ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Blackhawk

Pflugerville, TX 78660
Resale homes · closed Nov 1 – Oct 31, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 1, 2026 · 6:54 AM 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
52
single-family resale homes
Median net sale price
$526,766
average $531,591
Median net price per SF
$181
average $184
Median days on market
59 days
average 87 days
1. SummaryResale homes · 52 sales · November 1, 2025 – October 31, 2026

This study looks at the 52 resale homes sold in Blackhawk in the 365 days to October 31, 2026. A full year is used because only 27 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 sold52 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 $425K · 13 sales$425K–$524K · 13 sales$530K–$598K · 13 salesOver $598K · 13 sales
3. Quartiles by net sale priceResale homes · 52 sales · November 1, 2025 – October 31, 2026

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

2026-11-01T06:55:09.342124 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 13 13 13 13 52 sales Sales per group Under $425K: 13 sales (25%) $425K–$524K: 13 sales (25%) $530K–$598K: 13 sales (25%) Over $598K: 13 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 $425K$425K–$524K$530K–$598KOver $598K
Higher-priced homes Over $598K
  • Are much larger.
Lower-priced homes Under $425K
  • 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 $425K$425K–$524K$530K–$598KOver $598KReal difference?
Net price per SF$172 per SF$184 per SF$191 per SF$189 per SFunclear
Living area2,093 SFSmallest2,615 SF2,975 SF3,894 SFLargest✓ large
Year built2008201720172019unclear
Days on market71 days88 days36 days70 daysunclear
Discount from original list9.8%7.1%5.9%8.1%unclear
Price cut before sale85%62%31%46%unclear
Seller paid closing costs or repairs69%69%54%38%unclear
Has a view15%15%8%31%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

2026-11-01T06:55:09.370167 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $425K 13 sales $425K– $524K 13 sales $530K– $598K 13 sales Over $598K 13 sales $0 $100 $200 $172 $184 $191 $189 Net price per SF, average

The average is $189 per SF for homes over $598K and $172 per SF for homes under $425K. It does not move in a straight line; homes $530K–$598K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $598K are about 1,800 SF (86%) larger than homes under $425K

2026-11-01T06:55:09.392130 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $425K 13 sales $425K– $524K 13 sales $530K– $598K 13 sales Over $598K 13 sales 0 2,000 4,000 2,093 2,615 2,975 3,894 Living area (SF), average

The average is 3,894 SF for homes over $598K and 2,093 SF for homes under $425K. 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

2026-11-01T06:55:09.415671 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $425K 13 sales $425K– $524K 13 sales $530K– $598K 13 sales Over $598K 13 sales 2008 2012 2016 2020 2008 2017 2017 2019 Year built: median (dot) and middle half (bar)

The median is 2019 for homes over $598K and 2008 for homes under $425K. 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

2026-11-01T06:55:09.438840 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $425K 13 sales $425K– $524K 13 sales $530K– $598K 13 sales Over $598K 13 sales 0 50 100 71 88 36 70 Days on market, median

The median is 70 days for homes over $598K and 71 days for homes under $425K. It does not move in a straight line; homes $425K–$524K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-01T06:55:09.460433 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $425K 13 sales $425K– $524K 13 sales $530K– $598K 13 sales Over $598K 13 sales 0.0% 5.0% 10.0% 9.8% 7.1% 5.9% 8.1% Discount from original list, average

The average is 8.1% for homes over $598K and 9.8% for homes under $425K. It does not move in a straight line; homes under $425K 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

2026-11-01T06:55:09.490325 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% 85 69 15 62 69 15 31 54 8 46 38 31 Under $425K $425K–$524K $530K–$598K Over $598K

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

  • 46% of homes over $598K had a price cut before sale, against 85% of homes under $425K. Defined in 8.1.7.
  • 38% of homes over $598K had the seller pay closing costs or repairs, against 69% of homes under $425K. Defined in 8.1.8.
  • 31% of homes over $598K have a view, against 15% of homes under $425K. 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 $425K13 sales$425K–$524K13 sales$530K–$598K13 salesOver $598K13 salesAll52 salesReal difference?
Net sale price average$354,844$476,494$561,654$733,374$531,591by design
Net price per SF average$172$184$191$189$184unclear
Living area average2,0932,6152,9753,8942,894✓ large
Year built median20082017201720192016unclear

3.10 The numbers: selling

Under $425K13 sales$425K–$524K13 sales$530K–$598K13 salesOver $598K13 salesAll52 salesReal difference?
Days on market median7188367059unclear
Discount from original list average9.8%7.1%5.9%8.1%7.7%unclear
Price cut before sale85%62%31%46%56%unclear
Seller paid closing costs or repairs69%69%54%38%58%unclear
Has a view15%15%8%31%17%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.1.

