ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Saxony

Pflugerville, TX 78660
Resale homes · closed Oct 26 – Oct 25, 2026
Prepared for Buyers, sellers and agents
Prepared by ALEX Real Estate
Market Study · Resale Analysis
Version 2.4
October 26, 2026 · 5:36 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
$382,500
average $380,004
Median net price per SF
$180
average $180
Median days on market
27 days
average 38 days
1. SummaryResale homes · 22 sales · October 26, 2025 – October 25, 2026

This study looks at the 22 resale homes sold in Saxony in the 365 days to October 25, 2026. A full year is used because only 16 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 $359K · 6 sales$359K–$377K · 5 sales$388K–$409K · 5 salesOver $409K · 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.

2026-10-26T05:36:27.796863 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 5 5 6 22 sales Sales per group Under $359K: 6 sales (27%) $359K–$377K: 5 sales (23%) $388K–$409K: 5 sales (23%) Over $409K: 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 $359K$359K–$377K$388K–$409KOver $409KReal difference?
Net price per SF$156 per SF$185 per SF$184 per SF$197 per SFunclear
Living area1,979 SF2,018 SF2,192 SF2,304 SFunclear
Year built1992199319921992unclear
Days on market14 days34 days70 days24 daysunclear
Discount from original list7.2%4.3%4.1%4.6%unclear
Price cut before sale33%40%60%50%unclear
Seller paid closing costs or repairs33%80%80%100%unclear
Has a view0%20%0%33%unclear

How to read this section. Each heading gives the finding. The gold box says whether the gap is real (✓, with its size) or could be chance (–). The section ends with its numbers; the tests are in section 8.3.

3.3 Net price per SF: no clear difference

2026-10-26T05:36:27.827132 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $359K 6 sales $359K– $377K 5 sales $388K– $409K 5 sales Over $409K 6 sales $0 $100 $200 $156 $185 $184 $197 Net price per SF, average

The average is $197 per SF for homes over $409K and $156 per SF for homes under $359K. It does not move in a straight line; homes over $409K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Living area: no clear difference

2026-10-26T05:36:27.852283 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $359K 6 sales $359K– $377K 5 sales $388K– $409K 5 sales Over $409K 6 sales 0 1,000 2,000 1,979 2,018 2,192 2,304 Living area (SF), average

The average is 2,304 SF for homes over $409K and 1,979 SF for homes under $359K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

– No clear difference · could be chance

3.5 Year built: no clear difference

2026-10-26T05:36:27.878618 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $359K 6 sales $359K– $377K 5 sales $388K– $409K 5 sales Over $409K 6 sales 1988 1992 1996 2000 2004 1992 1993 1992 1992 Year built: median (dot) and middle half (bar)

The median is 1992 for homes over $409K and 1992 for homes under $359K. It does not move in a straight line; homes $359K–$377K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:36:27.904560 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $359K 6 sales $359K– $377K 5 sales $388K– $409K 5 sales Over $409K 6 sales 0 25 50 75 14 34 70 24 Days on market, median

The median is 24 days for homes over $409K and 14 days for homes under $359K. It does not move in a straight line; homes $388K–$409K are highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:36:27.929286 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $359K 6 sales $359K– $377K 5 sales $388K– $409K 5 sales Over $409K 6 sales 0.0% 2.5% 5.0% 7.5% 7.2% 4.3% 4.1% 4.6% Discount from original list, average

The average is 4.6% for homes over $409K and 7.2% for homes under $359K. It does not move in a straight line; homes under $359K are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T05:36:27.962043 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 33 0 40 80 20 60 80 0 50 100 33 Under $359K $359K–$377K $388K–$409K Over $409K

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

  • 50% of homes over $409K had a price cut before sale, against 33% of homes under $359K. Defined in 8.1.7.
  • 100% of homes over $409K had the seller pay closing costs or repairs, against 33% of homes under $359K. Defined in 8.1.8.
  • 33% of homes over $409K have a view, against 0% of homes under $359K. 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 $359K6 sales$359K–$377K5 sales$388K–$409K5 salesOver $409K6 salesAll22 salesReal difference?
Net sale price average$303,500$370,005$398,500$449,427$380,004by design
Net price per SF average$156$185$184$197$180unclear
Living area average1,9792,0182,1922,3042,125unclear
Year built median19921993199219921992unclear

