ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Lakeway

Lakeway, TX 78734 · 78738
Resale homes · closed Nov 7 – Nov 6, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 7, 2026 · 7:23 AM CST
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
129
single-family resale homes
Median net sale price
$718,500
average $844,101
Median net price per SF
$288
average $299
Median days on market
48 days
average 86 days
1. SummaryResale homes · 129 sales · November 7, 2025 – November 6, 2026

This study looks at the 129 resale homes sold in Lakeway in the 365 days to November 6, 2026. A full year is used because only 73 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 sold129 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 $614K · 32 sales$614K–$706K · 32 sales$718K–$891K · 33 salesOver $891K · 32 sales
3. Quartiles by net sale priceResale homes · 129 sales · November 7, 2025 – November 6, 2026

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

2026-11-07T07:24:04.391513 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 32 32 33 32 129 sales Sales per group Under $614K: 32 sales (25%) $614K–$706K: 32 sales (25%) $718K–$891K: 33 sales (26%) Over $891K: 32 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 $614K$614K–$706K$718K–$891KOver $891K
Higher-priced homes Over $891K
  • Are much larger.
  • Sell for more per square foot.
Lower-priced homes Under $614K
  • 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 $614K$614K–$706K$718K–$891KOver $891KReal difference?
Net price per SF$261 per SFLowest$268 per SF$304 per SF$363 per SFHighest✓ large
Living area2,186 SFSmallest2,531 SF2,647 SF3,705 SFLargest✓ large
Year built1988199019921998unclear
Days on market40 days82 days35 days48 daysunclear
Discount from original list7.5%9.3%4.3%5.7%unclear
Price cut before sale44%69%39%31%unclear
Seller paid closing costs or repairs47%44%48%50%unclear
Has a view53%75%76%81%unclear

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

3.3 Homes over $891K sell for about $102 per SF (39%) more than homes under $614K

2026-11-07T07:24:04.425744 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $614K 32 sales $614K– $706K 32 sales $718K– $891K 33 sales Over $891K 32 sales $0 $200 $400 $261 $268 $304 $363 Net price per SF, average

The average is $363 per SF for homes over $891K and $261 per SF for homes under $614K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $891K are about 1,520 SF (70%) larger than homes under $614K

2026-11-07T07:24:04.450931 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $614K 32 sales $614K– $706K 32 sales $718K– $891K 33 sales Over $891K 32 sales 0 2,000 4,000 2,186 2,531 2,647 3,705 Living area (SF), average

The average is 3,705 SF for homes over $891K and 2,186 SF for homes under $614K. 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

2026-11-07T07:24:04.475943 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $614K 32 sales $614K– $706K 32 sales $718K– $891K 33 sales Over $891K 32 sales 1986 1992 1998 2004 1988 1990 1992 1998 Year built: median (dot) and middle half (bar)

The median is 1998 for homes over $891K and 1988 for homes under $614K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-07T07:24:04.502727 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $614K 32 sales $614K– $706K 32 sales $718K– $891K 33 sales Over $891K 32 sales 0 25 50 75 40 82 35 48 Days on market, median

The median is 48 days for homes over $891K and 40 days for homes under $614K. It does not move in a straight line; homes $614K–$706K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-07T07:24:04.527822 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $614K 32 sales $614K– $706K 32 sales $718K– $891K 33 sales Over $891K 32 sales 0.0% 5.0% 10.0% 7.5% 9.3% 4.3% 5.7% Discount from original list, average

The average is 5.7% for homes over $891K and 7.5% for homes under $614K. It does not move in a straight line; homes $614K–$706K 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

2026-11-07T07:24:04.560937 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 47 53 69 44 75 39 48 76 31 50 81 Under $614K $614K–$706K $718K–$891K Over $891K

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

  • 31% of homes over $891K had a price cut before sale, against 44% of homes under $614K. Defined in 8.1.7.
  • 50% of homes over $891K had the seller pay closing costs or repairs, against 47% of homes under $614K. Defined in 8.1.8.
  • 81% of homes over $891K have a view, against 53% of homes under $614K. 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 $614K32 sales$614K–$706K32 sales$718K–$891K33 salesOver $891K32 salesAll129 salesReal difference?
Net sale price average$562,384$660,373$791,522$1,363,770$844,101by design
Net price per SF average$261$268$304$363$299✓ large
Living area average2,1862,5312,6473,7052,766✓ large
Year built median19881990199219981992unclear

