ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Allandale Park

Austin, TX 78757 · 78756
Resale homes · closed Nov 8 – Nov 7, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 8, 2026 · 7:23 AM CST
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
55
single-family resale homes
Median net sale price
$877,750
average $941,923
Median net price per SF
$456
average $446
Median days on market
41 days
average 69 days
1. SummaryResale homes · 55 sales · November 8, 2025 – November 7, 2026

This study looks at the 55 resale homes sold in Allandale Park in the 365 days to November 7, 2026. A full year is used because only 23 resale homes sold in the last 180 days. New construction is left out and shown on its own in section 7. The homes are compared four ways: by price, by living area, by year built and with or without a view. The first three are split into four equal groups (quartiles), each named by its range.

Each comparison has its own section (3–6) with everything about it in one place: the key differences, a table of every measure at a glance, the charts and the numbers.

2. Where the resale homes sold55 resale homes · colored by price range

Each dot is one resale home, colored by its price range. Use the buttons to show one price range at a time. Click a dot for that sale: address, close date, original and last list price, net sale price, living area, net sale per SF and days on market. Scroll or pinch to zoom.

Under $720K · 14 sales$720K–$878K · 14 sales$880K–$978K · 13 salesOver $978K · 14 sales
3. Quartiles by net sale priceResale homes · 55 sales · November 8, 2025 – November 7, 2026

Sales ranked by net sale price and cut into four equal groups. This is the usual way to read a market by price.

2026-11-08T07:23:29.977773 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 14 13 14 55 sales Sales per group Under $720K: 14 sales (25%) $720K–$878K: 14 sales (25%) $880K–$978K: 13 sales (24%) Over $978K: 14 sales (25%)
Bottom line

3.1 Key differences

The top group against the bottom group. Only real differences are listed. Section 8 explains each measure.

Under $720K$720K–$878K$880K–$978KOver $978K
Higher-priced homes Over $978K
  • Are much larger.
Lower-priced homes Under $720K
  • Are much smaller.

3.2 At a glance

Shaded rows are real differences; the darkest cell is the highest. Gray rows show no clear difference. Prices are averages; days on market and year built are medians.

Under $720K$720K–$878K$880K–$978KOver $978KReal difference?
Net price per SF$413 per SF$449 per SF$426 per SF$496 per SFunclear
Living area1,608 SFSmallest1,871 SF2,270 SF2,729 SFLargest✓ large
Year built1961196219621964unclear
Days on market93 days11 days38 days32 daysunclear
Discount from original list8.4%3.7%8.8%6.2%unclear
Price cut before sale50%21%46%36%unclear
Seller paid closing costs or repairs21%57%46%50%unclear
Has a view7%21%0%36%unclear

How to read this section. Each heading gives the finding. The gold box says whether the gap is real (✓, with its size) or could be chance (–). The section ends with its numbers; the tests are in section 8.3.

3.3 Net price per SF: no clear difference

2026-11-08T07:23:30.010131 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $720K 14 sales $720K– $878K 14 sales $880K– $978K 13 sales Over $978K 14 sales $0 $200 $400 $413 $449 $426 $496 Net price per SF, average

The average is $496 per SF for homes over $978K and $413 per SF for homes under $720K. It does not move in a straight line; homes over $978K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $978K are about 1,120 SF (70%) larger than homes under $720K

2026-11-08T07:23:30.033782 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $720K 14 sales $720K– $878K 14 sales $880K– $978K 13 sales Over $978K 14 sales 0 1,000 2,000 3,000 1,608 1,871 2,270 2,729 Living area (SF), average

The average is 2,729 SF for homes over $978K and 1,608 SF for homes under $720K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-11-08T07:23:30.057440 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $720K 14 sales $720K– $878K 14 sales $880K– $978K 13 sales Over $978K 14 sales 1965 1980 1995 1961 1962 1962 1964 Year built: median (dot) and middle half (bar)

The median is 1964 for homes over $978K and 1961 for homes under $720K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-08T07:23:30.081744 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $720K 14 sales $720K– $878K 14 sales $880K– $978K 13 sales Over $978K 14 sales 0 50 100 93 11 38 32 Days on market, median

The median is 32 days for homes over $978K and 93 days for homes under $720K. It does not move in a straight line; homes under $720K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-08T07:23:30.104783 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $720K 14 sales $720K– $878K 14 sales $880K– $978K 13 sales Over $978K 14 sales 0.0% 5.0% 10.0% 8.4% 3.7% 8.8% 6.2% Discount from original list, average

The average is 6.2% for homes over $978K and 8.4% for homes under $720K. It does not move in a straight line; homes $880K–$978K are highest. Defined in 8.1.6.

