ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Berry Creek

Georgetown, TX 78628
Resale homes · closed Nov 7 – Nov 6, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 7, 2026 · 7:00 AM CST
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
36
single-family resale homes
Median net sale price
$587,000
average $653,536
Median net price per SF
$209
average $209
Median days on market
50 days
average 98 days
1. SummaryResale homes · 36 sales · November 7, 2025 – November 6, 2026

This study looks at the 36 resale homes sold in Berry Creek in the 365 days to November 6, 2026. A full year is used because only 19 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 sold36 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 $492K · 9 sales$492K–$580K · 9 sales$594K–$720K · 9 salesOver $720K · 9 sales
3. Quartiles by net sale priceResale homes · 36 sales · November 7, 2025 – November 6, 2026

Sales ranked by net sale price and cut into four equal groups. This is the usual way to read a market by price.

2026-11-07T07:00:44.991608 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 9 9 9 36 sales Sales per group Under $492K: 9 sales (25%) $492K–$580K: 9 sales (25%) $594K–$720K: 9 sales (25%) Over $720K: 9 sales (25%)
Bottom line

3.1 Key differences

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

Under $492K$492K–$580K$594K–$720KOver $720K
Higher-priced homes Over $720K
  • Are much larger.
Lower-priced homes Under $492K
  • 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 $492K$492K–$580K$594K–$720KOver $720KReal difference?
Net price per SF$193 per SF$188 per SF$200 per SF$254 per SFunclear
Living area2,299 SFSmallest2,899 SF3,211 SF3,982 SFLargest✓ large
Year built1998199719942000unclear
Days on market74 days172 days47 days32 daysunclear
Discount from original list5.0%10.1%5.8%4.4%unclear
Price cut before sale44%44%56%11%unclear
Seller paid closing costs or repairs44%78%78%67%unclear
Has a view44%44%44%89%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

2026-11-07T07:00:45.020821 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $492K 9 sales $492K– $580K 9 sales $594K– $720K 9 sales Over $720K 9 sales $0 $100 $200 $300 $193 $188 $200 $254 Net price per SF, average

The average is $254 per SF for homes over $720K and $193 per SF for homes under $492K. It does not move in a straight line; homes over $720K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $720K are about 1,680 SF (73%) larger than homes under $492K

2026-11-07T07:00:45.047920 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $492K 9 sales $492K– $580K 9 sales $594K– $720K 9 sales Over $720K 9 sales 0 2,000 4,000 2,299 2,899 3,211 3,982 Living area (SF), average

The average is 3,982 SF for homes over $720K and 2,299 SF for homes under $492K. 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

2026-11-07T07:00:45.082779 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $492K 9 sales $492K– $580K 9 sales $594K– $720K 9 sales Over $720K 9 sales 1995 2000 2005 2010 2015 1998 1997 1994 2000 Year built: median (dot) and middle half (bar)

The median is 2000 for homes over $720K and 1998 for homes under $492K. It does not move in a straight line; homes over $720K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-07T07:00:45.113098 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $492K 9 sales $492K– $580K 9 sales $594K– $720K 9 sales Over $720K 9 sales 0 100 200 74 172 47 32 Days on market, median

The median is 32 days for homes over $720K and 74 days for homes under $492K. It does not move in a straight line; homes $492K–$580K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-07T07:00:45.139214 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $492K 9 sales $492K– $580K 9 sales $594K– $720K 9 sales Over $720K 9 sales 0.0% 5.0% 10.0% 5.0% 10.1% 5.8% 4.4% Discount from original list, average

The average is 4.4% for homes over $720K and 5.0% for homes under $492K. It does not move in a straight line; homes $492K–$580K 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

2026-11-07T07:00:45.177805 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 44 44 44 78 44 56 78 44 11 67 89 Under $492K $492K–$580K $594K–$720K Over $720K

