ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Travis Heights

Austin, TX 78704
Resale homes · closed Nov 6 – Nov 5, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 6, 2026 · 7:43 AM CST
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
28
single-family resale homes
Median net sale price
$1,037,000
average $1,338,134
Median net price per SF
$599
average $598
Median days on market
28 days
average 86 days
1. SummaryResale homes · 28 sales · November 6, 2025 – November 5, 2026

This study looks at the 28 resale homes sold in Travis Heights in the 365 days to November 5, 2026. A full year is used because only 16 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 sold28 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 $857K · 7 sales$857K–$1.00M · 7 sales$1.08M–$1.45M · 7 salesOver $1.45M · 7 sales
3. Quartiles by net sale priceResale homes · 28 sales · November 6, 2025 – November 5, 2026

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

2026-11-06T07:43:29.823018 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 7 7 28 sales Sales per group Under $857K: 7 sales (25%) $857K–$1.00M: 7 sales (25%) $1.08M–$1.45M: 7 sales (25%) Over $1.45M: 7 sales (25%)
Bottom line

3.1 Key differences

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

Under $857K$857K–$1.00M$1.08M–$1.45MOver $1.45M
Higher-priced homes Over $1.45M
  • Are much larger.
Lower-priced homes Under $857K
  • 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 $857K$857K–$1.00M$1.08M–$1.45MOver $1.45MReal difference?
Net price per SF$545 per SF$549 per SF$613 per SF$686 per SFunclear
Living area1,405 SFSmallest1,893 SF2,205 SF3,571 SFLargest✓ large
Year built1946194119502009unclear
Days on market24 days23 days20 days34 daysunclear
Discount from original list6.2%6.2%6.0%8.1%unclear
Price cut before sale14%43%29%57%unclear
Seller paid closing costs or repairs43%57%57%29%unclear
Has a view14%43%57%57%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

2026-11-06T07:43:29.851182 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $857K 7 sales $857K– $1.00M 7 sales $1.08M– $1.45M 7 sales Over $1.45M 7 sales $0 $250 $500 $750 $545 $549 $613 $686 Net price per SF, average

The average is $686 per SF for homes over $1.45M and $545 per SF for homes under $857K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $1.45M are about 2,170 SF (154%) larger than homes under $857K

2026-11-06T07:43:29.873433 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $857K 7 sales $857K– $1.00M 7 sales $1.08M– $1.45M 7 sales Over $1.45M 7 sales 0 2,000 4,000 1,405 1,893 2,205 3,571 Living area (SF), average

The average is 3,571 SF for homes over $1.45M and 1,405 SF for homes under $857K. 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

2026-11-06T07:43:29.896916 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $857K 7 sales $857K– $1.00M 7 sales $1.08M– $1.45M 7 sales Over $1.45M 7 sales 1940 1960 1980 2000 1946 1941 1950 2009 Year built: median (dot) and middle half (bar)

The median is 2009 for homes over $1.45M and 1946 for homes under $857K. It does not move in a straight line; homes over $1.45M are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-06T07:43:29.919707 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $857K 7 sales $857K– $1.00M 7 sales $1.08M– $1.45M 7 sales Over $1.45M 7 sales 0 20 40 24 23 20 34 Days on market, median

The median is 34 days for homes over $1.45M and 24 days for homes under $857K. It does not move in a straight line; homes over $1.45M are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-06T07:43:29.941842 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $857K 7 sales $857K– $1.00M 7 sales $1.08M– $1.45M 7 sales Over $1.45M 7 sales 0.0% 2.5% 5.0% 7.5% 6.2% 6.2% 6.0% 8.1% Discount from original list, average

The average is 8.1% for homes over $1.45M and 6.2% for homes under $857K. It does not move in a straight line; homes over $1.45M 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

2026-11-06T07:43:29.971510 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% 14 43 14 43 57 43 29 57 57 57 29 57 Under $857K $857K–$1.00M $1.08M–$1.45M Over $1.45M

