ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Hielscher Sec 12

Austin, TX 78739
Resale homes · closed Oct 31 – Oct 30, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 31, 2026 · 7:42 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
40
single-family resale homes
Median net sale price
$929,000
average $948,005
Median net price per SF
$299
average $301
Median days on market
14 days
average 44 days
1. SummaryResale homes · 40 sales · October 31, 2025 – October 30, 2026

This study looks at the 40 resale homes sold in Hielscher Sec 12 in the 365 days to October 30, 2026. A full year is used because only 25 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 sold40 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 $815K · 10 sales$815K–$926K · 10 sales$932K–$1.05M · 10 salesOver $1.05M · 10 sales
3. Quartiles by net sale priceResale homes · 40 sales · October 31, 2025 – October 30, 2026

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

2026-10-31T07:42:53.006094 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 10 10 40 sales Sales per group Under $815K: 10 sales (25%) $815K–$926K: 10 sales (25%) $932K–$1.05M: 10 sales (25%) Over $1.05M: 10 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 $815K$815K–$926K$932K–$1.05MOver $1.05M
Higher-priced homes Over $1.05M
  • Are much larger.
  • Sell for more per square foot.
Lower-priced homes Under $815K
  • Are much smaller.
  • Sell for less per square foot.

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 $815K$815K–$926K$932K–$1.05MOver $1.05MReal difference?
Net price per SF$297 per SF$280 per SFLowest$284 per SF$344 per SFHighest✓ large
Living area2,484 SFSmallest3,159 SF3,544 SFLargest3,507 SF✓ large
Year built2005200420042004unclear
Days on market61 days13 days11 days11 daysunclear
Discount from original list5.4%3.7%4.0%0.4%unclear
Price cut before sale60%30%40%20%unclear
Seller paid closing costs or repairs70%50%50%30%unclear
Has a view50%10%60%40%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 Homes over $1.05M sell for about $47 per SF (16%) more than homes under $815K

2026-10-31T07:42:53.033586 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $815K 10 sales $815K– $926K 10 sales $932K– $1.05M 10 sales Over $1.05M 10 sales $0 $200 $400 $297 $280 $284 $344 Net price per SF, average

The average is $344 per SF for homes over $1.05M and $297 per SF for homes under $815K. It does not move in a straight line; homes over $1.05M are highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $1.05M are about 1,020 SF (41%) larger than homes under $815K

2026-10-31T07:42:53.055194 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $815K 10 sales $815K– $926K 10 sales $932K– $1.05M 10 sales Over $1.05M 10 sales 0 2,000 4,000 2,484 3,159 3,544 3,507 Living area (SF), average

The average is 3,507 SF for homes over $1.05M and 2,484 SF for homes under $815K. It does not move in a straight line; homes $932K–$1.05M are highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-31T07:42:53.078240 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $815K 10 sales $815K– $926K 10 sales $932K– $1.05M 10 sales Over $1.05M 10 sales 2002 2003 2004 2005 2005 2004 2004 2004 Year built: median (dot) and middle half (bar)

The median is 2004 for homes over $1.05M and 2005 for homes under $815K. It does not move in a straight line; homes under $815K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-31T07:42:53.100170 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $815K 10 sales $815K– $926K 10 sales $932K– $1.05M 10 sales Over $1.05M 10 sales 0 20 40 60 61 13 11 11 Days on market, median

The median is 11 days for homes over $1.05M and 61 days for homes under $815K. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-31T07:42:53.121773 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $815K 10 sales $815K– $926K 10 sales $932K– $1.05M 10 sales Over $1.05M 10 sales 0.0% 2.0% 4.0% 6.0% 5.4% 3.7% 4.0% 0.4% Discount from original list, average

The average is 0.4% for homes over $1.05M and 5.4% for homes under $815K. It does not move in a straight line; homes under $815K 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

2026-10-31T07:42:53.151301 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 70 50 30 50 10 40 50 60 20 30 40 Under $815K $815K–$926K $932K–$1.05M Over $1.05M

