ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Meadows Brushy Creek

Austin, TX 78717
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 · 4:07 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
22
single-family resale homes
Median net sale price
$612,000
average $633,080
Median net price per SF
$229
average $226
Median days on market
13 days
average 34 days
1. SummaryResale homes · 22 sales · October 26, 2025 – October 25, 2026

This study looks at the 22 resale homes sold in Meadows Brushy Creek in the 365 days to October 25, 2026. A full year is used because only 12 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 $570K · 6 sales$570K–$603K · 5 sales$621K–$692K · 5 salesOver $692K · 6 sales
3. Quartiles by net sale priceResale homes · 22 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.

2026-10-26T04:07:23.604842 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 5 5 6 22 sales Sales per group Under $570K: 6 sales (27%) $570K–$603K: 5 sales (23%) $621K–$692K: 5 sales (23%) Over $692K: 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 $570K$570K–$603K$621K–$692KOver $692KReal difference?
Net price per SF$230 per SF$208 per SF$231 per SF$234 per SFunclear
Living area2,280 SF2,858 SF2,854 SF3,358 SFunclear
Year built1992199319941996unclear
Days on market16 days5 days12 days34 daysunclear
Discount from original list3.6%5.1%3.5%4.5%unclear
Price cut before sale33%40%0%33%unclear
Seller paid closing costs or repairs83%20%60%33%unclear
Has a view0%0%20%17%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

2026-10-26T04:07:23.637356 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $570K 6 sales $570K– $603K 5 sales $621K– $692K 5 sales Over $692K 6 sales $0 $100 $200 $230 $208 $231 $234 Net price per SF, average

The average is $234 per SF for homes over $692K and $230 per SF for homes under $570K. It does not move in a straight line; homes over $692K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-26T04:07:23.666573 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $570K 6 sales $570K– $603K 5 sales $621K– $692K 5 sales Over $692K 6 sales 0 2,000 4,000 2,280 2,858 2,854 3,358 Living area (SF), average

The average is 3,358 SF for homes over $692K and 2,280 SF for homes under $570K. It does not move in a straight line; homes over $692K are highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-26T04:07:23.693343 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $570K 6 sales $570K– $603K 5 sales $621K– $692K 5 sales Over $692K 6 sales 1992 1994 1996 1992 1993 1994 1996 Year built: median (dot) and middle half (bar)

The median is 1996 for homes over $692K and 1992 for homes under $570K. 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

2026-10-26T04:07:23.719277 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $570K 6 sales $570K– $603K 5 sales $621K– $692K 5 sales Over $692K 6 sales 0 20 40 16 5 12 34 Days on market, median

The median is 34 days for homes over $692K and 16 days for homes under $570K. It does not move in a straight line; homes over $692K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T04:07:23.744121 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $570K 6 sales $570K– $603K 5 sales $621K– $692K 5 sales Over $692K 6 sales 0.0% 2.0% 4.0% 6.0% 3.6% 5.1% 3.5% 4.5% Discount from original list, average

The average is 4.5% for homes over $692K and 3.6% for homes under $570K. It does not move in a straight line; homes $570K–$603K 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

2026-10-26T04:07:23.780106 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 83 0 40 20 0 0 60 20 33 33 17 Under $570K $570K–$603K $621K–$692K Over $692K

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

  • 33% of homes over $692K had a price cut before sale, against 33% of homes under $570K. Defined in 8.1.7.
  • 33% of homes over $692K had the seller pay closing costs or repairs, against 83% of homes under $570K. Defined in 8.1.8.
  • 17% of homes over $692K have a view, against 0% of homes under $570K. 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 $570K6 sales$570K–$603K5 sales$621K–$692K5 salesOver $692K6 salesAll22 salesReal difference?
Net sale price average$519,394$585,140$652,340$770,667$633,080by design
Net price per SF average$230$208$231$234$226unclear
Living area average2,2802,8582,8543,3582,836unclear
Year built median19921993199419961994unclear

3.10 The numbers: selling

Under $570K6 sales$570K–$603K5 sales$621K–$692K5 salesOver $692K6 salesAll22 salesReal difference?
Days on market median165123413unclear
Discount from original list average3.6%5.1%3.5%4.5%4.2%unclear
Price cut before sale33%40%0%33%27%unclear
Seller paid closing costs or repairs83%20%60%33%50%unclear
Has a view0%0%20%17%9%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 · October 26, 2025 – October 25, 2026

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

2026-10-26T04:07:23.804580 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 5 5 6 22 sales Sales per group Under 2,499 SF: 6 sales (27%) 2,499–2,688 SF: 5 sales (23%) 2,690–3,018 SF: 5 sales (23%) Over 3,018 SF: 6 sales (27%)
Bottom line

