ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Sendera Sec 15

Austin, TX 78749
Resale homes · closed Oct 27 – Oct 26, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 27, 2026 · 7:38 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
$552,000
average $559,056
Median net price per SF
$273
average $273
Median days on market
8 days
average 38 days
1. SummaryResale homes · 39 sales · October 27, 2025 – October 26, 2026

This study looks at the 39 resale homes sold in Sendera Sec 15 in the 365 days to October 26, 2026. A full year is used because only 23 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 $490K · 10 sales$490K–$552K · 10 sales$558K–$595K · 9 salesOver $595K · 10 sales
3. Quartiles by net sale priceResale homes · 39 sales · October 27, 2025 – October 26, 2026

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

2026-10-27T07:38:36.802888 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 9 10 39 sales Sales per group Under $490K: 10 sales (26%) $490K–$552K: 10 sales (26%) $558K–$595K: 9 sales (23%) Over $595K: 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 $490K$490K–$552K$558K–$595KOver $595K
Higher-priced homes Over $595K
  • Are much larger.
Lower-priced homes Under $490K
  • 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 $490K$490K–$552K$558K–$595KOver $595KReal difference?
Net price per SF$271 per SF$276 per SF$274 per SF$273 per SFunclear
Living area1,742 SFSmallest1,898 SF2,121 SF2,560 SFLargest✓ large
Year built1999199919991999unclear
Days on market58 days6 days6 days4 daysunclear
Discount from original list6.4%4.7%1.9%0.4%unclear
Price cut before sale50%20%11%20%unclear
Seller paid closing costs or repairs80%90%89%80%unclear
Has a view10%10%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

2026-10-27T07:38:36.834110 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $490K 10 sales $490K– $552K 10 sales $558K– $595K 9 sales Over $595K 10 sales $0 $100 $200 $300 $271 $276 $274 $273 Net price per SF, average

The average is $273 per SF for homes over $595K and $271 per SF for homes under $490K. It does not move in a straight line; homes $490K–$552K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $595K are about 820 SF (47%) larger than homes under $490K

2026-10-27T07:38:36.859456 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $490K 10 sales $490K– $552K 10 sales $558K– $595K 9 sales Over $595K 10 sales 0 1,000 2,000 3,000 1,742 1,898 2,121 2,560 Living area (SF), average

The average is 2,560 SF for homes over $595K and 1,742 SF for homes under $490K. 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

2026-10-27T07:38:36.887229 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $490K 10 sales $490K– $552K 10 sales $558K– $595K 9 sales Over $595K 10 sales 1997 1998 1999 2000 2001 1999 1999 1999 1999 Year built: median (dot) and middle half (bar)

The median is 1999 for homes over $595K and 1999 for homes under $490K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-27T07:38:36.913006 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $490K 10 sales $490K– $552K 10 sales $558K– $595K 9 sales Over $595K 10 sales 0 20 40 60 58 6 6 4 Days on market, median

The median is 4 days for homes over $595K and 58 days for homes under $490K. 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

2026-10-27T07:38:36.937131 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $490K 10 sales $490K– $552K 10 sales $558K– $595K 9 sales Over $595K 10 sales 0.0% 2.0% 4.0% 6.0% 6.4% 4.7% 1.9% 0.4% Discount from original list, average

The average is 0.4% for homes over $595K and 6.4% for homes under $490K. 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

2026-10-27T07:38:36.970501 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 50 80 10 20 90 10 11 89 11 20 80 10 Under $490K $490K–$552K $558K–$595K Over $595K

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

  • 20% of homes over $595K had a price cut before sale, against 50% of homes under $490K. Defined in 8.1.7.
  • 80% of homes over $595K had the seller pay closing costs or repairs, against 80% of homes under $490K. Defined in 8.1.8.
  • 10% of homes over $595K have a view, against 10% of homes under $490K. 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 $490K10 sales$490K–$552K10 sales$558K–$595K9 salesOver $595K10 salesAll39 salesReal difference?
Net sale price average$466,600$518,696$576,119$676,514$559,056by design
Net price per SF average$271$276$274$273$273unclear
Living area average1,7421,8982,1212,5602,079✓ large
Year built median19991999199919991999unclear