3.10 The numbers: selling

Under $359K6 sales$359K–$377K5 sales$388K–$409K5 salesOver $409K6 salesAll22 salesReal difference?
Days on market median1434702427unclear
Discount from original list average7.2%4.3%4.1%4.6%5.1%unclear
Price cut before sale33%40%60%50%45%unclear
Seller paid closing costs or repairs33%80%80%100%73%unclear
Has a view0%20%0%33%14%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.

2026-10-26T05:36:27.984414 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 5 5 6 22 sales Sales per group Under 1,983 SF: 6 sales (27%) 1,983–2,056 SF: 5 sales (23%) 2,078–2,336 SF: 5 sales (23%) Over 2,336 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 1,983 SF1,983–2,056 SF2,078–2,336 SFOver 2,336 SFReal difference?
Net sale price$346K$380K$361K$430Kunclear
Net price per SF$190 per SF$189 per SF$168 per SF$173 per SFunclear
Year built1992199219881993unclear
Days on market20 days13 days16 days55 daysunclear
Discount from original list5.6%3.4%4.9%6.3%unclear
Price cut before sale33%40%20%83%unclear
Seller paid closing costs or repairs83%80%40%83%unclear
Has a view17%0%20%17%unclear

4.3 Net sale price: no clear difference

2026-10-26T05:36:28.007091 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,983 SF 6 sales 1,983– 2,056 SF 5 sales 2,078– 2,336 SF 5 sales Over 2,336 SF 6 sales $0K $200K $400K $346K $380K $361K $430K Net sale price, average

The average is $430K for homes over 2,336 SF and $346K for homes under 1,983 SF. It does not move in a straight line; homes over 2,336 SF are highest. Defined in 8.1.1.

– No clear difference · could be chance

4.4 Net price per SF: no clear difference

2026-10-26T05:36:28.032153 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,983 SF 6 sales 1,983– 2,056 SF 5 sales 2,078– 2,336 SF 5 sales Over 2,336 SF 6 sales $0 $100 $200 $190 $189 $168 $173 Net price per SF, average

The average is $173 per SF for homes over 2,336 SF and $190 per SF for homes under 1,983 SF. It does not move in a straight line; homes under 1,983 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T05:36:28.058428 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,983 SF 6 sales 1,983– 2,056 SF 5 sales 2,078– 2,336 SF 5 sales Over 2,336 SF 6 sales 1986 1988 1990 1992 1994 1992 1992 1988 1993 Year built: median (dot) and middle half (bar)

The median is 1993 for homes over 2,336 SF and 1992 for homes under 1,983 SF. It does not move in a straight line; homes over 2,336 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T05:36:28.083239 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,983 SF 6 sales 1,983– 2,056 SF 5 sales 2,078– 2,336 SF 5 sales Over 2,336 SF 6 sales 0 20 40 60 20 13 16 55 Days on market, median

The median is 55 days for homes over 2,336 SF and 20 days for homes under 1,983 SF. It does not move in a straight line; homes over 2,336 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T05:36:28.106260 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 1,983 SF 6 sales 1,983– 2,056 SF 5 sales 2,078– 2,336 SF 5 sales Over 2,336 SF 6 sales 0.0% 2.0% 4.0% 6.0% 5.6% 3.4% 4.9% 6.3% Discount from original list, average

The average is 6.3% for homes over 2,336 SF and 5.6% for homes under 1,983 SF. It does not move in a straight line; homes over 2,336 SF are highest. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T05:36:28.133130 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 83 17 40 80 0 20 40 20 83 83 17 Under 1,983 SF 1,983–2,056 SF 2,078–2,336 SF Over 2,336 SF

