ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Teravista

Georgetown, TX 78626
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 · 7:40 AM CDT
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
40
single-family resale homes
Median net sale price
$407,750
average $443,771
Median net price per SF
$195
average $193
Median days on market
40 days
average 71 days
1. SummaryResale homes · 40 sales · October 26, 2025 – October 25, 2026

This study looks at the 40 resale homes sold in Teravista in the 365 days to October 25, 2026. A full year is used because only 21 resale homes sold in the last 180 days. New construction is left out and shown on its own in section 7. The homes are compared four ways: by price, by living area, by year built and with or without a view. The first three are split into four equal groups (quartiles), each named by its range.

Each comparison has its own section (3–6) with everything about it in one place: the key differences, a table of every measure at a glance, the charts and the numbers.

2. Where the resale homes sold40 resale homes · colored by price range

Each dot is one resale home, colored by its price range. Use the buttons to show one price range at a time. Click a dot for that sale: address, close date, original and last list price, net sale price, living area, net sale per SF and days on market. Scroll or pinch to zoom.

Under $354K · 10 sales$354K–$407K · 10 sales$408K–$487K · 10 salesOver $487K · 10 sales
3. Quartiles by net sale priceResale homes · 40 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.

2026-10-26T07:40:15.275924 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 10 10 40 sales Sales per group Under $354K: 10 sales (25%) $354K–$407K: 10 sales (25%) $408K–$487K: 10 sales (25%) Over $487K: 10 sales (25%)
Bottom line

3.1 Key differences

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

Under $354K$354K–$407K$408K–$487KOver $487K
Higher-priced homes Over $487K
  • Are much larger.
Lower-priced homes Under $354K
  • Are much smaller.

3.2 At a glance

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

Under $354K$354K–$407K$408K–$487KOver $487KReal difference?
Net price per SF$199 per SF$183 per SF$195 per SF$195 per SFunclear
Living area1,711 SFSmallest2,118 SF2,337 SF3,127 SFLargest✓ large
Year built2014201520152016unclear
Days on market38 days75 days24 days93 daysunclear
Discount from original list7.2%8.8%3.4%8.0%unclear
Price cut before sale50%70%30%50%unclear
Seller paid closing costs or repairs70%80%70%70%unclear
Has a view10%30%40%40%unclear

How to read this section. Each heading gives the finding. The gold box says whether the gap is real (✓, with its size) or could be chance (–). The section ends with its numbers; the tests are in section 8.3.

3.3 Net price per SF: no clear difference

2026-10-26T07:40:15.302881 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $407K 10 sales $408K– $487K 10 sales Over $487K 10 sales $0 $100 $200 $199 $183 $195 $195 Net price per SF, average

The average is $195 per SF for homes over $487K and $199 per SF for homes under $354K. It does not move in a straight line; homes under $354K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $487K are about 1,420 SF (83%) larger than homes under $354K

2026-10-26T07:40:15.324108 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $407K 10 sales $408K– $487K 10 sales Over $487K 10 sales 0 1,000 2,000 3,000 1,711 2,118 2,337 3,127 Living area (SF), average

The average is 3,127 SF for homes over $487K and 1,711 SF for homes under $354K. 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

2026-10-26T07:40:15.346573 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $407K 10 sales $408K– $487K 10 sales Over $487K 10 sales 2014 2016 2018 2014 2015 2015 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over $487K and 2014 for homes under $354K. 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

2026-10-26T07:40:15.368467 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $407K 10 sales $408K– $487K 10 sales Over $487K 10 sales 0 50 100 38 75 24 93 Days on market, median

The median is 93 days for homes over $487K and 38 days for homes under $354K. It does not move in a straight line; homes over $487K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:40:15.389638 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $407K 10 sales $408K– $487K 10 sales Over $487K 10 sales 0.0% 5.0% 10.0% 7.2% 8.8% 3.4% 8.0% Discount from original list, average

The average is 8.0% for homes over $487K and 7.2% for homes under $354K. It does not move in a straight line; homes $354K–$407K 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

2026-10-26T07:40:15.418261 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 70 10 70 80 30 30 70 40 50 70 40 Under $354K $354K–$407K $408K–$487K Over $487K

