ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Colorado Crossing

Austin, TX 78744
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 · 4:02 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
24
single-family resale homes
Median net sale price
$326,000
average $324,333
Median net price per SF
$199
average $190
Median days on market
43 days
average 104 days
1. SummaryResale homes · 24 sales · October 26, 2025 – October 25, 2026

This study looks at the 24 resale homes sold in Colorado Crossing in the 365 days to October 25, 2026. A full year is used because only 10 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 sold24 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 $300K · 6 sales$300K–$324K · 6 sales$328K–$357K · 6 salesOver $357K · 6 sales
3. Quartiles by net sale priceResale homes · 24 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.

2026-10-26T04:02:29.062950 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 6 6 24 sales Sales per group Under $300K: 6 sales (25%) $300K–$324K: 6 sales (25%) $328K–$357K: 6 sales (25%) Over $357K: 6 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 $300K$300K–$324K$328K–$357KOver $357K
Higher-priced homes Over $357K
  • Are much larger.
Lower-priced homes Under $300K
  • 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 $300K$300K–$324K$328K–$357KOver $357KReal difference?
Net price per SF$188 per SF$199 per SF$195 per SF$179 per SFunclear
Living area1,368 SFSmallest1,607 SF1,808 SF2,165 SFLargest✓ large
Year built2016201220162017unclear
Days on market120 days70 days30 days40 daysunclear
Discount from original list18.5%8.6%3.1%6.2%unclear
Price cut before sale83%67%17%50%unclear
Seller paid closing costs or repairs67%67%100%67%unclear
Has a view0%17%17%0%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

2026-10-26T04:02:29.092237 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $300K 6 sales $300K– $324K 6 sales $328K– $357K 6 sales Over $357K 6 sales $0 $100 $200 $188 $199 $195 $179 Net price per SF, average

The average is $179 per SF for homes over $357K and $188 per SF for homes under $300K. It does not move in a straight line; homes $300K–$324K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $357K are about 800 SF (58%) larger than homes under $300K

2026-10-26T04:02:29.115200 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $300K 6 sales $300K– $324K 6 sales $328K– $357K 6 sales Over $357K 6 sales 0 1,000 2,000 1,368 1,607 1,808 2,165 Living area (SF), average

The average is 2,165 SF for homes over $357K and 1,368 SF for homes under $300K. 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

2026-10-26T04:02:29.139705 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $300K 6 sales $300K– $324K 6 sales $328K– $357K 6 sales Over $357K 6 sales 2008 2011 2014 2017 2016 2012 2016 2017 Year built: median (dot) and middle half (bar)

The median is 2017 for homes over $357K and 2016 for homes under $300K. It does not move in a straight line; homes over $357K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T04:02:29.163367 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $300K 6 sales $300K– $324K 6 sales $328K– $357K 6 sales Over $357K 6 sales 0 50 100 120 70 30 40 Days on market, median

The median is 40 days for homes over $357K and 120 days for homes under $300K. It does not move in a straight line; homes under $300K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T04:02:29.184897 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $300K 6 sales $300K– $324K 6 sales $328K– $357K 6 sales Over $357K 6 sales 0.0% 10.0% 20.0% 18.5% 8.6% 3.1% 6.2% Discount from original list, average

The average is 6.2% for homes over $357K and 18.5% for homes under $300K. It does not move in a straight line; homes under $300K 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

2026-10-26T04:02:29.215097 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 0 67 67 17 17 100 17 50 67 0 Under $300K $300K–$324K $328K–$357K Over $357K

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

  • 50% of homes over $357K had a price cut before sale, against 83% of homes under $300K. Defined in 8.1.7.
  • 67% of homes over $357K had the seller pay closing costs or repairs, against 67% of homes under $300K. Defined in 8.1.8.
  • 0% of homes over $357K have a view, against 0% of homes under $300K. 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 $300K6 sales$300K–$324K6 sales$328K–$357K6 salesOver $357K6 salesAll24 salesReal difference?
Net sale price average$254,547$313,406$346,630$382,750$324,333by design
Net price per SF average$188$199$195$179$190unclear
Living area average1,3681,6071,8082,1651,737✓ large
Year built median20162012201620172016unclear

3.10 The numbers: selling

Under $300K6 sales$300K–$324K6 sales$328K–$357K6 salesOver $357K6 salesAll24 salesReal difference?
Days on market median12070304043unclear
Discount from original list average18.5%8.6%3.1%6.2%9.1%unclear
Price cut before sale83%67%17%50%54%unclear
Seller paid closing costs or repairs67%67%100%67%75%unclear
Has a view0%17%17%0%8%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 · 24 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.

