ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Wells Branch

Austin, TX 78728
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 · 7:41 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
39
single-family resale homes
Median net sale price
$386,844
average $377,327
Median net price per SF
$236
average $232
Median days on market
48 days
average 62 days
1. SummaryResale homes · 39 sales · November 8, 2025 – November 7, 2026

This study looks at the 39 resale homes sold in Wells Branch in the 365 days to November 7, 2026. A full year is used because only 15 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 sold39 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 $336K · 10 sales$336K–$387K · 10 sales$387K–$409K · 9 salesOver $409K · 10 sales
3. Quartiles by net sale priceResale homes · 39 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.

2026-11-08T07:41:21.504571 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 9 10 39 sales Sales per group Under $336K: 10 sales (26%) $336K–$387K: 10 sales (26%) $387K–$409K: 9 sales (23%) Over $409K: 10 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 $336K$336K–$387K$387K–$409KOver $409K
Higher-priced homes Over $409K
  • Are much larger.
Lower-priced homes Under $336K
  • 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 $336K$336K–$387K$387K–$409KOver $409KReal difference?
Net price per SF$217 per SF$235 per SF$242 per SF$236 per SFunclear
Living area1,425 SFSmallest1,580 SF1,668 SF1,983 SFLargest✓ large
Year built1984198519841989unclear
Days on market60 days24 days84 days14 daysunclear
Discount from original list9.3%8.6%9.4%3.4%unclear
Price cut before sale60%50%78%40%unclear
Seller paid closing costs or repairs20%80%78%60%unclear
Has a view20%0%11%10%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

2026-11-08T07:41:21.533080 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $336K 10 sales $336K– $387K 10 sales $387K– $409K 9 sales Over $409K 10 sales $0 $100 $200 $217 $235 $242 $236 Net price per SF, average

The average is $236 per SF for homes over $409K and $217 per SF for homes under $336K. It does not move in a straight line; homes $387K–$409K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $409K are about 560 SF (39%) larger than homes under $336K

2026-11-08T07:41:21.555012 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $336K 10 sales $336K– $387K 10 sales $387K– $409K 9 sales Over $409K 10 sales 0 1,000 2,000 1,425 1,580 1,668 1,983 Living area (SF), average

The average is 1,983 SF for homes over $409K and 1,425 SF for homes under $336K. 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

2026-11-08T07:41:21.578432 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $336K 10 sales $336K– $387K 10 sales $387K– $409K 9 sales Over $409K 10 sales 1984 1987 1990 1993 1984 1985 1984 1989 Year built: median (dot) and middle half (bar)

The median is 1989 for homes over $409K and 1984 for homes under $336K. It does not move in a straight line; homes over $409K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-08T07:41:21.601312 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $336K 10 sales $336K– $387K 10 sales $387K– $409K 9 sales Over $409K 10 sales 0 50 100 60 24 84 14 Days on market, median

The median is 14 days for homes over $409K and 60 days for homes under $336K. It does not move in a straight line; homes $387K–$409K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-08T07:41:21.622933 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $336K 10 sales $336K– $387K 10 sales $387K– $409K 9 sales Over $409K 10 sales 0.0% 5.0% 10.0% 9.3% 8.6% 9.4% 3.4% Discount from original list, average

The average is 3.4% for homes over $409K and 9.3% for homes under $336K. It does not move in a straight line; homes $387K–$409K 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

2026-11-08T07:41:21.651553 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% 60% 20% 20% 50% 80% 0% 78% 78% 11% 40% 60% 10% Under $336K $336K–$387K $387K–$409K Over $409K

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

  • 40% of homes over $409K had a price cut before sale, against 60% of homes under $336K. Defined in 8.1.7.
  • 60% of homes over $409K had the seller pay closing costs or repairs, against 20% of homes under $336K. Defined in 8.1.8.
  • 10% of homes over $409K have a view, against 20% of homes under $336K. 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 $336K10 sales$336K–$387K10 sales$387K–$409K9 salesOver $409K10 salesAll39 salesReal difference?
Net sale price average$292,416$362,392$395,203$461,084$377,327by design
Net price per SF average$217$235$242$236$232unclear
Living area average1,4251,5801,6681,9831,664✓ large
Year built median19841985198419891985unclear

3.10 The numbers: selling

Under $336K10 sales$336K–$387K10 sales$387K–$409K9 salesOver $409K10 salesAll39 salesReal difference?
Days on market median6024841448unclear
Discount from original list average9.3%8.6%9.4%3.4%7.6%unclear
Price cut before sale60%50%78%40%56%unclear
Seller paid closing costs or repairs20%80%78%60%59%unclear
Has a view20%0%11%10%10%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 · 39 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.

