ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Heritage Oaks

Georgetown, TX 78633
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 7:43 AM CDT
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
38
single-family resale homes
Median net sale price
$380,000
average $394,958
Median net price per SF
$189
average $188
Median days on market
84 days
average 119 days
1. SummaryResale homes · 38 sales · October 26, 2025 – October 25, 2026

This study looks at the 38 resale homes sold in Heritage Oaks in the 365 days to October 25, 2026. A full year is used because only 19 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 sold38 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 $354K · 10 sales$354K–$380K · 10 sales$384K–$410K · 8 salesOver $410K · 10 sales
3. Quartiles by net sale priceResale homes · 38 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:43:45.029119 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 8 10 38 sales Sales per group Under $354K: 10 sales (26%) $354K–$380K: 10 sales (26%) $384K–$410K: 8 sales (21%) Over $410K: 10 sales (26%)
Bottom line

3.1 Key differences

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

Under $354K$354K–$380K$384K–$410KOver $410K
Higher-priced homes Over $410K
  • Are much larger.
Lower-priced homes Under $354K
  • 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 $354K$354K–$380K$384K–$410KOver $410KReal difference?
Net price per SF$185 per SF$186 per SF$186 per SF$197 per SFunclear
Living area1,823 SFSmallest2,030 SF2,142 SF2,441 SFLargest✓ large
Year built2006200720072011unclear
Days on market138 days92 days50 days52 daysunclear
Discount from original list10.0%7.5%7.7%5.2%unclear
Price cut before sale70%50%50%50%unclear
Seller paid closing costs or repairs40%60%62%80%unclear
Has a view40%40%62%50%unclear

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

3.3 Net price per SF: no clear difference

2026-10-26T07:43:45.058881 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $380K 10 sales $384K– $410K 8 sales Over $410K 10 sales $0 $100 $200 $185 $186 $186 $197 Net price per SF, average

The average is $197 per SF for homes over $410K and $185 per SF for homes under $354K. It rises 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 $410K are about 620 SF (34%) larger than homes under $354K

2026-10-26T07:43:45.082301 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $380K 10 sales $384K– $410K 8 sales Over $410K 10 sales 0 1,000 2,000 1,823 2,030 2,142 2,441 Living area (SF), average

The average is 2,441 SF for homes over $410K and 1,823 SF for homes under $354K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-26T07:43:45.107252 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $380K 10 sales $384K– $410K 8 sales Over $410K 10 sales 2006 2008 2010 2012 2006 2007 2007 2011 Year built: median (dot) and middle half (bar)

The median is 2011 for homes over $410K and 2006 for homes under $354K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:43:45.131603 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $380K 10 sales $384K– $410K 8 sales Over $410K 10 sales 0 50 100 150 138 92 50 52 Days on market, median

The median is 52 days for homes over $410K and 138 days for homes under $354K. It does not move in a straight line; homes under $354K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:43:45.154339 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $354K 10 sales $354K– $380K 10 sales $384K– $410K 8 sales Over $410K 10 sales 0.0% 5.0% 10.0% 10.0% 7.5% 7.7% 5.2% Discount from original list, average

The average is 5.2% for homes over $410K and 10.0% for homes under $354K. It does not move in a straight line; homes under $354K are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:43:45.185717 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 40 40 50 60 40 50 62 62 50 80 50 Under $354K $354K–$380K $384K–$410K Over $410K

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

  • 50% of homes over $410K had a price cut before sale, against 70% of homes under $354K. Defined in 8.1.7.
  • 80% of homes over $410K had the seller pay closing costs or repairs, against 40% of homes under $354K. Defined in 8.1.8.
  • 50% of homes over $410K have a view, against 40% of homes under $354K. 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 $354K10 sales$354K–$380K10 sales$384K–$410K8 salesOver $410K10 salesAll38 salesReal difference?
Net sale price average$332,272$371,760$396,273$479,789$394,958by design
Net price per SF average$185$186$186$197$188unclear
Living area average1,8232,0302,1422,4412,107✓ large
Year built median20062007200720112008unclear

3.10 The numbers: selling

Under $354K10 sales$354K–$380K10 sales$384K–$410K8 salesOver $410K10 salesAll38 salesReal difference?
Days on market median13892505284unclear
Discount from original list average10.0%7.5%7.7%5.2%7.6%unclear
Price cut before sale70%50%50%50%55%unclear
Seller paid closing costs or repairs40%60%62%80%61%unclear
Has a view40%40%62%50%47%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 · 38 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:43:45.207769 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 9 9 10 38 sales Sales per group Under 1,908 SF: 10 sales (26%) 1,908–2,148 SF: 9 sales (24%) 2,159–2,276 SF: 9 sales (24%) Over 2,276 SF: 10 sales (26%)
Bottom line

4.1 Key differences

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

Under 1,908 SF1,908–2,148 SF2,159–2,276 SFOver 2,276 SF
Larger homes Over 2,276 SF
  • Sell for much more.
Smaller homes Under 1,908 SF
  • Sell for much less.

