ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Rim Rock

Driftwood, TX 78619
Resale homes · closed Nov 5 – Nov 4, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 5, 2026 · 2:35 PM CST
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
24
single-family resale homes
Median net sale price
$942,500
average $1,010,180
Median net price per SF
$291
average $300
Median days on market
43 days
average 60 days
1. SummaryResale homes · 24 sales · November 5, 2025 – November 4, 2026

This study looks at the 24 resale homes sold in Rim Rock in the 365 days to November 4, 2026. A full year is used because only 12 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 sold24 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 $865K · 6 sales$865K–$940K · 6 sales$945K–$1.15M · 6 salesOver $1.15M · 6 sales
3. Quartiles by net sale priceResale homes · 24 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T14:36:06.713991 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 6 6 24 sales Sales per group Under $865K: 6 sales (25%) $865K–$940K: 6 sales (25%) $945K–$1.15M: 6 sales (25%) Over $1.15M: 6 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 $865K$865K–$940K$945K–$1.15MOver $1.15M
Higher-priced homes Over $1.15M
  • Sell for more per square foot.
Lower-priced homes Under $865K
  • 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 $865K$865K–$940K$945K–$1.15MOver $1.15MReal difference?
Net price per SF$240 per SFLowest$299 per SF$283 per SF$376 per SFHighest✓ large
Living area3,460 SF3,072 SF3,594 SF3,495 SFunclear
Year built2014201720142016unclear
Days on market78 days9 days40 days31 daysunclear
Discount from original list7.0%1.9%9.0%7.0%unclear
Price cut before sale67%33%50%50%unclear
Seller paid closing costs or repairs100%50%33%33%unclear
Has a view83%100%83%67%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 Homes over $1.15M sell for about $136 per SF (57%) more than homes under $865K

2026-11-05T14:36:06.742112 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $865K 6 sales $865K– $940K 6 sales $945K– $1.15M 6 sales Over $1.15M 6 sales $0 $200 $400 $240 $299 $283 $376 Net price per SF, average

The average is $376 per SF for homes over $1.15M and $240 per SF for homes under $865K. It does not move in a straight line; homes over $1.15M are highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Living area: no clear difference

2026-11-05T14:36:06.763993 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $865K 6 sales $865K– $940K 6 sales $945K– $1.15M 6 sales Over $1.15M 6 sales 0 2,000 4,000 3,460 3,072 3,594 3,495 Living area (SF), average

The average is 3,495 SF for homes over $1.15M and 3,460 SF for homes under $865K. It does not move in a straight line; homes $945K–$1.15M are highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-11-05T14:36:06.787462 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $865K 6 sales $865K– $940K 6 sales $945K– $1.15M 6 sales Over $1.15M 6 sales 2012 2014 2016 2018 2014 2017 2014 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over $1.15M and 2014 for homes under $865K. It does not move in a straight line; homes $865K–$940K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-05T14:36:06.809643 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $865K 6 sales $865K– $940K 6 sales $945K– $1.15M 6 sales Over $1.15M 6 sales 0 25 50 75 78 9 40 31 Days on market, median

The median is 31 days for homes over $1.15M and 78 days for homes under $865K. It does not move in a straight line; homes under $865K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-05T14:36:06.832493 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $865K 6 sales $865K– $940K 6 sales $945K– $1.15M 6 sales Over $1.15M 6 sales 0.0% 5.0% 10.0% 7.0% 1.9% 9.0% 7.0% Discount from original list, average

The average is 7.0% for homes over $1.15M and 7.0% for homes under $865K. It does not move in a straight line; homes $945K–$1.15M 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

2026-11-05T14:36:06.861928 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% 67 100 83 33 50 100 50 33 83 50 33 67 Under $865K $865K–$940K $945K–$1.15M Over $1.15M

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

  • 50% of homes over $1.15M had a price cut before sale, against 67% of homes under $865K. Defined in 8.1.7.
  • 33% of homes over $1.15M had the seller pay closing costs or repairs, against 100% of homes under $865K. Defined in 8.1.8.
  • 67% of homes over $1.15M have a view, against 83% of homes under $865K. 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 $865K6 sales$865K–$940K6 sales$945K–$1.15M6 salesOver $1.15M6 salesAll24 salesReal difference?
Net sale price average$813,037$904,009$1,012,200$1,311,475$1,010,180by design
Net price per SF average$240$299$283$376$300✓ large
Living area average3,4603,0723,5943,4953,405unclear
Year built median20142017201420162014unclear

