ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Rancho Sienna

Georgetown, TX 78628
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 · 7:08 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
56
single-family resale homes
Median net sale price
$439,650
average $466,632
Median net price per SF
$184
average $183
Median days on market
76 days
average 95 days
1. SummaryResale homes · 56 sales · October 26, 2025 – October 25, 2026

This study looks at the 56 resale homes sold in Rancho Sienna in the 365 days to October 25, 2026. A full year is used because only 33 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 sold56 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 $380K · 13 sales$380K–$439K · 15 sales$440K–$540K · 14 salesOver $540K · 14 sales
3. Quartiles by net sale priceResale homes · 56 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.

2026-10-26T07:08:31.907329 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 13 15 14 14 56 sales Sales per group Under $380K: 13 sales (23%) $380K–$439K: 15 sales (27%) $440K–$540K: 14 sales (25%) Over $540K: 14 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 $380K$380K–$439K$440K–$540KOver $540K
Higher-priced homes Over $540K
  • Are much larger.
  • Sell for more per square foot.
Lower-priced homes Under $380K
  • Are much smaller.
  • Sell for less per square foot.

3.2 At a glance

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

Under $380K$380K–$439K$440K–$540KOver $540KReal difference?
Net price per SF$160 per SFLowest$180 per SF$190 per SF$200 per SFHighest✓ large
Living area2,234 SFSmallest2,273 SF2,562 SF3,128 SFLargest✓ large
Year built2019201920182020unclear
Days on market113 days53 days86 days50 daysunclear
Discount from original list11.8%6.6%5.0%6.4%unclear
Price cut before sale69%47%36%64%unclear
Seller paid closing costs or repairs46%73%71%57%unclear
Has a view15%27%50%43%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 $540K sell for about $40 per SF (25%) more than homes under $380K

2026-10-26T07:08:31.935974 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $380K 13 sales $380K– $439K 15 sales $440K– $540K 14 sales Over $540K 14 sales $0 $100 $200 $160 $180 $190 $200 Net price per SF, average

The average is $200 per SF for homes over $540K and $160 per SF for homes under $380K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $540K are about 890 SF (40%) larger than homes under $380K

2026-10-26T07:08:31.958115 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $380K 13 sales $380K– $439K 15 sales $440K– $540K 14 sales Over $540K 14 sales 0 1,000 2,000 3,000 2,234 2,273 2,562 3,128 Living area (SF), average

The average is 3,128 SF for homes over $540K and 2,234 SF for homes under $380K. 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

2026-10-26T07:08:31.982608 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $380K 13 sales $380K– $439K 15 sales $440K– $540K 14 sales Over $540K 14 sales 2017 2018 2019 2020 2019 2019 2018 2020 Year built: median (dot) and middle half (bar)

The median is 2020 for homes over $540K and 2019 for homes under $380K. It does not move in a straight line; homes over $540K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:08:32.005830 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $380K 13 sales $380K– $439K 15 sales $440K– $540K 14 sales Over $540K 14 sales 0 50 100 113 53 86 50 Days on market, median

The median is 50 days for homes over $540K and 113 days for homes under $380K. It does not move in a straight line; homes under $380K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:08:32.027849 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $380K 13 sales $380K– $439K 15 sales $440K– $540K 14 sales Over $540K 14 sales 0.0% 5.0% 10.0% 11.8% 6.6% 5.0% 6.4% Discount from original list, average

The average is 6.4% for homes over $540K and 11.8% for homes under $380K. It does not move in a straight line; homes under $380K 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

2026-10-26T07:08:32.058028 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% 69 46 15 47 73 27 36 71 50 64 57 43 Under $380K $380K–$439K $440K–$540K Over $540K

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

  • 64% of homes over $540K had a price cut before sale, against 69% of homes under $380K. Defined in 8.1.7.
  • 57% of homes over $540K had the seller pay closing costs or repairs, against 46% of homes under $380K. Defined in 8.1.8.
  • 43% of homes over $540K have a view, against 15% of homes under $380K. 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 $380K13 sales$380K–$439K15 sales$440K–$540K14 salesOver $540K14 salesAll56 salesReal difference?
Net sale price average$349,176$404,947$483,111$625,311$466,632by design
Net price per SF average$160$180$190$200$183✓ large
Living area average2,2342,2732,5623,1282,550✓ large
Year built median20192019201820202018unclear

3.10 The numbers: selling

Under $380K13 sales$380K–$439K15 sales$440K–$540K14 salesOver $540K14 salesAll56 salesReal difference?
Days on market median11353865076unclear
Discount from original list average11.8%6.6%5.0%6.4%7.4%unclear
Price cut before sale69%47%36%64%54%unclear
Seller paid closing costs or repairs46%73%71%57%62%unclear
Has a view15%27%50%43%34%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 · 56 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.

