ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Villages Of Hidden Lake

Pflugerville, TX 78660
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 · 5:35 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
25
single-family resale homes
Median net sale price
$372,000
average $378,814
Median net price per SF
$162
average $161
Median days on market
70 days
average 83 days
1. SummaryResale homes · 25 sales · October 26, 2025 – October 25, 2026

This study looks at the 25 resale homes sold in Villages Of Hidden Lake in the 365 days to October 25, 2026. A full year is used because only 11 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 sold25 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 $340K · 6 sales$340K–$367K · 6 sales$372K–$405K · 7 salesOver $405K · 6 sales
3. Quartiles by net sale priceResale homes · 25 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.

2026-10-26T05:36:07.241258 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 7 6 25 sales Sales per group Under $340K: 6 sales (24%) $340K–$367K: 6 sales (24%) $372K–$405K: 7 sales (28%) Over $405K: 6 sales (24%)
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 $340K$340K–$367K$372K–$405KOver $405KReal difference?
Net price per SF$146 per SF$144 per SF$181 per SF$169 per SFunclear
Living area2,047 SF2,561 SF2,226 SF2,856 SFunclear
Year built2006200720082014unclear
Days on market42 days106 days14 days123 daysunclear
Discount from original list9.4%9.0%4.8%3.8%unclear
Price cut before sale67%67%29%50%unclear
Seller paid closing costs or repairs83%100%43%67%unclear
Has a view0%33%14%33%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

2026-10-26T05:36:07.268817 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $340K 6 sales $340K– $367K 6 sales $372K– $405K 7 sales Over $405K 6 sales $0 $100 $200 $146 $144 $181 $169 Net price per SF, average

The average is $169 per SF for homes over $405K and $146 per SF for homes under $340K. It does not move in a straight line; homes $372K–$405K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-26T05:36:07.290410 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $340K 6 sales $340K– $367K 6 sales $372K– $405K 7 sales Over $405K 6 sales 0 1,000 2,000 3,000 2,047 2,561 2,226 2,856 Living area (SF), average

The average is 2,856 SF for homes over $405K and 2,047 SF for homes under $340K. It does not move in a straight line; homes over $405K are highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-26T05:36:07.313777 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $340K 6 sales $340K– $367K 6 sales $372K– $405K 7 sales Over $405K 6 sales 2008 2011 2014 2006 2007 2008 2014 Year built: median (dot) and middle half (bar)

The median is 2014 for homes over $405K and 2006 for homes under $340K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:36:07.336209 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $340K 6 sales $340K– $367K 6 sales $372K– $405K 7 sales Over $405K 6 sales 0 50 100 42 106 14 123 Days on market, median

The median is 123 days for homes over $405K and 42 days for homes under $340K. It does not move in a straight line; homes over $405K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:36:07.357705 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $340K 6 sales $340K– $367K 6 sales $372K– $405K 7 sales Over $405K 6 sales 0.0% 5.0% 10.0% 9.4% 9.0% 4.8% 3.8% Discount from original list, average

The average is 3.8% for homes over $405K and 9.4% for homes under $340K. 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

2026-10-26T05:36:07.387634 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 83 0 67 100 33 29 43 14 50 67 33 Under $340K $340K–$367K $372K–$405K Over $405K

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

  • 50% of homes over $405K had a price cut before sale, against 67% of homes under $340K. Defined in 8.1.7.
  • 67% of homes over $405K had the seller pay closing costs or repairs, against 83% of homes under $340K. Defined in 8.1.8.
  • 33% of homes over $405K have a view, against 0% of homes under $340K. 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 $340K6 sales$340K–$367K6 sales$372K–$405K7 salesOver $405K6 salesAll25 salesReal difference?
Net sale price average$290,162$355,068$387,264$481,353$378,814by design
Net price per SF average$146$144$181$169$161unclear
Living area average2,0472,5612,2262,8562,415unclear
Year built median20062007200820142008unclear

3.10 The numbers: selling

Under $340K6 sales$340K–$367K6 sales$372K–$405K7 salesOver $405K6 salesAll25 salesReal difference?
Days on market median421061412370unclear
Discount from original list average9.4%9.0%4.8%3.8%6.7%unclear
Price cut before sale67%67%29%50%52%unclear
Seller paid closing costs or repairs83%100%43%67%72%unclear
Has a view0%33%14%33%20%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 · 25 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.

