ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Wells Branch Ph D Sec 02

Austin, TX 78728
Resale homes · closed Oct 31 – Oct 30, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 31, 2026 · 7:39 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
43
single-family resale homes
Median net sale price
$387,300
average $382,436
Median net price per SF
$236
average $232
Median days on market
48 days
average 70 days
1. SummaryResale homes · 43 sales · October 31, 2025 – October 30, 2026

This study looks at the 43 resale homes sold in Wells Branch Ph D Sec 02 in the 365 days to October 30, 2026. A full year is used because only 16 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 sold43 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 $342K · 11 sales$342K–$387K · 11 sales$388K–$421K · 10 salesOver $421K · 11 sales
3. Quartiles by net sale priceResale homes · 43 sales · October 31, 2025 – October 30, 2026

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

2026-10-31T07:39:27.553962 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 11 10 11 43 sales Sales per group Under $342K: 11 sales (26%) $342K–$387K: 11 sales (26%) $388K–$421K: 10 sales (23%) Over $421K: 11 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 $342K$342K–$387K$388K–$421KOver $421K
Higher-priced homes Over $421K
  • Are much larger.
Lower-priced homes Under $342K
  • 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 $342K$342K–$387K$388K–$421KOver $421KReal difference?
Net price per SF$218 per SF$238 per SF$236 per SF$239 per SFunclear
Living area1,432 SFSmallest1,586 SF1,751 SF1,975 SFLargest✓ large
Year built1985198519851985unclear
Days on market58 days48 days88 days14 daysunclear
Discount from original list9.4%9.1%7.3%3.9%unclear
Price cut before sale55%64%70%27%unclear
Seller paid closing costs or repairs27%82%80%64%unclear
Has a view18%9%0%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

2026-10-31T07:39:27.585995 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $342K 11 sales $342K– $387K 11 sales $388K– $421K 10 sales Over $421K 11 sales $0 $100 $200 $218 $238 $236 $239 Net price per SF, average

The average is $239 per SF for homes over $421K and $218 per SF for homes under $342K. It does not move in a straight line; homes over $421K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $421K are about 540 SF (38%) larger than homes under $342K

2026-10-31T07:39:27.611470 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $342K 11 sales $342K– $387K 11 sales $388K– $421K 10 sales Over $421K 11 sales 0 1,000 2,000 1,432 1,586 1,751 1,975 Living area (SF), average

The average is 1,975 SF for homes over $421K and 1,432 SF for homes under $342K. 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

2026-10-31T07:39:27.638472 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $342K 11 sales $342K– $387K 11 sales $388K– $421K 10 sales Over $421K 11 sales 1984 1988 1992 1996 2000 1985 1985 1985 1985 Year built: median (dot) and middle half (bar)

The median is 1985 for homes over $421K and 1985 for homes under $342K. 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

2026-10-31T07:39:27.663330 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $342K 11 sales $342K– $387K 11 sales $388K– $421K 10 sales Over $421K 11 sales 0 50 100 58 48 88 14 Days on market, median

The median is 14 days for homes over $421K and 58 days for homes under $342K. It does not move in a straight line; homes $388K–$421K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-31T07:39:27.686430 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $342K 11 sales $342K– $387K 11 sales $388K– $421K 10 sales Over $421K 11 sales 0.0% 5.0% 10.0% 9.4% 9.1% 7.3% 3.9% Discount from original list, average

The average is 3.9% for homes over $421K and 9.4% for homes under $342K. 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

2026-10-31T07:39:27.718486 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 27 18 64 82 9 70 80 0 27 64 9 Under $342K $342K–$387K $388K–$421K Over $421K

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

  • 27% of homes over $421K had a price cut before sale, against 55% of homes under $342K. Defined in 8.1.7.
  • 64% of homes over $421K had the seller pay closing costs or repairs, against 27% of homes under $342K. Defined in 8.1.8.
  • 9% of homes over $421K have a view, against 18% of homes under $342K. 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 $342K11 sales$342K–$387K11 sales$388K–$421K10 salesOver $421K11 salesAll43 salesReal difference?
Net sale price average$296,333$369,341$401,608$464,205$382,436by design
Net price per SF average$218$238$236$239$232unclear
Living area average1,4321,5861,7511,9751,684✓ large
Year built median19851985198519851985unclear