4. Quartiles by living areaResale homes · 52 sales · November 1, 2025 – October 31, 2026

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

2026-11-01T06:55:09.510601 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 13 13 13 13 52 sales Sales per group Under 2,391 SF: 13 sales (25%) 2,391–2,805 SF: 13 sales (25%) 2,825–3,395 SF: 13 sales (25%) Over 3,395 SF: 13 sales (25%)
Bottom line

4.1 Key differences

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

Under 2,391 SF2,391–2,805 SF2,825–3,395 SFOver 3,395 SF
Larger homes Over 3,395 SF
  • Sell for much more.
Smaller homes Under 2,391 SF
  • Sell for much less.

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 2,391 SF2,391–2,805 SF2,825–3,395 SFOver 3,395 SFReal difference?
Net sale price$377KLowest$473K$567K$709KHighest✓ large
Net price per SF$188 per SF$180 per SF$190 per SF$177 per SFunclear
Year built2008201620172017unclear
Days on market58 days98 days51 days148 daysunclear
Discount from original list8.3%9.4%3.3%9.8%unclear
Price cut before sale77%69%23%54%unclear
Seller paid closing costs or repairs62%77%46%46%unclear
Has a view31%0%15%23%unclear

4.3 Homes over 3,395 SF sell for about $332K (88%) more than homes under 2,391 SF

2026-11-01T06:55:09.531404 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,391 SF 13 sales 2,391– 2,805 SF 13 sales 2,825– 3,395 SF 13 sales Over 3,395 SF 13 sales $0K $250K $500K $750K $377K $473K $567K $709K Net sale price, average

The average is $709K for homes over 3,395 SF and $377K for homes under 2,391 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-11-01T06:55:09.553757 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,391 SF 13 sales 2,391– 2,805 SF 13 sales 2,825– 3,395 SF 13 sales Over 3,395 SF 13 sales $0 $100 $200 $188 $180 $190 $177 Net price per SF, average

The average is $177 per SF for homes over 3,395 SF and $188 per SF for homes under 2,391 SF. It does not move in a straight line; homes 2,825–3,395 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-01T06:55:09.576660 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,391 SF 13 sales 2,391– 2,805 SF 13 sales 2,825– 3,395 SF 13 sales Over 3,395 SF 13 sales 2008 2012 2016 2020 2008 2016 2017 2017 Year built: median (dot) and middle half (bar)

The median is 2017 for homes over 3,395 SF and 2008 for homes under 2,391 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

2026-11-01T06:55:09.599016 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,391 SF 13 sales 2,391– 2,805 SF 13 sales 2,825– 3,395 SF 13 sales Over 3,395 SF 13 sales 0 50 100 150 58 98 51 148 Days on market, median

The median is 148 days for homes over 3,395 SF and 58 days for homes under 2,391 SF. It does not move in a straight line; homes over 3,395 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-01T06:55:09.620909 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,391 SF 13 sales 2,391– 2,805 SF 13 sales 2,825– 3,395 SF 13 sales Over 3,395 SF 13 sales 0.0% 5.0% 10.0% 8.3% 9.4% 3.3% 9.8% Discount from original list, average

The average is 9.8% for homes over 3,395 SF and 8.3% for homes under 2,391 SF. It does not move in a straight line; homes over 3,395 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

2026-11-01T06:55:09.647414 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% 77 62 31 69 77 0 23 46 15 54 46 23 Under 2,391 SF 2,391–2,805 SF 2,825–3,395 SF Over 3,395 SF

