ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Oak Creek Ph 2

Leander, TX 78641
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 5:22 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
28
single-family resale homes
Median net sale price
$416,625
average $409,715
Median net price per SF
$184
average $180
Median days on market
87 days
average 106 days
1. SummaryResale homes · 28 sales · October 26, 2025 – October 25, 2026

This study looks at the 28 resale homes sold in Oak Creek Ph 2 in the 365 days to October 25, 2026. A full year is used because only 14 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 sold28 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 $348K · 7 sales$348K–$414K · 7 sales$419K–$467K · 7 salesOver $467K · 7 sales
3. Quartiles by net sale priceResale homes · 28 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.

2026-10-26T05:22:14.499971 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 7 7 28 sales Sales per group Under $348K: 7 sales (25%) $348K–$414K: 7 sales (25%) $419K–$467K: 7 sales (25%) Over $467K: 7 sales (25%)
Bottom line

3.1 Key differences

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

Under $348K$348K–$414K$419K–$467KOver $467K
Higher-priced homes Over $467K
  • Are much larger.
Lower-priced homes Under $348K
  • 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 $348K$348K–$414K$419K–$467KOver $467KReal difference?
Net price per SF$194 per SF$184 per SF$157 per SF$185 per SFunclear
Living area1,627 SFSmallest2,031 SF2,795 SF2,841 SFLargest✓ large
Year built2016201620162016unclear
Days on market72 days38 days151 days113 daysunclear
Discount from original list9.1%6.0%8.4%7.9%unclear
Price cut before sale71%57%71%57%unclear
Seller paid closing costs or repairs71%86%71%57%unclear
Has a view29%14%0%29%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

2026-10-26T05:22:14.528282 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $348K 7 sales $348K– $414K 7 sales $419K– $467K 7 sales Over $467K 7 sales $0 $100 $200 $194 $184 $157 $185 Net price per SF, average

The average is $185 per SF for homes over $467K and $194 per SF for homes under $348K. It does not move in a straight line; homes under $348K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $467K are about 1,210 SF (75%) larger than homes under $348K

2026-10-26T05:22:14.550705 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $348K 7 sales $348K– $414K 7 sales $419K– $467K 7 sales Over $467K 7 sales 0 1,000 2,000 3,000 1,627 2,031 2,795 2,841 Living area (SF), average

The average is 2,841 SF for homes over $467K and 1,627 SF for homes under $348K. 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

2026-10-26T05:22:14.574035 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $348K 7 sales $348K– $414K 7 sales $419K– $467K 7 sales Over $467K 7 sales 2015 2016 2017 2016 2016 2016 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over $467K and 2016 for homes under $348K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:22:14.597592 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $348K 7 sales $348K– $414K 7 sales $419K– $467K 7 sales Over $467K 7 sales 0 50 100 150 72 38 151 113 Days on market, median

The median is 113 days for homes over $467K and 72 days for homes under $348K. It does not move in a straight line; homes $419K–$467K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:22:14.621100 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $348K 7 sales $348K– $414K 7 sales $419K– $467K 7 sales Over $467K 7 sales 0.0% 5.0% 10.0% 9.1% 6.0% 8.4% 7.9% Discount from original list, average

The average is 7.9% for homes over $467K and 9.1% for homes under $348K. It does not move in a straight line; homes under $348K 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

2026-10-26T05:22:14.652434 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 71 29 57 86 14 71 71 0 57 57 29 Under $348K $348K–$414K $419K–$467K Over $467K

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

  • 57% of homes over $467K had a price cut before sale, against 71% of homes under $348K. Defined in 8.1.7.
  • 57% of homes over $467K had the seller pay closing costs or repairs, against 71% of homes under $348K. Defined in 8.1.8.
  • 29% of homes over $467K have a view, against 29% of homes under $348K. 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 $348K7 sales$348K–$414K7 sales$419K–$467K7 salesOver $467K7 salesAll28 salesReal difference?
Net sale price average$314,010$374,196$434,514$516,141$409,715by design
Net price per SF average$194$184$157$185$180unclear
Living area average1,6272,0312,7952,8412,324✓ large
Year built median20162016201620162016unclear

3.10 The numbers: selling

Under $348K7 sales$348K–$414K7 sales$419K–$467K7 salesOver $467K7 salesAll28 salesReal difference?
Days on market median723815111387unclear
Discount from original list average9.1%6.0%8.4%7.9%7.8%unclear
Price cut before sale71%57%71%57%64%unclear
Seller paid closing costs or repairs71%86%71%57%71%unclear
Has a view29%14%0%29%18%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 · 28 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.

