ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Northwest Hills

Austin, TX 78731 · 78759
Resale homes · closed Oct 29 – Oct 28, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 29, 2026 · 7:24 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
50
single-family resale homes
Median net sale price
$1,248,750
average $1,385,024
Median net price per SF
$483
average $479
Median days on market
29 days
average 52 days
1. SummaryResale homes · 50 sales · October 29, 2025 – October 28, 2026

This study looks at the 50 resale homes sold in Northwest Hills in the 365 days to October 28, 2026. A full year is used because only 32 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 sold50 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 $1.08M · 12 sales$1.08M–$1.25M · 13 sales$1.25M–$1.61M · 13 salesOver $1.61M · 12 sales
3. Quartiles by net sale priceResale homes · 50 sales · October 29, 2025 – October 28, 2026

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

2026-10-29T07:24:52.941001 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 13 13 12 50 sales Sales per group Under $1.08M: 12 sales (24%) $1.08M–$1.25M: 13 sales (26%) $1.25M–$1.61M: 13 sales (26%) Over $1.61M: 12 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 $1.08M$1.08M–$1.25M$1.25M–$1.61MOver $1.61M
Higher-priced homes Over $1.61M
  • Sell for more per square foot.
  • Are much larger.
Lower-priced homes Under $1.08M
  • Sell for less per square foot.
  • 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 $1.08M$1.08M–$1.25M$1.25M–$1.61MOver $1.61MReal difference?
Net price per SF$357 per SFLowest$446 per SF$504 per SF$610 per SFHighest✓ large
Living area2,493 SFSmallest2,654 SF2,948 SF3,500 SFLargest✓ large
Year built1968196919711970unclear
Days on market66 days10 days21 days29 daysunclear
Discount from original list12.9%1.5%5.3%4.6%unclear
Price cut before sale67%15%23%50%unclear
Seller paid closing costs or repairs42%46%31%25%unclear
Has a view42%38%23%25%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 $1.61M sell for about $252 per SF (71%) more than homes under $1.08M

2026-10-29T07:24:52.969249 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.08M 12 sales $1.08M– $1.25M 13 sales $1.25M– $1.61M 13 sales Over $1.61M 12 sales $0 $200 $400 $600 $357 $446 $504 $610 Net price per SF, average

The average is $610 per SF for homes over $1.61M and $357 per SF for homes under $1.08M. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $1.61M are about 1,010 SF (40%) larger than homes under $1.08M

2026-10-29T07:24:52.992160 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.08M 12 sales $1.08M– $1.25M 13 sales $1.25M– $1.61M 13 sales Over $1.61M 12 sales 0 2,000 4,000 2,493 2,654 2,948 3,500 Living area (SF), average

The average is 3,500 SF for homes over $1.61M and 2,493 SF for homes under $1.08M. 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

2026-10-29T07:24:53.017351 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.08M 12 sales $1.08M– $1.25M 13 sales $1.25M– $1.61M 13 sales Over $1.61M 12 sales 1965 1970 1975 1980 1985 1968 1969 1971 1970 Year built: median (dot) and middle half (bar)

The median is 1970 for homes over $1.61M and 1968 for homes under $1.08M. It does not move in a straight line; homes $1.25M–$1.61M are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-29T07:24:53.040627 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.08M 12 sales $1.08M– $1.25M 13 sales $1.25M– $1.61M 13 sales Over $1.61M 12 sales 0 20 40 60 66 10 21 29 Days on market, median

The median is 29 days for homes over $1.61M and 66 days for homes under $1.08M. It does not move in a straight line; homes under $1.08M are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-29T07:24:53.062749 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.08M 12 sales $1.08M– $1.25M 13 sales $1.25M– $1.61M 13 sales Over $1.61M 12 sales 0.0% 5.0% 10.0% 15.0% 12.9% 1.5% 5.3% 4.6% Discount from original list, average

The average is 4.6% for homes over $1.61M and 12.9% for homes under $1.08M. It does not move in a straight line; homes under $1.08M 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

2026-10-29T07:24:53.093840 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 67 42 42 15 46 38 23 31 23 50 25 25 Under $1.08M $1.08M–$1.25M $1.25M–$1.61M Over $1.61M

