Most and least expensive streets

Reading, RG30


Reading, RG30 has a total of 390 streets. The most expensive street in RG30 is Gresham Way, with an average sale price of £4,275,000. The least expensive street in RG30 is Harvaston Parade, with an average sale price of £25,000.



Filter by number of transactions

Most expensive streets

Rank Street Transactions (Past 5 years) Average price
1 Gresham Way

RG30 6AW
1 £4,275,000
2 Bridgewater Close

RG30 1JT | RG30 1NS
2 £2,289,500
3 The Hatch

RG30 3TH | RG30 3TJ
5 £1,573,000
4 Loverock Road

RG30 1DY | RG30 1DZ
10 £1,396,522
5 Wigmore Lane

RG30 1HY | RG30 1NP
1 £1,240,000
6 Kendrick Gate

RG30 4DP
3 £1,143,333
7 Portman Road

RG30 1AH | RG30 1AW | RG30 1EA | RG30 1JG | RG30 1PD
7 £1,133,286
8 Southcote Lane

RG30 3AA | RG30 3AB | RG30 3AD | RG30 3AE | RG30 3AF | RG30 3AG | RG30 3AH | RG30 3AJ | RG30 3AL | RG30 3AP | RG30 3AQ | RG30 3AR | RG30 3AS | RG30 3AT | RG30 3AU | RG30 3AW | RG30 3AX | RG30 3AY | RG30 3BA | RG30 3BB | RG30 3BD | RG30 3BE | RG30 3BG | RG30 3BH | RG30 3BJ | RG30 3BL | RG30 3ES
67 £808,516
9 Deacon Way

RG30 6AQ | RG30 6AZ | RG30 6QG | RG30 6QQ
3 £715,333
10 Searles Farm Lane

RG30 3XB
1 £710,000


Least expensive streets

Rank Street Transactions (Past 5 years) Average price
1 Harvaston Parade

RG30 4LP
1 £25,000
2 Gordon Palmer Court

RG30 1EY
12 £109,083
3 Marcus Close

RG30 4EA | RG30 4EB
1 £132,500
4 Coronation Square

RG30 3QF | RG30 3QN | RG30 3QP | RG30 3QW
1 £140,000
5 Tylers Place

RG30 6BW
6 £178,667
6 Little Johns Lane

RG30 1LG | RG30 1LQ | RG30 1RA
3 £178,750
7 Rona Court

RG30 2RJ
5 £179,290
8 Bexley Court

RG30 2DY
8 £179,750
9 Burrcroft Court

RG30 2ET
9 £180,056
10 Moulsford Mews

RG30 1AP | RG30 1AR | RG30 1ER | RG30 1ES | RG30 1ET | RG30 1EU
42 £181,901


Street ranking notes

Average street prices are calculated using all sales in the HM Land Registry data from the past 5 years. It is important to note that as homes are demolished and built these prices will fluctuate over time accordingly. Use the transactions number filter to avoid any anomalous data caused by low transaction numbers.