ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Onion Creek

Austin, TX 78747
Resale homes · closed Oct 30 – Oct 29, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 30, 2026 · 7:48 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
31
single-family resale homes
Median net sale price
$552,200
average $600,203
Median net price per SF
$232
average $227
Median days on market
52 days
average 75 days
1. SummaryResale homes · 31 sales · October 30, 2025 – October 29, 2026

This study looks at the 31 resale homes sold in Onion Creek in the 365 days to October 29, 2026. A full year is used because only 19 resale homes sold in the last 180 days. New construction is left out and shown on its own in section 7. The homes are compared four ways: by price, by living area, by year built and with or without a view. The first three are split into four equal groups (quartiles), each named by its range.

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

2. Where the resale homes sold31 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 $520K · 8 sales$520K–$552K · 8 sales$586K–$671K · 7 salesOver $671K · 8 sales
3. Quartiles by net sale priceResale homes · 31 sales · October 30, 2025 – October 29, 2026

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

2026-10-30T07:48:52.937525 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 7 8 31 sales Sales per group Under $520K: 8 sales (26%) $520K–$552K: 8 sales (26%) $586K–$671K: 7 sales (23%) Over $671K: 8 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 $520K$520K–$552K$586K–$671KOver $671K
Higher-priced homes Over $671K
  • Are much larger.
Lower-priced homes Under $520K
  • 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 $520K$520K–$552K$586K–$671KOver $671KReal difference?
Net price per SF$198 per SF$230 per SF$221 per SF$260 per SFunclear
Living area2,248 SFSmallest2,363 SF2,882 SF3,145 SFLargest✓ large
Year built1981198119991984unclear
Days on market50 days13 days141 days24 daysunclear
Discount from original list14.6%4.9%10.2%2.7%unclear
Price cut before sale75%12%71%25%unclear
Seller paid closing costs or repairs12%88%71%50%unclear
Has a view12%25%57%38%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

2026-10-30T07:48:52.967245 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $520K 8 sales $520K– $552K 8 sales $586K– $671K 7 sales Over $671K 8 sales $0 $100 $200 $300 $198 $230 $221 $260 Net price per SF, average

The average is $260 per SF for homes over $671K and $198 per SF for homes under $520K. It does not move in a straight line; homes over $671K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $671K are about 900 SF (40%) larger than homes under $520K

2026-10-30T07:48:52.991300 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $520K 8 sales $520K– $552K 8 sales $586K– $671K 7 sales Over $671K 8 sales 0 1,000 2,000 3,000 2,248 2,363 2,882 3,145 Living area (SF), average

The average is 3,145 SF for homes over $671K and 2,248 SF for homes under $520K. 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

2026-10-30T07:48:53.016829 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $520K 8 sales $520K– $552K 8 sales $586K– $671K 7 sales Over $671K 8 sales 1980 1985 1990 1995 2000 1981 1981 1999 1984 Year built: median (dot) and middle half (bar)

The median is 1984 for homes over $671K and 1981 for homes under $520K. It does not move in a straight line; homes $586K–$671K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-30T07:48:53.041462 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $520K 8 sales $520K– $552K 8 sales $586K– $671K 7 sales Over $671K 8 sales 0 50 100 150 50 13 141 24 Days on market, median

The median is 24 days for homes over $671K and 50 days for homes under $520K. It does not move in a straight line; homes $586K–$671K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-30T07:48:53.064356 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $520K 8 sales $520K– $552K 8 sales $586K– $671K 7 sales Over $671K 8 sales 0.0% 5.0% 10.0% 15.0% 14.6% 4.9% 10.2% 2.7% Discount from original list, average

The average is 2.7% for homes over $671K and 14.6% for homes under $520K. It does not move in a straight line; homes under $520K 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

2026-10-30T07:48:53.095776 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 12 12 12 88 25 71 71 57 25 50 38 Under $520K $520K–$552K $586K–$671K Over $671K

