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Phoenix Mercury at Golden State Valkyries

PHX 81 – GS 87

June 9, 2026 · Final

Reg

Best model for this game

Reg
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 PHX at GS

All 12 models’ predicted scores

PHX — one dot per model GS — one dot per model Actual: PHX 81, GS 87
Vince Chambers Tol Warning
PHX 82.2–86.7 GS 80.2–86.1 Overlap 3.95 pts Actual: PHX 81, GS 87

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.5) — by 2.0 points. The ranges overlap almost entirely, so one game could go either way.

PHX 82.5–86.4 GS 80.7–84.9 Overlap 2.35 pts Actual: PHX 81, GS 87

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.5) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

PHX 82.8–86.1 GS 80.9–84.4 Overlap 1.6 pts Actual: PHX 81, GS 87

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.5) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

PHX 83.0–85.9 GS 81.2–83.7 Overlap 0.75 pts Actual: PHX 81, GS 87

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.5) — by 2.0 points. The ranges barely touch.

PHX 83.1–85.8 GS 81.3–83.5 Overlap 0.39 pts Actual: PHX 81, GS 87

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.5) — by 2.0 points. The ranges barely touch.

Show the math
Model
Vince Chambers (#1)
t-statistic
10.38
p-value
2.52e-19

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

Reg
PHX 81.5–86.8 GS 79.4–85.7 Overlap 4.24 pts Actual: PHX 81, GS 87

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.1) over Golden State Valkyries (avg. 82.5) — by 1.6 points. The ranges overlap almost entirely, so one game could go either way.

PHX 81.9–86.3 GS 79.9–85.2 Overlap 3.3 pts Actual: PHX 81, GS 87

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.1) over Golden State Valkyries (avg. 82.5) — by 1.6 points. The ranges overlap almost entirely, so one game could go either way.

PHX 82.2–86.1 GS 80.2–84.9 Overlap 2.69 pts Actual: PHX 81, GS 87

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.1) over Golden State Valkyries (avg. 82.5) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

PHX 82.4–85.9 GS 80.5–84.6 Overlap 2.22 pts Actual: PHX 81, GS 87

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.1) over Golden State Valkyries (avg. 82.5) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

PHX 82.6–85.7 GS 80.7–84.4 Overlap 1.83 pts Actual: PHX 81, GS 87

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.1) over Golden State Valkyries (avg. 82.5) — by 1.6 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Reg (#2)
t-statistic
7.93
p-value
3.60e-13

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
PHX 81.9–86.4 GS 79.2–85.0 Overlap 3.16 pts Actual: PHX 81, GS 87

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.1) — by 2.0 points. The ranges overlap almost entirely, so one game could go either way.

PHX 82.3–86.1 GS 79.7–84.6 Overlap 2.32 pts Actual: PHX 81, GS 87

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.1) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

PHX 82.5–85.8 GS 80.0–84.3 Overlap 1.78 pts Actual: PHX 81, GS 87

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.1) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

PHX 82.7–85.7 GS 80.2–84.0 Overlap 1.36 pts Actual: PHX 81, GS 87

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.1) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

PHX 82.8–85.5 GS 80.4–83.8 Overlap 1.02 pts Actual: PHX 81, GS 87

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.1) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Dr. Wallace (#3)
t-statistic
11.33
p-value
4.51e-22

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

Kevin
PHX 81.9–87.0 GS 79.5–84.7 Overlap 2.79 pts Actual: PHX 81, GS 87

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.5) over Golden State Valkyries (avg. 82.1) — by 2.3 points. The ranges overlap some — there's real uncertainty here.

PHX 82.3–86.6 GS 79.9–84.3 Overlap 1.97 pts Actual: PHX 81, GS 87

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.5) over Golden State Valkyries (avg. 82.1) — by 2.3 points. The ranges overlap some — there's real uncertainty here.

