ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Blanco Vista

San Marcos, TX 78666
Resale homes · closed Nov 1 – Oct 31, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 1, 2026 · 7:05 AM CST
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
22
single-family resale homes
Median net sale price
$261,250
average $275,705
Median net price per SF
$181
average $173
Median days on market
78 days
average 142 days
1. SummaryResale homes · 22 sales · November 1, 2025 – October 31, 2026

This study looks at the 22 resale homes sold in Blanco Vista in the 365 days to October 31, 2026. A full year is used because only 11 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 sold22 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 $233K · 6 sales$233K–$260K · 5 sales$262K–$300K · 5 salesOver $300K · 6 sales
3. Quartiles by net sale priceResale homes · 22 sales · November 1, 2025 – October 31, 2026

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

2026-11-01T07:05:59.216858 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 5 5 6 22 sales Sales per group Under $233K: 6 sales (27%) $233K–$260K: 5 sales (23%) $262K–$300K: 5 sales (23%) Over $300K: 6 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 $233K$233K–$260K$262K–$300KOver $300K
Higher-priced homes Over $300K
  • Are much larger.
Lower-priced homes Under $233K
  • 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 $233K$233K–$260K$262K–$300KOver $300KReal difference?
Net price per SF$177 per SF$181 per SF$176 per SF$158 per SFunclear
Living area1,217 SFSmallest1,337 SF1,634 SF2,348 SFLargest✓ large
Year built2016201620192016unclear
Days on market48 days111 days177 days124 daysunclear
Discount from original list7.4%8.5%8.8%9.6%unclear
Price cut before sale67%60%60%83%unclear
Seller paid closing costs or repairs50%80%60%67%unclear
Has a view17%0%0%67%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

2026-11-01T07:05:59.246100 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $233K 6 sales $233K– $260K 5 sales $262K– $300K 5 sales Over $300K 6 sales $0 $100 $200 $177 $181 $176 $158 Net price per SF, average

The average is $158 per SF for homes over $300K and $177 per SF for homes under $233K. It does not move in a straight line; homes $233K–$260K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $300K are about 1,130 SF (93%) larger than homes under $233K

2026-11-01T07:05:59.269164 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $233K 6 sales $233K– $260K 5 sales $262K– $300K 5 sales Over $300K 6 sales 0 1,000 2,000 1,217 1,337 1,634 2,348 Living area (SF), average

The average is 2,348 SF for homes over $300K and 1,217 SF for homes under $233K. 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

2026-11-01T07:05:59.293767 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $233K 6 sales $233K– $260K 5 sales $262K– $300K 5 sales Over $300K 6 sales 2008 2011 2014 2017 2020 2016 2016 2019 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over $300K and 2016 for homes under $233K. It does not move in a straight line; homes $262K–$300K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-01T07:05:59.318000 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $233K 6 sales $233K– $260K 5 sales $262K– $300K 5 sales Over $300K 6 sales 0 100 200 48 111 177 124 Days on market, median

The median is 124 days for homes over $300K and 48 days for homes under $233K. It does not move in a straight line; homes $262K–$300K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-01T07:05:59.339864 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $233K 6 sales $233K– $260K 5 sales $262K– $300K 5 sales Over $300K 6 sales 0.0% 5.0% 10.0% 7.4% 8.5% 8.8% 9.6% Discount from original list, average

The average is 9.6% for homes over $300K and 7.4% for homes under $233K. It rises step by step from the lowest range to the highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-01T07:05:59.369913 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% 67 50 17 60 80 0 60 60 0 83 67 67 Under $233K $233K–$260K $262K–$300K Over $300K

