ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Briarcliff Inc

Spicewood, TX 78669
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 · 5:54 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
27
single-family resale homes
Median net sale price
$465,000
average $581,828
Median net price per SF
$227
average $238
Median days on market
107 days
average 154 days
1. SummaryResale homes · 27 sales · October 26, 2025 – October 25, 2026

This study looks at the 27 resale homes sold in Briarcliff Inc in the 365 days to October 25, 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 $405K · 7 sales$405K–$452K · 6 sales$465K–$641K · 7 salesOver $641K · 7 sales
3. Quartiles by net sale priceResale homes · 27 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.

2026-10-26T05:54:53.834368 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 6 7 7 27 sales Sales per group Under $405K: 7 sales (26%) $405K–$452K: 6 sales (22%) $465K–$641K: 7 sales (26%) Over $641K: 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 $405K$405K–$452K$465K–$641KOver $641K
Higher-priced homes Over $641K
  • Are much larger.
Lower-priced homes Under $405K
  • 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 $405K$405K–$452K$465K–$641KOver $641KReal difference?
Net price per SF$197 per SF$216 per SF$257 per SF$279 per SFunclear
Living area1,619 SFSmallest2,075 SF2,259 SF3,504 SFLargest✓ large
Year built1998201420052001unclear
Days on market107 days177 days64 days85 daysunclear
Discount from original list10.5%10.1%3.7%16.0%unclear
Price cut before sale57%83%57%71%unclear
Seller paid closing costs or repairs43%33%71%57%unclear
Has a view57%83%86%86%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

2026-10-26T05:54:53.866956 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $405K 7 sales $405K– $452K 6 sales $465K– $641K 7 sales Over $641K 7 sales $0 $100 $200 $300 $197 $216 $257 $279 Net price per SF, average

The average is $279 per SF for homes over $641K and $197 per SF for homes under $405K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $641K are about 1,880 SF (116%) larger than homes under $405K

2026-10-26T05:54:53.894302 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $405K 7 sales $405K– $452K 6 sales $465K– $641K 7 sales Over $641K 7 sales 0 2,000 4,000 1,619 2,075 2,259 3,504 Living area (SF), average

The average is 3,504 SF for homes over $641K and 1,619 SF for homes under $405K. 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

2026-10-26T05:54:53.921598 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $405K 7 sales $405K– $452K 6 sales $465K– $641K 7 sales Over $641K 7 sales 1984 1992 2000 2008 2016 1998 2014 2005 2001 Year built: median (dot) and middle half (bar)

The median is 2001 for homes over $641K and 1998 for homes under $405K. It does not move in a straight line; homes $405K–$452K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:54:53.945833 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $405K 7 sales $405K– $452K 6 sales $465K– $641K 7 sales Over $641K 7 sales 0 100 200 107 177 64 85 Days on market, median

The median is 85 days for homes over $641K and 107 days for homes under $405K. It does not move in a straight line; homes $405K–$452K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:54:53.969197 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $405K 7 sales $405K– $452K 6 sales $465K– $641K 7 sales Over $641K 7 sales 0.0% 5.0% 10.0% 15.0% 10.5% 10.1% 3.7% 16.0% Discount from original list, average

The average is 16.0% for homes over $641K and 10.5% for homes under $405K. It does not move in a straight line; homes over $641K 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

2026-10-26T05:54:54.001069 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 57 83 33 83 57 71 86 71 57 86 Under $405K $405K–$452K $465K–$641K Over $641K

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

  • 71% of homes over $641K had a price cut before sale, against 57% of homes under $405K. Defined in 8.1.7.
  • 57% of homes over $641K had the seller pay closing costs or repairs, against 43% of homes under $405K. Defined in 8.1.8.
  • 86% of homes over $641K have a view, against 57% of homes under $405K. 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 $405K7 sales$405K–$452K6 sales$465K–$641K7 salesOver $641K7 salesAll27 salesReal difference?
Net sale price average$313,450$441,078$552,249$1,000,429$581,828by design
Net price per SF average$197$216$257$279$238unclear
Living area average1,6192,0752,2593,5042,375✓ large
Year built median19982014200520012005unclear