2026-10-26T07:08:32.078492 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 14 14 14 56 sales Sales per group Under 2,190 SF: 14 sales (25%) 2,190–2,568 SF: 14 sales (25%) 2,577–2,752 SF: 14 sales (25%) Over 2,752 SF: 14 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 2,190 SF2,190–2,568 SF2,577–2,752 SFOver 2,752 SF
Larger homes Over 2,752 SF
  • Sell for much more.
Smaller homes Under 2,190 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 2,190 SF2,190–2,568 SF2,577–2,752 SFOver 2,752 SFReal difference?
Net sale price$381KLowest$424K$451K$612KHighest✓ large
Net price per SF$191 per SF$177 per SF$170 per SF$194 per SFunclear
Year built2019201820182018unclear
Days on market48 days105 days100 days50 daysunclear
Discount from original list6.1%9.3%8.5%5.5%unclear
Price cut before sale43%64%50%57%unclear
Seller paid closing costs or repairs71%64%57%57%unclear
Has a view36%21%43%36%unclear

4.3 Homes over 2,752 SF sell for about $231K (61%) more than homes under 2,190 SF

2026-10-26T07:08:32.098959 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,190 SF 14 sales 2,190– 2,568 SF 14 sales 2,577– 2,752 SF 14 sales Over 2,752 SF 14 sales $0K $200K $400K $600K $381K $424K $451K $612K Net sale price, average

The average is $612K for homes over 2,752 SF and $381K for homes under 2,190 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

2026-10-26T07:08:32.121159 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,190 SF 14 sales 2,190– 2,568 SF 14 sales 2,577– 2,752 SF 14 sales Over 2,752 SF 14 sales $0 $100 $200 $191 $177 $170 $194 Net price per SF, average

The average is $194 per SF for homes over 2,752 SF and $191 per SF for homes under 2,190 SF. It does not move in a straight line; homes over 2,752 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T07:08:32.144993 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,190 SF 14 sales 2,190– 2,568 SF 14 sales 2,577– 2,752 SF 14 sales Over 2,752 SF 14 sales 2016 2017 2018 2019 2020 2019 2018 2018 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over 2,752 SF and 2019 for homes under 2,190 SF. It does not move in a straight line; homes under 2,190 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:08:32.168065 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,190 SF 14 sales 2,190– 2,568 SF 14 sales 2,577– 2,752 SF 14 sales Over 2,752 SF 14 sales 0 50 100 48 105 100 50 Days on market, median

The median is 50 days for homes over 2,752 SF and 48 days for homes under 2,190 SF. It does not move in a straight line; homes 2,190–2,568 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:08:32.189712 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,190 SF 14 sales 2,190– 2,568 SF 14 sales 2,577– 2,752 SF 14 sales Over 2,752 SF 14 sales 0.0% 5.0% 10.0% 6.1% 9.3% 8.5% 5.5% Discount from original list, average

The average is 5.5% for homes over 2,752 SF and 6.1% for homes under 2,190 SF. It does not move in a straight line; homes 2,190–2,568 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

2026-10-26T07:08:32.215815 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 36 64 64 21 50 57 43 57 57 36 Under 2,190 SF 2,190–2,568 SF 2,577–2,752 SF Over 2,752 SF

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

  • 57% of homes over 2,752 SF had a price cut before sale, against 43% of homes under 2,190 SF. Defined in 8.1.7.
  • 57% of homes over 2,752 SF had the seller pay closing costs or repairs, against 71% of homes under 2,190 SF. Defined in 8.1.8.
  • 36% of homes over 2,752 SF have a view, against 36% of homes under 2,190 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 2,190 SF14 sales2,190–2,568 SF14 sales2,577–2,752 SF14 salesOver 2,752 SF14 salesAll56 salesReal difference?
Net sale price average$380,551$423,529$450,895$611,554$466,632✓ large
Net price per SF average$191$177$170$194$183unclear
Living area average2,0042,3912,6583,1462,550by design
Year built median20192018201820182018unclear

4.10 The numbers: selling

Under 2,190 SF14 sales2,190–2,568 SF14 sales2,577–2,752 SF14 salesOver 2,752 SF14 salesAll56 salesReal difference?
Days on market median481051005076unclear
Discount from original list average6.1%9.3%8.5%5.5%7.4%unclear
Price cut before sale43%64%50%57%54%unclear
Seller paid closing costs or repairs71%64%57%57%62%unclear
Has a view36%21%43%36%34%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 · 56 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.

