ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Headwaters at Barton Creek

Dripping Springs, TX 78620
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 7:25 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
30
single-family resale homes
Median net sale price
$654,450
average $665,768
Median net price per SF
$231
average $228
Median days on market
52 days
average 58 days
1. SummaryResale homes · 30 sales · October 26, 2025 – October 25, 2026

This study looks at the 30 resale homes sold in Headwaters at Barton Creek in the 365 days to October 25, 2026. A full year is used because only 16 resale homes sold in the last 180 days. New construction is left out and shown on its own in section 7. The homes are compared four ways: by price, by living area, by year built and with or without a view. The first three are split into four equal groups (quartiles), each named by its range.

Each comparison has its own section (3–6) with everything about it in one place: the key differences, a table of every measure at a glance, the charts and the numbers.

2. Where the resale homes sold30 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 $614K · 8 sales$614K–$649K · 7 sales$660K–$711K · 7 salesOver $711K · 8 sales
3. Quartiles by net sale priceResale homes · 30 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:26:07.893145 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Under $614K: 8 sales (27%) $614K–$649K: 7 sales (23%) $660K–$711K: 7 sales (23%) Over $711K: 8 sales (27%)
Bottom line

3.1 Key differences

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

Under $614K$614K–$649K$660K–$711KOver $711K
Higher-priced homes Over $711K
  • Are much larger.
Lower-priced homes Under $614K
  • 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 $614K$614K–$649K$660K–$711KOver $711KReal difference?
Net price per SF$234 per SF$221 per SF$232 per SF$224 per SFunclear
Living area2,356 SFSmallest2,860 SF2,943 SF3,624 SFLargest✓ large
Year built2022201920222022unclear
Days on market89 days24 days54 days49 daysunclear
Discount from original list6.5%3.2%4.8%5.1%unclear
Price cut before sale88%14%57%50%unclear
Seller paid closing costs or repairs75%100%43%62%unclear
Has a view88%100%86%100%unclear

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

3.3 Net price per SF: no clear difference

2026-10-26T07:26:07.923324 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $614K 8 sales $614K– $649K 7 sales $660K– $711K 7 sales Over $711K 8 sales $0 $100 $200 $234 $221 $232 $224 Net price per SF, average

The average is $224 per SF for homes over $711K and $234 per SF for homes under $614K. It does not move in a straight line; homes under $614K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $711K are about 1,270 SF (54%) larger than homes under $614K

2026-10-26T07:26:07.946183 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $614K 8 sales $614K– $649K 7 sales $660K– $711K 7 sales Over $711K 8 sales 0 2,000 4,000 2,356 2,860 2,943 3,624 Living area (SF), average

The average is 3,624 SF for homes over $711K and 2,356 SF for homes under $614K. 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

2026-10-26T07:26:07.971720 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $614K 8 sales $614K– $649K 7 sales $660K– $711K 7 sales Over $711K 8 sales 2018 2019 2020 2021 2022 2022 2019 2022 2022 Year built: median (dot) and middle half (bar)

The median is 2022 for homes over $711K and 2022 for homes under $614K. It does not move in a straight line; homes $660K–$711K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:26:07.995546 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $614K 8 sales $614K– $649K 7 sales $660K– $711K 7 sales Over $711K 8 sales 0 50 100 89 24 54 49 Days on market, median

The median is 49 days for homes over $711K and 89 days for homes under $614K. It does not move in a straight line; homes under $614K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:26:08.017720 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $614K 8 sales $614K– $649K 7 sales $660K– $711K 7 sales Over $711K 8 sales 0.0% 2.0% 4.0% 6.0% 6.5% 3.2% 4.8% 5.1% Discount from original list, average

The average is 5.1% for homes over $711K and 6.5% for homes under $614K. It does not move in a straight line; homes under $614K are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:26:08.048950 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 88 75 88 14 100 100 57 43 86 50 62 100 Under $614K $614K–$649K $660K–$711K Over $711K

