ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Behrens Ranch

Round Rock, TX 78681
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 · 7:14 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
28
single-family resale homes
Median net sale price
$748,980
average $785,791
Median net price per SF
$223
average $227
Median days on market
40 days
average 49 days
1. SummaryResale homes · 28 sales · October 26, 2025 – October 25, 2026

This study looks at the 28 resale homes sold in Behrens Ranch in the 365 days to October 25, 2026. A full year is used because only 15 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 sold28 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 $688K · 7 sales$688K–$749K · 7 sales$749K–$808K · 7 salesOver $808K · 7 sales
3. Quartiles by net sale priceResale homes · 28 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.

2026-10-26T07:14:42.748963 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 7 7 28 sales Sales per group Under $688K: 7 sales (25%) $688K–$749K: 7 sales (25%) $749K–$808K: 7 sales (25%) Over $808K: 7 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 $688K$688K–$749K$749K–$808KOver $808K
Higher-priced homes Over $808K
  • Are much larger.
Lower-priced homes Under $688K
  • 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 $688K$688K–$749K$749K–$808KOver $808KReal difference?
Net price per SF$213 per SF$221 per SF$224 per SF$251 per SFunclear
Living area2,940 SFSmallest3,289 SF3,499 SF4,029 SFLargest✓ large
Year built2006200520052004unclear
Days on market58 days43 days14 days40 daysunclear
Discount from original list10.5%4.4%3.8%1.4%unclear
Price cut before sale57%43%29%0%unclear
Seller paid closing costs or repairs43%86%71%71%unclear
Has a view29%43%43%29%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

2026-10-26T07:14:42.776209 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $688K 7 sales $688K– $749K 7 sales $749K– $808K 7 sales Over $808K 7 sales $0 $100 $200 $300 $213 $221 $224 $251 Net price per SF, average

The average is $251 per SF for homes over $808K and $213 per SF for homes under $688K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $808K are about 1,090 SF (37%) larger than homes under $688K

2026-10-26T07:14:42.797930 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $688K 7 sales $688K– $749K 7 sales $749K– $808K 7 sales Over $808K 7 sales 0 2,000 4,000 2,940 3,289 3,499 4,029 Living area (SF), average

The average is 4,029 SF for homes over $808K and 2,940 SF for homes under $688K. 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

2026-10-26T07:14:42.820079 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $688K 7 sales $688K– $749K 7 sales $749K– $808K 7 sales Over $808K 7 sales 2004 2006 2008 2006 2005 2005 2004 Year built: median (dot) and middle half (bar)

The median is 2004 for homes over $808K and 2006 for homes under $688K. It falls step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:14:42.841867 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $688K 7 sales $688K– $749K 7 sales $749K– $808K 7 sales Over $808K 7 sales 0 20 40 60 58 43 14 40 Days on market, median

The median is 40 days for homes over $808K and 58 days for homes under $688K. It does not move in a straight line; homes under $688K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:14:42.863761 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $688K 7 sales $688K– $749K 7 sales $749K– $808K 7 sales Over $808K 7 sales 0.0% 5.0% 10.0% 10.5% 4.4% 3.8% 1.4% Discount from original list, average

The average is 1.4% for homes over $808K and 10.5% for homes under $688K. It falls step by step from the lowest range to the highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:14:42.893047 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% 57 43 29 43 86 43 29 71 43 0 71 29 Under $688K $688K–$749K $749K–$808K Over $808K

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

  • 0% of homes over $808K had a price cut before sale, against 57% of homes under $688K. Defined in 8.1.7.
  • 71% of homes over $808K had the seller pay closing costs or repairs, against 43% of homes under $688K. Defined in 8.1.8.
  • 29% of homes over $808K have a view, against 29% of homes under $688K. 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 $688K7 sales$688K–$749K7 sales$749K–$808K7 salesOver $808K7 salesAll28 salesReal difference?
Net sale price average$617,421$723,344$776,000$1,026,398$785,791by design
Net price per SF average$213$221$224$251$227unclear
Living area average2,9403,2893,4994,0293,439✓ large
Year built median20062005200520042005unclear

3.10 The numbers: selling

Under $688K7 sales$688K–$749K7 sales$749K–$808K7 salesOver $808K7 salesAll28 salesReal difference?
Days on market median5843144040unclear
Discount from original list average10.5%4.4%3.8%1.4%5.0%unclear
Price cut before sale57%43%29%0%32%unclear
Seller paid closing costs or repairs43%86%71%71%68%unclear
Has a view29%43%43%29%36%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 · 28 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.