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

  • 57% of homes over $1.45M had a price cut before sale, against 14% of homes under $857K. Defined in 8.1.7.
  • 29% of homes over $1.45M had the seller pay closing costs or repairs, against 43% of homes under $857K. Defined in 8.1.8.
  • 57% of homes over $1.45M have a view, against 14% of homes under $857K. 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 $857K7 sales$857K–$1.00M7 sales$1.08M–$1.45M7 salesOver $1.45M7 salesAll28 salesReal difference?
Net sale price average$715,422$922,900$1,288,462$2,425,754$1,338,134by design
Net price per SF average$545$549$613$686$598unclear
Living area average1,4051,8932,2053,5712,268✓ large
Year built median19461941195020091947unclear

3.10 The numbers: selling

Under $857K7 sales$857K–$1.00M7 sales$1.08M–$1.45M7 salesOver $1.45M7 salesAll28 salesReal difference?
Days on market median2423203428unclear
Discount from original list average6.2%6.2%6.0%8.1%6.6%unclear
Price cut before sale14%43%29%57%36%unclear
Seller paid closing costs or repairs43%57%57%29%46%unclear
Has a view14%43%57%57%43%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 · 28 sales · November 6, 2025 – November 5, 2026

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

2026-11-06T07:43:29.991352 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 7 7 28 sales Sales per group Under 1,379 SF: 7 sales (25%) 1,379–2,065 SF: 7 sales (25%) 2,068–3,015 SF: 7 sales (25%) Over 3,015 SF: 7 sales (25%)
Bottom line

4.1 Key differences

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

Under 1,379 SF1,379–2,065 SF2,068–3,015 SFOver 3,015 SF
Larger homes Over 3,015 SF
  • Sell for much more.
Smaller homes Under 1,379 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 1,379 SF1,379–2,065 SF2,068–3,015 SFOver 3,015 SFReal difference?
Net sale price$780KLowest$993K$1.17M$2.41MHighest✓ large
Net price per SF$671 per SF$571 per SF$491 per SF$659 per SFunclear
Year built1942194719522009unclear
Days on market9 days31 days23 days46 daysunclear
Discount from original list6.7%5.2%5.0%9.5%unclear
Price cut before sale29%0%57%57%unclear
Seller paid closing costs or repairs57%57%43%29%unclear
Has a view14%29%71%57%unclear

4.3 Homes over 3,015 SF sell for about $1.63M (209%) more than homes under 1,379 SF

2026-11-06T07:43:30.012127 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,379 SF 7 sales 1,379– 2,065 SF 7 sales 2,068– 3,015 SF 7 sales Over 3,015 SF 7 sales $0K $1.00M $2.00M $780K $993K $1.17M $2.41M Net sale price, average

The average is $2.41M for homes over 3,015 SF and $780K for homes under 1,379 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

2026-11-06T07:43:30.034968 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,379 SF 7 sales 1,379– 2,065 SF 7 sales 2,068– 3,015 SF 7 sales Over 3,015 SF 7 sales $0 $250 $500 $750 $671 $571 $491 $659 Net price per SF, average

The average is $659 per SF for homes over 3,015 SF and $671 per SF for homes under 1,379 SF. It does not move in a straight line; homes under 1,379 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-06T07:43:30.058592 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,379 SF 7 sales 1,379– 2,065 SF 7 sales 2,068– 3,015 SF 7 sales Over 3,015 SF 7 sales 1940 1960 1980 2000 1942 1947 1952 2009 Year built: median (dot) and middle half (bar)

The median is 2009 for homes over 3,015 SF and 1942 for homes under 1,379 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-06T07:43:30.081421 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,379 SF 7 sales 1,379– 2,065 SF 7 sales 2,068– 3,015 SF 7 sales Over 3,015 SF 7 sales 0 20 40 9 31 23 46 Days on market, median