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

  • 20% of homes over $1.05M had a price cut before sale, against 60% of homes under $815K. Defined in 8.1.7.
  • 30% of homes over $1.05M had the seller pay closing costs or repairs, against 70% of homes under $815K. Defined in 8.1.8.
  • 40% of homes over $1.05M have a view, against 50% of homes under $815K. 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 $815K10 sales$815K–$926K10 sales$932K–$1.05M10 salesOver $1.05M10 salesAll40 salesReal difference?
Net sale price average$732,790$879,765$983,900$1,195,564$948,005by design
Net price per SF average$297$280$284$344$301✓ large
Living area average2,4843,1593,5443,5073,174✓ large
Year built median20052004200420042004unclear

3.10 The numbers: selling

Under $815K10 sales$815K–$926K10 sales$932K–$1.05M10 salesOver $1.05M10 salesAll40 salesReal difference?
Days on market median6113111114unclear
Discount from original list average5.4%3.7%4.0%0.4%3.4%unclear
Price cut before sale60%30%40%20%38%unclear
Seller paid closing costs or repairs70%50%50%30%50%unclear
Has a view50%10%60%40%40%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 · 40 sales · October 31, 2025 – October 30, 2026

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

2026-10-31T07:42:53.171566 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 9 11 40 sales Sales per group Under 2,794 SF: 10 sales (25%) 2,794–3,143 SF: 10 sales (25%) 3,174–3,502 SF: 9 sales (22%) Over 3,502 SF: 11 sales (28%)
Bottom line

4.1 Key differences

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

Under 2,794 SF2,794–3,143 SF3,174–3,502 SFOver 3,502 SF
Larger homes Over 3,502 SF
  • Sell for much more.
Smaller homes Under 2,794 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 2,794 SF2,794–3,143 SF3,174–3,502 SFOver 3,502 SFReal difference?
Net sale price$753KLowest$934K$1.03M$1.07MHighest✓ large
Net price per SF$308 per SF$314 per SF$305 per SF$281 per SFunclear
Year built2005200220052004unclear
Days on market38 days7 days28 days5 daysunclear
Discount from original list4.4%1.8%2.5%4.6%unclear
Price cut before sale60%20%33%36%unclear
Seller paid closing costs or repairs60%40%33%64%unclear
Has a view50%20%44%45%unclear

4.3 Homes over 3,502 SF sell for about $315K (42%) more than homes under 2,794 SF

2026-10-31T07:42:53.192574 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,794 SF 10 sales 2,794– 3,143 SF 10 sales 3,174– 3,502 SF 9 sales Over 3,502 SF 11 sales $0K $500K $1.00M $753K $934K $1.03M $1.07M Net sale price, average

The average is $1.07M for homes over 3,502 SF and $753K for homes under 2,794 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

2026-10-31T07:42:53.215239 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,794 SF 10 sales 2,794– 3,143 SF 10 sales 3,174– 3,502 SF 9 sales Over 3,502 SF 11 sales $0 $100 $200 $300 $308 $314 $305 $281 Net price per SF, average

The average is $281 per SF for homes over 3,502 SF and $308 per SF for homes under 2,794 SF. It does not move in a straight line; homes 2,794–3,143 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-31T07:42:53.240627 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,794 SF 10 sales 2,794– 3,143 SF 10 sales 3,174– 3,502 SF 9 sales Over 3,502 SF 11 sales 2002 2003 2004 2005 2006 2005 2002 2005 2004 Year built: median (dot) and middle half (bar)

The median is 2004 for homes over 3,502 SF and 2005 for homes under 2,794 SF. It does not move in a straight line; homes under 2,794 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-31T07:42:53.264848 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,794 SF 10 sales 2,794– 3,143 SF 10 sales 3,174– 3,502 SF 9 sales Over 3,502 SF 11 sales 0 20 40 38 7 28 5 Days on market, median

