ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Terra Colinas Ph 1

Austin, TX 78738
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 4:27 AM CDT
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
15
single-family resale homes
Median net sale price
$679,000
average $685,052
Median net price per SF
$232
average $241
Median days on market
43 days
average 45 days
1. SummaryResale homes · 15 sales · October 26, 2025 – October 25, 2026

This study looks at the 15 resale homes sold in Terra Colinas Ph 1 in the 365 days to October 25, 2026. A full year is used because only 8 resale homes sold in the last 180 days. New construction is left out and shown on its own in section 7. The homes are compared four ways: by price, by living area, by year built and with or without a view. The first three are split into four equal groups (quartiles), each named by its range.

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

2. Where the resale homes sold15 resale homes · colored by price range

Each dot is one resale home, colored by its price range. Use the buttons to show one price range at a time. Click a dot for that sale: address, close date, original and last list price, net sale price, living area, net sale per SF and days on market. Scroll or pinch to zoom.

Under $600K · 4 sales$600K–$679K · 4 sales$690K–$715K · 3 salesOver $715K · 4 sales
3. Quartiles by net sale priceResale homes · 15 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T04:27:36.209512 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 4 3 4 15 sales Sales per group Under $600K: 4 sales (27%) $600K–$679K: 4 sales (27%) $690K–$715K: 3 sales (20%) Over $715K: 4 sales (27%)
Bottom line: too few sales to test.

3.1 Key differences

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

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

3.3 Net price per SF: described, not tested

2026-10-26T04:27:36.237217 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $600K 4 sales $600K– $679K 4 sales $690K– $715K 3 sales Over $715K 4 sales $0 $100 $200 $300 $242 $237 $227 $255 Net price per SF, average

The average is $255 per SF for homes over $715K and $242 per SF for homes under $600K. It does not move in a straight line; homes over $715K are highest. Defined in 8.1.2.

Not tested: too few sales.

3.4 Living area: described, not tested

2026-10-26T04:27:36.259379 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $600K 4 sales $600K– $679K 4 sales $690K– $715K 3 sales Over $715K 4 sales 0 2,000 4,000 2,365 2,716 3,104 3,342 Living area (SF), average

The average is 3,342 SF for homes over $715K and 2,365 SF for homes under $600K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

Not tested: too few sales.

3.5 Year built: described, not tested

2026-10-26T04:27:36.281899 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $600K 4 sales $600K– $679K 4 sales $690K– $715K 3 sales Over $715K 4 sales 2016 2017 2018 2017 2016 2018 2017 Year built: median (dot) and middle half (bar)

The median is 2017 for homes over $715K and 2017 for homes under $600K. It does not move in a straight line; homes $690K–$715K are highest. Defined in 8.1.4.

Not tested: too few sales.

3.6 Days on market: described, not tested

2026-10-26T04:27:36.304214 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $600K 4 sales $600K– $679K 4 sales $690K– $715K 3 sales Over $715K 4 sales 0 20 40 60 53 24 47 46 Days on market, median

The median is 46 days for homes over $715K and 53 days for homes under $600K. It does not move in a straight line; homes under $600K are highest. Defined in 8.1.5.

Not tested: too few sales.

3.7 Discount from original list: described, not tested

2026-10-26T04:27:36.326455 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $600K 4 sales $600K– $679K 4 sales $690K– $715K 3 sales Over $715K 4 sales 0.0% 2.5% 5.0% 7.5% 7.2% 2.0% 5.8% 4.6% Discount from original list, average

The average is 4.6% for homes over $715K and 7.2% for homes under $600K. It does not move in a straight line; homes under $600K 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

2026-10-26T04:27:36.355891 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% 100 75 50 50 0 25 67 33 33 75 25 75 Under $600K $600K–$679K $690K–$715K Over $715K

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

  • 75% of homes over $715K had a price cut before sale, against 100% of homes under $600K. Defined in 8.1.7.
  • 25% of homes over $715K had the seller pay closing costs or repairs, against 75% of homes under $600K. Defined in 8.1.8.
  • 75% of homes over $715K have a view, against 50% of homes under $600K. 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 $600K4 sales$600K–$679K4 sales$690K–$715K3 salesOver $715K4 salesAll15 sales
Net sale price average$569,881$638,500$702,667$833,562$685,052
Net price per SF average$242$237$227$255$241
Living area average2,3652,7163,1043,3422,867
Year built median20172016201820172017

3.10 The numbers: selling

Under $600K4 sales$600K–$679K4 sales$690K–$715K3 salesOver $715K4 salesAll15 sales
Days on market median5324474643
Discount from original list average7.2%2.0%5.8%4.6%4.9%
Price cut before sale100%50%67%75%73%
Seller paid closing costs or repairs75%0%33%25%33%
Has a view50%25%33%75%47%

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.1.

