ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Steiner Ranch

Austin, TX 78732
Resale homes · closed May 7 – Nov 2, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 3, 2026 · 6:49 AM CST
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 180 days
96
single-family resale homes
Median net sale price
$848,750
average $1,059,028
Median net price per SF
$271
average $291
Median days on market
44 days
average 68 days
1. SummaryResale homes · 96 sales · May 7, 2026 – November 2, 2026

This study looks at the 96 resale homes sold in Steiner Ranch in the 180 days to November 2, 2026. 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 sold96 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 $685K · 24 sales$685K–$842K · 24 sales$856K–$1.16M · 24 salesOver $1.16M · 24 sales
3. Quartiles by net sale priceResale homes · 96 sales · May 7, 2026 – November 2, 2026

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

2026-11-03T06:49:18.550438 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 24 24 24 24 96 sales Sales per group Under $685K: 24 sales (25%) $685K–$842K: 24 sales (25%) $856K–$1.16M: 24 sales (25%) Over $1.16M: 24 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 $685K$685K–$842K$856K–$1.16MOver $1.16M
Higher-priced homes Over $1.16M
  • Are much larger.
  • Sell for more per square foot.
  • Are more likely to have a view.
  • Tend to be newer.
Lower-priced homes Under $685K
  • Are much smaller.
  • Sell for less per square foot.
  • Are less likely to have a view.
  • 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 $685K$685K–$842K$856K–$1.16MOver $1.16MReal difference?
Net price per SF$247 per SFLowest$251 per SF$291 per SF$376 per SFHighest✓ large
Living area2,412 SFSmallest3,072 SF3,665 SF4,742 SFLargest✓ large
Year built1999Oldest200420052008Newest✓ large
Days on market36 days40 days54 days73 daysunclear
Discount from original list4.9%7.3%8.5%7.4%unclear
Price cut before sale46%54%50%54%unclear
Seller paid closing costs or repairs67%62%58%58%unclear
Has a view75%33%Fewest79%92%Most✓ medium

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

3.3 Homes over $1.16M sell for about $129 per SF (52%) more than homes under $685K

2026-11-03T06:49:18.578341 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $685K 24 sales $685K– $842K 24 sales $856K– $1.16M 24 sales Over $1.16M 24 sales $0 $200 $400 $247 $251 $291 $376 Net price per SF, average

The average is $376 per SF for homes over $1.16M and $247 per SF for homes under $685K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $1.16M are about 2,330 SF (97%) larger than homes under $685K

2026-11-03T06:49:18.600413 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $685K 24 sales $685K– $842K 24 sales $856K– $1.16M 24 sales Over $1.16M 24 sales 0 2,000 4,000 2,412 3,072 3,665 4,742 Living area (SF), average

The average is 4,742 SF for homes over $1.16M and 2,412 SF for homes under $685K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Homes over $1.16M are about 9 years newer than homes under $685K

2026-11-03T06:49:18.623761 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $685K 24 sales $685K– $842K 24 sales $856K– $1.16M 24 sales Over $1.16M 24 sales 1996 2000 2004 2008 1999 2004 2005 2008 Year built: median (dot) and middle half (bar)

The median is 2008 for homes over $1.16M and 1999 for homes under $685K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

✓ Real difference · large

3.6 Days on market: no clear difference

2026-11-03T06:49:18.646582 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $685K 24 sales $685K– $842K 24 sales $856K– $1.16M 24 sales Over $1.16M 24 sales 0 25 50 75 36 40 54 73 Days on market, median

The median is 73 days for homes over $1.16M and 36 days for homes under $685K. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-03T06:49:18.668360 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $685K 24 sales $685K– $842K 24 sales $856K– $1.16M 24 sales Over $1.16M 24 sales 0.0% 5.0% 10.0% 4.9% 7.3% 8.5% 7.4% Discount from original list, average

The average is 7.4% for homes over $1.16M and 4.9% for homes under $685K. It does not move in a straight line; homes $856K–$1.16M are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-03T06:49:18.697800 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% 46 67 75 54 62 33 50 58 79 54 58 92 Under $685K $685K–$842K $856K–$1.16M Over $1.16M

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

  • 54% of homes over $1.16M had a price cut before sale, against 46% of homes under $685K. Defined in 8.1.7.
  • 58% of homes over $1.16M had the seller pay closing costs or repairs, against 67% of homes under $685K. Defined in 8.1.8.
  • 92% of homes over $1.16M have a view, against 75% of homes under $685K. 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: ✓ Real difference · medium

