ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Windermere

Pflugerville, TX 78660
Resale homes · closed Oct 27 – Oct 26, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 27, 2026 · 7:46 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
30
single-family resale homes
Median net sale price
$280,000
average $280,075
Median net price per SF
$183
average $182
Median days on market
26 days
average 74 days
1. SummaryResale homes · 30 sales · October 27, 2025 – October 26, 2026

This study looks at the 30 resale homes sold in Windermere in the 365 days to October 26, 2026. A full year is used because only 17 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 sold30 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 $260K · 8 sales$260K–$274K · 6 sales$280K–$303K · 8 salesOver $303K · 8 sales
3. Quartiles by net sale priceResale homes · 30 sales · October 27, 2025 – October 26, 2026

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

2026-10-27T07:47:08.163050 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 6 8 8 30 sales Sales per group Under $260K: 8 sales (27%) $260K–$274K: 6 sales (20%) $280K–$303K: 8 sales (27%) Over $303K: 8 sales (27%)
Bottom line: no measure differs enough between the groups to rule out chance.

3.1 Key differences

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

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 $260K$260K–$274K$280K–$303KOver $303KReal difference?
Net price per SF$146 per SF$197 per SF$212 per SF$176 per SFunclear
Living area1,545 SF1,443 SF1,427 SF1,954 SFunclear
Year built1984199019861994unclear
Days on market15 days18 days46 days50 daysunclear
Discount from original list13.4%3.1%6.6%4.9%unclear
Price cut before sale38%0%50%50%unclear
Seller paid closing costs or repairs12%67%75%75%unclear
Has a view25%33%0%12%unclear

How to read this section. Each heading gives the finding. The gold box says whether the gap is real (✓, with its size) or could be chance (–). The section ends with its numbers; the tests are in section 8.3.

3.3 Net price per SF: no clear difference

2026-10-27T07:47:08.192062 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $260K 8 sales $260K– $274K 6 sales $280K– $303K 8 sales Over $303K 8 sales $0 $100 $200 $146 $197 $212 $176 Net price per SF, average

The average is $176 per SF for homes over $303K and $146 per SF for homes under $260K. It does not move in a straight line; homes $280K–$303K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-27T07:47:08.214715 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $260K 8 sales $260K– $274K 6 sales $280K– $303K 8 sales Over $303K 8 sales 0 1,000 2,000 1,545 1,443 1,427 1,954 Living area (SF), average

The average is 1,954 SF for homes over $303K and 1,545 SF for homes under $260K. It does not move in a straight line; homes over $303K are highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-27T07:47:08.240084 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $260K 8 sales $260K– $274K 6 sales $280K– $303K 8 sales Over $303K 8 sales 1984 1987 1990 1993 1996 1984 1990 1986 1994 Year built: median (dot) and middle half (bar)

The median is 1994 for homes over $303K and 1984 for homes under $260K. It does not move in a straight line; homes over $303K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-27T07:47:08.264034 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $260K 8 sales $260K– $274K 6 sales $280K– $303K 8 sales Over $303K 8 sales 0 20 40 15 18 46 50 Days on market, median

The median is 50 days for homes over $303K and 15 days for homes under $260K. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-27T07:47:08.286070 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $260K 8 sales $260K– $274K 6 sales $280K– $303K 8 sales Over $303K 8 sales 0.0% 5.0% 10.0% 15.0% 13.4% 3.1% 6.6% 4.9% Discount from original list, average

The average is 4.9% for homes over $303K and 13.4% for homes under $260K. It does not move in a straight line; homes under $260K 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

2026-10-27T07:47:08.316552 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% 38 12 25 0 67 33 50 75 0 50 75 12 Under $260K $260K–$274K $280K–$303K Over $303K

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

  • 50% of homes over $303K had a price cut before sale, against 38% of homes under $260K. Defined in 8.1.7.
  • 75% of homes over $303K had the seller pay closing costs or repairs, against 12% of homes under $260K. Defined in 8.1.8.
  • 12% of homes over $303K have a view, against 25% of homes under $260K. 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 $260K8 sales$260K–$274K6 sales$280K–$303K8 salesOver $303K8 salesAll30 salesReal difference?
Net sale price average$217,925$269,435$289,750$340,532$280,075by design
Net price per SF average$146$197$212$176$182unclear
Living area average1,5451,4431,4271,9541,602unclear
Year built median19841990198619941993unclear

