ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Crestview

Austin, TX 78757 · 78752
Resale homes · closed Oct 28 – Oct 27, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 28, 2026 · 7:22 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
40
single-family resale homes
Median net sale price
$665,000
average $780,291
Median net price per SF
$464
average $456
Median days on market
33 days
average 61 days
1. SummaryResale homes · 40 sales · October 28, 2025 – October 27, 2026

This study looks at the 40 resale homes sold in Crestview in the 365 days to October 27, 2026. A full year is used because only 19 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 sold40 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 $525K · 9 sales$525K–$625K · 11 sales$705K–$930K · 10 salesOver $930K · 10 sales
3. Quartiles by net sale priceResale homes · 40 sales · October 28, 2025 – October 27, 2026

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

2026-10-28T07:22:45.142037 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 11 10 10 40 sales Sales per group Under $525K: 9 sales (22%) $525K–$625K: 11 sales (28%) $705K–$930K: 10 sales (25%) Over $930K: 10 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 $525K$525K–$625K$705K–$930KOver $930K
Higher-priced homes Over $930K
  • Are much larger.
  • Tend to be newer.
Lower-priced homes Under $525K
  • Are much smaller.
  • Tend to be older.

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 $525K$525K–$625K$705K–$930KOver $930KReal difference?
Net price per SF$422 per SF$472 per SF$443 per SF$482 per SFunclear
Living area1,112 SFSmallest1,370 SF1,857 SF2,651 SFLargest✓ large
Year built1952Oldest195219542018Newest✓ large
Days on market40 days37 days7 days68 daysunclear
Discount from original list11.5%6.5%4.9%9.8%unclear
Price cut before sale44%27%20%70%unclear
Seller paid closing costs or repairs11%36%50%50%unclear
Has a view0%0%10%0%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

2026-10-28T07:22:45.170261 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $525K 9 sales $525K– $625K 11 sales $705K– $930K 10 sales Over $930K 10 sales $0 $200 $400 $422 $472 $443 $482 Net price per SF, average

The average is $482 per SF for homes over $930K and $422 per SF for homes under $525K. It does not move in a straight line; homes over $930K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $930K are about 1,540 SF (138%) larger than homes under $525K

2026-10-28T07:22:45.192340 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $525K 9 sales $525K– $625K 11 sales $705K– $930K 10 sales Over $930K 10 sales 0 1,000 2,000 3,000 1,112 1,370 1,857 2,651 Living area (SF), average

The average is 2,651 SF for homes over $930K and 1,112 SF for homes under $525K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Homes over $930K are about 66 years newer than homes under $525K

2026-10-28T07:22:45.216348 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $525K 9 sales $525K– $625K 11 sales $705K– $930K 10 sales Over $930K 10 sales 1960 1980 2000 2020 1952 1952 1954 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over $930K and 1952 for homes under $525K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

✓ Real difference · large

3.6 Days on market: no clear difference

2026-10-28T07:22:45.239388 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $525K 9 sales $525K– $625K 11 sales $705K– $930K 10 sales Over $930K 10 sales 0 25 50 75 40 37 7 68 Days on market, median

The median is 68 days for homes over $930K and 40 days for homes under $525K. It does not move in a straight line; homes over $930K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-28T07:22:45.261712 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $525K 9 sales $525K– $625K 11 sales $705K– $930K 10 sales Over $930K 10 sales 0.0% 5.0% 10.0% 11.5% 6.5% 4.9% 9.8% Discount from original list, average

The average is 9.8% for homes over $930K and 11.5% for homes under $525K. It does not move in a straight line; homes under $525K 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

2026-10-28T07:22:45.291078 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 44 11 0 27 36 0 20 50 10 70 50 0 Under $525K $525K–$625K $705K–$930K Over $930K