3.10 The numbers: selling

Under $405K7 sales$405K–$452K6 sales$465K–$641K7 salesOver $641K7 salesAll27 salesReal difference?
Days on market median1071776485107unclear
Discount from original list average10.5%10.1%3.7%16.0%10.0%unclear
Price cut before sale57%83%57%71%67%unclear
Seller paid closing costs or repairs43%33%71%57%52%unclear
Has a view57%83%86%86%78%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 · October 26, 2025 – October 25, 2026

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

2026-10-26T05:54:54.021852 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 6 7 27 sales Sales per group Under 1,761 SF: 7 sales (26%) 1,761–2,014 SF: 7 sales (26%) 2,051–2,754 SF: 6 sales (22%) Over 2,754 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 1,761 SF1,761–2,014 SF2,051–2,754 SFOver 2,754 SF
Larger homes Over 2,754 SF
  • Are more likely to have a view.
  • Sell for much more.
Smaller homes Under 1,761 SF
  • Are less likely to have a view.
  • Sell for much less.

4.2 At a glance

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

Under 1,761 SF1,761–2,014 SF2,051–2,754 SFOver 2,754 SFReal difference?
Net sale price$371KLowest$443K$526K$979KHighest✓ large
Net price per SF$238 per SF$229 per SF$219 per SF$263 per SFunclear
Year built1999201020122001unclear
Days on market107 days107 days130 days85 daysunclear
Discount from original list3.1%8.2%11.5%17.5%unclear
Price cut before sale57%57%83%71%unclear
Seller paid closing costs or repairs14%57%83%57%unclear
Has a view29%Fewest100%100%Most86%✓ large

4.3 Homes over 2,754 SF sell for about $609K (164%) more than homes under 1,761 SF

2026-10-26T05:54:54.042592 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,761 SF 7 sales 1,761– 2,014 SF 7 sales 2,051– 2,754 SF 6 sales Over 2,754 SF 7 sales $0K $500K $1.00M $371K $443K $526K $979K Net sale price, average

The average is $979K for homes over 2,754 SF and $371K for homes under 1,761 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

2026-10-26T05:54:54.065297 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,761 SF 7 sales 1,761– 2,014 SF 7 sales 2,051– 2,754 SF 6 sales Over 2,754 SF 7 sales $0 $100 $200 $300 $238 $229 $219 $263 Net price per SF, average

The average is $263 per SF for homes over 2,754 SF and $238 per SF for homes under 1,761 SF. It does not move in a straight line; homes over 2,754 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T05:54:54.090608 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,761 SF 7 sales 1,761– 2,014 SF 7 sales 2,051– 2,754 SF 6 sales Over 2,754 SF 7 sales 1992 1998 2004 2010 2016 1999 2010 2012 2001 Year built: median (dot) and middle half (bar)

The median is 2001 for homes over 2,754 SF and 1999 for homes under 1,761 SF. It does not move in a straight line; homes 2,051–2,754 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T05:54:54.114406 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,761 SF 7 sales 1,761– 2,014 SF 7 sales 2,051– 2,754 SF 6 sales Over 2,754 SF 7 sales 0 50 100 150 107 107 130 85 Days on market, median

The median is 85 days for homes over 2,754 SF and 107 days for homes under 1,761 SF. It does not move in a straight line; homes 2,051–2,754 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T05:54:54.136996 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,761 SF 7 sales 1,761– 2,014 SF 7 sales 2,051– 2,754 SF 6 sales Over 2,754 SF 7 sales 0.0% 10.0% 20.0% 3.1% 8.2% 11.5% 17.5% Discount from original list, average

The average is 17.5% for homes over 2,754 SF and 3.1% for homes under 1,761 SF. It rises step by step from the lowest range to the 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