– No clear difference · could be chance

3.8 How often: price cut before sale, seller paid closing costs or repairs, has a view

2026-11-08T07:23:30.135602 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 50% 21% 7% 21% 57% 21% 46% 46% 0% 36% 50% 36% Under $720K $720K–$878K $880K–$978K Over $978K

Each bar is the share of homes in the group, in percent.

  • 36% of homes over $978K had a price cut before sale, against 50% of homes under $720K. Defined in 8.1.7.
  • 50% of homes over $978K had the seller pay closing costs or repairs, against 21% of homes under $720K. Defined in 8.1.8.
  • 36% of homes over $978K have a view, against 7% of homes under $720K. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

3.9 The numbers: price and size

Under $720K14 sales$720K–$878K14 sales$880K–$978K13 salesOver $978K14 salesAll55 salesReal difference?
Net sale price average$650,791$813,410$937,729$1,365,460$941,923by design
Net price per SF average$413$449$426$496$446unclear
Living area average1,6081,8712,2702,7292,117✓ large
Year built median19611962196219641962unclear

3.10 The numbers: selling

Under $720K14 sales$720K–$878K14 sales$880K–$978K13 salesOver $978K14 salesAll55 salesReal difference?
Days on market median9311383241unclear
Discount from original list average8.4%3.7%8.8%6.2%6.7%unclear
Price cut before sale50%21%46%36%38%unclear
Seller paid closing costs or repairs21%57%46%50%44%unclear
Has a view7%21%0%36%16%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.1.

4. Quartiles by living areaResale homes · 55 sales · November 8, 2025 – November 7, 2026

Sales ranked by living area and cut into four equal groups, from the smallest homes to the largest.

2026-11-08T07:23:30.156486 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 14 13 14 55 sales Sales per group Under 1,710 SF: 14 sales (25%) 1,710–2,024 SF: 14 sales (25%) 2,043–2,438 SF: 13 sales (24%) Over 2,438 SF: 14 sales (25%)
Bottom line

4.1 Key differences

The top group against the bottom group. Only real differences are listed. Section 8 explains each measure.

Under 1,710 SF1,710–2,024 SF2,043–2,438 SFOver 2,438 SF
Larger homes Over 2,438 SF
  • Sell for much more.
Smaller homes Under 1,710 SF
  • Sell for much less.

4.2 At a glance

Shaded rows are real differences; the darkest cell is the highest. Gray rows show no clear difference. Prices are averages; days on market and year built are medians.

Under 1,710 SF1,710–2,024 SF2,043–2,438 SFOver 2,438 SFReal difference?
Net sale price$692KLowest$808K$956K$1.31MHighest✓ large
Net price per SF$474 per SF$431 per SF$430 per SF$450 per SFunclear
Year built1962196019621964unclear
Days on market69 days30 days31 days54 daysunclear
Discount from original list5.6%5.1%8.5%7.8%unclear
Price cut before sale43%29%46%36%unclear
Seller paid closing costs or repairs43%29%54%50%unclear
Has a view0%14%23%29%unclear

4.3 Homes over 2,438 SF sell for about $620K (90%) more than homes under 1,710 SF

2026-11-08T07:23:30.177209 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,710 SF 14 sales 1,710– 2,024 SF 14 sales 2,043– 2,438 SF 13 sales Over 2,438 SF 14 sales $0K $500K $1.00M $1.50M $692K $808K $956K $1.31M Net sale price, average

The average is $1.31M for homes over 2,438 SF and $692K for homes under 1,710 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-11-08T07:23:30.200885 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,710 SF 14 sales 1,710– 2,024 SF 14 sales 2,043– 2,438 SF 13 sales Over 2,438 SF 14 sales $0 $200 $400 $474 $431 $430 $450 Net price per SF, average

