ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Teravista

Round Rock, TX 78665
Resale homes · closed Oct 30 – Oct 29, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 30, 2026 · 6:57 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
64
single-family resale homes
Median net sale price
$468,532
average $507,713
Median net price per SF
$183
average $184
Median days on market
30 days
average 75 days
1. SummaryResale homes · 64 sales · October 30, 2025 – October 29, 2026

This study looks at the 64 resale homes sold in Teravista in the 365 days to October 29, 2026. A full year is used because only 26 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 sold64 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 $395K · 16 sales$395K–$462K · 16 sales$475K–$583K · 16 salesOver $583K · 16 sales
3. Quartiles by net sale priceResale homes · 64 sales · October 30, 2025 – October 29, 2026

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

2026-10-30T06:57:17.592158 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 16 16 16 16 64 sales Sales per group Under $395K: 16 sales (25%) $395K–$462K: 16 sales (25%) $475K–$583K: 16 sales (25%) Over $583K: 16 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 $395K$395K–$462K$475K–$583KOver $583K
Higher-priced homes Over $583K
  • Are much larger.
  • Tend to be newer.
Lower-priced homes Under $395K
  • Are much smaller.
  • Tend to be older.

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 $395K$395K–$462K$475K–$583KOver $583KReal difference?
Net price per SF$188 per SF$180 per SF$175 per SF$194 per SFunclear
Living area2,013 SFSmallest2,476 SF3,001 SF3,732 SFLargest✓ large
Year built2005Oldest200820082012Newest✓ large
Days on market61 days54 days25 days21 daysunclear
Discount from original list7.3%5.6%7.0%6.0%unclear
Price cut before sale50%44%50%38%unclear
Seller paid closing costs or repairs62%69%62%62%unclear
Has a view25%25%38%62%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

2026-10-30T06:57:17.621583 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $395K 16 sales $395K– $462K 16 sales $475K– $583K 16 sales Over $583K 16 sales $0 $100 $200 $188 $180 $175 $194 Net price per SF, average

The average is $194 per SF for homes over $583K and $188 per SF for homes under $395K. It does not move in a straight line; homes over $583K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $583K are about 1,720 SF (85%) larger than homes under $395K

2026-10-30T06:57:17.644251 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $395K 16 sales $395K– $462K 16 sales $475K– $583K 16 sales Over $583K 16 sales 0 2,000 4,000 2,013 2,476 3,001 3,732 Living area (SF), average

The average is 3,732 SF for homes over $583K and 2,013 SF for homes under $395K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Homes over $583K are about 6 years newer than homes under $395K

2026-10-30T06:57:17.666965 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $395K 16 sales $395K– $462K 16 sales $475K– $583K 16 sales Over $583K 16 sales 2005 2008 2011 2005 2008 2008 2012 Year built: median (dot) and middle half (bar)

The median is 2012 for homes over $583K and 2005 for homes under $395K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

✓ Real difference · large

3.6 Days on market: no clear difference

2026-10-30T06:57:17.689544 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $395K 16 sales $395K– $462K 16 sales $475K– $583K 16 sales Over $583K 16 sales 0 20 40 60 61 54 25 21 Days on market, median

The median is 21 days for homes over $583K and 61 days for homes under $395K. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-30T06:57:17.712456 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $395K 16 sales $395K– $462K 16 sales $475K– $583K 16 sales Over $583K 16 sales 0.0% 2.5% 5.0% 7.5% 7.3% 5.6% 7.0% 6.0% Discount from original list, average

The average is 6.0% for homes over $583K and 7.3% for homes under $395K. It does not move in a straight line; homes under $395K are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-30T06:57:17.743941 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% 50 62 25 44 69 25 50 62 38 38 62 62 Under $395K $395K–$462K $475K–$583K Over $583K

