ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Sunfield

Buda, TX 78610 · 76610 · 78640
Resale homes · closed Nov 8 – Nov 7, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 8, 2026 · 6:47 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
113
single-family resale homes
Median net sale price
$347,350
average $364,681
Median net price per SF
$170
average $170
Median days on market
65 days
average 88 days
1. SummaryResale homes · 113 sales · November 8, 2025 – November 7, 2026

This study looks at the 113 resale homes sold in Sunfield in the 365 days to November 7, 2026. A full year is used because only 66 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 sold113 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 $310K · 28 sales$310K–$345K · 28 sales$347K–$405K · 29 salesOver $405K · 28 sales
3. Quartiles by net sale priceResale homes · 113 sales · November 8, 2025 – November 7, 2026

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

2026-11-08T06:47:31.202396 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 28 28 29 28 113 sales Sales per group Under $310K: 28 sales (25%) $310K–$345K: 28 sales (25%) $347K–$405K: 29 sales (26%) Over $405K: 28 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 $310K$310K–$345K$347K–$405KOver $405K
Higher-priced homes Over $405K
  • Are much larger.
  • Tend to be newer.
Lower-priced homes Under $310K
  • Are much smaller.
  • Tend to be older.

3.2 At a glance

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

Under $310K$310K–$345K$347K–$405KOver $405KReal difference?
Net price per SF$168 per SF$173 per SF$171 per SF$167 per SFunclear
Living area1,680 SFSmallest1,927 SF2,223 SF2,921 SFLargest✓ large
Year built2017Oldest20192020Newest2020✓ large
Days on market113 days53 days57 days57 daysunclear
Discount from original list9.6%5.2%6.8%5.7%unclear
Price cut before sale75%50%66%46%unclear
Seller paid closing costs or repairs57%71%59%46%unclear
Has a view18%7%14%29%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

2026-11-08T06:47:31.233485 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 28 sales $310K– $345K 28 sales $347K– $405K 29 sales Over $405K 28 sales $0 $100 $200 $168 $173 $171 $167 Net price per SF, average

The average is $167 per SF for homes over $405K and $168 per SF for homes under $310K. It does not move in a straight line; homes $310K–$345K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $405K are about 1,240 SF (74%) larger than homes under $310K

2026-11-08T06:47:31.257707 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 28 sales $310K– $345K 28 sales $347K– $405K 29 sales Over $405K 28 sales 0 1,000 2,000 3,000 1,680 1,927 2,223 2,921 Living area (SF), average

The average is 2,921 SF for homes over $405K and 1,680 SF for homes under $310K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Homes over $405K are about 2 years newer than homes under $310K

2026-11-08T06:47:31.285064 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 28 sales $310K– $345K 28 sales $347K– $405K 29 sales Over $405K 28 sales 2014 2016 2018 2020 2022 2017 2019 2020 2020 Year built: median (dot) and middle half (bar)

The median is 2020 for homes over $405K and 2017 for homes under $310K. It does not move in a straight line; homes $347K–$405K are highest. Defined in 8.1.4.

✓ Real difference · large

3.6 Days on market: no clear difference

2026-11-08T06:47:31.311126 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 28 sales $310K– $345K 28 sales $347K– $405K 29 sales Over $405K 28 sales 0 50 100 113 53 57 57 Days on market, median

The median is 57 days for homes over $405K and 113 days for homes under $310K. It does not move in a straight line; homes under $310K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-08T06:47:31.335719 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 28 sales $310K– $345K 28 sales $347K– $405K 29 sales Over $405K 28 sales 0.0% 5.0% 10.0% 9.6% 5.2% 6.8% 5.7% Discount from original list, average

The average is 5.7% for homes over $405K and 9.6% for homes under $310K. It does not move in a straight line; homes under $310K 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

2026-11-08T06:47:31.367695 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% 57% 18% 50% 71% 7% 66% 59% 14% 46% 46% 29% Under $310K $310K–$345K $347K–$405K Over $405K

