ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Bluffs At Crystal Falls Sec 2

Leander, TX 78641
Resale homes · closed Nov 6 – Nov 5, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 6, 2026 · 7:35 AM CST
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
39
single-family resale homes
Median net sale price
$576,900
average $650,602
Median net price per SF
$211
average $220
Median days on market
40 days
average 67 days
1. SummaryResale homes · 39 sales · November 6, 2025 – November 5, 2026

This study looks at the 39 resale homes sold in Bluffs At Crystal Falls Sec 2 in the 365 days to November 5, 2026. A full year is used because only 19 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 sold39 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 $498K · 10 sales$498K–$577K · 10 sales$600K–$724K · 9 salesOver $724K · 10 sales
3. Quartiles by net sale priceResale homes · 39 sales · November 6, 2025 – November 5, 2026

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

2026-11-06T07:36:07.179144 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 9 10 39 sales Sales per group Under $498K: 10 sales (26%) $498K–$577K: 10 sales (26%) $600K–$724K: 9 sales (23%) Over $724K: 10 sales (26%)
Bottom line

3.1 Key differences

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

Under $498K$498K–$577K$600K–$724KOver $724K
Higher-priced homes Over $724K
  • Are much larger.
  • Sell for more per square foot.
Lower-priced homes Under $498K
  • Are much smaller.
  • Sell for less per square foot.

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 $498K$498K–$577K$600K–$724KOver $724KReal difference?
Net price per SF$198 per SFLowest$204 per SF$220 per SF$258 per SFHighest✓ large
Living area2,166 SFSmallest2,629 SF3,020 SF3,819 SFLargest✓ large
Year built2014201820172018unclear
Days on market46 days38 days27 days62 daysunclear
Discount from original list6.6%4.9%5.2%7.4%unclear
Price cut before sale60%30%33%60%unclear
Seller paid closing costs or repairs50%80%67%30%unclear
Has a view30%10%44%50%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 Homes over $724K sell for about $60 per SF (30%) more than homes under $498K

2026-11-06T07:36:07.207740 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $498K 10 sales $498K– $577K 10 sales $600K– $724K 9 sales Over $724K 10 sales $0 $100 $200 $300 $198 $204 $220 $258 Net price per SF, average

The average is $258 per SF for homes over $724K and $198 per SF for homes under $498K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $724K are about 1,650 SF (76%) larger than homes under $498K

2026-11-06T07:36:07.230579 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $498K 10 sales $498K– $577K 10 sales $600K– $724K 9 sales Over $724K 10 sales 0 2,000 4,000 2,166 2,629 3,020 3,819 Living area (SF), average

The average is 3,819 SF for homes over $724K and 2,166 SF for homes under $498K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-11-06T07:36:07.253506 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $498K 10 sales $498K– $577K 10 sales $600K– $724K 9 sales Over $724K 10 sales 2014 2016 2018 2014 2018 2017 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over $724K and 2014 for homes under $498K. It does not move in a straight line; homes over $724K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-06T07:36:07.275260 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $498K 10 sales $498K– $577K 10 sales $600K– $724K 9 sales Over $724K 10 sales 0 20 40 60 46 38 27 62 Days on market, median

The median is 62 days for homes over $724K and 46 days for homes under $498K. It does not move in a straight line; homes over $724K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-06T07:36:07.298657 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $498K 10 sales $498K– $577K 10 sales $600K– $724K 9 sales Over $724K 10 sales 0.0% 2.5% 5.0% 7.5% 6.6% 4.9% 5.2% 7.4% Discount from original list, average

The average is 7.4% for homes over $724K and 6.6% for homes under $498K. It does not move in a straight line; homes over $724K 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

2026-11-06T07:36:07.328279 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% 60 50 30 30 80 10 33 67 44 60 30 50 Under $498K $498K–$577K $600K–$724K Over $724K