2026-10-26T05:54:54.163738 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 14 29 57 57 100 83 83 100 71 57 86 Under 1,761 SF 1,761–2,014 SF 2,051–2,754 SF Over 2,754 SF

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

  • 71% of homes over 2,754 SF had a price cut before sale, against 57% of homes under 1,761 SF. Defined in 8.1.7.
  • 57% of homes over 2,754 SF had the seller pay closing costs or repairs, against 14% of homes under 1,761 SF. Defined in 8.1.8.
  • 86% of homes over 2,754 SF have a view, against 29% of homes under 1,761 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: ✓ Real difference · large

4.9 The numbers: price and size

Under 1,761 SF7 sales1,761–2,014 SF7 sales2,051–2,754 SF6 salesOver 2,754 SF7 salesAll27 salesReal difference?
Net sale price average$370,507$443,493$525,893$979,429$581,828✓ large
Net price per SF average$238$229$219$263$238unclear
Living area average1,5641,9292,4013,6102,375by design
Year built median19992010201220012005unclear

4.10 The numbers: selling

Under 1,761 SF7 sales1,761–2,014 SF7 sales2,051–2,754 SF6 salesOver 2,754 SF7 salesAll27 salesReal difference?
Days on market median10710713085107unclear
Discount from original list average3.1%8.2%11.5%17.5%10.0%unclear
Price cut before sale57%57%83%71%67%unclear
Seller paid closing costs or repairs14%57%83%57%52%unclear
Has a view29%100%100%86%78%✓ large

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 · 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.

2026-10-26T05:54:54.184310 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 8 6 7 27 sales Sales per group Before 1999: 6 sales (22%) 1999–2005: 8 sales (30%) 2006–2012: 6 sales (22%) After 2012: 7 sales (26%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

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

5.2 At a glance

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

Before 19991999–20052006–2012After 2012Real difference?
Net sale price$384K$759K$525K$597Kunclear
Net price per SF$193 per SF$263 per SF$231 per SF$254 per SFunclear
Living area2,023 SF2,758 SF2,275 SF2,324 SFunclear
Days on market80 days24 days242 days100 daysunclear
Discount from original list14.6%3.5%13.1%11.0%unclear
Price cut before sale50%38%83%100%unclear
Seller paid closing costs or repairs50%50%67%43%unclear
Has a view67%62%100%86%unclear

5.3 Net sale price: no clear difference

2026-10-26T05:54:54.205172 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 6 sales 1999– 2005 8 sales 2006– 2012 6 sales After 2012 7 sales $0K $250K $500K $750K $384K $759K $525K $597K Net sale price, average

The average is $597K for homes built after 2012 and $384K for homes built before 1999. It does not move in a straight line; homes built 1999–2005 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T05:54:54.228203 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 6 sales 1999– 2005 8 sales 2006– 2012 6 sales After 2012 7 sales $0 $100 $200 $300 $193 $263 $231 $254 Net price per SF, average

The average is $254 per SF for homes built after 2012 and $193 per SF for homes built before 1999. It does not move in a straight line; homes built 1999–2005 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T05:54:54.250060 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 6 sales 1999– 2005 8 sales 2006– 2012 6 sales After 2012 7 sales 0 1,000 2,000 3,000 2,023 2,758 2,275 2,324 Living area (SF), average

The average is 2,324 SF for homes built after 2012 and 2,023 SF for homes built before 1999. It does not move in a straight line; homes built 1999–2005 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T05:54:54.272218 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 6 sales 1999– 2005 8 sales 2006– 2012 6 sales After 2012 7 sales 0 100 200 80 24 242 100 Days on market, median

The median is 100 days for homes built after 2012 and 80 days for homes built before 1999. It does not move in a straight line; homes built 2006–2012 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T05:54:54.294511 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 6 sales 1999– 2005 8 sales 2006– 2012 6 sales After 2012 7 sales 0.0% 5.0% 10.0% 15.0% 14.6% 3.5% 13.1% 11.0% Discount from original list, average

