ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Rough Hollow

Austin, TX 78738 · 78734
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 · 6:58 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
25
single-family resale homes
Median net sale price
$894,400
average $1,112,740
Median net price per SF
$303
average $296
Median days on market
44 days
average 80 days
1. SummaryResale homes · 25 sales · October 27, 2025 – October 26, 2026

This study looks at the 25 resale homes sold in Rough Hollow in the 365 days to October 26, 2026. A full year is used because only 12 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 sold25 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 $722K · 6 sales$722K–$875K · 6 sales$894K–$1.26M · 7 salesOver $1.26M · 6 sales
3. Quartiles by net sale priceResale homes · 25 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.

2026-10-27T06:58:26.782835 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 7 6 25 sales Sales per group Under $722K: 6 sales (24%) $722K–$875K: 6 sales (24%) $894K–$1.26M: 7 sales (28%) Over $1.26M: 6 sales (24%)
Bottom line

3.1 Key differences

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

Under $722K$722K–$875K$894K–$1.26MOver $1.26M
Higher-priced homes Over $1.26M
  • Are much larger.
Lower-priced homes Under $722K
  • 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 $722K$722K–$875K$894K–$1.26MOver $1.26MReal difference?
Net price per SF$271 per SF$258 per SF$297 per SF$357 per SFunclear
Living area2,418 SFSmallest3,070 SF3,684 SF5,509 SFLargest✓ large
Year built2016201920192014unclear
Days on market92 days88 days7 days49 daysunclear
Discount from original list6.5%6.4%2.6%8.9%unclear
Price cut before sale67%50%14%33%unclear
Seller paid closing costs or repairs50%50%71%33%unclear
Has a view50%50%86%100%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

2026-10-27T06:58:26.811159 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $722K 6 sales $722K– $875K 6 sales $894K– $1.26M 7 sales Over $1.26M 6 sales $0 $200 $400 $271 $258 $297 $357 Net price per SF, average

The average is $357 per SF for homes over $1.26M and $271 per SF for homes under $722K. It does not move in a straight line; homes over $1.26M are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $1.26M are about 3,090 SF (128%) larger than homes under $722K

2026-10-27T06:58:26.833527 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $722K 6 sales $722K– $875K 6 sales $894K– $1.26M 7 sales Over $1.26M 6 sales 0 2,000 4,000 6,000 2,418 3,070 3,684 5,509 Living area (SF), average

The average is 5,509 SF for homes over $1.26M and 2,418 SF for homes under $722K. 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

2026-10-27T06:58:26.857893 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $722K 6 sales $722K– $875K 6 sales $894K– $1.26M 7 sales Over $1.26M 6 sales 2008 2012 2016 2020 2016 2019 2019 2014 Year built: median (dot) and middle half (bar)

The median is 2014 for homes over $1.26M and 2016 for homes under $722K. It does not move in a straight line; homes $722K–$875K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-27T06:58:26.881289 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $722K 6 sales $722K– $875K 6 sales $894K– $1.26M 7 sales Over $1.26M 6 sales 0 50 100 92 88 7 49 Days on market, median

The median is 49 days for homes over $1.26M and 92 days for homes under $722K. It does not move in a straight line; homes under $722K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-27T06:58:26.903433 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $722K 6 sales $722K– $875K 6 sales $894K– $1.26M 7 sales Over $1.26M 6 sales 0.0% 5.0% 10.0% 6.5% 6.4% 2.6% 8.9% Discount from original list, average

The average is 8.9% for homes over $1.26M and 6.5% for homes under $722K. It does not move in a straight line; homes over $1.26M 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

2026-10-27T06:58:26.933297 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% 67 50 50 50 50 50 14 71 86 33 33 100 Under $722K $722K–$875K $894K–$1.26M Over $1.26M

