ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Cimarron Hills

Georgetown, TX 78628
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 · 7:13 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
$1,199,634
average $1,283,134
Median net price per SF
$340
average $358
Median days on market
41 days
average 90 days
1. SummaryResale homes · 31 sales · October 26, 2025 – October 25, 2026

This study looks at the 31 resale homes sold in Cimarron Hills in the 365 days to October 25, 2026. A full year is used because only 19 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 $875K · 8 sales$875K–$1.20M · 8 sales$1.20M–$1.30M · 7 salesOver $1.30M · 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.

2026-10-26T07:13:18.984489 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 7 8 31 sales Sales per group Under $875K: 8 sales (26%) $875K–$1.20M: 8 sales (26%) $1.20M–$1.30M: 7 sales (23%) Over $1.30M: 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 $875K$875K–$1.20M$1.20M–$1.30MOver $1.30M
Higher-priced homes Over $1.30M
  • Are less likely to have a view.
  • Are much larger.
  • Sell for more per square foot.
Lower-priced homes Under $875K
  • Are more likely to have a view.
  • Are much smaller.
  • Sell for less per square foot.

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 $875K$875K–$1.20M$1.20M–$1.30MOver $1.30MReal difference?
Net price per SF$308 per SF$304 per SFLowest$362 per SF$460 per SFHighest✓ large
Living area2,479 SFSmallest3,561 SF3,542 SF4,386 SFLargest✓ large
Year built2016201820212016unclear
Days on market116 days140 days38 days17 daysunclear
Discount from original list10.6%10.7%11.0%4.4%unclear
Price cut before sale62%75%71%12%unclear
Seller paid closing costs or repairs50%62%14%62%unclear
Has a view100%Most88%29%Fewest88%✓ large

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 $1.30M sell for about $153 per SF (50%) more than homes under $875K

2026-10-26T07:13:19.013648 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $875K 8 sales $875K– $1.20M 8 sales $1.20M– $1.30M 7 sales Over $1.30M 8 sales $0 $200 $400 $308 $304 $362 $460 Net price per SF, average

The average is $460 per SF for homes over $1.30M and $308 per SF for homes under $875K. It does not move in a straight line; homes over $1.30M are highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $1.30M are about 1,910 SF (77%) larger than homes under $875K

2026-10-26T07:13:19.036952 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $875K 8 sales $875K– $1.20M 8 sales $1.20M– $1.30M 7 sales Over $1.30M 8 sales 0 2,000 4,000 2,479 3,561 3,542 4,386 Living area (SF), average

The average is 4,386 SF for homes over $1.30M and 2,479 SF for homes under $875K. It does not move in a straight line; homes over $1.30M are highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-26T07:13:19.061241 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $875K 8 sales $875K– $1.20M 8 sales $1.20M– $1.30M 7 sales Over $1.30M 8 sales 2011 2014 2017 2020 2016 2018 2021 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over $1.30M and 2016 for homes under $875K. It does not move in a straight line; homes $1.20M–$1.30M are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:13:19.084469 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $875K 8 sales $875K– $1.20M 8 sales $1.20M– $1.30M 7 sales Over $1.30M 8 sales 0 50 100 150 116 140 38 17 Days on market, median

The median is 17 days for homes over $1.30M and 116 days for homes under $875K. It does not move in a straight line; homes $875K–$1.20M are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:13:19.107411 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $875K 8 sales $875K– $1.20M 8 sales $1.20M– $1.30M 7 sales Over $1.30M 8 sales 0.0% 5.0% 10.0% 10.6% 10.7% 11.0% 4.4% Discount from original list, average

The average is 4.4% for homes over $1.30M and 10.6% for homes under $875K. It does not move in a straight line; homes $1.20M–$1.30M 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

2026-10-26T07:13:19.137941 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 50 100 75 62 88 71 14 29 12 62 88 Under $875K $875K–$1.20M $1.20M–$1.30M Over $1.30M

