UB10 has an average sold price of £353,266 across 17,172 HM Land Registry transactions covering 657 postcodes. The largest town grouping is Uxbridge.
Decision summary
UB10 postcode area averages £353,266 across 17,172 completed sales covering 657 postcodes. Check the median, sample depth and nearby postcodes before using the average as a market signal.
Average £353,266 · Median £325,000 · 17,172 transactions · +17.7% growth · 657 postcodes
Use the location comparison tool to put UB10 postcodes beside other postcode areas, towns or districts before narrowing your shortlist.
Property valuation guide
Professional valuers use recent sold prices as comparable evidence. In the UB10 area, the median sold price is £325,000 and the average is £353,266, based on 17,172 HM Land Registry transactions. Over five years, prices have moved +17.7%, which affects how comparables from earlier years should be weighted.
These are historical completed-sale prices — not a formal valuation, asking price or investment advice. Use them to sense-check an asking price or set expectations before instructing a surveyor.
The average sold price in UB10 is £353,266, based on 17,172 HM Land Registry transactions across 657 postcodes.
UB10 is -11.0% below the England and Wales national average of £396,803.
No. These are historical completed sale prices from HM Land Registry Price Paid Data. They are not current valuations, asking prices or investment advice.
The UB10 postcode area covers 657 individual postcodes with 17,172 registered sales. The largest town grouping is Uxbridge.
All sold price figures on this page come from HM Land Registry Price Paid Data for England and Wales, published under the Open Government Licence v3.0. Contains HM Land Registry data © Crown copyright and database right. These are historical completed sale prices — they are not current valuations, not forecasts and not investment advice. Past sale prices do not guarantee future values. Always seek independent professional advice before making property or financial decisions. Read the full methodology for details on data cleaning, grouping and limitations.