ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Plum Creek

Kyle, TX 78640
Resale homes · closed Nov 1 – Oct 31, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 1, 2026 · 6:53 AM 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
76
single-family resale homes
Median net sale price
$302,100
average $311,899
Median net price per SF
$169
average $168
Median days on market
50 days
average 71 days
1. SummaryResale homes · 76 sales · November 1, 2025 – October 31, 2026

This study looks at the 76 resale homes sold in Plum Creek in the 365 days to October 31, 2026. A full year is used because only 44 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 sold76 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 $275K · 19 sales$275K–$301K · 19 sales$303K–$348K · 19 salesOver $348K · 19 sales
3. Quartiles by net sale priceResale homes · 76 sales · November 1, 2025 – October 31, 2026

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

2026-11-01T06:54:00.453920 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 19 19 19 19 76 sales Sales per group Under $275K: 19 sales (25%) $275K–$301K: 19 sales (25%) $303K–$348K: 19 sales (25%) Over $348K: 19 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 $275K$275K–$301K$303K–$348KOver $348K
Higher-priced homes Over $348K
  • Are much larger.
Lower-priced homes Under $275K
  • 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 $275K$275K–$301K$303K–$348KOver $348KReal difference?
Net price per SF$169 per SF$172 per SF$169 per SF$162 per SFunclear
Living area1,536 SFSmallest1,710 SF1,949 SF2,385 SFLargest✓ large
Year built2008200520062009unclear
Days on market57 days36 days43 days58 daysunclear
Discount from original list9.6%7.0%5.4%3.5%unclear
Price cut before sale68%53%53%37%unclear
Seller paid closing costs or repairs68%68%63%84%unclear
Has a view21%21%26%32%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

2026-11-01T06:54:00.483504 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $275K 19 sales $275K– $301K 19 sales $303K– $348K 19 sales Over $348K 19 sales $0 $100 $200 $169 $172 $169 $162 Net price per SF, average

The average is $162 per SF for homes over $348K and $169 per SF for homes under $275K. It does not move in a straight line; homes $275K–$301K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $348K are about 850 SF (55%) larger than homes under $275K

2026-11-01T06:54:00.506458 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $275K 19 sales $275K– $301K 19 sales $303K– $348K 19 sales Over $348K 19 sales 0 1,000 2,000 1,536 1,710 1,949 2,385 Living area (SF), average

The average is 2,385 SF for homes over $348K and 1,536 SF for homes under $275K. 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

2026-11-01T06:54:00.531530 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $275K 19 sales $275K– $301K 19 sales $303K– $348K 19 sales Over $348K 19 sales 2000 2005 2010 2015 2020 2008 2005 2006 2009 Year built: median (dot) and middle half (bar)

The median is 2009 for homes over $348K and 2008 for homes under $275K. It does not move in a straight line; homes over $348K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-01T06:54:00.555407 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $275K 19 sales $275K– $301K 19 sales $303K– $348K 19 sales Over $348K 19 sales 0 20 40 60 57 36 43 58 Days on market, median

The median is 58 days for homes over $348K and 57 days for homes under $275K. It does not move in a straight line; homes over $348K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-01T06:54:00.578164 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $275K 19 sales $275K– $301K 19 sales $303K– $348K 19 sales Over $348K 19 sales 0.0% 5.0% 10.0% 9.6% 7.0% 5.4% 3.5% Discount from original list, average

The average is 3.5% for homes over $348K and 9.6% for homes under $275K. It falls step by step from the lowest range to the 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

2026-11-01T06:54:00.608557 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% 68 68 21 53 68 21 53 63 26 37 84 32 Under $275K $275K–$301K $303K–$348K Over $348K

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

  • 37% of homes over $348K had a price cut before sale, against 68% of homes under $275K. Defined in 8.1.7.
  • 84% of homes over $348K had the seller pay closing costs or repairs, against 68% of homes under $275K. Defined in 8.1.8.
  • 32% of homes over $348K have a view, against 21% of homes under $275K. 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 $275K19 sales$275K–$301K19 sales$303K–$348K19 salesOver $348K19 salesAll76 salesReal difference?
Net sale price average$250,151$290,763$324,769$381,913$311,899by design
Net price per SF average$169$172$169$162$168unclear
Living area average1,5361,7101,9492,3851,895✓ large
Year built median20082005200620092006unclear

