ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Brown Herman Add

Austin, TX 78703
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 · 4:32 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
13
single-family resale homes
Median net sale price
$2,050,000
average $2,346,269
Median net price per SF
$591
average $699
Median days on market
86 days
average 104 days
1. SummaryResale homes · 13 sales · October 26, 2025 – October 25, 2026

This study looks at the 13 resale homes sold in Brown Herman Add 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 sold13 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 $1.29M · 3 sales$1.29M–$1.99M · 3 sales$2.05M–$2.38M · 4 salesOver $2.38M · 3 sales
3. Quartiles by net sale priceResale homes · 13 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.

2026-10-26T04:33:02.773098 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 3 4 3 13 sales Sales per group Under $1.29M: 3 sales (23%) $1.29M–$1.99M: 3 sales (23%) $2.05M–$2.38M: 4 sales (31%) Over $2.38M: 3 sales (23%)
Bottom line: too few sales to test.

3.1 Key differences

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

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: described, not tested

2026-10-26T04:33:02.801444 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.29M 3 sales $1.29M– $1.99M 3 sales $2.05M– $2.38M 4 sales Over $2.38M 3 sales $0 $500 $1,000 $507 $558 $643 $1,107 Net price per SF, average

The average is $1,107 per SF for homes over $2.38M and $507 per SF for homes under $1.29M. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

Not tested: too few sales.

3.4 Living area: described, not tested

2026-10-26T04:33:02.823436 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.29M 3 sales $1.29M– $1.99M 3 sales $2.05M– $2.38M 4 sales Over $2.38M 3 sales 0 2,000 4,000 2,340 3,170 3,573 4,034 Living area (SF), average

The average is 4,034 SF for homes over $2.38M and 2,340 SF for homes under $1.29M. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

Not tested: too few sales.

3.5 Year built: described, not tested

2026-10-26T04:33:02.847489 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.29M 3 sales $1.29M– $1.99M 3 sales $2.05M– $2.38M 4 sales Over $2.38M 3 sales 1960 1970 1980 1990 1956 1982 1964 1972 Year built: median (dot) and middle half (bar)

The median is 1972 for homes over $2.38M and 1956 for homes under $1.29M. It does not move in a straight line; homes $1.29M–$1.99M are highest. Defined in 8.1.4.

Not tested: too few sales.

3.6 Days on market: described, not tested

2026-10-26T04:33:02.870406 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.29M 3 sales $1.29M– $1.99M 3 sales $2.05M– $2.38M 4 sales Over $2.38M 3 sales 0 50 100 75 86 98 104 Days on market, median

The median is 104 days for homes over $2.38M and 75 days for homes under $1.29M. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

Not tested: too few sales.

3.7 Discount from original list: described, not tested

2026-10-26T04:33:02.891949 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.29M 3 sales $1.29M– $1.99M 3 sales $2.05M– $2.38M 4 sales Over $2.38M 3 sales 0.0% 10.0% 20.0% 18.1% 8.2% 13.3% 10.3% Discount from original list, average

The average is 10.3% for homes over $2.38M and 18.1% for homes under $1.29M. It does not move in a straight line; homes under $1.29M are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T04:33:02.921907 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% 67 0 0 33 0 33 50 50 25 33 0 33 Under $1.29M $1.29M–$1.99M $2.05M–$2.38M Over $2.38M

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

  • 33% of homes over $2.38M had a price cut before sale, against 67% of homes under $1.29M. Defined in 8.1.7.
  • 0% of homes over $2.38M had the seller pay closing costs or repairs, against 0% of homes under $1.29M. Defined in 8.1.8.
  • 33% of homes over $2.38M have a view, against 0% of homes under $1.29M. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

3.9 The numbers: price and size

Under $1.29M3 sales$1.29M–$1.99M3 sales$2.05M–$2.38M4 salesOver $2.38M3 salesAll13 sales
Net sale price average$1,148,000$1,684,500$2,263,500$4,316,667$2,346,269
Net price per SF average$507$558$643$1,107$699
Living area average2,3403,1703,5734,0343,302
Year built median19561982196419721965

3.10 The numbers: selling

Under $1.29M3 sales$1.29M–$1.99M3 sales$2.05M–$2.38M4 salesOver $2.38M3 salesAll13 sales
Days on market median75869810486
Discount from original list average18.1%8.2%13.3%10.3%12.5%
Price cut before sale67%33%50%33%46%
Seller paid closing costs or repairs0%0%50%0%15%
Has a view0%33%25%33%23%

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 · 13 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.

