ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Belterra

Austin, TX 78737
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 · 7:00 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
83
single-family resale homes
Median net sale price
$674,900
average $707,654
Median net price per SF
$236
average $241
Median days on market
23 days
average 57 days
1. SummaryResale homes · 83 sales · October 26, 2025 – October 25, 2026

This study looks at the 83 resale homes sold in Belterra in the 365 days to October 25, 2026. A full year is used because only 49 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 sold83 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 $617K · 21 sales$617K–$675K · 21 sales$682K–$800K · 19 salesOver $800K · 22 sales
3. Quartiles by net sale priceResale homes · 83 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.

2026-10-26T07:01:05.033912 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 21 21 19 22 83 sales Sales per group Under $617K: 21 sales (25%) $617K–$675K: 21 sales (25%) $682K–$800K: 19 sales (23%) Over $800K: 22 sales (27%)
Bottom line

3.1 Key differences

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

Under $617K$617K–$675K$682K–$800KOver $800K
Higher-priced homes Over $800K
  • Are much larger.
  • Sell closer to their first asking price.
Lower-priced homes Under $617K
  • 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 $617K$617K–$675K$682K–$800KOver $800KReal difference?
Net price per SF$236 per SF$236 per SF$244 per SF$246 per SFunclear
Living area2,278 SFSmallest2,795 SF3,131 SF3,716 SFLargest✓ large
Year built2006201620132012unclear
Days on market34 days21 days21 days14 daysunclear
Discount from original list4.3%3.6%6.0%Biggest0.2%Smallest✓ large
Price cut before sale38%19%47%18%unclear
Seller paid closing costs or repairs62%62%53%50%unclear
Has a view48%57%58%68%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

2026-10-26T07:01:05.062870 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $617K 21 sales $617K– $675K 21 sales $682K– $800K 19 sales Over $800K 22 sales $0 $100 $200 $236 $236 $244 $246 Net price per SF, average

The average is $246 per SF for homes over $800K and $236 per SF for homes under $617K. It does not move in a straight line; homes over $800K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $800K are about 1,440 SF (63%) larger than homes under $617K

2026-10-26T07:01:05.085360 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $617K 21 sales $617K– $675K 21 sales $682K– $800K 19 sales Over $800K 22 sales 0 2,000 4,000 2,278 2,795 3,131 3,716 Living area (SF), average

The average is 3,716 SF for homes over $800K and 2,278 SF for homes under $617K. 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

2026-10-26T07:01:05.110367 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $617K 21 sales $617K– $675K 21 sales $682K– $800K 19 sales Over $800K 22 sales 2005 2008 2011 2014 2017 2006 2016 2013 2012 Year built: median (dot) and middle half (bar)

The median is 2012 for homes over $800K and 2006 for homes under $617K. It does not move in a straight line; homes $617K–$675K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:01:05.133603 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $617K 21 sales $617K– $675K 21 sales $682K– $800K 19 sales Over $800K 22 sales 0 20 40 34 21 21 14 Days on market, median

The median is 14 days for homes over $800K and 34 days for homes under $617K. 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 Homes over $800K sell about 4 percentage points closer to their first asking price than homes under $617K

2026-10-26T07:01:05.155689 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $617K 21 sales $617K– $675K 21 sales $682K– $800K 19 sales Over $800K 22 sales 0.0% 2.0% 4.0% 6.0% 4.3% 3.6% 6.0% 0.2% Discount from original list, average

The average is 0.2% for homes over $800K and 4.3% for homes under $617K. It does not move in a straight line; homes $682K–$800K 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

2026-10-26T07:01:05.185921 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% 38 62 48 19 62 57 47 53 58 18 50 68 Under $617K $617K–$675K $682K–$800K Over $800K

