ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Cottonwood Creek

San Marcos, TX 78666
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 · 7:23 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
27
single-family resale homes
Median net sale price
$253,000
average $252,699
Median net price per SF
$155
average $151
Median days on market
68 days
average 79 days
1. SummaryResale homes · 27 sales · October 26, 2025 – October 25, 2026

This study looks at the 27 resale homes sold in Cottonwood Creek in the 365 days to October 25, 2026. A full year is used because only 16 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 sold27 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 $236K · 7 sales$236K–$253K · 7 sales$255K–$262K · 6 salesOver $262K · 7 sales
3. Quartiles by net sale priceResale homes · 27 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.

2026-10-26T07:23:44.975643 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 6 7 27 sales Sales per group Under $236K: 7 sales (26%) $236K–$253K: 7 sales (26%) $255K–$262K: 6 sales (22%) Over $262K: 7 sales (26%)
Bottom line: no measure differs enough between the groups to rule out chance.

3.1 Key differences

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

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 $236K$236K–$253K$255K–$262KOver $262KReal difference?
Net price per SF$153 per SF$154 per SF$150 per SF$147 per SFunclear
Living area1,539 SF1,619 SF1,748 SF1,936 SFunclear
Year built2017201620212016unclear
Days on market36 days81 days62 days87 daysunclear
Discount from original list10.7%8.4%7.4%6.4%unclear
Price cut before sale43%71%50%57%unclear
Seller paid closing costs or repairs14%100%67%71%unclear
Has a view14%29%17%29%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

2026-10-26T07:23:45.005634 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $236K 7 sales $236K– $253K 7 sales $255K– $262K 6 sales Over $262K 7 sales $0 $50 $100 $150 $153 $154 $150 $147 Net price per SF, average

The average is $147 per SF for homes over $262K and $153 per SF for homes under $236K. It does not move in a straight line; homes $236K–$253K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-26T07:23:45.028222 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $236K 7 sales $236K– $253K 7 sales $255K– $262K 6 sales Over $262K 7 sales 0 1,000 2,000 1,539 1,619 1,748 1,936 Living area (SF), average

The average is 1,936 SF for homes over $262K and 1,539 SF for homes under $236K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-26T07:23:45.051847 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $236K 7 sales $236K– $253K 7 sales $255K– $262K 6 sales Over $262K 7 sales 2014 2016 2018 2020 2017 2016 2021 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over $262K and 2017 for homes under $236K. It does not move in a straight line; homes $255K–$262K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:23:45.075225 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $236K 7 sales $236K– $253K 7 sales $255K– $262K 6 sales Over $262K 7 sales 0 50 100 36 81 62 87 Days on market, median

The median is 87 days for homes over $262K and 36 days for homes under $236K. It does not move in a straight line; homes over $262K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:23:45.096792 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $236K 7 sales $236K– $253K 7 sales $255K– $262K 6 sales Over $262K 7 sales 0.0% 5.0% 10.0% 10.7% 8.4% 7.4% 6.4% Discount from original list, average

The average is 6.4% for homes over $262K and 10.7% for homes under $236K. It falls 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

2026-10-26T07:23:45.126483 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% 43 14 14 71 100 29 50 67 17 57 71 29 Under $236K $236K–$253K $255K–$262K Over $262K

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

  • 57% of homes over $262K had a price cut before sale, against 43% of homes under $236K. Defined in 8.1.7.
  • 71% of homes over $262K had the seller pay closing costs or repairs, against 14% of homes under $236K. Defined in 8.1.8.
  • 29% of homes over $262K have a view, against 14% of homes under $236K. 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 $236K7 sales$236K–$253K7 sales$255K–$262K6 salesOver $262K7 salesAll27 salesReal difference?
Net sale price average$227,318$246,668$258,025$279,548$252,699by design
Net price per SF average$153$154$150$147$151unclear
Living area average1,5391,6191,7481,9361,709unclear
Year built median20172016202120162018unclear

3.10 The numbers: selling

Under $236K7 sales$236K–$253K7 sales$255K–$262K6 salesOver $262K7 salesAll27 salesReal difference?
Days on market median3681628768unclear
Discount from original list average10.7%8.4%7.4%6.4%8.3%unclear
Price cut before sale43%71%50%57%56%unclear
Seller paid closing costs or repairs14%100%67%71%63%unclear
Has a view14%29%17%29%22%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 · 27 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.

