ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Lakeway

Lakeway, TX 78734 · 78738
Resale homes · closed Oct 29 – Oct 28, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 29, 2026 · 7:12 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
131
single-family resale homes
Median net sale price
$700,000
average $836,629
Median net price per SF
$286
average $297
Median days on market
49 days
average 87 days
1. SummaryResale homes · 131 sales · October 29, 2025 – October 28, 2026

This study looks at the 131 resale homes sold in Lakeway in the 365 days to October 28, 2026. A full year is used because only 75 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 sold131 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 $608K · 33 sales$608K–$700K · 33 sales$705K–$881K · 32 salesOver $881K · 33 sales
3. Quartiles by net sale priceResale homes · 131 sales · October 29, 2025 – October 28, 2026

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

2026-10-29T07:12:23.615783 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 33 33 32 33 131 sales Sales per group Under $608K: 33 sales (25%) $608K–$700K: 33 sales (25%) $705K–$881K: 32 sales (24%) Over $881K: 33 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 $608K$608K–$700K$705K–$881KOver $881K
Higher-priced homes Over $881K
  • Are much larger.
  • Sell for more per square foot.
Lower-priced homes Under $608K
  • 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 $608K$608K–$700K$705K–$881KOver $881KReal difference?
Net price per SF$257 per SFLowest$266 per SF$302 per SF$364 per SFHighest✓ large
Living area2,197 SFSmallest2,516 SF2,640 SF3,665 SFLargest✓ large
Year built1988198619921997unclear
Days on market56 days53 days40 days47 daysunclear
Discount from original list8.7%8.3%4.9%5.6%unclear
Price cut before sale52%61%44%30%unclear
Seller paid closing costs or repairs45%45%47%52%unclear
Has a view55%73%75%82%unclear

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

3.3 Homes over $881K sell for about $106 per SF (41%) more than homes under $608K

2026-10-29T07:12:23.643349 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $608K 33 sales $608K– $700K 33 sales $705K– $881K 32 sales Over $881K 33 sales $0 $200 $400 $257 $266 $302 $364 Net price per SF, average

The average is $364 per SF for homes over $881K and $257 per SF for homes under $608K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $881K are about 1,470 SF (67%) larger than homes under $608K

2026-10-29T07:12:23.664805 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $608K 33 sales $608K– $700K 33 sales $705K– $881K 32 sales Over $881K 33 sales 0 2,000 4,000 2,197 2,516 2,640 3,665 Living area (SF), average

The average is 3,665 SF for homes over $881K and 2,197 SF for homes under $608K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-29T07:12:23.687855 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $608K 33 sales $608K– $700K 33 sales $705K– $881K 32 sales Over $881K 33 sales 1986 1992 1998 2004 1988 1986 1992 1997 Year built: median (dot) and middle half (bar)

The median is 1997 for homes over $881K and 1988 for homes under $608K. It does not move in a straight line; homes over $881K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-29T07:12:23.709798 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $608K 33 sales $608K– $700K 33 sales $705K– $881K 32 sales Over $881K 33 sales 0 20 40 60 56 53 40 47 Days on market, median

The median is 47 days for homes over $881K and 56 days for homes under $608K. It does not move in a straight line; homes under $608K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-29T07:12:23.731496 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $608K 33 sales $608K– $700K 33 sales $705K– $881K 32 sales Over $881K 33 sales 0.0% 5.0% 10.0% 8.7% 8.3% 4.9% 5.6% Discount from original list, average

The average is 5.6% for homes over $881K and 8.7% for homes under $608K. It does not move in a straight line; homes under $608K 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

2026-10-29T07:12:23.760470 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% 52 45 55 61 45 73 44 47 75 30 52 82 Under $608K $608K–$700K $705K–$881K Over $881K