2026-10-26T04:33:02.942214 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 3 4 3 13 sales Sales per group Under 2,658 SF: 3 sales (23%) 2,658–3,271 SF: 3 sales (23%) 3,690–3,904 SF: 4 sales (31%) Over 3,904 SF: 3 sales (23%)
Bottom line: too few sales to test.

4.1 Key differences

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

4.3 Net sale price: described, not tested

2026-10-26T04:33:02.962444 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,658 SF 3 sales 2,658– 3,271 SF 3 sales 3,690– 3,904 SF 4 sales Over 3,904 SF 3 sales $0K $2.00M $4.00M $1.21M $1.91M $3.39M $2.53M Net sale price, average

The average is $2.53M for homes over 3,904 SF and $1.21M for homes under 2,658 SF. It does not move in a straight line; homes 3,690–3,904 SF are highest. Defined in 8.1.1.

Not tested: too few sales.

4.4 Net price per SF: described, not tested

2026-10-26T04:33:02.985085 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,658 SF 3 sales 2,658– 3,271 SF 3 sales 3,690– 3,904 SF 4 sales Over 3,904 SF 3 sales $0 $500 $1,000 $598 $623 $906 $600 Net price per SF, average

The average is $600 per SF for homes over 3,904 SF and $598 per SF for homes under 2,658 SF. It does not move in a straight line; homes 3,690–3,904 SF are highest. Defined in 8.1.2.

Not tested: too few sales.

4.5 Year built: described, not tested

2026-10-26T04:33:03.008682 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,658 SF 3 sales 2,658– 3,271 SF 3 sales 3,690– 3,904 SF 4 sales Over 3,904 SF 3 sales 1960 1970 1980 1990 1956 1962 1977 1972 Year built: median (dot) and middle half (bar)

The median is 1972 for homes over 3,904 SF and 1956 for homes under 2,658 SF. It does not move in a straight line; homes 3,690–3,904 SF are highest. Defined in 8.1.4.

Not tested: too few sales.

4.6 Days on market: described, not tested

2026-10-26T04:33:03.031495 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,658 SF 3 sales 2,658– 3,271 SF 3 sales 3,690– 3,904 SF 4 sales Over 3,904 SF 3 sales 0 50 100 150 75 161 55 77 Days on market, median

The median is 77 days for homes over 3,904 SF and 75 days for homes under 2,658 SF. It does not move in a straight line; homes 2,658–3,271 SF are highest. Defined in 8.1.5.

Not tested: too few sales.

4.7 Discount from original list: described, not tested

2026-10-26T04:33:03.053496 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,658 SF 3 sales 2,658– 3,271 SF 3 sales 3,690– 3,904 SF 4 sales Over 3,904 SF 3 sales 0.0% 5.0% 10.0% 15.0% 13.5% 14.7% 12.9% 8.7% Discount from original list, average

The average is 8.7% for homes over 3,904 SF and 13.5% for homes under 2,658 SF. It does not move in a straight line; homes 2,658–3,271 SF are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T04:33:03.079690 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% 67 0 0 67 33 33 50 0 50 0 33 0 Under 2,658 SF 2,658–3,271 SF 3,690–3,904 SF Over 3,904 SF

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

  • 0% of homes over 3,904 SF had a price cut before sale, against 67% of homes under 2,658 SF. Defined in 8.1.7.
  • 33% of homes over 3,904 SF had the seller pay closing costs or repairs, against 0% of homes under 2,658 SF. Defined in 8.1.8.
  • 0% of homes over 3,904 SF have a view, against 0% of homes under 2,658 SF. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

4.9 The numbers: price and size

Under 2,658 SF3 sales2,658–3,271 SF3 sales3,690–3,904 SF4 salesOver 3,904 SF3 salesAll13 sales
Net sale price average$1,213,000$1,906,667$3,389,625$2,528,000$2,346,269
Net price per SF average$598$623$906$600$699
Living area average2,0833,0053,7604,2083,302
Year built median19561962197719721965

4.10 The numbers: selling

Under 2,658 SF3 sales2,658–3,271 SF3 sales3,690–3,904 SF4 salesOver 3,904 SF3 salesAll13 sales
Days on market median75161557786
Discount from original list average13.5%14.7%12.9%8.7%12.5%
Price cut before sale67%67%50%0%46%
Seller paid closing costs or repairs0%33%0%33%15%
Has a view0%33%50%0%23%

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 · 13 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.