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

  • 12% of homes over $1.30M had a price cut before sale, against 62% of homes under $875K. Defined in 8.1.7.
  • 62% of homes over $1.30M had the seller pay closing costs or repairs, against 50% of homes under $875K. Defined in 8.1.8.
  • 88% of homes over $1.30M have a view, against 100% of homes under $875K. 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 · large

3.9 The numbers: price and size

Under $875K8 sales$875K–$1.20M8 sales$1.20M–$1.30M7 salesOver $1.30M8 salesAll31 salesReal difference?
Net sale price average$738,688$1,066,930$1,265,314$2,059,376$1,283,134by design
Net price per SF average$308$304$362$460$358✓ large
Living area average2,4793,5613,5424,3863,490✓ large
Year built median20162018202120162017unclear

3.10 The numbers: selling

Under $875K8 sales$875K–$1.20M8 sales$1.20M–$1.30M7 salesOver $1.30M8 salesAll31 salesReal difference?
Days on market median116140381741unclear
Discount from original list average10.6%10.7%11.0%4.4%9.1%unclear
Price cut before sale62%75%71%12%55%unclear
Seller paid closing costs or repairs50%62%14%62%48%unclear
Has a view100%88%29%88%77%✓ large

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.

2026-10-26T07:13:19.159097 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 7 8 31 sales Sales per group Under 3,023 SF: 8 sales (26%) 3,023–3,302 SF: 8 sales (26%) 3,588–4,116 SF: 7 sales (23%) Over 4,116 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 3,023 SF3,023–3,302 SF3,588–4,116 SFOver 4,116 SF
Larger homes Over 4,116 SF
  • Sell for much more.
Smaller homes Under 3,023 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 3,023 SF3,023–3,302 SF3,588–4,116 SFOver 4,116 SFReal difference?
Net sale price$777KLowest$1.12M$1.36M$1.89MHighest✓ large
Net price per SF$329 per SF$352 per SF$345 per SF$405 per SFunclear
Year built2017202120142018unclear
Days on market56 days47 days88 days20 daysunclear
Discount from original list7.6%8.0%10.6%10.5%unclear
Price cut before sale50%62%71%38%unclear
Seller paid closing costs or repairs50%38%71%38%unclear
Has a view100%50%86%75%unclear

4.3 Homes over 4,116 SF sell for about $1.11M (143%) more than homes under 3,023 SF

2026-10-26T07:13:19.179918 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,023 SF 8 sales 3,023– 3,302 SF 8 sales 3,588– 4,116 SF 7 sales Over 4,116 SF 8 sales $0K $1.00M $2.00M $777K $1.12M $1.36M $1.89M Net sale price, average

The average is $1.89M for homes over 4,116 SF and $777K for homes under 3,023 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

2026-10-26T07:13:19.202746 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,023 SF 8 sales 3,023– 3,302 SF 8 sales 3,588– 4,116 SF 7 sales Over 4,116 SF 8 sales $0 $200 $400 $329 $352 $345 $405 Net price per SF, average

The average is $405 per SF for homes over 4,116 SF and $329 per SF for homes under 3,023 SF. It does not move in a straight line; homes over 4,116 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:13:19.226721 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,023 SF 8 sales 3,023– 3,302 SF 8 sales 3,588– 4,116 SF 7 sales Over 4,116 SF 8 sales 2011 2014 2017 2020 2017 2021 2014 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over 4,116 SF and 2017 for homes under 3,023 SF. It does not move in a straight line; homes 3,023–3,302 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:13:19.250134 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,023 SF 8 sales 3,023– 3,302 SF 8 sales 3,588– 4,116 SF 7 sales Over 4,116 SF 8 sales 0 50 100 56 47 88 20 Days on market, median

