ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Williamson Creek

Austin, TX 78744
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 · 4:27 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
15
single-family resale homes
Median net sale price
$289,900
average $276,864
Median net price per SF
$228
average $206
Median days on market
53 days
average 64 days
1. SummaryResale homes · 15 sales · October 26, 2025 – October 25, 2026

This study looks at the 15 resale homes sold in Williamson Creek in the 365 days to October 25, 2026. A full year is used because only 9 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 sold15 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 $200K · 4 sales$200K–$290K · 4 sales$294K–$337K · 3 salesOver $337K · 4 sales
3. Quartiles by net sale priceResale homes · 15 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.

2026-10-26T04:27:19.595267 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 4 3 4 15 sales Sales per group Under $200K: 4 sales (27%) $200K–$290K: 4 sales (27%) $294K–$337K: 3 sales (20%) Over $337K: 4 sales (27%)
Bottom line: too few sales to test.

3.1 Key differences

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

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: described, not tested

2026-10-26T04:27:19.624054 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $200K 4 sales $200K– $290K 4 sales $294K– $337K 3 sales Over $337K 4 sales $0 $100 $200 $135 $215 $241 $241 Net price per SF, average

The average is $241 per SF for homes over $337K and $135 per SF for homes under $200K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

Not tested: too few sales.

3.4 Living area: described, not tested

2026-10-26T04:27:19.646027 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $200K 4 sales $200K– $290K 4 sales $294K– $337K 3 sales Over $337K 4 sales 0 500 1,000 1,500 1,338 1,165 1,316 1,546 Living area (SF), average

The average is 1,546 SF for homes over $337K and 1,338 SF for homes under $200K. It does not move in a straight line; homes over $337K are highest. Defined in 8.1.3.

Not tested: too few sales.

3.5 Year built: described, not tested

2026-10-26T04:27:19.671326 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $200K 4 sales $200K– $290K 4 sales $294K– $337K 3 sales Over $337K 4 sales 1984 1987 1990 1993 1996 1985 1990 1988 1986 Year built: median (dot) and middle half (bar)

The median is 1986 for homes over $337K and 1985 for homes under $200K. It does not move in a straight line; homes $200K–$290K are highest. Defined in 8.1.4.

Not tested: too few sales.

3.6 Days on market: described, not tested

2026-10-26T04:27:19.694790 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $200K 4 sales $200K– $290K 4 sales $294K– $337K 3 sales Over $337K 4 sales 0 50 100 56 50 108 52 Days on market, median

The median is 52 days for homes over $337K and 56 days for homes under $200K. It does not move in a straight line; homes $294K–$337K are highest. Defined in 8.1.5.

Not tested: too few sales.

3.7 Discount from original list: described, not tested

2026-10-26T04:27:19.716278 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $200K 4 sales $200K– $290K 4 sales $294K– $337K 3 sales Over $337K 4 sales 0.0% 10.0% 20.0% 30.0% 29.8% 14.8% 11.2% 6.3% Discount from original list, average

The average is 6.3% for homes over $337K and 29.8% for homes under $200K. It falls step by step from the lowest range to the highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T04:27:19.746124 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 0 0 50 75 25 67 33 0 25 50 0 Under $200K $200K–$290K $294K–$337K Over $337K

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

  • 25% of homes over $337K had a price cut before sale, against 25% of homes under $200K. Defined in 8.1.7.
  • 50% of homes over $337K had the seller pay closing costs or repairs, against 0% of homes under $200K. Defined in 8.1.8.
  • 0% of homes over $337K have a view, against 0% of homes under $200K. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

3.9 The numbers: price and size

Under $200K4 sales$200K–$290K4 sales$294K–$337K3 salesOver $337K4 salesAll15 sales
Net sale price average$180,250$250,788$313,450$372,112$276,864
Net price per SF average$135$215$241$241$206
Living area average1,3381,1651,3161,5461,343
Year built median19851990198819861986

3.10 The numbers: selling

Under $200K4 sales$200K–$290K4 sales$294K–$337K3 salesOver $337K4 salesAll15 sales
Days on market median56501085253
Discount from original list average29.8%14.8%11.2%6.3%15.8%
Price cut before sale25%50%67%25%40%
Seller paid closing costs or repairs0%75%33%50%40%
Has a view0%25%0%0%7%

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 · 15 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.

