ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Ranch At Deer Creek

Cedar Park, TX 78613
Resale homes · closed Nov 5 – Nov 4, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 5, 2026 · 3:45 PM 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
22
single-family resale homes
Median net sale price
$673,250
average $720,124
Median net price per SF
$209
average $210
Median days on market
50 days
average 62 days
1. SummaryResale homes · 22 sales · November 5, 2025 – November 4, 2026

This study looks at the 22 resale homes sold in Ranch At Deer Creek in the 365 days to November 4, 2026. A full year is used because only 15 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 sold22 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 $610K · 6 sales$610K–$656K · 5 sales$690K–$832K · 5 salesOver $832K · 6 sales
3. Quartiles by net sale priceResale homes · 22 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T15:45:20.893990 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 5 5 6 22 sales Sales per group Under $610K: 6 sales (27%) $610K–$656K: 5 sales (23%) $690K–$832K: 5 sales (23%) Over $832K: 6 sales (27%)
Bottom line: no measure differs enough between the groups to rule out chance.

3.1 Key differences

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

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 $610K$610K–$656K$690K–$832KOver $832KReal difference?
Net price per SF$196 per SF$195 per SF$214 per SF$234 per SFunclear
Living area2,933 SF3,240 SF3,641 SF3,932 SFunclear
Year built2004200520022002unclear
Days on market28 days96 days72 days52 daysunclear
Discount from original list-14.0%6.9%5.0%5.2%unclear
Price cut before sale17%80%40%50%unclear
Seller paid closing costs or repairs67%60%60%100%unclear
Has a view17%20%20%33%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

2026-11-05T15:45:20.922726 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $610K 6 sales $610K– $656K 5 sales $690K– $832K 5 sales Over $832K 6 sales $0 $100 $200 $196 $195 $214 $234 Net price per SF, average

The average is $234 per SF for homes over $832K and $196 per SF for homes under $610K. It does not move in a straight line; homes over $832K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-11-05T15:45:20.944903 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $610K 6 sales $610K– $656K 5 sales $690K– $832K 5 sales Over $832K 6 sales 0 2,000 4,000 2,933 3,240 3,641 3,932 Living area (SF), average

The average is 3,932 SF for homes over $832K and 2,933 SF for homes under $610K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-11-05T15:45:20.967465 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $610K 6 sales $610K– $656K 5 sales $690K– $832K 5 sales Over $832K 6 sales 2002 2004 2006 2004 2005 2002 2002 Year built: median (dot) and middle half (bar)

The median is 2002 for homes over $832K and 2004 for homes under $610K. It does not move in a straight line; homes $610K–$656K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-05T15:45:20.989950 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $610K 6 sales $610K– $656K 5 sales $690K– $832K 5 sales Over $832K 6 sales 0 50 100 28 96 72 52 Days on market, median

The median is 52 days for homes over $832K and 28 days for homes under $610K. It does not move in a straight line; homes $610K–$656K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-05T15:45:21.010699 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $610K 6 sales $610K– $656K 5 sales $690K– $832K 5 sales Over $832K 6 sales -10.0% 0.0% -14.0% 6.9% 5.0% 5.2% Discount from original list, average

The average is 5.2% for homes over $832K and -14.0% for homes under $610K. It does not move in a straight line; homes $610K–$656K 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

2026-11-05T15:45:21.039933 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% 17 67 17 80 60 20 40 60 20 50 100 33 Under $610K $610K–$656K $690K–$832K Over $832K

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

  • 50% of homes over $832K had a price cut before sale, against 17% of homes under $610K. Defined in 8.1.7.
  • 100% of homes over $832K had the seller pay closing costs or repairs, against 67% of homes under $610K. Defined in 8.1.8.
  • 33% of homes over $832K have a view, against 17% of homes under $610K. 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 $610K6 sales$610K–$656K5 sales$690K–$832K5 salesOver $832K6 salesAll22 salesReal difference?
Net sale price average$567,740$627,160$767,960$910,114$720,124by design
Net price per SF average$196$195$214$234$210unclear
Living area average2,9333,2403,6413,9323,436unclear
Year built median20042005200220022003unclear