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

  • 54% of homes over 3,395 SF had a price cut before sale, against 77% of homes under 2,391 SF. Defined in 8.1.7.
  • 46% of homes over 3,395 SF had the seller pay closing costs or repairs, against 62% of homes under 2,391 SF. Defined in 8.1.8.
  • 23% of homes over 3,395 SF have a view, against 31% of homes under 2,391 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 2,391 SF13 sales2,391–2,805 SF13 sales2,825–3,395 SF13 salesOver 3,395 SF13 salesAll52 salesReal difference?
Net sale price average$377,402$472,587$567,387$708,989$531,591✓ large
Net price per SF average$188$180$190$177$184unclear
Living area average2,0092,6162,9793,9732,894by design
Year built median20082016201720172016unclear

4.10 The numbers: selling

Under 2,391 SF13 sales2,391–2,805 SF13 sales2,825–3,395 SF13 salesOver 3,395 SF13 salesAll52 salesReal difference?
Days on market median58985114859unclear
Discount from original list average8.3%9.4%3.3%9.8%7.7%unclear
Price cut before sale77%69%23%54%56%unclear
Seller paid closing costs or repairs62%77%46%46%58%unclear
Has a view31%0%15%23%17%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.2.

5. Quartiles by year builtResale homes · 52 sales · November 1, 2025 – October 31, 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.

2026-11-01T06:55:09.667809 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 15 11 14 52 sales Sales per group Before 2008: 12 sales (23%) 2008–2016: 15 sales (29%) 2017–2019: 11 sales (21%) After 2019: 14 sales (27%)
Bottom line

5.1 Key differences

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

Before 20082008–20162017–2019After 2019
Newer homes After 2019
  • Sell for more per square foot.
Older homes Before 2008
  • Sell for less per square foot.

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 20082008–20162017–2019After 2019Real difference?
Net sale price$501K$481K$578K$575Kunclear
Net price per SF$176 per SFLowest$181 per SF$177 per SF$200 per SFHighest✓ large
Living area2,731 SF2,720 SF3,283 SF2,915 SFunclear
Days on market62 days71 days100 days52 daysunclear
Discount from original list9.3%6.9%7.0%7.8%unclear
Price cut before sale58%53%55%57%unclear
Seller paid closing costs or repairs42%60%64%64%unclear
Has a view25%13%18%14%unclear

5.3 Net sale price: no clear difference

2026-11-01T06:55:09.688372 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2008 12 sales 2008– 2016 15 sales 2017– 2019 11 sales After 2019 14 sales $0K $200K $400K $600K $501K $481K $578K $575K Net sale price, average

The average is $575K for homes built after 2019 and $501K for homes built before 2008. It does not move in a straight line; homes built 2017–2019 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Homes built after 2019 sell for about $24 per SF (14%) more than homes built before 2008

2026-11-01T06:55:09.711252 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2008 12 sales 2008– 2016 15 sales 2017– 2019 11 sales After 2019 14 sales $0 $100 $200 $176 $181 $177 $200 Net price per SF, average

The average is $200 per SF for homes built after 2019 and $176 per SF for homes built before 2008. It does not move in a straight line; homes built after 2019 are highest. Defined in 8.1.2.

✓ Real difference · large

5.5 Living area: no clear difference

2026-11-01T06:55:09.732646 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2008 12 sales 2008– 2016 15 sales 2017– 2019 11 sales After 2019 14 sales 0 1,000 2,000 3,000 2,731 2,720 3,283 2,915 Living area (SF), average

The average is 2,915 SF for homes built after 2019 and 2,731 SF for homes built before 2008. It does not move in a straight line; homes built 2017–2019 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-01T06:55:09.755043 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2008 12 sales 2008– 2016 15 sales 2017– 2019 11 sales After 2019 14 sales 0 50 100 62 71 100 52 Days on market, median

The median is 52 days for homes built after 2019 and 62 days for homes built before 2008. It does not move in a straight line; homes built 2017–2019 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-01T06:55:09.777594 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2008 12 sales 2008– 2016 15 sales 2017– 2019 11 sales After 2019 14 sales 0.0% 5.0% 10.0% 9.3% 6.9% 7.0% 7.8% Discount from original list, average

The average is 7.8% for homes built after 2019 and 9.3% for homes built before 2008. It does not move in a straight line; homes built before 2008 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

2026-11-01T06:55:09.802986 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% 58 42 25 53 60 13 55 64 18 57 64 14 Before 2008 2008–2016 2017–2019 After 2019

