ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Elm Creek

Elgin, TX 78621
Resale homes · closed Oct 31 – Oct 30, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 31, 2026 · 7:17 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
22
single-family resale homes
Median net sale price
$215,934
average $225,814
Median net price per SF
$136
average $139
Median days on market
74 days
average 89 days
1. SummaryResale homes · 22 sales · October 31, 2025 – October 30, 2026

This study looks at the 22 resale homes sold in Elm Creek in the 365 days to October 30, 2026. A full year is used because only 11 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 sold22 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 $210K · 6 sales$210K–$215K · 5 sales$217K–$235K · 5 salesOver $235K · 6 sales
3. Quartiles by net sale priceResale homes · 22 sales · October 31, 2025 – October 30, 2026

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

2026-10-31T07:18:10.104037 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 5 5 6 22 sales Sales per group Under $210K: 6 sales (27%) $210K–$215K: 5 sales (23%) $217K–$235K: 5 sales (23%) Over $235K: 6 sales (27%)
Bottom line: no measure differs enough between the groups to rule out chance.

3.1 Key differences

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

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 $210K$210K–$215K$217K–$235KOver $235KReal difference?
Net price per SF$135 per SF$139 per SF$165 per SF$122 per SFunclear
Living area1,497 SF1,642 SF1,418 SF2,367 SFunclear
Year built2008202220072006unclear
Days on market83 days87 days60 days55 daysunclear
Discount from original list10.9%10.7%4.5%9.1%unclear
Price cut before sale67%100%60%50%unclear
Seller paid closing costs or repairs67%40%100%83%unclear
Has a view0%0%20%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 Net price per SF: no clear difference

2026-10-31T07:18:10.136716 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $210K 6 sales $210K– $215K 5 sales $217K– $235K 5 sales Over $235K 6 sales $0 $50 $100 $150 $135 $139 $165 $122 Net price per SF, average

The average is $122 per SF for homes over $235K and $135 per SF for homes under $210K. It does not move in a straight line; homes $217K–$235K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-31T07:18:10.169544 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $210K 6 sales $210K– $215K 5 sales $217K– $235K 5 sales Over $235K 6 sales 0 1,000 2,000 1,497 1,642 1,418 2,367 Living area (SF), average

The average is 2,367 SF for homes over $235K and 1,497 SF for homes under $210K. It does not move in a straight line; homes over $235K are highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-31T07:18:10.199266 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $210K 6 sales $210K– $215K 5 sales $217K– $235K 5 sales Over $235K 6 sales 2008 2012 2016 2020 2008 2022 2007 2006 Year built: median (dot) and middle half (bar)

The median is 2006 for homes over $235K and 2008 for homes under $210K. It does not move in a straight line; homes $210K–$215K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-31T07:18:10.226117 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $210K 6 sales $210K– $215K 5 sales $217K– $235K 5 sales Over $235K 6 sales 0 50 100 83 87 60 55 Days on market, median

The median is 55 days for homes over $235K and 83 days for homes under $210K. It does not move in a straight line; homes $210K–$215K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-31T07:18:10.255113 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $210K 6 sales $210K– $215K 5 sales $217K– $235K 5 sales Over $235K 6 sales 0.0% 5.0% 10.0% 10.9% 10.7% 4.5% 9.1% Discount from original list, average

The average is 9.1% for homes over $235K and 10.9% for homes under $210K. It does not move in a straight line; homes under $210K 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

2026-10-31T07:18:10.299983 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% 67 67 0 100 40 0 60 100 20 50 83 17 Under $210K $210K–$215K $217K–$235K Over $235K

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

  • 50% of homes over $235K had a price cut before sale, against 67% of homes under $210K. Defined in 8.1.7.
  • 83% of homes over $235K had the seller pay closing costs or repairs, against 67% of homes under $210K. Defined in 8.1.8.
  • 17% of homes over $235K have a view, against 0% of homes under $210K. 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 $210K6 sales$210K–$215K5 sales$217K–$235K5 salesOver $235K6 salesAll22 salesReal difference?
Net sale price average$191,452$213,238$227,214$269,490$225,814by design
Net price per SF average$135$139$165$122$139unclear
Living area average1,4971,6421,4182,3671,749unclear
Year built median20082022200720062007unclear

