ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Northwest Hills

Austin, TX 78731 · 78759
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 7:27 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
52
single-family resale homes
Median net sale price
$1,248,750
average $1,372,015
Median net price per SF
$483
average $476
Median days on market
29 days
average 52 days
1. SummaryResale homes · 52 sales · October 26, 2025 – October 25, 2026

This study looks at the 52 resale homes sold in Northwest Hills in the 365 days to October 25, 2026. A full year is used because only 34 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 sold52 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 · 13 sales$1.08M–$1.25M · 13 sales$1.25M–$1.59M · 13 salesOver $1.59M · 13 sales
3. Quartiles by net sale priceResale homes · 52 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:28:01.934396 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 13 13 13 13 52 sales Sales per group Under $1.08M: 13 sales (25%) $1.08M–$1.25M: 13 sales (25%) $1.25M–$1.59M: 13 sales (25%) Over $1.59M: 13 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 $1.08M$1.08M–$1.25M$1.25M–$1.59MOver $1.59M
Higher-priced homes Over $1.59M
  • 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–$1.59MOver $1.59MReal difference?
Net price per SF$353 per SFLowest$446 per SF$491 per SF$615 per SFHighest✓ large
Living area2,497 SFSmallest2,654 SF2,972 SF3,414 SFLargest✓ large
Year built1968196919691971unclear
Days on market65 days10 days19 days30 daysunclear
Discount from original list14.7%1.5%4.8%4.8%unclear
Price cut before sale69%15%23%46%unclear
Seller paid closing costs or repairs38%46%38%23%unclear
Has a view38%38%15%31%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 $1.59M sell for about $262 per SF (74%) more than homes under $1.08M

2026-10-26T07:28:01.964104 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.08M 13 sales $1.08M– $1.25M 13 sales $1.25M– $1.59M 13 sales Over $1.59M 13 sales $0 $200 $400 $600 $353 $446 $491 $615 Net price per SF, average

The average is $615 per SF for homes over $1.59M and $353 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 $1.59M are about 920 SF (37%) larger than homes under $1.08M

2026-10-26T07:28:01.987437 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.08M 13 sales $1.08M– $1.25M 13 sales $1.25M– $1.59M 13 sales Over $1.59M 13 sales 0 2,000 4,000 2,497 2,654 2,972 3,414 Living area (SF), average

The average is 3,414 SF for homes over $1.59M and 2,497 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

2026-10-26T07:28:02.011978 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.08M 13 sales $1.08M– $1.25M 13 sales $1.25M– $1.59M 13 sales Over $1.59M 13 sales 1965 1970 1975 1980 1968 1969 1969 1971 Year built: median (dot) and middle half (bar)

The median is 1971 for homes over $1.59M and 1968 for homes under $1.08M. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:28:02.035310 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.08M 13 sales $1.08M– $1.25M 13 sales $1.25M– $1.59M 13 sales Over $1.59M 13 sales 0 20 40 60 65 10 19 30 Days on market, median

The median is 30 days for homes over $1.59M and 65 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

2026-10-26T07:28:02.057232 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.08M 13 sales $1.08M– $1.25M 13 sales $1.25M– $1.59M 13 sales Over $1.59M 13 sales 0.0% 5.0% 10.0% 15.0% 14.7% 1.5% 4.8% 4.8% Discount from original list, average

The average is 4.8% for homes over $1.59M and 14.7% 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

2026-10-26T07:28:02.089135 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% 69 38 38 15 46 38 23 38 15 46 23 31 Under $1.08M $1.08M–$1.25M $1.25M–$1.59M Over $1.59M

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

  • 46% of homes over $1.59M had a price cut before sale, against 69% of homes under $1.08M. Defined in 8.1.7.
  • 23% of homes over $1.59M had the seller pay closing costs or repairs, against 38% of homes under $1.08M. Defined in 8.1.8.
  • 31% of homes over $1.59M have a view, against 38% 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 $1.08M13 sales$1.08M–$1.25M13 sales$1.25M–$1.59M13 salesOver $1.59M13 salesAll52 salesReal difference?
Net sale price average$868,572$1,151,827$1,408,062$2,059,600$1,372,015by design
Net price per SF average$353$446$491$615$476✓ large
Living area average2,4972,6542,9723,4142,884✓ large
Year built median19681969196919711969unclear

