ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Cantarra

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 · 5:36 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
20
single-family resale homes
Median net sale price
$317,500
average $323,127
Median net price per SF
$185
average $180
Median days on market
73 days
average 104 days
1. SummaryResale homes · 20 sales · October 26, 2025 – October 25, 2026

This study looks at the 20 resale homes sold in Cantarra in the 365 days to October 25, 2026. A full year is used because only 12 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 sold20 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 $290K · 5 sales$290K–$295K · 5 sales$340K–$367K · 5 salesOver $367K · 5 sales
3. Quartiles by net sale priceResale homes · 20 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.

2026-10-26T05:37:15.660556 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 5 5 5 20 sales Sales per group Under $290K: 5 sales (25%) $290K–$295K: 5 sales (25%) $340K–$367K: 5 sales (25%) Over $367K: 5 sales (25%)
Bottom line

3.1 Key differences

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

Under $290K$290K–$295K$340K–$367KOver $367K
Higher-priced homes Over $367K
  • Are much larger.
Lower-priced homes Under $290K
  • 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 $290K$290K–$295K$340K–$367KOver $367KReal difference?
Net price per SF$177 per SF$192 per SF$179 per SF$173 per SFunclear
Living area1,485 SFSmallest1,527 SF2,021 SF2,257 SFLargest✓ large
Year built2016201820192018unclear
Days on market74 days51 days217 days61 daysunclear
Discount from original list16.1%6.9%5.3%7.5%unclear
Price cut before sale60%40%40%80%unclear
Seller paid closing costs or repairs60%80%40%40%unclear
Has a view0%40%0%60%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

2026-10-26T05:37:15.688131 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $290K 5 sales $290K– $295K 5 sales $340K– $367K 5 sales Over $367K 5 sales $0 $100 $200 $177 $192 $179 $173 Net price per SF, average

The average is $173 per SF for homes over $367K and $177 per SF for homes under $290K. It does not move in a straight line; homes $290K–$295K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $367K are about 770 SF (52%) larger than homes under $290K

2026-10-26T05:37:15.709944 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $290K 5 sales $290K– $295K 5 sales $340K– $367K 5 sales Over $367K 5 sales 0 1,000 2,000 1,485 1,527 2,021 2,257 Living area (SF), average

The average is 2,257 SF for homes over $367K and 1,485 SF for homes under $290K. 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

2026-10-26T05:37:15.733879 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $290K 5 sales $290K– $295K 5 sales $340K– $367K 5 sales Over $367K 5 sales 2008 2011 2014 2017 2020 2016 2018 2019 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over $367K and 2016 for homes under $290K. It does not move in a straight line; homes $340K–$367K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:37:15.756677 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $290K 5 sales $290K– $295K 5 sales $340K– $367K 5 sales Over $367K 5 sales 0 100 200 74 51 217 61 Days on market, median

The median is 61 days for homes over $367K and 74 days for homes under $290K. It does not move in a straight line; homes $340K–$367K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:37:15.777566 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $290K 5 sales $290K– $295K 5 sales $340K– $367K 5 sales Over $367K 5 sales 0.0% 5.0% 10.0% 15.0% 16.1% 6.9% 5.3% 7.5% Discount from original list, average

The average is 7.5% for homes over $367K and 16.1% for homes under $290K. It does not move in a straight line; homes under $290K 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

2026-10-26T05:37:15.806795 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 60 0 40 80 40 40 40 0 80 40 60 Under $290K $290K–$295K $340K–$367K Over $367K

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

  • 80% of homes over $367K had a price cut before sale, against 60% of homes under $290K. Defined in 8.1.7.
  • 40% of homes over $367K had the seller pay closing costs or repairs, against 60% of homes under $290K. Defined in 8.1.8.
  • 60% of homes over $367K have a view, against 0% of homes under $290K. 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 $290K5 sales$290K–$295K5 sales$340K–$367K5 salesOver $367K5 salesAll20 salesReal difference?
Net sale price average$258,144$292,932$357,270$384,160$323,127by design
Net price per SF average$177$192$179$173$180unclear
Living area average1,4851,5272,0212,2571,822✓ large
Year built median20162018201920182018unclear

3.10 The numbers: selling

Under $290K5 sales$290K–$295K5 sales$340K–$367K5 salesOver $367K5 salesAll20 salesReal difference?
Days on market median74512176173unclear
Discount from original list average16.1%6.9%5.3%7.5%8.9%unclear
Price cut before sale60%40%40%80%55%unclear
Seller paid closing costs or repairs60%80%40%40%55%unclear
Has a view0%40%0%60%25%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 · 20 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.

