ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Kensington Trails

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 · 5:13 AM CDT
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
21
single-family resale homes
Median net sale price
$262,000
average $268,139
Median net price per SF
$145
average $144
Median days on market
48 days
average 76 days
1. SummaryResale homes · 21 sales · October 26, 2025 – October 25, 2026

This study looks at the 21 resale homes sold in Kensington Trails in the 365 days to October 25, 2026. A full year is used because only 14 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 sold21 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 $230K · 5 sales$230K–$255K · 5 sales$262K–$303K · 6 salesOver $303K · 5 sales
3. Quartiles by net sale priceResale homes · 21 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.

2026-10-26T05:13:13.187460 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 5 6 5 21 sales Sales per group Under $230K: 5 sales (24%) $230K–$255K: 5 sales (24%) $262K–$303K: 6 sales (29%) Over $303K: 5 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 $230K$230K–$255K$262K–$303KOver $303K
Higher-priced homes Over $303K
  • Are much larger.
Lower-priced homes Under $230K
  • 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 $230K$230K–$255K$262K–$303KOver $303KReal difference?
Net price per SF$153 per SF$152 per SF$142 per SF$129 per SFunclear
Living area1,444 SFSmallest1,622 SF2,010 SF2,518 SFLargest✓ large
Year built2008200620122007unclear
Days on market77 days42 days72 days68 daysunclear
Discount from original list8.9%1.9%7.0%3.8%unclear
Price cut before sale60%40%50%40%unclear
Seller paid closing costs or repairs80%60%83%60%unclear
Has a view0%0%17%40%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

2026-10-26T05:13:13.218020 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $230K 5 sales $230K– $255K 5 sales $262K– $303K 6 sales Over $303K 5 sales $0 $50 $100 $150 $153 $152 $142 $129 Net price per SF, average

The average is $129 per SF for homes over $303K and $153 per SF for homes under $230K. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $303K are about 1,070 SF (74%) larger than homes under $230K

2026-10-26T05:13:13.241812 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $230K 5 sales $230K– $255K 5 sales $262K– $303K 6 sales Over $303K 5 sales 0 1,000 2,000 3,000 1,444 1,622 2,010 2,518 Living area (SF), average

The average is 2,518 SF for homes over $303K and 1,444 SF for homes under $230K. 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

2026-10-26T05:13:13.268717 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $230K 5 sales $230K– $255K 5 sales $262K– $303K 6 sales Over $303K 5 sales 2005 2008 2011 2014 2017 2008 2006 2012 2007 Year built: median (dot) and middle half (bar)

The median is 2007 for homes over $303K and 2008 for homes under $230K. It does not move in a straight line; homes $262K–$303K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:13:13.294033 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $230K 5 sales $230K– $255K 5 sales $262K– $303K 6 sales Over $303K 5 sales 0 25 50 75 77 42 72 68 Days on market, median

The median is 68 days for homes over $303K and 77 days for homes under $230K. It does not move in a straight line; homes under $230K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:13:13.317357 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $230K 5 sales $230K– $255K 5 sales $262K– $303K 6 sales Over $303K 5 sales 0.0% 5.0% 10.0% 8.9% 1.9% 7.0% 3.8% Discount from original list, average

The average is 3.8% for homes over $303K and 8.9% for homes under $230K. It does not move in a straight line; homes under $230K 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

2026-10-26T05:13:13.351098 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% 60 80 0 40 60 0 50 83 17 40 60 40 Under $230K $230K–$255K $262K–$303K Over $303K

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

  • 40% of homes over $303K had a price cut before sale, against 60% of homes under $230K. Defined in 8.1.7.
  • 60% of homes over $303K had the seller pay closing costs or repairs, against 80% of homes under $230K. Defined in 8.1.8.
  • 40% of homes over $303K have a view, against 0% of homes under $230K. 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 $230K5 sales$230K–$255K5 sales$262K–$303K6 salesOver $303K5 salesAll21 salesReal difference?
Net sale price average$220,892$243,700$282,882$322,135$268,139by design
Net price per SF average$153$152$142$129$144unclear
Living area average1,4441,6222,0102,5181,904✓ large
Year built median20082006201220072008unclear

3.10 The numbers: selling

Under $230K5 sales$230K–$255K5 sales$262K–$303K6 salesOver $303K5 salesAll21 salesReal difference?
Days on market median7742726848unclear
Discount from original list average8.9%1.9%7.0%3.8%5.5%unclear
Price cut before sale60%40%50%40%48%unclear
Seller paid closing costs or repairs80%60%83%60%71%unclear
Has a view0%0%17%40%14%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 · 21 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.