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

  • 18% of homes over $800K had a price cut before sale, against 38% of homes under $617K. Defined in 8.1.7.
  • 50% of homes over $800K had the seller pay closing costs or repairs, against 62% of homes under $617K. Defined in 8.1.8.
  • 68% of homes over $800K have a view, against 48% of homes under $617K. 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 $617K21 sales$617K–$675K21 sales$682K–$800K19 salesOver $800K22 salesAll83 salesReal difference?
Net sale price average$528,028$649,344$744,721$902,762$707,654by design
Net price per SF average$236$236$244$246$241unclear
Living area average2,2782,7953,1313,7162,985✓ large
Year built median20062016201320122012unclear

3.10 The numbers: selling

Under $617K21 sales$617K–$675K21 sales$682K–$800K19 salesOver $800K22 salesAll83 salesReal difference?
Days on market median3421211423unclear
Discount from original list average4.3%3.6%6.0%0.2%3.4%✓ large
Price cut before sale38%19%47%18%30%unclear
Seller paid closing costs or repairs62%62%53%50%57%unclear
Has a view48%57%58%68%58%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 · 83 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.

2026-10-26T07:01:05.206941 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 21 21 20 21 83 sales Sales per group Under 2,534 SF: 21 sales (25%) 2,534–2,924 SF: 21 sales (25%) 2,940–3,434 SF: 20 sales (24%) Over 3,434 SF: 21 sales (25%)
Bottom line

4.1 Key differences

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

Under 2,534 SF2,534–2,924 SF2,940–3,434 SFOver 3,434 SF
Larger homes Over 3,434 SF
  • Sell for much more.
  • Sell for less per square foot.
Smaller homes Under 2,534 SF
  • Sell for much less.
  • Sell for more per square foot.

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 2,534 SF2,534–2,924 SF2,940–3,434 SFOver 3,434 SFReal difference?
Net sale price$569KLowest$642K$742K$879KHighest✓ large
Net price per SF$266 per SFHighest$234 per SF$237 per SF$225 per SFLowest✓ large
Year built2010201320132008unclear
Days on market26 days34 days25 days14 daysunclear
Discount from original list3.1%5.0%4.2%1.5%unclear
Price cut before sale24%43%35%19%unclear
Seller paid closing costs or repairs52%67%55%52%unclear
Has a view67%52%45%67%unclear

4.3 Homes over 3,434 SF sell for about $310K (54%) more than homes under 2,534 SF

2026-10-26T07:01:05.228041 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,534 SF 21 sales 2,534– 2,924 SF 21 sales 2,940– 3,434 SF 20 sales Over 3,434 SF 21 sales $0K $500K $1.00M $569K $642K $742K $879K Net sale price, average

The average is $879K for homes over 3,434 SF and $569K for homes under 2,534 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 3,434 SF sell for about $41 per SF (15%) less than homes under 2,534 SF

2026-10-26T07:01:05.250748 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,534 SF 21 sales 2,534– 2,924 SF 21 sales 2,940– 3,434 SF 20 sales Over 3,434 SF 21 sales $0 $100 $200 $300 $266 $234 $237 $225 Net price per SF, average

The average is $225 per SF for homes over 3,434 SF and $266 per SF for homes under 2,534 SF. It does not move in a straight line; homes under 2,534 SF are highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-10-26T07:01:05.274584 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,534 SF 21 sales 2,534– 2,924 SF 21 sales 2,940– 3,434 SF 20 sales Over 3,434 SF 21 sales 2008 2011 2014 2017 2010 2013 2013 2008 Year built: median (dot) and middle half (bar)

The median is 2008 for homes over 3,434 SF and 2010 for homes under 2,534 SF. It does not move in a straight line; homes 2,534–2,924 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:01:05.297395 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,534 SF 21 sales 2,534– 2,924 SF 21 sales 2,940– 3,434 SF 20 sales Over 3,434 SF 21 sales 0 20 40 26 34 25 14 Days on market, median