3.10 The numbers: selling

Under $865K6 sales$865K–$940K6 sales$945K–$1.15M6 salesOver $1.15M6 salesAll24 salesReal difference?
Days on market median789403143unclear
Discount from original list average7.0%1.9%9.0%7.0%6.2%unclear
Price cut before sale67%33%50%50%50%unclear
Seller paid closing costs or repairs100%50%33%33%54%unclear
Has a view83%100%83%67%83%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 · 24 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T14:36:06.881607 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 6 6 24 sales Sales per group Under 3,253 SF: 6 sales (25%) 3,253–3,462 SF: 6 sales (25%) 3,473–3,719 SF: 6 sales (25%) Over 3,719 SF: 6 sales (25%)
Bottom line: no measure differs enough between the groups to rule out chance.

4.1 Key differences

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

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 3,253 SF3,253–3,462 SF3,473–3,719 SFOver 3,719 SFReal difference?
Net sale price$926K$1.10M$952K$1.07Munclear
Net price per SF$329 per SF$327 per SF$266 per SF$277 per SFunclear
Year built2018201420142014unclear
Days on market20 days28 days34 days78 daysunclear
Discount from original list3.2%3.9%6.3%11.6%unclear
Price cut before sale33%33%50%83%unclear
Seller paid closing costs or repairs50%67%50%50%unclear
Has a view100%83%83%67%unclear

4.3 Net sale price: no clear difference

2026-11-05T14:36:06.902030 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,253 SF 6 sales 3,253– 3,462 SF 6 sales 3,473– 3,719 SF 6 sales Over 3,719 SF 6 sales $0K $500K $1.00M $926K $1.10M $952K $1.07M Net sale price, average

The average is $1.07M for homes over 3,719 SF and $926K for homes under 3,253 SF. It does not move in a straight line; homes 3,253–3,462 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-11-05T14:36:06.924206 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,253 SF 6 sales 3,253– 3,462 SF 6 sales 3,473– 3,719 SF 6 sales Over 3,719 SF 6 sales $0 $100 $200 $300 $329 $327 $266 $277 Net price per SF, average

The average is $277 per SF for homes over 3,719 SF and $329 per SF for homes under 3,253 SF. It does not move in a straight line; homes under 3,253 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-05T14:36:06.946807 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,253 SF 6 sales 3,253– 3,462 SF 6 sales 3,473– 3,719 SF 6 sales Over 3,719 SF 6 sales 2014 2016 2018 2018 2014 2014 2014 Year built: median (dot) and middle half (bar)

The median is 2014 for homes over 3,719 SF and 2018 for homes under 3,253 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-05T14:36:06.970711 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,253 SF 6 sales 3,253– 3,462 SF 6 sales 3,473– 3,719 SF 6 sales Over 3,719 SF 6 sales 0 25 50 75 20 28 34 78 Days on market, median

The median is 78 days for homes over 3,719 SF and 20 days for homes under 3,253 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-05T14:36:06.993343 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,253 SF 6 sales 3,253– 3,462 SF 6 sales 3,473– 3,719 SF 6 sales Over 3,719 SF 6 sales 0.0% 5.0% 10.0% 3.2% 3.9% 6.3% 11.6% Discount from original list, average

The average is 11.6% for homes over 3,719 SF and 3.2% for homes under 3,253 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-05T14:36:07.019303 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% 33 50 100 33 67 83 50 50 83 83 50 67 Under 3,253 SF 3,253–3,462 SF 3,473–3,719 SF Over 3,719 SF

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

  • 83% of homes over 3,719 SF had a price cut before sale, against 33% of homes under 3,253 SF. Defined in 8.1.7.
  • 50% of homes over 3,719 SF had the seller pay closing costs or repairs, against 50% of homes under 3,253 SF. Defined in 8.1.8.
  • 67% of homes over 3,719 SF have a view, against 100% of homes under 3,253 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 3,253 SF6 sales3,253–3,462 SF6 sales3,473–3,719 SF6 salesOver 3,719 SF6 salesAll24 salesReal difference?
Net sale price average$925,542$1,097,700$952,133$1,065,345$1,010,180unclear
Net price per SF average$329$327$266$277$300unclear
Living area average2,8033,3523,5863,8803,405by design
Year built median20182014201420142014unclear

