ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Woodcreek

Wimberley, TX 78676
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 · 7:19 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
69
single-family resale homes
Median net sale price
$447,250
average $463,310
Median net price per SF
$245
average $242
Median days on market
64 days
average 95 days
1. SummaryResale homes · 69 sales · November 8, 2025 – November 7, 2026

This study looks at the 69 resale homes sold in Woodcreek in the 365 days to November 7, 2026. A full year is used because only 34 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 sold69 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 $384K · 17 sales$384K–$442K · 17 sales$447K–$515K · 18 salesOver $515K · 17 sales
3. Quartiles by net sale priceResale homes · 69 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.

2026-11-08T07:19:50.989604 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 17 17 18 17 69 sales Sales per group Under $384K: 17 sales (25%) $384K–$442K: 17 sales (25%) $447K–$515K: 18 sales (26%) Over $515K: 17 sales (25%)
Bottom line

3.1 Key differences

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

Under $384K$384K–$442K$447K–$515KOver $515K
Higher-priced homes Over $515K
  • Are much larger.
Lower-priced homes Under $384K
  • 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 $384K$384K–$442K$447K–$515KOver $515KReal difference?
Net price per SF$243 per SF$228 per SF$240 per SF$258 per SFunclear
Living area1,382 SFSmallest1,880 SF1,999 SF2,484 SFLargest✓ large
Year built2014200320162001unclear
Days on market70 days48 days72 days49 daysunclear
Discount from original list8.6%9.1%7.0%6.0%unclear
Price cut before sale47%53%44%41%unclear
Seller paid closing costs or repairs76%47%83%53%unclear
Has a view76%88%61%94%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

2026-11-08T07:19:51.018332 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $384K 17 sales $384K– $442K 17 sales $447K– $515K 18 sales Over $515K 17 sales $0 $100 $200 $300 $243 $228 $240 $258 Net price per SF, average

The average is $258 per SF for homes over $515K and $243 per SF for homes under $384K. It does not move in a straight line; homes over $515K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $515K are about 1,100 SF (80%) larger than homes under $384K

2026-11-08T07:19:51.041780 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $384K 17 sales $384K– $442K 17 sales $447K– $515K 18 sales Over $515K 17 sales 0 1,000 2,000 1,382 1,880 1,999 2,484 Living area (SF), average

The average is 2,484 SF for homes over $515K and 1,382 SF for homes under $384K. 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

2026-11-08T07:19:51.066883 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $384K 17 sales $384K– $442K 17 sales $447K– $515K 18 sales Over $515K 17 sales 1992 1998 2004 2010 2016 2014 2003 2016 2001 Year built: median (dot) and middle half (bar)

The median is 2001 for homes over $515K and 2014 for homes under $384K. It does not move in a straight line; homes $447K–$515K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-08T07:19:51.090688 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $384K 17 sales $384K– $442K 17 sales $447K– $515K 18 sales Over $515K 17 sales 0 25 50 75 70 48 72 49 Days on market, median

The median is 49 days for homes over $515K and 70 days for homes under $384K. It does not move in a straight line; homes $447K–$515K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-08T07:19:51.113187 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $384K 17 sales $384K– $442K 17 sales $447K– $515K 18 sales Over $515K 17 sales 0.0% 5.0% 10.0% 8.6% 9.1% 7.0% 6.0% Discount from original list, average

The average is 6.0% for homes over $515K and 8.6% for homes under $384K. It does not move in a straight line; homes $384K–$442K 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

2026-11-08T07:19:51.142230 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% 47% 76% 76% 53% 47% 88% 44% 83% 61% 41% 53% 94% Under $384K $384K–$442K $447K–$515K Over $515K

