ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Horseshoe Bay Proper

Horseshoe Bay, TX 78657
Resale homes · closed Oct 28 – Oct 27, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 28, 2026 · 7:49 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
29
single-family resale homes
Median net sale price
$634,000
average $1,270,009
Median net price per SF
$241
average $342
Median days on market
89 days
average 134 days
1. SummaryResale homes · 29 sales · October 28, 2025 – October 27, 2026

This study looks at the 29 resale homes sold in Horseshoe Bay Proper in the 365 days to October 27, 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 sold29 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 $515K · 7 sales$515K–$586K · 7 sales$634K–$863K · 8 salesOver $863K · 7 sales
3. Quartiles by net sale priceResale homes · 29 sales · October 28, 2025 – October 27, 2026

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

2026-10-28T07:49:49.123936 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 8 7 29 sales Sales per group Under $515K: 7 sales (24%) $515K–$586K: 7 sales (24%) $634K–$863K: 8 sales (28%) Over $863K: 7 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 $515K$515K–$586K$634K–$863KOver $863K
Higher-priced homes Over $863K
  • Sell for more per square foot.
  • Are much larger.
Lower-priced homes Under $515K
  • 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 $515K$515K–$586K$634K–$863KOver $863KReal difference?
Net price per SF$191 per SFLowest$224 per SF$244 per SF$721 per SFHighest✓ large
Living area2,101 SFSmallest2,466 SF3,041 SF4,135 SFLargest✓ large
Year built1991198419941993unclear
Days on market84 days118 days90 days64 daysunclear
Discount from original list11.6%9.7%9.3%10.0%unclear
Price cut before sale43%57%38%43%unclear
Seller paid closing costs or repairs29%29%62%57%unclear
Has a view71%86%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 $863K sell for about $530 per SF (277%) more than homes under $515K

2026-10-28T07:49:49.151962 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $515K 7 sales $515K– $586K 7 sales $634K– $863K 8 sales Over $863K 7 sales $0 $250 $500 $750 $191 $224 $244 $721 Net price per SF, average

The average is $721 per SF for homes over $863K and $191 per SF for homes under $515K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

✓ Real difference · large

3.4 Homes over $863K are about 2,030 SF (97%) larger than homes under $515K

2026-10-28T07:49:49.173927 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $515K 7 sales $515K– $586K 7 sales $634K– $863K 8 sales Over $863K 7 sales 0 2,000 4,000 2,101 2,466 3,041 4,135 Living area (SF), average

The average is 4,135 SF for homes over $863K and 2,101 SF for homes under $515K. 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

2026-10-28T07:49:49.197385 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $515K 7 sales $515K– $586K 7 sales $634K– $863K 8 sales Over $863K 7 sales 1984 1992 2000 2008 1991 1984 1994 1993 Year built: median (dot) and middle half (bar)

The median is 1993 for homes over $863K and 1991 for homes under $515K. It does not move in a straight line; homes $634K–$863K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-28T07:49:49.220206 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $515K 7 sales $515K– $586K 7 sales $634K– $863K 8 sales Over $863K 7 sales 0 50 100 84 118 90 64 Days on market, median

The median is 64 days for homes over $863K and 84 days for homes under $515K. It does not move in a straight line; homes $515K–$586K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-28T07:49:49.241902 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $515K 7 sales $515K– $586K 7 sales $634K– $863K 8 sales Over $863K 7 sales 0.0% 5.0% 10.0% 11.6% 9.7% 9.3% 10.0% Discount from original list, average

The average is 10.0% for homes over $863K and 11.6% for homes under $515K. It does not move in a straight line; homes under $515K 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

2026-10-28T07:49:49.271018 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 29 71 57 29 86 38 62 100 43 57 100 Under $515K $515K–$586K $634K–$863K Over $863K

