ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Windsor Park

Austin, TX 78723
Resale homes · closed Nov 9 – Nov 8, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 9, 2026 · 5:14 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
25
single-family resale homes
Median net sale price
$518,500
average $509,964
Median net price per SF
$347
average $336
Median days on market
66 days
average 90 days
1. SummaryResale homes · 25 sales · November 9, 2025 – November 8, 2026

This study looks at the 25 resale homes sold in Windsor Park in the 365 days to November 8, 2026. A full year is used because only 9 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 $389K · 6 sales$389K–$517K · 6 sales$518K–$633K · 7 salesOver $633K · 6 sales
3. Quartiles by net sale priceResale homes · 25 sales · November 9, 2025 – November 8, 2026

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

2026-11-09T05:14:57.829691 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 7 6 25 sales Sales per group Under $389K: 6 sales (24%) $389K–$517K: 6 sales (24%) $518K–$633K: 7 sales (28%) Over $633K: 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 $389K$389K–$517K$518K–$633KOver $633K
Higher-priced homes Over $633K
  • Are much larger.
  • Sell for more per square foot.
Lower-priced homes Under $389K
  • Are much smaller.
  • 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 $389K$389K–$517K$518K–$633KOver $633KReal difference?
Net price per SF$248 per SFLowest$356 per SF$349 per SF$387 per SFHighest✓ large
Living area1,183 SFSmallest1,284 SF1,741 SF1,838 SFLargest✓ large
Year built1958195619571956unclear
Days on market134 days42 days111 days40 daysunclear
Discount from original list19.7%7.8%9.7%5.5%unclear
Price cut before sale67%50%57%50%unclear
Seller paid closing costs or repairs0%67%71%33%unclear
Has a view17%0%29%0%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 $633K sell for about $139 per SF (56%) more than homes under $389K

2026-11-09T05:14:57.860222 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $389K 6 sales $389K– $517K 6 sales $518K– $633K 7 sales Over $633K 6 sales $0 $200 $400 $248 $356 $349 $387 Net price per SF, average

The average is $387 per SF for homes over $633K and $248 per SF for homes under $389K. It does not move in a straight line; homes over $633K are highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $633K are about 660 SF (55%) larger than homes under $389K

2026-11-09T05:14:57.884694 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $389K 6 sales $389K– $517K 6 sales $518K– $633K 7 sales Over $633K 6 sales 0 1,000 2,000 1,183 1,284 1,741 1,838 Living area (SF), average

The average is 1,838 SF for homes over $633K and 1,183 SF for homes under $389K. 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

2026-11-09T05:14:57.908792 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $389K 6 sales $389K– $517K 6 sales $518K– $633K 7 sales Over $633K 6 sales 1956 1958 1960 1958 1956 1957 1956 Year built: median (dot) and middle half (bar)

The median is 1956 for homes over $633K and 1958 for homes under $389K. It does not move in a straight line; homes under $389K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-09T05:14:57.931690 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $389K 6 sales $389K– $517K 6 sales $518K– $633K 7 sales Over $633K 6 sales 0 50 100 150 134 42 111 40 Days on market, median

The median is 40 days for homes over $633K and 134 days for homes under $389K. It does not move in a straight line; homes under $389K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-09T05:14:57.956120 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $389K 6 sales $389K– $517K 6 sales $518K– $633K 7 sales Over $633K 6 sales 0.0% 10.0% 20.0% 19.7% 7.8% 9.7% 5.5% Discount from original list, average

The average is 5.5% for homes over $633K and 19.7% for homes under $389K. It does not move in a straight line; homes under $389K 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

2026-11-09T05:14:57.987995 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% 67% 0% 17% 50% 67% 0% 57% 71% 29% 50% 33% 0% Under $389K $389K–$517K $518K–$633K Over $633K

