ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Highland Park Ph A Sec 01

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 · 7:22 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
56
single-family resale homes
Median net sale price
$361,603
average $371,986
Median net price per SF
$196
average $189
Median days on market
46 days
average 69 days
1. SummaryResale homes · 56 sales · October 26, 2025 – October 25, 2026

This study looks at the 56 resale homes sold in Highland Park Ph A Sec 01 in the 365 days to October 25, 2026. A full year is used because only 33 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 sold56 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 $318K · 14 sales$318K–$358K · 14 sales$365K–$415K · 14 salesOver $415K · 14 sales
3. Quartiles by net sale priceResale homes · 56 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.

2026-10-26T07:22:48.036369 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 14 14 14 56 sales Sales per group Under $318K: 14 sales (25%) $318K–$358K: 14 sales (25%) $365K–$415K: 14 sales (25%) Over $415K: 14 sales (25%)
Bottom line

3.1 Key differences

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

Under $318K$318K–$358K$365K–$415KOver $415K
Higher-priced homes Over $415K
  • Are much larger.
  • Sell for less per square foot.
  • Tend to be older.
Lower-priced homes Under $318K
  • Are much smaller.
  • Sell for more per square foot.
  • Tend to be newer.

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 $318K$318K–$358K$365K–$415KOver $415KReal difference?
Net price per SF$209 per SFHighest$204 per SF$186 per SF$157 per SFLowest✓ large
Living area1,443 SFSmallest1,675 SF2,110 SF3,096 SFLargest✓ large
Year built20132017Newest20082006Oldest✓ large
Days on market42 days42 days76 days31 daysunclear
Discount from original list6.8%4.1%7.0%4.8%unclear
Price cut before sale57%36%64%50%unclear
Seller paid closing costs or repairs71%79%64%64%unclear
Has a view21%14%21%14%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 Homes over $415K sell for about $52 per SF (25%) less than homes under $318K

2026-10-26T07:22:48.064734 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $318K 14 sales $318K– $358K 14 sales $365K– $415K 14 sales Over $415K 14 sales $0 $100 $200 $209 $204 $186 $157 Net price per SF, average

The average is $157 per SF for homes over $415K and $209 per SF for homes under $318K. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $415K are about 1,650 SF (115%) larger than homes under $318K

2026-10-26T07:22:48.086623 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $318K 14 sales $318K– $358K 14 sales $365K– $415K 14 sales Over $415K 14 sales 0 1,000 2,000 3,000 1,443 1,675 2,110 3,096 Living area (SF), average

The average is 3,096 SF for homes over $415K and 1,443 SF for homes under $318K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Homes over $415K are about 8 years older than homes under $318K

2026-10-26T07:22:48.111660 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $318K 14 sales $318K– $358K 14 sales $365K– $415K 14 sales Over $415K 14 sales 2005 2008 2011 2014 2017 2013 2017 2008 2006 Year built: median (dot) and middle half (bar)

The median is 2006 for homes over $415K and 2013 for homes under $318K. It does not move in a straight line; homes $318K–$358K are highest. Defined in 8.1.4.

✓ Real difference · large

3.6 Days on market: no clear difference

2026-10-26T07:22:48.134788 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $318K 14 sales $318K– $358K 14 sales $365K– $415K 14 sales Over $415K 14 sales 0 25 50 75 42 42 76 31 Days on market, median

The median is 31 days for homes over $415K and 42 days for homes under $318K. It does not move in a straight line; homes $365K–$415K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:22:48.157084 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $318K 14 sales $318K– $358K 14 sales $365K– $415K 14 sales Over $415K 14 sales 0.0% 2.5% 5.0% 7.5% 6.8% 4.1% 7.0% 4.8% Discount from original list, average

The average is 4.8% for homes over $415K and 6.8% for homes under $318K. It does not move in a straight line; homes $365K–$415K 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

2026-10-26T07:22:48.186898 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 71 21 36 79 14 64 64 21 50 64 14 Under $318K $318K–$358K $365K–$415K Over $415K