2026-10-26T04:33:03.099504 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 3 4 3 13 sales Sales per group Before 1962: 3 sales (23%) 1962–1964: 3 sales (23%) 1965–1972: 4 sales (31%) After 1972: 3 sales (23%)
Bottom line: too few sales to test.

5.1 Key differences

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

5.3 Net sale price: described, not tested

2026-10-26T04:33:03.119463 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1962 3 sales 1962– 1964 3 sales 1965– 1972 4 sales After 1972 3 sales $0K $2.00M $4.00M $1.19M $1.93M $3.65M $2.19M Net sale price, average

The average is $2.19M for homes built after 1972 and $1.19M for homes built before 1962. It does not move in a straight line; homes built 1965–1972 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T04:33:03.141917 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1962 3 sales 1962– 1964 3 sales 1965– 1972 4 sales After 1972 3 sales $0 $500 $1,000 $582 $638 $947 $546 Net price per SF, average

The average is $546 per SF for homes built after 1972 and $582 per SF for homes built before 1962. It does not move in a straight line; homes built 1965–1972 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T04:33:03.163020 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1962 3 sales 1962– 1964 3 sales 1965– 1972 4 sales After 1972 3 sales 0 2,000 4,000 2,115 2,973 3,931 3,979 Living area (SF), average

The average is 3,979 SF for homes built after 1972 and 2,115 SF for homes built before 1962. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T04:33:03.183928 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1962 3 sales 1962– 1964 3 sales 1965– 1972 4 sales After 1972 3 sales 0 50 100 150 129 119 90 35 Days on market, median

The median is 35 days for homes built after 1972 and 129 days for homes built before 1962. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T04:33:03.206295 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1962 3 sales 1962– 1964 3 sales 1965– 1972 4 sales After 1972 3 sales 0.0% 10.0% 20.0% 8.6% 19.7% 12.1% 9.9% Discount from original list, average

The average is 9.9% for homes built after 1972 and 8.6% for homes built before 1962. It does not move in a straight line; homes built 1962–1964 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T04:33:03.230962 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 0 0 100 33 33 25 25 25 33 0 33 Before 1962 1962–1964 1965–1972 After 1972

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

  • 33% of homes built after 1972 had a price cut before sale, against 33% of homes built before 1962. Defined in 8.1.7.
  • 0% of homes built after 1972 had the seller pay closing costs or repairs, against 0% of homes built before 1962. Defined in 8.1.8.
  • 33% of homes built after 1972 have a view, against 0% of homes built before 1962. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

5.9 The numbers: price and size

Before 19623 sales1962–19643 sales1965–19724 salesAfter 19723 salesAll13 sales
Net sale price average$1,186,333$1,933,333$3,646,000$2,186,167$2,346,269
Net price per SF average$582$638$947$546$699
Living area average2,1152,9733,9313,9793,302
Year built median19511964197020101965

5.10 The numbers: selling

Before 19623 sales1962–19643 sales1965–19724 salesAfter 19723 salesAll13 sales
Days on market median129119903586
Discount from original list average8.6%19.7%12.1%9.9%12.5%
Price cut before sale33%100%25%33%46%
Seller paid closing costs or repairs0%33%25%0%15%
Has a view0%33%25%33%23%

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 · 13 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. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T04:33:03.248668 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 9 12 sales Sales per group View: 3 sales (25%) No view: 9 sales (75%)
Bottom line: too few sales to test.

6.1 Key differences

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

6.3 Net sale price: described, not tested

2026-10-26T04:33:03.265342 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 9 sales $0K $1.00M $2.00M $3.00M $4.00M $4.03M $1.92M Net sale price, average

The average is $4.03M for homes with a view and $1.92M for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T04:33:03.283542 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 9 sales $0 $500 $1,000 $1,111 $593 Net price per SF, average

The average is $1,111 per SF for homes with a view and $593 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T04:33:03.302251 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 9 sales 0 1,000 2,000 3,000 4,000 3,572 3,284 Living area (SF), average

The average is 3,572 SF for homes with a view and 3,284 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T04:33:03.348622 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 9 sales 1963 1966 1969 1972 1975 1968 1965 Year built: median (dot) and middle half (bar)

