ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Grand Mesa At Crystal Falls

Leander, TX 78641
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 5:20 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
30
single-family resale homes
Median net sale price
$1,142,500
average $1,187,976
Median net price per SF
$288
average $302
Median days on market
108 days
average 146 days
1. SummaryResale homes · 30 sales · October 26, 2025 – October 25, 2026

This study looks at the 30 resale homes sold in Grand Mesa At Crystal Falls in the 365 days to October 25, 2026. A full year is used because only 20 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 $1.02M · 8 sales$1.02M–$1.14M · 7 sales$1.15M–$1.34M · 7 salesOver $1.34M · 8 sales
3. Quartiles by net sale priceResale homes · 30 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T05:20:35.236821 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Under $1.02M: 8 sales (27%) $1.02M–$1.14M: 7 sales (23%) $1.15M–$1.34M: 7 sales (23%) Over $1.34M: 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 $1.02M$1.02M–$1.14M$1.15M–$1.34MOver $1.34MReal difference?
Net price per SF$274 per SF$286 per SF$277 per SF$365 per SFunclear
Living area3,094 SF3,820 SF4,524 SF4,600 SFunclear
Year built2006201020122016unclear
Days on market182 days125 days61 days94 daysunclear
Discount from original list11.2%8.6%7.9%8.8%unclear
Price cut before sale88%57%57%50%unclear
Seller paid closing costs or repairs12%57%71%25%unclear
Has a view100%100%100%88%unclear

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

3.3 Net price per SF: no clear difference

2026-10-26T05:20:35.264300 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.02M 8 sales $1.02M– $1.14M 7 sales $1.15M– $1.34M 7 sales Over $1.34M 8 sales $0 $200 $400 $274 $286 $277 $365 Net price per SF, average

The average is $365 per SF for homes over $1.34M and $274 per SF for homes under $1.02M. It does not move in a straight line; homes over $1.34M are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-26T05:20:35.286387 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.02M 8 sales $1.02M– $1.14M 7 sales $1.15M– $1.34M 7 sales Over $1.34M 8 sales 0 2,000 4,000 3,094 3,820 4,524 4,600 Living area (SF), average

The average is 4,600 SF for homes over $1.34M and 3,094 SF for homes under $1.02M. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-26T05:20:35.309912 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.02M 8 sales $1.02M– $1.14M 7 sales $1.15M– $1.34M 7 sales Over $1.34M 8 sales 2004 2008 2012 2016 2006 2010 2012 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over $1.34M and 2006 for homes under $1.02M. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:20:35.332263 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.02M 8 sales $1.02M– $1.14M 7 sales $1.15M– $1.34M 7 sales Over $1.34M 8 sales 0 100 200 182 125 61 94 Days on market, median

The median is 94 days for homes over $1.34M and 182 days for homes under $1.02M. It does not move in a straight line; homes under $1.02M are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:20:35.353966 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $1.02M 8 sales $1.02M– $1.14M 7 sales $1.15M– $1.34M 7 sales Over $1.34M 8 sales 0.0% 5.0% 10.0% 11.2% 8.6% 7.9% 8.8% Discount from original list, average

The average is 8.8% for homes over $1.34M and 11.2% for homes under $1.02M. It does not move in a straight line; homes under $1.02M are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T05:20:35.383779 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% 88 12 100 57 57 100 57 71 100 50 25 88 Under $1.02M $1.02M–$1.14M $1.15M–$1.34M Over $1.34M

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

  • 50% of homes over $1.34M had a price cut before sale, against 88% of homes under $1.02M. Defined in 8.1.7.
  • 25% of homes over $1.34M had the seller pay closing costs or repairs, against 12% of homes under $1.02M. Defined in 8.1.8.
  • 88% of homes over $1.34M have a view, against 100% of homes under $1.02M. 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 $1.02M8 sales$1.02M–$1.14M7 sales$1.15M–$1.34M7 salesOver $1.34M8 salesAll30 salesReal difference?
Net sale price average$827,406$1,071,220$1,212,143$1,629,562$1,187,976by design
Net price per SF average$274$286$277$365$302unclear
Living area average3,0943,8204,5244,6003,998unclear
Year built median20062010201220162011unclear

