ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Vizcaya

Round Rock, TX 78665
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 · 5:47 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
20
single-family resale homes
Median net sale price
$522,175
average $576,899
Median net price per SF
$203
average $207
Median days on market
51 days
average 75 days
1. SummaryResale homes · 20 sales · October 26, 2025 – October 25, 2026

This study looks at the 20 resale homes sold in Vizcaya in the 365 days to October 25, 2026. A full year is used because only 13 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 sold20 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 $450K · 5 sales$450K–$519K · 5 sales$525K–$600K · 5 salesOver $600K · 5 sales
3. Quartiles by net sale priceResale homes · 20 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.

2026-10-26T05:47:40.413970 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 5 5 5 20 sales Sales per group Under $450K: 5 sales (25%) $450K–$519K: 5 sales (25%) $525K–$600K: 5 sales (25%) Over $600K: 5 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 $450K$450K–$519K$525K–$600KOver $600K
Higher-priced homes Over $600K
  • Are much larger.
Lower-priced homes Under $450K
  • Are much smaller.

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 $450K$450K–$519K$525K–$600KOver $600KReal difference?
Net price per SF$205 per SF$206 per SF$203 per SF$214 per SFunclear
Living area2,038 SFSmallest2,393 SF2,823 SF3,956 SFLargest✓ large
Year built2019201820172018unclear
Days on market52 days37 days56 days55 daysunclear
Discount from original list6.1%4.2%2.8%6.6%unclear
Price cut before sale80%40%80%80%unclear
Seller paid closing costs or repairs80%40%40%60%unclear
Has a view0%20%20%20%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

2026-10-26T05:47:40.443025 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $450K 5 sales $450K– $519K 5 sales $525K– $600K 5 sales Over $600K 5 sales $0 $100 $200 $205 $206 $203 $214 Net price per SF, average

The average is $214 per SF for homes over $600K and $205 per SF for homes under $450K. It does not move in a straight line; homes over $600K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $600K are about 1,920 SF (94%) larger than homes under $450K

2026-10-26T05:47:40.465113 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $450K 5 sales $450K– $519K 5 sales $525K– $600K 5 sales Over $600K 5 sales 0 2,000 4,000 2,038 2,393 2,823 3,956 Living area (SF), average

The average is 3,956 SF for homes over $600K and 2,038 SF for homes under $450K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-26T05:47:40.488296 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $450K 5 sales $450K– $519K 5 sales $525K– $600K 5 sales Over $600K 5 sales 2016 2018 2020 2019 2018 2017 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over $600K and 2019 for homes under $450K. It does not move in a straight line; homes under $450K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:47:40.510675 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $450K 5 sales $450K– $519K 5 sales $525K– $600K 5 sales Over $600K 5 sales 0 20 40 60 52 37 56 55 Days on market, median

The median is 55 days for homes over $600K and 52 days for homes under $450K. It does not move in a straight line; homes $525K–$600K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:47:40.532750 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $450K 5 sales $450K– $519K 5 sales $525K– $600K 5 sales Over $600K 5 sales 0.0% 2.0% 4.0% 6.0% 6.1% 4.2% 2.8% 6.6% Discount from original list, average

The average is 6.6% for homes over $600K and 6.1% for homes under $450K. It does not move in a straight line; homes over $600K 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

2026-10-26T05:47:40.563299 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% 80 80 0 40 40 20 80 40 20 80 60 20 Under $450K $450K–$519K $525K–$600K Over $600K

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

  • 80% of homes over $600K had a price cut before sale, against 80% of homes under $450K. Defined in 8.1.7.
  • 60% of homes over $600K had the seller pay closing costs or repairs, against 80% of homes under $450K. Defined in 8.1.8.
  • 20% of homes over $600K have a view, against 0% of homes under $450K. 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 $450K5 sales$450K–$519K5 sales$525K–$600K5 salesOver $600K5 salesAll20 salesReal difference?
Net sale price average$408,700$489,670$570,916$838,310$576,899by design
Net price per SF average$205$206$203$214$207unclear
Living area average2,0382,3932,8233,9562,802✓ large
Year built median20192018201720182018unclear

3.10 The numbers: selling

Under $450K5 sales$450K–$519K5 sales$525K–$600K5 salesOver $600K5 salesAll20 salesReal difference?
Days on market median5237565551unclear
Discount from original list average6.1%4.2%2.8%6.6%4.9%unclear
Price cut before sale80%40%80%80%70%unclear
Seller paid closing costs or repairs80%40%40%60%55%unclear
Has a view0%20%20%20%15%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 · 20 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.

