ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Chernosky 09

Austin, TX 78721 · 78741 · 78702
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 · 7:40 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
30
single-family resale homes
Median net sale price
$461,200
average $534,620
Median net price per SF
$358
average $361
Median days on market
32 days
average 61 days
1. SummaryResale homes · 30 sales · October 26, 2025 – October 25, 2026

This study looks at the 30 resale homes sold in Chernosky 09 in the 365 days to October 25, 2026. A full year is used because only 18 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 sold30 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 $343K · 8 sales$343K–$460K · 7 sales$462K–$714K · 7 salesOver $714K · 8 sales
3. Quartiles by net sale priceResale homes · 30 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.

2026-10-26T07:40:43.900368 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Under $343K: 8 sales (27%) $343K–$460K: 7 sales (23%) $462K–$714K: 7 sales (23%) Over $714K: 8 sales (27%)
Bottom line

3.1 Key differences

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

Under $343K$343K–$460K$462K–$714KOver $714K
Higher-priced homes Over $714K
  • Tend to be newer.
  • Are much larger.
  • Sell for more per square foot.
Lower-priced homes Under $343K
  • Tend to be older.
  • Are much smaller.
  • Sell for less per square foot.

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 $343K$343K–$460K$462K–$714KOver $714KReal difference?
Net price per SF$224 per SFLowest$380 per SF$425 per SF$427 per SFHighest✓ large
Living area1,100 SF1,069 SFSmallest1,407 SF2,255 SFLargest✓ large
Year built19621958Oldest2020Newest2016✓ large
Days on market36 days31 days70 days16 daysunclear
Discount from original list11.8%13.4%7.2%3.5%unclear
Price cut before sale38%57%71%25%unclear
Seller paid closing costs or repairs50%57%29%50%unclear
Has a view0%14%57%25%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 Homes over $714K sell for about $203 per SF (91%) more than homes under $343K

2026-10-26T07:40:43.928116 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $343K 8 sales $343K– $460K 7 sales $462K– $714K 7 sales Over $714K 8 sales $0 $200 $400 $224 $380 $425 $427 Net price per SF, average

The average is $427 per SF for homes over $714K and $224 per SF for homes under $343K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $714K are about 1,150 SF (105%) larger than homes under $343K

2026-10-26T07:40:43.950087 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $343K 8 sales $343K– $460K 7 sales $462K– $714K 7 sales Over $714K 8 sales 0 1,000 2,000 1,100 1,069 1,407 2,255 Living area (SF), average

The average is 2,255 SF for homes over $714K and 1,100 SF for homes under $343K. It does not move in a straight line; homes over $714K are highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Homes over $714K are about 55 years newer than homes under $343K

2026-10-26T07:40:43.974192 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $343K 8 sales $343K– $460K 7 sales $462K– $714K 7 sales Over $714K 8 sales 1940 1960 1980 2000 2020 1962 1958 2020 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over $714K and 1962 for homes under $343K. It does not move in a straight line; homes $462K–$714K are highest. Defined in 8.1.4.

✓ Real difference · large

3.6 Days on market: no clear difference

2026-10-26T07:40:43.997053 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $343K 8 sales $343K– $460K 7 sales $462K– $714K 7 sales Over $714K 8 sales 0 25 50 75 36 31 70 16 Days on market, median

The median is 16 days for homes over $714K and 36 days for homes under $343K. It does not move in a straight line; homes $462K–$714K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:40:44.018595 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $343K 8 sales $343K– $460K 7 sales $462K– $714K 7 sales Over $714K 8 sales 0.0% 5.0% 10.0% 15.0% 11.8% 13.4% 7.2% 3.5% Discount from original list, average

The average is 3.5% for homes over $714K and 11.8% for homes under $343K. It does not move in a straight line; homes $343K–$460K 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

2026-10-26T07:40:44.047881 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% 38 50 0 57 57 14 71 29 57 25 50 25 Under $343K $343K–$460K $462K–$714K Over $714K