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

  • 50% of homes over $711K had a price cut before sale, against 88% of homes under $614K. Defined in 8.1.7.
  • 62% of homes over $711K had the seller pay closing costs or repairs, against 75% of homes under $614K. Defined in 8.1.8.
  • 100% of homes over $711K have a view, against 88% of homes under $614K. 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 $614K8 sales$614K–$649K7 sales$660K–$711K7 salesOver $711K8 salesAll30 salesReal difference?
Net sale price average$546,600$629,755$675,171$808,219$665,768by design
Net price per SF average$234$221$232$224$228unclear
Living area average2,3562,8602,9433,6242,948✓ large
Year built median20222019202220222021unclear

3.10 The numbers: selling

Under $614K8 sales$614K–$649K7 sales$660K–$711K7 salesOver $711K8 salesAll30 salesReal difference?
Days on market median8924544952unclear
Discount from original list average6.5%3.2%4.8%5.1%5.0%unclear
Price cut before sale88%14%57%50%53%unclear
Seller paid closing costs or repairs75%100%43%62%70%unclear
Has a view88%100%86%100%93%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 · 30 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:26:08.070790 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Under 2,700 SF: 8 sales (27%) 2,700–2,805 SF: 7 sales (23%) 2,860–3,194 SF: 7 sales (23%) Over 3,194 SF: 8 sales (27%)
Bottom line

4.1 Key differences

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

Under 2,700 SF2,700–2,805 SF2,860–3,194 SFOver 3,194 SF
Larger homes Over 3,194 SF
  • Sell for much more.
Smaller homes Under 2,700 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 2,700 SF2,700–2,805 SF2,860–3,194 SFOver 3,194 SFReal difference?
Net sale price$573KLowest$619K$675K$791KHighest✓ large
Net price per SF$248 per SF$227 per SF$223 per SF$214 per SFunclear
Year built2022202120222021unclear
Days on market80 days33 days71 days40 daysunclear
Discount from original list4.4%4.9%5.8%4.9%unclear
Price cut before sale62%29%71%50%unclear
Seller paid closing costs or repairs75%71%86%50%unclear
Has a view100%86%86%100%unclear

4.3 Homes over 3,194 SF sell for about $217K (38%) more than homes under 2,700 SF

2026-10-26T07:26:08.092866 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,700 SF 8 sales 2,700– 2,805 SF 7 sales 2,860– 3,194 SF 7 sales Over 3,194 SF 8 sales $0K $250K $500K $750K $573K $619K $675K $791K Net sale price, average

The average is $791K for homes over 3,194 SF and $573K for homes under 2,700 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

2026-10-26T07:26:08.116894 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,700 SF 8 sales 2,700– 2,805 SF 7 sales 2,860– 3,194 SF 7 sales Over 3,194 SF 8 sales $0 $100 $200 $248 $227 $223 $214 Net price per SF, average

The average is $214 per SF for homes over 3,194 SF and $248 per SF for homes under 2,700 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:26:08.141773 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,700 SF 8 sales 2,700– 2,805 SF 7 sales 2,860– 3,194 SF 7 sales Over 3,194 SF 8 sales 2018 2019 2020 2021 2022 2022 2021 2022 2021 Year built: median (dot) and middle half (bar)

The median is 2021 for homes over 3,194 SF and 2022 for homes under 2,700 SF. It does not move in a straight line; homes under 2,700 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:26:08.166152 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,700 SF 8 sales 2,700– 2,805 SF 7 sales 2,860– 3,194 SF 7 sales Over 3,194 SF 8 sales 0 25 50 75 80 33 71 40 Days on market, median

The median is 40 days for homes over 3,194 SF and 80 days for homes under 2,700 SF. It does not move in a straight line; homes under 2,700 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:26:08.189023 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,700 SF 8 sales 2,700– 2,805 SF 7 sales 2,860– 3,194 SF 7 sales Over 3,194 SF 8 sales 0.0% 2.0% 4.0% 6.0% 4.4% 4.9% 5.8% 4.9% Discount from original list, average

The average is 4.9% for homes over 3,194 SF and 4.4% for homes under 2,700 SF. It does not move in a straight line; homes 2,860–3,194 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:26:08.217005 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% 62 75 100 29 71 86 71 86 86 50 50 100 Under 2,700 SF 2,700–2,805 SF 2,860–3,194 SF Over 3,194 SF

