ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Woodstone Village

Austin, TX 78749
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 4:00 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
25
single-family resale homes
Median net sale price
$424,000
average $415,838
Median net price per SF
$289
average $294
Median days on market
35 days
average 50 days
1. SummaryResale homes · 25 sales · October 26, 2025 – October 25, 2026

This study looks at the 25 resale homes sold in Woodstone Village in the 365 days to October 25, 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 sold25 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 $334K · 6 sales$334K–$423K · 6 sales$424K–$496K · 7 salesOver $496K · 6 sales
3. Quartiles by net sale priceResale homes · 25 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T04:01:04.346002 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 7 6 25 sales Sales per group Under $334K: 6 sales (24%) $334K–$423K: 6 sales (24%) $424K–$496K: 7 sales (28%) Over $496K: 6 sales (24%)
Bottom line

3.1 Key differences

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

Under $334K$334K–$423K$424K–$496KOver $496K
Higher-priced homes Over $496K
  • Sell for more per square foot.
Lower-priced homes Under $334K
  • Sell for less per square foot.

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 $334K$334K–$423K$424K–$496KOver $496KReal difference?
Net price per SF$220 per SFLowest$274 per SF$316 per SF$361 per SFHighest✓ large
Living area1,296 SF1,409 SF1,445 SF1,502 SFunclear
Year built1978197919811980unclear
Days on market16 days76 days10 days37 daysunclear
Discount from original list6.5%11.3%3.8%5.3%unclear
Price cut before sale17%67%14%33%unclear
Seller paid closing costs or repairs17%33%86%83%unclear
Has a view17%0%14%17%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 Homes over $496K sell for about $141 per SF (64%) more than homes under $334K

2026-10-26T04:01:04.374597 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $334K 6 sales $334K– $423K 6 sales $424K– $496K 7 sales Over $496K 6 sales $0 $200 $400 $220 $274 $316 $361 Net price per SF, average

The average is $361 per SF for homes over $496K and $220 per SF for homes under $334K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Living area: no clear difference

2026-10-26T04:01:04.397075 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $334K 6 sales $334K– $423K 6 sales $424K– $496K 7 sales Over $496K 6 sales 0 500 1,000 1,500 1,296 1,409 1,445 1,502 Living area (SF), average

The average is 1,502 SF for homes over $496K and 1,296 SF for homes under $334K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-26T04:01:04.420934 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $334K 6 sales $334K– $423K 6 sales $424K– $496K 7 sales Over $496K 6 sales 1978 1980 1982 1978 1979 1981 1980 Year built: median (dot) and middle half (bar)

The median is 1980 for homes over $496K and 1978 for homes under $334K. It does not move in a straight line; homes $424K–$496K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T04:01:04.444542 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $334K 6 sales $334K– $423K 6 sales $424K– $496K 7 sales Over $496K 6 sales 0 25 50 75 16 76 10 37 Days on market, median

The median is 37 days for homes over $496K and 16 days for homes under $334K. It does not move in a straight line; homes $334K–$423K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T04:01:04.467292 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $334K 6 sales $334K– $423K 6 sales $424K– $496K 7 sales Over $496K 6 sales 0.0% 5.0% 10.0% 6.5% 11.3% 3.8% 5.3% Discount from original list, average

The average is 5.3% for homes over $496K and 6.5% for homes under $334K. It does not move in a straight line; homes $334K–$423K 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

2026-10-26T04:01:04.497292 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% 17 17 17 67 33 0 14 86 14 33 83 17 Under $334K $334K–$423K $424K–$496K Over $496K

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

  • 33% of homes over $496K had a price cut before sale, against 17% of homes under $334K. Defined in 8.1.7.
  • 83% of homes over $496K had the seller pay closing costs or repairs, against 17% of homes under $334K. Defined in 8.1.8.
  • 17% of homes over $496K have a view, against 17% of homes under $334K. 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 $334K6 sales$334K–$423K6 sales$424K–$496K7 salesOver $496K6 salesAll25 salesReal difference?
Net sale price average$284,708$385,504$449,383$538,167$415,838by design
Net price per SF average$220$274$316$361$294✓ large
Living area average1,2961,4091,4451,5021,414unclear
Year built median19781979198119801979unclear

