ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Morningstar

Georgetown, TX 78628 · 78629
Resale homes · closed Nov 7 – Nov 6, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 7, 2026 · 7:05 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
56
single-family resale homes
Median net sale price
$338,834
average $362,228
Median net price per SF
$178
average $174
Median days on market
50 days
average 99 days
1. SummaryResale homes · 56 sales · November 7, 2025 – November 6, 2026

This study looks at the 56 resale homes sold in Morningstar in the 365 days to November 6, 2026. A full year is used because only 32 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 sold56 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 $292K · 14 sales$292K–$338K · 14 sales$339K–$406K · 14 salesOver $406K · 14 sales
3. Quartiles by net sale priceResale homes · 56 sales · November 7, 2025 – November 6, 2026

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

2026-11-07T07:05:25.571263 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 14 14 14 56 sales Sales per group Under $292K: 14 sales (25%) $292K–$338K: 14 sales (25%) $339K–$406K: 14 sales (25%) Over $406K: 14 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 $292K$292K–$338K$339K–$406KOver $406K
Higher-priced homes Over $406K
  • Are much larger.
Lower-priced homes Under $292K
  • 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 $292K$292K–$338K$339K–$406KOver $406KReal difference?
Net price per SF$175 per SF$186 per SF$166 per SF$170 per SFunclear
Living area1,582 SFSmallest1,714 SF2,251 SF2,893 SFLargest✓ large
Year built2019202120192020unclear
Days on market50 days71 days102 days41 daysunclear
Discount from original list12.5%6.7%8.2%5.4%unclear
Price cut before sale71%50%71%64%unclear
Seller paid closing costs or repairs57%79%93%57%unclear
Has a view0%36%14%21%unclear

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

3.3 Net price per SF: no clear difference

2026-11-07T07:05:25.601745 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $292K 14 sales $292K– $338K 14 sales $339K– $406K 14 sales Over $406K 14 sales $0 $100 $200 $175 $186 $166 $170 Net price per SF, average

The average is $170 per SF for homes over $406K and $175 per SF for homes under $292K. It does not move in a straight line; homes $292K–$338K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $406K are about 1,310 SF (83%) larger than homes under $292K

2026-11-07T07:05:25.625912 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $292K 14 sales $292K– $338K 14 sales $339K– $406K 14 sales Over $406K 14 sales 0 1,000 2,000 3,000 1,582 1,714 2,251 2,893 Living area (SF), average

The average is 2,893 SF for homes over $406K and 1,582 SF for homes under $292K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-11-07T07:05:25.654335 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $292K 14 sales $292K– $338K 14 sales $339K– $406K 14 sales Over $406K 14 sales 2019 2020 2021 2022 2023 2019 2021 2019 2020 Year built: median (dot) and middle half (bar)

The median is 2020 for homes over $406K and 2019 for homes under $292K. It does not move in a straight line; homes $292K–$338K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-07T07:05:25.678346 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $292K 14 sales $292K– $338K 14 sales $339K– $406K 14 sales Over $406K 14 sales 0 50 100 50 71 102 41 Days on market, median

The median is 41 days for homes over $406K and 50 days for homes under $292K. It does not move in a straight line; homes $339K–$406K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-07T07:05:25.700266 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $292K 14 sales $292K– $338K 14 sales $339K– $406K 14 sales Over $406K 14 sales 0.0% 5.0% 10.0% 15.0% 12.5% 6.7% 8.2% 5.4% Discount from original list, average

The average is 5.4% for homes over $406K and 12.5% for homes under $292K. It does not move in a straight line; homes under $292K are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-07T07:05:25.731757 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 71 57 0 50 79 36 71 93 14 64 57 21 Under $292K $292K–$338K $339K–$406K Over $406K