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

  • 11% of homes over $720K had a price cut before sale, against 44% of homes under $492K. Defined in 8.1.7.
  • 67% of homes over $720K had the seller pay closing costs or repairs, against 44% of homes under $492K. Defined in 8.1.8.
  • 89% of homes over $720K have a view, against 44% of homes under $492K. 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 $492K9 sales$492K–$580K9 sales$594K–$720K9 salesOver $720K9 salesAll36 salesReal difference?
Net sale price average$425,389$532,035$636,267$1,020,452$653,536by design
Net price per SF average$193$188$200$254$209unclear
Living area average2,2992,8993,2113,9823,098✓ large
Year built median19981997199420001998unclear

3.10 The numbers: selling

Under $492K9 sales$492K–$580K9 sales$594K–$720K9 salesOver $720K9 salesAll36 salesReal difference?
Days on market median74172473250unclear
Discount from original list average5.0%10.1%5.8%4.4%6.3%unclear
Price cut before sale44%44%56%11%39%unclear
Seller paid closing costs or repairs44%78%78%67%67%unclear
Has a view44%44%44%89%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 8.3.1.

4. Quartiles by living areaResale homes · 36 sales · November 7, 2025 – November 6, 2026

Sales ranked by living area and cut into four equal groups, from the smallest homes to the largest.

2026-11-07T07:00:45.206659 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 9 9 9 36 sales Sales per group Under 2,783 SF: 9 sales (25%) 2,783–3,023 SF: 9 sales (25%) 3,050–3,540 SF: 9 sales (25%) Over 3,540 SF: 9 sales (25%)
Bottom line

4.1 Key differences

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

Under 2,783 SF2,783–3,023 SF3,050–3,540 SFOver 3,540 SF
Larger homes Over 3,540 SF
  • Sell for much more.
Smaller homes Under 2,783 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 2,783 SF2,783–3,023 SF3,050–3,540 SFOver 3,540 SFReal difference?
Net sale price$448KLowest$532K$644K$990KHighest✓ large
Net price per SF$217 per SF$185 per SF$196 per SF$238 per SFunclear
Year built1996199419972000unclear
Days on market28 days52 days94 days33 daysunclear
Discount from original list4.9%6.3%7.4%6.6%unclear
Price cut before sale33%33%56%33%unclear
Seller paid closing costs or repairs44%78%67%78%unclear
Has a view56%33%56%78%unclear

4.3 Homes over 3,540 SF sell for about $542K (121%) more than homes under 2,783 SF

2026-11-07T07:00:45.232310 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,783 SF 9 sales 2,783– 3,023 SF 9 sales 3,050– 3,540 SF 9 sales Over 3,540 SF 9 sales $0K $500K $1.00M $448K $532K $644K $990K Net sale price, average

The average is $990K for homes over 3,540 SF and $448K for homes under 2,783 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

2026-11-07T07:00:45.260452 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,783 SF 9 sales 2,783– 3,023 SF 9 sales 3,050– 3,540 SF 9 sales Over 3,540 SF 9 sales $0 $100 $200 $217 $185 $196 $238 Net price per SF, average

The average is $238 per SF for homes over 3,540 SF and $217 per SF for homes under 2,783 SF. It does not move in a straight line; homes over 3,540 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-07T07:00:45.287397 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,783 SF 9 sales 2,783– 3,023 SF 9 sales 3,050– 3,540 SF 9 sales Over 3,540 SF 9 sales 1992 1996 2000 2004 1996 1994 1997 2000 Year built: median (dot) and middle half (bar)

The median is 2000 for homes over 3,540 SF and 1996 for homes under 2,783 SF. It does not move in a straight line; homes over 3,540 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-07T07:00:45.314865 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,783 SF 9 sales 2,783– 3,023 SF 9 sales 3,050– 3,540 SF 9 sales Over 3,540 SF 9 sales 0 50 100 28 52 94 33 Days on market, median

The median is 33 days for homes over 3,540 SF and 28 days for homes under 2,783 SF. It does not move in a straight line; homes 3,050–3,540 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-07T07:00:45.339183 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,783 SF 9 sales 2,783– 3,023 SF 9 sales 3,050– 3,540 SF 9 sales Over 3,540 SF 9 sales 0.0% 2.5% 5.0% 7.5% 4.9% 6.3% 7.4% 6.6% Discount from original list, average