The median is 46 days for homes over 3,015 SF and 9 days for homes under 1,379 SF. It does not move in a straight line; homes over 3,015 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-06T07:43:30.103074 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,379 SF 7 sales 1,379– 2,065 SF 7 sales 2,068– 3,015 SF 7 sales Over 3,015 SF 7 sales 0.0% 5.0% 10.0% 6.7% 5.2% 5.0% 9.5% Discount from original list, average

The average is 9.5% for homes over 3,015 SF and 6.7% for homes under 1,379 SF. It does not move in a straight line; homes over 3,015 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

2026-11-06T07:43:30.128341 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% 29 57 14 0 57 29 57 43 71 57 29 57 Under 1,379 SF 1,379–2,065 SF 2,068–3,015 SF Over 3,015 SF

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

  • 57% of homes over 3,015 SF had a price cut before sale, against 29% of homes under 1,379 SF. Defined in 8.1.7.
  • 29% of homes over 3,015 SF had the seller pay closing costs or repairs, against 57% of homes under 1,379 SF. Defined in 8.1.8.
  • 57% of homes over 3,015 SF have a view, against 14% of homes under 1,379 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 1,379 SF7 sales1,379–2,065 SF7 sales2,068–3,015 SF7 salesOver 3,015 SF7 salesAll28 salesReal difference?
Net sale price average$780,329$992,601$1,169,136$2,410,471$1,338,134✓ large
Net price per SF average$671$571$491$659$598unclear
Living area average1,2041,7592,4203,6902,268by design
Year built median19421947195220091947unclear

4.10 The numbers: selling

Under 1,379 SF7 sales1,379–2,065 SF7 sales2,068–3,015 SF7 salesOver 3,015 SF7 salesAll28 salesReal difference?
Days on market median931234628unclear
Discount from original list average6.7%5.2%5.0%9.5%6.6%unclear
Price cut before sale29%0%57%57%36%unclear
Seller paid closing costs or repairs57%57%43%29%46%unclear
Has a view14%29%71%57%43%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 · 28 sales · November 6, 2025 – November 5, 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.

2026-11-06T07:43:30.148832 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 6 8 7 28 sales Sales per group Before 1940: 7 sales (25%) 1940–1946: 6 sales (21%) 1947–1997: 8 sales (29%) After 1997: 7 sales (25%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

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

5.2 At a glance

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

Before 19401940–19461947–1997After 1997Real difference?
Net sale price$1.48M$812K$1.06M$1.97Munclear
Net price per SF$692 per SF$514 per SF$595 per SF$579 per SFunclear
Living area2,283 SF1,619 SF1,828 SF3,313 SFunclear
Days on market9 days10 days38 days98 daysunclear
Discount from original list5.2%3.5%7.9%9.2%unclear
Price cut before sale14%17%38%71%unclear
Seller paid closing costs or repairs43%50%50%43%unclear
Has a view43%17%62%43%unclear

5.3 Net sale price: no clear difference

2026-11-06T07:43:30.168801 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1940 7 sales 1940– 1946 6 sales 1947– 1997 8 sales After 1997 7 sales $0K $1.00M $2.00M $1.48M $812K $1.06M $1.97M Net sale price, average

The average is $1.97M for homes built after 1997 and $1.48M for homes built before 1940. It does not move in a straight line; homes built after 1997 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-06T07:43:30.191570 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1940 7 sales 1940– 1946 6 sales 1947– 1997 8 sales After 1997 7 sales $0 $250 $500 $750 $692 $514 $595 $579 Net price per SF, average

The average is $579 per SF for homes built after 1997 and $692 per SF for homes built before 1940. It does not move in a straight line; homes built before 1940 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-06T07:43:30.213183 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1940 7 sales 1940– 1946 6 sales 1947– 1997 8 sales After 1997 7 sales 0 1,000 2,000 3,000 2,283 1,619 1,828 3,313 Living area (SF), average

