ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Springfield

Austin, TX 78744 · 78747
Resale homes · closed Nov 1 – Oct 31, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 1, 2026 · 7:42 AM CST
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
40
single-family resale homes
Median net sale price
$348,250
average $352,771
Median net price per SF
$187
average $183
Median days on market
38 days
average 57 days
1. SummaryResale homes · 40 sales · November 1, 2025 – October 31, 2026

This study looks at the 40 resale homes sold in Springfield in the 365 days to October 31, 2026. A full year is used because only 15 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 sold40 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 $322K · 10 sales$322K–$346K · 10 sales$350K–$377K · 10 salesOver $377K · 10 sales
3. Quartiles by net sale priceResale homes · 40 sales · November 1, 2025 – October 31, 2026

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

2026-11-01T07:42:52.898242 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 10 10 10 10 40 sales Sales per group Under $322K: 10 sales (25%) $322K–$346K: 10 sales (25%) $350K–$377K: 10 sales (25%) Over $377K: 10 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 $322K$322K–$346K$350K–$377KOver $377K
Higher-priced homes Over $377K
  • Are much larger.
  • Tend to be newer.
Lower-priced homes Under $322K
  • Are much smaller.
  • Tend to be older.

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 $322K$322K–$346K$350K–$377KOver $377KReal difference?
Net price per SF$183 per SF$211 per SF$171 per SF$167 per SFunclear
Living area1,712 SF1,591 SFSmallest2,206 SF2,555 SFLargest✓ large
Year built2002Oldest20162018Newest2018✓ large
Days on market68 days20 days62 days26 daysunclear
Discount from original list10.0%4.3%5.5%5.3%unclear
Price cut before sale70%20%30%50%unclear
Seller paid closing costs or repairs70%80%70%90%unclear
Has a view10%10%10%20%unclear

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

3.3 Net price per SF: no clear difference

2026-11-01T07:42:52.927513 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $322K 10 sales $322K– $346K 10 sales $350K– $377K 10 sales Over $377K 10 sales $0 $100 $200 $183 $211 $171 $167 Net price per SF, average

The average is $167 per SF for homes over $377K and $183 per SF for homes under $322K. It does not move in a straight line; homes $322K–$346K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $377K are about 840 SF (49%) larger than homes under $322K

2026-11-01T07:42:52.949378 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $322K 10 sales $322K– $346K 10 sales $350K– $377K 10 sales Over $377K 10 sales 0 1,000 2,000 3,000 1,712 1,591 2,206 2,555 Living area (SF), average

The average is 2,555 SF for homes over $377K and 1,712 SF for homes under $322K. It does not move in a straight line; homes over $377K are highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Homes over $377K are about 16 years newer than homes under $322K

2026-11-01T07:42:52.973008 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $322K 10 sales $322K– $346K 10 sales $350K– $377K 10 sales Over $377K 10 sales 2000 2005 2010 2015 2002 2016 2018 2018 Year built: median (dot) and middle half (bar)

The median is 2018 for homes over $377K and 2002 for homes under $322K. It does not move in a straight line; homes $350K–$377K are highest. Defined in 8.1.4.

✓ Real difference · large

3.6 Days on market: no clear difference

2026-11-01T07:42:52.995843 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $322K 10 sales $322K– $346K 10 sales $350K– $377K 10 sales Over $377K 10 sales 0 25 50 75 68 20 62 26 Days on market, median

The median is 26 days for homes over $377K and 68 days for homes under $322K. It does not move in a straight line; homes under $322K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-01T07:42:53.017199 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $322K 10 sales $322K– $346K 10 sales $350K– $377K 10 sales Over $377K 10 sales 0.0% 5.0% 10.0% 10.0% 4.3% 5.5% 5.3% Discount from original list, average

The average is 5.3% for homes over $377K and 10.0% for homes under $322K. It does not move in a straight line; homes under $322K 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

2026-11-01T07:42:53.047039 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% 70 70 10 20 80 10 30 70 10 50 90 20 Under $322K $322K–$346K $350K–$377K Over $377K

