Adjusting Comp Filters

The comp analysis page in Deal Run gives you a filter toolbar above the map and grid views. These filters control which properties are included in your comparable sales search. Adjusting them correctly is one of the most important skills in deal analysis because the comps you select directly determine your ARV, which flows into your MAO calculation, your marketing price, and ultimately whether the deal works.

This guide walks through every filter, explains the defaults, and helps you understand how each change affects your ARV confidence level.

Radius slider

The radius slider controls how far from your subject property the search extends. It ranges from 0.25 miles to 2 miles, with a default of 0.5 miles.

• 0.25 miles is the tightest search. This captures only the immediate neighborhood, usually within the same subdivision. Use this when you are in a tract-built community where homes share similar floor plans, age, and lot sizes. You may only get 3 to 8 comps at this radius, but they will be highly comparable.
• 0.5 miles (default) balances quantity and quality. In most suburban markets this returns 10 to 30 comps while staying within the same school zone and market segment. This is the recommended starting point for most analyses.
• 1 mile is appropriate when the default radius does not return enough comps. This happens in rural areas, newer developments with few resales, or neighborhoods with very low turnover. Be careful at this distance. You may cross school zone boundaries, flood zone boundaries, or highway corridors that separate market segments.
• 1.5 to 2 miles should be used sparingly. At this distance you are likely pulling comps from fundamentally different neighborhoods. A comp at 1.8 miles in a Houston suburb might be in a different HOA, different school district, and different price tier. If you must go this wide, pay close attention to the similarity ranking and exclude comps that clearly serve a different buyer pool.

When you move the radius slider, the circle on the map updates in real time and the comp count refreshes. The number of comps found is displayed next to the filter bar so you can immediately see the effect of your change.

Date range filter

The date range filter controls how far back in time the search looks for closed sales. The options are 3 months, 6 months, and 12 months, with 12 months as the default.

• 3 months gives you the most current market data. In an active market with good turnover, 3 months might return 5 to 15 closed sales, which is plenty for a reliable ARV. Use this when you want to see only what is happening right now and the market has been shifting recently. If appreciation or depreciation is significant, limiting to 3 months eliminates the need for time adjustments.
• 6 months is the sweet spot for most markets. It is recent enough to reflect current conditions while providing enough data points for statistical confidence. Most appraisers use a 6-month window as their primary range, expanding only when necessary.
• 12 months (default) ensures you always have enough comps, even in slow-turnover neighborhoods. The tradeoff is that older comps may not reflect current market conditions. Deal Run accounts for this by weighting more recent sales more heavily in the similarity ranking. A comp from 2 months ago will carry more weight than one from 11 months ago, even if the 11-month comp is closer in distance.

Deal Run enforces a hard maximum of 12 months. Comps older than one year introduce too much market movement risk. If you cannot find adequate comps within 12 months and 2 miles, the market may be too thin for a reliable comp-based ARV, and you should note that uncertainty in your deal analysis.

Property type filter

The property type filter defaults to the same type as your subject property. The options include:

• Single Family Residence (SFR) -- detached homes on their own lot. This is the most common property type in wholesale deals.
• Townhouse -- attached homes that share one or more walls with neighboring units but have individual ownership of the land beneath.
• Condo -- units within a larger building or complex. Ownership includes the interior space but not necessarily the land. HOA fees and rules significantly affect valuation.

Mixing property types in a comp analysis is generally a mistake. An SFR and a townhouse in the same area may have similar square footage and bed/bath counts, but they appeal to different buyers and carry different cost structures (HOA fees, maintenance responsibility, land value). Keep the property type filter matched to your subject unless you are in a market where the distinction is genuinely minimal.

Status filter

The status filter controls which listing statuses are included in the results. By default, all three are enabled.

