ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Bell Farms Ph 1A

Manor, TX 78653
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 · 5:30 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
23
single-family resale homes
Median net sale price
$248,000
average $244,871
Median net price per SF
$146
average $148
Median days on market
65 days
average 59 days
1. SummaryResale homes · 23 sales · October 26, 2025 – October 25, 2026

This study looks at the 23 resale homes sold in Bell Farms Ph 1A in the 365 days to October 25, 2026. A full year is used because only 13 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 sold23 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 $233K · 6 sales$233K–$248K · 6 sales$250K–$260K · 5 salesOver $260K · 6 sales
3. Quartiles by net sale priceResale homes · 23 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.

2026-10-26T05:31:09.765125 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 5 6 23 sales Sales per group Under $233K: 6 sales (26%) $233K–$248K: 6 sales (26%) $250K–$260K: 5 sales (22%) Over $260K: 6 sales (26%)
Bottom line: no measure differs enough between the groups to rule out chance.

3.1 Key differences

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

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 $233K$233K–$248K$250K–$260KOver $260KReal difference?
Net price per SF$150 per SF$153 per SF$142 per SF$145 per SFunclear
Living area1,463 SF1,591 SF1,819 SF1,934 SFunclear
Year built2010201220092008unclear
Days on market58 days26 days65 days77 daysunclear
Discount from original list11.4%6.3%6.9%8.2%unclear
Price cut before sale67%50%60%67%unclear
Seller paid closing costs or repairs67%100%100%100%unclear
Has a view17%0%20%0%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

2026-10-26T05:31:09.796780 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $233K 6 sales $233K– $248K 6 sales $250K– $260K 5 sales Over $260K 6 sales $0 $50 $100 $150 $150 $153 $142 $145 Net price per SF, average

The average is $145 per SF for homes over $260K and $150 per SF for homes under $233K. It does not move in a straight line; homes $233K–$248K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-26T05:31:09.821301 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $233K 6 sales $233K– $248K 6 sales $250K– $260K 5 sales Over $260K 6 sales 0 1,000 2,000 1,463 1,591 1,819 1,934 Living area (SF), average

The average is 1,934 SF for homes over $260K and 1,463 SF for homes under $233K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-26T05:31:09.845985 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $233K 6 sales $233K– $248K 6 sales $250K– $260K 5 sales Over $260K 6 sales 2008 2011 2014 2010 2012 2009 2008 Year built: median (dot) and middle half (bar)

The median is 2008 for homes over $260K and 2010 for homes under $233K. It does not move in a straight line; homes $233K–$248K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:31:09.871886 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $233K 6 sales $233K– $248K 6 sales $250K– $260K 5 sales Over $260K 6 sales 0 25 50 75 58 26 65 77 Days on market, median

The median is 77 days for homes over $260K and 58 days for homes under $233K. It does not move in a straight line; homes over $260K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:31:09.897113 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $233K 6 sales $233K– $248K 6 sales $250K– $260K 5 sales Over $260K 6 sales 0.0% 5.0% 10.0% 11.4% 6.3% 6.9% 8.2% Discount from original list, average

The average is 8.2% for homes over $260K and 11.4% for homes under $233K. It does not move in a straight line; homes under $233K 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

2026-10-26T05:31:09.931097 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 67 67 17 50 100 0 60 100 20 67 100 0 Under $233K $233K–$248K $250K–$260K Over $260K

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

  • 67% of homes over $260K had a price cut before sale, against 67% of homes under $233K. Defined in 8.1.7.
  • 100% of homes over $260K had the seller pay closing costs or repairs, against 67% of homes under $233K. Defined in 8.1.8.
  • 0% of homes over $260K have a view, against 17% of homes under $233K. 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 $233K6 sales$233K–$248K6 sales$250K–$260K5 salesOver $260K6 salesAll23 salesReal difference?
Net sale price average$214,354$240,612$254,624$271,518$244,871by design
Net price per SF average$150$153$142$145$148unclear
Living area average1,4631,5911,8191,9341,697unclear
Year built median20102012200920082009unclear

