ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Maple Run

Austin, TX 78749
Resale homes · closed Nov 8 – Nov 7, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 8, 2026 · 7:33 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
46
single-family resale homes
Median net sale price
$489,500
average $481,433
Median net price per SF
$288
average $285
Median days on market
26 days
average 47 days
1. SummaryResale homes · 46 sales · November 8, 2025 – November 7, 2026

This study looks at the 46 resale homes sold in Maple Run in the 365 days to November 7, 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 sold46 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 $429K · 12 sales$429K–$482K · 11 sales$497K–$542K · 11 salesOver $542K · 12 sales
3. Quartiles by net sale priceResale homes · 46 sales · November 8, 2025 – November 7, 2026

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

2026-11-08T07:33:38.571991 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 11 11 12 46 sales Sales per group Under $429K: 12 sales (26%) $429K–$482K: 11 sales (24%) $497K–$542K: 11 sales (24%) Over $542K: 12 sales (26%)
Bottom line

3.1 Key differences

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

Under $429K$429K–$482K$497K–$542KOver $542K
Higher-priced homes Over $542K
  • Are much larger.
Lower-priced homes Under $429K
  • 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 $429K$429K–$482K$497K–$542KOver $542KReal difference?
Net price per SF$258 per SF$282 per SF$286 per SF$316 per SFunclear
Living area1,465 SFSmallest1,641 SF1,839 SF1,900 SFLargest✓ large
Year built1986198619901988unclear
Days on market18 days18 days29 days32 daysunclear
Discount from original list7.6%4.8%3.7%4.8%unclear
Price cut before sale50%36%55%42%unclear
Seller paid closing costs or repairs50%45%64%83%unclear
Has a view25%18%18%25%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

2026-11-08T07:33:38.608725 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $429K 12 sales $429K– $482K 11 sales $497K– $542K 11 sales Over $542K 12 sales $0 $100 $200 $300 $258 $282 $286 $316 Net price per SF, average

The average is $316 per SF for homes over $542K and $258 per SF for homes under $429K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $542K are about 440 SF (30%) larger than homes under $429K

2026-11-08T07:33:38.639314 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $429K 12 sales $429K– $482K 11 sales $497K– $542K 11 sales Over $542K 12 sales 0 1,000 2,000 1,465 1,641 1,839 1,900 Living area (SF), average

The average is 1,900 SF for homes over $542K and 1,465 SF for homes under $429K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-11-08T07:33:38.671242 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $429K 12 sales $429K– $482K 11 sales $497K– $542K 11 sales Over $542K 12 sales 1984 1986 1988 1990 1986 1986 1990 1988 Year built: median (dot) and middle half (bar)

The median is 1988 for homes over $542K and 1986 for homes under $429K. It does not move in a straight line; homes $497K–$542K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-08T07:33:38.700130 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $429K 12 sales $429K– $482K 11 sales $497K– $542K 11 sales Over $542K 12 sales 0 10 20 30 18 18 29 32 Days on market, median

The median is 32 days for homes over $542K and 18 days for homes under $429K. It does not move in a straight line; homes over $542K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-08T07:33:38.732251 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $429K 12 sales $429K– $482K 11 sales $497K– $542K 11 sales Over $542K 12 sales 0.0% 2.5% 5.0% 7.5% 7.6% 4.8% 3.7% 4.8% Discount from original list, average

The average is 4.8% for homes over $542K and 7.6% for homes under $429K. It does not move in a straight line; homes under $429K 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

2026-11-08T07:33:38.771825 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% 25% 36% 45% 18% 55% 64% 18% 42% 83% 25% Under $429K $429K–$482K $497K–$542K Over $542K

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

  • 42% of homes over $542K had a price cut before sale, against 50% of homes under $429K. Defined in 8.1.7.
  • 83% of homes over $542K had the seller pay closing costs or repairs, against 50% of homes under $429K. Defined in 8.1.8.
  • 25% of homes over $542K have a view, against 25% of homes under $429K. 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 $429K12 sales$429K–$482K11 sales$497K–$542K11 salesOver $542K12 salesAll46 salesReal difference?
Net sale price average$368,053$450,068$519,199$588,946$481,433by design
Net price per SF average$258$282$286$316$285unclear
Living area average1,4651,6411,8391,9001,710✓ large
Year built median19861986199019881986unclear

