ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Star Ranch

Hutto, TX 78634
Resale homes · closed Nov 7 – Nov 6, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 7, 2026 · 7:16 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, 365 days
33
single-family resale homes
Median net sale price
$385,000
average $388,850
Median net price per SF
$176
average $172
Median days on market
49 days
average 79 days
1. SummaryResale homes · 33 sales · November 7, 2025 – November 6, 2026

This study looks at the 33 resale homes sold in Star Ranch in the 365 days to November 6, 2026. A full year is used because only 22 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 sold33 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 $363K · 8 sales$363K–$385K · 8 sales$385K–$412K · 9 salesOver $412K · 8 sales
3. Quartiles by net sale priceResale homes · 33 sales · November 7, 2025 – November 6, 2026

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

2026-11-07T07:16:44.961362 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 9 8 33 sales Sales per group Under $363K: 8 sales (24%) $363K–$385K: 8 sales (24%) $385K–$412K: 9 sales (27%) Over $412K: 8 sales (24%)
Bottom line

3.1 Key differences

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

Under $363K$363K–$385K$385K–$412KOver $412K
Higher-priced homes Over $412K
  • Are much larger.
Lower-priced homes Under $363K
  • Are much smaller.

3.2 At a glance

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

Under $363K$363K–$385K$385K–$412KOver $412KReal difference?
Net price per SF$174 per SF$171 per SF$170 per SF$173 per SFunclear
Living area1,883 SFSmallest2,225 SF2,397 SF2,646 SFLargest✓ large
Year built2018201620172016unclear
Days on market37 days22 days118 days13 daysunclear
Discount from original list9.1%6.2%9.5%6.5%unclear
Price cut before sale75%38%78%50%unclear
Seller paid closing costs or repairs88%88%44%100%unclear
Has a view0%38%11%12%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

2026-11-07T07:16:44.990829 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $363K 8 sales $363K– $385K 8 sales $385K– $412K 9 sales Over $412K 8 sales $0 $100 $200 $174 $171 $170 $173 Net price per SF, average

The average is $173 per SF for homes over $412K and $174 per SF for homes under $363K. It does not move in a straight line; homes under $363K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $412K are about 760 SF (41%) larger than homes under $363K

2026-11-07T07:16:45.014127 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $363K 8 sales $363K– $385K 8 sales $385K– $412K 9 sales Over $412K 8 sales 0 1,000 2,000 3,000 1,883 2,225 2,397 2,646 Living area (SF), average

The average is 2,646 SF for homes over $412K and 1,883 SF for homes under $363K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-11-07T07:16:45.041108 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $363K 8 sales $363K– $385K 8 sales $385K– $412K 9 sales Over $412K 8 sales 2014 2016 2018 2020 2018 2016 2017 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over $412K and 2018 for homes under $363K. It does not move in a straight line; homes under $363K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-07T07:16:45.066263 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $363K 8 sales $363K– $385K 8 sales $385K– $412K 9 sales Over $412K 8 sales 0 50 100 37 22 118 13 Days on market, median

The median is 13 days for homes over $412K and 37 days for homes under $363K. It does not move in a straight line; homes $385K–$412K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-07T07:16:45.089025 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $363K 8 sales $363K– $385K 8 sales $385K– $412K 9 sales Over $412K 8 sales 0.0% 5.0% 10.0% 9.1% 6.2% 9.5% 6.5% Discount from original list, average

The average is 6.5% for homes over $412K and 9.1% for homes under $363K. It does not move in a straight line; homes $385K–$412K 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

2026-11-07T07:16:45.120430 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% 75 88 0 38 88 38 78 44 11 50 100 12 Under $363K $363K–$385K $385K–$412K Over $412K

