ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Twin Creeks Country Club Sec 2

Cedar Park, TX 78613
Resale homes · closed Oct 31 – Oct 30, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 31, 2026 · 7:14 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
27
single-family resale homes
Median net sale price
$683,075
average $746,072
Median net price per SF
$223
average $228
Median days on market
38 days
average 64 days
1. SummaryResale homes · 27 sales · October 31, 2025 – October 30, 2026

This study looks at the 27 resale homes sold in Twin Creeks Country Club Sec 2 in the 365 days to October 30, 2026. A full year is used because only 13 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 sold27 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 $615K · 7 sales$615K–$683K · 7 sales$694K–$850K · 6 salesOver $850K · 7 sales
3. Quartiles by net sale priceResale homes · 27 sales · October 31, 2025 – October 30, 2026

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

2026-10-31T07:15:10.403479 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 6 7 27 sales Sales per group Under $615K: 7 sales (26%) $615K–$683K: 7 sales (26%) $694K–$850K: 6 sales (22%) Over $850K: 7 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 $615K$615K–$683K$694K–$850KOver $850K
Higher-priced homes Over $850K
  • Are much larger.
Lower-priced homes Under $615K
  • 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 $615K$615K–$683K$694K–$850KOver $850KReal difference?
Net price per SF$229 per SF$207 per SF$228 per SF$250 per SFunclear
Living area2,535 SFSmallest3,152 SF3,409 SF4,040 SFLargest✓ large
Year built2005200520052004unclear
Days on market47 days42 days20 days38 daysunclear
Discount from original list9.8%7.5%4.4%5.0%unclear
Price cut before sale71%57%33%43%unclear
Seller paid closing costs or repairs57%86%67%86%unclear
Has a view14%14%0%43%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

2026-10-31T07:15:10.433576 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $615K 7 sales $615K– $683K 7 sales $694K– $850K 6 sales Over $850K 7 sales $0 $100 $200 $229 $207 $228 $250 Net price per SF, average

The average is $250 per SF for homes over $850K and $229 per SF for homes under $615K. It does not move in a straight line; homes over $850K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $850K are about 1,510 SF (59%) larger than homes under $615K

2026-10-31T07:15:10.456217 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $615K 7 sales $615K– $683K 7 sales $694K– $850K 6 sales Over $850K 7 sales 0 2,000 4,000 2,535 3,152 3,409 4,040 Living area (SF), average

The average is 4,040 SF for homes over $850K and 2,535 SF for homes under $615K. 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

2026-10-31T07:15:10.480028 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $615K 7 sales $615K– $683K 7 sales $694K– $850K 6 sales Over $850K 7 sales 2004 2005 2006 2005 2005 2005 2004 Year built: median (dot) and middle half (bar)

The median is 2004 for homes over $850K and 2005 for homes under $615K. It falls 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

2026-10-31T07:15:10.503412 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $615K 7 sales $615K– $683K 7 sales $694K– $850K 6 sales Over $850K 7 sales 0 20 40 47 42 20 38 Days on market, median

The median is 38 days for homes over $850K and 47 days for homes under $615K. It does not move in a straight line; homes under $615K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-31T07:15:10.526202 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $615K 7 sales $615K– $683K 7 sales $694K– $850K 6 sales Over $850K 7 sales 0.0% 5.0% 10.0% 9.8% 7.5% 4.4% 5.0% Discount from original list, average

The average is 5.0% for homes over $850K and 9.8% for homes under $615K. It does not move in a straight line; homes under $615K 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

2026-10-31T07:15:10.557344 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% 71 57 14 57 86 14 33 67 0 43 86 43 Under $615K $615K–$683K $694K–$850K Over $850K

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

  • 43% of homes over $850K had a price cut before sale, against 71% of homes under $615K. Defined in 8.1.7.
  • 86% of homes over $850K had the seller pay closing costs or repairs, against 57% of homes under $615K. Defined in 8.1.8.
  • 43% of homes over $850K have a view, against 14% of homes under $615K. 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 $615K7 sales$615K–$683K7 sales$694K–$850K6 salesOver $850K7 salesAll27 salesReal difference?
Net sale price average$566,518$647,438$770,625$1,003,214$746,072by design
Net price per SF average$229$207$228$250$228unclear
Living area average2,5353,1523,4094,0403,279✓ large
Year built median20052005200520042005unclear