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

  • 41% of homes over $515K had a price cut before sale, against 47% of homes under $384K. Defined in 8.1.7.
  • 53% of homes over $515K had the seller pay closing costs or repairs, against 76% of homes under $384K. Defined in 8.1.8.
  • 94% of homes over $515K have a view, against 76% of homes under $384K. 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 $384K17 sales$384K–$442K17 sales$447K–$515K18 salesOver $515K17 salesAll69 salesReal difference?
Net sale price average$329,012$409,220$474,398$639,957$463,310by design
Net price per SF average$243$228$240$258$242unclear
Living area average1,3821,8801,9992,4841,937✓ large
Year built median20142003201620012007unclear

3.10 The numbers: selling

Under $384K17 sales$384K–$442K17 sales$447K–$515K18 salesOver $515K17 salesAll69 salesReal difference?
Days on market median7048724964unclear
Discount from original list average8.6%9.1%7.0%6.0%7.7%unclear
Price cut before sale47%53%44%41%46%unclear
Seller paid closing costs or repairs76%47%83%53%65%unclear
Has a view76%88%61%94%80%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 · 69 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.

2026-11-08T07:19:51.162866 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 17 17 18 17 69 sales Sales per group Under 1,551 SF: 17 sales (25%) 1,551–1,826 SF: 17 sales (25%) 1,864–2,181 SF: 18 sales (26%) Over 2,181 SF: 17 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 1,551 SF1,551–1,826 SF1,864–2,181 SFOver 2,181 SF
Larger homes Over 2,181 SF
  • Sell for much more.
Smaller homes Under 1,551 SF
  • Sell for much less.

4.2 At a glance

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

Under 1,551 SF1,551–1,826 SF1,864–2,181 SFOver 2,181 SFReal difference?
Net sale price$342KLowest$414K$499K$597KHighest✓ large
Net price per SF$257 per SF$242 per SF$246 per SF$225 per SFunclear
Year built2014200220152001unclear
Days on market67 days31 days48 days126 daysunclear
Discount from original list7.6%6.3%6.5%10.3%unclear
Price cut before sale47%41%44%53%unclear
Seller paid closing costs or repairs65%71%61%65%unclear
Has a view71%82%78%88%unclear

4.3 Homes over 2,181 SF sell for about $255K (75%) more than homes under 1,551 SF

2026-11-08T07:19:51.183556 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,551 SF 17 sales 1,551– 1,826 SF 17 sales 1,864– 2,181 SF 18 sales Over 2,181 SF 17 sales $0K $200K $400K $600K $342K $414K $499K $597K Net sale price, average

The average is $597K for homes over 2,181 SF and $342K for homes under 1,551 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-11-08T07:19:51.206656 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,551 SF 17 sales 1,551– 1,826 SF 17 sales 1,864– 2,181 SF 18 sales Over 2,181 SF 17 sales $0 $100 $200 $300 $257 $242 $246 $225 Net price per SF, average

The average is $225 per SF for homes over 2,181 SF and $257 per SF for homes under 1,551 SF. It does not move in a straight line; homes under 1,551 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-08T07:19:51.230852 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,551 SF 17 sales 1,551– 1,826 SF 17 sales 1,864– 2,181 SF 18 sales Over 2,181 SF 17 sales 1992 2000 2008 2016 2014 2002 2015 2001 Year built: median (dot) and middle half (bar)

The median is 2001 for homes over 2,181 SF and 2014 for homes under 1,551 SF. It does not move in a straight line; homes 1,864–2,181 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-08T07:19:51.254184 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,551 SF 17 sales 1,551– 1,826 SF 17 sales 1,864– 2,181 SF 18 sales Over 2,181 SF 17 sales 0 50 100 150 67 31 48 126 Days on market, median

The median is 126 days for homes over 2,181 SF and 67 days for homes under 1,551 SF. It does not move in a straight line; homes over 2,181 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-08T07:19:51.276732 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,551 SF 17 sales 1,551– 1,826 SF 17 sales 1,864– 2,181 SF 18 sales Over 2,181 SF 17 sales 0.0% 5.0% 10.0% 7.6% 6.3% 6.5% 10.3% Discount from original list, average

The average is 10.3% for homes over 2,181 SF and 7.6% for homes under 1,551 SF. It does not move in a straight line; homes over 2,181 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

