ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Big Sky Ranch

Dripping Springs, TX 78620
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 · 7:02 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
30
single-family resale homes
Median net sale price
$430,000
average $427,781
Median net price per SF
$184
average $188
Median days on market
43 days
average 67 days
1. SummaryResale homes · 30 sales · October 26, 2025 – October 25, 2026

This study looks at the 30 resale homes sold in Big Sky Ranch in the 365 days to October 25, 2026. A full year is used because only 14 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 sold30 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 $366K · 8 sales$366K–$420K · 7 sales$440K–$474K · 7 salesOver $474K · 8 sales
3. Quartiles by net sale priceResale homes · 30 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.

2026-10-26T07:03:03.351557 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Under $366K: 8 sales (27%) $366K–$420K: 7 sales (23%) $440K–$474K: 7 sales (23%) Over $474K: 8 sales (27%)
Bottom line

3.1 Key differences

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

Under $366K$366K–$420K$440K–$474KOver $474K
Higher-priced homes Over $474K
  • Are much larger.
Lower-priced homes Under $366K
  • 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 $366K$366K–$420K$440K–$474KOver $474KReal difference?
Net price per SF$191 per SF$194 per SF$189 per SF$179 per SFunclear
Living area1,829 SFSmallest2,018 SF2,433 SF2,928 SFLargest✓ large
Year built2022202020232022unclear
Days on market44 days20 days52 days46 daysunclear
Discount from original list5.5%3.7%5.9%5.3%unclear
Price cut before sale50%43%57%88%unclear
Seller paid closing costs or repairs62%57%71%62%unclear
Has a view12%14%57%0%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

2026-10-26T07:03:03.381176 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $366K 8 sales $366K– $420K 7 sales $440K– $474K 7 sales Over $474K 8 sales $0 $100 $200 $191 $194 $189 $179 Net price per SF, average

The average is $179 per SF for homes over $474K and $191 per SF for homes under $366K. It does not move in a straight line; homes $366K–$420K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $474K are about 1,100 SF (60%) larger than homes under $366K

2026-10-26T07:03:03.403889 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $366K 8 sales $366K– $420K 7 sales $440K– $474K 7 sales Over $474K 8 sales 0 1,000 2,000 3,000 1,829 2,018 2,433 2,928 Living area (SF), average

The average is 2,928 SF for homes over $474K and 1,829 SF for homes under $366K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-26T07:03:03.428539 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $366K 8 sales $366K– $420K 7 sales $440K– $474K 7 sales Over $474K 8 sales 2020 2021 2022 2023 2022 2020 2023 2022 Year built: median (dot) and middle half (bar)

The median is 2022 for homes over $474K and 2022 for homes under $366K. It does not move in a straight line; homes $440K–$474K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:03:03.451749 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $366K 8 sales $366K– $420K 7 sales $440K– $474K 7 sales Over $474K 8 sales 0 20 40 60 44 20 52 46 Days on market, median

The median is 46 days for homes over $474K and 44 days for homes under $366K. It does not move in a straight line; homes $440K–$474K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:03:03.474199 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $366K 8 sales $366K– $420K 7 sales $440K– $474K 7 sales Over $474K 8 sales 0.0% 2.0% 4.0% 6.0% 5.5% 3.7% 5.9% 5.3% Discount from original list, average

The average is 5.3% for homes over $474K and 5.5% for homes under $366K. It does not move in a straight line; homes $440K–$474K 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

2026-10-26T07:03:03.505571 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% 50 62 12 43 57 14 57 71 57 88 62 0 Under $366K $366K–$420K $440K–$474K Over $474K

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

  • 88% of homes over $474K had a price cut before sale, against 50% of homes under $366K. Defined in 8.1.7.
  • 62% of homes over $474K had the seller pay closing costs or repairs, against 62% of homes under $366K. Defined in 8.1.8.
  • 0% of homes over $474K have a view, against 12% of homes under $366K. 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 $366K8 sales$366K–$420K7 sales$440K–$474K7 salesOver $474K8 salesAll30 salesReal difference?
Net sale price average$347,506$387,399$451,893$522,293$427,781by design
Net price per SF average$191$194$189$179$188unclear
Living area average1,8292,0182,4332,9282,307✓ large
Year built median20222020202320222022unclear

3.10 The numbers: selling

Under $366K8 sales$366K–$420K7 sales$440K–$474K7 salesOver $474K8 salesAll30 salesReal difference?
Days on market median4420524643unclear
Discount from original list average5.5%3.7%5.9%5.3%5.1%unclear
Price cut before sale50%43%57%88%60%unclear
Seller paid closing costs or repairs62%57%71%62%63%unclear
Has a view12%14%57%0%20%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 · 30 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.