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

  • 50% of homes over $415K had a price cut before sale, against 57% of homes under $318K. Defined in 8.1.7.
  • 64% of homes over $415K had the seller pay closing costs or repairs, against 71% of homes under $318K. Defined in 8.1.8.
  • 14% of homes over $415K have a view, against 21% of homes under $318K. 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 $318K14 sales$318K–$358K14 sales$365K–$415K14 salesOver $415K14 salesAll56 salesReal difference?
Net sale price average$296,490$341,325$380,055$470,071$371,986by design
Net price per SF average$209$204$186$157$189✓ large
Living area average1,4431,6752,1103,0962,081✓ large
Year built median20132017200820062010✓ large

3.10 The numbers: selling

Under $318K14 sales$318K–$358K14 sales$365K–$415K14 salesOver $415K14 salesAll56 salesReal difference?
Days on market median4242763146unclear
Discount from original list average6.8%4.1%7.0%4.8%5.7%unclear
Price cut before sale57%36%64%50%52%unclear
Seller paid closing costs or repairs71%79%64%64%70%unclear
Has a view21%14%21%14%18%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 · 56 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.

2026-10-26T07:22:48.207631 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 13 15 14 56 sales Sales per group Under 1,618 SF: 14 sales (25%) 1,618–1,821 SF: 13 sales (23%) 1,826–2,277 SF: 15 sales (27%) Over 2,277 SF: 14 sales (25%)
Bottom line

4.1 Key differences

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

Under 1,618 SF1,618–1,821 SF1,826–2,277 SFOver 2,277 SF
Larger homes Over 2,277 SF
  • Sell for much more.
  • Sell for less per square foot.
  • Tend to be older.
Smaller homes Under 1,618 SF
  • Sell for much less.
  • Sell for more per square foot.
  • Tend to be newer.

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 1,618 SF1,618–1,821 SF1,826–2,277 SFOver 2,277 SFReal difference?
Net sale price$299KLowest$342K$383K$462KHighest✓ large
Net price per SF$217 per SFHighest$201 per SF$191 per SF$147 per SFLowest✓ large
Year built20152016Newest20072006Oldest✓ large
Days on market30 days57 days55 days50 daysunclear
Discount from original list5.6%5.2%6.2%5.7%unclear
Price cut before sale43%38%73%50%unclear
Seller paid closing costs or repairs79%77%53%71%unclear
Has a view21%15%20%14%unclear

4.3 Homes over 2,277 SF sell for about $163K (54%) more than homes under 1,618 SF

2026-10-26T07:22:48.229077 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,618 SF 14 sales 1,618– 1,821 SF 13 sales 1,826– 2,277 SF 15 sales Over 2,277 SF 14 sales $0K $200K $400K $299K $342K $383K $462K Net sale price, average

The average is $462K for homes over 2,277 SF and $299K for homes under 1,618 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 2,277 SF sell for about $70 per SF (32%) less than homes under 1,618 SF

2026-10-26T07:22:48.252514 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,618 SF 14 sales 1,618– 1,821 SF 13 sales 1,826– 2,277 SF 15 sales Over 2,277 SF 14 sales $0 $100 $200 $217 $201 $191 $147 Net price per SF, average

The average is $147 per SF for homes over 2,277 SF and $217 per SF for homes under 1,618 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Homes over 2,277 SF are about 9 years older than homes under 1,618 SF

2026-10-26T07:22:48.277464 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,618 SF 14 sales 1,618– 1,821 SF 13 sales 1,826– 2,277 SF 15 sales Over 2,277 SF 14 sales 2005 2008 2011 2014 2017 2015 2016 2007 2006 Year built: median (dot) and middle half (bar)

The median is 2006 for homes over 2,277 SF and 2015 for homes under 1,618 SF. It does not move in a straight line; homes 1,618–1,821 SF are highest. Defined in 8.1.4.

