ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Whispering Hollow

Buda, TX 78610
Resale homes · closed Nov 8 – Nov 7, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 8, 2026 · 7:37 AM CST
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
42
single-family resale homes
Median net sale price
$400,750
average $424,062
Median net price per SF
$178
average $182
Median days on market
40 days
average 65 days
1. SummaryResale homes · 42 sales · November 8, 2025 – November 7, 2026

This study looks at the 42 resale homes sold in Whispering Hollow in the 365 days to November 7, 2026. A full year is used because only 14 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 sold42 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 $354K · 10 sales$354K–$399K · 11 sales$402K–$461K · 11 salesOver $461K · 10 sales
3. Quartiles by net sale priceResale homes · 42 sales · November 8, 2025 – November 7, 2026

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

2026-11-08T07:37:35.045986 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 11 11 10 42 sales Sales per group Under $354K: 10 sales (24%) $354K–$399K: 11 sales (26%) $402K–$461K: 11 sales (26%) Over $461K: 10 sales (24%)
Bottom line

3.1 Key differences

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

Under $354K$354K–$399K$402K–$461KOver $461K
Higher-priced homes Over $461K
  • Are much larger.
Lower-priced homes Under $354K
  • 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 $354K$354K–$399K$402K–$461KOver $461KReal difference?
Net price per SF$206 per SF$174 per SF$174 per SF$177 per SFunclear
Living area1,667 SFSmallest2,202 SF2,569 SF3,115 SFLargest✓ large
Year built2010201020122012unclear
Days on market44 days39 days49 days30 daysunclear
Discount from original list4.3%5.8%6.9%4.3%unclear
Price cut before sale40%36%73%40%unclear
Seller paid closing costs or repairs60%73%82%70%unclear
Has a view0%27%9%50%unclear

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

3.3 Net price per SF: no clear difference

2026-11-08T07:37:35.081848 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $399K 11 sales $402K– $461K 11 sales Over $461K 10 sales $0 $100 $200 $206 $174 $174 $177 Net price per SF, average

The average is $177 per SF for homes over $461K and $206 per SF for homes under $354K. It does not move in a straight line; homes under $354K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $461K are about 1,450 SF (87%) larger than homes under $354K

2026-11-08T07:37:35.107509 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $399K 11 sales $402K– $461K 11 sales Over $461K 10 sales 0 1,000 2,000 3,000 1,667 2,202 2,569 3,115 Living area (SF), average

The average is 3,115 SF for homes over $461K and 1,667 SF for homes under $354K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-11-08T07:37:35.132119 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $399K 11 sales $402K– $461K 11 sales Over $461K 10 sales 2008 2010 2012 2014 2010 2010 2012 2012 Year built: median (dot) and middle half (bar)

The median is 2012 for homes over $461K and 2010 for homes under $354K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-08T07:37:35.156852 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $399K 11 sales $402K– $461K 11 sales Over $461K 10 sales 0 20 40 44 39 49 30 Days on market, median

The median is 30 days for homes over $461K and 44 days for homes under $354K. It does not move in a straight line; homes $402K–$461K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-08T07:37:35.179586 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $399K 11 sales $402K– $461K 11 sales Over $461K 10 sales 0.0% 2.5% 5.0% 7.5% 4.3% 5.8% 6.9% 4.3% Discount from original list, average

The average is 4.3% for homes over $461K and 4.3% for homes under $354K. It does not move in a straight line; homes $402K–$461K are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-08T07:37:35.210530 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% 40% 60% 0% 36% 73% 27% 73% 82% 9% 40% 70% 50% Under $354K $354K–$399K $402K–$461K Over $461K

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

  • 40% of homes over $461K had a price cut before sale, against 40% of homes under $354K. Defined in 8.1.7.
  • 70% of homes over $461K had the seller pay closing costs or repairs, against 60% of homes under $354K. Defined in 8.1.8.
  • 50% of homes over $461K have a view, against 0% of homes under $354K. 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 $354K10 sales$354K–$399K11 sales$402K–$461K11 salesOver $461K10 salesAll42 salesReal difference?
Net sale price average$334,672$377,693$440,523$546,349$424,062by design
Net price per SF average$206$174$174$177$182unclear
Living area average1,6672,2022,5693,1152,388✓ large
Year built median20102010201220122011unclear