2026-10-26T07:03:03.527133 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Under 1,887 SF: 8 sales (27%) 1,887–2,174 SF: 7 sales (23%) 2,213–2,586 SF: 7 sales (23%) Over 2,586 SF: 8 sales (27%)
Bottom line

4.1 Key differences

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

Under 1,887 SF1,887–2,174 SF2,213–2,586 SFOver 2,586 SF
Larger homes Over 2,586 SF
  • Sell for much more.
  • Sell for less per square foot.
Smaller homes Under 1,887 SF
  • Sell for much less.
  • 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 1,887 SF1,887–2,174 SF2,213–2,586 SFOver 2,586 SFReal difference?
Net sale price$365KLowest$390K$432K$521KHighest✓ large
Net price per SF$206 per SFHighest$195 per SF$179 per SF$172 per SFLowest✓ large
Year built2022202120202023unclear
Days on market17 days40 days44 days70 daysunclear
Discount from original list3.2%5.6%5.1%6.6%unclear
Price cut before sale25%43%86%88%unclear
Seller paid closing costs or repairs38%86%71%62%unclear
Has a view12%43%14%12%unclear

4.3 Homes over 2,586 SF sell for about $156K (43%) more than homes under 1,887 SF

2026-10-26T07:03:03.548447 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,887 SF 8 sales 1,887– 2,174 SF 7 sales 2,213– 2,586 SF 7 sales Over 2,586 SF 8 sales $0K $200K $400K $600K $365K $390K $432K $521K Net sale price, average

The average is $521K for homes over 2,586 SF and $365K for homes under 1,887 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 2,586 SF sell for about $33 per SF (16%) less than homes under 1,887 SF

2026-10-26T07:03:03.571833 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,887 SF 8 sales 1,887– 2,174 SF 7 sales 2,213– 2,586 SF 7 sales Over 2,586 SF 8 sales $0 $100 $200 $206 $195 $179 $172 Net price per SF, average

The average is $172 per SF for homes over 2,586 SF and $206 per SF for homes under 1,887 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

2026-10-26T07:03:03.596958 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,887 SF 8 sales 1,887– 2,174 SF 7 sales 2,213– 2,586 SF 7 sales Over 2,586 SF 8 sales 2020 2021 2022 2023 2024 2022 2021 2020 2023 Year built: median (dot) and middle half (bar)

The median is 2023 for homes over 2,586 SF and 2022 for homes under 1,887 SF. It does not move in a straight line; homes over 2,586 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:03:03.621159 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,887 SF 8 sales 1,887– 2,174 SF 7 sales 2,213– 2,586 SF 7 sales Over 2,586 SF 8 sales 0 25 50 75 17 40 44 70 Days on market, median

The median is 70 days for homes over 2,586 SF and 17 days for homes under 1,887 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:03:03.643823 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,887 SF 8 sales 1,887– 2,174 SF 7 sales 2,213– 2,586 SF 7 sales Over 2,586 SF 8 sales 0.0% 2.0% 4.0% 6.0% 3.2% 5.6% 5.1% 6.6% Discount from original list, average

The average is 6.6% for homes over 2,586 SF and 3.2% for homes under 1,887 SF. It does not move in a straight line; homes over 2,586 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

2026-10-26T07:03:03.672068 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% 25 38 12 43 86 43 86 71 14 88 62 12 Under 1,887 SF 1,887–2,174 SF 2,213–2,586 SF Over 2,586 SF

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

  • 88% of homes over 2,586 SF had a price cut before sale, against 25% of homes under 1,887 SF. Defined in 8.1.7.
  • 62% of homes over 2,586 SF had the seller pay closing costs or repairs, against 38% of homes under 1,887 SF. Defined in 8.1.8.
  • 12% of homes over 2,586 SF have a view, against 12% of homes under 1,887 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 1,887 SF8 sales1,887–2,174 SF7 sales2,213–2,586 SF7 salesOver 2,586 SF8 salesAll30 salesReal difference?
Net sale price average$364,501$389,936$431,876$520,593$427,781✓ large
Net price per SF average$206$195$179$172$188✓ large
Living area average1,7731,9912,4183,0212,307by design
Year built median20222021202020232022unclear

4.10 The numbers: selling

Under 1,887 SF8 sales1,887–2,174 SF7 sales2,213–2,586 SF7 salesOver 2,586 SF8 salesAll30 salesReal difference?
Days on market median1740447043unclear
Discount from original list average3.2%5.6%5.1%6.6%5.1%unclear
Price cut before sale25%43%86%88%60%unclear
Seller paid closing costs or repairs38%86%71%62%63%unclear
Has a view12%43%14%12%20%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. Groups by year builtResale homes · 30 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. Only 3 groups are shown: homes here share a few year built values, and no group may hold fewer than 3 sales.

