ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Avalon

Pflugerville, TX 78660
Resale homes · closed Oct 28 – Oct 27, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 28, 2026 · 7:04 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
61
single-family resale homes
Median net sale price
$460,000
average $487,501
Median net price per SF
$181
average $182
Median days on market
49 days
average 79 days
1. SummaryResale homes · 61 sales · October 28, 2025 – October 27, 2026

This study looks at the 61 resale homes sold in Avalon in the 365 days to October 27, 2026. A full year is used because only 35 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 sold61 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 · 15 sales$410K–$450K · 15 sales$460K–$540K · 16 salesOver $540K · 15 sales
3. Quartiles by net sale priceResale homes · 61 sales · October 28, 2025 – October 27, 2026

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

2026-10-28T07:04:29.322822 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 15 15 16 15 61 sales Sales per group Under $410K: 15 sales (25%) $410K–$450K: 15 sales (25%) $460K–$540K: 16 sales (26%) Over $540K: 15 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–$540KOver $540K
Higher-priced homes Over $540K
  • 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–$540KOver $540KReal difference?
Net price per SF$169 per SF$174 per SF$196 per SF$188 per SFunclear
Living area2,274 SFSmallest2,497 SF2,708 SF3,392 SFLargest✓ large
Year built2014Oldest201520162017Newest✓ large
Days on market92 days48 days49 days45 daysunclear
Discount from original list8.8%5.6%6.8%4.1%unclear
Price cut before sale80%47%44%40%unclear
Seller paid closing costs or repairs73%53%75%67%unclear
Has a view27%7%6%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

2026-10-28T07:04:29.352813 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $410K 15 sales $410K– $450K 15 sales $460K– $540K 16 sales Over $540K 15 sales $0 $100 $200 $169 $174 $196 $188 Net price per SF, average

The average is $188 per SF for homes over $540K and $169 per SF for homes under $410K. It does not move in a straight line; homes $460K–$540K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $540K are about 1,120 SF (49%) larger than homes under $410K

2026-10-28T07:04:29.375930 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $410K 15 sales $410K– $450K 15 sales $460K– $540K 16 sales Over $540K 15 sales 0 2,000 4,000 2,274 2,497 2,708 3,392 Living area (SF), average

The average is 3,392 SF for homes over $540K and 2,274 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 $540K are about 3 years newer than homes under $410K

2026-10-28T07:04:29.401450 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $410K 15 sales $410K– $450K 15 sales $460K– $540K 16 sales Over $540K 15 sales 2008 2011 2014 2017 2014 2015 2016 2017 Year built: median (dot) and middle half (bar)

The median is 2017 for homes over $540K 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

2026-10-28T07:04:29.426004 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $410K 15 sales $410K– $450K 15 sales $460K– $540K 16 sales Over $540K 15 sales 0 50 100 92 48 49 45 Days on market, median

The median is 45 days for homes over $540K and 92 days for homes under $410K. It does not move in a straight line; homes under $410K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-28T07:04:29.448683 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $410K 15 sales $410K– $450K 15 sales $460K– $540K 16 sales Over $540K 15 sales 0.0% 5.0% 10.0% 8.8% 5.6% 6.8% 4.1% Discount from original list, average

The average is 4.1% for homes over $540K and 8.8% 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

2026-10-28T07:04:29.480522 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% 80 73 27 47 53 7 44 75 6 40 67 40 Under $410K $410K–$450K $460K–$540K Over $540K

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

  • 40% of homes over $540K had a price cut before sale, against 80% of homes under $410K. Defined in 8.1.7.
  • 67% of homes over $540K had the seller pay closing costs or repairs, against 73% of homes under $410K. Defined in 8.1.8.
  • 40% of homes over $540K have a view, against 27% 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 $410K15 sales$410K–$450K15 sales$460K–$540K16 salesOver $540K15 salesAll61 salesReal difference?
Net sale price average$374,339$429,396$512,826$631,753$487,501by design
Net price per SF average$169$174$196$188$182unclear
Living area average2,2742,4972,7083,3922,718✓ large
Year built median20142015201620172016✓ large

