ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

South Creek

Round Rock, TX 78664
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 5:43 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
34
single-family resale homes
Median net sale price
$326,738
average $327,728
Median net price per SF
$216
average $203
Median days on market
38 days
average 82 days
1. SummaryResale homes · 34 sales · October 26, 2025 – October 25, 2026

This study looks at the 34 resale homes sold in South Creek in the 365 days to October 25, 2026. A full year is used because only 20 resale homes sold in the last 180 days. New construction is left out and shown on its own in section 7. The homes are compared four ways: by price, by living area, by year built and with or without a view. The first three are split into four equal groups (quartiles), each named by its range.

Each comparison has its own section (3–6) with everything about it in one place: the key differences, a table of every measure at a glance, the charts and the numbers.

2. Where the resale homes sold34 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 $294K · 8 sales$294K–$325K · 9 sales$329K–$353K · 9 salesOver $353K · 8 sales
3. Quartiles by net sale priceResale homes · 34 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T05:43:22.035695 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 9 9 8 34 sales Sales per group Under $294K: 8 sales (24%) $294K–$325K: 9 sales (26%) $329K–$353K: 9 sales (26%) Over $353K: 8 sales (24%)
Bottom line: no measure differs enough between the groups to rule out chance.

3.1 Key differences

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

3.2 At a glance

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

Under $294K$294K–$325K$329K–$353KOver $353KReal difference?
Net price per SF$170 per SF$207 per SF$220 per SF$211 per SFunclear
Living area1,518 SF1,528 SF1,558 SF2,043 SFunclear
Year built1993198619921997unclear
Days on market60 days40 days122 days28 daysunclear
Discount from original list10.3%6.4%9.6%3.5%unclear
Price cut before sale62%44%56%25%unclear
Seller paid closing costs or repairs25%78%56%88%unclear
Has a view25%11%22%25%unclear

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

3.3 Net price per SF: no clear difference

2026-10-26T05:43:22.064886 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $294K 8 sales $294K– $325K 9 sales $329K– $353K 9 sales Over $353K 8 sales $0 $100 $200 $170 $207 $220 $211 Net price per SF, average

The average is $211 per SF for homes over $353K and $170 per SF for homes under $294K. It does not move in a straight line; homes $329K–$353K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-26T05:43:22.086724 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $294K 8 sales $294K– $325K 9 sales $329K– $353K 9 sales Over $353K 8 sales 0 1,000 2,000 1,518 1,528 1,558 2,043 Living area (SF), average

The average is 2,043 SF for homes over $353K and 1,518 SF for homes under $294K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-26T05:43:22.109382 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $294K 8 sales $294K– $325K 9 sales $329K– $353K 9 sales Over $353K 8 sales 1988 1992 1996 1993 1986 1992 1997 Year built: median (dot) and middle half (bar)

The median is 1997 for homes over $353K and 1993 for homes under $294K. It does not move in a straight line; homes over $353K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:43:22.131768 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $294K 8 sales $294K– $325K 9 sales $329K– $353K 9 sales Over $353K 8 sales 0 50 100 60 40 122 28 Days on market, median

The median is 28 days for homes over $353K and 60 days for homes under $294K. It does not move in a straight line; homes $329K–$353K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:43:22.152953 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $294K 8 sales $294K– $325K 9 sales $329K– $353K 9 sales Over $353K 8 sales 0.0% 5.0% 10.0% 10.3% 6.4% 9.6% 3.5% Discount from original list, average

The average is 3.5% for homes over $353K and 10.3% for homes under $294K. It does not move in a straight line; homes under $294K are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T05:43:22.182187 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 62 25 25 44 78 11 56 56 22 25 88 25 Under $294K $294K–$325K $329K–$353K Over $353K

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

  • 25% of homes over $353K had a price cut before sale, against 62% of homes under $294K. Defined in 8.1.7.
  • 88% of homes over $353K had the seller pay closing costs or repairs, against 25% of homes under $294K. Defined in 8.1.8.
  • 25% of homes over $353K have a view, against 25% of homes under $294K. 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 $294K8 sales$294K–$325K9 sales$329K–$353K9 salesOver $353K8 salesAll34 salesReal difference?
Net sale price average$251,438$308,194$340,116$412,059$327,728by design
Net price per SF average$170$207$220$211$203unclear
Living area average1,5181,5281,5582,0431,655unclear
Year built median19931986199219971993unclear

