ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Avery Ranch East Ph 01

Austin, TX 78717
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 · 6:59 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
29
single-family resale homes
Median net sale price
$700,000
average $691,832
Median net price per SF
$237
average $242
Median days on market
24 days
average 62 days
1. SummaryResale homes · 29 sales · October 26, 2025 – October 25, 2026

This study looks at the 29 resale homes sold in Avery Ranch East Ph 01 in the 365 days to October 25, 2026. A full year is used because only 13 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 sold29 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 $566K · 7 sales$566K–$679K · 7 sales$700K–$790K · 8 salesOver $790K · 7 sales
3. Quartiles by net sale priceResale homes · 29 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.

2026-10-26T07:00:06.345001 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 8 7 29 sales Sales per group Under $566K: 7 sales (24%) $566K–$679K: 7 sales (24%) $700K–$790K: 8 sales (28%) Over $790K: 7 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 $566K$566K–$679K$700K–$790KOver $790K
Higher-priced homes Over $790K
  • Are much larger.
Lower-priced homes Under $566K
  • 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 $566K$566K–$679K$700K–$790KOver $790KReal difference?
Net price per SF$243 per SF$224 per SF$249 per SF$253 per SFunclear
Living area1,992 SFSmallest2,829 SF2,997 SF3,621 SFLargest✓ large
Year built2005200420072007unclear
Days on market25 days76 days12 days24 daysunclear
Discount from original list6.4%4.7%2.7%3.2%unclear
Price cut before sale43%43%25%0%unclear
Seller paid closing costs or repairs43%43%25%29%unclear
Has a view14%57%25%57%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

2026-10-26T07:00:06.372684 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $566K 7 sales $566K– $679K 7 sales $700K– $790K 8 sales Over $790K 7 sales $0 $100 $200 $300 $243 $224 $249 $253 Net price per SF, average

The average is $253 per SF for homes over $790K and $243 per SF for homes under $566K. It does not move in a straight line; homes over $790K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $790K are about 1,630 SF (82%) larger than homes under $566K

2026-10-26T07:00:06.394725 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $566K 7 sales $566K– $679K 7 sales $700K– $790K 8 sales Over $790K 7 sales 0 2,000 4,000 1,992 2,829 2,997 3,621 Living area (SF), average

The average is 3,621 SF for homes over $790K and 1,992 SF for homes under $566K. 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

2026-10-26T07:00:06.416965 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $566K 7 sales $566K– $679K 7 sales $700K– $790K 8 sales Over $790K 7 sales 2005 2008 2011 2005 2004 2007 2007 Year built: median (dot) and middle half (bar)

The median is 2007 for homes over $790K and 2005 for homes under $566K. It does not move in a straight line; homes $700K–$790K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:00:06.439198 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $566K 7 sales $566K– $679K 7 sales $700K– $790K 8 sales Over $790K 7 sales 0 25 50 75 25 76 12 24 Days on market, median

The median is 24 days for homes over $790K and 25 days for homes under $566K. It does not move in a straight line; homes $566K–$679K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:00:06.460937 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $566K 7 sales $566K– $679K 7 sales $700K– $790K 8 sales Over $790K 7 sales 0.0% 2.0% 4.0% 6.0% 6.4% 4.7% 2.7% 3.2% Discount from original list, average

The average is 3.2% for homes over $790K and 6.4% for homes under $566K. It does not move in a straight line; homes under $566K 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

2026-10-26T07:00:06.490364 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 43 14 43 43 57 25 25 25 0 29 57 Under $566K $566K–$679K $700K–$790K Over $790K

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

  • 0% of homes over $790K had a price cut before sale, against 43% of homes under $566K. Defined in 8.1.7.
  • 29% of homes over $790K had the seller pay closing costs or repairs, against 43% of homes under $566K. Defined in 8.1.8.
  • 57% of homes over $790K have a view, against 14% of homes under $566K. 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 $566K7 sales$566K–$679K7 sales$700K–$790K8 salesOver $790K7 salesAll29 salesReal difference?
Net sale price average$482,326$631,600$731,738$915,963$691,832by design
Net price per SF average$243$224$249$253$242unclear
Living area average1,9922,8292,9973,6212,865✓ large
Year built median20052004200720072006unclear