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

  • 50% of homes over 3,194 SF had a price cut before sale, against 62% of homes under 2,700 SF. Defined in 8.1.7.
  • 50% of homes over 3,194 SF had the seller pay closing costs or repairs, against 75% of homes under 2,700 SF. Defined in 8.1.8.
  • 100% of homes over 3,194 SF have a view, against 100% of homes under 2,700 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 2,700 SF8 sales2,700–2,805 SF7 sales2,860–3,194 SF7 salesOver 3,194 SF8 salesAll30 salesReal difference?
Net sale price average$573,462$619,248$674,721$790,944$665,768✓ large
Net price per SF average$248$227$223$214$228unclear
Living area average2,3082,7333,0363,7002,948by design
Year built median20222021202220212021unclear

4.10 The numbers: selling

Under 2,700 SF8 sales2,700–2,805 SF7 sales2,860–3,194 SF7 salesOver 3,194 SF8 salesAll30 salesReal difference?
Days on market median8033714052unclear
Discount from original list average4.4%4.9%5.8%4.9%5.0%unclear
Price cut before sale62%29%71%50%53%unclear
Seller paid closing costs or repairs75%71%86%50%70%unclear
Has a view100%86%86%100%93%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 · 30 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:26:08.238292 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 10 10 3 30 sales Sales per group Before 2020: 7 sales (23%) 2020–2021: 10 sales (33%) 2022: 10 sales (33%) After 2022: 3 sales (10%)
Bottom line: too few sales to test.

5.1 Key differences

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

5.3 Net sale price: described, not tested

2026-10-26T07:26:08.259806 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2020 7 sales 2020– 2021 10 sales 2022 10 sales After 2022 3 sales $0K $250K $500K $750K $691K $641K $658K $715K Net sale price, average

The average is $715K for homes built after 2022 and $691K for homes built before 2020. It does not move in a straight line; homes built after 2022 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T07:26:08.283625 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2020 7 sales 2020– 2021 10 sales 2022 10 sales After 2022 3 sales $0 $100 $200 $220 $216 $247 $223 Net price per SF, average

The average is $223 per SF for homes built after 2022 and $220 per SF for homes built before 2020. It does not move in a straight line; homes built 2022 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T07:26:08.305122 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2020 7 sales 2020– 2021 10 sales 2022 10 sales After 2022 3 sales 0 1,000 2,000 3,000 3,137 2,990 2,698 3,206 Living area (SF), average

The average is 3,206 SF for homes built after 2022 and 3,137 SF for homes built before 2020. It does not move in a straight line; homes built after 2022 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T07:26:08.327602 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2020 7 sales 2020– 2021 10 sales 2022 10 sales After 2022 3 sales 0 25 50 75 24 70 52 71 Days on market, median

The median is 71 days for homes built after 2022 and 24 days for homes built before 2020. It does not move in a straight line; homes built after 2022 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T07:26:08.350759 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2020 7 sales 2020– 2021 10 sales 2022 10 sales After 2022 3 sales 0.0% 2.0% 4.0% 6.0% 4.1% 6.6% 3.9% 5.1% Discount from original list, average

The average is 5.1% for homes built after 2022 and 4.1% for homes built before 2020. It does not move in a straight line; homes built 2020–2021 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T07:26:08.376706 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% 29 100 100 70 50 90 50 70 90 67 67 100 Before 2020 2020–2021 2022 After 2022

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

  • 67% of homes built after 2022 had a price cut before sale, against 29% of homes built before 2020. Defined in 8.1.7.
  • 67% of homes built after 2022 had the seller pay closing costs or repairs, against 100% of homes built before 2020. Defined in 8.1.8.
  • 100% of homes built after 2022 have a view, against 100% of homes built before 2020. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

5.9 The numbers: price and size

Before 20207 sales2020–202110 sales202210 salesAfter 20223 salesAll30 sales
Net sale price average$691,296$641,167$657,739$714,967$665,768
Net price per SF average$220$216$247$223$228
Living area average3,1372,9902,6983,2062,948
Year built median20182021202220232021

5.10 The numbers: selling

Before 20207 sales2020–202110 sales202210 salesAfter 20223 salesAll30 sales
Days on market median2470527152
Discount from original list average4.1%6.6%3.9%5.1%5.0%
Price cut before sale29%70%50%67%53%
Seller paid closing costs or repairs100%50%70%67%70%
Has a view100%90%90%100%93%

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 · 30 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.

