ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Travisso

Leander, TX 78641
Resale homes · closed Oct 30 – Oct 29, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 30, 2026 · 6:55 AM CDT
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
56
single-family resale homes
Median net sale price
$755,000
average $823,740
Median net price per SF
$235
average $239
Median days on market
116 days
average 138 days
1. SummaryResale homes · 56 sales · October 30, 2025 – October 29, 2026

This study looks at the 56 resale homes sold in Travisso in the 365 days to October 29, 2026. A full year is used because only 31 resale homes sold in the last 180 days. New construction is left out and shown on its own in section 7. The homes are compared four ways: by price, by living area, by year built and with or without a view. The first three are split into four equal groups (quartiles), each named by its range.

Each comparison has its own section (3–6) with everything about it in one place: the key differences, a table of every measure at a glance, the charts and the numbers.

2. Where the resale homes sold56 resale homes · colored by price range

Each dot is one resale home, colored by its price range. Use the buttons to show one price range at a time. Click a dot for that sale: address, close date, original and last list price, net sale price, living area, net sale per SF and days on market. Scroll or pinch to zoom.

Under $550K · 14 sales$550K–$745K · 14 sales$765K–$975K · 14 salesOver $975K · 14 sales
3. Quartiles by net sale priceResale homes · 56 sales · October 30, 2025 – October 29, 2026

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

2026-10-30T06:56:07.798894 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 14 14 14 56 sales Sales per group Under $550K: 14 sales (25%) $550K–$745K: 14 sales (25%) $765K–$975K: 14 sales (25%) Over $975K: 14 sales (25%)
Bottom line

3.1 Key differences

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

Under $550K$550K–$745K$765K–$975KOver $975K
Higher-priced homes Over $975K
  • Are much larger.
Lower-priced homes Under $550K
  • Are much smaller.

3.2 At a glance

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

Under $550K$550K–$745K$765K–$975KOver $975KReal difference?
Net price per SF$237 per SF$223 per SF$230 per SF$266 per SFunclear
Living area2,113 SFSmallest2,958 SF4,003 SF4,696 SFLargest✓ large
Year built2019202020192020unclear
Days on market96 days103 days90 days174 daysunclear
Discount from original list6.9%10.2%12.9%16.5%unclear
Price cut before sale64%50%79%86%unclear
Seller paid closing costs or repairs64%50%36%36%unclear
Has a view50%43%93%71%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

2026-10-30T06:56:07.829067 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $550K 14 sales $550K– $745K 14 sales $765K– $975K 14 sales Over $975K 14 sales $0 $100 $200 $300 $237 $223 $230 $266 Net price per SF, average

The average is $266 per SF for homes over $975K and $237 per SF for homes under $550K. It does not move in a straight line; homes over $975K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $975K are about 2,580 SF (122%) larger than homes under $550K

2026-10-30T06:56:07.854635 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $550K 14 sales $550K– $745K 14 sales $765K– $975K 14 sales Over $975K 14 sales 0 2,000 4,000 2,113 2,958 4,003 4,696 Living area (SF), average

The average is 4,696 SF for homes over $975K and 2,113 SF for homes under $550K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-30T06:56:07.878548 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $550K 14 sales $550K– $745K 14 sales $765K– $975K 14 sales Over $975K 14 sales 2018 2020 2022 2019 2020 2019 2020 Year built: median (dot) and middle half (bar)

The median is 2020 for homes over $975K and 2019 for homes under $550K. It does not move in a straight line; homes $550K–$745K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-30T06:56:07.902307 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $550K 14 sales $550K– $745K 14 sales $765K– $975K 14 sales Over $975K 14 sales 0 100 200 96 103 90 174 Days on market, median

The median is 174 days for homes over $975K and 96 days for homes under $550K. It does not move in a straight line; homes over $975K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-30T06:56:07.924899 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $550K 14 sales $550K– $745K 14 sales $765K– $975K 14 sales Over $975K 14 sales 0.0% 5.0% 10.0% 15.0% 6.9% 10.2% 12.9% 16.5% Discount from original list, average

