ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Milwood

Austin, TX 78729 · 78727
Resale homes · closed Nov 8 – Nov 7, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 8, 2026 · 7:17 AM CST
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
137
single-family resale homes
Median net sale price
$464,000
average $472,064
Median net price per SF
$255
average $259
Median days on market
20 days
average 66 days
1. SummaryResale homes · 137 sales · November 8, 2025 – November 7, 2026

This study looks at the 137 resale homes sold in Milwood in the 365 days to November 7, 2026. A full year is used because only 67 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 sold137 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 $399K · 34 sales$399K–$462K · 34 sales$464K–$550K · 35 salesOver $550K · 34 sales
3. Quartiles by net sale priceResale homes · 137 sales · November 8, 2025 – November 7, 2026

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

2026-11-08T07:17:41.126587 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 34 34 35 34 137 sales Sales per group Under $399K: 34 sales (25%) $399K–$462K: 34 sales (25%) $464K–$550K: 35 sales (26%) Over $550K: 34 sales (25%)
Bottom line

3.1 Key differences

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

Under $399K$399K–$462K$464K–$550KOver $550K
Higher-priced homes Over $550K
  • Are much larger.
Lower-priced homes Under $399K
  • Are much smaller.

3.2 At a glance

Shaded rows are real differences; the darkest cell is the highest. Gray rows show no clear difference. Prices are averages; days on market and year built are medians.

Under $399K$399K–$462K$464K–$550KOver $550KReal difference?
Net price per SF$259 per SF$247 per SF$250 per SF$279 per SFunclear
Living area1,370 SFSmallest1,807 SF2,107 SF2,311 SFLargest✓ large
Year built1984198719861984unclear
Days on market34 days20 days20 days16 daysunclear
Discount from original list9.6%6.9%4.7%3.5%unclear
Price cut before sale41%47%46%24%unclear
Seller paid closing costs or repairs53%65%60%68%unclear
Has a view15%12%9%6%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

2026-11-08T07:17:41.154836 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $399K 34 sales $399K– $462K 34 sales $464K– $550K 35 sales Over $550K 34 sales $0 $100 $200 $300 $259 $247 $250 $279 Net price per SF, average

The average is $279 per SF for homes over $550K and $259 per SF for homes under $399K. It does not move in a straight line; homes over $550K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $550K are about 940 SF (69%) larger than homes under $399K

2026-11-08T07:17:41.178004 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $399K 34 sales $399K– $462K 34 sales $464K– $550K 35 sales Over $550K 34 sales 0 1,000 2,000 1,370 1,807 2,107 2,311 Living area (SF), average

The average is 2,311 SF for homes over $550K and 1,370 SF for homes under $399K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-11-08T07:17:41.201683 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $399K 34 sales $399K– $462K 34 sales $464K– $550K 35 sales Over $550K 34 sales 1980 1984 1988 1992 1984 1987 1986 1984 Year built: median (dot) and middle half (bar)

The median is 1984 for homes over $550K and 1984 for homes under $399K. It does not move in a straight line; homes $399K–$462K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-08T07:17:41.224174 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $399K 34 sales $399K– $462K 34 sales $464K– $550K 35 sales Over $550K 34 sales 0 20 40 34 20 20 16 Days on market, median

The median is 16 days for homes over $550K and 34 days for homes under $399K. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-08T07:17:41.245986 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $399K 34 sales $399K– $462K 34 sales $464K– $550K 35 sales Over $550K 34 sales 0.0% 5.0% 10.0% 9.6% 6.9% 4.7% 3.5% Discount from original list, average

The average is 3.5% for homes over $550K and 9.6% for homes under $399K. It falls step by step from the lowest range to the 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

2026-11-08T07:17:41.275617 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% 41% 53% 15% 47% 65% 12% 46% 60% 9% 24% 68% 6% Under $399K $399K–$462K $464K–$550K Over $550K