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

  • 33% of homes over $1.26M had a price cut before sale, against 67% of homes under $722K. Defined in 8.1.7.
  • 33% of homes over $1.26M had the seller pay closing costs or repairs, against 50% of homes under $722K. Defined in 8.1.8.
  • 100% of homes over $1.26M have a view, against 50% of homes under $722K. 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 $722K6 sales$722K–$875K6 sales$894K–$1.26M7 salesOver $1.26M6 salesAll25 salesReal difference?
Net sale price average$648,917$785,333$1,068,337$1,955,774$1,112,740by design
Net price per SF average$271$258$297$357$296unclear
Living area average2,4183,0703,6845,5093,671✓ large
Year built median20162019201920142018unclear

3.10 The numbers: selling

Under $722K6 sales$722K–$875K6 sales$894K–$1.26M7 salesOver $1.26M6 salesAll25 salesReal difference?
Days on market median928874944unclear
Discount from original list average6.5%6.4%2.6%8.9%6.0%unclear
Price cut before sale67%50%14%33%40%unclear
Seller paid closing costs or repairs50%50%71%33%52%unclear
Has a view50%50%86%100%72%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 · 25 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.

2026-10-27T06:58:26.953925 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 7 6 25 sales Sales per group Under 2,757 SF: 6 sales (24%) 2,757–3,221 SF: 6 sales (24%) 3,290–4,208 SF: 7 sales (28%) Over 4,208 SF: 6 sales (24%)
Bottom line

4.1 Key differences

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

Under 2,757 SF2,757–3,221 SF3,290–4,208 SFOver 4,208 SF
Larger homes Over 4,208 SF
  • Sell for much more.
Smaller homes Under 2,757 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 2,757 SF2,757–3,221 SF3,290–4,208 SFOver 4,208 SFReal difference?
Net sale price$655KLowest$838K$1.08M$1.88MHighest✓ large
Net price per SF$276 per SF$284 per SF$289 per SF$335 per SFunclear
Year built2015201820212017unclear
Days on market58 days67 days46 days36 daysunclear
Discount from original list5.7%5.9%4.0%8.7%unclear
Price cut before sale50%50%29%33%unclear
Seller paid closing costs or repairs67%50%57%33%unclear
Has a view50%67%86%83%unclear

4.3 Homes over 4,208 SF sell for about $1.23M (187%) more than homes under 2,757 SF

2026-10-27T06:58:26.974804 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,757 SF 6 sales 2,757– 3,221 SF 6 sales 3,290– 4,208 SF 7 sales Over 4,208 SF 6 sales $0K $1.00M $2.00M $655K $838K $1.08M $1.88M Net sale price, average

The average is $1.88M for homes over 4,208 SF and $655K for homes under 2,757 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-27T06:58:26.997608 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,757 SF 6 sales 2,757– 3,221 SF 6 sales 3,290– 4,208 SF 7 sales Over 4,208 SF 6 sales $0 $200 $400 $276 $284 $289 $335 Net price per SF, average

The average is $335 per SF for homes over 4,208 SF and $276 per SF for homes under 2,757 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-27T06:58:27.021414 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,757 SF 6 sales 2,757– 3,221 SF 6 sales 3,290– 4,208 SF 7 sales Over 4,208 SF 6 sales 2011 2014 2017 2020 2015 2018 2021 2017 Year built: median (dot) and middle half (bar)

The median is 2017 for homes over 4,208 SF and 2015 for homes under 2,757 SF. It does not move in a straight line; homes 3,290–4,208 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-27T06:58:27.044782 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,757 SF 6 sales 2,757– 3,221 SF 6 sales 3,290– 4,208 SF 7 sales Over 4,208 SF 6 sales 0 25 50 75 58 67 46 36 Days on market, median

The median is 36 days for homes over 4,208 SF and 58 days for homes under 2,757 SF. It does not move in a straight line; homes 2,757–3,221 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-27T06:58:27.067413 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,757 SF 6 sales 2,757– 3,221 SF 6 sales 3,290– 4,208 SF 7 sales Over 4,208 SF 6 sales 0.0% 5.0% 10.0% 5.7% 5.9% 4.0% 8.7% Discount from original list, average

