ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Delwood

Austin, TX 78723 · 78722
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 · 7:41 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
39
single-family resale homes
Median net sale price
$529,025
average $562,189
Median net price per SF
$367
average $371
Median days on market
26 days
average 45 days
1. SummaryResale homes · 39 sales · October 26, 2025 – October 25, 2026

This study looks at the 39 resale homes sold in Delwood in the 365 days to October 25, 2026. A full year is used because only 22 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 sold39 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 $457K · 10 sales$457K–$529K · 10 sales$540K–$620K · 9 salesOver $620K · 10 sales
3. Quartiles by net sale priceResale homes · 39 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.

2026-10-26T07:41:15.678368 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 9 10 39 sales Sales per group Under $457K: 10 sales (26%) $457K–$529K: 10 sales (26%) $540K–$620K: 9 sales (23%) Over $620K: 10 sales (26%)
Bottom line

3.1 Key differences

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

Under $457K$457K–$529K$540K–$620KOver $620K
Higher-priced homes Over $620K
  • Are much larger.
Lower-priced homes Under $457K
  • 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 $457K$457K–$529K$540K–$620KOver $620KReal difference?
Net price per SF$322 per SF$388 per SF$358 per SF$414 per SFunclear
Living area1,268 SFSmallest1,322 SF1,617 SF1,897 SFLargest✓ large
Year built1954195419581959unclear
Days on market8 days32 days39 days37 daysunclear
Discount from original list4.8%7.1%6.2%5.6%unclear
Price cut before sale10%40%56%50%unclear
Seller paid closing costs or repairs40%40%78%70%unclear
Has a view10%0%11%10%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

2026-10-26T07:41:15.705871 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $457K 10 sales $457K– $529K 10 sales $540K– $620K 9 sales Over $620K 10 sales $0 $200 $400 $322 $388 $358 $414 Net price per SF, average

The average is $414 per SF for homes over $620K and $322 per SF for homes under $457K. It does not move in a straight line; homes over $620K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $620K are about 630 SF (50%) larger than homes under $457K

2026-10-26T07:41:15.727443 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $457K 10 sales $457K– $529K 10 sales $540K– $620K 9 sales Over $620K 10 sales 0 1,000 2,000 1,268 1,322 1,617 1,897 Living area (SF), average

The average is 1,897 SF for homes over $620K and 1,268 SF for homes under $457K. 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

2026-10-26T07:41:15.749686 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $457K 10 sales $457K– $529K 10 sales $540K– $620K 9 sales Over $620K 10 sales 1954 1956 1958 1954 1954 1958 1959 Year built: median (dot) and middle half (bar)

The median is 1959 for homes over $620K and 1954 for homes under $457K. It does not move in a straight line; homes over $620K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:41:15.771544 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $457K 10 sales $457K– $529K 10 sales $540K– $620K 9 sales Over $620K 10 sales 0 20 40 8 32 39 37 Days on market, median

The median is 37 days for homes over $620K and 8 days for homes under $457K. It does not move in a straight line; homes $540K–$620K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:41:15.793405 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $457K 10 sales $457K– $529K 10 sales $540K– $620K 9 sales Over $620K 10 sales 0.0% 2.5% 5.0% 7.5% 4.8% 7.1% 6.2% 5.6% Discount from original list, average

The average is 5.6% for homes over $620K and 4.8% for homes under $457K. It does not move in a straight line; homes $457K–$529K 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

2026-10-26T07:41:15.823405 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% 10 40 10 40 40 0 56 78 11 50 70 10 Under $457K $457K–$529K $540K–$620K Over $620K

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

  • 50% of homes over $620K had a price cut before sale, against 10% of homes under $457K. Defined in 8.1.7.
  • 70% of homes over $620K had the seller pay closing costs or repairs, against 40% of homes under $457K. Defined in 8.1.8.
  • 10% of homes over $620K have a view, against 10% of homes under $457K. 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 $457K10 sales$457K–$529K10 sales$540K–$620K9 salesOver $620K10 salesAll39 salesReal difference?
Net sale price average$392,310$499,478$569,489$788,208$562,189by design
Net price per SF average$322$388$358$414$371unclear
Living area average1,2681,3221,6171,8971,523✓ large
Year built median19541954195819591955unclear

3.10 The numbers: selling

Under $457K10 sales$457K–$529K10 sales$540K–$620K9 salesOver $620K10 salesAll39 salesReal difference?
Days on market median832393726unclear
Discount from original list average4.8%7.1%6.2%5.6%5.9%unclear
Price cut before sale10%40%56%50%38%unclear
Seller paid closing costs or repairs40%40%78%70%56%unclear
Has a view10%0%11%10%8%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 · 39 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.

