ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Ranch At Brushy Creek Sec 01

Cedar Park, TX 78613
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 7:30 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
41
single-family resale homes
Median net sale price
$795,000
average $819,454
Median net price per SF
$239
average $246
Median days on market
20 days
average 57 days
1. SummaryResale homes · 41 sales · October 26, 2025 – October 25, 2026

This study looks at the 41 resale homes sold in Ranch At Brushy Creek Sec 01 in the 365 days to October 25, 2026. A full year is used because only 28 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 sold41 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 $630K · 10 sales$630K–$776K · 10 sales$795K–$894K · 11 salesOver $894K · 10 sales
3. Quartiles by net sale priceResale homes · 41 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:30:57.302333 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 11 10 41 sales Sales per group Under $630K: 10 sales (24%) $630K–$776K: 10 sales (24%) $795K–$894K: 11 sales (27%) Over $894K: 10 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 $630K$630K–$776K$795K–$894KOver $894K
Higher-priced homes Over $894K
  • Are much larger.
  • Sell for more per square foot.
Lower-priced homes Under $630K
  • Are much smaller.
  • Sell for less per square foot.

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 $630K$630K–$776K$795K–$894KOver $894KReal difference?
Net price per SF$238 per SF$227 per SFLowest$239 per SF$279 per SFHighest✓ large
Living area2,390 SFSmallest3,107 SF3,543 SF4,211 SFLargest✓ large
Year built2007200920102014unclear
Days on market42 days15 days21 days20 daysunclear
Discount from original list7.1%2.5%3.8%6.0%unclear
Price cut before sale50%10%27%40%unclear
Seller paid closing costs or repairs60%80%55%60%unclear
Has a view10%30%27%40%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 Homes over $894K sell for about $41 per SF (17%) more than homes under $630K

2026-10-26T07:30:57.330967 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $630K 10 sales $630K– $776K 10 sales $795K– $894K 11 sales Over $894K 10 sales $0 $100 $200 $300 $238 $227 $239 $279 Net price per SF, average

The average is $279 per SF for homes over $894K and $238 per SF for homes under $630K. It does not move in a straight line; homes over $894K are highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $894K are about 1,820 SF (76%) larger than homes under $630K

2026-10-26T07:30:57.354245 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $630K 10 sales $630K– $776K 10 sales $795K– $894K 11 sales Over $894K 10 sales 0 2,000 4,000 2,390 3,107 3,543 4,211 Living area (SF), average

The average is 4,211 SF for homes over $894K and 2,390 SF for homes under $630K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-26T07:30:57.379485 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $630K 10 sales $630K– $776K 10 sales $795K– $894K 11 sales Over $894K 10 sales 2006 2008 2010 2012 2014 2007 2009 2010 2014 Year built: median (dot) and middle half (bar)

The median is 2014 for homes over $894K and 2007 for homes under $630K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:30:57.402889 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $630K 10 sales $630K– $776K 10 sales $795K– $894K 11 sales Over $894K 10 sales 0 20 40 42 15 21 20 Days on market, median

The median is 20 days for homes over $894K and 42 days for homes under $630K. It does not move in a straight line; homes under $630K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:30:57.425562 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $630K 10 sales $630K– $776K 10 sales $795K– $894K 11 sales Over $894K 10 sales 0.0% 2.5% 5.0% 7.5% 7.1% 2.5% 3.8% 6.0% Discount from original list, average

The average is 6.0% for homes over $894K and 7.1% for homes under $630K. It does not move in a straight line; homes under $630K are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:30:57.456014 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 60 10 10 80 30 27 55 27 40 60 40 Under $630K $630K–$776K $795K–$894K Over $894K

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

  • 40% of homes over $894K had a price cut before sale, against 50% of homes under $630K. Defined in 8.1.7.
  • 60% of homes over $894K had the seller pay closing costs or repairs, against 60% of homes under $630K. Defined in 8.1.8.
  • 40% of homes over $894K have a view, against 10% of homes under $630K. 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 $630K10 sales$630K–$776K10 sales$795K–$894K11 salesOver $894K10 salesAll41 salesReal difference?
Net sale price average$563,806$702,139$837,364$1,172,716$819,454by design
Net price per SF average$238$227$239$279$246✓ large
Living area average2,3903,1073,5434,2113,319✓ large
Year built median20072009201020142010unclear

