ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Carmel West

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 · 5:34 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
34
single-family resale homes
Median net sale price
$423,750
average $462,846
Median net price per SF
$175
average $176
Median days on market
51 days
average 87 days
1. SummaryResale homes · 34 sales · October 26, 2025 – October 25, 2026

This study looks at the 34 resale homes sold in Carmel West in the 365 days to October 25, 2026. A full year is used because only 20 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 sold34 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 $357K · 8 sales$357K–$418K · 9 sales$430K–$570K · 9 salesOver $570K · 8 sales
3. Quartiles by net sale priceResale homes · 34 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.

2026-10-26T05:34:33.696647 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 9 9 8 34 sales Sales per group Under $357K: 8 sales (24%) $357K–$418K: 9 sales (26%) $430K–$570K: 9 sales (26%) Over $570K: 8 sales (24%)
Bottom line

3.1 Key differences

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

Under $357K$357K–$418K$430K–$570KOver $570K
Higher-priced homes Over $570K
  • Are much larger.
Lower-priced homes Under $357K
  • Are much smaller.

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 $357K$357K–$418K$430K–$570KOver $570KReal difference?
Net price per SF$188 per SF$177 per SF$172 per SF$166 per SFunclear
Living area1,830 SFSmallest2,316 SF2,910 SF3,824 SFLargest✓ large
Year built2019202020202020unclear
Days on market50 days60 days63 days42 daysunclear
Discount from original list7.9%6.6%6.1%5.0%unclear
Price cut before sale62%44%56%50%unclear
Seller paid closing costs or repairs75%67%44%25%unclear
Has a view0%11%44%25%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

2026-10-26T05:34:33.725318 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $357K 8 sales $357K– $418K 9 sales $430K– $570K 9 sales Over $570K 8 sales $0 $100 $200 $188 $177 $172 $166 Net price per SF, average

The average is $166 per SF for homes over $570K and $188 per SF for homes under $357K. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $570K are about 1,990 SF (109%) larger than homes under $357K

2026-10-26T05:34:33.747393 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $357K 8 sales $357K– $418K 9 sales $430K– $570K 9 sales Over $570K 8 sales 0 2,000 4,000 1,830 2,316 2,910 3,824 Living area (SF), average

The average is 3,824 SF for homes over $570K and 1,830 SF for homes under $357K. 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

2026-10-26T05:34:33.771506 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $357K 8 sales $357K– $418K 9 sales $430K– $570K 9 sales Over $570K 8 sales 2018 2019 2020 2021 2019 2020 2020 2020 Year built: median (dot) and middle half (bar)

The median is 2020 for homes over $570K and 2019 for homes under $357K. It rises 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

2026-10-26T05:34:33.794243 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $357K 8 sales $357K– $418K 9 sales $430K– $570K 9 sales Over $570K 8 sales 0 20 40 60 50 60 63 42 Days on market, median

The median is 42 days for homes over $570K and 50 days for homes under $357K. It does not move in a straight line; homes $430K–$570K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:34:33.816830 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $357K 8 sales $357K– $418K 9 sales $430K– $570K 9 sales Over $570K 8 sales 0.0% 2.5% 5.0% 7.5% 7.9% 6.6% 6.1% 5.0% Discount from original list, average

The average is 5.0% for homes over $570K and 7.9% for homes under $357K. It falls step by step from the lowest range to the 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

2026-10-26T05:34:33.847279 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% 62 75 0 44 67 11 56 44 44 50 25 25 Under $357K $357K–$418K $430K–$570K Over $570K

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

  • 50% of homes over $570K had a price cut before sale, against 62% of homes under $357K. Defined in 8.1.7.
  • 25% of homes over $570K had the seller pay closing costs or repairs, against 75% of homes under $357K. Defined in 8.1.8.
  • 25% of homes over $570K have a view, against 0% of homes under $357K. 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 $357K8 sales$357K–$418K9 sales$430K–$570K9 salesOver $570K8 salesAll34 salesReal difference?
Net sale price average$336,460$399,317$494,583$625,000$462,846by design
Net price per SF average$188$177$172$166$176unclear
Living area average1,8302,3162,9103,8242,714✓ large
Year built median20192020202020202020unclear

