ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Gracywoods Sec 09 & 10

Austin, TX 78758
Resale homes · closed Nov 7 – Nov 6, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 7, 2026 · 7:47 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
42
single-family resale homes
Median net sale price
$508,434
average $506,979
Median net price per SF
$266
average $269
Median days on market
40 days
average 66 days
1. SummaryResale homes · 42 sales · November 7, 2025 – November 6, 2026

This study looks at the 42 resale homes sold in Gracywoods Sec 09 & 10 in the 365 days to November 6, 2026. A full year is used because only 21 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 sold42 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 $441K · 10 sales$441K–$504K · 11 sales$513K–$562K · 11 salesOver $562K · 10 sales
3. Quartiles by net sale priceResale homes · 42 sales · November 7, 2025 – November 6, 2026

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

2026-11-07T07:48:00.250448 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 11 11 10 42 sales Sales per group Under $441K: 10 sales (24%) $441K–$504K: 11 sales (26%) $513K–$562K: 11 sales (26%) Over $562K: 10 sales (24%)
Bottom line

3.1 Key differences

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

Under $441K$441K–$504K$513K–$562KOver $562K
Higher-priced homes Over $562K
  • Sell for more per square foot.
Lower-priced homes Under $441K
  • Sell for less per square foot.

3.2 At a glance

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

Under $441K$441K–$504K$513K–$562KOver $562KReal difference?
Net price per SF$230 per SFLowest$253 per SF$276 per SF$318 per SFHighest✓ large
Living area1,700 SF1,868 SF1,991 SF2,049 SFunclear
Year built1983198419811984unclear
Days on market86 days21 days46 days18 daysunclear
Discount from original list9.2%5.0%7.5%4.0%unclear
Price cut before sale70%36%27%40%unclear
Seller paid closing costs or repairs40%55%82%70%unclear
Has a view10%18%9%60%unclear

How to read this section. Each heading gives the finding. The gold box says whether the gap is real (✓, with its size) or could be chance (–). The section ends with its numbers; the tests are in section 8.3.

3.3 Homes over $562K sell for about $87 per SF (38%) more than homes under $441K

2026-11-07T07:48:00.282310 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $441K 10 sales $441K– $504K 11 sales $513K– $562K 11 sales Over $562K 10 sales $0 $100 $200 $300 $230 $253 $276 $318 Net price per SF, average

The average is $318 per SF for homes over $562K and $230 per SF for homes under $441K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Living area: no clear difference

2026-11-07T07:48:00.307601 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $441K 10 sales $441K– $504K 11 sales $513K– $562K 11 sales Over $562K 10 sales 0 1,000 2,000 1,700 1,868 1,991 2,049 Living area (SF), average

The average is 2,049 SF for homes over $562K and 1,700 SF for homes under $441K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-11-07T07:48:00.334238 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $441K 10 sales $441K– $504K 11 sales $513K– $562K 11 sales Over $562K 10 sales 1978 1980 1982 1984 1983 1984 1981 1984 Year built: median (dot) and middle half (bar)

The median is 1984 for homes over $562K and 1983 for homes under $441K. It does not move in a straight line; homes $441K–$504K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-07T07:48:00.360400 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $441K 10 sales $441K– $504K 11 sales $513K– $562K 11 sales Over $562K 10 sales 0 50 100 86 21 46 18 Days on market, median

The median is 18 days for homes over $562K and 86 days for homes under $441K. It does not move in a straight line; homes under $441K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-07T07:48:00.384264 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $441K 10 sales $441K– $504K 11 sales $513K– $562K 11 sales Over $562K 10 sales 0.0% 5.0% 10.0% 9.2% 5.0% 7.5% 4.0% Discount from original list, average

The average is 4.0% for homes over $562K and 9.2% for homes under $441K. It does not move in a straight line; homes under $441K 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

2026-11-07T07:48:00.417623 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% 70 40 10 36 55 18 27 82 9 40 70 60 Under $441K $441K–$504K $513K–$562K Over $562K

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

  • 40% of homes over $562K had a price cut before sale, against 70% of homes under $441K. Defined in 8.1.7.
  • 70% of homes over $562K had the seller pay closing costs or repairs, against 40% of homes under $441K. Defined in 8.1.8.
  • 60% of homes over $562K have a view, against 10% of homes under $441K. 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 $441K10 sales$441K–$504K11 sales$513K–$562K11 salesOver $562K10 salesAll42 salesReal difference?
Net sale price average$386,087$462,506$535,375$645,555$506,979by design
Net price per SF average$230$253$276$318$269✓ large
Living area average1,7001,8681,9912,0491,903unclear
Year built median19831984198119841983unclear