2026-10-26T05:22:14.673921 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 7 7 28 sales Sales per group Under 1,861 SF: 7 sales (25%) 1,861–2,163 SF: 7 sales (25%) 2,175–2,745 SF: 7 sales (25%) Over 2,745 SF: 7 sales (25%)
Bottom line

4.1 Key differences

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

Under 1,861 SF1,861–2,163 SF2,175–2,745 SFOver 2,745 SF
Larger homes Over 2,745 SF
  • Sell for much more.
  • Sell for less per square foot.
Smaller homes Under 1,861 SF
  • Sell for much less.
  • Sell for more per square foot.

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 1,861 SF1,861–2,163 SF2,175–2,745 SFOver 2,745 SFReal difference?
Net sale price$318KLowest$388K$453K$480KHighest✓ large
Net price per SF$197 per SFHighest$190 per SF$178 per SF$157 per SFLowest✓ large
Year built2016201620162017unclear
Days on market62 days93 days81 days174 daysunclear
Discount from original list7.2%7.1%6.0%11.0%unclear
Price cut before sale57%71%43%86%unclear
Seller paid closing costs or repairs86%57%57%86%unclear
Has a view29%29%0%14%unclear

4.3 Homes over 2,745 SF sell for about $162K (51%) more than homes under 1,861 SF

2026-10-26T05:22:14.695558 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,861 SF 7 sales 1,861– 2,163 SF 7 sales 2,175– 2,745 SF 7 sales Over 2,745 SF 7 sales $0K $200K $400K $318K $388K $453K $480K Net sale price, average

The average is $480K for homes over 2,745 SF and $318K for homes under 1,861 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 2,745 SF sell for about $40 per SF (21%) less than homes under 1,861 SF

2026-10-26T05:22:14.719056 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,861 SF 7 sales 1,861– 2,163 SF 7 sales 2,175– 2,745 SF 7 sales Over 2,745 SF 7 sales $0 $100 $200 $197 $190 $178 $157 Net price per SF, average

The average is $157 per SF for homes over 2,745 SF and $197 per SF for homes under 1,861 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

2026-10-26T05:22:14.741242 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,861 SF 7 sales 1,861– 2,163 SF 7 sales 2,175– 2,745 SF 7 sales Over 2,745 SF 7 sales 2016 2017 2016 2016 2016 2017 Year built: median (dot) and middle half (bar)

The median is 2017 for homes over 2,745 SF and 2016 for homes under 1,861 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T05:22:14.764288 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,861 SF 7 sales 1,861– 2,163 SF 7 sales 2,175– 2,745 SF 7 sales Over 2,745 SF 7 sales 0 100 200 62 93 81 174 Days on market, median

The median is 174 days for homes over 2,745 SF and 62 days for homes under 1,861 SF. It does not move in a straight line; homes over 2,745 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T05:22:14.786711 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,861 SF 7 sales 1,861– 2,163 SF 7 sales 2,175– 2,745 SF 7 sales Over 2,745 SF 7 sales 0.0% 5.0% 10.0% 7.2% 7.1% 6.0% 11.0% Discount from original list, average

The average is 11.0% for homes over 2,745 SF and 7.2% for homes under 1,861 SF. It does not move in a straight line; homes over 2,745 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

2026-10-26T05:22:14.818865 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 86 29 71 57 29 43 57 0 86 86 14 Under 1,861 SF 1,861–2,163 SF 2,175–2,745 SF Over 2,745 SF

