ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Berry Creek

Georgetown, TX 78628
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
34
single-family resale homes
Median net sale price
$582,708
average $651,974
Median net price per SF
$209
average $209
Median days on market
42 days
average 95 days
1. SummaryResale homes · 34 sales · October 26, 2025 – October 25, 2026

This study looks at the 34 resale homes sold in Berry Creek in the 365 days to October 25, 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 sold34 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 $480K · 8 sales$480K–$571K · 9 sales$594K–$720K · 9 salesOver $720K · 8 sales
3. Quartiles by net sale priceResale homes · 34 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.

2026-10-26T06:59:41.531103 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 9 9 8 34 sales Sales per group Under $480K: 8 sales (24%) $480K–$571K: 9 sales (26%) $594K–$720K: 9 sales (26%) Over $720K: 8 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 $480K$480K–$571K$594K–$720KOver $720K
Higher-priced homes Over $720K
  • Are much larger.
Lower-priced homes Under $480K
  • 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 $480K$480K–$571K$594K–$720KOver $720KReal difference?
Net price per SF$196 per SF$190 per SF$200 per SF$255 per SFunclear
Living area2,238 SFSmallest2,801 SF3,211 SF4,092 SFLargest✓ large
Year built2000199719942000unclear
Days on market88 days52 days47 days31 daysunclear
Discount from original list5.4%8.6%5.8%4.7%unclear
Price cut before sale50%33%56%12%unclear
Seller paid closing costs or repairs50%78%78%62%unclear
Has a view50%33%44%88%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

2026-10-26T06:59:41.559613 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $480K 8 sales $480K– $571K 9 sales $594K– $720K 9 sales Over $720K 8 sales $0 $100 $200 $300 $196 $190 $200 $255 Net price per SF, average

The average is $255 per SF for homes over $720K and $196 per SF for homes under $480K. 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 1,850 SF (83%) larger than homes under $480K

2026-10-26T06:59:41.582202 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $480K 8 sales $480K– $571K 9 sales $594K– $720K 9 sales Over $720K 8 sales 0 2,000 4,000 2,238 2,801 3,211 4,092 Living area (SF), average

The average is 4,092 SF for homes over $720K and 2,238 SF for homes under $480K. 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

2026-10-26T06:59:41.607459 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $480K 8 sales $480K– $571K 9 sales $594K– $720K 9 sales Over $720K 8 sales 1995 2000 2005 2010 2015 2000 1997 1994 2000 Year built: median (dot) and middle half (bar)

The median is 2000 for homes over $720K and 2000 for homes under $480K. 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

2026-10-26T06:59:41.631028 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $480K 8 sales $480K– $571K 9 sales $594K– $720K 9 sales Over $720K 8 sales 0 50 100 88 52 47 31 Days on market, median

The median is 31 days for homes over $720K and 88 days for homes under $480K. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T06:59:41.653012 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $480K 8 sales $480K– $571K 9 sales $594K– $720K 9 sales Over $720K 8 sales 0.0% 5.0% 10.0% 5.4% 8.6% 5.8% 4.7% Discount from original list, average

The average is 4.7% for homes over $720K and 5.4% for homes under $480K. It does not move in a straight line; homes $480K–$571K 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

2026-10-26T06:59:41.682878 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% 50 50 50 33 78 33 56 78 44 12 62 88 Under $480K $480K–$571K $594K–$720K Over $720K

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

  • 12% of homes over $720K had a price cut before sale, against 50% of homes under $480K. Defined in 8.1.7.
  • 62% of homes over $720K had the seller pay closing costs or repairs, against 50% of homes under $480K. Defined in 8.1.8.
  • 88% of homes over $720K have a view, against 50% of homes under $480K. 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 $480K8 sales$480K–$571K9 sales$594K–$720K9 salesOver $720K8 salesAll34 salesReal difference?
Net sale price average$417,688$519,462$636,267$1,053,009$651,974by design
Net price per SF average$196$190$200$255$209unclear
Living area average2,2382,8013,2114,0923,081✓ large
Year built median20001997199420001998unclear

3.10 The numbers: selling

Under $480K8 sales$480K–$571K9 sales$594K–$720K9 salesOver $720K8 salesAll34 salesReal difference?
Days on market median8852473142unclear
Discount from original list average5.4%8.6%5.8%4.7%6.2%unclear
Price cut before sale50%33%56%12%38%unclear
Seller paid closing costs or repairs50%78%78%62%68%unclear
Has a view50%33%44%88%53%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 · 34 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.

