ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Shoalmont Add Sec 04

Austin, TX 78756 · 78731
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 4:10 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
20
single-family resale homes
Median net sale price
$1,019,500
average $1,269,898
Median net price per SF
$527
average $540
Median days on market
20 days
average 48 days
1. SummaryResale homes · 20 sales · October 26, 2025 – October 25, 2026

This study looks at the 20 resale homes sold in Shoalmont Add Sec 04 in the 365 days to October 25, 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 sold20 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 $810K · 5 sales$810K–$1.02M · 5 sales$1.02M–$1.25M · 5 salesOver $1.25M · 5 sales
3. Quartiles by net sale priceResale homes · 20 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T04:10:57.601493 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 5 5 5 20 sales Sales per group Under $810K: 5 sales (25%) $810K–$1.02M: 5 sales (25%) $1.02M–$1.25M: 5 sales (25%) Over $1.25M: 5 sales (25%)
Bottom line

3.1 Key differences

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

Under $810K$810K–$1.02M$1.02M–$1.25MOver $1.25M
Higher-priced homes Over $1.25M
  • Are much larger.
Lower-priced homes Under $810K
  • Are much smaller.

3.2 At a glance

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

Under $810K$810K–$1.02M$1.02M–$1.25MOver $1.25MReal difference?
Net price per SF$546 per SF$478 per SF$487 per SF$650 per SFunclear
Living area1,206 SFSmallest1,893 SF2,390 SF3,603 SFLargest✓ large
Year built1951195219502016unclear
Days on market37 days38 days19 days14 daysunclear
Discount from original list11.8%6.3%5.1%4.0%unclear
Price cut before sale60%60%20%0%unclear
Seller paid closing costs or repairs40%60%60%80%unclear
Has a view20%20%20%40%unclear

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

3.3 Net price per SF: no clear difference

2026-10-26T04:10:57.629417 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $810K 5 sales $810K– $1.02M 5 sales $1.02M– $1.25M 5 sales Over $1.25M 5 sales $0 $200 $400 $600 $546 $478 $487 $650 Net price per SF, average

The average is $650 per SF for homes over $1.25M and $546 per SF for homes under $810K. It does not move in a straight line; homes over $1.25M are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $1.25M are about 2,400 SF (199%) larger than homes under $810K

2026-10-26T04:10:57.652031 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $810K 5 sales $810K– $1.02M 5 sales $1.02M– $1.25M 5 sales Over $1.25M 5 sales 0 2,000 4,000 1,206 1,893 2,390 3,603 Living area (SF), average

The average is 3,603 SF for homes over $1.25M and 1,206 SF for homes under $810K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-26T04:10:57.675601 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $810K 5 sales $810K– $1.02M 5 sales $1.02M– $1.25M 5 sales Over $1.25M 5 sales 1960 1980 2000 2020 1951 1952 1950 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over $1.25M and 1951 for homes under $810K. It does not move in a straight line; homes over $1.25M are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T04:10:57.697732 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $810K 5 sales $810K– $1.02M 5 sales $1.02M– $1.25M 5 sales Over $1.25M 5 sales 0 20 40 37 38 19 14 Days on market, median

The median is 14 days for homes over $1.25M and 37 days for homes under $810K. It does not move in a straight line; homes $810K–$1.02M are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T04:10:57.719179 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $810K 5 sales $810K– $1.02M 5 sales $1.02M– $1.25M 5 sales Over $1.25M 5 sales 0.0% 5.0% 10.0% 11.8% 6.3% 5.1% 4.0% Discount from original list, average

The average is 4.0% for homes over $1.25M and 11.8% for homes under $810K. 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

2026-10-26T04:10:57.748770 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% 60 40 20 60 60 20 20 60 20 0 80 40 Under $810K $810K–$1.02M $1.02M–$1.25M Over $1.25M