2026-10-26T05:47:40.583633 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 5 5 5 20 sales Sales per group Under 2,234 SF: 5 sales (25%) 2,234–2,711 SF: 5 sales (25%) 2,731–3,159 SF: 5 sales (25%) Over 3,159 SF: 5 sales (25%)
Bottom line

4.1 Key differences

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

Under 2,234 SF2,234–2,711 SF2,731–3,159 SFOver 3,159 SF
Larger homes Over 3,159 SF
  • Sell for much more.
Smaller homes Under 2,234 SF
  • Sell for much less.

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 2,234 SF2,234–2,711 SF2,731–3,159 SFOver 3,159 SFReal difference?
Net sale price$416KLowest$499K$555K$838KHighest✓ large
Net price per SF$219 per SF$202 per SF$194 per SF$214 per SFunclear
Year built2019201720192018unclear
Days on market43 days103 days50 days55 daysunclear
Discount from original list4.2%6.5%2.4%6.6%unclear
Price cut before sale80%60%60%80%unclear
Seller paid closing costs or repairs60%40%60%60%unclear
Has a view0%40%0%20%unclear

4.3 Homes over 3,159 SF sell for about $422K (102%) more than homes under 2,234 SF

2026-10-26T05:47:40.604378 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,234 SF 5 sales 2,234– 2,711 SF 5 sales 2,731– 3,159 SF 5 sales Over 3,159 SF 5 sales $0K $500K $1.00M $416K $499K $555K $838K Net sale price, average

The average is $838K for homes over 3,159 SF and $416K for homes under 2,234 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-26T05:47:40.627172 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,234 SF 5 sales 2,234– 2,711 SF 5 sales 2,731– 3,159 SF 5 sales Over 3,159 SF 5 sales $0 $100 $200 $219 $202 $194 $214 Net price per SF, average

The average is $214 per SF for homes over 3,159 SF and $219 per SF for homes under 2,234 SF. It does not move in a straight line; homes under 2,234 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T05:47:40.649776 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,234 SF 5 sales 2,234– 2,711 SF 5 sales 2,731– 3,159 SF 5 sales Over 3,159 SF 5 sales 2016 2018 2020 2019 2017 2019 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over 3,159 SF and 2019 for homes under 2,234 SF. It does not move in a straight line; homes under 2,234 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T05:47:40.672666 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,234 SF 5 sales 2,234– 2,711 SF 5 sales 2,731– 3,159 SF 5 sales Over 3,159 SF 5 sales 0 50 100 43 103 50 55 Days on market, median

The median is 55 days for homes over 3,159 SF and 43 days for homes under 2,234 SF. It does not move in a straight line; homes 2,234–2,711 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T05:47:40.694391 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,234 SF 5 sales 2,234– 2,711 SF 5 sales 2,731– 3,159 SF 5 sales Over 3,159 SF 5 sales 0.0% 2.0% 4.0% 6.0% 4.2% 6.5% 2.4% 6.6% Discount from original list, average

The average is 6.6% for homes over 3,159 SF and 4.2% for homes under 2,234 SF. It does not move in a straight line; homes over 3,159 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

2026-10-26T05:47:40.721188 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% 80 60 0 60 40 40 60 60 0 80 60 20 Under 2,234 SF 2,234–2,711 SF 2,731–3,159 SF Over 3,159 SF

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

  • 80% of homes over 3,159 SF had a price cut before sale, against 80% of homes under 2,234 SF. Defined in 8.1.7.
  • 60% of homes over 3,159 SF had the seller pay closing costs or repairs, against 60% of homes under 2,234 SF. Defined in 8.1.8.
  • 20% of homes over 3,159 SF have a view, against 0% of homes under 2,234 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 2,234 SF5 sales2,234–2,711 SF5 sales2,731–3,159 SF5 salesOver 3,159 SF5 salesAll20 salesReal difference?
Net sale price average$415,850$498,720$554,716$838,310$576,899✓ large
Net price per SF average$219$202$194$214$207unclear
Living area average1,9072,4812,8663,9562,802by design
Year built median20192017201920182018unclear

4.10 The numbers: selling

Under 2,234 SF5 sales2,234–2,711 SF5 sales2,731–3,159 SF5 salesOver 3,159 SF5 salesAll20 salesReal difference?
Days on market median43103505551unclear
Discount from original list average4.2%6.5%2.4%6.6%4.9%unclear
Price cut before sale80%60%60%80%70%unclear
Seller paid closing costs or repairs60%40%60%60%55%unclear
Has a view0%40%0%20%15%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 · 20 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.