3.10 The numbers: selling

Under $490K10 sales$490K–$552K10 sales$558K–$595K9 salesOver $595K10 salesAll39 salesReal difference?
Days on market median586648unclear
Discount from original list average6.4%4.7%1.9%0.4%3.4%unclear
Price cut before sale50%20%11%20%26%unclear
Seller paid closing costs or repairs80%90%89%80%85%unclear
Has a view10%10%11%10%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 · 39 sales · October 27, 2025 – October 26, 2026

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

2026-10-27T07:38:36.993889 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 10 11 9 39 sales Sales per group Under 1,755 SF: 9 sales (23%) 1,755–2,023 SF: 10 sales (26%) 2,046–2,191 SF: 11 sales (28%) Over 2,191 SF: 9 sales (23%)
Bottom line

4.1 Key differences

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

Under 1,755 SF1,755–2,023 SF2,046–2,191 SFOver 2,191 SF
Larger homes Over 2,191 SF
  • Sell for much more.
  • Sell for less per square foot.
Smaller homes Under 1,755 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 1,755 SF1,755–2,023 SF2,046–2,191 SFOver 2,191 SFReal difference?
Net sale price$494KLowest$515K$560K$672KHighest✓ large
Net price per SF$306 per SFHighest$278 per SF$265 per SF$247 per SFLowest✓ large
Year built1998199820001999unclear
Days on market46 days33 days5 days5 daysunclear
Discount from original list5.1%6.2%2.3%-0.1%unclear
Price cut before sale33%40%18%11%unclear
Seller paid closing costs or repairs89%80%91%78%unclear
Has a view22%10%9%0%unclear

4.3 Homes over 2,191 SF sell for about $178K (36%) more than homes under 1,755 SF

2026-10-27T07:38:37.017071 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,755 SF 9 sales 1,755– 2,023 SF 10 sales 2,046– 2,191 SF 11 sales Over 2,191 SF 9 sales $0K $250K $500K $750K $494K $515K $560K $672K Net sale price, average

The average is $672K for homes over 2,191 SF and $494K for homes under 1,755 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 2,191 SF sell for about $59 per SF (19%) less than homes under 1,755 SF

2026-10-27T07:38:37.043010 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,755 SF 9 sales 1,755– 2,023 SF 10 sales 2,046– 2,191 SF 11 sales Over 2,191 SF 9 sales $0 $100 $200 $300 $306 $278 $265 $247 Net price per SF, average

The average is $247 per SF for homes over 2,191 SF and $306 per SF for homes under 1,755 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

2026-10-27T07:38:37.070996 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,755 SF 9 sales 1,755– 2,023 SF 10 sales 2,046– 2,191 SF 11 sales Over 2,191 SF 9 sales 1997 1998 1999 2000 2001 1998 1998 2000 1999 Year built: median (dot) and middle half (bar)

The median is 1999 for homes over 2,191 SF and 1998 for homes under 1,755 SF. It does not move in a straight line; homes 2,046–2,191 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-27T07:38:37.098749 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,755 SF 9 sales 1,755– 2,023 SF 10 sales 2,046– 2,191 SF 11 sales Over 2,191 SF 9 sales 0 20 40 46 33 5 5 Days on market, median

The median is 5 days for homes over 2,191 SF and 46 days for homes under 1,755 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-27T07:38:37.123338 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,755 SF 9 sales 1,755– 2,023 SF 10 sales 2,046– 2,191 SF 11 sales Over 2,191 SF 9 sales 0.0% 2.0% 4.0% 6.0% 5.1% 6.2% 2.3% -0.1% Discount from original list, average

The average is -0.1% for homes over 2,191 SF and 5.1% for homes under 1,755 SF. It does not move in a straight line; homes 1,755–2,023 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

2026-10-27T07:38:37.154078 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 22 40 80 10 18 91 9 11 78 0 Under 1,755 SF 1,755–2,023 SF 2,046–2,191 SF Over 2,191 SF

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

  • 11% of homes over 2,191 SF had a price cut before sale, against 33% of homes under 1,755 SF. Defined in 8.1.7.
  • 78% of homes over 2,191 SF had the seller pay closing costs or repairs, against 89% of homes under 1,755 SF. Defined in 8.1.8.
  • 0% of homes over 2,191 SF have a view, against 22% of homes under 1,755 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 1,755 SF9 sales1,755–2,023 SF10 sales2,046–2,191 SF11 salesOver 2,191 SF9 salesAll39 salesReal difference?
Net sale price average$494,289$514,663$559,964$672,038$559,056✓ large
Net price per SF average$306$278$265$247$273✓ large
Living area average1,6161,8532,1172,7472,079by design
Year built median19981998200019991999unclear