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

  • 50% of homes over $412K had a price cut before sale, against 75% of homes under $363K. Defined in 8.1.7.
  • 100% of homes over $412K had the seller pay closing costs or repairs, against 88% of homes under $363K. Defined in 8.1.8.
  • 12% of homes over $412K have a view, against 0% of homes under $363K. 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 $363K8 sales$363K–$385K8 sales$385K–$412K9 salesOver $412K8 salesAll33 salesReal difference?
Net sale price average$323,806$374,514$401,386$454,128$388,850by design
Net price per SF average$174$171$170$173$172unclear
Living area average1,8832,2252,3972,6462,291✓ large
Year built median20182016201720162017unclear

3.10 The numbers: selling

Under $363K8 sales$363K–$385K8 sales$385K–$412K9 salesOver $412K8 salesAll33 salesReal difference?
Days on market median37221181349unclear
Discount from original list average9.1%6.2%9.5%6.5%7.9%unclear
Price cut before sale75%38%78%50%61%unclear
Seller paid closing costs or repairs88%88%44%100%79%unclear
Has a view0%38%11%12%15%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 · 33 sales · November 7, 2025 – November 6, 2026

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

2026-11-07T07:16:45.142085 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 9 9 8 33 sales Sales per group Under 2,016 SF: 7 sales (21%) 2,016–2,172 SF: 9 sales (27%) 2,191–2,568 SF: 9 sales (27%) Over 2,568 SF: 8 sales (24%)
Bottom line

4.1 Key differences

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

Under 2,016 SF2,016–2,172 SF2,191–2,568 SFOver 2,568 SF
Larger homes Over 2,568 SF
  • Sell for much more.
Smaller homes Under 2,016 SF
  • Sell for much less.

4.2 At a glance

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

Under 2,016 SF2,016–2,172 SF2,191–2,568 SFOver 2,568 SFReal difference?
Net sale price$335KLowest$382K$384K$449KHighest✓ large
Net price per SF$184 per SF$182 per SF$166 per SF$157 per SFunclear
Year built2017201420192016unclear
Days on market49 days19 days51 days156 daysunclear
Discount from original list7.1%4.3%9.1%11.1%unclear
Price cut before sale71%56%56%62%unclear
Seller paid closing costs or repairs86%78%67%88%unclear
Has a view0%33%11%12%unclear

4.3 Homes over 2,568 SF sell for about $114K (34%) more than homes under 2,016 SF

2026-11-07T07:16:45.163914 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,016 SF 7 sales 2,016– 2,172 SF 9 sales 2,191– 2,568 SF 9 sales Over 2,568 SF 8 sales $0K $200K $400K $335K $382K $384K $449K Net sale price, average

The average is $449K for homes over 2,568 SF and $335K for homes under 2,016 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-11-07T07:16:45.187555 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,016 SF 7 sales 2,016– 2,172 SF 9 sales 2,191– 2,568 SF 9 sales Over 2,568 SF 8 sales $0 $100 $200 $184 $182 $166 $157 Net price per SF, average

The average is $157 per SF for homes over 2,568 SF and $184 per SF for homes under 2,016 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-07T07:16:45.211154 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,016 SF 7 sales 2,016– 2,172 SF 9 sales 2,191– 2,568 SF 9 sales Over 2,568 SF 8 sales 2014 2017 2020 2017 2014 2019 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over 2,568 SF and 2017 for homes under 2,016 SF. It does not move in a straight line; homes 2,191–2,568 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-07T07:16:45.234864 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,016 SF 7 sales 2,016– 2,172 SF 9 sales 2,191– 2,568 SF 9 sales Over 2,568 SF 8 sales 0 50 100 150 49 19 51 156 Days on market, median

The median is 156 days for homes over 2,568 SF and 49 days for homes under 2,016 SF. It does not move in a straight line; homes over 2,568 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-07T07:16:45.258323 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,016 SF 7 sales 2,016– 2,172 SF 9 sales 2,191– 2,568 SF 9 sales Over 2,568 SF 8 sales 0.0% 5.0% 10.0% 7.1% 4.3% 9.1% 11.1% Discount from original list, average

The average is 11.1% for homes over 2,568 SF and 7.1% for homes under 2,016 SF. It does not move in a straight line; homes over 2,568 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