4. Quartiles by living areaResale homes · 15 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T04:27:36.376016 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 4 3 4 15 sales Sales per group Under 2,469 SF: 4 sales (27%) 2,469–2,872 SF: 4 sales (27%) 2,903–3,064 SF: 3 sales (20%) Over 3,064 SF: 4 sales (27%)
Bottom line: too few sales to test.

4.1 Key differences

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

4.3 Net sale price: described, not tested

2026-10-26T04:27:36.396215 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,469 SF 4 sales 2,469– 2,872 SF 4 sales 2,903– 3,064 SF 3 sales Over 3,064 SF 4 sales $0K $250K $500K $750K $580K $672K $688K $801K Net sale price, average

The average is $801K for homes over 3,064 SF and $580K for homes under 2,469 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

Not tested: too few sales.

4.4 Net price per SF: described, not tested

2026-10-26T04:27:36.418603 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,469 SF 4 sales 2,469– 2,872 SF 4 sales 2,903– 3,064 SF 3 sales Over 3,064 SF 4 sales $0 $100 $200 $300 $251 $250 $232 $229 Net price per SF, average

The average is $229 per SF for homes over 3,064 SF and $251 per SF for homes under 2,469 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

Not tested: too few sales.

4.5 Year built: described, not tested

2026-10-26T04:27:36.443157 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,469 SF 4 sales 2,469– 2,872 SF 4 sales 2,903– 3,064 SF 3 sales Over 3,064 SF 4 sales 2014 2015 2016 2017 2018 2017 2017 2018 2015 Year built: median (dot) and middle half (bar)

The median is 2015 for homes over 3,064 SF and 2017 for homes under 2,469 SF. It does not move in a straight line; homes 2,903–3,064 SF are highest. Defined in 8.1.4.

Not tested: too few sales.

4.6 Days on market: described, not tested

2026-10-26T04:27:36.466791 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,469 SF 4 sales 2,469– 2,872 SF 4 sales 2,903– 3,064 SF 3 sales Over 3,064 SF 4 sales 0 25 50 75 54 16 69 48 Days on market, median

The median is 48 days for homes over 3,064 SF and 54 days for homes under 2,469 SF. It does not move in a straight line; homes 2,903–3,064 SF are highest. Defined in 8.1.5.

Not tested: too few sales.

4.7 Discount from original list: described, not tested

2026-10-26T04:27:36.488587 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,469 SF 4 sales 2,469– 2,872 SF 4 sales 2,903– 3,064 SF 3 sales Over 3,064 SF 4 sales 0.0% 2.0% 4.0% 6.0% 6.2% 2.8% 5.0% 5.4% Discount from original list, average

The average is 5.4% for homes over 3,064 SF and 6.2% for homes under 2,469 SF. It does not move in a straight line; homes under 2,469 SF are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T04:27:36.514781 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% 100 50 25 50 25 50 67 0 67 75 50 50 Under 2,469 SF 2,469–2,872 SF 2,903–3,064 SF Over 3,064 SF

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

  • 75% of homes over 3,064 SF had a price cut before sale, against 100% of homes under 2,469 SF. Defined in 8.1.7.
  • 50% of homes over 3,064 SF had the seller pay closing costs or repairs, against 50% of homes under 2,469 SF. Defined in 8.1.8.
  • 50% of homes over 3,064 SF have a view, against 25% of homes under 2,469 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 2,469 SF4 sales2,469–2,872 SF4 sales2,903–3,064 SF3 salesOver 3,064 SF4 salesAll15 sales
Net sale price average$579,881$671,625$688,333$801,188$685,052
Net price per SF average$251$250$232$229$241
Living area average2,3162,6962,9643,5152,867
Year built median20172017201820152017

4.10 The numbers: selling

Under 2,469 SF4 sales2,469–2,872 SF4 sales2,903–3,064 SF3 salesOver 3,064 SF4 salesAll15 sales
Days on market median5416694843
Discount from original list average6.2%2.8%5.0%5.4%4.9%
Price cut before sale100%50%67%75%73%
Seller paid closing costs or repairs50%25%0%50%33%
Has a view25%50%67%50%47%

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.2.