2026-10-26T05:47:40.742280 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 4 6 4 20 sales Sales per group Before 2017: 6 sales (30%) 2017–2018: 4 sales (20%) 2019: 6 sales (30%) After 2019: 4 sales (20%)
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

2026-10-26T05:47:40.762525 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 6 sales 2017– 2018 4 sales 2019 6 sales After 2019 4 sales $0K $200K $400K $600K $561K $660K $495K $641K Net sale price, average

The average is $641K for homes built after 2019 and $561K for homes built before 2017. It does not move in a straight line; homes built 2017–2018 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T05:47:40.785432 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 6 sales 2017– 2018 4 sales 2019 6 sales After 2019 4 sales $0 $100 $200 $202 $229 $197 $208 Net price per SF, average

The average is $208 per SF for homes built after 2019 and $202 per SF for homes built before 2017. It does not move in a straight line; homes built 2017–2018 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T05:47:40.806382 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 6 sales 2017– 2018 4 sales 2019 6 sales After 2019 4 sales 0 1,000 2,000 3,000 2,800 2,792 2,530 3,225 Living area (SF), average

The average is 3,225 SF for homes built after 2019 and 2,800 SF for homes built before 2017. It does not move in a straight line; homes built after 2019 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T05:47:40.827594 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 6 sales 2017– 2018 4 sales 2019 6 sales After 2019 4 sales 0 100 200 193 6 46 46 Days on market, median

The median is 46 days for homes built after 2019 and 193 days for homes built before 2017. It does not move in a straight line; homes built before 2017 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T05:47:40.850546 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 6 sales 2017– 2018 4 sales 2019 6 sales After 2019 4 sales 0.0% 2.5% 5.0% 7.5% 7.0% 2.7% 4.0% 5.5% Discount from original list, average

The average is 5.5% for homes built after 2019 and 7.0% for homes built before 2017. It does not move in a straight line; homes built before 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

2026-10-26T05:47:40.876041 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 17 25 25 50 67 50 0 75 100 0 Before 2017 2017–2018 2019 After 2019

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

  • 75% of homes built after 2019 had a price cut before sale, against 100% of homes built before 2017. Defined in 8.1.7.
  • 100% of homes built after 2019 had the seller pay closing costs or repairs, against 50% of homes built before 2017. Defined in 8.1.8.
  • 0% of homes built after 2019 have a view, against 17% 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 20176 sales2017–20184 sales20196 salesAfter 20194 salesAll20 sales
Net sale price average$560,522$659,925$495,017$641,262$576,899
Net price per SF average$202$229$197$208$207
Living area average2,8002,7922,5303,2252,802
Year built median20162018201920212018

5.10 The numbers: selling

Before 20176 sales2017–20184 sales20196 salesAfter 20194 salesAll20 sales
Days on market median1936464651
Discount from original list average7.0%2.7%4.0%5.5%4.9%
Price cut before sale100%25%67%75%70%
Seller paid closing costs or repairs50%25%50%100%55%
Has a view17%50%0%0%15%

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 · 20 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.

2026-10-26T05:47:40.894871 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 17 20 sales Sales per group View: 3 sales (15%) No view: 17 sales (85%)
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

2026-10-26T05:47:40.911736 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 17 sales $0K $200K $400K $600K $800K $727K $550K Net sale price, average

The average is $727K for homes with a view and $550K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T05:47:40.930831 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 17 sales $0 $100 $200 $247 $200 Net price per SF, average

The average is $247 per SF for homes with a view and $200 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T05:47:40.947791 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 17 sales 0 1,000 2,000 3,000 2,861 2,792 Living area (SF), average

The average is 2,861 SF for homes with a view and 2,792 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T05:47:40.993806 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 17 sales 2016 2017 2018 2019 2018 2019 Year built: median (dot) and middle half (bar)

The median is 2018 for homes with a view and 2019 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T05:47:41.012665 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 17 sales 0 25 50 75 100 103 50 Days on market, median

The median is 103 days for homes with a view and 50 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

2026-10-26T05:47:41.031285 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 17 sales 0.0% 2.0% 4.0% 6.0% 4.0% 5.1% Discount from original list, average

The average is 4.0% for homes with a view and 5.1% 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

2026-10-26T05:47:41.049952 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 67 0 71 65 View No view

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

  • 67% of homes with a view had a price cut before sale, against 71% 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 65% 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

View3 salesNo view17 salesAll20 sales
Net sale price average$726,667$550,469$576,899
Net price per SF average$247$200$207
Living area average2,8612,7922,802
Year built median201820192018

6.11 The numbers: selling

View3 salesNo view17 salesAll20 sales
Days on market median1035051
Discount from original list average4.0%5.1%4.9%
Price cut before sale67%71%70%
Seller paid closing costs or repairs0%65%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 Vizcaya.

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
20 resale sales. Average $576,899; median $522,175; standard deviation $190,631; middle half (25th–75th percentile) $444,975–$602,250; lowest $354,000, highest $1,100,000. 11 sales had a seller payment; their median payment was $1,000.

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
20 resale sales. Average $207; median $203; standard deviation $27; middle half (25th–75th percentile) $190–$218; lowest $156, highest $287.