2026-11-07T07:16:45.285523 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% 71 86 0 56 78 33 56 67 11 62 88 12 Under 2,016 SF 2,016–2,172 SF 2,191–2,568 SF Over 2,568 SF

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

  • 62% of homes over 2,568 SF had a price cut before sale, against 71% of homes under 2,016 SF. Defined in 8.1.7.
  • 88% of homes over 2,568 SF had the seller pay closing costs or repairs, against 86% of homes under 2,016 SF. Defined in 8.1.8.
  • 12% of homes over 2,568 SF have a view, against 0% of homes under 2,016 SF. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

4.9 The numbers: price and size

Under 2,016 SF7 sales2,016–2,172 SF9 sales2,191–2,568 SF9 salesOver 2,568 SF8 salesAll33 salesReal difference?
Net sale price average$334,929$381,800$384,363$449,012$388,850✓ large
Net price per SF average$184$182$166$157$172unclear
Living area average1,8252,0922,3132,8992,291by design
Year built median20172014201920162017unclear

4.10 The numbers: selling

Under 2,016 SF7 sales2,016–2,172 SF9 sales2,191–2,568 SF9 salesOver 2,568 SF8 salesAll33 salesReal difference?
Days on market median49195115649unclear
Discount from original list average7.1%4.3%9.1%11.1%7.9%unclear
Price cut before sale71%56%56%62%61%unclear
Seller paid closing costs or repairs86%78%67%88%79%unclear
Has a view0%33%11%12%15%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 · 33 sales · November 7, 2025 – November 6, 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.

2026-11-07T07:16:45.307177 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 6 9 9 33 sales Sales per group Before 2014: 9 sales (27%) 2014–2016: 6 sales (18%) 2017–2019: 9 sales (27%) After 2019: 9 sales (27%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

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

5.2 At a glance

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

Before 20142014–20162017–2019After 2019Real difference?
Net sale price$404K$383K$387K$379Kunclear
Net price per SF$170 per SF$178 per SF$177 per SF$165 per SFunclear
Living area2,425 SF2,160 SF2,188 SF2,348 SFunclear
Days on market118 days85 days25 days64 daysunclear
Discount from original list6.8%6.8%5.1%12.5%unclear
Price cut before sale56%83%44%67%unclear
Seller paid closing costs or repairs89%67%78%78%unclear
Has a view11%17%11%22%unclear

5.3 Net sale price: no clear difference

2026-11-07T07:16:45.327825 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 9 sales 2014– 2016 6 sales 2017– 2019 9 sales After 2019 9 sales $0K $200K $400K $404K $383K $387K $379K Net sale price, average

The average is $379K for homes built after 2019 and $404K for homes built before 2014. It does not move in a straight line; homes built before 2014 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-07T07:16:45.350724 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 9 sales 2014– 2016 6 sales 2017– 2019 9 sales After 2019 9 sales $0 $100 $200 $170 $178 $177 $165 Net price per SF, average

The average is $165 per SF for homes built after 2019 and $170 per SF for homes built before 2014. It does not move in a straight line; homes built 2014–2016 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-07T07:16:45.372653 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 9 sales 2014– 2016 6 sales 2017– 2019 9 sales After 2019 9 sales 0 1,000 2,000 2,425 2,160 2,188 2,348 Living area (SF), average

The average is 2,348 SF for homes built after 2019 and 2,425 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.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-07T07:16:45.394517 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 9 sales 2014– 2016 6 sales 2017– 2019 9 sales After 2019 9 sales 0 50 100 118 85 25 64 Days on market, median

The median is 64 days for homes built after 2019 and 118 days for homes built before 2014. It does not move in a straight line; homes built before 2014 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-07T07:16:45.417613 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 9 sales 2014– 2016 6 sales 2017– 2019 9 sales After 2019 9 sales 0.0% 5.0% 10.0% 6.8% 6.8% 5.1% 12.5% Discount from original list, average

The average is 12.5% for homes built after 2019 and 6.8% for homes built before 2014. It does not move in a straight line; homes built after 2019 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