The median is 20 days for homes over 4,116 SF and 56 days for homes under 3,023 SF. It does not move in a straight line; homes 3,588–4,116 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:13:19.272636 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,023 SF 8 sales 3,023– 3,302 SF 8 sales 3,588– 4,116 SF 7 sales Over 4,116 SF 8 sales 0.0% 5.0% 10.0% 7.6% 8.0% 10.6% 10.5% Discount from original list, average

The average is 10.5% for homes over 4,116 SF and 7.6% for homes under 3,023 SF. It does not move in a straight line; homes 3,588–4,116 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

2026-10-26T07:13:19.299726 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 50 100 62 38 50 71 71 86 38 38 75 Under 3,023 SF 3,023–3,302 SF 3,588–4,116 SF Over 4,116 SF

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

  • 38% of homes over 4,116 SF had a price cut before sale, against 50% of homes under 3,023 SF. Defined in 8.1.7.
  • 38% of homes over 4,116 SF had the seller pay closing costs or repairs, against 50% of homes under 3,023 SF. Defined in 8.1.8.
  • 75% of homes over 4,116 SF have a view, against 100% of homes under 3,023 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 3,023 SF8 sales3,023–3,302 SF8 sales3,588–4,116 SF7 salesOver 4,116 SF8 salesAll31 salesReal difference?
Net sale price average$776,938$1,118,401$1,358,092$1,888,475$1,283,134✓ large
Net price per SF average$329$352$345$405$358unclear
Living area average2,3433,1763,9464,5533,490by design
Year built median20172021201420182017unclear

4.10 The numbers: selling

Under 3,023 SF8 sales3,023–3,302 SF8 sales3,588–4,116 SF7 salesOver 4,116 SF8 salesAll31 salesReal difference?
Days on market median5647882041unclear
Discount from original list average7.6%8.0%10.6%10.5%9.1%unclear
Price cut before sale50%62%71%38%55%unclear
Seller paid closing costs or repairs50%38%71%38%48%unclear
Has a view100%50%86%75%77%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 · 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.

2026-10-26T07:13:19.321087 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 9 6 8 31 sales Sales per group Before 2014: 8 sales (26%) 2014–2017: 9 sales (29%) 2018–2021: 6 sales (19%) After 2021: 8 sales (26%)
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 20142014–20172018–2021After 2021Real difference?
Net sale price$1.32M$961K$1.87M$1.17Munclear
Net price per SF$344 per SF$324 per SF$446 per SF$346 per SFunclear
Living area3,845 SF2,987 SF3,951 SF3,357 SFunclear
Days on market54 days129 days12 days35 daysunclear
Discount from original list9.2%13.1%5.3%7.4%unclear
Price cut before sale50%89%17%50%unclear
Seller paid closing costs or repairs50%56%50%38%unclear
Has a view88%89%67%62%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:13:19.342099 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 8 sales 2014– 2017 9 sales 2018– 2021 6 sales After 2021 8 sales $0K $1.00M $2.00M $1.32M $961K $1.87M $1.17M Net sale price, average

The average is $1.17M for homes built after 2021 and $1.32M for homes built before 2014. It does not move in a straight line; homes built 2018–2021 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:13:19.365495 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 8 sales 2014– 2017 9 sales 2018– 2021 6 sales After 2021 8 sales $0 $200 $400 $344 $324 $446 $346 Net price per SF, average

The average is $346 per SF for homes built after 2021 and $344 per SF for homes built before 2014. It does not move in a straight line; homes built 2018–2021 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:13:19.387249 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 8 sales 2014– 2017 9 sales 2018– 2021 6 sales After 2021 8 sales 0 2,000 4,000 3,845 2,987 3,951 3,357 Living area (SF), average

The average is 3,357 SF for homes built after 2021 and 3,845 SF for homes built before 2014. It does not move in a straight line; homes built 2018–2021 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:13:19.408731 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 8 sales 2014– 2017 9 sales 2018– 2021 6 sales After 2021 8 sales 0 50 100 150 54 129 12 35 Days on market, median

