ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Hunters Chase

Austin, TX 78729
Resale homes · closed Nov 5 – Nov 4, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 5, 2026 · 4:09 PM 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
26
single-family resale homes
Median net sale price
$473,500
average $494,869
Median net price per SF
$202
average $217
Median days on market
32 days
average 59 days
1. SummaryResale homes · 26 sales · November 5, 2025 – November 4, 2026

This study looks at the 26 resale homes sold in Hunters Chase in the 365 days to November 4, 2026. A full year is used because only 9 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 sold26 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 $440K · 6 sales$440K–$472K · 7 sales$475K–$555K · 7 salesOver $555K · 6 sales
3. Quartiles by net sale priceResale homes · 26 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T16:09:25.011800 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 7 7 6 26 sales Sales per group Under $440K: 6 sales (23%) $440K–$472K: 7 sales (27%) $475K–$555K: 7 sales (27%) Over $555K: 6 sales (23%)
Bottom line: no measure differs enough between the groups to rule out chance.

3.1 Key differences

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

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 $440K$440K–$472K$475K–$555KOver $555KReal difference?
Net price per SF$208 per SF$198 per SF$204 per SF$264 per SFunclear
Living area2,041 SF2,285 SF2,486 SF2,404 SFunclear
Year built1985198719871986unclear
Days on market64 days34 days29 days30 daysunclear
Discount from original list8.7%5.5%5.2%3.9%unclear
Price cut before sale50%43%43%50%unclear
Seller paid closing costs or repairs50%71%43%50%unclear
Has a view33%0%0%17%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

2026-11-05T16:09:25.040430 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $440K 6 sales $440K– $472K 7 sales $475K– $555K 7 sales Over $555K 6 sales $0 $100 $200 $300 $208 $198 $204 $264 Net price per SF, average

The average is $264 per SF for homes over $555K and $208 per SF for homes under $440K. It does not move in a straight line; homes over $555K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-11-05T16:09:25.063839 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $440K 6 sales $440K– $472K 7 sales $475K– $555K 7 sales Over $555K 6 sales 0 1,000 2,000 2,041 2,285 2,486 2,404 Living area (SF), average

The average is 2,404 SF for homes over $555K and 2,041 SF for homes under $440K. It does not move in a straight line; homes $475K–$555K are highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-11-05T16:09:25.088973 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $440K 6 sales $440K– $472K 7 sales $475K– $555K 7 sales Over $555K 6 sales 1984 1986 1988 1990 1992 1985 1987 1987 1986 Year built: median (dot) and middle half (bar)

The median is 1986 for homes over $555K and 1985 for homes under $440K. It does not move in a straight line; homes $440K–$472K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-05T16:09:25.112430 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $440K 6 sales $440K– $472K 7 sales $475K– $555K 7 sales Over $555K 6 sales 0 20 40 60 64 34 29 30 Days on market, median

The median is 30 days for homes over $555K and 64 days for homes under $440K. It does not move in a straight line; homes under $440K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-05T16:09:25.134769 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $440K 6 sales $440K– $472K 7 sales $475K– $555K 7 sales Over $555K 6 sales 0.0% 5.0% 10.0% 8.7% 5.5% 5.2% 3.9% Discount from original list, average

The average is 3.9% for homes over $555K and 8.7% for homes under $440K. It falls step by step from the lowest range to the highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-05T16:09:25.164604 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 50 33 43 71 0 43 43 0 50 50 17 Under $440K $440K–$472K $475K–$555K Over $555K

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

  • 50% of homes over $555K had a price cut before sale, against 50% of homes under $440K. Defined in 8.1.7.
  • 50% of homes over $555K had the seller pay closing costs or repairs, against 50% of homes under $440K. Defined in 8.1.8.
  • 17% of homes over $555K have a view, against 33% of homes under $440K. 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 $440K6 sales$440K–$472K7 sales$475K–$555K7 salesOver $555K6 salesAll26 salesReal difference?
Net sale price average$413,418$451,456$506,057$613,917$494,869by design
Net price per SF average$208$198$204$264$217unclear
Living area average2,0412,2852,4862,4042,310unclear
Year built median19851987198719861986unclear

3.10 The numbers: selling

Under $440K6 sales$440K–$472K7 sales$475K–$555K7 salesOver $555K6 salesAll26 salesReal difference?
Days on market median6434293032unclear
Discount from original list average8.7%5.5%5.2%3.9%5.8%unclear
Price cut before sale50%43%43%50%46%unclear
Seller paid closing costs or repairs50%71%43%50%54%unclear
Has a view33%0%0%17%12%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 · 26 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T16:09:25.185309 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 7 7 6 26 sales Sales per group Under 2,156 SF: 6 sales (23%) 2,156–2,377 SF: 7 sales (27%) 2,382–2,486 SF: 7 sales (27%) Over 2,486 SF: 6 sales (23%)
Bottom line: no measure differs enough between the groups to rule out chance.