3.10 The numbers: selling

Under $1.08M13 sales$1.08M–$1.25M13 sales$1.25M–$1.59M13 salesOver $1.59M13 salesAll52 salesReal difference?
Days on market median6510193029unclear
Discount from original list average14.7%1.5%4.8%4.8%6.5%unclear
Price cut before sale69%15%23%46%38%unclear
Seller paid closing costs or repairs38%46%38%23%37%unclear
Has a view38%38%15%31%31%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 · 52 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:28:02.110213 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 13 13 13 13 52 sales Sales per group Under 2,405 SF: 13 sales (25%) 2,405–2,702 SF: 13 sales (25%) 2,728–3,131 SF: 13 sales (25%) Over 3,131 SF: 13 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 2,405 SF2,405–2,702 SF2,728–3,131 SFOver 3,131 SF
Larger homes Over 3,131 SF
  • Sell for much more.
Smaller homes Under 2,405 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 2,405 SF2,405–2,702 SF2,728–3,131 SFOver 3,131 SFReal difference?
Net sale price$1.19M$1.08MLowest$1.40M$1.82MHighest✓ large
Net price per SF$532 per SF$418 per SF$475 per SF$479 per SFunclear
Year built1969196819691970unclear
Days on market31 days19 days19 days43 daysunclear
Discount from original list4.7%8.3%8.9%3.9%unclear
Price cut before sale15%38%38%62%unclear
Seller paid closing costs or repairs23%46%46%31%unclear
Has a view38%23%23%38%unclear

4.3 Homes over 3,131 SF sell for about $632K (53%) more than homes under 2,405 SF

2026-10-26T07:28:02.131285 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,405 SF 13 sales 2,405– 2,702 SF 13 sales 2,728– 3,131 SF 13 sales Over 3,131 SF 13 sales $0K $1.00M $2.00M $1.19M $1.08M $1.40M $1.82M Net sale price, average

The average is $1.82M for homes over 3,131 SF and $1.19M for homes under 2,405 SF. It does not move in a straight line; homes over 3,131 SF are highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-26T07:28:02.153970 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,405 SF 13 sales 2,405– 2,702 SF 13 sales 2,728– 3,131 SF 13 sales Over 3,131 SF 13 sales $0 $200 $400 $600 $532 $418 $475 $479 Net price per SF, average

The average is $479 per SF for homes over 3,131 SF and $532 per SF for homes under 2,405 SF. It does not move in a straight line; homes under 2,405 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:28:02.178241 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,405 SF 13 sales 2,405– 2,702 SF 13 sales 2,728– 3,131 SF 13 sales Over 3,131 SF 13 sales 1968 1972 1976 1980 1969 1968 1969 1970 Year built: median (dot) and middle half (bar)

The median is 1970 for homes over 3,131 SF and 1969 for homes under 2,405 SF. It does not move in a straight line; homes over 3,131 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:28:02.201895 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,405 SF 13 sales 2,405– 2,702 SF 13 sales 2,728– 3,131 SF 13 sales Over 3,131 SF 13 sales 0 20 40 31 19 19 43 Days on market, median

The median is 43 days for homes over 3,131 SF and 31 days for homes under 2,405 SF. It does not move in a straight line; homes over 3,131 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:28:02.224197 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,405 SF 13 sales 2,405– 2,702 SF 13 sales 2,728– 3,131 SF 13 sales Over 3,131 SF 13 sales 0.0% 5.0% 10.0% 4.7% 8.3% 8.9% 3.9% Discount from original list, average

The average is 3.9% for homes over 3,131 SF and 4.7% for homes under 2,405 SF. It does not move in a straight line; homes 2,728–3,131 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:28:02.251450 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% 15 23 38 38 46 23 38 46 23 62 31 38 Under 2,405 SF 2,405–2,702 SF 2,728–3,131 SF Over 3,131 SF