3.10 The numbers: selling

Under $233K6 sales$233K–$248K6 sales$250K–$260K5 salesOver $260K6 salesAll23 salesReal difference?
Days on market median5826657765unclear
Discount from original list average11.4%6.3%6.9%8.2%8.3%unclear
Price cut before sale67%50%60%67%61%unclear
Seller paid closing costs or repairs67%100%100%100%91%unclear
Has a view17%0%20%0%9%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 · 23 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.

2026-10-26T05:31:09.956187 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 5 6 23 sales Sales per group Under 1,459 SF: 6 sales (26%) 1,459–1,656 SF: 6 sales (26%) 1,666–1,953 SF: 5 sales (22%) Over 1,953 SF: 6 sales (26%)
Bottom line

4.1 Key differences

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

Under 1,459 SF1,459–1,656 SF1,666–1,953 SFOver 1,953 SF
Larger homes Over 1,953 SF
  • Sell for less per square foot.
Smaller homes Under 1,459 SF
  • 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 1,459 SF1,459–1,656 SF1,666–1,953 SFOver 1,953 SFReal difference?
Net sale price$229K$244K$244K$262Kunclear
Net price per SF$173 per SFHighest$154 per SF$135 per SF$126 per SFLowest✓ large
Year built2010201320072006unclear
Days on market60 days69 days50 days50 daysunclear
Discount from original list7.2%10.1%8.5%7.2%unclear
Price cut before sale50%83%60%50%unclear
Seller paid closing costs or repairs83%83%100%100%unclear
Has a view0%0%20%17%unclear

4.3 Net sale price: no clear difference

2026-10-26T05:31:09.980217 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,459 SF 6 sales 1,459– 1,656 SF 6 sales 1,666– 1,953 SF 5 sales Over 1,953 SF 6 sales $0K $100K $200K $300K $229K $244K $244K $262K Net sale price, average

The average is $262K for homes over 1,953 SF and $229K for homes under 1,459 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Homes over 1,953 SF sell for about $47 per SF (27%) less than homes under 1,459 SF

2026-10-26T05:31:10.007623 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,459 SF 6 sales 1,459– 1,656 SF 6 sales 1,666– 1,953 SF 5 sales Over 1,953 SF 6 sales $0 $100 $200 $173 $154 $135 $126 Net price per SF, average

The average is $126 per SF for homes over 1,953 SF and $173 per SF for homes under 1,459 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

2026-10-26T05:31:10.033531 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,459 SF 6 sales 1,459– 1,656 SF 6 sales 1,666– 1,953 SF 5 sales Over 1,953 SF 6 sales 2008 2011 2014 2010 2013 2007 2006 Year built: median (dot) and middle half (bar)

The median is 2006 for homes over 1,953 SF and 2010 for homes under 1,459 SF. It does not move in a straight line; homes 1,459–1,656 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T05:31:10.059976 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,459 SF 6 sales 1,459– 1,656 SF 6 sales 1,666– 1,953 SF 5 sales Over 1,953 SF 6 sales 0 25 50 75 60 69 50 50 Days on market, median

The median is 50 days for homes over 1,953 SF and 60 days for homes under 1,459 SF. It does not move in a straight line; homes 1,459–1,656 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T05:31:10.084327 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,459 SF 6 sales 1,459– 1,656 SF 6 sales 1,666– 1,953 SF 5 sales Over 1,953 SF 6 sales 0.0% 5.0% 10.0% 7.2% 10.1% 8.5% 7.2% Discount from original list, average

The average is 7.2% for homes over 1,953 SF and 7.2% for homes under 1,459 SF. It does not move in a straight line; homes 1,459–1,656 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

