ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Texas Oaks

Austin, TX 78748
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 7:45 AM CDT
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
36
single-family resale homes
Median net sale price
$387,250
average $400,247
Median net price per SF
$253
average $251
Median days on market
48 days
average 66 days
1. SummaryResale homes · 36 sales · October 26, 2025 – October 25, 2026

This study looks at the 36 resale homes sold in Texas Oaks in the 365 days to October 25, 2026. A full year is used because only 18 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 sold36 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 $358K · 9 sales$358K–$384K · 9 sales$390K–$427K · 9 salesOver $427K · 9 sales
3. Quartiles by net sale priceResale homes · 36 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:45:49.814398 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 9 9 9 36 sales Sales per group Under $358K: 9 sales (25%) $358K–$384K: 9 sales (25%) $390K–$427K: 9 sales (25%) Over $427K: 9 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 $358K$358K–$384K$390K–$427KOver $427K
Higher-priced homes Over $427K
  • Are much larger.
Lower-priced homes Under $358K
  • 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 $358K$358K–$384K$390K–$427KOver $427KReal difference?
Net price per SF$229 per SF$265 per SF$244 per SF$264 per SFunclear
Living area1,451 SF1,444 SFSmallest1,719 SF1,930 SFLargest✓ large
Year built1986198619871982unclear
Days on market68 days30 days68 days50 daysunclear
Discount from original list9.8%4.1%5.0%6.4%unclear
Price cut before sale67%33%44%44%unclear
Seller paid closing costs or repairs33%100%78%89%unclear
Has a view11%0%0%33%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

2026-10-26T07:45:49.842316 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $358K 9 sales $358K– $384K 9 sales $390K– $427K 9 sales Over $427K 9 sales $0 $100 $200 $300 $229 $265 $244 $264 Net price per SF, average

The average is $264 per SF for homes over $427K and $229 per SF for homes under $358K. It does not move in a straight line; homes $358K–$384K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $427K are about 480 SF (33%) larger than homes under $358K

2026-10-26T07:45:49.863921 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $358K 9 sales $358K– $384K 9 sales $390K– $427K 9 sales Over $427K 9 sales 0 1,000 2,000 1,451 1,444 1,719 1,930 Living area (SF), average

The average is 1,930 SF for homes over $427K and 1,451 SF for homes under $358K. It does not move in a straight line; homes over $427K are highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-26T07:45:49.888539 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $358K 9 sales $358K– $384K 9 sales $390K– $427K 9 sales Over $427K 9 sales 1982 1984 1986 1988 1990 1986 1986 1987 1982 Year built: median (dot) and middle half (bar)

The median is 1982 for homes over $427K and 1986 for homes under $358K. It does not move in a straight line; homes $390K–$427K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:45:49.911092 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $358K 9 sales $358K– $384K 9 sales $390K– $427K 9 sales Over $427K 9 sales 0 25 50 75 68 30 68 50 Days on market, median

The median is 50 days for homes over $427K and 68 days for homes under $358K. It does not move in a straight line; homes under $358K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:45:49.932801 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $358K 9 sales $358K– $384K 9 sales $390K– $427K 9 sales Over $427K 9 sales 0.0% 5.0% 10.0% 9.8% 4.1% 5.0% 6.4% Discount from original list, average

The average is 6.4% for homes over $427K and 9.8% for homes under $358K. It does not move in a straight line; homes under $358K 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

2026-10-26T07:45:49.962160 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% 67 33 11 33 100 0 44 78 0 44 89 33 Under $358K $358K–$384K $390K–$427K Over $427K

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

  • 44% of homes over $427K had a price cut before sale, against 67% of homes under $358K. Defined in 8.1.7.
  • 89% of homes over $427K had the seller pay closing costs or repairs, against 33% of homes under $358K. Defined in 8.1.8.
  • 33% of homes over $427K have a view, against 11% of homes under $358K. 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 $358K9 sales$358K–$384K9 sales$390K–$427K9 salesOver $427K9 salesAll36 salesReal difference?
Net sale price average$310,944$374,922$411,422$503,698$400,247by design
Net price per SF average$229$265$244$264$251unclear
Living area average1,4511,4441,7191,9301,636✓ large
Year built median19861986198719821986unclear

