ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Lakeline Ranch

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 · 5:21 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
27
single-family resale homes
Median net sale price
$405,000
average $411,886
Median net price per SF
$181
average $179
Median days on market
35 days
average 74 days
1. SummaryResale homes · 27 sales · October 26, 2025 – October 25, 2026

This study looks at the 27 resale homes sold in Lakeline Ranch in the 365 days to October 25, 2026. A full year is used because only 22 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 sold27 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 $374K · 7 sales$374K–$405K · 7 sales$414K–$433K · 6 salesOver $433K · 7 sales
3. Quartiles by net sale priceResale homes · 27 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.

2026-10-26T05:21:54.533824 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 6 7 27 sales Sales per group Under $374K: 7 sales (26%) $374K–$405K: 7 sales (26%) $414K–$433K: 6 sales (22%) Over $433K: 7 sales (26%)
Bottom line

3.1 Key differences

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

Under $374K$374K–$405K$414K–$433KOver $433K
Higher-priced homes Over $433K
  • Are much larger.
Lower-priced homes Under $374K
  • 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 $374K$374K–$405K$414K–$433KOver $433KReal difference?
Net price per SF$178 per SF$191 per SF$174 per SF$174 per SFunclear
Living area1,908 SFSmallest2,065 SF2,474 SF2,892 SFLargest✓ large
Year built2005200520062004unclear
Days on market35 days14 days38 days55 daysunclear
Discount from original list8.7%4.2%5.4%5.0%unclear
Price cut before sale71%43%50%14%unclear
Seller paid closing costs or repairs57%57%83%86%unclear
Has a view0%29%17%14%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

2026-10-26T05:21:54.562446 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $374K 7 sales $374K– $405K 7 sales $414K– $433K 6 sales Over $433K 7 sales $0 $100 $200 $178 $191 $174 $174 Net price per SF, average

The average is $174 per SF for homes over $433K and $178 per SF for homes under $374K. It does not move in a straight line; homes $374K–$405K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $433K are about 980 SF (52%) larger than homes under $374K

2026-10-26T05:21:54.584633 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $374K 7 sales $374K– $405K 7 sales $414K– $433K 6 sales Over $433K 7 sales 0 1,000 2,000 3,000 1,908 2,065 2,474 2,892 Living area (SF), average

The average is 2,892 SF for homes over $433K and 1,908 SF for homes under $374K. 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

2026-10-26T05:21:54.608302 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $374K 7 sales $374K– $405K 7 sales $414K– $433K 6 sales Over $433K 7 sales 2004 2005 2006 2005 2005 2006 2004 Year built: median (dot) and middle half (bar)

The median is 2004 for homes over $433K and 2005 for homes under $374K. It does not move in a straight line; homes $414K–$433K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:21:54.630814 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $374K 7 sales $374K– $405K 7 sales $414K– $433K 6 sales Over $433K 7 sales 0 20 40 60 35 14 38 55 Days on market, median

The median is 55 days for homes over $433K and 35 days for homes under $374K. It does not move in a straight line; homes over $433K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:21:54.652996 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $374K 7 sales $374K– $405K 7 sales $414K– $433K 6 sales Over $433K 7 sales 0.0% 5.0% 10.0% 8.7% 4.2% 5.4% 5.0% Discount from original list, average

The average is 5.0% for homes over $433K and 8.7% for homes under $374K. It does not move in a straight line; homes under $374K 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

2026-10-26T05:21:54.683759 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs Has a view 0% 25% 50% 75% 100% 71 57 0 43 57 29 50 83 17 14 86 14 Under $374K $374K–$405K $414K–$433K Over $433K

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

  • 14% of homes over $433K had a price cut before sale, against 71% of homes under $374K. Defined in 8.1.7.
  • 86% of homes over $433K had the seller pay closing costs or repairs, against 57% of homes under $374K. Defined in 8.1.8.
  • 14% of homes over $433K have a view, against 0% of homes under $374K. 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 $374K7 sales$374K–$405K7 sales$414K–$433K6 salesOver $433K7 salesAll27 salesReal difference?
Net sale price average$337,100$391,118$424,223$496,865$411,886by design
Net price per SF average$178$191$174$174$179unclear
Living area average1,9082,0652,4742,8922,329✓ large
Year built median20052005200620042005unclear

