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Dallas Wings at Seattle Storm

DAL 103 – SEA 91

September 23, 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 DAL at SEA

All 12 models’ predicted scores

DAL — one dot per model SEA — one dot per model Actual: DAL 103, SEA 91
Vince Chambers
DAL 84.5–89.1 SEA 81.7–86.6 Overlap 2.14 pts Actual: DAL 103, SEA 91

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Seattle Storm (avg. 84.1) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 84.8–88.7 SEA 82.1–86.2 Overlap 1.37 pts Actual: DAL 103, SEA 91

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Seattle Storm (avg. 84.1) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 85.1–88.5 SEA 82.3–85.9 Overlap 0.86 pts Actual: DAL 103, SEA 91

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Seattle Storm (avg. 84.1) — by 2.7 points. The ranges barely touch.

DAL 85.3–88.3 SEA 82.5–85.7 Overlap 0.48 pts Actual: DAL 103, SEA 91

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Seattle Storm (avg. 84.1) — by 2.7 points. The ranges barely touch.

DAL 85.4–88.1 SEA 82.7–85.6 Overlap 0.16 pts Actual: DAL 103, SEA 91

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Seattle Storm (avg. 84.1) — by 2.7 points. The ranges barely touch.

Show the math
Model
Vince Chambers (#1)
t-statistic
23.25
p-value
6.27e-75

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
DAL 84.4–89.3 SEA 81.5–87.2 Overlap 2.82 pts Actual: DAL 103, SEA 91

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Seattle Storm (avg. 84.4) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 85.0–88.9 SEA 81.9–86.8 Overlap 1.74 pts Actual: DAL 103, SEA 91

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Seattle Storm (avg. 84.4) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 85.3–88.7 SEA 82.2–86.5 Overlap 1.21 pts Actual: DAL 103, SEA 91

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Seattle Storm (avg. 84.4) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 85.6–88.5 SEA 82.5–86.2 Overlap 0.6 pts Actual: DAL 103, SEA 91

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Seattle Storm (avg. 84.4) — by 2.7 points. The ranges barely touch.

DAL 85.9–88.4 SEA 82.7–86.0 Overlap 0.17 pts Actual: DAL 103, SEA 91

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Seattle Storm (avg. 84.4) — by 2.7 points. The ranges barely touch.

Show the math
Model
Reg (#2)
t-statistic
20.02
p-value
2.27e-61

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
DAL 84.5–89.0 SEA 81.8–86.8 Overlap 2.25 pts Actual: DAL 103, SEA 91

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Seattle Storm (avg. 84.1) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 84.9–88.7 SEA 82.1–86.4 Overlap 1.44 pts Actual: DAL 103, SEA 91

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Seattle Storm (avg. 84.1) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 85.2–88.5 SEA 82.4–85.9 Overlap 0.73 pts Actual: DAL 103, SEA 91

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Seattle Storm (avg. 84.1) — by 2.7 points. The ranges barely touch.

DAL 85.5–88.3 SEA 82.7–85.6 Overlap 0.04 pts Actual: DAL 103, SEA 91

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Seattle Storm (avg. 84.1) — by 2.7 points. The ranges barely touch.

DAL 85.6–88.1 SEA 83.0–85.5 No overlap Actual: DAL 103, SEA 91

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Seattle Storm (avg. 84.1) — by 2.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Wallace (#3)
t-statistic
21.88
p-value
2.87e-69

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
DAL 84.7–89.4 SEA 81.6–87.0 Overlap 2.21 pts Actual: DAL 103, SEA 91

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Seattle Storm (avg. 84.3) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 85.3–88.9 SEA 82.1–86.5 Overlap 1.22 pts Actual: DAL 103, SEA 91

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Seattle Storm (avg. 84.3) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 85.5–88.6 SEA 82.3–86.2 Overlap 0.72 pts Actual: DAL 103, SEA 91

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Seattle Storm (avg. 84.3) — by 2.7 points. The ranges barely touch.

DAL 85.6–88.5 SEA 82.5–86.0 Overlap 0.39 pts Actual: DAL 103, SEA 91

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Seattle Storm (avg. 84.3) — by 2.7 points. The ranges barely touch.

DAL 85.8–88.3 SEA 82.7–85.9 Overlap 0.09 pts Actual: DAL 103, SEA 91

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Seattle Storm (avg. 84.3) — by 2.7 points. The ranges barely touch.

Show the math
Model
Kevin (#4)
t-statistic
22.23
p-value
1.12e-70

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
DAL 83.6–88.6 SEA 82.0–86.6 Overlap 3.03 pts Actual: DAL 103, SEA 91

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 85.9) over Seattle Storm (avg. 83.9) — by 1.9 points. The ranges overlap almost entirely, so one game could go either way.

