ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Saddlecreek

Georgetown, TX 78626
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 7:10 AM CDT
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
31
single-family resale homes
Median net sale price
$343,700
average $367,116
Median net price per SF
$185
average $188
Median days on market
52 days
average 71 days
1. SummaryResale homes · 31 sales · October 26, 2025 – October 25, 2026

This study looks at the 31 resale homes sold in Saddlecreek in the 365 days to October 25, 2026. A full year is used because only 13 resale homes sold in the last 180 days. New construction is left out and shown on its own in section 7. The homes are compared four ways: by price, by living area, by year built and with or without a view. The first three are split into four equal groups (quartiles), each named by its range.

Each comparison has its own section (3–6) with everything about it in one place: the key differences, a table of every measure at a glance, the charts and the numbers.

2. Where the resale homes sold31 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 $317K · 8 sales$317K–$344K · 8 sales$349K–$398K · 7 salesOver $398K · 8 sales
3. Quartiles by net sale priceResale homes · 31 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:10:58.977788 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 7 8 31 sales Sales per group Under $317K: 8 sales (26%) $317K–$344K: 8 sales (26%) $349K–$398K: 7 sales (23%) Over $398K: 8 sales (26%)
Bottom line

3.1 Key differences

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

Under $317K$317K–$344K$349K–$398KOver $398K
Higher-priced homes Over $398K
  • Are much larger.
Lower-priced homes Under $317K
  • Are much smaller.

3.2 At a glance

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

Under $317K$317K–$344K$349K–$398KOver $398KReal difference?
Net price per SF$201 per SF$184 per SF$174 per SF$191 per SFunclear
Living area1,535 SFSmallest1,833 SF2,153 SF2,441 SFLargest✓ large
Year built2020201920202019unclear
Days on market75 days67 days47 days28 daysunclear
Discount from original list8.3%6.4%6.9%3.7%unclear
Price cut before sale75%62%71%25%unclear
Seller paid closing costs or repairs75%62%57%75%unclear
Has a view12%0%0%12%unclear

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

3.3 Net price per SF: no clear difference

2026-10-26T07:10:59.005298 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $317K 8 sales $317K– $344K 8 sales $349K– $398K 7 sales Over $398K 8 sales $0 $100 $200 $201 $184 $174 $191 Net price per SF, average

The average is $191 per SF for homes over $398K and $201 per SF for homes under $317K. It does not move in a straight line; homes under $317K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $398K are about 910 SF (59%) larger than homes under $317K

2026-10-26T07:10:59.027250 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $317K 8 sales $317K– $344K 8 sales $349K– $398K 7 sales Over $398K 8 sales 0 1,000 2,000 1,535 1,833 2,153 2,441 Living area (SF), average

The average is 2,441 SF for homes over $398K and 1,535 SF for homes under $317K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-26T07:10:59.049284 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $317K 8 sales $317K– $344K 8 sales $349K– $398K 7 sales Over $398K 8 sales 2018 2019 2020 2020 2019 2020 2019 Year built: median (dot) and middle half (bar)

The median is 2019 for homes over $398K and 2020 for homes under $317K. It does not move in a straight line; homes under $317K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:10:59.071394 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $317K 8 sales $317K– $344K 8 sales $349K– $398K 7 sales Over $398K 8 sales 0 25 50 75 75 67 47 28 Days on market, median

The median is 28 days for homes over $398K and 75 days for homes under $317K. 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 Discount from original list: no clear difference

2026-10-26T07:10:59.093494 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $317K 8 sales $317K– $344K 8 sales $349K– $398K 7 sales Over $398K 8 sales 0.0% 2.5% 5.0% 7.5% 8.3% 6.4% 6.9% 3.7% Discount from original list, average

The average is 3.7% for homes over $398K and 8.3% for homes under $317K. It does not move in a straight line; homes under $317K are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:10:59.122881 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% 75 75 12 62 62 0 71 57 0 25 75 12 Under $317K $317K–$344K $349K–$398K Over $398K

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

  • 25% of homes over $398K had a price cut before sale, against 75% of homes under $317K. Defined in 8.1.7.
  • 75% of homes over $398K had the seller pay closing costs or repairs, against 75% of homes under $317K. Defined in 8.1.8.
  • 12% of homes over $398K have a view, against 12% of homes under $317K. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