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

  • 60% of homes over $724K had a price cut before sale, against 60% of homes under $498K. Defined in 8.1.7.
  • 30% of homes over $724K had the seller pay closing costs or repairs, against 50% of homes under $498K. Defined in 8.1.8.
  • 50% of homes over $724K have a view, against 30% of homes under $498K. 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 $498K10 sales$498K–$577K10 sales$600K–$724K9 salesOver $724K10 salesAll39 salesReal difference?
Net sale price average$426,801$534,128$656,935$985,176$650,602by design
Net price per SF average$198$204$220$258$220✓ large
Living area average2,1662,6293,0203,8192,906✓ large
Year built median20142018201720182017unclear

3.10 The numbers: selling

Under $498K10 sales$498K–$577K10 sales$600K–$724K9 salesOver $724K10 salesAll39 salesReal difference?
Days on market median4638276240unclear
Discount from original list average6.6%4.9%5.2%7.4%6.1%unclear
Price cut before sale60%30%33%60%46%unclear
Seller paid closing costs or repairs50%80%67%30%56%unclear
Has a view30%10%44%50%33%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 · 39 sales · November 6, 2025 – November 5, 2026

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

2026-11-06T07:36:07.349854 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 8 11 39 sales Sales per group Under 2,509 SF: 10 sales (26%) 2,509–2,750 SF: 10 sales (26%) 2,754–3,371 SF: 8 sales (21%) Over 3,371 SF: 11 sales (28%)
Bottom line

4.1 Key differences

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

Under 2,509 SF2,509–2,750 SF2,754–3,371 SFOver 3,371 SF
Larger homes Over 3,371 SF
  • Sell for much more.
Smaller homes Under 2,509 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 2,509 SF2,509–2,750 SF2,754–3,371 SFOver 3,371 SFReal difference?
Net sale price$435KLowest$549K$635K$950KHighest✓ large
Net price per SF$204 per SF$212 per SF$209 per SF$249 per SFunclear
Year built2015201620182018unclear
Days on market22 days31 days42 days62 daysunclear
Discount from original list5.6%4.5%6.0%7.9%unclear
Price cut before sale50%30%50%55%unclear
Seller paid closing costs or repairs40%90%62%36%unclear
Has a view30%30%12%55%unclear

4.3 Homes over 3,371 SF sell for about $515K (118%) more than homes under 2,509 SF

2026-11-06T07:36:07.371202 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,509 SF 10 sales 2,509– 2,750 SF 10 sales 2,754– 3,371 SF 8 sales Over 3,371 SF 11 sales $0K $500K $1.00M $435K $549K $635K $950K Net sale price, average

The average is $950K for homes over 3,371 SF and $435K for homes under 2,509 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-11-06T07:36:07.394360 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,509 SF 10 sales 2,509– 2,750 SF 10 sales 2,754– 3,371 SF 8 sales Over 3,371 SF 11 sales $0 $100 $200 $204 $212 $209 $249 Net price per SF, average

The average is $249 per SF for homes over 3,371 SF and $204 per SF for homes under 2,509 SF. It does not move in a straight line; homes over 3,371 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-11-06T07:36:07.417176 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,509 SF 10 sales 2,509– 2,750 SF 10 sales 2,754– 3,371 SF 8 sales Over 3,371 SF 11 sales 2014 2016 2018 2015 2016 2018 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over 3,371 SF and 2015 for homes under 2,509 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-06T07:36:07.440263 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,509 SF 10 sales 2,509– 2,750 SF 10 sales 2,754– 3,371 SF 8 sales Over 3,371 SF 11 sales 0 20 40 60 22 31 42 62 Days on market, median

The median is 62 days for homes over 3,371 SF and 22 days for homes under 2,509 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-06T07:36:07.463198 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,509 SF 10 sales 2,509– 2,750 SF 10 sales 2,754– 3,371 SF 8 sales Over 3,371 SF 11 sales 0.0% 2.5% 5.0% 7.5% 5.6% 4.5% 6.0% 7.9% Discount from original list, average

