ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Paloma Lake

Round Rock, TX 78665
Resale homes · closed Oct 30 – Oct 29, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 30, 2026 · 7:09 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
49
single-family resale homes
Median net sale price
$492,083
average $515,975
Median net price per SF
$188
average $190
Median days on market
41 days
average 70 days
1. SummaryResale homes · 49 sales · October 30, 2025 – October 29, 2026

This study looks at the 49 resale homes sold in Paloma Lake in the 365 days to October 29, 2026. A full year is used because only 30 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 sold49 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 $435K · 12 sales$435K–$490K · 12 sales$492K–$580K · 13 salesOver $580K · 12 sales
3. Quartiles by net sale priceResale homes · 49 sales · October 30, 2025 – October 29, 2026

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

2026-10-30T07:09:22.860377 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 12 13 12 49 sales Sales per group Under $435K: 12 sales (24%) $435K–$490K: 12 sales (24%) $492K–$580K: 13 sales (27%) Over $580K: 12 sales (24%)
Bottom line

3.1 Key differences

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

Under $435K$435K–$490K$492K–$580KOver $580K
Higher-priced homes Over $580K
  • Are much larger.
Lower-priced homes Under $435K
  • 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 $435K$435K–$490K$492K–$580KOver $580KReal difference?
Net price per SF$189 per SF$181 per SF$191 per SF$200 per SFunclear
Living area2,089 SFSmallest2,653 SF2,804 SF3,360 SFLargest✓ large
Year built2014201420142016unclear
Days on market20 days44 days54 days44 daysunclear
Discount from original list7.2%2.9%4.7%5.0%unclear
Price cut before sale33%33%54%67%unclear
Seller paid closing costs or repairs50%58%62%67%unclear
Has a view17%17%8%33%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

2026-10-30T07:09:22.889073 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $435K 12 sales $435K– $490K 12 sales $492K– $580K 13 sales Over $580K 12 sales $0 $100 $200 $189 $181 $191 $200 Net price per SF, average

The average is $200 per SF for homes over $580K and $189 per SF for homes under $435K. It does not move in a straight line; homes over $580K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $580K are about 1,270 SF (61%) larger than homes under $435K

2026-10-30T07:09:22.911608 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $435K 12 sales $435K– $490K 12 sales $492K– $580K 13 sales Over $580K 12 sales 0 2,000 4,000 2,089 2,653 2,804 3,360 Living area (SF), average

The average is 3,360 SF for homes over $580K and 2,089 SF for homes under $435K. 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

2026-10-30T07:09:22.935839 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $435K 12 sales $435K– $490K 12 sales $492K– $580K 13 sales Over $580K 12 sales 2012 2014 2016 2018 2014 2014 2014 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over $580K and 2014 for homes under $435K. It does not move in a straight line; homes over $580K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-30T07:09:22.959081 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $435K 12 sales $435K– $490K 12 sales $492K– $580K 13 sales Over $580K 12 sales 0 20 40 60 20 44 54 44 Days on market, median

The median is 44 days for homes over $580K and 20 days for homes under $435K. It does not move in a straight line; homes $492K–$580K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-30T07:09:22.982181 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $435K 12 sales $435K– $490K 12 sales $492K– $580K 13 sales Over $580K 12 sales 0.0% 2.5% 5.0% 7.5% 7.2% 2.9% 4.7% 5.0% Discount from original list, average

The average is 5.0% for homes over $580K and 7.2% for homes under $435K. It does not move in a straight line; homes under $435K 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

2026-10-30T07:09:23.012923 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 17 33 58 17 54 62 8 67 67 33 Under $435K $435K–$490K $492K–$580K Over $580K