3.9 The numbers: price and size

Under $317K8 sales$317K–$344K8 sales$349K–$398K7 salesOver $398K8 salesAll31 salesReal difference?
Net sale price average$302,419$332,483$369,114$464,698$367,116by design
Net price per SF average$201$184$174$191$188unclear
Living area average1,5351,8332,1532,4411,985✓ large
Year built median20202019202020192019unclear

3.10 The numbers: selling

Under $317K8 sales$317K–$344K8 sales$349K–$398K7 salesOver $398K8 salesAll31 salesReal difference?
Days on market median7567472852unclear
Discount from original list average8.3%6.4%6.9%3.7%6.3%unclear
Price cut before sale75%62%71%25%58%unclear
Seller paid closing costs or repairs75%62%57%75%68%unclear
Has a view12%0%0%12%6%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.1.

4. Quartiles by living areaResale homes · 31 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:10:59.143149 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 8 8 31 sales Sales per group Under 1,624 SF: 8 sales (26%) 1,624–1,961 SF: 7 sales (23%) 2,022–2,302 SF: 8 sales (26%) Over 2,302 SF: 8 sales (26%)
Bottom line

4.1 Key differences

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

Under 1,624 SF1,624–1,961 SF2,022–2,302 SFOver 2,302 SF
Larger homes Over 2,302 SF
  • Sell for much more.
Smaller homes Under 1,624 SF
  • Sell for much less.

4.2 At a glance

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

Under 1,624 SF1,624–1,961 SF2,022–2,302 SFOver 2,302 SFReal difference?
Net sale price$306KLowest$341K$370K$448KHighest✓ large
Net price per SF$213 per SF$187 per SF$174 per SF$177 per SFunclear
Year built2020202020202018unclear
Days on market28 days59 days95 days34 daysunclear
Discount from original list5.9%5.4%8.6%5.2%unclear
Price cut before sale50%71%62%50%unclear
Seller paid closing costs or repairs62%71%75%62%unclear
Has a view12%0%12%0%unclear

4.3 Homes over 2,302 SF sell for about $142K (46%) more than homes under 1,624 SF

2026-10-26T07:10:59.163494 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,624 SF 8 sales 1,624– 1,961 SF 7 sales 2,022– 2,302 SF 8 sales Over 2,302 SF 8 sales $0K $200K $400K $306K $341K $370K $448K Net sale price, average

The average is $448K for homes over 2,302 SF and $306K for homes under 1,624 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-26T07:10:59.185846 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,624 SF 8 sales 1,624– 1,961 SF 7 sales 2,022– 2,302 SF 8 sales Over 2,302 SF 8 sales $0 $100 $200 $213 $187 $174 $177 Net price per SF, average

The average is $177 per SF for homes over 2,302 SF and $213 per SF for homes under 1,624 SF. It does not move in a straight line; homes under 1,624 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:10:59.207695 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,624 SF 8 sales 1,624– 1,961 SF 7 sales 2,022– 2,302 SF 8 sales Over 2,302 SF 8 sales 2018 2019 2020 2020 2020 2020 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over 2,302 SF and 2020 for homes under 1,624 SF. It does not move in a straight line; homes 1,624–1,961 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:10:59.229735 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,624 SF 8 sales 1,624– 1,961 SF 7 sales 2,022– 2,302 SF 8 sales Over 2,302 SF 8 sales 0 50 100 28 59 95 34 Days on market, median

The median is 34 days for homes over 2,302 SF and 28 days for homes under 1,624 SF. It does not move in a straight line; homes 2,022–2,302 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:10:59.251439 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,624 SF 8 sales 1,624– 1,961 SF 7 sales 2,022– 2,302 SF 8 sales Over 2,302 SF 8 sales 0.0% 5.0% 10.0% 5.9% 5.4% 8.6% 5.2% Discount from original list, average

The average is 5.2% for homes over 2,302 SF and 5.9% for homes under 1,624 SF. It does not move in a straight line; homes 2,022–2,302 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:10:59.276943 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 62 12 71 71 0 62 75 12 50 62 0 Under 1,624 SF 1,624–1,961 SF 2,022–2,302 SF Over 2,302 SF