5. Groups by year builtResale homes · 15 sales · October 26, 2025 – October 25, 2026

Sales ranked by year built and cut into four groups, from the oldest to the newest. Homes built in the same year always stay in the same group, so group sizes can differ a little. Only 3 groups are shown: homes here share a few year built values, and no group may hold fewer than 3 sales.

2026-10-26T04:27:36.532874 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 3 5 15 sales Sales per group Before 2017: 7 sales (47%) 2017: 3 sales (20%) After 2017: 5 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

2026-10-26T04:27:36.551205 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 7 sales 2017 3 sales After 2017 5 sales $0K $200K $400K $600K $800K $685K $577K $750K Net sale price, average

The average is $750K for homes built after 2017 and $685K for homes built before 2017. It does not move in a straight line; homes built after 2017 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T04:27:36.571966 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 7 sales 2017 3 sales After 2017 5 sales $0 $100 $200 $300 $226 $247 $258 Net price per SF, average

The average is $258 per SF for homes built after 2017 and $226 per SF for homes built before 2017. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T04:27:36.591490 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 7 sales 2017 3 sales After 2017 5 sales 0 1,000 2,000 3,000 3,071 2,337 2,900 Living area (SF), average

The average is 2,900 SF for homes built after 2017 and 3,071 SF for homes built before 2017. It does not move in a straight line; homes built before 2017 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T04:27:36.610355 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 7 sales 2017 3 sales After 2017 5 sales 0 20 40 60 47 65 29 Days on market, median

The median is 29 days for homes built after 2017 and 47 days for homes built before 2017. It does not move in a straight line; homes built 2017 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T04:27:36.630607 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 7 sales 2017 3 sales After 2017 5 sales 0.0% 2.0% 4.0% 6.0% 4.8% 6.2% 4.1% Discount from original list, average

The average is 4.1% for homes built after 2017 and 4.8% for homes built before 2017. It does not move in a straight line; homes built 2017 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T04:27:36.653172 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% 71 43 29 100 33 33 60 20 80 Before 2017 2017 After 2017

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

  • 60% of homes built after 2017 had a price cut before sale, against 71% of homes built before 2017. Defined in 8.1.7.
  • 20% of homes built after 2017 had the seller pay closing costs or repairs, against 43% of homes built before 2017. Defined in 8.1.8.
  • 80% of homes built after 2017 have a view, against 29% of homes built before 2017. 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 20177 sales20173 salesAfter 20175 salesAll15 sales
Net sale price average$685,468$576,667$749,500$685,052
Net price per SF average$226$247$258$241
Living area average3,0712,3372,9002,867
Year built median2016201720182017

5.10 The numbers: selling

Before 20177 sales20173 salesAfter 20175 salesAll15 sales
Days on market median47652943
Discount from original list average4.8%6.2%4.1%4.9%
Price cut before sale71%100%60%73%
Seller paid closing costs or repairs43%33%20%33%
Has a view29%33%80%47%

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.3.

6. View and no viewResale homes · 15 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T04:27:36.669144 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 8 15 sales Sales per group View: 7 sales (47%) No view: 8 sales (53%)
Bottom line: no measure differs enough between the groups to rule out chance.

6.1 Key differences

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

6.2 At a glance

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

ViewNo viewReal difference?
Net sale price$723K$652Kunclear
Net price per SF$250 per SF$233 per SFunclear
Living area2,889 SF2,848 SFunclear
Year built20182016unclear
Days on market50 days42 daysunclear
Discount from original list5.2%4.6%unclear
Price cut before sale86%62%unclear
Seller paid closing costs or repairs43%25%unclear

6.3 Net sale price: no clear difference

2026-10-26T04:27:36.686259 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 8 sales $0K $200K $400K $600K $800K $723K $652K Net sale price, average

The average is $723K for homes with a view and $652K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-10-26T04:27:36.703650 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 8 sales $0 $100 $200 $300 $250 $233 Net price per SF, average

The average is $250 per SF for homes with a view and $233 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-10-26T04:27:36.721147 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 8 sales 0 1,000 2,000 3,000 2,889 2,848 Living area (SF), average

The average is 2,889 SF for homes with a view and 2,848 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T04:27:36.739646 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 8 sales 2016 2017 2018 2018 2016 Year built: median (dot) and middle half (bar)

The median is 2018 for homes with a view and 2016 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T04:27:36.779164 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 8 sales 0 20 40 60 50 42 Days on market, median