The average is 6.6% for homes over 3,540 SF and 4.9% for homes under 2,783 SF. It does not move in a straight line; homes 3,050–3,540 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

2026-11-07T07:00:45.368603 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 44 56 33 78 33 56 67 56 33 78 78 Under 2,783 SF 2,783–3,023 SF 3,050–3,540 SF Over 3,540 SF

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

  • 33% of homes over 3,540 SF had a price cut before sale, against 33% of homes under 2,783 SF. Defined in 8.1.7.
  • 78% of homes over 3,540 SF had the seller pay closing costs or repairs, against 44% of homes under 2,783 SF. Defined in 8.1.8.
  • 78% of homes over 3,540 SF have a view, against 56% of homes under 2,783 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 2,783 SF9 sales2,783–3,023 SF9 sales3,050–3,540 SF9 salesOver 3,540 SF9 salesAll36 salesReal difference?
Net sale price average$447,800$531,656$644,467$990,221$653,536✓ large
Net price per SF average$217$185$196$238$209unclear
Living area average2,0742,8823,2994,1343,098by design
Year built median19961994199720001998unclear

4.10 The numbers: selling

Under 2,783 SF9 sales2,783–3,023 SF9 sales3,050–3,540 SF9 salesOver 3,540 SF9 salesAll36 salesReal difference?
Days on market median2852943350unclear
Discount from original list average4.9%6.3%7.4%6.6%6.3%unclear
Price cut before sale33%33%56%33%39%unclear
Seller paid closing costs or repairs44%78%67%78%67%unclear
Has a view56%33%56%78%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 8.3.2.

5. Quartiles by year builtResale homes · 36 sales · November 7, 2025 – November 6, 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.

2026-11-07T07:00:45.391290 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 9 9 9 36 sales Sales per group Before 1994: 9 sales (25%) 1994–1997: 9 sales (25%) 1998–2001: 9 sales (25%) After 2001: 9 sales (25%)
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 19941994–19971998–2001After 2001Real difference?
Net sale price$536K$679K$731K$668Kunclear
Net price per SF$215 per SF$213 per SF$207 per SF$200 per SFunclear
Living area2,519 SF3,110 SF3,435 SF3,326 SFunclear
Days on market52 days47 days33 days56 daysunclear
Discount from original list4.5%7.3%7.0%6.4%unclear
Price cut before sale33%44%44%33%unclear
Seller paid closing costs or repairs67%67%78%56%unclear
Has a view44%67%56%56%unclear

5.3 Net sale price: no clear difference

2026-11-07T07:00:45.413566 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1994 9 sales 1994– 1997 9 sales 1998– 2001 9 sales After 2001 9 sales $0K $250K $500K $750K $536K $679K $731K $668K Net sale price, average

The average is $668K for homes built after 2001 and $536K for homes built before 1994. It does not move in a straight line; homes built 1998–2001 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-07T07:00:45.438112 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1994 9 sales 1994– 1997 9 sales 1998– 2001 9 sales After 2001 9 sales $0 $100 $200 $215 $213 $207 $200 Net price per SF, average

The average is $200 per SF for homes built after 2001 and $215 per SF for homes built before 1994. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-07T07:00:45.459769 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1994 9 sales 1994– 1997 9 sales 1998– 2001 9 sales After 2001 9 sales 0 2,000 4,000 2,519 3,110 3,435 3,326 Living area (SF), average

The average is 3,326 SF for homes built after 2001 and 2,519 SF for homes built before 1994. It does not move in a straight line; homes built 1998–2001 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-07T07:00:45.481865 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1994 9 sales 1994– 1997 9 sales 1998– 2001 9 sales After 2001 9 sales 0 20 40 60 52 47 33 56 Days on market, median

The median is 56 days for homes built after 2001 and 52 days for homes built before 1994. It does not move in a straight line; homes built after 2001 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-07T07:00:45.505481 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1994 9 sales 1994– 1997 9 sales 1998– 2001 9 sales After 2001 9 sales 0.0% 2.5% 5.0% 7.5% 4.5% 7.3% 7.0% 6.4% Discount from original list, average

