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Toronto Tempo at Phoenix Mercury

TOR 69 – PHX 101

August 29, 2026 · Final

Vince Chambers

Best model for this game

Vince Chambers
All models: 6-6
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 TOR at PHX

All 12 models’ predicted scores

TOR — one dot per model PHX — one dot per model Actual: TOR 69, PHX 101
Vince Chambers
TOR 80.9–85.3 PHX 83.1–88.4 Overlap 2.25 pts Actual: TOR 69, PHX 101

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.7) over Toronto Tempo (avg. 83.1) — by 2.6 points. The ranges overlap some — there's real uncertainty here.

TOR 81.2–85.0 PHX 83.5–87.9 Overlap 1.47 pts Actual: TOR 69, PHX 101

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.7) over Toronto Tempo (avg. 83.1) — by 2.6 points. The ranges overlap some — there's real uncertainty here.

TOR 81.5–84.7 PHX 83.8–87.7 Overlap 0.96 pts Actual: TOR 69, PHX 101

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.7) over Toronto Tempo (avg. 83.1) — by 2.6 points. The ranges barely touch.

TOR 81.6–84.6 PHX 84.0–87.5 Overlap 0.56 pts Actual: TOR 69, PHX 101

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.7) over Toronto Tempo (avg. 83.1) — by 2.6 points. The ranges barely touch.

TOR 81.8–84.4 PHX 84.2–87.3 Overlap 0.24 pts Actual: TOR 69, PHX 101

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.7) over Toronto Tempo (avg. 83.1) — by 2.6 points. The ranges barely touch.

Show the math
Model
Vince Chambers (#1)
t-statistic
-21.25
p-value
1.91e-63

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
TOR 81.5–88.3 PHX 82.2–89.1 Overlap 6.16 pts Actual: TOR 69, PHX 101

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.6) over Toronto Tempo (avg. 83.9) — by 1.7 points. The ranges overlap almost entirely, so one game could go either way.

TOR 81.7–87.5 PHX 82.7–88.5 Overlap 4.8 pts Actual: TOR 69, PHX 101

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.6) over Toronto Tempo (avg. 83.9) — by 1.7 points. The ranges overlap almost entirely, so one game could go either way.

TOR 81.9–87.1 PHX 83.1–88.2 Overlap 4.04 pts Actual: TOR 69, PHX 101

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.6) over Toronto Tempo (avg. 83.9) — by 1.7 points. The ranges overlap almost entirely, so one game could go either way.

TOR 82.0–86.8 PHX 83.4–87.9 Overlap 3.45 pts Actual: TOR 69, PHX 101

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.6) over Toronto Tempo (avg. 83.9) — by 1.7 points. The ranges overlap almost entirely, so one game could go either way.

TOR 82.2–86.2 PHX 83.6–87.7 Overlap 2.61 pts Actual: TOR 69, PHX 101

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.6) over Toronto Tempo (avg. 83.9) — by 1.7 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Reg (#2)
t-statistic
-9.01
p-value
1.72e-17

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
TOR 80.9–88.5 PHX 82.0–87.9 Overlap 5.85 pts Actual: TOR 69, PHX 101

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.3) over Toronto Tempo (avg. 83.8) — by 1.5 points. The ranges overlap almost entirely, so one game could go either way.

TOR 81.1–87.7 PHX 82.2–87.7 Overlap 5.47 pts Actual: TOR 69, PHX 101

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.3) over Toronto Tempo (avg. 83.8) — by 1.5 points. The ranges overlap almost entirely, so one game could go either way.

TOR 81.3–87.5 PHX 82.5–87.6 Overlap 5.0 pts Actual: TOR 69, PHX 101

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.3) over Toronto Tempo (avg. 83.8) — by 1.5 points. The ranges overlap almost entirely, so one game could go either way.

TOR 81.6–87.2 PHX 83.2–87.2 Overlap 4.0 pts Actual: TOR 69, PHX 101

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.3) over Toronto Tempo (avg. 83.8) — by 1.5 points. The ranges overlap almost entirely, so one game could go either way.

TOR 81.7–86.8 PHX 83.6–86.7 Overlap 3.06 pts Actual: TOR 69, PHX 101

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.3) over Toronto Tempo (avg. 83.8) — by 1.5 points. The ranges overlap almost entirely, so one game could go either way.