The average is 3,313 SF for homes built after 1997 and 2,283 SF for homes built before 1940. It does not move in a straight line; homes built after 1997 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-06T07:43:30.235145 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1940 7 sales 1940– 1946 6 sales 1947– 1997 8 sales After 1997 7 sales 0 50 100 9 10 38 98 Days on market, median

The median is 98 days for homes built after 1997 and 9 days for homes built before 1940. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-06T07:43:30.257638 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1940 7 sales 1940– 1946 6 sales 1947– 1997 8 sales After 1997 7 sales 0.0% 5.0% 10.0% 5.2% 3.5% 7.9% 9.2% Discount from original list, average

The average is 9.2% for homes built after 1997 and 5.2% for homes built before 1940. It does not move in a straight line; homes built after 1997 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

2026-11-06T07:43:30.282403 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% 14 43 43 17 50 17 38 50 62 71 43 43 Before 1940 1940–1946 1947–1997 After 1997

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

  • 71% of homes built after 1997 had a price cut before sale, against 14% of homes built before 1940. Defined in 8.1.7.
  • 43% of homes built after 1997 had the seller pay closing costs or repairs, against 43% of homes built before 1940. Defined in 8.1.8.
  • 43% of homes built after 1997 have a view, against 43% of homes built before 1940. 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 19407 sales1940–19466 sales1947–19978 salesAfter 19977 salesAll28 salesReal difference?
Net sale price average$1,476,894$811,717$1,058,988$1,969,614$1,338,134unclear
Net price per SF average$692$514$595$579$598unclear
Living area average2,2831,6191,8283,3132,268unclear
Year built median19341942195120121947by design

5.10 The numbers: selling

Before 19407 sales1940–19466 sales1947–19978 salesAfter 19977 salesAll28 salesReal difference?
Days on market median910389828unclear
Discount from original list average5.2%3.5%7.9%9.2%6.6%unclear
Price cut before sale14%17%38%71%36%unclear
Seller paid closing costs or repairs43%50%50%43%46%unclear
Has a view43%17%62%43%43%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 · 28 sales · November 6, 2025 – November 5, 2026

Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood.

2026-11-06T07:43:30.300321 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 16 28 sales Sales per group View: 12 sales (43%) No view: 16 sales (57%)
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$1.51M$1.21Munclear
Net price per SF$595 per SF$600 per SFunclear
Living area2,581 SF2,034 SFunclear
Year built19521946unclear
Days on market34 days21 daysunclear
Discount from original list6.9%6.4%unclear
Price cut before sale50%25%unclear
Seller paid closing costs or repairs42%50%unclear

6.3 Net sale price: no clear difference

2026-11-06T07:43:30.315943 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 16 sales $0K $500K $1.00M $1.50M $1.51M $1.21M Net sale price, average

The average is $1.51M for homes with a view and $1.21M 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

2026-11-06T07:43:30.333513 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 16 sales $0 $200 $400 $600 $595 $600 Net price per SF, average

The average is $595 per SF for homes with a view and $600 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

2026-11-06T07:43:30.350900 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 16 sales 0 1,000 2,000 3,000 2,581 2,034 Living area (SF), average

The average is 2,581 SF for homes with a view and 2,034 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-06T07:43:30.391438 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 16 sales 1950 1965 1980 1995 1952 1946 Year built: median (dot) and middle half (bar)

The median is 1952 for homes with a view and 1946 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-06T07:43:30.410011 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 16 sales 0 10 20 30 40 34 21 Days on market, median

The median is 34 days for homes with a view and 21 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

2026-11-06T07:43:30.429351 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 16 sales 0.0% 2.0% 4.0% 6.0% 8.0% 6.9% 6.4% Discount from original list, average

The average is 6.9% for homes with a view and 6.4% 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

2026-11-06T07:43:30.448217 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 50 42 25 50 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 25% of homes without a view. Defined in 8.1.7.
  • 42% of homes with a view had the seller pay closing costs or repairs, against 50% 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