3.10 The numbers: selling

Under $294K8 sales$294K–$325K9 sales$329K–$353K9 salesOver $353K8 salesAll34 salesReal difference?
Days on market median60401222838unclear
Discount from original list average10.3%6.4%9.6%3.5%7.5%unclear
Price cut before sale62%44%56%25%47%unclear
Seller paid closing costs or repairs25%78%56%88%62%unclear
Has a view25%11%22%25%21%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 · 34 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T05:43:22.202405 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 9 9 8 34 sales Sales per group Under 1,401 SF: 8 sales (24%) 1,401–1,606 SF: 9 sales (26%) 1,609–1,724 SF: 9 sales (26%) Over 1,724 SF: 8 sales (24%)
Bottom line: no measure differs enough between the groups to rule out chance.

4.1 Key differences

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

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 1,401 SF1,401–1,606 SF1,609–1,724 SFOver 1,724 SFReal difference?
Net sale price$296K$310K$341K$364Kunclear
Net price per SF$227 per SF$210 per SF$203 per SF$170 per SFunclear
Year built1994199219921998unclear
Days on market24 days122 days12 days82 daysunclear
Discount from original list4.3%10.1%4.9%10.6%unclear
Price cut before sale38%67%33%50%unclear
Seller paid closing costs or repairs50%56%67%75%unclear
Has a view25%11%33%12%unclear

4.3 Net sale price: no clear difference

2026-10-26T05:43:22.222506 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,401 SF 8 sales 1,401– 1,606 SF 9 sales 1,609– 1,724 SF 9 sales Over 1,724 SF 8 sales $0K $200K $400K $296K $310K $341K $364K Net sale price, average

The average is $364K for homes over 1,724 SF and $296K for homes under 1,401 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-10-26T05:43:22.244789 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,401 SF 8 sales 1,401– 1,606 SF 9 sales 1,609– 1,724 SF 9 sales Over 1,724 SF 8 sales $0 $100 $200 $227 $210 $203 $170 Net price per SF, average

The average is $170 per SF for homes over 1,724 SF and $227 per SF for homes under 1,401 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T05:43:22.268648 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,401 SF 8 sales 1,401– 1,606 SF 9 sales 1,609– 1,724 SF 9 sales Over 1,724 SF 8 sales 1987 1990 1993 1996 1999 1994 1992 1992 1998 Year built: median (dot) and middle half (bar)

The median is 1998 for homes over 1,724 SF and 1994 for homes under 1,401 SF. It does not move in a straight line; homes over 1,724 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T05:43:22.291815 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,401 SF 8 sales 1,401– 1,606 SF 9 sales 1,609– 1,724 SF 9 sales Over 1,724 SF 8 sales 0 50 100 24 122 12 82 Days on market, median

The median is 82 days for homes over 1,724 SF and 24 days for homes under 1,401 SF. It does not move in a straight line; homes 1,401–1,606 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T05:43:22.313688 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,401 SF 8 sales 1,401– 1,606 SF 9 sales 1,609– 1,724 SF 9 sales Over 1,724 SF 8 sales 0.0% 5.0% 10.0% 4.3% 10.1% 4.9% 10.6% Discount from original list, average

The average is 10.6% for homes over 1,724 SF and 4.3% for homes under 1,401 SF. It does not move in a straight line; homes over 1,724 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T05:43:22.339636 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 38 50 25 67 56 11 33 67 33 50 75 12 Under 1,401 SF 1,401–1,606 SF 1,609–1,724 SF Over 1,724 SF

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

  • 50% of homes over 1,724 SF had a price cut before sale, against 38% of homes under 1,401 SF. Defined in 8.1.7.
  • 75% of homes over 1,724 SF had the seller pay closing costs or repairs, against 50% of homes under 1,401 SF. Defined in 8.1.8.
  • 12% of homes over 1,724 SF have a view, against 25% of homes under 1,401 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 1,401 SF8 sales1,401–1,606 SF9 sales1,609–1,724 SF9 salesOver 1,724 SF8 salesAll34 salesReal difference?
Net sale price average$295,906$310,464$341,194$363,824$327,728unclear
Net price per SF average$227$210$203$170$203unclear
Living area average1,3031,4791,6812,1741,655by design
Year built median19941992199219981993unclear