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

  • 64% of homes over $406K had a price cut before sale, against 71% of homes under $292K. Defined in 8.1.7.
  • 57% of homes over $406K had the seller pay closing costs or repairs, against 57% of homes under $292K. Defined in 8.1.8.
  • 21% of homes over $406K have a view, against 0% of homes under $292K. 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 $292K14 sales$292K–$338K14 sales$339K–$406K14 salesOver $406K14 salesAll56 salesReal difference?
Net sale price average$274,789$316,480$366,705$490,937$362,228by design
Net price per SF average$175$186$166$170$174unclear
Living area average1,5821,7142,2512,8932,110✓ large
Year built median20192021201920202020unclear

3.10 The numbers: selling

Under $292K14 sales$292K–$338K14 sales$339K–$406K14 salesOver $406K14 salesAll56 salesReal difference?
Days on market median50711024150unclear
Discount from original list average12.5%6.7%8.2%5.4%8.2%unclear
Price cut before sale71%50%71%64%64%unclear
Seller paid closing costs or repairs57%79%93%57%71%unclear
Has a view0%36%14%21%18%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 · 56 sales · November 7, 2025 – November 6, 2026

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

2026-11-07T07:05:25.753012 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 14 14 14 56 sales Sales per group Under 1,599 SF: 14 sales (25%) 1,599–1,872 SF: 14 sales (25%) 1,881–2,623 SF: 14 sales (25%) Over 2,623 SF: 14 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 1,599 SF1,599–1,872 SF1,881–2,623 SFOver 2,623 SF
Larger homes Over 2,623 SF
  • Sell for much more.
  • Sell for less per square foot.
Smaller homes Under 1,599 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 1,599 SF1,599–1,872 SF1,881–2,623 SFOver 2,623 SFReal difference?
Net sale price$283KLowest$313K$373K$480KHighest✓ large
Net price per SF$189 per SFHighest$179 per SF$167 per SF$163 per SFLowest✓ large
Year built2019202020192020unclear
Days on market78 days32 days74 days102 daysunclear
Discount from original list10.6%7.6%8.1%6.5%unclear
Price cut before sale71%43%71%71%unclear
Seller paid closing costs or repairs64%71%93%57%unclear
Has a view14%21%14%21%unclear

4.3 Homes over 2,623 SF sell for about $197K (70%) more than homes under 1,599 SF

2026-11-07T07:05:25.774573 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,599 SF 14 sales 1,599– 1,872 SF 14 sales 1,881– 2,623 SF 14 sales Over 2,623 SF 14 sales $0K $200K $400K $283K $313K $373K $480K Net sale price, average

The average is $480K for homes over 2,623 SF and $283K for homes under 1,599 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 2,623 SF sell for about $27 per SF (14%) less than homes under 1,599 SF

2026-11-07T07:05:25.798155 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,599 SF 14 sales 1,599– 1,872 SF 14 sales 1,881– 2,623 SF 14 sales Over 2,623 SF 14 sales $0 $100 $200 $189 $179 $167 $163 Net price per SF, average

The average is $163 per SF for homes over 2,623 SF and $189 per SF for homes under 1,599 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

2026-11-07T07:05:25.822926 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,599 SF 14 sales 1,599– 1,872 SF 14 sales 1,881– 2,623 SF 14 sales Over 2,623 SF 14 sales 2019 2020 2021 2022 2019 2020 2019 2020 Year built: median (dot) and middle half (bar)

The median is 2020 for homes over 2,623 SF and 2019 for homes under 1,599 SF. It does not move in a straight line; homes 1,599–1,872 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-07T07:05:25.848861 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,599 SF 14 sales 1,599– 1,872 SF 14 sales 1,881– 2,623 SF 14 sales Over 2,623 SF 14 sales 0 50 100 78 32 74 102 Days on market, median

The median is 102 days for homes over 2,623 SF and 78 days for homes under 1,599 SF. It does not move in a straight line; homes over 2,623 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-07T07:05:25.872447 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,599 SF 14 sales 1,599– 1,872 SF 14 sales 1,881– 2,623 SF 14 sales Over 2,623 SF 14 sales 0.0% 5.0% 10.0% 10.6% 7.6% 8.1% 6.5% Discount from original list, average

