ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Parkside at Mayfield Ranch

Georgetown, TX 78628
Resale homes · closed Oct 28 – Oct 27, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 28, 2026 · 7:35 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
29
single-family resale homes
Median net sale price
$569,000
average $593,741
Median net price per SF
$198
average $199
Median days on market
33 days
average 71 days
1. SummaryResale homes · 29 sales · October 28, 2025 – October 27, 2026

This study looks at the 29 resale homes sold in Parkside at Mayfield Ranch in the 365 days to October 27, 2026. A full year is used because only 17 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 sold29 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 $523K · 7 sales$523K–$562K · 7 sales$569K–$660K · 8 salesOver $660K · 7 sales
3. Quartiles by net sale priceResale homes · 29 sales · October 28, 2025 – October 27, 2026

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

2026-10-28T07:35:15.896030 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 8 7 29 sales Sales per group Under $523K: 7 sales (24%) $523K–$562K: 7 sales (24%) $569K–$660K: 8 sales (28%) Over $660K: 7 sales (24%)
Bottom line

3.1 Key differences

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

Under $523K$523K–$562K$569K–$660KOver $660K
Higher-priced homes Over $660K
  • Are much larger.
Lower-priced homes Under $523K
  • 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 $523K$523K–$562K$569K–$660KOver $660KReal difference?
Net price per SF$191 per SF$188 per SF$209 per SF$207 per SFunclear
Living area2,357 SFSmallest2,885 SF3,013 SF3,694 SFLargest✓ large
Year built2013201120142015unclear
Days on market78 days49 days30 days17 daysunclear
Discount from original list7.7%5.5%3.3%3.9%unclear
Price cut before sale57%43%38%14%unclear
Seller paid closing costs or repairs71%57%50%57%unclear
Has a view14%14%62%14%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

2026-10-28T07:35:15.924292 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $523K 7 sales $523K– $562K 7 sales $569K– $660K 8 sales Over $660K 7 sales $0 $100 $200 $191 $188 $209 $207 Net price per SF, average

The average is $207 per SF for homes over $660K and $191 per SF for homes under $523K. It does not move in a straight line; homes $569K–$660K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $660K are about 1,340 SF (57%) larger than homes under $523K

2026-10-28T07:35:15.946070 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $523K 7 sales $523K– $562K 7 sales $569K– $660K 8 sales Over $660K 7 sales 0 2,000 4,000 2,357 2,885 3,013 3,694 Living area (SF), average

The average is 3,694 SF for homes over $660K and 2,357 SF for homes under $523K. 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

2026-10-28T07:35:15.969651 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $523K 7 sales $523K– $562K 7 sales $569K– $660K 8 sales Over $660K 7 sales 2010 2012 2014 2016 2013 2011 2014 2015 Year built: median (dot) and middle half (bar)

The median is 2015 for homes over $660K and 2013 for homes under $523K. It does not move in a straight line; homes over $660K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-28T07:35:15.992403 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $523K 7 sales $523K– $562K 7 sales $569K– $660K 8 sales Over $660K 7 sales 0 25 50 75 78 49 30 17 Days on market, median

The median is 17 days for homes over $660K and 78 days for homes under $523K. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-28T07:35:16.014847 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $523K 7 sales $523K– $562K 7 sales $569K– $660K 8 sales Over $660K 7 sales 0.0% 2.5% 5.0% 7.5% 7.7% 5.5% 3.3% 3.9% Discount from original list, average

The average is 3.9% for homes over $660K and 7.7% for homes under $523K. It does not move in a straight line; homes under $523K 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

2026-10-28T07:35:16.044438 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 71 14 43 57 14 38 50 62 14 57 14 Under $523K $523K–$562K $569K–$660K Over $660K

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

  • 14% of homes over $660K had a price cut before sale, against 57% of homes under $523K. Defined in 8.1.7.
  • 57% of homes over $660K had the seller pay closing costs or repairs, against 71% of homes under $523K. Defined in 8.1.8.
  • 14% of homes over $660K have a view, against 14% of homes under $523K. 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 $523K7 sales$523K–$562K7 sales$569K–$660K8 salesOver $660K7 salesAll29 salesReal difference?
Net sale price average$440,626$540,786$623,688$765,587$593,741by design
Net price per SF average$191$188$209$207$199unclear
Living area average2,3572,8853,0133,6942,988✓ large
Year built median20132011201420152014unclear

