ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

ZIP 78633

Georgetown, TX
Resale homes · closed May 4 – Oct 30, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 31, 2026 · 3:37 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
442
single-family resale homes
Median net sale price
$412,750
average $500,510
Median net price per SF
$213
average $228
Median days on market
45 days
average 78 days
1. SummaryResale homes · 442 sales · May 4, 2026 – October 30, 2026

This study looks at the 442 resale homes sold in ZIP 78633 in the 180 days to October 30, 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 sold442 resale homes · colored by price range

Each dot is one resale home, colored by its price range. The map is drawn around the middle 99% of sales; 7 sales with map points far outside the area are left off it (they stay in every figure). 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 $326K · 110 sales$326K–$412K · 111 sales$414K–$574K · 111 salesOver $574K · 110 sales
3. Quartiles by net sale priceResale homes · 442 sales · May 4, 2026 – October 30, 2026

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

2026-10-31T15:37:18.852560 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 110 111 111 110 442 sales Sales per group Under $326K: 110 sales (25%) $326K–$412K: 111 sales (25%) $414K–$574K: 111 sales (25%) Over $574K: 110 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 $326K$326K–$412K$414K–$574KOver $574K
Higher-priced homes Over $574K
  • Are much larger.
  • Sell for more per square foot.
  • Are more likely to have a view.
  • Sell closer to their first asking price.
  • Sell faster.
Lower-priced homes Under $326K
  • Are much smaller.
  • Sell for less per square foot.
  • Are less likely to have a view.
  • Sell further below their first asking price.
  • Take longer to sell.

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 $326K$326K–$412K$414K–$574KOver $574KReal difference?
Net price per SF$197 per SFLowest$198 per SF$218 per SF$302 per SFHighest✓ large
Living area1,467 SFSmallest1,884 SF2,241 SF2,990 SFLargest✓ large
Year built2006200620062008unclear
Days on market67 daysSlowest48 days26 daysFastest46 days✓ small
Discount from original list8.2%Biggest5.7%4.6%Smallest4.9%✓ small
Price cut before sale57%47%41%36%unclear
Seller paid closing costs or repairs63%62%63%47%unclear
Has a view41%Fewest50%54%77%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 $574K sell for about $104 per SF (53%) more than homes under $326K

2026-10-31T15:37:18.881321 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $326K 110 sales $326K– $412K 111 sales $414K– $574K 111 sales Over $574K 110 sales $0 $100 $200 $300 $197 $198 $218 $302 Net price per SF, average

The average is $302 per SF for homes over $574K and $197 per SF for homes under $326K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $574K are about 1,520 SF (104%) larger than homes under $326K

2026-10-31T15:37:18.903961 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $326K 110 sales $326K– $412K 111 sales $414K– $574K 111 sales Over $574K 110 sales 0 1,000 2,000 3,000 1,467 1,884 2,241 2,990 Living area (SF), average

The average is 2,990 SF for homes over $574K and 1,467 SF for homes under $326K. 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

2026-10-31T15:37:18.927782 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $326K 110 sales $326K– $412K 111 sales $414K– $574K 111 sales Over $574K 110 sales 2000 2005 2010 2015 2006 2006 2006 2008 Year built: median (dot) and middle half (bar)

The median is 2008 for homes over $574K and 2006 for homes under $326K. 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 Homes over $574K sell 21 days faster than homes under $326K

2026-10-31T15:37:18.950334 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $326K 110 sales $326K– $412K 111 sales $414K– $574K 111 sales Over $574K 110 sales 0 25 50 75 67 48 26 46 Days on market, median

The median is 46 days for homes over $574K and 67 days for homes under $326K. It does not move in a straight line; homes under $326K are highest. Defined in 8.1.5.

✓ Real difference · small

3.7 Homes over $574K sell about 3 percentage points closer to their first asking price than homes under $326K

2026-10-31T15:37:18.972994 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $326K 110 sales $326K– $412K 111 sales $414K– $574K 111 sales Over $574K 110 sales 0.0% 2.5% 5.0% 7.5% 8.2% 5.7% 4.6% 4.9% Discount from original list, average

The average is 4.9% for homes over $574K and 8.2% for homes under $326K. It does not move in a straight line; homes under $326K are highest. Defined in 8.1.6.