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

  • 50% of homes over $633K had a price cut before sale, against 67% of homes under $389K. Defined in 8.1.7.
  • 33% of homes over $633K had the seller pay closing costs or repairs, against 0% of homes under $389K. Defined in 8.1.8.
  • 0% of homes over $633K have a view, against 17% of homes under $389K. 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 $389K6 sales$389K–$517K6 sales$518K–$633K7 salesOver $633K6 salesAll25 salesReal difference?
Net sale price average$287,150$453,542$577,643$710,242$509,964by design
Net price per SF average$248$356$349$387$336✓ large
Living area average1,1831,2841,7411,8381,521✓ large
Year built median19581956195719561957unclear

3.10 The numbers: selling

Under $389K6 sales$389K–$517K6 sales$518K–$633K7 salesOver $633K6 salesAll25 salesReal difference?
Days on market median134421114066unclear
Discount from original list average19.7%7.8%9.7%5.5%10.6%unclear
Price cut before sale67%50%57%50%56%unclear
Seller paid closing costs or repairs0%67%71%33%44%unclear
Has a view17%0%29%0%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 · November 9, 2025 – November 8, 2026

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

2026-11-09T05:14:58.011357 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 7 7 6 25 sales Sales per group Under 1,188 SF: 5 sales (20%) 1,188–1,438 SF: 7 sales (28%) 1,495–1,812 SF: 7 sales (28%) Over 1,812 SF: 6 sales (24%)
Bottom line

4.1 Key differences

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

Under 1,188 SF1,188–1,438 SF1,495–1,812 SFOver 1,812 SF
Larger homes Over 1,812 SF
  • Sell for much more.
Smaller homes Under 1,188 SF
  • Sell for much less.

4.2 At a glance

Shaded rows are real differences; the darkest cell is the highest. Gray rows show no clear difference. Prices are averages; days on market and year built are medians.

Under 1,188 SF1,188–1,438 SF1,495–1,812 SFOver 1,812 SFReal difference?
Net sale price$382KLowest$404K$579K$660KHighest✓ large
Net price per SF$369 per SF$303 per SF$352 per SF$326 per SFunclear
Year built1958195619571956unclear
Days on market28 days131 days58 days58 daysunclear
Discount from original list7.4%15.5%11.4%6.8%unclear
Price cut before sale40%71%71%33%unclear
Seller paid closing costs or repairs20%43%29%83%unclear
Has a view40%0%14%0%unclear

4.3 Homes over 1,812 SF sell for about $278K (73%) more than homes under 1,188 SF

2026-11-09T05:14:58.033428 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,188 SF 5 sales 1,188– 1,438 SF 7 sales 1,495– 1,812 SF 7 sales Over 1,812 SF 6 sales $0K $200K $400K $600K $382K $404K $579K $660K Net sale price, average

The average is $660K for homes over 1,812 SF and $382K for homes under 1,188 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-11-09T05:14:58.057785 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,188 SF 5 sales 1,188– 1,438 SF 7 sales 1,495– 1,812 SF 7 sales Over 1,812 SF 6 sales $0 $200 $400 $369 $303 $352 $326 Net price per SF, average

The average is $326 per SF for homes over 1,812 SF and $369 per SF for homes under 1,188 SF. It does not move in a straight line; homes under 1,188 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-09T05:14:58.082752 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,188 SF 5 sales 1,188– 1,438 SF 7 sales 1,495– 1,812 SF 7 sales Over 1,812 SF 6 sales 1955 1956 1957 1958 1958 1956 1957 1956 Year built: median (dot) and middle half (bar)

The median is 1956 for homes over 1,812 SF and 1958 for homes under 1,188 SF. It does not move in a straight line; homes under 1,188 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-09T05:14:58.106649 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,188 SF 5 sales 1,188– 1,438 SF 7 sales 1,495– 1,812 SF 7 sales Over 1,812 SF 6 sales 0 50 100 150 28 131 58 58 Days on market, median

The median is 58 days for homes over 1,812 SF and 28 days for homes under 1,188 SF. It does not move in a straight line; homes 1,188–1,438 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-09T05:14:58.130224 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,188 SF 5 sales 1,188– 1,438 SF 7 sales 1,495– 1,812 SF 7 sales Over 1,812 SF 6 sales 0.0% 5.0% 10.0% 15.0% 7.4% 15.5% 11.4% 6.8% Discount from original list, average