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

  • 50% of homes over $1.61M had a price cut before sale, against 67% of homes under $1.08M. Defined in 8.1.7.
  • 25% of homes over $1.61M had the seller pay closing costs or repairs, against 42% of homes under $1.08M. Defined in 8.1.8.
  • 25% of homes over $1.61M have a view, against 42% of homes under $1.08M. 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 $1.08M12 sales$1.08M–$1.25M13 sales$1.25M–$1.61M13 salesOver $1.61M12 salesAll50 salesReal difference?
Net sale price average$878,036$1,151,827$1,428,939$2,097,067$1,385,024by design
Net price per SF average$357$446$504$610$479✓ large
Living area average2,4932,6542,9483,5002,895✓ large
Year built median19681969197119701969unclear

3.10 The numbers: selling

Under $1.08M12 sales$1.08M–$1.25M13 sales$1.25M–$1.61M13 salesOver $1.61M12 salesAll50 salesReal difference?
Days on market median6610212929unclear
Discount from original list average12.9%1.5%5.3%4.6%6.0%unclear
Price cut before sale67%15%23%50%38%unclear
Seller paid closing costs or repairs42%46%31%25%36%unclear
Has a view42%38%23%25%32%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 · 50 sales · October 29, 2025 – October 28, 2026

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

2026-10-29T07:24:53.114722 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 13 13 12 50 sales Sales per group Under 2,403 SF: 12 sales (24%) 2,403–2,728 SF: 13 sales (26%) 2,795–3,263 SF: 13 sales (26%) Over 3,263 SF: 12 sales (24%)
Bottom line

4.1 Key differences

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

Under 2,403 SF2,403–2,728 SF2,795–3,263 SFOver 3,263 SF
Larger homes Over 3,263 SF
  • Sell for much more.
Smaller homes Under 2,403 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 2,403 SF2,403–2,728 SF2,795–3,263 SFOver 3,263 SFReal difference?
Net sale price$1.18M$1.10MLowest$1.41M$1.87MHighest✓ large
Net price per SF$532 per SF$428 per SF$473 per SF$488 per SFunclear
Year built1969196819711970unclear
Days on market33 days7 days19 days52 daysunclear
Discount from original list5.0%6.2%6.3%6.3%unclear
Price cut before sale17%31%38%67%unclear
Seller paid closing costs or repairs25%38%46%33%unclear
Has a view42%23%31%33%unclear

4.3 Homes over 3,263 SF sell for about $687K (58%) more than homes under 2,403 SF

2026-10-29T07:24:53.135378 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,403 SF 12 sales 2,403– 2,728 SF 13 sales 2,795– 3,263 SF 13 sales Over 3,263 SF 12 sales $0K $1.00M $2.00M $1.18M $1.10M $1.41M $1.87M Net sale price, average

The average is $1.87M for homes over 3,263 SF and $1.18M for homes under 2,403 SF. It does not move in a straight line; homes over 3,263 SF are highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-29T07:24:53.157926 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,403 SF 12 sales 2,403– 2,728 SF 13 sales 2,795– 3,263 SF 13 sales Over 3,263 SF 12 sales $0 $200 $400 $600 $532 $428 $473 $488 Net price per SF, average

The average is $488 per SF for homes over 3,263 SF and $532 per SF for homes under 2,403 SF. It does not move in a straight line; homes under 2,403 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-29T07:24:53.183067 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,403 SF 12 sales 2,403– 2,728 SF 13 sales 2,795– 3,263 SF 13 sales Over 3,263 SF 12 sales 1965 1970 1975 1980 1985 1969 1968 1971 1970 Year built: median (dot) and middle half (bar)

The median is 1970 for homes over 3,263 SF and 1969 for homes under 2,403 SF. It does not move in a straight line; homes 2,795–3,263 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-29T07:24:53.206372 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,403 SF 12 sales 2,403– 2,728 SF 13 sales 2,795– 3,263 SF 13 sales Over 3,263 SF 12 sales 0 20 40 60 33 7 19 52 Days on market, median

