ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Post Oak

Kyle, TX 78640
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 · 5:11 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
28
single-family resale homes
Median net sale price
$241,525
average $235,063
Median net price per SF
$146
average $150
Median days on market
58 days
average 77 days
1. SummaryResale homes · 28 sales · October 26, 2025 – October 25, 2026

This study looks at the 28 resale homes sold in Post Oak in the 365 days to October 25, 2026. A full year is used because only 15 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 $224K · 7 sales$224K–$241K · 7 sales$242K–$250K · 7 salesOver $250K · 7 sales
3. Quartiles by net sale priceResale homes · 28 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.

2026-10-26T05:12:08.664506 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 7 7 28 sales Sales per group Under $224K: 7 sales (25%) $224K–$241K: 7 sales (25%) $242K–$250K: 7 sales (25%) Over $250K: 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 $224K$224K–$241K$242K–$250KOver $250KReal difference?
Net price per SF$150 per SF$145 per SF$155 per SF$148 per SFunclear
Living area1,339 SF1,638 SF1,600 SF1,812 SFunclear
Year built2007200920072014unclear
Days on market63 days61 days45 days37 daysunclear
Discount from original list19.6%9.0%6.4%7.9%unclear
Price cut before sale86%86%57%57%unclear
Seller paid closing costs or repairs43%71%71%86%unclear
Has a view0%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

2026-10-26T05:12:08.693704 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $224K 7 sales $224K– $241K 7 sales $242K– $250K 7 sales Over $250K 7 sales $0 $50 $100 $150 $150 $145 $155 $148 Net price per SF, average

The average is $148 per SF for homes over $250K and $150 per SF for homes under $224K. It does not move in a straight line; homes $242K–$250K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-26T05:12:08.716748 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $224K 7 sales $224K– $241K 7 sales $242K– $250K 7 sales Over $250K 7 sales 0 1,000 2,000 1,339 1,638 1,600 1,812 Living area (SF), average

The average is 1,812 SF for homes over $250K and 1,339 SF for homes under $224K. It does not move in a straight line; homes over $250K are highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-26T05:12:08.741193 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $224K 7 sales $224K– $241K 7 sales $242K– $250K 7 sales Over $250K 7 sales 2005 2008 2011 2014 2007 2009 2007 2014 Year built: median (dot) and middle half (bar)

The median is 2014 for homes over $250K and 2007 for homes under $224K. It does not move in a straight line; homes over $250K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:12:08.764218 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $224K 7 sales $224K– $241K 7 sales $242K– $250K 7 sales Over $250K 7 sales 0 20 40 60 63 61 45 37 Days on market, median

The median is 37 days for homes over $250K and 63 days for homes under $224K. 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

2026-10-26T05:12:08.786054 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $224K 7 sales $224K– $241K 7 sales $242K– $250K 7 sales Over $250K 7 sales 0.0% 10.0% 20.0% 19.6% 9.0% 6.4% 7.9% Discount from original list, average

The average is 7.9% for homes over $250K and 19.6% for homes under $224K. It does not move in a straight line; homes under $224K 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

2026-10-26T05:12:08.816551 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 43 0 86 71 0 57 71 14 57 86 0 Under $224K $224K–$241K $242K–$250K Over $250K

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

  • 57% of homes over $250K had a price cut before sale, against 86% of homes under $224K. Defined in 8.1.7.
  • 86% of homes over $250K had the seller pay closing costs or repairs, against 43% of homes under $224K. Defined in 8.1.8.
  • 0% of homes over $250K have a view, against 0% of homes under $224K. 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 $224K7 sales$224K–$241K7 sales$242K–$250K7 salesOver $250K7 salesAll28 salesReal difference?
Net sale price average$193,170$235,573$245,940$265,569$235,063by design
Net price per SF average$150$145$155$148$150unclear
Living area average1,3391,6381,6001,8121,597unclear
Year built median20072009200720142008unclear

3.10 The numbers: selling

Under $224K7 sales$224K–$241K7 sales$242K–$250K7 salesOver $250K7 salesAll28 salesReal difference?
Days on market median6361453758unclear
Discount from original list average19.6%9.0%6.4%7.9%10.7%unclear
Price cut before sale86%86%57%57%71%unclear
Seller paid closing costs or repairs43%71%71%86%68%unclear
Has a view0%0%14%0%4%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 · October 26, 2025 – October 25, 2026

