ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Cantarra

Pflugerville, TX 78660
Resale homes · closed Nov 5 – Nov 4, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 5, 2026 · 3:56 PM CST
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
26
single-family resale homes
Median net sale price
$305,750
average $323,361
Median net price per SF
$183
average $180
Median days on market
73 days
average 103 days
1. SummaryResale homes · 26 sales · November 5, 2025 – November 4, 2026

This study looks at the 26 resale homes sold in Cantarra in the 365 days to November 4, 2026. A full year is used because only 13 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 sold26 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 $292K · 6 sales$292K–$305K · 7 sales$306K–$367K · 7 salesOver $367K · 6 sales
3. Quartiles by net sale priceResale homes · 26 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T15:56:53.024229 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 7 7 6 26 sales Sales per group Under $292K: 6 sales (23%) $292K–$305K: 7 sales (27%) $306K–$367K: 7 sales (27%) Over $367K: 6 sales (23%)
Bottom line

3.1 Key differences

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

Under $292K$292K–$305K$306K–$367KOver $367K
Higher-priced homes Over $367K
  • Are much larger.
Lower-priced homes Under $292K
  • 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 $292K$292K–$305K$306K–$367KOver $367KReal difference?
Net price per SF$181 per SF$188 per SF$175 per SF$176 per SFunclear
Living area1,480 SFSmallest1,583 SF2,011 SF2,217 SFLargest✓ large
Year built2012202020192018unclear
Days on market58 days51 days205 days68 daysunclear
Discount from original list13.1%10.3%6.8%7.4%unclear
Price cut before sale50%57%57%83%unclear
Seller paid closing costs or repairs50%100%57%33%unclear
Has a view17%14%0%50%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

2026-11-05T15:56:53.051922 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $292K 6 sales $292K– $305K 7 sales $306K– $367K 7 sales Over $367K 6 sales $0 $100 $200 $181 $188 $175 $176 Net price per SF, average

The average is $176 per SF for homes over $367K and $181 per SF for homes under $292K. It does not move in a straight line; homes $292K–$305K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $367K are about 740 SF (50%) larger than homes under $292K

2026-11-05T15:56:53.074093 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $292K 6 sales $292K– $305K 7 sales $306K– $367K 7 sales Over $367K 6 sales 0 1,000 2,000 1,480 1,583 2,011 2,217 Living area (SF), average

The average is 2,217 SF for homes over $367K and 1,480 SF for homes under $292K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-11-05T15:56:53.098373 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $292K 6 sales $292K– $305K 7 sales $306K– $367K 7 sales Over $367K 6 sales 2008 2011 2014 2017 2020 2012 2020 2019 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over $367K and 2012 for homes under $292K. It does not move in a straight line; homes $292K–$305K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-05T15:56:53.121156 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $292K 6 sales $292K– $305K 7 sales $306K– $367K 7 sales Over $367K 6 sales 0 100 200 58 51 205 68 Days on market, median

The median is 68 days for homes over $367K and 58 days for homes under $292K. It does not move in a straight line; homes $306K–$367K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-05T15:56:53.142244 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $292K 6 sales $292K– $305K 7 sales $306K– $367K 7 sales Over $367K 6 sales 0.0% 5.0% 10.0% 15.0% 13.1% 10.3% 6.8% 7.4% Discount from original list, average

The average is 7.4% for homes over $367K and 13.1% for homes under $292K. It does not move in a straight line; homes under $292K are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-05T15:56:53.171688 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 50 17 57 100 14 57 57 0 83 33 50 Under $292K $292K–$305K $306K–$367K Over $367K

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

  • 83% of homes over $367K had a price cut before sale, against 50% of homes under $292K. Defined in 8.1.7.
  • 33% of homes over $367K had the seller pay closing costs or repairs, against 50% of homes under $292K. Defined in 8.1.8.
  • 50% of homes over $367K have a view, against 17% of homes under $292K. 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 $292K6 sales$292K–$305K7 sales$306K–$367K7 salesOver $367K6 salesAll26 salesReal difference?
Net sale price average$263,454$297,789$347,907$384,467$323,361by design
Net price per SF average$181$188$175$176$180unclear
Living area average1,4801,5832,0112,2171,821✓ large
Year built median20122020201920182018unclear

