ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Pioneer Crossing West

Austin, TX 78754
Resale homes · closed Nov 5 – Nov 4, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 5, 2026 · 3:21 PM 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
30
single-family resale homes
Median net sale price
$364,862
average $362,461
Median net price per SF
$195
average $192
Median days on market
34 days
average 43 days
1. SummaryResale homes · 30 sales · November 5, 2025 – November 4, 2026

This study looks at the 30 resale homes sold in Pioneer Crossing West in the 365 days to November 4, 2026. A full year is used because only 17 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 sold30 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 $355K · 8 sales$355K–$365K · 7 sales$365K–$374K · 7 salesOver $374K · 8 sales
3. Quartiles by net sale priceResale homes · 30 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T15:21:18.284786 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Under $355K: 8 sales (27%) $355K–$365K: 7 sales (23%) $365K–$374K: 7 sales (23%) Over $374K: 8 sales (27%)
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 $355K$355K–$365K$365K–$374KOver $374KReal difference?
Net price per SF$192 per SF$184 per SF$188 per SF$202 per SFunclear
Living area1,765 SF2,001 SF2,002 SF1,922 SFunclear
Year built2008200620092008unclear
Days on market57 days33 days20 days36 daysunclear
Discount from original list5.7%6.1%4.4%4.7%unclear
Price cut before sale38%43%29%25%unclear
Seller paid closing costs or repairs38%71%57%75%unclear
Has a view0%14%29%25%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

2026-11-05T15:21:18.312901 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $355K 8 sales $355K– $365K 7 sales $365K– $374K 7 sales Over $374K 8 sales $0 $100 $200 $192 $184 $188 $202 Net price per SF, average

The average is $202 per SF for homes over $374K and $192 per SF for homes under $355K. It does not move in a straight line; homes over $374K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-11-05T15:21:18.335123 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $355K 8 sales $355K– $365K 7 sales $365K– $374K 7 sales Over $374K 8 sales 0 1,000 2,000 1,765 2,001 2,002 1,922 Living area (SF), average

The average is 1,922 SF for homes over $374K and 1,765 SF for homes under $355K. It does not move in a straight line; homes $365K–$374K are highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-11-05T15:21:18.357750 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $355K 8 sales $355K– $365K 7 sales $365K– $374K 7 sales Over $374K 8 sales 2006 2008 2010 2008 2006 2009 2008 Year built: median (dot) and middle half (bar)

The median is 2008 for homes over $374K and 2008 for homes under $355K. It does not move in a straight line; homes $365K–$374K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-05T15:21:18.379416 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $355K 8 sales $355K– $365K 7 sales $365K– $374K 7 sales Over $374K 8 sales 0 20 40 60 57 33 20 36 Days on market, median

The median is 36 days for homes over $374K and 57 days for homes under $355K. It does not move in a straight line; homes under $355K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-05T15:21:18.402012 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $355K 8 sales $355K– $365K 7 sales $365K– $374K 7 sales Over $374K 8 sales 0.0% 2.0% 4.0% 6.0% 5.7% 6.1% 4.4% 4.7% Discount from original list, average

The average is 4.7% for homes over $374K and 5.7% for homes under $355K. It does not move in a straight line; homes $355K–$365K 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

2026-11-05T15:21:18.432065 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% 38 38 0 43 71 14 29 57 29 25 75 25 Under $355K $355K–$365K $365K–$374K Over $374K

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

  • 25% of homes over $374K had a price cut before sale, against 38% of homes under $355K. Defined in 8.1.7.
  • 75% of homes over $374K had the seller pay closing costs or repairs, against 38% of homes under $355K. Defined in 8.1.8.
  • 25% of homes over $374K have a view, against 0% of homes under $355K. 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 $355K8 sales$355K–$365K7 sales$365K–$374K7 salesOver $374K8 salesAll30 salesReal difference?
Net sale price average$337,256$358,975$369,550$384,512$362,461by design
Net price per SF average$192$184$188$202$192unclear
Living area average1,7652,0012,0021,9221,917unclear
Year built median20082006200920082006unclear

3.10 The numbers: selling

Under $355K8 sales$355K–$365K7 sales$365K–$374K7 salesOver $374K8 salesAll30 salesReal difference?
Days on market median5733203634unclear
Discount from original list average5.7%6.1%4.4%4.7%5.2%unclear
Price cut before sale38%43%29%25%33%unclear
Seller paid closing costs or repairs38%71%57%75%60%unclear
Has a view0%14%29%25%17%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 · 30 sales · November 5, 2025 – November 4, 2026