2026-10-26T05:13:13.374345 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 6 6 5 21 sales Sales per group Under 1,509 SF: 4 sales (19%) 1,509–1,734 SF: 6 sales (29%) 1,774–2,322 SF: 6 sales (29%) Over 2,322 SF: 5 sales (24%)
Bottom line: too few sales to test.

4.1 Key differences

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

4.3 Net sale price: described, not tested

2026-10-26T05:13:13.396157 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,509 SF 4 sales 1,509– 1,734 SF 6 sales 1,774– 2,322 SF 6 sales Over 2,322 SF 5 sales $0K $100K $200K $300K $226K $240K $285K $316K Net sale price, average

The average is $316K for homes over 2,322 SF and $226K for homes under 1,509 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

Not tested: too few sales.

4.4 Net price per SF: described, not tested

2026-10-26T05:13:13.420478 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,509 SF 4 sales 1,509– 1,734 SF 6 sales 1,774– 2,322 SF 6 sales Over 2,322 SF 5 sales $0 $50 $100 $150 $164 $150 $141 $126 Net price per SF, average

The average is $126 per SF for homes over 2,322 SF and $164 per SF for homes under 1,509 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

Not tested: too few sales.

4.5 Year built: described, not tested

2026-10-26T05:13:13.446570 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,509 SF 4 sales 1,509– 1,734 SF 6 sales 1,774– 2,322 SF 6 sales Over 2,322 SF 5 sales 2006 2008 2010 2012 2008 2007 2008 2007 Year built: median (dot) and middle half (bar)

The median is 2007 for homes over 2,322 SF and 2008 for homes under 1,509 SF. It does not move in a straight line; homes under 1,509 SF are highest. Defined in 8.1.4.

Not tested: too few sales.

4.6 Days on market: described, not tested

2026-10-26T05:13:13.471475 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,509 SF 4 sales 1,509– 1,734 SF 6 sales 1,774– 2,322 SF 6 sales Over 2,322 SF 5 sales 0 50 100 150 9 45 134 31 Days on market, median

The median is 31 days for homes over 2,322 SF and 9 days for homes under 1,509 SF. It does not move in a straight line; homes 1,774–2,322 SF are highest. Defined in 8.1.5.

Not tested: too few sales.

4.7 Discount from original list: described, not tested

2026-10-26T05:13:13.495283 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,509 SF 4 sales 1,509– 1,734 SF 6 sales 1,774– 2,322 SF 6 sales Over 2,322 SF 5 sales 0.0% 2.5% 5.0% 7.5% 2.0% 7.4% 6.9% 4.3% Discount from original list, average

The average is 4.3% for homes over 2,322 SF and 2.0% for homes under 1,509 SF. It does not move in a straight line; homes 1,509–1,734 SF are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T05:13:13.523925 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 75 0 50 67 0 67 83 33 40 60 20 Under 1,509 SF 1,509–1,734 SF 1,774–2,322 SF Over 2,322 SF

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

  • 40% of homes over 2,322 SF had a price cut before sale, against 25% of homes under 1,509 SF. Defined in 8.1.7.
  • 60% of homes over 2,322 SF had the seller pay closing costs or repairs, against 75% of homes under 1,509 SF. Defined in 8.1.8.
  • 20% of homes over 2,322 SF have a view, against 0% of homes under 1,509 SF. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

4.9 The numbers: price and size

Under 1,509 SF4 sales1,509–1,734 SF6 sales1,774–2,322 SF6 salesOver 2,322 SF5 salesAll21 sales
Net sale price average$226,225$239,593$285,017$315,674$268,139
Net price per SF average$164$150$141$126$144
Living area average1,3881,6032,0322,5251,904
Year built median20082007200820072008

4.10 The numbers: selling

Under 1,509 SF4 sales1,509–1,734 SF6 sales1,774–2,322 SF6 salesOver 2,322 SF5 salesAll21 sales
Days on market median9451343148
Discount from original list average2.0%7.4%6.9%4.3%5.5%
Price cut before sale25%50%67%40%48%
Seller paid closing costs or repairs75%67%83%60%71%
Has a view0%0%33%20%14%

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 · 21 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.

2026-10-26T05:13:13.545426 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 5 7 4 21 sales Sales per group Before 2006: 5 sales (24%) 2006–2007: 5 sales (24%) 2008–2009: 7 sales (33%) After 2009: 4 sales (19%)
Bottom line: too few sales to test.