The average is $450 per SF for homes over 2,438 SF and $474 per SF for homes under 1,710 SF. It does not move in a straight line; homes under 1,710 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-08T07:23:30.223758 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,710 SF 14 sales 1,710– 2,024 SF 14 sales 2,043– 2,438 SF 13 sales Over 2,438 SF 14 sales 1965 1980 1995 1962 1960 1962 1964 Year built: median (dot) and middle half (bar)

The median is 1964 for homes over 2,438 SF and 1962 for homes under 1,710 SF. It does not move in a straight line; homes over 2,438 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-08T07:23:30.249239 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,710 SF 14 sales 1,710– 2,024 SF 14 sales 2,043– 2,438 SF 13 sales Over 2,438 SF 14 sales 0 25 50 75 69 30 31 54 Days on market, median

The median is 54 days for homes over 2,438 SF and 69 days for homes under 1,710 SF. It does not move in a straight line; homes under 1,710 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-08T07:23:30.272632 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,710 SF 14 sales 1,710– 2,024 SF 14 sales 2,043– 2,438 SF 13 sales Over 2,438 SF 14 sales 0.0% 5.0% 10.0% 5.6% 5.1% 8.5% 7.8% Discount from original list, average

The average is 7.8% for homes over 2,438 SF and 5.6% for homes under 1,710 SF. It does not move in a straight line; homes 2,043–2,438 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

4.8 How often: price cut before sale, seller paid closing costs or repairs, has a view

2026-11-08T07:23:30.299440 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 43% 43% 0% 29% 29% 14% 46% 54% 23% 36% 50% 29% Under 1,710 SF 1,710–2,024 SF 2,043–2,438 SF Over 2,438 SF

Each bar is the share of homes in the group, in percent.

  • 36% of homes over 2,438 SF had a price cut before sale, against 43% of homes under 1,710 SF. Defined in 8.1.7.
  • 50% of homes over 2,438 SF had the seller pay closing costs or repairs, against 43% of homes under 1,710 SF. Defined in 8.1.8.
  • 29% of homes over 2,438 SF have a view, against 0% of homes under 1,710 SF. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

4.9 The numbers: price and size

Under 1,710 SF14 sales1,710–2,024 SF14 sales2,043–2,438 SF13 salesOver 2,438 SF14 salesAll55 salesReal difference?
Net sale price average$692,130$808,227$956,466$1,311,907$941,923✓ large
Net price per SF average$474$431$430$450$446unclear
Living area average1,4681,8802,2292,8992,117by design
Year built median19621960196219641962unclear

4.10 The numbers: selling

Under 1,710 SF14 sales1,710–2,024 SF14 sales2,043–2,438 SF13 salesOver 2,438 SF14 salesAll55 salesReal difference?
Days on market median6930315441unclear
Discount from original list average5.6%5.1%8.5%7.8%6.7%unclear
Price cut before sale43%29%46%36%38%unclear
Seller paid closing costs or repairs43%29%54%50%44%unclear
Has a view0%14%23%29%16%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.2.

5. Quartiles by year builtResale homes · 55 sales · November 8, 2025 – November 7, 2026

Sales ranked by year built and cut into four groups, from the oldest to the newest. Homes built in the same year always stay in the same group, so group sizes can differ a little.

2026-11-08T07:23:30.322075 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 13 20 9 13 55 sales Sales per group Before 1960: 13 sales (24%) 1960–1962: 20 sales (36%) 1963–1964: 9 sales (16%) After 1964: 13 sales (24%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

The top group against the bottom group: no measure differs enough to rule out chance.

5.2 At a glance

Shaded rows are real differences; the darkest cell is the highest. Gray rows show no clear difference. Prices are averages; days on market and year built are medians.

