ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Highland Lake Estates

Lago Vista, TX 78645
Resale homes · closed Oct 31 – Oct 30, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 31, 2026 · 7:19 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
78
single-family resale homes
Median net sale price
$385,500
average $462,153
Median net price per SF
$206
average $217
Median days on market
52 days
average 110 days
1. SummaryResale homes · 78 sales · October 31, 2025 – October 30, 2026

This study looks at the 78 resale homes sold in Highland Lake Estates in the 365 days to October 30, 2026. A full year is used because only 44 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 sold78 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 $332K · 20 sales$332K–$381K · 19 sales$390K–$470K · 19 salesOver $470K · 20 sales
3. Quartiles by net sale priceResale homes · 78 sales · October 31, 2025 – October 30, 2026

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

2026-10-31T07:20:04.609196 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 20 19 19 20 78 sales Sales per group Under $332K: 20 sales (26%) $332K–$381K: 19 sales (24%) $390K–$470K: 19 sales (24%) Over $470K: 20 sales (26%)
Bottom line

3.1 Key differences

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

Under $332K$332K–$381K$390K–$470KOver $470K
Higher-priced homes Over $470K
  • Are more likely to have a view.
  • Are much larger.
  • Sell for more per square foot.
Lower-priced homes Under $332K
  • Are less likely to have a view.
  • 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 $332K$332K–$381K$390K–$470KOver $470KReal difference?
Net price per SF$180 per SFLowest$199 per SF$216 per SF$271 per SFHighest✓ large
Living area1,986 SF1,792 SFSmallest2,006 SF2,851 SFLargest✓ large
Year built2017202020142015unclear
Days on market59 days21 days78 days61 daysunclear
Discount from original list8.0%3.7%7.4%5.0%unclear
Price cut before sale55%21%47%35%unclear
Seller paid closing costs or repairs70%79%47%70%unclear
Has a view50%21%Fewest95%95%Most✓ large

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 $470K sell for about $90 per SF (50%) more than homes under $332K

2026-10-31T07:20:04.637604 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $332K 20 sales $332K– $381K 19 sales $390K– $470K 19 sales Over $470K 20 sales $0 $100 $200 $300 $180 $199 $216 $271 Net price per SF, average

The average is $271 per SF for homes over $470K and $180 per SF for homes under $332K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $470K are about 870 SF (44%) larger than homes under $332K

2026-10-31T07:20:04.660142 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $332K 20 sales $332K– $381K 19 sales $390K– $470K 19 sales Over $470K 20 sales 0 1,000 2,000 3,000 1,986 1,792 2,006 2,851 Living area (SF), average

The average is 2,851 SF for homes over $470K and 1,986 SF for homes under $332K. It does not move in a straight line; homes over $470K are highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-31T07:20:04.685340 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $332K 20 sales $332K– $381K 19 sales $390K– $470K 19 sales Over $470K 20 sales 2000 2005 2010 2015 2020 2017 2020 2014 2015 Year built: median (dot) and middle half (bar)

The median is 2015 for homes over $470K and 2017 for homes under $332K. It does not move in a straight line; homes $332K–$381K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-31T07:20:04.708346 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $332K 20 sales $332K– $381K 19 sales $390K– $470K 19 sales Over $470K 20 sales 0 25 50 75 59 21 78 61 Days on market, median

The median is 61 days for homes over $470K and 59 days for homes under $332K. It does not move in a straight line; homes $390K–$470K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-31T07:20:04.730554 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $332K 20 sales $332K– $381K 19 sales $390K– $470K 19 sales Over $470K 20 sales 0.0% 2.5% 5.0% 7.5% 8.0% 3.7% 7.4% 5.0% Discount from original list, average

The average is 5.0% for homes over $470K and 8.0% for homes under $332K. It does not move in a straight line; homes under $332K 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

2026-10-31T07:20:04.760642 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% 55 70 50 21 79 21 47 47 95 35 70 95 Under $332K $332K–$381K $390K–$470K Over $470K

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

  • 35% of homes over $470K had a price cut before sale, against 55% of homes under $332K. Defined in 8.1.7.
  • 70% of homes over $470K had the seller pay closing costs or repairs, against 70% of homes under $332K. Defined in 8.1.8.
  • 95% of homes over $470K have a view, against 50% of homes under $332K. 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: ✓ Real difference · large

