ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Waterleaf

Kyle, TX 78640
Resale homes · closed Nov 5 – Nov 4, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 5, 2026 · 2:43 PM 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
30
single-family resale homes
Median net sale price
$261,700
average $268,203
Median net price per SF
$128
average $129
Median days on market
74 days
average 90 days
1. SummaryResale homes · 30 sales · November 5, 2025 – November 4, 2026

This study looks at the 30 resale homes sold in Waterleaf in the 365 days to November 4, 2026. A full year is used because only 19 resale homes sold in the last 180 days. New construction is left out and shown on its own in section 7. The homes are compared four ways: by price, by living area, by year built and with or without a view. The first three are split into four equal groups (quartiles), each named by its range.

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

2. Where the resale homes sold30 resale homes · colored by price range

Each dot is one resale home, colored by its price range. Use the buttons to show one price range at a time. Click a dot for that sale: address, close date, original and last list price, net sale price, living area, net sale per SF and days on market. Scroll or pinch to zoom.

Under $236K · 8 sales$236K–$260K · 7 sales$264K–$288K · 7 salesOver $288K · 8 sales
3. Quartiles by net sale priceResale homes · 30 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T14:43:16.657794 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Under $236K: 8 sales (27%) $236K–$260K: 7 sales (23%) $264K–$288K: 7 sales (23%) Over $288K: 8 sales (27%)
Bottom line

3.1 Key differences

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

Under $236K$236K–$260K$264K–$288KOver $288K
Higher-priced homes Over $288K
  • Are much larger.
Lower-priced homes Under $236K
  • 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 $236K$236K–$260K$264K–$288KOver $288KReal difference?
Net price per SF$138 per SF$134 per SF$128 per SF$118 per SFunclear
Living area1,653 SFSmallest1,877 SF2,218 SF2,789 SFLargest✓ large
Year built2008200620122010unclear
Days on market96 days36 days35 days74 daysunclear
Discount from original list13.3%8.4%8.2%7.8%unclear
Price cut before sale75%29%43%50%unclear
Seller paid closing costs or repairs75%86%86%88%unclear
Has a view12%43%43%25%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

2026-11-05T14:43:16.685381 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $236K 8 sales $236K– $260K 7 sales $264K– $288K 7 sales Over $288K 8 sales $0 $50 $100 $150 $138 $134 $128 $118 Net price per SF, average

The average is $118 per SF for homes over $288K and $138 per SF for homes under $236K. It falls 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 $288K are about 1,140 SF (69%) larger than homes under $236K

2026-11-05T14:43:16.707649 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $236K 8 sales $236K– $260K 7 sales $264K– $288K 7 sales Over $288K 8 sales 0 1,000 2,000 3,000 1,653 1,877 2,218 2,789 Living area (SF), average

The average is 2,789 SF for homes over $288K and 1,653 SF for homes under $236K. 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

2026-11-05T14:43:16.731216 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $236K 8 sales $236K– $260K 7 sales $264K– $288K 7 sales Over $288K 8 sales 2006 2008 2010 2012 2008 2006 2012 2010 Year built: median (dot) and middle half (bar)

The median is 2010 for homes over $288K and 2008 for homes under $236K. It does not move in a straight line; homes $264K–$288K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-05T14:43:16.753846 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $236K 8 sales $236K– $260K 7 sales $264K– $288K 7 sales Over $288K 8 sales 0 50 100 96 36 35 74 Days on market, median

The median is 74 days for homes over $288K and 96 days for homes under $236K. It does not move in a straight line; homes under $236K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-05T14:43:16.774768 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $236K 8 sales $236K– $260K 7 sales $264K– $288K 7 sales Over $288K 8 sales 0.0% 5.0% 10.0% 15.0% 13.3% 8.4% 8.2% 7.8% Discount from original list, average

The average is 7.8% for homes over $288K and 13.3% for homes under $236K. It falls step by step from the lowest range to the 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

2026-11-05T14:43:16.804257 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% 75 75 12 29 86 43 43 86 43 50 88 25 Under $236K $236K–$260K $264K–$288K Over $288K

