ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Austin Lake Hills Sec 02

Austin, TX 78733
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 4:01 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
24
single-family resale homes
Median net sale price
$755,250
average $844,986
Median net price per SF
$417
average $406
Median days on market
14 days
average 61 days
1. SummaryResale homes · 24 sales · October 26, 2025 – October 25, 2026

This study looks at the 24 resale homes sold in Austin Lake Hills Sec 02 in the 365 days to October 25, 2026. A full year is used because only 7 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 sold24 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 $669K · 6 sales$669K–$738K · 6 sales$772K–$850K · 6 salesOver $850K · 6 sales
3. Quartiles by net sale priceResale homes · 24 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T04:02:07.956581 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 6 6 24 sales Sales per group Under $669K: 6 sales (25%) $669K–$738K: 6 sales (25%) $772K–$850K: 6 sales (25%) Over $850K: 6 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 $669K$669K–$738K$772K–$850KOver $850K
Higher-priced homes Over $850K
  • Are much larger.
Lower-priced homes Under $669K
  • 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 $669K$669K–$738K$772K–$850KOver $850KReal difference?
Net price per SF$406 per SF$440 per SF$355 per SF$423 per SFunclear
Living area1,483 SFSmallest1,627 SF2,360 SF3,170 SFLargest✓ large
Year built1983199419892011unclear
Days on market34 days8 days25 days3 daysunclear
Discount from original list4.7%3.2%5.8%5.0%unclear
Price cut before sale33%17%33%33%unclear
Seller paid closing costs or repairs17%50%17%67%unclear
Has a view33%50%50%50%unclear

How to read this section. Each heading gives the finding. The gold box says whether the gap is real (✓, with its size) or could be chance (–). The section ends with its numbers; the tests are in section 8.3.

3.3 Net price per SF: no clear difference

2026-10-26T04:02:07.987432 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $669K 6 sales $669K– $738K 6 sales $772K– $850K 6 sales Over $850K 6 sales $0 $200 $400 $406 $440 $355 $423 Net price per SF, average

The average is $423 per SF for homes over $850K and $406 per SF for homes under $669K. It does not move in a straight line; homes $669K–$738K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $850K are about 1,690 SF (114%) larger than homes under $669K

2026-10-26T04:02:08.011175 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $669K 6 sales $669K– $738K 6 sales $772K– $850K 6 sales Over $850K 6 sales 0 1,000 2,000 3,000 1,483 1,627 2,360 3,170 Living area (SF), average

The average is 3,170 SF for homes over $850K and 1,483 SF for homes under $669K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-26T04:02:08.037507 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $669K 6 sales $669K– $738K 6 sales $772K– $850K 6 sales Over $850K 6 sales 1965 1980 1995 2010 1983 1994 1989 2011 Year built: median (dot) and middle half (bar)

The median is 2011 for homes over $850K and 1983 for homes under $669K. It does not move in a straight line; homes over $850K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T04:02:08.061719 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $669K 6 sales $669K– $738K 6 sales $772K– $850K 6 sales Over $850K 6 sales 0 20 40 34 8 25 3 Days on market, median

The median is 3 days for homes over $850K and 34 days for homes under $669K. It does not move in a straight line; homes under $669K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T04:02:08.084386 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $669K 6 sales $669K– $738K 6 sales $772K– $850K 6 sales Over $850K 6 sales 0.0% 2.0% 4.0% 6.0% 4.7% 3.2% 5.8% 5.0% Discount from original list, average

The average is 5.0% for homes over $850K and 4.7% for homes under $669K. It does not move in a straight line; homes $772K–$850K are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T04:02:08.115529 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% 33 17 33 17 50 50 33 17 50 33 67 50 Under $669K $669K–$738K $772K–$850K Over $850K