3.10 The numbers: selling

Under $410K15 sales$410K–$450K15 sales$460K–$540K16 salesOver $540K15 salesAll61 salesReal difference?
Days on market median9248494549unclear
Discount from original list average8.8%5.6%6.8%4.1%6.3%unclear
Price cut before sale80%47%44%40%52%unclear
Seller paid closing costs or repairs73%53%75%67%67%unclear
Has a view27%7%6%40%20%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 · 61 sales · October 28, 2025 – October 27, 2026

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

2026-10-28T07:04:29.502510 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 15 15 15 16 61 sales Sales per group Under 2,168 SF: 15 sales (25%) 2,168–2,632 SF: 15 sales (25%) 2,695–2,984 SF: 15 sales (25%) Over 2,984 SF: 16 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$410KLowest$448K$489K$595KHighest✓ large
Net price per SF$204 per SF$184 per SF$172 per SF$170 per SFunclear
Year built2015201520162016unclear
Days on market49 days60 days47 days50 daysunclear
Discount from original list6.0%6.2%8.4%4.7%unclear
Price cut before sale53%60%53%44%unclear
Seller paid closing costs or repairs73%60%53%81%unclear
Has a view7%7%20%44%unclear

4.3 Homes over 2,984 SF sell for about $185K (45%) more than homes under 2,168 SF

2026-10-28T07:04:29.524040 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,168 SF 15 sales 2,168– 2,632 SF 15 sales 2,695– 2,984 SF 15 sales Over 2,984 SF 16 sales $0K $200K $400K $600K $410K $448K $489K $595K Net sale price, average

The average is $595K for homes over 2,984 SF and $410K 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

2026-10-28T07:04:29.547749 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,168 SF 15 sales 2,168– 2,632 SF 15 sales 2,695– 2,984 SF 15 sales Over 2,984 SF 16 sales $0 $100 $200 $204 $184 $172 $170 Net price per SF, average

The average is $170 per SF for homes over 2,984 SF and $204 per SF for homes under 2,168 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-28T07:04:29.572872 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,168 SF 15 sales 2,168– 2,632 SF 15 sales 2,695– 2,984 SF 15 sales Over 2,984 SF 16 sales 2010 2012 2014 2016 2018 2015 2015 2016 2016 Year built: median (dot) and middle half (bar)

The median is 2016 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

2026-10-28T07:04:29.596635 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,168 SF 15 sales 2,168– 2,632 SF 15 sales 2,695– 2,984 SF 15 sales Over 2,984 SF 16 sales 0 20 40 60 49 60 47 50 Days on market, median

The median is 50 days for homes over 2,984 SF and 49 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

2026-10-28T07:04:29.619861 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,168 SF 15 sales 2,168– 2,632 SF 15 sales 2,695– 2,984 SF 15 sales Over 2,984 SF 16 sales 0.0% 5.0% 10.0% 6.0% 6.2% 8.4% 4.7% Discount from original list, average

The average is 4.7% for homes over 2,984 SF and 6.0% 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

2026-10-28T07:04:29.647521 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 53 73 7 60 60 7 53 53 20 44 81 44 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.

  • 44% of homes over 2,984 SF had a price cut before sale, against 53% of homes under 2,168 SF. Defined in 8.1.7.
  • 81% of homes over 2,984 SF had the seller pay closing costs or repairs, against 73% of homes under 2,168 SF. Defined in 8.1.8.
  • 44% 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 SF15 sales2,168–2,632 SF15 sales2,695–2,984 SF15 salesOver 2,984 SF16 salesAll61 salesReal difference?
Net sale price average$410,181$448,079$489,152$595,397$487,501✓ large
Net price per SF average$204$184$172$170$182unclear
Living area average2,0132,4492,8443,5112,718by design
Year built median20152015201620162016unclear

4.10 The numbers: selling

Under 2,168 SF15 sales2,168–2,632 SF15 sales2,695–2,984 SF15 salesOver 2,984 SF16 salesAll61 salesReal difference?
Days on market median4960475049unclear
Discount from original list average6.0%6.2%8.4%4.7%6.3%unclear
Price cut before sale53%60%53%44%52%unclear
Seller paid closing costs or repairs73%60%53%81%67%unclear
Has a view7%7%20%44%20%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 · 61 sales · October 28, 2025 – October 27, 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.