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

  • 70% of homes over $930K had a price cut before sale, against 44% of homes under $525K. Defined in 8.1.7.
  • 50% of homes over $930K had the seller pay closing costs or repairs, against 11% of homes under $525K. Defined in 8.1.8.
  • 0% of homes over $930K have a view, against 0% of homes under $525K. 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 $525K9 sales$525K–$625K11 sales$705K–$930K10 salesOver $930K10 salesAll40 salesReal difference?
Net sale price average$452,722$580,890$802,300$1,272,436$780,291by design
Net price per SF average$422$472$443$482$456unclear
Living area average1,1121,3701,8572,6511,754✓ large
Year built median19521952195420181953✓ large

3.10 The numbers: selling

Under $525K9 sales$525K–$625K11 sales$705K–$930K10 salesOver $930K10 salesAll40 salesReal difference?
Days on market median403776833unclear
Discount from original list average11.5%6.5%4.9%9.8%8.1%unclear
Price cut before sale44%27%20%70%40%unclear
Seller paid closing costs or repairs11%36%50%50%38%unclear
Has a view0%0%10%0%2%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 · 40 sales · October 28, 2025 – October 27, 2026

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

2026-10-28T07:22:45.311224 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 10 10 40 sales Sales per group Under 1,176 SF: 10 sales (25%) 1,176–1,603 SF: 10 sales (25%) 1,632–2,187 SF: 10 sales (25%) Over 2,187 SF: 10 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 1,176 SF1,176–1,603 SF1,632–2,187 SFOver 2,187 SF
Larger homes Over 2,187 SF
  • Sell for much more.
  • Tend to be newer.
  • Take longer to sell.
Smaller homes Under 1,176 SF
  • Sell for much less.
  • Tend to be older.
  • Sell faster.

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 1,176 SF1,176–1,603 SF1,632–2,187 SFOver 2,187 SFReal difference?
Net sale price$483KLowest$633K$827K$1.18MHighest✓ large
Net price per SF$520 per SF$452 per SF$429 per SF$423 per SFunclear
Year built1952Oldest195219562016Newest✓ large
Days on market48 days6 daysFastest14 days88 daysSlowest✓ large
Discount from original list6.7%4.0%6.1%15.5%unclear
Price cut before sale30%20%30%80%unclear
Seller paid closing costs or repairs20%40%40%50%unclear
Has a view0%0%10%0%unclear

4.3 Homes over 2,187 SF sell for about $696K (144%) more than homes under 1,176 SF

2026-10-28T07:22:45.331721 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,176 SF 10 sales 1,176– 1,603 SF 10 sales 1,632– 2,187 SF 10 sales Over 2,187 SF 10 sales $0K $500K $1.00M $483K $633K $827K $1.18M Net sale price, average

The average is $1.18M for homes over 2,187 SF and $483K for homes under 1,176 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

2026-10-28T07:22:45.353637 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,176 SF 10 sales 1,176– 1,603 SF 10 sales 1,632– 2,187 SF 10 sales Over 2,187 SF 10 sales $0 $200 $400 $600 $520 $452 $429 $423 Net price per SF, average

The average is $423 per SF for homes over 2,187 SF and $520 per SF for homes under 1,176 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Homes over 2,187 SF are about 64 years newer than homes under 1,176 SF

2026-10-28T07:22:45.376810 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,176 SF 10 sales 1,176– 1,603 SF 10 sales 1,632– 2,187 SF 10 sales Over 2,187 SF 10 sales 1960 1980 2000 2020 1952 1952 1956 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over 2,187 SF and 1952 for homes under 1,176 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

✓ Real difference · large

4.6 Homes over 2,187 SF take 40 days longer to sell than homes under 1,176 SF

2026-10-28T07:22:45.399351 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,176 SF 10 sales 1,176– 1,603 SF 10 sales 1,632– 2,187 SF 10 sales Over 2,187 SF 10 sales 0 50 100 48 6 14 88 Days on market, median

The median is 88 days for homes over 2,187 SF and 48 days for homes under 1,176 SF. It does not move in a straight line; homes over 2,187 SF are highest. Defined in 8.1.5.