3.10 The numbers: selling

Under $441K10 sales$441K–$504K11 sales$513K–$562K11 salesOver $562K10 salesAll42 salesReal difference?
Days on market median8621461840unclear
Discount from original list average9.2%5.0%7.5%4.0%6.4%unclear
Price cut before sale70%36%27%40%43%unclear
Seller paid closing costs or repairs40%55%82%70%62%unclear
Has a view10%18%9%60%24%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 · 42 sales · November 7, 2025 – November 6, 2026

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

2026-11-07T07:48:00.440772 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 11 11 10 42 sales Sales per group Under 1,698 SF: 10 sales (24%) 1,698–1,769 SF: 11 sales (26%) 1,775–2,131 SF: 11 sales (26%) Over 2,131 SF: 10 sales (24%)
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 1,698 SF1,698–1,769 SF1,775–2,131 SFOver 2,131 SFReal difference?
Net sale price$441K$480K$564K$540Kunclear
Net price per SF$280 per SF$276 per SF$289 per SF$229 per SFunclear
Year built1984198319831984unclear
Days on market46 days47 days26 days68 daysunclear
Discount from original list6.5%6.7%4.7%7.9%unclear
Price cut before sale40%64%18%50%unclear
Seller paid closing costs or repairs50%64%64%70%unclear
Has a view10%9%36%40%unclear

4.3 Net sale price: no clear difference

2026-11-07T07:48:00.463269 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,698 SF 10 sales 1,698– 1,769 SF 11 sales 1,775– 2,131 SF 11 sales Over 2,131 SF 10 sales $0K $200K $400K $600K $441K $480K $564K $540K Net sale price, average

The average is $540K for homes over 2,131 SF and $441K for homes under 1,698 SF. It does not move in a straight line; homes 1,775–2,131 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-11-07T07:48:00.488487 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,698 SF 10 sales 1,698– 1,769 SF 11 sales 1,775– 2,131 SF 11 sales Over 2,131 SF 10 sales $0 $100 $200 $300 $280 $276 $289 $229 Net price per SF, average

The average is $229 per SF for homes over 2,131 SF and $280 per SF for homes under 1,698 SF. It does not move in a straight line; homes 1,775–2,131 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-07T07:48:00.513844 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,698 SF 10 sales 1,698– 1,769 SF 11 sales 1,775– 2,131 SF 11 sales Over 2,131 SF 10 sales 1980 1982 1984 1984 1983 1983 1984 Year built: median (dot) and middle half (bar)

The median is 1984 for homes over 2,131 SF and 1984 for homes under 1,698 SF. It does not move in a straight line; homes under 1,698 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-07T07:48:00.539654 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,698 SF 10 sales 1,698– 1,769 SF 11 sales 1,775– 2,131 SF 11 sales Over 2,131 SF 10 sales 0 25 50 75 46 47 26 68 Days on market, median

The median is 68 days for homes over 2,131 SF and 46 days for homes under 1,698 SF. It does not move in a straight line; homes over 2,131 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-07T07:48:00.564356 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,698 SF 10 sales 1,698– 1,769 SF 11 sales 1,775– 2,131 SF 11 sales Over 2,131 SF 10 sales 0.0% 2.5% 5.0% 7.5% 6.5% 6.7% 4.7% 7.9% Discount from original list, average

The average is 7.9% for homes over 2,131 SF and 6.5% for homes under 1,698 SF. It does not move in a straight line; homes over 2,131 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

2026-11-07T07:48:00.593565 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% 40 50 10 64 64 9 18 64 36 50 70 40 Under 1,698 SF 1,698–1,769 SF 1,775–2,131 SF Over 2,131 SF

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

  • 50% of homes over 2,131 SF had a price cut before sale, against 40% of homes under 1,698 SF. Defined in 8.1.7.
  • 70% of homes over 2,131 SF had the seller pay closing costs or repairs, against 50% of homes under 1,698 SF. Defined in 8.1.8.
  • 40% of homes over 2,131 SF have a view, against 10% of homes under 1,698 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 1,698 SF10 sales1,698–1,769 SF11 sales1,775–2,131 SF11 salesOver 2,131 SF10 salesAll42 salesReal difference?
Net sale price average$440,542$479,727$564,379$540,253$506,979unclear
Net price per SF average$280$276$289$229$269unclear
Living area average1,5731,7361,9522,3621,903by design
Year built median19841983198319841983unclear

4.10 The numbers: selling

Under 1,698 SF10 sales1,698–1,769 SF11 sales1,775–2,131 SF11 salesOver 2,131 SF10 salesAll42 salesReal difference?
Days on market median4647266840unclear
Discount from original list average6.5%6.7%4.7%7.9%6.4%unclear
Price cut before sale40%64%18%50%43%unclear
Seller paid closing costs or repairs50%64%64%70%62%unclear
Has a view10%9%36%40%24%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 · 42 sales · November 7, 2025 – November 6, 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.