3.10 The numbers: selling

Under $429K12 sales$429K–$482K11 sales$497K–$542K11 salesOver $542K12 salesAll46 salesReal difference?
Days on market median1818293226unclear
Discount from original list average7.6%4.8%3.7%4.8%5.3%unclear
Price cut before sale50%36%55%42%46%unclear
Seller paid closing costs or repairs50%45%64%83%61%unclear
Has a view25%18%18%25%22%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 · 46 sales · November 8, 2025 – November 7, 2026

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

2026-11-08T07:33:38.800223 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 11 11 12 46 sales Sales per group Under 1,510 SF: 12 sales (26%) 1,510–1,681 SF: 11 sales (24%) 1,705–1,842 SF: 11 sales (24%) Over 1,842 SF: 12 sales (26%)
Bottom line

4.1 Key differences

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

Under 1,510 SF1,510–1,681 SF1,705–1,842 SFOver 1,842 SF
Larger homes Over 1,842 SF
  • Sell for much more.
Smaller homes Under 1,510 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 1,510 SF1,510–1,681 SF1,705–1,842 SFOver 1,842 SFReal difference?
Net sale price$403KLowest$470K$519K$536KHighest✓ large
Net price per SF$301 per SF$294 per SF$297 per SF$252 per SFunclear
Year built1986198619841989unclear
Days on market18 days24 days30 days25 daysunclear
Discount from original list6.7%4.4%4.4%5.5%unclear
Price cut before sale50%55%55%25%unclear
Seller paid closing costs or repairs42%64%73%67%unclear
Has a view25%18%9%33%unclear

4.3 Homes over 1,842 SF sell for about $133K (33%) more than homes under 1,510 SF

2026-11-08T07:33:38.824614 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,510 SF 12 sales 1,510– 1,681 SF 11 sales 1,705– 1,842 SF 11 sales Over 1,842 SF 12 sales $0K $200K $400K $600K $403K $470K $519K $536K Net sale price, average

The average is $536K for homes over 1,842 SF and $403K for homes under 1,510 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

2026-11-08T07:33:38.852519 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,510 SF 12 sales 1,510– 1,681 SF 11 sales 1,705– 1,842 SF 11 sales Over 1,842 SF 12 sales $0 $100 $200 $300 $301 $294 $297 $252 Net price per SF, average

The average is $252 per SF for homes over 1,842 SF and $301 per SF for homes under 1,510 SF. It does not move in a straight line; homes under 1,510 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-08T07:33:38.877983 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,510 SF 12 sales 1,510– 1,681 SF 11 sales 1,705– 1,842 SF 11 sales Over 1,842 SF 12 sales 1984 1987 1990 1986 1986 1984 1989 Year built: median (dot) and middle half (bar)

The median is 1989 for homes over 1,842 SF and 1986 for homes under 1,510 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

2026-11-08T07:33:38.901354 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,510 SF 12 sales 1,510– 1,681 SF 11 sales 1,705– 1,842 SF 11 sales Over 1,842 SF 12 sales 0 10 20 30 18 24 30 25 Days on market, median

The median is 25 days for homes over 1,842 SF and 18 days for homes under 1,510 SF. It does not move in a straight line; homes 1,705–1,842 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-08T07:33:38.925981 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,510 SF 12 sales 1,510– 1,681 SF 11 sales 1,705– 1,842 SF 11 sales Over 1,842 SF 12 sales 0.0% 2.0% 4.0% 6.0% 6.7% 4.4% 4.4% 5.5% Discount from original list, average

The average is 5.5% for homes over 1,842 SF and 6.7% for homes under 1,510 SF. It does not move in a straight line; homes under 1,510 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

2026-11-08T07:33:38.953097 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% 42% 25% 55% 64% 18% 55% 73% 9% 25% 67% 33% Under 1,510 SF 1,510–1,681 SF 1,705–1,842 SF Over 1,842 SF

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

  • 25% of homes over 1,842 SF had a price cut before sale, against 50% of homes under 1,510 SF. Defined in 8.1.7.
  • 67% of homes over 1,842 SF had the seller pay closing costs or repairs, against 42% of homes under 1,510 SF. Defined in 8.1.8.
  • 33% of homes over 1,842 SF have a view, against 25% of homes under 1,510 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 1,510 SF12 sales1,510–1,681 SF11 sales1,705–1,842 SF11 salesOver 1,842 SF12 salesAll46 salesReal difference?
Net sale price average$402,641$470,009$519,350$535,941$481,433✓ large
Net price per SF average$301$294$297$252$285unclear
Living area average1,3391,5971,7512,1481,710by design
Year built median19861986198419891986unclear