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

  • 50% of homes over $288K had a price cut before sale, against 75% of homes under $236K. Defined in 8.1.7.
  • 88% of homes over $288K had the seller pay closing costs or repairs, against 75% of homes under $236K. Defined in 8.1.8.
  • 25% of homes over $288K have a view, against 12% of homes under $236K. 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 $236K8 sales$236K–$260K7 sales$264K–$288K7 salesOver $288K8 salesAll30 salesReal difference?
Net sale price average$219,109$251,286$277,814$323,690$268,203by design
Net price per SF average$138$134$128$118$129unclear
Living area average1,6531,8772,2182,7892,140✓ large
Year built median20082006201220102009unclear

3.10 The numbers: selling

Under $236K8 sales$236K–$260K7 sales$264K–$288K7 salesOver $288K8 salesAll30 salesReal difference?
Days on market median9636357474unclear
Discount from original list average13.3%8.4%8.2%7.8%9.5%unclear
Price cut before sale75%29%43%50%50%unclear
Seller paid closing costs or repairs75%86%86%88%83%unclear
Has a view12%43%43%25%30%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.1.

4. Quartiles by living areaResale homes · 30 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T14:43:16.824591 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 5 9 8 30 sales Sales per group Under 1,843 SF: 8 sales (27%) 1,843–1,964 SF: 5 sales (17%) 1,991–2,245 SF: 9 sales (30%) Over 2,245 SF: 8 sales (27%)
Bottom line

4.1 Key differences

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

Under 1,843 SF1,843–1,964 SF1,991–2,245 SFOver 2,245 SF
Larger homes Over 2,245 SF
  • Sell for much more.
  • Sell for less per square foot.
Smaller homes Under 1,843 SF
  • Sell for much less.
  • Sell for more per square foot.

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 1,843 SF1,843–1,964 SF1,991–2,245 SFOver 2,245 SFReal difference?
Net sale price$234KLowest$237K$269K$321KHighest✓ large
Net price per SF$151 per SFHighest$124 per SF$130 per SF$111 per SFLowest✓ large
Year built2006200920102008unclear
Days on market62 days80 days49 days74 daysunclear
Discount from original list7.7%14.1%10.3%7.6%unclear
Price cut before sale38%60%56%50%unclear
Seller paid closing costs or repairs75%60%100%88%unclear
Has a view25%60%22%25%unclear

4.3 Homes over 2,245 SF sell for about $86K (37%) more than homes under 1,843 SF

2026-11-05T14:43:16.844876 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,843 SF 8 sales 1,843– 1,964 SF 5 sales 1,991– 2,245 SF 9 sales Over 2,245 SF 8 sales $0K $100K $200K $300K $234K $237K $269K $321K Net sale price, average

The average is $321K for homes over 2,245 SF and $234K for homes under 1,843 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 2,245 SF sell for about $41 per SF (27%) less than homes under 1,843 SF

2026-11-05T14:43:16.867955 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,843 SF 8 sales 1,843– 1,964 SF 5 sales 1,991– 2,245 SF 9 sales Over 2,245 SF 8 sales $0 $50 $100 $150 $151 $124 $130 $111 Net price per SF, average

The average is $111 per SF for homes over 2,245 SF and $151 per SF for homes under 1,843 SF. It does not move in a straight line; homes under 1,843 SF are highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-11-05T14:43:16.892429 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,843 SF 8 sales 1,843– 1,964 SF 5 sales 1,991– 2,245 SF 9 sales Over 2,245 SF 8 sales 2006 2008 2010 2012 2006 2009 2010 2008 Year built: median (dot) and middle half (bar)

The median is 2008 for homes over 2,245 SF and 2006 for homes under 1,843 SF. It does not move in a straight line; homes 1,991–2,245 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-05T14:43:16.914907 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,843 SF 8 sales 1,843– 1,964 SF 5 sales 1,991– 2,245 SF 9 sales Over 2,245 SF 8 sales 0 25 50 75 62 80 49 74 Days on market, median

The median is 74 days for homes over 2,245 SF and 62 days for homes under 1,843 SF. It does not move in a straight line; homes 1,843–1,964 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-05T14:43:16.937664 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,843 SF 8 sales 1,843– 1,964 SF 5 sales 1,991– 2,245 SF 9 sales Over 2,245 SF 8 sales 0.0% 5.0% 10.0% 15.0% 7.7% 14.1% 10.3% 7.6% Discount from original list, average

The average is 7.6% for homes over 2,245 SF and 7.7% for homes under 1,843 SF. It does not move in a straight line; homes 1,843–1,964 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