The median is 50 days for homes with a view and 42 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-10-26T04:27:36.796256 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 7 sales No view 8 sales 0.0% 2.0% 4.0% 6.0% 5.2% 4.6% Discount from original list, average

The average is 5.2% for homes with a view and 4.6% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T04:27:36.814848 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 86 43 62 25 View No view

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

  • 86% of homes with a view had a price cut before sale, against 62% of homes without a view. Defined in 8.1.7.
  • 43% of homes with a view had the seller pay closing costs or repairs, against 25% of homes without a view. Defined in 8.1.8.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance

6.10 The numbers: price and size

View7 salesNo view8 salesAll15 salesReal difference?
Net sale price average$722,750$652,066$685,052unclear
Net price per SF average$250$233$241unclear
Living area average2,8892,8482,867unclear
Year built median201820162017unclear

6.11 The numbers: selling

View7 salesNo view8 salesAll15 salesReal difference?
Days on market median504243unclear
Discount from original list average5.2%4.6%4.9%unclear
Price cut before sale86%62%73%unclear
Seller paid closing costs or repairs43%25%33%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.4.

7. New constructionBasic statistics · 0 sales · October 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 Terra Colinas Ph 1.

No new-construction sales were reported in ABOR MLS in this window.

Same definitions as the rest of the study (section 8). New construction = NewConstructionYN true, or PropertyCondition “New Construction” or “Under Construction”.

8. AppendixMeasures, methods and tests

Each measure and method three ways: in plain words, as statistics, and with the data from this study.

8.1 Measures

8.1.1 Net sale price

In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
15 resale sales. Average $685,052; median $679,000; standard deviation $112,767; middle half (25th–75th percentile) $594,762–$730,000; lowest $560,000, highest $950,000. 5 sales had a seller payment; their median payment was $5,000.

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
15 resale sales. Average $241; median $232; standard deviation $30; middle half (25th–75th percentile) $226–$254; lowest $193, highest $316.

8.1.3 Living area

In simple terms
The heated and cooled space, as listed in the MLS. Garages and porches are not counted.
Statistically
RESO LivingArea, in square feet. Sales under 400 SF are treated as entry errors and left out.
The data
15 resale sales. Average 2,867; median 2,872; standard deviation 489; middle half (25th–75th percentile) 2,464–3,194; lowest 2,256, highest 3,857.

8.1.4 Year built

In simple terms
The year the home was finished, as listed in the MLS. It shows whether a group leans to older or newer phases of the community.
Statistically
RESO YearBuilt; summarized by the median, with the 25th–75th percentile (middle half) on the charts.
The data
15 resale sales. Average 2017; median 2017; standard deviation 1; middle half (25th–75th percentile) 2016–2018; lowest 2014, highest 2019.

8.1.5 Days on market

In simple terms
How many days the home was on the market before the buyer's offer was accepted, counting any earlier listing periods (relists). This is the days on market agents and clients quote.
Statistically
CDOM = max(CumulativeDaysOnMarket, DaysOnMarket, PurchaseContractDate − ListingContractDate). The MLS counter can freeze at a price change, so the contract-date gap is a floor. Summarized by the median, because a few homes that sat for months pull an average up.
The data
15 resale sales. Average 45; median 43; standard deviation 31; middle half (25th–75th percentile) 19–67; lowest 2, highest 102. 0 sales went under contract on their listing date (0 days).

8.1.6 Discount from original list

In simple terms
How far below the first asking price the home sold, after seller payments. It measures how much negotiating room sellers gave up. A negative figure means the home sold above its first asking price.
Statistically
Discount % = (OriginalListPrice − Net) ÷ OriginalListPrice × 100, per sale; summarized by the mean.
The data
15 resale sales. Average 4.9%; median 5.7%; standard deviation 3.3%; middle half (25th–75th percentile) 1.9%–7.2%; lowest 0.0%, highest 9.5%. 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
11 of 15 resale sales (73.3%).

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
5 of 15 resale sales (33.3%).

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
7 sales with a view, 8 without, 0 unclassified. Most common View entries: Neighborhood 6, None 5, Hill Country 4, Park/Greenbelt 1, Trees/Woods 1, Pool 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 “terra colinas”, “bella colinas”, “bella colinas secs” (case-insensitive). A record is kept when its subdivision name belongs to the Terra Colinas Ph 1 family, the same rule comparable sales use (it includes Bella Colinas Sec 1, Bella Colinas Secs 3,4,5 & 6, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 15 closed Terra Colinas Ph 1 records over the prior year, in ZIP 78738. 7 subdivision spellings kept: Bella Colinas Secs 3,4,5 & 6 (3); Terra Colinas Ph 1 (3); Bella Colinas Sec 1 (2); Bella Colinas (2); Terra Colinas (2); Bella Colinas Sec 2 (2); Bella Colinas Sec 7,8,& 9 (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 8 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
15 single-family sales in the window: 15 resale, 0 new construction.

