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Washington Mystics at Golden State Valkyries

WAS 69 – GS 74

July 18, 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 WAS at GS

All 12 models’ predicted scores

WAS — one dot per model GS — one dot per model Actual: WAS 69, GS 74
Vince Chambers
WAS 80.7–85.5 GS 77.6–83.1 Overlap 2.4 pts Actual: WAS 69, GS 74

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 80.4) — by 2.8 points. The ranges overlap some — there's real uncertainty here.

WAS 81.1–85.1 GS 78.0–82.7 Overlap 1.57 pts Actual: WAS 69, GS 74

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 80.4) — by 2.8 points. The ranges overlap some — there's real uncertainty here.

WAS 81.4–84.9 GS 78.3–82.4 Overlap 1.03 pts Actual: WAS 69, GS 74

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 80.4) — by 2.8 points. The ranges overlap some — there's real uncertainty here.

WAS 81.6–84.7 GS 78.5–82.2 Overlap 0.62 pts Actual: WAS 69, GS 74

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 80.4) — by 2.8 points. The ranges barely touch.

WAS 81.7–84.5 GS 78.7–82.0 Overlap 0.27 pts Actual: WAS 69, GS 74

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 80.4) — by 2.8 points. The ranges barely touch.

Show the math
Model
Vince Chambers (#1)
t-statistic
16.69
p-value
4.62e-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.

Reg
WAS 81.5–85.7 GS 77.5–83.5 Overlap 2.01 pts Actual: WAS 69, GS 74

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.5) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

WAS 81.7–85.0 GS 78.0–83.1 Overlap 1.4 pts Actual: WAS 69, GS 74

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.5) — by 2.7 points. The ranges overlap some — there's real uncertainty here.

WAS 81.9–85.0 GS 78.3–82.7 Overlap 0.87 pts Actual: WAS 69, GS 74

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.5) — by 2.7 points. The ranges barely touch.

WAS 81.9–84.8 GS 78.6–82.5 Overlap 0.59 pts Actual: WAS 69, GS 74

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.5) — by 2.7 points. The ranges barely touch.

WAS 81.9–84.5 GS 78.8–82.3 Overlap 0.36 pts Actual: WAS 69, GS 74

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.5) — by 2.7 points. The ranges barely touch.

Show the math
Model
Reg (#2)
t-statistic
15.02
p-value
4.62e-34

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
WAS 81.3–84.7 GS 77.7–82.8 Overlap 1.5 pts Actual: WAS 69, GS 74

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.0) over Golden State Valkyries (avg. 80.2) — by 2.8 points. The ranges overlap some — there's real uncertainty here.

WAS 81.6–84.4 GS 78.1–82.4 Overlap 0.82 pts Actual: WAS 69, GS 74

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.0) over Golden State Valkyries (avg. 80.2) — by 2.8 points. The ranges barely touch.

WAS 81.8–84.3 GS 78.4–82.1 Overlap 0.37 pts Actual: WAS 69, GS 74

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.0) over Golden State Valkyries (avg. 80.2) — by 2.8 points. The ranges barely touch.

WAS 81.9–84.1 GS 78.6–81.9 Overlap 0.03 pts Actual: WAS 69, GS 74

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.0) over Golden State Valkyries (avg. 80.2) — by 2.8 points. The ranges barely touch.

WAS 82.0–84.0 GS 78.7–81.8 No overlap Actual: WAS 69, GS 74

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.0) over Golden State Valkyries (avg. 80.2) — by 2.8 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Wallace (#3)
t-statistic
19.88
p-value
5.15e-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.

Kevin
WAS 81.3–85.0 GS 77.6–82.4 Overlap 1.04 pts Actual: WAS 69, GS 74

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.0) — by 3.2 points. The ranges overlap some — there's real uncertainty here.

WAS 81.6–84.7 GS 78.0–82.0 Overlap 0.37 pts Actual: WAS 69, GS 74

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.0) — by 3.2 points. The ranges barely touch.

WAS 81.8–84.5 GS 78.3–81.7 No overlap Actual: WAS 69, GS 74

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.0) — by 3.2 points. The 85% ranges don't overlap at all — a confident model.

WAS 82.0–84.4 GS 78.4–81.5 No overlap Actual: WAS 69, GS 74

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.0) — by 3.2 points. The 80% ranges don't overlap at all — a confident model.

WAS 82.1–84.2 GS 78.6–81.4 No overlap Actual: WAS 69, GS 74

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.0) — by 3.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Kevin (#4)
t-statistic
23.39
p-value
7.23e-57

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
WAS 81.0–85.3 GS 77.5–82.4 Overlap 1.38 pts Actual: WAS 69, GS 74

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 79.6) — by 3.5 points. The ranges overlap some — there's real uncertainty here.