2026-11-05T14:43:16.963442 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% 38 75 25 60 60 60 56 100 22 50 88 25 Under 1,843 SF 1,843–1,964 SF 1,991–2,245 SF Over 2,245 SF

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

  • 50% of homes over 2,245 SF had a price cut before sale, against 38% of homes under 1,843 SF. Defined in 8.1.7.
  • 88% of homes over 2,245 SF had the seller pay closing costs or repairs, against 75% of homes under 1,843 SF. Defined in 8.1.8.
  • 25% of homes over 2,245 SF have a view, against 25% of homes under 1,843 SF. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

4.9 The numbers: price and size

Under 1,843 SF8 sales1,843–1,964 SF5 sales1,991–2,245 SF9 salesOver 2,245 SF8 salesAll30 salesReal difference?
Net sale price average$234,394$237,164$268,941$320,582$268,203✓ large
Net price per SF average$151$124$130$111$129✓ large
Living area average1,5761,9232,0702,9192,140by design
Year built median20062009201020082009unclear

4.10 The numbers: selling

Under 1,843 SF8 sales1,843–1,964 SF5 sales1,991–2,245 SF9 salesOver 2,245 SF8 salesAll30 salesReal difference?
Days on market median6280497474unclear
Discount from original list average7.7%14.1%10.3%7.6%9.5%unclear
Price cut before sale38%60%56%50%50%unclear
Seller paid closing costs or repairs75%60%100%88%83%unclear
Has a view25%60%22%25%30%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.2.

5. Quartiles by year builtResale homes · 30 sales · November 5, 2025 – November 4, 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.

2026-11-05T14:43:16.983997 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 8 8 30 sales Sales per group Before 2006: 7 sales (23%) 2006–2008: 7 sales (23%) 2009–2012: 8 sales (27%) After 2012: 8 sales (27%)
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 20062006–20082009–2012After 2012Real difference?
Net sale price$242K$282K$266K$282Kunclear
Net price per SF$128 per SF$127 per SF$140 per SF$123 per SFunclear
Living area1,951 SF2,273 SF1,978 SF2,352 SFunclear
Days on market128 days135 days59 days34 daysunclear
Discount from original list8.7%9.6%10.9%8.8%unclear
Price cut before sale57%57%50%38%unclear
Seller paid closing costs or repairs100%71%88%75%unclear
Has a view29%57%25%12%unclear

5.3 Net sale price: no clear difference

2026-11-05T14:43:17.003380 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 7 sales 2006– 2008 7 sales 2009– 2012 8 sales After 2012 8 sales $0K $100K $200K $300K $242K $282K $266K $282K Net sale price, average

The average is $282K for homes built after 2012 and $242K for homes built before 2006. It does not move in a straight line; homes built after 2012 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-05T14:43:17.024619 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 7 sales 2006– 2008 7 sales 2009– 2012 8 sales After 2012 8 sales $0 $50 $100 $150 $128 $127 $140 $123 Net price per SF, average

The average is $123 per SF for homes built after 2012 and $128 per SF for homes built before 2006. It does not move in a straight line; homes built 2009–2012 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-05T14:43:17.046960 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 7 sales 2006– 2008 7 sales 2009– 2012 8 sales After 2012 8 sales 0 1,000 2,000 1,951 2,273 1,978 2,352 Living area (SF), average

The average is 2,352 SF for homes built after 2012 and 1,951 SF for homes built before 2006. It does not move in a straight line; homes built after 2012 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-05T14:43:17.067278 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 7 sales 2006– 2008 7 sales 2009– 2012 8 sales After 2012 8 sales 0 50 100 150 128 135 59 34 Days on market, median

The median is 34 days for homes built after 2012 and 128 days for homes built before 2006. It does not move in a straight line; homes built 2006–2008 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-05T14:43:17.089384 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 7 sales 2006– 2008 7 sales 2009– 2012 8 sales After 2012 8 sales 0.0% 5.0% 10.0% 8.7% 9.6% 10.9% 8.8% Discount from original list, average

The average is 8.8% for homes built after 2012 and 8.7% for homes built before 2006. It does not move in a straight line; homes built 2009–2012 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

2026-11-05T14:43:17.114176 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% 57 100 29 57 71 57 50 88 25 38 75 12 Before 2006 2006–2008 2009–2012 After 2012