The median is 5 days for homes over 3,502 SF and 38 days for homes under 2,794 SF. It does not move in a straight line; homes under 2,794 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-31T07:42:53.288365 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,794 SF 10 sales 2,794– 3,143 SF 10 sales 3,174– 3,502 SF 9 sales Over 3,502 SF 11 sales 0.0% 2.0% 4.0% 4.4% 1.8% 2.5% 4.6% Discount from original list, average

The average is 4.6% for homes over 3,502 SF and 4.4% for homes under 2,794 SF. It does not move in a straight line; homes over 3,502 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-31T07:42:53.315167 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 50 20 40 20 33 33 44 36 64 45 Under 2,794 SF 2,794–3,143 SF 3,174–3,502 SF Over 3,502 SF

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

  • 36% of homes over 3,502 SF had a price cut before sale, against 60% of homes under 2,794 SF. Defined in 8.1.7.
  • 64% of homes over 3,502 SF had the seller pay closing costs or repairs, against 60% of homes under 2,794 SF. Defined in 8.1.8.
  • 45% of homes over 3,502 SF have a view, against 50% of homes under 2,794 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 2,794 SF10 sales2,794–3,143 SF10 sales3,174–3,502 SF9 salesOver 3,502 SF11 salesAll40 salesReal difference?
Net sale price average$753,290$933,936$1,032,649$1,068,555$948,005✓ large
Net price per SF average$308$314$305$281$301unclear
Living area average2,4582,9803,3873,8253,174by design
Year built median20052002200520042004unclear

4.10 The numbers: selling

Under 2,794 SF10 sales2,794–3,143 SF10 sales3,174–3,502 SF9 salesOver 3,502 SF11 salesAll40 salesReal difference?
Days on market median38728514unclear
Discount from original list average4.4%1.8%2.5%4.6%3.4%unclear
Price cut before sale60%20%33%36%38%unclear
Seller paid closing costs or repairs60%40%33%64%50%unclear
Has a view50%20%44%45%40%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 · 40 sales · October 31, 2025 – October 30, 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.

2026-10-31T07:42:53.335323 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 15 8 10 40 sales Sales per group Before 2003: 7 sales (18%) 2003–2004: 15 sales (38%) 2005: 8 sales (20%) After 2005: 10 sales (25%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

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

5.2 At a glance

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

Before 20032003–20042005After 2005Real difference?
Net sale price$978K$959K$984K$882Kunclear
Net price per SF$329 per SF$301 per SF$308 per SF$277 per SFunclear
Living area2,990 SF3,209 SF3,216 SF3,215 SFunclear
Days on market12 days5 days16 days32 daysunclear
Discount from original list2.6%1.7%4.1%5.8%unclear
Price cut before sale29%20%50%60%unclear
Seller paid closing costs or repairs43%47%38%70%unclear
Has a view29%33%62%40%unclear

5.3 Net sale price: no clear difference

2026-10-31T07:42:53.355944 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 7 sales 2003– 2004 15 sales 2005 8 sales After 2005 10 sales $0K $500K $1.00M $978K $959K $984K $882K Net sale price, average

The average is $882K for homes built after 2005 and $978K for homes built before 2003. It does not move in a straight line; homes built 2005 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-31T07:42:53.378185 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 7 sales 2003– 2004 15 sales 2005 8 sales After 2005 10 sales $0 $100 $200 $300 $329 $301 $308 $277 Net price per SF, average

The average is $277 per SF for homes built after 2005 and $329 per SF for homes built before 2003. It does not move in a straight line; homes built before 2003 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-31T07:42:53.399587 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 7 sales 2003– 2004 15 sales 2005 8 sales After 2005 10 sales 0 1,000 2,000 3,000 2,990 3,209 3,216 3,215 Living area (SF), average

The average is 3,215 SF for homes built after 2005 and 2,990 SF for homes built before 2003. It does not move in a straight line; homes built 2005 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-31T07:42:53.420858 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 7 sales 2003– 2004 15 sales 2005 8 sales After 2005 10 sales 0 10 20 30 12 5 16 32 Days on market, median