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

  • 62% of homes over 3,131 SF had a price cut before sale, against 15% of homes under 2,405 SF. Defined in 8.1.7.
  • 31% of homes over 3,131 SF had the seller pay closing costs or repairs, against 23% of homes under 2,405 SF. Defined in 8.1.8.
  • 38% of homes over 3,131 SF have a view, against 38% of homes under 2,405 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 2,405 SF13 sales2,405–2,702 SF13 sales2,728–3,131 SF13 salesOver 3,131 SF13 salesAll52 salesReal difference?
Net sale price average$1,189,904$1,079,315$1,396,837$1,822,005$1,372,015✓ large
Net price per SF average$532$418$475$479$476unclear
Living area average2,2272,5872,9413,7812,884by design
Year built median19691968196919701969unclear

4.10 The numbers: selling

Under 2,405 SF13 sales2,405–2,702 SF13 sales2,728–3,131 SF13 salesOver 3,131 SF13 salesAll52 salesReal difference?
Days on market median3119194329unclear
Discount from original list average4.7%8.3%8.9%3.9%6.5%unclear
Price cut before sale15%38%38%62%38%unclear
Seller paid closing costs or repairs23%46%46%31%37%unclear
Has a view38%23%23%38%31%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 · 52 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:28:02.272733 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 13 14 14 52 sales Sales per group Before 1966: 11 sales (21%) 1966–1968: 13 sales (25%) 1969–1972: 14 sales (27%) After 1972: 14 sales (27%)
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 19661966–19681969–1972After 1972Real difference?
Net sale price$1.43M$1.07M$1.33M$1.65Munclear
Net price per SF$477 per SF$414 per SF$481 per SF$528 per SFunclear
Living area3,086 SF2,631 SF2,744 SF3,100 SFunclear
Days on market28 days35 days11 days51 daysunclear
Discount from original list9.0%6.6%5.0%5.8%unclear
Price cut before sale45%38%29%43%unclear
Seller paid closing costs or repairs45%54%29%21%unclear
Has a view27%23%14%57%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:28:02.293729 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1966 11 sales 1966– 1968 13 sales 1969– 1972 14 sales After 1972 14 sales $0K $500K $1.00M $1.50M $1.43M $1.07M $1.33M $1.65M Net sale price, average

The average is $1.65M for homes built after 1972 and $1.43M for homes built before 1966. It does not move in a straight line; homes built after 1972 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:28:02.317310 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1966 11 sales 1966– 1968 13 sales 1969– 1972 14 sales After 1972 14 sales $0 $200 $400 $600 $477 $414 $481 $528 Net price per SF, average

The average is $528 per SF for homes built after 1972 and $477 per SF for homes built before 1966. It does not move in a straight line; homes built after 1972 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:28:02.339414 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1966 11 sales 1966– 1968 13 sales 1969– 1972 14 sales After 1972 14 sales 0 1,000 2,000 3,000 3,086 2,631 2,744 3,100 Living area (SF), average

The average is 3,100 SF for homes built after 1972 and 3,086 SF for homes built before 1966. It does not move in a straight line; homes built after 1972 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:28:02.361554 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1966 11 sales 1966– 1968 13 sales 1969– 1972 14 sales After 1972 14 sales 0 20 40 60 28 35 11 51 Days on market, median

The median is 51 days for homes built after 1972 and 28 days for homes built before 1966. It does not move in a straight line; homes built after 1972 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:28:02.384745 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1966 11 sales 1966– 1968 13 sales 1969– 1972 14 sales After 1972 14 sales 0.0% 5.0% 10.0% 9.0% 6.6% 5.0% 5.8% Discount from original list, average

The average is 5.8% for homes built after 1972 and 9.0% 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

2026-10-26T07:28:02.410177 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 45 45 27 38 54 23 29 29 14 43 21 57 Before 1966 1966–1968 1969–1972 After 1972

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

  • 43% of homes built after 1972 had a price cut before sale, against 45% of homes built before 1966. Defined in 8.1.7.
  • 21% of homes built after 1972 had the seller pay closing costs or repairs, against 45% of homes built before 1966. Defined in 8.1.8.
  • 57% of homes built after 1972 have a view, against 27% 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 196611 sales1966–196813 sales1969–197214 salesAfter 197214 salesAll52 salesReal difference?
Net sale price average$1,428,217$1,067,923$1,330,132$1,652,111$1,372,015unclear
Net price per SF average$477$414$481$528$476unclear
Living area average3,0862,6312,7443,1002,884unclear
Year built median19631967197119801969by design