3.10 The numbers: selling

Under $615K7 sales$615K–$683K7 sales$694K–$850K6 salesOver $850K7 salesAll27 salesReal difference?
Days on market median4742203838unclear
Discount from original list average9.8%7.5%4.4%5.0%6.8%unclear
Price cut before sale71%57%33%43%52%unclear
Seller paid closing costs or repairs57%86%67%86%74%unclear
Has a view14%14%0%43%19%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 · 27 sales · October 31, 2025 – October 30, 2026

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

2026-10-31T07:15:10.580805 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 6 7 27 sales Sales per group Under 2,906 SF: 7 sales (26%) 2,906–3,336 SF: 7 sales (26%) 3,377–3,672 SF: 6 sales (22%) Over 3,672 SF: 7 sales (26%)
Bottom line

4.1 Key differences

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

Under 2,906 SF2,906–3,336 SF3,377–3,672 SFOver 3,672 SF
Larger homes Over 3,672 SF
  • Sell for much more.
Smaller homes Under 2,906 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 2,906 SF2,906–3,336 SF3,377–3,672 SFOver 3,672 SFReal difference?
Net sale price$580KLowest$682K$737K$984KHighest✓ large
Net price per SF$241 per SF$218 per SF$208 per SF$244 per SFunclear
Year built2005200520052004unclear
Days on market42 days35 days52 days38 daysunclear
Discount from original list7.7%5.8%9.1%4.7%unclear
Price cut before sale57%57%50%43%unclear
Seller paid closing costs or repairs71%86%67%71%unclear
Has a view14%0%17%43%unclear

4.3 Homes over 3,672 SF sell for about $404K (70%) more than homes under 2,906 SF

2026-10-31T07:15:10.602884 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,906 SF 7 sales 2,906– 3,336 SF 7 sales 3,377– 3,672 SF 6 sales Over 3,672 SF 7 sales $0K $500K $1.00M $580K $682K $737K $984K Net sale price, average

The average is $984K for homes over 3,672 SF and $580K for homes under 2,906 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-31T07:15:10.627861 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,906 SF 7 sales 2,906– 3,336 SF 7 sales 3,377– 3,672 SF 6 sales Over 3,672 SF 7 sales $0 $100 $200 $241 $218 $208 $244 Net price per SF, average

The average is $244 per SF for homes over 3,672 SF and $241 per SF for homes under 2,906 SF. It does not move in a straight line; homes over 3,672 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-31T07:15:10.651226 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,906 SF 7 sales 2,906– 3,336 SF 7 sales 3,377– 3,672 SF 6 sales Over 3,672 SF 7 sales 2004 2005 2006 2005 2005 2005 2004 Year built: median (dot) and middle half (bar)

The median is 2004 for homes over 3,672 SF and 2005 for homes under 2,906 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-31T07:15:10.674409 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,906 SF 7 sales 2,906– 3,336 SF 7 sales 3,377– 3,672 SF 6 sales Over 3,672 SF 7 sales 0 20 40 60 42 35 52 38 Days on market, median

The median is 38 days for homes over 3,672 SF and 42 days for homes under 2,906 SF. It does not move in a straight line; homes 3,377–3,672 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-31T07:15:10.697800 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,906 SF 7 sales 2,906– 3,336 SF 7 sales 3,377– 3,672 SF 6 sales Over 3,672 SF 7 sales 0.0% 5.0% 10.0% 7.7% 5.8% 9.1% 4.7% Discount from original list, average

The average is 4.7% for homes over 3,672 SF and 7.7% for homes under 2,906 SF. It does not move in a straight line; homes 3,377–3,672 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

2026-10-31T07:15:10.725453 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% 57 71 14 57 86 0 50 67 17 43 71 43 Under 2,906 SF 2,906–3,336 SF 3,377–3,672 SF Over 3,672 SF

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

  • 43% of homes over 3,672 SF had a price cut before sale, against 57% of homes under 2,906 SF. Defined in 8.1.7.
  • 71% of homes over 3,672 SF had the seller pay closing costs or repairs, against 71% of homes under 2,906 SF. Defined in 8.1.8.
  • 43% of homes over 3,672 SF have a view, against 14% of homes under 2,906 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 2,906 SF7 sales2,906–3,336 SF7 sales3,377–3,672 SF6 salesOver 3,672 SF7 salesAll27 salesReal difference?
Net sale price average$579,804$682,009$736,958$984,214$746,072✓ large
Net price per SF average$241$218$208$244$228unclear
Living area average2,4143,1433,5474,0533,279by design
Year built median20052005200520042005unclear