✓ Real difference · small

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

2026-10-31T15:37:19.002864 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 63 41 47 62 50 41 63 54 36 47 77 Under $326K $326K–$412K $414K–$574K Over $574K

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

  • 36% of homes over $574K had a price cut before sale, against 57% of homes under $326K. Defined in 8.1.7.
  • 47% of homes over $574K had the seller pay closing costs or repairs, against 63% of homes under $326K. Defined in 8.1.8.
  • 77% of homes over $574K have a view, against 41% of homes under $326K. 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 $326K110 sales$326K–$412K111 sales$414K–$574K111 salesOver $574K110 salesAll442 salesReal difference?
Net sale price average$286,181$365,748$479,516$872,010$500,510by design
Net price per SF average$197$198$218$302$228✓ large
Living area average1,4671,8842,2412,9902,145✓ large
Year built median20062006200620082006unclear

3.10 The numbers: selling

Under $326K110 sales$326K–$412K111 sales$414K–$574K111 salesOver $574K110 salesAll442 salesReal difference?
Days on market median6748264645✓ small
Discount from original list average8.2%5.7%4.6%4.9%5.8%✓ small
Price cut before sale57%47%41%36%45%unclear
Seller paid closing costs or repairs63%62%63%47%59%unclear
Has a view41%50%54%77%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 · 442 sales · May 4, 2026 – October 30, 2026

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

2026-10-31T15:37:19.024273 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 111 110 111 110 442 sales Sales per group Under 1,608 SF: 111 sales (25%) 1,608–1,978 SF: 110 sales (25%) 1,981–2,536 SF: 111 sales (25%) Over 2,536 SF: 110 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 1,608 SF1,608–1,978 SF1,981–2,536 SFOver 2,536 SF
Larger homes Over 2,536 SF
  • Sell for much more.
  • Sell for more per square foot.
  • Tend to be newer.
Smaller homes Under 1,608 SF
  • Sell for much less.
  • Sell for less per square foot.
  • Tend to be older.

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 1,608 SF1,608–1,978 SF1,981–2,536 SFOver 2,536 SFReal difference?
Net sale price$309KLowest$385K$490K$820KHighest✓ large
Net price per SF$228 per SF$213 per SFLowest$218 per SF$255 per SFHighest✓ medium
Year built200620062004Oldest2011Newest✓ small
Days on market51 days32 days49 days48 daysunclear
Discount from original list6.5%5.9%5.2%5.6%unclear
Price cut before sale52%43%50%37%unclear
Seller paid closing costs or repairs65%54%63%54%unclear
Has a view46%56%53%66%unclear

4.3 Homes over 2,536 SF sell for about $511K (165%) more than homes under 1,608 SF

2026-10-31T15:37:19.046272 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,608 SF 111 sales 1,608– 1,978 SF 110 sales 1,981– 2,536 SF 111 sales Over 2,536 SF 110 sales $0K $250K $500K $750K $309K $385K $490K $820K Net sale price, average

The average is $820K for homes over 2,536 SF and $309K for homes under 1,608 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 2,536 SF sell for about $28 per SF (12%) more than homes under 1,608 SF

2026-10-31T15:37:19.068656 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,608 SF 111 sales 1,608– 1,978 SF 110 sales 1,981– 2,536 SF 111 sales Over 2,536 SF 110 sales $0 $100 $200 $300 $228 $213 $218 $255 Net price per SF, average

The average is $255 per SF for homes over 2,536 SF and $228 per SF for homes under 1,608 SF. It does not move in a straight line; homes over 2,536 SF are highest. Defined in 8.1.2.

✓ Real difference · medium

4.5 Homes over 2,536 SF are about 5 years newer than homes under 1,608 SF

2026-10-31T15:37:19.092522 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,608 SF 111 sales 1,608– 1,978 SF 110 sales 1,981– 2,536 SF 111 sales Over 2,536 SF 110 sales 2000 2005 2010 2015 2006 2006 2004 2011 Year built: median (dot) and middle half (bar)

The median is 2011 for homes over 2,536 SF and 2006 for homes under 1,608 SF. It does not move in a straight line; homes over 2,536 SF are highest. Defined in 8.1.4.