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

  • 38% of homes over $583K had a price cut before sale, against 50% of homes under $395K. Defined in 8.1.7.
  • 62% of homes over $583K had the seller pay closing costs or repairs, against 62% of homes under $395K. Defined in 8.1.8.
  • 62% of homes over $583K have a view, against 25% of homes under $395K. 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 $395K16 sales$395K–$462K16 sales$475K–$583K16 salesOver $583K16 salesAll64 salesReal difference?
Net sale price average$365,829$432,857$517,520$714,646$507,713by design
Net price per SF average$188$180$175$194$184unclear
Living area average2,0132,4763,0013,7322,805✓ large
Year built median20052008200820122008✓ large

3.10 The numbers: selling

Under $395K16 sales$395K–$462K16 sales$475K–$583K16 salesOver $583K16 salesAll64 salesReal difference?
Days on market median6154252130unclear
Discount from original list average7.3%5.6%7.0%6.0%6.5%unclear
Price cut before sale50%44%50%38%45%unclear
Seller paid closing costs or repairs62%69%62%62%64%unclear
Has a view25%25%38%62%38%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 · 64 sales · October 30, 2025 – October 29, 2026

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

2026-10-30T06:57:17.765578 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 16 16 16 16 64 sales Sales per group Under 2,274 SF: 16 sales (25%) 2,274–2,708 SF: 16 sales (25%) 2,740–3,252 SF: 16 sales (25%) Over 3,252 SF: 16 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 2,274 SF2,274–2,708 SF2,740–3,252 SFOver 3,252 SF
Larger homes Over 3,252 SF
  • Sell for much more.
  • Sell for less per square foot.
Smaller homes Under 2,274 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 2,274 SF2,274–2,708 SF2,740–3,252 SFOver 3,252 SFReal difference?
Net sale price$385KLowest$446K$498K$702KHighest✓ large
Net price per SF$211 per SFHighest$179 per SF$168 per SFLowest$179 per SF✓ large
Year built2006200820072011unclear
Days on market38 days58 days36 days26 daysunclear
Discount from original list4.2%6.7%7.1%8.0%unclear
Price cut before sale44%50%44%44%unclear
Seller paid closing costs or repairs56%69%62%69%unclear
Has a view38%19%50%44%unclear

4.3 Homes over 3,252 SF sell for about $317K (82%) more than homes under 2,274 SF

2026-10-30T06:57:17.786945 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,274 SF 16 sales 2,274– 2,708 SF 16 sales 2,740– 3,252 SF 16 sales Over 3,252 SF 16 sales $0K $250K $500K $750K $385K $446K $498K $702K Net sale price, average

The average is $702K for homes over 3,252 SF and $385K for homes under 2,274 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 3,252 SF sell for about $32 per SF (15%) less than homes under 2,274 SF

2026-10-30T06:57:17.810262 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,274 SF 16 sales 2,274– 2,708 SF 16 sales 2,740– 3,252 SF 16 sales Over 3,252 SF 16 sales $0 $100 $200 $211 $179 $168 $179 Net price per SF, average

The average is $179 per SF for homes over 3,252 SF and $211 per SF for homes under 2,274 SF. It does not move in a straight line; homes under 2,274 SF are highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-10-30T06:57:17.832739 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,274 SF 16 sales 2,274– 2,708 SF 16 sales 2,740– 3,252 SF 16 sales Over 3,252 SF 16 sales 2005 2008 2011 2006 2008 2007 2011 Year built: median (dot) and middle half (bar)

The median is 2011 for homes over 3,252 SF and 2006 for homes under 2,274 SF. It does not move in a straight line; homes over 3,252 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-30T06:57:17.855416 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,274 SF 16 sales 2,274– 2,708 SF 16 sales 2,740– 3,252 SF 16 sales Over 3,252 SF 16 sales 0 20 40 60 38 58 36 26 Days on market, median