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

  • 57% of homes built after 2019 had a price cut before sale, against 58% of homes built before 2008. Defined in 8.1.7.
  • 64% of homes built after 2019 had the seller pay closing costs or repairs, against 42% of homes built before 2008. Defined in 8.1.8.
  • 14% of homes built after 2019 have a view, against 25% of homes built before 2008. 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 200812 sales2008–201615 sales2017–201911 salesAfter 201914 salesAll52 salesReal difference?
Net sale price average$501,386$481,307$578,442$574,546$531,591unclear
Net price per SF average$176$181$177$200$184✓ large
Living area average2,7312,7203,2832,9152,894unclear
Year built median20062013201820202016by design

5.10 The numbers: selling

Before 200812 sales2008–201615 sales2017–201911 salesAfter 201914 salesAll52 salesReal difference?
Days on market median62711005259unclear
Discount from original list average9.3%6.9%7.0%7.8%7.7%unclear
Price cut before sale58%53%55%57%56%unclear
Seller paid closing costs or repairs42%60%64%64%58%unclear
Has a view25%13%18%14%17%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.3.

6. View and no viewResale homes · 52 sales · November 1, 2025 – October 31, 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. 3 sales whose MLS view entry is only “See Remarks” are left out.

2026-11-01T06:55:09.821481 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 40 49 sales Sales per group View: 9 sales (18%) No view: 40 sales (82%)
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$625K$507Kunclear
Net price per SF$200 per SF$180 per SFunclear
Living area3,070 SF2,828 SFunclear
Year built20112016unclear
Days on market51 days65 daysunclear
Discount from original list7.3%7.8%unclear
Price cut before sale67%55%unclear
Seller paid closing costs or repairs56%60%unclear

6.3 Net sale price: no clear difference

2026-11-01T06:55:09.837040 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 40 sales $0K $200K $400K $600K $625K $507K Net sale price, average

The average is $625K for homes with a view and $507K 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

2026-11-01T06:55:09.855277 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 40 sales $0 $50 $100 $150 $200 $200 $180 Net price per SF, average

The average is $200 per SF for homes with a view and $180 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

2026-11-01T06:55:09.873566 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 40 sales 0 1,000 2,000 3,000 3,070 2,828 Living area (SF), average

The average is 3,070 SF for homes with a view and 2,828 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-01T06:55:09.936800 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 40 sales 2008 2011 2014 2017 2020 2011 2016 Year built: median (dot) and middle half (bar)

The median is 2011 for homes with a view and 2016 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-01T06:55:09.955312 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 40 sales 0 20 40 60 51 65 Days on market, median

The median is 51 days for homes with a view and 65 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

2026-11-01T06:55:09.974243 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 40 sales 0.0% 2.0% 4.0% 6.0% 8.0% 7.3% 7.8% Discount from original list, average

The average is 7.3% for homes with a view and 7.8% 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

2026-11-01T06:55:09.993273 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 67 56 55 60 View No view

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

  • 67% of homes with a view had a price cut before sale, against 55% of homes without a view. Defined in 8.1.7.
  • 56% 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

View9 salesNo view40 salesAll49 salesReal difference?
Net sale price average$624,889$506,955$528,617unclear
Net price per SF average$200$180$184unclear
Living area average3,0702,8282,872unclear
Year built median201120162016unclear

6.11 The numbers: selling

View9 salesNo view40 salesAll49 salesReal difference?
Days on market median516558unclear
Discount from original list average7.3%7.8%7.7%unclear
Price cut before sale67%55%57%unclear
Seller paid closing costs or repairs56%60%59%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 · 60 sales · November 1, 2025 – October 31, 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: 60 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 Blackhawk.
MeasureAverageMedian
Sales60
Net sale price$586,778$573,495
Net price per SF$207$206
Living area (SF)2,8532,900
Days on market118106
Discount from original list7.7%7.1%
Price cut before sale68% of sales
Seller paid closing costs or repairs43% of sales
Year built2023–2026

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
52 resale sales. Average $531,591; median $526,766; standard deviation $176,415; middle half (25th–75th percentile) $417,500–$599,010; lowest $242,750, highest $1,374,500. 30 sales had a seller payment; their median payment was $6,000.

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
52 resale sales. Average $184; median $181; standard deviation $29; middle half (25th–75th percentile) $169–$198; lowest $135, highest $297.

