ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Caliterra

Dripping Springs, TX 78620 · 78625
Resale homes · closed Nov 7 – Nov 6, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 7, 2026 · 7:38 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
27
single-family resale homes
Median net sale price
$755,000
average $797,550
Median net price per SF
$249
average $251
Median days on market
44 days
average 63 days
1. SummaryResale homes · 27 sales · November 7, 2025 – November 6, 2026

This study looks at the 27 resale homes sold in Caliterra in the 365 days to November 6, 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 sold27 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 $574K · 7 sales$574K–$755K · 7 sales$798K–$908K · 6 salesOver $908K · 7 sales
3. Quartiles by net sale priceResale homes · 27 sales · November 7, 2025 – November 6, 2026

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

2026-11-07T07:38:40.281163 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 6 7 27 sales Sales per group Under $574K: 7 sales (26%) $574K–$755K: 7 sales (26%) $798K–$908K: 6 sales (22%) Over $908K: 7 sales (26%)
Bottom line

3.1 Key differences

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

Under $574K$574K–$755K$798K–$908KOver $908K
Higher-priced homes Over $908K
  • Are much larger.
Lower-priced homes Under $574K
  • 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 $574K$574K–$755K$798K–$908KOver $908KReal difference?
Net price per SF$254 per SF$253 per SF$223 per SF$270 per SFunclear
Living area2,008 SFSmallest2,624 SF3,882 SF4,311 SFLargest✓ large
Year built2021202220202021unclear
Days on market78 days66 days42 days26 daysunclear
Discount from original list5.1%7.5%5.6%2.5%unclear
Price cut before sale57%57%50%29%unclear
Seller paid closing costs or repairs43%71%50%71%unclear
Has a view71%57%50%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

2026-11-07T07:38:40.319334 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $574K 7 sales $574K– $755K 7 sales $798K– $908K 6 sales Over $908K 7 sales $0 $100 $200 $300 $254 $253 $223 $270 Net price per SF, average

The average is $270 per SF for homes over $908K and $254 per SF for homes under $574K. It does not move in a straight line; homes over $908K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $908K are about 2,300 SF (115%) larger than homes under $574K

2026-11-07T07:38:40.345088 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $574K 7 sales $574K– $755K 7 sales $798K– $908K 6 sales Over $908K 7 sales 0 2,000 4,000 2,008 2,624 3,882 4,311 Living area (SF), average

The average is 4,311 SF for homes over $908K and 2,008 SF for homes under $574K. 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

2026-11-07T07:38:40.372761 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $574K 7 sales $574K– $755K 7 sales $798K– $908K 6 sales Over $908K 7 sales 2020 2021 2022 2023 2021 2022 2020 2021 Year built: median (dot) and middle half (bar)

The median is 2021 for homes over $908K and 2021 for homes under $574K. It does not move in a straight line; homes $574K–$755K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-07T07:38:40.397413 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $574K 7 sales $574K– $755K 7 sales $798K– $908K 6 sales Over $908K 7 sales 0 25 50 75 78 66 42 26 Days on market, median

The median is 26 days for homes over $908K and 78 days for homes under $574K. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-07T07:38:40.421007 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $574K 7 sales $574K– $755K 7 sales $798K– $908K 6 sales Over $908K 7 sales 0.0% 2.5% 5.0% 7.5% 5.1% 7.5% 5.6% 2.5% Discount from original list, average

The average is 2.5% for homes over $908K and 5.1% for homes under $574K. It does not move in a straight line; homes $574K–$755K 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

2026-11-07T07:38:40.454584 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% 57 43 71 57 71 57 50 50 50 29 71 100 Under $574K $574K–$755K $798K–$908K Over $908K

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

  • 29% of homes over $908K had a price cut before sale, against 57% of homes under $574K. Defined in 8.1.7.
  • 71% of homes over $908K had the seller pay closing costs or repairs, against 43% of homes under $574K. Defined in 8.1.8.
  • 100% of homes over $908K have a view, against 71% of homes under $574K. 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 $574K7 sales$574K–$755K7 sales$798K–$908K6 salesOver $908K7 salesAll27 salesReal difference?
Net sale price average$507,939$663,693$857,583$1,169,560$797,550by design
Net price per SF average$254$253$223$270$251unclear
Living area average2,0082,6243,8824,3113,181✓ large
Year built median20212022202020212021unclear

