Clay's Almanac
WNBA · July 6, 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

Golden State Valkyries at Washington Mystics

GS 62 – WAS 49

July 6, 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 GS at WAS

All 12 models’ predicted scores

GS — one dot per model WAS — one dot per model Actual: GS 62, WAS 49
Vince Chambers
GS 77.0–83.9 WAS 81.1–86.3 Overlap 2.85 pts Actual: GS 62, WAS 49

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.4) — by 3.2 points. The ranges overlap some — there's real uncertainty here.

GS 77.5–83.4 WAS 81.5–85.8 Overlap 1.87 pts Actual: GS 62, WAS 49

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.4) — by 3.2 points. The ranges overlap some — there's real uncertainty here.

GS 77.9–83.0 WAS 81.8–85.6 Overlap 1.24 pts Actual: GS 62, WAS 49

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.4) — by 3.2 points. The ranges overlap some — there's real uncertainty here.

GS 78.2–82.7 WAS 82.0–85.4 Overlap 0.75 pts Actual: GS 62, WAS 49

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.4) — by 3.2 points. The ranges barely touch.

GS 78.4–82.5 WAS 82.1–85.2 Overlap 0.34 pts Actual: GS 62, WAS 49

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.4) — by 3.2 points. The ranges barely touch.

Show the math
Model
Vince Chambers (#1)
t-statistic
-16.60
p-value
2.51e-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.

Reg
GS 77.0–83.9 WAS 81.1–86.5 Overlap 2.82 pts Actual: GS 62, WAS 49

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.8) over Golden State Valkyries (avg. 80.4) — by 3.3 points. The ranges overlap some — there's real uncertainty here.

GS 77.6–83.3 WAS 81.5–86.0 Overlap 1.83 pts Actual: GS 62, WAS 49

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.8) over Golden State Valkyries (avg. 80.4) — by 3.3 points. The ranges overlap some — there's real uncertainty here.

GS 77.9–83.0 WAS 81.8–85.7 Overlap 1.19 pts Actual: GS 62, WAS 49

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.8) over Golden State Valkyries (avg. 80.4) — by 3.3 points. The ranges overlap some — there's real uncertainty here.

GS 78.2–82.7 WAS 82.0–85.5 Overlap 0.69 pts Actual: GS 62, WAS 49

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.8) over Golden State Valkyries (avg. 80.4) — by 3.3 points. The ranges barely touch.

GS 78.4–82.5 WAS 82.2–85.3 Overlap 0.28 pts Actual: GS 62, WAS 49

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.8) over Golden State Valkyries (avg. 80.4) — by 3.3 points. The ranges barely touch.

Show the math
Model
Reg (#2)
t-statistic
-16.96
p-value
9.84e-40

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
GS 77.3–83.8 WAS 81.9–86.4 Overlap 1.89 pts Actual: GS 62, WAS 49

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.6) over Golden State Valkyries (avg. 80.5) — by 3.1 points. The ranges overlap some — there's real uncertainty here.

GS 77.8–83.3 WAS 82.1–85.6 Overlap 1.2 pts Actual: GS 62, WAS 49

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.6) over Golden State Valkyries (avg. 80.5) — by 3.1 points. The ranges overlap some — there's real uncertainty here.

GS 78.1–82.9 WAS 82.4–85.3 Overlap 0.56 pts Actual: GS 62, WAS 49

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.6) over Golden State Valkyries (avg. 80.5) — by 3.1 points. The ranges barely touch.

GS 78.4–82.7 WAS 82.5–85.1 Overlap 0.18 pts Actual: GS 62, WAS 49

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.6) over Golden State Valkyries (avg. 80.5) — by 3.1 points. The ranges barely touch.

GS 78.6–82.4 WAS 82.6–84.8 No overlap Actual: GS 62, WAS 49

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.6) over Golden State Valkyries (avg. 80.5) — by 3.1 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Wallace (#3)
t-statistic
-16.74
p-value
1.06e-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.