4.10 The numbers: selling

Under 3,253 SF6 sales3,253–3,462 SF6 sales3,473–3,719 SF6 salesOver 3,719 SF6 salesAll24 salesReal difference?
Days on market median2028347843unclear
Discount from original list average3.2%3.9%6.3%11.6%6.2%unclear
Price cut before sale33%33%50%83%50%unclear
Seller paid closing costs or repairs50%67%50%50%54%unclear
Has a view100%83%83%67%83%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 · 24 sales · November 5, 2025 – November 4, 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.

2026-11-05T14:36:07.041082 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 8 4 6 24 sales Sales per group Before 2014: 6 sales (25%) 2014: 8 sales (33%) 2015–2018: 4 sales (17%) After 2018: 6 sales (25%)
Bottom line: too few sales to test.

5.1 Key differences

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

5.3 Net sale price: described, not tested

2026-11-05T14:36:07.061973 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014 8 sales 2015– 2018 4 sales After 2018 6 sales $0K $500K $1.00M $884K $1.10M $989K $1.04M Net sale price, average

The average is $1.04M for homes built after 2018 and $884K for homes built before 2014. It does not move in a straight line; homes built 2014 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-11-05T14:36:07.083639 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014 8 sales 2015– 2018 4 sales After 2018 6 sales $0 $100 $200 $300 $239 $316 $312 $330 Net price per SF, average

The average is $330 per SF for homes built after 2018 and $239 per SF for homes built before 2014. It does not move in a straight line; homes built after 2018 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-11-05T14:36:07.105932 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014 8 sales 2015– 2018 4 sales After 2018 6 sales 0 2,000 4,000 3,724 3,472 3,204 3,132 Living area (SF), average

The average is 3,132 SF for homes built after 2018 and 3,724 SF for homes built before 2014. It falls step by step from the lowest range to the highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-11-05T14:36:07.127941 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014 8 sales 2015– 2018 4 sales After 2018 6 sales 0 25 50 75 66 68 20 43 Days on market, median

The median is 43 days for homes built after 2018 and 66 days for homes built before 2014. It does not move in a straight line; homes built 2014 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-11-05T14:36:07.152074 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2014 6 sales 2014 8 sales 2015– 2018 4 sales After 2018 6 sales 0.0% 5.0% 10.0% 8.5% 5.4% 3.2% 7.1% Discount from original list, average

The average is 7.1% for homes built after 2018 and 8.5% for homes built before 2014. It does not move in a straight line; homes built before 2014 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-11-05T14:36:07.178595 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% 67 67 83 50 38 88 25 100 100 50 33 67 Before 2014 2014 2015–2018 After 2018

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

  • 50% of homes built after 2018 had a price cut before sale, against 67% of homes built before 2014. Defined in 8.1.7.
  • 33% of homes built after 2018 had the seller pay closing costs or repairs, against 67% of homes built before 2014. Defined in 8.1.8.
  • 67% of homes built after 2018 have a view, against 83% of homes built before 2014. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

5.9 The numbers: price and size

Before 20146 sales20148 sales2015–20184 salesAfter 20186 salesAll24 sales
Net sale price average$883,737$1,095,294$988,888$1,037,333$1,010,180
Net price per SF average$239$316$312$330$300
Living area average3,7243,4723,2043,1323,405
Year built median20122014201720192014

5.10 The numbers: selling

Before 20146 sales20148 sales2015–20184 salesAfter 20186 salesAll24 sales
Days on market median6668204343
Discount from original list average8.5%5.4%3.2%7.1%6.2%
Price cut before sale67%50%25%50%50%
Seller paid closing costs or repairs67%38%100%33%54%
Has a view83%88%100%67%83%

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 · 24 sales · November 5, 2025 – November 4, 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.