3.10 The numbers: selling

Under $523K7 sales$523K–$562K7 sales$569K–$660K8 salesOver $660K7 salesAll29 salesReal difference?
Days on market median7849301733unclear
Discount from original list average7.7%5.5%3.3%3.9%5.0%unclear
Price cut before sale57%43%38%14%38%unclear
Seller paid closing costs or repairs71%57%50%57%59%unclear
Has a view14%14%62%14%28%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 · 29 sales · October 28, 2025 – October 27, 2026

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

2026-10-28T07:35:16.064502 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 8 7 29 sales Sales per group Under 2,740 SF: 7 sales (24%) 2,740–2,959 SF: 7 sales (24%) 2,985–3,476 SF: 8 sales (28%) Over 3,476 SF: 7 sales (24%)
Bottom line

4.1 Key differences

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

Under 2,740 SF2,740–2,959 SF2,985–3,476 SFOver 3,476 SF
Larger homes Over 3,476 SF
  • Sell for much more.
Smaller homes Under 2,740 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 2,740 SF2,740–2,959 SF2,985–3,476 SFOver 3,476 SFReal difference?
Net sale price$460KLowest$546K$611K$755KHighest✓ large
Net price per SF$209 per SF$189 per SF$195 per SF$203 per SFunclear
Year built2015201520132015unclear
Days on market18 days42 days90 days33 daysunclear
Discount from original list4.6%5.1%5.7%4.6%unclear
Price cut before sale29%43%50%29%unclear
Seller paid closing costs or repairs43%86%50%57%unclear
Has a view29%14%50%14%unclear

4.3 Homes over 3,476 SF sell for about $295K (64%) more than homes under 2,740 SF

2026-10-28T07:35:16.085338 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,740 SF 7 sales 2,740– 2,959 SF 7 sales 2,985– 3,476 SF 8 sales Over 3,476 SF 7 sales $0K $250K $500K $750K $460K $546K $611K $755K Net sale price, average

The average is $755K for homes over 3,476 SF and $460K for homes under 2,740 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

2026-10-28T07:35:16.108308 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,740 SF 7 sales 2,740– 2,959 SF 7 sales 2,985– 3,476 SF 8 sales Over 3,476 SF 7 sales $0 $100 $200 $209 $189 $195 $203 Net price per SF, average

The average is $203 per SF for homes over 3,476 SF and $209 per SF for homes under 2,740 SF. It does not move in a straight line; homes under 2,740 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-28T07:35:16.131193 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,740 SF 7 sales 2,740– 2,959 SF 7 sales 2,985– 3,476 SF 8 sales Over 3,476 SF 7 sales 2010 2012 2014 2016 2015 2015 2013 2015 Year built: median (dot) and middle half (bar)

The median is 2015 for homes over 3,476 SF and 2015 for homes under 2,740 SF. It does not move in a straight line; homes under 2,740 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-28T07:35:16.153930 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,740 SF 7 sales 2,740– 2,959 SF 7 sales 2,985– 3,476 SF 8 sales Over 3,476 SF 7 sales 0 50 100 18 42 90 33 Days on market, median

The median is 33 days for homes over 3,476 SF and 18 days for homes under 2,740 SF. It does not move in a straight line; homes 2,985–3,476 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-28T07:35:16.175598 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,740 SF 7 sales 2,740– 2,959 SF 7 sales 2,985– 3,476 SF 8 sales Over 3,476 SF 7 sales 0.0% 2.0% 4.0% 6.0% 4.6% 5.1% 5.7% 4.6% Discount from original list, average

The average is 4.6% for homes over 3,476 SF and 4.6% for homes under 2,740 SF. It does not move in a straight line; homes 2,985–3,476 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

2026-10-28T07:35:16.201950 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% 29 43 29 43 86 14 50 50 50 29 57 14 Under 2,740 SF 2,740–2,959 SF 2,985–3,476 SF Over 3,476 SF

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

  • 29% of homes over 3,476 SF had a price cut before sale, against 29% of homes under 2,740 SF. Defined in 8.1.7.
  • 57% of homes over 3,476 SF had the seller pay closing costs or repairs, against 43% of homes under 2,740 SF. Defined in 8.1.8.
  • 14% of homes over 3,476 SF have a view, against 29% of homes under 2,740 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 2,740 SF7 sales2,740–2,959 SF7 sales2,985–3,476 SF8 salesOver 3,476 SF7 salesAll29 salesReal difference?
Net sale price average$460,141$546,357$610,723$755,318$593,741✓ large
Net price per SF average$209$189$195$203$199unclear
Living area average2,2012,8943,1253,7132,988by design
Year built median20152015201320152014unclear

4.10 The numbers: selling

Under 2,740 SF7 sales2,740–2,959 SF7 sales2,985–3,476 SF8 salesOver 3,476 SF7 salesAll29 salesReal difference?
Days on market median1842903333unclear
Discount from original list average4.6%5.1%5.7%4.6%5.0%unclear
Price cut before sale29%43%50%29%38%unclear
Seller paid closing costs or repairs43%86%50%57%59%unclear
Has a view29%14%50%14%28%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 · 29 sales · October 28, 2025 – October 27, 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.