3.9 The numbers: price and size

Under $332K20 sales$332K–$381K19 sales$390K–$470K19 salesOver $470K20 salesAll78 salesReal difference?
Net sale price average$288,824$354,434$428,255$770,017$462,153by design
Net price per SF average$180$199$216$271$217✓ large
Living area average1,9861,7922,0062,8512,165✓ large
Year built median20172020201420152017unclear

3.10 The numbers: selling

Under $332K20 sales$332K–$381K19 sales$390K–$470K19 salesOver $470K20 salesAll78 salesReal difference?
Days on market median5921786152unclear
Discount from original list average8.0%3.7%7.4%5.0%6.1%unclear
Price cut before sale55%21%47%35%40%unclear
Seller paid closing costs or repairs70%79%47%70%67%unclear
Has a view50%21%95%95%65%✓ large

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 · 78 sales · October 31, 2025 – October 30, 2026

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

2026-10-31T07:20:04.781161 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 20 19 19 20 78 sales Sales per group Under 1,706 SF: 20 sales (26%) 1,706–1,836 SF: 19 sales (24%) 1,843–2,274 SF: 19 sales (24%) Over 2,274 SF: 20 sales (26%)
Bottom line

4.1 Key differences

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

Under 1,706 SF1,706–1,836 SF1,843–2,274 SFOver 2,274 SF
Larger homes Over 2,274 SF
  • Sell for much more.
  • Are more likely to have a view.
  • Less often have the seller pay buyer costs or repairs.
Smaller homes Under 1,706 SF
  • Sell for much less.
  • Are less likely to have a view.
  • More often have the seller pay buyer costs or repairs.

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 1,706 SF1,706–1,836 SF1,843–2,274 SFOver 2,274 SFReal difference?
Net sale price$334KLowest$349K$434K$725KHighest✓ large
Net price per SF$217 per SF$194 per SF$215 per SF$239 per SFunclear
Year built2017201920182008unclear
Days on market13 days54 days58 days83 daysunclear
Discount from original list5.3%6.5%4.5%7.9%unclear
Price cut before sale35%47%32%45%unclear
Seller paid closing costs or repairs90%Most79%42%Fewest55%✓ medium
Has a view55%37%Fewest79%90%Most✓ medium

4.3 Homes over 2,274 SF sell for about $391K (117%) more than homes under 1,706 SF

2026-10-31T07:20:04.801946 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,706 SF 20 sales 1,706– 1,836 SF 19 sales 1,843– 2,274 SF 19 sales Over 2,274 SF 20 sales $0K $250K $500K $750K $334K $349K $434K $725K Net sale price, average

The average is $725K for homes over 2,274 SF and $334K for homes under 1,706 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

2026-10-31T07:20:04.824850 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,706 SF 20 sales 1,706– 1,836 SF 19 sales 1,843– 2,274 SF 19 sales Over 2,274 SF 20 sales $0 $100 $200 $217 $194 $215 $239 Net price per SF, average

The average is $239 per SF for homes over 2,274 SF and $217 per SF for homes under 1,706 SF. It does not move in a straight line; homes over 2,274 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-31T07:20:04.848256 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,706 SF 20 sales 1,706– 1,836 SF 19 sales 1,843– 2,274 SF 19 sales Over 2,274 SF 20 sales 1998 2004 2010 2016 2017 2019 2018 2008 Year built: median (dot) and middle half (bar)

The median is 2008 for homes over 2,274 SF and 2017 for homes under 1,706 SF. It does not move in a straight line; homes 1,706–1,836 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-31T07:20:04.871357 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,706 SF 20 sales 1,706– 1,836 SF 19 sales 1,843– 2,274 SF 19 sales Over 2,274 SF 20 sales 0 25 50 75 13 54 58 83 Days on market, median

The median is 83 days for homes over 2,274 SF and 13 days for homes under 1,706 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-31T07:20:04.893924 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,706 SF 20 sales 1,706– 1,836 SF 19 sales 1,843– 2,274 SF 19 sales Over 2,274 SF 20 sales 0.0% 2.5% 5.0% 7.5% 5.3% 6.5% 4.5% 7.9% Discount from original list, average

