ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Northwood

Austin, TX 78727
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 · 4:02 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
24
single-family resale homes
Median net sale price
$500,250
average $494,217
Median net price per SF
$291
average $289
Median days on market
21 days
average 64 days
1. SummaryResale homes · 24 sales · October 26, 2025 – October 25, 2026

This study looks at the 24 resale homes sold in Northwood in the 365 days to October 25, 2026. A full year is used because only 12 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 sold24 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 $440K · 6 sales$440K–$492K · 6 sales$509K–$572K · 6 salesOver $572K · 6 sales
3. Quartiles by net sale priceResale homes · 24 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.

2026-10-26T04:02:51.541123 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 6 6 24 sales Sales per group Under $440K: 6 sales (25%) $440K–$492K: 6 sales (25%) $509K–$572K: 6 sales (25%) Over $572K: 6 sales (25%)
Bottom line

3.1 Key differences

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

Under $440K$440K–$492K$509K–$572KOver $572K
Higher-priced homes Over $572K
  • Sell for more per square foot.
Lower-priced homes Under $440K
  • Sell for less per square foot.

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 $440K$440K–$492K$509K–$572KOver $572KReal difference?
Net price per SF$249 per SFLowest$280 per SF$287 per SF$342 per SFHighest✓ large
Living area1,522 SF1,674 SF1,887 SF1,790 SFunclear
Year built1982197919791979unclear
Days on market77 days18 days20 days15 daysunclear
Discount from original list13.2%5.0%1.7%3.0%unclear
Price cut before sale67%33%33%17%unclear
Seller paid closing costs or repairs33%50%83%50%unclear
Has a view17%0%0%17%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 Homes over $572K sell for about $93 per SF (37%) more than homes under $440K

2026-10-26T04:02:51.569327 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $440K 6 sales $440K– $492K 6 sales $509K– $572K 6 sales Over $572K 6 sales $0 $200 $400 $249 $280 $287 $342 Net price per SF, average

The average is $342 per SF for homes over $572K and $249 per SF for homes under $440K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Living area: no clear difference

2026-10-26T04:02:51.591040 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $440K 6 sales $440K– $492K 6 sales $509K– $572K 6 sales Over $572K 6 sales 0 1,000 2,000 1,522 1,674 1,887 1,790 Living area (SF), average

The average is 1,790 SF for homes over $572K and 1,522 SF for homes under $440K. It does not move in a straight line; homes $509K–$572K are highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-26T04:02:51.614867 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $440K 6 sales $440K– $492K 6 sales $509K– $572K 6 sales Over $572K 6 sales 1979 1980 1981 1982 1982 1979 1979 1979 Year built: median (dot) and middle half (bar)

The median is 1979 for homes over $572K and 1982 for homes under $440K. It falls step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T04:02:51.637981 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $440K 6 sales $440K– $492K 6 sales $509K– $572K 6 sales Over $572K 6 sales 0 25 50 75 77 18 20 15 Days on market, median

The median is 15 days for homes over $572K and 77 days for homes under $440K. It does not move in a straight line; homes under $440K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T04:02:51.659680 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $440K 6 sales $440K– $492K 6 sales $509K– $572K 6 sales Over $572K 6 sales 0.0% 5.0% 10.0% 15.0% 13.2% 5.0% 1.7% 3.0% Discount from original list, average

The average is 3.0% for homes over $572K and 13.2% for homes under $440K. It does not move in a straight line; homes under $440K 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

2026-10-26T04:02:51.689742 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 33 17 33 50 0 33 83 0 17 50 17 Under $440K $440K–$492K $509K–$572K Over $572K

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

  • 17% of homes over $572K had a price cut before sale, against 67% of homes under $440K. Defined in 8.1.7.
  • 50% of homes over $572K had the seller pay closing costs or repairs, against 33% of homes under $440K. Defined in 8.1.8.
  • 17% of homes over $572K have a view, against 17% of homes under $440K. 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 $440K6 sales$440K–$492K6 sales$509K–$572K6 salesOver $572K6 salesAll24 salesReal difference?
Net sale price average$369,975$468,378$531,360$607,156$494,217by design
Net price per SF average$249$280$287$342$289✓ large
Living area average1,5221,6741,8871,7901,718unclear
Year built median19821979197919791979unclear

3.10 The numbers: selling

Under $440K6 sales$440K–$492K6 sales$509K–$572K6 salesOver $572K6 salesAll24 salesReal difference?
Days on market median7718201521unclear
Discount from original list average13.2%5.0%1.7%3.0%5.7%unclear
Price cut before sale67%33%33%17%38%unclear
Seller paid closing costs or repairs33%50%83%50%54%unclear
Has a view17%0%0%17%8%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 · 24 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.