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

  • 25% of homes over $671K had a price cut before sale, against 75% of homes under $520K. Defined in 8.1.7.
  • 50% of homes over $671K had the seller pay closing costs or repairs, against 12% of homes under $520K. Defined in 8.1.8.
  • 38% of homes over $671K have a view, against 12% of homes under $520K. 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 $520K8 sales$520K–$552K8 sales$586K–$671K7 salesOver $671K8 salesAll31 salesReal difference?
Net sale price average$436,519$535,708$623,032$808,406$600,203by design
Net price per SF average$198$230$221$260$227unclear
Living area average2,2482,3632,8823,1452,652✓ large
Year built median19811981199919841983unclear

3.10 The numbers: selling

Under $520K8 sales$520K–$552K8 sales$586K–$671K7 salesOver $671K8 salesAll31 salesReal difference?
Days on market median50131412452unclear
Discount from original list average14.6%4.9%10.2%2.7%8.0%unclear
Price cut before sale75%12%71%25%45%unclear
Seller paid closing costs or repairs12%88%71%50%55%unclear
Has a view12%25%57%38%32%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 · 31 sales · October 30, 2025 – October 29, 2026

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

2026-10-30T07:48:53.117244 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 7 8 31 sales Sales per group Under 2,264 SF: 8 sales (26%) 2,264–2,500 SF: 8 sales (26%) 2,693–2,910 SF: 7 sales (23%) Over 2,910 SF: 8 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 2,264 SF2,264–2,500 SF2,693–2,910 SFOver 2,910 SF
Larger homes Over 2,910 SF
  • Sell for much more.
Smaller homes Under 2,264 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 2,264 SF2,264–2,500 SF2,693–2,910 SFOver 2,910 SFReal difference?
Net sale price$497KLowest$525K$662K$724KHighest✓ large
Net price per SF$240 per SF$220 per SF$236 per SF$214 per SFunclear
Year built1980198119981987unclear
Days on market18 days52 days16 days104 daysunclear
Discount from original list5.9%10.9%7.4%7.9%unclear
Price cut before sale25%50%43%62%unclear
Seller paid closing costs or repairs38%62%86%38%unclear
Has a view12%25%57%38%unclear

4.3 Homes over 2,910 SF sell for about $227K (46%) more than homes under 2,264 SF

2026-10-30T07:48:53.139144 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,264 SF 8 sales 2,264– 2,500 SF 8 sales 2,693– 2,910 SF 7 sales Over 2,910 SF 8 sales $0K $250K $500K $750K $497K $525K $662K $724K Net sale price, average

The average is $724K for homes over 2,910 SF and $497K for homes under 2,264 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

2026-10-30T07:48:53.162862 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,264 SF 8 sales 2,264– 2,500 SF 8 sales 2,693– 2,910 SF 7 sales Over 2,910 SF 8 sales $0 $100 $200 $240 $220 $236 $214 Net price per SF, average

The average is $214 per SF for homes over 2,910 SF and $240 per SF for homes under 2,264 SF. It does not move in a straight line; homes under 2,264 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-30T07:48:53.188726 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,264 SF 8 sales 2,264– 2,500 SF 8 sales 2,693– 2,910 SF 7 sales Over 2,910 SF 8 sales 1980 1985 1990 1995 2000 1980 1981 1998 1987 Year built: median (dot) and middle half (bar)

The median is 1987 for homes over 2,910 SF and 1980 for homes under 2,264 SF. It does not move in a straight line; homes 2,693–2,910 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-30T07:48:53.214219 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,264 SF 8 sales 2,264– 2,500 SF 8 sales 2,693– 2,910 SF 7 sales Over 2,910 SF 8 sales 0 50 100 18 52 16 104 Days on market, median

The median is 104 days for homes over 2,910 SF and 18 days for homes under 2,264 SF. It does not move in a straight line; homes over 2,910 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-30T07:48:53.237689 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,264 SF 8 sales 2,264– 2,500 SF 8 sales 2,693– 2,910 SF 7 sales Over 2,910 SF 8 sales 0.0% 5.0% 10.0% 5.9% 10.9% 7.4% 7.9% Discount from original list, average