2026-10-26T04:27:19.766923 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 4 3 4 15 sales Sales per group Under 1,202 SF: 4 sales (27%) 1,202–1,288 SF: 4 sales (27%) 1,325–1,468 SF: 3 sales (20%) Over 1,468 SF: 4 sales (27%)
Bottom line: too few sales to test.

4.1 Key differences

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

4.3 Net sale price: described, not tested

2026-10-26T04:27:19.787039 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,202 SF 4 sales 1,202– 1,288 SF 4 sales 1,325– 1,468 SF 3 sales Over 1,468 SF 4 sales $0K $100K $200K $300K $252K $242K $303K $318K Net sale price, average

The average is $318K for homes over 1,468 SF and $252K for homes under 1,202 SF. It does not move in a straight line; homes over 1,468 SF are highest. Defined in 8.1.1.

Not tested: too few sales.

4.4 Net price per SF: described, not tested

2026-10-26T04:27:19.809958 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,202 SF 4 sales 1,202– 1,288 SF 4 sales 1,325– 1,468 SF 3 sales Over 1,468 SF 4 sales $0 $100 $200 $222 $191 $213 $199 Net price per SF, average

The average is $199 per SF for homes over 1,468 SF and $222 per SF for homes under 1,202 SF. It does not move in a straight line; homes under 1,202 SF are highest. Defined in 8.1.2.

Not tested: too few sales.

4.5 Year built: described, not tested

2026-10-26T04:27:19.834260 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,202 SF 4 sales 1,202– 1,288 SF 4 sales 1,325– 1,468 SF 3 sales Over 1,468 SF 4 sales 1984 1987 1990 1993 1996 1996 1987 1986 1985 Year built: median (dot) and middle half (bar)

The median is 1985 for homes over 1,468 SF and 1996 for homes under 1,202 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.4.

Not tested: too few sales.

4.6 Days on market: described, not tested

2026-10-26T04:27:19.857529 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,202 SF 4 sales 1,202– 1,288 SF 4 sales 1,325– 1,468 SF 3 sales Over 1,468 SF 4 sales 0 50 100 50 108 52 50 Days on market, median

The median is 50 days for homes over 1,468 SF and 50 days for homes under 1,202 SF. It does not move in a straight line; homes 1,202–1,288 SF are highest. Defined in 8.1.5.

Not tested: too few sales.

4.7 Discount from original list: described, not tested

2026-10-26T04:27:19.879395 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,202 SF 4 sales 1,202– 1,288 SF 4 sales 1,325– 1,468 SF 3 sales Over 1,468 SF 4 sales 0.0% 10.0% 20.0% 15.5% 23.7% 9.1% 13.3% Discount from original list, average

The average is 13.3% for homes over 1,468 SF and 15.5% for homes under 1,202 SF. It does not move in a straight line; homes 1,202–1,288 SF are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T04:27:19.905019 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 50 25 50 25 0 33 33 0 50 50 0 Under 1,202 SF 1,202–1,288 SF 1,325–1,468 SF Over 1,468 SF

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

  • 50% of homes over 1,468 SF had a price cut before sale, against 25% of homes under 1,202 SF. Defined in 8.1.7.
  • 50% of homes over 1,468 SF had the seller pay closing costs or repairs, against 50% of homes under 1,202 SF. Defined in 8.1.8.
  • 0% of homes over 1,468 SF have a view, against 25% of homes under 1,202 SF. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

4.9 The numbers: price and size

Under 1,202 SF4 sales1,202–1,288 SF4 sales1,325–1,468 SF3 salesOver 1,468 SF4 salesAll15 sales
Net sale price average$251,814$241,812$302,817$317,500$276,864
Net price per SF average$222$191$213$199$206
Living area average1,1361,2601,4081,5841,343
Year built median19961987198619851986

4.10 The numbers: selling

Under 1,202 SF4 sales1,202–1,288 SF4 sales1,325–1,468 SF3 salesOver 1,468 SF4 salesAll15 sales
Days on market median50108525053
Discount from original list average15.5%23.7%9.1%13.3%15.8%
Price cut before sale25%50%33%50%40%
Seller paid closing costs or repairs50%25%33%50%40%
Has a view25%0%0%0%7%

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. Groups by year builtResale homes · 15 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. Only 3 groups are shown: homes here share a few year built values, and no group may hold fewer than 3 sales.

