ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Garlic Creek West

Buda, TX 78610
Resale homes · closed Nov 5 – Nov 4, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 5, 2026 · 2:33 PM 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
32
single-family resale homes
Median net sale price
$392,000
average $401,659
Median net price per SF
$169
average $170
Median days on market
48 days
average 61 days
1. SummaryResale homes · 32 sales · November 5, 2025 – November 4, 2026

This study looks at the 32 resale homes sold in Garlic Creek West in the 365 days to November 4, 2026. A full year is used because only 15 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 sold32 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 $372K · 8 sales$372K–$387K · 8 sales$397K–$439K · 8 salesOver $439K · 8 sales
3. Quartiles by net sale priceResale homes · 32 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T14:33:13.026387 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 8 8 32 sales Sales per group Under $372K: 8 sales (25%) $372K–$387K: 8 sales (25%) $397K–$439K: 8 sales (25%) Over $439K: 8 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 $372K$372K–$387K$397K–$439KOver $439K
Higher-priced homes Over $439K
  • Are much larger.
Lower-priced homes Under $372K
  • 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 $372K$372K–$387K$397K–$439KOver $439KReal difference?
Net price per SF$188 per SF$175 per SF$162 per SF$156 per SFunclear
Living area1,754 SFSmallest2,222 SF2,596 SF3,152 SFLargest✓ large
Year built2012201320082014unclear
Days on market40 days52 days38 days52 daysunclear
Discount from original list8.0%6.3%6.4%4.3%unclear
Price cut before sale75%50%38%50%unclear
Seller paid closing costs or repairs62%88%88%50%unclear
Has a view25%25%0%38%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

2026-11-05T14:33:13.053903 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $372K 8 sales $372K– $387K 8 sales $397K– $439K 8 sales Over $439K 8 sales $0 $100 $200 $188 $175 $162 $156 Net price per SF, average

The average is $156 per SF for homes over $439K and $188 per SF for homes under $372K. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $439K are about 1,400 SF (80%) larger than homes under $372K

2026-11-05T14:33:13.075854 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $372K 8 sales $372K– $387K 8 sales $397K– $439K 8 sales Over $439K 8 sales 0 1,000 2,000 3,000 1,754 2,222 2,596 3,152 Living area (SF), average

The average is 3,152 SF for homes over $439K and 1,754 SF for homes under $372K. 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

2026-11-05T14:33:13.099566 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $372K 8 sales $372K– $387K 8 sales $397K– $439K 8 sales Over $439K 8 sales 2008 2010 2012 2014 2012 2013 2008 2014 Year built: median (dot) and middle half (bar)

The median is 2014 for homes over $439K and 2012 for homes under $372K. It does not move in a straight line; homes over $439K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-05T14:33:13.121097 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $372K 8 sales $372K– $387K 8 sales $397K– $439K 8 sales Over $439K 8 sales 0 20 40 60 40 52 38 52 Days on market, median

The median is 52 days for homes over $439K and 40 days for homes under $372K. It does not move in a straight line; homes $372K–$387K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-05T14:33:13.143654 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $372K 8 sales $372K– $387K 8 sales $397K– $439K 8 sales Over $439K 8 sales 0.0% 2.5% 5.0% 7.5% 8.0% 6.3% 6.4% 4.3% Discount from original list, average

The average is 4.3% for homes over $439K and 8.0% for homes under $372K. It does not move in a straight line; homes under $372K 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

2026-11-05T14:33:13.173524 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 62 25 50 88 25 38 88 0 50 50 38 Under $372K $372K–$387K $397K–$439K Over $439K