3.10 The numbers: selling

Under $630K10 sales$630K–$776K10 sales$795K–$894K11 salesOver $894K10 salesAll41 salesReal difference?
Days on market median4215212020unclear
Discount from original list average7.1%2.5%3.8%6.0%4.8%unclear
Price cut before sale50%10%27%40%32%unclear
Seller paid closing costs or repairs60%80%55%60%63%unclear
Has a view10%30%27%40%27%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 · 41 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:30:57.476824 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 11 10 41 sales Sales per group Under 2,775 SF: 10 sales (24%) 2,775–3,233 SF: 10 sales (24%) 3,273–3,828 SF: 11 sales (27%) Over 3,828 SF: 10 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 2,775 SF2,775–3,233 SF3,273–3,828 SFOver 3,828 SF
Larger homes Over 3,828 SF
  • Sell for much more.
Smaller homes Under 2,775 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 2,775 SF2,775–3,233 SF3,273–3,828 SFOver 3,828 SFReal difference?
Net sale price$565KLowest$737K$849K$1.12MHighest✓ large
Net price per SF$239 per SF$248 per SF$238 per SF$259 per SFunclear
Year built2007201020112010unclear
Days on market42 days15 days18 days24 daysunclear
Discount from original list6.8%3.9%3.8%4.8%unclear
Price cut before sale50%20%18%40%unclear
Seller paid closing costs or repairs60%60%82%50%unclear
Has a view10%50%18%30%unclear

4.3 Homes over 3,828 SF sell for about $558K (99%) more than homes under 2,775 SF

2026-10-26T07:30:57.497925 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,775 SF 10 sales 2,775– 3,233 SF 10 sales 3,273– 3,828 SF 11 sales Over 3,828 SF 10 sales $0K $500K $1.00M $565K $737K $849K $1.12M Net sale price, average

The average is $1.12M for homes over 3,828 SF and $565K for homes under 2,775 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-26T07:30:57.520804 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,775 SF 10 sales 2,775– 3,233 SF 10 sales 3,273– 3,828 SF 11 sales Over 3,828 SF 10 sales $0 $100 $200 $300 $239 $248 $238 $259 Net price per SF, average

The average is $259 per SF for homes over 3,828 SF and $239 per SF for homes under 2,775 SF. It does not move in a straight line; homes over 3,828 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:30:57.546197 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,775 SF 10 sales 2,775– 3,233 SF 10 sales 3,273– 3,828 SF 11 sales Over 3,828 SF 10 sales 2006 2008 2010 2012 2014 2007 2010 2011 2010 Year built: median (dot) and middle half (bar)

The median is 2010 for homes over 3,828 SF and 2007 for homes under 2,775 SF. It does not move in a straight line; homes 3,273–3,828 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:30:57.569623 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,775 SF 10 sales 2,775– 3,233 SF 10 sales 3,273– 3,828 SF 11 sales Over 3,828 SF 10 sales 0 20 40 42 15 18 24 Days on market, median

The median is 24 days for homes over 3,828 SF and 42 days for homes under 2,775 SF. It does not move in a straight line; homes under 2,775 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:30:57.592331 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,775 SF 10 sales 2,775– 3,233 SF 10 sales 3,273– 3,828 SF 11 sales Over 3,828 SF 10 sales 0.0% 2.5% 5.0% 7.5% 6.8% 3.9% 3.8% 4.8% Discount from original list, average

The average is 4.8% for homes over 3,828 SF and 6.8% for homes under 2,775 SF. It does not move in a straight line; homes under 2,775 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:30:57.619547 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 60 10 20 60 50 18 82 18 40 50 30 Under 2,775 SF 2,775–3,233 SF 3,273–3,828 SF Over 3,828 SF

