ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Legends Hutto Ph 03

Hutto, TX 78634
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 7:48 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
32
single-family resale homes
Median net sale price
$295,925
average $298,640
Median net price per SF
$143
average $151
Median days on market
54 days
average 77 days
1. SummaryResale homes · 32 sales · October 26, 2025 – October 25, 2026

This study looks at the 32 resale homes sold in Legends Hutto Ph 03 in the 365 days to October 25, 2026. A full year is used because only 19 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 sold32 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 $269K · 8 sales$269K–$296K · 8 sales$296K–$320K · 8 salesOver $320K · 8 sales
3. Quartiles by net sale priceResale homes · 32 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:49:08.449302 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 8 8 32 sales Sales per group Under $269K: 8 sales (25%) $269K–$296K: 8 sales (25%) $296K–$320K: 8 sales (25%) Over $320K: 8 sales (25%)
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 $269K$269K–$296K$296K–$320KOver $320KReal difference?
Net price per SF$161 per SF$160 per SF$150 per SF$133 per SFunclear
Living area1,705 SF1,847 SF2,148 SF2,827 SFunclear
Year built2002200220052006unclear
Days on market58 days64 days21 days69 daysunclear
Discount from original list8.5%7.5%2.6%5.0%unclear
Price cut before sale62%50%25%38%unclear
Seller paid closing costs or repairs75%88%50%75%unclear
Has a view0%12%12%38%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

2026-10-26T07:49:08.477162 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $269K 8 sales $269K– $296K 8 sales $296K– $320K 8 sales Over $320K 8 sales $0 $50 $100 $150 $161 $160 $150 $133 Net price per SF, average

The average is $133 per SF for homes over $320K and $161 per SF for homes under $269K. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-26T07:49:08.499703 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $269K 8 sales $269K– $296K 8 sales $296K– $320K 8 sales Over $320K 8 sales 0 1,000 2,000 3,000 1,705 1,847 2,148 2,827 Living area (SF), average

The average is 2,827 SF for homes over $320K and 1,705 SF for homes under $269K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-26T07:49:08.522886 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $269K 8 sales $269K– $296K 8 sales $296K– $320K 8 sales Over $320K 8 sales 2002 2004 2006 2002 2002 2005 2006 Year built: median (dot) and middle half (bar)

The median is 2006 for homes over $320K and 2002 for homes under $269K. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:49:08.545440 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $269K 8 sales $269K– $296K 8 sales $296K– $320K 8 sales Over $320K 8 sales 0 25 50 75 58 64 21 69 Days on market, median

The median is 69 days for homes over $320K and 58 days for homes under $269K. It does not move in a straight line; homes over $320K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:49:08.567228 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $269K 8 sales $269K– $296K 8 sales $296K– $320K 8 sales Over $320K 8 sales 0.0% 5.0% 10.0% 8.5% 7.5% 2.6% 5.0% Discount from original list, average

The average is 5.0% for homes over $320K and 8.5% for homes under $269K. It does not move in a straight line; homes under $269K are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:49:08.596421 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% 62 75 0 50 88 12 25 50 12 38 75 38 Under $269K $269K–$296K $296K–$320K Over $320K

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

  • 38% of homes over $320K had a price cut before sale, against 62% of homes under $269K. Defined in 8.1.7.
  • 75% of homes over $320K had the seller pay closing costs or repairs, against 75% of homes under $269K. Defined in 8.1.8.
  • 38% of homes over $320K have a view, against 0% of homes under $269K. 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 $269K8 sales$269K–$296K8 sales$296K–$320K8 salesOver $320K8 salesAll32 salesReal difference?
Net sale price average$248,236$282,313$308,970$355,041$298,640by design
Net price per SF average$161$160$150$133$151unclear
Living area average1,7051,8472,1482,8272,132unclear
Year built median20022002200520062004unclear

