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Chicago Sky at Seattle Storm

CHI 33 – SEA 43

August 10, 2026 · Final

Coach Sarah Watanabe

Best model for this game

Coach Sarah Watanabe
All models: 0-12
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 CHI at SEA

All 12 models’ predicted scores

CHI — one dot per model SEA — one dot per model Actual: CHI 33, SEA 43
Vince Chambers
CHI 85.6–92.3 SEA 82.1–88.5 Overlap 2.92 pts Actual: CHI 33, SEA 43

In 95 out of 100 simulated runs, leans Chicago Sky (avg. 89.0) over Seattle Storm (avg. 85.3) — by 3.6 points. The ranges overlap some — there's real uncertainty here.

CHI 86.1–91.8 SEA 82.6–88.0 Overlap 1.87 pts Actual: CHI 33, SEA 43

In 90 out of 100 simulated runs, leans Chicago Sky (avg. 89.0) over Seattle Storm (avg. 85.3) — by 3.6 points. The ranges overlap some — there's real uncertainty here.

CHI 86.5–91.4 SEA 83.0–87.7 Overlap 1.18 pts Actual: CHI 33, SEA 43

In 85 out of 100 simulated runs, leans Chicago Sky (avg. 89.0) over Seattle Storm (avg. 85.3) — by 3.6 points. The ranges overlap some — there's real uncertainty here.

CHI 86.8–91.2 SEA 83.2–87.4 Overlap 0.65 pts Actual: CHI 33, SEA 43

In 80 out of 100 simulated runs, leans Chicago Sky (avg. 89.0) over Seattle Storm (avg. 85.3) — by 3.6 points. The ranges barely touch.

CHI 87.0–90.9 SEA 83.4–87.2 Overlap 0.21 pts Actual: CHI 33, SEA 43

In 75 out of 100 simulated runs, leans Chicago Sky (avg. 89.0) over Seattle Storm (avg. 85.3) — by 3.6 points. The ranges barely touch.

Show the math
Model
Vince Chambers (#1)
t-statistic
18.95
p-value
2.11e-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.

Reg
CHI 85.8–92.7 SEA 81.8–89.8 Overlap 4.01 pts Actual: CHI 33, SEA 43

In 95 out of 100 simulated runs, leans Chicago Sky (avg. 89.3) over Seattle Storm (avg. 85.8) — by 3.5 points. The ranges overlap almost entirely, so one game could go either way.

CHI 86.4–92.2 SEA 82.4–89.2 Overlap 2.81 pts Actual: CHI 33, SEA 43

In 90 out of 100 simulated runs, leans Chicago Sky (avg. 89.3) over Seattle Storm (avg. 85.8) — by 3.5 points. The ranges overlap some — there's real uncertainty here.

CHI 86.7–91.8 SEA 82.9–88.8 Overlap 2.03 pts Actual: CHI 33, SEA 43

In 85 out of 100 simulated runs, leans Chicago Sky (avg. 89.3) over Seattle Storm (avg. 85.8) — by 3.5 points. The ranges overlap some — there's real uncertainty here.

CHI 87.0–91.5 SEA 83.2–88.4 Overlap 1.43 pts Actual: CHI 33, SEA 43

In 80 out of 100 simulated runs, leans Chicago Sky (avg. 89.3) over Seattle Storm (avg. 85.8) — by 3.5 points. The ranges overlap some — there's real uncertainty here.

CHI 87.2–91.3 SEA 83.4–88.2 Overlap 0.93 pts Actual: CHI 33, SEA 43

In 75 out of 100 simulated runs, leans Chicago Sky (avg. 89.3) over Seattle Storm (avg. 85.8) — by 3.5 points. The ranges barely touch.

Show the math
Model
Reg (#2)
t-statistic
15.77
p-value
1.39e-38

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
CHI 86.8–92.2 SEA 82.8–87.8 Overlap 0.99 pts Actual: CHI 33, SEA 43

In 95 out of 100 simulated runs, leans Chicago Sky (avg. 88.9) over Seattle Storm (avg. 85.3) — by 3.6 points. The ranges barely touch.