2026-11-07T07:48:00.618249 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 17 5 12 42 sales Sales per group Before 1979: 8 sales (19%) 1979–1983: 17 sales (40%) 1984: 5 sales (12%) After 1984: 12 sales (29%)
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 19791979–19831984After 1984Real difference?
Net sale price$474K$514K$521K$513Kunclear
Net price per SF$268 per SF$283 per SF$239 per SF$263 per SFunclear
Living area1,786 SF1,818 SF2,196 SF1,979 SFunclear
Days on market58 days46 days136 days13 daysunclear
Discount from original list8.1%6.4%7.7%4.8%unclear
Price cut before sale38%47%60%33%unclear
Seller paid closing costs or repairs50%65%80%58%unclear
Has a view38%6%40%33%unclear

5.3 Net sale price: no clear difference

2026-11-07T07:48:00.640986 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 8 sales 1979– 1983 17 sales 1984 5 sales After 1984 12 sales $0K $200K $400K $600K $474K $514K $521K $513K Net sale price, average

The average is $513K for homes built after 1984 and $474K for homes built before 1979. It does not move in a straight line; homes built 1984 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-07T07:48:00.665194 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 8 sales 1979– 1983 17 sales 1984 5 sales After 1984 12 sales $0 $100 $200 $300 $268 $283 $239 $263 Net price per SF, average

The average is $263 per SF for homes built after 1984 and $268 per SF for homes built before 1979. It does not move in a straight line; homes built 1979–1983 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-07T07:48:00.691366 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 8 sales 1979– 1983 17 sales 1984 5 sales After 1984 12 sales 0 1,000 2,000 1,786 1,818 2,196 1,979 Living area (SF), average

The average is 1,979 SF for homes built after 1984 and 1,786 SF for homes built before 1979. It does not move in a straight line; homes built 1984 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-07T07:48:00.714473 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 8 sales 1979– 1983 17 sales 1984 5 sales After 1984 12 sales 0 50 100 150 58 46 136 13 Days on market, median

The median is 13 days for homes built after 1984 and 58 days for homes built before 1979. It does not move in a straight line; homes built 1984 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-07T07:48:00.740426 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 8 sales 1979– 1983 17 sales 1984 5 sales After 1984 12 sales 0.0% 2.5% 5.0% 7.5% 8.1% 6.4% 7.7% 4.8% Discount from original list, average

The average is 4.8% for homes built after 1984 and 8.1% for homes built before 1979. It does not move in a straight line; homes built before 1979 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

2026-11-07T07:48:00.768995 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 38 50 38 47 65 6 60 80 40 33 58 33 Before 1979 1979–1983 1984 After 1984

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

  • 33% of homes built after 1984 had a price cut before sale, against 38% of homes built before 1979. Defined in 8.1.7.
  • 58% of homes built after 1984 had the seller pay closing costs or repairs, against 50% of homes built before 1979. Defined in 8.1.8.
  • 33% of homes built after 1984 have a view, against 38% of homes built before 1979. 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 19798 sales1979–198317 sales19845 salesAfter 198412 salesAll42 salesReal difference?
Net sale price average$473,944$514,292$521,005$512,797$506,979unclear
Net price per SF average$268$283$239$263$269unclear
Living area average1,7861,8182,1961,9791,903unclear
Year built median19781983198419851983by design

5.10 The numbers: selling

Before 19798 sales1979–198317 sales19845 salesAfter 198412 salesAll42 salesReal difference?
Days on market median58461361340unclear
Discount from original list average8.1%6.4%7.7%4.8%6.4%unclear
Price cut before sale38%47%60%33%43%unclear
Seller paid closing costs or repairs50%65%80%58%62%unclear
Has a view38%6%40%33%24%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 · 42 sales · November 7, 2025 – November 6, 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.