• Sold (Closed) -- completed transactions. These are the foundation of your ARV. The sold price is what a buyer actually paid, recorded in MLS and/or county deed records. You should always have sold comps enabled.
• Active -- currently listed for sale. Active listings show you the current asking prices in the area. They serve as a ceiling check: if your calculated ARV is significantly higher than every active listing, you may be overestimating. Active listings are not used in the ARV calculation itself because asking price is not market value.
• Pending -- under contract but not yet closed. Pending listings are the most current signal of buyer behavior. They tell you what price a buyer was willing to sign a contract at. The actual closing price may differ slightly, but pending data bridges the gap between historical sold data and current market conditions.

For a conservative analysis, some wholesalers prefer to disable Active and Pending and look only at closed sales. This is valid, but you lose the context of current market direction. A market where active listings are priced 5% above recent solds may be appreciating. A market where active listings have been sitting for 90+ days at 10% above recent solds is a warning sign of softening demand.

Beds and baths range

By default, Deal Run matches the subject property's bedroom and bathroom count. A 3-bed, 2-bath subject will search for 3/2 comps. You can expand this range to include plus or minus one bedroom or bathroom if the default is too restrictive.

When you include comps with a different bed/bath count, Deal Run applies dollar adjustments automatically. A comp with 4 bedrooms compared to your 3-bedroom subject gets adjusted downward by the local per-bedroom value (typically $8,000 to $15,000 depending on the market and price tier). A comp missing a bathroom gets adjusted upward by the per-bathroom value ($10,000 to $18,000 for a full bath).

Expanding the bed/bath range is useful when your subject has an unusual configuration (like a 2-bedroom home in a market dominated by 3-bedroom inventory) or when the exact-match search returns too few results. Just be aware that each mismatch introduces adjustment uncertainty. A comp that needs bedroom, bathroom, and square footage adjustments totaling $30,000 is far less reliable than one that needs only a $2,000 square footage adjustment.

Map boundary drawing

For situations where a circular radius does not capture the right comps, Deal Run provides a boundary drawing tool on the map. Click the polygon icon in the map toolbar to activate drawing mode. Click points on the map to create a custom polygon boundary. Double-click or click the starting point to close the shape.

Once drawn, only comps inside your custom boundary are included in the analysis. This is especially useful in markets with natural or man-made boundaries that divide neighborhoods:

• Highways and major roads often separate price tiers. A custom boundary can keep your comps on the correct side of I-10, Highway 99, or a busy arterial road.
• Flood zones create value boundaries within the same subdivision. A home in Zone X (minimal flood risk) may be worth 10-15% more than an identical home in Zone AE (high risk) two streets over. Draw your boundary to match flood zone lines when this is a factor.
• School zones can create sharp value changes at seemingly arbitrary geographic lines. Two homes 500 feet apart in different school attendance zones may have a $20,000 value gap.
• Subdivision boundaries are the most common use case. An HOA with amenities (pool, park, gated entry) will have different values than the non-HOA neighborhood next door.

To clear a custom boundary and return to the radius-based search, click the trash icon in the map toolbar or simply adjust the radius slider, which removes the custom boundary automatically.

Grid vs map view toggle

The comp analysis page provides two views that you can switch between using the toggle in the toolbar.

Map view shows all comps as colored markers on a Google Maps base layer with your subject property at the center. This view is best for understanding spatial relationships: which comps are in the same subdivision, which are across a highway, which are near a school or park. You can click any marker to see a summary card with the property's key details.

Grid view displays comps in a sortable table format. Each row shows the address, sold/list price, adjusted price, square footage, bed/bath count, year built, condition, distance from subject, and days since sale. You can sort by any column. This view is best for comparing specific numbers across comps and for selecting or deselecting individual comps from your analysis.

Both views respond to your filter settings. Changing a filter in map view is reflected immediately in grid view and vice versa. The comp count and recommended ARV update in real time as you add or remove comps from the analysis.

How filters affect ARV confidence

Every filter change involves a tradeoff between quantity of data and quality of comparability. Understanding these tradeoffs helps you build a defensible ARV.

The ideal comp search returns 5 to 10 closed sales within a tight radius and recent date range that closely match your subject property's size, configuration, and condition. When you achieve that, your ARV carries high confidence. When you have to stretch multiple filters to find enough comps, note the reduced confidence and build a larger cushion into your offer price.