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

  • 0% of homes over $1.25M had a price cut before sale, against 60% of homes under $810K. Defined in 8.1.7.
  • 80% of homes over $1.25M had the seller pay closing costs or repairs, against 40% of homes under $810K. Defined in 8.1.8.
  • 40% of homes over $1.25M have a view, against 20% of homes under $810K. 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 $810K5 sales$810K–$1.02M5 sales$1.02M–$1.25M5 salesOver $1.25M5 salesAll20 salesReal difference?
Net sale price average$639,200$904,760$1,151,200$2,384,430$1,269,898by design
Net price per SF average$546$478$487$650$540unclear
Living area average1,2061,8932,3903,6032,273✓ large
Year built median19511952195020161952unclear

3.10 The numbers: selling

Under $810K5 sales$810K–$1.02M5 sales$1.02M–$1.25M5 salesOver $1.25M5 salesAll20 salesReal difference?
Days on market median3738191420unclear
Discount from original list average11.8%6.3%5.1%4.0%6.8%unclear
Price cut before sale60%60%20%0%35%unclear
Seller paid closing costs or repairs40%60%60%80%60%unclear
Has a view20%20%20%40%25%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 · 20 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T04:10:57.768690 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 5 5 5 20 sales Sales per group Under 1,760 SF: 5 sales (25%) 1,760–2,003 SF: 5 sales (25%) 2,090–2,698 SF: 5 sales (25%) Over 2,698 SF: 5 sales (25%)
Bottom line

4.1 Key differences

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

Under 1,760 SF1,760–2,003 SF2,090–2,698 SFOver 2,698 SF
Larger homes Over 2,698 SF
  • Sell for much more.
Smaller homes Under 1,760 SF
  • Sell for much less.

4.2 At a glance

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

Under 1,760 SF1,760–2,003 SF2,090–2,698 SFOver 2,698 SFReal difference?
Net sale price$657KLowest$887K$1.31M$2.22MHighest✓ large
Net price per SF$560 per SF$468 per SF$556 per SF$576 per SFunclear
Year built1952195119492012unclear
Days on market38 days19 days6 days17 daysunclear
Discount from original list10.3%7.9%3.3%5.8%unclear
Price cut before sale60%40%40%0%unclear
Seller paid closing costs or repairs40%60%80%60%unclear
Has a view0%60%0%40%unclear

4.3 Homes over 2,698 SF sell for about $1.57M (238%) more than homes under 1,760 SF

2026-10-26T04:10:57.789196 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,760 SF 5 sales 1,760– 2,003 SF 5 sales 2,090– 2,698 SF 5 sales Over 2,698 SF 5 sales $0K $1.00M $2.00M $657K $887K $1.31M $2.22M Net sale price, average

The average is $2.22M for homes over 2,698 SF and $657K for homes under 1,760 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

2026-10-26T04:10:57.810833 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,760 SF 5 sales 1,760– 2,003 SF 5 sales 2,090– 2,698 SF 5 sales Over 2,698 SF 5 sales $0 $200 $400 $600 $560 $468 $556 $576 Net price per SF, average

The average is $576 per SF for homes over 2,698 SF and $560 per SF for homes under 1,760 SF. It does not move in a straight line; homes over 2,698 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T04:10:57.833917 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,760 SF 5 sales 1,760– 2,003 SF 5 sales 2,090– 2,698 SF 5 sales Over 2,698 SF 5 sales 1960 1980 2000 2020 1952 1951 1949 2012 Year built: median (dot) and middle half (bar)

The median is 2012 for homes over 2,698 SF and 1952 for homes under 1,760 SF. It does not move in a straight line; homes over 2,698 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T04:10:57.855757 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,760 SF 5 sales 1,760– 2,003 SF 5 sales 2,090– 2,698 SF 5 sales Over 2,698 SF 5 sales 0 20 40 38 19 6 17 Days on market, median

The median is 17 days for homes over 2,698 SF and 38 days for homes under 1,760 SF. It does not move in a straight line; homes under 1,760 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T04:10:57.876966 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,760 SF 5 sales 1,760– 2,003 SF 5 sales 2,090– 2,698 SF 5 sales Over 2,698 SF 5 sales 0.0% 5.0% 10.0% 10.3% 7.9% 3.3% 5.8% Discount from original list, average