3.10 The numbers: selling

Under $334K6 sales$334K–$423K6 sales$424K–$496K7 salesOver $496K6 salesAll25 salesReal difference?
Days on market median1676103735unclear
Discount from original list average6.5%11.3%3.8%5.3%6.6%unclear
Price cut before sale17%67%14%33%32%unclear
Seller paid closing costs or repairs17%33%86%83%56%unclear
Has a view17%0%14%17%12%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 · 25 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T04:01:04.518045 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 7 6 25 sales Sales per group Under 1,312 SF: 6 sales (24%) 1,312–1,392 SF: 6 sales (24%) 1,409–1,469 SF: 7 sales (28%) Over 1,469 SF: 6 sales (24%)
Bottom line: no measure differs enough between the groups to rule out chance.

4.1 Key differences

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

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 1,312 SF1,312–1,392 SF1,409–1,469 SFOver 1,469 SFReal difference?
Net sale price$364K$396K$417K$487Kunclear
Net price per SF$294 per SF$295 per SF$288 per SF$300 per SFunclear
Year built1980197719801981unclear
Days on market16 days22 days41 days36 daysunclear
Discount from original list0.8%11.6%9.0%4.5%unclear
Price cut before sale17%33%57%17%unclear
Seller paid closing costs or repairs50%50%43%83%unclear
Has a view17%17%0%17%unclear

4.3 Net sale price: no clear difference

2026-10-26T04:01:04.539306 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,312 SF 6 sales 1,312– 1,392 SF 6 sales 1,409– 1,469 SF 7 sales Over 1,469 SF 6 sales $0K $200K $400K $364K $396K $417K $487K Net sale price, average

The average is $487K for homes over 1,469 SF and $364K for homes under 1,312 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-10-26T04:01:04.562410 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,312 SF 6 sales 1,312– 1,392 SF 6 sales 1,409– 1,469 SF 7 sales Over 1,469 SF 6 sales $0 $100 $200 $300 $294 $295 $288 $300 Net price per SF, average

The average is $300 per SF for homes over 1,469 SF and $294 per SF for homes under 1,312 SF. It does not move in a straight line; homes over 1,469 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T04:01:04.587387 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,312 SF 6 sales 1,312– 1,392 SF 6 sales 1,409– 1,469 SF 7 sales Over 1,469 SF 6 sales 1976 1978 1980 1982 1980 1977 1980 1981 Year built: median (dot) and middle half (bar)

The median is 1981 for homes over 1,469 SF and 1980 for homes under 1,312 SF. It does not move in a straight line; homes over 1,469 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T04:01:04.610557 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,312 SF 6 sales 1,312– 1,392 SF 6 sales 1,409– 1,469 SF 7 sales Over 1,469 SF 6 sales 0 20 40 16 22 41 36 Days on market, median

The median is 36 days for homes over 1,469 SF and 16 days for homes under 1,312 SF. It does not move in a straight line; homes 1,409–1,469 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T04:01:04.633188 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,312 SF 6 sales 1,312– 1,392 SF 6 sales 1,409– 1,469 SF 7 sales Over 1,469 SF 6 sales 0.0% 5.0% 10.0% 0.8% 11.6% 9.0% 4.5% Discount from original list, average

The average is 4.5% for homes over 1,469 SF and 0.8% for homes under 1,312 SF. It does not move in a straight line; homes 1,312–1,392 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

2026-10-26T04:01:04.659890 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% 17 50 17 33 50 17 57 43 0 17 83 17 Under 1,312 SF 1,312–1,392 SF 1,409–1,469 SF Over 1,469 SF

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

  • 17% of homes over 1,469 SF had a price cut before sale, against 17% of homes under 1,312 SF. Defined in 8.1.7.
  • 83% of homes over 1,469 SF had the seller pay closing costs or repairs, against 50% of homes under 1,312 SF. Defined in 8.1.8.
  • 17% of homes over 1,469 SF have a view, against 17% of homes under 1,312 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 1,312 SF6 sales1,312–1,392 SF6 sales1,409–1,469 SF7 salesOver 1,469 SF6 salesAll25 salesReal difference?
Net sale price average$363,500$396,250$416,896$486,530$415,838unclear
Net price per SF average$294$295$288$300$294unclear
Living area average1,2301,3451,4491,6271,414by design
Year built median19801977198019811979unclear

