Clay's Almanac
WNBA · June 1, 2026
Almanac — change team skin

Repaints the site's chrome in a team's colours. Predictions, grades and the colours on each game card are unchanged.

Almanac
NBA
WNBA
Log in Join

← Back to WNBA

Seattle Storm at Dallas Wings

SEA 56 – DAL 79

June 1, 2026 · Final

Coach Sarah Watanabe

Best model for this game

Coach Sarah Watanabe
All models: 12-0
Prediction ranges

In 95 out of 100 simulated runs, each team scored inside its band below — this is about where the final score lands, not a claim about the average.

In 90 out of 100 simulated runs, each team scored inside its band below — this is about where the final score lands, not a claim about the average.

In 85 out of 100 simulated runs, each team scored inside its band below — this is about where the final score lands, not a claim about the average.

In 80 out of 100 simulated runs, each team scored inside its band below — this is about where the final score lands, not a claim about the average.

In 75 out of 100 simulated runs, each team scored inside its band below — this is about where the final score lands, not a claim about the average.

Confidence level for SEA at DAL

All 12 models’ predicted scores

SEA — one dot per model DAL — one dot per model Actual: SEA 56, DAL 79
Vince Chambers
SEA 79.4–84.4 DAL 81.0–86.0 Overlap 3.4 pts Actual: SEA 56, DAL 79

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 83.5) over Seattle Storm (avg. 81.9) — by 1.6 points. The ranges overlap almost entirely, so one game could go either way.

SEA 79.8–84.0 DAL 81.4–85.6 Overlap 2.6 pts Actual: SEA 56, DAL 79

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 83.5) over Seattle Storm (avg. 81.9) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

SEA 80.1–83.7 DAL 81.6–85.3 Overlap 2.08 pts Actual: SEA 56, DAL 79

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 83.5) over Seattle Storm (avg. 81.9) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

SEA 80.3–83.5 DAL 81.8–85.1 Overlap 1.68 pts Actual: SEA 56, DAL 79

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 83.5) over Seattle Storm (avg. 81.9) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

SEA 80.4–83.3 DAL 82.0–84.9 Overlap 1.35 pts Actual: SEA 56, DAL 79

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 83.5) over Seattle Storm (avg. 81.9) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Vince Chambers (#1)
t-statistic
-9.41
p-value
3.19e-17

A low p-value means the two teams' average scores are statistically distinguishable — even when their ranges above overlap. Overlap describes where the final score could land; the test above is about whether the two averages differ. They are different claims, and either can hold without the other.

Reg
SEA 79.5–84.0 DAL 80.7–86.1 Overlap 3.32 pts Actual: SEA 56, DAL 79

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.7) — by 1.7 points. The ranges overlap almost entirely, so one game could go either way.

SEA 79.8–83.6 DAL 81.1–85.7 Overlap 2.52 pts Actual: SEA 56, DAL 79

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.7) — by 1.7 points. The ranges overlap some — there's real uncertainty here.

SEA 80.1–83.4 DAL 81.4–85.4 Overlap 2.0 pts Actual: SEA 56, DAL 79

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.7) — by 1.7 points. The ranges overlap some — there's real uncertainty here.

SEA 80.3–83.2 DAL 81.6–85.2 Overlap 1.59 pts Actual: SEA 56, DAL 79

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.7) — by 1.7 points. The ranges overlap some — there's real uncertainty here.

SEA 80.4–83.1 DAL 81.8–85.0 Overlap 1.26 pts Actual: SEA 56, DAL 79

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.7) — by 1.7 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Reg (#2)
t-statistic
-9.95
p-value
1.33e-18

A low p-value means the two teams' average scores are statistically distinguishable — even when their ranges above overlap. Overlap describes where the final score could land; the test above is about whether the two averages differ. They are different claims, and either can hold without the other.

Dr. Wallace
SEA 80.0–84.0 DAL 81.1–85.7 Overlap 2.85 pts Actual: SEA 56, DAL 79

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 82.0) — by 1.4 points. The ranges overlap some — there's real uncertainty here.