2026-11-08T07:19:51.303554 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% 47% 65% 71% 41% 71% 82% 44% 61% 78% 53% 65% 88% Under 1,551 SF 1,551–1,826 SF 1,864–2,181 SF Over 2,181 SF

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

  • 53% of homes over 2,181 SF had a price cut before sale, against 47% of homes under 1,551 SF. Defined in 8.1.7.
  • 65% of homes over 2,181 SF had the seller pay closing costs or repairs, against 65% of homes under 1,551 SF. Defined in 8.1.8.
  • 88% of homes over 2,181 SF have a view, against 71% of homes under 1,551 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 1,551 SF17 sales1,551–1,826 SF17 sales1,864–2,181 SF18 salesOver 2,181 SF17 salesAll69 salesReal difference?
Net sale price average$341,515$413,821$499,182$596,613$463,310✓ large
Net price per SF average$257$242$246$225$242unclear
Living area average1,3411,7102,0282,6651,937by design
Year built median20142002201520012007unclear

4.10 The numbers: selling

Under 1,551 SF17 sales1,551–1,826 SF17 sales1,864–2,181 SF18 salesOver 2,181 SF17 salesAll69 salesReal difference?
Days on market median67314812664unclear
Discount from original list average7.6%6.3%6.5%10.3%7.7%unclear
Price cut before sale47%41%44%53%46%unclear
Seller paid closing costs or repairs65%71%61%65%65%unclear
Has a view71%82%78%88%80%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 · 69 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.

2026-11-08T07:19:51.324435 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 17 17 17 18 69 sales Sales per group Before 2000: 17 sales (25%) 2000–2006: 17 sales (25%) 2007–2016: 17 sales (25%) After 2016: 18 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 20002000–20062007–2016After 2016Real difference?
Net sale price$477K$491K$467K$420Kunclear
Net price per SF$228 per SF$242 per SF$245 per SF$253 per SFunclear
Living area2,147 SF2,013 SF1,910 SF1,692 SFunclear
Days on market140 days43 days28 days68 daysunclear
Discount from original list11.9%7.5%4.9%6.4%unclear
Price cut before sale71%41%29%44%unclear
Seller paid closing costs or repairs71%53%76%61%unclear
Has a view94%76%71%78%unclear

5.3 Net sale price: no clear difference

2026-11-08T07:19:51.345443 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 17 sales 2000– 2006 17 sales 2007– 2016 17 sales After 2016 18 sales $0K $200K $400K $477K $491K $467K $420K Net sale price, average

The average is $420K for homes built after 2016 and $477K for homes built before 2000. It does not move in a straight line; homes built 2000–2006 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-08T07:19:51.368346 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 17 sales 2000– 2006 17 sales 2007– 2016 17 sales After 2016 18 sales $0 $100 $200 $300 $228 $242 $245 $253 Net price per SF, average

The average is $253 per SF for homes built after 2016 and $228 per SF for homes built before 2000. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-08T07:19:51.391155 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 17 sales 2000– 2006 17 sales 2007– 2016 17 sales After 2016 18 sales 0 1,000 2,000 2,147 2,013 1,910 1,692 Living area (SF), average

The average is 1,692 SF for homes built after 2016 and 2,147 SF for homes built before 2000. It falls step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-08T07:19:51.414635 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 17 sales 2000– 2006 17 sales 2007– 2016 17 sales After 2016 18 sales 0 50 100 150 140 43 28 68 Days on market, median

The median is 68 days for homes built after 2016 and 140 days for homes built before 2000. It does not move in a straight line; homes built before 2000 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-08T07:19:51.438633 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 17 sales 2000– 2006 17 sales 2007– 2016 17 sales After 2016 18 sales 0.0% 5.0% 10.0% 11.9% 7.5% 4.9% 6.4% Discount from original list, average

The average is 6.4% for homes built after 2016 and 11.9% for homes built before 2000. It does not move in a straight line; homes built before 2000 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