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

  • 50% of homes over $439K had a price cut before sale, against 75% of homes under $372K. Defined in 8.1.7.
  • 50% of homes over $439K had the seller pay closing costs or repairs, against 62% of homes under $372K. Defined in 8.1.8.
  • 38% of homes over $439K have a view, against 25% of homes under $372K. 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 $372K8 sales$372K–$387K8 sales$397K–$439K8 salesOver $439K8 salesAll32 salesReal difference?
Net sale price average$324,353$379,745$415,821$486,717$401,659by design
Net price per SF average$188$175$162$156$170unclear
Living area average1,7542,2222,5963,1522,431✓ large
Year built median20122013200820142013unclear

3.10 The numbers: selling

Under $372K8 sales$372K–$387K8 sales$397K–$439K8 salesOver $439K8 salesAll32 salesReal difference?
Days on market median4052385248unclear
Discount from original list average8.0%6.3%6.4%4.3%6.3%unclear
Price cut before sale75%50%38%50%53%unclear
Seller paid closing costs or repairs62%88%88%50%72%unclear
Has a view25%25%0%38%22%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 · 32 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T14:33:13.194048 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 7 9 32 sales Sales per group Under 1,902 SF: 8 sales (25%) 1,902–2,422 SF: 8 sales (25%) 2,442–2,792 SF: 7 sales (22%) Over 2,792 SF: 9 sales (28%)
Bottom line

4.1 Key differences

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

Under 1,902 SF1,902–2,422 SF2,442–2,792 SFOver 2,792 SF
Larger homes Over 2,792 SF
  • Sell for less per square foot.
  • Sell for much more.
Smaller homes Under 1,902 SF
  • Sell for more per square foot.
  • 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 1,902 SF1,902–2,422 SF2,442–2,792 SFOver 2,792 SFReal difference?
Net sale price$326KLowest$393K$416K$466KHighest✓ large
Net price per SF$194 per SFHighest$182 per SF$155 per SF$149 per SFLowest✓ large
Year built2012201220142013unclear
Days on market40 days38 days53 days75 daysunclear
Discount from original list6.9%4.0%5.5%8.3%unclear
Price cut before sale75%25%57%56%unclear
Seller paid closing costs or repairs50%100%71%67%unclear
Has a view38%12%14%22%unclear

4.3 Homes over 2,792 SF sell for about $141K (43%) more than homes under 1,902 SF

2026-11-05T14:33:13.215242 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,902 SF 8 sales 1,902– 2,422 SF 8 sales 2,442– 2,792 SF 7 sales Over 2,792 SF 9 sales $0K $200K $400K $326K $393K $416K $466K Net sale price, average

The average is $466K for homes over 2,792 SF and $326K for homes under 1,902 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 2,792 SF sell for about $45 per SF (23%) less than homes under 1,902 SF

2026-11-05T14:33:13.237855 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,902 SF 8 sales 1,902– 2,422 SF 8 sales 2,442– 2,792 SF 7 sales Over 2,792 SF 9 sales $0 $100 $200 $194 $182 $155 $149 Net price per SF, average

The average is $149 per SF for homes over 2,792 SF and $194 per SF for homes under 1,902 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

2026-11-05T14:33:13.260222 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,902 SF 8 sales 1,902– 2,422 SF 8 sales 2,442– 2,792 SF 7 sales Over 2,792 SF 9 sales 2010 2012 2014 2012 2012 2014 2013 Year built: median (dot) and middle half (bar)

The median is 2013 for homes over 2,792 SF and 2012 for homes under 1,902 SF. It does not move in a straight line; homes 2,442–2,792 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-05T14:33:13.282906 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,902 SF 8 sales 1,902– 2,422 SF 8 sales 2,442– 2,792 SF 7 sales Over 2,792 SF 9 sales 0 25 50 75 40 38 53 75 Days on market, median

The median is 75 days for homes over 2,792 SF and 40 days for homes under 1,902 SF. It does not move in a straight line; homes over 2,792 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-05T14:33:13.305596 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,902 SF 8 sales 1,902– 2,422 SF 8 sales 2,442– 2,792 SF 7 sales Over 2,792 SF 9 sales 0.0% 2.5% 5.0% 7.5% 6.9% 4.0% 5.5% 8.3% Discount from original list, average