The average is 16.5% for homes over $975K and 6.9% for homes under $550K. It rises step by step from the lowest range to the 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

2026-10-30T06:56:07.956872 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% 64 64 50 50 50 43 79 36 93 86 36 71 Under $550K $550K–$745K $765K–$975K Over $975K

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

  • 86% of homes over $975K had a price cut before sale, against 64% of homes under $550K. Defined in 8.1.7.
  • 36% of homes over $975K had the seller pay closing costs or repairs, against 64% of homes under $550K. Defined in 8.1.8.
  • 71% of homes over $975K have a view, against 50% of homes under $550K. 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 $550K14 sales$550K–$745K14 sales$765K–$975K14 salesOver $975K14 salesAll56 salesReal difference?
Net sale price average$497,425$650,214$897,306$1,250,017$823,740by design
Net price per SF average$237$223$230$266$239unclear
Living area average2,1132,9584,0034,6963,443✓ large
Year built median20192020201920202019unclear

3.10 The numbers: selling

Under $550K14 sales$550K–$745K14 sales$765K–$975K14 salesOver $975K14 salesAll56 salesReal difference?
Days on market median9610390174116unclear
Discount from original list average6.9%10.2%12.9%16.5%11.6%unclear
Price cut before sale64%50%79%86%70%unclear
Seller paid closing costs or repairs64%50%36%36%46%unclear
Has a view50%43%93%71%64%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.1.

4. Quartiles by living areaResale homes · 56 sales · October 30, 2025 – October 29, 2026

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

2026-10-30T06:56:07.977982 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 14 14 14 14 56 sales Sales per group Under 2,512 SF: 14 sales (25%) 2,512–3,351 SF: 14 sales (25%) 3,427–4,296 SF: 14 sales (25%) Over 4,296 SF: 14 sales (25%)
Bottom line

4.1 Key differences

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

Under 2,512 SF2,512–3,351 SF3,427–4,296 SFOver 4,296 SF
Larger homes Over 4,296 SF
  • Sell for much more.
Smaller homes Under 2,512 SF
  • Sell for much less.

4.2 At a glance

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

Under 2,512 SF2,512–3,351 SF3,427–4,296 SFOver 4,296 SFReal difference?
Net sale price$512KLowest$666K$896K$1.22MHighest✓ large
Net price per SF$244 per SF$231 per SF$232 per SF$248 per SFunclear
Year built2019201820192020unclear
Days on market110 days84 days136 days174 daysunclear
Discount from original list6.8%8.5%13.7%17.3%unclear
Price cut before sale57%57%79%86%unclear
Seller paid closing costs or repairs64%50%43%29%unclear
Has a view64%43%71%79%unclear

4.3 Homes over 4,296 SF sell for about $709K (138%) more than homes under 2,512 SF

2026-10-30T06:56:07.999531 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,512 SF 14 sales 2,512– 3,351 SF 14 sales 3,427– 4,296 SF 14 sales Over 4,296 SF 14 sales $0K $500K $1.00M $512K $666K $896K $1.22M Net sale price, average

The average is $1.22M for homes over 4,296 SF and $512K for homes under 2,512 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-30T06:56:08.023535 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,512 SF 14 sales 2,512– 3,351 SF 14 sales 3,427– 4,296 SF 14 sales Over 4,296 SF 14 sales $0 $100 $200 $244 $231 $232 $248 Net price per SF, average

The average is $248 per SF for homes over 4,296 SF and $244 per SF for homes under 2,512 SF. It does not move in a straight line; homes over 4,296 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-30T06:56:08.048084 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,512 SF 14 sales 2,512– 3,351 SF 14 sales 3,427– 4,296 SF 14 sales Over 4,296 SF 14 sales 2018 2019 2020 2021 2019 2018 2019 2020 Year built: median (dot) and middle half (bar)