4.1 Key differences

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

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 2,156 SF2,156–2,377 SF2,382–2,486 SFOver 2,486 SFReal difference?
Net sale price$480K$480K$476K$549Kunclear
Net price per SF$261 per SF$211 per SF$196 per SF$205 per SFunclear
Year built1984198719861993unclear
Days on market66 days26 days74 days30 daysunclear
Discount from original list4.5%4.1%9.0%5.3%unclear
Price cut before sale50%29%57%50%unclear
Seller paid closing costs or repairs67%57%29%67%unclear
Has a view33%14%0%0%unclear

4.3 Net sale price: no clear difference

2026-11-05T16:09:25.205704 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,156 SF 6 sales 2,156– 2,377 SF 7 sales 2,382– 2,486 SF 7 sales Over 2,486 SF 6 sales $0K $200K $400K $600K $480K $480K $476K $549K Net sale price, average

The average is $549K for homes over 2,486 SF and $480K for homes under 2,156 SF. It does not move in a straight line; homes over 2,486 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-11-05T16:09:25.228940 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,156 SF 6 sales 2,156– 2,377 SF 7 sales 2,382– 2,486 SF 7 sales Over 2,486 SF 6 sales $0 $100 $200 $300 $261 $211 $196 $205 Net price per SF, average

The average is $205 per SF for homes over 2,486 SF and $261 per SF for homes under 2,156 SF. It does not move in a straight line; homes under 2,156 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-05T16:09:25.253231 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,156 SF 6 sales 2,156– 2,377 SF 7 sales 2,382– 2,486 SF 7 sales Over 2,486 SF 6 sales 1984 1987 1990 1993 1984 1987 1986 1993 Year built: median (dot) and middle half (bar)

The median is 1993 for homes over 2,486 SF and 1984 for homes under 2,156 SF. It does not move in a straight line; homes over 2,486 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-05T16:09:25.277092 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,156 SF 6 sales 2,156– 2,377 SF 7 sales 2,382– 2,486 SF 7 sales Over 2,486 SF 6 sales 0 25 50 75 66 26 74 30 Days on market, median

The median is 30 days for homes over 2,486 SF and 66 days for homes under 2,156 SF. It does not move in a straight line; homes 2,382–2,486 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-05T16:09:25.299790 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,156 SF 6 sales 2,156– 2,377 SF 7 sales 2,382– 2,486 SF 7 sales Over 2,486 SF 6 sales 0.0% 5.0% 10.0% 4.5% 4.1% 9.0% 5.3% Discount from original list, average

The average is 5.3% for homes over 2,486 SF and 4.5% for homes under 2,156 SF. It does not move in a straight line; homes 2,382–2,486 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

2026-11-05T16:09:25.325838 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 33 29 57 14 57 29 0 50 67 0 Under 2,156 SF 2,156–2,377 SF 2,382–2,486 SF Over 2,486 SF

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

  • 50% of homes over 2,486 SF had a price cut before sale, against 50% of homes under 2,156 SF. Defined in 8.1.7.
  • 67% of homes over 2,486 SF had the seller pay closing costs or repairs, against 67% of homes under 2,156 SF. Defined in 8.1.8.
  • 0% of homes over 2,486 SF have a view, against 33% of homes under 2,156 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 2,156 SF6 sales2,156–2,377 SF7 sales2,382–2,486 SF7 salesOver 2,486 SF6 salesAll26 salesReal difference?
Net sale price average$480,334$479,764$476,178$548,833$494,869unclear
Net price per SF average$261$211$196$205$217unclear
Living area average1,8582,2712,4262,6742,310by design
Year built median19841987198619931986unclear

4.10 The numbers: selling

Under 2,156 SF6 sales2,156–2,377 SF7 sales2,382–2,486 SF7 salesOver 2,486 SF6 salesAll26 salesReal difference?
Days on market median6626743032unclear
Discount from original list average4.5%4.1%9.0%5.3%5.8%unclear
Price cut before sale50%29%57%50%46%unclear
Seller paid closing costs or repairs67%57%29%67%54%unclear
Has a view33%14%0%0%12%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 · 26 sales · November 5, 2025 – November 4, 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.