View12 salesNo view16 salesAll28 salesReal difference?
Net sale price average$1,514,830$1,205,612$1,338,134unclear
Net price per SF average$595$600$598unclear
Living area average2,5812,0342,268unclear
Year built median195219461947unclear

6.11 The numbers: selling

View12 salesNo view16 salesAll28 salesReal difference?
Days on market median342128unclear
Discount from original list average6.9%6.4%6.6%unclear
Price cut before sale50%25%36%unclear
Seller paid closing costs or repairs42%50%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 · 1 sales · November 6, 2025 – November 5, 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 Travis Heights.
MeasureAverageMedian
Sales1
Net sale price$1,595,000$1,595,000
Net price per SF$708$708
Living area (SF)2,2522,252
Days on market11
Discount from original list0.0%0.0%
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
28 resale sales. Average $1,338,134; median $1,037,000; standard deviation $705,737; middle half (25th–75th percentile) $848,863–$1,467,569; lowest $576,000, highest $2,750,000. 13 sales had a seller payment; their median payment was $8,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
28 resale sales. Average $598; median $599; standard deviation $166; middle half (25th–75th percentile) $451–$713; lowest $299, highest $967.

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
28 resale sales. Average 2,268; median 2,066; standard deviation 999; middle half (25th–75th percentile) 1,367–3,024; lowest 812, highest 4,638.

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
28 resale sales. Average 1962; median 1947; standard deviation 33; middle half (25th–75th percentile) 1940–1998; lowest 1922, 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
28 resale sales. Average 86; median 28; standard deviation 157; middle half (25th–75th percentile) 9–78; lowest 3, highest 742. 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
28 resale sales. Average 6.6%; median 4.6%; standard deviation 6.4%; middle half (25th–75th percentile) 2.0%–9.9%; lowest −5.4%, highest 26.4%. 2 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 28 resale sales (35.7%).

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
13 of 28 resale sales (46.4%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
12 sales with a view, 16 without, 0 unclassified. Most common View entries: None 12, City 8, Neighborhood 8, Trees/Woods 5, Downtown 3, Skyline 3, City Lights 2, Park/Greenbelt 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
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-06 13:30 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “travis heights”, “pleasant view add” (case-insensitive). A record is kept when its subdivision name belongs to the Travis Heights family, the same rule comparable sales use (it includes Pleasant View Add, proven adjacent and priced alike).
The data
Pulled November 6, 2026: 36 closed Travis Heights records over the prior year, in ZIP 78704. 2 subdivision spellings kept: Travis Heights (33); Pleasant View Add (3). Names found by the search but not part of Travis Heights, left out: Travis Heights Condo The Amd (1); Fawn Ridge Sec 02 (East Travis Heights) (1); Travis Heights Terrace Condo Amd (1); Travis Heights Terrace Condominiums (1); Pleasant View Addition (1); River Oaks Sec 01 aka East Travis Heights (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 16 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 6, 2025 to November 5, 2026 inclusive.
The data
29 single-family sales in the window: 28 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
28 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
5 sale(s) other than single-family homes (condo, townhome and similar); 2 sale(s) with concessions above 10% of price