3.10 The numbers: selling

Under $354K10 sales$354K–$399K11 sales$402K–$461K11 salesOver $461K10 salesAll42 salesReal difference?
Days on market median4439493040unclear
Discount from original list average4.3%5.8%6.9%4.3%5.3%unclear
Price cut before sale40%36%73%40%48%unclear
Seller paid closing costs or repairs60%73%82%70%71%unclear
Has a view0%27%9%50%21%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 · 42 sales · November 8, 2025 – November 7, 2026

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

2026-11-08T07:37:35.234932 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 11 10 11 42 sales Sales per group Under 1,880 SF: 10 sales (24%) 1,880–2,392 SF: 11 sales (26%) 2,467–2,779 SF: 10 sales (24%) Over 2,779 SF: 11 sales (26%)
Bottom line

4.1 Key differences

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

Under 1,880 SF1,880–2,392 SF2,467–2,779 SFOver 2,779 SF
Larger homes Over 2,779 SF
  • Sell for much more.
  • Sell for less per square foot.
Smaller homes Under 1,880 SF
  • Sell for much less.
  • 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 1,880 SF1,880–2,392 SF2,467–2,779 SFOver 2,779 SFReal difference?
Net sale price$346KLowest$379K$451K$516KHighest✓ large
Net price per SF$218 per SFHighest$177 per SF$171 per SF$165 per SFLowest✓ large
Year built2011201420122011unclear
Days on market20 days37 days58 days40 daysunclear
Discount from original list4.6%3.4%6.1%7.3%unclear
Price cut before sale40%27%70%55%unclear
Seller paid closing costs or repairs70%73%60%82%unclear
Has a view0%18%20%45%unclear

4.3 Homes over 2,779 SF sell for about $169K (49%) more than homes under 1,880 SF

2026-11-08T07:37:35.257579 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,880 SF 10 sales 1,880– 2,392 SF 11 sales 2,467– 2,779 SF 10 sales Over 2,779 SF 11 sales $0K $200K $400K $600K $346K $379K $451K $516K Net sale price, average

The average is $516K for homes over 2,779 SF and $346K for homes under 1,880 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 2,779 SF sell for about $53 per SF (24%) less than homes under 1,880 SF

2026-11-08T07:37:35.283869 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,880 SF 10 sales 1,880– 2,392 SF 11 sales 2,467– 2,779 SF 10 sales Over 2,779 SF 11 sales $0 $100 $200 $218 $177 $171 $165 Net price per SF, average

The average is $165 per SF for homes over 2,779 SF and $218 per SF for homes under 1,880 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

2026-11-08T07:37:35.308609 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,880 SF 10 sales 1,880– 2,392 SF 11 sales 2,467– 2,779 SF 10 sales Over 2,779 SF 11 sales 2008 2010 2012 2014 2011 2014 2012 2011 Year built: median (dot) and middle half (bar)

The median is 2011 for homes over 2,779 SF and 2011 for homes under 1,880 SF. It does not move in a straight line; homes 1,880–2,392 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-08T07:37:35.333631 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,880 SF 10 sales 1,880– 2,392 SF 11 sales 2,467– 2,779 SF 10 sales Over 2,779 SF 11 sales 0 20 40 60 20 37 58 40 Days on market, median

The median is 40 days for homes over 2,779 SF and 20 days for homes under 1,880 SF. It does not move in a straight line; homes 2,467–2,779 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-08T07:37:35.357742 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,880 SF 10 sales 1,880– 2,392 SF 11 sales 2,467– 2,779 SF 10 sales Over 2,779 SF 11 sales 0.0% 2.5% 5.0% 7.5% 4.6% 3.4% 6.1% 7.3% Discount from original list, average