The median is 35 days for homes built after 2021 and 54 days for homes built before 2014. It does not move in a straight line; homes built 2014–2017 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:13:19.431781 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 8 sales 2014– 2017 9 sales 2018– 2021 6 sales After 2021 8 sales 0.0% 5.0% 10.0% 15.0% 9.2% 13.1% 5.3% 7.4% Discount from original list, average

The average is 7.4% for homes built after 2021 and 9.2% for homes built before 2014. It does not move in a straight line; homes built 2014–2017 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

2026-10-26T07:13:19.457728 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 50 88 89 56 89 17 50 67 50 38 62 Before 2014 2014–2017 2018–2021 After 2021

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

  • 50% of homes built after 2021 had a price cut before sale, against 50% of homes built before 2014. Defined in 8.1.7.
  • 38% of homes built after 2021 had the seller pay closing costs or repairs, against 50% of homes built before 2014. Defined in 8.1.8.
  • 62% of homes built after 2021 have a view, against 88% of homes built before 2014. 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 20148 sales2014–20179 sales2018–20216 salesAfter 20218 salesAll31 salesReal difference?
Net sale price average$1,324,442$960,558$1,866,083$1,167,512$1,283,134unclear
Net price per SF average$344$324$446$346$358unclear
Living area average3,8452,9873,9513,3573,490unclear
Year built median20102015202120222017by design

5.10 The numbers: selling

Before 20148 sales2014–20179 sales2018–20216 salesAfter 20218 salesAll31 salesReal difference?
Days on market median54129123541unclear
Discount from original list average9.2%13.1%5.3%7.4%9.1%unclear
Price cut before sale50%89%17%50%55%unclear
Seller paid closing costs or repairs50%56%50%38%48%unclear
Has a view88%89%67%62%77%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.

2026-10-26T07:13:19.476862 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 24 7 31 sales Sales per group View: 24 sales (77%) No view: 7 sales (23%)
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
  • More often have the seller pay buyer costs or repairs.
Homes without a view no view listed
  • Less often have the seller pay buyer costs or repairs.

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$1.29M$1.24Munclear
Net price per SF$361 per SF$350 per SFunclear
Living area3,463 SF3,585 SFunclear
Year built20162021unclear
Days on market58 days32 daysunclear
Discount from original list8.8%10.2%unclear
Price cut before sale54%57%unclear
Seller paid closing costs or repairs62%Most0%Fewest✓ large

6.3 Net sale price: no clear difference

2026-10-26T07:13:19.492936 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 7 sales $0K $500K $1.00M $1.50M $1.29M $1.24M Net sale price, average

The average is $1.29M for homes with a view and $1.24M for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-10-26T07:13:19.511714 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 7 sales $0 $100 $200 $300 $400 $361 $350 Net price per SF, average

The average is $361 per SF for homes with a view and $350 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-10-26T07:13:19.531604 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 7 sales 0 1,000 2,000 3,000 4,000 3,463 3,585 Living area (SF), average

The average is 3,463 SF for homes with a view and 3,585 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:13:19.580235 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 7 sales 2014 2016 2018 2020 2022 2016 2021 Year built: median (dot) and middle half (bar)

The median is 2016 for homes with a view and 2021 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:13:19.598785 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 7 sales 0 20 40 60 58 32 Days on market, median

The median is 58 days for homes with a view and 32 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-10-26T07:13:19.618152 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 24 sales No view 7 sales 0.0% 2.5% 5.0% 7.5% 10.0% 8.8% 10.2% Discount from original list, average

The average is 8.8% for homes with a view and 10.2% 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

2026-10-26T07:13:19.637638 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 54 62 57 0 View No view

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

  • 54% of homes with a view had a price cut before sale, against 57% of homes without a view. Defined in 8.1.7.
  • 62% of homes with a view had the seller pay closing costs or repairs, against 0% 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: ✓ Real difference · large

