ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Maple Run

Austin, TX 78749
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 7:33 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
45
single-family resale homes
Median net sale price
$475,125
average $476,785
Median net price per SF
$288
average $286
Median days on market
29 days
average 47 days
1. SummaryResale homes · 45 sales · October 26, 2025 – October 25, 2026

This study looks at the 45 resale homes sold in Maple Run in the 365 days to October 25, 2026. A full year is used because only 25 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 sold45 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 $416K · 11 sales$416K–$467K · 11 sales$475K–$539K · 12 salesOver $539K · 11 sales
3. Quartiles by net sale priceResale homes · 45 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:33:45.182637 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 11 12 11 45 sales Sales per group Under $416K: 11 sales (24%) $416K–$467K: 11 sales (24%) $475K–$539K: 12 sales (27%) Over $539K: 11 sales (24%)
Bottom line

3.1 Key differences

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

Under $416K$416K–$467K$475K–$539KOver $539K
Higher-priced homes Over $539K
  • Are much larger.
Lower-priced homes Under $416K
  • Are much smaller.

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 $416K$416K–$467K$475K–$539KOver $539KReal difference?
Net price per SF$254 per SF$290 per SF$281 per SF$317 per SFunclear
Living area1,468 SFSmallest1,569 SF1,831 SF1,898 SFLargest✓ large
Year built1986198619861989unclear
Days on market21 days17 days32 days30 daysunclear
Discount from original list8.0%5.1%3.7%3.5%unclear
Price cut before sale55%45%50%27%unclear
Seller paid closing costs or repairs45%55%58%82%unclear
Has a view27%18%17%18%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

2026-10-26T07:33:45.211585 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $416K 11 sales $416K– $467K 11 sales $475K– $539K 12 sales Over $539K 11 sales $0 $100 $200 $300 $254 $290 $281 $317 Net price per SF, average

The average is $317 per SF for homes over $539K and $254 per SF for homes under $416K. It does not move in a straight line; homes over $539K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $539K are about 430 SF (29%) larger than homes under $416K

2026-10-26T07:33:45.236719 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $416K 11 sales $416K– $467K 11 sales $475K– $539K 12 sales Over $539K 11 sales 0 1,000 2,000 1,468 1,569 1,831 1,898 Living area (SF), average

The average is 1,898 SF for homes over $539K and 1,468 SF for homes under $416K. 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

2026-10-26T07:33:45.262049 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $416K 11 sales $416K– $467K 11 sales $475K– $539K 12 sales Over $539K 11 sales 1984 1986 1988 1990 1986 1986 1986 1989 Year built: median (dot) and middle half (bar)

The median is 1989 for homes over $539K and 1986 for homes under $416K. 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

2026-10-26T07:33:45.286166 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $416K 11 sales $416K– $467K 11 sales $475K– $539K 12 sales Over $539K 11 sales 0 10 20 30 21 17 32 30 Days on market, median

The median is 30 days for homes over $539K and 21 days for homes under $416K. It does not move in a straight line; homes $475K–$539K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:33:45.309422 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $416K 11 sales $416K– $467K 11 sales $475K– $539K 12 sales Over $539K 11 sales 0.0% 2.5% 5.0% 7.5% 8.0% 5.1% 3.7% 3.5% Discount from original list, average

The average is 3.5% for homes over $539K and 8.0% for homes under $416K. It falls step by step from the lowest range to the highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:33:45.341160 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 55 45 27 45 55 18 50 58 17 27 82 18 Under $416K $416K–$467K $475K–$539K Over $539K

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

  • 27% of homes over $539K had a price cut before sale, against 55% of homes under $416K. Defined in 8.1.7.
  • 82% of homes over $539K had the seller pay closing costs or repairs, against 45% of homes under $416K. Defined in 8.1.8.
  • 18% of homes over $539K have a view, against 27% of homes under $416K. 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 $416K11 sales$416K–$467K11 sales$475K–$539K12 salesOver $539K11 salesAll45 salesReal difference?
Net sale price average$363,649$442,818$508,526$589,259$476,785by design
Net price per SF average$254$290$281$317$286unclear
Living area average1,4681,5691,8311,8981,695✓ large
Year built median19861986198619891986unclear

