ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Canyon Creek

Austin, TX 78726
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 · 7:39 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
41
single-family resale homes
Median net sale price
$720,000
average $751,012
Median net price per SF
$250
average $246
Median days on market
19 days
average 42 days
1. SummaryResale homes · 41 sales · October 26, 2025 – October 25, 2026

This study looks at the 41 resale homes sold in Canyon Creek in the 365 days to October 25, 2026. A full year is used because only 24 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 sold41 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 $665K · 10 sales$665K–$718K · 10 sales$720K–$821K · 11 salesOver $821K · 10 sales
3. Quartiles by net sale priceResale homes · 41 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.

2026-10-26T07:39:13.532879 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 11 10 41 sales Sales per group Under $665K: 10 sales (24%) $665K–$718K: 10 sales (24%) $720K–$821K: 11 sales (27%) Over $821K: 10 sales (24%)
Bottom line

3.1 Key differences

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

Under $665K$665K–$718K$720K–$821KOver $821K
Higher-priced homes Over $821K
  • Are much larger.
Lower-priced homes Under $665K
  • 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 $665K$665K–$718K$720K–$821KOver $821KReal difference?
Net price per SF$244 per SF$230 per SF$243 per SF$268 per SFunclear
Living area2,446 SFSmallest3,032 SF3,176 SF3,582 SFLargest✓ large
Year built1993199419991999unclear
Days on market16 days14 days29 days21 daysunclear
Discount from original list6.1%4.0%3.3%5.2%unclear
Price cut before sale40%30%18%50%unclear
Seller paid closing costs or repairs30%60%73%60%unclear
Has a view20%10%36%80%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

2026-10-26T07:39:13.563131 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $665K 10 sales $665K– $718K 10 sales $720K– $821K 11 sales Over $821K 10 sales $0 $100 $200 $300 $244 $230 $243 $268 Net price per SF, average

The average is $268 per SF for homes over $821K and $244 per SF for homes under $665K. It does not move in a straight line; homes over $821K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $821K are about 1,140 SF (46%) larger than homes under $665K

2026-10-26T07:39:13.586747 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $665K 10 sales $665K– $718K 10 sales $720K– $821K 11 sales Over $821K 10 sales 0 2,000 4,000 2,446 3,032 3,176 3,582 Living area (SF), average

The average is 3,582 SF for homes over $821K and 2,446 SF for homes under $665K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-26T07:39:13.611813 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $665K 10 sales $665K– $718K 10 sales $720K– $821K 11 sales Over $821K 10 sales 1993 1996 1999 2002 1993 1994 1999 1999 Year built: median (dot) and middle half (bar)

The median is 1999 for homes over $821K and 1993 for homes under $665K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:39:13.635733 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $665K 10 sales $665K– $718K 10 sales $720K– $821K 11 sales Over $821K 10 sales 0 10 20 30 16 14 29 21 Days on market, median

The median is 21 days for homes over $821K and 16 days for homes under $665K. It does not move in a straight line; homes $720K–$821K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:39:13.658526 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $665K 10 sales $665K– $718K 10 sales $720K– $821K 11 sales Over $821K 10 sales 0.0% 2.0% 4.0% 6.0% 6.1% 4.0% 3.3% 5.2% Discount from original list, average

The average is 5.2% for homes over $821K and 6.1% for homes under $665K. It does not move in a straight line; homes under $665K are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:39:13.690069 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 40 30 20 30 60 10 18 73 36 50 60 80 Under $665K $665K–$718K $720K–$821K Over $821K

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

  • 50% of homes over $821K had a price cut before sale, against 40% of homes under $665K. Defined in 8.1.7.
  • 60% of homes over $821K had the seller pay closing costs or repairs, against 30% of homes under $665K. Defined in 8.1.8.
  • 80% of homes over $821K have a view, against 20% of homes under $665K. 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 $665K10 sales$665K–$718K10 sales$720K–$821K11 salesOver $821K10 salesAll41 salesReal difference?
Net sale price average$589,375$692,005$763,218$958,230$751,012by design
Net price per SF average$244$230$243$268$246unclear
Living area average2,4463,0323,1763,5823,062✓ large
Year built median19931994199919991997unclear