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

  • 40% of homes over 3,828 SF had a price cut before sale, against 50% of homes under 2,775 SF. Defined in 8.1.7.
  • 50% of homes over 3,828 SF had the seller pay closing costs or repairs, against 60% of homes under 2,775 SF. Defined in 8.1.8.
  • 30% of homes over 3,828 SF have a view, against 10% of homes under 2,775 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 2,775 SF10 sales2,775–3,233 SF10 sales3,273–3,828 SF11 salesOver 3,828 SF10 salesAll41 salesReal difference?
Net sale price average$565,396$736,980$849,153$1,123,316$819,454✓ large
Net price per SF average$239$248$238$259$246unclear
Living area average2,3902,9723,5644,3243,319by design
Year built median20072010201120102010unclear

4.10 The numbers: selling

Under 2,775 SF10 sales2,775–3,233 SF10 sales3,273–3,828 SF11 salesOver 3,828 SF10 salesAll41 salesReal difference?
Days on market median4215182420unclear
Discount from original list average6.8%3.9%3.8%4.8%4.8%unclear
Price cut before sale50%20%18%40%32%unclear
Seller paid closing costs or repairs60%60%82%50%63%unclear
Has a view10%50%18%30%27%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 · 41 sales · October 26, 2025 – October 25, 2026

Sales ranked by year built and cut into four groups, from the oldest to the newest. Homes built in the same year always stay in the same group, so group sizes can differ a little.

2026-10-26T07:30:57.640433 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 12 12 9 41 sales Sales per group Before 2007: 8 sales (20%) 2007–2009: 12 sales (29%) 2010–2013: 12 sales (29%) After 2013: 9 sales (22%)
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 20072007–20092010–2013After 2013Real difference?
Net sale price$658K$785K$784K$1.06Munclear
Net price per SF$220 per SF$244 per SF$242 per SF$275 per SFunclear
Living area2,981 SF3,196 SF3,275 SF3,840 SFunclear
Days on market10 days26 days20 days18 daysunclear
Discount from original list5.5%5.7%4.2%3.8%unclear
Price cut before sale25%42%33%22%unclear
Seller paid closing costs or repairs75%50%75%56%unclear
Has a view38%0%33%44%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:30:57.661458 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 8 sales 2007– 2009 12 sales 2010– 2013 12 sales After 2013 9 sales $0K $500K $1.00M $658K $785K $784K $1.06M Net sale price, average

The average is $1.06M for homes built after 2013 and $658K for homes built before 2007. It does not move in a straight line; homes built after 2013 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:30:57.684191 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 8 sales 2007– 2009 12 sales 2010– 2013 12 sales After 2013 9 sales $0 $100 $200 $300 $220 $244 $242 $275 Net price per SF, average

The average is $275 per SF for homes built after 2013 and $220 per SF for homes built before 2007. It does not move in a straight line; homes built after 2013 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:30:57.706180 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 8 sales 2007– 2009 12 sales 2010– 2013 12 sales After 2013 9 sales 0 2,000 4,000 2,981 3,196 3,275 3,840 Living area (SF), average

The average is 3,840 SF for homes built after 2013 and 2,981 SF for homes built before 2007. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:30:57.727699 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 8 sales 2007– 2009 12 sales 2010– 2013 12 sales After 2013 9 sales 0 10 20 30 10 26 20 18 Days on market, median

The median is 18 days for homes built after 2013 and 10 days for homes built before 2007. It does not move in a straight line; homes built 2007–2009 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:30:57.750749 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 8 sales 2007– 2009 12 sales 2010– 2013 12 sales After 2013 9 sales 0.0% 2.0% 4.0% 6.0% 5.5% 5.7% 4.2% 3.8% Discount from original list, average

The average is 3.8% for homes built after 2013 and 5.5% for homes built before 2007. It does not move in a straight line; homes built 2007–2009 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:30:57.776739 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 75 38 42 50 0 33 75 33 22 56 44 Before 2007 2007–2009 2010–2013 After 2013