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

  • 24% of homes over $550K had a price cut before sale, against 41% of homes under $399K. Defined in 8.1.7.
  • 68% of homes over $550K had the seller pay closing costs or repairs, against 53% of homes under $399K. Defined in 8.1.8.
  • 6% of homes over $550K have a view, against 15% of homes under $399K. 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 $399K34 sales$399K–$462K34 sales$464K–$550K35 salesOver $550K34 salesAll137 salesReal difference?
Net sale price average$341,151$428,193$499,011$619,111$472,064by design
Net price per SF average$259$247$250$279$259unclear
Living area average1,3701,8072,1072,3111,900✓ large
Year built median19841987198619841985unclear

3.10 The numbers: selling

Under $399K34 sales$399K–$462K34 sales$464K–$550K35 salesOver $550K34 salesAll137 salesReal difference?
Days on market median3420201620unclear
Discount from original list average9.6%6.9%4.7%3.5%6.2%unclear
Price cut before sale41%47%46%24%39%unclear
Seller paid closing costs or repairs53%65%60%68%61%unclear
Has a view15%12%9%6%10%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 · 137 sales · November 8, 2025 – November 7, 2026

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

2026-11-08T07:17:41.296418 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 34 34 35 34 137 sales Sales per group Under 1,510 SF: 34 sales (25%) 1,510–1,823 SF: 34 sales (25%) 1,850–2,175 SF: 35 sales (26%) Over 2,175 SF: 34 sales (25%)
Bottom line

4.1 Key differences

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

Under 1,510 SF1,510–1,823 SF1,850–2,175 SFOver 2,175 SF
Larger homes Over 2,175 SF
  • Sell for much more.
  • Sell for less per square foot.
  • Tend to be newer.
Smaller homes Under 1,510 SF
  • Sell for much less.
  • Sell for more per square foot.
  • Tend to be older.

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 1,510 SF1,510–1,823 SF1,850–2,175 SFOver 2,175 SFReal difference?
Net sale price$361KLowest$466K$488K$572KHighest✓ large
Net price per SF$289 per SFHighest$283 per SF$243 per SF$220 per SFLowest✓ large
Year built1984Oldest198419891989Newest✓ medium
Days on market18 days26 days39 days19 daysunclear
Discount from original list7.0%5.9%6.5%5.4%unclear
Price cut before sale35%38%51%32%unclear
Seller paid closing costs or repairs62%50%54%79%unclear
Has a view15%9%11%6%unclear

4.3 Homes over 2,175 SF sell for about $211K (59%) more than homes under 1,510 SF

2026-11-08T07:17:41.317636 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,510 SF 34 sales 1,510– 1,823 SF 34 sales 1,850– 2,175 SF 35 sales Over 2,175 SF 34 sales $0K $200K $400K $600K $361K $466K $488K $572K Net sale price, average

The average is $572K for homes over 2,175 SF and $361K for homes under 1,510 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 2,175 SF sell for about $69 per SF (24%) less than homes under 1,510 SF

2026-11-08T07:17:41.341422 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,510 SF 34 sales 1,510– 1,823 SF 34 sales 1,850– 2,175 SF 35 sales Over 2,175 SF 34 sales $0 $100 $200 $300 $289 $283 $243 $220 Net price per SF, average

The average is $220 per SF for homes over 2,175 SF and $289 per SF for homes under 1,510 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Homes over 2,175 SF are about 5 years newer than homes under 1,510 SF

2026-11-08T07:17:41.365083 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,510 SF 34 sales 1,510– 1,823 SF 34 sales 1,850– 2,175 SF 35 sales Over 2,175 SF 34 sales 1984 1988 1992 1996 1984 1984 1989 1989 Year built: median (dot) and middle half (bar)

The median is 1989 for homes over 2,175 SF and 1984 for homes under 1,510 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

✓ Real difference · medium

4.6 Days on market: no clear difference

2026-11-08T07:17:41.387708 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,510 SF 34 sales 1,510– 1,823 SF 34 sales 1,850– 2,175 SF 35 sales Over 2,175 SF 34 sales 0 20 40 18 26 39 19 Days on market, median