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
52 resale sales. Average 2,894; median 2,815; standard deviation 771; middle half (25th–75th percentile) 2,391–3,403; lowest 1,526, highest 4,689.

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
52 resale sales. Average 2014; median 2016; standard deviation 6; middle half (25th–75th percentile) 2008–2020; lowest 2000, highest 2023.

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
52 resale sales. Average 87; median 59; standard deviation 75; middle half (25th–75th percentile) 29–136; lowest 2, highest 284. 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
52 resale sales. Average 7.7%; median 5.2%; standard deviation 7.1%; middle half (25th–75th percentile) 2.8%–9.8%; lowest −0.2%, highest 29.6%. 2 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
29 of 52 resale sales (55.8%).

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
30 of 52 resale sales (57.7%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
9 sales with a view, 40 without, 3 unclassified. Most common View entries: None 27, Neighborhood 16, Pond 5, See Remarks 3, Park/Greenbelt 3, Pool 2, Trees/Woods 2, Panoramic 2.

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 2026-11-01 12:45 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Pflugerville, SubdivisionName contains any of “blackhawk”, “park at blackhawk”, “grove at blackhawk”, “lakeside at blackhawk”, “park at blackhawk vi”, “the park at blackhawk”, “park at blackhawk ii”, “lakeside at blackhawk iii”, “lakeside at blackhawk ii” (case-insensitive). A record is kept when its subdivision name belongs to the Blackhawk family, the same rule comparable sales use (it includes Park at Blackhawk, Grove at Blackhawk, Lakeside at Blackhawk, Park At Blackhawk Vi Sec 1 The, The Park at Blackhawk, Park At Blackhawk Ii Ph 3B Th, Lakeside At Blackhawk Ii Ph 2, proven adjacent and priced alike).
The data
Pulled November 1, 2026: 112 closed Blackhawk records over the prior year, in ZIP 78660. 27 subdivision spellings kept, the most common: Blackhawk (42); Grove at Blackhawk (27); The Park at Blackhawk (4); Park at Blackhawk (4); Park At Blackhawk 4 (3); Park At Blackhawk (3); Park At Blackhawk Vi Sec 1 The (3); Park At Blackhawk Sec 05 (3); Lakeside At Blackhawk Ii Ph 2 (2); Lakeside At Blackhawk Sec 02 (2); Lakeside at Blackhawk (2); Park At Blackhawk 06 Sec 01 The (2); and 15 more (15 records). Names found by the search but not part of Blackhawk, left out: Meadows Blackhawk Ph 01 (5); Meadows Blackhawk Ph 05 (4); Meadows Blackhawk Ph 06 (4); Fairways Of Blackhawk Ph 5A (3); Fairways Blackhawk Ph 04 (3); Park At Blackhawk Iv Ph 6A (3); Park At Blackhawk Vii Sec 1A T (2); Meadows Blackhawk Ph 02 (2); The Groves at Blackhawk (2); Ridge at Blackhawk (2); MEADOWS OF BLACKHAWK PHS 1 (1); Trails at Blackhawk (1); Meadows of Blackhawk (1); Park at Blackhawk and Lakeside (1); Fairways Of Blackhawk Ph 5a (1); Park/Blackhawk Iv Ph 3 (1); Fairways Blackhawk Ph 03-A (1); Ridge/Blackhawk Ph 1 Sec 1 (1); Fairways Blackhawk (1); Park/Blackhawk Vii Sec 3 (1); Park/Blackhawk 6 Sec 5 (1); Fairways Blackhawk Ph 1-A (1); Lakeside/Blackhawk Ii Ph I B (1); Park/Blackhawk 06 Sec U (1); Park/Blackhawk Iii Sec 2 (1); Ridge at Blackhawk Ph 1 Sec 2 (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 27 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 1, 2025 to October 31, 2026 inclusive.
The data
112 single-family sales in the window: 52 resale, 60 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
52 resale; 60 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 $425K”.
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 $425K: $242,750–$395,000 (13 sales); $425K–$524K: $425,000–$523,532 (13 sales); $530K–$598K: $530,000–$598,500 (13 sales); Over $598K: $600,540–$1,374,500 (13 sales)
