ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Horseshoe Bay Proper

Horseshoe Bay, TX 78657
Resale homes · closed Nov 6 – Nov 5, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
November 6, 2026 · 7:40 AM CST
MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
31
single-family resale homes
Median net sale price
$586,000
average $1,218,234
Median net price per SF
$241
average $334
Median days on market
89 days
average 132 days
1. SummaryResale homes · 31 sales · November 6, 2025 – November 5, 2026

This study looks at the 31 resale homes sold in Horseshoe Bay Proper in the 365 days to November 5, 2026. A full year is used because only 17 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 sold31 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 $510K · 8 sales$510K–$586K · 8 sales$634K–$808K · 7 salesOver $808K · 8 sales
3. Quartiles by net sale priceResale homes · 31 sales · November 6, 2025 – November 5, 2026

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

2026-11-06T07:41:02.844203 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 7 8 31 sales Sales per group Under $510K: 8 sales (26%) $510K–$586K: 8 sales (26%) $634K–$808K: 7 sales (23%) Over $808K: 8 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 $510K$510K–$586K$634K–$808KOver $808K
Higher-priced homes Over $808K
  • Sell for more per square foot.
  • Are much larger.
Lower-priced homes Under $510K
  • Sell for less per square foot.
  • 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 $510K$510K–$586K$634K–$808KOver $808KReal difference?
Net price per SF$199 per SFLowest$218 per SF$241 per SF$665 per SFHighest✓ large
Living area2,046 SFSmallest2,514 SF3,018 SF4,018 SFLargest✓ large
Year built1998198419951990unclear
Days on market89 days104 days102 days50 daysunclear
Discount from original list11.5%11.0%9.4%9.8%unclear
Price cut before sale50%50%43%38%unclear
Seller paid closing costs or repairs25%25%71%50%unclear
Has a view75%88%100%100%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 $808K sell for about $465 per SF (233%) more than homes under $510K

2026-11-06T07:41:02.872991 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $510K 8 sales $510K– $586K 8 sales $634K– $808K 7 sales Over $808K 8 sales $0 $200 $400 $600 $199 $218 $241 $665 Net price per SF, average

The average is $665 per SF for homes over $808K and $199 per SF for homes under $510K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $808K are about 1,970 SF (96%) larger than homes under $510K

2026-11-06T07:41:02.897664 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $510K 8 sales $510K– $586K 8 sales $634K– $808K 7 sales Over $808K 8 sales 0 2,000 4,000 2,046 2,514 3,018 4,018 Living area (SF), average

The average is 4,018 SF for homes over $808K and 2,046 SF for homes under $510K. 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

2026-11-06T07:41:02.923501 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $510K 8 sales $510K– $586K 8 sales $634K– $808K 7 sales Over $808K 8 sales 1986 1992 1998 2004 1998 1984 1995 1990 Year built: median (dot) and middle half (bar)

The median is 1990 for homes over $808K and 1998 for homes under $510K. It does not move in a straight line; homes under $510K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-11-06T07:41:02.946830 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $510K 8 sales $510K– $586K 8 sales $634K– $808K 7 sales Over $808K 8 sales 0 50 100 89 104 102 50 Days on market, median

The median is 50 days for homes over $808K and 89 days for homes under $510K. It does not move in a straight line; homes $510K–$586K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-11-06T07:41:02.971327 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $510K 8 sales $510K– $586K 8 sales $634K– $808K 7 sales Over $808K 8 sales 0.0% 5.0% 10.0% 11.5% 11.0% 9.4% 9.8% Discount from original list, average

The average is 9.8% for homes over $808K and 11.5% for homes under $510K. It does not move in a straight line; homes under $510K are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-06T07:41:03.002811 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% 50 25 75 50 25 88 43 71 100 38 50 100 Under $510K $510K–$586K $634K–$808K Over $808K

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

  • 38% of homes over $808K had a price cut before sale, against 50% of homes under $510K. Defined in 8.1.7.
  • 50% of homes over $808K had the seller pay closing costs or repairs, against 25% of homes under $510K. Defined in 8.1.8.
  • 100% of homes over $808K have a view, against 75% of homes under $510K. 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 $510K8 sales$510K–$586K8 sales$634K–$808K7 salesOver $808K8 salesAll31 salesReal difference?
Net sale price average$391,125$544,875$712,929$3,160,846$1,218,234by design
Net price per SF average$199$218$241$665$334✓ large
Living area average2,0462,5143,0184,0182,895✓ large
Year built median19981984199519901991unclear