The average is 6.8% for homes over 1,812 SF and 7.4% for homes under 1,188 SF. It does not move in a straight line; homes 1,188–1,438 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

2026-11-09T05:14:58.157546 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% 20% 40% 71% 43% 0% 71% 29% 14% 33% 83% 0% Under 1,188 SF 1,188–1,438 SF 1,495–1,812 SF Over 1,812 SF

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

  • 33% of homes over 1,812 SF had a price cut before sale, against 40% of homes under 1,188 SF. Defined in 8.1.7.
  • 83% of homes over 1,812 SF had the seller pay closing costs or repairs, against 20% of homes under 1,188 SF. Defined in 8.1.8.
  • 0% of homes over 1,812 SF have a view, against 40% of homes under 1,188 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 1,188 SF5 sales1,188–1,438 SF7 sales1,495–1,812 SF7 salesOver 1,812 SF6 salesAll25 salesReal difference?
Net sale price average$382,057$403,553$579,000$660,159$509,964✓ large
Net price per SF average$369$303$352$326$336unclear
Living area average1,0361,3151,6362,0301,521by design
Year built median19581956195719561957unclear

4.10 The numbers: selling

Under 1,188 SF5 sales1,188–1,438 SF7 sales1,495–1,812 SF7 salesOver 1,812 SF6 salesAll25 salesReal difference?
Days on market median28131585866unclear
Discount from original list average7.4%15.5%11.4%6.8%10.6%unclear
Price cut before sale40%71%71%33%56%unclear
Seller paid closing costs or repairs20%43%29%83%44%unclear
Has a view40%0%14%0%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 · November 9, 2025 – November 8, 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.

2026-11-09T05:14:58.181823 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 8 9 4 25 sales Sales per group Before 1955: 4 sales (16%) 1955–1956: 8 sales (32%) 1957–1958: 9 sales (36%) After 1958: 4 sales (16%)
Bottom line: too few sales to test.

5.1 Key differences

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

5.3 Net sale price: described, not tested

2026-11-09T05:14:58.204917 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1955 4 sales 1955– 1956 8 sales 1957– 1958 9 sales After 1958 4 sales $0K $200K $400K $600K $572K $558K $496K $384K Net sale price, average

The average is $384K for homes built after 1958 and $572K for homes built before 1955. It falls step by step from the lowest range to the highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-11-09T05:14:58.228665 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1955 4 sales 1955– 1956 8 sales 1957– 1958 9 sales After 1958 4 sales $0 $200 $400 $369 $346 $341 $268 Net price per SF, average

The average is $268 per SF for homes built after 1958 and $369 per SF for homes built before 1955. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-11-09T05:14:58.252300 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1955 4 sales 1955– 1956 8 sales 1957– 1958 9 sales After 1958 4 sales 0 500 1,000 1,500 1,518 1,615 1,463 1,466 Living area (SF), average

The average is 1,466 SF for homes built after 1958 and 1,518 SF for homes built before 1955. It does not move in a straight line; homes built 1955–1956 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-11-09T05:14:58.274882 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1955 4 sales 1955– 1956 8 sales 1957– 1958 9 sales After 1958 4 sales 0 25 50 75 60 82 68 22 Days on market, median

The median is 22 days for homes built after 1958 and 60 days for homes built before 1955. It does not move in a straight line; homes built 1955–1956 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-11-09T05:14:58.298972 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1955 4 sales 1955– 1956 8 sales 1957– 1958 9 sales After 1958 4 sales 0.0% 5.0% 10.0% 9.8% 12.2% 11.0% 7.5% Discount from original list, average

The average is 7.5% for homes built after 1958 and 9.8% for homes built before 1955. It does not move in a straight line; homes built 1955–1956 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-11-09T05:14:58.327876 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% 25% 0% 50% 62% 12% 78% 44% 22% 25% 25% 0% Before 1955 1955–1956 1957–1958 After 1958

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

  • 25% of homes built after 1958 had a price cut before sale, against 50% of homes built before 1955. Defined in 8.1.7.
  • 25% of homes built after 1958 had the seller pay closing costs or repairs, against 25% of homes built before 1955. Defined in 8.1.8.
  • 0% of homes built after 1958 have a view, against 0% of homes built before 1955. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

