ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Avalon

Pflugerville, TX 78660
Resale homes · closed Nov 7 – Nov 6, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 7, 2026 · 7:08 AM CST
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
57
single-family resale homes
Median net sale price
$460,000
average $489,095
Median net price per SF
$181
average $182
Median days on market
48 days
average 70 days
1. SummaryResale homes · 57 sales · November 7, 2025 – November 6, 2026

This study looks at the 57 resale homes sold in Avalon in the 365 days to November 6, 2026. A full year is used because only 34 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 sold57 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 $410K · 14 sales$410K–$450K · 14 sales$460K–$545K · 15 salesOver $545K · 14 sales
3. Quartiles by net sale priceResale homes · 57 sales · November 7, 2025 – November 6, 2026

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

2026-11-07T07:08:48.285065 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 14 15 14 57 sales Sales per group Under $410K: 14 sales (25%) $410K–$450K: 14 sales (25%) $460K–$545K: 15 sales (26%) Over $545K: 14 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 $410K$410K–$450K$460K–$545KOver $545K
Higher-priced homes Over $545K
  • Are much larger.
  • Tend to be newer.
Lower-priced homes Under $410K
  • Are much smaller.
  • Tend to be older.

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 $410K$410K–$450K$460K–$545KOver $545KReal difference?
Net price per SF$167 per SF$174 per SF$198 per SF$188 per SFunclear
Living area2,305 SFSmallest2,492 SF2,678 SF3,426 SFLargest✓ large
Year built2014Oldest201520162017Newest✓ large
Days on market88 days42 days38 days37 daysunclear
Discount from original list8.5%4.5%6.6%4.0%unclear
Price cut before sale79%43%40%43%unclear
Seller paid closing costs or repairs71%57%73%64%unclear
Has a view29%7%7%43%unclear

How to read this section. Each heading gives the finding. The gold box says whether the gap is real (✓, with its size) or could be chance (–). The section ends with its numbers; the tests are in section 8.3.

3.3 Net price per SF: no clear difference

2026-11-07T07:08:48.314739 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $410K 14 sales $410K– $450K 14 sales $460K– $545K 15 sales Over $545K 14 sales $0 $100 $200 $167 $174 $198 $188 Net price per SF, average

The average is $188 per SF for homes over $545K and $167 per SF for homes under $410K. It does not move in a straight line; homes $460K–$545K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $545K are about 1,120 SF (49%) larger than homes under $410K

2026-11-07T07:08:48.337992 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $410K 14 sales $410K– $450K 14 sales $460K– $545K 15 sales Over $545K 14 sales 0 2,000 4,000 2,305 2,492 2,678 3,426 Living area (SF), average

The average is 3,426 SF for homes over $545K and 2,305 SF for homes under $410K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Homes over $545K are about 2 years newer than homes under $410K

2026-11-07T07:08:48.363048 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $410K 14 sales $410K– $450K 14 sales $460K– $545K 15 sales Over $545K 14 sales 2008 2011 2014 2017 2014 2015 2016 2017 Year built: median (dot) and middle half (bar)

The median is 2017 for homes over $545K and 2014 for homes under $410K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

✓ Real difference · large

3.6 Days on market: no clear difference

2026-11-07T07:08:48.387422 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $410K 14 sales $410K– $450K 14 sales $460K– $545K 15 sales Over $545K 14 sales 0 50 100 88 42 38 37 Days on market, median

The median is 37 days for homes over $545K and 88 days for homes under $410K. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-07T07:08:48.409702 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $410K 14 sales $410K– $450K 14 sales $460K– $545K 15 sales Over $545K 14 sales 0.0% 5.0% 10.0% 8.5% 4.5% 6.6% 4.0% Discount from original list, average

The average is 4.0% for homes over $545K and 8.5% for homes under $410K. It does not move in a straight line; homes under $410K 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

2026-11-07T07:08:48.440157 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% 79 71 29 43 57 7 40 73 7 43 64 43 Under $410K $410K–$450K $460K–$545K Over $545K