4.2 At a glance

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

Under 1,908 SF1,908–2,148 SF2,159–2,276 SFOver 2,276 SFReal difference?
Net sale price$340KLowest$387K$383K$468KHighest✓ large
Net price per SF$201 per SF$192 per SF$171 per SF$188 per SFunclear
Year built2010200620072010unclear
Days on market111 days70 days49 days123 daysunclear
Discount from original list9.0%6.8%8.1%6.5%unclear
Price cut before sale70%56%44%50%unclear
Seller paid closing costs or repairs60%44%67%70%unclear
Has a view60%33%56%40%unclear

4.3 Homes over 2,276 SF sell for about $129K (38%) more than homes under 1,908 SF

2026-10-26T07:43:45.230543 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,908 SF 10 sales 1,908– 2,148 SF 9 sales 2,159– 2,276 SF 9 sales Over 2,276 SF 10 sales $0K $200K $400K $340K $387K $383K $468K Net sale price, average

The average is $468K for homes over 2,276 SF and $340K for homes under 1,908 SF. It does not move in a straight line; homes over 2,276 SF are highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-26T07:43:45.254325 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,908 SF 10 sales 1,908– 2,148 SF 9 sales 2,159– 2,276 SF 9 sales Over 2,276 SF 10 sales $0 $100 $200 $201 $192 $171 $188 Net price per SF, average

The average is $188 per SF for homes over 2,276 SF and $201 per SF for homes under 1,908 SF. It does not move in a straight line; homes under 1,908 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:43:45.279107 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,908 SF 10 sales 1,908– 2,148 SF 9 sales 2,159– 2,276 SF 9 sales Over 2,276 SF 10 sales 2006 2008 2010 2012 2010 2006 2007 2010 Year built: median (dot) and middle half (bar)

The median is 2010 for homes over 2,276 SF and 2010 for homes under 1,908 SF. It does not move in a straight line; homes over 2,276 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:43:45.303314 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,908 SF 10 sales 1,908– 2,148 SF 9 sales 2,159– 2,276 SF 9 sales Over 2,276 SF 10 sales 0 50 100 111 70 49 123 Days on market, median

The median is 123 days for homes over 2,276 SF and 111 days for homes under 1,908 SF. It does not move in a straight line; homes over 2,276 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:43:45.326268 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,908 SF 10 sales 1,908– 2,148 SF 9 sales 2,159– 2,276 SF 9 sales Over 2,276 SF 10 sales 0.0% 5.0% 10.0% 9.0% 6.8% 8.1% 6.5% Discount from original list, average

The average is 6.5% for homes over 2,276 SF and 9.0% for homes under 1,908 SF. It does not move in a straight line; homes under 1,908 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:43:45.355093 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 60 60 56 44 33 44 67 56 50 70 40 Under 1,908 SF 1,908–2,148 SF 2,159–2,276 SF Over 2,276 SF

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

  • 50% of homes over 2,276 SF had a price cut before sale, against 70% of homes under 1,908 SF. Defined in 8.1.7.
  • 70% of homes over 2,276 SF had the seller pay closing costs or repairs, against 60% of homes under 1,908 SF. Defined in 8.1.8.
  • 40% of homes over 2,276 SF have a view, against 60% of homes under 1,908 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 1,908 SF10 sales1,908–2,148 SF9 sales2,159–2,276 SF9 salesOver 2,276 SF10 salesAll38 salesReal difference?
Net sale price average$339,566$387,256$382,628$468,379$394,958✓ large
Net price per SF average$201$192$171$188$188unclear
Living area average1,6972,0182,2362,4822,107by design
Year built median20102006200720102008unclear

