ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Windsor Park

Austin, TX 78723
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 · 3:56 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
27
single-family resale homes
Median net sale price
$518,500
average $509,504
Median net price per SF
$347
average $336
Median days on market
66 days
average 88 days
1. SummaryResale homes · 27 sales · October 26, 2025 – October 25, 2026

This study looks at the 27 resale homes sold in Windsor Park in the 365 days to October 25, 2026. A full year is used because only 10 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 sold27 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 · 7 sales$389K–$518K · 7 sales$537K–$633K · 6 salesOver $633K · 7 sales
3. Quartiles by net sale priceResale homes · 27 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.

2026-10-26T03:57:00.298400 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 6 7 27 sales Sales per group Under $389K: 7 sales (26%) $389K–$518K: 7 sales (26%) $537K–$633K: 6 sales (22%) Over $633K: 7 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 $389K$389K–$518K$537K–$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–$518K$537K–$633KOver $633KReal difference?
Net price per SF$258 per SFLowest$342 per SF$364 per SF$384 per SFHighest✓ large
Living area1,151 SFSmallest1,387 SF1,696 SF1,849 SFLargest✓ large
Year built1958195719561956unclear
Days on market111 days17 days116 days31 daysunclear
Discount from original list18.6%7.5%10.3%5.2%unclear
Price cut before sale71%43%67%43%unclear
Seller paid closing costs or repairs14%71%67%29%unclear
Has a view14%0%33%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 $127 per SF (49%) more than homes under $389K

2026-10-26T03:57:00.326761 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $389K 7 sales $389K– $518K 7 sales $537K– $633K 6 sales Over $633K 7 sales $0 $200 $400 $258 $342 $364 $384 Net price per SF, average

The average is $384 per SF for homes over $633K and $258 per SF for homes under $389K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $633K are about 700 SF (61%) larger than homes under $389K

2026-10-26T03:57:00.349199 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $389K 7 sales $389K– $518K 7 sales $537K– $633K 6 sales Over $633K 7 sales 0 1,000 2,000 1,151 1,387 1,696 1,849 Living area (SF), average

The average is 1,849 SF for homes over $633K and 1,151 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

2026-10-26T03:57:00.374261 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $389K 7 sales $389K– $518K 7 sales $537K– $633K 6 sales Over $633K 7 sales 1955 1956 1957 1958 1959 1958 1957 1956 1956 Year built: median (dot) and middle half (bar)

The median is 1956 for homes over $633K and 1958 for homes under $389K. It falls step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T03:57:00.398131 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $389K 7 sales $389K– $518K 7 sales $537K– $633K 6 sales Over $633K 7 sales 0 50 100 111 17 116 31 Days on market, median

The median is 31 days for homes over $633K and 111 days for homes under $389K. It does not move in a straight line; homes $537K–$633K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T03:57:00.420008 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $389K 7 sales $389K– $518K 7 sales $537K– $633K 6 sales Over $633K 7 sales 0.0% 10.0% 20.0% 18.6% 7.5% 10.3% 5.2% Discount from original list, average

The average is 5.2% for homes over $633K and 18.6% 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

2026-10-26T03:57:00.450077 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 14 14 43 71 0 67 67 33 43 29 0 Under $389K $389K–$518K $537K–$633K Over $633K

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

  • 43% of homes over $633K had a price cut before sale, against 71% of homes under $389K. Defined in 8.1.7.
  • 29% of homes over $633K had the seller pay closing costs or repairs, against 14% of homes under $389K. Defined in 8.1.8.
  • 0% of homes over $633K have a view, against 14% 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 $389K7 sales$389K–$518K7 sales$537K–$633K6 salesOver $633K7 salesAll27 salesReal difference?
Net sale price average$289,343$462,822$587,500$709,493$509,504by design
Net price per SF average$258$342$364$384$336✓ large
Living area average1,1511,3871,6961,8491,514✓ large
Year built median19581957195619561957unclear

3.10 The numbers: selling

Under $389K7 sales$389K–$518K7 sales$537K–$633K6 salesOver $633K7 salesAll27 salesReal difference?
Days on market median111171163166unclear
Discount from original list average18.6%7.5%10.3%5.2%10.4%unclear
Price cut before sale71%43%67%43%56%unclear
Seller paid closing costs or repairs14%71%67%29%44%unclear
Has a view14%0%33%0%11%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 · 27 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.