2026-10-26T07:14:42.912746 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 7 7 28 sales Sales per group Under 3,044 SF: 7 sales (25%) 3,044–3,454 SF: 7 sales (25%) 3,531–3,765 SF: 7 sales (25%) Over 3,765 SF: 7 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 3,044 SF3,044–3,454 SF3,531–3,765 SFOver 3,765 SF
Larger homes Over 3,765 SF
  • Sell for much more.
Smaller homes Under 3,044 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 3,044 SF3,044–3,454 SF3,531–3,765 SFOver 3,765 SFReal difference?
Net sale price$648KLowest$721K$774K$1.00MHighest✓ large
Net price per SF$236 per SF$218 per SF$213 per SF$242 per SFunclear
Year built2006200520052004unclear
Days on market27 days43 days23 days41 daysunclear
Discount from original list5.6%5.3%4.7%4.5%unclear
Price cut before sale29%43%43%14%unclear
Seller paid closing costs or repairs57%71%86%57%unclear
Has a view43%57%14%29%unclear

4.3 Homes over 3,765 SF sell for about $353K (55%) more than homes under 3,044 SF

2026-10-26T07:14:42.932721 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,044 SF 7 sales 3,044– 3,454 SF 7 sales 3,531– 3,765 SF 7 sales Over 3,765 SF 7 sales $0K $500K $1.00M $648K $721K $774K $1.00M Net sale price, average

The average is $1.00M for homes over 3,765 SF and $648K for homes under 3,044 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

2026-10-26T07:14:42.955118 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,044 SF 7 sales 3,044– 3,454 SF 7 sales 3,531– 3,765 SF 7 sales Over 3,765 SF 7 sales $0 $100 $200 $236 $218 $213 $242 Net price per SF, average

The average is $242 per SF for homes over 3,765 SF and $236 per SF for homes under 3,044 SF. It does not move in a straight line; homes over 3,765 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:14:42.979065 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,044 SF 7 sales 3,044– 3,454 SF 7 sales 3,531– 3,765 SF 7 sales Over 3,765 SF 7 sales 2003 2004 2005 2006 2007 2006 2005 2005 2004 Year built: median (dot) and middle half (bar)

The median is 2004 for homes over 3,765 SF and 2006 for homes under 3,044 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:14:43.002171 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,044 SF 7 sales 3,044– 3,454 SF 7 sales 3,531– 3,765 SF 7 sales Over 3,765 SF 7 sales 0 20 40 27 43 23 41 Days on market, median

The median is 41 days for homes over 3,765 SF and 27 days for homes under 3,044 SF. It does not move in a straight line; homes 3,044–3,454 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:14:43.023594 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,044 SF 7 sales 3,044– 3,454 SF 7 sales 3,531– 3,765 SF 7 sales Over 3,765 SF 7 sales 0.0% 2.0% 4.0% 6.0% 5.6% 5.3% 4.7% 4.5% Discount from original list, average

The average is 4.5% for homes over 3,765 SF and 5.6% for homes under 3,044 SF. It falls step by step from the lowest range to the 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

2026-10-26T07:14:43.049802 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 57 43 43 71 57 43 86 14 14 57 29 Under 3,044 SF 3,044–3,454 SF 3,531–3,765 SF Over 3,765 SF

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

  • 14% of homes over 3,765 SF had a price cut before sale, against 29% of homes under 3,044 SF. Defined in 8.1.7.
  • 57% of homes over 3,765 SF had the seller pay closing costs or repairs, against 57% of homes under 3,044 SF. Defined in 8.1.8.
  • 29% of homes over 3,765 SF have a view, against 43% of homes under 3,044 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 3,044 SF7 sales3,044–3,454 SF7 sales3,531–3,765 SF7 salesOver 3,765 SF7 salesAll28 salesReal difference?
Net sale price average$647,564$721,487$773,607$1,000,505$785,791✓ large
Net price per SF average$236$218$213$242$227unclear
Living area average2,7363,3173,6404,0643,439by design
Year built median20062005200520042005unclear

4.10 The numbers: selling

Under 3,044 SF7 sales3,044–3,454 SF7 sales3,531–3,765 SF7 salesOver 3,765 SF7 salesAll28 salesReal difference?
Days on market median2743234140unclear
Discount from original list average5.6%5.3%4.7%4.5%5.0%unclear
Price cut before sale29%43%43%14%32%unclear
Seller paid closing costs or repairs57%71%86%57%68%unclear
Has a view43%57%14%29%36%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 · 28 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.