3.10 The numbers: selling

Under $269K8 sales$269K–$296K8 sales$296K–$320K8 salesOver $320K8 salesAll32 salesReal difference?
Days on market median5864216954unclear
Discount from original list average8.5%7.5%2.6%5.0%5.9%unclear
Price cut before sale62%50%25%38%44%unclear
Seller paid closing costs or repairs75%88%50%75%72%unclear
Has a view0%12%12%38%16%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 · 32 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:49:08.616374 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 8 8 32 sales Sales per group Under 1,681 SF: 8 sales (25%) 1,681–1,904 SF: 8 sales (25%) 1,936–2,522 SF: 8 sales (25%) Over 2,522 SF: 8 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 1,681 SF1,681–1,904 SF1,936–2,522 SFOver 2,522 SF
Larger homes Over 2,522 SF
  • Sell for less per square foot.
Smaller homes Under 1,681 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 1,681 SF1,681–1,904 SF1,936–2,522 SFOver 2,522 SFReal difference?
Net sale price$262K$293K$303K$337Kunclear
Net price per SF$199 per SFHighest$164 per SF$132 per SF$109 per SFLowest✓ large
Year built2002200420042006unclear
Days on market22 days48 days60 days112 daysunclear
Discount from original list4.7%4.7%5.6%8.6%unclear
Price cut before sale25%38%38%75%unclear
Seller paid closing costs or repairs88%62%62%75%unclear
Has a view12%25%0%25%unclear

4.3 Net sale price: no clear difference

2026-10-26T07:49:08.636480 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,681 SF 8 sales 1,681– 1,904 SF 8 sales 1,936– 2,522 SF 8 sales Over 2,522 SF 8 sales $0K $200K $400K $262K $293K $303K $337K Net sale price, average

The average is $337K for homes over 2,522 SF and $262K for homes under 1,681 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Homes over 2,522 SF sell for about $90 per SF (45%) less than homes under 1,681 SF

2026-10-26T07:49:08.658423 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,681 SF 8 sales 1,681– 1,904 SF 8 sales 1,936– 2,522 SF 8 sales Over 2,522 SF 8 sales $0 $100 $200 $199 $164 $132 $109 Net price per SF, average

The average is $109 per SF for homes over 2,522 SF and $199 per SF for homes under 1,681 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

4.5 Year built: no clear difference

2026-10-26T07:49:08.680412 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,681 SF 8 sales 1,681– 1,904 SF 8 sales 1,936– 2,522 SF 8 sales Over 2,522 SF 8 sales 2002 2004 2006 2002 2004 2004 2006 Year built: median (dot) and middle half (bar)

The median is 2006 for homes over 2,522 SF and 2002 for homes under 1,681 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T07:49:08.702961 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,681 SF 8 sales 1,681– 1,904 SF 8 sales 1,936– 2,522 SF 8 sales Over 2,522 SF 8 sales 0 50 100 22 48 60 112 Days on market, median

The median is 112 days for homes over 2,522 SF and 22 days for homes under 1,681 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:49:08.724528 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,681 SF 8 sales 1,681– 1,904 SF 8 sales 1,936– 2,522 SF 8 sales Over 2,522 SF 8 sales 0.0% 5.0% 10.0% 4.7% 4.7% 5.6% 8.6% Discount from original list, average

The average is 8.6% for homes over 2,522 SF and 4.7% for homes under 1,681 SF. It does not move in a straight line; homes over 2,522 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:49:08.750373 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% 25 88 12 38 62 25 38 62 0 75 75 25 Under 1,681 SF 1,681–1,904 SF 1,936–2,522 SF Over 2,522 SF

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

  • 75% of homes over 2,522 SF had a price cut before sale, against 25% of homes under 1,681 SF. Defined in 8.1.7.
  • 75% of homes over 2,522 SF had the seller pay closing costs or repairs, against 88% of homes under 1,681 SF. Defined in 8.1.8.
  • 25% of homes over 2,522 SF have a view, against 12% of homes under 1,681 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 1,681 SF8 sales1,681–1,904 SF8 sales1,936–2,522 SF8 salesOver 2,522 SF8 salesAll32 salesReal difference?
Net sale price average$262,037$293,155$302,675$336,694$298,640unclear
Net price per SF average$199$164$132$109$151✓ large
Living area average1,3251,7942,2983,1092,132by design
Year built median20022004200420062004unclear

4.10 The numbers: selling

Under 1,681 SF8 sales1,681–1,904 SF8 sales1,936–2,522 SF8 salesOver 2,522 SF8 salesAll32 salesReal difference?
Days on market median22486011254unclear
Discount from original list average4.7%4.7%5.6%8.6%5.9%unclear
Price cut before sale25%38%38%75%44%unclear
Seller paid closing costs or repairs88%62%62%75%72%unclear
Has a view12%25%0%25%16%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 · 32 sales · October 26, 2025 – October 25, 2026

Sales ranked by year built and cut into four groups, from the oldest to the newest. Homes built in the same year always stay in the same group, so group sizes can differ a little.

2026-10-26T07:49:08.770623 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 10 9 7 32 sales Sales per group Before 2002: 6 sales (19%) 2002–2004: 10 sales (31%) 2005–2006: 9 sales (28%) After 2006: 7 sales (22%)
Bottom line: no measure differs enough between the groups to rule out chance.

