ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Lake Pointe

Austin, TX 78738
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 7:45 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
36
single-family resale homes
Median net sale price
$1,015,500
average $1,211,153
Median net price per SF
$352
average $349
Median days on market
30 days
average 59 days
1. SummaryResale homes · 36 sales · October 26, 2025 – October 25, 2026

This study looks at the 36 resale homes sold in Lake Pointe in the 365 days to October 25, 2026. A full year is used because only 24 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 sold36 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 $850K · 9 sales$850K–$1.00M · 9 sales$1.03M–$1.43M · 9 salesOver $1.43M · 9 sales
3. Quartiles by net sale priceResale homes · 36 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:45:19.704841 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 9 9 9 36 sales Sales per group Under $850K: 9 sales (25%) $850K–$1.00M: 9 sales (25%) $1.03M–$1.43M: 9 sales (25%) Over $1.43M: 9 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 $850K$850K–$1.00M$1.03M–$1.43MOver $1.43M
Higher-priced homes Over $1.43M
  • Are much larger.
  • Are more likely to have a view.
  • Sell for more per square foot.
  • Tend to be newer.
Lower-priced homes Under $850K
  • Are much smaller.
  • Are less likely to have a view.
  • Sell for less per square foot.
  • Tend to be older.

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 $850K$850K–$1.00M$1.03M–$1.43MOver $1.43MReal difference?
Net price per SF$320 per SF$319 per SFLowest$331 per SF$425 per SFHighest✓ large
Living area2,240 SFSmallest2,979 SF3,838 SF4,539 SFLargest✓ large
Year built1999Oldest200020002006Newest✓ large
Days on market24 days11 days28 days66 daysunclear
Discount from original list3.1%4.4%6.8%7.4%unclear
Price cut before sale56%22%44%44%unclear
Seller paid closing costs or repairs67%22%44%56%unclear
Has a view11%Fewest33%78%89%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 $1.43M sell for about $105 per SF (33%) more than homes under $850K

2026-10-26T07:45:19.734894 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $850K 9 sales $850K– $1.00M 9 sales $1.03M– $1.43M 9 sales Over $1.43M 9 sales $0 $200 $400 $320 $319 $331 $425 Net price per SF, average

The average is $425 per SF for homes over $1.43M and $320 per SF for homes under $850K. It does not move in a straight line; homes over $1.43M are highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $1.43M are about 2,300 SF (103%) larger than homes under $850K

2026-10-26T07:45:19.758274 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $850K 9 sales $850K– $1.00M 9 sales $1.03M– $1.43M 9 sales Over $1.43M 9 sales 0 2,000 4,000 2,240 2,979 3,838 4,539 Living area (SF), average

The average is 4,539 SF for homes over $1.43M and 2,240 SF for homes under $850K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Homes over $1.43M are about 7 years newer than homes under $850K

2026-10-26T07:45:19.782551 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $850K 9 sales $850K– $1.00M 9 sales $1.03M– $1.43M 9 sales Over $1.43M 9 sales 1999 2002 2005 1999 2000 2000 2006 Year built: median (dot) and middle half (bar)

The median is 2006 for homes over $1.43M and 1999 for homes under $850K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

✓ Real difference · large

3.6 Days on market: no clear difference

2026-10-26T07:45:19.806427 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $850K 9 sales $850K– $1.00M 9 sales $1.03M– $1.43M 9 sales Over $1.43M 9 sales 0 20 40 60 24 11 28 66 Days on market, median

The median is 66 days for homes over $1.43M and 24 days for homes under $850K. It does not move in a straight line; homes over $1.43M are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:45:19.829897 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $850K 9 sales $850K– $1.00M 9 sales $1.03M– $1.43M 9 sales Over $1.43M 9 sales 0.0% 2.5% 5.0% 7.5% 3.1% 4.4% 6.8% 7.4% Discount from original list, average

The average is 7.4% for homes over $1.43M and 3.1% for homes under $850K. It rises 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

2026-10-26T07:45:19.861727 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% 56 67 11 22 22 33 44 44 78 44 56 89 Under $850K $850K–$1.00M $1.03M–$1.43M Over $1.43M