4.10 The numbers: selling

Under 1,908 SF10 sales1,908–2,148 SF9 sales2,159–2,276 SF9 salesOver 2,276 SF10 salesAll38 salesReal difference?
Days on market median111704912384unclear
Discount from original list average9.0%6.8%8.1%6.5%7.6%unclear
Price cut before sale70%56%44%50%55%unclear
Seller paid closing costs or repairs60%44%67%70%61%unclear
Has a view60%33%56%40%47%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 · 38 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:43:45.376510 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 13 6 8 11 38 sales Sales per group Before 2007: 13 sales (34%) 2007: 6 sales (16%) 2008–2011: 8 sales (21%) After 2011: 11 sales (29%)
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 200720072008–2011After 2011Real difference?
Net sale price$369K$362K$440K$410Kunclear
Net price per SF$181 per SF$178 per SF$193 per SF$200 per SFunclear
Living area2,062 SF2,060 SF2,284 SF2,058 SFunclear
Days on market134 days79 days48 days89 daysunclear
Discount from original list9.9%8.5%5.5%5.9%unclear
Price cut before sale77%33%38%55%unclear
Seller paid closing costs or repairs62%33%88%55%unclear
Has a view31%50%50%64%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:43:45.398490 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 13 sales 2007 6 sales 2008– 2011 8 sales After 2011 11 sales $0K $200K $400K $369K $362K $440K $410K Net sale price, average

The average is $410K for homes built after 2011 and $369K for homes built before 2007. It does not move in a straight line; homes built 2008–2011 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:43:45.421751 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 13 sales 2007 6 sales 2008– 2011 8 sales After 2011 11 sales $0 $100 $200 $181 $178 $193 $200 Net price per SF, average

The average is $200 per SF for homes built after 2011 and $181 per SF for homes built before 2007. It does not move in a straight line; homes built after 2011 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:43:45.444234 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 13 sales 2007 6 sales 2008– 2011 8 sales After 2011 11 sales 0 1,000 2,000 2,062 2,060 2,284 2,058 Living area (SF), average

The average is 2,058 SF for homes built after 2011 and 2,062 SF for homes built before 2007. It does not move in a straight line; homes built 2008–2011 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:43:45.466488 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 13 sales 2007 6 sales 2008– 2011 8 sales After 2011 11 sales 0 50 100 150 134 79 48 89 Days on market, median

The median is 89 days for homes built after 2011 and 134 days for homes built before 2007. It does not move in a straight line; homes built before 2007 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:43:45.490953 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 13 sales 2007 6 sales 2008– 2011 8 sales After 2011 11 sales 0.0% 5.0% 10.0% 9.9% 8.5% 5.5% 5.9% Discount from original list, average

The average is 5.9% for homes built after 2011 and 9.9% for homes built before 2007. It does not move in a straight line; homes built before 2007 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

2026-10-26T07:43:45.517084 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% 77 62 31 33 33 50 38 88 50 55 55 64 Before 2007 2007 2008–2011 After 2011

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

  • 55% of homes built after 2011 had a price cut before sale, against 77% of homes built before 2007. Defined in 8.1.7.
  • 55% of homes built after 2011 had the seller pay closing costs or repairs, against 62% of homes built before 2007. Defined in 8.1.8.
  • 64% of homes built after 2011 have a view, against 31% of homes built before 2007. 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 200713 sales20076 sales2008–20118 salesAfter 201111 salesAll38 salesReal difference?
Net sale price average$369,338$362,008$440,124$410,360$394,958unclear
Net price per SF average$181$178$193$200$188unclear
Living area average2,0622,0602,2842,0582,107unclear
Year built median20062007201020142008by design

5.10 The numbers: selling

Before 200713 sales20076 sales2008–20118 salesAfter 201111 salesAll38 salesReal difference?
Days on market median13479488984unclear
Discount from original list average9.9%8.5%5.5%5.9%7.6%unclear
Price cut before sale77%33%38%55%55%unclear
Seller paid closing costs or repairs62%33%88%55%61%unclear
Has a view31%50%50%64%47%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 · 38 sales · October 26, 2025 – October 25, 2026

Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood. 2 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T07:43:45.535601 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 18 18 36 sales Sales per group View: 18 sales (50%) No view: 18 sales (50%)
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$404K$381Kunclear
Net price per SF$192 per SF$186 per SFunclear
Living area2,115 SF2,066 SFunclear
Year built20102007unclear
Days on market48 days106 daysunclear
Discount from original list7.0%7.7%unclear
Price cut before sale39%67%unclear
Seller paid closing costs or repairs72%50%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:43:45.552939 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 18 sales $0K $100K $200K $300K $400K $404K $381K Net sale price, average

