ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Sonterra

Jarrell, TX 76537 · 76588
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 · 6:52 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
82
single-family resale homes
Median net sale price
$236,500
average $233,537
Median net price per SF
$135
average $132
Median days on market
88 days
average 94 days
1. SummaryResale homes · 82 sales · October 26, 2025 – October 25, 2026

This study looks at the 82 resale homes sold in Sonterra in the 365 days to October 25, 2026. A full year is used because only 54 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 sold82 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 $212K · 20 sales$212K–$235K · 21 sales$238K–$259K · 21 salesOver $259K · 20 sales
3. Quartiles by net sale priceResale homes · 82 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.

2026-10-26T06:52:18.300569 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 20 21 21 20 82 sales Sales per group Under $212K: 20 sales (24%) $212K–$235K: 21 sales (26%) $238K–$259K: 21 sales (26%) Over $259K: 20 sales (24%)
Bottom line

3.1 Key differences

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

Under $212K$212K–$235K$238K–$259KOver $259K
Higher-priced homes Over $259K
  • Are much larger.
  • Sell closer to their first asking price.
Lower-priced homes Under $212K
  • Are much smaller.
  • Sell further below their first asking price.

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 $212K$212K–$235K$238K–$259KOver $259KReal difference?
Net price per SF$130 per SF$139 per SF$130 per SF$131 per SFunclear
Living area1,454 SFSmallest1,644 SF1,970 SF2,198 SFLargest✓ large
Year built2016201720182018unclear
Days on market70 days67 days89 days86 daysunclear
Discount from original list12.4%Biggest8.1%10.3%4.6%Smallest✓ large
Price cut before sale70%76%67%55%unclear
Seller paid closing costs or repairs55%86%86%50%unclear
Has a view10%10%10%5%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

2026-10-26T06:52:18.329247 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $212K 20 sales $212K– $235K 21 sales $238K– $259K 21 sales Over $259K 20 sales $0 $50 $100 $150 $130 $139 $130 $131 Net price per SF, average

The average is $131 per SF for homes over $259K and $130 per SF for homes under $212K. It does not move in a straight line; homes $212K–$235K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $259K are about 740 SF (51%) larger than homes under $212K

2026-10-26T06:52:18.351968 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $212K 20 sales $212K– $235K 21 sales $238K– $259K 21 sales Over $259K 20 sales 0 1,000 2,000 1,454 1,644 1,970 2,198 Living area (SF), average

The average is 2,198 SF for homes over $259K and 1,454 SF for homes under $212K. 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

2026-10-26T06:52:18.376919 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $212K 20 sales $212K– $235K 21 sales $238K– $259K 21 sales Over $259K 20 sales 2012 2014 2016 2018 2020 2016 2017 2018 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over $259K and 2016 for homes under $212K. 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

2026-10-26T06:52:18.400042 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $212K 20 sales $212K– $235K 21 sales $238K– $259K 21 sales Over $259K 20 sales 0 50 100 70 67 89 86 Days on market, median

The median is 86 days for homes over $259K and 70 days for homes under $212K. It does not move in a straight line; homes $238K–$259K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Homes over $259K sell about 8 percentage points closer to their first asking price than homes under $212K

2026-10-26T06:52:18.421890 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $212K 20 sales $212K– $235K 21 sales $238K– $259K 21 sales Over $259K 20 sales 0.0% 5.0% 10.0% 12.4% 8.1% 10.3% 4.6% Discount from original list, average

The average is 4.6% for homes over $259K and 12.4% for homes under $212K. It does not move in a straight line; homes under $212K are highest. Defined in 8.1.6.