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

  • 50% of homes over $377K had a price cut before sale, against 70% of homes under $322K. Defined in 8.1.7.
  • 90% of homes over $377K had the seller pay closing costs or repairs, against 70% of homes under $322K. Defined in 8.1.8.
  • 20% of homes over $377K have a view, against 10% of homes under $322K. 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 $322K10 sales$322K–$346K10 sales$350K–$377K10 salesOver $377K10 salesAll40 salesReal difference?
Net sale price average$292,369$333,100$367,005$418,608$352,771by design
Net price per SF average$183$211$171$167$183unclear
Living area average1,7121,5912,2062,5552,016✓ large
Year built median20022016201820182016✓ large

3.10 The numbers: selling

Under $322K10 sales$322K–$346K10 sales$350K–$377K10 salesOver $377K10 salesAll40 salesReal difference?
Days on market median6820622638unclear
Discount from original list average10.0%4.3%5.5%5.3%6.3%unclear
Price cut before sale70%20%30%50%42%unclear
Seller paid closing costs or repairs70%80%70%90%78%unclear
Has a view10%10%10%20%12%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 · 40 sales · November 1, 2025 – October 31, 2026

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

2026-11-01T07:42:53.067460 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 10 11 10 40 sales Sales per group Under 1,514 SF: 9 sales (22%) 1,514–1,795 SF: 10 sales (25%) 1,861–2,383 SF: 11 sales (28%) Over 2,383 SF: 10 sales (25%)
Bottom line

4.1 Key differences

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

Under 1,514 SF1,514–1,795 SF1,861–2,383 SFOver 2,383 SF
Larger homes Over 2,383 SF
  • Sell for less per square foot.
  • Sell for much more.
Smaller homes Under 1,514 SF
  • Sell for more per square foot.
  • Sell for much less.

4.2 At a glance

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

Under 1,514 SF1,514–1,795 SF1,861–2,383 SFOver 2,383 SFReal difference?
Net sale price$300KLowest$334K$370K$400KHighest✓ large
Net price per SF$221 per SFHighest$199 per SF$173 per SF$144 per SFLowest✓ large
Year built2002201820182016unclear
Days on market30 days17 days73 days78 daysunclear
Discount from original list5.9%5.4%6.0%7.8%unclear
Price cut before sale44%30%45%50%unclear
Seller paid closing costs or repairs89%70%82%70%unclear
Has a view11%10%18%10%unclear

4.3 Homes over 2,383 SF sell for about $99K (33%) more than homes under 1,514 SF

2026-11-01T07:42:53.088441 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,514 SF 9 sales 1,514– 1,795 SF 10 sales 1,861– 2,383 SF 11 sales Over 2,383 SF 10 sales $0K $200K $400K $300K $334K $370K $400K Net sale price, average

The average is $400K for homes over 2,383 SF and $300K for homes under 1,514 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Homes over 2,383 SF sell for about $77 per SF (35%) less than homes under 1,514 SF

2026-11-01T07:42:53.111460 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,514 SF 9 sales 1,514– 1,795 SF 10 sales 1,861– 2,383 SF 11 sales Over 2,383 SF 10 sales $0 $100 $200 $221 $199 $173 $144 Net price per SF, average

The average is $144 per SF for homes over 2,383 SF and $221 per SF for homes under 1,514 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

2026-11-01T07:42:53.134964 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,514 SF 9 sales 1,514– 1,795 SF 10 sales 1,861– 2,383 SF 11 sales Over 2,383 SF 10 sales 1998 2004 2010 2016 2002 2018 2018 2016 Year built: median (dot) and middle half (bar)

The median is 2016 for homes over 2,383 SF and 2002 for homes under 1,514 SF. It does not move in a straight line; homes 1,514–1,795 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-01T07:42:53.158479 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,514 SF 9 sales 1,514– 1,795 SF 10 sales 1,861– 2,383 SF 11 sales Over 2,383 SF 10 sales 0 25 50 75 30 17 73 78 Days on market, median

