ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Sun City Georgetown

Georgetown, TX 78633
Resale homes · closed Apr 27 – Oct 23, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 24, 2026 · 8:45 PM 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, 180 days
306
single-family resale homes
Median net sale price
$366,156
average $407,586
Median net price per SF
$210
average $214
Median days on market
44 days
average 74 days
1. SummaryResale homes · 306 sales · April 27, 2026 – October 23, 2026

This study looks at the 306 resale homes sold in Sun City Georgetown in the 180 days to October 23, 2026. 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 sold306 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 · 77 sales$310K–$364K · 76 sales$368K–$462K · 77 salesOver $462K · 76 sales
3. Quartiles by net sale priceResale homes · 306 sales · April 27, 2026 – October 23, 2026

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

2026-10-24T20:45:48.666521 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 77 76 77 76 306 sales Sales per group Under $310K: 77 sales (25%) $310K–$364K: 76 sales (25%) $368K–$462K: 77 sales (25%) Over $462K: 76 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–$364K$368K–$462KOver $462K
Higher-priced homes Over $462K
  • Are much larger.
  • Sell for more per square foot.
  • Are more likely to have a view.
  • Sell closer to their first asking price.
Lower-priced homes Under $310K
  • Are much smaller.
  • Sell for less per square foot.
  • Are less likely to have a view.
  • Sell further below their first asking price.

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–$364K$368K–$462KOver $462KReal difference?
Net price per SF$195 per SFLowest$203 per SF$214 per SF$244 per SFHighest✓ large
Living area1,420 SFSmallest1,671 SF1,974 SF2,475 SFLargest✓ large
Year built2005200620072008unclear
Days on market60 days50 days27 days25 daysunclear
Discount from original list8.2%Biggest6.6%3.8%Smallest4.3%✓ medium
Price cut before sale56%55%36%37%unclear
Seller paid closing costs or repairs65%59%55%59%unclear
Has a view47%Fewest51%47%79%Most✓ small

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 Homes over $462K sell for about $49 per SF (25%) more than homes under $310K

2026-10-24T20:45:48.695180 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 77 sales $310K– $364K 76 sales $368K– $462K 77 sales Over $462K 76 sales $0 $100 $200 $195 $203 $214 $244 Net price per SF, average

The average is $244 per SF for homes over $462K and $195 per SF for homes under $310K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $462K are about 1,060 SF (74%) larger than homes under $310K

2026-10-24T20:45:48.717376 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 77 sales $310K– $364K 76 sales $368K– $462K 77 sales Over $462K 76 sales 0 1,000 2,000 1,420 1,671 1,974 2,475 Living area (SF), average

The average is 2,475 SF for homes over $462K and 1,420 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 Year built: no clear difference

2026-10-24T20:45:48.740717 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 77 sales $310K– $364K 76 sales $368K– $462K 77 sales Over $462K 76 sales 2000 2005 2010 2015 2005 2006 2007 2008 Year built: median (dot) and middle half (bar)

The median is 2008 for homes over $462K and 2005 for homes under $310K. 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

2026-10-24T20:45:48.762868 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 77 sales $310K– $364K 76 sales $368K– $462K 77 sales Over $462K 76 sales 0 20 40 60 60 50 27 25 Days on market, median

The median is 25 days for homes over $462K and 60 days for homes under $310K. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Homes over $462K sell about 4 percentage points closer to their first asking price than homes under $310K

2026-10-24T20:45:48.785403 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 77 sales $310K– $364K 76 sales $368K– $462K 77 sales Over $462K 76 sales 0.0% 2.5% 5.0% 7.5% 8.2% 6.6% 3.8% 4.3% Discount from original list, average

The average is 4.3% for homes over $462K and 8.2% for homes under $310K. It does not move in a straight line; homes under $310K are highest. Defined in 8.1.6.

