ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Highland Hills

Austin, TX 78731
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 · 4:11 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
20
single-family resale homes
Median net sale price
$1,113,250
average $1,180,227
Median net price per SF
$449
average $466
Median days on market
10 days
average 46 days
1. SummaryResale homes · 20 sales · October 26, 2025 – October 25, 2026

This study looks at the 20 resale homes sold in Highland Hills in the 365 days to October 25, 2026. A full year is used because only 9 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 sold20 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 $952K · 5 sales$952K–$1.10M · 5 sales$1.13M–$1.33M · 5 salesOver $1.33M · 5 sales
3. Quartiles by net sale priceResale homes · 20 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.

2026-10-26T04:11:25.237537 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 5 5 5 20 sales Sales per group Under $952K: 5 sales (25%) $952K–$1.10M: 5 sales (25%) $1.13M–$1.33M: 5 sales (25%) Over $1.33M: 5 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 $952K$952K–$1.10M$1.13M–$1.33MOver $1.33M
Higher-priced homes Over $1.33M
  • Are much larger.
Lower-priced homes Under $952K
  • Are much smaller.

3.2 At a glance

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

Under $952K$952K–$1.10M$1.13M–$1.33MOver $1.33MReal difference?
Net price per SF$460 per SF$406 per SF$476 per SF$522 per SFunclear
Living area1,814 SFSmallest2,540 SF2,563 SF3,313 SFLargest✓ large
Year built1967196419661976unclear
Days on market112 days9 days7 days22 daysunclear
Discount from original list9.8%7.9%6.1%8.2%unclear
Price cut before sale60%40%40%40%unclear
Seller paid closing costs or repairs20%100%80%80%unclear
Has a view80%20%20%40%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

2026-10-26T04:11:25.266342 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $952K 5 sales $952K– $1.10M 5 sales $1.13M– $1.33M 5 sales Over $1.33M 5 sales $0 $200 $400 $600 $460 $406 $476 $522 Net price per SF, average

The average is $522 per SF for homes over $1.33M and $460 per SF for homes under $952K. It does not move in a straight line; homes over $1.33M are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $1.33M are about 1,500 SF (83%) larger than homes under $952K

2026-10-26T04:11:25.288825 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $952K 5 sales $952K– $1.10M 5 sales $1.13M– $1.33M 5 sales Over $1.33M 5 sales 0 1,000 2,000 3,000 1,814 2,540 2,563 3,313 Living area (SF), average

The average is 3,313 SF for homes over $1.33M and 1,814 SF for homes under $952K. 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

2026-10-26T04:11:25.314894 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $952K 5 sales $952K– $1.10M 5 sales $1.13M– $1.33M 5 sales Over $1.33M 5 sales 1960 1965 1970 1975 1980 1967 1964 1966 1976 Year built: median (dot) and middle half (bar)

The median is 1976 for homes over $1.33M and 1967 for homes under $952K. It does not move in a straight line; homes over $1.33M are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T04:11:25.338108 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $952K 5 sales $952K– $1.10M 5 sales $1.13M– $1.33M 5 sales Over $1.33M 5 sales 0 50 100 112 9 7 22 Days on market, median

The median is 22 days for homes over $1.33M and 112 days for homes under $952K. It does not move in a straight line; homes under $952K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T04:11:25.359431 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $952K 5 sales $952K– $1.10M 5 sales $1.13M– $1.33M 5 sales Over $1.33M 5 sales 0.0% 5.0% 10.0% 9.8% 7.9% 6.1% 8.2% Discount from original list, average

The average is 8.2% for homes over $1.33M and 9.8% for homes under $952K. It does not move in a straight line; homes under $952K 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

2026-10-26T04:11:25.388959 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% 60 20 80 40 100 20 40 80 20 40 80 40 Under $952K $952K–$1.10M $1.13M–$1.33M Over $1.33M

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

  • 40% of homes over $1.33M had a price cut before sale, against 60% of homes under $952K. Defined in 8.1.7.
  • 80% of homes over $1.33M had the seller pay closing costs or repairs, against 20% of homes under $952K. Defined in 8.1.8.
  • 40% of homes over $1.33M have a view, against 80% of homes under $952K. 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 $952K5 sales$952K–$1.10M5 sales$1.13M–$1.33M5 salesOver $1.33M5 salesAll20 salesReal difference?
Net sale price average$814,500$1,026,046$1,201,561$1,678,800$1,180,227by design
Net price per SF average$460$406$476$522$466unclear
Living area average1,8142,5402,5633,3132,558✓ large
Year built median19671964196619761968unclear

3.10 The numbers: selling

Under $952K5 sales$952K–$1.10M5 sales$1.13M–$1.33M5 salesOver $1.33M5 salesAll20 salesReal difference?
Days on market median112972210unclear
Discount from original list average9.8%7.9%6.1%8.2%8.0%unclear
Price cut before sale60%40%40%40%45%unclear
Seller paid closing costs or repairs20%100%80%80%70%unclear
Has a view80%20%20%40%40%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 · 20 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.