2026-10-26T07:26:08.396321 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 28 2 30 sales Sales per group View: 28 sales (93%) No view: 2 sales (7%)
Bottom line: too few sales to test.

6.1 Key differences

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

6.3 Net sale price: described, not tested

2026-10-26T07:26:08.413440 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 2 sales $0K $200K $400K $600K $800K $668K $630K Net sale price, average

The average is $668K for homes with a view and $630K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T07:26:08.432420 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 2 sales $0 $100 $200 $228 $225 Net price per SF, average

The average is $228 per SF for homes with a view and $225 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T07:26:08.451030 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 2 sales 0 1,000 2,000 3,000 2,960 2,792 Living area (SF), average

The average is 2,960 SF for homes with a view and 2,792 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T07:26:08.548421 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 2 sales 2020 2021 2022 2021 2022 Year built: median (dot) and middle half (bar)

The median is 2021 for homes with a view and 2022 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T07:26:08.568078 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 2 sales 0 20 40 60 80 43 68 Days on market, median

The median is 43 days for homes with a view and 68 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-26T07:26:08.587472 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 2 sales 0.0% 5.0% 10.0% 4.5% 11.6% Discount from original list, average

The average is 4.5% for homes with a view and 11.6% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T07:26:08.606554 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 50 68 100 100 View No view

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

  • 50% of homes with a view had a price cut before sale, against 100% of homes without a view. Defined in 8.1.7.
  • 68% of homes with a view had the seller pay closing costs or repairs, against 100% 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

View28 salesNo view2 salesAll30 sales
Net sale price average$668,323$630,000$665,768
Net price per SF average$228$225$228
Living area average2,9602,7922,948
Year built median202120222021

6.11 The numbers: selling

View28 salesNo view2 salesAll30 sales
Days on market median436852
Discount from original list average4.5%11.6%5.0%
Price cut before sale50%100%53%
Seller paid closing costs or repairs68%100%70%

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 · 24 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: 24 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 Headwaters at Barton Creek.
MeasureAverageMedian
Sales24
Net sale price$724,705$713,592
Net price per SF$256$250
Living area (SF)2,8602,910
Days on market128100
Discount from original list9.1%7.7%
Price cut before sale71% of sales
Seller paid closing costs or repairs42% of sales
Year built2024–2026

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
30 resale sales. Average $665,768; median $654,450; standard deviation $110,261; middle half (25th–75th percentile) $596,125–$725,175; lowest $455,900, highest $957,925. 21 sales had a seller payment; their median payment was $5,000.

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
30 resale sales. Average $228; median $231; standard deviation $21; middle half (25th–75th percentile) $210–$243; lowest $196, highest $276.

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
30 resale sales. Average 2,948; median 2,832; standard deviation 576; middle half (25th–75th percentile) 2,608–3,305; lowest 2,044, highest 4,395.

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
30 resale sales. Average 2021; median 2021; standard deviation 2; middle half (25th–75th percentile) 2020–2022; lowest 2017, highest 2023.

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
30 resale sales. Average 58; median 52; standard deviation 46; middle half (25th–75th percentile) 18–85; lowest 3, highest 174. 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
30 resale sales. Average 5.0%; median 4.0%; standard deviation 4.0%; middle half (25th–75th percentile) 1.8%–7.0%; lowest 0.0%, highest 15.6%. 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
16 of 30 resale sales (53.3%).