4.10 The numbers: selling

Under 1,312 SF6 sales1,312–1,392 SF6 sales1,409–1,469 SF7 salesOver 1,469 SF6 salesAll25 salesReal difference?
Days on market median1622413635unclear
Discount from original list average0.8%11.6%9.0%4.5%6.6%unclear
Price cut before sale17%33%57%17%32%unclear
Seller paid closing costs or repairs50%50%43%83%56%unclear
Has a view17%17%0%17%12%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 · 25 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T04:01:04.680571 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 8 5 7 25 sales Sales per group Before 1978: 5 sales (20%) 1978–1979: 8 sales (32%) 1980–1982: 5 sales (20%) After 1982: 7 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 19781978–19791980–1982After 1982Real difference?
Net sale price$370K$416K$432K$438Kunclear
Net price per SF$288 per SF$284 per SF$293 per SF$309 per SFunclear
Living area1,274 SF1,451 SF1,468 SF1,434 SFunclear
Days on market35 days40 days10 days36 daysunclear
Discount from original list9.3%10.8%-1.1%5.4%unclear
Price cut before sale40%50%20%14%unclear
Seller paid closing costs or repairs60%38%80%57%unclear
Has a view0%12%20%14%unclear

5.3 Net sale price: no clear difference

2026-10-26T04:01:04.701635 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1978 5 sales 1978– 1979 8 sales 1980– 1982 5 sales After 1982 7 sales $0K $200K $400K $370K $416K $432K $438K Net sale price, average

The average is $438K for homes built after 1982 and $370K for homes built before 1978. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T04:01:04.724381 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1978 5 sales 1978– 1979 8 sales 1980– 1982 5 sales After 1982 7 sales $0 $100 $200 $300 $288 $284 $293 $309 Net price per SF, average

The average is $309 per SF for homes built after 1982 and $288 per SF for homes built before 1978. It does not move in a straight line; homes built after 1982 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T04:01:04.746285 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1978 5 sales 1978– 1979 8 sales 1980– 1982 5 sales After 1982 7 sales 0 500 1,000 1,500 1,274 1,451 1,468 1,434 Living area (SF), average

The average is 1,434 SF for homes built after 1982 and 1,274 SF for homes built before 1978. It does not move in a straight line; homes built 1980–1982 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T04:01:04.768283 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1978 5 sales 1978– 1979 8 sales 1980– 1982 5 sales After 1982 7 sales 0 20 40 35 40 10 36 Days on market, median

The median is 36 days for homes built after 1982 and 35 days for homes built before 1978. It does not move in a straight line; homes built 1978–1979 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T04:01:04.791394 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1978 5 sales 1978– 1979 8 sales 1980– 1982 5 sales After 1982 7 sales 0.0% 5.0% 10.0% 9.3% 10.8% -1.1% 5.4% Discount from original list, average

The average is 5.4% for homes built after 1982 and 9.3% for homes built before 1978. It does not move in a straight line; homes built 1978–1979 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

2026-10-26T04:01:04.817200 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% 40 60 0 50 38 12 20 80 20 14 57 14 Before 1978 1978–1979 1980–1982 After 1982

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

  • 14% of homes built after 1982 had a price cut before sale, against 40% of homes built before 1978. Defined in 8.1.7.
  • 57% of homes built after 1982 had the seller pay closing costs or repairs, against 60% of homes built before 1978. Defined in 8.1.8.
  • 14% of homes built after 1982 have a view, against 0% of homes built before 1978. 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 19785 sales1978–19798 sales1980–19825 salesAfter 19827 salesAll25 salesReal difference?
Net sale price average$369,500$415,612$431,600$437,937$415,838unclear
Net price per SF average$288$284$293$309$294unclear
Living area average1,2741,4511,4681,4341,414unclear
Year built median19761979198119831979by design