2026-10-26T03:57:00.471150 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 8 6 7 27 sales Sales per group Under 1,188 SF: 6 sales (22%) 1,188–1,495 SF: 8 sales (30%) 1,543–1,812 SF: 6 sales (22%) Over 1,812 SF: 7 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 1,188 SF1,188–1,495 SF1,543–1,812 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 SF1,188–1,495 SF1,543–1,812 SFOver 1,812 SFReal difference?
Net sale price$369KLowest$389K$627K$667KHighest✓ large
Net price per SF$360 per SF$290 per SF$378 per SF$332 per SFunclear
Year built1958195619571956unclear
Days on market65 days100 days84 days49 daysunclear
Discount from original list8.2%15.7%10.5%6.3%unclear
Price cut before sale50%62%83%29%unclear
Seller paid closing costs or repairs33%38%33%71%unclear
Has a view33%0%17%0%unclear

4.3 Homes over 1,812 SF sell for about $298K (81%) more than homes under 1,188 SF

2026-10-26T03:57:00.492018 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,188 SF 6 sales 1,188– 1,495 SF 8 sales 1,543– 1,812 SF 6 sales Over 1,812 SF 7 sales $0K $200K $400K $600K $369K $389K $627K $667K Net sale price, average

The average is $667K for homes over 1,812 SF and $369K 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

2026-10-26T03:57:00.515305 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,188 SF 6 sales 1,188– 1,495 SF 8 sales 1,543– 1,812 SF 6 sales Over 1,812 SF 7 sales $0 $200 $400 $360 $290 $378 $332 Net price per SF, average

The average is $332 per SF for homes over 1,812 SF and $360 per SF for homes under 1,188 SF. It does not move in a straight line; homes 1,543–1,812 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T03:57:00.538351 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,188 SF 6 sales 1,188– 1,495 SF 8 sales 1,543– 1,812 SF 6 sales Over 1,812 SF 7 sales 1956 1958 1960 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

2026-10-26T03:57:00.561679 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,188 SF 6 sales 1,188– 1,495 SF 8 sales 1,543– 1,812 SF 6 sales Over 1,812 SF 7 sales 0 50 100 65 100 84 49 Days on market, median

The median is 49 days for homes over 1,812 SF and 65 days for homes under 1,188 SF. It does not move in a straight line; homes 1,188–1,495 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T03:57:00.583883 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,188 SF 6 sales 1,188– 1,495 SF 8 sales 1,543– 1,812 SF 6 sales Over 1,812 SF 7 sales 0.0% 5.0% 10.0% 15.0% 8.2% 15.7% 10.5% 6.3% Discount from original list, average

The average is 6.3% for homes over 1,812 SF and 8.2% for homes under 1,188 SF. It does not move in a straight line; homes 1,188–1,495 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

2026-10-26T03:57:00.611184 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 33 33 62 38 0 83 33 17 29 71 0 Under 1,188 SF 1,188–1,495 SF 1,543–1,812 SF Over 1,812 SF

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

  • 29% of homes over 1,812 SF had a price cut before sale, against 50% of homes under 1,188 SF. Defined in 8.1.7.
  • 71% of homes over 1,812 SF had the seller pay closing costs or repairs, against 33% of homes under 1,188 SF. Defined in 8.1.8.
  • 0% of homes over 1,812 SF have a view, against 33% 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 SF6 sales1,188–1,495 SF8 sales1,543–1,812 SF6 salesOver 1,812 SF7 salesAll27 salesReal difference?
Net sale price average$368,797$389,359$627,167$666,565$509,504✓ large
Net price per SF average$360$290$378$332$336unclear
Living area average1,0231,3381,6592,0131,514by design
Year built median19581956195719561957unclear

4.10 The numbers: selling

Under 1,188 SF6 sales1,188–1,495 SF8 sales1,543–1,812 SF6 salesOver 1,812 SF7 salesAll27 salesReal difference?
Days on market median65100844966unclear
Discount from original list average8.2%15.7%10.5%6.3%10.4%unclear
Price cut before sale50%62%83%29%56%unclear
Seller paid closing costs or repairs33%38%33%71%44%unclear
Has a view33%0%17%0%11%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 · 27 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.