The median is 2020 for homes over 4,296 SF and 2019 for homes under 2,512 SF. It does not move in a straight line; homes over 4,296 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-30T06:56:08.071765 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,512 SF 14 sales 2,512– 3,351 SF 14 sales 3,427– 4,296 SF 14 sales Over 4,296 SF 14 sales 0 100 200 110 84 136 174 Days on market, median

The median is 174 days for homes over 4,296 SF and 110 days for homes under 2,512 SF. It does not move in a straight line; homes over 4,296 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-30T06:56:08.095285 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,512 SF 14 sales 2,512– 3,351 SF 14 sales 3,427– 4,296 SF 14 sales Over 4,296 SF 14 sales 0.0% 10.0% 20.0% 6.8% 8.5% 13.7% 17.3% Discount from original list, average

The average is 17.3% for homes over 4,296 SF and 6.8% for homes under 2,512 SF. It rises step by step from the lowest range to the 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

2026-10-30T06:56:08.123830 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 57 64 64 57 50 43 79 43 71 86 29 79 Under 2,512 SF 2,512–3,351 SF 3,427–4,296 SF Over 4,296 SF

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

  • 86% of homes over 4,296 SF had a price cut before sale, against 57% of homes under 2,512 SF. Defined in 8.1.7.
  • 29% of homes over 4,296 SF had the seller pay closing costs or repairs, against 64% of homes under 2,512 SF. Defined in 8.1.8.
  • 79% of homes over 4,296 SF have a view, against 64% of homes under 2,512 SF. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

4.9 The numbers: price and size

Under 2,512 SF14 sales2,512–3,351 SF14 sales3,427–4,296 SF14 salesOver 4,296 SF14 salesAll56 salesReal difference?
Net sale price average$512,232$665,721$895,972$1,221,036$823,740✓ large
Net price per SF average$244$231$232$248$239unclear
Living area average2,1022,8803,8594,9303,443by design
Year built median20192018201920202019unclear

4.10 The numbers: selling

Under 2,512 SF14 sales2,512–3,351 SF14 sales3,427–4,296 SF14 salesOver 4,296 SF14 salesAll56 salesReal difference?
Days on market median11084136174116unclear
Discount from original list average6.8%8.5%13.7%17.3%11.6%unclear
Price cut before sale57%57%79%86%70%unclear
Seller paid closing costs or repairs64%50%43%29%46%unclear
Has a view64%43%71%79%64%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.2.

5. Quartiles by year builtResale homes · 56 sales · October 30, 2025 – October 29, 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.

2026-10-30T06:56:08.147712 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 13 16 11 16 56 sales Sales per group Before 2018: 13 sales (23%) 2018–2019: 16 sales (29%) 2020: 11 sales (20%) After 2020: 16 sales (29%)
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 20182018–20192020After 2020Real difference?
Net sale price$784K$766K$902K$860Kunclear
Net price per SF$237 per SF$250 per SF$241 per SF$228 per SFunclear
Living area3,287 SF3,004 SF3,677 SF3,847 SFunclear
Days on market166 days72 days158 days98 daysunclear
Discount from original list10.4%7.6%14.3%14.8%unclear
Price cut before sale54%62%82%81%unclear
Seller paid closing costs or repairs46%38%36%62%unclear
Has a view69%56%64%69%unclear

5.3 Net sale price: no clear difference

2026-10-30T06:56:08.172129 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2018 13 sales 2018– 2019 16 sales 2020 11 sales After 2020 16 sales $0K $500K $1.00M $784K $766K $902K $860K Net sale price, average

The average is $860K for homes built after 2020 and $784K for homes built before 2018. It does not move in a straight line; homes built 2020 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-30T06:56:08.196701 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2018 13 sales 2018– 2019 16 sales 2020 11 sales After 2020 16 sales $0 $100 $200 $300 $237 $250 $241 $228 Net price per SF, average