2026-10-26T04:02:51.709777 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 6 6 6 24 sales Sales per group Under 1,614 SF: 6 sales (25%) 1,614–1,664 SF: 6 sales (25%) 1,690–1,766 SF: 6 sales (25%) Over 1,766 SF: 6 sales (25%)
Bottom line: no measure differs enough between the groups to rule out chance.

4.1 Key differences

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

4.2 At a glance

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

Under 1,614 SF1,614–1,664 SF1,690–1,766 SFOver 1,766 SFReal difference?
Net sale price$379K$529K$518K$551Kunclear
Net price per SF$267 per SF$323 per SF$301 per SF$267 per SFunclear
Year built1982197919801979unclear
Days on market33 days28 days6 days22 daysunclear
Discount from original list10.2%3.8%0.8%8.0%unclear
Price cut before sale67%17%17%50%unclear
Seller paid closing costs or repairs50%33%83%50%unclear
Has a view17%17%0%0%unclear

4.3 Net sale price: no clear difference

2026-10-26T04:02:51.730389 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,614 SF 6 sales 1,614– 1,664 SF 6 sales 1,690– 1,766 SF 6 sales Over 1,766 SF 6 sales $0K $200K $400K $600K $379K $529K $518K $551K Net sale price, average

The average is $551K for homes over 1,766 SF and $379K for homes under 1,614 SF. It does not move in a straight line; homes over 1,766 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-10-26T04:02:51.752625 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,614 SF 6 sales 1,614– 1,664 SF 6 sales 1,690– 1,766 SF 6 sales Over 1,766 SF 6 sales $0 $100 $200 $300 $267 $323 $301 $267 Net price per SF, average

The average is $267 per SF for homes over 1,766 SF and $267 per SF for homes under 1,614 SF. It does not move in a straight line; homes 1,614–1,664 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T04:02:51.775775 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,614 SF 6 sales 1,614– 1,664 SF 6 sales 1,690– 1,766 SF 6 sales Over 1,766 SF 6 sales 1979 1980 1981 1982 1982 1979 1980 1979 Year built: median (dot) and middle half (bar)

The median is 1979 for homes over 1,766 SF and 1982 for homes under 1,614 SF. It does not move in a straight line; homes under 1,614 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T04:02:51.798138 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,614 SF 6 sales 1,614– 1,664 SF 6 sales 1,690– 1,766 SF 6 sales Over 1,766 SF 6 sales 0 10 20 30 33 28 6 22 Days on market, median

The median is 22 days for homes over 1,766 SF and 33 days for homes under 1,614 SF. It does not move in a straight line; homes under 1,614 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T04:02:51.819495 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,614 SF 6 sales 1,614– 1,664 SF 6 sales 1,690– 1,766 SF 6 sales Over 1,766 SF 6 sales 0.0% 5.0% 10.0% 10.2% 3.8% 0.8% 8.0% Discount from original list, average

The average is 8.0% for homes over 1,766 SF and 10.2% for homes under 1,614 SF. It does not move in a straight line; homes under 1,614 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

2026-10-26T04:02:51.845447 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 50 17 17 33 17 17 83 0 50 50 0 Under 1,614 SF 1,614–1,664 SF 1,690–1,766 SF Over 1,766 SF

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

  • 50% of homes over 1,766 SF had a price cut before sale, against 67% of homes under 1,614 SF. Defined in 8.1.7.
  • 50% of homes over 1,766 SF had the seller pay closing costs or repairs, against 50% of homes under 1,614 SF. Defined in 8.1.8.
  • 0% of homes over 1,766 SF have a view, against 17% of homes under 1,614 SF. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

4.9 The numbers: price and size

Under 1,614 SF6 sales1,614–1,664 SF6 sales1,690–1,766 SF6 salesOver 1,766 SF6 salesAll24 salesReal difference?
Net sale price average$379,104$528,783$518,148$550,833$494,217unclear
Net price per SF average$267$323$301$267$289unclear
Living area average1,4161,6381,7242,0961,718by design
Year built median19821979198019791979unclear

4.10 The numbers: selling

Under 1,614 SF6 sales1,614–1,664 SF6 sales1,690–1,766 SF6 salesOver 1,766 SF6 salesAll24 salesReal difference?
Days on market median332862221unclear
Discount from original list average10.2%3.8%0.8%8.0%5.7%unclear
Price cut before sale67%17%17%50%38%unclear
Seller paid closing costs or repairs50%33%83%50%54%unclear
Has a view17%17%0%0%8%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 · 24 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.