The median is 19 days for homes over 2,175 SF and 18 days for homes under 1,510 SF. It does not move in a straight line; homes 1,850–2,175 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-08T07:17:41.409843 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,510 SF 34 sales 1,510– 1,823 SF 34 sales 1,850– 2,175 SF 35 sales Over 2,175 SF 34 sales 0.0% 2.5% 5.0% 7.5% 7.0% 5.9% 6.5% 5.4% Discount from original list, average

The average is 5.4% for homes over 2,175 SF and 7.0% for homes under 1,510 SF. It does not move in a straight line; homes under 1,510 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

2026-11-08T07:17:41.436807 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% 35% 62% 15% 38% 50% 9% 51% 54% 11% 32% 79% 6% Under 1,510 SF 1,510–1,823 SF 1,850–2,175 SF Over 2,175 SF

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

  • 32% of homes over 2,175 SF had a price cut before sale, against 35% of homes under 1,510 SF. Defined in 8.1.7.
  • 79% of homes over 2,175 SF had the seller pay closing costs or repairs, against 62% of homes under 1,510 SF. Defined in 8.1.8.
  • 6% of homes over 2,175 SF have a view, against 15% of homes under 1,510 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 1,510 SF34 sales1,510–1,823 SF34 sales1,850–2,175 SF35 salesOver 2,175 SF34 salesAll137 salesReal difference?
Net sale price average$360,859$466,382$488,447$572,088$472,064✓ large
Net price per SF average$289$283$243$220$259✓ large
Living area average1,2641,6482,0162,6701,900by design
Year built median19841984198919891985✓ medium

4.10 The numbers: selling

Under 1,510 SF34 sales1,510–1,823 SF34 sales1,850–2,175 SF35 salesOver 2,175 SF34 salesAll137 salesReal difference?
Days on market median1826391920unclear
Discount from original list average7.0%5.9%6.5%5.4%6.2%unclear
Price cut before sale35%38%51%32%39%unclear
Seller paid closing costs or repairs62%50%54%79%61%unclear
Has a view15%9%11%6%10%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 · 137 sales · November 8, 2025 – November 7, 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.

2026-11-08T07:17:41.457298 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 34 28 43 32 137 sales Sales per group Before 1984: 34 sales (25%) 1984: 28 sales (20%) 1985–1991: 43 sales (31%) After 1991: 32 sales (23%)
Bottom line

5.1 Key differences

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

Before 198419841985–1991After 1991
Newer homes After 1991
  • Sell for much less.
  • Are much larger.
  • Sell for less per square foot.
Older homes Before 1984
  • Sell for much more.
  • Are much smaller.
  • Sell for more per square foot.

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 198419841985–1991After 1991Real difference?
Net sale price$548KHighest$405KLowest$426K$512K✓ large
Net price per SF$299 per SFHighest$271 per SF$246 per SF$222 per SFLowest✓ large
Living area1,838 SF1,526 SFSmallest1,854 SF2,356 SFLargest✓ large
Days on market32 days24 days23 days13 daysunclear
Discount from original list5.6%7.4%7.1%4.5%unclear
Price cut before sale41%39%44%31%unclear
Seller paid closing costs or repairs53%54%65%72%unclear
Has a view9%11%12%9%unclear

5.3 Homes built after 1991 sell for about $36K (7%) less than homes built before 1984

2026-11-08T07:17:41.477783 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 34 sales 1984 28 sales 1985– 1991 43 sales After 1991 32 sales $0K $200K $400K $600K $548K $405K $426K $512K Net sale price, average

The average is $512K for homes built after 1991 and $548K for homes built before 1984. It does not move in a straight line; homes built before 1984 are highest. Defined in 8.1.1.

✓ Real difference · large

5.4 Homes built after 1991 sell for about $77 per SF (26%) less than homes built before 1984

2026-11-08T07:17:41.500726 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 34 sales 1984 28 sales 1985– 1991 43 sales After 1991 32 sales $0 $100 $200 $300 $299 $271 $246 $222 Net price per SF, average

The average is $222 per SF for homes built after 1991 and $299 per SF for homes built before 1984. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

5.5 Homes built after 1991 are about 520 SF (28%) larger than homes built before 1984

2026-11-08T07:17:41.523404 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 34 sales 1984 28 sales 1985– 1991 43 sales After 1991 32 sales 0 1,000 2,000 1,838 1,526 1,854 2,356 Living area (SF), average

The average is 2,356 SF for homes built after 1991 and 1,838 SF for homes built before 1984. It does not move in a straight line; homes built after 1991 are highest. Defined in 8.1.3.

