ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Cedar Park Towncenter

Cedar Park, TX 78613
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 · 7:49 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
$344,500
average $346,165
Median net price per SF
$194
average $203
Median days on market
52 days
average 67 days
1. SummaryResale homes · 30 sales · October 26, 2025 – October 25, 2026

This study looks at the 30 resale homes sold in Cedar Park Towncenter in the 365 days to October 25, 2026. A full year is used because only 23 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 $319K · 8 sales$319K–$344K · 7 sales$345K–$360K · 7 salesOver $360K · 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.

2026-10-26T07:49:32.451771 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Under $319K: 8 sales (27%) $319K–$344K: 7 sales (23%) $345K–$360K: 7 sales (23%) Over $360K: 8 sales (27%)
Bottom line

3.1 Key differences

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

Under $319K$319K–$344K$345K–$360KOver $360K
Higher-priced homes Over $360K
  • Are much larger.
Lower-priced homes Under $319K
  • Are much smaller.

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 $319K$319K–$344K$345K–$360KOver $360KReal difference?
Net price per SF$197 per SF$209 per SF$219 per SF$189 per SFunclear
Living area1,571 SFSmallest1,636 SF1,633 SF2,108 SFLargest✓ large
Year built2008200720082006unclear
Days on market62 days32 days27 days72 daysunclear
Discount from original list11.9%9.8%4.1%5.7%unclear
Price cut before sale100%43%29%50%unclear
Seller paid closing costs or repairs88%86%86%62%unclear
Has a view12%0%0%0%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

2026-10-26T07:49:32.480425 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $319K 8 sales $319K– $344K 7 sales $345K– $360K 7 sales Over $360K 8 sales $0 $100 $200 $197 $209 $219 $189 Net price per SF, average

The average is $189 per SF for homes over $360K and $197 per SF for homes under $319K. It does not move in a straight line; homes $345K–$360K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $360K are about 540 SF (34%) larger than homes under $319K

2026-10-26T07:49:32.503016 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $319K 8 sales $319K– $344K 7 sales $345K– $360K 7 sales Over $360K 8 sales 0 1,000 2,000 1,571 1,636 1,633 2,108 Living area (SF), average

The average is 2,108 SF for homes over $360K and 1,571 SF for homes under $319K. It does not move in a straight line; homes over $360K are highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-26T07:49:32.526835 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $319K 8 sales $319K– $344K 7 sales $345K– $360K 7 sales Over $360K 8 sales 2006 2007 2008 2009 2008 2007 2008 2006 Year built: median (dot) and middle half (bar)

The median is 2006 for homes over $360K and 2008 for homes under $319K. It does not move in a straight line; homes $345K–$360K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:49:32.549879 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $319K 8 sales $319K– $344K 7 sales $345K– $360K 7 sales Over $360K 8 sales 0 25 50 75 62 32 27 72 Days on market, median

The median is 72 days for homes over $360K and 62 days for homes under $319K. It does not move in a straight line; homes over $360K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:49:32.572164 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $319K 8 sales $319K– $344K 7 sales $345K– $360K 7 sales Over $360K 8 sales 0.0% 5.0% 10.0% 11.9% 9.8% 4.1% 5.7% Discount from original list, average

The average is 5.7% for homes over $360K and 11.9% for homes under $319K. It does not move in a straight line; homes under $319K 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

2026-10-26T07:49:32.602013 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% 100 88 12 43 86 0 29 86 0 50 62 0 Under $319K $319K–$344K $345K–$360K Over $360K

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

  • 50% of homes over $360K had a price cut before sale, against 100% of homes under $319K. Defined in 8.1.7.
  • 62% of homes over $360K had the seller pay closing costs or repairs, against 88% of homes under $319K. Defined in 8.1.8.
  • 0% of homes over $360K have a view, against 12% of homes under $319K. 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 $319K8 sales$319K–$344K7 sales$345K–$360K7 salesOver $360K8 salesAll30 salesReal difference?
Net sale price average$305,494$330,641$350,117$396,962$346,165by design
Net price per SF average$197$209$219$189$203unclear
Living area average1,5711,6361,6332,1081,744✓ large
Year built median20082007200820062007unclear

3.10 The numbers: selling

Under $319K8 sales$319K–$344K7 sales$345K–$360K7 salesOver $360K8 salesAll30 salesReal difference?
Days on market median6232277252unclear
Discount from original list average11.9%9.8%4.1%5.7%7.9%unclear
Price cut before sale100%43%29%50%57%unclear
Seller paid closing costs or repairs88%86%86%62%80%unclear
Has a view12%0%0%0%3%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.