2026-11-07T07:48:00.789653 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 32 42 sales Sales per group View: 10 sales (24%) No view: 32 sales (76%)
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$578K$485Kunclear
Net price per SF$285 per SF$264 per SFunclear
Living area2,034 SF1,862 SFunclear
Year built19841983unclear
Days on market57 days40 daysunclear
Discount from original list5.5%6.7%unclear
Price cut before sale40%44%unclear
Seller paid closing costs or repairs60%62%unclear

6.3 Net sale price: no clear difference

2026-11-07T07:48:00.809720 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 32 sales $0K $200K $400K $600K $578K $485K Net sale price, average

The average is $578K for homes with a view and $485K 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

2026-11-07T07:48:00.829191 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 32 sales $0 $100 $200 $300 $285 $264 Net price per SF, average

The average is $285 per SF for homes with a view and $264 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

2026-11-07T07:48:00.849608 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 32 sales 0 500 1,000 1,500 2,000 2,034 1,862 Living area (SF), average

The average is 2,034 SF for homes with a view and 1,862 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-07T07:48:00.964098 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 32 sales 1978 1980 1982 1984 1984 1983 Year built: median (dot) and middle half (bar)

The median is 1984 for homes with a view and 1983 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-07T07:48:00.984650 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 32 sales 0 20 40 60 57 40 Days on market, median

The median is 57 days for homes with a view and 40 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

2026-11-07T07:48:01.005381 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 32 sales 0.0% 2.0% 4.0% 6.0% 8.0% 5.5% 6.7% Discount from original list, average

The average is 5.5% for homes with a view and 6.7% 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

2026-11-07T07:48:01.027956 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 40 60 44 62 View No view

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

  • 40% of homes with a view had a price cut before sale, against 44% of homes without a view. Defined in 8.1.7.
  • 60% of homes with a view had the seller pay closing costs or repairs, against 62% 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

View10 salesNo view32 salesAll42 salesReal difference?
Net sale price average$578,158$484,735$506,979unclear
Net price per SF average$285$264$269unclear
Living area average2,0341,8621,903unclear
Year built median198419831983unclear

6.11 The numbers: selling

View10 salesNo view32 salesAll42 salesReal difference?
Days on market median574040unclear
Discount from original list average5.5%6.7%6.4%unclear
Price cut before sale40%44%43%unclear
Seller paid closing costs or repairs60%62%62%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 · 0 sales · November 7, 2025 – November 6, 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 Gracywoods Sec 09 & 10.

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
42 resale sales. Average $506,979; median $508,434; standard deviation $101,728; middle half (25th–75th percentile) $442,000–$561,550; lowest $355,000, highest $782,999. 26 sales had a seller payment; their median payment was $7,750.

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
42 resale sales. Average $269; median $266; standard deviation $48; middle half (25th–75th percentile) $228–$306; lowest $164, highest $357.

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
42 resale sales. Average 1,903; median 1,772; standard deviation 320; middle half (25th–75th percentile) 1,702–2,131; lowest 1,362, highest 2,695.

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
42 resale sales. Average 1982; median 1983; standard deviation 3; middle half (25th–75th percentile) 1979–1985; lowest 1976, highest 1993.

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
42 resale sales. Average 66; median 40; standard deviation 67; middle half (25th–75th percentile) 10–106; lowest 0, highest 279. 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
42 resale sales. Average 6.4%; median 4.5%; standard deviation 6.7%; middle half (25th–75th percentile) 1.7%–9.2%; lowest −7.1%, highest 21.1%. 3 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
18 of 42 resale sales (42.9%).

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
26 of 42 resale sales (61.9%).