3.10 The numbers: selling

Under $610K6 sales$610K–$656K5 sales$690K–$832K5 salesOver $832K6 salesAll22 salesReal difference?
Days on market median2896725250unclear
Discount from original list average−14.0%6.9%5.0%5.2%0.3%unclear
Price cut before sale17%80%40%50%45%unclear
Seller paid closing costs or repairs67%60%60%100%73%unclear
Has a view17%20%20%33%23%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 · 22 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T15:45:21.060159 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 5 5 6 22 sales Sales per group Under 3,063 SF: 6 sales (27%) 3,063–3,368 SF: 5 sales (23%) 3,391–3,784 SF: 5 sales (23%) Over 3,784 SF: 6 sales (27%)
Bottom line: no measure differs enough between the groups to rule out chance.

4.1 Key differences

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

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 3,063 SF3,063–3,368 SF3,391–3,784 SFOver 3,784 SFReal difference?
Net sale price$592K$735K$677K$871Kunclear
Net price per SF$210 per SF$228 per SF$189 per SF$212 per SFunclear
Year built2004200220042003unclear
Days on market37 days37 days96 days57 daysunclear
Discount from original list4.3%6.4%-14.9%4.0%unclear
Price cut before sale33%40%80%33%unclear
Seller paid closing costs or repairs50%60%80%100%unclear
Has a view0%60%20%17%unclear

4.3 Net sale price: no clear difference

2026-11-05T15:45:21.080813 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,063 SF 6 sales 3,063– 3,368 SF 5 sales 3,391– 3,784 SF 5 sales Over 3,784 SF 6 sales $0K $500K $1.00M $592K $735K $677K $871K Net sale price, average

The average is $871K for homes over 3,784 SF and $592K for homes under 3,063 SF. It does not move in a straight line; homes over 3,784 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-11-05T15:45:21.103401 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,063 SF 6 sales 3,063– 3,368 SF 5 sales 3,391– 3,784 SF 5 sales Over 3,784 SF 6 sales $0 $100 $200 $210 $228 $189 $212 Net price per SF, average

The average is $212 per SF for homes over 3,784 SF and $210 per SF for homes under 3,063 SF. It does not move in a straight line; homes 3,063–3,368 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-05T15:45:21.125599 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,063 SF 6 sales 3,063– 3,368 SF 5 sales 3,391– 3,784 SF 5 sales Over 3,784 SF 6 sales 2002 2004 2006 2004 2002 2004 2003 Year built: median (dot) and middle half (bar)

The median is 2003 for homes over 3,784 SF and 2004 for homes under 3,063 SF. It does not move in a straight line; homes under 3,063 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-05T15:45:21.147841 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,063 SF 6 sales 3,063– 3,368 SF 5 sales 3,391– 3,784 SF 5 sales Over 3,784 SF 6 sales 0 50 100 37 37 96 57 Days on market, median

The median is 57 days for homes over 3,784 SF and 37 days for homes under 3,063 SF. It does not move in a straight line; homes 3,391–3,784 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-05T15:45:21.168598 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,063 SF 6 sales 3,063– 3,368 SF 5 sales 3,391– 3,784 SF 5 sales Over 3,784 SF 6 sales -10.0% 0.0% 4.3% 6.4% -14.9% 4.0% Discount from original list, average

The average is 4.0% for homes over 3,784 SF and 4.3% for homes under 3,063 SF. It does not move in a straight line; homes 3,063–3,368 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

2026-11-05T15:45:21.194170 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 50 0 40 60 60 80 80 20 33 100 17 Under 3,063 SF 3,063–3,368 SF 3,391–3,784 SF Over 3,784 SF

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

  • 33% of homes over 3,784 SF had a price cut before sale, against 33% of homes under 3,063 SF. Defined in 8.1.7.
  • 100% of homes over 3,784 SF had the seller pay closing costs or repairs, against 50% of homes under 3,063 SF. Defined in 8.1.8.
  • 17% of homes over 3,784 SF have a view, against 0% of homes under 3,063 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 3,063 SF6 sales3,063–3,368 SF5 sales3,391–3,784 SF5 salesOver 3,784 SF6 salesAll22 salesReal difference?
Net sale price average$592,117$734,968$677,404$871,360$720,124unclear
Net price per SF average$210$228$189$212$210unclear
Living area average2,8253,2103,5694,1243,436by design
Year built median20042002200420032003unclear

