ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Greenwood Hills

Austin, TX 78745
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 · 4:39 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
12
single-family resale homes
Median net sale price
$346,250
average $341,258
Median net price per SF
$339
average $321
Median days on market
24 days
average 32 days
1. SummaryResale homes · 12 sales · October 26, 2025 – October 25, 2026

This study looks at the 12 resale homes sold in Greenwood Hills in the 365 days to October 25, 2026. A full year is used because only 7 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 sold12 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 $322K · 3 sales$322K–$342K · 3 sales$350K–$379K · 3 salesOver $379K · 3 sales
3. Quartiles by net sale priceResale homes · 12 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.

2026-10-26T04:40:09.226424 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 3 3 3 12 sales Sales per group Under $322K: 3 sales (25%) $322K–$342K: 3 sales (25%) $350K–$379K: 3 sales (25%) Over $379K: 3 sales (25%)
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

2026-10-26T04:40:09.256570 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $322K 3 sales $322K– $342K 3 sales $350K– $379K 3 sales Over $379K 3 sales $0 $200 $400 $233 $334 $369 $349 Net price per SF, average

The average is $349 per SF for homes over $379K and $233 per SF for homes under $322K. It does not move in a straight line; homes $350K–$379K are highest. Defined in 8.1.2.

Not tested: too few sales.

3.4 Living area: described, not tested

2026-10-26T04:40:09.281488 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $322K 3 sales $322K– $342K 3 sales $350K– $379K 3 sales Over $379K 3 sales 0 500 1,000 1,039 1,011 982 1,238 Living area (SF), average

The average is 1,238 SF for homes over $379K and 1,039 SF for homes under $322K. It does not move in a straight line; homes over $379K are highest. Defined in 8.1.3.

Not tested: too few sales.

3.5 Year built: described, not tested

2026-10-26T04:40:09.306481 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $322K 3 sales $322K– $342K 3 sales $350K– $379K 3 sales Over $379K 3 sales 1966 1968 1970 1965 1965 1967 1970 Year built: median (dot) and middle half (bar)

The median is 1970 for homes over $379K and 1965 for homes under $322K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

Not tested: too few sales.

3.6 Days on market: described, not tested

2026-10-26T04:40:09.330281 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $322K 3 sales $322K– $342K 3 sales $350K– $379K 3 sales Over $379K 3 sales 0 20 40 2 47 21 36 Days on market, median

The median is 36 days for homes over $379K and 2 days for homes under $322K. It does not move in a straight line; homes $322K–$342K are highest. Defined in 8.1.5.

Not tested: too few sales.

3.7 Discount from original list: described, not tested

2026-10-26T04:40:09.352240 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $322K 3 sales $322K– $342K 3 sales $350K– $379K 3 sales Over $379K 3 sales 0.0% 5.0% 10.0% 15.0% 13.7% 7.4% 5.6% 9.3% Discount from original list, average

The average is 9.3% for homes over $379K and 13.7% for homes under $322K. It does not move in a straight line; homes under $322K are 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

2026-10-26T04:40:09.383954 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% 33 67 0 0 67 0 33 33 0 100 100 33 Under $322K $322K–$342K $350K–$379K Over $379K

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

  • 100% of homes over $379K had a price cut before sale, against 33% of homes under $322K. Defined in 8.1.7.
  • 100% of homes over $379K had the seller pay closing costs or repairs, against 67% of homes under $322K. Defined in 8.1.8.
  • 33% of homes over $379K have a view, against 0% of homes under $322K. 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 $322K3 sales$322K–$342K3 sales$350K–$379K3 salesOver $379K3 salesAll12 sales
Net sale price average$241,067$335,000$361,333$427,633$341,258
Net price per SF average$233$334$369$349$321
Living area average1,0391,0119821,2381,067
Year built median19651965196719701966

3.10 The numbers: selling

Under $322K3 sales$322K–$342K3 sales$350K–$379K3 salesOver $379K3 salesAll12 sales
Days on market median247213624
Discount from original list average13.7%7.4%5.6%9.3%9.0%
Price cut before sale33%0%33%100%42%
Seller paid closing costs or repairs67%67%33%100%67%
Has a view0%0%0%33%8%

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 · 12 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.