2026-10-26T05:36:07.408009 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 7 6 25 sales Sales per group Under 1,984 SF: 6 sales (24%) 1,984–2,283 SF: 6 sales (24%) 2,420–2,892 SF: 7 sales (28%) Over 2,892 SF: 6 sales (24%)
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 1,984 SF1,984–2,283 SF2,420–2,892 SFOver 2,892 SFReal difference?
Net sale price$322K$351K$434K$399Kunclear
Net price per SF$186 per SF$164 per SF$161 per SF$132 per SFunclear
Year built2006201020132007unclear
Days on market74 days20 days131 days85 daysunclear
Discount from original list10.6%3.3%6.5%6.4%unclear
Price cut before sale67%33%57%50%unclear
Seller paid closing costs or repairs50%83%71%83%unclear
Has a view17%0%14%50%unclear

4.3 Net sale price: no clear difference

2026-10-26T05:36:07.428491 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,984 SF 6 sales 1,984– 2,283 SF 6 sales 2,420– 2,892 SF 7 sales Over 2,892 SF 6 sales $0K $200K $400K $322K $351K $434K $399K Net sale price, average

The average is $399K for homes over 2,892 SF and $322K for homes under 1,984 SF. It does not move in a straight line; homes 2,420–2,892 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-10-26T05:36:07.450368 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,984 SF 6 sales 1,984– 2,283 SF 6 sales 2,420– 2,892 SF 7 sales Over 2,892 SF 6 sales $0 $100 $200 $186 $164 $161 $132 Net price per SF, average

The average is $132 per SF for homes over 2,892 SF and $186 per SF for homes under 1,984 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T05:36:07.474214 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,984 SF 6 sales 1,984– 2,283 SF 6 sales 2,420– 2,892 SF 7 sales Over 2,892 SF 6 sales 2006 2008 2010 2012 2014 2006 2010 2013 2007 Year built: median (dot) and middle half (bar)

The median is 2007 for homes over 2,892 SF and 2006 for homes under 1,984 SF. It does not move in a straight line; homes 2,420–2,892 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T05:36:07.496967 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,984 SF 6 sales 1,984– 2,283 SF 6 sales 2,420– 2,892 SF 7 sales Over 2,892 SF 6 sales 0 50 100 150 74 20 131 85 Days on market, median

The median is 85 days for homes over 2,892 SF and 74 days for homes under 1,984 SF. It does not move in a straight line; homes 2,420–2,892 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T05:36:07.519185 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,984 SF 6 sales 1,984– 2,283 SF 6 sales 2,420– 2,892 SF 7 sales Over 2,892 SF 6 sales 0.0% 5.0% 10.0% 10.6% 3.3% 6.5% 6.4% Discount from original list, average

The average is 6.4% for homes over 2,892 SF and 10.6% for homes under 1,984 SF. It does not move in a straight line; homes under 1,984 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T05:36:07.545238 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 17 33 83 0 57 71 14 50 83 50 Under 1,984 SF 1,984–2,283 SF 2,420–2,892 SF Over 2,892 SF

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

  • 50% of homes over 2,892 SF had a price cut before sale, against 67% of homes under 1,984 SF. Defined in 8.1.7.
  • 83% of homes over 2,892 SF had the seller pay closing costs or repairs, against 50% of homes under 1,984 SF. Defined in 8.1.8.
  • 50% of homes over 2,892 SF have a view, against 17% of homes under 1,984 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 1,984 SF6 sales1,984–2,283 SF6 sales2,420–2,892 SF7 salesOver 2,892 SF6 salesAll25 salesReal difference?
Net sale price average$322,000$351,079$434,238$398,702$378,814unclear
Net price per SF average$186$164$161$132$161unclear
Living area average1,7522,1442,6983,0182,415by design
Year built median20062010201320072008unclear

4.10 The numbers: selling

Under 1,984 SF6 sales1,984–2,283 SF6 sales2,420–2,892 SF7 salesOver 2,892 SF6 salesAll25 salesReal difference?
Days on market median74201318570unclear
Discount from original list average10.6%3.3%6.5%6.4%6.7%unclear
Price cut before sale67%33%57%50%52%unclear
Seller paid closing costs or repairs50%83%71%83%72%unclear
Has a view17%0%14%50%20%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 · 25 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.

