ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Copperfield

Austin, TX 78753
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 · 7:46 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
35
single-family resale homes
Median net sale price
$311,211
average $315,893
Median net price per SF
$242
average $238
Median days on market
47 days
average 82 days
1. SummaryResale homes · 35 sales · October 26, 2025 – October 25, 2026

This study looks at the 35 resale homes sold in Copperfield in the 365 days to October 25, 2026. A full year is used because only 17 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 sold35 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 $282K · 9 sales$282K–$311K · 9 sales$313K–$348K · 8 salesOver $348K · 9 sales
3. Quartiles by net sale priceResale homes · 35 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.

2026-10-26T07:46:21.999475 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 9 8 9 35 sales Sales per group Under $282K: 9 sales (26%) $282K–$311K: 9 sales (26%) $313K–$348K: 8 sales (23%) Over $348K: 9 sales (26%)
Bottom line

3.1 Key differences

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

Under $282K$282K–$311K$313K–$348KOver $348K
Higher-priced homes Over $348K
  • Are much larger.
  • Tend to be newer.
Lower-priced homes Under $282K
  • Are much smaller.
  • Tend to be older.

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 $282K$282K–$311K$313K–$348KOver $348KReal difference?
Net price per SF$238 per SF$247 per SF$254 per SF$217 per SFunclear
Living area1,087 SFSmallest1,209 SF1,308 SF1,922 SFLargest✓ large
Year built1983Oldest198519841993Newest✓ large
Days on market35 days77 days50 days32 daysunclear
Discount from original list8.8%11.9%5.9%4.4%unclear
Price cut before sale56%89%50%56%unclear
Seller paid closing costs or repairs67%100%75%89%unclear
Has a view0%33%12%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

2026-10-26T07:46:22.026906 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $282K 9 sales $282K– $311K 9 sales $313K– $348K 8 sales Over $348K 9 sales $0 $100 $200 $300 $238 $247 $254 $217 Net price per SF, average

The average is $217 per SF for homes over $348K and $238 per SF for homes under $282K. It does not move in a straight line; homes $313K–$348K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $348K are about 840 SF (77%) larger than homes under $282K

2026-10-26T07:46:22.048872 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $282K 9 sales $282K– $311K 9 sales $313K– $348K 8 sales Over $348K 9 sales 0 1,000 2,000 1,087 1,209 1,308 1,922 Living area (SF), average

The average is 1,922 SF for homes over $348K and 1,087 SF for homes under $282K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Homes over $348K are about 10 years newer than homes under $282K

2026-10-26T07:46:22.072293 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $282K 9 sales $282K– $311K 9 sales $313K– $348K 8 sales Over $348K 9 sales 1984 1988 1992 1996 1983 1985 1984 1993 Year built: median (dot) and middle half (bar)

The median is 1993 for homes over $348K and 1983 for homes under $282K. It does not move in a straight line; homes over $348K are highest. Defined in 8.1.4.

✓ Real difference · large

3.6 Days on market: no clear difference

2026-10-26T07:46:22.094896 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $282K 9 sales $282K– $311K 9 sales $313K– $348K 8 sales Over $348K 9 sales 0 25 50 75 35 77 50 32 Days on market, median

The median is 32 days for homes over $348K and 35 days for homes under $282K. It does not move in a straight line; homes $282K–$311K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:46:22.116615 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $282K 9 sales $282K– $311K 9 sales $313K– $348K 8 sales Over $348K 9 sales 0.0% 5.0% 10.0% 8.8% 11.9% 5.9% 4.4% Discount from original list, average

The average is 4.4% for homes over $348K and 8.8% for homes under $282K. It does not move in a straight line; homes $282K–$311K 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

2026-10-26T07:46:22.145713 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% 56 67 0 89 100 33 50 75 12 56 89 0 Under $282K $282K–$311K $313K–$348K Over $348K

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

  • 56% of homes over $348K had a price cut before sale, against 56% of homes under $282K. Defined in 8.1.7.
  • 89% of homes over $348K had the seller pay closing costs or repairs, against 67% of homes under $282K. Defined in 8.1.8.
  • 0% of homes over $348K have a view, against 0% of homes under $282K. 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 $282K9 sales$282K–$311K9 sales$313K–$348K8 salesOver $348K9 salesAll35 salesReal difference?
Net sale price average$252,444$295,334$326,865$390,146$315,893by design
Net price per SF average$238$247$254$217$238unclear
Living area average1,0871,2091,3081,9221,384✓ large
Year built median19831985198419931985✓ large

3.10 The numbers: selling

Under $282K9 sales$282K–$311K9 sales$313K–$348K8 salesOver $348K9 salesAll35 salesReal difference?
Days on market median3577503247unclear
Discount from original list average8.8%11.9%5.9%4.4%7.8%unclear
Price cut before sale56%89%50%56%63%unclear
Seller paid closing costs or repairs67%100%75%89%83%unclear
Has a view0%33%12%0%11%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 · 35 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.