The average is 7.9% for homes over 3,371 SF and 5.6% for homes under 2,509 SF. It does not move in a straight line; homes over 3,371 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

2026-11-06T07:36:07.489560 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 50 40 30 30 90 30 50 62 12 55 36 55 Under 2,509 SF 2,509–2,750 SF 2,754–3,371 SF Over 3,371 SF

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

  • 55% of homes over 3,371 SF had a price cut before sale, against 50% of homes under 2,509 SF. Defined in 8.1.7.
  • 36% of homes over 3,371 SF had the seller pay closing costs or repairs, against 40% of homes under 2,509 SF. Defined in 8.1.8.
  • 55% of homes over 3,371 SF have a view, against 30% of homes under 2,509 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 2,509 SF10 sales2,509–2,750 SF10 sales2,754–3,371 SF8 salesOver 3,371 SF11 salesAll39 salesReal difference?
Net sale price average$435,279$548,850$635,475$949,853$650,602✓ large
Net price per SF average$204$212$209$249$220unclear
Living area average2,1362,5833,0473,7962,906by design
Year built median20152016201820182017unclear

4.10 The numbers: selling

Under 2,509 SF10 sales2,509–2,750 SF10 sales2,754–3,371 SF8 salesOver 3,371 SF11 salesAll39 salesReal difference?
Days on market median2231426240unclear
Discount from original list average5.6%4.5%6.0%7.9%6.1%unclear
Price cut before sale50%30%50%55%46%unclear
Seller paid closing costs or repairs40%90%62%36%56%unclear
Has a view30%30%12%55%33%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 · 39 sales · November 6, 2025 – November 5, 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.

2026-11-06T07:36:07.510681 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 8 13 9 39 sales Sales per group Before 2015: 9 sales (23%) 2015–2016: 8 sales (21%) 2017–2018: 13 sales (33%) After 2018: 9 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 20152015–20162017–2018After 2018Real difference?
Net sale price$506K$576K$741K$731Kunclear
Net price per SF$200 per SF$211 per SF$234 per SF$227 per SFunclear
Living area2,537 SF2,684 SF3,095 SF3,197 SFunclear
Days on market68 days42 days27 days40 daysunclear
Discount from original list7.9%7.0%4.4%5.7%unclear
Price cut before sale67%62%23%44%unclear
Seller paid closing costs or repairs78%88%31%44%unclear
Has a view44%25%31%33%unclear

5.3 Net sale price: no clear difference

2026-11-06T07:36:07.531409 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 9 sales 2015– 2016 8 sales 2017– 2018 13 sales After 2018 9 sales $0K $250K $500K $750K $506K $576K $741K $731K Net sale price, average

The average is $731K for homes built after 2018 and $506K for homes built before 2015. It does not move in a straight line; homes built 2017–2018 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-06T07:36:07.554818 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 9 sales 2015– 2016 8 sales 2017– 2018 13 sales After 2018 9 sales $0 $100 $200 $200 $211 $234 $227 Net price per SF, average

The average is $227 per SF for homes built after 2018 and $200 per SF for homes built before 2015. It does not move in a straight line; homes built 2017–2018 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-06T07:36:07.576423 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 9 sales 2015– 2016 8 sales 2017– 2018 13 sales After 2018 9 sales 0 1,000 2,000 3,000 2,537 2,684 3,095 3,197 Living area (SF), average

The average is 3,197 SF for homes built after 2018 and 2,537 SF for homes built before 2015. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-06T07:36:07.598534 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 9 sales 2015– 2016 8 sales 2017– 2018 13 sales After 2018 9 sales 0 25 50 75 68 42 27 40 Days on market, median

