ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Tanglewood Forest

Austin, TX 78748
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 · 3:58 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
26
single-family resale homes
Median net sale price
$411,325
average $409,617
Median net price per SF
$273
average $281
Median days on market
38 days
average 72 days
1. SummaryResale homes · 26 sales · October 26, 2025 – October 25, 2026

This study looks at the 26 resale homes sold in Tanglewood Forest 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 sold26 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 $340K · 6 sales$340K–$408K · 7 sales$415K–$483K · 7 salesOver $483K · 6 sales
3. Quartiles by net sale priceResale homes · 26 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.

2026-10-26T03:58:44.778984 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 7 7 6 26 sales Sales per group Under $340K: 6 sales (23%) $340K–$408K: 7 sales (27%) $415K–$483K: 7 sales (27%) Over $483K: 6 sales (23%)
Bottom line: no measure differs enough between the groups to rule out chance.

3.1 Key differences

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

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 $340K$340K–$408K$415K–$483KOver $483KReal difference?
Net price per SF$279 per SF$257 per SF$277 per SF$318 per SFunclear
Living area1,141 SF1,471 SF1,624 SF1,730 SFunclear
Year built1984198319841984unclear
Days on market22 days80 days30 days42 daysunclear
Discount from original list10.3%10.0%6.3%4.0%unclear
Price cut before sale50%71%71%33%unclear
Seller paid closing costs or repairs33%57%14%100%unclear
Has a view0%0%0%33%unclear

How to read this section. Each heading gives the finding. The gold box says whether the gap is real (✓, with its size) or could be chance (–). The section ends with its numbers; the tests are in section 8.3.

3.3 Net price per SF: no clear difference

2026-10-26T03:58:44.806677 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $340K 6 sales $340K– $408K 7 sales $415K– $483K 7 sales Over $483K 6 sales $0 $100 $200 $300 $279 $257 $277 $318 Net price per SF, average

The average is $318 per SF for homes over $483K and $279 per SF for homes under $340K. It does not move in a straight line; homes over $483K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-26T03:58:44.828771 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $340K 6 sales $340K– $408K 7 sales $415K– $483K 7 sales Over $483K 6 sales 0 1,000 2,000 1,141 1,471 1,624 1,730 Living area (SF), average

The average is 1,730 SF for homes over $483K and 1,141 SF for homes under $340K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-26T03:58:44.851921 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $340K 6 sales $340K– $408K 7 sales $415K– $483K 7 sales Over $483K 6 sales 1983 1984 1985 1984 1983 1984 1984 Year built: median (dot) and middle half (bar)

The median is 1984 for homes over $483K and 1984 for homes under $340K. It does not move in a straight line; homes under $340K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T03:58:44.874662 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $340K 6 sales $340K– $408K 7 sales $415K– $483K 7 sales Over $483K 6 sales 0 25 50 75 22 80 30 42 Days on market, median

The median is 42 days for homes over $483K and 22 days for homes under $340K. It does not move in a straight line; homes $340K–$408K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T03:58:44.896502 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $340K 6 sales $340K– $408K 7 sales $415K– $483K 7 sales Over $483K 6 sales 0.0% 5.0% 10.0% 10.3% 10.0% 6.3% 4.0% Discount from original list, average

The average is 4.0% for homes over $483K and 10.3% for homes under $340K. It falls step by step from the lowest range to the 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

2026-10-26T03:58:44.926803 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% 50 33 0 71 57 0 71 14 0 33 100 33 Under $340K $340K–$408K $415K–$483K Over $483K

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

  • 33% of homes over $483K had a price cut before sale, against 50% of homes under $340K. Defined in 8.1.7.
  • 100% of homes over $483K had the seller pay closing costs or repairs, against 33% of homes under $340K. Defined in 8.1.8.
  • 33% of homes over $483K have a view, against 0% of homes under $340K. 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 $340K6 sales$340K–$408K7 sales$415K–$483K7 salesOver $483K6 salesAll26 salesReal difference?
Net sale price average$288,238$374,396$436,771$540,408$409,617by design
Net price per SF average$279$257$277$318$281unclear
Living area average1,1411,4711,6241,7301,496unclear
Year built median19841983198419841984unclear