2026-10-26T04:02:29.236004 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 7 6 6 24 sales Sales per group Under 1,450 SF: 5 sales (21%) 1,450–1,680 SF: 7 sales (29%) 1,699–1,983 SF: 6 sales (25%) Over 1,983 SF: 6 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 1,450 SF1,450–1,680 SF1,699–1,983 SFOver 1,983 SF
Larger homes Over 1,983 SF
  • Sell for much more.
Smaller homes Under 1,450 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 1,450 SF1,450–1,680 SF1,699–1,983 SFOver 1,983 SFReal difference?
Net sale price$251KLowest$326K$344K$364KHighest✓ large
Net price per SF$196 per SF$212 per SF$191 per SF$160 per SFunclear
Year built2015202020122016unclear
Days on market168 days17 days58 days128 daysunclear
Discount from original list18.5%2.7%8.7%9.2%unclear
Price cut before sale100%14%50%67%unclear
Seller paid closing costs or repairs60%86%100%50%unclear
Has a view0%14%17%0%unclear

4.3 Homes over 1,983 SF sell for about $114K (45%) more than homes under 1,450 SF

2026-10-26T04:02:29.257006 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,450 SF 5 sales 1,450– 1,680 SF 7 sales 1,699– 1,983 SF 6 sales Over 1,983 SF 6 sales $0K $200K $400K $251K $326K $344K $364K Net sale price, average

The average is $364K for homes over 1,983 SF and $251K for homes under 1,450 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

2026-10-26T04:02:29.280439 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,450 SF 5 sales 1,450– 1,680 SF 7 sales 1,699– 1,983 SF 6 sales Over 1,983 SF 6 sales $0 $100 $200 $196 $212 $191 $160 Net price per SF, average

The average is $160 per SF for homes over 1,983 SF and $196 per SF for homes under 1,450 SF. It does not move in a straight line; homes 1,450–1,680 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T04:02:29.305550 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,450 SF 5 sales 1,450– 1,680 SF 7 sales 1,699– 1,983 SF 6 sales Over 1,983 SF 6 sales 2008 2011 2014 2017 2020 2015 2020 2012 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over 1,983 SF and 2015 for homes under 1,450 SF. It does not move in a straight line; homes 1,450–1,680 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T04:02:29.329439 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,450 SF 5 sales 1,450– 1,680 SF 7 sales 1,699– 1,983 SF 6 sales Over 1,983 SF 6 sales 0 100 200 168 17 58 128 Days on market, median

The median is 128 days for homes over 1,983 SF and 168 days for homes under 1,450 SF. It does not move in a straight line; homes under 1,450 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T04:02:29.351399 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,450 SF 5 sales 1,450– 1,680 SF 7 sales 1,699– 1,983 SF 6 sales Over 1,983 SF 6 sales 0.0% 10.0% 20.0% 18.5% 2.7% 8.7% 9.2% Discount from original list, average

The average is 9.2% for homes over 1,983 SF and 18.5% for homes under 1,450 SF. It does not move in a straight line; homes under 1,450 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

2026-10-26T04:02:29.378096 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% 100 60 0 14 86 14 50 100 17 67 50 0 Under 1,450 SF 1,450–1,680 SF 1,699–1,983 SF Over 1,983 SF

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

  • 67% of homes over 1,983 SF had a price cut before sale, against 100% of homes under 1,450 SF. Defined in 8.1.7.
  • 50% of homes over 1,983 SF had the seller pay closing costs or repairs, against 60% of homes under 1,450 SF. Defined in 8.1.8.
  • 0% of homes over 1,983 SF have a view, against 0% of homes under 1,450 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 1,450 SF5 sales1,450–1,680 SF7 sales1,699–1,983 SF6 salesOver 1,983 SF6 salesAll24 salesReal difference?
Net sale price average$250,572$325,858$344,180$364,175$324,333✓ large
Net price per SF average$196$212$191$160$190unclear
Living area average1,2761,5411,8042,2821,737by design
Year built median20152020201220162016unclear

