ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Spicewood At Balcones Villages

Austin, TX 78750
Resale homes · closed Oct 31 – Oct 30, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 31, 2026 · 7:31 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
47
single-family resale homes
Median net sale price
$986,000
average $983,531
Median net price per SF
$358
average $358
Median days on market
17 days
average 34 days
1. SummaryResale homes · 47 sales · October 31, 2025 – October 30, 2026

This study looks at the 47 resale homes sold in Spicewood At Balcones Villages in the 365 days to October 30, 2026. A full year is used because only 29 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 sold47 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 $840K · 12 sales$840K–$986K · 12 sales$988K–$1.13M · 11 salesOver $1.13M · 12 sales
3. Quartiles by net sale priceResale homes · 47 sales · October 31, 2025 – October 30, 2026

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

2026-10-31T07:31:22.940386 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 12 11 12 47 sales Sales per group Under $840K: 12 sales (26%) $840K–$986K: 12 sales (26%) $988K–$1.13M: 11 sales (23%) Over $1.13M: 12 sales (26%)
Bottom line

3.1 Key differences

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

Under $840K$840K–$986K$988K–$1.13MOver $1.13M
Higher-priced homes Over $1.13M
  • Are much larger.
  • Tend to be newer.
  • Sell for more per square foot.
Lower-priced homes Under $840K
  • Are much smaller.
  • Tend to be older.
  • 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 $840K$840K–$986K$988K–$1.13MOver $1.13MReal difference?
Net price per SF$311 per SFLowest$362 per SF$401 per SFHighest$359 per SF✓ large
Living area2,332 SFSmallest2,540 SF2,696 SF3,544 SFLargest✓ large
Year built1976Oldest197719761982Newest✓ large
Days on market18 days20 days10 days32 daysunclear
Discount from original list5.1%4.2%1.6%5.2%unclear
Price cut before sale33%42%9%50%unclear
Seller paid closing costs or repairs50%58%64%50%unclear
Has a view25%50%82%50%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 $1.13M sell for about $48 per SF (15%) more than homes under $840K

2026-10-31T07:31:22.969119 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $840K 12 sales $840K– $986K 12 sales $988K– $1.13M 11 sales Over $1.13M 12 sales $0 $200 $400 $311 $362 $401 $359 Net price per SF, average

The average is $359 per SF for homes over $1.13M and $311 per SF for homes under $840K. It does not move in a straight line; homes $988K–$1.13M are highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $1.13M are about 1,210 SF (52%) larger than homes under $840K

2026-10-31T07:31:22.991531 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $840K 12 sales $840K– $986K 12 sales $988K– $1.13M 11 sales Over $1.13M 12 sales 0 2,000 4,000 2,332 2,540 2,696 3,544 Living area (SF), average

The average is 3,544 SF for homes over $1.13M and 2,332 SF for homes under $840K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Homes over $1.13M are about 6 years newer than homes under $840K

2026-10-31T07:31:23.016350 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $840K 12 sales $840K– $986K 12 sales $988K– $1.13M 11 sales Over $1.13M 12 sales 1972 1975 1978 1981 1984 1976 1977 1976 1982 Year built: median (dot) and middle half (bar)

The median is 1982 for homes over $1.13M and 1976 for homes under $840K. It does not move in a straight line; homes over $1.13M are highest. Defined in 8.1.4.

✓ Real difference · large

3.6 Days on market: no clear difference

2026-10-31T07:31:23.039352 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $840K 12 sales $840K– $986K 12 sales $988K– $1.13M 11 sales Over $1.13M 12 sales 0 10 20 30 18 20 10 32 Days on market, median

The median is 32 days for homes over $1.13M and 18 days for homes under $840K. It does not move in a straight line; homes over $1.13M are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-31T07:31:23.061426 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $840K 12 sales $840K– $986K 12 sales $988K– $1.13M 11 sales Over $1.13M 12 sales 0.0% 2.0% 4.0% 6.0% 5.1% 4.2% 1.6% 5.2% Discount from original list, average