The average is 5.8% for homes over 2,698 SF and 10.3% for homes under 1,760 SF. It does not move in a straight line; homes under 1,760 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

2026-10-26T04:10:57.902508 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% 60 40 0 40 60 60 40 80 0 0 60 40 Under 1,760 SF 1,760–2,003 SF 2,090–2,698 SF Over 2,698 SF

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

  • 0% of homes over 2,698 SF had a price cut before sale, against 60% of homes under 1,760 SF. Defined in 8.1.7.
  • 60% of homes over 2,698 SF had the seller pay closing costs or repairs, against 40% of homes under 1,760 SF. Defined in 8.1.8.
  • 40% of homes over 2,698 SF have a view, against 0% of homes under 1,760 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 1,760 SF5 sales1,760–2,003 SF5 sales2,090–2,698 SF5 salesOver 2,698 SF5 salesAll20 salesReal difference?
Net sale price average$657,400$886,760$1,310,500$2,224,930$1,269,898✓ large
Net price per SF average$560$468$556$576$540unclear
Living area average1,1891,8912,3453,6682,273by design
Year built median19521951194920121952unclear

4.10 The numbers: selling

Under 1,760 SF5 sales1,760–2,003 SF5 sales2,090–2,698 SF5 salesOver 2,698 SF5 salesAll20 salesReal difference?
Days on market median381961720unclear
Discount from original list average10.3%7.9%3.3%5.8%6.8%unclear
Price cut before sale60%40%40%0%35%unclear
Seller paid closing costs or repairs40%60%80%60%60%unclear
Has a view0%60%0%40%25%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 · 20 sales · October 26, 2025 – October 25, 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.

2026-10-26T04:10:57.921899 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 5 5 5 20 sales Sales per group Before 1949: 5 sales (25%) 1949–1951: 5 sales (25%) 1952–1957: 5 sales (25%) After 1957: 5 sales (25%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

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

5.2 At a glance

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

Before 19491949–19511952–1957After 1957Real difference?
Net sale price$976K$1.02M$1.33M$1.75Munclear
Net price per SF$574 per SF$477 per SF$536 per SF$574 per SFunclear
Living area1,705 SF2,143 SF2,263 SF2,982 SFunclear
Days on market20 days19 days38 days17 daysunclear
Discount from original list5.6%7.6%9.1%4.9%unclear
Price cut before sale40%40%60%0%unclear
Seller paid closing costs or repairs40%80%60%60%unclear
Has a view0%40%40%20%unclear

5.3 Net sale price: no clear difference

2026-10-26T04:10:57.941648 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1949 5 sales 1949– 1951 5 sales 1952– 1957 5 sales After 1957 5 sales $0K $1.00M $2.00M $976K $1.02M $1.33M $1.75M Net sale price, average

The average is $1.75M for homes built after 1957 and $976K for homes built before 1949. 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

2026-10-26T04:10:57.962848 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1949 5 sales 1949– 1951 5 sales 1952– 1957 5 sales After 1957 5 sales $0 $200 $400 $600 $574 $477 $536 $574 Net price per SF, average

The average is $574 per SF for homes built after 1957 and $574 per SF for homes built before 1949. It does not move in a straight line; homes built after 1957 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T04:10:57.983337 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1949 5 sales 1949– 1951 5 sales 1952– 1957 5 sales After 1957 5 sales 0 1,000 2,000 3,000 1,705 2,143 2,263 2,982 Living area (SF), average

The average is 2,982 SF for homes built after 1957 and 1,705 SF for homes built before 1949. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T04:10:58.003853 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1949 5 sales 1949– 1951 5 sales 1952– 1957 5 sales After 1957 5 sales 0 20 40 20 19 38 17 Days on market, median