4.1 Key differences

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

Under 2,499 SF2,499–2,688 SF2,690–3,018 SFOver 3,018 SF
Larger homes Over 3,018 SF
  • Sell for much more.
Smaller homes Under 2,499 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 2,499 SF2,499–2,688 SF2,690–3,018 SFOver 3,018 SFReal difference?
Net sale price$527KLowest$642K$637K$729KHighest✓ large
Net price per SF$236 per SF$246 per SF$219 per SF$205 per SFunclear
Year built1992199219951995unclear
Days on market21 days10 days8 days24 daysunclear
Discount from original list6.2%1.4%2.5%5.8%unclear
Price cut before sale50%0%20%33%unclear
Seller paid closing costs or repairs83%40%20%50%unclear
Has a view0%0%0%33%unclear

4.3 Homes over 3,018 SF sell for about $202K (38%) more than homes under 2,499 SF

2026-10-26T04:07:23.828320 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,499 SF 6 sales 2,499– 2,688 SF 5 sales 2,690– 3,018 SF 5 sales Over 3,018 SF 6 sales $0K $250K $500K $750K $527K $642K $637K $729K Net sale price, average

The average is $729K for homes over 3,018 SF and $527K for homes under 2,499 SF. It does not move in a straight line; homes over 3,018 SF are highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-26T04:07:23.855676 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,499 SF 6 sales 2,499– 2,688 SF 5 sales 2,690– 3,018 SF 5 sales Over 3,018 SF 6 sales $0 $100 $200 $236 $246 $219 $205 Net price per SF, average

The average is $205 per SF for homes over 3,018 SF and $236 per SF for homes under 2,499 SF. It does not move in a straight line; homes 2,499–2,688 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T04:07:23.881279 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,499 SF 6 sales 2,499– 2,688 SF 5 sales 2,690– 3,018 SF 5 sales Over 3,018 SF 6 sales 1992 1994 1996 1992 1992 1995 1995 Year built: median (dot) and middle half (bar)

The median is 1995 for homes over 3,018 SF and 1992 for homes under 2,499 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T04:07:23.910187 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,499 SF 6 sales 2,499– 2,688 SF 5 sales 2,690– 3,018 SF 5 sales Over 3,018 SF 6 sales 0 10 20 21 10 8 24 Days on market, median

The median is 24 days for homes over 3,018 SF and 21 days for homes under 2,499 SF. It does not move in a straight line; homes over 3,018 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T04:07:23.937666 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,499 SF 6 sales 2,499– 2,688 SF 5 sales 2,690– 3,018 SF 5 sales Over 3,018 SF 6 sales 0.0% 2.0% 4.0% 6.0% 6.2% 1.4% 2.5% 5.8% Discount from original list, average

The average is 5.8% for homes over 3,018 SF and 6.2% for homes under 2,499 SF. It does not move in a straight line; homes under 2,499 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

2026-10-26T04:07:23.973184 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 83 0 0 40 0 20 20 0 33 50 33 Under 2,499 SF 2,499–2,688 SF 2,690–3,018 SF Over 3,018 SF

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

  • 33% of homes over 3,018 SF had a price cut before sale, against 50% of homes under 2,499 SF. Defined in 8.1.7.
  • 50% of homes over 3,018 SF had the seller pay closing costs or repairs, against 83% of homes under 2,499 SF. Defined in 8.1.8.
  • 33% of homes over 3,018 SF have a view, against 0% of homes under 2,499 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 2,499 SF6 sales2,499–2,688 SF5 sales2,690–3,018 SF5 salesOver 3,018 SF6 salesAll22 salesReal difference?
Net sale price average$526,652$642,200$636,670$728,917$633,080✓ large
Net price per SF average$236$246$219$205$226unclear
Living area average2,2342,6102,9003,5722,836by design
Year built median19921992199519951994unclear

4.10 The numbers: selling

Under 2,499 SF6 sales2,499–2,688 SF5 sales2,690–3,018 SF5 salesOver 3,018 SF6 salesAll22 salesReal difference?
Days on market median211082413unclear
Discount from original list average6.2%1.4%2.5%5.8%4.2%unclear
Price cut before sale50%0%20%33%27%unclear
Seller paid closing costs or repairs83%40%20%50%50%unclear
Has a view0%0%0%33%9%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 · 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.