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

  • 50% of homes over 2,302 SF had a price cut before sale, against 50% of homes under 1,624 SF. Defined in 8.1.7.
  • 62% of homes over 2,302 SF had the seller pay closing costs or repairs, against 62% of homes under 1,624 SF. Defined in 8.1.8.
  • 0% of homes over 2,302 SF have a view, against 12% of homes under 1,624 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 1,624 SF8 sales1,624–1,961 SF7 sales2,022–2,302 SF8 salesOver 2,302 SF8 salesAll31 salesReal difference?
Net sale price average$306,112$341,184$369,664$448,262$367,116✓ large
Net price per SF average$213$187$174$177$188unclear
Living area average1,4431,8242,1262,5291,985by design
Year built median20202020202020182019unclear

4.10 The numbers: selling

Under 1,624 SF8 sales1,624–1,961 SF7 sales2,022–2,302 SF8 salesOver 2,302 SF8 salesAll31 salesReal difference?
Days on market median2859953452unclear
Discount from original list average5.9%5.4%8.6%5.2%6.3%unclear
Price cut before sale50%71%62%50%58%unclear
Seller paid closing costs or repairs62%71%75%62%68%unclear
Has a view12%0%12%0%6%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. Groups by year builtResale homes · 31 sales · October 26, 2025 – October 25, 2026

Sales ranked by year built and cut into four groups, from the oldest to the newest. Homes built in the same year always stay in the same group, so group sizes can differ a little. Only 3 groups are shown: homes here share a few year built values, and no group may hold fewer than 3 sales.

2026-10-26T07:10:59.295515 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 9 14 31 sales Sales per group Before 2019: 8 sales (26%) 2019: 9 sales (29%) After 2019: 14 sales (45%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

The top group against the bottom group: no measure differs enough to rule out chance.

5.2 At a glance

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

Before 20192019After 2019Real difference?
Net sale price$389K$377K$348Kunclear
Net price per SF$174 per SF$197 per SF$190 per SFunclear
Living area2,266 SF1,925 SF1,864 SFunclear
Days on market40 days45 days72 daysunclear
Discount from original list4.8%5.2%7.9%unclear
Price cut before sale62%56%57%unclear
Seller paid closing costs or repairs88%56%64%unclear
Has a view0%0%14%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:10:59.314219 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 8 sales 2019 9 sales After 2019 14 sales $0K $100K $200K $300K $400K $389K $377K $348K Net sale price, average

The average is $348K for homes built after 2019 and $389K for homes built before 2019. It falls step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:10:59.335600 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 8 sales 2019 9 sales After 2019 14 sales $0 $50 $100 $150 $200 $174 $197 $190 Net price per SF, average

The average is $190 per SF for homes built after 2019 and $174 per SF for homes built before 2019. It does not move in a straight line; homes built 2019 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:10:59.355516 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 8 sales 2019 9 sales After 2019 14 sales 0 1,000 2,000 2,266 1,925 1,864 Living area (SF), average

The average is 1,864 SF for homes built after 2019 and 2,266 SF for homes built before 2019. It falls step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:10:59.374933 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 8 sales 2019 9 sales After 2019 14 sales 0 20 40 60 80 40 45 72 Days on market, median

The median is 72 days for homes built after 2019 and 40 days for homes built before 2019. 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

2026-10-26T07:10:59.396269 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 8 sales 2019 9 sales After 2019 14 sales 0.0% 2.0% 4.0% 6.0% 8.0% 4.8% 5.2% 7.9% Discount from original list, average

The average is 7.9% for homes built after 2019 and 4.8% for homes built before 2019. It rises step by step from the lowest range to the highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:10:59.419023 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% 62 88 0 56 56 0 57 64 14 Before 2019 2019 After 2019

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

  • 57% of homes built after 2019 had a price cut before sale, against 62% of homes built before 2019. Defined in 8.1.7.
  • 64% of homes built after 2019 had the seller pay closing costs or repairs, against 88% of homes built before 2019. Defined in 8.1.8.
  • 14% of homes built after 2019 have a view, against 0% of homes built before 2019. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

5.9 The numbers: price and size

Before 20198 sales20199 salesAfter 201914 salesAll31 salesReal difference?
Net sale price average$388,693$377,221$348,291$367,116unclear
Net price per SF average$174$197$190$188unclear
Living area average2,2661,9251,8641,985unclear
Year built median2018201920202019by design

5.10 The numbers: selling

Before 20198 sales20199 salesAfter 201914 salesAll31 salesReal difference?
Days on market median40457252unclear
Discount from original list average4.8%5.2%7.9%6.3%unclear
Price cut before sale62%56%57%58%unclear
Seller paid closing costs or repairs88%56%64%68%unclear
Has a view0%0%14%6%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.3.

