ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Plum Creek

Kyle, TX 78640
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 6:53 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
73
single-family resale homes
Median net sale price
$305,000
average $314,457
Median net price per SF
$167
average $167
Median days on market
54 days
average 72 days
1. SummaryResale homes · 73 sales · October 26, 2025 – October 25, 2026

This study looks at the 73 resale homes sold in Plum Creek in the 365 days to October 25, 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 sold73 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 $280K · 18 sales$280K–$303K · 18 sales$305K–$349K · 19 salesOver $349K · 18 sales
3. Quartiles by net sale priceResale homes · 73 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T06:53:56.926673 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 18 18 19 18 73 sales Sales per group Under $280K: 18 sales (25%) $280K–$303K: 18 sales (25%) $305K–$349K: 19 sales (26%) Over $349K: 18 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 $280K$280K–$303K$305K–$349KOver $349K
Higher-priced homes Over $349K
  • Are much larger.
  • Sell closer to their first asking price.
Lower-priced homes Under $280K
  • Are much smaller.
  • Sell further below their first asking price.

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 $280K$280K–$303K$305K–$349KOver $349KReal difference?
Net price per SF$169 per SF$169 per SF$167 per SF$162 per SFunclear
Living area1,552 SFSmallest1,750 SF1,978 SF2,393 SFLargest✓ large
Year built2005200620062010unclear
Days on market62 days38 days54 days59 daysunclear
Discount from original list10.1%Biggest7.0%5.5%3.3%Smallest✓ large
Price cut before sale72%56%58%33%unclear
Seller paid closing costs or repairs67%67%63%83%unclear
Has a view22%17%26%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

2026-10-26T06:53:56.958465 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $280K 18 sales $280K– $303K 18 sales $305K– $349K 19 sales Over $349K 18 sales $0 $100 $200 $169 $169 $167 $162 Net price per SF, average

The average is $162 per SF for homes over $349K and $169 per SF for homes under $280K. It does not move in a straight line; homes $280K–$303K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $349K are about 840 SF (54%) larger than homes under $280K

2026-10-26T06:53:56.983795 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $280K 18 sales $280K– $303K 18 sales $305K– $349K 19 sales Over $349K 18 sales 0 1,000 2,000 1,552 1,750 1,978 2,393 Living area (SF), average

The average is 2,393 SF for homes over $349K and 1,552 SF for homes under $280K. 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

2026-10-26T06:53:57.009839 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $280K 18 sales $280K– $303K 18 sales $305K– $349K 19 sales Over $349K 18 sales 2005 2010 2015 2020 2005 2006 2006 2010 Year built: median (dot) and middle half (bar)

The median is 2010 for homes over $349K and 2005 for homes under $280K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T06:53:57.035306 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $280K 18 sales $280K– $303K 18 sales $305K– $349K 19 sales Over $349K 18 sales 0 20 40 60 62 38 54 59 Days on market, median

The median is 59 days for homes over $349K and 62 days for homes under $280K. It does not move in a straight line; homes under $280K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Homes over $349K sell about 7 percentage points closer to their first asking price than homes under $280K

2026-10-26T06:53:57.058868 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $280K 18 sales $280K– $303K 18 sales $305K– $349K 19 sales Over $349K 18 sales 0.0% 5.0% 10.0% 10.1% 7.0% 5.5% 3.3% Discount from original list, average

The average is 3.3% for homes over $349K and 10.1% for homes under $280K. It falls step by step from the lowest range to the highest. Defined in 8.1.6.

✓ Real difference · large

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

2026-10-26T06:53:57.091769 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% 72 67 22 56 67 17 58 63 26 33 83 33 Under $280K $280K–$303K $305K–$349K Over $349K

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

  • 33% of homes over $349K had a price cut before sale, against 72% of homes under $280K. Defined in 8.1.7.
  • 83% of homes over $349K had the seller pay closing costs or repairs, against 67% of homes under $280K. Defined in 8.1.8.
  • 33% of homes over $349K have a view, against 22% of homes under $280K. 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 $280K18 sales$280K–$303K18 sales$305K–$349K19 salesOver $349K18 salesAll73 salesReal difference?
Net sale price average$253,914$293,031$326,473$383,741$314,457by design
Net price per SF average$169$169$167$162$167unclear
Living area average1,5521,7501,9782,3931,919✓ large
Year built median20052006200620102006unclear