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

  • 44% of homes over $1.43M had a price cut before sale, against 56% of homes under $850K. Defined in 8.1.7.
  • 56% of homes over $1.43M had the seller pay closing costs or repairs, against 67% of homes under $850K. Defined in 8.1.8.
  • 89% of homes over $1.43M have a view, against 11% of homes under $850K. 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 $850K9 sales$850K–$1.00M9 sales$1.03M–$1.43M9 salesOver $1.43M9 salesAll36 salesReal difference?
Net sale price average$698,002$933,444$1,252,056$1,961,110$1,211,153by design
Net price per SF average$320$319$331$425$349✓ large
Living area average2,2402,9793,8384,5393,399✓ large
Year built median19992000200020062000✓ large

3.10 The numbers: selling

Under $850K9 sales$850K–$1.00M9 sales$1.03M–$1.43M9 salesOver $1.43M9 salesAll36 salesReal difference?
Days on market median2411286630unclear
Discount from original list average3.1%4.4%6.8%7.4%5.4%unclear
Price cut before sale56%22%44%44%42%unclear
Seller paid closing costs or repairs67%22%44%56%47%unclear
Has a view11%33%78%89%53%✓ 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 · 36 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:45:19.883533 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 9 9 9 36 sales Sales per group Under 2,645 SF: 9 sales (25%) 2,645–3,354 SF: 9 sales (25%) 3,389–3,914 SF: 9 sales (25%) Over 3,914 SF: 9 sales (25%)
Bottom line

4.1 Key differences

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

Under 2,645 SF2,645–3,354 SF3,389–3,914 SFOver 3,914 SF
Larger homes Over 3,914 SF
  • Sell for much more.
  • Tend to be newer.
Smaller homes Under 2,645 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 2,645 SF2,645–3,354 SF3,389–3,914 SFOver 3,914 SFReal difference?
Net sale price$746KLowest$917K$1.30M$1.88MHighest✓ large
Net price per SF$355 per SF$299 per SF$360 per SF$382 per SFunclear
Year built1998Oldest200020012004Newest✓ large
Days on market22 days30 days28 days92 daysunclear
Discount from original list2.3%3.2%8.0%8.2%unclear
Price cut before sale44%22%56%44%unclear
Seller paid closing costs or repairs44%67%22%56%unclear
Has a view11%44%89%67%unclear

4.3 Homes over 3,914 SF sell for about $1.13M (152%) more than homes under 2,645 SF

2026-10-26T07:45:19.904736 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,645 SF 9 sales 2,645– 3,354 SF 9 sales 3,389– 3,914 SF 9 sales Over 3,914 SF 9 sales $0K $1.00M $2.00M $746K $917K $1.30M $1.88M Net sale price, average

The average is $1.88M for homes over 3,914 SF and $746K for homes under 2,645 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

2026-10-26T07:45:19.928166 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,645 SF 9 sales 2,645– 3,354 SF 9 sales 3,389– 3,914 SF 9 sales Over 3,914 SF 9 sales $0 $200 $400 $355 $299 $360 $382 Net price per SF, average

The average is $382 per SF for homes over 3,914 SF and $355 per SF for homes under 2,645 SF. It does not move in a straight line; homes over 3,914 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Homes over 3,914 SF are about 6 years newer than homes under 2,645 SF

2026-10-26T07:45:19.953577 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,645 SF 9 sales 2,645– 3,354 SF 9 sales 3,389– 3,914 SF 9 sales Over 3,914 SF 9 sales 1998 2000 2002 2004 2006 1998 2000 2001 2004 Year built: median (dot) and middle half (bar)

The median is 2004 for homes over 3,914 SF and 1998 for homes under 2,645 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

✓ Real difference · large

4.6 Days on market: no clear difference

2026-10-26T07:45:19.978137 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,645 SF 9 sales 2,645– 3,354 SF 9 sales 3,389– 3,914 SF 9 sales Over 3,914 SF 9 sales 0 50 100 22 30 28 92 Days on market, median