The average is 11.0% for homes built after 2012 and 14.6% for homes built before 1999. It does not move in a straight line; homes built before 1999 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

2026-10-26T05:54:54.320246 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 50 67 38 50 62 83 67 100 100 43 86 Before 1999 1999–2005 2006–2012 After 2012

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

  • 100% of homes built after 2012 had a price cut before sale, against 50% of homes built before 1999. Defined in 8.1.7.
  • 43% of homes built after 2012 had the seller pay closing costs or repairs, against 50% of homes built before 1999. Defined in 8.1.8.
  • 86% of homes built after 2012 have a view, against 67% of homes built before 1999. 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 19996 sales1999–20058 sales2006–20126 salesAfter 20127 salesAll27 salesReal difference?
Net sale price average$384,167$759,256$524,767$597,387$581,828unclear
Net price per SF average$193$263$231$254$238unclear
Living area average2,0232,7582,2752,3242,375unclear
Year built median19792001200820172005by design

5.10 The numbers: selling

Before 19996 sales1999–20058 sales2006–20126 salesAfter 20127 salesAll27 salesReal difference?
Days on market median8024242100107unclear
Discount from original list average14.6%3.5%13.1%11.0%10.0%unclear
Price cut before sale50%38%83%100%67%unclear
Seller paid closing costs or repairs50%50%67%43%52%unclear
Has a view67%62%100%86%78%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 · 27 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.

2026-10-26T05:54:54.339300 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 21 6 27 sales Sales per group View: 21 sales (78%) No view: 6 sales (22%)
Bottom line

6.1 Key differences

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

ViewNo view
Homes with a view MLS lists a view
  • Are much larger.
  • Sell further below their first asking price.
Homes without a view no view listed
  • Are much smaller.
  • Sell closer to their first asking price.

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$614K$470Kunclear
Net price per SF$231 per SF$262 per SFunclear
Living area2,529 SFLargest1,836 SFSmallest✓ large
Year built20072000unclear
Days on market110 days24 daysunclear
Discount from original list13.6%Biggest-2.4%Smallest✓ large
Price cut before sale76%33%unclear
Seller paid closing costs or repairs57%33%unclear

6.3 Net sale price: no clear difference

2026-10-26T05:54:54.355187 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 21 sales No view 6 sales $0K $200K $400K $600K $614K $470K Net sale price, average

The average is $614K for homes with a view and $470K 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

2026-10-26T05:54:54.372635 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 21 sales No view 6 sales $0 $100 $200 $300 $231 $262 Net price per SF, average

The average is $231 per SF for homes with a view and $262 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Homes with a view are about 690 SF (38%) larger than homes without a view

2026-10-26T05:54:54.391242 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 21 sales No view 6 sales 0 1,000 2,000 3,000 2,529 1,836 Living area (SF), average

The average is 2,529 SF for homes with a view and 1,836 SF for homes without a view. Defined in 8.1.3.

✓ Real difference · large

6.6 Year built: no clear difference

2026-10-26T05:54:54.440973 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 21 sales No view 6 sales 2000 2004 2008 2012 2016 2007 2000 Year built: median (dot) and middle half (bar)

The median is 2007 for homes with a view and 2000 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T05:54:54.461566 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 21 sales No view 6 sales 0 50 100 110 24 Days on market, median

The median is 110 days for homes with a view and 24 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Homes with a view sell about 16 percentage points further below their first asking price than homes without a view

2026-10-26T05:54:54.481111 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 21 sales No view 6 sales 0.0% 5.0% 10.0% 15.0% 13.6% -2.4% Discount from original list, average

The average is 13.6% for homes with a view and -2.4% for homes without a view. Defined in 8.1.6.

