ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Post Oak

Kyle, TX 78640
Resale homes · closed Nov 5 – Nov 4, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 5, 2026 · 2:41 PM 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
28
single-family resale homes
Median net sale price
$240,300
average $230,377
Median net price per SF
$149
average $150
Median days on market
50 days
average 74 days
1. SummaryResale homes · 28 sales · November 5, 2025 – November 4, 2026

This study looks at the 28 resale homes sold in Post Oak in the 365 days to November 4, 2026. A full year is used because only 16 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 sold28 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 $223K · 7 sales$223K–$240K · 7 sales$241K–$248K · 7 salesOver $248K · 7 sales
3. Quartiles by net sale priceResale homes · 28 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T14:41:54.576895 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 7 7 28 sales Sales per group Under $223K: 7 sales (25%) $223K–$240K: 7 sales (25%) $241K–$248K: 7 sales (25%) Over $248K: 7 sales (25%)
Bottom line: no measure differs enough between the groups to rule out chance.

3.1 Key differences

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

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 $223K$223K–$240K$241K–$248KOver $248KReal difference?
Net price per SF$150 per SF$150 per SF$154 per SF$146 per SFunclear
Living area1,280 SF1,562 SF1,601 SF1,793 SFunclear
Year built2007200820072012unclear
Days on market63 days54 days45 days37 daysunclear
Discount from original list20.2%9.2%5.8%9.2%unclear
Price cut before sale86%86%57%57%unclear
Seller paid closing costs or repairs29%86%57%86%unclear
Has a view14%0%14%0%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

2026-11-05T14:41:54.605485 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $223K 7 sales $223K– $240K 7 sales $241K– $248K 7 sales Over $248K 7 sales $0 $50 $100 $150 $150 $150 $154 $146 Net price per SF, average

The average is $146 per SF for homes over $248K and $150 per SF for homes under $223K. It does not move in a straight line; homes $241K–$248K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-11-05T14:41:54.627779 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $223K 7 sales $223K– $240K 7 sales $241K– $248K 7 sales Over $248K 7 sales 0 1,000 2,000 1,280 1,562 1,601 1,793 Living area (SF), average

The average is 1,793 SF for homes over $248K and 1,280 SF for homes under $223K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-11-05T14:41:54.651832 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $223K 7 sales $223K– $240K 7 sales $241K– $248K 7 sales Over $248K 7 sales 2005 2008 2011 2014 2007 2008 2007 2012 Year built: median (dot) and middle half (bar)

The median is 2012 for homes over $248K and 2007 for homes under $223K. It does not move in a straight line; homes over $248K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-05T14:41:54.674399 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $223K 7 sales $223K– $240K 7 sales $241K– $248K 7 sales Over $248K 7 sales 0 20 40 60 63 54 45 37 Days on market, median

The median is 37 days for homes over $248K and 63 days for homes under $223K. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-05T14:41:54.695651 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $223K 7 sales $223K– $240K 7 sales $241K– $248K 7 sales Over $248K 7 sales 0.0% 10.0% 20.0% 20.2% 9.2% 5.8% 9.2% Discount from original list, average

The average is 9.2% for homes over $248K and 20.2% for homes under $223K. It does not move in a straight line; homes under $223K 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

2026-11-05T14:41:54.725541 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% 86 29 14 86 86 0 57 57 14 57 86 0 Under $223K $223K–$240K $241K–$248K Over $248K

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

  • 57% of homes over $248K had a price cut before sale, against 86% of homes under $223K. Defined in 8.1.7.
  • 86% of homes over $248K had the seller pay closing costs or repairs, against 29% of homes under $223K. Defined in 8.1.8.
  • 0% of homes over $248K have a view, against 14% of homes under $223K. 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 $223K7 sales$223K–$240K7 sales$241K–$248K7 salesOver $248K7 salesAll28 salesReal difference?
Net sale price average$184,556$233,073$244,597$259,283$230,377by design
Net price per SF average$150$150$154$146$150unclear
Living area average1,2801,5621,6011,7931,559unclear
Year built median20072008200720122008unclear