✓ Real difference · large

4.7 Discount from original list: no clear difference

2026-10-28T07:22:45.420756 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,176 SF 10 sales 1,176– 1,603 SF 10 sales 1,632– 2,187 SF 10 sales Over 2,187 SF 10 sales 0.0% 5.0% 10.0% 15.0% 6.7% 4.0% 6.1% 15.5% Discount from original list, average

The average is 15.5% for homes over 2,187 SF and 6.7% for homes under 1,176 SF. It does not move in a straight line; homes over 2,187 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

2026-10-28T07:22:45.447153 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% 30 20 0 20 40 0 30 40 10 80 50 0 Under 1,176 SF 1,176–1,603 SF 1,632–2,187 SF Over 2,187 SF

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

  • 80% of homes over 2,187 SF had a price cut before sale, against 30% of homes under 1,176 SF. Defined in 8.1.7.
  • 50% of homes over 2,187 SF had the seller pay closing costs or repairs, against 20% of homes under 1,176 SF. Defined in 8.1.8.
  • 0% of homes over 2,187 SF have a view, against 0% of homes under 1,176 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 1,176 SF10 sales1,176–1,603 SF10 sales1,632–2,187 SF10 salesOver 2,187 SF10 salesAll40 salesReal difference?
Net sale price average$482,975$632,604$827,025$1,178,561$780,291✓ large
Net price per SF average$520$452$429$423$456unclear
Living area average9441,4001,9072,7651,754by design
Year built median19521952195620161953✓ large

4.10 The numbers: selling

Under 1,176 SF10 sales1,176–1,603 SF10 sales1,632–2,187 SF10 salesOver 2,187 SF10 salesAll40 salesReal difference?
Days on market median486148833✓ large
Discount from original list average6.7%4.0%6.1%15.5%8.1%unclear
Price cut before sale30%20%30%80%40%unclear
Seller paid closing costs or repairs20%40%40%50%38%unclear
Has a view0%0%10%0%2%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 · 40 sales · October 28, 2025 – October 27, 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.

2026-10-28T07:22:45.467185 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 12 9 10 40 sales Sales per group Before 1951: 9 sales (22%) 1951–1953: 12 sales (30%) 1954–2005: 9 sales (22%) After 2005: 10 sales (25%)
Bottom line

5.1 Key differences

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

Before 19511951–19531954–2005After 2005
Newer homes After 2005
  • Sell for much more.
  • Are much larger.
Older homes Before 1951
  • Sell for much less.
  • Are much smaller.

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 19511951–19531954–2005After 2005Real difference?
Net sale price$574KLowest$655K$635K$1.25MHighest✓ large
Net price per SF$486 per SF$452 per SF$413 per SF$473 per SFunclear
Living area1,219 SFSmallest1,479 SF1,671 SF2,640 SFLargest✓ large
Days on market7 days20 days67 days68 daysunclear
Discount from original list5.1%6.3%11.9%9.5%unclear
Price cut before sale11%33%56%60%unclear
Seller paid closing costs or repairs22%42%44%40%unclear
Has a view0%0%11%0%unclear

5.3 Homes built after 2005 sell for about $672K (117%) more than homes built before 1951

2026-10-28T07:22:45.487978 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1951 9 sales 1951– 1953 12 sales 1954– 2005 9 sales After 2005 10 sales $0K $500K $1.00M $574K $655K $635K $1.25M Net sale price, average

The average is $1.25M for homes built after 2005 and $574K for homes built before 1951. It does not move in a straight line; homes built after 2005 are highest. Defined in 8.1.1.

✓ Real difference · large

5.4 Net price per SF: no clear difference

2026-10-28T07:22:45.510530 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1951 9 sales 1951– 1953 12 sales 1954– 2005 9 sales After 2005 10 sales $0 $200 $400 $486 $452 $413 $473 Net price per SF, average

The average is $473 per SF for homes built after 2005 and $486 per SF for homes built before 1951. It does not move in a straight line; homes built before 1951 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Homes built after 2005 are about 1,420 SF (117%) larger than homes built before 1951

2026-10-28T07:22:45.531807 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1951 9 sales 1951– 1953 12 sales 1954– 2005 9 sales After 2005 10 sales 0 1,000 2,000 3,000 1,219 1,479 1,671 2,640 Living area (SF), average

