ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Bradshaw Crossing

Austin, TX 78747
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 · 4:04 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
23
single-family resale homes
Median net sale price
$314,123
average $317,319
Median net price per SF
$165
average $171
Median days on market
79 days
average 87 days
1. SummaryResale homes · 23 sales · October 26, 2025 – October 25, 2026

This study looks at the 23 resale homes sold in Bradshaw Crossing in the 365 days to October 25, 2026. A full year is used because only 13 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 sold23 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 $293K · 6 sales$293K–$314K · 6 sales$314K–$331K · 5 salesOver $331K · 6 sales
3. Quartiles by net sale priceResale homes · 23 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.

2026-10-26T04:04:17.387026 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 5 6 23 sales Sales per group Under $293K: 6 sales (26%) $293K–$314K: 6 sales (26%) $314K–$331K: 5 sales (22%) Over $331K: 6 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 $293K$293K–$314K$314K–$331KOver $331K
Higher-priced homes Over $331K
  • Tend to be newer.
Lower-priced homes Under $293K
  • Tend to be older.

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 $293K$293K–$314K$314K–$331KOver $331KReal difference?
Net price per SF$172 per SF$186 per SF$161 per SF$161 per SFunclear
Living area1,684 SF1,612 SF2,086 SF2,324 SFunclear
Year built2014Oldest2018Newest20142016✓ large
Days on market72 days76 days48 days106 daysunclear
Discount from original list14.5%5.8%4.8%4.5%unclear
Price cut before sale100%83%60%50%unclear
Seller paid closing costs or repairs50%83%100%67%unclear
Has a view17%0%0%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 Net price per SF: no clear difference

2026-10-26T04:04:17.417169 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $293K 6 sales $293K– $314K 6 sales $314K– $331K 5 sales Over $331K 6 sales $0 $100 $200 $172 $186 $161 $161 Net price per SF, average

The average is $161 per SF for homes over $331K and $172 per SF for homes under $293K. It does not move in a straight line; homes $293K–$314K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-26T04:04:17.440839 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $293K 6 sales $293K– $314K 6 sales $314K– $331K 5 sales Over $331K 6 sales 0 1,000 2,000 1,684 1,612 2,086 2,324 Living area (SF), average

The average is 2,324 SF for homes over $331K and 1,684 SF for homes under $293K. It does not move in a straight line; homes over $331K are highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Homes over $331K are about 2 years newer than homes under $293K

2026-10-26T04:04:17.466085 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $293K 6 sales $293K– $314K 6 sales $314K– $331K 5 sales Over $331K 6 sales 2014 2016 2018 2020 2014 2018 2014 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over $331K and 2014 for homes under $293K. It does not move in a straight line; homes $293K–$314K are highest. Defined in 8.1.4.

✓ Real difference · large

3.6 Days on market: no clear difference

2026-10-26T04:04:17.490131 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $293K 6 sales $293K– $314K 6 sales $314K– $331K 5 sales Over $331K 6 sales 0 50 100 72 76 48 106 Days on market, median

The median is 106 days for homes over $331K and 72 days for homes under $293K. It does not move in a straight line; homes over $331K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T04:04:17.512211 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $293K 6 sales $293K– $314K 6 sales $314K– $331K 5 sales Over $331K 6 sales 0.0% 5.0% 10.0% 15.0% 14.5% 5.8% 4.8% 4.5% Discount from original list, average

The average is 4.5% for homes over $331K and 14.5% for homes under $293K. 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

2026-10-26T04:04:17.543305 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% 100 50 17 83 83 0 60 100 0 50 67 50 Under $293K $293K–$314K $314K–$331K Over $331K