4.10 The numbers: selling

Under 2,906 SF7 sales2,906–3,336 SF7 sales3,377–3,672 SF6 salesOver 3,672 SF7 salesAll27 salesReal difference?
Days on market median4235523838unclear
Discount from original list average7.7%5.8%9.1%4.7%6.8%unclear
Price cut before sale57%57%50%43%52%unclear
Seller paid closing costs or repairs71%86%67%71%74%unclear
Has a view14%0%17%43%19%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 · 27 sales · October 31, 2025 – October 30, 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.

2026-10-31T07:15:10.746584 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 8 8 7 27 sales Sales per group Before 2004: 4 sales (15%) 2004: 8 sales (30%) 2005: 8 sales (30%) After 2005: 7 sales (26%)
Bottom line: too few sales to test.

5.1 Key differences

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

5.3 Net sale price: described, not tested

2026-10-31T07:15:10.768680 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 4 sales 2004 8 sales 2005 8 sales After 2005 7 sales $0K $250K $500K $750K $1.00M $773K $869K $704K $638K Net sale price, average

The average is $638K for homes built after 2005 and $773K for homes built before 2004. It does not move in a straight line; homes built 2004 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-31T07:15:10.792246 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 4 sales 2004 8 sales 2005 8 sales After 2005 7 sales $0 $100 $200 $221 $232 $231 $225 Net price per SF, average

The average is $225 per SF for homes built after 2005 and $221 per SF for homes built before 2004. It does not move in a straight line; homes built 2004 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-31T07:15:10.815050 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 4 sales 2004 8 sales 2005 8 sales After 2005 7 sales 0 1,000 2,000 3,000 4,000 3,472 3,734 3,074 2,885 Living area (SF), average

The average is 2,885 SF for homes built after 2005 and 3,472 SF for homes built before 2004. It does not move in a straight line; homes built 2004 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-31T07:15:10.839802 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 4 sales 2004 8 sales 2005 8 sales After 2005 7 sales 0 25 50 75 100 98 30 34 35 Days on market, median

The median is 35 days for homes built after 2005 and 98 days for homes built before 2004. It does not move in a straight line; homes built before 2004 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-31T07:15:10.862509 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2004 4 sales 2004 8 sales 2005 8 sales After 2005 7 sales 0.0% 5.0% 10.0% 11.8% 5.0% 6.6% 6.1% Discount from original list, average

The average is 6.1% for homes built after 2005 and 11.8% for homes built before 2004. It does not move in a straight line; homes built before 2004 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-31T07:15:10.889858 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 75 50 38 88 25 38 62 0 71 71 14 Before 2004 2004 2005 After 2005

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

  • 71% of homes built after 2005 had a price cut before sale, against 75% of homes built before 2004. Defined in 8.1.7.
  • 71% of homes built after 2005 had the seller pay closing costs or repairs, against 75% of homes built before 2004. Defined in 8.1.8.
  • 14% of homes built after 2005 have a view, against 50% of homes built before 2004. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

5.9 The numbers: price and size

Before 20044 sales20048 sales20058 salesAfter 20057 salesAll27 sales
Net sale price average$773,019$869,235$703,797$638,230$746,072
Net price per SF average$221$232$231$225$228
Living area average3,4723,7343,0742,8853,279
Year built median20032004200520062005

5.10 The numbers: selling

Before 20044 sales20048 sales20058 salesAfter 20057 salesAll27 sales
Days on market median9830343538
Discount from original list average11.8%5.0%6.6%6.1%6.8%
Price cut before sale75%38%38%71%52%
Seller paid closing costs or repairs75%88%62%71%74%
Has a view50%25%0%14%19%

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 · 27 sales · October 31, 2025 – October 30, 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. 3 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-31T07:15:10.909450 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 19 24 sales Sales per group View: 5 sales (21%) No view: 19 sales (79%)
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$887K$707Kunclear
Net price per SF$241 per SF$222 per SFunclear
Living area3,639 SF3,218 SFunclear
Year built20042005unclear
Days on market63 days35 daysunclear
Discount from original list11.4%6.0%unclear
Price cut before sale80%42%unclear
Seller paid closing costs or repairs80%74%unclear