2026-10-26T04:40:09.405357 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 3 3 3 12 sales Sales per group Under 986 SF: 3 sales (25%) 986–1,009 SF: 3 sales (25%) 1,032–1,098 SF: 3 sales (25%) Over 1,098 SF: 3 sales (25%)
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

2026-10-26T04:40:09.426420 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 986 SF 3 sales 986– 1,009 SF 3 sales 1,032– 1,098 SF 3 sales Over 1,098 SF 3 sales $0K $200K $400K $358K $328K $272K $408K Net sale price, average

The average is $408K for homes over 1,098 SF and $358K for homes under 986 SF. It does not move in a straight line; homes over 1,098 SF are highest. Defined in 8.1.1.

Not tested: too few sales.

4.4 Net price per SF: described, not tested

2026-10-26T04:40:09.449625 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 986 SF 3 sales 986– 1,009 SF 3 sales 1,032– 1,098 SF 3 sales Over 1,098 SF 3 sales $0 $200 $400 $381 $327 $258 $319 Net price per SF, average

The average is $319 per SF for homes over 1,098 SF and $381 per SF for homes under 986 SF. It does not move in a straight line; homes under 986 SF are highest. Defined in 8.1.2.

Not tested: too few sales.

4.5 Year built: described, not tested

2026-10-26T04:40:09.471838 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 986 SF 3 sales 986– 1,009 SF 3 sales 1,032– 1,098 SF 3 sales Over 1,098 SF 3 sales 1964 1966 1968 1969 1965 1964 1965 Year built: median (dot) and middle half (bar)

The median is 1965 for homes over 1,098 SF and 1969 for homes under 986 SF. It does not move in a straight line; homes under 986 SF are highest. Defined in 8.1.4.

Not tested: too few sales.

4.6 Days on market: described, not tested

2026-10-26T04:40:09.494124 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 986 SF 3 sales 986– 1,009 SF 3 sales 1,032– 1,098 SF 3 sales Over 1,098 SF 3 sales 0 20 40 21 47 6 26 Days on market, median

The median is 26 days for homes over 1,098 SF and 21 days for homes under 986 SF. It does not move in a straight line; homes 986–1,009 SF are highest. Defined in 8.1.5.

Not tested: too few sales.

4.7 Discount from original list: described, not tested

2026-10-26T04:40:09.515085 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 986 SF 3 sales 986– 1,009 SF 3 sales 1,032– 1,098 SF 3 sales Over 1,098 SF 3 sales 0.0% 5.0% 10.0% 15.0% 5.7% 6.8% 15.0% 8.5% Discount from original list, average

The average is 8.5% for homes over 1,098 SF and 5.7% for homes under 986 SF. It does not move in a straight line; homes 1,032–1,098 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

2026-10-26T04:40:09.541429 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% 0 0 0 33 100 0 67 67 0 67 100 33 Under 986 SF 986–1,009 SF 1,032–1,098 SF Over 1,098 SF

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

  • 67% of homes over 1,098 SF had a price cut before sale, against 0% of homes under 986 SF. Defined in 8.1.7.
  • 100% of homes over 1,098 SF had the seller pay closing costs or repairs, against 0% of homes under 986 SF. Defined in 8.1.8.
  • 33% of homes over 1,098 SF have a view, against 0% of homes under 986 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 986 SF3 sales986–1,009 SF3 sales1,032–1,098 SF3 salesOver 1,098 SF3 salesAll12 sales
Net sale price average$358,000$327,603$271,797$407,633$341,258
Net price per SF average$381$327$258$319$321
Living area average9419991,0581,2711,067
Year built median19691965196419651966

4.10 The numbers: selling

Under 986 SF3 sales986–1,009 SF3 sales1,032–1,098 SF3 salesOver 1,098 SF3 salesAll12 sales
Days on market median214762624
Discount from original list average5.7%6.8%15.0%8.5%9.0%
Price cut before sale0%33%67%67%42%
Seller paid closing costs or repairs0%100%67%100%67%
Has a view0%0%0%33%8%

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 · 12 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.

