ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Larkspur

Leander, TX 78641
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 · 7:09 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
49
single-family resale homes
Median net sale price
$365,000
average $363,845
Median net price per SF
$175
average $175
Median days on market
54 days
average 78 days
1. SummaryResale homes · 49 sales · October 26, 2025 – October 25, 2026

This study looks at the 49 resale homes sold in Larkspur in the 365 days to October 25, 2026. A full year is used because only 25 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 sold49 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 $315K · 12 sales$315K–$364K · 11 sales$365K–$390K · 14 salesOver $390K · 12 sales
3. Quartiles by net sale priceResale homes · 49 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.

2026-10-26T07:09:33.120795 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 12 11 14 12 49 sales Sales per group Under $315K: 12 sales (24%) $315K–$364K: 11 sales (22%) $365K–$390K: 14 sales (29%) Over $390K: 12 sales (24%)
Bottom line

3.1 Key differences

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

Under $315K$315K–$364K$365K–$390KOver $390K
Higher-priced homes Over $390K
  • Are much larger.
  • Sell for less per square foot.
Lower-priced homes Under $315K
  • Are much smaller.
  • Sell for more per square foot.

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 $315K$315K–$364K$365K–$390KOver $390KReal difference?
Net price per SF$194 per SFHighest$179 per SF$167 per SF$164 per SFLowest✓ large
Living area1,570 SFSmallest1,957 SF2,267 SF2,677 SFLargest✓ large
Year built2019202020202020unclear
Days on market66 days35 days82 days50 daysunclear
Discount from original list6.4%6.3%5.1%5.1%unclear
Price cut before sale58%64%57%50%unclear
Seller paid closing costs or repairs83%82%71%75%unclear
Has a view33%27%21%50%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 Homes over $390K sell for about $30 per SF (15%) less than homes under $315K

2026-10-26T07:09:33.150756 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $315K 12 sales $315K– $364K 11 sales $365K– $390K 14 sales Over $390K 12 sales $0 $100 $200 $194 $179 $167 $164 Net price per SF, average

The average is $164 per SF for homes over $390K and $194 per SF for homes under $315K. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $390K are about 1,110 SF (71%) larger than homes under $315K

2026-10-26T07:09:33.173787 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $315K 12 sales $315K– $364K 11 sales $365K– $390K 14 sales Over $390K 12 sales 0 1,000 2,000 3,000 1,570 1,957 2,267 2,677 Living area (SF), average

The average is 2,677 SF for homes over $390K and 1,570 SF for homes under $315K. 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

2026-10-26T07:09:33.199836 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $315K 12 sales $315K– $364K 11 sales $365K– $390K 14 sales Over $390K 12 sales 2018 2019 2020 2021 2022 2019 2020 2020 2020 Year built: median (dot) and middle half (bar)

The median is 2020 for homes over $390K and 2019 for homes under $315K. It does not move in a straight line; homes $315K–$364K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T07:09:33.223921 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $315K 12 sales $315K– $364K 11 sales $365K– $390K 14 sales Over $390K 12 sales 0 25 50 75 66 35 82 50 Days on market, median

The median is 50 days for homes over $390K and 66 days for homes under $315K. It does not move in a straight line; homes $365K–$390K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T07:09:33.246835 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $315K 12 sales $315K– $364K 11 sales $365K– $390K 14 sales Over $390K 12 sales 0.0% 2.0% 4.0% 6.0% 6.4% 6.3% 5.1% 5.1% Discount from original list, average

The average is 5.1% for homes over $390K and 6.4% for homes under $315K. It falls 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

2026-10-26T07:09:33.278429 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% 58 83 33 64 82 27 57 71 21 50 75 50 Under $315K $315K–$364K $365K–$390K Over $390K

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

  • 50% of homes over $390K had a price cut before sale, against 58% of homes under $315K. Defined in 8.1.7.
  • 75% of homes over $390K had the seller pay closing costs or repairs, against 83% of homes under $315K. Defined in 8.1.8.
  • 50% of homes over $390K have a view, against 33% of homes under $315K. 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 $315K12 sales$315K–$364K11 sales$365K–$390K14 salesOver $390K12 salesAll49 salesReal difference?
Net sale price average$301,473$339,108$375,672$435,093$363,845by design
Net price per SF average$194$179$167$164$175✓ large
Living area average1,5701,9572,2672,6772,127✓ large
Year built median20192020202020202020unclear

3.10 The numbers: selling

Under $315K12 sales$315K–$364K11 sales$365K–$390K14 salesOver $390K12 salesAll49 salesReal difference?
Days on market median6635825054unclear
Discount from original list average6.4%6.3%5.1%5.1%5.7%unclear
Price cut before sale58%64%57%50%57%unclear
Seller paid closing costs or repairs83%82%71%75%78%unclear
Has a view33%27%21%50%33%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 · 49 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.