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

2026-11-05T15:21:18.452601 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Under 1,722 SF: 8 sales (27%) 1,722–1,870 SF: 7 sales (23%) 1,874–1,952 SF: 7 sales (23%) Over 1,952 SF: 8 sales (27%)
Bottom line

4.1 Key differences

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

Under 1,722 SF1,722–1,870 SF1,874–1,952 SFOver 1,952 SF
Larger homes Over 1,952 SF
  • Sell for less per square foot.
Smaller homes Under 1,722 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 1,722 SF1,722–1,870 SF1,874–1,952 SFOver 1,952 SFReal difference?
Net sale price$350K$368K$373K$362Kunclear
Net price per SF$213 per SFHighest$202 per SF$195 per SF$159 per SFLowest✓ large
Year built2010200620062006unclear
Days on market38 days33 days33 days41 daysunclear
Discount from original list4.0%3.8%3.8%8.9%unclear
Price cut before sale25%29%14%62%unclear
Seller paid closing costs or repairs75%43%43%75%unclear
Has a view12%14%14%25%unclear

4.3 Net sale price: no clear difference

2026-11-05T15:21:18.472984 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,722 SF 8 sales 1,722– 1,870 SF 7 sales 1,874– 1,952 SF 7 sales Over 1,952 SF 8 sales $0K $200K $400K $350K $368K $373K $362K Net sale price, average

The average is $362K for homes over 1,952 SF and $350K for homes under 1,722 SF. It does not move in a straight line; homes 1,874–1,952 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Homes over 1,952 SF sell for about $55 per SF (26%) less than homes under 1,722 SF

2026-11-05T15:21:18.495977 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,722 SF 8 sales 1,722– 1,870 SF 7 sales 1,874– 1,952 SF 7 sales Over 1,952 SF 8 sales $0 $100 $200 $213 $202 $195 $159 Net price per SF, average

The average is $159 per SF for homes over 1,952 SF and $213 per SF for homes under 1,722 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

2026-11-05T15:21:18.519195 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,722 SF 8 sales 1,722– 1,870 SF 7 sales 1,874– 1,952 SF 7 sales Over 1,952 SF 8 sales 2006 2008 2010 2012 2010 2006 2006 2006 Year built: median (dot) and middle half (bar)

The median is 2006 for homes over 1,952 SF and 2010 for homes under 1,722 SF. It does not move in a straight line; homes under 1,722 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-05T15:21:18.540941 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,722 SF 8 sales 1,722– 1,870 SF 7 sales 1,874– 1,952 SF 7 sales Over 1,952 SF 8 sales 0 20 40 38 33 33 41 Days on market, median

The median is 41 days for homes over 1,952 SF and 38 days for homes under 1,722 SF. It does not move in a straight line; homes over 1,952 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-05T15:21:18.563516 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,722 SF 8 sales 1,722– 1,870 SF 7 sales 1,874– 1,952 SF 7 sales Over 1,952 SF 8 sales 0.0% 5.0% 10.0% 4.0% 3.8% 3.8% 8.9% Discount from original list, average

The average is 8.9% for homes over 1,952 SF and 4.0% for homes under 1,722 SF. It does not move in a straight line; homes over 1,952 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

2026-11-05T15:21:18.589373 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 25 75 12 29 43 14 14 43 14 62 75 25 Under 1,722 SF 1,722–1,870 SF 1,874–1,952 SF Over 1,952 SF

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

  • 62% of homes over 1,952 SF had a price cut before sale, against 25% of homes under 1,722 SF. Defined in 8.1.7.
  • 75% of homes over 1,952 SF had the seller pay closing costs or repairs, against 75% of homes under 1,722 SF. Defined in 8.1.8.
  • 25% of homes over 1,952 SF have a view, against 12% of homes under 1,722 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 1,722 SF8 sales1,722–1,870 SF7 sales1,874–1,952 SF7 salesOver 1,952 SF8 salesAll30 salesReal difference?
Net sale price average$350,031$367,571$372,514$361,622$362,461unclear
Net price per SF average$213$202$195$159$192✓ large
Living area average1,6401,8171,9132,2861,917by design
Year built median20102006200620062006unclear

4.10 The numbers: selling

Under 1,722 SF8 sales1,722–1,870 SF7 sales1,874–1,952 SF7 salesOver 1,952 SF8 salesAll30 salesReal difference?
Days on market median3833334134unclear
Discount from original list average4.0%3.8%3.8%8.9%5.2%unclear
Price cut before sale25%29%14%62%33%unclear
Seller paid closing costs or repairs75%43%43%75%60%unclear
Has a view12%14%14%25%17%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 · 30 sales · November 5, 2025 – November 4, 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.