SEA 80.3–83.6 DAL 81.5–85.3 Overlap 2.16 pts Actual: SEA 56, DAL 79

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 82.0) — by 1.4 points. The ranges overlap some — there's real uncertainty here.

SEA 80.5–83.4 DAL 81.7–85.1 Overlap 1.71 pts Actual: SEA 56, DAL 79

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 82.0) — by 1.4 points. The ranges overlap some — there's real uncertainty here.

SEA 80.7–83.3 DAL 81.9–84.9 Overlap 1.37 pts Actual: SEA 56, DAL 79

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 82.0) — by 1.4 points. The ranges overlap some — there's real uncertainty here.

SEA 80.8–83.1 DAL 82.1–84.8 Overlap 1.08 pts Actual: SEA 56, DAL 79

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 82.0) — by 1.4 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Dr. Wallace (#3)
t-statistic
-9.94
p-value
1.31e-18

A low p-value means the two teams' average scores are statistically distinguishable — even when their ranges above overlap. Overlap describes where the final score could land; the test above is about whether the two averages differ. They are different claims, and either can hold without the other.

Kevin
SEA 79.8–84.0 DAL 81.1–85.8 Overlap 2.87 pts Actual: SEA 56, DAL 79

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.9) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

SEA 80.1–83.6 DAL 81.5–85.4 Overlap 2.16 pts Actual: SEA 56, DAL 79

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.9) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

SEA 80.3–83.4 DAL 81.7–85.2 Overlap 1.69 pts Actual: SEA 56, DAL 79

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.9) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

SEA 80.5–83.2 DAL 81.9–85.0 Overlap 1.33 pts Actual: SEA 56, DAL 79

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.9) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

SEA 80.6–83.1 DAL 82.1–84.8 Overlap 1.04 pts Actual: SEA 56, DAL 79

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.9) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Kevin (#4)
t-statistic
-10.51
p-value
3.10e-20

A low p-value means the two teams' average scores are statistically distinguishable — even when their ranges above overlap. Overlap describes where the final score could land; the test above is about whether the two averages differ. They are different claims, and either can hold without the other.

Dr. Lila Shah
SEA 79.7–83.5 DAL 80.2–84.7 Overlap 3.27 pts Actual: SEA 56, DAL 79

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 82.5) over Seattle Storm (avg. 81.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

SEA 80.0–83.2 DAL 80.6–84.4 Overlap 2.61 pts Actual: SEA 56, DAL 79

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 82.5) over Seattle Storm (avg. 81.6) — by under a point. The ranges overlap some — there's real uncertainty here.

SEA 80.2–83.0 DAL 80.8–84.1 Overlap 2.17 pts Actual: SEA 56, DAL 79

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 82.5) over Seattle Storm (avg. 81.6) — by under a point. The ranges overlap some — there's real uncertainty here.

SEA 80.4–82.8 DAL 81.0–83.9 Overlap 1.84 pts Actual: SEA 56, DAL 79

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 82.5) over Seattle Storm (avg. 81.6) — by under a point. The ranges overlap some — there's real uncertainty here.

SEA 80.5–82.7 DAL 81.2–83.8 Overlap 1.56 pts Actual: SEA 56, DAL 79

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 82.5) over Seattle Storm (avg. 81.6) — by under a point. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
-6.22
p-value
3.88e-09

A low p-value means the two teams' average scores are statistically distinguishable — even when their ranges above overlap. Overlap describes where the final score could land; the test above is about whether the two averages differ. They are different claims, and either can hold without the other.

Ice
SEA 79.8–83.7 DAL 80.8–85.3 Overlap 2.87 pts Actual: SEA 56, DAL 79

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 83.0) over Seattle Storm (avg. 81.7) — by 1.3 points. The ranges overlap some — there's real uncertainty here.