2026-11-05T14:36:07.197855 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 20 4 24 sales Sales per group View: 20 sales (83%) No view: 4 sales (17%)
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

2026-11-05T14:36:07.216924 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 20 sales No view 4 sales $0K $500K $1.00M $984K $1.14M Net sale price, average

The average is $984K for homes with a view and $1.14M for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-11-05T14:36:07.235122 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 20 sales No view 4 sales $0 $100 $200 $300 $296 $317 Net price per SF, average

The average is $296 per SF for homes with a view and $317 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-11-05T14:36:07.253649 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 20 sales No view 4 sales 0 1,000 2,000 3,000 4,000 3,366 3,599 Living area (SF), average

The average is 3,366 SF for homes with a view and 3,599 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-11-05T14:36:07.294533 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 20 sales No view 4 sales 2014 2016 2018 2014 2016 Year built: median (dot) and middle half (bar)

The median is 2014 for homes with a view and 2016 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-11-05T14:36:07.312835 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 20 sales No view 4 sales 0 25 50 75 100 32 98 Days on market, median

The median is 32 days for homes with a view and 98 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

2026-11-05T14:36:07.331257 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 20 sales No view 4 sales 0.0% 2.0% 4.0% 6.0% 8.0% 6.0% 7.2% Discount from original list, average

The average is 6.0% for homes with a view and 7.2% 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

2026-11-05T14:36:07.350561 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 45 55 75 50 View No view

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

  • 45% of homes with a view had a price cut before sale, against 75% of homes without a view. Defined in 8.1.7.
  • 55% of homes with a view had the seller pay closing costs or repairs, against 50% 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

View20 salesNo view4 salesAll24 sales
Net sale price average$984,399$1,139,088$1,010,180
Net price per SF average$296$317$300
Living area average3,3663,5993,405
Year built median201420162014

6.11 The numbers: selling

View20 salesNo view4 salesAll24 sales
Days on market median329843
Discount from original list average6.0%7.2%6.2%
Price cut before sale45%75%50%
Seller paid closing costs or repairs55%50%54%

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 · 0 sales · November 5, 2025 – November 4, 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: 0 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 Rim Rock.

No new-construction sales were reported in ABOR MLS in this window.

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
24 resale sales. Average $1,010,180; median $942,500; standard deviation $202,865; middle half (25th–75th percentile) $861,064–$1,165,500; lowest $722,500, highest $1,449,000. 13 sales had a seller payment; their median payment was $3,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
24 resale sales. Average $300; median $291; standard deviation $60; middle half (25th–75th percentile) $250–$340; lowest $206, highest $413.

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
24 resale sales. Average 3,405; median 3,468; standard deviation 437; middle half (25th–75th percentile) 3,244–3,721; lowest 2,368, highest 4,037.

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
24 resale sales. Average 2015; median 2014; standard deviation 3; middle half (25th–75th percentile) 2014–2018; lowest 2009, highest 2024.

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
24 resale sales. Average 60; median 43; standard deviation 61; middle half (25th–75th percentile) 6–94; lowest 1, highest 217. 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
24 resale sales. Average 6.2%; median 5.6%; standard deviation 5.6%; middle half (25th–75th percentile) 2.1%–9.9%; lowest −2.9%, highest 18.3%. 2 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
12 of 24 resale sales (50.0%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
13 of 24 resale sales (54.2%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
20 sales with a view, 4 without, 0 unclassified. Most common View entries: Hill Country 14, Trees/Woods 13, Park/Greenbelt 5, Neighborhood 5, Panoramic 4, None 2, Pool 2, 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
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-05 20:30 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Driftwood, SubdivisionName contains any of “rim rock” (case-insensitive). A record is kept when its subdivision name belongs to the Rim Rock family, the same rule comparable sales use.
The data
Pulled November 5, 2026: 24 closed Rim Rock records over the prior year, in ZIP 78619. 10 subdivision spellings kept: Rim Rock Ph Two Sec Four (5); Rim Rock Ph Three Sec Three (3); Rim Rock Ph 1 Sec 1 (3); Rim Rock Ph Two Sec Three (3); Rim Rock (3); Rim Rock Ph Two Sec Two (3); Rim Rock Ph 01 Sec 03 (1); Rim Rock Ph One Sec Four (1); Rim Rock Ph Two Sec Five (1); Rim Rock Ph One Sec Five (1). Names found by the search but not part of Rim Rock, left out: Rim Rock Ranch Ph 1 Sec 3 (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 12 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 5, 2025 to November 4, 2026 inclusive.
The data
24 single-family sales in the window: 24 resale, 0 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
24 resale; 0 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
None in this window.

