Most and least expensive streets

Cheltenham, GL51


Cheltenham, GL51 has a total of 693 streets. The most expensive street in GL51 is Gallagher Retail Park, with an average sale price of £73,240,000. The least expensive street in GL51 is Monkscroft, with an average sale price of £71,563.



Filter by number of transactions

Most expensive streets

Rank Street Transactions (Past 5 years) Average price
1 Gallagher Retail Park

GL51 9RR
1 £73,240,000
2 Manor Road

GL51 9NR | GL51 9RQ | GL51 9SQ | GL51 9TP
1 £4,032,000
3 Hesters Way Lane

GL51 0EY | GL51 0LB | GL51 0LE | GL51 0LL | GL51 0LN | GL51 0LR | GL51 0LS
7 £3,996,660
4 Rutherford Way

GL51 9TS | GL51 9TU
3 £2,578,827
5 Huntscote Road

GL51 9NX
1 £2,575,000
6 Hatherley Lane

GL51 6HJ | GL51 6PL | GL51 6PN | GL51 6PW | GL51 6SH | GL51 6SY | GL51 6TA
13 £2,501,083
7 Fiddlers Green Lane

GL51 0FG | GL51 0JS | GL51 0JT | GL51 0SF | GL51 0SZ | GL51 0TA | GL51 0TB | GL51 0TD
12 £2,001,875
8 Mackenzie Way

GL51 9TX
1 £1,890,000
9 Malmesbury Road

GL51 9PL
2 £1,553,500
10 Kingsditch Lane

GL51 9NE | GL51 9NN | GL51 9PB | GL51 9PE | GL51 9PX
1 £1,160,000


Least expensive streets

Rank Street Transactions (Past 5 years) Average price
1 Monkscroft

GL51 7TP | GL51 7TR | GL51 7TS | GL51 7TT | GL51 7TU | GL51 7TX | GL51 7TY | GL51 7TZ
6 £71,563
2 Elm Close

GL51 9BZ
1 £80,000
3 Edinburgh Place

GL51 7NT | GL51 7RH | GL51 7RP | GL51 7SA | GL51 7SB | GL51 7SD | GL51 7SE | GL51 7SF
3 £83,500
4 Pitman Road

GL51 7UA | GL51 7UB | GL51 7UD | GL51 7UE | GL51 7UF | GL51 7UG
11 £84,817
5 Lygon Walk

GL51 7JN | GL51 7JW
2 £94,500
6 Caernarvon Close

GL51 3LQ
1 £105,000
7 Seacombe Road

GL51 0HX | GL51 0HY
4 £106,500
8 St. Peters Square

GL51 9EF
1 £107,000
9 Swindon Close

GL51 9EA
4 £107,313
10 De Ferriers Walk

GL51 0JG | GL51 0JQ
1 £110,000


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.