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
21 of 30 resale sales (70.0%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
28 sales with a view, 2 without, 0 unclassified. Most common View entries: Park/Greenbelt 22, Hill Country 16, Trees/Woods 12, Neighborhood 9, Panoramic 5, Pool 1, None 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 = Dripping Springs, SubdivisionName contains any of “headwaters at barton creek”, “headwaters”, “headwaters legacy”, “headwaters preserve” (case-insensitive). A record is kept when its subdivision name belongs to the Headwaters at Barton Creek family, the same rule comparable sales use (it includes Headwaters, Headwaters Legacy, Headwaters Preserve, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 54 closed Headwaters at Barton Creek records over the prior year, in ZIP 78620. 10 subdivision spellings kept: Headwaters (15); Headwaters at Barton Creek (11); Headwaters At Barton Creek Ph 1 (8); Headwaters At Barton Creek Ph 2 (6); Headwaters At Barton Creek Ph 4 Sec 3 (5); Headwaters At Barton Creek Ph 4 Sec 4 (3); Headwaters At Barton Creek Ph 5 Sec 2 (2); Headwaters At Barton Creek Ph 5 Sec 1 (2); Headwaters At Barton Creek (1); HEADWATERS AT BARTON CREEK (1). Names found by the search but not part of Headwaters at Barton Creek, left out: Toll Brothers at Headwaters - Preserve Collection (6); Toll Brothers at Headwaters - Legacy Collection (6); Headwaters Barton Creek Ph 4 Sec 1 (2).

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 16 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
54 single-family sales in the window: 30 resale, 24 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
30 resale; 24 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 $614K”.
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 $614K: $455,900–$590,000 (8 sales); $614K–$649K: $614,500–$648,900 (7 sales); $660K–$711K: $660,000–$711,000 (7 sales); Over $711K: $729,900–$957,925 (8 sales)
Quartiles by living area: Under 2,700 SF: 2,044–2,578 SF (8 sales); 2,700–2,805 SF: 2,700–2,805 SF (7 sales); 2,860–3,194 SF: 2,860–3,194 SF (7 sales); Over 3,194 SF: 3,342–4,395 SF (8 sales)
Quartiles by year built: Before 2020: 2017–2019 (7 sales); 2020–2021: 2020–2021 (10 sales); 2022: 2022–2022 (10 sales); After 2022: 2023–2023 (3 sales)
View and no view: View: MLS lists a view (28 sales); No view: None or Neighborhood (2 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 $665,768, median $654,450. Days on market: average 58, median 52: 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

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 = 1.6130.6568p < 0.0063Unclearε² = 0.056small
Living areaKruskal–WallisH = 20.6330.0001p < 0.0063Yesε² = 0.711large
Year builtKruskal–WallisH = 6.4330.0923p < 0.0063Unclearε² = 0.222large
Days on marketKruskal–WallisH = 7.7230.0522p < 0.0063Unclearε² = 0.266large
Discount from original listKruskal–WallisH = 2.6130.4565p < 0.0063Unclearε² = 0.090medium
Price cut before saleChi-squareχ² = 8.1230.0437p < 0.0063UnclearCramér’s V = 0.520large
Seller paid closing costs or repairsChi-squareχ² = 5.7730.1236p < 0.0063UnclearCramér’s V = 0.438medium
Has a viewChi-squareχ² = 2.1630.5395p < 0.0063UnclearCramér’s V = 0.268small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 18.2230.0004p < 0.0063Yesε² = 0.628large
Net price per SFKruskal–WallisH = 10.4730.0149p < 0.0063Unclearε² = 0.361large
Year builtKruskal–WallisH = 0.9430.8156p < 0.0063Unclearε² = 0.032small
Days on marketKruskal–WallisH = 1.2430.7433p < 0.0063Unclearε² = 0.043small
Discount from original listKruskal–WallisH = 0.5530.9067p < 0.0063Unclearε² = 0.019small
Price cut before saleChi-squareχ² = 2.9530.3992p < 0.0063UnclearCramér’s V = 0.314medium
Seller paid closing costs or repairsChi-squareχ² = 2.4530.4846p < 0.0063UnclearCramér’s V = 0.286small
Has a viewChi-squareχ² = 2.4530.4846p < 0.0063UnclearCramér’s V = 0.286small

8.3.3 Quartiles by year built

Too few sales in a group to test.

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

Left out of the analysis: 24 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 30 closed MLS resale sales; the 24 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.