3.10 The numbers: selling

Under $260K8 sales$260K–$274K6 sales$280K–$303K8 salesOver $303K8 salesAll30 salesReal difference?
Days on market median1518465026unclear
Discount from original list average13.4%3.1%6.6%4.9%7.2%unclear
Price cut before sale38%0%50%50%37%unclear
Seller paid closing costs or repairs12%67%75%75%57%unclear
Has a view25%33%0%12%17%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 · 30 sales · October 27, 2025 – October 26, 2026

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

2026-10-27T07:47:08.337658 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Under 1,326 SF: 8 sales (27%) 1,326–1,440 SF: 7 sales (23%) 1,547–1,795 SF: 7 sales (23%) Over 1,795 SF: 8 sales (27%)
Bottom line

4.1 Key differences

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

Under 1,326 SF1,326–1,440 SF1,547–1,795 SFOver 1,795 SF
Larger homes Over 1,795 SF
  • Sell for less per square foot.
Smaller homes Under 1,326 SF
  • Sell for more per square foot.

4.2 At a glance

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

Under 1,326 SF1,326–1,440 SF1,547–1,795 SFOver 1,795 SFReal difference?
Net sale price$272K$252K$267K$323Kunclear
Net price per SF$229 per SFHighest$186 per SF$161 per SF$150 per SFLowest✓ large
Year built1985198519931995unclear
Days on market39 days18 days98 days32 daysunclear
Discount from original list6.0%7.2%13.9%2.7%unclear
Price cut before sale12%43%57%38%unclear
Seller paid closing costs or repairs62%57%29%75%unclear
Has a view12%14%29%12%unclear

4.3 Net sale price: no clear difference

2026-10-27T07:47:08.358470 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,326 SF 8 sales 1,326– 1,440 SF 7 sales 1,547– 1,795 SF 7 sales Over 1,795 SF 8 sales $0K $100K $200K $300K $272K $252K $267K $323K Net sale price, average

The average is $323K for homes over 1,795 SF and $272K for homes under 1,326 SF. It does not move in a straight line; homes over 1,795 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Homes over 1,795 SF sell for about $78 per SF (34%) less than homes under 1,326 SF

2026-10-27T07:47:08.382185 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,326 SF 8 sales 1,326– 1,440 SF 7 sales 1,547– 1,795 SF 7 sales Over 1,795 SF 8 sales $0 $100 $200 $229 $186 $161 $150 Net price per SF, average

The average is $150 per SF for homes over 1,795 SF and $229 per SF for homes under 1,326 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-10-27T07:47:08.406506 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,326 SF 8 sales 1,326– 1,440 SF 7 sales 1,547– 1,795 SF 7 sales Over 1,795 SF 8 sales 1984 1987 1990 1993 1985 1985 1993 1995 Year built: median (dot) and middle half (bar)

The median is 1995 for homes over 1,795 SF and 1985 for homes under 1,326 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-27T07:47:08.430235 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,326 SF 8 sales 1,326– 1,440 SF 7 sales 1,547– 1,795 SF 7 sales Over 1,795 SF 8 sales 0 50 100 39 18 98 32 Days on market, median

The median is 32 days for homes over 1,795 SF and 39 days for homes under 1,326 SF. It does not move in a straight line; homes 1,547–1,795 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-27T07:47:08.452296 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,326 SF 8 sales 1,326– 1,440 SF 7 sales 1,547– 1,795 SF 7 sales Over 1,795 SF 8 sales 0.0% 5.0% 10.0% 15.0% 6.0% 7.2% 13.9% 2.7% Discount from original list, average

The average is 2.7% for homes over 1,795 SF and 6.0% for homes under 1,326 SF. It does not move in a straight line; homes 1,547–1,795 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