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

  • 33% of homes over $850K had a price cut before sale, against 33% of homes under $669K. Defined in 8.1.7.
  • 67% of homes over $850K had the seller pay closing costs or repairs, against 17% of homes under $669K. Defined in 8.1.8.
  • 50% of homes over $850K have a view, against 33% of homes under $669K. 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 $669K6 sales$669K–$738K6 sales$772K–$850K6 salesOver $850K6 salesAll24 salesReal difference?
Net sale price average$580,183$707,385$797,498$1,294,877$844,986by design
Net price per SF average$406$440$355$423$406unclear
Living area average1,4831,6272,3603,1702,160✓ large
Year built median19831994198920111991unclear

3.10 The numbers: selling

Under $669K6 sales$669K–$738K6 sales$772K–$850K6 salesOver $850K6 salesAll24 salesReal difference?
Days on market median34825314unclear
Discount from original list average4.7%3.2%5.8%5.0%4.7%unclear
Price cut before sale33%17%33%33%29%unclear
Seller paid closing costs or repairs17%50%17%67%38%unclear
Has a view33%50%50%50%46%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 · 24 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T04:02:08.137203 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 6 6 24 sales Sales per group Under 1,508 SF: 6 sales (25%) 1,508–1,851 SF: 6 sales (25%) 1,949–2,404 SF: 6 sales (25%) Over 2,404 SF: 6 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 1,508 SF1,508–1,851 SF1,949–2,404 SFOver 2,404 SF
Larger homes Over 2,404 SF
  • Sell for much more.
  • Tend to be newer.
Smaller homes Under 1,508 SF
  • Sell for much less.
  • Tend to be older.

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 1,508 SF1,508–1,851 SF1,949–2,404 SFOver 2,404 SFReal difference?
Net sale price$633KLowest$662K$861K$1.22MHighest✓ large
Net price per SF$469 per SF$389 per SF$402 per SF$364 per SFunclear
Year built1972Oldest199219882014Newest✓ large
Days on market21 days14 days22 days28 daysunclear
Discount from original list3.9%2.9%6.9%5.0%unclear
Price cut before sale33%0%50%33%unclear
Seller paid closing costs or repairs33%33%17%67%unclear
Has a view33%33%67%50%unclear

4.3 Homes over 2,404 SF sell for about $591K (93%) more than homes under 1,508 SF

2026-10-26T04:02:08.159158 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,508 SF 6 sales 1,508– 1,851 SF 6 sales 1,949– 2,404 SF 6 sales Over 2,404 SF 6 sales $0K $500K $1.00M $633K $662K $861K $1.22M Net sale price, average

The average is $1.22M for homes over 2,404 SF and $633K for homes under 1,508 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-26T04:02:08.183317 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,508 SF 6 sales 1,508– 1,851 SF 6 sales 1,949– 2,404 SF 6 sales Over 2,404 SF 6 sales $0 $200 $400 $469 $389 $402 $364 Net price per SF, average

The average is $364 per SF for homes over 2,404 SF and $469 per SF for homes under 1,508 SF. It does not move in a straight line; homes under 1,508 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Homes over 2,404 SF are about 42 years newer than homes under 1,508 SF

2026-10-26T04:02:08.207671 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,508 SF 6 sales 1,508– 1,851 SF 6 sales 1,949– 2,404 SF 6 sales Over 2,404 SF 6 sales 1965 1980 1995 2010 1972 1992 1988 2014 Year built: median (dot) and middle half (bar)

The median is 2014 for homes over 2,404 SF and 1972 for homes under 1,508 SF. It does not move in a straight line; homes over 2,404 SF are highest. Defined in 8.1.4.