✓ Real difference · small

4.6 Days on market: no clear difference

2026-10-31T15:37:19.115089 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,608 SF 111 sales 1,608– 1,978 SF 110 sales 1,981– 2,536 SF 111 sales Over 2,536 SF 110 sales 0 20 40 60 51 32 49 48 Days on market, median

The median is 48 days for homes over 2,536 SF and 51 days for homes under 1,608 SF. It does not move in a straight line; homes under 1,608 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-31T15:37:19.137297 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,608 SF 111 sales 1,608– 1,978 SF 110 sales 1,981– 2,536 SF 111 sales Over 2,536 SF 110 sales 0.0% 2.0% 4.0% 6.0% 6.5% 5.9% 5.2% 5.6% Discount from original list, average

The average is 5.6% for homes over 2,536 SF and 6.5% for homes under 1,608 SF. It does not move in a straight line; homes under 1,608 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

2026-10-31T15:37:19.164174 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% 52 65 46 43 54 56 50 63 53 37 54 66 Under 1,608 SF 1,608–1,978 SF 1,981–2,536 SF Over 2,536 SF

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

  • 37% of homes over 2,536 SF had a price cut before sale, against 52% of homes under 1,608 SF. Defined in 8.1.7.
  • 54% of homes over 2,536 SF had the seller pay closing costs or repairs, against 65% of homes under 1,608 SF. Defined in 8.1.8.
  • 66% of homes over 2,536 SF have a view, against 46% of homes under 1,608 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 1,608 SF111 sales1,608–1,978 SF110 sales1,981–2,536 SF111 salesOver 2,536 SF110 salesAll442 salesReal difference?
Net sale price average$309,051$384,613$490,025$820,185$500,510✓ large
Net price per SF average$228$213$218$255$228✓ medium
Living area average1,4091,8052,2463,1262,145by design
Year built median20062006200420112006✓ small

4.10 The numbers: selling

Under 1,608 SF111 sales1,608–1,978 SF110 sales1,981–2,536 SF111 salesOver 2,536 SF110 salesAll442 salesReal difference?
Days on market median5132494845unclear
Discount from original list average6.5%5.9%5.2%5.6%5.8%unclear
Price cut before sale52%43%50%37%45%unclear
Seller paid closing costs or repairs65%54%63%54%59%unclear
Has a view46%56%53%66%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 · 442 sales · May 4, 2026 – October 30, 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.

2026-10-31T15:37:19.185877 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 104 122 102 114 442 sales Sales per group Before 2000: 104 sales (24%) 2000–2006: 122 sales (28%) 2007–2015: 102 sales (23%) After 2015: 114 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 20002000–20062007–2015After 2015
Newer homes After 2015
  • Are less likely to have a view.
  • Sell for less per square foot.
Older homes Before 2000
  • Are more likely to have a view.
  • Sell for more 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 20002000–20062007–2015After 2015Real difference?
Net sale price$462K$465K$539K$539Kunclear
Net price per SF$242 per SFHighest$211 per SFLowest$227 per SF$236 per SF✓ small
Living area2,001 SF2,143 SF2,237 SF2,196 SFunclear
Days on market43 days43 days46 days54 daysunclear
Discount from original list6.5%6.3%4.9%5.5%unclear
Price cut before sale51%42%36%53%unclear
Seller paid closing costs or repairs56%66%60%54%unclear
Has a view50%52%75%Most46%Fewest✓ small

5.3 Net sale price: no clear difference

2026-10-31T15:37:19.206726 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 104 sales 2000– 2006 122 sales 2007– 2015 102 sales After 2015 114 sales $0K $200K $400K $600K $462K $465K $539K $539K Net sale price, average

The average is $539K for homes built after 2015 and $462K for homes built before 2000. It does not move in a straight line; homes built 2007–2015 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Homes built after 2015 sell for about $5 per SF (2%) less than homes built before 2000

2026-10-31T15:37:19.230239 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 104 sales 2000– 2006 122 sales 2007– 2015 102 sales After 2015 114 sales $0 $100 $200 $242 $211 $227 $236 Net price per SF, average

The average is $236 per SF for homes built after 2015 and $242 per SF for homes built before 2000. It does not move in a straight line; homes built before 2000 are highest. Defined in 8.1.2.