2026-11-08T07:41:21.672045 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 9 10 39 sales Sales per group Under 1,428 SF: 10 sales (26%) 1,428–1,542 SF: 10 sales (26%) 1,642–1,951 SF: 9 sales (23%) Over 1,951 SF: 10 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 1,428 SF1,428–1,542 SF1,642–1,951 SFOver 1,951 SF
Larger homes Over 1,951 SF
  • Sell for less per square foot.
Smaller homes Under 1,428 SF
  • Sell for more per square foot.

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 1,428 SF1,428–1,542 SF1,642–1,951 SFOver 1,951 SFReal difference?
Net sale price$328K$357K$415K$413Kunclear
Net price per SF$264 per SFHighest$239 per SF$235 per SF$192 per SFLowest✓ large
Year built1984198519851994unclear
Days on market58 days16 days43 days90 daysunclear
Discount from original list6.6%6.1%8.9%9.2%unclear
Price cut before sale50%40%56%80%unclear
Seller paid closing costs or repairs30%70%78%60%unclear
Has a view0%20%0%20%unclear

4.3 Net sale price: no clear difference

2026-11-08T07:41:21.692394 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,428 SF 10 sales 1,428– 1,542 SF 10 sales 1,642– 1,951 SF 9 sales Over 1,951 SF 10 sales $0K $200K $400K $328K $357K $415K $413K Net sale price, average

The average is $413K for homes over 1,951 SF and $328K for homes under 1,428 SF. It does not move in a straight line; homes 1,642–1,951 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Homes over 1,951 SF sell for about $72 per SF (27%) less than homes under 1,428 SF

2026-11-08T07:41:21.714619 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,428 SF 10 sales 1,428– 1,542 SF 10 sales 1,642– 1,951 SF 9 sales Over 1,951 SF 10 sales $0 $100 $200 $300 $264 $239 $235 $192 Net price per SF, average

The average is $192 per SF for homes over 1,951 SF and $264 per SF for homes under 1,428 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

2026-11-08T07:41:21.739079 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,428 SF 10 sales 1,428– 1,542 SF 10 sales 1,642– 1,951 SF 9 sales Over 1,951 SF 10 sales 1984 1987 1990 1993 1996 1984 1985 1985 1994 Year built: median (dot) and middle half (bar)

The median is 1994 for homes over 1,951 SF and 1984 for homes under 1,428 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

2026-11-08T07:41:21.762285 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,428 SF 10 sales 1,428– 1,542 SF 10 sales 1,642– 1,951 SF 9 sales Over 1,951 SF 10 sales 0 50 100 58 16 43 90 Days on market, median

The median is 90 days for homes over 1,951 SF and 58 days for homes under 1,428 SF. It does not move in a straight line; homes over 1,951 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-08T07:41:21.784086 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,428 SF 10 sales 1,428– 1,542 SF 10 sales 1,642– 1,951 SF 9 sales Over 1,951 SF 10 sales 0.0% 5.0% 10.0% 6.6% 6.1% 8.9% 9.2% Discount from original list, average

The average is 9.2% for homes over 1,951 SF and 6.6% for homes under 1,428 SF. It does not move in a straight line; homes over 1,951 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

2026-11-08T07:41:21.809465 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% 30% 0% 40% 70% 20% 56% 78% 0% 80% 60% 20% Under 1,428 SF 1,428–1,542 SF 1,642–1,951 SF Over 1,951 SF