3.10 The numbers: selling

Under $340K6 sales$340K–$408K7 sales$415K–$483K7 salesOver $483K6 salesAll26 salesReal difference?
Days on market median2280304238unclear
Discount from original list average10.3%10.0%6.3%4.0%7.7%unclear
Price cut before sale50%71%71%33%58%unclear
Seller paid closing costs or repairs33%57%14%100%50%unclear
Has a view0%0%0%33%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 · 26 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.

2026-10-26T03:58:44.947134 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 7 7 6 26 sales Sales per group Under 1,350 SF: 6 sales (23%) 1,350–1,460 SF: 7 sales (27%) 1,538–1,689 SF: 7 sales (27%) Over 1,689 SF: 6 sales (23%)
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 1,350 SF1,350–1,460 SF1,538–1,689 SFOver 1,689 SFReal difference?
Net sale price$336K$387K$435K$480Kunclear
Net price per SF$326 per SF$279 per SF$269 per SF$254 per SFunclear
Year built1984198319841984unclear
Days on market28 days40 days30 days76 daysunclear
Discount from original list6.2%8.1%11.5%4.3%unclear
Price cut before sale67%43%57%67%unclear
Seller paid closing costs or repairs33%43%57%67%unclear
Has a view0%0%14%17%unclear

4.3 Net sale price: no clear difference

2026-10-26T03:58:44.967786 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,350 SF 6 sales 1,350– 1,460 SF 7 sales 1,538– 1,689 SF 7 sales Over 1,689 SF 6 sales $0K $200K $400K $336K $387K $435K $480K Net sale price, average

The average is $480K for homes over 1,689 SF and $336K for homes under 1,350 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-10-26T03:58:44.990133 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,350 SF 6 sales 1,350– 1,460 SF 7 sales 1,538– 1,689 SF 7 sales Over 1,689 SF 6 sales $0 $100 $200 $300 $326 $279 $269 $254 Net price per SF, average

The average is $254 per SF for homes over 1,689 SF and $326 per SF for homes under 1,350 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T03:58:45.012550 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,350 SF 6 sales 1,350– 1,460 SF 7 sales 1,538– 1,689 SF 7 sales Over 1,689 SF 6 sales 1983 1984 1985 1984 1983 1984 1984 Year built: median (dot) and middle half (bar)

The median is 1984 for homes over 1,689 SF and 1984 for homes under 1,350 SF. It does not move in a straight line; homes under 1,350 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T03:58:45.035004 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,350 SF 6 sales 1,350– 1,460 SF 7 sales 1,538– 1,689 SF 7 sales Over 1,689 SF 6 sales 0 25 50 75 28 40 30 76 Days on market, median

The median is 76 days for homes over 1,689 SF and 28 days for homes under 1,350 SF. It does not move in a straight line; homes over 1,689 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T03:58:45.057151 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,350 SF 6 sales 1,350– 1,460 SF 7 sales 1,538– 1,689 SF 7 sales Over 1,689 SF 6 sales 0.0% 5.0% 10.0% 6.2% 8.1% 11.5% 4.3% Discount from original list, average

The average is 4.3% for homes over 1,689 SF and 6.2% for homes under 1,350 SF. It does not move in a straight line; homes 1,538–1,689 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

2026-10-26T03:58:45.083110 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 0 43 43 0 57 57 14 67 67 17 Under 1,350 SF 1,350–1,460 SF 1,538–1,689 SF Over 1,689 SF

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

  • 67% of homes over 1,689 SF had a price cut before sale, against 67% of homes under 1,350 SF. Defined in 8.1.7.
  • 67% of homes over 1,689 SF had the seller pay closing costs or repairs, against 33% of homes under 1,350 SF. Defined in 8.1.8.
  • 17% of homes over 1,689 SF have a view, against 0% of homes under 1,350 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 1,350 SF6 sales1,350–1,460 SF7 sales1,538–1,689 SF7 salesOver 1,689 SF6 salesAll26 salesReal difference?
Net sale price average$336,238$387,017$435,114$479,616$409,617unclear
Net price per SF average$326$279$269$254$281unclear
Living area average1,0621,3851,6181,9161,496by design
Year built median19841983198419841984unclear