CHI 86.9–91.8 SEA 83.2–87.4 Overlap 0.42 pts Actual: CHI 33, SEA 43

In 90 out of 100 simulated runs, leans Chicago Sky (avg. 88.9) over Seattle Storm (avg. 85.3) — by 3.6 points. The ranges barely touch.

CHI 87.1–91.4 SEA 83.5–87.1 Overlap 0.02 pts Actual: CHI 33, SEA 43

In 85 out of 100 simulated runs, leans Chicago Sky (avg. 88.9) over Seattle Storm (avg. 85.3) — by 3.6 points. The ranges barely touch.

CHI 87.2–91.0 SEA 83.7–86.9 No overlap Actual: CHI 33, SEA 43

In 80 out of 100 simulated runs, leans Chicago Sky (avg. 88.9) over Seattle Storm (avg. 85.3) — by 3.6 points. The 80% ranges don't overlap at all — a confident model.

CHI 87.4–90.6 SEA 83.8–86.7 No overlap Actual: CHI 33, SEA 43

In 75 out of 100 simulated runs, leans Chicago Sky (avg. 88.9) over Seattle Storm (avg. 85.3) — by 3.6 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Wallace (#3)
t-statistic
21.52
p-value
1.89e-56

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
CHI 86.4–92.2 SEA 82.9–88.0 Overlap 1.65 pts Actual: CHI 33, SEA 43

In 95 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.4) — by 3.3 points. The ranges overlap some — there's real uncertainty here.

CHI 86.9–91.6 SEA 83.3–87.6 Overlap 0.72 pts Actual: CHI 33, SEA 43

In 90 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.4) — by 3.3 points. The ranges barely touch.

CHI 87.1–91.5 SEA 83.6–87.3 Overlap 0.26 pts Actual: CHI 33, SEA 43

In 85 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.4) — by 3.3 points. The ranges barely touch.

CHI 87.3–91.1 SEA 83.8–87.1 No overlap Actual: CHI 33, SEA 43

In 80 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.4) — by 3.3 points. The 80% ranges don't overlap at all — a confident model.

CHI 87.3–90.6 SEA 83.9–87.0 No overlap Actual: CHI 33, SEA 43

In 75 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.4) — by 3.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Kevin (#4)
t-statistic
18.93
p-value
2.91e-48

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
CHI 85.3–91.8 SEA 82.1–88.3 Overlap 2.95 pts Actual: CHI 33, SEA 43

In 95 out of 100 simulated runs, leans Chicago Sky (avg. 88.6) over Seattle Storm (avg. 84.9) — by 3.7 points. The ranges overlap some — there's real uncertainty here.

CHI 85.8–91.3 SEA 82.7–87.9 Overlap 2.09 pts Actual: CHI 33, SEA 43

In 90 out of 100 simulated runs, leans Chicago Sky (avg. 88.6) over Seattle Storm (avg. 84.9) — by 3.7 points. The ranges overlap some — there's real uncertainty here.

CHI 86.2–91.0 SEA 83.1–87.6 Overlap 1.39 pts Actual: CHI 33, SEA 43

In 85 out of 100 simulated runs, leans Chicago Sky (avg. 88.6) over Seattle Storm (avg. 84.9) — by 3.7 points. The ranges overlap some — there's real uncertainty here.

CHI 86.4–90.7 SEA 83.3–86.9 Overlap 0.45 pts Actual: CHI 33, SEA 43

In 80 out of 100 simulated runs, leans Chicago Sky (avg. 88.6) over Seattle Storm (avg. 84.9) — by 3.7 points. The ranges barely touch.

CHI 86.7–90.5 SEA 83.5–86.5 No overlap Actual: CHI 33, SEA 43

In 75 out of 100 simulated runs, leans Chicago Sky (avg. 88.6) over Seattle Storm (avg. 84.9) — by 3.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
19.00
p-value
1.41e-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.

