ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Shiloh

Austin, TX 78745
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 · 4:06 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
22
single-family resale homes
Median net sale price
$479,750
average $491,203
Median net price per SF
$303
average $309
Median days on market
46 days
average 68 days
1. SummaryResale homes · 22 sales · October 26, 2025 – October 25, 2026

This study looks at the 22 resale homes sold in Shiloh in the 365 days to October 25, 2026. A full year is used because only 8 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 sold22 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 $429K · 6 sales$429K–$479K · 5 sales$480K–$530K · 5 salesOver $530K · 6 sales
3. Quartiles by net sale priceResale homes · 22 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.

2026-10-26T04:06:51.723517 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 5 5 6 22 sales Sales per group Under $429K: 6 sales (27%) $429K–$479K: 5 sales (23%) $480K–$530K: 5 sales (23%) Over $530K: 6 sales (27%)
Bottom line: no measure differs enough between the groups to rule out chance.

3.1 Key differences

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

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 $429K$429K–$479K$480K–$530KOver $530KReal difference?
Net price per SF$256 per SF$284 per SF$304 per SF$388 per SFunclear
Living area1,477 SF1,645 SF1,664 SF1,625 SFunclear
Year built1981197919791978unclear
Days on market33 days54 days39 days49 daysunclear
Discount from original list10.0%9.7%5.8%3.8%unclear
Price cut before sale50%80%40%50%unclear
Seller paid closing costs or repairs50%100%80%50%unclear
Has a view33%0%40%0%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

2026-10-26T04:06:51.752086 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $429K 6 sales $429K– $479K 5 sales $480K– $530K 5 sales Over $530K 6 sales $0 $200 $400 $256 $284 $304 $388 Net price per SF, average

The average is $388 per SF for homes over $530K and $256 per SF for homes under $429K. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-26T04:06:51.774168 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $429K 6 sales $429K– $479K 5 sales $480K– $530K 5 sales Over $530K 6 sales 0 500 1,000 1,500 1,477 1,645 1,664 1,625 Living area (SF), average

The average is 1,625 SF for homes over $530K and 1,477 SF for homes under $429K. It does not move in a straight line; homes $480K–$530K are highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-26T04:06:51.798595 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $429K 6 sales $429K– $479K 5 sales $480K– $530K 5 sales Over $530K 6 sales 1978 1979 1980 1981 1981 1979 1979 1978 Year built: median (dot) and middle half (bar)

The median is 1978 for homes over $530K and 1981 for homes under $429K. It falls step by step from the lowest range to the highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T04:06:51.821372 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $429K 6 sales $429K– $479K 5 sales $480K– $530K 5 sales Over $530K 6 sales 0 20 40 60 33 54 39 49 Days on market, median

The median is 49 days for homes over $530K and 33 days for homes under $429K. It does not move in a straight line; homes $429K–$479K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T04:06:51.842974 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $429K 6 sales $429K– $479K 5 sales $480K– $530K 5 sales Over $530K 6 sales 0.0% 5.0% 10.0% 10.0% 9.7% 5.8% 3.8% Discount from original list, average

The average is 3.8% for homes over $530K and 10.0% for homes under $429K. It falls step by step from the lowest range to the highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T04:06:51.872437 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 50 33 80 100 0 40 80 40 50 50 0 Under $429K $429K–$479K $480K–$530K Over $530K

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

  • 50% of homes over $530K had a price cut before sale, against 50% of homes under $429K. Defined in 8.1.7.
  • 50% of homes over $530K had the seller pay closing costs or repairs, against 50% of homes under $429K. Defined in 8.1.8.
  • 0% of homes over $530K have a view, against 33% of homes under $429K. 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 $429K6 sales$429K–$479K5 sales$480K–$530K5 salesOver $530K6 salesAll22 salesReal difference?
Net sale price average$372,610$455,859$505,478$627,352$491,203by design
Net price per SF average$256$284$304$388$309unclear
Living area average1,4771,6451,6641,6251,598unclear
Year built median19811979197919781979unclear

3.10 The numbers: selling

Under $429K6 sales$429K–$479K5 sales$480K–$530K5 salesOver $530K6 salesAll22 salesReal difference?
Days on market median3354394946unclear
Discount from original list average10.0%9.7%5.8%3.8%7.3%unclear
Price cut before sale50%80%40%50%55%unclear
Seller paid closing costs or repairs50%100%80%50%68%unclear
Has a view33%0%40%0%18%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 · 22 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.

2026-10-26T04:06:51.892835 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 5 5 6 22 sales Sales per group Under 1,482 SF: 6 sales (27%) 1,482–1,651 SF: 5 sales (23%) 1,655–1,701 SF: 5 sales (23%) Over 1,701 SF: 6 sales (27%)
Bottom line: no measure differs enough between the groups to rule out chance.