2026-10-26T05:36:07.564845 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 7 6 25 sales Sales per group Before 2007: 6 sales (24%) 2007: 6 sales (24%) 2008–2012: 7 sales (28%) After 2012: 6 sales (24%)
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 200720072008–2012After 2012Real difference?
Net sale price$337K$352K$371K$456Kunclear
Net price per SF$147 per SF$165 per SF$155 per SF$177 per SFunclear
Living area2,339 SF2,268 SF2,466 SF2,578 SFunclear
Days on market126 days28 days43 days123 daysunclear
Discount from original list11.1%6.1%6.0%3.7%unclear
Price cut before sale67%50%57%33%unclear
Seller paid closing costs or repairs67%67%86%67%unclear
Has a view17%50%0%17%unclear

5.3 Net sale price: no clear difference

2026-10-26T05:36:07.585322 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 6 sales 2007 6 sales 2008– 2012 7 sales After 2012 6 sales $0K $200K $400K $337K $352K $371K $456K Net sale price, average

The average is $456K for homes built after 2012 and $337K for homes built before 2007. 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

2026-10-26T05:36:07.606536 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 6 sales 2007 6 sales 2008– 2012 7 sales After 2012 6 sales $0 $100 $200 $147 $165 $155 $177 Net price per SF, average

The average is $177 per SF for homes built after 2012 and $147 per SF for homes built before 2007. It does not move in a straight line; homes built after 2012 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T05:36:07.626773 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 6 sales 2007 6 sales 2008– 2012 7 sales After 2012 6 sales 0 1,000 2,000 3,000 2,339 2,268 2,466 2,578 Living area (SF), average

The average is 2,578 SF for homes built after 2012 and 2,339 SF for homes built before 2007. 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

2026-10-26T05:36:07.647709 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 6 sales 2007 6 sales 2008– 2012 7 sales After 2012 6 sales 0 50 100 150 126 28 43 123 Days on market, median

The median is 123 days for homes built after 2012 and 126 days for homes built before 2007. It does not move in a straight line; homes built before 2007 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T05:36:07.669495 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 6 sales 2007 6 sales 2008– 2012 7 sales After 2012 6 sales 0.0% 5.0% 10.0% 11.1% 6.1% 6.0% 3.7% Discount from original list, average

The average is 3.7% for homes built after 2012 and 11.1% for homes built before 2007. It falls step by step from the lowest range to the 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

2026-10-26T05:36:07.693970 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 67 17 50 67 50 57 86 0 33 67 17 Before 2007 2007 2008–2012 After 2012

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

  • 33% of homes built after 2012 had a price cut before sale, against 67% of homes built before 2007. Defined in 8.1.7.
  • 67% of homes built after 2012 had the seller pay closing costs or repairs, against 67% of homes built before 2007. Defined in 8.1.8.
  • 17% of homes built after 2012 have a view, against 17% of homes built before 2007. 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 20076 sales20076 sales2008–20127 salesAfter 20126 salesAll25 salesReal difference?
Net sale price average$336,850$352,097$371,464$456,069$378,814unclear
Net price per SF average$147$165$155$177$161unclear
Living area average2,3392,2682,4662,5782,415unclear
Year built median20062007200920152008by design

5.10 The numbers: selling

Before 20076 sales20076 sales2008–20127 salesAfter 20126 salesAll25 salesReal difference?
Days on market median126284312370unclear
Discount from original list average11.1%6.1%6.0%3.7%6.7%unclear
Price cut before sale67%50%57%33%52%unclear
Seller paid closing costs or repairs67%67%86%67%72%unclear
Has a view17%50%0%17%20%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 · 25 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.

2026-10-26T05:36:07.712077 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 20 25 sales Sales per group View: 5 sales (20%) No view: 20 sales (80%)
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$415K$370Kunclear
Net price per SF$164 per SF$160 per SFunclear
Living area2,683 SF2,348 SFunclear
Year built20072008unclear
Days on market79 days64 daysunclear
Discount from original list5.1%7.1%unclear
Price cut before sale40%55%unclear
Seller paid closing costs or repairs60%75%unclear

6.3 Net sale price: no clear difference

2026-10-26T05:36:07.728560 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 20 sales $0K $100K $200K $300K $400K $415K $370K Net sale price, average

The average is $415K for homes with a view and $370K 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