✓ Real difference · large

4.6 Days on market: no clear difference

2026-10-26T07:22:48.301121 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,618 SF 14 sales 1,618– 1,821 SF 13 sales 1,826– 2,277 SF 15 sales Over 2,277 SF 14 sales 0 20 40 60 30 57 55 50 Days on market, median

The median is 50 days for homes over 2,277 SF and 30 days for homes under 1,618 SF. It does not move in a straight line; homes 1,618–1,821 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:22:48.323695 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,618 SF 14 sales 1,618– 1,821 SF 13 sales 1,826– 2,277 SF 15 sales Over 2,277 SF 14 sales 0.0% 2.0% 4.0% 6.0% 5.6% 5.2% 6.2% 5.7% Discount from original list, average

The average is 5.7% for homes over 2,277 SF and 5.6% for homes under 1,618 SF. It does not move in a straight line; homes 1,826–2,277 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

2026-10-26T07:22:48.350989 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 43 79 21 38 77 15 73 53 20 50 71 14 Under 1,618 SF 1,618–1,821 SF 1,826–2,277 SF Over 2,277 SF

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

  • 50% of homes over 2,277 SF had a price cut before sale, against 43% of homes under 1,618 SF. Defined in 8.1.7.
  • 71% of homes over 2,277 SF had the seller pay closing costs or repairs, against 79% of homes under 1,618 SF. Defined in 8.1.8.
  • 14% of homes over 2,277 SF have a view, against 21% of homes under 1,618 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 1,618 SF14 sales1,618–1,821 SF13 sales1,826–2,277 SF15 salesOver 2,277 SF14 salesAll56 salesReal difference?
Net sale price average$298,947$341,858$382,548$461,682$371,986✓ large
Net price per SF average$217$201$191$147$189✓ large
Living area average1,3771,7012,0093,2162,081by design
Year built median20152016200720062010✓ large

4.10 The numbers: selling

Under 1,618 SF14 sales1,618–1,821 SF13 sales1,826–2,277 SF15 salesOver 2,277 SF14 salesAll56 salesReal difference?
Days on market median3057555046unclear
Discount from original list average5.6%5.2%6.2%5.7%5.7%unclear
Price cut before sale43%38%73%50%52%unclear
Seller paid closing costs or repairs79%77%53%71%70%unclear
Has a view21%15%20%14%18%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 · 56 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.

2026-10-26T07:22:48.371662 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 15 13 14 14 56 sales Sales per group Before 2006: 15 sales (27%) 2006–2009: 13 sales (23%) 2011–2016: 14 sales (25%) After 2016: 14 sales (25%)
Bottom line

5.1 Key differences

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

Before 20062006–20092011–2016After 2016
Newer homes After 2016
  • Sell for more per square foot.
  • Are much smaller.
Older homes Before 2006
  • Sell for less per square foot.
  • Are much larger.

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 20062006–20092011–2016After 2016Real difference?
Net sale price$400K$399K$358K$330Kunclear
Net price per SF$176 per SF$169 per SFLowest$202 per SF$208 per SFHighest✓ large
Living area2,425 SF2,505 SFLargest1,790 SF1,610 SFSmallest✓ large
Days on market20 days77 days38 days52 daysunclear
Discount from original list6.2%7.3%4.3%5.1%unclear
Price cut before sale47%77%29%57%unclear
Seller paid closing costs or repairs67%69%64%79%unclear
Has a view27%8%29%7%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:22:48.392269 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 15 sales 2006– 2009 13 sales 2011– 2016 14 sales After 2016 14 sales $0K $200K $400K $400K $399K $358K $330K Net sale price, average

The average is $330K for homes built after 2016 and $400K for homes built before 2006. It falls step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Homes built after 2016 sell for about $32 per SF (18%) more than homes built before 2006

2026-10-26T07:22:48.414809 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 15 sales 2006– 2009 13 sales 2011– 2016 14 sales After 2016 14 sales $0 $100 $200 $176 $169 $202 $208 Net price per SF, average

The average is $208 per SF for homes built after 2016 and $176 per SF for homes built before 2006. It does not move in a straight line; homes built after 2016 are highest. Defined in 8.1.2.