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

  • 50% of homes over $487K had a price cut before sale, against 50% of homes under $354K. Defined in 8.1.7.
  • 70% of homes over $487K had the seller pay closing costs or repairs, against 70% of homes under $354K. Defined in 8.1.8.
  • 40% of homes over $487K have a view, against 10% of homes under $354K. 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 $354K10 sales$354K–$407K10 sales$408K–$487K10 salesOver $487K10 salesAll40 salesReal difference?
Net sale price average$336,597$380,941$453,656$603,891$443,771by design
Net price per SF average$199$183$195$195$193unclear
Living area average1,7112,1182,3373,1272,323✓ large
Year built median20142015201520162015unclear

3.10 The numbers: selling

Under $354K10 sales$354K–$407K10 sales$408K–$487K10 salesOver $487K10 salesAll40 salesReal difference?
Days on market median3875249340unclear
Discount from original list average7.2%8.8%3.4%8.0%6.9%unclear
Price cut before sale50%70%30%50%50%unclear
Seller paid closing costs or repairs70%80%70%70%72%unclear
Has a view10%30%40%40%30%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.1.

4. Quartiles by living areaResale homes · 40 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:40:15.438089 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 10 10 40 sales Sales per group Under 1,951 SF: 10 sales (25%) 1,951–2,238 SF: 10 sales (25%) 2,246–2,607 SF: 10 sales (25%) Over 2,607 SF: 10 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 1,951 SF1,951–2,238 SF2,246–2,607 SFOver 2,607 SF
Larger homes Over 2,607 SF
  • Sell for much more.
Smaller homes Under 1,951 SF
  • Sell for much less.

4.2 At a glance

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

Under 1,951 SF1,951–2,238 SF2,246–2,607 SFOver 2,607 SFReal difference?
Net sale price$339KLowest$403K$460K$573KHighest✓ large
Net price per SF$207 per SF$194 per SF$193 per SF$179 per SFunclear
Year built2014201520162016unclear
Days on market33 days33 days28 days114 daysunclear
Discount from original list4.8%5.7%6.1%10.8%unclear
Price cut before sale40%50%40%70%unclear
Seller paid closing costs or repairs70%70%90%60%unclear
Has a view10%40%30%40%unclear

4.3 Homes over 2,607 SF sell for about $234K (69%) more than homes under 1,951 SF

2026-10-26T07:40:15.457921 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,951 SF 10 sales 1,951– 2,238 SF 10 sales 2,246– 2,607 SF 10 sales Over 2,607 SF 10 sales $0K $200K $400K $600K $339K $403K $460K $573K Net sale price, average

The average is $573K for homes over 2,607 SF and $339K for homes under 1,951 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-26T07:40:15.480047 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,951 SF 10 sales 1,951– 2,238 SF 10 sales 2,246– 2,607 SF 10 sales Over 2,607 SF 10 sales $0 $100 $200 $207 $194 $193 $179 Net price per SF, average

The average is $179 per SF for homes over 2,607 SF and $207 per SF for homes under 1,951 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:40:15.501782 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,951 SF 10 sales 1,951– 2,238 SF 10 sales 2,246– 2,607 SF 10 sales Over 2,607 SF 10 sales 2014 2016 2018 2014 2015 2016 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over 2,607 SF and 2014 for homes under 1,951 SF. It does not move in a straight line; homes 2,246–2,607 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:40:15.523759 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,951 SF 10 sales 1,951– 2,238 SF 10 sales 2,246– 2,607 SF 10 sales Over 2,607 SF 10 sales 0 50 100 33 33 28 114 Days on market, median

The median is 114 days for homes over 2,607 SF and 33 days for homes under 1,951 SF. It does not move in a straight line; homes over 2,607 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:40:15.545023 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,951 SF 10 sales 1,951– 2,238 SF 10 sales 2,246– 2,607 SF 10 sales Over 2,607 SF 10 sales 0.0% 5.0% 10.0% 4.8% 5.7% 6.1% 10.8% Discount from original list, average

The average is 10.8% for homes over 2,607 SF and 4.8% for homes under 1,951 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

2026-10-26T07:40:15.570684 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% 40 70 10 50 70 40 40 90 30 70 60 40 Under 1,951 SF 1,951–2,238 SF 2,246–2,607 SF Over 2,607 SF

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

  • 70% of homes over 2,607 SF had a price cut before sale, against 40% of homes under 1,951 SF. Defined in 8.1.7.
  • 60% of homes over 2,607 SF had the seller pay closing costs or repairs, against 70% of homes under 1,951 SF. Defined in 8.1.8.
  • 40% of homes over 2,607 SF have a view, against 10% of homes under 1,951 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 1,951 SF10 sales1,951–2,238 SF10 sales2,246–2,607 SF10 salesOver 2,607 SF10 salesAll40 salesReal difference?
Net sale price average$339,234$402,702$460,115$573,034$443,771✓ large
Net price per SF average$207$194$193$179$193unclear
Living area average1,6462,0732,3843,1902,323by design
Year built median20142015201620162015unclear

