ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Sun City Georgetown

Georgetown, TX 78633
Resale homes · closed Apr 29 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 6:42 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, 180 days
299
single-family resale homes
Median net sale price
$368,313
average $409,581
Median net price per SF
$210
average $214
Median days on market
44 days
average 74 days
1. SummaryResale homes · 299 sales · April 29, 2026 – October 25, 2026

This study looks at the 299 resale homes sold in Sun City Georgetown in the 180 days to October 25, 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 sold299 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 · 75 sales$310K–$368K · 75 sales$370K–$463K · 74 salesOver $463K · 75 sales
3. Quartiles by net sale priceResale homes · 299 sales · April 29, 2026 – 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.

2026-10-26T06:43:08.419049 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 75 75 74 75 299 sales Sales per group Under $310K: 75 sales (25%) $310K–$368K: 75 sales (25%) $370K–$463K: 74 sales (25%) Over $463K: 75 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–$368K$370K–$463KOver $463K
Higher-priced homes Over $463K
  • 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–$368K$370K–$463KOver $463KReal difference?
Net price per SF$195 per SFLowest$202 per SF$215 per SF$245 per SFHighest✓ large
Living area1,423 SFSmallest1,678 SF1,973 SF2,476 SFLargest✓ large
Year built2005200520072007unclear
Days on market67 days44 days28 days23 daysunclear
Discount from original list8.5%Biggest6.5%3.8%Smallest4.2%✓ medium
Price cut before sale57%53%38%36%unclear
Seller paid closing costs or repairs65%59%55%57%unclear
Has a view44%Fewest52%47%80%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 $463K sell for about $50 per SF (26%) more than homes under $310K

2026-10-26T06:43:08.448318 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 75 sales $310K– $368K 75 sales $370K– $463K 74 sales Over $463K 75 sales $0 $100 $200 $195 $202 $215 $245 Net price per SF, average

The average is $245 per SF for homes over $463K 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 $463K are about 1,050 SF (74%) larger than homes under $310K

2026-10-26T06:43:08.471220 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 75 sales $310K– $368K 75 sales $370K– $463K 74 sales Over $463K 75 sales 0 1,000 2,000 1,423 1,678 1,973 2,476 Living area (SF), average

The average is 2,476 SF for homes over $463K and 1,423 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

2026-10-26T06:43:08.494740 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 75 sales $310K– $368K 75 sales $370K– $463K 74 sales Over $463K 75 sales 2000 2005 2010 2015 2005 2005 2007 2007 Year built: median (dot) and middle half (bar)

The median is 2007 for homes over $463K 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

2026-10-26T06:43:08.517532 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 75 sales $310K– $368K 75 sales $370K– $463K 74 sales Over $463K 75 sales 0 25 50 75 67 44 28 23 Days on market, median

The median is 23 days for homes over $463K and 67 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 $463K sell about 4 percentage points closer to their first asking price than homes under $310K

2026-10-26T06:43:08.540075 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 75 sales $310K– $368K 75 sales $370K– $463K 74 sales Over $463K 75 sales 0.0% 5.0% 10.0% 8.5% 6.5% 3.8% 4.2% Discount from original list, average

The average is 4.2% for homes over $463K and 8.5% 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

2026-10-26T06:43:08.569982 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% 57 65 44 53 59 52 38 55 47 36 57 80 Under $310K $310K–$368K $370K–$463K Over $463K

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

  • 36% of homes over $463K had a price cut before sale, against 57% of homes under $310K. Defined in 8.1.7.
  • 57% of homes over $463K had the seller pay closing costs or repairs, against 65% of homes under $310K. Defined in 8.1.8.
  • 80% of homes over $463K have a view, against 44% 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 $310K75 sales$310K–$368K75 sales$370K–$463K74 salesOver $463K75 salesAll299 salesReal difference?
Net sale price average$273,913$335,794$420,277$608,482$409,581by design
Net price per SF average$195$202$215$245$214✓ large
Living area average1,4231,6781,9732,4761,887✓ large
Year built median20052005200720072006unclear