5.1 Key differences

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

5.3 Net sale price: described, not tested

2026-10-26T05:13:13.566517 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 5 sales 2006– 2007 5 sales 2008– 2009 7 sales After 2009 4 sales $0K $100K $200K $300K $269K $268K $271K $262K Net sale price, average

The average is $262K for homes built after 2009 and $269K for homes built before 2006. It does not move in a straight line; homes built 2008–2009 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T05:13:13.589745 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 5 sales 2006– 2007 5 sales 2008– 2009 7 sales After 2009 4 sales $0 $50 $100 $150 $134 $146 $145 $152 Net price per SF, average

The average is $152 per SF for homes built after 2009 and $134 per SF for homes built before 2006. It does not move in a straight line; homes built after 2009 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T05:13:13.611913 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 5 sales 2006– 2007 5 sales 2008– 2009 7 sales After 2009 4 sales 0 1,000 2,000 2,061 1,884 1,904 1,732 Living area (SF), average

The average is 1,732 SF for homes built after 2009 and 2,061 SF for homes built before 2006. It does not move in a straight line; homes built before 2006 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T05:13:13.633870 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 5 sales 2006– 2007 5 sales 2008– 2009 7 sales After 2009 4 sales 0 25 50 75 42 48 77 70 Days on market, median

The median is 70 days for homes built after 2009 and 42 days for homes built before 2006. It does not move in a straight line; homes built 2008–2009 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T05:13:13.657276 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 5 sales 2006– 2007 5 sales 2008– 2009 7 sales After 2009 4 sales 0.0% 2.5% 5.0% 7.5% 6.4% 3.2% 5.6% 7.1% Discount from original list, average

The average is 7.1% for homes built after 2009 and 6.4% for homes built before 2006. It does not move in a straight line; homes built after 2009 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T05:13:13.683813 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% 60 80 0 40 40 20 43 86 14 50 75 25 Before 2006 2006–2007 2008–2009 After 2009

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

  • 50% of homes built after 2009 had a price cut before sale, against 60% of homes built before 2006. Defined in 8.1.7.
  • 75% of homes built after 2009 had the seller pay closing costs or repairs, against 80% of homes built before 2006. Defined in 8.1.8.
  • 25% of homes built after 2009 have a view, against 0% of homes built before 2006. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

5.9 The numbers: price and size

Before 20065 sales2006–20075 sales2008–20097 salesAfter 20094 salesAll21 sales
Net sale price average$268,915$268,380$270,922$262,000$268,139
Net price per SF average$134$146$145$152$144
Living area average2,0611,8841,9041,7321,904
Year built median20052006200820162008

5.10 The numbers: selling

Before 20065 sales2006–20075 sales2008–20097 salesAfter 20094 salesAll21 sales
Days on market median4248777048
Discount from original list average6.4%3.2%5.6%7.1%5.5%
Price cut before sale60%40%43%50%48%
Seller paid closing costs or repairs80%40%86%75%71%
Has a view0%20%14%25%14%

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 · 21 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. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T05:13:13.703651 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 17 20 sales Sales per group View: 3 sales (15%) No view: 17 sales (85%)
Bottom line: too few sales to test.

6.1 Key differences

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

6.3 Net sale price: described, not tested

2026-10-26T05:13:13.719599 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 17 sales $0K $100K $200K $300K $310K $262K Net sale price, average

The average is $310K for homes with a view and $262K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T05:13:13.737488 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 17 sales $0 $50 $100 $150 $143 $142 Net price per SF, average

The average is $143 per SF for homes with a view and $142 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T05:13:13.756006 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 17 sales 0 1,000 2,000 2,190 1,886 Living area (SF), average

The average is 2,190 SF for homes with a view and 1,886 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T05:13:13.845891 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 17 sales 2006 2008 2010 2012 2008 2007 Year built: median (dot) and middle half (bar)

The median is 2008 for homes with a view and 2007 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T05:13:13.864931 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 17 sales 0 50 100 116 42 Days on market, median

The median is 116 days for homes with a view and 42 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-26T05:13:13.884437 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 17 sales 0.0% 2.0% 4.0% 6.0% 8.0% 7.9% 5.8% Discount from original list, average

The average is 7.9% for homes with a view and 5.8% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

6.9 How often: price cut before sale, seller paid closing costs or repairs

2026-10-26T05:13:13.904232 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 67 67 47 71 View No view

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

  • 67% of homes with a view had a price cut before sale, against 47% 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 71% of homes without a view. Defined in 8.1.8.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View3 salesNo view17 salesAll20 sales
Net sale price average$310,367$261,931$269,196
Net price per SF average$143$142$142
Living area average2,1901,8861,932
Year built median200820072008

6.11 The numbers: selling

View3 salesNo view17 salesAll20 sales
Days on market median1164258
Discount from original list average7.9%5.8%6.1%
Price cut before sale67%47%50%
Seller paid closing costs or repairs67%71%70%

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 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: 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 Kensington Trails.