3.10 The numbers: selling

Under $416K11 sales$416K–$467K11 sales$475K–$539K12 salesOver $539K11 salesAll45 salesReal difference?
Days on market median2117323029unclear
Discount from original list average8.0%5.1%3.7%3.5%5.0%unclear
Price cut before sale55%45%50%27%44%unclear
Seller paid closing costs or repairs45%55%58%82%60%unclear
Has a view27%18%17%18%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 · 45 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:33:45.361922 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 11 12 11 45 sales Sales per group Under 1,463 SF: 11 sales (24%) 1,463–1,650 SF: 11 sales (24%) 1,667–1,842 SF: 12 sales (27%) Over 1,842 SF: 11 sales (24%)
Bottom line

4.1 Key differences

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

Under 1,463 SF1,463–1,650 SF1,667–1,842 SFOver 1,842 SF
Larger homes Over 1,842 SF
  • Sell for much more.
Smaller homes Under 1,463 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 1,463 SF1,463–1,650 SF1,667–1,842 SFOver 1,842 SFReal difference?
Net sale price$401KLowest$445K$523K$534KHighest✓ large
Net price per SF$305 per SF$285 per SF$302 per SF$249 per SFunclear
Year built1986198619861991unclear
Days on market16 days36 days32 days17 daysunclear
Discount from original list5.4%5.5%4.7%4.6%unclear
Price cut before sale45%55%58%18%unclear
Seller paid closing costs or repairs55%45%75%64%unclear
Has a view27%9%17%27%unclear

4.3 Homes over 1,842 SF sell for about $134K (33%) more than homes under 1,463 SF

2026-10-26T07:33:45.382700 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,463 SF 11 sales 1,463– 1,650 SF 11 sales 1,667– 1,842 SF 12 sales Over 1,842 SF 11 sales $0K $200K $400K $600K $401K $445K $523K $534K Net sale price, average

The average is $534K for homes over 1,842 SF and $401K for homes under 1,463 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-26T07:33:45.405922 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,463 SF 11 sales 1,463– 1,650 SF 11 sales 1,667– 1,842 SF 12 sales Over 1,842 SF 11 sales $0 $100 $200 $300 $305 $285 $302 $249 Net price per SF, average

The average is $249 per SF for homes over 1,842 SF and $305 per SF for homes under 1,463 SF. It does not move in a straight line; homes under 1,463 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:33:45.429924 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,463 SF 11 sales 1,463– 1,650 SF 11 sales 1,667– 1,842 SF 12 sales Over 1,842 SF 11 sales 1984 1986 1988 1990 1986 1986 1986 1991 Year built: median (dot) and middle half (bar)

The median is 1991 for homes over 1,842 SF and 1986 for homes under 1,463 SF. It does not move in a straight line; homes over 1,842 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:33:45.453099 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,463 SF 11 sales 1,463– 1,650 SF 11 sales 1,667– 1,842 SF 12 sales Over 1,842 SF 11 sales 0 20 40 16 36 32 17 Days on market, median

The median is 17 days for homes over 1,842 SF and 16 days for homes under 1,463 SF. It does not move in a straight line; homes 1,463–1,650 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:33:45.475321 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,463 SF 11 sales 1,463– 1,650 SF 11 sales 1,667– 1,842 SF 12 sales Over 1,842 SF 11 sales 0.0% 2.0% 4.0% 6.0% 5.4% 5.5% 4.7% 4.6% Discount from original list, average

The average is 4.6% for homes over 1,842 SF and 5.4% for homes under 1,463 SF. It does not move in a straight line; homes 1,463–1,650 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:33:45.502456 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% 45 55 27 55 45 9 58 75 17 18 64 27 Under 1,463 SF 1,463–1,650 SF 1,667–1,842 SF Over 1,842 SF

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

  • 18% of homes over 1,842 SF had a price cut before sale, against 45% of homes under 1,463 SF. Defined in 8.1.7.
  • 64% of homes over 1,842 SF had the seller pay closing costs or repairs, against 55% of homes under 1,463 SF. Defined in 8.1.8.
  • 27% of homes over 1,842 SF have a view, against 27% of homes under 1,463 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 1,463 SF11 sales1,463–1,650 SF11 sales1,667–1,842 SF12 salesOver 1,842 SF11 salesAll45 salesReal difference?
Net sale price average$400,517$444,668$523,498$534,208$476,785✓ large
Net price per SF average$305$285$302$249$286unclear
Living area average1,3131,5621,7352,1661,695by design
Year built median19861986198619911986unclear

4.10 The numbers: selling

Under 1,463 SF11 sales1,463–1,650 SF11 sales1,667–1,842 SF12 salesOver 1,842 SF11 salesAll45 salesReal difference?
Days on market median1636321729unclear
Discount from original list average5.4%5.5%4.7%4.6%5.0%unclear
Price cut before sale45%55%58%18%44%unclear
Seller paid closing costs or repairs55%45%75%64%60%unclear
Has a view27%9%17%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 8.3.2.