2026-10-26T07:09:33.300162 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 12 14 12 49 sales Sales per group Under 1,703 SF: 11 sales (22%) 1,703–2,104 SF: 12 sales (24%) 2,146–2,467 SF: 14 sales (29%) Over 2,467 SF: 12 sales (24%)
Bottom line

4.1 Key differences

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

Under 1,703 SF1,703–2,104 SF2,146–2,467 SFOver 2,467 SF
Larger homes Over 2,467 SF
  • Sell for much more.
  • Sell for less per square foot.
Smaller homes Under 1,703 SF
  • Sell for much less.
  • 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 1,703 SF1,703–2,104 SF2,146–2,467 SFOver 2,467 SFReal difference?
Net sale price$302KLowest$343K$379K$424KHighest✓ large
Net price per SF$201 per SFHighest$185 per SF$166 per SF$153 per SFLowest✓ large
Year built2019201920202020unclear
Days on market49 days30 days82 days85 daysunclear
Discount from original list4.9%4.5%4.0%9.5%unclear
Price cut before sale55%50%50%75%unclear
Seller paid closing costs or repairs64%100%79%67%unclear
Has a view27%33%21%50%unclear

4.3 Homes over 2,467 SF sell for about $122K (40%) more than homes under 1,703 SF

2026-10-26T07:09:33.321901 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,703 SF 11 sales 1,703– 2,104 SF 12 sales 2,146– 2,467 SF 14 sales Over 2,467 SF 12 sales $0K $200K $400K $302K $343K $379K $424K Net sale price, average

The average is $424K for homes over 2,467 SF and $302K for homes under 1,703 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 2,467 SF sell for about $48 per SF (24%) less than homes under 1,703 SF

2026-10-26T07:09:33.345039 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,703 SF 11 sales 1,703– 2,104 SF 12 sales 2,146– 2,467 SF 14 sales Over 2,467 SF 12 sales $0 $100 $200 $201 $185 $166 $153 Net price per SF, average

The average is $153 per SF for homes over 2,467 SF and $201 per SF for homes under 1,703 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

2026-10-26T07:09:33.370506 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,703 SF 11 sales 1,703– 2,104 SF 12 sales 2,146– 2,467 SF 14 sales Over 2,467 SF 12 sales 2018 2019 2020 2021 2022 2019 2019 2020 2020 Year built: median (dot) and middle half (bar)

The median is 2020 for homes over 2,467 SF and 2019 for homes under 1,703 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

2026-10-26T07:09:33.394642 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,703 SF 11 sales 1,703– 2,104 SF 12 sales 2,146– 2,467 SF 14 sales Over 2,467 SF 12 sales 0 50 100 49 30 82 85 Days on market, median

The median is 85 days for homes over 2,467 SF and 49 days for homes under 1,703 SF. It does not move in a straight line; homes over 2,467 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T07:09:33.417230 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,703 SF 11 sales 1,703– 2,104 SF 12 sales 2,146– 2,467 SF 14 sales Over 2,467 SF 12 sales 0.0% 5.0% 10.0% 4.9% 4.5% 4.0% 9.5% Discount from original list, average

The average is 9.5% for homes over 2,467 SF and 4.9% for homes under 1,703 SF. It does not move in a straight line; homes over 2,467 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

2026-10-26T07:09:33.444543 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% 55 64 27 50 100 33 50 79 21 75 67 50 Under 1,703 SF 1,703–2,104 SF 2,146–2,467 SF Over 2,467 SF

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

  • 75% of homes over 2,467 SF had a price cut before sale, against 55% of homes under 1,703 SF. Defined in 8.1.7.
  • 67% of homes over 2,467 SF had the seller pay closing costs or repairs, against 64% of homes under 1,703 SF. Defined in 8.1.8.
  • 50% of homes over 2,467 SF have a view, against 27% of homes under 1,703 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 1,703 SF11 sales1,703–2,104 SF12 sales2,146–2,467 SF14 salesOver 2,467 SF12 salesAll49 salesReal difference?
Net sale price average$301,930$342,921$378,812$424,062$363,845✓ large
Net price per SF average$201$185$166$153$175✓ large
Living area average1,5051,8602,2912,7732,127by design
Year built median20192019202020202020unclear

