ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Hills Lakeway

The Hills, TX 78738
Resale homes · closed Oct 30 – Oct 29, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 30, 2026 · 7:32 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
45
single-family resale homes
Median net sale price
$950,000
average $1,078,514
Median net price per SF
$280
average $305
Median days on market
33 days
average 78 days
1. SummaryResale homes · 45 sales · October 30, 2025 – October 29, 2026

This study looks at the 45 resale homes sold in Hills Lakeway in the 365 days to October 29, 2026. A full year is used because only 27 resale homes sold in the last 180 days. New construction is left out and shown on its own in section 7. The homes are compared four ways: by price, by living area, by year built and with or without a view. The first three are split into four equal groups (quartiles), each named by its range.

Each comparison has its own section (3–6) with everything about it in one place: the key differences, a table of every measure at a glance, the charts and the numbers.

2. Where the resale homes sold45 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 $861K · 11 sales$861K–$938K · 11 sales$950K–$1.20M · 12 salesOver $1.20M · 11 sales
3. Quartiles by net sale priceResale homes · 45 sales · October 30, 2025 – October 29, 2026

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

2026-10-30T07:32:51.618981 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 11 12 11 45 sales Sales per group Under $861K: 11 sales (24%) $861K–$938K: 11 sales (24%) $950K–$1.20M: 12 sales (27%) Over $1.20M: 11 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 $861K$861K–$938K$950K–$1.20MOver $1.20M
Higher-priced homes Over $1.20M
  • Are much larger.
  • Sell for more per square foot.
Lower-priced homes Under $861K
  • Are much smaller.
  • Sell for less per square foot.

3.2 At a glance

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

Under $861K$861K–$938K$950K–$1.20MOver $1.20MReal difference?
Net price per SF$255 per SFLowest$277 per SF$326 per SF$360 per SFHighest✓ large
Living area3,059 SFSmallest3,249 SF3,474 SF4,392 SFLargest✓ large
Year built1988200120001999unclear
Days on market45 days87 days38 days19 daysunclear
Discount from original list10.7%7.6%4.9%3.8%unclear
Price cut before sale64%36%42%18%unclear
Seller paid closing costs or repairs36%55%33%45%unclear
Has a view55%36%75%82%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 $1.20M sell for about $105 per SF (41%) more than homes under $861K

2026-10-30T07:32:51.647359 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $861K 11 sales $861K– $938K 11 sales $950K– $1.20M 12 sales Over $1.20M 11 sales $0 $200 $400 $255 $277 $326 $360 Net price per SF, average

The average is $360 per SF for homes over $1.20M and $255 per SF for homes under $861K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $1.20M are about 1,330 SF (44%) larger than homes under $861K

2026-10-30T07:32:51.670170 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $861K 11 sales $861K– $938K 11 sales $950K– $1.20M 12 sales Over $1.20M 11 sales 0 2,000 4,000 3,059 3,249 3,474 4,392 Living area (SF), average

The average is 4,392 SF for homes over $1.20M and 3,059 SF for homes under $861K. 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

2026-10-30T07:32:51.695138 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $861K 11 sales $861K– $938K 11 sales $950K– $1.20M 12 sales Over $1.20M 11 sales 1985 1990 1995 2000 2005 1988 2001 2000 1999 Year built: median (dot) and middle half (bar)

The median is 1999 for homes over $1.20M and 1988 for homes under $861K. It does not move in a straight line; homes $861K–$938K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-30T07:32:51.718723 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $861K 11 sales $861K– $938K 11 sales $950K– $1.20M 12 sales Over $1.20M 11 sales 0 50 100 45 87 38 19 Days on market, median

The median is 19 days for homes over $1.20M and 45 days for homes under $861K. It does not move in a straight line; homes $861K–$938K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-30T07:32:51.741196 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $861K 11 sales $861K– $938K 11 sales $950K– $1.20M 12 sales Over $1.20M 11 sales 0.0% 5.0% 10.0% 10.7% 7.6% 4.9% 3.8% Discount from original list, average