The average is 6.4% for homes built after 2001 and 4.5% for homes built before 1994. It does not move in a straight line; homes built 1994–1997 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

2026-11-07T07:00:45.531631 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 67 44 44 67 67 44 78 56 33 56 56 Before 1994 1994–1997 1998–2001 After 2001

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

  • 33% of homes built after 2001 had a price cut before sale, against 33% of homes built before 1994. Defined in 8.1.7.
  • 56% of homes built after 2001 had the seller pay closing costs or repairs, against 67% of homes built before 1994. Defined in 8.1.8.
  • 56% of homes built after 2001 have a view, against 44% of homes built before 1994. 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 19949 sales1994–19979 sales1998–20019 salesAfter 20019 salesAll36 salesReal difference?
Net sale price average$536,022$679,244$730,774$668,102$653,536unclear
Net price per SF average$215$213$207$200$209unclear
Living area average2,5193,1103,4353,3263,098unclear
Year built median19921996200020141998by design

5.10 The numbers: selling

Before 19949 sales1994–19979 sales1998–20019 salesAfter 20019 salesAll36 salesReal difference?
Days on market median5247335650unclear
Discount from original list average4.5%7.3%7.0%6.4%6.3%unclear
Price cut before sale33%44%44%33%39%unclear
Seller paid closing costs or repairs67%67%78%56%67%unclear
Has a view44%67%56%56%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 8.3.3.

6. View and no viewResale homes · 36 sales · November 7, 2025 – November 6, 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.

2026-11-07T07:00:45.550923 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 20 15 35 sales Sales per group View: 20 sales (57%) No view: 15 sales (43%)
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$736K$543Kunclear
Net price per SF$226 per SF$190 per SFunclear
Living area3,209 SF2,882 SFunclear
Year built19981997unclear
Days on market34 days52 daysunclear
Discount from original list5.8%6.9%unclear
Price cut before sale30%47%unclear
Seller paid closing costs or repairs75%53%unclear

6.3 Net sale price: no clear difference

2026-11-07T07:00:45.568493 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 20 sales No view 15 sales $0K $200K $400K $600K $800K $736K $543K Net sale price, average

The average is $736K for homes with a view and $543K 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

2026-11-07T07:00:45.587526 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 20 sales No view 15 sales $0 $100 $200 $226 $190 Net price per SF, average

The average is $226 per SF for homes with a view and $190 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

2026-11-07T07:00:45.604831 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 20 sales No view 15 sales 0 1,000 2,000 3,000 3,209 2,882 Living area (SF), average

The average is 3,209 SF for homes with a view and 2,882 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-07T07:00:45.666723 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 20 sales No view 15 sales 1994 1996 1998 2000 2002 1998 1997 Year built: median (dot) and middle half (bar)

The median is 1998 for homes with a view and 1997 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-07T07:00:45.685090 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 20 sales No view 15 sales 0 20 40 60 34 52 Days on market, median

The median is 34 days for homes with a view and 52 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

2026-11-07T07:00:45.704851 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 20 sales No view 15 sales 0.0% 2.0% 4.0% 6.0% 8.0% 5.8% 6.9% Discount from original list, average

The average is 5.8% for homes with a view and 6.9% 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

2026-11-07T07:00:45.724881 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 30 75 47 53 View No view

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

  • 30% of homes with a view had a price cut before sale, against 47% 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 53% 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

View20 salesNo view15 salesAll35 salesReal difference?
Net sale price average$735,904$542,847$653,165unclear
Net price per SF average$226$190$210unclear
Living area average3,2092,8823,069unclear
Year built median199819971997unclear

6.11 The numbers: selling

View20 salesNo view15 salesAll35 salesReal difference?
Days on market median345247unclear
Discount from original list average5.8%6.9%6.3%unclear
Price cut before sale30%47%37%unclear
Seller paid closing costs or repairs75%53%66%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 · November 7, 2025 – November 6, 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 Berry 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
36 resale sales. Average $653,536; median $587,000; standard deviation $275,987; middle half (25th–75th percentile) $491,125–$727,500; lowest $340,000, highest $1,596,575. 24 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
36 resale sales. Average $209; median $209; standard deviation $47; middle half (25th–75th percentile) $178–$221; lowest $139, highest $354.