2026-10-28T07:04:29.669116 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 15 14 21 11 61 sales Sales per group Before 2012: 15 sales (25%) 2012–2015: 14 sales (23%) 2016–2017: 21 sales (34%) After 2017: 11 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 20122012–20152016–2017After 2017
Newer homes After 2017
  • Are much larger.
  • Sell for much more.
Older homes Before 2012
  • Are much smaller.
  • Sell for much less.

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 20122012–20152016–2017After 2017Real difference?
Net sale price$460K$428KLowest$506K$565KHighest✓ large
Net price per SF$162 per SF$192 per SF$189 per SF$182 per SFunclear
Living area2,883 SF2,256 SFSmallest2,697 SF3,119 SFLargest✓ large
Days on market48 days56 days38 days48 daysunclear
Discount from original list6.3%6.4%5.4%7.8%unclear
Price cut before sale53%71%38%55%unclear
Seller paid closing costs or repairs80%71%52%73%unclear
Has a view33%14%14%18%unclear

5.3 Homes built after 2017 sell for about $104K (23%) more than homes built before 2012

2026-10-28T07:04:29.691095 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2012 15 sales 2012– 2015 14 sales 2016– 2017 21 sales After 2017 11 sales $0K $200K $400K $600K $460K $428K $506K $565K Net sale price, average

The average is $565K for homes built after 2017 and $460K for homes built before 2012. It does not move in a straight line; homes built after 2017 are highest. Defined in 8.1.1.

✓ Real difference · large

5.4 Net price per SF: no clear difference

2026-10-28T07:04:29.715538 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2012 15 sales 2012– 2015 14 sales 2016– 2017 21 sales After 2017 11 sales $0 $100 $200 $162 $192 $189 $182 Net price per SF, average

The average is $182 per SF for homes built after 2017 and $162 per SF for homes built before 2012. It does not move in a straight line; homes built 2012–2015 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Homes built after 2017 are about 240 SF (8%) larger than homes built before 2012

2026-10-28T07:04:29.737680 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2012 15 sales 2012– 2015 14 sales 2016– 2017 21 sales After 2017 11 sales 0 1,000 2,000 3,000 2,883 2,256 2,697 3,119 Living area (SF), average

The average is 3,119 SF for homes built after 2017 and 2,883 SF for homes built before 2012. 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

2026-10-28T07:04:29.760278 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2012 15 sales 2012– 2015 14 sales 2016– 2017 21 sales After 2017 11 sales 0 20 40 60 48 56 38 48 Days on market, median

The median is 48 days for homes built after 2017 and 48 days for homes built before 2012. It does not move in a straight line; homes built 2012–2015 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-28T07:04:29.784414 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2012 15 sales 2012– 2015 14 sales 2016– 2017 21 sales After 2017 11 sales 0.0% 2.5% 5.0% 7.5% 6.3% 6.4% 5.4% 7.8% Discount from original list, average

The average is 7.8% for homes built after 2017 and 6.3% for homes built before 2012. 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

2026-10-28T07:04:29.811160 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 53 80 33 71 71 14 38 52 14 55 73 18 Before 2012 2012–2015 2016–2017 After 2017

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

  • 55% of homes built after 2017 had a price cut before sale, against 53% of homes built before 2012. Defined in 8.1.7.
  • 73% of homes built after 2017 had the seller pay closing costs or repairs, against 80% of homes built before 2012. Defined in 8.1.8.
  • 18% of homes built after 2017 have a view, against 33% of homes built before 2012. 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 201215 sales2012–201514 sales2016–201721 salesAfter 201711 salesAll61 salesReal difference?
Net sale price average$460,192$428,179$506,202$564,536$487,501✓ large
Net price per SF average$162$192$189$182$182unclear
Living area average2,8832,2562,6973,1192,718✓ large
Year built median20082015201720182016by design

5.10 The numbers: selling

Before 201215 sales2012–201514 sales2016–201721 salesAfter 201711 salesAll61 salesReal difference?
Days on market median4856384849unclear
Discount from original list average6.3%6.4%5.4%7.8%6.3%unclear
Price cut before sale53%71%38%55%52%unclear
Seller paid closing costs or repairs80%71%52%73%67%unclear
Has a view33%14%14%18%20%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 · 61 sales · October 28, 2025 – October 27, 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.