3.10 The numbers: selling

Under $614K32 sales$614K–$706K32 sales$718K–$891K33 salesOver $891K32 salesAll129 salesReal difference?
Days on market median4082354848unclear
Discount from original list average7.5%9.3%4.3%5.7%6.7%unclear
Price cut before sale44%69%39%31%46%unclear
Seller paid closing costs or repairs47%44%48%50%47%unclear
Has a view53%75%76%81%71%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 · 129 sales · November 7, 2025 – November 6, 2026

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

2026-11-07T07:24:04.584471 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 32 32 33 32 129 sales Sales per group Under 2,268 SF: 32 sales (25%) 2,268–2,575 SF: 32 sales (25%) 2,582–3,013 SF: 33 sales (26%) Over 3,013 SF: 32 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 2,268 SF2,268–2,575 SF2,582–3,013 SFOver 3,013 SF
Larger homes Over 3,013 SF
  • Sell for much more.
Smaller homes Under 2,268 SF
  • Sell for much less.

4.2 At a glance

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

Under 2,268 SF2,268–2,575 SF2,582–3,013 SFOver 3,013 SFReal difference?
Net sale price$639KLowest$690K$753K$1.30MHighest✓ large
Net price per SF$316 per SF$285 per SF$270 per SF$326 per SFunclear
Year built1985198819931995unclear
Days on market52 days40 days47 days64 daysunclear
Discount from original list5.8%6.6%7.0%7.2%unclear
Price cut before sale38%50%52%44%unclear
Seller paid closing costs or repairs44%47%52%47%unclear
Has a view56%72%76%81%unclear

4.3 Homes over 3,013 SF sell for about $659K (103%) more than homes under 2,268 SF

2026-11-07T07:24:04.614215 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,268 SF 32 sales 2,268– 2,575 SF 32 sales 2,582– 3,013 SF 33 sales Over 3,013 SF 32 sales $0K $500K $1.00M $1.50M $639K $690K $753K $1.30M Net sale price, average

The average is $1.30M for homes over 3,013 SF and $639K for homes under 2,268 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

2026-11-07T07:24:04.639481 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,268 SF 32 sales 2,268– 2,575 SF 32 sales 2,582– 3,013 SF 33 sales Over 3,013 SF 32 sales $0 $100 $200 $300 $316 $285 $270 $326 Net price per SF, average

The average is $326 per SF for homes over 3,013 SF and $316 per SF for homes under 2,268 SF. It does not move in a straight line; homes over 3,013 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-07T07:24:04.665413 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,268 SF 32 sales 2,268– 2,575 SF 32 sales 2,582– 3,013 SF 33 sales Over 3,013 SF 32 sales 1985 1990 1995 2000 1985 1988 1993 1995 Year built: median (dot) and middle half (bar)

The median is 1995 for homes over 3,013 SF and 1985 for homes under 2,268 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-07T07:24:04.694810 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,268 SF 32 sales 2,268– 2,575 SF 32 sales 2,582– 3,013 SF 33 sales Over 3,013 SF 32 sales 0 20 40 60 52 40 47 64 Days on market, median

The median is 64 days for homes over 3,013 SF and 52 days for homes under 2,268 SF. It does not move in a straight line; homes over 3,013 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-07T07:24:04.718097 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,268 SF 32 sales 2,268– 2,575 SF 32 sales 2,582– 3,013 SF 33 sales Over 3,013 SF 32 sales 0.0% 2.5% 5.0% 7.5% 5.8% 6.6% 7.0% 7.2% Discount from original list, average

The average is 7.2% for homes over 3,013 SF and 5.8% for homes under 2,268 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

2026-11-07T07:24:04.745598 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 44 56 50 47 72 52 52 76 44 47 81 Under 2,268 SF 2,268–2,575 SF 2,582–3,013 SF Over 3,013 SF

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

  • 44% of homes over 3,013 SF had a price cut before sale, against 38% of homes under 2,268 SF. Defined in 8.1.7.
  • 47% of homes over 3,013 SF had the seller pay closing costs or repairs, against 44% of homes under 2,268 SF. Defined in 8.1.8.
  • 81% of homes over 3,013 SF have a view, against 56% of homes under 2,268 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 2,268 SF32 sales2,268–2,575 SF32 sales2,582–3,013 SF33 salesOver 3,013 SF32 salesAll129 salesReal difference?
Net sale price average$638,864$689,718$753,172$1,297,492$844,101✓ large
Net price per SF average$316$285$270$326$299unclear
Living area average2,0182,4192,7923,8362,766by design
Year built median19851988199319951992unclear

