ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Siena-Section Siena-Sec

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 · 7:18 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
92
single-family resale homes
Median net sale price
$387,434
average $400,752
Median net price per SF
$174
average $171
Median days on market
32 days
average 65 days
1. SummaryResale homes · 92 sales · October 26, 2025 – October 25, 2026

This study looks at the 92 resale homes sold in Siena-Section Siena-Sec in the 365 days to October 25, 2026. A full year is used because only 57 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 sold92 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 $356K · 23 sales$356K–$387K · 23 sales$388K–$426K · 23 salesOver $426K · 23 sales
3. Quartiles by net sale priceResale homes · 92 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.

2026-10-26T07:18:48.386334 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 23 23 23 23 92 sales Sales per group Under $356K: 23 sales (25%) $356K–$387K: 23 sales (25%) $388K–$426K: 23 sales (25%) Over $426K: 23 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 $356K$356K–$387K$388K–$426KOver $426K
Higher-priced homes Over $426K
  • Are much larger.
  • Sell for less per square foot.
Lower-priced homes Under $356K
  • Are much smaller.
  • Sell for more per square foot.

3.2 At a glance

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

Under $356K$356K–$387K$388K–$426KOver $426KReal difference?
Net price per SF$179 per SF$183 per SFHighest$164 per SF$159 per SFLowest✓ large
Living area1,929 SFSmallest2,057 SF2,521 SF3,123 SFLargest✓ large
Year built2017201820182019unclear
Days on market55 days35 days44 days20 daysunclear
Discount from original list7.0%5.3%6.5%5.4%unclear
Price cut before sale57%61%48%35%unclear
Seller paid closing costs or repairs61%74%57%78%unclear
Has a view0%9%13%17%unclear

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

3.3 Homes over $426K sell for about $20 per SF (11%) less than homes under $356K

2026-10-26T07:18:48.414590 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $356K 23 sales $356K– $387K 23 sales $388K– $426K 23 sales Over $426K 23 sales $0 $100 $200 $179 $183 $164 $159 Net price per SF, average

The average is $159 per SF for homes over $426K and $179 per SF for homes under $356K. It does not move in a straight line; homes $356K–$387K are highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $426K are about 1,190 SF (62%) larger than homes under $356K

2026-10-26T07:18:48.436264 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $356K 23 sales $356K– $387K 23 sales $388K– $426K 23 sales Over $426K 23 sales 0 1,000 2,000 3,000 1,929 2,057 2,521 3,123 Living area (SF), average

The average is 3,123 SF for homes over $426K and 1,929 SF for homes under $356K. 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

2026-10-26T07:18:48.460100 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $356K 23 sales $356K– $387K 23 sales $388K– $426K 23 sales Over $426K 23 sales 2016 2017 2018 2019 2017 2018 2018 2019 Year built: median (dot) and middle half (bar)

The median is 2019 for homes over $426K and 2017 for homes under $356K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:18:48.482405 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $356K 23 sales $356K– $387K 23 sales $388K– $426K 23 sales Over $426K 23 sales 0 20 40 60 55 35 44 20 Days on market, median

The median is 20 days for homes over $426K and 55 days for homes under $356K. It does not move in a straight line; homes under $356K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:18:48.504309 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $356K 23 sales $356K– $387K 23 sales $388K– $426K 23 sales Over $426K 23 sales 0.0% 2.5% 5.0% 7.5% 7.0% 5.3% 6.5% 5.4% Discount from original list, average

The average is 5.4% for homes over $426K and 7.0% for homes under $356K. It does not move in a straight line; homes under $356K 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

2026-10-26T07:18:48.534429 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% 57 61 0 61 74 9 48 57 13 35 78 17 Under $356K $356K–$387K $388K–$426K Over $426K

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

  • 35% of homes over $426K had a price cut before sale, against 57% of homes under $356K. Defined in 8.1.7.
  • 78% of homes over $426K had the seller pay closing costs or repairs, against 61% of homes under $356K. Defined in 8.1.8.
  • 17% of homes over $426K have a view, against 0% of homes under $356K. 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 $356K23 sales$356K–$387K23 sales$388K–$426K23 salesOver $426K23 salesAll92 salesReal difference?
Net sale price average$334,789$371,998$407,578$488,642$400,752by design
Net price per SF average$179$183$164$159$171✓ large
Living area average1,9292,0572,5213,1232,407✓ large
Year built median20172018201820192018unclear

3.10 The numbers: selling

Under $356K23 sales$356K–$387K23 sales$388K–$426K23 salesOver $426K23 salesAll92 salesReal difference?
Days on market median5535442032unclear
Discount from original list average7.0%5.3%6.5%5.4%6.1%unclear
Price cut before sale57%61%48%35%50%unclear
Seller paid closing costs or repairs61%74%57%78%67%unclear
Has a view0%9%13%17%10%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 · 92 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.