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

  • 22% of homes built after 2013 had a price cut before sale, against 25% of homes built before 2007. Defined in 8.1.7.
  • 56% of homes built after 2013 had the seller pay closing costs or repairs, against 75% of homes built before 2007. Defined in 8.1.8.
  • 44% of homes built after 2013 have a view, against 38% of homes built before 2007. 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 20078 sales2007–200912 sales2010–201312 salesAfter 20139 salesAll41 salesReal difference?
Net sale price average$658,237$785,400$783,745$1,055,773$819,454unclear
Net price per SF average$220$244$242$275$246unclear
Living area average2,9813,1963,2753,8403,319unclear
Year built median20062008201120142010by design

5.10 The numbers: selling

Before 20078 sales2007–200912 sales2010–201312 salesAfter 20139 salesAll41 salesReal difference?
Days on market median1026201820unclear
Discount from original list average5.5%5.7%4.2%3.8%4.8%unclear
Price cut before sale25%42%33%22%32%unclear
Seller paid closing costs or repairs75%50%75%56%63%unclear
Has a view38%0%33%44%27%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 · 41 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:30:57.795414 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 29 40 sales Sales per group View: 11 sales (28%) No view: 29 sales (72%)
Bottom line

6.1 Key differences

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

ViewNo view
Homes with a view MLS lists a view
  • Sell faster.
Homes without a view no view listed
  • Take longer to sell.

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$927K$786Kunclear
Net price per SF$264 per SF$239 per SFunclear
Living area3,454 SF3,292 SFunclear
Year built20132009unclear
Days on market6 daysFastest32 daysSlowest✓ large
Discount from original list3.5%5.4%unclear
Price cut before sale9%41%unclear
Seller paid closing costs or repairs64%62%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:30:57.813054 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 29 sales $0K $250K $500K $750K $1.00M $927K $786K Net sale price, average

The average is $927K for homes with a view and $786K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-10-26T07:30:57.831236 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 29 sales $0 $100 $200 $300 $264 $239 Net price per SF, average

The average is $264 per SF for homes with a view and $239 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-10-26T07:30:57.850784 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 29 sales 0 1,000 2,000 3,000 4,000 3,454 3,292 Living area (SF), average

The average is 3,454 SF for homes with a view and 3,292 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:30:57.897784 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 29 sales 2008 2010 2012 2014 2013 2009 Year built: median (dot) and middle half (bar)

The median is 2013 for homes with a view and 2009 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Homes with a view sell 26 days faster than homes without a view

2026-10-26T07:30:57.915875 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 29 sales 0 10 20 30 6 32 Days on market, median

The median is 6 days for homes with a view and 32 days for homes without a view. Defined in 8.1.5.

✓ Real difference · large

6.8 Discount from original list: no clear difference

2026-10-26T07:30:57.934326 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 11 sales No view 29 sales 0.0% 2.0% 4.0% 6.0% 3.5% 5.4% Discount from original list, average

The average is 3.5% for homes with a view and 5.4% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:30:57.953212 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 9 64 41 62 View No view

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

  • 9% of homes with a view had a price cut before sale, against 41% of homes without a view. Defined in 8.1.7.
  • 64% of homes with a view had the seller pay closing costs or repairs, against 62% of homes without a view. Defined in 8.1.8.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance

6.10 The numbers: price and size

View11 salesNo view29 salesAll40 salesReal difference?
Net sale price average$926,778$785,519$824,365unclear
Net price per SF average$264$239$246unclear
Living area average3,4543,2923,337unclear
Year built median201320092010unclear

6.11 The numbers: selling

View11 salesNo view29 salesAll40 salesReal difference?
Days on market median63220✓ large
Discount from original list average3.5%5.4%4.9%unclear
Price cut before sale9%41%32%unclear
Seller paid closing costs or repairs64%62%62%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 Ranch At Brushy Creek Sec 01.

No new-construction sales were reported in ABOR MLS in this window.

Same definitions as the rest of the study (section 8). New construction = NewConstructionYN true, or PropertyCondition “New Construction” or “Under Construction”.