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

  • 83% of homes over $300K had a price cut before sale, against 67% of homes under $233K. Defined in 8.1.7.
  • 67% of homes over $300K had the seller pay closing costs or repairs, against 50% of homes under $233K. Defined in 8.1.8.
  • 67% of homes over $300K have a view, against 17% of homes under $233K. 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 $233K6 sales$233K–$260K5 sales$262K–$300K5 salesOver $300K6 salesAll22 salesReal difference?
Net sale price average$211,923$241,673$277,300$366,517$275,705by design
Net price per SF average$177$181$176$158$173unclear
Living area average1,2171,3371,6342,3481,648✓ large
Year built median20162016201920162016unclear

3.10 The numbers: selling

Under $233K6 sales$233K–$260K5 sales$262K–$300K5 salesOver $300K6 salesAll22 salesReal difference?
Days on market median4811117712478unclear
Discount from original list average7.4%8.5%8.8%9.6%8.6%unclear
Price cut before sale67%60%60%83%68%unclear
Seller paid closing costs or repairs50%80%60%67%64%unclear
Has a view17%0%0%67%23%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 · 22 sales · November 1, 2025 – October 31, 2026

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

2026-11-01T07:05:59.390577 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 5 5 6 22 sales Sales per group Under 1,301 SF: 6 sales (27%) 1,301–1,420 SF: 5 sales (23%) 1,424–1,841 SF: 5 sales (23%) Over 1,841 SF: 6 sales (27%)
Bottom line

4.1 Key differences

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

Under 1,301 SF1,301–1,420 SF1,424–1,841 SFOver 1,841 SF
Larger homes Over 1,841 SF
  • Sell for much more.
Smaller homes Under 1,301 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 1,301 SF1,301–1,420 SF1,424–1,841 SFOver 1,841 SFReal difference?
Net sale price$218KLowest$253K$268K$358KHighest✓ large
Net price per SF$189 per SF$183 per SF$173 per SF$147 per SFunclear
Year built2016201820142016unclear
Days on market55 days148 days67 days180 daysunclear
Discount from original list5.3%6.5%7.8%14.1%unclear
Price cut before sale33%60%80%100%unclear
Seller paid closing costs or repairs67%60%60%67%unclear
Has a view17%0%20%50%unclear

4.3 Homes over 1,841 SF sell for about $140K (65%) more than homes under 1,301 SF

2026-11-01T07:05:59.411410 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,301 SF 6 sales 1,301– 1,420 SF 5 sales 1,424– 1,841 SF 5 sales Over 1,841 SF 6 sales $0K $200K $400K $218K $253K $268K $358K Net sale price, average

The average is $358K for homes over 1,841 SF and $218K for homes under 1,301 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

2026-11-01T07:05:59.434069 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,301 SF 6 sales 1,301– 1,420 SF 5 sales 1,424– 1,841 SF 5 sales Over 1,841 SF 6 sales $0 $100 $200 $189 $183 $173 $147 Net price per SF, average

The average is $147 per SF for homes over 1,841 SF and $189 per SF for homes under 1,301 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

2026-11-01T07:05:59.457683 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,301 SF 6 sales 1,301– 1,420 SF 5 sales 1,424– 1,841 SF 5 sales Over 1,841 SF 6 sales 2011 2014 2017 2020 2016 2018 2014 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over 1,841 SF and 2016 for homes under 1,301 SF. It does not move in a straight line; homes 1,301–1,420 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-01T07:05:59.480722 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,301 SF 6 sales 1,301– 1,420 SF 5 sales 1,424– 1,841 SF 5 sales Over 1,841 SF 6 sales 0 100 200 55 148 67 180 Days on market, median

The median is 180 days for homes over 1,841 SF and 55 days for homes under 1,301 SF. It does not move in a straight line; homes over 1,841 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-01T07:05:59.502440 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,301 SF 6 sales 1,301– 1,420 SF 5 sales 1,424– 1,841 SF 5 sales Over 1,841 SF 6 sales 0.0% 5.0% 10.0% 15.0% 5.3% 6.5% 7.8% 14.1% Discount from original list, average