2026-11-07T07:16:45.444062 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% 56 89 11 83 67 17 44 78 11 67 78 22 Before 2014 2014–2016 2017–2019 After 2019

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

  • 67% of homes built after 2019 had a price cut before sale, against 56% of homes built before 2014. Defined in 8.1.7.
  • 78% of homes built after 2019 had the seller pay closing costs or repairs, against 89% of homes built before 2014. Defined in 8.1.8.
  • 22% of homes built after 2019 have a view, against 11% of homes built before 2014. 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 20149 sales2014–20166 sales2017–20199 salesAfter 20199 salesAll33 salesReal difference?
Net sale price average$404,433$382,817$387,222$378,918$388,850unclear
Net price per SF average$170$178$177$165$172unclear
Living area average2,4252,1602,1882,3482,291unclear
Year built median20122016201720212017by design

5.10 The numbers: selling

Before 20149 sales2014–20166 sales2017–20199 salesAfter 20199 salesAll33 salesReal difference?
Days on market median11885256449unclear
Discount from original list average6.8%6.8%5.1%12.5%7.9%unclear
Price cut before sale56%83%44%67%61%unclear
Seller paid closing costs or repairs89%67%78%78%79%unclear
Has a view11%17%11%22%15%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 · 33 sales · November 7, 2025 – November 6, 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.

2026-11-07T07:16:45.464388 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 27 32 sales Sales per group View: 5 sales (16%) No view: 27 sales (84%)
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$388K$388Kunclear
Net price per SF$168 per SF$172 per SFunclear
Living area2,362 SF2,284 SFunclear
Year built20172017unclear
Days on market51 days49 daysunclear
Discount from original list8.5%7.6%unclear
Price cut before sale60%59%unclear
Seller paid closing costs or repairs100%74%unclear

6.3 Net sale price: no clear difference

2026-11-07T07:16:45.481870 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 27 sales $0K $100K $200K $300K $400K $388K $388K Net sale price, average

The average is $388K for homes with a view and $388K 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

2026-11-07T07:16:45.501639 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 27 sales $0 $50 $100 $150 $200 $168 $172 Net price per SF, average

The average is $168 per SF for homes with a view and $172 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

2026-11-07T07:16:45.521366 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 27 sales 0 1,000 2,000 2,362 2,284 Living area (SF), average

The average is 2,362 SF for homes with a view and 2,284 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-07T07:16:45.579290 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 27 sales 2014 2016 2018 2020 2017 2017 Year built: median (dot) and middle half (bar)

The median is 2017 for homes with a view and 2017 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-07T07:16:45.598145 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 27 sales 0 20 40 60 51 49 Days on market, median

The median is 51 days for homes with a view and 49 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

2026-11-07T07:16:45.618710 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 27 sales 0.0% 2.5% 5.0% 7.5% 10.0% 8.5% 7.6% Discount from original list, average

The average is 8.5% for homes with a view and 7.6% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-07T07:16:45.638319 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 60 100 59 74 View No view

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

  • 60% of homes with a view had a price cut before sale, against 59% 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 74% of homes without a view. Defined in 8.1.8.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance

6.10 The numbers: price and size

View5 salesNo view27 salesAll32 salesReal difference?
Net sale price average$388,405$388,316$388,330unclear
Net price per SF average$168$172$171unclear
Living area average2,3622,2842,296unclear
Year built median201720172017unclear

6.11 The numbers: selling

View5 salesNo view27 salesAll32 salesReal difference?
Days on market median514950unclear
Discount from original list average8.5%7.6%7.7%unclear
Price cut before sale60%59%59%unclear
Seller paid closing costs or repairs100%74%78%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 · November 7, 2025 – November 6, 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 Star 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
33 resale sales. Average $388,850; median $385,000; standard deviation $52,338; middle half (25th–75th percentile) $363,000–$412,000; lowest $277,000, highest $530,000. 26 sales had a seller payment; their median payment was $5,000.