6. View and no viewResale homes · 31 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:10:59.435677 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 2 27 29 sales Sales per group View: 2 sales (7%) No view: 27 sales (93%)
Bottom line: too few sales to test.

6.1 Key differences

The top group against the bottom group: no measure differs enough to rule out chance.

6.3 Net sale price: described, not tested

2026-10-26T07:10:59.452486 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 27 sales $0K $100K $200K $300K $400K $366K $370K Net sale price, average

The average is $366K for homes with a view and $370K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T07:10:59.470246 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 27 sales $0 $100 $200 $216 $184 Net price per SF, average

The average is $216 per SF for homes with a view and $184 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T07:10:59.487669 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 27 sales 0 500 1,000 1,500 2,000 1,709 2,042 Living area (SF), average

The average is 1,709 SF for homes with a view and 2,042 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T07:10:59.529401 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 27 sales −1 0 +2.02e3 2020 2019 Year built: median (dot) and middle half (bar)

The median is 2020 for homes with a view and 2019 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T07:10:59.546265 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 27 sales 0 20 40 60 16 56 Days on market, median

The median is 16 days for homes with a view and 56 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-26T07:10:59.564348 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 27 sales 0.0% 2.0% 4.0% 6.0% 8.0% 1.7% 6.9% Discount from original list, average

The average is 1.7% for homes with a view and 6.9% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

6.9 How often: price cut before sale, seller paid closing costs or repairs

2026-10-26T07:10:59.583375 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 0 100 67 67 View No view

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

  • 0% of homes with a view had a price cut before sale, against 67% of homes without a view. Defined in 8.1.7.
  • 100% of homes with a view had the seller pay closing costs or repairs, against 67% of homes without a view. Defined in 8.1.8.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View2 salesNo view27 salesAll29 sales
Net sale price average$366,000$370,354$370,054
Net price per SF average$216$184$186
Living area average1,7092,0422,019
Year built median202020192019

6.11 The numbers: selling

View2 salesNo view27 salesAll29 sales
Days on market median165654
Discount from original list average1.7%6.9%6.6%
Price cut before sale0%67%62%
Seller paid closing costs or repairs100%67%69%

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 · 6 sales · October 26, 2025 – October 25, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 6 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 Saddlecreek.
MeasureAverageMedian
Sales6
Net sale price$312,225$296,900
Net price per SF$180$182
Living area (SF)1,7381,759
Days on market203182
Discount from original list13.2%11.9%
Price cut before sale100% of sales
Seller paid closing costs or repairs50% of sales
Year built2017–2025

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
31 resale sales. Average $367,116; median $343,700; standard deviation $70,005; middle half (25th–75th percentile) $315,946–$401,744; lowest $288,000, highest $586,150. 21 sales had a seller payment; their median payment was $8,109.

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
31 resale sales. Average $188; median $185; standard deviation $24; middle half (25th–75th percentile) $171–$210; lowest $149, highest $232.

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
31 resale sales. Average 1,985; median 2,022; standard deviation 429; middle half (25th–75th percentile) 1,613–2,313; lowest 1,314, highest 2,817.

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
31 resale sales. Average 2019; median 2019; standard deviation 1; middle half (25th–75th percentile) 2018–2020; lowest 2017, highest 2022.

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
31 resale sales. Average 71; median 52; standard deviation 63; middle half (25th–75th percentile) 21–113; lowest 5, highest 235. 0 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
31 resale sales. Average 6.3%; median 5.5%; standard deviation 4.8%; middle half (25th–75th percentile) 2.4%–9.3%; lowest −3.1%, highest 16.9%. 1 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
18 of 31 resale sales (58.1%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
21 of 31 resale sales (67.7%).

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
2 sales with a view, 27 without, 2 unclassified. Most common View entries: None 18, Neighborhood 10, See Remarks 2, Park/Greenbelt 1, Garden 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Georgetown, SubdivisionName contains any of “saddlecreek”, “saddle creek twinhomes”, “saddlecreek condominiums”, “saddle creek”, “saddle crk”, “saddlecreek sub”, “saddlecreek condos” (case-insensitive). A record is kept when its subdivision name belongs to the Saddlecreek family, the same rule comparable sales use (it includes Saddle Creek Twinhomes, Saddlecreek Condos, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 47 closed Saddlecreek records over the prior year, in ZIP 78626. 13 subdivision spellings kept, the most common: Saddlecreek (16); Saddle Creek Twinhomes (8); Saddle Creek (5); Saddlecreek Condos (4); Saddlecreek Ph 1D (4); SADDLECREEK (2); Saddlecreek Ph 1B (2); Saddlecreek Ph 9 (1); Saddlecreek Ph 3A (1); Saddlecreek Ph 1e (1); Saddlecreek Ph 1 D (1); Saddlecreek Ph 5 (1); and 1 more (1 records). No other names were found by the search.