The median is 26 days for homes over 3,252 SF and 38 days for homes under 2,274 SF. It does not move in a straight line; homes 2,274–2,708 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-30T06:57:17.879058 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,274 SF 16 sales 2,274– 2,708 SF 16 sales 2,740– 3,252 SF 16 sales Over 3,252 SF 16 sales 0.0% 2.5% 5.0% 7.5% 4.2% 6.7% 7.1% 8.0% Discount from original list, average

The average is 8.0% for homes over 3,252 SF and 4.2% for homes under 2,274 SF. It rises 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

2026-10-30T06:57:17.906064 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% 44 56 38 50 69 19 44 62 50 44 69 44 Under 2,274 SF 2,274–2,708 SF 2,740–3,252 SF Over 3,252 SF

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

  • 44% of homes over 3,252 SF had a price cut before sale, against 44% of homes under 2,274 SF. Defined in 8.1.7.
  • 69% of homes over 3,252 SF had the seller pay closing costs or repairs, against 56% of homes under 2,274 SF. Defined in 8.1.8.
  • 44% of homes over 3,252 SF have a view, against 38% of homes under 2,274 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 2,274 SF16 sales2,274–2,708 SF16 sales2,740–3,252 SF16 salesOver 3,252 SF16 salesAll64 salesReal difference?
Net sale price average$384,922$446,024$498,102$701,805$507,713✓ large
Net price per SF average$211$179$168$179$184✓ large
Living area average1,8382,4952,9713,9182,805by design
Year built median20062008200720112008unclear

4.10 The numbers: selling

Under 2,274 SF16 sales2,274–2,708 SF16 sales2,740–3,252 SF16 salesOver 3,252 SF16 salesAll64 salesReal difference?
Days on market median3858362630unclear
Discount from original list average4.2%6.7%7.1%8.0%6.5%unclear
Price cut before sale44%50%44%44%45%unclear
Seller paid closing costs or repairs56%69%62%69%64%unclear
Has a view38%19%50%44%38%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 · 64 sales · October 30, 2025 – October 29, 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.

2026-10-30T06:57:17.926888 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 15 17 13 19 64 sales Sales per group Before 2005: 15 sales (23%) 2005–2007: 17 sales (27%) 2008–2010: 13 sales (20%) After 2010: 19 sales (30%)
Bottom line

5.1 Key differences

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

Before 20052005–20072008–2010After 2010
Newer homes After 2010
  • Sell for much more.
Older homes Before 2005
  • Sell for much less.

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 20052005–20072008–2010After 2010Real difference?
Net sale price$414KLowest$453K$492K$641KHighest✓ large
Net price per SF$182 per SF$170 per SF$184 per SF$198 per SFunclear
Living area2,330 SF2,773 SF2,713 SF3,272 SFunclear
Days on market42 days29 days54 days17 daysunclear
Discount from original list4.5%8.6%6.8%5.8%unclear
Price cut before sale33%47%54%47%unclear
Seller paid closing costs or repairs53%65%62%74%unclear
Has a view33%29%31%53%unclear

5.3 Homes built after 2010 sell for about $228K (55%) more than homes built before 2005

2026-10-30T06:57:17.948254 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 15 sales 2005– 2007 17 sales 2008– 2010 13 sales After 2010 19 sales $0K $200K $400K $600K $414K $453K $492K $641K Net sale price, average

The average is $641K for homes built after 2010 and $414K for homes built before 2005. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

5.4 Net price per SF: no clear difference

2026-10-30T06:57:17.971989 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 15 sales 2005– 2007 17 sales 2008– 2010 13 sales After 2010 19 sales $0 $100 $200 $182 $170 $184 $198 Net price per SF, average

The average is $198 per SF for homes built after 2010 and $182 per SF for homes built before 2005. It does not move in a straight line; homes built after 2010 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-30T06:57:17.994441 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 15 sales 2005– 2007 17 sales 2008– 2010 13 sales After 2010 19 sales 0 1,000 2,000 3,000 2,330 2,773 2,713 3,272 Living area (SF), average