✓ Real difference · large

5.5 Homes built after 2016 are about 820 SF (34%) smaller than homes built before 2006

2026-10-26T07:22:48.436357 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 15 sales 2006– 2009 13 sales 2011– 2016 14 sales After 2016 14 sales 0 1,000 2,000 3,000 2,425 2,505 1,790 1,610 Living area (SF), average

The average is 1,610 SF for homes built after 2016 and 2,425 SF for homes built before 2006. It does not move in a straight line; homes built 2006–2009 are highest. Defined in 8.1.3.

✓ Real difference · large

5.6 Days on market: no clear difference

2026-10-26T07:22:48.458480 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 15 sales 2006– 2009 13 sales 2011– 2016 14 sales After 2016 14 sales 0 25 50 75 20 77 38 52 Days on market, median

The median is 52 days for homes built after 2016 and 20 days for homes built before 2006. It does not move in a straight line; homes built 2006–2009 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:22:48.481722 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 15 sales 2006– 2009 13 sales 2011– 2016 14 sales After 2016 14 sales 0.0% 2.5% 5.0% 7.5% 6.2% 7.3% 4.3% 5.1% Discount from original list, average

The average is 5.1% for homes built after 2016 and 6.2% for homes built before 2006. It does not move in a straight line; homes built 2006–2009 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

2026-10-26T07:22:48.507947 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% 47 67 27 77 69 8 29 64 29 57 79 7 Before 2006 2006–2009 2011–2016 After 2016

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

  • 57% of homes built after 2016 had a price cut before sale, against 47% of homes built before 2006. Defined in 8.1.7.
  • 79% of homes built after 2016 had the seller pay closing costs or repairs, against 67% of homes built before 2006. Defined in 8.1.8.
  • 7% of homes built after 2016 have a view, against 27% 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 200615 sales2006–200913 sales2011–201614 salesAfter 201614 salesAll56 salesReal difference?
Net sale price average$400,140$399,104$358,346$330,279$371,986unclear
Net price per SF average$176$169$202$208$189✓ large
Living area average2,4252,5051,7901,6102,081✓ large
Year built median20042007201420172010by design

5.10 The numbers: selling

Before 200615 sales2006–200913 sales2011–201614 salesAfter 201614 salesAll56 salesReal difference?
Days on market median2077385246unclear
Discount from original list average6.2%7.3%4.3%5.1%5.7%unclear
Price cut before sale47%77%29%57%52%unclear
Seller paid closing costs or repairs67%69%64%79%70%unclear
Has a view27%8%29%7%18%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 · 56 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. 2 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T07:22:48.527053 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 44 54 sales Sales per group View: 10 sales (19%) No view: 44 sales (81%)
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$360K$376Kunclear
Net price per SF$187 per SF$191 per SFunclear
Living area2,056 SF2,084 SFunclear
Year built20092012unclear
Days on market38 days50 daysunclear
Discount from original list6.0%5.4%unclear
Price cut before sale40%52%unclear
Seller paid closing costs or repairs70%70%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:22:48.543937 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 44 sales $0K $100K $200K $300K $400K $360K $376K Net sale price, average

The average is $360K for homes with a view and $376K 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

2026-10-26T07:22:48.562988 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 44 sales $0 $50 $100 $150 $200 $187 $191 Net price per SF, average

The average is $187 per SF for homes with a view and $191 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

2026-10-26T07:22:48.607010 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 44 sales 0 1,000 2,000 2,056 2,084 Living area (SF), average

The average is 2,056 SF for homes with a view and 2,084 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:22:48.627373 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 44 sales 2005 2008 2011 2014 2017 2009 2012 Year built: median (dot) and middle half (bar)

The median is 2009 for homes with a view and 2012 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:22:48.646442 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 44 sales 0 20 40 60 38 50 Days on market, median

The median is 38 days for homes with a view and 50 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