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

  • 46% of homes over $405K had a price cut before sale, against 75% of homes under $310K. Defined in 8.1.7.
  • 46% of homes over $405K had the seller pay closing costs or repairs, against 57% of homes under $310K. Defined in 8.1.8.
  • 29% of homes over $405K have a view, against 18% of homes under $310K. 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 $310K28 sales$310K–$345K28 sales$347K–$405K29 salesOver $405K28 salesAll113 salesReal difference?
Net sale price average$275,326$328,139$375,675$479,193$364,681by design
Net price per SF average$168$173$171$167$170unclear
Living area average1,6801,9272,2232,9212,188✓ large
Year built median20172019202020202019✓ large

3.10 The numbers: selling

Under $310K28 sales$310K–$345K28 sales$347K–$405K29 salesOver $405K28 salesAll113 salesReal difference?
Days on market median11353575765unclear
Discount from original list average9.6%5.2%6.8%5.7%6.8%unclear
Price cut before sale75%50%66%46%59%unclear
Seller paid closing costs or repairs57%71%59%46%58%unclear
Has a view18%7%14%29%17%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.1.

4. Quartiles by living areaResale homes · 113 sales · November 8, 2025 – November 7, 2026

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

2026-11-08T06:47:31.389480 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 27 27 31 28 113 sales Sales per group Under 1,797 SF: 27 sales (24%) 1,797–2,067 SF: 27 sales (24%) 2,151–2,473 SF: 31 sales (27%) Over 2,473 SF: 28 sales (25%)
Bottom line

4.1 Key differences

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

Under 1,797 SF1,797–2,067 SF2,151–2,473 SFOver 2,473 SF
Larger homes Over 2,473 SF
  • Sell for much more.
  • Sell for less per square foot.
Smaller homes Under 1,797 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 1,797 SF1,797–2,067 SF2,151–2,473 SFOver 2,473 SFReal difference?
Net sale price$288KLowest$335K$363K$469KHighest✓ large
Net price per SF$188 per SFHighest$173 per SF$161 per SF$159 per SFLowest✓ large
Year built2017201920202020unclear
Days on market69 days90 days57 days57 daysunclear
Discount from original list7.1%8.6%5.6%6.2%unclear
Price cut before sale70%67%52%50%unclear
Seller paid closing costs or repairs52%70%65%46%unclear
Has a view19%4%29%14%unclear

4.3 Homes over 2,473 SF sell for about $181K (63%) more than homes under 1,797 SF

2026-11-08T06:47:31.413144 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,797 SF 27 sales 1,797– 2,067 SF 27 sales 2,151– 2,473 SF 31 sales Over 2,473 SF 28 sales $0K $200K $400K $288K $335K $363K $469K Net sale price, average

The average is $469K for homes over 2,473 SF and $288K for homes under 1,797 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 2,473 SF sell for about $29 per SF (15%) less than homes under 1,797 SF

2026-11-08T06:47:31.438598 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,797 SF 27 sales 1,797– 2,067 SF 27 sales 2,151– 2,473 SF 31 sales Over 2,473 SF 28 sales $0 $100 $200 $188 $173 $161 $159 Net price per SF, average

The average is $159 per SF for homes over 2,473 SF and $188 per SF for homes under 1,797 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

2026-11-08T06:47:31.464560 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,797 SF 27 sales 1,797– 2,067 SF 27 sales 2,151– 2,473 SF 31 sales Over 2,473 SF 28 sales 2014 2016 2018 2020 2022 2017 2019 2020 2020 Year built: median (dot) and middle half (bar)

The median is 2020 for homes over 2,473 SF and 2017 for homes under 1,797 SF. It does not move in a straight line; homes 2,151–2,473 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-08T06:47:31.491598 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,797 SF 27 sales 1,797– 2,067 SF 27 sales 2,151– 2,473 SF 31 sales Over 2,473 SF 28 sales 0 50 100 69 90 57 57 Days on market, median