2026-10-26T07:46:22.166240 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 9 8 9 35 sales Sales per group Under 1,104 SF: 9 sales (26%) 1,104–1,309 SF: 9 sales (26%) 1,366–1,422 SF: 8 sales (23%) Over 1,422 SF: 9 sales (26%)
Bottom line

4.1 Key differences

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

Under 1,104 SF1,104–1,309 SF1,366–1,422 SFOver 1,422 SF
Larger homes Over 1,422 SF
  • Sell for much more.
  • Sell for less per square foot.
  • Tend to be newer.
Smaller homes Under 1,104 SF
  • Sell for much less.
  • Sell for more per square foot.
  • 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 1,104 SF1,104–1,309 SF1,366–1,422 SFOver 1,422 SFReal difference?
Net sale price$270KLowest$301K$332K$363KHighest✓ large
Net price per SF$269 per SFHighest$254 per SF$238 per SF$192 per SFLowest✓ large
Year built1983Oldest198519841993Newest✓ large
Days on market42 days46 days72 days34 daysunclear
Discount from original list7.0%8.9%8.4%7.0%unclear
Price cut before sale67%44%88%56%unclear
Seller paid closing costs or repairs67%89%100%78%unclear
Has a view11%22%12%0%unclear

4.3 Homes over 1,422 SF sell for about $93K (34%) more than homes under 1,104 SF

2026-10-26T07:46:22.186423 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,104 SF 9 sales 1,104– 1,309 SF 9 sales 1,366– 1,422 SF 8 sales Over 1,422 SF 9 sales $0K $200K $400K $270K $301K $332K $363K Net sale price, average

The average is $363K for homes over 1,422 SF and $270K for homes under 1,104 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 1,422 SF sell for about $77 per SF (29%) less than homes under 1,104 SF

2026-10-26T07:46:22.208493 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,104 SF 9 sales 1,104– 1,309 SF 9 sales 1,366– 1,422 SF 8 sales Over 1,422 SF 9 sales $0 $100 $200 $300 $269 $254 $238 $192 Net price per SF, average

The average is $192 per SF for homes over 1,422 SF and $269 per SF for homes under 1,104 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Homes over 1,422 SF are about 10 years newer than homes under 1,104 SF

2026-10-26T07:46:22.231922 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,104 SF 9 sales 1,104– 1,309 SF 9 sales 1,366– 1,422 SF 8 sales Over 1,422 SF 9 sales 1984 1988 1992 1996 1983 1985 1984 1993 Year built: median (dot) and middle half (bar)

The median is 1993 for homes over 1,422 SF and 1983 for homes under 1,104 SF. It does not move in a straight line; homes over 1,422 SF are highest. Defined in 8.1.4.

✓ Real difference · large

4.6 Days on market: no clear difference

2026-10-26T07:46:22.254725 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,104 SF 9 sales 1,104– 1,309 SF 9 sales 1,366– 1,422 SF 8 sales Over 1,422 SF 9 sales 0 25 50 75 42 46 72 34 Days on market, median

The median is 34 days for homes over 1,422 SF and 42 days for homes under 1,104 SF. It does not move in a straight line; homes 1,366–1,422 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:46:22.276541 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,104 SF 9 sales 1,104– 1,309 SF 9 sales 1,366– 1,422 SF 8 sales Over 1,422 SF 9 sales 0.0% 5.0% 10.0% 7.0% 8.9% 8.4% 7.0% Discount from original list, average

The average is 7.0% for homes over 1,422 SF and 7.0% for homes under 1,104 SF. It does not move in a straight line; homes 1,104–1,309 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

2026-10-26T07:46:22.302710 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 67 11 44 89 22 88 100 12 56 78 0 Under 1,104 SF 1,104–1,309 SF 1,366–1,422 SF Over 1,422 SF