4.10 The numbers: selling

Under 1,450 SF5 sales1,450–1,680 SF7 sales1,699–1,983 SF6 salesOver 1,983 SF6 salesAll24 salesReal difference?
Days on market median168175812843unclear
Discount from original list average18.5%2.7%8.7%9.2%9.1%unclear
Price cut before sale100%14%50%67%54%unclear
Seller paid closing costs or repairs60%86%100%50%75%unclear
Has a view0%14%17%0%8%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 · 24 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.

2026-10-26T04:02:29.398781 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 3 9 6 24 sales Sales per group Before 2011: 6 sales (25%) 2011–2015: 3 sales (12%) 2016–2017: 9 sales (38%) After 2017: 6 sales (25%)
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

2026-10-26T04:02:29.419312 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2011 6 sales 2011– 2015 3 sales 2016– 2017 9 sales After 2017 6 sales $0K $200K $400K $335K $274K $329K $332K Net sale price, average

The average is $332K for homes built after 2017 and $335K for homes built before 2011. It does not move in a straight line; homes built before 2011 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T04:02:29.442361 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2011 6 sales 2011– 2015 3 sales 2016– 2017 9 sales After 2017 6 sales $0 $100 $200 $184 $171 $185 $214 Net price per SF, average

The average is $214 per SF for homes built after 2017 and $184 per SF for homes built before 2011. It does not move in a straight line; homes built after 2017 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T04:02:29.463522 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2011 6 sales 2011– 2015 3 sales 2016– 2017 9 sales After 2017 6 sales 0 1,000 2,000 1,865 1,573 1,822 1,564 Living area (SF), average

The average is 1,564 SF for homes built after 2017 and 1,865 SF for homes built before 2011. It does not move in a straight line; homes built before 2011 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T04:02:29.485639 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2011 6 sales 2011– 2015 3 sales 2016– 2017 9 sales After 2017 6 sales 0 100 200 78 168 17 34 Days on market, median

The median is 34 days for homes built after 2017 and 78 days for homes built before 2011. It does not move in a straight line; homes built 2011–2015 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T04:02:29.507453 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2011 6 sales 2011– 2015 3 sales 2016– 2017 9 sales After 2017 6 sales 0.0% 10.0% 20.0% 10.6% 23.3% 7.0% 3.8% Discount from original list, average

The average is 3.8% for homes built after 2017 and 10.6% for homes built before 2011. It does not move in a straight line; homes built 2011–2015 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

2026-10-26T04:02:29.532929 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 83 17 100 33 0 44 67 0 33 100 17 Before 2011 2011–2015 2016–2017 After 2017

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

  • 33% of homes built after 2017 had a price cut before sale, against 67% of homes built before 2011. Defined in 8.1.7.
  • 100% of homes built after 2017 had the seller pay closing costs or repairs, against 83% of homes built before 2011. Defined in 8.1.8.
  • 17% of homes built after 2017 have a view, against 17% of homes built before 2011. 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 20116 sales2011–20153 sales2016–20179 salesAfter 20176 salesAll24 sales
Net sale price average$335,494$273,767$328,806$331,746$324,333
Net price per SF average$184$171$185$214$190
Living area average1,8651,5731,8221,5641,737
Year built median20082015201620202016

5.10 The numbers: selling

Before 20116 sales2011–20153 sales2016–20179 salesAfter 20176 salesAll24 sales
Days on market median78168173443
Discount from original list average10.6%23.3%7.0%3.8%9.1%
Price cut before sale67%100%44%33%54%
Seller paid closing costs or repairs83%33%67%100%75%
Has a view17%0%0%17%8%

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 · 24 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.

2026-10-26T04:02:29.552223 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 2 22 24 sales Sales per group View: 2 sales (8%) No view: 22 sales (92%)
Bottom line: too few sales to test.