✓ Real difference · small

5.5 Living area: no clear difference

2026-10-31T15:37:19.252352 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 104 sales 2000– 2006 122 sales 2007– 2015 102 sales After 2015 114 sales 0 1,000 2,000 2,001 2,143 2,237 2,196 Living area (SF), average

The average is 2,196 SF for homes built after 2015 and 2,001 SF for homes built before 2000. It does not move in a straight line; homes built 2007–2015 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-31T15:37:19.274175 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 104 sales 2000– 2006 122 sales 2007– 2015 102 sales After 2015 114 sales 0 20 40 60 43 43 46 54 Days on market, median

The median is 54 days for homes built after 2015 and 43 days for homes built before 2000. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-31T15:37:19.296439 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2000 104 sales 2000– 2006 122 sales 2007– 2015 102 sales After 2015 114 sales 0.0% 2.0% 4.0% 6.0% 6.5% 6.3% 4.9% 5.5% Discount from original list, average

The average is 5.5% for homes built after 2015 and 6.5% 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

2026-10-31T15:37:19.323240 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 50 42 66 52 36 60 75 53 54 46 Before 2000 2000–2006 2007–2015 After 2015

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

  • 53% of homes built after 2015 had a price cut before sale, against 51% of homes built before 2000. Defined in 8.1.7.
  • 54% of homes built after 2015 had the seller pay closing costs or repairs, against 56% of homes built before 2000. Defined in 8.1.8.
  • 46% of homes built after 2015 have a view, against 50% 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 2000104 sales2000–2006122 sales2007–2015102 salesAfter 2015114 salesAll442 salesReal difference?
Net sale price average$462,062$464,927$539,371$538,893$500,510unclear
Net price per SF average$242$211$227$236$228✓ small
Living area average2,0012,1432,2372,1962,145unclear
Year built median19972004201120202006by design

5.10 The numbers: selling

Before 2000104 sales2000–2006122 sales2007–2015102 salesAfter 2015114 salesAll442 salesReal difference?
Days on market median4343465445unclear
Discount from original list average6.5%6.3%4.9%5.5%5.8%unclear
Price cut before sale51%42%36%53%45%unclear
Seller paid closing costs or repairs56%66%60%54%59%unclear
Has a view50%52%75%46%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 · 442 sales · May 4, 2026 – October 30, 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. 9 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-31T15:37:19.341697 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 245 188 433 sales Sales per group View: 245 sales (57%) No view: 188 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$558KHighest$427KLowest✓ small
Net price per SF$245 per SFHighest$208 per SFLowest✓ medium
Living area2,233 SF2,037 SFunclear
Year built20072005unclear
Days on market39 daysFastest52 daysSlowest✓ small
Discount from original list5.3%6.4%unclear
Price cut before sale41%51%unclear
Seller paid closing costs or repairs59%57%unclear

6.3 Homes with a view sell for about $131K (31%) more than homes without a view

2026-10-31T15:37:19.358164 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 245 sales No view 188 sales $0K $200K $400K $600K $558K $427K Net sale price, average

The average is $558K for homes with a view and $427K for homes without a view. Defined in 8.1.1.

✓ Real difference · small

6.4 Homes with a view sell for about $37 per SF (18%) more than homes without a view

2026-10-31T15:37:19.376204 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 245 sales No view 188 sales $0 $100 $200 $245 $208 Net price per SF, average

The average is $245 per SF for homes with a view and $208 per SF for homes without a view. Defined in 8.1.2.