3.10 The numbers: selling

Under $223K7 sales$223K–$240K7 sales$241K–$248K7 salesOver $248K7 salesAll28 salesReal difference?
Days on market median6354453750unclear
Discount from original list average20.2%9.2%5.8%9.2%11.1%unclear
Price cut before sale86%86%57%57%71%unclear
Seller paid closing costs or repairs29%86%57%86%64%unclear
Has a view14%0%14%0%7%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 · 28 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T14:41:54.746735 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 6 7 7 28 sales Sales per group Under 1,467 SF: 8 sales (29%) 1,467–1,590 SF: 6 sales (21%) 1,616–1,704 SF: 7 sales (25%) Over 1,704 SF: 7 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 1,467 SF1,467–1,590 SF1,616–1,704 SFOver 1,704 SF
Larger homes Over 1,704 SF
  • Sell for less per square foot.
Smaller homes Under 1,467 SF
  • Sell for more per square foot.

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 1,467 SF1,467–1,590 SF1,616–1,704 SFOver 1,704 SFReal difference?
Net sale price$205K$236K$231K$253Kunclear
Net price per SF$168 per SFHighest$157 per SF$140 per SF$135 per SFLowest✓ large
Year built2006201020082009unclear
Days on market35 days26 days54 days72 daysunclear
Discount from original list12.8%7.3%11.6%11.9%unclear
Price cut before sale88%33%71%86%unclear
Seller paid closing costs or repairs62%50%57%86%unclear
Has a view12%0%14%0%unclear

4.3 Net sale price: no clear difference

2026-11-05T14:41:54.767592 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,467 SF 8 sales 1,467– 1,590 SF 6 sales 1,616– 1,704 SF 7 sales Over 1,704 SF 7 sales $0K $100K $200K $300K $205K $236K $231K $253K Net sale price, average

The average is $253K for homes over 1,704 SF and $205K for homes under 1,467 SF. It does not move in a straight line; homes over 1,704 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Homes over 1,704 SF sell for about $32 per SF (19%) less than homes under 1,467 SF

2026-11-05T14:41:54.790979 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,467 SF 8 sales 1,467– 1,590 SF 6 sales 1,616– 1,704 SF 7 sales Over 1,704 SF 7 sales $0 $100 $200 $168 $157 $140 $135 Net price per SF, average

The average is $135 per SF for homes over 1,704 SF and $168 per SF for homes under 1,467 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-11-05T14:41:54.816273 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,467 SF 8 sales 1,467– 1,590 SF 6 sales 1,616– 1,704 SF 7 sales Over 1,704 SF 7 sales 2005 2008 2011 2014 2006 2010 2008 2009 Year built: median (dot) and middle half (bar)

The median is 2009 for homes over 1,704 SF and 2006 for homes under 1,467 SF. It does not move in a straight line; homes 1,467–1,590 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-05T14:41:54.841807 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,467 SF 8 sales 1,467– 1,590 SF 6 sales 1,616– 1,704 SF 7 sales Over 1,704 SF 7 sales 0 25 50 75 35 26 54 72 Days on market, median

The median is 72 days for homes over 1,704 SF and 35 days for homes under 1,467 SF. It does not move in a straight line; homes over 1,704 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-05T14:41:54.865731 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,467 SF 8 sales 1,467– 1,590 SF 6 sales 1,616– 1,704 SF 7 sales Over 1,704 SF 7 sales 0.0% 5.0% 10.0% 15.0% 12.8% 7.3% 11.6% 11.9% Discount from original list, average

The average is 11.9% for homes over 1,704 SF and 12.8% for homes under 1,467 SF. It does not move in a straight line; homes under 1,467 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

2026-11-05T14:41:54.893692 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% 88 62 12 33 50 0 71 57 14 86 86 0 Under 1,467 SF 1,467–1,590 SF 1,616–1,704 SF Over 1,704 SF

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

  • 86% of homes over 1,704 SF had a price cut before sale, against 88% of homes under 1,467 SF. Defined in 8.1.7.
  • 86% of homes over 1,704 SF had the seller pay closing costs or repairs, against 62% of homes under 1,467 SF. Defined in 8.1.8.
  • 0% of homes over 1,704 SF have a view, against 12% of homes under 1,467 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 1,467 SF8 sales1,467–1,590 SF6 sales1,616–1,704 SF7 salesOver 1,704 SF7 salesAll28 salesReal difference?
Net sale price average$205,391$235,648$231,426$253,366$230,377unclear
Net price per SF average$168$157$140$135$150✓ large
Living area average1,2321,5091,6581,8771,559by design
Year built median20062010200820092008unclear