5.9 The numbers: price and size

Before 19554 sales1955–19568 sales1957–19589 salesAfter 19584 salesAll25 sales
Net sale price average$572,225$557,700$495,623$384,500$509,964
Net price per SF average$369$346$341$268$336
Living area average1,5181,6151,4631,4661,521
Year built median19541956195819611957

5.10 The numbers: selling

Before 19554 sales1955–19568 sales1957–19589 salesAfter 19584 salesAll25 sales
Days on market median6082682266
Discount from original list average9.8%12.2%11.0%7.5%10.6%
Price cut before sale50%50%78%25%56%
Seller paid closing costs or repairs25%62%44%25%44%
Has a view0%12%22%0%12%

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 · November 9, 2025 – November 8, 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. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-11-09T05:14:58.349025 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 21 24 sales Sales per group View: 3 sales (12%) No view: 21 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

2026-11-09T05:14:58.368380 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 21 sales $0K $200K $400K $600K $464K $511K Net sale price, average

The average is $464K for homes with a view and $511K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-11-09T05:14:58.388120 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 21 sales $0 $100 $200 $300 $400 $396 $329 Net price per SF, average

The average is $396 per SF for homes with a view and $329 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-11-09T05:14:58.407570 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 21 sales 0 500 1,000 1,500 1,179 1,542 Living area (SF), average

The average is 1,179 SF for homes with a view and 1,542 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-11-09T05:14:58.508079 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 21 sales 1955 1956 1957 1958 1957 1957 Year built: median (dot) and middle half (bar)

The median is 1957 for homes with a view and 1957 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-11-09T05:14:58.533474 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 21 sales 0 50 100 120 58 Days on market, median

The median is 120 days for homes with a view and 58 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

2026-11-09T05:14:58.553234 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 21 sales 0.0% 5.0% 10.0% 11.2% 10.9% Discount from original list, average

The average is 11.2% for homes with a view and 10.9% 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

2026-11-09T05:14:58.575445 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 67% 33% 57% 43% View No view

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

  • 67% of homes with a view had a price cut before sale, against 57% of homes without a view. Defined in 8.1.7.
  • 33% of homes with a view had the seller pay closing costs or repairs, against 43% 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 view21 salesAll24 sales
Net sale price average$464,333$510,624$504,838
Net price per SF average$396$329$337
Living area average1,1791,5421,497
Year built median195719571957

6.11 The numbers: selling

View3 salesNo view21 salesAll24 sales
Days on market median1205862
Discount from original list average11.2%10.9%11.0%
Price cut before sale67%57%58%
Seller paid closing costs or repairs33%43%42%

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 9, 2025 – November 8, 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 Windsor Park.

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 $509,964; median $518,500; standard deviation $166,823; middle half (25th–75th percentile) $388,884–$633,000; lowest $167,500, highest $846,000. 11 sales had a seller payment; their median payment was $10,546.

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 $336; median $347; standard deviation $80; middle half (25th–75th percentile) $301–$387; lowest $141, highest $538.

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 1,521; median 1,495; standard deviation 375; middle half (25th–75th percentile) 1,188–1,812; lowest 915, highest 2,098.

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 1957; median 1957; standard deviation 3; middle half (25th–75th percentile) 1955–1958; lowest 1954, highest 1967.

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 90; median 66; standard deviation 92; middle half (25th–75th percentile) 15–131; lowest 3, highest 373. 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 10.6%; median 10.2%; standard deviation 11.1%; middle half (25th–75th percentile) 4.8%–15.6%; lowest −3.8%, highest 52.1%. 3 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
14 of 25 resale sales (56.0%).

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
11 of 25 resale sales (44.0%).