✓ Real difference · medium

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

2026-10-24T20:45:48.815054 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% 56 65 47 55 59 51 36 55 47 37 59 79 Under $310K $310K–$364K $368K–$462K Over $462K

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

  • 37% of homes over $462K had a price cut before sale, against 56% of homes under $310K. Defined in 8.1.7.
  • 59% of homes over $462K had the seller pay closing costs or repairs, against 65% of homes under $310K. Defined in 8.1.8.
  • 79% of homes over $462K have a view, against 47% 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: ✓ Real difference · small

3.9 The numbers: price and size

Under $310K77 sales$310K–$364K76 sales$368K–$462K77 salesOver $462K76 salesAll306 salesReal difference?
Net sale price average$273,327$334,812$418,775$605,050$407,586by design
Net price per SF average$195$203$214$244$214✓ large
Living area average1,4201,6711,9742,4751,884✓ large
Year built median20052006200720082006unclear

3.10 The numbers: selling

Under $310K77 sales$310K–$364K76 sales$368K–$462K77 salesOver $462K76 salesAll306 salesReal difference?
Days on market median6050272544unclear
Discount from original list average8.2%6.6%3.8%4.3%5.7%✓ medium
Price cut before sale56%55%36%37%46%unclear
Seller paid closing costs or repairs65%59%55%59%59%unclear
Has a view47%51%47%79%56%✓ small

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 · 306 sales · April 27, 2026 – October 23, 2026

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

2026-10-24T20:45:48.835760 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 76 76 78 76 306 sales Sales per group Under 1,490 SF: 76 sales (25%) 1,490–1,822 SF: 76 sales (25%) 1,845–2,091 SF: 78 sales (25%) Over 2,091 SF: 76 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 1,490 SF1,490–1,822 SF1,845–2,091 SFOver 2,091 SF
Larger homes Over 2,091 SF
  • Sell for much more.
  • Sell for more per square foot.
Smaller homes Under 1,490 SF
  • Sell for much less.
  • Sell for less 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 1,490 SF1,490–1,822 SF1,845–2,091 SFOver 2,091 SFReal difference?
Net sale price$284KLowest$338K$420K$587KHighest✓ large
Net price per SF$208 per SF$205 per SFLowest$214 per SF$228 per SFHighest✓ small
Year built2009200520052006unclear
Days on market54 days33 days28 days47 daysunclear
Discount from original list7.1%5.6%5.2%5.1%unclear
Price cut before sale55%45%41%43%unclear
Seller paid closing costs or repairs64%61%56%57%unclear
Has a view50%54%54%66%unclear

4.3 Homes over 2,091 SF sell for about $304K (107%) more than homes under 1,490 SF

2026-10-24T20:45:48.856952 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,490 SF 76 sales 1,490– 1,822 SF 76 sales 1,845– 2,091 SF 78 sales Over 2,091 SF 76 sales $0K $200K $400K $600K $284K $338K $420K $587K Net sale price, average

The average is $587K for homes over 2,091 SF and $284K for homes under 1,490 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 2,091 SF sell for about $20 per SF (9%) more than homes under 1,490 SF

2026-10-24T20:45:48.879363 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,490 SF 76 sales 1,490– 1,822 SF 76 sales 1,845– 2,091 SF 78 sales Over 2,091 SF 76 sales $0 $100 $200 $208 $205 $214 $228 Net price per SF, average

The average is $228 per SF for homes over 2,091 SF and $208 per SF for homes under 1,490 SF. It does not move in a straight line; homes over 2,091 SF are highest. Defined in 8.1.2.

✓ Real difference · small

4.5 Year built: no clear difference

2026-10-24T20:45:48.902425 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,490 SF 76 sales 1,490– 1,822 SF 76 sales 1,845– 2,091 SF 78 sales Over 2,091 SF 76 sales 2000 2005 2010 2015 2009 2005 2005 2006 Year built: median (dot) and middle half (bar)

The median is 2006 for homes over 2,091 SF and 2009 for homes under 1,490 SF. It does not move in a straight line; homes under 1,490 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-24T20:45:48.924776 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,490 SF 76 sales 1,490– 1,822 SF 76 sales 1,845– 2,091 SF 78 sales Over 2,091 SF 76 sales 0 20 40 60 54 33 28 47 Days on market, median

The median is 47 days for homes over 2,091 SF and 54 days for homes under 1,490 SF. It does not move in a straight line; homes under 1,490 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-24T20:45:48.947212 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,490 SF 76 sales 1,490– 1,822 SF 76 sales 1,845– 2,091 SF 78 sales Over 2,091 SF 76 sales 0.0% 2.5% 5.0% 7.5% 7.1% 5.6% 5.2% 5.1% Discount from original list, average