4.1 Key differences

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

4.2 At a glance

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

Under 1,482 SF1,482–1,651 SF1,655–1,701 SFOver 1,701 SFReal difference?
Net sale price$428K$532K$478K$531Kunclear
Net price per SF$316 per SF$340 per SF$285 per SF$297 per SFunclear
Year built1982198119781979unclear
Days on market61 days7 days31 days53 daysunclear
Discount from original list11.9%4.4%3.6%8.2%unclear
Price cut before sale83%40%40%50%unclear
Seller paid closing costs or repairs33%100%60%83%unclear
Has a view33%20%0%17%unclear

4.3 Net sale price: no clear difference

2026-10-26T04:06:51.913076 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,482 SF 6 sales 1,482– 1,651 SF 5 sales 1,655– 1,701 SF 5 sales Over 1,701 SF 6 sales $0K $200K $400K $600K $428K $532K $478K $531K Net sale price, average

The average is $531K for homes over 1,701 SF and $428K for homes under 1,482 SF. It does not move in a straight line; homes 1,482–1,651 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-10-26T04:06:51.935531 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,482 SF 6 sales 1,482– 1,651 SF 5 sales 1,655– 1,701 SF 5 sales Over 1,701 SF 6 sales $0 $200 $400 $316 $340 $285 $297 Net price per SF, average

The average is $297 per SF for homes over 1,701 SF and $316 per SF for homes under 1,482 SF. It does not move in a straight line; homes 1,482–1,651 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T04:06:51.957873 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,482 SF 6 sales 1,482– 1,651 SF 5 sales 1,655– 1,701 SF 5 sales Over 1,701 SF 6 sales 1978 1980 1982 1982 1981 1978 1979 Year built: median (dot) and middle half (bar)

The median is 1979 for homes over 1,701 SF and 1982 for homes under 1,482 SF. It does not move in a straight line; homes under 1,482 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T04:06:51.982912 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,482 SF 6 sales 1,482– 1,651 SF 5 sales 1,655– 1,701 SF 5 sales Over 1,701 SF 6 sales 0 20 40 60 61 7 31 53 Days on market, median

The median is 53 days for homes over 1,701 SF and 61 days for homes under 1,482 SF. It does not move in a straight line; homes under 1,482 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T04:06:52.005487 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,482 SF 6 sales 1,482– 1,651 SF 5 sales 1,655– 1,701 SF 5 sales Over 1,701 SF 6 sales 0.0% 5.0% 10.0% 11.9% 4.4% 3.6% 8.2% Discount from original list, average

The average is 8.2% for homes over 1,701 SF and 11.9% for homes under 1,482 SF. It does not move in a straight line; homes under 1,482 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

2026-10-26T04:06:52.031908 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% 83 33 33 40 100 20 40 60 0 50 83 17 Under 1,482 SF 1,482–1,651 SF 1,655–1,701 SF Over 1,701 SF

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

  • 50% of homes over 1,701 SF had a price cut before sale, against 83% of homes under 1,482 SF. Defined in 8.1.7.
  • 83% of homes over 1,701 SF had the seller pay closing costs or repairs, against 33% of homes under 1,482 SF. Defined in 8.1.8.
  • 17% of homes over 1,701 SF have a view, against 33% of homes under 1,482 SF. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance

4.9 The numbers: price and size

Under 1,482 SF6 sales1,482–1,651 SF5 sales1,655–1,701 SF5 salesOver 1,701 SF6 salesAll22 salesReal difference?
Net sale price average$428,324$532,050$477,598$531,379$491,203unclear
Net price per SF average$316$340$285$297$309unclear
Living area average1,3541,5571,6761,8101,598by design
Year built median19821981197819791979unclear

4.10 The numbers: selling

Under 1,482 SF6 sales1,482–1,651 SF5 sales1,655–1,701 SF5 salesOver 1,701 SF6 salesAll22 salesReal difference?
Days on market median617315346unclear
Discount from original list average11.9%4.4%3.6%8.2%7.3%unclear
Price cut before sale83%40%40%50%55%unclear
Seller paid closing costs or repairs33%100%60%83%68%unclear
Has a view33%20%0%17%18%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 · 22 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.