4.10 The numbers: selling

Under 1,510 SF12 sales1,510–1,681 SF11 sales1,705–1,842 SF11 salesOver 1,842 SF12 salesAll46 salesReal difference?
Days on market median1824302526unclear
Discount from original list average6.7%4.4%4.4%5.5%5.3%unclear
Price cut before sale50%55%55%25%46%unclear
Seller paid closing costs or repairs42%64%73%67%61%unclear
Has a view25%18%9%33%22%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 · 46 sales · November 8, 2025 – November 7, 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.

2026-11-08T07:33:38.974577 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 8 12 15 46 sales Sales per group Before 1984: 11 sales (24%) 1984–1985: 8 sales (17%) 1986–1990: 12 sales (26%) After 1990: 15 sales (33%)
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 19841984–19851986–1990After 1990Real difference?
Net sale price$482K$457K$452K$517Kunclear
Net price per SF$269 per SF$287 per SF$285 per SF$296 per SFunclear
Living area1,817 SF1,593 SF1,605 SF1,778 SFunclear
Days on market17 days94 days20 days35 daysunclear
Discount from original list2.2%8.4%6.2%5.2%unclear
Price cut before sale36%75%42%40%unclear
Seller paid closing costs or repairs36%62%75%67%unclear
Has a view9%25%17%33%unclear

5.3 Net sale price: no clear difference

2026-11-08T07:33:38.995131 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984– 1985 8 sales 1986– 1990 12 sales After 1990 15 sales $0K $200K $400K $600K $482K $457K $452K $517K Net sale price, average

The average is $517K for homes built after 1990 and $482K for homes built before 1984. It does not move in a straight line; homes built after 1990 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-08T07:33:39.017663 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984– 1985 8 sales 1986– 1990 12 sales After 1990 15 sales $0 $100 $200 $300 $269 $287 $285 $296 Net price per SF, average

The average is $296 per SF for homes built after 1990 and $269 per SF for homes built before 1984. It does not move in a straight line; homes built after 1990 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-08T07:33:39.041157 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984– 1985 8 sales 1986– 1990 12 sales After 1990 15 sales 0 1,000 2,000 1,817 1,593 1,605 1,778 Living area (SF), average

The average is 1,778 SF for homes built after 1990 and 1,817 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

2026-11-08T07:33:39.063323 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984– 1985 8 sales 1986– 1990 12 sales After 1990 15 sales 0 50 100 17 94 20 35 Days on market, median

The median is 35 days for homes built after 1990 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

2026-11-08T07:33:39.087028 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984– 1985 8 sales 1986– 1990 12 sales After 1990 15 sales 0.0% 5.0% 10.0% 2.2% 8.4% 6.2% 5.2% Discount from original list, average

The average is 5.2% for homes built after 1990 and 2.2% 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

2026-11-08T07:33:39.113576 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% 75% 62% 25% 42% 75% 17% 40% 67% 33% Before 1984 1984–1985 1986–1990 After 1990

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

  • 40% of homes built after 1990 had a price cut before sale, against 36% of homes built before 1984. Defined in 8.1.7.
  • 67% of homes built after 1990 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 1990 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 sales1984–19858 sales1986–199012 salesAfter 199015 salesAll46 salesReal difference?
Net sale price average$482,391$457,419$452,299$516,846$481,433unclear
Net price per SF average$269$287$285$296$285unclear
Living area average1,8171,5931,6051,7781,710unclear
Year built median19831984198619921986by design

5.10 The numbers: selling

Before 198411 sales1984–19858 sales1986–199012 salesAfter 199015 salesAll46 salesReal difference?
Days on market median1794203526unclear
Discount from original list average2.2%8.4%6.2%5.2%5.3%unclear
Price cut before sale36%75%42%40%46%unclear
Seller paid closing costs or repairs36%62%75%67%61%unclear
Has a view9%25%17%33%22%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 · 46 sales · November 8, 2025 – November 7, 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.