2026-10-28T07:35:16.221906 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 9 6 8 29 sales Sales per group Before 2011: 6 sales (21%) 2011–2014: 9 sales (31%) 2015: 6 sales (21%) After 2015: 8 sales (28%)
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 20112011–20142015After 2015Real difference?
Net sale price$578K$570K$590K$634Kunclear
Net price per SF$180 per SF$200 per SF$203 per SF$209 per SFunclear
Living area3,200 SF2,883 SF2,881 SF3,028 SFunclear
Days on market114 days18 days25 days66 daysunclear
Discount from original list9.5%4.7%5.3%1.9%unclear
Price cut before sale83%33%33%12%unclear
Seller paid closing costs or repairs50%67%50%62%unclear
Has a view0%33%33%38%unclear

5.3 Net sale price: no clear difference

2026-10-28T07:35:16.241818 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2011 6 sales 2011– 2014 9 sales 2015 6 sales After 2015 8 sales $0K $200K $400K $600K $578K $570K $590K $634K Net sale price, average

The average is $634K for homes built after 2015 and $578K for homes built before 2011. It does not move in a straight line; homes built after 2015 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-28T07:35:16.264425 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2011 6 sales 2011– 2014 9 sales 2015 6 sales After 2015 8 sales $0 $100 $200 $180 $200 $203 $209 Net price per SF, average

The average is $209 per SF for homes built after 2015 and $180 per SF for homes built before 2011. 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

2026-10-28T07:35:16.285303 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2011 6 sales 2011– 2014 9 sales 2015 6 sales After 2015 8 sales 0 1,000 2,000 3,000 3,200 2,883 2,881 3,028 Living area (SF), average

The average is 3,028 SF for homes built after 2015 and 3,200 SF for homes built before 2011. It does not move in a straight line; homes built before 2011 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-28T07:35:16.306959 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2011 6 sales 2011– 2014 9 sales 2015 6 sales After 2015 8 sales 0 50 100 114 18 25 66 Days on market, median

The median is 66 days for homes built after 2015 and 114 days for homes built before 2011. It does not move in a straight line; homes built before 2011 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-28T07:35:16.328909 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2011 6 sales 2011– 2014 9 sales 2015 6 sales After 2015 8 sales 0.0% 5.0% 10.0% 9.5% 4.7% 5.3% 1.9% Discount from original list, average

The average is 1.9% for homes built after 2015 and 9.5% for homes built before 2011. It does not move in a straight line; homes built before 2011 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

2026-10-28T07:35:16.353719 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% 83 50 0 33 67 33 33 50 33 12 62 38 Before 2011 2011–2014 2015 After 2015

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

  • 12% of homes built after 2015 had a price cut before sale, against 83% of homes built before 2011. Defined in 8.1.7.
  • 62% of homes built after 2015 had the seller pay closing costs or repairs, against 50% of homes built before 2011. Defined in 8.1.8.
  • 38% of homes built after 2015 have a view, against 0% of homes built before 2011. 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 20116 sales2011–20149 sales20156 salesAfter 20158 salesAll29 salesReal difference?
Net sale price average$578,354$570,454$590,375$634,004$593,741unclear
Net price per SF average$180$200$203$209$199unclear
Living area average3,2002,8832,8813,0282,988unclear
Year built median20102013201520162014by design

5.10 The numbers: selling

Before 20116 sales2011–20149 sales20156 salesAfter 20158 salesAll29 salesReal difference?
Days on market median11418256633unclear
Discount from original list average9.5%4.7%5.3%1.9%5.0%unclear
Price cut before sale83%33%33%12%38%unclear
Seller paid closing costs or repairs50%67%50%62%59%unclear
Has a view0%33%33%38%28%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 · 29 sales · October 28, 2025 – October 27, 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. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-28T07:35:16.371280 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 20 28 sales Sales per group View: 8 sales (29%) No view: 20 sales (71%)
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$621K$592Kunclear
Net price per SF$206 per SF$196 per SFunclear
Living area3,004 SF3,028 SFunclear
Year built20152014unclear
Days on market38 days33 daysunclear
Discount from original list4.1%5.1%unclear
Price cut before sale38%35%unclear
Seller paid closing costs or repairs38%65%unclear