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

  • 86% of homes over 2,745 SF had a price cut before sale, against 57% of homes under 1,861 SF. Defined in 8.1.7.
  • 86% of homes over 2,745 SF had the seller pay closing costs or repairs, against 86% of homes under 1,861 SF. Defined in 8.1.8.
  • 14% of homes over 2,745 SF have a view, against 29% of homes under 1,861 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 1,861 SF7 sales1,861–2,163 SF7 sales2,175–2,745 SF7 salesOver 2,745 SF7 salesAll28 salesReal difference?
Net sale price average$318,061$387,716$452,771$480,312$409,715✓ large
Net price per SF average$197$190$178$157$180✓ large
Living area average1,6212,0362,5523,0862,324by design
Year built median20162016201620172016unclear

4.10 The numbers: selling

Under 1,861 SF7 sales1,861–2,163 SF7 sales2,175–2,745 SF7 salesOver 2,745 SF7 salesAll28 salesReal difference?
Days on market median62938117487unclear
Discount from original list average7.2%7.1%6.0%11.0%7.8%unclear
Price cut before sale57%71%43%86%64%unclear
Seller paid closing costs or repairs86%57%57%86%71%unclear
Has a view29%29%0%14%18%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 · 28 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.

2026-10-26T05:22:14.845107 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 12 5 5 28 sales Sales per group Before 2016: 6 sales (21%) 2016: 12 sales (43%) 2017: 5 sales (18%) After 2017: 5 sales (18%)
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 201620162017After 2017Real difference?
Net sale price$369K$413K$431K$428Kunclear
Net price per SF$173 per SF$187 per SF$174 per SF$181 per SFunclear
Living area2,182 SF2,233 SF2,569 SF2,464 SFunclear
Days on market117 days78 days41 days113 daysunclear
Discount from original list8.9%5.4%9.1%10.9%unclear
Price cut before sale100%42%60%80%unclear
Seller paid closing costs or repairs83%50%100%80%unclear
Has a view33%17%0%20%unclear

5.3 Net sale price: no clear difference

2026-10-26T05:22:14.871231 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2016 6 sales 2016 12 sales 2017 5 sales After 2017 5 sales $0K $200K $400K $369K $413K $431K $428K Net sale price, average

The average is $428K for homes built after 2017 and $369K for homes built before 2016. It does not move in a straight line; homes built 2017 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T05:22:14.902699 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2016 6 sales 2016 12 sales 2017 5 sales After 2017 5 sales $0 $50 $100 $150 $200 $173 $187 $174 $181 Net price per SF, average

The average is $181 per SF for homes built after 2017 and $173 per SF for homes built before 2016. It does not move in a straight line; homes built 2016 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T05:22:14.931446 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2016 6 sales 2016 12 sales 2017 5 sales After 2017 5 sales 0 1,000 2,000 3,000 2,182 2,233 2,569 2,464 Living area (SF), average

The average is 2,464 SF for homes built after 2017 and 2,182 SF for homes built before 2016. It does not move in a straight line; homes built 2017 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T05:22:14.960033 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2016 6 sales 2016 12 sales 2017 5 sales After 2017 5 sales 0 50 100 117 78 41 113 Days on market, median

The median is 113 days for homes built after 2017 and 117 days for homes built before 2016. It does not move in a straight line; homes built before 2016 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T05:22:14.990474 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2016 6 sales 2016 12 sales 2017 5 sales After 2017 5 sales 0.0% 5.0% 10.0% 8.9% 5.4% 9.1% 10.9% Discount from original list, average

The average is 10.9% for homes built after 2017 and 8.9% for homes built before 2016. It does not move in a straight line; homes built after 2017 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

2026-10-26T05:22:15.023846 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 83 33 42 50 17 60 100 0 80 80 20 Before 2016 2016 2017 After 2017