2026-10-26T07:18:48.554926 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 23 23 23 23 92 sales Sales per group Under 1,936 SF: 23 sales (25%) 1,936–2,256 SF: 23 sales (25%) 2,263–2,721 SF: 23 sales (25%) Over 2,721 SF: 23 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 1,936 SF1,936–2,256 SF2,263–2,721 SFOver 2,721 SF
Larger homes Over 2,721 SF
  • Sell for less per square foot.
  • Sell for much more.
Smaller homes Under 1,936 SF
  • Sell for more per square foot.
  • 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 1,936 SF1,936–2,256 SF2,263–2,721 SFOver 2,721 SFReal difference?
Net sale price$341KLowest$378K$414K$469KHighest✓ large
Net price per SF$195 per SFHighest$182 per SF$165 per SF$144 per SFLowest✓ large
Year built2017201820182019unclear
Days on market35 days25 days38 days60 daysunclear
Discount from original list4.6%5.2%5.9%8.5%unclear
Price cut before sale48%61%39%52%unclear
Seller paid closing costs or repairs61%74%70%65%unclear
Has a view0%13%9%17%unclear

4.3 Homes over 2,721 SF sell for about $128K (38%) more than homes under 1,936 SF

2026-10-26T07:18:48.575918 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,936 SF 23 sales 1,936– 2,256 SF 23 sales 2,263– 2,721 SF 23 sales Over 2,721 SF 23 sales $0K $200K $400K $341K $378K $414K $469K Net sale price, average

The average is $469K for homes over 2,721 SF and $341K for homes under 1,936 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 2,721 SF sell for about $51 per SF (26%) less than homes under 1,936 SF

2026-10-26T07:18:48.597870 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,936 SF 23 sales 1,936– 2,256 SF 23 sales 2,263– 2,721 SF 23 sales Over 2,721 SF 23 sales $0 $100 $200 $195 $182 $165 $144 Net price per SF, average

The average is $144 per SF for homes over 2,721 SF and $195 per SF for homes under 1,936 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-10-26T07:18:48.621014 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,936 SF 23 sales 1,936– 2,256 SF 23 sales 2,263– 2,721 SF 23 sales Over 2,721 SF 23 sales 2016 2017 2018 2019 2017 2018 2018 2019 Year built: median (dot) and middle half (bar)

The median is 2019 for homes over 2,721 SF and 2017 for homes under 1,936 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:18:48.643314 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,936 SF 23 sales 1,936– 2,256 SF 23 sales 2,263– 2,721 SF 23 sales Over 2,721 SF 23 sales 0 20 40 60 35 25 38 60 Days on market, median

The median is 60 days for homes over 2,721 SF and 35 days for homes under 1,936 SF. It does not move in a straight line; homes over 2,721 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:18:48.665547 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,936 SF 23 sales 1,936– 2,256 SF 23 sales 2,263– 2,721 SF 23 sales Over 2,721 SF 23 sales 0.0% 5.0% 10.0% 4.6% 5.2% 5.9% 8.5% Discount from original list, average

The average is 8.5% for homes over 2,721 SF and 4.6% for homes under 1,936 SF. It rises step by step from the lowest range to the 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

2026-10-26T07:18:48.692662 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% 48 61 0 61 74 13 39 70 9 52 65 17 Under 1,936 SF 1,936–2,256 SF 2,263–2,721 SF Over 2,721 SF

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

  • 52% of homes over 2,721 SF had a price cut before sale, against 48% of homes under 1,936 SF. Defined in 8.1.7.
  • 65% of homes over 2,721 SF had the seller pay closing costs or repairs, against 61% of homes under 1,936 SF. Defined in 8.1.8.
  • 17% of homes over 2,721 SF have a view, against 0% of homes under 1,936 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 1,936 SF23 sales1,936–2,256 SF23 sales2,263–2,721 SF23 salesOver 2,721 SF23 salesAll92 salesReal difference?
Net sale price average$341,227$377,853$414,488$469,439$400,752✓ large
Net price per SF average$195$182$165$144$171✓ large
Living area average1,7592,0782,5133,2802,407by design
Year built median20172018201820192018unclear

4.10 The numbers: selling

Under 1,936 SF23 sales1,936–2,256 SF23 sales2,263–2,721 SF23 salesOver 2,721 SF23 salesAll92 salesReal difference?
Days on market median3525386032unclear
Discount from original list average4.6%5.2%5.9%8.5%6.1%unclear
Price cut before sale48%61%39%52%50%unclear
Seller paid closing costs or repairs61%74%70%65%67%unclear
Has a view0%13%9%17%10%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 · 92 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.