3.9 The numbers: price and size

Under $685K24 sales$685K–$842K24 sales$856K–$1.16M24 salesOver $1.16M24 salesAll96 salesReal difference?
Net sale price average$585,763$765,520$1,059,320$1,825,508$1,059,028by design
Net price per SF average$247$251$291$376$291✓ large
Living area average2,4123,0723,6654,7423,473✓ large
Year built median19992004200520082005✓ large

3.10 The numbers: selling

Under $685K24 sales$685K–$842K24 sales$856K–$1.16M24 salesOver $1.16M24 salesAll96 salesReal difference?
Days on market median3640547344unclear
Discount from original list average4.9%7.3%8.5%7.4%7.0%unclear
Price cut before sale46%54%50%54%51%unclear
Seller paid closing costs or repairs67%62%58%58%61%unclear
Has a view75%33%79%92%70%✓ medium

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 · 96 sales · May 7, 2026 – November 2, 2026

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

2026-11-03T06:49:18.718023 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 24 24 24 24 96 sales Sales per group Under 2,783 SF: 24 sales (25%) 2,783–3,347 SF: 24 sales (25%) 3,368–4,100 SF: 24 sales (25%) Over 4,100 SF: 24 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 2,783 SF2,783–3,347 SF3,368–4,100 SFOver 4,100 SF
Larger homes Over 4,100 SF
  • Sell for much more.
  • Are more likely to have a view.
  • Sell for more per square foot.
  • Tend to be newer.
Smaller homes Under 2,783 SF
  • Sell for much less.
  • Are less likely to have a view.
  • Sell for less per square foot.
  • Tend to be older.

4.2 At a glance

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

Under 2,783 SF2,783–3,347 SF3,368–4,100 SFOver 4,100 SFReal difference?
Net sale price$602KLowest$792K$1.07M$1.77MHighest✓ large
Net price per SF$259 per SF$258 per SFLowest$289 per SF$359 per SFHighest✓ large
Year built1999Oldest200020052006Newest✓ large
Days on market38 days34 days54 days74 daysunclear
Discount from original list5.8%6.8%6.6%8.9%unclear
Price cut before sale54%42%50%58%unclear
Seller paid closing costs or repairs62%62%67%54%unclear
Has a view75%38%Fewest75%92%Most✓ medium

4.3 Homes over 4,100 SF sell for about $1.17M (194%) more than homes under 2,783 SF

2026-11-03T06:49:18.738317 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,783 SF 24 sales 2,783– 3,347 SF 24 sales 3,368– 4,100 SF 24 sales Over 4,100 SF 24 sales $0K $1.00M $2.00M $602K $792K $1.07M $1.77M Net sale price, average

The average is $1.77M for homes over 4,100 SF and $602K for homes under 2,783 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 4,100 SF sell for about $100 per SF (38%) more than homes under 2,783 SF

2026-11-03T06:49:18.760186 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,783 SF 24 sales 2,783– 3,347 SF 24 sales 3,368– 4,100 SF 24 sales Over 4,100 SF 24 sales $0 $200 $400 $259 $258 $289 $359 Net price per SF, average

The average is $359 per SF for homes over 4,100 SF and $259 per SF for homes under 2,783 SF. It does not move in a straight line; homes over 4,100 SF are highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Homes over 4,100 SF are about 8 years newer than homes under 2,783 SF

2026-11-03T06:49:18.783215 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,783 SF 24 sales 2,783– 3,347 SF 24 sales 3,368– 4,100 SF 24 sales Over 4,100 SF 24 sales 1999 2002 2005 2008 1999 2000 2005 2006 Year built: median (dot) and middle half (bar)

The median is 2006 for homes over 4,100 SF and 1999 for homes under 2,783 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

✓ Real difference · large

4.6 Days on market: no clear difference

2026-11-03T06:49:18.805592 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,783 SF 24 sales 2,783– 3,347 SF 24 sales 3,368– 4,100 SF 24 sales Over 4,100 SF 24 sales 0 25 50 75 38 34 54 74 Days on market, median

The median is 74 days for homes over 4,100 SF and 38 days for homes under 2,783 SF. It does not move in a straight line; homes over 4,100 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-03T06:49:18.827366 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,783 SF 24 sales 2,783– 3,347 SF 24 sales 3,368– 4,100 SF 24 sales Over 4,100 SF 24 sales 0.0% 5.0% 10.0% 5.8% 6.8% 6.6% 8.9% Discount from original list, average