The average is $404K for homes with a view and $381K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-10-26T07:43:45.573789 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 18 sales $0 $50 $100 $150 $200 $192 $186 Net price per SF, average

The average is $192 per SF for homes with a view and $186 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-10-26T07:43:45.672163 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 18 sales 0 1,000 2,000 2,115 2,066 Living area (SF), average

The average is 2,115 SF for homes with a view and 2,066 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:43:45.695948 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 18 sales 2006 2008 2010 2012 2014 2010 2007 Year built: median (dot) and middle half (bar)

The median is 2010 for homes with a view and 2007 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:43:45.715898 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 18 sales 0 50 100 48 106 Days on market, median

The median is 48 days for homes with a view and 106 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-10-26T07:43:45.735389 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 18 sales 0.0% 2.0% 4.0% 6.0% 8.0% 7.0% 7.7% Discount from original list, average

The average is 7.0% for homes with a view and 7.7% 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

2026-10-26T07:43:45.755071 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 39 72 67 50 View No view

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

  • 39% of homes with a view had a price cut before sale, against 67% of homes without a view. Defined in 8.1.7.
  • 72% of homes with a view had the seller pay closing costs or repairs, against 50% 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

View18 salesNo view18 salesAll36 salesReal difference?
Net sale price average$404,099$380,706$392,403unclear
Net price per SF average$192$186$189unclear
Living area average2,1152,0662,090unclear
Year built median201020072008unclear

6.11 The numbers: selling

View18 salesNo view18 salesAll36 salesReal difference?
Days on market median4810677unclear
Discount from original list average7.0%7.7%7.4%unclear
Price cut before sale39%67%53%unclear
Seller paid closing costs or repairs72%50%61%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.4.

7. New constructionBasic statistics · 0 sales · October 26, 2025 – October 25, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 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 Heritage Oaks.

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
38 resale sales. Average $394,958; median $380,000; standard deviation $62,346; middle half (25th–75th percentile) $353,682–$421,125; lowest $300,000, highest $563,900. 23 sales had a seller payment; their median payment was $2,400.

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
38 resale sales. Average $188; median $189; standard deviation $19; middle half (25th–75th percentile) $174–$206; lowest $153, highest $218.

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
38 resale sales. Average 2,107; median 2,154; standard deviation 317; middle half (25th–75th percentile) 1,870–2,303; lowest 1,395, highest 2,693.

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
38 resale sales. Average 2009; median 2008; standard deviation 3; middle half (25th–75th percentile) 2006–2012; lowest 2005, highest 2016.

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
38 resale sales. Average 119; median 84; standard deviation 134; middle half (25th–75th percentile) 30–161; lowest 0, highest 722. 1 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
38 resale sales. Average 7.6%; median 6.8%; standard deviation 5.2%; middle half (25th–75th percentile) 3.5%–10.5%; lowest 0.0%, highest 21.8%. 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
21 of 38 resale sales (55.3%).

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
23 of 38 resale sales (60.5%).

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
18 sales with a view, 18 without, 2 unclassified. Most common View entries: Park/Greenbelt 13, Neighborhood 12, None 9, Trees/Woods 9, See Remarks 3, Creek/Stream 3, Hill Country 1, Garden 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Georgetown, SubdivisionName contains any of “heritage oaks” (case-insensitive). A record is kept when its subdivision name belongs to the Heritage Oaks family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 38 closed Heritage Oaks records over the prior year, in ZIP 78633. 8 subdivision spellings kept: Heritage Oaks Sec 1 (11); Heritage Oaks (10); Heritage Oaks Sec 3 (6); Heritage Oaks Sec 7 (4); Heritage Oaks Sec 4 (2); Heritage Oaks Sec 4-B (2); Heritage Oaks Sec 6 (2); Heritage Oaks Sec 2 (1). No other names were found by the search.