2026-10-26T04:11:25.408892 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 5 5 5 20 sales Sales per group Under 2,153 SF: 5 sales (25%) 2,153–2,551 SF: 5 sales (25%) 2,609–2,839 SF: 5 sales (25%) Over 2,839 SF: 5 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 2,153 SF2,153–2,551 SF2,609–2,839 SFOver 2,839 SF
Larger homes Over 2,839 SF
  • Sell for much more.
Smaller homes Under 2,153 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 2,153 SF2,153–2,551 SF2,609–2,839 SFOver 2,839 SFReal difference?
Net sale price$828KLowest$1.08M$1.25M$1.56MHighest✓ large
Net price per SF$480 per SF$458 per SF$465 per SF$461 per SFunclear
Year built1963196419681976unclear
Days on market6 days9 days12 days22 daysunclear
Discount from original list5.7%9.6%9.3%7.3%unclear
Price cut before sale40%40%60%40%unclear
Seller paid closing costs or repairs20%100%80%80%unclear
Has a view80%20%0%60%unclear

4.3 Homes over 2,839 SF sell for about $728K (88%) more than homes under 2,153 SF

2026-10-26T04:11:25.428829 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,153 SF 5 sales 2,153– 2,551 SF 5 sales 2,609– 2,839 SF 5 sales Over 2,839 SF 5 sales $0K $500K $1.00M $1.50M $828K $1.08M $1.25M $1.56M Net sale price, average

The average is $1.56M for homes over 2,839 SF and $828K for homes under 2,153 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

2026-10-26T04:11:25.451272 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,153 SF 5 sales 2,153– 2,551 SF 5 sales 2,609– 2,839 SF 5 sales Over 2,839 SF 5 sales $0 $200 $400 $480 $458 $465 $461 Net price per SF, average

The average is $461 per SF for homes over 2,839 SF and $480 per SF for homes under 2,153 SF. It does not move in a straight line; homes under 2,153 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T04:11:25.474269 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,153 SF 5 sales 2,153– 2,551 SF 5 sales 2,609– 2,839 SF 5 sales Over 2,839 SF 5 sales 1960 1965 1970 1975 1963 1964 1968 1976 Year built: median (dot) and middle half (bar)

The median is 1976 for homes over 2,839 SF and 1963 for homes under 2,153 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T04:11:25.496593 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,153 SF 5 sales 2,153– 2,551 SF 5 sales 2,609– 2,839 SF 5 sales Over 2,839 SF 5 sales 0 10 20 6 9 12 22 Days on market, median

The median is 22 days for homes over 2,839 SF and 6 days for homes under 2,153 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T04:11:25.517861 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,153 SF 5 sales 2,153– 2,551 SF 5 sales 2,609– 2,839 SF 5 sales Over 2,839 SF 5 sales 0.0% 5.0% 10.0% 5.7% 9.6% 9.3% 7.3% Discount from original list, average

The average is 7.3% for homes over 2,839 SF and 5.7% for homes under 2,153 SF. It does not move in a straight line; homes 2,153–2,551 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

2026-10-26T04:11:25.543912 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% 40 20 80 40 100 20 60 80 0 40 80 60 Under 2,153 SF 2,153–2,551 SF 2,609–2,839 SF Over 2,839 SF

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

  • 40% of homes over 2,839 SF had a price cut before sale, against 40% of homes under 2,153 SF. Defined in 8.1.7.
  • 80% of homes over 2,839 SF had the seller pay closing costs or repairs, against 20% of homes under 2,153 SF. Defined in 8.1.8.
  • 60% of homes over 2,839 SF have a view, against 80% of homes under 2,153 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 2,153 SF5 sales2,153–2,551 SF5 sales2,609–2,839 SF5 salesOver 2,839 SF5 salesAll20 salesReal difference?
Net sale price average$828,020$1,084,861$1,252,026$1,556,000$1,180,227✓ large
Net price per SF average$480$458$465$461$466unclear
Living area average1,7342,3912,7033,4022,558by design
Year built median19631964196819761968unclear

4.10 The numbers: selling

Under 2,153 SF5 sales2,153–2,551 SF5 sales2,609–2,839 SF5 salesOver 2,839 SF5 salesAll20 salesReal difference?
Days on market median69122210unclear
Discount from original list average5.7%9.6%9.3%7.3%8.0%unclear
Price cut before sale40%40%60%40%45%unclear
Seller paid closing costs or repairs20%100%80%80%70%unclear
Has a view80%20%0%60%40%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 · 20 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.