The median is 92 days for homes over 3,914 SF and 22 days for homes under 2,645 SF. It does not move in a straight line; homes over 3,914 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:45:20.001468 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,645 SF 9 sales 2,645– 3,354 SF 9 sales 3,389– 3,914 SF 9 sales Over 3,914 SF 9 sales 0.0% 2.5% 5.0% 7.5% 2.3% 3.2% 8.0% 8.2% Discount from original list, average

The average is 8.2% for homes over 3,914 SF and 2.3% for homes under 2,645 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:45:20.029753 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% 44 44 11 22 67 44 56 22 89 44 56 67 Under 2,645 SF 2,645–3,354 SF 3,389–3,914 SF Over 3,914 SF

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

  • 44% of homes over 3,914 SF had a price cut before sale, against 44% of homes under 2,645 SF. Defined in 8.1.7.
  • 56% of homes over 3,914 SF had the seller pay closing costs or repairs, against 44% of homes under 2,645 SF. Defined in 8.1.8.
  • 67% of homes over 3,914 SF have a view, against 11% of homes under 2,645 SF. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

4.9 The numbers: price and size

Under 2,645 SF9 sales2,645–3,354 SF9 sales3,389–3,914 SF9 salesOver 3,914 SF9 salesAll36 salesReal difference?
Net sale price average$746,318$917,129$1,301,174$1,879,991$1,211,153✓ large
Net price per SF average$355$299$360$382$349unclear
Living area average2,0993,0643,6064,8253,399by design
Year built median19982000200120042000✓ large

4.10 The numbers: selling

Under 2,645 SF9 sales2,645–3,354 SF9 sales3,389–3,914 SF9 salesOver 3,914 SF9 salesAll36 salesReal difference?
Days on market median2230289230unclear
Discount from original list average2.3%3.2%8.0%8.2%5.4%unclear
Price cut before sale44%22%56%44%42%unclear
Seller paid closing costs or repairs44%67%22%56%47%unclear
Has a view11%44%89%67%53%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 · 36 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:45:20.050856 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 11 9 36 sales Sales per group Before 1999: 8 sales (22%) 1999: 8 sales (22%) 2000–2001: 11 sales (31%) After 2001: 9 sales (25%)
Bottom line

5.1 Key differences

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

Before 199919992000–2001After 2001
Newer homes After 2001
  • Are more likely to have a view.
  • Sell for much more.
  • Sell for more per square foot.
  • Are much larger.
Older homes Before 1999
  • Are less likely to have a view.
  • Sell for much less.
  • Sell for less per square foot.
  • Are much smaller.

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 199919992000–2001After 2001Real difference?
Net sale price$895KLowest$1.00M$1.06M$1.87MHighest✓ large
Net price per SF$344 per SF$335 per SF$311 per SFLowest$412 per SFHighest✓ large
Living area2,601 SFSmallest3,052 SF3,378 SF4,442 SFLargest✓ large
Days on market17 days26 days36 days57 daysunclear
Discount from original list2.5%3.1%6.8%8.4%unclear
Price cut before sale38%25%45%56%unclear
Seller paid closing costs or repairs50%75%27%44%unclear
Has a view50%12%Fewest45%100%Most✓ large

5.3 Homes built after 2001 sell for about $975K (109%) more than homes built before 1999

2026-10-26T07:45:20.072016 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 8 sales 1999 8 sales 2000– 2001 11 sales After 2001 9 sales $0K $1.00M $2.00M $895K $1.00M $1.06M $1.87M Net sale price, average

The average is $1.87M for homes built after 2001 and $895K for homes built before 1999. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

5.4 Homes built after 2001 sell for about $68 per SF (20%) more than homes built before 1999

2026-10-26T07:45:20.095345 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 8 sales 1999 8 sales 2000– 2001 11 sales After 2001 9 sales $0 $200 $400 $344 $335 $311 $412 Net price per SF, average

The average is $412 per SF for homes built after 2001 and $344 per SF for homes built before 1999. It does not move in a straight line; homes built after 2001 are highest. Defined in 8.1.2.