✓ Real difference · large

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

2026-10-26T05:54:54.500134 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 76 57 33 33 View No view

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

  • 76% of homes with a view had a price cut before sale, against 33% of homes without a view. Defined in 8.1.7.
  • 57% of homes with a view had the seller pay closing costs or repairs, against 33% 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

View21 salesNo view6 salesAll27 salesReal difference?
Net sale price average$613,896$469,592$581,828unclear
Net price per SF average$231$262$238unclear
Living area average2,5291,8362,375✓ large
Year built median200720002005unclear

6.11 The numbers: selling

View21 salesNo view6 salesAll27 salesReal difference?
Days on market median11024107unclear
Discount from original list average13.6%−2.4%10.0%✓ large
Price cut before sale76%33%67%unclear
Seller paid closing costs or repairs57%33%52%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 · 2 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: 2 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 Briarcliff Inc.
MeasureAverageMedian
Sales2
Net sale price$693,750$693,750
Net price per SF$266$266
Living area (SF)2,6282,628
Days on market126126
Discount from original list14.4%14.4%
Price cut before sale100% of sales
Seller paid closing costs or repairs0% 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
27 resale sales. Average $581,828; median $465,000; standard deviation $337,099; middle half (25th–75th percentile) $395,000–$643,197; lowest $140,000, highest $1,800,000. 14 sales had a seller payment; their median payment was $10,000.

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
27 resale sales. Average $238; median $227; standard deviation $65; middle half (25th–75th percentile) $197–$268; lowest $83, highest $383.

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 2,375; median 2,014; standard deviation 866; middle half (25th–75th percentile) 1,730–2,806; lowest 1,344, highest 4,848.

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 2003; median 2005; standard deviation 14; middle half (25th–75th percentile) 1999–2012; lowest 1969, 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
27 resale sales. Average 154; median 107; standard deviation 171; middle half (25th–75th percentile) 36–190; lowest 5, highest 731. 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 10.0%; median 7.4%; standard deviation 13.8%; middle half (25th–75th percentile) 5.3%–16.7%; lowest −32.6%, highest 40.0%. 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
18 of 27 resale sales (66.7%).

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
14 of 27 resale sales (51.9%).

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
21 sales with a view, 6 without, 0 unclassified. Most common View entries: Hill Country 18, Lake 8, Panoramic 6, Neighborhood 6, Trees/Woods 5, Park/Greenbelt 4, None 3, River 2.