The average is 3.8% for homes over $1.20M and 10.7% for homes under $861K. It falls step by step from the lowest range to the 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

2026-10-30T07:32:51.771258 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 64 36 55 36 55 36 42 33 75 18 45 82 Under $861K $861K–$938K $950K–$1.20M Over $1.20M

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

  • 18% of homes over $1.20M had a price cut before sale, against 64% of homes under $861K. Defined in 8.1.7.
  • 45% of homes over $1.20M had the seller pay closing costs or repairs, against 36% of homes under $861K. Defined in 8.1.8.
  • 82% of homes over $1.20M have a view, against 55% of homes under $861K. 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 $861K11 sales$861K–$938K11 sales$950K–$1.20M12 salesOver $1.20M11 salesAll45 salesReal difference?
Net sale price average$772,195$888,132$1,118,338$1,531,769$1,078,514by design
Net price per SF average$255$277$326$360$305✓ large
Living area average3,0593,2493,4744,3923,542✓ large
Year built median19882001200019991999unclear

3.10 The numbers: selling

Under $861K11 sales$861K–$938K11 sales$950K–$1.20M12 salesOver $1.20M11 salesAll45 salesReal difference?
Days on market median4587381933unclear
Discount from original list average10.7%7.6%4.9%3.8%6.7%unclear
Price cut before sale64%36%42%18%40%unclear
Seller paid closing costs or repairs36%55%33%45%42%unclear
Has a view55%36%75%82%62%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 · 45 sales · October 30, 2025 – October 29, 2026

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

2026-10-30T07:32:51.792074 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 11 12 11 45 sales Sales per group Under 3,182 SF: 11 sales (24%) 3,182–3,418 SF: 11 sales (24%) 3,460–3,798 SF: 12 sales (27%) Over 3,798 SF: 11 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 3,182 SF3,182–3,418 SF3,460–3,798 SFOver 3,798 SF
Larger homes Over 3,798 SF
  • Sell for much more.
Smaller homes Under 3,182 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 3,182 SF3,182–3,418 SF3,460–3,798 SFOver 3,798 SFReal difference?
Net sale price$835KLowest$985K$1.05M$1.45MHighest✓ large
Net price per SF$306 per SF$299 per SF$290 per SF$326 per SFunclear
Year built1998200119991999unclear
Days on market30 days95 days66 days20 daysunclear
Discount from original list4.6%8.7%7.7%5.8%unclear
Price cut before sale36%45%42%36%unclear
Seller paid closing costs or repairs36%45%42%45%unclear
Has a view45%55%75%73%unclear

4.3 Homes over 3,798 SF sell for about $616K (74%) more than homes under 3,182 SF

2026-10-30T07:32:51.813551 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,182 SF 11 sales 3,182– 3,418 SF 11 sales 3,460– 3,798 SF 12 sales Over 3,798 SF 11 sales $0K $500K $1.00M $1.50M $835K $985K $1.05M $1.45M Net sale price, average

The average is $1.45M for homes over 3,798 SF and $835K for homes under 3,182 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-30T07:32:51.835897 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,182 SF 11 sales 3,182– 3,418 SF 11 sales 3,460– 3,798 SF 12 sales Over 3,798 SF 11 sales $0 $100 $200 $300 $306 $299 $290 $326 Net price per SF, average

The average is $326 per SF for homes over 3,798 SF and $306 per SF for homes under 3,182 SF. It does not move in a straight line; homes over 3,798 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-30T07:32:51.860175 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,182 SF 11 sales 3,182– 3,418 SF 11 sales 3,460– 3,798 SF 12 sales Over 3,798 SF 11 sales 1988 1992 1996 2000 1998 2001 1999 1999 Year built: median (dot) and middle half (bar)