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, 21 without, 1 unclassified. Most common View entries: None 14, Neighborhood 8, Park/Greenbelt 2, Creek/Stream 2, See Remarks 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-09 11:00 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “windsor park”, “meadowbrook” (case-insensitive). A record is kept when its subdivision name belongs to the Windsor Park family, the same rule comparable sales use (it includes Meadowbrook, proven adjacent and priced alike).
The data
Pulled November 9, 2026: 26 closed Windsor Park records over the prior year, in ZIP 78723. 12 subdivision spellings kept: Windsor Park (5); Windsor Park Sec 01 (4); Windsor Park 03 Sec 01 (3); Meadowbrook Sec 01 (3); Windsor Park 02 Sec 01 (3); Windsor Park 02 Sec 03 (2); Windsor Park 02 Sec 04 (1); Windsor Park 03 Sec 02 (1); Windsor Park 02 Sec 05 (1); Windsor Park 03 Sec 03 (1); Windsor Park Sec 02 (1); Windsor Park Sec 03 (1). Names found by the search but not part of Windsor Park, left out: Windsor Park Hills Sec 03 (4); Windsor Park Hills Sec 07 (2); Windsor Park Hills Sec 06 (2); Windsor Park Hills Sec 01 (1); WINDSOR PARK HILLS (1); Windsor Park (Gaston Park) (1); Windsor Park Iii Sec 4 First R (1); Windsor Park Hills (1); Windsor Park Hills Sec 04 (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 9 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 9, 2025 to November 8, 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
1 sale(s) other than single-family homes (condo, townhome and similar)

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 $389K”.
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 $389K: $167,500–$337,500 (6 sales); $389K–$517K: $388,884–$517,150 (6 sales); $518K–$633K: $518,500–$633,000 (7 sales); Over $633K: $639,000–$846,000 (6 sales)
Quartiles by living area: Under 1,188 SF: 915–1,170 SF (5 sales); 1,188–1,438 SF: 1,188–1,438 SF (7 sales); 1,495–1,812 SF: 1,495–1,812 SF (7 sales); Over 1,812 SF: 1,850–2,098 SF (6 sales)
Quartiles by year built: Before 1955: 1954–1954 (4 sales); 1955–1956: 1955–1956 (8 sales); 1957–1958: 1957–1958 (9 sales); After 1958: 1959–1967 (4 sales)
View and no view: View: MLS lists a view (3 sales); No view: None or Neighborhood (21 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 $509,964, median $518,500. Days on market: average 90, median 66: 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

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 = 12.7130.0053p < 0.0063Yesε² = 0.530large
Living areaKruskal–WallisH = 14.5830.0022p < 0.0063Yesε² = 0.607large
Year builtKruskal–WallisH = 2.3630.5014p < 0.0063Unclearε² = 0.098medium
Days on marketKruskal–WallisH = 3.1430.3698p < 0.0063Unclearε² = 0.131medium
Discount from original listKruskal–WallisH = 5.4130.1444p < 0.0063Unclearε² = 0.225large
Price cut before saleChi-squareχ² = 0.4630.9284p < 0.0063UnclearCramér’s V = 0.135small
Seller paid closing costs or repairsChi-squareχ² = 8.3830.0388p < 0.0063UnclearCramér’s V = 0.579large
Has a viewChi-squareχ² = 3.5830.3105p < 0.0063UnclearCramér’s V = 0.378medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 13.0930.0044p < 0.0063Yesε² = 0.546large
Net price per SFKruskal–WallisH = 2.2430.5242p < 0.0063Unclearε² = 0.093medium
Year builtKruskal–WallisH = 0.3730.9473p < 0.0063Unclearε² = 0.015small
Days on marketKruskal–WallisH = 2.2930.5139p < 0.0063Unclearε² = 0.096medium
Discount from original listKruskal–WallisH = 2.2030.5311p < 0.0063Unclearε² = 0.092medium
Price cut before saleChi-squareχ² = 3.1230.3730p < 0.0063UnclearCramér’s V = 0.353medium
Seller paid closing costs or repairsChi-squareχ² = 5.6230.1319p < 0.0063UnclearCramér’s V = 0.474medium
Has a viewChi-squareχ² = 5.5230.1375p < 0.0063UnclearCramér’s V = 0.470medium

8.3.3 Quartiles by year built

Too few sales in a group to test.

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); 1 sale(s) other than single-family homes (condo, townhome and similar). 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 November 9, 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.