The average is 14.1% for homes over 1,841 SF and 5.3% for homes under 1,301 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

2026-11-01T07:05:59.528581 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 67 17 60 60 0 80 60 20 100 67 50 Under 1,301 SF 1,301–1,420 SF 1,424–1,841 SF Over 1,841 SF

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

  • 100% of homes over 1,841 SF had a price cut before sale, against 33% of homes under 1,301 SF. Defined in 8.1.7.
  • 67% of homes over 1,841 SF had the seller pay closing costs or repairs, against 67% of homes under 1,301 SF. Defined in 8.1.8.
  • 50% of homes over 1,841 SF have a view, against 17% of homes under 1,301 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 1,301 SF6 sales1,301–1,420 SF5 sales1,424–1,841 SF5 salesOver 1,841 SF6 salesAll22 salesReal difference?
Net sale price average$217,784$253,380$268,460$358,267$275,705✓ large
Net price per SF average$189$183$173$147$173unclear
Living area average1,1551,3821,5502,4441,648by design
Year built median20162018201420162016unclear

4.10 The numbers: selling

Under 1,301 SF6 sales1,301–1,420 SF5 sales1,424–1,841 SF5 salesOver 1,841 SF6 salesAll22 salesReal difference?
Days on market median551486718078unclear
Discount from original list average5.3%6.5%7.8%14.1%8.6%unclear
Price cut before sale33%60%80%100%68%unclear
Seller paid closing costs or repairs67%60%60%67%64%unclear
Has a view17%0%20%50%23%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 · 22 sales · November 1, 2025 – October 31, 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.

2026-11-01T07:05:59.549763 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 4 5 7 22 sales Sales per group Before 2014: 6 sales (27%) 2014–2015: 4 sales (18%) 2016–2018: 5 sales (23%) After 2018: 7 sales (32%)
Bottom line: too few sales to test.

5.1 Key differences

The top group against the bottom group: no measure differs enough to rule out chance.

5.3 Net sale price: described, not tested

2026-11-01T07:05:59.569937 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014– 2015 4 sales 2016– 2018 5 sales After 2018 7 sales $0K $100K $200K $300K $287K $256K $252K $294K Net sale price, average

The average is $294K for homes built after 2018 and $287K for homes built before 2014. It does not move in a straight line; homes built after 2018 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-11-01T07:05:59.593040 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014– 2015 4 sales 2016– 2018 5 sales After 2018 7 sales $0 $100 $200 $164 $171 $184 $172 Net price per SF, average

The average is $172 per SF for homes built after 2018 and $164 per SF for homes built before 2014. It does not move in a straight line; homes built 2016–2018 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-11-01T07:05:59.614620 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014– 2015 4 sales 2016– 2018 5 sales After 2018 7 sales 0 1,000 2,000 1,811 1,530 1,368 1,774 Living area (SF), average

The average is 1,774 SF for homes built after 2018 and 1,811 SF for homes built before 2014. It does not move in a straight line; homes built before 2014 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-11-01T07:05:59.635878 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014– 2015 4 sales 2016– 2018 5 sales After 2018 7 sales 0 100 200 159 44 68 177 Days on market, median

The median is 177 days for homes built after 2018 and 159 days for homes built before 2014. It does not move in a straight line; homes built after 2018 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-11-01T07:05:59.658730 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014– 2015 4 sales 2016– 2018 5 sales After 2018 7 sales 0.0% 5.0% 10.0% 9.1% 8.3% 4.5% 11.2% Discount from original list, average

The average is 11.2% for homes built after 2018 and 9.1% for homes built before 2014. It does not move in a straight line; homes built after 2018 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-11-01T07:05:59.684308 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% 83 67 17 50 25 25 40 80 20 86 71 29 Before 2014 2014–2015 2016–2018 After 2018