Before 19601960–19621963–1964After 1964Real difference?
Net sale price$810K$930K$825K$1.17Munclear
Net price per SF$458 per SF$433 per SF$435 per SF$463 per SFunclear
Living area1,787 SF2,195 SF1,913 SF2,467 SFunclear
Days on market55 days41 days38 days25 daysunclear
Discount from original list6.0%8.1%6.4%5.6%unclear
Price cut before sale31%45%44%31%unclear
Seller paid closing costs or repairs31%70%11%38%unclear
Has a view8%15%22%23%unclear

5.3 Net sale price: no clear difference

2026-11-08T07:23:30.342942 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1960 13 sales 1960– 1962 20 sales 1963– 1964 9 sales After 1964 13 sales $0K $500K $1.00M $810K $930K $825K $1.17M Net sale price, average

The average is $1.17M for homes built after 1964 and $810K for homes built before 1960. It does not move in a straight line; homes built after 1964 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-08T07:23:30.366234 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1960 13 sales 1960– 1962 20 sales 1963– 1964 9 sales After 1964 13 sales $0 $200 $400 $458 $433 $435 $463 Net price per SF, average

The average is $463 per SF for homes built after 1964 and $458 per SF for homes built before 1960. It does not move in a straight line; homes built after 1964 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-08T07:23:30.388231 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1960 13 sales 1960– 1962 20 sales 1963– 1964 9 sales After 1964 13 sales 0 1,000 2,000 1,787 2,195 1,913 2,467 Living area (SF), average

The average is 2,467 SF for homes built after 1964 and 1,787 SF for homes built before 1960. It does not move in a straight line; homes built after 1964 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-08T07:23:30.409627 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1960 13 sales 1960– 1962 20 sales 1963– 1964 9 sales After 1964 13 sales 0 20 40 60 55 41 38 25 Days on market, median

The median is 25 days for homes built after 1964 and 55 days for homes built before 1960. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-08T07:23:30.434433 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1960 13 sales 1960– 1962 20 sales 1963– 1964 9 sales After 1964 13 sales 0.0% 2.5% 5.0% 7.5% 6.0% 8.1% 6.4% 5.6% Discount from original list, average

The average is 5.6% for homes built after 1964 and 6.0% for homes built before 1960. It does not move in a straight line; homes built 1960–1962 are highest. Defined in 8.1.6.

– No clear difference · could be chance

5.8 How often: price cut before sale, seller paid closing costs or repairs, has a view

2026-11-08T07:23:30.460293 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 31% 31% 8% 45% 70% 15% 44% 11% 22% 31% 38% 23% Before 1960 1960–1962 1963–1964 After 1964

Each bar is the share of homes in the group, in percent.

  • 31% of homes built after 1964 had a price cut before sale, against 31% of homes built before 1960. Defined in 8.1.7.
  • 38% of homes built after 1964 had the seller pay closing costs or repairs, against 31% of homes built before 1960. Defined in 8.1.8.
  • 23% of homes built after 1964 have a view, against 8% of homes built before 1960. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

5.9 The numbers: price and size

Before 196013 sales1960–196220 sales1963–19649 salesAfter 196413 salesAll55 salesReal difference?
Net sale price average$809,936$930,495$825,256$1,172,261$941,923unclear
Net price per SF average$458$433$435$463$446unclear
Living area average1,7872,1951,9132,4672,117unclear
Year built median19531962196319671962by design

5.10 The numbers: selling

Before 196013 sales1960–196220 sales1963–19649 salesAfter 196413 salesAll55 salesReal difference?
Days on market median5541382541unclear
Discount from original list average6.0%8.1%6.4%5.6%6.7%unclear
Price cut before sale31%45%44%31%38%unclear
Seller paid closing costs or repairs31%70%11%38%44%unclear
Has a view8%15%22%23%16%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.3.

6. View and no viewResale homes · 55 sales · November 8, 2025 – November 7, 2026

Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-11-08T07:23:30.480612 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 45 54 sales Sales per group View: 9 sales (17%) No view: 45 sales (83%)
Bottom line: no measure differs enough between the groups to rule out chance.

6.1 Key differences

The top group against the bottom group: no measure differs enough to rule out chance.

6.2 At a glance

Shaded rows are real differences; the darkest cell is the highest. Gray rows show no clear difference. Prices are averages; days on market and year built are medians.