6.1 Key differences

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

6.3 Net sale price: described, not tested

2026-10-26T04:02:29.568948 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 22 sales $0K $100K $200K $300K $400K $340K $323K Net sale price, average

The average is $340K for homes with a view and $323K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T04:02:29.587272 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 22 sales $0 $100 $200 $215 $188 Net price per SF, average

The average is $215 per SF for homes with a view and $188 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T04:02:29.665040 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 22 sales 0 500 1,000 1,500 2,000 1,586 1,751 Living area (SF), average

The average is 1,586 SF for homes with a view and 1,751 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T04:02:29.685935 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 22 sales 2012 2014 2016 2014 2016 Year built: median (dot) and middle half (bar)

The median is 2014 for homes with a view and 2016 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T04:02:29.704299 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 22 sales 0 20 40 36 43 Days on market, median

The median is 36 days for homes with a view and 43 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-26T04:02:29.724032 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 22 sales 0.0% 2.5% 5.0% 7.5% 10.0% 4.8% 9.5% Discount from original list, average

The average is 4.8% for homes with a view and 9.5% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

6.9 How often: price cut before sale, seller paid closing costs or repairs

2026-10-26T04:02:29.743570 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 50 100 55 73 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 55% 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 73% of homes without a view. Defined in 8.1.8.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View2 salesNo view22 salesAll24 sales
Net sale price average$340,364$322,876$324,333
Net price per SF average$215$188$190
Living area average1,5861,7511,737
Year built median201420162016

6.11 The numbers: selling

View2 salesNo view22 salesAll24 sales
Days on market median364343
Discount from original list average4.8%9.5%9.1%
Price cut before sale50%55%54%
Seller paid closing costs or repairs100%73%75%

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.4.

7. New constructionBasic statistics · 0 sales · October 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: 0 sales, no groups, no tests.

Note: these are only the new-construction sales reported in ABOR MLS. Builders often sell homes without listing them in the MLS, so these figures do not necessarily represent all new-construction sales in Colorado Crossing.

No new-construction sales were reported in ABOR MLS in this window.

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

8. AppendixMeasures, methods and tests

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

8.1 Measures

8.1.1 Net sale price

In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
24 resale sales. Average $324,333; median $326,000; standard deviation $53,846; middle half (25th–75th percentile) $299,922–$359,464; lowest $185,000, highest $418,000. 18 sales had a seller payment; their median payment was $8,249.

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
24 resale sales. Average $190; median $199; standard deviation $27; middle half (25th–75th percentile) $173–$210; lowest $142, highest $235.

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
24 resale sales. Average 1,737; median 1,690; standard deviation 390; middle half (25th–75th percentile) 1,450–1,983; lowest 1,220, highest 2,507.

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
24 resale sales. Average 2015; median 2016; standard deviation 5; middle half (25th–75th percentile) 2010–2018; lowest 2006, highest 2020.

8.1.5 Days on market

In simple terms
How many days the home was on the market before the buyer's offer was accepted, counting any earlier listing periods (relists). This is the days on market agents and clients quote.
Statistically
CDOM = max(CumulativeDaysOnMarket, DaysOnMarket, PurchaseContractDate − ListingContractDate). The MLS counter can freeze at a price change, so the contract-date gap is a floor. Summarized by the median, because a few homes that sat for months pull an average up.
The data
24 resale sales. Average 104; median 43; standard deviation 124; middle half (25th–75th percentile) 17–182; lowest 0, highest 445. 1 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
24 resale sales. Average 9.1%; median 6.5%; standard deviation 9.5%; middle half (25th–75th percentile) 3.7%–8.6%; lowest 0.3%, highest 39.3%. 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
13 of 24 resale sales (54.2%).

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
18 of 24 resale sales (75.0%).