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

  • 80% of homes over 1,951 SF had a price cut before sale, against 50% of homes under 1,428 SF. Defined in 8.1.7.
  • 60% of homes over 1,951 SF had the seller pay closing costs or repairs, against 30% of homes under 1,428 SF. Defined in 8.1.8.
  • 20% of homes over 1,951 SF have a view, against 0% of homes under 1,428 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 1,428 SF10 sales1,428–1,542 SF10 sales1,642–1,951 SF9 salesOver 1,951 SF10 salesAll39 salesReal difference?
Net sale price average$327,730$356,639$415,300$413,436$377,327unclear
Net price per SF average$264$239$235$192$232✓ large
Living area average1,2451,4941,7732,1541,664by design
Year built median19841985198519941985unclear

4.10 The numbers: selling

Under 1,428 SF10 sales1,428–1,542 SF10 sales1,642–1,951 SF9 salesOver 1,951 SF10 salesAll39 salesReal difference?
Days on market median5816439048unclear
Discount from original list average6.6%6.1%8.9%9.2%7.6%unclear
Price cut before sale50%40%56%80%56%unclear
Seller paid closing costs or repairs30%70%78%60%59%unclear
Has a view0%20%0%20%10%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 · 39 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.

2026-11-08T07:41:21.829604 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 8 13 11 39 sales Sales per group Before 1984: 7 sales (18%) 1984: 8 sales (21%) 1985–1986: 13 sales (33%) After 1986: 11 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$360K$358K$372K$409Kunclear
Net price per SF$222 per SF$247 per SF$242 per SF$217 per SFunclear
Living area1,662 SF1,472 SF1,578 SF1,906 SFunclear
Days on market66 days20 days27 days43 daysunclear
Discount from original list10.6%7.3%6.8%7.0%unclear
Price cut before sale71%50%54%55%unclear
Seller paid closing costs or repairs71%62%54%55%unclear
Has a view29%0%8%9%unclear

5.3 Net sale price: no clear difference

2026-11-08T07:41:21.849896 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 7 sales 1984 8 sales 1985– 1986 13 sales After 1986 11 sales $0K $200K $400K $360K $358K $372K $409K Net sale price, average

The average is $409K for homes built after 1986 and $360K 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

2026-11-08T07:41:21.872375 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 7 sales 1984 8 sales 1985– 1986 13 sales After 1986 11 sales $0 $100 $200 $222 $247 $242 $217 Net price per SF, average

The average is $217 per SF for homes built after 1986 and $222 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

2026-11-08T07:41:21.893522 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 7 sales 1984 8 sales 1985– 1986 13 sales After 1986 11 sales 0 1,000 2,000 1,662 1,472 1,578 1,906 Living area (SF), average

The average is 1,906 SF for homes built after 1986 and 1,662 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

2026-11-08T07:41:21.914610 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 7 sales 1984 8 sales 1985– 1986 13 sales After 1986 11 sales 0 20 40 60 66 20 27 43 Days on market, median

The median is 43 days for homes built after 1986 and 66 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

2026-11-08T07:41:21.937160 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 7 sales 1984 8 sales 1985– 1986 13 sales After 1986 11 sales 0.0% 5.0% 10.0% 10.6% 7.3% 6.8% 7.0% Discount from original list, average

The average is 7.0% for homes built after 1986 and 10.6% 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

2026-11-08T07:41:21.961235 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% 71% 71% 29% 50% 62% 0% 54% 54% 8% 55% 55% 9% Before 1984 1984 1985–1986 After 1986

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

  • 55% of homes built after 1986 had a price cut before sale, against 71% of homes built before 1984. Defined in 8.1.7.
  • 55% of homes built after 1986 had the seller pay closing costs or repairs, against 71% of homes built before 1984. Defined in 8.1.8.
  • 9% of homes built after 1986 have a view, against 29% 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 19847 sales19848 sales1985–198613 salesAfter 198611 salesAll39 salesReal difference?
Net sale price average$359,719$358,380$371,566$409,120$377,327unclear
Net price per SF average$222$247$242$217$232unclear
Living area average1,6621,4721,5781,9061,664unclear
Year built median19831984198519961985by design

5.10 The numbers: selling

Before 19847 sales19848 sales1985–198613 salesAfter 198611 salesAll39 salesReal difference?
Days on market median6620274348unclear
Discount from original list average10.6%7.3%6.8%7.0%7.6%unclear
Price cut before sale71%50%54%55%56%unclear
Seller paid closing costs or repairs71%62%54%55%59%unclear
Has a view29%0%8%9%10%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 · 39 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.

