ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Highland Hills

Austin, TX 78731
Resale homes · closed Nov 5 – Nov 4, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 5, 2026 · 3:07 PM CST
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
21
single-family resale homes
Median net sale price
$1,096,500
average $1,171,644
Median net price per SF
$441
average $459
Median days on market
12 days
average 44 days
1. SummaryResale homes · 21 sales · November 5, 2025 – November 4, 2026

This study looks at the 21 resale homes sold in Highland Hills in the 365 days to November 4, 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 sold21 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–$1.07M · 5 sales$1.10M–$1.33M · 6 salesOver $1.33M · 5 sales
3. Quartiles by net sale priceResale homes · 21 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T15:07:17.359318 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 5 6 5 21 sales Sales per group Under $952K: 5 sales (24%) $952K–$1.07M: 5 sales (24%) $1.10M–$1.33M: 6 sales (29%) Over $1.33M: 5 sales (24%)
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–$1.07M$1.10M–$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–$1.07M$1.10M–$1.33MOver $1.33MReal difference?
Net price per SF$460 per SF$387 per SF$466 per SF$522 per SFunclear
Living area1,814 SFSmallest2,638 SF2,571 SF3,313 SFLargest✓ large
Year built1967196419621976unclear
Days on market112 days9 days10 days22 daysunclear
Discount from original list9.8%7.0%7.3%8.2%unclear
Price cut before sale60%20%50%40%unclear
Seller paid closing costs or repairs20%80%83%80%unclear
Has a view80%20%17%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

2026-11-05T15:07:17.387784 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $952K 5 sales $952K– $1.07M 5 sales $1.10M– $1.33M 6 sales Over $1.33M 5 sales $0 $200 $400 $600 $460 $387 $466 $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

2026-11-05T15:07:17.410845 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $952K 5 sales $952K– $1.07M 5 sales $1.10M– $1.33M 6 sales Over $1.33M 5 sales 0 1,000 2,000 3,000 1,814 2,638 2,571 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 does not move in a straight line; homes over $1.33M are highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-11-05T15:07:17.436842 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $952K 5 sales $952K– $1.07M 5 sales $1.10M– $1.33M 6 sales Over $1.33M 5 sales 1960 1965 1970 1975 1980 1967 1964 1962 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

2026-11-05T15:07:17.461004 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $952K 5 sales $952K– $1.07M 5 sales $1.10M– $1.33M 6 sales Over $1.33M 5 sales 0 50 100 112 9 10 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

2026-11-05T15:07:17.483136 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $952K 5 sales $952K– $1.07M 5 sales $1.10M– $1.33M 6 sales Over $1.33M 5 sales 0.0% 5.0% 10.0% 9.8% 7.0% 7.3% 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

2026-11-05T15:07:17.513154 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 20 80 20 50 83 17 40 80 40 Under $952K $952K–$1.07M $1.10M–$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–$1.07M5 sales$1.10M–$1.33M6 salesOver $1.33M5 salesAll21 salesReal difference?
Net sale price average$814,500$1,006,746$1,184,051$1,678,800$1,171,644by design
Net price per SF average$460$387$466$522$459unclear
Living area average1,8142,6382,5713,3132,583✓ large
Year built median19671964196219761967unclear

3.10 The numbers: selling

Under $952K5 sales$952K–$1.07M5 sales$1.10M–$1.33M6 salesOver $1.33M5 salesAll21 salesReal difference?
Days on market median1129102212unclear
Discount from original list average9.8%7.0%7.3%8.2%8.0%unclear
Price cut before sale60%20%50%40%43%unclear
Seller paid closing costs or repairs20%80%83%80%67%unclear
Has a view80%20%17%40%38%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 · 21 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T15:07:17.533670 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 5 6 5 21 sales Sales per group Under 2,153 SF: 5 sales (24%) 2,153–2,551 SF: 5 sales (24%) 2,609–3,004 SF: 6 sales (29%) Over 3,004 SF: 5 sales (24%)
Bottom line: no measure differs enough between the groups to rule out chance.

4.1 Key differences

The top group against the bottom group: no measure differs enough to rule out chance.