3.10 The numbers: selling

Under $342K11 sales$342K–$387K11 sales$388K–$421K10 salesOver $421K11 salesAll43 salesReal difference?
Days on market median5848881448unclear
Discount from original list average9.4%9.1%7.3%3.9%7.4%unclear
Price cut before sale55%64%70%27%53%unclear
Seller paid closing costs or repairs27%82%80%64%63%unclear
Has a view18%9%0%9%9%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 · 43 sales · October 31, 2025 – October 30, 2026

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

2026-10-31T07:39:27.741303 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 10 11 11 43 sales Sales per group Under 1,473 SF: 11 sales (26%) 1,473–1,589 SF: 10 sales (23%) 1,642–1,996 SF: 11 sales (26%) Over 1,996 SF: 11 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 1,473 SF1,473–1,589 SF1,642–1,996 SFOver 1,996 SF
Larger homes Over 1,996 SF
  • Sell for less per square foot.
  • Sell for much more.
Smaller homes Under 1,473 SF
  • Sell for more per square foot.
  • 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 1,473 SF1,473–1,589 SF1,642–1,996 SFOver 1,996 SFReal difference?
Net sale price$332KLowest$364K$426KHighest$406K✓ large
Net price per SF$264 per SFHighest$241 per SF$239 per SF$187 per SFLowest✓ large
Year built1985198519851992unclear
Days on market62 days16 days43 days109 daysunclear
Discount from original list7.0%5.1%7.4%10.0%unclear
Price cut before sale55%30%45%82%unclear
Seller paid closing costs or repairs36%70%73%73%unclear
Has a view0%20%0%18%unclear

4.3 Homes over 1,996 SF sell for about $74K (22%) more than homes under 1,473 SF

2026-10-31T07:39:27.764582 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,473 SF 11 sales 1,473– 1,589 SF 10 sales 1,642– 1,996 SF 11 sales Over 1,996 SF 11 sales $0K $200K $400K $332K $364K $426K $406K Net sale price, average

The average is $406K for homes over 1,996 SF and $332K for homes under 1,473 SF. It does not move in a straight line; homes 1,642–1,996 SF are highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 1,996 SF sell for about $77 per SF (29%) less than homes under 1,473 SF

2026-10-31T07:39:27.788301 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,473 SF 11 sales 1,473– 1,589 SF 10 sales 1,642– 1,996 SF 11 sales Over 1,996 SF 11 sales $0 $100 $200 $300 $264 $241 $239 $187 Net price per SF, average

The average is $187 per SF for homes over 1,996 SF and $264 per SF for homes under 1,473 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-10-31T07:39:27.819567 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,473 SF 11 sales 1,473– 1,589 SF 10 sales 1,642– 1,996 SF 11 sales Over 1,996 SF 11 sales 1985 1990 1995 2000 2005 1985 1985 1985 1992 Year built: median (dot) and middle half (bar)

The median is 1992 for homes over 1,996 SF and 1985 for homes under 1,473 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-31T07:39:27.848426 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,473 SF 11 sales 1,473– 1,589 SF 10 sales 1,642– 1,996 SF 11 sales Over 1,996 SF 11 sales 0 50 100 62 16 43 109 Days on market, median

The median is 109 days for homes over 1,996 SF and 62 days for homes under 1,473 SF. It does not move in a straight line; homes over 1,996 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-31T07:39:27.871400 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,473 SF 11 sales 1,473– 1,589 SF 10 sales 1,642– 1,996 SF 11 sales Over 1,996 SF 11 sales 0.0% 5.0% 10.0% 7.0% 5.1% 7.4% 10.0% Discount from original list, average

The average is 10.0% for homes over 1,996 SF and 7.0% for homes under 1,473 SF. It does not move in a straight line; homes over 1,996 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

2026-10-31T07:39:27.898967 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 36 0 30 70 20 45 73 0 82 73 18 Under 1,473 SF 1,473–1,589 SF 1,642–1,996 SF Over 1,996 SF

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

  • 82% of homes over 1,996 SF had a price cut before sale, against 55% of homes under 1,473 SF. Defined in 8.1.7.
  • 73% of homes over 1,996 SF had the seller pay closing costs or repairs, against 36% of homes under 1,473 SF. Defined in 8.1.8.
  • 18% of homes over 1,996 SF have a view, against 0% of homes under 1,473 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 1,473 SF11 sales1,473–1,589 SF10 sales1,642–1,996 SF11 salesOver 1,996 SF11 salesAll43 salesReal difference?
Net sale price average$331,936$364,359$426,227$405,578$382,436✓ large
Net price per SF average$264$241$239$187$232✓ large
Living area average1,2611,5101,7892,1611,684by design
Year built median19851985198519921985unclear

4.10 The numbers: selling

Under 1,473 SF11 sales1,473–1,589 SF10 sales1,642–1,996 SF11 salesOver 1,996 SF11 salesAll43 salesReal difference?
Days on market median62164310948unclear
Discount from original list average7.0%5.1%7.4%10.0%7.4%unclear
Price cut before sale55%30%45%82%53%unclear
Seller paid closing costs or repairs36%70%73%73%63%unclear
Has a view0%20%0%18%9%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 · 43 sales · October 31, 2025 – October 30, 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.