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

  • 67% of homes over $580K had a price cut before sale, against 33% of homes under $435K. Defined in 8.1.7.
  • 67% of homes over $580K had the seller pay closing costs or repairs, against 50% of homes under $435K. Defined in 8.1.8.
  • 33% of homes over $580K have a view, against 17% of homes under $435K. 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 $435K12 sales$435K–$490K12 sales$492K–$580K13 salesOver $580K12 salesAll49 salesReal difference?
Net sale price average$393,899$473,612$528,622$666,713$515,975by design
Net price per SF average$189$181$191$200$190unclear
Living area average2,0892,6532,8043,3602,728✓ large
Year built median20142014201420162015unclear

3.10 The numbers: selling

Under $435K12 sales$435K–$490K12 sales$492K–$580K13 salesOver $580K12 salesAll49 salesReal difference?
Days on market median2044544441unclear
Discount from original list average7.2%2.9%4.7%5.0%5.0%unclear
Price cut before sale33%33%54%67%47%unclear
Seller paid closing costs or repairs50%58%62%67%59%unclear
Has a view17%17%8%33%18%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 · 49 sales · October 30, 2025 – October 29, 2026

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

2026-10-30T07:09:23.033956 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 12 13 12 49 sales Sales per group Under 2,305 SF: 12 sales (24%) 2,305–2,729 SF: 12 sales (24%) 2,741–3,154 SF: 13 sales (27%) Over 3,154 SF: 12 sales (24%)
Bottom line

4.1 Key differences

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

Under 2,305 SF2,305–2,729 SF2,741–3,154 SFOver 3,154 SF
Larger homes Over 3,154 SF
  • Sell for much more.
Smaller homes Under 2,305 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 2,305 SF2,305–2,729 SF2,741–3,154 SFOver 3,154 SFReal difference?
Net sale price$411KLowest$481K$521K$651KHighest✓ large
Net price per SF$201 per SF$194 per SF$178 per SF$189 per SFunclear
Year built2014201720142015unclear
Days on market14 days61 days66 days44 daysunclear
Discount from original list4.9%5.5%4.2%5.3%unclear
Price cut before sale25%42%54%67%unclear
Seller paid closing costs or repairs58%50%62%67%unclear
Has a view8%33%15%17%unclear

4.3 Homes over 3,154 SF sell for about $240K (58%) more than homes under 2,305 SF

2026-10-30T07:09:23.054966 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,305 SF 12 sales 2,305– 2,729 SF 12 sales 2,741– 3,154 SF 13 sales Over 3,154 SF 12 sales $0K $200K $400K $600K $411K $481K $521K $651K Net sale price, average

The average is $651K for homes over 3,154 SF and $411K for homes under 2,305 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

2026-10-30T07:09:23.078555 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,305 SF 12 sales 2,305– 2,729 SF 12 sales 2,741– 3,154 SF 13 sales Over 3,154 SF 12 sales $0 $100 $200 $201 $194 $178 $189 Net price per SF, average

The average is $189 per SF for homes over 3,154 SF and $201 per SF for homes under 2,305 SF. It does not move in a straight line; homes under 2,305 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-30T07:09:23.102622 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,305 SF 12 sales 2,305– 2,729 SF 12 sales 2,741– 3,154 SF 13 sales Over 3,154 SF 12 sales 2012 2014 2016 2018 2014 2017 2014 2015 Year built: median (dot) and middle half (bar)

The median is 2015 for homes over 3,154 SF and 2014 for homes under 2,305 SF. It does not move in a straight line; homes 2,305–2,729 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-30T07:09:23.126092 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,305 SF 12 sales 2,305– 2,729 SF 12 sales 2,741– 3,154 SF 13 sales Over 3,154 SF 12 sales 0 20 40 60 14 61 66 44 Days on market, median

The median is 44 days for homes over 3,154 SF and 14 days for homes under 2,305 SF. It does not move in a straight line; homes 2,741–3,154 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-30T07:09:23.148925 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,305 SF 12 sales 2,305– 2,729 SF 12 sales 2,741– 3,154 SF 13 sales Over 3,154 SF 12 sales 0.0% 2.0% 4.0% 6.0% 4.9% 5.5% 4.2% 5.3% Discount from original list, average