5.1 Key differences

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

5.2 At a glance

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

Before 20022002–20042005–2006After 2006Real difference?
Net sale price$264K$287K$306K$336Kunclear
Net price per SF$189 per SF$142 per SF$132 per SF$154 per SFunclear
Living area1,427 SF2,121 SF2,431 SF2,366 SFunclear
Days on market21 days91 days76 days21 daysunclear
Discount from original list2.6%8.2%6.4%4.8%unclear
Price cut before sale0%80%44%29%unclear
Seller paid closing costs or repairs83%80%56%71%unclear
Has a view17%10%11%29%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:49:08.791116 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 6 sales 2002– 2004 10 sales 2005– 2006 9 sales After 2006 7 sales $0K $200K $400K $264K $287K $306K $336K Net sale price, average

The average is $336K for homes built after 2006 and $264K for homes built before 2002. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:49:08.813628 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 6 sales 2002– 2004 10 sales 2005– 2006 9 sales After 2006 7 sales $0 $100 $200 $189 $142 $132 $154 Net price per SF, average

The average is $154 per SF for homes built after 2006 and $189 per SF for homes built before 2002. It does not move in a straight line; homes built before 2002 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:49:08.835348 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 6 sales 2002– 2004 10 sales 2005– 2006 9 sales After 2006 7 sales 0 1,000 2,000 1,427 2,121 2,431 2,366 Living area (SF), average

The average is 2,366 SF for homes built after 2006 and 1,427 SF for homes built before 2002. It does not move in a straight line; homes built 2005–2006 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T07:49:08.856795 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 6 sales 2002– 2004 10 sales 2005– 2006 9 sales After 2006 7 sales 0 50 100 21 91 76 21 Days on market, median

The median is 21 days for homes built after 2006 and 21 days for homes built before 2002. It does not move in a straight line; homes built 2002–2004 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:49:08.879569 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2002 6 sales 2002– 2004 10 sales 2005– 2006 9 sales After 2006 7 sales 0.0% 2.5% 5.0% 7.5% 2.6% 8.2% 6.4% 4.8% Discount from original list, average

The average is 4.8% for homes built after 2006 and 2.6% for homes built before 2002. It does not move in a straight line; homes built 2002–2004 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T07:49:08.905171 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% 0 83 17 80 80 10 44 56 11 29 71 29 Before 2002 2002–2004 2005–2006 After 2006

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

  • 29% of homes built after 2006 had a price cut before sale, against 0% of homes built before 2002. Defined in 8.1.7.
  • 71% of homes built after 2006 had the seller pay closing costs or repairs, against 83% of homes built before 2002. Defined in 8.1.8.
  • 29% of homes built after 2006 have a view, against 17% 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 20026 sales2002–200410 sales2005–20069 salesAfter 20067 salesAll32 salesReal difference?
Net sale price average$264,038$286,618$306,072$335,919$298,640unclear
Net price per SF average$189$142$132$154$151unclear
Living area average1,4272,1212,4312,3662,132unclear
Year built median20002003200620072004by design

5.10 The numbers: selling

Before 20026 sales2002–200410 sales2005–20069 salesAfter 20067 salesAll32 salesReal difference?
Days on market median2191762154unclear
Discount from original list average2.6%8.2%6.4%4.8%5.9%unclear
Price cut before sale0%80%44%29%44%unclear
Seller paid closing costs or repairs83%80%56%71%72%unclear
Has a view17%10%11%29%16%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 · 32 sales · October 26, 2025 – October 25, 2026

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

2026-10-26T07:49:08.923913 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 5 27 32 sales Sales per group View: 5 sales (16%) No view: 27 sales (84%)
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$327K$293Kunclear
Net price per SF$157 per SF$150 per SFunclear
Living area2,311 SF2,098 SFunclear
Year built20062004unclear
Days on market62 days52 daysunclear
Discount from original list6.5%5.8%unclear
Price cut before sale60%41%unclear
Seller paid closing costs or repairs80%70%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:49:08.939642 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 27 sales $0K $100K $200K $300K $327K $293K Net sale price, average

The average is $327K for homes with a view and $293K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-10-26T07:49:08.957037 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 27 sales $0 $50 $100 $150 $157 $150 Net price per SF, average

The average is $157 per SF for homes with a view and $150 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-10-26T07:49:08.975592 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 27 sales 0 1,000 2,000 2,311 2,098 Living area (SF), average