The average is 7.3% for homes over 2,779 SF and 4.6% for homes under 1,880 SF. It does not move in a straight line; homes over 2,779 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-08T07:37:35.385780 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% 40% 70% 0% 27% 73% 18% 70% 60% 20% 55% 82% 45% Under 1,880 SF 1,880–2,392 SF 2,467–2,779 SF Over 2,779 SF

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

  • 55% of homes over 2,779 SF had a price cut before sale, against 40% of homes under 1,880 SF. Defined in 8.1.7.
  • 82% of homes over 2,779 SF had the seller pay closing costs or repairs, against 70% of homes under 1,880 SF. Defined in 8.1.8.
  • 45% of homes over 2,779 SF have a view, against 0% of homes under 1,880 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 1,880 SF10 sales1,880–2,392 SF11 sales2,467–2,779 SF10 salesOver 2,779 SF11 salesAll42 salesReal difference?
Net sale price average$346,112$379,103$450,775$515,599$424,062✓ large
Net price per SF average$218$177$171$165$182✓ large
Living area average1,6042,1392,6403,1222,388by design
Year built median20112014201220112011unclear

4.10 The numbers: selling

Under 1,880 SF10 sales1,880–2,392 SF11 sales2,467–2,779 SF10 salesOver 2,779 SF11 salesAll42 salesReal difference?
Days on market median2037584040unclear
Discount from original list average4.6%3.4%6.1%7.3%5.3%unclear
Price cut before sale40%27%70%55%48%unclear
Seller paid closing costs or repairs70%73%60%82%71%unclear
Has a view0%18%20%45%21%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 · 42 sales · November 8, 2025 – November 7, 2026

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

2026-11-08T07:37:35.409120 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 12 9 11 42 sales Sales per group Before 2009: 10 sales (24%) 2009–2011: 12 sales (29%) 2012–2014: 9 sales (21%) After 2014: 11 sales (26%)
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 20092009–20112012–2014After 2014Real difference?
Net sale price$400K$417K$466K$419Kunclear
Net price per SF$171 per SF$181 per SF$177 per SF$199 per SFunclear
Living area2,392 SF2,359 SF2,690 SF2,170 SFunclear
Days on market58 days46 days49 days20 daysunclear
Discount from original list6.0%5.7%6.7%3.2%unclear
Price cut before sale50%42%67%36%unclear
Seller paid closing costs or repairs70%75%67%73%unclear
Has a view10%25%44%9%unclear

5.3 Net sale price: no clear difference

2026-11-08T07:37:35.431368 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 10 sales 2009– 2011 12 sales 2012– 2014 9 sales After 2014 11 sales $0K $200K $400K $400K $417K $466K $419K Net sale price, average

The average is $419K for homes built after 2014 and $400K for homes built before 2009. It does not move in a straight line; homes built 2012–2014 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-08T07:37:35.456233 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 10 sales 2009– 2011 12 sales 2012– 2014 9 sales After 2014 11 sales $0 $100 $200 $171 $181 $177 $199 Net price per SF, average

The average is $199 per SF for homes built after 2014 and $171 per SF for homes built before 2009. It does not move in a straight line; homes built after 2014 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-08T07:37:35.478473 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 10 sales 2009– 2011 12 sales 2012– 2014 9 sales After 2014 11 sales 0 1,000 2,000 3,000 2,392 2,359 2,690 2,170 Living area (SF), average

The average is 2,170 SF for homes built after 2014 and 2,392 SF for homes built before 2009. It does not move in a straight line; homes built 2012–2014 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-08T07:37:35.501524 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 10 sales 2009– 2011 12 sales 2012– 2014 9 sales After 2014 11 sales 0 20 40 60 58 46 49 20 Days on market, median