✓ Real difference · large

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

2026-10-26T06:52:18.451443 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% 70 55 10 76 86 10 67 86 10 55 50 5 Under $212K $212K–$235K $238K–$259K Over $259K

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

  • 55% of homes over $259K had a price cut before sale, against 70% of homes under $212K. Defined in 8.1.7.
  • 50% of homes over $259K had the seller pay closing costs or repairs, against 55% of homes under $212K. Defined in 8.1.8.
  • 5% of homes over $259K have a view, against 10% of homes under $212K. 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 $212K20 sales$212K–$235K21 sales$238K–$259K21 salesOver $259K20 salesAll82 salesReal difference?
Net sale price average$185,411$224,273$247,950$276,257$233,537by design
Net price per SF average$130$139$130$131$132unclear
Living area average1,4541,6441,9702,1981,816✓ large
Year built median20162017201820182018unclear

3.10 The numbers: selling

Under $212K20 sales$212K–$235K21 sales$238K–$259K21 salesOver $259K20 salesAll82 salesReal difference?
Days on market median7067898688unclear
Discount from original list average12.4%8.1%10.3%4.6%8.9%✓ large
Price cut before sale70%76%67%55%67%unclear
Seller paid closing costs or repairs55%86%86%50%70%unclear
Has a view10%10%10%5%9%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 · 82 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.

2026-10-26T06:52:18.472447 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 20 21 21 20 82 sales Sales per group Under 1,450 SF: 20 sales (24%) 1,450–1,692 SF: 21 sales (26%) 1,733–2,010 SF: 21 sales (26%) Over 2,010 SF: 20 sales (24%)
Bottom line

4.1 Key differences

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

Under 1,450 SF1,450–1,692 SF1,733–2,010 SFOver 2,010 SF
Larger homes Over 2,010 SF
  • Sell for less per square foot.
  • Sell for much more.
Smaller homes Under 1,450 SF
  • Sell for more per square foot.
  • 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 1,450 SF1,450–1,692 SF1,733–2,010 SFOver 2,010 SFReal difference?
Net sale price$202KLowest$226K$241K$265KHighest✓ large
Net price per SF$149 per SFHighest$144 per SF$128 per SF$108 per SFLowest✓ large
Year built2017201820172019unclear
Days on market76 days62 days94 days96 daysunclear
Discount from original list10.4%7.8%8.5%8.8%unclear
Price cut before sale75%62%52%80%unclear
Seller paid closing costs or repairs65%81%62%70%unclear
Has a view5%5%19%5%unclear

4.3 Homes over 2,010 SF sell for about $63K (31%) more than homes under 1,450 SF

2026-10-26T06:52:18.494070 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,450 SF 20 sales 1,450– 1,692 SF 21 sales 1,733– 2,010 SF 21 sales Over 2,010 SF 20 sales $0K $100K $200K $300K $202K $226K $241K $265K Net sale price, average

The average is $265K for homes over 2,010 SF and $202K for homes under 1,450 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 2,010 SF sell for about $42 per SF (28%) less than homes under 1,450 SF

2026-10-26T06:52:18.516231 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,450 SF 20 sales 1,450– 1,692 SF 21 sales 1,733– 2,010 SF 21 sales Over 2,010 SF 20 sales $0 $50 $100 $150 $149 $144 $128 $108 Net price per SF, average

The average is $108 per SF for homes over 2,010 SF and $149 per SF for homes under 1,450 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-10-26T06:52:18.541580 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,450 SF 20 sales 1,450– 1,692 SF 21 sales 1,733– 2,010 SF 21 sales Over 2,010 SF 20 sales 2012 2014 2016 2018 2020 2017 2018 2017 2019 Year built: median (dot) and middle half (bar)

The median is 2019 for homes over 2,010 SF and 2017 for homes under 1,450 SF. It does not move in a straight line; homes over 2,010 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T06:52:18.565162 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,450 SF 20 sales 1,450– 1,692 SF 21 sales 1,733– 2,010 SF 21 sales Over 2,010 SF 20 sales 0 50 100 76 62 94 96 Days on market, median

The median is 96 days for homes over 2,010 SF and 76 days for homes under 1,450 SF. It does not move in a straight line; homes over 2,010 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T06:52:18.586547 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,450 SF 20 sales 1,450– 1,692 SF 21 sales 1,733– 2,010 SF 21 sales Over 2,010 SF 20 sales 0.0% 5.0% 10.0% 10.4% 7.8% 8.5% 8.8% Discount from original list, average