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

  • 80% of homes built after 2017 had a price cut before sale, against 100% of homes built before 2016. Defined in 8.1.7.
  • 80% of homes built after 2017 had the seller pay closing costs or repairs, against 83% of homes built before 2016. Defined in 8.1.8.
  • 20% of homes built after 2017 have a view, against 33% of homes built before 2016. 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 20166 sales201612 sales20175 salesAfter 20175 salesAll28 salesReal difference?
Net sale price average$369,314$413,497$430,755$428,080$409,715unclear
Net price per SF average$173$187$174$181$180unclear
Living area average2,1822,2332,5692,4642,324unclear
Year built median20142016201720182016by design

5.10 The numbers: selling

Before 20166 sales201612 sales20175 salesAfter 20175 salesAll28 salesReal difference?
Days on market median117784111387unclear
Discount from original list average8.9%5.4%9.1%10.9%7.8%unclear
Price cut before sale100%42%60%80%64%unclear
Seller paid closing costs or repairs83%50%100%80%71%unclear
Has a view33%17%0%20%18%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 · 28 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.

2026-10-26T05:22:15.050311 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 22 27 sales Sales per group View: 5 sales (19%) No view: 22 sales (81%)
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$417K$407Kunclear
Net price per SF$191 per SF$179 per SFunclear
Living area2,246 SF2,314 SFunclear
Year built20162016unclear
Days on market108 days74 daysunclear
Discount from original list8.3%7.4%unclear
Price cut before sale80%59%unclear
Seller paid closing costs or repairs60%73%unclear

6.3 Net sale price: no clear difference

2026-10-26T05:22:15.072675 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 22 sales $0K $200K $400K $417K $407K Net sale price, average

The average is $417K for homes with a view and $407K 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

2026-10-26T05:22:15.097473 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 22 sales $0 $50 $100 $150 $200 $191 $179 Net price per SF, average

The average is $191 per SF for homes with a view and $179 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

2026-10-26T05:22:15.172785 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 22 sales 0 1,000 2,000 2,246 2,314 Living area (SF), average

The average is 2,246 SF for homes with a view and 2,314 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T05:22:15.198220 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 22 sales 2015 2016 2017 2016 2016 Year built: median (dot) and middle half (bar)

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

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T05:22:15.222473 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 22 sales 0 50 100 108 74 Days on market, median

The median is 108 days for homes with a view and 74 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

2026-10-26T05:22:15.249417 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 22 sales 0.0% 2.0% 4.0% 6.0% 8.0% 8.3% 7.4% Discount from original list, average

The average is 8.3% 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

2026-10-26T05:22:15.276270 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 80 60 59 73 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 59% of homes without a view. Defined in 8.1.7.
  • 60% of homes with a view had the seller pay closing costs or repairs, against 73% 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 view22 salesAll27 salesReal difference?
Net sale price average$417,010$406,935$408,801unclear
Net price per SF average$191$179$182unclear
Living area average2,2462,3142,302unclear
Year built median201620162016unclear

6.11 The numbers: selling

View5 salesNo view22 salesAll27 salesReal difference?
Days on market median1087481unclear
Discount from original list average8.3%7.4%7.6%unclear
Price cut before sale80%59%63%unclear
Seller paid closing costs or repairs60%73%70%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 Oak Creek Ph 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
28 resale sales. Average $409,715; median $416,625; standard deviation $78,921; middle half (25th–75th percentile) $346,875–$467,721; lowest $274,000, highest $538,000. 20 sales had a seller payment; their median payment was $4,500.

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
28 resale sales. Average $180; median $184; standard deviation $24; middle half (25th–75th percentile) $163–$191; lowest $132, highest $243.

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
28 resale sales. Average 2,324; median 2,169; standard deviation 598; middle half (25th–75th percentile) 1,854–2,760; lowest 1,340, highest 3,538.

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
28 resale sales. Average 2016; median 2016; standard deviation 1; middle half (25th–75th percentile) 2016–2017; lowest 2014, highest 2020.

