ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Legend Oaks Sec 07

Austin, TX 78749
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 · 7:47 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
36
single-family resale homes
Median net sale price
$619,500
average $632,019
Median net price per SF
$277
average $278
Median days on market
14 days
average 34 days
1. SummaryResale homes · 36 sales · October 26, 2025 – October 25, 2026

This study looks at the 36 resale homes sold in Legend Oaks Sec 07 in the 365 days to October 25, 2026. A full year is used because only 17 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 sold36 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 $548K · 9 sales$548K–$609K · 9 sales$630K–$660K · 9 salesOver $660K · 9 sales
3. Quartiles by net sale priceResale homes · 36 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.

2026-10-26T07:47:41.621494 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 9 9 9 36 sales Sales per group Under $548K: 9 sales (25%) $548K–$609K: 9 sales (25%) $630K–$660K: 9 sales (25%) Over $660K: 9 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 $548K$548K–$609K$630K–$660KOver $660K
Higher-priced homes Over $660K
  • Are much larger.
Lower-priced homes Under $548K
  • 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 $548K$548K–$609K$630K–$660KOver $660KReal difference?
Net price per SF$271 per SF$299 per SF$269 per SF$273 per SFunclear
Living area1,970 SFSmallest1,975 SF2,427 SF2,965 SFLargest✓ large
Year built1994199319951995unclear
Days on market20 days13 days14 days17 daysunclear
Discount from original list6.4%2.8%1.3%1.3%unclear
Price cut before sale44%22%11%33%unclear
Seller paid closing costs or repairs78%89%44%44%unclear
Has a view11%33%22%33%unclear

How to read this section. Each heading gives the finding. The gold box says whether the gap is real (✓, with its size) or could be chance (–). The section ends with its numbers; the tests are in section 8.3.

3.3 Net price per SF: no clear difference

2026-10-26T07:47:41.649278 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $548K 9 sales $548K– $609K 9 sales $630K– $660K 9 sales Over $660K 9 sales $0 $100 $200 $300 $271 $299 $269 $273 Net price per SF, average

The average is $273 per SF for homes over $660K and $271 per SF for homes under $548K. It does not move in a straight line; homes $548K–$609K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $660K are about 990 SF (51%) larger than homes under $548K

2026-10-26T07:47:41.671508 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $548K 9 sales $548K– $609K 9 sales $630K– $660K 9 sales Over $660K 9 sales 0 1,000 2,000 3,000 1,970 1,975 2,427 2,965 Living area (SF), average

The average is 2,965 SF for homes over $660K and 1,970 SF for homes under $548K. 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

2026-10-26T07:47:41.696185 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $548K 9 sales $548K– $609K 9 sales $630K– $660K 9 sales Over $660K 9 sales 1990 1992 1994 1996 1998 1994 1993 1995 1995 Year built: median (dot) and middle half (bar)

The median is 1995 for homes over $660K and 1994 for homes under $548K. It does not move in a straight line; homes $630K–$660K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:47:41.718941 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $548K 9 sales $548K– $609K 9 sales $630K– $660K 9 sales Over $660K 9 sales 0 10 20 20 13 14 17 Days on market, median

The median is 17 days for homes over $660K and 20 days for homes under $548K. It does not move in a straight line; homes under $548K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:47:41.740216 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $548K 9 sales $548K– $609K 9 sales $630K– $660K 9 sales Over $660K 9 sales 0.0% 2.0% 4.0% 6.0% 6.4% 2.8% 1.3% 1.3% Discount from original list, average

The average is 1.3% for homes over $660K and 6.4% for homes under $548K. It does not move in a straight line; homes under $548K 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

2026-10-26T07:47:41.770098 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% 44 78 11 22 89 33 11 44 22 33 44 33 Under $548K $548K–$609K $630K–$660K Over $660K