3.10 The numbers: selling

Under $574K7 sales$574K–$755K7 sales$798K–$908K6 salesOver $908K7 salesAll27 salesReal difference?
Days on market median7866422644unclear
Discount from original list average5.1%7.5%5.6%2.5%5.2%unclear
Price cut before sale57%57%50%29%48%unclear
Seller paid closing costs or repairs43%71%50%71%59%unclear
Has a view71%57%50%100%70%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 · 27 sales · November 7, 2025 – November 6, 2026

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

2026-11-07T07:38:40.476949 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 6 7 27 sales Sales per group Under 2,426 SF: 7 sales (26%) 2,426–2,951 SF: 7 sales (26%) 3,465–3,799 SF: 6 sales (22%) Over 3,799 SF: 7 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 2,426 SF2,426–2,951 SF3,465–3,799 SFOver 3,799 SF
Larger homes Over 3,799 SF
  • Sell for much more.
Smaller homes Under 2,426 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 2,426 SF2,426–2,951 SF3,465–3,799 SFOver 3,799 SFReal difference?
Net sale price$515KLowest$657K$902K$1.13MHighest✓ large
Net price per SF$261 per SF$246 per SF$252 per SF$245 per SFunclear
Year built2023202120202021unclear
Days on market40 days68 days28 days39 daysunclear
Discount from original list4.5%8.1%3.0%4.7%unclear
Price cut before sale43%71%33%43%unclear
Seller paid closing costs or repairs43%71%67%57%unclear
Has a view86%43%50%100%unclear

4.3 Homes over 3,799 SF sell for about $617K (120%) more than homes under 2,426 SF

2026-11-07T07:38:40.500200 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,426 SF 7 sales 2,426– 2,951 SF 7 sales 3,465– 3,799 SF 6 sales Over 3,799 SF 7 sales $0K $500K $1.00M $515K $657K $902K $1.13M Net sale price, average

The average is $1.13M for homes over 3,799 SF and $515K for homes under 2,426 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

2026-11-07T07:38:40.525560 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,426 SF 7 sales 2,426– 2,951 SF 7 sales 3,465– 3,799 SF 6 sales Over 3,799 SF 7 sales $0 $100 $200 $300 $261 $246 $252 $245 Net price per SF, average

The average is $245 per SF for homes over 3,799 SF and $261 per SF for homes under 2,426 SF. It does not move in a straight line; homes under 2,426 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-07T07:38:40.551572 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,426 SF 7 sales 2,426– 2,951 SF 7 sales 3,465– 3,799 SF 6 sales Over 3,799 SF 7 sales 2019 2020 2021 2022 2023 2023 2021 2020 2021 Year built: median (dot) and middle half (bar)

The median is 2021 for homes over 3,799 SF and 2023 for homes under 2,426 SF. It does not move in a straight line; homes under 2,426 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-07T07:38:40.578601 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,426 SF 7 sales 2,426– 2,951 SF 7 sales 3,465– 3,799 SF 6 sales Over 3,799 SF 7 sales 0 25 50 75 40 68 28 39 Days on market, median

The median is 39 days for homes over 3,799 SF and 40 days for homes under 2,426 SF. It does not move in a straight line; homes 2,426–2,951 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-07T07:38:40.603652 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,426 SF 7 sales 2,426– 2,951 SF 7 sales 3,465– 3,799 SF 6 sales Over 3,799 SF 7 sales 0.0% 2.5% 5.0% 7.5% 4.5% 8.1% 3.0% 4.7% Discount from original list, average

The average is 4.7% for homes over 3,799 SF and 4.5% for homes under 2,426 SF. It does not move in a straight line; homes 2,426–2,951 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

2026-11-07T07:38:40.632170 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% 43 43 86 71 71 43 33 67 50 43 57 100 Under 2,426 SF 2,426–2,951 SF 3,465–3,799 SF Over 3,799 SF