The average is 6.5% for homes over 2,623 SF and 10.6% for homes under 1,599 SF. It does not move in a straight line; homes under 1,599 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-07T07:05:25.900698 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 71 64 14 43 71 21 71 93 14 71 57 21 Under 1,599 SF 1,599–1,872 SF 1,881–2,623 SF Over 2,623 SF

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

  • 71% of homes over 2,623 SF had a price cut before sale, against 71% of homes under 1,599 SF. Defined in 8.1.7.
  • 57% of homes over 2,623 SF had the seller pay closing costs or repairs, against 64% of homes under 1,599 SF. Defined in 8.1.8.
  • 21% of homes over 2,623 SF have a view, against 14% of homes under 1,599 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 1,599 SF14 sales1,599–1,872 SF14 sales1,881–2,623 SF14 salesOver 2,623 SF14 salesAll56 salesReal difference?
Net sale price average$282,920$313,004$372,689$480,298$362,228✓ large
Net price per SF average$189$179$167$163$174✓ large
Living area average1,4951,7562,2392,9502,110by design
Year built median20192020201920202020unclear

4.10 The numbers: selling

Under 1,599 SF14 sales1,599–1,872 SF14 sales1,881–2,623 SF14 salesOver 2,623 SF14 salesAll56 salesReal difference?
Days on market median78327410250unclear
Discount from original list average10.6%7.6%8.1%6.5%8.2%unclear
Price cut before sale71%43%71%71%64%unclear
Seller paid closing costs or repairs64%71%93%57%71%unclear
Has a view14%21%14%21%18%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 · 56 sales · November 7, 2025 – November 6, 2026

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

2026-11-07T07:05:25.924009 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 21 13 17 56 sales Sales per group Before 2019: 5 sales (9%) 2019: 21 sales (38%) 2020: 13 sales (23%) After 2020: 17 sales (30%)
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 201920192020After 2020Real difference?
Net sale price$334K$362K$398K$344Kunclear
Net price per SF$171 per SF$177 per SF$174 per SF$173 per SFunclear
Living area1,988 SF2,091 SF2,300 SF2,024 SFunclear
Days on market31 days47 days35 days132 daysunclear
Discount from original list9.1%8.7%5.4%9.6%unclear
Price cut before sale60%67%54%71%unclear
Seller paid closing costs or repairs80%67%69%76%unclear
Has a view0%0%31%35%unclear

5.3 Net sale price: no clear difference

2026-11-07T07:05:25.945689 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 5 sales 2019 21 sales 2020 13 sales After 2020 17 sales $0K $100K $200K $300K $400K $334K $362K $398K $344K Net sale price, average

The average is $344K for homes built after 2020 and $334K for homes built before 2019. It does not move in a straight line; homes built 2020 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-07T07:05:25.970785 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 5 sales 2019 21 sales 2020 13 sales After 2020 17 sales $0 $50 $100 $150 $200 $171 $177 $174 $173 Net price per SF, average

The average is $173 per SF for homes built after 2020 and $171 per SF for homes built before 2019. It does not move in a straight line; homes built 2019 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-07T07:05:25.994206 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 5 sales 2019 21 sales 2020 13 sales After 2020 17 sales 0 1,000 2,000 1,988 2,091 2,300 2,024 Living area (SF), average

The average is 2,024 SF for homes built after 2020 and 1,988 SF for homes built before 2019. It does not move in a straight line; homes built 2020 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-07T07:05:26.017031 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 5 sales 2019 21 sales 2020 13 sales After 2020 17 sales 0 50 100 150 31 47 35 132 Days on market, median

