ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Sun City Georgetown

Georgetown, TX 78633
Resale homes · closed May 3 – Oct 29, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 30, 2026 · 6:41 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
300
single-family resale homes
Median net sale price
$360,650
average $409,299
Median net price per SF
$210
average $214
Median days on market
43 days
average 74 days
1. SummaryResale homes · 300 sales · May 3, 2026 – October 29, 2026

This study looks at the 300 resale homes sold in Sun City Georgetown in the 180 days to October 29, 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 sold300 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–$360K · 75 sales$362K–$463K · 75 salesOver $463K · 75 sales
3. Quartiles by net sale priceResale homes · 300 sales · May 3, 2026 – October 29, 2026

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

2026-10-30T06:41:34.257772 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 75 75 75 75 300 sales Sales per group Under $310K: 75 sales (25%) $310K–$360K: 75 sales (25%) $362K–$463K: 75 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–$360K$362K–$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–$360K$362K–$463KOver $463KReal difference?
Net price per SF$196 per SFLowest$202 per SF$215 per SF$245 per SFHighest✓ large
Living area1,418 SFSmallest1,677 SF1,965 SF2,478 SFLargest✓ large
Year built2005200620052007unclear
Days on market52 days48 days28 days23 daysunclear
Discount from original list8.2%Biggest7.3%3.8%Smallest4.2%✓ medium
Price cut before sale56%55%37%36%unclear
Seller paid closing costs or repairs65%61%53%57%unclear
Has a view44%Fewest52%45%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

2026-10-30T06:41:34.290734 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 75 sales $310K– $360K 75 sales $362K– $463K 75 sales Over $463K 75 sales $0 $100 $200 $196 $202 $215 $245 Net price per SF, average

The average is $245 per SF for homes over $463K and $196 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 1,060 SF (75%) larger than homes under $310K

2026-10-30T06:41:34.320656 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 75 sales $310K– $360K 75 sales $362K– $463K 75 sales Over $463K 75 sales 0 1,000 2,000 1,418 1,677 1,965 2,478 Living area (SF), average

The average is 2,478 SF for homes over $463K and 1,418 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

2026-10-30T06:41:34.349733 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 75 sales $310K– $360K 75 sales $362K– $463K 75 sales Over $463K 75 sales 2000 2005 2010 2015 2005 2006 2005 2007 Year built: median (dot) and middle half (bar)

The median is 2007 for homes over $463K and 2005 for homes under $310K. It does not move in a straight line; homes over $463K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-30T06:41:34.376343 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 75 sales $310K– $360K 75 sales $362K– $463K 75 sales Over $463K 75 sales 0 20 40 60 52 48 28 23 Days on market, median

The median is 23 days for homes over $463K and 52 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

2026-10-30T06:41:34.401756 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $310K 75 sales $310K– $360K 75 sales $362K– $463K 75 sales Over $463K 75 sales 0.0% 2.5% 5.0% 7.5% 8.2% 7.3% 3.8% 4.2% Discount from original list, average

The average is 4.2% for homes over $463K 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

2026-10-30T06:41:34.438113 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 44 55 61 52 37 53 45 36 57 80 Under $310K $310K–$360K $362K–$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 56% 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–$360K75 sales$362K–$463K75 salesOver $463K75 salesAll300 salesReal difference?
Net sale price average$274,082$334,777$417,754$610,584$409,299by design
Net price per SF average$196$202$215$245$214✓ large
Living area average1,4181,6771,9652,4781,884✓ large
Year built median20052006200520072006unclear

3.10 The numbers: selling

Under $310K75 sales$310K–$360K75 sales$362K–$463K75 salesOver $463K75 salesAll300 salesReal difference?
Days on market median5248282343unclear
Discount from original list average8.2%7.3%3.8%4.2%5.9%✓ medium
Price cut before sale56%55%37%36%46%unclear
Seller paid closing costs or repairs65%61%53%57%59%unclear
Has a view44%52%45%80%55%✓ 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 · 300 sales · May 3, 2026 – October 29, 2026