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

  • 43% of homes over 3,799 SF had a price cut before sale, against 43% of homes under 2,426 SF. Defined in 8.1.7.
  • 57% of homes over 3,799 SF had the seller pay closing costs or repairs, against 43% of homes under 2,426 SF. Defined in 8.1.8.
  • 100% of homes over 3,799 SF have a view, against 86% of homes under 2,426 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 2,426 SF7 sales2,426–2,951 SF7 sales3,465–3,799 SF6 salesOver 3,799 SF7 salesAll27 salesReal difference?
Net sale price average$514,557$657,075$901,603$1,131,829$797,550✓ large
Net price per SF average$261$246$252$245$251unclear
Living area average1,9712,6603,5804,5693,181by design
Year built median20232021202020212021unclear

4.10 The numbers: selling

Under 2,426 SF7 sales2,426–2,951 SF7 sales3,465–3,799 SF6 salesOver 3,799 SF7 salesAll27 salesReal difference?
Days on market median4068283944unclear
Discount from original list average4.5%8.1%3.0%4.7%5.2%unclear
Price cut before sale43%71%33%43%48%unclear
Seller paid closing costs or repairs43%71%67%57%59%unclear
Has a view86%43%50%100%70%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 · 27 sales · November 7, 2025 – November 6, 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.

2026-11-07T07:38:40.654008 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 12 3 7 27 sales Sales per group Before 2020: 5 sales (19%) 2020–2021: 12 sales (44%) 2022: 3 sales (11%) After 2022: 7 sales (26%)
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

2026-11-07T07:38:40.675039 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2020 5 sales 2020– 2021 12 sales 2022 3 sales After 2022 7 sales $0K $500K $1.00M $852K $747K $980K $767K Net sale price, average

The average is $767K for homes built after 2022 and $852K for homes built before 2020. It does not move in a straight line; homes built 2022 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-11-07T07:38:40.698193 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2020 5 sales 2020– 2021 12 sales 2022 3 sales After 2022 7 sales $0 $100 $200 $300 $245 $240 $249 $275 Net price per SF, average

The average is $275 per SF for homes built after 2022 and $245 per SF for homes built before 2020. It does not move in a straight line; homes built after 2022 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-11-07T07:38:40.720781 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2020 5 sales 2020– 2021 12 sales 2022 3 sales After 2022 7 sales 0 2,000 4,000 3,493 3,136 4,011 2,680 Living area (SF), average

The average is 2,680 SF for homes built after 2022 and 3,493 SF for homes built before 2020. It does not move in a straight line; homes built 2022 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-11-07T07:38:40.745799 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2020 5 sales 2020– 2021 12 sales 2022 3 sales After 2022 7 sales 0 25 50 75 52 40 26 68 Days on market, median

The median is 68 days for homes built after 2022 and 52 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

2026-11-07T07:38:40.770809 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2020 5 sales 2020– 2021 12 sales 2022 3 sales After 2022 7 sales 0.0% 5.0% 10.0% 5.6% 4.2% 9.3% 4.8% Discount from original list, average

The average is 4.8% for homes built after 2022 and 5.6% for homes built before 2020. It does not move in a straight line; homes built 2022 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

2026-11-07T07:38:40.797609 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% 60 40 100 42 67 58 33 67 67 57 57 71 Before 2020 2020–2021 2022 After 2022

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

  • 57% of homes built after 2022 had a price cut before sale, against 60% of homes built before 2020. Defined in 8.1.7.
  • 57% of homes built after 2022 had the seller pay closing costs or repairs, against 40% of homes built before 2020. Defined in 8.1.8.
  • 71% 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 20205 sales2020–202112 sales20223 salesAfter 20227 salesAll27 sales
Net sale price average$851,724$747,292$979,667$766,961$797,550
Net price per SF average$245$240$249$275$251
Living area average3,4933,1364,0112,6803,181
Year built median20192021202220232021

5.10 The numbers: selling

Before 20205 sales2020–202112 sales20223 salesAfter 20227 salesAll27 sales
Days on market median5240266844
Discount from original list average5.6%4.2%9.3%4.8%5.2%
Price cut before sale60%42%33%57%48%
Seller paid closing costs or repairs40%67%67%57%59%
Has a view100%58%67%71%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 8.3.3.

6. View and no viewResale homes · 27 sales · November 7, 2025 – November 6, 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.