2026-10-26T05:36:07.746197 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 20 sales $0 $50 $100 $150 $164 $160 Net price per SF, average

The average is $164 per SF for homes with a view and $160 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

2026-10-26T05:36:07.764326 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 20 sales 0 1,000 2,000 3,000 2,683 2,348 Living area (SF), average

The average is 2,683 SF for homes with a view and 2,348 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T05:36:07.841769 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 20 sales 2008 2010 2012 2007 2008 Year built: median (dot) and middle half (bar)

The median is 2007 for homes with a view and 2008 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T05:36:07.859914 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 20 sales 0 20 40 60 80 79 64 Days on market, median

The median is 79 days for homes with a view and 64 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

2026-10-26T05:36:07.879023 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 20 sales 0.0% 2.0% 4.0% 6.0% 8.0% 5.1% 7.1% Discount from original list, average

The average is 5.1% for homes with a view and 7.1% 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

2026-10-26T05:36:07.897821 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 40 60 55 75 View No view

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

  • 40% of homes with a view had a price cut before sale, against 55% of homes without a view. Defined in 8.1.7.
  • 60% of homes with a view had the seller pay closing costs or repairs, against 75% 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

View5 salesNo view20 salesAll25 salesReal difference?
Net sale price average$414,951$369,780$378,814unclear
Net price per SF average$164$160$161unclear
Living area average2,6832,3482,415unclear
Year built median200720082008unclear

6.11 The numbers: selling

View5 salesNo view20 salesAll25 salesReal difference?
Days on market median796470unclear
Discount from original list average5.1%7.1%6.7%unclear
Price cut before sale40%55%52%unclear
Seller paid closing costs or repairs60%75%72%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 · 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: 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 Villages Of Hidden Lake.

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
25 resale sales. Average $378,814; median $372,000; standard deviation $71,946; middle half (25th–75th percentile) $339,500–$405,000; lowest $251,625, highest $506,198. 18 sales had a seller payment; their median payment was $6,591.

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
25 resale sales. Average $161; median $162; standard deviation $33; middle half (25th–75th percentile) $138–$179; lowest $116, highest $249.

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
25 resale sales. Average 2,415; median 2,420; standard deviation 515; middle half (25th–75th percentile) 1,984–2,892; lowest 1,491, highest 3,156.

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
25 resale sales. Average 2009; median 2008; standard deviation 4; middle half (25th–75th percentile) 2007–2012; lowest 2004, highest 2017.

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
25 resale sales. Average 83; median 70; standard deviation 66; middle half (25th–75th percentile) 24–142; lowest 5, highest 234. 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
25 resale sales. Average 6.7%; median 6.0%; standard deviation 5.7%; middle half (25th–75th percentile) 3.1%–10.3%; lowest −1.4%, highest 23.4%. 2 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
13 of 25 resale sales (52.0%).