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

  • 56% of homes over 1,422 SF had a price cut before sale, against 67% of homes under 1,104 SF. Defined in 8.1.7.
  • 78% of homes over 1,422 SF had the seller pay closing costs or repairs, against 67% of homes under 1,104 SF. Defined in 8.1.8.
  • 0% of homes over 1,422 SF have a view, against 11% of homes under 1,104 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 1,104 SF9 sales1,104–1,309 SF9 sales1,366–1,422 SF8 salesOver 1,422 SF9 salesAll35 salesReal difference?
Net sale price average$270,056$300,801$331,698$362,772$315,893✓ large
Net price per SF average$269$254$238$192$238✓ large
Living area average1,0101,1791,3951,9531,384by design
Year built median19831985198419931985✓ large

4.10 The numbers: selling

Under 1,104 SF9 sales1,104–1,309 SF9 sales1,366–1,422 SF8 salesOver 1,422 SF9 salesAll35 salesReal difference?
Days on market median4246723447unclear
Discount from original list average7.0%8.9%8.4%7.0%7.8%unclear
Price cut before sale67%44%88%56%63%unclear
Seller paid closing costs or repairs67%89%100%78%83%unclear
Has a view11%22%12%0%11%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 · 35 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.

2026-10-26T07:46:22.323152 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 10 9 9 35 sales Sales per group Before 1983: 7 sales (20%) 1983–1984: 10 sales (29%) 1985–1986: 9 sales (26%) After 1986: 9 sales (26%)
Bottom line

5.1 Key differences

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

Before 19831983–19841985–1986After 1986
Newer homes After 1986
  • Sell for much more.
  • Are much larger.
Older homes Before 1983
  • Sell for much less.
  • 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 19831983–19841985–1986After 1986Real difference?
Net sale price$270KLowest$325K$291K$366KHighest✓ large
Net price per SF$239 per SF$269 per SF$239 per SF$202 per SFunclear
Living area1,152 SFSmallest1,217 SF1,227 SF1,905 SFLargest✓ large
Days on market42 days52 days78 days21 daysunclear
Discount from original list12.1%6.7%8.8%4.8%unclear
Price cut before sale86%50%67%56%unclear
Seller paid closing costs or repairs71%90%78%89%unclear
Has a view0%20%11%11%unclear

5.3 Homes built after 1986 sell for about $97K (36%) more than homes built before 1983

2026-10-26T07:46:22.343076 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1983 7 sales 1983– 1984 10 sales 1985– 1986 9 sales After 1986 9 sales $0K $200K $400K $270K $325K $291K $366K Net sale price, average

The average is $366K for homes built after 1986 and $270K for homes built before 1983. It does not move in a straight line; homes built after 1986 are highest. Defined in 8.1.1.

✓ Real difference · large

5.4 Net price per SF: no clear difference

2026-10-26T07:46:22.365139 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1983 7 sales 1983– 1984 10 sales 1985– 1986 9 sales After 1986 9 sales $0 $100 $200 $300 $239 $269 $239 $202 Net price per SF, average

The average is $202 per SF for homes built after 1986 and $239 per SF for homes built before 1983. It does not move in a straight line; homes built 1983–1984 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Homes built after 1986 are about 750 SF (65%) larger than homes built before 1983

2026-10-26T07:46:22.386521 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1983 7 sales 1983– 1984 10 sales 1985– 1986 9 sales After 1986 9 sales 0 1,000 2,000 1,152 1,217 1,227 1,905 Living area (SF), average

The average is 1,905 SF for homes built after 1986 and 1,152 SF for homes built before 1983. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

5.6 Days on market: no clear difference

2026-10-26T07:46:22.407972 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1983 7 sales 1983– 1984 10 sales 1985– 1986 9 sales After 1986 9 sales 0 25 50 75 42 52 78 21 Days on market, median

The median is 21 days for homes built after 1986 and 42 days for homes built before 1983. It does not move in a straight line; homes built 1985–1986 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:46:22.431145 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1983 7 sales 1983– 1984 10 sales 1985– 1986 9 sales After 1986 9 sales 0.0% 5.0% 10.0% 12.1% 6.7% 8.8% 4.8% Discount from original list, average

The average is 4.8% for homes built after 1986 and 12.1% for homes built before 1983. It does not move in a straight line; homes built before 1983 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

2026-10-26T07:46:22.456460 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% 86 71 0 50 90 20 67 78 11 56 89 11 Before 1983 1983–1984 1985–1986 After 1986

