HOME VALUE, MADE HUMAN

A little detail.
A clearer picture.

You know the home. We’ll do the number crunching.
Explore its estimated value in a few simple steps.

A home is more
than a number.

A clearer view of your home’s value. Estimates are automatically adjusted using the latest published Ames housing index.

01 THE HOME

Tell us a little about it.

Just the things you probably already know.

What kind of home?
sq ft
300 sq ft5,000 sq ft
Finished indoor space, excluding the basement and garage.
How would you describe the finishes? Pick what feels closest.

Supports homes built by 2010. The estimate uses the details you provide and assumptions about other features.

No sign-up. Property details stay in your browser.

02 THE NEIGHBORHOOD
AMES, IA

Put it on the map.

Pick a neighborhood. We’ll take it from there.

Neighborhood centers · approximate locations
North AmesLoading neighborhood details…
03 THE BIG PICTURE

Let’s find its ballpark.

A few familiar details. A model-backed estimate.

$— — —

Your estimate will appear right here.

A market-adjusted estimate for older Ames homes. Individual properties can move differently from the metropolitan index.
01 /

Everyday questions.

No property jargon. Just size, rooms, finishes, and a place on the map.

02 /

A real predictive model.

Built on 2,589 historical Ames sales. The saved model runs right in your browser.

03 /

Room for uncertainty.

A useful starting point, with the assumptions and model limits in plain sight.

What are we filling in for you?

The model uses 75 property inputs. We start from a representative training home of the same type in your chosen neighborhood, then replace its main details with your answers. If that combination has no training homes, we use a representative home of that type elsewhere in Ames.

Basement, lot, half bathrooms, renovation year, maintenance condition, and other unasked details come from that example. Garage area is assumed at 240 sq ft per car. These choices affect the estimate. Market change is applied automatically while holding these characteristics fixed.

The five finish levels map to the model’s material-quality scores of 2, 4, 5, 7, and 9 out of 10. Maintenance condition is a separate, automatically filled field. The estimate download includes all supplied and assumed model inputs, the latest available index period, and the market-index source.

A QUICK TOUR

From home to estimate.

  1. Describe the home.

    Choose a house or townhouse built by 2010. Enter its living area, rooms, construction year, garage spaces, and finishes. Use square feet or square meters.

  2. Find the neighborhood.

    Use the map or the neighborhood dropdown. Markers show approximate centers.

  3. Get an adjusted estimate.

    The latest published Ames housing index is applied automatically. Check its date and the assumed details, then save the estimate or change a detail and calculate again.

Your property inputs are processed locally. The map requests tiles from OpenStreetMap, which receives ordinary connection and viewport information.

BEHIND THE NUMBER

A model with context.

The histogram gradient boosting model learns from 2,589 Ames sales from 2006–2009. Every training price is first adjusted to a common market reference using the FHFA index. The model learns property values at that level, then the latest published market adjustment is applied automatically. Sale year and month are excluded from its 75 property inputs.

Historical check · simplified form

—2010 average absolute error
—2010 sales within 20%

These figures describe the simplified form on 317 supported 2010 houses and townhouses. This year was already examined in the original benchmark. Asking fewer questions increases uncertainty. These historical figures do not measure accuracy at the latest market level.

Automatic market adjustment

Accuracy for the adjusted period is unknown. There are no recent property-level sale records in this project. A retrospective 2010 check uses revised index values and actual sale-quarter indices, so it is not an as-of-date forecast. An average historical error is not an individual prediction interval.

Where it applies

Ames houses and townhouses built by 2010, with the supplied property characteristics held fixed. Renovations, aging, and neighborhood-specific price changes are not predicted. Individual apartments, newer buildings, and other cities remain unsupported.

Browser inference is checked against Python. The portal uses the bundled index snapshot and runs without retraining.