3.10 The numbers: selling

Under $510K8 sales$510K–$586K8 sales$634K–$808K7 salesOver $808K8 salesAll31 salesReal difference?
Days on market median891041025089unclear
Discount from original list average11.5%11.0%9.4%9.8%10.5%unclear
Price cut before sale50%50%43%38%45%unclear
Seller paid closing costs or repairs25%25%71%50%42%unclear
Has a view75%88%100%100%90%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 · 31 sales · November 6, 2025 – November 5, 2026

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

2026-11-06T07:41:03.024703 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 8 7 8 31 sales Sales per group Under 2,324 SF: 8 sales (26%) 2,324–2,594 SF: 8 sales (26%) 2,673–3,068 SF: 7 sales (23%) Over 3,068 SF: 8 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 2,324 SF2,324–2,594 SF2,673–3,068 SFOver 3,068 SF
Larger homes Over 3,068 SF
  • Sell for much more.
Smaller homes Under 2,324 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 2,324 SF2,324–2,594 SF2,673–3,068 SFOver 3,068 SFReal difference?
Net sale price$421KLowest$652K$781K$2.96MHighest✓ large
Net price per SF$217 per SF$267 per SF$274 per SF$569 per SFunclear
Year built2002198419931994unclear
Days on market92 days125 days102 days44 daysunclear
Discount from original list9.2%9.8%12.9%10.3%unclear
Price cut before sale50%50%29%50%unclear
Seller paid closing costs or repairs25%38%71%38%unclear
Has a view62%100%100%100%unclear

4.3 Homes over 3,068 SF sell for about $2.54M (605%) more than homes under 2,324 SF

2026-11-06T07:41:03.046201 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,324 SF 8 sales 2,324– 2,594 SF 8 sales 2,673– 3,068 SF 7 sales Over 3,068 SF 8 sales $0K $1.00M $2.00M $3.00M $421K $652K $781K $2.96M Net sale price, average

The average is $2.96M for homes over 3,068 SF and $421K for homes under 2,324 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

2026-11-06T07:41:03.070592 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,324 SF 8 sales 2,324– 2,594 SF 8 sales 2,673– 3,068 SF 7 sales Over 3,068 SF 8 sales $0 $200 $400 $600 $217 $267 $274 $569 Net price per SF, average

The average is $569 per SF for homes over 3,068 SF and $217 per SF for homes under 2,324 SF. It rises 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

2026-11-06T07:41:03.095873 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,324 SF 8 sales 2,324– 2,594 SF 8 sales 2,673– 3,068 SF 7 sales Over 3,068 SF 8 sales 1986 1992 1998 2004 2002 1984 1993 1994 Year built: median (dot) and middle half (bar)

The median is 1994 for homes over 3,068 SF and 2002 for homes under 2,324 SF. It does not move in a straight line; homes under 2,324 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-11-06T07:41:03.121554 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,324 SF 8 sales 2,324– 2,594 SF 8 sales 2,673– 3,068 SF 7 sales Over 3,068 SF 8 sales 0 50 100 150 92 125 102 44 Days on market, median

The median is 44 days for homes over 3,068 SF and 92 days for homes under 2,324 SF. It does not move in a straight line; homes 2,324–2,594 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-11-06T07:41:03.144551 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,324 SF 8 sales 2,324– 2,594 SF 8 sales 2,673– 3,068 SF 7 sales Over 3,068 SF 8 sales 0.0% 5.0% 10.0% 15.0% 9.2% 9.8% 12.9% 10.3% Discount from original list, average

The average is 10.3% for homes over 3,068 SF and 9.2% for homes under 2,324 SF. It does not move in a straight line; homes 2,673–3,068 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-06T07:41:03.171581 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% 50 25 62 50 38 100 29 71 100 50 38 100 Under 2,324 SF 2,324–2,594 SF 2,673–3,068 SF Over 3,068 SF

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

  • 50% of homes over 3,068 SF had a price cut before sale, against 50% of homes under 2,324 SF. Defined in 8.1.7.
  • 38% of homes over 3,068 SF had the seller pay closing costs or repairs, against 25% of homes under 2,324 SF. Defined in 8.1.8.
  • 100% of homes over 3,068 SF have a view, against 62% of homes under 2,324 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 2,324 SF8 sales2,324–2,594 SF8 sales2,673–3,068 SF7 salesOver 3,068 SF8 salesAll31 salesReal difference?
Net sale price average$420,625$652,375$781,071$2,964,221$1,218,234✓ large
Net price per SF average$217$267$274$569$334unclear
Living area average1,9342,4712,8634,3082,895by design
Year built median20021984199319941991unclear