3.10 The numbers: selling

Under $1.02M8 sales$1.02M–$1.14M7 sales$1.15M–$1.34M7 salesOver $1.34M8 salesAll30 salesReal difference?
Days on market median1821256194108unclear
Discount from original list average11.2%8.6%7.9%8.8%9.2%unclear
Price cut before sale88%57%57%50%63%unclear
Seller paid closing costs or repairs12%57%71%25%40%unclear
Has a view100%100%100%88%97%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 · October 26, 2025 – October 25, 2026

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

2026-10-26T05:20:35.403942 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Under 3,352 SF: 8 sales (27%) 3,352–3,737 SF: 7 sales (23%) 3,799–4,619 SF: 7 sales (23%) Over 4,619 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 3,352 SF3,352–3,737 SF3,799–4,619 SFOver 4,619 SF
Larger homes Over 4,619 SF
  • Sell for much more.
Smaller homes Under 3,352 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 3,352 SF3,352–3,737 SF3,799–4,619 SFOver 4,619 SFReal difference?
Net sale price$868KLowest$1.26M$1.16M$1.46MHighest✓ large
Net price per SF$301 per SF$356 per SF$278 per SF$277 per SFunclear
Year built2009201320092012unclear
Days on market89 days38 days167 days134 daysunclear
Discount from original list7.3%5.3%10.3%13.4%unclear
Price cut before sale75%43%57%75%unclear
Seller paid closing costs or repairs25%29%43%62%unclear
Has a view100%86%100%100%unclear

4.3 Homes over 4,619 SF sell for about $595K (69%) more than homes under 3,352 SF

2026-10-26T05:20:35.424156 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,352 SF 8 sales 3,352– 3,737 SF 7 sales 3,799– 4,619 SF 7 sales Over 4,619 SF 8 sales $0K $500K $1.00M $1.50M $868K $1.26M $1.16M $1.46M Net sale price, average

The average is $1.46M for homes over 4,619 SF and $868K for homes under 3,352 SF. It does not move in a straight line; homes over 4,619 SF are highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-26T05:20:35.446532 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,352 SF 8 sales 3,352– 3,737 SF 7 sales 3,799– 4,619 SF 7 sales Over 4,619 SF 8 sales $0 $200 $400 $301 $356 $278 $277 Net price per SF, average

The average is $277 per SF for homes over 4,619 SF and $301 per SF for homes under 3,352 SF. It does not move in a straight line; homes 3,352–3,737 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T05:20:35.470443 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,352 SF 8 sales 3,352– 3,737 SF 7 sales 3,799– 4,619 SF 7 sales Over 4,619 SF 8 sales 2002 2005 2008 2011 2014 2009 2013 2009 2012 Year built: median (dot) and middle half (bar)

The median is 2012 for homes over 4,619 SF and 2009 for homes under 3,352 SF. It does not move in a straight line; homes 3,352–3,737 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T05:20:35.493165 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,352 SF 8 sales 3,352– 3,737 SF 7 sales 3,799– 4,619 SF 7 sales Over 4,619 SF 8 sales 0 100 200 89 38 167 134 Days on market, median

The median is 134 days for homes over 4,619 SF and 89 days for homes under 3,352 SF. It does not move in a straight line; homes 3,799–4,619 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T05:20:35.514637 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 3,352 SF 8 sales 3,352– 3,737 SF 7 sales 3,799– 4,619 SF 7 sales Over 4,619 SF 8 sales 0.0% 5.0% 10.0% 15.0% 7.3% 5.3% 10.3% 13.4% Discount from original list, average

The average is 13.4% for homes over 4,619 SF and 7.3% for homes under 3,352 SF. It does not move in a straight line; homes over 4,619 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T05:20:35.541044 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% 75 25 100 43 29 86 57 43 100 75 62 100 Under 3,352 SF 3,352–3,737 SF 3,799–4,619 SF Over 4,619 SF

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

  • 75% of homes over 4,619 SF had a price cut before sale, against 75% of homes under 3,352 SF. Defined in 8.1.7.
  • 62% of homes over 4,619 SF had the seller pay closing costs or repairs, against 25% of homes under 3,352 SF. Defined in 8.1.8.
  • 100% of homes over 4,619 SF have a view, against 100% of homes under 3,352 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 3,352 SF8 sales3,352–3,737 SF7 sales3,799–4,619 SF7 salesOver 4,619 SF8 salesAll30 salesReal difference?
Net sale price average$867,656$1,264,249$1,164,143$1,462,413$1,187,976✓ large
Net price per SF average$301$356$278$277$302unclear
Living area average2,9103,5674,1725,3123,998by design
Year built median20092013200920122011unclear