6.3 Net sale price: no clear difference

2026-10-31T07:15:10.927170 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 19 sales $0K $250K $500K $750K $1.00M $887K $707K Net sale price, average

The average is $887K for homes with a view and $707K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-10-31T07:15:10.945952 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 19 sales $0 $100 $200 $241 $222 Net price per SF, average

The average is $241 per SF for homes with a view and $222 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

2026-10-31T07:15:11.016701 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 19 sales 0 1,000 2,000 3,000 4,000 3,639 3,218 Living area (SF), average

The average is 3,639 SF for homes with a view and 3,218 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-31T07:15:11.036910 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 19 sales 2003 2004 2005 2004 2005 Year built: median (dot) and middle half (bar)

The median is 2004 for homes with a view and 2005 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-31T07:15:11.054761 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 19 sales 0 20 40 60 63 35 Days on market, median

The median is 63 days for homes with a view and 35 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-10-31T07:15:11.073845 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 19 sales 0.0% 5.0% 10.0% 11.4% 6.0% Discount from original list, average

The average is 11.4% for homes with a view and 6.0% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-31T07:15:11.092634 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 80 80 42 74 View No view

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

  • 80% of homes with a view had a price cut before sale, against 42% of homes without a view. Defined in 8.1.7.
  • 80% of homes with a view had the seller pay closing costs or repairs, against 74% of homes without a view. Defined in 8.1.8.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance

6.10 The numbers: price and size

View5 salesNo view19 salesAll24 salesReal difference?
Net sale price average$887,100$707,155$744,643unclear
Net price per SF average$241$222$226unclear
Living area average3,6393,2183,306unclear
Year built median200420052005unclear

6.11 The numbers: selling

View5 salesNo view19 salesAll24 salesReal difference?
Days on market median633540unclear
Discount from original list average11.4%6.0%7.1%unclear
Price cut before sale80%42%50%unclear
Seller paid closing costs or repairs80%74%75%unclear

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

7. New constructionBasic statistics · 0 sales · October 31, 2025 – October 30, 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 Twin Creeks Country Club 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
27 resale sales. Average $746,072; median $683,075; standard deviation $181,831; middle half (25th–75th percentile) $603,250–$884,500; lowest $512,000, highest $1,199,500. 20 sales had a seller payment; their median payment was $4,750.

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
27 resale sales. Average $228; median $223; standard deviation $32; middle half (25th–75th percentile) $208–$247; lowest $161, highest $291.

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
27 resale sales. Average 3,279; median 3,336; standard deviation 657; middle half (25th–75th percentile) 2,842–3,676; lowest 2,134, highest 4,489.

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
27 resale sales. Average 2005; median 2005; standard deviation 1; middle half (25th–75th percentile) 2004–2006; lowest 2002, highest 2007.

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
27 resale sales. Average 64; median 38; standard deviation 70; middle half (25th–75th percentile) 18–78; lowest 4, highest 275. 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
27 resale sales. Average 6.8%; median 5.3%; standard deviation 6.3%; middle half (25th–75th percentile) 2.3%–9.4%; lowest −1.4%, highest 25.5%. 2 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
14 of 27 resale sales (51.9%).

