ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Highpointe

Austin, TX 78737
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 · 7:33 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
44
single-family resale homes
Median net sale price
$827,875
average $821,215
Median net price per SF
$244
average $248
Median days on market
40 days
average 73 days
1. SummaryResale homes · 44 sales · October 26, 2025 – October 25, 2026

This study looks at the 44 resale homes sold in Highpointe in the 365 days to October 25, 2026. A full year is used because only 27 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 sold44 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 $710K · 11 sales$710K–$813K · 11 sales$843K–$895K · 11 salesOver $895K · 11 sales
3. Quartiles by net sale priceResale homes · 44 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.

2026-10-26T07:33:17.271338 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 11 11 11 44 sales Sales per group Under $710K: 11 sales (25%) $710K–$813K: 11 sales (25%) $843K–$895K: 11 sales (25%) Over $895K: 11 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 $710K$710K–$813K$843K–$895KOver $895K
Higher-priced homes Over $895K
  • Are much larger.
  • Sell for more per square foot.
Lower-priced homes Under $710K
  • Are much smaller.
  • Sell for less per square foot.

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 $710K$710K–$813K$843K–$895KOver $895KReal difference?
Net price per SF$219 per SFLowest$239 per SF$259 per SF$275 per SFHighest✓ large
Living area2,747 SFSmallest3,239 SF3,397 SF3,893 SFLargest✓ large
Year built2011201420182020unclear
Days on market47 days62 days20 days20 daysunclear
Discount from original list3.5%5.6%3.6%2.9%unclear
Price cut before sale64%64%27%27%unclear
Seller paid closing costs or repairs36%55%73%64%unclear
Has a view64%27%64%45%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 $895K sell for about $55 per SF (25%) more than homes under $710K

2026-10-26T07:33:17.299352 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $710K 11 sales $710K– $813K 11 sales $843K– $895K 11 sales Over $895K 11 sales $0 $100 $200 $300 $219 $239 $259 $275 Net price per SF, average

The average is $275 per SF for homes over $895K and $219 per SF for homes under $710K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $895K are about 1,150 SF (42%) larger than homes under $710K

2026-10-26T07:33:17.321633 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $710K 11 sales $710K– $813K 11 sales $843K– $895K 11 sales Over $895K 11 sales 0 2,000 4,000 2,747 3,239 3,397 3,893 Living area (SF), average

The average is 3,893 SF for homes over $895K and 2,747 SF for homes under $710K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-26T07:33:17.346098 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $710K 11 sales $710K– $813K 11 sales $843K– $895K 11 sales Over $895K 11 sales 2008 2011 2014 2017 2020 2011 2014 2018 2020 Year built: median (dot) and middle half (bar)

The median is 2020 for homes over $895K and 2011 for homes under $710K. 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

2026-10-26T07:33:17.368865 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $710K 11 sales $710K– $813K 11 sales $843K– $895K 11 sales Over $895K 11 sales 0 20 40 60 47 62 20 20 Days on market, median

The median is 20 days for homes over $895K and 47 days for homes under $710K. It does not move in a straight line; homes $710K–$813K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:33:17.390608 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $710K 11 sales $710K– $813K 11 sales $843K– $895K 11 sales Over $895K 11 sales 0.0% 2.0% 4.0% 6.0% 3.5% 5.6% 3.6% 2.9% Discount from original list, average

The average is 2.9% for homes over $895K and 3.5% for homes under $710K. It does not move in a straight line; homes $710K–$813K 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

2026-10-26T07:33:17.420459 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% 64 36 64 64 55 27 27 73 64 27 64 45 Under $710K $710K–$813K $843K–$895K Over $895K

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

  • 27% of homes over $895K had a price cut before sale, against 64% of homes under $710K. Defined in 8.1.7.
  • 64% of homes over $895K had the seller pay closing costs or repairs, against 36% of homes under $710K. Defined in 8.1.8.
  • 45% of homes over $895K have a view, against 64% of homes under $710K. 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 $710K11 sales$710K–$813K11 sales$843K–$895K11 salesOver $895K11 salesAll44 salesReal difference?
Net sale price average$600,834$765,214$868,152$1,050,660$821,215by design
Net price per SF average$219$239$259$275$248✓ large
Living area average2,7473,2393,3973,8933,319✓ large
Year built median20112014201820202014unclear

3.10 The numbers: selling

Under $710K11 sales$710K–$813K11 sales$843K–$895K11 salesOver $895K11 salesAll44 salesReal difference?
Days on market median4762202040unclear
Discount from original list average3.5%5.6%3.6%2.9%3.9%unclear
Price cut before sale64%64%27%27%45%unclear
Seller paid closing costs or repairs36%55%73%64%57%unclear
Has a view64%27%64%45%50%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 · 44 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.

