Clos Islwyn

Swansea, Abertawe - Swansea, Wales

Residential Mixed character Car + some transport Risk: Low Growth pocket Medium confidence

Reality check: At £275,000, this is a premium entry point. Strong 20% growth over 5 years supports the investment case.

Who Is This Street For?

Scored by profile based on what matters most to each group.

Best fit: InvestorsGood

Strong case: 20% 5-year growth.

Families
Fair

Weak across environment (35), safety (60), or school access (45). Not ideal for children.

How this is calculated

Safety 30%, Schools 30%, Environment 20%, Amenities 10%, Energy 10%

Young Professionals
Fair

Limited connectivity (transport 40, walkability 60). May not suit a commuting lifestyle.

How this is calculated

Transport 35%, Walkability 30%, Amenities 25%, Market 10%

Investors
Good

Strong case: 20% 5-year growth.

How this is calculated

Liquidity 35%, Market 35%, Price trend bonus up to +30

Retirees
Fair

Good with limitations — safe, walkable. But environment (35) suggests noise or density, limited nearby services (30).

How this is calculated

Safety 25%, Environment 25%, Amenities 20%, Energy 15%, Walkability 15%

First-time Buyers
Below Average

Price (£275,000) and connectivity (transport 40) both limit appeal for first-time buyers.

How this is calculated

Affordability 40%, Transport 25%, Amenities 20%, Safety 15%

51
Liveability Score
Top 16% in SwanseaTop 34% nationally
Medium confidence Based on 5 data sources, 6 transactions

How Life Works Here

Clos Islwyn is located in Swansea, near Abertawe / Swansea, Abertawe - Swansea. Crime levels are below the local average (62 incidents in 12 months). Some amenities are available nearby, though a car may be useful for regular errands like grocery shopping. The nearest transport stop is 124m away (bus). Rail links may require a connecting journey. The median property price is £275,000, with strong growth of 20% over five years. Based on 6 transactions recorded since 2014. The local area has a moderate population, with larger households suggesting families. This street may particularly suit property investors. Overall, this street scores 51 out of 100 for liveability, placing it in the top 16% within its district.

Nearby Services (5 km)

Score Breakdown

Each dimension scored 0-100 from open government data. Source listed under each bar.

Safety Good (60)

police.uk crime data (12-month rolling)

Daily Access Below Average (30)

OpenStreetMap amenities within 2km

Transport Below Average (40)

DfT NaPTAN + TfL stops

Environment Below Average (35)

DEFRA noise & air quality, OS green space

Market Value Excellent (75)

HM Land Registry price paid data

Family Fair (45)

GIAS schools + Ofsted ratings

Walkability Good (60)

OSM footpath density + connectivity

Energy Data pending

EPC Register — awaiting public API access

Flood Risk Excellent (90)

Environment Agency flood zones

Property Market

£275,000
Median Price
6
Transactions (2015–2024)
+20.4%
5-Year Price Trend

Detached | Freehold | Market: stable

Based on 6 transactions. Moderate sample — prices may not fully represent current market value.

Source: HM Land Registry Price Paid Data (Open Government Licence v3.0)

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Public Services Nearby

Public facilities within walking distance from Clos Islwyn, with detailed information for each.

parks & green spaces (3)

Transport Links

Lamb Lane bus_stop124m
Byron Way bus_stop150m
Tennyson Way bus_stop156m
Lon Alfa bus_stop220m
Gwelfor bus_stop306m

Similar Streets

Data Transparency

5 open data sources
62% data uniqueness
View all data sources
  • OS Open Roads — Crown copyright and database right
  • HM Land Registry Price Paid Data — Crown copyright
  • police.uk crime data — Open Government Licence v3.0
  • OpenStreetMap — ODbL licence
  • DfT NaPTAN — Open Government Licence v3.0
  • GIAS schools data — Crown copyright
  • Environment Agency flood data — OGL v3.0
  • DEFRA noise and air quality — OGL v3.0
  • ONS Census 2021 — Open Government Licence v3.0

All scores are computed from publicly available government and open data. No proprietary data is used. Scores reflect statistical patterns, not guarantees.