2026-10-26T07:08:32.236214 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 18 6 20 56 sales Sales per group Before 2017: 12 sales (21%) 2017–2018: 18 sales (32%) 2019: 6 sales (11%) After 2019: 20 sales (36%)
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 20172017–20182019After 2019Real difference?
Net sale price$483K$450K$412K$488Kunclear
Net price per SF$178 per SF$182 per SF$183 per SF$186 per SFunclear
Living area2,700 SF2,478 SF2,259 SF2,612 SFunclear
Days on market74 days54 days70 days82 daysunclear
Discount from original list7.3%7.0%4.7%8.6%unclear
Price cut before sale42%56%50%60%unclear
Seller paid closing costs or repairs75%72%67%45%unclear
Has a view25%33%33%40%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:08:32.257152 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 12 sales 2017– 2018 18 sales 2019 6 sales After 2019 20 sales $0K $200K $400K $483K $450K $412K $488K Net sale price, average

The average is $488K for homes built after 2019 and $483K 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

2026-10-26T07:08:32.279098 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 12 sales 2017– 2018 18 sales 2019 6 sales After 2019 20 sales $0 $100 $200 $178 $182 $183 $186 Net price per SF, average

The average is $186 per SF for homes built after 2019 and $178 per SF for homes built before 2017. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:08:32.300197 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 12 sales 2017– 2018 18 sales 2019 6 sales After 2019 20 sales 0 1,000 2,000 3,000 2,700 2,478 2,259 2,612 Living area (SF), average

The average is 2,612 SF for homes built after 2019 and 2,700 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.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:08:32.322019 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 12 sales 2017– 2018 18 sales 2019 6 sales After 2019 20 sales 0 25 50 75 74 54 70 82 Days on market, median

The median is 82 days for homes built after 2019 and 74 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

2026-10-26T07:08:32.344584 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2017 12 sales 2017– 2018 18 sales 2019 6 sales After 2019 20 sales 0.0% 5.0% 10.0% 7.3% 7.0% 4.7% 8.6% Discount from original list, average

The average is 8.6% for homes built after 2019 and 7.3% for homes built before 2017. It does not move in a straight line; homes built after 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

2026-10-26T07:08:32.369697 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% 42 75 25 56 72 33 50 67 33 60 45 40 Before 2017 2017–2018 2019 After 2019

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

  • 60% of homes built after 2019 had a price cut before sale, against 42% of homes built before 2017. Defined in 8.1.7.
  • 45% of homes built after 2019 had the seller pay closing costs or repairs, against 75% of homes built before 2017. Defined in 8.1.8.
  • 40% of homes built after 2019 have a view, against 25% 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 201712 sales2017–201818 sales20196 salesAfter 201920 salesAll56 salesReal difference?
Net sale price average$483,396$450,013$411,858$487,962$466,632unclear
Net price per SF average$178$182$183$186$183unclear
Living area average2,7002,4782,2592,6122,550unclear
Year built median20152018201920202018by design

5.10 The numbers: selling

Before 201712 sales2017–201818 sales20196 salesAfter 201920 salesAll56 salesReal difference?
Days on market median7454708276unclear
Discount from original list average7.3%7.0%4.7%8.6%7.4%unclear
Price cut before sale42%56%50%60%54%unclear
Seller paid closing costs or repairs75%72%67%45%62%unclear
Has a view25%33%33%40%34%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 · 56 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. 4 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T07:08:32.387534 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 19 33 52 sales Sales per group View: 19 sales (37%) No view: 33 sales (63%)
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$491K$460Kunclear
Net price per SF$189 per SF$180 per SFunclear
Living area2,592 SF2,550 SFunclear
Year built20192018unclear
Days on market57 days81 daysunclear
Discount from original list7.8%6.9%unclear
Price cut before sale53%58%unclear
Seller paid closing costs or repairs63%64%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:08:32.403433 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 33 sales $0K $200K $400K $491K $460K Net sale price, average

