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Most and least expensive streets

Birmingham, B5

Birmingham, B5 has a total of 140 streets. The most expensive street in B5 is Albert Street, with an average sale price of £34,677,240. The least expensive street in B5 is Cley Close, with an average sale price of £20,200.

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Most expensive streets

Rank	Street	Transactions (Past 5 years)	Average price
1	Albert Street B5 5JT \| B5 5LG	1	£34,677,240
2	Smallbrook Queensway B5 4EG \| B5 4EN \| B5 4EW \| B5 4HA \| B5 4HE \| B5 4HP \| B5 4HQ \| B5 4HX \| B5 4JL \| B5 4LJ	1	£20,000,000
3	Fazeley Street B5 5RD \| B5 5RF \| B5 5RR \| B5 5RS \| B5 5RT \| B5 5RX \| B5 5SE	2	£7,242,746
4	Pershore Street B5 4RU \| B5 4RW \| B5 6ND \| B5 6PA \| B5 6UA \| B5 6UB \| B5 6UD \| B5 6UE \| B5 6UL \| B5 6UN \| B5 6UQ \| B5 6UU	1	£4,375,000
5	Bristol Road B5 7SL \| B5 7SN \| B5 7SP \| B5 7SQ \| B5 7SR \| B5 7SS \| B5 7SW \| B5 7TA \| B5 7TS \| B5 7TT \| B5 7TU \| B5 7TX \| B5 7UA \| B5 7UB \| B5 7UH \| B5 7XG \| B5 7XH \| B5 7XJ \| B5 7XT \| B5 7XU \| B5 7XX	55	£4,230,129
6	Gooch Street North B5 6QU	1	£3,900,000
7	Station Street B5 4AL \| B5 4DS \| B5 4DY	1	£3,020,000
8	Bristol Street B5 7AA \| B5 7AF \| B5 7AH \| B5 7AP \| B5 7AY \| B5 7AZ \| B5 7BE	1	£3,000,000
9	Macdonald Street B5 6RL \| B5 6TG \| B5 6TN	1	£2,500,000
10	Bellevue B5 7LX	1	£2,490,000

Least expensive streets

Rank	Street	Transactions (Past 5 years)	Average price
1	Cley Close B5 7XF	1	£20,200
2	Ladywell Walk B5 4ST	1	£39,000
3	Bullring B5 4BA \| B5 4BE \| B5 4BF \| B5 4BG \| B5 4BL \| B5 4BP \| B5 4BS \| B5 4BT \| B5 4BU	1	£50,000
4	Caraway Road B5 7RF	6	£63,759
5	Lenchs Green B5 7PX	2	£67,750
6	Foster Way B5 7QJ	3	£95,333
7	Murrell Close B5 7LZ \| B5 7NA \| B5 7NB	1	£99,950
8	Dollery Drive B5 7TD \| B5 7TE \| B5 7TF \| B5 7TG	3	£100,833
9	Hodnet Grove B5 7DG	1	£115,000
10	Dalloway Close B5 7RD	1	£122,000

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.