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

  • 33% of homes over $660K had a price cut before sale, against 44% of homes under $548K. Defined in 8.1.7.
  • 44% of homes over $660K had the seller pay closing costs or repairs, against 78% of homes under $548K. Defined in 8.1.8.
  • 33% of homes over $660K have a view, against 11% of homes under $548K. 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 $548K9 sales$548K–$609K9 sales$630K–$660K9 salesOver $660K9 salesAll36 salesReal difference?
Net sale price average$515,392$576,383$647,244$789,059$632,019by design
Net price per SF average$271$299$269$273$278unclear
Living area average1,9701,9752,4272,9652,334✓ large
Year built median19941993199519951995unclear

3.10 The numbers: selling

Under $548K9 sales$548K–$609K9 sales$630K–$660K9 salesOver $660K9 salesAll36 salesReal difference?
Days on market median2013141714unclear
Discount from original list average6.4%2.8%1.3%1.3%2.9%unclear
Price cut before sale44%22%11%33%28%unclear
Seller paid closing costs or repairs78%89%44%44%64%unclear
Has a view11%33%22%33%25%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 · 36 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.

2026-10-26T07:47:41.790203 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 9 9 9 36 sales Sales per group Under 1,932 SF: 9 sales (25%) 1,932–2,304 SF: 9 sales (25%) 2,306–2,648 SF: 9 sales (25%) Over 2,648 SF: 9 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 1,932 SF1,932–2,304 SF2,306–2,648 SFOver 2,648 SF
Larger homes Over 2,648 SF
  • Sell for much more.
  • Sell for less per square foot.
Smaller homes Under 1,932 SF
  • Sell for much less.
  • Sell for more per square foot.

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 1,932 SF1,932–2,304 SF2,306–2,648 SFOver 2,648 SFReal difference?
Net sale price$532KLowest$590K$688K$718KHighest✓ large
Net price per SF$315 per SFHighest$285 per SF$281 per SF$232 per SFLowest✓ large
Year built1995199319951995unclear
Days on market13 days19 days14 days17 daysunclear
Discount from original list3.6%2.0%2.3%3.8%unclear
Price cut before sale33%11%22%44%unclear
Seller paid closing costs or repairs89%78%56%33%unclear
Has a view11%56%22%11%unclear

4.3 Homes over 2,648 SF sell for about $186K (35%) more than homes under 1,932 SF

2026-10-26T07:47:41.810939 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,932 SF 9 sales 1,932– 2,304 SF 9 sales 2,306– 2,648 SF 9 sales Over 2,648 SF 9 sales $0K $250K $500K $750K $532K $590K $688K $718K Net sale price, average

The average is $718K for homes over 2,648 SF and $532K for homes under 1,932 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 2,648 SF sell for about $83 per SF (26%) less than homes under 1,932 SF

2026-10-26T07:47:41.833711 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,932 SF 9 sales 1,932– 2,304 SF 9 sales 2,306– 2,648 SF 9 sales Over 2,648 SF 9 sales $0 $100 $200 $300 $315 $285 $281 $232 Net price per SF, average

The average is $232 per SF for homes over 2,648 SF and $315 per SF for homes under 1,932 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-10-26T07:47:41.856060 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,932 SF 9 sales 1,932– 2,304 SF 9 sales 2,306– 2,648 SF 9 sales Over 2,648 SF 9 sales 1990 1993 1996 1995 1993 1995 1995 Year built: median (dot) and middle half (bar)

The median is 1995 for homes over 2,648 SF and 1995 for homes under 1,932 SF. It does not move in a straight line; homes under 1,932 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:47:41.878250 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,932 SF 9 sales 1,932– 2,304 SF 9 sales 2,306– 2,648 SF 9 sales Over 2,648 SF 9 sales 0 10 20 13 19 14 17 Days on market, median