5.10 The numbers: selling

Before 196611 sales1966–196813 sales1969–197214 salesAfter 197214 salesAll52 salesReal difference?
Days on market median2835115129unclear
Discount from original list average9.0%6.6%5.0%5.8%6.5%unclear
Price cut before sale45%38%29%43%38%unclear
Seller paid closing costs or repairs45%54%29%21%37%unclear
Has a view27%23%14%57%31%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 · 52 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:28:02.429458 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 16 34 50 sales Sales per group View: 16 sales (32%) No view: 34 sales (68%)
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$1.38Munclear
Net price per SF$447 per SF$487 per SFunclear
Living area2,896 SF2,826 SFunclear
Year built19731968unclear
Days on market64 days19 daysunclear
Discount from original list8.4%5.3%unclear
Price cut before sale56%26%unclear
Seller paid closing costs or repairs50%29%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:28:02.446361 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 34 sales $0K $500K $1.00M $1.50M $1.27M $1.38M Net sale price, average

The average is $1.27M for homes with a view and $1.38M for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-10-26T07:28:02.465463 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 34 sales $0 $200 $400 $447 $487 Net price per SF, average

The average is $447 per SF for homes with a view and $487 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-10-26T07:28:02.483579 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 34 sales 0 1,000 2,000 3,000 2,896 2,826 Living area (SF), average

The average is 2,896 SF for homes with a view and 2,826 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:28:02.533491 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 34 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

2026-10-26T07:28:02.552351 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 34 sales 0 20 40 60 64 19 Days on market, median

The median is 64 days for homes with a view and 19 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-10-26T07:28:02.572715 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 34 sales 0.0% 2.5% 5.0% 7.5% 10.0% 8.4% 5.3% Discount from original list, average

The average is 8.4% for homes with a view and 5.3% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:28:02.592709 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 56 50 26 29 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 26% 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 29% 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 view34 salesAll50 salesReal difference?
Net sale price average$1,271,491$1,377,528$1,343,596unclear
Net price per SF average$447$487$474unclear
Living area average2,8962,8262,849unclear
Year built median197319681969unclear

6.11 The numbers: selling

View16 salesNo view34 salesAll50 salesReal difference?
Days on market median641926unclear
Discount from original list average8.4%5.3%6.3%unclear
Price cut before sale56%26%36%unclear
Seller paid closing costs or repairs50%29%36%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 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
52 resale sales. Average $1,372,015; median $1,248,750; standard deviation $499,268; middle half (25th–75th percentile) $1,061,875–$1,595,000; lowest $755,000, highest $3,225,000. 19 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
52 resale sales. Average $476; median $483; standard deviation $128; middle half (25th–75th percentile) $368–$536; 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
52 resale sales. Average 2,884; median 2,715; standard deviation 648; middle half (25th–75th percentile) 2,404–3,164; 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
52 resale sales. Average 1972; 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
52 resale sales. Average 52; median 29; standard deviation 69; middle half (25th–75th percentile) 6–69; 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
52 resale sales. Average 6.5%; median 3.6%; standard deviation 10.9%; middle half (25th–75th percentile) 0.7%–10.9%; lowest −25.0%, highest 37.1%. 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
20 of 52 resale sales (38.5%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
19 of 52 resale sales (36.5%).