3.10 The numbers: selling

Under $358K9 sales$358K–$384K9 sales$390K–$427K9 salesOver $427K9 salesAll36 salesReal difference?
Days on market median6830685048unclear
Discount from original list average9.8%4.1%5.0%6.4%6.3%unclear
Price cut before sale67%33%44%44%47%unclear
Seller paid closing costs or repairs33%100%78%89%75%unclear
Has a view11%0%0%33%11%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 · 36 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:45:49.982081 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 9 9 9 36 sales Sales per group Under 1,379 SF: 9 sales (25%) 1,379–1,627 SF: 9 sales (25%) 1,667–1,872 SF: 9 sales (25%) Over 1,872 SF: 9 sales (25%)
Bottom line: no measure differs enough between the groups to rule out chance.

4.1 Key differences

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

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 1,379 SF1,379–1,627 SF1,667–1,872 SFOver 1,872 SFReal difference?
Net sale price$352K$381K$412K$456Kunclear
Net price per SF$293 per SF$254 per SF$230 per SF$226 per SFunclear
Year built1986198619851989unclear
Days on market24 days68 days87 days50 daysunclear
Discount from original list2.6%6.5%8.4%7.7%unclear
Price cut before sale22%44%67%56%unclear
Seller paid closing costs or repairs56%89%67%89%unclear
Has a view11%0%11%22%unclear

4.3 Net sale price: no clear difference

2026-10-26T07:45:50.002265 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,379 SF 9 sales 1,379– 1,627 SF 9 sales 1,667– 1,872 SF 9 sales Over 1,872 SF 9 sales $0K $200K $400K $352K $381K $412K $456K Net sale price, average

The average is $456K for homes over 1,872 SF and $352K for homes under 1,379 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-10-26T07:45:50.023940 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,379 SF 9 sales 1,379– 1,627 SF 9 sales 1,667– 1,872 SF 9 sales Over 1,872 SF 9 sales $0 $100 $200 $300 $293 $254 $230 $226 Net price per SF, average

The average is $226 per SF for homes over 1,872 SF and $293 per SF for homes under 1,379 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:45:50.048583 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,379 SF 9 sales 1,379– 1,627 SF 9 sales 1,667– 1,872 SF 9 sales Over 1,872 SF 9 sales 1982 1984 1986 1988 1990 1986 1986 1985 1989 Year built: median (dot) and middle half (bar)

The median is 1989 for homes over 1,872 SF and 1986 for homes under 1,379 SF. It does not move in a straight line; homes over 1,872 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:45:50.071544 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,379 SF 9 sales 1,379– 1,627 SF 9 sales 1,667– 1,872 SF 9 sales Over 1,872 SF 9 sales 0 50 100 24 68 87 50 Days on market, median

The median is 50 days for homes over 1,872 SF and 24 days for homes under 1,379 SF. It does not move in a straight line; homes 1,667–1,872 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:45:50.092911 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,379 SF 9 sales 1,379– 1,627 SF 9 sales 1,667– 1,872 SF 9 sales Over 1,872 SF 9 sales 0.0% 5.0% 10.0% 2.6% 6.5% 8.4% 7.7% Discount from original list, average

The average is 7.7% for homes over 1,872 SF and 2.6% for homes under 1,379 SF. It does not move in a straight line; homes 1,667–1,872 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

2026-10-26T07:45:50.118445 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% 22 56 11 44 89 0 67 67 11 56 89 22 Under 1,379 SF 1,379–1,627 SF 1,667–1,872 SF Over 1,872 SF

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

  • 56% of homes over 1,872 SF had a price cut before sale, against 22% of homes under 1,379 SF. Defined in 8.1.7.
  • 89% of homes over 1,872 SF had the seller pay closing costs or repairs, against 56% of homes under 1,379 SF. Defined in 8.1.8.
  • 22% of homes over 1,872 SF have a view, against 11% of homes under 1,379 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 1,379 SF9 sales1,379–1,627 SF9 sales1,667–1,872 SF9 salesOver 1,872 SF9 salesAll36 salesReal difference?
Net sale price average$351,906$380,856$412,347$455,878$400,247unclear
Net price per SF average$293$254$230$226$251unclear
Living area average1,2201,5061,7972,0211,636by design
Year built median19861986198519891986unclear

4.10 The numbers: selling

Under 1,379 SF9 sales1,379–1,627 SF9 sales1,667–1,872 SF9 salesOver 1,872 SF9 salesAll36 salesReal difference?
Days on market median2468875048unclear
Discount from original list average2.6%6.5%8.4%7.7%6.3%unclear
Price cut before sale22%44%67%56%47%unclear
Seller paid closing costs or repairs56%89%67%89%75%unclear
Has a view11%0%11%22%11%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 · 36 sales · October 26, 2025 – October 25, 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.