3.10 The numbers: selling

Under $275K19 sales$275K–$301K19 sales$303K–$348K19 salesOver $348K19 salesAll76 salesReal difference?
Days on market median5736435850unclear
Discount from original list average9.6%7.0%5.4%3.5%6.4%unclear
Price cut before sale68%53%53%37%53%unclear
Seller paid closing costs or repairs68%68%63%84%71%unclear
Has a view21%21%26%32%25%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 · 76 sales · November 1, 2025 – October 31, 2026

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

2026-11-01T06:54:00.629400 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 19 19 19 19 76 sales Sales per group Under 1,636 SF: 19 sales (25%) 1,636–1,846 SF: 19 sales (25%) 1,864–2,104 SF: 19 sales (25%) Over 2,104 SF: 19 sales (25%)
Bottom line

4.1 Key differences

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

Under 1,636 SF1,636–1,846 SF1,864–2,104 SFOver 2,104 SF
Larger homes Over 2,104 SF
  • Sell for much more.
  • Sell for less per square foot.
Smaller homes Under 1,636 SF
  • Sell for much less.
  • Sell for more per square foot.

4.2 At a glance

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

Under 1,636 SF1,636–1,846 SF1,864–2,104 SFOver 2,104 SFReal difference?
Net sale price$263KLowest$296K$311K$377KHighest✓ large
Net price per SF$191 per SFHighest$169 per SF$157 per SF$154 per SFLowest✓ large
Year built2005200220122009unclear
Days on market36 days54 days43 days60 daysunclear
Discount from original list6.6%7.4%7.1%4.5%unclear
Price cut before sale53%58%53%47%unclear
Seller paid closing costs or repairs63%68%68%84%unclear
Has a view21%21%21%37%unclear

4.3 Homes over 2,104 SF sell for about $113K (43%) more than homes under 1,636 SF

2026-11-01T06:54:00.650138 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,636 SF 19 sales 1,636– 1,846 SF 19 sales 1,864– 2,104 SF 19 sales Over 2,104 SF 19 sales $0K $200K $400K $263K $296K $311K $377K Net sale price, average

The average is $377K for homes over 2,104 SF and $263K for homes under 1,636 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 2,104 SF sell for about $37 per SF (19%) less than homes under 1,636 SF

2026-11-01T06:54:00.673010 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,636 SF 19 sales 1,636– 1,846 SF 19 sales 1,864– 2,104 SF 19 sales Over 2,104 SF 19 sales $0 $100 $200 $191 $169 $157 $154 Net price per SF, average

The average is $154 per SF for homes over 2,104 SF and $191 per SF for homes under 1,636 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-11-01T06:54:00.697668 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,636 SF 19 sales 1,636– 1,846 SF 19 sales 1,864– 2,104 SF 19 sales Over 2,104 SF 19 sales 2000 2005 2010 2015 2020 2005 2002 2012 2009 Year built: median (dot) and middle half (bar)

The median is 2009 for homes over 2,104 SF and 2005 for homes under 1,636 SF. It does not move in a straight line; homes 1,864–2,104 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-01T06:54:00.721239 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,636 SF 19 sales 1,636– 1,846 SF 19 sales 1,864– 2,104 SF 19 sales Over 2,104 SF 19 sales 0 20 40 60 36 54 43 60 Days on market, median

The median is 60 days for homes over 2,104 SF and 36 days for homes under 1,636 SF. It does not move in a straight line; homes over 2,104 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-01T06:54:00.744026 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,636 SF 19 sales 1,636– 1,846 SF 19 sales 1,864– 2,104 SF 19 sales Over 2,104 SF 19 sales 0.0% 2.5% 5.0% 7.5% 6.6% 7.4% 7.1% 4.5% Discount from original list, average

The average is 4.5% for homes over 2,104 SF and 6.6% for homes under 1,636 SF. It does not move in a straight line; homes 1,636–1,846 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

2026-11-01T06:54:00.770283 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% 53 63 21 58 68 21 53 68 21 47 84 37 Under 1,636 SF 1,636–1,846 SF 1,864–2,104 SF Over 2,104 SF