2026-10-26T05:37:15.826835 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 4 5 5 20 sales Sales per group Under 1,538 SF: 6 sales (30%) 1,538–1,672 SF: 4 sales (20%) 1,795–2,017 SF: 5 sales (25%) Over 2,017 SF: 5 sales (25%)
Bottom line: too few sales to test.

4.1 Key differences

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

4.3 Net sale price: described, not tested

2026-10-26T05:37:15.847064 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,538 SF 6 sales 1,538– 1,672 SF 4 sales 1,795– 2,017 SF 5 sales Over 2,017 SF 5 sales $0K $200K $400K $283K $264K $364K $378K Net sale price, average

The average is $378K for homes over 2,017 SF and $283K 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.

Not tested: too few sales.

4.4 Net price per SF: described, not tested

2026-10-26T05:37:15.869290 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,538 SF 6 sales 1,538– 1,672 SF 4 sales 1,795– 2,017 SF 5 sales Over 2,017 SF 5 sales $0 $100 $200 $198 $164 $192 $160 Net price per SF, average

The average is $160 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.

Not tested: too few sales.

4.5 Year built: described, not tested

2026-10-26T05:37:15.892623 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,538 SF 6 sales 1,538– 1,672 SF 4 sales 1,795– 2,017 SF 5 sales Over 2,017 SF 5 sales 2011 2014 2017 2020 2017 2016 2019 2015 Year built: median (dot) and middle half (bar)

The median is 2015 for homes over 2,017 SF and 2017 for homes under 1,538 SF. It does not move in a straight line; homes 1,795–2,017 SF are highest. Defined in 8.1.4.

Not tested: too few sales.

4.6 Days on market: described, not tested

2026-10-26T05:37:15.914984 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,538 SF 6 sales 1,538– 1,672 SF 4 sales 1,795– 2,017 SF 5 sales Over 2,017 SF 5 sales 0 50 100 150 62 62 147 72 Days on market, median

The median is 72 days for homes over 2,017 SF and 62 days for homes under 1,538 SF. It does not move in a straight line; homes 1,795–2,017 SF are highest. Defined in 8.1.5.

Not tested: too few sales.

4.7 Discount from original list: described, not tested

2026-10-26T05:37:15.937287 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,538 SF 6 sales 1,538– 1,672 SF 4 sales 1,795– 2,017 SF 5 sales Over 2,017 SF 5 sales 0.0% 10.0% 20.0% 4.6% 21.7% 5.8% 7.0% Discount from original list, average

The average is 7.0% for homes over 2,017 SF and 4.6% for homes under 1,538 SF. It does not move in a straight line; homes 1,538–1,672 SF are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T05:37:15.963434 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% 33 83 33 75 50 0 60 40 0 60 40 60 Under 1,538 SF 1,538–1,672 SF 1,795–2,017 SF Over 2,017 SF

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

  • 60% of homes over 2,017 SF had a price cut before sale, against 33% of homes under 1,538 SF. Defined in 8.1.7.
  • 40% of homes over 2,017 SF had the seller pay closing costs or repairs, against 83% of homes under 1,538 SF. Defined in 8.1.8.
  • 60% of homes over 2,017 SF have a view, against 33% of homes under 1,538 SF. 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.

4.9 The numbers: price and size

Under 1,538 SF6 sales1,538–1,672 SF4 sales1,795–2,017 SF5 salesOver 2,017 SF5 salesAll20 sales
Net sale price average$282,897$264,500$363,530$377,900$323,127
Net price per SF average$198$164$192$160$180
Living area average1,4321,6161,8942,3841,822
Year built median20172016201920152018

4.10 The numbers: selling

Under 1,538 SF6 sales1,538–1,672 SF4 sales1,795–2,017 SF5 salesOver 2,017 SF5 salesAll20 sales
Days on market median62621477273
Discount from original list average4.6%21.7%5.8%7.0%8.9%
Price cut before sale33%75%60%60%55%
Seller paid closing costs or repairs83%50%40%40%55%
Has a view33%0%0%60%25%

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 · 20 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.

2026-10-26T05:37:15.983070 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 4 7 4 20 sales Sales per group Before 2015: 5 sales (25%) 2015–2017: 4 sales (20%) 2018–2019: 7 sales (35%) After 2019: 4 sales (20%)
Bottom line: too few sales to test.