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

2026-10-26T05:12:08.837731 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 6 7 8 28 sales Sales per group Under 1,467 SF: 7 sales (25%) 1,467–1,590 SF: 6 sales (21%) 1,616–1,704 SF: 7 sales (25%) Over 1,704 SF: 8 sales (29%)
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$211K$236K$231K$258Kunclear
Net price per SF$169 per SFHighest$157 per SF$140 per SF$136 per SFLowest✓ large
Year built2006201020082010unclear
Days on market36 days26 days54 days82 daysunclear
Discount from original list12.0%7.3%11.6%11.4%unclear
Price cut before sale86%33%71%88%unclear
Seller paid closing costs or repairs71%50%57%88%unclear
Has a view0%0%14%0%unclear

4.3 Net sale price: no clear difference

2026-10-26T05:12:08.858923 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,467 SF 7 sales 1,467– 1,590 SF 6 sales 1,616– 1,704 SF 7 sales Over 1,704 SF 8 sales $0K $100K $200K $300K $211K $236K $231K $258K Net sale price, average

The average is $258K for homes over 1,704 SF and $211K 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 $33 per SF (20%) less than homes under 1,467 SF

2026-10-26T05:12:08.882246 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,467 SF 7 sales 1,467– 1,590 SF 6 sales 1,616– 1,704 SF 7 sales Over 1,704 SF 8 sales $0 $100 $200 $169 $157 $140 $136 Net price per SF, average

The average is $136 per SF for homes over 1,704 SF and $169 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

2026-10-26T05:12:08.906365 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,467 SF 7 sales 1,467– 1,590 SF 6 sales 1,616– 1,704 SF 7 sales Over 1,704 SF 8 sales 2005 2008 2011 2014 2006 2010 2008 2010 Year built: median (dot) and middle half (bar)

The median is 2010 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

2026-10-26T05:12:08.930360 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,467 SF 7 sales 1,467– 1,590 SF 6 sales 1,616– 1,704 SF 7 sales Over 1,704 SF 8 sales 0 25 50 75 36 26 54 82 Days on market, median

The median is 82 days for homes over 1,704 SF and 36 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

2026-10-26T05:12:08.953511 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,467 SF 7 sales 1,467– 1,590 SF 6 sales 1,616– 1,704 SF 7 sales Over 1,704 SF 8 sales 0.0% 5.0% 10.0% 12.0% 7.3% 11.6% 11.4% Discount from original list, average

The average is 11.4% for homes over 1,704 SF and 12.0% 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

2026-10-26T05:12:08.980681 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 71 0 33 50 0 71 57 14 88 88 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.

  • 88% of homes over 1,704 SF had a price cut before sale, against 86% of homes under 1,467 SF. Defined in 8.1.7.
  • 88% of homes over 1,704 SF had the seller pay closing costs or repairs, against 71% of homes under 1,467 SF. Defined in 8.1.8.
  • 0% of homes over 1,704 SF have a view, against 0% 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 SF7 sales1,467–1,590 SF6 sales1,616–1,704 SF7 salesOver 1,704 SF8 salesAll28 salesReal difference?
Net sale price average$211,476$235,648$231,426$258,445$235,063unclear
Net price per SF average$169$157$140$136$150✓ large
Living area average1,2611,5091,6581,9041,597by design
Year built median20062010200820102008unclear

4.10 The numbers: selling

Under 1,467 SF7 sales1,467–1,590 SF6 sales1,616–1,704 SF7 salesOver 1,704 SF8 salesAll28 salesReal difference?
Days on market median3626548258unclear
Discount from original list average12.0%7.3%11.6%11.4%10.7%unclear
Price cut before sale86%33%71%88%71%unclear
Seller paid closing costs or repairs71%50%57%88%68%unclear
Has a view0%0%14%0%4%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 · 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.

2026-10-26T05:12:09.001662 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 8 8 6 28 sales Sales per group Before 2006: 6 sales (21%) 2006–2007: 8 sales (29%) 2008–2014: 8 sales (29%) After 2014: 6 sales (21%)
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 20062006–20072008–2014After 2014Real difference?
Net sale price$236K$224K$234K$250Kunclear
Net price per SF$152 per SF$152 per SF$151 per SF$143 per SFunclear
Living area1,569 SF1,528 SF1,567 SF1,758 SFunclear
Days on market60 days68 days30 days46 daysunclear
Discount from original list11.2%14.8%10.0%5.7%unclear
Price cut before sale67%100%62%50%unclear
Seller paid closing costs or repairs100%38%62%83%unclear
Has a view0%0%0%17%unclear

