Paired sales analysis
The oldest and most intuitive way to support an adjustment: find two sales that differ in one element and let the price difference speak.
What paired sales analysis is
Paired sales analysis isolates the contributory value of a single property characteristic by comparing two closed sales that are alike in every other material respect. If the two properties differ only in the presence of an in-ground pool, the difference in their sale prices is the market's indication of what the pool contributes. Repeat the exercise across several pairs and the range of indications becomes the support for the adjustment you apply in the grid.
A worked example
Two sales in the same subdivision, closed six weeks apart, both 2,150 sq ft, both three-bedroom, both two-bay garages, both average condition, similar sites:
| Sale | Pool | Sale price |
|---|---|---|
| Sale A | In-ground pool | $498,000 |
| Sale B | No pool | $481,500 |
| Indicated pool contribution | $16,500 | |
One pair is an indication, not a conclusion. It tells you the order of magnitude — that the pool contributes far less than it cost to install — and it gives you something specific to reconcile against other pairs and other methods.
Where the method breaks down
- Truly matched pairs are rare. Outside of tract subdivisions, two sales almost always differ in more than one element, and the price difference then reflects all of them at once.
- Small samples are noisy. Negotiation, motivation, and timing move prices by amounts comparable to the adjustment you are trying to measure.
- Elements are correlated. Larger homes tend to have more garage bays and more bathrooms, so a single pair cannot separate their effects.
- It is slow to document. Each pair requires its own verification, and reviewers ask for the work behind the number.
How regression complements it
Regression uses every qualified sale in the competitive market area instead of two, and estimates the contribution of each element while the others are held constant. That directly addresses the two weaknesses above: sample size and correlation between characteristics. It does not replace paired sales — a paired sale remains an excellent sanity check on a regression coefficient, and a coefficient that contradicts a clean pair is a reason to look harder at the data.
Read more on regression analysis in appraisal, or try the adjustment calculator.
The figures on this page are illustrative and are not a market study. CompShield is an analytical support tool and does not replace the appraiser's professional judgment. The appraiser remains responsible for data selection, methodology, analysis, conclusions, and compliance with applicable appraisal standards.