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
21 resale sales. Average $268,139; median $262,000; standard deviation $40,287; middle half (25th–75th percentile) $229,500–$303,293; lowest $216,000, highest $335,600. 15 sales had a seller payment; their median payment was $6,000.

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
21 resale sales. Average $144; median $145; standard deviation $16; middle half (25th–75th percentile) $131–$150; lowest $111, highest $183.

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
21 resale sales. Average 1,904; median 1,774; standard deviation 461; middle half (25th–75th percentile) 1,509–2,322; lowest 1,301, highest 2,950.

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
21 resale sales. Average 2008; median 2008; standard deviation 4; middle half (25th–75th percentile) 2006–2009; lowest 2003, highest 2017.

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
21 resale sales. Average 76; median 48; standard deviation 73; middle half (25th–75th percentile) 17–116; lowest 5, highest 249. 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
21 resale sales. Average 5.5%; median 4.7%; standard deviation 5.6%; middle half (25th–75th percentile) 2.5%–7.7%; lowest −7.4%, highest 18.7%. 1 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
10 of 21 resale sales (47.6%).

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
15 of 21 resale sales (71.4%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
3 sales with a view, 17 without, 1 unclassified. Most common View entries: None 14, Neighborhood 4, Creek/Stream 1, Hill Country 1, Trees/Woods 1, Park/Greenbelt 1, See Remarks 1, Water 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 “kensington trails” (case-insensitive). A record is kept when its subdivision name belongs to the Kensington Trails family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 22 closed Kensington Trails records over the prior year, in ZIP 78640. 14 subdivision spellings kept, the most common: Kensington Trails Sec 1 (4); Kensington Trails Sec 4B (3); Kensington Trails Sec 2 (3); Kensington Trails Sec 4A (2); Kensington Trails Sec 5B & 5C (1); KENSINGTON TRAILS (1); Kensington Trails Sec 5D (1); Kensington Trails Sec 6 (1); Kensington Trails Sec 3B (1); KENSINGTON TRAILS SEC 4B (1); Kensington Trails Sec 01 (1); Kensington Trails Sec 4a (1); and 2 more (2 records). No other names were found by the search.

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 14 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
21 single-family sales in the window: 21 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
21 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
1 sale(s) with concessions above 10% of price

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $230K”.
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 $230K: $216,000–$227,560 (5 sales); $230K–$255K: $229,500–$255,000 (5 sales); $262K–$303K: $262,000–$303,293 (6 sales); Over $303K: $309,775–$335,600 (5 sales)
Quartiles by living area: Under 1,509 SF: 1,301–1,464 SF (4 sales); 1,509–1,734 SF: 1,509–1,734 SF (6 sales); 1,774–2,322 SF: 1,774–2,322 SF (6 sales); Over 2,322 SF: 2,356–2,950 SF (5 sales)
Quartiles by year built: Before 2006: 2003–2005 (5 sales); 2006–2007: 2006–2007 (5 sales); 2008–2009: 2008–2009 (7 sales); After 2009: 2010–2017 (4 sales)
View and no view: View: MLS lists a view (3 sales); No view: None or Neighborhood (17 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 $268,139, median $262,000. Days on market: average 76, median 48: 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

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
1 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

In simple terms
Headings and sentences round figures so they read easily; the tables at the end of each section give them in full.
Statistically
Prices in headings round to the nearest $1K; price per SF and days on market to the nearest whole number; living area to the nearest 10 SF; shares and percentage gaps to whole percents.
The data
Days on market is always shown in days.

8.3 Test results

Every test behind every gold box. Statistic, degrees of freedom (df), p-value, the threshold it must beat, and the size of the difference.

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 8.4030.0384p < 0.0063Unclearε² = 0.420large
Living areaKruskal–WallisH = 16.0230.0011p < 0.0063Yesε² = 0.801large
Year builtKruskal–WallisH = 2.8130.4211p < 0.0063Unclearε² = 0.141large
Days on marketKruskal–WallisH = 0.9830.8065p < 0.0063Unclearε² = 0.049small
Discount from original listKruskal–WallisH = 4.1530.2452p < 0.0063Unclearε² = 0.208large
Price cut before saleChi-squareχ² = 0.5530.9070p < 0.0063UnclearCramér’s V = 0.162small
Seller paid closing costs or repairsChi-squareχ² = 1.2430.7442p < 0.0063UnclearCramér’s V = 0.243small
Has a viewChi-squareχ² = 4.3930.2219p < 0.0063UnclearCramér’s V = 0.457medium

8.3.2 Quartiles by living area

Too few sales in a group to test.

8.3.3 Quartiles by year built

Too few sales in a group to test.

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 1 sale(s) with concessions above 10% of price. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

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

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 21 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 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.