The average is 8.8% for homes over 2,010 SF and 10.4% for homes under 1,450 SF. It does not move in a straight line; homes under 1,450 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

2026-10-26T06:52:18.612709 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% 75 65 5 62 81 5 52 62 19 80 70 5 Under 1,450 SF 1,450–1,692 SF 1,733–2,010 SF Over 2,010 SF

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

  • 80% of homes over 2,010 SF had a price cut before sale, against 75% of homes under 1,450 SF. Defined in 8.1.7.
  • 70% of homes over 2,010 SF had the seller pay closing costs or repairs, against 65% of homes under 1,450 SF. Defined in 8.1.8.
  • 5% of homes over 2,010 SF have a view, against 5% of homes under 1,450 SF. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

4.9 The numbers: price and size

Under 1,450 SF20 sales1,450–1,692 SF21 sales1,733–2,010 SF21 salesOver 2,010 SF20 salesAll82 salesReal difference?
Net sale price average$201,871$226,398$241,188$264,666$233,537✓ large
Net price per SF average$149$144$128$108$132✓ large
Living area average1,3551,5731,8822,4651,816by design
Year built median20172018201720192018unclear

4.10 The numbers: selling

Under 1,450 SF20 sales1,450–1,692 SF21 sales1,733–2,010 SF21 salesOver 2,010 SF20 salesAll82 salesReal difference?
Days on market median7662949688unclear
Discount from original list average10.4%7.8%8.5%8.8%8.9%unclear
Price cut before sale75%62%52%80%67%unclear
Seller paid closing costs or repairs65%81%62%70%70%unclear
Has a view5%5%19%5%9%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 · 82 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.

2026-10-26T06:52:18.633516 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 20 18 27 17 82 sales Sales per group Before 2014: 20 sales (24%) 2014–2017: 18 sales (22%) 2018–2019: 27 sales (33%) After 2019: 17 sales (21%)
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 20142014–20172018–2019After 2019Real difference?
Net sale price$217K$236K$236K$248Kunclear
Net price per SF$131 per SF$134 per SF$130 per SF$136 per SFunclear
Living area1,692 SF1,835 SF1,858 SF1,877 SFunclear
Days on market80 days63 days89 days75 daysunclear
Discount from original list11.2%9.1%7.7%7.6%unclear
Price cut before sale60%61%70%76%unclear
Seller paid closing costs or repairs60%72%74%71%unclear
Has a view0%6%11%18%unclear

5.3 Net sale price: no clear difference

2026-10-26T06:52:18.654790 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 20 sales 2014– 2017 18 sales 2018– 2019 27 sales After 2019 17 sales $0K $100K $200K $217K $236K $236K $248K Net sale price, average

The average is $248K for homes built after 2019 and $217K for homes built before 2014. It rises 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

2026-10-26T06:52:18.677452 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 20 sales 2014– 2017 18 sales 2018– 2019 27 sales After 2019 17 sales $0 $50 $100 $150 $131 $134 $130 $136 Net price per SF, average

The average is $136 per SF for homes built after 2019 and $131 per SF for homes built before 2014. It does not move in a straight line; homes built after 2019 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T06:52:18.699267 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 20 sales 2014– 2017 18 sales 2018– 2019 27 sales After 2019 17 sales 0 1,000 2,000 1,692 1,835 1,858 1,877 Living area (SF), average

The average is 1,877 SF for homes built after 2019 and 1,692 SF for homes built before 2014. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T06:52:18.722204 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 20 sales 2014– 2017 18 sales 2018– 2019 27 sales After 2019 17 sales 0 50 100 80 63 89 75 Days on market, median

The median is 75 days for homes built after 2019 and 80 days for homes built before 2014. It does not move in a straight line; homes built 2018–2019 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T06:52:18.744585 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 20 sales 2014– 2017 18 sales 2018– 2019 27 sales After 2019 17 sales 0.0% 5.0% 10.0% 11.2% 9.1% 7.7% 7.6% Discount from original list, average