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

  • 43% of homes over $545K had a price cut before sale, against 79% of homes under $410K. Defined in 8.1.7.
  • 64% of homes over $545K had the seller pay closing costs or repairs, against 71% of homes under $410K. Defined in 8.1.8.
  • 43% of homes over $545K have a view, against 29% of homes under $410K. 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 $410K14 sales$410K–$450K14 sales$460K–$545K15 salesOver $545K14 salesAll57 salesReal difference?
Net sale price average$375,363$427,924$513,406$637,950$489,095by design
Net price per SF average$167$174$198$188$182unclear
Living area average2,3052,4922,6783,4262,724✓ large
Year built median20142015201620172016✓ large

3.10 The numbers: selling

Under $410K14 sales$410K–$450K14 sales$460K–$545K15 salesOver $545K14 salesAll57 salesReal difference?
Days on market median8842383748unclear
Discount from original list average8.5%4.5%6.6%4.0%5.9%unclear
Price cut before sale79%43%40%43%51%unclear
Seller paid closing costs or repairs71%57%73%64%67%unclear
Has a view29%7%7%43%21%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 · 57 sales · November 7, 2025 – November 6, 2026

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

2026-11-07T07:08:48.461407 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 14 14 15 57 sales Sales per group Under 2,168 SF: 14 sales (25%) 2,168–2,632 SF: 14 sales (25%) 2,695–2,984 SF: 14 sales (25%) Over 2,984 SF: 15 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 2,168 SF2,168–2,632 SF2,695–2,984 SFOver 2,984 SF
Larger homes Over 2,984 SF
  • Sell for much more.
Smaller homes Under 2,168 SF
  • Sell for much less.

4.2 At a glance

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

Under 2,168 SF2,168–2,632 SF2,695–2,984 SFOver 2,984 SFReal difference?
Net sale price$414KLowest$448K$486K$600KHighest✓ large
Net price per SF$204 per SF$184 per SF$170 per SF$171 per SFunclear
Year built2015201620162017unclear
Days on market40 days57 days43 days48 daysunclear
Discount from original list5.5%5.2%8.2%4.8%unclear
Price cut before sale50%57%50%47%unclear
Seller paid closing costs or repairs71%64%50%80%unclear
Has a view7%7%21%47%unclear

4.3 Homes over 2,984 SF sell for about $186K (45%) more than homes under 2,168 SF

2026-11-07T07:08:48.482510 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,168 SF 14 sales 2,168– 2,632 SF 14 sales 2,695– 2,984 SF 14 sales Over 2,984 SF 15 sales $0K $200K $400K $600K $414K $448K $486K $600K Net sale price, average

The average is $600K for homes over 2,984 SF and $414K for homes under 2,168 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-11-07T07:08:48.505903 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,168 SF 14 sales 2,168– 2,632 SF 14 sales 2,695– 2,984 SF 14 sales Over 2,984 SF 15 sales $0 $100 $200 $204 $184 $170 $171 Net price per SF, average

The average is $171 per SF for homes over 2,984 SF and $204 per SF for homes under 2,168 SF. It does not move in a straight line; homes under 2,168 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-07T07:08:48.531130 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,168 SF 14 sales 2,168– 2,632 SF 14 sales 2,695– 2,984 SF 14 sales Over 2,984 SF 15 sales 2010 2012 2014 2016 2018 2015 2016 2016 2017 Year built: median (dot) and middle half (bar)

The median is 2017 for homes over 2,984 SF and 2015 for homes under 2,168 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-07T07:08:48.554886 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,168 SF 14 sales 2,168– 2,632 SF 14 sales 2,695– 2,984 SF 14 sales Over 2,984 SF 15 sales 0 20 40 60 40 57 43 48 Days on market, median

The median is 48 days for homes over 2,984 SF and 40 days for homes under 2,168 SF. It does not move in a straight line; homes 2,168–2,632 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-07T07:08:48.578192 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,168 SF 14 sales 2,168– 2,632 SF 14 sales 2,695– 2,984 SF 14 sales Over 2,984 SF 15 sales 0.0% 2.5% 5.0% 7.5% 5.5% 5.2% 8.2% 4.8% Discount from original list, average