The average is 5.1% for homes over 2,091 SF and 7.1% for homes under 1,490 SF. It falls step by step from the lowest range to the 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

2026-10-24T20:45:48.973988 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 55 64 50 45 61 54 41 56 54 43 57 66 Under 1,490 SF 1,490–1,822 SF 1,845–2,091 SF Over 2,091 SF

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

  • 43% of homes over 2,091 SF had a price cut before sale, against 55% of homes under 1,490 SF. Defined in 8.1.7.
  • 57% of homes over 2,091 SF had the seller pay closing costs or repairs, against 64% of homes under 1,490 SF. Defined in 8.1.8.
  • 66% of homes over 2,091 SF have a view, against 50% of homes under 1,490 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 1,490 SF76 sales1,490–1,822 SF76 sales1,845–2,091 SF78 salesOver 2,091 SF76 salesAll306 salesReal difference?
Net sale price average$283,889$338,350$420,351$587,420$407,586✓ large
Net price per SF average$208$205$214$228$214✓ small
Living area average1,3691,6531,9612,5491,884by design
Year built median20092005200520062006unclear

4.10 The numbers: selling

Under 1,490 SF76 sales1,490–1,822 SF76 sales1,845–2,091 SF78 salesOver 2,091 SF76 salesAll306 salesReal difference?
Days on market median5433284744unclear
Discount from original list average7.1%5.6%5.2%5.1%5.7%unclear
Price cut before sale55%45%41%43%46%unclear
Seller paid closing costs or repairs64%61%56%57%59%unclear
Has a view50%54%54%66%56%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 · 306 sales · April 27, 2026 – October 23, 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.

2026-10-24T20:45:48.995392 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 77 68 82 79 306 sales Sales per group Before 2000: 77 sales (25%) 2000–2005: 68 sales (22%) 2006–2014: 82 sales (27%) After 2014: 79 sales (26%)
Bottom line

5.1 Key differences

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

Before 20002000–20052006–2014After 2014
Newer homes After 2014
  • Are more likely to have a view.
  • Sell for more per square foot.
Older homes Before 2000
  • Are less likely to have a view.
  • Sell for less per square foot.

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 20002000–20052006–2014After 2014Real difference?
Net sale price$383K$419K$394K$435Kunclear
Net price per SF$207 per SFLowest$208 per SF$213 per SF$226 per SFHighest✓ medium
Living area1,849 SF1,945 SF1,836 SF1,915 SFunclear
Days on market44 days42 days25 days59 daysunclear
Discount from original list6.4%5.7%5.1%5.8%unclear
Price cut before sale51%41%37%56%unclear
Seller paid closing costs or repairs56%65%61%57%unclear
Has a view43%Fewest46%79%Most53%✓ small

5.3 Net sale price: no clear difference

2026-10-24T20:45:49.016479 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 77 sales 2000– 2005 68 sales 2006– 2014 82 sales After 2014 79 sales $0K $200K $400K $383K $419K $394K $435K Net sale price, average

The average is $435K for homes built after 2014 and $383K for homes built before 2000. It does not move in a straight line; homes built after 2014 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Homes built after 2014 sell for about $19 per SF (9%) more than homes built before 2000

2026-10-24T20:45:49.039384 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 77 sales 2000– 2005 68 sales 2006– 2014 82 sales After 2014 79 sales $0 $100 $200 $207 $208 $213 $226 Net price per SF, average

The average is $226 per SF for homes built after 2014 and $207 per SF for homes built before 2000. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · medium

5.5 Living area: no clear difference

2026-10-24T20:45:49.060817 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 77 sales 2000– 2005 68 sales 2006– 2014 82 sales After 2014 79 sales 0 1,000 2,000 1,849 1,945 1,836 1,915 Living area (SF), average

The average is 1,915 SF for homes built after 2014 and 1,849 SF for homes built before 2000. It does not move in a straight line; homes built 2000–2005 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-24T20:45:49.082876 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 77 sales 2000– 2005 68 sales 2006– 2014 82 sales After 2014 79 sales 0 20 40 60 44 42 25 59 Days on market, median

The median is 59 days for homes built after 2014 and 44 days for homes built before 2000. It does not move in a straight line; homes built after 2014 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-24T20:45:49.105065 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 77 sales 2000– 2005 68 sales 2006– 2014 82 sales After 2014 79 sales 0.0% 2.0% 4.0% 6.0% 6.4% 5.7% 5.1% 5.8% Discount from original list, average

