ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Windermere

Pflugerville, TX 78660
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 · 5:35 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
29
single-family resale homes
Median net sale price
$280,000
average $283,975
Median net price per SF
$184
average $185
Median days on market
25 days
average 64 days
1. SummaryResale homes · 29 sales · October 26, 2025 – October 25, 2026

This study looks at the 29 resale homes sold in Windermere in the 365 days to October 25, 2026. A full year is used because only 16 resale homes sold in the last 180 days. New construction is left out and shown on its own in section 7. The homes are compared four ways: by price, by living area, by year built and with or without a view. The first three are split into four equal groups (quartiles), each named by its range.

Each comparison has its own section (3–6) with everything about it in one place: the key differences, a table of every measure at a glance, the charts and the numbers.

2. Where the resale homes sold29 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 · 7 sales$260K–$274K · 6 sales$280K–$310K · 9 salesOver $310K · 7 sales
3. Quartiles by net sale priceResale homes · 29 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.

2026-10-26T05:35:48.661837 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 6 9 7 29 sales Sales per group Under $260K: 7 sales (24%) $260K–$274K: 6 sales (21%) $280K–$310K: 9 sales (31%) Over $310K: 7 sales (24%)
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–$310KOver $310KReal difference?
Net price per SF$152 per SF$197 per SF$208 per SF$176 per SFunclear
Living area1,541 SF1,443 SF1,468 SF1,977 SFunclear
Year built1985199019861995unclear
Days on market15 days18 days35 days63 daysunclear
Discount from original list10.8%3.1%6.2%5.1%unclear
Price cut before sale29%0%44%57%unclear
Seller paid closing costs or repairs14%67%67%86%unclear
Has a view14%33%0%14%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

2026-10-26T05:35:48.690285 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $260K 7 sales $260K– $274K 6 sales $280K– $310K 9 sales Over $310K 7 sales $0 $100 $200 $152 $197 $208 $176 Net price per SF, average

The average is $176 per SF for homes over $310K and $152 per SF for homes under $260K. It does not move in a straight line; homes $280K–$310K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-26T05:35:48.713093 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $260K 7 sales $260K– $274K 6 sales $280K– $310K 9 sales Over $310K 7 sales 0 1,000 2,000 1,541 1,443 1,468 1,977 Living area (SF), average

The average is 1,977 SF for homes over $310K and 1,541 SF for homes under $260K. It does not move in a straight line; homes over $310K are highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-26T05:35:48.739096 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $260K 7 sales $260K– $274K 6 sales $280K– $310K 9 sales Over $310K 7 sales 1984 1987 1990 1993 1996 1985 1990 1986 1995 Year built: median (dot) and middle half (bar)

The median is 1995 for homes over $310K and 1985 for homes under $260K. It does not move in a straight line; homes over $310K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:35:48.762724 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $260K 7 sales $260K– $274K 6 sales $280K– $310K 9 sales Over $310K 7 sales 0 20 40 60 15 18 35 63 Days on market, median

The median is 63 days for homes over $310K 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

2026-10-26T05:35:48.785625 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $260K 7 sales $260K– $274K 6 sales $280K– $310K 9 sales Over $310K 7 sales 0.0% 5.0% 10.0% 10.8% 3.1% 6.2% 5.1% Discount from original list, average

The average is 5.1% for homes over $310K and 10.8% 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

2026-10-26T05:35:48.815655 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% 29 14 14 0 67 33 44 67 0 57 86 14 Under $260K $260K–$274K $280K–$310K Over $310K

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

  • 57% of homes over $310K had a price cut before sale, against 29% of homes under $260K. Defined in 8.1.7.
  • 86% of homes over $310K had the seller pay closing costs or repairs, against 14% of homes under $260K. Defined in 8.1.8.
  • 14% of homes over $310K have a view, against 14% 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 $260K7 sales$260K–$274K6 sales$280K–$310K9 salesOver $310K7 salesAll29 salesReal difference?
Net sale price average$225,200$269,435$292,000$344,893$283,975by design
Net price per SF average$152$197$208$176$185unclear
Living area average1,5411,4431,4681,9771,603unclear
Year built median19851990198619951993unclear

3.10 The numbers: selling

Under $260K7 sales$260K–$274K6 sales$280K–$310K9 salesOver $310K7 salesAll29 salesReal difference?
Days on market median1518356325unclear
Discount from original list average10.8%3.1%6.2%5.1%6.4%unclear
Price cut before sale29%0%44%57%34%unclear
Seller paid closing costs or repairs14%67%67%86%59%unclear
Has a view14%33%0%14%14%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 · 29 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.