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

  • 47% of homes over 2,104 SF had a price cut before sale, against 53% of homes under 1,636 SF. Defined in 8.1.7.
  • 84% of homes over 2,104 SF had the seller pay closing costs or repairs, against 63% of homes under 1,636 SF. Defined in 8.1.8.
  • 37% of homes over 2,104 SF have a view, against 21% of homes under 1,636 SF. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

4.9 The numbers: price and size

Under 1,636 SF19 sales1,636–1,846 SF19 sales1,864–2,104 SF19 salesOver 2,104 SF19 salesAll76 salesReal difference?
Net sale price average$263,323$296,418$311,040$376,814$311,899✓ large
Net price per SF average$191$169$157$154$168✓ large
Living area average1,3861,7541,9812,4601,895by design
Year built median20052002201220092006unclear

4.10 The numbers: selling

Under 1,636 SF19 sales1,636–1,846 SF19 sales1,864–2,104 SF19 salesOver 2,104 SF19 salesAll76 salesReal difference?
Days on market median3654436050unclear
Discount from original list average6.6%7.4%7.1%4.5%6.4%unclear
Price cut before sale53%58%53%47%53%unclear
Seller paid closing costs or repairs63%68%68%84%71%unclear
Has a view21%21%21%37%25%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 · 76 sales · November 1, 2025 – October 31, 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.

2026-11-01T06:54:00.792569 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 19 20 18 19 76 sales Sales per group Before 2003: 19 sales (25%) 2003–2006: 20 sales (26%) 2008–2016: 18 sales (24%) After 2016: 19 sales (25%)
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 20032003–20062008–2016After 2016Real difference?
Net sale price$296K$325K$291K$334Kunclear
Net price per SF$175 per SF$166 per SF$165 per SF$165 per SFunclear
Living area1,714 SF2,011 SF1,802 SF2,042 SFunclear
Days on market34 days60 days55 days60 daysunclear
Discount from original list5.7%6.4%8.3%5.2%unclear
Price cut before sale47%50%61%53%unclear
Seller paid closing costs or repairs68%70%72%74%unclear
Has a view21%15%39%26%unclear

5.3 Net sale price: no clear difference

2026-11-01T06:54:00.813382 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 19 sales 2003– 2006 20 sales 2008– 2016 18 sales After 2016 19 sales $0K $200K $400K $296K $325K $291K $334K Net sale price, average

The average is $334K for homes built after 2016 and $296K for homes built before 2003. It does not move in a straight line; homes built after 2016 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-01T06:54:00.837325 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 19 sales 2003– 2006 20 sales 2008– 2016 18 sales After 2016 19 sales $0 $100 $200 $175 $166 $165 $165 Net price per SF, average

The average is $165 per SF for homes built after 2016 and $175 per SF for homes built before 2003. It does not move in a straight line; homes built before 2003 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-01T06:54:00.859022 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 19 sales 2003– 2006 20 sales 2008– 2016 18 sales After 2016 19 sales 0 1,000 2,000 1,714 2,011 1,802 2,042 Living area (SF), average

The average is 2,042 SF for homes built after 2016 and 1,714 SF for homes built before 2003. It does not move in a straight line; homes built after 2016 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-01T06:54:00.880221 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 19 sales 2003– 2006 20 sales 2008– 2016 18 sales After 2016 19 sales 0 20 40 60 34 60 55 60 Days on market, median

The median is 60 days for homes built after 2016 and 34 days for homes built before 2003. It does not move in a straight line; homes built 2003–2006 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-01T06:54:00.904589 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 19 sales 2003– 2006 20 sales 2008– 2016 18 sales After 2016 19 sales 0.0% 2.5% 5.0% 7.5% 5.7% 6.4% 8.3% 5.2% Discount from original list, average

The average is 5.2% for homes built after 2016 and 5.7% for homes built before 2003. It does not move in a straight line; homes built 2008–2016 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

2026-11-01T06:54:00.931446 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% 47 68 21 50 70 15 61 72 39 53 74 26 Before 2003 2003–2006 2008–2016 After 2016

