ALEX · Alexander Tiffany Southwest, LLC – ALEX Companies

Wood Glen

Round Rock, TX 78681
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 · 5:44 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
$607,000
average $633,906
Median net price per SF
$213
average $209
Median days on market
41 days
average 90 days
1. SummaryResale homes · 29 sales · October 26, 2025 – October 25, 2026

This study looks at the 29 resale homes sold in Wood Glen in the 365 days to October 25, 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 $535K · 7 sales$535K–$605K · 7 sales$607K–$712K · 8 salesOver $712K · 7 sales
3. Quartiles by net sale priceResale homes · 29 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.

2026-10-26T05:44:23.234317 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 8 7 29 sales Sales per group Under $535K: 7 sales (24%) $535K–$605K: 7 sales (24%) $607K–$712K: 8 sales (28%) Over $712K: 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 $535K$535K–$605K$607K–$712KOver $712K
Higher-priced homes Over $712K
  • Are much larger.
Lower-priced homes Under $535K
  • 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 $535K$535K–$605K$607K–$712KOver $712KReal difference?
Net price per SF$208 per SF$197 per SF$206 per SF$224 per SFunclear
Living area2,200 SFSmallest3,029 SF3,169 SF3,767 SFLargest✓ large
Year built1999199819992000unclear
Days on market62 days43 days40 days20 daysunclear
Discount from original list5.6%8.4%5.8%2.7%unclear
Price cut before sale29%57%38%29%unclear
Seller paid closing costs or repairs57%71%88%71%unclear
Has a view0%57%12%43%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

2026-10-26T05:44:23.262148 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $535K 7 sales $535K– $605K 7 sales $607K– $712K 8 sales Over $712K 7 sales $0 $100 $200 $208 $197 $206 $224 Net price per SF, average

The average is $224 per SF for homes over $712K and $208 per SF for homes under $535K. It does not move in a straight line; homes over $712K are highest. Defined in 8.1.2.

– No clear difference · could be chance

3.4 Homes over $712K are about 1,570 SF (71%) larger than homes under $535K

2026-10-26T05:44:23.283791 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $535K 7 sales $535K– $605K 7 sales $607K– $712K 8 sales Over $712K 7 sales 0 2,000 4,000 2,200 3,029 3,169 3,767 Living area (SF), average

The average is 3,767 SF for homes over $712K and 2,200 SF for homes under $535K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.

✓ Real difference · large

3.5 Year built: no clear difference

2026-10-26T05:44:23.306126 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $535K 7 sales $535K– $605K 7 sales $607K– $712K 8 sales Over $712K 7 sales 1996 1998 2000 1999 1998 1999 2000 Year built: median (dot) and middle half (bar)

The median is 2000 for homes over $712K and 1999 for homes under $535K. It does not move in a straight line; homes over $712K are highest. Defined in 8.1.4.

– No clear difference · could be chance

3.6 Days on market: no clear difference

2026-10-26T05:44:23.327910 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $535K 7 sales $535K– $605K 7 sales $607K– $712K 8 sales Over $712K 7 sales 0 20 40 60 62 43 40 20 Days on market, median

The median is 20 days for homes over $712K and 62 days for homes under $535K. It falls step by step from the lowest range to the highest. Defined in 8.1.5.

– No clear difference · could be chance

3.7 Discount from original list: no clear difference

2026-10-26T05:44:23.350555 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under $535K 7 sales $535K– $605K 7 sales $607K– $712K 8 sales Over $712K 7 sales 0.0% 5.0% 10.0% 5.6% 8.4% 5.8% 2.7% Discount from original list, average

The average is 2.7% for homes over $712K and 5.6% for homes under $535K. It does not move in a straight line; homes $535K–$605K 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

2026-10-26T05:44:23.379826 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% 29 57 0 57 71 57 38 88 12 29 71 43 Under $535K $535K–$605K $607K–$712K Over $712K

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

  • 29% of homes over $712K had a price cut before sale, against 29% of homes under $535K. Defined in 8.1.7.
  • 71% of homes over $712K had the seller pay closing costs or repairs, against 57% of homes under $535K. Defined in 8.1.8.
  • 43% of homes over $712K have a view, against 0% of homes under $535K. 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 $535K7 sales$535K–$605K7 sales$607K–$712K8 salesOver $712K7 salesAll29 salesReal difference?
Net sale price average$456,339$578,533$652,852$845,194$633,906by design
Net price per SF average$208$197$206$224$209unclear
Living area average2,2003,0293,1693,7673,046✓ large
Year built median19991998199920001999unclear