The median is 132 days for homes built after 2020 and 31 days for homes built before 2019. It does not move in a straight line; homes built after 2020 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-07T07:05:26.041939 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 5 sales 2019 21 sales 2020 13 sales After 2020 17 sales 0.0% 2.5% 5.0% 7.5% 10.0% 9.1% 8.7% 5.4% 9.6% Discount from original list, average

The average is 9.6% for homes built after 2020 and 9.1% for homes built before 2019. It does not move in a straight line; homes built after 2020 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-07T07:05:26.070504 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% 60 80 0 67 67 0 54 69 31 71 76 35 Before 2019 2019 2020 After 2020

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

  • 71% of homes built after 2020 had a price cut before sale, against 60% of homes built before 2019. Defined in 8.1.7.
  • 76% of homes built after 2020 had the seller pay closing costs or repairs, against 80% of homes built before 2019. Defined in 8.1.8.
  • 35% of homes built after 2020 have a view, against 0% of homes built before 2019. 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 20195 sales201921 sales202013 salesAfter 202017 salesAll56 salesReal difference?
Net sale price average$333,635$361,554$397,985$344,126$362,228unclear
Net price per SF average$171$177$174$173$174unclear
Living area average1,9882,0912,3002,0242,110unclear
Year built median20182019202020222020by design

5.10 The numbers: selling

Before 20195 sales201921 sales202013 salesAfter 202017 salesAll56 salesReal difference?
Days on market median31473513250unclear
Discount from original list average9.1%8.7%5.4%9.6%8.2%unclear
Price cut before sale60%67%54%71%64%unclear
Seller paid closing costs or repairs80%67%69%76%71%unclear
Has a view0%0%31%35%18%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 · 56 sales · November 7, 2025 – November 6, 2026

Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-11-07T07:05:26.092758 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 45 55 sales Sales per group View: 10 sales (18%) No view: 45 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$371K$358Kunclear
Net price per SF$175 per SF$174 per SFunclear
Living area2,162 SF2,088 SFunclear
Year built20212019unclear
Days on market68 days52 daysunclear
Discount from original list6.5%8.7%unclear
Price cut before sale40%71%unclear
Seller paid closing costs or repairs70%71%unclear

6.3 Net sale price: no clear difference

2026-11-07T07:05:26.111352 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 45 sales $0K $100K $200K $300K $400K $371K $358K Net sale price, average

The average is $371K for homes with a view and $358K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-11-07T07:05:26.131808 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 45 sales $0 $50 $100 $150 $200 $175 $174 Net price per SF, average

The average is $175 per SF for homes with a view and $174 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-11-07T07:05:26.150829 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 45 sales 0 1,000 2,000 2,162 2,088 Living area (SF), average

The average is 2,162 SF for homes with a view and 2,088 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-07T07:05:26.212970 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 45 sales 2019 2020 2021 2021 2019 Year built: median (dot) and middle half (bar)

The median is 2021 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

2026-11-07T07:05:26.232037 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 45 sales 0 20 40 60 80 68 52 Days on market, median

The median is 68 days for homes with a view and 52 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-11-07T07:05:26.252557 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 45 sales 0.0% 2.5% 5.0% 7.5% 10.0% 6.5% 8.7% Discount from original list, average

The average is 6.5% for homes with a view and 8.7% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-07T07:05:26.271945 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 40 70 71 71 View No view

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

  • 40% of homes with a view had a price cut before sale, against 71% of homes without a view. Defined in 8.1.7.
  • 70% of homes with a view had the seller pay closing costs or repairs, against 71% 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

View10 salesNo view45 salesAll55 salesReal difference?
Net sale price average$371,202$357,897$360,316unclear
Net price per SF average$175$174$174unclear
Living area average2,1622,0882,102unclear
Year built median202120192020unclear