2026-10-26T07:33:17.440643 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 11 11 11 44 sales Sales per group Under 2,895 SF: 11 sales (25%) 2,895–3,279 SF: 11 sales (25%) 3,295–3,565 SF: 11 sales (25%) Over 3,565 SF: 11 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 2,895 SF2,895–3,279 SF3,295–3,565 SFOver 3,565 SF
Larger homes Over 3,565 SF
  • Sell for much more.
Smaller homes Under 2,895 SF
  • Sell for much less.

4.2 At a glance

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

Under 2,895 SF2,895–3,279 SF3,295–3,565 SFOver 3,565 SFReal difference?
Net sale price$636KLowest$776K$879K$994KHighest✓ large
Net price per SF$238 per SF$252 per SF$260 per SF$242 per SFunclear
Year built2012201520172013unclear
Days on market46 days44 days30 days44 daysunclear
Discount from original list3.4%4.3%3.1%4.9%unclear
Price cut before sale45%64%36%36%unclear
Seller paid closing costs or repairs55%36%73%64%unclear
Has a view45%36%55%64%unclear

4.3 Homes over 3,565 SF sell for about $357K (56%) more than homes under 2,895 SF

2026-10-26T07:33:17.461467 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,895 SF 11 sales 2,895– 3,279 SF 11 sales 3,295– 3,565 SF 11 sales Over 3,565 SF 11 sales $0K $500K $1.00M $636K $776K $879K $994K Net sale price, average

The average is $994K for homes over 3,565 SF and $636K for homes under 2,895 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-26T07:33:17.483882 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,895 SF 11 sales 2,895– 3,279 SF 11 sales 3,295– 3,565 SF 11 sales Over 3,565 SF 11 sales $0 $100 $200 $300 $238 $252 $260 $242 Net price per SF, average

The average is $242 per SF for homes over 3,565 SF and $238 per SF for homes under 2,895 SF. It does not move in a straight line; homes 3,295–3,565 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:33:17.508706 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,895 SF 11 sales 2,895– 3,279 SF 11 sales 3,295– 3,565 SF 11 sales Over 3,565 SF 11 sales 2008 2011 2014 2017 2020 2012 2015 2017 2013 Year built: median (dot) and middle half (bar)

The median is 2013 for homes over 3,565 SF and 2012 for homes under 2,895 SF. It does not move in a straight line; homes 3,295–3,565 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:33:17.532009 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,895 SF 11 sales 2,895– 3,279 SF 11 sales 3,295– 3,565 SF 11 sales Over 3,565 SF 11 sales 0 20 40 46 44 30 44 Days on market, median

The median is 44 days for homes over 3,565 SF and 46 days for homes under 2,895 SF. It does not move in a straight line; homes under 2,895 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:33:17.554112 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,895 SF 11 sales 2,895– 3,279 SF 11 sales 3,295– 3,565 SF 11 sales Over 3,565 SF 11 sales 0.0% 2.0% 4.0% 3.4% 4.3% 3.1% 4.9% Discount from original list, average

The average is 4.9% for homes over 3,565 SF and 3.4% for homes under 2,895 SF. It does not move in a straight line; homes over 3,565 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

2026-10-26T07:33:17.580163 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% 45 55 45 64 36 36 36 73 55 36 64 64 Under 2,895 SF 2,895–3,279 SF 3,295–3,565 SF Over 3,565 SF