WAS 81.3–85.0 GS 77.7–82.1 Overlap 0.74 pts Actual: WAS 69, GS 74

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 79.6) — by 3.5 points. The ranges barely touch.

WAS 81.6–84.7 GS 78.1–81.9 Overlap 0.28 pts Actual: WAS 69, GS 74

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 79.6) — by 3.5 points. The ranges barely touch.

WAS 81.7–84.6 GS 78.1–81.1 No overlap Actual: WAS 69, GS 74

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 79.6) — by 3.5 points. The 80% ranges don't overlap at all — a confident model.

WAS 81.9–84.4 GS 78.3–81.0 No overlap Actual: WAS 69, GS 74

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 79.6) — by 3.5 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
21.99
p-value
5.36e-53

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
WAS 81.5–85.8 GS 77.1–82.8 Overlap 1.3 pts Actual: WAS 69, GS 74

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.0) — by 3.2 points. The ranges overlap some — there's real uncertainty here.

WAS 81.8–84.5 GS 77.5–82.4 Overlap 0.55 pts Actual: WAS 69, GS 74

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.0) — by 3.2 points. The ranges barely touch.

WAS 82.1–84.4 GS 77.8–82.1 Overlap 0.01 pts Actual: WAS 69, GS 74

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.0) — by 3.2 points. The ranges barely touch.

WAS 82.2–84.1 GS 78.1–81.8 No overlap Actual: WAS 69, GS 74

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.0) — by 3.2 points. The 80% ranges don't overlap at all — a confident model.

WAS 82.3–84.0 GS 78.3–81.6 No overlap Actual: WAS 69, GS 74

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.0) — by 3.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Ice (#6)
t-statistic
19.75
p-value
4.46e-47

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
WAS 81.0–85.4 GS 77.8–82.9 Overlap 1.91 pts Actual: WAS 69, GS 74

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.3) — by 2.9 points. The ranges overlap some — there's real uncertainty here.

WAS 81.3–85.1 GS 78.2–82.5 Overlap 1.14 pts Actual: WAS 69, GS 74

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.3) — by 2.9 points. The ranges overlap some — there's real uncertainty here.

WAS 81.6–84.8 GS 78.4–82.2 Overlap 0.64 pts Actual: WAS 69, GS 74

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.3) — by 2.9 points. The ranges barely touch.

WAS 81.7–84.7 GS 78.6–82.0 Overlap 0.25 pts Actual: WAS 69, GS 74

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.3) — by 2.9 points. The ranges barely touch.

WAS 81.9–84.5 GS 78.8–81.8 No overlap Actual: WAS 69, GS 74

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 80.3) — by 2.9 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jamal (#7)
t-statistic
18.80
p-value
2.92e-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
WAS 81.5–84.9 GS 77.0–82.7 Overlap 1.25 pts Actual: WAS 69, GS 74

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 79.9) — by 3.3 points. The ranges overlap some — there's real uncertainty here.

WAS 81.7–84.5 GS 77.5–82.3 Overlap 0.62 pts Actual: WAS 69, GS 74

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 79.9) — by 3.3 points. The ranges barely touch.

WAS 82.0–84.2 GS 77.8–82.0 Overlap 0.01 pts Actual: WAS 69, GS 74

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 79.9) — by 3.3 points. The ranges barely touch.

WAS 82.1–84.1 GS 78.0–81.8 No overlap Actual: WAS 69, GS 74

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 79.9) — by 3.3 points. The 80% ranges don't overlap at all — a confident model.

WAS 82.2–84.0 GS 78.2–81.6 No overlap Actual: WAS 69, GS 74

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.2) over Golden State Valkyries (avg. 79.9) — by 3.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jordan (#8)
t-statistic
20.65
p-value
9.12e-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
WAS 81.1–85.2 GS 77.4–82.7 Overlap 1.59 pts Actual: WAS 69, GS 74

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 80.0) — by 3.1 points. The ranges overlap some — there's real uncertainty here.

WAS 81.4–84.9 GS 77.9–82.2 Overlap 0.84 pts Actual: WAS 69, GS 74

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 80.0) — by 3.1 points. The ranges barely touch.

WAS 81.6–84.6 GS 78.1–82.0 Overlap 0.35 pts Actual: WAS 69, GS 74

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 80.0) — by 3.1 points. The ranges barely touch.

WAS 81.8–84.5 GS 78.3–81.7 No overlap Actual: WAS 69, GS 74

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 80.0) — by 3.1 points. The 80% ranges don't overlap at all — a confident model.

WAS 81.9–84.3 GS 78.5–81.6 No overlap Actual: WAS 69, GS 74

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.1) over Golden State Valkyries (avg. 80.0) — by 3.1 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
20.50
p-value
1.93e-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.

