,000 from the comp
- Garage vs. no garage: subtract $8,000-$15,000 from the comp
- Size difference: use median PSF × the sqft gap between comp and subject
- Bath count: $5,000-$12,000 per bath
- Lot size: matters in lot-premium markets; less so in standard subdivisions
Keep adjustments reasonable — if you're making a $40,000 adjustment on a $180,000 comp, you need better comps.
Step 6: Use price per square foot as your sanity check
Once you have your adjusted values, compute the median price per square foot of your comps and multiply by your subject's finished square footage. If that number is close to your adjusted ARV (within 5-8%), you're in good shape. If it's far off, revisit your comps.
PSF works well in homogeneous neighborhoods. It works poorly when houses have unusual lot sizes, finished basements counted differently, or widely varying finish levels.
Step 7: Land on a defensible number
Your ARV is not the average of your adjustments. It's your professional opinion about where this specific property lands — backed by named comps that you can point to.
For underwriting purposes: bias slightly conservative. If your comps range from $228,000 to $238,000 and your subject has a smaller lot than the median, $225,000 might be the right ARV rather than $233,000. That conservatism is what keeps your MAO from getting you into trouble when the renovation runs long or the market softens during your hold.
Document your comp selection. "ARV is $225,000 based on 4 sales within 3 blocks, all renovated 3/2s, sold in the last 75 days" is a defensible number you can explain to anyone.
Running ARV in Underwritey
Underwritey pulls the subject property, ranks nearby sold comps by location and recency first (the way experienced investors do it), then by property fit. You see the ranked list with each comp's distance, recency, beds, baths, sqft, and sale price.
You stay in control. Remove a comp that doesn't belong — a distressed outlier, a sale across a highway — and the ARV recalculates immediately using only what you kept. Add your own comp if you found one the system missed. The math is visible at every step.
Once you have ARV, the MAO formula runs automatically: ARV × your target percentage minus your repair estimate. Try it free on your next deal →