Ice
CHI 85.9–93.2 SEA 81.6–88.4 Overlap 2.55 pts Actual: CHI 33, SEA 43

In 95 out of 100 simulated runs, leans Chicago Sky (avg. 88.4) over Seattle Storm (avg. 85.0) — by 3.4 points. The ranges overlap some — there's real uncertainty here.

CHI 86.1–92.4 SEA 82.2–87.9 Overlap 1.75 pts Actual: CHI 33, SEA 43

In 90 out of 100 simulated runs, leans Chicago Sky (avg. 88.4) over Seattle Storm (avg. 85.0) — by 3.4 points. The ranges overlap some — there's real uncertainty here.

CHI 86.3–91.5 SEA 82.5–87.5 Overlap 1.22 pts Actual: CHI 33, SEA 43

In 85 out of 100 simulated runs, leans Chicago Sky (avg. 88.4) over Seattle Storm (avg. 85.0) — by 3.4 points. The ranges overlap some — there's real uncertainty here.

CHI 86.6–90.5 SEA 82.8–87.2 Overlap 0.58 pts Actual: CHI 33, SEA 43

In 80 out of 100 simulated runs, leans Chicago Sky (avg. 88.4) over Seattle Storm (avg. 85.0) — by 3.4 points. The ranges barely touch.

CHI 86.8–90.1 SEA 83.0–87.0 Overlap 0.14 pts Actual: CHI 33, SEA 43

In 75 out of 100 simulated runs, leans Chicago Sky (avg. 88.4) over Seattle Storm (avg. 85.0) — by 3.4 points. The ranges barely touch.

Show the math
Model
Ice (#6)
t-statistic
15.89
p-value
5.09e-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.

Jamal
CHI 86.2–91.5 SEA 82.0–87.6 Overlap 1.4 pts Actual: CHI 33, SEA 43

In 95 out of 100 simulated runs, leans Chicago Sky (avg. 88.4) over Seattle Storm (avg. 85.0) — by 3.4 points. The ranges overlap some — there's real uncertainty here.

CHI 86.6–91.1 SEA 82.6–87.3 Overlap 0.67 pts Actual: CHI 33, SEA 43

In 90 out of 100 simulated runs, leans Chicago Sky (avg. 88.4) over Seattle Storm (avg. 85.0) — by 3.4 points. The ranges barely touch.

CHI 86.7–90.3 SEA 83.1–86.8 Overlap 0.04 pts Actual: CHI 33, SEA 43

In 85 out of 100 simulated runs, leans Chicago Sky (avg. 88.4) over Seattle Storm (avg. 85.0) — by 3.4 points. The ranges barely touch.

CHI 86.8–90.2 SEA 83.3–86.5 No overlap Actual: CHI 33, SEA 43

In 80 out of 100 simulated runs, leans Chicago Sky (avg. 88.4) over Seattle Storm (avg. 85.0) — by 3.4 points. The 80% ranges don't overlap at all — a confident model.

CHI 87.0–89.9 SEA 83.6–86.4 No overlap Actual: CHI 33, SEA 43

In 75 out of 100 simulated runs, leans Chicago Sky (avg. 88.4) over Seattle Storm (avg. 85.0) — by 3.4 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jamal (#7)
t-statistic
17.78
p-value
3.32e-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.

Jordan
CHI 85.9–92.8 SEA 82.2–88.3 Overlap 2.34 pts Actual: CHI 33, SEA 43

In 95 out of 100 simulated runs, leans Chicago Sky (avg. 89.1) over Seattle Storm (avg. 85.2) — by 3.8 points. The ranges overlap some — there's real uncertainty here.

CHI 86.5–92.5 SEA 82.7–87.8 Overlap 1.3 pts Actual: CHI 33, SEA 43

In 90 out of 100 simulated runs, leans Chicago Sky (avg. 89.1) over Seattle Storm (avg. 85.2) — by 3.8 points. The ranges overlap some — there's real uncertainty here.