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

  • 38% of homes built after 2012 had a price cut before sale, against 57% of homes built before 2006. Defined in 8.1.7.
  • 75% of homes built after 2012 had the seller pay closing costs or repairs, against 100% of homes built before 2006. Defined in 8.1.8.
  • 12% of homes built after 2012 have a view, against 29% of homes built before 2006. 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 20067 sales2006–20087 sales2009–20128 salesAfter 20128 salesAll30 salesReal difference?
Net sale price average$241,546$281,728$265,958$281,938$268,203unclear
Net price per SF average$128$127$140$123$129unclear
Living area average1,9512,2731,9782,3522,140unclear
Year built median20042007200920142009by design

5.10 The numbers: selling

Before 20067 sales2006–20087 sales2009–20128 salesAfter 20128 salesAll30 salesReal difference?
Days on market median128135593474unclear
Discount from original list average8.7%9.6%10.9%8.8%9.5%unclear
Price cut before sale57%57%50%38%50%unclear
Seller paid closing costs or repairs100%71%88%75%83%unclear
Has a view29%57%25%12%30%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 · 30 sales · November 5, 2025 – November 4, 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.

2026-11-05T14:43:17.131263 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 20 29 sales Sales per group View: 9 sales (31%) No view: 20 sales (69%)
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$270K$270Kunclear
Net price per SF$133 per SF$127 per SFunclear
Living area2,051 SF2,212 SFunclear
Year built20072010unclear
Days on market46 days74 daysunclear
Discount from original list8.3%9.9%unclear
Price cut before sale33%55%unclear
Seller paid closing costs or repairs67%90%unclear

6.3 Net sale price: no clear difference

2026-11-05T14:43:17.147263 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 20 sales $0K $100K $200K $300K $270K $270K Net sale price, average

The average is $270K for homes with a view and $270K 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

2026-11-05T14:43:17.164141 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 20 sales $0 $50 $100 $150 $133 $127 Net price per SF, average

The average is $133 per SF for homes with a view and $127 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

2026-11-05T14:43:17.181662 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 20 sales 0 1,000 2,000 2,051 2,212 Living area (SF), average

The average is 2,051 SF for homes with a view and 2,212 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-05T14:43:17.222223 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 20 sales 2006 2008 2010 2012 2007 2010 Year built: median (dot) and middle half (bar)

The median is 2007 for homes with a view and 2010 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-05T14:43:17.240477 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 20 sales 0 20 40 60 80 46 74 Days on market, median

The median is 46 days for homes with a view and 74 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

2026-11-05T14:43:17.259270 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 20 sales 0.0% 2.5% 5.0% 7.5% 10.0% 8.3% 9.9% Discount from original list, average

The average is 8.3% for homes with a view and 9.9% 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

2026-11-05T14:43:17.278445 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 33 67 55 90 View No view

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

  • 33% of homes with a view had a price cut before sale, against 55% of homes without a view. Defined in 8.1.7.
  • 67% of homes with a view had the seller pay closing costs or repairs, against 90% 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

View9 salesNo view20 salesAll29 salesReal difference?
Net sale price average$269,756$270,464$270,244unclear
Net price per SF average$133$127$129unclear
Living area average2,0512,2122,162unclear
Year built median200720102009unclear

6.11 The numbers: selling

View9 salesNo view20 salesAll29 salesReal difference?
Days on market median467469unclear
Discount from original list average8.3%9.9%9.4%unclear
Price cut before sale33%55%48%unclear
Seller paid closing costs or repairs67%90%83%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 · 0 sales · November 5, 2025 – November 4, 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: 0 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 Waterleaf.

No new-construction sales were reported in ABOR MLS in this window.

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

8. AppendixMeasures, methods and tests

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

8.1 Measures

8.1.1 Net sale price

In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
30 resale sales. Average $268,203; median $261,700; standard deviation $41,981; middle half (25th–75th percentile) $231,500–$293,975; lowest $200,000, highest $355,000. 25 sales had a seller payment; their median payment was $9,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
30 resale sales. Average $129; median $128; standard deviation $22; middle half (25th–75th percentile) $118–$140; lowest $93, highest $208.

8.1.3 Living area

In simple terms
The heated and cooled space, as listed in the MLS. Garages and porches are not counted.
Statistically
RESO LivingArea, in square feet. Sales under 400 SF are treated as entry errors and left out.
The data
30 resale sales. Average 2,140; median 1,991; standard deviation 558; middle half (25th–75th percentile) 1,808–2,438; lowest 1,106, highest 3,560.