The median is 1968 for homes with a view and 1965 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T04:33:03.366781 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 9 sales 0 50 100 150 161 77 Days on market, median

The median is 161 days for homes with a view and 77 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-26T04:33:03.384702 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 9 sales 0.0% 5.0% 10.0% 15.0% 13.4% 12.1% Discount from original list, average

The average is 13.4% for homes with a view and 12.1% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T04:33:03.403354 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 67 33 44 11 View No view

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

  • 67% of homes with a view had a price cut before sale, against 44% of homes without a view. Defined in 8.1.7.
  • 33% of homes with a view had the seller pay closing costs or repairs, against 11% of homes without a view. Defined in 8.1.8.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View3 salesNo view9 salesAll12 sales
Net sale price average$4,029,500$1,923,667$2,450,125
Net price per SF average$1,111$593$723
Living area average3,5723,2843,356
Year built median196819651966

6.11 The numbers: selling

View3 salesNo view9 salesAll12 sales
Days on market median1617782
Discount from original list average13.4%12.1%12.4%
Price cut before sale67%44%50%
Seller paid closing costs or repairs33%11%17%

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 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: 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 Brown Herman Add.

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
13 resale sales. Average $2,346,269; median $2,050,000; standard deviation $1,717,119; middle half (25th–75th percentile) $1,295,000–$2,384,000; lowest $1,100,000, highest $7,750,000. 2 sales had a seller payment; their median payment was $64,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
13 resale sales. Average $699; median $591; standard deviation $428; middle half (25th–75th percentile) $536–$686; lowest $414, highest $2,081.

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
13 resale sales. Average 3,302; median 3,690; standard deviation 848; middle half (25th–75th percentile) 2,658–3,904; lowest 1,799, highest 4,314.

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
13 resale sales. Average 1971; median 1965; standard deviation 20; middle half (25th–75th percentile) 1962–1972; lowest 1951, highest 2012.

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
13 resale sales. Average 104; median 86; standard deviation 77; middle half (25th–75th percentile) 45–129; lowest 5, highest 277. 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
13 resale sales. Average 12.5%; median 12.2%; standard deviation 8.8%; middle half (25th–75th percentile) 7.5%–18.4%; lowest 0.0%, highest 28.5%. 0 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
6 of 13 resale sales (46.2%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
2 of 13 resale sales (15.4%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
3 sales with a view, 9 without, 1 unclassified. Most common View entries: None 8, Trees/Woods 2, Neighborhood 1, See Remarks 1, Lake 1, Park/Greenbelt 1, 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
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “brown herman add” (case-insensitive). A record is kept when its subdivision name belongs to the Brown Herman Add family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 13 closed Brown Herman Add records over the prior year, in ZIP 78703. 4 subdivision spellings kept: Brown Herman Add 02 Sec 01 (5); Brown Herman Add (4); Brown Herman Add 02 Sec 04 (2); Brown Herman Add 02 Sec 05 (2). Names found by the search but not part of Brown Herman Add, left out: BROWN HERMAN ADDN (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
13 single-family sales in the window: 13 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
13 resale; 0 new construction.

8.2.4 Sales left out

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

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $1.29M”.
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 $1.29M: $1,100,000–$1,180,000 (3 sales); $1.29M–$1.99M: $1,295,000–$1,993,500 (3 sales); $2.05M–$2.38M: $2,050,000–$2,384,000 (4 sales); Over $2.38M: $2,400,000–$7,750,000 (3 sales)
Quartiles by living area: Under 2,658 SF: 1,799–2,562 SF (3 sales); 2,658–3,271 SF: 2,658–3,271 SF (3 sales); 3,690–3,904 SF: 3,690–3,904 SF (4 sales); Over 3,904 SF: 4,064–4,314 SF (3 sales)
Quartiles by year built: Before 1962: 1951–1956 (3 sales); 1962–1964: 1962–1964 (3 sales); 1965–1972: 1965–1972 (4 sales); After 1972: 1982–2012 (3 sales)
View and no view: View: MLS lists a view (3 sales); No view: None or Neighborhood (9 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 $2,346,269, median $2,050,000. Days on market: average 104, median 86: 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

8.2.11 Size of a difference

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

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

Too few sales in a group to test.

8.3.2 Quartiles by living area

Too few sales in a group to test.

8.3.3 Quartiles by year built

Too few sales in a group to test.

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

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

8.5 References

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

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 13 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 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.