2026-10-26T04:02:51.865357 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 9 3 8 24 sales Sales per group Before 1979: 4 sales (17%) 1979: 9 sales (38%) 1980–1981: 3 sales (12%) After 1981: 8 sales (33%)
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

2026-10-26T04:02:51.885453 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 4 sales 1979 9 sales 1980– 1981 3 sales After 1981 8 sales $0K $200K $400K $600K $497K $536K $478K $452K Net sale price, average

The average is $452K for homes built after 1981 and $497K for homes built before 1979. It does not move in a straight line; homes built 1979 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T04:02:51.907971 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 4 sales 1979 9 sales 1980– 1981 3 sales After 1981 8 sales $0 $100 $200 $300 $279 $300 $294 $281 Net price per SF, average

The average is $281 per SF for homes built after 1981 and $279 per SF for homes built before 1979. It does not move in a straight line; homes built 1979 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T04:02:51.929352 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 4 sales 1979 9 sales 1980– 1981 3 sales After 1981 8 sales 0 1,000 2,000 1,823 1,810 1,612 1,603 Living area (SF), average

The average is 1,603 SF for homes built after 1981 and 1,823 SF for homes built before 1979. It falls step by step from the lowest range to the highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T04:02:51.950679 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 4 sales 1979 9 sales 1980– 1981 3 sales After 1981 8 sales 0 25 50 75 8 21 24 77 Days on market, median

The median is 77 days for homes built after 1981 and 8 days for homes built before 1979. 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

2026-10-26T04:02:51.973273 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 4 sales 1979 9 sales 1980– 1981 3 sales After 1981 8 sales 0.0% 5.0% 10.0% 6.5% 2.9% 3.6% 9.2% Discount from original list, average

The average is 9.2% for homes built after 1981 and 6.5% for homes built before 1979. It does not move in a straight line; homes built after 1981 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

2026-10-26T04:02:51.998128 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 25 25 11 78 0 67 33 0 62 50 12 Before 1979 1979 1980–1981 After 1981

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

  • 62% of homes built after 1981 had a price cut before sale, against 25% of homes built before 1979. Defined in 8.1.7.
  • 50% of homes built after 1981 had the seller pay closing costs or repairs, against 25% of homes built before 1979. Defined in 8.1.8.
  • 12% of homes built after 1981 have a view, against 25% of homes built before 1979. 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 19794 sales19799 sales1980–19813 salesAfter 19818 salesAll24 sales
Net sale price average$496,712$536,175$478,500$451,661$494,217
Net price per SF average$279$300$294$281$289
Living area average1,8231,8101,6121,6031,718
Year built median19761979198119821979

5.10 The numbers: selling

Before 19794 sales19799 sales1980–19813 salesAfter 19818 salesAll24 sales
Days on market median821247721
Discount from original list average6.5%2.9%3.6%9.2%5.7%
Price cut before sale25%11%67%62%38%
Seller paid closing costs or repairs25%78%33%50%54%
Has a view25%0%0%12%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 · 24 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. 2 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T04:02:52.016530 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 2 20 22 sales Sales per group View: 2 sales (9%) No view: 20 sales (91%)
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

2026-10-26T04:02:52.032039 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales $0K $200K $400K $600K $511K $489K Net sale price, average

The average is $511K for homes with a view and $489K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T04:02:52.049443 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales $0 $100 $200 $300 $330 $281 Net price per SF, average

The average is $330 per SF for homes with a view and $281 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T04:02:52.067533 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 0 500 1,000 1,500 2,000 1,537 1,746 Living area (SF), average

The average is 1,537 SF for homes with a view and 1,746 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T04:02:52.141061 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 1979 1980 1981 1982 1981 1980 Year built: median (dot) and middle half (bar)

The median is 1981 for homes with a view and 1980 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T04:02:52.159418 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 0 10 20 10 22 Days on market, median

The median is 10 days for homes with a view and 22 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

2026-10-26T04:02:52.177022 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 0.0% 2.0% 4.0% 6.0% 1.6% 6.3% Discount from original list, average

The average is 1.6% for homes with a view and 6.3% 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

2026-10-26T04:02:52.195426 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 0 0 45 60 View No view

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

  • 0% of homes with a view had a price cut before sale, against 45% 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 60% 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

View2 salesNo view20 salesAll22 sales
Net sale price average$511,250$488,861$490,896
Net price per SF average$330$281$286
Living area average1,5371,7461,727
Year built median198119801980

6.11 The numbers: selling

View2 salesNo view20 salesAll22 sales
Days on market median102221
Discount from original list average1.6%6.3%5.9%
Price cut before sale0%45%41%
Seller paid closing costs or repairs0%60%55%

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 Northwood.