4.10 The numbers: selling

Under 2,268 SF32 sales2,268–2,575 SF32 sales2,582–3,013 SF33 salesOver 3,013 SF32 salesAll129 salesReal difference?
Days on market median5240476448unclear
Discount from original list average5.8%6.6%7.0%7.2%6.7%unclear
Price cut before sale38%50%52%44%46%unclear
Seller paid closing costs or repairs44%47%52%47%47%unclear
Has a view56%72%76%81%71%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 · 129 sales · November 7, 2025 – November 6, 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.

2026-11-07T07:24:04.767727 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 31 32 35 31 129 sales Sales per group Before 1983: 31 sales (24%) 1983–1990: 32 sales (25%) 1992–1998: 35 sales (27%) After 1998: 31 sales (24%)
Bottom line

5.1 Key differences

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

Before 19831983–19901992–1998After 1998
Newer homes After 1998
  • Are much larger.
Older homes Before 1983
  • 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 19831983–19901992–1998After 1998Real difference?
Net sale price$817K$710K$744K$1.12Munclear
Net price per SF$314 per SF$289 per SF$274 per SF$323 per SFunclear
Living area2,606 SF2,475 SFSmallest2,719 SF3,280 SFLargest✓ large
Days on market48 days71 days27 days48 daysunclear
Discount from original list7.4%8.1%5.7%5.5%unclear
Price cut before sale48%50%46%39%unclear
Seller paid closing costs or repairs48%62%37%42%unclear
Has a view68%78%71%68%unclear

5.3 Net sale price: no clear difference

2026-11-07T07:24:04.790039 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1983 31 sales 1983– 1990 32 sales 1992– 1998 35 sales After 1998 31 sales $0K $500K $1.00M $817K $710K $744K $1.12M Net sale price, average

The average is $1.12M for homes built after 1998 and $817K for homes built before 1983. It does not move in a straight line; homes built after 1998 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-07T07:24:04.813261 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1983 31 sales 1983– 1990 32 sales 1992– 1998 35 sales After 1998 31 sales $0 $100 $200 $300 $314 $289 $274 $323 Net price per SF, average

The average is $323 per SF for homes built after 1998 and $314 per SF for homes built before 1983. It does not move in a straight line; homes built after 1998 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Homes built after 1998 are about 670 SF (26%) larger than homes built before 1983

2026-11-07T07:24:04.836350 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1983 31 sales 1983– 1990 32 sales 1992– 1998 35 sales After 1998 31 sales 0 1,000 2,000 3,000 2,606 2,475 2,719 3,280 Living area (SF), average

The average is 3,280 SF for homes built after 1998 and 2,606 SF for homes built before 1983. It does not move in a straight line; homes built after 1998 are highest. Defined in 8.1.3.

✓ Real difference · large

5.6 Days on market: no clear difference

2026-11-07T07:24:04.859007 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1983 31 sales 1983– 1990 32 sales 1992– 1998 35 sales After 1998 31 sales 0 25 50 75 48 71 27 48 Days on market, median

The median is 48 days for homes built after 1998 and 48 days for homes built before 1983. It does not move in a straight line; homes built 1983–1990 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-07T07:24:04.882911 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1983 31 sales 1983– 1990 32 sales 1992– 1998 35 sales After 1998 31 sales 0.0% 2.5% 5.0% 7.5% 7.4% 8.1% 5.7% 5.5% Discount from original list, average

The average is 5.5% for homes built after 1998 and 7.4% for homes built before 1983. It does not move in a straight line; homes built 1983–1990 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

2026-11-07T07:24:04.909712 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% 48 48 68 50 62 78 46 37 71 39 42 68 Before 1983 1983–1990 1992–1998 After 1998