4.10 The numbers: selling

Under 1,951 SF10 sales1,951–2,238 SF10 sales2,246–2,607 SF10 salesOver 2,607 SF10 salesAll40 salesReal difference?
Days on market median33332811440unclear
Discount from original list average4.8%5.7%6.1%10.8%6.9%unclear
Price cut before sale40%50%40%70%50%unclear
Seller paid closing costs or repairs70%70%90%60%72%unclear
Has a view10%40%30%40%30%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.2.

5. Quartiles by year builtResale homes · 40 sales · October 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.

2026-10-26T07:40:15.590433 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 13 10 10 7 40 sales Sales per group Before 2015: 13 sales (32%) 2015: 10 sales (25%) 2016: 10 sales (25%) After 2016: 7 sales (18%)
Bottom line

5.1 Key differences

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

Before 201520152016After 2016
Newer homes After 2016
  • Sell for much more.
  • Are much larger.
Older homes Before 2015
  • Sell for much less.
  • Are much smaller.

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 201520152016After 2016Real difference?
Net sale price$381KLowest$429K$430K$601KHighest✓ large
Net price per SF$192 per SF$184 per SF$200 per SF$198 per SFunclear
Living area2,032 SFSmallest2,360 SF2,161 SF3,042 SFLargest✓ large
Days on market41 days38 days56 days22 daysunclear
Discount from original list6.3%7.2%8.2%5.3%unclear
Price cut before sale54%60%60%14%unclear
Seller paid closing costs or repairs69%80%60%86%unclear
Has a view38%50%20%0%unclear

5.3 Homes built after 2016 sell for about $220K (58%) more than homes built before 2015

2026-10-26T07:40:15.610031 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 13 sales 2015 10 sales 2016 10 sales After 2016 7 sales $0K $200K $400K $600K $381K $429K $430K $601K Net sale price, average

The average is $601K for homes built after 2016 and $381K for homes built before 2015. 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

2026-10-26T07:40:15.632617 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 13 sales 2015 10 sales 2016 10 sales After 2016 7 sales $0 $50 $100 $150 $200 $192 $184 $200 $198 Net price per SF, average

The average is $198 per SF for homes built after 2016 and $192 per SF for homes built before 2015. It does not move in a straight line; homes built 2016 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Homes built after 2016 are about 1,010 SF (50%) larger than homes built before 2015

2026-10-26T07:40:15.653868 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 13 sales 2015 10 sales 2016 10 sales After 2016 7 sales 0 1,000 2,000 3,000 2,032 2,360 2,161 3,042 Living area (SF), average

The average is 3,042 SF for homes built after 2016 and 2,032 SF for homes built before 2015. It does not move in a straight line; homes built after 2016 are highest. Defined in 8.1.3.

✓ Real difference · large

5.6 Days on market: no clear difference

2026-10-26T07:40:15.674392 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 13 sales 2015 10 sales 2016 10 sales After 2016 7 sales 0 20 40 60 41 38 56 22 Days on market, median

The median is 22 days for homes built after 2016 and 41 days for homes built before 2015. It does not move in a straight line; homes built 2016 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:40:15.696894 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 13 sales 2015 10 sales 2016 10 sales After 2016 7 sales 0.0% 2.0% 4.0% 6.0% 8.0% 6.3% 7.2% 8.2% 5.3% Discount from original list, average

The average is 5.3% for homes built after 2016 and 6.3% for homes built before 2015. It does not move in a straight line; homes built 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

2026-10-26T07:40:15.722002 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% 54 69 38 60 80 50 60 60 20 14 86 0 Before 2015 2015 2016 After 2016

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

  • 14% of homes built after 2016 had a price cut before sale, against 54% of homes built before 2015. Defined in 8.1.7.
  • 86% of homes built after 2016 had the seller pay closing costs or repairs, against 69% of homes built before 2015. Defined in 8.1.8.
  • 0% of homes built after 2016 have a view, against 38% of homes built before 2015. 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 201513 sales201510 sales201610 salesAfter 20167 salesAll40 salesReal difference?
Net sale price average$381,428$428,686$429,883$600,942$443,771✓ large
Net price per SF average$192$184$200$198$193unclear
Living area average2,0322,3602,1613,0422,323✓ large
Year built median20142015201620192015by design

5.10 The numbers: selling

Before 201513 sales201510 sales201610 salesAfter 20167 salesAll40 salesReal difference?
Days on market median4138562240unclear
Discount from original list average6.3%7.2%8.2%5.3%6.9%unclear
Price cut before sale54%60%60%14%50%unclear
Seller paid closing costs or repairs69%80%60%86%72%unclear
Has a view38%50%20%0%30%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.3.