2026-10-26T07:14:43.069816 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 5 8 8 28 sales Sales per group Before 2004: 7 sales (25%) 2004: 5 sales (18%) 2005–2006: 8 sales (29%) After 2006: 8 sales (29%)
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 200420042005–2006After 2006Real difference?
Net sale price$893K$815K$742K$717Kunclear
Net price per SF$239 per SF$226 per SF$226 per SF$219 per SFunclear
Living area3,633 SF3,653 SF3,293 SF3,283 SFunclear
Days on market43 days10 days30 days44 daysunclear
Discount from original list4.1%5.4%4.1%6.5%unclear
Price cut before sale29%40%25%38%unclear
Seller paid closing costs or repairs71%40%88%62%unclear
Has a view43%40%38%25%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:14:43.090283 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 7 sales 2004 5 sales 2005– 2006 8 sales After 2006 8 sales $0K $500K $1.00M $893K $815K $742K $717K Net sale price, average

The average is $717K for homes built after 2006 and $893K for homes built before 2004. It falls step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:14:43.112366 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 7 sales 2004 5 sales 2005– 2006 8 sales After 2006 8 sales $0 $100 $200 $239 $226 $226 $219 Net price per SF, average

The average is $219 per SF for homes built after 2006 and $239 per SF for homes built before 2004. It does not move in a straight line; homes built before 2004 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:14:43.132989 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 7 sales 2004 5 sales 2005– 2006 8 sales After 2006 8 sales 0 2,000 4,000 3,633 3,653 3,293 3,283 Living area (SF), average

The average is 3,283 SF for homes built after 2006 and 3,633 SF for homes built before 2004. It does not move in a straight line; homes built 2004 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:14:43.153860 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 7 sales 2004 5 sales 2005– 2006 8 sales After 2006 8 sales 0 20 40 43 10 30 44 Days on market, median

The median is 44 days for homes built after 2006 and 43 days for homes built before 2004. It does not move in a straight line; homes built after 2006 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:14:43.175867 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 7 sales 2004 5 sales 2005– 2006 8 sales After 2006 8 sales 0.0% 2.0% 4.0% 6.0% 4.1% 5.4% 4.1% 6.5% Discount from original list, average

The average is 6.5% for homes built after 2006 and 4.1% for homes built before 2004. It does not move in a straight line; homes built after 2006 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

2026-10-26T07:14:43.200852 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 71 43 40 40 40 25 88 38 38 62 25 Before 2004 2004 2005–2006 After 2006

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

  • 38% of homes built after 2006 had a price cut before sale, against 29% of homes built before 2004. Defined in 8.1.7.
  • 62% of homes built after 2006 had the seller pay closing costs or repairs, against 71% of homes built before 2004. Defined in 8.1.8.
  • 25% of homes built after 2006 have a view, against 43% of homes built before 2004. 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 20047 sales20045 sales2005–20068 salesAfter 20068 salesAll28 salesReal difference?
Net sale price average$893,336$814,967$742,101$717,144$785,791unclear
Net price per SF average$239$226$226$219$227unclear
Living area average3,6333,6533,2933,2833,439unclear
Year built median20012004200520082005by design

5.10 The numbers: selling

Before 20047 sales20045 sales2005–20068 salesAfter 20068 salesAll28 salesReal difference?
Days on market median4310304440unclear
Discount from original list average4.1%5.4%4.1%6.5%5.0%unclear
Price cut before sale29%40%25%38%32%unclear
Seller paid closing costs or repairs71%40%88%62%68%unclear
Has a view43%40%38%25%36%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 · 28 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. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T07:14:43.218558 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 17 27 sales Sales per group View: 10 sales (37%) No view: 17 sales (63%)
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$759K$803Kunclear
Net price per SF$229 per SF$227 per SFunclear
Living area3,318 SF3,491 SFunclear
Year built20042005unclear
Days on market28 days40 daysunclear
Discount from original list4.2%5.1%unclear
Price cut before sale20%35%unclear
Seller paid closing costs or repairs80%59%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:14:43.234943 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 17 sales $0K $200K $400K $600K $800K $759K $803K Net sale price, average