4.10 The numbers: selling

Under 2,324 SF8 sales2,324–2,594 SF8 sales2,673–3,068 SF7 salesOver 3,068 SF8 salesAll31 salesReal difference?
Days on market median921251024489unclear
Discount from original list average9.2%9.8%12.9%10.3%10.5%unclear
Price cut before sale50%50%29%50%45%unclear
Seller paid closing costs or repairs25%38%71%38%42%unclear
Has a view62%100%100%100%90%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 · 31 sales · November 6, 2025 – November 5, 2026

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

2026-11-06T07:41:03.194101 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 9 8 6 8 31 sales Sales per group Before 1985: 9 sales (29%) 1985–1991: 8 sales (26%) 1993–1998: 6 sales (19%) After 1998: 8 sales (26%)
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 19851985–19911993–1998After 1998Real difference?
Net sale price$549K$977K$1.45M$2.04Munclear
Net price per SF$214 per SF$352 per SF$411 per SF$392 per SFunclear
Living area2,536 SF2,693 SF3,180 SF3,288 SFunclear
Days on market50 days86 days228 days86 daysunclear
Discount from original list12.5%10.6%11.2%7.5%unclear
Price cut before sale33%50%67%38%unclear
Seller paid closing costs or repairs22%50%67%38%unclear
Has a view78%100%100%88%unclear

5.3 Net sale price: no clear difference

2026-11-06T07:41:03.215288 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 9 sales 1985– 1991 8 sales 1993– 1998 6 sales After 1998 8 sales $0K $1.00M $2.00M $549K $977K $1.45M $2.04M Net sale price, average

The average is $2.04M for homes built after 1998 and $549K for homes built before 1985. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-11-06T07:41:03.237991 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 9 sales 1985– 1991 8 sales 1993– 1998 6 sales After 1998 8 sales $0 $200 $400 $214 $352 $411 $392 Net price per SF, average

The average is $392 per SF for homes built after 1998 and $214 per SF for homes built before 1985. It does not move in a straight line; homes built 1993–1998 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-11-06T07:41:03.261983 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 9 sales 1985– 1991 8 sales 1993– 1998 6 sales After 1998 8 sales 0 1,000 2,000 3,000 2,536 2,693 3,180 3,288 Living area (SF), average

The average is 3,288 SF for homes built after 1998 and 2,536 SF for homes built before 1985. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-11-06T07:41:03.285382 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 9 sales 1985– 1991 8 sales 1993– 1998 6 sales After 1998 8 sales 0 100 200 50 86 228 86 Days on market, median

The median is 86 days for homes built after 1998 and 50 days for homes built before 1985. It does not move in a straight line; homes built 1993–1998 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-11-06T07:41:03.310410 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1985 9 sales 1985– 1991 8 sales 1993– 1998 6 sales After 1998 8 sales 0.0% 5.0% 10.0% 12.5% 10.6% 11.2% 7.5% Discount from original list, average

The average is 7.5% for homes built after 1998 and 12.5% for homes built before 1985. It does not move in a straight line; homes built before 1985 are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-11-06T07:41:03.338702 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% 33 22 78 50 50 100 67 67 100 38 38 88 Before 1985 1985–1991 1993–1998 After 1998

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

  • 38% of homes built after 1998 had a price cut before sale, against 33% of homes built before 1985. Defined in 8.1.7.
  • 38% of homes built after 1998 had the seller pay closing costs or repairs, against 22% of homes built before 1985. Defined in 8.1.8.
  • 88% of homes built after 1998 have a view, against 78% of homes built before 1985. 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 19859 sales1985–19918 sales1993–19986 salesAfter 19988 salesAll31 salesReal difference?
Net sale price average$548,700$976,688$1,447,411$2,041,125$1,218,234unclear
Net price per SF average$214$352$411$392$334unclear
Living area average2,5362,6933,1803,2882,895unclear
Year built median19821988199620141991by design

5.10 The numbers: selling

Before 19859 sales1985–19918 sales1993–19986 salesAfter 19988 salesAll31 salesReal difference?
Days on market median50862288689unclear
Discount from original list average12.5%10.6%11.2%7.5%10.5%unclear
Price cut before sale33%50%67%38%45%unclear
Seller paid closing costs or repairs22%50%67%38%42%unclear
Has a view78%100%100%88%90%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 · 31 sales · November 6, 2025 – November 5, 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.