ViewNo viewReal difference?
Net sale price$1.03M$925Kunclear
Net price per SF$442 per SF$446 per SFunclear
Living area2,315 SF2,083 SFunclear
Year built19631962unclear
Days on market23 days41 daysunclear
Discount from original list5.4%7.1%unclear
Price cut before sale44%38%unclear
Seller paid closing costs or repairs22%49%unclear

6.3 Net sale price: no clear difference

2026-11-08T07:23:30.497963 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 45 sales $0K $250K $500K $750K $1.00M $1.03M $925K Net sale price, average

The average is $1.03M for homes with a view and $925K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-11-08T07:23:30.518797 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 45 sales $0 $200 $400 $442 $446 Net price per SF, average

The average is $442 per SF for homes with a view and $446 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-11-08T07:23:30.537860 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 45 sales 0 1,000 2,000 2,315 2,083 Living area (SF), average

The average is 2,315 SF for homes with a view and 2,083 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-08T07:23:30.628920 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 45 sales 1960 1962 1964 1966 1963 1962 Year built: median (dot) and middle half (bar)

The median is 1963 for homes with a view and 1962 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-08T07:23:30.649049 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 45 sales 0 10 20 30 40 23 41 Days on market, median

The median is 23 days for homes with a view and 41 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-11-08T07:23:30.670526 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 45 sales 0.0% 2.0% 4.0% 6.0% 8.0% 5.4% 7.1% Discount from original list, average

The average is 5.4% for homes with a view and 7.1% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

6.9 How often: price cut before sale, seller paid closing costs or repairs

2026-11-08T07:23:30.690409 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 44% 22% 38% 49% View No view

Each bar is the share of homes in the group, in percent.

  • 44% of homes with a view had a price cut before sale, against 38% of homes without a view. Defined in 8.1.7.
  • 22% of homes with a view had the seller pay closing costs or repairs, against 49% of homes without a view. Defined in 8.1.8.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance

6.10 The numbers: price and size

View9 salesNo view45 salesAll54 salesReal difference?
Net sale price average$1,028,501$924,761$942,051unclear
Net price per SF average$442$446$445unclear
Living area average2,3152,0832,121unclear
Year built median196319621962unclear

6.11 The numbers: selling

View9 salesNo view45 salesAll54 salesReal difference?
Days on market median234141unclear
Discount from original list average5.4%7.1%6.8%unclear
Price cut before sale44%38%39%unclear
Seller paid closing costs or repairs22%49%44%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.4.

7. New constructionBasic statistics · 7 sales · November 8, 2025 – November 7, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 7 sales, no groups, no tests.

Note: these are only the new-construction sales reported in ABOR MLS. Builders often sell homes without listing them in the MLS, so these figures do not necessarily represent all new-construction sales in Allandale Park.
MeasureAverageMedian
Sales7
Net sale price$2,299,571$2,325,000
Net price per SF$644$644
Living area (SF)3,5743,550
Days on market115131
Discount from original list5.5%5.1%
Price cut before sale57% of sales
Seller paid closing costs or repairs0% of sales
Year built2025–2026

Same definitions as the rest of the study (section 8). New construction = NewConstructionYN true, or PropertyCondition “New Construction” or “Under Construction”.

8. AppendixMeasures, methods and tests

Each measure and method three ways: in plain words, as statistics, and with the data from this study.

8.1 Measures

8.1.1 Net sale price

In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
55 resale sales. Average $941,923; median $877,750; standard deviation $338,046; middle half (25th–75th percentile) $717,498–$980,128; lowest $450,000, highest $2,530,000. 24 sales had a seller payment; their median payment was $10,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
55 resale sales. Average $446; median $456; standard deviation $75; middle half (25th–75th percentile) $391–$496; lowest $256, highest $617.

8.1.3 Living area

In simple terms
The heated and cooled space, as listed in the MLS. Garages and porches are not counted.
Statistically
RESO LivingArea, in square feet. Sales under 400 SF are treated as entry errors and left out.
The data
55 resale sales. Average 2,117; median 2,024; standard deviation 606; middle half (25th–75th percentile) 1,704–2,460; lowest 962, highest 4,320.

8.1.4 Year built

In simple terms
The year the home was finished, as listed in the MLS. It shows whether a group leans to older or newer phases of the community.
Statistically
RESO YearBuilt; summarized by the median, with the 25th–75th percentile (middle half) on the charts.
The data
55 resale sales. Average 1965; median 1962; standard deviation 16; middle half (25th–75th percentile) 1960–1964; lowest 1950, highest 2023.