6.11 The numbers: selling

View10 salesNo view45 salesAll55 salesReal difference?
Days on market median685252unclear
Discount from original list average6.5%8.7%8.3%unclear
Price cut before sale40%71%65%unclear
Seller paid closing costs or repairs70%71%71%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 · 19 sales · November 7, 2025 – November 6, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 19 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 Morningstar.
MeasureAverageMedian
Sales19
Net sale price$350,836$341,212
Net price per SF$193$188
Living area (SF)1,8601,981
Days on market128136
Discount from original list13.2%12.1%
Price cut before sale89% of sales
Seller paid closing costs or repairs95% of sales
Year built2023–2025

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
56 resale sales. Average $362,228; median $338,834; standard deviation $92,991; middle half (25th–75th percentile) $291,865–$407,325; lowest $234,000, highest $721,000. 40 sales had a seller payment; their median payment was $7,400.

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
56 resale sales. Average $174; median $178; standard deviation $19; middle half (25th–75th percentile) $158–$185; lowest $137, highest $212.

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
56 resale sales. Average 2,110; median 1,876; standard deviation 619; middle half (25th–75th percentile) 1,596–2,624; lowest 1,392, highest 4,023.

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
56 resale sales. Average 2020; median 2020; standard deviation 2; middle half (25th–75th percentile) 2019–2021; lowest 2016, 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
56 resale sales. Average 99; median 50; standard deviation 109; middle half (25th–75th percentile) 21–136; lowest 5, highest 549. 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
56 resale sales. Average 8.2%; median 6.9%; standard deviation 6.2%; middle half (25th–75th percentile) 3.3%–12.8%; lowest 0.0%, highest 25.7%. 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
36 of 56 resale sales (64.3%).

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
40 of 56 resale sales (71.4%).

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
10 sales with a view, 45 without, 1 unclassified. Most common View entries: None 30, Neighborhood 17, Park/Greenbelt 6, Trees/Woods 2, See Remarks 2, Pond 2, Pasture 1, Hill Country 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-07 13:00 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Georgetown, SubdivisionName contains any of “morningstar”, “morning star” (case-insensitive). A record is kept when its subdivision name belongs to the Morningstar family, the same rule comparable sales use.
The data
Pulled November 7, 2026: 75 closed Morningstar records over the prior year, in ZIP 78628, 78629. 20 subdivision spellings kept, the most common: Morningstar (36); MorningStar (6); Morning Star (4); MORNINGSTAR (4); Morningstar Ph 3 Sec 3 (3); Morningstar Ph 2 Sec 4 & 5 (3); Morningstar Ph 1 Sec 2 (3); Morningstar Ph 3 Sec 1B (2); Morningstar Ph 3 Sec 2A (2); Morningstar Ph 1 Sec 3 (2); Morningstar Ph 1 Sec 4A (1); MORNINGSTAR PH 3 SEC 2A (1); and 8 more (8 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 32 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 7, 2025 to November 6, 2026 inclusive.
The data
75 single-family sales in the window: 56 resale, 19 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
56 resale; 19 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 $292K”.
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 $292K: $234,000–$291,550 (14 sales); $292K–$338K: $291,970–$338,500 (14 sales); $339K–$406K: $339,167–$406,500 (14 sales); Over $406K: $409,800–$721,000 (14 sales)
Quartiles by living area: Under 1,599 SF: 1,392–1,589 SF (14 sales); 1,599–1,872 SF: 1,599–1,872 SF (14 sales); 1,881–2,623 SF: 1,881–2,623 SF (14 sales); Over 2,623 SF: 2,625–4,023 SF (14 sales)
Quartiles by year built: Before 2019: 2016–2018 (5 sales); 2019: 2019–2019 (21 sales); 2020: 2020–2020 (13 sales); After 2020: 2021–2025 (17 sales)
View and no view: View: MLS lists a view (10 sales); No view: None or Neighborhood (45 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 $362,228, median $338,834. Days on market: average 99, median 50: 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
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 = 8.1730.0426p < 0.0063Unclearε² = 0.149large
Living areaKruskal–WallisH = 41.083< 0.0001p < 0.0063Yesε² = 0.747large
Year builtKruskal–WallisH = 7.4130.0599p < 0.0063Unclearε² = 0.135medium
Days on marketKruskal–WallisH = 1.7630.6241p < 0.0063Unclearε² = 0.032small
Discount from original listKruskal–WallisH = 9.2630.0260p < 0.0063Unclearε² = 0.168large
Price cut before saleChi-squareχ² = 1.8730.6005p < 0.0063UnclearCramér’s V = 0.183small
Seller paid closing costs or repairsChi-squareχ² = 6.3030.0979p < 0.0063UnclearCramér’s V = 0.335medium
Has a viewChi-squareχ² = 6.3330.0966p < 0.0063UnclearCramér’s V = 0.336medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 42.833< 0.0001p < 0.0063Yesε² = 0.779large
Net price per SFKruskal–WallisH = 16.8630.0008p < 0.0063Yesε² = 0.306large
Year builtKruskal–WallisH = 2.3530.5036p < 0.0063Unclearε² = 0.043small
Days on marketKruskal–WallisH = 2.2530.5218p < 0.0063Unclearε² = 0.041small
Discount from original listKruskal–WallisH = 2.8230.4209p < 0.0063Unclearε² = 0.051small
Price cut before saleChi-squareχ² = 3.7330.2917p < 0.0063UnclearCramér’s V = 0.258small
Seller paid closing costs or repairsChi-squareχ² = 4.9030.1793p < 0.0063UnclearCramér’s V = 0.296small
Has a viewChi-squareχ² = 0.4930.9217p < 0.0063UnclearCramér’s V = 0.093negligible