The average is $228 per SF for homes built after 2020 and $237 per SF for homes built before 2018. It does not move in a straight line; homes built 2018–2019 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-30T06:56:08.219531 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2018 13 sales 2018– 2019 16 sales 2020 11 sales After 2020 16 sales 0 2,000 4,000 3,287 3,004 3,677 3,847 Living area (SF), average

The average is 3,847 SF for homes built after 2020 and 3,287 SF for homes built before 2018. It does not move in a straight line; homes built after 2020 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-30T06:56:08.242020 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2018 13 sales 2018– 2019 16 sales 2020 11 sales After 2020 16 sales 0 50 100 150 166 72 158 98 Days on market, median

The median is 98 days for homes built after 2020 and 166 days for homes built before 2018. It does not move in a straight line; homes built before 2018 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-30T06:56:08.265465 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2018 13 sales 2018– 2019 16 sales 2020 11 sales After 2020 16 sales 0.0% 5.0% 10.0% 15.0% 10.4% 7.6% 14.3% 14.8% Discount from original list, average

The average is 14.8% for homes built after 2020 and 10.4% for homes built before 2018. It does not move in a straight line; homes built after 2020 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

2026-10-30T06:56:08.292730 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% 54 46 69 62 38 56 82 36 64 81 62 69 Before 2018 2018–2019 2020 After 2020

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

  • 81% of homes built after 2020 had a price cut before sale, against 54% of homes built before 2018. Defined in 8.1.7.
  • 62% of homes built after 2020 had the seller pay closing costs or repairs, against 46% of homes built before 2018. Defined in 8.1.8.
  • 69% of homes built after 2020 have a view, against 69% of homes built before 2018. 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 201813 sales2018–201916 sales202011 salesAfter 202016 salesAll56 salesReal difference?
Net sale price average$783,815$765,509$902,230$860,449$823,740unclear
Net price per SF average$237$250$241$228$239unclear
Living area average3,2873,0043,6773,8473,443unclear
Year built median20142018202020222019by design

5.10 The numbers: selling

Before 201813 sales2018–201916 sales202011 salesAfter 202016 salesAll56 salesReal difference?
Days on market median1667215898116unclear
Discount from original list average10.4%7.6%14.3%14.8%11.6%unclear
Price cut before sale54%62%82%81%70%unclear
Seller paid closing costs or repairs46%38%36%62%46%unclear
Has a view69%56%64%69%64%unclear

Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.3.

6. View and no viewResale homes · 56 sales · October 30, 2025 – October 29, 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.

2026-10-30T06:56:08.312701 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 36 18 54 sales Sales per group View: 36 sales (67%) No view: 18 sales (33%)
Bottom line

6.1 Key differences

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

ViewNo view
Homes with a view MLS lists a view
  • Sell for more per square foot.
Homes without a view no view listed
  • Sell for less per square foot.

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$902K$670Kunclear
Net price per SF$253 per SFHighest$212 per SFLowest✓ large
Living area3,561 SF3,206 SFunclear
Year built20202019unclear
Days on market110 days114 daysunclear
Discount from original list11.2%11.9%unclear
Price cut before sale69%72%unclear
Seller paid closing costs or repairs39%56%unclear

6.3 Net sale price: no clear difference

2026-10-30T06:56:08.330742 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 36 sales No view 18 sales $0K $250K $500K $750K $1.00M $902K $670K Net sale price, average

The average is $902K for homes with a view and $670K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Homes with a view sell for about $42 per SF (20%) more than homes without a view

2026-10-30T06:56:08.349477 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 36 sales No view 18 sales $0 $100 $200 $300 $253 $212 Net price per SF, average

The average is $253 per SF for homes with a view and $212 per SF for homes without a view. Defined in 8.1.2.