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
20 resale sales. Average 2,802; median 2,721; standard deviation 872; middle half (25th–75th percentile) 2,208–3,169; lowest 1,508, highest 5,187.

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
20 resale sales. Average 2018; median 2018; standard deviation 2; middle half (25th–75th percentile) 2016–2019; lowest 2015, highest 2021.

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
20 resale sales. Average 75; median 51; standard deviation 74; middle half (25th–75th percentile) 37–77; lowest 0, highest 246. 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
20 resale sales. Average 4.9%; median 4.3%; standard deviation 3.6%; middle half (25th–75th percentile) 2.6%–7.4%; lowest −0.1%, highest 13.7%. 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
14 of 20 resale sales (70.0%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
11 of 20 resale sales (55.0%).

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
3 sales with a view, 17 without, 0 unclassified. Most common View entries: None 13, Neighborhood 5, Park/Greenbelt 2, See Remarks 1, Trees/Woods 1, Skyline 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 = Round Rock, SubdivisionName contains any of “vizcaya”, “vizcaya traditions”, “traditions at vizcaya” (case-insensitive). A record is kept when its subdivision name belongs to the Vizcaya family, the same rule comparable sales use (it includes Vizcaya (Traditions), Traditions at Vizcaya, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 20 closed Vizcaya records over the prior year, in ZIP 78665. 12 subdivision spellings kept: Traditions at Vizcaya (4); Vizcaya (Traditions) (4); Vizcaya Ph 1 (2); Vizcaya Ph 4D (2); Vizcaya Ph 6B & 7D (1); Vizcaya Ph 3B Sub (1); Vizcaya Ph 3E (1); Vizcaya Ph 2B Sub (1); Vizcaya Ph 2B (1); Vizcaya (1); Vizcaya Ph 4C (1); Vizcaya Ph 1 Sub (1). Names found by the search but not part of Vizcaya, left out: Heritage at Vizcaya (12); Heritage at Vizcaya 53s (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 13 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
20 single-family sales in the window: 20 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
20 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 $450K”.
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 $450K: $354,000–$429,900 (5 sales); $450K–$519K: $450,000–$519,350 (5 sales); $525K–$600K: $525,000–$600,000 (5 sales); Over $600K: $609,000–$1,100,000 (5 sales)
Quartiles by living area: Under 2,234 SF: 1,508–2,132 SF (5 sales); 2,234–2,711 SF: 2,234–2,711 SF (5 sales); 2,731–3,159 SF: 2,731–3,159 SF (5 sales); Over 3,159 SF: 3,200–5,187 SF (5 sales)
Quartiles by year built: Before 2017: 2015–2016 (6 sales); 2017–2018: 2017–2018 (4 sales); 2019: 2019–2019 (6 sales); After 2019: 2021–2021 (4 sales)
View and no view: View: MLS lists a view (3 sales); No view: None or Neighborhood (17 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 $576,899, median $522,175. Days on market: average 75, median 51: 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
2 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 = 0.5730.9042p < 0.0063Unclearε² = 0.030small
Living areaKruskal–WallisH = 15.6730.0013p < 0.0063Yesε² = 0.825large
Year builtKruskal–WallisH = 3.1430.3708p < 0.0063Unclearε² = 0.165large
Days on marketKruskal–WallisH = 1.9830.5763p < 0.0063Unclearε² = 0.104medium
Discount from original listKruskal–WallisH = 3.0930.3777p < 0.0063Unclearε² = 0.163large
Price cut before saleChi-squareχ² = 2.8630.4142p < 0.0063UnclearCramér’s V = 0.378medium
Seller paid closing costs or repairsChi-squareχ² = 2.2230.5276p < 0.0063UnclearCramér’s V = 0.333medium
Has a viewChi-squareχ² = 1.1830.7587p < 0.0063UnclearCramér’s V = 0.243small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 15.3330.0016p < 0.0063Yesε² = 0.807large
Net price per SFKruskal–WallisH = 5.2330.1558p < 0.0063Unclearε² = 0.275large
Year builtKruskal–WallisH = 2.5630.4645p < 0.0063Unclearε² = 0.135medium
Days on marketKruskal–WallisH = 0.8730.8315p < 0.0063Unclearε² = 0.046small
Discount from original listKruskal–WallisH = 4.4130.2209p < 0.0063Unclearε² = 0.232large
Price cut before saleChi-squareχ² = 0.9530.8128p < 0.0063UnclearCramér’s V = 0.218small
Seller paid closing costs or repairsChi-squareχ² = 0.6130.8950p < 0.0063UnclearCramér’s V = 0.174small
Has a viewChi-squareχ² = 4.3130.2295p < 0.0063UnclearCramér’s V = 0.464medium

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 20 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.