2026-10-26T04:27:19.923510 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 5 6 15 sales Sales per group Before 1985: 4 sales (27%) 1985–1986: 5 sales (33%) After 1986: 6 sales (40%)
Bottom line: too few sales to test.

5.1 Key differences

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

5.3 Net sale price: described, not tested

2026-10-26T04:27:19.942222 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 4 sales 1985– 1986 5 sales After 1986 6 sales $0K $100K $200K $300K $249K $309K $268K Net sale price, average

The average is $268K for homes built after 1986 and $249K for homes built before 1985. It does not move in a straight line; homes built 1985–1986 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T04:27:19.963514 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 4 sales 1985– 1986 5 sales After 1986 6 sales $0 $100 $200 $180 $213 $218 Net price per SF, average

The average is $218 per SF for homes built after 1986 and $180 per SF for homes built before 1985. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T04:27:19.982615 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 4 sales 1985– 1986 5 sales After 1986 6 sales 0 500 1,000 1,500 1,397 1,438 1,227 Living area (SF), average

The average is 1,227 SF for homes built after 1986 and 1,397 SF for homes built before 1985. It does not move in a straight line; homes built 1985–1986 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T04:27:20.002476 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 4 sales 1985– 1986 5 sales After 1986 6 sales 0 50 100 20 52 86 Days on market, median

The median is 86 days for homes built after 1986 and 20 days for homes built before 1985. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T04:27:20.022569 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 4 sales 1985– 1986 5 sales After 1986 6 sales 0.0% 10.0% 20.0% 14.6% 12.4% 19.5% Discount from original list, average

The average is 19.5% for homes built after 1986 and 14.6% for homes built before 1985. It does not move in a straight line; homes built after 1986 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T04:27:20.044939 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 50 0 40 60 0 50 17 17 Before 1985 1985–1986 After 1986

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

  • 50% of homes built after 1986 had a price cut before sale, against 25% of homes built before 1985. Defined in 8.1.7.
  • 17% of homes built after 1986 had the seller pay closing costs or repairs, against 50% of homes built before 1985. Defined in 8.1.8.
  • 17% of homes built after 1986 have a view, against 0% of homes built before 1985. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

5.9 The numbers: price and size

Before 19854 sales1985–19865 salesAfter 19866 salesAll15 sales
Net sale price average$249,000$309,470$268,267$276,864
Net price per SF average$180$213$218$206
Living area average1,3971,4381,2271,343
Year built median1984198619971986

5.10 The numbers: selling

Before 19854 sales1985–19865 salesAfter 19866 salesAll15 sales
Days on market median20528653
Discount from original list average14.6%12.4%19.5%15.8%
Price cut before sale25%40%50%40%
Seller paid closing costs or repairs50%60%17%40%
Has a view0%0%17%7%

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 · 15 sales · October 26, 2025 – October 25, 2026

Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood.

2026-10-26T04:27:20.062045 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 1 14 15 sales Sales per group View: 1 sales (7%) No view: 14 sales (93%)
Bottom line: too few sales to test.