✓ Real difference · large

6.5 Living area: no clear difference

2026-10-30T06:56:08.370041 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 36 sales No view 18 sales 0 1,000 2,000 3,000 4,000 3,561 3,206 Living area (SF), average

The average is 3,561 SF for homes with a view and 3,206 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-30T06:56:08.464050 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 36 sales No view 18 sales 2018 2019 2020 2021 2020 2019 Year built: median (dot) and middle half (bar)

The median is 2020 for homes with a view and 2019 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-30T06:56:08.483445 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 36 sales No view 18 sales 0 50 100 110 114 Days on market, median

The median is 110 days for homes with a view and 114 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

2026-10-30T06:56:08.503813 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 36 sales No view 18 sales 0.0% 5.0% 10.0% 11.2% 11.9% Discount from original list, average

The average is 11.2% for homes with a view and 11.9% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-30T06:56:08.523634 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 69 39 72 56 View No view

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

  • 69% of homes with a view had a price cut before sale, against 72% of homes without a view. Defined in 8.1.7.
  • 39% of homes with a view had the seller pay closing costs or repairs, against 56% 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

View36 salesNo view18 salesAll54 salesReal difference?
Net sale price average$902,189$669,736$824,705unclear
Net price per SF average$253$212$239✓ large
Living area average3,5613,2063,442unclear
Year built median202020192019unclear

6.11 The numbers: selling

View36 salesNo view18 salesAll54 salesReal difference?
Days on market median110114110unclear
Discount from original list average11.2%11.9%11.4%unclear
Price cut before sale69%72%70%unclear
Seller paid closing costs or repairs39%56%44%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 · 50 sales · October 30, 2025 – October 29, 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: 50 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 Travisso.
MeasureAverageMedian
Sales50
Net sale price$825,410$762,166
Net price per SF$219$212
Living area (SF)3,7643,899
Days on market10396
Discount from original list15.1%16.2%
Price cut before sale70% of sales
Seller paid closing costs or repairs58% of sales
Year built2021–2026

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
56 resale sales. Average $823,740; median $755,000; standard deviation $322,928; middle half (25th–75th percentile) $549,175–$977,800; lowest $440,000, highest $1,800,000. 26 sales had a seller payment; their median payment was $4,800.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
56 resale sales. Average $239; median $235; standard deviation $39; middle half (25th–75th percentile) $216–$263; lowest $168, highest $377.

8.1.3 Living area

In simple terms
The heated and cooled space, as listed in the MLS. Garages and porches are not counted.
Statistically
RESO LivingArea, in square feet. Sales under 400 SF are treated as entry errors and left out.
The data
56 resale sales. Average 3,443; median 3,389; standard deviation 1,115; middle half (25th–75th percentile) 2,507–4,312; lowest 1,912, highest 5,687.

8.1.4 Year built

In simple terms
The year the home was finished, as listed in the MLS. It shows whether a group leans to older or newer phases of the community.
Statistically
RESO YearBuilt; summarized by the median, with the 25th–75th percentile (middle half) on the charts.
The data
56 resale sales. Average 2019; median 2019; standard deviation 3; middle half (25th–75th percentile) 2018–2021; lowest 2014, highest 2026.

8.1.5 Days on market

In simple terms
How many days the home was on the market before the buyer's offer was accepted, counting any earlier listing periods (relists). This is the days on market agents and clients quote.
Statistically
CDOM = max(CumulativeDaysOnMarket, DaysOnMarket, PurchaseContractDate − ListingContractDate). The MLS counter can freeze at a price change, so the contract-date gap is a floor. Summarized by the median, because a few homes that sat for months pull an average up.
The data
56 resale sales. Average 138; median 116; standard deviation 123; middle half (25th–75th percentile) 51–194; lowest 2, highest 549. 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
56 resale sales. Average 11.6%; median 10.3%; standard deviation 9.4%; middle half (25th–75th percentile) 4.5%–15.3%; lowest −2.1%, highest 39.7%. 3 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
39 of 56 resale sales (69.6%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
26 of 56 resale sales (46.4%).

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
36 sales with a view, 18 without, 2 unclassified. Most common View entries: Hill Country 22, Neighborhood 20, Park/Greenbelt 19, Panoramic 15, Trees/Woods 14, None 9, Pool 3, See Remarks 3.