SEA 80.1–83.4 DAL 81.2–84.9 Overlap 2.2 pts Actual: SEA 56, DAL 79

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 83.0) over Seattle Storm (avg. 81.7) — by 1.3 points. The ranges overlap some — there's real uncertainty here.

SEA 80.3–83.2 DAL 81.4–84.7 Overlap 1.76 pts Actual: SEA 56, DAL 79

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 83.0) over Seattle Storm (avg. 81.7) — by 1.3 points. The ranges overlap some — there's real uncertainty here.

SEA 80.4–83.0 DAL 81.6–84.5 Overlap 1.42 pts Actual: SEA 56, DAL 79

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 83.0) over Seattle Storm (avg. 81.7) — by 1.3 points. The ranges overlap some — there's real uncertainty here.

SEA 80.6–82.9 DAL 81.7–84.3 Overlap 1.14 pts Actual: SEA 56, DAL 79

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 83.0) over Seattle Storm (avg. 81.7) — by 1.3 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Ice (#6)
t-statistic
-9.34
p-value
5.32e-17

A low p-value means the two teams' average scores are statistically distinguishable — even when their ranges above overlap. Overlap describes where the final score could land; the test above is about whether the two averages differ. They are different claims, and either can hold without the other.

Jamal
SEA 79.9–84.0 DAL 81.1–85.7 Overlap 2.84 pts Actual: SEA 56, DAL 79

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.9) — by 1.5 points. The ranges overlap some — there's real uncertainty here.

SEA 80.2–83.6 DAL 81.5–85.4 Overlap 2.14 pts Actual: SEA 56, DAL 79

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.9) — by 1.5 points. The ranges overlap some — there's real uncertainty here.

SEA 80.4–83.4 DAL 81.7–85.1 Overlap 1.68 pts Actual: SEA 56, DAL 79

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.9) — by 1.5 points. The ranges overlap some — there's real uncertainty here.

SEA 80.6–83.3 DAL 81.9–84.9 Overlap 1.33 pts Actual: SEA 56, DAL 79

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.9) — by 1.5 points. The ranges overlap some — there's real uncertainty here.

SEA 80.7–83.1 DAL 82.1–84.8 Overlap 1.04 pts Actual: SEA 56, DAL 79

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 83.4) over Seattle Storm (avg. 81.9) — by 1.5 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Jamal (#7)
t-statistic
-10.32
p-value
1.13e-19

A low p-value means the two teams' average scores are statistically distinguishable — even when their ranges above overlap. Overlap describes where the final score could land; the test above is about whether the two averages differ. They are different claims, and either can hold without the other.

Jordan Tol Warning
SEA 80.1–83.2 DAL 81.1–85.2 Overlap 2.16 pts Actual: SEA 56, DAL 79

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 83.2) over Seattle Storm (avg. 81.6) — by 1.5 points. The ranges overlap some — there's real uncertainty here.

SEA 80.4–82.9 DAL 81.4–84.9 Overlap 1.49 pts Actual: SEA 56, DAL 79

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 83.2) over Seattle Storm (avg. 81.6) — by 1.5 points. The ranges overlap some — there's real uncertainty here.

SEA 80.5–82.8 DAL 81.6–84.7 Overlap 1.2 pts Actual: SEA 56, DAL 79

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 83.2) over Seattle Storm (avg. 81.6) — by 1.5 points. The ranges overlap some — there's real uncertainty here.

SEA 80.7–82.8 DAL 81.8–84.5 Overlap 0.98 pts Actual: SEA 56, DAL 79

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 83.2) over Seattle Storm (avg. 81.6) — by 1.5 points. The ranges barely touch.

SEA 80.8–82.5 DAL 81.9–84.4 Overlap 0.59 pts Actual: SEA 56, DAL 79

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 83.2) over Seattle Storm (avg. 81.6) — by 1.5 points. The ranges barely touch.

Show the math
Model
Jordan (#8)
t-statistic
-11.14
p-value
4.76e-22

A low p-value means the two teams' average scores are statistically distinguishable — even when their ranges above overlap. Overlap describes where the final score could land; the test above is about whether the two averages differ. They are different claims, and either can hold without the other.