3.10 The numbers: selling

Under $280K18 sales$280K–$303K18 sales$305K–$349K19 salesOver $349K18 salesAll73 salesReal difference?
Days on market median6238545954unclear
Discount from original list average10.1%7.0%5.5%3.3%6.5%✓ large
Price cut before sale72%56%58%33%55%unclear
Seller paid closing costs or repairs67%67%63%83%70%unclear
Has a view22%17%26%33%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 · 73 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T06:53:57.115714 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 17 19 19 18 73 sales Sales per group Under 1,636 SF: 17 sales (23%) 1,636–1,864 SF: 19 sales (26%) 1,897–2,123 SF: 19 sales (26%) Over 2,123 SF: 18 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 SF1,636–1,864 SF1,897–2,123 SFOver 2,123 SF
Larger homes Over 2,123 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 SF1,636–1,864 SF1,897–2,123 SFOver 2,123 SFReal difference?
Net sale price$267KLowest$298K$313K$378KHighest✓ large
Net price per SF$190 per SFHighest$170 per SF$156 per SF$153 per SFLowest✓ large
Year built2005200420112012unclear
Days on market36 days54 days47 days62 daysunclear
Discount from original list6.6%7.3%7.4%4.5%unclear
Price cut before sale53%58%63%44%unclear
Seller paid closing costs or repairs59%63%74%83%unclear
Has a view18%26%21%33%unclear

4.3 Homes over 2,123 SF sell for about $111K (42%) more than homes under 1,636 SF

2026-10-26T06:53:57.139216 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,636 SF 17 sales 1,636– 1,864 SF 19 sales 1,897– 2,123 SF 19 sales Over 2,123 SF 18 sales $0K $200K $400K $267K $298K $313K $378K Net sale price, average

The average is $378K for homes over 2,123 SF and $267K 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 2,123 SF sell for about $36 per SF (19%) less than homes under 1,636 SF

2026-10-26T06:53:57.164736 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,636 SF 17 sales 1,636– 1,864 SF 19 sales 1,897– 2,123 SF 19 sales Over 2,123 SF 18 sales $0 $100 $200 $190 $170 $156 $153 Net price per SF, average

The average is $153 per SF for homes over 2,123 SF and $190 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

2026-10-26T06:53:57.191959 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,636 SF 17 sales 1,636– 1,864 SF 19 sales 1,897– 2,123 SF 19 sales Over 2,123 SF 18 sales 2000 2005 2010 2015 2020 2005 2004 2011 2012 Year built: median (dot) and middle half (bar)

The median is 2012 for homes over 2,123 SF and 2005 for homes under 1,636 SF. It does not move in a straight line; homes over 2,123 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T06:53:57.218290 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,636 SF 17 sales 1,636– 1,864 SF 19 sales 1,897– 2,123 SF 19 sales Over 2,123 SF 18 sales 0 20 40 60 36 54 47 62 Days on market, median

The median is 62 days for homes over 2,123 SF and 36 days for homes under 1,636 SF. It does not move in a straight line; homes over 2,123 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T06:53:57.243267 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,636 SF 17 sales 1,636– 1,864 SF 19 sales 1,897– 2,123 SF 19 sales Over 2,123 SF 18 sales 0.0% 2.5% 5.0% 7.5% 6.6% 7.3% 7.4% 4.5% Discount from original list, average

The average is 4.5% for homes over 2,123 SF and 6.6% for homes under 1,636 SF. It does not move in a straight line; homes 1,897–2,123 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

2026-10-26T06:53:57.273853 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 59 18 58 63 26 63 74 21 44 83 33 Under 1,636 SF 1,636–1,864 SF 1,897–2,123 SF Over 2,123 SF

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

  • 44% of homes over 2,123 SF had a price cut before sale, against 53% of homes under 1,636 SF. Defined in 8.1.7.
  • 83% of homes over 2,123 SF had the seller pay closing costs or repairs, against 59% of homes under 1,636 SF. Defined in 8.1.8.
  • 33% of homes over 2,123 SF have a view, against 18% 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 SF17 sales1,636–1,864 SF19 sales1,897–2,123 SF19 salesOver 2,123 SF18 salesAll73 salesReal difference?
Net sale price average$266,861$298,311$313,157$377,824$314,457✓ large
Net price per SF average$190$170$156$153$167✓ large
Living area average1,4121,7562,0052,4791,919by design
Year built median20052004201120122006unclear