2026-11-07T07:38:40.816636 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 19 7 26 sales Sales per group View: 19 sales (73%) No view: 7 sales (27%)
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$822K$717Kunclear
Net price per SF$252 per SF$248 per SFunclear
Living area3,269 SF2,900 SFunclear
Year built20212021unclear
Days on market40 days68 daysunclear
Discount from original list4.7%6.8%unclear
Price cut before sale47%57%unclear
Seller paid closing costs or repairs53%71%unclear

6.3 Net sale price: no clear difference

2026-11-07T07:38:40.834000 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 7 sales $0K $200K $400K $600K $800K $822K $717K Net sale price, average

The average is $822K for homes with a view and $717K 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

2026-11-07T07:38:40.852855 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 7 sales $0 $100 $200 $300 $252 $248 Net price per SF, average

The average is $252 per SF for homes with a view and $248 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

2026-11-07T07:38:40.874357 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 7 sales 0 1,000 2,000 3,000 3,269 2,900 Living area (SF), average

The average is 3,269 SF for homes with a view and 2,900 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-07T07:38:40.960931 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 7 sales 2020 2021 2022 2021 2021 Year built: median (dot) and middle half (bar)

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

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-07T07:38:40.982426 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 7 sales 0 20 40 60 80 40 68 Days on market, median

The median is 40 days for homes with a view and 68 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

2026-11-07T07:38:41.002978 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 7 sales 0.0% 2.0% 4.0% 6.0% 8.0% 4.7% 6.8% Discount from original list, average

The average is 4.7% for homes with a view and 6.8% 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

2026-11-07T07:38:41.023118 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 47 53 57 71 View No view

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

  • 47% of homes with a view had a price cut before sale, against 57% of homes without a view. Defined in 8.1.7.
  • 53% of homes with a view had the seller pay closing costs or repairs, against 71% 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

View19 salesNo view7 salesAll26 salesReal difference?
Net sale price average$821,550$716,700$793,321unclear
Net price per SF average$252$248$251unclear
Living area average3,2692,9003,170unclear
Year built median202120212021unclear

6.11 The numbers: selling

View19 salesNo view7 salesAll26 salesReal difference?
Days on market median406848unclear
Discount from original list average4.7%6.8%5.3%unclear
Price cut before sale47%57%50%unclear
Seller paid closing costs or repairs53%71%58%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 7, 2025 – November 6, 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 Caliterra.
MeasureAverageMedian
Sales21
Net sale price$1,050,343$967,809
Net price per SF$270$263
Living area (SF)3,8843,800
Days on market10537
Discount from original list8.9%10.9%
Price cut before sale43% of sales
Seller paid closing costs or repairs38% 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
27 resale sales. Average $797,550; median $755,000; standard deviation $300,678; middle half (25th–75th percentile) $573,500–$925,250; lowest $438,700, highest $1,828,800. 16 sales had a seller payment; their median payment was $1,750.

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
27 resale sales. Average $251; median $249; standard deviation $32; middle half (25th–75th percentile) $232–$270; lowest $188, highest $348.

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
27 resale sales. Average 3,181; median 2,951; standard deviation 1,040; middle half (25th–75th percentile) 2,334–3,952; lowest 1,602, highest 5,262.

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
27 resale sales. Average 2021; median 2021; standard deviation 2; middle half (25th–75th percentile) 2020–2022; lowest 2015, 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
27 resale sales. Average 63; median 44; standard deviation 65; middle half (25th–75th percentile) 16–74; lowest 4, highest 275. 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
27 resale sales. Average 5.2%; median 4.0%; standard deviation 5.3%; middle half (25th–75th percentile) 1.7%–7.3%; lowest −2.0%, highest 22.6%. 2 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
13 of 27 resale sales (48.1%).