The average is 7.9% for homes over 2,274 SF and 5.3% for homes under 1,706 SF. It does not move in a straight line; homes over 2,274 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

2026-10-31T07:20:04.921204 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% 35 90 55 47 79 37 32 42 79 45 55 90 Under 1,706 SF 1,706–1,836 SF 1,843–2,274 SF Over 2,274 SF

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

  • 45% of homes over 2,274 SF had a price cut before sale, against 35% of homes under 1,706 SF. Defined in 8.1.7.
  • 55% of homes over 2,274 SF had the seller pay closing costs or repairs, against 90% of homes under 1,706 SF. Defined in 8.1.8.
  • 90% of homes over 2,274 SF have a view, against 55% of homes under 1,706 SF. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: ✓ Real difference · medium
Has a view: ✓ Real difference · medium

4.9 The numbers: price and size

Under 1,706 SF20 sales1,706–1,836 SF19 sales1,843–2,274 SF19 salesOver 2,274 SF20 salesAll78 salesReal difference?
Net sale price average$334,280$348,679$433,661$724,892$462,153✓ large
Net price per SF average$217$194$215$239$217unclear
Living area average1,5451,7962,0163,2782,165by design
Year built median20172019201820082017unclear

4.10 The numbers: selling

Under 1,706 SF20 sales1,706–1,836 SF19 sales1,843–2,274 SF19 salesOver 2,274 SF20 salesAll78 salesReal difference?
Days on market median1354588352unclear
Discount from original list average5.3%6.5%4.5%7.9%6.1%unclear
Price cut before sale35%47%32%45%40%unclear
Seller paid closing costs or repairs90%79%42%55%67%✓ medium
Has a view55%37%79%90%65%✓ medium

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 · 78 sales · October 31, 2025 – October 30, 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.

2026-10-31T07:20:04.941512 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 19 22 22 15 78 sales Sales per group Before 2001: 19 sales (24%) 2001–2017: 22 sales (28%) 2018–2020: 22 sales (28%) After 2020: 15 sales (19%)
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 20012001–20172018–2020After 2020Real difference?
Net sale price$499K$456K$477K$403Kunclear
Net price per SF$207 per SF$223 per SF$225 per SF$207 per SFunclear
Living area2,703 SF2,000 SF2,024 SF1,932 SFunclear
Days on market58 days55 days46 days25 daysunclear
Discount from original list5.7%8.8%5.7%3.0%unclear
Price cut before sale37%50%36%33%unclear
Seller paid closing costs or repairs58%73%68%67%unclear
Has a view74%73%59%53%unclear

5.3 Net sale price: no clear difference

2026-10-31T07:20:04.962355 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2001 19 sales 2001– 2017 22 sales 2018– 2020 22 sales After 2020 15 sales $0K $200K $400K $499K $456K $477K $403K Net sale price, average

The average is $403K for homes built after 2020 and $499K for homes built before 2001. It does not move in a straight line; homes built before 2001 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-31T07:20:04.985259 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2001 19 sales 2001– 2017 22 sales 2018– 2020 22 sales After 2020 15 sales $0 $100 $200 $207 $223 $225 $207 Net price per SF, average

The average is $207 per SF for homes built after 2020 and $207 per SF for homes built before 2001. It does not move in a straight line; homes built 2018–2020 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-31T07:20:05.006410 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2001 19 sales 2001– 2017 22 sales 2018– 2020 22 sales After 2020 15 sales 0 1,000 2,000 3,000 2,703 2,000 2,024 1,932 Living area (SF), average

The average is 1,932 SF for homes built after 2020 and 2,703 SF for homes built before 2001. It does not move in a straight line; homes built before 2001 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-31T07:20:05.028397 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2001 19 sales 2001– 2017 22 sales 2018– 2020 22 sales After 2020 15 sales 0 20 40 60 58 55 46 25 Days on market, median

The median is 25 days for homes built after 2020 and 58 days for homes built before 2001. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-31T07:20:05.050922 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2001 19 sales 2001– 2017 22 sales 2018– 2020 22 sales After 2020 15 sales 0.0% 5.0% 10.0% 5.7% 8.8% 5.7% 3.0% Discount from original list, average