4.10 The numbers: selling

Under 1,401 SF8 sales1,401–1,606 SF9 sales1,609–1,724 SF9 salesOver 1,724 SF8 salesAll34 salesReal difference?
Days on market median24122128238unclear
Discount from original list average4.3%10.1%4.9%10.6%7.5%unclear
Price cut before sale38%67%33%50%47%unclear
Seller paid closing costs or repairs50%56%67%75%62%unclear
Has a view25%11%33%12%21%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 · 34 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T05:43:22.359627 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 11 7 34 sales Sales per group Before 1987: 8 sales (24%) 1987–1992: 8 sales (24%) 1993–1998: 11 sales (32%) After 1998: 7 sales (21%)
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 19871987–19921993–1998After 1998Real difference?
Net sale price$324K$316K$320K$356Kunclear
Net price per SF$219 per SF$195 per SF$213 per SF$178 per SFunclear
Living area1,497 SF1,645 SF1,514 SF2,068 SFunclear
Days on market6 days18 days63 days98 daysunclear
Discount from original list4.4%6.4%7.9%11.7%unclear
Price cut before sale25%38%64%57%unclear
Seller paid closing costs or repairs75%62%45%71%unclear
Has a view12%12%36%14%unclear

5.3 Net sale price: no clear difference

2026-10-26T05:43:22.379683 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1987 8 sales 1987– 1992 8 sales 1993– 1998 11 sales After 1998 7 sales $0K $200K $400K $324K $316K $320K $356K Net sale price, average

The average is $356K for homes built after 1998 and $324K for homes built before 1987. It does not move in a straight line; homes built after 1998 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T05:43:22.402151 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1987 8 sales 1987– 1992 8 sales 1993– 1998 11 sales After 1998 7 sales $0 $100 $200 $219 $195 $213 $178 Net price per SF, average

The average is $178 per SF for homes built after 1998 and $219 per SF for homes built before 1987. It does not move in a straight line; homes built before 1987 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T05:43:22.423129 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1987 8 sales 1987– 1992 8 sales 1993– 1998 11 sales After 1998 7 sales 0 1,000 2,000 1,497 1,645 1,514 2,068 Living area (SF), average

The average is 2,068 SF for homes built after 1998 and 1,497 SF for homes built before 1987. It does not move in a straight line; homes built after 1998 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T05:43:22.445011 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1987 8 sales 1987– 1992 8 sales 1993– 1998 11 sales After 1998 7 sales 0 50 100 6 18 63 98 Days on market, median

The median is 98 days for homes built after 1998 and 6 days for homes built before 1987. It rises 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

2026-10-26T05:43:22.467532 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1987 8 sales 1987– 1992 8 sales 1993– 1998 11 sales After 1998 7 sales 0.0% 5.0% 10.0% 4.4% 6.4% 7.9% 11.7% Discount from original list, average

The average is 11.7% for homes built after 1998 and 4.4% for homes built before 1987. It rises step by step from the lowest range to the highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T05:43:22.493330 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 25 75 12 38 62 12 64 45 36 57 71 14 Before 1987 1987–1992 1993–1998 After 1998

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

  • 57% of homes built after 1998 had a price cut before sale, against 25% of homes built before 1987. Defined in 8.1.7.
  • 71% of homes built after 1998 had the seller pay closing costs or repairs, against 75% of homes built before 1987. Defined in 8.1.8.
  • 14% of homes built after 1998 have a view, against 12% of homes built before 1987. 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 19878 sales1987–19928 sales1993–199811 salesAfter 19987 salesAll34 salesReal difference?
Net sale price average$324,453$316,456$320,182$356,214$327,728unclear
Net price per SF average$219$195$213$178$203unclear
Living area average1,4971,6451,5142,0681,655unclear
Year built median19861992199519991993by design

5.10 The numbers: selling

Before 19878 sales1987–19928 sales1993–199811 salesAfter 19987 salesAll34 salesReal difference?
Days on market median618639838unclear
Discount from original list average4.4%6.4%7.9%11.7%7.5%unclear
Price cut before sale25%38%64%57%47%unclear
Seller paid closing costs or repairs75%62%45%71%62%unclear
Has a view12%12%36%14%21%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 · 34 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. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T05:43:22.512025 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 26 33 sales Sales per group View: 7 sales (21%) No view: 26 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$330K$326Kunclear
Net price per SF$206 per SF$201 per SFunclear
Living area1,618 SF1,665 SFunclear
Year built19961992unclear
Days on market98 days38 daysunclear
Discount from original list8.6%7.4%unclear
Price cut before sale57%46%unclear
Seller paid closing costs or repairs86%54%unclear