3.10 The numbers: selling

Under $566K7 sales$566K–$679K7 sales$700K–$790K8 salesOver $790K7 salesAll29 salesReal difference?
Days on market median2576122424unclear
Discount from original list average6.4%4.7%2.7%3.2%4.2%unclear
Price cut before sale43%43%25%0%28%unclear
Seller paid closing costs or repairs43%43%25%29%34%unclear
Has a view14%57%25%57%38%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 · 29 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.

2026-10-26T07:00:06.512146 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 8 7 29 sales Sales per group Under 2,477 SF: 7 sales (24%) 2,477–2,748 SF: 7 sales (24%) 2,770–3,311 SF: 8 sales (28%) Over 3,311 SF: 7 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 2,477 SF2,477–2,748 SF2,770–3,311 SFOver 3,311 SF
Larger homes Over 3,311 SF
  • Sell for much more.
Smaller homes Under 2,477 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 2,477 SF2,477–2,748 SF2,770–3,311 SFOver 3,311 SFReal difference?
Net sale price$482KLowest$670K$725K$885KHighest✓ large
Net price per SF$243 per SF$254 per SF$237 per SF$236 per SFunclear
Year built2005200620062007unclear
Days on market25 days42 days6 days30 daysunclear
Discount from original list6.4%4.2%0.2%6.6%unclear
Price cut before sale43%29%12%29%unclear
Seller paid closing costs or repairs43%29%50%14%unclear
Has a view14%57%25%57%unclear

4.3 Homes over 3,311 SF sell for about $403K (84%) more than homes under 2,477 SF

2026-10-26T07:00:06.533767 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,477 SF 7 sales 2,477– 2,748 SF 7 sales 2,770– 3,311 SF 8 sales Over 3,311 SF 7 sales $0K $500K $1.00M $482K $670K $725K $885K Net sale price, average

The average is $885K for homes over 3,311 SF and $482K for homes under 2,477 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

2026-10-26T07:00:06.557666 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,477 SF 7 sales 2,477– 2,748 SF 7 sales 2,770– 3,311 SF 8 sales Over 3,311 SF 7 sales $0 $100 $200 $300 $243 $254 $237 $236 Net price per SF, average

The average is $236 per SF for homes over 3,311 SF and $243 per SF for homes under 2,477 SF. It does not move in a straight line; homes 2,477–2,748 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:00:06.581692 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,477 SF 7 sales 2,477– 2,748 SF 7 sales 2,770– 3,311 SF 8 sales Over 3,311 SF 7 sales 2005 2008 2011 2005 2006 2006 2007 Year built: median (dot) and middle half (bar)

The median is 2007 for homes over 3,311 SF and 2005 for homes under 2,477 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:00:06.605708 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,477 SF 7 sales 2,477– 2,748 SF 7 sales 2,770– 3,311 SF 8 sales Over 3,311 SF 7 sales 0 20 40 25 42 6 30 Days on market, median

The median is 30 days for homes over 3,311 SF and 25 days for homes under 2,477 SF. It does not move in a straight line; homes 2,477–2,748 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:00:06.629132 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,477 SF 7 sales 2,477– 2,748 SF 7 sales 2,770– 3,311 SF 8 sales Over 3,311 SF 7 sales 0.0% 2.0% 4.0% 6.0% 6.4% 4.2% 0.2% 6.6% Discount from original list, average

The average is 6.6% for homes over 3,311 SF and 6.4% for homes under 2,477 SF. It does not move in a straight line; homes over 3,311 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

2026-10-26T07:00:06.658855 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 43 14 29 29 57 12 50 25 29 14 57 Under 2,477 SF 2,477–2,748 SF 2,770–3,311 SF Over 3,311 SF

