ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Mueller

Austin, TX 78723
Resale homes · closed Nov 1 – Oct 31, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 1, 2026 · 6:59 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
44
single-family resale homes
Median net sale price
$969,505
average $981,391
Median net price per SF
$461
average $458
Median days on market
16 days
average 40 days
1. SummaryResale homes · 44 sales · November 1, 2025 – October 31, 2026

This study looks at the 44 resale homes sold in Mueller in the 365 days to October 31, 2026. A full year is used because only 18 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 sold44 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 $860K · 11 sales$860K–$962K · 11 sales$977K–$1.07M · 11 salesOver $1.07M · 11 sales
3. Quartiles by net sale priceResale homes · 44 sales · November 1, 2025 – October 31, 2026

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

2026-11-01T06:59:21.271105 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 11 11 11 44 sales Sales per group Under $860K: 11 sales (25%) $860K–$962K: 11 sales (25%) $977K–$1.07M: 11 sales (25%) Over $1.07M: 11 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 $860K$860K–$962K$977K–$1.07MOver $1.07M
Higher-priced homes Over $1.07M
  • Are much larger.
  • Tend to be newer.
Lower-priced homes Under $860K
  • Are much smaller.
  • 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 $860K$860K–$962K$977K–$1.07MOver $1.07MReal difference?
Net price per SF$459 per SF$431 per SF$461 per SF$479 per SFunclear
Living area1,531 SFSmallest2,126 SF2,217 SF2,729 SFLargest✓ large
Year built20112008Oldest20102019Newest✓ large
Days on market27 days32 days11 days9 daysunclear
Discount from original list3.7%4.9%2.5%0.1%unclear
Price cut before sale18%55%27%18%unclear
Seller paid closing costs or repairs36%45%36%55%unclear
Has a view18%27%27%9%unclear

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

3.3 Net price per SF: no clear difference

2026-11-01T06:59:21.299927 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $860K 11 sales $860K– $962K 11 sales $977K– $1.07M 11 sales Over $1.07M 11 sales $0 $200 $400 $459 $431 $461 $479 Net price per SF, average

The average is $479 per SF for homes over $1.07M and $459 per SF for homes under $860K. It does not move in a straight line; homes over $1.07M are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $1.07M are about 1,200 SF (78%) larger than homes under $860K

2026-11-01T06:59:21.322284 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $860K 11 sales $860K– $962K 11 sales $977K– $1.07M 11 sales Over $1.07M 11 sales 0 1,000 2,000 3,000 1,531 2,126 2,217 2,729 Living area (SF), average

The average is 2,729 SF for homes over $1.07M and 1,531 SF for homes under $860K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Homes over $1.07M are about 8 years newer than homes under $860K

2026-11-01T06:59:21.347551 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $860K 11 sales $860K– $962K 11 sales $977K– $1.07M 11 sales Over $1.07M 11 sales 2008 2011 2014 2017 2020 2011 2008 2010 2019 Year built: median (dot) and middle half (bar)

The median is 2019 for homes over $1.07M and 2011 for homes under $860K. It does not move in a straight line; homes over $1.07M are highest. Defined in 8.1.4.

✓ Real difference · large

3.6 Days on market: no clear difference

2026-11-01T06:59:21.370719 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $860K 11 sales $860K– $962K 11 sales $977K– $1.07M 11 sales Over $1.07M 11 sales 0 10 20 30 27 32 11 9 Days on market, median

The median is 9 days for homes over $1.07M and 27 days for homes under $860K. It does not move in a straight line; homes $860K–$962K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-01T06:59:21.393078 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $860K 11 sales $860K– $962K 11 sales $977K– $1.07M 11 sales Over $1.07M 11 sales 0.0% 2.0% 4.0% 3.7% 4.9% 2.5% 0.1% Discount from original list, average

The average is 0.1% for homes over $1.07M and 3.7% for homes under $860K. It does not move in a straight line; homes $860K–$962K 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

2026-11-01T06:59:21.422843 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% 18 36 18 55 45 27 27 36 27 18 55 9 Under $860K $860K–$962K $977K–$1.07M Over $1.07M