4.2 At a glance

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

Under 2,153 SF2,153–2,551 SF2,609–3,004 SFOver 3,004 SFReal difference?
Net sale price$828K$1.08M$1.30M$1.45Munclear
Net price per SF$480 per SF$458 per SF$472 per SF$424 per SFunclear
Year built1963196419671976unclear
Days on market6 days9 days18 days12 daysunclear
Discount from original list5.7%9.6%9.9%6.6%unclear
Price cut before sale40%40%67%20%unclear
Seller paid closing costs or repairs20%100%67%80%unclear
Has a view80%20%0%60%unclear

4.3 Net sale price: no clear difference

2026-11-05T15:07:17.554212 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– 3,004 SF 6 sales Over 3,004 SF 5 sales $0K $500K $1.00M $1.50M $828K $1.08M $1.30M $1.45M Net sale price, average

The average is $1.45M for homes over 3,004 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.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-11-05T15:07:17.577562 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– 3,004 SF 6 sales Over 3,004 SF 5 sales $0 $200 $400 $480 $458 $472 $424 Net price per SF, average

The average is $424 per SF for homes over 3,004 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

2026-11-05T15:07:17.601380 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– 3,004 SF 6 sales Over 3,004 SF 5 sales 1960 1965 1970 1975 1963 1964 1967 1976 Year built: median (dot) and middle half (bar)

The median is 1976 for homes over 3,004 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

2026-11-05T15:07:17.624282 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– 3,004 SF 6 sales Over 3,004 SF 5 sales 0 10 20 6 9 18 12 Days on market, median

The median is 12 days for homes over 3,004 SF and 6 days for homes under 2,153 SF. It does not move in a straight line; homes 2,609–3,004 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-05T15:07:17.646383 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– 3,004 SF 6 sales Over 3,004 SF 5 sales 0.0% 5.0% 10.0% 5.7% 9.6% 9.9% 6.6% Discount from original list, average

The average is 6.6% for homes over 3,004 SF and 5.7% for homes under 2,153 SF. It does not move in a straight line; homes 2,609–3,004 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-05T15:07:17.672560 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 67 67 0 20 80 60 Under 2,153 SF 2,153–2,551 SF 2,609–3,004 SF Over 3,004 SF

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

  • 20% of homes over 3,004 SF had a price cut before sale, against 40% of homes under 2,153 SF. Defined in 8.1.7.
  • 80% of homes over 3,004 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 3,004 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 sales2,609–3,004 SF6 salesOver 3,004 SF5 salesAll21 salesReal difference?
Net sale price average$828,020$1,084,861$1,297,521$1,451,000$1,171,644unclear
Net price per SF average$480$458$472$424$459unclear
Living area average1,7342,3912,7533,4212,583by design
Year built median19631964196719761967unclear

4.10 The numbers: selling

Under 2,153 SF5 sales2,153–2,551 SF5 sales2,609–3,004 SF6 salesOver 3,004 SF5 salesAll21 salesReal difference?
Days on market median69181212unclear
Discount from original list average5.7%9.6%9.9%6.6%8.0%unclear
Price cut before sale40%40%67%20%43%unclear
Seller paid closing costs or repairs20%100%67%80%67%unclear
Has a view80%20%0%60%38%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 · 21 sales · November 5, 2025 – November 4, 2026

Sales ranked by year built and cut into four groups, from the oldest to the newest. Homes built in the same year always stay in the same group, so group sizes can differ a little.

2026-11-05T15:07:17.692658 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 5 6 5 21 sales Sales per group Before 1958: 5 sales (24%) 1958–1966: 5 sales (24%) 1967–1973: 6 sales (29%) After 1973: 5 sales (24%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

The top group against the bottom group: no measure differs enough to rule out chance.