4.10 The numbers: selling

Under 3,063 SF6 sales3,063–3,368 SF5 sales3,391–3,784 SF5 salesOver 3,784 SF6 salesAll22 salesReal difference?
Days on market median3737965750unclear
Discount from original list average4.3%6.4%−14.9%4.0%0.3%unclear
Price cut before sale33%40%80%33%45%unclear
Seller paid closing costs or repairs50%60%80%100%73%unclear
Has a view0%60%20%17%23%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 · 22 sales · November 5, 2025 – November 4, 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.

2026-11-05T15:45:21.214215 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 4 6 6 22 sales Sales per group Before 2002: 6 sales (27%) 2002: 4 sales (18%) 2003–2004: 6 sales (27%) After 2004: 6 sales (27%)
Bottom line: too few sales to test.

5.1 Key differences

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

5.3 Net sale price: described, not tested

2026-11-05T15:45:21.234206 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 6 sales 2002 4 sales 2003– 2004 6 sales After 2004 6 sales $0K $250K $500K $750K $774K $747K $743K $626K Net sale price, average

The average is $626K for homes built after 2004 and $774K for homes built before 2002. It falls step by step from the lowest range to the highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-11-05T15:45:21.256535 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 6 sales 2002 4 sales 2003– 2004 6 sales After 2004 6 sales $0 $100 $200 $226 $214 $205 $197 Net price per SF, average

The average is $197 per SF for homes built after 2004 and $226 per SF for homes built before 2002. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-11-05T15:45:21.276979 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 6 sales 2002 4 sales 2003– 2004 6 sales After 2004 6 sales 0 2,000 4,000 3,450 3,482 3,583 3,245 Living area (SF), average

The average is 3,245 SF for homes built after 2004 and 3,450 SF for homes built before 2002. It does not move in a straight line; homes built 2003–2004 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-11-05T15:45:21.297831 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 6 sales 2002 4 sales 2003– 2004 6 sales After 2004 6 sales 0 50 100 45 24 40 92 Days on market, median

The median is 92 days for homes built after 2004 and 45 days for homes built before 2002. It does not move in a straight line; homes built after 2004 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-11-05T15:45:21.318330 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 6 sales 2002 4 sales 2003– 2004 6 sales After 2004 6 sales -10.0% 0.0% 7.4% 1.2% -14.4% 7.3% Discount from original list, average

The average is 7.3% for homes built after 2004 and 7.4% for homes built before 2002. It does not move in a straight line; homes built before 2002 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-11-05T15:45:21.342766 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 67 33 25 75 25 33 83 17 67 67 17 Before 2002 2002 2003–2004 After 2004

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

  • 67% of homes built after 2004 had a price cut before sale, against 50% of homes built before 2002. Defined in 8.1.7.
  • 67% of homes built after 2004 had the seller pay closing costs or repairs, against 67% of homes built before 2002. Defined in 8.1.8.
  • 17% of homes built after 2004 have a view, against 33% of homes built before 2002. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

5.9 The numbers: price and size

Before 20026 sales20024 sales2003–20046 salesAfter 20046 salesAll22 sales
Net sale price average$774,000$746,566$742,543$626,200$720,124
Net price per SF average$226$214$205$197$210
Living area average3,4503,4823,5833,2453,436
Year built median20012002200420062003

5.10 The numbers: selling

Before 20026 sales20024 sales2003–20046 salesAfter 20046 salesAll22 sales
Days on market median4524409250
Discount from original list average7.4%1.2%−14.4%7.3%0.3%
Price cut before sale50%25%33%67%45%
Seller paid closing costs or repairs67%75%83%67%73%
Has a view33%25%17%17%23%

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 · 22 sales · November 5, 2025 – November 4, 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.