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

  • 30% of homes over $881K had a price cut before sale, against 52% of homes under $608K. Defined in 8.1.7.
  • 52% of homes over $881K had the seller pay closing costs or repairs, against 45% of homes under $608K. Defined in 8.1.8.
  • 82% of homes over $881K have a view, against 55% of homes under $608K. 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 $608K33 sales$608K–$700K33 sales$705K–$881K32 salesOver $881K33 salesAll131 salesReal difference?
Net sale price average$557,429$655,055$782,952$1,349,451$836,629by design
Net price per SF average$257$266$302$364$297✓ large
Living area average2,1972,5162,6403,6652,755✓ large
Year built median19881986199219971992unclear

3.10 The numbers: selling

Under $608K33 sales$608K–$700K33 sales$705K–$881K32 salesOver $881K33 salesAll131 salesReal difference?
Days on market median5653404749unclear
Discount from original list average8.7%8.3%4.9%5.6%6.9%unclear
Price cut before sale52%61%44%30%47%unclear
Seller paid closing costs or repairs45%45%47%52%47%unclear
Has a view55%73%75%82%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 · 131 sales · October 29, 2025 – October 28, 2026

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

2026-10-29T07:12:23.780953 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 33 33 32 33 131 sales Sales per group Under 2,268 SF: 33 sales (25%) 2,268–2,559 SF: 33 sales (25%) 2,575–2,963 SF: 32 sales (24%) Over 2,963 SF: 33 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 SF2,268–2,559 SF2,575–2,963 SFOver 2,963 SF
Larger homes Over 2,963 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 SF2,268–2,559 SF2,575–2,963 SFOver 2,963 SFReal difference?
Net sale price$632KLowest$681K$751K$1.28MHighest✓ large
Net price per SF$313 per SF$282 per SF$270 per SF$323 per SFunclear
Year built1985198819941994unclear
Days on market56 days45 days42 days52 daysunclear
Discount from original list6.5%6.7%7.0%7.2%unclear
Price cut before sale39%52%53%42%unclear
Seller paid closing costs or repairs42%52%47%48%unclear
Has a view58%70%78%79%unclear

4.3 Homes over 2,963 SF sell for about $647K (102%) more than homes under 2,268 SF

2026-10-29T07:12:23.801175 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,268 SF 33 sales 2,268– 2,559 SF 33 sales 2,575– 2,963 SF 32 sales Over 2,963 SF 33 sales $0K $500K $1.00M $1.50M $632K $681K $751K $1.28M Net sale price, average

The average is $1.28M for homes over 2,963 SF and $632K 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

2026-10-29T07:12:23.823385 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,268 SF 33 sales 2,268– 2,559 SF 33 sales 2,575– 2,963 SF 32 sales Over 2,963 SF 33 sales $0 $100 $200 $300 $313 $282 $270 $323 Net price per SF, average

The average is $323 per SF for homes over 2,963 SF and $313 per SF for homes under 2,268 SF. It does not move in a straight line; homes over 2,963 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-29T07:12:23.846480 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,268 SF 33 sales 2,268– 2,559 SF 33 sales 2,575– 2,963 SF 32 sales Over 2,963 SF 33 sales 1985 1990 1995 2000 1985 1988 1994 1994 Year built: median (dot) and middle half (bar)

The median is 1994 for homes over 2,963 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

2026-10-29T07:12:23.868418 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,268 SF 33 sales 2,268– 2,559 SF 33 sales 2,575– 2,963 SF 32 sales Over 2,963 SF 33 sales 0 20 40 60 56 45 42 52 Days on market, median

The median is 52 days for homes over 2,963 SF and 56 days for homes under 2,268 SF. It does not move in a straight line; homes under 2,268 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-29T07:12:23.890506 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,268 SF 33 sales 2,268– 2,559 SF 33 sales 2,575– 2,963 SF 32 sales Over 2,963 SF 33 sales 0.0% 2.5% 5.0% 7.5% 6.5% 6.7% 7.0% 7.2% Discount from original list, average

The average is 7.2% for homes over 2,963 SF and 6.5% 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