5.10 The numbers: selling

Before 19785 sales1978–19798 sales1980–19825 salesAfter 19827 salesAll25 salesReal difference?
Days on market median3540103635unclear
Discount from original list average9.3%10.8%−1.1%5.4%6.6%unclear
Price cut before sale40%50%20%14%32%unclear
Seller paid closing costs or repairs60%38%80%57%56%unclear
Has a view0%12%20%14%12%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 · 25 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T04:01:04.836274 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 22 25 sales Sales per group View: 3 sales (12%) No view: 22 sales (88%)
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

2026-10-26T04:01:04.852536 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 22 sales $0K $200K $400K $438K $413K Net sale price, average

The average is $438K for homes with a view and $413K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T04:01:04.870053 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 22 sales $0 $100 $200 $300 $306 $292 Net price per SF, average

The average is $306 per SF for homes with a view and $292 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T04:01:04.888574 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 22 sales 0 500 1,000 1,500 1,483 1,405 Living area (SF), average

The average is 1,483 SF for homes with a view and 1,405 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T04:01:04.933504 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 22 sales 1978 1980 1982 1982 1979 Year built: median (dot) and middle half (bar)

The median is 1982 for homes with a view and 1979 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T04:01:04.952050 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 22 sales 0 10 20 30 40 36 35 Days on market, median

The median is 36 days for homes with a view and 35 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

2026-10-26T04:01:04.970669 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 22 sales 0.0% 5.0% 10.0% 15.0% 13.2% 5.7% Discount from original list, average

The average is 13.2% for homes with a view and 5.7% 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

2026-10-26T04:01:04.989537 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 33 67 32 55 View No view

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

  • 33% of homes with a view had a price cut before sale, against 32% of homes without a view. Defined in 8.1.7.
  • 67% of homes with a view had the seller pay closing costs or repairs, against 55% 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

View3 salesNo view22 salesAll25 sales
Net sale price average$438,000$412,816$415,838
Net price per SF average$306$292$294
Living area average1,4831,4051,414
Year built median198219791979

6.11 The numbers: selling

View3 salesNo view22 salesAll25 sales
Days on market median363535
Discount from original list average13.2%5.7%6.6%
Price cut before sale33%32%32%
Seller paid closing costs or repairs67%55%56%

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

7. New constructionBasic statistics · 0 sales · October 26, 2025 – October 25, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 0 sales, no groups, no tests.

Note: these are only the new-construction sales reported in ABOR MLS. Builders often sell homes without listing them in the MLS, so these figures do not necessarily represent all new-construction sales in Woodstone Village.

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
25 resale sales. Average $415,838; median $424,000; standard deviation $98,288; middle half (25th–75th percentile) $334,000–$495,500; lowest $230,000, highest $570,000. 14 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
25 resale sales. Average $294; median $289; standard deviation $64; middle half (25th–75th percentile) $234–$344; lowest $192, highest $453.

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
25 resale sales. Average 1,414; median 1,409; standard deviation 158; middle half (25th–75th percentile) 1,312–1,469; lowest 1,119, highest 1,812.

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
25 resale sales. Average 1980; median 1979; standard deviation 3; middle half (25th–75th percentile) 1978–1983; lowest 1976, highest 1984.

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
25 resale sales. Average 50; median 35; standard deviation 53; middle half (25th–75th percentile) 7–73; lowest 3, highest 196. 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
25 resale sales. Average 6.6%; median 5.0%; standard deviation 10.2%; middle half (25th–75th percentile) 2.5%–12.3%; lowest −28.1%, highest 24.1%. 1 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
8 of 25 resale sales (32.0%).

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
14 of 25 resale sales (56.0%).

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
3 sales with a view, 22 without, 0 unclassified. Most common View entries: None 13, Neighborhood 11, Creek/Stream 2, Trees/Woods 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 “woodstone village” (case-insensitive). A record is kept when its subdivision name belongs to the Woodstone Village family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 25 closed Woodstone Village records over the prior year, in ZIP 78749. 7 subdivision spellings kept: Woodstone Village Sec 01 (6); Woodstone Village Sec 06 (4); Woodstone Village Sec 03 (4); Woodstone Village Sec 04 (4); Woodstone Village Sec 02 (3); Woodstone Village (2); Woodstone Village 06-A (2). No other names were found by the search.

