ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Clearwater Ranch-Ph

Liberty Hill, TX 78642
Resale homes · closed Nov 1 – Oct 31, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 1, 2026 · 7:40 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
24
single-family resale homes
Median net sale price
$882,688
average $902,221
Median net price per SF
$253
average $260
Median days on market
63 days
average 104 days
1. SummaryResale homes · 24 sales · November 1, 2025 – October 31, 2026

This study looks at the 24 resale homes sold in Clearwater Ranch-Ph in the 365 days to October 31, 2026. A full year is used because only 17 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 sold24 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 $815K · 6 sales$815K–$880K · 6 sales$885K–$986K · 6 salesOver $986K · 6 sales
3. Quartiles by net sale priceResale homes · 24 sales · November 1, 2025 – October 31, 2026

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

2026-11-01T07:41:00.311314 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 6 6 24 sales Sales per group Under $815K: 6 sales (25%) $815K–$880K: 6 sales (25%) $885K–$986K: 6 sales (25%) Over $986K: 6 sales (25%)
Bottom line: no measure differs enough between the groups to rule out chance.

3.1 Key differences

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

3.2 At a glance

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

Under $815K$815K–$880K$885K–$986KOver $986KReal difference?
Net price per SF$240 per SF$266 per SF$264 per SF$269 per SFunclear
Living area3,086 SF3,206 SF3,617 SF4,123 SFunclear
Year built2017201720212020unclear
Days on market94 days80 days40 days57 daysunclear
Discount from original list7.3%5.7%4.9%6.7%unclear
Price cut before sale67%50%50%33%unclear
Seller paid closing costs or repairs50%33%50%33%unclear
Has a view83%33%50%50%unclear

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

3.3 Net price per SF: no clear difference

2026-11-01T07:41:00.340321 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $815K 6 sales $815K– $880K 6 sales $885K– $986K 6 sales Over $986K 6 sales $0 $100 $200 $300 $240 $266 $264 $269 Net price per SF, average

The average is $269 per SF for homes over $986K and $240 per SF for homes under $815K. It does not move in a straight line; homes over $986K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-11-01T07:41:00.372015 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $815K 6 sales $815K– $880K 6 sales $885K– $986K 6 sales Over $986K 6 sales 0 2,000 4,000 3,086 3,206 3,617 4,123 Living area (SF), average

The average is 4,123 SF for homes over $986K and 3,086 SF for homes under $815K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-11-01T07:41:00.404442 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $815K 6 sales $815K– $880K 6 sales $885K– $986K 6 sales Over $986K 6 sales 2016 2018 2020 2022 2017 2017 2021 2020 Year built: median (dot) and middle half (bar)

The median is 2020 for homes over $986K and 2017 for homes under $815K. It does not move in a straight line; homes $885K–$986K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-01T07:41:00.429618 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $815K 6 sales $815K– $880K 6 sales $885K– $986K 6 sales Over $986K 6 sales 0 50 100 94 80 40 57 Days on market, median

The median is 57 days for homes over $986K and 94 days for homes under $815K. It does not move in a straight line; homes under $815K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-01T07:41:00.458667 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $815K 6 sales $815K– $880K 6 sales $885K– $986K 6 sales Over $986K 6 sales 0.0% 2.5% 5.0% 7.5% 7.3% 5.7% 4.9% 6.7% Discount from original list, average

The average is 6.7% for homes over $986K and 7.3% for homes under $815K. It does not move in a straight line; homes under $815K 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

2026-11-01T07:41:00.500358 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 67 50 83 50 33 33 50 50 50 33 33 50 Under $815K $815K–$880K $885K–$986K Over $986K