2026-10-26T04:06:52.052036 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 6 5 4 22 sales Sales per group Before 1979: 7 sales (32%) 1979: 6 sales (27%) 1981: 5 sales (23%) After 1981: 4 sales (18%)
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

2026-10-26T04:06:52.071807 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 7 sales 1979 6 sales 1981 5 sales After 1981 4 sales $0K $200K $400K $600K $527K $492K $417K $521K Net sale price, average

The average is $521K for homes built after 1981 and $527K for homes built before 1979. It does not move in a straight line; homes built before 1979 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T04:06:52.095035 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 7 sales 1979 6 sales 1981 5 sales After 1981 4 sales $0 $100 $200 $300 $400 $310 $293 $284 $365 Net price per SF, average

The average is $365 per SF for homes built after 1981 and $310 per SF for homes built before 1979. It does not move in a straight line; homes built after 1981 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T04:06:52.124686 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 7 sales 1979 6 sales 1981 5 sales After 1981 4 sales 0 500 1,000 1,500 2,000 1,718 1,686 1,472 1,414 Living area (SF), average

The average is 1,414 SF for homes built after 1981 and 1,718 SF for homes built before 1979. It falls step by step from the lowest range to the highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T04:06:52.147956 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 7 sales 1979 6 sales 1981 5 sales After 1981 4 sales 0 20 40 60 80 37 77 10 58 Days on market, median

The median is 58 days for homes built after 1981 and 37 days for homes built before 1979. It does not move in a straight line; homes built 1979 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T04:06:52.171851 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1979 7 sales 1979 6 sales 1981 5 sales After 1981 4 sales 0.0% 2.5% 5.0% 7.5% 10.0% 6.2% 8.3% 5.6% 9.9% Discount from original list, average

The average is 9.9% for homes built after 1981 and 6.2% for homes built before 1979. It does not move in a straight line; homes built after 1981 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

2026-10-26T04:06:52.198105 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 67 83 17 20 60 20 100 50 25 Before 1979 1979 1981 After 1981

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

  • 100% of homes built after 1981 had a price cut before sale, against 43% of homes built before 1979. Defined in 8.1.7.
  • 50% of homes built after 1981 had the seller pay closing costs or repairs, against 71% of homes built before 1979. Defined in 8.1.8.
  • 25% of homes built after 1981 have a view, against 14% of homes built before 1979. 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 19797 sales19796 sales19815 salesAfter 19814 salesAll22 sales
Net sale price average$526,792$491,995$416,652$520,920$491,203
Net price per SF average$310$293$284$365$309
Living area average1,7181,6861,4721,4141,598
Year built median19781979198119821979

5.10 The numbers: selling

Before 19797 sales19796 sales19815 salesAfter 19814 salesAll22 sales
Days on market median3777105846
Discount from original list average6.2%8.3%5.6%9.9%7.3%
Price cut before sale43%67%20%100%55%
Seller paid closing costs or repairs71%83%60%50%68%
Has a view14%17%20%25%18%

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 · 22 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.

2026-10-26T04:06:52.217069 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 4 17 21 sales Sales per group View: 4 sales (19%) No view: 17 sales (81%)
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

2026-10-26T04:06:52.232432 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 17 sales $0K $200K $400K $600K $430K $515K Net sale price, average

The average is $430K for homes with a view and $515K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T04:06:52.249717 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 17 sales $0 $100 $200 $300 $282 $322 Net price per SF, average

The average is $282 per SF for homes with a view and $322 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T04:06:52.267627 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 17 sales 0 500 1,000 1,500 1,514 1,614 Living area (SF), average

The average is 1,514 SF for homes with a view and 1,614 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T04:06:52.337175 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 17 sales 1978 1979 1980 1981 1980 1979 Year built: median (dot) and middle half (bar)

The median is 1980 for homes with a view and 1979 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T04:06:52.356002 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 17 sales 0 20 40 60 80 74 39 Days on market, median

The median is 74 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

2026-10-26T04:06:52.376263 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 4 sales No view 17 sales 0.0% 5.0% 10.0% 15.0% 15.5% 5.8% Discount from original list, average

The average is 15.5% for homes with a view and 5.8% 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

2026-10-26T04:06:52.395432 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 75 50 53 71 View No view

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

  • 75% of homes with a view had a price cut before sale, against 53% 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 71% 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 view17 salesAll21 sales
Net sale price average$430,475$515,268$499,117
Net price per SF average$282$322$315
Living area average1,5141,6141,595
Year built median198019791979

6.11 The numbers: selling

View4 salesNo view17 salesAll21 sales
Days on market median743954
Discount from original list average15.5%5.8%7.6%
Price cut before sale75%53%57%
Seller paid closing costs or repairs50%71%67%

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 Shiloh.

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
22 resale sales. Average $491,203; median $479,750; standard deviation $106,166; middle half (25th–75th percentile) $427,425–$534,560; lowest $324,999, highest $715,000. 15 sales had a seller payment; their median payment was $7,000.

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
22 resale sales. Average $309; median $303; standard deviation $65; middle half (25th–75th percentile) $265–$339; lowest $196, highest $439.

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
22 resale sales. Average 1,598; median 1,653; standard deviation 197; middle half (25th–75th percentile) 1,446–1,710; lowest 1,224, highest 2,102.