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 26, 2025 to October 25, 2026 inclusive.
The data
25 single-family sales in the window: 25 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
25 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 $334K”.
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 $334K: $230,000–$320,000 (6 sales); $334K–$423K: $334,000–$423,000 (6 sales); $424K–$496K: $424,000–$495,500 (7 sales); Over $496K: $498,000–$570,000 (6 sales)
Quartiles by living area: Under 1,312 SF: 1,119–1,311 SF (6 sales); 1,312–1,392 SF: 1,312–1,392 SF (6 sales); 1,409–1,469 SF: 1,409–1,469 SF (7 sales); Over 1,469 SF: 1,498–1,812 SF (6 sales)
Quartiles by year built: Before 1978: 1976–1976 (5 sales); 1978–1979: 1978–1979 (8 sales); 1980–1982: 1980–1982 (5 sales); After 1982: 1983–1984 (7 sales)
View and no view: View: MLS lists a view (3 sales); No view: None or Neighborhood (22 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 $415,838, median $424,000. Days on market: average 50, median 35: 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
1 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 = 16.1630.0011p < 0.0063Yesε² = 0.673large
Living areaKruskal–WallisH = 5.7630.1237p < 0.0063Unclearε² = 0.240large
Year builtKruskal–WallisH = 1.3930.7086p < 0.0063Unclearε² = 0.058small
Days on marketKruskal–WallisH = 3.2630.3536p < 0.0063Unclearε² = 0.136medium
Discount from original listKruskal–WallisH = 5.0330.1697p < 0.0063Unclearε² = 0.210large
Price cut before saleChi-squareχ² = 4.9830.1735p < 0.0063UnclearCramér’s V = 0.446medium
Seller paid closing costs or repairsChi-squareχ² = 9.3530.0250p < 0.0063UnclearCramér’s V = 0.611large
Has a viewChi-squareχ² = 1.1030.7770p < 0.0063UnclearCramér’s V = 0.210small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 4.6930.1958p < 0.0063Unclearε² = 0.196large
Net price per SFKruskal–WallisH = 0.3830.9450p < 0.0063Unclearε² = 0.016small
Year builtKruskal–WallisH = 5.9930.1120p < 0.0063Unclearε² = 0.250large
Days on marketKruskal–WallisH = 3.7330.2921p < 0.0063Unclearε² = 0.155large
Discount from original listKruskal–WallisH = 2.4030.4940p < 0.0063Unclearε² = 0.100medium
Price cut before saleChi-squareχ² = 3.3430.3428p < 0.0063UnclearCramér’s V = 0.365medium
Seller paid closing costs or repairsChi-squareχ² = 2.4930.4780p < 0.0063UnclearCramér’s V = 0.315medium
Has a viewChi-squareχ² = 1.3330.7230p < 0.0063UnclearCramér’s V = 0.230small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 1.6130.6579p < 0.0063Unclearε² = 0.067medium
Net price per SFKruskal–WallisH = 0.2530.9691p < 0.0063Unclearε² = 0.010small
Living areaKruskal–WallisH = 6.1030.1070p < 0.0063Unclearε² = 0.254large
Days on marketKruskal–WallisH = 1.3930.7080p < 0.0063Unclearε² = 0.058small
Discount from original listKruskal–WallisH = 4.7430.1919p < 0.0063Unclearε² = 0.197large
Price cut before saleChi-squareχ² = 2.6830.4439p < 0.0063UnclearCramér’s V = 0.327medium
Seller paid closing costs or repairsChi-squareχ² = 2.3230.5094p < 0.0063UnclearCramér’s V = 0.304medium
Has a viewChi-squareχ² = 1.0230.7961p < 0.0063UnclearCramér’s V = 0.202small

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 25 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 26, 2026. Map data © OpenStreetMap contributors. ALEX Companies · Licensed by the Texas Real Estate Commission · Broker: Alexander Tiffany Southwest, LLC (ALEX Real Estate), #565194-BB · Diane Hart Alexander, Designated Broker, #574877-B.