The average is 4.8% for homes over 2,984 SF and 5.5% for homes under 2,168 SF. It does not move in a straight line; homes 2,695–2,984 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-07T07:08:48.607374 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 71 7 57 64 7 50 50 21 47 80 47 Under 2,168 SF 2,168–2,632 SF 2,695–2,984 SF Over 2,984 SF

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

  • 47% of homes over 2,984 SF had a price cut before sale, against 50% of homes under 2,168 SF. Defined in 8.1.7.
  • 80% of homes over 2,984 SF had the seller pay closing costs or repairs, against 71% of homes under 2,168 SF. Defined in 8.1.8.
  • 47% of homes over 2,984 SF have a view, against 7% of homes under 2,168 SF. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

4.9 The numbers: price and size

Under 2,168 SF14 sales2,168–2,632 SF14 sales2,695–2,984 SF14 salesOver 2,984 SF15 salesAll57 salesReal difference?
Net sale price average$413,765$447,942$486,475$600,257$489,095✓ large
Net price per SF average$204$184$170$171$182unclear
Living area average2,0262,4402,8543,5202,724by design
Year built median20152016201620172016unclear

4.10 The numbers: selling

Under 2,168 SF14 sales2,168–2,632 SF14 sales2,695–2,984 SF14 salesOver 2,984 SF15 salesAll57 salesReal difference?
Days on market median4057434848unclear
Discount from original list average5.5%5.2%8.2%4.8%5.9%unclear
Price cut before sale50%57%50%47%51%unclear
Seller paid closing costs or repairs71%64%50%80%67%unclear
Has a view7%7%21%47%21%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 · 57 sales · November 7, 2025 – November 6, 2026

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

2026-11-07T07:08:48.630482 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 12 21 10 57 sales Sales per group Before 2013: 14 sales (25%) 2013–2015: 12 sales (21%) 2016–2017: 21 sales (37%) After 2017: 10 sales (18%)
Bottom line

5.1 Key differences

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

Before 20132013–20152016–2017After 2017
Newer homes After 2017
  • Are much larger.
Older homes Before 2013
  • Are much smaller.

5.2 At a glance

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

Before 20132013–20152016–2017After 2017Real difference?
Net sale price$456K$432K$506K$568Kunclear
Net price per SF$163 per SF$193 per SF$189 per SF$181 per SFunclear
Living area2,848 SF2,265 SFSmallest2,697 SF3,160 SFLargest✓ large
Days on market46 days50 days38 days48 daysunclear
Discount from original list6.6%4.6%5.4%7.5%unclear
Price cut before sale57%67%38%50%unclear
Seller paid closing costs or repairs79%75%52%70%unclear
Has a view36%17%14%20%unclear

5.3 Net sale price: no clear difference

2026-11-07T07:08:48.652991 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2013 14 sales 2013– 2015 12 sales 2016– 2017 21 sales After 2017 10 sales $0K $200K $400K $600K $456K $432K $506K $568K Net sale price, average

The average is $568K for homes built after 2017 and $456K for homes built before 2013. It does not move in a straight line; homes built after 2017 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-07T07:08:48.679067 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2013 14 sales 2013– 2015 12 sales 2016– 2017 21 sales After 2017 10 sales $0 $100 $200 $163 $193 $189 $181 Net price per SF, average

The average is $181 per SF for homes built after 2017 and $163 per SF for homes built before 2013. It does not move in a straight line; homes built 2013–2015 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Homes built after 2017 are about 310 SF (11%) larger than homes built before 2013

2026-11-07T07:08:48.703557 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2013 14 sales 2013– 2015 12 sales 2016– 2017 21 sales After 2017 10 sales 0 1,000 2,000 3,000 2,848 2,265 2,697 3,160 Living area (SF), average

The average is 3,160 SF for homes built after 2017 and 2,848 SF for homes built before 2013. It does not move in a straight line; homes built after 2017 are highest. Defined in 8.1.3.