2026-10-26T05:31:10.117041 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% 50 83 0 83 83 0 60 100 20 50 100 17 Under 1,459 SF 1,459–1,656 SF 1,666–1,953 SF Over 1,953 SF

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

  • 50% of homes over 1,953 SF had a price cut before sale, against 50% of homes under 1,459 SF. Defined in 8.1.7.
  • 100% of homes over 1,953 SF had the seller pay closing costs or repairs, against 83% of homes under 1,459 SF. Defined in 8.1.8.
  • 17% of homes over 1,953 SF have a view, against 0% of homes under 1,459 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 1,459 SF6 sales1,459–1,656 SF6 sales1,666–1,953 SF5 salesOver 1,953 SF6 salesAll23 salesReal difference?
Net sale price average$229,119$243,562$244,456$262,276$244,871unclear
Net price per SF average$173$154$135$126$148✓ large
Living area average1,3331,5791,8072,0861,697by design
Year built median20102013200720062009unclear

4.10 The numbers: selling

Under 1,459 SF6 sales1,459–1,656 SF6 sales1,666–1,953 SF5 salesOver 1,953 SF6 salesAll23 salesReal difference?
Days on market median6069505065unclear
Discount from original list average7.2%10.1%8.5%7.2%8.3%unclear
Price cut before sale50%83%60%50%61%unclear
Seller paid closing costs or repairs83%83%100%100%91%unclear
Has a view0%0%20%17%9%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 · 23 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.

2026-10-26T05:31:10.141346 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 7 4 6 23 sales Sales per group Before 2007: 6 sales (26%) 2007–2009: 7 sales (30%) 2010–2012: 4 sales (17%) After 2012: 6 sales (26%)
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

2026-10-26T05:31:10.163594 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 6 sales 2007– 2009 7 sales 2010– 2012 4 sales After 2012 6 sales $0K $100K $200K $300K $238K $254K $231K $250K Net sale price, average

The average is $250K for homes built after 2012 and $238K for homes built before 2007. It does not move in a straight line; homes built 2007–2009 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T05:31:10.188889 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 6 sales 2007– 2009 7 sales 2010– 2012 4 sales After 2012 6 sales $0 $50 $100 $150 $133 $144 $150 $165 Net price per SF, average

The average is $165 per SF for homes built after 2012 and $133 per SF for homes built before 2007. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T05:31:10.211773 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 6 sales 2007– 2009 7 sales 2010– 2012 4 sales After 2012 6 sales 0 1,000 2,000 1,872 1,776 1,554 1,525 Living area (SF), average

The average is 1,525 SF for homes built after 2012 and 1,872 SF for homes built before 2007. It falls step by step from the lowest range to the highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T05:31:10.233597 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 6 sales 2007– 2009 7 sales 2010– 2012 4 sales After 2012 6 sales 0 25 50 75 39 65 72 56 Days on market, median

The median is 56 days for homes built after 2012 and 39 days for homes built before 2007. It does not move in a straight line; homes built 2010–2012 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T05:31:10.256562 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 6 sales 2007– 2009 7 sales 2010– 2012 4 sales After 2012 6 sales 0.0% 5.0% 10.0% 10.3% 6.1% 10.0% 7.5% Discount from original list, average

The average is 7.5% for homes built after 2012 and 10.3% for homes built before 2007. It does not move in a straight line; homes built before 2007 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

2026-10-26T05:31:10.282758 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% 50 83 17 57 100 0 75 75 25 67 100 0 Before 2007 2007–2009 2010–2012 After 2012

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

  • 67% of homes built after 2012 had a price cut before sale, against 50% of homes built before 2007. Defined in 8.1.7.
  • 100% of homes built after 2012 had the seller pay closing costs or repairs, against 83% of homes built before 2007. Defined in 8.1.8.
  • 0% of homes built after 2012 have a view, against 17% of homes built before 2007. 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 20076 sales2007–20097 sales2010–20124 salesAfter 20126 salesAll23 sales
Net sale price average$237,745$254,439$231,128$249,995$244,871
Net price per SF average$133$144$150$165$148
Living area average1,8721,7761,5541,5251,697
Year built median20062009201120162009