✓ Real difference · medium

6.5 Living area: no clear difference

2026-10-31T15:37:19.416841 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 245 sales No view 188 sales 0 1,000 2,000 2,233 2,037 Living area (SF), average

The average is 2,233 SF for homes with a view and 2,037 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-31T15:37:19.436320 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 245 sales No view 188 sales 2000 2004 2008 2012 2016 2007 2005 Year built: median (dot) and middle half (bar)

The median is 2007 for homes with a view and 2005 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Homes with a view sell 14 days faster than homes without a view

2026-10-31T15:37:19.454819 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 245 sales No view 188 sales 0 20 40 60 39 52 Days on market, median

The median is 39 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

2026-10-31T15:37:19.472626 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 245 sales No view 188 sales 0.0% 2.0% 4.0% 6.0% 5.3% 6.4% Discount from original list, average

The average is 5.3% for homes with a view and 6.4% 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

2026-10-31T15:37:19.491399 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 41 59 51 57 View No view

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

  • 41% of homes with a view had a price cut before sale, against 51% of homes without a view. Defined in 8.1.7.
  • 59% of homes with a view had the seller pay closing costs or repairs, against 57% 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

View245 salesNo view188 salesAll433 salesReal difference?
Net sale price average$558,365$427,094$501,370✓ small
Net price per SF average$245$208$229✓ medium
Living area average2,2332,0372,148unclear
Year built median200720052006unclear

6.11 The numbers: selling

View245 salesNo view188 salesAll433 salesReal difference?
Days on market median395245✓ small
Discount from original list average5.3%6.4%5.8%unclear
Price cut before sale41%51%45%unclear
Seller paid closing costs or repairs59%57%58%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 · 154 sales · May 4, 2026 – October 30, 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: 154 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 ZIP 78633.
MeasureAverageMedian
Sales154
Net sale price$498,678$468,242
Net price per SF$195$192
Living area (SF)2,5712,598
Days on market11986
Discount from original list10.2%8.8%
Price cut before sale69% of sales
Seller paid closing costs or repairs69% 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
442 resale sales. Average $500,510; median $412,750; standard deviation $307,485; middle half (25th–75th percentile) $326,425–$573,451; lowest $203,450, highest $4,365,000. 260 sales had a seller payment; their median payment was $2,498.

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
442 resale sales. Average $228; median $213; standard deviation $90; middle half (25th–75th percentile) $193–$246; lowest $128, highest $1,530.

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
442 resale sales. Average 2,145; median 1,980; standard deviation 730; middle half (25th–75th percentile) 1,607–2,535; lowest 768, highest 7,077.

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 parts of the area.
Statistically
RESO YearBuilt; summarized by the median, with the 25th–75th percentile (middle half) on the charts.
The data
442 resale sales. Average 2007; median 2006; standard deviation 9; middle half (25th–75th percentile) 2000–2016; lowest 1945, 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
442 resale sales. Average 78; median 45; standard deviation 101; middle half (25th–75th percentile) 11–104; lowest 0, highest 722. 20 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
442 resale sales. Average 5.8%; median 4.5%; standard deviation 6.0%; middle half (25th–75th percentile) 1.5%–8.6%; lowest −6.9%, highest 33.1%. 25 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
201 of 442 resale sales (45.5%).

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
260 of 442 resale sales (58.8%).

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
245 sales with a view, 188 without, 9 unclassified. Most common View entries: Park/Greenbelt 148, Neighborhood 125, Trees/Woods 114, None 106, Golf Course 34, Hill Country 33, See Remarks 18, Panoramic 16.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-10-31 20:30 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, PostalCode = 78633.
The data
Pulled October 31, 2026: 1,193 closed ZIP 78633 records over the prior year. Cities: Georgetown (1,192); Florence (1). ZIP codes: 1, the most sales in 78633.