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
33 resale sales. Average $172; median $176; standard deviation $20; middle half (25th–75th percentile) $166–$184; lowest $123, highest $204.

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
33 resale sales. Average 2,291; median 2,191; standard deviation 416; middle half (25th–75th percentile) 2,016–2,568; lowest 1,715, highest 3,357.

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
33 resale sales. Average 2016; median 2017; standard deviation 5; middle half (25th–75th percentile) 2013–2020; lowest 2003, 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
33 resale sales. Average 79; median 49; standard deviation 80; middle half (25th–75th percentile) 12–128; lowest 2, highest 240. 0 sales went under contract on their listing date (0 days).

8.1.6 Discount from original list

In simple terms
How far below the first asking price the home sold, after seller payments. It measures how much negotiating room sellers gave up. A negative figure means the home sold above its first asking price.
Statistically
Discount % = (OriginalListPrice − Net) ÷ OriginalListPrice × 100, per sale; summarized by the mean.
The data
33 resale sales. Average 7.9%; median 6.2%; standard deviation 7.3%; middle half (25th–75th percentile) 3.0%–11.0%; lowest −2.4%, highest 28.1%. 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
20 of 33 resale sales (60.6%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
26 of 33 resale sales (78.8%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
5 sales with a view, 27 without, 1 unclassified. Most common View entries: None 19, Neighborhood 9, Trees/Woods 2, Golf Course 1, See Remarks 1, Panoramic 1, Park/Greenbelt 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
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-07 13:15 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Hutto, SubdivisionName contains any of “star ranch” (case-insensitive). A record is kept when its subdivision name belongs to the Star Ranch family, the same rule comparable sales use.
The data
Pulled November 7, 2026: 34 closed Star Ranch records over the prior year, in ZIP 78634. 15 subdivision spellings kept, the most common: Star Ranch (16); Star Ranch Ph 7 Sec 7 (3); Star Ranch Sec 7 Ph 5 (2); Star Ranch Ph 2 Sec 7 (2); Star Ranch Ph 5 Sec 7 (1); Star Ranch Sec 5 Ph 2 (1); Star Ranch Ph 1A Sec 7 (1); Star Ranch Sec 7 Ph 4 (1); Star Ranch Sec 01 (1); Star Ranch Sec 02 (1); Star Ranch Ph Ib Sec 7 (1); STAR RANCH SEC 7 PH 6 (1); and 3 more (3 records). Names found by the search but not part of Star Ranch, left out: Villas/Star Ranch Sec 22 (1); Villas/Star Ranch Condos Sec 2 (1); Villas/Star Ranch (1); Villas/Star Ranch Condos (1); Villas/Star Ranch Condos Ph 3 (1); Star Ranch Prcl 23 (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 22 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 7, 2025 to November 6, 2026 inclusive.
The data
33 single-family sales in the window: 33 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
33 resale; 0 new construction.

8.2.4 Sales left out

In simple terms
A few records cannot be used as entered and are left out before any analysis.
Statistically
Excluded: PropertySubType other than Single Family Residence; no OriginalListPrice; LivingArea under 400 SF; seller payments above 10% of ClosePrice (treated as entry errors).
The data
1 sale(s) with concessions above 10% of 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 $363K”.
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 $363K: $277,000–$350,000 (8 sales); $363K–$385K: $363,000–$384,915 (8 sales); $385K–$412K: $385,000–$412,000 (9 sales); Over $412K: $412,325–$530,000 (8 sales)
Quartiles by living area: Under 2,016 SF: 1,715–2,009 SF (7 sales); 2,016–2,172 SF: 2,016–2,172 SF (9 sales); 2,191–2,568 SF: 2,191–2,568 SF (9 sales); Over 2,568 SF: 2,637–3,357 SF (8 sales)
Quartiles by year built: Before 2014: 2003–2013 (9 sales); 2014–2016: 2014–2016 (6 sales); 2017–2019: 2017–2019 (9 sales); After 2019: 2020–2022 (9 sales)
View and no view: View: MLS lists a view (5 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 $388,850, median $385,000. Days on market: average 79, median 49: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