2026-10-26T04:07:24.002191 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 7 5 6 22 sales Sales per group Before 1992: 4 sales (18%) 1992–1993: 7 sales (32%) 1994–1996: 5 sales (23%) After 1996: 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

2026-10-26T04:07:24.027887 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1992 4 sales 1992– 1993 7 sales 1994– 1996 5 sales After 1996 6 sales $0K $250K $500K $750K $570K $615K $734K $612K Net sale price, average

The average is $612K for homes built after 1996 and $570K for homes built before 1992. It does not move in a straight line; homes built 1994–1996 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T04:07:24.056959 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1992 4 sales 1992– 1993 7 sales 1994– 1996 5 sales After 1996 6 sales $0 $100 $200 $224 $227 $229 $225 Net price per SF, average

The average is $225 per SF for homes built after 1996 and $224 per SF for homes built before 1992. It does not move in a straight line; homes built 1994–1996 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T04:07:24.084121 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1992 4 sales 1992– 1993 7 sales 1994– 1996 5 sales After 1996 6 sales 0 1,000 2,000 3,000 2,560 2,793 3,248 2,725 Living area (SF), average

The average is 2,725 SF for homes built after 1996 and 2,560 SF for homes built before 1992. It does not move in a straight line; homes built 1994–1996 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T04:07:24.109732 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1992 4 sales 1992– 1993 7 sales 1994– 1996 5 sales After 1996 6 sales 0 50 100 89 8 35 13 Days on market, median

The median is 13 days for homes built after 1996 and 89 days for homes built before 1992. It does not move in a straight line; homes built before 1992 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T04:07:24.136037 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1992 4 sales 1992– 1993 7 sales 1994– 1996 5 sales After 1996 6 sales 0.0% 2.5% 5.0% 7.5% 7.9% 2.6% 4.8% 2.9% Discount from original list, average

The average is 2.9% for homes built after 1996 and 7.9% for homes built before 1992. It does not move in a straight line; homes built before 1992 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

2026-10-26T04:07:24.163866 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% 75 50 0 14 57 14 40 40 20 0 50 0 Before 1992 1992–1993 1994–1996 After 1996

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

  • 0% of homes built after 1996 had a price cut before sale, against 75% of homes built before 1992. Defined in 8.1.7.
  • 50% of homes built after 1996 had the seller pay closing costs or repairs, against 50% of homes built before 1992. Defined in 8.1.8.
  • 0% of homes built after 1996 have a view, against 0% of homes built before 1992. 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 19924 sales1992–19937 sales1994–19965 salesAfter 19966 salesAll22 sales
Net sale price average$569,975$615,295$734,000$611,800$633,080
Net price per SF average$224$227$229$225$226
Living area average2,5602,7933,2482,7252,836
Year built median19891992199619981994

5.10 The numbers: selling

Before 19924 sales1992–19937 sales1994–19965 salesAfter 19966 salesAll22 sales
Days on market median898351313
Discount from original list average7.9%2.6%4.8%2.9%4.2%
Price cut before sale75%14%40%0%27%
Seller paid closing costs or repairs50%57%40%50%50%
Has a view0%14%20%0%9%

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 · October 26, 2025 – October 25, 2026

Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood.

2026-10-26T04:07:24.183915 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 2 20 22 sales Sales per group View: 2 sales (9%) No view: 20 sales (91%)
Bottom line: too few sales to test.

6.1 Key differences

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

6.3 Net sale price: described, not tested

2026-10-26T04:07:24.201252 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales $0K $200K $400K $600K $800K $725K $624K Net sale price, average

The average is $725K for homes with a view and $624K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T04:07:24.220615 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales $0 $100 $200 $188 $230 Net price per SF, average

The average is $188 per SF for homes with a view and $230 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T04:07:24.242436 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 0 1,000 2,000 3,000 4,000 3,851 2,734 Living area (SF), average

The average is 3,851 SF for homes with a view and 2,734 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T04:07:24.349695 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 1992 1994 1996 1994 1994 Year built: median (dot) and middle half (bar)

The median is 1994 for homes with a view and 1994 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T04:07:24.368141 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 0 5 10 15 20 20 13 Days on market, median

The median is 20 days for homes with a view and 13 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-26T04:07:24.387528 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 0.0% 2.0% 4.0% 4.8% 4.1% Discount from original list, average

The average is 4.8% for homes with a view and 4.1% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T04:07:24.405763 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 0 0 30 55 View No view

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

  • 0% of homes with a view had a price cut before sale, against 30% of homes without a view. Defined in 8.1.7.
  • 0% of homes with a view had the seller pay closing costs or repairs, against 55% of homes without a view. Defined in 8.1.8.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View2 salesNo view20 salesAll22 sales
Net sale price average$725,000$623,888$633,080
Net price per SF average$188$230$226
Living area average3,8512,7342,836
Year built median199419941994

6.11 The numbers: selling

View2 salesNo view20 salesAll22 sales
Days on market median201313
Discount from original list average4.8%4.1%4.2%
Price cut before sale0%30%27%
Seller paid closing costs or repairs0%55%50%

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 Meadows Brushy 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 $633,080; median $612,000; standard deviation $103,744; middle half (25th–75th percentile) $565,875–$697,875; lowest $487,012, highest $825,000. 11 sales had a seller payment; their median payment was $8,500.