2026-11-08T07:41:21.979388 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 35 39 sales Sales per group View: 4 sales (10%) No view: 35 sales (90%)
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

2026-11-08T07:41:21.995712 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 35 sales $0K $100K $200K $300K $400K $364K $379K Net sale price, average

The average is $364K for homes with a view and $379K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-11-08T07:41:22.013860 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 35 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

2026-11-08T07:41:22.053473 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 35 sales 0 500 1,000 1,500 2,000 1,964 1,630 Living area (SF), average

The average is 1,964 SF for homes with a view and 1,630 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-11-08T07:41:22.072228 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 35 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

2026-11-08T07:41:22.089991 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 35 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

2026-11-08T07:41:22.109583 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 35 sales 0.0% 2.5% 5.0% 7.5% 10.0% 9.6% 7.4% Discount from original list, average

The average is 9.6% for homes with a view and 7.4% 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

2026-11-08T07:41:22.127542 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 50% 25% 57% 63% 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 57% 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 63% 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 view35 salesAll39 sales
Net sale price average$364,498$378,793$377,327
Net price per SF average$187$237$232
Living area average1,9641,6301,664
Year built median198419851985

6.11 The numbers: selling

View4 salesNo view35 salesAll39 sales
Days on market median714348
Discount from original list average9.6%7.4%7.6%
Price cut before sale50%57%56%
Seller paid closing costs or repairs25%63%59%

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 Wells Branch.

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
39 resale sales. Average $377,327; median $386,844; standard deviation $68,756; middle half (25th–75th percentile) $330,250–$409,350; lowest $220,760, highest $549,000. 23 sales had a seller payment; their median payment was $5,500.

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
39 resale sales. Average $232; median $236; standard deviation $42; middle half (25th–75th percentile) $205–$261; 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
39 resale sales. Average 1,664; median 1,542; standard deviation 370; middle half (25th–75th percentile) 1,428–1,974; 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
39 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
39 resale sales. Average 62; median 48; standard deviation 66; middle half (25th–75th percentile) 10–91; lowest 0, highest 286. 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
39 resale sales. Average 7.6%; median 7.1%; standard deviation 7.2%; middle half (25th–75th percentile) 2.3%–12.0%; 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
22 of 39 resale sales (56.4%).

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
23 of 39 resale sales (59.0%).

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
4 sales with a view, 35 without, 0 unclassified. Most common View entries: None 30, Neighborhood 6, 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
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 “wells branch”, “village at wells branch” (case-insensitive). A record is kept when its subdivision name belongs to the Wells Branch family, the same rule comparable sales use (it includes Village at Wells Branch, proven adjacent and priced alike).
The data
Pulled November 8, 2026: 39 closed Wells Branch records over the prior year, in ZIP 78728. 18 subdivision spellings kept, the most common: Wells Branch Ph C Sec 01 (5); Wells Branch Ph D Sec 02 (5); Wells Branch (4); Wells Branch Ph D Sec 01 (3); Wells Branch Ph B Sec 03 (3); Wells Branch Ph E Sec 03 (3); Village at Wells Branch (2); Wells Branch Ph F (2); Wells Branch Ph A Sec 01 (2); Wells Branch Ph P Resub (2); Wells Branch Ph W-2A (1); Wells Branch Ph B Sec 01 (1); and 6 more (6 records). Names found by the search but not part of Wells Branch, left out: Wells Branch Phs E Sec 3 (1); WELLS BRANCH PHS R SEC 3 (1); WELLS BRANCH PHS F (1); The Crossing at Wells Branch (1); Lake At Wells Branch Sec 02 (1); WELLS BRANCH PHS A SEC 2 (1); Lake At Wells Branch Sec 01 (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 15 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 8, 2025 to November 7, 2026 inclusive.
The data
39 single-family sales in the window: 39 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
39 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 $336K”.
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 $336K: $220,760–$325,000 (10 sales); $336K–$387K: $335,500–$386,844 (10 sales); $387K–$409K: $387,030–$409,200 (9 sales); Over $409K: $409,500–$549,000 (10 sales)
Quartiles by living area: Under 1,428 SF: 1,007–1,427 SF (10 sales); 1,428–1,542 SF: 1,428–1,542 SF (10 sales); 1,642–1,951 SF: 1,642–1,951 SF (9 sales); Over 1,951 SF: 1,996–2,664 SF (10 sales)
Quartiles by year built: Before 1984: 1982–1983 (7 sales); 1984: 1984–1984 (8 sales); 1985–1986: 1985–1986 (13 sales); After 1986: 1992–2018 (11 sales)
View and no view: View: MLS lists a view (4 sales); No view: None or Neighborhood (35 sales)