Show the math
Model
Dr. Wallace (#3)
t-statistic
-6.90
p-value
3.13e-11

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
TOR 81.0–88.7 PHX 81.6–88.3 Overlap 6.74 pts Actual: TOR 69, PHX 101

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.0) over Toronto Tempo (avg. 84.3) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 81.5–88.0 PHX 82.2–87.8 Overlap 5.65 pts Actual: TOR 69, PHX 101

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.0) over Toronto Tempo (avg. 84.3) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 81.7–87.6 PHX 82.5–87.5 Overlap 4.95 pts Actual: TOR 69, PHX 101

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.0) over Toronto Tempo (avg. 84.3) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 81.9–87.4 PHX 82.8–87.2 Overlap 4.4 pts Actual: TOR 69, PHX 101

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.0) over Toronto Tempo (avg. 84.3) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.0–87.3 PHX 83.0–87.0 Overlap 3.95 pts Actual: TOR 69, PHX 101

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 85.0) over Toronto Tempo (avg. 84.3) — by under a point. The ranges overlap almost entirely, so one game could go either way.

Show the math
Model
Kevin (#4)
t-statistic
-3.12
p-value
1.99e-03

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
TOR 80.5–87.9 PHX 81.0–86.7 Overlap 5.68 pts Actual: TOR 69, PHX 101

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 83.9) over Phoenix Mercury (avg. 83.9) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 80.8–87.4 PHX 81.5–86.3 Overlap 4.77 pts Actual: TOR 69, PHX 101

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 83.9) over Phoenix Mercury (avg. 83.9) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 80.9–87.4 PHX 81.8–86.0 Overlap 4.17 pts Actual: TOR 69, PHX 101

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 83.9) over Phoenix Mercury (avg. 83.9) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 81.1–87.1 PHX 82.0–85.7 Overlap 3.72 pts Actual: TOR 69, PHX 101

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 83.9) over Phoenix Mercury (avg. 83.9) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 81.4–86.8 PHX 82.2–85.5 Overlap 3.34 pts Actual: TOR 69, PHX 101

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 83.9) over Phoenix Mercury (avg. 83.9) — by under a point. The ranges overlap almost entirely, so one game could go either way.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
0.16
p-value
8.72e-01

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
TOR 81.4–88.6 PHX 81.9–88.6 Overlap 6.7 pts Actual: TOR 69, PHX 101

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.9) over Toronto Tempo (avg. 84.8) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 81.7–87.9 PHX 82.4–88.1 Overlap 5.52 pts Actual: TOR 69, PHX 101

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.9) over Toronto Tempo (avg. 84.8) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.0–87.8 PHX 82.5–87.6 Overlap 5.16 pts Actual: TOR 69, PHX 101

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.9) over Toronto Tempo (avg. 84.8) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.1–87.5 PHX 82.8–87.2 Overlap 4.39 pts Actual: TOR 69, PHX 101

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.9) over Toronto Tempo (avg. 84.8) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.2–87.4 PHX 83.0–86.7 Overlap 3.69 pts Actual: TOR 69, PHX 101

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.9) over Toronto Tempo (avg. 84.8) — by under a point. The ranges overlap almost entirely, so one game could go either way.

Show the math
Model
Ice (#6)
t-statistic
-0.31
p-value
7.57e-01

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
TOR 80.9–88.7 PHX 82.1–87.5 Overlap 5.44 pts Actual: TOR 69, PHX 101

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Phoenix Mercury (avg. 84.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 81.2–88.1 PHX 82.4–87.1 Overlap 4.75 pts Actual: TOR 69, PHX 101

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Phoenix Mercury (avg. 84.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 81.6–87.9 PHX 82.7–86.8 Overlap 4.16 pts Actual: TOR 69, PHX 101

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Phoenix Mercury (avg. 84.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 81.9–87.6 PHX 82.9–86.7 Overlap 3.76 pts Actual: TOR 69, PHX 101

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Phoenix Mercury (avg. 84.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.0–87.5 PHX 83.0–86.6 Overlap 3.59 pts Actual: TOR 69, PHX 101