6.10 The numbers: price and size

View24 salesNo view7 salesAll31 salesReal difference?
Net sale price average$1,294,519$1,244,100$1,283,134unclear
Net price per SF average$361$350$358unclear
Living area average3,4633,5853,490unclear
Year built median201620212017unclear

6.11 The numbers: selling

View24 salesNo view7 salesAll31 salesReal difference?
Days on market median583241unclear
Discount from original list average8.8%10.2%9.1%unclear
Price cut before sale54%57%55%unclear
Seller paid closing costs or repairs62%0%48%✓ large

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 · 4 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: 4 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 Cimarron Hills.
MeasureAverageMedian
Sales4
Net sale price$1,434,716$1,420,000
Net price per SF$397$365
Living area (SF)3,6453,190
Days on market182124
Discount from original list11.4%6.6%
Price cut before sale50% of sales
Seller paid closing costs or repairs0% of sales
Year built2021–2026

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
31 resale sales. Average $1,283,134; median $1,199,634; standard deviation $626,419; middle half (25th–75th percentile) $873,515–$1,392,754; lowest $518,875, highest $3,744,000. 15 sales had a seller payment; their median payment was $4,401.

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 $358; median $340; standard deviation $87; middle half (25th–75th percentile) $302–$397; lowest $201, highest $611.

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 3,490; median 3,302; standard deviation 932; middle half (25th–75th percentile) 3,012–4,136; lowest 1,648, highest 6,126.

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 2017; median 2017; standard deviation 6; middle half (25th–75th percentile) 2014–2022; lowest 2004, highest 2025.

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 90; median 41; standard deviation 106; middle half (25th–75th percentile) 14–141; lowest 2, highest 405. 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 9.1%; median 6.5%; standard deviation 6.8%; middle half (25th–75th percentile) 3.9%–14.0%; lowest −0.4%, highest 25.5%. 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
17 of 31 resale sales (54.8%).

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
15 of 31 resale sales (48.4%).

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
24 sales with a view, 7 without, 0 unclassified. Most common View entries: Golf Course 16, Park/Greenbelt 9, None 5, Trees/Woods 4, Neighborhood 3, Pond 2, Pool 2, Panoramic 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 “cimarron hills” (case-insensitive). A record is kept when its subdivision name belongs to the Cimarron Hills family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 36 closed Cimarron Hills records over the prior year, in ZIP 78628. 9 subdivision spellings kept: Cimarron Hills (18); Cimarron Hills Ph 3 Sec 2 (6); Cimarron Hills Ph 2 Sec 2 (4); Cimarron Hills Ph 3 Sec 3 (2); Cimarron Hills Ph 1 Sec 2 (2); Cimarron Hills Ph 2 Sec 1 (1); Cimarron Hills Ph 1 Sec 3 (1); Cimarron Hills Ph 02 Sec 01 Pud (1); Cimarron Hills Ph 1 Sec 1 (1). Names found by the search but not part of Cimarron Hills, left out: Villas At Cimarron Hills Pud (1); Cimarron Hills Country Club (1).