The average is 5.2% for homes over $1.13M and 5.1% for homes under $840K. It does not move in a straight line; homes over $1.13M 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

2026-10-31T07:31:23.091310 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 33 50 25 42 58 50 9 64 82 50 50 50 Under $840K $840K–$986K $988K–$1.13M Over $1.13M

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

  • 50% of homes over $1.13M had a price cut before sale, against 33% of homes under $840K. Defined in 8.1.7.
  • 50% of homes over $1.13M had the seller pay closing costs or repairs, against 50% of homes under $840K. Defined in 8.1.8.
  • 50% of homes over $1.13M have a view, against 25% of homes under $840K. 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 $840K12 sales$840K–$986K12 sales$988K–$1.13M11 salesOver $1.13M12 salesAll47 salesReal difference?
Net sale price average$709,831$909,655$1,064,219$1,257,142$983,531by design
Net price per SF average$311$362$401$359$358✓ large
Living area average2,3322,5402,6963,5442,780✓ large
Year built median19761977197619821976✓ large

3.10 The numbers: selling

Under $840K12 sales$840K–$986K12 sales$988K–$1.13M11 salesOver $1.13M12 salesAll47 salesReal difference?
Days on market median1820103217unclear
Discount from original list average5.1%4.2%1.6%5.2%4.1%unclear
Price cut before sale33%42%9%50%34%unclear
Seller paid closing costs or repairs50%58%64%50%55%unclear
Has a view25%50%82%50%51%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 · 47 sales · October 31, 2025 – October 30, 2026

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

2026-10-31T07:31:23.111983 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 12 11 12 47 sales Sales per group Under 2,403 SF: 12 sales (26%) 2,403–2,627 SF: 12 sales (26%) 2,643–3,068 SF: 11 sales (23%) Over 3,068 SF: 12 sales (26%)
Bottom line

4.1 Key differences

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

Under 2,403 SF2,403–2,627 SF2,643–3,068 SFOver 3,068 SF
Larger homes Over 3,068 SF
  • Sell for much more.
Smaller homes Under 2,403 SF
  • Sell for much less.

4.2 At a glance

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

Under 2,403 SF2,403–2,627 SF2,643–3,068 SFOver 3,068 SFReal difference?
Net sale price$814KLowest$924K$988K$1.21MHighest✓ large
Net price per SF$379 per SF$369 per SF$352 per SF$330 per SFunclear
Year built1976197619761980unclear
Days on market12 days20 days17 days32 daysunclear
Discount from original list3.4%4.5%3.3%5.0%unclear
Price cut before sale25%50%27%33%unclear
Seller paid closing costs or repairs58%58%55%50%unclear
Has a view50%50%64%42%unclear

4.3 Homes over 3,068 SF sell for about $394K (48%) more than homes under 2,403 SF

2026-10-31T07:31:23.132797 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,403 SF 12 sales 2,403– 2,627 SF 12 sales 2,643– 3,068 SF 11 sales Over 3,068 SF 12 sales $0K $500K $1.00M $814K $924K $988K $1.21M Net sale price, average

The average is $1.21M for homes over 3,068 SF and $814K for homes under 2,403 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

2026-10-31T07:31:23.155004 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,403 SF 12 sales 2,403– 2,627 SF 12 sales 2,643– 3,068 SF 11 sales Over 3,068 SF 12 sales $0 $200 $400 $379 $369 $352 $330 Net price per SF, average

The average is $330 per SF for homes over 3,068 SF and $379 per SF for homes under 2,403 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 Year built: no clear difference

2026-10-31T07:31:23.178868 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,403 SF 12 sales 2,403– 2,627 SF 12 sales 2,643– 3,068 SF 11 sales Over 3,068 SF 12 sales 1972 1975 1978 1981 1984 1976 1976 1976 1980 Year built: median (dot) and middle half (bar)