PHX 82.6–86.3 GS 80.2–84.0 Overlap 1.43 pts Actual: PHX 81, GS 87

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.5) over Golden State Valkyries (avg. 82.1) — by 2.3 points. The ranges overlap some — there's real uncertainty here.

PHX 82.8–86.1 GS 80.4–83.8 Overlap 1.02 pts Actual: PHX 81, GS 87

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.5) over Golden State Valkyries (avg. 82.1) — by 2.3 points. The ranges overlap some — there's real uncertainty here.

PHX 83.0–85.9 GS 80.6–83.7 Overlap 0.68 pts Actual: PHX 81, GS 87

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.5) over Golden State Valkyries (avg. 82.1) — by 2.3 points. The ranges barely touch.

Show the math
Model
Kevin (#4)
t-statistic
13.28
p-value
8.83e-28

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 Tol Warning
PHX 81.5–86.3 GS 79.3–84.1 Overlap 2.63 pts Actual: PHX 81, GS 87

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 83.9) over Golden State Valkyries (avg. 81.3) — by 2.6 points. The ranges overlap some — there's real uncertainty here.

PHX 81.9–85.9 GS 79.6–83.4 Overlap 1.53 pts Actual: PHX 81, GS 87

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 83.9) over Golden State Valkyries (avg. 81.3) — by 2.6 points. The ranges overlap some — there's real uncertainty here.

PHX 82.1–85.6 GS 79.8–83.3 Overlap 1.14 pts Actual: PHX 81, GS 87

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 83.9) over Golden State Valkyries (avg. 81.3) — by 2.6 points. The ranges overlap some — there's real uncertainty here.

PHX 82.3–85.5 GS 79.9–83.0 Overlap 0.66 pts Actual: PHX 81, GS 87

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 83.9) over Golden State Valkyries (avg. 81.3) — by 2.6 points. The ranges barely touch.

PHX 82.5–85.3 GS 80.0–82.7 Overlap 0.24 pts Actual: PHX 81, GS 87

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 83.9) over Golden State Valkyries (avg. 81.3) — by 2.6 points. The ranges barely touch.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
14.59
p-value
4.07e-31

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
PHX 82.0–86.6 GS 78.8–85.5 Overlap 3.51 pts Actual: PHX 81, GS 87

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.3) over Golden State Valkyries (avg. 82.2) — by 2.1 points. The ranges overlap almost entirely, so one game could go either way.

PHX 82.4–86.2 GS 79.3–85.0 Overlap 2.61 pts Actual: PHX 81, GS 87

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.3) over Golden State Valkyries (avg. 82.2) — by 2.1 points. The ranges overlap some — there's real uncertainty here.

PHX 82.6–86.0 GS 79.7–84.6 Overlap 2.01 pts Actual: PHX 81, GS 87

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.3) over Golden State Valkyries (avg. 82.2) — by 2.1 points. The ranges overlap some — there's real uncertainty here.

PHX 82.8–85.8 GS 80.0–84.4 Overlap 1.56 pts Actual: PHX 81, GS 87

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.3) over Golden State Valkyries (avg. 82.2) — by 2.1 points. The ranges overlap some — there's real uncertainty here.

PHX 83.0–85.6 GS 80.2–84.1 Overlap 1.18 pts Actual: PHX 81, GS 87

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.3) over Golden State Valkyries (avg. 82.2) — by 2.1 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Ice (#6)
t-statistic
10.83
p-value
2.22e-20

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

Jamal
PHX 82.3–86.4 GS 79.5–84.8 Overlap 2.57 pts Actual: PHX 81, GS 87

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.2) — by 2.2 points. The ranges overlap some — there's real uncertainty here.

PHX 82.6–86.1 GS 79.9–84.4 Overlap 1.8 pts Actual: PHX 81, GS 87

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.2) — by 2.2 points. The ranges overlap some — there's real uncertainty here.