6.1 Key differences

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

6.3 Net sale price: described, not tested

2026-10-26T04:27:20.078232 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 14 sales $0K $100K $200K $300K $200K $282K Net sale price, average

The average is $200K for homes with a view and $282K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T04:27:20.095717 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 14 sales $0 $100 $200 $170 $209 Net price per SF, average

The average is $170 per SF for homes with a view and $209 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T04:27:20.112632 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 14 sales 0 500 1,000 1,500 1,178 1,355 Living area (SF), average

The average is 1,178 SF for homes with a view and 1,355 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T04:27:20.178454 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 14 sales 1984 1987 1990 1993 1996 1997 1986 Year built: median (dot) and middle half (bar)

The median is 1997 for homes with a view and 1986 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T04:27:20.198468 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 14 sales 0 25 50 75 100 85 52 Days on market, median

The median is 85 days for homes with a view and 52 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-26T04:27:20.216113 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 14 sales 0.0% 10.0% 20.0% 30.0% 33.3% 14.6% Discount from original list, average

The average is 33.3% for homes with a view and 14.6% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T04:27:20.235529 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 100 0 36 43 View No view

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

  • 100% of homes with a view had a price cut before sale, against 36% of homes without a view. Defined in 8.1.7.
  • 0% of homes with a view had the seller pay closing costs or repairs, against 43% of homes without a view. Defined in 8.1.8.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View1 salesNo view14 salesAll15 sales
Net sale price average$200,000$282,354$276,864
Net price per SF average$170$209$206
Living area average1,1781,3551,343
Year built median199719861986

6.11 The numbers: selling

View1 salesNo view14 salesAll15 sales
Days on market median855253
Discount from original list average33.3%14.6%15.8%
Price cut before sale100%36%40%
Seller paid closing costs or repairs0%43%40%

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 Williamson 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
15 resale sales. Average $276,864; median $289,900; standard deviation $79,444; middle half (25th–75th percentile) $197,500–$338,675; lowest $170,000, highest $405,000. 6 sales had a seller payment; their median payment was $10,500.

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
15 resale sales. Average $206; median $228; standard deviation $50; middle half (25th–75th percentile) $158–$242; lowest $121, highest $262.

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
15 resale sales. Average 1,343; median 1,288; standard deviation 185; middle half (25th–75th percentile) 1,190–1,488; lowest 1,100, highest 1,664.

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
15 resale sales. Average 1989; median 1986; standard deviation 6; middle half (25th–75th percentile) 1984–1996; lowest 1983, highest 1997.

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
15 resale sales. Average 64; median 53; standard deviation 50; middle half (25th–75th percentile) 20–94; lowest 2, highest 176. 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
15 resale sales. Average 15.8%; median 9.9%; standard deviation 12.6%; middle half (25th–75th percentile) 8.3%–22.1%; lowest 2.4%, highest 43.3%. 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
6 of 15 resale sales (40.0%).

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
6 of 15 resale sales (40.0%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
1 sales with a view, 14 without, 0 unclassified. Most common View entries: None 12, Neighborhood 2, Creek/Stream 1, Trees/Woods 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 “williamson creek” (case-insensitive). A record is kept when its subdivision name belongs to the Williamson Creek family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 15 closed Williamson Creek records over the prior year, in ZIP 78744. 2 subdivision spellings kept: Williamson Creek Sec 02 (9); Williamson Creek Sec 01-A (6). Names found by the search but not part of Williamson Creek, left out: Viewpoint At Williamson Creek (5); Viewpoint At Williamson Creek Ph 01 (2).

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 9 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
15 single-family sales in the window: 15 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
15 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 $200K”.
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 $200K: $170,000–$195,000 (4 sales); $200K–$290K: $200,000–$289,900 (4 sales); $294K–$337K: $294,000–$337,350 (3 sales); Over $337K: $340,000–$405,000 (4 sales)
Quartiles by living area: Under 1,202 SF: 1,100–1,178 SF (4 sales); 1,202–1,288 SF: 1,202–1,288 SF (4 sales); 1,325–1,468 SF: 1,325–1,468 SF (3 sales); Over 1,468 SF: 1,507–1,664 SF (4 sales)
Groups by year built: Before 1985: 1983–1984 (4 sales); 1985–1986: 1985–1986 (5 sales); After 1986: 1988–1997 (6 sales)
View and no view: View: MLS lists a view (1 sales); No view: None or Neighborhood (14 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 $276,864, median $289,900. Days on market: average 64, median 53: 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

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

Too few sales in a group to test.

8.3.2 Quartiles by living area

Too few sales in a group to test.

8.3.3 Groups by year built

Too few sales in a group to test.

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 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 15 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.