2026-10-28T07:04:29.831546 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 49 61 sales Sales per group View: 12 sales (20%) No view: 49 sales (80%)
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$184 per SFunclear
Living area3,215 SFLargest2,596 SFSmallest✓ large
Year built20152016unclear
Days on market30 days54 daysunclear
Discount from original list4.1%6.9%unclear
Price cut before sale50%53%unclear
Seller paid closing costs or repairs83%63%unclear

6.3 Net sale price: no clear difference

2026-10-28T07:04:29.848165 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 49 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

2026-10-28T07:04:29.867367 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 49 sales $0 $50 $100 $150 $200 $172 $184 Net price per SF, average

The average is $172 per SF for homes with a view and $184 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

2026-10-28T07:04:29.887081 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 49 sales 0 1,000 2,000 3,000 3,215 2,596 Living area (SF), average

The average is 3,215 SF for homes with a view and 2,596 SF for homes without a view. Defined in 8.1.3.

✓ Real difference · large

6.6 Year built: no clear difference

2026-10-28T07:04:29.985293 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 49 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

2026-10-28T07:04:30.004335 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 49 sales 0 20 40 60 30 54 Days on market, median

The median is 30 days for homes with a view and 54 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-10-28T07:04:30.024531 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 12 sales No view 49 sales 0.0% 2.0% 4.0% 6.0% 8.0% 4.1% 6.9% Discount from original list, average

The average is 4.1% for homes with a view and 6.9% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-28T07:04:30.044627 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 50 83 53 63 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 53% 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 63% 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 view49 salesAll61 salesReal difference?
Net sale price average$555,444$470,861$487,501unclear
Net price per SF average$172$184$182unclear
Living area average3,2152,5962,718✓ large
Year built median201520162016unclear

6.11 The numbers: selling

View12 salesNo view49 salesAll61 salesReal difference?
Days on market median305449unclear
Discount from original list average4.1%6.9%6.3%unclear
Price cut before sale50%53%52%unclear
Seller paid closing costs or repairs83%63%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 · October 28, 2025 – October 27, 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
61 resale sales. Average $487,501; median $460,000; standard deviation $104,321; middle half (25th–75th percentile) $410,000–$540,000; lowest $332,000, highest $742,200. 41 sales had a seller payment; their median payment was $6,500.

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
61 resale sales. Average $182; median $181; standard deviation $29; middle half (25th–75th percentile) $164–$198; 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
61 resale sales. Average 2,718; median 2,695; standard deviation 598; 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
61 resale sales. Average 2014; median 2016; standard deviation 4; middle half (25th–75th percentile) 2012–2017; 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
61 resale sales. Average 79; median 49; standard deviation 93; middle half (25th–75th percentile) 17–98; lowest 3, highest 477. 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
61 resale sales. Average 6.3%; median 5.6%; standard deviation 6.1%; middle half (25th–75th percentile) 1.3%–8.4%; 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
32 of 61 resale sales (52.5%).

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
41 of 61 resale sales (67.2%).