4.10 The numbers: selling

Under 3,352 SF8 sales3,352–3,737 SF7 sales3,799–4,619 SF7 salesOver 4,619 SF8 salesAll30 salesReal difference?
Days on market median8938167134108unclear
Discount from original list average7.3%5.3%10.3%13.4%9.2%unclear
Price cut before sale75%43%57%75%63%unclear
Seller paid closing costs or repairs25%29%43%62%40%unclear
Has a view100%86%100%100%97%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 · October 26, 2025 – October 25, 2026

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

2026-10-26T05:20:35.561105 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Before 2007: 8 sales (27%) 2007–2010: 7 sales (23%) 2012–2014: 7 sales (23%) After 2014: 8 sales (27%)
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 20072007–20102012–2014After 2014Real difference?
Net sale price$1.03M$1.09M$1.07M$1.53Munclear
Net price per SF$293 per SF$257 per SF$294 per SF$357 per SFunclear
Living area3,580 SF4,386 SF3,632 SF4,398 SFunclear
Days on market89 days167 days107 days58 daysunclear
Discount from original list11.4%11.1%7.9%6.3%unclear
Price cut before sale62%71%71%50%unclear
Seller paid closing costs or repairs25%71%43%25%unclear
Has a view100%100%100%88%unclear

5.3 Net sale price: no clear difference

2026-10-26T05:20:35.581003 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 8 sales 2007– 2010 7 sales 2012– 2014 7 sales After 2014 8 sales $0K $500K $1.00M $1.50M $1.03M $1.09M $1.07M $1.53M Net sale price, average

The average is $1.53M for homes built after 2014 and $1.03M for homes built before 2007. It does not move in a straight line; homes built after 2014 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T05:20:35.603233 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 8 sales 2007– 2010 7 sales 2012– 2014 7 sales After 2014 8 sales $0 $200 $400 $293 $257 $294 $357 Net price per SF, average

The average is $357 per SF for homes built after 2014 and $293 per SF for homes built before 2007. It does not move in a straight line; homes built after 2014 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T05:20:35.624602 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 8 sales 2007– 2010 7 sales 2012– 2014 7 sales After 2014 8 sales 0 2,000 4,000 3,580 4,386 3,632 4,398 Living area (SF), average

The average is 4,398 SF for homes built after 2014 and 3,580 SF for homes built before 2007. It does not move in a straight line; homes built after 2014 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T05:20:35.645093 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 8 sales 2007– 2010 7 sales 2012– 2014 7 sales After 2014 8 sales 0 100 200 89 167 107 58 Days on market, median

The median is 58 days for homes built after 2014 and 89 days for homes built before 2007. 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

2026-10-26T05:20:35.667090 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 8 sales 2007– 2010 7 sales 2012– 2014 7 sales After 2014 8 sales 0.0% 5.0% 10.0% 11.4% 11.1% 7.9% 6.3% Discount from original list, average

The average is 6.3% for homes built after 2014 and 11.4% for homes built before 2007. It falls step by step from the lowest range to the 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

2026-10-26T05:20:35.691668 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% 62 25 100 71 71 100 71 43 100 50 25 88 Before 2007 2007–2010 2012–2014 After 2014

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

  • 50% of homes built after 2014 had a price cut before sale, against 62% of homes built before 2007. Defined in 8.1.7.
  • 25% of homes built after 2014 had the seller pay closing costs or repairs, against 25% of homes built before 2007. Defined in 8.1.8.
  • 88% of homes built after 2014 have a view, against 100% of homes built before 2007. 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 20078 sales2007–20107 sales2012–20147 salesAfter 20148 salesAll30 salesReal difference?
Net sale price average$1,031,469$1,091,614$1,067,820$1,533,938$1,187,976unclear
Net price per SF average$293$257$294$357$302unclear
Living area average3,5804,3863,6324,3983,998unclear
Year built median20022008201320162011by design

5.10 The numbers: selling

Before 20078 sales2007–20107 sales2012–20147 salesAfter 20148 salesAll30 salesReal difference?
Days on market median8916710758108unclear
Discount from original list average11.4%11.1%7.9%6.3%9.2%unclear
Price cut before sale62%71%71%50%63%unclear
Seller paid closing costs or repairs25%71%43%25%40%unclear
Has a view100%100%100%88%97%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 · October 26, 2025 – October 25, 2026

Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood.