The average is 8.3% for homes over 2,792 SF and 6.9% for homes under 1,902 SF. It does not move in a straight line; homes over 2,792 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

2026-11-05T14:33:13.331675 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 50 38 25 100 12 57 71 14 56 67 22 Under 1,902 SF 1,902–2,422 SF 2,442–2,792 SF Over 2,792 SF

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

  • 56% of homes over 2,792 SF had a price cut before sale, against 75% of homes under 1,902 SF. Defined in 8.1.7.
  • 67% of homes over 2,792 SF had the seller pay closing costs or repairs, against 50% of homes under 1,902 SF. Defined in 8.1.8.
  • 22% of homes over 2,792 SF have a view, against 38% of homes under 1,902 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 1,902 SF8 sales1,902–2,422 SF8 sales2,442–2,792 SF7 salesOver 2,792 SF9 salesAll32 salesReal difference?
Net sale price average$325,712$392,548$415,775$466,287$401,659✓ large
Net price per SF average$194$182$155$149$170✓ large
Living area average1,6802,1652,6843,1382,431by design
Year built median20122012201420132013unclear

4.10 The numbers: selling

Under 1,902 SF8 sales1,902–2,422 SF8 sales2,442–2,792 SF7 salesOver 2,792 SF9 salesAll32 salesReal difference?
Days on market median4038537548unclear
Discount from original list average6.9%4.0%5.5%8.3%6.3%unclear
Price cut before sale75%25%57%56%53%unclear
Seller paid closing costs or repairs50%100%71%67%72%unclear
Has a view38%12%14%22%22%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 · 32 sales · November 5, 2025 – November 4, 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.

2026-11-05T14:33:13.352360 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 8 12 5 32 sales Sales per group Before 2009: 7 sales (22%) 2009–2012: 8 sales (25%) 2013–2014: 12 sales (38%) After 2014: 5 sales (16%)
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 20092009–20122013–2014After 2014Real difference?
Net sale price$409K$382K$413K$397Kunclear
Net price per SF$162 per SF$179 per SF$163 per SF$183 per SFunclear
Living area2,576 SF2,173 SF2,604 SF2,225 SFunclear
Days on market48 days47 days44 days28 daysunclear
Discount from original list7.6%7.2%5.9%3.7%unclear
Price cut before sale43%50%75%20%unclear
Seller paid closing costs or repairs71%75%83%40%unclear
Has a view14%25%25%20%unclear

5.3 Net sale price: no clear difference

2026-11-05T14:33:13.372521 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 7 sales 2009– 2012 8 sales 2013– 2014 12 sales After 2014 5 sales $0K $200K $400K $409K $382K $413K $397K Net sale price, average

The average is $397K for homes built after 2014 and $409K for homes built before 2009. It does not move in a straight line; homes built 2013–2014 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-05T14:33:13.393860 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 7 sales 2009– 2012 8 sales 2013– 2014 12 sales After 2014 5 sales $0 $100 $200 $162 $179 $163 $183 Net price per SF, average

The average is $183 per SF for homes built after 2014 and $162 per SF for homes built before 2009. It does not move in a straight line; homes built after 2014 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-05T14:33:13.415867 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 7 sales 2009– 2012 8 sales 2013– 2014 12 sales After 2014 5 sales 0 1,000 2,000 3,000 2,576 2,173 2,604 2,225 Living area (SF), average

The average is 2,225 SF for homes built after 2014 and 2,576 SF for homes built before 2009. It does not move in a straight line; homes built 2013–2014 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-05T14:33:13.437648 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 7 sales 2009– 2012 8 sales 2013– 2014 12 sales After 2014 5 sales 0 20 40 48 47 44 28 Days on market, median

The median is 28 days for homes built after 2014 and 48 days for homes built before 2009. It falls 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