✓ Real difference · large

5.5 Homes built after 2001 are about 1,840 SF (71%) larger than homes built before 1999

2026-10-26T07:45:20.117711 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 8 sales 1999 8 sales 2000– 2001 11 sales After 2001 9 sales 0 2,000 4,000 2,601 3,052 3,378 4,442 Living area (SF), average

The average is 4,442 SF for homes built after 2001 and 2,601 SF for homes built before 1999. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

5.6 Days on market: no clear difference

2026-10-26T07:45:20.139666 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 8 sales 1999 8 sales 2000– 2001 11 sales After 2001 9 sales 0 20 40 60 17 26 36 57 Days on market, median

The median is 57 days for homes built after 2001 and 17 days for homes built before 1999. It rises 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

2026-10-26T07:45:20.163134 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1999 8 sales 1999 8 sales 2000– 2001 11 sales After 2001 9 sales 0.0% 5.0% 10.0% 2.5% 3.1% 6.8% 8.4% Discount from original list, average

The average is 8.4% for homes built after 2001 and 2.5% for homes built before 1999. It rises step by step from the lowest range to the highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:45:20.189556 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% 38 50 50 25 75 12 45 27 45 56 44 100 Before 1999 1999 2000–2001 After 2001

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

  • 56% of homes built after 2001 had a price cut before sale, against 38% of homes built before 1999. Defined in 8.1.7.
  • 44% of homes built after 2001 had the seller pay closing costs or repairs, against 50% of homes built before 1999. Defined in 8.1.8.
  • 100% of homes built after 2001 have a view, against 50% of homes built before 1999. 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

5.9 The numbers: price and size

Before 19998 sales19998 sales2000–200111 salesAfter 20019 salesAll36 salesReal difference?
Net sale price average$895,050$999,640$1,055,516$1,870,369$1,211,153✓ large
Net price per SF average$344$335$311$412$349✓ large
Living area average2,6013,0523,3784,4423,399✓ large
Year built median19971999200120062000by design

5.10 The numbers: selling

Before 19998 sales19998 sales2000–200111 salesAfter 20019 salesAll36 salesReal difference?
Days on market median1726365730unclear
Discount from original list average2.5%3.1%6.8%8.4%5.4%unclear
Price cut before sale38%25%45%56%42%unclear
Seller paid closing costs or repairs50%75%27%44%47%unclear
Has a view50%12%45%100%53%✓ 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 8.3.3.

6. View and no viewResale homes · 36 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. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T07:45:20.209308 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 19 16 35 sales Sales per group View: 19 sales (54%) No view: 16 sales (46%)
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.
  • Tend to be newer.
Homes without a view no view listed
  • Sell for much less.
  • Tend to be older.

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$1.47MHighest$925KLowest✓ large
Net price per SF$368 per SF$325 per SFunclear
Living area3,868 SF2,891 SFunclear
Year built2001Newest1999Oldest✓ large
Days on market57 days26 daysunclear
Discount from original list7.3%3.5%unclear
Price cut before sale47%38%unclear
Seller paid closing costs or repairs47%50%unclear

6.3 Homes with a view sell for about $543K (59%) more than homes without a view

2026-10-26T07:45:20.225967 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 16 sales $0K $500K $1.00M $1.50M $1.47M $925K Net sale price, average

The average is $1.47M for homes with a view and $925K for homes without a view. Defined in 8.1.1.

✓ Real difference · large

6.4 Net price per SF: no clear difference

2026-10-26T07:45:20.245204 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 16 sales $0 $100 $200 $300 $400 $368 $325 Net price per SF, average

The average is $368 per SF for homes with a view and $325 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-10-26T07:45:20.349662 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 16 sales 0 1,000 2,000 3,000 4,000 3,868 2,891 Living area (SF), average

The average is 3,868 SF for homes with a view and 2,891 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Homes with a view are about 2 years newer than homes without a view

2026-10-26T07:45:20.372399 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 16 sales 2000 2002 2004 2001 1999 Year built: median (dot) and middle half (bar)

The median is 2001 for homes with a view and 1999 for homes without a view. Defined in 8.1.4.