Darren "Dimes" Lin
SEA 79.4–84.1 DAL 80.8–85.9 Overlap 3.31 pts Actual: SEA 56, DAL 79

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 83.3) over Seattle Storm (avg. 81.7) — by 1.6 points. The ranges overlap almost entirely, so one game could go either way.

SEA 79.8–83.7 DAL 81.2–85.4 Overlap 2.53 pts Actual: SEA 56, DAL 79

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 83.3) over Seattle Storm (avg. 81.7) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

SEA 80.0–83.4 DAL 81.4–85.2 Overlap 2.02 pts Actual: SEA 56, DAL 79

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 83.3) over Seattle Storm (avg. 81.7) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

SEA 80.2–83.3 DAL 81.6–85.0 Overlap 1.63 pts Actual: SEA 56, DAL 79

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 83.3) over Seattle Storm (avg. 81.7) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

SEA 80.4–83.1 DAL 81.8–84.8 Overlap 1.3 pts Actual: SEA 56, DAL 79

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 83.3) over Seattle Storm (avg. 81.7) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
-9.53
p-value
1.61e-17

A low p-value means the two teams' average scores are statistically distinguishable — even when their ranges above overlap. Overlap describes where the final score could land; the test above is about whether the two averages differ. They are different claims, and either can hold without the other.

Maya Jefferson
SEA 79.7–83.7 DAL 80.7–85.6 Overlap 2.98 pts Actual: SEA 56, DAL 79

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 83.1) over Seattle Storm (avg. 81.7) — by 1.4 points. The ranges overlap some — there's real uncertainty here.

SEA 80.0–83.4 DAL 81.1–85.2 Overlap 2.27 pts Actual: SEA 56, DAL 79

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 83.1) over Seattle Storm (avg. 81.7) — by 1.4 points. The ranges overlap some — there's real uncertainty here.

SEA 80.2–83.1 DAL 81.3–84.9 Overlap 1.81 pts Actual: SEA 56, DAL 79

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 83.1) over Seattle Storm (avg. 81.7) — by 1.4 points. The ranges overlap some — there's real uncertainty here.

SEA 80.4–83.0 DAL 81.5–84.7 Overlap 1.45 pts Actual: SEA 56, DAL 79

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 83.1) over Seattle Storm (avg. 81.7) — by 1.4 points. The ranges overlap some — there's real uncertainty here.

SEA 80.5–82.9 DAL 81.7–84.6 Overlap 1.15 pts Actual: SEA 56, DAL 79

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 83.1) over Seattle Storm (avg. 81.7) — by 1.4 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Maya Jefferson (#10)
t-statistic
-9.66
p-value
8.82e-18

A low p-value means the two teams' average scores are statistically distinguishable — even when their ranges above overlap. Overlap describes where the final score could land; the test above is about whether the two averages differ. They are different claims, and either can hold without the other.

Lexi Tol Warning
SEA 80.2–83.8 DAL 81.1–85.9 Overlap 2.75 pts Actual: SEA 56, DAL 79

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 83.5) over Seattle Storm (avg. 81.8) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

SEA 80.7–83.4 DAL 81.4–85.5 Overlap 1.93 pts Actual: SEA 56, DAL 79

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 83.5) over Seattle Storm (avg. 81.8) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

SEA 80.7–83.1 DAL 81.7–85.3 Overlap 1.39 pts Actual: SEA 56, DAL 79

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 83.5) over Seattle Storm (avg. 81.8) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

SEA 80.8–83.0 DAL 81.9–85.1 Overlap 1.08 pts Actual: SEA 56, DAL 79

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 83.5) over Seattle Storm (avg. 81.8) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

SEA 80.9–82.9 DAL 82.1–84.9 Overlap 0.83 pts Actual: SEA 56, DAL 79

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 83.5) over Seattle Storm (avg. 81.8) — by 1.6 points. The ranges barely touch.