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

2026-10-30T06:41:34.462808 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 75 74 77 74 300 sales Sales per group Under 1,497 SF: 75 sales (25%) 1,497–1,822 SF: 74 sales (25%) 1,845–2,091 SF: 77 sales (26%) Over 2,091 SF: 74 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 1,497 SF1,497–1,822 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 1,497 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 1,497 SF1,497–1,822 SF1,845–2,091 SFOver 2,091 SFReal difference?
Net sale price$284KLowest$339K$420K$595KHighest✓ large
Net price per SF$208 per SF$205 per SFLowest$214 per SF$231 per SFHighest✓ small
Year built2008200520052006unclear
Days on market52 days33 days27 days47 daysunclear
Discount from original list7.2%5.8%5.5%4.9%unclear
Price cut before sale55%46%40%43%unclear
Seller paid closing costs or repairs65%61%57%54%unclear
Has a view47%54%53%68%unclear

4.3 Homes over 2,091 SF sell for about $311K (110%) more than homes under 1,497 SF

2026-10-30T06:41:34.487704 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,497 SF 75 sales 1,497– 1,822 SF 74 sales 1,845– 2,091 SF 77 sales Over 2,091 SF 74 sales $0K $200K $400K $600K $284K $339K $420K $595K Net sale price, average

The average is $595K for homes over 2,091 SF and $284K for homes under 1,497 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 (11%) more than homes under 1,497 SF

2026-10-30T06:41:34.517828 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,497 SF 75 sales 1,497– 1,822 SF 74 sales 1,845– 2,091 SF 77 sales Over 2,091 SF 74 sales $0 $100 $200 $208 $205 $214 $231 Net price per SF, average

The average is $231 per SF for homes over 2,091 SF and $208 per SF for homes under 1,497 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

2026-10-30T06:41:34.546906 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,497 SF 75 sales 1,497– 1,822 SF 74 sales 1,845– 2,091 SF 77 sales Over 2,091 SF 74 sales 2000 2005 2010 2015 2008 2005 2005 2006 Year built: median (dot) and middle half (bar)

The median is 2006 for homes over 2,091 SF and 2008 for homes under 1,497 SF. It does not move in a straight line; homes under 1,497 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-30T06:41:34.575001 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,497 SF 75 sales 1,497– 1,822 SF 74 sales 1,845– 2,091 SF 77 sales Over 2,091 SF 74 sales 0 20 40 60 52 33 27 47 Days on market, median

The median is 47 days for homes over 2,091 SF and 52 days for homes under 1,497 SF. It does not move in a straight line; homes under 1,497 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-30T06:41:34.609330 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,497 SF 75 sales 1,497– 1,822 SF 74 sales 1,845– 2,091 SF 77 sales Over 2,091 SF 74 sales 0.0% 2.5% 5.0% 7.5% 7.2% 5.8% 5.5% 4.9% Discount from original list, average

The average is 4.9% for homes over 2,091 SF and 7.2% for homes under 1,497 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

2026-10-30T06:41:34.648716 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 65 47 46 61 54 40 57 53 43 54 68 Under 1,497 SF 1,497–1,822 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 1,497 SF. Defined in 8.1.7.
  • 54% of homes over 2,091 SF had the seller pay closing costs or repairs, against 65% of homes under 1,497 SF. Defined in 8.1.8.
  • 68% of homes over 2,091 SF have a view, against 47% of homes under 1,497 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 1,497 SF75 sales1,497–1,822 SF74 sales1,845–2,091 SF77 salesOver 2,091 SF74 salesAll300 salesReal difference?
Net sale price average$284,040$339,089$420,192$595,125$409,299✓ large
Net price per SF average$208$205$214$231$214✓ small
Living area average1,3701,6581,9622,5511,884by design
Year built median20082005200520062006unclear

4.10 The numbers: selling

Under 1,497 SF75 sales1,497–1,822 SF74 sales1,845–2,091 SF77 salesOver 2,091 SF74 salesAll300 salesReal difference?
Days on market median5233274743unclear
Discount from original list average7.2%5.8%5.5%4.9%5.9%unclear
Price cut before sale55%46%40%43%46%unclear
Seller paid closing costs or repairs65%61%57%54%59%unclear
Has a view47%54%53%68%55%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 · 300 sales · May 3, 2026 – October 29, 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.