The median is 17 days for homes over 2,648 SF and 13 days for homes under 1,932 SF. It does not move in a straight line; homes 1,932–2,304 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:47:41.899895 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,932 SF 9 sales 1,932– 2,304 SF 9 sales 2,306– 2,648 SF 9 sales Over 2,648 SF 9 sales 0.0% 2.0% 4.0% 3.6% 2.0% 2.3% 3.8% Discount from original list, average

The average is 3.8% for homes over 2,648 SF and 3.6% for homes under 1,932 SF. It does not move in a straight line; homes over 2,648 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:47:41.926042 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 89 11 11 78 56 22 56 22 44 33 11 Under 1,932 SF 1,932–2,304 SF 2,306–2,648 SF Over 2,648 SF

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

  • 44% of homes over 2,648 SF had a price cut before sale, against 33% of homes under 1,932 SF. Defined in 8.1.7.
  • 33% of homes over 2,648 SF had the seller pay closing costs or repairs, against 89% of homes under 1,932 SF. Defined in 8.1.8.
  • 11% of homes over 2,648 SF have a view, against 11% of homes under 1,932 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 1,932 SF9 sales1,932–2,304 SF9 sales2,306–2,648 SF9 salesOver 2,648 SF9 salesAll36 salesReal difference?
Net sale price average$532,100$589,697$688,256$718,026$632,019✓ large
Net price per SF average$315$285$281$232$278✓ large
Living area average1,7082,0682,4573,1032,334by design
Year built median19951993199519951995unclear

4.10 The numbers: selling

Under 1,932 SF9 sales1,932–2,304 SF9 sales2,306–2,648 SF9 salesOver 2,648 SF9 salesAll36 salesReal difference?
Days on market median1319141714unclear
Discount from original list average3.6%2.0%2.3%3.8%2.9%unclear
Price cut before sale33%11%22%44%28%unclear
Seller paid closing costs or repairs89%78%56%33%64%unclear
Has a view11%56%22%11%25%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 · 36 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.

2026-10-26T07:47:41.946998 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 11 9 36 sales Sales per group Before 1992: 8 sales (22%) 1992–1994: 8 sales (22%) 1995–1996: 11 sales (31%) After 1996: 9 sales (25%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

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

5.2 At a glance

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

Before 19921992–19941995–1996After 1996Real difference?
Net sale price$571K$657K$700K$581Kunclear
Net price per SF$288 per SF$261 per SF$275 per SF$288 per SFunclear
Living area2,007 SF2,530 SF2,631 SF2,088 SFunclear
Days on market7 days24 days14 days20 daysunclear
Discount from original list1.7%5.3%1.3%3.9%unclear
Price cut before sale12%38%27%33%unclear
Seller paid closing costs or repairs75%62%36%89%unclear
Has a view38%12%18%33%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:47:41.967849 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1992 8 sales 1992– 1994 8 sales 1995– 1996 11 sales After 1996 9 sales $0K $250K $500K $750K $571K $657K $700K $581K Net sale price, average

The average is $581K for homes built after 1996 and $571K for homes built before 1992. It does not move in a straight line; homes built 1995–1996 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:47:41.990613 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1992 8 sales 1992– 1994 8 sales 1995– 1996 11 sales After 1996 9 sales $0 $100 $200 $300 $288 $261 $275 $288 Net price per SF, average

The average is $288 per SF for homes built after 1996 and $288 per SF for homes built before 1992. It does not move in a straight line; homes built after 1996 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:47:42.012310 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1992 8 sales 1992– 1994 8 sales 1995– 1996 11 sales After 1996 9 sales 0 1,000 2,000 3,000 2,007 2,530 2,631 2,088 Living area (SF), average

The average is 2,088 SF for homes built after 1996 and 2,007 SF for homes built before 1992. It does not move in a straight line; homes built 1995–1996 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:47:42.034149 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1992 8 sales 1992– 1994 8 sales 1995– 1996 11 sales After 1996 9 sales 0 10 20 7 24 14 20 Days on market, median