Show the math
Model
Lexi (#11)
t-statistic
-10.41
p-value
5.65e-20

A low p-value means the two teams' average scores are statistically distinguishable — even when their ranges above overlap. Overlap describes where the final score could land; the test above is about whether the two averages differ. They are different claims, and either can hold without the other.

Coach Sarah Watanabe Tol Warning
SEA 80.0–83.7 DAL 82.2–87.2 Overlap 1.56 pts Actual: SEA 56, DAL 79

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 84.7) over Seattle Storm (avg. 81.6) — by 3.1 points. The ranges overlap some — there's real uncertainty here.

SEA 80.2–83.4 DAL 82.6–86.8 Overlap 0.78 pts Actual: SEA 56, DAL 79

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 84.7) over Seattle Storm (avg. 81.6) — by 3.1 points. The ranges barely touch.

SEA 80.3–83.1 DAL 82.8–86.5 Overlap 0.24 pts Actual: SEA 56, DAL 79

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 84.7) over Seattle Storm (avg. 81.6) — by 3.1 points. The ranges barely touch.

SEA 80.4–82.8 DAL 83.0–86.3 No overlap Actual: SEA 56, DAL 79

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 84.7) over Seattle Storm (avg. 81.6) — by 3.1 points. The 80% ranges don't overlap at all — a confident model.

SEA 80.5–82.7 DAL 83.2–86.2 No overlap Actual: SEA 56, DAL 79

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 84.7) over Seattle Storm (avg. 81.6) — by 3.1 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
-19.63
p-value
1.75e-45

A low p-value means the two teams' average scores are statistically distinguishable — even when their ranges above overlap. Overlap describes where the final score could land; the test above is about whether the two averages differ. They are different claims, and either can hold without the other.