The median is 52 days for homes over 3,263 SF and 33 days for homes under 2,403 SF. It does not move in a straight line; homes over 3,263 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-29T07:24:53.228600 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,403 SF 12 sales 2,403– 2,728 SF 13 sales 2,795– 3,263 SF 13 sales Over 3,263 SF 12 sales 0.0% 2.0% 4.0% 6.0% 5.0% 6.2% 6.3% 6.3% Discount from original list, average

The average is 6.3% for homes over 3,263 SF and 5.0% for homes under 2,403 SF. It rises step by step from the lowest range to the 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

2026-10-29T07:24:53.255562 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% 17 25 42 31 38 23 38 46 31 67 33 33 Under 2,403 SF 2,403–2,728 SF 2,795–3,263 SF Over 3,263 SF

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

  • 67% of homes over 3,263 SF had a price cut before sale, against 17% of homes under 2,403 SF. Defined in 8.1.7.
  • 33% of homes over 3,263 SF had the seller pay closing costs or repairs, against 25% of homes under 2,403 SF. Defined in 8.1.8.
  • 33% of homes over 3,263 SF have a view, against 42% of homes under 2,403 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 2,403 SF12 sales2,403–2,728 SF13 sales2,795–3,263 SF13 salesOver 3,263 SF12 salesAll50 salesReal difference?
Net sale price average$1,182,729$1,100,269$1,408,683$1,870,172$1,385,024✓ large
Net price per SF average$532$428$473$488$479unclear
Living area average2,2122,5792,9823,8242,895by design
Year built median19691968197119701969unclear

4.10 The numbers: selling

Under 2,403 SF12 sales2,403–2,728 SF13 sales2,795–3,263 SF13 salesOver 3,263 SF12 salesAll50 salesReal difference?
Days on market median337195229unclear
Discount from original list average5.0%6.2%6.3%6.3%6.0%unclear
Price cut before sale17%31%38%67%38%unclear
Seller paid closing costs or repairs25%38%46%33%36%unclear
Has a view42%23%31%33%32%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 · 50 sales · October 29, 2025 – October 28, 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.

2026-10-29T07:24:53.276342 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 13 15 12 50 sales Sales per group Before 1966: 10 sales (20%) 1966–1968: 13 sales (26%) 1969–1974: 15 sales (30%) After 1974: 12 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 19661966–19681969–1974After 1974Real difference?
Net sale price$1.44M$1.07M$1.39M$1.68Munclear
Net price per SF$475 per SF$414 per SF$497 per SF$530 per SFunclear
Living area3,125 SF2,631 SF2,791 SF3,118 SFunclear
Days on market29 days35 days7 days64 daysunclear
Discount from original list9.8%6.6%2.2%6.7%unclear
Price cut before sale50%38%20%50%unclear
Seller paid closing costs or repairs40%54%27%25%unclear
Has a view30%23%20%58%unclear

5.3 Net sale price: no clear difference

2026-10-29T07:24:53.297206 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1966 10 sales 1966– 1968 13 sales 1969– 1974 15 sales After 1974 12 sales $0K $1.00M $2.00M $1.44M $1.07M $1.39M $1.68M Net sale price, average

The average is $1.68M for homes built after 1974 and $1.44M for homes built before 1966. It does not move in a straight line; homes built after 1974 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-29T07:24:53.320262 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1966 10 sales 1966– 1968 13 sales 1969– 1974 15 sales After 1974 12 sales $0 $200 $400 $600 $475 $414 $497 $530 Net price per SF, average

The average is $530 per SF for homes built after 1974 and $475 per SF for homes built before 1966. It does not move in a straight line; homes built after 1974 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-29T07:24:53.342607 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1966 10 sales 1966– 1968 13 sales 1969– 1974 15 sales After 1974 12 sales 0 1,000 2,000 3,000 3,125 2,631 2,791 3,118 Living area (SF), average

The average is 3,118 SF for homes built after 1974 and 3,125 SF for homes built before 1966. It does not move in a straight line; homes built before 1966 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-29T07:24:53.364605 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1966 10 sales 1966– 1968 13 sales 1969– 1974 15 sales After 1974 12 sales 0 20 40 60 29 35 7 64 Days on market, median

The median is 64 days for homes built after 1974 and 29 days for homes built before 1966. It does not move in a straight line; homes built after 1974 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-29T07:24:53.387992 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1966 10 sales 1966– 1968 13 sales 1969– 1974 15 sales After 1974 12 sales 0.0% 5.0% 10.0% 9.8% 6.6% 2.2% 6.7% Discount from original list, average