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

  • 50% of homes over $331K had a price cut before sale, against 100% of homes under $293K. Defined in 8.1.7.
  • 67% of homes over $331K had the seller pay closing costs or repairs, against 50% of homes under $293K. Defined in 8.1.8.
  • 50% of homes over $331K have a view, against 17% of homes under $293K. 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 $293K6 sales$293K–$314K6 sales$314K–$331K5 salesOver $331K6 salesAll23 salesReal difference?
Net sale price average$282,467$298,137$323,758$365,986$317,319by design
Net price per SF average$172$186$161$161$171unclear
Living area average1,6841,6122,0862,3241,920unclear
Year built median20142018201420162016✓ large

3.10 The numbers: selling

Under $293K6 sales$293K–$314K6 sales$314K–$331K5 salesOver $331K6 salesAll23 salesReal difference?
Days on market median72764810679unclear
Discount from original list average14.5%5.8%4.8%4.5%7.5%unclear
Price cut before sale100%83%60%50%74%unclear
Seller paid closing costs or repairs50%83%100%67%74%unclear
Has a view17%0%0%50%17%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 · 23 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.

2026-10-26T04:04:17.565116 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 5 6 23 sales Sales per group Under 1,645 SF: 6 sales (26%) 1,645–1,706 SF: 6 sales (26%) 1,820–2,280 SF: 5 sales (22%) Over 2,280 SF: 6 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 1,645 SF1,645–1,706 SF1,820–2,280 SFOver 2,280 SF
Larger homes Over 2,280 SF
  • Sell for less per square foot.
Smaller homes Under 1,645 SF
  • Sell for more per square foot.

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 1,645 SF1,645–1,706 SF1,820–2,280 SFOver 2,280 SFReal difference?
Net sale price$299K$300K$313K$357Kunclear
Net price per SF$205 per SFHighest$179 per SF$154 per SF$141 per SFLowest✓ large
Year built2018201620142015unclear
Days on market56 days69 days58 days118 daysunclear
Discount from original list6.6%10.0%8.2%5.3%unclear
Price cut before sale67%100%80%50%unclear
Seller paid closing costs or repairs67%67%80%83%unclear
Has a view17%17%20%17%unclear

4.3 Net sale price: no clear difference

2026-10-26T04:04:17.586443 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,645 SF 6 sales 1,645– 1,706 SF 6 sales 1,820– 2,280 SF 5 sales Over 2,280 SF 6 sales $0K $200K $400K $299K $300K $313K $357K Net sale price, average

The average is $357K for homes over 2,280 SF and $299K for homes under 1,645 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Homes over 2,280 SF sell for about $63 per SF (31%) less than homes under 1,645 SF

2026-10-26T04:04:17.609851 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,645 SF 6 sales 1,645– 1,706 SF 6 sales 1,820– 2,280 SF 5 sales Over 2,280 SF 6 sales $0 $100 $200 $205 $179 $154 $141 Net price per SF, average

The average is $141 per SF for homes over 2,280 SF and $205 per SF for homes under 1,645 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-10-26T04:04:17.633506 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,645 SF 6 sales 1,645– 1,706 SF 6 sales 1,820– 2,280 SF 5 sales Over 2,280 SF 6 sales 2014 2016 2018 2018 2016 2014 2015 Year built: median (dot) and middle half (bar)

The median is 2015 for homes over 2,280 SF and 2018 for homes under 1,645 SF. It does not move in a straight line; homes under 1,645 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T04:04:17.657244 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,645 SF 6 sales 1,645– 1,706 SF 6 sales 1,820– 2,280 SF 5 sales Over 2,280 SF 6 sales 0 50 100 56 69 58 118 Days on market, median

The median is 118 days for homes over 2,280 SF and 56 days for homes under 1,645 SF. It does not move in a straight line; homes over 2,280 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T04:04:17.679702 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,645 SF 6 sales 1,645– 1,706 SF 6 sales 1,820– 2,280 SF 5 sales Over 2,280 SF 6 sales 0.0% 5.0% 10.0% 6.6% 10.0% 8.2% 5.3% Discount from original list, average