6.3 Net sale price: no clear difference

2026-10-26T05:43:22.527632 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 26 sales $0K $100K $200K $300K $330K $326K Net sale price, average

The average is $330K for homes with a view and $326K 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

2026-10-26T05:43:22.545776 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 26 sales $0 $50 $100 $150 $200 $206 $201 Net price per SF, average

The average is $206 per SF for homes with a view and $201 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

2026-10-26T05:43:22.586191 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 26 sales 0 500 1,000 1,500 1,618 1,665 Living area (SF), average

The average is 1,618 SF for homes with a view and 1,665 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T05:43:22.604822 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 26 sales 1987 1990 1993 1996 1996 1992 Year built: median (dot) and middle half (bar)

The median is 1996 for homes with a view and 1992 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T05:43:22.623911 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 26 sales 0 25 50 75 100 98 38 Days on market, median

The median is 98 days for homes with a view and 38 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

2026-10-26T05:43:22.642918 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 26 sales 0.0% 2.5% 5.0% 7.5% 10.0% 8.6% 7.4% Discount from original list, average

The average is 8.6% for homes with a view and 7.4% 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

2026-10-26T05:43:22.661757 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 57 86 46 54 View No view

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

  • 57% of homes with a view had a price cut before sale, against 46% of homes without a view. Defined in 8.1.7.
  • 86% of homes with a view had the seller pay closing costs or repairs, against 54% 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

View7 salesNo view26 salesAll33 salesReal difference?
Net sale price average$330,393$325,755$326,738unclear
Net price per SF average$206$201$202unclear
Living area average1,6181,6651,655unclear
Year built median199619921993unclear

6.11 The numbers: selling

View7 salesNo view26 salesAll33 salesReal difference?
Days on market median983840unclear
Discount from original list average8.6%7.4%7.7%unclear
Price cut before sale57%46%48%unclear
Seller paid closing costs or repairs86%54%61%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 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 South Creek.

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
34 resale sales. Average $327,728; median $326,738; standard deviation $65,329; middle half (25th–75th percentile) $295,500–$351,950; lowest $216,000, highest $525,000. 21 sales had a seller payment; their median payment was $6,500.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
34 resale sales. Average $203; median $216; standard deviation $37; middle half (25th–75th percentile) $170–$228; lowest $117, highest $263.

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
34 resale sales. Average 1,655; median 1,608; standard deviation 427; middle half (25th–75th percentile) 1,402–1,724; lowest 1,200, highest 3,275.

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
34 resale sales. Average 1993; median 1993; standard deviation 5; middle half (25th–75th percentile) 1988–1998; lowest 1985, highest 2001.

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
34 resale sales. Average 82; median 38; standard deviation 94; middle half (25th–75th percentile) 6–136; lowest 2, highest 322. 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
34 resale sales. Average 7.5%; median 6.0%; standard deviation 8.0%; middle half (25th–75th percentile) 1.8%–14.2%; lowest −7.7%, highest 27.0%. 6 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
16 of 34 resale sales (47.1%).

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
21 of 34 resale sales (61.8%).