2026-11-08T07:19:51.463433 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% 71% 71% 94% 41% 53% 76% 29% 76% 71% 44% 61% 78% Before 2000 2000–2006 2007–2016 After 2016

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

  • 44% of homes built after 2016 had a price cut before sale, against 71% of homes built before 2000. Defined in 8.1.7.
  • 61% of homes built after 2016 had the seller pay closing costs or repairs, against 71% of homes built before 2000. Defined in 8.1.8.
  • 78% of homes built after 2016 have a view, against 94% of homes built before 2000. 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 200017 sales2000–200617 sales2007–201617 salesAfter 201618 salesAll69 salesReal difference?
Net sale price average$476,714$491,189$467,454$420,407$463,310unclear
Net price per SF average$228$242$245$253$242unclear
Living area average2,1472,0131,9101,6921,937unclear
Year built median19932002201420202007by design

5.10 The numbers: selling

Before 200017 sales2000–200617 sales2007–201617 salesAfter 201618 salesAll69 salesReal difference?
Days on market median14043286864unclear
Discount from original list average11.9%7.5%4.9%6.4%7.7%unclear
Price cut before sale71%41%29%44%46%unclear
Seller paid closing costs or repairs71%53%76%61%65%unclear
Has a view94%76%71%78%80%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 · 69 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.

2026-11-08T07:19:51.482475 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 55 14 69 sales Sales per group View: 55 sales (80%) No view: 14 sales (20%)
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$469K$442Kunclear
Net price per SF$241 per SF$247 per SFunclear
Living area1,971 SF1,806 SFunclear
Year built20062014unclear
Days on market66 days54 daysunclear
Discount from original list7.5%8.3%unclear
Price cut before sale45%50%unclear
Seller paid closing costs or repairs65%64%unclear

6.3 Net sale price: no clear difference

2026-11-08T07:19:51.498941 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 55 sales No view 14 sales $0K $200K $400K $469K $442K Net sale price, average

The average is $469K for homes with a view and $442K 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

2026-11-08T07:19:51.516634 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 55 sales No view 14 sales $0 $100 $200 $241 $247 Net price per SF, average

The average is $241 per SF for homes with a view and $247 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

2026-11-08T07:19:51.535823 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 55 sales No view 14 sales 0 500 1,000 1,500 2,000 1,971 1,806 Living area (SF), average

The average is 1,971 SF for homes with a view and 1,806 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-08T07:19:51.580908 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 55 sales No view 14 sales 2000 2005 2010 2015 2006 2014 Year built: median (dot) and middle half (bar)

The median is 2006 for homes with a view and 2014 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-08T07:19:51.598919 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 55 sales No view 14 sales 0 20 40 60 66 54 Days on market, median

The median is 66 days for homes with a view and 54 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

2026-11-08T07:19:51.618466 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 55 sales No view 14 sales 0.0% 2.0% 4.0% 6.0% 8.0% 7.5% 8.3% Discount from original list, average

The average is 7.5% for homes with a view and 8.3% 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

2026-11-08T07:19:51.637159 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 45% 65% 50% 64% View No view

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

  • 45% of homes with a view had a price cut before sale, against 50% of homes without a view. Defined in 8.1.7.
  • 65% of homes with a view had the seller pay closing costs or repairs, against 64% 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

View55 salesNo view14 salesAll69 salesReal difference?
Net sale price average$468,682$442,206$463,310unclear
Net price per SF average$241$247$242unclear
Living area average1,9711,8061,937unclear
Year built median200620142007unclear

6.11 The numbers: selling

View55 salesNo view14 salesAll69 salesReal difference?
Days on market median665464unclear
Discount from original list average7.5%8.3%7.7%unclear
Price cut before sale45%50%46%unclear
Seller paid closing costs or repairs65%64%65%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 · 21 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: 21 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 Woodcreek.
MeasureAverageMedian
Sales21
Net sale price$433,946$426,000
Net price per SF$239$237
Living area (SF)1,8171,888
Days on market154138
Discount from original list7.1%6.4%
Price cut before sale62% of sales
Seller paid closing costs or repairs57% of sales
Year built2023–2026