The median is 1980 for homes over 3,068 SF and 1976 for homes under 2,403 SF. It does not move in a straight line; homes over 3,068 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-31T07:31:23.201472 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,403 SF 12 sales 2,403– 2,627 SF 12 sales 2,643– 3,068 SF 11 sales Over 3,068 SF 12 sales 0 10 20 30 12 20 17 32 Days on market, median

The median is 32 days for homes over 3,068 SF and 12 days for homes under 2,403 SF. It does not move in a straight line; homes over 3,068 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-31T07:31:23.223730 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,403 SF 12 sales 2,403– 2,627 SF 12 sales 2,643– 3,068 SF 11 sales Over 3,068 SF 12 sales 0.0% 2.0% 4.0% 6.0% 3.4% 4.5% 3.3% 5.0% Discount from original list, average

The average is 5.0% for homes over 3,068 SF and 3.4% for homes under 2,403 SF. It does not move in a straight line; homes over 3,068 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

2026-10-31T07:31:23.250204 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% 25 58 50 50 58 50 27 55 64 33 50 42 Under 2,403 SF 2,403–2,627 SF 2,643–3,068 SF Over 3,068 SF

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

  • 33% of homes over 3,068 SF had a price cut before sale, against 25% of homes under 2,403 SF. Defined in 8.1.7.
  • 50% of homes over 3,068 SF had the seller pay closing costs or repairs, against 58% of homes under 2,403 SF. Defined in 8.1.8.
  • 42% of homes over 3,068 SF have a view, against 50% of homes under 2,403 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 2,403 SF12 sales2,403–2,627 SF12 sales2,643–3,068 SF11 salesOver 3,068 SF12 salesAll47 salesReal difference?
Net sale price average$814,287$923,697$988,426$1,208,121$983,531✓ large
Net price per SF average$379$369$352$330$358unclear
Living area average2,1482,5032,8063,6642,780by design
Year built median19761976197619801976unclear

4.10 The numbers: selling

Under 2,403 SF12 sales2,403–2,627 SF12 sales2,643–3,068 SF11 salesOver 3,068 SF12 salesAll47 salesReal difference?
Days on market median1220173217unclear
Discount from original list average3.4%4.5%3.3%5.0%4.1%unclear
Price cut before sale25%50%27%33%34%unclear
Seller paid closing costs or repairs58%58%55%50%55%unclear
Has a view50%50%64%42%51%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 · 47 sales · October 31, 2025 – October 30, 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.

2026-10-31T07:31:23.270706 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 15 9 11 47 sales Sales per group Before 1975: 12 sales (26%) 1975–1976: 15 sales (32%) 1977–1978: 9 sales (19%) After 1978: 11 sales (23%)
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 19751975–19761977–1978After 1978Real difference?
Net sale price$905K$966K$980K$1.10Munclear
Net price per SF$347 per SF$367 per SF$377 per SF$340 per SFunclear
Living area2,654 SF2,650 SF2,606 SF3,236 SFunclear
Days on market14 days19 days22 days25 daysunclear
Discount from original list4.8%3.8%4.0%3.7%unclear
Price cut before sale33%33%33%36%unclear
Seller paid closing costs or repairs42%53%78%55%unclear
Has a view67%67%44%18%unclear

5.3 Net sale price: no clear difference

2026-10-31T07:31:23.291591 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1975 12 sales 1975– 1976 15 sales 1977– 1978 9 sales After 1978 11 sales $0K $500K $1.00M $905K $966K $980K $1.10M Net sale price, average

The average is $1.10M for homes built after 1978 and $905K for homes built before 1975. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-31T07:31:23.313997 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1975 12 sales 1975– 1976 15 sales 1977– 1978 9 sales After 1978 11 sales $0 $200 $400 $347 $367 $377 $340 Net price per SF, average

The average is $340 per SF for homes built after 1978 and $347 per SF for homes built before 1975. It does not move in a straight line; homes built 1977–1978 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-31T07:31:23.335361 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1975 12 sales 1975– 1976 15 sales 1977– 1978 9 sales After 1978 11 sales 0 1,000 2,000 3,000 2,654 2,650 2,606 3,236 Living area (SF), average