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

  • 53% of homes built after 2016 had a price cut before sale, against 47% of homes built before 2003. Defined in 8.1.7.
  • 74% of homes built after 2016 had the seller pay closing costs or repairs, against 68% of homes built before 2003. Defined in 8.1.8.
  • 26% of homes built after 2016 have a view, against 21% of homes built before 2003. 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 200319 sales2003–200620 sales2008–201618 salesAfter 201619 salesAll76 salesReal difference?
Net sale price average$295,964$325,377$290,895$333,544$311,899unclear
Net price per SF average$175$166$165$165$168unclear
Living area average1,7142,0111,8022,0421,895unclear
Year built median20012005201320212006by design

5.10 The numbers: selling

Before 200319 sales2003–200620 sales2008–201618 salesAfter 201619 salesAll76 salesReal difference?
Days on market median3460556050unclear
Discount from original list average5.7%6.4%8.3%5.2%6.4%unclear
Price cut before sale47%50%61%53%53%unclear
Seller paid closing costs or repairs68%70%72%74%71%unclear
Has a view21%15%39%26%25%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 · 76 sales · November 1, 2025 – October 31, 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.

2026-11-01T06:54:00.950155 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 19 55 74 sales Sales per group View: 19 sales (26%) No view: 55 sales (74%)
Bottom line: no measure differs enough between the groups to rule out chance.

6.1 Key differences

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

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$318K$310Kunclear
Net price per SF$169 per SF$168 per SFunclear
Living area1,921 SF1,876 SFunclear
Year built20142006unclear
Days on market58 days49 daysunclear
Discount from original list7.2%6.2%unclear
Price cut before sale58%53%unclear
Seller paid closing costs or repairs74%69%unclear

6.3 Net sale price: no clear difference

2026-11-01T06:54:00.966247 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 55 sales $0K $100K $200K $300K $318K $310K Net sale price, average

The average is $318K for homes with a view and $310K 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

2026-11-01T06:54:00.985075 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 55 sales $0 $50 $100 $150 $200 $169 $168 Net price per SF, average

The average is $169 per SF for homes with a view and $168 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

2026-11-01T06:54:01.004205 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 55 sales 0 500 1,000 1,500 2,000 1,921 1,876 Living area (SF), average

The average is 1,921 SF for homes with a view and 1,876 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-01T06:54:01.069516 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 55 sales 2004 2008 2012 2016 2014 2006 Year built: median (dot) and middle half (bar)

The median is 2014 for homes with a view and 2006 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-01T06:54:01.088147 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 55 sales 0 20 40 60 58 49 Days on market, median

The median is 58 days for homes with a view and 49 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

2026-11-01T06:54:01.108124 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 55 sales 0.0% 2.0% 4.0% 6.0% 8.0% 7.2% 6.2% Discount from original list, average

The average is 7.2% for homes with a view and 6.2% 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

2026-11-01T06:54:01.127580 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 58 74 53 69 View No view

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

  • 58% of homes with a view had a price cut before sale, against 53% of homes without a view. Defined in 8.1.7.
  • 74% of homes with a view had the seller pay closing costs or repairs, against 69% 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

View19 salesNo view55 salesAll74 salesReal difference?
Net sale price average$318,260$309,759$311,942unclear
Net price per SF average$169$168$169unclear
Living area average1,9211,8761,888unclear
Year built median201420062006unclear

6.11 The numbers: selling

View19 salesNo view55 salesAll74 salesReal difference?
Days on market median584950unclear
Discount from original list average7.2%6.2%6.4%unclear
Price cut before sale58%53%54%unclear
Seller paid closing costs or repairs74%69%70%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 · 89 sales · November 1, 2025 – October 31, 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: 89 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 Plum Creek.
MeasureAverageMedian
Sales89
Net sale price$296,722$300,800
Net price per SF$166$165
Living area (SF)1,8141,879
Days on market6755
Discount from original list10.1%10.4%
Price cut before sale74% of sales
Seller paid closing costs or repairs75% of sales
Year built2025–2026

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
76 resale sales. Average $311,899; median $302,100; standard deviation $53,627; middle half (25th–75th percentile) $274,712–$347,875; lowest $200,000, highest $481,200. 54 sales had a seller payment; their median payment was $3,750.

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
76 resale sales. Average $168; median $169; standard deviation $22; middle half (25th–75th percentile) $153–$179; lowest $119, highest $218.