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
36 resale sales. Average 3,098; median 3,036; standard deviation 795; middle half (25th–75th percentile) 2,724–3,606; lowest 1,578, highest 4,991.

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
36 resale sales. Average 1999; median 1998; standard deviation 8; middle half (25th–75th percentile) 1994–2002; lowest 1986, highest 2016.

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
36 resale sales. Average 98; median 50; standard deviation 113; middle half (25th–75th percentile) 16–172; lowest 0, highest 509. 1 sales went under contract on their listing date (0 days).

8.1.6 Discount from original list

In simple terms
How far below the first asking price the home sold, after seller payments. It measures how much negotiating room sellers gave up. A negative figure means the home sold above its first asking price.
Statistically
Discount % = (OriginalListPrice − Net) ÷ OriginalListPrice × 100, per sale; summarized by the mean.
The data
36 resale sales. Average 6.3%; median 4.3%; standard deviation 6.4%; middle half (25th–75th percentile) 1.0%–9.7%; lowest −0.2%, highest 25.2%. 1 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
14 of 36 resale sales (38.9%).

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
24 of 36 resale sales (66.7%).

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
20 sales with a view, 15 without, 1 unclassified. Most common View entries: Golf Course 11, Neighborhood 10, None 7, Trees/Woods 7, Pool 4, See Remarks 2, Pond 2, Panoramic 2.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-07 13:00 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Georgetown, SubdivisionName contains any of “berry creek”, “berry crk” (case-insensitive). A record is kept when its subdivision name belongs to the Berry Creek family, the same rule comparable sales use.
The data
Pulled November 7, 2026: 36 closed Berry Creek records over the prior year, in ZIP 78628. 18 subdivision spellings kept, the most common: Berry Creek (11); Berry Creek Sec 04 (3); Berry Creek Sec 09 Ph 03 Rev (2); BERRY CREEK (2); Berry Creek Sec 11 Ph 02 (2); Berry Creek Sec 03 Resub (2); Berry Creek Sec 01 (2); Berry Creek Sec 02 (2); Berry Creek Sec 07 Ph 01 Resub (1); Berry Creek Sec 11 Ph 03 (1); Berry creek (1); Berry Crk Sub Ph 2 Sec 5 (1); and 6 more (6 records). Names found by the search but not part of Berry Creek, left out: Berry Creek Highlands (48); Hidden Oaks At Berry Creek (5); Villages Of Berry Creek Sec 01 (3); Hidden Oaks at Berry Creek (3); Villages Berry Creek Sec 2A (3); Berry Crk Hlnds Ph 1B (2); Reserve at Berry Creek (2); Woods At Berry Creek Sec 02 (1); Reserve At Berry Creek Ph 02 (1); Villages Of Berry Creek Sec 2B (1); The Reserve at Berry Creek (1); Woods at Berry Creek (1); Reserve/Berry Crk Ph 02 (1); Woods/Berry Crk Sec 03 (1); Reserve At Berry Creek Sec 01A Ph 01 (1); Woods At Berry Creek Sec 03 (1); Meadows End At Berry Creek Berry Creek Sec 01 (1); Reserve/Berry Crk Sec 4 (1); Woods Berry Creek Ph 01 (1); Villages Berry Creek Sec 2a (1); Villages Of Berry Creek Sec 2A (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 19 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 7, 2025 to November 6, 2026 inclusive.
The data
36 single-family sales in the window: 36 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
36 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 $492K”.
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 $492K: $340,000–$487,000 (9 sales); $492K–$580K: $492,500–$580,000 (9 sales); $594K–$720K: $594,000–$720,000 (9 sales); Over $720K: $750,000–$1,596,575 (9 sales)
