Rental Comps: How to Find and Analyze Rental Comparables

What a rental comparable is

A rental comp is a property similar enough to the subject that its rent is a meaningful data point. If five similar homes in the same neighborhood rent for $1,500 to $1,700, a sixth similar home will rent in that band. Rent is set by the market, not by the landlord, and comps are how you read the market.

The difficulty is that no two properties are identical. Every comp differs from the subject in some way, so the skill is in two places: choosing comps that are close enough to matter, and adjusting for the differences that remain.

The five criteria a good rental comp meets

A useful comparable matches the subject on five things. The more it matches, the more its rent predicts yours, and the first two are non-negotiable.

Condition and finish level are the sixth, softer criterion. A comp with the same numbers and a full renovation is not the same property, and it belongs in the outlier discussion below.

Example uses public listing data for illustration. See disclaimer.

Where to find rental comps

Each source covers a different slice of the rental market, and none covers all of it. Cross-reference two, or use an aggregated set that already combines them.

How to adjust a comp toward the subject

Adjusting is arithmetic with one rule: if the comp has a feature the subject lacks, subtract that feature's value from the comp's rent; if the comp lacks a feature the subject has, add it. The result is what the comp would rent for if it were the subject property.

When you have ten comps and four attributes, hand adjustment stops scaling. A regression over the comparable set prices each attribute from local data and applies the adjustments in one pass, which is the method behind a good automated estimate. Our guide to estimating rent shows the difference on a worked set.

Spotting and excluding outliers

An outlier is a comp whose rent is far from the rest of the set for a reason that does not apply to the subject. One outlier in five comps shifts a plain average by 15% or more, so finding them matters as much as finding comps in the first place.

The usual suspects, and what gives them away:

• Luxury renovations. Same beds and size, but quartz, custom cabinetry and smart-home fittings. Rents 10% to 20% above the cluster. Adjust heavily or drop.
• Subsidized leases. Section 8 rents follow HUD fair market rent tables, not the local market, and can sit above or below it. Exclude unless the subject will target the program.
• Furnished and short-term units. A $2,500 listing where everything else is $1,600 is almost always furnished or corporate. Exclude.
• Below-market leases. A comp far under the cluster is usually a long-term tenant without increases, a family arrangement, or deferred maintenance. Exclude.

Example uses public listing data for illustration. See disclaimer.

When the comps disagree with your gut

A clean comparable set that lands below the rent you hoped for is doing its job. The number to question is the hoped-for rent, not the comps. If the set is thin, widen the radius to a mile and accept a wider range; if it is still thin, call two property managers before you trust any figure.

The one case where the comps can be wrong is a subject that is genuinely unusual for its area: the only four-bedroom, the only new build, the only house with a pool. There the adjustments carry the estimate, the range should be wide, and a conservative figure in the lower half of it is the number to underwrite with.