Kevin
GS 77.5–83.7 WAS 81.8–85.8 Overlap 1.84 pts Actual: GS 62, WAS 49

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.8) over Golden State Valkyries (avg. 80.6) — by 3.2 points. The ranges overlap some — there's real uncertainty here.

GS 77.9–83.2 WAS 82.1–85.5 Overlap 1.02 pts Actual: GS 62, WAS 49

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.8) over Golden State Valkyries (avg. 80.6) — by 3.2 points. The ranges overlap some — there's real uncertainty here.

GS 78.3–82.8 WAS 82.3–85.2 Overlap 0.49 pts Actual: GS 62, WAS 49

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.8) over Golden State Valkyries (avg. 80.6) — by 3.2 points. The ranges barely touch.

GS 78.5–82.6 WAS 82.5–85.1 Overlap 0.08 pts Actual: GS 62, WAS 49

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.8) over Golden State Valkyries (avg. 80.6) — by 3.2 points. The ranges barely touch.

GS 78.7–82.4 WAS 82.6–85.0 No overlap Actual: GS 62, WAS 49

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.8) over Golden State Valkyries (avg. 80.6) — by 3.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Kevin (#4)
t-statistic
-19.58
p-value
4.69e-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.

Dr. Lila Shah
GS 77.9–83.7 WAS 82.1–86.0 Overlap 1.55 pts Actual: GS 62, WAS 49

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.9) over Golden State Valkyries (avg. 80.8) — by 3.1 points. The ranges overlap some — there's real uncertainty here.

GS 78.3–83.2 WAS 82.3–85.8 Overlap 0.89 pts Actual: GS 62, WAS 49

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.9) over Golden State Valkyries (avg. 80.8) — by 3.1 points. The ranges barely touch.

GS 78.6–82.9 WAS 82.6–85.5 Overlap 0.29 pts Actual: GS 62, WAS 49

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.9) over Golden State Valkyries (avg. 80.8) — by 3.1 points. The ranges barely touch.

GS 78.9–82.7 WAS 82.7–85.4 No overlap Actual: GS 62, WAS 49

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.9) over Golden State Valkyries (avg. 80.8) — by 3.1 points. The 80% ranges don't overlap at all — a confident model.

GS 79.1–82.5 WAS 82.9–85.3 No overlap Actual: GS 62, WAS 49

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.9) over Golden State Valkyries (avg. 80.8) — by 3.1 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
-18.65
p-value
1.57e-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.

Ice
GS 77.1–83.6 WAS 81.5–85.5 Overlap 2.01 pts Actual: GS 62, WAS 49

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.3) — by 3.2 points. The ranges overlap some — there's real uncertainty here.

GS 77.6–83.0 WAS 81.9–85.2 Overlap 1.17 pts Actual: GS 62, WAS 49

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.3) — by 3.2 points. The ranges overlap some — there's real uncertainty here.

GS 77.9–82.7 WAS 82.1–85.0 Overlap 0.62 pts Actual: GS 62, WAS 49

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.3) — by 3.2 points. The ranges barely touch.

GS 78.2–82.4 WAS 82.2–84.8 Overlap 0.2 pts Actual: GS 62, WAS 49

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.3) — by 3.2 points. The ranges barely touch.

GS 78.4–82.2 WAS 82.4–84.7 No overlap Actual: GS 62, WAS 49

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.3) — by 3.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Ice (#6)
t-statistic
-18.86
p-value
8.32e-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.

Jamal
GS 78.0–83.3 WAS 81.4–85.8 Overlap 1.88 pts Actual: GS 62, WAS 49

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.6) over Golden State Valkyries (avg. 80.2) — by 3.4 points. The ranges overlap some — there's real uncertainty here.

GS 78.4–82.9 WAS 81.7–85.4 Overlap 1.21 pts Actual: GS 62, WAS 49

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.6) over Golden State Valkyries (avg. 80.2) — by 3.4 points. The ranges overlap some — there's real uncertainty here.

GS 78.4–82.6 WAS 82.0–85.2 Overlap 0.61 pts Actual: GS 62, WAS 49

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.6) over Golden State Valkyries (avg. 80.2) — by 3.4 points. The ranges barely touch.