The median is 20 days for homes built after 2014 and 58 days for homes built before 2009. It does not move in a straight line; homes built before 2009 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-08T07:37:35.525452 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 10 sales 2009– 2011 12 sales 2012– 2014 9 sales After 2014 11 sales 0.0% 2.5% 5.0% 7.5% 6.0% 5.7% 6.7% 3.2% Discount from original list, average

The average is 3.2% for homes built after 2014 and 6.0% for homes built before 2009. It does not move in a straight line; homes built 2012–2014 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-08T07:37:35.551531 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 50% 70% 10% 42% 75% 25% 67% 67% 44% 36% 73% 9% Before 2009 2009–2011 2012–2014 After 2014

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

  • 36% of homes built after 2014 had a price cut before sale, against 50% of homes built before 2009. Defined in 8.1.7.
  • 73% of homes built after 2014 had the seller pay closing costs or repairs, against 70% of homes built before 2009. Defined in 8.1.8.
  • 9% of homes built after 2014 have a view, against 10% of homes built before 2009. 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 200910 sales2009–201112 sales2012–20149 salesAfter 201411 salesAll42 salesReal difference?
Net sale price average$400,450$417,244$466,128$418,545$424,062unclear
Net price per SF average$171$181$177$199$182unclear
Living area average2,3922,3592,6902,1702,388unclear
Year built median20072010201420162011by design

5.10 The numbers: selling

Before 200910 sales2009–201112 sales2012–20149 salesAfter 201411 salesAll42 salesReal difference?
Days on market median5846492040unclear
Discount from original list average6.0%5.7%6.7%3.2%5.3%unclear
Price cut before sale50%42%67%36%48%unclear
Seller paid closing costs or repairs70%75%67%73%71%unclear
Has a view10%25%44%9%21%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 · 42 sales · November 8, 2025 – November 7, 2026

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

2026-11-08T07:37:35.571793 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 32 41 sales Sales per group View: 9 sales (22%) No view: 32 sales (78%)
Bottom line: no measure differs enough between the groups to rule out chance.

6.1 Key differences

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

6.2 At a glance

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

ViewNo viewReal difference?
Net sale price$490K$408Kunclear
Net price per SF$172 per SF$184 per SFunclear
Living area2,863 SF2,282 SFunclear
Year built20122011unclear
Days on market40 days38 daysunclear
Discount from original list5.9%5.1%unclear
Price cut before sale44%47%unclear
Seller paid closing costs or repairs89%66%unclear

6.3 Net sale price: no clear difference

2026-11-08T07:37:35.588681 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 32 sales $0K $200K $400K $490K $408K Net sale price, average

The average is $490K for homes with a view and $408K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-11-08T07:37:35.607610 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 32 sales $0 $50 $100 $150 $200 $172 $184 Net price per SF, average

The average is $172 per SF for homes with a view and $184 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-11-08T07:37:35.625795 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 32 sales 0 1,000 2,000 3,000 2,863 2,282 Living area (SF), average

The average is 2,863 SF for homes with a view and 2,282 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-08T07:37:35.711853 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 32 sales 2008 2010 2012 2014 2012 2011 Year built: median (dot) and middle half (bar)

The median is 2012 for homes with a view and 2011 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-08T07:37:35.731795 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 32 sales 0 10 20 30 40 40 38 Days on market, median

The median is 40 days for homes with a view and 38 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-11-08T07:37:35.751763 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 32 sales 0.0% 2.0% 4.0% 6.0% 5.9% 5.1% Discount from original list, average

The average is 5.9% for homes with a view and 5.1% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-08T07:37:35.769853 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 44% 89% 47% 66% View No view

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

  • 44% of homes with a view had a price cut before sale, against 47% of homes without a view. Defined in 8.1.7.
  • 89% of homes with a view had the seller pay closing costs or repairs, against 66% of homes without a view. Defined in 8.1.8.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance

6.10 The numbers: price and size

View9 salesNo view32 salesAll41 salesReal difference?
Net sale price average$489,580$408,454$426,262unclear
Net price per SF average$172$184$181unclear
Living area average2,8632,2822,409unclear
Year built median201220112011unclear

6.11 The numbers: selling

View9 salesNo view32 salesAll41 salesReal difference?
Days on market median403839unclear
Discount from original list average5.9%5.1%5.3%unclear
Price cut before sale44%47%46%unclear
Seller paid closing costs or repairs89%66%71%unclear

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

7. New constructionBasic statistics · 0 sales · November 8, 2025 – November 7, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 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 Whispering Hollow.