4.10 The numbers: selling

Under 1,636 SF17 sales1,636–1,864 SF19 sales1,897–2,123 SF19 salesOver 2,123 SF18 salesAll73 salesReal difference?
Days on market median3654476254unclear
Discount from original list average6.6%7.3%7.4%4.5%6.5%unclear
Price cut before sale53%58%63%44%55%unclear
Seller paid closing costs or repairs59%63%74%83%70%unclear
Has a view18%26%21%33%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 · 73 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T06:53:57.297748 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 17 21 16 19 73 sales Sales per group Before 2003: 17 sales (23%) 2003–2006: 21 sales (29%) 2008–2016: 16 sales (22%) After 2016: 19 sales (26%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

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

5.2 At a glance

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

Before 20032003–20062008–2016After 2016Real difference?
Net sale price$296K$325K$298K$334Kunclear
Net price per SF$177 per SF$165 per SF$160 per SF$165 per SFunclear
Living area1,696 SF2,016 SF1,882 SF2,042 SFunclear
Days on market41 days62 days55 days60 daysunclear
Discount from original list5.9%6.6%8.5%5.2%unclear
Price cut before sale53%52%62%53%unclear
Seller paid closing costs or repairs65%71%69%74%unclear
Has a view18%19%38%26%unclear

5.3 Net sale price: no clear difference

2026-10-26T06:53:57.320573 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2006 21 sales 2008– 2016 16 sales After 2016 19 sales $0K $200K $400K $296K $325K $298K $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

2026-10-26T06:53:57.346205 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2006 21 sales 2008– 2016 16 sales After 2016 19 sales $0 $100 $200 $177 $165 $160 $165 Net price per SF, average

The average is $165 per SF for homes built after 2016 and $177 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

2026-10-26T06:53:57.369418 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2006 21 sales 2008– 2016 16 sales After 2016 19 sales 0 1,000 2,000 1,696 2,016 1,882 2,042 Living area (SF), average

The average is 2,042 SF for homes built after 2016 and 1,696 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

2026-10-26T06:53:57.393093 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2006 21 sales 2008– 2016 16 sales After 2016 19 sales 0 20 40 60 41 62 55 60 Days on market, median

The median is 60 days for homes built after 2016 and 41 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

2026-10-26T06:53:57.418593 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2003 17 sales 2003– 2006 21 sales 2008– 2016 16 sales After 2016 19 sales 0.0% 5.0% 10.0% 5.9% 6.6% 8.5% 5.2% Discount from original list, average

The average is 5.2% for homes built after 2016 and 5.9% 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

2026-10-26T06:53:57.446881 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 65 18 52 71 19 62 69 38 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 53% 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 65% of homes built before 2003. Defined in 8.1.8.
  • 26% of homes built after 2016 have a view, against 18% 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 200317 sales2003–200621 sales2008–201616 salesAfter 201619 salesAll73 salesReal difference?
Net sale price average$295,837$324,722$298,100$333,544$314,457unclear
Net price per SF average$177$165$160$165$167unclear
Living area average1,6962,0161,8822,0421,919unclear
Year built median20012005201220212006by design

5.10 The numbers: selling

Before 200317 sales2003–200621 sales2008–201616 salesAfter 201619 salesAll73 salesReal difference?
Days on market median4162556054unclear
Discount from original list average5.9%6.6%8.5%5.2%6.5%unclear
Price cut before sale53%52%62%53%55%unclear
Seller paid closing costs or repairs65%71%69%74%70%unclear
Has a view18%19%38%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 · 73 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T06:53:57.468750 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 18 53 71 sales Sales per group View: 18 sales (25%) No view: 53 sales (75%)
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$324K$312Kunclear
Net price per SF$165 per SF$168 per SFunclear
Living area1,986 SF1,886 SFunclear
Year built20132006unclear
Days on market60 days52 daysunclear
Discount from original list7.0%6.3%unclear
Price cut before sale61%55%unclear
Seller paid closing costs or repairs72%68%unclear

6.3 Net sale price: no clear difference

2026-10-26T06:53:57.486286 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 53 sales $0K $100K $200K $300K $324K $312K Net sale price, average

The average is $324K for homes with a view and $312K 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

2026-10-26T06:53:57.506871 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 53 sales $0 $50 $100 $150 $200 $165 $168 Net price per SF, average

The average is $165 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

2026-10-26T06:53:57.528916 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 53 sales 0 500 1,000 1,500 2,000 1,986 1,886 Living area (SF), average