GS 78.4–82.2 WAS 82.1–85.0 Overlap 0.08 pts Actual: GS 62, WAS 49

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.6) over Golden State Valkyries (avg. 80.2) — by 3.4 points. The ranges barely touch.

GS 78.6–82.0 WAS 82.3–84.9 No overlap Actual: GS 62, WAS 49

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.6) over Golden State Valkyries (avg. 80.2) — by 3.4 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jamal (#7)
t-statistic
-18.82
p-value
2.19e-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.

Jordan
GS 77.3–83.1 WAS 81.3–85.7 Overlap 1.76 pts Actual: GS 62, WAS 49

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.1) — by 3.3 points. The ranges overlap some — there's real uncertainty here.

GS 77.7–82.6 WAS 81.7–85.3 Overlap 0.93 pts Actual: GS 62, WAS 49

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.1) — by 3.3 points. The ranges barely touch.

GS 78.0–82.3 WAS 81.9–85.1 Overlap 0.39 pts Actual: GS 62, WAS 49

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.1) — by 3.3 points. The ranges barely touch.

GS 78.3–82.0 WAS 82.1–84.9 No overlap Actual: GS 62, WAS 49

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.1) — by 3.3 points. The 80% ranges don't overlap at all — a confident model.

GS 78.5–81.9 WAS 82.2–84.8 No overlap Actual: GS 62, WAS 49

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.1) — by 3.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jordan (#8)
t-statistic
-20.42
p-value
1.12e-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.

Darren "Dimes" Lin
GS 77.2–83.5 WAS 81.5–85.8 Overlap 1.97 pts Actual: GS 62, WAS 49

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.4) — by 3.3 points. The ranges overlap some — there's real uncertainty here.

GS 77.7–83.0 WAS 81.9–85.5 Overlap 1.12 pts Actual: GS 62, WAS 49

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.4) — by 3.3 points. The ranges overlap some — there's real uncertainty here.

GS 78.0–82.7 WAS 82.1–85.3 Overlap 0.56 pts Actual: GS 62, WAS 49

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.4) — by 3.3 points. The ranges barely touch.

GS 78.3–82.4 WAS 82.3–85.1 Overlap 0.13 pts Actual: GS 62, WAS 49

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.4) — by 3.3 points. The ranges barely touch.

GS 78.5–82.2 WAS 82.4–85.0 No overlap Actual: GS 62, WAS 49

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.4) — by 3.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
-19.36
p-value
5.95e-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.

Maya Jefferson
GS 77.3–83.1 WAS 81.4–85.6 Overlap 1.68 pts Actual: GS 62, WAS 49

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.2) — by 3.3 points. The ranges overlap some — there's real uncertainty here.

GS 77.7–82.6 WAS 81.7–85.3 Overlap 0.87 pts Actual: GS 62, WAS 49

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.2) — by 3.3 points. The ranges barely touch.

GS 78.0–82.3 WAS 81.9–85.1 Overlap 0.35 pts Actual: GS 62, WAS 49

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.2) — by 3.3 points. The ranges barely touch.

GS 78.3–82.1 WAS 82.1–84.9 No overlap Actual: GS 62, WAS 49

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.2) — by 3.3 points. The 80% ranges don't overlap at all — a confident model.

GS 78.5–81.9 WAS 82.3–84.8 No overlap Actual: GS 62, WAS 49

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.5) over Golden State Valkyries (avg. 80.2) — by 3.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Maya Jefferson (#10)
t-statistic
-20.60
p-value
4.50e-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.

Lexi
GS 77.0–83.6 WAS 81.4–86.0 Overlap 2.18 pts Actual: GS 62, WAS 49

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.3) — by 3.4 points. The ranges overlap some — there's real uncertainty here.

GS 77.5–83.0 WAS 81.8–85.6 Overlap 1.28 pts Actual: GS 62, WAS 49

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.3) — by 3.4 points. The ranges overlap some — there's real uncertainty here.