2026-10-26T05:35:48.836266 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 8 7 29 sales Sales per group Under 1,299 SF: 7 sales (24%) 1,299–1,387 SF: 7 sales (24%) 1,440–1,886 SF: 8 sales (28%) Over 1,886 SF: 7 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 1,299 SF1,299–1,387 SF1,440–1,886 SFOver 1,886 SF
Larger homes Over 1,886 SF
  • Sell for less per square foot.
Smaller homes Under 1,299 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 1,299 SF1,299–1,387 SF1,440–1,886 SFOver 1,886 SFReal difference?
Net sale price$272K$251K$291K$320Kunclear
Net price per SF$231 per SFHighest$188 per SF$175 per SF$146 per SFLowest✓ large
Year built1985198519941995unclear
Days on market57 days18 days108 days27 daysunclear
Discount from original list6.3%6.0%10.0%2.8%unclear
Price cut before sale14%29%50%43%unclear
Seller paid closing costs or repairs57%71%38%71%unclear
Has a view14%14%12%14%unclear

4.3 Net sale price: no clear difference

2026-10-26T05:35:48.856917 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,299 SF 7 sales 1,299– 1,387 SF 7 sales 1,440– 1,886 SF 8 sales Over 1,886 SF 7 sales $0K $100K $200K $300K $272K $251K $291K $320K Net sale price, average

The average is $320K for homes over 1,886 SF and $272K for homes under 1,299 SF. It does not move in a straight line; homes over 1,886 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Homes over 1,886 SF sell for about $85 per SF (37%) less than homes under 1,299 SF

2026-10-26T05:35:48.880345 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,299 SF 7 sales 1,299– 1,387 SF 7 sales 1,440– 1,886 SF 8 sales Over 1,886 SF 7 sales $0 $100 $200 $231 $188 $175 $146 Net price per SF, average

The average is $146 per SF for homes over 1,886 SF and $231 per SF for homes under 1,299 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

2026-10-26T05:35:48.904876 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,299 SF 7 sales 1,299– 1,387 SF 7 sales 1,440– 1,886 SF 8 sales Over 1,886 SF 7 sales 1984 1987 1990 1993 1996 1985 1985 1994 1995 Year built: median (dot) and middle half (bar)

The median is 1995 for homes over 1,886 SF and 1985 for homes under 1,299 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

2026-10-26T05:35:48.928725 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,299 SF 7 sales 1,299– 1,387 SF 7 sales 1,440– 1,886 SF 8 sales Over 1,886 SF 7 sales 0 50 100 57 18 108 27 Days on market, median

The median is 27 days for homes over 1,886 SF and 57 days for homes under 1,299 SF. It does not move in a straight line; homes 1,440–1,886 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T05:35:48.950976 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,299 SF 7 sales 1,299– 1,387 SF 7 sales 1,440– 1,886 SF 8 sales Over 1,886 SF 7 sales 0.0% 5.0% 10.0% 6.3% 6.0% 10.0% 2.8% Discount from original list, average

The average is 2.8% for homes over 1,886 SF and 6.3% for homes under 1,299 SF. It does not move in a straight line; homes 1,440–1,886 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

2026-10-26T05:35:48.977284 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% 14 57 14 29 71 14 50 38 12 43 71 14 Under 1,299 SF 1,299–1,387 SF 1,440–1,886 SF Over 1,886 SF