3.10 The numbers: selling

Under $292K6 sales$292K–$305K7 sales$306K–$367K7 salesOver $367K6 salesAll26 salesReal difference?
Days on market median58512056873unclear
Discount from original list average13.1%10.3%6.8%7.4%9.3%unclear
Price cut before sale50%57%57%83%62%unclear
Seller paid closing costs or repairs50%100%57%33%62%unclear
Has a view17%14%0%50%19%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 · 26 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T15:56:53.191790 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 6 7 6 26 sales Sales per group Under 1,538 SF: 7 sales (27%) 1,538–1,707 SF: 6 sales (23%) 1,779–2,017 SF: 7 sales (27%) Over 2,017 SF: 6 sales (23%)
Bottom line

4.1 Key differences

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

Under 1,538 SF1,538–1,707 SF1,779–2,017 SFOver 2,017 SF
Larger homes Over 2,017 SF
  • Sell for much more.
  • Sell for less per square foot.
Smaller homes Under 1,538 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 1,538 SF1,538–1,707 SF1,779–2,017 SFOver 2,017 SFReal difference?
Net sale price$285K$278KLowest$359K$372KHighest✓ large
Net price per SF$198 per SFHighest$170 per SF$189 per SF$159 per SFLowest✓ large
Year built2018201920192016unclear
Days on market51 days62 days74 days118 daysunclear
Discount from original list5.2%19.1%6.1%8.2%unclear
Price cut before sale29%83%71%67%unclear
Seller paid closing costs or repairs86%67%43%50%unclear
Has a view29%0%0%50%unclear

4.3 Homes over 2,017 SF sell for about $87K (30%) more than homes under 1,538 SF

2026-11-05T15:56:53.211862 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,538 SF 7 sales 1,538– 1,707 SF 6 sales 1,779– 2,017 SF 7 sales Over 2,017 SF 6 sales $0K $200K $400K $285K $278K $359K $372K Net sale price, average

The average is $372K for homes over 2,017 SF and $285K for homes under 1,538 SF. It does not move in a straight line; homes over 2,017 SF are highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 2,017 SF sell for about $39 per SF (20%) less than homes under 1,538 SF

2026-11-05T15:56:53.233758 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,538 SF 7 sales 1,538– 1,707 SF 6 sales 1,779– 2,017 SF 7 sales Over 2,017 SF 6 sales $0 $100 $200 $198 $170 $189 $159 Net price per SF, average

The average is $159 per SF for homes over 2,017 SF and $198 per SF for homes under 1,538 SF. It does not move in a straight line; homes under 1,538 SF are highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-11-05T15:56:53.257609 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,538 SF 7 sales 1,538– 1,707 SF 6 sales 1,779– 2,017 SF 7 sales Over 2,017 SF 6 sales 2012 2014 2016 2018 2020 2018 2019 2019 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over 2,017 SF and 2018 for homes under 1,538 SF. It does not move in a straight line; homes 1,538–1,707 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-05T15:56:53.280597 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,538 SF 7 sales 1,538– 1,707 SF 6 sales 1,779– 2,017 SF 7 sales Over 2,017 SF 6 sales 0 50 100 51 62 74 118 Days on market, median

The median is 118 days for homes over 2,017 SF and 51 days for homes under 1,538 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-05T15:56:53.301775 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,538 SF 7 sales 1,538– 1,707 SF 6 sales 1,779– 2,017 SF 7 sales Over 2,017 SF 6 sales 0.0% 10.0% 20.0% 5.2% 19.1% 6.1% 8.2% Discount from original list, average

The average is 8.2% for homes over 2,017 SF and 5.2% for homes under 1,538 SF. It does not move in a straight line; homes 1,538–1,707 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-05T15:56:53.327521 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 86 29 83 67 0 71 43 0 67 50 50 Under 1,538 SF 1,538–1,707 SF 1,779–2,017 SF Over 2,017 SF

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

  • 67% of homes over 2,017 SF had a price cut before sale, against 29% of homes under 1,538 SF. Defined in 8.1.7.
  • 50% of homes over 2,017 SF had the seller pay closing costs or repairs, against 86% of homes under 1,538 SF. Defined in 8.1.8.
  • 50% of homes over 2,017 SF have a view, against 29% of homes under 1,538 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 1,538 SF7 sales1,538–1,707 SF6 sales1,779–2,017 SF7 salesOver 2,017 SF6 salesAll26 salesReal difference?
Net sale price average$285,340$277,978$358,593$372,000$323,361✓ large
Net price per SF average$198$170$189$159$180✓ large
Living area average1,4451,6411,8952,3521,821by design
Year built median20182019201920162018unclear