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

  • 33% of homes over $986K had a price cut before sale, against 67% of homes under $815K. Defined in 8.1.7.
  • 33% of homes over $986K had the seller pay closing costs or repairs, against 50% of homes under $815K. Defined in 8.1.8.
  • 50% of homes over $986K have a view, against 83% of homes under $815K. 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 $815K6 sales$815K–$880K6 sales$885K–$986K6 salesOver $986K6 salesAll24 salesReal difference?
Net sale price average$732,533$843,896$942,042$1,090,415$902,221by design
Net price per SF average$240$266$264$269$260unclear
Living area average3,0863,2063,6174,1233,508unclear
Year built median20172017202120202020unclear

3.10 The numbers: selling

Under $815K6 sales$815K–$880K6 sales$885K–$986K6 salesOver $986K6 salesAll24 salesReal difference?
Days on market median9480405763unclear
Discount from original list average7.3%5.7%4.9%6.7%6.1%unclear
Price cut before sale67%50%50%33%50%unclear
Seller paid closing costs or repairs50%33%50%33%42%unclear
Has a view83%33%50%50%54%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 · 24 sales · November 1, 2025 – October 31, 2026

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

2026-11-01T07:41:00.528617 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 6 6 24 sales Sales per group Under 3,059 SF: 6 sales (25%) 3,059–3,344 SF: 6 sales (25%) 3,364–3,790 SF: 6 sales (25%) Over 3,790 SF: 6 sales (25%)
Bottom line: no measure differs enough between the groups to rule out chance.

4.1 Key differences

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

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 3,059 SF3,059–3,344 SF3,364–3,790 SFOver 3,790 SFReal difference?
Net sale price$787K$899K$861K$1.06Munclear
Net price per SF$282 per SF$277 per SF$238 per SF$242 per SFunclear
Year built2018201820192021unclear
Days on market52 days33 days56 days122 daysunclear
Discount from original list6.4%5.2%5.8%7.2%unclear
Price cut before sale50%33%67%50%unclear
Seller paid closing costs or repairs33%33%50%50%unclear
Has a view33%83%83%17%unclear

4.3 Net sale price: no clear difference

2026-11-01T07:41:00.557185 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,059 SF 6 sales 3,059– 3,344 SF 6 sales 3,364– 3,790 SF 6 sales Over 3,790 SF 6 sales $0K $500K $1.00M $787K $899K $861K $1.06M Net sale price, average

The average is $1.06M for homes over 3,790 SF and $787K for homes under 3,059 SF. It does not move in a straight line; homes over 3,790 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-11-01T07:41:00.594645 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,059 SF 6 sales 3,059– 3,344 SF 6 sales 3,364– 3,790 SF 6 sales Over 3,790 SF 6 sales $0 $100 $200 $300 $282 $277 $238 $242 Net price per SF, average

The average is $242 per SF for homes over 3,790 SF and $282 per SF for homes under 3,059 SF. It does not move in a straight line; homes under 3,059 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-01T07:41:00.627838 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,059 SF 6 sales 3,059– 3,344 SF 6 sales 3,364– 3,790 SF 6 sales Over 3,790 SF 6 sales 2018 2020 2022 2018 2018 2019 2021 Year built: median (dot) and middle half (bar)

The median is 2021 for homes over 3,790 SF and 2018 for homes under 3,059 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-01T07:41:00.668559 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,059 SF 6 sales 3,059– 3,344 SF 6 sales 3,364– 3,790 SF 6 sales Over 3,790 SF 6 sales 0 50 100 52 33 56 122 Days on market, median

The median is 122 days for homes over 3,790 SF and 52 days for homes under 3,059 SF. It does not move in a straight line; homes over 3,790 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-01T07:41:00.708677 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,059 SF 6 sales 3,059– 3,344 SF 6 sales 3,364– 3,790 SF 6 sales Over 3,790 SF 6 sales 0.0% 2.5% 5.0% 7.5% 6.4% 5.2% 5.8% 7.2% Discount from original list, average

The average is 7.2% for homes over 3,790 SF and 6.4% for homes under 3,059 SF. It does not move in a straight line; homes over 3,790 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