4.10 The numbers: selling

Under 1,350 SF6 sales1,350–1,460 SF7 sales1,538–1,689 SF7 salesOver 1,689 SF6 salesAll26 salesReal difference?
Days on market median2840307638unclear
Discount from original list average6.2%8.1%11.5%4.3%7.7%unclear
Price cut before sale67%43%57%67%58%unclear
Seller paid closing costs or repairs33%43%57%67%50%unclear
Has a view0%0%14%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 8.3.2.

5. Groups by year builtResale homes · 26 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.

2026-10-26T03:58:45.101793 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 8 7 26 sales Sales per group Before 1984: 11 sales (42%) 1984: 8 sales (31%) After 1984: 7 sales (27%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

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

5.2 At a glance

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

Before 19841984After 1984Real difference?
Net sale price$365K$440K$444Kunclear
Net price per SF$249 per SF$300 per SF$312 per SFunclear
Living area1,488 SF1,494 SF1,509 SFunclear
Days on market35 days46 days25 daysunclear
Discount from original list8.6%7.5%6.5%unclear
Price cut before sale45%75%57%unclear
Seller paid closing costs or repairs27%62%71%unclear
Has a view0%25%0%unclear

5.3 Net sale price: no clear difference

2026-10-26T03:58:45.119958 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984 8 sales After 1984 7 sales $0K $200K $400K $365K $440K $444K Net sale price, average

The average is $444K for homes built after 1984 and $365K for homes built before 1984. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T03:58:45.139799 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984 8 sales After 1984 7 sales $0 $100 $200 $300 $249 $300 $312 Net price per SF, average

The average is $312 per SF for homes built after 1984 and $249 per SF for homes built before 1984. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T03:58:45.159010 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984 8 sales After 1984 7 sales 0 500 1,000 1,500 1,488 1,494 1,509 Living area (SF), average

The average is 1,509 SF for homes built after 1984 and 1,488 SF for homes built before 1984. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T03:58:45.178356 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984 8 sales After 1984 7 sales 0 20 40 35 46 25 Days on market, median

The median is 25 days for homes built after 1984 and 35 days for homes built before 1984. It does not move in a straight line; homes built 1984 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T03:58:45.199432 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 11 sales 1984 8 sales After 1984 7 sales 0.0% 2.5% 5.0% 7.5% 10.0% 8.6% 7.5% 6.5% Discount from original list, average

The average is 6.5% for homes built after 1984 and 8.6% for homes built before 1984. It falls step by step from the lowest range to the highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T03:58:45.222411 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% 45 27 0 75 62 25 57 71 0 Before 1984 1984 After 1984

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

  • 57% of homes built after 1984 had a price cut before sale, against 45% of homes built before 1984. Defined in 8.1.7.
  • 71% of homes built after 1984 had the seller pay closing costs or repairs, against 27% of homes built before 1984. Defined in 8.1.8.
  • 0% of homes built after 1984 have a view, against 0% of homes built before 1984. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

5.9 The numbers: price and size

Before 198411 sales19848 salesAfter 19847 salesAll26 salesReal difference?
Net sale price average$365,284$440,292$444,227$409,617unclear
Net price per SF average$249$300$312$281unclear
Living area average1,4881,4941,5091,496unclear
Year built median1983198419851984by design

5.10 The numbers: selling

Before 198411 sales19848 salesAfter 19847 salesAll26 salesReal difference?
Days on market median35462538unclear
Discount from original list average8.6%7.5%6.5%7.7%unclear
Price cut before sale45%75%57%58%unclear
Seller paid closing costs or repairs27%62%71%50%unclear
Has a view0%25%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 8.3.3.