8.1.5 Days on market

In simple terms
How many days the home was on the market before the buyer's offer was accepted, counting any earlier listing periods (relists). This is the days on market agents and clients quote.
Statistically
CDOM = max(CumulativeDaysOnMarket, DaysOnMarket, PurchaseContractDate − ListingContractDate). The MLS counter can freeze at a price change, so the contract-date gap is a floor. Summarized by the median, because a few homes that sat for months pull an average up.
The data
55 resale sales. Average 69; median 41; standard deviation 96; middle half (25th–75th percentile) 8–102; lowest 1, highest 609. 0 sales went under contract on their listing date (0 days).

8.1.6 Discount from original list

In simple terms
How far below the first asking price the home sold, after seller payments. It measures how much negotiating room sellers gave up. A negative figure means the home sold above its first asking price.
Statistically
Discount % = (OriginalListPrice − Net) ÷ OriginalListPrice × 100, per sale; summarized by the mean.
The data
55 resale sales. Average 6.7%; median 5.1%; standard deviation 7.1%; middle half (25th–75th percentile) 2.1%–11.8%; lowest −6.7%, highest 20.6%. 7 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
21 of 55 resale sales (38.2%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
24 of 55 resale sales (43.6%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
9 sales with a view, 45 without, 1 unclassified. Most common View entries: None 38, Neighborhood 10, Trees/Woods 3, Creek/Stream 3, Pool 2, Garden 1, See Remarks 1, City Lights 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-08 13:15 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “allandale park”, “allandale”, “allandale terrace” (case-insensitive). A record is kept when its subdivision name belongs to the Allandale Park family, the same rule comparable sales use (it includes Allandale, Allandale Terrace, proven adjacent and priced alike).
The data
Pulled November 8, 2026: 64 closed Allandale Park records over the prior year, in ZIP 78757, 78756. 22 subdivision spellings kept, the most common: Allandale Park Sec 06 (8); Allandale Terrace Sec 03 (6); Allandale Park Sec 05 (5); Allandale Park Sec 04 (5); Allandale Park Sec 01 (5); Allandale Terrace Sec 02 Ph 04 (4); Allandale Park Sec 02 (4); Allandale (4); Allandale Sec 01 (3); Allandale Sec 03 (3); Allandale Terrace Sec 02 (3); Allandale Park Sec 09 (2); and 10 more (12 records). Names found by the search but not part of Allandale Park, left out: Allandale Estates Sec 01 (6); Allandale Oaks (6); Allandale The (4); Allandale West Sec 02 (4); Allandale West Sec 05 (3); Allandale North Sec 02 (3); Allandale North Sec 03 (3); Allandale North Sec 01 (2); Allandale West Sec 04 (2); Allandale Estates Sec 04 (2); ALLANDALE ESTATES SEC 1 (1); Allandale - Shoalmont Add Resub (1); Allandale North Sec 04 (1); Allandale Place Sec 01 (1); Allandale North/North Shoal Creek (1); Allandale West Sec 06 (1).

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 23 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 8, 2025 to November 7, 2026 inclusive.
The data
62 single-family sales in the window: 55 resale, 7 new construction.

8.2.3 Resale and new construction

In simple terms
A resale home was previously owned. New construction is sold by the builder and behaves differently, so it is kept out of every analysis and reported once on its own.
Statistically
New construction = NewConstructionYN true, or PropertyCondition contains “New Construction” or “Under Construction”. Everything else is resale.
The data
55 resale; 7 new construction.