4.10 The numbers: selling

Under 1,703 SF11 sales1,703–2,104 SF12 sales2,146–2,467 SF14 salesOver 2,467 SF12 salesAll49 salesReal difference?
Days on market median4930828554unclear
Discount from original list average4.9%4.5%4.0%9.5%5.7%unclear
Price cut before sale55%50%50%75%57%unclear
Seller paid closing costs or repairs64%100%79%67%78%unclear
Has a view27%33%21%50%33%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 · 49 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.

2026-10-26T07:09:33.465810 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 11 12 19 7 49 sales Sales per group Before 2019: 11 sales (22%) 2019: 12 sales (24%) 2020: 19 sales (39%) After 2020: 7 sales (14%)
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 201920192020After 2020Real difference?
Net sale price$368K$335K$359K$420Kunclear
Net price per SF$174 per SF$183 per SF$178 per SF$157 per SFunclear
Living area2,127 SF1,856 SF2,091 SF2,690 SFunclear
Days on market80 days42 days45 days81 daysunclear
Discount from original list4.5%6.3%5.6%6.7%unclear
Price cut before sale55%42%63%71%unclear
Seller paid closing costs or repairs100%75%68%71%unclear
Has a view45%25%32%29%unclear

5.3 Net sale price: no clear difference

2026-10-26T07:09:33.486838 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 11 sales 2019 12 sales 2020 19 sales After 2020 7 sales $0K $200K $400K $368K $335K $359K $420K Net sale price, average

The average is $420K for homes built after 2020 and $368K for homes built before 2019. It does not move in a straight line; homes built after 2020 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T07:09:33.510503 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 11 sales 2019 12 sales 2020 19 sales After 2020 7 sales $0 $50 $100 $150 $200 $174 $183 $178 $157 Net price per SF, average

The average is $157 per SF for homes built after 2020 and $174 per SF for homes built before 2019. It does not move in a straight line; homes built 2019 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T07:09:33.532738 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 11 sales 2019 12 sales 2020 19 sales After 2020 7 sales 0 1,000 2,000 3,000 2,127 1,856 2,091 2,690 Living area (SF), average

The average is 2,690 SF for homes built after 2020 and 2,127 SF for homes built before 2019. 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

2026-10-26T07:09:33.556197 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 11 sales 2019 12 sales 2020 19 sales After 2020 7 sales 0 20 40 60 80 80 42 45 81 Days on market, median

The median is 81 days for homes built after 2020 and 80 days for homes built before 2019. It does not move in a straight line; homes built after 2020 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T07:09:33.579681 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2019 11 sales 2019 12 sales 2020 19 sales After 2020 7 sales 0.0% 2.0% 4.0% 6.0% 8.0% 4.5% 6.3% 5.6% 6.7% Discount from original list, average

The average is 6.7% for homes built after 2020 and 4.5% for homes built before 2019. 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

2026-10-26T07:09:33.606588 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% 55 100 45 42 75 25 63 68 32 71 71 29 Before 2019 2019 2020 After 2020

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

  • 71% of homes built after 2020 had a price cut before sale, against 55% of homes built before 2019. Defined in 8.1.7.
  • 71% of homes built after 2020 had the seller pay closing costs or repairs, against 100% of homes built before 2019. Defined in 8.1.8.
  • 29% of homes built after 2020 have a view, against 45% of homes built before 2019. 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 201911 sales201912 sales202019 salesAfter 20207 salesAll49 salesReal difference?
Net sale price average$368,027$335,420$358,559$420,346$363,845unclear
Net price per SF average$174$183$178$157$175unclear
Living area average2,1271,8562,0912,6902,127unclear
Year built median20182019202020222020by design

5.10 The numbers: selling

Before 201911 sales201912 sales202019 salesAfter 20207 salesAll49 salesReal difference?
Days on market median8042458154unclear
Discount from original list average4.5%6.3%5.6%6.7%5.7%unclear
Price cut before sale55%42%63%71%57%unclear
Seller paid closing costs or repairs100%75%68%71%78%unclear
Has a view45%25%32%29%33%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 · 49 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.