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 = Leander, SubdivisionName contains any of “travisso”, “travisso siena collection”, “travisso capri collection” (case-insensitive). A record is kept when its subdivision name belongs to the Travisso family, the same rule comparable sales use (it includes Travisso - Siena Collection, Travisso - Capri Collection, proven adjacent and priced alike).
The data
Pulled October 30, 2026: 106 closed Travisso records over the prior year, in ZIP 78641. 22 subdivision spellings kept, the most common: Travisso (59); Travisso - Capri Collection (10); Travisso - Siena Collection (7); Travisso Ph 3 Sec 5 (3); Travisso Sec 1 Ph 2 (3); Travisso Ph 2 Sec 1M (2); Travisso Ph 2 Secs 2F 2G & 2H (2); Travisso Ph 4 Sec 6A (2); Travisso Ph 4 Secs 1 2 & 3 (2); Travisso Ph 3 Secs 1 & 3 (2); Travisso Ph 3 Sec 1 3 (2); Travisso Ph 2 Secs 2C 2D & 2E (2); and 10 more (10 records). Names found by the search but not part of Travisso, left out: Travisso - Florence Collection (5); Travisso - Verona Collection (4); Travisso - Naples Collection (3); Travisso Florence Collection (1); Travisso-Florence Collection (1); TRAVISSO PHS 3 SEC 4 (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 31 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 30, 2025 to October 29, 2026 inclusive.
The data
106 single-family sales in the window: 56 resale, 50 new construction.

8.2.3 Resale and new construction

In simple terms
A resale home was previously owned. New construction is sold by the builder and behaves differently, so it is kept out of every analysis and reported once on its own.
Statistically
New construction = NewConstructionYN true, or PropertyCondition contains “New Construction” or “Under Construction”. Everything else is resale.
The data
56 resale; 50 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 $550K”.
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 $550K: $440,000–$546,700 (14 sales); $550K–$745K: $550,000–$745,000 (14 sales); $765K–$975K: $765,000–$975,000 (14 sales); Over $975K: $986,200–$1,800,000 (14 sales)
Quartiles by living area: Under 2,512 SF: 1,912–2,493 SF (14 sales); 2,512–3,351 SF: 2,512–3,351 SF (14 sales); 3,427–4,296 SF: 3,427–4,296 SF (14 sales); Over 4,296 SF: 4,359–5,687 SF (14 sales)
Quartiles by year built: Before 2018: 2014–2017 (13 sales); 2018–2019: 2018–2019 (16 sales); 2020: 2020–2020 (11 sales); After 2020: 2021–2026 (16 sales)
View and no view: View: MLS lists a view (36 sales); No view: None or Neighborhood (18 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 $823,740, median $755,000. Days on market: average 138, median 116: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

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

8.2.8 Mann–Whitney U test

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

8.2.9 Chi-square test

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

8.2.10 Real difference (significance)

In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063; Quartiles by year built: m = 8, threshold p < 0.0063; View and no view: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
3 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

In simple terms
Headings and sentences round figures so they read easily; the tables at the end of each section give them in full.
Statistically
Prices in headings round to the nearest $1K; price per SF and days on market to the nearest whole number; living area to the nearest 10 SF; shares and percentage gaps to whole percents.
The data
Days on market is always shown in days.

8.3 Test results

Every test behind every gold box. Statistic, degrees of freedom (df), p-value, the threshold it must beat, and the size of the difference.