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

  • 43% of homes over $863K had a price cut before sale, against 43% of homes under $515K. Defined in 8.1.7.
  • 57% of homes over $863K had the seller pay closing costs or repairs, against 29% of homes under $515K. Defined in 8.1.8.
  • 100% of homes over $863K have a view, against 71% of homes under $515K. 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 $515K7 sales$515K–$586K7 sales$634K–$863K8 salesOver $863K7 salesAll29 salesReal difference?
Net sale price average$386,286$549,857$731,725$3,489,067$1,270,009by design
Net price per SF average$191$224$244$721$342✓ large
Living area average2,1012,4663,0414,1352,939✓ large
Year built median19911984199419931991unclear

3.10 The numbers: selling

Under $515K7 sales$515K–$586K7 sales$634K–$863K8 salesOver $863K7 salesAll29 salesReal difference?
Days on market median84118906489unclear
Discount from original list average11.6%9.7%9.3%10.0%10.1%unclear
Price cut before sale43%57%38%43%45%unclear
Seller paid closing costs or repairs29%29%62%57%45%unclear
Has a view71%86%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 · 29 sales · October 28, 2025 – October 27, 2026

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

2026-10-28T07:49:49.291007 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 8 7 29 sales Sales per group Under 2,324 SF: 7 sales (24%) 2,324–2,560 SF: 7 sales (24%) 2,594–3,138 SF: 8 sales (28%) Over 3,138 SF: 7 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 2,324 SF2,324–2,560 SF2,594–3,138 SFOver 3,138 SF
Larger homes Over 3,138 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 SF2,324–2,560 SF2,594–3,138 SFOver 3,138 SFReal difference?
Net sale price$420KLowest$672K$1.08M$2.93MHighest✓ large
Net price per SF$212 per SF$277 per SF$370 per SF$505 per SFunclear
Year built1999198519901997unclear
Days on market89 days132 days83 days50 daysunclear
Discount from original list9.0%10.3%9.9%11.3%unclear
Price cut before sale43%57%25%57%unclear
Seller paid closing costs or repairs29%43%62%43%unclear
Has a view57%100%100%100%unclear

4.3 Homes over 3,138 SF sell for about $2.51M (598%) more than homes under 2,324 SF

2026-10-28T07:49:49.311217 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,324 SF 7 sales 2,324– 2,560 SF 7 sales 2,594– 3,138 SF 8 sales Over 3,138 SF 7 sales $0K $1.00M $2.00M $3.00M $420K $672K $1.08M $2.93M Net sale price, average

The average is $2.93M for homes over 3,138 SF and $420K 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

2026-10-28T07:49:49.333534 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,324 SF 7 sales 2,324– 2,560 SF 7 sales 2,594– 3,138 SF 8 sales Over 3,138 SF 7 sales $0 $200 $400 $600 $212 $277 $370 $505 Net price per SF, average

The average is $505 per SF for homes over 3,138 SF and $212 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

2026-10-28T07:49:49.356989 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,324 SF 7 sales 2,324– 2,560 SF 7 sales 2,594– 3,138 SF 8 sales Over 3,138 SF 7 sales 1984 1992 2000 2008 1999 1985 1990 1997 Year built: median (dot) and middle half (bar)

The median is 1997 for homes over 3,138 SF and 1999 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

2026-10-28T07:49:49.379279 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,324 SF 7 sales 2,324– 2,560 SF 7 sales 2,594– 3,138 SF 8 sales Over 3,138 SF 7 sales 0 50 100 150 89 132 83 50 Days on market, median

The median is 50 days for homes over 3,138 SF and 89 days for homes under 2,324 SF. It does not move in a straight line; homes 2,324–2,560 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-28T07:49:49.401361 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,324 SF 7 sales 2,324– 2,560 SF 7 sales 2,594– 3,138 SF 8 sales Over 3,138 SF 7 sales 0.0% 5.0% 10.0% 9.0% 10.3% 9.9% 11.3% Discount from original list, average

The average is 11.3% for homes over 3,138 SF and 9.0% for homes under 2,324 SF. It does not move in a straight line; homes over 3,138 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