2026-10-26T07:09:33.625587 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 16 33 49 sales Sales per group View: 16 sales (33%) No view: 33 sales (67%)
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$374K$359Kunclear
Net price per SF$174 per SF$176 per SFunclear
Living area2,194 SF2,095 SFunclear
Year built20202020unclear
Days on market30 days69 daysunclear
Discount from original list4.3%6.3%unclear
Price cut before sale38%67%unclear
Seller paid closing costs or repairs81%76%unclear

6.3 Net sale price: no clear difference

2026-10-26T07:09:33.642601 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 33 sales $0K $100K $200K $300K $400K $374K $359K Net sale price, average

The average is $374K for homes with a view and $359K 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

2026-10-26T07:09:33.661730 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 33 sales $0 $50 $100 $150 $200 $174 $176 Net price per SF, average

The average is $174 per SF for homes with a view and $176 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

2026-10-26T07:09:33.735429 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 33 sales 0 1,000 2,000 2,194 2,095 Living area (SF), average

The average is 2,194 SF for homes with a view and 2,095 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T07:09:33.754359 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 33 sales 2018 2019 2020 2020 2020 Year built: median (dot) and middle half (bar)

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

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T07:09:33.772872 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 33 sales 0 20 40 60 80 30 69 Days on market, median

The median is 30 days for homes with a view and 69 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

2026-10-26T07:09:33.791942 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 16 sales No view 33 sales 0.0% 2.0% 4.0% 6.0% 4.3% 6.3% Discount from original list, average

The average is 4.3% for homes with a view and 6.3% 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

2026-10-26T07:09:33.811265 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 38 81 67 76 View No view

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

  • 38% of homes with a view had a price cut before sale, against 67% of homes without a view. Defined in 8.1.7.
  • 81% 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

View16 salesNo view33 salesAll49 salesReal difference?
Net sale price average$373,892$358,973$363,845unclear
Net price per SF average$174$176$175unclear
Living area average2,1942,0952,127unclear
Year built median202020202020unclear

6.11 The numbers: selling

View16 salesNo view33 salesAll49 salesReal difference?
Days on market median306954unclear
Discount from original list average4.3%6.3%5.7%unclear
Price cut before sale38%67%57%unclear
Seller paid closing costs or repairs81%76%78%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 Larkspur.

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
49 resale sales. Average $363,845; median $365,000; standard deviation $52,285; middle half (25th–75th percentile) $315,000–$390,000; lowest $281,500, highest $475,000. 38 sales had a seller payment; their median payment was $5,250.

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
49 resale sales. Average $175; median $175; standard deviation $23; middle half (25th–75th percentile) $158–$190; lowest $126, highest $225.

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
49 resale sales. Average 2,127; median 2,146; standard deviation 487; middle half (25th–75th percentile) 1,703–2,467; lowest 1,393, highest 3,050.

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
49 resale sales. Average 2019; median 2020; standard deviation 1; middle half (25th–75th percentile) 2019–2020; lowest 2017, highest 2022.

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
49 resale sales. Average 78; median 54; standard deviation 81; middle half (25th–75th percentile) 19–106; lowest 0, highest 431. 1 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
49 resale sales. Average 5.7%; median 4.1%; standard deviation 5.2%; middle half (25th–75th percentile) 2.0%–8.0%; lowest −1.3%, highest 22.6%. 2 sales closed above their first asking price.

8.1.7 Price cut before sale

In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
28 of 49 resale sales (57.1%).