The average is 8.7% for homes over 4,208 SF and 5.7% for homes under 2,757 SF. It does not move in a straight line; homes over 4,208 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

2026-10-27T06:58:27.093907 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 67 50 50 50 67 29 57 86 33 33 83 Under 2,757 SF 2,757–3,221 SF 3,290–4,208 SF Over 4,208 SF

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

  • 33% of homes over 4,208 SF had a price cut before sale, against 50% of homes under 2,757 SF. Defined in 8.1.7.
  • 33% of homes over 4,208 SF had the seller pay closing costs or repairs, against 67% of homes under 2,757 SF. Defined in 8.1.8.
  • 83% of homes over 4,208 SF have a view, against 50% of homes under 2,757 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 2,757 SF6 sales2,757–3,221 SF6 sales3,290–4,208 SF7 salesOver 4,208 SF6 salesAll25 salesReal difference?
Net sale price average$655,083$838,017$1,080,751$1,882,440$1,112,740✓ large
Net price per SF average$276$284$289$335$296unclear
Living area average2,3892,9503,7395,5933,671by design
Year built median20152018202120172018unclear

4.10 The numbers: selling

Under 2,757 SF6 sales2,757–3,221 SF6 sales3,290–4,208 SF7 salesOver 4,208 SF6 salesAll25 salesReal difference?
Days on market median5867463644unclear
Discount from original list average5.7%5.9%4.0%8.7%6.0%unclear
Price cut before sale50%50%29%33%40%unclear
Seller paid closing costs or repairs67%50%57%33%52%unclear
Has a view50%67%86%83%72%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 · 25 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.

2026-10-27T06:58:27.114244 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 5 8 6 25 sales Sales per group Before 2015: 6 sales (24%) 2015–2017: 5 sales (20%) 2018–2021: 8 sales (32%) After 2021: 6 sales (24%)
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 20152015–20172018–2021After 2021Real difference?
Net sale price$1.45M$819K$939K$1.25Munclear
Net price per SF$325 per SF$267 per SF$283 per SF$308 per SFunclear
Living area4,286 SF3,138 SF3,321 SF3,965 SFunclear
Days on market46 days78 days32 days36 daysunclear
Discount from original list9.3%6.3%5.4%3.2%unclear
Price cut before sale33%60%50%17%unclear
Seller paid closing costs or repairs33%40%75%50%unclear
Has a view83%40%75%83%unclear

5.3 Net sale price: no clear difference

2026-10-27T06:58:27.134680 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 6 sales 2015– 2017 5 sales 2018– 2021 8 sales After 2021 6 sales $0K $500K $1.00M $1.50M $1.45M $819K $939K $1.25M Net sale price, average

The average is $1.25M for homes built after 2021 and $1.45M for homes built before 2015. It does not move in a straight line; homes built before 2015 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-27T06:58:27.157771 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 6 sales 2015– 2017 5 sales 2018– 2021 8 sales After 2021 6 sales $0 $100 $200 $300 $325 $267 $283 $308 Net price per SF, average

The average is $308 per SF for homes built after 2021 and $325 per SF for homes built before 2015. It does not move in a straight line; homes built before 2015 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-27T06:58:27.180093 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 6 sales 2015– 2017 5 sales 2018– 2021 8 sales After 2021 6 sales 0 2,000 4,000 4,286 3,138 3,321 3,965 Living area (SF), average

The average is 3,965 SF for homes built after 2021 and 4,286 SF for homes built before 2015. It does not move in a straight line; homes built before 2015 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-27T06:58:27.202159 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 6 sales 2015– 2017 5 sales 2018– 2021 8 sales After 2021 6 sales 0 25 50 75 46 78 32 36 Days on market, median

The median is 36 days for homes built after 2021 and 46 days for homes built before 2015. It does not move in a straight line; homes built 2015–2017 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-27T06:58:27.225157 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 6 sales 2015– 2017 5 sales 2018– 2021 8 sales After 2021 6 sales 0.0% 5.0% 10.0% 9.3% 6.3% 5.4% 3.2% Discount from original list, average