2026-10-26T04:40:09.560750 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 3 3 3 12 sales Sales per group Before 1965: 3 sales (25%) 1965: 3 sales (25%) 1967–1969: 3 sales (25%) After 1969: 3 sales (25%)
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

2026-10-26T04:40:09.583043 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1965 3 sales 1965 3 sales 1967– 1969 3 sales After 1969 3 sales $0K $200K $400K $322K $308K $358K $377K Net sale price, average

The average is $377K for homes built after 1969 and $322K for homes built before 1965. It does not move in a straight line; homes built after 1969 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T04:40:09.605747 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1965 3 sales 1965 3 sales 1967– 1969 3 sales After 1969 3 sales $0 $200 $400 $274 $298 $381 $333 Net price per SF, average

The average is $333 per SF for homes built after 1969 and $274 per SF for homes built before 1965. It does not move in a straight line; homes built 1967–1969 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T04:40:09.626768 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1965 3 sales 1965 3 sales 1967– 1969 3 sales After 1969 3 sales 0 500 1,000 1,173 1,033 941 1,123 Living area (SF), average

The average is 1,123 SF for homes built after 1969 and 1,173 SF for homes built before 1965. It does not move in a straight line; homes built before 1965 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T04:40:09.647468 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1965 3 sales 1965 3 sales 1967– 1969 3 sales After 1969 3 sales 0 20 40 36 8 21 26 Days on market, median

The median is 26 days for homes built after 1969 and 36 days for homes built before 1965. It does not move in a straight line; homes built before 1965 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T04:40:09.669168 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1965 3 sales 1965 3 sales 1967– 1969 3 sales After 1969 3 sales 0.0% 5.0% 10.0% 15.0% 13.3% 6.0% 5.7% 10.9% Discount from original list, average

The average is 10.9% for homes built after 1969 and 13.3% for homes built before 1965. It does not move in a straight line; homes built before 1965 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

2026-10-26T04:40:09.693828 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% 67 67 0 0 100 0 0 0 0 100 100 33 Before 1965 1965 1967–1969 After 1969

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

  • 100% of homes built after 1969 had a price cut before sale, against 67% of homes built before 1965. Defined in 8.1.7.
  • 100% of homes built after 1969 had the seller pay closing costs or repairs, against 67% of homes built before 1965. Defined in 8.1.8.
  • 33% of homes built after 1969 have a view, against 0% of homes built before 1965. 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 19653 sales19653 sales1967–19693 salesAfter 19693 salesAll12 sales
Net sale price average$322,467$307,603$358,000$376,964$341,258
Net price per SF average$274$298$381$333$321
Living area average1,1731,0339411,1231,067
Year built median19641965196919701966

5.10 The numbers: selling

Before 19653 sales19653 sales1967–19693 salesAfter 19693 salesAll12 sales
Days on market median368212624
Discount from original list average13.3%6.0%5.7%10.9%9.0%
Price cut before sale67%0%0%100%42%
Seller paid closing costs or repairs67%100%0%100%67%
Has a view0%0%0%33%8%

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 · 12 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.