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

  • 83% of homes over 2,336 SF had a price cut before sale, against 33% of homes under 1,983 SF. Defined in 8.1.7.
  • 83% of homes over 2,336 SF had the seller pay closing costs or repairs, against 83% of homes under 1,983 SF. Defined in 8.1.8.
  • 17% of homes over 2,336 SF have a view, against 17% of homes under 1,983 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 1,983 SF6 sales1,983–2,056 SF5 sales2,078–2,336 SF5 salesOver 2,336 SF6 salesAll22 salesReal difference?
Net sale price average$346,121$379,758$361,500$429,512$380,004unclear
Net price per SF average$190$189$168$173$180unclear
Living area average1,8282,0142,1552,4882,125by design
Year built median19921992198819931992unclear

4.10 The numbers: selling

Under 1,983 SF6 sales1,983–2,056 SF5 sales2,078–2,336 SF5 salesOver 2,336 SF6 salesAll22 salesReal difference?
Days on market median2013165527unclear
Discount from original list average5.6%3.4%4.9%6.3%5.1%unclear
Price cut before sale33%40%20%83%45%unclear
Seller paid closing costs or repairs83%80%40%83%73%unclear
Has a view17%0%20%17%14%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.

2026-10-26T05:36:28.155723 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 6 7 3 6 22 sales Sales per group Before 1991: 6 sales (27%) 1991–1992: 7 sales (32%) 1993: 3 sales (14%) After 1993: 6 sales (27%)
Bottom line: too few sales to test.

5.1 Key differences

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

5.3 Net sale price: described, not tested

2026-10-26T05:36:28.177944 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1991 6 sales 1991– 1992 7 sales 1993 3 sales After 1993 6 sales $0K $200K $400K $359K $402K $334K $398K Net sale price, average

The average is $398K for homes built after 1993 and $359K for homes built before 1991. It does not move in a straight line; homes built 1991–1992 are highest. Defined in 8.1.1.

Not tested: too few sales.

5.4 Net price per SF: described, not tested

2026-10-26T05:36:28.202395 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1991 6 sales 1991– 1992 7 sales 1993 3 sales After 1993 6 sales $0 $100 $200 $164 $196 $173 $181 Net price per SF, average

The average is $181 per SF for homes built after 1993 and $164 per SF for homes built before 1991. It does not move in a straight line; homes built 1991–1992 are highest. Defined in 8.1.2.

Not tested: too few sales.

5.5 Living area: described, not tested

2026-10-26T05:36:28.226103 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1991 6 sales 1991– 1992 7 sales 1993 3 sales After 1993 6 sales 0 1,000 2,000 2,200 2,067 1,936 2,211 Living area (SF), average

The average is 2,211 SF for homes built after 1993 and 2,200 SF for homes built before 1991. It does not move in a straight line; homes built after 1993 are highest. Defined in 8.1.3.

Not tested: too few sales.

5.6 Days on market: described, not tested

2026-10-26T05:36:28.248230 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1991 6 sales 1991– 1992 7 sales 1993 3 sales After 1993 6 sales 0 20 40 15 34 3 36 Days on market, median

The median is 36 days for homes built after 1993 and 15 days for homes built before 1991. It does not move in a straight line; homes built after 1993 are highest. Defined in 8.1.5.

Not tested: too few sales.

5.7 Discount from original list: described, not tested

2026-10-26T05:36:28.272418 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1991 6 sales 1991– 1992 7 sales 1993 3 sales After 1993 6 sales 0.0% 2.5% 5.0% 7.5% 7.0% 2.7% 2.8% 7.2% Discount from original list, average

The average is 7.2% for homes built after 1993 and 7.0% for homes built before 1991. It does not move in a straight line; homes built after 1993 are highest. Defined in 8.1.6.

Not tested: too few sales.