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

  • 36% of homes over 3,565 SF had a price cut before sale, against 45% of homes under 2,895 SF. Defined in 8.1.7.
  • 64% of homes over 3,565 SF had the seller pay closing costs or repairs, against 55% of homes under 2,895 SF. Defined in 8.1.8.
  • 64% of homes over 3,565 SF have a view, against 45% of homes under 2,895 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 2,895 SF11 sales2,895–3,279 SF11 sales3,295–3,565 SF11 salesOver 3,565 SF11 salesAll44 salesReal difference?
Net sale price average$636,493$776,034$878,709$993,624$821,215✓ large
Net price per SF average$238$252$260$242$248unclear
Living area average2,6713,0873,3764,1423,319by design
Year built median20122015201720132014unclear

4.10 The numbers: selling

Under 2,895 SF11 sales2,895–3,279 SF11 sales3,295–3,565 SF11 salesOver 3,565 SF11 salesAll44 salesReal difference?
Days on market median4644304440unclear
Discount from original list average3.4%4.3%3.1%4.9%3.9%unclear
Price cut before sale45%64%36%36%45%unclear
Seller paid closing costs or repairs55%36%73%64%57%unclear
Has a view45%36%55%64%50%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 · 44 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.

2026-10-26T07:33:17.600507 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 9 12 12 44 sales Sales per group Before 2010: 11 sales (25%) 2010–2013: 9 sales (20%) 2014–2018: 12 sales (27%) After 2018: 12 sales (27%)
Bottom line

5.1 Key differences

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

Before 20102010–20132014–2018After 2018
Newer homes After 2018
  • Sell for more per square foot.
  • Sell for much more.
Older homes Before 2010
  • Sell for less per square foot.
  • Sell for much less.

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 20102010–20132014–2018After 2018Real difference?
Net sale price$766K$677KLowest$780K$1.02MHighest✓ large
Net price per SF$220 per SFLowest$225 per SF$249 per SF$290 per SFHighest✓ large
Living area3,528 SF2,993 SF3,135 SF3,555 SFunclear
Days on market53 days33 days48 days10 daysunclear
Discount from original list5.4%2.4%3.8%3.8%unclear
Price cut before sale73%33%50%25%unclear
Seller paid closing costs or repairs64%56%50%58%unclear
Has a view64%78%25%42%unclear

5.3 Homes built after 2018 sell for about $255K (33%) more than homes built before 2010

2026-10-26T07:33:17.621040 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2010 11 sales 2010– 2013 9 sales 2014– 2018 12 sales After 2018 12 sales $0K $500K $1.00M $766K $677K $780K $1.02M Net sale price, average

The average is $1.02M for homes built after 2018 and $766K for homes built before 2010. It does not move in a straight line; homes built after 2018 are highest. Defined in 8.1.1.

✓ Real difference · large

5.4 Homes built after 2018 sell for about $70 per SF (32%) more than homes built before 2010

2026-10-26T07:33:17.644023 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2010 11 sales 2010– 2013 9 sales 2014– 2018 12 sales After 2018 12 sales $0 $100 $200 $300 $220 $225 $249 $290 Net price per SF, average

The average is $290 per SF for homes built after 2018 and $220 per SF for homes built before 2010. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

5.5 Living area: no clear difference

2026-10-26T07:33:17.666036 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2010 11 sales 2010– 2013 9 sales 2014– 2018 12 sales After 2018 12 sales 0 2,000 4,000 3,528 2,993 3,135 3,555 Living area (SF), average

The average is 3,555 SF for homes built after 2018 and 3,528 SF for homes built before 2010. It does not move in a straight line; homes built after 2018 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:33:17.687737 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2010 11 sales 2010– 2013 9 sales 2014– 2018 12 sales After 2018 12 sales 0 20 40 60 53 33 48 10 Days on market, median

The median is 10 days for homes built after 2018 and 53 days for homes built before 2010. It does not move in a straight line; homes built before 2010 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:33:17.710595 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2010 11 sales 2010– 2013 9 sales 2014– 2018 12 sales After 2018 12 sales 0.0% 2.0% 4.0% 6.0% 5.4% 2.4% 3.8% 3.8% Discount from original list, average

The average is 3.8% for homes built after 2018 and 5.4% for homes built before 2010. It does not move in a straight line; homes built before 2010 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