5.2 At a glance

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

Before 19581958–19661967–1973After 1973Real difference?
Net sale price$1.01M$1.05M$1.12M$1.51Munclear
Net price per SF$469 per SF$392 per SF$476 per SF$497 per SFunclear
Living area2,161 SF2,652 SF2,446 SF3,102 SFunclear
Days on market12 days9 days59 days22 daysunclear
Discount from original list10.0%5.3%10.4%5.9%unclear
Price cut before sale60%20%50%40%unclear
Seller paid closing costs or repairs80%20%67%100%unclear
Has a view20%40%50%40%unclear

5.3 Net sale price: no clear difference

2026-11-05T15:07:17.713088 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1958 5 sales 1958– 1966 5 sales 1967– 1973 6 sales After 1973 5 sales $0K $500K $1.00M $1.50M $1.01M $1.05M $1.12M $1.51M Net sale price, average

The average is $1.51M for homes built after 1973 and $1.01M for homes built before 1958. 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

2026-11-05T15:07:17.736175 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1958 5 sales 1958– 1966 5 sales 1967– 1973 6 sales After 1973 5 sales $0 $200 $400 $469 $392 $476 $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 1958. It does not move in a straight line; homes built after 1973 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-05T15:07:17.757362 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1958 5 sales 1958– 1966 5 sales 1967– 1973 6 sales After 1973 5 sales 0 1,000 2,000 3,000 2,161 2,652 2,446 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 1958. 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

2026-11-05T15:07:17.778580 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1958 5 sales 1958– 1966 5 sales 1967– 1973 6 sales After 1973 5 sales 0 20 40 60 12 9 59 22 Days on market, median

The median is 22 days for homes built after 1973 and 12 days for homes built before 1958. It does not move in a straight line; homes built 1967–1973 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-05T15:07:17.801321 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1958 5 sales 1958– 1966 5 sales 1967– 1973 6 sales After 1973 5 sales 0.0% 5.0% 10.0% 10.0% 5.3% 10.4% 5.9% Discount from original list, average

The average is 5.9% for homes built after 1973 and 10.0% for homes built before 1958. It does not move in a straight line; homes built 1967–1973 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-05T15:07:17.826468 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 20 20 40 50 67 50 40 100 40 Before 1958 1958–1966 1967–1973 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 1958. 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 1958. Defined in 8.1.8.
  • 40% of homes built after 1973 have a view, against 20% of homes built before 1958. 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 19585 sales1958–19665 sales1967–19736 salesAfter 19735 salesAll21 salesReal difference?
Net sale price average$1,012,381$1,048,500$1,122,750$1,512,726$1,171,644unclear
Net price per SF average$469$392$476$497$459unclear
Living area average2,1612,6522,4463,1022,583unclear
Year built median19571964196919771967by design

5.10 The numbers: selling

Before 19585 sales1958–19665 sales1967–19736 salesAfter 19735 salesAll21 salesReal difference?
Days on market median129592212unclear
Discount from original list average10.0%5.3%10.4%5.9%8.0%unclear
Price cut before sale60%20%50%40%43%unclear
Seller paid closing costs or repairs80%20%67%100%67%unclear
Has a view20%40%50%40%38%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 · 21 sales · November 5, 2025 – November 4, 2026

Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood. 2 sales whose MLS view entry is only “See Remarks” are left out.

2026-11-05T15:07:17.844676 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

2026-11-05T15:07:17.860467 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

2026-11-05T15:07:17.878353 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

2026-11-05T15:07:17.896358 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

2026-11-05T15:07:17.940841 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

2026-11-05T15:07:17.958434 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

2026-11-05T15:07:17.977695 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

2026-11-05T15:07:17.996827 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 · November 5, 2025 – November 4, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 0 sales, no groups, no tests.

Note: these are only the new-construction sales reported in ABOR MLS. Builders often sell homes without listing them in the MLS, so these figures do not necessarily represent all new-construction sales in 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
21 resale sales. Average $1,171,644; median $1,096,500; standard deviation $339,604; middle half (25th–75th percentile) $952,500–$1,331,000; 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
21 resale sales. Average $459; median $441; standard deviation $96; middle half (25th–75th percentile) $390–$515; lowest $323, 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
21 resale sales. Average 2,583; median 2,609; standard deviation 664; middle half (25th–75th percentile) 2,153–3,004; 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
21 resale sales. Average 1969; median 1967; standard deviation 14; middle half (25th–75th percentile) 1958–1973; 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
21 resale sales. Average 44; median 12; standard deviation 58; middle half (25th–75th percentile) 5–100; 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
21 resale sales. Average 8.0%; median 7.4%; standard deviation 8.6%; middle half (25th–75th percentile) 2.4%–12.9%; 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 21 resale sales (42.9%).

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 21 resale sales (66.7%).