2026-10-26T07:03:03.691785 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 8 11 30 sales Sales per group Before 2021: 11 sales (37%) 2021–2022: 8 sales (27%) After 2022: 11 sales (37%)
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 20212021–2022After 2022Real difference?
Net sale price$407K$395K$472Kunclear
Net price per SF$190 per SF$197 per SF$180 per SFunclear
Living area2,156 SF2,025 SF2,663 SFunclear
Days on market33 days41 days69 daysunclear
Discount from original list4.4%5.2%5.8%unclear
Price cut before sale55%50%73%unclear
Seller paid closing costs or repairs64%62%64%unclear
Has a view18%0%36%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:03:03.711273 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2021 11 sales 2021– 2022 8 sales After 2022 11 sales $0K $200K $400K $407K $395K $472K Net sale price, average

The average is $472K for homes built after 2022 and $407K for homes built before 2021. It does not move in a straight line; homes built after 2022 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:03:03.732587 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2021 11 sales 2021– 2022 8 sales After 2022 11 sales $0 $100 $200 $190 $197 $180 Net price per SF, average

The average is $180 per SF for homes built after 2022 and $190 per SF for homes built before 2021. It does not move in a straight line; homes built 2021–2022 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:03:03.752019 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2021 11 sales 2021– 2022 8 sales After 2022 11 sales 0 1,000 2,000 3,000 2,156 2,025 2,663 Living area (SF), average

The average is 2,663 SF for homes built after 2022 and 2,156 SF for homes built before 2021. It does not move in a straight line; homes built after 2022 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:03:03.772135 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2021 11 sales 2021– 2022 8 sales After 2022 11 sales 0 25 50 75 33 41 69 Days on market, median

The median is 69 days for homes built after 2022 and 33 days for homes built before 2021. 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

2026-10-26T07:03:03.793930 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2021 11 sales 2021– 2022 8 sales After 2022 11 sales 0.0% 2.0% 4.0% 6.0% 4.4% 5.2% 5.8% Discount from original list, average

The average is 5.8% for homes built after 2022 and 4.4% for homes built before 2021. It rises step by step from the lowest range to the highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:03:03.817554 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% 55 64 18 50 62 0 73 64 36 Before 2021 2021–2022 After 2022

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

  • 73% of homes built after 2022 had a price cut before sale, against 55% of homes built before 2021. Defined in 8.1.7.
  • 64% of homes built after 2022 had the seller pay closing costs or repairs, against 64% of homes built before 2021. Defined in 8.1.8.
  • 36% of homes built after 2022 have a view, against 18% of homes built before 2021. 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 202111 sales2021–20228 salesAfter 202211 salesAll30 salesReal difference?
Net sale price average$407,448$395,190$471,818$427,781unclear
Net price per SF average$190$197$180$188unclear
Living area average2,1562,0252,6632,307unclear
Year built median2020202220232022by design

5.10 The numbers: selling

Before 202111 sales2021–20228 salesAfter 202211 salesAll30 salesReal difference?
Days on market median33416943unclear
Discount from original list average4.4%5.2%5.8%5.1%unclear
Price cut before sale55%50%73%60%unclear
Seller paid closing costs or repairs64%62%64%63%unclear
Has a view18%0%36%20%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 · 30 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. 4 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T07:03:03.835634 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 20 26 sales Sales per group View: 6 sales (23%) No view: 20 sales (77%)
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$421K$434Kunclear
Net price per SF$193 per SF$188 per SFunclear
Living area2,215 SF2,341 SFunclear
Year built20232022unclear
Days on market28 days46 daysunclear
Discount from original list4.4%5.2%unclear
Price cut before sale50%65%unclear
Seller paid closing costs or repairs67%65%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:03:03.853470 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 6 sales No view 20 sales $0K $200K $400K $421K $434K Net sale price, average