The median is 78 days for homes over 2,383 SF and 30 days for homes under 1,514 SF. It does not move in a straight line; homes over 2,383 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-01T07:42:53.181098 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,514 SF 9 sales 1,514– 1,795 SF 10 sales 1,861– 2,383 SF 11 sales Over 2,383 SF 10 sales 0.0% 2.5% 5.0% 7.5% 5.9% 5.4% 6.0% 7.8% Discount from original list, average

The average is 7.8% for homes over 2,383 SF and 5.9% for homes under 1,514 SF. It does not move in a straight line; homes over 2,383 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

2026-11-01T07:42:53.207584 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% 44 89 11 30 70 10 45 82 18 50 70 10 Under 1,514 SF 1,514–1,795 SF 1,861–2,383 SF Over 2,383 SF

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

  • 50% of homes over 2,383 SF had a price cut before sale, against 44% of homes under 1,514 SF. Defined in 8.1.7.
  • 70% of homes over 2,383 SF had the seller pay closing costs or repairs, against 89% of homes under 1,514 SF. Defined in 8.1.8.
  • 10% of homes over 2,383 SF have a view, against 11% of homes under 1,514 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 1,514 SF9 sales1,514–1,795 SF10 sales1,861–2,383 SF11 salesOver 2,383 SF10 salesAll40 salesReal difference?
Net sale price average$300,476$333,533$370,210$399,890$352,771✓ large
Net price per SF average$221$199$173$144$183✓ large
Living area average1,3631,6812,1572,7842,016by design
Year built median20022018201820162016unclear

4.10 The numbers: selling

Under 1,514 SF9 sales1,514–1,795 SF10 sales1,861–2,383 SF11 salesOver 2,383 SF10 salesAll40 salesReal difference?
Days on market median3017737838unclear
Discount from original list average5.9%5.4%6.0%7.8%6.3%unclear
Price cut before sale44%30%45%50%42%unclear
Seller paid closing costs or repairs89%70%82%70%78%unclear
Has a view11%10%18%10%12%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 · 40 sales · November 1, 2025 – October 31, 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.

2026-11-01T07:42:53.228682 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 10 17 5 40 sales Sales per group Before 2002: 8 sales (20%) 2002–2015: 10 sales (25%) 2016–2018: 17 sales (42%) After 2018: 5 sales (12%)
Bottom line

5.1 Key differences

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

Before 20022002–20152016–2018After 2018
Newer homes After 2018
  • Sell for much more.
  • Are much larger.
Older homes Before 2002
  • Sell for much less.
  • Are much smaller.

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 20022002–20152016–2018After 2018Real difference?
Net sale price$302KLowest$331K$388KHighest$355K✓ large
Net price per SF$195 per SF$181 per SF$170 per SF$213 per SFunclear
Living area1,584 SFSmallest1,972 SF2,345 SFLargest1,677 SF✓ large
Days on market16 days68 days62 days24 daysunclear
Discount from original list7.8%6.3%6.9%1.7%unclear
Price cut before sale38%40%53%20%unclear
Seller paid closing costs or repairs75%70%82%80%unclear
Has a view12%0%12%40%unclear

5.3 Homes built after 2018 sell for about $53K (17%) more than homes built before 2002

2026-11-01T07:42:53.248850 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 8 sales 2002– 2015 10 sales 2016– 2018 17 sales After 2018 5 sales $0K $200K $400K $302K $331K $388K $355K Net sale price, average

The average is $355K for homes built after 2018 and $302K for homes built before 2002. It does not move in a straight line; homes built 2016–2018 are highest. Defined in 8.1.1.

✓ Real difference · large

5.4 Net price per SF: no clear difference

2026-11-01T07:42:53.271715 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 8 sales 2002– 2015 10 sales 2016– 2018 17 sales After 2018 5 sales $0 $100 $200 $195 $181 $170 $213 Net price per SF, average

The average is $213 per SF for homes built after 2018 and $195 per SF for homes built before 2002. It does not move in a straight line; homes built after 2018 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Homes built after 2018 are about 90 SF (6%) larger than homes built before 2002

2026-11-01T07:42:53.293714 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 8 sales 2002– 2015 10 sales 2016– 2018 17 sales After 2018 5 sales 0 1,000 2,000 1,584 1,972 2,345 1,677 Living area (SF), average

The average is 1,677 SF for homes built after 2018 and 1,584 SF for homes built before 2002. It does not move in a straight line; homes built 2016–2018 are highest. Defined in 8.1.3.