8.1.4 Year built

In simple terms
The year the home was finished, as listed in the MLS. It shows whether a group leans to older or newer phases of the community.
Statistically
RESO YearBuilt; summarized by the median, with the 25th–75th percentile (middle half) on the charts.
The data
30 resale sales. Average 2009; median 2009; standard deviation 4; middle half (25th–75th percentile) 2006–2013; lowest 2003, highest 2015.

8.1.5 Days on market

In simple terms
How many days the home was on the market before the buyer's offer was accepted, counting any earlier listing periods (relists). This is the days on market agents and clients quote.
Statistically
CDOM = max(CumulativeDaysOnMarket, DaysOnMarket, PurchaseContractDate − ListingContractDate). The MLS counter can freeze at a price change, so the contract-date gap is a floor. Summarized by the median, because a few homes that sat for months pull an average up.
The data
30 resale sales. Average 90; median 74; standard deviation 77; middle half (25th–75th percentile) 31–133; lowest 4, highest 281. 0 sales went under contract on their listing date (0 days).

8.1.6 Discount from original list

In simple terms
How far below the first asking price the home sold, after seller payments. It measures how much negotiating room sellers gave up. A negative figure means the home sold above its first asking price.
Statistically
Discount % = (OriginalListPrice − Net) ÷ OriginalListPrice × 100, per sale; summarized by the mean.
The data
30 resale sales. Average 9.5%; median 9.2%; standard deviation 7.1%; middle half (25th–75th percentile) 4.3%–13.7%; lowest 0.0%, highest 27.3%. 0 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
15 of 30 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
25 of 30 resale sales (83.3%).

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
9 sales with a view, 20 without, 1 unclassified. Most common View entries: None 16, Neighborhood 7, Park/Greenbelt 6, Trees/Woods 3, See Remarks 2, Pasture 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 2026-11-05 20:30 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Kyle, SubdivisionName contains any of “waterleaf” (case-insensitive). A record is kept when its subdivision name belongs to the Waterleaf family, the same rule comparable sales use.
The data
Pulled November 5, 2026: 30 closed Waterleaf records over the prior year, in ZIP 78640. 11 subdivision spellings kept: Waterleaf Ph A Sec 1 (6); Waterleaf Ph B Sec 1 (6); Waterleaf Ph A Sec 2 (5); Waterleaf Ph A Sec 4 (3); Waterleaf Ph B Sec 4 (2); Waterleaf Ph A Sec 3A (2); Waterleaf Ph B Sec 5 (2); Waterleaf Ph A Sec 3B (1); Waterleaf Ph B Sec 2 (1); Waterleaf Ph B Sec 3B (1); Waterleaf Ph B Sec 3a (1). Names found by the search but not part of Waterleaf, left out: S9334 - WATERLEAF PHASE B SEC 2 (1).

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 19 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 5, 2025 to November 4, 2026 inclusive.
The data
30 single-family sales in the window: 30 resale, 0 new construction.