2026-10-26T07:41:15.844562 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 9 10 39 sales Sales per group Under 1,244 SF: 10 sales (26%) 1,244–1,530 SF: 10 sales (26%) 1,542–1,674 SF: 9 sales (23%) Over 1,674 SF: 10 sales (26%)
Bottom line

4.1 Key differences

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

Under 1,244 SF1,244–1,530 SF1,542–1,674 SFOver 1,674 SF
Larger homes Over 1,674 SF
  • Sell for much more.
Smaller homes Under 1,244 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 1,244 SF1,244–1,530 SF1,542–1,674 SFOver 1,674 SFReal difference?
Net sale price$450KLowest$479K$581K$741KHighest✓ large
Net price per SF$408 per SF$343 per SF$361 per SF$370 per SFunclear
Year built1954195419591958unclear
Days on market18 days20 days71 days28 daysunclear
Discount from original list1.8%6.9%7.2%7.9%unclear
Price cut before sale10%30%78%40%unclear
Seller paid closing costs or repairs40%60%56%70%unclear
Has a view0%20%11%0%unclear

4.3 Homes over 1,674 SF sell for about $291K (65%) more than homes under 1,244 SF

2026-10-26T07:41:15.865213 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,244 SF 10 sales 1,244– 1,530 SF 10 sales 1,542– 1,674 SF 9 sales Over 1,674 SF 10 sales $0K $250K $500K $750K $450K $479K $581K $741K Net sale price, average

The average is $741K for homes over 1,674 SF and $450K for homes under 1,244 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

2026-10-26T07:41:15.887713 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,244 SF 10 sales 1,244– 1,530 SF 10 sales 1,542– 1,674 SF 9 sales Over 1,674 SF 10 sales $0 $200 $400 $408 $343 $361 $370 Net price per SF, average

The average is $370 per SF for homes over 1,674 SF and $408 per SF for homes under 1,244 SF. It does not move in a straight line; homes under 1,244 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:41:15.909848 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,244 SF 10 sales 1,244– 1,530 SF 10 sales 1,542– 1,674 SF 9 sales Over 1,674 SF 10 sales 1954 1956 1958 1954 1954 1959 1958 Year built: median (dot) and middle half (bar)

The median is 1958 for homes over 1,674 SF and 1954 for homes under 1,244 SF. It does not move in a straight line; homes 1,542–1,674 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:41:15.932470 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,244 SF 10 sales 1,244– 1,530 SF 10 sales 1,542– 1,674 SF 9 sales Over 1,674 SF 10 sales 0 25 50 75 18 20 71 28 Days on market, median

The median is 28 days for homes over 1,674 SF and 18 days for homes under 1,244 SF. It does not move in a straight line; homes 1,542–1,674 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:41:15.954638 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,244 SF 10 sales 1,244– 1,530 SF 10 sales 1,542– 1,674 SF 9 sales Over 1,674 SF 10 sales 0.0% 2.5% 5.0% 7.5% 1.8% 6.9% 7.2% 7.9% Discount from original list, average

The average is 7.9% for homes over 1,674 SF and 1.8% for homes under 1,244 SF. It rises step by step from the lowest range to the 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

2026-10-26T07:41:15.981094 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% 10 40 0 30 60 20 78 56 11 40 70 0 Under 1,244 SF 1,244–1,530 SF 1,542–1,674 SF Over 1,674 SF

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

  • 40% of homes over 1,674 SF had a price cut before sale, against 10% of homes under 1,244 SF. Defined in 8.1.7.
  • 70% of homes over 1,674 SF had the seller pay closing costs or repairs, against 40% of homes under 1,244 SF. Defined in 8.1.8.
  • 0% of homes over 1,674 SF have a view, against 0% of homes under 1,244 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 1,244 SF10 sales1,244–1,530 SF10 sales1,542–1,674 SF9 salesOver 1,674 SF10 salesAll39 salesReal difference?
Net sale price average$449,900$478,888$581,300$740,578$562,189✓ large
Net price per SF average$408$343$361$370$371unclear
Living area average1,1151,4021,6061,9781,523by design
Year built median19541954195919581955unclear

4.10 The numbers: selling

Under 1,244 SF10 sales1,244–1,530 SF10 sales1,542–1,674 SF9 salesOver 1,674 SF10 salesAll39 salesReal difference?
Days on market median1820712826unclear
Discount from original list average1.8%6.9%7.2%7.9%5.9%unclear
Price cut before sale10%30%78%40%38%unclear
Seller paid closing costs or repairs40%60%56%70%56%unclear
Has a view0%20%11%0%8%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 · 39 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.