3.10 The numbers: selling

Under $665K10 sales$665K–$718K10 sales$720K–$821K11 salesOver $821K10 salesAll41 salesReal difference?
Days on market median1614292119unclear
Discount from original list average6.1%4.0%3.3%5.2%4.6%unclear
Price cut before sale40%30%18%50%34%unclear
Seller paid closing costs or repairs30%60%73%60%56%unclear
Has a view20%10%36%80%37%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 · 41 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.

2026-10-26T07:39:13.711776 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 11 10 41 sales Sales per group Under 2,737 SF: 10 sales (24%) 2,737–3,180 SF: 10 sales (24%) 3,189–3,323 SF: 11 sales (27%) Over 3,323 SF: 10 sales (24%)
Bottom line

4.1 Key differences

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

Under 2,737 SF2,737–3,180 SF3,189–3,323 SFOver 3,323 SF
Larger homes Over 3,323 SF
  • Sell for much more.
  • Tend to be newer.
Smaller homes Under 2,737 SF
  • Sell for much less.
  • Tend to be older.

4.2 At a glance

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

Under 2,737 SF2,737–3,180 SF3,189–3,323 SFOver 3,323 SFReal difference?
Net sale price$607KLowest$720K$755K$921KHighest✓ large
Net price per SF$257 per SF$245 per SF$232 per SF$251 per SFunclear
Year built1993Oldest19942000Newest1999✓ large
Days on market13 days30 days29 days9 daysunclear
Discount from original list4.7%4.0%4.3%5.6%unclear
Price cut before sale30%30%45%30%unclear
Seller paid closing costs or repairs50%40%73%60%unclear
Has a view10%30%27%80%unclear

4.3 Homes over 3,323 SF sell for about $315K (52%) more than homes under 2,737 SF

2026-10-26T07:39:13.733733 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,737 SF 10 sales 2,737– 3,180 SF 10 sales 3,189– 3,323 SF 11 sales Over 3,323 SF 10 sales $0K $500K $1.00M $607K $720K $755K $921K Net sale price, average

The average is $921K for homes over 3,323 SF and $607K for homes under 2,737 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-26T07:39:13.756975 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,737 SF 10 sales 2,737– 3,180 SF 10 sales 3,189– 3,323 SF 11 sales Over 3,323 SF 10 sales $0 $100 $200 $300 $257 $245 $232 $251 Net price per SF, average

The average is $251 per SF for homes over 3,323 SF and $257 per SF for homes under 2,737 SF. It does not move in a straight line; homes under 2,737 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Homes over 3,323 SF are about 6 years newer than homes under 2,737 SF

2026-10-26T07:39:13.782671 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,737 SF 10 sales 2,737– 3,180 SF 10 sales 3,189– 3,323 SF 11 sales Over 3,323 SF 10 sales 1990 1993 1996 1999 2002 1993 1994 2000 1999 Year built: median (dot) and middle half (bar)

The median is 1999 for homes over 3,323 SF and 1993 for homes under 2,737 SF. It does not move in a straight line; homes 3,189–3,323 SF are highest. Defined in 8.1.4.

✓ Real difference · large

4.6 Days on market: no clear difference

2026-10-26T07:39:13.806736 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,737 SF 10 sales 2,737– 3,180 SF 10 sales 3,189– 3,323 SF 11 sales Over 3,323 SF 10 sales 0 10 20 30 13 30 29 9 Days on market, median

The median is 9 days for homes over 3,323 SF and 13 days for homes under 2,737 SF. It does not move in a straight line; homes 2,737–3,180 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:39:13.829437 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,737 SF 10 sales 2,737– 3,180 SF 10 sales 3,189– 3,323 SF 11 sales Over 3,323 SF 10 sales 0.0% 2.0% 4.0% 6.0% 4.7% 4.0% 4.3% 5.6% Discount from original list, average