2026-10-26T07:18:48.713369 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 28 16 28 20 92 sales Sales per group Before 2017: 28 sales (30%) 2017: 16 sales (17%) 2018–2019: 28 sales (30%) After 2019: 20 sales (22%)
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 201720172018–2019After 2019Real difference?
Net sale price$400K$389K$401K$412Kunclear
Net price per SF$174 per SF$169 per SF$172 per SF$169 per SFunclear
Living area2,351 SF2,420 SF2,384 SF2,510 SFunclear
Days on market32 days23 days39 days58 daysunclear
Discount from original list5.4%5.6%7.1%5.8%unclear
Price cut before sale43%50%57%50%unclear
Seller paid closing costs or repairs71%69%75%50%unclear
Has a view11%6%11%10%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:18:48.733878 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 28 sales 2017 16 sales 2018– 2019 28 sales After 2019 20 sales $0K $200K $400K $400K $389K $401K $412K Net sale price, average

The average is $412K for homes built after 2019 and $400K for homes built before 2017. It does not move in a straight line; homes built after 2019 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:18:48.755780 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 28 sales 2017 16 sales 2018– 2019 28 sales After 2019 20 sales $0 $100 $200 $174 $169 $172 $169 Net price per SF, average

The average is $169 per SF for homes built after 2019 and $174 per SF for homes built before 2017. It does not move in a straight line; homes built before 2017 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:18:48.776709 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 28 sales 2017 16 sales 2018– 2019 28 sales After 2019 20 sales 0 1,000 2,000 3,000 2,351 2,420 2,384 2,510 Living area (SF), average

The average is 2,510 SF for homes built after 2019 and 2,351 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.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:18:48.798043 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 28 sales 2017 16 sales 2018– 2019 28 sales After 2019 20 sales 0 20 40 60 32 23 39 58 Days on market, median

The median is 58 days for homes built after 2019 and 32 days for homes built before 2017. It does not move in a straight line; homes built after 2019 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:18:48.820670 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 28 sales 2017 16 sales 2018– 2019 28 sales After 2019 20 sales 0.0% 2.5% 5.0% 7.5% 5.4% 5.6% 7.1% 5.8% Discount from original list, average

The average is 5.8% for homes built after 2019 and 5.4% for homes built before 2017. It does not move in a straight line; homes built 2018–2019 are 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

2026-10-26T07:18:48.846037 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% 43 71 11 50 69 6 57 75 11 50 50 10 Before 2017 2017 2018–2019 After 2019

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

  • 50% of homes built after 2019 had a price cut before sale, against 43% of homes built before 2017. Defined in 8.1.7.
  • 50% of homes built after 2019 had the seller pay closing costs or repairs, against 71% of homes built before 2017. Defined in 8.1.8.
  • 10% of homes built after 2019 have a view, against 11% of homes built before 2017. 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 201728 sales201716 sales2018–201928 salesAfter 201920 salesAll92 salesReal difference?
Net sale price average$399,658$388,881$400,796$411,716$400,752unclear
Net price per SF average$174$169$172$169$171unclear
Living area average2,3512,4202,3842,5102,407unclear
Year built median20162017201920202018by design

5.10 The numbers: selling

Before 201728 sales201716 sales2018–201928 salesAfter 201920 salesAll92 salesReal difference?
Days on market median3223395832unclear
Discount from original list average5.4%5.6%7.1%5.8%6.1%unclear
Price cut before sale43%50%57%50%50%unclear
Seller paid closing costs or repairs71%69%75%50%67%unclear
Has a view11%6%11%10%10%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 · 92 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. 6 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T07:18:48.864846 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 77 86 sales Sales per group View: 9 sales (10%) No view: 77 sales (90%)
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$438K$397Kunclear
Net price per SF$171 per SF$172 per SFunclear
Living area2,608 SF2,388 SFunclear
Year built20192018unclear
Days on market28 days35 daysunclear
Discount from original list5.5%6.1%unclear
Price cut before sale44%48%unclear
Seller paid closing costs or repairs67%66%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:18:48.880829 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 77 sales $0K $200K $400K $438K $397K Net sale price, average