2026-10-31T07:39:27.920671 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 15 12 43 sales Sales per group Before 1984: 8 sales (19%) 1984: 8 sales (19%) 1985–1986: 15 sales (35%) After 1986: 12 sales (28%)
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 198419841985–1986After 1986Real difference?
Net sale price$368K$358K$382K$409Kunclear
Net price per SF$218 per SF$247 per SF$246 per SF$216 per SFunclear
Living area1,732 SF1,472 SF1,589 SF1,914 SFunclear
Days on market62 days20 days27 days57 daysunclear
Discount from original list10.0%7.3%6.3%7.3%unclear
Price cut before sale62%50%47%58%unclear
Seller paid closing costs or repairs75%62%60%58%unclear
Has a view25%0%7%8%unclear

5.3 Net sale price: no clear difference

2026-10-31T07:39:27.943171 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 8 sales 1984 8 sales 1985– 1986 15 sales After 1986 12 sales $0K $200K $400K $368K $358K $382K $409K Net sale price, average

The average is $409K for homes built after 1986 and $368K for homes built before 1984. It does not move in a straight line; homes built after 1986 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-31T07:39:27.969782 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 8 sales 1984 8 sales 1985– 1986 15 sales After 1986 12 sales $0 $100 $200 $218 $247 $246 $216 Net price per SF, average

The average is $216 per SF for homes built after 1986 and $218 per SF for homes built before 1984. It does not move in a straight line; homes built 1984 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-31T07:39:27.991893 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 8 sales 1984 8 sales 1985– 1986 15 sales After 1986 12 sales 0 1,000 2,000 1,732 1,472 1,589 1,914 Living area (SF), average

The average is 1,914 SF for homes built after 1986 and 1,732 SF for homes built before 1984. It does not move in a straight line; homes built after 1986 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-31T07:39:28.014873 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 8 sales 1984 8 sales 1985– 1986 15 sales After 1986 12 sales 0 20 40 60 62 20 27 57 Days on market, median

The median is 57 days for homes built after 1986 and 62 days for homes built before 1984. It does not move in a straight line; homes built before 1984 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-31T07:39:28.036897 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 8 sales 1984 8 sales 1985– 1986 15 sales After 1986 12 sales 0.0% 5.0% 10.0% 10.0% 7.3% 6.3% 7.3% Discount from original list, average

The average is 7.3% for homes built after 1986 and 10.0% for homes built before 1984. It does not move in a straight line; homes built before 1984 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

2026-10-31T07:39:28.063268 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% 62 75 25 50 62 0 47 60 7 58 58 8 Before 1984 1984 1985–1986 After 1986

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

  • 58% of homes built after 1986 had a price cut before sale, against 62% of homes built before 1984. Defined in 8.1.7.
  • 58% of homes built after 1986 had the seller pay closing costs or repairs, against 75% of homes built before 1984. Defined in 8.1.8.
  • 8% of homes built after 1986 have a view, against 25% 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 19848 sales19848 sales1985–198615 salesAfter 198612 salesAll43 salesReal difference?
Net sale price average$367,754$358,380$382,157$408,610$382,436unclear
Net price per SF average$218$247$246$216$232unclear
Living area average1,7321,4721,5891,9141,684unclear
Year built median19831984198519981985by design

5.10 The numbers: selling

Before 19848 sales19848 sales1985–198615 salesAfter 198612 salesAll43 salesReal difference?
Days on market median6220275748unclear
Discount from original list average10.0%7.3%6.3%7.3%7.4%unclear
Price cut before sale62%50%47%58%53%unclear
Seller paid closing costs or repairs75%62%60%58%63%unclear
Has a view25%0%7%8%9%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 · 43 sales · October 31, 2025 – October 30, 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.

2026-10-31T07:39:28.082884 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 39 43 sales Sales per group View: 4 sales (9%) No view: 39 sales (91%)
Bottom line: too few sales to test.