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

  • 39% of homes built after 1998 had a price cut before sale, against 48% of homes built before 1983. Defined in 8.1.7.
  • 42% of homes built after 1998 had the seller pay closing costs or repairs, against 48% of homes built before 1983. Defined in 8.1.8.
  • 68% of homes built after 1998 have a view, against 68% of homes built before 1983. 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 198331 sales1983–199032 sales1992–199835 salesAfter 199831 salesAll129 salesReal difference?
Net sale price average$816,926$709,841$743,799$1,123,113$844,101unclear
Net price per SF average$314$289$274$323$299unclear
Living area average2,6062,4752,7193,2802,766✓ large
Year built median19761986199420041992by design

5.10 The numbers: selling

Before 198331 sales1983–199032 sales1992–199835 salesAfter 199831 salesAll129 salesReal difference?
Days on market median4871274848unclear
Discount from original list average7.4%8.1%5.7%5.5%6.7%unclear
Price cut before sale48%50%46%39%46%unclear
Seller paid closing costs or repairs48%62%37%42%47%unclear
Has a view68%78%71%68%71%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 · 129 sales · November 7, 2025 – November 6, 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. 4 sales whose MLS view entry is only “See Remarks” are left out.

2026-11-07T07:24:04.929302 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 92 33 125 sales Sales per group View: 92 sales (74%) No view: 33 sales (26%)
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 more.
Homes without a view no view listed
  • Sell for less.

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$895KHighest$679KLowest✓ medium
Net price per SF$308 per SF$278 per SFunclear
Living area2,838 SF2,466 SFunclear
Year built19911992unclear
Days on market54 days46 daysunclear
Discount from original list7.2%5.5%unclear
Price cut before sale47%42%unclear
Seller paid closing costs or repairs47%52%unclear

6.3 Homes with a view sell for about $216K (32%) more than homes without a view

2026-11-07T07:24:04.947120 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 92 sales No view 33 sales $0K $250K $500K $750K $1.00M $895K $679K Net sale price, average

The average is $895K for homes with a view and $679K for homes without a view. Defined in 8.1.1.

✓ Real difference · medium

6.4 Net price per SF: no clear difference

2026-11-07T07:24:04.965568 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 92 sales No view 33 sales $0 $100 $200 $300 $308 $278 Net price per SF, average

The average is $308 per SF for homes with a view and $278 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

2026-11-07T07:24:04.985028 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 92 sales No view 33 sales 0 1,000 2,000 3,000 2,838 2,466 Living area (SF), average

The average is 2,838 SF for homes with a view and 2,466 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-07T07:24:05.048036 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 92 sales No view 33 sales 1984 1988 1992 1996 1991 1992 Year built: median (dot) and middle half (bar)

The median is 1991 for homes with a view and 1992 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-07T07:24:05.065907 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 92 sales No view 33 sales 0 20 40 60 54 46 Days on market, median

The median is 54 days for homes with a view and 46 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

2026-11-07T07:24:05.085247 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 92 sales No view 33 sales 0.0% 2.0% 4.0% 6.0% 8.0% 7.2% 5.5% Discount from original list, average

The average is 7.2% for homes with a view and 5.5% 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

2026-11-07T07:24:05.104984 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 47 47 42 52 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 42% 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 52% 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

View92 salesNo view33 salesAll125 salesReal difference?
Net sale price average$895,134$679,447$838,193✓ medium
Net price per SF average$308$278$300unclear
Living area average2,8382,4662,740unclear
Year built median199119921992unclear

6.11 The numbers: selling

View92 salesNo view33 salesAll125 salesReal difference?
Days on market median544649unclear
Discount from original list average7.2%5.5%6.8%unclear
Price cut before sale47%42%46%unclear
Seller paid closing costs or repairs47%52%48%unclear

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

7. New constructionBasic statistics · 0 sales · November 7, 2025 – November 6, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 0 sales, no groups, no tests.

Note: these are only the new-construction sales reported in ABOR MLS. Builders often sell homes without listing them in the MLS, so these figures do not necessarily represent all new-construction sales in Lakeway.

No new-construction sales were reported in ABOR MLS in this window.

Same definitions as the rest of the study (section 8). New construction = NewConstructionYN true, or PropertyCondition “New Construction” or “Under Construction”.

8. AppendixMeasures, methods and tests

Each measure and method three ways: in plain words, as statistics, and with the data from this study.