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
2 sales with a view, 22 without, 0 unclassified. Most common View entries: None 19, Neighborhood 4, Park/Greenbelt 2.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “colorado crossing”, “colorado crossing iv” (case-insensitive). A record is kept when its subdivision name belongs to the Colorado Crossing family, the same rule comparable sales use (it includes Colorado Crossing Iv Sec 3, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 24 closed Colorado Crossing records over the prior year, in ZIP 78744. 10 subdivision spellings kept: Colorado Crossing (7); Colorado Crossing 02 Sec 01 (4); Colorado Crossing Iv Sec 3 (4); Colorado Crossing Iv Sec 6-B (2); Colorado Crossing Iv Sec 6-A (2); colorado crossing (1); COLORADO CROSSING (1); Colorado Crossing 02 Sec 04 (1); Colorado Crossing 03 Sec 05 (1); Colorado Crossing IV Sec 3 (1). Names found by the search but not part of Colorado Crossing, left out: COLORADO CROSSING III SEC 5 (1); Colorado Crossing Iii Sec 8 (1); Colorado Crossing III Sec 7 (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 10 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
24 single-family sales in the window: 24 resale, 0 new construction.

8.2.3 Resale and new construction

In simple terms
A resale home was previously owned. New construction is sold by the builder and behaves differently, so it is kept out of every analysis and reported once on its own.
Statistically
New construction = NewConstructionYN true, or PropertyCondition contains “New Construction” or “Under Construction”. Everything else is resale.
The data
24 resale; 0 new construction.

8.2.4 Sales left out

In simple terms
A few records cannot be used as entered and are left out before any analysis.
Statistically
Excluded: PropertySubType other than Single Family Residence; no OriginalListPrice; LivingArea under 400 SF; seller payments above 10% of ClosePrice (treated as entry errors).
The data
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 $300K”.
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 $300K: $185,000–$299,500 (6 sales); $300K–$324K: $300,062–$324,000 (6 sales); $328K–$357K: $328,000–$356,952 (6 sales); Over $357K: $367,000–$418,000 (6 sales)
Quartiles by living area: Under 1,450 SF: 1,220–1,436 SF (5 sales); 1,450–1,680 SF: 1,450–1,680 SF (7 sales); 1,699–1,983 SF: 1,699–1,983 SF (6 sales); Over 1,983 SF: 1,984–2,507 SF (6 sales)
Quartiles by year built: Before 2011: 2006–2009 (6 sales); 2011–2015: 2011–2015 (3 sales); 2016–2017: 2016–2017 (9 sales); After 2017: 2020–2020 (6 sales)
View and no view: View: MLS lists a view (2 sales); No view: None or Neighborhood (22 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 $324,333, median $326,000. Days on market: average 104, median 43: 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

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 = 2.2530.5228p < 0.0063Unclearε² = 0.098medium
Living areaKruskal–WallisH = 13.9330.0030p < 0.0063Yesε² = 0.606large
Year builtKruskal–WallisH = 0.8430.8403p < 0.0063Unclearε² = 0.036small
Days on marketKruskal–WallisH = 3.2130.3597p < 0.0063Unclearε² = 0.140medium
Discount from original listKruskal–WallisH = 9.1330.0276p < 0.0063Unclearε² = 0.397large
Price cut before saleChi-squareχ² = 5.8730.1179p < 0.0063UnclearCramér’s V = 0.495medium
Seller paid closing costs or repairsChi-squareχ² = 2.6730.4459p < 0.0063UnclearCramér’s V = 0.333medium
Has a viewChi-squareχ² = 2.1830.5355p < 0.0063UnclearCramér’s V = 0.302medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 12.4430.0060p < 0.0063Yesε² = 0.541large
Net price per SFKruskal–WallisH = 11.7630.0083p < 0.0063Unclearε² = 0.511large
Year builtKruskal–WallisH = 5.5630.1350p < 0.0063Unclearε² = 0.242large
Days on marketKruskal–WallisH = 6.8030.0785p < 0.0063Unclearε² = 0.296large
Discount from original listKruskal–WallisH = 11.0130.0117p < 0.0063Unclearε² = 0.478large
Price cut before saleChi-squareχ² = 9.1330.0276p < 0.0063UnclearCramér’s V = 0.617large
Seller paid closing costs or repairsChi-squareχ² = 5.0330.1697p < 0.0063UnclearCramér’s V = 0.458medium
Has a viewChi-squareχ² = 1.8730.5998p < 0.0063UnclearCramér’s V = 0.279small

8.3.3 Quartiles by year built

Too few sales in a group to test.

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

Left out of the analysis: 0 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 24 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 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.