3.10 The numbers: selling

Under $374K7 sales$374K–$405K7 sales$414K–$433K6 salesOver $433K7 salesAll27 salesReal difference?
Days on market median3514385535unclear
Discount from original list average8.7%4.2%5.4%5.0%5.8%unclear
Price cut before sale71%43%50%14%44%unclear
Seller paid closing costs or repairs57%57%83%86%70%unclear
Has a view0%29%17%14%15%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 · 27 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.

2026-10-26T05:21:54.704718 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 6 7 27 sales Sales per group Under 2,045 SF: 7 sales (26%) 2,045–2,157 SF: 7 sales (26%) 2,177–2,585 SF: 6 sales (22%) Over 2,585 SF: 7 sales (26%)
Bottom line

4.1 Key differences

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

Under 2,045 SF2,045–2,157 SF2,177–2,585 SFOver 2,585 SF
Larger homes Over 2,585 SF
  • Sell for much more.
Smaller homes Under 2,045 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 2,045 SF2,045–2,157 SF2,177–2,585 SFOver 2,585 SFReal difference?
Net sale price$355KLowest$383K$421K$490KHighest✓ large
Net price per SF$196 per SF$182 per SF$176 per SF$163 per SFunclear
Year built2006200520052005unclear
Days on market31 days4 days32 days85 daysunclear
Discount from original list5.6%5.5%4.1%7.9%unclear
Price cut before sale57%29%50%43%unclear
Seller paid closing costs or repairs57%86%67%71%unclear
Has a view0%14%33%14%unclear

4.3 Homes over 2,585 SF sell for about $136K (38%) more than homes under 2,045 SF

2026-10-26T05:21:54.726006 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,045 SF 7 sales 2,045– 2,157 SF 7 sales 2,177– 2,585 SF 6 sales Over 2,585 SF 7 sales $0K $200K $400K $355K $383K $421K $490K Net sale price, average

The average is $490K for homes over 2,585 SF and $355K for homes under 2,045 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

2026-10-26T05:21:54.748334 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,045 SF 7 sales 2,045– 2,157 SF 7 sales 2,177– 2,585 SF 6 sales Over 2,585 SF 7 sales $0 $100 $200 $196 $182 $176 $163 Net price per SF, average

The average is $163 per SF for homes over 2,585 SF and $196 per SF for homes under 2,045 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T05:21:54.770674 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,045 SF 7 sales 2,045– 2,157 SF 7 sales 2,177– 2,585 SF 6 sales Over 2,585 SF 7 sales 2004 2005 2006 2006 2005 2005 2005 Year built: median (dot) and middle half (bar)

The median is 2005 for homes over 2,585 SF and 2006 for homes under 2,045 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T05:21:54.793718 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,045 SF 7 sales 2,045– 2,157 SF 7 sales 2,177– 2,585 SF 6 sales Over 2,585 SF 7 sales 0 50 100 31 4 32 85 Days on market, median

The median is 85 days for homes over 2,585 SF and 31 days for homes under 2,045 SF. It does not move in a straight line; homes over 2,585 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T05:21:54.815696 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,045 SF 7 sales 2,045– 2,157 SF 7 sales 2,177– 2,585 SF 6 sales Over 2,585 SF 7 sales 0.0% 2.5% 5.0% 7.5% 5.6% 5.5% 4.1% 7.9% Discount from original list, average

The average is 7.9% for homes over 2,585 SF and 5.6% for homes under 2,045 SF. It does not move in a straight line; homes over 2,585 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

2026-10-26T05:21:54.843307 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 57 0 29 86 14 50 67 33 43 71 14 Under 2,045 SF 2,045–2,157 SF 2,177–2,585 SF Over 2,585 SF