The median is 32 days for homes built after 2005 and 12 days for homes built before 2003. It does not move in a straight line; homes built after 2005 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-31T07:42:53.443509 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 7 sales 2003– 2004 15 sales 2005 8 sales After 2005 10 sales 0.0% 2.0% 4.0% 6.0% 2.6% 1.7% 4.1% 5.8% Discount from original list, average

The average is 5.8% for homes built after 2005 and 2.6% for homes built before 2003. It does not move in a straight line; homes built after 2005 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-31T07:42:53.469175 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 43 29 20 47 33 50 38 62 60 70 40 Before 2003 2003–2004 2005 After 2005

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

  • 60% of homes built after 2005 had a price cut before sale, against 29% of homes built before 2003. Defined in 8.1.7.
  • 70% of homes built after 2005 had the seller pay closing costs or repairs, against 43% of homes built before 2003. Defined in 8.1.8.
  • 40% of homes built after 2005 have a view, against 29% of homes built before 2003. 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 20037 sales2003–200415 sales20058 salesAfter 200510 salesAll40 salesReal difference?
Net sale price average$978,358$958,653$984,250$881,790$948,005unclear
Net price per SF average$329$301$308$277$301unclear
Living area average2,9903,2093,2163,2153,174unclear
Year built median20022003200520062004by design

5.10 The numbers: selling

Before 20037 sales2003–200415 sales20058 salesAfter 200510 salesAll40 salesReal difference?
Days on market median125163214unclear
Discount from original list average2.6%1.7%4.1%5.8%3.4%unclear
Price cut before sale29%20%50%60%38%unclear
Seller paid closing costs or repairs43%47%38%70%50%unclear
Has a view29%33%62%40%40%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 · 40 sales · October 31, 2025 – October 30, 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.

2026-10-31T07:42:53.488202 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 16 24 40 sales Sales per group View: 16 sales (40%) No view: 24 sales (60%)
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$965K$937Kunclear
Net price per SF$303 per SF$300 per SFunclear
Living area3,218 SF3,144 SFunclear
Year built20052004unclear
Days on market10 days18 daysunclear
Discount from original list2.3%4.1%unclear
Price cut before sale31%42%unclear
Seller paid closing costs or repairs44%54%unclear

6.3 Net sale price: no clear difference

2026-10-31T07:42:53.505538 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 24 sales $0K $250K $500K $750K $1.00M $965K $937K Net sale price, average

The average is $965K for homes with a view and $937K 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

2026-10-31T07:42:53.523323 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 24 sales $0 $100 $200 $300 $303 $300 Net price per SF, average

The average is $303 per SF for homes with a view and $300 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

2026-10-31T07:42:53.541289 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 24 sales 0 1,000 2,000 3,000 3,218 3,144 Living area (SF), average

The average is 3,218 SF for homes with a view and 3,144 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-31T07:42:53.581812 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 24 sales 2003 2004 2005 2005 2004 Year built: median (dot) and middle half (bar)

The median is 2005 for homes with a view and 2004 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-31T07:42:53.599698 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 24 sales 0 5 10 15 20 10 18 Days on market, median

The median is 10 days for homes with a view and 18 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

2026-10-31T07:42:53.618684 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 24 sales 0.0% 1.0% 2.0% 3.0% 4.0% 2.3% 4.1% Discount from original list, average

The average is 2.3% for homes with a view and 4.1% 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

2026-10-31T07:42:53.638098 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 31 44 42 54 View No view

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

  • 31% of homes with a view had a price cut before sale, against 42% of homes without a view. Defined in 8.1.7.
  • 44% of homes with a view had the seller pay closing costs or repairs, against 54% 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

View16 salesNo view24 salesAll40 salesReal difference?
Net sale price average$965,168$936,563$948,005unclear
Net price per SF average$303$300$301unclear
Living area average3,2183,1443,174unclear
Year built median200520042004unclear

6.11 The numbers: selling

View16 salesNo view24 salesAll40 salesReal difference?
Days on market median101814unclear
Discount from original list average2.3%4.1%3.4%unclear
Price cut before sale31%42%38%unclear
Seller paid closing costs or repairs44%54%50%unclear

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

7. New constructionBasic statistics · 0 sales · October 31, 2025 – October 30, 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 Hielscher Sec 12.