✓ Real difference · large

5.6 Days on market: no clear difference

2026-11-08T07:17:41.545346 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 34 sales 1984 28 sales 1985– 1991 43 sales After 1991 32 sales 0 10 20 30 32 24 23 13 Days on market, median

The median is 13 days for homes built after 1991 and 32 days for homes built before 1984. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-08T07:17:41.568750 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 34 sales 1984 28 sales 1985– 1991 43 sales After 1991 32 sales 0.0% 2.5% 5.0% 7.5% 5.6% 7.4% 7.1% 4.5% Discount from original list, average

The average is 4.5% for homes built after 1991 and 5.6% for homes built before 1984. It does not move in a straight line; homes built 1984 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-08T07:17:41.593664 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% 41% 53% 9% 39% 54% 11% 44% 65% 12% 31% 72% 9% Before 1984 1984 1985–1991 After 1991

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

  • 31% of homes built after 1991 had a price cut before sale, against 41% of homes built before 1984. Defined in 8.1.7.
  • 72% of homes built after 1991 had the seller pay closing costs or repairs, against 53% of homes built before 1984. Defined in 8.1.8.
  • 9% of homes built after 1991 have a view, against 9% of homes built before 1984. 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 198434 sales198428 sales1985–199143 salesAfter 199132 salesAll137 salesReal difference?
Net sale price average$548,004$405,267$425,855$511,919$472,064✓ large
Net price per SF average$299$271$246$222$259✓ large
Living area average1,8381,5261,8542,3561,900✓ large
Year built median19811984198719961985by design

5.10 The numbers: selling

Before 198434 sales198428 sales1985–199143 salesAfter 199132 salesAll137 salesReal difference?
Days on market median3224231320unclear
Discount from original list average5.6%7.4%7.1%4.5%6.2%unclear
Price cut before sale41%39%44%31%39%unclear
Seller paid closing costs or repairs53%54%65%72%61%unclear
Has a view9%11%12%9%10%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 · 137 sales · November 8, 2025 – November 7, 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. 3 sales whose MLS view entry is only “See Remarks” are left out.

2026-11-08T07:17:41.612488 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 120 134 sales Sales per group View: 14 sales (10%) No view: 120 sales (90%)
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$429K$475Kunclear
Net price per SF$265 per SF$258 per SFunclear
Living area1,711 SF1,919 SFunclear
Year built19861985unclear
Days on market21 days22 daysunclear
Discount from original list5.4%6.4%unclear
Price cut before sale43%40%unclear
Seller paid closing costs or repairs64%60%unclear

6.3 Net sale price: no clear difference

2026-11-08T07:17:41.628888 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 14 sales No view 120 sales $0K $200K $400K $429K $475K Net sale price, average

The average is $429K for homes with a view and $475K 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

2026-11-08T07:17:41.645979 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 14 sales No view 120 sales $0 $100 $200 $300 $265 $258 Net price per SF, average

The average is $265 per SF for homes with a view and $258 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

2026-11-08T07:17:41.664263 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 14 sales No view 120 sales 0 500 1,000 1,500 2,000 1,711 1,919 Living area (SF), average

The average is 1,711 SF for homes with a view and 1,919 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-08T07:17:41.706153 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 14 sales No view 120 sales 1984 1986 1988 1990 1986 1985 Year built: median (dot) and middle half (bar)

The median is 1986 for homes with a view and 1985 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-08T07:17:41.724086 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 14 sales No view 120 sales 0 10 20 21 22 Days on market, median

The median is 21 days for homes with a view and 22 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

2026-11-08T07:17:41.742201 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 14 sales No view 120 sales 0.0% 2.0% 4.0% 6.0% 5.4% 6.4% Discount from original list, average

The average is 5.4% for homes with a view and 6.4% 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