The average is 1,986 SF for homes with a view and 1,886 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T06:53:57.633240 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 53 sales 2004 2008 2012 2016 2013 2006 Year built: median (dot) and middle half (bar)

The median is 2013 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

2026-10-26T06:53:57.652385 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 53 sales 0 20 40 60 60 52 Days on market, median

The median is 60 days for homes with a view and 52 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

2026-10-26T06:53:57.673715 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 18 sales No view 53 sales 0.0% 2.0% 4.0% 6.0% 8.0% 7.0% 6.3% Discount from original list, average

The average is 7.0% for homes with a view and 6.3% 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

2026-10-26T06:53:57.695153 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 61 72 55 68 View No view

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

  • 61% of homes with a view had a price cut before sale, against 55% of homes without a view. Defined in 8.1.7.
  • 72% of homes with a view had the seller pay closing costs or repairs, against 68% 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

View18 salesNo view53 salesAll71 salesReal difference?
Net sale price average$323,576$311,516$314,573unclear
Net price per SF average$165$168$168unclear
Living area average1,9861,8861,912unclear
Year built median201320062006unclear

6.11 The numbers: selling

View18 salesNo view53 salesAll71 salesReal difference?
Days on market median605254unclear
Discount from original list average7.0%6.3%6.5%unclear
Price cut before sale61%55%56%unclear
Seller paid closing costs or repairs72%68%69%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 · 91 sales · October 26, 2025 – October 25, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 91 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
Sales91
Net sale price$296,391$300,800
Net price per SF$166$166
Living area (SF)1,8081,879
Days on market6653
Discount from original list10.1%10.4%
Price cut before sale73% of sales
Seller paid closing costs or repairs76% 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
73 resale sales. Average $314,457; median $305,000; standard deviation $52,661; middle half (25th–75th percentile) $280,000–$349,000; lowest $200,000, highest $481,200. 51 sales had a seller payment; their median payment was $4,000.

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
73 resale sales. Average $167; median $167; standard deviation $22; middle half (25th–75th percentile) $151–$177; lowest $119, highest $212.

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
73 resale sales. Average 1,919; median 1,897; standard deviation 423; middle half (25th–75th percentile) 1,636–2,123; lowest 1,137, 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
73 resale sales. Average 2010; median 2006; standard deviation 8; middle half (25th–75th percentile) 2003–2019; 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
73 resale sales. Average 72; median 54; standard deviation 78; middle half (25th–75th percentile) 16–90; 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
73 resale sales. Average 6.5%; median 6.3%; standard deviation 5.5%; middle half (25th–75th percentile) 2.4%–9.4%; 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 73 resale sales (54.8%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
51 of 73 resale sales (69.9%).