The average is 5.6% for homes over 3,323 SF and 4.7% for homes under 2,737 SF. It does not move in a straight line; homes over 3,323 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

2026-10-26T07:39:13.857643 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% 30 50 10 30 40 30 45 73 27 30 60 80 Under 2,737 SF 2,737–3,180 SF 3,189–3,323 SF Over 3,323 SF

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

  • 30% of homes over 3,323 SF had a price cut before sale, against 30% of homes under 2,737 SF. Defined in 8.1.7.
  • 60% of homes over 3,323 SF had the seller pay closing costs or repairs, against 50% of homes under 2,737 SF. Defined in 8.1.8.
  • 80% of homes over 3,323 SF have a view, against 10% of homes under 2,737 SF. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

4.9 The numbers: price and size

Under 2,737 SF10 sales2,737–3,180 SF10 sales3,189–3,323 SF11 salesOver 3,323 SF10 salesAll41 salesReal difference?
Net sale price average$606,780$720,490$754,923$921,465$751,012✓ large
Net price per SF average$257$245$232$251$246unclear
Living area average2,3612,9413,2513,6753,062by design
Year built median19931994200019991997✓ large

4.10 The numbers: selling

Under 2,737 SF10 sales2,737–3,180 SF10 sales3,189–3,323 SF11 salesOver 3,323 SF10 salesAll41 salesReal difference?
Days on market median133029919unclear
Discount from original list average4.7%4.0%4.3%5.6%4.6%unclear
Price cut before sale30%30%45%30%34%unclear
Seller paid closing costs or repairs50%40%73%60%56%unclear
Has a view10%30%27%80%37%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 · 41 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.

2026-10-26T07:39:13.879808 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 11 10 11 41 sales Sales per group Before 1993: 9 sales (22%) 1993–1996: 11 sales (27%) 1997–1999: 10 sales (24%) After 1999: 11 sales (27%)
Bottom line

5.1 Key differences

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

Before 19931993–19961997–1999After 1999
Newer homes After 1999
  • Are much larger.
Older homes Before 1993
  • Are much smaller.

5.2 At a glance

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

Before 19931993–19961997–1999After 1999Real difference?
Net sale price$652K$709K$868K$767Kunclear
Net price per SF$241 per SF$259 per SF$254 per SF$230 per SFunclear
Living area2,702 SFSmallest2,759 SF3,426 SFLargest3,329 SF✓ large
Days on market16 days11 days24 days30 daysunclear
Discount from original list6.5%2.2%4.0%6.2%unclear
Price cut before sale44%27%20%45%unclear
Seller paid closing costs or repairs56%45%70%55%unclear
Has a view22%18%50%55%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:39:13.901852 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1993 9 sales 1993– 1996 11 sales 1997– 1999 10 sales After 1999 11 sales $0K $500K $1.00M $652K $709K $868K $767K Net sale price, average

The average is $767K for homes built after 1999 and $652K for homes built before 1993. It does not move in a straight line; homes built 1997–1999 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:39:13.925292 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1993 9 sales 1993– 1996 11 sales 1997– 1999 10 sales After 1999 11 sales $0 $100 $200 $300 $241 $259 $254 $230 Net price per SF, average

The average is $230 per SF for homes built after 1999 and $241 per SF for homes built before 1993. It does not move in a straight line; homes built 1993–1996 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Homes built after 1999 are about 630 SF (23%) larger than homes built before 1993

2026-10-26T07:39:13.947544 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1993 9 sales 1993– 1996 11 sales 1997– 1999 10 sales After 1999 11 sales 0 2,000 4,000 2,702 2,759 3,426 3,329 Living area (SF), average

The average is 3,329 SF for homes built after 1999 and 2,702 SF for homes built before 1993. It does not move in a straight line; homes built 1997–1999 are highest. Defined in 8.1.3.