2026-11-08T07:33:39.132830 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 36 46 sales Sales per group View: 10 sales (22%) No view: 36 sales (78%)
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$471K$484Kunclear
Net price per SF$285 per SF$285 per SFunclear
Living area1,681 SF1,718 SFunclear
Year built19901986unclear
Days on market32 days21 daysunclear
Discount from original list5.0%5.3%unclear
Price cut before sale60%42%unclear
Seller paid closing costs or repairs70%58%unclear

6.3 Net sale price: no clear difference

2026-11-08T07:33:39.151194 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 36 sales $0K $200K $400K $471K $484K Net sale price, average

The average is $471K for homes with a view and $484K 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

2026-11-08T07:33:39.168467 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 36 sales $0 $100 $200 $300 $285 $285 Net price per SF, average

The average is $285 per SF for homes with a view and $285 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

2026-11-08T07:33:39.187044 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 36 sales 0 500 1,000 1,500 2,000 1,681 1,718 Living area (SF), average

The average is 1,681 SF for homes with a view and 1,718 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-08T07:33:39.290400 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 36 sales 1984 1986 1988 1990 1992 1990 1986 Year built: median (dot) and middle half (bar)

The median is 1990 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

2026-11-08T07:33:39.308804 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 36 sales 0 10 20 30 32 21 Days on market, median

The median is 32 days for homes with a view and 21 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

2026-11-08T07:33:39.326526 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 36 sales 0.0% 2.0% 4.0% 6.0% 5.0% 5.3% Discount from original list, average

The average is 5.0% 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

2026-11-08T07:33:39.346841 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 60% 70% 42% 58% View No view

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

  • 60% of homes with a view had a price cut before sale, against 42% of homes without a view. Defined in 8.1.7.
  • 70% 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

View10 salesNo view36 salesAll46 salesReal difference?
Net sale price average$470,639$484,432$481,433unclear
Net price per SF average$285$285$285unclear
Living area average1,6811,7181,710unclear
Year built median199019861986unclear

6.11 The numbers: selling

View10 salesNo view36 salesAll46 salesReal difference?
Days on market median322126unclear
Discount from original list average5.0%5.3%5.3%unclear
Price cut before sale60%42%46%unclear
Seller paid closing costs or repairs70%58%61%unclear

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

7. New constructionBasic statistics · 0 sales · November 8, 2025 – November 7, 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
46 resale sales. Average $481,433; median $489,500; standard deviation $90,218; middle half (25th–75th percentile) $419,625–$542,375; lowest $320,000, highest $676,000. 28 sales had a seller payment; their median payment was $10,000.

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
46 resale sales. Average $285; median $288; standard deviation $46; middle half (25th–75th percentile) $259–$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
46 resale sales. Average 1,710; median 1,693; standard deviation 332; middle half (25th–75th percentile) 1,505–1,858; 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
46 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
46 resale sales. Average 47; median 26; standard deviation 64; middle half (25th–75th percentile) 9–56; 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
46 resale sales. Average 5.3%; median 3.5%; standard deviation 6.9%; middle half (25th–75th percentile) 1.5%–8.5%; 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
21 of 46 resale sales (45.7%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
28 of 46 resale sales (60.9%).