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

  • 18% of homes over $1.07M had a price cut before sale, against 18% of homes under $860K. Defined in 8.1.7.
  • 55% of homes over $1.07M had the seller pay closing costs or repairs, against 36% of homes under $860K. Defined in 8.1.8.
  • 9% of homes over $1.07M have a view, against 18% of homes under $860K. 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 $860K11 sales$860K–$962K11 sales$977K–$1.07M11 salesOver $1.07M11 salesAll44 salesReal difference?
Net sale price average$688,787$912,637$1,020,714$1,303,425$981,391by design
Net price per SF average$459$431$461$479$458unclear
Living area average1,5312,1262,2172,7292,150✓ large
Year built median20112008201020192012✓ large

3.10 The numbers: selling

Under $860K11 sales$860K–$962K11 sales$977K–$1.07M11 salesOver $1.07M11 salesAll44 salesReal difference?
Days on market median273211916unclear
Discount from original list average3.7%4.9%2.5%0.1%2.8%unclear
Price cut before sale18%55%27%18%30%unclear
Seller paid closing costs or repairs36%45%36%55%43%unclear
Has a view18%27%27%9%20%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 · 44 sales · November 1, 2025 – October 31, 2026

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

2026-11-01T06:59:21.443716 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 10 11 12 44 sales Sales per group Under 2,005 SF: 11 sales (25%) 2,005–2,122 SF: 10 sales (23%) 2,192–2,328 SF: 11 sales (25%) Over 2,328 SF: 12 sales (27%)
Bottom line

4.1 Key differences

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

Under 2,005 SF2,005–2,122 SF2,192–2,328 SFOver 2,328 SF
Larger homes Over 2,328 SF
  • Sell for much more.
Smaller homes Under 2,005 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 2,005 SF2,005–2,122 SF2,192–2,328 SFOver 2,328 SFReal difference?
Net sale price$695KLowest$945K$1.02M$1.24MHighest✓ large
Net price per SF$467 per SF$456 per SF$453 per SF$455 per SFunclear
Year built2009200820152018unclear
Days on market22 days10 days18 days15 daysunclear
Discount from original list3.4%2.3%3.7%1.9%unclear
Price cut before sale18%20%36%42%unclear
Seller paid closing costs or repairs36%50%45%42%unclear
Has a view18%40%18%8%unclear

4.3 Homes over 2,328 SF sell for about $546K (79%) more than homes under 2,005 SF

2026-11-01T06:59:21.465145 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,005 SF 11 sales 2,005– 2,122 SF 10 sales 2,192– 2,328 SF 11 sales Over 2,328 SF 12 sales $0K $500K $1.00M $695K $945K $1.02M $1.24M Net sale price, average

The average is $1.24M for homes over 2,328 SF and $695K for homes under 2,005 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

2026-11-01T06:59:21.488657 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,005 SF 11 sales 2,005– 2,122 SF 10 sales 2,192– 2,328 SF 11 sales Over 2,328 SF 12 sales $0 $200 $400 $467 $456 $453 $455 Net price per SF, average

The average is $455 per SF for homes over 2,328 SF and $467 per SF for homes under 2,005 SF. It does not move in a straight line; homes under 2,005 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-01T06:59:21.513592 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,005 SF 11 sales 2,005– 2,122 SF 10 sales 2,192– 2,328 SF 11 sales Over 2,328 SF 12 sales 2008 2011 2014 2017 2020 2009 2008 2015 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over 2,328 SF and 2009 for homes under 2,005 SF. It does not move in a straight line; homes over 2,328 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-01T06:59:21.537717 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,005 SF 11 sales 2,005– 2,122 SF 10 sales 2,192– 2,328 SF 11 sales Over 2,328 SF 12 sales 0 10 20 22 10 18 15 Days on market, median

The median is 15 days for homes over 2,328 SF and 22 days for homes under 2,005 SF. It does not move in a straight line; homes under 2,005 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-01T06:59:21.559878 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,005 SF 11 sales 2,005– 2,122 SF 10 sales 2,192– 2,328 SF 11 sales Over 2,328 SF 12 sales 0.0% 2.0% 4.0% 3.4% 2.3% 3.7% 1.9% Discount from original list, average

The average is 1.9% for homes over 2,328 SF and 3.4% for homes under 2,005 SF. It does not move in a straight line; homes 2,192–2,328 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-01T06:59:21.586627 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% 18 36 18 20 50 40 36 45 18 42 42 8 Under 2,005 SF 2,005–2,122 SF 2,192–2,328 SF Over 2,328 SF