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 = Spicewood, SubdivisionName contains any of “briarcliff inc” (case-insensitive). A record is kept when its subdivision name belongs to the Briarcliff Inc family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 29 closed Briarcliff Inc records over the prior year, in ZIP 78669. 11 subdivision spellings kept: Briarcliff Inc Sec 01 (5); Briarcliff Inc Sec 04 (4); Briarcliff Inc Sec 15 (4); Briarcliff Inc Sec 06 (3); Briarcliff Inc Sec 16 (3); Briarcliff Inc Sec 09 Amd (3); Briarcliff Inc Sec 14 (2); Briarcliff Inc Sec 12 (2); Briarcliff Inc Sec 11 (1); Briarcliff Inc Sec 10 (1); Briarcliff Inc Sec 13 (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 14 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
29 single-family sales in the window: 27 resale, 2 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; 2 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 $405K”.
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 $405K: $140,000–$385,000 (7 sales); $405K–$452K: $405,000–$452,000 (6 sales); $465K–$641K: $465,000–$641,394 (7 sales); Over $641K: $645,000–$1,800,000 (7 sales)
Quartiles by living area: Under 1,761 SF: 1,344–1,699 SF (7 sales); 1,761–2,014 SF: 1,761–2,014 SF (7 sales); 2,051–2,754 SF: 2,051–2,754 SF (6 sales); Over 2,754 SF: 2,859–4,848 SF (7 sales)
Quartiles by year built: Before 1999: 1969–1998 (6 sales); 1999–2005: 1999–2005 (8 sales); 2006–2012: 2006–2012 (6 sales); After 2012: 2013–2023 (7 sales)
View and no view: View: MLS lists a view (21 sales); No view: None or Neighborhood (6 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 $581,828, median $465,000. Days on market: average 154, median 107: 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
5 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 = 5.7530.1245p < 0.0063Unclearε² = 0.221large
Living areaKruskal–WallisH = 17.7930.0005p < 0.0063Yesε² = 0.684large
Year builtKruskal–WallisH = 7.6730.0533p < 0.0063Unclearε² = 0.295large
Days on marketKruskal–WallisH = 3.3130.3460p < 0.0063Unclearε² = 0.127medium
Discount from original listKruskal–WallisH = 4.0930.2518p < 0.0063Unclearε² = 0.157large
Price cut before saleChi-squareχ² = 1.3930.7072p < 0.0063UnclearCramér’s V = 0.227small
Seller paid closing costs or repairsChi-squareχ² = 2.2030.5311p < 0.0063UnclearCramér’s V = 0.286small
Has a viewChi-squareχ² = 2.3430.5046p < 0.0063UnclearCramér’s V = 0.295small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 15.6630.0013p < 0.0063Yesε² = 0.602large
Net price per SFKruskal–WallisH = 1.1930.7566p < 0.0063Unclearε² = 0.046small
Year builtKruskal–WallisH = 5.1530.1615p < 0.0063Unclearε² = 0.198large
Days on marketKruskal–WallisH = 0.6830.8767p < 0.0063Unclearε² = 0.026small
Discount from original listKruskal–WallisH = 3.7930.2854p < 0.0063Unclearε² = 0.146large
Price cut before saleChi-squareχ² = 1.3930.7072p < 0.0063UnclearCramér’s V = 0.227small
Seller paid closing costs or repairsChi-squareχ² = 6.5030.0898p < 0.0063UnclearCramér’s V = 0.490medium
Has a viewChi-squareχ² = 13.7830.0032p < 0.0063YesCramér’s V = 0.714large

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 4.5030.2119p < 0.0063Unclearε² = 0.173large
Net price per SFKruskal–WallisH = 3.3430.3424p < 0.0063Unclearε² = 0.128medium
Living areaKruskal–WallisH = 2.4530.4840p < 0.0063Unclearε² = 0.094medium
Days on marketKruskal–WallisH = 8.9130.0305p < 0.0063Unclearε² = 0.343large
Discount from original listKruskal–WallisH = 4.3930.2223p < 0.0063Unclearε² = 0.169large
Price cut before saleChi-squareχ² = 8.0630.0447p < 0.0063UnclearCramér’s V = 0.546large
Seller paid closing costs or repairsChi-squareχ² = 0.7730.8558p < 0.0063UnclearCramér’s V = 0.169small
Has a viewChi-squareχ² = 3.4830.3236p < 0.0063UnclearCramér’s V = 0.359medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 83.00—0.2553p < 0.0063Unclearrank-biserial r = 0.317medium
Net price per SFMann–Whitney UU = 45.00—0.3163p < 0.0063Unclearrank-biserial r = 0.286small
Living areaMann–Whitney UU = 109.00—0.0054p < 0.0063Yesrank-biserial r = 0.730large
Year builtMann–Whitney UU = 85.00—0.2095p < 0.0063Unclearrank-biserial r = 0.349medium
Days on marketMann–Whitney UU = 99.50—0.0357p < 0.0063Unclearrank-biserial r = 0.579large
Discount from original listMann–Whitney UU = 109.00—0.0054p < 0.0063Yesrank-biserial r = 0.730large
Price cut before saleChi-squareχ² = 3.8610.0495p < 0.0063UnclearCramér’s V = 0.378medium
Seller paid closing costs or repairsChi-squareχ² = 1.0610.3033p < 0.0063UnclearCramér’s V = 0.198small

8.4 Data notes

Left out of the analysis: 2 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 2 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.