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

  • 25% of homes over $714K had a price cut before sale, against 38% of homes under $343K. Defined in 8.1.7.
  • 50% of homes over $714K had the seller pay closing costs or repairs, against 50% of homes under $343K. Defined in 8.1.8.
  • 25% of homes over $714K have a view, against 0% of homes under $343K. 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 $343K8 sales$343K–$460K7 sales$462K–$714K7 salesOver $714K8 salesAll30 salesReal difference?
Net sale price average$215,729$389,095$557,629$960,712$534,620by design
Net price per SF average$224$380$425$427$361✓ large
Living area average1,1001,0691,4072,2551,472✓ large
Year built median19621958202020162010✓ large

3.10 The numbers: selling

Under $343K8 sales$343K–$460K7 sales$462K–$714K7 salesOver $714K8 salesAll30 salesReal difference?
Days on market median3631701632unclear
Discount from original list average11.8%13.4%7.2%3.5%8.9%unclear
Price cut before sale38%57%71%25%47%unclear
Seller paid closing costs or repairs50%57%29%50%47%unclear
Has a view0%14%57%25%23%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 · 30 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.

2026-10-26T07:40:44.068047 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Under 1,031 SF: 8 sales (27%) 1,031–1,236 SF: 7 sales (23%) 1,256–2,033 SF: 7 sales (23%) Over 2,033 SF: 8 sales (27%)
Bottom line

4.1 Key differences

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

Under 1,031 SF1,031–1,236 SF1,256–2,033 SFOver 2,033 SF
Larger homes Over 2,033 SF
  • Sell for much more.
Smaller homes Under 1,031 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 1,031 SF1,031–1,236 SF1,256–2,033 SFOver 2,033 SFReal difference?
Net sale price$374K$324KLowest$454K$949KHighest✓ large
Net price per SF$439 per SF$296 per SF$287 per SF$406 per SFunclear
Year built1962196419622016unclear
Days on market94 days10 days15 days20 daysunclear
Discount from original list16.3%11.4%2.6%4.9%unclear
Price cut before sale88%29%29%38%unclear
Seller paid closing costs or repairs62%43%14%62%unclear
Has a view12%14%43%25%unclear

4.3 Homes over 2,033 SF sell for about $575K (154%) more than homes under 1,031 SF

2026-10-26T07:40:44.088484 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,031 SF 8 sales 1,031– 1,236 SF 7 sales 1,256– 2,033 SF 7 sales Over 2,033 SF 8 sales $0K $500K $1.00M $374K $324K $454K $949K Net sale price, average

The average is $949K for homes over 2,033 SF and $374K for homes under 1,031 SF. It does not move in a straight line; homes over 2,033 SF are highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-26T07:40:44.110779 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,031 SF 8 sales 1,031– 1,236 SF 7 sales 1,256– 2,033 SF 7 sales Over 2,033 SF 8 sales $0 $200 $400 $439 $296 $287 $406 Net price per SF, average

The average is $406 per SF for homes over 2,033 SF and $439 per SF for homes under 1,031 SF. It does not move in a straight line; homes under 1,031 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:40:44.134884 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,031 SF 8 sales 1,031– 1,236 SF 7 sales 1,256– 2,033 SF 7 sales Over 2,033 SF 8 sales 1940 1960 1980 2000 2020 1962 1964 1962 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over 2,033 SF and 1962 for homes under 1,031 SF. It does not move in a straight line; homes over 2,033 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:40:44.157886 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,031 SF 8 sales 1,031– 1,236 SF 7 sales 1,256– 2,033 SF 7 sales Over 2,033 SF 8 sales 0 50 100 94 10 15 20 Days on market, median

The median is 20 days for homes over 2,033 SF and 94 days for homes under 1,031 SF. It does not move in a straight line; homes under 1,031 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:40:44.179279 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,031 SF 8 sales 1,031– 1,236 SF 7 sales 1,256– 2,033 SF 7 sales Over 2,033 SF 8 sales 0.0% 5.0% 10.0% 15.0% 16.3% 11.4% 2.6% 4.9% Discount from original list, average