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 13 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
37 single-family sales in the window: 31 resale, 6 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
31 resale; 6 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
10 sale(s) other than single-family homes (condo, townhome and similar)

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 $317K”.
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 $317K: $288,000–$315,000 (8 sales); $317K–$344K: $316,891–$343,700 (8 sales); $349K–$398K: $349,000–$397,500 (7 sales); Over $398K: $405,987–$586,150 (8 sales)
Quartiles by living area: Under 1,624 SF: 1,314–1,602 SF (8 sales); 1,624–1,961 SF: 1,624–1,961 SF (7 sales); 2,022–2,302 SF: 2,022–2,302 SF (8 sales); Over 2,302 SF: 2,324–2,817 SF (8 sales)
Groups by year built: Before 2019: 2017–2018 (8 sales); 2019: 2019–2019 (9 sales); After 2019: 2020–2022 (14 sales)
View and no view: View: MLS lists a view (2 sales); No view: None or Neighborhood (27 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 $367,116, median $343,700. Days on market: average 71, median 52: 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; Groups by year built: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

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

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 5.8330.1204p < 0.0063Unclearε² = 0.194large
Living areaKruskal–WallisH = 19.6030.0002p < 0.0063Yesε² = 0.653large
Year builtKruskal–WallisH = 2.8430.4165p < 0.0063Unclearε² = 0.095medium
Days on marketKruskal–WallisH = 2.0530.5619p < 0.0063Unclearε² = 0.068medium
Discount from original listKruskal–WallisH = 4.0230.2594p < 0.0063Unclearε² = 0.134medium
Price cut before saleChi-squareχ² = 5.1130.1638p < 0.0063UnclearCramér’s V = 0.406medium
Seller paid closing costs or repairsChi-squareχ² = 0.8530.8384p < 0.0063UnclearCramér’s V = 0.165small
Has a viewChi-squareχ² = 2.0030.5715p < 0.0063UnclearCramér’s V = 0.254small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 20.8530.0001p < 0.0063Yesε² = 0.695large
Net price per SFKruskal–WallisH = 11.8730.0078p < 0.0063Unclearε² = 0.396large
Year builtKruskal–WallisH = 6.2330.1008p < 0.0063Unclearε² = 0.208large
Days on marketKruskal–WallisH = 3.1430.3707p < 0.0063Unclearε² = 0.105medium
Discount from original listKruskal–WallisH = 1.3230.7245p < 0.0063Unclearε² = 0.044small
Price cut before saleChi-squareχ² = 1.0130.7999p < 0.0063UnclearCramér’s V = 0.180small
Seller paid closing costs or repairsChi-squareχ² = 0.4430.9324p < 0.0063UnclearCramér’s V = 0.119small
Has a viewChi-squareχ² = 2.0030.5715p < 0.0063UnclearCramér’s V = 0.254small

8.3.3 Groups by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 2.1220.3459p < 0.0063Unclearε² = 0.071medium
Net price per SFKruskal–WallisH = 3.4720.1766p < 0.0063Unclearε² = 0.116medium
Living areaKruskal–WallisH = 4.5420.1035p < 0.0063Unclearε² = 0.151large
Days on marketKruskal–WallisH = 2.1920.3351p < 0.0063Unclearε² = 0.073medium
Discount from original listKruskal–WallisH = 1.9720.3742p < 0.0063Unclearε² = 0.066medium
Price cut before saleChi-squareχ² = 0.0920.9547p < 0.0063UnclearCramér’s V = 0.055negligible
Seller paid closing costs or repairsChi-squareχ² = 2.1220.3469p < 0.0063UnclearCramér’s V = 0.261small
Has a viewChi-squareχ² = 2.6020.2731p < 0.0063UnclearCramér’s V = 0.289small

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

Left out of the analysis: 6 new-construction sales (basic statistics only, section 7); 10 sale(s) other than single-family homes (condo, townhome and similar). 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 31 closed MLS resale sales; the 6 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.