The median is 14 days for homes over 3,434 SF and 26 days for homes under 2,534 SF. It does not move in a straight line; homes 2,534–2,924 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:01:05.319867 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,534 SF 21 sales 2,534– 2,924 SF 21 sales 2,940– 3,434 SF 20 sales Over 3,434 SF 21 sales 0.0% 2.0% 4.0% 3.1% 5.0% 4.2% 1.5% Discount from original list, average

The average is 1.5% for homes over 3,434 SF and 3.1% for homes under 2,534 SF. It does not move in a straight line; homes 2,534–2,924 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

2026-10-26T07:01:05.346320 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% 24 52 67 43 67 52 35 55 45 19 52 67 Under 2,534 SF 2,534–2,924 SF 2,940–3,434 SF Over 3,434 SF

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

  • 19% of homes over 3,434 SF had a price cut before sale, against 24% of homes under 2,534 SF. Defined in 8.1.7.
  • 52% of homes over 3,434 SF had the seller pay closing costs or repairs, against 52% of homes under 2,534 SF. Defined in 8.1.8.
  • 67% of homes over 3,434 SF have a view, against 67% of homes under 2,534 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 2,534 SF21 sales2,534–2,924 SF21 sales2,940–3,434 SF20 salesOver 3,434 SF21 salesAll83 salesReal difference?
Net sale price average$569,147$641,947$742,349$878,825$707,654✓ large
Net price per SF average$266$234$237$225$241✓ large
Living area average2,1532,7453,1353,9162,985by design
Year built median20102013201320082012unclear

4.10 The numbers: selling

Under 2,534 SF21 sales2,534–2,924 SF21 sales2,940–3,434 SF20 salesOver 3,434 SF21 salesAll83 salesReal difference?
Days on market median2634251423unclear
Discount from original list average3.1%5.0%4.2%1.5%3.4%unclear
Price cut before sale24%43%35%19%30%unclear
Seller paid closing costs or repairs52%67%55%52%57%unclear
Has a view67%52%45%67%58%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 · 83 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.

2026-10-26T07:01:05.367344 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 25 14 23 21 83 sales Sales per group Before 2007: 25 sales (30%) 2007–2011: 14 sales (17%) 2012–2016: 23 sales (28%) After 2016: 21 sales (25%)
Bottom line

5.1 Key differences

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

Before 20072007–20112012–2016After 2016
Newer homes After 2016
  • Sell for more per square foot.
Older homes Before 2007
  • Sell for less per square foot.

5.2 At a glance

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

Before 20072007–20112012–2016After 2016Real difference?
Net sale price$675K$692K$692K$774Kunclear
Net price per SF$227 per SFLowest$232 per SF$239 per SF$265 per SFHighest✓ large
Living area3,054 SF3,019 SF2,908 SF2,967 SFunclear
Days on market23 days17 days19 days29 daysunclear
Discount from original list3.2%1.7%3.4%4.9%unclear
Price cut before sale20%21%43%33%unclear
Seller paid closing costs or repairs56%79%57%43%unclear
Has a view52%50%57%71%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:01:05.388442 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 25 sales 2007– 2011 14 sales 2012– 2016 23 sales After 2016 21 sales $0K $250K $500K $750K $675K $692K $692K $774K Net sale price, average

The average is $774K for homes built after 2016 and $675K for homes built before 2007. It does not move in a straight line; homes built after 2016 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Homes built after 2016 sell for about $38 per SF (17%) more than homes built before 2007

2026-10-26T07:01:05.411906 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 25 sales 2007– 2011 14 sales 2012– 2016 23 sales After 2016 21 sales $0 $100 $200 $300 $227 $232 $239 $265 Net price per SF, average

The average is $265 per SF for homes built after 2016 and $227 per SF for homes built before 2007. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

5.5 Living area: no clear difference

2026-10-26T07:01:05.434226 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 25 sales 2007– 2011 14 sales 2012– 2016 23 sales After 2016 21 sales 0 1,000 2,000 3,000 3,054 3,019 2,908 2,967 Living area (SF), average