The average is 7.6% for homes built after 2019 and 11.2% for homes built before 2014. It falls step by step from the lowest range to the 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

2026-10-26T06:52:18.770955 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 60 60 0 61 72 6 70 74 11 76 71 18 Before 2014 2014–2017 2018–2019 After 2019

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

  • 76% of homes built after 2019 had a price cut before sale, against 60% of homes built before 2014. Defined in 8.1.7.
  • 71% of homes built after 2019 had the seller pay closing costs or repairs, against 60% of homes built before 2014. Defined in 8.1.8.
  • 18% of homes built after 2019 have a view, against 0% of homes built before 2014. 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 201420 sales2014–201718 sales2018–201927 salesAfter 201917 salesAll82 salesReal difference?
Net sale price average$216,914$235,577$235,621$247,624$233,537unclear
Net price per SF average$131$134$130$136$132unclear
Living area average1,6921,8351,8581,8771,816unclear
Year built median20102016201920212018by design

5.10 The numbers: selling

Before 201420 sales2014–201718 sales2018–201927 salesAfter 201917 salesAll82 salesReal difference?
Days on market median8063897588unclear
Discount from original list average11.2%9.1%7.7%7.6%8.9%unclear
Price cut before sale60%61%70%76%67%unclear
Seller paid closing costs or repairs60%72%74%71%70%unclear
Has a view0%6%11%18%9%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 · 82 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. 2 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T06:52:18.789991 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 73 80 sales Sales per group View: 7 sales (9%) No view: 73 sales (91%)
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$229K$234Kunclear
Net price per SF$125 per SF$133 per SFunclear
Living area1,838 SF1,818 SFunclear
Year built20192017unclear
Days on market117 days82 daysunclear
Discount from original list8.1%8.9%unclear
Price cut before sale57%67%unclear
Seller paid closing costs or repairs86%68%unclear

6.3 Net sale price: no clear difference

2026-10-26T06:52:18.806472 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 73 sales $0K $100K $200K $229K $234K Net sale price, average

The average is $229K for homes with a view and $234K 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

2026-10-26T06:52:18.824143 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 73 sales $0 $50 $100 $150 $125 $133 Net price per SF, average

The average is $125 per SF for homes with a view and $133 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

2026-10-26T06:52:18.907664 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 73 sales 0 500 1,000 1,500 2,000 1,838 1,818 Living area (SF), average

The average is 1,838 SF for homes with a view and 1,818 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T06:52:18.928651 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 73 sales 2014 2016 2018 2020 2019 2017 Year built: median (dot) and middle half (bar)

The median is 2019 for homes with a view and 2017 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T06:52:18.947605 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 73 sales 0 50 100 117 82 Days on market, median

The median is 117 days for homes with a view and 82 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

2026-10-26T06:52:18.966131 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 73 sales 0.0% 2.5% 5.0% 7.5% 10.0% 8.1% 8.9% Discount from original list, average

The average is 8.1% for homes with a view and 8.9% 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

2026-10-26T06:52:18.985884 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 57 86 67 68 View No view

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

  • 57% of homes with a view had a price cut before sale, against 67% of homes without a view. Defined in 8.1.7.
  • 86% of homes with a view had the seller pay closing costs or repairs, against 68% 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

View7 salesNo view73 salesAll80 salesReal difference?
Net sale price average$229,187$233,614$233,227unclear
Net price per SF average$125$133$132unclear
Living area average1,8381,8181,819unclear
Year built median201920172018unclear

6.11 The numbers: selling

View7 salesNo view73 salesAll80 salesReal difference?
Days on market median1178288unclear
Discount from original list average8.1%8.9%8.9%unclear
Price cut before sale57%67%66%unclear
Seller paid closing costs or repairs86%68%70%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 · 94 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: 94 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 Sonterra.
MeasureAverageMedian
Sales94
Net sale price$275,812$274,950
Net price per SF$145$142
Living area (SF)1,9582,003
Days on market152125
Discount from original list11.4%10.8%
Price cut before sale77% of sales
Seller paid closing costs or repairs80% of sales
Year built2024–2026

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
82 resale sales. Average $233,537; median $236,500; standard deviation $36,365; middle half (25th–75th percentile) $212,414–$258,575; lowest $141,000, highest $350,000. 57 sales had a seller payment; their median payment was $8,699.