2026-10-26T07:41:16.001471 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 16 4 6 13 39 sales Sales per group Before 1955: 16 sales (41%) 1955: 4 sales (10%) 1956–1958: 6 sales (15%) After 1958: 13 sales (33%)
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

2026-10-26T07:41:16.021878 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1955 16 sales 1955 4 sales 1956– 1958 6 sales After 1958 13 sales $0K $200K $400K $600K $507K $526K $655K $598K Net sale price, average

The average is $598K for homes built after 1958 and $507K for homes built before 1955. It does not move in a straight line; homes built 1956–1958 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T07:41:16.044354 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1955 16 sales 1955 4 sales 1956– 1958 6 sales After 1958 13 sales $0 $200 $400 $384 $341 $368 $365 Net price per SF, average

The average is $365 per SF for homes built after 1958 and $384 per SF for homes built before 1955. It does not move in a straight line; homes built before 1955 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T07:41:16.065248 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1955 16 sales 1955 4 sales 1956– 1958 6 sales After 1958 13 sales 0 1,000 2,000 1,349 1,498 1,761 1,636 Living area (SF), average

The average is 1,636 SF for homes built after 1958 and 1,349 SF for homes built before 1955. It does not move in a straight line; homes built 1956–1958 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T07:41:16.086363 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1955 16 sales 1955 4 sales 1956– 1958 6 sales After 1958 13 sales 0 25 50 75 22 16 79 25 Days on market, median

The median is 25 days for homes built after 1958 and 22 days for homes built before 1955. It does not move in a straight line; homes built 1956–1958 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T07:41:16.108738 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1955 16 sales 1955 4 sales 1956– 1958 6 sales After 1958 13 sales 0.0% 5.0% 10.0% 6.2% 1.3% 10.5% 4.9% Discount from original list, average

The average is 4.9% for homes built after 1958 and 6.2% for homes built before 1955. It does not move in a straight line; homes built 1956–1958 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

2026-10-26T07:41:16.133461 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% 31 50 6 0 25 0 83 67 33 38 69 0 Before 1955 1955 1956–1958 After 1958

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

  • 38% of homes built after 1958 had a price cut before sale, against 31% of homes built before 1955. Defined in 8.1.7.
  • 69% of homes built after 1958 had the seller pay closing costs or repairs, against 50% of homes built before 1955. Defined in 8.1.8.
  • 0% of homes built after 1958 have a view, against 6% of homes built before 1955. 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 195516 sales19554 sales1956–19586 salesAfter 195813 salesAll39 sales
Net sale price average$507,016$526,250$655,233$598,207$562,189
Net price per SF average$384$341$368$365$371
Living area average1,3491,4981,7611,6361,523
Year built median19541955195719591955

5.10 The numbers: selling

Before 195516 sales19554 sales1956–19586 salesAfter 195813 salesAll39 sales
Days on market median2216792526
Discount from original list average6.2%1.3%10.5%4.9%5.9%
Price cut before sale31%0%83%38%38%
Seller paid closing costs or repairs50%25%67%69%56%
Has a view6%0%33%0%8%

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 · 39 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.

2026-10-26T07:41:16.151775 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 36 39 sales Sales per group View: 3 sales (8%) No view: 36 sales (92%)
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

2026-10-26T07:41:16.166934 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 36 sales $0K $200K $400K $600K $524K $565K Net sale price, average

The average is $524K for homes with a view and $565K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T07:41:16.185733 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 36 sales $0 $100 $200 $300 $400 $343 $373 Net price per SF, average

The average is $343 per SF for homes with a view and $373 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T07:41:16.204562 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 36 sales 0 500 1,000 1,500 1,496 1,526 Living area (SF), average

The average is 1,496 SF for homes with a view and 1,526 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T07:41:16.244093 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 36 sales 1954 1956 1958 1957 1955 Year built: median (dot) and middle half (bar)

The median is 1957 for homes with a view and 1955 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T07:41:16.261840 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 36 sales 0 10 20 30 40 39 26 Days on market, median

The median is 39 days for homes with a view and 26 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

2026-10-26T07:41:16.279867 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 36 sales 0.0% 2.0% 4.0% 6.0% 6.1% 5.9% Discount from original list, average

The average is 6.1% for homes with a view and 5.9% 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

2026-10-26T07:41:16.298009 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 67 33 36 58 View No view

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

  • 67% of homes with a view had a price cut before sale, against 36% of homes without a view. Defined in 8.1.7.
  • 33% of homes with a view had the seller pay closing costs or repairs, against 58% 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

View3 salesNo view36 salesAll39 sales
Net sale price average$524,500$565,329$562,189
Net price per SF average$343$373$371
Living area average1,4961,5261,523
Year built median195719551955

6.11 The numbers: selling

View3 salesNo view36 salesAll39 sales
Days on market median392626
Discount from original list average6.1%5.9%5.9%
Price cut before sale67%36%38%
Seller paid closing costs or repairs33%58%56%

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 Delwood.