Quartiles by living area: Under 2,783 SF: 1,578–2,546 SF (9 sales); 2,783–3,023 SF: 2,783–3,023 SF (9 sales); 3,050–3,540 SF: 3,050–3,540 SF (9 sales); Over 3,540 SF: 3,803–4,991 SF (9 sales)
Quartiles by year built: Before 1994: 1986–1993 (9 sales); 1994–1997: 1994–1997 (9 sales); 1998–2001: 1998–2001 (9 sales); After 2001: 2003–2016 (9 sales)
View and no view: View: MLS lists a view (20 sales); No view: None or Neighborhood (15 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 $653,536, median $587,000. Days on market: average 98, median 50: 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 = 7.3330.0621p < 0.0063Unclearε² = 0.209large
Living areaKruskal–WallisH = 21.253< 0.0001p < 0.0063Yesε² = 0.607large
Year builtKruskal–WallisH = 3.0630.3826p < 0.0063Unclearε² = 0.087medium
Days on marketKruskal–WallisH = 2.0030.5714p < 0.0063Unclearε² = 0.057small
Discount from original listKruskal–WallisH = 1.9130.5917p < 0.0063Unclearε² = 0.055small
Price cut before saleChi-squareχ² = 4.2130.2399p < 0.0063UnclearCramér’s V = 0.342medium
Seller paid closing costs or repairsChi-squareχ² = 3.0030.3916p < 0.0063UnclearCramér’s V = 0.289small
Has a viewChi-squareχ² = 5.4030.1447p < 0.0063UnclearCramér’s V = 0.387medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 24.843< 0.0001p < 0.0063Yesε² = 0.710large
Net price per SFKruskal–WallisH = 7.3630.0612p < 0.0063Unclearε² = 0.210large
Year builtKruskal–WallisH = 7.5030.0576p < 0.0063Unclearε² = 0.214large
Days on marketKruskal–WallisH = 0.9130.8234p < 0.0063Unclearε² = 0.026small
Discount from original listKruskal–WallisH = 1.5630.6686p < 0.0063Unclearε² = 0.045small
Price cut before saleChi-squareχ² = 1.4030.7049p < 0.0063UnclearCramér’s V = 0.197small
Seller paid closing costs or repairsChi-squareχ² = 3.0030.3916p < 0.0063UnclearCramér’s V = 0.289small
Has a viewChi-squareχ² = 3.6030.3080p < 0.0063UnclearCramér’s V = 0.316medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 2.5730.4621p < 0.0063Unclearε² = 0.074medium
Net price per SFKruskal–WallisH = 2.3530.5035p < 0.0063Unclearε² = 0.067medium
Living areaKruskal–WallisH = 8.5830.0355p < 0.0063Unclearε² = 0.245large
Days on marketKruskal–WallisH = 0.6230.8919p < 0.0063Unclearε² = 0.018small
Discount from original listKruskal–WallisH = 2.3130.5101p < 0.0063Unclearε² = 0.066medium
Price cut before saleChi-squareχ² = 0.4730.9260p < 0.0063UnclearCramér’s V = 0.114small
Seller paid closing costs or repairsChi-squareχ² = 1.0030.8013p < 0.0063UnclearCramér’s V = 0.167small
Has a viewChi-squareχ² = 0.9030.8254p < 0.0063UnclearCramér’s V = 0.158small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 207.00—0.0597p < 0.0063Unclearrank-biserial r = 0.380medium
Net price per SFMann–Whitney UU = 220.00—0.0205p < 0.0063Unclearrank-biserial r = 0.467medium
Living areaMann–Whitney UU = 191.00—0.1770p < 0.0063Unclearrank-biserial r = 0.273small
Year builtMann–Whitney UU = 161.50—0.7130p < 0.0063Unclearrank-biserial r = 0.077negligible
Days on marketMann–Whitney UU = 133.00—0.5823p < 0.0063Unclearrank-biserial r = 0.113small
Discount from original listMann–Whitney UU = 148.00—0.9601p < 0.0063Unclearrank-biserial r = 0.013negligible
Price cut before saleChi-squareχ² = 1.0210.3126p < 0.0063UnclearCramér’s V = 0.171small
Seller paid closing costs or repairsChi-squareχ² = 1.7910.1814p < 0.0063UnclearCramér’s V = 0.226small

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 36 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 November 7, 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.