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

  • 29% of homes over 3,311 SF had a price cut before sale, against 43% of homes under 2,477 SF. Defined in 8.1.7.
  • 14% of homes over 3,311 SF had the seller pay closing costs or repairs, against 43% of homes under 2,477 SF. Defined in 8.1.8.
  • 57% of homes over 3,311 SF have a view, against 14% of homes under 2,477 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 2,477 SF7 sales2,477–2,748 SF7 sales2,770–3,311 SF8 salesOver 3,311 SF7 salesAll29 salesReal difference?
Net sale price average$482,326$670,400$724,756$885,143$691,832✓ large
Net price per SF average$243$254$237$236$242unclear
Living area average1,9922,6443,0573,7372,865by design
Year built median20052006200620072006unclear

4.10 The numbers: selling

Under 2,477 SF7 sales2,477–2,748 SF7 sales2,770–3,311 SF8 salesOver 3,311 SF7 salesAll29 salesReal difference?
Days on market median254263024unclear
Discount from original list average6.4%4.2%0.2%6.6%4.2%unclear
Price cut before sale43%29%12%29%28%unclear
Seller paid closing costs or repairs43%29%50%14%34%unclear
Has a view14%57%25%57%38%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 · 29 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.

2026-10-26T07:00:06.680468 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 9 9 5 29 sales Sales per group Before 2004: 6 sales (21%) 2004–2006: 9 sales (31%) 2007: 9 sales (31%) After 2007: 5 sales (17%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

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

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 20042004–20062007After 2007Real difference?
Net sale price$575K$740K$780K$586Kunclear
Net price per SF$234 per SF$255 per SF$240 per SF$234 per SFunclear
Living area2,499 SF2,874 SF3,276 SF2,545 SFunclear
Days on market14 days30 days19 days25 daysunclear
Discount from original list4.5%5.2%3.6%3.0%unclear
Price cut before sale33%22%22%40%unclear
Seller paid closing costs or repairs17%22%44%60%unclear
Has a view33%56%44%0%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:00:06.701357 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 6 sales 2004– 2006 9 sales 2007 9 sales After 2007 5 sales $0K $250K $500K $750K $575K $740K $780K $586K Net sale price, average

The average is $586K for homes built after 2007 and $575K for homes built before 2004. It does not move in a straight line; homes built 2007 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:00:06.723948 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 6 sales 2004– 2006 9 sales 2007 9 sales After 2007 5 sales $0 $100 $200 $300 $234 $255 $240 $234 Net price per SF, average

The average is $234 per SF for homes built after 2007 and $234 per SF for homes built before 2004. It does not move in a straight line; homes built 2004–2006 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:00:06.745119 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 6 sales 2004– 2006 9 sales 2007 9 sales After 2007 5 sales 0 1,000 2,000 3,000 2,499 2,874 3,276 2,545 Living area (SF), average

The average is 2,545 SF for homes built after 2007 and 2,499 SF for homes built before 2004. It does not move in a straight line; homes built 2007 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:00:06.766166 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 6 sales 2004– 2006 9 sales 2007 9 sales After 2007 5 sales 0 10 20 30 14 30 19 25 Days on market, median

The median is 25 days for homes built after 2007 and 14 days for homes built before 2004. It does not move in a straight line; homes built 2004–2006 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:00:06.788389 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 6 sales 2004– 2006 9 sales 2007 9 sales After 2007 5 sales 0.0% 2.0% 4.0% 6.0% 4.5% 5.2% 3.6% 3.0% Discount from original list, average

The average is 3.0% for homes built after 2007 and 4.5% for homes built before 2004. It does not move in a straight line; homes built 2004–2006 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

2026-10-26T07:00:06.813690 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 33 17 33 22 22 56 22 44 44 40 60 0 Before 2004 2004–2006 2007 After 2007