3.10 The numbers: selling

Under $535K7 sales$535K–$605K7 sales$607K–$712K8 salesOver $712K7 salesAll29 salesReal difference?
Days on market median6243402041unclear
Discount from original list average5.6%8.4%5.8%2.7%5.6%unclear
Price cut before sale29%57%38%29%38%unclear
Seller paid closing costs or repairs57%71%88%71%72%unclear
Has a view0%57%12%43%28%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 26, 2025 – October 25, 2026

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

2026-10-26T05:44:23.399928 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 7 8 7 29 sales Sales per group Under 2,418 SF: 7 sales (24%) 2,418–3,084 SF: 7 sales (24%) 3,155–3,459 SF: 8 sales (28%) Over 3,459 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 2,418 SF2,418–3,084 SF3,155–3,459 SFOver 3,459 SF
Larger homes Over 3,459 SF
  • Sell for much more.
Smaller homes Under 2,418 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 2,418 SF2,418–3,084 SF3,155–3,459 SFOver 3,459 SFReal difference?
Net sale price$487KLowest$585K$664K$795KHighest✓ large
Net price per SF$224 per SF$206 per SF$201 per SF$206 per SFunclear
Year built1999199720002000unclear
Days on market43 days25 days128 days20 daysunclear
Discount from original list3.1%5.9%6.6%6.6%unclear
Price cut before sale29%29%62%29%unclear
Seller paid closing costs or repairs57%86%75%71%unclear
Has a view14%14%25%57%unclear

4.3 Homes over 3,459 SF sell for about $309K (63%) more than homes under 2,418 SF

2026-10-26T05:44:23.420427 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,418 SF 7 sales 2,418– 3,084 SF 7 sales 3,155– 3,459 SF 8 sales Over 3,459 SF 7 sales $0K $250K $500K $750K $487K $585K $664K $795K Net sale price, average

The average is $795K for homes over 3,459 SF and $487K for homes under 2,418 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.

✓ Real difference · large

4.4 Net price per SF: no clear difference

2026-10-26T05:44:23.443001 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,418 SF 7 sales 2,418– 3,084 SF 7 sales 3,155– 3,459 SF 8 sales Over 3,459 SF 7 sales $0 $100 $200 $224 $206 $201 $206 Net price per SF, average

The average is $206 per SF for homes over 3,459 SF and $224 per SF for homes under 2,418 SF. It does not move in a straight line; homes under 2,418 SF are highest. Defined in 8.1.2.

– No clear difference · could be chance

4.5 Year built: no clear difference

2026-10-26T05:44:23.465687 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,418 SF 7 sales 2,418– 3,084 SF 7 sales 3,155– 3,459 SF 8 sales Over 3,459 SF 7 sales 1996 1998 2000 1999 1997 2000 2000 Year built: median (dot) and middle half (bar)

The median is 2000 for homes over 3,459 SF and 1999 for homes under 2,418 SF. It does not move in a straight line; homes over 3,459 SF are highest. Defined in 8.1.4.

– No clear difference · could be chance

4.6 Days on market: no clear difference

2026-10-26T05:44:23.487668 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,418 SF 7 sales 2,418– 3,084 SF 7 sales 3,155– 3,459 SF 8 sales Over 3,459 SF 7 sales 0 50 100 150 43 25 128 20 Days on market, median

The median is 20 days for homes over 3,459 SF and 43 days for homes under 2,418 SF. It does not move in a straight line; homes 3,155–3,459 SF are highest. Defined in 8.1.5.