2026-11-06T07:41:03.359135 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 28 3 31 sales Sales per group View: 28 sales (90%) No view: 3 sales (10%)
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

2026-11-06T07:41:03.377391 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 3 sales $0K $500K $1.00M $1.50M $1.31M $393K Net sale price, average

The average is $1.31M for homes with a view and $393K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-11-06T07:41:03.397313 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 3 sales $0 $100 $200 $300 $400 $347 $208 Net price per SF, average

The average is $347 per SF for homes with a view and $208 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-11-06T07:41:03.416582 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 3 sales 0 1,000 2,000 3,000 3,007 1,855 Living area (SF), average

The average is 3,007 SF for homes with a view and 1,855 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-11-06T07:41:03.464339 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 3 sales 1980 1985 1990 1995 2000 1991 1984 Year built: median (dot) and middle half (bar)

The median is 1991 for homes with a view and 1984 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-11-06T07:41:03.484098 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 3 sales 0 25 50 75 100 89 89 Days on market, median

The median is 89 days for homes with a view and 89 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

2026-11-06T07:41:03.503372 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 28 sales No view 3 sales 0.0% 5.0% 10.0% 10.6% 9.3% Discount from original list, average

The average is 10.6% for homes with a view and 9.3% 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

2026-11-06T07:41:03.522089 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 43 46 67 0 View No view

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

  • 43% of homes with a view had a price cut before sale, against 67% of homes without a view. Defined in 8.1.7.
  • 46% of homes with a view had the seller pay closing costs or repairs, against 0% 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

View28 salesNo view3 salesAll31 sales
Net sale price average$1,306,617$393,333$1,218,234
Net price per SF average$347$208$334
Living area average3,0071,8552,895
Year built median199119841991

6.11 The numbers: selling

View28 salesNo view3 salesAll31 sales
Days on market median898989
Discount from original list average10.6%9.3%10.5%
Price cut before sale43%67%45%
Seller paid closing costs or repairs46%0%42%

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 · 1 sales · November 6, 2025 – November 5, 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: 1 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 Horseshoe Bay Proper.
MeasureAverageMedian
Sales1
Net sale price$580,000$580,000
Net price per SF$274$274
Living area (SF)2,1202,120
Days on market112112
Discount from original list9.4%9.4%
Price cut before sale100% of sales
Seller paid closing costs or repairs0% of sales
Year built2025–2025

Same definitions as the rest of the study (section 8). New construction = NewConstructionYN true, or PropertyCondition “New Construction” or “Under Construction”.

8. AppendixMeasures, methods and tests

Each measure and method three ways: in plain words, as statistics, and with the data from this study.

8.1 Measures

8.1.1 Net sale price

In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
31 resale sales. Average $1,218,234; median $586,000; standard deviation $2,078,460; middle half (25th–75th percentile) $487,500–$835,400; lowest $270,000, highest $11,300,000. 13 sales had a seller payment; their median payment was $6,000.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
31 resale sales. Average $334; median $241; standard deviation $265; middle half (25th–75th percentile) $205–$282; lowest $99, highest $1,123.

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
31 resale sales. Average 2,895; median 2,594; standard deviation 1,470; middle half (25th–75th percentile) 2,301–3,103; lowest 1,512, highest 10,065.

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
31 resale sales. Average 1994; median 1991; standard deviation 13; middle half (25th–75th percentile) 1984–1998; lowest 1975, highest 2020.

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
31 resale sales. Average 132; median 89; standard deviation 133; middle half (25th–75th percentile) 36–200; lowest 4, highest 535. 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
31 resale sales. Average 10.5%; median 9.3%; standard deviation 7.0%; middle half (25th–75th percentile) 5.4%–14.6%; lowest 0.0%, highest 26.1%. 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
14 of 31 resale sales (45.2%).

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
13 of 31 resale sales (41.9%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
28 sales with a view, 3 without, 0 unclassified. Most common View entries: Hill Country 17, Golf Course 12, Lake 11, Panoramic 6, Trees/Woods 3, None 3, River 2, Water 2.