The average is 2,311 SF for homes with a view and 2,098 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:49:09.018354 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 27 sales 2002 2004 2006 2006 2004 Year built: median (dot) and middle half (bar)

The median is 2006 for homes with a view and 2004 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:49:09.035438 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 27 sales 0 20 40 60 62 52 Days on market, median

The median is 62 days for homes with a view and 52 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-10-26T07:49:09.053938 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 5 sales No view 27 sales 0.0% 2.0% 4.0% 6.0% 6.5% 5.8% Discount from original list, average

The average is 6.5% for homes with a view and 5.8% 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

2026-10-26T07:49:09.072332 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 60 80 41 70 View No view

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

  • 60% of homes with a view had a price cut before sale, against 41% 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 70% 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 view27 salesAll32 salesReal difference?
Net sale price average$326,898$293,407$298,640unclear
Net price per SF average$157$150$151unclear
Living area average2,3112,0982,132unclear
Year built median200620042004unclear

6.11 The numbers: selling

View5 salesNo view27 salesAll32 salesReal difference?
Days on market median625254unclear
Discount from original list average6.5%5.8%5.9%unclear
Price cut before sale60%41%44%unclear
Seller paid closing costs or repairs80%70%72%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.4.

7. New constructionBasic statistics · 0 sales · October 26, 2025 – October 25, 2026

Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 0 sales, no groups, no tests.

Note: these are only the new-construction sales reported in ABOR MLS. Builders often sell homes without listing them in the MLS, so these figures do not necessarily represent all new-construction sales in Legends Hutto Ph 03.

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
32 resale sales. Average $298,640; median $295,925; standard deviation $42,713; middle half (25th–75th percentile) $267,930–$324,282; lowest $223,100, highest $414,800. 23 sales had a seller payment; their median payment was $10,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
32 resale sales. Average $151; median $143; standard deviation $37; middle half (25th–75th percentile) $119–$182; lowest $83, highest $221.

8.1.3 Living area

In simple terms
The heated and cooled space, as listed in the MLS. Garages and porches are not counted.
Statistically
RESO LivingArea, in square feet. Sales under 400 SF are treated as entry errors and left out.
The data
32 resale sales. Average 2,132; median 1,920; standard deviation 709; middle half (25th–75th percentile) 1,649–2,540; lowest 1,009, highest 3,640.

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
32 resale sales. Average 2004; median 2004; standard deviation 3; middle half (25th–75th percentile) 2002–2006; lowest 2000, highest 2014.

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
32 resale sales. Average 77; median 54; standard deviation 89; middle half (25th–75th percentile) 21–104; lowest 4, highest 429. 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
32 resale sales. Average 5.9%; median 4.4%; standard deviation 5.8%; middle half (25th–75th percentile) 1.7%–11.7%; lowest −3.4%, highest 16.2%. 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
14 of 32 resale sales (43.8%).

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
23 of 32 resale sales (71.9%).

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, 27 without, 0 unclassified. Most common View entries: None 20, Neighborhood 7, Park/Greenbelt 4, Orchard 2, Pasture 1, Skyline 1, Trees/Woods 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 = Hutto, SubdivisionName contains any of “legends hutto”, “legends of hutto”, “creekside estates” (case-insensitive). A record is kept when its subdivision name belongs to the Legends Hutto Ph 03 family, the same rule comparable sales use (it includes Legends Of Hutto Ph 5B, Creekside Estates Sec 1, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 32 closed Legends Hutto Ph 03 records over the prior year, in ZIP 78634. 15 subdivision spellings kept, the most common: Legends Of Hutto Ph 5B (5); Legends Hutto Ph 01 (4); Creekside Estates Sec 1 (3); Legends Hutto Ph 04 (3); Legends Hutto Ph 02 (2); Legends Hutto (2); Legends Of Hutto Ph 4 (2); Creekside Estates Sec 3 (2); LEGENDS OF HUTTO (2); Legends Of Hutto Ph 5b (2); Legends Hutto Ph 5a (1); Legends Hutto Ph 5A (1); and 3 more (3 records). No other names were found by the search.