– No clear difference · could be chance

4.7 Discount from original list: no clear difference

2026-10-26T05:44:23.509341 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Under 2,418 SF 7 sales 2,418– 3,084 SF 7 sales 3,155– 3,459 SF 8 sales Over 3,459 SF 7 sales 0.0% 2.0% 4.0% 6.0% 3.1% 5.9% 6.6% 6.6% Discount from original list, average

The average is 6.6% for homes over 3,459 SF and 3.1% for homes under 2,418 SF. It does not move in a straight line; homes 3,155–3,459 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

2026-10-26T05:44:23.535487 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% 29 57 14 29 86 14 62 75 25 29 71 57 Under 2,418 SF 2,418–3,084 SF 3,155–3,459 SF Over 3,459 SF

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

  • 29% of homes over 3,459 SF had a price cut before sale, against 29% of homes under 2,418 SF. Defined in 8.1.7.
  • 71% of homes over 3,459 SF had the seller pay closing costs or repairs, against 57% of homes under 2,418 SF. Defined in 8.1.8.
  • 57% of homes over 3,459 SF have a view, against 14% of homes under 2,418 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 2,418 SF7 sales2,418–3,084 SF7 sales3,155–3,459 SF8 salesOver 3,459 SF7 salesAll29 salesReal difference?
Net sale price average$486,629$584,755$664,479$795,394$633,906✓ large
Net price per SF average$224$206$201$206$209unclear
Living area average2,1682,8393,3013,8393,046by design
Year built median19991997200020001999unclear

4.10 The numbers: selling

Under 2,418 SF7 sales2,418–3,084 SF7 sales3,155–3,459 SF8 salesOver 3,459 SF7 salesAll29 salesReal difference?
Days on market median43251282041unclear
Discount from original list average3.1%5.9%6.6%6.6%5.6%unclear
Price cut before sale29%29%62%29%38%unclear
Seller paid closing costs or repairs57%86%75%71%72%unclear
Has a view14%14%25%57%28%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 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.

2026-10-26T05:44:23.555906 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 7 9 7 6 29 sales Sales per group Before 1998: 7 sales (24%) 1998–1999: 9 sales (31%) 2000: 7 sales (24%) After 2000: 6 sales (21%)
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 19981998–19992000After 2000Real difference?
Net sale price$594K$591K$687K$682Kunclear
Net price per SF$195 per SF$207 per SF$217 per SF$219 per SFunclear
Living area3,048 SF2,859 SF3,157 SF3,194 SFunclear
Days on market41 days20 days114 days28 daysunclear
Discount from original list7.3%6.4%2.5%6.1%unclear
Price cut before sale43%33%29%50%unclear
Seller paid closing costs or repairs71%56%71%100%unclear
Has a view14%22%29%50%unclear

5.3 Net sale price: no clear difference

2026-10-26T05:44:23.576270 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1998 7 sales 1998– 1999 9 sales 2000 7 sales After 2000 6 sales $0K $250K $500K $750K $594K $591K $687K $682K Net sale price, average

The average is $682K for homes built after 2000 and $594K for homes built before 1998. It does not move in a straight line; homes built 2000 are highest. Defined in 8.1.1.

– No clear difference · could be chance

5.4 Net price per SF: no clear difference

2026-10-26T05:44:23.598900 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1998 7 sales 1998– 1999 9 sales 2000 7 sales After 2000 6 sales $0 $100 $200 $195 $207 $217 $219 Net price per SF, average

The average is $219 per SF for homes built after 2000 and $195 per SF for homes built before 1998. It rises step by step from the lowest range to the highest. Defined in 8.1.2.

– No clear difference · could be chance

5.5 Living area: no clear difference

2026-10-26T05:44:23.619667 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1998 7 sales 1998– 1999 9 sales 2000 7 sales After 2000 6 sales 0 1,000 2,000 3,000 3,048 2,859 3,157 3,194 Living area (SF), average

The average is 3,194 SF for homes built after 2000 and 3,048 SF for homes built before 1998. It does not move in a straight line; homes built after 2000 are highest. Defined in 8.1.3.

– No clear difference · could be chance

5.6 Days on market: no clear difference

2026-10-26T05:44:23.640785 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1998 7 sales 1998– 1999 9 sales 2000 7 sales After 2000 6 sales 0 50 100 41 20 114 28 Days on market, median

The median is 28 days for homes built after 2000 and 41 days for homes built before 1998. It does not move in a straight line; homes built 2000 are highest. Defined in 8.1.5.