CHI 86.6–91.7 SEA 83.0–87.5 Overlap 0.83 pts Actual: CHI 33, SEA 43

In 85 out of 100 simulated runs, leans Chicago Sky (avg. 89.1) over Seattle Storm (avg. 85.2) — by 3.8 points. The ranges barely touch.

CHI 87.1–91.4 SEA 83.2–87.2 Overlap 0.08 pts Actual: CHI 33, SEA 43

In 80 out of 100 simulated runs, leans Chicago Sky (avg. 89.1) over Seattle Storm (avg. 85.2) — by 3.8 points. The ranges barely touch.

CHI 87.2–90.8 SEA 83.4–87.0 No overlap Actual: CHI 33, SEA 43

In 75 out of 100 simulated runs, leans Chicago Sky (avg. 89.1) over Seattle Storm (avg. 85.2) — by 3.8 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jordan (#8)
t-statistic
19.06
p-value
4.89e-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.

Darren "Dimes" Lin
CHI 86.2–92.1 SEA 82.6–88.8 Overlap 2.57 pts Actual: CHI 33, SEA 43

In 95 out of 100 simulated runs, leans Chicago Sky (avg. 88.7) over Seattle Storm (avg. 85.3) — by 3.4 points. The ranges overlap some — there's real uncertainty here.

CHI 86.6–91.0 SEA 83.1–88.0 Overlap 1.37 pts Actual: CHI 33, SEA 43

In 90 out of 100 simulated runs, leans Chicago Sky (avg. 88.7) over Seattle Storm (avg. 85.3) — by 3.4 points. The ranges overlap some — there's real uncertainty here.

CHI 86.7–90.8 SEA 83.2–87.7 Overlap 1.02 pts Actual: CHI 33, SEA 43

In 85 out of 100 simulated runs, leans Chicago Sky (avg. 88.7) over Seattle Storm (avg. 85.3) — by 3.4 points. The ranges overlap some — there's real uncertainty here.

CHI 86.9–90.5 SEA 83.4–87.5 Overlap 0.67 pts Actual: CHI 33, SEA 43

In 80 out of 100 simulated runs, leans Chicago Sky (avg. 88.7) over Seattle Storm (avg. 85.3) — by 3.4 points. The ranges barely touch.

CHI 87.0–90.4 SEA 83.8–87.2 Overlap 0.17 pts Actual: CHI 33, SEA 43

In 75 out of 100 simulated runs, leans Chicago Sky (avg. 88.7) over Seattle Storm (avg. 85.3) — by 3.4 points. The ranges barely touch.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
17.48
p-value
1.51e-44

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
CHI 86.5–91.5 SEA 83.1–88.0 Overlap 1.5 pts Actual: CHI 33, SEA 43

In 95 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.5) — by 3.3 points. The ranges overlap some — there's real uncertainty here.

CHI 86.7–91.2 SEA 83.2–87.9 Overlap 1.12 pts Actual: CHI 33, SEA 43

In 90 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.5) — by 3.3 points. The ranges overlap some — there's real uncertainty here.

CHI 87.1–91.1 SEA 83.5–87.3 Overlap 0.21 pts Actual: CHI 33, SEA 43

In 85 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.5) — by 3.3 points. The ranges barely touch.

CHI 87.3–90.8 SEA 83.8–86.8 No overlap Actual: CHI 33, SEA 43

In 80 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.5) — by 3.3 points. The 80% ranges don't overlap at all — a confident model.

CHI 87.4–90.5 SEA 84.0–86.7 No overlap Actual: CHI 33, SEA 43

In 75 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.5) — by 3.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Maya Jefferson (#10)
t-statistic
17.99
p-value
2.84e-46

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
CHI 86.5–93.0 SEA 82.5–88.6 Overlap 2.09 pts Actual: CHI 33, SEA 43

In 95 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.2) — by 3.6 points. The ranges overlap some — there's real uncertainty here.