3.10 The numbers: selling

Under $210K6 sales$210K–$215K5 sales$217K–$235K5 salesOver $235K6 salesAll22 salesReal difference?
Days on market median8387605574unclear
Discount from original list average10.9%10.7%4.5%9.1%8.9%unclear
Price cut before sale67%100%60%50%68%unclear
Seller paid closing costs or repairs67%40%100%83%73%unclear
Has a view0%0%20%17%9%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 · 22 sales · October 31, 2025 – October 30, 2026

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

2026-10-31T07:18:10.333869 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 5 5 6 22 sales Sales per group Under 1,442 SF: 6 sales (27%) 1,442–1,600 SF: 5 sales (23%) 1,666–2,146 SF: 5 sales (23%) Over 2,146 SF: 6 sales (27%)
Bottom line

4.1 Key differences

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

Under 1,442 SF1,442–1,600 SF1,666–2,146 SFOver 2,146 SF
Larger homes Over 2,146 SF
  • Sell for less per square foot.
Smaller homes Under 1,442 SF
  • Sell for more per square foot.

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 1,442 SF1,442–1,600 SF1,666–2,146 SFOver 2,146 SFReal difference?
Net sale price$201K$224K$212K$263Kunclear
Net price per SF$178 per SFHighest$149 per SF$119 per SF$108 per SFLowest✓ large
Year built2014200920072006unclear
Days on market68 days62 days97 days70 daysunclear
Discount from original list4.4%9.4%13.0%9.5%unclear
Price cut before sale67%100%60%50%unclear
Seller paid closing costs or repairs50%80%100%67%unclear
Has a view0%20%0%17%unclear

4.3 Net sale price: no clear difference

2026-10-31T07:18:10.361834 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,442 SF 6 sales 1,442– 1,600 SF 5 sales 1,666– 2,146 SF 5 sales Over 2,146 SF 6 sales $0K $100K $200K $300K $201K $224K $212K $263K Net sale price, average

The average is $263K for homes over 2,146 SF and $201K for homes under 1,442 SF. It does not move in a straight line; homes over 2,146 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Homes over 2,146 SF sell for about $70 per SF (39%) less than homes under 1,442 SF

2026-10-31T07:18:10.388485 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,442 SF 6 sales 1,442– 1,600 SF 5 sales 1,666– 2,146 SF 5 sales Over 2,146 SF 6 sales $0 $100 $200 $178 $149 $119 $108 Net price per SF, average

The average is $108 per SF for homes over 2,146 SF and $178 per SF for homes under 1,442 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

2026-10-31T07:18:10.416696 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,442 SF 6 sales 1,442– 1,600 SF 5 sales 1,666– 2,146 SF 5 sales Over 2,146 SF 6 sales 2008 2012 2016 2020 2014 2009 2007 2006 Year built: median (dot) and middle half (bar)

The median is 2006 for homes over 2,146 SF and 2014 for homes under 1,442 SF. It falls 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

2026-10-31T07:18:10.443868 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,442 SF 6 sales 1,442– 1,600 SF 5 sales 1,666– 2,146 SF 5 sales Over 2,146 SF 6 sales 0 50 100 68 62 97 70 Days on market, median

The median is 70 days for homes over 2,146 SF and 68 days for homes under 1,442 SF. It does not move in a straight line; homes 1,666–2,146 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-31T07:18:10.466887 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,442 SF 6 sales 1,442– 1,600 SF 5 sales 1,666– 2,146 SF 5 sales Over 2,146 SF 6 sales 0.0% 5.0% 10.0% 15.0% 4.4% 9.4% 13.0% 9.5% Discount from original list, average

The average is 9.5% for homes over 2,146 SF and 4.4% for homes under 1,442 SF. It does not move in a straight line; homes 1,666–2,146 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

2026-10-31T07:18:10.498280 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% 67 50 0 100 80 20 60 100 0 50 67 17 Under 1,442 SF 1,442–1,600 SF 1,666–2,146 SF Over 2,146 SF

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

  • 50% of homes over 2,146 SF had a price cut before sale, against 67% of homes under 1,442 SF. Defined in 8.1.7.
  • 67% of homes over 2,146 SF had the seller pay closing costs or repairs, against 50% of homes under 1,442 SF. Defined in 8.1.8.
  • 17% of homes over 2,146 SF have a view, against 0% of homes under 1,442 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 1,442 SF6 sales1,442–1,600 SF5 sales1,666–2,146 SF5 salesOver 2,146 SF6 salesAll22 salesReal difference?
Net sale price average$200,830$224,238$212,260$263,407$225,814unclear
Net price per SF average$178$149$119$108$139✓ large
Living area average1,1361,5141,8002,5161,749by design
Year built median20142009200720062007unclear