✓ Real difference · large

5.6 Days on market: no clear difference

2026-11-07T07:08:48.727892 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2013 14 sales 2013– 2015 12 sales 2016– 2017 21 sales After 2017 10 sales 0 20 40 60 46 50 38 48 Days on market, median

The median is 48 days for homes built after 2017 and 46 days for homes built before 2013. It does not move in a straight line; homes built 2013–2015 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-07T07:08:48.756777 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2013 14 sales 2013– 2015 12 sales 2016– 2017 21 sales After 2017 10 sales 0.0% 2.5% 5.0% 7.5% 6.6% 4.6% 5.4% 7.5% Discount from original list, average

The average is 7.5% for homes built after 2017 and 6.6% for homes built before 2013. It does not move in a straight line; homes built after 2017 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-07T07:08:48.787251 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% 57 79 36 67 75 17 38 52 14 50 70 20 Before 2013 2013–2015 2016–2017 After 2017

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

  • 50% of homes built after 2017 had a price cut before sale, against 57% of homes built before 2013. Defined in 8.1.7.
  • 70% of homes built after 2017 had the seller pay closing costs or repairs, against 79% of homes built before 2013. Defined in 8.1.8.
  • 20% of homes built after 2017 have a view, against 36% of homes built before 2013. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

5.9 The numbers: price and size

Before 201314 sales2013–201512 sales2016–201721 salesAfter 201710 salesAll57 salesReal difference?
Net sale price average$455,742$432,042$506,202$568,327$489,095unclear
Net price per SF average$163$193$189$181$182unclear
Living area average2,8482,2652,6973,1602,724✓ large
Year built median20082015201720182016by design

5.10 The numbers: selling

Before 201314 sales2013–201512 sales2016–201721 salesAfter 201710 salesAll57 salesReal difference?
Days on market median4650384848unclear
Discount from original list average6.6%4.6%5.4%7.5%5.9%unclear
Price cut before sale57%67%38%50%51%unclear
Seller paid closing costs or repairs79%75%52%70%67%unclear
Has a view36%17%14%20%21%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 · 57 sales · November 7, 2025 – November 6, 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.

2026-11-07T07:08:48.811029 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 45 57 sales Sales per group View: 12 sales (21%) No view: 45 sales (79%)
Bottom line

6.1 Key differences

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

ViewNo view
Homes with a view MLS lists a view
  • Are much larger.
Homes without a view no view listed
  • Are much smaller.

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$555K$471Kunclear
Net price per SF$172 per SF$185 per SFunclear
Living area3,215 SFLargest2,593 SFSmallest✓ large
Year built20152016unclear
Days on market30 days49 daysunclear
Discount from original list4.1%6.4%unclear
Price cut before sale50%51%unclear
Seller paid closing costs or repairs83%62%unclear

6.3 Net sale price: no clear difference

2026-11-07T07:08:48.829649 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 45 sales $0K $200K $400K $600K $555K $471K Net sale price, average

The average is $555K for homes with a view and $471K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-11-07T07:08:48.852643 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 45 sales $0 $50 $100 $150 $200 $172 $185 Net price per SF, average

The average is $172 per SF for homes with a view and $185 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Homes with a view are about 620 SF (24%) larger than homes without a view

2026-11-07T07:08:48.875109 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 45 sales 0 1,000 2,000 3,000 3,215 2,593 Living area (SF), average

The average is 3,215 SF for homes with a view and 2,593 SF for homes without a view. Defined in 8.1.3.

✓ Real difference · large

6.6 Year built: no clear difference

2026-11-07T07:08:48.954189 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 45 sales 2008 2010 2012 2014 2016 2015 2016 Year built: median (dot) and middle half (bar)

The median is 2015 for homes with a view and 2016 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-07T07:08:48.974858 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 45 sales 0 20 40 30 49 Days on market, median

The median is 30 days for homes with a view and 49 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-11-07T07:08:48.994574 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 45 sales 0.0% 2.0% 4.0% 6.0% 4.1% 6.4% Discount from original list, average

The average is 4.1% for homes with a view and 6.4% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-07T07:08:49.015100 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 50 83 51 62 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 51% of homes without a view. Defined in 8.1.7.
  • 83% of homes with a view had the seller pay closing costs or repairs, against 62% 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

View12 salesNo view45 salesAll57 salesReal difference?
Net sale price average$555,444$471,402$489,095unclear
Net price per SF average$172$185$182unclear
Living area average3,2152,5932,724✓ large
Year built median201520162016unclear

6.11 The numbers: selling

View12 salesNo view45 salesAll57 salesReal difference?
Days on market median304948unclear
Discount from original list average4.1%6.4%5.9%unclear
Price cut before sale50%51%51%unclear
Seller paid closing costs or repairs83%62%67%unclear

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

7. New constructionBasic statistics · 0 sales · November 7, 2025 – November 6, 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 Avalon.