3.10 The numbers: selling

Under $310K75 sales$310K–$368K75 sales$370K–$463K74 salesOver $463K75 salesAll299 salesReal difference?
Days on market median6744282344unclear
Discount from original list average8.5%6.5%3.8%4.2%5.7%✓ medium
Price cut before sale57%53%38%36%46%unclear
Seller paid closing costs or repairs65%59%55%57%59%unclear
Has a view44%52%47%80%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 · 299 sales · April 29, 2026 – October 25, 2026

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

2026-10-26T06:43:08.591504 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 75 75 74 75 299 sales Sales per group Under 1,530 SF: 75 sales (25%) 1,530–1,845 SF: 75 sales (25%) 1,848–2,091 SF: 74 sales (25%) Over 2,091 SF: 75 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 1,530 SF1,530–1,845 SF1,848–2,091 SFOver 2,091 SF
Larger homes Over 2,091 SF
  • Sell for much more.
  • Sell for more per square foot.
Smaller homes Under 1,530 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 1,530 SF1,530–1,845 SF1,848–2,091 SFOver 2,091 SFReal difference?
Net sale price$284KLowest$343K$420K$591KHighest✓ large
Net price per SF$208 per SF$206 per SFLowest$214 per SF$229 per SFHighest✓ small
Year built2009200520042006unclear
Days on market55 days31 days30 days47 daysunclear
Discount from original list7.4%5.3%5.3%4.9%unclear
Price cut before sale56%44%42%43%unclear
Seller paid closing costs or repairs64%60%58%55%unclear
Has a view48%53%54%68%unclear

4.3 Homes over 2,091 SF sell for about $307K (108%) more than homes under 1,530 SF

2026-10-26T06:43:08.613282 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,530 SF 75 sales 1,530– 1,845 SF 75 sales 1,848– 2,091 SF 74 sales Over 2,091 SF 75 sales $0K $200K $400K $600K $284K $343K $420K $591K Net sale price, average

The average is $591K for homes over 2,091 SF and $284K for homes under 1,530 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 $22 per SF (10%) more than homes under 1,530 SF

2026-10-26T06:43:08.636160 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,530 SF 75 sales 1,530– 1,845 SF 75 sales 1,848– 2,091 SF 74 sales Over 2,091 SF 75 sales $0 $100 $200 $208 $206 $214 $229 Net price per SF, average

The average is $229 per SF for homes over 2,091 SF and $208 per SF for homes under 1,530 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

2026-10-26T06:43:08.660046 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,530 SF 75 sales 1,530– 1,845 SF 75 sales 1,848– 2,091 SF 74 sales Over 2,091 SF 75 sales 2000 2005 2010 2015 2009 2005 2004 2006 Year built: median (dot) and middle half (bar)

The median is 2006 for homes over 2,091 SF and 2009 for homes under 1,530 SF. It does not move in a straight line; homes under 1,530 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T06:43:08.682971 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,530 SF 75 sales 1,530– 1,845 SF 75 sales 1,848– 2,091 SF 74 sales Over 2,091 SF 75 sales 0 20 40 60 55 31 30 47 Days on market, median

The median is 47 days for homes over 2,091 SF and 55 days for homes under 1,530 SF. It does not move in a straight line; homes under 1,530 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T06:43:08.705644 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,530 SF 75 sales 1,530– 1,845 SF 75 sales 1,848– 2,091 SF 74 sales Over 2,091 SF 75 sales 0.0% 2.5% 5.0% 7.5% 7.4% 5.3% 5.3% 4.9% Discount from original list, average

The average is 4.9% for homes over 2,091 SF and 7.4% for homes under 1,530 SF. It does not move in a straight line; homes under 1,530 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

2026-10-26T06:43:08.732951 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 64 48 44 60 53 42 58 54 43 55 68 Under 1,530 SF 1,530–1,845 SF 1,848–2,091 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 56% of homes under 1,530 SF. Defined in 8.1.7.
  • 55% of homes over 2,091 SF had the seller pay closing costs or repairs, against 64% of homes under 1,530 SF. Defined in 8.1.8.
  • 68% of homes over 2,091 SF have a view, against 48% of homes under 1,530 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 1,530 SF75 sales1,530–1,845 SF75 sales1,848–2,091 SF74 salesOver 2,091 SF75 salesAll299 salesReal difference?
Net sale price average$284,132$342,960$420,185$591,189$409,581✓ large
Net price per SF average$208$206$214$229$214✓ small
Living area average1,3731,6671,9662,5451,887by design
Year built median20092005200420062006unclear

4.10 The numbers: selling

Under 1,530 SF75 sales1,530–1,845 SF75 sales1,848–2,091 SF74 salesOver 2,091 SF75 salesAll299 salesReal difference?
Days on market median5531304744unclear
Discount from original list average7.4%5.3%5.3%4.9%5.7%unclear
Price cut before sale56%44%42%43%46%unclear
Seller paid closing costs or repairs64%60%58%55%59%unclear
Has a view48%53%54%68%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 · 299 sales · April 29, 2026 – 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.