The median is 1999 for homes over 3,798 SF and 1998 for homes under 3,182 SF. It does not move in a straight line; homes 3,182–3,418 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-30T07:32:51.883782 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,182 SF 11 sales 3,182– 3,418 SF 11 sales 3,460– 3,798 SF 12 sales Over 3,798 SF 11 sales 0 50 100 30 95 66 20 Days on market, median

The median is 20 days for homes over 3,798 SF and 30 days for homes under 3,182 SF. It does not move in a straight line; homes 3,182–3,418 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-30T07:32:51.906011 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,182 SF 11 sales 3,182– 3,418 SF 11 sales 3,460– 3,798 SF 12 sales Over 3,798 SF 11 sales 0.0% 5.0% 10.0% 4.6% 8.7% 7.7% 5.8% Discount from original list, average

The average is 5.8% for homes over 3,798 SF and 4.6% for homes under 3,182 SF. It does not move in a straight line; homes 3,182–3,418 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

2026-10-30T07:32:51.932361 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% 36 36 45 45 45 55 42 42 75 36 45 73 Under 3,182 SF 3,182–3,418 SF 3,460–3,798 SF Over 3,798 SF

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

  • 36% of homes over 3,798 SF had a price cut before sale, against 36% of homes under 3,182 SF. Defined in 8.1.7.
  • 45% of homes over 3,798 SF had the seller pay closing costs or repairs, against 36% of homes under 3,182 SF. Defined in 8.1.8.
  • 73% of homes over 3,798 SF have a view, against 45% of homes under 3,182 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 3,182 SF11 sales3,182–3,418 SF11 sales3,460–3,798 SF12 salesOver 3,798 SF11 salesAll45 salesReal difference?
Net sale price average$834,748$984,959$1,046,302$1,450,974$1,078,514✓ large
Net price per SF average$306$299$290$326$305unclear
Living area average2,7273,3033,6024,5293,542by design
Year built median19982001199919991999unclear

4.10 The numbers: selling

Under 3,182 SF11 sales3,182–3,418 SF11 sales3,460–3,798 SF12 salesOver 3,798 SF11 salesAll45 salesReal difference?
Days on market median3095662033unclear
Discount from original list average4.6%8.7%7.7%5.8%6.7%unclear
Price cut before sale36%45%42%36%40%unclear
Seller paid closing costs or repairs36%45%42%45%42%unclear
Has a view45%55%75%73%62%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 · 45 sales · October 30, 2025 – October 29, 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.

2026-10-30T07:32:51.953071 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 13 10 11 45 sales Sales per group Before 1993: 11 sales (24%) 1993–1999: 13 sales (29%) 2000–2001: 10 sales (22%) After 2001: 11 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 19931993–19992000–2001After 2001Real difference?
Net sale price$1.04M$1.20M$1.02M$1.03Munclear
Net price per SF$306 per SF$328 per SF$298 per SF$283 per SFunclear
Living area3,316 SF3,692 SF3,385 SF3,734 SFunclear
Days on market43 days20 days70 days32 daysunclear
Discount from original list10.3%3.8%7.7%5.7%unclear
Price cut before sale45%31%50%36%unclear
Seller paid closing costs or repairs45%46%40%36%unclear
Has a view55%62%70%64%unclear

5.3 Net sale price: no clear difference

2026-10-30T07:32:51.974147 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1993 11 sales 1993– 1999 13 sales 2000– 2001 10 sales After 2001 11 sales $0K $500K $1.00M $1.04M $1.20M $1.02M $1.03M Net sale price, average

The average is $1.03M for homes built after 2001 and $1.04M for homes built before 1993. It does not move in a straight line; homes built 1993–1999 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-30T07:32:51.996907 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1993 11 sales 1993– 1999 13 sales 2000– 2001 10 sales After 2001 11 sales $0 $100 $200 $300 $306 $328 $298 $283 Net price per SF, average

The average is $283 per SF for homes built after 2001 and $306 per SF for homes built before 1993. It does not move in a straight line; homes built 1993–1999 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-30T07:32:52.018922 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1993 11 sales 1993– 1999 13 sales 2000– 2001 10 sales After 2001 11 sales 0 2,000 4,000 3,316 3,692 3,385 3,734 Living area (SF), average