6.3 Net sale price: no clear difference

2026-10-28T07:35:16.386847 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales $0K $200K $400K $600K $621K $592K Net sale price, average

The average is $621K for homes with a view and $592K 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

2026-10-28T07:35:16.405120 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales $0 $50 $100 $150 $200 $206 $196 Net price per SF, average

The average is $206 per SF for homes with a view and $196 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

2026-10-28T07:35:16.423348 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales 0 1,000 2,000 3,000 3,004 3,028 Living area (SF), average

The average is 3,004 SF for homes with a view and 3,028 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-28T07:35:16.463403 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales 2010 2012 2014 2016 2015 2014 Year built: median (dot) and middle half (bar)

The median is 2015 for homes with a view and 2014 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-28T07:35:16.481690 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales 0 10 20 30 40 38 33 Days on market, median

The median is 38 days for homes with a view and 33 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

2026-10-28T07:35:16.499857 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales 0.0% 2.0% 4.0% 6.0% 4.1% 5.1% Discount from original list, average

The average is 4.1% for homes with a view and 5.1% 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

2026-10-28T07:35:16.518074 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 38 38 35 65 View No view

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

  • 38% of homes with a view had a price cut before sale, against 35% of homes without a view. Defined in 8.1.7.
  • 38% 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: – 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

View8 salesNo view20 salesAll28 salesReal difference?
Net sale price average$620,567$592,223$600,321unclear
Net price per SF average$206$196$199unclear
Living area average3,0043,0283,021unclear
Year built median201520142014unclear

6.11 The numbers: selling

View8 salesNo view20 salesAll28 salesReal difference?
Days on market median383333unclear
Discount from original list average4.1%5.1%4.8%unclear
Price cut before sale38%35%36%unclear
Seller paid closing costs or repairs38%65%57%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 28, 2025 – October 27, 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 Parkside at Mayfield Ranch.

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
29 resale sales. Average $593,741; median $569,000; standard deviation $128,887; middle half (25th–75th percentile) $523,000–$659,500; lowest $376,250, highest $920,000. 17 sales had a seller payment; their median payment was $4,115.

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
29 resale sales. Average $199; median $198; standard deviation $19; middle half (25th–75th percentile) $188–$213; lowest $162, highest $240.

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
29 resale sales. Average 2,988; median 2,985; standard deviation 574; middle half (25th–75th percentile) 2,740–3,476; lowest 1,819, highest 4,069.

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
29 resale sales. Average 2013; median 2014; standard deviation 3; middle half (25th–75th percentile) 2011–2016; lowest 2008, highest 2017.

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
29 resale sales. Average 71; median 33; standard deviation 74; middle half (25th–75th percentile) 16–125; lowest 4, highest 258. 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
29 resale sales. Average 5.0%; median 3.4%; standard deviation 6.3%; middle half (25th–75th percentile) 0.6%–9.4%; lowest −7.0%, highest 21.4%. 5 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
11 of 29 resale sales (37.9%).

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
17 of 29 resale sales (58.6%).

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
8 sales with a view, 20 without, 1 unclassified. Most common View entries: None 18, Trees/Woods 5, Park/Greenbelt 4, Neighborhood 2, See Remarks 2, Hill Country 1, Rural 1, Panoramic 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 “parkside at mayfield ranch”, “parkside mayfield ranch” (case-insensitive). A record is kept when its subdivision name belongs to the Parkside at Mayfield Ranch family, the same rule comparable sales use (it includes Parkside/Mayfield Ranch Sec 12, proven adjacent and priced alike).
The data
Pulled October 28, 2026: 29 closed Parkside at Mayfield Ranch records over the prior year, in ZIP 78628. 9 subdivision spellings kept: Parkside at Mayfield Ranch (17); PARKSIDE AT MAYFIELD RANCH (3); Parkside At Mayfield Ranch Sec 01 (2); Parkside At Mayfield Ranch (2); Parkside at Mayfield Ranch Sec 4B (1); Parkside At Mayfield Ranch Sec 10 (1); Parkside Mayfield Ranch Sec (1); Parkside At Mayfield Ranch Sec 02 (1); Parkside at Mayfield Ranch Sec 8 (1). No other names were found by the search.