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

  • 43% of homes over 2,585 SF had a price cut before sale, against 57% of homes under 2,045 SF. Defined in 8.1.7.
  • 71% of homes over 2,585 SF had the seller pay closing costs or repairs, against 57% of homes under 2,045 SF. Defined in 8.1.8.
  • 14% of homes over 2,585 SF have a view, against 0% of homes under 2,045 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 2,045 SF7 sales2,045–2,157 SF7 sales2,177–2,585 SF6 salesOver 2,585 SF7 salesAll27 salesReal difference?
Net sale price average$354,643$382,761$421,173$490,294$411,886✓ large
Net price per SF average$196$182$176$163$179unclear
Living area average1,8072,1052,4023,0152,329by design
Year built median20062005200520052005unclear

4.10 The numbers: selling

Under 2,045 SF7 sales2,045–2,157 SF7 sales2,177–2,585 SF6 salesOver 2,585 SF7 salesAll27 salesReal difference?
Days on market median314328535unclear
Discount from original list average5.6%5.5%4.1%7.9%5.8%unclear
Price cut before sale57%29%50%43%44%unclear
Seller paid closing costs or repairs57%86%67%71%70%unclear
Has a view0%14%33%14%15%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 · 27 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.

2026-10-26T05:21:54.864252 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 10 7 3 27 sales Sales per group Before 2005: 7 sales (26%) 2005: 10 sales (37%) 2006: 7 sales (26%) After 2006: 3 sales (11%)
Bottom line: too few sales to test.

5.1 Key differences

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

5.3 Net sale price: described, not tested

2026-10-26T05:21:54.884489 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 7 sales 2005 10 sales 2006 7 sales After 2006 3 sales $0K $200K $400K $430K $396K $416K $412K Net sale price, average

The average is $412K for homes built after 2006 and $430K for homes built before 2005. It does not move in a straight line; homes built before 2005 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T05:21:54.907114 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 7 sales 2005 10 sales 2006 7 sales After 2006 3 sales $0 $50 $100 $150 $200 $172 $177 $188 $183 Net price per SF, average

The average is $183 per SF for homes built after 2006 and $172 per SF for homes built before 2005. It does not move in a straight line; homes built 2006 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T05:21:54.928503 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 7 sales 2005 10 sales 2006 7 sales After 2006 3 sales 0 1,000 2,000 3,000 2,546 2,256 2,238 2,282 Living area (SF), average

The average is 2,282 SF for homes built after 2006 and 2,546 SF for homes built before 2005. It does not move in a straight line; homes built before 2005 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T05:21:54.949533 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 7 sales 2005 10 sales 2006 7 sales After 2006 3 sales 0 50 100 150 35 26 17 163 Days on market, median

The median is 163 days for homes built after 2006 and 35 days for homes built before 2005. It does not move in a straight line; homes built after 2006 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T05:21:54.972606 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 2005 7 sales 2005 10 sales 2006 7 sales After 2006 3 sales 0.0% 2.0% 4.0% 6.0% 8.0% 6.2% 6.5% 3.9% 7.3% Discount from original list, average

The average is 7.3% for homes built after 2006 and 6.2% for homes built before 2005. It does not move in a straight line; homes built after 2006 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T05:21:54.998623 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% 43 71 14 50 60 20 29 86 14 67 67 0 Before 2005 2005 2006 After 2006

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

  • 67% of homes built after 2006 had a price cut before sale, against 43% of homes built before 2005. Defined in 8.1.7.
  • 67% of homes built after 2006 had the seller pay closing costs or repairs, against 71% of homes built before 2005. Defined in 8.1.8.
  • 0% of homes built after 2006 have a view, against 14% of homes built before 2005. Defined in 8.1.9.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.
Has a view: Not tested: too few sales.