The average is 3,734 SF for homes built after 2001 and 3,316 SF for homes built before 1993. It does not move in a straight line; homes built after 2001 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-30T07:32:52.041793 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1993 11 sales 1993– 1999 13 sales 2000– 2001 10 sales After 2001 11 sales 0 25 50 75 43 20 70 32 Days on market, median

The median is 32 days for homes built after 2001 and 43 days for homes built before 1993. It does not move in a straight line; homes built 2000–2001 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-30T07:32:52.063978 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1993 11 sales 1993– 1999 13 sales 2000– 2001 10 sales After 2001 11 sales 0.0% 5.0% 10.0% 10.3% 3.8% 7.7% 5.7% Discount from original list, average

The average is 5.7% for homes built after 2001 and 10.3% for homes built before 1993. It does not move in a straight line; homes built before 1993 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

2026-10-30T07:32:52.089947 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 55 31 46 62 50 40 70 36 36 64 Before 1993 1993–1999 2000–2001 After 2001

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

  • 36% of homes built after 2001 had a price cut before sale, against 45% of homes built before 1993. Defined in 8.1.7.
  • 36% of homes built after 2001 had the seller pay closing costs or repairs, against 45% of homes built before 1993. Defined in 8.1.8.
  • 64% of homes built after 2001 have a view, against 55% of homes built before 1993. 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 199311 sales1993–199913 sales2000–200110 salesAfter 200111 salesAll45 salesReal difference?
Net sale price average$1,042,654$1,200,335$1,018,357$1,025,091$1,078,514unclear
Net price per SF average$306$328$298$283$305unclear
Living area average3,3163,6923,3853,7343,542unclear
Year built median19851999200120041999by design

5.10 The numbers: selling

Before 199311 sales1993–199913 sales2000–200110 salesAfter 200111 salesAll45 salesReal difference?
Days on market median4320703233unclear
Discount from original list average10.3%3.8%7.7%5.7%6.7%unclear
Price cut before sale45%31%50%36%40%unclear
Seller paid closing costs or repairs45%46%40%36%42%unclear
Has a view55%62%70%64%62%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 · 45 sales · October 30, 2025 – October 29, 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.

2026-10-30T07:32:52.108620 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 28 15 43 sales Sales per group View: 28 sales (65%) No view: 15 sales (35%)
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$1.17M$955Kunclear
Net price per SF$318 per SF$290 per SFunclear
Living area3,680 SF3,315 SFunclear
Year built20001999unclear
Days on market36 days33 daysunclear
Discount from original list6.8%5.2%unclear
Price cut before sale43%27%unclear
Seller paid closing costs or repairs46%40%unclear

6.3 Net sale price: no clear difference

2026-10-30T07:32:52.125002 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 15 sales $0K $500K $1.00M $1.17M $955K Net sale price, average

The average is $1.17M for homes with a view and $955K 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

2026-10-30T07:32:52.142393 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 15 sales $0 $100 $200 $300 $318 $290 Net price per SF, average

The average is $318 per SF for homes with a view and $290 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

2026-10-30T07:32:52.187393 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 15 sales 0 1,000 2,000 3,000 4,000 3,680 3,315 Living area (SF), average

The average is 3,680 SF for homes with a view and 3,315 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-30T07:32:52.207007 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 15 sales 1994 1996 1998 2000 2000 1999 Year built: median (dot) and middle half (bar)

The median is 2000 for homes with a view and 1999 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-30T07:32:52.225635 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 15 sales 0 10 20 30 40 36 33 Days on market, median

The median is 36 days for homes with a view and 33 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

2026-10-30T07:32:52.245454 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 15 sales 0.0% 2.0% 4.0% 6.0% 8.0% 6.8% 5.2% Discount from original list, average