4.10 The numbers: selling

Under 1,442 SF6 sales1,442–1,600 SF5 sales1,666–2,146 SF5 salesOver 2,146 SF6 salesAll22 salesReal difference?
Days on market median6862977074unclear
Discount from original list average4.4%9.4%13.0%9.5%8.9%unclear
Price cut before sale67%100%60%50%68%unclear
Seller paid closing costs or repairs50%80%100%67%73%unclear
Has a view0%20%0%17%9%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 · 22 sales · October 31, 2025 – October 30, 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.

2026-10-31T07:18:10.521389 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 3 6 6 22 sales Sales per group Before 2006: 7 sales (32%) 2006: 3 sales (14%) 2007–2010: 6 sales (27%) After 2010: 6 sales (27%)
Bottom line: too few sales to test.

5.1 Key differences

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

5.3 Net sale price: described, not tested

2026-10-31T07:18:10.547835 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 7 sales 2006 3 sales 2007– 2010 6 sales After 2010 6 sales $0K $100K $200K $235K $244K $223K $210K Net sale price, average

The average is $210K for homes built after 2010 and $235K for homes built before 2006. It does not move in a straight line; homes built 2006 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-31T07:18:10.575110 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 7 sales 2006 3 sales 2007– 2010 6 sales After 2010 6 sales $0 $50 $100 $150 $126 $133 $138 $158 Net price per SF, average

The average is $158 per SF for homes built after 2010 and $126 per SF for homes built before 2006. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-31T07:18:10.598168 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 7 sales 2006 3 sales 2007– 2010 6 sales After 2010 6 sales 0 1,000 2,000 2,004 1,831 1,781 1,379 Living area (SF), average

The average is 1,379 SF for homes built after 2010 and 2,004 SF for homes built before 2006. It falls step by step from the lowest range to the highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-31T07:18:10.621008 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 7 sales 2006 3 sales 2007– 2010 6 sales After 2010 6 sales 0 50 100 97 5 61 90 Days on market, median

The median is 90 days for homes built after 2010 and 97 days for homes built before 2006. It does not move in a straight line; homes built before 2006 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-31T07:18:10.644957 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2006 7 sales 2006 3 sales 2007– 2010 6 sales After 2010 6 sales 0.0% 5.0% 10.0% 10.0% 2.4% 12.2% 7.4% Discount from original list, average

The average is 7.4% for homes built after 2010 and 10.0% for homes built before 2006. It does not move in a straight line; homes built 2007–2010 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-31T07:18:10.672665 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 71 86 14 0 33 0 100 100 17 67 50 0 Before 2006 2006 2007–2010 After 2010

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

  • 67% of homes built after 2010 had a price cut before sale, against 71% of homes built before 2006. Defined in 8.1.7.
  • 50% of homes built after 2010 had the seller pay closing costs or repairs, against 86% of homes built before 2006. Defined in 8.1.8.
  • 0% of homes built after 2010 have a view, against 14% of homes built before 2006. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

5.9 The numbers: price and size

Before 20067 sales20063 sales2007–20106 salesAfter 20106 salesAll22 sales
Net sale price average$234,528$244,000$222,553$209,815$225,814
Net price per SF average$126$133$138$158$139
Living area average2,0041,8311,7811,3791,749
Year built median20052006200720222007

5.10 The numbers: selling

Before 20067 sales20063 sales2007–20106 salesAfter 20106 salesAll22 sales
Days on market median975619074
Discount from original list average10.0%2.4%12.2%7.4%8.9%
Price cut before sale71%0%100%67%68%
Seller paid closing costs or repairs86%33%100%50%73%
Has a view14%0%17%0%9%

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 · 22 sales · October 31, 2025 – October 30, 2026

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

2026-10-31T07:18:10.695288 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 2 20 22 sales Sales per group View: 2 sales (9%) No view: 20 sales (91%)
Bottom line: too few sales to test.