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
28 resale sales. Average 106; median 87; standard deviation 79; middle half (25th–75th percentile) 36–174; lowest 10, highest 292. 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
28 resale sales. Average 7.8%; median 7.7%; standard deviation 5.7%; middle half (25th–75th percentile) 2.8%–12.9%; lowest 0.0%, highest 20.0%. 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
18 of 28 resale sales (64.3%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
20 of 28 resale sales (71.4%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
5 sales with a view, 22 without, 1 unclassified. Most common View entries: None 16, Neighborhood 7, Park/Greenbelt 3, See Remarks 2, Panoramic 1, Pool 1, Skyline 1, Garden 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 = Leander, SubdivisionName contains any of “oak creek”, “northside mdw”, “northside meadow” (case-insensitive). A record is kept when its subdivision name belongs to the Oak Creek Ph 2 family, the same rule comparable sales use (it includes Northside Mdw Ph 3, Northside Meadow, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 28 closed Oak Creek Ph 2 records over the prior year, in ZIP 78641. 10 subdivision spellings kept: Oak Creek Ph 2 (7); Northside Meadow (7); Northside Mdw Ph 2 (3); Northside Mdw Ph 3 (3); Oak Creek Ph 4 (2); Northside Mdw Ph 1B (2); Oak Creek Ph 5 (1); Northside Mdw Ph 4 (1); Oak Creek Ph 3 (1); Oak Creek (1). Names found by the search but not part of Oak Creek Ph 2, left out: Northside Meadows (3).

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 14 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
28 single-family sales in the window: 28 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
28 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 $348K”.
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 $348K: $274,000–$345,000 (7 sales); $348K–$414K: $347,500–$414,250 (7 sales); $419K–$467K: $419,000–$467,300 (7 sales); Over $467K: $468,985–$538,000 (7 sales)
Quartiles by living area: Under 1,861 SF: 1,340–1,831 SF (7 sales); 1,861–2,163 SF: 1,861–2,163 SF (7 sales); 2,175–2,745 SF: 2,175–2,745 SF (7 sales); Over 2,745 SF: 2,803–3,538 SF (7 sales)
Quartiles by year built: Before 2016: 2014–2015 (6 sales); 2016: 2016–2016 (12 sales); 2017: 2017–2017 (5 sales); After 2017: 2018–2020 (5 sales)
View and no view: View: MLS lists a view (5 sales); No view: None or Neighborhood (22 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 $409,715, median $416,625. Days on market: average 106, median 87: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

In simple terms
Checks whether a measure really differs across the four groups of a slice. It uses each sale's rank, not its value, so a few extreme sales cannot drive the answer.
Statistically
H = [12/(n(n+1))] Σ Rⱼ²/nⱼ − 3(n+1), compared with χ² on k − 1 degrees of freedom (Kruskal & Wallis, 1952). Effect size ε² = H/(n − 1): ≥ .01 small, ≥ .06 medium, ≥ .14 large (Tomczak & Tomczak, 2014). A slice is tested only when every group has at least 5 sales; smaller groups are described, not tested.
The data
Run on every measure in sections 3–5; each result is in 8.3.

8.2.8 Mann–Whitney U test

In simple terms
The same check when there are only two groups: view against no view.
Statistically
Two-sided U test (Mann & Whitney, 1947). Effect size = rank-biserial correlation |1 − 2U/(n₁n₂)|: ≥ .10 small, ≥ .30 medium, ≥ .50 large (Kerby, 2014; Cohen, 1988).
The data
Run on every measure in section 6; results in 8.3.

8.2.9 Chi-square test

In simple terms
Checks whether a yes/no share (price cut, seller payment, view) differs between groups more than chance would.
Statistically
Pearson χ² on the 2 × k table of counts, no continuity correction (Pearson, 1900). Effect size Cramér's V = √(χ²/n): ≥ .10 small, ≥ .30 medium, ≥ .50 large (Cramér, 1946).
The data
Run on the three shares in every slice; results in 8.3.