The average is $491K for homes with a view and $460K 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

2026-10-26T07:08:32.421298 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 33 sales $0 $50 $100 $150 $200 $189 $180 Net price per SF, average

The average is $189 per SF for homes with a view and $180 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

2026-10-26T07:08:32.503534 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 33 sales 0 1,000 2,000 3,000 2,592 2,550 Living area (SF), average

The average is 2,592 SF for homes with a view and 2,550 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:08:32.524239 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 33 sales 2017 2018 2019 2020 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

2026-10-26T07:08:32.542644 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 33 sales 0 20 40 60 80 57 81 Days on market, median

The median is 57 days for homes with a view and 81 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

2026-10-26T07:08:32.562001 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 19 sales No view 33 sales 0.0% 2.0% 4.0% 6.0% 8.0% 7.8% 6.9% Discount from original list, average

The average is 7.8% for homes with a view and 6.9% 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

2026-10-26T07:08:32.581004 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 53 63 58 64 View No view

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

  • 53% of homes with a view had a price cut before sale, against 58% of homes without a view. Defined in 8.1.7.
  • 63% of homes with a view had the seller pay closing costs or repairs, against 64% 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

View19 salesNo view33 salesAll52 salesReal difference?
Net sale price average$491,268$459,958$471,398unclear
Net price per SF average$189$180$183unclear
Living area average2,5922,5502,565unclear
Year built median201920182018unclear

6.11 The numbers: selling

View19 salesNo view33 salesAll52 salesReal difference?
Days on market median578178unclear
Discount from original list average7.8%6.9%7.2%unclear
Price cut before sale53%58%56%unclear
Seller paid closing costs or repairs63%64%63%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 Rancho Sienna.

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
56 resale sales. Average $466,632; median $439,650; standard deviation $112,657; middle half (25th–75th percentile) $380,000–$544,175; lowest $284,681, highest $771,000. 35 sales had a seller payment; their median payment was $10,000.

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
56 resale sales. Average $183; median $184; standard deviation $25; middle half (25th–75th percentile) $170–$201; lowest $110, highest $250.

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
56 resale sales. Average 2,550; median 2,572; standard deviation 451; middle half (25th–75th percentile) 2,187–2,760; lowest 1,465, highest 3,798.

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
56 resale sales. Average 2018; median 2018; standard deviation 2; middle half (25th–75th percentile) 2017–2020; lowest 2013, 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
56 resale sales. Average 95; median 76; standard deviation 88; middle half (25th–75th percentile) 30–127; lowest 0, highest 409. 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
56 resale sales. Average 7.4%; median 6.8%; standard deviation 6.3%; middle half (25th–75th percentile) 2.2%–10.1%; lowest −1.1%, highest 24.7%. 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
30 of 56 resale sales (53.6%).

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
35 of 56 resale sales (62.5%).