The average is 3,236 SF for homes built after 1978 and 2,654 SF for homes built before 1975. It does not move in a straight line; homes built after 1978 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-31T07:31:23.358513 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1975 12 sales 1975– 1976 15 sales 1977– 1978 9 sales After 1978 11 sales 0 10 20 30 14 19 22 25 Days on market, median

The median is 25 days for homes built after 1978 and 14 days for homes built before 1975. 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

2026-10-31T07:31:23.382665 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1975 12 sales 1975– 1976 15 sales 1977– 1978 9 sales After 1978 11 sales 0.0% 2.0% 4.0% 4.8% 3.8% 4.0% 3.7% Discount from original list, average

The average is 3.7% for homes built after 1978 and 4.8% for homes built before 1975. It does not move in a straight line; homes built before 1975 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

2026-10-31T07:31:23.408353 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 33 42 67 33 53 67 33 78 44 36 55 18 Before 1975 1975–1976 1977–1978 After 1978

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

  • 36% of homes built after 1978 had a price cut before sale, against 33% of homes built before 1975. Defined in 8.1.7.
  • 55% of homes built after 1978 had the seller pay closing costs or repairs, against 42% of homes built before 1975. Defined in 8.1.8.
  • 18% of homes built after 1978 have a view, against 67% of homes built before 1975. 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 197512 sales1975–197615 sales1977–19789 salesAfter 197811 salesAll47 salesReal difference?
Net sale price average$904,952$965,612$980,102$1,096,492$983,531unclear
Net price per SF average$347$367$377$340$358unclear
Living area average2,6542,6502,6063,2362,780unclear
Year built median19721976197819831976by design

5.10 The numbers: selling

Before 197512 sales1975–197615 sales1977–19789 salesAfter 197811 salesAll47 salesReal difference?
Days on market median1419222517unclear
Discount from original list average4.8%3.8%4.0%3.7%4.1%unclear
Price cut before sale33%33%33%36%34%unclear
Seller paid closing costs or repairs42%53%78%55%55%unclear
Has a view67%67%44%18%51%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 · 47 sales · October 31, 2025 – October 30, 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.

2026-10-31T07:31:23.426387 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 24 23 47 sales Sales per group View: 24 sales (51%) No view: 23 sales (49%)
Bottom line: no measure differs enough between the groups to rule out chance.

6.1 Key differences

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

6.2 At a glance

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

ViewNo viewReal difference?
Net sale price$1.00M$965Kunclear
Net price per SF$369 per SF$346 per SFunclear
Living area2,765 SF2,796 SFunclear
Year built19761978unclear
Days on market26 days9 daysunclear
Discount from original list5.5%2.6%unclear
Price cut before sale42%26%unclear
Seller paid closing costs or repairs58%52%unclear

6.3 Net sale price: no clear difference

2026-10-31T07:31:23.443175 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 23 sales $0K $250K $500K $750K $1.00M $1.00M $965K Net sale price, average

The average is $1.00M for homes with a view and $965K 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

2026-10-31T07:31:23.462330 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 23 sales $0 $100 $200 $300 $400 $369 $346 Net price per SF, average

The average is $369 per SF for homes with a view and $346 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

2026-10-31T07:31:23.503203 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 23 sales 0 1,000 2,000 3,000 2,765 2,796 Living area (SF), average

The average is 2,765 SF for homes with a view and 2,796 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-31T07:31:23.523222 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 23 sales 1972 1974 1976 1978 1980 1976 1978 Year built: median (dot) and middle half (bar)

The median is 1976 for homes with a view and 1978 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-31T07:31:23.540716 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 23 sales 0 10 20 30 26 9 Days on market, median

The median is 26 days for homes with a view and 9 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-10-31T07:31:23.558632 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 23 sales 0.0% 2.0% 4.0% 6.0% 5.5% 2.6% Discount from original list, average

The average is 5.5% for homes with a view and 2.6% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-31T07:31:23.576886 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 42 58 26 52 View No view