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

  • 56% of homes built after 1986 had a price cut before sale, against 86% of homes built before 1983. Defined in 8.1.7.
  • 89% of homes built after 1986 had the seller pay closing costs or repairs, against 71% of homes built before 1983. Defined in 8.1.8.
  • 11% of homes built after 1986 have a view, against 0% of homes built before 1983. 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 19837 sales1983–198410 sales1985–19869 salesAfter 19869 salesAll35 salesReal difference?
Net sale price average$269,864$325,376$290,665$366,382$315,893✓ large
Net price per SF average$239$269$239$202$238unclear
Living area average1,1521,2171,2271,9051,384✓ large
Year built median19821984198519941985by design

5.10 The numbers: selling

Before 19837 sales1983–198410 sales1985–19869 salesAfter 19869 salesAll35 salesReal difference?
Days on market median4252782147unclear
Discount from original list average12.1%6.7%8.8%4.8%7.8%unclear
Price cut before sale86%50%67%56%63%unclear
Seller paid closing costs or repairs71%90%78%89%83%unclear
Has a view0%20%11%11%11%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 · 35 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.

2026-10-26T07:46:22.474886 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 31 35 sales Sales per group View: 4 sales (11%) No view: 31 sales (89%)
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

2026-10-26T07:46:22.490121 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 31 sales $0K $100K $200K $300K $298K $318K Net sale price, average

The average is $298K for homes with a view and $318K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T07:46:22.507215 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 31 sales $0 $100 $200 $300 $266 $235 Net price per SF, average

The average is $266 per SF for homes with a view and $235 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T07:46:22.525103 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 31 sales 0 500 1,000 1,500 1,142 1,415 Living area (SF), average

The average is 1,142 SF for homes with a view and 1,415 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T07:46:22.566517 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 31 sales 1983 1984 1985 1986 1987 1984 1985 Year built: median (dot) and middle half (bar)

The median is 1984 for homes with a view and 1985 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T07:46:22.585012 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 31 sales 0 20 40 60 80 74 46 Days on market, median

The median is 74 days for homes with a view and 46 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

2026-10-26T07:46:22.602990 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 31 sales 0.0% 5.0% 10.0% 15.0% 12.6% 7.2% Discount from original list, average

The average is 12.6% for homes with a view and 7.2% 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

2026-10-26T07:46:22.621072 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 75 75 61 84 View No view

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

  • 75% of homes with a view had a price cut before sale, against 61% of homes without a view. Defined in 8.1.7.
  • 75% of homes with a view had the seller pay closing costs or repairs, against 84% 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

View4 salesNo view31 salesAll35 sales
Net sale price average$298,237$318,171$315,893
Net price per SF average$266$235$238
Living area average1,1421,4151,384
Year built median198419851985

6.11 The numbers: selling

View4 salesNo view31 salesAll35 sales
Days on market median744647
Discount from original list average12.6%7.2%7.8%
Price cut before sale75%61%63%
Seller paid closing costs or repairs75%84%83%

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 Copperfield.

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
35 resale sales. Average $315,893; median $311,211; standard deviation $56,165; middle half (25th–75th percentile) $282,250–$353,800; lowest $185,000, highest $428,415. 29 sales had a seller payment; their median payment was $7,450.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
35 resale sales. Average $238; median $242; standard deviation $46; middle half (25th–75th percentile) $213–$267; lowest $146, highest $330.

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
35 resale sales. Average 1,384; median 1,309; standard deviation 433; middle half (25th–75th percentile) 1,102–1,440; lowest 854, highest 2,731.

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
35 resale sales. Average 1986; median 1985; standard deviation 5; middle half (25th–75th percentile) 1983–1986; lowest 1982, highest 1999.

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
35 resale sales. Average 82; median 47; standard deviation 91; middle half (25th–75th percentile) 22–106; lowest 3, highest 413. 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
35 resale sales. Average 7.8%; median 7.1%; standard deviation 6.2%; middle half (25th–75th percentile) 4.1%–11.1%; lowest −2.6%, highest 27.7%. 2 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
22 of 35 resale sales (62.9%).

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
29 of 35 resale sales (82.9%).