2026-10-28T07:49:49.426935 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 29 57 57 43 100 25 62 100 57 43 100 Under 2,324 SF 2,324–2,560 SF 2,594–3,138 SF Over 3,138 SF

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

  • 57% of homes over 3,138 SF had a price cut before sale, against 43% of homes under 2,324 SF. Defined in 8.1.7.
  • 43% of homes over 3,138 SF had the seller pay closing costs or repairs, against 29% of homes under 2,324 SF. Defined in 8.1.8.
  • 100% of homes over 3,138 SF have a view, against 57% 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 SF7 sales2,324–2,560 SF7 sales2,594–3,138 SF8 salesOver 3,138 SF7 salesAll29 salesReal difference?
Net sale price average$420,000$672,000$1,084,062$2,930,538$1,270,009✓ large
Net price per SF average$212$277$370$505$342unclear
Living area average1,9742,4532,8664,4752,939by design
Year built median19991985199019971991unclear

4.10 The numbers: selling

Under 2,324 SF7 sales2,324–2,560 SF7 sales2,594–3,138 SF8 salesOver 3,138 SF7 salesAll29 salesReal difference?
Days on market median89132835089unclear
Discount from original list average9.0%10.3%9.9%11.3%10.1%unclear
Price cut before sale43%57%25%57%45%unclear
Seller paid closing costs or repairs29%43%62%43%45%unclear
Has a view57%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 · 29 sales · October 28, 2025 – October 27, 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.

2026-10-28T07:49:49.446560 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 7 9 7 29 sales Sales per group Before 1984: 6 sales (21%) 1984–1988: 7 sales (24%) 1991–1998: 9 sales (31%) After 1998: 7 sales (24%)
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 19841984–19881991–1998After 1998Real difference?
Net sale price$512K$1.08M$1.15M$2.27Munclear
Net price per SF$198 per SF$391 per SF$345 per SF$411 per SFunclear
Living area2,580 SF2,611 SF2,982 SF3,521 SFunclear
Days on market72 days50 days211 days84 daysunclear
Discount from original list14.5%8.3%11.0%7.0%unclear
Price cut before sale50%29%67%29%unclear
Seller paid closing costs or repairs17%29%78%43%unclear
Has a view83%86%100%86%unclear

5.3 Net sale price: no clear difference

2026-10-28T07:49:49.467166 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 6 sales 1984– 1988 7 sales 1991– 1998 9 sales After 1998 7 sales $0K $1.00M $2.00M $512K $1.08M $1.15M $2.27M Net sale price, average

The average is $2.27M for homes built after 1998 and $512K for homes built before 1984. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-28T07:49:49.489466 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 6 sales 1984– 1988 7 sales 1991– 1998 9 sales After 1998 7 sales $0 $200 $400 $198 $391 $345 $411 Net price per SF, average

The average is $411 per SF for homes built after 1998 and $198 per SF for homes built before 1984. It does not move in a straight line; homes built after 1998 are highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-28T07:49:49.510554 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 6 sales 1984– 1988 7 sales 1991– 1998 9 sales After 1998 7 sales 0 2,000 4,000 2,580 2,611 2,982 3,521 Living area (SF), average

The average is 3,521 SF for homes built after 1998 and 2,580 SF for homes built before 1984. 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

2026-10-28T07:49:49.531760 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 6 sales 1984– 1988 7 sales 1991– 1998 9 sales After 1998 7 sales 0 100 200 72 50 211 84 Days on market, median

The median is 84 days for homes built after 1998 and 72 days for homes built before 1984. It does not move in a straight line; homes built 1991–1998 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-28T07:49:49.553457 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1984 6 sales 1984– 1988 7 sales 1991– 1998 9 sales After 1998 7 sales 0.0% 5.0% 10.0% 15.0% 14.5% 8.3% 11.0% 7.0% Discount from original list, average

The average is 7.0% for homes built after 1998 and 14.5% for homes built before 1984. It does not move in a straight line; homes built before 1984 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

2026-10-28T07:49:49.578717 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 17 83 29 29 86 67 78 100 29 43 86 Before 1984 1984–1988 1991–1998 After 1998