2026-10-26T07:45:50.138687 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 12 7 8 36 sales Sales per group Before 1984: 9 sales (25%) 1984–1986: 12 sales (33%) 1987–1989: 7 sales (19%) After 1989: 8 sales (22%)
Bottom line

5.1 Key differences

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

Before 19841984–19861987–1989After 1989
Newer homes After 1989
  • Are much smaller.
Older homes Before 1984
  • Are much larger.

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 19841984–19861987–1989After 1989Real difference?
Net sale price$434K$367K$420K$395Kunclear
Net price per SF$232 per SF$262 per SF$294 per SF$218 per SFunclear
Living area1,867 SFLargest1,422 SFSmallest1,473 SF1,839 SF✓ large
Days on market50 days28 days30 days114 daysunclear
Discount from original list6.4%6.0%3.1%9.5%unclear
Price cut before sale44%42%29%75%unclear
Seller paid closing costs or repairs67%75%86%75%unclear
Has a view11%0%43%0%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:45:50.159513 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 9 sales 1984– 1986 12 sales 1987– 1989 7 sales After 1989 8 sales $0K $200K $400K $434K $367K $420K $395K Net sale price, average

The average is $395K for homes built after 1989 and $434K for homes built before 1984. It does not move in a straight line; homes built before 1984 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:45:50.181517 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 9 sales 1984– 1986 12 sales 1987– 1989 7 sales After 1989 8 sales $0 $100 $200 $300 $232 $262 $294 $218 Net price per SF, average

The average is $218 per SF for homes built after 1989 and $232 per SF for homes built before 1984. It does not move in a straight line; homes built 1987–1989 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Homes built after 1989 are about 30 SF (1%) smaller than homes built before 1984

2026-10-26T07:45:50.202979 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 9 sales 1984– 1986 12 sales 1987– 1989 7 sales After 1989 8 sales 0 1,000 2,000 1,867 1,422 1,473 1,839 Living area (SF), average

The average is 1,839 SF for homes built after 1989 and 1,867 SF for homes built before 1984. It does not move in a straight line; homes built before 1984 are highest. Defined in 8.1.3.

✓ Real difference · large

5.6 Days on market: no clear difference

2026-10-26T07:45:50.225301 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 9 sales 1984– 1986 12 sales 1987– 1989 7 sales After 1989 8 sales 0 50 100 50 28 30 114 Days on market, median

The median is 114 days for homes built after 1989 and 50 days for homes built before 1984. It does not move in a straight line; homes built after 1989 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:45:50.247075 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 9 sales 1984– 1986 12 sales 1987– 1989 7 sales After 1989 8 sales 0.0% 5.0% 10.0% 6.4% 6.0% 3.1% 9.5% Discount from original list, average

The average is 9.5% for homes built after 1989 and 6.4% for homes built before 1984. It does not move in a straight line; homes built after 1989 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

2026-10-26T07:45:50.272302 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% 44 67 11 42 75 0 29 86 43 75 75 0 Before 1984 1984–1986 1987–1989 After 1989

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

  • 75% of homes built after 1989 had a price cut before sale, against 44% of homes built before 1984. Defined in 8.1.7.
  • 75% of homes built after 1989 had the seller pay closing costs or repairs, against 67% of homes built before 1984. Defined in 8.1.8.
  • 0% of homes built after 1989 have a view, against 11% of homes built before 1984. 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 19849 sales1984–198612 sales1987–19897 salesAfter 19898 salesAll36 salesReal difference?
Net sale price average$434,162$366,546$420,232$395,156$400,247unclear
Net price per SF average$232$262$294$218$251unclear
Living area average1,8671,4221,4731,8391,636✓ large
Year built median19821986198819911986by design

5.10 The numbers: selling

Before 19849 sales1984–198612 sales1987–19897 salesAfter 19898 salesAll36 salesReal difference?
Days on market median50283011448unclear
Discount from original list average6.4%6.0%3.1%9.5%6.3%unclear
Price cut before sale44%42%29%75%47%unclear
Seller paid closing costs or repairs67%75%86%75%75%unclear
Has a view11%0%43%0%11%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 · 36 sales · October 26, 2025 – October 25, 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.