The average is 5.3% for homes over 3,154 SF and 4.9% for homes under 2,305 SF. It does not move in a straight line; homes 2,305–2,729 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

2026-10-30T07:09:23.176908 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% 25 58 8 42 50 33 54 62 15 67 67 17 Under 2,305 SF 2,305–2,729 SF 2,741–3,154 SF Over 3,154 SF

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

  • 67% of homes over 3,154 SF had a price cut before sale, against 25% of homes under 2,305 SF. Defined in 8.1.7.
  • 67% of homes over 3,154 SF had the seller pay closing costs or repairs, against 58% of homes under 2,305 SF. Defined in 8.1.8.
  • 17% of homes over 3,154 SF have a view, against 8% of homes under 2,305 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 2,305 SF12 sales2,305–2,729 SF12 sales2,741–3,154 SF13 salesOver 3,154 SF12 salesAll49 salesReal difference?
Net sale price average$410,857$481,071$520,728$650,848$515,975✓ large
Net price per SF average$201$194$178$189$190unclear
Living area average2,0452,4752,9323,4432,728by design
Year built median20142017201420152015unclear

4.10 The numbers: selling

Under 2,305 SF12 sales2,305–2,729 SF12 sales2,741–3,154 SF13 salesOver 3,154 SF12 salesAll49 salesReal difference?
Days on market median1461664441unclear
Discount from original list average4.9%5.5%4.2%5.3%5.0%unclear
Price cut before sale25%42%54%67%47%unclear
Seller paid closing costs or repairs58%50%62%67%59%unclear
Has a view8%33%15%17%18%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 · 49 sales · October 30, 2025 – October 29, 2026

Sales ranked by year built and cut into four groups, from the oldest to the newest. Homes built in the same year always stay in the same group, so group sizes can differ a little.

2026-10-30T07:09:23.198172 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 9 14 12 49 sales Sales per group Before 2013: 14 sales (29%) 2013–2014: 9 sales (18%) 2015–2017: 14 sales (29%) After 2017: 12 sales (24%)
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 20132013–20142015–2017After 2017Real difference?
Net sale price$475K$483K$555K$543Kunclear
Net price per SF$185 per SF$182 per SF$203 per SF$188 per SFunclear
Living area2,612 SF2,686 SF2,742 SF2,878 SFunclear
Days on market26 days18 days62 days28 daysunclear
Discount from original list3.5%5.1%7.0%4.1%unclear
Price cut before sale29%33%79%42%unclear
Seller paid closing costs or repairs79%56%43%58%unclear
Has a view0%0%29%42%unclear

5.3 Net sale price: no clear difference

2026-10-30T07:09:23.219193 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2013 14 sales 2013– 2014 9 sales 2015– 2017 14 sales After 2017 12 sales $0K $200K $400K $600K $475K $483K $555K $543K Net sale price, average

The average is $543K for homes built after 2017 and $475K for homes built before 2013. It does not move in a straight line; homes built 2015–2017 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-30T07:09:23.242913 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2013 14 sales 2013– 2014 9 sales 2015– 2017 14 sales After 2017 12 sales $0 $100 $200 $185 $182 $203 $188 Net price per SF, average

The average is $188 per SF for homes built after 2017 and $185 per SF for homes built before 2013. It does not move in a straight line; homes built 2015–2017 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-30T07:09:23.265097 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2013 14 sales 2013– 2014 9 sales 2015– 2017 14 sales After 2017 12 sales 0 1,000 2,000 3,000 2,612 2,686 2,742 2,878 Living area (SF), average

The average is 2,878 SF for homes built after 2017 and 2,612 SF for homes built before 2013. It rises 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

2026-10-30T07:09:23.287606 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2013 14 sales 2013– 2014 9 sales 2015– 2017 14 sales After 2017 12 sales 0 20 40 60 26 18 62 28 Days on market, median