The average is 8.9% for homes over 4,100 SF and 5.8% for homes under 2,783 SF. It does not move in a straight line; homes over 4,100 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-03T06:49:18.853302 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% 54 62 75 42 62 38 50 67 75 58 54 92 Under 2,783 SF 2,783–3,347 SF 3,368–4,100 SF Over 4,100 SF

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

  • 58% of homes over 4,100 SF had a price cut before sale, against 54% of homes under 2,783 SF. Defined in 8.1.7.
  • 54% of homes over 4,100 SF had the seller pay closing costs or repairs, against 62% of homes under 2,783 SF. Defined in 8.1.8.
  • 92% of homes over 4,100 SF have a view, against 75% of homes under 2,783 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: ✓ Real difference · medium

4.9 The numbers: price and size

Under 2,783 SF24 sales2,783–3,347 SF24 sales3,368–4,100 SF24 salesOver 4,100 SF24 salesAll96 salesReal difference?
Net sale price average$601,742$791,899$1,070,517$1,771,954$1,059,028✓ large
Net price per SF average$259$258$289$359$291✓ large
Living area average2,3383,0753,6854,7953,473by design
Year built median19992000200520062005✓ large

4.10 The numbers: selling

Under 2,783 SF24 sales2,783–3,347 SF24 sales3,368–4,100 SF24 salesOver 4,100 SF24 salesAll96 salesReal difference?
Days on market median3834547444unclear
Discount from original list average5.8%6.8%6.6%8.9%7.0%unclear
Price cut before sale54%42%50%58%51%unclear
Seller paid closing costs or repairs62%62%67%54%61%unclear
Has a view75%38%75%92%70%✓ medium

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 · 96 sales · May 7, 2026 – November 2, 2026

Sales ranked by year built and cut into four groups, from the oldest to the newest. Homes built in the same year always stay in the same group, so group sizes can differ a little.

2026-11-03T06:49:18.873747 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 25 21 28 22 96 sales Sales per group Before 2000: 25 sales (26%) 2000–2004: 21 sales (22%) 2005–2007: 28 sales (29%) After 2007: 22 sales (23%)
Bottom line

5.1 Key differences

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

Before 20002000–20042005–2007After 2007
Newer homes After 2007
  • Sell for much more.
  • Are much larger.
  • Sell for more per square foot.
Older homes Before 2000
  • Sell for much less.
  • Are much smaller.
  • Sell for less per square foot.

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 20002000–20042005–2007After 2007Real difference?
Net sale price$704KLowest$901K$1.09M$1.57MHighest✓ large
Net price per SF$257 per SFLowest$265 per SF$290 per SF$357 per SFHighest✓ large
Living area2,732 SFSmallest3,340 SF3,677 SF4,182 SFLargest✓ large
Days on market28 days43 days52 days83 daysunclear
Discount from original list4.5%8.4%7.4%8.1%unclear
Price cut before sale36%57%57%55%unclear
Seller paid closing costs or repairs60%67%43%82%unclear
Has a view60%52%75%91%unclear

5.3 Homes built after 2007 sell for about $869K (124%) more than homes built before 2000

2026-11-03T06:49:18.894385 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 25 sales 2000– 2004 21 sales 2005– 2007 28 sales After 2007 22 sales $0K $500K $1.00M $1.50M $704K $901K $1.09M $1.57M Net sale price, average

The average is $1.57M for homes built after 2007 and $704K for homes built before 2000. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

5.4 Homes built after 2007 sell for about $100 per SF (39%) more than homes built before 2000

2026-11-03T06:49:18.917037 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 25 sales 2000– 2004 21 sales 2005– 2007 28 sales After 2007 22 sales $0 $200 $400 $257 $265 $290 $357 Net price per SF, average

The average is $357 per SF for homes built after 2007 and $257 per SF for homes built before 2000. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

5.5 Homes built after 2007 are about 1,450 SF (53%) larger than homes built before 2000

2026-11-03T06:49:18.938756 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 25 sales 2000– 2004 21 sales 2005– 2007 28 sales After 2007 22 sales 0 2,000 4,000 2,732 3,340 3,677 4,182 Living area (SF), average