✓ Real difference · large

6.7 Days on market: no clear difference

2026-10-26T07:45:20.390881 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 16 sales 0 20 40 60 57 26 Days on market, median

The median is 57 days for homes with a view and 26 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-10-26T07:45:20.411122 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 16 sales 0.0% 2.0% 4.0% 6.0% 8.0% 7.3% 3.5% Discount from original list, average

The average is 7.3% for homes with a view and 3.5% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:45:20.431227 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 47 47 38 50 View No view

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

  • 47% of homes with a view had a price cut before sale, against 38% of homes without a view. Defined in 8.1.7.
  • 47% of homes with a view had the seller pay closing costs or repairs, against 50% 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

View19 salesNo view16 salesAll35 salesReal difference?
Net sale price average$1,467,736$924,970$1,219,615✓ large
Net price per SF average$368$325$349unclear
Living area average3,8682,8913,421unclear
Year built median200119992000✓ large

6.11 The numbers: selling

View19 salesNo view16 salesAll35 salesReal difference?
Days on market median572630unclear
Discount from original list average7.3%3.5%5.6%unclear
Price cut before sale47%38%43%unclear
Seller paid closing costs or repairs47%50%49%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 · 1 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: 1 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 Lake Pointe.
MeasureAverageMedian
Sales1
Net sale price$2,850,000$2,850,000
Net price per SF$592$592
Living area (SF)4,8174,817
Days on market9898
Discount from original list5.0%5.0%
Price cut before sale100% of sales
Seller paid closing costs or repairs0% of sales
Year built2026–2026

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
36 resale sales. Average $1,211,153; median $1,015,500; standard deviation $652,910; middle half (25th–75th percentile) $841,875–$1,432,918; lowest $588,500, highest $4,325,000. 17 sales had a seller payment; their median payment was $8,000.

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
36 resale sales. Average $349; median $352; standard deviation $62; middle half (25th–75th percentile) $299–$378; lowest $252, highest $493.

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
36 resale sales. Average 3,399; median 3,372; standard deviation 1,261; middle half (25th–75th percentile) 2,637–3,948; lowest 1,601, highest 8,778.

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
36 resale sales. Average 2001; median 2000; standard deviation 4; middle half (25th–75th percentile) 1999–2001; lowest 1996, 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
36 resale sales. Average 59; median 30; standard deviation 73; middle half (25th–75th percentile) 9–82; lowest 0, highest 333. 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
36 resale sales. Average 5.4%; median 4.4%; standard deviation 6.3%; middle half (25th–75th percentile) 1.2%–7.8%; lowest −4.0%, highest 20.6%. 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
15 of 36 resale sales (41.7%).

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
17 of 36 resale sales (47.2%).

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
19 sales with a view, 16 without, 1 unclassified. Most common View entries: Hill Country 15, None 12, Panoramic 12, Neighborhood 10, Park/Greenbelt 9, Trees/Woods 6, Lake 4, River 3.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “lake pointe” (case-insensitive). A record is kept when its subdivision name belongs to the Lake Pointe family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 38 closed Lake Pointe records over the prior year, in ZIP 78738. 13 subdivision spellings kept, the most common: Lake Pointe Sec 07 (10); Lake Pointe (6); Lake Pointe Ph 02 (5); Lake Pointe Ph 04-A (3); Lake Pointe Sec 09 (3); Lake Pointe Sec 05 (2); Lake Pointe Sec 03 Ph 01 (2); Lake Pointe Ph 01b (2); Lake Pointe Ph 01-E (1); Lake Pointe Sec 03 Ph 03 (1); Lake Pointe Sec 03 Ph 02 (1); Lake Pointe Ph 01B (1); and 1 more (1 records). Names found by the search but not part of Lake Pointe, left out: Lake Pointe Phs Ii (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 24 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
37 single-family sales in the window: 36 resale, 1 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
36 resale; 1 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
1 sale(s) with no original list 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 $850K”.
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 $850K: $588,500–$817,500 (9 sales); $850K–$1.00M: $850,000–$1,000,000 (9 sales); $1.03M–$1.43M: $1,031,000–$1,425,000 (9 sales); Over $1.43M: $1,456,671–$4,325,000 (9 sales)
Quartiles by living area: Under 2,645 SF: 1,601–2,614 SF (9 sales); 2,645–3,354 SF: 2,645–3,354 SF (9 sales); 3,389–3,914 SF: 3,389–3,914 SF (9 sales); Over 3,914 SF: 4,048–8,778 SF (9 sales)
Quartiles by year built: Before 1999: 1996–1998 (8 sales); 1999: 1999–1999 (8 sales); 2000–2001: 2000–2001 (11 sales); After 2001: 2002–2017 (9 sales)
View and no view: View: MLS lists a view (19 sales); No view: None or Neighborhood (16 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 $1,211,153, median $1,015,500. Days on market: average 59, median 30: 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
12 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 = 15.4830.0015p < 0.0063Yesε² = 0.442large
Living areaKruskal–WallisH = 26.303< 0.0001p < 0.0063Yesε² = 0.752large
Year builtKruskal–WallisH = 15.1430.0017p < 0.0063Yesε² = 0.433large
Days on marketKruskal–WallisH = 5.8330.1201p < 0.0063Unclearε² = 0.167large
Discount from original listKruskal–WallisH = 3.2730.3518p < 0.0063Unclearε² = 0.093medium
Price cut before saleChi-squareχ² = 2.1730.5376p < 0.0063UnclearCramér’s V = 0.246small
Seller paid closing costs or repairsChi-squareχ² = 3.9030.2724p < 0.0063UnclearCramér’s V = 0.329medium
Has a viewChi-squareχ² = 14.6030.0022p < 0.0063YesCramér’s V = 0.637large