8. AppendixMeasures, methods and tests

Each measure and method three ways: in plain words, as statistics, and with the data from this study.

8.1 Measures

8.1.1 Net sale price

In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
41 resale sales. Average $819,454; median $795,000; standard deviation $241,761; middle half (25th–75th percentile) $630,000–$894,000; lowest $450,000, highest $1,425,000. 26 sales had a seller payment; their median payment was $3,000.

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
41 resale sales. Average $246; median $239; standard deviation $32; middle half (25th–75th percentile) $221–$267; lowest $197, highest $326.

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
41 resale sales. Average 3,319; median 3,273; standard deviation 758; middle half (25th–75th percentile) 2,775–3,828; lowest 2,065, highest 4,760.

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
41 resale sales. Average 2010; median 2010; standard deviation 3; middle half (25th–75th percentile) 2007–2013; lowest 2005, highest 2015.

8.1.5 Days on market

In simple terms
How many days the home was on the market before the buyer's offer was accepted, counting any earlier listing periods (relists). This is the days on market agents and clients quote.
Statistically
CDOM = max(CumulativeDaysOnMarket, DaysOnMarket, PurchaseContractDate − ListingContractDate). The MLS counter can freeze at a price change, so the contract-date gap is a floor. Summarized by the median, because a few homes that sat for months pull an average up.
The data
41 resale sales. Average 57; median 20; standard deviation 84; middle half (25th–75th percentile) 7–65; lowest 1, highest 310. 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
41 resale sales. Average 4.8%; median 3.5%; standard deviation 4.8%; middle half (25th–75th percentile) 1.8%–6.2%; lowest −1.3%, highest 21.0%. 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
13 of 41 resale sales (31.7%).