GS 77.9–82.7 WAS 82.0–85.4 Overlap 0.69 pts Actual: GS 62, WAS 49

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.3) — by 3.4 points. The ranges barely touch.

GS 78.1–82.4 WAS 82.2–85.2 Overlap 0.24 pts Actual: GS 62, WAS 49

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.3) — by 3.4 points. The ranges barely touch.

GS 78.4–82.2 WAS 82.3–85.1 No overlap Actual: GS 62, WAS 49

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 83.7) over Golden State Valkyries (avg. 80.3) — by 3.4 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Lexi (#11)
t-statistic
-18.84
p-value
6.87e-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
GS 76.0–83.8 WAS 81.1–84.8 Overlap 2.66 pts Actual: GS 62, WAS 49

In 95 out of 100 simulated runs, leans Washington Mystics (avg. 82.7) over Golden State Valkyries (avg. 79.9) — by 2.8 points. The ranges overlap some — there's real uncertainty here.

GS 76.6–83.2 WAS 81.5–84.4 Overlap 1.66 pts Actual: GS 62, WAS 49

In 90 out of 100 simulated runs, leans Washington Mystics (avg. 82.7) over Golden State Valkyries (avg. 79.9) — by 2.8 points. The ranges overlap some — there's real uncertainty here.

GS 77.0–82.8 WAS 81.7–84.2 Overlap 1.06 pts Actual: GS 62, WAS 49

In 85 out of 100 simulated runs, leans Washington Mystics (avg. 82.7) over Golden State Valkyries (avg. 79.9) — by 2.8 points. The ranges overlap some — there's real uncertainty here.

GS 77.3–82.4 WAS 81.7–84.0 Overlap 0.71 pts Actual: GS 62, WAS 49

In 80 out of 100 simulated runs, leans Washington Mystics (avg. 82.7) over Golden State Valkyries (avg. 79.9) — by 2.8 points. The ranges barely touch.