4.10 The numbers: selling

Under 1,755 SF9 sales1,755–2,023 SF10 sales2,046–2,191 SF11 salesOver 2,191 SF9 salesAll39 salesReal difference?
Days on market median4633558unclear
Discount from original list average5.1%6.2%2.3%−0.1%3.4%unclear
Price cut before sale33%40%18%11%26%unclear
Seller paid closing costs or repairs89%80%91%78%85%unclear
Has a view22%10%9%0%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 · 39 sales · October 27, 2025 – October 26, 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.

2026-10-27T07:38:37.177609 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 6 10 14 39 sales Sales per group Before 1998: 9 sales (23%) 1998: 6 sales (15%) 1999: 10 sales (26%) After 1999: 14 sales (36%)
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 199819981999After 1999Real difference?
Net sale price$572K$542K$562K$556Kunclear
Net price per SF$280 per SF$272 per SF$282 per SF$264 per SFunclear
Living area2,096 SF2,063 SF2,005 SF2,129 SFunclear
Days on market5 days14 days48 days6 daysunclear
Discount from original list3.6%5.3%5.1%1.2%unclear
Price cut before sale33%33%30%14%unclear
Seller paid closing costs or repairs100%67%70%93%unclear
Has a view0%17%30%0%unclear

5.3 Net sale price: no clear difference

2026-10-27T07:38:37.200006 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1998 9 sales 1998 6 sales 1999 10 sales After 1999 14 sales $0K $200K $400K $600K $572K $542K $562K $556K Net sale price, average

The average is $556K for homes built after 1999 and $572K for homes built before 1998. It does not move in a straight line; homes built before 1998 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-27T07:38:37.225251 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1998 9 sales 1998 6 sales 1999 10 sales After 1999 14 sales $0 $100 $200 $300 $280 $272 $282 $264 Net price per SF, average

The average is $264 per SF for homes built after 1999 and $280 per SF for homes built before 1998. It does not move in a straight line; homes built 1999 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-27T07:38:37.249357 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1998 9 sales 1998 6 sales 1999 10 sales After 1999 14 sales 0 1,000 2,000 2,096 2,063 2,005 2,129 Living area (SF), average

The average is 2,129 SF for homes built after 1999 and 2,096 SF for homes built before 1998. It does not move in a straight line; homes built after 1999 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-27T07:38:37.272607 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1998 9 sales 1998 6 sales 1999 10 sales After 1999 14 sales 0 20 40 5 14 48 6 Days on market, median

The median is 6 days for homes built after 1999 and 5 days for homes built before 1998. It does not move in a straight line; homes built 1999 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-27T07:38:37.297485 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1998 9 sales 1998 6 sales 1999 10 sales After 1999 14 sales 0.0% 2.0% 4.0% 6.0% 3.6% 5.3% 5.1% 1.2% Discount from original list, average

The average is 1.2% for homes built after 1999 and 3.6% for homes built before 1998. It does not move in a straight line; homes built 1998 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

2026-10-27T07:38:37.325506 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% 33 100 0 33 67 17 30 70 30 14 93 0 Before 1998 1998 1999 After 1999

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

  • 14% of homes built after 1999 had a price cut before sale, against 33% of homes built before 1998. Defined in 8.1.7.
  • 93% of homes built after 1999 had the seller pay closing costs or repairs, against 100% of homes built before 1998. Defined in 8.1.8.
  • 0% of homes built after 1999 have a view, against 0% of homes built before 1998. 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 19989 sales19986 sales199910 salesAfter 199914 salesAll39 salesReal difference?
Net sale price average$571,825$541,917$562,313$555,865$559,056unclear
Net price per SF average$280$272$282$264$273unclear
Living area average2,0962,0632,0052,1292,079unclear
Year built median19971998199920001999by design

5.10 The numbers: selling

Before 19989 sales19986 sales199910 salesAfter 199914 salesAll39 salesReal difference?
Days on market median5144868unclear
Discount from original list average3.6%5.3%5.1%1.2%3.4%unclear
Price cut before sale33%33%30%14%26%unclear
Seller paid closing costs or repairs100%67%70%93%85%unclear
Has a view0%17%30%0%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 · 39 sales · October 27, 2025 – October 26, 2026