The average is 2,640 SF for homes built after 2005 and 1,219 SF for homes built before 1951. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

5.6 Days on market: no clear difference

2026-10-28T07:22:45.553635 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1951 9 sales 1951– 1953 12 sales 1954– 2005 9 sales After 2005 10 sales 0 25 50 75 7 20 67 68 Days on market, median

The median is 68 days for homes built after 2005 and 7 days for homes built before 1951. 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

2026-10-28T07:22:45.576387 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1951 9 sales 1951– 1953 12 sales 1954– 2005 9 sales After 2005 10 sales 0.0% 5.0% 10.0% 5.1% 6.3% 11.9% 9.5% Discount from original list, average

The average is 9.5% for homes built after 2005 and 5.1% for homes built before 1951. It does not move in a straight line; homes built 1954–2005 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-28T07:22:45.601308 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% 11 22 0 33 42 0 56 44 11 60 40 0 Before 1951 1951–1953 1954–2005 After 2005

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

  • 60% of homes built after 2005 had a price cut before sale, against 11% of homes built before 1951. Defined in 8.1.7.
  • 40% of homes built after 2005 had the seller pay closing costs or repairs, against 22% of homes built before 1951. Defined in 8.1.8.
  • 0% of homes built after 2005 have a view, against 0% of homes built before 1951. 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 19519 sales1951–195312 sales1954–20059 salesAfter 200510 salesAll40 salesReal difference?
Net sale price average$574,500$654,649$635,417$1,246,661$780,291✓ large
Net price per SF average$486$452$413$473$456unclear
Living area average1,2191,4791,6712,6401,754✓ large
Year built median19501952195520181953by design

5.10 The numbers: selling

Before 19519 sales1951–195312 sales1954–20059 salesAfter 200510 salesAll40 salesReal difference?
Days on market median720676833unclear
Discount from original list average5.1%6.3%11.9%9.5%8.1%unclear
Price cut before sale11%33%56%60%40%unclear
Seller paid closing costs or repairs22%42%44%40%38%unclear
Has a view0%0%11%0%2%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 · 40 sales · October 28, 2025 – October 27, 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.

2026-10-28T07:22:45.619618 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 1 38 39 sales Sales per group View: 1 sales (3%) No view: 38 sales (97%)
Bottom line: too few sales to test.

6.1 Key differences

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

6.3 Net sale price: described, not tested

2026-10-28T07:22:45.636360 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 38 sales $0K $250K $500K $750K $1.00M $858K $788K Net sale price, average

The average is $858K for homes with a view and $788K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-28T07:22:45.654489 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 38 sales $0 $200 $400 $424 $459 Net price per SF, average

The average is $424 per SF for homes with a view and $459 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-28T07:22:45.694155 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 38 sales 0 500 1,000 1,500 2,000 2,024 1,764 Living area (SF), average

The average is 2,024 SF for homes with a view and 1,764 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-28T07:22:45.714166 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 38 sales 1950 1965 1980 1995 2010 1954 1953 Year built: median (dot) and middle half (bar)

The median is 1954 for homes with a view and 1953 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-28T07:22:45.732757 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 38 sales 0 10 20 30 40 5 36 Days on market, median

The median is 5 days for homes with a view and 36 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-28T07:22:45.752244 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 38 sales 0.0% 2.5% 5.0% 7.5% 10.0% 2.0% 8.5% Discount from original list, average

The average is 2.0% for homes with a view and 8.5% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-28T07:22:45.771072 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 0 100 42 37 View No view

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

  • 0% of homes with a view had a price cut before sale, against 42% of homes without a view. Defined in 8.1.7.
  • 100% of homes with a view had the seller pay closing costs or repairs, against 37% of homes without a view. Defined in 8.1.8.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View1 salesNo view38 salesAll39 sales
Net sale price average$857,500$787,609$789,401
Net price per SF average$424$459$458
Living area average2,0241,7641,771
Year built median195419531953

6.11 The numbers: selling

View1 salesNo view38 salesAll39 sales
Days on market median53634
Discount from original list average2.0%8.5%8.3%
Price cut before sale0%42%41%
Seller paid closing costs or repairs100%37%38%