8.2.10 Real difference (significance)

In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063; Quartiles by year built: m = 8, threshold p < 0.0063; View and no view: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
3 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

In simple terms
Headings and sentences round figures so they read easily; the tables at the end of each section give them in full.
Statistically
Prices in headings round to the nearest $1K; price per SF and days on market to the nearest whole number; living area to the nearest 10 SF; shares and percentage gaps to whole percents.
The data
Days on market is always shown in days.

8.3 Test results

Every test behind every gold box. Statistic, degrees of freedom (df), p-value, the threshold it must beat, and the size of the difference.

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 10.6530.0138p < 0.0063Unclearε² = 0.394large
Living areaKruskal–WallisH = 22.173< 0.0001p < 0.0063Yesε² = 0.821large
Year builtKruskal–WallisH = 1.6330.6518p < 0.0063Unclearε² = 0.061medium
Days on marketKruskal–WallisH = 2.9230.4035p < 0.0063Unclearε² = 0.108medium
Discount from original listKruskal–WallisH = 0.8030.8484p < 0.0063Unclearε² = 0.030small
Price cut before saleChi-squareχ² = 0.6230.8913p < 0.0063UnclearCramér’s V = 0.149small
Seller paid closing costs or repairsChi-squareχ² = 1.4030.7055p < 0.0063UnclearCramér’s V = 0.224small
Has a viewChi-squareχ² = 2.6830.4439p < 0.0063UnclearCramér’s V = 0.309medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 18.7930.0003p < 0.0063Yesε² = 0.696large
Net price per SFKruskal–WallisH = 14.1630.0027p < 0.0063Yesε² = 0.524large
Year builtKruskal–WallisH = 1.8630.6019p < 0.0063Unclearε² = 0.069medium
Days on marketKruskal–WallisH = 2.8530.4157p < 0.0063Unclearε² = 0.105medium
Discount from original listKruskal–WallisH = 2.7430.4328p < 0.0063Unclearε² = 0.102medium
Price cut before saleChi-squareχ² = 3.1130.3748p < 0.0063UnclearCramér’s V = 0.333medium
Seller paid closing costs or repairsChi-squareχ² = 2.8030.4235p < 0.0063UnclearCramér’s V = 0.316medium
Has a viewChi-squareχ² = 2.6830.4439p < 0.0063UnclearCramér’s V = 0.309medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 2.0730.5590p < 0.0063Unclearε² = 0.076medium
Net price per SFKruskal–WallisH = 0.8930.8267p < 0.0063Unclearε² = 0.033small
Living areaKruskal–WallisH = 1.0130.7978p < 0.0063Unclearε² = 0.038small
Days on marketKruskal–WallisH = 0.1030.9923p < 0.0063Unclearε² = 0.004negligible
Discount from original listKruskal–WallisH = 5.3430.1485p < 0.0063Unclearε² = 0.198large
Price cut before saleChi-squareχ² = 6.5930.0864p < 0.0063UnclearCramér’s V = 0.485medium
Seller paid closing costs or repairsChi-squareχ² = 5.3030.1513p < 0.0063UnclearCramér’s V = 0.435medium
Has a viewChi-squareχ² = 2.0930.5531p < 0.0063UnclearCramér’s V = 0.273small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 57.00—0.9254p < 0.0063Unclearrank-biserial r = 0.036negligible
Net price per SFMann–Whitney UU = 63.00—0.6497p < 0.0063Unclearrank-biserial r = 0.145small
Living areaMann–Whitney UU = 48.00—0.6849p < 0.0063Unclearrank-biserial r = 0.127small
Year builtMann–Whitney UU = 41.00—0.3760p < 0.0063Unclearrank-biserial r = 0.255small
Days on marketMann–Whitney UU = 62.00—0.6940p < 0.0063Unclearrank-biserial r = 0.127small
Discount from original listMann–Whitney UU = 60.00—0.7788p < 0.0063Unclearrank-biserial r = 0.091negligible
Price cut before saleChi-squareχ² = 0.7610.3821p < 0.0063UnclearCramér’s V = 0.168small
Seller paid closing costs or repairsChi-squareχ² = 0.3210.5737p < 0.0063UnclearCramér’s V = 0.108small

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 28 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.