2026-10-26T07:33:17.736350 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% 73 64 64 33 56 78 50 50 25 25 58 42 Before 2010 2010–2013 2014–2018 After 2018

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

  • 25% of homes built after 2018 had a price cut before sale, against 73% of homes built before 2010. Defined in 8.1.7.
  • 58% of homes built after 2018 had the seller pay closing costs or repairs, against 64% of homes built before 2010. Defined in 8.1.8.
  • 42% of homes built after 2018 have a view, against 64% of homes built before 2010. 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 201011 sales2010–20139 sales2014–201812 salesAfter 201812 salesAll44 salesReal difference?
Net sale price average$766,443$676,522$779,917$1,021,240$821,215✓ large
Net price per SF average$220$225$249$290$248✓ large
Living area average3,5282,9933,1353,5553,319unclear
Year built median20072012201520202014by design

5.10 The numbers: selling

Before 201011 sales2010–20139 sales2014–201812 salesAfter 201812 salesAll44 salesReal difference?
Days on market median5333481040unclear
Discount from original list average5.4%2.4%3.8%3.8%3.9%unclear
Price cut before sale73%33%50%25%45%unclear
Seller paid closing costs or repairs64%56%50%58%57%unclear
Has a view64%78%25%42%50%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 · 44 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.

2026-10-26T07:33:17.754856 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 22 20 42 sales Sales per group View: 22 sales (52%) No view: 20 sales (48%)
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$818K$823Kunclear
Net price per SF$238 per SF$256 per SFunclear
Living area3,440 SF3,209 SFunclear
Year built20122014unclear
Days on market26 days52 daysunclear
Discount from original list2.8%5.3%unclear
Price cut before sale36%55%unclear
Seller paid closing costs or repairs59%50%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:33:17.771699 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 22 sales No view 20 sales $0K $200K $400K $600K $800K $818K $823K Net sale price, average

The average is $818K for homes with a view and $823K 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

2026-10-26T07:33:17.789625 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 22 sales No view 20 sales $0 $100 $200 $300 $238 $256 Net price per SF, average

The average is $238 per SF for homes with a view and $256 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

2026-10-26T07:33:17.808929 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 22 sales No view 20 sales 0 1,000 2,000 3,000 4,000 3,440 3,209 Living area (SF), average

The average is 3,440 SF for homes with a view and 3,209 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:33:17.854563 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 22 sales No view 20 sales 2008 2011 2014 2017 2020 2012 2014 Year built: median (dot) and middle half (bar)

The median is 2012 for homes with a view and 2014 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:33:17.872658 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 22 sales No view 20 sales 0 20 40 60 26 52 Days on market, median

The median is 26 days for homes with a view and 52 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

2026-10-26T07:33:17.890750 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 22 sales No view 20 sales 0.0% 2.0% 4.0% 6.0% 2.8% 5.3% Discount from original list, average

The average is 2.8% for homes with a view and 5.3% 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

2026-10-26T07:33:17.909536 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 36 59 55 50 View No view

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

  • 36% of homes with a view had a price cut before sale, against 55% of homes without a view. Defined in 8.1.7.
  • 59% of homes with a view had the seller pay closing costs or repairs, against 50% 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

View22 salesNo view20 salesAll42 salesReal difference?
Net sale price average$817,707$823,100$820,275unclear
Net price per SF average$238$256$247unclear
Living area average3,4403,2093,330unclear
Year built median201220142014unclear

6.11 The numbers: selling

View22 salesNo view20 salesAll42 salesReal difference?
Days on market median265240unclear
Discount from original list average2.8%5.3%4.0%unclear
Price cut before sale36%55%45%unclear
Seller paid closing costs or repairs59%50%55%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 Highpointe.

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
44 resale sales. Average $821,215; median $827,875; standard deviation $178,628; middle half (25th–75th percentile) $702,500–$901,156; lowest $527,900, highest $1,275,000. 25 sales had a seller payment; their median payment was $3,720.

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
44 resale sales. Average $248; median $244; standard deviation $35; middle half (25th–75th percentile) $215–$274; lowest $185, highest $330.

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
44 resale sales. Average 3,319; median 3,287; standard deviation 602; middle half (25th–75th percentile) 2,891–3,576; lowest 2,360, highest 4,947.