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, 34 without, 2 unclassified. Most common View entries: None 24, 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 26, 2026: 52 closed Northwest Hills records over the prior year, in ZIP 78731, 78759. 17 subdivision spellings kept, the most common: Northwest Hills Mesa Oaks Ph (17); 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); Northwest Hills Ranch Sec 01 (2); Townhomes Northwest Hills (2); Northwest Hills Cat Mountain S (2); Northwest Hills Lakeview 02 (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 34 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
52 single-family sales in the window: 52 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
52 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: $755,000–$1,000,000 (13 sales); $1.08M–$1.25M: $1,082,500–$1,245,000 (13 sales); $1.25M–$1.59M: $1,252,500–$1,590,000 (13 sales); Over $1.59M: $1,610,000–$3,225,000 (13 sales)
Quartiles by living area: Under 2,405 SF: 1,786–2,403 SF (13 sales); 2,405–2,702 SF: 2,405–2,702 SF (13 sales); 2,728–3,131 SF: 2,728–3,131 SF (13 sales); Over 3,131 SF: 3,263–4,934 SF (13 sales)
Quartiles by year built: Before 1966: 1959–1965 (11 sales); 1966–1968: 1966–1968 (13 sales); 1969–1972: 1969–1972 (14 sales); After 1972: 1974–2024 (14 sales)
View and no view: View: MLS lists a view (16 sales); No view: None or Neighborhood (34 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 $1,372,015, 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 = 28.083< 0.0001p < 0.0063Yesε² = 0.551large
Living areaKruskal–WallisH = 14.0030.0029p < 0.0063Yesε² = 0.275large
Year builtKruskal–WallisH = 1.4730.6889p < 0.0063Unclearε² = 0.029small
Days on marketKruskal–WallisH = 2.9430.4014p < 0.0063Unclearε² = 0.058small
Discount from original listKruskal–WallisH = 8.2730.0407p < 0.0063Unclearε² = 0.162large
Price cut before saleChi-squareχ² = 9.7530.0208p < 0.0063UnclearCramér’s V = 0.433medium
Seller paid closing costs or repairsChi-squareχ² = 1.5830.6649p < 0.0063UnclearCramér’s V = 0.174small
Has a viewChi-squareχ² = 2.1730.5385p < 0.0063UnclearCramér’s V = 0.204small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 16.0630.0011p < 0.0063Yesε² = 0.315large
Net price per SFKruskal–WallisH = 5.2230.1563p < 0.0063Unclearε² = 0.102medium
Year builtKruskal–WallisH = 1.8630.6011p < 0.0063Unclearε² = 0.037small
Days on marketKruskal–WallisH = 1.3930.7077p < 0.0063Unclearε² = 0.027small
Discount from original listKruskal–WallisH = 2.0730.5587p < 0.0063Unclearε² = 0.041small
Price cut before saleChi-squareχ² = 5.8530.1191p < 0.0063UnclearCramér’s V = 0.335medium
Seller paid closing costs or repairsChi-squareχ² = 2.2430.5243p < 0.0063UnclearCramér’s V = 0.208small
Has a viewChi-squareχ² = 1.4430.6952p < 0.0063UnclearCramér’s V = 0.167small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 9.8430.0200p < 0.0063Unclearε² = 0.193large
Net price per SFKruskal–WallisH = 5.6530.1297p < 0.0063Unclearε² = 0.111medium
Living areaKruskal–WallisH = 5.3430.1486p < 0.0063Unclearε² = 0.105medium
Days on marketKruskal–WallisH = 4.7630.1902p < 0.0063Unclearε² = 0.093medium
Discount from original listKruskal–WallisH = 1.6630.6459p < 0.0063Unclearε² = 0.033small
Price cut before saleChi-squareχ² = 0.9230.8206p < 0.0063UnclearCramér’s V = 0.133small
Seller paid closing costs or repairsChi-squareχ² = 3.8230.2818p < 0.0063UnclearCramér’s V = 0.271small
Has a viewChi-squareχ² = 6.7830.0792p < 0.0063UnclearCramér’s V = 0.361medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 227.00—0.3547p < 0.0063Unclearrank-biserial r = 0.165small
Net price per SFMann–Whitney UU = 216.00—0.2484p < 0.0063Unclearrank-biserial r = 0.206small
Living areaMann–Whitney UU = 276.00—0.9420p < 0.0063Unclearrank-biserial r = 0.015negligible
Year builtMann–Whitney UU = 355.50—0.0835p < 0.0063Unclearrank-biserial r = 0.307medium
Days on marketMann–Whitney UU = 363.50—0.0582p < 0.0063Unclearrank-biserial r = 0.336medium
Discount from original listMann–Whitney UU = 322.00—0.3032p < 0.0063Unclearrank-biserial r = 0.184small
Price cut before saleChi-squareχ² = 4.1910.0407p < 0.0063UnclearCramér’s V = 0.289small
Seller paid closing costs or repairsChi-squareχ² = 2.0010.1571p < 0.0063UnclearCramér’s V = 0.200small

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 52 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.