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

  • 29% of homes built after 1998 had a price cut before sale, against 50% of homes built before 1984. Defined in 8.1.7.
  • 43% of homes built after 1998 had the seller pay closing costs or repairs, against 17% of homes built before 1984. Defined in 8.1.8.
  • 86% of homes built after 1998 have a view, against 83% of homes built before 1984. 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 19846 sales1984–19887 sales1991–19989 salesAfter 19987 salesAll29 salesReal difference?
Net sale price average$511,717$1,075,286$1,147,663$2,272,000$1,270,009unclear
Net price per SF average$198$391$345$411$342unclear
Living area average2,5802,6112,9823,5212,939unclear
Year built median19811985199320151991by design

5.10 The numbers: selling

Before 19846 sales1984–19887 sales1991–19989 salesAfter 19987 salesAll29 salesReal difference?
Days on market median72502118489unclear
Discount from original list average14.5%8.3%11.0%7.0%10.1%unclear
Price cut before sale50%29%67%29%45%unclear
Seller paid closing costs or repairs17%29%78%43%45%unclear
Has a view83%86%100%86%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 · 29 sales · October 28, 2025 – October 27, 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.

2026-10-28T07:49:49.597131 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 26 3 29 sales Sales per group View: 26 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

2026-10-28T07:49:49.612474 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 26 sales No view 3 sales $0K $500K $1.00M $1.50M $1.37M $393K Net sale price, average

The average is $1.37M 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

2026-10-28T07:49:49.630652 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 26 sales No view 3 sales $0 $100 $200 $300 $400 $357 $208 Net price per SF, average

The average is $357 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

2026-10-28T07:49:49.648787 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 26 sales No view 3 sales 0 1,000 2,000 3,000 3,065 1,855 Living area (SF), average

The average is 3,065 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

2026-10-28T07:49:49.689041 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 26 sales No view 3 sales 1980 1985 1990 1995 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

2026-10-28T07:49:49.707593 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 26 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

2026-10-28T07:49:49.726447 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 26 sales No view 3 sales 0.0% 2.5% 5.0% 7.5% 10.0% 10.2% 9.3% Discount from original list, average

The average is 10.2% 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

2026-10-28T07:49:49.745148 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 42 50 67 0 View No view

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

  • 42% of homes with a view had a price cut before sale, against 67% of homes without a view. Defined in 8.1.7.
  • 50% 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

View26 salesNo view3 salesAll29 sales
Net sale price average$1,371,164$393,333$1,270,009
Net price per SF average$357$208$342
Living area average3,0651,8552,939
Year built median199119841991

6.11 The numbers: selling

View26 salesNo view3 salesAll29 sales
Days on market median898989
Discount from original list average10.2%9.3%10.1%
Price cut before sale42%67%45%
Seller paid closing costs or repairs50%0%45%

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 · October 28, 2025 – October 27, 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
29 resale sales. Average $1,270,009; median $634,000; standard deviation $2,141,356; middle half (25th–75th percentile) $515,000–$863,300; 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
29 resale sales. Average $342; median $241; standard deviation $272; middle half (25th–75th percentile) $205–$284; 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
29 resale sales. Average 2,939; median 2,594; standard deviation 1,503; middle half (25th–75th percentile) 2,324–3,138; 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
29 resale sales. Average 1993; 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
29 resale sales. Average 134; median 89; standard deviation 136; middle half (25th–75th percentile) 37–211; 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
29 resale sales. Average 10.1%; median 8.6%; standard deviation 7.0%; middle half (25th–75th percentile) 4.8%–13.8%; 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
13 of 29 resale sales (44.8%).

8.1.8 Seller paid closing costs or repairs

In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
13 of 29 resale sales (44.8%).