2026-10-26T04:11:25.563397 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 5 5 5 20 sales Sales per group Before 1963: 5 sales (25%) 1963–1967: 5 sales (25%) 1968–1973: 5 sales (25%) After 1973: 5 sales (25%)
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 19631963–19671968–1973After 1973Real difference?
Net sale price$1.01M$1.03M$1.16M$1.51Munclear
Net price per SF$469 per SF$400 per SF$499 per SF$497 per SFunclear
Living area2,161 SF2,543 SF2,424 SF3,102 SFunclear
Days on market12 days9 days6 days22 daysunclear
Discount from original list10.0%8.7%7.3%5.9%unclear
Price cut before sale60%40%40%40%unclear
Seller paid closing costs or repairs80%40%60%100%unclear
Has a view20%40%60%40%unclear

5.3 Net sale price: no clear difference

2026-10-26T04:11:25.583085 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1963 5 sales 1963– 1967 5 sales 1968– 1973 5 sales After 1973 5 sales $0K $500K $1.00M $1.50M $1.01M $1.03M $1.16M $1.51M Net sale price, average

The average is $1.51M for homes built after 1973 and $1.01M for homes built before 1963. 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

2026-10-26T04:11:25.605204 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1963 5 sales 1963– 1967 5 sales 1968– 1973 5 sales After 1973 5 sales $0 $200 $400 $469 $400 $499 $497 Net price per SF, average

The average is $497 per SF for homes built after 1973 and $469 per SF for homes built before 1963. It does not move in a straight line; homes built 1968–1973 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T04:11:25.625445 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1963 5 sales 1963– 1967 5 sales 1968– 1973 5 sales After 1973 5 sales 0 1,000 2,000 3,000 2,161 2,543 2,424 3,102 Living area (SF), average

The average is 3,102 SF for homes built after 1973 and 2,161 SF for homes built before 1963. It does not move in a straight line; homes built after 1973 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T04:11:25.646468 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1963 5 sales 1963– 1967 5 sales 1968– 1973 5 sales After 1973 5 sales 0 10 20 12 9 6 22 Days on market, median

The median is 22 days for homes built after 1973 and 12 days for homes built before 1963. It does not move in a straight line; homes built after 1973 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T04:11:25.667832 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1963 5 sales 1963– 1967 5 sales 1968– 1973 5 sales After 1973 5 sales 0.0% 5.0% 10.0% 10.0% 8.7% 7.3% 5.9% Discount from original list, average

The average is 5.9% for homes built after 1973 and 10.0% for homes built before 1963. 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

2026-10-26T04:11:25.693087 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% 60 80 20 40 40 40 40 60 60 40 100 40 Before 1963 1963–1967 1968–1973 After 1973

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

  • 40% of homes built after 1973 had a price cut before sale, against 60% of homes built before 1963. Defined in 8.1.7.
  • 100% of homes built after 1973 had the seller pay closing costs or repairs, against 80% of homes built before 1963. Defined in 8.1.8.
  • 40% of homes built after 1973 have a view, against 20% of homes built before 1963. 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 19635 sales1963–19675 sales1968–19735 salesAfter 19735 salesAll20 salesReal difference?
Net sale price average$1,012,381$1,033,500$1,162,300$1,512,726$1,180,227unclear
Net price per SF average$469$400$499$497$466unclear
Living area average2,1612,5432,4243,1022,558unclear
Year built median19571966196919771968by design

5.10 The numbers: selling

Before 19635 sales1963–19675 sales1968–19735 salesAfter 19735 salesAll20 salesReal difference?
Days on market median12962210unclear
Discount from original list average10.0%8.7%7.3%5.9%8.0%unclear
Price cut before sale60%40%40%40%45%unclear
Seller paid closing costs or repairs80%40%60%100%70%unclear
Has a view20%40%60%40%40%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 · 20 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. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T04:11:25.711758 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 11 19 sales Sales per group View: 8 sales (42%) No view: 11 sales (58%)
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$1.09M$1.25Munclear
Net price per SF$463 per SF$472 per SFunclear
Living area2,376 SF2,685 SFunclear
Year built19701967unclear
Days on market16 days7 daysunclear
Discount from original list6.0%8.9%unclear
Price cut before sale38%45%unclear
Seller paid closing costs or repairs50%82%unclear