2026-11-01T07:41:00.748005 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 50 33 33 33 33 83 67 50 83 50 50 17 Under 3,059 SF 3,059–3,344 SF 3,364–3,790 SF Over 3,790 SF

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

  • 50% of homes over 3,790 SF had a price cut before sale, against 50% of homes under 3,059 SF. Defined in 8.1.7.
  • 50% of homes over 3,790 SF had the seller pay closing costs or repairs, against 33% of homes under 3,059 SF. Defined in 8.1.8.
  • 17% of homes over 3,790 SF have a view, against 33% of homes under 3,059 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 3,059 SF6 sales3,059–3,344 SF6 sales3,364–3,790 SF6 salesOver 3,790 SF6 salesAll24 salesReal difference?
Net sale price average$786,762$898,833$861,042$1,062,248$902,221unclear
Net price per SF average$282$277$238$242$260unclear
Living area average2,7753,2503,6204,3863,508by design
Year built median20182018201920212020unclear

4.10 The numbers: selling

Under 3,059 SF6 sales3,059–3,344 SF6 sales3,364–3,790 SF6 salesOver 3,790 SF6 salesAll24 salesReal difference?
Days on market median52335612263unclear
Discount from original list average6.4%5.2%5.8%7.2%6.1%unclear
Price cut before sale50%33%67%50%50%unclear
Seller paid closing costs or repairs33%33%50%50%42%unclear
Has a view33%83%83%17%54%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 · 24 sales · November 1, 2025 – October 31, 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.

2026-11-01T07:41:00.775831 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 6 5 8 24 sales Sales per group Before 2017: 5 sales (21%) 2017–2019: 6 sales (25%) 2020: 5 sales (21%) After 2020: 8 sales (33%)
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 20172017–20192020After 2020Real difference?
Net sale price$778K$894K$906K$984Kunclear
Net price per SF$245 per SF$283 per SF$252 per SF$256 per SFunclear
Living area3,211 SF3,172 SF3,583 SF3,898 SFunclear
Days on market121 days52 days50 days52 daysunclear
Discount from original list6.9%4.1%9.9%4.9%unclear
Price cut before sale80%33%60%38%unclear
Seller paid closing costs or repairs40%33%60%38%unclear
Has a view40%67%80%38%unclear

5.3 Net sale price: no clear difference

2026-11-01T07:41:00.803873 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 5 sales 2017– 2019 6 sales 2020 5 sales After 2020 8 sales $0K $500K $1.00M $778K $894K $906K $984K Net sale price, average

The average is $984K for homes built after 2020 and $778K for homes built before 2017. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-01T07:41:00.829791 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 5 sales 2017– 2019 6 sales 2020 5 sales After 2020 8 sales $0 $100 $200 $300 $245 $283 $252 $256 Net price per SF, average

The average is $256 per SF for homes built after 2020 and $245 per SF for homes built before 2017. It does not move in a straight line; homes built 2017–2019 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-01T07:41:00.863133 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 5 sales 2017– 2019 6 sales 2020 5 sales After 2020 8 sales 0 2,000 4,000 3,211 3,172 3,583 3,898 Living area (SF), average

The average is 3,898 SF for homes built after 2020 and 3,211 SF for homes built before 2017. It does not move in a straight line; homes built after 2020 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-01T07:41:00.893634 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 5 sales 2017– 2019 6 sales 2020 5 sales After 2020 8 sales 0 50 100 121 52 50 52 Days on market, median

The median is 52 days for homes built after 2020 and 121 days for homes built before 2017. It does not move in a straight line; homes built before 2017 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-01T07:41:00.925249 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 5 sales 2017– 2019 6 sales 2020 5 sales After 2020 8 sales 0.0% 5.0% 10.0% 6.9% 4.1% 9.9% 4.9% Discount from original list, average

The average is 4.9% for homes built after 2020 and 6.9% for homes built before 2017. It does not move in a straight line; homes built 2020 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