2026-10-27T07:47:08.479405 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% 12 62 12 43 57 14 57 29 29 38 75 12 Under 1,326 SF 1,326–1,440 SF 1,547–1,795 SF Over 1,795 SF

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

  • 38% of homes over 1,795 SF had a price cut before sale, against 12% of homes under 1,326 SF. Defined in 8.1.7.
  • 75% of homes over 1,795 SF had the seller pay closing costs or repairs, against 62% of homes under 1,326 SF. Defined in 8.1.8.
  • 12% of homes over 1,795 SF have a view, against 12% of homes under 1,326 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 1,326 SF8 sales1,326–1,440 SF7 sales1,547–1,795 SF7 salesOver 1,795 SF8 salesAll30 salesReal difference?
Net sale price average$272,376$252,500$267,000$323,344$280,075unclear
Net price per SF average$229$186$161$150$182✓ large
Living area average1,1981,3601,6592,1681,602by design
Year built median19851985199319951993unclear

4.10 The numbers: selling

Under 1,326 SF8 sales1,326–1,440 SF7 sales1,547–1,795 SF7 salesOver 1,795 SF8 salesAll30 salesReal difference?
Days on market median3918983226unclear
Discount from original list average6.0%7.2%13.9%2.7%7.2%unclear
Price cut before sale12%43%57%38%37%unclear
Seller paid closing costs or repairs62%57%29%75%57%unclear
Has a view12%14%29%12%17%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 · 30 sales · October 27, 2025 – October 26, 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.

2026-10-27T07:47:08.500263 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 6 7 9 30 sales Sales per group Before 1985: 8 sales (27%) 1985–1986: 6 sales (20%) 1993–1994: 7 sales (23%) After 1994: 9 sales (30%)
Bottom line

5.1 Key differences

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

Before 19851985–19861993–1994After 1994
Newer homes After 1994
  • Are much larger.
Older homes Before 1985
  • Are much smaller.

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 19851985–19861993–1994After 1994Real difference?
Net sale price$240K$275K$311K$295Kunclear
Net price per SF$188 per SF$212 per SF$174 per SF$162 per SFunclear
Living area1,324 SF1,302 SFSmallest1,810 SF1,888 SFLargest✓ large
Days on market25 days20 days119 days19 daysunclear
Discount from original list9.9%7.1%4.9%6.8%unclear
Price cut before sale25%33%57%33%unclear
Seller paid closing costs or repairs25%83%57%67%unclear
Has a view38%0%0%22%unclear

5.3 Net sale price: no clear difference

2026-10-27T07:47:08.521374 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 8 sales 1985– 1986 6 sales 1993– 1994 7 sales After 1994 9 sales $0K $100K $200K $300K $240K $275K $311K $295K Net sale price, average

The average is $295K for homes built after 1994 and $240K for homes built before 1985. It does not move in a straight line; homes built 1993–1994 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-27T07:47:08.545543 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 8 sales 1985– 1986 6 sales 1993– 1994 7 sales After 1994 9 sales $0 $100 $200 $188 $212 $174 $162 Net price per SF, average

The average is $162 per SF for homes built after 1994 and $188 per SF for homes built before 1985. It does not move in a straight line; homes built 1985–1986 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Homes built after 1994 are about 560 SF (43%) larger than homes built before 1985

2026-10-27T07:47:08.567667 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 8 sales 1985– 1986 6 sales 1993– 1994 7 sales After 1994 9 sales 0 1,000 2,000 1,324 1,302 1,810 1,888 Living area (SF), average

The average is 1,888 SF for homes built after 1994 and 1,324 SF for homes built before 1985. It does not move in a straight line; homes built after 1994 are highest. Defined in 8.1.3.