8.2.4 Sales left out

In simple terms
A few records cannot be used as entered and are left out before any analysis.
Statistically
Excluded: PropertySubType other than Single Family Residence; no OriginalListPrice; LivingArea under 400 SF; seller payments above 10% of ClosePrice (treated as entry errors).
The data
1 sale(s) other than single-family homes (condo, townhome and similar); 1 sale(s) with no original list price

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $720K”.
Statistically
Sort by the slicing variable; cut k sits at round(nk/4), k = 1…3. A cut that would split tied values moves to the nearer edge of the tie. A group under 3 sales merges into its smaller neighbor. Range names use the next group's lowest value (“Under”) and the previous group's highest value (“Over”/“After”).
The data
Quartiles by net sale price: Under $720K: $450,000–$715,000 (14 sales); $720K–$878K: $719,997–$877,750 (14 sales); $880K–$978K: $880,000–$978,000 (13 sales); Over $978K: $982,255–$2,530,000 (14 sales)
Quartiles by living area: Under 1,710 SF: 962–1,699 SF (14 sales); 1,710–2,024 SF: 1,710–2,024 SF (14 sales); 2,043–2,438 SF: 2,043–2,438 SF (13 sales); Over 2,438 SF: 2,483–4,320 SF (14 sales)
Quartiles by year built: Before 1960: 1950–1959 (13 sales); 1960–1962: 1960–1962 (20 sales); 1963–1964: 1963–1964 (9 sales); After 1964: 1966–2023 (13 sales)
View and no view: View: MLS lists a view (9 sales); No view: None or Neighborhood (45 sales)

8.2.6 Average and median

In simple terms
The average adds the values and divides by how many; one very expensive home can pull it up. The median is the middle value, with half above and half below.
Statistically
Mean x̄ = (1/n) Σ xᵢ; median = 50th percentile. Price, price per SF, living area and discount use the mean; days on market and year built use the median (skewed or whole-year values).
The data
Net sale price: average $941,923, median $877,750. Days on market: average 69, median 41: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

In simple terms
Checks whether a measure really differs across the four groups of a slice. It uses each sale's rank, not its value, so a few extreme sales cannot drive the answer.
Statistically
H = [12/(n(n+1))] Σ Rⱼ²/nⱼ − 3(n+1), compared with χ² on k − 1 degrees of freedom (Kruskal & Wallis, 1952). Effect size ε² = H/(n − 1): ≥ .01 small, ≥ .06 medium, ≥ .14 large (Tomczak & Tomczak, 2014). A slice is tested only when every group has at least 5 sales; smaller groups are described, not tested.
The data
Run on every measure in sections 3–5; each result is in 8.3.

8.2.8 Mann–Whitney U test

In simple terms
The same check when there are only two groups: view against no view.
Statistically
Two-sided U test (Mann & Whitney, 1947). Effect size = rank-biserial correlation |1 − 2U/(n₁n₂)|: ≥ .10 small, ≥ .30 medium, ≥ .50 large (Kerby, 2014; Cohen, 1988).
The data
Run on every measure in section 6; results in 8.3.

8.2.9 Chi-square test

In simple terms
Checks whether a yes/no share (price cut, seller payment, view) differs between groups more than chance would.
Statistically
Pearson χ² on the 2 × k table of counts, no continuity correction (Pearson, 1900). Effect size Cramér's V = √(χ²/n): ≥ .10 small, ≥ .30 medium, ≥ .50 large (Cramér, 1946).
The data
Run on the three shares in every slice; results in 8.3.

8.2.10 Real difference (significance)

In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063; Quartiles by year built: m = 8, threshold p < 0.0063; View and no view: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
2 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

In simple terms
Headings and sentences round figures so they read easily; the tables at the end of each section give them in full.
Statistically
Prices in headings round to the nearest $1K; price per SF and days on market to the nearest whole number; living area to the nearest 10 SF; shares and percentage gaps to whole percents.
The data
Days on market is always shown in days.

8.3 Test results

Every test behind every gold box. Statistic, degrees of freedom (df), p-value, the threshold it must beat, and the size of the difference.