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
57 resale sales. Average $489,095; median $460,000; standard deviation $106,269; middle half (25th–75th percentile) $410,000–$545,000; lowest $332,000, highest $742,200. 38 sales had a seller payment; their median payment was $6,645.

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
57 resale sales. Average $182; median $181; standard deviation $30; middle half (25th–75th percentile) $164–$199; lowest $125, highest $256.

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
57 resale sales. Average 2,724; median 2,695; standard deviation 600; middle half (25th–75th percentile) 2,168–3,016; lowest 1,670, highest 4,072.

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
57 resale sales. Average 2014; median 2016; standard deviation 4; middle half (25th–75th percentile) 2013–2017; lowest 2007, highest 2019.

8.1.5 Days on market

In simple terms
How many days the home was on the market before the buyer's offer was accepted, counting any earlier listing periods (relists). This is the days on market agents and clients quote.
Statistically
CDOM = max(CumulativeDaysOnMarket, DaysOnMarket, PurchaseContractDate − ListingContractDate). The MLS counter can freeze at a price change, so the contract-date gap is a floor. Summarized by the median, because a few homes that sat for months pull an average up.
The data
57 resale sales. Average 70; median 48; standard deviation 79; middle half (25th–75th percentile) 17–92; lowest 3, highest 425. 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
57 resale sales. Average 5.9%; median 5.3%; standard deviation 5.8%; middle half (25th–75th percentile) 1.3%–8.2%; lowest −5.1%, highest 23.3%. 5 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
29 of 57 resale sales (50.9%).

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
38 of 57 resale sales (66.7%).

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
12 sales with a view, 45 without, 0 unclassified. Most common View entries: None 35, Neighborhood 14, Park/Greenbelt 5, Pool 4, City 3, Garden 2, Trees/Woods 1, See Remarks 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-07 13:00 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Pflugerville, SubdivisionName contains any of “avalon” (case-insensitive). A record is kept when its subdivision name belongs to the Avalon family, the same rule comparable sales use.
The data
Pulled November 7, 2026: 57 closed Avalon records over the prior year, in ZIP 78660. 26 subdivision spellings kept, the most common: Avalon (12); Avalon Ph 03 (6); Avalon Ph 14 (3); Avalon Ph 02 (3); Avalon Ph 01 (3); Avalon Ph 12A (3); Avalon Ph 5C (3); Avalon Ph 8a (2); Avalon Ph 5B (2); Avalon Ph 10 (2); Avalon Ph 16A (2); Avalon Ph 5A (2); and 14 more (14 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 34 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 7, 2025 to November 6, 2026 inclusive.
The data
57 single-family sales in the window: 57 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
57 resale; 0 new construction.

8.2.4 Sales left out

In simple terms
A few records cannot be used as entered and are left out before any analysis.
Statistically
Excluded: PropertySubType other than Single Family Residence; no OriginalListPrice; LivingArea under 400 SF; seller payments above 10% of ClosePrice (treated as entry errors).
The data
None in this window.