3.10 The numbers: selling

Under $357K8 sales$357K–$418K9 sales$430K–$570K9 salesOver $570K8 salesAll34 salesReal difference?
Days on market median5060634251unclear
Discount from original list average7.9%6.6%6.1%5.0%6.4%unclear
Price cut before sale62%44%56%50%53%unclear
Seller paid closing costs or repairs75%67%44%25%53%unclear
Has a view0%11%44%25%21%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 · 34 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.

2026-10-26T05:34:33.868241 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 9 9 8 34 sales Sales per group Under 1,912 SF: 8 sales (24%) 1,912–2,632 SF: 9 sales (26%) 2,656–3,357 SF: 9 sales (26%) Over 3,357 SF: 8 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 1,912 SF1,912–2,632 SF2,656–3,357 SFOver 3,357 SF
Larger homes Over 3,357 SF
  • Sell for much more.
  • Sell for less per square foot.
Smaller homes Under 1,912 SF
  • Sell for much less.
  • 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 1,912 SF1,912–2,632 SF2,656–3,357 SFOver 3,357 SFReal difference?
Net sale price$340KLowest$428K$469K$618KHighest✓ large
Net price per SF$201 per SFHighest$182 per SF$160 per SFLowest$160 per SF✓ large
Year built2019202020202020unclear
Days on market48 days60 days108 days42 daysunclear
Discount from original list5.2%5.8%8.1%6.5%unclear
Price cut before sale50%33%78%50%unclear
Seller paid closing costs or repairs88%33%67%25%unclear
Has a view0%22%22%38%unclear

4.3 Homes over 3,357 SF sell for about $277K (82%) more than homes under 1,912 SF

2026-10-26T05:34:33.888967 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,912 SF 8 sales 1,912– 2,632 SF 9 sales 2,656– 3,357 SF 9 sales Over 3,357 SF 8 sales $0K $200K $400K $600K $340K $428K $469K $618K Net sale price, average

The average is $618K for homes over 3,357 SF and $340K for homes under 1,912 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 3,357 SF sell for about $41 per SF (20%) less than homes under 1,912 SF

2026-10-26T05:34:33.911582 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,912 SF 8 sales 1,912– 2,632 SF 9 sales 2,656– 3,357 SF 9 sales Over 3,357 SF 8 sales $0 $100 $200 $201 $182 $160 $160 Net price per SF, average

The average is $160 per SF for homes over 3,357 SF and $201 per SF for homes under 1,912 SF. It does not move in a straight line; homes under 1,912 SF are highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-10-26T05:34:33.934950 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,912 SF 8 sales 1,912– 2,632 SF 9 sales 2,656– 3,357 SF 9 sales Over 3,357 SF 8 sales 2018 2019 2020 2021 2019 2020 2020 2020 Year built: median (dot) and middle half (bar)

The median is 2020 for homes over 3,357 SF and 2019 for homes under 1,912 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

2026-10-26T05:34:33.957966 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,912 SF 8 sales 1,912– 2,632 SF 9 sales 2,656– 3,357 SF 9 sales Over 3,357 SF 8 sales 0 50 100 48 60 108 42 Days on market, median

The median is 42 days for homes over 3,357 SF and 48 days for homes under 1,912 SF. It does not move in a straight line; homes 2,656–3,357 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T05:34:33.980455 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,912 SF 8 sales 1,912– 2,632 SF 9 sales 2,656– 3,357 SF 9 sales Over 3,357 SF 8 sales 0.0% 2.5% 5.0% 7.5% 5.2% 5.8% 8.1% 6.5% Discount from original list, average

