TQ10 has an average sold price of £261,443 across 1,955 HM Land Registry transactions covering 152 postcodes. The largest town grouping is South Brent.
Decision summary
TQ10 postcode area averages £261,443 across 1,955 completed sales covering 152 postcodes. Check the median, sample depth and nearby postcodes before using the average as a market signal.
Average £261,443 · Median £253,000 · 1,955 transactions · +61.8% growth · 152 postcodes
Use the location comparison tool to put TQ10 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 TQ10 area, the median sold price is £253,000 and the average is £261,443, based on 1,955 HM Land Registry transactions. Over five years, prices have moved +61.8%, 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 TQ10 is £261,443, based on 1,955 HM Land Registry transactions across 152 postcodes.
TQ10 is -34.1% 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 TQ10 postcode area covers 152 individual postcodes with 1,955 registered sales. The largest town grouping is South Brent.
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.