2026-10-26T07:23:45.147228 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 6 7 27 sales Sales per group Under 1,562 SF: 7 sales (26%) 1,562–1,587 SF: 7 sales (26%) 1,647–1,839 SF: 6 sales (22%) Over 1,839 SF: 7 sales (26%)
Bottom line

4.1 Key differences

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

Under 1,562 SF1,562–1,587 SF1,647–1,839 SFOver 1,839 SF
Larger homes Over 1,839 SF
  • Sell for less per square foot.
  • Sell for much more.
Smaller homes Under 1,562 SF
  • Sell for more per square foot.
  • Sell for much less.

4.2 At a glance

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

Under 1,562 SF1,562–1,587 SF1,647–1,839 SFOver 1,839 SFReal difference?
Net sale price$231KLowest$248K$264K$269KHighest✓ large
Net price per SF$167 per SFHighest$158 per SF$152 per SF$127 per SFLowest✓ large
Year built2016202120162019unclear
Days on market89 days39 days122 days82 daysunclear
Discount from original list9.3%5.1%7.8%10.7%unclear
Price cut before sale71%14%67%71%unclear
Seller paid closing costs or repairs43%71%83%57%unclear
Has a view29%29%33%0%unclear

4.3 Homes over 1,839 SF sell for about $38K (16%) more than homes under 1,562 SF

2026-10-26T07:23:45.167588 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,562 SF 7 sales 1,562– 1,587 SF 7 sales 1,647– 1,839 SF 6 sales Over 1,839 SF 7 sales $0K $100K $200K $300K $231K $248K $264K $269K Net sale price, average

The average is $269K for homes over 1,839 SF and $231K for homes under 1,562 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 1,839 SF sell for about $40 per SF (24%) less than homes under 1,562 SF

2026-10-26T07:23:45.189788 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,562 SF 7 sales 1,562– 1,587 SF 7 sales 1,647– 1,839 SF 6 sales Over 1,839 SF 7 sales $0 $100 $200 $167 $158 $152 $127 Net price per SF, average

The average is $127 per SF for homes over 1,839 SF and $167 per SF for homes under 1,562 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-10-26T07:23:45.212961 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,562 SF 7 sales 1,562– 1,587 SF 7 sales 1,647– 1,839 SF 6 sales Over 1,839 SF 7 sales 2014 2016 2018 2020 2016 2021 2016 2019 Year built: median (dot) and middle half (bar)

The median is 2019 for homes over 1,839 SF and 2016 for homes under 1,562 SF. It does not move in a straight line; homes 1,562–1,587 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:23:45.235590 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,562 SF 7 sales 1,562– 1,587 SF 7 sales 1,647– 1,839 SF 6 sales Over 1,839 SF 7 sales 0 50 100 89 39 122 82 Days on market, median

The median is 82 days for homes over 1,839 SF and 89 days for homes under 1,562 SF. It does not move in a straight line; homes 1,647–1,839 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:23:45.257215 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,562 SF 7 sales 1,562– 1,587 SF 7 sales 1,647– 1,839 SF 6 sales Over 1,839 SF 7 sales 0.0% 5.0% 10.0% 9.3% 5.1% 7.8% 10.7% Discount from original list, average

The average is 10.7% for homes over 1,839 SF and 9.3% for homes under 1,562 SF. It does not move in a straight line; homes over 1,839 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:23:45.283224 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% 71 43 29 14 71 29 67 83 33 71 57 0 Under 1,562 SF 1,562–1,587 SF 1,647–1,839 SF Over 1,839 SF

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

  • 71% of homes over 1,839 SF had a price cut before sale, against 71% of homes under 1,562 SF. Defined in 8.1.7.
  • 57% of homes over 1,839 SF had the seller pay closing costs or repairs, against 43% of homes under 1,562 SF. Defined in 8.1.8.
  • 0% of homes over 1,839 SF have a view, against 29% of homes under 1,562 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 1,562 SF7 sales1,562–1,587 SF7 sales1,647–1,839 SF6 salesOver 1,839 SF7 salesAll27 salesReal difference?
Net sale price average$231,211$247,757$264,256$269,225$252,699✓ large
Net price per SF average$167$158$152$127$151✓ large
Living area average1,3871,5731,7382,1431,709by design
Year built median20162021201620192018unclear

4.10 The numbers: selling

Under 1,562 SF7 sales1,562–1,587 SF7 sales1,647–1,839 SF6 salesOver 1,839 SF7 salesAll27 salesReal difference?
Days on market median89391228268unclear
Discount from original list average9.3%5.1%7.8%10.7%8.3%unclear
Price cut before sale71%14%67%71%56%unclear
Seller paid closing costs or repairs43%71%83%57%63%unclear
Has a view29%29%33%0%22%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 · 27 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.