2026-10-30T06:41:34.674053 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 78 66 79 77 300 sales Sales per group Before 2000: 78 sales (26%) 2000–2005: 66 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$421K$397K$435Kunclear
Net price per SF$208 per SFLowest$209 per SF$214 per SF$226 per SFHighest✓ medium
Living area1,852 SF1,946 SF1,840 SF1,909 SFunclear
Days on market42 days44 days25 days59 daysunclear
Discount from original list6.3%6.2%5.2%5.8%unclear
Price cut before sale49%44%37%55%unclear
Seller paid closing costs or repairs55%65%61%57%unclear
Has a view44%Fewest44%77%Most55%✓ small

5.3 Net sale price: no clear difference

2026-10-30T06:41:34.698398 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 78 sales 2000– 2005 66 sales 2006– 2014 79 sales After 2014 77 sales $0K $200K $400K $387K $421K $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 $17 per SF (8%) more than homes built before 2000

2026-10-30T06:41:34.725368 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 78 sales 2000– 2005 66 sales 2006– 2014 79 sales After 2014 77 sales $0 $100 $200 $208 $209 $214 $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

2026-10-30T06:41:34.754429 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 78 sales 2000– 2005 66 sales 2006– 2014 79 sales After 2014 77 sales 0 1,000 2,000 1,852 1,946 1,840 1,909 Living area (SF), average

The average is 1,909 SF for homes built after 2014 and 1,852 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

2026-10-30T06:41:34.783481 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 78 sales 2000– 2005 66 sales 2006– 2014 79 sales After 2014 77 sales 0 20 40 60 42 44 25 59 Days on market, median

The median is 59 days for homes built after 2014 and 42 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

2026-10-30T06:41:34.811650 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 78 sales 2000– 2005 66 sales 2006– 2014 79 sales After 2014 77 sales 0.0% 2.0% 4.0% 6.0% 6.3% 6.2% 5.2% 5.8% Discount from original list, average

The average is 5.8% for homes built after 2014 and 6.3% 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

2026-10-30T06:41:34.844955 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% 49 55 44 44 65 44 37 61 77 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 49% 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 sales2000–200566 sales2006–201479 salesAfter 201477 salesAll300 salesReal difference?
Net sale price average$387,167$420,812$396,778$434,696$409,299unclear
Net price per SF average$208$209$214$226$214✓ medium
Living area average1,8521,9461,8401,9091,884unclear
Year built median19972003200820192006by design

5.10 The numbers: selling

Before 200078 sales2000–200566 sales2006–201479 salesAfter 201477 salesAll300 salesReal difference?
Days on market median4244255943unclear
Discount from original list average6.3%6.2%5.2%5.8%5.9%unclear
Price cut before sale49%44%37%55%46%unclear
Seller paid closing costs or repairs55%65%61%57%59%unclear
Has a view44%44%77%55%55%✓ 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 · 300 sales · May 3, 2026 – October 29, 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.

2026-10-30T06:41:34.874504 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 166 128 294 sales Sales per group View: 166 sales (56%) No view: 128 sales (44%)
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$446KHighest$362KLowest✓ medium
Net price per SF$223 per SFHighest$203 per SFLowest✓ medium
Living area1,957 SF1,787 SFunclear
Year built20072002unclear
Days on market26 daysFastest52 daysSlowest✓ small
Discount from original list5.1%6.7%unclear
Price cut before sale40%53%unclear
Seller paid closing costs or repairs60%59%unclear