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
39 resale sales. Average $562,189; median $529,025; standard deviation $169,001; middle half (25th–75th percentile) $455,250–$627,045; lowest $275,000, highest $1,045,000. 22 sales had a seller payment; their median payment was $6,750.

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
39 resale sales. Average $371; median $367; standard deviation $73; middle half (25th–75th percentile) $333–$416; lowest $208, highest $518.

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
39 resale sales. Average 1,523; median 1,530; standard deviation 348; middle half (25th–75th percentile) 1,234–1,693; lowest 849, highest 2,346.

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
39 resale sales. Average 1956; median 1955; standard deviation 3; middle half (25th–75th percentile) 1954–1959; lowest 1947, highest 1963.

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
39 resale sales. Average 45; median 26; standard deviation 50; middle half (25th–75th percentile) 10–60; lowest 4, highest 195. 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
39 resale sales. Average 5.9%; median 4.0%; standard deviation 6.6%; middle half (25th–75th percentile) 2.3%–9.5%; lowest −6.7%, highest 27.5%. 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
15 of 39 resale sales (38.5%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
22 of 39 resale sales (56.4%).

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
3 sales with a view, 36 without, 0 unclassified. Most common View entries: None 29, Neighborhood 10, City 2, Trees/Woods 1, Pasture 1, Garden 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 = Austin, SubdivisionName contains any of “delwood” (case-insensitive). A record is kept when its subdivision name belongs to the Delwood family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 40 closed Delwood records over the prior year, in ZIP 78723, 78722. 11 subdivision spellings kept: Delwood 04 East Sec 03 (10); Delwood 04 Sec B (9); Delwood Sec 04 (8); Delwood 04 East Sec 02 (4); Delwood (2); Delwood Sec 02 (2); Delwood 04 East Sec 01 (1); Delwood 4 East Sec 3 (1); Delwood 04 East Sec 04 (1); Delwood Sec (1); Delwood Sec 01 (1). Names found by the search but not part of Delwood, left out: Delwood Heights (7); Delwood Terrace Sec 01 (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 22 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
39 single-family sales in the window: 39 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
39 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 $457K”.
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 $457K: $275,000–$453,500 (10 sales); $457K–$529K: $457,000–$529,025 (10 sales); $540K–$620K: $540,000–$620,000 (9 sales); Over $620K: $634,090–$1,045,000 (10 sales)
Quartiles by living area: Under 1,244 SF: 849–1,224 SF (10 sales); 1,244–1,530 SF: 1,244–1,530 SF (10 sales); 1,542–1,674 SF: 1,542–1,674 SF (9 sales); Over 1,674 SF: 1,712–2,346 SF (10 sales)
Quartiles by year built: Before 1955: 1947–1954 (16 sales); 1955: 1955–1955 (4 sales); 1956–1958: 1956–1958 (6 sales); After 1958: 1959–1963 (13 sales)
View and no view: View: MLS lists a view (3 sales); No view: None or Neighborhood (36 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 $562,189, median $529,025. Days on market: average 45, median 26: 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
2 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 11.1830.0108p < 0.0063Unclearε² = 0.294large
Living areaKruskal–WallisH = 22.143< 0.0001p < 0.0063Yesε² = 0.583large
Year builtKruskal–WallisH = 8.3430.0395p < 0.0063Unclearε² = 0.219large
Days on marketKruskal–WallisH = 4.0930.2516p < 0.0063Unclearε² = 0.108medium
Discount from original listKruskal–WallisH = 1.2630.7389p < 0.0063Unclearε² = 0.033small
Price cut before saleChi-squareχ² = 5.1130.1642p < 0.0063UnclearCramér’s V = 0.362medium
Seller paid closing costs or repairsChi-squareχ² = 4.6130.2025p < 0.0063UnclearCramér’s V = 0.344medium
Has a viewChi-squareχ² = 1.1330.7695p < 0.0063UnclearCramér’s V = 0.170small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 19.0930.0003p < 0.0063Yesε² = 0.502large
Net price per SFKruskal–WallisH = 5.2030.1579p < 0.0063Unclearε² = 0.137medium
Year builtKruskal–WallisH = 10.1530.0173p < 0.0063Unclearε² = 0.267large
Days on marketKruskal–WallisH = 4.2230.2388p < 0.0063Unclearε² = 0.111medium
Discount from original listKruskal–WallisH = 6.0830.1076p < 0.0063Unclearε² = 0.160large
Price cut before saleChi-squareχ² = 9.6130.0222p < 0.0063UnclearCramér’s V = 0.496medium
Seller paid closing costs or repairsChi-squareχ² = 1.9030.5931p < 0.0063UnclearCramér’s V = 0.221small
Has a viewChi-squareχ² = 3.9530.2671p < 0.0063UnclearCramér’s V = 0.318medium

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); 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 39 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.