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
42 resale sales. Average $424,062; median $400,750; standard deviation $83,957; middle half (25th–75th percentile) $355,092–$460,200; lowest $315,000, highest $614,988. 30 sales had a seller payment; their median payment was $6,088.

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
42 resale sales. Average $182; median $178; standard deviation $28; middle half (25th–75th percentile) $163–$196; lowest $138, highest $283.

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
42 resale sales. Average 2,388; median 2,430; standard deviation 605; middle half (25th–75th percentile) 1,922–2,780; lowest 1,114, highest 3,521.

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
42 resale sales. Average 2011; median 2011; standard deviation 3; middle half (25th–75th percentile) 2009–2015; lowest 2005, 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
42 resale sales. Average 65; median 40; standard deviation 92; middle half (25th–75th percentile) 9–78; lowest 3, highest 507. 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
42 resale sales. Average 5.3%; median 5.1%; standard deviation 5.2%; middle half (25th–75th percentile) 1.5%–7.3%; lowest −3.4%, highest 18.1%. 4 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 42 resale sales (47.6%).

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
30 of 42 resale sales (71.4%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
9 sales with a view, 32 without, 1 unclassified. Most common View entries: Neighborhood 21, None 14, Park/Greenbelt 6, Trees/Woods 3, See Remarks 1, City 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-08 13:30 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Buda, SubdivisionName contains any of “whispering hollow”, “summer pointe”, “stonewood commons” (case-insensitive). A record is kept when its subdivision name belongs to the Whispering Hollow family, the same rule comparable sales use (it includes Summer Pointe, Stonewood Commons, proven adjacent and priced alike).
The data
Pulled November 8, 2026: 42 closed Whispering Hollow records over the prior year, in ZIP 78610. 19 subdivision spellings kept, the most common: Whispering Hollow Ph 1 Sec 3 (6); Whispering Hollow (4); Whispering Hollow Ph 1 Sec 1 (4); Stonewood Commons (4); Summer Pointe Sec One (3); Whispering Hollow Ph 1 Sec 7B (3); Whispering Hollow Ph I Sec 5C (2); Whispering Hollow Ph 2 Sec 3 (2); Whispering Hollow Ph I Sec 4A (2); Whispering Hollow Ph 2 Sec 4 (2); Whispering Hollow Ph Ii Sec 2 (2); Whispering Hollow Ph 02 Sec 02 (1); and 7 more (7 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 14 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 8, 2025 to November 7, 2026 inclusive.
The data
42 single-family sales in the window: 42 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
42 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 $354K”.
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 $354K: $315,000–$354,000 (10 sales); $354K–$399K: $354,290–$399,000 (11 sales); $402K–$461K: $402,500–$460,600 (11 sales); Over $461K: $468,000–$614,988 (10 sales)
Quartiles by living area: Under 1,880 SF: 1,114–1,812 SF (10 sales); 1,880–2,392 SF: 1,880–2,392 SF (11 sales); 2,467–2,779 SF: 2,467–2,779 SF (10 sales); Over 2,779 SF: 2,780–3,521 SF (11 sales)
Quartiles by year built: Before 2009: 2005–2008 (10 sales); 2009–2011: 2009–2011 (12 sales); 2012–2014: 2012–2014 (9 sales); After 2014: 2015–2016 (11 sales)
View and no view: View: MLS lists a view (9 sales); No view: None or Neighborhood (32 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 $424,062, median $400,750. Days on market: average 65, median 40: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