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
44 resale sales. Average 2014; median 2014; standard deviation 5; middle half (25th–75th percentile) 2010–2019; lowest 2006, highest 2022.

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
44 resale sales. Average 73; median 40; standard deviation 97; middle half (25th–75th percentile) 10–78; lowest 0, highest 427. 1 sales went under contract on their listing date (0 days).

8.1.6 Discount from original list

In simple terms
How far below the first asking price the home sold, after seller payments. It measures how much negotiating room sellers gave up. A negative figure means the home sold above its first asking price.
Statistically
Discount % = (OriginalListPrice − Net) ÷ OriginalListPrice × 100, per sale; summarized by the mean.
The data
44 resale sales. Average 3.9%; median 3.5%; standard deviation 4.6%; middle half (25th–75th percentile) 0.7%–6.5%; lowest −10.2%, highest 16.2%. 4 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
20 of 44 resale sales (45.5%).

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 44 resale sales (56.8%).

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
22 sales with a view, 20 without, 2 unclassified. Most common View entries: Park/Greenbelt 15, Neighborhood 13, None 12, Hill Country 7, Trees/Woods 5, See Remarks 2, Panoramic 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 = Austin, SubdivisionName contains any of “highpointe”, “burba ranch”, “high pointe” (case-insensitive). A record is kept when its subdivision name belongs to the Highpointe family, the same rule comparable sales use (it includes Burba Ranch, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 45 closed Highpointe records over the prior year, in ZIP 78737. 20 subdivision spellings kept, the most common: Highpointe Condo (8); Highpointe Ph V Sec Two (5); Highpointe Ph V Sec Three (4); Highpointe Ph Ii Sec Two-B (3); High Pointe Ph I Sec One (3); Highpointe Ph I Sec Three A (3); Highpointe (3); Highpointe Ph I Sec 01 (2); Burba Ranch (2); Highpointe Ph II Sec Two-B (2); HighPointe Ph I Sec One (1); High Pointe Ph Iii Sec One (1); and 8 more (8 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 27 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
44 single-family sales in the window: 44 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
44 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
1 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 $710K”.
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 $710K: $527,900–$680,000 (11 sales); $710K–$813K: $710,000–$813,000 (11 sales); $843K–$895K: $842,750–$894,875 (11 sales); Over $895K: $920,000–$1,275,000 (11 sales)
Quartiles by living area: Under 2,895 SF: 2,360–2,879 SF (11 sales); 2,895–3,279 SF: 2,895–3,279 SF (11 sales); 3,295–3,565 SF: 3,295–3,565 SF (11 sales); Over 3,565 SF: 3,608–4,947 SF (11 sales)
Quartiles by year built: Before 2010: 2006–2008 (11 sales); 2010–2013: 2010–2013 (9 sales); 2014–2018: 2014–2018 (12 sales); After 2018: 2019–2022 (12 sales)
View and no view: View: MLS lists a view (22 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 $821,215, median $827,875. Days on market: average 73, median 40: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

In simple terms
Checks whether a measure really differs across the four groups of a slice. It uses each sale's rank, not its value, so a few extreme sales cannot drive the answer.
Statistically
H = [12/(n(n+1))] Σ Rⱼ²/nⱼ − 3(n+1), compared with χ² on k − 1 degrees of freedom (Kruskal & Wallis, 1952). Effect size ε² = H/(n − 1): ≥ .01 small, ≥ .06 medium, ≥ .14 large (Tomczak & Tomczak, 2014). A slice is tested only when every group has at least 5 sales; smaller groups are described, not tested.
The data
Run on every measure in sections 3–5; each result is in 8.3.

8.2.8 Mann–Whitney U test

In simple terms
The same check when there are only two groups: view against no view.
Statistically
Two-sided U test (Mann & Whitney, 1947). Effect size = rank-biserial correlation |1 − 2U/(n₁n₂)|: ≥ .10 small, ≥ .30 medium, ≥ .50 large (Kerby, 2014; Cohen, 1988).
The data
Run on every measure in section 6; results in 8.3.