✓ Real difference · large

5.6 Days on market: no clear difference

2026-10-27T07:47:08.590750 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 8 sales 1985– 1986 6 sales 1993– 1994 7 sales After 1994 9 sales 0 50 100 25 20 119 19 Days on market, median

The median is 19 days for homes built after 1994 and 25 days for homes built before 1985. It does not move in a straight line; homes built 1993–1994 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-27T07:47:08.613368 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 8 sales 1985– 1986 6 sales 1993– 1994 7 sales After 1994 9 sales 0.0% 5.0% 10.0% 9.9% 7.1% 4.9% 6.8% Discount from original list, average

The average is 6.8% for homes built after 1994 and 9.9% for homes built before 1985. It does not move in a straight line; homes built before 1985 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

2026-10-27T07:47:08.639293 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% 25 25 38 33 83 0 57 57 0 33 67 22 Before 1985 1985–1986 1993–1994 After 1994

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

  • 33% of homes built after 1994 had a price cut before sale, against 25% of homes built before 1985. Defined in 8.1.7.
  • 67% of homes built after 1994 had the seller pay closing costs or repairs, against 25% of homes built before 1985. Defined in 8.1.8.
  • 22% of homes built after 1994 have a view, against 38% of homes built before 1985. 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 19858 sales1985–19866 sales1993–19947 salesAfter 19949 salesAll30 salesReal difference?
Net sale price average$239,625$275,343$310,671$295,389$280,075unclear
Net price per SF average$188$212$174$162$182unclear
Living area average1,3241,3021,8101,8881,602✓ large
Year built median19831985199319961993by design

5.10 The numbers: selling

Before 19858 sales1985–19866 sales1993–19947 salesAfter 19949 salesAll30 salesReal difference?
Days on market median25201191926unclear
Discount from original list average9.9%7.1%4.9%6.8%7.2%unclear
Price cut before sale25%33%57%33%37%unclear
Seller paid closing costs or repairs25%83%57%67%57%unclear
Has a view38%0%0%22%17%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 · 30 sales · October 27, 2025 – October 26, 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.

2026-10-27T07:47:08.658557 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 24 29 sales Sales per group View: 5 sales (17%) No view: 24 sales (83%)
Bottom line: no measure differs enough between the groups to rule out chance.

6.1 Key differences

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

6.2 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.

ViewNo viewReal difference?
Net sale price$257K$285Kunclear
Net price per SF$171 per SF$183 per SFunclear
Living area1,538 SF1,628 SFunclear
Year built19831993unclear
Days on market63 days26 daysunclear
Discount from original list11.2%6.6%unclear
Price cut before sale40%38%unclear
Seller paid closing costs or repairs40%58%unclear

6.3 Net sale price: no clear difference

2026-10-27T07:47:08.674947 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 24 sales $0K $100K $200K $300K $257K $285K Net sale price, average

The average is $257K for homes with a view and $285K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-10-27T07:47:08.693788 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 24 sales $0 $50 $100 $150 $200 $171 $183 Net price per SF, average

The average is $171 per SF for homes with a view and $183 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-10-27T07:47:08.738919 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 24 sales 0 500 1,000 1,500 1,538 1,628 Living area (SF), average

The average is 1,538 SF for homes with a view and 1,628 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-27T07:47:08.758571 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 24 sales 1984 1987 1990 1993 1983 1993 Year built: median (dot) and middle half (bar)

The median is 1983 for homes with a view and 1993 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-27T07:47:08.776401 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 24 sales 0 20 40 60 63 26 Days on market, median

The median is 63 days for homes with a view and 26 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-10-27T07:47:08.795435 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 24 sales 0.0% 5.0% 10.0% 11.2% 6.6% Discount from original list, average

The average is 11.2% for homes with a view and 6.6% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-27T07:47:08.814078 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 40 40 38 58 View No view

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

  • 40% of homes with a view had a price cut before sale, against 38% of homes without a view. Defined in 8.1.7.
  • 40% of homes with a view had the seller pay closing costs or repairs, against 58% of homes without a view. Defined in 8.1.8.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance

6.10 The numbers: price and size

View5 salesNo view24 salesAll29 salesReal difference?
Net sale price average$257,470$285,019$280,269unclear
Net price per SF average$171$183$181unclear
Living area average1,5381,6281,613unclear
Year built median198319931993unclear

6.11 The numbers: selling

View5 salesNo view24 salesAll29 salesReal difference?
Days on market median632627unclear
Discount from original list average11.2%6.6%7.4%unclear
Price cut before sale40%38%38%unclear
Seller paid closing costs or repairs40%58%55%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 8.3.4.