The average is 5.8% for homes built after 2014 and 6.4% for homes built before 2000. It does not move in a straight line; homes built before 2000 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

2026-10-24T20:45:49.130729 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% 51 56 43 41 65 46 37 61 79 56 57 53 Before 2000 2000–2005 2006–2014 After 2014

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

  • 56% of homes built after 2014 had a price cut before sale, against 51% of homes built before 2000. Defined in 8.1.7.
  • 57% of homes built after 2014 had the seller pay closing costs or repairs, against 56% of homes built before 2000. Defined in 8.1.8.
  • 53% of homes built after 2014 have a view, against 43% of homes built before 2000. 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: ✓ Real difference · small

5.9 The numbers: price and size

Before 200077 sales2000–200568 sales2006–201482 salesAfter 201479 salesAll306 salesReal difference?
Net sale price average$383,404$419,143$394,158$435,148$407,586unclear
Net price per SF average$207$208$213$226$214✓ medium
Living area average1,8491,9451,8361,9151,884unclear
Year built median19972003200820192006by design

5.10 The numbers: selling

Before 200077 sales2000–200568 sales2006–201482 salesAfter 201479 salesAll306 salesReal difference?
Days on market median4442255944unclear
Discount from original list average6.4%5.7%5.1%5.8%5.7%unclear
Price cut before sale51%41%37%56%46%unclear
Seller paid closing costs or repairs56%65%61%57%59%unclear
Has a view43%46%79%53%56%✓ small

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 · 306 sales · April 27, 2026 – October 23, 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.

2026-10-24T20:45:49.149493 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 171 129 300 sales Sales per group View: 171 sales (57%) No view: 129 sales (43%)
Bottom line

6.1 Key differences

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

ViewNo view
Homes with a view MLS lists a view
  • Sell for more per square foot.
  • Sell for more.
  • Sell faster.
Homes without a view no view listed
  • Sell for less per square foot.
  • Sell for less.
  • Take longer to sell.

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$440KHighest$365KLowest✓ small
Net price per SF$222 per SFHighest$203 per SFLowest✓ medium
Living area1,944 SF1,801 SFunclear
Year built20072003unclear
Days on market25 daysFastest53 daysSlowest✓ small
Discount from original list5.1%6.5%unclear
Price cut before sale40%54%unclear
Seller paid closing costs or repairs60%58%unclear

6.3 Homes with a view sell for about $76K (21%) more than homes without a view

2026-10-24T20:45:49.166014 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 171 sales No view 129 sales $0K $200K $400K $440K $365K Net sale price, average

The average is $440K for homes with a view and $365K for homes without a view. Defined in 8.1.1.

✓ Real difference · small

6.4 Homes with a view sell for about $19 per SF (9%) more than homes without a view

2026-10-24T20:45:49.183526 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 171 sales No view 129 sales $0 $100 $200 $222 $203 Net price per SF, average

The average is $222 per SF for homes with a view and $203 per SF for homes without a view. Defined in 8.1.2.

✓ Real difference · medium

6.5 Living area: no clear difference

2026-10-24T20:45:49.223925 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 171 sales No view 129 sales 0 500 1,000 1,500 2,000 1,944 1,801 Living area (SF), average

The average is 1,944 SF for homes with a view and 1,801 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-24T20:45:49.244109 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 171 sales No view 129 sales 2000 2004 2008 2012 2016 2007 2003 Year built: median (dot) and middle half (bar)

The median is 2007 for homes with a view and 2003 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Homes with a view sell 28 days faster than homes without a view

2026-10-24T20:45:49.262339 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 171 sales No view 129 sales 0 20 40 60 25 53 Days on market, median

The median is 25 days for homes with a view and 53 days for homes without a view. Defined in 8.1.5.