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
22 resale sales. Average 1980; median 1979; standard deviation 2; middle half (25th–75th percentile) 1978–1981; lowest 1977, highest 1983.

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
22 resale sales. Average 68; median 46; standard deviation 78; middle half (25th–75th percentile) 14–82; lowest 0, highest 268. 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
22 resale sales. Average 7.3%; median 3.6%; standard deviation 7.3%; middle half (25th–75th percentile) 1.9%–12.5%; lowest −0.2%, highest 24.2%. 1 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 22 resale sales (54.5%).

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
15 of 22 resale sales (68.2%).

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, 17 without, 1 unclassified. Most common View entries: None 12, Neighborhood 7, Park/Greenbelt 4, Trees/Woods 3, City 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 = Austin, SubdivisionName contains any of “shiloh” (case-insensitive). A record is kept when its subdivision name belongs to the Shiloh family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 22 closed Shiloh records over the prior year, in ZIP 78745. 5 subdivision spellings kept: Shiloh Ph 02 Sec 01 Amd (12); Shiloh Ph 04 Sec 01 (6); Shiloh Ph 01 Sec 01 (2); Shiloh Subdivision (1); Shiloh Ph 04 Sec 02 (1). Names found by the search but not part of Shiloh, left out: SHILOH SUBD PHS 2 SEC 1 AMEN (1).

8.2.2 Study window

In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 8 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from October 26, 2025 to October 25, 2026 inclusive.
The data
22 single-family sales in the window: 22 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
22 resale; 0 new construction.

8.2.4 Sales left out

In simple terms
A few records cannot be used as entered and are left out before any analysis.
Statistically
Excluded: PropertySubType other than Single Family Residence; no OriginalListPrice; LivingArea under 400 SF; seller payments above 10% of ClosePrice (treated as entry errors).
The data
None in this window.

8.2.5 Quartiles and groups

In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $429K”.
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 $429K: $324,999–$426,900 (6 sales); $429K–$479K: $429,000–$479,000 (5 sales); $480K–$530K: $480,500–$530,000 (5 sales); Over $530K: $536,080–$715,000 (6 sales)
Quartiles by living area: Under 1,482 SF: 1,224–1,434 SF (6 sales); 1,482–1,651 SF: 1,482–1,651 SF (5 sales); 1,655–1,701 SF: 1,655–1,701 SF (5 sales); Over 1,701 SF: 1,713–2,102 SF (6 sales)
Quartiles by year built: Before 1979: 1977–1978 (7 sales); 1979: 1979–1979 (6 sales); 1981: 1981–1981 (5 sales); After 1981: 1982–1983 (4 sales)
View and no view: View: MLS lists a view (4 sales); No view: None or Neighborhood (17 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 $491,203, median $479,750. Days on market: average 68, median 46: 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
0 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 = 11.7130.0085p < 0.0063Unclearε² = 0.557large
Living areaKruskal–WallisH = 2.9930.3925p < 0.0063Unclearε² = 0.143large
Year builtKruskal–WallisH = 0.7330.8653p < 0.0063Unclearε² = 0.035small
Days on marketKruskal–WallisH = 0.6930.8751p < 0.0063Unclearε² = 0.033small
Discount from original listKruskal–WallisH = 3.9830.2634p < 0.0063Unclearε² = 0.190large
Price cut before saleChi-squareχ² = 1.8330.6077p < 0.0063UnclearCramér’s V = 0.289small
Seller paid closing costs or repairsChi-squareχ² = 4.4830.2137p < 0.0063UnclearCramér’s V = 0.451medium
Has a viewChi-squareχ² = 4.9730.1740p < 0.0063UnclearCramér’s V = 0.475medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 3.9830.2641p < 0.0063Unclearε² = 0.189large
Net price per SFKruskal–WallisH = 2.6330.4514p < 0.0063Unclearε² = 0.125medium
Year builtKruskal–WallisH = 8.6830.0339p < 0.0063Unclearε² = 0.413large
Days on marketKruskal–WallisH = 3.3730.3381p < 0.0063Unclearε² = 0.160large
Discount from original listKruskal–WallisH = 4.0330.2579p < 0.0063Unclearε² = 0.192large
Price cut before saleChi-squareχ² = 2.9130.4059p < 0.0063UnclearCramér’s V = 0.364medium
Seller paid closing costs or repairsChi-squareχ² = 6.4830.0904p < 0.0063UnclearCramér’s V = 0.543large
Has a viewChi-squareχ² = 2.0630.5606p < 0.0063UnclearCramér’s V = 0.306medium

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); nothing else. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.

8.5 References

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

This is a market study of closed sales, not an appraisal or an opinion of value for any home. The analysis covers 22 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.