The median is 57 days for homes over 2,473 SF and 69 days for homes under 1,797 SF. It does not move in a straight line; homes 1,797–2,067 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-08T06:47:31.515907 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,797 SF 27 sales 1,797– 2,067 SF 27 sales 2,151– 2,473 SF 31 sales Over 2,473 SF 28 sales 0.0% 5.0% 10.0% 7.1% 8.6% 5.6% 6.2% Discount from original list, average

The average is 6.2% for homes over 2,473 SF and 7.1% for homes under 1,797 SF. It does not move in a straight line; homes 1,797–2,067 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

2026-11-08T06:47:31.544827 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% 70% 52% 19% 67% 70% 4% 52% 65% 29% 50% 46% 14% Under 1,797 SF 1,797–2,067 SF 2,151–2,473 SF Over 2,473 SF

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

  • 50% of homes over 2,473 SF had a price cut before sale, against 70% of homes under 1,797 SF. Defined in 8.1.7.
  • 46% of homes over 2,473 SF had the seller pay closing costs or repairs, against 52% of homes under 1,797 SF. Defined in 8.1.8.
  • 14% of homes over 2,473 SF have a view, against 19% of homes under 1,797 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 1,797 SF27 sales1,797–2,067 SF27 sales2,151–2,473 SF31 salesOver 2,473 SF28 salesAll113 salesReal difference?
Net sale price average$288,080$335,376$362,718$468,979$364,681✓ large
Net price per SF average$188$173$161$159$170✓ large
Living area average1,5341,9372,2592,9822,188by design
Year built median20172019202020202019unclear

4.10 The numbers: selling

Under 1,797 SF27 sales1,797–2,067 SF27 sales2,151–2,473 SF31 salesOver 2,473 SF28 salesAll113 salesReal difference?
Days on market median6990575765unclear
Discount from original list average7.1%8.6%5.6%6.2%6.8%unclear
Price cut before sale70%67%52%50%59%unclear
Seller paid closing costs or repairs52%70%65%46%58%unclear
Has a view19%4%29%14%17%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.2.

5. Quartiles by year builtResale homes · 113 sales · November 8, 2025 – November 7, 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.

2026-11-08T06:47:31.566547 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 29 29 30 25 113 sales Sales per group Before 2017: 29 sales (26%) 2017–2019: 29 sales (26%) 2020–2021: 30 sales (27%) After 2021: 25 sales (22%)
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 20172017–20192020–2021After 2021Real difference?
Net sale price$340K$361K$371K$389Kunclear
Net price per SF$167 per SF$172 per SF$170 per SF$169 per SFunclear
Living area2,092 SF2,129 SF2,217 SF2,333 SFunclear
Days on market50 days53 days80 days65 daysunclear
Discount from original list7.6%5.3%7.6%6.8%unclear
Price cut before sale55%48%73%60%unclear
Seller paid closing costs or repairs52%66%53%64%unclear
Has a view14%21%13%20%unclear

5.3 Net sale price: no clear difference

2026-11-08T06:47:31.587377 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 29 sales 2017– 2019 29 sales 2020– 2021 30 sales After 2021 25 sales $0K $200K $400K $340K $361K $371K $389K Net sale price, average

The average is $389K for homes built after 2021 and $340K for homes built before 2017. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-08T06:47:31.610556 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 29 sales 2017– 2019 29 sales 2020– 2021 30 sales After 2021 25 sales $0 $100 $200 $167 $172 $170 $169 Net price per SF, average

The average is $169 per SF for homes built after 2021 and $167 per SF for homes built before 2017. It does not move in a straight line; homes built 2017–2019 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-08T06:47:31.632372 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 29 sales 2017– 2019 29 sales 2020– 2021 30 sales After 2021 25 sales 0 1,000 2,000 2,092 2,129 2,217 2,333 Living area (SF), average

The average is 2,333 SF for homes built after 2021 and 2,092 SF for homes built before 2017. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-08T06:47:31.653840 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 29 sales 2017– 2019 29 sales 2020– 2021 30 sales After 2021 25 sales 0 25 50 75 50 53 80 65 Days on market, median