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
7 sales with a view, 26 without, 1 unclassified. Most common View entries: None 21, Neighborhood 5, Park/Greenbelt 5, Trees/Woods 2, See Remarks 2, Creek/Stream 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 = Round Rock, SubdivisionName contains any of “south creek”, “south crk” (case-insensitive). A record is kept when its subdivision name belongs to the South Creek family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 34 closed South Creek records over the prior year, in ZIP 78664. 18 subdivision spellings kept, the most common: South Creek Sec 10 (5); South Creek Sec 02 (5); South Creek Sec 04 (3); South Creek Sec 12 (3); South Creek Sec 06 (2); South Creek (2); South Creek Sec 16 Amd (2); South Creek Sec 01 (2); South Creek Sec 20 Ph 01 (1); South Creek Sec 14 Amd (1); South Crk Sec 12 (1); South Creek Section 12 (1); and 6 more (6 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 20 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
34 single-family sales in the window: 34 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
34 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 $294K”.
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 $294K: $216,000–$293,500 (8 sales); $294K–$325K: $294,000–$324,950 (9 sales); $329K–$353K: $328,525–$352,600 (9 sales); Over $353K: $357,000–$525,000 (8 sales)
Quartiles by living area: Under 1,401 SF: 1,200–1,360 SF (8 sales); 1,401–1,606 SF: 1,401–1,606 SF (9 sales); 1,609–1,724 SF: 1,609–1,724 SF (9 sales); Over 1,724 SF: 1,751–3,275 SF (8 sales)
Quartiles by year built: Before 1987: 1985–1986 (8 sales); 1987–1992: 1987–1992 (8 sales); 1993–1998: 1993–1998 (11 sales); After 1998: 1999–2001 (7 sales)
View and no view: View: MLS lists a view (7 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 $327,728, median $326,738. Days on market: average 82, 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; 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
0 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 = 7.9330.0475p < 0.0063Unclearε² = 0.240large
Living areaKruskal–WallisH = 6.2930.0982p < 0.0063Unclearε² = 0.191large
Year builtKruskal–WallisH = 4.6530.1996p < 0.0063Unclearε² = 0.141large
Days on marketKruskal–WallisH = 0.6830.8780p < 0.0063Unclearε² = 0.021small
Discount from original listKruskal–WallisH = 3.1730.3665p < 0.0063Unclearε² = 0.096medium
Price cut before saleChi-squareχ² = 2.6130.4551p < 0.0063UnclearCramér’s V = 0.277small
Seller paid closing costs or repairsChi-squareχ² = 7.9530.0471p < 0.0063UnclearCramér’s V = 0.483medium
Has a viewChi-squareχ² = 0.7030.8733p < 0.0063UnclearCramér’s V = 0.143small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 5.8330.1204p < 0.0063Unclearε² = 0.177large
Net price per SFKruskal–WallisH = 8.9130.0306p < 0.0063Unclearε² = 0.270large
Year builtKruskal–WallisH = 5.1630.1605p < 0.0063Unclearε² = 0.156large
Days on marketKruskal–WallisH = 4.6430.2000p < 0.0063Unclearε² = 0.141large
Discount from original listKruskal–WallisH = 4.8530.1832p < 0.0063Unclearε² = 0.147large
Price cut before saleChi-squareχ² = 2.3930.4954p < 0.0063UnclearCramér’s V = 0.265small
Seller paid closing costs or repairsChi-squareχ² = 1.3030.7289p < 0.0063UnclearCramér’s V = 0.196small
Has a viewChi-squareχ² = 1.8030.6141p < 0.0063UnclearCramér’s V = 0.230small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 0.3330.9537p < 0.0063Unclearε² = 0.010small
Net price per SFKruskal–WallisH = 6.7930.0789p < 0.0063Unclearε² = 0.206large
Living areaKruskal–WallisH = 7.0830.0694p < 0.0063Unclearε² = 0.214large
Days on marketKruskal–WallisH = 2.9630.3975p < 0.0063Unclearε² = 0.090medium
Discount from original listKruskal–WallisH = 3.1830.3654p < 0.0063Unclearε² = 0.096medium
Price cut before saleChi-squareχ² = 3.3630.3401p < 0.0063UnclearCramér’s V = 0.314medium
Seller paid closing costs or repairsChi-squareχ² = 2.1130.5497p < 0.0063UnclearCramér’s V = 0.249small
Has a viewChi-squareχ² = 2.4830.4781p < 0.0063UnclearCramér’s V = 0.270small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 104.00—0.5820p < 0.0063Unclearrank-biserial r = 0.143small
Net price per SFMann–Whitney UU = 92.00—0.9828p < 0.0063Unclearrank-biserial r = 0.011negligible
Living areaMann–Whitney UU = 96.00—0.8464p < 0.0063Unclearrank-biserial r = 0.055negligible
Year builtMann–Whitney UU = 116.00—0.2771p < 0.0063Unclearrank-biserial r = 0.275small
Days on marketMann–Whitney UU = 90.00—0.9824p < 0.0063Unclearrank-biserial r = 0.011negligible
Discount from original listMann–Whitney UU = 100.00—0.7143p < 0.0063Unclearrank-biserial r = 0.099negligible
Price cut before saleChi-squareχ² = 0.2710.6056p < 0.0063UnclearCramér’s V = 0.090negligible
Seller paid closing costs or repairsChi-squareχ² = 2.3510.1256p < 0.0063UnclearCramér’s V = 0.267small

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 34 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.