6.3 Net sale price: no clear difference

2026-10-26T04:11:25.727595 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 11 sales $0K $500K $1.00M $1.50M $1.09M $1.25M Net sale price, average

The average is $1.09M for homes with a view and $1.25M 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

2026-10-26T04:11:25.745866 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 11 sales $0 $200 $400 $463 $472 Net price per SF, average

The average is $463 per SF for homes with a view and $472 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

2026-10-26T04:11:25.763561 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 11 sales 0 1,000 2,000 3,000 2,376 2,685 Living area (SF), average

The average is 2,376 SF for homes with a view and 2,685 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T04:11:25.867829 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 11 sales 1963 1966 1969 1972 1970 1967 Year built: median (dot) and middle half (bar)

The median is 1970 for homes with a view and 1967 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T04:11:25.885977 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 11 sales 0 5 10 15 16 7 Days on market, median

The median is 16 days for homes with a view and 7 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

2026-10-26T04:11:25.905096 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 11 sales 0.0% 2.5% 5.0% 7.5% 10.0% 6.0% 8.9% Discount from original list, average

The average is 6.0% for homes with a view and 8.9% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T04:11:25.924064 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 38 50 45 82 View No view

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

  • 38% of homes with a view had a price cut before sale, against 45% of homes without a view. Defined in 8.1.7.
  • 50% of homes with a view had the seller pay closing costs or repairs, against 82% 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

View8 salesNo view11 salesAll19 salesReal difference?
Net sale price average$1,088,250$1,254,730$1,184,633unclear
Net price per SF average$463$472$469unclear
Living area average2,3762,6852,555unclear
Year built median197019671968unclear

6.11 The numbers: selling

View8 salesNo view11 salesAll19 salesReal difference?
Days on market median1679unclear
Discount from original list average6.0%8.9%7.7%unclear
Price cut before sale38%45%42%unclear
Seller paid closing costs or repairs50%82%68%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 Hills.

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
20 resale sales. Average $1,180,227; median $1,113,250; standard deviation $346,082; middle half (25th–75th percentile) $951,875–$1,379,500; lowest $635,000, highest $1,945,000. 14 sales had a seller payment; their median payment was $16,200.

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
20 resale sales. Average $466; median $449; standard deviation $93; middle half (25th–75th percentile) $396–$520; lowest $351, highest $738.

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
20 resale sales. Average 2,558; median 2,580; standard deviation 670; middle half (25th–75th percentile) 2,152–2,880; lowest 1,404, highest 4,029.

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
20 resale sales. Average 1969; median 1968; standard deviation 14; middle half (25th–75th percentile) 1962–1974; lowest 1956, highest 2021.

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
20 resale sales. Average 46; median 10; standard deviation 59; middle half (25th–75th percentile) 5–101; lowest 2, highest 177. 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
20 resale sales. Average 8.0%; median 6.8%; standard deviation 8.9%; middle half (25th–75th percentile) 2.2%–13.0%; lowest −7.2%, highest 26.0%. 3 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
9 of 20 resale sales (45.0%).

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
14 of 20 resale sales (70.0%).