2026-10-26T07:23:45.303469 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 8 4 9 27 sales Sales per group Before 2014: 6 sales (22%) 2014–2018: 8 sales (30%) 2019–2020: 4 sales (15%) After 2020: 9 sales (33%)
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

2026-10-26T07:23:45.323503 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014– 2018 8 sales 2019– 2020 4 sales After 2020 9 sales $0K $100K $200K $300K $251K $247K $275K $249K Net sale price, average

The average is $249K for homes built after 2020 and $251K for homes built before 2014. It does not move in a straight line; homes built 2019–2020 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T07:23:45.346223 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014– 2018 8 sales 2019– 2020 4 sales After 2020 9 sales $0 $50 $100 $150 $162 $157 $133 $147 Net price per SF, average

The average is $147 per SF for homes built after 2020 and $162 per SF for homes built before 2014. It does not move in a straight line; homes built before 2014 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T07:23:45.368166 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014– 2018 8 sales 2019– 2020 4 sales After 2020 9 sales 0 1,000 2,000 1,556 1,594 2,094 1,743 Living area (SF), average

The average is 1,743 SF for homes built after 2020 and 1,556 SF for homes built before 2014. It does not move in a straight line; homes built 2019–2020 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T07:23:45.389232 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014– 2018 8 sales 2019– 2020 4 sales After 2020 9 sales 0 50 100 150 130 78 67 56 Days on market, median

The median is 56 days for homes built after 2020 and 130 days for homes built before 2014. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T07:23:45.411515 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014– 2018 8 sales 2019– 2020 4 sales After 2020 9 sales 0.0% 5.0% 10.0% 6.1% 6.9% 10.3% 10.0% Discount from original list, average

The average is 10.0% for homes built after 2020 and 6.1% for homes built before 2014. It does not move in a straight line; homes built 2019–2020 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

2026-10-26T07:23:45.436545 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 67 50 38 62 25 100 75 0 56 56 11 Before 2014 2014–2018 2019–2020 After 2020

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

  • 56% of homes built after 2020 had a price cut before sale, against 50% of homes built before 2014. Defined in 8.1.7.
  • 56% of homes built after 2020 had the seller pay closing costs or repairs, against 67% of homes built before 2014. Defined in 8.1.8.
  • 11% of homes built after 2020 have a view, against 50% 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 sales2014–20188 sales2019–20204 salesAfter 20209 salesAll27 sales
Net sale price average$250,816$247,377$274,950$248,797$252,699
Net price per SF average$162$157$133$147$151
Living area average1,5561,5942,0941,7431,709
Year built median20102016201920212018

5.10 The numbers: selling

Before 20146 sales2014–20188 sales2019–20204 salesAfter 20209 salesAll27 sales
Days on market median13078675668
Discount from original list average6.1%6.9%10.3%10.0%8.3%
Price cut before sale50%38%100%56%56%
Seller paid closing costs or repairs67%62%75%56%63%
Has a view50%25%0%11%22%

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 · 27 sales · October 26, 2025 – October 25, 2026

Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood. 2 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T07:23:45.454804 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 19 25 sales Sales per group View: 6 sales (24%) No view: 19 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$251K$252Kunclear
Net price per SF$161 per SF$148 per SFunclear
Living area1,554 SF1,728 SFunclear
Year built20142019unclear
Days on market89 days67 daysunclear
Discount from original list8.2%7.7%unclear
Price cut before sale50%58%unclear
Seller paid closing costs or repairs100%58%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:23:45.470313 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 6 sales No view 19 sales $0K $100K $200K $300K $251K $252K Net sale price, average

The average is $251K for homes with a view and $252K 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

2026-10-26T07:23:45.487627 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 6 sales No view 19 sales $0 $50 $100 $150 $161 $148 Net price per SF, average

The average is $161 per SF for homes with a view and $148 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

2026-10-26T07:23:45.506395 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 6 sales No view 19 sales 0 500 1,000 1,500 2,000 1,554 1,728 Living area (SF), average

The average is 1,554 SF for homes with a view and 1,728 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:23:45.546786 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 6 sales No view 19 sales 2014 2017 2020 2014 2019 Year built: median (dot) and middle half (bar)