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 19 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
35 single-family sales in the window: 31 resale, 4 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; 4 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 $875K”.
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 $875K: $518,875–$872,030 (8 sales); $875K–$1.20M: $875,000–$1,199,634 (8 sales); $1.20M–$1.30M: $1,200,000–$1,300,000 (7 sales); Over $1.30M: $1,485,508–$3,744,000 (8 sales)
Quartiles by living area: Under 3,023 SF: 1,648–3,000 SF (8 sales); 3,023–3,302 SF: 3,023–3,302 SF (8 sales); 3,588–4,116 SF: 3,588–4,116 SF (7 sales); Over 4,116 SF: 4,155–6,126 SF (8 sales)
Quartiles by year built: Before 2014: 2004–2013 (8 sales); 2014–2017: 2014–2017 (9 sales); 2018–2021: 2018–2021 (6 sales); After 2021: 2022–2025 (8 sales)
View and no view: View: MLS lists a view (24 sales); No view: None or Neighborhood (7 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 $1,283,134, median $1,199,634. Days on market: average 90, median 41: 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
5 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 = 17.0230.0007p < 0.0063Yesε² = 0.567large
Living areaKruskal–WallisH = 17.0730.0007p < 0.0063Yesε² = 0.569large
Year builtKruskal–WallisH = 1.9330.5876p < 0.0063Unclearε² = 0.064medium
Days on marketKruskal–WallisH = 8.2530.0411p < 0.0063Unclearε² = 0.275large
Discount from original listKruskal–WallisH = 4.8330.1844p < 0.0063Unclearε² = 0.161large
Price cut before saleChi-squareχ² = 8.0730.0446p < 0.0063UnclearCramér’s V = 0.510large
Seller paid closing costs or repairsChi-squareχ² = 4.5430.2084p < 0.0063UnclearCramér’s V = 0.383medium
Has a viewChi-squareχ² = 12.8230.0050p < 0.0063YesCramér’s V = 0.643large

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 18.3030.0004p < 0.0063Yesε² = 0.610large
Net price per SFKruskal–WallisH = 1.5230.6787p < 0.0063Unclearε² = 0.051small
Year builtKruskal–WallisH = 2.6930.4419p < 0.0063Unclearε² = 0.090medium
Days on marketKruskal–WallisH = 1.2130.7508p < 0.0063Unclearε² = 0.040small
Discount from original listKruskal–WallisH = 0.9330.8175p < 0.0063Unclearε² = 0.031small
Price cut before saleChi-squareχ² = 2.0130.5695p < 0.0063UnclearCramér’s V = 0.255small
Seller paid closing costs or repairsChi-squareχ² = 2.2630.5210p < 0.0063UnclearCramér’s V = 0.270small
Has a viewChi-squareχ² = 6.0830.1080p < 0.0063UnclearCramér’s V = 0.443medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 5.7830.1229p < 0.0063Unclearε² = 0.193large
Net price per SFKruskal–WallisH = 5.4030.1445p < 0.0063Unclearε² = 0.180large
Living areaKruskal–WallisH = 5.0830.1658p < 0.0063Unclearε² = 0.169large
Days on marketKruskal–WallisH = 5.5030.1388p < 0.0063Unclearε² = 0.183large
Discount from original listKruskal–WallisH = 5.6930.1276p < 0.0063Unclearε² = 0.190large
Price cut before saleChi-squareχ² = 7.8930.0482p < 0.0063UnclearCramér’s V = 0.505large
Seller paid closing costs or repairsChi-squareχ² = 0.5830.9011p < 0.0063UnclearCramér’s V = 0.137small
Has a viewChi-squareχ² = 2.5630.4650p < 0.0063UnclearCramér’s V = 0.287small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 62.00—0.3174p < 0.0063Unclearrank-biserial r = 0.262small
Net price per SFMann–Whitney UU = 83.00—0.9816p < 0.0063Unclearrank-biserial r = 0.012negligible
Living areaMann–Whitney UU = 78.00—0.7995p < 0.0063Unclearrank-biserial r = 0.071negligible
Year builtMann–Whitney UU = 54.50—0.1687p < 0.0063Unclearrank-biserial r = 0.351medium
Days on marketMann–Whitney UU = 96.50—0.5705p < 0.0063Unclearrank-biserial r = 0.149small
Discount from original listMann–Whitney UU = 67.00—0.4443p < 0.0063Unclearrank-biserial r = 0.202small
Price cut before saleChi-squareχ² = 0.0210.8893p < 0.0063UnclearCramér’s V = 0.025negligible
Seller paid closing costs or repairsChi-squareχ² = 8.4810.0036p < 0.0063YesCramér’s V = 0.523large

8.4 Data notes

Left out of the analysis: 4 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 31 closed MLS resale sales; the 4 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.