2026-11-05T15:21:18.610409 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 6 8 7 30 sales Sales per group Before 2006: 9 sales (30%) 2006: 6 sales (20%) 2007–2010: 8 sales (27%) After 2010: 7 sales (23%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

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

5.2 At a glance

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

Before 200620062007–2010After 2010Real difference?
Net sale price$358K$357K$372K$362Kunclear
Net price per SF$195 per SF$179 per SF$194 per SF$197 per SFunclear
Living area1,857 SF2,031 SF1,948 SF1,862 SFunclear
Days on market34 days28 days44 days9 daysunclear
Discount from original list3.5%6.6%6.7%4.6%unclear
Price cut before sale22%33%50%29%unclear
Seller paid closing costs or repairs33%67%88%57%unclear
Has a view0%17%25%29%unclear

5.3 Net sale price: no clear difference

2026-11-05T15:21:18.630500 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 9 sales 2006 6 sales 2007– 2010 8 sales After 2010 7 sales $0K $200K $400K $358K $357K $372K $362K Net sale price, average

The average is $362K for homes built after 2010 and $358K for homes built before 2006. It does not move in a straight line; homes built 2007–2010 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-05T15:21:18.652065 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 9 sales 2006 6 sales 2007– 2010 8 sales After 2010 7 sales $0 $100 $200 $195 $179 $194 $197 Net price per SF, average

The average is $197 per SF for homes built after 2010 and $195 per SF for homes built before 2006. It does not move in a straight line; homes built after 2010 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-05T15:21:18.674207 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 9 sales 2006 6 sales 2007– 2010 8 sales After 2010 7 sales 0 1,000 2,000 1,857 2,031 1,948 1,862 Living area (SF), average

The average is 1,862 SF for homes built after 2010 and 1,857 SF for homes built before 2006. It does not move in a straight line; homes built 2006 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-05T15:21:18.695750 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 9 sales 2006 6 sales 2007– 2010 8 sales After 2010 7 sales 0 20 40 34 28 44 9 Days on market, median

The median is 9 days for homes built after 2010 and 34 days for homes built before 2006. It does not move in a straight line; homes built 2007–2010 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-05T15:21:18.718210 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 9 sales 2006 6 sales 2007– 2010 8 sales After 2010 7 sales 0.0% 2.0% 4.0% 6.0% 3.5% 6.6% 6.7% 4.6% Discount from original list, average

The average is 4.6% for homes built after 2010 and 3.5% for homes built before 2006. It does not move in a straight line; homes built 2007–2010 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

2026-11-05T15:21:18.743771 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% 22 33 0 33 67 17 50 88 25 29 57 29 Before 2006 2006 2007–2010 After 2010

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

  • 29% of homes built after 2010 had a price cut before sale, against 22% of homes built before 2006. Defined in 8.1.7.
  • 57% of homes built after 2010 had the seller pay closing costs or repairs, against 33% of homes built before 2006. Defined in 8.1.8.
  • 29% of homes built after 2010 have a view, against 0% of homes built before 2006. 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 20069 sales20066 sales2007–20108 salesAfter 20107 salesAll30 salesReal difference?
Net sale price average$358,500$356,654$371,706$361,964$362,461unclear
Net price per SF average$195$179$194$197$192unclear
Living area average1,8572,0311,9481,8621,917unclear
Year built median20052006201020142006by design

5.10 The numbers: selling

Before 20069 sales20066 sales2007–20108 salesAfter 20107 salesAll30 salesReal difference?
Days on market median342844934unclear
Discount from original list average3.5%6.6%6.7%4.6%5.2%unclear
Price cut before sale22%33%50%29%33%unclear
Seller paid closing costs or repairs33%67%88%57%60%unclear
Has a view0%17%25%29%17%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 · 30 sales · November 5, 2025 – November 4, 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.

2026-11-05T15:21:18.761699 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 24 29 sales Sales per group View: 5 sales (17%) No view: 24 sales (83%)
Bottom line: no measure differs enough between the groups to rule out chance.