The median is 40 days for homes built after 2018 and 68 days for homes built before 2015. It does not move in a straight line; homes built before 2015 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-06T07:36:07.621805 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2015 9 sales 2015– 2016 8 sales 2017– 2018 13 sales After 2018 9 sales 0.0% 2.5% 5.0% 7.5% 7.9% 7.0% 4.4% 5.7% Discount from original list, average

The average is 5.7% for homes built after 2018 and 7.9% for homes built before 2015. It does not move in a straight line; homes built before 2015 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

2026-11-06T07:36:07.647540 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 67 78 44 62 88 25 23 31 31 44 44 33 Before 2015 2015–2016 2017–2018 After 2018

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

  • 44% of homes built after 2018 had a price cut before sale, against 67% of homes built before 2015. Defined in 8.1.7.
  • 44% of homes built after 2018 had the seller pay closing costs or repairs, against 78% of homes built before 2015. Defined in 8.1.8.
  • 33% of homes built after 2018 have a view, against 44% of homes built before 2015. 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 20159 sales2015–20168 sales2017–201813 salesAfter 20189 salesAll39 salesReal difference?
Net sale price average$506,205$575,971$740,850$730,979$650,602unclear
Net price per SF average$200$211$234$227$220unclear
Living area average2,5372,6843,0953,1972,906unclear
Year built median20132015201820192017by design

5.10 The numbers: selling

Before 20159 sales2015–20168 sales2017–201813 salesAfter 20189 salesAll39 salesReal difference?
Days on market median6842274040unclear
Discount from original list average7.9%7.0%4.4%5.7%6.1%unclear
Price cut before sale67%62%23%44%46%unclear
Seller paid closing costs or repairs78%88%31%44%56%unclear
Has a view44%25%31%33%33%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 · 39 sales · November 6, 2025 – November 5, 2026

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

2026-11-06T07:36:07.665202 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 13 26 39 sales Sales per group View: 13 sales (33%) No view: 26 sales (67%)
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$742K$605Kunclear
Net price per SF$237 per SF$211 per SFunclear
Living area3,057 SF2,830 SFunclear
Year built20172017unclear
Days on market24 days40 daysunclear
Discount from original list6.0%6.1%unclear
Price cut before sale38%50%unclear
Seller paid closing costs or repairs54%58%unclear

6.3 Net sale price: no clear difference

2026-11-06T07:36:07.682931 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 13 sales No view 26 sales $0K $200K $400K $600K $800K $742K $605K Net sale price, average

The average is $742K for homes with a view and $605K 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

2026-11-06T07:36:07.701209 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 13 sales No view 26 sales $0 $100 $200 $237 $211 Net price per SF, average

The average is $237 per SF for homes with a view and $211 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

2026-11-06T07:36:07.718673 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 13 sales No view 26 sales 0 1,000 2,000 3,000 3,057 2,830 Living area (SF), average

The average is 3,057 SF for homes with a view and 2,830 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-06T07:36:07.765450 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 13 sales No view 26 sales 2014 2015 2016 2017 2018 2017 2017 Year built: median (dot) and middle half (bar)

The median is 2017 for homes with a view and 2017 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-06T07:36:07.784604 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 13 sales No view 26 sales 0 10 20 30 40 24 40 Days on market, median

The median is 24 days for homes with a view and 40 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

2026-11-06T07:36:07.802573 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 13 sales No view 26 sales 0.0% 2.0% 4.0% 6.0% 6.0% 6.1% Discount from original list, average

The average is 6.0% for homes with a view and 6.1% 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

2026-11-06T07:36:07.821985 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 38 54 50 58 View No view

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

  • 38% of homes with a view had a price cut before sale, against 50% of homes without a view. Defined in 8.1.7.
  • 54% of homes with a view had the seller pay closing costs or repairs, against 58% 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

View13 salesNo view26 salesAll39 salesReal difference?
Net sale price average$741,752$605,027$650,602unclear
Net price per SF average$237$211$220unclear
Living area average3,0572,8302,906unclear
Year built median201720172017unclear

6.11 The numbers: selling

View13 salesNo view26 salesAll39 salesReal difference?
Days on market median244040unclear
Discount from original list average6.0%6.1%6.1%unclear
Price cut before sale38%50%46%unclear
Seller paid closing costs or repairs54%58%56%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 6, 2025 – November 5, 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 Bluffs At Crystal Falls Sec 2.