The median is 2014 for homes with a view and 2019 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:23:45.565042 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 6 sales No view 19 sales 0 25 50 75 100 89 67 Days on market, median

The median is 89 days for homes with a view and 67 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

2026-10-26T07:23:45.583852 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 6 sales No view 19 sales 0.0% 2.0% 4.0% 6.0% 8.0% 8.2% 7.7% Discount from original list, average

The average is 8.2% 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

2026-10-26T07:23:45.602338 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 50 100 58 58 View No view

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

  • 50% of homes with a view had a price cut before sale, against 58% of homes without a view. Defined in 8.1.7.
  • 100% of homes with a view had the seller pay closing costs or repairs, against 58% 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

View6 salesNo view19 salesAll25 salesReal difference?
Net sale price average$250,553$251,819$251,515unclear
Net price per SF average$161$148$151unclear
Living area average1,5541,7281,686unclear
Year built median201420192017unclear

6.11 The numbers: selling

View6 salesNo view19 salesAll25 salesReal difference?
Days on market median896768unclear
Discount from original list average8.2%7.7%7.8%unclear
Price cut before sale50%58%56%unclear
Seller paid closing costs or repairs100%58%68%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 · 30 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: 30 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 Cottonwood Creek.
MeasureAverageMedian
Sales30
Net sale price$261,540$260,685
Net price per SF$152$150
Living area (SF)1,7571,785
Days on market127134
Discount from original list12.0%12.3%
Price cut before sale83% of sales
Seller paid closing costs or repairs70% of sales
Year built2025–2026

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
27 resale sales. Average $252,699; median $253,000; standard deviation $21,165; middle half (25th–75th percentile) $235,500–$265,048; lowest $211,200, highest $300,000. 17 sales had a seller payment; their median payment was $4,200.

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
27 resale sales. Average $151; median $155; standard deviation $19; middle half (25th–75th percentile) $142–$165; lowest $99, highest $177.

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
27 resale sales. Average 1,709; median 1,587; standard deviation 324; middle half (25th–75th percentile) 1,524–1,864; lowest 1,309, highest 2,662.

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
27 resale sales. Average 2017; median 2018; standard deviation 4; middle half (25th–75th percentile) 2014–2021; lowest 2009, 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
27 resale sales. Average 79; median 68; standard deviation 56; middle half (25th–75th percentile) 40–94; lowest 2, highest 201. 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
27 resale sales. Average 8.3%; median 7.0%; standard deviation 6.4%; middle half (25th–75th percentile) 3.7%–10.3%; lowest −0.9%, highest 22.0%. 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
15 of 27 resale sales (55.6%).

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
17 of 27 resale sales (63.0%).

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
6 sales with a view, 19 without, 2 unclassified. Most common View entries: None 10, Neighborhood 9, Park/Greenbelt 3, See Remarks 2, Pond 2, Hill Country 1, Panoramic 1, Pasture 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 = San Marcos, SubdivisionName contains any of “cottonwood creek”, “pinnacle at cottonwood creek”, “cottonwood crk” (case-insensitive). A record is kept when its subdivision name belongs to the Cottonwood Creek family, the same rule comparable sales use (it includes Pinnacle at Cottonwood Creek, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 59 closed Cottonwood Creek records over the prior year, in ZIP 78666. 14 subdivision spellings kept, the most common: Pinnacle at Cottonwood Creek (15); Cottonwood Crk Ph 4 Un 1 (9); Cottonwood Creek (8); Cottonwood Creek Ph 3 Unit 8 (6); Cottonwood Creek Ph 1 Sec 3 (4); Cottonwood Creek Ph 1 Sec 1-B (4); COTTONWOOD CREEK (3); Cottonwood Creek Ph 3 Unit 2 (2); Cottonwood Crk (2); Cottonwood Creek Ph 1 Sec 1D (2); Cottonwood Creek Ph 3 Unit 6 (1); Cottonwood creek (1); and 2 more (2 records). Names found by the search but not part of Cottonwood Creek, left out: Cottonwood Creek Ph1 Sec2 (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 16 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
57 single-family sales in the window: 27 resale, 30 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
27 resale; 30 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
2 sale(s) other than single-family homes (condo, townhome and similar)