2026-10-26T05:20:35.709904 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 29 1 30 sales Sales per group View: 29 sales (97%) No view: 1 sales (3%)
Bottom line: too few sales to test.

6.1 Key differences

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

6.3 Net sale price: described, not tested

2026-10-26T05:20:35.725217 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 29 sales No view 1 sales $0K $500K $1.00M $1.50M $1.17M $1.58M Net sale price, average

The average is $1.17M for homes with a view and $1.58M for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T05:20:35.742734 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 29 sales No view 1 sales $0 $200 $400 $297 $448 Net price per SF, average

The average is $297 per SF for homes with a view and $448 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T05:20:35.785077 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 29 sales No view 1 sales 0 1,000 2,000 3,000 4,000 4,015 3,533 Living area (SF), average

The average is 4,015 SF for homes with a view and 3,533 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T05:20:35.803635 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 29 sales No view 1 sales 2008 2011 2014 2010 2016 Year built: median (dot) and middle half (bar)

The median is 2010 for homes with a view and 2016 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T05:20:35.820707 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 29 sales No view 1 sales 0 50 100 109 45 Days on market, median

The median is 109 days for homes with a view and 45 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-26T05:20:35.839395 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 29 sales No view 1 sales 0.0% 2.5% 5.0% 7.5% 10.0% 9.4% 2.6% Discount from original list, average

The average is 9.4% for homes with a view and 2.6% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T05:20:35.857920 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 66 41 0 0 View No view

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

  • 66% of homes with a view had a price cut before sale, against 0% of homes without a view. Defined in 8.1.7.
  • 41% of homes with a view had the seller pay closing costs or repairs, against 0% of homes without a view. Defined in 8.1.8.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View29 salesNo view1 salesAll30 sales
Net sale price average$1,174,372$1,582,500$1,187,976
Net price per SF average$297$448$302
Living area average4,0153,5333,998
Year built median201020162011

6.11 The numbers: selling

View29 salesNo view1 salesAll30 sales
Days on market median10945108
Discount from original list average9.4%2.6%9.2%
Price cut before sale66%0%63%
Seller paid closing costs or repairs41%0%40%

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

7. New constructionBasic statistics · 0 sales · October 26, 2025 – October 25, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 0 sales, no groups, no tests.

Note: these are only the new-construction sales reported in ABOR MLS. Builders often sell homes without listing them in the MLS, so these figures do not necessarily represent all new-construction sales in Grand Mesa At Crystal Falls.

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 $1,187,976; median $1,142,500; standard deviation $330,929; middle half (25th–75th percentile) $1,002,500–$1,375,925; lowest $587,000, highest $1,970,000. 12 sales had a seller payment; their median payment was $8,500.

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
30 resale sales. Average $302; median $288; standard deviation $65; middle half (25th–75th percentile) $253–$348; lowest $183, highest $448.

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 3,998; median 3,768; standard deviation 1,022; middle half (25th–75th percentile) 3,342–4,626; lowest 2,057, highest 6,794.

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 2010; median 2011; standard deviation 6; middle half (25th–75th percentile) 2006–2015; lowest 2000, 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
30 resale sales. Average 146; median 108; standard deviation 140; middle half (25th–75th percentile) 38–199; lowest 1, highest 476. 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 9.2%; median 7.2%; standard deviation 7.1%; middle half (25th–75th percentile) 4.6%–13.9%; lowest −4.6%, highest 23.8%. 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
19 of 30 resale sales (63.3%).

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
12 of 30 resale sales (40.0%).

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
29 sales with a view, 1 without, 0 unclassified. Most common View entries: Hill Country 21, Trees/Woods 21, Panoramic 11, Park/Greenbelt 8, Pool 5, Canyon 4, Golf Course 2, See Remarks 2.