The average is 3,272 SF for homes built after 2010 and 2,330 SF for homes built before 2005. It does not move in a straight line; homes built after 2010 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-30T06:57:18.016630 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 15 sales 2005– 2007 17 sales 2008– 2010 13 sales After 2010 19 sales 0 20 40 60 42 29 54 17 Days on market, median

The median is 17 days for homes built after 2010 and 42 days for homes built before 2005. It does not move in a straight line; homes built 2008–2010 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-30T06:57:18.040449 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 15 sales 2005– 2007 17 sales 2008– 2010 13 sales After 2010 19 sales 0.0% 5.0% 10.0% 4.5% 8.6% 6.8% 5.8% Discount from original list, average

The average is 5.8% for homes built after 2010 and 4.5% for homes built before 2005. It does not move in a straight line; homes built 2005–2007 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

2026-10-30T06:57:18.066729 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% 33 53 33 47 65 29 54 62 31 47 74 53 Before 2005 2005–2007 2008–2010 After 2010

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

  • 47% of homes built after 2010 had a price cut before sale, against 33% of homes built before 2005. Defined in 8.1.7.
  • 74% of homes built after 2010 had the seller pay closing costs or repairs, against 53% of homes built before 2005. Defined in 8.1.8.
  • 53% of homes built after 2010 have a view, against 33% of homes built before 2005. 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 200515 sales2005–200717 sales2008–201013 salesAfter 201019 salesAll64 salesReal difference?
Net sale price average$413,731$453,222$492,024$641,399$507,713✓ large
Net price per SF average$182$170$184$198$184unclear
Living area average2,3302,7732,7133,2722,805unclear
Year built median20032006200920122008by design

5.10 The numbers: selling

Before 200515 sales2005–200717 sales2008–201013 salesAfter 201019 salesAll64 salesReal difference?
Days on market median4229541730unclear
Discount from original list average4.5%8.6%6.8%5.8%6.5%unclear
Price cut before sale33%47%54%47%45%unclear
Seller paid closing costs or repairs53%65%62%74%64%unclear
Has a view33%29%31%53%38%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 · 64 sales · October 30, 2025 – October 29, 2026

Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood. 3 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-30T06:57:18.086603 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 24 37 61 sales Sales per group View: 24 sales (39%) No view: 37 sales (61%)
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$563K$472Kunclear
Net price per SF$194 per SF$179 per SFunclear
Living area2,965 SF2,692 SFunclear
Year built20082007unclear
Days on market22 days33 daysunclear
Discount from original list5.9%6.7%unclear
Price cut before sale46%43%unclear
Seller paid closing costs or repairs54%68%unclear

6.3 Net sale price: no clear difference

2026-10-30T06:57:18.102935 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 37 sales $0K $200K $400K $600K $563K $472K Net sale price, average

The average is $563K for homes with a view and $472K 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

2026-10-30T06:57:18.122751 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 37 sales $0 $50 $100 $150 $200 $194 $179 Net price per SF, average

The average is $194 per SF for homes with a view and $179 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

2026-10-30T06:57:18.141691 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 37 sales 0 1,000 2,000 3,000 2,965 2,692 Living area (SF), average

The average is 2,965 SF for homes with a view and 2,692 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-30T06:57:18.225255 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 37 sales 2004 2006 2008 2010 2012 2008 2007 Year built: median (dot) and middle half (bar)

The median is 2008 for homes with a view and 2007 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-30T06:57:18.243720 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 37 sales 0 10 20 30 22 33 Days on market, median

The median is 22 days for homes with a view and 33 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

2026-10-30T06:57:18.263512 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 37 sales 0.0% 2.0% 4.0% 6.0% 8.0% 5.9% 6.7% Discount from original list, average

The average is 5.9% for homes with a view and 6.7% 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

2026-10-30T06:57:18.282832 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 46 54 43 68 View No view