2026-10-26T07:49:32.622741 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 7 7 8 30 sales Sales per group Under 1,460 SF: 8 sales (27%) 1,460–1,832 SF: 7 sales (23%) 1,854–1,947 SF: 7 sales (23%) Over 1,947 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 1,460 SF1,460–1,832 SF1,854–1,947 SFOver 1,947 SF
Larger homes Over 1,947 SF
  • Sell for less per square foot.
  • Sell for much more.
Smaller homes Under 1,460 SF
  • Sell for more per square foot.
  • 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 1,460 SF1,460–1,832 SF1,854–1,947 SFOver 1,947 SFReal difference?
Net sale price$335K$311KLowest$343K$391KHighest✓ large
Net price per SF$243 per SFHighest$201 per SF$182 per SF$182 per SFLowest✓ large
Year built2008200720062007unclear
Days on market51 days61 days27 days72 daysunclear
Discount from original list8.1%10.6%7.2%6.1%unclear
Price cut before sale50%86%43%50%unclear
Seller paid closing costs or repairs100%71%86%62%unclear
Has a view12%0%0%0%unclear

4.3 Homes over 1,947 SF sell for about $57K (17%) more than homes under 1,460 SF

2026-10-26T07:49:32.643896 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,460 SF 8 sales 1,460– 1,832 SF 7 sales 1,854– 1,947 SF 7 sales Over 1,947 SF 8 sales $0K $200K $400K $335K $311K $343K $391K Net sale price, average

The average is $391K for homes over 1,947 SF and $335K for homes under 1,460 SF. It does not move in a straight line; homes over 1,947 SF are highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 1,947 SF sell for about $61 per SF (25%) less than homes under 1,460 SF

2026-10-26T07:49:32.666024 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,460 SF 8 sales 1,460– 1,832 SF 7 sales 1,854– 1,947 SF 7 sales Over 1,947 SF 8 sales $0 $100 $200 $243 $201 $182 $182 Net price per SF, average

The average is $182 per SF for homes over 1,947 SF and $243 per SF for homes under 1,460 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

2026-10-26T07:49:32.689799 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,460 SF 8 sales 1,460– 1,832 SF 7 sales 1,854– 1,947 SF 7 sales Over 1,947 SF 8 sales 2006 2007 2008 2009 2008 2007 2006 2007 Year built: median (dot) and middle half (bar)

The median is 2007 for homes over 1,947 SF and 2008 for homes under 1,460 SF. It does not move in a straight line; homes under 1,460 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:49:32.713122 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,460 SF 8 sales 1,460– 1,832 SF 7 sales 1,854– 1,947 SF 7 sales Over 1,947 SF 8 sales 0 25 50 75 51 61 27 72 Days on market, median

The median is 72 days for homes over 1,947 SF and 51 days for homes under 1,460 SF. It does not move in a straight line; homes over 1,947 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:49:32.735910 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,460 SF 8 sales 1,460– 1,832 SF 7 sales 1,854– 1,947 SF 7 sales Over 1,947 SF 8 sales 0.0% 5.0% 10.0% 8.1% 10.6% 7.2% 6.1% Discount from original list, average

The average is 6.1% for homes over 1,947 SF and 8.1% for homes under 1,460 SF. It does not move in a straight line; homes 1,460–1,832 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

2026-10-26T07:49:32.762895 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% 50 100 12 86 71 0 43 86 0 50 62 0 Under 1,460 SF 1,460–1,832 SF 1,854–1,947 SF Over 1,947 SF

