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Most and least expensive streets

Sheffield, S1

Sheffield, S1 has a total of 153 streets. The most expensive street in S1 is Hartshead, with an average sale price of £35,500,000. The least expensive street in S1 is Surrey Street, with an average sale price of £24,000.

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Most expensive streets

Rank	Street	Transactions (Past 5 years)	Average price
1	Hartshead S1 2EL	2	£35,500,000
2	Hartshead Square S1 2FD	1	£35,500,000
3	Mortimer Street S1 4RZ \| S1 4SF	9	£26,945,531
4	Matilda Street S1 4QB \| S1 4QD \| S1 4QF \| S1 4QG	3	£26,886,750
5	Holland Street S1 4NL	1	£19,100,000
6	Concourse Way S1 2BJ	2	£13,305,100
7	Union Street S1 2FU \| S1 2JN \| S1 2JP \| S1 2JQ \| S1 2LF \| S1 2LR \| S1 2LS \| S1 2SH	2	£9,974,150
8	Young Street S1 4LA \| S1 4UP	4	£8,187,030
9	Pond Hill S1 2BG	2	£7,550,000
10	Eyre Street S1 3FG \| S1 3GQ \| S1 3HU \| S1 4QW \| S1 4QY \| S1 4QZ	4	£7,408,750

Least expensive streets

Rank	Street	Transactions (Past 5 years)	Average price
1	Surrey Street S1 1XX \| S1 1XZ \| S1 2HY \| S1 2LG \| S1 2LH \| S1 9SA \| S1 9SB \| S1 9SD \| S1 9SE \| S1 9SF \| S1 9SG \| S1 9SH \| S1 9SJ \| S1 9SL \| S1 9SN \| S1 9SP \| S1 9SQ \| S1 9SR \| S1 9SS \| S1 9ST \| S1 9SU \| S1 9SW \| S1 9SX \| S1 9SY \| S1 9SZ \| S1 9TA \| S1 9TB \| S1 9TD \| S1 9TE \| S1 9TF \| S1 9TG \| S1 9TH \| S1 9TJ \| S1 9TL \| S1 9ZS \| S1 9ZT \| S1 9ZU \| S1 9ZW \| S1 9ZX \| S1 9ZY \| S1 9ZZ	1	£24,000
2	Egerton Street S1 4JX	137	£53,462
3	North Church Street S1 1TD \| S1 2DH	1	£65,000
4	Townhead Street S1 1YG \| S1 2EB \| S1 2ED \| S1 2EE	3	£84,000
5	Milton Street S1 4JU	5	£97,350
6	Sylvester Street S1 4RL \| S1 4RN	6	£97,813
7	Baron Street S1 4TG	1	£110,000
8	Furnival Street S1 4LG \| S1 4QS \| S1 4QT	16	£112,298
9	Leadmill Street S1 4SA	13	£112,621
10	Trafalgar Street S1 3RL \| S1 4GN \| S1 4JT \| S1 4LQ	13	£113,538

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.