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $236K”.
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 $236K: $211,200–$235,000 (7 sales); $236K–$253K: $236,000–$253,000 (7 sales); $255K–$262K: $255,000–$261,500 (6 sales); Over $262K: $268,595–$300,000 (7 sales)
Quartiles by living area: Under 1,562 SF: 1,309–1,486 SF (7 sales); 1,562–1,587 SF: 1,562–1,587 SF (7 sales); 1,647–1,839 SF: 1,647–1,839 SF (6 sales); Over 1,839 SF: 1,890–2,662 SF (7 sales)
Quartiles by year built: Before 2014: 2009–2013 (6 sales); 2014–2018: 2014–2018 (8 sales); 2019–2020: 2019–2020 (4 sales); After 2020: 2021–2022 (9 sales)
View and no view: View: MLS lists a view (6 sales); No view: None or Neighborhood (19 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 $252,699, median $253,000. Days on market: average 79, median 68: 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 = 1.1230.7718p < 0.0063Unclearε² = 0.043small
Living areaKruskal–WallisH = 8.8330.0317p < 0.0063Unclearε² = 0.340large
Year builtKruskal–WallisH = 9.7830.0205p < 0.0063Unclearε² = 0.376large
Days on marketKruskal–WallisH = 5.2930.1517p < 0.0063Unclearε² = 0.204large
Discount from original listKruskal–WallisH = 2.3130.5106p < 0.0063Unclearε² = 0.089medium
Price cut before saleChi-squareχ² = 1.2530.7402p < 0.0063UnclearCramér’s V = 0.215small
Seller paid closing costs or repairsChi-squareχ² = 11.4830.0094p < 0.0063UnclearCramér’s V = 0.652large
Has a viewChi-squareχ² = 0.6930.8758p < 0.0063UnclearCramér’s V = 0.160small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 14.8430.0020p < 0.0063Yesε² = 0.571large
Net price per SFKruskal–WallisH = 16.3030.0010p < 0.0063Yesε² = 0.627large
Year builtKruskal–WallisH = 2.8330.4190p < 0.0063Unclearε² = 0.109medium
Days on marketKruskal–WallisH = 6.0930.1073p < 0.0063Unclearε² = 0.234large
Discount from original listKruskal–WallisH = 3.9230.2702p < 0.0063Unclearε² = 0.151large
Price cut before saleChi-squareχ² = 6.5630.0874p < 0.0063UnclearCramér’s V = 0.493medium
Seller paid closing costs or repairsChi-squareχ² = 2.6030.4579p < 0.0063UnclearCramér’s V = 0.310medium
Has a viewChi-squareχ² = 2.7630.4309p < 0.0063UnclearCramér’s V = 0.319medium

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 = 60.00—0.8736p < 0.0063Unclearrank-biserial r = 0.053negligible
Net price per SFMann–Whitney UU = 83.00—0.1060p < 0.0063Unclearrank-biserial r = 0.456medium
Living areaMann–Whitney UU = 37.50—0.2253p < 0.0063Unclearrank-biserial r = 0.342medium
Year builtMann–Whitney UU = 34.00—0.1470p < 0.0063Unclearrank-biserial r = 0.404medium
Days on marketMann–Whitney UU = 72.00—0.3561p < 0.0063Unclearrank-biserial r = 0.263small
Discount from original listMann–Whitney UU = 56.00—0.9753p < 0.0063Unclearrank-biserial r = 0.018negligible
Price cut before saleChi-squareχ² = 0.1210.7341p < 0.0063UnclearCramér’s V = 0.068negligible
Seller paid closing costs or repairsChi-squareχ² = 3.7210.0539p < 0.0063UnclearCramér’s V = 0.385medium

8.4 Data notes

Left out of the analysis: 30 new-construction sales (basic statistics only, section 7); 2 sale(s) other than single-family homes (condo, townhome and similar). Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

  1. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Erlbaum.
  2. Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press.
  3. Dunn, O. J. (1961). Multiple comparisons among means. JASA, 56(293), 52–64.
  4. Kerby, D. S. (2014). The simple difference formula: an approach to teaching nonparametric correlation. Comprehensive Psychology, 3, 11.IT.3.1.
  5. Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. JASA, 47(260), 583–621.
  6. Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18(1), 50–60.
  7. Pearson, K. (1900). On the criterion that a given system of deviations… Philosophical Magazine, 50(302), 157–175.
  8. Tomczak, M., & Tomczak, E. (2014). The need to report effect size estimates revisited. Trends in Sport Sciences, 21(1), 19–25.

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 27 closed MLS resale sales; the 30 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.