The median is 17 days for homes built after 1957 and 20 days for homes built before 1949. It does not move in a straight line; homes built 1952–1957 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T04:10:58.025141 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1949 5 sales 1949– 1951 5 sales 1952– 1957 5 sales After 1957 5 sales 0.0% 5.0% 10.0% 5.6% 7.6% 9.1% 4.9% Discount from original list, average

The average is 4.9% for homes built after 1957 and 5.6% for homes built before 1949. It does not move in a straight line; homes built 1952–1957 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

2026-10-26T04:10:58.049424 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 40 0 40 80 40 60 60 40 0 60 20 Before 1949 1949–1951 1952–1957 After 1957

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

  • 0% of homes built after 1957 had a price cut before sale, against 40% of homes built before 1949. Defined in 8.1.7.
  • 60% of homes built after 1957 had the seller pay closing costs or repairs, against 40% of homes built before 1949. Defined in 8.1.8.
  • 20% of homes built after 1957 have a view, against 0% of homes built before 1949. 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 19495 sales1949–19515 sales1952–19575 salesAfter 19575 salesAll20 salesReal difference?
Net sale price average$975,500$1,018,800$1,331,940$1,753,350$1,269,898unclear
Net price per SF average$574$477$536$574$540unclear
Living area average1,7052,1432,2632,9822,273unclear
Year built median19471950195420161952by design

5.10 The numbers: selling

Before 19495 sales1949–19515 sales1952–19575 salesAfter 19575 salesAll20 salesReal difference?
Days on market median2019381720unclear
Discount from original list average5.6%7.6%9.1%4.9%6.8%unclear
Price cut before sale40%40%60%0%35%unclear
Seller paid closing costs or repairs40%80%60%60%60%unclear
Has a view0%40%40%20%25%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 · 20 sales · October 26, 2025 – October 25, 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.

2026-10-26T04:10:58.066700 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 15 20 sales Sales per group View: 5 sales (25%) No view: 15 sales (75%)
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$1.61M$1.16Munclear
Net price per SF$525 per SF$545 per SFunclear
Living area2,822 SF2,090 SFunclear
Year built19531950unclear
Days on market37 days17 daysunclear
Discount from original list10.6%5.5%unclear
Price cut before sale40%33%unclear
Seller paid closing costs or repairs60%60%unclear

6.3 Net sale price: no clear difference

2026-10-26T04:10:58.082036 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 15 sales $0K $500K $1.00M $1.50M $1.61M $1.16M Net sale price, average

The average is $1.61M for homes with a view and $1.16M 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

2026-10-26T04:10:58.099089 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 15 sales $0 $200 $400 $600 $525 $545 Net price per SF, average

The average is $525 per SF for homes with a view and $545 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

2026-10-26T04:10:58.116916 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 15 sales 0 1,000 2,000 3,000 2,822 2,090 Living area (SF), average

The average is 2,822 SF for homes with a view and 2,090 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T04:10:58.190879 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 15 sales 1948 1951 1954 1957 1960 1953 1950 Year built: median (dot) and middle half (bar)

The median is 1953 for homes with a view and 1950 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T04:10:58.209934 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 15 sales 0 10 20 30 40 37 17 Days on market, median

The median is 37 days for homes with a view and 17 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

2026-10-26T04:10:58.228214 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 15 sales 0.0% 5.0% 10.0% 10.6% 5.5% Discount from original list, average

The average is 10.6% for homes with a view and 5.5% 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

2026-10-26T04:10:58.246171 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 40 60 33 60 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 33% 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 60% 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

View5 salesNo view15 salesAll20 salesReal difference?
Net sale price average$1,611,540$1,156,017$1,269,898unclear
Net price per SF average$525$545$540unclear
Living area average2,8222,0902,273unclear
Year built median195319501952unclear

6.11 The numbers: selling

View5 salesNo view15 salesAll20 salesReal difference?
Days on market median371720unclear
Discount from original list average10.6%5.5%6.8%unclear
Price cut before sale40%33%35%unclear
Seller paid closing costs or repairs60%60%60%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 · 3 sales · October 26, 2025 – October 25, 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: 3 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 Shoalmont Add Sec 04.
MeasureAverageMedian
Sales3
Net sale price$1,976,667$1,775,000
Net price per SF$600$571
Living area (SF)3,2903,380
Days on market9638
Discount from original list7.5%4.1%
Price cut before sale33% of sales
Seller paid closing costs or repairs0% of sales
Year built2023–2026