The average is 6.5% for homes over 3,357 SF and 5.2% for homes under 1,912 SF. It does not move in a straight line; homes 2,656–3,357 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

2026-10-26T05:34:34.007293 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 88 0 33 33 22 78 67 22 50 25 38 Under 1,912 SF 1,912–2,632 SF 2,656–3,357 SF Over 3,357 SF

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

  • 50% of homes over 3,357 SF had a price cut before sale, against 50% of homes under 1,912 SF. Defined in 8.1.7.
  • 25% of homes over 3,357 SF had the seller pay closing costs or repairs, against 88% of homes under 1,912 SF. Defined in 8.1.8.
  • 38% of homes over 3,357 SF have a view, against 0% of homes under 1,912 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 1,912 SF8 sales1,912–2,632 SF9 sales2,656–3,357 SF9 salesOver 3,357 SF8 salesAll34 salesReal difference?
Net sale price average$340,116$428,367$468,950$617,500$462,846✓ large
Net price per SF average$201$182$160$160$176✓ large
Living area average1,7022,3532,9263,8932,714by design
Year built median20192020202020202020unclear

4.10 The numbers: selling

Under 1,912 SF8 sales1,912–2,632 SF9 sales2,656–3,357 SF9 salesOver 3,357 SF8 salesAll34 salesReal difference?
Days on market median48601084251unclear
Discount from original list average5.2%5.8%8.1%6.5%6.4%unclear
Price cut before sale50%33%78%50%53%unclear
Seller paid closing costs or repairs88%33%67%25%53%unclear
Has a view0%22%22%38%21%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 · 34 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.

2026-10-26T05:34:34.027812 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 9 10 7 34 sales Sales per group Before 2019: 8 sales (24%) 2019: 9 sales (26%) 2020: 10 sales (29%) After 2020: 7 sales (21%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

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

5.2 At a glance

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

Before 201920192020After 2020Real difference?
Net sale price$432K$414K$518K$481Kunclear
Net price per SF$172 per SF$176 per SF$179 per SF$174 per SFunclear
Living area2,574 SF2,405 SF3,058 SF2,777 SFunclear
Days on market36 days75 days30 days75 daysunclear
Discount from original list6.6%8.7%5.0%5.4%unclear
Price cut before sale62%67%30%57%unclear
Seller paid closing costs or repairs50%67%50%43%unclear
Has a view0%11%40%29%unclear

5.3 Net sale price: no clear difference

2026-10-26T05:34:34.048082 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 8 sales 2019 9 sales 2020 10 sales After 2020 7 sales $0K $200K $400K $600K $432K $414K $518K $481K Net sale price, average

The average is $481K for homes built after 2020 and $432K for homes built before 2019. It does not move in a straight line; homes built 2020 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T05:34:34.071522 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 8 sales 2019 9 sales 2020 10 sales After 2020 7 sales $0 $50 $100 $150 $200 $172 $176 $179 $174 Net price per SF, average

The average is $174 per SF for homes built after 2020 and $172 per SF for homes built before 2019. It does not move in a straight line; homes built 2020 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T05:34:34.093107 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 8 sales 2019 9 sales 2020 10 sales After 2020 7 sales 0 1,000 2,000 3,000 2,574 2,405 3,058 2,777 Living area (SF), average

The average is 2,777 SF for homes built after 2020 and 2,574 SF for homes built before 2019. It does not move in a straight line; homes built 2020 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T05:34:34.115184 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 8 sales 2019 9 sales 2020 10 sales After 2020 7 sales 0 20 40 60 80 36 75 30 75 Days on market, median

The median is 75 days for homes built after 2020 and 36 days for homes built before 2019. It does not move in a straight line; homes built 2019 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T05:34:34.139013 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 8 sales 2019 9 sales 2020 10 sales After 2020 7 sales 0.0% 2.5% 5.0% 7.5% 10.0% 6.6% 8.7% 5.0% 5.4% Discount from original list, average