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
4 sales with a view, 31 without, 0 unclassified. Most common View entries: None 23, Neighborhood 9, Park/Greenbelt 3, Trees/Woods 2, Creek/Stream 1, Water 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 “copperfield” (case-insensitive). A record is kept when its subdivision name belongs to the Copperfield family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 37 closed Copperfield records over the prior year, in ZIP 78753. 16 subdivision spellings kept, the most common: Copperfield Sec 03-B (6); Copperfield Sec 01 Ph C (4); Copperfield (4); Copperfield Sec 01 Ph B (3); Copperfield Sec 02-B Amd (3); Copperfield Sec 01 Ph E (2); Copperfield Sec 02-A Amd (2); Copperfield Sec 03-D (2); Copperfield Sec 01 Ph A (2); Copperfield 04 Sec I-B (2); Copperfield Sec 01 Ph D (2); Copperfield 04 Sec I-A (1); and 4 more (4 records). Names found by the search but not part of Copperfield, left out: Copperfield Twnhms Ph 01 Amd (2); Copperfield Twnhms Ph 02 (2); Copperfield Twnhms Ph 03 (1); COPPERFIELD TOWNHOMES PHS 3 (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 17 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
35 single-family sales in the window: 35 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
35 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
2 sale(s) other than single-family homes (condo, townhome and similar)

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $282K”.
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 $282K: $185,000–$282,000 (9 sales); $282K–$311K: $282,500–$311,211 (9 sales); $313K–$348K: $312,550–$348,500 (8 sales); Over $348K: $359,100–$428,415 (9 sales)
Quartiles by living area: Under 1,104 SF: 854–1,099 SF (9 sales); 1,104–1,309 SF: 1,104–1,309 SF (9 sales); 1,366–1,422 SF: 1,366–1,422 SF (8 sales); Over 1,422 SF: 1,459–2,731 SF (9 sales)
Quartiles by year built: Before 1983: 1982–1982 (7 sales); 1983–1984: 1983–1984 (10 sales); 1985–1986: 1985–1986 (9 sales); After 1986: 1987–1999 (9 sales)
View and no view: View: MLS lists a view (4 sales); No view: None or Neighborhood (31 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 $315,893, median $311,211. Days on market: average 82, median 47: 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

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
7 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 = 3.0930.3783p < 0.0063Unclearε² = 0.091medium
Living areaKruskal–WallisH = 17.7430.0005p < 0.0063Yesε² = 0.522large
Year builtKruskal–WallisH = 13.0830.0045p < 0.0063Yesε² = 0.385large
Days on marketKruskal–WallisH = 4.3030.2304p < 0.0063Unclearε² = 0.127medium
Discount from original listKruskal–WallisH = 9.1230.0278p < 0.0063Unclearε² = 0.268large
Price cut before saleChi-squareχ² = 3.5930.3093p < 0.0063UnclearCramér’s V = 0.320medium
Seller paid closing costs or repairsChi-squareχ² = 4.1030.2507p < 0.0063UnclearCramér’s V = 0.342medium
Has a viewChi-squareχ² = 6.6030.0859p < 0.0063UnclearCramér’s V = 0.434medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 15.9730.0012p < 0.0063Yesε² = 0.470large
Net price per SFKruskal–WallisH = 15.7730.0013p < 0.0063Yesε² = 0.464large
Year builtKruskal–WallisH = 12.7030.0053p < 0.0063Yesε² = 0.374large
Days on marketKruskal–WallisH = 1.6930.6385p < 0.0063Unclearε² = 0.050small
Discount from original listKruskal–WallisH = 2.1130.5489p < 0.0063Unclearε² = 0.062medium
Price cut before saleChi-squareχ² = 3.6530.3019p < 0.0063UnclearCramér’s V = 0.323medium
Seller paid closing costs or repairsChi-squareχ² = 3.7130.2945p < 0.0063UnclearCramér’s V = 0.326medium
Has a viewChi-squareχ² = 2.2130.5306p < 0.0063UnclearCramér’s V = 0.251small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 13.7330.0033p < 0.0063Yesε² = 0.404large
Net price per SFKruskal–WallisH = 9.0030.0293p < 0.0063Unclearε² = 0.265large
Living areaKruskal–WallisH = 13.5730.0036p < 0.0063Yesε² = 0.399large
Days on marketKruskal–WallisH = 4.3030.2310p < 0.0063Unclearε² = 0.126medium
Discount from original listKruskal–WallisH = 5.4030.1448p < 0.0063Unclearε² = 0.159large
Price cut before saleChi-squareχ² = 2.5430.4688p < 0.0063UnclearCramér’s V = 0.269small
Seller paid closing costs or repairsChi-squareχ² = 1.4030.7063p < 0.0063UnclearCramér’s V = 0.200small
Has a viewChi-squareχ² = 1.6330.6524p < 0.0063UnclearCramér’s V = 0.216small

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); 2 sale(s) other than single-family homes (condo, townhome and similar). Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

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

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 35 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.