7. New constructionBasic statistics · 0 sales · October 27, 2025 – October 26, 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 Windermere.

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
30 resale sales. Average $280,075; median $280,000; standard deviation $51,806; middle half (25th–75th percentile) $259,250–$308,250; lowest $165,000, highest $375,203. 17 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
30 resale sales. Average $182; median $183; standard deviation $44; middle half (25th–75th percentile) $156–$210; lowest $106, highest $271.

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
30 resale sales. Average 1,602; median 1,494; standard deviation 399; middle half (25th–75th percentile) 1,306–1,863; lowest 1,034, highest 2,334.

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
30 resale sales. Average 1990; median 1993; standard deviation 5; middle half (25th–75th percentile) 1984–1995; lowest 1983, highest 1996.

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
30 resale sales. Average 74; median 26; standard deviation 97; middle half (25th–75th percentile) 13–98; lowest 0, highest 360. 1 sales went under contract on their listing date (0 days).

8.1.6 Discount from original list

In simple terms
How far below the first asking price the home sold, after seller payments. It measures how much negotiating room sellers gave up. A negative figure means the home sold above its first asking price.
Statistically
Discount % = (OriginalListPrice − Net) ÷ OriginalListPrice × 100, per sale; summarized by the mean.
The data
30 resale sales. Average 7.2%; median 5.2%; standard deviation 9.4%; middle half (25th–75th percentile) 3.0%–8.7%; lowest −6.5%, highest 40.9%. 2 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
11 of 30 resale sales (36.7%).

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
17 of 30 resale sales (56.7%).

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
5 sales with a view, 24 without, 1 unclassified. Most common View entries: None 16, Neighborhood 10, Trees/Woods 3, City 1, See Remarks 1, Panoramic 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 = Pflugerville, SubdivisionName contains any of “windermere” (case-insensitive). A record is kept when its subdivision name belongs to the Windermere family, the same rule comparable sales use.
The data
Pulled October 27, 2026: 34 closed Windermere records over the prior year, in ZIP 78660. 12 subdivision spellings kept: Windermere Ph F Sec 03 (7); Windermere Ph D (5); Windermere Ph A Sec 01 (4); Windermere Ph F Sec 01 (3); Windermere (3); Windermere Ph E (3); Windermere Ph G Sec 01 (2); Windermere Ph B (2); Windermere Ph H Sec 02 (2); Windermere Ph A Sec 02 (1); Windermere Ph C (1); Windermere Ph F Sec 02 (1). Names found by the search but not part of Windermere, left out: WINDERMERE PHS F SEC 3 (1); Windermere Phs G Sec 1 (1); WINDERMERE PHS F SEC 1 (1); Windermere Terrace (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 17 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 27, 2025 to October 26, 2026 inclusive.
The data
30 single-family sales in the window: 30 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
30 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
4 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 $260K”.
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 $260K: $165,000–$259,000 (8 sales); $260K–$274K: $260,000–$274,450 (6 sales); $280K–$303K: $280,000–$303,000 (8 sales); Over $303K: $310,000–$375,203 (8 sales)
Quartiles by living area: Under 1,326 SF: 1,034–1,299 SF (8 sales); 1,326–1,440 SF: 1,326–1,440 SF (7 sales); 1,547–1,795 SF: 1,547–1,795 SF (7 sales); Over 1,795 SF: 1,886–2,334 SF (8 sales)
Quartiles by year built: Before 1985: 1983–1984 (8 sales); 1985–1986: 1985–1986 (6 sales); 1993–1994: 1993–1994 (7 sales); After 1994: 1995–1996 (9 sales)
View and no view: View: MLS lists a view (5 sales); No view: None or Neighborhood (24 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 $280,075, median $280,000. Days on market: average 74, median 26: 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; View and no view: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
2 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

In simple terms
Headings and sentences round figures so they read easily; the tables at the end of each section give them in full.
Statistically
Prices in headings round to the nearest $1K; price per SF and days on market to the nearest whole number; living area to the nearest 10 SF; shares and percentage gaps to whole percents.
The data
Days on market is always shown in days.