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

  • 40% of homes built after 2007 had a price cut before sale, against 33% of homes built before 2004. Defined in 8.1.7.
  • 60% of homes built after 2007 had the seller pay closing costs or repairs, against 17% of homes built before 2004. Defined in 8.1.8.
  • 0% of homes built after 2007 have a view, against 33% of homes built before 2004. 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 20046 sales2004–20069 sales20079 salesAfter 20075 salesAll29 salesReal difference?
Net sale price average$575,400$739,533$780,305$586,438$691,832unclear
Net price per SF average$234$255$240$234$242unclear
Living area average2,4992,8743,2762,5452,865unclear
Year built median20022005200720132006by design

5.10 The numbers: selling

Before 20046 sales2004–20069 sales20079 salesAfter 20075 salesAll29 salesReal difference?
Days on market median1430192524unclear
Discount from original list average4.5%5.2%3.6%3.0%4.2%unclear
Price cut before sale33%22%22%40%28%unclear
Seller paid closing costs or repairs17%22%44%60%34%unclear
Has a view33%56%44%0%38%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 · 29 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:00:06.832311 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 17 28 sales Sales per group View: 11 sales (39%) No view: 17 sales (61%)
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$770K$646Kunclear
Net price per SF$251 per SF$238 per SFunclear
Living area3,063 SF2,745 SFunclear
Year built20062007unclear
Days on market19 days25 daysunclear
Discount from original list2.9%4.6%unclear
Price cut before sale0%41%unclear
Seller paid closing costs or repairs27%41%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:00:06.848752 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 17 sales $0K $200K $400K $600K $800K $770K $646K Net sale price, average

The average is $770K for homes with a view and $646K 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

2026-10-26T07:00:06.866434 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 17 sales $0 $100 $200 $300 $251 $238 Net price per SF, average

The average is $251 per SF for homes with a view and $238 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

2026-10-26T07:00:06.883588 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 17 sales 0 1,000 2,000 3,000 3,063 2,745 Living area (SF), average

The average is 3,063 SF for homes with a view and 2,745 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:00:06.951423 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 17 sales 2004 2005 2006 2007 2008 2006 2007 Year built: median (dot) and middle half (bar)

The median is 2006 for homes with a view and 2007 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:00:06.970913 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 17 sales 0 10 20 30 19 25 Days on market, median

The median is 19 days for homes with a view and 25 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

2026-10-26T07:00:06.989296 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 17 sales 0.0% 2.0% 4.0% 2.9% 4.6% Discount from original list, average

The average is 2.9% for homes with a view and 4.6% 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

2026-10-26T07:00:07.007286 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 0 27 41 41 View No view

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

  • 0% of homes with a view had a price cut before sale, against 41% of homes without a view. Defined in 8.1.7.
  • 27% of homes with a view had the seller pay closing costs or repairs, against 41% 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

View11 salesNo view17 salesAll28 salesReal difference?
Net sale price average$769,655$646,143$694,665unclear
Net price per SF average$251$238$243unclear
Living area average3,0632,7452,870unclear
Year built median200620072006unclear

6.11 The numbers: selling

View11 salesNo view17 salesAll28 salesReal difference?
Days on market median192522unclear
Discount from original list average2.9%4.6%4.0%unclear
Price cut before sale0%41%25%unclear
Seller paid closing costs or repairs27%41%36%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 Avery Ranch East Ph 01.

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
29 resale sales. Average $691,832; median $700,000; standard deviation $177,427; middle half (25th–75th percentile) $566,300–$790,000; lowest $350,000, highest $1,226,000. 10 sales had a seller payment; their median payment was $1,550.

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
29 resale sales. Average $242; median $237; standard deviation $31; middle half (25th–75th percentile) $225–$259; lowest $188, highest $305.

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
29 resale sales. Average 2,865; median 2,770; standard deviation 664; middle half (25th–75th percentile) 2,477–3,311; lowest 1,660, highest 4,020.

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
29 resale sales. Average 2006; median 2006; standard deviation 3; middle half (25th–75th percentile) 2004–2007; lowest 2001, highest 2015.

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
29 resale sales. Average 62; median 24; standard deviation 78; middle half (25th–75th percentile) 6–83; lowest 2, highest 232. 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
29 resale sales. Average 4.2%; median 3.2%; standard deviation 5.4%; middle half (25th–75th percentile) 0.0%–5.6%; lowest −5.0%, highest 18.6%. 3 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
8 of 29 resale sales (27.6%).