The average is 6.7% for homes built after 1974 and 9.8% for homes built before 1966. It does not move in a straight line; homes built before 1966 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

2026-10-29T07:24:53.413711 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% 50 40 30 38 54 23 20 27 20 50 25 58 Before 1966 1966–1968 1969–1974 After 1974

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

  • 50% of homes built after 1974 had a price cut before sale, against 50% of homes built before 1966. Defined in 8.1.7.
  • 25% of homes built after 1974 had the seller pay closing costs or repairs, against 40% of homes built before 1966. Defined in 8.1.8.
  • 58% of homes built after 1974 have a view, against 30% of homes built before 1966. 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 196610 sales1966–196813 sales1969–197415 salesAfter 197412 salesAll50 salesReal difference?
Net sale price average$1,437,178$1,067,923$1,386,607$1,683,109$1,385,024unclear
Net price per SF average$475$414$497$530$479unclear
Living area average3,1252,6312,7913,1182,895unclear
Year built median19631967197119811969by design

5.10 The numbers: selling

Before 196610 sales1966–196813 sales1969–197415 salesAfter 197412 salesAll50 salesReal difference?
Days on market median293576429unclear
Discount from original list average9.8%6.6%2.2%6.7%6.0%unclear
Price cut before sale50%38%20%50%38%unclear
Seller paid closing costs or repairs40%54%27%25%36%unclear
Has a view30%23%20%58%32%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 · 50 sales · October 29, 2025 – October 28, 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.

2026-10-29T07:24:53.432150 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 16 32 48 sales Sales per group View: 16 sales (33%) No view: 32 sales (67%)
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$1.27M$1.40Munclear
Net price per SF$447 per SF$493 per SFunclear
Living area2,896 SF2,839 SFunclear
Year built19731968unclear
Days on market64 days18 daysunclear
Discount from original list8.4%4.5%unclear
Price cut before sale56%25%unclear
Seller paid closing costs or repairs50%28%unclear

6.3 Net sale price: no clear difference

2026-10-29T07:24:53.448226 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 32 sales $0K $500K $1.00M $1.50M $1.27M $1.40M Net sale price, average

The average is $1.27M for homes with a view and $1.40M 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

2026-10-29T07:24:53.466248 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 32 sales $0 $200 $400 $447 $493 Net price per SF, average

The average is $447 per SF for homes with a view and $493 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

2026-10-29T07:24:53.483251 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 32 sales 0 1,000 2,000 3,000 2,896 2,839 Living area (SF), average

The average is 2,896 SF for homes with a view and 2,839 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-29T07:24:53.529594 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 32 sales 1966 1969 1972 1975 1978 1973 1968 Year built: median (dot) and middle half (bar)

The median is 1973 for homes with a view and 1968 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-29T07:24:53.547716 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 32 sales 0 20 40 60 64 18 Days on market, median

The median is 64 days for homes with a view and 18 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

2026-10-29T07:24:53.567384 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 32 sales 0.0% 2.5% 5.0% 7.5% 10.0% 8.4% 4.5% Discount from original list, average

The average is 8.4% for homes with a view and 4.5% 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

2026-10-29T07:24:53.586625 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 56 50 25 28 View No view

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

  • 56% of homes with a view had a price cut before sale, against 25% 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 28% 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

View16 salesNo view32 salesAll48 salesReal difference?
Net sale price average$1,271,491$1,398,198$1,355,962unclear
Net price per SF average$447$493$478unclear
Living area average2,8962,8392,858unclear
Year built median197319681969unclear

6.11 The numbers: selling

View16 salesNo view32 salesAll48 salesReal difference?
Days on market median641826unclear
Discount from original list average8.4%4.5%5.8%unclear
Price cut before sale56%25%35%unclear
Seller paid closing costs or repairs50%28%35%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 29, 2025 – October 28, 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 Northwest 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
50 resale sales. Average $1,385,024; median $1,248,750; standard deviation $501,475; middle half (25th–75th percentile) $1,083,125–$1,605,000; lowest $800,000, highest $3,225,000. 18 sales had a seller payment; their median payment was $10,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
50 resale sales. Average $479; median $483; standard deviation $128; middle half (25th–75th percentile) $369–$537; lowest $294, highest $875.