The average is 5.4% for homes built after 2020 and 6.6% for homes built before 2019. It does not move in a straight line; homes built 2019 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

2026-10-26T05:34:34.166485 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% 62 50 0 67 67 11 30 50 40 57 43 29 Before 2019 2019 2020 After 2020

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

  • 57% of homes built after 2020 had a price cut before sale, against 62% of homes built before 2019. Defined in 8.1.7.
  • 43% of homes built after 2020 had the seller pay closing costs or repairs, against 50% of homes built before 2019. Defined in 8.1.8.
  • 29% of homes built after 2020 have a view, against 0% of homes built before 2019. 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 20198 sales20199 sales202010 salesAfter 20207 salesAll34 salesReal difference?
Net sale price average$432,431$413,998$518,405$481,043$462,846unclear
Net price per SF average$172$176$179$174$176unclear
Living area average2,5742,4053,0582,7772,714unclear
Year built median20182019202020212020by design

5.10 The numbers: selling

Before 20198 sales20199 sales202010 salesAfter 20207 salesAll34 salesReal difference?
Days on market median3675307551unclear
Discount from original list average6.6%8.7%5.0%5.4%6.4%unclear
Price cut before sale62%67%30%57%53%unclear
Seller paid closing costs or repairs50%67%50%43%53%unclear
Has a view0%11%40%29%21%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 · 34 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. 2 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T05:34:34.186846 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 25 32 sales Sales per group View: 7 sales (22%) No view: 25 sales (78%)
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$544K$443Kunclear
Net price per SF$170 per SF$179 per SFunclear
Living area3,324 SF2,532 SFunclear
Year built20202019unclear
Days on market63 days48 daysunclear
Discount from original list6.9%5.9%unclear
Price cut before sale57%48%unclear
Seller paid closing costs or repairs57%48%unclear

6.3 Net sale price: no clear difference

2026-10-26T05:34:34.202814 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 25 sales $0K $200K $400K $600K $544K $443K Net sale price, average

The average is $544K for homes with a view and $443K 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

2026-10-26T05:34:34.221279 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 25 sales $0 $50 $100 $150 $200 $170 $179 Net price per SF, average

The average is $170 per SF for homes with a view and $179 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

2026-10-26T05:34:34.240177 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 25 sales 0 1,000 2,000 3,000 3,324 2,532 Living area (SF), average

The average is 3,324 SF for homes with a view and 2,532 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T05:34:34.327187 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 25 sales 2018 2019 2020 2020 2019 Year built: median (dot) and middle half (bar)

The median is 2020 for homes with a view and 2019 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T05:34:34.345670 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 25 sales 0 20 40 60 63 48 Days on market, median

The median is 63 days for homes with a view and 48 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

2026-10-26T05:34:34.365342 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 25 sales 0.0% 2.0% 4.0% 6.0% 8.0% 6.9% 5.9% Discount from original list, average

The average is 6.9% for homes with a view and 5.9% 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

2026-10-26T05:34:34.384916 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 57 57 48 48 View No view

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

  • 57% of homes with a view had a price cut before sale, against 48% of homes without a view. Defined in 8.1.7.
  • 57% of homes with a view had the seller pay closing costs or repairs, against 48% 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

View7 salesNo view25 salesAll32 salesReal difference?
Net sale price average$544,286$442,581$464,829unclear
Net price per SF average$170$179$177unclear
Living area average3,3242,5322,705unclear
Year built median202020192020unclear

6.11 The numbers: selling

View7 salesNo view25 salesAll32 salesReal difference?
Days on market median634850unclear
Discount from original list average6.9%5.9%6.2%unclear
Price cut before sale57%48%50%unclear
Seller paid closing costs or repairs57%48%50%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 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 Carmel West.