– No clear difference · could be chance

5.7 Discount from original list: no clear difference

2026-10-26T05:44:23.664223 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Before 1998 7 sales 1998– 1999 9 sales 2000 7 sales After 2000 6 sales 0.0% 2.5% 5.0% 7.5% 7.3% 6.4% 2.5% 6.1% Discount from original list, average

The average is 6.1% for homes built after 2000 and 7.3% for homes built before 1998. It does not move in a straight line; homes built before 1998 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

2026-10-26T05:44:23.689346 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 33 56 22 29 71 29 50 100 50 Before 1998 1998–1999 2000 After 2000

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

  • 50% of homes built after 2000 had a price cut before sale, against 43% of homes built before 1998. Defined in 8.1.7.
  • 100% of homes built after 2000 had the seller pay closing costs or repairs, against 71% of homes built before 1998. Defined in 8.1.8.
  • 50% of homes built after 2000 have a view, against 14% of homes built before 1998. 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 19987 sales1998–19999 sales20007 salesAfter 20006 salesAll29 salesReal difference?
Net sale price average$594,387$590,939$687,445$682,000$633,906unclear
Net price per SF average$195$207$217$219$209unclear
Living area average3,0482,8593,1573,1943,046unclear
Year built median19961999200020021999by design

5.10 The numbers: selling

Before 19987 sales1998–19999 sales20007 salesAfter 20006 salesAll29 salesReal difference?
Days on market median41201142841unclear
Discount from original list average7.3%6.4%2.5%6.1%5.6%unclear
Price cut before sale43%33%29%50%38%unclear
Seller paid closing costs or repairs71%56%71%100%72%unclear
Has a view14%22%29%50%28%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 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.

2026-10-26T05:44:23.707019 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 8 20 28 sales Sales per group View: 8 sales (29%) No view: 20 sales (71%)
Bottom line: no measure differs enough between the groups to rule out chance.

6.1 Key differences

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

6.2 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.

ViewNo viewReal difference?
Net sale price$705K$615Kunclear
Net price per SF$209 per SF$210 per SFunclear
Living area3,404 SF2,939 SFunclear
Year built20001999unclear
Days on market68 days30 daysunclear
Discount from original list6.9%5.3%unclear
Price cut before sale62%30%unclear
Seller paid closing costs or repairs75%75%unclear

6.3 Net sale price: no clear difference

2026-10-26T05:44:23.723425 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales $0K $200K $400K $600K $800K $705K $615K Net sale price, average

The average is $705K for homes with a view and $615K for homes without a view. Defined in 8.1.1.

– No clear difference · could be chance

6.4 Net price per SF: no clear difference

2026-10-26T05:44:23.741259 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales $0 $100 $200 $209 $210 Net price per SF, average

The average is $209 per SF for homes with a view and $210 per SF for homes without a view. Defined in 8.1.2.

– No clear difference · could be chance

6.5 Living area: no clear difference

2026-10-26T05:44:23.759539 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales 0 1,000 2,000 3,000 4,000 3,404 2,939 Living area (SF), average

The average is 3,404 SF for homes with a view and 2,939 SF for homes without a view. Defined in 8.1.3.

– No clear difference · could be chance

6.6 Year built: no clear difference

2026-10-26T05:44:23.800923 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales 1997 1998 1999 2000 2001 2000 1999 Year built: median (dot) and middle half (bar)

The median is 2000 for homes with a view and 1999 for homes without a view. Defined in 8.1.4.

– No clear difference · could be chance

6.7 Days on market: no clear difference

2026-10-26T05:44:23.819194 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales 0 20 40 60 80 68 30 Days on market, median

The median is 68 days for homes with a view and 30 days for homes without a view. Defined in 8.1.5.

– No clear difference · could be chance

6.8 Discount from original list: no clear difference

2026-10-26T05:44:23.838247 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ View 8 sales No view 20 sales 0.0% 2.0% 4.0% 6.0% 8.0% 6.9% 5.3% Discount from original list, average

The average is 6.9% for homes with a view and 5.3% for homes without a view. Defined in 8.1.6.