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

8. AppendixMeasures, methods and tests

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

8.1 Measures

8.1.1 Net sale price

In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
69 resale sales. Average $463,310; median $447,250; standard deviation $142,702; middle half (25th–75th percentile) $384,000–$515,000; lowest $248,946, highest $1,220,000. 45 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
69 resale sales. Average $242; median $245; standard deviation $37; middle half (25th–75th percentile) $225–$263; lowest $121, highest $338.

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
69 resale sales. Average 1,937; median 1,864; standard deviation 552; middle half (25th–75th percentile) 1,551–2,181; lowest 1,012, highest 3,607.

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
69 resale sales. Average 2006; median 2007; standard deviation 13; middle half (25th–75th percentile) 2000–2017; lowest 1973, highest 2024.

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
69 resale sales. Average 95; median 64; standard deviation 142; middle half (25th–75th percentile) 22–136; lowest 1, highest 1,100. 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
69 resale sales. Average 7.7%; median 5.9%; standard deviation 7.3%; middle half (25th–75th percentile) 2.8%–9.4%; lowest 0.0%, highest 31.2%. 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
32 of 69 resale sales (46.4%).

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
45 of 69 resale sales (65.2%).

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
55 sales with a view, 14 without, 0 unclassified. Most common View entries: Hill Country 33, Trees/Woods 24, Golf Course 16, Neighborhood 14, None 12, Park/Greenbelt 12, Creek/Stream 5, Pool 3.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-08 13:15 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Wimberley, SubdivisionName contains any of “woodcreek”, “brookmeadow”, “brook meadow” (case-insensitive). A record is kept when its subdivision name belongs to the Woodcreek family, the same rule comparable sales use (it includes Brookmeadow, proven adjacent and priced alike).
The data
Pulled November 8, 2026: 92 closed Woodcreek records over the prior year, in ZIP 78676. 30 subdivision spellings kept, the most common: Woodcreek Sec 19 (11); Woodcreek Sec 6-C (9); Woodcreek Sec 9A (6); Woodcreek (6); Woodcreek Sec 20 (6); Woodcreek Sec 22 (5); Woodcreek Sec 2 (5); Woodcreek Sec 9-B (5); Woodcreek Sec 8 (5); Woodcreek Sec 9-A (4); Woodcreek Sec 12 (3); Woodcreek Sec 1 (3); and 18 more (24 records). Names found by the search but not part of Woodcreek, left out: Deer Field Place At Woodcreek (1); Woodcreekd (1); Woodcreek Village Sec 6 (1).

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 34 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 8, 2025 to November 7, 2026 inclusive.
The data
90 single-family sales in the window: 69 resale, 21 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
69 resale; 21 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
2 sale(s) other than single-family homes (condo, townhome and similar)

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 $384K”.
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 $384K: $248,946–$380,000 (17 sales); $384K–$442K: $384,000–$442,500 (17 sales); $447K–$515K: $447,250–$515,000 (18 sales); Over $515K: $516,000–$1,220,000 (17 sales)
Quartiles by living area: Under 1,551 SF: 1,012–1,529 SF (17 sales); 1,551–1,826 SF: 1,551–1,826 SF (17 sales); 1,864–2,181 SF: 1,864–2,181 SF (18 sales); Over 2,181 SF: 2,200–3,607 SF (17 sales)
Quartiles by year built: Before 2000: 1973–1999 (17 sales); 2000–2006: 2000–2006 (17 sales); 2007–2016: 2007–2016 (17 sales); After 2016: 2017–2024 (18 sales)
View and no view: View: MLS lists a view (55 sales); No view: None or Neighborhood (14 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 $463,310, median $447,250. Days on market: average 95, median 64: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