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

  • 42% of homes over 2,328 SF had a price cut before sale, against 18% of homes under 2,005 SF. Defined in 8.1.7.
  • 42% of homes over 2,328 SF had the seller pay closing costs or repairs, against 36% of homes under 2,005 SF. Defined in 8.1.8.
  • 8% of homes over 2,328 SF have a view, against 18% of homes under 2,005 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 2,005 SF11 sales2,005–2,122 SF10 sales2,192–2,328 SF11 salesOver 2,328 SF12 salesAll44 salesReal difference?
Net sale price average$695,151$945,211$1,016,641$1,241,615$981,391✓ large
Net price per SF average$467$456$453$455$458unclear
Living area average1,5102,0722,2462,7152,150by design
Year built median20092008201520182012unclear

4.10 The numbers: selling

Under 2,005 SF11 sales2,005–2,122 SF10 sales2,192–2,328 SF11 salesOver 2,328 SF12 salesAll44 salesReal difference?
Days on market median2210181516unclear
Discount from original list average3.4%2.3%3.7%1.9%2.8%unclear
Price cut before sale18%20%36%42%30%unclear
Seller paid closing costs or repairs36%50%45%42%43%unclear
Has a view18%40%18%8%20%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 · 44 sales · November 1, 2025 – October 31, 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.

2026-11-01T06:59:21.607005 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 8 11 11 44 sales Sales per group Before 2009: 14 sales (32%) 2009–2011: 8 sales (18%) 2012–2017: 11 sales (25%) After 2017: 11 sales (25%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

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

5.2 At a glance

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

Before 20092009–20112012–2017After 2017Real difference?
Net sale price$921K$879K$961K$1.15Munclear
Net price per SF$465 per SF$448 per SF$440 per SF$473 per SFunclear
Living area2,015 SF1,970 SF2,176 SF2,429 SFunclear
Days on market12 days8 days34 days16 daysunclear
Discount from original list3.9%1.6%3.8%1.4%unclear
Price cut before sale36%12%45%18%unclear
Seller paid closing costs or repairs29%50%36%64%unclear
Has a view14%38%9%27%unclear

5.3 Net sale price: no clear difference

2026-11-01T06:59:21.627972 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 14 sales 2009– 2011 8 sales 2012– 2017 11 sales After 2017 11 sales $0K $500K $1.00M $921K $879K $961K $1.15M Net sale price, average

The average is $1.15M for homes built after 2017 and $921K for homes built before 2009. It does not move in a straight line; homes built after 2017 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-01T06:59:21.651209 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 14 sales 2009– 2011 8 sales 2012– 2017 11 sales After 2017 11 sales $0 $200 $400 $465 $448 $440 $473 Net price per SF, average

The average is $473 per SF for homes built after 2017 and $465 per SF for homes built before 2009. It does not move in a straight line; homes built after 2017 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-01T06:59:21.673164 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 14 sales 2009– 2011 8 sales 2012– 2017 11 sales After 2017 11 sales 0 1,000 2,000 2,015 1,970 2,176 2,429 Living area (SF), average

The average is 2,429 SF for homes built after 2017 and 2,015 SF for homes built before 2009. It does not move in a straight line; homes built after 2017 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-01T06:59:21.694435 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 14 sales 2009– 2011 8 sales 2012– 2017 11 sales After 2017 11 sales 0 20 40 12 8 34 16 Days on market, median

The median is 16 days for homes built after 2017 and 12 days for homes built before 2009. It does not move in a straight line; homes built 2012–2017 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-01T06:59:21.716971 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 14 sales 2009– 2011 8 sales 2012– 2017 11 sales After 2017 11 sales 0.0% 2.0% 4.0% 3.9% 1.6% 3.8% 1.4% Discount from original list, average

The average is 1.4% for homes built after 2017 and 3.9% for homes built before 2009. It does not move in a straight line; homes built before 2009 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

2026-11-01T06:59:21.742559 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% 36 29 14 12 50 38 45 36 9 18 64 27 Before 2009 2009–2011 2012–2017 After 2017

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

  • 18% of homes built after 2017 had a price cut before sale, against 36% of homes built before 2009. Defined in 8.1.7.
  • 64% of homes built after 2017 had the seller pay closing costs or repairs, against 29% of homes built before 2009. Defined in 8.1.8.
  • 27% of homes built after 2017 have a view, against 14% of homes built before 2009. 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 200914 sales2009–20118 sales2012–201711 salesAfter 201711 salesAll44 salesReal difference?
Net sale price average$920,543$878,981$961,419$1,153,285$981,391unclear
Net price per SF average$465$448$440$473$458unclear
Living area average2,0151,9702,1762,4292,150unclear
Year built median20082009201520212012by design

5.10 The numbers: selling

Before 200914 sales2009–20118 sales2012–201711 salesAfter 201711 salesAll44 salesReal difference?
Days on market median128341616unclear
Discount from original list average3.9%1.6%3.8%1.4%2.8%unclear
Price cut before sale36%12%45%18%30%unclear
Seller paid closing costs or repairs29%50%36%64%43%unclear
Has a view14%38%9%27%20%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 · 44 sales · November 1, 2025 – October 31, 2026

Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood.