6.1 Key differences

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

6.3 Net sale price: described, not tested

2026-10-31T07:18:10.712918 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales $0K $100K $200K $300K $268K $222K Net sale price, average

The average is $268K for homes with a view and $222K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-31T07:18:10.732102 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales $0 $50 $100 $150 $131 $140 Net price per SF, average

The average is $131 per SF for homes with a view and $140 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-31T07:18:10.796493 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 0 1,000 2,000 2,254 1,699 Living area (SF), average

The average is 2,254 SF for homes with a view and 1,699 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-31T07:18:10.818614 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 2008 2012 2016 2020 2008 2007 Year built: median (dot) and middle half (bar)

The median is 2008 for homes with a view and 2007 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-31T07:18:10.839280 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 0 20 40 60 80 34 82 Days on market, median

The median is 34 days for homes with a view and 82 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-31T07:18:10.864628 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 2 sales No view 20 sales 0.0% 2.5% 5.0% 7.5% 10.0% 0.7% 9.7% Discount from original list, average

The average is 0.7% for homes with a view and 9.7% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-31T07:18:10.885757 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 50 100 70 70 View No view

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

  • 50% of homes with a view had a price cut before sale, against 70% of homes without a view. Defined in 8.1.7.
  • 100% of homes with a view had the seller pay closing costs or repairs, against 70% of homes without a view. Defined in 8.1.8.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View2 salesNo view20 salesAll22 sales
Net sale price average$267,900$221,605$225,814
Net price per SF average$131$140$139
Living area average2,2541,6991,749
Year built median200820072007

6.11 The numbers: selling

View2 salesNo view20 salesAll22 sales
Days on market median348274
Discount from original list average0.7%9.7%8.9%
Price cut before sale50%70%68%
Seller paid closing costs or repairs100%70%73%

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 · 98 sales · October 31, 2025 – October 30, 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: 98 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 Elm Creek.
MeasureAverageMedian
Sales98
Net sale price$253,958$248,287
Net price per SF$137$134
Living area (SF)1,8911,891
Days on market6055
Discount from original list10.5%9.8%
Price cut before sale85% of sales
Seller paid closing costs or repairs91% of sales
Year built2025–2026

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
22 resale sales. Average $225,814; median $215,934; standard deviation $34,520; middle half (25th–75th percentile) $209,550–$239,605; lowest $155,000, highest $300,800. 16 sales had a seller payment; their median payment was $6,000.

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
22 resale sales. Average $139; median $136; standard deviation $36; middle half (25th–75th percentile) $118–$162; lowest $74, highest $205.

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
22 resale sales. Average 1,749; median 1,633; standard deviation 600; middle half (25th–75th percentile) 1,283–2,148; lowest 1,047, highest 3,245.

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
22 resale sales. Average 2010; median 2007; standard deviation 7; middle half (25th–75th percentile) 2005–2018; lowest 2003, highest 2023.

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
22 resale sales. Average 89; median 74; standard deviation 70; middle half (25th–75th percentile) 44–126; lowest 5, highest 288. 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
22 resale sales. Average 8.9%; median 8.2%; standard deviation 7.1%; middle half (25th–75th percentile) 3.4%–12.7%; lowest −3.3%, highest 27.3%. 2 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
15 of 22 resale sales (68.2%).

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
16 of 22 resale sales (72.7%).

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
2 sales with a view, 20 without, 0 unclassified. Most common View entries: None 13, Neighborhood 7, Park/Greenbelt 2.

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 = Elgin, SubdivisionName contains any of “elm creek”, “elm creek north”, “elm crk”, “elm crk north” (case-insensitive). A record is kept when its subdivision name belongs to the Elm Creek family, the same rule comparable sales use (it includes Elm Crk North Ph Iv, proven adjacent and priced alike).
The data
Pulled October 31, 2026: 120 closed Elm Creek records over the prior year, in ZIP 78621. 9 subdivision spellings kept: Elm Creek (102); Elm Creek Sec 04 (4); Elm Creek Sec 02 (4); Elm Creek Sec 01 (3); Elm Creek Sec 5B (2); Elm Creek North (2); Elm Creek Sec 5A (1); Elm Creek Sec 03 (1); Elm Crk North Ph Iv (1). Names found by the search but not part of Elm Creek, left out: Elm Crk Northwest Ph 1 (2); ELM CREEK NORTH PHS 1 (1).