The median is 20 days for homes built after 1996 and 7 days for homes built before 1992. It does not move in a straight line; homes built 1992–1994 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:47:42.056593 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1992 8 sales 1992– 1994 8 sales 1995– 1996 11 sales After 1996 9 sales 0.0% 2.0% 4.0% 6.0% 1.7% 5.3% 1.3% 3.9% Discount from original list, average

The average is 3.9% for homes built after 1996 and 1.7% for homes built before 1992. It does not move in a straight line; homes built 1992–1994 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:47:42.082380 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% 12 75 38 38 62 12 27 36 18 33 89 33 Before 1992 1992–1994 1995–1996 After 1996

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

  • 33% of homes built after 1996 had a price cut before sale, against 12% of homes built before 1992. Defined in 8.1.7.
  • 89% of homes built after 1996 had the seller pay closing costs or repairs, against 75% of homes built before 1992. Defined in 8.1.8.
  • 33% of homes built after 1996 have a view, against 38% of homes built before 1992. 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 19928 sales1992–19948 sales1995–199611 salesAfter 19969 salesAll36 salesReal difference?
Net sale price average$570,564$656,900$700,039$581,395$632,019unclear
Net price per SF average$288$261$275$288$278unclear
Living area average2,0072,5302,6312,0882,334unclear
Year built median19901993199519981995by design

5.10 The numbers: selling

Before 19928 sales1992–19948 sales1995–199611 salesAfter 19969 salesAll36 salesReal difference?
Days on market median724142014unclear
Discount from original list average1.7%5.3%1.3%3.9%2.9%unclear
Price cut before sale12%38%27%33%28%unclear
Seller paid closing costs or repairs75%62%36%89%64%unclear
Has a view38%12%18%33%25%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 · 36 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. 2 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T07:47:42.100632 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 25 34 sales Sales per group View: 9 sales (26%) No view: 25 sales (74%)
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$655K$628Kunclear
Net price per SF$303 per SF$269 per SFunclear
Living area2,201 SF2,403 SFunclear
Year built19951995unclear
Days on market10 days14 daysunclear
Discount from original list-0.1%4.1%unclear
Price cut before sale0%40%unclear
Seller paid closing costs or repairs78%56%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:47:42.116346 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 25 sales $0K $200K $400K $600K $655K $628K Net sale price, average

The average is $655K for homes with a view and $628K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-10-26T07:47:42.133853 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 25 sales $0 $100 $200 $300 $303 $269 Net price per SF, average

The average is $303 per SF for homes with a view and $269 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-10-26T07:47:42.151518 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 25 sales 0 1,000 2,000 2,201 2,403 Living area (SF), average

The average is 2,201 SF for homes with a view and 2,403 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:47:42.195427 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 25 sales 1992 1994 1996 1998 1995 1995 Year built: median (dot) and middle half (bar)

The median is 1995 for homes with a view and 1995 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:47:42.212936 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 25 sales 0 5 10 15 10 14 Days on market, median

The median is 10 days for homes with a view and 14 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

2026-10-26T07:47:42.232206 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 25 sales 0.0% 1.0% 2.0% 3.0% 4.0% -0.1% 4.1% Discount from original list, average

The average is -0.1% for homes with a view and 4.1% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:47:42.251285 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 0 78 40 56 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 40% of homes without a view. Defined in 8.1.7.
  • 78% of homes with a view had the seller pay closing costs or repairs, against 56% 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

View9 salesNo view25 salesAll34 salesReal difference?
Net sale price average$654,564$627,957$635,000unclear
Net price per SF average$303$269$278unclear
Living area average2,2012,4032,350unclear
Year built median199519951995unclear

6.11 The numbers: selling

View9 salesNo view25 salesAll34 salesReal difference?
Days on market median101413unclear
Discount from original list average−0.1%4.1%3.0%unclear
Price cut before sale0%40%29%unclear
Seller paid closing costs or repairs78%56%62%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.4.