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
26 of 41 resale sales (63.4%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
11 sales with a view, 29 without, 1 unclassified. Most common View entries: None 20, Neighborhood 14, Park/Greenbelt 9, Trees/Woods 4, Pond 2, See Remarks 2, Pool 1, Panoramic 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 = Cedar Park, SubdivisionName contains any of “ranch at brushy creek”, “ranch brushy creek”, “walsh trls”, “ranch at brushy crk”, “ranch brushy crk” (case-insensitive). A record is kept when its subdivision name belongs to the Ranch At Brushy Creek Sec 01 family, the same rule comparable sales use (it includes Ranch/Brushy Crk Sec 01, Walsh Trls Sec 02, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 41 closed Ranch At Brushy Creek Sec 01 records over the prior year, in ZIP 78613. 16 subdivision spellings kept, the most common: Ranch at Brushy Creek (8); Ranch At Brushy Creek Sec 01 (6); Ranch At Brushy Creek (5); Ranch At Brushy Creek Sec 2B Amd (4); Ranch At Brushy Creek Sec 03 (4); RANCH AT BRUSHY CREEK (3); Ranch At Brushy Creek Sec 06 (2); Ranch at Brushy Creek Sec 8A (1); Walsh Trls Sec 03 (1); Ranch at Brushy Creek Sec 9A (1); Ranch Brushy Creek Sec 02B Amd P (1); Ranch at Brushy Crk Sec 3 (1); and 4 more (4 records). Names found by the search but not part of Ranch At Brushy Creek Sec 01, left out: Trailside At The Ranch At Brushy Creek (2); Ranch At Brushy Crk North Ph 2 (1); RANCH AT BRUSHY CREEK NORTH PH 2 (1); Ranch Brushy Crk South (1); Ranch At Brushy Creek Estates (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 28 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
41 single-family sales in the window: 41 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
41 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 $630K”.
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 $630K: $450,000–$624,300 (10 sales); $630K–$776K: $630,000–$776,000 (10 sales); $795K–$894K: $795,000–$894,000 (11 sales); Over $894K: $996,999–$1,425,000 (10 sales)
Quartiles by living area: Under 2,775 SF: 2,065–2,774 SF (10 sales); 2,775–3,233 SF: 2,775–3,233 SF (10 sales); 3,273–3,828 SF: 3,273–3,828 SF (11 sales); Over 3,828 SF: 3,837–4,760 SF (10 sales)
Quartiles by year built: Before 2007: 2005–2006 (8 sales); 2007–2009: 2007–2009 (12 sales); 2010–2013: 2010–2013 (12 sales); After 2013: 2014–2015 (9 sales)
View and no view: View: MLS lists a view (11 sales); No view: None or Neighborhood (29 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 $819,454, median $795,000. Days on market: average 57, median 20: 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
4 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 = 14.5630.0022p < 0.0063Yesε² = 0.364large
Living areaKruskal–WallisH = 31.313< 0.0001p < 0.0063Yesε² = 0.783large
Year builtKruskal–WallisH = 9.0830.0282p < 0.0063Unclearε² = 0.227large
Days on marketKruskal–WallisH = 1.2330.7447p < 0.0063Unclearε² = 0.031small
Discount from original listKruskal–WallisH = 4.2830.2331p < 0.0063Unclearε² = 0.107medium
Price cut before saleChi-squareχ² = 4.1430.2468p < 0.0063UnclearCramér’s V = 0.318medium
Seller paid closing costs or repairsChi-squareχ² = 1.6630.6461p < 0.0063UnclearCramér’s V = 0.201small
Has a viewChi-squareχ² = 2.3830.4976p < 0.0063UnclearCramér’s V = 0.241small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 31.293< 0.0001p < 0.0063Yesε² = 0.782large
Net price per SFKruskal–WallisH = 2.0130.5704p < 0.0063Unclearε² = 0.050small
Year builtKruskal–WallisH = 5.7230.1260p < 0.0063Unclearε² = 0.143large
Days on marketKruskal–WallisH = 1.4230.7014p < 0.0063Unclearε² = 0.035small
Discount from original listKruskal–WallisH = 0.7330.8667p < 0.0063Unclearε² = 0.018small
Price cut before saleChi-squareχ² = 3.4330.3306p < 0.0063UnclearCramér’s V = 0.289small
Seller paid closing costs or repairsChi-squareχ² = 2.4830.4786p < 0.0063UnclearCramér’s V = 0.246small
Has a viewChi-squareχ² = 4.6530.1995p < 0.0063UnclearCramér’s V = 0.337medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 11.0830.0113p < 0.0063Unclearε² = 0.277large
Net price per SFKruskal–WallisH = 12.0230.0073p < 0.0063Unclearε² = 0.301large
Living areaKruskal–WallisH = 6.7130.0818p < 0.0063Unclearε² = 0.168large
Days on marketKruskal–WallisH = 1.1330.7690p < 0.0063Unclearε² = 0.028small
Discount from original listKruskal–WallisH = 0.4230.9356p < 0.0063Unclearε² = 0.011small
Price cut before saleChi-squareχ² = 1.1030.7760p < 0.0063UnclearCramér’s V = 0.164small
Seller paid closing costs or repairsChi-squareχ² = 2.3330.5073p < 0.0063UnclearCramér’s V = 0.238small
Has a viewChi-squareχ² = 6.5530.0879p < 0.0063UnclearCramér’s V = 0.400medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 205.00—0.1729p < 0.0063Unclearrank-biserial r = 0.285small
Net price per SFMann–Whitney UU = 222.00—0.0604p < 0.0063Unclearrank-biserial r = 0.392medium
Living areaMann–Whitney UU = 173.00—0.6937p < 0.0063Unclearrank-biserial r = 0.085negligible
Year builtMann–Whitney UU = 191.50—0.3365p < 0.0063Unclearrank-biserial r = 0.201small
Days on marketMann–Whitney UU = 62.00—0.0033p < 0.0063Yesrank-biserial r = 0.611large
Discount from original listMann–Whitney UU = 128.00—0.3477p < 0.0063Unclearrank-biserial r = 0.197small
Price cut before saleChi-squareχ² = 3.7910.0516p < 0.0063UnclearCramér’s V = 0.308medium
Seller paid closing costs or repairsChi-squareχ² = 0.0110.9272p < 0.0063UnclearCramér’s V = 0.014negligible

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 41 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.