The average is $421K for homes with a view and $434K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-10-26T07:03:03.871954 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 6 sales No view 20 sales $0 $50 $100 $150 $200 $193 $188 Net price per SF, average

The average is $193 per SF for homes with a view and $188 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-10-26T07:03:03.890506 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 6 sales No view 20 sales 0 1,000 2,000 2,215 2,341 Living area (SF), average

The average is 2,215 SF for homes with a view and 2,341 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:03:03.986248 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 6 sales No view 20 sales 2020 2021 2022 2023 2023 2022 Year built: median (dot) and middle half (bar)

The median is 2023 for homes with a view and 2022 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:03:04.005821 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 6 sales No view 20 sales 0 20 40 28 46 Days on market, median

The median is 28 days for homes with a view and 46 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-10-26T07:03:04.023610 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 6 sales No view 20 sales 0.0% 2.0% 4.0% 6.0% 4.4% 5.2% Discount from original list, average

The average is 4.4% for homes with a view and 5.2% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:03:04.043519 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 50 67 65 65 View No view

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

  • 50% of homes with a view had a price cut before sale, against 65% 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 65% 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

View6 salesNo view20 salesAll26 salesReal difference?
Net sale price average$420,818$433,602$430,652unclear
Net price per SF average$193$188$189unclear
Living area average2,2152,3412,312unclear
Year built median202320222022unclear

6.11 The numbers: selling

View6 salesNo view20 salesAll26 salesReal difference?
Days on market median284642unclear
Discount from original list average4.4%5.2%5.0%unclear
Price cut before sale50%65%62%unclear
Seller paid closing costs or repairs67%65%65%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 · 49 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: 49 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 Big Sky Ranch.
MeasureAverageMedian
Sales49
Net sale price$480,666$474,249
Net price per SF$195$202
Living area (SF)2,5262,585
Days on market5338
Discount from original list8.3%7.7%
Price cut before sale45% of sales
Seller paid closing costs or repairs94% of sales
Year built2025–2026

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

8. AppendixMeasures, methods and tests

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

8.1 Measures

8.1.1 Net sale price

In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
30 resale sales. Average $427,781; median $430,000; standard deviation $74,206; middle half (25th–75th percentile) $361,625–$476,600; lowest $311,850, highest $598,500. 19 sales had a seller payment; their median payment was $6,000.

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
30 resale sales. Average $188; median $184; standard deviation $18; middle half (25th–75th percentile) $172–$198; lowest $164, highest $226.

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
30 resale sales. Average 2,307; median 2,194; standard deviation 523; middle half (25th–75th percentile) 1,882–2,703; lowest 1,630, highest 3,369.

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
30 resale sales. Average 2022; median 2022; standard deviation 1; middle half (25th–75th percentile) 2020–2023; lowest 2020, highest 2024.

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
30 resale sales. Average 67; median 43; standard deviation 81; middle half (25th–75th percentile) 18–75; lowest 5, highest 397. 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
30 resale sales. Average 5.1%; median 4.5%; standard deviation 3.2%; middle half (25th–75th percentile) 2.9%–7.5%; lowest 0.0%, highest 11.3%. 0 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
18 of 30 resale sales (60.0%).

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
19 of 30 resale sales (63.3%).