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Phoenix Mercury (avg. 84.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

Show the math
Model
Jamal (#7)
t-statistic
0.59
p-value
5.58e-01

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
TOR 81.2–88.9 PHX 82.3–88.2 Overlap 5.97 pts Actual: TOR 69, PHX 101

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Phoenix Mercury (avg. 84.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 81.8–88.6 PHX 82.5–87.6 Overlap 5.03 pts Actual: TOR 69, PHX 101

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Phoenix Mercury (avg. 84.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.0–88.1 PHX 82.8–87.3 Overlap 4.55 pts Actual: TOR 69, PHX 101

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Phoenix Mercury (avg. 84.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.3–88.0 PHX 82.9–86.6 Overlap 3.67 pts Actual: TOR 69, PHX 101

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Phoenix Mercury (avg. 84.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.4–87.9 PHX 83.0–86.5 Overlap 3.43 pts Actual: TOR 69, PHX 101

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Phoenix Mercury (avg. 84.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

Show the math
Model
Jordan (#8)
t-statistic
2.48
p-value
1.37e-02

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
TOR 81.6–89.0 PHX 81.1–88.0 Overlap 6.31 pts Actual: TOR 69, PHX 101

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 85.3) over Phoenix Mercury (avg. 84.5) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.1–88.6 PHX 81.6–87.4 Overlap 5.35 pts Actual: TOR 69, PHX 101

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 85.3) over Phoenix Mercury (avg. 84.5) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.3–88.1 PHX 82.0–87.0 Overlap 4.74 pts Actual: TOR 69, PHX 101

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 85.3) over Phoenix Mercury (avg. 84.5) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.4–88.0 PHX 82.3–86.8 Overlap 4.35 pts Actual: TOR 69, PHX 101

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 85.3) over Phoenix Mercury (avg. 84.5) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.6–87.8 PHX 82.5–86.5 Overlap 3.92 pts Actual: TOR 69, PHX 101

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 85.3) over Phoenix Mercury (avg. 84.5) — by under a point. The ranges overlap almost entirely, so one game could go either way.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
3.91
p-value
1.13e-04

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
TOR 81.1–88.7 PHX 81.2–88.0 Overlap 6.79 pts Actual: TOR 69, PHX 101

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Phoenix Mercury (avg. 84.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 81.6–88.3 PHX 81.7–87.4 Overlap 5.7 pts Actual: TOR 69, PHX 101

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Phoenix Mercury (avg. 84.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 81.9–87.9 PHX 82.1–87.1 Overlap 4.99 pts Actual: TOR 69, PHX 101

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Phoenix Mercury (avg. 84.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.1–87.6 PHX 82.4–86.8 Overlap 4.44 pts Actual: TOR 69, PHX 101

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Phoenix Mercury (avg. 84.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.4–87.5 PHX 82.6–86.6 Overlap 3.98 pts Actual: TOR 69, PHX 101

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Phoenix Mercury (avg. 84.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

Show the math
Model
Maya Jefferson (#10)
t-statistic
2.84
p-value
4.89e-03

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
TOR 81.2–88.6 PHX 81.5–88.2 Overlap 6.72 pts Actual: TOR 69, PHX 101

In 95 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.8) over Toronto Tempo (avg. 84.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 81.7–88.1 PHX 82.0–87.7 Overlap 5.64 pts Actual: TOR 69, PHX 101

In 90 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.8) over Toronto Tempo (avg. 84.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 81.9–87.7 PHX 82.4–87.3 Overlap 4.93 pts Actual: TOR 69, PHX 101

In 85 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.8) over Toronto Tempo (avg. 84.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.1–87.3 PHX 82.6–87.0 Overlap 4.39 pts Actual: TOR 69, PHX 101

In 80 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.8) over Toronto Tempo (avg. 84.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.2–87.1 PHX 82.9–86.8 Overlap 3.94 pts Actual: TOR 69, PHX 101

In 75 out of 100 simulated runs, leans Phoenix Mercury (avg. 84.8) over Toronto Tempo (avg. 84.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

Show the math
Model
Lexi (#11)
t-statistic
-0.83
p-value
4.07e-01

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
TOR 82.1–88.4 PHX 81.8–87.7 Overlap 5.58 pts Actual: TOR 69, PHX 101