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 · 12 sales · October 28, 2025 – October 27, 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: 12 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 Crestview.
MeasureAverageMedian
Sales12
Net sale price$1,628,000$1,677,500
Net price per SF$539$555
Living area (SF)2,9783,149
Days on market97112
Discount from original list8.9%8.6%
Price cut before sale50% of sales
Seller paid closing costs or repairs8% of sales
Year built2025–2026

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
40 resale sales. Average $780,291; median $665,000; standard deviation $328,734; middle half (25th–75th percentile) $525,000–$952,125; lowest $395,000, highest $1,574,614. 15 sales had a seller payment; their median payment was $5,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
40 resale sales. Average $456; median $464; standard deviation $91; middle half (25th–75th percentile) $385–$514; lowest $224, highest $691.

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
40 resale sales. Average 1,754; median 1,618; standard deviation 711; middle half (25th–75th percentile) 1,167–2,225; lowest 760, highest 3,058.

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
40 resale sales. Average 1970; median 1953; standard deviation 29; middle half (25th–75th percentile) 1951–2006; lowest 1949, 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
40 resale sales. Average 61; median 33; standard deviation 100; middle half (25th–75th percentile) 7–80; lowest 0, highest 598. 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
40 resale sales. Average 8.1%; median 5.0%; standard deviation 9.8%; middle half (25th–75th percentile) 2.0%–11.0%; lowest −4.3%, highest 40.5%. 5 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
16 of 40 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
15 of 40 resale sales (37.5%).

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
1 sales with a view, 38 without, 1 unclassified. Most common View entries: None 32, Neighborhood 6, Garden 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 “crestview” (case-insensitive). A record is kept when its subdivision name belongs to the Crestview family, the same rule comparable sales use.
The data
Pulled October 28, 2026: 57 closed Crestview records over the prior year, in ZIP 78757, 78752. 16 subdivision spellings kept, the most common: Crestview Add Sec 01 (11); Crestview Add Sec 03 (10); Crestview (6); Crestview Add Sec 05 (5); Crestview Add Sec 08 (5); Crestview Add Sec 04 (3); Crestview Sec 02 (3); Crestview Add Sec 07 (3); Crestview Sec 2 Resub Of Pt Of (2); Crestview Add Sec 06 (2); Crestview Add Sec 12 (2); Crestview Add Sec 09 (1); and 4 more (4 records). Names found by the search but not part of Crestview, left out: Crestview Station Resub Of Lt (9); Jefferson Village / Crestview (1); Crestview Addn (1); Crestview Addn Sec 10 (1); Crestview Northgate Addn (1); CRESTVIEW ADDN SEC 7 (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 19 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 28, 2025 to October 27, 2026 inclusive.
The data
52 single-family sales in the window: 40 resale, 12 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
40 resale; 12 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)

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 $525K”.
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 $525K: $395,000–$510,000 (9 sales); $525K–$625K: $525,000–$625,000 (11 sales); $705K–$930K: $705,000–$929,500 (10 sales); Over $930K: $1,020,000–$1,574,614 (10 sales)
Quartiles by living area: Under 1,176 SF: 760–1,140 SF (10 sales); 1,176–1,603 SF: 1,176–1,603 SF (10 sales); 1,632–2,187 SF: 1,632–2,187 SF (10 sales); Over 2,187 SF: 2,339–3,058 SF (10 sales)
Quartiles by year built: Before 1951: 1949–1950 (9 sales); 1951–1953: 1951–1953 (12 sales); 1954–2005: 1954–2005 (9 sales); After 2005: 2008–2023 (10 sales)
View and no view: View: MLS lists a view (1 sales); No view: None or Neighborhood (38 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 $780,291, median $665,000. Days on market: average 61, median 33: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

In simple terms
Checks whether a measure really differs across the four groups of a slice. It uses each sale's rank, not its value, so a few extreme sales cannot drive the answer.
Statistically
H = [12/(n(n+1))] Σ Rⱼ²/nⱼ − 3(n+1), compared with χ² on k − 1 degrees of freedom (Kruskal & Wallis, 1952). Effect size ε² = H/(n − 1): ≥ .01 small, ≥ .06 medium, ≥ .14 large (Tomczak & Tomczak, 2014). A slice is tested only when every group has at least 5 sales; smaller groups are described, not tested.
The data
Run on every measure in sections 3–5; each result is in 8.3.

