Sold prices in SN1 For sale in SN1 To rent in SN1

Most and least expensive streets

Swindon, SN1

Swindon, SN1 has a total of 316 streets. The most expensive street in SN1 is Gloucester Street, with an average sale price of £8,500,000. The least expensive street in SN1 is Havelock Street, with an average sale price of £1,000.

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Most expensive streets

Rank	Street	Transactions (Past 5 years)	Average price
1	Gloucester Street SN1 1GW	1	£8,500,000
2	New Bridge Square SN1 1BY \| SN1 1EA \| SN1 1HN	3	£8,103,000
3	Regent Street SN1 1JL \| SN1 1JQ \| SN1 1JS \| SN1 1JY \| SN1 1JZ \| SN1 1LA \| SN1 1QB \| SN1 1UH	12	£3,127,106
4	Princes Street SN1 2DF \| SN1 2DL \| SN1 2HJ \| SN1 2HP \| SN1 2HX \| SN1 2HY \| SN1 2JA \| SN1 2JB \| SN1 2SD \| SN1 2SF	5	£3,008,888
5	Bristol Street SN1 5EQ \| SN1 5ET	2	£2,730,000
6	Belgrave Street SN1 3HR	4	£2,253,763
7	George Street SN1 5HE	6	£1,520,842
8	Fleet Street SN1 1RA \| SN1 1RE \| SN1 1RL \| SN1 1RQ	2	£1,412,500
9	Kent Road SN1 3NG \| SN1 3NJ \| SN1 3NP \| SN1 3NQ \| SN1 3NW \| SN1 4NH	23	£1,160,606
10	Regent Circus SN1 1PJ \| SN1 1PN \| SN1 1PP \| SN1 1PR \| SN1 1PX \| SN1 1PY \| SN1 1PZ \| SN1 1QF \| SN1 1QG \| SN1 1UG \| SN1 1UQ	3	£953,333

Least expensive streets

Rank	Street	Transactions (Past 5 years)	Average price
1	Havelock Street SN1 1SD	1	£1,000
2	Redcross Place SN1 3QF	5	£65,000
3	Arnhill Road SN1 7AB	1	£75,000
4	Erin Court SN1 4NS	6	£76,333
5	Reading Street SN1 5BS	1	£77,000
6	The Heights SN1 4NN	12	£80,708
7	David Murray John Tower SN1 1LH \| SN1 1LP \| SN1 1LR \| SN1 1LS \| SN1 1LT \| SN1 1LU \| SN1 1LW \| SN1 1LX \| SN1 1LY \| SN1 1LZ \| SN1 1NB	1	£85,000
8	Yersin Court SN1 4GY	18	£92,778
9	Wellington Street SN1 1DX \| SN1 1EB	13	£103,115
10	The Moorings SN1 5AB \| SN1 5AD \| SN1 5JJ	12	£104,417

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.