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

  • 43% of homes over 1,886 SF had a price cut before sale, against 14% of homes under 1,299 SF. Defined in 8.1.7.
  • 71% of homes over 1,886 SF had the seller pay closing costs or repairs, against 57% of homes under 1,299 SF. Defined in 8.1.8.
  • 14% of homes over 1,886 SF have a view, against 14% of homes under 1,299 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 1,299 SF7 sales1,299–1,387 SF7 sales1,440–1,886 SF8 salesOver 1,886 SF7 salesAll29 salesReal difference?
Net sale price average$272,080$250,993$291,312$320,465$283,975unclear
Net price per SF average$231$188$175$146$185✓ large
Living area average1,1841,3401,6712,2081,603by design
Year built median19851985199419951993unclear

4.10 The numbers: selling

Under 1,299 SF7 sales1,299–1,387 SF7 sales1,440–1,886 SF8 salesOver 1,886 SF7 salesAll29 salesReal difference?
Days on market median57181082725unclear
Discount from original list average6.3%6.0%10.0%2.8%6.4%unclear
Price cut before sale14%29%50%43%34%unclear
Seller paid closing costs or repairs57%71%38%71%59%unclear
Has a view14%14%12%14%14%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 · 29 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.

2026-10-26T05:35:48.997726 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 6 7 9 29 sales Sales per group Before 1985: 7 sales (24%) 1985–1986: 6 sales (21%) 1993–1994: 7 sales (24%) After 1994: 9 sales (31%)
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$250K$275K$311K$295Kunclear
Net price per SF$200 per SF$212 per SF$174 per SF$162 per SFunclear
Living area1,288 SFSmallest1,302 SF1,810 SF1,888 SFLargest✓ large
Days on market15 days20 days119 days19 daysunclear
Discount from original list6.7%7.1%4.9%6.8%unclear
Price cut before sale14%33%57%33%unclear
Seller paid closing costs or repairs29%83%57%67%unclear
Has a view29%0%0%22%unclear

5.3 Net sale price: no clear difference

2026-10-26T05:35:49.018341 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 7 sales 1985– 1986 6 sales 1993– 1994 7 sales After 1994 9 sales $0K $100K $200K $300K $250K $275K $311K $295K Net sale price, average

The average is $295K for homes built after 1994 and $250K 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

2026-10-26T05:35:49.041899 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 7 sales 1985– 1986 6 sales 1993– 1994 7 sales After 1994 9 sales $0 $100 $200 $200 $212 $174 $162 Net price per SF, average

The average is $162 per SF for homes built after 1994 and $200 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 600 SF (47%) larger than homes built before 1985

2026-10-26T05:35:49.063766 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 7 sales 1985– 1986 6 sales 1993– 1994 7 sales After 1994 9 sales 0 1,000 2,000 1,288 1,302 1,810 1,888 Living area (SF), average

The average is 1,888 SF for homes built after 1994 and 1,288 SF for homes built before 1985. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

5.6 Days on market: no clear difference

2026-10-26T05:35:49.086306 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 7 sales 1985– 1986 6 sales 1993– 1994 7 sales After 1994 9 sales 0 50 100 15 20 119 19 Days on market, median

The median is 19 days for homes built after 1994 and 15 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

2026-10-26T05:35:49.108681 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 7 sales 1985– 1986 6 sales 1993– 1994 7 sales After 1994 9 sales 0.0% 2.5% 5.0% 7.5% 6.7% 7.1% 4.9% 6.8% Discount from original list, average

The average is 6.8% for homes built after 1994 and 6.7% for homes built before 1985. It does not move in a straight line; homes built 1985–1986 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

2026-10-26T05:35:49.134575 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% 14 29 29 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 14% 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 29% of homes built before 1985. Defined in 8.1.8.
  • 22% of homes built after 1994 have a view, against 29% 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 19857 sales1985–19866 sales1993–19947 salesAfter 19949 salesAll29 salesReal difference?
Net sale price average$250,000$275,343$310,671$295,389$283,975unclear
Net price per SF average$200$212$174$162$185unclear
Living area average1,2881,3021,8101,8881,603✓ large
Year built median19831985199319961993by design

5.10 The numbers: selling

Before 19857 sales1985–19866 sales1993–19947 salesAfter 19949 salesAll29 salesReal difference?
Days on market median15201191925unclear
Discount from original list average6.7%7.1%4.9%6.8%6.4%unclear
Price cut before sale14%33%57%33%34%unclear
Seller paid closing costs or repairs29%83%57%67%59%unclear
Has a view29%0%0%22%14%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 · 29 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.