✓ Real difference · large

4.6 Days on market: no clear difference

2026-10-26T04:02:08.231418 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,508 SF 6 sales 1,508– 1,851 SF 6 sales 1,949– 2,404 SF 6 sales Over 2,404 SF 6 sales 0 10 20 30 21 14 22 28 Days on market, median

The median is 28 days for homes over 2,404 SF and 21 days for homes under 1,508 SF. It does not move in a straight line; homes over 2,404 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T04:02:08.254984 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,508 SF 6 sales 1,508– 1,851 SF 6 sales 1,949– 2,404 SF 6 sales Over 2,404 SF 6 sales 0.0% 2.5% 5.0% 7.5% 3.9% 2.9% 6.9% 5.0% Discount from original list, average

The average is 5.0% for homes over 2,404 SF and 3.9% for homes under 1,508 SF. It does not move in a straight line; homes 1,949–2,404 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T04:02:08.283454 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% 33 33 33 0 33 33 50 17 67 33 67 50 Under 1,508 SF 1,508–1,851 SF 1,949–2,404 SF Over 2,404 SF

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

  • 33% of homes over 2,404 SF had a price cut before sale, against 33% of homes under 1,508 SF. Defined in 8.1.7.
  • 67% of homes over 2,404 SF had the seller pay closing costs or repairs, against 33% of homes under 1,508 SF. Defined in 8.1.8.
  • 50% of homes over 2,404 SF have a view, against 33% of homes under 1,508 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 1,508 SF6 sales1,508–1,851 SF6 sales1,949–2,404 SF6 salesOver 2,404 SF6 salesAll24 salesReal difference?
Net sale price average$632,902$662,417$860,581$1,224,044$844,986✓ large
Net price per SF average$469$389$402$364$406unclear
Living area average1,3531,7182,1443,4262,160by design
Year built median19721992198820141991✓ large

4.10 The numbers: selling

Under 1,508 SF6 sales1,508–1,851 SF6 sales1,949–2,404 SF6 salesOver 2,404 SF6 salesAll24 salesReal difference?
Days on market median2114222814unclear
Discount from original list average3.9%2.9%6.9%5.0%4.7%unclear
Price cut before sale33%0%50%33%29%unclear
Seller paid closing costs or repairs33%33%17%67%38%unclear
Has a view33%33%67%50%46%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 · 24 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T04:02:08.304296 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 6 6 24 sales Sales per group Before 1985: 6 sales (25%) 1985–1990: 6 sales (25%) 1992–1996: 6 sales (25%) After 1996: 6 sales (25%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

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

5.2 At a glance

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

Before 19851985–19901992–1996After 1996Real difference?
Net sale price$743K$700K$774K$1.16Munclear
Net price per SF$481 per SF$358 per SF$405 per SF$380 per SFunclear
Living area1,522 SF1,975 SF2,071 SF3,072 SFunclear
Days on market10 days34 days7 days143 daysunclear
Discount from original list3.1%6.5%2.1%7.0%unclear
Price cut before sale17%50%0%50%unclear
Seller paid closing costs or repairs33%0%50%67%unclear
Has a view50%33%33%67%unclear

5.3 Net sale price: no clear difference

2026-10-26T04:02:08.325592 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 6 sales 1985– 1990 6 sales 1992– 1996 6 sales After 1996 6 sales $0K $500K $1.00M $743K $700K $774K $1.16M Net sale price, average

The average is $1.16M for homes built after 1996 and $743K for homes built before 1985. It does not move in a straight line; homes built after 1996 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T04:02:08.349060 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 6 sales 1985– 1990 6 sales 1992– 1996 6 sales After 1996 6 sales $0 $200 $400 $481 $358 $405 $380 Net price per SF, average

The average is $380 per SF for homes built after 1996 and $481 per SF for homes built before 1985. It does not move in a straight line; homes built before 1985 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T04:02:08.370427 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 6 sales 1985– 1990 6 sales 1992– 1996 6 sales After 1996 6 sales 0 1,000 2,000 3,000 1,522 1,975 2,071 3,072 Living area (SF), average

The average is 3,072 SF for homes built after 1996 and 1,522 SF for homes built before 1985. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T04:02:08.392365 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 6 sales 1985– 1990 6 sales 1992– 1996 6 sales After 1996 6 sales 0 50 100 150 10 34 7 143 Days on market, median