The average is 4,182 SF for homes built after 2007 and 2,732 SF for homes built before 2000. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

5.6 Days on market: no clear difference

2026-11-03T06:49:18.960518 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 25 sales 2000– 2004 21 sales 2005– 2007 28 sales After 2007 22 sales 0 25 50 75 28 43 52 83 Days on market, median

The median is 83 days for homes built after 2007 and 28 days for homes built before 2000. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-03T06:49:18.983335 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 25 sales 2000– 2004 21 sales 2005– 2007 28 sales After 2007 22 sales 0.0% 5.0% 10.0% 4.5% 8.4% 7.4% 8.1% Discount from original list, average

The average is 8.1% for homes built after 2007 and 4.5% for homes built before 2000. It does not move in a straight line; homes built 2000–2004 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-03T06:49:19.008413 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% 36 60 60 57 67 52 57 43 75 55 82 91 Before 2000 2000–2004 2005–2007 After 2007

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

  • 55% of homes built after 2007 had a price cut before sale, against 36% of homes built before 2000. Defined in 8.1.7.
  • 82% of homes built after 2007 had the seller pay closing costs or repairs, against 60% of homes built before 2000. Defined in 8.1.8.
  • 91% of homes built after 2007 have a view, against 60% of homes built before 2000. 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 200025 sales2000–200421 sales2005–200728 salesAfter 200722 salesAll96 salesReal difference?
Net sale price average$703,673$901,114$1,090,873$1,573,047$1,059,028✓ large
Net price per SF average$257$265$290$357$291✓ large
Living area average2,7323,3403,6774,1823,473✓ large
Year built median19972003200620102005by design

5.10 The numbers: selling

Before 200025 sales2000–200421 sales2005–200728 salesAfter 200722 salesAll96 salesReal difference?
Days on market median2843528344unclear
Discount from original list average4.5%8.4%7.4%8.1%7.0%unclear
Price cut before sale36%57%57%55%51%unclear
Seller paid closing costs or repairs60%67%43%82%61%unclear
Has a view60%52%75%91%70%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 · 96 sales · May 7, 2026 – November 2, 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.

2026-11-03T06:49:19.026304 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 67 27 94 sales Sales per group View: 67 sales (71%) No view: 27 sales (29%)
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$1.16M$793Kunclear
Net price per SF$303 per SF$260 per SFunclear
Living area3,617 SF3,060 SFunclear
Year built20052001unclear
Days on market53 days34 daysunclear
Discount from original list7.6%5.8%unclear
Price cut before sale57%37%unclear
Seller paid closing costs or repairs67%48%unclear

6.3 Net sale price: no clear difference

2026-11-03T06:49:19.042266 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 67 sales No view 27 sales $0K $500K $1.00M $1.16M $793K Net sale price, average

The average is $1.16M for homes with a view and $793K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-11-03T06:49:19.059125 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 67 sales No view 27 sales $0 $100 $200 $300 $303 $260 Net price per SF, average

The average is $303 per SF for homes with a view and $260 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-11-03T06:49:19.099007 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 67 sales No view 27 sales 0 1,000 2,000 3,000 4,000 3,617 3,060 Living area (SF), average

The average is 3,617 SF for homes with a view and 3,060 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-03T06:49:19.118378 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 67 sales No view 27 sales 1999 2002 2005 2008 2005 2001 Year built: median (dot) and middle half (bar)

The median is 2005 for homes with a view and 2001 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-03T06:49:19.135503 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 67 sales No view 27 sales 0 20 40 60 53 34 Days on market, median

The median is 53 days for homes with a view and 34 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-11-03T06:49:19.154218 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 67 sales No view 27 sales 0.0% 2.0% 4.0% 6.0% 8.0% 7.6% 5.8% Discount from original list, average

The average is 7.6% for homes with a view and 5.8% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-03T06:49:19.172899 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 57 67 37 48 View No view

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

  • 57% of homes with a view had a price cut before sale, against 37% of homes without a view. Defined in 8.1.7.
  • 67% of homes with a view had the seller pay closing costs or repairs, against 48% 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

View67 salesNo view27 salesAll94 salesReal difference?
Net sale price average$1,157,074$793,139$1,052,539unclear
Net price per SF average$303$260$291unclear
Living area average3,6173,0603,457unclear
Year built median200520012005unclear

6.11 The numbers: selling

View67 salesNo view27 salesAll94 salesReal difference?
Days on market median533444unclear
Discount from original list average7.6%5.8%7.1%unclear
Price cut before sale57%37%51%unclear
Seller paid closing costs or repairs67%48%62%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.4.