5.9 The numbers: price and size

Before 20057 sales200510 sales20067 salesAfter 20063 salesAll27 sales
Net sale price average$430,300$396,182$415,828$412,065$411,886
Net price per SF average$172$177$188$183$179
Living area average2,5462,2562,2382,2822,329
Year built median20042005200620072005

5.10 The numbers: selling

Before 20057 sales200510 sales20067 salesAfter 20063 salesAll27 sales
Days on market median35261716335
Discount from original list average6.2%6.5%3.9%7.3%5.8%
Price cut before sale43%50%29%67%44%
Seller paid closing costs or repairs71%60%86%67%70%
Has a view14%20%14%0%15%

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 · 27 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. 1 sales whose MLS view entry is only “See Remarks” are left out.

2026-10-26T05:21:55.017425 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 22 26 sales Sales per group View: 4 sales (15%) No view: 22 sales (85%)
Bottom line: too few sales to test.

6.1 Key differences

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

6.3 Net sale price: described, not tested

2026-10-26T05:21:55.033416 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 22 sales $0K $200K $400K $428K $411K Net sale price, average

The average is $428K for homes with a view and $411K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T05:21:55.051328 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 22 sales $0 $50 $100 $150 $200 $172 $181 Net price per SF, average

The average is $172 per SF for homes with a view and $181 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T05:21:55.070018 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 22 sales 0 1,000 2,000 3,000 2,502 2,305 Living area (SF), average

The average is 2,502 SF for homes with a view and 2,305 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T05:21:55.153679 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 22 sales 2005 2006 2005 2005 Year built: median (dot) and middle half (bar)

The median is 2005 for homes with a view and 2005 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T05:21:55.171385 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 22 sales 0 10 20 30 40 38 39 Days on market, median

The median is 38 days for homes with a view and 39 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-26T05:21:55.190047 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 22 sales 0.0% 2.0% 4.0% 6.0% 3.3% 6.2% Discount from original list, average

The average is 3.3% for homes with a view and 6.2% for homes without a view. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T05:21:55.208811 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 25 75 45 73 View No view

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

  • 25% of homes with a view had a price cut before sale, against 45% of homes without a view. Defined in 8.1.7.
  • 75% of homes with a view had the seller pay closing costs or repairs, against 73% of homes without a view. Defined in 8.1.8.
Price cut before sale: Not tested: too few sales.
Seller paid closing costs or repairs: Not tested: too few sales.

6.10 The numbers: price and size

View4 salesNo view22 salesAll26 sales
Net sale price average$428,350$411,024$413,689
Net price per SF average$172$181$180
Living area average2,5022,3052,335
Year built median200520052005

6.11 The numbers: selling

View4 salesNo view22 salesAll26 sales
Days on market median383939
Discount from original list average3.3%6.2%5.8%
Price cut before sale25%45%42%
Seller paid closing costs or repairs75%73%73%

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

7. New constructionBasic statistics · 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 Lakeline Ranch.

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
27 resale sales. Average $411,886; median $405,000; standard deviation $65,056; middle half (25th–75th percentile) $372,000–$439,250; lowest $293,000, highest $568,000. 19 sales had a seller payment; their median payment was $5,300.

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
27 resale sales. Average $179; median $181; standard deviation $19; middle half (25th–75th percentile) $167–$194; lowest $140, highest $215.

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
27 resale sales. Average 2,329; median 2,157; standard deviation 490; middle half (25th–75th percentile) 1,979–2,632; lowest 1,577, highest 3,386.

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
27 resale sales. Average 2005; median 2005; standard deviation 1; middle half (25th–75th percentile) 2004–2006; lowest 2003, highest 2008.

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
27 resale sales. Average 74; median 35; standard deviation 98; middle half (25th–75th percentile) 12–78; lowest 0, highest 414. 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
27 resale sales. Average 5.8%; median 5.4%; standard deviation 5.8%; middle half (25th–75th percentile) 1.7%–7.2%; lowest 0.0%, highest 23.1%. 0 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
12 of 27 resale sales (44.4%).

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
19 of 27 resale sales (70.4%).