2026-11-05T14:33:13.460174 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2009 7 sales 2009– 2012 8 sales 2013– 2014 12 sales After 2014 5 sales 0.0% 2.5% 5.0% 7.5% 7.6% 7.2% 5.9% 3.7% Discount from original list, average

The average is 3.7% for homes built after 2014 and 7.6% for homes built before 2009. It falls 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

2026-11-05T14:33:13.485599 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% 43 71 14 50 75 25 75 83 25 20 40 20 Before 2009 2009–2012 2013–2014 After 2014

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

  • 20% of homes built after 2014 had a price cut before sale, against 43% of homes built before 2009. Defined in 8.1.7.
  • 40% of homes built after 2014 had the seller pay closing costs or repairs, against 71% of homes built before 2009. Defined in 8.1.8.
  • 20% of homes built after 2014 have a view, against 14% of homes built before 2009. 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 20097 sales2009–20128 sales2013–201412 salesAfter 20145 salesAll32 salesReal difference?
Net sale price average$409,399$381,550$412,611$396,713$401,659unclear
Net price per SF average$162$179$163$183$170unclear
Living area average2,5762,1732,6042,2252,431unclear
Year built median20082010201420152013by design

5.10 The numbers: selling

Before 20097 sales2009–20128 sales2013–201412 salesAfter 20145 salesAll32 salesReal difference?
Days on market median4847442848unclear
Discount from original list average7.6%7.2%5.9%3.7%6.3%unclear
Price cut before sale43%50%75%20%53%unclear
Seller paid closing costs or repairs71%75%83%40%72%unclear
Has a view14%25%25%20%22%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 · 32 sales · November 5, 2025 – November 4, 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.

2026-11-05T14:33:13.503300 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 24 31 sales Sales per group View: 7 sales (23%) No view: 24 sales (77%)
Bottom line

6.1 Key differences

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

ViewNo view
Homes with a view MLS lists a view
  • Less often have the seller pay buyer costs or repairs.
Homes without a view no view listed
  • More often have the seller pay buyer costs or repairs.

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$403K$404Kunclear
Net price per SF$177 per SF$166 per SFunclear
Living area2,323 SF2,501 SFunclear
Year built20132012unclear
Days on market43 days48 daysunclear
Discount from original list3.8%7.1%unclear
Price cut before sale71%50%unclear
Seller paid closing costs or repairs29%Fewest83%Most✓ large

6.3 Net sale price: no clear difference

2026-11-05T14:33:13.520446 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 24 sales $0K $100K $200K $300K $400K $403K $404K Net sale price, average

The average is $403K for homes with a view and $404K 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

2026-11-05T14:33:13.538816 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 24 sales $0 $50 $100 $150 $200 $177 $166 Net price per SF, average

The average is $177 per SF for homes with a view and $166 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

2026-11-05T14:33:13.556299 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 24 sales 0 1,000 2,000 3,000 2,323 2,501 Living area (SF), average

The average is 2,323 SF for homes with a view and 2,501 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-05T14:33:13.595520 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 24 sales 2010 2012 2014 2013 2012 Year built: median (dot) and middle half (bar)

The median is 2013 for homes with a view and 2012 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-05T14:33:13.612844 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 24 sales 0 20 40 43 48 Days on market, median

The median is 43 days for homes with a view and 48 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

2026-11-05T14:33:13.630665 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 24 sales 0.0% 2.0% 4.0% 6.0% 8.0% 3.8% 7.1% Discount from original list, average

The average is 3.8% for homes with a view and 7.1% 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

2026-11-05T14:33:13.650053 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 71 29 50 83 View No view

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

  • 71% of homes with a view had a price cut before sale, against 50% of homes without a view. Defined in 8.1.7.
  • 29% of homes with a view had the seller pay closing costs or repairs, against 83% 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: ✓ Real difference · large

6.10 The numbers: price and size

View7 salesNo view24 salesAll31 salesReal difference?
Net sale price average$403,407$403,885$403,777unclear
Net price per SF average$177$166$168unclear
Living area average2,3232,5012,461unclear
Year built median201320122013unclear

6.11 The numbers: selling

View7 salesNo view24 salesAll31 salesReal difference?
Days on market median434848unclear
Discount from original list average3.8%7.1%6.3%unclear
Price cut before sale71%50%55%unclear
Seller paid closing costs or repairs29%83%71%✓ large

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 5, 2025 – November 4, 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 Garlic Creek West.