The average is 3.2% for homes built after 2021 and 9.3% for homes built before 2015. 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

2026-10-27T06:58:27.250464 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 33 83 60 40 40 50 75 75 17 50 83 Before 2015 2015–2017 2018–2021 After 2021

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

  • 17% of homes built after 2021 had a price cut before sale, against 33% of homes built before 2015. Defined in 8.1.7.
  • 50% of homes built after 2021 had the seller pay closing costs or repairs, against 33% of homes built before 2015. Defined in 8.1.8.
  • 83% of homes built after 2021 have a view, against 83% of homes built before 2015. 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 20156 sales2015–20175 sales2018–20218 salesAfter 20216 salesAll25 salesReal difference?
Net sale price average$1,454,167$819,270$939,450$1,246,925$1,112,740unclear
Net price per SF average$325$267$283$308$296unclear
Living area average4,2863,1383,3213,9653,671unclear
Year built median20102015202020222018by design

5.10 The numbers: selling

Before 20156 sales2015–20175 sales2018–20218 salesAfter 20216 salesAll25 salesReal difference?
Days on market median4678323644unclear
Discount from original list average9.3%6.3%5.4%3.2%6.0%unclear
Price cut before sale33%60%50%17%40%unclear
Seller paid closing costs or repairs33%40%75%50%52%unclear
Has a view83%40%75%83%72%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 · 25 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.

2026-10-27T06:58:27.268444 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 18 6 24 sales Sales per group View: 18 sales (75%) No view: 6 sales (25%)
Bottom line

6.1 Key differences

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

ViewNo view
Homes with a view MLS lists a view
  • Sell for more per square foot.
Homes without a view no view listed
  • Sell for less per square foot.

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$1.25M$759Kunclear
Net price per SF$317 per SFHighest$242 per SFLowest✓ large
Living area3,872 SF3,210 SFunclear
Year built20182018unclear
Days on market41 days36 daysunclear
Discount from original list5.8%5.6%unclear
Price cut before sale33%50%unclear
Seller paid closing costs or repairs61%33%unclear

6.3 Net sale price: no clear difference

2026-10-27T06:58:27.284352 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 6 sales $0K $500K $1.00M $1.50M $1.25M $759K Net sale price, average

The average is $1.25M for homes with a view and $759K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Homes with a view sell for about $75 per SF (31%) more than homes without a view

2026-10-27T06:58:27.302045 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 6 sales $0 $100 $200 $300 $317 $242 Net price per SF, average

The average is $317 per SF for homes with a view and $242 per SF for homes without a view. Defined in 8.1.2.

✓ Real difference · large

6.5 Living area: no clear difference

2026-10-27T06:58:27.321283 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 6 sales 0 1,000 2,000 3,000 4,000 3,872 3,210 Living area (SF), average

The average is 3,872 SF for homes with a view and 3,210 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-27T06:58:27.369512 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 6 sales 2014 2016 2018 2020 2022 2018 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes with a view and 2018 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-27T06:58:27.388556 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 6 sales 0 10 20 30 40 41 36 Days on market, median

The median is 41 days for homes with a view and 36 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

2026-10-27T06:58:27.407095 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 6 sales 0.0% 2.0% 4.0% 6.0% 5.8% 5.6% Discount from original list, average

The average is 5.8% for homes with a view and 5.6% 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

2026-10-27T06:58:27.425841 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 33 61 50 33 View No view

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

  • 33% of homes with a view had a price cut before sale, against 50% of homes without a view. Defined in 8.1.7.
  • 61% of homes with a view had the seller pay closing costs or repairs, against 33% 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

View18 salesNo view6 salesAll24 salesReal difference?
Net sale price average$1,254,394$759,067$1,130,563unclear
Net price per SF average$317$242$298✓ large
Living area average3,8723,2103,706unclear
Year built median201820182018unclear