CHI 86.8–91.5 SEA 83.1–87.5 Overlap 0.78 pts Actual: CHI 33, SEA 43

In 90 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.2) — by 3.6 points. The ranges barely touch.

CHI 86.9–91.0 SEA 83.3–87.2 Overlap 0.32 pts Actual: CHI 33, SEA 43

In 85 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.2) — by 3.6 points. The ranges barely touch.

CHI 87.1–90.9 SEA 83.5–87.0 No overlap Actual: CHI 33, SEA 43

In 80 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.2) — by 3.6 points. The 80% ranges don't overlap at all — a confident model.

CHI 87.2–90.6 SEA 83.6–86.8 No overlap Actual: CHI 33, SEA 43

In 75 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.2) — by 3.6 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Lexi (#11)
t-statistic
17.04
p-value
4.30e-43

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
CHI 85.2–92.3 SEA 82.6–88.8 Overlap 3.57 pts Actual: CHI 33, SEA 43

In 95 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.7) — by 3.1 points. The ranges overlap almost entirely, so one game could go either way.

CHI 85.8–91.7 SEA 83.1–88.3 Overlap 2.5 pts Actual: CHI 33, SEA 43

In 90 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.7) — by 3.1 points. The ranges overlap some — there's real uncertainty here.

CHI 86.2–91.3 SEA 83.4–88.0 Overlap 1.81 pts Actual: CHI 33, SEA 43

In 85 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.7) — by 3.1 points. The ranges overlap some — there's real uncertainty here.

CHI 86.5–91.1 SEA 83.6–87.7 Overlap 1.27 pts Actual: CHI 33, SEA 43

In 80 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.7) — by 3.1 points. The ranges overlap some — there's real uncertainty here.

CHI 86.7–90.8 SEA 83.9–87.5 Overlap 0.83 pts Actual: CHI 33, SEA 43

In 75 out of 100 simulated runs, leans Chicago Sky (avg. 88.8) over Seattle Storm (avg. 85.7) — by 3.1 points. The ranges barely touch.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
15.77
p-value
1.07e-38