✓ Real difference · large

5.6 Days on market: no clear difference

2026-10-26T07:39:13.969145 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1993 9 sales 1993– 1996 11 sales 1997– 1999 10 sales After 1999 11 sales 0 10 20 30 16 11 24 30 Days on market, median

The median is 30 days for homes built after 1999 and 16 days for homes built before 1993. It does not move in a straight line; homes built after 1999 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:39:13.992674 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1993 9 sales 1993– 1996 11 sales 1997– 1999 10 sales After 1999 11 sales 0.0% 2.0% 4.0% 6.0% 6.5% 2.2% 4.0% 6.2% Discount from original list, average

The average is 6.2% for homes built after 1999 and 6.5% for homes built before 1993. It does not move in a straight line; homes built before 1993 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:39:14.019630 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 44 56 22 27 45 18 20 70 50 45 55 55 Before 1993 1993–1996 1997–1999 After 1999

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

  • 45% of homes built after 1999 had a price cut before sale, against 44% of homes built before 1993. Defined in 8.1.7.
  • 55% of homes built after 1999 had the seller pay closing costs or repairs, against 56% of homes built before 1993. Defined in 8.1.8.
  • 55% of homes built after 1999 have a view, against 22% of homes built before 1993. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

5.9 The numbers: price and size

Before 19939 sales1993–199611 sales1997–199910 salesAfter 199911 salesAll41 salesReal difference?
Net sale price average$652,420$709,006$867,940$767,386$751,012unclear
Net price per SF average$241$259$254$230$246unclear
Living area average2,7022,7593,4263,3293,062✓ large
Year built median19901994199920021997by design

5.10 The numbers: selling

Before 19939 sales1993–199611 sales1997–199910 salesAfter 199911 salesAll41 salesReal difference?
Days on market median1611243019unclear
Discount from original list average6.5%2.2%4.0%6.2%4.6%unclear
Price cut before sale44%27%20%45%34%unclear
Seller paid closing costs or repairs56%45%70%55%56%unclear
Has a view22%18%50%55%37%unclear

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

6. View and no viewResale homes · 41 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.

2026-10-26T07:39:14.041039 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 15 26 41 sales Sales per group View: 15 sales (37%) No view: 26 sales (63%)
Bottom line

6.1 Key differences

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

ViewNo view
Homes with a view MLS lists a view
  • Sell for much more.
Homes without a view no view listed
  • Sell for much less.

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$847KHighest$696KLowest✓ large
Net price per SF$254 per SF$241 per SFunclear
Living area3,339 SF2,902 SFunclear
Year built19991994unclear
Days on market10 days21 daysunclear
Discount from original list5.5%4.1%unclear
Price cut before sale40%31%unclear
Seller paid closing costs or repairs40%65%unclear

6.3 Homes with a view sell for about $151K (22%) more than homes without a view

2026-10-26T07:39:14.060440 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 15 sales No view 26 sales $0K $250K $500K $750K $1.00M $847K $696K Net sale price, average

The average is $847K for homes with a view and $696K for homes without a view. Defined in 8.1.1.

✓ Real difference · large

6.4 Net price per SF: no clear difference

2026-10-26T07:39:14.080533 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 15 sales No view 26 sales $0 $100 $200 $300 $254 $241 Net price per SF, average

The average is $254 per SF for homes with a view and $241 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

2026-10-26T07:39:14.102421 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 15 sales No view 26 sales 0 1,000 2,000 3,000 4,000 3,339 2,902 Living area (SF), average

The average is 3,339 SF for homes with a view and 2,902 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:39:14.208262 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 15 sales No view 26 sales 1992 1994 1996 1998 2000 1999 1994 Year built: median (dot) and middle half (bar)

The median is 1999 for homes with a view and 1994 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:39:14.228755 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 15 sales No view 26 sales 0 10 20 10 21 Days on market, median

The median is 10 days for homes with a view and 21 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

2026-10-26T07:39:14.247759 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 15 sales No view 26 sales 0.0% 2.0% 4.0% 6.0% 5.5% 4.1% Discount from original list, average

The average is 5.5% for homes with a view and 4.1% 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