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

8. AppendixMeasures, methods and tests

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

8.1 Measures

8.1.1 Net sale price

In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
20 resale sales. Average $1,269,898; median $1,019,500; standard deviation $812,680; middle half (25th–75th percentile) $802,500–$1,324,375; lowest $420,000, highest $3,525,400. 12 sales had a seller payment; their median payment was $8,500.

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
20 resale sales. Average $540; median $527; standard deviation $95; middle half (25th–75th percentile) $480–$577; lowest $405, highest $747.

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
20 resale sales. Average 2,273; median 2,046; standard deviation 1,044; middle half (25th–75th percentile) 1,742–2,708; lowest 764, highest 4,721.

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
20 resale sales. Average 1965; median 1952; standard deviation 28; middle half (25th–75th percentile) 1949–1959; lowest 1946, 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
20 resale sales. Average 48; median 20; standard deviation 58; middle half (25th–75th percentile) 11–64; lowest 0, highest 211. 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
20 resale sales. Average 6.8%; median 6.5%; standard deviation 5.9%; middle half (25th–75th percentile) 2.0%–11.1%; lowest −1.3%, highest 20.1%. 2 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
7 of 20 resale sales (35.0%).

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
12 of 20 resale sales (60.0%).

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
5 sales with a view, 15 without, 0 unclassified. Most common View entries: None 11, Neighborhood 5, Trees/Woods 3, Creek/Stream 3, Park/Greenbelt 1, See Remarks 1, Garden 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “shoalmont add”, “shoalmont add resub”, “shoalmont” (case-insensitive). A record is kept when its subdivision name belongs to the Shoalmont Add Sec 04 family, the same rule comparable sales use (it includes Shoalmont Add Resub, Shoalmont, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 24 closed Shoalmont Add Sec 04 records over the prior year, in ZIP 78756, 78731. 7 subdivision spellings kept: Shoalmont Add Resub (10); Shoalmont Add Sec 03 (5); Shoalmont Add Sec 02 (3); Shoalmont (2); Shoalmont Add Sec 04 (2); Shoalmont Addition Sec 4 (1); Shoalmont Sec 05 (1). Names found by the search but not part of Shoalmont Add Sec 04, left out: Allandale - Shoalmont Add Resub (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 October 26, 2025 to October 25, 2026 inclusive.
The data
23 single-family sales in the window: 20 resale, 3 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
20 resale; 3 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 $810K”.
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 $810K: $420,000–$780,000 (5 sales); $810K–$1.02M: $810,000–$1,019,000 (5 sales); $1.02M–$1.25M: $1,020,000–$1,250,000 (5 sales); Over $1.25M: $1,547,500–$3,525,400 (5 sales)
Quartiles by living area: Under 1,760 SF: 764–1,689 SF (5 sales); 1,760–2,003 SF: 1,760–2,003 SF (5 sales); 2,090–2,698 SF: 2,090–2,698 SF (5 sales); Over 2,698 SF: 2,739–4,721 SF (5 sales)
Quartiles by year built: Before 1949: 1946–1948 (5 sales); 1949–1951: 1949–1951 (5 sales); 1952–1957: 1952–1957 (5 sales); After 1957: 1965–2023 (5 sales)
View and no view: View: MLS lists a view (5 sales); No view: None or Neighborhood (15 sales)

8.2.6 Average and median

In simple terms
The average adds the values and divides by how many; one very expensive home can pull it up. The median is the middle value, with half above and half below.
Statistically
Mean x̄ = (1/n) Σ xᵢ; median = 50th percentile. Price, price per SF, living area and discount use the mean; days on market and year built use the median (skewed or whole-year values).
The data
Net sale price: average $1,269,898, median $1,019,500. Days on market: average 48, median 20: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