The median is 28 days for homes built after 2017 and 26 days for homes built before 2013. It does not move in a straight line; homes built 2015–2017 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-30T07:09:23.311671 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2013 14 sales 2013– 2014 9 sales 2015– 2017 14 sales After 2017 12 sales 0.0% 2.5% 5.0% 7.5% 3.5% 5.1% 7.0% 4.1% Discount from original list, average

The average is 4.1% for homes built after 2017 and 3.5% for homes built before 2013. It does not move in a straight line; homes built 2015–2017 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

2026-10-30T07:09:23.338089 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% 29 79 0 33 56 0 79 43 29 42 58 42 Before 2013 2013–2014 2015–2017 After 2017

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

  • 42% of homes built after 2017 had a price cut before sale, against 29% of homes built before 2013. Defined in 8.1.7.
  • 58% of homes built after 2017 had the seller pay closing costs or repairs, against 79% of homes built before 2013. Defined in 8.1.8.
  • 42% of homes built after 2017 have a view, against 0% of homes built before 2013. 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 201314 sales2013–20149 sales2015–201714 salesAfter 201712 salesAll49 salesReal difference?
Net sale price average$475,297$483,294$554,712$542,750$515,975unclear
Net price per SF average$185$182$203$188$190unclear
Living area average2,6122,6862,7422,8782,728unclear
Year built median20112014201620192015by design

5.10 The numbers: selling

Before 201314 sales2013–20149 sales2015–201714 salesAfter 201712 salesAll49 salesReal difference?
Days on market median2618622841unclear
Discount from original list average3.5%5.1%7.0%4.1%5.0%unclear
Price cut before sale29%33%79%42%47%unclear
Seller paid closing costs or repairs79%56%43%58%59%unclear
Has a view0%0%29%42%18%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 · 49 sales · October 30, 2025 – October 29, 2026

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

2026-10-30T07:09:23.357598 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 38 47 sales Sales per group View: 9 sales (19%) No view: 38 sales (81%)
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
  • Tend to be newer.
Homes without a view no view listed
  • Tend to be older.

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$558K$504Kunclear
Net price per SF$202 per SF$188 per SFunclear
Living area2,757 SF2,713 SFunclear
Year built2018Newest2014Oldest✓ large
Days on market41 days44 daysunclear
Discount from original list4.4%5.3%unclear
Price cut before sale56%45%unclear
Seller paid closing costs or repairs67%58%unclear

6.3 Net sale price: no clear difference

2026-10-30T07:09:23.373816 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 38 sales $0K $200K $400K $600K $558K $504K Net sale price, average

The average is $558K for homes with a view and $504K 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

2026-10-30T07:09:23.392759 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 38 sales $0 $50 $100 $150 $200 $202 $188 Net price per SF, average

The average is $202 per SF for homes with a view and $188 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

2026-10-30T07:09:23.410972 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 38 sales 0 1,000 2,000 3,000 2,757 2,713 Living area (SF), average

The average is 2,757 SF for homes with a view and 2,713 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Homes with a view are about 4 years newer than homes without a view

2026-10-30T07:09:23.457719 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 38 sales 2012 2014 2016 2018 2018 2014 Year built: median (dot) and middle half (bar)

The median is 2018 for homes with a view and 2014 for homes without a view. Defined in 8.1.4.

✓ Real difference · large

6.7 Days on market: no clear difference

2026-10-30T07:09:23.476348 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 38 sales 0 20 40 41 44 Days on market, median

The median is 41 days for homes with a view and 44 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

2026-10-30T07:09:23.495138 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 38 sales 0.0% 2.0% 4.0% 6.0% 4.4% 5.3% Discount from original list, average

The average is 4.4% for homes with a view and 5.3% 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

2026-10-30T07:09:23.514599 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 56 67 45 58 View No view

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

  • 56% of homes with a view had a price cut before sale, against 45% of homes without a view. Defined in 8.1.7.
  • 67% of homes with a view had the seller pay closing costs or repairs, against 58% of homes without a view. Defined in 8.1.8.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance

6.10 The numbers: price and size

View9 salesNo view38 salesAll47 salesReal difference?
Net sale price average$558,185$504,384$514,687unclear
Net price per SF average$202$188$190unclear
Living area average2,7572,7132,722unclear
Year built median201820142015✓ large

6.11 The numbers: selling

View9 salesNo view38 salesAll47 salesReal difference?
Days on market median414442unclear
Discount from original list average4.4%5.3%5.1%unclear
Price cut before sale56%45%47%unclear
Seller paid closing costs or repairs67%58%60%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.4.