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
39 resale sales. Average $650,602; median $576,900; standard deviation $237,594; middle half (25th–75th percentile) $481,500–$745,150; lowest $380,000, highest $1,410,000. 22 sales had a seller payment; their median payment was $4,888.

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
39 resale sales. Average $220; median $211; standard deviation $34; middle half (25th–75th percentile) $198–$227; lowest $167, highest $310.

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
39 resale sales. Average 2,906; median 2,750; standard deviation 702; middle half (25th–75th percentile) 2,368–3,373; lowest 1,978, highest 4,570.

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
39 resale sales. Average 2017; median 2017; standard deviation 3; middle half (25th–75th percentile) 2015–2018; lowest 2011, highest 2023.

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
39 resale sales. Average 67; median 40; standard deviation 75; middle half (25th–75th percentile) 17–93; lowest 2, highest 306. 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
39 resale sales. Average 6.1%; median 5.0%; standard deviation 5.3%; middle half (25th–75th percentile) 2.3%–9.0%; lowest −0.7%, highest 22.9%. 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
18 of 39 resale sales (46.2%).

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
22 of 39 resale sales (56.4%).

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
13 sales with a view, 26 without, 0 unclassified. Most common View entries: None 20, Neighborhood 9, Park/Greenbelt 8, Trees/Woods 7, Hill Country 5, Canyon 3, Panoramic 2, Pond 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 2026-11-06 13:30 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Leander, SubdivisionName contains any of “bluffs at crystal falls”, “bluffs crystal falls”, “bluffs/crystal falls”, “bluffs/ crystal falls” (case-insensitive). A record is kept when its subdivision name belongs to the Bluffs At Crystal Falls Sec 2 family, the same rule comparable sales use (it includes Bluffs/Crystal Falls Sec 3 Ph, proven adjacent and priced alike).
The data
Pulled November 6, 2026: 39 closed Bluffs At Crystal Falls Sec 2 records over the prior year, in ZIP 78641. 14 subdivision spellings kept, the most common: Bluffs At Crystal Falls Sec 2 (8); Bluffs At Crystal Falls Sec 3 (7); Bluffs at Crystal Falls (5); Bluffs/Crystal Falls Sec 3 Ph (5); Bluffs At Crystal Falls Sec 1 (3); Bluffs/Crystal Falls Ph 3D Sec (2); Bluffs/Crystal Falls Ph 31 Sec (2); Bluffs/Crystal Falls Sec Ph 01 (1); Bluffs/Crystal Falls Sec 3 (1); Bluffs/Crystal Falls Ph 1B Sec (1); BLUFFS AT CRYSTAL FALLS (1); THE BLUFFS AT CRYSTAL FALLS (1); and 2 more (2 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 19 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 6, 2025 to November 5, 2026 inclusive.
The data
39 single-family sales in the window: 39 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
39 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 $498K”.
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 $498K: $380,000–$465,000 (10 sales); $498K–$577K: $498,000–$576,900 (10 sales); $600K–$724K: $600,000–$724,000 (9 sales); Over $724K: $766,300–$1,410,000 (10 sales)
Quartiles by living area: Under 2,509 SF: 1,978–2,228 SF (10 sales); 2,509–2,750 SF: 2,509–2,750 SF (10 sales); 2,754–3,371 SF: 2,754–3,371 SF (8 sales); Over 3,371 SF: 3,373–4,570 SF (11 sales)