8.2.9 Chi-square test

In simple terms
Checks whether a yes/no share (price cut, seller payment, view) differs between groups more than chance would.
Statistically
Pearson χ² on the 2 × k table of counts, no continuity correction (Pearson, 1900). Effect size Cramér's V = √(χ²/n): ≥ .10 small, ≥ .30 medium, ≥ .50 large (Cramér, 1946).
The data
Run on the three shares in every slice; results in 8.3.

8.2.10 Real difference (significance)

In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063; Quartiles by year built: m = 8, threshold p < 0.0063; View and no view: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
5 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 14.2030.0026p < 0.0063Yesε² = 0.330large
Living areaKruskal–WallisH = 23.443< 0.0001p < 0.0063Yesε² = 0.545large
Year builtKruskal–WallisH = 9.6030.0223p < 0.0063Unclearε² = 0.223large
Days on marketKruskal–WallisH = 3.2730.3512p < 0.0063Unclearε² = 0.076medium
Discount from original listKruskal–WallisH = 1.5130.6802p < 0.0063Unclearε² = 0.035small
Price cut before saleChi-squareχ² = 5.8730.1183p < 0.0063UnclearCramér’s V = 0.365medium
Seller paid closing costs or repairsChi-squareχ² = 3.2430.3558p < 0.0063UnclearCramér’s V = 0.271small
Has a viewChi-squareχ² = 4.0030.2615p < 0.0063UnclearCramér’s V = 0.302medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 24.773< 0.0001p < 0.0063Yesε² = 0.576large
Net price per SFKruskal–WallisH = 2.8230.4207p < 0.0063Unclearε² = 0.066medium
Year builtKruskal–WallisH = 4.7830.1887p < 0.0063Unclearε² = 0.111medium
Days on marketKruskal–WallisH = 0.4130.9378p < 0.0063Unclearε² = 0.010negligible
Discount from original listKruskal–WallisH = 0.7330.8661p < 0.0063Unclearε² = 0.017small
Price cut before saleChi-squareχ² = 2.2030.5319p < 0.0063UnclearCramér’s V = 0.224small
Seller paid closing costs or repairsChi-squareχ² = 3.2430.3558p < 0.0063UnclearCramér’s V = 0.271small
Has a viewChi-squareχ² = 1.8230.6110p < 0.0063UnclearCramér’s V = 0.203small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 21.923< 0.0001p < 0.0063Yesε² = 0.510large
Net price per SFKruskal–WallisH = 27.223< 0.0001p < 0.0063Yesε² = 0.633large
Living areaKruskal–WallisH = 6.4730.0909p < 0.0063Unclearε² = 0.150large
Days on marketKruskal–WallisH = 6.5130.0893p < 0.0063Unclearε² = 0.151large
Discount from original listKruskal–WallisH = 2.6630.4465p < 0.0063Unclearε² = 0.062medium
Price cut before saleChi-squareχ² = 5.9630.1137p < 0.0063UnclearCramér’s V = 0.368medium
Seller paid closing costs or repairsChi-squareχ² = 0.4530.9291p < 0.0063UnclearCramér’s V = 0.101small
Has a viewChi-squareχ² = 6.9330.0742p < 0.0063UnclearCramér’s V = 0.397medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 212.00—0.8502p < 0.0063Unclearrank-biserial r = 0.036negligible
Net price per SFMann–Whitney UU = 161.00—0.1407p < 0.0063Unclearrank-biserial r = 0.268small
Living areaMann–Whitney UU = 252.50—0.4203p < 0.0063Unclearrank-biserial r = 0.148small
Year builtMann–Whitney UU = 159.50—0.1295p < 0.0063Unclearrank-biserial r = 0.275small
Days on marketMann–Whitney UU = 162.50—0.1510p < 0.0063Unclearrank-biserial r = 0.261small
Discount from original listMann–Whitney UU = 141.00—0.0480p < 0.0063Unclearrank-biserial r = 0.359medium
Price cut before saleChi-squareχ² = 1.4710.2255p < 0.0063UnclearCramér’s V = 0.187small
Seller paid closing costs or repairsChi-squareχ² = 0.3510.5544p < 0.0063UnclearCramér’s V = 0.091negligible

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 1 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 44 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.