The average is 4.9% for homes over 2,033 SF and 16.3% for homes under 1,031 SF. It does not move in a straight line; homes under 1,031 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

2026-10-26T07:40:44.205419 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% 88 62 12 29 43 14 29 14 43 38 62 25 Under 1,031 SF 1,031–1,236 SF 1,256–2,033 SF Over 2,033 SF

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

  • 38% of homes over 2,033 SF had a price cut before sale, against 88% of homes under 1,031 SF. Defined in 8.1.7.
  • 62% of homes over 2,033 SF had the seller pay closing costs or repairs, against 62% of homes under 1,031 SF. Defined in 8.1.8.
  • 25% of homes over 2,033 SF have a view, against 12% of homes under 1,031 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 1,031 SF8 sales1,031–1,236 SF7 sales1,256–2,033 SF7 salesOver 2,033 SF8 salesAll30 salesReal difference?
Net sale price average$374,445$324,313$453,950$949,400$534,620✓ large
Net price per SF average$439$296$287$406$361unclear
Living area average8461,1181,5602,3321,472by design
Year built median19621964196220162010unclear

4.10 The numbers: selling

Under 1,031 SF8 sales1,031–1,236 SF7 sales1,256–2,033 SF7 salesOver 2,033 SF8 salesAll30 salesReal difference?
Days on market median9410152032unclear
Discount from original list average16.3%11.4%2.6%4.9%8.9%unclear
Price cut before sale88%29%29%38%47%unclear
Seller paid closing costs or repairs62%43%14%62%47%unclear
Has a view12%14%43%25%23%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 · 30 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.

2026-10-26T07:40:44.225661 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 6 9 30 sales Sales per group Before 1961: 8 sales (27%) 1961–2006: 7 sales (23%) 2013–2017: 6 sales (20%) After 2017: 9 sales (30%)
Bottom line

5.1 Key differences

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

Before 19611961–20062013–2017After 2017
Newer homes After 2017
  • Sell for much more.
Older homes Before 1961
  • Sell for much less.

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 19611961–20062013–2017After 2017Real difference?
Net sale price$344KLowest$348K$805KHighest$669K✓ large
Net price per SF$353 per SF$236 per SF$406 per SF$437 per SFunclear
Living area995 SF1,513 SF1,908 SF1,575 SFunclear
Days on market32 days33 days17 days44 daysunclear
Discount from original list16.9%7.4%5.6%5.2%unclear
Price cut before sale62%29%33%56%unclear
Seller paid closing costs or repairs50%29%67%44%unclear
Has a view12%14%33%33%unclear

5.3 Homes built after 2017 sell for about $325K (94%) more than homes built before 1961

2026-10-26T07:40:44.246318 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1961 8 sales 1961– 2006 7 sales 2013– 2017 6 sales After 2017 9 sales $0K $250K $500K $750K $344K $348K $805K $669K Net sale price, average

The average is $669K for homes built after 2017 and $344K for homes built before 1961. It does not move in a straight line; homes built 2013–2017 are highest. Defined in 8.1.1.

✓ Real difference · large

5.4 Net price per SF: no clear difference

2026-10-26T07:40:44.269127 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1961 8 sales 1961– 2006 7 sales 2013– 2017 6 sales After 2017 9 sales $0 $200 $400 $353 $236 $406 $437 Net price per SF, average

The average is $437 per SF for homes built after 2017 and $353 per SF for homes built before 1961. It does not move in a straight line; homes built after 2017 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:40:44.290144 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1961 8 sales 1961– 2006 7 sales 2013– 2017 6 sales After 2017 9 sales 0 1,000 2,000 995 1,513 1,908 1,575 Living area (SF), average