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
82 resale sales. Average $132; median $135; standard deviation $23; middle half (25th–75th percentile) $115–$149; lowest $76, highest $196.

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
82 resale sales. Average 1,816; median 1,712; standard deviation 444; middle half (25th–75th percentile) 1,453–2,006; lowest 1,183, highest 3,222.

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
82 resale sales. Average 2016; median 2018; standard deviation 4; middle half (25th–75th percentile) 2014–2019; lowest 2006, highest 2022.

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
82 resale sales. Average 94; median 88; standard deviation 76; middle half (25th–75th percentile) 41–119; lowest 2, highest 410. 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
82 resale sales. Average 8.9%; median 8.0%; standard deviation 6.9%; middle half (25th–75th percentile) 5.5%–11.9%; lowest −13.8%, highest 34.4%. 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
55 of 82 resale sales (67.1%).

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
57 of 82 resale sales (69.5%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
7 sales with a view, 73 without, 2 unclassified. Most common View entries: None 47, Neighborhood 30, Pasture 3, Park/Greenbelt 3, City 1, Trees/Woods 1, See Remarks 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Jarrell, SubdivisionName contains any of “sonterra”, “sonterra west”, “eastwood at sonterra”, “sonterra cool water”, “sonterra eastwood”, “sonterra coolwater” (case-insensitive). A record is kept when its subdivision name belongs to the Sonterra family, the same rule comparable sales use (it includes Sonterra West, Eastwood at Sonterra, Sonterra Cool Water, Sonterra-Eastwood, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 180 closed Sonterra records over the prior year, in ZIP 76537, 76588. 39 subdivision spellings kept, the most common: Sonterra (70); Eastwood at Sonterra (35); Sonterra West (20); Sonterra Sec 13 (5); SONTERRA (4); Sonterra West Sec 08-C (4); Sonterra West Sec 07-A Ph 01 A (3); Sonterra West Sec 7 Ph 4 (2); Sonterra West Ph 06 (2); Sonterra Cool Water (2); Sonterra West Ph V-A (2); Sonterra West Ph 4 Sec 7 (2); and 27 more (29 records). Names found by the search but not part of Sonterra, left out: Cool Water at Sonterra (24); Sonterra Ii Condos Ph 2 (1); Sonterra II Condos (1); Sonterra Ii Condos Ph Viii (1); Sonterra Ii Condos Ph Iv (1); Sonterra I Condos (1); Sonterra L Condos (1); Sonterra Ii Condos PhIii (1); Sonterra Il Condos Ph Iv (1); Sonterra Il Condos Ph Iii (1); Sonterra Ii Condos (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 54 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
176 single-family sales in the window: 82 resale, 94 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
82 resale; 94 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
4 sale(s) other than single-family homes (condo, townhome and similar)