2026-10-26T06:59:41.703556 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 9 9 8 34 sales Sales per group Under 2,546 SF: 8 sales (24%) 2,546–2,987 SF: 9 sales (26%) 3,023–3,803 SF: 9 sales (26%) Over 3,803 SF: 8 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 2,546 SF2,546–2,987 SF3,023–3,803 SFOver 3,803 SF
Larger homes Over 3,803 SF
  • Sell for much more.
Smaller homes Under 2,546 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 2,546 SF2,546–2,987 SF3,023–3,803 SFOver 3,803 SFReal difference?
Net sale price$432KLowest$534K$705K$946KHighest✓ large
Net price per SF$218 per SF$189 per SF$210 per SF$223 per SFunclear
Year built2000199319972000unclear
Days on market32 days52 days56 days32 daysunclear
Discount from original list3.7%5.6%8.6%6.6%unclear
Price cut before sale25%33%56%38%unclear
Seller paid closing costs or repairs62%67%67%75%unclear
Has a view62%33%44%75%unclear

4.3 Homes over 3,803 SF sell for about $514K (119%) more than homes under 2,546 SF

2026-10-26T06:59:41.724798 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,546 SF 8 sales 2,546– 2,987 SF 9 sales 3,023– 3,803 SF 9 sales Over 3,803 SF 8 sales $0K $500K $1.00M $432K $534K $705K $946K Net sale price, average

The average is $946K for homes over 3,803 SF and $432K for homes under 2,546 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

2026-10-26T06:59:41.747620 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,546 SF 8 sales 2,546– 2,987 SF 9 sales 3,023– 3,803 SF 9 sales Over 3,803 SF 8 sales $0 $100 $200 $218 $189 $210 $223 Net price per SF, average

The average is $223 per SF for homes over 3,803 SF and $218 per SF for homes under 2,546 SF. It does not move in a straight line; homes over 3,803 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T06:59:41.772245 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,546 SF 8 sales 2,546– 2,987 SF 9 sales 3,023– 3,803 SF 9 sales Over 3,803 SF 8 sales 1992 1996 2000 2004 2008 2000 1993 1997 2000 Year built: median (dot) and middle half (bar)

The median is 2000 for homes over 3,803 SF and 2000 for homes under 2,546 SF. It does not move in a straight line; homes under 2,546 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T06:59:41.795276 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,546 SF 8 sales 2,546– 2,987 SF 9 sales 3,023– 3,803 SF 9 sales Over 3,803 SF 8 sales 0 20 40 60 32 52 56 32 Days on market, median

The median is 32 days for homes over 3,803 SF and 32 days for homes under 2,546 SF. It does not move in a straight line; homes 3,023–3,803 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T06:59:41.817723 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,546 SF 8 sales 2,546– 2,987 SF 9 sales 3,023– 3,803 SF 9 sales Over 3,803 SF 8 sales 0.0% 5.0% 10.0% 3.7% 5.6% 8.6% 6.6% Discount from original list, average

The average is 6.6% for homes over 3,803 SF and 3.7% for homes under 2,546 SF. It does not move in a straight line; homes 3,023–3,803 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

2026-10-26T06:59:41.843979 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% 25 62 62 33 67 33 56 67 44 38 75 75 Under 2,546 SF 2,546–2,987 SF 3,023–3,803 SF Over 3,803 SF

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

  • 38% of homes over 3,803 SF had a price cut before sale, against 25% of homes under 2,546 SF. Defined in 8.1.7.
  • 75% of homes over 3,803 SF had the seller pay closing costs or repairs, against 62% of homes under 2,546 SF. Defined in 8.1.8.
  • 75% of homes over 3,803 SF have a view, against 62% of homes under 2,546 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 2,546 SF8 sales2,546–2,987 SF9 sales3,023–3,803 SF9 salesOver 3,803 SF8 salesAll34 salesReal difference?
Net sale price average$432,005$533,767$704,522$945,811$651,974✓ large
Net price per SF average$218$189$210$223$209unclear
Living area average2,0002,8293,3204,1763,081by design
Year built median20001993199720001998unclear

4.10 The numbers: selling

Under 2,546 SF8 sales2,546–2,987 SF9 sales3,023–3,803 SF9 salesOver 3,803 SF8 salesAll34 salesReal difference?
Days on market median3252563242unclear
Discount from original list average3.7%5.6%8.6%6.6%6.2%unclear
Price cut before sale25%33%56%38%38%unclear
Seller paid closing costs or repairs62%67%67%75%68%unclear
Has a view62%33%44%75%53%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 · 34 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.