2026-11-01T07:41:00.971171 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% 80 40 40 33 33 67 60 60 80 38 38 38 Before 2017 2017–2019 2020 After 2020

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

  • 38% of homes built after 2020 had a price cut before sale, against 80% of homes built before 2017. Defined in 8.1.7.
  • 38% of homes built after 2020 had the seller pay closing costs or repairs, against 40% of homes built before 2017. Defined in 8.1.8.
  • 38% of homes built after 2020 have a view, against 40% of homes built before 2017. 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 20175 sales2017–20196 sales20205 salesAfter 20208 salesAll24 salesReal difference?
Net sale price average$778,500$893,562$905,640$983,905$902,221unclear
Net price per SF average$245$283$252$256$260unclear
Living area average3,2113,1723,5833,8983,508unclear
Year built median20162018202020212020by design

5.10 The numbers: selling

Before 20175 sales2017–20196 sales20205 salesAfter 20208 salesAll24 salesReal difference?
Days on market median12152505263unclear
Discount from original list average6.9%4.1%9.9%4.9%6.1%unclear
Price cut before sale80%33%60%38%50%unclear
Seller paid closing costs or repairs40%33%60%38%42%unclear
Has a view40%67%80%38%54%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 · 24 sales · November 1, 2025 – October 31, 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.

2026-11-01T07:41:01.002544 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 13 11 24 sales Sales per group View: 13 sales (54%) No view: 11 sales (46%)
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$883K$925Kunclear
Net price per SF$260 per SF$260 per SFunclear
Living area3,400 SF3,636 SFunclear
Year built20202020unclear
Days on market40 days104 daysunclear
Discount from original list5.9%6.4%unclear
Price cut before sale38%64%unclear
Seller paid closing costs or repairs46%36%unclear

6.3 Net sale price: no clear difference

2026-11-01T07:41:01.032976 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 13 sales No view 11 sales $0K $250K $500K $750K $1.00M $883K $925K Net sale price, average

The average is $883K for homes with a view and $925K 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

2026-11-01T07:41:01.061781 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 13 sales No view 11 sales $0 $100 $200 $300 $260 $260 Net price per SF, average

The average is $260 per SF for homes with a view and $260 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

2026-11-01T07:41:01.083533 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 13 sales No view 11 sales 0 1,000 2,000 3,000 4,000 3,400 3,636 Living area (SF), average

The average is 3,400 SF for homes with a view and 3,636 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-01T07:41:01.194008 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 13 sales No view 11 sales 2017 2018 2019 2020 2021 2020 2020 Year built: median (dot) and middle half (bar)

The median is 2020 for homes with a view and 2020 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-01T07:41:01.221069 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 13 sales No view 11 sales 0 25 50 75 100 40 104 Days on market, median

The median is 40 days for homes with a view and 104 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

2026-11-01T07:41:01.247794 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 13 sales No view 11 sales 0.0% 2.0% 4.0% 6.0% 5.9% 6.4% Discount from original list, average

The average is 5.9% for homes with a view and 6.4% 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

2026-11-01T07:41:01.277154 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 38 46 64 36 View No view

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

  • 38% of homes with a view had a price cut before sale, against 64% of homes without a view. Defined in 8.1.7.
  • 46% of homes with a view had the seller pay closing costs or repairs, against 36% 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

View13 salesNo view11 salesAll24 salesReal difference?
Net sale price average$882,535$925,488$902,221unclear
Net price per SF average$260$260$260unclear
Living area average3,4003,6363,508unclear
Year built median202020202020unclear

6.11 The numbers: selling

View13 salesNo view11 salesAll24 salesReal difference?
Days on market median4010463unclear
Discount from original list average5.9%6.4%6.1%unclear
Price cut before sale38%64%50%unclear
Seller paid closing costs or repairs46%36%42%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 · 14 sales · November 1, 2025 – October 31, 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: 14 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 Clearwater Ranch-Ph.
MeasureAverageMedian
Sales14
Net sale price$1,048,201$1,004,000
Net price per SF$261$258
Living area (SF)4,0683,965
Days on market135119
Discount from original list7.7%7.8%
Price cut before sale50% of sales
Seller paid closing costs or repairs14% of sales
Year built2025–2026

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
24 resale sales. Average $902,221; median $882,688; standard deviation $146,467; middle half (25th–75th percentile) $811,000–$992,000; lowest $588,200, highest $1,199,990. 10 sales had a seller payment; their median payment was $7,000.