The median is 143 days for homes built after 1996 and 10 days for homes built before 1985. It does not move in a straight line; homes built after 1996 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T04:02:08.416214 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 6 sales 1985– 1990 6 sales 1992– 1996 6 sales After 1996 6 sales 0.0% 2.5% 5.0% 7.5% 3.1% 6.5% 2.1% 7.0% Discount from original list, average

The average is 7.0% for homes built after 1996 and 3.1% for homes built before 1985. It does not move in a straight line; homes built after 1996 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

2026-10-26T04:02:08.442154 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 33 50 50 0 33 0 50 33 50 67 67 Before 1985 1985–1990 1992–1996 After 1996

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

  • 50% of homes built after 1996 had a price cut before sale, against 17% of homes built before 1985. Defined in 8.1.7.
  • 67% of homes built after 1996 had the seller pay closing costs or repairs, against 33% of homes built before 1985. Defined in 8.1.8.
  • 67% of homes built after 1996 have a view, against 50% of homes built before 1985. 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 19856 sales1985–19906 sales1992–19966 salesAfter 19966 salesAll24 salesReal difference?
Net sale price average$742,517$699,998$774,469$1,162,960$844,986unclear
Net price per SF average$481$358$405$380$406unclear
Living area average1,5221,9752,0713,0722,160unclear
Year built median19661986199420141991by design

5.10 The numbers: selling

Before 19856 sales1985–19906 sales1992–19966 salesAfter 19966 salesAll24 salesReal difference?
Days on market median1034714314unclear
Discount from original list average3.1%6.5%2.1%7.0%4.7%unclear
Price cut before sale17%50%0%50%29%unclear
Seller paid closing costs or repairs33%0%50%67%38%unclear
Has a view50%33%33%67%46%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 · 24 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.

2026-10-26T04:02:08.462020 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 13 24 sales Sales per group View: 11 sales (46%) No view: 13 sales (54%)
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$935K$768Kunclear
Net price per SF$414 per SF$399 per SFunclear
Living area2,300 SF2,042 SFunclear
Year built19931988unclear
Days on market8 days17 daysunclear
Discount from original list3.6%5.6%unclear
Price cut before sale18%38%unclear
Seller paid closing costs or repairs45%31%unclear

6.3 Net sale price: no clear difference

2026-10-26T04:02:08.480041 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 13 sales $0K $250K $500K $750K $1.00M $935K $768K Net sale price, average

The average is $935K for homes with a view and $768K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-10-26T04:02:08.499677 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 13 sales $0 $100 $200 $300 $400 $414 $399 Net price per SF, average

The average is $414 per SF for homes with a view and $399 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-10-26T04:02:08.614100 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 13 sales 0 1,000 2,000 2,300 2,042 Living area (SF), average

The average is 2,300 SF for homes with a view and 2,042 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T04:02:08.637619 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 13 sales 1985 1990 1995 2000 2005 1993 1988 Year built: median (dot) and middle half (bar)

The median is 1993 for homes with a view and 1988 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T04:02:08.657863 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 13 sales 0 5 10 15 20 8 17 Days on market, median

The median is 8 days for homes with a view and 17 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-10-26T04:02:08.677374 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 13 sales 0.0% 2.0% 4.0% 6.0% 3.6% 5.6% Discount from original list, average

The average is 3.6% for homes with a view and 5.6% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T04:02:08.697278 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 18 45 38 31 View No view

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

  • 18% of homes with a view had a price cut before sale, against 38% of homes without a view. Defined in 8.1.7.
  • 45% of homes with a view had the seller pay closing costs or repairs, against 31% 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

View11 salesNo view13 salesAll24 salesReal difference?
Net sale price average$935,428$768,458$844,986unclear
Net price per SF average$414$399$406unclear
Living area average2,3002,0422,160unclear
Year built median199319881991unclear

6.11 The numbers: selling

View11 salesNo view13 salesAll24 salesReal difference?
Days on market median81714unclear
Discount from original list average3.6%5.6%4.7%unclear
Price cut before sale18%38%29%unclear
Seller paid closing costs or repairs45%31%38%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.4.