The average is $759K for homes with a view and $803K 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

2026-10-26T07:14:43.253136 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 17 sales $0 $100 $200 $229 $227 Net price per SF, average

The average is $229 per SF for homes with a view and $227 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

2026-10-26T07:14:43.271760 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 17 sales 0 1,000 2,000 3,000 4,000 3,318 3,491 Living area (SF), average

The average is 3,318 SF for homes with a view and 3,491 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:14:43.313938 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 17 sales 2004 2005 2006 2007 2004 2005 Year built: median (dot) and middle half (bar)

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

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:14:43.332395 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 17 sales 0 10 20 30 40 28 40 Days on market, median

The median is 28 days for homes with a view and 40 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

2026-10-26T07:14:43.351199 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 17 sales 0.0% 2.0% 4.0% 6.0% 4.2% 5.1% Discount from original list, average

The average is 4.2% for homes with a view and 5.1% 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

2026-10-26T07:14:43.369644 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 20 80 35 59 View No view

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

  • 20% of homes with a view had a price cut before sale, against 35% of homes without a view. Defined in 8.1.7.
  • 80% of homes with a view had the seller pay closing costs or repairs, against 59% 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

View10 salesNo view17 salesAll27 salesReal difference?
Net sale price average$758,799$802,656$786,413unclear
Net price per SF average$229$227$228unclear
Living area average3,3183,4913,427unclear
Year built median200420052005unclear

6.11 The numbers: selling

View10 salesNo view17 salesAll27 salesReal difference?
Days on market median284040unclear
Discount from original list average4.2%5.1%4.8%unclear
Price cut before sale20%35%30%unclear
Seller paid closing costs or repairs80%59%67%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 Behrens Ranch.

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
28 resale sales. Average $785,791; median $748,980; standard deviation $225,083; middle half (25th–75th percentile) $684,688–$817,562; lowest $480,000, highest $1,799,000. 19 sales had a seller payment; their median payment was $3,000.

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
28 resale sales. Average $227; median $223; standard deviation $36; middle half (25th–75th percentile) $213–$234; lowest $172, highest $380.

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
28 resale sales. Average 3,439; median 3,492; standard deviation 541; middle half (25th–75th percentile) 3,022–3,773; lowest 2,104, highest 4,734.

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
28 resale sales. Average 2005; median 2005; standard deviation 3; middle half (25th–75th percentile) 2004–2007; lowest 2001, 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
28 resale sales. Average 49; median 40; standard deviation 50; middle half (25th–75th percentile) 12–64; lowest 1, highest 219. 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
28 resale sales. Average 5.0%; median 3.4%; standard deviation 5.1%; middle half (25th–75th percentile) 1.7%–7.0%; lowest −2.6%, highest 19.4%. 3 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
9 of 28 resale sales (32.1%).

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
19 of 28 resale sales (67.9%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
10 sales with a view, 17 without, 1 unclassified. Most common View entries: None 17, Park/Greenbelt 5, Trees/Woods 3, See Remarks 2, Neighborhood 2, Panoramic 1, Pool 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 = Round Rock, SubdivisionName contains any of “behrens ranch” (case-insensitive). A record is kept when its subdivision name belongs to the Behrens Ranch family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 28 closed Behrens Ranch records over the prior year, in ZIP 78681. 15 subdivision spellings kept, the most common: Behrens Ranch (8); Behrens Ranch Ph B Sec 02 (3); Behrens Ranch Ph B Sec 03 (3); Behrens Ranch Ph F Sec 01 (2); Behrens Ranch Ph C Sec 05 (2); Behrens Ranch Ph B Sec 01 (1); Behrens Ranch Ph A (1); Behrens Ranch Ph D Sec 05 (1); Behrens Ranch Ph C Sec 01C (1); Behrens Ranch Ph C Sec 01-C (1); Behrens Ranch Ph E Sec 01 (1); Behrens Ranch Ph C Sec 01c (1); and 3 more (3 records). No other names were found by the search.