Maya Jefferson
WAS 81.2–85.5 GS 77.5–82.8 Overlap 1.61 pts Actual: WAS 69, GS 74

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.3) over Golden State Valkyries (avg. 80.2) — by 3.2 points. The ranges overlap some — there's real uncertainty here.

WAS 81.5–85.1 GS 78.0–82.4 Overlap 0.84 pts Actual: WAS 69, GS 74

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.3) over Golden State Valkyries (avg. 80.2) — by 3.2 points. The ranges barely touch.

WAS 81.7–84.9 GS 78.2–82.1 Overlap 0.34 pts Actual: WAS 69, GS 74

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.3) over Golden State Valkyries (avg. 80.2) — by 3.2 points. The ranges barely touch.

WAS 81.9–84.7 GS 78.4–81.9 No overlap Actual: WAS 69, GS 74

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.3) over Golden State Valkyries (avg. 80.2) — by 3.2 points. The 80% ranges don't overlap at all — a confident model.

WAS 82.1–84.6 GS 78.6–81.7 No overlap Actual: WAS 69, GS 74

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.3) over Golden State Valkyries (avg. 80.2) — by 3.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Maya Jefferson (#10)
t-statistic
20.65
p-value
4.29e-50

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
WAS 81.0–85.1 GS 77.5–82.9 Overlap 1.88 pts Actual: WAS 69, GS 74

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.0) over Golden State Valkyries (avg. 80.2) — by 2.8 points. The ranges overlap some — there's real uncertainty here.

WAS 81.3–84.7 GS 78.0–82.4 Overlap 1.12 pts Actual: WAS 69, GS 74

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.0) over Golden State Valkyries (avg. 80.2) — by 2.8 points. The ranges overlap some — there's real uncertainty here.

WAS 81.5–84.5 GS 78.3–82.1 Overlap 0.63 pts Actual: WAS 69, GS 74

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.0) over Golden State Valkyries (avg. 80.2) — by 2.8 points. The ranges barely touch.

WAS 81.7–84.4 GS 78.5–81.9 Overlap 0.25 pts Actual: WAS 69, GS 74

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.0) over Golden State Valkyries (avg. 80.2) — by 2.8 points. The ranges barely touch.

WAS 81.8–84.2 GS 78.6–81.8 No overlap Actual: WAS 69, GS 74

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.0) over Golden State Valkyries (avg. 80.2) — by 2.8 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Lexi (#11)
t-statistic
18.66
p-value
3.56e-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.

Coach Sarah Watanabe
WAS 80.0–84.4 GS 77.8–82.7 Overlap 2.68 pts Actual: WAS 69, GS 74

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 82.2) over Golden State Valkyries (avg. 80.2) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

WAS 80.4–84.1 GS 78.2–82.3 Overlap 1.93 pts Actual: WAS 69, GS 74

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 82.2) over Golden State Valkyries (avg. 80.2) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

WAS 80.6–83.8 GS 78.4–82.1 Overlap 1.44 pts Actual: WAS 69, GS 74

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 82.2) over Golden State Valkyries (avg. 80.2) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

WAS 80.8–83.6 GS 78.6–81.9 Overlap 1.07 pts Actual: WAS 69, GS 74

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 82.2) over Golden State Valkyries (avg. 80.2) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

WAS 80.9–83.5 GS 78.8–81.7 Overlap 0.75 pts Actual: WAS 69, GS 74

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 82.2) over Golden State Valkyries (avg. 80.2) — by 2.0 points. The ranges barely touch.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
13.28
p-value
5.92e-29