2026-10-26T03:57:00.631978 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 4 10 5 27 sales Sales per group Before 1956: 8 sales (30%) 1956: 4 sales (15%) 1957–1958: 10 sales (37%) After 1958: 5 sales (19%)
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

2026-10-26T03:57:00.652434 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1956 8 sales 1956 4 sales 1957– 1958 10 sales After 1958 5 sales $0K $200K $400K $600K $618K $451K $476K $449K Net sale price, average

The average is $449K for homes built after 1958 and $618K for homes built before 1956. It does not move in a straight line; homes built before 1956 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T03:57:00.675627 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1956 8 sales 1956 4 sales 1957– 1958 10 sales After 1958 5 sales $0 $200 $400 $383 $295 $339 $288 Net price per SF, average

The average is $288 per SF for homes built after 1958 and $383 per SF for homes built before 1956. It does not move in a straight line; homes built before 1956 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T03:57:00.697273 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1956 8 sales 1956 4 sales 1957– 1958 10 sales After 1958 5 sales 0 500 1,000 1,500 1,639 1,470 1,412 1,555 Living area (SF), average

The average is 1,555 SF for homes built after 1958 and 1,639 SF for homes built before 1956. It does not move in a straight line; homes built before 1956 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T03:57:00.719543 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1956 8 sales 1956 4 sales 1957– 1958 10 sales After 1958 5 sales 0 50 100 82 122 85 16 Days on market, median

The median is 16 days for homes built after 1958 and 82 days for homes built before 1956. It does not move in a straight line; homes built 1956 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T03:57:00.741981 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1956 8 sales 1956 4 sales 1957– 1958 10 sales After 1958 5 sales 0.0% 10.0% 20.0% 7.9% 18.4% 11.1% 6.6% Discount from original list, average

The average is 6.6% for homes built after 1958 and 7.9% for homes built before 1956. It does not move in a straight line; homes built 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

2026-10-26T03:57:00.767228 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 38 12 50 75 0 80 50 20 20 20 0 Before 1956 1956 1957–1958 After 1958

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

  • 20% of homes built after 1958 had a price cut before sale, against 50% of homes built before 1956. Defined in 8.1.7.
  • 20% of homes built after 1958 had the seller pay closing costs or repairs, against 38% of homes built before 1956. Defined in 8.1.8.
  • 0% of homes built after 1958 have a view, against 12% of homes built before 1956. 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 19568 sales19564 sales1957–195810 salesAfter 19585 salesAll27 sales
Net sale price average$618,419$450,788$476,310$448,600$509,504
Net price per SF average$383$295$339$288$336
Living area average1,6391,4701,4121,5551,514
Year built median19541956195819611957

5.10 The numbers: selling

Before 19568 sales19564 sales1957–195810 salesAfter 19585 salesAll27 sales
Days on market median82122851666
Discount from original list average7.9%18.4%11.1%6.6%10.4%
Price cut before sale50%50%80%20%56%
Seller paid closing costs or repairs38%75%50%20%44%
Has a view12%0%20%0%11%

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 · 27 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. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T03:57:00.786069 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 23 26 sales Sales per group View: 3 sales (12%) No view: 23 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

2026-10-26T03:57:00.801888 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 23 sales $0K $200K $400K $600K $464K $510K Net sale price, average

The average is $464K for homes with a view and $510K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T03:57:00.820639 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 23 sales $0 $100 $200 $300 $400 $396 $330 Net price per SF, average

The average is $396 per SF for homes with a view and $330 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T03:57:00.839595 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 23 sales 0 500 1,000 1,500 1,179 1,533 Living area (SF), average

The average is 1,179 SF for homes with a view and 1,533 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T03:57:00.883950 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 23 sales 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

2026-10-26T03:57:00.901872 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 23 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

2026-10-26T03:57:00.920281 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 23 sales 0.0% 5.0% 10.0% 11.2% 10.7% Discount from original list, average

The average is 11.2% for homes with a view and 10.7% 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

2026-10-26T03:57:00.938818 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 view23 salesAll26 sales
Net sale price average$464,333$510,026$504,754
Net price per SF average$396$330$337
Living area average1,1791,5331,492
Year built median195719571957

6.11 The numbers: selling

View3 salesNo view23 salesAll26 sales
Days on market median1205862
Discount from original list average11.2%10.7%10.7%
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 · 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 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
27 resale sales. Average $509,504; median $518,500; standard deviation $169,728; middle half (25th–75th percentile) $363,192–$636,000; lowest $167,500, highest $846,000. 12 sales had a seller payment; their median payment was $10,273.