6.3 Homes with a view sell for about $84K (23%) more than homes without a view

2026-10-30T06:41:34.897326 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 166 sales No view 128 sales $0K $200K $400K $446K $362K Net sale price, average

The average is $446K for homes with a view and $362K 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

2026-10-30T06:41:34.917484 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 166 sales No view 128 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

2026-10-30T06:41:34.988953 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 166 sales No view 128 sales 0 500 1,000 1,500 2,000 1,957 1,787 Living area (SF), average

The average is 1,957 SF for homes with a view and 1,787 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-30T06:41:35.011701 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 166 sales No view 128 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 26 days faster than homes without a view

2026-10-30T06:41:35.031402 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 166 sales No view 128 sales 0 20 40 60 26 52 Days on market, median

The median is 26 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

2026-10-30T06:41:35.053613 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 166 sales No view 128 sales 0.0% 2.0% 4.0% 6.0% 8.0% 5.1% 6.7% Discount from original list, average

The average is 5.1% for homes with a view and 6.7% 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

2026-10-30T06:41:35.077447 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 40 60 53 59 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 53% 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 59% 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

View166 salesNo view128 salesAll294 salesReal difference?
Net sale price average$446,206$362,031$409,558✓ medium
Net price per SF average$223$203$215✓ medium
Living area average1,9571,7871,883unclear
Year built median200720022006unclear

6.11 The numbers: selling

View166 salesNo view128 salesAll294 salesReal difference?
Days on market median265243✓ small
Discount from original list average5.1%6.7%5.8%unclear
Price cut before sale40%53%46%unclear
Seller paid closing costs or repairs60%59%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 · 10 sales · May 3, 2026 – October 29, 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: 10 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
Sales10
Net sale price$391,682$359,186
Net price per SF$237$239
Living area (SF)1,6711,524
Days on market8440
Discount from original list7.3%6.4%
Price cut before sale60% 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
300 resale sales. Average $409,299; median $360,650; standard deviation $156,220; middle half (25th–75th percentile) $309,375–$463,170; lowest $203,450, highest $1,588,000. 178 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
300 resale sales. Average $214; median $210; standard deviation $33; middle half (25th–75th percentile) $193–$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
300 resale sales. Average 1,884; median 1,845; standard deviation 486; middle half (25th–75th percentile) 1,495–2,091; 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
300 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
300 resale sales. Average 74; median 43; standard deviation 97; middle half (25th–75th percentile) 9–93; lowest 0, highest 645. 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
300 resale sales. Average 5.9%; median 4.4%; standard deviation 6.0%; middle half (25th–75th percentile) 1.5%–8.7%; lowest −6.9%, highest 33.1%. 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 300 resale sales (46.0%).

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
178 of 300 resale sales (59.3%).