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
26 sales with a view, 3 without, 0 unclassified. Most common View entries: Hill Country 16, Lake 11, Golf Course 11, Panoramic 6, None 3, Trees/Woods 3, Water 2, Neighborhood 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
Bridge Interactive RESO Web API (OData), ABOR dataset, every field returned. 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 October 28, 2026: 34 closed Horseshoe Bay Proper records over the prior year, in ZIP 78657. 1 subdivision spellings kept: Horseshoe Bay Proper (34). 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 October 28, 2025 to October 27, 2026 inclusive.
The data
30 single-family sales in the window: 29 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
29 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
4 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 $515K”.
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 $515K: $270,000–$465,000 (7 sales); $515K–$586K: $515,000–$586,000 (7 sales); $634K–$863K: $634,000–$863,300 (8 sales); Over $863K: $993,000–$11,300,000 (7 sales)
Quartiles by living area: Under 2,324 SF: 1,512–2,278 SF (7 sales); 2,324–2,560 SF: 2,324–2,560 SF (7 sales); 2,594–3,138 SF: 2,594–3,138 SF (8 sales); Over 3,138 SF: 3,168–10,065 SF (7 sales)
Quartiles by year built: Before 1984: 1975–1983 (6 sales); 1984–1988: 1984–1988 (7 sales); 1991–1998: 1991–1998 (9 sales); After 1998: 1999–2020 (7 sales)
View and no view: View: MLS lists a view (26 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 $1,270,009, median $634,000. Days on market: average 134, 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 = 18.6930.0003p < 0.0063Yesε² = 0.667large
Living areaKruskal–WallisH = 15.0730.0018p < 0.0063Yesε² = 0.538large
Year builtKruskal–WallisH = 3.8330.2798p < 0.0063Unclearε² = 0.137medium
Days on marketKruskal–WallisH = 1.2030.7526p < 0.0063Unclearε² = 0.043small
Discount from original listKruskal–WallisH = 0.0630.9965p < 0.0063Unclearε² = 0.002negligible
Price cut before saleChi-squareχ² = 0.6230.8907p < 0.0063UnclearCramér’s V = 0.147small
Seller paid closing costs or repairsChi-squareχ² = 2.9430.4017p < 0.0063UnclearCramér’s V = 0.318medium
Has a viewChi-squareχ² = 4.3630.2256p < 0.0063UnclearCramér’s V = 0.388medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 13.9730.0029p < 0.0063Yesε² = 0.499large
Net price per SFKruskal–WallisH = 4.9730.1742p < 0.0063Unclearε² = 0.177large
Year builtKruskal–WallisH = 4.1730.2440p < 0.0063Unclearε² = 0.149large
Days on marketKruskal–WallisH = 1.8030.6146p < 0.0063Unclearε² = 0.064medium
Discount from original listKruskal–WallisH = 1.1630.7629p < 0.0063Unclearε² = 0.041small
Price cut before saleChi-squareχ² = 2.1430.5436p < 0.0063UnclearCramér’s V = 0.272small
Seller paid closing costs or repairsChi-squareχ² = 1.7830.6193p < 0.0063UnclearCramér’s V = 0.248small
Has a viewChi-squareχ² = 10.5230.0146p < 0.0063UnclearCramér’s V = 0.602large

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 3.8630.2775p < 0.0063Unclearε² = 0.138medium
Net price per SFKruskal–WallisH = 4.2430.2363p < 0.0063Unclearε² = 0.152large
Living areaKruskal–WallisH = 1.1130.7752p < 0.0063Unclearε² = 0.040small
Days on marketKruskal–WallisH = 7.2930.0632p < 0.0063Unclearε² = 0.260large
Discount from original listKruskal–WallisH = 4.4730.2152p < 0.0063Unclearε² = 0.160large
Price cut before saleChi-squareχ² = 3.3030.3481p < 0.0063UnclearCramér’s V = 0.337medium
Seller paid closing costs or repairsChi-squareχ² = 6.6330.0845p < 0.0063UnclearCramér’s V = 0.478medium
Has a viewChi-squareχ² = 1.5330.6750p < 0.0063UnclearCramér’s V = 0.230small

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); 4 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 29 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 October 28, 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.