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 6.6230.0851p < 0.0063Unclearε² = 0.120medium
Living areaKruskal–WallisH = 45.323< 0.0001p < 0.0063Yesε² = 0.824large
Year builtKruskal–WallisH = 1.6230.6551p < 0.0063Unclearε² = 0.029small
Days on marketKruskal–WallisH = 3.4230.3312p < 0.0063Unclearε² = 0.062medium
Discount from original listKruskal–WallisH = 9.4730.0236p < 0.0063Unclearε² = 0.172large
Price cut before saleChi-squareχ² = 4.9830.1730p < 0.0063UnclearCramér’s V = 0.298small
Seller paid closing costs or repairsChi-squareχ² = 3.1630.3678p < 0.0063UnclearCramér’s V = 0.238small
Has a viewChi-squareχ² = 9.3330.0252p < 0.0063UnclearCramér’s V = 0.408medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 44.423< 0.0001p < 0.0063Yesε² = 0.808large
Net price per SFKruskal–WallisH = 1.1930.7543p < 0.0063Unclearε² = 0.022small
Year builtKruskal–WallisH = 2.4330.4885p < 0.0063Unclearε² = 0.044small
Days on marketKruskal–WallisH = 3.4030.3334p < 0.0063Unclearε² = 0.062medium
Discount from original listKruskal–WallisH = 12.0730.0071p < 0.0063Unclearε² = 0.219large
Price cut before saleChi-squareχ² = 4.3130.2301p < 0.0063UnclearCramér’s V = 0.277small
Seller paid closing costs or repairsChi-squareχ² = 3.7330.2917p < 0.0063UnclearCramér’s V = 0.258small
Has a viewChi-squareχ² = 4.3630.2255p < 0.0063UnclearCramér’s V = 0.279small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 2.0030.5730p < 0.0063Unclearε² = 0.036small
Net price per SFKruskal–WallisH = 2.2130.5295p < 0.0063Unclearε² = 0.040small
Living areaKruskal–WallisH = 4.4830.2143p < 0.0063Unclearε² = 0.081medium
Days on marketKruskal–WallisH = 3.5330.3174p < 0.0063Unclearε² = 0.064medium
Discount from original listKruskal–WallisH = 5.6330.1313p < 0.0063Unclearε² = 0.102medium
Price cut before saleChi-squareχ² = 3.7130.2944p < 0.0063UnclearCramér’s V = 0.257small
Seller paid closing costs or repairsChi-squareχ² = 2.6230.4535p < 0.0063UnclearCramér’s V = 0.216small
Has a viewChi-squareχ² = 0.7330.8663p < 0.0063UnclearCramér’s V = 0.114small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 458.00—0.0143p < 0.0063Unclearrank-biserial r = 0.414medium
Net price per SFMann–Whitney UU = 536.00—0.0001p < 0.0063Yesrank-biserial r = 0.654large
Living areaMann–Whitney UU = 385.50—0.2630p < 0.0063Unclearrank-biserial r = 0.190small
Year builtMann–Whitney UU = 320.00—0.9483p < 0.0063Unclearrank-biserial r = 0.012negligible
Days on marketMann–Whitney UU = 333.50—0.8688p < 0.0063Unclearrank-biserial r = 0.029negligible
Discount from original listMann–Whitney UU = 282.50—0.4518p < 0.0063Unclearrank-biserial r = 0.128small
Price cut before saleChi-squareχ² = 0.0410.8331p < 0.0063UnclearCramér’s V = 0.029negligible
Seller paid closing costs or repairsChi-squareχ² = 1.3510.2453p < 0.0063UnclearCramér’s V = 0.158small

8.4 Data notes

Left out of the analysis: 50 new-construction sales (basic statistics only, section 7); nothing else. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

  1. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Erlbaum.
  2. Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press.
  3. Dunn, O. J. (1961). Multiple comparisons among means. JASA, 56(293), 52–64.
  4. Kerby, D. S. (2014). The simple difference formula: an approach to teaching nonparametric correlation. Comprehensive Psychology, 3, 11.IT.3.1.
  5. Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. JASA, 47(260), 583–621.
  6. Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18(1), 50–60.
  7. Pearson, K. (1900). On the criterion that a given system of deviations… Philosophical Magazine, 50(302), 157–175.
  8. Tomczak, M., & Tomczak, E. (2014). The need to report effect size estimates revisited. Trends in Sport Sciences, 21(1), 19–25.

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 56 closed MLS resale sales; the 50 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled October 30, 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.