5.1 Key differences

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

5.3 Net sale price: described, not tested

2026-10-26T05:37:16.002792 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 5 sales 2015– 2017 4 sales 2018– 2019 7 sales After 2019 4 sales $0K $200K $400K $297K $331K $335K $326K Net sale price, average

The average is $326K for homes built after 2019 and $297K for homes built before 2015. It does not move in a straight line; homes built 2018–2019 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T05:37:16.024680 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 5 sales 2015– 2017 4 sales 2018– 2019 7 sales After 2019 4 sales $0 $100 $200 $170 $183 $178 $194 Net price per SF, average

The average is $194 per SF for homes built after 2019 and $170 per SF for homes built before 2015. It does not move in a straight line; homes built after 2019 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T05:37:16.045492 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 5 sales 2015– 2017 4 sales 2018– 2019 7 sales After 2019 4 sales 0 1,000 2,000 1,810 1,851 1,897 1,679 Living area (SF), average

The average is 1,679 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 2018–2019 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T05:37:16.066399 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 5 sales 2015– 2017 4 sales 2018– 2019 7 sales After 2019 4 sales 0 100 200 72 206 61 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 2015–2017 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T05:37:16.088138 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 5 sales 2015– 2017 4 sales 2018– 2019 7 sales After 2019 4 sales 0.0% 5.0% 10.0% 15.0% 14.6% 7.4% 6.8% 7.2% Discount from original list, average

The average is 7.2% 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

2026-10-26T05:37:16.113461 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 50 100 0 71 43 43 25 75 0 Before 2015 2015–2017 2018–2019 After 2019

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

  • 25% 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 sales2015–20174 sales2018–20197 salesAfter 20194 salesAll20 sales
Net sale price average$297,400$331,425$335,183$325,888$323,127
Net price per SF average$170$183$178$194$180
Living area average1,8101,8511,8971,6791,822
Year built median20082016201820202018

5.10 The numbers: selling

Before 20155 sales2015–20174 sales2018–20197 salesAfter 20194 salesAll20 sales
Days on market median72206614973
Discount from original list average14.6%7.4%6.8%7.2%8.9%
Price cut before sale60%50%71%25%55%
Seller paid closing costs or repairs20%100%43%75%55%
Has a view40%0%43%0%25%

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 · 20 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.

2026-10-26T05:37:16.130920 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 15 20 sales Sales per group View: 5 sales (25%) No view: 15 sales (75%)
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$315Kunclear
Net price per SF$174 per SF$182 per SFunclear
Living area2,062 SF1,743 SFunclear
Year built20182018unclear
Days on market61 days74 daysunclear
Discount from original list7.4%9.4%unclear
Price cut before sale60%53%unclear
Seller paid closing costs or repairs40%60%unclear

6.3 Net sale price: no clear difference

2026-10-26T05:37:16.147292 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 15 sales $0K $100K $200K $300K $400K $349K $315K Net sale price, average

The average is $349K for homes with a view and $315K 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

2026-10-26T05:37:16.165811 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 15 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

2026-10-26T05:37:16.206341 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 15 sales 0 500 1,000 1,500 2,000 2,062 1,743 Living area (SF), average

The average is 2,062 SF for homes with a view and 1,743 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T05:37:16.225641 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 15 sales 2012 2014 2016 2018 2018 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes with a view and 2018 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T05:37:16.243727 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 15 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

2026-10-26T05:37:16.263960 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 15 sales 0.0% 2.5% 5.0% 7.5% 10.0% 7.4% 9.4% Discount from original list, average

The average is 7.4% for homes with a view and 9.4% 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

2026-10-26T05:37:16.283430 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 60 40 53 60 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 53% 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 60% 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 view15 salesAll20 salesReal difference?
Net sale price average$348,812$314,565$323,127unclear
Net price per SF average$174$182$180unclear
Living area average2,0621,7431,822unclear
Year built median201820182018unclear

6.11 The numbers: selling

View5 salesNo view15 salesAll20 salesReal difference?
Days on market median617473unclear
Discount from original list average7.4%9.4%8.9%unclear
Price cut before sale60%53%55%unclear
Seller paid closing costs or repairs40%60%55%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.4.

7. New constructionBasic statistics · 0 sales · October 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 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
20 resale sales. Average $323,127; median $317,500; standard deviation $54,618; middle half (25th–75th percentile) $287,475–$369,000; lowest $192,500, highest $400,000. 11 sales had a seller payment; their median payment was $7,000.