5.3 Net sale price: no clear difference

2026-10-26T05:12:09.022600 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 6 sales 2006– 2007 8 sales 2008– 2014 8 sales After 2014 6 sales $0K $100K $200K $300K $236K $224K $234K $250K Net sale price, average

The average is $250K for homes built after 2014 and $236K for homes built before 2006. It does not move in a straight line; homes built after 2014 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T05:12:09.045392 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 6 sales 2006– 2007 8 sales 2008– 2014 8 sales After 2014 6 sales $0 $50 $100 $150 $152 $152 $151 $143 Net price per SF, average

The average is $143 per SF for homes built after 2014 and $152 per SF for homes built before 2006. It does not move in a straight line; homes built 2006–2007 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T05:12:09.067030 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 6 sales 2006– 2007 8 sales 2008– 2014 8 sales After 2014 6 sales 0 1,000 2,000 1,569 1,528 1,567 1,758 Living area (SF), average

The average is 1,758 SF for homes built after 2014 and 1,569 SF for homes built before 2006. It does not move in a straight line; homes built after 2014 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T05:12:09.088476 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 6 sales 2006– 2007 8 sales 2008– 2014 8 sales After 2014 6 sales 0 25 50 75 60 68 30 46 Days on market, median

The median is 46 days for homes built after 2014 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

2026-10-26T05:12:09.111053 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 6 sales 2006– 2007 8 sales 2008– 2014 8 sales After 2014 6 sales 0.0% 5.0% 10.0% 15.0% 11.2% 14.8% 10.0% 5.7% Discount from original list, average

The average is 5.7% for homes built after 2014 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

2026-10-26T05:12:09.137096 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 62 62 0 50 83 17 Before 2006 2006–2007 2008–2014 After 2014

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

  • 50% of homes built after 2014 had a price cut before sale, against 67% of homes built before 2006. Defined in 8.1.7.
  • 83% of homes built after 2014 had the seller pay closing costs or repairs, against 100% of homes built before 2006. Defined in 8.1.8.
  • 17% of homes built after 2014 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 sales2008–20148 salesAfter 20146 salesAll28 salesReal difference?
Net sale price average$236,186$224,350$233,600$250,174$235,063unclear
Net price per SF average$152$152$151$143$150unclear
Living area average1,5691,5281,5671,7581,597unclear
Year built median20042007201220162008by design

5.10 The numbers: selling

Before 20066 sales2006–20078 sales2008–20148 salesAfter 20146 salesAll28 salesReal difference?
Days on market median6068304658unclear
Discount from original list average11.2%14.8%10.0%5.7%10.7%unclear
Price cut before sale67%100%62%50%71%unclear
Seller paid closing costs or repairs100%38%62%83%68%unclear
Has a view0%0%0%17%4%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 · 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.

2026-10-26T05:12:09.156426 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 1 27 28 sales Sales per group View: 1 sales (4%) No view: 27 sales (96%)
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

2026-10-26T05:12:09.172613 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 27 sales $0K $100K $200K $242K $235K Net sale price, average

The average is $242K for homes with a view and $235K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T05:12:09.190041 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 27 sales $0 $50 $100 $150 $146 $150 Net price per SF, average

The average is $146 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

2026-10-26T05:12:09.207782 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 27 sales 0 500 1,000 1,500 1,664 1,595 Living area (SF), average

The average is 1,664 SF for homes with a view and 1,595 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T05:12:09.312501 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 27 sales 2008 2011 2014 2016 2007 Year built: median (dot) and middle half (bar)

The median is 2016 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

2026-10-26T05:12:09.332666 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 27 sales 0 25 50 75 100 85 54 Days on market, median

The median is 85 days for homes with a view and 54 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

2026-10-26T05:12:09.352438 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 27 sales 0.0% 5.0% 10.0% 8.5% 10.8% Discount from original list, average

The average is 8.5% for homes with a view and 10.8% 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

2026-10-26T05:12:09.371573 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 100 100 70 67 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 70% of homes without a view. Defined in 8.1.7.
  • 100% of homes with a view had the seller pay closing costs or repairs, against 67% 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

View1 salesNo view27 salesAll28 sales
Net sale price average$242,450$234,789$235,063
Net price per SF average$146$150$150
Living area average1,6641,5951,597
Year built median201620072008

6.11 The numbers: selling

View1 salesNo view27 salesAll28 sales
Days on market median855458
Discount from original list average8.5%10.8%10.7%
Price cut before sale100%70%71%
Seller paid closing costs or repairs100%67%68%

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 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 $235,063; median $241,525; standard deviation $29,973; middle half (25th–75th percentile) $223,400–$251,225; lowest $160,000, highest $294,000. 19 sales had a seller payment; their median payment was $8,000.