2026-11-05T16:09:25.347177 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 6 6 7 26 sales Sales per group Before 1985: 7 sales (27%) 1985–1986: 6 sales (23%) 1987–1991: 6 sales (23%) After 1991: 7 sales (27%)
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 19851985–19861987–1991After 1991Real difference?
Net sale price$514K$461K$497K$504Kunclear
Net price per SF$233 per SF$221 per SF$220 per SF$195 per SFunclear
Living area2,253 SF2,114 SF2,272 SF2,569 SFunclear
Days on market74 days30 days18 days85 daysunclear
Discount from original list5.4%5.8%2.3%9.1%unclear
Price cut before sale57%33%17%71%unclear
Seller paid closing costs or repairs14%67%83%57%unclear
Has a view14%33%0%0%unclear

5.3 Net sale price: no clear difference

2026-11-05T16:09:25.367381 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 7 sales 1985– 1986 6 sales 1987– 1991 6 sales After 1991 7 sales $0K $200K $400K $600K $514K $461K $497K $504K Net sale price, average

The average is $504K for homes built after 1991 and $514K for homes built before 1985. It does not move in a straight line; homes built before 1985 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-05T16:09:25.390562 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 7 sales 1985– 1986 6 sales 1987– 1991 6 sales After 1991 7 sales $0 $100 $200 $233 $221 $220 $195 Net price per SF, average

The average is $195 per SF for homes built after 1991 and $233 per SF for homes built before 1985. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-05T16:09:25.411921 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 7 sales 1985– 1986 6 sales 1987– 1991 6 sales After 1991 7 sales 0 1,000 2,000 3,000 2,253 2,114 2,272 2,569 Living area (SF), average

The average is 2,569 SF for homes built after 1991 and 2,253 SF for homes built before 1985. It does not move in a straight line; homes built after 1991 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-05T16:09:25.433923 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 7 sales 1985– 1986 6 sales 1987– 1991 6 sales After 1991 7 sales 0 50 100 74 30 18 85 Days on market, median

The median is 85 days for homes built after 1991 and 74 days for homes built before 1985. It does not move in a straight line; homes built after 1991 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-05T16:09:25.456621 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 7 sales 1985– 1986 6 sales 1987– 1991 6 sales After 1991 7 sales 0.0% 5.0% 10.0% 5.4% 5.8% 2.3% 9.1% Discount from original list, average

The average is 9.1% for homes built after 1991 and 5.4% for homes built before 1985. It does not move in a straight line; homes built after 1991 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

2026-11-05T16:09:25.481981 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% 57 14 14 33 67 33 17 83 0 71 57 0 Before 1985 1985–1986 1987–1991 After 1991

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

  • 71% of homes built after 1991 had a price cut before sale, against 57% of homes built before 1985. Defined in 8.1.7.
  • 57% of homes built after 1991 had the seller pay closing costs or repairs, against 14% of homes built before 1985. Defined in 8.1.8.
  • 0% of homes built after 1991 have a view, against 14% of homes built before 1985. 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 19857 sales1985–19866 sales1987–19916 salesAfter 19917 salesAll26 salesReal difference?
Net sale price average$513,929$460,650$496,524$503,721$494,869unclear
Net price per SF average$233$221$220$195$217unclear
Living area average2,2532,1142,2722,5692,310unclear
Year built median19831985198719941986by design

5.10 The numbers: selling

Before 19857 sales1985–19866 sales1987–19916 salesAfter 19917 salesAll26 salesReal difference?
Days on market median7430188532unclear
Discount from original list average5.4%5.8%2.3%9.1%5.8%unclear
Price cut before sale57%33%17%71%46%unclear
Seller paid closing costs or repairs14%67%83%57%54%unclear
Has a view14%33%0%0%12%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 · 26 sales · November 5, 2025 – November 4, 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.