✓ Real difference · small

6.8 Discount from original list: no clear difference

2026-10-24T20:45:49.279716 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 171 sales No view 129 sales 0.0% 2.0% 4.0% 6.0% 5.1% 6.5% Discount from original list, average

The average is 5.1% for homes with a view and 6.5% 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

2026-10-24T20:45:49.298278 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 40 60 54 58 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 54% of homes without a view. Defined in 8.1.7.
  • 60% 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

View171 salesNo view129 salesAll300 salesReal difference?
Net sale price average$440,363$364,649$407,806✓ small
Net price per SF average$222$203$214✓ medium
Living area average1,9441,8011,883unclear
Year built median200720032006unclear

6.11 The numbers: selling

View171 salesNo view129 salesAll300 salesReal difference?
Days on market median255344✓ small
Discount from original list average5.1%6.5%5.7%unclear
Price cut before sale40%54%46%unclear
Seller paid closing costs or repairs60%58%59%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 · 12 sales · April 27, 2026 – October 23, 2026

Homes sold new by the builder in the same 180 days. They are left out of every other section and shown here as basic figures only: 12 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 Sun City Georgetown.
MeasureAverageMedian
Sales12
Net sale price$420,609$365,495
Net price per SF$243$239
Living area (SF)1,7281,550
Days on market8240
Discount from original list7.0%6.0%
Price cut before sale58% of sales
Seller paid closing costs or repairs50% of sales
Year built2024–2026

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
306 resale sales. Average $407,586; median $366,156; standard deviation $154,076; middle half (25th–75th percentile) $309,125–$462,375; lowest $203,450, highest $1,588,000. 182 sales had a seller payment; their median payment was $2,000.

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
306 resale sales. Average $214; median $210; standard deviation $33; middle half (25th–75th percentile) $193–$231; lowest $134, highest $346.

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
306 resale sales. Average 1,884; median 1,845; standard deviation 486; middle half (25th–75th percentile) 1,492–2,091; lowest 915, highest 4,866.

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
306 resale sales. Average 2007; median 2006; standard deviation 9; middle half (25th–75th percentile) 1999–2015; lowest 1995, highest 2026.

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
306 resale sales. Average 74; median 44; standard deviation 94; middle half (25th–75th percentile) 9–95; lowest 0, highest 564. 17 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
306 resale sales. Average 5.7%; median 4.6%; standard deviation 5.7%; middle half (25th–75th percentile) 1.5%–8.6%; lowest −6.2%, highest 31.3%. 12 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
141 of 306 resale sales (46.1%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
182 of 306 resale sales (59.5%).

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
171 sales with a view, 129 without, 6 unclassified. Most common View entries: Park/Greenbelt 134, Neighborhood 98, None 65, Trees/Woods 62, Golf Course 32, Hill Country 15, See Remarks 13, Panoramic 8.

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 “sun city georgetown”, “sun city”, “sun city texas”, “sun city george town”, “sun city georgetown nbhrd” (case-insensitive). A record is kept when its subdivision name belongs to the Sun City Georgetown family, the same rule comparable sales use (it includes Sun City, Sun City Texas, proven adjacent and priced alike).
The data
Pulled October 24, 2026: 585 closed Sun City Georgetown records over the prior year, in ZIP 78633. 169 subdivision spellings kept, the most common: Sun City (93); Sun City Texas (63); Sun City Georgetown Neighborhood 04 (18); Sun City Georgetown (17); Sun City Georgetown Ph 04A Neighborhood 15 Pu (12); Sun City Georgetown Ph 02A Neighborhood 11 Pu (11); Sun City Georgetown Neighborhood 06 Amd B (10); Sun City Georgetown Neighborhood 07 (9); Sun City Georgetown Ph 02 Neighborhood 10 Pud (9); Sun City Georgetown Neighborhood 02 Amd B (8); Sun City Nbrhd 83 (8); Sun City Georgetown Neighborhood 40 Pud (8); and 157 more (319 records). No other names were found by the search.

8.2.2 Study window

In simple terms
The most recent 180 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales.
Statistically
CloseDate from April 27, 2026 to October 23, 2026 inclusive.
The data
318 single-family sales in the window: 306 resale, 12 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
306 resale; 12 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
1 sale(s) with no original list price