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
34 resale sales. Average $462,846; median $423,750; standard deviation $112,919; middle half (25th–75th percentile) $357,788–$566,250; lowest $309,260, highest $697,000. 18 sales had a seller payment; their median payment was $2,750.

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
34 resale sales. Average $176; median $175; standard deviation $25; middle half (25th–75th percentile) $159–$190; lowest $124, highest $227.

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
34 resale sales. Average 2,714; median 2,644; standard deviation 859; middle half (25th–75th percentile) 1,974–3,292; lowest 1,486, highest 5,173.

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
34 resale sales. Average 2020; median 2020; standard deviation 1; middle half (25th–75th percentile) 2019–2020; lowest 2018, highest 2022.

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
34 resale sales. Average 87; median 51; standard deviation 96; middle half (25th–75th percentile) 22–114; lowest 6, highest 456. 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
34 resale sales. Average 6.4%; median 4.5%; standard deviation 5.1%; middle half (25th–75th percentile) 3.5%–9.7%; lowest 0.0%, highest 24.4%. 0 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
18 of 34 resale sales (52.9%).

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
18 of 34 resale sales (52.9%).

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
7 sales with a view, 25 without, 2 unclassified. Most common View entries: None 15, Neighborhood 14, Park/Greenbelt 3, Trees/Woods 2, See Remarks 2, Pasture 2, Pool 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 “carmel west”, “carmel” (case-insensitive). A record is kept when its subdivision name belongs to the Carmel West family, the same rule comparable sales use (it includes Carmel, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 34 closed Carmel West records over the prior year, in ZIP 78660. 10 subdivision spellings kept: Carmel (15); Carmel West (8); Carmel West Ph 1 Sec 1 (2); Carmel West Ph 2 Sec 5 (2); Carmel West Ph 2 Sec 1 (2); CARMEL WEST PH S 2 SEC 5 (1); Carmel West Ph 2 Sec 2 (1); Carmel West Ph 1 Sec 2 (1); CARMEL (1); Carmel West Ph 3 Sec 2 (1). Names found by the search but not part of Carmel West, left out: The Trails at Carmel (6).

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 20 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
34 single-family sales in the window: 34 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
34 resale; 0 new construction.

8.2.4 Sales left out

In simple terms
A few records cannot be used as entered and are left out before any analysis.
Statistically
Excluded: PropertySubType other than Single Family Residence; no OriginalListPrice; LivingArea under 400 SF; seller payments above 10% of ClosePrice (treated as entry errors).
The data
None in this window.