2026-11-05T15:45:21.361119 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 16 21 sales Sales per group View: 5 sales (24%) No view: 16 sales (76%)
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$793K$686Kunclear
Net price per SF$231 per SF$204 per SFunclear
Living area3,434 SF3,362 SFunclear
Year built20022004unclear
Days on market42 days50 daysunclear
Discount from original list7.8%-2.6%unclear
Price cut before sale40%44%unclear
Seller paid closing costs or repairs80%69%unclear

6.3 Net sale price: no clear difference

2026-11-05T15:45:21.377596 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 16 sales $0K $200K $400K $600K $800K $793K $686K Net sale price, average

The average is $793K for homes with a view and $686K 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

2026-11-05T15:45:21.395678 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 16 sales $0 $100 $200 $231 $204 Net price per SF, average

The average is $231 per SF for homes with a view and $204 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

2026-11-05T15:45:21.414099 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 16 sales 0 1,000 2,000 3,000 4,000 3,434 3,362 Living area (SF), average

The average is 3,434 SF for homes with a view and 3,362 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-05T15:45:21.456246 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 16 sales 2001 2002 2003 2004 2005 2002 2004 Year built: median (dot) and middle half (bar)

The median is 2002 for homes with a view and 2004 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-05T15:45:21.475018 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 16 sales 0 20 40 60 42 50 Days on market, median

The median is 42 days for homes with a view and 50 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

2026-11-05T15:45:21.494413 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 16 sales -2.5% 0.0% 2.5% 5.0% 7.5% 7.8% -2.6% Discount from original list, average

The average is 7.8% for homes with a view and -2.6% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

6.9 How often: price cut before sale, seller paid closing costs or repairs

2026-11-05T15:45:21.513119 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 40 80 44 69 View No view

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

  • 40% of homes with a view had a price cut before sale, against 44% of homes without a view. Defined in 8.1.7.
  • 80% of homes with a view had the seller pay closing costs or repairs, against 69% 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

View5 salesNo view16 salesAll21 salesReal difference?
Net sale price average$792,508$686,093$711,430unclear
Net price per SF average$231$204$211unclear
Living area average3,4343,3623,379unclear
Year built median200220042003unclear

6.11 The numbers: selling

View5 salesNo view16 salesAll21 salesReal difference?
Days on market median425047unclear
Discount from original list average7.8%−2.6%−0.1%unclear
Price cut before sale40%44%43%unclear
Seller paid closing costs or repairs80%69%71%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 5, 2025 – November 4, 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 Ranch At Deer 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
22 resale sales. Average $720,124; median $673,250; standard deviation $146,158; middle half (25th–75th percentile) $600,625–$844,342; lowest $500,000, highest $973,160. 16 sales had a seller payment; their median payment was $3,350.

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
22 resale sales. Average $210; median $209; standard deviation $30; middle half (25th–75th percentile) $194–$224; lowest $147, highest $282.

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
22 resale sales. Average 3,436; median 3,380; standard deviation 548; middle half (25th–75th percentile) 3,034–3,836; lowest 2,378, highest 4,640.

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
22 resale sales. Average 2003; median 2003; standard deviation 2; middle half (25th–75th percentile) 2001–2005; lowest 2001, highest 2007.

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
22 resale sales. Average 62; median 50; standard deviation 48; middle half (25th–75th percentile) 23–94; lowest 3, highest 173. 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
22 resale sales. Average 0.3%; median 4.4%; standard deviation 22.7%; middle half (25th–75th percentile) 1.9%–7.0%; lowest −100.0%, highest 13.6%. 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
10 of 22 resale sales (45.5%).

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
16 of 22 resale sales (72.7%).

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
5 sales with a view, 16 without, 1 unclassified. Most common View entries: None 13, Trees/Woods 4, Neighborhood 4, Golf Course 2, Hill Country 2, See Remarks 1, Park/Greenbelt 1, Pool 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
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-05 21:45 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Cedar Park, SubdivisionName contains any of “ranch at deer creek” (case-insensitive). A record is kept when its subdivision name belongs to the Ranch At Deer Creek family, the same rule comparable sales use.
The data
Pulled November 5, 2026: 22 closed Ranch At Deer Creek records over the prior year, in ZIP 78613. 6 subdivision spellings kept: Ranch At Deer Creek Ph 2 Sec (11); Ranch At Deer Creek (4); Ranch At Deer Creek Ph 1 Sec (3); Ranch At Deer Creek Ph 3 Sec (2); Ranch At Deer Creek Ph 03 Sec (1); Ranch At Deer Creek Ph 03 Sec 04 (1). No other names were found by the search.