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
20 of 27 resale sales (74.1%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
5 sales with a view, 19 without, 3 unclassified. Most common View entries: None 11, Neighborhood 9, Hill Country 5, See Remarks 2, Golf Course 2, Park/Greenbelt 1, Lake 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 “twin creeks country club”, “twin creeks” (case-insensitive). A record is kept when its subdivision name belongs to the Twin Creeks Country Club Sec 2 family, the same rule comparable sales use (it includes Twin Creeks, proven adjacent and priced alike).
The data
Pulled October 31, 2026: 27 closed Twin Creeks Country Club Sec 2 records over the prior year, in ZIP 78613. 12 subdivision spellings kept: Twin Creeks Country Club Sec 4 (6); Twin Creeks Country Club Sec 2 (4); Twin Creeks Country Club Sec 8 (4); Twin Creeks (3); Twin Creeks Country Club (2); Twin Creeks Country Club Sec 5 (2); Twin Creeks Country Club Sec 7 (1); Twin Creeks Country Club Sec 1 (1); Twin Creeks Country Club Sec 9 (1); Twin Creeks Country Club Sec 6 (1); Twin Creeks Country Club Sec 10a Rep (1); Twin Creeks Country Club Sec 06a (1). Names found by the search but not part of Twin Creeks Country Club Sec 2, left out: Reserve At Twin Creeks Sec 15 (2); Reserve At Twin Creeks Sec 13 (2); Twin Creeks - Sunset Ridge (1); Reserve At Twin Creeks Sec 16 The (1); Twin Creeks Cc Sec 08 (1); Reserve At Twin Creeks Sec 16 (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 13 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 31, 2025 to October 30, 2026 inclusive.
The data
27 single-family sales in the window: 27 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
27 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 $615K”.
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 $615K: $512,000–$591,500 (7 sales); $615K–$683K: $615,000–$683,075 (7 sales); $694K–$850K: $694,000–$850,000 (6 sales); Over $850K: $919,000–$1,199,500 (7 sales)
Quartiles by living area: Under 2,906 SF: 2,134–2,779 SF (7 sales); 2,906–3,336 SF: 2,906–3,336 SF (7 sales); 3,377–3,672 SF: 3,377–3,672 SF (6 sales); Over 3,672 SF: 3,681–4,489 SF (7 sales)
Quartiles by year built: Before 2004: 2002–2003 (4 sales); 2004: 2004–2004 (8 sales); 2005: 2005–2005 (8 sales); After 2005: 2006–2007 (7 sales)
View and no view: View: MLS lists a view (5 sales); No view: None or Neighborhood (19 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 $746,072, median $683,075. Days on market: average 64, median 38: 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; 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
2 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 = 8.0730.0447p < 0.0063Unclearε² = 0.310large
Living areaKruskal–WallisH = 18.7930.0003p < 0.0063Yesε² = 0.723large
Year builtKruskal–WallisH = 5.6530.1301p < 0.0063Unclearε² = 0.217large
Days on marketKruskal–WallisH = 2.3030.5130p < 0.0063Unclearε² = 0.088medium
Discount from original listKruskal–WallisH = 4.2830.2325p < 0.0063Unclearε² = 0.165large
Price cut before saleChi-squareχ² = 2.2030.5311p < 0.0063UnclearCramér’s V = 0.286small
Seller paid closing costs or repairsChi-squareχ² = 2.2030.5311p < 0.0063UnclearCramér’s V = 0.286small
Has a viewChi-squareχ² = 4.2830.2330p < 0.0063UnclearCramér’s V = 0.398medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 19.0630.0003p < 0.0063Yesε² = 0.733large
Net price per SFKruskal–WallisH = 7.4430.0591p < 0.0063Unclearε² = 0.286large
Year builtKruskal–WallisH = 4.4130.2209p < 0.0063Unclearε² = 0.169large
Days on marketKruskal–WallisH = 1.6430.6506p < 0.0063Unclearε² = 0.063medium
Discount from original listKruskal–WallisH = 1.5430.6729p < 0.0063Unclearε² = 0.059small
Price cut before saleChi-squareχ² = 0.3930.9419p < 0.0063UnclearCramér’s V = 0.121small
Seller paid closing costs or repairsChi-squareχ² = 0.7230.8694p < 0.0063UnclearCramér’s V = 0.163small
Has a viewChi-squareχ² = 4.4430.2181p < 0.0063UnclearCramér’s V = 0.405medium

8.3.3 Quartiles by year built

Too few sales in a group to test.

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 63.00—0.2965p < 0.0063Unclearrank-biserial r = 0.326medium
Net price per SFMann–Whitney UU = 63.00—0.2965p < 0.0063Unclearrank-biserial r = 0.326medium
Living areaMann–Whitney UU = 68.00—0.1550p < 0.0063Unclearrank-biserial r = 0.432medium
Year builtMann–Whitney UU = 29.00—0.1843p < 0.0063Unclearrank-biserial r = 0.389medium
Days on marketMann–Whitney UU = 56.50—0.5455p < 0.0063Unclearrank-biserial r = 0.189small
Discount from original listMann–Whitney UU = 64.00—0.2647p < 0.0063Unclearrank-biserial r = 0.347medium
Price cut before saleChi-squareχ² = 2.2710.1316p < 0.0063UnclearCramér’s V = 0.308medium
Seller paid closing costs or repairsChi-squareχ² = 0.0810.7717p < 0.0063UnclearCramér’s V = 0.059negligible

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 27 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 31, 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.