Avilla Apartment

Bandar Puchong Jaya, 47100 Puchong, Selangor, Malaysia

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From
RM600K
Size
800 sqft

Property Transactions

7 subsales grouped by size

Median
RM425,000
PSF
RM421
Period
transactions middle 50% (P25–P75)
950 sqft
Condo
RM408,000
Level 7
969 sqft · RM421 PSF
RM430,000
Level 10
969 sqft · RM444 PSF
RM435,000
Level 5
969 sqft · RM449 PSF
RM425,000
Level 7
969 sqft · RM439 PSF
RM405,000
Level 9
969 sqft · RM418 PSF
RM408,000
Level 11
969 sqft · RM421 PSF
1,050 sqft
Condo
RM435,000
Level 11
1,033 sqft · RM421 PSF
Legend Recent Highest Price Highest PSF

Selling in Avilla Apartment? Homes here sold for a median of RM425,000.

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Market Snapshot

Residential

RM425,000

RM421 psf

Median transaction price

Avilla Kondominium - Bandar Puchong Jaya
© OpenStreetMap · CARTO

Avilla Apartment, Bandar Puchong Jaya, 47100 Puchong, Selangor, Malaysia

Maps

Avilla Apartment in Petaling, Selangor recorded 7 subsale transactions between 2021 and 2026, with a median price of RM425K and a median price per square foot (PSF) of RM421.

This area consists exclusively of residential properties, with no commercial listings recorded.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM425K, with most transactions falling within a stable range of RM415K to RM435K, and a typical market range of RM413K to RM435K.

Most transactions involved condominium/apartment, with minimal variety in property types.

For price per square foot, the median is RM421, with most transactions between RM418 and RM424. The usual range is RM410.91 to RM431.41, showing that most units are priced quite close to each other. A typical spread (IQR) of RM20.50 and an average deviation (MAD) of RM3 indicate a highly stable PSF trend across properties.

Overall, the market in this area appears stable with consistent appreciation, making it an attractive option for both investors and homebuyers. The consistent property type and stable pricing make it easier to assess value and compare trends. Limited transaction history suggests carefully evaluating comparable sales data.