The average is $438K for homes with a view and $397K 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

2026-10-26T07:18:48.898746 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 77 sales $0 $50 $100 $150 $200 $171 $172 Net price per SF, average

The average is $171 per SF for homes with a view and $172 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

2026-10-26T07:18:48.917742 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 77 sales 0 1,000 2,000 3,000 2,608 2,388 Living area (SF), average

The average is 2,608 SF for homes with a view and 2,388 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:18:49.008632 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 77 sales 2016 2017 2018 2019 2019 2018 Year built: median (dot) and middle half (bar)

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

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:18:49.027478 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 77 sales 0 10 20 30 40 28 35 Days on market, median

The median is 28 days for homes with a view and 35 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

2026-10-26T07:18:49.045845 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 9 sales No view 77 sales 0.0% 2.0% 4.0% 6.0% 5.5% 6.1% Discount from original list, average

The average is 5.5% for homes with a view and 6.1% 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

2026-10-26T07:18:49.064574 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 44 67 48 66 View No view

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

  • 44% of homes with a view had a price cut before sale, against 48% of homes without a view. Defined in 8.1.7.
  • 67% of homes with a view had the seller pay closing costs or repairs, against 66% 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

View9 salesNo view77 salesAll86 salesReal difference?
Net sale price average$438,317$397,111$401,423unclear
Net price per SF average$171$172$172unclear
Living area average2,6082,3882,411unclear
Year built median201920182018unclear

6.11 The numbers: selling

View9 salesNo view77 salesAll86 salesReal difference?
Days on market median283532unclear
Discount from original list average5.5%6.1%6.0%unclear
Price cut before sale44%48%48%unclear
Seller paid closing costs or repairs67%66%66%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 Siena-Section Siena-Sec.

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
92 resale sales. Average $400,752; median $387,434; standard deviation $64,979; middle half (25th–75th percentile) $355,458–$427,500; lowest $299,500, highest $657,400. 62 sales had a seller payment; their median payment was $6,850.

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
92 resale sales. Average $171; median $174; standard deviation $24; middle half (25th–75th percentile) $154–$189; lowest $100, highest $221.

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
92 resale sales. Average 2,407; median 2,260; standard deviation 626; middle half (25th–75th percentile) 1,935–2,721; lowest 1,561, highest 4,317.

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
92 resale sales. Average 2018; median 2018; standard deviation 2; middle half (25th–75th percentile) 2016–2019; lowest 2013, highest 2024.

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
92 resale sales. Average 65; median 32; standard deviation 77; middle half (25th–75th percentile) 14–83; lowest 2, highest 370. 0 sales went under contract on their listing date (0 days).

8.1.6 Discount from original list

In simple terms
How far below the first asking price the home sold, after seller payments. It measures how much negotiating room sellers gave up. A negative figure means the home sold above its first asking price.
Statistically
Discount % = (OriginalListPrice − Net) ÷ OriginalListPrice × 100, per sale; summarized by the mean.
The data
92 resale sales. Average 6.1%; median 5.2%; standard deviation 5.5%; middle half (25th–75th percentile) 2.7%–7.8%; lowest −2.8%, highest 32.0%. 4 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
46 of 92 resale sales (50.0%).

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
62 of 92 resale sales (67.4%).

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
9 sales with a view, 77 without, 6 unclassified. Most common View entries: None 47, Neighborhood 36, See Remarks 8, Park/Greenbelt 5, Pasture 3, Trees/Woods 2, Pool 1, Garden 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 “siena section siena sec”, “siena”, “siena-section siena-sec” (case-insensitive). A record is kept when its subdivision name belongs to the Siena-Section Siena-Sec family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 93 closed Siena-Section Siena-Sec records over the prior year, in ZIP 78665. 27 subdivision spellings kept, the most common: Siena (35); Siena Sec 7 (7); Siena Sec 25 (5); Siena Ph 1 Sec 24 (5); Siena Sec 14 (5); Siena Sec 28 (4); Siena Sec 23A (3); Siena Sec 5 (3); Siena Sec 26 (2); SIENA (2); Siena Sec 19 (2); Siena Sec 16 (2); and 15 more (18 records). Names found by the search but not part of Siena-Section Siena-Sec, left out: Siena Patio Homes (3).