2026-11-05T16:09:25.500296 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 23 26 sales Sales per group View: 3 sales (12%) No view: 23 sales (88%)
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

2026-11-05T16:09:25.517413 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 23 sales $0K $200K $400K $460K $499K Net sale price, average

The average is $460K for homes with a view and $499K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-11-05T16:09:25.534854 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 23 sales $0 $100 $200 $300 $257 $212 Net price per SF, average

The average is $257 per SF for homes with a view and $212 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-11-05T16:09:25.552884 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 23 sales 0 1,000 2,000 1,865 2,369 Living area (SF), average

The average is 1,865 SF for homes with a view and 2,369 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-11-05T16:09:25.599247 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 23 sales 1984 1986 1988 1990 1992 1985 1987 Year built: median (dot) and middle half (bar)

The median is 1985 for homes with a view and 1987 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-11-05T16:09:25.618461 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 23 sales 0 10 20 30 40 39 30 Days on market, median

The median is 39 days for homes with a view and 30 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

2026-11-05T16:09:25.638520 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 23 sales 0.0% 2.5% 5.0% 7.5% 10.0% 8.7% 5.4% Discount from original list, average

The average is 8.7% for homes with a view and 5.4% 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

2026-11-05T16:09:25.657828 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 100 33 39 57 View No view

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

  • 100% of homes with a view had a price cut before sale, against 39% of homes without a view. Defined in 8.1.7.
  • 33% of homes with a view had the seller pay closing costs or repairs, against 57% of homes without a view. Defined in 8.1.8.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View3 salesNo view23 salesAll26 sales
Net sale price average$459,667$499,461$494,869
Net price per SF average$257$212$217
Living area average1,8652,3692,310
Year built median198519871986

6.11 The numbers: selling

View3 salesNo view23 salesAll26 sales
Days on market median393032
Discount from original list average8.7%5.4%5.8%
Price cut before sale100%39%46%
Seller paid closing costs or repairs33%57%54%

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.4.

7. New constructionBasic statistics · 0 sales · November 5, 2025 – November 4, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 0 sales, no groups, no tests.

Note: these are only the new-construction sales reported in ABOR MLS. Builders often sell homes without listing them in the MLS, so these figures do not necessarily represent all new-construction sales in Hunters Chase.

No new-construction sales were reported in ABOR MLS in this window.

Same definitions as the rest of the study (section 8). New construction = NewConstructionYN true, or PropertyCondition “New Construction” or “Under Construction”.

8. AppendixMeasures, methods and tests

Each measure and method three ways: in plain words, as statistics, and with the data from this study.

8.1 Measures

8.1.1 Net sale price

In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
26 resale sales. Average $494,869; median $473,500; standard deviation $78,111; middle half (25th–75th percentile) $440,262–$548,100; lowest $380,000, highest $675,000. 14 sales had a seller payment; their median payment was $6,250.

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
26 resale sales. Average $217; median $202; standard deviation $42; middle half (25th–75th percentile) $192–$231; lowest $164, highest $358.

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
26 resale sales. Average 2,310; median 2,380; standard deviation 322; middle half (25th–75th percentile) 2,158–2,480; lowest 1,519, highest 2,861.

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
26 resale sales. Average 1988; median 1986; standard deviation 5; middle half (25th–75th percentile) 1984–1992; lowest 1983, highest 1998.

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
26 resale sales. Average 59; median 32; standard deviation 58; middle half (25th–75th percentile) 14–91; lowest 2, highest 201. 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
26 resale sales. Average 5.8%; median 4.0%; standard deviation 5.4%; middle half (25th–75th percentile) 1.1%–9.7%; lowest 0.0%, highest 18.8%. 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
12 of 26 resale sales (46.2%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
14 of 26 resale sales (53.8%).

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
3 sales with a view, 23 without, 0 unclassified. Most common View entries: None 18, Neighborhood 5, Park/Greenbelt 2, Trees/Woods 2.

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 2026-11-05 22:00 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “hunters chase” (case-insensitive). A record is kept when its subdivision name belongs to the Hunters Chase family, the same rule comparable sales use.
The data
Pulled November 5, 2026: 26 closed Hunters Chase records over the prior year, in ZIP 78729. 11 subdivision spellings kept: Hunters Chase Sec 04 (7); Hunters Chase Sec 05 Amd (5); Hunters Chase Sec 01 (3); Hunters Chase Sec 07 Amd Pt Amd (3); Hunters Chase Sec 02 (2); Hunters Chase Sec 07 Amd (1); HUNTERS CHASE SEC 4 (1); Hunters Chase Sec 06 (1); Hunters Chase Sec 4 (1); Hunters Chase Sec 05 (1); Hunters Chase (1). Names found by the search but not part of Hunters Chase, left out: Estates At Hunters Chase Sec 01 (1); HUNTERS CHASE DRIVE ROW DEDI (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 9 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 5, 2025 to November 4, 2026 inclusive.
The data
26 single-family sales in the window: 26 resale, 0 new construction.