The median is 65 days for homes built after 2021 and 50 days for homes built before 2017. It does not move in a straight line; homes built 2020–2021 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-08T06:47:31.676745 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 29 sales 2017– 2019 29 sales 2020– 2021 30 sales After 2021 25 sales 0.0% 2.5% 5.0% 7.5% 7.6% 5.3% 7.6% 6.8% Discount from original list, average

The average is 6.8% for homes built after 2021 and 7.6% for homes built before 2017. It does not move in a straight line; homes built before 2017 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

2026-11-08T06:47:31.701699 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% 52% 14% 48% 66% 21% 73% 53% 13% 60% 64% 20% Before 2017 2017–2019 2020–2021 After 2021

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

  • 60% of homes built after 2021 had a price cut before sale, against 55% of homes built before 2017. Defined in 8.1.7.
  • 64% of homes built after 2021 had the seller pay closing costs or repairs, against 52% of homes built before 2017. Defined in 8.1.8.
  • 20% of homes built after 2021 have a view, against 14% of homes built before 2017. 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 201729 sales2017–201929 sales2020–202130 salesAfter 202125 salesAll113 salesReal difference?
Net sale price average$340,347$361,450$371,283$388,736$364,681unclear
Net price per SF average$167$172$170$169$170unclear
Living area average2,0922,1292,2172,3332,188unclear
Year built median20142018202020222019by design

5.10 The numbers: selling

Before 201729 sales2017–201929 sales2020–202130 salesAfter 202125 salesAll113 salesReal difference?
Days on market median5053806565unclear
Discount from original list average7.6%5.3%7.6%6.8%6.8%unclear
Price cut before sale55%48%73%60%59%unclear
Seller paid closing costs or repairs52%66%53%64%58%unclear
Has a view14%21%13%20%17%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.3.

6. View and no viewResale homes · 113 sales · November 8, 2025 – November 7, 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. 6 sales whose MLS view entry is only “See Remarks” are left out.

2026-11-08T06:47:31.720951 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 19 88 107 sales Sales per group View: 19 sales (18%) No view: 88 sales (82%)
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$374K$365Kunclear
Net price per SF$177 per SF$169 per SFunclear
Living area2,160 SF2,191 SFunclear
Year built20192019unclear
Days on market28 days70 daysunclear
Discount from original list4.7%7.1%unclear
Price cut before sale47%62%unclear
Seller paid closing costs or repairs58%58%unclear

6.3 Net sale price: no clear difference

2026-11-08T06:47:31.737758 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 88 sales $0K $100K $200K $300K $400K $374K $365K Net sale price, average

The average is $374K for homes with a view and $365K 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

2026-11-08T06:47:31.756559 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 88 sales $0 $50 $100 $150 $200 $177 $169 Net price per SF, average

The average is $177 per SF for homes with a view and $169 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

2026-11-08T06:47:31.806898 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 88 sales 0 1,000 2,000 2,160 2,191 Living area (SF), average

The average is 2,160 SF for homes with a view and 2,191 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-08T06:47:31.826882 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 88 sales 2016 2018 2020 2019 2019 Year built: median (dot) and middle half (bar)

The median is 2019 for homes with a view and 2019 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-08T06:47:31.847167 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 88 sales 0 20 40 60 80 28 70 Days on market, median

The median is 28 days for homes with a view and 70 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

2026-11-08T06:47:31.868005 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 88 sales 0.0% 2.0% 4.0% 6.0% 8.0% 4.7% 7.1% Discount from original list, average

The average is 4.7% 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

2026-11-08T06:47:31.886869 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 47% 58% 62% 58% View No view

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

  • 47% of homes with a view had a price cut before sale, against 62% of homes without a view. Defined in 8.1.7.
  • 58% of homes with a view had the seller pay closing costs or repairs, against 58% 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

View19 salesNo view88 salesAll107 salesReal difference?
Net sale price average$374,067$364,669$366,338unclear
Net price per SF average$177$169$171unclear
Living area average2,1602,1912,185unclear
Year built median201920192019unclear