The average is 3.0% for homes built after 2020 and 5.7% for homes built before 2001. It does not move in a straight line; homes built 2001–2017 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

2026-10-31T07:20:05.076460 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% 37 58 74 50 73 73 36 68 59 33 67 53 Before 2001 2001–2017 2018–2020 After 2020

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

  • 33% of homes built after 2020 had a price cut before sale, against 37% of homes built before 2001. Defined in 8.1.7.
  • 67% of homes built after 2020 had the seller pay closing costs or repairs, against 58% of homes built before 2001. Defined in 8.1.8.
  • 53% of homes built after 2020 have a view, against 74% of homes built before 2001. 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 200119 sales2001–201722 sales2018–202022 salesAfter 202015 salesAll78 salesReal difference?
Net sale price average$498,768$455,824$477,045$403,213$462,153unclear
Net price per SF average$207$223$225$207$217unclear
Living area average2,7032,0002,0241,9322,165unclear
Year built median19952014202020222017by design

5.10 The numbers: selling

Before 200119 sales2001–201722 sales2018–202022 salesAfter 202015 salesAll78 salesReal difference?
Days on market median5855462552unclear
Discount from original list average5.7%8.8%5.7%3.0%6.1%unclear
Price cut before sale37%50%36%33%40%unclear
Seller paid closing costs or repairs58%73%68%67%67%unclear
Has a view74%73%59%53%65%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 · 78 sales · October 31, 2025 – October 30, 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. 5 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-31T07:20:05.096508 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 51 22 73 sales Sales per group View: 51 sales (70%) No view: 22 sales (30%)
Bottom line

6.1 Key differences

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

ViewNo view
Homes with a view MLS lists a view
  • Sell for much more.
  • Sell for more per square foot.
Homes without a view no view listed
  • Sell for much less.
  • Sell for less per square foot.

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$533KHighest$325KLowest✓ large
Net price per SF$234 per SFHighest$181 per SFLowest✓ large
Living area2,228 SF2,123 SFunclear
Year built20162018unclear
Days on market54 days47 daysunclear
Discount from original list6.0%5.6%unclear
Price cut before sale39%41%unclear
Seller paid closing costs or repairs63%77%unclear

6.3 Homes with a view sell for about $208K (64%) more than homes without a view

2026-10-31T07:20:05.112359 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 51 sales No view 22 sales $0K $200K $400K $600K $533K $325K Net sale price, average

The average is $533K for homes with a view and $325K for homes without a view. Defined in 8.1.1.

✓ Real difference · large

6.4 Homes with a view sell for about $53 per SF (29%) more than homes without a view

2026-10-31T07:20:05.130302 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 51 sales No view 22 sales $0 $100 $200 $234 $181 Net price per SF, average

The average is $234 per SF for homes with a view and $181 per SF for homes without a view. Defined in 8.1.2.

✓ Real difference · large

6.5 Living area: no clear difference

2026-10-31T07:20:05.148772 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 51 sales No view 22 sales 0 1,000 2,000 2,228 2,123 Living area (SF), average

The average is 2,228 SF for homes with a view and 2,123 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-31T07:20:05.200358 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 51 sales No view 22 sales 2000 2005 2010 2015 2020 2016 2018 Year built: median (dot) and middle half (bar)

The median is 2016 for homes with a view and 2018 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-31T07:20:05.218441 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 51 sales No view 22 sales 0 20 40 60 54 47 Days on market, median

The median is 54 days for homes with a view and 47 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

2026-10-31T07:20:05.236540 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 51 sales No view 22 sales 0.0% 2.0% 4.0% 6.0% 6.0% 5.6% Discount from original list, average

The average is 6.0% 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

2026-10-31T07:20:05.255616 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 39 63 41 77 View No view

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

  • 39% of homes with a view had a price cut before sale, against 41% of homes without a view. Defined in 8.1.7.
  • 63% of homes with a view had the seller pay closing costs or repairs, against 77% 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

View51 salesNo view22 salesAll73 salesReal difference?
Net sale price average$532,978$324,838$470,251✓ large
Net price per SF average$234$181$218✓ large
Living area average2,2282,1232,196unclear
Year built median201620182017unclear

6.11 The numbers: selling

View51 salesNo view22 salesAll73 salesReal difference?
Days on market median544753unclear
Discount from original list average6.0%5.6%5.9%unclear
Price cut before sale39%41%40%unclear
Seller paid closing costs or repairs63%77%67%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 · 12 sales · October 31, 2025 – October 30, 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: 12 sales, no groups, no tests.