– No clear difference · could be chance

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

2026-10-26T05:44:23.856720 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ Price cut Seller paid costs or repairs 0% 25% 50% 75% 100% 62 75 30 75 View No view

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

  • 62% of homes with a view had a price cut before sale, against 30% of homes without a view. Defined in 8.1.7.
  • 75% of homes with a view had the seller pay closing costs or repairs, against 75% of homes without a view. Defined in 8.1.8.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance

6.10 The numbers: price and size

View8 salesNo view20 salesAll28 salesReal difference?
Net sale price average$705,283$614,781$640,638unclear
Net price per SF average$209$210$210unclear
Living area average3,4042,9393,072unclear
Year built median200019991999unclear

6.11 The numbers: selling

View8 salesNo view20 salesAll28 salesReal difference?
Days on market median683040unclear
Discount from original list average6.9%5.3%5.8%unclear
Price cut before sale62%30%39%unclear
Seller paid closing costs or repairs75%75%75%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 8.3.4.

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 Wood Glen.

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
29 resale sales. Average $633,906; median $607,000; standard deviation $150,667; middle half (25th–75th percentile) $534,730–$712,500; lowest $404,000, highest $980,700. 21 sales had a seller payment; their median payment was $7,300.

8.1.2 Net price per SF

In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
29 resale sales. Average $209; median $213; standard deviation $25; middle half (25th–75th percentile) $194–$225; lowest $152, highest $262.

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 3,046; median 3,155; standard deviation 655; middle half (25th–75th percentile) 2,418–3,459; lowest 1,889, highest 4,332.

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 1999; median 1999; standard deviation 2; middle half (25th–75th percentile) 1998–2000; lowest 1996, highest 2005.

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 90; median 41; standard deviation 108; middle half (25th–75th percentile) 14–128; lowest 1, highest 430. 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 5.6%; median 3.6%; standard deviation 6.7%; middle half (25th–75th percentile) 0.3%–7.0%; lowest −1.1%, highest 23.6%. 5 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
11 of 29 resale sales (37.9%).

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
21 of 29 resale sales (72.4%).

8.1.9 Has a view

In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
8 sales with a view, 20 without, 1 unclassified. Most common View entries: None 15, Neighborhood 5, Trees/Woods 4, Park/Greenbelt 3, Pool 2, Panoramic 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 = Round Rock, SubdivisionName contains any of “wood glen”, “woodglen” (case-insensitive). A record is kept when its subdivision name belongs to the Wood Glen family, the same rule comparable sales use.
The data
Pulled October 26, 2026: 29 closed Wood Glen records over the prior year, in ZIP 78681. 15 subdivision spellings kept, the most common: Wood Glen Sec 01 Ph 01-A Amd (7); Wood Glen (5); Wood Glen Sec 04 Ph 02 (3); Wood Glen Sec 05 Ph 02 (2); Wood Glen Sec 06 (2); Wood Glen Sec 3 (1); Wood Glen Sec I Ph 02 (1); Wood Glen Sec 02 Ph 01 (1); Wood Glen Sec 03 (1); Wood Glen Sec 01 Ph 02 (1); WOOD GLEN SEC 1 PH 2 (1); Wood Glen Sec I Ph I-B (1); and 3 more (3 records). 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 26, 2025 to October 25, 2026 inclusive.
The data
29 single-family sales in the window: 29 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
29 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 $535K”.
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 $535K: $404,000–$501,830 (7 sales); $535K–$605K: $534,730–$605,000 (7 sales); $607K–$712K: $607,000–$712,500 (8 sales); Over $712K: $722,000–$980,700 (7 sales)
Quartiles by living area: Under 2,418 SF: 1,889–2,407 SF (7 sales); 2,418–3,084 SF: 2,418–3,084 SF (7 sales); 3,155–3,459 SF: 3,155–3,459 SF (8 sales); Over 3,459 SF: 3,516–4,332 SF (7 sales)
Quartiles by year built: Before 1998: 1996–1997 (7 sales); 1998–1999: 1998–1999 (9 sales); 2000: 2000–2000 (7 sales); After 2000: 2001–2005 (6 sales)
View and no view: View: MLS lists a view (8 sales); No view: None or Neighborhood (20 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 $633,906, median $607,000. Days on market: average 90, median 41: 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; View and no view: m = 8, threshold p < 0.0063

8.2.11 Size of a difference

In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
2 real differences across the four slices; sizes are listed in 8.3.

8.2.12 Rounding in the text

In simple terms
Headings and sentences round figures so they read easily; the tables at the end of each section give them in full.
Statistically
Prices in headings round to the nearest $1K; price per SF and days on market to the nearest whole number; living area to the nearest 10 SF; shares and percentage gaps to whole percents.
The data
Days on market is always shown in days.