8.1 Measures

8.1.1 Net sale price

In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
129 resale sales. Average $844,101; median $718,500; standard deviation $460,068; middle half (25th–75th percentile) $614,000–$891,250; lowest $417,500, highest $3,683,750. 61 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
129 resale sales. Average $299; median $288; standard deviation $84; middle half (25th–75th percentile) $257–$317; lowest $182, highest $840.

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
129 resale sales. Average 2,766; median 2,582; standard deviation 758; middle half (25th–75th percentile) 2,268–3,013; lowest 1,544, highest 5,894.

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
129 resale sales. Average 1991; median 1992; standard deviation 12; middle half (25th–75th percentile) 1983–1998; lowest 1968, 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
129 resale sales. Average 86; median 48; standard deviation 97; middle half (25th–75th percentile) 12–125; lowest 0, highest 445. 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
129 resale sales. Average 6.7%; median 5.5%; standard deviation 6.8%; middle half (25th–75th percentile) 1.8%–9.0%; lowest −5.4%, highest 30.4%. 6 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
59 of 129 resale sales (45.7%).

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
61 of 129 resale sales (47.3%).

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
92 sales with a view, 33 without, 4 unclassified. Most common View entries: Hill Country 41, Trees/Woods 37, Neighborhood 35, Golf Course 27, None 23, Lake 18, Panoramic 17, Water 10.

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
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-07 13:15 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Lakeway, SubdivisionName contains any of “lakeway” (case-insensitive). A record is kept when its subdivision name belongs to the Lakeway family, the same rule comparable sales use.
The data
Pulled November 7, 2026: 130 closed Lakeway records over the prior year, in ZIP 78734, 78738. 40 subdivision spellings kept, the most common: Lakeway (16); Lakeway Sec 24 (8); Lakeway Sec 26 (8); Lakeway Sec 28 (7); Lakeway Sec 16 (6); Lakeway Sec 22 (6); Lakeway Sec 24-B (6); Lakeway Sec 02 (6); Lakeway Sec Clusters 28 05 (5); Lakeway Sec Clusters 28 04 (5); Lakeway Sec 17 (5); Lakeway Sec 27 (5); and 28 more (47 records). Names found by the search but not part of Lakeway, left out: Boulevard At Lakeway (7); Lakeway World Tennis Condo (3); North Lakeway Village Sec 03 (2); Vistas At Lakeway Condo (2); Lakeway Condo Patio Home (2); Estates Lakeway Hills Sec 03 (2); Lakeway Highlands Ph 1 Sec 3 (1); Arbolago; Lakeway (1); Westside Landing; Rough Hollow; Lakeway (1); Pinnacle at Lakeway Condos (1); Lakeway Hlnds Ph 3 Sec 6B (1); Rough Hollow Lakeway (1); Landing/Lakeway Condos (1); Hills Lakeway Ph 04 (1); The Vistas of Lakeway (1); Lakeway Hlnds Ph 3 Sec 4 (1); Vistas at Lakeway (1); North Lakeway Village Sec 06 (1); LAKEWAY; Lohmans Crossing Estates Sec 1 (1); The Landing at Lakeway (1); Lohmans Crossing Estates Sec 07 of Lakeway (1); Coves At Lakeway (1); Cardinal Hills, Lakeway (1); Lakeway Highlands Ph 1 Sec 5 (1); The Preserve at Lakeway (1).

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 73 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 7, 2025 to November 6, 2026 inclusive.
The data
129 single-family sales in the window: 129 resale, 0 new construction.

8.2.3 Resale and new construction

In simple terms
A resale home was previously owned. New construction is sold by the builder and behaves differently, so it is kept out of every analysis and reported once on its own.
Statistically
New construction = NewConstructionYN true, or PropertyCondition contains “New Construction” or “Under Construction”. Everything else is resale.
The data
129 resale; 0 new construction.