5. Quartiles by year builtResale homes · 45 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:33:45.523136 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 7 18 9 45 sales Sales per group Before 1984: 11 sales (24%) 1984–1985: 7 sales (16%) 1986–1991: 18 sales (40%) After 1991: 9 sales (20%)
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 19841984–19851986–1991After 1991Real difference?
Net sale price$473K$443K$473K$515Kunclear
Net price per SF$271 per SF$287 per SF$282 per SF$309 per SFunclear
Living area1,783 SF1,542 SF1,706 SF1,683 SFunclear
Days on market17 days128 days27 days29 daysunclear
Discount from original list2.0%7.5%6.7%3.6%unclear
Price cut before sale36%71%50%22%unclear
Seller paid closing costs or repairs36%57%83%44%unclear
Has a view9%14%22%33%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:33:45.543779 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984– 1985 7 sales 1986– 1991 18 sales After 1991 9 sales $0K $200K $400K $600K $473K $443K $473K $515K Net sale price, average

The average is $515K for homes built after 1991 and $473K for homes built before 1984. It does not move in a straight line; homes built after 1991 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:33:45.567122 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984– 1985 7 sales 1986– 1991 18 sales After 1991 9 sales $0 $100 $200 $300 $271 $287 $282 $309 Net price per SF, average

The average is $309 per SF for homes built after 1991 and $271 per SF for homes built before 1984. It does not move in a straight line; homes built after 1991 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:33:45.589434 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984– 1985 7 sales 1986– 1991 18 sales After 1991 9 sales 0 1,000 2,000 1,783 1,542 1,706 1,683 Living area (SF), average

The average is 1,683 SF for homes built after 1991 and 1,783 SF for homes built before 1984. It does not move in a straight line; homes built before 1984 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:33:45.611052 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984– 1985 7 sales 1986– 1991 18 sales After 1991 9 sales 0 50 100 150 17 128 27 29 Days on market, median

The median is 29 days for homes built after 1991 and 17 days for homes built before 1984. It does not move in a straight line; homes built 1984–1985 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:33:45.634936 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984– 1985 7 sales 1986– 1991 18 sales After 1991 9 sales 0.0% 2.5% 5.0% 7.5% 2.0% 7.5% 6.7% 3.6% Discount from original list, average

The average is 3.6% for homes built after 1991 and 2.0% for homes built before 1984. It does not move in a straight line; homes built 1984–1985 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:33:45.661035 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 36 9 71 57 14 50 83 22 22 44 33 Before 1984 1984–1985 1986–1991 After 1991

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

  • 22% of homes built after 1991 had a price cut before sale, against 36% of homes built before 1984. Defined in 8.1.7.
  • 44% of homes built after 1991 had the seller pay closing costs or repairs, against 36% of homes built before 1984. Defined in 8.1.8.
  • 33% of homes built after 1991 have a view, against 9% 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 198411 sales1984–19857 sales1986–199118 salesAfter 19919 salesAll45 salesReal difference?
Net sale price average$472,777$443,479$472,884$515,388$476,785unclear
Net price per SF average$271$287$282$309$286unclear
Living area average1,7831,5421,7061,6831,695unclear
Year built median19831984198619921986by design

5.10 The numbers: selling

Before 198411 sales1984–19857 sales1986–199118 salesAfter 19919 salesAll45 salesReal difference?
Days on market median17128272929unclear
Discount from original list average2.0%7.5%6.7%3.6%5.0%unclear
Price cut before sale36%71%50%22%44%unclear
Seller paid closing costs or repairs36%57%83%44%60%unclear
Has a view9%14%22%33%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 · 45 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:33:45.680322 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 36 45 sales Sales per group View: 9 sales (20%) No view: 36 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$461K$481Kunclear
Net price per SF$285 per SF$286 per SFunclear
Living area1,651 SF1,706 SFunclear
Year built19911986unclear
Days on market29 days25 daysunclear
Discount from original list3.9%5.3%unclear
Price cut before sale56%42%unclear
Seller paid closing costs or repairs67%58%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:33:45.696672 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 36 sales $0K $200K $400K $461K $481K Net sale price, average

The average is $461K for homes with a view and $481K 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