2026-10-26T07:45:50.290696 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 31 35 sales Sales per group View: 4 sales (11%) No view: 31 sales (89%)
Bottom line: too few sales to test.

6.1 Key differences

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

6.3 Net sale price: described, not tested

2026-10-26T07:45:50.306478 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 31 sales $0K $200K $400K $479K $391K Net sale price, average

The average is $479K for homes with a view and $391K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T07:45:50.323453 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 31 sales $0 $100 $200 $300 $315 $243 Net price per SF, average

The average is $315 per SF for homes with a view and $243 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T07:45:50.385806 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 31 sales 0 500 1,000 1,500 1,601 1,639 Living area (SF), average

The average is 1,601 SF for homes with a view and 1,639 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T07:45:50.404077 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 31 sales 1984 1986 1988 1988 1986 Year built: median (dot) and middle half (bar)

The median is 1988 for homes with a view and 1986 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T07:45:50.421782 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 31 sales 0 20 40 60 80 14 67 Days on market, median

The median is 14 days for homes with a view and 67 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-26T07:45:50.440084 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 31 sales 0.0% 2.0% 4.0% 6.0% 2.9% 6.4% Discount from original list, average

The average is 2.9% for homes with a view and 6.4% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T07:45:50.458741 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 0 75 52 74 View No view

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

  • 0% of homes with a view had a price cut before sale, against 52% of homes without a view. Defined in 8.1.7.
  • 75% of homes with a view had the seller pay closing costs or repairs, against 74% of homes without a view. Defined in 8.1.8.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View4 salesNo view31 salesAll35 sales
Net sale price average$479,056$390,663$400,765
Net price per SF average$315$243$251
Living area average1,6011,6391,635
Year built median198819861986

6.11 The numbers: selling

View4 salesNo view31 salesAll35 sales
Days on market median146747
Discount from original list average2.9%6.4%6.0%
Price cut before sale0%52%46%
Seller paid closing costs or repairs75%74%74%

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 · 0 sales · October 26, 2025 – October 25, 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: 0 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 Texas Oaks.

No new-construction sales were reported in ABOR MLS in this window.

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
36 resale sales. Average $400,247; median $387,250; standard deviation $79,862; middle half (25th–75th percentile) $356,875–$429,000; lowest $261,000, highest $616,223. 27 sales had a seller payment; their median payment was $6,000.

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
36 resale sales. Average $251; median $253; standard deviation $53; middle half (25th–75th percentile) $217–$283; lowest $144, highest $396.

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
36 resale sales. Average 1,636; median 1,647; standard deviation 327; middle half (25th–75th percentile) 1,377–1,875; lowest 795, highest 2,205.

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
36 resale sales. Average 1986; median 1986; standard deviation 3; middle half (25th–75th percentile) 1984–1989; lowest 1981, highest 1993.

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
36 resale sales. Average 66; median 48; standard deviation 70; middle half (25th–75th percentile) 12–90; lowest 2, highest 307. 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
36 resale sales. Average 6.3%; median 5.8%; standard deviation 8.0%; middle half (25th–75th percentile) 0.2%–10.9%; lowest −16.0%, highest 22.7%. 6 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
17 of 36 resale sales (47.2%).

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
27 of 36 resale sales (75.0%).