The average is 6.8% for homes with a view and 5.2% 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

2026-10-30T07:32:52.264682 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 43 46 27 40 View No view

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

  • 43% of homes with a view had a price cut before sale, against 27% of homes without a view. Defined in 8.1.7.
  • 46% of homes with a view had the seller pay closing costs or repairs, against 40% 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

View28 salesNo view15 salesAll43 salesReal difference?
Net sale price average$1,168,099$954,557$1,093,607unclear
Net price per SF average$318$290$308unclear
Living area average3,6803,3153,553unclear
Year built median200019991999unclear

6.11 The numbers: selling

View28 salesNo view15 salesAll43 salesReal difference?
Days on market median363333unclear
Discount from original list average6.8%5.2%6.2%unclear
Price cut before sale43%27%37%unclear
Seller paid closing costs or repairs46%40%44%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 30, 2025 – October 29, 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 Hills Lakeway.

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
45 resale sales. Average $1,078,514; median $950,000; standard deviation $359,747; middle half (25th–75th percentile) $861,400–$1,200,000; lowest $600,000, highest $2,675,000. 19 sales had a seller payment; their median payment was $7,500.

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
45 resale sales. Average $305; median $280; standard deviation $74; middle half (25th–75th percentile) $262–$337; lowest $201, highest $616.

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
45 resale sales. Average 3,542; median 3,460; standard deviation 755; middle half (25th–75th percentile) 3,182–3,798; lowest 2,417, highest 6,460.

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
45 resale sales. Average 1998; median 1999; standard deviation 8; middle half (25th–75th percentile) 1993–2001; lowest 1982, highest 2017.

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
45 resale sales. Average 78; median 33; standard deviation 93; middle half (25th–75th percentile) 14–114; lowest 0, highest 411. 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
45 resale sales. Average 6.7%; median 4.1%; standard deviation 7.9%; middle half (25th–75th percentile) 0.8%–10.9%; lowest −5.7%, highest 30.0%. 4 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
18 of 45 resale sales (40.0%).

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
19 of 45 resale sales (42.2%).