The average is 1,575 SF for homes built after 2017 and 995 SF for homes built before 1961. It does not move in a straight line; homes built 2013–2017 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:40:44.311973 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1961 8 sales 1961– 2006 7 sales 2013– 2017 6 sales After 2017 9 sales 0 20 40 32 33 17 44 Days on market, median

The median is 44 days for homes built after 2017 and 32 days for homes built before 1961. It does not move in a straight line; homes built after 2017 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:40:44.333228 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1961 8 sales 1961– 2006 7 sales 2013– 2017 6 sales After 2017 9 sales 0.0% 10.0% 20.0% 16.9% 7.4% 5.6% 5.2% Discount from original list, average

The average is 5.2% for homes built after 2017 and 16.9% for homes built before 1961. It falls step by step from the lowest range to the 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

2026-10-26T07:40:44.358779 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% 62 50 12 29 29 14 33 67 33 56 44 33 Before 1961 1961–2006 2013–2017 After 2017

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

  • 56% of homes built after 2017 had a price cut before sale, against 62% of homes built before 1961. Defined in 8.1.7.
  • 44% of homes built after 2017 had the seller pay closing costs or repairs, against 50% of homes built before 1961. Defined in 8.1.8.
  • 33% of homes built after 2017 have a view, against 12% of homes built before 1961. 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 19618 sales1961–20067 sales2013–20176 salesAfter 20179 salesAll30 salesReal difference?
Net sale price average$343,964$348,429$805,018$668,642$534,620✓ large
Net price per SF average$353$236$406$437$361unclear
Living area average9951,5131,9081,5751,472unclear
Year built median19481964201620222010by design

5.10 The numbers: selling

Before 19618 sales1961–20067 sales2013–20176 salesAfter 20179 salesAll30 salesReal difference?
Days on market median3233174432unclear
Discount from original list average16.9%7.4%5.6%5.2%8.9%unclear
Price cut before sale62%29%33%56%47%unclear
Seller paid closing costs or repairs50%29%67%44%47%unclear
Has a view12%14%33%33%23%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 · 30 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.

2026-10-26T07:40:44.375644 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 21 28 sales Sales per group View: 7 sales (25%) No view: 21 sales (75%)
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$636K$503Kunclear
Net price per SF$388 per SF$351 per SFunclear
Living area1,666 SF1,406 SFunclear
Year built20171965unclear
Days on market33 days30 daysunclear
Discount from original list3.7%9.5%unclear
Price cut before sale43%43%unclear
Seller paid closing costs or repairs14%57%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:40:44.391054 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 21 sales $0K $200K $400K $600K $636K $503K Net sale price, average

The average is $636K for homes with a view and $503K 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

2026-10-26T07:40:44.409111 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 21 sales $0 $100 $200 $300 $400 $388 $351 Net price per SF, average

The average is $388 per SF for homes with a view and $351 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

2026-10-26T07:40:44.448977 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 21 sales 0 500 1,000 1,500 1,666 1,406 Living area (SF), average

The average is 1,666 SF for homes with a view and 1,406 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:40:44.467407 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 21 sales 1965 1980 1995 2010 2017 1965 Year built: median (dot) and middle half (bar)

The median is 2017 for homes with a view and 1965 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:40:44.484939 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 21 sales 0 10 20 30 33 30 Days on market, median

The median is 33 days for homes with a view and 30 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

2026-10-26T07:40:44.503310 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 21 sales 0.0% 2.5% 5.0% 7.5% 10.0% 3.7% 9.5% Discount from original list, average

The average is 3.7% for homes with a view and 9.5% 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

2026-10-26T07:40:44.522042 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 43 14 43 57 View No view

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

  • 43% of homes with a view had a price cut before sale, against 43% of homes without a view. Defined in 8.1.7.
  • 14% of homes with a view had the seller pay closing costs or repairs, against 57% 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

View7 salesNo view21 salesAll28 salesReal difference?
Net sale price average$636,200$503,367$536,575unclear
Net price per SF average$388$351$360unclear
Living area average1,6661,4061,471unclear
Year built median201719652010unclear