5.10 The numbers: selling

Before 20076 sales2007–20097 sales2010–20124 salesAfter 20126 salesAll23 sales
Days on market median3965725665
Discount from original list average10.3%6.1%10.0%7.5%8.3%
Price cut before sale50%57%75%67%61%
Seller paid closing costs or repairs83%100%75%100%91%
Has a view17%0%25%0%9%

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 · 23 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.

2026-10-26T05:31:10.302159 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 2 20 22 sales Sales per group View: 2 sales (9%) No view: 20 sales (91%)
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

2026-10-26T05:31:10.318604 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales $0K $100K $200K $240K $245K Net sale price, average

The average is $240K for homes with a view and $245K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T05:31:10.336105 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales $0 $50 $100 $150 $124 $151 Net price per SF, average

The average is $124 per SF for homes with a view and $151 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T05:31:10.355815 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 0 500 1,000 1,500 2,000 1,948 1,657 Living area (SF), average

The average is 1,948 SF for homes with a view and 1,657 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T05:31:10.400403 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 2008 2010 2012 2009 2009 Year built: median (dot) and middle half (bar)

The median is 2009 for homes with a view and 2009 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T05:31:10.418631 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 0 20 40 60 80 42 68 Days on market, median

The median is 42 days for homes with a view and 68 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

2026-10-26T05:31:10.438360 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 0.0% 2.5% 5.0% 7.5% 10.0% 6.8% 8.6% Discount from original list, average

The average is 6.8% for homes with a view and 8.6% 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

2026-10-26T05:31:10.457461 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 50 100 65 90 View No view

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

  • 50% of homes with a view had a price cut before sale, against 65% of homes without a view. Defined in 8.1.7.
  • 100% of homes with a view had the seller pay closing costs or repairs, against 90% 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

View2 salesNo view20 salesAll22 sales
Net sale price average$240,155$245,186$244,728
Net price per SF average$124$151$149
Living area average1,9481,6571,683
Year built median200920092009

6.11 The numbers: selling

View2 salesNo view20 salesAll22 sales
Days on market median426866
Discount from original list average6.8%8.6%8.4%
Price cut before sale50%65%64%
Seller paid closing costs or repairs100%90%91%

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 Bell Farms Ph 1A.

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
23 resale sales. Average $244,871; median $248,000; standard deviation $24,238; middle half (25th–75th percentile) $232,100–$260,508; lowest $194,900, highest $289,020. 21 sales had a seller payment; their median payment was $7,300.

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
23 resale sales. Average $148; median $146; standard deviation $23; middle half (25th–75th percentile) $131–$158; lowest $113, highest $204.

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
23 resale sales. Average 1,697; median 1,656; standard deviation 317; middle half (25th–75th percentile) 1,442–1,972; lowest 1,036, highest 2,420.

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
23 resale sales. Average 2010; median 2009; standard deviation 4; middle half (25th–75th percentile) 2006–2012; lowest 2005, 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
23 resale sales. Average 59; median 65; standard deviation 41; middle half (25th–75th percentile) 24–80; lowest 5, highest 156. 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
23 resale sales. Average 8.3%; median 7.3%; standard deviation 5.5%; middle half (25th–75th percentile) 4.7%–11.2%; lowest −0.2%, highest 20.4%. 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
14 of 23 resale sales (60.9%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
21 of 23 resale sales (91.3%).