2026-11-08T07:17:41.760441 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 43% 64% 40% 60% View No view

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

  • 43% of homes with a view had a price cut before sale, against 40% 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 60% of homes without a view. Defined in 8.1.8.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance

6.10 The numbers: price and size

View14 salesNo view120 salesAll134 salesReal difference?
Net sale price average$428,802$475,430$470,558unclear
Net price per SF average$265$258$258unclear
Living area average1,7111,9191,897unclear
Year built median198619851985unclear

6.11 The numbers: selling

View14 salesNo view120 salesAll134 salesReal difference?
Days on market median212222unclear
Discount from original list average5.4%6.4%6.3%unclear
Price cut before sale43%40%40%unclear
Seller paid closing costs or repairs64%60%60%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 8, 2025 – November 7, 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 Milwood.

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
137 resale sales. Average $472,064; median $464,000; standard deviation $112,395; middle half (25th–75th percentile) $399,000–$549,707; lowest $205,000, highest $981,000. 84 sales had a seller payment; their median payment was $7,082.

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
137 resale sales. Average $259; median $255; standard deviation $55; middle half (25th–75th percentile) $219–$296; lowest $140, highest $405.

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
137 resale sales. Average 1,900; median 1,850; standard deviation 576; middle half (25th–75th percentile) 1,510–2,175; lowest 778, highest 3,933.

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
137 resale sales. Average 1987; median 1985; standard deviation 6; middle half (25th–75th percentile) 1984–1991; lowest 1973, 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
137 resale sales. Average 66; median 20; standard deviation 95; middle half (25th–75th percentile) 9–83; lowest 1, highest 692. 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
137 resale sales. Average 6.2%; median 4.3%; standard deviation 8.2%; middle half (25th–75th percentile) 0.9%–8.9%; lowest −9.6%, highest 41.3%. 16 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
54 of 137 resale sales (39.4%).

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
84 of 137 resale sales (61.3%).

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
14 sales with a view, 120 without, 3 unclassified. Most common View entries: None 93, Neighborhood 33, Park/Greenbelt 8, Garden 4, Trees/Woods 4, See Remarks 2, Creek/Stream 2, City 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 2026-11-08 13:15 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “milwood”, “angus valley annex” (case-insensitive). A record is kept when its subdivision name belongs to the Milwood family, the same rule comparable sales use (it includes Angus Valley Annex, proven adjacent and priced alike).
The data
Pulled November 8, 2026: 138 closed Milwood records over the prior year, in ZIP 78729, 78727. 56 subdivision spellings kept, the most common: Milwood Sec 38B (8); Milwood Sec 11 (7); Milwood (7); Milwood Sec 01 Ph 01 (6); Milwood Sec 08 (6); Milwood Sec 10 (6); Milwood Sec 14 (6); Milwood Sec 28 (5); Milwood Sec 15-A (5); Milwood Sec 36 (5); Milwood Sec 31A (4); Milwood Sec 26B (4); and 44 more (69 records). 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 67 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 8, 2025 to November 7, 2026 inclusive.
The data
137 single-family sales in the window: 137 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
137 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
1 sale(s) with no original list price

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 $399K”.
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 $399K: $205,000–$397,500 (34 sales); $399K–$462K: $399,000–$462,230 (34 sales); $464K–$550K: $464,000–$549,707 (35 sales); Over $550K: $550,000–$981,000 (34 sales)
Quartiles by living area: Under 1,510 SF: 778–1,509 SF (34 sales); 1,510–1,823 SF: 1,510–1,823 SF (34 sales); 1,850–2,175 SF: 1,850–2,175 SF (35 sales); Over 2,175 SF: 2,183–3,933 SF (34 sales)
Quartiles by year built: Before 1984: 1973–1983 (34 sales); 1984: 1984–1984 (28 sales); 1985–1991: 1985–1991 (43 sales); After 1991: 1992–1999 (32 sales)
View and no view: View: MLS lists a view (14 sales); No view: None or Neighborhood (120 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 $472,064, median $464,000. Days on market: average 66, 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
7 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

In simple terms
Headings and sentences round figures so they read easily; the tables at the end of each section give them in full.
Statistically
Prices in headings round to the nearest $1K; price per SF and days on market to the nearest whole number; living area to the nearest 10 SF; shares and percentage gaps to whole percents.
The data
Days on market is always shown in days.