7. New constructionBasic statistics · 0 sales · May 7, 2026 – November 2, 2026

Homes sold new by the builder in the same 180 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 Steiner Ranch.

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
96 resale sales. Average $1,059,028; median $848,750; standard deviation $607,883; middle half (25th–75th percentile) $681,250–$1,159,750; lowest $498,877, highest $4,490,000. 59 sales had a seller payment; their median payment was $8,000.

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
96 resale sales. Average $291; median $271; standard deviation $71; middle half (25th–75th percentile) $245–$318; lowest $184, highest $595.

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
96 resale sales. Average 3,473; median 3,358; standard deviation 1,007; middle half (25th–75th percentile) 2,777–4,101; lowest 1,865, highest 7,540.

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
96 resale sales. Average 2004; median 2005; standard deviation 6; middle half (25th–75th percentile) 1999–2007; lowest 1988, highest 2020.

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
96 resale sales. Average 68; median 44; standard deviation 71; middle half (25th–75th percentile) 19–94; lowest 0, highest 378. 2 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
96 resale sales. Average 7.0%; median 6.2%; standard deviation 5.9%; middle half (25th–75th percentile) 3.5%–9.7%; lowest −8.0%, highest 32.3%. 3 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
49 of 96 resale sales (51.0%).

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
59 of 96 resale sales (61.5%).

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
67 sales with a view, 27 without, 2 unclassified. Most common View entries: Park/Greenbelt 44, Trees/Woods 37, Neighborhood 36, Hill Country 24, None 12, Panoramic 12, Golf Course 9, Pool 8.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-03 12:45 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “steiner ranch”, “steiner ranch river dance” (case-insensitive). A record is kept when its subdivision name belongs to the Steiner Ranch family, the same rule comparable sales use (it includes Steiner Ranch, River Dance, proven adjacent and priced alike).
The data
Pulled November 3, 2026: 165 closed Steiner Ranch records over the prior year, in ZIP 78732. 53 subdivision spellings kept, the most common: Steiner Ranch (34); Steiner Ranch Ph 01 Sec 09 (9); Steiner Ranch Ph 01 Sec 08 (9); Steiner Ranch Ph 01 Sec 02-A (9); Steiner Ranch Ph 01 Sec 7A (8); Steiner Ranch Ph 02 Sec 05 (7); Steiner Ranch Ph 01 Sec 03 (6); Steiner Ranch Ph 01 Sec 10B (6); Steiner Ranch Ph 01 Sec 06B (5); Steiner Ranch Ph 01 Sec 10C (5); Steiner Ranch Ph 01 Sec 01 (5); Steiner Ranch Ph 01 Sec 10A (3); and 41 more (59 records). Names found by the search but not part of Steiner Ranch, left out: Steiner Ranch Parkside (8); Fairways At Steiner Ranch (2); The Retreat at Steiner Ranch (2); Steiner Ranch Casitas Sub-Cond (2); Lakeview At Steiner Ranch (2); Steiner Ranch Phs 1 Sec 3 (1); Steiner Ranch I River Dance (1); River Dance Steiner Ranch (1); STEINER RANCH PHS 1 SEC 5B (1); STEINER RANCH PHS 2 SEC 3 C (1); Steiner Ranch Phs 1 Sec 10b (1); River Dance Ph 6A, Steiner Ranch (1); River Dance Ph 03- Steiner Ranch (1); Steiner Ranch Casitas (1); View At Steiner Ranch Condomin (1); The Grove at Steiner Ranch (1).

8.2.2 Study window

In simple terms
The most recent 180 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales.
Statistically
CloseDate from May 7, 2026 to November 2, 2026 inclusive.
The data
96 single-family sales in the window: 96 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
96 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
2 sale(s) other than single-family homes (condo, townhome and similar); 1 sale(s) with no original list price