7. New constructionBasic statistics · 0 sales · October 30, 2025 – October 29, 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 Paloma Lake.

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
49 resale sales. Average $515,975; median $492,083; standard deviation $103,922; middle half (25th–75th percentile) $435,000–$580,000; lowest $355,000, highest $779,700. 29 sales had a seller payment; their median payment was $2,705.

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
49 resale sales. Average $190; median $188; standard deviation $21; middle half (25th–75th percentile) $178–$200; lowest $147, highest $244.

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
49 resale sales. Average 2,728; median 2,741; standard deviation 543; middle half (25th–75th percentile) 2,305–3,154; lowest 1,766, highest 3,822.

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
49 resale sales. Average 2015; median 2015; standard deviation 3; middle half (25th–75th percentile) 2012–2017; lowest 2009, highest 2019.

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
49 resale sales. Average 70; median 41; standard deviation 81; middle half (25th–75th percentile) 11–87; lowest 0, highest 328. 1 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
49 resale sales. Average 5.0%; median 3.7%; standard deviation 4.8%; middle half (25th–75th percentile) 1.6%–7.8%; lowest −4.5%, highest 19.0%. 3 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
23 of 49 resale sales (46.9%).

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
29 of 49 resale sales (59.2%).

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
9 sales with a view, 38 without, 2 unclassified. Most common View entries: None 30, Neighborhood 11, Park/Greenbelt 5, Trees/Woods 4, See Remarks 2, Lake 2, Pond 1, 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 = Round Rock, SubdivisionName contains any of “paloma lake” (case-insensitive). A record is kept when its subdivision name belongs to the Paloma Lake family, the same rule comparable sales use.
The data
Pulled October 30, 2026: 49 closed Paloma Lake records over the prior year, in ZIP 78665. 16 subdivision spellings kept, the most common: Paloma Lake (30); Paloma Lake Sec 25 (3); Paloma Lake Sec 06 (2); Paloma Lake Sec 4B (2); Paloma Lake Sec 22A (1); Paloma Lake Sec 23B (1); Paloma Lake Sec 24 (1); Paloma Lake Sec 01A (1); Paloma Lake Sec 8 (1); Paloma Lake Sec 01B (1); Paloma Lake Sec 23A (1); Paloma Lake Sec 18 (1); and 4 more (4 records). Names found by the search but not part of Paloma Lake, left out: Paloma Lake Master Community (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 30 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 30, 2025 to October 29, 2026 inclusive.
The data
49 single-family sales in the window: 49 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
49 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 $435K”.
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 $435K: $355,000–$425,000 (12 sales); $435K–$490K: $435,000–$490,300 (12 sales); $492K–$580K: $492,083–$580,000 (13 sales); Over $580K: $605,000–$779,700 (12 sales)
Quartiles by living area: Under 2,305 SF: 1,766–2,285 SF (12 sales); 2,305–2,729 SF: 2,305–2,729 SF (12 sales); 2,741–3,154 SF: 2,741–3,154 SF (13 sales); Over 3,154 SF: 3,179–3,822 SF (12 sales)
Quartiles by year built: Before 2013: 2009–2012 (14 sales); 2013–2014: 2013–2014 (9 sales); 2015–2017: 2015–2017 (14 sales); After 2017: 2018–2019 (12 sales)