6.1 Key differences

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

6.3 Net sale price: described, not tested

2026-10-31T07:39:28.100046 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 39 sales $0K $100K $200K $300K $400K $364K $384K Net sale price, average

The average is $364K for homes with a view and $384K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-31T07:39:28.118592 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 39 sales $0 $100 $200 $187 $237 Net price per SF, average

The average is $187 per SF for homes with a view and $237 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-31T07:39:28.250978 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 39 sales 0 500 1,000 1,500 2,000 1,964 1,656 Living area (SF), average

The average is 1,964 SF for homes with a view and 1,656 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-31T07:39:28.273377 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 39 sales 1984 1987 1990 1984 1985 Year built: median (dot) and middle half (bar)

The median is 1984 for homes with a view and 1985 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-31T07:39:28.294990 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 39 sales 0 20 40 60 80 71 43 Days on market, median

The median is 71 days for homes with a view and 43 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-31T07:39:28.315942 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 39 sales 0.0% 2.5% 5.0% 7.5% 10.0% 9.6% 7.2% Discount from original list, average

The average is 9.6% for homes with a view and 7.2% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-31T07:39:28.339074 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 50 25 54 67 View No view

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

  • 50% of homes with a view had a price cut before sale, against 54% of homes without a view. Defined in 8.1.7.
  • 25% of homes with a view had the seller pay closing costs or repairs, against 67% of homes without a view. Defined in 8.1.8.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View4 salesNo view39 salesAll43 sales
Net sale price average$364,498$384,276$382,436
Net price per SF average$187$237$232
Living area average1,9641,6561,684
Year built median198419851985

6.11 The numbers: selling

View4 salesNo view39 salesAll43 sales
Days on market median714348
Discount from original list average9.6%7.2%7.4%
Price cut before sale50%54%53%
Seller paid closing costs or repairs25%67%63%

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 31, 2025 – October 30, 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 Wells Branch Ph D Sec 02.

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
43 resale sales. Average $382,436; median $387,300; standard deviation $67,649; middle half (25th–75th percentile) $338,750–$422,540; lowest $220,760, highest $549,000. 27 sales had a seller payment; their median payment was $6,000.

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
43 resale sales. Average $232; median $236; standard deviation $42; middle half (25th–75th percentile) $203–$262; lowest $137, highest $306.

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
43 resale sales. Average 1,684; median 1,642; standard deviation 366; middle half (25th–75th percentile) 1,450–1,999; lowest 1,007, highest 2,664.

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
43 resale sales. Average 1990; median 1985; standard deviation 11; middle half (25th–75th percentile) 1984–1992; lowest 1982, 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
43 resale sales. Average 70; median 48; standard deviation 82; middle half (25th–75th percentile) 10–104; lowest 0, highest 391. 1 sales went under contract on their listing date (0 days).

8.1.6 Discount from original list

In simple terms
How far below the first asking price the home sold, after seller payments. It measures how much negotiating room sellers gave up. A negative figure means the home sold above its first asking price.
Statistically
Discount % = (OriginalListPrice − Net) ÷ OriginalListPrice × 100, per sale; summarized by the mean.
The data
43 resale sales. Average 7.4%; median 7.1%; standard deviation 6.9%; middle half (25th–75th percentile) 2.3%–11.2%; lowest −6.4%, highest 28.7%. 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
23 of 43 resale sales (53.5%).

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
27 of 43 resale sales (62.8%).