4.10 The numbers: selling

Under 1,538 SF7 sales1,538–1,707 SF6 sales1,779–2,017 SF7 salesOver 2,017 SF6 salesAll26 salesReal difference?
Days on market median51627411873unclear
Discount from original list average5.2%19.1%6.1%8.2%9.3%unclear
Price cut before sale29%83%71%67%62%unclear
Seller paid closing costs or repairs86%67%43%50%62%unclear
Has a view29%0%0%50%19%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 · 26 sales · November 5, 2025 – November 4, 2026

Sales ranked by year built and cut into four groups, from the oldest to the newest. Homes built in the same year always stay in the same group, so group sizes can differ a little.

2026-11-05T15:56:53.347394 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 9 4 8 26 sales Sales per group Before 2015: 5 sales (19%) 2015–2018: 9 sales (35%) 2019: 4 sales (15%) After 2019: 8 sales (31%)
Bottom line: too few sales to test.

5.1 Key differences

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

5.3 Net sale price: described, not tested

2026-11-05T15:56:53.366842 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 5 sales 2015– 2018 9 sales 2019 4 sales After 2019 8 sales $0K $200K $400K $297K $336K $325K $325K Net sale price, average

The average is $325K for homes built after 2019 and $297K for homes built before 2015. It does not move in a straight line; homes built 2015–2018 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-11-05T15:56:53.388684 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 5 sales 2015– 2018 9 sales 2019 4 sales After 2019 8 sales $0 $100 $200 $170 $176 $181 $191 Net price per SF, average

The average is $191 per SF for homes built after 2019 and $170 per SF for homes built before 2015. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-11-05T15:56:53.409555 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 5 sales 2015– 2018 9 sales 2019 4 sales After 2019 8 sales 0 1,000 2,000 1,810 1,942 1,794 1,704 Living area (SF), average

The average is 1,704 SF for homes built after 2019 and 1,810 SF for homes built before 2015. It does not move in a straight line; homes built 2015–2018 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-11-05T15:56:53.430153 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 5 sales 2015– 2018 9 sales 2019 4 sales After 2019 8 sales 0 50 100 150 72 136 62 49 Days on market, median

The median is 49 days for homes built after 2019 and 72 days for homes built before 2015. It does not move in a straight line; homes built 2015–2018 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-11-05T15:56:53.451975 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 5 sales 2015– 2018 9 sales 2019 4 sales After 2019 8 sales 0.0% 5.0% 10.0% 15.0% 14.6% 9.0% 4.3% 9.0% Discount from original list, average

The average is 9.0% for homes built after 2019 and 14.6% for homes built before 2015. It does not move in a straight line; homes built before 2015 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-11-05T15:56:53.476867 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% 60 20 40 67 78 33 75 50 0 50 75 0 Before 2015 2015–2018 2019 After 2019

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

  • 50% of homes built after 2019 had a price cut before sale, against 60% of homes built before 2015. Defined in 8.1.7.
  • 75% of homes built after 2019 had the seller pay closing costs or repairs, against 20% of homes built before 2015. Defined in 8.1.8.
  • 0% of homes built after 2019 have a view, against 40% of homes built before 2015. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

5.9 The numbers: price and size

Before 20155 sales2015–20189 sales20194 salesAfter 20198 salesAll26 sales
Net sale price average$297,400$335,796$324,706$324,927$323,361
Net price per SF average$170$176$181$191$180
Living area average1,8101,9421,7941,7041,821
Year built median20082017201920202018

5.10 The numbers: selling

Before 20155 sales2015–20189 sales20194 salesAfter 20198 salesAll26 sales
Days on market median72136624973
Discount from original list average14.6%9.0%4.3%9.0%9.3%
Price cut before sale60%67%75%50%62%
Seller paid closing costs or repairs20%78%50%75%62%
Has a view40%33%0%0%19%

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 · 26 sales · November 5, 2025 – November 4, 2026

Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-11-05T15:56:53.495056 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 20 25 sales Sales per group View: 5 sales (20%) No view: 20 sales (80%)
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$349K$318Kunclear
Net price per SF$174 per SF$182 per SFunclear
Living area2,062 SF1,766 SFunclear
Year built20182019unclear
Days on market61 days74 daysunclear
Discount from original list7.4%9.8%unclear
Price cut before sale60%60%unclear
Seller paid closing costs or repairs40%65%unclear

6.3 Net sale price: no clear difference

2026-11-05T15:56:53.511273 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 20 sales $0K $100K $200K $300K $400K $349K $318K Net sale price, average

The average is $349K for homes with a view and $318K 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

2026-11-05T15:56:53.529753 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 20 sales $0 $50 $100 $150 $200 $174 $182 Net price per SF, average

The average is $174 per SF for homes with a view and $182 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

2026-11-05T15:56:53.547987 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 20 sales 0 500 1,000 1,500 2,000 2,062 1,766 Living area (SF), average

The average is 2,062 SF for homes with a view and 1,766 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-05T15:56:53.589813 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 20 sales 2012 2014 2016 2018 2020 2018 2019 Year built: median (dot) and middle half (bar)

The median is 2018 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

2026-11-05T15:56:53.608227 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 20 sales 0 20 40 60 80 61 74 Days on market, median

The median is 61 days for homes with a view and 74 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

2026-11-05T15:56:53.627371 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 20 sales 0.0% 2.5% 5.0% 7.5% 10.0% 7.4% 9.8% Discount from original list, average

The average is 7.4% for homes with a view and 9.8% 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

2026-11-05T15:56:53.645779 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 60 40 60 65 View No view

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

  • 60% of homes with a view had a price cut before sale, against 60% 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 65% 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 view20 salesAll25 salesReal difference?
Net sale price average$348,812$317,924$324,101unclear
Net price per SF average$174$182$180unclear
Living area average2,0621,7661,825unclear
Year built median201820192018unclear

6.11 The numbers: selling

View5 salesNo view20 salesAll25 salesReal difference?
Days on market median617474unclear
Discount from original list average7.4%9.8%9.4%unclear
Price cut before sale60%60%60%unclear
Seller paid closing costs or repairs40%65%60%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 · November 5, 2025 – November 4, 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 Cantarra.

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
26 resale sales. Average $323,361; median $305,750; standard deviation $49,992; middle half (25th–75th percentile) $292,250–$366,962; lowest $192,500, highest $400,000. 16 sales had a seller payment; their median payment was $7,500.

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
26 resale sales. Average $180; median $183; standard deviation $22; middle half (25th–75th percentile) $173–$195; lowest $116, highest $218.

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
26 resale sales. Average 1,821; median 1,743; standard deviation 365; middle half (25th–75th percentile) 1,525–2,017; lowest 1,203, highest 2,642.

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
26 resale sales. Average 2017; median 2018; standard deviation 4; middle half (25th–75th percentile) 2015–2020; lowest 2008, highest 2021.

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
26 resale sales. Average 103; median 73; standard deviation 88; middle half (25th–75th percentile) 40–160; lowest 5, highest 305. 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
26 resale sales. Average 9.3%; median 7.2%; standard deviation 10.0%; middle half (25th–75th percentile) 3.3%–12.1%; lowest −1.8%, highest 51.1%. 1 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
16 of 26 resale sales (61.5%).

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
16 of 26 resale sales (61.5%).