8.2 Methods

8.2.1 Data source

In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-06 13:30 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Horseshoe Bay, SubdivisionName contains any of “horseshoe bay proper” (case-insensitive). A record is kept when its subdivision name belongs to the Horseshoe Bay Proper family, the same rule comparable sales use.
The data
Pulled November 6, 2026: 37 closed Horseshoe Bay Proper records over the prior year, in ZIP 78657. 1 subdivision spellings kept: Horseshoe Bay Proper (37). 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 17 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 6, 2025 to November 5, 2026 inclusive.
The data
32 single-family sales in the window: 31 resale, 1 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
31 resale; 1 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
5 sale(s) other than single-family homes (condo, townhome and similar)

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 $510K”.
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 $510K: $270,000–$465,000 (8 sales); $510K–$586K: $510,000–$586,000 (8 sales); $634K–$808K: $634,000–$807,500 (7 sales); Over $808K: $863,300–$11,300,000 (8 sales)
Quartiles by living area: Under 2,324 SF: 1,512–2,278 SF (8 sales); 2,324–2,594 SF: 2,324–2,594 SF (8 sales); 2,673–3,068 SF: 2,673–3,068 SF (7 sales); Over 3,068 SF: 3,138–10,065 SF (8 sales)
Quartiles by year built: Before 1985: 1975–1984 (9 sales); 1985–1991: 1985–1991 (8 sales); 1993–1998: 1993–1998 (6 sales); After 1998: 1999–2020 (8 sales)
View and no view: View: MLS lists a view (28 sales); No view: None or Neighborhood (3 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 $1,218,234, median $586,000. Days on market: average 132, median 89: 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

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 = 18.1830.0004p < 0.0063Yesε² = 0.606large
Living areaKruskal–WallisH = 16.7630.0008p < 0.0063Yesε² = 0.559large
Year builtKruskal–WallisH = 4.3430.2267p < 0.0063Unclearε² = 0.145large
Days on marketKruskal–WallisH = 1.1030.7770p < 0.0063Unclearε² = 0.037small
Discount from original listKruskal–WallisH = 0.1930.9788p < 0.0063Unclearε² = 0.006negligible
Price cut before saleChi-squareχ² = 0.3630.9492p < 0.0063UnclearCramér’s V = 0.107small
Seller paid closing costs or repairsChi-squareχ² = 4.6030.2036p < 0.0063UnclearCramér’s V = 0.385medium
Has a viewChi-squareχ² = 3.8330.2805p < 0.0063UnclearCramér’s V = 0.351medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 15.9630.0012p < 0.0063Yesε² = 0.532large
Net price per SFKruskal–WallisH = 3.8230.2816p < 0.0063Unclearε² = 0.127medium
Year builtKruskal–WallisH = 5.7630.1241p < 0.0063Unclearε² = 0.192large
Days on marketKruskal–WallisH = 1.4930.6843p < 0.0063Unclearε² = 0.050small
Discount from original listKruskal–WallisH = 1.1430.7676p < 0.0063Unclearε² = 0.038small
Price cut before saleChi-squareχ² = 1.0030.8001p < 0.0063UnclearCramér’s V = 0.180small
Seller paid closing costs or repairsChi-squareχ² = 3.5730.3115p < 0.0063UnclearCramér’s V = 0.339medium
Has a viewChi-squareχ² = 9.5530.0228p < 0.0063UnclearCramér’s V = 0.555large

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 6.1230.1058p < 0.0063Unclearε² = 0.204large
Net price per SFKruskal–WallisH = 6.5330.0884p < 0.0063Unclearε² = 0.218large
Living areaKruskal–WallisH = 2.8730.4114p < 0.0063Unclearε² = 0.096medium
Days on marketKruskal–WallisH = 4.8430.1837p < 0.0063Unclearε² = 0.161large
Discount from original listKruskal–WallisH = 2.4530.4835p < 0.0063Unclearε² = 0.082medium
Price cut before saleChi-squareχ² = 1.8930.5947p < 0.0063UnclearCramér’s V = 0.247small
Seller paid closing costs or repairsChi-squareχ² = 3.2230.3587p < 0.0063UnclearCramér’s V = 0.322medium
Has a viewChi-squareχ² = 3.1930.3628p < 0.0063UnclearCramér’s V = 0.321medium

8.3.4 View and no view

Too few sales in a group to test.

8.4 Data notes

Left out of the analysis: 1 new-construction sales (basic statistics only, section 7); 5 sale(s) other than single-family homes (condo, townhome and similar). 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 31 closed MLS resale sales; the 1 new-construction sales appear only in their own section, as basic statistics. Sale and listing data: ABOR MLS via secure APIs, pulled November 6, 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.