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

  • 46% of homes with a view had a price cut before sale, against 43% of homes without a view. Defined in 8.1.7.
  • 54% 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

View24 salesNo view37 salesAll61 salesReal difference?
Net sale price average$563,326$471,716$507,759unclear
Net price per SF average$194$179$185unclear
Living area average2,9652,6922,799unclear
Year built median200820072007unclear

6.11 The numbers: selling

View24 salesNo view37 salesAll61 salesReal difference?
Days on market median223329unclear
Discount from original list average5.9%6.7%6.4%unclear
Price cut before sale46%43%44%unclear
Seller paid closing costs or repairs54%68%62%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 30, 2025 – October 29, 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 Teravista.

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
64 resale sales. Average $507,713; median $468,532; standard deviation $148,632; middle half (25th–75th percentile) $394,500–$584,741; lowest $307,838, highest $967,389. 41 sales had a seller payment; their median payment was $9,000.

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
64 resale sales. Average $184; median $183; standard deviation $29; middle half (25th–75th percentile) $162–$210; lowest $125, highest $247.

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
64 resale sales. Average 2,805; median 2,724; standard deviation 823; middle half (25th–75th percentile) 2,266–3,274; lowest 1,397, highest 4,768.

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
64 resale sales. Average 2008; median 2008; standard deviation 4; middle half (25th–75th percentile) 2005–2011; lowest 2002, highest 2017.

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
64 resale sales. Average 75; median 30; standard deviation 109; middle half (25th–75th percentile) 10–98; lowest 2, highest 611. 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
64 resale sales. Average 6.5%; median 5.5%; standard deviation 5.9%; middle half (25th–75th percentile) 1.6%–9.7%; lowest −1.9%, highest 32.7%. 2 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
29 of 64 resale sales (45.3%).

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
41 of 64 resale sales (64.1%).

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
24 sales with a view, 37 without, 3 unclassified. Most common View entries: None 28, Neighborhood 19, Golf Course 11, Park/Greenbelt 8, See Remarks 4, Trees/Woods 3, Panoramic 3, Pool 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 = Round Rock, SubdivisionName contains any of “teravista” (case-insensitive). A record is kept when its subdivision name belongs to the Teravista family, the same rule comparable sales use.
The data
Pulled October 30, 2026: 66 closed Teravista records over the prior year, in ZIP 78665. 24 subdivision spellings kept, the most common: Teravista (16); Teravista Sec 08 (7); Teravista Sec 21 (6); Teravista Sec 07 (5); Teravista Sec 13B (5); Teravista Sec 14B (4); Teravista Sec 15b (2); Teravista Sec 12 Amd (2); Teravista Sec 10A (2); Teravista Sec 16A (2); Teravista Sec 09 (2); Teravista Sec 16B (1); and 12 more (12 records). Names found by the search but not part of Teravista, left out: Rd Only Teravista Sec 12 Amd (2).

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 26 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 30, 2025 to October 29, 2026 inclusive.
The data
64 single-family sales in the window: 64 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
64 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
1 sale(s) other than single-family homes (condo, townhome and similar); 1 sale(s) with concessions above 10% of price