8.3 Test results

Every test behind every gold box. Statistic, degrees of freedom (df), p-value, the threshold it must beat, and the size of the difference.

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 5.4730.1403p < 0.0063Unclearε² = 0.040small
Living areaKruskal–WallisH = 62.633< 0.0001p < 0.0063Yesε² = 0.461large
Year builtKruskal–WallisH = 6.7330.0809p < 0.0063Unclearε² = 0.050small
Days on marketKruskal–WallisH = 3.3830.3367p < 0.0063Unclearε² = 0.025small
Discount from original listKruskal–WallisH = 9.0130.0292p < 0.0063Unclearε² = 0.066medium
Price cut before saleChi-squareχ² = 5.0530.1681p < 0.0063UnclearCramér’s V = 0.192small
Seller paid closing costs or repairsChi-squareχ² = 1.7730.6215p < 0.0063UnclearCramér’s V = 0.114small
Has a viewChi-squareχ² = 1.6430.6515p < 0.0063UnclearCramér’s V = 0.109small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 68.243< 0.0001p < 0.0063Yesε² = 0.502large
Net price per SFKruskal–WallisH = 40.083< 0.0001p < 0.0063Yesε² = 0.295large
Year builtKruskal–WallisH = 13.7930.0032p < 0.0063Yesε² = 0.101medium
Days on marketKruskal–WallisH = 1.3830.7095p < 0.0063Unclearε² = 0.010small
Discount from original listKruskal–WallisH = 0.5030.9194p < 0.0063Unclearε² = 0.004negligible
Price cut before saleChi-squareχ² = 3.0930.3784p < 0.0063UnclearCramér’s V = 0.150small
Seller paid closing costs or repairsChi-squareχ² = 7.2630.0640p < 0.0063UnclearCramér’s V = 0.230small
Has a viewChi-squareχ² = 1.5730.6660p < 0.0063UnclearCramér’s V = 0.107small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 38.013< 0.0001p < 0.0063Yesε² = 0.279large
Net price per SFKruskal–WallisH = 36.423< 0.0001p < 0.0063Yesε² = 0.268large
Living areaKruskal–WallisH = 36.973< 0.0001p < 0.0063Yesε² = 0.272large
Days on marketKruskal–WallisH = 4.1130.2503p < 0.0063Unclearε² = 0.030small
Discount from original listKruskal–WallisH = 3.2630.3533p < 0.0063Unclearε² = 0.024small
Price cut before saleChi-squareχ² = 1.3530.7179p < 0.0063UnclearCramér’s V = 0.099negligible
Seller paid closing costs or repairsChi-squareχ² = 3.4830.3235p < 0.0063UnclearCramér’s V = 0.159small
Has a viewChi-squareχ² = 0.2030.9780p < 0.0063UnclearCramér’s V = 0.038negligible

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 627.00—0.1222p < 0.0063Unclearrank-biserial r = 0.254small
Net price per SFMann–Whitney UU = 909.00—0.6183p < 0.0063Unclearrank-biserial r = 0.082negligible
Living areaMann–Whitney UU = 687.00—0.2673p < 0.0063Unclearrank-biserial r = 0.182small
Year builtMann–Whitney UU = 849.50—0.9475p < 0.0063Unclearrank-biserial r = 0.011negligible
Days on marketMann–Whitney UU = 884.00—0.7516p < 0.0063Unclearrank-biserial r = 0.052negligible
Discount from original listMann–Whitney UU = 825.50—0.9189p < 0.0063Unclearrank-biserial r = 0.017negligible
Price cut before saleChi-squareχ² = 0.0410.8366p < 0.0063UnclearCramér’s V = 0.018negligible
Seller paid closing costs or repairsChi-squareχ² = 0.1010.7563p < 0.0063UnclearCramér’s V = 0.027negligible

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 1 sale(s) with no original list price. 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 137 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 8, 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.