The average is 7.9% for homes over 2,910 SF and 5.9% for homes under 2,264 SF. It does not move in a straight line; homes 2,264–2,500 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

2026-10-30T07:48:53.265005 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 38 12 50 62 25 43 86 57 62 38 38 Under 2,264 SF 2,264–2,500 SF 2,693–2,910 SF Over 2,910 SF

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

  • 62% of homes over 2,910 SF had a price cut before sale, against 25% of homes under 2,264 SF. Defined in 8.1.7.
  • 38% of homes over 2,910 SF had the seller pay closing costs or repairs, against 38% of homes under 2,264 SF. Defined in 8.1.8.
  • 38% of homes over 2,910 SF have a view, against 12% of homes under 2,264 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 2,264 SF8 sales2,264–2,500 SF8 sales2,693–2,910 SF7 salesOver 2,910 SF8 salesAll31 salesReal difference?
Net sale price average$497,464$524,704$662,316$724,092$600,203✓ large
Net price per SF average$240$220$236$214$227unclear
Living area average2,0772,3762,7973,3772,652by design
Year built median19801981199819871983unclear

4.10 The numbers: selling

Under 2,264 SF8 sales2,264–2,500 SF8 sales2,693–2,910 SF7 salesOver 2,910 SF8 salesAll31 salesReal difference?
Days on market median18521610452unclear
Discount from original list average5.9%10.9%7.4%7.9%8.0%unclear
Price cut before sale25%50%43%62%45%unclear
Seller paid closing costs or repairs38%62%86%38%55%unclear
Has a view12%25%57%38%32%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 · 31 sales · October 30, 2025 – October 29, 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.

2026-10-30T07:48:53.285825 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 9 6 8 31 sales Sales per group Before 1981: 8 sales (26%) 1981–1983: 9 sales (29%) 1984–1996: 6 sales (19%) After 1996: 8 sales (26%)
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 19811981–19831984–1996After 1996Real difference?
Net sale price$539K$586K$675K$621Kunclear
Net price per SF$229 per SF$218 per SF$218 per SF$243 per SFunclear
Living area2,348 SF2,705 SF3,085 SF2,572 SFunclear
Days on market78 days52 days93 days12 daysunclear
Discount from original list9.2%8.3%10.2%5.0%unclear
Price cut before sale38%56%50%38%unclear
Seller paid closing costs or repairs50%44%50%75%unclear
Has a view38%11%33%50%unclear

5.3 Net sale price: no clear difference

2026-10-30T07:48:53.307883 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1981 8 sales 1981– 1983 9 sales 1984– 1996 6 sales After 1996 8 sales $0K $250K $500K $750K $539K $586K $675K $621K Net sale price, average

The average is $621K for homes built after 1996 and $539K for homes built before 1981. It does not move in a straight line; homes built 1984–1996 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-30T07:48:53.331452 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1981 8 sales 1981– 1983 9 sales 1984– 1996 6 sales After 1996 8 sales $0 $100 $200 $229 $218 $218 $243 Net price per SF, average

The average is $243 per SF for homes built after 1996 and $229 per SF for homes built before 1981. It does not move in a straight line; homes built after 1996 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-30T07:48:53.353302 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1981 8 sales 1981– 1983 9 sales 1984– 1996 6 sales After 1996 8 sales 0 1,000 2,000 3,000 2,348 2,705 3,085 2,572 Living area (SF), average

The average is 2,572 SF for homes built after 1996 and 2,348 SF for homes built before 1981. It does not move in a straight line; homes built 1984–1996 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-30T07:48:53.375815 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1981 8 sales 1981– 1983 9 sales 1984– 1996 6 sales After 1996 8 sales 0 50 100 78 52 93 12 Days on market, median

The median is 12 days for homes built after 1996 and 78 days for homes built before 1981. It does not move in a straight line; homes built 1984–1996 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-30T07:48:53.398918 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1981 8 sales 1981– 1983 9 sales 1984– 1996 6 sales After 1996 8 sales 0.0% 5.0% 10.0% 9.2% 8.3% 10.2% 5.0% Discount from original list, average