PHX 82.8–85.9 GS 80.2–84.1 Overlap 1.3 pts Actual: PHX 81, GS 87

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.2) — by 2.2 points. The ranges overlap some — there's real uncertainty here.

PHX 83.0–85.7 GS 80.4–83.9 Overlap 0.92 pts Actual: PHX 81, GS 87

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.2) — by 2.2 points. The ranges barely touch.

PHX 83.1–85.6 GS 80.6–83.7 Overlap 0.6 pts Actual: PHX 81, GS 87

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.2) — by 2.2 points. The ranges barely touch.

Show the math
Model
Jamal (#7)
t-statistic
13.36
p-value
1.46e-27

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
PHX 82.3–86.4 GS 79.3–84.8 Overlap 2.5 pts Actual: PHX 81, GS 87

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.0) — by 2.3 points. The ranges overlap some — there's real uncertainty here.

PHX 82.6–86.1 GS 79.7–84.4 Overlap 1.72 pts Actual: PHX 81, GS 87

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.0) — by 2.3 points. The ranges overlap some — there's real uncertainty here.

PHX 82.8–85.9 GS 80.0–84.1 Overlap 1.22 pts Actual: PHX 81, GS 87

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.0) — by 2.3 points. The ranges overlap some — there's real uncertainty here.

PHX 83.0–85.7 GS 80.2–83.8 Overlap 0.83 pts Actual: PHX 81, GS 87

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.0) — by 2.3 points. The ranges barely touch.

PHX 83.1–85.6 GS 80.4–83.7 Overlap 0.51 pts Actual: PHX 81, GS 87

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.0) — by 2.3 points. The ranges barely touch.

Show the math
Model
Jordan (#8)
t-statistic
13.93
p-value
6.56e-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.

Darren "Dimes" Lin
PHX 82.2–86.6 GS 79.6–85.0 Overlap 2.83 pts Actual: PHX 81, GS 87

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.3) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

PHX 82.5–86.2 GS 80.1–84.6 Overlap 2.05 pts Actual: PHX 81, GS 87

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.3) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

PHX 82.7–86.0 GS 80.3–84.3 Overlap 1.54 pts Actual: PHX 81, GS 87

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.3) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

PHX 82.9–85.8 GS 80.6–84.1 Overlap 1.14 pts Actual: PHX 81, GS 87

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.3) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

PHX 83.1–85.7 GS 80.7–83.9 Overlap 0.82 pts Actual: PHX 81, GS 87

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.3) — by 2.0 points. The ranges barely touch.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
12.19
p-value
1.68e-24

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
PHX 82.5–86.4 GS 79.2–85.1 Overlap 2.62 pts Actual: PHX 81, GS 87

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.1) — by 2.3 points. The ranges overlap some — there's real uncertainty here.

PHX 82.8–86.1 GS 79.7–84.6 Overlap 1.83 pts Actual: PHX 81, GS 87

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.1) — by 2.3 points. The ranges overlap some — there's real uncertainty here.

PHX 83.0–85.9 GS 80.0–84.3 Overlap 1.32 pts Actual: PHX 81, GS 87

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.1) — by 2.3 points. The ranges overlap some — there's real uncertainty here.

PHX 83.2–85.7 GS 80.2–84.1 Overlap 0.92 pts Actual: PHX 81, GS 87

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.1) — by 2.3 points. The ranges barely touch.

PHX 83.3–85.6 GS 80.4–83.9 Overlap 0.59 pts Actual: PHX 81, GS 87

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.4) over Golden State Valkyries (avg. 82.1) — by 2.3 points. The ranges barely touch.

Show the math
Model
Maya Jefferson (#10)
t-statistic
13.34
p-value
7.90e-27

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

Lexi Tol Warning
PHX 81.5–86.9 GS 79.9–84.9 Overlap 3.47 pts Actual: PHX 81, GS 87

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.2) — by 2.0 points. The ranges overlap almost entirely, so one game could go either way.