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 9.5130.0233p < 0.0063Unclearε² = 0.176large
Living areaKruskal–WallisH = 32.653< 0.0001p < 0.0063Yesε² = 0.605large
Year builtKruskal–WallisH = 3.9530.2670p < 0.0063Unclearε² = 0.073medium
Days on marketKruskal–WallisH = 6.0730.1083p < 0.0063Unclearε² = 0.112medium
Discount from original listKruskal–WallisH = 5.4430.1425p < 0.0063Unclearε² = 0.101medium
Price cut before saleChi-squareχ² = 2.8830.4106p < 0.0063UnclearCramér’s V = 0.229small
Seller paid closing costs or repairsChi-squareχ² = 4.1130.2499p < 0.0063UnclearCramér’s V = 0.273small
Has a viewChi-squareχ² = 7.5130.0574p < 0.0063UnclearCramér’s V = 0.369medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 35.093< 0.0001p < 0.0063Yesε² = 0.650large
Net price per SFKruskal–WallisH = 3.2230.3589p < 0.0063Unclearε² = 0.060small
Year builtKruskal–WallisH = 7.8930.0483p < 0.0063Unclearε² = 0.146large
Days on marketKruskal–WallisH = 1.5130.6805p < 0.0063Unclearε² = 0.028small
Discount from original listKruskal–WallisH = 2.1730.5371p < 0.0063Unclearε² = 0.040small
Price cut before saleChi-squareχ² = 1.0630.7859p < 0.0063UnclearCramér’s V = 0.139small
Seller paid closing costs or repairsChi-squareχ² = 2.0830.5566p < 0.0063UnclearCramér’s V = 0.194small
Has a viewChi-squareχ² = 4.7430.1922p < 0.0063UnclearCramér’s V = 0.293small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 7.0730.0697p < 0.0063Unclearε² = 0.131medium
Net price per SFKruskal–WallisH = 1.0430.7907p < 0.0063Unclearε² = 0.019small
Living areaKruskal–WallisH = 9.0230.0291p < 0.0063Unclearε² = 0.167large
Days on marketKruskal–WallisH = 0.1430.9864p < 0.0063Unclearε² = 0.003negligible
Discount from original listKruskal–WallisH = 1.0930.7804p < 0.0063Unclearε² = 0.020small
Price cut before saleChi-squareχ² = 1.1530.7653p < 0.0063UnclearCramér’s V = 0.145small
Seller paid closing costs or repairsChi-squareχ² = 10.5430.0145p < 0.0063UnclearCramér’s V = 0.438medium
Has a viewChi-squareχ² = 1.4030.7067p < 0.0063UnclearCramér’s V = 0.159small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 255.50—0.2230p < 0.0063Unclearrank-biserial r = 0.262small
Net price per SFMann–Whitney UU = 193.00—0.8345p < 0.0063Unclearrank-biserial r = 0.047negligible
Living areaMann–Whitney UU = 269.00—0.1255p < 0.0063Unclearrank-biserial r = 0.328medium
Year builtMann–Whitney UU = 246.00—0.3155p < 0.0063Unclearrank-biserial r = 0.215small
Days on marketMann–Whitney UU = 178.50—0.5853p < 0.0063Unclearrank-biserial r = 0.119small
Discount from original listMann–Whitney UU = 157.00—0.2963p < 0.0063Unclearrank-biserial r = 0.225small
Price cut before saleChi-squareχ² = 0.1410.7080p < 0.0063UnclearCramér’s V = 0.051negligible
Seller paid closing costs or repairsChi-squareχ² = 2.1610.1416p < 0.0063UnclearCramér’s V = 0.200small

8.4 Data notes

Left out of the analysis: 7 new-construction sales (basic statistics only, section 7); 1 sale(s) other than single-family homes (condo, townhome and similar); 1 sale(s) with no original list price. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

  1. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Erlbaum.
  2. Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press.
  3. Dunn, O. J. (1961). Multiple comparisons among means. JASA, 56(293), 52–64.
  4. Kerby, D. S. (2014). The simple difference formula: an approach to teaching nonparametric correlation. Comprehensive Psychology, 3, 11.IT.3.1.
  5. Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. JASA, 47(260), 583–621.
  6. Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18(1), 50–60.
  7. Pearson, K. (1900). On the criterion that a given system of deviations… Philosophical Magazine, 50(302), 157–175.
  8. Tomczak, M., & Tomczak, E. (2014). The need to report effect size estimates revisited. Trends in Sport Sciences, 21(1), 19–25.

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 55 closed MLS resale sales; the 7 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 8, 2026. Map data © OpenStreetMap contributors. ALEX Companies · Licensed by the Texas Real Estate Commission · Broker: Alexander Tiffany Southwest, LLC (ALEX Real Estate), #565194-BB · Diane Hart Alexander, Designated Broker, #574877-B.