2026-10-29T07:12:23.916654 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% 39 42 58 52 52 70 53 47 78 42 48 79 Under 2,268 SF 2,268–2,559 SF 2,575–2,963 SF Over 2,963 SF

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

  • 42% of homes over 2,963 SF had a price cut before sale, against 39% of homes under 2,268 SF. Defined in 8.1.7.
  • 48% of homes over 2,963 SF had the seller pay closing costs or repairs, against 42% of homes under 2,268 SF. Defined in 8.1.8.
  • 79% of homes over 2,963 SF have a view, against 58% 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 SF33 sales2,268–2,559 SF33 sales2,575–2,963 SF32 salesOver 2,963 SF33 salesAll131 salesReal difference?
Net sale price average$632,494$680,958$750,506$1,279,947$836,629✓ large
Net price per SF average$313$282$270$323$297unclear
Living area average2,0202,4142,7773,8112,755by design
Year built median19851988199419941992unclear

4.10 The numbers: selling

Under 2,268 SF33 sales2,268–2,559 SF33 sales2,575–2,963 SF32 salesOver 2,963 SF33 salesAll131 salesReal difference?
Days on market median5645425249unclear
Discount from original list average6.5%6.7%7.0%7.2%6.9%unclear
Price cut before sale39%52%53%42%47%unclear
Seller paid closing costs or repairs42%52%47%48%47%unclear
Has a view58%70%78%79%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 · 131 sales · October 29, 2025 – October 28, 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.

2026-10-29T07:12:23.936814 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 32 33 32 34 131 sales Sales per group Before 1984: 32 sales (24%) 1984–1990: 33 sales (25%) 1992–1997: 32 sales (24%) After 1997: 34 sales (26%)
Bottom line

5.1 Key differences

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

Before 19841984–19901992–1997After 1997
Newer homes After 1997
  • Are larger.
Older homes Before 1984
  • Are 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 19841984–19901992–1997After 1997Real difference?
Net sale price$805K$710K$743K$1.08Munclear
Net price per SF$309 per SF$289 per SF$272 per SF$318 per SFunclear
Living area2,602 SF2,471 SFSmallest2,732 SF3,198 SFLargest✓ medium
Days on market48 days67 days30 days46 daysunclear
Discount from original list8.2%7.2%6.5%5.6%unclear
Price cut before sale50%48%47%41%unclear
Seller paid closing costs or repairs50%64%34%41%unclear
Has a view69%76%69%71%unclear

5.3 Net sale price: no clear difference

2026-10-29T07:12:23.957141 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 32 sales 1984– 1990 33 sales 1992– 1997 32 sales After 1997 34 sales $0K $500K $1.00M $805K $710K $743K $1.08M Net sale price, average

The average is $1.08M for homes built after 1997 and $805K for homes built before 1984. It does not move in a straight line; homes built after 1997 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-29T07:12:23.979015 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 32 sales 1984– 1990 33 sales 1992– 1997 32 sales After 1997 34 sales $0 $100 $200 $300 $309 $289 $272 $318 Net price per SF, average

The average is $318 per SF for homes built after 1997 and $309 per SF for homes built before 1984. It does not move in a straight line; homes built after 1997 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Homes built after 1997 are about 600 SF (23%) larger than homes built before 1984

2026-10-29T07:12:24.000538 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 32 sales 1984– 1990 33 sales 1992– 1997 32 sales After 1997 34 sales 0 1,000 2,000 3,000 2,602 2,471 2,732 3,198 Living area (SF), average

The average is 3,198 SF for homes built after 1997 and 2,602 SF for homes built before 1984. It does not move in a straight line; homes built after 1997 are highest. Defined in 8.1.3.