8.2.4 Sales left out

In simple terms
A few records cannot be used as entered and are left out before any analysis.
Statistically
Excluded: PropertySubType other than Single Family Residence; no OriginalListPrice; LivingArea under 400 SF; seller payments above 10% of ClosePrice (treated as entry errors).
The data
1 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 $614K”.
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 $614K: $417,500–$613,600 (32 sales); $614K–$706K: $614,000–$705,500 (32 sales); $718K–$891K: $718,500–$891,250 (33 sales); Over $891K: $892,000–$3,683,750 (32 sales)
Quartiles by living area: Under 2,268 SF: 1,544–2,248 SF (32 sales); 2,268–2,575 SF: 2,268–2,575 SF (32 sales); 2,582–3,013 SF: 2,582–3,013 SF (33 sales); Over 3,013 SF: 3,078–5,894 SF (32 sales)
Quartiles by year built: Before 1983: 1968–1982 (31 sales); 1983–1990: 1983–1990 (32 sales); 1992–1998: 1992–1998 (35 sales); After 1998: 1999–2024 (31 sales)
View and no view: View: MLS lists a view (92 sales); No view: None or Neighborhood (33 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 $844,101, median $718,500. Days on market: average 86, median 48: 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
5 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 = 42.873< 0.0001p < 0.0063Yesε² = 0.335large
Living areaKruskal–WallisH = 71.463< 0.0001p < 0.0063Yesε² = 0.558large
Year builtKruskal–WallisH = 8.0930.0442p < 0.0063Unclearε² = 0.063medium
Days on marketKruskal–WallisH = 3.8530.2780p < 0.0063Unclearε² = 0.030small
Discount from original listKruskal–WallisH = 7.1830.0663p < 0.0063Unclearε² = 0.056small
Price cut before saleChi-squareχ² = 10.1230.0176p < 0.0063UnclearCramér’s V = 0.280small
Seller paid closing costs or repairsChi-squareχ² = 0.2830.9644p < 0.0063UnclearCramér’s V = 0.046negligible
Has a viewChi-squareχ² = 7.2530.0643p < 0.0063UnclearCramér’s V = 0.237small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 65.513< 0.0001p < 0.0063Yesε² = 0.512large
Net price per SFKruskal–WallisH = 11.1030.0112p < 0.0063Unclearε² = 0.087medium
Year builtKruskal–WallisH = 10.7430.0132p < 0.0063Unclearε² = 0.084medium
Days on marketKruskal–WallisH = 3.3730.3380p < 0.0063Unclearε² = 0.026small
Discount from original listKruskal–WallisH = 0.3830.9440p < 0.0063Unclearε² = 0.003negligible
Price cut before saleChi-squareχ² = 1.6030.6585p < 0.0063UnclearCramér’s V = 0.112small
Seller paid closing costs or repairsChi-squareχ² = 0.4030.9399p < 0.0063UnclearCramér’s V = 0.056negligible
Has a viewChi-squareχ² = 5.4230.1436p < 0.0063UnclearCramér’s V = 0.205small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 11.9430.0076p < 0.0063Unclearε² = 0.093medium
Net price per SFKruskal–WallisH = 6.6330.0846p < 0.0063Unclearε² = 0.052small
Living areaKruskal–WallisH = 19.3530.0002p < 0.0063Yesε² = 0.151large
Days on marketKruskal–WallisH = 1.1030.7773p < 0.0063Unclearε² = 0.009negligible
Discount from original listKruskal–WallisH = 3.0630.3827p < 0.0063Unclearε² = 0.024small
Price cut before saleChi-squareχ² = 0.9430.8160p < 0.0063UnclearCramér’s V = 0.085negligible
Seller paid closing costs or repairsChi-squareχ² = 4.7930.1881p < 0.0063UnclearCramér’s V = 0.193small
Has a viewChi-squareχ² = 1.1130.7740p < 0.0063UnclearCramér’s V = 0.093negligible

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 2,067.00—0.0021p < 0.0063Yesrank-biserial r = 0.362medium
Net price per SFMann–Whitney UU = 1,825.00—0.0860p < 0.0063Unclearrank-biserial r = 0.202small
Living areaMann–Whitney UU = 1,942.00—0.0177p < 0.0063Unclearrank-biserial r = 0.279small
Year builtMann–Whitney UU = 1,613.00—0.5963p < 0.0063Unclearrank-biserial r = 0.063negligible
Days on marketMann–Whitney UU = 1,702.00—0.3040p < 0.0063Unclearrank-biserial r = 0.121small
Discount from original listMann–Whitney UU = 1,622.00—0.5621p < 0.0063Unclearrank-biserial r = 0.069negligible
Price cut before saleChi-squareχ² = 0.1810.6694p < 0.0063UnclearCramér’s V = 0.038negligible
Seller paid closing costs or repairsChi-squareχ² = 0.2210.6375p < 0.0063UnclearCramér’s V = 0.042negligible

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 1 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 129 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 7, 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.