7. New constructionBasic statistics · 0 sales · October 26, 2025 – October 25, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 0 sales, no groups, no tests.

Note: these are only the new-construction sales reported in ABOR MLS. Builders often sell homes without listing them in the MLS, so these figures do not necessarily represent all new-construction sales in Legend Oaks Sec 07.

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
36 resale sales. Average $632,019; median $619,500; standard deviation $112,079; middle half (25th–75th percentile) $547,100–$669,188; lowest $475,000, highest $926,300. 23 sales had a seller payment; their median payment was $8,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
36 resale sales. Average $278; median $277; standard deviation $46; middle half (25th–75th percentile) $245–$300; lowest $175, highest $392.

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
36 resale sales. Average 2,334; median 2,305; standard deviation 554; middle half (25th–75th percentile) 1,930–2,676; lowest 1,441, highest 3,467.

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
36 resale sales. Average 1994; median 1995; standard deviation 3; middle half (25th–75th percentile) 1992–1996; lowest 1988, highest 2001.

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
36 resale sales. Average 34; median 14; standard deviation 49; middle half (25th–75th percentile) 6–34; lowest 2, highest 201. 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
36 resale sales. Average 2.9%; median 2.0%; standard deviation 5.2%; middle half (25th–75th percentile) −0.4%–6.0%; lowest −9.7%, highest 15.6%. 12 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
10 of 36 resale sales (27.8%).

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
23 of 36 resale sales (63.9%).