8.2.3 Resale and new construction

In simple terms
A resale home was previously owned. New construction is sold by the builder and behaves differently, so it is kept out of every analysis and reported once on its own.
Statistically
New construction = NewConstructionYN true, or PropertyCondition contains “New Construction” or “Under Construction”. Everything else is resale.
The data
15 resale; 0 new construction.

8.2.4 Sales left out

In simple terms
A few records cannot be used as entered and are left out before any analysis.
Statistically
Excluded: PropertySubType other than Single Family Residence; no OriginalListPrice; LivingArea under 400 SF; seller payments above 10% of ClosePrice (treated as entry errors).
The data
None in this window.

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $600K”.
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 $600K: $560,000–$589,525 (4 sales); $600K–$679K: $600,000–$679,000 (4 sales); $690K–$715K: $690,000–$715,000 (3 sales); Over $715K: $745,000–$950,000 (4 sales)
Quartiles by living area: Under 2,469 SF: 2,256–2,458 SF (4 sales); 2,469–2,872 SF: 2,469–2,872 SF (4 sales); 2,903–3,064 SF: 2,903–3,064 SF (3 sales); Over 3,064 SF: 3,323–3,857 SF (4 sales)
Groups by year built: Before 2017: 2014–2016 (7 sales); 2017: 2017–2017 (3 sales); After 2017: 2018–2019 (5 sales)
View and no view: View: MLS lists a view (7 sales); No view: None or Neighborhood (8 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 $685,052, median $679,000. Days on market: average 45, median 43: 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
View and no view: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
0 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

In simple terms
Headings and sentences round figures so they read easily; the tables at the end of each section give them in full.
Statistically
Prices in headings round to the nearest $1K; price per SF and days on market to the nearest whole number; living area to the nearest 10 SF; shares and percentage gaps to whole percents.
The data
Days on market is always shown in days.

8.3 Test results

Every test behind every gold box. Statistic, degrees of freedom (df), p-value, the threshold it must beat, and the size of the difference.

8.3.1 Quartiles by net sale price

Too few sales in a group to test.

8.3.2 Quartiles by living area

Too few sales in a group to test.

8.3.3 Groups by year built

Too few sales in a group to test.

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 33.00—0.6022p < 0.0063Unclearrank-biserial r = 0.179small
Net price per SFMann–Whitney UU = 35.00—0.4634p < 0.0063Unclearrank-biserial r = 0.250small
Living areaMann–Whitney UU = 32.50—0.6431p < 0.0063Unclearrank-biserial r = 0.161small
Year builtMann–Whitney UU = 43.50—0.0730p < 0.0063Unclearrank-biserial r = 0.554large
Days on marketMann–Whitney UU = 34.50—0.4871p < 0.0063Unclearrank-biserial r = 0.232small
Discount from original listMann–Whitney UU = 28.00—1.0000p < 0.0063Unclearrank-biserial r = 0.000negligible
Price cut before saleChi-squareχ² = 1.0310.3104p < 0.0063UnclearCramér’s V = 0.262small
Seller paid closing costs or repairsChi-squareχ² = 0.5410.4642p < 0.0063UnclearCramér’s V = 0.189small

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); nothing else. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

  1. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Erlbaum.
  2. Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press.
  3. Dunn, O. J. (1961). Multiple comparisons among means. JASA, 56(293), 52–64.
  4. Kerby, D. S. (2014). The simple difference formula: an approach to teaching nonparametric correlation. Comprehensive Psychology, 3, 11.IT.3.1.
  5. Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. JASA, 47(260), 583–621.
  6. Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18(1), 50–60.
  7. Pearson, K. (1900). On the criterion that a given system of deviations… Philosophical Magazine, 50(302), 157–175.
  8. Tomczak, M., & Tomczak, E. (2014). The need to report effect size estimates revisited. Trends in Sport Sciences, 21(1), 19–25.

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 15 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 26, 2026. Map data © OpenStreetMap contributors. ALEX Companies · Licensed by the Texas Real Estate Commission · Broker: Alexander Tiffany Southwest, LLC (ALEX Real Estate), #565194-BB · Diane Hart Alexander, Designated Broker, #574877-B.