The average is 2,967 SF for homes built after 2016 and 3,054 SF for homes built before 2007. It does not move in a straight line; homes built before 2007 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:01:05.456445 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 25 sales 2007– 2011 14 sales 2012– 2016 23 sales After 2016 21 sales 0 10 20 30 23 17 19 29 Days on market, median

The median is 29 days for homes built after 2016 and 23 days for homes built before 2007. It does not move in a straight line; homes built after 2016 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:01:05.480149 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 25 sales 2007– 2011 14 sales 2012– 2016 23 sales After 2016 21 sales 0.0% 2.0% 4.0% 3.2% 1.7% 3.4% 4.9% Discount from original list, average

The average is 4.9% for homes built after 2016 and 3.2% for homes built before 2007. It does not move in a straight line; homes built after 2016 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

2026-10-26T07:01:05.505992 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% 20 56 52 21 79 50 43 57 57 33 43 71 Before 2007 2007–2011 2012–2016 After 2016

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

  • 33% of homes built after 2016 had a price cut before sale, against 20% of homes built before 2007. Defined in 8.1.7.
  • 43% of homes built after 2016 had the seller pay closing costs or repairs, against 56% of homes built before 2007. Defined in 8.1.8.
  • 71% of homes built after 2016 have a view, against 52% of homes built before 2007. 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 200725 sales2007–201114 sales2012–201623 salesAfter 201621 salesAll83 salesReal difference?
Net sale price average$674,779$692,246$692,205$773,983$707,654unclear
Net price per SF average$227$232$239$265$241✓ large
Living area average3,0543,0192,9082,9672,985unclear
Year built median20052009201320182012by design

5.10 The numbers: selling

Before 200725 sales2007–201114 sales2012–201623 salesAfter 201621 salesAll83 salesReal difference?
Days on market median2317192923unclear
Discount from original list average3.2%1.7%3.4%4.9%3.4%unclear
Price cut before sale20%21%43%33%30%unclear
Seller paid closing costs or repairs56%79%57%43%57%unclear
Has a view52%50%57%71%58%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 · 83 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.

2026-10-26T07:01:05.524507 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 48 33 81 sales Sales per group View: 48 sales (59%) No view: 33 sales (41%)
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$730K$680Kunclear
Net price per SF$244 per SF$235 per SFunclear
Living area3,045 SF2,933 SFunclear
Year built20132009unclear
Days on market21 days32 daysunclear
Discount from original list3.2%3.7%unclear
Price cut before sale29%30%unclear
Seller paid closing costs or repairs65%45%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:01:05.541608 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 48 sales No view 33 sales $0K $200K $400K $600K $800K $730K $680K Net sale price, average

The average is $730K for homes with a view and $680K 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

2026-10-26T07:01:05.560241 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 48 sales No view 33 sales $0 $100 $200 $244 $235 Net price per SF, average

The average is $244 per SF for homes with a view and $235 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

2026-10-26T07:01:05.578408 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 48 sales No view 33 sales 0 1,000 2,000 3,000 3,045 2,933 Living area (SF), average

The average is 3,045 SF for homes with a view and 2,933 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:01:05.625574 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 48 sales No view 33 sales 2005 2008 2011 2014 2017 2013 2009 Year built: median (dot) and middle half (bar)

The median is 2013 for homes with a view and 2009 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:01:05.643661 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 48 sales No view 33 sales 0 10 20 30 21 32 Days on market, median

The median is 21 days for homes with a view and 32 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

2026-10-26T07:01:05.663126 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 48 sales No view 33 sales 0.0% 1.0% 2.0% 3.0% 4.0% 3.2% 3.7% Discount from original list, average

The average is 3.2% for homes with a view and 3.7% 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

2026-10-26T07:01:05.682297 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 29 65 30 45 View No view

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

  • 29% of homes with a view had a price cut before sale, against 30% of homes without a view. Defined in 8.1.7.
  • 65% of homes with a view had the seller pay closing costs or repairs, against 45% 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