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

  • 50% of homes over 1,947 SF had a price cut before sale, against 50% of homes under 1,460 SF. Defined in 8.1.7.
  • 62% of homes over 1,947 SF had the seller pay closing costs or repairs, against 100% of homes under 1,460 SF. Defined in 8.1.8.
  • 0% of homes over 1,947 SF have a view, against 12% of homes under 1,460 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 1,460 SF8 sales1,460–1,832 SF7 sales1,854–1,947 SF7 salesOver 1,947 SF8 salesAll30 salesReal difference?
Net sale price average$334,529$310,850$343,296$391,212$346,165✓ large
Net price per SF average$243$201$182$182$203✓ large
Living area average1,3761,5591,8822,1521,744by design
Year built median20082007200620072007unclear

4.10 The numbers: selling

Under 1,460 SF8 sales1,460–1,832 SF7 sales1,854–1,947 SF7 salesOver 1,947 SF8 salesAll30 salesReal difference?
Days on market median5161277252unclear
Discount from original list average8.1%10.6%7.2%6.1%7.9%unclear
Price cut before sale50%86%43%50%57%unclear
Seller paid closing costs or repairs100%71%86%62%80%unclear
Has a view12%0%0%0%3%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.

2026-10-26T07:49:32.783945 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 8 7 6 30 sales Sales per group Before 2007: 9 sales (30%) 2007: 8 sales (27%) 2008: 7 sales (23%) After 2008: 6 sales (20%)
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 200720072008After 2008Real difference?
Net sale price$361K$337K$326K$360Kunclear
Net price per SF$201 per SF$198 per SF$200 per SF$215 per SFunclear
Living area1,824 SF1,736 SF1,656 SF1,736 SFunclear
Days on market59 days55 days54 days49 daysunclear
Discount from original list6.4%10.6%8.3%6.3%unclear
Price cut before sale44%62%71%50%unclear
Seller paid closing costs or repairs78%62%100%83%unclear
Has a view11%0%0%0%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:49:32.805062 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 9 sales 2007 8 sales 2008 7 sales After 2008 6 sales $0K $100K $200K $300K $400K $361K $337K $326K $360K Net sale price, average

The average is $360K for homes built after 2008 and $361K for homes built before 2007. It does not move in a straight line; homes built before 2007 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:49:32.828397 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 9 sales 2007 8 sales 2008 7 sales After 2008 6 sales $0 $100 $200 $201 $198 $200 $215 Net price per SF, average

The average is $215 per SF for homes built after 2008 and $201 per SF for homes built before 2007. It does not move in a straight line; homes built after 2008 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:49:32.850267 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 9 sales 2007 8 sales 2008 7 sales After 2008 6 sales 0 500 1,000 1,500 2,000 1,824 1,736 1,656 1,736 Living area (SF), average

The average is 1,736 SF for homes built after 2008 and 1,824 SF for homes built before 2007. It does not move in a straight line; homes built before 2007 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:49:32.872501 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 9 sales 2007 8 sales 2008 7 sales After 2008 6 sales 0 20 40 60 59 55 54 49 Days on market, median

The median is 49 days for homes built after 2008 and 59 days for homes built before 2007. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:49:32.894389 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2007 9 sales 2007 8 sales 2008 7 sales After 2008 6 sales 0.0% 5.0% 10.0% 6.4% 10.6% 8.3% 6.3% Discount from original list, average

The average is 6.3% for homes built after 2008 and 6.4% for homes built before 2007. It does not move in a straight line; homes built 2007 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:49:32.919698 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% 44 78 11 62 62 0 71 100 0 50 83 0 Before 2007 2007 2008 After 2008

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

  • 50% of homes built after 2008 had a price cut before sale, against 44% of homes built before 2007. Defined in 8.1.7.
  • 83% of homes built after 2008 had the seller pay closing costs or repairs, against 78% of homes built before 2007. Defined in 8.1.8.
  • 0% of homes built after 2008 have a view, against 11% 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 20079 sales20078 sales20087 salesAfter 20086 salesAll30 salesReal difference?
Net sale price average$361,013$336,620$325,810$360,368$346,165unclear
Net price per SF average$201$198$200$215$203unclear
Living area average1,8241,7361,6561,7361,744unclear
Year built median20062007200820112007by design

5.10 The numbers: selling

Before 20079 sales20078 sales20087 salesAfter 20086 salesAll30 salesReal difference?
Days on market median5955544952unclear
Discount from original list average6.4%10.6%8.3%6.3%7.9%unclear
Price cut before sale44%62%71%50%57%unclear
Seller paid closing costs or repairs78%62%100%83%80%unclear
Has a view11%0%0%0%3%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.