✓ Real difference · medium

5.6 Days on market: no clear difference

2026-10-29T07:12:24.021939 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 32 sales 1984– 1990 33 sales 1992– 1997 32 sales After 1997 34 sales 0 25 50 75 48 67 30 46 Days on market, median

The median is 46 days for homes built after 1997 and 48 days for homes built before 1984. It does not move in a straight line; homes built 1984–1990 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-29T07:12:24.044692 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 32 sales 1984– 1990 33 sales 1992– 1997 32 sales After 1997 34 sales 0.0% 2.5% 5.0% 7.5% 8.2% 7.2% 6.5% 5.6% Discount from original list, average

The average is 5.6% for homes built after 1997 and 8.2% for homes built before 1984. It falls 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

2026-10-29T07:12:24.069700 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% 50 50 69 48 64 76 47 34 69 41 41 71 Before 1984 1984–1990 1992–1997 After 1997

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

  • 41% of homes built after 1997 had a price cut before sale, against 50% of homes built before 1984. Defined in 8.1.7.
  • 41% of homes built after 1997 had the seller pay closing costs or repairs, against 50% of homes built before 1984. Defined in 8.1.8.
  • 71% of homes built after 1997 have a view, against 69% of homes built before 1984. 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 198432 sales1984–199033 sales1992–199732 salesAfter 199734 salesAll131 salesReal difference?
Net sale price average$804,522$709,561$742,550$1,078,721$836,629unclear
Net price per SF average$309$289$272$318$297unclear
Living area average2,6022,4712,7323,1982,755✓ medium
Year built median19761986199420041992by design

5.10 The numbers: selling

Before 198432 sales1984–199033 sales1992–199732 salesAfter 199734 salesAll131 salesReal difference?
Days on market median4867304649unclear
Discount from original list average8.2%7.2%6.5%5.6%6.9%unclear
Price cut before sale50%48%47%41%47%unclear
Seller paid closing costs or repairs50%64%34%41%47%unclear
Has a view69%76%69%71%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 · 131 sales · October 29, 2025 – October 28, 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.

2026-10-29T07:12:24.087446 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 93 34 127 sales Sales per group View: 93 sales (73%) No view: 34 sales (27%)
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$887KHighest$677KLowest✓ medium
Net price per SF$306 per SF$277 per SFunclear
Living area2,826 SF2,463 SFunclear
Year built19901990unclear
Days on market56 days47 daysunclear
Discount from original list7.5%5.6%unclear
Price cut before sale47%44%unclear
Seller paid closing costs or repairs47%50%unclear

6.3 Homes with a view sell for about $210K (31%) more than homes without a view

2026-10-29T07:12:24.104502 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 93 sales No view 34 sales $0K $250K $500K $750K $1.00M $887K $677K Net sale price, average

The average is $887K for homes with a view and $677K for homes without a view. Defined in 8.1.1.

✓ Real difference · medium

6.4 Net price per SF: no clear difference

2026-10-29T07:12:24.121964 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 93 sales No view 34 sales $0 $100 $200 $300 $306 $277 Net price per SF, average

The average is $306 per SF for homes with a view and $277 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

2026-10-29T07:12:24.139689 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 93 sales No view 34 sales 0 1,000 2,000 3,000 2,826 2,463 Living area (SF), average

The average is 2,826 SF for homes with a view and 2,463 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-29T07:12:24.179282 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 93 sales No view 34 sales 1984 1988 1992 1996 1990 1990 Year built: median (dot) and middle half (bar)

The median is 1990 for homes with a view and 1990 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-29T07:12:24.196283 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 93 sales No view 34 sales 0 20 40 60 56 47 Days on market, median

The median is 56 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

2026-10-29T07:12:24.214782 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 93 sales No view 34 sales 0.0% 2.0% 4.0% 6.0% 8.0% 7.5% 5.6% Discount from original list, average

The average is 7.5% 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

2026-10-29T07:12:24.233171 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 47 47 44 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 44% 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

View93 salesNo view34 salesAll127 salesReal difference?
Net sale price average$886,813$676,758$830,577✓ medium
Net price per SF average$306$277$298unclear
Living area average2,8262,4632,729unclear
Year built median199019901990unclear