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
10 sales with a view, 36 without, 0 unclassified. Most common View entries: None 28, Neighborhood 10, Park/Greenbelt 7, Trees/Woods 5, Rural 1, City 1, See Remarks 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 2026-11-08 13:30 UTC), every field. 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 November 8, 2026: 46 closed Maple Run records over the prior year, in ZIP 78749. 14 subdivision spellings kept, the most common: Maple Run Sec 09 (9); Maple Run Sec 06 (6); Maple Run Sec 07-B (5); Maple Run Sec 03 (5); Maple Run Sec 02-A (4); Maple Run Sec 08 (3); Maple Run Sec 04-A (3); Maple Run Sec 05-A (3); Maple Run Sec 01 (2); Maple Run (2); MAPLE RUN SEC 9 (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 10 (1); Deer Park At Maple Run Sec 11- (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 November 8, 2025 to November 7, 2026 inclusive.
The data
46 single-family sales in the window: 46 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
46 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 $429K”.
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 $429K: $320,000–$416,500 (12 sales); $429K–$482K: $429,000–$482,000 (11 sales); $497K–$542K: $497,000–$542,000 (11 sales); Over $542K: $542,500–$676,000 (12 sales)
Quartiles by living area: Under 1,510 SF: 1,220–1,503 SF (12 sales); 1,510–1,681 SF: 1,510–1,681 SF (11 sales); 1,705–1,842 SF: 1,705–1,842 SF (11 sales); Over 1,842 SF: 1,863–2,701 SF (12 sales)
Quartiles by year built: Before 1984: 1981–1983 (11 sales); 1984–1985: 1984–1985 (8 sales); 1986–1990: 1986–1990 (12 sales); After 1990: 1991–2018 (15 sales)
View and no view: View: MLS lists a view (10 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 $481,433, median $489,500. Days on market: average 47, median 26: 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 = 9.2030.0268p < 0.0063Unclearε² = 0.204large
Living areaKruskal–WallisH = 15.7230.0013p < 0.0063Yesε² = 0.349large
Year builtKruskal–WallisH = 0.6530.8853p < 0.0063Unclearε² = 0.014small
Days on marketKruskal–WallisH = 0.3530.9499p < 0.0063Unclearε² = 0.008negligible
Discount from original listKruskal–WallisH = 1.4630.6914p < 0.0063Unclearε² = 0.032small
Price cut before saleChi-squareχ² = 0.9030.8251p < 0.0063UnclearCramér’s V = 0.140small
Seller paid closing costs or repairsChi-squareχ² = 4.2730.2337p < 0.0063UnclearCramér’s V = 0.305medium
Has a viewChi-squareχ² = 0.3130.9574p < 0.0063UnclearCramér’s V = 0.083negligible

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 17.7930.0005p < 0.0063Yesε² = 0.395large
Net price per SFKruskal–WallisH = 9.1730.0272p < 0.0063Unclearε² = 0.204large
Year builtKruskal–WallisH = 2.7730.4288p < 0.0063Unclearε² = 0.062medium
Days on marketKruskal–WallisH = 0.4630.9271p < 0.0063Unclearε² = 0.010small
Discount from original listKruskal–WallisH = 0.5230.9151p < 0.0063Unclearε² = 0.011small
Price cut before saleChi-squareχ² = 2.8630.4144p < 0.0063UnclearCramér’s V = 0.249small
Seller paid closing costs or repairsChi-squareχ² = 2.7130.4382p < 0.0063UnclearCramér’s V = 0.243small
Has a viewChi-squareχ² = 2.1430.5440p < 0.0063UnclearCramér’s V = 0.216small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 3.4730.3245p < 0.0063Unclearε² = 0.077medium
Net price per SFKruskal–WallisH = 3.1530.3695p < 0.0063Unclearε² = 0.070medium
Living areaKruskal–WallisH = 5.0630.1673p < 0.0063Unclearε² = 0.113medium
Days on marketKruskal–WallisH = 4.4930.2131p < 0.0063Unclearε² = 0.100medium
Discount from original listKruskal–WallisH = 2.3830.4973p < 0.0063Unclearε² = 0.053small
Price cut before saleChi-squareχ² = 3.4330.3300p < 0.0063UnclearCramér’s V = 0.273small
Seller paid closing costs or repairsChi-squareχ² = 4.0030.2615p < 0.0063UnclearCramér’s V = 0.295small
Has a viewChi-squareχ² = 2.4530.4842p < 0.0063UnclearCramér’s V = 0.231small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 167.00—0.7392p < 0.0063Unclearrank-biserial r = 0.072negligible
Net price per SFMann–Whitney UU = 195.00—0.6994p < 0.0063Unclearrank-biserial r = 0.083negligible
Living areaMann–Whitney UU = 177.50—0.9575p < 0.0063Unclearrank-biserial r = 0.014negligible
Year builtMann–Whitney UU = 222.50—0.2600p < 0.0063Unclearrank-biserial r = 0.236small
Days on marketMann–Whitney UU = 196.50—0.6699p < 0.0063Unclearrank-biserial r = 0.092negligible
Discount from original listMann–Whitney UU = 193.00—0.7392p < 0.0063Unclearrank-biserial r = 0.072negligible
Price cut before saleChi-squareχ² = 1.0610.3032p < 0.0063UnclearCramér’s V = 0.152small
Seller paid closing costs or repairsChi-squareχ² = 0.4510.5037p < 0.0063UnclearCramér’s V = 0.099negligible

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 46 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 8, 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.