6. View and no viewResale homes · 40 sales · October 26, 2025 – October 25, 2026

Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T07:40:15.739518 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 27 39 sales Sales per group View: 12 sales (31%) No view: 27 sales (69%)
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$453K$444Kunclear
Net price per SF$186 per SF$198 per SFunclear
Living area2,452 SF2,269 SFunclear
Year built20152016unclear
Days on market73 days34 daysunclear
Discount from original list6.8%6.3%unclear
Price cut before sale58%44%unclear
Seller paid closing costs or repairs58%78%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:40:15.755256 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 27 sales $0K $200K $400K $453K $444K Net sale price, average

The average is $453K for homes with a view and $444K 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

2026-10-26T07:40:15.773060 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 27 sales $0 $50 $100 $150 $200 $186 $198 Net price per SF, average

The average is $186 per SF for homes with a view and $198 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

2026-10-26T07:40:15.791507 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 27 sales 0 1,000 2,000 2,452 2,269 Living area (SF), average

The average is 2,452 SF for homes with a view and 2,269 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:40:15.830295 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 27 sales 2014 2015 2016 2015 2016 Year built: median (dot) and middle half (bar)

The median is 2015 for homes with a view and 2016 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:40:15.848127 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 27 sales 0 20 40 60 80 73 34 Days on market, median

The median is 73 days for homes with a view and 34 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

2026-10-26T07:40:15.867259 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 27 sales 0.0% 2.0% 4.0% 6.0% 8.0% 6.8% 6.3% Discount from original list, average

The average is 6.8% for homes with a view and 6.3% 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

2026-10-26T07:40:15.885722 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 58 58 44 78 View No view

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

  • 58% of homes with a view had a price cut before sale, against 44% of homes without a view. Defined in 8.1.7.
  • 58% of homes with a view had the seller pay closing costs or repairs, against 78% 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

View12 salesNo view27 salesAll39 salesReal difference?
Net sale price average$452,602$444,166$446,762unclear
Net price per SF average$186$198$194unclear
Living area average2,4522,2692,325unclear
Year built median201520162015unclear

6.11 The numbers: selling

View12 salesNo view27 salesAll39 salesReal difference?
Days on market median733440unclear
Discount from original list average6.8%6.3%6.4%unclear
Price cut before sale58%44%49%unclear
Seller paid closing costs or repairs58%78%72%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 Teravista.
MeasureAverageMedian
Sales1
Net sale price$340,600$340,600
Net price per SF$191$191
Living area (SF)1,7861,786
Days on market1212
Discount from original list2.7%2.7%
Price cut before sale0% of sales
Seller paid closing costs or repairs100% of sales
Year built2014–2014

Same definitions as the rest of the study (section 8). New construction = NewConstructionYN true, or PropertyCondition “New Construction” or “Under Construction”.

8. AppendixMeasures, methods and tests

Each measure and method three ways: in plain words, as statistics, and with the data from this study.

8.1 Measures

8.1.1 Net sale price

In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
40 resale sales. Average $443,771; median $407,750; standard deviation $111,012; middle half (25th–75th percentile) $352,625–$492,370; lowest $313,490, highest $735,000. 29 sales had a seller payment; their median payment was $5,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
40 resale sales. Average $193; median $195; standard deviation $22; middle half (25th–75th percentile) $182–$207; lowest $124, highest $251.

8.1.3 Living area

In simple terms
The heated and cooled space, as listed in the MLS. Garages and porches are not counted.
Statistically
RESO LivingArea, in square feet. Sales under 400 SF are treated as entry errors and left out.
The data
40 resale sales. Average 2,323; median 2,242; standard deviation 598; middle half (25th–75th percentile) 1,929–2,634; lowest 1,573, highest 3,641.