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 $395K”.
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 $395K: $307,838–$393,000 (16 sales); $395K–$462K: $395,000–$462,250 (16 sales); $475K–$583K: $474,815–$583,000 (16 sales); Over $583K: $589,965–$967,389 (16 sales)
Quartiles by living area: Under 2,274 SF: 1,397–2,240 SF (16 sales); 2,274–2,708 SF: 2,274–2,708 SF (16 sales); 2,740–3,252 SF: 2,740–3,252 SF (16 sales); Over 3,252 SF: 3,342–4,768 SF (16 sales)
Quartiles by year built: Before 2005: 2002–2004 (15 sales); 2005–2007: 2005–2007 (17 sales); 2008–2010: 2008–2010 (13 sales); After 2010: 2011–2017 (19 sales)
View and no view: View: MLS lists a view (24 sales); No view: None or Neighborhood (37 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 $507,713, median $468,532. Days on market: average 75, median 30: 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 = 4.4130.2207p < 0.0063Unclearε² = 0.070medium
Living areaKruskal–WallisH = 40.313< 0.0001p < 0.0063Yesε² = 0.640large
Year builtKruskal–WallisH = 22.773< 0.0001p < 0.0063Yesε² = 0.362large
Days on marketKruskal–WallisH = 2.7330.4354p < 0.0063Unclearε² = 0.043small
Discount from original listKruskal–WallisH = 1.2730.7371p < 0.0063Unclearε² = 0.020small
Price cut before saleChi-squareχ² = 0.6930.8747p < 0.0063UnclearCramér’s V = 0.104small
Seller paid closing costs or repairsChi-squareχ² = 0.2030.9770p < 0.0063UnclearCramér’s V = 0.056negligible
Has a viewChi-squareχ² = 6.4030.0937p < 0.0063UnclearCramér’s V = 0.316medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 42.833< 0.0001p < 0.0063Yesε² = 0.680large
Net price per SFKruskal–WallisH = 19.3030.0002p < 0.0063Yesε² = 0.306large
Year builtKruskal–WallisH = 11.8930.0078p < 0.0063Unclearε² = 0.189large
Days on marketKruskal–WallisH = 1.1930.7553p < 0.0063Unclearε² = 0.019small
Discount from original listKruskal–WallisH = 4.5230.2103p < 0.0063Unclearε² = 0.072medium
Price cut before saleChi-squareχ² = 0.1930.9793p < 0.0063UnclearCramér’s V = 0.054negligible
Seller paid closing costs or repairsChi-squareχ² = 0.7530.8622p < 0.0063UnclearCramér’s V = 0.108small
Has a viewChi-squareχ² = 3.7330.2917p < 0.0063UnclearCramér’s V = 0.242small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 22.903< 0.0001p < 0.0063Yesε² = 0.363large
Net price per SFKruskal–WallisH = 8.8130.0319p < 0.0063Unclearε² = 0.140medium
Living areaKruskal–WallisH = 9.5030.0234p < 0.0063Unclearε² = 0.151large
Days on marketKruskal–WallisH = 4.3430.2271p < 0.0063Unclearε² = 0.069medium
Discount from original listKruskal–WallisH = 4.5530.2077p < 0.0063Unclearε² = 0.072medium
Price cut before saleChi-squareχ² = 1.3030.7282p < 0.0063UnclearCramér’s V = 0.143small
Seller paid closing costs or repairsChi-squareχ² = 1.5530.6701p < 0.0063UnclearCramér’s V = 0.156small
Has a viewChi-squareχ² = 2.6930.4414p < 0.0063UnclearCramér’s V = 0.205small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 591.00—0.0305p < 0.0063Unclearrank-biserial r = 0.331medium
Net price per SFMann–Whitney UU = 582.00—0.0424p < 0.0063Unclearrank-biserial r = 0.311medium
Living areaMann–Whitney UU = 520.00—0.2650p < 0.0063Unclearrank-biserial r = 0.171small
Year builtMann–Whitney UU = 540.50—0.1548p < 0.0063Unclearrank-biserial r = 0.217small
Days on marketMann–Whitney UU = 350.50—0.1697p < 0.0063Unclearrank-biserial r = 0.211small
Discount from original listMann–Whitney UU = 425.00—0.7848p < 0.0063Unclearrank-biserial r = 0.043negligible
Price cut before saleChi-squareχ² = 0.0410.8423p < 0.0063UnclearCramér’s V = 0.025negligible
Seller paid closing costs or repairsChi-squareχ² = 1.1110.2914p < 0.0063UnclearCramér’s V = 0.135small

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 1 sale(s) other than single-family homes (condo, townhome and similar); 1 sale(s) with concessions above 10% of price. 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 64 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 30, 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.