PHX 81.9–86.5 GS 80.2–84.6 Overlap 2.67 pts Actual: PHX 81, GS 87

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.2) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

PHX 82.2–86.2 GS 80.3–84.4 Overlap 2.17 pts Actual: PHX 81, GS 87

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.2) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

PHX 82.4–86.0 GS 80.5–84.2 Overlap 1.76 pts Actual: PHX 81, GS 87

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.2) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

PHX 82.6–85.8 GS 80.6–84.0 Overlap 1.41 pts Actual: PHX 81, GS 87

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.2) — by 2.0 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Lexi (#11)
t-statistic
9.80
p-value
5.01e-18

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

Coach Sarah Watanabe
PHX 81.6–86.9 GS 80.1–84.8 Overlap 3.19 pts Actual: PHX 81, GS 87

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.4) — by 1.8 points. The ranges overlap almost entirely, so one game could go either way.

PHX 82.0–86.5 GS 80.5–84.4 Overlap 2.38 pts Actual: PHX 81, GS 87

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.4) — by 1.8 points. The ranges overlap some — there's real uncertainty here.

PHX 82.3–86.2 GS 80.7–84.1 Overlap 1.86 pts Actual: PHX 81, GS 87

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.4) — by 1.8 points. The ranges overlap some — there's real uncertainty here.

PHX 82.5–86.0 GS 80.9–83.9 Overlap 1.46 pts Actual: PHX 81, GS 87

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.4) — by 1.8 points. The ranges overlap some — there's real uncertainty here.

PHX 82.7–85.8 GS 81.0–83.8 Overlap 1.12 pts Actual: PHX 81, GS 87

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.2) over Golden State Valkyries (avg. 82.4) — by 1.8 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
10.58
p-value
3.32e-20