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

8.2.8 Mann–Whitney U test

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

8.2.9 Chi-square test

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

8.2.10 Real difference (significance)

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

8.2.11 Size of a difference

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

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 4.4130.2207p < 0.0063Unclearε² = 0.065medium
Living areaKruskal–WallisH = 45.423< 0.0001p < 0.0063Yesε² = 0.668large
Year builtKruskal–WallisH = 7.9830.0464p < 0.0063Unclearε² = 0.117medium
Days on marketKruskal–WallisH = 0.5330.9123p < 0.0063Unclearε² = 0.008negligible
Discount from original listKruskal–WallisH = 2.9730.3968p < 0.0063Unclearε² = 0.044small
Price cut before saleChi-squareχ² = 0.5130.9168p < 0.0063UnclearCramér’s V = 0.086negligible
Seller paid closing costs or repairsChi-squareχ² = 7.1530.0672p < 0.0063UnclearCramér’s V = 0.322medium
Has a viewChi-squareχ² = 6.9130.0750p < 0.0063UnclearCramér’s V = 0.316medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 45.043< 0.0001p < 0.0063Yesε² = 0.662large
Net price per SFKruskal–WallisH = 7.5730.0557p < 0.0063Unclearε² = 0.111medium
Year builtKruskal–WallisH = 10.2530.0165p < 0.0063Unclearε² = 0.151large
Days on marketKruskal–WallisH = 8.9230.0303p < 0.0063Unclearε² = 0.131medium
Discount from original listKruskal–WallisH = 4.8130.1862p < 0.0063Unclearε² = 0.071medium
Price cut before saleChi-squareχ² = 0.5130.9168p < 0.0063UnclearCramér’s V = 0.086negligible
Seller paid closing costs or repairsChi-squareχ² = 0.3530.9496p < 0.0063UnclearCramér’s V = 0.072negligible
Has a viewChi-squareχ² = 1.7530.6251p < 0.0063UnclearCramér’s V = 0.159small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 2.0130.5708p < 0.0063Unclearε² = 0.030small
Net price per SFKruskal–WallisH = 3.1930.3630p < 0.0063Unclearε² = 0.047small
Living areaKruskal–WallisH = 4.7930.1876p < 0.0063Unclearε² = 0.070medium
Days on marketKruskal–WallisH = 8.7930.0322p < 0.0063Unclearε² = 0.129medium
Discount from original listKruskal–WallisH = 7.0330.0710p < 0.0063Unclearε² = 0.103medium
Price cut before saleChi-squareχ² = 6.1930.1029p < 0.0063UnclearCramér’s V = 0.299small
Seller paid closing costs or repairsChi-squareχ² = 2.4330.4884p < 0.0063UnclearCramér’s V = 0.188small
Has a viewChi-squareχ² = 3.2130.3606p < 0.0063UnclearCramér’s V = 0.216small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 403.50—0.7883p < 0.0063Unclearrank-biserial r = 0.048negligible
Net price per SFMann–Whitney UU = 362.00—0.7371p < 0.0063Unclearrank-biserial r = 0.060negligible
Living areaMann–Whitney UU = 441.00—0.4076p < 0.0063Unclearrank-biserial r = 0.145small
Year builtMann–Whitney UU = 307.50—0.2502p < 0.0063Unclearrank-biserial r = 0.201small
Days on marketMann–Whitney UU = 367.50—0.7997p < 0.0063Unclearrank-biserial r = 0.045negligible
Discount from original listMann–Whitney UU = 368.50—0.8113p < 0.0063Unclearrank-biserial r = 0.043negligible
Price cut before saleChi-squareχ² = 0.0910.7608p < 0.0063UnclearCramér’s V = 0.037negligible
Seller paid closing costs or repairsChi-squareχ² = 0.0110.9347p < 0.0063UnclearCramér’s V = 0.010negligible

8.4 Data notes

Left out of the analysis: 21 new-construction sales (basic statistics only, section 7); 2 sale(s) other than single-family homes (condo, townhome and similar). 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 69 closed MLS resale sales; the 21 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.