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
10 sales with a view, 32 without, 0 unclassified. Most common View entries: None 22, Neighborhood 15, Trees/Woods 8, Park/Greenbelt 4, Garden 1, Pool 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 2026-11-07 13:45 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “gracywoods”, “village at walnut creek” (case-insensitive). A record is kept when its subdivision name belongs to the Gracywoods Sec 09 & 10 family, the same rule comparable sales use (it includes Village At Walnut Creek Ph 1, proven adjacent and priced alike).
The data
Pulled November 7, 2026: 43 closed Gracywoods Sec 09 & 10 records over the prior year, in ZIP 78758. 13 subdivision spellings kept, the most common: Gracywoods (6); Gracywoods Sec 08 (5); Gracywoods Sec 09 & 10 (4); Gracywoods Sec 06-B (4); Gracywoods Sec 01 (4); Village At Walnut Creek Ph 1 (4); Gracywoods Sec 02 (4); Gracywoods Sec 03 (3); Gracywoods Sec 04 (3); Gracywoods Sec 06-A (3); Gracywoods Pud Sec 02 (1); Gracywoods Sec 05 (1); and 1 more (1 records). Names found by the search but not part of Gracywoods Sec 09 & 10, left out: Enclave At Gracywoods (2); The Enclave at Gracywoods (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 21 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 7, 2025 to November 6, 2026 inclusive.
The data
42 single-family sales in the window: 42 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
42 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
1 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 $441K”.
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 $441K: $355,000–$435,000 (10 sales); $441K–$504K: $441,000–$503,867 (11 sales); $513K–$562K: $513,000–$561,900 (11 sales); Over $562K: $585,900–$782,999 (10 sales)
Quartiles by living area: Under 1,698 SF: 1,362–1,678 SF (10 sales); 1,698–1,769 SF: 1,698–1,769 SF (11 sales); 1,775–2,131 SF: 1,775–2,131 SF (11 sales); Over 2,131 SF: 2,184–2,695 SF (10 sales)
Quartiles by year built: Before 1979: 1976–1978 (8 sales); 1979–1983: 1979–1983 (17 sales); 1984: 1984–1984 (5 sales); After 1984: 1985–1993 (12 sales)
View and no view: View: MLS lists a view (10 sales); No view: None or Neighborhood (32 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 $506,979, median $508,434. Days on market: average 66, median 40: 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
1 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 = 18.7030.0003p < 0.0063Yesε² = 0.456large
Living areaKruskal–WallisH = 9.0830.0282p < 0.0063Unclearε² = 0.222large
Year builtKruskal–WallisH = 1.7330.6301p < 0.0063Unclearε² = 0.042small
Days on marketKruskal–WallisH = 2.6830.4431p < 0.0063Unclearε² = 0.065medium
Discount from original listKruskal–WallisH = 4.1930.2417p < 0.0063Unclearε² = 0.102medium
Price cut before saleChi-squareχ² = 4.3230.2287p < 0.0063UnclearCramér’s V = 0.321medium
Seller paid closing costs or repairsChi-squareχ² = 4.4130.2200p < 0.0063UnclearCramér’s V = 0.324medium
Has a viewChi-squareχ² = 9.7830.0206p < 0.0063UnclearCramér’s V = 0.482medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 9.4530.0239p < 0.0063Unclearε² = 0.230large
Net price per SFKruskal–WallisH = 7.7130.0524p < 0.0063Unclearε² = 0.188large
Year builtKruskal–WallisH = 4.7830.1890p < 0.0063Unclearε² = 0.116medium
Days on marketKruskal–WallisH = 0.8230.8441p < 0.0063Unclearε² = 0.020small
Discount from original listKruskal–WallisH = 2.0230.5675p < 0.0063Unclearε² = 0.049small
Price cut before saleChi-squareχ² = 4.9230.1781p < 0.0063UnclearCramér’s V = 0.342medium
Seller paid closing costs or repairsChi-squareχ² = 0.9130.8238p < 0.0063UnclearCramér’s V = 0.147small
Has a viewChi-squareχ² = 4.7730.1898p < 0.0063UnclearCramér’s V = 0.337medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 0.9030.8252p < 0.0063Unclearε² = 0.022small
Net price per SFKruskal–WallisH = 3.4730.3250p < 0.0063Unclearε² = 0.085medium
Living areaKruskal–WallisH = 6.0630.1089p < 0.0063Unclearε² = 0.148large
Days on marketKruskal–WallisH = 5.2830.1526p < 0.0063Unclearε² = 0.129medium
Discount from original listKruskal–WallisH = 1.3130.7271p < 0.0063Unclearε² = 0.032small
Price cut before saleChi-squareχ² = 1.2630.7385p < 0.0063UnclearCramér’s V = 0.173small
Seller paid closing costs or repairsChi-squareχ² = 1.3030.7300p < 0.0063UnclearCramér’s V = 0.176small
Has a viewChi-squareχ² = 5.1630.1604p < 0.0063UnclearCramér’s V = 0.351medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 232.00—0.0347p < 0.0063Unclearrank-biserial r = 0.450medium
Net price per SFMann–Whitney UU = 206.00—0.1791p < 0.0063Unclearrank-biserial r = 0.288small
Living areaMann–Whitney UU = 220.00—0.0789p < 0.0063Unclearrank-biserial r = 0.375medium
Year builtMann–Whitney UU = 171.00—0.7533p < 0.0063Unclearrank-biserial r = 0.069negligible
Days on marketMann–Whitney UU = 190.50—0.3755p < 0.0063Unclearrank-biserial r = 0.191small
Discount from original listMann–Whitney UU = 150.00—0.7790p < 0.0063Unclearrank-biserial r = 0.062negligible
Price cut before saleChi-squareχ² = 0.0410.8343p < 0.0063UnclearCramér’s V = 0.032negligible
Seller paid closing costs or repairsChi-squareχ² = 0.0210.8870p < 0.0063UnclearCramér’s V = 0.022negligible

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 1 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 42 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 7, 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.