2026-10-26T05:35:49.153521 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 24 28 sales Sales per group View: 4 sales (14%) No view: 24 sales (86%)
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

2026-10-26T05:35:49.169262 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 24 sales $0K $100K $200K $300K $280K $285K Net sale price, average

The average is $280K for homes with a view and $285K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T05:35:49.187863 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 24 sales $0 $50 $100 $150 $200 $187 $183 Net price per SF, average

The average is $187 per SF for homes with a view and $183 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T05:35:49.232013 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 24 sales 0 500 1,000 1,500 1,529 1,628 Living area (SF), average

The average is 1,529 SF for homes with a view and 1,628 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T05:35:49.251195 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 24 sales 1984 1987 1990 1993 1989 1993 Year built: median (dot) and middle half (bar)

The median is 1989 for homes with a view and 1993 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T05:35:49.269846 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 24 sales 0 10 20 30 40 40 26 Days on market, median

The median is 40 days for homes with a view and 26 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

2026-10-26T05:35:49.288593 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 24 sales 0.0% 2.0% 4.0% 6.0% 6.1% 6.6% Discount from original list, average

The average is 6.1% for homes with a view and 6.6% 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

2026-10-26T05:35:49.307442 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 25 50 38 58 View No view

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

  • 25% of homes with a view had a price cut before sale, against 38% of homes without a view. Defined in 8.1.7.
  • 50% 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: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View4 salesNo view24 salesAll28 sales
Net sale price average$280,088$285,019$284,315
Net price per SF average$187$183$184
Living area average1,5291,6281,614
Year built median198919931993

6.11 The numbers: selling

View4 salesNo view24 salesAll28 sales
Days on market median402626
Discount from original list average6.1%6.6%6.5%
Price cut before sale25%38%36%
Seller paid closing costs or repairs50%58%57%

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 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
29 resale sales. Average $283,975; median $280,000; standard deviation $48,035; middle half (25th–75th percentile) $260,000–$310,000; 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
29 resale sales. Average $185; median $184; standard deviation $42; middle half (25th–75th percentile) $159–$211; lowest $107, 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
29 resale sales. Average 1,603; median 1,440; standard deviation 406; middle half (25th–75th percentile) 1,299–1,886; 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
29 resale sales. Average 1990; median 1993; standard deviation 5; middle half (25th–75th percentile) 1985–1995; 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
29 resale sales. Average 64; median 25; standard deviation 82; middle half (25th–75th percentile) 12–96; lowest 0, highest 313. 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
29 resale sales. Average 6.4%; median 5.1%; standard deviation 8.3%; middle half (25th–75th percentile) 3.0%–8.5%; 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
10 of 29 resale sales (34.5%).

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 29 resale sales (58.6%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
4 sales with a view, 24 without, 1 unclassified. Most common View entries: None 16, Neighborhood 10, Trees/Woods 2, 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 26, 2026: 33 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 F Sec 01 (3); Windermere (3); Windermere Ph A Sec 01 (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 16 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
29 single-family sales in the window: 29 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
29 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 (7 sales); $260K–$274K: $260,000–$274,450 (6 sales); $280K–$310K: $280,000–$310,000 (9 sales); Over $310K: $320,000–$375,203 (7 sales)
Quartiles by living area: Under 1,299 SF: 1,034–1,296 SF (7 sales); 1,299–1,387 SF: 1,299–1,387 SF (7 sales); 1,440–1,886 SF: 1,440–1,886 SF (8 sales); Over 1,886 SF: 1,957–2,334 SF (7 sales)
Quartiles by year built: Before 1985: 1983–1984 (7 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 (4 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 $283,975, median $280,000. Days on market: average 64, median 25: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

In simple terms
Checks whether a measure really differs across the four groups of a slice. It uses each sale's rank, not its value, so a few extreme sales cannot drive the answer.
Statistically
H = [12/(n(n+1))] Σ Rⱼ²/nⱼ − 3(n+1), compared with χ² on k − 1 degrees of freedom (Kruskal & Wallis, 1952). Effect size ε² = H/(n − 1): ≥ .01 small, ≥ .06 medium, ≥ .14 large (Tomczak & Tomczak, 2014). A slice is tested only when every group has at least 5 sales; smaller groups are described, not tested.
The data
Run on every measure in sections 3–5; each result is in 8.3.