6.11 The numbers: selling

View19 salesNo view88 salesAll107 salesReal difference?
Days on market median287062unclear
Discount from original list average4.7%7.1%6.7%unclear
Price cut before sale47%62%60%unclear
Seller paid closing costs or repairs58%58%58%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 · 136 sales · November 8, 2025 – November 7, 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: 136 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 Sunfield.
MeasureAverageMedian
Sales136
Net sale price$400,449$375,026
Net price per SF$182$178
Living area (SF)2,2412,218
Days on market7366
Discount from original list8.4%8.3%
Price cut before sale59% of sales
Seller paid closing costs or repairs74% of sales
Year built2019–2026

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
113 resale sales. Average $364,681; median $347,350; standard deviation $82,468; middle half (25th–75th percentile) $310,000–$405,000; lowest $204,500, highest $615,000. 66 sales had a seller payment; their median payment was $8,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
113 resale sales. Average $170; median $170; standard deviation $22; middle half (25th–75th percentile) $156–$182; lowest $106, highest $257.

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
113 resale sales. Average 2,188; median 2,151; standard deviation 587; middle half (25th–75th percentile) 1,797–2,473; lowest 1,196, highest 4,154.

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
113 resale sales. Average 2019; median 2019; standard deviation 3; middle half (25th–75th percentile) 2016–2021; lowest 2010, highest 2025.

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
113 resale sales. Average 88; median 65; standard deviation 87; middle half (25th–75th percentile) 24–123; lowest 3, highest 625. 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
113 resale sales. Average 6.8%; median 6.0%; standard deviation 6.5%; middle half (25th–75th percentile) 2.9%–9.4%; lowest −10.4%, highest 34.4%. 7 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
67 of 113 resale sales (59.3%).

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
66 of 113 resale sales (58.4%).