The average is 5.3% for homes over 2,280 SF and 6.6% for homes under 1,645 SF. It does not move in a straight line; homes 1,645–1,706 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

2026-10-26T04:04:17.707344 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 67 17 100 67 17 80 80 20 50 83 17 Under 1,645 SF 1,645–1,706 SF 1,820–2,280 SF Over 2,280 SF

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

  • 50% of homes over 2,280 SF had a price cut before sale, against 67% of homes under 1,645 SF. Defined in 8.1.7.
  • 83% of homes over 2,280 SF had the seller pay closing costs or repairs, against 67% of homes under 1,645 SF. Defined in 8.1.8.
  • 17% of homes over 2,280 SF have a view, against 17% of homes under 1,645 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 1,645 SF6 sales1,645–1,706 SF6 sales1,820–2,280 SF5 salesOver 2,280 SF6 salesAll23 salesReal difference?
Net sale price average$299,204$300,150$312,543$356,582$317,319unclear
Net price per SF average$205$179$154$141$171✓ large
Living area average1,4661,6762,0282,5261,920by design
Year built median20182016201420152016unclear

4.10 The numbers: selling

Under 1,645 SF6 sales1,645–1,706 SF6 sales1,820–2,280 SF5 salesOver 2,280 SF6 salesAll23 salesReal difference?
Days on market median56695811879unclear
Discount from original list average6.6%10.0%8.2%5.3%7.5%unclear
Price cut before sale67%100%80%50%74%unclear
Seller paid closing costs or repairs67%67%80%83%74%unclear
Has a view17%17%20%17%17%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 · 23 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.

2026-10-26T04:04:17.729298 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 7 3 8 23 sales Sales per group Before 2014: 5 sales (22%) 2014–2016: 7 sales (30%) 2017: 3 sales (13%) After 2017: 8 sales (35%)
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

2026-10-26T04:04:17.750651 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 5 sales 2014– 2016 7 sales 2017 3 sales After 2017 8 sales $0K $200K $400K $309K $319K $338K $314K Net sale price, average

The average is $314K for homes built after 2017 and $309K for homes built before 2014. It does not move in a straight line; homes built 2017 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T04:04:17.774441 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 5 sales 2014– 2016 7 sales 2017 3 sales After 2017 8 sales $0 $100 $200 $160 $164 $177 $181 Net price per SF, average

The average is $181 per SF for homes built after 2017 and $160 per SF for homes built before 2014. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T04:04:17.796604 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 5 sales 2014– 2016 7 sales 2017 3 sales After 2017 8 sales 0 1,000 2,000 2,021 1,990 2,014 1,759 Living area (SF), average

The average is 1,759 SF for homes built after 2017 and 2,021 SF for homes built before 2014. It does not move in a straight line; homes built before 2014 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T04:04:17.818917 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 5 sales 2014– 2016 7 sales 2017 3 sales After 2017 8 sales 0 25 50 75 65 79 26 82 Days on market, median

The median is 82 days for homes built after 2017 and 65 days for homes built before 2014. It does not move in a straight line; homes built after 2017 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T04:04:17.842764 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 5 sales 2014– 2016 7 sales 2017 3 sales After 2017 8 sales 0.0% 5.0% 10.0% 11.4% 8.5% 4.7% 5.3% Discount from original list, average

The average is 5.3% for homes built after 2017 and 11.4% for homes built before 2014. It does not move in a straight line; homes built before 2014 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

2026-10-26T04:04:17.869251 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% 80 60 20 86 71 29 33 67 0 75 88 12 Before 2014 2014–2016 2017 After 2017