4.10 The numbers: selling

Under 1,467 SF8 sales1,467–1,590 SF6 sales1,616–1,704 SF7 salesOver 1,704 SF7 salesAll28 salesReal difference?
Days on market median3526547250unclear
Discount from original list average12.8%7.3%11.6%11.9%11.1%unclear
Price cut before sale88%33%71%86%71%unclear
Seller paid closing costs or repairs62%50%57%86%64%unclear
Has a view12%0%14%0%7%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 · 28 sales · November 5, 2025 – November 4, 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.

2026-11-05T14:41:54.916620 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 8 6 8 28 sales Sales per group Before 2006: 6 sales (21%) 2006–2007: 8 sales (29%) 2008–2013: 6 sales (21%) After 2013: 8 sales (29%)
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 20062006–20072008–2013After 2013Real difference?
Net sale price$236K$224K$216K$242Kunclear
Net price per SF$152 per SF$152 per SF$142 per SF$154 per SFunclear
Living area1,569 SF1,528 SF1,546 SF1,593 SFunclear
Days on market60 days68 days48 days24 daysunclear
Discount from original list11.2%14.8%14.3%4.9%unclear
Price cut before sale67%100%83%38%unclear
Seller paid closing costs or repairs100%38%50%75%unclear
Has a view0%0%17%12%unclear

5.3 Net sale price: no clear difference

2026-11-05T14:41:54.938393 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 6 sales 2006– 2007 8 sales 2008– 2013 6 sales After 2013 8 sales $0K $100K $200K $236K $224K $216K $242K Net sale price, average

The average is $242K for homes built after 2013 and $236K for homes built before 2006. It does not move in a straight line; homes built after 2013 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-05T14:41:54.961295 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 6 sales 2006– 2007 8 sales 2008– 2013 6 sales After 2013 8 sales $0 $50 $100 $150 $152 $152 $142 $154 Net price per SF, average

The average is $154 per SF for homes built after 2013 and $152 per SF for homes built before 2006. It does not move in a straight line; homes built after 2013 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-05T14:41:54.982899 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 6 sales 2006– 2007 8 sales 2008– 2013 6 sales After 2013 8 sales 0 500 1,000 1,500 1,569 1,528 1,546 1,593 Living area (SF), average

The average is 1,593 SF for homes built after 2013 and 1,569 SF for homes built before 2006. It does not move in a straight line; homes built after 2013 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-05T14:41:55.004408 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 6 sales 2006– 2007 8 sales 2008– 2013 6 sales After 2013 8 sales 0 25 50 75 60 68 48 24 Days on market, median

The median is 24 days for homes built after 2013 and 60 days for homes built before 2006. It does not move in a straight line; homes built 2006–2007 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-05T14:41:55.026309 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 6 sales 2006– 2007 8 sales 2008– 2013 6 sales After 2013 8 sales 0.0% 5.0% 10.0% 15.0% 11.2% 14.8% 14.3% 4.9% Discount from original list, average

The average is 4.9% for homes built after 2013 and 11.2% for homes built before 2006. It does not move in a straight line; homes built 2006–2007 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

2026-11-05T14:41:55.051558 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% 67 100 0 100 38 0 83 50 17 38 75 12 Before 2006 2006–2007 2008–2013 After 2013

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

  • 38% of homes built after 2013 had a price cut before sale, against 67% of homes built before 2006. Defined in 8.1.7.
  • 75% of homes built after 2013 had the seller pay closing costs or repairs, against 100% of homes built before 2006. Defined in 8.1.8.
  • 12% of homes built after 2013 have a view, against 0% of homes built before 2006. 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 20066 sales2006–20078 sales2008–20136 salesAfter 20138 salesAll28 salesReal difference?
Net sale price average$236,186$224,350$216,484$242,468$230,377unclear
Net price per SF average$152$152$142$154$150unclear
Living area average1,5691,5281,5461,5931,559unclear
Year built median20042007201020162008by design

5.10 The numbers: selling

Before 20066 sales2006–20078 sales2008–20136 salesAfter 20138 salesAll28 salesReal difference?
Days on market median6068482450unclear
Discount from original list average11.2%14.8%14.3%4.9%11.1%unclear
Price cut before sale67%100%83%38%71%unclear
Seller paid closing costs or repairs100%38%50%75%64%unclear
Has a view0%0%17%12%7%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 · 28 sales · November 5, 2025 – November 4, 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.