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
166 sales with a view, 128 without, 6 unclassified. Most common View entries: Park/Greenbelt 128, Neighborhood 97, None 62, Trees/Woods 61, Golf Course 33, 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 30, 2026: 587 closed Sun City Georgetown records over the prior year, in ZIP 78633. 170 subdivision spellings kept, the most common: Sun City (94); Sun City Texas (63); Sun City Georgetown Neighborhood 04 (19); 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 158 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 May 3, 2026 to October 29, 2026 inclusive.
The data
310 single-family sales in the window: 300 resale, 10 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
300 resale; 10 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 (75 sales); $310K–$360K: $309,500–$359,800 (75 sales); $362K–$463K: $361,500–$462,560 (75 sales); Over $463K: $465,000–$1,588,000 (75 sales)
Quartiles by living area: Under 1,497 SF: 915–1,490 SF (75 sales); 1,497–1,822 SF: 1,497–1,822 SF (74 sales); 1,845–2,091 SF: 1,845–2,091 SF (77 sales); Over 2,091 SF: 2,100–4,866 SF (74 sales)
Quartiles by year built: Before 2000: 1995–1999 (78 sales); 2000–2005: 2000–2005 (66 sales); 2006–2014: 2006–2014 (79 sales); After 2014: 2015–2026 (77 sales)
View and no view: View: MLS lists a view (166 sales); No view: None or Neighborhood (128 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 $409,299, median $360,650. Days on market: average 74, median 43: 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 = 88.983< 0.0001p < 0.0063Yesε² = 0.298large
Living areaKruskal–WallisH = 224.573< 0.0001p < 0.0063Yesε² = 0.751large
Year builtKruskal–WallisH = 2.4130.4910p < 0.0063Unclearε² = 0.008negligible
Days on marketKruskal–WallisH = 10.8130.0128p < 0.0063Unclearε² = 0.036small
Discount from original listKruskal–WallisH = 34.773< 0.0001p < 0.0063Yesε² = 0.116medium
Price cut before saleChi-squareχ² = 10.5730.0143p < 0.0063UnclearCramér’s V = 0.188small
Seller paid closing costs or repairsChi-squareχ² = 2.4930.4777p < 0.0063UnclearCramér’s V = 0.091negligible
Has a viewChi-squareχ² = 25.733< 0.0001p < 0.0063YesCramér’s V = 0.293small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 227.853< 0.0001p < 0.0063Yesε² = 0.762large
Net price per SFKruskal–WallisH = 16.1530.0011p < 0.0063Yesε² = 0.054small
Year builtKruskal–WallisH = 7.1630.0670p < 0.0063Unclearε² = 0.024small
Days on marketKruskal–WallisH = 5.9530.1139p < 0.0063Unclearε² = 0.020small
Discount from original listKruskal–WallisH = 9.0430.0288p < 0.0063Unclearε² = 0.030small
Price cut before saleChi-squareχ² = 3.5230.3187p < 0.0063UnclearCramér’s V = 0.108small
Seller paid closing costs or repairsChi-squareχ² = 2.1930.5332p < 0.0063UnclearCramér’s V = 0.086negligible
Has a viewChi-squareχ² = 6.9530.0737p < 0.0063UnclearCramér’s V = 0.152small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 5.2730.1532p < 0.0063Unclearε² = 0.018small
Net price per SFKruskal–WallisH = 24.983< 0.0001p < 0.0063Yesε² = 0.084medium
Living areaKruskal–WallisH = 0.6230.8913p < 0.0063Unclearε² = 0.002negligible
Days on marketKruskal–WallisH = 10.1430.0174p < 0.0063Unclearε² = 0.034small
Discount from original listKruskal–WallisH = 1.0530.7895p < 0.0063Unclearε² = 0.004negligible
Price cut before saleChi-squareχ² = 5.3530.1476p < 0.0063UnclearCramér’s V = 0.134small
Seller paid closing costs or repairsChi-squareχ² = 1.7230.6331p < 0.0063UnclearCramér’s V = 0.076negligible
Has a viewChi-squareχ² = 23.143< 0.0001p < 0.0063YesCramér’s V = 0.278small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 13,844.00—< 0.0001p < 0.0063Yesrank-biserial r = 0.303medium
Net price per SFMann–Whitney UU = 14,288.50—< 0.0001p < 0.0063Yesrank-biserial r = 0.345medium
Living areaMann–Whitney UU = 12,571.50—0.0071p < 0.0063Unclearrank-biserial r = 0.183small
Year builtMann–Whitney UU = 12,451.00—0.0114p < 0.0063Unclearrank-biserial r = 0.172small
Days on marketMann–Whitney UU = 8,337.00—0.0016p < 0.0063Yesrank-biserial r = 0.215small
Discount from original listMann–Whitney UU = 9,153.50—0.0420p < 0.0063Unclearrank-biserial r = 0.138small
Price cut before saleChi-squareχ² = 4.7410.0295p < 0.0063UnclearCramér’s V = 0.127small
Seller paid closing costs or repairsChi-squareχ² = 0.0310.8566p < 0.0063UnclearCramér’s V = 0.011negligible

8.4 Data notes

Left out of the analysis: 10 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 300 closed MLS resale sales; the 10 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 30, 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.