✓ Real difference · large

5.6 Days on market: no clear difference

2026-11-01T07:42:53.315823 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 8 sales 2002– 2015 10 sales 2016– 2018 17 sales After 2018 5 sales 0 25 50 75 16 68 62 24 Days on market, median

The median is 24 days for homes built after 2018 and 16 days for homes built before 2002. It does not move in a straight line; homes built 2002–2015 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-01T07:42:53.339114 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 8 sales 2002– 2015 10 sales 2016– 2018 17 sales After 2018 5 sales 0.0% 2.5% 5.0% 7.5% 7.8% 6.3% 6.9% 1.7% Discount from original list, average

The average is 1.7% for homes built after 2018 and 7.8% for homes built before 2002. It does not move in a straight line; homes built before 2002 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

2026-11-01T07:42:53.364713 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% 38 75 12 40 70 0 53 82 12 20 80 40 Before 2002 2002–2015 2016–2018 After 2018

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

  • 20% of homes built after 2018 had a price cut before sale, against 38% of homes built before 2002. Defined in 8.1.7.
  • 80% of homes built after 2018 had the seller pay closing costs or repairs, against 75% of homes built before 2002. Defined in 8.1.8.
  • 40% of homes built after 2018 have a view, against 12% of homes built before 2002. 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 20028 sales2002–201510 sales2016–201817 salesAfter 20185 salesAll40 salesReal difference?
Net sale price average$302,494$331,074$388,492$355,153$352,771✓ large
Net price per SF average$195$181$170$213$183unclear
Living area average1,5841,9722,3451,6772,016✓ large
Year built median19982002201820192016by design

5.10 The numbers: selling

Before 20028 sales2002–201510 sales2016–201817 salesAfter 20185 salesAll40 salesReal difference?
Days on market median1668622438unclear
Discount from original list average7.8%6.3%6.9%1.7%6.3%unclear
Price cut before sale38%40%53%20%42%unclear
Seller paid closing costs or repairs75%70%82%80%78%unclear
Has a view12%0%12%40%12%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 · 40 sales · November 1, 2025 – October 31, 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. 2 sales whose MLS view entry is only “See Remarks” are left out.

2026-11-01T07:42:53.383545 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 33 38 sales Sales per group View: 5 sales (13%) No view: 33 sales (87%)
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$367K$353Kunclear
Net price per SF$209 per SF$178 per SFunclear
Living area1,804 SF2,070 SFunclear
Year built20182016unclear
Days on market13 days59 daysunclear
Discount from original list3.3%6.8%unclear
Price cut before sale20%45%unclear
Seller paid closing costs or repairs80%76%unclear

6.3 Net sale price: no clear difference

2026-11-01T07:42:53.400304 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 33 sales $0K $100K $200K $300K $400K $367K $353K Net sale price, average

The average is $367K for homes with a view and $353K 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

2026-11-01T07:42:53.418364 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 33 sales $0 $100 $200 $209 $178 Net price per SF, average

The average is $209 per SF for homes with a view and $178 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

2026-11-01T07:42:53.437072 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 33 sales 0 500 1,000 1,500 2,000 1,804 2,070 Living area (SF), average

The average is 1,804 SF for homes with a view and 2,070 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-11-01T07:42:53.481486 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 33 sales 2004 2008 2012 2016 2018 2016 Year built: median (dot) and middle half (bar)

The median is 2018 for homes with a view and 2016 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-11-01T07:42:53.499642 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 33 sales 0 20 40 60 13 59 Days on market, median

The median is 13 days for homes with a view and 59 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

2026-11-01T07:42:53.518642 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 33 sales 0.0% 2.0% 4.0% 6.0% 8.0% 3.3% 6.8% Discount from original list, average

The average is 3.3% for homes with a view and 6.8% 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