2026-10-26T07:33:45.714167 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 36 sales $0 $100 $200 $300 $285 $286 Net price per SF, average

The average is $285 per SF for homes with a view and $286 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-10-26T07:33:45.732749 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 36 sales 0 500 1,000 1,500 2,000 1,651 1,706 Living area (SF), average

The average is 1,651 SF for homes with a view and 1,706 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:33:45.780002 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 36 sales 1984 1986 1988 1990 1992 1991 1986 Year built: median (dot) and middle half (bar)

The median is 1991 for homes with a view and 1986 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:33:45.798307 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 36 sales 0 10 20 30 29 25 Days on market, median

The median is 29 days for homes with a view and 25 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-10-26T07:33:45.816650 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 36 sales 0.0% 2.0% 4.0% 6.0% 3.9% 5.3% Discount from original list, average

The average is 3.9% for homes with a view and 5.3% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:33:45.835611 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 56 67 42 58 View No view

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

  • 56% of homes with a view had a price cut before sale, against 42% of homes without a view. Defined in 8.1.7.
  • 67% of homes with a view had the seller pay closing costs or repairs, against 58% 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 view36 salesAll45 salesReal difference?
Net sale price average$461,266$480,664$476,785unclear
Net price per SF average$285$286$286unclear
Living area average1,6511,7061,695unclear
Year built median199119861986unclear

6.11 The numbers: selling

View9 salesNo view36 salesAll45 salesReal difference?
Days on market median292529unclear
Discount from original list average3.9%5.3%5.0%unclear
Price cut before sale56%42%44%unclear
Seller paid closing costs or repairs67%58%60%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 26, 2025 – October 25, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 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 Maple Run.

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
45 resale sales. Average $476,785; median $475,125; standard deviation $89,352; middle half (25th–75th percentile) $416,500–$539,200; lowest $320,000, highest $676,000. 27 sales had a seller payment; their median payment was $8,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
45 resale sales. Average $286; median $288; standard deviation $47; middle half (25th–75th percentile) $258–$317; lowest $180, highest $404.

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
45 resale sales. Average 1,695; median 1,667; standard deviation 338; middle half (25th–75th percentile) 1,463–1,842; lowest 1,220, highest 2,701.

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
45 resale sales. Average 1988; median 1986; standard deviation 6; middle half (25th–75th percentile) 1984–1991; lowest 1981, highest 2018.

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
45 resale sales. Average 47; median 29; standard deviation 65; middle half (25th–75th percentile) 8–45; lowest 1, highest 334. 0 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
45 resale sales. Average 5.0%; median 3.2%; standard deviation 6.9%; middle half (25th–75th percentile) 1.5%–7.8%; lowest −17.8%, highest 20.7%. 5 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
20 of 45 resale sales (44.4%).

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
27 of 45 resale sales (60.0%).

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, 36 without, 0 unclassified. Most common View entries: None 27, Neighborhood 11, Park/Greenbelt 6, Trees/Woods 4, Rural 1, See Remarks 1, City 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
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “maple run” (case-insensitive). A record is kept when its subdivision name belongs to the Maple Run family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 45 closed Maple Run records over the prior year, in ZIP 78749. 14 subdivision spellings kept, the most common: Maple Run Sec 09 (8); Maple Run Sec 06 (6); Maple Run Sec 07-B (5); Maple Run Sec 02-A (4); Maple Run Sec 03 (4); Maple Run (3); Maple Run Sec 05-A (3); Maple Run Sec 08 (3); Maple Run Sec 04-A (3); Maple Run Sec 01 (2); MAPLE RUN SEC 3 (1); MAPLE RUN SEC 8 (1); and 2 more (2 records). Names found by the search but not part of Maple Run, left out: Deer Park At Maple Run Sec 11-A (2); Deer Park At Maple Run Sec 11- (1); Deer Park At Maple Run Sec 10 (1); Deer Park At Maple Run Sec 11A (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 25 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
45 single-family sales in the window: 45 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
45 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
None in this window.