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

  • 86% of homes built after 2018 had a price cut before sale, against 83% of homes built before 2014. Defined in 8.1.7.
  • 71% of homes built after 2018 had the seller pay closing costs or repairs, against 67% of homes built before 2014. Defined in 8.1.8.
  • 29% of homes built after 2018 have a view, against 17% of homes built before 2014. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

5.9 The numbers: price and size

Before 20146 sales2014–20154 sales2016–20185 salesAfter 20187 salesAll22 sales
Net sale price average$287,367$256,438$252,013$293,641$275,705
Net price per SF average$164$171$184$172$173
Living area average1,8111,5301,3681,7741,648
Year built median20082014201820202016

5.10 The numbers: selling

Before 20146 sales2014–20154 sales2016–20185 salesAfter 20187 salesAll22 sales
Days on market median159446817778
Discount from original list average9.1%8.3%4.5%11.2%8.6%
Price cut before sale83%50%40%86%68%
Seller paid closing costs or repairs67%25%80%71%64%
Has a view17%25%20%29%23%

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 · 22 sales · November 1, 2025 – October 31, 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.

2026-11-01T07:05:59.702360 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 16 21 sales Sales per group View: 5 sales (24%) No view: 16 sales (76%)
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$341K$254Kunclear
Net price per SF$169 per SF$177 per SFunclear
Living area2,076 SF1,466 SFunclear
Year built20182015unclear
Days on market55 days78 daysunclear
Discount from original list7.0%7.7%unclear
Price cut before sale60%69%unclear
Seller paid closing costs or repairs60%62%unclear

6.3 Net sale price: no clear difference

2026-11-01T07:05:59.719897 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 16 sales $0K $100K $200K $300K $400K $341K $254K Net sale price, average

The average is $341K for homes with a view and $254K 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

2026-11-01T07:05:59.738616 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 16 sales $0 $50 $100 $150 $200 $169 $177 Net price per SF, average

The average is $169 per SF for homes with a view and $177 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

2026-11-01T07:05:59.757274 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 16 sales 0 500 1,000 1,500 2,000 2,076 1,466 Living area (SF), average

The average is 2,076 SF for homes with a view and 1,466 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-01T07:05:59.803953 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 16 sales 2012 2014 2016 2018 2020 2018 2015 Year built: median (dot) and middle half (bar)

The median is 2018 for homes with a view and 2015 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-01T07:05:59.823203 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 16 sales 0 20 40 60 80 55 78 Days on market, median

The median is 55 days for homes with a view and 78 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

2026-11-01T07:05:59.842785 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 16 sales 0.0% 2.0% 4.0% 6.0% 8.0% 7.0% 7.7% Discount from original list, average

The average is 7.0% for homes with a view and 7.7% 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

2026-11-01T07:05:59.861780 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 60 60 69 62 View No view

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

  • 60% of homes with a view had a price cut before sale, against 69% of homes without a view. Defined in 8.1.7.
  • 60% of homes with a view had the seller pay closing costs or repairs, against 62% 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

View5 salesNo view16 salesAll21 salesReal difference?
Net sale price average$341,470$253,635$274,548unclear
Net price per SF average$169$177$175unclear
Living area average2,0761,4661,611unclear
Year built median201820152016unclear

6.11 The numbers: selling

View5 salesNo view16 salesAll21 salesReal difference?
Days on market median557878unclear
Discount from original list average7.0%7.7%7.5%unclear
Price cut before sale60%69%67%unclear
Seller paid closing costs or repairs60%62%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 · 13 sales · November 1, 2025 – October 31, 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: 13 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 Blanco Vista.
MeasureAverageMedian
Sales13
Net sale price$337,991$335,900
Net price per SF$174$178
Living area (SF)2,0401,883
Days on market149181
Discount from original list15.2%16.1%
Price cut before sale85% of sales
Seller paid closing costs or repairs54% of sales
Year built2022–2026

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
22 resale sales. Average $275,705; median $261,250; standard deviation $66,150; middle half (25th–75th percentile) $227,734–$307,500; lowest $198,590, highest $435,700. 14 sales had a seller payment; their median payment was $5,450.