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 19 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
32 single-family sales in the window: 32 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
32 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 $269K”.
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 $269K: $223,100–$265,000 (8 sales); $269K–$296K: $268,906–$295,850 (8 sales); $296K–$320K: $296,000–$320,500 (8 sales); Over $320K: $335,630–$414,800 (8 sales)
Quartiles by living area: Under 1,681 SF: 1,009–1,554 SF (8 sales); 1,681–1,904 SF: 1,681–1,904 SF (8 sales); 1,936–2,522 SF: 1,936–2,522 SF (8 sales); Over 2,522 SF: 2,594–3,640 SF (8 sales)
Quartiles by year built: Before 2002: 2000–2001 (6 sales); 2002–2004: 2002–2004 (10 sales); 2005–2006: 2005–2006 (9 sales); After 2006: 2007–2014 (7 sales)
View and no view: View: MLS lists a view (5 sales); No view: None or Neighborhood (27 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 $298,640, median $295,925. Days on market: average 77, median 54: 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
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 = 3.8830.2743p < 0.0063Unclearε² = 0.125medium
Living areaKruskal–WallisH = 11.4930.0094p < 0.0063Unclearε² = 0.371large
Year builtKruskal–WallisH = 7.6430.0541p < 0.0063Unclearε² = 0.246large
Days on marketKruskal–WallisH = 2.3230.5079p < 0.0063Unclearε² = 0.075medium
Discount from original listKruskal–WallisH = 5.7030.1274p < 0.0063Unclearε² = 0.184large
Price cut before saleChi-squareχ² = 2.5430.4682p < 0.0063UnclearCramér’s V = 0.282small
Seller paid closing costs or repairsChi-squareχ² = 2.9430.4014p < 0.0063UnclearCramér’s V = 0.303medium
Has a viewChi-squareχ² = 4.5030.2120p < 0.0063UnclearCramér’s V = 0.375medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 11.7030.0085p < 0.0063Unclearε² = 0.377large
Net price per SFKruskal–WallisH = 27.143< 0.0001p < 0.0063Yesε² = 0.876large
Year builtKruskal–WallisH = 5.6330.1313p < 0.0063Unclearε² = 0.181large
Days on marketKruskal–WallisH = 6.8830.0758p < 0.0063Unclearε² = 0.222large
Discount from original listKruskal–WallisH = 2.0030.5724p < 0.0063Unclearε² = 0.065medium
Price cut before saleChi-squareχ² = 4.5730.2060p < 0.0063UnclearCramér’s V = 0.378medium
Seller paid closing costs or repairsChi-squareχ² = 1.7030.6368p < 0.0063UnclearCramér’s V = 0.231small
Has a viewChi-squareχ² = 2.6130.4562p < 0.0063UnclearCramér’s V = 0.285small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 9.9430.0191p < 0.0063Unclearε² = 0.321large
Net price per SFKruskal–WallisH = 7.9730.0466p < 0.0063Unclearε² = 0.257large
Living areaKruskal–WallisH = 9.5730.0226p < 0.0063Unclearε² = 0.309large
Days on marketKruskal–WallisH = 8.7130.0333p < 0.0063Unclearε² = 0.281large
Discount from original listKruskal–WallisH = 3.9930.2623p < 0.0063Unclearε² = 0.129medium
Price cut before saleChi-squareχ² = 10.6630.0137p < 0.0063UnclearCramér’s V = 0.577large
Seller paid closing costs or repairsChi-squareχ² = 1.9030.5929p < 0.0063UnclearCramér’s V = 0.244small
Has a viewChi-squareχ² = 1.2730.7353p < 0.0063UnclearCramér’s V = 0.200small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 101.50—0.0820p < 0.0063Unclearrank-biserial r = 0.504large
Net price per SFMann–Whitney UU = 71.00—0.8801p < 0.0063Unclearrank-biserial r = 0.052negligible
Living areaMann–Whitney UU = 73.00—0.7952p < 0.0063Unclearrank-biserial r = 0.081negligible
Year builtMann–Whitney UU = 79.50—0.5477p < 0.0063Unclearrank-biserial r = 0.178small
Days on marketMann–Whitney UU = 78.00—0.6036p < 0.0063Unclearrank-biserial r = 0.156small
Discount from original listMann–Whitney UU = 69.00—0.9599p < 0.0063Unclearrank-biserial r = 0.022negligible
Price cut before saleChi-squareχ² = 0.6410.4252p < 0.0063UnclearCramér’s V = 0.141small
Seller paid closing costs or repairsChi-squareχ² = 0.1910.6600p < 0.0063UnclearCramér’s V = 0.078negligible

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 32 closed MLS resale sales; the 0 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 26, 2026. Map data © OpenStreetMap contributors. ALEX Companies · Licensed by the Texas Real Estate Commission · Broker: Alexander Tiffany Southwest, LLC (ALEX Real Estate), #565194-BB · Diane Hart Alexander, Designated Broker, #574877-B.