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 $416K”.
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 $416K: $320,000–$411,500 (11 sales); $416K–$467K: $416,500–$466,750 (11 sales); $475K–$539K: $475,125–$539,200 (12 sales); Over $539K: $542,000–$676,000 (11 sales)
Quartiles by living area: Under 1,463 SF: 1,220–1,458 SF (11 sales); 1,463–1,650 SF: 1,463–1,650 SF (11 sales); 1,667–1,842 SF: 1,667–1,842 SF (12 sales); Over 1,842 SF: 1,863–2,701 SF (11 sales)
Quartiles by year built: Before 1984: 1981–1983 (11 sales); 1984–1985: 1984–1985 (7 sales); 1986–1991: 1986–1991 (18 sales); After 1991: 1992–2018 (9 sales)
View and no view: View: MLS lists a view (9 sales); No view: None or Neighborhood (36 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 $476,785, median $475,125. Days on market: average 47, median 29: 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
2 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 = 9.9330.0192p < 0.0063Unclearε² = 0.226large
Living areaKruskal–WallisH = 16.3230.0010p < 0.0063Yesε² = 0.371large
Year builtKruskal–WallisH = 1.3130.7279p < 0.0063Unclearε² = 0.030small
Days on marketKruskal–WallisH = 1.0830.7812p < 0.0063Unclearε² = 0.025small
Discount from original listKruskal–WallisH = 2.1730.5378p < 0.0063Unclearε² = 0.049small
Price cut before saleChi-squareχ² = 1.9230.5886p < 0.0063UnclearCramér’s V = 0.207small
Seller paid closing costs or repairsChi-squareχ² = 3.3030.3474p < 0.0063UnclearCramér’s V = 0.271small
Has a viewChi-squareχ² = 0.4930.9206p < 0.0063UnclearCramér’s V = 0.105small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 18.7130.0003p < 0.0063Yesε² = 0.425large
Net price per SFKruskal–WallisH = 9.6830.0215p < 0.0063Unclearε² = 0.220large
Year builtKruskal–WallisH = 1.7530.6251p < 0.0063Unclearε² = 0.040small
Days on marketKruskal–WallisH = 2.2530.5215p < 0.0063Unclearε² = 0.051small
Discount from original listKruskal–WallisH = 0.1430.9868p < 0.0063Unclearε² = 0.003negligible
Price cut before saleChi-squareχ² = 4.4730.2150p < 0.0063UnclearCramér’s V = 0.315medium
Seller paid closing costs or repairsChi-squareχ² = 2.2930.5141p < 0.0063UnclearCramér’s V = 0.226small
Has a viewChi-squareχ² = 1.6330.6529p < 0.0063UnclearCramér’s V = 0.190small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 2.9330.4018p < 0.0063Unclearε² = 0.067medium
Net price per SFKruskal–WallisH = 4.5530.2076p < 0.0063Unclearε² = 0.103medium
Living areaKruskal–WallisH = 2.6830.4432p < 0.0063Unclearε² = 0.061medium
Days on marketKruskal–WallisH = 2.9230.4044p < 0.0063Unclearε² = 0.066medium
Discount from original listKruskal–WallisH = 3.6330.3045p < 0.0063Unclearε² = 0.082medium
Price cut before saleChi-squareχ² = 4.3830.2232p < 0.0063UnclearCramér’s V = 0.312medium
Seller paid closing costs or repairsChi-squareχ² = 7.5830.0557p < 0.0063UnclearCramér’s V = 0.410medium
Has a viewChi-squareχ² = 2.0230.5690p < 0.0063UnclearCramér’s V = 0.212small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 141.00—0.5608p < 0.0063Unclearrank-biserial r = 0.130small
Net price per SFMann–Whitney UU = 179.00—0.6396p < 0.0063Unclearrank-biserial r = 0.105small
Living areaMann–Whitney UU = 151.50—0.7766p < 0.0063Unclearrank-biserial r = 0.065negligible
Year builtMann–Whitney UU = 213.50—0.1447p < 0.0063Unclearrank-biserial r = 0.318medium
Days on marketMann–Whitney UU = 168.00—0.8759p < 0.0063Unclearrank-biserial r = 0.037negligible
Discount from original listMann–Whitney UU = 161.00—0.9887p < 0.0063Unclearrank-biserial r = 0.006negligible
Price cut before saleChi-squareχ² = 0.5610.4533p < 0.0063UnclearCramér’s V = 0.112small
Seller paid closing costs or repairsChi-squareχ² = 0.2110.6481p < 0.0063UnclearCramér’s V = 0.068negligible

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); nothing else. 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 45 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 26, 2026. Map data © OpenStreetMap contributors. ALEX Companies · Licensed by the Texas Real Estate Commission · Broker: Alexander Tiffany Southwest, LLC (ALEX Real Estate), #565194-BB · Diane Hart Alexander, Designated Broker, #574877-B.