GS 77.6–82.2 WAS 81.8–83.8 Overlap 0.42 pts Actual: GS 62, WAS 49

In 75 out of 100 simulated runs, leans Washington Mystics (avg. 82.7) over Golden State Valkyries (avg. 79.9) — by 2.8 points. The ranges barely touch.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
-14.19
p-value
1.80e-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 — GS at WAS — Actual: GS 62, WAS 49
Level GS range WAS range Overlap Tol Warning Actual landed in range?
95% 77.0–83.9 81.1–86.3 2.85 pts — No
90% 77.5–83.4 81.5–85.8 1.87 pts — No
85% 77.9–83.0 81.8–85.6 1.24 pts — No
80% 78.2–82.7 82.0–85.4 0.75 pts — No
75% 78.4–82.5 82.1–85.2 0.34 pts — No
Reg — GS at WAS — Actual: GS 62, WAS 49
Level GS range WAS range Overlap Tol Warning Actual landed in range?
95% 77.0–83.9 81.1–86.5 2.82 pts — No
90% 77.6–83.3 81.5–86.0 1.83 pts — No
85% 77.9–83.0 81.8–85.7 1.19 pts — No
80% 78.2–82.7 82.0–85.5 0.69 pts — No
75% 78.4–82.5 82.2–85.3 0.28 pts — No
Dr. Wallace — GS at WAS — Actual: GS 62, WAS 49
Level GS range WAS range Overlap Tol Warning Actual landed in range?
95% 77.3–83.8 81.9–86.4 1.89 pts — No
90% 77.8–83.3 82.1–85.6 1.2 pts — No
85% 78.1–82.9 82.4–85.3 0.56 pts — No
80% 78.4–82.7 82.5–85.1 0.18 pts — No
75% 78.6–82.4 82.6–84.8 — pts — No
Kevin — GS at WAS — Actual: GS 62, WAS 49
Level GS range WAS range Overlap Tol Warning Actual landed in range?
95% 77.5–83.7 81.8–85.8 1.84 pts — No
90% 77.9–83.2 82.1–85.5 1.02 pts — No
85% 78.3–82.8 82.3–85.2 0.49 pts — No
80% 78.5–82.6 82.5–85.1 0.08 pts — No
75% 78.7–82.4 82.6–85.0 — pts — No
Dr. Lila Shah — GS at WAS — Actual: GS 62, WAS 49
Level GS range WAS range Overlap Tol Warning Actual landed in range?
95% 77.9–83.7 82.1–86.0 1.55 pts — No
90% 78.3–83.2 82.3–85.8 0.89 pts — No
85% 78.6–82.9 82.6–85.5 0.29 pts — No
80% 78.9–82.7 82.7–85.4 — pts — No
75% 79.1–82.5 82.9–85.3 — pts — No
Ice — GS at WAS — Actual: GS 62, WAS 49
Level GS range WAS range Overlap Tol Warning Actual landed in range?
95% 77.1–83.6 81.5–85.5 2.01 pts — No
90% 77.6–83.0 81.9–85.2 1.17 pts — No
85% 77.9–82.7 82.1–85.0 0.62 pts — No
80% 78.2–82.4 82.2–84.8 0.2 pts — No
75% 78.4–82.2 82.4–84.7 — pts — No
Jamal — GS at WAS — Actual: GS 62, WAS 49
Level GS range WAS range Overlap Tol Warning Actual landed in range?
95% 78.0–83.3 81.4–85.8 1.88 pts — No
90% 78.4–82.9 81.7–85.4 1.21 pts — No
85% 78.4–82.6 82.0–85.2 0.61 pts — No
80% 78.4–82.2 82.1–85.0 0.08 pts — No
75% 78.6–82.0 82.3–84.9 — pts — No
Jordan — GS at WAS — Actual: GS 62, WAS 49
Level GS range WAS range Overlap Tol Warning Actual landed in range?
95% 77.3–83.1 81.3–85.7 1.76 pts — No
90% 77.7–82.6 81.7–85.3 0.93 pts — No
85% 78.0–82.3 81.9–85.1 0.39 pts — No
80% 78.3–82.0 82.1–84.9 — pts — No
75% 78.5–81.9 82.2–84.8 — pts — No
Darren "Dimes" Lin — GS at WAS — Actual: GS 62, WAS 49
Level GS range WAS range Overlap Tol Warning Actual landed in range?
95% 77.2–83.5 81.5–85.8 1.97 pts — No
90% 77.7–83.0 81.9–85.5 1.12 pts — No
85% 78.0–82.7 82.1–85.3 0.56 pts — No
80% 78.3–82.4 82.3–85.1 0.13 pts — No
75% 78.5–82.2 82.4–85.0 — pts — No
Maya Jefferson — GS at WAS — Actual: GS 62, WAS 49
Level GS range WAS range Overlap Tol Warning Actual landed in range?
95% 77.3–83.1 81.4–85.6 1.68 pts — No
90% 77.7–82.6 81.7–85.3 0.87 pts — No
85% 78.0–82.3 81.9–85.1 0.35 pts — No
80% 78.3–82.1 82.1–84.9 — pts — No
75% 78.5–81.9 82.3–84.8 — pts — No
Lexi — GS at WAS — Actual: GS 62, WAS 49
Level GS range WAS range Overlap Tol Warning Actual landed in range?
95% 77.0–83.6 81.4–86.0 2.18 pts — No
90% 77.5–83.0 81.8–85.6 1.28 pts — No
85% 77.9–82.7 82.0–85.4 0.69 pts — No
80% 78.1–82.4 82.2–85.2 0.24 pts — No
75% 78.4–82.2 82.3–85.1 — pts — No
Coach Sarah Watanabe — GS at WAS — Actual: GS 62, WAS 49
Level GS range WAS range Overlap Tol Warning Actual landed in range?
95% 76.0–83.8 81.1–84.8 2.66 pts — No
90% 76.6–83.2 81.5–84.4 1.66 pts — No
85% 77.0–82.8 81.7–84.2 1.06 pts — No
80% 77.3–82.4 81.7–84.0 0.71 pts — No
75% 77.6–82.2 81.8–83.8 0.42 pts — No