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

  • 42% of homes with a view had a price cut before sale, against 26% of homes without a view. Defined in 8.1.7.
  • 58% of homes with a view had the seller pay closing costs or repairs, against 52% 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

View24 salesNo view23 salesAll47 salesReal difference?
Net sale price average$1,001,075$965,223$983,531unclear
Net price per SF average$369$346$358unclear
Living area average2,7652,7962,780unclear
Year built median197619781976unclear

6.11 The numbers: selling

View24 salesNo view23 salesAll47 salesReal difference?
Days on market median26917unclear
Discount from original list average5.5%2.6%4.1%unclear
Price cut before sale42%26%34%unclear
Seller paid closing costs or repairs58%52%55%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 · October 31, 2025 – October 30, 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 Spicewood At Balcones Villages.

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
47 resale sales. Average $983,531; median $986,000; standard deviation $223,845; middle half (25th–75th percentile) $833,200–$1,129,000; lowest $590,000, highest $1,568,000. 26 sales had a seller payment; their median payment was $6,059.

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
47 resale sales. Average $358; median $358; standard deviation $57; middle half (25th–75th percentile) $313–$400; lowest $253, highest $449.

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
47 resale sales. Average 2,780; median 2,627; standard deviation 612; middle half (25th–75th percentile) 2,398–3,083; lowest 1,732, highest 4,179.

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
47 resale sales. Average 1978; median 1976; standard deviation 9; middle half (25th–75th percentile) 1974–1978; lowest 1970, 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
47 resale sales. Average 34; median 17; standard deviation 44; middle half (25th–75th percentile) 5–34; lowest 1, highest 240. 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
47 resale sales. Average 4.1%; median 2.3%; standard deviation 6.8%; middle half (25th–75th percentile) 0.2%–7.5%; lowest −12.8%, highest 22.7%. 9 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 47 resale sales (34.0%).

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
26 of 47 resale sales (55.3%).

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
24 sales with a view, 23 without, 0 unclassified. Most common View entries: None 20, Golf Course 13, Neighborhood 9, Trees/Woods 6, Pool 5, Garden 3, Park/Greenbelt 3, See Remarks 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
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “spicewood at balcones villages”, “balcones village”, “spicewood at balcones village”, “spicewood at balcones villag”, “balcones vlg” (case-insensitive). A record is kept when its subdivision name belongs to the Spicewood At Balcones Villages family, the same rule comparable sales use (it includes Balcones Village, proven adjacent and priced alike).
The data
Pulled October 31, 2026: 48 closed Spicewood At Balcones Villages records over the prior year, in ZIP 78750. 13 subdivision spellings kept, the most common: Spicewood At Balcones Villages (25); Balcones Village Sec 08 (4); Balcones Village (3); Balcones Village Sec 03 Ph C (3); Balcones Village Sec 06 (2); Balcones Village Sec 05 Ph A (2); Balcones Village Sec 04 (2); Balcones Village Sec 09 (2); Balcones Village Sec 01-B (1); Spicewood At Balcones Village (1); Balcones Village Sec 03 Ph A (1); Balcones Village Sec 10 (1); and 1 more (1 records). No other names were found by the search.

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 29 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 31, 2025 to October 30, 2026 inclusive.
The data
47 single-family sales in the window: 47 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
47 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) with no original list price