View48 salesNo view33 salesAll81 salesReal difference?
Net sale price average$730,137$680,022$709,720unclear
Net price per SF average$244$235$240unclear
Living area average3,0452,9332,999unclear
Year built median201320092012unclear

6.11 The numbers: selling

View48 salesNo view33 salesAll81 salesReal difference?
Days on market median213222unclear
Discount from original list average3.2%3.7%3.4%unclear
Price cut before sale29%30%30%unclear
Seller paid closing costs or repairs65%45%57%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 · 1 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: 1 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 Belterra.
MeasureAverageMedian
Sales1
Net sale price$1,285,000$1,285,000
Net price per SF$321$321
Living area (SF)4,0084,008
Days on market11
Discount from original list2.7%2.7%
Price cut before sale0% of sales
Seller paid closing costs or repairs0% of sales
Year built2026–2026

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
83 resale sales. Average $707,654; median $674,900; standard deviation $150,979; middle half (25th–75th percentile) $616,600–$800,000; lowest $475,077, highest $1,263,625. 47 sales had a seller payment; their median payment was $3,625.

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
83 resale sales. Average $241; median $236; standard deviation $34; middle half (25th–75th percentile) $220–$256; lowest $169, highest $335.

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
83 resale sales. Average 2,985; median 2,924; standard deviation 698; middle half (25th–75th percentile) 2,528–3,443; lowest 1,747, highest 5,085.

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
83 resale sales. Average 2011; median 2012; standard deviation 6; middle half (25th–75th percentile) 2006–2016; lowest 2003, highest 2020.

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
83 resale sales. Average 57; median 23; standard deviation 89; middle half (25th–75th percentile) 12–56; lowest 0, highest 604. 2 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
83 resale sales. Average 3.4%; median 2.1%; standard deviation 5.1%; middle half (25th–75th percentile) 0.6%–5.2%; lowest −7.0%, highest 27.3%. 10 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
25 of 83 resale sales (30.1%).

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
47 of 83 resale sales (56.6%).