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: $203,450–$309,000 (77 sales); $310K–$364K: $309,500–$364,000 (76 sales); $368K–$462K: $368,313–$462,500 (77 sales); Over $462K: $462,560–$1,588,000 (76 sales)
Quartiles by living area: Under 1,490 SF: 915–1,488 SF (76 sales); 1,490–1,822 SF: 1,490–1,822 SF (76 sales); 1,845–2,091 SF: 1,845–2,091 SF (78 sales); Over 2,091 SF: 2,100–4,866 SF (76 sales)
Quartiles by year built: Before 2000: 1995–1999 (77 sales); 2000–2005: 2000–2005 (68 sales); 2006–2014: 2006–2014 (82 sales); After 2014: 2015–2026 (79 sales)
View and no view: View: MLS lists a view (171 sales); No view: None or Neighborhood (129 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 $407,586, median $366,156. Days on market: average 74, median 44: 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
11 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 = 86.993< 0.0001p < 0.0063Yesε² = 0.285large
Living areaKruskal–WallisH = 228.403< 0.0001p < 0.0063Yesε² = 0.749large
Year builtKruskal–WallisH = 2.7030.4402p < 0.0063Unclearε² = 0.009negligible
Days on marketKruskal–WallisH = 11.9130.0077p < 0.0063Unclearε² = 0.039small
Discount from original listKruskal–WallisH = 32.473< 0.0001p < 0.0063Yesε² = 0.106medium
Price cut before saleChi-squareχ² = 11.0730.0114p < 0.0063UnclearCramér’s V = 0.190small
Seller paid closing costs or repairsChi-squareχ² = 1.7330.6296p < 0.0063UnclearCramér’s V = 0.075negligible
Has a viewChi-squareχ² = 22.253< 0.0001p < 0.0063YesCramér’s V = 0.270small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 229.743< 0.0001p < 0.0063Yesε² = 0.753large
Net price per SFKruskal–WallisH = 12.7130.0053p < 0.0063Yesε² = 0.042small
Year builtKruskal–WallisH = 8.5130.0366p < 0.0063Unclearε² = 0.028small
Days on marketKruskal–WallisH = 6.3930.0939p < 0.0063Unclearε² = 0.021small
Discount from original listKruskal–WallisH = 8.8530.0314p < 0.0063Unclearε² = 0.029small
Price cut before saleChi-squareχ² = 3.6530.3015p < 0.0063UnclearCramér’s V = 0.109small
Seller paid closing costs or repairsChi-squareχ² = 1.3930.7076p < 0.0063UnclearCramér’s V = 0.067negligible
Has a viewChi-squareχ² = 4.3430.2271p < 0.0063UnclearCramér’s V = 0.119small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 6.0530.1092p < 0.0063Unclearε² = 0.020small
Net price per SFKruskal–WallisH = 27.193< 0.0001p < 0.0063Yesε² = 0.089medium
Living areaKruskal–WallisH = 0.7630.8597p < 0.0063Unclearε² = 0.002negligible
Days on marketKruskal–WallisH = 10.3830.0156p < 0.0063Unclearε² = 0.034small
Discount from original listKruskal–WallisH = 1.8530.6039p < 0.0063Unclearε² = 0.006negligible
Price cut before saleChi-squareχ² = 7.2230.0652p < 0.0063UnclearCramér’s V = 0.154small
Seller paid closing costs or repairsChi-squareχ² = 1.4830.6876p < 0.0063UnclearCramér’s V = 0.069negligible
Has a viewChi-squareχ² = 26.653< 0.0001p < 0.0063YesCramér’s V = 0.295small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 14,037.00—< 0.0001p < 0.0063Yesrank-biserial r = 0.273small
Net price per SFMann–Whitney UU = 14,643.50—< 0.0001p < 0.0063Yesrank-biserial r = 0.328medium
Living areaMann–Whitney UU = 12,695.50—0.0251p < 0.0063Unclearrank-biserial r = 0.151small
Year builtMann–Whitney UU = 12,889.50—0.0123p < 0.0063Unclearrank-biserial r = 0.169small
Days on marketMann–Whitney UU = 8,383.50—0.0004p < 0.0063Yesrank-biserial r = 0.240small
Discount from original listMann–Whitney UU = 9,307.50—0.0206p < 0.0063Unclearrank-biserial r = 0.156small
Price cut before saleChi-squareχ² = 6.2210.0126p < 0.0063UnclearCramér’s V = 0.144small
Seller paid closing costs or repairsChi-squareχ² = 0.1310.7147p < 0.0063UnclearCramér’s V = 0.021negligible

8.4 Data notes

Left out of the analysis: 12 new-construction sales (basic statistics only, section 7); 1 sale(s) with no original list price. 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 306 closed MLS resale sales; the 12 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 24, 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.