2026-11-01T07:42:53.537697 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 20 80 45 76 View No view

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

  • 20% of homes with a view had a price cut before sale, against 45% of homes without a view. Defined in 8.1.7.
  • 80% of homes with a view had the seller pay closing costs or repairs, against 76% 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

View5 salesNo view33 salesAll38 salesReal difference?
Net sale price average$366,643$352,735$354,565unclear
Net price per SF average$209$178$182unclear
Living area average1,8042,0702,035unclear
Year built median201820162016unclear

6.11 The numbers: selling

View5 salesNo view33 salesAll38 salesReal difference?
Days on market median135938unclear
Discount from original list average3.3%6.8%6.3%unclear
Price cut before sale20%45%42%unclear
Seller paid closing costs or repairs80%76%76%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 · 2 sales · November 1, 2025 – October 31, 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: 2 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 Springfield.
MeasureAverageMedian
Sales2
Net sale price$423,725$423,725
Net price per SF$163$163
Living area (SF)2,5922,592
Days on market5252
Discount from original list11.7%11.7%
Price cut before sale100% of sales
Seller paid closing costs or repairs50% of sales
Year built2025–2025

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
40 resale sales. Average $352,771; median $348,250; standard deviation $54,186; middle half (25th–75th percentile) $321,488–$377,275; lowest $256,170, highest $552,900. 31 sales had a seller payment; their median payment was $7,500.

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
40 resale sales. Average $183; median $187; standard deviation $35; middle half (25th–75th percentile) $157–$211; lowest $114, highest $244.

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
40 resale sales. Average 2,016; median 1,861; standard deviation 567; middle half (25th–75th percentile) 1,514–2,401; lowest 1,231, highest 3,549.

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
40 resale sales. Average 2010; median 2016; standard deviation 9; middle half (25th–75th percentile) 2002–2018; lowest 1987, highest 2019.

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
40 resale sales. Average 57; median 38; standard deviation 56; middle half (25th–75th percentile) 12–86; lowest 2, highest 220. 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
40 resale sales. Average 6.3%; median 6.0%; standard deviation 5.5%; middle half (25th–75th percentile) 2.7%–9.1%; lowest −3.4%, highest 23.5%. 4 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
17 of 40 resale sales (42.5%).

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
31 of 40 resale sales (77.5%).