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
4 sales with a view, 39 without, 0 unclassified. Most common View entries: None 33, Neighborhood 7, Park/Greenbelt 4, Pond 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 “wells branch”, “village at wells branch” (case-insensitive). A record is kept when its subdivision name belongs to the Wells Branch Ph D Sec 02 family, the same rule comparable sales use (it includes Village at Wells Branch, proven adjacent and priced alike).
The data
Pulled October 31, 2026: 43 closed Wells Branch Ph D Sec 02 records over the prior year, in ZIP 78728. 18 subdivision spellings kept, the most common: Wells Branch Ph C Sec 01 (6); Wells Branch Ph D Sec 02 (5); Wells Branch Ph B Sec 03 (4); Wells Branch (4); Wells Branch Ph E Sec 03 (3); Village at Wells Branch (3); Wells Branch Ph D Sec 01 (3); Wells Branch Ph E Sec 01 (2); Wells Branch Ph P Resub (2); Wells Branch Ph A Sec 01 (2); Wells Branch Ph F (2); Wells Branch Ph W-2A (1); and 6 more (6 records). Names found by the search but not part of Wells Branch Ph D Sec 02, left out: The Crossing at Wells Branch (1); WELLS BRANCH PHS F (1); Wells Branch Phs E Sec 3 (1); Lake At Wells Branch Sec 01 (1); Lake At Wells Branch Sec 02 (1); WELLS BRANCH PHS A SEC 2 (1); WELLS BRANCH PHS R SEC 3 (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 16 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 31, 2025 to October 30, 2026 inclusive.
The data
43 single-family sales in the window: 43 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
43 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 $342K”.
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 $342K: $220,760–$335,500 (11 sales); $342K–$387K: $342,000–$387,300 (11 sales); $388K–$421K: $388,500–$421,080 (10 sales); Over $421K: $424,000–$549,000 (11 sales)
Quartiles by living area: Under 1,473 SF: 1,007–1,428 SF (11 sales); 1,473–1,589 SF: 1,473–1,589 SF (10 sales); 1,642–1,996 SF: 1,642–1,996 SF (11 sales); Over 1,996 SF: 2,002–2,664 SF (11 sales)
Quartiles by year built: Before 1984: 1982–1983 (8 sales); 1984: 1984–1984 (8 sales); 1985–1986: 1985–1986 (15 sales); After 1986: 1992–2018 (12 sales)
View and no view: View: MLS lists a view (4 sales); No view: None or Neighborhood (39 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 $382,436, median $387,300. Days on market: average 70, median 48: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

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

8.2.8 Mann–Whitney U test

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

8.2.9 Chi-square test

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

8.2.10 Real difference (significance)

In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063; Quartiles by year built: m = 8, threshold p < 0.0063

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 = 0.9730.8075p < 0.0063Unclearε² = 0.023small
Living areaKruskal–WallisH = 14.1930.0027p < 0.0063Yesε² = 0.338large
Year builtKruskal–WallisH = 2.5830.4603p < 0.0063Unclearε² = 0.062medium
Days on marketKruskal–WallisH = 1.4530.6928p < 0.0063Unclearε² = 0.035small
Discount from original listKruskal–WallisH = 5.1630.1602p < 0.0063Unclearε² = 0.123medium
Price cut before saleChi-squareχ² = 4.5930.2040p < 0.0063UnclearCramér’s V = 0.327medium
Seller paid closing costs or repairsChi-squareχ² = 8.9130.0304p < 0.0063UnclearCramér’s V = 0.455medium
Has a viewChi-squareχ² = 2.0530.5611p < 0.0063UnclearCramér’s V = 0.219small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 13.5430.0036p < 0.0063Yesε² = 0.322large
Net price per SFKruskal–WallisH = 21.0030.0001p < 0.0063Yesε² = 0.500large
Year builtKruskal–WallisH = 2.7230.4373p < 0.0063Unclearε² = 0.065medium
Days on marketKruskal–WallisH = 7.3630.0613p < 0.0063Unclearε² = 0.175large
Discount from original listKruskal–WallisH = 3.7930.2855p < 0.0063Unclearε² = 0.090medium
Price cut before saleChi-squareχ² = 6.0630.1089p < 0.0063UnclearCramér’s V = 0.375medium
Seller paid closing costs or repairsChi-squareχ² = 4.4430.2177p < 0.0063UnclearCramér’s V = 0.321medium
Has a viewChi-squareχ² = 4.6430.2001p < 0.0063UnclearCramér’s V = 0.329medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 2.6730.4454p < 0.0063Unclearε² = 0.064medium
Net price per SFKruskal–WallisH = 5.7130.1268p < 0.0063Unclearε² = 0.136medium
Living areaKruskal–WallisH = 7.9730.0467p < 0.0063Unclearε² = 0.190large
Days on marketKruskal–WallisH = 0.8230.8452p < 0.0063Unclearε² = 0.019small
Discount from original listKruskal–WallisH = 2.4630.4819p < 0.0063Unclearε² = 0.059small
Price cut before saleChi-squareχ² = 0.6930.8746p < 0.0063UnclearCramér’s V = 0.127small
Seller paid closing costs or repairsChi-squareχ² = 0.6630.8819p < 0.0063UnclearCramér’s V = 0.124small
Has a viewChi-squareχ² = 3.2930.3485p < 0.0063UnclearCramér’s V = 0.277small

8.3.4 View and no view

Too few sales in a group to test.

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 43 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 31, 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.