2026-10-26T07:39:14.267989 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 40 40 31 65 View No view

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

  • 40% of homes with a view had a price cut before sale, against 31% of homes without a view. Defined in 8.1.7.
  • 40% of homes with a view had the seller pay closing costs or repairs, against 65% 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

View15 salesNo view26 salesAll41 salesReal difference?
Net sale price average$846,610$695,860$751,012✓ large
Net price per SF average$254$241$246unclear
Living area average3,3392,9023,062unclear
Year built median199919941997unclear

6.11 The numbers: selling

View15 salesNo view26 salesAll41 salesReal difference?
Days on market median102119unclear
Discount from original list average5.5%4.1%4.6%unclear
Price cut before sale40%31%34%unclear
Seller paid closing costs or repairs40%65%56%unclear

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

7. New constructionBasic statistics · 0 sales · October 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 Canyon Creek.

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
41 resale sales. Average $751,012; median $720,000; standard deviation $150,792; middle half (25th–75th percentile) $665,000–$820,750; lowest $389,000, highest $1,087,250. 23 sales had a seller payment; their median payment was $5,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
41 resale sales. Average $246; median $250; standard deviation $32; middle half (25th–75th percentile) $227–$258; lowest $174, highest $318.

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
41 resale sales. Average 3,062; median 3,189; standard deviation 521; middle half (25th–75th percentile) 2,737–3,323; lowest 2,046, highest 4,348.

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
41 resale sales. Average 1996; median 1997; standard deviation 5; middle half (25th–75th percentile) 1993–2000; lowest 1989, highest 2006.

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
41 resale sales. Average 42; median 19; standard deviation 51; middle half (25th–75th percentile) 6–65; lowest 1, highest 226. 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
41 resale sales. Average 4.6%; median 2.9%; standard deviation 6.0%; middle half (25th–75th percentile) 0.2%–9.4%; lowest −5.5%, highest 18.2%. 7 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
14 of 41 resale sales (34.1%).

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
23 of 41 resale sales (56.1%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
15 sales with a view, 26 without, 0 unclassified. Most common View entries: None 15, Park/Greenbelt 13, Neighborhood 13, Trees/Woods 10, Hill Country 5, Panoramic 2, See Remarks 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 = Austin, SubdivisionName contains any of “canyon creek” (case-insensitive). A record is kept when its subdivision name belongs to the Canyon Creek family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 41 closed Canyon Creek records over the prior year, in ZIP 78726. 21 subdivision spellings kept, the most common: Canyon Creek Sec 01 (6); Canyon Creek Sec 21 (4); Canyon Creek Sec 26 (3); Canyon Creek (3); Canyon Creek Sec 11 (2); Canyon Creek Sec 17B (2); Canyon Creek Sec 22 (2); Canyon Creek Sec 28 (2); Canyon Creek Sec 17c (2); Canyon Creek Sec 19B (2); Canyon Creek Sec 17C (2); Canyon Creek Sec 19A (2); and 9 more (9 records). Names found by the search but not part of Canyon Creek, left out: Villas At Canyon Creek Condo (3); Canyon Creek West Sec 01 (2); Canyon Creek West (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 24 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
41 single-family sales in the window: 41 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
41 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 $665K”.
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 $665K: $389,000–$660,000 (10 sales); $665K–$718K: $665,000–$718,500 (10 sales); $720K–$821K: $720,000–$820,750 (11 sales); Over $821K: $835,000–$1,087,250 (10 sales)
Quartiles by living area: Under 2,737 SF: 2,046–2,721 SF (10 sales); 2,737–3,180 SF: 2,737–3,180 SF (10 sales); 3,189–3,323 SF: 3,189–3,323 SF (11 sales); Over 3,323 SF: 3,341–4,348 SF (10 sales)
Quartiles by year built: Before 1993: 1989–1992 (9 sales); 1993–1996: 1993–1996 (11 sales); 1997–1999: 1997–1999 (10 sales); After 1999: 2000–2006 (11 sales)
View and no view: View: MLS lists a view (15 sales); No view: None or Neighborhood (26 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 $751,012, median $720,000. Days on market: average 42, median 19: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