8.1.4 Year built

In simple terms
The year the home was finished, as listed in the MLS. It shows whether a group leans to older or newer phases of the community.
Statistically
RESO YearBuilt; summarized by the median, with the 25th–75th percentile (middle half) on the charts.
The data
40 resale sales. Average 2015; median 2015; standard deviation 2; middle half (25th–75th percentile) 2014–2016; lowest 2011, highest 2019.

8.1.5 Days on market

In simple terms
How many days the home was on the market before the buyer's offer was accepted, counting any earlier listing periods (relists). This is the days on market agents and clients quote.
Statistically
CDOM = max(CumulativeDaysOnMarket, DaysOnMarket, PurchaseContractDate − ListingContractDate). The MLS counter can freeze at a price change, so the contract-date gap is a floor. Summarized by the median, because a few homes that sat for months pull an average up.
The data
40 resale sales. Average 71; median 40; standard deviation 74; middle half (25th–75th percentile) 17–114; lowest 2, highest 314. 0 sales went under contract on their listing date (0 days).

8.1.6 Discount from original list

In simple terms
How far below the first asking price the home sold, after seller payments. It measures how much negotiating room sellers gave up. A negative figure means the home sold above its first asking price.
Statistically
Discount % = (OriginalListPrice − Net) ÷ OriginalListPrice × 100, per sale; summarized by the mean.
The data
40 resale sales. Average 6.9%; median 5.3%; standard deviation 6.5%; middle half (25th–75th percentile) 2.6%–11.2%; lowest −1.0%, highest 24.2%. 1 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
20 of 40 resale sales (50.0%).

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
29 of 40 resale sales (72.5%).

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
12 sales with a view, 27 without, 1 unclassified. Most common View entries: None 20, Neighborhood 10, Park/Greenbelt 9, Pond 2, See Remarks 2, Pool 1, Garden 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Georgetown, SubdivisionName contains any of “teravista”, “teravista secs” (case-insensitive). A record is kept when its subdivision name belongs to the Teravista family, the same rule comparable sales use (it includes Teravista Secs 322B & 323, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 41 closed Teravista records over the prior year, in ZIP 78626. 17 subdivision spellings kept, the most common: Teravista (14); TERAVISTA (4); Teravista Sec 325 (3); Teravista Sec 322A Ph 2 (2); Teravista Sec 313 Ph 2 (2); Teravista Sec 330 (2); Teravista Secs 322B & 323 (2); Teravista Ph 1 Sec 401 (2); Teravista Sec 326 (2); Teravista Sec 322b & 323 (1); Teravista Sec 401 Ph 2 (1); Teravista Ph 1 Sec 313 (1); and 5 more (5 records). Names found by the search but not part of Teravista, left out: TERAVISTA BRIAR GLEN (2); Teravista Sermon 326 (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 21 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
41 single-family sales in the window: 40 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
40 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 $354K”.
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 $354K: $313,490–$350,000 (10 sales); $354K–$407K: $353,500–$407,000 (10 sales); $408K–$487K: $408,500–$487,160 (10 sales); Over $487K: $508,000–$735,000 (10 sales)
Quartiles by living area: Under 1,951 SF: 1,573–1,863 SF (10 sales); 1,951–2,238 SF: 1,951–2,238 SF (10 sales); 2,246–2,607 SF: 2,246–2,607 SF (10 sales); Over 2,607 SF: 2,715–3,641 SF (10 sales)
Quartiles by year built: Before 2015: 2011–2014 (13 sales); 2015: 2015–2015 (10 sales); 2016: 2016–2016 (10 sales); After 2016: 2017–2019 (7 sales)
View and no view: View: MLS lists a view (12 sales); No view: None or Neighborhood (27 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 $443,771, median $407,750. Days on market: average 71, median 40: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

In simple terms
Checks whether a measure really differs across the four groups of a slice. It uses each sale's rank, not its value, so a few extreme sales cannot drive the answer.
Statistically
H = [12/(n(n+1))] Σ Rⱼ²/nⱼ − 3(n+1), compared with χ² on k − 1 degrees of freedom (Kruskal & Wallis, 1952). Effect size ε² = H/(n − 1): ≥ .01 small, ≥ .06 medium, ≥ .14 large (Tomczak & Tomczak, 2014). A slice is tested only when every group has at least 5 sales; smaller groups are described, not tested.
The data
Run on every measure in sections 3–5; each result is in 8.3.