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $357K”.
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 $357K: $309,260–$354,200 (8 sales); $357K–$418K: $357,050–$417,500 (9 sales); $430K–$570K: $430,000–$570,000 (9 sales); Over $570K: $575,000–$697,000 (8 sales)
Quartiles by living area: Under 1,912 SF: 1,486–1,854 SF (8 sales); 1,912–2,632 SF: 1,912–2,632 SF (9 sales); 2,656–3,357 SF: 2,656–3,357 SF (9 sales); Over 3,357 SF: 3,411–5,173 SF (8 sales)
Quartiles by year built: Before 2019: 2018–2018 (8 sales); 2019: 2019–2019 (9 sales); 2020: 2020–2020 (10 sales); After 2020: 2021–2022 (7 sales)
View and no view: View: MLS lists a view (7 sales); No view: None or Neighborhood (25 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 $462,846, median $423,750. Days on market: average 87, median 51: 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
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 = 3.5930.3095p < 0.0063Unclearε² = 0.109medium
Living areaKruskal–WallisH = 24.883< 0.0001p < 0.0063Yesε² = 0.754large
Year builtKruskal–WallisH = 6.9430.0738p < 0.0063Unclearε² = 0.210large
Days on marketKruskal–WallisH = 0.3830.9441p < 0.0063Unclearε² = 0.012small
Discount from original listKruskal–WallisH = 0.5430.9111p < 0.0063Unclearε² = 0.016small
Price cut before saleChi-squareχ² = 0.6130.8949p < 0.0063UnclearCramér’s V = 0.134small
Seller paid closing costs or repairsChi-squareχ² = 5.0130.1710p < 0.0063UnclearCramér’s V = 0.384medium
Has a viewChi-squareχ² = 5.8030.1219p < 0.0063UnclearCramér’s V = 0.413medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 24.703< 0.0001p < 0.0063Yesε² = 0.748large
Net price per SFKruskal–WallisH = 17.2330.0006p < 0.0063Yesε² = 0.522large
Year builtKruskal–WallisH = 2.1030.5512p < 0.0063Unclearε² = 0.064medium
Days on marketKruskal–WallisH = 3.6430.3032p < 0.0063Unclearε² = 0.110medium
Discount from original listKruskal–WallisH = 3.0930.3780p < 0.0063Unclearε² = 0.094medium
Price cut before saleChi-squareχ² = 3.6730.2990p < 0.0063UnclearCramér’s V = 0.329medium
Seller paid closing costs or repairsChi-squareχ² = 8.4130.0382p < 0.0063UnclearCramér’s V = 0.497medium
Has a viewChi-squareχ² = 3.5030.3204p < 0.0063UnclearCramér’s V = 0.321medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 5.4530.1415p < 0.0063Unclearε² = 0.165large
Net price per SFKruskal–WallisH = 0.5330.9130p < 0.0063Unclearε² = 0.016small
Living areaKruskal–WallisH = 2.3630.5010p < 0.0063Unclearε² = 0.072medium
Days on marketKruskal–WallisH = 3.3330.3436p < 0.0063Unclearε² = 0.101medium
Discount from original listKruskal–WallisH = 1.8130.6133p < 0.0063Unclearε² = 0.055small
Price cut before saleChi-squareχ² = 3.1430.3711p < 0.0063UnclearCramér’s V = 0.304medium
Seller paid closing costs or repairsChi-squareχ² = 1.0330.7943p < 0.0063UnclearCramér’s V = 0.174small
Has a viewChi-squareχ² = 5.1530.1614p < 0.0063UnclearCramér’s V = 0.389medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 130.00—0.0555p < 0.0063Unclearrank-biserial r = 0.486medium
Net price per SFMann–Whitney UU = 67.00—0.3702p < 0.0063Unclearrank-biserial r = 0.234small
Living areaMann–Whitney UU = 128.50—0.0647p < 0.0063Unclearrank-biserial r = 0.469medium
Year builtMann–Whitney UU = 126.00—0.0736p < 0.0063Unclearrank-biserial r = 0.440medium
Days on marketMann–Whitney UU = 102.00—0.5232p < 0.0063Unclearrank-biserial r = 0.166small
Discount from original listMann–Whitney UU = 110.00—0.3159p < 0.0063Unclearrank-biserial r = 0.257small
Price cut before saleChi-squareχ² = 0.1810.6689p < 0.0063UnclearCramér’s V = 0.076negligible
Seller paid closing costs or repairsChi-squareχ² = 0.1810.6689p < 0.0063UnclearCramér’s V = 0.076negligible

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); nothing else. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

  1. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Erlbaum.
  2. Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press.
  3. Dunn, O. J. (1961). Multiple comparisons among means. JASA, 56(293), 52–64.
  4. Kerby, D. S. (2014). The simple difference formula: an approach to teaching nonparametric correlation. Comprehensive Psychology, 3, 11.IT.3.1.
  5. Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. JASA, 47(260), 583–621.
  6. Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18(1), 50–60.
  7. Pearson, K. (1900). On the criterion that a given system of deviations… Philosophical Magazine, 50(302), 157–175.
  8. Tomczak, M., & Tomczak, E. (2014). The need to report effect size estimates revisited. Trends in Sport Sciences, 21(1), 19–25.

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 34 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.