8.3 Test results

Every test behind every gold box. Statistic, degrees of freedom (df), p-value, the threshold it must beat, and the size of the difference.

8.3.1 Quartiles by net sale price

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net price per SFKruskal–WallisH = 4.9430.1760p < 0.0063Unclearε² = 0.177large
Living areaKruskal–WallisH = 18.8430.0003p < 0.0063Yesε² = 0.673large
Year builtKruskal–WallisH = 2.1330.5452p < 0.0063Unclearε² = 0.076medium
Days on marketKruskal–WallisH = 0.4430.9326p < 0.0063Unclearε² = 0.016small
Discount from original listKruskal–WallisH = 1.4530.6946p < 0.0063Unclearε² = 0.052small
Price cut before saleChi-squareχ² = 1.6230.6551p < 0.0063UnclearCramér’s V = 0.236small
Seller paid closing costs or repairsChi-squareχ² = 1.7430.6291p < 0.0063UnclearCramér’s V = 0.245small
Has a viewChi-squareχ² = 7.4630.0587p < 0.0063UnclearCramér’s V = 0.507large

8.3.2 Quartiles by living area

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 15.1130.0017p < 0.0063Yesε² = 0.540large
Net price per SFKruskal–WallisH = 3.5730.3112p < 0.0063Unclearε² = 0.128medium
Year builtKruskal–WallisH = 4.1230.2487p < 0.0063Unclearε² = 0.147large
Days on marketKruskal–WallisH = 2.3330.5071p < 0.0063Unclearε² = 0.083medium
Discount from original listKruskal–WallisH = 1.5430.6735p < 0.0063Unclearε² = 0.055small
Price cut before saleChi-squareχ² = 2.8330.4182p < 0.0063UnclearCramér’s V = 0.313medium
Seller paid closing costs or repairsChi-squareχ² = 1.4730.6898p < 0.0063UnclearCramér’s V = 0.225small
Has a viewChi-squareχ² = 4.3330.2282p < 0.0063UnclearCramér’s V = 0.386medium

8.3.3 Quartiles by year built

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceKruskal–WallisH = 2.8130.4223p < 0.0063Unclearε² = 0.100medium
Net price per SFKruskal–WallisH = 4.9430.1764p < 0.0063Unclearε² = 0.176large
Living areaKruskal–WallisH = 0.7430.8644p < 0.0063Unclearε² = 0.026small
Days on marketKruskal–WallisH = 1.6130.6579p < 0.0063Unclearε² = 0.057small
Discount from original listKruskal–WallisH = 1.6630.6458p < 0.0063Unclearε² = 0.059small
Price cut before saleChi-squareχ² = 0.7830.8531p < 0.0063UnclearCramér’s V = 0.164small
Seller paid closing costs or repairsChi-squareχ² = 3.5730.3114p < 0.0063UnclearCramér’s V = 0.351medium
Has a viewChi-squareχ² = 2.2630.5199p < 0.0063UnclearCramér’s V = 0.279small

8.3.4 View and no view

MeasureTestStatisticdfp-valueThresholdReal difference?Effect sizeSize
Net sale priceMann–Whitney UU = 99.00—0.3542p < 0.0063Unclearrank-biserial r = 0.238small
Net price per SFMann–Whitney UU = 85.00—0.8227p < 0.0063Unclearrank-biserial r = 0.062negligible
Living areaMann–Whitney UU = 117.00—0.0625p < 0.0063Unclearrank-biserial r = 0.462medium
Year builtMann–Whitney UU = 106.50—0.1797p < 0.0063Unclearrank-biserial r = 0.331medium
Days on marketMann–Whitney UU = 95.50—0.4454p < 0.0063Unclearrank-biserial r = 0.194small
Discount from original listMann–Whitney UU = 91.50—0.5758p < 0.0063Unclearrank-biserial r = 0.144small
Price cut before saleChi-squareχ² = 2.5310.1117p < 0.0063UnclearCramér’s V = 0.301medium
Seller paid closing costs or repairsChi-squareχ² = 0.0011.0000p < 0.0063UnclearCramér’s V = 0.000negligible

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 29 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.