6.11 The numbers: selling

View7 salesNo view21 salesAll28 salesReal difference?
Days on market median333030unclear
Discount from original list average3.7%9.5%8.0%unclear
Price cut before sale43%43%43%unclear
Seller paid closing costs or repairs14%57%46%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 · 3 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: 3 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 Chernosky 09.
MeasureAverageMedian
Sales3
Net sale price$981,035$1,005,000
Net price per SF$404$375
Living area (SF)2,2512,678
Days on market13894
Discount from original list10.1%7.7%
Price cut before sale67% of sales
Seller paid closing costs or repairs100% of sales
Year built2023–2026

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
30 resale sales. Average $534,620; median $461,200; standard deviation $316,675; middle half (25th–75th percentile) $331,402–$731,375; lowest $150,000, highest $1,410,000. 14 sales had a seller payment; their median payment was $8,050.

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
30 resale sales. Average $361; median $358; standard deviation $128; middle half (25th–75th percentile) $306–$459; lowest $103, highest $582.

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
30 resale sales. Average 1,472; median 1,246; standard deviation 609; middle half (25th–75th percentile) 1,023–2,106; lowest 672, highest 2,678.

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
30 resale sales. Average 1989; median 2010; standard deviation 34; middle half (25th–75th percentile) 1959–2019; lowest 1927, highest 2024.

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
30 resale sales. Average 61; median 32; standard deviation 90; middle half (25th–75th percentile) 11–73; lowest 0, highest 471. 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
30 resale sales. Average 8.9%; median 6.4%; standard deviation 11.1%; middle half (25th–75th percentile) 2.1%–12.1%; lowest −13.3%, highest 42.4%. 4 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
14 of 30 resale sales (46.7%).

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
14 of 30 resale sales (46.7%).

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
7 sales with a view, 21 without, 2 unclassified. Most common View entries: None 16, Neighborhood 7, City 4, See Remarks 2, Trees/Woods 2, City Lights 1, Downtown 1, Skyline 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 “chernosky”, “em franklin”, “chernosky sub”, “e m franklin sub”, “em franklin sub” (case-insensitive). A record is kept when its subdivision name belongs to the Chernosky 09 family, the same rule comparable sales use (it includes Em Franklin 2nd Resub, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 40 closed Chernosky 09 records over the prior year, in ZIP 78721, 78741, 78702, 78723. 19 subdivision spellings kept, the most common: Chernosky 09 (7); Chernosky 12 (5); Chernosky 11 (4); Chernosky 16 (3); Chernosky 17 (3); Chernosky 10 (2); Chernosky 15 (2); Chernosky 08 (2); Chernosky 04 (2); CHERNOSKY 16 (1); Chernosky Sub # 16 Un 2 (1); Chernosky No 09 (1); and 7 more (7 records). Names found by the search but not part of Chernosky 09, left out: Em Franklin Second (1); Chernosky M E (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 18 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
33 single-family sales in the window: 30 resale, 3 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
30 resale; 3 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
7 sale(s) other than single-family homes (condo, townhome and similar)