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
18 of 25 resale sales (72.0%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
5 sales with a view, 20 without, 0 unclassified. Most common View entries: None 11, Neighborhood 9, Park/Greenbelt 4, Lake 2, Panoramic 1, Pond 1, Pool 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Pflugerville, SubdivisionName contains any of “villages of hidden lake” (case-insensitive). A record is kept when its subdivision name belongs to the Villages Of Hidden Lake family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 25 closed Villages Of Hidden Lake records over the prior year, in ZIP 78660. 13 subdivision spellings kept, the most common: Villages Of Hidden Lake Ph 3B (8); Villages Of Hidden Lake Ph 4C (2); Villages Of Hidden Lake Ph 5A (2); Villages Of Hidden Lake Ph 5B (2); Villages Of Hidden Lake Ph 4A (2); Villages Of Hidden Lake Ph 6A (2); Villages Of Hidden Lake Ph 4b (1); Villages Of Hidden Lake Ph 6B (1); The Villages Of Hidden Lake (1); Villages Of Hidden Lake Ph 4B (1); Villages Of Hidden Lake (1); Villages of Hidden Lake (1); and 1 more (1 records). Names found by the search but not part of Villages Of Hidden Lake, left out: Lakeside at Villages of Hidden Lake (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 11 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
25 single-family sales in the window: 25 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
25 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 $340K”.
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 $340K: $251,625–$339,000 (6 sales); $340K–$367K: $339,500–$366,600 (6 sales); $372K–$405K: $372,000–$405,000 (7 sales); Over $405K: $460,000–$506,198 (6 sales)
Quartiles by living area: Under 1,984 SF: 1,491–1,959 SF (6 sales); 1,984–2,283 SF: 1,984–2,283 SF (6 sales); 2,420–2,892 SF: 2,420–2,892 SF (7 sales); Over 2,892 SF: 2,946–3,156 SF (6 sales)
Quartiles by year built: Before 2007: 2004–2006 (6 sales); 2007: 2007–2007 (6 sales); 2008–2012: 2008–2012 (7 sales); After 2012: 2013–2017 (6 sales)
View and no view: View: MLS lists a view (5 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 $378,814, median $372,000. Days on market: average 83, median 70: 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 = 5.6830.1283p < 0.0063Unclearε² = 0.237large
Living areaKruskal–WallisH = 8.7030.0336p < 0.0063Unclearε² = 0.362large
Year builtKruskal–WallisH = 8.1930.0423p < 0.0063Unclearε² = 0.341large
Days on marketKruskal–WallisH = 3.4430.3292p < 0.0063Unclearε² = 0.143large
Discount from original listKruskal–WallisH = 3.6430.3035p < 0.0063Unclearε² = 0.152large
Price cut before saleChi-squareχ² = 2.5830.4604p < 0.0063UnclearCramér’s V = 0.321medium
Seller paid closing costs or repairsChi-squareχ² = 5.7530.1245p < 0.0063UnclearCramér’s V = 0.480medium
Has a viewChi-squareχ² = 2.9830.3953p < 0.0063UnclearCramér’s V = 0.345medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 6.7230.0813p < 0.0063Unclearε² = 0.280large
Net price per SFKruskal–WallisH = 7.7430.0518p < 0.0063Unclearε² = 0.322large
Year builtKruskal–WallisH = 9.6730.0216p < 0.0063Unclearε² = 0.403large
Days on marketKruskal–WallisH = 3.9630.2654p < 0.0063Unclearε² = 0.165large
Discount from original listKruskal–WallisH = 4.6030.2034p < 0.0063Unclearε² = 0.192large
Price cut before saleChi-squareχ² = 1.4430.6965p < 0.0063UnclearCramér’s V = 0.240small
Seller paid closing costs or repairsChi-squareχ² = 2.2130.5307p < 0.0063UnclearCramér’s V = 0.297small
Has a viewChi-squareχ² = 5.0630.1675p < 0.0063UnclearCramér’s V = 0.450medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 9.7730.0206p < 0.0063Unclearε² = 0.407large
Net price per SFKruskal–WallisH = 4.0430.2569p < 0.0063Unclearε² = 0.168large
Living areaKruskal–WallisH = 0.8230.8456p < 0.0063Unclearε² = 0.034small
Days on marketKruskal–WallisH = 3.8930.2741p < 0.0063Unclearε² = 0.162large
Discount from original listKruskal–WallisH = 3.7830.2865p < 0.0063Unclearε² = 0.157large
Price cut before saleChi-squareχ² = 1.4430.6965p < 0.0063UnclearCramér’s V = 0.240small
Seller paid closing costs or repairsChi-squareχ² = 0.9130.8237p < 0.0063UnclearCramér’s V = 0.190small
Has a viewChi-squareχ² = 5.2130.1572p < 0.0063UnclearCramér’s V = 0.456medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 66.00—0.3027p < 0.0063Unclearrank-biserial r = 0.320medium
Net price per SFMann–Whitney UU = 46.00—0.8180p < 0.0063Unclearrank-biserial r = 0.080negligible
Living areaMann–Whitney UU = 73.50—0.1177p < 0.0063Unclearrank-biserial r = 0.470medium
Year builtMann–Whitney UU = 41.00—0.5589p < 0.0063Unclearrank-biserial r = 0.180small
Days on marketMann–Whitney UU = 54.50—0.7858p < 0.0063Unclearrank-biserial r = 0.090negligible
Discount from original listMann–Whitney UU = 43.00—0.6685p < 0.0063Unclearrank-biserial r = 0.140small
Price cut before saleChi-squareχ² = 0.3610.5482p < 0.0063UnclearCramér’s V = 0.120small
Seller paid closing costs or repairsChi-squareχ² = 0.4510.5040p < 0.0063UnclearCramér’s V = 0.134small

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 25 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 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.