The average is 5.0% for homes built after 1996 and 9.2% for homes built before 1981. It does not move in a straight line; homes built 1984–1996 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

2026-10-30T07:48:53.424679 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 38 56 44 11 50 50 33 38 75 50 Before 1981 1981–1983 1984–1996 After 1996

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

  • 38% of homes built after 1996 had a price cut before sale, against 38% of homes built before 1981. Defined in 8.1.7.
  • 75% of homes built after 1996 had the seller pay closing costs or repairs, against 50% of homes built before 1981. Defined in 8.1.8.
  • 50% of homes built after 1996 have a view, against 38% of homes built before 1981. 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 19818 sales1981–19839 sales1984–19966 salesAfter 19968 salesAll31 salesReal difference?
Net sale price average$539,000$586,395$674,616$621,129$600,203unclear
Net price per SF average$229$218$218$243$227unclear
Living area average2,3482,7053,0852,5722,652unclear
Year built median19781982199420001983by design

5.10 The numbers: selling

Before 19818 sales1981–19839 sales1984–19966 salesAfter 19968 salesAll31 salesReal difference?
Days on market median7852931252unclear
Discount from original list average9.2%8.3%10.2%5.0%8.0%unclear
Price cut before sale38%56%50%38%45%unclear
Seller paid closing costs or repairs50%44%50%75%55%unclear
Has a view38%11%33%50%32%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 · 31 sales · October 30, 2025 – October 29, 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. 2 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-30T07:48:53.443320 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 19 29 sales Sales per group View: 10 sales (34%) No view: 19 sales (66%)
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$631K$562Kunclear
Net price per SF$227 per SF$224 per SFunclear
Living area2,811 SF2,526 SFunclear
Year built19961982unclear
Days on market101 days43 daysunclear
Discount from original list8.3%8.8%unclear
Price cut before sale60%42%unclear
Seller paid closing costs or repairs60%58%unclear

6.3 Net sale price: no clear difference

2026-10-30T07:48:53.459947 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 19 sales $0K $200K $400K $600K $631K $562K Net sale price, average

The average is $631K for homes with a view and $562K 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

2026-10-30T07:48:53.478705 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 19 sales $0 $100 $200 $227 $224 Net price per SF, average

The average is $227 per SF for homes with a view and $224 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

2026-10-30T07:48:53.496855 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 19 sales 0 1,000 2,000 3,000 2,811 2,526 Living area (SF), average

The average is 2,811 SF for homes with a view and 2,526 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-30T07:48:53.571258 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 19 sales 1980 1985 1990 1995 1996 1982 Year built: median (dot) and middle half (bar)

The median is 1996 for homes with a view and 1982 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-30T07:48:53.591136 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 19 sales 0 25 50 75 100 101 43 Days on market, median

The median is 101 days for homes with a view and 43 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

2026-10-30T07:48:53.611624 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 10 sales No view 19 sales 0.0% 2.5% 5.0% 7.5% 10.0% 8.3% 8.8% Discount from original list, average

The average is 8.3% for homes with a view and 8.8% 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

2026-10-30T07:48:53.631044 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 60 60 42 58 View No view

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

  • 60% of homes with a view had a price cut before sale, against 42% 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 58% of homes without a view. Defined in 8.1.8.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance

6.10 The numbers: price and size

View10 salesNo view19 salesAll29 salesReal difference?
Net sale price average$630,945$561,939$585,734unclear
Net price per SF average$227$224$225unclear
Living area average2,8112,5262,625unclear
Year built median199619821983unclear

6.11 The numbers: selling

View10 salesNo view19 salesAll29 salesReal difference?
Days on market median1014353unclear
Discount from original list average8.3%8.8%8.6%unclear
Price cut before sale60%42%48%unclear
Seller paid closing costs or repairs60%58%59%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 30, 2025 – October 29, 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 Onion 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
31 resale sales. Average $600,203; median $552,200; standard deviation $163,804; middle half (25th–75th percentile) $509,575–$679,245; lowest $305,000, highest $1,159,999. 17 sales had a seller payment; their median payment was $9,000.

