Use multiple source types
We compare consumer-market cost datasets with standardized industry benchmarks rather than copying one headline average.
A useful estimate should show where the range came from, what assumptions it made, and what it still does not know.
We compare consumer-market cost datasets with standardized industry benchmarks rather than copying one headline average.
Roof cost sources can disagree because project scope, roof size, geography and data collection methods differ. We use ranges rather than hiding that uncertainty.
Published cost bands are source anchors. HomeQuoteCheck modifiers and planning midpoints are labeled as model assumptions.
The current national roof replacement model uses four source anchors:
The first public model intentionally does not apply ZIP-code pricing. It also excludes decking repairs, permit fees, unusual tear-off scope, flashing/skylight counts, gutters, structural work and insurance adjustments until those variables have defensible data contracts.
The checklist's core industry anchor is Kentucky Roofing Contractors Association proposal guidance. Its scope categories include roofing material, underlayment/water protection, removal and replacement scope, flashing, ventilation, dates and payment procedures.
Kentucky Roofing Contractors Association FAQ
HomeQuoteCheck adds project-administration categories such as hidden decking, cleanup, warranty and change-order handling. The completeness score is a HomeQuoteCheck heuristic, not an industry standard or contractor grade.
The decision model uses homeowner guidance from the National Roofing Contractors Association and Owens Corning. It treats roof age as one signal rather than a diagnosis, and gives priority to widespread deterioration, repeated leaks/repairs, storm concerns, unknowns and structural-risk signals.
This model is directional decision support. It does not determine safety, structural condition, insurability or code compliance.
No. Planning midpoints and complexity modifiers are HomeQuoteCheck modeling assumptions built around multiple source anchors.
Because the current data contract does not support reliable repeatable ZIP-level precision. We prefer visible uncertainty over fake specificity.
When source datasets materially change, when a major model assumption changes, or when the stated data version becomes stale enough to undermine the planning use case.
Every estimate or decision tool must identify its data/review version, assumptions, applicability limits, variables most likely to change the result, and a clear next step. Tools are planning aids, not bids or professional inspections.