Sold prices in SE22 For sale in SE22 To rent in SE22

Most and least expensive streets

London, SE22

London, SE22 has a total of 150 streets. The most expensive street in SE22 is Eynella Road, with an average sale price of £1,909,200. The least expensive street in SE22 is Lytcott Grove, with an average sale price of £150,287.

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Most expensive streets

Rank	Street	Transactions (Past 5 years)	Average price
1	Eynella Road SE22 8XF	5	£1,909,200
2	Townley Road SE22 8SR \| SE22 8SU \| SE22 8SW \| SE22 8SX	6	£1,690,103
3	Elsie Road SE22 8DX	8	£1,494,500
4	Dovercourt Road SE22 8SS \| SE22 8ST \| SE22 8UW	10	£1,478,313
5	Woodwarde Road SE22 8UJ \| SE22 8UL \| SE22 8UN \| SE22 8UP \| SE22 8UR \| SE22 8UT	16	£1,426,713
6	Beauval Road SE22 8UG \| SE22 8UH \| SE22 8UQ	13	£1,239,568
7	Great Spilmans SE22 8SZ	1	£1,168,000
8	Scutari Road SE22 0NN	3	£1,078,333
9	Matham Grove SE22 8PN	8	£1,071,938
10	Shelbury Road SE22 0NL	7	£1,047,286

Least expensive streets

Rank	Street	Transactions (Past 5 years)	Average price
1	Lytcott Grove SE22 8QX	1	£150,287
2	Hillsboro Road SE22 8QE	1	£295,000
3	Dulwich Common SE22 8NS \| SE22 8NT	3	£325,000
4	East Dulwich Estate SE22 8AD \| SE22 8AE \| SE22 8AF \| SE22 8AG \| SE22 8AL \| SE22 8AN \| SE22 8AP \| SE22 8AQ \| SE22 8AR \| SE22 8AW \| SE22 8BJ \| SE22 8BL \| SE22 8BN \| SE22 8BP \| SE22 8BS \| SE22 8BT \| SE22 8BU \| SE22 8BW \| SE22 8BX \| SE22 8BY \| SE22 8BZ \| SE22 8DB \| SE22 8DD	60	£336,454
5	Dulwich Lawn Close SE22 8QT	1	£350,000
6	Dog Kennel Hill SE22 8AA \| SE22 8AB \| SE22 8BB \| SE22 8BE \| SE22 8BF \| SE22 8BQ	4	£368,000
7	Dudrich Mews SE22 8AS	1	£368,500
8	Quorn Road SE22 8BH	1	£368,500
9	Blackwater Street SE22 8RS \| SE22 8SD	14	£397,076
10	Highwood Close SE22 8NH \| SE22 8NJ \| SE22 8NL \| SE22 8NN \| SE22 8NP \| SE22 8NQ \| SE22 8NR \| SE22 8NW	20	£408,667

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.