DAL 83.9–87.8 SEA 82.1–86.2 Overlap 2.36 pts Actual: DAL 103, SEA 91

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 85.9) over Seattle Storm (avg. 83.9) — by 1.9 points. The ranges overlap some — there's real uncertainty here.

DAL 84.2–87.6 SEA 82.3–85.7 Overlap 1.47 pts Actual: DAL 103, SEA 91

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 85.9) over Seattle Storm (avg. 83.9) — by 1.9 points. The ranges overlap some — there's real uncertainty here.

DAL 84.4–87.3 SEA 82.4–85.5 Overlap 1.04 pts Actual: DAL 103, SEA 91

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 85.9) over Seattle Storm (avg. 83.9) — by 1.9 points. The ranges overlap some — there's real uncertainty here.

DAL 84.6–87.1 SEA 82.5–85.3 Overlap 0.7 pts Actual: DAL 103, SEA 91

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 85.9) over Seattle Storm (avg. 83.9) — by 1.9 points. The ranges barely touch.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
14.69
p-value
6.03e-39

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
DAL 83.7–88.9 SEA 82.2–87.7 Overlap 3.96 pts Actual: DAL 103, SEA 91

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.4) — by 2.3 points. The ranges overlap almost entirely, so one game could go either way.

DAL 84.4–88.6 SEA 82.5–86.9 Overlap 2.48 pts Actual: DAL 103, SEA 91

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.4) — by 2.3 points. The ranges overlap some — there's real uncertainty here.

DAL 84.8–88.4 SEA 82.7–86.4 Overlap 1.58 pts Actual: DAL 103, SEA 91

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.4) — by 2.3 points. The ranges overlap some — there's real uncertainty here.

DAL 85.2–88.1 SEA 83.1–85.9 Overlap 0.66 pts Actual: DAL 103, SEA 91

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.4) — by 2.3 points. The ranges barely touch.

DAL 85.4–88.0 SEA 83.2–85.7 Overlap 0.28 pts Actual: DAL 103, SEA 91

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.4) — by 2.3 points. The ranges barely touch.

Show the math
Model
Ice (#6)
t-statistic
17.07
p-value
9.04e-49

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
DAL 83.7–89.3 SEA 81.9–87.3 Overlap 3.66 pts Actual: DAL 103, SEA 91

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.2) — by 2.5 points. The ranges overlap almost entirely, so one game could go either way.

DAL 84.5–88.8 SEA 82.4–86.5 Overlap 2.01 pts Actual: DAL 103, SEA 91

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.2) — by 2.5 points. The ranges overlap some — there's real uncertainty here.

DAL 85.1–88.6 SEA 82.6–86.0 Overlap 0.97 pts Actual: DAL 103, SEA 91

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.2) — by 2.5 points. The ranges barely touch.

DAL 85.2–88.4 SEA 82.9–85.8 Overlap 0.59 pts Actual: DAL 103, SEA 91

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.2) — by 2.5 points. The ranges barely touch.

DAL 85.4–88.2 SEA 83.0–85.7 Overlap 0.3 pts Actual: DAL 103, SEA 91

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.2) — by 2.5 points. The ranges barely touch.

Show the math
Model
Jamal (#7)
t-statistic
17.88
p-value
2.66e-52

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
DAL 83.9–89.2 SEA 81.3–87.3 Overlap 3.39 pts Actual: DAL 103, SEA 91

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.0) — by 2.7 points. The ranges overlap almost entirely, so one game could go either way.

DAL 84.6–88.8 SEA 81.6–86.6 Overlap 2.07 pts Actual: DAL 103, SEA 91

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.0) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 84.8–88.5 SEA 82.0–85.9 Overlap 1.12 pts Actual: DAL 103, SEA 91

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.0) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 85.0–88.3 SEA 82.3–85.6 Overlap 0.59 pts Actual: DAL 103, SEA 91

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.0) — by 2.7 points. The ranges barely touch.

DAL 85.2–88.1 SEA 82.5–85.3 Overlap 0.09 pts Actual: DAL 103, SEA 91

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.0) — by 2.7 points. The ranges barely touch.

Show the math
Model
Jordan (#8)
t-statistic
18.52
p-value
5.23e-55

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
DAL 84.0–89.0 SEA 81.8–86.9 Overlap 2.89 pts Actual: DAL 103, SEA 91

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.2) — by 2.5 points. The ranges overlap some — there's real uncertainty here.

DAL 84.4–88.6 SEA 82.1–86.4 Overlap 1.96 pts Actual: DAL 103, SEA 91

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.2) — by 2.5 points. The ranges overlap some — there's real uncertainty here.

DAL 85.1–88.5 SEA 82.5–85.8 Overlap 0.73 pts Actual: DAL 103, SEA 91

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.2) — by 2.5 points. The ranges barely touch.