6. View and no viewResale homes · 26 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.

2026-10-26T03:58:45.239132 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 2 24 26 sales Sales per group View: 2 sales (8%) No view: 24 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

2026-10-26T03:58:45.255257 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 24 sales $0K $200K $400K $600K $560K $397K Net sale price, average

The average is $560K for homes with a view and $397K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T03:58:45.272285 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 24 sales $0 $100 $200 $300 $305 $279 Net price per SF, average

The average is $305 per SF for homes with a view and $279 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T03:58:45.290184 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 24 sales 0 500 1,000 1,500 2,000 1,908 1,461 Living area (SF), average

The average is 1,908 SF for homes with a view and 1,461 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T03:58:45.330230 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 24 sales 1983 1984 1985 1984 1984 Year built: median (dot) and middle half (bar)

The median is 1984 for homes with a view and 1984 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T03:58:45.348704 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 24 sales 0 25 50 75 100 90 38 Days on market, median

The median is 90 days for homes with a view and 38 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

2026-10-26T03:58:45.367241 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 24 sales 0.0% 2.0% 4.0% 6.0% 8.0% 4.9% 7.9% Discount from original list, average

The average is 4.9% for homes with a view and 7.9% 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

2026-10-26T03:58:45.386466 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 50 100 58 46 View No view

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

  • 50% of homes with a view had a price cut before sale, against 58% 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 46% 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 view24 salesAll26 sales
Net sale price average$559,500$397,127$409,617
Net price per SF average$305$279$281
Living area average1,9081,4611,496
Year built median198419841984

6.11 The numbers: selling

View2 salesNo view24 salesAll26 sales
Days on market median903838
Discount from original list average4.9%7.9%7.7%
Price cut before sale50%58%58%
Seller paid closing costs or repairs100%46%50%

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 Tanglewood Forest.

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
26 resale sales. Average $409,617; median $411,325; standard deviation $96,464; middle half (25th–75th percentile) $341,780–$475,500; lowest $242,000, highest $617,000. 13 sales had a seller payment; their median payment was $9,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
26 resale sales. Average $281; median $273; standard deviation $66; middle half (25th–75th percentile) $236–$324; lowest $163, highest $432.

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
26 resale sales. Average 1,496; median 1,499; standard deviation 345; middle half (25th–75th percentile) 1,354–1,682; lowest 754, highest 2,265.

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
26 resale sales. Average 1984; median 1984; standard deviation 3; middle half (25th–75th percentile) 1983–1985; lowest 1983, highest 1994.

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
26 resale sales. Average 72; median 38; standard deviation 100; middle half (25th–75th percentile) 8–80; lowest 0, highest 440. 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
26 resale sales. Average 7.7%; median 5.9%; standard deviation 7.0%; middle half (25th–75th percentile) 2.3%–10.8%; lowest −0.7%, highest 24.4%. 1 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
15 of 26 resale sales (57.7%).

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
13 of 26 resale sales (50.0%).

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
2 sales with a view, 24 without, 0 unclassified. Most common View entries: None 20, Neighborhood 5, Park/Greenbelt 2, Creek/Stream 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 “tanglewood forest” (case-insensitive). A record is kept when its subdivision name belongs to the Tanglewood Forest family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 27 closed Tanglewood Forest records over the prior year, in ZIP 78748. 11 subdivision spellings kept: Tanglewood Forest Sec 02 Ph A (5); Tanglewood Forest Sec 04 Ph B (5); Tanglewood Forest Sec 02 Ph D (3); Tanglewood Forest Sec 04 Ph A (3); Tanglewood Forest Sec 01 (3); Tanglewood Forest Sec 02 Ph C (2); Tanglewood Forest Sec 04 Ph C (2); Tanglewood Forest Sec 02 Ph E (1); TANGLEWOOD FOREST SEC 4 PHS (1); Tanglewood Forest Sec 04 Ph F (1); Tanglewood Forest (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 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
26 single-family sales in the window: 26 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
26 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
1 sale(s) other than single-family homes (condo, townhome and similar)