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, 2 unclassified. Most common View entries: Trees/Woods 7, Neighborhood 7, None 6, Hill Country 2, See Remarks 2, Panoramic 2, Garden 1, Creek/Stream 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-05 21:00 UTC), every field. 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 November 5, 2026: 22 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 Sec 03 (2); Highland Hills Sec 10 (2); Highland Hills Sec 09 Ph 02 (2); Highland Hills Sec 09 Ph 01 (2); Highland Hills (2); Highland Hills Sec 05 Ph 02 (2); Highland Hills Sec 04 (1); Highland Hills Sec 02 (1); Highland Hills Sec 01 (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 5 (1); Highland Hills Northwest Sec 6 (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 November 5, 2025 to November 4, 2026 inclusive.
The data
21 single-family sales in the window: 21 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
21 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–$1.07M: $952,500–$1,070,000 (5 sales); $1.10M–$1.33M: $1,096,500–$1,331,000 (6 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); 2,609–3,004 SF: 2,609–3,004 SF (6 sales); Over 3,004 SF: 3,084–4,029 SF (5 sales)
Quartiles by year built: Before 1958: 1956–1957 (5 sales); 1958–1966: 1958–1966 (5 sales); 1967–1973: 1967–1973 (6 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 $1,171,644, median $1,096,500. Days on market: average 44, median 12: 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
1 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 5.2030.1579p < 0.0063Unclearε² = 0.260large
Living areaKruskal–WallisH = 12.4330.0060p < 0.0063Yesε² = 0.622large
Year builtKruskal–WallisH = 5.7530.1245p < 0.0063Unclearε² = 0.287large
Days on marketKruskal–WallisH = 0.9130.8227p < 0.0063Unclearε² = 0.046small
Discount from original listKruskal–WallisH = 0.1530.9845p < 0.0063Unclearε² = 0.008negligible
Price cut before saleChi-squareχ² = 1.8130.6131p < 0.0063UnclearCramér’s V = 0.293small
Seller paid closing costs or repairsChi-squareχ² = 6.4530.0917p < 0.0063UnclearCramér’s V = 0.554large
Has a viewChi-squareχ² = 5.5930.1332p < 0.0063UnclearCramér’s V = 0.516large

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 11.5230.0092p < 0.0063Unclearε² = 0.576large
Net price per SFKruskal–WallisH = 1.0930.7786p < 0.0063Unclearε² = 0.055small
Year builtKruskal–WallisH = 5.4930.1392p < 0.0063Unclearε² = 0.275large
Days on marketKruskal–WallisH = 0.2530.9693p < 0.0063Unclearε² = 0.012small
Discount from original listKruskal–WallisH = 1.1730.7594p < 0.0063Unclearε² = 0.059small
Price cut before saleChi-squareχ² = 2.4930.4773p < 0.0063UnclearCramér’s V = 0.344medium
Seller paid closing costs or repairsChi-squareχ² = 7.8030.0503p < 0.0063UnclearCramér’s V = 0.609large
Has a viewChi-squareχ² = 9.1330.0277p < 0.0063UnclearCramér’s V = 0.659large

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 5.3830.1457p < 0.0063Unclearε² = 0.269large
Net price per SFKruskal–WallisH = 4.6530.1992p < 0.0063Unclearε² = 0.233large
Living areaKruskal–WallisH = 7.4730.0584p < 0.0063Unclearε² = 0.373large
Days on marketKruskal–WallisH = 0.7930.8517p < 0.0063Unclearε² = 0.040small
Discount from original listKruskal–WallisH = 1.1330.7695p < 0.0063Unclearε² = 0.057small
Price cut before saleChi-squareχ² = 1.8130.6131p < 0.0063UnclearCramér’s V = 0.293small
Seller paid closing costs or repairsChi-squareχ² = 7.8030.0503p < 0.0063UnclearCramér’s V = 0.609large
Has a viewChi-squareχ² = 1.0730.7843p < 0.0063UnclearCramér’s V = 0.226small

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 21 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 5, 2026. Map data © OpenStreetMap contributors. ALEX Companies · Licensed by the Texas Real Estate Commission · Broker: Alexander Tiffany Southwest, LLC (ALEX Real Estate), #565194-BB · Diane Hart Alexander, Designated Broker, #574877-B.