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
48 sales with a view, 33 without, 2 unclassified. Most common View entries: Park/Greenbelt 31, Neighborhood 27, None 24, Trees/Woods 21, Hill Country 15, See Remarks 4, Pond 3, Panoramic 2.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “belterra” (case-insensitive). A record is kept when its subdivision name belongs to the Belterra family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 84 closed Belterra records over the prior year, in ZIP 78737. 36 subdivision spellings kept, the most common: Belterra (13); Belterra Ph 4 Sec 13 (8); Belterra Ph Ii Sec 2 (6); BELTERRA (5); Belterra Sec 15 (4); Belterra Sec 20-1 (3); Belterra Ph Ii Sec 9B (3); Belterra Ph 5 Sec 10 (3); Belterra Ph 3 Sec 11A (2); Belterra Ph 4 Sec 12A (2); Belterra Ph 1 Sec 3A (2); Belterra Ph 4 Sec 14 (2); and 24 more (31 records). Names found by the search but not part of Belterra, left out: The Cottages At Belterra Village (6); Belterra- san saba (1); The Cottage At Belterra Village (1); Hudson At Belterra Condo (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 49 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
84 single-family sales in the window: 83 resale, 1 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
83 resale; 1 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 $617K”.
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 $617K: $475,077–$616,200 (21 sales); $617K–$675K: $617,000–$674,900 (21 sales); $682K–$800K: $682,500–$799,900 (19 sales); Over $800K: $800,000–$1,263,625 (22 sales)
Quartiles by living area: Under 2,534 SF: 1,747–2,522 SF (21 sales); 2,534–2,924 SF: 2,534–2,924 SF (21 sales); 2,940–3,434 SF: 2,940–3,434 SF (20 sales); Over 3,434 SF: 3,452–5,085 SF (21 sales)
Quartiles by year built: Before 2007: 2003–2006 (25 sales); 2007–2011: 2007–2011 (14 sales); 2012–2016: 2012–2016 (23 sales); After 2016: 2017–2020 (21 sales)
View and no view: View: MLS lists a view (48 sales); No view: None or Neighborhood (33 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 $707,654, median $674,900. Days on market: average 57, median 23: 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
5 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 = 1.9430.5857p < 0.0063Unclearε² = 0.024small
Living areaKruskal–WallisH = 52.723< 0.0001p < 0.0063Yesε² = 0.643large
Year builtKruskal–WallisH = 8.8630.0312p < 0.0063Unclearε² = 0.108medium
Days on marketKruskal–WallisH = 11.0730.0114p < 0.0063Unclearε² = 0.135medium
Discount from original listKruskal–WallisH = 13.1930.0042p < 0.0063Yesε² = 0.161large
Price cut before saleChi-squareχ² = 6.0330.1100p < 0.0063UnclearCramér’s V = 0.270small
Seller paid closing costs or repairsChi-squareχ² = 0.9930.8029p < 0.0063UnclearCramér’s V = 0.109small
Has a viewChi-squareχ² = 1.8730.6001p < 0.0063UnclearCramér’s V = 0.150small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 50.713< 0.0001p < 0.0063Yesε² = 0.618large
Net price per SFKruskal–WallisH = 12.3730.0062p < 0.0063Yesε² = 0.151large
Year builtKruskal–WallisH = 1.6930.6392p < 0.0063Unclearε² = 0.021small
Days on marketKruskal–WallisH = 9.4930.0235p < 0.0063Unclearε² = 0.116medium
Discount from original listKruskal–WallisH = 7.1330.0678p < 0.0063Unclearε² = 0.087medium
Price cut before saleChi-squareχ² = 3.4730.3253p < 0.0063UnclearCramér’s V = 0.204small
Seller paid closing costs or repairsChi-squareχ² = 1.1930.7550p < 0.0063UnclearCramér’s V = 0.120small
Has a viewChi-squareχ² = 2.9530.3993p < 0.0063UnclearCramér’s V = 0.189small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 4.6030.2033p < 0.0063Unclearε² = 0.056small
Net price per SFKruskal–WallisH = 12.4330.0061p < 0.0063Yesε² = 0.152large
Living areaKruskal–WallisH = 0.4130.9382p < 0.0063Unclearε² = 0.005negligible
Days on marketKruskal–WallisH = 1.0330.7929p < 0.0063Unclearε² = 0.013small
Discount from original listKruskal–WallisH = 2.6330.4514p < 0.0063Unclearε² = 0.032small
Price cut before saleChi-squareχ² = 3.7730.2872p < 0.0063UnclearCramér’s V = 0.213small
Seller paid closing costs or repairsChi-squareχ² = 4.3730.2242p < 0.0063UnclearCramér’s V = 0.229small
Has a viewChi-squareχ² = 2.3130.5108p < 0.0063UnclearCramér’s V = 0.167small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 942.50—0.1494p < 0.0063Unclearrank-biserial r = 0.190small
Net price per SFMann–Whitney UU = 939.00—0.1591p < 0.0063Unclearrank-biserial r = 0.186small
Living areaMann–Whitney UU = 811.00—0.8589p < 0.0063Unclearrank-biserial r = 0.024negligible
Year builtMann–Whitney UU = 978.00—0.0738p < 0.0063Unclearrank-biserial r = 0.235small
Days on marketMann–Whitney UU = 637.50—0.1387p < 0.0063Unclearrank-biserial r = 0.195small
Discount from original listMann–Whitney UU = 745.00—0.6549p < 0.0063Unclearrank-biserial r = 0.059negligible
Price cut before saleChi-squareχ² = 0.0110.9124p < 0.0063UnclearCramér’s V = 0.012negligible
Seller paid closing costs or repairsChi-squareχ² = 2.9210.0877p < 0.0063UnclearCramér’s V = 0.190small

8.4 Data notes

Left out of the analysis: 1 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 83 closed MLS resale sales; the 1 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.