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

  • 75% of homes built after 2017 had a price cut before sale, against 80% of homes built before 2014. Defined in 8.1.7.
  • 88% of homes built after 2017 had the seller pay closing costs or repairs, against 60% of homes built before 2014. Defined in 8.1.8.
  • 12% of homes built after 2017 have a view, against 20% of homes built before 2014. 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 20145 sales2014–20167 sales20173 salesAfter 20178 salesAll23 sales
Net sale price average$309,120$318,527$337,500$313,817$317,319
Net price per SF average$160$164$177$181$171
Living area average2,0211,9902,0141,7591,920
Year built median20132014201720182016

5.10 The numbers: selling

Before 20145 sales2014–20167 sales20173 salesAfter 20178 salesAll23 sales
Days on market median6579268279
Discount from original list average11.4%8.5%4.7%5.3%7.5%
Price cut before sale80%86%33%75%74%
Seller paid closing costs or repairs60%71%67%88%74%
Has a view20%29%0%12%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 8.3.3.

6. View and no viewResale homes · 23 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. 2 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T04:04:17.889173 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 17 21 sales Sales per group View: 4 sales (19%) No view: 17 sales (81%)
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

2026-10-26T04:04:17.906280 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 17 sales $0K $100K $200K $300K $400K $341K $314K Net sale price, average

The average is $341K for homes with a view and $314K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T04:04:17.925771 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 17 sales $0 $50 $100 $150 $200 $185 $167 Net price per SF, average

The average is $185 per SF for homes with a view and $167 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T04:04:18.044976 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 17 sales 0 500 1,000 1,500 2,000 1,927 1,935 Living area (SF), average

The average is 1,927 SF for homes with a view and 1,935 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T04:04:18.068465 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 17 sales 2014 2015 2016 2017 2018 2016 2015 Year built: median (dot) and middle half (bar)

The median is 2016 for homes with a view and 2015 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T04:04:18.087620 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 17 sales 0 50 100 150 152 65 Days on market, median

The median is 152 days for homes with a view and 65 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

2026-10-26T04:04:18.108297 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 17 sales 0.0% 2.5% 5.0% 7.5% 10.0% 8.9% 7.3% Discount from original list, average

The average is 8.9% for homes with a view and 7.3% 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

2026-10-26T04:04:18.128164 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 100 100 65 65 View No view

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

  • 100% of homes with a view had a price cut before sale, against 65% of homes without a view. Defined in 8.1.7.
  • 100% of homes with a view had the seller pay closing costs or repairs, against 65% 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

View4 salesNo view17 salesAll21 sales
Net sale price average$341,204$314,324$319,444
Net price per SF average$185$167$171
Living area average1,9271,9351,934
Year built median201620152016

6.11 The numbers: selling

View4 salesNo view17 salesAll21 sales
Days on market median1526573
Discount from original list average8.9%7.3%7.6%
Price cut before sale100%65%71%
Seller paid closing costs or repairs100%65%71%

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 Bradshaw Crossing.

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
23 resale sales. Average $317,319; median $314,123; standard deviation $35,318; middle half (25th–75th percentile) $292,250–$334,208; lowest $260,000, highest $391,200. 17 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
23 resale sales. Average $171; median $165; standard deviation $28; middle half (25th–75th percentile) $149–$195; lowest $132, highest $224.

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
23 resale sales. Average 1,920; median 1,706; standard deviation 441; middle half (25th–75th percentile) 1,616–2,314; lowest 1,256, highest 2,861.

8.1.4 Year built

In simple terms
The year the home was finished, as listed in the MLS. It shows whether a group leans to older or newer phases of the community.
Statistically
RESO YearBuilt; summarized by the median, with the 25th–75th percentile (middle half) on the charts.
The data
23 resale sales. Average 2016; median 2016; standard deviation 3; middle half (25th–75th percentile) 2014–2018; lowest 2012, highest 2022.