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
6 sales with a view, 20 without, 4 unclassified. Most common View entries: Neighborhood 10, None 10, See Remarks 6, Hill Country 4, Park/Greenbelt 3, Trees/Woods 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 = Dripping Springs, SubdivisionName contains any of “big sky ranch” (case-insensitive). A record is kept when its subdivision name belongs to the Big Sky Ranch family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 79 closed Big Sky Ranch records over the prior year, in ZIP 78620. 8 subdivision spellings kept: Big Sky Ranch (59); Big Sky Ranch Ph 1 At Dripping Spgs (7); Big Sky Ranch Ph 3 At Dripping Spgs (5); Big Sky Ranch Ph 2 At Dripping Spgs (4); Big Sky Ranch Ph 1 (1); Big Sky Ranch Ph 4 At Dripping Spgs (1); Big Sky Ranch Ph One At Dripping Spgs (1); BIG SKY RANCH PHASE 2 AT DRIPPING SPRING (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 14 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
79 single-family sales in the window: 30 resale, 49 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
30 resale; 49 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 $366K”.
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 $366K: $311,850–$360,000 (8 sales); $366K–$420K: $366,500–$420,000 (7 sales); $440K–$474K: $440,000–$473,900 (7 sales); Over $474K: $477,500–$598,500 (8 sales)
Quartiles by living area: Under 1,887 SF: 1,630–1,880 SF (8 sales); 1,887–2,174 SF: 1,887–2,174 SF (7 sales); 2,213–2,586 SF: 2,213–2,586 SF (7 sales); Over 2,586 SF: 2,742–3,369 SF (8 sales)
Groups by year built: Before 2021: 2020–2020 (11 sales); 2021–2022: 2021–2022 (8 sales); After 2022: 2023–2024 (11 sales)
View and no view: View: MLS lists a view (6 sales); No view: None or Neighborhood (20 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 $427,781, median $430,000. Days on market: average 67, median 43: 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; Groups 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
3 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 = 3.3630.3400p < 0.0063Unclearε² = 0.116medium
Living areaKruskal–WallisH = 20.5430.0001p < 0.0063Yesε² = 0.708large
Year builtKruskal–WallisH = 5.7930.1224p < 0.0063Unclearε² = 0.200large
Days on marketKruskal–WallisH = 2.6230.4532p < 0.0063Unclearε² = 0.091medium
Discount from original listKruskal–WallisH = 1.7630.6238p < 0.0063Unclearε² = 0.061medium
Price cut before saleChi-squareχ² = 3.7430.2915p < 0.0063UnclearCramér’s V = 0.353medium
Seller paid closing costs or repairsChi-squareχ² = 0.3230.9566p < 0.0063UnclearCramér’s V = 0.103small
Has a viewChi-squareχ² = 8.4630.0374p < 0.0063UnclearCramér’s V = 0.531large

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 20.2230.0002p < 0.0063Yesε² = 0.697large
Net price per SFKruskal–WallisH = 17.9230.0005p < 0.0063Yesε² = 0.618large
Year builtKruskal–WallisH = 7.5130.0573p < 0.0063Unclearε² = 0.259large
Days on marketKruskal–WallisH = 6.1230.1058p < 0.0063Unclearε² = 0.211large
Discount from original listKruskal–WallisH = 4.4730.2149p < 0.0063Unclearε² = 0.154large
Price cut before saleChi-squareχ² = 9.3930.0245p < 0.0063UnclearCramér’s V = 0.559large
Seller paid closing costs or repairsChi-squareχ² = 4.0130.2605p < 0.0063UnclearCramér’s V = 0.366medium
Has a viewChi-squareχ² = 2.9930.3930p < 0.0063UnclearCramér’s V = 0.316medium

8.3.3 Groups by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 4.4920.1060p < 0.0063Unclearε² = 0.155large
Net price per SFKruskal–WallisH = 5.7820.0555p < 0.0063Unclearε² = 0.199large
Living areaKruskal–WallisH = 7.2320.0269p < 0.0063Unclearε² = 0.249large
Days on marketKruskal–WallisH = 2.8520.2404p < 0.0063Unclearε² = 0.098medium
Discount from original listKruskal–WallisH = 0.9420.6248p < 0.0063Unclearε² = 0.032small
Price cut before saleChi-squareχ² = 1.2120.5455p < 0.0063UnclearCramér’s V = 0.201small
Seller paid closing costs or repairsChi-squareχ² = 0.0020.9984p < 0.0063UnclearCramér’s V = 0.010negligible
Has a viewChi-squareχ² = 3.8620.1449p < 0.0063UnclearCramér’s V = 0.359medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 56.00—0.8313p < 0.0063Unclearrank-biserial r = 0.067negligible
Net price per SFMann–Whitney UU = 65.00—0.7897p < 0.0063Unclearrank-biserial r = 0.083negligible
Living areaMann–Whitney UU = 57.00—0.8789p < 0.0063Unclearrank-biserial r = 0.050negligible
Year builtMann–Whitney UU = 73.00—0.4295p < 0.0063Unclearrank-biserial r = 0.217small
Days on marketMann–Whitney UU = 49.00—0.5220p < 0.0063Unclearrank-biserial r = 0.183small
Discount from original listMann–Whitney UU = 52.00—0.6565p < 0.0063Unclearrank-biserial r = 0.133small
Price cut before saleChi-squareχ² = 0.4410.5077p < 0.0063UnclearCramér’s V = 0.130small
Seller paid closing costs or repairsChi-squareχ² = 0.0110.9400p < 0.0063UnclearCramér’s V = 0.015negligible

8.4 Data notes

Left out of the analysis: 49 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 30 closed MLS resale sales; the 49 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.