6.11 The numbers: selling

View18 salesNo view6 salesAll24 salesReal difference?
Days on market median413641unclear
Discount from original list average5.8%5.6%5.8%unclear
Price cut before sale33%50%38%unclear
Seller paid closing costs or repairs61%33%54%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 · 1 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: 1 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 Rough Hollow.
MeasureAverageMedian
Sales1
Net sale price$2,100,000$2,100,000
Net price per SF$406$406
Living area (SF)5,1725,172
Days on market185185
Discount from original list11.8%11.8%
Price cut before sale0% of sales
Seller paid closing costs or repairs0% of sales
Year built2026–2026

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
25 resale sales. Average $1,112,740; median $894,400; standard deviation $574,215; middle half (25th–75th percentile) $722,000–$1,260,000; lowest $608,000, highest $2,900,000. 13 sales had a seller payment; their median payment was $2,500.

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
25 resale sales. Average $296; median $303; standard deviation $55; middle half (25th–75th percentile) $250–$328; lowest $197, highest $419.

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
25 resale sales. Average 3,671; median 3,290; standard deviation 1,419; middle half (25th–75th percentile) 2,757–4,208; lowest 2,054, highest 8,559.

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
25 resale sales. Average 2017; median 2018; standard deviation 5; middle half (25th–75th percentile) 2015–2021; lowest 2007, highest 2023.

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
25 resale sales. Average 80; median 44; standard deviation 108; middle half (25th–75th percentile) 10–105; lowest 2, highest 442. 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
25 resale sales. Average 6.0%; median 4.9%; standard deviation 6.5%; middle half (25th–75th percentile) 2.3%–7.7%; lowest −0.8%, highest 31.8%. 1 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 25 resale sales (40.0%).

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
13 of 25 resale sales (52.0%).

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
18 sales with a view, 6 without, 1 unclassified. Most common View entries: Hill Country 13, Trees/Woods 12, Neighborhood 9, Park/Greenbelt 8, Panoramic 7, Lake 5, None 4, Pool 4.