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, 20 without, 1 unclassified. Most common View entries: None 15, Neighborhood 7, Creek/Stream 2, Park/Greenbelt 2, Pool 1, Trees/Woods 1, See Remarks 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-05 21:45 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Pflugerville, SubdivisionName contains any of “cantarra”, “cantarra meadow” (case-insensitive). A record is kept when its subdivision name belongs to the Cantarra family, the same rule comparable sales use (it includes CANTARRA MEADOW, proven adjacent and priced alike).
The data
Pulled November 5, 2026: 26 closed Cantarra records over the prior year, in ZIP 78660. 10 subdivision spellings kept: Cantarra (7); Cantarra Sec 01 (5); Cantarra Sec Iiib (3); CANTARRA MEADOW (3); Cantarra Meadow (2); Cantarra Sec Iib-2 Sub (2); Cantarra Sec Iib-1 Sub (1); Cantarra Sec Iiia (1); Cantarra Sec Iv (1); Cantarra Meadow 40's (1). Names found by the search but not part of Cantarra, left out: CANTARRA EAST (2); LOT 13 BLK KK CANTARRA 1 NORTH SECS 6 & 7 (1); Cantarra Meadows (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 13 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 5, 2025 to November 4, 2026 inclusive.
The data
26 single-family sales in the window: 26 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
26 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 $292K”.
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 $292K: $192,500–$290,000 (6 sales); $292K–$305K: $291,700–$305,000 (7 sales); $306K–$367K: $306,500–$367,000 (7 sales); Over $367K: $375,000–$400,000 (6 sales)
Quartiles by living area: Under 1,538 SF: 1,203–1,521 SF (7 sales); 1,538–1,707 SF: 1,538–1,707 SF (6 sales); 1,779–2,017 SF: 1,779–2,017 SF (7 sales); Over 2,017 SF: 2,088–2,642 SF (6 sales)
Quartiles by year built: Before 2015: 2008–2011 (5 sales); 2015–2018: 2015–2018 (9 sales); 2019: 2019–2019 (4 sales); After 2019: 2020–2021 (8 sales)
View and no view: View: MLS lists a view (5 sales); No view: None or Neighborhood (20 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 $323,361, median $305,750. Days on market: average 103, median 73: 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; 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 = 2.1630.5397p < 0.0063Unclearε² = 0.086medium
Living areaKruskal–WallisH = 19.8230.0002p < 0.0063Yesε² = 0.793large
Year builtKruskal–WallisH = 6.8030.0787p < 0.0063Unclearε² = 0.272large
Days on marketKruskal–WallisH = 2.3530.5024p < 0.0063Unclearε² = 0.094medium
Discount from original listKruskal–WallisH = 1.9430.5846p < 0.0063Unclearε² = 0.078medium
Price cut before saleChi-squareχ² = 1.6630.6468p < 0.0063UnclearCramér’s V = 0.252small
Seller paid closing costs or repairsChi-squareχ² = 6.7930.0790p < 0.0063UnclearCramér’s V = 0.511large
Has a viewChi-squareχ² = 5.4630.1411p < 0.0063UnclearCramér’s V = 0.458medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 19.0030.0003p < 0.0063Yesε² = 0.760large
Net price per SFKruskal–WallisH = 16.2430.0010p < 0.0063Yesε² = 0.649large
Year builtKruskal–WallisH = 6.5530.0875p < 0.0063Unclearε² = 0.262large
Days on marketKruskal–WallisH = 1.3230.7233p < 0.0063Unclearε² = 0.053small
Discount from original listKruskal–WallisH = 7.8230.0499p < 0.0063Unclearε² = 0.313large
Price cut before saleChi-squareχ² = 4.7730.1891p < 0.0063UnclearCramér’s V = 0.429medium
Seller paid closing costs or repairsChi-squareχ² = 3.1630.3669p < 0.0063UnclearCramér’s V = 0.349medium
Has a viewChi-squareχ² = 7.1530.0674p < 0.0063UnclearCramér’s V = 0.524large

8.3.3 Quartiles by year built

Too few sales in a group to test.

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 68.00—0.2344p < 0.0063Unclearrank-biserial r = 0.360medium
Net price per SFMann–Whitney UU = 40.00—0.5304p < 0.0063Unclearrank-biserial r = 0.200small
Living areaMann–Whitney UU = 63.00—0.3946p < 0.0063Unclearrank-biserial r = 0.260small
Year builtMann–Whitney UU = 31.50—0.2178p < 0.0063Unclearrank-biserial r = 0.370medium
Days on marketMann–Whitney UU = 33.00—0.2622p < 0.0063Unclearrank-biserial r = 0.340medium
Discount from original listMann–Whitney UU = 45.00—0.7671p < 0.0063Unclearrank-biserial r = 0.100negligible
Price cut before saleChi-squareχ² = 0.0011.0000p < 0.0063UnclearCramér’s V = 0.000negligible
Seller paid closing costs or repairsChi-squareχ² = 1.0410.3074p < 0.0063UnclearCramér’s V = 0.204small

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 26 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 5, 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.