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
76 resale sales. Average 1,895; median 1,855; standard deviation 432; middle half (25th–75th percentile) 1,634–2,106; lowest 960, highest 3,208.

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
76 resale sales. Average 2010; median 2006; standard deviation 8; middle half (25th–75th percentile) 2003–2017; lowest 1999, 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
76 resale sales. Average 71; median 50; standard deviation 79; middle half (25th–75th percentile) 13–90; lowest 1, highest 416. 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
76 resale sales. Average 6.4%; median 6.2%; standard deviation 5.5%; middle half (25th–75th percentile) 2.1%–8.7%; lowest −1.5%, highest 21.1%. 4 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
40 of 76 resale sales (52.6%).

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
54 of 76 resale sales (71.1%).

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
19 sales with a view, 55 without, 2 unclassified. Most common View entries: Neighborhood 35, None 30, Park/Greenbelt 10, Golf Course 8, Trees/Woods 6, Panoramic 3, See Remarks 2, Hill Country 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 2026-11-01 12:45 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Kyle, SubdivisionName contains any of “plum creek”, “plum creek north” (case-insensitive). A record is kept when its subdivision name belongs to the Plum Creek family, the same rule comparable sales use (it includes Plum Creek North, proven adjacent and priced alike).
The data
Pulled November 1, 2026: 167 closed Plum Creek records over the prior year, in ZIP 78640. 38 subdivision spellings kept, the most common: Plum Creek North (59); Plum Creek (46); Plum Creek Ph 2 Sec 1 (7); Plum Creek Ph I Sec 2j (4); Plum Creek Ph 2 Sec 2 (4); Plum Creek Ph 1 Sec 2-A (3); Plum Creek Ph 1 Sec 2C (3); Plum Creek Ph I Sec 2J (3); Plum Creek Ph I Sec 2-B (2); Plum Creek Ph I Sec 6D (2); Plum Creek Ph I Sec 1-B (2); Plum Creek Ph 1 Sec 1F (2); and 26 more (30 records). Names found by the search but not part of Plum Creek, left out: Silverado At Plum Creek Sec 3A (3); Silverado At Plum Creek Sec 1B (2); SILVERADO AT PLUM CREEK SEC 4 (1); Silverado At Plum Creek Sec 4 (1); 1880 At Plum Creek Condos (1); Silverado At Plum Creek (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 44 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 1, 2025 to October 31, 2026 inclusive.
The data
165 single-family sales in the window: 76 resale, 89 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
76 resale; 89 new construction.

8.2.4 Sales left out

In simple terms
A few records cannot be used as entered and are left out before any analysis.
Statistically
Excluded: PropertySubType other than Single Family Residence; no OriginalListPrice; LivingArea under 400 SF; seller payments above 10% of ClosePrice (treated as entry errors).
The data
2 sale(s) other than single-family homes (condo, townhome and similar)