View as table
Vince Chambers — SEA at DAL — Actual: SEA 56, DAL 79
Level SEA range DAL range Overlap Tol Warning Actual landed in range?
95% 79.4–84.4 81.0–86.0 3.4 pts — No
90% 79.8–84.0 81.4–85.6 2.6 pts — No
85% 80.1–83.7 81.6–85.3 2.08 pts — No
80% 80.3–83.5 81.8–85.1 1.68 pts — No
75% 80.4–83.3 82.0–84.9 1.35 pts — No
Reg — SEA at DAL — Actual: SEA 56, DAL 79
Level SEA range DAL range Overlap Tol Warning Actual landed in range?
95% 79.5–84.0 80.7–86.1 3.32 pts — No
90% 79.8–83.6 81.1–85.7 2.52 pts — No
85% 80.1–83.4 81.4–85.4 2.0 pts — No
80% 80.3–83.2 81.6–85.2 1.59 pts — No
75% 80.4–83.1 81.8–85.0 1.26 pts — No
Dr. Wallace — SEA at DAL — Actual: SEA 56, DAL 79
Level SEA range DAL range Overlap Tol Warning Actual landed in range?
95% 80.0–84.0 81.1–85.7 2.85 pts — No
90% 80.3–83.6 81.5–85.3 2.16 pts — No
85% 80.5–83.4 81.7–85.1 1.71 pts — No
80% 80.7–83.3 81.9–84.9 1.37 pts — No
75% 80.8–83.1 82.1–84.8 1.08 pts — No
Kevin — SEA at DAL — Actual: SEA 56, DAL 79
Level SEA range DAL range Overlap Tol Warning Actual landed in range?
95% 79.8–84.0 81.1–85.8 2.87 pts — No
90% 80.1–83.6 81.5–85.4 2.16 pts — No
85% 80.3–83.4 81.7–85.2 1.69 pts — No
80% 80.5–83.2 81.9–85.0 1.33 pts — No
75% 80.6–83.1 82.1–84.8 1.04 pts — No
Dr. Lila Shah — SEA at DAL — Actual: SEA 56, DAL 79
Level SEA range DAL range Overlap Tol Warning Actual landed in range?
95% 79.7–83.5 80.2–84.7 3.27 pts — No
90% 80.0–83.2 80.6–84.4 2.61 pts — No
85% 80.2–83.0 80.8–84.1 2.17 pts — No
80% 80.4–82.8 81.0–83.9 1.84 pts — No
75% 80.5–82.7 81.2–83.8 1.56 pts — No
Ice — SEA at DAL — Actual: SEA 56, DAL 79
Level SEA range DAL range Overlap Tol Warning Actual landed in range?
95% 79.8–83.7 80.8–85.3 2.87 pts — No
90% 80.1–83.4 81.2–84.9 2.2 pts — No
85% 80.3–83.2 81.4–84.7 1.76 pts — No
80% 80.4–83.0 81.6–84.5 1.42 pts — No
75% 80.6–82.9 81.7–84.3 1.14 pts — No
Jamal — SEA at DAL — Actual: SEA 56, DAL 79
Level SEA range DAL range Overlap Tol Warning Actual landed in range?
95% 79.9–84.0 81.1–85.7 2.84 pts — No
90% 80.2–83.6 81.5–85.4 2.14 pts — No
85% 80.4–83.4 81.7–85.1 1.68 pts — No
80% 80.6–83.3 81.9–84.9 1.33 pts — No
75% 80.7–83.1 82.1–84.8 1.04 pts — No
Jordan — SEA at DAL — Actual: SEA 56, DAL 79
Level SEA range DAL range Overlap Tol Warning Actual landed in range?
95% 80.1–83.2 81.1–85.2 2.16 pts Yes No
90% 80.4–82.9 81.4–84.9 1.49 pts Yes No
85% 80.5–82.8 81.6–84.7 1.2 pts Yes No
80% 80.7–82.8 81.8–84.5 0.98 pts Yes No
75% 80.8–82.5 81.9–84.4 0.59 pts Yes No
Darren "Dimes" Lin — SEA at DAL — Actual: SEA 56, DAL 79
Level SEA range DAL range Overlap Tol Warning Actual landed in range?
95% 79.4–84.1 80.8–85.9 3.31 pts — No
90% 79.8–83.7 81.2–85.4 2.53 pts — No
85% 80.0–83.4 81.4–85.2 2.02 pts — No
80% 80.2–83.3 81.6–85.0 1.63 pts — No
75% 80.4–83.1 81.8–84.8 1.3 pts — No
Maya Jefferson — SEA at DAL — Actual: SEA 56, DAL 79
Level SEA range DAL range Overlap Tol Warning Actual landed in range?
95% 79.7–83.7 80.7–85.6 2.98 pts — No
90% 80.0–83.4 81.1–85.2 2.27 pts — No
85% 80.2–83.1 81.3–84.9 1.81 pts — No
80% 80.4–83.0 81.5–84.7 1.45 pts — No
75% 80.5–82.9 81.7–84.6 1.15 pts — No
Lexi — SEA at DAL — Actual: SEA 56, DAL 79
Level SEA range DAL range Overlap Tol Warning Actual landed in range?
95% 80.2–83.8 81.1–85.9 2.75 pts Yes No
90% 80.7–83.4 81.4–85.5 1.93 pts Yes No
85% 80.7–83.1 81.7–85.3 1.39 pts Yes No
80% 80.8–83.0 81.9–85.1 1.08 pts Yes No
75% 80.9–82.9 82.1–84.9 0.83 pts Yes No
Coach Sarah Watanabe — SEA at DAL — Actual: SEA 56, DAL 79
Level SEA range DAL range Overlap Tol Warning Actual landed in range?
95% 80.0–83.7 82.2–87.2 1.56 pts Yes No
90% 80.2–83.4 82.6–86.8 0.78 pts Yes No
85% 80.3–83.1 82.8–86.5 0.24 pts Yes No
80% 80.4–82.8 83.0–86.3 — pts Yes No
75% 80.5–82.7 83.2–86.2 — pts Yes No