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 15 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 5, 2025 to November 4, 2026 inclusive.
The data
22 single-family sales in the window: 22 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
22 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 $610K”.
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 $610K: $500,000–$597,500 (6 sales); $610K–$656K: $610,000–$656,500 (5 sales); $690K–$832K: $690,000–$831,800 (5 sales); Over $832K: $848,522–$973,160 (6 sales)
Quartiles by living area: Under 3,063 SF: 2,378–3,024 SF (6 sales); 3,063–3,368 SF: 3,063–3,368 SF (5 sales); 3,391–3,784 SF: 3,391–3,784 SF (5 sales); Over 3,784 SF: 3,854–4,640 SF (6 sales)
Quartiles by year built: Before 2002: 2001–2001 (6 sales); 2002: 2002–2002 (4 sales); 2003–2004: 2003–2004 (6 sales); After 2004: 2005–2007 (6 sales)
View and no view: View: MLS lists a view (5 sales); No view: None or Neighborhood (16 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 $720,124, median $673,250. Days on market: average 62, 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; 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
0 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 = 6.2530.1001p < 0.0063Unclearε² = 0.298large
Living areaKruskal–WallisH = 11.7130.0085p < 0.0063Unclearε² = 0.557large
Year builtKruskal–WallisH = 3.9430.2678p < 0.0063Unclearε² = 0.188large
Days on marketKruskal–WallisH = 3.7130.2948p < 0.0063Unclearε² = 0.177large
Discount from original listKruskal–WallisH = 3.5130.3191p < 0.0063Unclearε² = 0.167large
Price cut before saleChi-squareχ² = 4.5230.2103p < 0.0063UnclearCramér’s V = 0.453medium
Seller paid closing costs or repairsChi-squareχ² = 3.1830.3650p < 0.0063UnclearCramér’s V = 0.380medium
Has a viewChi-squareχ² = 0.5530.9073p < 0.0063UnclearCramér’s V = 0.158small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 11.6230.0088p < 0.0063Unclearε² = 0.554large
Net price per SFKruskal–WallisH = 2.5630.4650p < 0.0063Unclearε² = 0.122medium
Year builtKruskal–WallisH = 1.9230.5891p < 0.0063Unclearε² = 0.091medium
Days on marketKruskal–WallisH = 1.8030.6143p < 0.0063Unclearε² = 0.086medium
Discount from original listKruskal–WallisH = 0.8530.8366p < 0.0063Unclearε² = 0.041small
Price cut before saleChi-squareχ² = 3.1830.3650p < 0.0063UnclearCramér’s V = 0.380medium
Seller paid closing costs or repairsChi-squareχ² = 4.3530.2257p < 0.0063UnclearCramér’s V = 0.445medium
Has a viewChi-squareχ² = 5.8730.1183p < 0.0063UnclearCramér’s V = 0.516large

8.3.3 Quartiles by year built

Too few sales in a group to test.

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 55.00—0.2398p < 0.0063Unclearrank-biserial r = 0.375medium
Net price per SFMann–Whitney UU = 53.00—0.3127p < 0.0063Unclearrank-biserial r = 0.325medium
Living areaMann–Whitney UU = 44.00—0.7725p < 0.0063Unclearrank-biserial r = 0.100small
Year builtMann–Whitney UU = 26.00—0.2585p < 0.0063Unclearrank-biserial r = 0.350medium
Days on marketMann–Whitney UU = 33.50—0.6200p < 0.0063Unclearrank-biserial r = 0.162small
Discount from original listMann–Whitney UU = 60.00—0.1092p < 0.0063Unclearrank-biserial r = 0.500large
Price cut before saleChi-squareχ² = 0.0210.8824p < 0.0063UnclearCramér’s V = 0.032negligible
Seller paid closing costs or repairsChi-squareχ² = 0.2410.6269p < 0.0063UnclearCramér’s V = 0.106small

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 22 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 5, 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.