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 $275K”.
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 $275K: $200,000–$274,600 (19 sales); $275K–$301K: $274,750–$301,000 (19 sales); $303K–$348K: $303,200–$347,500 (19 sales); Over $348K: $349,000–$481,200 (19 sales)
Quartiles by living area: Under 1,636 SF: 960–1,630 SF (19 sales); 1,636–1,846 SF: 1,636–1,846 SF (19 sales); 1,864–2,104 SF: 1,864–2,104 SF (19 sales); Over 2,104 SF: 2,112–3,208 SF (19 sales)
Quartiles by year built: Before 2003: 1999–2002 (19 sales); 2003–2006: 2003–2006 (20 sales); 2008–2016: 2008–2016 (18 sales); After 2016: 2019–2024 (19 sales)
View and no view: View: MLS lists a view (19 sales); No view: None or Neighborhood (55 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 $311,899, median $302,100. Days on market: average 71, median 50: 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 = 2.3230.5094p < 0.0063Unclearε² = 0.031small
Living areaKruskal–WallisH = 42.353< 0.0001p < 0.0063Yesε² = 0.565large
Year builtKruskal–WallisH = 3.3830.3364p < 0.0063Unclearε² = 0.045small
Days on marketKruskal–WallisH = 2.0130.5702p < 0.0063Unclearε² = 0.027small
Discount from original listKruskal–WallisH = 10.3530.0158p < 0.0063Unclearε² = 0.138medium
Price cut before saleChi-squareχ² = 3.8030.2839p < 0.0063UnclearCramér’s V = 0.224small
Seller paid closing costs or repairsChi-squareχ² = 2.3030.5119p < 0.0063UnclearCramér’s V = 0.174small
Has a viewChi-squareχ² = 0.7730.8562p < 0.0063UnclearCramér’s V = 0.101small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 47.193< 0.0001p < 0.0063Yesε² = 0.629large
Net price per SFKruskal–WallisH = 31.823< 0.0001p < 0.0063Yesε² = 0.424large
Year builtKruskal–WallisH = 10.4430.0152p < 0.0063Unclearε² = 0.139medium
Days on marketKruskal–WallisH = 1.4830.6860p < 0.0063Unclearε² = 0.020small
Discount from original listKruskal–WallisH = 2.3530.5030p < 0.0063Unclearε² = 0.031small
Price cut before saleChi-squareχ² = 0.4230.9356p < 0.0063UnclearCramér’s V = 0.075negligible
Seller paid closing costs or repairsChi-squareχ² = 2.3030.5119p < 0.0063UnclearCramér’s V = 0.174small
Has a viewChi-squareχ² = 1.8930.5945p < 0.0063UnclearCramér’s V = 0.158small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 7.3630.0612p < 0.0063Unclearε² = 0.098medium
Net price per SFKruskal–WallisH = 3.4830.3234p < 0.0063Unclearε² = 0.046small
Living areaKruskal–WallisH = 8.1630.0429p < 0.0063Unclearε² = 0.109medium
Days on marketKruskal–WallisH = 1.9230.5890p < 0.0063Unclearε² = 0.026small
Discount from original listKruskal–WallisH = 1.9430.5846p < 0.0063Unclearε² = 0.026small
Price cut before saleChi-squareχ² = 0.7930.8529p < 0.0063UnclearCramér’s V = 0.102small
Seller paid closing costs or repairsChi-squareχ² = 0.1530.9851p < 0.0063UnclearCramér’s V = 0.045negligible
Has a viewChi-squareχ² = 3.0930.3774p < 0.0063UnclearCramér’s V = 0.202small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 566.50—0.5904p < 0.0063Unclearrank-biserial r = 0.084negligible
Net price per SFMann–Whitney UU = 514.00—0.9211p < 0.0063Unclearrank-biserial r = 0.016negligible
Living areaMann–Whitney UU = 586.50—0.4320p < 0.0063Unclearrank-biserial r = 0.122small
Year builtMann–Whitney UU = 615.00—0.2539p < 0.0063Unclearrank-biserial r = 0.177small
Days on marketMann–Whitney UU = 607.00—0.2985p < 0.0063Unclearrank-biserial r = 0.162small
Discount from original listMann–Whitney UU = 571.50—0.5484p < 0.0063Unclearrank-biserial r = 0.094negligible
Price cut before saleChi-squareχ² = 0.1510.6968p < 0.0063UnclearCramér’s V = 0.045negligible
Seller paid closing costs or repairsChi-squareχ² = 0.1410.7057p < 0.0063UnclearCramér’s V = 0.044negligible

8.4 Data notes

Left out of the analysis: 89 new-construction sales (basic statistics only, section 7); 2 sale(s) other than single-family homes (condo, townhome and similar). Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

  1. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Erlbaum.
  2. Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press.
  3. Dunn, O. J. (1961). Multiple comparisons among means. JASA, 56(293), 52–64.
  4. Kerby, D. S. (2014). The simple difference formula: an approach to teaching nonparametric correlation. Comprehensive Psychology, 3, 11.IT.3.1.
  5. Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. JASA, 47(260), 583–621.
  6. Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18(1), 50–60.
  7. Pearson, K. (1900). On the criterion that a given system of deviations… Philosophical Magazine, 50(302), 157–175.
  8. Tomczak, M., & Tomczak, E. (2014). The need to report effect size estimates revisited. Trends in Sport Sciences, 21(1), 19–25.

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 76 closed MLS resale sales; the 89 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 1, 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.