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 $865K”.
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 $865K: $722,500–$850,000 (6 sales); $865K–$940K: $864,752–$940,000 (6 sales); $945K–$1.15M: $945,000–$1,147,500 (6 sales); Over $1.15M: $1,219,500–$1,449,000 (6 sales)
Quartiles by living area: Under 3,253 SF: 2,368–3,216 SF (6 sales); 3,253–3,462 SF: 3,253–3,462 SF (6 sales); 3,473–3,719 SF: 3,473–3,719 SF (6 sales); Over 3,719 SF: 3,726–4,037 SF (6 sales)
Quartiles by year built: Before 2014: 2009–2013 (6 sales); 2014: 2014–2014 (8 sales); 2015–2018: 2015–2018 (4 sales); After 2018: 2019–2024 (6 sales)
View and no view: View: MLS lists a view (20 sales); No view: None or Neighborhood (4 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 $1,010,180, median $942,500. Days on market: average 60, median 43: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

In simple terms
Checks whether a measure really differs across the four groups of a slice. It uses each sale's rank, not its value, so a few extreme sales cannot drive the answer.
Statistically
H = [12/(n(n+1))] Σ Rⱼ²/nⱼ − 3(n+1), compared with χ² on k − 1 degrees of freedom (Kruskal & Wallis, 1952). Effect size ε² = H/(n − 1): ≥ .01 small, ≥ .06 medium, ≥ .14 large (Tomczak & Tomczak, 2014). A slice is tested only when every group has at least 5 sales; smaller groups are described, not tested.
The data
Run on every measure in sections 3–5; each result is in 8.3.

8.2.8 Mann–Whitney U test

In simple terms
The same check when there are only two groups: view against no view.
Statistically
Two-sided U test (Mann & Whitney, 1947). Effect size = rank-biserial correlation |1 − 2U/(n₁n₂)|: ≥ .10 small, ≥ .30 medium, ≥ .50 large (Kerby, 2014; Cohen, 1988).
The data
Run on every measure in section 6; results in 8.3.

8.2.9 Chi-square test

In simple terms
Checks whether a yes/no share (price cut, seller payment, view) differs between groups more than chance would.
Statistically
Pearson χ² on the 2 × k table of counts, no continuity correction (Pearson, 1900). Effect size Cramér's V = √(χ²/n): ≥ .10 small, ≥ .30 medium, ≥ .50 large (Cramér, 1946).
The data
Run on the three shares in every slice; results in 8.3.

8.2.10 Real difference (significance)

In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063

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
1 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 = 15.5830.0014p < 0.0063Yesε² = 0.677large
Living areaKruskal–WallisH = 3.8530.2785p < 0.0063Unclearε² = 0.167large
Year builtKruskal–WallisH = 3.9830.2636p < 0.0063Unclearε² = 0.173large
Days on marketKruskal–WallisH = 3.6730.2992p < 0.0063Unclearε² = 0.160large
Discount from original listKruskal–WallisH = 4.7530.1908p < 0.0063Unclearε² = 0.207large
Price cut before saleChi-squareχ² = 1.3330.7212p < 0.0063UnclearCramér’s V = 0.236small
Seller paid closing costs or repairsChi-squareχ² = 7.2230.0653p < 0.0063UnclearCramér’s V = 0.548large
Has a viewChi-squareχ² = 2.4030.4936p < 0.0063UnclearCramér’s V = 0.316medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 2.5930.4587p < 0.0063Unclearε² = 0.113medium
Net price per SFKruskal–WallisH = 5.7330.1257p < 0.0063Unclearε² = 0.249large
Year builtKruskal–WallisH = 3.9730.2642p < 0.0063Unclearε² = 0.173large
Days on marketKruskal–WallisH = 2.3330.5074p < 0.0063Unclearε² = 0.101medium
Discount from original listKruskal–WallisH = 8.6630.0342p < 0.0063Unclearε² = 0.377large
Price cut before saleChi-squareχ² = 4.0030.2615p < 0.0063UnclearCramér’s V = 0.408medium
Seller paid closing costs or repairsChi-squareχ² = 0.5030.9181p < 0.0063UnclearCramér’s V = 0.145small
Has a viewChi-squareχ² = 2.4030.4936p < 0.0063UnclearCramér’s V = 0.316medium

8.3.3 Quartiles by year built

Too few sales in a group to test.

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); nothing else. 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 24 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 5, 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.