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
50 resale sales. Average 2,895; median 2,762; standard deviation 659; middle half (25th–75th percentile) 2,404–3,230; lowest 1,786, highest 4,934.

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
50 resale sales. Average 1973; median 1969; standard deviation 12; middle half (25th–75th percentile) 1966–1974; lowest 1959, highest 2024.

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
50 resale sales. Average 52; median 29; standard deviation 70; middle half (25th–75th percentile) 5–70; lowest 0, highest 323. 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
50 resale sales. Average 6.0%; median 3.6%; standard deviation 10.2%; middle half (25th–75th percentile) 0.7%–10.6%; lowest −25.0%, highest 31.1%. 9 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
19 of 50 resale sales (38.0%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
18 of 50 resale sales (36.0%).

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
16 sales with a view, 32 without, 2 unclassified. Most common View entries: None 22, Neighborhood 17, Trees/Woods 10, Hill Country 7, See Remarks 5, Panoramic 4, Park/Greenbelt 4, Canyon 3.

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 “northwest hills”, “northwest hills mesa oaks”, “highland hills northwest” (case-insensitive). A record is kept when its subdivision name belongs to the Northwest Hills family, the same rule comparable sales use (it includes Northwest Hills Mesa Oaks Ph, Highland Hills Northwest Sec 2, proven adjacent and priced alike).
The data
Pulled October 29, 2026: 50 closed Northwest Hills records over the prior year, in ZIP 78731, 78759. 17 subdivision spellings kept, the most common: Northwest Hills Mesa Oaks Ph (15); Northwest Hills (5); Northwest Hills Sec 06 (4); Northwest Hills Sec 13 (4); Northwest Hills Sec 12 (3); Northwest Hills Sec 07 (3); Highland Hills Northwest Sec 3 (2); Northwest Hills Sec 08 (2); Highland Hills Northwest Sec 1 (2); Northwest Hills Sec 01 (2); Highland Hills Northwest Sec 2 (2); Northwest Hills Sec 05 Ph 02 (1); and 5 more (5 records). Names found by the search but not part of Northwest Hills, left out: Northwest Hills Northwest Oaks (6); Northwest Hills Lakeview 03 (4); Townhomes Northwest Hills (2); Northwest Hills Cat Mountain S (2); Northwest Hills Lakeview 02 (1); Northwest Hills Ranch Sec 01 (1); Northwest Hills Ranch Sec 1 (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 32 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 29, 2025 to October 28, 2026 inclusive.
The data
50 single-family sales in the window: 50 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
50 resale; 0 new construction.

8.2.4 Sales left out

In simple terms
A few records cannot be used as entered and are left out before any analysis.
Statistically
Excluded: PropertySubType other than Single Family Residence; no OriginalListPrice; LivingArea under 400 SF; seller payments above 10% of ClosePrice (treated as entry errors).
The data
None in this window.