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

8.2.8 Mann–Whitney U test

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

8.2.9 Chi-square test

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

8.2.10 Real difference (significance)

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

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
3 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 = 8.3930.0386p < 0.0063Unclearε² = 0.205large
Living areaKruskal–WallisH = 30.043< 0.0001p < 0.0063Yesε² = 0.733large
Year builtKruskal–WallisH = 1.1530.7652p < 0.0063Unclearε² = 0.028small
Days on marketKruskal–WallisH = 0.8830.8291p < 0.0063Unclearε² = 0.022small
Discount from original listKruskal–WallisH = 3.0330.3874p < 0.0063Unclearε² = 0.074medium
Price cut before saleChi-squareχ² = 3.8030.2834p < 0.0063UnclearCramér’s V = 0.301medium
Seller paid closing costs or repairsChi-squareχ² = 1.2430.7432p < 0.0063UnclearCramér’s V = 0.172small
Has a viewChi-squareχ² = 8.7930.0322p < 0.0063UnclearCramér’s V = 0.458medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 28.703< 0.0001p < 0.0063Yesε² = 0.700large
Net price per SFKruskal–WallisH = 22.683< 0.0001p < 0.0063Yesε² = 0.553large
Year builtKruskal–WallisH = 1.8130.6135p < 0.0063Unclearε² = 0.044small
Days on marketKruskal–WallisH = 3.0230.3878p < 0.0063Unclearε² = 0.074medium
Discount from original listKruskal–WallisH = 2.0030.5727p < 0.0063Unclearε² = 0.049small
Price cut before saleChi-squareχ² = 4.2830.2330p < 0.0063UnclearCramér’s V = 0.319medium
Seller paid closing costs or repairsChi-squareχ² = 1.2430.7432p < 0.0063UnclearCramér’s V = 0.172small
Has a viewChi-squareχ² = 6.5830.0866p < 0.0063UnclearCramér’s V = 0.396medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 3.8330.2805p < 0.0063Unclearε² = 0.093medium
Net price per SFKruskal–WallisH = 5.8330.1200p < 0.0063Unclearε² = 0.142large
Living areaKruskal–WallisH = 3.4530.3278p < 0.0063Unclearε² = 0.084medium
Days on marketKruskal–WallisH = 5.1230.1636p < 0.0063Unclearε² = 0.125medium
Discount from original listKruskal–WallisH = 2.3130.5102p < 0.0063Unclearε² = 0.056small
Price cut before saleChi-squareχ² = 2.0630.5599p < 0.0063UnclearCramér’s V = 0.222small
Seller paid closing costs or repairsChi-squareχ² = 0.1930.9785p < 0.0063UnclearCramér’s V = 0.068negligible
Has a viewChi-squareχ² = 4.6930.1957p < 0.0063UnclearCramér’s V = 0.334medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 216.50—0.0233p < 0.0063Unclearrank-biserial r = 0.503large
Net price per SFMann–Whitney UU = 112.00—0.3211p < 0.0063Unclearrank-biserial r = 0.222small
Living areaMann–Whitney UU = 222.50—0.0140p < 0.0063Unclearrank-biserial r = 0.545large
Year builtMann–Whitney UU = 159.50—0.6344p < 0.0063Unclearrank-biserial r = 0.108small
Days on marketMann–Whitney UU = 126.50—0.5921p < 0.0063Unclearrank-biserial r = 0.122small
Discount from original listMann–Whitney UU = 139.00—0.8873p < 0.0063Unclearrank-biserial r = 0.035negligible
Price cut before saleChi-squareχ² = 0.0210.8972p < 0.0063UnclearCramér’s V = 0.020negligible
Seller paid closing costs or repairsChi-squareχ² = 1.8410.1754p < 0.0063UnclearCramér’s V = 0.212small

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 42 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 8, 2026. Map data © OpenStreetMap contributors. ALEX Companies · Licensed by the Texas Real Estate Commission · Broker: Alexander Tiffany Southwest, LLC (ALEX Real Estate), #565194-BB · Diane Hart Alexander, Designated Broker, #574877-B.