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
8 sales with a view, 11 without, 1 unclassified. Most common View entries: Trees/Woods 7, Neighborhood 7, None 6, Hill Country 2, Panoramic 2, Creek/Stream 1, Park/Greenbelt 1, See Remarks 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 “highland hills” (case-insensitive). A record is kept when its subdivision name belongs to the Highland Hills family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 21 closed Highland Hills records over the prior year, in ZIP 78731. 11 subdivision spellings kept: Highland Hills Sec 07 Ph 01 (4); Highland Hills Sec 08 (3); Highland Hills (2); Highland Hills Sec 05 Ph 02 (2); Highland Hills Sec 09 Ph 02 (2); Highland Hills Sec 10 (2); Highland Hills Sec 09 Ph 01 (2); Highland Hills Sec 04 (1); Highland Hills Sec 01 (1); Highland Hills Sec 02 (1); Highland Hills Sec 03 (1). Names found by the search but not part of Highland Hills, left out: Highland Hills Northwest Sec 3 (2); Highland Hills Northwest Sec 1 (2); Highland Hills Northwest Sec 2 (2); Highland Hills Northwest Sec 6 (1); Highland Hills Northwest Sec 5 (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 9 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
20 single-family sales in the window: 20 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
20 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 $952K”.
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 $952K: $635,000–$950,000 (5 sales); $952K–$1.10M: $952,500–$1,096,500 (5 sales); $1.13M–$1.33M: $1,130,000–$1,331,000 (5 sales); Over $1.33M: $1,525,000–$1,945,000 (5 sales)
Quartiles by living area: Under 2,153 SF: 1,404–2,150 SF (5 sales); 2,153–2,551 SF: 2,153–2,551 SF (5 sales); 2,609–2,839 SF: 2,609–2,839 SF (5 sales); Over 2,839 SF: 3,004–4,029 SF (5 sales)
Quartiles by year built: Before 1963: 1956–1957 (5 sales); 1963–1967: 1963–1967 (5 sales); 1968–1973: 1968–1973 (5 sales); After 1973: 1976–2021 (5 sales)
View and no view: View: MLS lists a view (8 sales); No view: None or Neighborhood (11 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 $1,180,227, median $1,113,250. Days on market: average 46, median 10: 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
2 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 = 3.8730.2760p < 0.0063Unclearε² = 0.204large
Living areaKruskal–WallisH = 12.4630.0060p < 0.0063Yesε² = 0.656large
Year builtKruskal–WallisH = 5.2730.1531p < 0.0063Unclearε² = 0.277large
Days on marketKruskal–WallisH = 0.9230.8194p < 0.0063Unclearε² = 0.049small
Discount from original listKruskal–WallisH = 0.3530.9506p < 0.0063Unclearε² = 0.018small
Price cut before saleChi-squareχ² = 0.6130.8950p < 0.0063UnclearCramér’s V = 0.174small
Seller paid closing costs or repairsChi-squareχ² = 8.5730.0356p < 0.0063UnclearCramér’s V = 0.655large
Has a viewChi-squareχ² = 5.0030.1718p < 0.0063UnclearCramér’s V = 0.500large

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 13.0830.0045p < 0.0063Yesε² = 0.688large
Net price per SFKruskal–WallisH = 0.9830.8068p < 0.0063Unclearε² = 0.051small
Year builtKruskal–WallisH = 6.5630.0873p < 0.0063Unclearε² = 0.345large
Days on marketKruskal–WallisH = 0.0930.9931p < 0.0063Unclearε² = 0.005negligible
Discount from original listKruskal–WallisH = 0.6630.8832p < 0.0063Unclearε² = 0.035small
Price cut before saleChi-squareχ² = 0.6130.8950p < 0.0063UnclearCramér’s V = 0.174small
Seller paid closing costs or repairsChi-squareχ² = 8.5730.0356p < 0.0063UnclearCramér’s V = 0.655large
Has a viewChi-squareχ² = 8.3330.0396p < 0.0063UnclearCramér’s V = 0.645large

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 5.3730.1469p < 0.0063Unclearε² = 0.282large
Net price per SFKruskal–WallisH = 5.7830.1230p < 0.0063Unclearε² = 0.304large
Living areaKruskal–WallisH = 7.3030.0630p < 0.0063Unclearε² = 0.384large
Days on marketKruskal–WallisH = 0.3430.9527p < 0.0063Unclearε² = 0.018small
Discount from original listKruskal–WallisH = 0.5730.9042p < 0.0063Unclearε² = 0.030small
Price cut before saleChi-squareχ² = 0.6130.8950p < 0.0063UnclearCramér’s V = 0.174small
Seller paid closing costs or repairsChi-squareχ² = 4.7630.1901p < 0.0063UnclearCramér’s V = 0.488medium
Has a viewChi-squareχ² = 1.6730.6444p < 0.0063UnclearCramér’s V = 0.289small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 29.00—0.2375p < 0.0063Unclearrank-biserial r = 0.341medium
Net price per SFMann–Whitney UU = 44.00—1.0000p < 0.0063Unclearrank-biserial r = 0.000negligible
Living areaMann–Whitney UU = 34.00—0.4421p < 0.0063Unclearrank-biserial r = 0.227small
Year builtMann–Whitney UU = 48.50—0.7406p < 0.0063Unclearrank-biserial r = 0.102small
Days on marketMann–Whitney UU = 49.50—0.6793p < 0.0063Unclearrank-biserial r = 0.125small
Discount from original listMann–Whitney UU = 36.00—0.5448p < 0.0063Unclearrank-biserial r = 0.182small
Price cut before saleChi-squareχ² = 0.1210.7288p < 0.0063UnclearCramér’s V = 0.080negligible
Seller paid closing costs or repairsChi-squareχ² = 2.1710.1407p < 0.0063UnclearCramér’s V = 0.338medium

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 20 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.