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 57 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
92 single-family sales in the window: 92 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
92 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) with concessions above 10% of price

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 $356K”.
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 $356K: $299,500–$355,000 (23 sales); $356K–$387K: $355,610–$386,869 (23 sales); $388K–$426K: $388,000–$426,000 (23 sales); Over $426K: $432,000–$657,400 (23 sales)
Quartiles by living area: Under 1,936 SF: 1,561–1,933 SF (23 sales); 1,936–2,256 SF: 1,936–2,256 SF (23 sales); 2,263–2,721 SF: 2,263–2,721 SF (23 sales); Over 2,721 SF: 2,722–4,317 SF (23 sales)
Quartiles by year built: Before 2017: 2013–2016 (28 sales); 2017: 2017–2017 (16 sales); 2018–2019: 2018–2019 (28 sales); After 2019: 2020–2024 (20 sales)
View and no view: View: MLS lists a view (9 sales); No view: None or Neighborhood (77 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 $400,752, median $387,434. Days on market: average 65, median 32: 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; Quartiles by year built: m = 8, threshold p < 0.0063; 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
4 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 = 20.2630.0001p < 0.0063Yesε² = 0.223large
Living areaKruskal–WallisH = 56.653< 0.0001p < 0.0063Yesε² = 0.622large
Year builtKruskal–WallisH = 0.3130.9589p < 0.0063Unclearε² = 0.003negligible
Days on marketKruskal–WallisH = 2.8630.4136p < 0.0063Unclearε² = 0.031small
Discount from original listKruskal–WallisH = 0.4230.9360p < 0.0063Unclearε² = 0.005negligible
Price cut before saleChi-squareχ² = 3.6530.3016p < 0.0063UnclearCramér’s V = 0.199small
Seller paid closing costs or repairsChi-squareχ² = 3.3630.3389p < 0.0063UnclearCramér’s V = 0.191small
Has a viewChi-squareχ² = 4.3130.2298p < 0.0063UnclearCramér’s V = 0.216small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 57.923< 0.0001p < 0.0063Yesε² = 0.636large
Net price per SFKruskal–WallisH = 63.053< 0.0001p < 0.0063Yesε² = 0.693large
Year builtKruskal–WallisH = 1.0630.7872p < 0.0063Unclearε² = 0.012small
Days on marketKruskal–WallisH = 1.7230.6332p < 0.0063Unclearε² = 0.019small
Discount from original listKruskal–WallisH = 2.7130.4380p < 0.0063Unclearε² = 0.030small
Price cut before saleChi-squareχ² = 2.2630.5201p < 0.0063UnclearCramér’s V = 0.157small
Seller paid closing costs or repairsChi-squareχ² = 0.9930.8039p < 0.0063UnclearCramér’s V = 0.104small
Has a viewChi-squareχ² = 4.3130.2298p < 0.0063UnclearCramér’s V = 0.216small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 0.9430.8147p < 0.0063Unclearε² = 0.010small
Net price per SFKruskal–WallisH = 0.4630.9285p < 0.0063Unclearε² = 0.005negligible
Living areaKruskal–WallisH = 0.5430.9109p < 0.0063Unclearε² = 0.006negligible
Days on marketKruskal–WallisH = 3.0830.3802p < 0.0063Unclearε² = 0.034small
Discount from original listKruskal–WallisH = 1.4930.6846p < 0.0063Unclearε² = 0.016small
Price cut before saleChi-squareχ² = 1.1430.7667p < 0.0063UnclearCramér’s V = 0.111small
Seller paid closing costs or repairsChi-squareχ² = 3.7130.2944p < 0.0063UnclearCramér’s V = 0.201small
Has a viewChi-squareχ² = 0.2830.9633p < 0.0063UnclearCramér’s V = 0.055negligible

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 501.00—0.0298p < 0.0063Unclearrank-biserial r = 0.446medium
Net price per SFMann–Whitney UU = 342.00—0.9550p < 0.0063Unclearrank-biserial r = 0.013negligible
Living areaMann–Whitney UU = 454.00—0.1312p < 0.0063Unclearrank-biserial r = 0.310medium
Year builtMann–Whitney UU = 355.00—0.9085p < 0.0063Unclearrank-biserial r = 0.025negligible
Days on marketMann–Whitney UU = 314.00—0.6516p < 0.0063Unclearrank-biserial r = 0.094negligible
Discount from original listMann–Whitney UU = 359.00—0.8656p < 0.0063Unclearrank-biserial r = 0.036negligible
Price cut before saleChi-squareχ² = 0.0410.8375p < 0.0063UnclearCramér’s V = 0.022negligible
Seller paid closing costs or repairsChi-squareχ² = 0.0010.9793p < 0.0063UnclearCramér’s V = 0.003negligible

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 1 sale(s) with concessions above 10% of price. 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 92 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.