2026-11-01T06:59:21.761627 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 35 44 sales Sales per group View: 9 sales (20%) No view: 35 sales (80%)
Bottom line: no measure differs enough between the groups to rule out chance.

6.1 Key differences

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

6.2 At a glance

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

ViewNo viewReal difference?
Net sale price$966K$985Kunclear
Net price per SF$460 per SF$457 per SFunclear
Living area2,097 SF2,164 SFunclear
Year built20112012unclear
Days on market16 days15 daysunclear
Discount from original list3.0%2.8%unclear
Price cut before sale11%34%unclear
Seller paid closing costs or repairs56%40%unclear

6.3 Net sale price: no clear difference

2026-11-01T06:59:21.778949 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 35 sales $0K $250K $500K $750K $1.00M $966K $985K Net sale price, average

The average is $966K for homes with a view and $985K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-11-01T06:59:21.797389 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 35 sales $0 $200 $400 $460 $457 Net price per SF, average

The average is $460 per SF for homes with a view and $457 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

2026-11-01T06:59:21.841153 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 35 sales 0 1,000 2,000 2,097 2,164 Living area (SF), average

The average is 2,097 SF for homes with a view and 2,164 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-01T06:59:21.861424 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 35 sales 2008 2011 2014 2017 2020 2011 2012 Year built: median (dot) and middle half (bar)

The median is 2011 for homes with a view and 2012 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-01T06:59:21.879276 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 35 sales 0 5 10 15 16 15 Days on market, median

The median is 16 days for homes with a view and 15 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

2026-11-01T06:59:21.897482 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 35 sales 0.0% 1.0% 2.0% 3.0% 3.0% 2.8% Discount from original list, average

The average is 3.0% for homes with a view and 2.8% 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

2026-11-01T06:59:21.916199 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 11 56 34 40 View No view

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

  • 11% of homes with a view had a price cut before sale, against 34% of homes without a view. Defined in 8.1.7.
  • 56% of homes with a view had the seller pay closing costs or repairs, against 40% 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

View9 salesNo view35 salesAll44 salesReal difference?
Net sale price average$965,546$985,465$981,391unclear
Net price per SF average$460$457$458unclear
Living area average2,0972,1642,150unclear
Year built median201120122012unclear

6.11 The numbers: selling

View9 salesNo view35 salesAll44 salesReal difference?
Days on market median161516unclear
Discount from original list average3.0%2.8%2.8%unclear
Price cut before sale11%34%30%unclear
Seller paid closing costs or repairs56%40%43%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 · 3 sales · November 1, 2025 – October 31, 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: 3 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 Mueller.
MeasureAverageMedian
Sales3
Net sale price$1,153,000$1,140,000
Net price per SF$571$563
Living area (SF)2,0312,090
Days on market11881
Discount from original list2.0%1.1%
Price cut before sale67% of sales
Seller paid closing costs or repairs33% of sales
Year built2025–2026

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

8. AppendixMeasures, methods and tests

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

8.1 Measures

8.1.1 Net sale price

In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
44 resale sales. Average $981,391; median $969,505; standard deviation $248,123; middle half (25th–75th percentile) $842,500–$1,081,250; lowest $590,000, highest $1,629,975. 19 sales had a seller payment; their median payment was $1,899.

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
44 resale sales. Average $458; median $461; standard deviation $45; middle half (25th–75th percentile) $428–$487; lowest $360, highest $583.

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
44 resale sales. Average 2,150; median 2,192; standard deviation 510; middle half (25th–75th percentile) 1,974–2,345; lowest 1,051, highest 3,439.

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
44 resale sales. Average 2013; median 2012; standard deviation 5; middle half (25th–75th percentile) 2008–2017; lowest 2007, highest 2023.