2026-10-26T07:22:48.664859 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 44 sales 0.0% 2.0% 4.0% 6.0% 6.0% 5.4% Discount from original list, average

The average is 6.0% for homes with a view and 5.4% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:22:48.683575 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 40 70 52 70 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 52% of homes without a view. Defined in 8.1.7.
  • 70% of homes with a view had the seller pay closing costs or repairs, against 70% 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

View10 salesNo view44 salesAll54 salesReal difference?
Net sale price average$360,499$376,027$373,152unclear
Net price per SF average$187$191$190unclear
Living area average2,0562,0842,079unclear
Year built median200920122011unclear

6.11 The numbers: selling

View10 salesNo view44 salesAll54 salesReal difference?
Days on market median385044unclear
Discount from original list average6.0%5.4%5.5%unclear
Price cut before sale40%52%50%unclear
Seller paid closing costs or repairs70%70%70%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.4.

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 Highland Park Ph A Sec 01.

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
56 resale sales. Average $371,986; median $361,603; standard deviation $67,290; middle half (25th–75th percentile) $316,500–$416,250; lowest $272,700, highest $525,000. 39 sales had a seller payment; their median payment was $7,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
56 resale sales. Average $189; median $196; standard deviation $31; middle half (25th–75th percentile) $178–$208; lowest $109, highest $238.

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
56 resale sales. Average 2,081; median 1,826; standard deviation 760; middle half (25th–75th percentile) 1,591–2,294; lowest 1,292, highest 4,050.

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
56 resale sales. Average 2010; median 2010; standard deviation 5; middle half (25th–75th percentile) 2005–2016; lowest 2004, highest 2018.

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
56 resale sales. Average 69; median 46; standard deviation 70; middle half (25th–75th percentile) 15–105; lowest 3, highest 373. 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
56 resale sales. Average 5.7%; median 5.0%; standard deviation 3.8%; middle half (25th–75th percentile) 3.0%–8.0%; lowest −0.9%, highest 19.8%. 1 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
29 of 56 resale sales (51.8%).

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
39 of 56 resale sales (69.6%).

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
10 sales with a view, 44 without, 2 unclassified. Most common View entries: None 35, Neighborhood 11, Park/Greenbelt 7, See Remarks 3, Trees/Woods 2, Panoramic 1, City 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 “highland park”, “highland park north” (case-insensitive). A record is kept when its subdivision name belongs to the Highland Park Ph A Sec 01 family, the same rule comparable sales use (it includes Highland Park North Ph B Sec, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 60 closed Highland Park Ph A Sec 01 records over the prior year, in ZIP 78660. 25 subdivision spellings kept, the most common: Highland Park North Ph B Sec (7); Highland Park Ph C Sec 1 (7); Highland Park North Ph C Sec (5); Highland Park North Ph A Sec (4); Highland Park Ph C Sec 2 (4); Highland Park Ph A Sec 01 (4); Highland Park (4); Highland Park Ph D Sec 02 (3); HIGHLAND PARK (2); Highland Park Condo Amd (2); Highland Park Ph A Sec 2C (2); Highland Park Ph D Sec 7 (2); and 13 more (14 records). No other names were found by the search.

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 33 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
56 single-family sales in the window: 56 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
56 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
4 sale(s) other than single-family homes (condo, townhome and similar)