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

8.2.8 Mann–Whitney U test

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

8.2.9 Chi-square test

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

8.2.10 Real difference (significance)

In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063; Quartiles by year built: m = 8, threshold p < 0.0063; View and no view: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
2 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 9.5130.0232p < 0.0063Unclearε² = 0.501large
Living areaKruskal–WallisH = 15.7130.0013p < 0.0063Yesε² = 0.827large
Year builtKruskal–WallisH = 3.7830.2866p < 0.0063Unclearε² = 0.199large
Days on marketKruskal–WallisH = 1.2430.7423p < 0.0063Unclearε² = 0.066medium
Discount from original listKruskal–WallisH = 3.4330.3294p < 0.0063Unclearε² = 0.181large
Price cut before saleChi-squareχ² = 5.9330.1149p < 0.0063UnclearCramér’s V = 0.545large
Seller paid closing costs or repairsChi-squareχ² = 1.6730.6444p < 0.0063UnclearCramér’s V = 0.289small
Has a viewChi-squareχ² = 0.8030.8495p < 0.0063UnclearCramér’s V = 0.200small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 15.8330.0012p < 0.0063Yesε² = 0.833large
Net price per SFKruskal–WallisH = 4.7730.1893p < 0.0063Unclearε² = 0.251large
Year builtKruskal–WallisH = 5.2430.1552p < 0.0063Unclearε² = 0.276large
Days on marketKruskal–WallisH = 1.4130.7030p < 0.0063Unclearε² = 0.074medium
Discount from original listKruskal–WallisH = 2.9430.4005p < 0.0063Unclearε² = 0.155large
Price cut before saleChi-squareχ² = 4.1830.2431p < 0.0063UnclearCramér’s V = 0.457medium
Seller paid closing costs or repairsChi-squareχ² = 1.6730.6444p < 0.0063UnclearCramér’s V = 0.289small
Has a viewChi-squareχ² = 7.2030.0658p < 0.0063UnclearCramér’s V = 0.600large

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 3.5530.3145p < 0.0063Unclearε² = 0.187large
Net price per SFKruskal–WallisH = 3.9830.2633p < 0.0063Unclearε² = 0.210large
Living areaKruskal–WallisH = 4.0530.2560p < 0.0063Unclearε² = 0.213large
Days on marketKruskal–WallisH = 0.5430.9098p < 0.0063Unclearε² = 0.028small
Discount from original listKruskal–WallisH = 1.3530.7163p < 0.0063Unclearε² = 0.071medium
Price cut before saleChi-squareχ² = 4.1830.2431p < 0.0063UnclearCramér’s V = 0.457medium
Seller paid closing costs or repairsChi-squareχ² = 1.6730.6444p < 0.0063UnclearCramér’s V = 0.289small
Has a viewChi-squareχ² = 2.9330.4020p < 0.0063UnclearCramér’s V = 0.383medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 46.00—0.4973p < 0.0063Unclearrank-biserial r = 0.227small
Net price per SFMann–Whitney UU = 29.00—0.4973p < 0.0063Unclearrank-biserial r = 0.227small
Living areaMann–Whitney UU = 49.00—0.3486p < 0.0063Unclearrank-biserial r = 0.307medium
Year builtMann–Whitney UU = 48.00—0.3817p < 0.0063Unclearrank-biserial r = 0.280small
Days on marketMann–Whitney UU = 45.00—0.5409p < 0.0063Unclearrank-biserial r = 0.200small
Discount from original listMann–Whitney UU = 58.00—0.0806p < 0.0063Unclearrank-biserial r = 0.547large
Price cut before saleChi-squareχ² = 0.0710.7866p < 0.0063UnclearCramér’s V = 0.061negligible
Seller paid closing costs or repairsChi-squareχ² = 0.0011.0000p < 0.0063UnclearCramér’s V = 0.000negligible

8.4 Data notes

Left out of the analysis: 3 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 20 closed MLS resale sales; the 3 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 26, 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.