6.11 The numbers: selling

View93 salesNo view34 salesAll127 salesReal difference?
Days on market median564749unclear
Discount from original list average7.5%5.6%7.0%unclear
Price cut before sale47%44%46%unclear
Seller paid closing costs or repairs47%50%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 · October 29, 2025 – October 28, 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
131 resale sales. Average $836,629; median $700,000; standard deviation $459,101; middle half (25th–75th percentile) $606,500–$885,976; lowest $417,500, highest $3,683,750. 62 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
131 resale sales. Average $297; median $286; standard deviation $84; middle half (25th–75th percentile) $256–$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
131 resale sales. Average 2,755; median 2,559; standard deviation 756; middle half (25th–75th percentile) 2,258–2,988; 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
131 resale sales. Average 1991; median 1992; standard deviation 12; middle half (25th–75th percentile) 1984–1998; 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
131 resale sales. Average 87; median 49; standard deviation 97; middle half (25th–75th percentile) 12–128; 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
131 resale sales. Average 6.9%; median 5.5%; standard deviation 7.0%; middle half (25th–75th percentile) 1.9%–9.5%; lowest −5.4%, highest 30.4%. 7 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
61 of 131 resale sales (46.6%).

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
62 of 131 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
93 sales with a view, 34 without, 4 unclassified. Most common View entries: Hill Country 40, Trees/Woods 39, Neighborhood 36, Golf Course 28, 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
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. 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 October 29, 2026: 132 closed Lakeway records over the prior year, in ZIP 78734, 78738. 40 subdivision spellings kept, the most common: Lakeway (16); Lakeway Sec 26 (8); Lakeway Sec 24 (8); Lakeway Sec 28 (7); Lakeway Sec 22 (6); Lakeway Sec Clusters 28 05 (6); Lakeway Sec 02 (6); Lakeway Sec 24-B (6); Lakeway Sec 16 (6); Lakeway Sec 27 (5); Lakeway Sec Clusters 28 04 (5); Lakeway Sec 17 (5); and 28 more (48 records). Names found by the search but not part of Lakeway, left out: Boulevard At Lakeway (7); Vistas At Lakeway Condo (2); Estates Lakeway Hills Sec 03 (2); Lakeway Condo Patio Home (2); North Lakeway Village Sec 03 (2); Lakeway World Tennis Condo (2); Lakeway Highlands Ph 1 Sec 3 (1); LAKEWAY; Lohmans Crossing Estates Sec 1 (1); Rough Hollow Lakeway (1); Vistas at Lakeway (1); Lakeway Hlnds Ph 3 Sec 6B (1); Pinnacle at Lakeway Condos (1); Lakeway Highlands Ph 1 Sec 5 (1); Westside Landing; Rough Hollow; Lakeway (1); The Landing at Lakeway (1); Lakeway Hlnds Ph 3 Sec 4 (1); Hills Lakeway Ph 04 (1); North Lakeway Village Sec 06 (1); The Vistas of Lakeway (1); Landing/Lakeway Condos (1); Arbolago; Lakeway (1); Cardinal Hills, Lakeway (1); Lohmans Crossing Estates Sec 07 of Lakeway (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 75 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 29, 2025 to October 28, 2026 inclusive.
The data
131 single-family sales in the window: 131 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
131 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 $608K”.
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 $608K: $417,500–$605,000 (33 sales); $608K–$700K: $608,000–$700,000 (33 sales); $705K–$881K: $705,000–$880,702 (32 sales); Over $881K: $891,250–$3,683,750 (33 sales)