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $1.08M”.
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 $1.08M: $800,000–$1,000,000 (12 sales); $1.08M–$1.25M: $1,082,500–$1,245,000 (13 sales); $1.25M–$1.61M: $1,252,500–$1,610,000 (13 sales); Over $1.61M: $1,650,000–$3,225,000 (12 sales)
Quartiles by living area: Under 2,403 SF: 1,786–2,400 SF (12 sales); 2,403–2,728 SF: 2,403–2,728 SF (13 sales); 2,795–3,263 SF: 2,795–3,263 SF (13 sales); Over 3,263 SF: 3,269–4,934 SF (12 sales)
Quartiles by year built: Before 1966: 1959–1965 (10 sales); 1966–1968: 1966–1968 (13 sales); 1969–1974: 1969–1974 (15 sales); After 1974: 1975–2024 (12 sales)
View and no view: View: MLS lists a view (16 sales); No view: None or Neighborhood (32 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 $1,385,024, median $1,248,750. Days on market: average 52, median 29: 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
3 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 = 25.133< 0.0001p < 0.0063Yesε² = 0.513large
Living areaKruskal–WallisH = 15.6330.0014p < 0.0063Yesε² = 0.319large
Year builtKruskal–WallisH = 1.0730.7851p < 0.0063Unclearε² = 0.022small
Days on marketKruskal–WallisH = 2.1030.5523p < 0.0063Unclearε² = 0.043small
Discount from original listKruskal–WallisH = 6.6930.0824p < 0.0063Unclearε² = 0.137medium
Price cut before saleChi-squareχ² = 8.9730.0297p < 0.0063UnclearCramér’s V = 0.424medium
Seller paid closing costs or repairsChi-squareχ² = 1.5330.6745p < 0.0063UnclearCramér’s V = 0.175small
Has a viewChi-squareχ² = 1.5130.6798p < 0.0063UnclearCramér’s V = 0.174small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 16.6430.0008p < 0.0063Yesε² = 0.340large
Net price per SFKruskal–WallisH = 3.4130.3326p < 0.0063Unclearε² = 0.070medium
Year builtKruskal–WallisH = 1.2630.7395p < 0.0063Unclearε² = 0.026small
Days on marketKruskal–WallisH = 3.2330.3573p < 0.0063Unclearε² = 0.066medium
Discount from original listKruskal–WallisH = 1.3330.7226p < 0.0063Unclearε² = 0.027small
Price cut before saleChi-squareχ² = 6.7930.0788p < 0.0063UnclearCramér’s V = 0.369medium
Seller paid closing costs or repairsChi-squareχ² = 1.2830.7331p < 0.0063UnclearCramér’s V = 0.160small
Has a viewChi-squareχ² = 1.0130.7989p < 0.0063UnclearCramér’s V = 0.142small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 9.7430.0209p < 0.0063Unclearε² = 0.199large
Net price per SFKruskal–WallisH = 6.3130.0977p < 0.0063Unclearε² = 0.129medium
Living areaKruskal–WallisH = 5.4630.1410p < 0.0063Unclearε² = 0.111medium
Days on marketKruskal–WallisH = 7.8630.0490p < 0.0063Unclearε² = 0.160large
Discount from original listKruskal–WallisH = 5.1230.1635p < 0.0063Unclearε² = 0.104medium
Price cut before saleChi-squareχ² = 3.4130.3328p < 0.0063UnclearCramér’s V = 0.261small
Seller paid closing costs or repairsChi-squareχ² = 3.0630.3819p < 0.0063UnclearCramér’s V = 0.248small
Has a viewChi-squareχ² = 5.3130.1504p < 0.0063UnclearCramér’s V = 0.326medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 205.00—0.2694p < 0.0063Unclearrank-biserial r = 0.199small
Net price per SFMann–Whitney UU = 196.00—0.1932p < 0.0063Unclearrank-biserial r = 0.234small
Living areaMann–Whitney UU = 258.00—0.9738p < 0.0063Unclearrank-biserial r = 0.008negligible
Year builtMann–Whitney UU = 333.50—0.0914p < 0.0063Unclearrank-biserial r = 0.303medium
Days on marketMann–Whitney UU = 344.50—0.0541p < 0.0063Unclearrank-biserial r = 0.346medium
Discount from original listMann–Whitney UU = 311.00—0.2333p < 0.0063Unclearrank-biserial r = 0.215small
Price cut before saleChi-squareχ² = 4.5510.0328p < 0.0063UnclearCramér’s V = 0.308medium
Seller paid closing costs or repairsChi-squareχ² = 2.2310.1352p < 0.0063UnclearCramér’s V = 0.216small

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); nothing else. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

  1. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Erlbaum.
  2. Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press.
  3. Dunn, O. J. (1961). Multiple comparisons among means. JASA, 56(293), 52–64.
  4. Kerby, D. S. (2014). The simple difference formula: an approach to teaching nonparametric correlation. Comprehensive Psychology, 3, 11.IT.3.1.
  5. Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. JASA, 47(260), 583–621.
  6. Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18(1), 50–60.
  7. Pearson, K. (1900). On the criterion that a given system of deviations… Philosophical Magazine, 50(302), 157–175.
  8. Tomczak, M., & Tomczak, E. (2014). The need to report effect size estimates revisited. Trends in Sport Sciences, 21(1), 19–25.

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 50 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 29, 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.