Scoring factor
How to weight commute access
Weight commute for a trip you will take most days. The default score is a town average or a single listing figure, not a door-to-door time to your office. A high weight will still reorder the list, so aim it at a commute you actually have.
How hard to weight it
People who go to an office put this first. The commute preset is 35, which makes a 15-minute town versus a 45-minute town a 17.5-point swing. That will beat schools, value, and the yard unless those gaps are extreme.
Remote workers do the opposite. The lifestyle preset leaves commute at 3, so the same 15-versus-45 gap is 1.5 points. The town’s average trip stays on the report and does not pick the house. Downsizers sit in the middle, at 22, because the trip is errands and appointments rather than a daily train.
If your destination is not what the average measures, lower the weight and use the requirements field for a maximum you will not cross. The weight cannot aim at your building. The maximum can at least cap a listing that carries its own commute time.
What the weight does to the total
On the default formula, 0 minutes scores 100, 30 minutes scores 50, and 60 minutes scores 0. Fifteen minutes scores 75. Forty-five minutes scores 25.
| Weight | Effect on the total |
|---|---|
| Weight 35 | 15 minutes versus 45 is 17.5 points. Commute leads the ranking. |
| Weight 22 | The same gap is 11 points. A serious factor beside condition, not the only one. |
| Weight 3 | The same gap is 1.5 points. The house decides. |
The property score is the weighted sum: each factor score times its weight, divided by 100. Weights are scaled to add up to 100 before that sum.
What the score uses
By default an analysis uses the formulas in “What the score uses.” The new scoring engine runs only when FEATURE_USE_NEW_SCORING_ENGINE is on, or when a rollout percentage includes that account. Where that engine differs, it is called out separately. A missing input scores 50. That is a neutral, not a zero, and it can outrank a known weak result.
If the listing record includes commuteTime, the score is 100 − (minutes ÷ 60) × 100, floored at 0. The analyzer treats that field as minutes.
Otherwise the default engine uses the stored average minutes for the same city list as the other town factors, with the same formula. Boston is stored at 20 minutes (score 67). Lexington is stored at 35 (score 42). Los Angeles is stored at 35. A city off the list, with no listing commute, scores 50, which is exactly a 30-minute result. An unknown suburb outranks a known 40-minute town, because 40 minutes scores about 33.
The figure is not a route to your desk. Stored values are one number per city. A house near a highway and a house on the far side of the same city share it, unless the listing itself carried a commute time.
score = max(0, 100 − (minutes ÷ 60) × 100)
Minutes come from the listing when present, otherwise from the stored city average
No minutes and no listed city → 50
When the new engine is on
When the new engine is on, census mean commute minutes score as 100 − minutes × 2, which is harsher: 30 minutes is 40, not 50. A transit-share bonus of up to 15 points is added inside that piece (transit percent ÷ 2, capped at 15). If a separate transit-access score also exists, the census piece is then mixed at 70% and transit access at 30%. The transit share can influence the result twice. With neither census commute nor a transit score, the factor is 50.
The public overview is the methodology page. Where that page says comparables, orientation, or documented updates, the formulas on this page are the ones that run.
Tradeoffs against the other factors
- School quality
The stored table pairs stronger school ratings with longer averages. Commute at 35 and schools at 4, which is the office preset, will not follow a district. Flip those weights and you will drive farther.
- Home age
The office preset also puts age at 25. You are asking for a newer house in a short-commute city. Those listings are the expensive intersection. Value is only weighted 10, so price will not save you from that pair.
- Lot size
Closer-in stock tends to have smaller lots. A high commute weight and a high lot weight fight. Remote workers drop commute to 3 so the lot can win. Office commuters do the reverse.
Mistakes that move the ranking
- Assuming the score is your commute. It is a city average, unless that particular listing had a commute field.
- Treating 50 as a half-hour you measured. Off the list, with a blank listing, 50 is the fallback, and it beats a measured 40-minute town.
- Raising the weight to punish a long drive and then searching only inside one city. Every house shares the stored average, so the weight adds a constant and does not rank them.
Profiles that lean on this
The other six factors
Set the weight yourself
The builder opens on an even split, or on the platform default if one is saved. It does not assume this factor. If you want a whole profile filled in, start from a buyer preset.
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