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
24 resale sales. Average $260; median $253; standard deviation $31; middle half (25th–75th percentile) $234–$282; lowest $219, highest $312.

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
24 resale sales. Average 3,508; median 3,354; standard deviation 655; middle half (25th–75th percentile) 3,056–3,824; lowest 2,391, highest 5,094.

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
24 resale sales. Average 2019; median 2020; standard deviation 3; middle half (25th–75th percentile) 2017–2021; lowest 2014, 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
24 resale sales. Average 104; median 63; standard deviation 113; middle half (25th–75th percentile) 30–130; lowest 0, highest 425. 1 sales went under contract on their listing date (0 days).

8.1.6 Discount from original list

In simple terms
How far below the first asking price the home sold, after seller payments. It measures how much negotiating room sellers gave up. A negative figure means the home sold above its first asking price.
Statistically
Discount % = (OriginalListPrice − Net) ÷ OriginalListPrice × 100, per sale; summarized by the mean.
The data
24 resale sales. Average 6.1%; median 5.2%; standard deviation 5.3%; middle half (25th–75th percentile) 2.0%–9.4%; lowest −0.7%, highest 22.4%. 1 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
12 of 24 resale sales (50.0%).

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
10 of 24 resale sales (41.7%).

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
13 sales with a view, 11 without, 0 unclassified. Most common View entries: None 10, Trees/Woods 7, Hill Country 5, Neighborhood 5, Pool 4, Pasture 2, Garden 1, Panoramic 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 2026-11-01 13:30 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Liberty Hill, SubdivisionName contains any of “clearwater ranch ph”, “clearwater ranch”, “clearwater ranch-ph” (case-insensitive). A record is kept when its subdivision name belongs to the Clearwater Ranch-Ph family, the same rule comparable sales use.
The data
Pulled November 1, 2026: 40 closed Clearwater Ranch-Ph records over the prior year, in ZIP 78642. 9 subdivision spellings kept: Clearwater Ranch (17); Clearwater Ranch Ph 1 (6); Clearwater Ranch Ph 2 (6); Clearwater Ranch Ph 5 (4); Clearwater Ranch-Ph 5 (2); Clearwater Ranch Ph Four (2); CLEARWATER RANCH (1); Clearwater Ranch Ph 4 (1); Clearwater Ranch Phase 5 (1). No other names were found by the search.

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 17 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 1, 2025 to October 31, 2026 inclusive.
The data
38 single-family sales in the window: 24 resale, 14 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
24 resale; 14 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) with concessions above 10% of price