8.2.8 Mann–Whitney U test

In simple terms
The same check when there are only two groups: view against no view.
Statistically
Two-sided U test (Mann & Whitney, 1947). Effect size = rank-biserial correlation |1 − 2U/(n₁n₂)|: ≥ .10 small, ≥ .30 medium, ≥ .50 large (Kerby, 2014; Cohen, 1988).
The data
Run on every measure in section 6; results in 8.3.

8.2.9 Chi-square test

In simple terms
Checks whether a yes/no share (price cut, seller payment, view) differs between groups more than chance would.
Statistically
Pearson χ² on the 2 × k table of counts, no continuity correction (Pearson, 1900). Effect size Cramér's V = √(χ²/n): ≥ .10 small, ≥ .30 medium, ≥ .50 large (Cramér, 1946).
The data
Run on the three shares in every slice; results in 8.3.

8.2.10 Real difference (significance)

In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063; Quartiles by year built: m = 8, threshold p < 0.0063; View and no view: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
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 = 4.1130.2502p < 0.0063Unclearε² = 0.105medium
Living areaKruskal–WallisH = 29.903< 0.0001p < 0.0063Yesε² = 0.767large
Year builtKruskal–WallisH = 10.0030.0186p < 0.0063Unclearε² = 0.256large
Days on marketKruskal–WallisH = 4.0330.2585p < 0.0063Unclearε² = 0.103medium
Discount from original listKruskal–WallisH = 5.5130.1383p < 0.0063Unclearε² = 0.141large
Price cut before saleChi-squareχ² = 3.2030.3618p < 0.0063UnclearCramér’s V = 0.283small
Seller paid closing costs or repairsChi-squareχ² = 0.3830.9451p < 0.0063UnclearCramér’s V = 0.097negligible
Has a viewChi-squareχ² = 2.8630.4142p < 0.0063UnclearCramér’s V = 0.267small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 26.703< 0.0001p < 0.0063Yesε² = 0.685large
Net price per SFKruskal–WallisH = 9.9730.0188p < 0.0063Unclearε² = 0.256large
Year builtKruskal–WallisH = 9.9930.0186p < 0.0063Unclearε² = 0.256large
Days on marketKruskal–WallisH = 5.8330.1203p < 0.0063Unclearε² = 0.149large
Discount from original listKruskal–WallisH = 5.3630.1472p < 0.0063Unclearε² = 0.137medium
Price cut before saleChi-squareχ² = 2.4030.4936p < 0.0063UnclearCramér’s V = 0.245small
Seller paid closing costs or repairsChi-squareχ² = 2.3830.4969p < 0.0063UnclearCramér’s V = 0.244small
Has a viewChi-squareχ² = 2.8630.4142p < 0.0063UnclearCramér’s V = 0.267small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 14.0830.0028p < 0.0063Yesε² = 0.361large
Net price per SFKruskal–WallisH = 3.1630.3679p < 0.0063Unclearε² = 0.081medium
Living areaKruskal–WallisH = 12.5730.0057p < 0.0063Yesε² = 0.322large
Days on marketKruskal–WallisH = 1.2330.7447p < 0.0063Unclearε² = 0.032small
Discount from original listKruskal–WallisH = 1.2730.7367p < 0.0063Unclearε² = 0.033small
Price cut before saleChi-squareχ² = 4.4530.2169p < 0.0063UnclearCramér’s V = 0.333medium
Seller paid closing costs or repairsChi-squareχ² = 1.7530.6262p < 0.0063UnclearCramér’s V = 0.209small
Has a viewChi-squareχ² = 5.8230.1205p < 0.0063UnclearCramér’s V = 0.382medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 194.00—0.3378p < 0.0063Unclearrank-biserial r = 0.198small
Net price per SFMann–Whitney UU = 85.00—0.0199p < 0.0063Unclearrank-biserial r = 0.475medium
Living areaMann–Whitney UU = 196.00—0.3080p < 0.0063Unclearrank-biserial r = 0.210small
Year builtMann–Whitney UU = 100.00—0.0562p < 0.0063Unclearrank-biserial r = 0.383medium
Days on marketMann–Whitney UU = 206.50—0.1805p < 0.0063Unclearrank-biserial r = 0.275small
Discount from original listMann–Whitney UU = 191.50—0.3775p < 0.0063Unclearrank-biserial r = 0.182small
Price cut before saleChi-squareχ² = 0.6410.4232p < 0.0063UnclearCramér’s V = 0.128small
Seller paid closing costs or repairsChi-squareχ² = 1.5510.2130p < 0.0063UnclearCramér’s V = 0.199small

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 40 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.