Note: these are only the new-construction sales reported in ABOR MLS. Builders often sell homes without listing them in the MLS, so these figures do not necessarily represent all new-construction sales in Highland Lake Estates.
MeasureAverageMedian
Sales12
Net sale price$457,625$392,350
Net price per SF$214$210
Living area (SF)2,1512,174
Days on market10882
Discount from original list9.8%8.0%
Price cut before sale67% of sales
Seller paid closing costs or repairs58% of sales
Year built2022–2026

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
78 resale sales. Average $462,153; median $385,500; standard deviation $272,804; middle half (25th–75th percentile) $330,500–$478,250; lowest $50,000, highest $2,030,000. 52 sales had a seller payment; their median payment was $5,000.

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
78 resale sales. Average $217; median $206; standard deviation $64; middle half (25th–75th percentile) $187–$228; lowest $5, highest $567.

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
78 resale sales. Average 2,165; median 1,840; standard deviation 1,041; middle half (25th–75th percentile) 1,702–2,288; lowest 1,200, highest 9,173.

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
78 resale sales. Average 2011; median 2017; standard deviation 12; middle half (25th–75th percentile) 2001–2020; lowest 1971, 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
78 resale sales. Average 110; median 52; standard deviation 143; middle half (25th–75th percentile) 15–145; lowest 0, highest 673. 2 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
78 resale sales. Average 6.1%; median 4.4%; standard deviation 7.1%; middle half (25th–75th percentile) 1.6%–8.3%; lowest −6.9%, highest 34.9%. 8 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
31 of 78 resale sales (39.7%).

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
52 of 78 resale sales (66.7%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
51 sales with a view, 22 without, 5 unclassified. Most common View entries: Hill Country 31, Trees/Woods 27, Neighborhood 21, Lake 18, None 12, Panoramic 10, Golf Course 8, See Remarks 5.

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 = Lago Vista, SubdivisionName contains any of “highland lake estates”, “highland lake estate” (case-insensitive). A record is kept when its subdivision name belongs to the Highland Lake Estates family, the same rule comparable sales use.
The data
Pulled October 31, 2026: 92 closed Highland Lake Estates records over the prior year, in ZIP 78645. 33 subdivision spellings kept, the most common: Highland Lake Estates Sec 31 (11); Highland Lake Estates Sec 33 (8); Highland Lake Estates Sec 34 (7); Highland Lake Estates (5); Highland Lake Estates Sec 15 (5); Highland Lake Estates Sec 09 (5); Highland Lake Estates Sec 28 (4); Highland Lake Estates Sec 12 A (4); Highland Lake Estates Sec 30 (4); Highland Lake Estates Sec 21 (4); Highland Lake Estates Sec 22 (3); Highland Lake Estates Sec 04 (3); and 21 more (29 records). Names found by the search but not part of Highland Lake Estates, left out: Oaks At Highland Lake Estatesphs 02 (1); Oaks At Highland Lake Estatesp (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 44 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 31, 2025 to October 30, 2026 inclusive.
The data
90 single-family sales in the window: 78 resale, 12 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
78 resale; 12 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
2 sale(s) with concessions above 10% of price