2026-10-26T06:59:41.864568 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 10 9 8 34 sales Sales per group Before 1994: 7 sales (21%) 1994–1998: 10 sales (29%) 1999–2003: 9 sales (26%) After 2003: 8 sales (24%)
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 19941994–19981999–2003After 2003Real difference?
Net sale price$509K$653K$778K$634Kunclear
Net price per SF$208 per SF$206 per SF$215 per SF$209 per SFunclear
Living area2,489 SF3,092 SF3,563 SF3,042 SFunclear
Days on market52 days70 days32 days46 daysunclear
Discount from original list5.6%7.9%5.7%5.2%unclear
Price cut before sale43%50%33%25%unclear
Seller paid closing costs or repairs71%70%78%50%unclear
Has a view43%60%56%50%unclear

5.3 Net sale price: no clear difference

2026-10-26T06:59:41.885954 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1994 7 sales 1994– 1998 10 sales 1999– 2003 9 sales After 2003 8 sales $0K $250K $500K $750K $509K $653K $778K $634K Net sale price, average

The average is $634K for homes built after 2003 and $509K for homes built before 1994. It does not move in a straight line; homes built 1999–2003 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T06:59:41.909362 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1994 7 sales 1994– 1998 10 sales 1999– 2003 9 sales After 2003 8 sales $0 $100 $200 $208 $206 $215 $209 Net price per SF, average

The average is $209 per SF for homes built after 2003 and $208 per SF for homes built before 1994. It does not move in a straight line; homes built 1999–2003 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T06:59:41.930804 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1994 7 sales 1994– 1998 10 sales 1999– 2003 9 sales After 2003 8 sales 0 2,000 4,000 2,489 3,092 3,563 3,042 Living area (SF), average

The average is 3,042 SF for homes built after 2003 and 2,489 SF for homes built before 1994. It does not move in a straight line; homes built 1999–2003 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T06:59:41.953373 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1994 7 sales 1994– 1998 10 sales 1999– 2003 9 sales After 2003 8 sales 0 25 50 75 52 70 32 46 Days on market, median

The median is 46 days for homes built after 2003 and 52 days for homes built before 1994. It does not move in a straight line; homes built 1994–1998 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T06:59:41.975876 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1994 7 sales 1994– 1998 10 sales 1999– 2003 9 sales After 2003 8 sales 0.0% 2.5% 5.0% 7.5% 5.6% 7.9% 5.7% 5.2% Discount from original list, average

The average is 5.2% for homes built after 2003 and 5.6% for homes built before 1994. It does not move in a straight line; homes built 1994–1998 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

2026-10-26T06:59:42.002287 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 71 43 50 70 60 33 78 56 25 50 50 Before 1994 1994–1998 1999–2003 After 2003

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

  • 25% of homes built after 2003 had a price cut before sale, against 43% of homes built before 1994. Defined in 8.1.7.
  • 50% of homes built after 2003 had the seller pay closing costs or repairs, against 71% of homes built before 1994. Defined in 8.1.8.
  • 50% of homes built after 2003 have a view, against 43% 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 19947 sales1994–199810 sales1999–20039 salesAfter 20038 salesAll34 salesReal difference?
Net sale price average$509,171$652,820$778,441$633,594$651,974unclear
Net price per SF average$208$206$215$209$209unclear
Living area average2,4893,0923,5633,0423,081unclear
Year built median19921996200020141998by design

5.10 The numbers: selling

Before 19947 sales1994–199810 sales1999–20039 salesAfter 20038 salesAll34 salesReal difference?
Days on market median5270324642unclear
Discount from original list average5.6%7.9%5.7%5.2%6.2%unclear
Price cut before sale43%50%33%25%38%unclear
Seller paid closing costs or repairs71%70%78%50%68%unclear
Has a view43%60%56%50%53%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 · 34 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.

2026-10-26T06:59:42.020370 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 18 15 33 sales Sales per group View: 18 sales (55%) No view: 15 sales (45%)
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$743K$542Kunclear
Net price per SF$228 per SF$190 per SFunclear
Living area3,196 SF2,874 SFunclear
Year built19981998unclear
Days on market32 days52 daysunclear
Discount from original list5.3%7.2%unclear
Price cut before sale28%47%unclear
Seller paid closing costs or repairs72%60%unclear

6.3 Net sale price: no clear difference

2026-10-26T06:59:42.036879 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 15 sales $0K $200K $400K $600K $800K $743K $542K Net sale price, average

The average is $743K for homes with a view and $542K 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

2026-10-26T06:59:42.055022 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 15 sales $0 $100 $200 $228 $190 Net price per SF, average