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 “rough hollow” (case-insensitive). A record is kept when its subdivision name belongs to the Rough Hollow family, the same rule comparable sales use.
The data
Pulled October 27, 2026: 29 closed Rough Hollow records over the prior year, in ZIP 78738, 78734. 7 subdivision spellings kept: Rough Hollow (22); Rough Hollow Sec 5A (2); Rough Hollow Sec 07 Amd (1); Rough Hollow Sec 2 Amd Pla (1); Rough Hollow Sec 07 (1); Rough Hollow Sec 3 Condo (1); Rough Hollow Sec 10 (1). Names found by the search but not part of Rough Hollow, left out: Vineyard/Rough Hollow Condos B (3); Rough Hollow- Lakeway Highlands Ph 1 Sec 6 (1); Rough Hollow - Lakeway Highlands Ph 1 Sec 5 (1); Westside Landing at Rough Hollow (1); The Vineyards at Rough Hollow (1); Lakeway Hlghlands Rough Hollow (1); Vineyard at Rough Hollow (1); Westside Landing / Rough Hollow (1); Cypress Ridge At Rough Hollow (1); The Point at Rough Hollow (1); Rough Hollow The Peninsula (1); Rough Hollow, Lakeway Highlands Ph 2 Sec 4 (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 12 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 27, 2025 to October 26, 2026 inclusive.
The data
26 single-family sales in the window: 25 resale, 1 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
25 resale; 1 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
3 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 $722K”.
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 $722K: $608,000–$685,000 (6 sales); $722K–$875K: $722,000–$875,000 (6 sales); $894K–$1.26M: $894,400–$1,260,000 (7 sales); Over $1.26M: $1,350,000–$2,900,000 (6 sales)
Quartiles by living area: Under 2,757 SF: 2,054–2,701 SF (6 sales); 2,757–3,221 SF: 2,757–3,221 SF (6 sales); 3,290–4,208 SF: 3,290–4,208 SF (7 sales); Over 4,208 SF: 4,494–8,559 SF (6 sales)
Quartiles by year built: Before 2015: 2007–2013 (6 sales); 2015–2017: 2015–2017 (5 sales); 2018–2021: 2018–2021 (8 sales); After 2021: 2022–2023 (6 sales)
View and no view: View: MLS lists a view (18 sales); No view: None or Neighborhood (6 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 $1,112,740, median $894,400. Days on market: average 80, median 44: 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 = 10.9230.0122p < 0.0063Unclearε² = 0.455large
Living areaKruskal–WallisH = 18.6530.0003p < 0.0063Yesε² = 0.777large
Year builtKruskal–WallisH = 1.1830.7571p < 0.0063Unclearε² = 0.049small
Days on marketKruskal–WallisH = 8.1730.0426p < 0.0063Unclearε² = 0.340large
Discount from original listKruskal–WallisH = 4.5530.2078p < 0.0063Unclearε² = 0.190large
Price cut before saleChi-squareχ² = 4.0730.2543p < 0.0063UnclearCramér’s V = 0.403medium
Seller paid closing costs or repairsChi-squareχ² = 1.9230.5901p < 0.0063UnclearCramér’s V = 0.277small
Has a viewChi-squareχ² = 5.8730.1182p < 0.0063UnclearCramér’s V = 0.484medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 18.9530.0003p < 0.0063Yesε² = 0.790large
Net price per SFKruskal–WallisH = 3.4830.3236p < 0.0063Unclearε² = 0.145large
Year builtKruskal–WallisH = 1.9430.5858p < 0.0063Unclearε² = 0.081medium
Days on marketKruskal–WallisH = 0.3430.9532p < 0.0063Unclearε² = 0.014small
Discount from original listKruskal–WallisH = 0.5030.9187p < 0.0063Unclearε² = 0.021small
Price cut before saleChi-squareχ² = 0.9930.8032p < 0.0063UnclearCramér’s V = 0.199small
Seller paid closing costs or repairsChi-squareχ² = 1.4430.6965p < 0.0063UnclearCramér’s V = 0.240small
Has a viewChi-squareχ² = 2.5630.4645p < 0.0063UnclearCramér’s V = 0.320medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 3.1330.3716p < 0.0063Unclearε² = 0.131medium
Net price per SFKruskal–WallisH = 3.3430.3416p < 0.0063Unclearε² = 0.139medium
Living areaKruskal–WallisH = 1.7230.6317p < 0.0063Unclearε² = 0.072medium
Days on marketKruskal–WallisH = 0.7730.8560p < 0.0063Unclearε² = 0.032small
Discount from original listKruskal–WallisH = 2.0230.5685p < 0.0063Unclearε² = 0.084medium
Price cut before saleChi-squareχ² = 2.6430.4507p < 0.0063UnclearCramér’s V = 0.325medium
Seller paid closing costs or repairsChi-squareχ² = 2.8330.4184p < 0.0063UnclearCramér’s V = 0.337medium
Has a viewChi-squareχ² = 3.3430.3421p < 0.0063UnclearCramér’s V = 0.366medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 83.00—0.0574p < 0.0063Unclearrank-biserial r = 0.537large
Net price per SFMann–Whitney UU = 98.00—0.0019p < 0.0063Yesrank-biserial r = 0.815large
Living areaMann–Whitney UU = 68.00—0.3781p < 0.0063Unclearrank-biserial r = 0.259small
Year builtMann–Whitney UU = 54.50—1.0000p < 0.0063Unclearrank-biserial r = 0.009negligible
Days on marketMann–Whitney UU = 45.00—0.5706p < 0.0063Unclearrank-biserial r = 0.167small
Discount from original listMann–Whitney UU = 46.00—0.6261p < 0.0063Unclearrank-biserial r = 0.148small
Price cut before saleChi-squareχ² = 0.5310.4652p < 0.0063UnclearCramér’s V = 0.149small
Seller paid closing costs or repairsChi-squareχ² = 1.4010.2370p < 0.0063UnclearCramér’s V = 0.241small

8.4 Data notes

Left out of the analysis: 1 new-construction sales (basic statistics only, section 7); 3 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 25 closed MLS resale sales; the 1 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.