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
40 resale sales. Average $948,005; median $929,000; standard deviation $179,801; middle half (25th–75th percentile) $812,062–$1,063,179; lowest $624,150, highest $1,386,000. 20 sales had a seller payment; their median payment was $5,000.

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
40 resale sales. Average $301; median $299; standard deviation $43; middle half (25th–75th percentile) $272–$329; lowest $228, highest $445.

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
40 resale sales. Average 3,174; median 3,158; standard deviation 567; middle half (25th–75th percentile) 2,777–3,515; lowest 1,977, highest 4,492.

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
40 resale sales. Average 2004; median 2004; standard deviation 2; middle half (25th–75th percentile) 2003–2005; lowest 1998, highest 2012.

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
40 resale sales. Average 44; median 14; standard deviation 65; middle half (25th–75th percentile) 3–62; lowest 2, highest 292. 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
40 resale sales. Average 3.4%; median 1.2%; standard deviation 6.9%; middle half (25th–75th percentile) −1.4%–7.1%; lowest −7.7%, highest 24.2%. 15 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
15 of 40 resale sales (37.5%).

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
20 of 40 resale sales (50.0%).

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
16 sales with a view, 24 without, 0 unclassified. Most common View entries: None 19, Park/Greenbelt 10, Neighborhood 8, Trees/Woods 6, Pool 2, See Remarks 1, Garden 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 = Austin, SubdivisionName contains any of “hielscher”, “lacrosse”, “circle c ranch hielscher” (case-insensitive). A record is kept when its subdivision name belongs to the Hielscher Sec 12 family, the same rule comparable sales use (it includes Lacrosse Sec 02, Circle C Ranch Hielscher Sec 08, proven adjacent and priced alike).
The data
Pulled October 31, 2026: 40 closed Hielscher Sec 12 records over the prior year, in ZIP 78739. 21 subdivision spellings kept, the most common: Hielscher Sec 12 (5); Hielscher Sec 15 (4); Hielscher Sec 04 (4); Hielscher Sec 14 (4); Lacrosse Sec 01 (3); Lacrosse Sec 02 (3); Hielscher Sec 09 (3); CIRCLE C RANCH , Hielscher Sec 12 (1); Hielscher Sec 04 Circle C Ranch (1); Circle C Ranch , Hielscher Sec 12 (1); Lacrosse Sec 03 (1); Circle C Ranch - Hielscher Sec 11 (1); and 9 more (9 records). Names found by the search but not part of Hielscher Sec 12, left out: Circle C Ranch West - Hielscher Sec 14 (1); Circle C Hielscher Sec 07 (1); Circle C Ranch - Lacrosse Sec 02 (1); Circle C, Hielscher Sec 07 (1); Hielscher Circle C West (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 25 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 31, 2025 to October 30, 2026 inclusive.
The data
40 single-family sales in the window: 40 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
40 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 $815K”.
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 $815K: $624,150–$803,250 (10 sales); $815K–$926K: $815,000–$926,000 (10 sales); $932K–$1.05M: $932,000–$1,050,905 (10 sales); Over $1.05M: $1,100,000–$1,386,000 (10 sales)
Quartiles by living area: Under 2,794 SF: 1,977–2,726 SF (10 sales); 2,794–3,143 SF: 2,794–3,143 SF (10 sales); 3,174–3,502 SF: 3,174–3,502 SF (9 sales); Over 3,502 SF: 3,515–4,492 SF (11 sales)
Quartiles by year built: Before 2003: 1998–2002 (7 sales); 2003–2004: 2003–2004 (15 sales); 2005: 2005–2005 (8 sales); After 2005: 2006–2012 (10 sales)
View and no view: View: MLS lists a view (16 sales); No view: None or Neighborhood (24 sales)