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
4 sales with a view, 31 without, 1 unclassified. Most common View entries: None 26, Neighborhood 6, See Remarks 2, Park/Greenbelt 2, Trees/Woods 2, Creek/Stream 1, Hill Country 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
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “texas oaks” (case-insensitive). A record is kept when its subdivision name belongs to the Texas Oaks family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 37 closed Texas Oaks records over the prior year, in ZIP 78748. 14 subdivision spellings kept, the most common: Texas Oaks (12); Texas Oaks 02 (5); Texas Oaks 05 (5); Texas Oaks 07-B (3); Texas Oaks 10 (2); Texas Oaks 09 (2); Texas Oaks Sec 07-C (1); Texas Oaks 06 (1); TEXAS OAKS SEC 7 C (1); Texas Oaks Sec 09 (1); TEXAS OAKS 10 (1); Texas Oaks Sec 08-B (1); and 2 more (2 records). No other names were found by the search.

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 18 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
36 single-family sales in the window: 36 resale, 0 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
36 resale; 0 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) 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 $358K”.
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 $358K: $261,000–$352,000 (9 sales); $358K–$384K: $358,500–$384,500 (9 sales); $390K–$427K: $390,000–$427,000 (9 sales); Over $427K: $435,000–$616,223 (9 sales)
Quartiles by living area: Under 1,379 SF: 795–1,372 SF (9 sales); 1,379–1,627 SF: 1,379–1,627 SF (9 sales); 1,667–1,872 SF: 1,667–1,872 SF (9 sales); Over 1,872 SF: 1,884–2,205 SF (9 sales)
Quartiles by year built: Before 1984: 1981–1982 (9 sales); 1984–1986: 1984–1986 (12 sales); 1987–1989: 1987–1989 (7 sales); After 1989: 1990–1993 (8 sales)
View and no view: View: MLS lists a view (4 sales); No view: None or Neighborhood (31 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 $400,247, median $387,250. Days on market: average 66, median 48: 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

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 = 4.3130.2299p < 0.0063Unclearε² = 0.123medium
Living areaKruskal–WallisH = 14.9030.0019p < 0.0063Yesε² = 0.426large
Year builtKruskal–WallisH = 1.0530.7887p < 0.0063Unclearε² = 0.030small
Days on marketKruskal–WallisH = 1.9730.5793p < 0.0063Unclearε² = 0.056small
Discount from original listKruskal–WallisH = 3.5830.3100p < 0.0063Unclearε² = 0.102medium
Price cut before saleChi-squareχ² = 2.1230.5484p < 0.0063UnclearCramér’s V = 0.243small
Seller paid closing costs or repairsChi-squareχ² = 12.3030.0064p < 0.0063UnclearCramér’s V = 0.584large
Has a viewChi-squareχ² = 6.7530.0803p < 0.0063UnclearCramér’s V = 0.433medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 11.0730.0113p < 0.0063Unclearε² = 0.316large
Net price per SFKruskal–WallisH = 9.9530.0190p < 0.0063Unclearε² = 0.284large
Year builtKruskal–WallisH = 0.6430.8865p < 0.0063Unclearε² = 0.018small
Days on marketKruskal–WallisH = 4.6730.1979p < 0.0063Unclearε² = 0.133medium
Discount from original listKruskal–WallisH = 6.8030.0785p < 0.0063Unclearε² = 0.194large
Price cut before saleChi-squareχ² = 3.9030.2724p < 0.0063UnclearCramér’s V = 0.329medium
Seller paid closing costs or repairsChi-squareχ² = 4.0030.2615p < 0.0063UnclearCramér’s V = 0.333medium
Has a viewChi-squareχ² = 2.2530.5222p < 0.0063UnclearCramér’s V = 0.250small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 4.6130.2031p < 0.0063Unclearε² = 0.132medium
Net price per SFKruskal–WallisH = 8.0430.0453p < 0.0063Unclearε² = 0.230large
Living areaKruskal–WallisH = 15.5630.0014p < 0.0063Yesε² = 0.445large
Days on marketKruskal–WallisH = 4.5030.2125p < 0.0063Unclearε² = 0.128medium
Discount from original listKruskal–WallisH = 3.7430.2912p < 0.0063Unclearε² = 0.107medium
Price cut before saleChi-squareχ² = 3.6330.3043p < 0.0063UnclearCramér’s V = 0.318medium
Seller paid closing costs or repairsChi-squareχ² = 0.7630.8586p < 0.0063UnclearCramér’s V = 0.145small
Has a viewChi-squareχ² = 9.6430.0219p < 0.0063UnclearCramér’s V = 0.518large

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 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 36 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 26, 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.