Most and least expensive streets

Carlisle, CA1


Carlisle, CA1 has a total of 290 streets. The most expensive street in CA1 is Court Square, with an average sale price of £2,814,921. The least expensive street in CA1 is Petteril Bank Road, with an average sale price of £2,500.



Filter by number of transactions

Most expensive streets

Rank Street Transactions (Past 5 years) Average price
1 Court Square

CA1 1QX | CA1 1QY | CA1 1QZ
3 £2,814,921
2 Junction Street

CA1 1AA
1 £1,035,088
3 Borland Avenue

CA1 2SX | CA1 2SY | CA1 2TF | CA1 2TJ | CA1 2TL
3 £1,005,500
4 Botchergate

CA1 1QL | CA1 1QP | CA1 1QS | CA1 1RD | CA1 1RP | CA1 1RS | CA1 1RY | CA1 1RZ | CA1 1SG | CA1 1SH | CA1 1SN | CA1 1SW
3 £858,116
5 London Road

CA1 2EA | CA1 2EL | CA1 2JU | CA1 2JY | CA1 2JZ | CA1 2LE | CA1 2LF | CA1 2LG | CA1 2LS | CA1 2NG | CA1 2NS | CA1 2PD | CA1 2PE | CA1 2PR | CA1 2PY | CA1 2QH | CA1 2QQ | CA1 2QS | CA1 2QW | CA1 2QX | CA1 3DB | CA1 3DF | CA1 3DL | CA1 3DQ | CA1 3EJ | CA1 3EP | CA1 3ER | CA1 3ES | CA1 3ET | CA1 3EY | CA1 3EZ | CA1 3HA
60 £706,797
6 Holywell Crescent

CA1 2TD
1 £600,000
7 Auchinlek Drive

CA1 2UR
1 £490,000
8 Portland Square

CA1 1PE | CA1 1PT | CA1 1PU | CA1 1PY
2 £433,990
9 Sycamore Lane

CA1 3SR
2 £322,500
10 Alfred Street North

CA1 1PX
3 £313,000


Least expensive streets

Rank Street Transactions (Past 5 years) Average price
1 Petteril Bank Road

CA1 3AF | CA1 3AG | CA1 3AH | CA1 3AJ | CA1 3AP | CA1 3AW
1 £2,500
2 Central Avenue

CA1 3QB
1 £45,000
3 Margaret Creighton Gardens

CA1 2DN
1 £47,000
4 Rydal Court

CA1 2BN
1 £48,000
5 Charlotte Terrace

CA1 2RX
2 £48,500
6 Mount Florida

CA1 2SL
1 £49,000
7 Thirlwell Gardens

CA1 2DU
6 £51,500
8 Charles Street

CA1 2ET
3 £56,333
9 St. Nicholas Street

CA1 2EE | CA1 2EF | CA1 2EJ
3 £56,667
10 Grange Road

CA1 2QT
2 £58,125


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.