8.2.6 Average and median

In simple terms
The average adds the values and divides by how many; one very expensive home can pull it up. The median is the middle value, with half above and half below.
Statistically
Mean x̄ = (1/n) Σ xᵢ; median = 50th percentile. Price, price per SF, living area and discount use the mean; days on market and year built use the median (skewed or whole-year values).
The data
Net sale price: average $377,327, median $386,844. Days on market: average 62, 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
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 = 1.0030.8014p < 0.0063Unclearε² = 0.026small
Living areaKruskal–WallisH = 13.2030.0042p < 0.0063Yesε² = 0.347large
Year builtKruskal–WallisH = 4.6030.2036p < 0.0063Unclearε² = 0.121medium
Days on marketKruskal–WallisH = 1.4930.6853p < 0.0063Unclearε² = 0.039small
Discount from original listKruskal–WallisH = 5.1130.1641p < 0.0063Unclearε² = 0.134medium
Price cut before saleChi-squareχ² = 2.9930.3938p < 0.0063UnclearCramér’s V = 0.277small
Seller paid closing costs or repairsChi-squareχ² = 9.4330.0241p < 0.0063UnclearCramér’s V = 0.492medium
Has a viewChi-squareχ² = 2.1830.5355p < 0.0063UnclearCramér’s V = 0.237small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 12.0430.0072p < 0.0063Unclearε² = 0.317large
Net price per SFKruskal–WallisH = 16.2530.0010p < 0.0063Yesε² = 0.428large
Year builtKruskal–WallisH = 4.4930.2130p < 0.0063Unclearε² = 0.118medium
Days on marketKruskal–WallisH = 4.5530.2081p < 0.0063Unclearε² = 0.120medium
Discount from original listKruskal–WallisH = 2.1530.5415p < 0.0063Unclearε² = 0.057small
Price cut before saleChi-squareχ² = 3.5330.3171p < 0.0063UnclearCramér’s V = 0.301medium
Seller paid closing costs or repairsChi-squareχ² = 5.2930.1516p < 0.0063UnclearCramér’s V = 0.368medium
Has a viewChi-squareχ² = 4.2330.2373p < 0.0063UnclearCramér’s V = 0.330medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 2.8530.4159p < 0.0063Unclearε² = 0.075medium
Net price per SFKruskal–WallisH = 4.0830.2533p < 0.0063Unclearε² = 0.107medium
Living areaKruskal–WallisH = 7.0030.0719p < 0.0063Unclearε² = 0.184large
Days on marketKruskal–WallisH = 1.3530.7180p < 0.0063Unclearε² = 0.035small
Discount from original listKruskal–WallisH = 2.2730.5179p < 0.0063Unclearε² = 0.060small
Price cut before saleChi-squareχ² = 0.8330.8432p < 0.0063UnclearCramér’s V = 0.146small
Seller paid closing costs or repairsChi-squareχ² = 0.7230.8684p < 0.0063UnclearCramér’s V = 0.136small
Has a viewChi-squareχ² = 3.5730.3112p < 0.0063UnclearCramér’s V = 0.303medium

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 39 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.