Quartiles by living area: Under 2,268 SF: 1,544–2,248 SF (33 sales); 2,268–2,559 SF: 2,268–2,559 SF (33 sales); 2,575–2,963 SF: 2,575–2,963 SF (32 sales); Over 2,963 SF: 3,013–5,894 SF (33 sales)
Quartiles by year built: Before 1984: 1968–1983 (32 sales); 1984–1990: 1984–1990 (33 sales); 1992–1997: 1992–1997 (32 sales); After 1997: 1998–2024 (34 sales)
View and no view: View: MLS lists a view (93 sales); No view: None or Neighborhood (34 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 $836,629, median $700,000. Days on market: average 87, median 49: 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 = 46.513< 0.0001p < 0.0063Yesε² = 0.358large
Living areaKruskal–WallisH = 69.193< 0.0001p < 0.0063Yesε² = 0.532large
Year builtKruskal–WallisH = 7.5430.0565p < 0.0063Unclearε² = 0.058small
Days on marketKruskal–WallisH = 0.9030.8263p < 0.0063Unclearε² = 0.007negligible
Discount from original listKruskal–WallisH = 6.5730.0868p < 0.0063Unclearε² = 0.051small
Price cut before saleChi-squareχ² = 6.5530.0878p < 0.0063UnclearCramér’s V = 0.224small
Seller paid closing costs or repairsChi-squareχ² = 0.3330.9547p < 0.0063UnclearCramér’s V = 0.050negligible
Has a viewChi-squareχ² = 6.5130.0892p < 0.0063UnclearCramér’s V = 0.223small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 66.043< 0.0001p < 0.0063Yesε² = 0.508large
Net price per SFKruskal–WallisH = 9.6330.0220p < 0.0063Unclearε² = 0.074medium
Year builtKruskal–WallisH = 9.7530.0208p < 0.0063Unclearε² = 0.075medium
Days on marketKruskal–WallisH = 3.2930.3497p < 0.0063Unclearε² = 0.025small
Discount from original listKruskal–WallisH = 0.3030.9593p < 0.0063Unclearε² = 0.002negligible
Price cut before saleChi-squareχ² = 1.7930.6176p < 0.0063UnclearCramér’s V = 0.117small
Seller paid closing costs or repairsChi-squareχ² = 0.5730.9031p < 0.0063UnclearCramér’s V = 0.066negligible
Has a viewChi-squareχ² = 4.6830.1971p < 0.0063UnclearCramér’s V = 0.189small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 8.7130.0334p < 0.0063Unclearε² = 0.067medium
Net price per SFKruskal–WallisH = 5.7130.1264p < 0.0063Unclearε² = 0.044small
Living areaKruskal–WallisH = 16.6330.0008p < 0.0063Yesε² = 0.128medium
Days on marketKruskal–WallisH = 1.2030.7530p < 0.0063Unclearε² = 0.009negligible
Discount from original listKruskal–WallisH = 2.1330.5451p < 0.0063Unclearε² = 0.016small
Price cut before saleChi-squareχ² = 0.6030.8967p < 0.0063UnclearCramér’s V = 0.068negligible
Seller paid closing costs or repairsChi-squareχ² = 6.2830.0987p < 0.0063UnclearCramér’s V = 0.219small
Has a viewChi-squareχ² = 0.5230.9138p < 0.0063UnclearCramér’s V = 0.063negligible

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 2,127.00—0.0030p < 0.0063Yesrank-biserial r = 0.345medium
Net price per SFMann–Whitney UU = 1,876.00—0.1088p < 0.0063Unclearrank-biserial r = 0.187small
Living areaMann–Whitney UU = 2,005.00—0.0211p < 0.0063Unclearrank-biserial r = 0.268small
Year builtMann–Whitney UU = 1,694.50—0.5380p < 0.0063Unclearrank-biserial r = 0.072negligible
Days on marketMann–Whitney UU = 1,764.50—0.3190p < 0.0063Unclearrank-biserial r = 0.116small
Discount from original listMann–Whitney UU = 1,685.00—0.5730p < 0.0063Unclearrank-biserial r = 0.066negligible
Price cut before saleChi-squareχ² = 0.1010.7493p < 0.0063UnclearCramér’s V = 0.028negligible
Seller paid closing costs or repairsChi-squareχ² = 0.0710.7883p < 0.0063UnclearCramér’s V = 0.024negligible

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 131 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 29, 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.