8.2.3 Resale and new construction

In simple terms
A resale home was previously owned. New construction is sold by the builder and behaves differently, so it is kept out of every analysis and reported once on its own.
Statistically
New construction = NewConstructionYN true, or PropertyCondition contains “New Construction” or “Under Construction”. Everything else is resale.
The data
30 resale; 0 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 $236K”.
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 $236K: $200,000–$230,000 (8 sales); $236K–$260K: $236,000–$259,900 (7 sales); $264K–$288K: $263,500–$287,900 (7 sales); Over $288K: $296,000–$355,000 (8 sales)
Quartiles by living area: Under 1,843 SF: 1,106–1,796 SF (8 sales); 1,843–1,964 SF: 1,843–1,964 SF (5 sales); 1,991–2,245 SF: 1,991–2,245 SF (9 sales); Over 2,245 SF: 2,503–3,560 SF (8 sales)
Quartiles by year built: Before 2006: 2003–2005 (7 sales); 2006–2008: 2006–2008 (7 sales); 2009–2012: 2009–2012 (8 sales); After 2012: 2013–2015 (8 sales)
View and no view: View: MLS lists a view (9 sales); No view: None or Neighborhood (20 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 $268,203, median $261,700. Days on market: average 90, median 74: 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
3 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 4.9530.1758p < 0.0063Unclearε² = 0.171large
Living areaKruskal–WallisH = 20.2330.0002p < 0.0063Yesε² = 0.697large
Year builtKruskal–WallisH = 5.2530.1544p < 0.0063Unclearε² = 0.181large
Days on marketKruskal–WallisH = 3.0430.3849p < 0.0063Unclearε² = 0.105medium
Discount from original listKruskal–WallisH = 3.6730.2998p < 0.0063Unclearε² = 0.126medium
Price cut before saleChi-squareχ² = 3.4330.3301p < 0.0063UnclearCramér’s V = 0.338medium
Seller paid closing costs or repairsChi-squareχ² = 0.5630.9062p < 0.0063UnclearCramér’s V = 0.136small
Has a viewChi-squareχ² = 2.3630.5004p < 0.0063UnclearCramér’s V = 0.281small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 20.0030.0002p < 0.0063Yesε² = 0.690large
Net price per SFKruskal–WallisH = 17.5830.0005p < 0.0063Yesε² = 0.606large
Year builtKruskal–WallisH = 2.6930.4416p < 0.0063Unclearε² = 0.093medium
Days on marketKruskal–WallisH = 0.7330.8670p < 0.0063Unclearε² = 0.025small
Discount from original listKruskal–WallisH = 1.5830.6645p < 0.0063Unclearε² = 0.054small
Price cut before saleChi-squareχ² = 0.8130.8468p < 0.0063UnclearCramér’s V = 0.164small
Seller paid closing costs or repairsChi-squareχ² = 4.2630.2347p < 0.0063UnclearCramér’s V = 0.377medium
Has a viewChi-squareχ² = 2.5930.4588p < 0.0063UnclearCramér’s V = 0.294small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 5.0030.1719p < 0.0063Unclearε² = 0.172large
Net price per SFKruskal–WallisH = 1.7430.6289p < 0.0063Unclearε² = 0.060small
Living areaKruskal–WallisH = 2.9430.4008p < 0.0063Unclearε² = 0.101medium
Days on marketKruskal–WallisH = 4.4030.2216p < 0.0063Unclearε² = 0.152large
Discount from original listKruskal–WallisH = 0.5430.9110p < 0.0063Unclearε² = 0.018small
Price cut before saleChi-squareχ² = 0.7930.8529p < 0.0063UnclearCramér’s V = 0.162small
Seller paid closing costs or repairsChi-squareχ² = 2.6130.4550p < 0.0063UnclearCramér’s V = 0.295small
Has a viewChi-squareχ² = 3.7230.2928p < 0.0063UnclearCramér’s V = 0.352medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 93.00—0.9062p < 0.0063Unclearrank-biserial r = 0.033negligible
Net price per SFMann–Whitney UU = 119.00—0.1791p < 0.0063Unclearrank-biserial r = 0.322medium
Living areaMann–Whitney UU = 74.00—0.4643p < 0.0063Unclearrank-biserial r = 0.178small
Year builtMann–Whitney UU = 56.00—0.1121p < 0.0063Unclearrank-biserial r = 0.378medium
Days on marketMann–Whitney UU = 74.00—0.4649p < 0.0063Unclearrank-biserial r = 0.178small
Discount from original listMann–Whitney UU = 68.00—0.3106p < 0.0063Unclearrank-biserial r = 0.244small
Price cut before saleChi-squareχ² = 1.1710.2800p < 0.0063UnclearCramér’s V = 0.201small
Seller paid closing costs or repairsChi-squareχ² = 2.3710.1238p < 0.0063UnclearCramér’s V = 0.286small

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); nothing else. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

  1. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Erlbaum.
  2. Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press.
  3. Dunn, O. J. (1961). Multiple comparisons among means. JASA, 56(293), 52–64.
  4. Kerby, D. S. (2014). The simple difference formula: an approach to teaching nonparametric correlation. Comprehensive Psychology, 3, 11.IT.3.1.
  5. Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. JASA, 47(260), 583–621.
  6. Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18(1), 50–60.
  7. Pearson, K. (1900). On the criterion that a given system of deviations… Philosophical Magazine, 50(302), 157–175.
  8. Tomczak, M., & Tomczak, E. (2014). The need to report effect size estimates revisited. Trends in Sport Sciences, 21(1), 19–25.

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 30 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 5, 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.