View and no view: View: MLS lists a view (9 sales); No view: None or Neighborhood (38 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 $515,975, median $492,083. Days on market: average 70, 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
3 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 = 4.9830.1735p < 0.0063Unclearε² = 0.104medium
Living areaKruskal–WallisH = 33.203< 0.0001p < 0.0063Yesε² = 0.692large
Year builtKruskal–WallisH = 3.9430.2683p < 0.0063Unclearε² = 0.082medium
Days on marketKruskal–WallisH = 1.5230.6782p < 0.0063Unclearε² = 0.032small
Discount from original listKruskal–WallisH = 3.2830.3501p < 0.0063Unclearε² = 0.068medium
Price cut before saleChi-squareχ² = 3.9130.2716p < 0.0063UnclearCramér’s V = 0.282small
Seller paid closing costs or repairsChi-squareχ² = 0.7330.8660p < 0.0063UnclearCramér’s V = 0.122small
Has a viewChi-squareχ² = 2.8330.4191p < 0.0063UnclearCramér’s V = 0.240small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 33.203< 0.0001p < 0.0063Yesε² = 0.692large
Net price per SFKruskal–WallisH = 10.2430.0167p < 0.0063Unclearε² = 0.213large
Year builtKruskal–WallisH = 1.0130.7985p < 0.0063Unclearε² = 0.021small
Days on marketKruskal–WallisH = 5.2930.1515p < 0.0063Unclearε² = 0.110medium
Discount from original listKruskal–WallisH = 0.2630.9666p < 0.0063Unclearε² = 0.006negligible
Price cut before saleChi-squareχ² = 4.5830.2055p < 0.0063UnclearCramér’s V = 0.306medium
Seller paid closing costs or repairsChi-squareχ² = 0.7330.8660p < 0.0063UnclearCramér’s V = 0.122small
Has a viewChi-squareχ² = 2.7030.4405p < 0.0063UnclearCramér’s V = 0.235small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 4.6530.1994p < 0.0063Unclearε² = 0.097medium
Net price per SFKruskal–WallisH = 8.3530.0393p < 0.0063Unclearε² = 0.174large
Living areaKruskal–WallisH = 1.9130.5910p < 0.0063Unclearε² = 0.040small
Days on marketKruskal–WallisH = 4.5730.2063p < 0.0063Unclearε² = 0.095medium
Discount from original listKruskal–WallisH = 6.2130.1017p < 0.0063Unclearε² = 0.129medium
Price cut before saleChi-squareχ² = 8.3230.0398p < 0.0063UnclearCramér’s V = 0.412medium
Seller paid closing costs or repairsChi-squareχ² = 3.7830.2867p < 0.0063UnclearCramér’s V = 0.278small
Has a viewChi-squareχ² = 10.4930.0148p < 0.0063UnclearCramér’s V = 0.463medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 210.00—0.2979p < 0.0063Unclearrank-biserial r = 0.228small
Net price per SFMann–Whitney UU = 227.00—0.1335p < 0.0063Unclearrank-biserial r = 0.327medium
Living areaMann–Whitney UU = 183.00—0.7558p < 0.0063Unclearrank-biserial r = 0.070negligible
Year builtMann–Whitney UU = 286.00—0.0018p < 0.0063Yesrank-biserial r = 0.673large
Days on marketMann–Whitney UU = 175.50—0.9138p < 0.0063Unclearrank-biserial r = 0.026negligible
Discount from original listMann–Whitney UU = 134.00—0.3237p < 0.0063Unclearrank-biserial r = 0.216small
Price cut before saleChi-squareχ² = 0.3410.5586p < 0.0063UnclearCramér’s V = 0.085negligible
Seller paid closing costs or repairsChi-squareχ² = 0.2310.6297p < 0.0063UnclearCramér’s V = 0.070negligible

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 49 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 October 30, 2026. Map data © OpenStreetMap contributors. ALEX Companies · Licensed by the Texas Real Estate Commission · Broker: Alexander Tiffany Southwest, LLC (ALEX Real Estate), #565194-BB · Diane Hart Alexander, Designated Broker, #574877-B.