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
22 resale sales. Average $173; median $181; standard deviation $22; middle half (25th–75th percentile) $164–$188; lowest $124, highest $201.

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
22 resale sales. Average 1,648; median 1,422; standard deviation 547; middle half (25th–75th percentile) 1,272–1,911; lowest 1,026, highest 2,843.

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
22 resale sales. Average 2016; median 2016; standard deviation 5; middle half (25th–75th percentile) 2012–2019; lowest 2008, highest 2022.

8.1.5 Days on market

In simple terms
How many days the home was on the market before the buyer's offer was accepted, counting any earlier listing periods (relists). This is the days on market agents and clients quote.
Statistically
CDOM = max(CumulativeDaysOnMarket, DaysOnMarket, PurchaseContractDate − ListingContractDate). The MLS counter can freeze at a price change, so the contract-date gap is a floor. Summarized by the median, because a few homes that sat for months pull an average up.
The data
22 resale sales. Average 142; median 78; standard deviation 159; middle half (25th–75th percentile) 54–175; lowest 3, highest 601. 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
22 resale sales. Average 8.6%; median 6.2%; standard deviation 6.8%; middle half (25th–75th percentile) 4.5%–11.7%; lowest 0.0%, highest 30.2%. 0 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
15 of 22 resale sales (68.2%).

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
14 of 22 resale sales (63.6%).

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
5 sales with a view, 16 without, 1 unclassified. Most common View entries: None 11, Neighborhood 7, Hill Country 2, Park/Greenbelt 2, See Remarks 1, Pond 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
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-01 13:00 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = San Marcos, SubdivisionName contains any of “blanco vista”, “blanco vista tr e 3”, “blanco vista tr e 2”, “blanco vista tr e 1”, “blanco vista tr e” (case-insensitive). A record is kept when its subdivision name belongs to the Blanco Vista family, the same rule comparable sales use (it includes Blanco Vista Tr E-3, Blanco Vista Tr E-2, Blanco Vista Tr E-1, proven adjacent and priced alike).
The data
Pulled November 1, 2026: 35 closed Blanco Vista records over the prior year, in ZIP 78666. 7 subdivision spellings kept: Blanco Vista (22); Blanco Vista Ph 1-A (5); Blanco Vista Tr E-2 (2); Blanco Vista Tr E-1 (2); Blanco Vista Tr E-3 (2); BLANCO VISTA (1); Blanco Vista Ph 3 Sec 1 (1). Names found by the search but not part of Blanco Vista, left out: Blanco Vista Tr K-1 (7); Blanco Vista Tr G-H (5); Blanco Vista Tr R (4); Blanco Vista Tr S-T (4); Blanco Vista Heritage Point (3); Blanco Vista Tr D (3); Blanco Vista Tr Q Sec 3 (2); Blanco Vista Tr C-2 (2); Blanco Vista Tr 1 (1); Blanco Vista Tr Q Sec 2 (1); Blanco Vista Tr N (1); Blanco Vista Tr L (1); Blanco Vista Tr Q Sec 1 (1); Blanco Vista Tr O (1); Blanco Vista Tr K-2B (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 11 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 1, 2025 to October 31, 2026 inclusive.
The data
35 single-family sales in the window: 22 resale, 13 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
22 resale; 13 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 $233K”.
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 $233K: $198,590–$226,000 (6 sales); $233K–$260K: $232,935–$260,000 (5 sales); $262K–$300K: $262,500–$300,000 (5 sales); Over $300K: $310,000–$435,700 (6 sales)
Quartiles by living area: Under 1,301 SF: 1,026–1,262 SF (6 sales); 1,301–1,420 SF: 1,301–1,420 SF (5 sales); 1,424–1,841 SF: 1,424–1,841 SF (5 sales); Over 1,841 SF: 1,934–2,843 SF (6 sales)
Quartiles by year built: Before 2014: 2008–2012 (6 sales); 2014–2015: 2014–2015 (4 sales); 2016–2018: 2016–2018 (5 sales); After 2018: 2019–2022 (7 sales)
View and no view: View: MLS lists a view (5 sales); No view: None or Neighborhood (16 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 $275,705, median $261,250. Days on market: average 142, median 78: 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; View and no view: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
2 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