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
28 resale sales. Average $150; median $146; standard deviation $21; middle half (25th–75th percentile) $140–$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 1,597; median 1,616; standard deviation 272; middle half (25th–75th percentile) 1,460–1,755; lowest 1,002, highest 2,096.

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 5; 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 77; median 58; standard deviation 78; middle half (25th–75th percentile) 29–87; 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 10.7%; median 9.7%; standard deviation 9.6%; middle half (25th–75th percentile) 4.8%–12.8%; 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
19 of 28 resale sales (67.9%).

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
1 sales with a view, 27 without, 0 unclassified. Most common View entries: None 17, Neighborhood 10, Rural 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 = Kyle, SubdivisionName contains any of “post oak”, “post oak sub” (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 October 26, 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 5A (2); Post Oak Ph 4a (1); Post Oak Ph 4A (1); Post Oak Ph 02 (1); Post Oak Ph 4B (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 15 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 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 $224K”.
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 $224K: $160,000–$223,100 (7 sales); $224K–$241K: $223,500–$240,600 (7 sales); $242K–$250K: $242,450–$250,000 (7 sales); Over $250K: $254,900–$294,000 (7 sales)
Quartiles by living area: Under 1,467 SF: 1,002–1,439 SF (7 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: 1,755–2,096 SF (8 sales)
Quartiles by year built: Before 2006: 2003–2005 (6 sales); 2006–2007: 2006–2007 (8 sales); 2008–2014: 2008–2014 (8 sales); After 2014: 2015–2016 (6 sales)
View and no view: View: MLS lists a view (1 sales); No view: None or Neighborhood (27 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 $235,063, median $241,525. Days on market: average 77, median 58: 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 = 1.8530.6047p < 0.0063Unclearε² = 0.068medium
Living areaKruskal–WallisH = 10.3830.0156p < 0.0063Unclearε² = 0.384large
Year builtKruskal–WallisH = 3.4830.3229p < 0.0063Unclearε² = 0.129medium
Days on marketKruskal–WallisH = 0.1230.9893p < 0.0063Unclearε² = 0.004negligible
Discount from original listKruskal–WallisH = 5.0830.1662p < 0.0063Unclearε² = 0.188large
Price cut before saleChi-squareχ² = 2.8030.4235p < 0.0063UnclearCramér’s V = 0.316medium
Seller paid closing costs or repairsChi-squareχ² = 3.1130.3748p < 0.0063UnclearCramér’s V = 0.333medium
Has a viewChi-squareχ² = 3.1130.3748p < 0.0063UnclearCramér’s V = 0.333medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 11.1630.0109p < 0.0063Unclearε² = 0.413large
Net price per SFKruskal–WallisH = 14.0430.0029p < 0.0063Yesε² = 0.520large
Year builtKruskal–WallisH = 4.1230.2485p < 0.0063Unclearε² = 0.153large
Days on marketKruskal–WallisH = 3.5430.3151p < 0.0063Unclearε² = 0.131medium
Discount from original listKruskal–WallisH = 4.5130.2112p < 0.0063Unclearε² = 0.167large
Price cut before saleChi-squareχ² = 5.9830.1126p < 0.0063UnclearCramér’s V = 0.462medium
Seller paid closing costs or repairsChi-squareχ² = 2.7030.4399p < 0.0063UnclearCramér’s V = 0.311medium
Has a viewChi-squareχ² = 3.1130.3748p < 0.0063UnclearCramér’s V = 0.333medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 1.5430.6733p < 0.0063Unclearε² = 0.057small
Net price per SFKruskal–WallisH = 1.3130.7270p < 0.0063Unclearε² = 0.048small
Living areaKruskal–WallisH = 2.8430.4177p < 0.0063Unclearε² = 0.105medium
Days on marketKruskal–WallisH = 3.7830.2861p < 0.0063Unclearε² = 0.140large
Discount from original listKruskal–WallisH = 4.4830.2141p < 0.0063Unclearε² = 0.166large
Price cut before saleChi-squareχ² = 4.9330.1771p < 0.0063UnclearCramér’s V = 0.420medium
Seller paid closing costs or repairsChi-squareχ² = 6.9930.0723p < 0.0063UnclearCramér’s V = 0.500medium
Has a viewChi-squareχ² = 3.8030.2836p < 0.0063UnclearCramér’s V = 0.369medium

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 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.