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
31 resale sales. Average $227; median $232; standard deviation $40; middle half (25th–75th percentile) $199–$251; lowest $130, highest $310.

8.1.3 Living area

In simple terms
The heated and cooled space, as listed in the MLS. Garages and porches are not counted.
Statistically
RESO LivingArea, in square feet. Sales under 400 SF are treated as entry errors and left out.
The data
31 resale sales. Average 2,652; median 2,500; standard deviation 573; middle half (25th–75th percentile) 2,260–2,911; lowest 1,799, highest 4,194.

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
31 resale sales. Average 1988; median 1983; standard deviation 11; middle half (25th–75th percentile) 1980–1997; lowest 1974, highest 2018.

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
31 resale sales. Average 75; median 52; standard deviation 76; middle half (25th–75th percentile) 9–123; lowest 0, highest 288. 1 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
31 resale sales. Average 8.0%; median 5.1%; standard deviation 10.4%; middle half (25th–75th percentile) 1.6%–13.2%; lowest −5.5%, highest 45.5%. 4 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 31 resale sales (45.2%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
17 of 31 resale sales (54.8%).

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
10 sales with a view, 19 without, 2 unclassified. Most common View entries: None 16, Golf Course 8, Neighborhood 5, Panoramic 3, Pool 2, Park/Greenbelt 2, Trees/Woods 1, See Remarks 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 = Austin, SubdivisionName contains any of “onion creek” (case-insensitive). A record is kept when its subdivision name belongs to the Onion Creek family, the same rule comparable sales use.
The data
Pulled October 30, 2026: 35 closed Onion Creek records over the prior year, in ZIP 78747. 9 subdivision spellings kept: Onion Creek Add (10); Onion Creek Sec 03 (8); Onion Creek Sec 05-B (4); Onion Creek (3); Onion Creek Sec 01 (3); Onion Creek Sec 05-A (2); Onion Creek Sec 06-A (2); Onion Creek Sec 02 Amd (2); ONION CREEK SEC 5 A (1). Names found by the search but not part of Onion Creek, left out: Cascades at Onion Creek (62); Crossing At Onion Creek Sec 3& (6); Crossing At Onion Creek Sec 01 (5); Crossing At Onion Creek Sec 05 (4); One Onion Creek Condo Amd (3); Courtyards At Onion Creek Condo (2); Legends Way at Onion Creek (2); Crossing At Onion Creek Sec 02 (2); Crossing at Onion Creek (2); Onion Creek Twnhs (1); Onion Creek, Courtyard At Onion Creek (1); ONE ONION CREEK CONDOMINIUMS (1); Onion Creek Condo At Pointe (1); Onion Creek - Shadow Lane Townhomes (1); Greens Onion Creek (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 19 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 30, 2025 to October 29, 2026 inclusive.
The data
31 single-family sales in the window: 31 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
31 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
2 sale(s) other than single-family homes (condo, townhome and similar); 2 sale(s) with concessions above 10% of price

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 $520K”.
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 $520K: $305,000–$499,150 (8 sales); $520K–$552K: $520,000–$552,200 (8 sales); $586K–$671K: $586,000–$671,240 (7 sales); Over $671K: $687,250–$1,159,999 (8 sales)
Quartiles by living area: Under 2,264 SF: 1,799–2,256 SF (8 sales); 2,264–2,500 SF: 2,264–2,500 SF (8 sales); 2,693–2,910 SF: 2,693–2,910 SF (7 sales); Over 2,910 SF: 2,912–4,194 SF (8 sales)
Quartiles by year built: Before 1981: 1974–1980 (8 sales); 1981–1983: 1981–1983 (9 sales); 1984–1996: 1984–1996 (6 sales); After 1996: 1998–2018 (8 sales)
View and no view: View: MLS lists a view (10 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 $600,203, median $552,200. Days on market: average 75, median 52: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