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
32 resale sales. Average $401,659; median $392,000; standard deviation $64,825; middle half (25th–75th percentile) $369,707–$439,250; lowest $294,000, highest $575,000. 23 sales had a seller payment; their median payment was $10,000.

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
32 resale sales. Average $170; median $169; standard deviation $23; middle half (25th–75th percentile) $148–$187; lowest $137, highest $223.

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
32 resale sales. Average 2,431; median 2,432; standard deviation 619; middle half (25th–75th percentile) 1,894–2,802; lowest 1,508, highest 4,028.

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
32 resale sales. Average 2012; median 2013; standard deviation 3; middle half (25th–75th percentile) 2009–2014; lowest 2007, highest 2015.

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
32 resale sales. Average 61; median 48; standard deviation 60; middle half (25th–75th percentile) 19–77; lowest 1, highest 241. 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
32 resale sales. Average 6.3%; median 4.1%; standard deviation 5.8%; middle half (25th–75th percentile) 3.0%–8.7%; lowest −2.5%, highest 23.1%. 1 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
17 of 32 resale sales (53.1%).

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
23 of 32 resale sales (71.9%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
7 sales with a view, 24 without, 1 unclassified. Most common View entries: None 16, Neighborhood 12, Trees/Woods 4, Pond 2, Park/Greenbelt 2, Rural 1, See Remarks 1, Creek/Stream 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 2026-11-05 20:30 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Buda, SubdivisionName contains any of “garlic creek west” (case-insensitive). A record is kept when its subdivision name belongs to the Garlic Creek West family, the same rule comparable sales use.
The data
Pulled November 5, 2026: 32 closed Garlic Creek West records over the prior year, in ZIP 78610. 19 subdivision spellings kept, the most common: Garlic Creek West Ph Iii Sec 1 (4); Garlic Creek West Ph Iii Sec 3 (3); Garlic Creek West Ph Iii Sec 2 (3); Garlic Creek West Ph Iii Sec 8 (3); Garlic Creek West Ph Iii Sec 6A (2); Garlic Creek West Ph Iii Sec 4C (2); Garlic Creek West Ph III Sec 1 (2); Garlic Creek West Ph Iii Sec 7 (2); Garlic Creek West PH III, SEC 5C (1); Garlic Creek West (1); Garlic Creek West Ph 03 Sec 01 (1); Garlic Creek West Ph III Sec 4a (1); and 7 more (7 records). 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 15 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 5, 2025 to November 4, 2026 inclusive.
The data
32 single-family sales in the window: 32 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
32 resale; 0 new construction.