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 $332K”.
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 $332K: $50,000–$330,000 (20 sales); $332K–$381K: $332,000–$381,000 (19 sales); $390K–$470K: $390,000–$470,000 (19 sales); Over $470K: $481,000–$2,030,000 (20 sales)
Quartiles by living area: Under 1,706 SF: 1,200–1,700 SF (20 sales); 1,706–1,836 SF: 1,706–1,836 SF (19 sales); 1,843–2,274 SF: 1,843–2,274 SF (19 sales); Over 2,274 SF: 2,292–9,173 SF (20 sales)
Quartiles by year built: Before 2001: 1971–2000 (19 sales); 2001–2017: 2001–2017 (22 sales); 2018–2020: 2018–2020 (22 sales); After 2020: 2021–2024 (15 sales)
View and no view: View: MLS lists a view (51 sales); No view: None or Neighborhood (22 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 $462,153, median $385,500. Days on market: average 110, median 52: 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
8 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 25.933< 0.0001p < 0.0063Yesε² = 0.337large
Living areaKruskal–WallisH = 43.763< 0.0001p < 0.0063Yesε² = 0.568large
Year builtKruskal–WallisH = 6.9530.0735p < 0.0063Unclearε² = 0.090medium
Days on marketKruskal–WallisH = 7.1030.0686p < 0.0063Unclearε² = 0.092medium
Discount from original listKruskal–WallisH = 4.6230.2019p < 0.0063Unclearε² = 0.060small
Price cut before saleChi-squareχ² = 5.3630.1470p < 0.0063UnclearCramér’s V = 0.262small
Seller paid closing costs or repairsChi-squareχ² = 4.6730.1973p < 0.0063UnclearCramér’s V = 0.245small
Has a viewChi-squareχ² = 33.573< 0.0001p < 0.0063YesCramér’s V = 0.656large

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 45.603< 0.0001p < 0.0063Yesε² = 0.592large
Net price per SFKruskal–WallisH = 6.8530.0767p < 0.0063Unclearε² = 0.089medium
Year builtKruskal–WallisH = 4.9530.1755p < 0.0063Unclearε² = 0.064medium
Days on marketKruskal–WallisH = 9.0230.0290p < 0.0063Unclearε² = 0.117medium
Discount from original listKruskal–WallisH = 0.9530.8139p < 0.0063Unclearε² = 0.012small
Price cut before saleChi-squareχ² = 1.4130.7035p < 0.0063UnclearCramér’s V = 0.134small
Seller paid closing costs or repairsChi-squareχ² = 12.5730.0057p < 0.0063YesCramér’s V = 0.401medium
Has a viewChi-squareχ² = 14.6930.0021p < 0.0063YesCramér’s V = 0.434medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 0.9330.8189p < 0.0063Unclearε² = 0.012small
Net price per SFKruskal–WallisH = 0.7530.8604p < 0.0063Unclearε² = 0.010negligible
Living areaKruskal–WallisH = 1.8930.5963p < 0.0063Unclearε² = 0.024small
Days on marketKruskal–WallisH = 1.5330.6759p < 0.0063Unclearε² = 0.020small
Discount from original listKruskal–WallisH = 6.8930.0754p < 0.0063Unclearε² = 0.090medium
Price cut before saleChi-squareχ² = 1.4030.7066p < 0.0063UnclearCramér’s V = 0.134small
Seller paid closing costs or repairsChi-squareχ² = 1.0430.7905p < 0.0063UnclearCramér’s V = 0.116small
Has a viewChi-squareχ² = 2.4530.4844p < 0.0063UnclearCramér’s V = 0.177small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 931.00—< 0.0001p < 0.0063Yesrank-biserial r = 0.660large
Net price per SFMann–Whitney UU = 886.00—< 0.0001p < 0.0063Yesrank-biserial r = 0.579large
Living areaMann–Whitney UU = 759.50—0.0173p < 0.0063Unclearrank-biserial r = 0.354medium
Year builtMann–Whitney UU = 487.50—0.3788p < 0.0063Unclearrank-biserial r = 0.131small
Days on marketMann–Whitney UU = 611.50—0.5477p < 0.0063Unclearrank-biserial r = 0.090negligible
Discount from original listMann–Whitney UU = 556.00—0.9569p < 0.0063Unclearrank-biserial r = 0.009negligible
Price cut before saleChi-squareχ² = 0.0210.8921p < 0.0063UnclearCramér’s V = 0.016negligible
Seller paid closing costs or repairsChi-squareχ² = 1.4710.2254p < 0.0063UnclearCramér’s V = 0.142small

8.4 Data notes

Left out of the analysis: 12 new-construction sales (basic statistics only, section 7); 2 sale(s) with concessions above 10% of price. 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 78 closed MLS resale sales; the 12 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 31, 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.