6.1 Key differences

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

6.2 At a glance

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

ViewNo viewReal difference?
Net sale price$377K$360Kunclear
Net price per SF$192 per SF$193 per SFunclear
Living area2,000 SF1,883 SFunclear
Year built20102006unclear
Days on market46 days33 daysunclear
Discount from original list5.6%4.7%unclear
Price cut before sale40%29%unclear
Seller paid closing costs or repairs100%50%unclear

6.3 Net sale price: no clear difference

2026-11-05T15:21:18.779342 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 24 sales $0K $100K $200K $300K $400K $377K $360K Net sale price, average

The average is $377K for homes with a view and $360K 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

2026-11-05T15:21:18.798004 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 24 sales $0 $50 $100 $150 $200 $192 $193 Net price per SF, average

The average is $192 per SF for homes with a view and $193 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-11-05T15:21:18.816601 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 24 sales 0 500 1,000 1,500 2,000 2,000 1,883 Living area (SF), average

The average is 2,000 SF for homes with a view and 1,883 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-05T15:21:18.862129 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 24 sales 2006 2008 2010 2012 2014 2010 2006 Year built: median (dot) and middle half (bar)

The median is 2010 for homes with a view and 2006 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-05T15:21:18.880792 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 24 sales 0 20 40 46 33 Days on market, median

The median is 46 days for homes with a view and 33 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

2026-11-05T15:21:18.898739 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 24 sales 0.0% 2.0% 4.0% 6.0% 5.6% 4.7% Discount from original list, average

The average is 5.6% for homes with a view and 4.7% 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

2026-11-05T15:21:18.917572 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 40 100 29 50 View No view

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

  • 40% of homes with a view had a price cut before sale, against 29% 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 50% 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

View5 salesNo view24 salesAll29 salesReal difference?
Net sale price average$376,785$359,704$362,649unclear
Net price per SF average$192$193$193unclear
Living area average2,0001,8831,903unclear
Year built median201020062006unclear

6.11 The numbers: selling

View5 salesNo view24 salesAll29 salesReal difference?
Days on market median463333unclear
Discount from original list average5.6%4.7%4.8%unclear
Price cut before sale40%29%31%unclear
Seller paid closing costs or repairs100%50%59%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 5, 2025 – November 4, 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 Pioneer Crossing West.

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
30 resale sales. Average $362,461; median $364,862; standard deviation $20,164; middle half (25th–75th percentile) $355,050–$374,775; lowest $315,000, highest $403,000. 18 sales had a seller payment; their median payment was $10,138.

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
30 resale sales. Average $192; median $195; standard deviation $24; middle half (25th–75th percentile) $186–$207; lowest $146, highest $229.

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
30 resale sales. Average 1,917; median 1,872; standard deviation 264; middle half (25th–75th percentile) 1,694–1,956; lowest 1,608, highest 2,432.

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
30 resale sales. Average 2008; median 2006; standard deviation 4; middle half (25th–75th percentile) 2005–2010; lowest 2003, highest 2018.

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
30 resale sales. Average 43; median 34; standard deviation 44; middle half (25th–75th percentile) 15–56; lowest 3, highest 217. 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
30 resale sales. Average 5.2%; median 4.1%; standard deviation 4.7%; middle half (25th–75th percentile) 2.0%–7.8%; lowest −1.5%, highest 17.9%. 1 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
10 of 30 resale sales (33.3%).

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
18 of 30 resale sales (60.0%).