7. New constructionBasic statistics · 2 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: 2 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 Austin Lake Hills Sec 02.
MeasureAverageMedian
Sales2
Net sale price$1,465,750$1,465,750
Net price per SF$435$435
Living area (SF)3,2703,270
Days on market201201
Discount from original list11.5%11.5%
Price cut before sale50% of sales
Seller paid closing costs or repairs50% of sales
Year built2025–2026

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
24 resale sales. Average $844,986; median $755,250; standard deviation $313,300; middle half (25th–75th percentile) $664,250–$900,140; lowest $400,000, highest $1,817,500. 9 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
24 resale sales. Average $406; median $417; standard deviation $89; middle half (25th–75th percentile) $350–$461; lowest $223, highest $584.

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
24 resale sales. Average 2,160; median 1,900; standard deviation 847; middle half (25th–75th percentile) 1,494–2,454; lowest 1,130, highest 4,153.

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
24 resale sales. Average 1990; median 1991; standard deviation 19; middle half (25th–75th percentile) 1984–1998; lowest 1940, highest 2023.

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
24 resale sales. Average 61; median 14; standard deviation 95; middle half (25th–75th percentile) 7–50; lowest 3, highest 328. 0 sales went under contract on their listing date (0 days).

8.1.6 Discount from original list

In simple terms
How far below the first asking price the home sold, after seller payments. It measures how much negotiating room sellers gave up. A negative figure means the home sold above its first asking price.
Statistically
Discount % = (OriginalListPrice − Net) ÷ OriginalListPrice × 100, per sale; summarized by the mean.
The data
24 resale sales. Average 4.7%; median 4.2%; standard deviation 6.2%; middle half (25th–75th percentile) 0.0%–7.1%; lowest −2.2%, highest 24.7%. 5 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
7 of 24 resale sales (29.2%).

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
9 of 24 resale sales (37.5%).