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 11 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 31, 2025 to October 30, 2026 inclusive.
The data
120 single-family sales in the window: 22 resale, 98 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
22 resale; 98 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 $210K”.
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 $210K: $155,000–$209,400 (6 sales); $210K–$215K: $210,000–$215,289 (5 sales); $217K–$235K: $216,580–$235,000 (5 sales); Over $235K: $241,140–$300,800 (6 sales)
Quartiles by living area: Under 1,442 SF: 1,047–1,230 SF (6 sales); 1,442–1,600 SF: 1,442–1,600 SF (5 sales); 1,666–2,146 SF: 1,666–2,146 SF (5 sales); Over 2,146 SF: 2,149–3,245 SF (6 sales)
Quartiles by year built: Before 2006: 2003–2005 (7 sales); 2006: 2006–2006 (3 sales); 2007–2010: 2007–2010 (6 sales); After 2010: 2020–2023 (6 sales)
View and no view: View: MLS lists a view (2 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 $225,814, median $215,934. Days on market: average 89, median 74: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

In simple terms
Checks whether a measure really differs across the four groups of a slice. It uses each sale's rank, not its value, so a few extreme sales cannot drive the answer.
Statistically
H = [12/(n(n+1))] Σ Rⱼ²/nⱼ − 3(n+1), compared with χ² on k − 1 degrees of freedom (Kruskal & Wallis, 1952). Effect size ε² = H/(n − 1): ≥ .01 small, ≥ .06 medium, ≥ .14 large (Tomczak & Tomczak, 2014). A slice is tested only when every group has at least 5 sales; smaller groups are described, not tested.
The data
Run on every measure in sections 3–5; each result is in 8.3.

8.2.8 Mann–Whitney U test

In simple terms
The same check when there are only two groups: view against no view.
Statistically
Two-sided U test (Mann & Whitney, 1947). Effect size = rank-biserial correlation |1 − 2U/(n₁n₂)|: ≥ .10 small, ≥ .30 medium, ≥ .50 large (Kerby, 2014; Cohen, 1988).
The data
Run on every measure in section 6; results in 8.3.

8.2.9 Chi-square test

In simple terms
Checks whether a yes/no share (price cut, seller payment, view) differs between groups more than chance would.
Statistically
Pearson χ² on the 2 × k table of counts, no continuity correction (Pearson, 1900). Effect size Cramér's V = √(χ²/n): ≥ .10 small, ≥ .30 medium, ≥ .50 large (Cramér, 1946).
The data
Run on the three shares in every slice; results in 8.3.

8.2.10 Real difference (significance)

In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
1 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 = 4.8830.1809p < 0.0063Unclearε² = 0.232large
Living areaKruskal–WallisH = 7.3330.0620p < 0.0063Unclearε² = 0.349large
Year builtKruskal–WallisH = 2.2930.5154p < 0.0063Unclearε² = 0.109medium
Days on marketKruskal–WallisH = 1.7230.6323p < 0.0063Unclearε² = 0.082medium
Discount from original listKruskal–WallisH = 3.7530.2895p < 0.0063Unclearε² = 0.179large
Price cut before saleChi-squareχ² = 3.4130.3329p < 0.0063UnclearCramér’s V = 0.394medium
Seller paid closing costs or repairsChi-squareχ² = 5.0330.1699p < 0.0063UnclearCramér’s V = 0.478medium
Has a viewChi-squareχ² = 2.2430.5248p < 0.0063UnclearCramér’s V = 0.319medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 9.7730.0206p < 0.0063Unclearε² = 0.465large
Net price per SFKruskal–WallisH = 12.5430.0057p < 0.0063Yesε² = 0.597large
Year builtKruskal–WallisH = 4.3030.2309p < 0.0063Unclearε² = 0.205large
Days on marketKruskal–WallisH = 0.3230.9567p < 0.0063Unclearε² = 0.015small
Discount from original listKruskal–WallisH = 3.3830.3362p < 0.0063Unclearε² = 0.161large
Price cut before saleChi-squareχ² = 3.4130.3329p < 0.0063UnclearCramér’s V = 0.394medium
Seller paid closing costs or repairsChi-squareχ² = 3.6830.2979p < 0.0063UnclearCramér’s V = 0.409medium
Has a viewChi-squareχ² = 2.2430.5248p < 0.0063UnclearCramér’s V = 0.319medium

8.3.3 Quartiles by year built

Too few sales in a group to test.

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

Left out of the analysis: 98 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 22 closed MLS resale sales; the 98 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 31, 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.