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 $318K”.
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 $318K: $272,700–$312,000 (14 sales); $318K–$358K: $318,000–$358,206 (14 sales); $365K–$415K: $365,000–$415,000 (14 sales); Over $415K: $420,000–$525,000 (14 sales)
Quartiles by living area: Under 1,618 SF: 1,292–1,509 SF (14 sales); 1,618–1,821 SF: 1,618–1,821 SF (13 sales); 1,826–2,277 SF: 1,826–2,277 SF (15 sales); Over 2,277 SF: 2,344–4,050 SF (14 sales)
Quartiles by year built: Before 2006: 2004–2005 (15 sales); 2006–2009: 2006–2009 (13 sales); 2011–2016: 2011–2016 (14 sales); After 2016: 2017–2018 (14 sales)
View and no view: View: MLS lists a view (10 sales); No view: None or Neighborhood (44 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 $371,986, median $361,603. Days on market: average 69, median 46: 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
8 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 = 26.383< 0.0001p < 0.0063Yesε² = 0.480large
Living areaKruskal–WallisH = 44.933< 0.0001p < 0.0063Yesε² = 0.817large
Year builtKruskal–WallisH = 17.2230.0006p < 0.0063Yesε² = 0.313large
Days on marketKruskal–WallisH = 3.2630.3529p < 0.0063Unclearε² = 0.059small
Discount from original listKruskal–WallisH = 5.4930.1392p < 0.0063Unclearε² = 0.100medium
Price cut before saleChi-squareχ² = 2.5030.4747p < 0.0063UnclearCramér’s V = 0.211small
Seller paid closing costs or repairsChi-squareχ² = 0.9330.8184p < 0.0063UnclearCramér’s V = 0.129small
Has a viewChi-squareχ² = 0.4930.9217p < 0.0063UnclearCramér’s V = 0.093negligible

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 47.173< 0.0001p < 0.0063Yesε² = 0.858large
Net price per SFKruskal–WallisH = 40.683< 0.0001p < 0.0063Yesε² = 0.740large
Year builtKruskal–WallisH = 15.4530.0015p < 0.0063Yesε² = 0.281large
Days on marketKruskal–WallisH = 1.8230.6106p < 0.0063Unclearε² = 0.033small
Discount from original listKruskal–WallisH = 0.8930.8276p < 0.0063Unclearε² = 0.016small
Price cut before saleChi-squareχ² = 4.1830.2428p < 0.0063UnclearCramér’s V = 0.273small
Seller paid closing costs or repairsChi-squareχ² = 2.7630.4298p < 0.0063UnclearCramér’s V = 0.222small
Has a viewChi-squareχ² = 0.3430.9514p < 0.0063UnclearCramér’s V = 0.078negligible

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 10.3030.0162p < 0.0063Unclearε² = 0.187large
Net price per SFKruskal–WallisH = 16.3930.0009p < 0.0063Yesε² = 0.298large
Living areaKruskal–WallisH = 15.7430.0013p < 0.0063Yesε² = 0.286large
Days on marketKruskal–WallisH = 5.7530.1246p < 0.0063Unclearε² = 0.105medium
Discount from original listKruskal–WallisH = 5.0730.1670p < 0.0063Unclearε² = 0.092medium
Price cut before saleChi-squareχ² = 6.6330.0847p < 0.0063UnclearCramér’s V = 0.344medium
Seller paid closing costs or repairsChi-squareχ² = 0.7830.8538p < 0.0063UnclearCramér’s V = 0.118small
Has a viewChi-squareχ² = 3.9030.2724p < 0.0063UnclearCramér’s V = 0.264small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 196.00—0.6008p < 0.0063Unclearrank-biserial r = 0.109small
Net price per SFMann–Whitney UU = 209.00—0.8151p < 0.0063Unclearrank-biserial r = 0.050negligible
Living areaMann–Whitney UU = 209.00—0.8150p < 0.0063Unclearrank-biserial r = 0.050negligible
Year builtMann–Whitney UU = 181.00—0.3861p < 0.0063Unclearrank-biserial r = 0.177small
Days on marketMann–Whitney UU = 224.00—0.9379p < 0.0063Unclearrank-biserial r = 0.018negligible
Discount from original listMann–Whitney UU = 253.00—0.4692p < 0.0063Unclearrank-biserial r = 0.150small
Price cut before saleChi-squareχ² = 0.4910.4835p < 0.0063UnclearCramér’s V = 0.095negligible
Seller paid closing costs or repairsChi-squareχ² = 0.0010.9773p < 0.0063UnclearCramér’s V = 0.004negligible

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 4 sale(s) other than single-family homes (condo, townhome and similar). 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 56 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.