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
18 sales with a view, 53 without, 2 unclassified. Most common View entries: Neighborhood 32, None 29, Park/Greenbelt 10, Golf Course 8, Trees/Woods 5, 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
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. 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 October 26, 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 I Sec 2J (3); Plum Creek Ph 1 Sec 2C (3); PLUM CREEK (2); Plum Creek Ph I Sec 1-B (2); Plum Creek Ph 1 Sec 2c (2); Plum Creek Ph 1 Sec 1F (2); Plum Creek Ph 1 Sec 6H-2 (2); and 26 more (31 records). Names found by the search but not part of Plum Creek, left out: Silverado At Plum Creek Sec 3A (4); Silverado At Plum Creek Sec 1B (2); Silverado At Plum Creek (1); 1880 At Plum Creek Condos (1); Silverado At Plum Creek Sec 4 (1); SILVERADO AT PLUM CREEK SEC 4 (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 October 26, 2025 to October 25, 2026 inclusive.
The data
164 single-family sales in the window: 73 resale, 91 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
73 resale; 91 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
3 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 $280K”.
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 $280K: $200,000–$278,390 (18 sales); $280K–$303K: $280,000–$303,200 (18 sales); $305K–$349K: $305,000–$349,000 (19 sales); Over $349K: $350,000–$481,200 (18 sales)
Quartiles by living area: Under 1,636 SF: 1,137–1,630 SF (17 sales); 1,636–1,864 SF: 1,636–1,864 SF (19 sales); 1,897–2,123 SF: 1,897–2,123 SF (19 sales); Over 2,123 SF: 2,156–3,208 SF (18 sales)
Quartiles by year built: Before 2003: 1999–2002 (17 sales); 2003–2006: 2003–2006 (21 sales); 2008–2016: 2008–2016 (16 sales); After 2016: 2019–2024 (19 sales)
View and no view: View: MLS lists a view (18 sales); No view: None or Neighborhood (53 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 $314,457, median $305,000. Days on market: average 72, median 54: 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
4 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 = 1.2930.7322p < 0.0063Unclearε² = 0.018small
Living areaKruskal–WallisH = 40.483< 0.0001p < 0.0063Yesε² = 0.562large
Year builtKruskal–WallisH = 3.3830.3362p < 0.0063Unclearε² = 0.047small
Days on marketKruskal–WallisH = 1.7930.6179p < 0.0063Unclearε² = 0.025small
Discount from original listKruskal–WallisH = 12.6130.0056p < 0.0063Yesε² = 0.175large
Price cut before saleChi-squareχ² = 5.6330.1310p < 0.0063UnclearCramér’s V = 0.278small
Seller paid closing costs or repairsChi-squareχ² = 2.1330.5455p < 0.0063UnclearCramér’s V = 0.171small
Has a viewChi-squareχ² = 1.4330.6977p < 0.0063UnclearCramér’s V = 0.140small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 43.223< 0.0001p < 0.0063Yesε² = 0.600large
Net price per SFKruskal–WallisH = 30.433< 0.0001p < 0.0063Yesε² = 0.423large
Year builtKruskal–WallisH = 10.9730.0119p < 0.0063Unclearε² = 0.152large
Days on marketKruskal–WallisH = 0.9330.8178p < 0.0063Unclearε² = 0.013small
Discount from original listKruskal–WallisH = 2.0730.5588p < 0.0063Unclearε² = 0.029small
Price cut before saleChi-squareχ² = 1.4130.7027p < 0.0063UnclearCramér’s V = 0.139small
Seller paid closing costs or repairsChi-squareχ² = 3.0730.3805p < 0.0063UnclearCramér’s V = 0.205small
Has a viewChi-squareχ² = 1.3430.7196p < 0.0063UnclearCramér’s V = 0.135small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 5.7430.1252p < 0.0063Unclearε² = 0.080medium
Net price per SFKruskal–WallisH = 6.2630.0996p < 0.0063Unclearε² = 0.087medium
Living areaKruskal–WallisH = 8.8830.0309p < 0.0063Unclearε² = 0.123medium
Days on marketKruskal–WallisH = 1.0430.7910p < 0.0063Unclearε² = 0.014small
Discount from original listKruskal–WallisH = 2.0530.5628p < 0.0063Unclearε² = 0.028small
Price cut before saleChi-squareχ² = 0.4930.9206p < 0.0063UnclearCramér’s V = 0.082negligible
Seller paid closing costs or repairsChi-squareχ² = 0.3830.9443p < 0.0063UnclearCramér’s V = 0.072negligible
Has a viewChi-squareχ² = 2.2530.5214p < 0.0063UnclearCramér’s V = 0.176small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 532.50—0.4672p < 0.0063Unclearrank-biserial r = 0.116small
Net price per SFMann–Whitney UU = 423.00—0.4795p < 0.0063Unclearrank-biserial r = 0.113small
Living areaMann–Whitney UU = 571.50—0.2140p < 0.0063Unclearrank-biserial r = 0.198small
Year builtMann–Whitney UU = 576.00—0.1918p < 0.0063Unclearrank-biserial r = 0.208small
Days on marketMann–Whitney UU = 546.50—0.3617p < 0.0063Unclearrank-biserial r = 0.146small
Discount from original listMann–Whitney UU = 502.50—0.7411p < 0.0063Unclearrank-biserial r = 0.053negligible
Price cut before saleChi-squareχ² = 0.2210.6365p < 0.0063UnclearCramér’s V = 0.056negligible
Seller paid closing costs or repairsChi-squareχ² = 0.1210.7334p < 0.0063UnclearCramér’s V = 0.040negligible

8.4 Data notes

Left out of the analysis: 91 new-construction sales (basic statistics only, section 7); 3 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 73 closed MLS resale sales; the 91 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 26, 2026. Map data © OpenStreetMap contributors. ALEX Companies · Licensed by the Texas Real Estate Commission · Broker: Alexander Tiffany Southwest, LLC (ALEX Real Estate), #565194-BB · Diane Hart Alexander, Designated Broker, #574877-B.