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
28 sales with a view, 15 without, 2 unclassified. Most common View entries: None 12, Trees/Woods 12, Golf Course 11, Hill Country 7, Neighborhood 7, Pool 6, Park/Greenbelt 5, Panoramic 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 = The Hills, SubdivisionName contains any of “hills lakeway” (case-insensitive). A record is kept when its subdivision name belongs to the Hills Lakeway family, the same rule comparable sales use.
The data
Pulled October 30, 2026: 45 closed Hills Lakeway records over the prior year, in ZIP 78738. 9 subdivision spellings kept: Hills Lakeway Ph 08 (9); Hills Lakeway Ph 04 (8); Hills Lakeway Ph 01 (7); Hills Lakeway Ph 02 (7); Hills Lakeway Ph 09 (5); Hills Lakeway Ph 03 (4); Hills Lakeway Ph 08-A (2); Hills Lakeway Ph 06 (2); Hills Lakeway Ph 05 Amd (1). Names found by the search but not part of Hills Lakeway, left out: Hills Of Lakeway Ph 02 The Amd, Hills Lakeway (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 27 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 30, 2025 to October 29, 2026 inclusive.
The data
45 single-family sales in the window: 45 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
45 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 $861K”.
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 $861K: $600,000–$850,000 (11 sales); $861K–$938K: $861,400–$938,000 (11 sales); $950K–$1.20M: $950,000–$1,200,000 (12 sales); Over $1.20M: $1,202,916–$2,675,000 (11 sales)
Quartiles by living area: Under 3,182 SF: 2,417–2,920 SF (11 sales); 3,182–3,418 SF: 3,182–3,418 SF (11 sales); 3,460–3,798 SF: 3,460–3,798 SF (12 sales); Over 3,798 SF: 3,880–6,460 SF (11 sales)
Quartiles by year built: Before 1993: 1982–1992 (11 sales); 1993–1999: 1993–1999 (13 sales); 2000–2001: 2000–2001 (10 sales); After 2001: 2002–2017 (11 sales)
View and no view: View: MLS lists a view (28 sales); No view: None or Neighborhood (15 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 $1,078,514, median $950,000. Days on market: average 78, median 33: 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 = 17.7030.0005p < 0.0063Yesε² = 0.402large
Living areaKruskal–WallisH = 18.8530.0003p < 0.0063Yesε² = 0.428large
Year builtKruskal–WallisH = 4.2830.2324p < 0.0063Unclearε² = 0.097medium
Days on marketKruskal–WallisH = 4.9130.1784p < 0.0063Unclearε² = 0.112medium
Discount from original listKruskal–WallisH = 3.8330.2803p < 0.0063Unclearε² = 0.087medium
Price cut before saleChi-squareχ² = 4.8230.1857p < 0.0063UnclearCramér’s V = 0.327medium
Seller paid closing costs or repairsChi-squareχ² = 1.2830.7350p < 0.0063UnclearCramér’s V = 0.168small
Has a viewChi-squareχ² = 6.0430.1099p < 0.0063UnclearCramér’s V = 0.366medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 20.7430.0001p < 0.0063Yesε² = 0.471large
Net price per SFKruskal–WallisH = 1.3630.7138p < 0.0063Unclearε² = 0.031small
Year builtKruskal–WallisH = 2.0230.5682p < 0.0063Unclearε² = 0.046small
Days on marketKruskal–WallisH = 2.5130.4738p < 0.0063Unclearε² = 0.057small
Discount from original listKruskal–WallisH = 2.9730.3959p < 0.0063Unclearε² = 0.068medium
Price cut before saleChi-squareχ² = 0.2730.9653p < 0.0063UnclearCramér’s V = 0.078negligible
Seller paid closing costs or repairsChi-squareχ² = 0.2530.9691p < 0.0063UnclearCramér’s V = 0.075negligible
Has a viewChi-squareχ² = 2.9430.4007p < 0.0063UnclearCramér’s V = 0.256small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 6.0030.1117p < 0.0063Unclearε² = 0.136medium
Net price per SFKruskal–WallisH = 5.3830.1458p < 0.0063Unclearε² = 0.122medium
Living areaKruskal–WallisH = 1.7030.6358p < 0.0063Unclearε² = 0.039small
Days on marketKruskal–WallisH = 1.1630.7630p < 0.0063Unclearε² = 0.026small
Discount from original listKruskal–WallisH = 3.7830.2861p < 0.0063Unclearε² = 0.086medium
Price cut before saleChi-squareχ² = 1.0830.7831p < 0.0063UnclearCramér’s V = 0.155small
Seller paid closing costs or repairsChi-squareχ² = 0.3030.9592p < 0.0063UnclearCramér’s V = 0.082negligible
Has a viewChi-squareχ² = 0.5530.9089p < 0.0063UnclearCramér’s V = 0.110small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 277.00—0.0901p < 0.0063Unclearrank-biserial r = 0.319medium
Net price per SFMann–Whitney UU = 255.00—0.2568p < 0.0063Unclearrank-biserial r = 0.214small
Living areaMann–Whitney UU = 278.00—0.0854p < 0.0063Unclearrank-biserial r = 0.324medium
Year builtMann–Whitney UU = 206.50—0.9387p < 0.0063Unclearrank-biserial r = 0.017negligible
Days on marketMann–Whitney UU = 185.00—0.5323p < 0.0063Unclearrank-biserial r = 0.119small
Discount from original listMann–Whitney UU = 225.00—0.7117p < 0.0063Unclearrank-biserial r = 0.071negligible
Price cut before saleChi-squareχ² = 1.1010.2952p < 0.0063UnclearCramér’s V = 0.160small
Seller paid closing costs or repairsChi-squareχ² = 0.1610.6858p < 0.0063UnclearCramér’s V = 0.062negligible

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 45 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 30, 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.