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
11 sales with a view, 13 without, 0 unclassified. Most common View entries: None 10, Trees/Woods 7, Neighborhood 6, Hill Country 6, Creek/Stream 1, See Remarks 1, Canyon 1, Panoramic 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “austin lake hills”, “austin lake estates” (case-insensitive). A record is kept when its subdivision name belongs to the Austin Lake Hills Sec 02 family, the same rule comparable sales use (it includes Austin Lake Estates Sec 01, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 26 closed Austin Lake Hills Sec 02 records over the prior year, in ZIP 78733. 8 subdivision spellings kept: Austin Lake Hills Sec 02 (8); Austin Lake Estates Sec 01 (5); Austin Lake Estates Sec 02 (4); Austin Lake Hills Sec 03 (4); Austin Lake Hills Sec 01 (2); Austin Lake Estates Sec 03 (1); Austin Lake Hills (1); AUSTIN LAKE HILLS SEC 3 (1). Names found by the search but not part of Austin Lake Hills Sec 02, left out: Austin Lake Estates Resub (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 7 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
26 single-family sales in the window: 24 resale, 2 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
24 resale; 2 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 $669K”.
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 $669K: $400,000–$650,000 (6 sales); $669K–$738K: $669,000–$738,500 (6 sales); $772K–$850K: $772,000–$850,000 (6 sales); Over $850K: $1,050,558–$1,817,500 (6 sales)
Quartiles by living area: Under 1,508 SF: 1,130–1,450 SF (6 sales); 1,508–1,851 SF: 1,508–1,851 SF (6 sales); 1,949–2,404 SF: 1,949–2,404 SF (6 sales); Over 2,404 SF: 2,603–4,153 SF (6 sales)
Quartiles by year built: Before 1985: 1940–1983 (6 sales); 1985–1990: 1985–1990 (6 sales); 1992–1996: 1992–1996 (6 sales); After 1996: 2006–2023 (6 sales)
View and no view: View: MLS lists a view (11 sales); No view: None or Neighborhood (13 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 $844,986, median $755,250. Days on market: average 61, median 14: 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 = 4.0630.2551p < 0.0063Unclearε² = 0.177large
Living areaKruskal–WallisH = 16.9730.0007p < 0.0063Yesε² = 0.738large
Year builtKruskal–WallisH = 7.9530.0470p < 0.0063Unclearε² = 0.346large
Days on marketKruskal–WallisH = 3.9630.2660p < 0.0063Unclearε² = 0.172large
Discount from original listKruskal–WallisH = 2.0130.5703p < 0.0063Unclearε² = 0.087medium
Price cut before saleChi-squareχ² = 0.6130.8953p < 0.0063UnclearCramér’s V = 0.159small
Seller paid closing costs or repairsChi-squareχ² = 4.8030.1870p < 0.0063UnclearCramér’s V = 0.447medium
Has a viewChi-squareχ² = 0.5030.9181p < 0.0063UnclearCramér’s V = 0.145small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 18.5030.0003p < 0.0063Yesε² = 0.804large
Net price per SFKruskal–WallisH = 6.3030.0979p < 0.0063Unclearε² = 0.274large
Year builtKruskal–WallisH = 13.8530.0031p < 0.0063Yesε² = 0.602large
Days on marketKruskal–WallisH = 0.5130.9173p < 0.0063Unclearε² = 0.022small
Discount from original listKruskal–WallisH = 2.1630.5405p < 0.0063Unclearε² = 0.094medium
Price cut before saleChi-squareχ² = 3.8330.2802p < 0.0063UnclearCramér’s V = 0.400medium
Seller paid closing costs or repairsChi-squareχ² = 3.3830.3370p < 0.0063UnclearCramér’s V = 0.375medium
Has a viewChi-squareχ² = 1.8530.6049p < 0.0063UnclearCramér’s V = 0.277small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 8.2330.0414p < 0.0063Unclearε² = 0.358large
Net price per SFKruskal–WallisH = 7.2630.0641p < 0.0063Unclearε² = 0.316large
Living areaKruskal–WallisH = 12.0530.0072p < 0.0063Unclearε² = 0.524large
Days on marketKruskal–WallisH = 4.9030.1794p < 0.0063Unclearε² = 0.213large
Discount from original listKruskal–WallisH = 2.7730.4282p < 0.0063Unclearε² = 0.120medium
Price cut before saleChi-squareχ² = 5.4530.1419p < 0.0063UnclearCramér’s V = 0.476medium
Seller paid closing costs or repairsChi-squareχ² = 6.2230.1013p < 0.0063UnclearCramér’s V = 0.509large
Has a viewChi-squareχ² = 1.8530.6049p < 0.0063UnclearCramér’s V = 0.277small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 85.00—0.4513p < 0.0063Unclearrank-biserial r = 0.189small
Net price per SFMann–Whitney UU = 73.00—0.9538p < 0.0063Unclearrank-biserial r = 0.021negligible
Living areaMann–Whitney UU = 87.00—0.3848p < 0.0063Unclearrank-biserial r = 0.217small
Year builtMann–Whitney UU = 84.50—0.4686p < 0.0063Unclearrank-biserial r = 0.182small
Days on marketMann–Whitney UU = 56.50—0.3983p < 0.0063Unclearrank-biserial r = 0.210small
Discount from original listMann–Whitney UU = 62.00—0.6018p < 0.0063Unclearrank-biserial r = 0.133small
Price cut before saleChi-squareχ² = 1.1910.2761p < 0.0063UnclearCramér’s V = 0.222small
Seller paid closing costs or repairsChi-squareχ² = 0.5510.4590p < 0.0063UnclearCramér’s V = 0.151small

8.4 Data notes

Left out of the analysis: 2 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 24 closed MLS resale sales; the 2 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.