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
16 of 27 resale sales (59.3%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
19 sales with a view, 7 without, 1 unclassified. Most common View entries: Park/Greenbelt 10, Neighborhood 10, Hill Country 9, Trees/Woods 7, Panoramic 4, None 3, See Remarks 1, Garden 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 2026-11-07 13:30 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Dripping Springs, SubdivisionName contains any of “caliterra” (case-insensitive). A record is kept when its subdivision name belongs to the Caliterra family, the same rule comparable sales use.
The data
Pulled November 7, 2026: 48 closed Caliterra records over the prior year, in ZIP 78620, 78625. 13 subdivision spellings kept, the most common: Caliterra (10); Caliterra - 110' (6); Caliterra - 80' (6); Caliterra Ph Three Sec Nine (5); Caliterra Ph Two Sec Seven (5); Caliterra Ph Four Sec 12 (4); Caliterra Ph Two Sec Eight (4); Caliterra Ph Four Sec 11 (2); Caliterra Ph One Sec Two (2); Caliterra - 70' (1); Caliterra - 100' (1); CALITERRA (1); and 1 more (1 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 7, 2025 to November 6, 2026 inclusive.
The data
48 single-family sales in the window: 27 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
27 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
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 $574K”.
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 $574K: $438,700–$573,375 (7 sales); $574K–$755K: $573,626–$755,000 (7 sales); $798K–$908K: $798,500–$907,500 (6 sales); Over $908K: $943,000–$1,828,800 (7 sales)
Quartiles by living area: Under 2,426 SF: 1,602–2,242 SF (7 sales); 2,426–2,951 SF: 2,426–2,951 SF (7 sales); 3,465–3,799 SF: 3,465–3,799 SF (6 sales); Over 3,799 SF: 4,106–5,262 SF (7 sales)
Quartiles by year built: Before 2020: 2015–2019 (5 sales); 2020–2021: 2020–2021 (12 sales); 2022: 2022–2022 (3 sales); After 2022: 2023–2024 (7 sales)
View and no view: View: MLS lists a view (19 sales); No view: None or Neighborhood (7 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 $797,550, median $755,000. Days on market: average 63, median 44: 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; 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 = 6.6830.0830p < 0.0063Unclearε² = 0.257large
Living areaKruskal–WallisH = 21.913< 0.0001p < 0.0063Yesε² = 0.843large
Year builtKruskal–WallisH = 5.0630.1673p < 0.0063Unclearε² = 0.195large
Days on marketKruskal–WallisH = 3.8230.2810p < 0.0063Unclearε² = 0.147large
Discount from original listKruskal–WallisH = 1.6230.6549p < 0.0063Unclearε² = 0.062medium
Price cut before saleChi-squareχ² = 1.5430.6739p < 0.0063UnclearCramér’s V = 0.239small
Seller paid closing costs or repairsChi-squareχ² = 1.8530.6037p < 0.0063UnclearCramér’s V = 0.262small
Has a viewChi-squareχ² = 4.7330.1925p < 0.0063UnclearCramér’s V = 0.419medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 22.093< 0.0001p < 0.0063Yesε² = 0.850large
Net price per SFKruskal–WallisH = 2.4130.4913p < 0.0063Unclearε² = 0.093medium
Year builtKruskal–WallisH = 6.6230.0849p < 0.0063Unclearε² = 0.255large
Days on marketKruskal–WallisH = 3.3230.3451p < 0.0063Unclearε² = 0.128medium
Discount from original listKruskal–WallisH = 2.0830.5561p < 0.0063Unclearε² = 0.080medium
Price cut before saleChi-squareχ² = 2.2030.5311p < 0.0063UnclearCramér’s V = 0.286small
Seller paid closing costs or repairsChi-squareχ² = 1.3630.7152p < 0.0063UnclearCramér’s V = 0.224small
Has a viewChi-squareχ² = 7.4730.0583p < 0.0063UnclearCramér’s V = 0.526large

8.3.3 Quartiles by year built

Too few sales in a group to test.

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 76.00—0.6028p < 0.0063Unclearrank-biserial r = 0.143small
Net price per SFMann–Whitney UU = 73.00—0.7347p < 0.0063Unclearrank-biserial r = 0.098negligible
Living areaMann–Whitney UU = 73.00—0.7347p < 0.0063Unclearrank-biserial r = 0.098negligible
Year builtMann–Whitney UU = 49.00—0.3178p < 0.0063Unclearrank-biserial r = 0.263small
Days on marketMann–Whitney UU = 41.00—0.1482p < 0.0063Unclearrank-biserial r = 0.383medium
Discount from original listMann–Whitney UU = 63.00—0.8623p < 0.0063Unclearrank-biserial r = 0.053negligible
Price cut before saleChi-squareχ² = 0.2010.6584p < 0.0063UnclearCramér’s V = 0.087negligible
Seller paid closing costs or repairsChi-squareχ² = 0.7410.3895p < 0.0063UnclearCramér’s V = 0.169small

8.4 Data notes

Left out of the analysis: 21 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 27 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 7, 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.