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
5 sales with a view, 33 without, 2 unclassified. Most common View entries: None 20, Neighborhood 15, Trees/Woods 3, See Remarks 2, Park/Greenbelt 2, Pasture 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
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-01 13:30 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Austin, SubdivisionName contains any of “springfield” (case-insensitive). A record is kept when its subdivision name belongs to the Springfield family, the same rule comparable sales use.
The data
Pulled November 1, 2026: 42 closed Springfield records over the prior year, in ZIP 78744, 78747. 16 subdivision spellings kept, the most common: Springfield Sec 01 (6); Springfield Sec 7 (5); Springfield Sec 2 (4); Springfield Ph B Sec 01 (4); Springfield Ph C (4); Springfield Sec 9 (3); Springfield Sec 8B (3); Springfield (3); Springfield Sec 5 (2); Springfield Sec 3 (2); Springfield Ph B Sec 05 (1); Springfield Ph B Sec 03 (1); and 4 more (4 records). Names found by the search but not part of Springfield, left out: Springfield PHS C SUBD (1); Vista Point (Springfield) (1); Springfield Reserve at McKinney Falls (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 15 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 1, 2025 to October 31, 2026 inclusive.
The data
42 single-family sales in the window: 40 resale, 2 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
40 resale; 2 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 $322K”.
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 $322K: $256,170–$319,950 (10 sales); $322K–$346K: $322,000–$346,500 (10 sales); $350K–$377K: $350,000–$376,700 (10 sales); Over $377K: $379,000–$552,900 (10 sales)
Quartiles by living area: Under 1,514 SF: 1,231–1,511 SF (9 sales); 1,514–1,795 SF: 1,514–1,795 SF (10 sales); 1,861–2,383 SF: 1,861–2,383 SF (11 sales); Over 2,383 SF: 2,456–3,549 SF (10 sales)
Quartiles by year built: Before 2002: 1987–2001 (8 sales); 2002–2015: 2002–2015 (10 sales); 2016–2018: 2016–2018 (17 sales); After 2018: 2019–2019 (5 sales)
View and no view: View: MLS lists a view (5 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 $352,771, median $348,250. Days on market: average 57, median 38: 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
6 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 = 10.0130.0185p < 0.0063Unclearε² = 0.257large
Living areaKruskal–WallisH = 20.2330.0002p < 0.0063Yesε² = 0.519large
Year builtKruskal–WallisH = 14.1330.0027p < 0.0063Yesε² = 0.362large
Days on marketKruskal–WallisH = 5.9530.1139p < 0.0063Unclearε² = 0.153large
Discount from original listKruskal–WallisH = 5.1030.1645p < 0.0063Unclearε² = 0.131medium
Price cut before saleChi-squareχ² = 6.0430.1099p < 0.0063UnclearCramér’s V = 0.388medium
Seller paid closing costs or repairsChi-squareχ² = 1.5830.6646p < 0.0063UnclearCramér’s V = 0.199small
Has a viewChi-squareχ² = 0.6930.8766p < 0.0063UnclearCramér’s V = 0.131small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 20.4830.0001p < 0.0063Yesε² = 0.525large
Net price per SFKruskal–WallisH = 26.713< 0.0001p < 0.0063Yesε² = 0.685large
Year builtKruskal–WallisH = 8.7730.0325p < 0.0063Unclearε² = 0.225large
Days on marketKruskal–WallisH = 2.3230.5083p < 0.0063Unclearε² = 0.060small
Discount from original listKruskal–WallisH = 1.9230.5886p < 0.0063Unclearε² = 0.049small
Price cut before saleChi-squareχ² = 0.9230.8199p < 0.0063UnclearCramér’s V = 0.152small
Seller paid closing costs or repairsChi-squareχ² = 1.4330.6980p < 0.0063UnclearCramér’s V = 0.189small
Has a viewChi-squareχ² = 0.4530.9287p < 0.0063UnclearCramér’s V = 0.107small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 18.0030.0004p < 0.0063Yesε² = 0.462large
Net price per SFKruskal–WallisH = 7.0030.0720p < 0.0063Unclearε² = 0.179large
Living areaKruskal–WallisH = 13.1030.0044p < 0.0063Yesε² = 0.336large
Days on marketKruskal–WallisH = 3.2630.3529p < 0.0063Unclearε² = 0.084medium
Discount from original listKruskal–WallisH = 4.8130.1864p < 0.0063Unclearε² = 0.123medium
Price cut before saleChi-squareχ² = 1.9030.5931p < 0.0063UnclearCramér’s V = 0.218small
Seller paid closing costs or repairsChi-squareχ² = 0.6030.8967p < 0.0063UnclearCramér’s V = 0.122small
Has a viewChi-squareχ² = 4.8930.1797p < 0.0063UnclearCramér’s V = 0.350medium

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 105.00—0.3530p < 0.0063Unclearrank-biserial r = 0.273small
Net price per SFMann–Whitney UU = 127.00—0.0556p < 0.0063Unclearrank-biserial r = 0.539large
Living areaMann–Whitney UU = 65.00—0.4626p < 0.0063Unclearrank-biserial r = 0.212small
Year builtMann–Whitney UU = 116.00—0.1488p < 0.0063Unclearrank-biserial r = 0.406medium
Days on marketMann–Whitney UU = 37.00—0.0519p < 0.0063Unclearrank-biserial r = 0.552large
Discount from original listMann–Whitney UU = 53.00—0.2104p < 0.0063Unclearrank-biserial r = 0.358medium
Price cut before saleChi-squareχ² = 1.1510.2827p < 0.0063UnclearCramér’s V = 0.174small
Seller paid closing costs or repairsChi-squareχ² = 0.0410.8353p < 0.0063UnclearCramér’s V = 0.034negligible

8.4 Data notes

Left out of the analysis: 2 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 40 closed MLS resale sales; the 2 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 1, 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.