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
24 resale sales. Average $494,217; median $500,250; standard deviation $92,932; middle half (25th–75th percentile) $436,250–$573,000; lowest $320,000, highest $635,000. 13 sales had a seller payment; their median payment was $3,150.

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
24 resale sales. Average $289; median $291; standard deviation $46; middle half (25th–75th percentile) $260–$314; lowest $190, highest $385.

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
24 resale sales. Average 1,718; median 1,677; standard deviation 272; middle half (25th–75th percentile) 1,612–1,784; lowest 1,314, highest 2,358.

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
24 resale sales. Average 1980; median 1979; standard deviation 2; middle half (25th–75th percentile) 1979–1982; lowest 1974, highest 1984.

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
24 resale sales. Average 64; median 21; standard deviation 104; middle half (25th–75th percentile) 7–51; lowest 3, highest 370. 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
24 resale sales. Average 5.7%; median 4.0%; standard deviation 7.3%; middle half (25th–75th percentile) 2.2%–6.9%; lowest −6.6%, highest 24.4%. 3 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
9 of 24 resale sales (37.5%).

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
13 of 24 resale sales (54.2%).

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
2 sales with a view, 20 without, 2 unclassified. Most common View entries: None 16, Neighborhood 4, See Remarks 2, Trees/Woods 2.

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 “northwood” (case-insensitive). A record is kept when its subdivision name belongs to the Northwood family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 24 closed Northwood records over the prior year, in ZIP 78727. 7 subdivision spellings kept: Northwood 04 (9); Northwood Sec 06 (6); Northwood (3); Northwood 03 (2); Northwood Sec 02 (2); NORTHWOOD (1); Northwood 05 (1). Names found by the search but not part of Northwood, left out: Northwoods Avery Station (5); Northwoods at Avery Ranch (2); Northwoods Avery Station Cottages (2); Reserve At Northwood (1); Northwoods At Avery Ranch (1); Northwood Iv (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 12 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
24 single-family sales in the window: 24 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
24 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 $440K”.
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 $440K: $320,000–$425,000 (6 sales); $440K–$492K: $440,000–$491,500 (6 sales); $509K–$572K: $509,000–$572,000 (6 sales); Over $572K: $576,000–$635,000 (6 sales)
Quartiles by living area: Under 1,614 SF: 1,314–1,607 SF (6 sales); 1,614–1,664 SF: 1,614–1,664 SF (6 sales); 1,690–1,766 SF: 1,690–1,766 SF (6 sales); Over 1,766 SF: 1,838–2,358 SF (6 sales)
Quartiles by year built: Before 1979: 1974–1978 (4 sales); 1979: 1979–1979 (9 sales); 1980–1981: 1980–1981 (3 sales); After 1981: 1982–1984 (8 sales)
View and no view: View: MLS lists a view (2 sales); No view: None or Neighborhood (20 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 $494,217, median $500,250. Days on market: average 64, median 21: 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

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
1 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 = 12.5030.0059p < 0.0063Yesε² = 0.543large
Living areaKruskal–WallisH = 7.4330.0593p < 0.0063Unclearε² = 0.323large
Year builtKruskal–WallisH = 3.7030.2958p < 0.0063Unclearε² = 0.161large
Days on marketKruskal–WallisH = 2.5230.4724p < 0.0063Unclearε² = 0.109medium
Discount from original listKruskal–WallisH = 7.2130.0656p < 0.0063Unclearε² = 0.313large
Price cut before saleChi-squareχ² = 3.3830.3370p < 0.0063UnclearCramér’s V = 0.375medium
Seller paid closing costs or repairsChi-squareχ² = 3.1930.3634p < 0.0063UnclearCramér’s V = 0.365medium
Has a viewChi-squareχ² = 2.1830.5355p < 0.0063UnclearCramér’s V = 0.302medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 11.1530.0109p < 0.0063Unclearε² = 0.485large
Net price per SFKruskal–WallisH = 6.3830.0945p < 0.0063Unclearε² = 0.277large
Year builtKruskal–WallisH = 7.0830.0693p < 0.0063Unclearε² = 0.308large
Days on marketKruskal–WallisH = 4.1330.2474p < 0.0063Unclearε² = 0.180large
Discount from original listKruskal–WallisH = 5.5030.1386p < 0.0063Unclearε² = 0.239large
Price cut before saleChi-squareχ² = 4.8030.1870p < 0.0063UnclearCramér’s V = 0.447medium
Seller paid closing costs or repairsChi-squareχ² = 3.1930.3634p < 0.0063UnclearCramér’s V = 0.365medium
Has a viewChi-squareχ² = 2.1830.5355p < 0.0063UnclearCramér’s V = 0.302medium

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 24 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.