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

2026-10-27T07:38:37.347362 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 34 38 sales Sales per group View: 4 sales (11%) No view: 34 sales (89%)
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

2026-10-27T07:38:37.364652 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 34 sales $0K $200K $400K $600K $537K $561K Net sale price, average

The average is $537K for homes with a view and $561K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-27T07:38:37.384003 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 34 sales $0 $100 $200 $300 $300 $270 Net price per SF, average

The average is $300 per SF for homes with a view and $270 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-27T07:38:37.405612 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 34 sales 0 1,000 2,000 1,806 2,108 Living area (SF), average

The average is 1,806 SF for homes with a view and 2,108 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-27T07:38:37.514563 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 34 sales 1998 1999 2000 1999 1999 Year built: median (dot) and middle half (bar)

The median is 1999 for homes with a view and 1999 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-27T07:38:37.534550 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 34 sales 0 20 40 60 80 68 7 Days on market, median

The median is 68 days for homes with a view and 7 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

2026-10-27T07:38:37.554260 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 34 sales 0.0% 2.0% 4.0% 6.0% 6.3% 3.1% Discount from original list, average

The average is 6.3% for homes with a view and 3.1% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-27T07:38:37.574220 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 50 100 24 85 View No view

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

  • 50% of homes with a view had a price cut before sale, against 24% of homes without a view. Defined in 8.1.7.
  • 100% of homes with a view had the seller pay closing costs or repairs, against 85% 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

View4 salesNo view34 salesAll38 sales
Net sale price average$537,494$560,538$558,112
Net price per SF average$300$270$274
Living area average1,8062,1082,076
Year built median199919991999

6.11 The numbers: selling

View4 salesNo view34 salesAll38 sales
Days on market median68710
Discount from original list average6.3%3.1%3.5%
Price cut before sale50%24%26%
Seller paid closing costs or repairs100%85%87%

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 27, 2025 – October 26, 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 Sendera Sec 15.

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 $559,056; median $552,000; standard deviation $91,422; middle half (25th–75th percentile) $486,500–$596,260; lowest $448,500, highest $814,137. 33 sales had a seller payment; their median payment was $5,000.

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
39 resale sales. Average $273; median $273; standard deviation $32; middle half (25th–75th percentile) $248–$291; lowest $212, highest $360.

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 2,079; median 2,046; standard deviation 477; middle half (25th–75th percentile) 1,755–2,191; lowest 1,511, highest 3,562.

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 1999; median 1999; standard deviation 2; middle half (25th–75th percentile) 1998–2000; lowest 1994, 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
39 resale sales. Average 38; median 8; standard deviation 57; middle half (25th–75th percentile) 4–58; lowest 0, highest 295. 1 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 3.4%; median 2.0%; standard deviation 5.4%; middle half (25th–75th percentile) 0.5%–7.9%; lowest −12.3%, highest 15.5%. 6 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 39 resale sales (25.6%).

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
33 of 39 resale sales (84.6%).

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
4 sales with a view, 34 without, 1 unclassified. Most common View entries: None 22, Neighborhood 13, Park/Greenbelt 4, Trees/Woods 2, See Remarks 1, Hill Country 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 “sendera”, “sendera south”, “deer park at maple run” (case-insensitive). A record is kept when its subdivision name belongs to the Sendera Sec 15 family, the same rule comparable sales use (it includes Sendera South Sec 04, Deer Park At Maple Run Sec 11-, proven adjacent and priced alike).
The data
Pulled October 27, 2026: 39 closed Sendera Sec 15 records over the prior year, in ZIP 78749. 18 subdivision spellings kept, the most common: Sendera South Sec 02 (5); Sendera Sec 15 (5); Sendera Sec 12-A (4); Sendera South Sec 04 (4); Sendera Sec 15 B (3); Deer Park At Maple Run Sec 11-A (2); Sendera Sec 16 (2); Sendera Sec 12-B (2); Sendera South Sec 03 (2); Sendera (2); Sendera South Sec 01 (1); Sendera South (1); and 6 more (6 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 23 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 27, 2025 to October 26, 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
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 $490K”.
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 $490K: $448,500–$483,500 (10 sales); $490K–$552K: $489,500–$552,000 (10 sales); $558K–$595K: $558,000–$594,900 (9 sales); Over $595K: $597,621–$814,137 (10 sales)
Quartiles by living area: Under 1,755 SF: 1,511–1,686 SF (9 sales); 1,755–2,023 SF: 1,755–2,023 SF (10 sales); 2,046–2,191 SF: 2,046–2,191 SF (11 sales); Over 2,191 SF: 2,195–3,562 SF (9 sales)
Quartiles by year built: Before 1998: 1994–1997 (9 sales); 1998: 1998–1998 (6 sales); 1999: 1999–1999 (10 sales); After 1999: 2000–2001 (14 sales)
View and no view: View: MLS lists a view (4 sales); No view: None or Neighborhood (34 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 $559,056, median $552,000. Days on market: average 38, median 8: 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