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
5 sales with a view, 24 without, 1 unclassified. Most common View entries: None 18, Neighborhood 9, Park/Greenbelt 3, Trees/Woods 2, 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 2026-11-05 21:15 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “pioneer crossing west” (case-insensitive). A record is kept when its subdivision name belongs to the Pioneer Crossing West family, the same rule comparable sales use.
The data
Pulled November 5, 2026: 30 closed Pioneer Crossing West records over the prior year, in ZIP 78754. 11 subdivision spellings kept: Pioneer Crossing West Sec 04 (7); Pioneer Crossing West (6); Pioneer Crossing West Sec 07 (5); Pioneer Crossing West Sec 02 (4); Pioneer Crossing West Sec 8A (2); Pioneer Crossing West Sec 9b (1); Pioneer Crossing West Sec 05 (1); Pioneer Crossing West Sec 9a (1); Pioneer Crossing West Sec 8b (1); Pioneer Crossing West Sec 8B (1); Pioneer Crossing West Sec 06 (1). Names found by the search but not part of Pioneer Crossing West, left out: Creekside at Pioneer Crossing West (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 17 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 5, 2025 to November 4, 2026 inclusive.
The data
30 single-family sales in the window: 30 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
30 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 $355K”.
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 $355K: $315,000–$355,000 (8 sales); $355K–$365K: $355,200–$364,725 (7 sales); $365K–$374K: $365,000–$374,100 (7 sales); Over $374K: $375,000–$403,000 (8 sales)
Quartiles by living area: Under 1,722 SF: 1,608–1,685 SF (8 sales); 1,722–1,870 SF: 1,722–1,870 SF (7 sales); 1,874–1,952 SF: 1,874–1,952 SF (7 sales); Over 1,952 SF: 1,957–2,432 SF (8 sales)
Quartiles by year built: Before 2006: 2003–2005 (9 sales); 2006: 2006–2006 (6 sales); 2007–2010: 2007–2010 (8 sales); After 2010: 2011–2018 (7 sales)
View and no view: View: MLS lists a view (5 sales); No view: None or Neighborhood (24 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 $362,461, median $364,862. Days on market: average 43, median 34: 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
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 = 3.7030.2962p < 0.0063Unclearε² = 0.127medium
Living areaKruskal–WallisH = 4.1030.2510p < 0.0063Unclearε² = 0.141large
Year builtKruskal–WallisH = 0.3930.9432p < 0.0063Unclearε² = 0.013small
Days on marketKruskal–WallisH = 1.8230.6099p < 0.0063Unclearε² = 0.063medium
Discount from original listKruskal–WallisH = 0.8230.8457p < 0.0063Unclearε² = 0.028small
Price cut before saleChi-squareχ² = 0.6730.8803p < 0.0063UnclearCramér’s V = 0.149small
Seller paid closing costs or repairsChi-squareχ² = 2.8430.4166p < 0.0063UnclearCramér’s V = 0.308medium
Has a viewChi-squareχ² = 2.7430.4330p < 0.0063UnclearCramér’s V = 0.302medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 4.7230.1936p < 0.0063Unclearε² = 0.163large
Net price per SFKruskal–WallisH = 21.1030.0001p < 0.0063Yesε² = 0.727large
Year builtKruskal–WallisH = 1.3930.7086p < 0.0063Unclearε² = 0.048small
Days on marketKruskal–WallisH = 1.7130.6343p < 0.0063Unclearε² = 0.059small
Discount from original listKruskal–WallisH = 3.8830.2742p < 0.0063Unclearε² = 0.134medium
Price cut before saleChi-squareχ² = 4.5330.2099p < 0.0063UnclearCramér’s V = 0.388medium
Seller paid closing costs or repairsChi-squareχ² = 3.2130.3598p < 0.0063UnclearCramér’s V = 0.327medium
Has a viewChi-squareχ² = 0.5630.9062p < 0.0063UnclearCramér’s V = 0.136small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 3.3030.3471p < 0.0063Unclearε² = 0.114medium
Net price per SFKruskal–WallisH = 1.6030.6590p < 0.0063Unclearε² = 0.055small
Living areaKruskal–WallisH = 1.6430.6493p < 0.0063Unclearε² = 0.057small
Days on marketKruskal–WallisH = 3.1830.3643p < 0.0063Unclearε² = 0.110medium
Discount from original listKruskal–WallisH = 3.8430.2793p < 0.0063Unclearε² = 0.132medium
Price cut before saleChi-squareχ² = 1.5730.6659p < 0.0063UnclearCramér’s V = 0.229small
Seller paid closing costs or repairsChi-squareχ² = 5.3230.1497p < 0.0063UnclearCramér’s V = 0.421medium
Has a viewChi-squareχ² = 2.9130.4050p < 0.0063UnclearCramér’s V = 0.312medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 91.00—0.0779p < 0.0063Unclearrank-biserial r = 0.517large
Net price per SFMann–Whitney UU = 64.00—0.8449p < 0.0063Unclearrank-biserial r = 0.067negligible
Living areaMann–Whitney UU = 69.50—0.6030p < 0.0063Unclearrank-biserial r = 0.158small
Year builtMann–Whitney UU = 91.00—0.0748p < 0.0063Unclearrank-biserial r = 0.517large
Days on marketMann–Whitney UU = 61.00—0.9770p < 0.0063Unclearrank-biserial r = 0.017negligible
Discount from original listMann–Whitney UU = 65.00—0.8013p < 0.0063Unclearrank-biserial r = 0.083negligible
Price cut before saleChi-squareχ² = 0.2310.6338p < 0.0063UnclearCramér’s V = 0.088negligible
Seller paid closing costs or repairsChi-squareχ² = 4.2610.0389p < 0.0063UnclearCramér’s V = 0.383medium

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 30 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 5, 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.