8.2.8 Mann–Whitney U test

In simple terms
The same check when there are only two groups: view against no view.
Statistically
Two-sided U test (Mann & Whitney, 1947). Effect size = rank-biserial correlation |1 − 2U/(n₁n₂)|: ≥ .10 small, ≥ .30 medium, ≥ .50 large (Kerby, 2014; Cohen, 1988).
The data
Run on every measure in section 6; results in 8.3.

8.2.9 Chi-square test

In simple terms
Checks whether a yes/no share (price cut, seller payment, view) differs between groups more than chance would.
Statistically
Pearson χ² on the 2 × k table of counts, no continuity correction (Pearson, 1900). Effect size Cramér's V = √(χ²/n): ≥ .10 small, ≥ .30 medium, ≥ .50 large (Cramér, 1946).
The data
Run on the three shares in every slice; results in 8.3.

8.2.10 Real difference (significance)

In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063; Quartiles by year built: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
7 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 = 3.4630.3253p < 0.0063Unclearε² = 0.089medium
Living areaKruskal–WallisH = 26.433< 0.0001p < 0.0063Yesε² = 0.678large
Year builtKruskal–WallisH = 19.4830.0002p < 0.0063Yesε² = 0.500large
Days on marketKruskal–WallisH = 7.2630.0640p < 0.0063Unclearε² = 0.186large
Discount from original listKruskal–WallisH = 4.0130.2602p < 0.0063Unclearε² = 0.103medium
Price cut before saleChi-squareχ² = 6.2330.1008p < 0.0063UnclearCramér’s V = 0.395medium
Seller paid closing costs or repairsChi-squareχ² = 4.0130.2600p < 0.0063UnclearCramér’s V = 0.317medium
Has a viewChi-squareχ² = 3.0830.3799p < 0.0063UnclearCramér’s V = 0.277small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 26.503< 0.0001p < 0.0063Yesε² = 0.679large
Net price per SFKruskal–WallisH = 5.1930.1585p < 0.0063Unclearε² = 0.133medium
Year builtKruskal–WallisH = 20.0130.0002p < 0.0063Yesε² = 0.513large
Days on marketKruskal–WallisH = 12.6830.0054p < 0.0063Yesε² = 0.325large
Discount from original listKruskal–WallisH = 7.0030.0719p < 0.0063Unclearε² = 0.180large
Price cut before saleChi-squareχ² = 9.1730.0272p < 0.0063UnclearCramér’s V = 0.479medium
Seller paid closing costs or repairsChi-squareχ² = 2.0330.5669p < 0.0063UnclearCramér’s V = 0.225small
Has a viewChi-squareχ² = 3.0830.3799p < 0.0063UnclearCramér’s V = 0.277small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 21.413< 0.0001p < 0.0063Yesε² = 0.549large
Net price per SFKruskal–WallisH = 3.8930.2734p < 0.0063Unclearε² = 0.100medium
Living areaKruskal–WallisH = 19.9930.0002p < 0.0063Yesε² = 0.512large
Days on marketKruskal–WallisH = 5.7030.1274p < 0.0063Unclearε² = 0.146large
Discount from original listKruskal–WallisH = 3.6530.3024p < 0.0063Unclearε² = 0.093medium
Price cut before saleChi-squareχ² = 5.9330.1153p < 0.0063UnclearCramér’s V = 0.385medium
Seller paid closing costs or repairsChi-squareχ² = 1.2030.7537p < 0.0063UnclearCramér’s V = 0.173small
Has a viewChi-squareχ² = 3.5330.3165p < 0.0063UnclearCramér’s V = 0.297small

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

Left out of the analysis: 12 new-construction sales (basic statistics only, section 7); 5 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 40 closed MLS resale sales; the 12 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 28, 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.