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 17 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 28, 2025 to October 27, 2026 inclusive.
The data
29 single-family sales in the window: 29 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
29 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 $523K”.
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 $523K: $376,250–$502,400 (7 sales); $523K–$562K: $523,000–$562,000 (7 sales); $569K–$660K: $569,000–$659,500 (8 sales); Over $660K: $675,000–$920,000 (7 sales)
Quartiles by living area: Under 2,740 SF: 1,819–2,574 SF (7 sales); 2,740–2,959 SF: 2,740–2,959 SF (7 sales); 2,985–3,476 SF: 2,985–3,476 SF (8 sales); Over 3,476 SF: 3,482–4,069 SF (7 sales)
Quartiles by year built: Before 2011: 2008–2010 (6 sales); 2011–2014: 2011–2014 (9 sales); 2015: 2015–2015 (6 sales); After 2015: 2016–2017 (8 sales)
View and no view: View: MLS lists a view (8 sales); No view: None or Neighborhood (20 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 $593,741, median $569,000. Days on market: average 71, median 33: 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
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 = 7.1230.0680p < 0.0063Unclearε² = 0.254large
Living areaKruskal–WallisH = 17.7630.0005p < 0.0063Yesε² = 0.634large
Year builtKruskal–WallisH = 2.2230.5276p < 0.0063Unclearε² = 0.079medium
Days on marketKruskal–WallisH = 2.1530.5411p < 0.0063Unclearε² = 0.077medium
Discount from original listKruskal–WallisH = 2.0630.5598p < 0.0063Unclearε² = 0.074medium
Price cut before saleChi-squareχ² = 2.8330.4182p < 0.0063UnclearCramér’s V = 0.313medium
Seller paid closing costs or repairsChi-squareχ² = 0.7330.8659p < 0.0063UnclearCramér’s V = 0.159small
Has a viewChi-squareχ² = 6.7430.0806p < 0.0063UnclearCramér’s V = 0.482medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 19.7330.0002p < 0.0063Yesε² = 0.705large
Net price per SFKruskal–WallisH = 3.8230.2813p < 0.0063Unclearε² = 0.137medium
Year builtKruskal–WallisH = 1.2830.7347p < 0.0063Unclearε² = 0.046small
Days on marketKruskal–WallisH = 0.5530.9076p < 0.0063Unclearε² = 0.020small
Discount from original listKruskal–WallisH = 0.0630.9959p < 0.0063Unclearε² = 0.002negligible
Price cut before saleChi-squareχ² = 1.0930.7800p < 0.0063UnclearCramér’s V = 0.194small
Seller paid closing costs or repairsChi-squareχ² = 3.0930.3784p < 0.0063UnclearCramér’s V = 0.326medium
Has a viewChi-squareχ² = 3.2630.3539p < 0.0063UnclearCramér’s V = 0.335medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 0.9730.8086p < 0.0063Unclearε² = 0.035small
Net price per SFKruskal–WallisH = 7.9430.0473p < 0.0063Unclearε² = 0.284large
Living areaKruskal–WallisH = 2.0330.5669p < 0.0063Unclearε² = 0.072medium
Days on marketKruskal–WallisH = 3.9430.2677p < 0.0063Unclearε² = 0.141large
Discount from original listKruskal–WallisH = 4.8230.1852p < 0.0063Unclearε² = 0.172large
Price cut before saleChi-squareχ² = 7.5930.0554p < 0.0063UnclearCramér’s V = 0.511large
Seller paid closing costs or repairsChi-squareχ² = 0.6630.8832p < 0.0063UnclearCramér’s V = 0.151small
Has a viewChi-squareχ² = 2.9330.4030p < 0.0063UnclearCramér’s V = 0.318medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 95.00—0.4608p < 0.0063Unclearrank-biserial r = 0.188small
Net price per SFMann–Whitney UU = 109.00—0.1500p < 0.0063Unclearrank-biserial r = 0.363medium
Living areaMann–Whitney UU = 80.00—1.0000p < 0.0063Unclearrank-biserial r = 0.000negligible
Year builtMann–Whitney UU = 101.00—0.2933p < 0.0063Unclearrank-biserial r = 0.262small
Days on marketMann–Whitney UU = 82.00—0.9391p < 0.0063Unclearrank-biserial r = 0.025negligible
Discount from original listMann–Whitney UU = 71.00—0.6718p < 0.0063Unclearrank-biserial r = 0.113small
Price cut before saleChi-squareχ² = 0.0210.9007p < 0.0063UnclearCramér’s V = 0.024negligible
Seller paid closing costs or repairsChi-squareχ² = 1.7610.1841p < 0.0063UnclearCramér’s V = 0.251small

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 29 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 28, 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.