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 2.1030.5509p < 0.0063Unclearε² = 0.038small
Net price per SFKruskal–WallisH = 0.3530.9497p < 0.0063Unclearε² = 0.006negligible
Living areaKruskal–WallisH = 2.2330.5256p < 0.0063Unclearε² = 0.041small
Days on marketKruskal–WallisH = 6.3130.0976p < 0.0063Unclearε² = 0.115medium
Discount from original listKruskal–WallisH = 3.6930.2973p < 0.0063Unclearε² = 0.067medium
Price cut before saleChi-squareχ² = 1.0030.8005p < 0.0063UnclearCramér’s V = 0.134small
Seller paid closing costs or repairsChi-squareχ² = 0.6630.8835p < 0.0063UnclearCramér’s V = 0.108small
Has a viewChi-squareχ² = 10.6530.0138p < 0.0063UnclearCramér’s V = 0.436medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 274.00—0.2899p < 0.0063Unclearrank-biserial r = 0.218small
Net price per SFMann–Whitney UU = 232.00—0.8872p < 0.0063Unclearrank-biserial r = 0.031negligible
Living areaMann–Whitney UU = 259.00—0.4647p < 0.0063Unclearrank-biserial r = 0.151small
Year builtMann–Whitney UU = 344.00—0.0075p < 0.0063Unclearrank-biserial r = 0.529large
Days on marketMann–Whitney UU = 214.50—0.8272p < 0.0063Unclearrank-biserial r = 0.047negligible
Discount from original listMann–Whitney UU = 164.00—0.1868p < 0.0063Unclearrank-biserial r = 0.271small
Price cut before saleChi-squareχ² = 3.5010.0613p < 0.0063UnclearCramér’s V = 0.252small
Seller paid closing costs or repairsChi-squareχ² = 0.0010.9442p < 0.0063UnclearCramér’s V = 0.009negligible

8.4 Data notes

Left out of the analysis: 19 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 56 closed MLS resale sales; the 19 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 7, 2026. Map data © OpenStreetMap contributors. ALEX Companies · Licensed by the Texas Real Estate Commission · Broker: Alexander Tiffany Southwest, LLC (ALEX Real Estate), #565194-BB · Diane Hart Alexander, Designated Broker, #574877-B.