2026-10-26T06:43:08.754609 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 78 65 79 77 299 sales Sales per group Before 2000: 78 sales (26%) 2000–2005: 65 sales (22%) 2006–2014: 79 sales (26%) After 2014: 77 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$387K$422K$397K$435Kunclear
Net price per SF$208 per SFLowest$209 per SF$213 per SF$226 per SFHighest✓ medium
Living area1,856 SF1,946 SF1,849 SF1,909 SFunclear
Days on market44 days43 days25 days59 daysunclear
Discount from original list6.2%5.9%5.1%5.8%unclear
Price cut before sale50%43%37%55%unclear
Seller paid closing costs or repairs55%65%61%57%unclear
Has a view44%Fewest45%78%Most55%✓ small

5.3 Net sale price: no clear difference

2026-10-26T06:43:08.776045 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 78 sales 2000– 2005 65 sales 2006– 2014 79 sales After 2014 77 sales $0K $200K $400K $387K $422K $397K $435K Net sale price, average

The average is $435K for homes built after 2014 and $387K 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 $18 per SF (9%) more than homes built before 2000

2026-10-26T06:43:08.799488 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 78 sales 2000– 2005 65 sales 2006– 2014 79 sales After 2014 77 sales $0 $100 $200 $208 $209 $213 $226 Net price per SF, average

The average is $226 per SF for homes built after 2014 and $208 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

2026-10-26T06:43:08.821213 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 78 sales 2000– 2005 65 sales 2006– 2014 79 sales After 2014 77 sales 0 1,000 2,000 1,856 1,946 1,849 1,909 Living area (SF), average

The average is 1,909 SF for homes built after 2014 and 1,856 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

2026-10-26T06:43:08.843611 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 78 sales 2000– 2005 65 sales 2006– 2014 79 sales After 2014 77 sales 0 20 40 60 44 43 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

2026-10-26T06:43:08.866278 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 78 sales 2000– 2005 65 sales 2006– 2014 79 sales After 2014 77 sales 0.0% 2.0% 4.0% 6.0% 6.2% 5.9% 5.1% 5.8% Discount from original list, average

The average is 5.8% for homes built after 2014 and 6.2% 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

2026-10-26T06:43:08.893111 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% 50 55 44 43 65 45 37 61 78 55 57 55 Before 2000 2000–2005 2006–2014 After 2014

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

  • 55% of homes built after 2014 had a price cut before sale, against 50% 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 55% of homes built before 2000. Defined in 8.1.8.
  • 55% of homes built after 2014 have a view, against 44% 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 200078 sales2000–200565 sales2006–201479 salesAfter 201477 salesAll299 salesReal difference?
Net sale price average$387,462$421,971$396,746$434,696$409,581unclear
Net price per SF average$208$209$213$226$214✓ medium
Living area average1,8561,9461,8491,9091,887unclear
Year built median19972003200820192006by design

5.10 The numbers: selling

Before 200078 sales2000–200565 sales2006–201479 salesAfter 201477 salesAll299 salesReal difference?
Days on market median4443255944unclear
Discount from original list average6.2%5.9%5.1%5.8%5.7%unclear
Price cut before sale50%43%37%55%46%unclear
Seller paid closing costs or repairs55%65%61%57%59%unclear
Has a view44%45%78%55%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 · 299 sales · April 29, 2026 – 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. 6 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T06:43:08.911530 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 167 126 293 sales Sales per group View: 167 sales (57%) No view: 126 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$445KHighest$363KLowest✓ medium
Net price per SF$223 per SFHighest$203 per SFLowest✓ medium
Living area1,958 SF1,791 SFunclear
Year built20072002unclear
Days on market25 daysFastest52 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 $83K (23%) more than homes without a view

2026-10-26T06:43:08.928245 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 167 sales No view 126 sales $0K $200K $400K $445K $363K Net sale price, average

The average is $445K for homes with a view and $363K for homes without a view. Defined in 8.1.1.