8.2.8 Mann–Whitney U test

In simple terms
The same check when there are only two groups: view against no view.
Statistically
Two-sided U test (Mann & Whitney, 1947). Effect size = rank-biserial correlation |1 − 2U/(n₁n₂)|: ≥ .10 small, ≥ .30 medium, ≥ .50 large (Kerby, 2014; Cohen, 1988).
The data
Run on every measure in section 6; results in 8.3.

8.2.9 Chi-square test

In simple terms
Checks whether a yes/no share (price cut, seller payment, view) differs between groups more than chance would.
Statistically
Pearson χ² on the 2 × k table of counts, no continuity correction (Pearson, 1900). Effect size Cramér's V = √(χ²/n): ≥ .10 small, ≥ .30 medium, ≥ .50 large (Cramér, 1946).
The data
Run on the three shares in every slice; results in 8.3.

8.2.10 Real difference (significance)

In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063; Quartiles by year built: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

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

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 7.3030.0630p < 0.0063Unclearε² = 0.261large
Living areaKruskal–WallisH = 8.3430.0396p < 0.0063Unclearε² = 0.298large
Year builtKruskal–WallisH = 8.5830.0355p < 0.0063Unclearε² = 0.306large
Days on marketKruskal–WallisH = 4.9030.1789p < 0.0063Unclearε² = 0.175large
Discount from original listKruskal–WallisH = 2.0730.5585p < 0.0063Unclearε² = 0.074medium
Price cut before saleChi-squareχ² = 5.2530.1542p < 0.0063UnclearCramér’s V = 0.426medium
Seller paid closing costs or repairsChi-squareχ² = 8.1930.0422p < 0.0063UnclearCramér’s V = 0.531large
Has a viewChi-squareχ² = 3.3730.3381p < 0.0063UnclearCramér’s V = 0.341medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 6.6230.0852p < 0.0063Unclearε² = 0.236large
Net price per SFKruskal–WallisH = 17.2030.0006p < 0.0063Yesε² = 0.614large
Year builtKruskal–WallisH = 11.1030.0112p < 0.0063Unclearε² = 0.396large
Days on marketKruskal–WallisH = 7.4130.0599p < 0.0063Unclearε² = 0.265large
Discount from original listKruskal–WallisH = 3.3130.3468p < 0.0063Unclearε² = 0.118medium
Price cut before saleChi-squareχ² = 2.4430.4858p < 0.0063UnclearCramér’s V = 0.290small
Seller paid closing costs or repairsChi-squareχ² = 2.4230.4891p < 0.0063UnclearCramér’s V = 0.289small
Has a viewChi-squareχ² = 0.0230.9995p < 0.0063UnclearCramér’s V = 0.023negligible

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 6.2530.1001p < 0.0063Unclearε² = 0.223large
Net price per SFKruskal–WallisH = 7.2530.0643p < 0.0063Unclearε² = 0.259large
Living areaKruskal–WallisH = 13.6630.0034p < 0.0063Yesε² = 0.488large
Days on marketKruskal–WallisH = 5.6730.1286p < 0.0063Unclearε² = 0.203large
Discount from original listKruskal–WallisH = 3.2830.3505p < 0.0063Unclearε² = 0.117medium
Price cut before saleChi-squareχ² = 2.8630.4131p < 0.0063UnclearCramér’s V = 0.314medium
Seller paid closing costs or repairsChi-squareχ² = 4.3630.2249p < 0.0063UnclearCramér’s V = 0.388medium
Has a viewChi-squareχ² = 3.9030.2721p < 0.0063UnclearCramér’s V = 0.367medium

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); 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 29 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.