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 15 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
28 single-family sales in the window: 28 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
28 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 $688K”.
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 $688K: $480,000–$674,750 (7 sales); $688K–$749K: $688,000–$748,960 (7 sales); $749K–$808K: $749,000–$808,000 (7 sales); Over $808K: $846,250–$1,799,000 (7 sales)
Quartiles by living area: Under 3,044 SF: 2,104–2,954 SF (7 sales); 3,044–3,454 SF: 3,044–3,454 SF (7 sales); 3,531–3,765 SF: 3,531–3,765 SF (7 sales); Over 3,765 SF: 3,797–4,734 SF (7 sales)
Quartiles by year built: Before 2004: 2001–2003 (7 sales); 2004: 2004–2004 (5 sales); 2005–2006: 2005–2006 (8 sales); After 2006: 2007–2012 (8 sales)
View and no view: View: MLS lists a view (10 sales); No view: None or Neighborhood (17 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 $785,791, median $748,980. Days on market: average 49, median 40: 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
2 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 = 4.3430.2268p < 0.0063Unclearε² = 0.161large
Living areaKruskal–WallisH = 15.6630.0013p < 0.0063Yesε² = 0.580large
Year builtKruskal–WallisH = 1.2830.7346p < 0.0063Unclearε² = 0.047small
Days on marketKruskal–WallisH = 3.7030.2959p < 0.0063Unclearε² = 0.137medium
Discount from original listKruskal–WallisH = 12.2230.0067p < 0.0063Unclearε² = 0.453large
Price cut before saleChi-squareχ² = 5.7330.1255p < 0.0063UnclearCramér’s V = 0.452medium
Seller paid closing costs or repairsChi-squareχ² = 3.1130.3748p < 0.0063UnclearCramér’s V = 0.333medium
Has a viewChi-squareχ² = 0.6230.8913p < 0.0063UnclearCramér’s V = 0.149small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 15.1230.0017p < 0.0063Yesε² = 0.560large
Net price per SFKruskal–WallisH = 6.6530.0840p < 0.0063Unclearε² = 0.246large
Year builtKruskal–WallisH = 1.9030.5928p < 0.0063Unclearε² = 0.070medium
Days on marketKruskal–WallisH = 1.0630.7857p < 0.0063Unclearε² = 0.039small
Discount from original listKruskal–WallisH = 1.3230.7235p < 0.0063Unclearε² = 0.049small
Price cut before saleChi-squareχ² = 1.8030.6147p < 0.0063UnclearCramér’s V = 0.254small
Seller paid closing costs or repairsChi-squareχ² = 1.8030.6147p < 0.0063UnclearCramér’s V = 0.254small
Has a viewChi-squareχ² = 3.1130.3748p < 0.0063UnclearCramér’s V = 0.333medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 2.0330.5667p < 0.0063Unclearε² = 0.075medium
Net price per SFKruskal–WallisH = 0.6630.8828p < 0.0063Unclearε² = 0.024small
Living areaKruskal–WallisH = 2.9130.4056p < 0.0063Unclearε² = 0.108medium
Days on marketKruskal–WallisH = 3.8030.2834p < 0.0063Unclearε² = 0.141large
Discount from original listKruskal–WallisH = 1.5530.6708p < 0.0063Unclearε² = 0.057small
Price cut before saleChi-squareχ² = 0.4730.9244p < 0.0063UnclearCramér’s V = 0.130small
Seller paid closing costs or repairsChi-squareχ² = 3.3430.3421p < 0.0063UnclearCramér’s V = 0.345medium
Has a viewChi-squareχ² = 0.6130.8949p < 0.0063UnclearCramér’s V = 0.147small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 87.00—0.9400p < 0.0063Unclearrank-biserial r = 0.024negligible
Net price per SFMann–Whitney UU = 104.00—0.3530p < 0.0063Unclearrank-biserial r = 0.224small
Living areaMann–Whitney UU = 63.00—0.2804p < 0.0063Unclearrank-biserial r = 0.259small
Year builtMann–Whitney UU = 78.50—0.7609p < 0.0063Unclearrank-biserial r = 0.076negligible
Days on marketMann–Whitney UU = 79.00—0.7823p < 0.0063Unclearrank-biserial r = 0.071negligible
Discount from original listMann–Whitney UU = 64.00—0.3033p < 0.0063Unclearrank-biserial r = 0.247small
Price cut before saleChi-squareχ² = 0.7110.4007p < 0.0063UnclearCramér’s V = 0.162small
Seller paid closing costs or repairsChi-squareχ² = 1.2710.2597p < 0.0063UnclearCramér’s V = 0.217small

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 28 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.