✓ Real difference · medium

6.4 Homes with a view sell for about $20 per SF (10%) more than homes without a view

2026-10-26T06:43:08.945913 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 167 sales No view 126 sales $0 $100 $200 $223 $203 Net price per SF, average

The average is $223 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

2026-10-26T06:43:08.992106 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 167 sales No view 126 sales 0 500 1,000 1,500 2,000 1,958 1,791 Living area (SF), average

The average is 1,958 SF for homes with a view and 1,791 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T06:43:09.012718 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 167 sales No view 126 sales 2000 2004 2008 2012 2016 2007 2002 Year built: median (dot) and middle half (bar)

The median is 2007 for homes with a view and 2002 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

2026-10-26T06:43:09.031396 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 167 sales No view 126 sales 0 20 40 60 25 52 Days on market, median

The median is 25 days for homes with a view and 52 days for homes without a view. Defined in 8.1.5.

✓ Real difference · small

6.8 Discount from original list: no clear difference

2026-10-26T06:43:09.049313 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 167 sales No view 126 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

2026-10-26T06:43:09.068213 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

View167 salesNo view126 salesAll293 salesReal difference?
Net sale price average$445,330$362,818$409,847✓ medium
Net price per SF average$223$203$214✓ medium
Living area average1,9581,7911,886unclear
Year built median200720022006unclear

6.11 The numbers: selling

View167 salesNo view126 salesAll293 salesReal difference?
Days on market median255244✓ 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 · 11 sales · April 29, 2026 – October 25, 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: 11 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
Sales11
Net sale price$425,256$363,000
Net price per SF$244$241
Living area (SF)1,7421,550
Days on market7832
Discount from original list7.1%6.0%
Price cut before sale55% of sales
Seller paid closing costs or repairs55% 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
299 resale sales. Average $409,581; median $368,313; standard deviation $155,736; middle half (25th–75th percentile) $309,750–$463,780; lowest $203,450, highest $1,588,000. 177 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
299 resale sales. Average $214; median $210; standard deviation $33; middle half (25th–75th percentile) $194–$232; 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
299 resale sales. Average 1,887; median 1,845; standard deviation 485; middle half (25th–75th percentile) 1,516–2,096; 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
299 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
299 resale sales. Average 74; median 44; standard deviation 94; middle half (25th–75th percentile) 9–96; 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
299 resale sales. Average 5.7%; median 4.5%; standard deviation 5.7%; middle half (25th–75th percentile) 1.5%–8.7%; lowest −6.9%, 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
138 of 299 resale sales (46.2%).

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
177 of 299 resale sales (59.2%).

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
167 sales with a view, 126 without, 6 unclassified. Most common View entries: Park/Greenbelt 130, Neighborhood 95, None 63, Trees/Woods 61, Golf Course 32, Hill Country 14, See Remarks 13, Panoramic 7.