8.2.4 Sales left out

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

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $372K”.
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 $372K: $294,000–$363,127 (8 sales); $372K–$387K: $371,900–$387,000 (8 sales); $397K–$439K: $397,000–$439,000 (8 sales); Over $439K: $440,000–$575,000 (8 sales)
Quartiles by living area: Under 1,902 SF: 1,508–1,868 SF (8 sales); 1,902–2,422 SF: 1,902–2,422 SF (8 sales); 2,442–2,792 SF: 2,442–2,792 SF (7 sales); Over 2,792 SF: 2,802–4,028 SF (9 sales)
Quartiles by year built: Before 2009: 2007–2008 (7 sales); 2009–2012: 2009–2012 (8 sales); 2013–2014: 2013–2014 (12 sales); After 2014: 2015–2015 (5 sales)
View and no view: View: MLS lists a view (7 sales); No view: None or Neighborhood (24 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 $401,659, median $392,000. Days on market: average 61, median 48: 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
4 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 = 8.8230.0318p < 0.0063Unclearε² = 0.284large
Living areaKruskal–WallisH = 22.663< 0.0001p < 0.0063Yesε² = 0.731large
Year builtKruskal–WallisH = 3.9630.2655p < 0.0063Unclearε² = 0.128medium
Days on marketKruskal–WallisH = 0.8630.8362p < 0.0063Unclearε² = 0.028small
Discount from original listKruskal–WallisH = 2.9730.3964p < 0.0063Unclearε² = 0.096medium
Price cut before saleChi-squareχ² = 2.3830.4966p < 0.0063UnclearCramér’s V = 0.273small
Seller paid closing costs or repairsChi-squareχ² = 4.1730.2433p < 0.0063UnclearCramér’s V = 0.361medium
Has a viewChi-squareχ² = 3.4730.3241p < 0.0063UnclearCramér’s V = 0.330medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 20.7230.0001p < 0.0063Yesε² = 0.668large
Net price per SFKruskal–WallisH = 21.933< 0.0001p < 0.0063Yesε² = 0.707large
Year builtKruskal–WallisH = 0.7530.8624p < 0.0063Unclearε² = 0.024small
Days on marketKruskal–WallisH = 2.1030.5512p < 0.0063Unclearε² = 0.068medium
Discount from original listKruskal–WallisH = 3.4230.3307p < 0.0063Unclearε² = 0.110medium
Price cut before saleChi-squareχ² = 4.1530.2462p < 0.0063UnclearCramér’s V = 0.360medium
Seller paid closing costs or repairsChi-squareχ² = 5.1530.1614p < 0.0063UnclearCramér’s V = 0.401medium
Has a viewChi-squareχ² = 1.7930.6169p < 0.0063UnclearCramér’s V = 0.237small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 1.7430.6286p < 0.0063Unclearε² = 0.056small
Net price per SFKruskal–WallisH = 4.2930.2314p < 0.0063Unclearε² = 0.139medium
Living areaKruskal–WallisH = 2.8530.4149p < 0.0063Unclearε² = 0.092medium
Days on marketKruskal–WallisH = 0.4530.9299p < 0.0063Unclearε² = 0.014small
Discount from original listKruskal–WallisH = 2.2130.5303p < 0.0063Unclearε² = 0.071medium
Price cut before saleChi-squareχ² = 4.8430.1841p < 0.0063UnclearCramér’s V = 0.389medium
Seller paid closing costs or repairsChi-squareχ² = 3.3330.3432p < 0.0063UnclearCramér’s V = 0.323medium
Has a viewChi-squareχ² = 0.3630.9483p < 0.0063UnclearCramér’s V = 0.106small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 84.00—1.0000p < 0.0063Unclearrank-biserial r = 0.000negligible
Net price per SFMann–Whitney UU = 106.00—0.3097p < 0.0063Unclearrank-biserial r = 0.262small
Living areaMann–Whitney UU = 73.50—0.6365p < 0.0063Unclearrank-biserial r = 0.125small
Year builtMann–Whitney UU = 92.50—0.7013p < 0.0063Unclearrank-biserial r = 0.101small
Days on marketMann–Whitney UU = 78.00—0.7949p < 0.0063Unclearrank-biserial r = 0.071negligible
Discount from original listMann–Whitney UU = 55.50—0.1858p < 0.0063Unclearrank-biserial r = 0.339medium
Price cut before saleChi-squareχ² = 1.0010.3162p < 0.0063UnclearCramér’s V = 0.180small
Seller paid closing costs or repairsChi-squareχ² = 7.8910.0050p < 0.0063YesCramér’s V = 0.504large

8.4 Data notes

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

8.5 References

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

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 32 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 5, 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.