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
10 of 29 resale sales (34.5%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
11 sales with a view, 17 without, 1 unclassified. Most common View entries: None 15, Park/Greenbelt 9, Trees/Woods 8, Neighborhood 3, Garden 2, Panoramic 2, Golf Course 1, Hill Country 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 “avery ranch east”, “avery ranch” (case-insensitive). A record is kept when its subdivision name belongs to the Avery Ranch East Ph 01 family, the same rule comparable sales use (it includes Avery Ranch, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 30 closed Avery Ranch East Ph 01 records over the prior year, in ZIP 78717. 10 subdivision spellings kept: Avery Ranch (11); Avery Ranch East Ph 02 Sec 05 (5); Avery Ranch East Ph 01 (3); Avery Ranch East Ph 02 Sec 04 (3); Avery Ranch East Ph 02 Sec 02 (2); Avery Ranch East Ph 02 Sec 01 (2); Avery Ranch East Ph 02 Sec 03 (1); AVERY RANCH (1); Avery Ranch East (1); Avery Ranch East Ph 01 Amd (1). Names found by the search but not part of Avery Ranch East Ph 01, left out: Avery Ranch West Ph 02 (7); Avery Ranch Far West Ph 01 Sec 05 (5); Avery Ranch West Condo (4); Avery Ranch West Ph 01 (4); Commons At Avery Ranch Condo (4); Avery Ranch Far West (4); Avery Ranch Far West Ph 3 Sec (3); Avery Ranch Far West Ph 02 Sec 02 (3); Avery Ranch Far West Ph 02 Sec 04 (3); Avery Ranch Far West Ph 03 Sec 02 (2); Plaza Twnhms At Avery Ranch Condo (2); Northwoods at Avery Ranch (2); Avery Ranch Far West Ph 01 Sec 04 (2); Avery Ranch Far West Ph 01 Sec 01 (2); Avery Ranch Far West Ph 02 Sec 01 (2); Avery Ranch North Sec 02 Pud Amd (2); Avery Ranch Far West Ph 01 Sec 03 (2); Avery Ranch Garden Homes PUD (2); Avery Ranch Garden Homes Pud (2); Avery Ranch Far West Ph 01 Sec 02 (2); Avery Ranch Morningside (1); Golf Club At Avery Ranch, Avery Estates, Champions (1); Avery Ranch West (1); Golf Club/Avery Ranch (1); Avery Ranch Far West Ph 02 Sec 03 (1); Commons/Avery Ranch Condos (1); Avery Ranch -Ingleside (1); Avery Ranch East Parkside (1); Avery Ranch Ingleside Condos (1); Reserve At Avery Ranch 03 (1); Avery Ranch Brookside Ph 01 (1); Avery Ranch Far West Ph Sec 01 (1); AVERY RANCH FAR WEST PH 3 SEC 3 (1); Avery Ranch - Ingleside Condo (1); Casitas At Avery Ranch 02 Amd (1); Northwoods At Avery Ranch (1); Avery Ranch West Ph 2 (1); Avery Ranch Far West Ph 03 (1); Avery Ranch North Sec 01 Pud Amd (1); Avery Ranch Far West Ph 01 Sec 06 (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 13 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
29 single-family sales in the window: 29 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
29 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
1 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 $566K”.
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 $566K: $350,000–$565,000 (7 sales); $566K–$679K: $566,300–$679,000 (7 sales); $700K–$790K: $700,000–$790,000 (8 sales); Over $790K: $820,744–$1,226,000 (7 sales)
Quartiles by living area: Under 2,477 SF: 1,660–2,325 SF (7 sales); 2,477–2,748 SF: 2,477–2,748 SF (7 sales); 2,770–3,311 SF: 2,770–3,311 SF (8 sales); Over 3,311 SF: 3,350–4,020 SF (7 sales)
Quartiles by year built: Before 2004: 2001–2003 (6 sales); 2004–2006: 2004–2006 (9 sales); 2007: 2007–2007 (9 sales); After 2007: 2008–2015 (5 sales)