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
23 resale sales. Average 87; median 79; standard deviation 62; middle half (25th–75th percentile) 46–108; lowest 15, highest 274. 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
23 resale sales. Average 7.5%; median 6.5%; standard deviation 6.7%; middle half (25th–75th percentile) 3.4%–11.2%; lowest −9.9%, highest 19.0%. 1 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
17 of 23 resale sales (73.9%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
17 of 23 resale sales (73.9%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
4 sales with a view, 17 without, 2 unclassified. Most common View entries: None 12, Neighborhood 7, Trees/Woods 2, Park/Greenbelt 2, See Remarks 2, Skyline 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 “bradshaw crossing”, “bradshaw crossing sub”, “bradshaw xing sub” (case-insensitive). A record is kept when its subdivision name belongs to the Bradshaw Crossing family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 23 closed Bradshaw Crossing records over the prior year, in ZIP 78747. 9 subdivision spellings kept: Bradshaw Crossing (5); Bradshaw Xing Sub Sec 12 (5); Bradshaw Crossing Sub Sec 9 (3); Bradshaw Crossing Sub Sec 10 (3); Bradshaw Crossing Sub Sec 11 (2); Bradshaw Crossing Sub (2); BRADSHAW CROSSING SUBD SEC 12 (1); Bradshaw Crossing Sub Sec 8 (1); Bradshaw Crossing Sub Sec 7 (1). 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 13 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: 23 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
23 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 $293K”.
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 $293K: $260,000–$291,500 (6 sales); $293K–$314K: $293,000–$314,123 (6 sales); $314K–$331K: $314,500–$330,700 (5 sales); Over $331K: $337,716–$391,200 (6 sales)
Quartiles by living area: Under 1,645 SF: 1,256–1,586 SF (6 sales); 1,645–1,706 SF: 1,645–1,706 SF (6 sales); 1,820–2,280 SF: 1,820–2,280 SF (5 sales); Over 2,280 SF: 2,348–2,861 SF (6 sales)
Quartiles by year built: Before 2014: 2012–2013 (5 sales); 2014–2016: 2014–2016 (7 sales); 2017: 2017–2017 (3 sales); After 2017: 2018–2022 (8 sales)
View and no view: View: MLS lists a view (4 sales); No view: None or Neighborhood (17 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 $317,319, median $314,123. Days on market: average 87, median 79: 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

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 = 3.3230.3444p < 0.0063Unclearε² = 0.151large
Living areaKruskal–WallisH = 9.3630.0248p < 0.0063Unclearε² = 0.426large
Year builtKruskal–WallisH = 13.7930.0032p < 0.0063Yesε² = 0.627large
Days on marketKruskal–WallisH = 2.4830.4791p < 0.0063Unclearε² = 0.113medium
Discount from original listKruskal–WallisH = 8.8630.0312p < 0.0063Unclearε² = 0.403large
Price cut before saleChi-squareχ² = 4.6830.1972p < 0.0063UnclearCramér’s V = 0.451medium
Seller paid closing costs or repairsChi-squareχ² = 3.9830.2632p < 0.0063UnclearCramér’s V = 0.416medium
Has a viewChi-squareχ² = 6.7630.0800p < 0.0063UnclearCramér’s V = 0.542large

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 9.3130.0255p < 0.0063Unclearε² = 0.423large
Net price per SFKruskal–WallisH = 16.9330.0007p < 0.0063Yesε² = 0.770large
Year builtKruskal–WallisH = 1.0830.7816p < 0.0063Unclearε² = 0.049small
Days on marketKruskal–WallisH = 4.2930.2316p < 0.0063Unclearε² = 0.195large
Discount from original listKruskal–WallisH = 1.8230.6110p < 0.0063Unclearε² = 0.083medium
Price cut before saleChi-squareχ² = 4.1630.2450p < 0.0063UnclearCramér’s V = 0.425medium
Seller paid closing costs or repairsChi-squareχ² = 0.7030.8734p < 0.0063UnclearCramér’s V = 0.174small
Has a viewChi-squareχ² = 0.0330.9986p < 0.0063UnclearCramér’s V = 0.036negligible

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 23 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.