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
19 sales with a view, 33 without, 4 unclassified. Most common View entries: None 20, Neighborhood 18, Park/Greenbelt 6, Hill Country 6, Trees/Woods 5, See Remarks 4, Pond 3, Lake 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 = Georgetown, SubdivisionName contains any of “rancho sienna” (case-insensitive). A record is kept when its subdivision name belongs to the Rancho Sienna family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 56 closed Rancho Sienna records over the prior year, in ZIP 78628. 24 subdivision spellings kept, the most common: Rancho Sienna (25); Rancho Sienna Sec 16 (3); Rancho Sienna Sec 01 (2); Rancho Sienna Ph 2 Sec 4 (2); Rancho Sienna Sec 5B (2); Rancho Sienna Sec 7 (2); Rancho Sienna Sec 15 (2); RANCHO SIENNA (2); Rancho Sienna Sec 18B (1); Rancho Sienna Sec 5A (1); Rancho Sienna Sec 13A & 13B (1); Rancho Sienna Sec 19B (1); and 12 more (12 records). 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 33 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
56 single-family sales in the window: 56 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
56 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 $380K”.
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 $380K: $284,681–$379,200 (13 sales); $380K–$439K: $380,000–$439,299 (15 sales); $440K–$540K: $440,000–$539,900 (14 sales); Over $540K: $557,000–$771,000 (14 sales)
Quartiles by living area: Under 2,190 SF: 1,465–2,178 SF (14 sales); 2,190–2,568 SF: 2,190–2,568 SF (14 sales); 2,577–2,752 SF: 2,577–2,752 SF (14 sales); Over 2,752 SF: 2,786–3,798 SF (14 sales)
Quartiles by year built: Before 2017: 2013–2016 (12 sales); 2017–2018: 2017–2018 (18 sales); 2019: 2019–2019 (6 sales); After 2019: 2020–2021 (20 sales)
View and no view: View: MLS lists a view (19 sales); No view: None or Neighborhood (33 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 $466,632, median $439,650. Days on market: average 95, median 76: 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
3 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 = 17.9230.0005p < 0.0063Yesε² = 0.326large
Living areaKruskal–WallisH = 33.603< 0.0001p < 0.0063Yesε² = 0.611large
Year builtKruskal–WallisH = 4.4330.2189p < 0.0063Unclearε² = 0.080medium
Days on marketKruskal–WallisH = 3.8030.2836p < 0.0063Unclearε² = 0.069medium
Discount from original listKruskal–WallisH = 6.3830.0947p < 0.0063Unclearε² = 0.116medium
Price cut before saleChi-squareχ² = 4.0130.2604p < 0.0063UnclearCramér’s V = 0.268small
Seller paid closing costs or repairsChi-squareχ² = 2.8830.4104p < 0.0063UnclearCramér’s V = 0.227small
Has a viewChi-squareχ² = 4.4630.2161p < 0.0063UnclearCramér’s V = 0.282small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 31.003< 0.0001p < 0.0063Yesε² = 0.564large
Net price per SFKruskal–WallisH = 7.5730.0558p < 0.0063Unclearε² = 0.138medium
Year builtKruskal–WallisH = 0.9230.8199p < 0.0063Unclearε² = 0.017small
Days on marketKruskal–WallisH = 3.8130.2827p < 0.0063Unclearε² = 0.069medium
Discount from original listKruskal–WallisH = 3.2430.3558p < 0.0063Unclearε² = 0.059small
Price cut before saleChi-squareχ² = 1.4430.6971p < 0.0063UnclearCramér’s V = 0.160small
Seller paid closing costs or repairsChi-squareχ² = 0.8430.8403p < 0.0063UnclearCramér’s V = 0.122small
Has a viewChi-squareχ² = 1.5130.6792p < 0.0063UnclearCramér’s V = 0.164small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 3.0530.3840p < 0.0063Unclearε² = 0.055small
Net price per SFKruskal–WallisH = 0.7230.8696p < 0.0063Unclearε² = 0.013small
Living areaKruskal–WallisH = 5.1430.1621p < 0.0063Unclearε² = 0.093medium
Days on marketKruskal–WallisH = 1.0730.7851p < 0.0063Unclearε² = 0.019small
Discount from original listKruskal–WallisH = 2.1630.5390p < 0.0063Unclearε² = 0.039small
Price cut before saleChi-squareχ² = 1.0830.7830p < 0.0063UnclearCramér’s V = 0.139small
Seller paid closing costs or repairsChi-squareχ² = 4.1830.2423p < 0.0063UnclearCramér’s V = 0.273small
Has a viewChi-squareχ² = 0.7630.8591p < 0.0063UnclearCramér’s V = 0.116small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 394.00—0.1284p < 0.0063Unclearrank-biserial r = 0.257small
Net price per SFMann–Whitney UU = 389.00—0.1541p < 0.0063Unclearrank-biserial r = 0.241small
Living areaMann–Whitney UU = 337.00—0.6621p < 0.0063Unclearrank-biserial r = 0.075negligible
Year builtMann–Whitney UU = 341.00—0.6024p < 0.0063Unclearrank-biserial r = 0.088negligible
Days on marketMann–Whitney UU = 260.00—0.3138p < 0.0063Unclearrank-biserial r = 0.171small
Discount from original listMann–Whitney UU = 324.00—0.8493p < 0.0063Unclearrank-biserial r = 0.033negligible
Price cut before saleChi-squareχ² = 0.1210.7296p < 0.0063UnclearCramér’s V = 0.048negligible
Seller paid closing costs or repairsChi-squareχ² = 0.0010.9725p < 0.0063UnclearCramér’s V = 0.005negligible

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 56 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.