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

2026-10-26T05:36:28.299126 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 50 17 43 86 14 33 67 0 67 83 17 Before 1991 1991–1992 1993 After 1993

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

  • 67% of homes built after 1993 had a price cut before sale, against 33% of homes built before 1991. Defined in 8.1.7.
  • 83% of homes built after 1993 had the seller pay closing costs or repairs, against 50% of homes built before 1991. Defined in 8.1.8.
  • 17% of homes built after 1993 have a view, against 17% of homes built before 1991. 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 19916 sales1991–19927 sales19933 salesAfter 19936 salesAll22 sales
Net sale price average$358,916$402,031$334,000$398,396$380,004
Net price per SF average$164$196$173$181$180
Living area average2,2002,0671,9362,2112,125
Year built median19861992199319981992

5.10 The numbers: selling

Before 19916 sales1991–19927 sales19933 salesAfter 19936 salesAll22 sales
Days on market median153433627
Discount from original list average7.0%2.7%2.8%7.2%5.1%
Price cut before sale33%43%33%67%45%
Seller paid closing costs or repairs50%86%67%83%73%
Has a view17%14%0%17%14%

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.

2026-10-26T05:36:28.320118 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 3 18 21 sales Sales per group View: 3 sales (14%) No view: 18 sales (86%)
Bottom line: too few sales to test.

6.1 Key differences

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

6.3 Net sale price: described, not tested

2026-10-26T05:36:28.338234 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 18 sales $0K $200K $400K $447K $370K Net sale price, average

The average is $447K for homes with a view and $370K for homes without a view. Defined in 8.1.1.

Not tested: too few sales.

6.4 Net price per SF: described, not tested

2026-10-26T05:36:28.358060 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 18 sales $0 $50 $100 $150 $200 $204 $176 Net price per SF, average

The average is $204 per SF for homes with a view and $176 per SF for homes without a view. Defined in 8.1.2.

Not tested: too few sales.

6.5 Living area: described, not tested

2026-10-26T05:36:28.408744 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 18 sales 0 1,000 2,000 2,193 2,121 Living area (SF), average

The average is 2,193 SF for homes with a view and 2,121 SF for homes without a view. Defined in 8.1.3.

Not tested: too few sales.

6.6 Year built: described, not tested

2026-10-26T05:36:28.429783 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 18 sales 1989 1990 1991 1992 1993 1992 1992 Year built: median (dot) and middle half (bar)

The median is 1992 for homes with a view and 1992 for homes without a view. Defined in 8.1.4.

Not tested: too few sales.

6.7 Days on market: described, not tested

2026-10-26T05:36:28.449682 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 18 sales 0 10 20 30 40 14 34 Days on market, median

The median is 14 days for homes with a view and 34 days for homes without a view. Defined in 8.1.5.

Not tested: too few sales.

6.8 Discount from original list: described, not tested

2026-10-26T05:36:28.469098 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 3 sales No view 18 sales 0.0% 2.0% 4.0% 6.0% 3.3% 5.3% Discount from original list, average

The average is 3.3% for homes with a view and 5.3% 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

2026-10-26T05:36:28.487983 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 33 67 44 72 View No view

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

  • 33% of homes with a view had a price cut before sale, against 44% of homes without a view. Defined in 8.1.7.
  • 67% of homes with a view had the seller pay closing costs or repairs, against 72% 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

View3 salesNo view18 salesAll21 sales
Net sale price average$447,167$369,988$381,014
Net price per SF average$204$176$180
Living area average2,1932,1212,131
Year built median199219921992

6.11 The numbers: selling

View3 salesNo view18 salesAll21 sales
Days on market median143434
Discount from original list average3.3%5.3%5.0%
Price cut before sale33%44%43%
Seller paid closing costs or repairs67%72%71%

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 Saxony.

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 $380,004; median $382,500; standard deviation $63,988; middle half (25th–75th percentile) $355,950–$415,428; lowest $250,000, highest $530,000. 16 sales had a seller payment; their median payment was $6,600.

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 $180; median $180; standard deviation $28; middle half (25th–75th percentile) $164–$199; lowest $120, highest $225.

8.1.3 Living area

In simple terms
The heated and cooled space, as listed in the MLS. Garages and porches are not counted.
Statistically
RESO LivingArea, in square feet. Sales under 400 SF are treated as entry errors and left out.
The data
22 resale sales. Average 2,125; median 2,067; standard deviation 274; middle half (25th–75th percentile) 1,981–2,346; lowest 1,678, highest 2,682.