2026-11-05T14:41:55.069798 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 2 26 28 sales Sales per group View: 2 sales (7%) No view: 26 sales (93%)
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

2026-11-05T14:41:55.085502 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 26 sales $0K $100K $200K $203K $233K Net sale price, average

The average is $203K for homes with a view and $233K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-11-05T14:41:55.102317 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 26 sales $0 $50 $100 $150 $152 $150 Net price per SF, average

The average is $152 per SF for homes with a view and $150 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-11-05T14:41:55.119209 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 26 sales 0 500 1,000 1,500 1,348 1,575 Living area (SF), average

The average is 1,348 SF for homes with a view and 1,575 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-11-05T14:41:55.161321 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 26 sales 2006 2008 2010 2012 2014 2013 2007 Year built: median (dot) and middle half (bar)

The median is 2013 for homes with a view and 2007 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-11-05T14:41:55.179026 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 26 sales 0 20 40 60 54 50 Days on market, median

The median is 54 days for homes with a view and 50 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

2026-11-05T14:41:55.196697 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 26 sales 0.0% 5.0% 10.0% 15.0% 13.5% 10.9% Discount from original list, average

The average is 13.5% for homes with a view and 10.9% 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

2026-11-05T14:41:55.214940 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 100 50 69 65 View No view

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

  • 100% of homes with a view had a price cut before sale, against 69% of homes without a view. Defined in 8.1.7.
  • 50% of homes with a view had the seller pay closing costs or repairs, against 65% 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

View2 salesNo view26 salesAll28 sales
Net sale price average$202,625$232,512$230,377
Net price per SF average$152$150$150
Living area average1,3481,5751,559
Year built median201320072008

6.11 The numbers: selling

View2 salesNo view26 salesAll28 sales
Days on market median545050
Discount from original list average13.5%10.9%11.1%
Price cut before sale100%69%71%
Seller paid closing costs or repairs50%65%64%

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 · November 5, 2025 – November 4, 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 Post Oak.

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
28 resale sales. Average $230,377; median $240,300; standard deviation $30,666; middle half (25th–75th percentile) $220,575–$248,747; lowest $160,000, highest $266,000. 18 sales had a seller payment; their median payment was $8,155.

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
28 resale sales. Average $150; median $149; standard deviation $21; middle half (25th–75th percentile) $142–$162; lowest $94, highest $196.

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
28 resale sales. Average 1,559; median 1,603; standard deviation 274; middle half (25th–75th percentile) 1,439–1,717; lowest 1,002, highest 1,991.

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
28 resale sales. Average 2009; median 2008; standard deviation 4; middle half (25th–75th percentile) 2006–2014; lowest 2003, highest 2016.

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
28 resale sales. Average 74; median 50; standard deviation 78; middle half (25th–75th percentile) 25–82; lowest 0, highest 327. 1 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
28 resale sales. Average 11.1%; median 10.0%; standard deviation 9.7%; middle half (25th–75th percentile) 4.8%–13.7%; lowest 0.0%, highest 44.8%. 0 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
20 of 28 resale sales (71.4%).

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
18 of 28 resale sales (64.3%).