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

8.2.8 Mann–Whitney U test

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

8.2.9 Chi-square test

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

8.2.10 Real difference (significance)

In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063; Quartiles by year built: m = 8, threshold p < 0.0063; 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 = 9.9330.0192p < 0.0063Unclearε² = 0.331large
Living areaKruskal–WallisH = 14.7530.0020p < 0.0063Yesε² = 0.492large
Year builtKruskal–WallisH = 4.8830.1807p < 0.0063Unclearε² = 0.163large
Days on marketKruskal–WallisH = 8.5230.0365p < 0.0063Unclearε² = 0.284large
Discount from original listKruskal–WallisH = 8.1030.0440p < 0.0063Unclearε² = 0.270large
Price cut before saleChi-squareχ² = 9.5930.0224p < 0.0063UnclearCramér’s V = 0.556large
Seller paid closing costs or repairsChi-squareχ² = 10.0930.0178p < 0.0063UnclearCramér’s V = 0.571large
Has a viewChi-squareχ² = 3.7130.2950p < 0.0063UnclearCramér’s V = 0.346medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 12.5630.0057p < 0.0063Yesε² = 0.419large
Net price per SFKruskal–WallisH = 1.9730.5786p < 0.0063Unclearε² = 0.066medium
Year builtKruskal–WallisH = 6.9830.0724p < 0.0063Unclearε² = 0.233large
Days on marketKruskal–WallisH = 2.6730.4448p < 0.0063Unclearε² = 0.089medium
Discount from original listKruskal–WallisH = 0.3830.9436p < 0.0063Unclearε² = 0.013small
Price cut before saleChi-squareχ² = 2.3730.4983p < 0.0063UnclearCramér’s V = 0.277small
Seller paid closing costs or repairsChi-squareχ² = 4.8330.1850p < 0.0063UnclearCramér’s V = 0.395medium
Has a viewChi-squareχ² = 3.7130.2950p < 0.0063UnclearCramér’s V = 0.346medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 2.6930.4420p < 0.0063Unclearε² = 0.090medium
Net price per SFKruskal–WallisH = 2.9130.4057p < 0.0063Unclearε² = 0.097medium
Living areaKruskal–WallisH = 5.5430.1361p < 0.0063Unclearε² = 0.185large
Days on marketKruskal–WallisH = 1.7330.6300p < 0.0063Unclearε² = 0.058small
Discount from original listKruskal–WallisH = 1.0130.7994p < 0.0063Unclearε² = 0.034small
Price cut before saleChi-squareχ² = 0.8330.8426p < 0.0063UnclearCramér’s V = 0.163small
Seller paid closing costs or repairsChi-squareχ² = 1.8430.6067p < 0.0063UnclearCramér’s V = 0.243small
Has a viewChi-squareχ² = 3.1030.3768p < 0.0063UnclearCramér’s V = 0.316medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 133.50—0.0812p < 0.0063Unclearrank-biserial r = 0.405medium
Net price per SFMann–Whitney UU = 93.00—0.9451p < 0.0063Unclearrank-biserial r = 0.021negligible
Living areaMann–Whitney UU = 131.00—0.1033p < 0.0063Unclearrank-biserial r = 0.379medium
Year builtMann–Whitney UU = 112.00—0.4477p < 0.0063Unclearrank-biserial r = 0.179small
Days on marketMann–Whitney UU = 135.00—0.0698p < 0.0063Unclearrank-biserial r = 0.421medium
Discount from original listMann–Whitney UU = 106.00—0.6300p < 0.0063Unclearrank-biserial r = 0.116small
Price cut before saleChi-squareχ² = 0.8410.3593p < 0.0063UnclearCramér’s V = 0.170small
Seller paid closing costs or repairsChi-squareχ² = 0.0110.9129p < 0.0063UnclearCramér’s V = 0.020negligible

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 2 sale(s) other than single-family homes (condo, townhome and similar); 2 sale(s) with concessions above 10% of price. 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 31 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 30, 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.