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
20 resale sales. Average $180; median $185; standard deviation $24; middle half (25th–75th percentile) $172–$196; 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
20 resale sales. Average 1,822; median 1,734; standard deviation 399; middle half (25th–75th percentile) 1,521–2,035; 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
20 resale sales. Average 2016; median 2018; standard deviation 5; middle half (25th–75th percentile) 2014–2019; 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
20 resale sales. Average 104; median 73; standard deviation 88; middle half (25th–75th percentile) 42–151; 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
20 resale sales. Average 8.9%; median 6.8%; standard deviation 11.2%; middle half (25th–75th percentile) 2.9%–11.8%; 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
11 of 20 resale sales (55.0%).

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
11 of 20 resale sales (55.0%).

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, 15 without, 0 unclassified. Most common View entries: None 11, Neighborhood 6, Creek/Stream 2, Park/Greenbelt 2, Pool 1, Trees/Woods 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 “cantarra” (case-insensitive). A record is kept when its subdivision name belongs to the Cantarra family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 20 closed Cantarra records over the prior year, in ZIP 78660. 7 subdivision spellings kept: Cantarra (7); Cantarra Sec 01 (5); Cantarra Sec Iiib (3); Cantarra Sec Iib-2 Sub (2); Cantarra Sec Iv (1); Cantarra Sec Iiia (1); Cantarra Sec Iib-1 Sub (1). Names found by the search but not part of Cantarra, left out: CANTARRA MEADOW (3); Cantarra Meadow (2); CANTARRA EAST (2); Cantarra Meadows (1); LOT 13 BLK KK CANTARRA 1 NORTH SECS 6 & 7 (1); Cantarra Meadow 40's (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 12 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
20 single-family sales in the window: 20 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
20 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 $290K”.
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 $290K: $192,500–$279,900 (5 sales); $290K–$295K: $290,000–$295,000 (5 sales); $340K–$367K: $340,000–$367,000 (5 sales); Over $367K: $375,000–$400,000 (5 sales)
Quartiles by living area: Under 1,538 SF: 1,203–1,521 SF (6 sales); 1,538–1,672 SF: 1,538–1,672 SF (4 sales); 1,795–2,017 SF: 1,795–2,017 SF (5 sales); Over 2,017 SF: 2,088–2,642 SF (5 sales)
Quartiles by year built: Before 2015: 2008–2011 (5 sales); 2015–2017: 2015–2017 (4 sales); 2018–2019: 2018–2019 (7 sales); After 2019: 2020–2021 (4 sales)
View and no view: View: MLS lists a view (5 sales); No view: None or Neighborhood (15 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 $323,127, median $317,500. Days on market: average 104, 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; 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
1 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 = 2.1330.5456p < 0.0063Unclearε² = 0.112medium
Living areaKruskal–WallisH = 14.9230.0019p < 0.0063Yesε² = 0.785large
Year builtKruskal–WallisH = 1.7630.6245p < 0.0063Unclearε² = 0.092medium
Days on marketKruskal–WallisH = 2.3130.5098p < 0.0063Unclearε² = 0.122medium
Discount from original listKruskal–WallisH = 0.8330.8426p < 0.0063Unclearε² = 0.044small
Price cut before saleChi-squareχ² = 2.2230.5276p < 0.0063UnclearCramér’s V = 0.333medium
Seller paid closing costs or repairsChi-squareχ² = 2.2230.5276p < 0.0063UnclearCramér’s V = 0.333medium
Has a viewChi-squareχ² = 7.2030.0658p < 0.0063UnclearCramér’s V = 0.600large

8.3.2 Quartiles by living area

Too few sales in a group to test.

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 = 55.00—0.1377p < 0.0063Unclearrank-biserial r = 0.467medium
Net price per SFMann–Whitney UU = 28.00—0.4445p < 0.0063Unclearrank-biserial r = 0.253small
Living areaMann–Whitney UU = 48.50—0.3583p < 0.0063Unclearrank-biserial r = 0.293small
Year builtMann–Whitney UU = 28.50—0.4545p < 0.0063Unclearrank-biserial r = 0.240small
Days on marketMann–Whitney UU = 25.00—0.3056p < 0.0063Unclearrank-biserial r = 0.333medium
Discount from original listMann–Whitney UU = 37.00—1.0000p < 0.0063Unclearrank-biserial r = 0.013negligible
Price cut before saleChi-squareχ² = 0.0710.7952p < 0.0063UnclearCramér’s V = 0.058negligible
Seller paid closing costs or repairsChi-squareχ² = 0.6110.4363p < 0.0063UnclearCramér’s V = 0.174small

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 20 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.