DAL 85.2–88.2 SEA 82.8–85.7 Overlap 0.47 pts Actual: DAL 103, SEA 91

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.2) — by 2.5 points. The ranges barely touch.

DAL 85.4–88.1 SEA 83.0–85.5 Overlap 0.08 pts Actual: DAL 103, SEA 91

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.2) — by 2.5 points. The ranges barely touch.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
18.49
p-value
7.51e-55

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
DAL 84.3–89.2 SEA 82.4–87.0 Overlap 2.7 pts Actual: DAL 103, SEA 91

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Seattle Storm (avg. 84.2) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 85.0–88.8 SEA 82.6–86.3 Overlap 1.22 pts Actual: DAL 103, SEA 91

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Seattle Storm (avg. 84.2) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 85.3–88.5 SEA 82.7–86.1 Overlap 0.77 pts Actual: DAL 103, SEA 91

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Seattle Storm (avg. 84.2) — by 2.7 points. The ranges barely touch.

DAL 85.5–88.4 SEA 82.8–85.8 Overlap 0.26 pts Actual: DAL 103, SEA 91

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Seattle Storm (avg. 84.2) — by 2.7 points. The ranges barely touch.

DAL 85.7–88.3 SEA 83.0–85.6 No overlap Actual: DAL 103, SEA 91

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Seattle Storm (avg. 84.2) — by 2.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Maya Jefferson (#10)
t-statistic
20.74
p-value
5.35e-64

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
DAL 84.0–88.9 SEA 81.8–86.4 Overlap 2.4 pts Actual: DAL 103, SEA 91

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.1) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 84.9–88.7 SEA 82.1–86.0 Overlap 1.09 pts Actual: DAL 103, SEA 91

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.1) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

DAL 85.1–88.3 SEA 82.4–85.8 Overlap 0.71 pts Actual: DAL 103, SEA 91

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.1) — by 2.7 points. The ranges barely touch.

DAL 85.3–88.2 SEA 82.5–85.6 Overlap 0.3 pts Actual: DAL 103, SEA 91

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.1) — by 2.7 points. The ranges barely touch.

DAL 85.4–88.1 SEA 82.7–85.4 Overlap 0.01 pts Actual: DAL 103, SEA 91

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Seattle Storm (avg. 84.1) — by 2.7 points. The ranges barely touch.

Show the math
Model
Lexi (#11)
t-statistic
21.80
p-value
2.91e-68

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
DAL 84.4–89.7 SEA 81.3–87.2 Overlap 2.83 pts Actual: DAL 103, SEA 91

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Seattle Storm (avg. 84.0) — by 3.0 points. The ranges overlap some — there's real uncertainty here.

DAL 84.8–89.3 SEA 81.6–86.5 Overlap 1.7 pts Actual: DAL 103, SEA 91

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Seattle Storm (avg. 84.0) — by 3.0 points. The ranges overlap some — there's real uncertainty here.

DAL 85.1–89.0 SEA 82.1–86.1 Overlap 1.01 pts Actual: DAL 103, SEA 91

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Seattle Storm (avg. 84.0) — by 3.0 points. The ranges overlap some — there's real uncertainty here.

DAL 85.3–88.8 SEA 82.2–85.7 Overlap 0.36 pts Actual: DAL 103, SEA 91

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Seattle Storm (avg. 84.0) — by 3.0 points. The ranges barely touch.

DAL 85.5–88.6 SEA 82.6–85.4 No overlap Actual: DAL 103, SEA 91

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Seattle Storm (avg. 84.0) — by 3.0 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
21.67
p-value
1.35e-67