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 = 0.4830.9236p < 0.0063Unclearε² = 0.013small
Living areaKruskal–WallisH = 16.5830.0009p < 0.0063Yesε² = 0.436large
Year builtKruskal–WallisH = 2.6130.4565p < 0.0063Unclearε² = 0.069medium
Days on marketKruskal–WallisH = 8.5230.0365p < 0.0063Unclearε² = 0.224large
Discount from original listKruskal–WallisH = 4.4830.2145p < 0.0063Unclearε² = 0.118medium
Price cut before saleChi-squareχ² = 4.4430.2175p < 0.0063UnclearCramér’s V = 0.338medium
Seller paid closing costs or repairsChi-squareχ² = 0.6830.8788p < 0.0063UnclearCramér’s V = 0.132small
Has a viewChi-squareχ² = 0.0130.9998p < 0.0063UnclearCramér’s V = 0.015negligible

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 18.9930.0003p < 0.0063Yesε² = 0.500large
Net price per SFKruskal–WallisH = 14.4830.0023p < 0.0063Yesε² = 0.381large
Year builtKruskal–WallisH = 4.6130.2027p < 0.0063Unclearε² = 0.121medium
Days on marketKruskal–WallisH = 3.7730.2873p < 0.0063Unclearε² = 0.099medium
Discount from original listKruskal–WallisH = 6.0230.1104p < 0.0063Unclearε² = 0.159large
Price cut before saleChi-squareχ² = 2.6830.4439p < 0.0063UnclearCramér’s V = 0.262small
Seller paid closing costs or repairsChi-squareχ² = 0.9530.8139p < 0.0063UnclearCramér’s V = 0.156small
Has a viewChi-squareχ² = 2.4530.4852p < 0.0063UnclearCramér’s V = 0.250small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 1.2130.7517p < 0.0063Unclearε² = 0.032small
Net price per SFKruskal–WallisH = 1.3030.7299p < 0.0063Unclearε² = 0.034small
Living areaKruskal–WallisH = 1.3930.7075p < 0.0063Unclearε² = 0.037small
Days on marketKruskal–WallisH = 3.5330.3164p < 0.0063Unclearε² = 0.093medium
Discount from original listKruskal–WallisH = 3.5630.3135p < 0.0063Unclearε² = 0.094medium
Price cut before saleChi-squareχ² = 1.5130.6795p < 0.0063UnclearCramér’s V = 0.197small
Seller paid closing costs or repairsChi-squareχ² = 5.4930.1391p < 0.0063UnclearCramér’s V = 0.375medium
Has a viewChi-squareχ² = 7.1330.0678p < 0.0063UnclearCramér’s V = 0.428medium

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); nothing else. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

  1. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Erlbaum.
  2. Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press.
  3. Dunn, O. J. (1961). Multiple comparisons among means. JASA, 56(293), 52–64.
  4. Kerby, D. S. (2014). The simple difference formula: an approach to teaching nonparametric correlation. Comprehensive Psychology, 3, 11.IT.3.1.
  5. Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. JASA, 47(260), 583–621.
  6. Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18(1), 50–60.
  7. Pearson, K. (1900). On the criterion that a given system of deviations… Philosophical Magazine, 50(302), 157–175.
  8. Tomczak, M., & Tomczak, E. (2014). The need to report effect size estimates revisited. Trends in Sport Sciences, 21(1), 19–25.

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 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 27, 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.