8.2.6 Average and median

In simple terms
The average adds the values and divides by how many; one very expensive home can pull it up. The median is the middle value, with half above and half below.
Statistically
Mean x̄ = (1/n) Σ xᵢ; median = 50th percentile. Price, price per SF, living area and discount use the mean; days on market and year built use the median (skewed or whole-year values).
The data
Net sale price: average $948,005, median $929,000. Days on market: average 44, median 14: 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 = 12.9630.0047p < 0.0063Yesε² = 0.332large
Living areaKruskal–WallisH = 23.133< 0.0001p < 0.0063Yesε² = 0.593large
Year builtKruskal–WallisH = 1.3830.7101p < 0.0063Unclearε² = 0.035small
Days on marketKruskal–WallisH = 1.3030.7292p < 0.0063Unclearε² = 0.033small
Discount from original listKruskal–WallisH = 2.0130.5704p < 0.0063Unclearε² = 0.052small
Price cut before saleChi-squareχ² = 3.7330.2917p < 0.0063UnclearCramér’s V = 0.306medium
Seller paid closing costs or repairsChi-squareχ² = 3.2030.3618p < 0.0063UnclearCramér’s V = 0.283small
Has a viewChi-squareχ² = 5.8330.1200p < 0.0063UnclearCramér’s V = 0.382medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 20.7230.0001p < 0.0063Yesε² = 0.531large
Net price per SFKruskal–WallisH = 3.2730.3513p < 0.0063Unclearε² = 0.084medium
Year builtKruskal–WallisH = 10.9230.0122p < 0.0063Unclearε² = 0.280large
Days on marketKruskal–WallisH = 2.5230.4710p < 0.0063Unclearε² = 0.065medium
Discount from original listKruskal–WallisH = 1.3030.7299p < 0.0063Unclearε² = 0.033small
Price cut before saleChi-squareχ² = 3.5430.3157p < 0.0063UnclearCramér’s V = 0.297small
Seller paid closing costs or repairsChi-squareχ² = 2.6230.4543p < 0.0063UnclearCramér’s V = 0.256small
Has a viewChi-squareχ² = 2.2930.5137p < 0.0063UnclearCramér’s V = 0.239small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 1.7630.6234p < 0.0063Unclearε² = 0.045small
Net price per SFKruskal–WallisH = 6.3230.0969p < 0.0063Unclearε² = 0.162large
Living areaKruskal–WallisH = 1.5930.6622p < 0.0063Unclearε² = 0.041small
Days on marketKruskal–WallisH = 1.3630.7152p < 0.0063Unclearε² = 0.035small
Discount from original listKruskal–WallisH = 2.8930.4090p < 0.0063Unclearε² = 0.074medium
Price cut before saleChi-squareχ² = 4.8930.1799p < 0.0063UnclearCramér’s V = 0.350medium
Seller paid closing costs or repairsChi-squareχ² = 2.3130.5107p < 0.0063UnclearCramér’s V = 0.240small
Has a viewChi-squareχ² = 2.3530.5037p < 0.0063UnclearCramér’s V = 0.242small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 208.00—0.6687p < 0.0063Unclearrank-biserial r = 0.083negligible
Net price per SFMann–Whitney UU = 212.00—0.5903p < 0.0063Unclearrank-biserial r = 0.104small
Living areaMann–Whitney UU = 205.00—0.7300p < 0.0063Unclearrank-biserial r = 0.068negligible
Year builtMann–Whitney UU = 213.50—0.5568p < 0.0063Unclearrank-biserial r = 0.112small
Days on marketMann–Whitney UU = 168.00—0.5151p < 0.0063Unclearrank-biserial r = 0.125small
Discount from original listMann–Whitney UU = 144.00—0.1897p < 0.0063Unclearrank-biserial r = 0.250small
Price cut before saleChi-squareχ² = 0.4410.5050p < 0.0063UnclearCramér’s V = 0.105small
Seller paid closing costs or repairsChi-squareχ² = 0.4210.5186p < 0.0063UnclearCramér’s V = 0.102small

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 40 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 31, 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.