View and no view: View: MLS lists a view (11 sales); No view: None or Neighborhood (17 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 $691,832, median $700,000. Days on market: average 62, median 24: 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
2 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 3.9130.2714p < 0.0063Unclearε² = 0.140medium
Living areaKruskal–WallisH = 20.9030.0001p < 0.0063Yesε² = 0.747large
Year builtKruskal–WallisH = 3.0330.3867p < 0.0063Unclearε² = 0.108medium
Days on marketKruskal–WallisH = 2.1930.5333p < 0.0063Unclearε² = 0.078medium
Discount from original listKruskal–WallisH = 2.4030.4936p < 0.0063Unclearε² = 0.086medium
Price cut before saleChi-squareχ² = 4.3330.2282p < 0.0063UnclearCramér’s V = 0.386medium
Seller paid closing costs or repairsChi-squareχ² = 0.8630.8348p < 0.0063UnclearCramér’s V = 0.172small
Has a viewChi-squareχ² = 4.4330.2190p < 0.0063UnclearCramér’s V = 0.391medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 21.0430.0001p < 0.0063Yesε² = 0.751large
Net price per SFKruskal–WallisH = 1.7330.6299p < 0.0063Unclearε² = 0.062medium
Year builtKruskal–WallisH = 1.3630.7149p < 0.0063Unclearε² = 0.049small
Days on marketKruskal–WallisH = 9.1830.0270p < 0.0063Unclearε² = 0.328large
Discount from original listKruskal–WallisH = 7.5930.0553p < 0.0063Unclearε² = 0.271large
Price cut before saleChi-squareχ² = 1.7430.6291p < 0.0063UnclearCramér’s V = 0.245small
Seller paid closing costs or repairsChi-squareχ² = 2.4430.4858p < 0.0063UnclearCramér’s V = 0.290small
Has a viewChi-squareχ² = 4.4330.2190p < 0.0063UnclearCramér’s V = 0.391medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 9.9330.0191p < 0.0063Unclearε² = 0.355large
Net price per SFKruskal–WallisH = 2.2630.5199p < 0.0063Unclearε² = 0.081medium
Living areaKruskal–WallisH = 5.5630.1352p < 0.0063Unclearε² = 0.199large
Days on marketKruskal–WallisH = 1.3730.7132p < 0.0063Unclearε² = 0.049small
Discount from original listKruskal–WallisH = 0.8330.8424p < 0.0063Unclearε² = 0.030small
Price cut before saleChi-squareχ² = 0.7430.8628p < 0.0063UnclearCramér’s V = 0.160small
Seller paid closing costs or repairsChi-squareχ² = 3.2830.3507p < 0.0063UnclearCramér’s V = 0.336medium
Has a viewChi-squareχ² = 4.4630.2160p < 0.0063UnclearCramér’s V = 0.392medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 124.00—0.1582p < 0.0063Unclearrank-biserial r = 0.326medium
Net price per SFMann–Whitney UU = 110.00—0.4517p < 0.0063Unclearrank-biserial r = 0.176small
Living areaMann–Whitney UU = 115.00—0.3232p < 0.0063Unclearrank-biserial r = 0.230small
Year builtMann–Whitney UU = 69.00—0.2496p < 0.0063Unclearrank-biserial r = 0.262small
Days on marketMann–Whitney UU = 78.50—0.4948p < 0.0063Unclearrank-biserial r = 0.160small
Discount from original listMann–Whitney UU = 83.50—0.6545p < 0.0063Unclearrank-biserial r = 0.107small
Price cut before saleChi-squareχ² = 6.0410.0140p < 0.0063UnclearCramér’s V = 0.464medium
Seller paid closing costs or repairsChi-squareχ² = 0.5610.4533p < 0.0063UnclearCramér’s V = 0.142small

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 1 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 29 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.