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
2 sales with a view, 20 without, 1 unclassified. Most common View entries: None 15, Neighborhood 5, See Remarks 1, Pasture 1, Park/Greenbelt 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 = Manor, SubdivisionName contains any of “bell farms”, “carriage hills”, “bell farms sub” (case-insensitive). A record is kept when its subdivision name belongs to the Bell Farms Ph 1A family, the same rule comparable sales use (it includes Carriage Hills Sec 02, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 24 closed Bell Farms Ph 1A records over the prior year, in ZIP 78653. 13 subdivision spellings kept, the most common: Bell Farms Ph 1A (4); Carriage Hills Sec 02 (4); Bell Farms Ph 2A Amd (3); Carriage Hills Sec 01 (2); Bell Farms Ph 4 (2); Bell Farms Ph 1a (2); Bell Farms Ph 3 (1); Bell Farms Ph 1B (1); Bell Farms (1); CARRIAGE HILLS (1); Carriage Hills Sec 03 (1); Bell Farms Sub Ph 4 (1); and 1 more (1 records). Names found by the search but not part of Bell Farms Ph 1A, left out: BELL FARMS PHS 1-A (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 13 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
23 single-family sales in the window: 23 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
23 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 $233K”.
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 $233K: $194,900–$231,500 (6 sales); $233K–$248K: $232,700–$248,000 (6 sales); $250K–$260K: $250,000–$260,000 (5 sales); Over $260K: $261,015–$289,020 (6 sales)
Quartiles by living area: Under 1,459 SF: 1,036–1,424 SF (6 sales); 1,459–1,656 SF: 1,459–1,656 SF (6 sales); 1,666–1,953 SF: 1,666–1,953 SF (5 sales); Over 1,953 SF: 1,991–2,420 SF (6 sales)
Quartiles by year built: Before 2007: 2005–2006 (6 sales); 2007–2009: 2007–2009 (7 sales); 2010–2012: 2010–2012 (4 sales); After 2012: 2013–2017 (6 sales)
View and no view: View: MLS lists a view (2 sales); No view: None or Neighborhood (20 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 $244,871, median $248,000. Days on market: average 59, median 65: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

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

8.2.8 Mann–Whitney U test

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

8.2.9 Chi-square test

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

8.2.10 Real difference (significance)

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

8.2.11 Size of a difference

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

8.2.12 Rounding in the text

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

8.3 Test results

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

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 1.6930.6381p < 0.0063Unclearε² = 0.077medium
Living areaKruskal–WallisH = 6.8730.0761p < 0.0063Unclearε² = 0.312large
Year builtKruskal–WallisH = 2.0130.5712p < 0.0063Unclearε² = 0.091medium
Days on marketKruskal–WallisH = 2.0830.5566p < 0.0063Unclearε² = 0.094medium
Discount from original listKruskal–WallisH = 1.9430.5847p < 0.0063Unclearε² = 0.088medium
Price cut before saleChi-squareχ² = 0.4730.9258p < 0.0063UnclearCramér’s V = 0.143small
Seller paid closing costs or repairsChi-squareχ² = 6.2130.1020p < 0.0063UnclearCramér’s V = 0.519large
Has a viewChi-squareχ² = 2.4330.4885p < 0.0063UnclearCramér’s V = 0.325medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 5.1630.1606p < 0.0063Unclearε² = 0.234large
Net price per SFKruskal–WallisH = 15.5330.0014p < 0.0063Yesε² = 0.706large
Year builtKruskal–WallisH = 7.7830.0507p < 0.0063Unclearε² = 0.354large
Days on marketKruskal–WallisH = 0.3330.9538p < 0.0063Unclearε² = 0.015small
Discount from original listKruskal–WallisH = 0.8530.8373p < 0.0063Unclearε² = 0.039small
Price cut before saleChi-squareχ² = 1.8730.6003p < 0.0063UnclearCramér’s V = 0.285small
Seller paid closing costs or repairsChi-squareχ² = 2.0130.5708p < 0.0063UnclearCramér’s V = 0.295small
Has a viewChi-squareχ² = 2.4330.4885p < 0.0063UnclearCramér’s V = 0.325medium

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 23 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.