In simple terms
Headings and sentences round figures so they read easily; the tables at the end of each section give them in full.
Statistically
Prices in headings round to the nearest $1K; price per SF and days on market to the nearest whole number; living area to the nearest 10 SF; shares and percentage gaps to whole percents.
The data
Days on market is always shown in days.

8.3 Test results

Every test behind every gold box. Statistic, degrees of freedom (df), p-value, the threshold it must beat, and the size of the difference.

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 3.2930.3489p < 0.0063Unclearε² = 0.157large
Living areaKruskal–WallisH = 14.6830.0021p < 0.0063Yesε² = 0.699large
Year builtKruskal–WallisH = 0.3830.9438p < 0.0063Unclearε² = 0.018small
Days on marketKruskal–WallisH = 5.3530.1478p < 0.0063Unclearε² = 0.255large
Discount from original listKruskal–WallisH = 1.4530.6943p < 0.0063Unclearε² = 0.069medium
Price cut before saleChi-squareχ² = 0.9530.8134p < 0.0063UnclearCramér’s V = 0.208small
Seller paid closing costs or repairsChi-squareχ² = 1.1130.7739p < 0.0063UnclearCramér’s V = 0.225small
Has a viewChi-squareχ² = 9.6630.0217p < 0.0063UnclearCramér’s V = 0.663large

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 15.0430.0018p < 0.0063Yesε² = 0.716large
Net price per SFKruskal–WallisH = 11.1030.0112p < 0.0063Unclearε² = 0.528large
Year builtKruskal–WallisH = 0.7930.8508p < 0.0063Unclearε² = 0.038small
Days on marketKruskal–WallisH = 7.1230.0682p < 0.0063Unclearε² = 0.339large
Discount from original listKruskal–WallisH = 5.0530.1684p < 0.0063Unclearε² = 0.240large
Price cut before saleChi-squareχ² = 6.6330.0845p < 0.0063UnclearCramér’s V = 0.549large
Seller paid closing costs or repairsChi-squareχ² = 0.1030.9913p < 0.0063UnclearCramér’s V = 0.069negligible
Has a viewChi-squareχ² = 4.1630.2449p < 0.0063UnclearCramér’s V = 0.435medium

8.3.3 Quartiles by year built

Too few sales in a group to test.

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 63.00—0.0616p < 0.0063Unclearrank-biserial r = 0.575large
Net price per SFMann–Whitney UU = 28.00—0.3539p < 0.0063Unclearrank-biserial r = 0.300medium
Living areaMann–Whitney UU = 62.00—0.0753p < 0.0063Unclearrank-biserial r = 0.550large
Year builtMann–Whitney UU = 52.50—0.3194p < 0.0063Unclearrank-biserial r = 0.312medium
Days on marketMann–Whitney UU = 31.00—0.4825p < 0.0063Unclearrank-biserial r = 0.225small
Discount from original listMann–Whitney UU = 34.00—0.6599p < 0.0063Unclearrank-biserial r = 0.150small
Price cut before saleChi-squareχ² = 0.1310.7171p < 0.0063UnclearCramér’s V = 0.079negligible
Seller paid closing costs or repairsChi-squareχ² = 0.0110.9200p < 0.0063UnclearCramér’s V = 0.022negligible

8.4 Data notes

Left out of the analysis: 13 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 22 closed MLS resale sales; the 13 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 1, 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.