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $685K”.
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 $685K: $498,877–$670,000 (24 sales); $685K–$842K: $685,000–$842,000 (24 sales); $856K–$1.16M: $855,500–$1,158,000 (24 sales); Over $1.16M: $1,165,000–$4,490,000 (24 sales)
Quartiles by living area: Under 2,783 SF: 1,865–2,760 SF (24 sales); 2,783–3,347 SF: 2,783–3,347 SF (24 sales); 3,368–4,100 SF: 3,368–4,100 SF (24 sales); Over 4,100 SF: 4,105–7,540 SF (24 sales)
Quartiles by year built: Before 2000: 1988–1999 (25 sales); 2000–2004: 2000–2004 (21 sales); 2005–2007: 2005–2007 (28 sales); After 2007: 2008–2020 (22 sales)
View and no view: View: MLS lists a view (67 sales); No view: None or Neighborhood (27 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 $1,059,028, median $848,750. Days on market: average 68, median 44: 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
11 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 = 54.933< 0.0001p < 0.0063Yesε² = 0.578large
Living areaKruskal–WallisH = 78.273< 0.0001p < 0.0063Yesε² = 0.824large
Year builtKruskal–WallisH = 30.593< 0.0001p < 0.0063Yesε² = 0.322large
Days on marketKruskal–WallisH = 6.1630.1041p < 0.0063Unclearε² = 0.065medium
Discount from original listKruskal–WallisH = 4.5130.2113p < 0.0063Unclearε² = 0.047small
Price cut before saleChi-squareχ² = 0.4630.9279p < 0.0063UnclearCramér’s V = 0.069negligible
Seller paid closing costs or repairsChi-squareχ² = 0.4830.9224p < 0.0063UnclearCramér’s V = 0.071negligible
Has a viewChi-squareχ² = 21.893< 0.0001p < 0.0063YesCramér’s V = 0.477medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 76.393< 0.0001p < 0.0063Yesε² = 0.804large
Net price per SFKruskal–WallisH = 28.973< 0.0001p < 0.0063Yesε² = 0.305large
Year builtKruskal–WallisH = 27.873< 0.0001p < 0.0063Yesε² = 0.293large
Days on marketKruskal–WallisH = 8.6230.0347p < 0.0063Unclearε² = 0.091medium
Discount from original listKruskal–WallisH = 4.3130.2300p < 0.0063Unclearε² = 0.045small
Price cut before saleChi-squareχ² = 1.4630.6918p < 0.0063UnclearCramér’s V = 0.123small
Seller paid closing costs or repairsChi-squareχ² = 0.8430.8409p < 0.0063UnclearCramér’s V = 0.093negligible
Has a viewChi-squareχ² = 17.9430.0005p < 0.0063YesCramér’s V = 0.432medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 31.113< 0.0001p < 0.0063Yesε² = 0.327large
Net price per SFKruskal–WallisH = 26.623< 0.0001p < 0.0063Yesε² = 0.280large
Living areaKruskal–WallisH = 27.423< 0.0001p < 0.0063Yesε² = 0.289large
Days on marketKruskal–WallisH = 9.8830.0196p < 0.0063Unclearε² = 0.104medium
Discount from original listKruskal–WallisH = 7.3630.0611p < 0.0063Unclearε² = 0.078medium
Price cut before saleChi-squareχ² = 3.1030.3762p < 0.0063UnclearCramér’s V = 0.180small
Seller paid closing costs or repairsChi-squareχ² = 8.2030.0420p < 0.0063UnclearCramér’s V = 0.292small
Has a viewChi-squareχ² = 9.1730.0271p < 0.0063UnclearCramér’s V = 0.309medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 1,206.00—0.0119p < 0.0063Unclearrank-biserial r = 0.333medium
Net price per SFMann–Whitney UU = 1,231.00—0.0064p < 0.0063Unclearrank-biserial r = 0.361medium
Living areaMann–Whitney UU = 1,206.00—0.0119p < 0.0063Unclearrank-biserial r = 0.333medium
Year builtMann–Whitney UU = 1,225.00—0.0073p < 0.0063Unclearrank-biserial r = 0.354medium
Days on marketMann–Whitney UU = 1,133.50—0.0562p < 0.0063Unclearrank-biserial r = 0.253small
Discount from original listMann–Whitney UU = 1,184.50—0.0195p < 0.0063Unclearrank-biserial r = 0.310medium
Price cut before saleChi-squareχ² = 2.9810.0842p < 0.0063UnclearCramér’s V = 0.178small
Seller paid closing costs or repairsChi-squareχ² = 2.9410.0861p < 0.0063UnclearCramér’s V = 0.177small

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 2 sale(s) other than single-family homes (condo, townhome and similar); 1 sale(s) with no original list price. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

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

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 96 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 3, 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.