8.1.5 Days on market

In simple terms
How many days the home was on the market before the buyer's offer was accepted, counting any earlier listing periods (relists). This is the days on market agents and clients quote.
Statistically
CDOM = max(CumulativeDaysOnMarket, DaysOnMarket, PurchaseContractDate − ListingContractDate). The MLS counter can freeze at a price change, so the contract-date gap is a floor. Summarized by the median, because a few homes that sat for months pull an average up.
The data
44 resale sales. Average 40; median 16; standard deviation 73; middle half (25th–75th percentile) 5–45; lowest 0, highest 408. 3 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
44 resale sales. Average 2.8%; median 2.5%; standard deviation 4.7%; middle half (25th–75th percentile) 0.2%–4.7%; lowest −11.1%, highest 15.2%. 8 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
13 of 44 resale sales (29.5%).

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
19 of 44 resale sales (43.2%).

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
9 sales with a view, 35 without, 0 unclassified. Most common View entries: None 29, Neighborhood 7, Park/Greenbelt 6, Pond 2, Water 1, City 1, Golf Course 1, Garden 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-01 12:45 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “mueller” (case-insensitive). A record is kept when its subdivision name belongs to the Mueller family, the same rule comparable sales use.
The data
Pulled November 1, 2026: 94 closed Mueller records over the prior year, in ZIP 78723. 14 subdivision spellings kept, the most common: Mueller (17); Mueller Sec 11 Sub (13); Mueller Sec 04 Amd (10); Mueller Sec 05 (10); Mueller Sec Vii-C Sub Amd (10); Mueller Sec Ix Sub Amd (9); Mueller Sec 10 A Sub (8); Mueller Sec 11 (4); Mueller Sec Vi Sub (4); Mueller Sec I-C Ph 1 Sub (3); Mueller Sec 10A (2); Mueller Sec 05 Resub (2); and 2 more (2 records). Names found by the search but not part of Mueller, left out: Parkside/Mueller Condos (8); 52 MUELLER CONDOMINIUMS (2); MUELLER HOUSES II AMENDED (1); Mueller Fred A (1); Concourse at Mueller Condominiums (1); Mueller Garden Homes (1); Wendlandt & Mueller (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 18 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 1, 2025 to October 31, 2026 inclusive.
The data
47 single-family sales in the window: 44 resale, 3 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
44 resale; 3 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
47 sale(s) other than single-family homes (condo, townhome and similar)

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 $860K”.
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 $860K: $590,000–$790,000 (11 sales); $860K–$962K: $860,000–$962,010 (11 sales); $977K–$1.07M: $977,000–$1,075,000 (11 sales); Over $1.07M: $1,100,000–$1,629,975 (11 sales)
Quartiles by living area: Under 2,005 SF: 1,051–1,880 SF (11 sales); 2,005–2,122 SF: 2,005–2,122 SF (10 sales); 2,192–2,328 SF: 2,192–2,328 SF (11 sales); Over 2,328 SF: 2,345–3,439 SF (12 sales)
Quartiles by year built: Before 2009: 2007–2008 (14 sales); 2009–2011: 2009–2011 (8 sales); 2012–2017: 2012–2017 (11 sales); After 2017: 2018–2023 (11 sales)
View and no view: View: MLS lists a view (9 sales); No view: None or Neighborhood (35 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 $981,391, median $969,505. Days on market: average 40, median 16: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

In simple terms
Checks whether a measure really differs across the four groups of a slice. It uses each sale's rank, not its value, so a few extreme sales cannot drive the answer.
Statistically
H = [12/(n(n+1))] Σ Rⱼ²/nⱼ − 3(n+1), compared with χ² on k − 1 degrees of freedom (Kruskal & Wallis, 1952). Effect size ε² = H/(n − 1): ≥ .01 small, ≥ .06 medium, ≥ .14 large (Tomczak & Tomczak, 2014). A slice is tested only when every group has at least 5 sales; smaller groups are described, not tested.
The data
Run on every measure in sections 3–5; each result is in 8.3.

8.2.8 Mann–Whitney U test

In simple terms
The same check when there are only two groups: view against no view.
Statistically
Two-sided U test (Mann & Whitney, 1947). Effect size = rank-biserial correlation |1 − 2U/(n₁n₂)|: ≥ .10 small, ≥ .30 medium, ≥ .50 large (Kerby, 2014; Cohen, 1988).
The data
Run on every measure in section 6; results in 8.3.