Quartiles by year built: Before 2015: 2011–2014 (9 sales); 2015–2016: 2015–2016 (8 sales); 2017–2018: 2017–2018 (13 sales); After 2018: 2019–2023 (9 sales)
View and no view: View: MLS lists a view (13 sales); No view: None or Neighborhood (26 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 $650,602, median $576,900. Days on market: average 67, median 40: 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
3 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 = 18.3830.0004p < 0.0063Yesε² = 0.484large
Living areaKruskal–WallisH = 32.383< 0.0001p < 0.0063Yesε² = 0.852large
Year builtKruskal–WallisH = 8.8230.0317p < 0.0063Unclearε² = 0.232large
Days on marketKruskal–WallisH = 2.2730.5185p < 0.0063Unclearε² = 0.060small
Discount from original listKruskal–WallisH = 2.9030.4070p < 0.0063Unclearε² = 0.076medium
Price cut before saleChi-squareχ² = 3.1930.3635p < 0.0063UnclearCramér’s V = 0.286small
Seller paid closing costs or repairsChi-squareχ² = 5.6530.1298p < 0.0063UnclearCramér’s V = 0.381medium
Has a viewChi-squareχ² = 4.2530.2357p < 0.0063UnclearCramér’s V = 0.330medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 30.943< 0.0001p < 0.0063Yesε² = 0.814large
Net price per SFKruskal–WallisH = 8.9130.0306p < 0.0063Unclearε² = 0.234large
Year builtKruskal–WallisH = 4.7830.1883p < 0.0063Unclearε² = 0.126medium
Days on marketKruskal–WallisH = 3.9230.2707p < 0.0063Unclearε² = 0.103medium
Discount from original listKruskal–WallisH = 1.7530.6260p < 0.0063Unclearε² = 0.046small
Price cut before saleChi-squareχ² = 1.4730.6895p < 0.0063UnclearCramér’s V = 0.194small
Seller paid closing costs or repairsChi-squareχ² = 7.6030.0550p < 0.0063UnclearCramér’s V = 0.442medium
Has a viewChi-squareχ² = 3.8930.2736p < 0.0063UnclearCramér’s V = 0.316medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 8.4730.0372p < 0.0063Unclearε² = 0.223large
Net price per SFKruskal–WallisH = 9.6130.0222p < 0.0063Unclearε² = 0.253large
Living areaKruskal–WallisH = 6.1930.1026p < 0.0063Unclearε² = 0.163large
Days on marketKruskal–WallisH = 0.3930.9428p < 0.0063Unclearε² = 0.010small
Discount from original listKruskal–WallisH = 1.8830.5984p < 0.0063Unclearε² = 0.049small
Price cut before saleChi-squareχ² = 5.1830.1591p < 0.0063UnclearCramér’s V = 0.364medium
Seller paid closing costs or repairsChi-squareχ² = 8.8230.0318p < 0.0063UnclearCramér’s V = 0.475medium
Has a viewChi-squareχ² = 0.7930.8522p < 0.0063UnclearCramér’s V = 0.142small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 219.00—0.1403p < 0.0063Unclearrank-biserial r = 0.296small
Net price per SFMann–Whitney UU = 235.00—0.0510p < 0.0063Unclearrank-biserial r = 0.391medium
Living areaMann–Whitney UU = 199.50—0.3711p < 0.0063Unclearrank-biserial r = 0.180small
Year builtMann–Whitney UU = 139.00—0.3759p < 0.0063Unclearrank-biserial r = 0.178small
Days on marketMann–Whitney UU = 155.00—0.6874p < 0.0063Unclearrank-biserial r = 0.083negligible
Discount from original listMann–Whitney UU = 142.00—0.4298p < 0.0063Unclearrank-biserial r = 0.160small
Price cut before saleChi-squareχ² = 0.4610.4956p < 0.0063UnclearCramér’s V = 0.109small
Seller paid closing costs or repairsChi-squareχ² = 0.0510.8194p < 0.0063UnclearCramér’s V = 0.037negligible

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 39 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 6, 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.