8.3 Test results

Every test behind every gold box. Statistic, degrees of freedom (df), p-value, the threshold it must beat, and the size of the difference.

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 9.7030.0213p < 0.0063Unclearε² = 0.334large
Living areaKruskal–WallisH = 9.8430.0200p < 0.0063Unclearε² = 0.339large
Year builtKruskal–WallisH = 8.9930.0295p < 0.0063Unclearε² = 0.310large
Days on marketKruskal–WallisH = 3.0630.3822p < 0.0063Unclearε² = 0.106medium
Discount from original listKruskal–WallisH = 3.5130.3196p < 0.0063Unclearε² = 0.121medium
Price cut before saleChi-squareχ² = 4.7030.1951p < 0.0063UnclearCramér’s V = 0.396medium
Seller paid closing costs or repairsChi-squareχ² = 8.7930.0322p < 0.0063UnclearCramér’s V = 0.541large
Has a viewChi-squareχ² = 3.3030.3476p < 0.0063UnclearCramér’s V = 0.332medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 6.4830.0906p < 0.0063Unclearε² = 0.223large
Net price per SFKruskal–WallisH = 17.4930.0006p < 0.0063Yesε² = 0.603large
Year builtKruskal–WallisH = 9.8430.0199p < 0.0063Unclearε² = 0.339large
Days on marketKruskal–WallisH = 3.8030.2845p < 0.0063Unclearε² = 0.131medium
Discount from original listKruskal–WallisH = 4.9930.1727p < 0.0063Unclearε² = 0.172large
Price cut before saleChi-squareχ² = 3.3930.3348p < 0.0063UnclearCramér’s V = 0.336medium
Seller paid closing costs or repairsChi-squareχ² = 3.4630.3264p < 0.0063UnclearCramér’s V = 0.339medium
Has a viewChi-squareχ² = 0.9430.8151p < 0.0063UnclearCramér’s V = 0.177small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 7.5430.0566p < 0.0063Unclearε² = 0.260large
Net price per SFKruskal–WallisH = 6.0530.1094p < 0.0063Unclearε² = 0.208large
Living areaKruskal–WallisH = 13.4230.0038p < 0.0063Yesε² = 0.463large
Days on marketKruskal–WallisH = 4.1930.2417p < 0.0063Unclearε² = 0.144large
Discount from original listKruskal–WallisH = 3.7930.2854p < 0.0063Unclearε² = 0.131medium
Price cut before saleChi-squareχ² = 1.8030.6140p < 0.0063UnclearCramér’s V = 0.245small
Seller paid closing costs or repairsChi-squareχ² = 5.3730.1465p < 0.0063UnclearCramér’s V = 0.423medium
Has a viewChi-squareχ² = 5.3030.1511p < 0.0063UnclearCramér’s V = 0.420medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 37.00—0.1938p < 0.0063Unclearrank-biserial r = 0.383medium
Net price per SFMann–Whitney UU = 50.00—0.5942p < 0.0063Unclearrank-biserial r = 0.167small
Living areaMann–Whitney UU = 55.00—0.7950p < 0.0063Unclearrank-biserial r = 0.083negligible
Year builtMann–Whitney UU = 46.50—0.4484p < 0.0063Unclearrank-biserial r = 0.225small
Days on marketMann–Whitney UU = 73.50—0.4528p < 0.0063Unclearrank-biserial r = 0.225small
Discount from original listMann–Whitney UU = 79.00—0.2955p < 0.0063Unclearrank-biserial r = 0.317medium
Price cut before saleChi-squareχ² = 0.0110.9165p < 0.0063UnclearCramér’s V = 0.019negligible
Seller paid closing costs or repairsChi-squareχ² = 0.5610.4533p < 0.0063UnclearCramér’s V = 0.139small

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 4 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 30 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 27, 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.