2026-10-26T07:49:32.938315 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 1 29 30 sales Sales per group View: 1 sales (3%) No view: 29 sales (97%)
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

2026-10-26T07:49:32.954971 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 29 sales $0K $100K $200K $300K $400K $316K $347K Net sale price, average

The average is $316K for homes with a view and $347K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T07:49:32.973377 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 29 sales $0 $100 $200 $247 $201 Net price per SF, average

The average is $247 per SF for homes with a view and $201 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T07:49:33.017632 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 29 sales 0 500 1,000 1,500 2,000 1,277 1,760 Living area (SF), average

The average is 1,277 SF for homes with a view and 1,760 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T07:49:33.037088 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 29 sales 2005 2006 2007 2008 2005 2007 Year built: median (dot) and middle half (bar)

The median is 2005 for homes with a view and 2007 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T07:49:33.055346 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 29 sales 0 20 40 60 59 50 Days on market, median

The median is 59 days for homes with a view and 50 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

2026-10-26T07:49:33.074404 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 29 sales 0.0% 2.5% 5.0% 7.5% 10.0% 9.7% 7.9% Discount from original list, average

The average is 9.7% for homes with a view and 7.9% 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

2026-10-26T07:49:33.093420 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 100 100 55 79 View No view

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

  • 100% of homes with a view had a price cut before sale, against 55% 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 79% 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

View1 salesNo view29 salesAll30 sales
Net sale price average$316,000$347,205$346,165
Net price per SF average$247$201$203
Living area average1,2771,7601,744
Year built median200520072007

6.11 The numbers: selling

View1 salesNo view29 salesAll30 sales
Days on market median595052
Discount from original list average9.7%7.9%7.9%
Price cut before sale100%55%57%
Seller paid closing costs or repairs100%79%80%

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 Cedar Park Towncenter.

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 $346,165; median $344,500; standard deviation $37,737; middle half (25th–75th percentile) $316,826–$368,288; lowest $287,000, highest $450,000. 24 sales had a seller payment; their median payment was $5,625.

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 $203; median $194; standard deviation $30; middle half (25th–75th percentile) $179–$234; lowest $155, highest $252.

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 1,744; median 1,843; standard deviation 323; middle half (25th–75th percentile) 1,446–1,986; lowest 1,277, highest 2,339.

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 2007; standard deviation 2; middle half (25th–75th percentile) 2006–2008; lowest 2004, highest 2014.

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 67; median 52; standard deviation 66; middle half (25th–75th percentile) 26–89; lowest 2, highest 313. 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 7.9%; median 7.4%; standard deviation 5.1%; middle half (25th–75th percentile) 3.5%–12.5%; lowest 0.4%, highest 17.2%. 0 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
17 of 30 resale sales (56.7%).

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
24 of 30 resale sales (80.0%).

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
1 sales with a view, 29 without, 0 unclassified. Most common View entries: None 21, Neighborhood 8, City 1.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. Filter: StandardStatus = Closed, PropertyType = Residential, City = Cedar Park, SubdivisionName contains any of “cedar park towncenter”, “cedar park town center” (case-insensitive). A record is kept when its subdivision name belongs to the Cedar Park Towncenter family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 35 closed Cedar Park Towncenter records over the prior year, in ZIP 78613. 16 subdivision spellings kept, the most common: Cedar Park Towncenter Sec 5 (5); Cedar Park Towncenter Sec 7 (5); Cedar Park Towncenter Sec 10 (4); Cedar Park Towncenter Sec 4 (4); Cedar Park Towncenter Sec 9 (3); Cedar Park Towncenter Sec 2E (3); Cedar Park Towncenter Sec 2B (2); Cedar Park Town Center Condo (1); Cedar Park Towncenter Sec 11 (1); Cedar Park Towncenter Sec 2A (1); Cedar Park Towncenter Sec 6 (1); Cedar Park Towncenter Sec 1 (1); and 4 more (4 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 23 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
5 sale(s) other than single-family homes (condo, townhome and similar)