The average is $228 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

2026-10-26T06:59:42.132910 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 15 sales 0 1,000 2,000 3,000 3,196 2,874 Living area (SF), average

The average is 3,196 SF for homes with a view and 2,874 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T06:59:42.151817 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 15 sales 1996 1999 2002 1998 1998 Year built: median (dot) and middle half (bar)

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

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T06:59:42.169017 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 15 sales 0 20 40 60 32 52 Days on market, median

The median is 32 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

2026-10-26T06:59:42.188110 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 15 sales 0.0% 2.0% 4.0% 6.0% 8.0% 5.3% 7.2% Discount from original list, average

The average is 5.3% for homes with a view and 7.2% 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

2026-10-26T06:59:42.207358 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 28 72 47 60 View No view

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

  • 28% of homes with a view had a price cut before sale, against 47% of homes without a view. Defined in 8.1.7.
  • 72% of homes with a view had the seller pay closing costs or repairs, against 60% 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

View18 salesNo view15 salesAll33 salesReal difference?
Net sale price average$743,227$541,503$651,534unclear
Net price per SF average$228$190$211unclear
Living area average3,1962,8743,050unclear
Year built median199819981998unclear

6.11 The numbers: selling

View18 salesNo view15 salesAll33 salesReal difference?
Days on market median325236unclear
Discount from original list average5.3%7.2%6.2%unclear
Price cut before sale28%47%36%unclear
Seller paid closing costs or repairs72%60%67%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 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
34 resale sales. Average $651,974; median $582,708; standard deviation $283,682; middle half (25th–75th percentile) $481,630–$706,625; lowest $340,000, highest $1,596,575. 23 sales had a seller payment; their median payment was $5,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
34 resale sales. Average $209; median $209; standard deviation $47; middle half (25th–75th percentile) $179–$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
34 resale sales. Average 3,081; median 3,005; standard deviation 820; middle half (25th–75th percentile) 2,605–3,734; 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
34 resale sales. Average 2000; 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
34 resale sales. Average 95; median 42; standard deviation 115; middle half (25th–75th percentile) 18–161; 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
34 resale sales. Average 6.2%; median 4.7%; standard deviation 6.0%; middle half (25th–75th percentile) 1.1%–9.4%; 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
13 of 34 resale sales (38.2%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
23 of 34 resale sales (67.6%).