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 — CHI at SEA — Actual: CHI 33, SEA 43
Level CHI range SEA range Overlap Tol Warning Actual landed in range?
95% 85.6–92.3 82.1–88.5 2.92 pts — No
90% 86.1–91.8 82.6–88.0 1.87 pts — No
85% 86.5–91.4 83.0–87.7 1.18 pts — No
80% 86.8–91.2 83.2–87.4 0.65 pts — No
75% 87.0–90.9 83.4–87.2 0.21 pts — No
Reg — CHI at SEA — Actual: CHI 33, SEA 43
Level CHI range SEA range Overlap Tol Warning Actual landed in range?
95% 85.8–92.7 81.8–89.8 4.01 pts — No
90% 86.4–92.2 82.4–89.2 2.81 pts — No
85% 86.7–91.8 82.9–88.8 2.03 pts — No
80% 87.0–91.5 83.2–88.4 1.43 pts — No
75% 87.2–91.3 83.4–88.2 0.93 pts — No
Dr. Wallace — CHI at SEA — Actual: CHI 33, SEA 43
Level CHI range SEA range Overlap Tol Warning Actual landed in range?
95% 86.8–92.2 82.8–87.8 0.99 pts — No
90% 86.9–91.8 83.2–87.4 0.42 pts — No
85% 87.1–91.4 83.5–87.1 0.02 pts — No
80% 87.2–91.0 83.7–86.9 — pts — No
75% 87.4–90.6 83.8–86.7 — pts — No
Kevin — CHI at SEA — Actual: CHI 33, SEA 43
Level CHI range SEA range Overlap Tol Warning Actual landed in range?
95% 86.4–92.2 82.9–88.0 1.65 pts — No
90% 86.9–91.6 83.3–87.6 0.72 pts — No
85% 87.1–91.5 83.6–87.3 0.26 pts — No
80% 87.3–91.1 83.8–87.1 — pts — No
75% 87.3–90.6 83.9–87.0 — pts — No
Dr. Lila Shah — CHI at SEA — Actual: CHI 33, SEA 43
Level CHI range SEA range Overlap Tol Warning Actual landed in range?
95% 85.3–91.8 82.1–88.3 2.95 pts — No
90% 85.8–91.3 82.7–87.9 2.09 pts — No
85% 86.2–91.0 83.1–87.6 1.39 pts — No
80% 86.4–90.7 83.3–86.9 0.45 pts — No
75% 86.7–90.5 83.5–86.5 — pts — No
Ice — CHI at SEA — Actual: CHI 33, SEA 43
Level CHI range SEA range Overlap Tol Warning Actual landed in range?
95% 85.9–93.2 81.6–88.4 2.55 pts — No
90% 86.1–92.4 82.2–87.9 1.75 pts — No
85% 86.3–91.5 82.5–87.5 1.22 pts — No
80% 86.6–90.5 82.8–87.2 0.58 pts — No
75% 86.8–90.1 83.0–87.0 0.14 pts — No
Jamal — CHI at SEA — Actual: CHI 33, SEA 43
Level CHI range SEA range Overlap Tol Warning Actual landed in range?
95% 86.2–91.5 82.0–87.6 1.4 pts — No
90% 86.6–91.1 82.6–87.3 0.67 pts — No
85% 86.7–90.3 83.1–86.8 0.04 pts — No
80% 86.8–90.2 83.3–86.5 — pts — No
75% 87.0–89.9 83.6–86.4 — pts — No
Jordan — CHI at SEA — Actual: CHI 33, SEA 43
Level CHI range SEA range Overlap Tol Warning Actual landed in range?
95% 85.9–92.8 82.2–88.3 2.34 pts — No
90% 86.5–92.5 82.7–87.8 1.3 pts — No
85% 86.6–91.7 83.0–87.5 0.83 pts — No
80% 87.1–91.4 83.2–87.2 0.08 pts — No
75% 87.2–90.8 83.4–87.0 — pts — No
Darren "Dimes" Lin — CHI at SEA — Actual: CHI 33, SEA 43
Level CHI range SEA range Overlap Tol Warning Actual landed in range?
95% 86.2–92.1 82.6–88.8 2.57 pts — No
90% 86.6–91.0 83.1–88.0 1.37 pts — No
85% 86.7–90.8 83.2–87.7 1.02 pts — No
80% 86.9–90.5 83.4–87.5 0.67 pts — No
75% 87.0–90.4 83.8–87.2 0.17 pts — No
Maya Jefferson — CHI at SEA — Actual: CHI 33, SEA 43
Level CHI range SEA range Overlap Tol Warning Actual landed in range?
95% 86.5–91.5 83.1–88.0 1.5 pts — No
90% 86.7–91.2 83.2–87.9 1.12 pts — No
85% 87.1–91.1 83.5–87.3 0.21 pts — No
80% 87.3–90.8 83.8–86.8 — pts — No
75% 87.4–90.5 84.0–86.7 — pts — No
Lexi — CHI at SEA — Actual: CHI 33, SEA 43
Level CHI range SEA range Overlap Tol Warning Actual landed in range?
95% 86.5–93.0 82.5–88.6 2.09 pts — No
90% 86.8–91.5 83.1–87.5 0.78 pts — No
85% 86.9–91.0 83.3–87.2 0.32 pts — No
80% 87.1–90.9 83.5–87.0 — pts — No
75% 87.2–90.6 83.6–86.8 — pts — No
Coach Sarah Watanabe — CHI at SEA — Actual: CHI 33, SEA 43
Level CHI range SEA range Overlap Tol Warning Actual landed in range?
95% 85.2–92.3 82.6–88.8 3.57 pts — No
90% 85.8–91.7 83.1–88.3 2.5 pts — No
85% 86.2–91.3 83.4–88.0 1.81 pts — No
80% 86.5–91.1 83.6–87.7 1.27 pts — No
75% 86.7–90.8 83.9–87.5 0.83 pts — No