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
38 of 49 resale sales (77.6%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
16 sales with a view, 33 without, 0 unclassified. Most common View entries: Neighborhood 21, None 20, Park/Greenbelt 13, Trees/Woods 6, Hill Country 1, Creek/Stream 1, Pond 1, See Remarks 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 = Leander, SubdivisionName contains any of “larkspur” (case-insensitive). A record is kept when its subdivision name belongs to the Larkspur family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 49 closed Larkspur records over the prior year, in ZIP 78641. 2 subdivision spellings kept: Larkspur (45); LARKSPUR (4). Names found by the search but not part of Larkspur, left out: Larkspur Caughfield (1); Larkspur, Caughfield (1); Larkspur Subdivison (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 25 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
49 single-family sales in the window: 49 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
49 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 $315K”.
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 $315K: $281,500–$314,000 (12 sales); $315K–$364K: $315,000–$363,750 (11 sales); $365K–$390K: $365,000–$390,000 (14 sales); Over $390K: $390,712–$475,000 (12 sales)
Quartiles by living area: Under 1,703 SF: 1,393–1,698 SF (11 sales); 1,703–2,104 SF: 1,703–2,104 SF (12 sales); 2,146–2,467 SF: 2,146–2,467 SF (14 sales); Over 2,467 SF: 2,484–3,050 SF (12 sales)
Quartiles by year built: Before 2019: 2017–2018 (11 sales); 2019: 2019–2019 (12 sales); 2020: 2020–2020 (19 sales); After 2020: 2021–2022 (7 sales)
View and no view: View: MLS lists a view (16 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 $363,845, median $365,000. Days on market: average 78, 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
4 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 = 13.8730.0031p < 0.0063Yesε² = 0.289large
Living areaKruskal–WallisH = 32.513< 0.0001p < 0.0063Yesε² = 0.677large
Year builtKruskal–WallisH = 3.1730.3656p < 0.0063Unclearε² = 0.066medium
Days on marketKruskal–WallisH = 0.4430.9328p < 0.0063Unclearε² = 0.009negligible
Discount from original listKruskal–WallisH = 2.0930.5533p < 0.0063Unclearε² = 0.044small
Price cut before saleChi-squareχ² = 0.4530.9305p < 0.0063UnclearCramér’s V = 0.095negligible
Seller paid closing costs or repairsChi-squareχ² = 0.6930.8751p < 0.0063UnclearCramér’s V = 0.119small
Has a viewChi-squareχ² = 2.5930.4590p < 0.0063UnclearCramér’s V = 0.230small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 35.573< 0.0001p < 0.0063Yesε² = 0.741large
Net price per SFKruskal–WallisH = 30.463< 0.0001p < 0.0063Yesε² = 0.635large
Year builtKruskal–WallisH = 8.7230.0333p < 0.0063Unclearε² = 0.182large
Days on marketKruskal–WallisH = 4.5630.2067p < 0.0063Unclearε² = 0.095medium
Discount from original listKruskal–WallisH = 4.1130.2498p < 0.0063Unclearε² = 0.086medium
Price cut before saleChi-squareχ² = 2.1330.5450p < 0.0063UnclearCramér’s V = 0.209small
Seller paid closing costs or repairsChi-squareχ² = 5.5230.1373p < 0.0063UnclearCramér’s V = 0.336medium
Has a viewChi-squareχ² = 2.5930.4590p < 0.0063UnclearCramér’s V = 0.230small

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 9.4730.0236p < 0.0063Unclearε² = 0.197large
Net price per SFKruskal–WallisH = 6.1430.1052p < 0.0063Unclearε² = 0.128medium
Living areaKruskal–WallisH = 12.0730.0071p < 0.0063Unclearε² = 0.251large
Days on marketKruskal–WallisH = 2.6930.4428p < 0.0063Unclearε² = 0.056small
Discount from original listKruskal–WallisH = 0.4930.9207p < 0.0063Unclearε² = 0.010small
Price cut before saleChi-squareχ² = 2.0730.5584p < 0.0063UnclearCramér’s V = 0.205small
Seller paid closing costs or repairsChi-squareχ² = 4.2930.2319p < 0.0063UnclearCramér’s V = 0.296small
Has a viewChi-squareχ² = 1.2030.7524p < 0.0063UnclearCramér’s V = 0.157small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 293.00—0.5434p < 0.0063Unclearrank-biserial r = 0.110small
Net price per SFMann–Whitney UU = 247.00—0.7250p < 0.0063Unclearrank-biserial r = 0.064negligible
Living areaMann–Whitney UU = 296.00—0.5018p < 0.0063Unclearrank-biserial r = 0.121small
Year builtMann–Whitney UU = 232.00—0.4845p < 0.0063Unclearrank-biserial r = 0.121small
Days on marketMann–Whitney UU = 216.00—0.3111p < 0.0063Unclearrank-biserial r = 0.182small
Discount from original listMann–Whitney UU = 170.00—0.0462p < 0.0063Unclearrank-biserial r = 0.356medium
Price cut before saleChi-squareχ² = 3.7410.0530p < 0.0063UnclearCramér’s V = 0.276small
Seller paid closing costs or repairsChi-squareχ² = 0.1910.6657p < 0.0063UnclearCramér’s V = 0.062negligible

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 49 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.