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
9 sales with a view, 25 without, 2 unclassified. Most common View entries: None 22, Neighborhood 9, Trees/Woods 5, Park/Greenbelt 5, See Remarks 2, Hill Country 1, Pool 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “legend oaks”, “woods legend oaks” (case-insensitive). A record is kept when its subdivision name belongs to the Legend Oaks Sec 07 family, the same rule comparable sales use (it includes Woods Legend Oaks Sec 01, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 36 closed Legend Oaks Sec 07 records over the prior year, in ZIP 78749. 15 subdivision spellings kept, the most common: Woods Legend Oaks Sec 01 (5); Legend Oaks Sec 07 (5); Legend Oaks Sec 08 (4); Legend Oaks Ph A Sec 04 & Ph B (4); Legend Oaks (3); Legend Oaks Ph A Sec 05B (3); Legend Oaks Sec 06 (2); Legend Oaks Ph A Sec 02 (2); Legend Oaks Ph A Sec 03B (2); Legend Oaks Ph A Sec 02A (1); Legend Oaks Sec 02 (1); Legend Oaks Ph A Sec 05A (1); and 3 more (3 records). Names found by the search but not part of Legend Oaks Sec 07, left out: Laurels At Legend Oaks Ph 2 A (3); Legend Oaks Phs A Sec 2 (2); LEGEND OAKS PHS A SEC 4 (1); LEGEND OAKS PHS A SEC 4 & PH (1); Laurels At Legend Oaks Ph 03 A Condo (1); Laurels At Legend Oaks Ph 1 A (1); Laurels at Legend Oaks Ph 1 A (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 17 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
36 single-family sales in the window: 36 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
36 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 $548K”.
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 $548K: $475,000–$543,500 (9 sales); $548K–$609K: $548,300–$609,000 (9 sales); $630K–$660K: $630,000–$660,000 (9 sales); Over $660K: $696,750–$926,300 (9 sales)
Quartiles by living area: Under 1,932 SF: 1,441–1,925 SF (9 sales); 1,932–2,304 SF: 1,932–2,304 SF (9 sales); 2,306–2,648 SF: 2,306–2,648 SF (9 sales); Over 2,648 SF: 2,758–3,467 SF (9 sales)
Quartiles by year built: Before 1992: 1988–1991 (8 sales); 1992–1994: 1992–1994 (8 sales); 1995–1996: 1995–1996 (11 sales); After 1996: 1997–2001 (9 sales)
View and no view: View: MLS lists a view (9 sales); No view: None or Neighborhood (25 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 $632,019, median $619,500. Days on market: average 34, median 14: 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
3 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 = 2.1830.5369p < 0.0063Unclearε² = 0.062medium
Living areaKruskal–WallisH = 19.7930.0002p < 0.0063Yesε² = 0.566large
Year builtKruskal–WallisH = 1.1130.7757p < 0.0063Unclearε² = 0.032small
Days on marketKruskal–WallisH = 0.9230.8205p < 0.0063Unclearε² = 0.026small
Discount from original listKruskal–WallisH = 5.4830.1399p < 0.0063Unclearε² = 0.157large
Price cut before saleChi-squareχ² = 2.7730.4286p < 0.0063UnclearCramér’s V = 0.277small
Seller paid closing costs or repairsChi-squareχ² = 6.1430.1050p < 0.0063UnclearCramér’s V = 0.413medium
Has a viewChi-squareχ² = 1.6330.6527p < 0.0063UnclearCramér’s V = 0.213small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 19.1030.0003p < 0.0063Yesε² = 0.546large
Net price per SFKruskal–WallisH = 16.1730.0010p < 0.0063Yesε² = 0.462large
Year builtKruskal–WallisH = 0.8530.8368p < 0.0063Unclearε² = 0.024small
Days on marketKruskal–WallisH = 0.9530.8125p < 0.0063Unclearε² = 0.027small
Discount from original listKruskal–WallisH = 1.0230.7964p < 0.0063Unclearε² = 0.029small
Price cut before saleChi-squareχ² = 2.7730.4286p < 0.0063UnclearCramér’s V = 0.277small
Seller paid closing costs or repairsChi-squareχ² = 7.1030.0687p < 0.0063UnclearCramér’s V = 0.444medium
Has a viewChi-squareχ² = 6.3730.0949p < 0.0063UnclearCramér’s V = 0.421medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 9.4730.0236p < 0.0063Unclearε² = 0.271large
Net price per SFKruskal–WallisH = 1.5730.6665p < 0.0063Unclearε² = 0.045small
Living areaKruskal–WallisH = 9.4130.0243p < 0.0063Unclearε² = 0.269large
Days on marketKruskal–WallisH = 1.4530.6939p < 0.0063Unclearε² = 0.041small
Discount from original listKruskal–WallisH = 3.5530.3146p < 0.0063Unclearε² = 0.101medium
Price cut before saleChi-squareχ² = 1.4530.6944p < 0.0063UnclearCramér’s V = 0.201small
Seller paid closing costs or repairsChi-squareχ² = 6.4930.0902p < 0.0063UnclearCramér’s V = 0.424medium
Has a viewChi-squareχ² = 1.9430.5851p < 0.0063UnclearCramér’s V = 0.232small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 126.00—0.6118p < 0.0063Unclearrank-biserial r = 0.120small
Net price per SFMann–Whitney UU = 154.00—0.1095p < 0.0063Unclearrank-biserial r = 0.369medium
Living areaMann–Whitney UU = 95.50—0.5194p < 0.0063Unclearrank-biserial r = 0.151small
Year builtMann–Whitney UU = 126.50—0.5957p < 0.0063Unclearrank-biserial r = 0.124small
Days on marketMann–Whitney UU = 81.50—0.2326p < 0.0063Unclearrank-biserial r = 0.276small
Discount from original listMann–Whitney UU = 51.00—0.0173p < 0.0063Unclearrank-biserial r = 0.547large
Price cut before saleChi-squareχ² = 5.1010.0239p < 0.0063UnclearCramér’s V = 0.387medium
Seller paid closing costs or repairsChi-squareχ² = 1.3310.2490p < 0.0063UnclearCramér’s V = 0.198small

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 36 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.