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

View as table
Vince Chambers — PHX at GS — Actual: PHX 81, GS 87
Level PHX range GS range Overlap Tol Warning Actual landed in range?
95% 82.2–86.7 80.2–86.1 3.95 pts Yes No
90% 82.5–86.4 80.7–84.9 2.35 pts Yes No
85% 82.8–86.1 80.9–84.4 1.6 pts Yes No
80% 83.0–85.9 81.2–83.7 0.75 pts Yes No
75% 83.1–85.8 81.3–83.5 0.39 pts Yes No
Reg — PHX at GS — Actual: PHX 81, GS 87
Level PHX range GS range Overlap Tol Warning Actual landed in range?
95% 81.5–86.8 79.4–85.7 4.24 pts — No
90% 81.9–86.3 79.9–85.2 3.3 pts — No
85% 82.2–86.1 80.2–84.9 2.69 pts — No
80% 82.4–85.9 80.5–84.6 2.22 pts — No
75% 82.6–85.7 80.7–84.4 1.83 pts — No
Dr. Wallace — PHX at GS — Actual: PHX 81, GS 87
Level PHX range GS range Overlap Tol Warning Actual landed in range?
95% 81.9–86.4 79.2–85.0 3.16 pts — No
90% 82.3–86.1 79.7–84.6 2.32 pts — No
85% 82.5–85.8 80.0–84.3 1.78 pts — No
80% 82.7–85.7 80.2–84.0 1.36 pts — No
75% 82.8–85.5 80.4–83.8 1.02 pts — No
Kevin — PHX at GS — Actual: PHX 81, GS 87
Level PHX range GS range Overlap Tol Warning Actual landed in range?
95% 81.9–87.0 79.5–84.7 2.79 pts — No
90% 82.3–86.6 79.9–84.3 1.97 pts — No
85% 82.6–86.3 80.2–84.0 1.43 pts — No
80% 82.8–86.1 80.4–83.8 1.02 pts — No
75% 83.0–85.9 80.6–83.7 0.68 pts — No
Dr. Lila Shah — PHX at GS — Actual: PHX 81, GS 87
Level PHX range GS range Overlap Tol Warning Actual landed in range?
95% 81.5–86.3 79.3–84.1 2.63 pts Yes No
90% 81.9–85.9 79.6–83.4 1.53 pts Yes No
85% 82.1–85.6 79.8–83.3 1.14 pts Yes No
80% 82.3–85.5 79.9–83.0 0.66 pts Yes No
75% 82.5–85.3 80.0–82.7 0.24 pts Yes No
Ice — PHX at GS — Actual: PHX 81, GS 87
Level PHX range GS range Overlap Tol Warning Actual landed in range?
95% 82.0–86.6 78.8–85.5 3.51 pts — No
90% 82.4–86.2 79.3–85.0 2.61 pts — No
85% 82.6–86.0 79.7–84.6 2.01 pts — No
80% 82.8–85.8 80.0–84.4 1.56 pts — No
75% 83.0–85.6 80.2–84.1 1.18 pts — No
Jamal — PHX at GS — Actual: PHX 81, GS 87
Level PHX range GS range Overlap Tol Warning Actual landed in range?
95% 82.3–86.4 79.5–84.8 2.57 pts — No
90% 82.6–86.1 79.9–84.4 1.8 pts — No
85% 82.8–85.9 80.2–84.1 1.3 pts — No
80% 83.0–85.7 80.4–83.9 0.92 pts — No
75% 83.1–85.6 80.6–83.7 0.6 pts — No
Jordan — PHX at GS — Actual: PHX 81, GS 87
Level PHX range GS range Overlap Tol Warning Actual landed in range?
95% 82.3–86.4 79.3–84.8 2.5 pts — No
90% 82.6–86.1 79.7–84.4 1.72 pts — No
85% 82.8–85.9 80.0–84.1 1.22 pts — No
80% 83.0–85.7 80.2–83.8 0.83 pts — No
75% 83.1–85.6 80.4–83.7 0.51 pts — No
Darren "Dimes" Lin — PHX at GS — Actual: PHX 81, GS 87
Level PHX range GS range Overlap Tol Warning Actual landed in range?
95% 82.2–86.6 79.6–85.0 2.83 pts — No
90% 82.5–86.2 80.1–84.6 2.05 pts — No
85% 82.7–86.0 80.3–84.3 1.54 pts — No
80% 82.9–85.8 80.6–84.1 1.14 pts — No
75% 83.1–85.7 80.7–83.9 0.82 pts — No
Maya Jefferson — PHX at GS — Actual: PHX 81, GS 87
Level PHX range GS range Overlap Tol Warning Actual landed in range?
95% 82.5–86.4 79.2–85.1 2.62 pts — No
90% 82.8–86.1 79.7–84.6 1.83 pts — No
85% 83.0–85.9 80.0–84.3 1.32 pts — No
80% 83.2–85.7 80.2–84.1 0.92 pts — No
75% 83.3–85.6 80.4–83.9 0.59 pts — No
Lexi — PHX at GS — Actual: PHX 81, GS 87
Level PHX range GS range Overlap Tol Warning Actual landed in range?
95% 81.5–86.9 79.9–84.9 3.47 pts Yes No
90% 81.9–86.5 80.2–84.6 2.67 pts Yes No
85% 82.2–86.2 80.3–84.4 2.17 pts Yes No
80% 82.4–86.0 80.5–84.2 1.76 pts Yes No
75% 82.6–85.8 80.6–84.0 1.41 pts Yes No
Coach Sarah Watanabe — PHX at GS — Actual: PHX 81, GS 87
Level PHX range GS range Overlap Tol Warning Actual landed in range?
95% 81.6–86.9 80.1–84.8 3.19 pts — No
90% 82.0–86.5 80.5–84.4 2.38 pts — No
85% 82.3–86.2 80.7–84.1 1.86 pts — No
80% 82.5–86.0 80.9–83.9 1.46 pts — No
75% 82.7–85.8 81.0–83.8 1.12 pts — No