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 $340K”.
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 $340K: $242,000–$325,788 (6 sales); $340K–$408K: $340,000–$407,650 (7 sales); $415K–$483K: $415,000–$483,000 (7 sales); Over $483K: $490,000–$617,000 (6 sales)
Quartiles by living area: Under 1,350 SF: 754–1,333 SF (6 sales); 1,350–1,460 SF: 1,350–1,460 SF (7 sales); 1,538–1,689 SF: 1,538–1,689 SF (7 sales); Over 1,689 SF: 1,698–2,265 SF (6 sales)
Groups by year built: Before 1984: 1983–1983 (11 sales); 1984: 1984–1984 (8 sales); After 1984: 1985–1994 (7 sales)
View and no view: View: MLS lists a view (2 sales); No view: None or Neighborhood (24 sales)

8.2.6 Average and median

In simple terms
The average adds the values and divides by how many; one very expensive home can pull it up. The median is the middle value, with half above and half below.
Statistically
Mean x̄ = (1/n) Σ xᵢ; median = 50th percentile. Price, price per SF, living area and discount use the mean; days on market and year built use the median (skewed or whole-year values).
The data
Net sale price: average $409,617, median $411,325. Days on market: average 72, median 38: 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; Groups by year built: 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
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

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 2.9330.4024p < 0.0063Unclearε² = 0.117medium
Living areaKruskal–WallisH = 8.9830.0296p < 0.0063Unclearε² = 0.359large
Year builtKruskal–WallisH = 5.3130.1506p < 0.0063Unclearε² = 0.212large
Days on marketKruskal–WallisH = 3.8730.2760p < 0.0063Unclearε² = 0.155large
Discount from original listKruskal–WallisH = 3.9230.2707p < 0.0063Unclearε² = 0.157large
Price cut before saleChi-squareχ² = 2.6930.4426p < 0.0063UnclearCramér’s V = 0.321medium
Seller paid closing costs or repairsChi-squareχ² = 10.3830.0156p < 0.0063UnclearCramér’s V = 0.632large
Has a viewChi-squareχ² = 7.2230.0651p < 0.0063UnclearCramér’s V = 0.527large

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 7.8130.0501p < 0.0063Unclearε² = 0.312large
Net price per SFKruskal–WallisH = 4.1530.2460p < 0.0063Unclearε² = 0.166large
Year builtKruskal–WallisH = 5.3130.1505p < 0.0063Unclearε² = 0.212large
Days on marketKruskal–WallisH = 2.6630.4471p < 0.0063Unclearε² = 0.106medium
Discount from original listKruskal–WallisH = 3.4430.3285p < 0.0063Unclearε² = 0.138medium
Price cut before saleChi-squareχ² = 1.0330.7945p < 0.0063UnclearCramér’s V = 0.199small
Seller paid closing costs or repairsChi-squareχ² = 1.6230.6551p < 0.0063UnclearCramér’s V = 0.250small
Has a viewChi-squareχ² = 2.1930.5334p < 0.0063UnclearCramér’s V = 0.290small

8.3.3 Groups by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 4.4720.1072p < 0.0063Unclearε² = 0.179large
Net price per SFKruskal–WallisH = 3.8620.1451p < 0.0063Unclearε² = 0.154large
Living areaKruskal–WallisH = 0.0720.9674p < 0.0063Unclearε² = 0.003negligible
Days on marketKruskal–WallisH = 0.7020.7052p < 0.0063Unclearε² = 0.028small
Discount from original listKruskal–WallisH = 0.3820.8272p < 0.0063Unclearε² = 0.015small
Price cut before saleChi-squareχ² = 1.6620.4366p < 0.0063UnclearCramér’s V = 0.252small
Seller paid closing costs or repairsChi-squareχ² = 4.0620.1314p < 0.0063UnclearCramér’s V = 0.395medium
Has a viewChi-squareχ² = 4.8820.0874p < 0.0063UnclearCramér’s V = 0.433medium

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); 1 sale(s) other than single-family homes (condo, townhome and similar). 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 26 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.