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Prospective homebuyers had a range of options in various neighborhoods throughout the region between Jan. 6 and Jan. 12. We've compiled recent property sales in Town of Clay and Liverpool, focusing on homes under $300,000.
Below are the top five properties in each area, chosen for their proximity to the desired price range and largest living spaces. Please note that these properties were recorded during the week of Jan. 6, even if they may have been sold earlier.
1. $285K, 3 bedrooms / 2 baths
A single-family residence at 210 Seventh Street was sold in December for $285,000 ($178 per square foot). The home spans 1,600 square feet with three bedrooms and two bathrooms on a 20,520-square-foot lot. The deal was finalized on Dec. 18.
2. $275K, 4 bedrooms / 3 bathrooms
This single-family home at 4950 Darien Drive sold in December for $275,000 ($153 per square foot). The property features four bedrooms and three baths, a living area of 1,792 square feet, and an 11,700-square-foot lot. The deal was finalized on Dec. 18.
3. $261K, 3 bedrooms / 3 bathrooms
Priced at $261,000 ($172 per square foot), this single-family residence at 5316 Teramo Circle was sold in December. The home spans 1,520 square feet with three bedrooms and three baths on a 7,910-square-foot lot. The deal was finalized on Dec. 17.
4. $260K, 4 bedrooms / 2 baths
At $260,000 ($161 per square foot), the single-family residence at 124 Sotherden Drive offered another opportunity below the targeted price range when it changed hands in December. This property provides 1,616 square feet of living space with four bedrooms and two bathrooms on a 10,140-square-foot lot. The deal was finalized on Dec. 19.
5. $250K, 3 bedrooms / 2 bathrooms
This single-family home at 62 Cherry Tree Circle sold in December for $250,000 ($183 per square foot). The property features three bedrooms and two bathrooms, a living area of 1,364 square feet, and a 7,708-square-foot lot. The deal was finalized on Dec. 18.
Real Estate Newswire is a service provided by United Robots, which uses machine learning to generate analysis of data from Propmix, an aggregator of national real-estate data.