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 19 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
38 single-family sales in the window: 38 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
38 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 $354K”.
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 $354K: $300,000–$353,500 (10 sales); $354K–$380K: $354,230–$380,000 (10 sales); $384K–$410K: $383,700–$409,500 (8 sales); Over $410K: $425,000–$563,900 (10 sales)
Quartiles by living area: Under 1,908 SF: 1,395–1,858 SF (10 sales); 1,908–2,148 SF: 1,908–2,148 SF (9 sales); 2,159–2,276 SF: 2,159–2,276 SF (9 sales); Over 2,276 SF: 2,312–2,693 SF (10 sales)
Quartiles by year built: Before 2007: 2005–2006 (13 sales); 2007: 2007–2007 (6 sales); 2008–2011: 2008–2011 (8 sales); After 2011: 2012–2016 (11 sales)
View and no view: View: MLS lists a view (18 sales); No view: None or Neighborhood (18 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 $394,958, median $380,000. Days on market: average 119, median 84: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

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

8.2.8 Mann–Whitney U test

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

8.2.9 Chi-square test

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

8.2.10 Real difference (significance)

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

8.2.11 Size of a difference

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

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 2.2530.5229p < 0.0063Unclearε² = 0.061medium
Living areaKruskal–WallisH = 20.2430.0002p < 0.0063Yesε² = 0.547large
Year builtKruskal–WallisH = 3.9930.2626p < 0.0063Unclearε² = 0.108medium
Days on marketKruskal–WallisH = 4.6530.1997p < 0.0063Unclearε² = 0.126medium
Discount from original listKruskal–WallisH = 4.2030.2403p < 0.0063Unclearε² = 0.114medium
Price cut before saleChi-squareχ² = 1.1930.7549p < 0.0063UnclearCramér’s V = 0.177small
Seller paid closing costs or repairsChi-squareχ² = 3.3630.3387p < 0.0063UnclearCramér’s V = 0.298small
Has a viewChi-squareχ² = 1.2030.7535p < 0.0063UnclearCramér’s V = 0.178small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 22.063< 0.0001p < 0.0063Yesε² = 0.596large
Net price per SFKruskal–WallisH = 11.8030.0081p < 0.0063Unclearε² = 0.319large
Year builtKruskal–WallisH = 4.2130.2392p < 0.0063Unclearε² = 0.114medium
Days on marketKruskal–WallisH = 2.4530.4844p < 0.0063Unclearε² = 0.066medium
Discount from original listKruskal–WallisH = 1.8630.6013p < 0.0063Unclearε² = 0.050small
Price cut before saleChi-squareχ² = 1.4230.7016p < 0.0063UnclearCramér’s V = 0.193small
Seller paid closing costs or repairsChi-squareχ² = 1.4930.6839p < 0.0063UnclearCramér’s V = 0.198small
Has a viewChi-squareχ² = 1.8130.6126p < 0.0063UnclearCramér’s V = 0.218small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 7.9730.0467p < 0.0063Unclearε² = 0.215large
Net price per SFKruskal–WallisH = 8.0930.0442p < 0.0063Unclearε² = 0.219large
Living areaKruskal–WallisH = 3.4830.3237p < 0.0063Unclearε² = 0.094medium
Days on marketKruskal–WallisH = 3.4030.3341p < 0.0063Unclearε² = 0.092medium
Discount from original listKruskal–WallisH = 6.5630.0874p < 0.0063Unclearε² = 0.177large
Price cut before saleChi-squareχ² = 4.6630.1987p < 0.0063UnclearCramér’s V = 0.350medium
Seller paid closing costs or repairsChi-squareχ² = 4.4630.2156p < 0.0063UnclearCramér’s V = 0.343medium
Has a viewChi-squareχ² = 2.6430.4499p < 0.0063UnclearCramér’s V = 0.264small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 193.00—0.3344p < 0.0063Unclearrank-biserial r = 0.191small
Net price per SFMann–Whitney UU = 186.00—0.4572p < 0.0063Unclearrank-biserial r = 0.148small
Living areaMann–Whitney UU = 170.00—0.8124p < 0.0063Unclearrank-biserial r = 0.049negligible
Year builtMann–Whitney UU = 217.00—0.0814p < 0.0063Unclearrank-biserial r = 0.340medium
Days on marketMann–Whitney UU = 122.00—0.2113p < 0.0063Unclearrank-biserial r = 0.247small
Discount from original listMann–Whitney UU = 146.00—0.6239p < 0.0063Unclearrank-biserial r = 0.099negligible
Price cut before saleChi-squareχ² = 2.7910.0951p < 0.0063UnclearCramér’s V = 0.278small
Seller paid closing costs or repairsChi-squareχ² = 1.8710.1715p < 0.0063UnclearCramér’s V = 0.228small

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 38 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 October 26, 2026. Map data © OpenStreetMap contributors. ALEX Companies · Licensed by the Texas Real Estate Commission · Broker: Alexander Tiffany Southwest, LLC (ALEX Real Estate), #565194-BB · Diane Hart Alexander, Designated Broker, #574877-B.