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 $319K”.
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 $319K: $287,000–$316,200 (8 sales); $319K–$344K: $318,705–$344,000 (7 sales); $345K–$360K: $345,000–$360,000 (7 sales); Over $360K: $371,050–$450,000 (8 sales)
Quartiles by living area: Under 1,460 SF: 1,277–1,441 SF (8 sales); 1,460–1,832 SF: 1,460–1,832 SF (7 sales); 1,854–1,947 SF: 1,854–1,947 SF (7 sales); Over 1,947 SF: 1,999–2,339 SF (8 sales)
Quartiles by year built: Before 2007: 2004–2006 (9 sales); 2007: 2007–2007 (8 sales); 2008: 2008–2008 (7 sales); After 2008: 2009–2014 (6 sales)
View and no view: View: MLS lists a view (1 sales); No view: None or Neighborhood (29 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 $346,165, median $344,500. Days on market: average 67, median 52: 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
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 = 2.5630.4637p < 0.0063Unclearε² = 0.088medium
Living areaKruskal–WallisH = 13.1130.0044p < 0.0063Yesε² = 0.452large
Year builtKruskal–WallisH = 2.4330.4874p < 0.0063Unclearε² = 0.084medium
Days on marketKruskal–WallisH = 4.1530.2460p < 0.0063Unclearε² = 0.143large
Discount from original listKruskal–WallisH = 10.9430.0121p < 0.0063Unclearε² = 0.377large
Price cut before saleChi-squareχ² = 9.0630.0286p < 0.0063UnclearCramér’s V = 0.549large
Seller paid closing costs or repairsChi-squareχ² = 2.1030.5523p < 0.0063UnclearCramér’s V = 0.264small
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 = 17.2730.0006p < 0.0063Yesε² = 0.595large
Net price per SFKruskal–WallisH = 17.8930.0005p < 0.0063Yesε² = 0.617large
Year builtKruskal–WallisH = 1.7830.6189p < 0.0063Unclearε² = 0.061medium
Days on marketKruskal–WallisH = 1.2030.7525p < 0.0063Unclearε² = 0.041small
Discount from original listKruskal–WallisH = 3.2630.3538p < 0.0063Unclearε² = 0.112medium
Price cut before saleChi-squareχ² = 3.2430.3563p < 0.0063UnclearCramér’s V = 0.329medium
Seller paid closing costs or repairsChi-squareχ² = 4.0030.2619p < 0.0063UnclearCramér’s V = 0.365medium
Has a viewChi-squareχ² = 2.8430.4162p < 0.0063UnclearCramér’s V = 0.308medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 4.6230.2021p < 0.0063Unclearε² = 0.159large
Net price per SFKruskal–WallisH = 1.1930.7558p < 0.0063Unclearε² = 0.041small
Living areaKruskal–WallisH = 1.5830.6637p < 0.0063Unclearε² = 0.055small
Days on marketKruskal–WallisH = 0.4730.9257p < 0.0063Unclearε² = 0.016small
Discount from original listKruskal–WallisH = 3.1830.3645p < 0.0063Unclearε² = 0.110medium
Price cut before saleChi-squareχ² = 1.3930.7083p < 0.0063UnclearCramér’s V = 0.215small
Seller paid closing costs or repairsChi-squareχ² = 3.3530.3406p < 0.0063UnclearCramér’s V = 0.334medium
Has a viewChi-squareχ² = 2.4130.4911p < 0.0063UnclearCramér’s V = 0.284small

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); 5 sale(s) other than single-family homes (condo, townhome and similar). 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.