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 26.923< 0.0001p < 0.0063Yesε² = 0.769large
Net price per SFKruskal–WallisH = 9.4530.0239p < 0.0063Unclearε² = 0.270large
Year builtKruskal–WallisH = 13.1030.0044p < 0.0063Yesε² = 0.374large
Days on marketKruskal–WallisH = 5.8130.1214p < 0.0063Unclearε² = 0.166large
Discount from original listKruskal–WallisH = 5.5830.1337p < 0.0063Unclearε² = 0.160large
Price cut before saleChi-squareχ² = 2.1730.5376p < 0.0063UnclearCramér’s V = 0.246small
Seller paid closing costs or repairsChi-squareχ² = 3.9030.2724p < 0.0063UnclearCramér’s V = 0.329medium
Has a viewChi-squareχ² = 11.9330.0076p < 0.0063UnclearCramér’s V = 0.576large

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 16.1230.0011p < 0.0063Yesε² = 0.460large
Net price per SFKruskal–WallisH = 13.5230.0036p < 0.0063Yesε² = 0.386large
Living areaKruskal–WallisH = 12.7030.0053p < 0.0063Yesε² = 0.363large
Days on marketKruskal–WallisH = 2.9930.3927p < 0.0063Unclearε² = 0.086medium
Discount from original listKruskal–WallisH = 4.1930.2420p < 0.0063Unclearε² = 0.120medium
Price cut before saleChi-squareχ² = 1.7530.6257p < 0.0063UnclearCramér’s V = 0.221small
Seller paid closing costs or repairsChi-squareχ² = 4.2930.2322p < 0.0063UnclearCramér’s V = 0.345medium
Has a viewChi-squareχ² = 13.5230.0036p < 0.0063YesCramér’s V = 0.613large

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 254.00—0.0008p < 0.0063Yesrank-biserial r = 0.671large
Net price per SFMann–Whitney UU = 212.00—0.0488p < 0.0063Unclearrank-biserial r = 0.395medium
Living areaMann–Whitney UU = 233.00—0.0077p < 0.0063Unclearrank-biserial r = 0.533large
Year builtMann–Whitney UU = 236.00—0.0052p < 0.0063Yesrank-biserial r = 0.553large
Days on marketMann–Whitney UU = 198.50—0.1276p < 0.0063Unclearrank-biserial r = 0.306medium
Discount from original listMann–Whitney UU = 196.00—0.1497p < 0.0063Unclearrank-biserial r = 0.289small
Price cut before saleChi-squareχ² = 0.3510.5567p < 0.0063UnclearCramér’s V = 0.099negligible
Seller paid closing costs or repairsChi-squareχ² = 0.0210.8767p < 0.0063UnclearCramér’s V = 0.026negligible

8.4 Data notes

Left out of the analysis: 1 new-construction sales (basic statistics only, section 7); 1 sale(s) with no original list 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 36 closed MLS resale sales; the 1 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.