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”, “sun city georgetown nbhd”, “sun city nbrhds”, “sun city neighborhoods”, “sun city neighborhoods eighty one e”, “sun city neighborhoods eighty”, “sun city nbrhds eighty one e” (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 26, 2026: 584 closed Sun City Georgetown records over the prior year, in ZIP 78633. 169 subdivision spellings kept, the most common: Sun City (94); Sun City Texas (62); 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 07 (9); Sun City Georgetown Ph 02 Neighborhood 10 Pud (9); Sun City Georgetown Neighborhood 06 Amd B (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 29, 2026 to October 25, 2026 inclusive.
The data
310 single-family sales in the window: 299 resale, 11 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
299 resale; 11 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–$309,500 (75 sales); $310K–$368K: $310,000–$368,313 (75 sales); $370K–$463K: $370,000–$462,560 (74 sales); Over $463K: $465,000–$1,588,000 (75 sales)
Quartiles by living area: Under 1,530 SF: 915–1,502 SF (75 sales); 1,530–1,845 SF: 1,530–1,845 SF (75 sales); 1,848–2,091 SF: 1,848–2,091 SF (74 sales); Over 2,091 SF: 2,100–4,866 SF (75 sales)
Quartiles by year built: Before 2000: 1995–1999 (78 sales); 2000–2005: 2000–2005 (65 sales); 2006–2014: 2006–2014 (79 sales); After 2014: 2015–2026 (77 sales)
View and no view: View: MLS lists a view (167 sales); No view: None or Neighborhood (126 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 $409,581, median $368,313. 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 = 88.863< 0.0001p < 0.0063Yesε² = 0.298large
Living areaKruskal–WallisH = 223.073< 0.0001p < 0.0063Yesε² = 0.749large
Year builtKruskal–WallisH = 2.7530.4311p < 0.0063Unclearε² = 0.009negligible
Days on marketKruskal–WallisH = 12.1130.0070p < 0.0063Unclearε² = 0.041small
Discount from original listKruskal–WallisH = 33.843< 0.0001p < 0.0063Yesε² = 0.114medium
Price cut before saleChi-squareχ² = 10.5030.0148p < 0.0063UnclearCramér’s V = 0.187small
Seller paid closing costs or repairsChi-squareχ² = 1.7330.6311p < 0.0063UnclearCramér’s V = 0.076negligible
Has a viewChi-squareχ² = 24.663< 0.0001p < 0.0063YesCramér’s V = 0.287small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 223.603< 0.0001p < 0.0063Yesε² = 0.750large
Net price per SFKruskal–WallisH = 13.5030.0037p < 0.0063Yesε² = 0.045small
Year builtKruskal–WallisH = 9.5630.0227p < 0.0063Unclearε² = 0.032small
Days on marketKruskal–WallisH = 8.2030.0421p < 0.0063Unclearε² = 0.028small
Discount from original listKruskal–WallisH = 10.6330.0139p < 0.0063Unclearε² = 0.036small
Price cut before saleChi-squareχ² = 3.9730.2643p < 0.0063UnclearCramér’s V = 0.115small
Seller paid closing costs or repairsChi-squareχ² = 1.4130.7032p < 0.0063UnclearCramér’s V = 0.069negligible
Has a viewChi-squareχ² = 6.6530.0838p < 0.0063UnclearCramér’s V = 0.149small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 5.1530.1612p < 0.0063Unclearε² = 0.017small
Net price per SFKruskal–WallisH = 24.553< 0.0001p < 0.0063Yesε² = 0.082medium
Living areaKruskal–WallisH = 0.3530.9508p < 0.0063Unclearε² = 0.001negligible
Days on marketKruskal–WallisH = 10.0130.0185p < 0.0063Unclearε² = 0.034small
Discount from original listKruskal–WallisH = 1.2130.7506p < 0.0063Unclearε² = 0.004negligible
Price cut before saleChi-squareχ² = 5.7330.1255p < 0.0063UnclearCramér’s V = 0.138small
Seller paid closing costs or repairsChi-squareχ² = 1.5430.6733p < 0.0063UnclearCramér’s V = 0.072negligible
Has a viewChi-squareχ² = 24.543< 0.0001p < 0.0063YesCramér’s V = 0.287small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 13,695.00—< 0.0001p < 0.0063Yesrank-biserial r = 0.302medium
Net price per SFMann–Whitney UU = 14,079.50—< 0.0001p < 0.0063Yesrank-biserial r = 0.338medium
Living areaMann–Whitney UU = 12,415.50—0.0083p < 0.0063Unclearrank-biserial r = 0.180small
Year builtMann–Whitney UU = 12,328.50—0.0117p < 0.0063Unclearrank-biserial r = 0.172small
Days on marketMann–Whitney UU = 8,018.00—0.0005p < 0.0063Yesrank-biserial r = 0.238small
Discount from original listMann–Whitney UU = 9,017.50—0.0363p < 0.0063Unclearrank-biserial r = 0.143small
Price cut before saleChi-squareχ² = 5.5410.0186p < 0.0063UnclearCramér’s V = 0.138small
Seller paid closing costs or repairsChi-squareχ² = 0.1110.7377p < 0.0063UnclearCramér’s V = 0.020negligible

8.4 Data notes

Left out of the analysis: 11 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 299 closed MLS resale sales; the 11 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.