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Most and least expensive streets

London, E5

London, E5 has a total of 189 streets. The most expensive street in E5 is Theydon Road, with an average sale price of £1,536,389. The least expensive street in E5 is Gilpin Road, with an average sale price of £196,000.

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Most expensive streets

Rank	Street	Transactions (Past 5 years)	Average price
1	Theydon Road E5 9BQ \| E5 9NA \| E5 9NY \| E5 9NZ	9	£1,536,389
2	Chailey Street E5 0RX	1	£1,455,000
3	Wattisfield Road E5 9QH \| E5 9QN	4	£1,201,125
4	Mount Pleasant Hill E5 9EZ \| E5 9NB \| E5 9NE \| E5 9NF	7	£1,197,079
5	Upper Clapton Road E5 8AE \| E5 8AY \| E5 8AZ \| E5 8BA \| E5 8BB \| E5 8BD \| E5 8BG \| E5 8BQ \| E5 8SR \| E5 8SS \| E5 8ST \| E5 8SU \| E5 9BU \| E5 9BX \| E5 9BY \| E5 9BZ \| E5 9DA \| E5 9DB \| E5 9DH \| E5 9DS \| E5 9JP \| E5 9JU \| E5 9JY \| E5 9JZ \| E5 9LA \| E5 9LB \| E5 9SA	74	£1,131,872
6	Moresby Road E5 9LD \| E5 9LE \| E5 9LF	7	£1,124,167
7	Lingwood Road E5 9BN	5	£1,116,050
8	Newick Road E5 0RP \| E5 0RR	11	£1,062,275
9	Spring Hill E5 9BE \| E5 9BL	2	£1,000,000
10	Alconbury Road E5 8RG \| E5 8RH	11	£982,760

Least expensive streets

Rank	Street	Transactions (Past 5 years)	Average price
1	Gilpin Road E5 0HH \| E5 0HJ \| E5 0HL	2	£196,000
2	Big Hill E5 9HH	9	£242,750
3	Woodmill Road E5 9GA \| E5 9GB \| E5 9GD \| E5 9GE \| E5 9GF \| E5 9GG \| E5 9GH \| E5 9GJ \| E5 9GL \| E5 9GN \| E5 9GP \| E5 9GQ \| E5 9GR \| E5 9GS \| E5 9GT \| E5 9GU \| E5 9GW \| E5 9GX \| E5 9GZ	45	£251,966
4	Pembury Place E5 8GZ \| E5 8LX	9	£287,083
5	Napoleon Road E5 8TE \| E5 8TF \| E5 8TX	3	£297,667
6	High Hill Ferry E5 9HG	2	£300,000
7	Charnwood Street E5 8SH \| E5 8SJ \| E5 8SL \| E5 8SN \| E5 8SW \| E5 8TD	6	£319,722
8	Athlone Close E5 8HD	1	£325,000
9	Nye Bevan Estate E5 0AG \| E5 0AH \| E5 0AQ	14	£332,373
10	Monteagle Way E5 8JF \| E5 8PH \| E5 8PQ	8	£341,650

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.