8.2.3 Resale and new construction

In simple terms
A resale home was previously owned. New construction is sold by the builder and behaves differently, so it is kept out of every analysis and reported once on its own.
Statistically
New construction = NewConstructionYN true, or PropertyCondition contains “New Construction” or “Under Construction”. Everything else is resale.
The data
26 resale; 0 new construction.

8.2.4 Sales left out

In simple terms
A few records cannot be used as entered and are left out before any analysis.
Statistically
Excluded: PropertySubType other than Single Family Residence; no OriginalListPrice; LivingArea under 400 SF; seller payments above 10% of ClosePrice (treated as entry errors).
The data
None in this window.

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $440K”.
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 $440K: $380,000–$440,000 (6 sales); $440K–$472K: $440,050–$472,000 (7 sales); $475K–$555K: $475,000–$555,000 (7 sales); Over $555K: $595,000–$675,000 (6 sales)
Quartiles by living area: Under 2,156 SF: 1,519–2,105 SF (6 sales); 2,156–2,377 SF: 2,156–2,377 SF (7 sales); 2,382–2,486 SF: 2,382–2,486 SF (7 sales); Over 2,486 SF: 2,557–2,861 SF (6 sales)
Quartiles by year built: Before 1985: 1983–1984 (7 sales); 1985–1986: 1985–1986 (6 sales); 1987–1991: 1987–1991 (6 sales); After 1991: 1992–1998 (7 sales)
View and no view: View: MLS lists a view (3 sales); No view: None or Neighborhood (23 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 $494,869, median $473,500. Days on market: average 59, median 32: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

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

8.2.8 Mann–Whitney U test

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

8.2.9 Chi-square test

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

8.2.10 Real difference (significance)

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

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
0 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 = 8.5630.0357p < 0.0063Unclearε² = 0.342large
Living areaKruskal–WallisH = 8.3730.0390p < 0.0063Unclearε² = 0.335large
Year builtKruskal–WallisH = 0.2830.9646p < 0.0063Unclearε² = 0.011small
Days on marketKruskal–WallisH = 0.4230.9367p < 0.0063Unclearε² = 0.017small
Discount from original listKruskal–WallisH = 1.9930.5738p < 0.0063Unclearε² = 0.080medium
Price cut before saleChi-squareχ² = 0.1330.9876p < 0.0063UnclearCramér’s V = 0.071negligible
Seller paid closing costs or repairsChi-squareχ² = 1.2830.7333p < 0.0063UnclearCramér’s V = 0.222small
Has a viewChi-squareχ² = 4.7730.1892p < 0.0063UnclearCramér’s V = 0.428medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 4.9930.1726p < 0.0063Unclearε² = 0.200large
Net price per SFKruskal–WallisH = 7.9930.0462p < 0.0063Unclearε² = 0.320large
Year builtKruskal–WallisH = 8.1830.0425p < 0.0063Unclearε² = 0.327large
Days on marketKruskal–WallisH = 2.9030.4075p < 0.0063Unclearε² = 0.116medium
Discount from original listKruskal–WallisH = 3.6830.2977p < 0.0063Unclearε² = 0.147large
Price cut before saleChi-squareχ² = 1.2830.7333p < 0.0063UnclearCramér’s V = 0.222small
Seller paid closing costs or repairsChi-squareχ² = 2.6230.4534p < 0.0063UnclearCramér’s V = 0.318medium
Has a viewChi-squareχ² = 4.5430.2088p < 0.0063UnclearCramér’s V = 0.418medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 3.5630.3133p < 0.0063Unclearε² = 0.142large
Net price per SFKruskal–WallisH = 3.7930.2846p < 0.0063Unclearε² = 0.152large
Living areaKruskal–WallisH = 6.9130.0750p < 0.0063Unclearε² = 0.276large
Days on marketKruskal–WallisH = 4.8030.1867p < 0.0063Unclearε² = 0.192large
Discount from original listKruskal–WallisH = 4.2730.2334p < 0.0063Unclearε² = 0.171large
Price cut before saleChi-squareχ² = 4.6430.2005p < 0.0063UnclearCramér’s V = 0.422medium
Seller paid closing costs or repairsChi-squareχ² = 6.9330.0740p < 0.0063UnclearCramér’s V = 0.516large
Has a viewChi-squareχ² = 4.5430.2088p < 0.0063UnclearCramér’s V = 0.418medium

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

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

8.5 References

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

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 26 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 5, 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.