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
18 sales with a view, 15 without, 1 unclassified. Most common View entries: Neighborhood 11, Golf Course 10, None 6, Trees/Woods 6, Pool 4, Pond 2, Pasture 1, See Remarks 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Georgetown, SubdivisionName contains any of “berry creek”, “berry crk”, “berry crk sub”, “berry creek sub” (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 October 26, 2026: 34 closed Berry Creek records over the prior year, in ZIP 78628. 18 subdivision spellings kept, the most common: Berry Creek (10); Berry Creek Sec 04 (3); Berry Creek Sec 01 (2); BERRY CREEK (2); Berry Creek Sec 09 Ph 03 Rev (2); Berry Creek Sec 03 Resub (2); Berry Creek Sec 11 Ph 02 (2); Berry Crk Sub Ph 2 Sec 5 (1); Berry Creek Sec 09 Ph 02 Rev (1); Berry Creek Sec 02 (1); Berry Creek Sec 08 Ph 01 Resub P ts Blk B K (1); Berry creek (1); and 6 more (6 records). Names found by the search but not part of Berry Creek, left out: Berry Creek Highlands (47); Hidden Oaks At Berry Creek (5); Villages Berry Creek Sec 2A (3); Villages Of Berry Creek Sec 01 (3); Hidden Oaks at Berry Creek (3); Reserve/Berry Crk Sec 4 (2); Reserve at Berry Creek (2); Berry Crk Hlnds Ph 1B (2); Village/Berry Crk Sec 01 (1); Villages of Berry Creek Sec 2A (1); Woods at Berry Creek (1); Woods At Berry Creek Sec 03 (1); Reserve At Berry Creek Ph 02 (1); Villages Of Berry Creek Sec 2A (1); Meadows End At Berry Creek Berry Creek Sec 01 (1); Villages Of Berry Creek Sec 2B (1); Reserve/Berry Crk Ph 02 (1); The Reserve at Berry Creek (1); Woods/Berry Crk Sec 03 (1); Reserve At Berry Creek Sec 01A Ph 01 (1); Woods Berry Creek Ph 01 (1); Villages Berry Creek Sec 2a (1); Woods At Berry Creek Sec 02 (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 October 26, 2025 to October 25, 2026 inclusive.
The data
34 single-family sales in the window: 34 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
34 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 $480K”.
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 $480K: $340,000–$460,000 (8 sales); $480K–$571K: $479,840–$571,416 (9 sales); $594K–$720K: $594,000–$720,000 (9 sales); Over $720K: $750,000–$1,596,575 (8 sales)
Quartiles by living area: Under 2,546 SF: 1,578–2,468 SF (8 sales); 2,546–2,987 SF: 2,546–2,987 SF (9 sales); 3,023–3,803 SF: 3,023–3,803 SF (9 sales); Over 3,803 SF: 3,885–4,991 SF (8 sales)
Quartiles by year built: Before 1994: 1986–1993 (7 sales); 1994–1998: 1994–1998 (10 sales); 1999–2003: 1999–2003 (9 sales); After 2003: 2005–2016 (8 sales)
View and no view: View: MLS lists a view (18 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 $651,974, median $582,708. Days on market: average 95, median 42: 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 = 5.6530.1302p < 0.0063Unclearε² = 0.171large
Living areaKruskal–WallisH = 21.753< 0.0001p < 0.0063Yesε² = 0.659large
Year builtKruskal–WallisH = 4.8830.1810p < 0.0063Unclearε² = 0.148large
Days on marketKruskal–WallisH = 2.7030.4395p < 0.0063Unclearε² = 0.082medium
Discount from original listKruskal–WallisH = 1.3430.7207p < 0.0063Unclearε² = 0.040small
Price cut before saleChi-squareχ² = 3.9530.2672p < 0.0063UnclearCramér’s V = 0.341medium
Seller paid closing costs or repairsChi-squareχ² = 2.0830.5561p < 0.0063UnclearCramér’s V = 0.247small
Has a viewChi-squareχ² = 5.5130.1379p < 0.0063UnclearCramér’s V = 0.403medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 23.303< 0.0001p < 0.0063Yesε² = 0.706large
Net price per SFKruskal–WallisH = 4.8530.1829p < 0.0063Unclearε² = 0.147large
Year builtKruskal–WallisH = 8.8530.0313p < 0.0063Unclearε² = 0.268large
Days on marketKruskal–WallisH = 0.7930.8510p < 0.0063Unclearε² = 0.024small
Discount from original listKruskal–WallisH = 2.1630.5394p < 0.0063Unclearε² = 0.066medium
Price cut before saleChi-squareχ² = 1.8330.6084p < 0.0063UnclearCramér’s V = 0.232small
Seller paid closing costs or repairsChi-squareχ² = 0.3030.9596p < 0.0063UnclearCramér’s V = 0.094negligible
Has a viewChi-squareχ² = 3.5130.3200p < 0.0063UnclearCramér’s V = 0.321medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 4.8530.1828p < 0.0063Unclearε² = 0.147large
Net price per SFKruskal–WallisH = 0.2830.9639p < 0.0063Unclearε² = 0.008negligible
Living areaKruskal–WallisH = 7.8430.0495p < 0.0063Unclearε² = 0.238large
Days on marketKruskal–WallisH = 1.4930.6851p < 0.0063Unclearε² = 0.045small
Discount from original listKruskal–WallisH = 1.5630.6682p < 0.0063Unclearε² = 0.047small
Price cut before saleChi-squareχ² = 1.3330.7210p < 0.0063UnclearCramér’s V = 0.198small
Seller paid closing costs or repairsChi-squareχ² = 1.6330.6523p < 0.0063UnclearCramér’s V = 0.219small
Has a viewChi-squareχ² = 0.5430.9104p < 0.0063UnclearCramér’s V = 0.126small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 183.00—0.0859p < 0.0063Unclearrank-biserial r = 0.356medium
Net price per SFMann–Whitney UU = 203.00—0.0147p < 0.0063Unclearrank-biserial r = 0.504large
Living areaMann–Whitney UU = 166.00—0.2701p < 0.0063Unclearrank-biserial r = 0.230small
Year builtMann–Whitney UU = 129.50—0.8561p < 0.0063Unclearrank-biserial r = 0.041negligible
Days on marketMann–Whitney UU = 105.00—0.2862p < 0.0063Unclearrank-biserial r = 0.222small
Discount from original listMann–Whitney UU = 120.50—0.6127p < 0.0063Unclearrank-biserial r = 0.107small
Price cut before saleChi-squareχ² = 1.2610.2614p < 0.0063UnclearCramér’s V = 0.196small
Seller paid closing costs or repairsChi-squareχ² = 0.5510.4583p < 0.0063UnclearCramér’s V = 0.129small

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 34 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.