8.2.9 Chi-square test

In simple terms
Checks whether a yes/no share (price cut, seller payment, view) differs between groups more than chance would.
Statistically
Pearson χ² on the 2 × k table of counts, no continuity correction (Pearson, 1900). Effect size Cramér's V = √(χ²/n): ≥ .10 small, ≥ .30 medium, ≥ .50 large (Cramér, 1946).
The data
Run on the three shares in every slice; results in 8.3.

8.2.10 Real difference (significance)

In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063; Quartiles by year built: m = 8, threshold p < 0.0063; View and no view: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
3 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 8.3630.0391p < 0.0063Unclearε² = 0.194large
Living areaKruskal–WallisH = 32.683< 0.0001p < 0.0063Yesε² = 0.760large
Year builtKruskal–WallisH = 13.8830.0031p < 0.0063Yesε² = 0.323large
Days on marketKruskal–WallisH = 4.7930.1882p < 0.0063Unclearε² = 0.111medium
Discount from original listKruskal–WallisH = 3.6330.3048p < 0.0063Unclearε² = 0.084medium
Price cut before saleChi-squareχ² = 4.6930.1956p < 0.0063UnclearCramér’s V = 0.327medium
Seller paid closing costs or repairsChi-squareχ² = 1.0230.7967p < 0.0063UnclearCramér’s V = 0.152small
Has a viewChi-squareχ² = 1.5430.6739p < 0.0063UnclearCramér’s V = 0.187small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 30.183< 0.0001p < 0.0063Yesε² = 0.702large
Net price per SFKruskal–WallisH = 0.2630.9665p < 0.0063Unclearε² = 0.006negligible
Year builtKruskal–WallisH = 8.0830.0444p < 0.0063Unclearε² = 0.188large
Days on marketKruskal–WallisH = 0.7930.8513p < 0.0063Unclearε² = 0.018small
Discount from original listKruskal–WallisH = 0.4230.9365p < 0.0063Unclearε² = 0.010negligible
Price cut before saleChi-squareχ² = 2.2130.5294p < 0.0063UnclearCramér’s V = 0.224small
Seller paid closing costs or repairsChi-squareχ² = 0.4330.9335p < 0.0063UnclearCramér’s V = 0.099negligible
Has a viewChi-squareχ² = 3.5030.3206p < 0.0063UnclearCramér’s V = 0.282small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 7.6030.0550p < 0.0063Unclearε² = 0.177large
Net price per SFKruskal–WallisH = 5.1130.1640p < 0.0063Unclearε² = 0.119medium
Living areaKruskal–WallisH = 7.1730.0665p < 0.0063Unclearε² = 0.167large
Days on marketKruskal–WallisH = 2.7330.4356p < 0.0063Unclearε² = 0.063medium
Discount from original listKruskal–WallisH = 2.4830.4789p < 0.0063Unclearε² = 0.058small
Price cut before saleChi-squareχ² = 3.3930.3350p < 0.0063UnclearCramér’s V = 0.278small
Seller paid closing costs or repairsChi-squareχ² = 3.4530.3268p < 0.0063UnclearCramér’s V = 0.280small
Has a viewChi-squareχ² = 2.9430.4004p < 0.0063UnclearCramér’s V = 0.259small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 147.00—0.7710p < 0.0063Unclearrank-biserial r = 0.067negligible
Net price per SFMann–Whitney UU = 162.00—0.9073p < 0.0063Unclearrank-biserial r = 0.029negligible
Living areaMann–Whitney UU = 121.00—0.2945p < 0.0063Unclearrank-biserial r = 0.232small
Year builtMann–Whitney UU = 176.00—0.5975p < 0.0063Unclearrank-biserial r = 0.117small
Days on marketMann–Whitney UU = 158.50—0.9884p < 0.0063Unclearrank-biserial r = 0.006negligible
Discount from original listMann–Whitney UU = 176.00—0.6005p < 0.0063Unclearrank-biserial r = 0.117small
Price cut before saleChi-squareχ² = 1.8510.1741p < 0.0063UnclearCramér’s V = 0.205small
Seller paid closing costs or repairsChi-squareχ² = 0.7110.4008p < 0.0063UnclearCramér’s V = 0.127small

8.4 Data notes

Left out of the analysis: 3 new-construction sales (basic statistics only, section 7); 47 sale(s) other than single-family homes (condo, townhome and similar). 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 44 closed MLS resale sales; the 3 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 1, 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.