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
4 sales with a view, 22 without, 1 unclassified. Most common View entries: None 17, Neighborhood 6, Trees/Woods 2, Park/Greenbelt 2, 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 “lakeline ranch”, “lakeline ranch sub” (case-insensitive). A record is kept when its subdivision name belongs to the Lakeline Ranch family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 32 closed Lakeline Ranch records over the prior year, in ZIP 78641. 11 subdivision spellings kept: Lakeline Ranch Sub (9); Lakeline Ranch Ph 05 (5); Lakeline Ranch Ph 02 (4); Lakeline Ranch Ph 04 Amd (3); Lakeline Ranch Ph 07 Amd (3); Lakeline Ranch (3); Lakeline Ranch Ph 3A (1); Lakeline Ranch Ph 7 (1); Lakeline Ranch Ph 06 (1); Lakeline Ranch ph 04 Amd (1); LAKELINE RANCH SUB (1). 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 22 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
27 single-family sales in the window: 27 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
27 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
4 sale(s) other than single-family homes (condo, townhome and similar); 1 sale(s) with concessions above 10% of price

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 $374K”.
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 $374K: $293,000–$370,000 (7 sales); $374K–$405K: $373,999–$405,000 (7 sales); $414K–$433K: $413,540–$433,000 (6 sales); Over $433K: $445,500–$568,000 (7 sales)
Quartiles by living area: Under 2,045 SF: 1,577–1,913 SF (7 sales); 2,045–2,157 SF: 2,045–2,157 SF (7 sales); 2,177–2,585 SF: 2,177–2,585 SF (6 sales); Over 2,585 SF: 2,678–3,386 SF (7 sales)
Quartiles by year built: Before 2005: 2003–2004 (7 sales); 2005: 2005–2005 (10 sales); 2006: 2006–2006 (7 sales); After 2006: 2007–2008 (3 sales)
View and no view: View: MLS lists a view (4 sales); No view: None or Neighborhood (22 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 $411,886, median $405,000. Days on market: average 74, median 35: the average is pulled up by a few long listings.

8.2.7 Kruskal–Wallis test

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

8.2.8 Mann–Whitney U test

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

8.2.9 Chi-square test

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

8.2.10 Real difference (significance)

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

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
2 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 = 3.0130.3901p < 0.0063Unclearε² = 0.116medium
Living areaKruskal–WallisH = 17.1030.0007p < 0.0063Yesε² = 0.658large
Year builtKruskal–WallisH = 3.8530.2786p < 0.0063Unclearε² = 0.148large
Days on marketKruskal–WallisH = 2.1530.5410p < 0.0063Unclearε² = 0.083medium
Discount from original listKruskal–WallisH = 5.2330.1557p < 0.0063Unclearε² = 0.201large
Price cut before saleChi-squareχ² = 4.7230.1931p < 0.0063UnclearCramér’s V = 0.418medium
Seller paid closing costs or repairsChi-squareχ² = 2.4530.4846p < 0.0063UnclearCramér’s V = 0.301medium
Has a viewChi-squareχ² = 2.2830.5154p < 0.0063UnclearCramér’s V = 0.291small

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 17.8730.0005p < 0.0063Yesε² = 0.687large
Net price per SFKruskal–WallisH = 10.6130.0140p < 0.0063Unclearε² = 0.408large
Year builtKruskal–WallisH = 0.3830.9453p < 0.0063Unclearε² = 0.014small
Days on marketKruskal–WallisH = 9.9630.0189p < 0.0063Unclearε² = 0.383large
Discount from original listKruskal–WallisH = 0.4030.9404p < 0.0063Unclearε² = 0.015small
Price cut before saleChi-squareχ² = 1.2530.7402p < 0.0063UnclearCramér’s V = 0.215small
Seller paid closing costs or repairsChi-squareχ² = 1.4230.7006p < 0.0063UnclearCramér’s V = 0.229small
Has a viewChi-squareχ² = 2.8530.4152p < 0.0063UnclearCramér’s V = 0.325medium

8.3.3 Quartiles by year built

Too few sales in a group to test.

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); 4 sale(s) other than single-family homes (condo, townhome and similar); 1 sale(s) with concessions above 10% of price. 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 27 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.