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $840K”.
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 $840K: $590,000–$826,400 (12 sales); $840K–$986K: $840,000–$986,000 (12 sales); $988K–$1.13M: $987,852–$1,127,999 (11 sales); Over $1.13M: $1,130,000–$1,568,000 (12 sales)
Quartiles by living area: Under 2,403 SF: 1,732–2,392 SF (12 sales); 2,403–2,627 SF: 2,403–2,627 SF (12 sales); 2,643–3,068 SF: 2,643–3,068 SF (11 sales); Over 3,068 SF: 3,098–4,179 SF (12 sales)
Quartiles by year built: Before 1975: 1970–1974 (12 sales); 1975–1976: 1975–1976 (15 sales); 1977–1978: 1977–1978 (9 sales); After 1978: 1980–2023 (11 sales)
View and no view: View: MLS lists a view (24 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 $983,531, median $986,000. Days on market: average 34, median 17: 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
4 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 = 15.0730.0018p < 0.0063Yesε² = 0.328large
Living areaKruskal–WallisH = 22.843< 0.0001p < 0.0063Yesε² = 0.497large
Year builtKruskal–WallisH = 15.2630.0016p < 0.0063Yesε² = 0.332large
Days on marketKruskal–WallisH = 4.0830.2532p < 0.0063Unclearε² = 0.089medium
Discount from original listKruskal–WallisH = 2.3130.5108p < 0.0063Unclearε² = 0.050small
Price cut before saleChi-squareχ² = 4.7230.1931p < 0.0063UnclearCramér’s V = 0.317medium
Seller paid closing costs or repairsChi-squareχ² = 0.6330.8903p < 0.0063UnclearCramér’s V = 0.115small
Has a viewChi-squareχ² = 7.4430.0592p < 0.0063UnclearCramér’s V = 0.398medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 19.9830.0002p < 0.0063Yesε² = 0.434large
Net price per SFKruskal–WallisH = 4.5530.2076p < 0.0063Unclearε² = 0.099medium
Year builtKruskal–WallisH = 4.8630.1822p < 0.0063Unclearε² = 0.106medium
Days on marketKruskal–WallisH = 0.4530.9290p < 0.0063Unclearε² = 0.010negligible
Discount from original listKruskal–WallisH = 1.0530.7894p < 0.0063Unclearε² = 0.023small
Price cut before saleChi-squareχ² = 2.0330.5672p < 0.0063UnclearCramér’s V = 0.208small
Seller paid closing costs or repairsChi-squareχ² = 0.2330.9729p < 0.0063UnclearCramér’s V = 0.070negligible
Has a viewChi-squareχ² = 1.1330.7697p < 0.0063UnclearCramér’s V = 0.155small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 4.9030.1790p < 0.0063Unclearε² = 0.107medium
Net price per SFKruskal–WallisH = 2.8130.4224p < 0.0063Unclearε² = 0.061medium
Living areaKruskal–WallisH = 4.5130.2117p < 0.0063Unclearε² = 0.098medium
Days on marketKruskal–WallisH = 0.3830.9441p < 0.0063Unclearε² = 0.008negligible
Discount from original listKruskal–WallisH = 0.1430.9871p < 0.0063Unclearε² = 0.003negligible
Price cut before saleChi-squareχ² = 0.0330.9983p < 0.0063UnclearCramér’s V = 0.027negligible
Seller paid closing costs or repairsChi-squareχ² = 2.7730.4288p < 0.0063UnclearCramér’s V = 0.243small
Has a viewChi-squareχ² = 7.5530.0563p < 0.0063UnclearCramér’s V = 0.401medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 325.00—0.3020p < 0.0063Unclearrank-biserial r = 0.178small
Net price per SFMann–Whitney UU = 347.00—0.1335p < 0.0063Unclearrank-biserial r = 0.257small
Living areaMann–Whitney UU = 271.50—0.9322p < 0.0063Unclearrank-biserial r = 0.016negligible
Year builtMann–Whitney UU = 159.00—0.0117p < 0.0063Unclearrank-biserial r = 0.424medium
Days on marketMann–Whitney UU = 378.00—0.0306p < 0.0063Unclearrank-biserial r = 0.370medium
Discount from original listMann–Whitney UU = 312.00—0.4499p < 0.0063Unclearrank-biserial r = 0.130small
Price cut before saleChi-squareχ² = 1.2710.2598p < 0.0063UnclearCramér’s V = 0.164small
Seller paid closing costs or repairsChi-squareχ² = 0.1810.6711p < 0.0063UnclearCramér’s V = 0.062negligible

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 1 sale(s) with no original list price. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

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

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 47 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 October 31, 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.