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $410K”.
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 $410K: $332,000–$405,000 (14 sales); $410K–$450K: $410,000–$450,000 (14 sales); $460K–$545K: $460,000–$545,000 (15 sales); Over $545K: $547,000–$742,200 (14 sales)
Quartiles by living area: Under 2,168 SF: 1,670–2,165 SF (14 sales); 2,168–2,632 SF: 2,168–2,632 SF (14 sales); 2,695–2,984 SF: 2,695–2,984 SF (14 sales); Over 2,984 SF: 3,016–4,072 SF (15 sales)
Quartiles by year built: Before 2013: 2007–2010 (14 sales); 2013–2015: 2013–2015 (12 sales); 2016–2017: 2016–2017 (21 sales); After 2017: 2018–2019 (10 sales)
View and no view: View: MLS lists a view (12 sales); No view: None or Neighborhood (45 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 $489,095, median $460,000. Days on market: average 70, 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; 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
5 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 = 7.7430.0516p < 0.0063Unclearε² = 0.138medium
Living areaKruskal–WallisH = 26.943< 0.0001p < 0.0063Yesε² = 0.481large
Year builtKruskal–WallisH = 14.8730.0019p < 0.0063Yesε² = 0.265large
Days on marketKruskal–WallisH = 6.1330.1056p < 0.0063Unclearε² = 0.109medium
Discount from original listKruskal–WallisH = 4.2130.2401p < 0.0063Unclearε² = 0.075medium
Price cut before saleChi-squareχ² = 5.7330.1257p < 0.0063UnclearCramér’s V = 0.317medium
Seller paid closing costs or repairsChi-squareχ² = 1.0530.7892p < 0.0063UnclearCramér’s V = 0.136small
Has a viewChi-squareχ² = 7.9830.0465p < 0.0063UnclearCramér’s V = 0.374medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 23.823< 0.0001p < 0.0063Yesε² = 0.425large
Net price per SFKruskal–WallisH = 11.0330.0116p < 0.0063Unclearε² = 0.197large
Year builtKruskal–WallisH = 2.7030.4403p < 0.0063Unclearε² = 0.048small
Days on marketKruskal–WallisH = 1.6030.6591p < 0.0063Unclearε² = 0.029small
Discount from original listKruskal–WallisH = 1.5630.6690p < 0.0063Unclearε² = 0.028small
Price cut before saleChi-squareχ² = 0.3330.9533p < 0.0063UnclearCramér’s V = 0.077negligible
Seller paid closing costs or repairsChi-squareχ² = 3.1330.3722p < 0.0063UnclearCramér’s V = 0.234small
Has a viewChi-squareχ² = 9.1830.0270p < 0.0063UnclearCramér’s V = 0.401medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 11.5730.0090p < 0.0063Unclearε² = 0.207large
Net price per SFKruskal–WallisH = 8.0630.0448p < 0.0063Unclearε² = 0.144large
Living areaKruskal–WallisH = 14.5530.0022p < 0.0063Yesε² = 0.260large
Days on marketKruskal–WallisH = 0.2230.9741p < 0.0063Unclearε² = 0.004negligible
Discount from original listKruskal–WallisH = 1.3530.7176p < 0.0063Unclearε² = 0.024small
Price cut before saleChi-squareχ² = 2.7930.4247p < 0.0063UnclearCramér’s V = 0.221small
Seller paid closing costs or repairsChi-squareχ² = 3.2530.3552p < 0.0063UnclearCramér’s V = 0.239small
Has a viewChi-squareχ² = 2.5330.4690p < 0.0063UnclearCramér’s V = 0.211small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 351.00—0.1151p < 0.0063Unclearrank-biserial r = 0.300medium
Net price per SFMann–Whitney UU = 198.00—0.1617p < 0.0063Unclearrank-biserial r = 0.267small
Living areaMann–Whitney UU = 418.50—0.0038p < 0.0063Yesrank-biserial r = 0.550large
Year builtMann–Whitney UU = 224.00—0.3680p < 0.0063Unclearrank-biserial r = 0.170small
Days on marketMann–Whitney UU = 203.50—0.1963p < 0.0063Unclearrank-biserial r = 0.246small
Discount from original listMann–Whitney UU = 225.50—0.3888p < 0.0063Unclearrank-biserial r = 0.165small
Price cut before saleChi-squareχ² = 0.0010.9455p < 0.0063UnclearCramér’s V = 0.009negligible
Seller paid closing costs or repairsChi-squareχ² = 1.9010.1681p < 0.0063UnclearCramér’s V = 0.183small

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); nothing else. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

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

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 57 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 November 7, 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.