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
2 sales with a view, 26 without, 0 unclassified. Most common View entries: None 16, Neighborhood 10, Rural 1, Pasture 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 2026-11-05 20:30 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Kyle, SubdivisionName contains any of “post oak” (case-insensitive). A record is kept when its subdivision name belongs to the Post Oak family, the same rule comparable sales use.
The data
Pulled November 5, 2026: 28 closed Post Oak records over the prior year, in ZIP 78640. 11 subdivision spellings kept: Post Oak Ph 3 (6); Post Oak Ph One (5); Post Oak (4); Post Oak Sub Ph 6 (3); Post Oak Ph 2 (3); Post Oak Ph 4A (2); Post Oak Ph 5a (1); Post Oak Ph 02 (1); Post Oak Ph 4B (1); Post Oak Ph 4a (1); Post Oak Ph 5A (1). 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 16 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 5, 2025 to November 4, 2026 inclusive.
The data
28 single-family sales in the window: 28 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
28 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
None in this window.

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 $223K”.
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 $223K: $160,000–$213,000 (7 sales); $223K–$240K: $223,100–$240,000 (7 sales); $241K–$248K: $240,600–$248,329 (7 sales); Over $248K: $250,000–$266,000 (7 sales)
Quartiles by living area: Under 1,467 SF: 1,002–1,439 SF (8 sales); 1,467–1,590 SF: 1,467–1,590 SF (6 sales); 1,616–1,704 SF: 1,616–1,704 SF (7 sales); Over 1,704 SF: 1,755–1,991 SF (7 sales)
Quartiles by year built: Before 2006: 2003–2005 (6 sales); 2006–2007: 2006–2007 (8 sales); 2008–2013: 2008–2013 (6 sales); After 2013: 2014–2016 (8 sales)
View and no view: View: MLS lists a view (2 sales); No view: None or Neighborhood (26 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 $230,377, median $240,300. Days on market: average 74, median 50: 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
1 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 = 1.3730.7116p < 0.0063Unclearε² = 0.051small
Living areaKruskal–WallisH = 10.9330.0121p < 0.0063Unclearε² = 0.405large
Year builtKruskal–WallisH = 0.9330.8181p < 0.0063Unclearε² = 0.034small
Days on marketKruskal–WallisH = 0.0730.9955p < 0.0063Unclearε² = 0.002negligible
Discount from original listKruskal–WallisH = 5.6330.1308p < 0.0063Unclearε² = 0.209large
Price cut before saleChi-squareχ² = 2.8030.4235p < 0.0063UnclearCramér’s V = 0.316medium
Seller paid closing costs or repairsChi-squareχ² = 6.8430.0770p < 0.0063UnclearCramér’s V = 0.494medium
Has a viewChi-squareχ² = 2.1530.5411p < 0.0063UnclearCramér’s V = 0.277small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 10.9230.0122p < 0.0063Unclearε² = 0.404large
Net price per SFKruskal–WallisH = 14.1330.0027p < 0.0063Yesε² = 0.523large
Year builtKruskal–WallisH = 3.0230.3890p < 0.0063Unclearε² = 0.112medium
Days on marketKruskal–WallisH = 3.1430.3704p < 0.0063Unclearε² = 0.116medium
Discount from original listKruskal–WallisH = 5.1630.1604p < 0.0063Unclearε² = 0.191large
Price cut before saleChi-squareχ² = 5.9830.1126p < 0.0063UnclearCramér’s V = 0.462medium
Seller paid closing costs or repairsChi-squareχ² = 2.1030.5519p < 0.0063UnclearCramér’s V = 0.274small
Has a viewChi-squareχ² = 1.8830.5967p < 0.0063UnclearCramér’s V = 0.259small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 2.1630.5400p < 0.0063Unclearε² = 0.080medium
Net price per SFKruskal–WallisH = 1.6830.6410p < 0.0063Unclearε² = 0.062medium
Living areaKruskal–WallisH = 0.6930.8753p < 0.0063Unclearε² = 0.026small
Days on marketKruskal–WallisH = 6.9030.0753p < 0.0063Unclearε² = 0.255large
Discount from original listKruskal–WallisH = 8.1930.0422p < 0.0063Unclearε² = 0.303large
Price cut before saleChi-squareχ² = 8.2030.0421p < 0.0063UnclearCramér’s V = 0.541large
Seller paid closing costs or repairsChi-squareχ² = 6.7730.0797p < 0.0063UnclearCramér’s V = 0.492medium
Has a viewChi-squareχ² = 2.2430.5234p < 0.0063UnclearCramér’s V = 0.283small

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); nothing else. 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 28 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 November 5, 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.