Quartiles by living area: Under 2,391 SF: 1,526–2,390 SF (13 sales); 2,391–2,805 SF: 2,391–2,805 SF (13 sales); 2,825–3,395 SF: 2,825–3,395 SF (13 sales); Over 3,395 SF: 3,427–4,689 SF (13 sales)
Quartiles by year built: Before 2008: 2000–2007 (12 sales); 2008–2016: 2008–2016 (15 sales); 2017–2019: 2017–2019 (11 sales); After 2019: 2020–2023 (14 sales)
View and no view: View: MLS lists a view (9 sales); No view: None or Neighborhood (40 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 $531,591, median $526,766. Days on market: average 87, median 59: 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 = 4.2930.2320p < 0.0063Unclearε² = 0.084medium
Living areaKruskal–WallisH = 38.213< 0.0001p < 0.0063Yesε² = 0.749large
Year builtKruskal–WallisH = 11.6530.0087p < 0.0063Unclearε² = 0.228large
Days on marketKruskal–WallisH = 2.1730.5374p < 0.0063Unclearε² = 0.043small
Discount from original listKruskal–WallisH = 3.2030.3619p < 0.0063Unclearε² = 0.063medium
Price cut before saleChi-squareχ² = 8.3430.0395p < 0.0063UnclearCramér’s V = 0.401medium
Seller paid closing costs or repairsChi-squareχ² = 3.4730.3251p < 0.0063UnclearCramér’s V = 0.258small
Has a viewChi-squareχ² = 2.5530.4658p < 0.0063UnclearCramér’s V = 0.222small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 36.713< 0.0001p < 0.0063Yesε² = 0.720large
Net price per SFKruskal–WallisH = 4.3530.2259p < 0.0063Unclearε² = 0.085medium
Year builtKruskal–WallisH = 3.5630.3136p < 0.0063Unclearε² = 0.070medium
Days on marketKruskal–WallisH = 5.0530.1685p < 0.0063Unclearε² = 0.099medium
Discount from original listKruskal–WallisH = 8.1730.0427p < 0.0063Unclearε² = 0.160large
Price cut before saleChi-squareχ² = 8.9730.0298p < 0.0063UnclearCramér’s V = 0.415medium
Seller paid closing costs or repairsChi-squareχ² = 3.4730.3251p < 0.0063UnclearCramér’s V = 0.258small
Has a viewChi-squareχ² = 4.7030.1949p < 0.0063UnclearCramér’s V = 0.301medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 8.8030.0321p < 0.0063Unclearε² = 0.172large
Net price per SFKruskal–WallisH = 12.8530.0050p < 0.0063Yesε² = 0.252large
Living areaKruskal–WallisH = 6.7530.0805p < 0.0063Unclearε² = 0.132medium
Days on marketKruskal–WallisH = 0.2230.9750p < 0.0063Unclearε² = 0.004negligible
Discount from original listKruskal–WallisH = 1.7130.6357p < 0.0063Unclearε² = 0.033small
Price cut before saleChi-squareχ² = 0.0930.9935p < 0.0063UnclearCramér’s V = 0.041negligible
Seller paid closing costs or repairsChi-squareχ² = 1.7030.6361p < 0.0063UnclearCramér’s V = 0.181small
Has a viewChi-squareχ² = 0.7630.8598p < 0.0063UnclearCramér’s V = 0.121small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 212.50—0.4086p < 0.0063Unclearrank-biserial r = 0.181small
Net price per SFMann–Whitney UU = 196.00—0.6890p < 0.0063Unclearrank-biserial r = 0.089negligible
Living areaMann–Whitney UU = 196.00—0.6890p < 0.0063Unclearrank-biserial r = 0.089negligible
Year builtMann–Whitney UU = 159.50—0.6046p < 0.0063Unclearrank-biserial r = 0.114small
Days on marketMann–Whitney UU = 134.00—0.2400p < 0.0063Unclearrank-biserial r = 0.256small
Discount from original listMann–Whitney UU = 182.00—0.9691p < 0.0063Unclearrank-biserial r = 0.011negligible
Price cut before saleChi-squareχ² = 0.4110.5228p < 0.0063UnclearCramér’s V = 0.091negligible
Seller paid closing costs or repairsChi-squareχ² = 0.0610.8064p < 0.0063UnclearCramér’s V = 0.035negligible

8.4 Data notes

Left out of the analysis: 60 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 52 closed MLS resale sales; the 60 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 1, 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.