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, 49 without, 0 unclassified. Most common View entries: None 38, Neighborhood 15, Park/Greenbelt 5, Pool 4, City 3, Garden 2, Trees/Woods 1, Golf Course 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 = 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 October 28, 2026: 61 closed Avalon records over the prior year, in ZIP 78660. 27 subdivision spellings kept, the most common: Avalon (14); Avalon Ph 03 (6); Avalon Ph 02 (4); Avalon Ph 14 (3); Avalon Ph 5C (3); Avalon Ph 01 (3); Avalon Ph 12A (3); Avalon Ph 8a (2); Avalon Ph 16A (2); Avalon Ph 5A (2); Avalon Ph 10 (2); Avalon Ph 5B (2); and 15 more (15 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 35 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 28, 2025 to October 27, 2026 inclusive.
The data
61 single-family sales in the window: 61 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
61 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 (15 sales); $410K–$450K: $410,000–$450,000 (15 sales); $460K–$540K: $460,000–$540,000 (16 sales); Over $540K: $545,000–$742,200 (15 sales)
Quartiles by living area: Under 2,168 SF: 1,670–2,165 SF (15 sales); 2,168–2,632 SF: 2,168–2,632 SF (15 sales); 2,695–2,984 SF: 2,695–2,984 SF (15 sales); Over 2,984 SF: 3,016–4,072 SF (16 sales)
Quartiles by year built: Before 2012: 2007–2010 (15 sales); 2012–2015: 2012–2015 (14 sales); 2016–2017: 2016–2017 (21 sales); After 2017: 2018–2019 (11 sales)
View and no view: View: MLS lists a view (12 sales); No view: None or Neighborhood (49 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 $487,501, median $460,000. Days on market: average 79, median 49: 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
6 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 = 6.5130.0892p < 0.0063Unclearε² = 0.109medium
Living areaKruskal–WallisH = 28.753< 0.0001p < 0.0063Yesε² = 0.479large
Year builtKruskal–WallisH = 16.4330.0009p < 0.0063Yesε² = 0.274large
Days on marketKruskal–WallisH = 5.9930.1122p < 0.0063Unclearε² = 0.100medium
Discount from original listKruskal–WallisH = 4.7330.1928p < 0.0063Unclearε² = 0.079medium
Price cut before saleChi-squareχ² = 6.1830.1030p < 0.0063UnclearCramér’s V = 0.318medium
Seller paid closing costs or repairsChi-squareχ² = 2.0130.5706p < 0.0063UnclearCramér’s V = 0.181small
Has a viewChi-squareχ² = 7.8230.0500p < 0.0063UnclearCramér’s V = 0.358medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 26.333< 0.0001p < 0.0063Yesε² = 0.439large
Net price per SFKruskal–WallisH = 12.2730.0065p < 0.0063Unclearε² = 0.205large
Year builtKruskal–WallisH = 3.1230.3741p < 0.0063Unclearε² = 0.052small
Days on marketKruskal–WallisH = 1.6030.6603p < 0.0063Unclearε² = 0.027small
Discount from original listKruskal–WallisH = 2.2930.5149p < 0.0063Unclearε² = 0.038small
Price cut before saleChi-squareχ² = 0.8430.8404p < 0.0063UnclearCramér’s V = 0.117small
Seller paid closing costs or repairsChi-squareχ² = 3.3530.3406p < 0.0063UnclearCramér’s V = 0.234small
Has a viewChi-squareχ² = 9.0830.0282p < 0.0063UnclearCramér’s V = 0.386medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 12.9630.0047p < 0.0063Yesε² = 0.216large
Net price per SFKruskal–WallisH = 9.4030.0244p < 0.0063Unclearε² = 0.157large
Living areaKruskal–WallisH = 16.3030.0010p < 0.0063Yesε² = 0.272large
Days on marketKruskal–WallisH = 1.0230.7970p < 0.0063Unclearε² = 0.017small
Discount from original listKruskal–WallisH = 1.8530.6044p < 0.0063Unclearε² = 0.031small
Price cut before saleChi-squareχ² = 3.7830.2861p < 0.0063UnclearCramér’s V = 0.249small
Seller paid closing costs or repairsChi-squareχ² = 3.4730.3242p < 0.0063UnclearCramér’s V = 0.239small
Has a viewChi-squareχ² = 2.4330.4881p < 0.0063UnclearCramér’s V = 0.200small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 384.00—0.1044p < 0.0063Unclearrank-biserial r = 0.306medium
Net price per SFMann–Whitney UU = 214.00—0.1492p < 0.0063Unclearrank-biserial r = 0.272small
Living areaMann–Whitney UU = 456.50—0.0033p < 0.0063Yesrank-biserial r = 0.553large
Year builtMann–Whitney UU = 245.50—0.3796p < 0.0063Unclearrank-biserial r = 0.165small
Days on marketMann–Whitney UU = 204.50—0.1063p < 0.0063Unclearrank-biserial r = 0.304medium
Discount from original listMann–Whitney UU = 232.50—0.2682p < 0.0063Unclearrank-biserial r = 0.209small
Price cut before saleChi-squareχ² = 0.0410.8491p < 0.0063UnclearCramér’s V = 0.024negligible
Seller paid closing costs or repairsChi-squareχ² = 1.7610.1844p < 0.0063UnclearCramér’s V = 0.170small

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 61 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 28, 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.