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 — DAL at SEA — Actual: DAL 103, SEA 91
Level DAL range SEA range Overlap Tol Warning Actual landed in range?
95% 84.5–89.1 81.7–86.6 2.14 pts — No
90% 84.8–88.7 82.1–86.2 1.37 pts — No
85% 85.1–88.5 82.3–85.9 0.86 pts — No
80% 85.3–88.3 82.5–85.7 0.48 pts — No
75% 85.4–88.1 82.7–85.6 0.16 pts — No
Reg — DAL at SEA — Actual: DAL 103, SEA 91
Level DAL range SEA range Overlap Tol Warning Actual landed in range?
95% 84.4–89.3 81.5–87.2 2.82 pts — No
90% 85.0–88.9 81.9–86.8 1.74 pts — No
85% 85.3–88.7 82.2–86.5 1.21 pts — No
80% 85.6–88.5 82.5–86.2 0.6 pts — No
75% 85.9–88.4 82.7–86.0 0.17 pts — No
Dr. Wallace — DAL at SEA — Actual: DAL 103, SEA 91
Level DAL range SEA range Overlap Tol Warning Actual landed in range?
95% 84.5–89.0 81.8–86.8 2.25 pts — No
90% 84.9–88.7 82.1–86.4 1.44 pts — No
85% 85.2–88.5 82.4–85.9 0.73 pts — No
80% 85.5–88.3 82.7–85.6 0.04 pts — No
75% 85.6–88.1 83.0–85.5 — pts — No
Kevin — DAL at SEA — Actual: DAL 103, SEA 91
Level DAL range SEA range Overlap Tol Warning Actual landed in range?
95% 84.7–89.4 81.6–87.0 2.21 pts — No
90% 85.3–88.9 82.1–86.5 1.22 pts — No
85% 85.5–88.6 82.3–86.2 0.72 pts — No
80% 85.6–88.5 82.5–86.0 0.39 pts — No
75% 85.8–88.3 82.7–85.9 0.09 pts — No
Dr. Lila Shah — DAL at SEA — Actual: DAL 103, SEA 91
Level DAL range SEA range Overlap Tol Warning Actual landed in range?
95% 83.6–88.6 82.0–86.6 3.03 pts — No
90% 83.9–87.8 82.1–86.2 2.36 pts — No
85% 84.2–87.6 82.3–85.7 1.47 pts — No
80% 84.4–87.3 82.4–85.5 1.04 pts — No
75% 84.6–87.1 82.5–85.3 0.7 pts — No
Ice — DAL at SEA — Actual: DAL 103, SEA 91
Level DAL range SEA range Overlap Tol Warning Actual landed in range?
95% 83.7–88.9 82.2–87.7 3.96 pts — No
90% 84.4–88.6 82.5–86.9 2.48 pts — No
85% 84.8–88.4 82.7–86.4 1.58 pts — No
80% 85.2–88.1 83.1–85.9 0.66 pts — No
75% 85.4–88.0 83.2–85.7 0.28 pts — No
Jamal — DAL at SEA — Actual: DAL 103, SEA 91
Level DAL range SEA range Overlap Tol Warning Actual landed in range?
95% 83.7–89.3 81.9–87.3 3.66 pts — No
90% 84.5–88.8 82.4–86.5 2.01 pts — No
85% 85.1–88.6 82.6–86.0 0.97 pts — No
80% 85.2–88.4 82.9–85.8 0.59 pts — No
75% 85.4–88.2 83.0–85.7 0.3 pts — No
Jordan — DAL at SEA — Actual: DAL 103, SEA 91
Level DAL range SEA range Overlap Tol Warning Actual landed in range?
95% 83.9–89.2 81.3–87.3 3.39 pts — No
90% 84.6–88.8 81.6–86.6 2.07 pts — No
85% 84.8–88.5 82.0–85.9 1.12 pts — No
80% 85.0–88.3 82.3–85.6 0.59 pts — No
75% 85.2–88.1 82.5–85.3 0.09 pts — No
Darren "Dimes" Lin — DAL at SEA — Actual: DAL 103, SEA 91
Level DAL range SEA range Overlap Tol Warning Actual landed in range?
95% 84.0–89.0 81.8–86.9 2.89 pts — No
90% 84.4–88.6 82.1–86.4 1.96 pts — No
85% 85.1–88.5 82.5–85.8 0.73 pts — No
80% 85.2–88.2 82.8–85.7 0.47 pts — No
75% 85.4–88.1 83.0–85.5 0.08 pts — No
Maya Jefferson — DAL at SEA — Actual: DAL 103, SEA 91
Level DAL range SEA range Overlap Tol Warning Actual landed in range?
95% 84.3–89.2 82.4–87.0 2.7 pts — No
90% 85.0–88.8 82.6–86.3 1.22 pts — No
85% 85.3–88.5 82.7–86.1 0.77 pts — No
80% 85.5–88.4 82.8–85.8 0.26 pts — No
75% 85.7–88.3 83.0–85.6 — pts — No
Lexi — DAL at SEA — Actual: DAL 103, SEA 91
Level DAL range SEA range Overlap Tol Warning Actual landed in range?
95% 84.0–88.9 81.8–86.4 2.4 pts — No
90% 84.9–88.7 82.1–86.0 1.09 pts — No
85% 85.1–88.3 82.4–85.8 0.71 pts — No
80% 85.3–88.2 82.5–85.6 0.3 pts — No
75% 85.4–88.1 82.7–85.4 0.01 pts — No
Coach Sarah Watanabe — DAL at SEA — Actual: DAL 103, SEA 91
Level DAL range SEA range Overlap Tol Warning Actual landed in range?
95% 84.4–89.7 81.3–87.2 2.83 pts — No
90% 84.8–89.3 81.6–86.5 1.7 pts — No
85% 85.1–89.0 82.1–86.1 1.01 pts — No
80% 85.3–88.8 82.2–85.7 0.36 pts — No
75% 85.5–88.6 82.6–85.4 — pts — No