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

8.2.8 Mann–Whitney U test

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

8.2.9 Chi-square test

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

8.2.10 Real difference (significance)

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

8.2.11 Size of a difference

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

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 9.1230.0278p < 0.0063Unclearε² = 0.228large
Living areaKruskal–WallisH = 24.713< 0.0001p < 0.0063Yesε² = 0.618large
Year builtKruskal–WallisH = 8.0230.0456p < 0.0063Unclearε² = 0.200large
Days on marketKruskal–WallisH = 0.6830.8780p < 0.0063Unclearε² = 0.017small
Discount from original listKruskal–WallisH = 0.3230.9559p < 0.0063Unclearε² = 0.008negligible
Price cut before saleChi-squareχ² = 2.5930.4587p < 0.0063UnclearCramér’s V = 0.251small
Seller paid closing costs or repairsChi-squareχ² = 4.1230.2484p < 0.0063UnclearCramér’s V = 0.317medium
Has a viewChi-squareχ² = 12.3630.0063p < 0.0063UnclearCramér’s V = 0.549large

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 24.633< 0.0001p < 0.0063Yesε² = 0.616large
Net price per SFKruskal–WallisH = 5.9130.1160p < 0.0063Unclearε² = 0.148large
Year builtKruskal–WallisH = 14.0930.0028p < 0.0063Yesε² = 0.352large
Days on marketKruskal–WallisH = 1.5930.6626p < 0.0063Unclearε² = 0.040small
Discount from original listKruskal–WallisH = 0.4430.9327p < 0.0063Unclearε² = 0.011small
Price cut before saleChi-squareχ² = 0.8530.8363p < 0.0063UnclearCramér’s V = 0.144small
Seller paid closing costs or repairsChi-squareχ² = 2.5030.4753p < 0.0063UnclearCramér’s V = 0.247small
Has a viewChi-squareχ² = 11.7730.0082p < 0.0063UnclearCramér’s V = 0.536large

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 11.4330.0096p < 0.0063Unclearε² = 0.286large
Net price per SFKruskal–WallisH = 6.3130.0973p < 0.0063Unclearε² = 0.158large
Living areaKruskal–WallisH = 18.0230.0004p < 0.0063Yesε² = 0.451large
Days on marketKruskal–WallisH = 1.2130.7495p < 0.0063Unclearε² = 0.030small
Discount from original listKruskal–WallisH = 3.5330.3171p < 0.0063Unclearε² = 0.088medium
Price cut before saleChi-squareχ² = 2.1730.5377p < 0.0063UnclearCramér’s V = 0.230small
Seller paid closing costs or repairsChi-squareχ² = 1.3030.7285p < 0.0063UnclearCramér’s V = 0.178small
Has a viewChi-squareχ² = 4.7130.1942p < 0.0063UnclearCramér’s V = 0.339medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 306.00—0.0028p < 0.0063Yesrank-biserial r = 0.569large
Net price per SFMann–Whitney UU = 240.00—0.2284p < 0.0063Unclearrank-biserial r = 0.231small
Living areaMann–Whitney UU = 289.50—0.0109p < 0.0063Unclearrank-biserial r = 0.485medium
Year builtMann–Whitney UU = 264.50—0.0608p < 0.0063Unclearrank-biserial r = 0.356medium
Days on marketMann–Whitney UU = 151.00—0.2386p < 0.0063Unclearrank-biserial r = 0.226small
Discount from original listMann–Whitney UU = 206.00—0.7763p < 0.0063Unclearrank-biserial r = 0.056negligible
Price cut before saleChi-squareχ² = 0.3610.5483p < 0.0063UnclearCramér’s V = 0.094negligible
Seller paid closing costs or repairsChi-squareχ² = 2.4910.1147p < 0.0063UnclearCramér’s V = 0.246small

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 41 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.