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 $815K”.
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 $815K: $588,200–$799,000 (6 sales); $815K–$880K: $815,000–$880,375 (6 sales); $885K–$986K: $885,000–$986,000 (6 sales); Over $986K: $1,010,000–$1,199,990 (6 sales)
Quartiles by living area: Under 3,059 SF: 2,391–3,046 SF (6 sales); 3,059–3,344 SF: 3,059–3,344 SF (6 sales); 3,364–3,790 SF: 3,364–3,790 SF (6 sales); Over 3,790 SF: 3,926–5,094 SF (6 sales)
Quartiles by year built: Before 2017: 2014–2016 (5 sales); 2017–2019: 2017–2019 (6 sales); 2020: 2020–2020 (5 sales); After 2020: 2021–2024 (8 sales)
View and no view: View: MLS lists a view (13 sales); No view: None or Neighborhood (11 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 $902,221, median $882,688. Days on market: average 104, median 63: 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
0 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 = 3.3330.3439p < 0.0063Unclearε² = 0.145large
Living areaKruskal–WallisH = 8.1930.0423p < 0.0063Unclearε² = 0.356large
Year builtKruskal–WallisH = 11.0030.0117p < 0.0063Unclearε² = 0.478large
Days on marketKruskal–WallisH = 0.7630.8593p < 0.0063Unclearε² = 0.033small
Discount from original listKruskal–WallisH = 0.6130.8934p < 0.0063Unclearε² = 0.027small
Price cut before saleChi-squareχ² = 1.3330.7212p < 0.0063UnclearCramér’s V = 0.236small
Seller paid closing costs or repairsChi-squareχ² = 0.6930.8766p < 0.0063UnclearCramér’s V = 0.169small
Has a viewChi-squareχ² = 3.1930.3634p < 0.0063UnclearCramér’s V = 0.365medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 10.3230.0161p < 0.0063Unclearε² = 0.449large
Net price per SFKruskal–WallisH = 10.1330.0175p < 0.0063Unclearε² = 0.440large
Year builtKruskal–WallisH = 6.5030.0898p < 0.0063Unclearε² = 0.282large
Days on marketKruskal–WallisH = 3.0530.3845p < 0.0063Unclearε² = 0.132medium
Discount from original listKruskal–WallisH = 0.9130.8222p < 0.0063Unclearε² = 0.040small
Price cut before saleChi-squareχ² = 1.3330.7212p < 0.0063UnclearCramér’s V = 0.236small
Seller paid closing costs or repairsChi-squareχ² = 0.6930.8766p < 0.0063UnclearCramér’s V = 0.169small
Has a viewChi-squareχ² = 8.5630.0358p < 0.0063UnclearCramér’s V = 0.597large

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 7.8330.0498p < 0.0063Unclearε² = 0.340large
Net price per SFKruskal–WallisH = 4.0430.2573p < 0.0063Unclearε² = 0.176large
Living areaKruskal–WallisH = 5.3530.1479p < 0.0063Unclearε² = 0.233large
Days on marketKruskal–WallisH = 1.3130.7257p < 0.0063Unclearε² = 0.057small
Discount from original listKruskal–WallisH = 2.6530.4484p < 0.0063Unclearε² = 0.115medium
Price cut before saleChi-squareχ² = 3.1730.3666p < 0.0063UnclearCramér’s V = 0.363medium
Seller paid closing costs or repairsChi-squareχ² = 0.9330.8192p < 0.0063UnclearCramér’s V = 0.196small
Has a viewChi-squareχ² = 3.0230.3884p < 0.0063UnclearCramér’s V = 0.355medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 58.00—0.4512p < 0.0063Unclearrank-biserial r = 0.189small
Net price per SFMann–Whitney UU = 73.00—0.9538p < 0.0063Unclearrank-biserial r = 0.021negligible
Living areaMann–Whitney UU = 64.00—0.6850p < 0.0063Unclearrank-biserial r = 0.105small
Year builtMann–Whitney UU = 64.00—0.6818p < 0.0063Unclearrank-biserial r = 0.105small
Days on marketMann–Whitney UU = 44.50—0.1246p < 0.0063Unclearrank-biserial r = 0.378medium
Discount from original listMann–Whitney UU = 59.00—0.4869p < 0.0063Unclearrank-biserial r = 0.175small
Price cut before saleChi-squareχ² = 1.5110.2191p < 0.0063UnclearCramér’s V = 0.251small
Seller paid closing costs or repairsChi-squareχ² = 0.2310.6279p < 0.0063UnclearCramér’s V = 0.099negligible

8.4 Data notes

Left out of the analysis: 14 new-construction sales (basic statistics only, section 7); 2 sale(s) with concessions above 10% of price. 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 24 closed MLS resale sales; the 14 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 1, 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.