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

8.2.8 Mann–Whitney U test

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

8.2.9 Chi-square test

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

8.2.10 Real difference (significance)

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

8.2.11 Size of a difference

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

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 0.1730.9828p < 0.0063Unclearε² = 0.005negligible
Living areaKruskal–WallisH = 18.0130.0004p < 0.0063Yesε² = 0.563large
Year builtKruskal–WallisH = 0.1430.9872p < 0.0063Unclearε² = 0.004negligible
Days on marketKruskal–WallisH = 4.1930.2420p < 0.0063Unclearε² = 0.131medium
Discount from original listKruskal–WallisH = 1.6930.6393p < 0.0063Unclearε² = 0.053small
Price cut before saleChi-squareχ² = 3.9730.2645p < 0.0063UnclearCramér’s V = 0.347medium
Seller paid closing costs or repairsChi-squareχ² = 9.2330.0264p < 0.0063UnclearCramér’s V = 0.529large
Has a viewChi-squareχ² = 4.6930.1956p < 0.0063UnclearCramér’s V = 0.377medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 18.9030.0003p < 0.0063Yesε² = 0.591large
Net price per SFKruskal–WallisH = 10.0630.0180p < 0.0063Unclearε² = 0.314large
Year builtKruskal–WallisH = 5.9630.1136p < 0.0063Unclearε² = 0.186large
Days on marketKruskal–WallisH = 2.7430.4339p < 0.0063Unclearε² = 0.086medium
Discount from original listKruskal–WallisH = 2.6130.4560p < 0.0063Unclearε² = 0.082medium
Price cut before saleChi-squareχ² = 0.5530.9083p < 0.0063UnclearCramér’s V = 0.129small
Seller paid closing costs or repairsChi-squareχ² = 1.3630.7147p < 0.0063UnclearCramér’s V = 0.203small
Has a viewChi-squareχ² = 3.7230.2931p < 0.0063UnclearCramér’s V = 0.336medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 1.0630.7856p < 0.0063Unclearε² = 0.033small
Net price per SFKruskal–WallisH = 1.0130.7994p < 0.0063Unclearε² = 0.031small
Living areaKruskal–WallisH = 1.9830.5764p < 0.0063Unclearε² = 0.062medium
Days on marketKruskal–WallisH = 2.8230.4210p < 0.0063Unclearε² = 0.088medium
Discount from original listKruskal–WallisH = 2.8330.4193p < 0.0063Unclearε² = 0.088medium
Price cut before saleChi-squareχ² = 2.5230.4722p < 0.0063UnclearCramér’s V = 0.276small
Seller paid closing costs or repairsChi-squareχ² = 1.0930.7800p < 0.0063UnclearCramér’s V = 0.182small
Has a viewChi-squareχ² = 0.5930.8989p < 0.0063UnclearCramér’s V = 0.134small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 69.00—0.9599p < 0.0063Unclearrank-biserial r = 0.022negligible
Net price per SFMann–Whitney UU = 63.00—0.8406p < 0.0063Unclearrank-biserial r = 0.067negligible
Living areaMann–Whitney UU = 76.00—0.6779p < 0.0063Unclearrank-biserial r = 0.126small
Year builtMann–Whitney UU = 80.00—0.5309p < 0.0063Unclearrank-biserial r = 0.185small
Days on marketMann–Whitney UU = 67.00—1.0000p < 0.0063Unclearrank-biserial r = 0.007negligible
Discount from original listMann–Whitney UU = 72.00—0.8355p < 0.0063Unclearrank-biserial r = 0.067negligible
Price cut before saleChi-squareχ² = 0.0010.9753p < 0.0063UnclearCramér’s V = 0.005negligible
Seller paid closing costs or repairsChi-squareχ² = 1.6610.1977p < 0.0063UnclearCramér’s V = 0.228small

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 1 sale(s) with concessions above 10% of 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 33 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 7, 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.