2026-10-26T04:40:09.712337 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 1 11 12 sales Sales per group View: 1 sales (8%) No view: 11 sales (92%)
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

2026-10-26T04:40:09.728177 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 11 sales $0K $200K $400K $488K $328K Net sale price, average

The average is $488K for homes with a view and $328K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T04:40:09.746672 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 11 sales $0 $100 $200 $300 $400 $368 $317 Net price per SF, average

The average is $368 per SF for homes with a view and $317 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T04:40:09.765751 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 11 sales 0 500 1,000 1,500 1,327 1,044 Living area (SF), average

The average is 1,327 SF for homes with a view and 1,044 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T04:40:09.830301 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 11 sales 1966 1968 1970 1970 1965 Year built: median (dot) and middle half (bar)

The median is 1970 for homes with a view and 1965 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T04:40:09.847872 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 11 sales 0 10 20 30 26 21 Days on market, median

The median is 26 days for homes with a view and 21 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

2026-10-26T04:40:09.867064 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 1 sales No view 11 sales 0.0% 2.5% 5.0% 7.5% 10.0% 9.6% 8.9% Discount from original list, average

The average is 9.6% for homes with a view and 8.9% 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

2026-10-26T04:40:09.887262 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 100 100 36 64 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.
  • 100% of homes with a view had the seller pay closing costs or repairs, against 64% 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 view11 salesAll12 sales
Net sale price average$488,000$327,918$341,258
Net price per SF average$368$317$321
Living area average1,3271,0441,067
Year built median197019651966

6.11 The numbers: selling

View1 salesNo view11 salesAll12 sales
Days on market median262124
Discount from original list average9.6%8.9%9.0%
Price cut before sale100%36%42%
Seller paid closing costs or repairs100%64%67%

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 Greenwood Hills.

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
12 resale sales. Average $341,258; median $346,250; standard deviation $75,323; middle half (25th–75th percentile) $306,973–$379,875; lowest $205,000, highest $488,000. 8 sales had a seller payment; their median payment was $8,900.

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
12 resale sales. Average $321; median $339; standard deviation $64; middle half (25th–75th percentile) $283–$369; lowest $187, highest $403.

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
12 resale sales. Average 1,067; median 1,020; standard deviation 145; middle half (25th–75th percentile) 980–1,101; lowest 920, highest 1,377.

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
12 resale sales. Average 1967; median 1966; standard deviation 3; middle half (25th–75th percentile) 1965–1969; lowest 1964, highest 1970.

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
12 resale sales. Average 32; median 24; standard deviation 31; middle half (25th–75th percentile) 6–50; lowest 0, highest 95. 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
12 resale sales. Average 9.0%; median 8.6%; standard deviation 5.2%; middle half (25th–75th percentile) 5.3%–9.7%; lowest 2.7%, highest 22.6%. 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
5 of 12 resale sales (41.7%).

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
8 of 12 resale sales (66.7%).

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, 11 without, 0 unclassified. Most common View entries: None 9, Neighborhood 3, 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 “greenwood hills” (case-insensitive). A record is kept when its subdivision name belongs to the Greenwood Hills family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 12 closed Greenwood Hills records over the prior year, in ZIP 78745. 7 subdivision spellings kept: Greenwood Hills Sec 06 (3); Greenwood Hills Sec 01 (3); Greenwood Hills Sec 05 (2); Greenwood Hills Sec 02 (1); Greenwood Hills Sec 1 (1); Greenwood Hills (1); Greenwood Hills Sec 03 (1). No other names were found by the search.

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 7 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
12 single-family sales in the window: 12 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
12 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 $322K”.
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 $322K: $205,000–$260,391 (3 sales); $322K–$342K: $322,500–$342,500 (3 sales); $350K–$379K: $350,000–$379,000 (3 sales); Over $379K: $382,500–$488,000 (3 sales)
Quartiles by living area: Under 986 SF: 920–962 SF (3 sales); 986–1,009 SF: 986–1,009 SF (3 sales); 1,032–1,098 SF: 1,032–1,098 SF (3 sales); Over 1,098 SF: 1,110–1,377 SF (3 sales)
Quartiles by year built: Before 1965: 1964–1964 (3 sales); 1965: 1965–1965 (3 sales); 1967–1969: 1967–1969 (3 sales); After 1969: 1970–1970 (3 sales)
View and no view: View: MLS lists a view (1 sales); No view: None or Neighborhood (11 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 $341,258, median $346,250. Days on market: average 32, median 24: 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 Quartiles 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 12 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.