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
19 sales with a view, 88 without, 6 unclassified. Most common View entries: None 57, Neighborhood 37, Park/Greenbelt 13, See Remarks 8, Trees/Woods 5, City 3, Pond 1, Panoramic 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 2026-11-08 12:45 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Buda, SubdivisionName contains any of “sunfield” (case-insensitive). A record is kept when its subdivision name belongs to the Sunfield family, the same rule comparable sales use.
The data
Pulled November 8, 2026: 249 closed Sunfield records over the prior year, in ZIP 78610, 76610, 78640. 32 subdivision spellings kept, the most common: Sunfield (153); Sunfield Ph One Sec Two (10); Sunfield Ph Two Sec Four (9); Sunfield Ph Three Sec Two (7); Sunfield Ph Three Sec Six A (6); Sunfield Ph Two Sec Ten (6); Sunfield Ph Three Sec Five B (5); Sunfield Ph Three Sec Five C (4); Sunfield Ph Two Sec Eleven (4); Sunfield Ph Two Sec Six (4); Sunfield Ph Three Sec Three (4); Sunfield Ph Two Sec Twelve (3); and 20 more (34 records). Names found by the search but not part of Sunfield, left out: Sunfield Amenity Center (1); S8402 - SUNFIELD PHASE TWO SECTION FIVE (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 66 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 8, 2025 to November 7, 2026 inclusive.
The data
249 single-family sales in the window: 113 resale, 136 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
113 resale; 136 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 $310K”.
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 $310K: $204,500–$309,000 (28 sales); $310K–$345K: $310,000–$345,000 (28 sales); $347K–$405K: $347,350–$405,000 (29 sales); Over $405K: $406,800–$615,000 (28 sales)
Quartiles by living area: Under 1,797 SF: 1,196–1,743 SF (27 sales); 1,797–2,067 SF: 1,797–2,067 SF (27 sales); 2,151–2,473 SF: 2,151–2,473 SF (31 sales); Over 2,473 SF: 2,503–4,154 SF (28 sales)
Quartiles by year built: Before 2017: 2010–2016 (29 sales); 2017–2019: 2017–2019 (29 sales); 2020–2021: 2020–2021 (30 sales); After 2021: 2022–2025 (25 sales)
View and no view: View: MLS lists a view (19 sales); No view: None or Neighborhood (88 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 $364,681, median $347,350. Days on market: average 88, median 65: 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 = 1.5130.6806p < 0.0063Unclearε² = 0.013small
Living areaKruskal–WallisH = 74.543< 0.0001p < 0.0063Yesε² = 0.666large
Year builtKruskal–WallisH = 15.7330.0013p < 0.0063Yesε² = 0.140large
Days on marketKruskal–WallisH = 6.7330.0809p < 0.0063Unclearε² = 0.060medium
Discount from original listKruskal–WallisH = 7.2330.0650p < 0.0063Unclearε² = 0.065medium
Price cut before saleChi-squareχ² = 6.2530.1001p < 0.0063UnclearCramér’s V = 0.235small
Seller paid closing costs or repairsChi-squareχ² = 3.6330.3047p < 0.0063UnclearCramér’s V = 0.179small
Has a viewChi-squareχ² = 4.8530.1831p < 0.0063UnclearCramér’s V = 0.207small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 74.793< 0.0001p < 0.0063Yesε² = 0.668large
Net price per SFKruskal–WallisH = 34.923< 0.0001p < 0.0063Yesε² = 0.312large
Year builtKruskal–WallisH = 12.0230.0073p < 0.0063Unclearε² = 0.107medium
Days on marketKruskal–WallisH = 1.9330.5868p < 0.0063Unclearε² = 0.017small
Discount from original listKruskal–WallisH = 3.4830.3237p < 0.0063Unclearε² = 0.031small
Price cut before saleChi-squareχ² = 3.7430.2909p < 0.0063UnclearCramér’s V = 0.182small
Seller paid closing costs or repairsChi-squareχ² = 4.2030.2408p < 0.0063UnclearCramér’s V = 0.193small
Has a viewChi-squareχ² = 6.8130.0782p < 0.0063UnclearCramér’s V = 0.246small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 8.5830.0354p < 0.0063Unclearε² = 0.077medium
Net price per SFKruskal–WallisH = 0.8930.8285p < 0.0063Unclearε² = 0.008negligible
Living areaKruskal–WallisH = 6.0330.1102p < 0.0063Unclearε² = 0.054small
Days on marketKruskal–WallisH = 3.7830.2867p < 0.0063Unclearε² = 0.034small
Discount from original listKruskal–WallisH = 1.7730.6215p < 0.0063Unclearε² = 0.016small
Price cut before saleChi-squareχ² = 4.1230.2490p < 0.0063UnclearCramér’s V = 0.191small
Seller paid closing costs or repairsChi-squareχ² = 1.7830.6201p < 0.0063UnclearCramér’s V = 0.125small
Has a viewChi-squareχ² = 0.9430.8153p < 0.0063UnclearCramér’s V = 0.091negligible

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 951.00—0.3506p < 0.0063Unclearrank-biserial r = 0.138small
Net price per SFMann–Whitney UU = 952.00—0.3464p < 0.0063Unclearrank-biserial r = 0.139small
Living areaMann–Whitney UU = 876.50—0.7443p < 0.0063Unclearrank-biserial r = 0.048negligible
Year builtMann–Whitney UU = 866.50—0.8058p < 0.0063Unclearrank-biserial r = 0.036negligible
Days on marketMann–Whitney UU = 517.00—0.0094p < 0.0063Unclearrank-biserial r = 0.382medium
Discount from original listMann–Whitney UU = 677.00—0.1963p < 0.0063Unclearrank-biserial r = 0.190small
Price cut before saleChi-squareχ² = 1.4910.2225p < 0.0063UnclearCramér’s V = 0.118small
Seller paid closing costs or repairsChi-squareχ² = 0.0010.9962p < 0.0063UnclearCramér’s V = 0.000negligible

8.4 Data notes

Left out of the analysis: 136 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 113 closed MLS resale sales; the 136 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 8, 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.