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $857K”.
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 $857K: $576,000–$824,451 (7 sales); $857K–$1.00M: $857,000–$997,500 (7 sales); $1.08M–$1.45M: $1,076,500–$1,450,000 (7 sales); Over $1.45M: $1,520,275–$2,750,000 (7 sales)
Quartiles by living area: Under 1,379 SF: 812–1,332 SF (7 sales); 1,379–2,065 SF: 1,379–2,065 SF (7 sales); 2,068–3,015 SF: 2,068–3,015 SF (7 sales); Over 3,015 SF: 3,053–4,638 SF (7 sales)
Quartiles by year built: Before 1940: 1922–1939 (7 sales); 1940–1946: 1940–1946 (6 sales); 1947–1997: 1947–1997 (8 sales); After 1997: 2003–2023 (7 sales)
View and no view: View: MLS lists a view (12 sales); No view: None or Neighborhood (16 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 $1,338,134, median $1,037,000. Days on market: average 86, median 28: 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
2 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 5.1330.1627p < 0.0063Unclearε² = 0.190large
Living areaKruskal–WallisH = 17.4230.0006p < 0.0063Yesε² = 0.645large
Year builtKruskal–WallisH = 1.9930.5740p < 0.0063Unclearε² = 0.074medium
Days on marketKruskal–WallisH = 1.2330.7459p < 0.0063Unclearε² = 0.046small
Discount from original listKruskal–WallisH = 1.9730.5787p < 0.0063Unclearε² = 0.073medium
Price cut before saleChi-squareχ² = 3.1130.3748p < 0.0063UnclearCramér’s V = 0.333medium
Seller paid closing costs or repairsChi-squareχ² = 1.5830.6640p < 0.0063UnclearCramér’s V = 0.238small
Has a viewChi-squareχ² = 3.5030.3208p < 0.0063UnclearCramér’s V = 0.354medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 18.9930.0003p < 0.0063Yesε² = 0.703large
Net price per SFKruskal–WallisH = 5.5530.1357p < 0.0063Unclearε² = 0.206large
Year builtKruskal–WallisH = 3.2330.3576p < 0.0063Unclearε² = 0.120medium
Days on marketKruskal–WallisH = 2.9430.4002p < 0.0063Unclearε² = 0.109medium
Discount from original listKruskal–WallisH = 3.0330.3877p < 0.0063Unclearε² = 0.112medium
Price cut before saleChi-squareχ² = 6.8430.0770p < 0.0063UnclearCramér’s V = 0.494medium
Seller paid closing costs or repairsChi-squareχ² = 1.5830.6640p < 0.0063UnclearCramér’s V = 0.238small
Has a viewChi-squareχ² = 5.8330.1200p < 0.0063UnclearCramér’s V = 0.456medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 9.2630.0260p < 0.0063Unclearε² = 0.343large
Net price per SFKruskal–WallisH = 3.7030.2957p < 0.0063Unclearε² = 0.137medium
Living areaKruskal–WallisH = 10.9830.0119p < 0.0063Unclearε² = 0.406large
Days on marketKruskal–WallisH = 12.1330.0069p < 0.0063Unclearε² = 0.449large
Discount from original listKruskal–WallisH = 5.3630.1470p < 0.0063Unclearε² = 0.199large
Price cut before saleChi-squareχ² = 6.2530.1001p < 0.0063UnclearCramér’s V = 0.472medium
Seller paid closing costs or repairsChi-squareχ² = 0.1430.9861p < 0.0063UnclearCramér’s V = 0.072negligible
Has a viewChi-squareχ² = 2.9430.4008p < 0.0063UnclearCramér’s V = 0.324medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 137.00—0.0601p < 0.0063Unclearrank-biserial r = 0.427medium
Net price per SFMann–Whitney UU = 97.00—0.9815p < 0.0063Unclearrank-biserial r = 0.010negligible
Living areaMann–Whitney UU = 134.00—0.0817p < 0.0063Unclearrank-biserial r = 0.396medium
Year builtMann–Whitney UU = 104.50—0.7102p < 0.0063Unclearrank-biserial r = 0.089negligible
Days on marketMann–Whitney UU = 112.50—0.4572p < 0.0063Unclearrank-biserial r = 0.172small
Discount from original listMann–Whitney UU = 115.00—0.3904p < 0.0063Unclearrank-biserial r = 0.198small
Price cut before saleChi-squareχ² = 1.8710.1719p < 0.0063UnclearCramér’s V = 0.258small
Seller paid closing costs or repairsChi-squareχ² = 0.1910.6617p < 0.0063UnclearCramér’s V = 0.083negligible

8.4 Data notes

Left out of the analysis: 1 new-construction sales (basic statistics only, section 7); 5 sale(s) other than single-family homes (condo, townhome and similar); 2 sale(s) with concessions above 10% of price. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

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

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 28 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 November 6, 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.