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 $226; median $229; standard deviation $26; middle half (25th–75th percentile) $206–$247; lowest $180, highest $263.

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 2,836; median 2,689; standard deviation 572; middle half (25th–75th percentile) 2,489–3,027; lowest 1,941, highest 4,244.

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 1994; median 1994; standard deviation 3; middle half (25th–75th percentile) 1992–1997; lowest 1987, highest 1999.

8.1.5 Days on market

In simple terms
How many days the home was on the market before the buyer's offer was accepted, counting any earlier listing periods (relists). This is the days on market agents and clients quote.
Statistically
CDOM = max(CumulativeDaysOnMarket, DaysOnMarket, PurchaseContractDate − ListingContractDate). The MLS counter can freeze at a price change, so the contract-date gap is a floor. Summarized by the median, because a few homes that sat for months pull an average up.
The data
22 resale sales. Average 34; median 13; standard deviation 43; middle half (25th–75th percentile) 7–47; lowest 3, highest 169. 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 4.2%; median 3.6%; standard deviation 4.5%; middle half (25th–75th percentile) 0.7%–7.0%; lowest −2.7%, highest 15.0%. 5 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
6 of 22 resale sales (27.3%).

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
11 of 22 resale sales (50.0%).

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
2 sales with a view, 20 without, 0 unclassified. Most common View entries: None 16, Neighborhood 4, Park/Greenbelt 2.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “meadows brushy creek”, “meadows brushy crk” (case-insensitive). A record is kept when its subdivision name belongs to the Meadows Brushy Creek family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 22 closed Meadows Brushy Creek records over the prior year, in ZIP 78717. 3 subdivision spellings kept: Meadows Brushy Creek (19); Meadows Brushy Creek Ph 04 (2); Meadows Brushy Creek Ph 05 (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 12 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 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 $570K”.
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 $570K: $487,012–$564,500 (6 sales); $570K–$603K: $570,000–$603,000 (5 sales); $621K–$692K: $621,000–$691,500 (5 sales); Over $692K: $700,000–$825,000 (6 sales)
Quartiles by living area: Under 2,499 SF: 1,941–2,486 SF (6 sales); 2,499–2,688 SF: 2,499–2,688 SF (5 sales); 2,690–3,018 SF: 2,690–3,018 SF (5 sales); Over 3,018 SF: 3,030–4,244 SF (6 sales)
Quartiles by year built: Before 1992: 1987–1991 (4 sales); 1992–1993: 1992–1993 (7 sales); 1994–1996: 1994–1996 (5 sales); After 1996: 1997–1999 (6 sales)
View and no view: View: MLS lists a view (2 sales); No view: None or Neighborhood (20 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 $633,080, median $612,000. Days on market: average 34, median 13: 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

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
1 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 = 2.7830.4270p < 0.0063Unclearε² = 0.132medium
Living areaKruskal–WallisH = 10.9030.0123p < 0.0063Unclearε² = 0.519large
Year builtKruskal–WallisH = 0.4730.9253p < 0.0063Unclearε² = 0.022small
Days on marketKruskal–WallisH = 0.5830.9014p < 0.0063Unclearε² = 0.028small
Discount from original listKruskal–WallisH = 0.0330.9984p < 0.0063Unclearε² = 0.002negligible
Price cut before saleChi-squareχ² = 2.5130.4743p < 0.0063UnclearCramér’s V = 0.337medium
Seller paid closing costs or repairsChi-squareχ² = 5.3330.1490p < 0.0063UnclearCramér’s V = 0.492medium
Has a viewChi-squareχ² = 2.2430.5248p < 0.0063UnclearCramér’s V = 0.319medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 12.4930.0059p < 0.0063Yesε² = 0.595large
Net price per SFKruskal–WallisH = 8.4430.0378p < 0.0063Unclearε² = 0.402large
Year builtKruskal–WallisH = 2.3330.5074p < 0.0063Unclearε² = 0.111medium
Days on marketKruskal–WallisH = 3.2030.3625p < 0.0063Unclearε² = 0.152large
Discount from original listKruskal–WallisH = 4.4230.2198p < 0.0063Unclearε² = 0.210large
Price cut before saleChi-squareχ² = 3.6830.2979p < 0.0063UnclearCramér’s V = 0.409medium
Seller paid closing costs or repairsChi-squareχ² = 4.6730.1979p < 0.0063UnclearCramér’s V = 0.461medium
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

Too few sales in a group to test.

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 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 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.