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 4, 2026 to October 30, 2026 inclusive.
The data
596 single-family sales in the window: 442 resale, 154 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
442 resale; 154 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
2 sale(s) other than single-family homes (condo, townhome and similar); 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 $326K”.
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 $326K: $203,450–$325,400 (110 sales); $326K–$412K: $326,000–$412,000 (111 sales); $414K–$574K: $413,500–$573,601 (111 sales); Over $574K: $574,000–$4,365,000 (110 sales)
Quartiles by living area: Under 1,608 SF: 768–1,607 SF (111 sales); 1,608–1,978 SF: 1,608–1,978 SF (110 sales); 1,981–2,536 SF: 1,981–2,536 SF (111 sales); Over 2,536 SF: 2,545–7,077 SF (110 sales)
Quartiles by year built: Before 2000: 1945–1999 (104 sales); 2000–2006: 2000–2006 (122 sales); 2007–2015: 2007–2015 (102 sales); After 2015: 2016–2026 (114 sales)
View and no view: View: MLS lists a view (245 sales); No view: None or Neighborhood (188 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 $500,510, median $412,750. Days on market: average 78, median 45: 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
13 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 = 205.853< 0.0001p < 0.0063Yesε² = 0.467large
Living areaKruskal–WallisH = 311.423< 0.0001p < 0.0063Yesε² = 0.706large
Year builtKruskal–WallisH = 1.5030.6832p < 0.0063Unclearε² = 0.003negligible
Days on marketKruskal–WallisH = 15.7830.0013p < 0.0063Yesε² = 0.036small
Discount from original listKruskal–WallisH = 26.403< 0.0001p < 0.0063Yesε² = 0.060small
Price cut before saleChi-squareχ² = 10.6730.0136p < 0.0063UnclearCramér’s V = 0.155small
Seller paid closing costs or repairsChi-squareχ² = 8.0930.0443p < 0.0063UnclearCramér’s V = 0.135small
Has a viewChi-squareχ² = 32.273< 0.0001p < 0.0063YesCramér’s V = 0.270small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 315.063< 0.0001p < 0.0063Yesε² = 0.714large
Net price per SFKruskal–WallisH = 44.053< 0.0001p < 0.0063Yesε² = 0.100medium
Year builtKruskal–WallisH = 16.5430.0009p < 0.0063Yesε² = 0.037small
Days on marketKruskal–WallisH = 5.5730.1345p < 0.0063Unclearε² = 0.013small
Discount from original listKruskal–WallisH = 4.9430.1766p < 0.0063Unclearε² = 0.011small
Price cut before saleChi-squareχ² = 6.1230.1060p < 0.0063UnclearCramér’s V = 0.118small
Seller paid closing costs or repairsChi-squareχ² = 4.9430.1762p < 0.0063UnclearCramér’s V = 0.106small
Has a viewChi-squareχ² = 9.6430.0219p < 0.0063UnclearCramér’s V = 0.148small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 6.5730.0870p < 0.0063Unclearε² = 0.015small
Net price per SFKruskal–WallisH = 19.1930.0002p < 0.0063Yesε² = 0.044small
Living areaKruskal–WallisH = 4.0330.2580p < 0.0063Unclearε² = 0.009negligible
Days on marketKruskal–WallisH = 1.2030.7533p < 0.0063Unclearε² = 0.003negligible
Discount from original listKruskal–WallisH = 2.5230.4715p < 0.0063Unclearε² = 0.006negligible
Price cut before saleChi-squareχ² = 7.7630.0512p < 0.0063UnclearCramér’s V = 0.133small
Seller paid closing costs or repairsChi-squareχ² = 4.0730.2545p < 0.0063UnclearCramér’s V = 0.096negligible
Has a viewChi-squareχ² = 22.253< 0.0001p < 0.0063YesCramér’s V = 0.224small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 29,493.50—< 0.0001p < 0.0063Yesrank-biserial r = 0.281small
Net price per SFMann–Whitney UU = 30,808.50—< 0.0001p < 0.0063Yesrank-biserial r = 0.338medium
Living areaMann–Whitney UU = 26,398.50—0.0091p < 0.0063Unclearrank-biserial r = 0.146small
Year builtMann–Whitney UU = 24,288.50—0.3293p < 0.0063Unclearrank-biserial r = 0.055negligible
Days on marketMann–Whitney UU = 19,210.00—0.0031p < 0.0063Yesrank-biserial r = 0.166small
Discount from original listMann–Whitney UU = 20,438.50—0.0447p < 0.0063Unclearrank-biserial r = 0.113small
Price cut before saleChi-squareχ² = 4.5110.0337p < 0.0063UnclearCramér’s V = 0.102small
Seller paid closing costs or repairsChi-squareχ² = 0.1310.7162p < 0.0063UnclearCramér’s V = 0.017negligible

8.4 Data notes

Left out of the analysis: 154 new-construction sales (basic statistics only, section 7); 2 sale(s) other than single-family homes (condo, townhome and similar); 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 442 closed MLS resale sales; the 154 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 31, 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.