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 $212K”.
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 $212K: $141,000–$207,500 (20 sales); $212K–$235K: $212,000–$235,000 (21 sales); $238K–$259K: $238,000–$259,000 (21 sales); Over $259K: $260,000–$350,000 (20 sales)
Quartiles by living area: Under 1,450 SF: 1,183–1,449 SF (20 sales); 1,450–1,692 SF: 1,450–1,692 SF (21 sales); 1,733–2,010 SF: 1,733–2,010 SF (21 sales); Over 2,010 SF: 2,112–3,222 SF (20 sales)
Quartiles by year built: Before 2014: 2006–2013 (20 sales); 2014–2017: 2014–2017 (18 sales); 2018–2019: 2018–2019 (27 sales); After 2019: 2020–2022 (17 sales)
View and no view: View: MLS lists a view (7 sales); No view: None or Neighborhood (73 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 $233,537, median $236,500. Days on market: average 94, median 88: 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
4 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 = 3.1830.3646p < 0.0063Unclearε² = 0.039small
Living areaKruskal–WallisH = 35.643< 0.0001p < 0.0063Yesε² = 0.440large
Year builtKruskal–WallisH = 6.0830.1080p < 0.0063Unclearε² = 0.075medium
Days on marketKruskal–WallisH = 0.9630.8111p < 0.0063Unclearε² = 0.012small
Discount from original listKruskal–WallisH = 13.9730.0029p < 0.0063Yesε² = 0.173large
Price cut before saleChi-squareχ² = 2.1930.5340p < 0.0063UnclearCramér’s V = 0.163small
Seller paid closing costs or repairsChi-squareχ² = 10.7830.0130p < 0.0063UnclearCramér’s V = 0.363medium
Has a viewChi-squareχ² = 0.4330.9345p < 0.0063UnclearCramér’s V = 0.072negligible

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 35.223< 0.0001p < 0.0063Yesε² = 0.435large
Net price per SFKruskal–WallisH = 43.433< 0.0001p < 0.0063Yesε² = 0.536large
Year builtKruskal–WallisH = 6.7830.0794p < 0.0063Unclearε² = 0.084medium
Days on marketKruskal–WallisH = 5.2530.1541p < 0.0063Unclearε² = 0.065medium
Discount from original listKruskal–WallisH = 1.9930.5745p < 0.0063Unclearε² = 0.025small
Price cut before saleChi-squareχ² = 4.3930.2224p < 0.0063UnclearCramér’s V = 0.231small
Seller paid closing costs or repairsChi-squareχ² = 2.0630.5591p < 0.0063UnclearCramér’s V = 0.159small
Has a viewChi-squareχ² = 4.0030.2620p < 0.0063UnclearCramér’s V = 0.221small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 5.0430.1686p < 0.0063Unclearε² = 0.062medium
Net price per SFKruskal–WallisH = 0.8530.8382p < 0.0063Unclearε² = 0.010small
Living areaKruskal–WallisH = 2.4130.4923p < 0.0063Unclearε² = 0.030small
Days on marketKruskal–WallisH = 2.4030.4945p < 0.0063Unclearε² = 0.030small
Discount from original listKruskal–WallisH = 3.3630.3388p < 0.0063Unclearε² = 0.042small
Price cut before saleChi-squareχ² = 1.5630.6695p < 0.0063UnclearCramér’s V = 0.138small
Seller paid closing costs or repairsChi-squareχ² = 1.1930.7552p < 0.0063UnclearCramér’s V = 0.121small
Has a viewChi-squareχ² = 4.1130.2500p < 0.0063UnclearCramér’s V = 0.224small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 233.50—0.7143p < 0.0063Unclearrank-biserial r = 0.086negligible
Net price per SFMann–Whitney UU = 194.00—0.2990p < 0.0063Unclearrank-biserial r = 0.241small
Living areaMann–Whitney UU = 298.00—0.4745p < 0.0063Unclearrank-biserial r = 0.166small
Year builtMann–Whitney UU = 385.50—0.0265p < 0.0063Unclearrank-biserial r = 0.509large
Days on marketMann–Whitney UU = 323.00—0.2539p < 0.0063Unclearrank-biserial r = 0.264small
Discount from original listMann–Whitney UU = 217.00—0.5176p < 0.0063Unclearrank-biserial r = 0.151small
Price cut before saleChi-squareχ² = 0.2810.5937p < 0.0063UnclearCramér’s V = 0.060negligible
Seller paid closing costs or repairsChi-squareχ² = 0.9010.3422p < 0.0063UnclearCramér’s V = 0.106small

8.4 Data notes

Left out of the analysis: 94 new-construction sales (basic statistics only, section 7); 4 sale(s) other than single-family homes (condo, townhome and similar). 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 82 closed MLS resale sales; the 94 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.