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 1992; median 1992; standard deviation 5; middle half (25th–75th percentile) 1990–1994; lowest 1984, highest 2004.

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 38; median 27; standard deviation 39; middle half (25th–75th percentile) 8–56; lowest 1, highest 152. 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
22 resale sales. Average 5.1%; median 5.8%; standard deviation 4.8%; middle half (25th–75th percentile) 1.8%–7.0%; lowest −2.8%, highest 20.3%. 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
10 of 22 resale sales (45.5%).

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
16 of 22 resale sales (72.7%).

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
3 sales with a view, 18 without, 1 unclassified. Most common View entries: Neighborhood 10, None 9, Pool 2, See Remarks 1, Park/Greenbelt 1, Trees/Woods 1, Garden 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 = Pflugerville, SubdivisionName contains any of “saxony”, “brookhollow” (case-insensitive). A record is kept when its subdivision name belongs to the Saxony family, the same rule comparable sales use (it includes Brookhollow Sec 01, proven adjacent and priced alike).
The data
Pulled October 26, 2026: 22 closed Saxony records over the prior year, in ZIP 78660. 2 subdivision spellings kept: Saxony (19); Brookhollow Sec 01 (3). 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 16 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 $359K”.
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 $359K: $250,000–$355,000 (6 sales); $359K–$377K: $358,800–$377,000 (5 sales); $388K–$409K: $388,000–$409,000 (5 sales); Over $409K: $417,570–$530,000 (6 sales)
Quartiles by living area: Under 1,983 SF: 1,678–1,980 SF (6 sales); 1,983–2,056 SF: 1,983–2,056 SF (5 sales); 2,078–2,336 SF: 2,078–2,336 SF (5 sales); Over 2,336 SF: 2,349–2,682 SF (6 sales)
Quartiles by year built: Before 1991: 1984–1989 (6 sales); 1991–1992: 1991–1992 (7 sales); 1993: 1993–1993 (3 sales); After 1993: 1994–2004 (6 sales)
View and no view: View: MLS lists a view (3 sales); No view: None or Neighborhood (18 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 $380,004, median $382,500. Days on market: average 38, median 27: 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 = 5.9030.1164p < 0.0063Unclearε² = 0.281large
Living areaKruskal–WallisH = 4.7730.1891p < 0.0063Unclearε² = 0.227large
Year builtKruskal–WallisH = 1.6430.6509p < 0.0063Unclearε² = 0.078medium
Days on marketKruskal–WallisH = 0.3930.9418p < 0.0063Unclearε² = 0.019small
Discount from original listKruskal–WallisH = 0.6030.8954p < 0.0063Unclearε² = 0.029small
Price cut before saleChi-squareχ² = 0.8930.8273p < 0.0063UnclearCramér’s V = 0.201small
Seller paid closing costs or repairsChi-squareχ² = 7.2130.0655p < 0.0063UnclearCramér’s V = 0.573large
Has a viewChi-squareχ² = 3.8930.2741p < 0.0063UnclearCramér’s V = 0.420medium

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 5.8030.1220p < 0.0063Unclearε² = 0.276large
Net price per SFKruskal–WallisH = 3.2730.3519p < 0.0063Unclearε² = 0.156large
Year builtKruskal–WallisH = 1.8330.6092p < 0.0063Unclearε² = 0.087medium
Days on marketKruskal–WallisH = 2.2730.5183p < 0.0063Unclearε² = 0.108medium
Discount from original listKruskal–WallisH = 1.3930.7076p < 0.0063Unclearε² = 0.066medium
Price cut before saleChi-squareχ² = 5.1930.1581p < 0.0063UnclearCramér’s V = 0.486medium
Seller paid closing costs or repairsChi-squareχ² = 3.5130.3190p < 0.0063UnclearCramér’s V = 0.400medium
Has a viewChi-squareχ² = 1.0530.7880p < 0.0063UnclearCramér’s V = 0.219small

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.