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Most and least expensive streets

Waterlooville, PO7

Waterlooville, PO7 has a total of 597 streets. The most expensive street in PO7 is Cotswold Way, with an average sale price of £32,673,358. The least expensive street in PO7 is Timothy Walk, with an average sale price of £60,750.

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Most expensive streets

Rank	Street	Transactions (Past 5 years)	Average price
1	Cotswold Way PO7 7GJ	1	£32,673,358
2	Aston Road PO7 7HT \| PO7 7RH \| PO7 7UD \| PO7 7UX \| PO7 7XD \| PO7 7XE \| PO7 7XF \| PO7 7XG \| PO7 7XJ \| PO7 7XQ	12	£6,730,179
3	Elettra Avenue PO7 7TZ \| PO7 7XN \| PO7 7XW	9	£3,479,750
4	Hambledon Road PO7 4QN \| PO7 6DF \| PO7 6DQ \| PO7 6EP \| PO7 6ER \| PO7 6ES \| PO7 6EU \| PO7 6EX \| PO7 6HB \| PO7 6HD \| PO7 6HL \| PO7 6JB \| PO7 6LQ \| PO7 6LR \| PO7 6LS \| PO7 6LT \| PO7 6NF \| PO7 6NG \| PO7 6NN \| PO7 6NR \| PO7 6NU \| PO7 6PN \| PO7 6PP \| PO7 6PS \| PO7 6PW \| PO7 6QA \| PO7 6QF \| PO7 6QG \| PO7 6UP \| PO7 6UT \| PO7 6XA \| PO7 6XB \| PO7 6XE \| PO7 6XF \| PO7 7FG \| PO7 7UB \| PO7 7UL	79	£2,125,600
5	Waterberry Drive PO7 7TH \| PO7 7TP \| PO7 7UN \| PO7 7UW \| PO7 7XU \| PO7 7XX \| PO7 7YH	4	£1,808,667
6	Curzon Road PO7 7HF \| PO7 7NS	1	£1,578,078
7	Anmore Lane PO7 6HN	1	£1,400,000
8	Purbrook Heath Road PO7 5RT \| PO7 5RU \| PO7 5RY \| PO7 5RZ \| PO7 5SA	1	£1,300,000
9	Kiln Lane PO7 4QJ	2	£1,300,000
10	Lower Crabbick Lane PO7 6UQ	1	£1,200,000

Least expensive streets

Rank	Street	Transactions (Past 5 years)	Average price
1	Timothy Walk PO7 7YE	1	£60,750
2	Purbrook Chase Precinct PO7 5QH	2	£79,000
3	Celia Close PO7 8LS	7	£101,886
4	Peasgood Lane PO7 3AY	1	£117,000
5	Arragon Court PO7 8NR	6	£121,629
6	Vancouver Avenue PO7 5BF	5	£123,400
7	Regency Gardens PO7 7AT	1	£125,000
8	Reedmace Close PO7 8HH	5	£139,100
9	Mercury Place PO7 8BA	4	£143,375
10	Tor Close PO7 8SU	14	£144,499

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.