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 — WAS at GS — Actual: WAS 69, GS 74
Level WAS range GS range Overlap Tol Warning Actual landed in range?
95% 80.7–85.5 77.6–83.1 2.4 pts — No
90% 81.1–85.1 78.0–82.7 1.57 pts — No
85% 81.4–84.9 78.3–82.4 1.03 pts — No
80% 81.6–84.7 78.5–82.2 0.62 pts — No
75% 81.7–84.5 78.7–82.0 0.27 pts — No
Reg — WAS at GS — Actual: WAS 69, GS 74
Level WAS range GS range Overlap Tol Warning Actual landed in range?
95% 81.5–85.7 77.5–83.5 2.01 pts — No
90% 81.7–85.0 78.0–83.1 1.4 pts — No
85% 81.9–85.0 78.3–82.7 0.87 pts — No
80% 81.9–84.8 78.6–82.5 0.59 pts — No
75% 81.9–84.5 78.8–82.3 0.36 pts — No
Dr. Wallace — WAS at GS — Actual: WAS 69, GS 74
Level WAS range GS range Overlap Tol Warning Actual landed in range?
95% 81.3–84.7 77.7–82.8 1.5 pts — No
90% 81.6–84.4 78.1–82.4 0.82 pts — No
85% 81.8–84.3 78.4–82.1 0.37 pts — No
80% 81.9–84.1 78.6–81.9 0.03 pts — No
75% 82.0–84.0 78.7–81.8 — pts — No
Kevin — WAS at GS — Actual: WAS 69, GS 74
Level WAS range GS range Overlap Tol Warning Actual landed in range?
95% 81.3–85.0 77.6–82.4 1.04 pts — No
90% 81.6–84.7 78.0–82.0 0.37 pts — No
85% 81.8–84.5 78.3–81.7 — pts — No
80% 82.0–84.4 78.4–81.5 — pts — No
75% 82.1–84.2 78.6–81.4 — pts — No
Dr. Lila Shah — WAS at GS — Actual: WAS 69, GS 74
Level WAS range GS range Overlap Tol Warning Actual landed in range?
95% 81.0–85.3 77.5–82.4 1.38 pts — No
90% 81.3–85.0 77.7–82.1 0.74 pts — No
85% 81.6–84.7 78.1–81.9 0.28 pts — No
80% 81.7–84.6 78.1–81.1 — pts — No
75% 81.9–84.4 78.3–81.0 — pts — No
Ice — WAS at GS — Actual: WAS 69, GS 74
Level WAS range GS range Overlap Tol Warning Actual landed in range?
95% 81.5–85.8 77.1–82.8 1.3 pts — No
90% 81.8–84.5 77.5–82.4 0.55 pts — No
85% 82.1–84.4 77.8–82.1 0.01 pts — No
80% 82.2–84.1 78.1–81.8 — pts — No
75% 82.3–84.0 78.3–81.6 — pts — No
Jamal — WAS at GS — Actual: WAS 69, GS 74
Level WAS range GS range Overlap Tol Warning Actual landed in range?
95% 81.0–85.4 77.8–82.9 1.91 pts — No
90% 81.3–85.1 78.2–82.5 1.14 pts — No
85% 81.6–84.8 78.4–82.2 0.64 pts — No
80% 81.7–84.7 78.6–82.0 0.25 pts — No
75% 81.9–84.5 78.8–81.8 — pts — No
Jordan — WAS at GS — Actual: WAS 69, GS 74
Level WAS range GS range Overlap Tol Warning Actual landed in range?
95% 81.5–84.9 77.0–82.7 1.25 pts — No
90% 81.7–84.5 77.5–82.3 0.62 pts — No
85% 82.0–84.2 77.8–82.0 0.01 pts — No
80% 82.1–84.1 78.0–81.8 — pts — No
75% 82.2–84.0 78.2–81.6 — pts — No
Darren "Dimes" Lin — WAS at GS — Actual: WAS 69, GS 74
Level WAS range GS range Overlap Tol Warning Actual landed in range?
95% 81.1–85.2 77.4–82.7 1.59 pts — No
90% 81.4–84.9 77.9–82.2 0.84 pts — No
85% 81.6–84.6 78.1–82.0 0.35 pts — No
80% 81.8–84.5 78.3–81.7 — pts — No
75% 81.9–84.3 78.5–81.6 — pts — No
Maya Jefferson — WAS at GS — Actual: WAS 69, GS 74
Level WAS range GS range Overlap Tol Warning Actual landed in range?
95% 81.2–85.5 77.5–82.8 1.61 pts — No
90% 81.5–85.1 78.0–82.4 0.84 pts — No
85% 81.7–84.9 78.2–82.1 0.34 pts — No
80% 81.9–84.7 78.4–81.9 — pts — No
75% 82.1–84.6 78.6–81.7 — pts — No
Lexi — WAS at GS — Actual: WAS 69, GS 74
Level WAS range GS range Overlap Tol Warning Actual landed in range?
95% 81.0–85.1 77.5–82.9 1.88 pts — No
90% 81.3–84.7 78.0–82.4 1.12 pts — No
85% 81.5–84.5 78.3–82.1 0.63 pts — No
80% 81.7–84.4 78.5–81.9 0.25 pts — No
75% 81.8–84.2 78.6–81.8 — pts — No
Coach Sarah Watanabe — WAS at GS — Actual: WAS 69, GS 74
Level WAS range GS range Overlap Tol Warning Actual landed in range?
95% 80.0–84.4 77.8–82.7 2.68 pts — No
90% 80.4–84.1 78.2–82.3 1.93 pts — No
85% 80.6–83.8 78.4–82.1 1.44 pts — No
80% 80.8–83.6 78.6–81.9 1.07 pts — No
75% 80.9–83.5 78.8–81.7 0.75 pts — No