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 = Leander, SubdivisionName contains any of “grand mesa at crystal falls ii”, “grand mesa”, “grand mesa crystal falls”, “grand mesa at crystal falls” (case-insensitive). A record is kept when its subdivision name belongs to the Grand Mesa At Crystal Falls family, the same rule comparable sales use (it includes Grand Mesa 02 At Crystal Falls, Grand Mesa/Crystal Falls, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 30 closed Grand Mesa At Crystal Falls records over the prior year, in ZIP 78641. 9 subdivision spellings kept: Grand Mesa At Crystal Falls (11); Grand Mesa At Crystal Falls Ii (10); Grand Mesa At Crystal Falls II (3); GRAND MESA (1); GRAND MESA AT CRYSTAL FALLS (1); Grand Mesa at Crystal Falls (1); Grand Mesa 04 At Crystal Falls (1); Grand Mesa/Crystal Falls (1); Grand Mesa 02 At Crystal Falls (1). Names found by the search but not part of Grand Mesa At Crystal Falls, left out: Travisso Sec 1 Ph 2 / Grand Mesa Crystal Falls (1); Crystal Falls Grand Mesa (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 20 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 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 $1.02M”.
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 $1.02M: $587,000–$995,000 (8 sales); $1.02M–$1.14M: $1,025,000–$1,140,000 (7 sales); $1.15M–$1.34M: $1,145,000–$1,336,700 (7 sales); Over $1.34M: $1,389,000–$1,970,000 (8 sales)
Quartiles by living area: Under 3,352 SF: 2,057–3,339 SF (8 sales); 3,352–3,737 SF: 3,352–3,737 SF (7 sales); 3,799–4,619 SF: 3,799–4,619 SF (7 sales); Over 4,619 SF: 4,629–6,794 SF (8 sales)
Quartiles by year built: Before 2007: 2000–2006 (8 sales); 2007–2010: 2007–2010 (7 sales); 2012–2014: 2012–2014 (7 sales); After 2014: 2015–2019 (8 sales)
View and no view: View: MLS lists a view (29 sales); No view: None or Neighborhood (1 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 $1,187,976, median $1,142,500. Days on market: average 146, median 108: 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

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 = 10.0630.0181p < 0.0063Unclearε² = 0.347large
Living areaKruskal–WallisH = 11.4430.0096p < 0.0063Unclearε² = 0.394large
Year builtKruskal–WallisH = 5.1430.1620p < 0.0063Unclearε² = 0.177large
Days on marketKruskal–WallisH = 4.0630.2547p < 0.0063Unclearε² = 0.140large
Discount from original listKruskal–WallisH = 0.6830.8777p < 0.0063Unclearε² = 0.023small
Price cut before saleChi-squareχ² = 2.8630.4145p < 0.0063UnclearCramér’s V = 0.309medium
Seller paid closing costs or repairsChi-squareχ² = 7.0130.0716p < 0.0063UnclearCramér’s V = 0.483medium
Has a viewChi-squareχ² = 2.8430.4162p < 0.0063UnclearCramér’s V = 0.308medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 14.4930.0023p < 0.0063Yesε² = 0.500large
Net price per SFKruskal–WallisH = 5.7730.1232p < 0.0063Unclearε² = 0.199large
Year builtKruskal–WallisH = 2.1330.5451p < 0.0063Unclearε² = 0.074medium
Days on marketKruskal–WallisH = 2.4030.4939p < 0.0063Unclearε² = 0.083medium
Discount from original listKruskal–WallisH = 7.4130.0599p < 0.0063Unclearε² = 0.256large
Price cut before saleChi-squareχ² = 2.3230.5092p < 0.0063UnclearCramér’s V = 0.278small
Seller paid closing costs or repairsChi-squareχ² = 2.8430.4166p < 0.0063UnclearCramér’s V = 0.308medium
Has a viewChi-squareχ² = 3.4030.3341p < 0.0063UnclearCramér’s V = 0.337medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 10.2830.0163p < 0.0063Unclearε² = 0.354large
Net price per SFKruskal–WallisH = 10.0130.0185p < 0.0063Unclearε² = 0.345large
Living areaKruskal–WallisH = 3.3230.3447p < 0.0063Unclearε² = 0.115medium
Days on marketKruskal–WallisH = 1.8030.6158p < 0.0063Unclearε² = 0.062medium
Discount from original listKruskal–WallisH = 1.7130.6346p < 0.0063Unclearε² = 0.059small
Price cut before saleChi-squareχ² = 1.0130.7989p < 0.0063UnclearCramér’s V = 0.183small
Seller paid closing costs or repairsChi-squareχ² = 4.4030.2209p < 0.0063UnclearCramér’s V = 0.383medium
Has a viewChi-squareχ² = 2.8430.4162p < 0.0063UnclearCramér’s V = 0.308medium

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 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 October 26, 2026. Map data © OpenStreetMap contributors. ALEX Companies · Licensed by the Texas Real Estate Commission · Broker: Alexander Tiffany Southwest, LLC (ALEX Real Estate), #565194-BB · Diane Hart Alexander, Designated Broker, #574877-B.