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
27 resale sales. Average $336; median $347; standard deviation $77; middle half (25th–75th percentile) $301–$383; 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
27 resale sales. Average 1,514; median 1,495; standard deviation 385; middle half (25th–75th percentile) 1,188–1,831; 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
27 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
27 resale sales. Average 88; median 66; standard deviation 89; middle half (25th–75th percentile) 16–126; 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
27 resale sales. Average 10.4%; median 10.2%; standard deviation 10.8%; middle half (25th–75th percentile) 4.0%–15.2%; 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
15 of 27 resale sales (55.6%).

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
12 of 27 resale sales (44.4%).

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, 23 without, 1 unclassified. Most common View entries: None 15, Neighborhood 9, Creek/Stream 2, Park/Greenbelt 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
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. 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 Sec 01, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 28 closed Windsor Park records over the prior year, in ZIP 78723. 12 subdivision spellings kept: Windsor Park (6); Windsor Park Sec 01 (4); Windsor Park 02 Sec 03 (3); Windsor Park 02 Sec 01 (3); Meadowbrook Sec 01 (3); Windsor Park 03 Sec 01 (3); Windsor Park Sec 02 (1); Windsor Park 02 Sec 04 (1); Windsor Park 03 Sec 02 (1); Windsor Park Sec 03 (1); Windsor Park 02 Sec 05 (1); Windsor Park 03 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 06 (2); Windsor Park Hills Sec 07 (2); WINDSOR PARK HILLS (1); Windsor Park Hills Sec 04 (1); Windsor Park Hills Sec 01 (1); Windsor Park Hills (1); Windsor Park (Gaston Park) (1); Windsor Park Iii Sec 4 First R (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 10 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
27 single-family sales in the window: 27 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
27 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 (7 sales); $389K–$518K: $388,884–$518,500 (7 sales); $537K–$633K: $537,000–$633,000 (6 sales); Over $633K: $639,000–$846,000 (7 sales)
Quartiles by living area: Under 1,188 SF: 915–1,170 SF (6 sales); 1,188–1,495 SF: 1,188–1,495 SF (8 sales); 1,543–1,812 SF: 1,543–1,812 SF (6 sales); Over 1,812 SF: 1,850–2,098 SF (7 sales)
Quartiles by year built: Before 1956: 1954–1955 (8 sales); 1956: 1956–1956 (4 sales); 1957–1958: 1957–1958 (10 sales); After 1958: 1959–1967 (5 sales)
View and no view: View: MLS lists a view (3 sales); No view: None or Neighborhood (23 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 $509,504, median $518,500. Days on market: average 88, 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 = 12.9830.0047p < 0.0063Yesε² = 0.499large
Living areaKruskal–WallisH = 14.2530.0026p < 0.0063Yesε² = 0.548large
Year builtKruskal–WallisH = 2.3030.5129p < 0.0063Unclearε² = 0.088medium
Days on marketKruskal–WallisH = 4.5930.2044p < 0.0063Unclearε² = 0.177large
Discount from original listKruskal–WallisH = 6.7830.0794p < 0.0063Unclearε² = 0.261large
Price cut before saleChi-squareχ² = 1.9330.5874p < 0.0063UnclearCramér’s V = 0.267small
Seller paid closing costs or repairsChi-squareχ² = 6.5630.0874p < 0.0063UnclearCramér’s V = 0.493medium
Has a viewChi-squareχ² = 4.8230.1853p < 0.0063UnclearCramér’s V = 0.423medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 18.3630.0004p < 0.0063Yesε² = 0.706large
Net price per SFKruskal–WallisH = 5.3430.1485p < 0.0063Unclearε² = 0.205large
Year builtKruskal–WallisH = 0.3730.9467p < 0.0063Unclearε² = 0.014small
Days on marketKruskal–WallisH = 0.9230.8209p < 0.0063Unclearε² = 0.035small
Discount from original listKruskal–WallisH = 2.5630.4637p < 0.0063Unclearε² = 0.099medium
Price cut before saleChi-squareχ² = 4.1730.2436p < 0.0063UnclearCramér’s V = 0.393medium
Seller paid closing costs or repairsChi-squareχ² = 2.8230.4201p < 0.0063UnclearCramér’s V = 0.323medium
Has a viewChi-squareχ² = 5.0630.1673p < 0.0063UnclearCramér’s V = 0.433medium

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 27 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.