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 $343K”.
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 $343K: $150,000–$327,410 (8 sales); $343K–$460K: $343,380–$460,000 (7 sales); $462K–$714K: $462,400–$714,500 (7 sales); Over $714K: $737,000–$1,410,000 (8 sales)
Quartiles by living area: Under 1,031 SF: 672–1,020 SF (8 sales); 1,031–1,236 SF: 1,031–1,236 SF (7 sales); 1,256–2,033 SF: 1,256–2,033 SF (7 sales); Over 2,033 SF: 2,131–2,678 SF (8 sales)
Quartiles by year built: Before 1961: 1927–1958 (8 sales); 1961–2006: 1961–2006 (7 sales); 2013–2017: 2013–2017 (6 sales); After 2017: 2019–2024 (9 sales)
View and no view: View: MLS lists a view (7 sales); No view: None or Neighborhood (21 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 $534,620, median $461,200. Days on market: average 61, median 32: 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
5 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 = 12.7130.0053p < 0.0063Yesε² = 0.438large
Living areaKruskal–WallisH = 15.7530.0013p < 0.0063Yesε² = 0.543large
Year builtKruskal–WallisH = 17.3830.0006p < 0.0063Yesε² = 0.599large
Days on marketKruskal–WallisH = 2.1630.5392p < 0.0063Unclearε² = 0.075medium
Discount from original listKruskal–WallisH = 5.3630.1470p < 0.0063Unclearε² = 0.185large
Price cut before saleChi-squareχ² = 3.8130.2825p < 0.0063UnclearCramér’s V = 0.356medium
Seller paid closing costs or repairsChi-squareχ² = 1.3030.7289p < 0.0063UnclearCramér’s V = 0.208small
Has a viewChi-squareχ² = 7.2430.0646p < 0.0063UnclearCramér’s V = 0.491medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 16.7230.0008p < 0.0063Yesε² = 0.577large
Net price per SFKruskal–WallisH = 6.7330.0810p < 0.0063Unclearε² = 0.232large
Year builtKruskal–WallisH = 3.9030.2724p < 0.0063Unclearε² = 0.135medium
Days on marketKruskal–WallisH = 9.2630.0260p < 0.0063Unclearε² = 0.319large
Discount from original listKruskal–WallisH = 8.1330.0434p < 0.0063Unclearε² = 0.280large
Price cut before saleChi-squareχ² = 7.4730.0583p < 0.0063UnclearCramér’s V = 0.499medium
Seller paid closing costs or repairsChi-squareχ² = 4.6030.2034p < 0.0063UnclearCramér’s V = 0.392medium
Has a viewChi-squareχ² = 2.3530.5032p < 0.0063UnclearCramér’s V = 0.280small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 12.7730.0052p < 0.0063Yesε² = 0.440large
Net price per SFKruskal–WallisH = 8.7530.0329p < 0.0063Unclearε² = 0.302large
Living areaKruskal–WallisH = 8.0230.0456p < 0.0063Unclearε² = 0.277large
Days on marketKruskal–WallisH = 0.6830.8768p < 0.0063Unclearε² = 0.024small
Discount from original listKruskal–WallisH = 3.9930.2621p < 0.0063Unclearε² = 0.138medium
Price cut before saleChi-squareχ² = 2.4430.4860p < 0.0063UnclearCramér’s V = 0.285small
Seller paid closing costs or repairsChi-squareχ² = 1.9430.5852p < 0.0063UnclearCramér’s V = 0.254small
Has a viewChi-squareχ² = 1.6830.6406p < 0.0063UnclearCramér’s V = 0.237small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 104.00—0.1114p < 0.0063Unclearrank-biserial r = 0.415medium
Net price per SFMann–Whitney UU = 86.00—0.5329p < 0.0063Unclearrank-biserial r = 0.170small
Living areaMann–Whitney UU = 91.00—0.3756p < 0.0063Unclearrank-biserial r = 0.238small
Year builtMann–Whitney UU = 102.50—0.1300p < 0.0063Unclearrank-biserial r = 0.395medium
Days on marketMann–Whitney UU = 81.50—0.6905p < 0.0063Unclearrank-biserial r = 0.109small
Discount from original listMann–Whitney UU = 45.00—0.1400p < 0.0063Unclearrank-biserial r = 0.388medium
Price cut before saleChi-squareχ² = 0.0011.0000p < 0.0063UnclearCramér’s V = 0.000negligible
Seller paid closing costs or repairsChi-squareχ² = 3.8810.0490p < 0.0063UnclearCramér’s V = 0.372medium

8.4 Data notes

Left out of the analysis: 3 new-construction sales (basic statistics only, section 7); 7 sale(s) other than single-family homes (condo, townhome and similar). 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 30 closed MLS resale sales; the 3 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.