How is running comps different for rental properties versus sales?

Sales comps use closed sale prices to estimate market value or ARV. Rental comps use recently signed leases to estimate market rent. The selection criteria are similar — proximity, recency, size, condition — but the data sources differ. For rentals, active listing rents are a proxy in liquid markets; signed lease data from a local property manager or agent is more reliable.

What if there aren't enough comps within a mile?

Extend the radius, and note it. In rural or suburban markets, appraisers sometimes go two to three miles and cross a highway to find comps. The further the concession from your ideal criteria, the more your estimate becomes a range rather than a point. Write down where the comp set is thin so you don't over-trust the number, and expect the lender's appraiser to pull a different set than you did.

Should I use list prices or sale prices for comps?

Sale prices only. A listing price is an ask, not a transaction. If you comp a property using active listings, you are estimating what sellers hope to get, which in most markets runs only a few percent above the eventual sale price, but can be much higher on overpriced or stale listings. The only exception is using active listings as a directional sanity check after you've already built your estimate from closed data.

How do adjustments affect the final value estimate?

Each adjustment introduces estimation error. The paired-sale data behind an adjustment is itself derived from a limited number of transactions, so the per-square-foot value or garage value is an approximation. Large adjustments — correcting for a 30% size difference or a full renovation gap — produce wider uncertainty ranges. A common rule of thumb keeps total gross adjustments under about 25% of the comp's sale price. As an investor, use that as a signal: if your adjustments are getting big, find better comps.

How to run comps on a property (sales and rental)

Adjustments are the step most investors skip

Pulling recent nearby sales is the easy part. Adjusting each comp for its differences from the subject is the step that makes the estimate rigorous. Skip it and the estimate quietly falls apart.

Most informal comp analysis skips straight to averaging the raw sale prices. That works when the comps are nearly identical to the subject. When they’re not, an un-adjusted average blends a renovated comp and a dated one into one number that looks precise and hides the spread.

The good news: you don’t need appraiser-level paired-sale databases to do this well. Two or three well-sourced adjustment figures — a garage value, a per-sqft rate, a bathroom adjustment — applied consistently across your comps produces a defensible estimate for any purchase decision.

What a paired-sale adjustment actually looks like

Take a two-car garage as an example. On the same street, two otherwise equivalent houses sold: one with a two-car garage for $285,000, and one without for $271,000. The market’s implied value for that garage is $14,000.

You can now use that figure as an adjustment across any comp on that street that differs from the subject on garage count. If your subject has a garage and a comp does not, add $14,000 to the comp’s sale price. If the subject has no garage and a comp does, subtract $14,000.

This is all a paired-sale adjustment is: an isolated, market-derived dollar value for one specific difference. Use it where you have a clean pair. Where you don’t, put down your best estimate and label it an estimate, not a measured value.

Step 1: Define the subject precisely

Before pulling a single comp, write down the subject’s key attributes:

Address and neighborhood
Square footage (gross living area)
Bedroom and bathroom count
Lot size
Year built
Garage count and type
Current condition (distressed / dated / updated / renovated)

Those are the axes you’ll adjust on. Skip one and you’ll catch yourself comparing a renovated 1,400 sqft house against a dated 1,750 sqft one, then puzzling over the wide range.

Step 2: Pull recent closed sales

Target closed sales within roughly one mile, sold in the past three to six months, within 15–20% of the subject’s square footage. Aim for three to six. Use closed sales only — active listings show what sellers are asking, not what buyers are paying.

Common sources: MLS data (through an agent or data platform), county assessor records, and data providers that carry historical transaction data. For rental comps, use recently signed leases from listing platforms or a local property manager rather than asking rents, which in a softening market can lag actual lease rates by a noticeable margin.

In thin markets you’ll have to extend the radius or the lookback window. Document each concession: “Extended to 1.5 miles — no comps within one mile in the past 6 months” is useful context when you return to the analysis or share it.

Step 3: Screen for true comparability

Before adjusting, cut the comps that shouldn’t be in the stack:

Drop non-arm’s-length sales. Estate sales, foreclosure auctions, transactions between family members, and lender-owned sales can show up in the data at prices that reflect circumstances, not market value. A quit-claim deed or a below-market price with zero days on market is a flag. Pull the deed type and check.

Flag distress indicators. A property that sold in two days at 92% of list is a market sale. One that sat 180 days and sold with $15,000 in concessions is a different story.

Check condition carefully. A renovated comparable used to value a distressed subject will require a large, hard-to-quantify condition adjustment. Better to value off three comps already in similar shape than to bolt big downward condition adjustments onto five that aren’t.

Step 4: Adjust each comp

For each remaining comp, adjust its sale price to what it would have fetched if it matched your subject. Adjustments run both directions:

If the comp is…	Adjust the comp’s price…
Larger than the subject	Downward (comp got credit for more space)
Smaller than the subject	Upward (comp sold for less partly because it’s smaller)
Has a garage; subject does not	Downward
No garage; subject does	Upward
In better condition	Downward
In worse condition	Upward

Use the paired-sale method to source the per-unit adjustment values where possible. When you can’t find a clean pair, use a conservative estimate and note it.

Watch total gross adjustments. If a comp’s adjustments add up to more than about 25% of its sale price, the comp is probably too different from the subject to be reliable — find a better one.

Step 5: Reconcile into a value range

Once each comp is adjusted, you have a set of indicated values. Weight the results toward comps that needed fewer and smaller adjustments — they were closest to begin with.

If the adjusted values cluster (three comps landing at $305,000, $298,000, and $312,000), a point estimate in that range is defensible. The midpoint, $305,000, is reasonable.

If they scatter (adjusted values at $278,000, $310,000, and $345,000), either the comps aren’t truly comparable or the market has real uncertainty. Narrow the comp set, look for what’s driving the spread, and widen your value range when you underwrite.

For ARV on a fix-and-flip, the reconciled value range is what sets your maximum offer via the 70% rule. For a buy-and-hold, sales comps tell you whether the price is sane and rental comps tell you whether it pays. Pin down both before you offer.

You’ll land on a range, not a single number, and that’s the honest output. Anyone who hands you a value down to the dollar off a comp set like this is selling false confidence.