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Phoenix Mercury (avg. 84.8) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.4–88.1 PHX 82.3–87.2 Overlap 4.77 pts Actual: TOR 69, PHX 101

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Phoenix Mercury (avg. 84.8) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.6–87.6 PHX 82.6–86.9 Overlap 4.31 pts Actual: TOR 69, PHX 101

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Phoenix Mercury (avg. 84.8) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.8–87.5 PHX 82.8–86.7 Overlap 3.84 pts Actual: TOR 69, PHX 101

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Phoenix Mercury (avg. 84.8) — by under a point. The ranges overlap almost entirely, so one game could go either way.

TOR 82.9–87.2 PHX 83.0–86.5 Overlap 3.44 pts Actual: TOR 69, PHX 101

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Phoenix Mercury (avg. 84.8) — by under a point. The ranges overlap almost entirely, so one game could go either way.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
1.36
p-value
1.75e-01

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 — TOR at PHX — Actual: TOR 69, PHX 101
Level TOR range PHX range Overlap Tol Warning Actual landed in range?
95% 80.9–85.3 83.1–88.4 2.25 pts No
90% 81.2–85.0 83.5–87.9 1.47 pts No
85% 81.5–84.7 83.8–87.7 0.96 pts No
80% 81.6–84.6 84.0–87.5 0.56 pts No
75% 81.8–84.4 84.2–87.3 0.24 pts No
Reg — TOR at PHX — Actual: TOR 69, PHX 101
Level TOR range PHX range Overlap Tol Warning Actual landed in range?
95% 81.5–88.3 82.2–89.1 6.16 pts No
90% 81.7–87.5 82.7–88.5 4.8 pts No
85% 81.9–87.1 83.1–88.2 4.04 pts No
80% 82.0–86.8 83.4–87.9 3.45 pts No
75% 82.2–86.2 83.6–87.7 2.61 pts No
Dr. Wallace — TOR at PHX — Actual: TOR 69, PHX 101
Level TOR range PHX range Overlap Tol Warning Actual landed in range?
95% 80.9–88.5 82.0–87.9 5.85 pts No
90% 81.1–87.7 82.2–87.7 5.47 pts No
85% 81.3–87.5 82.5–87.6 5.0 pts No
80% 81.6–87.2 83.2–87.2 4.0 pts No
75% 81.7–86.8 83.6–86.7 3.06 pts No
Kevin — TOR at PHX — Actual: TOR 69, PHX 101
Level TOR range PHX range Overlap Tol Warning Actual landed in range?
95% 81.0–88.7 81.6–88.3 6.74 pts No
90% 81.5–88.0 82.2–87.8 5.65 pts No
85% 81.7–87.6 82.5–87.5 4.95 pts No
80% 81.9–87.4 82.8–87.2 4.4 pts No
75% 82.0–87.3 83.0–87.0 3.95 pts No
Dr. Lila Shah — TOR at PHX — Actual: TOR 69, PHX 101
Level TOR range PHX range Overlap Tol Warning Actual landed in range?
95% 80.5–87.9 81.0–86.7 5.68 pts No
90% 80.8–87.4 81.5–86.3 4.77 pts No
85% 80.9–87.4 81.8–86.0 4.17 pts No
80% 81.1–87.1 82.0–85.7 3.72 pts No
75% 81.4–86.8 82.2–85.5 3.34 pts No
Ice — TOR at PHX — Actual: TOR 69, PHX 101
Level TOR range PHX range Overlap Tol Warning Actual landed in range?
95% 81.4–88.6 81.9–88.6 6.7 pts No
90% 81.7–87.9 82.4–88.1 5.52 pts No
85% 82.0–87.8 82.5–87.6 5.16 pts No
80% 82.1–87.5 82.8–87.2 4.39 pts No
75% 82.2–87.4 83.0–86.7 3.69 pts No
Jamal — TOR at PHX — Actual: TOR 69, PHX 101
Level TOR range PHX range Overlap Tol Warning Actual landed in range?
95% 80.9–88.7 82.1–87.5 5.44 pts No
90% 81.2–88.1 82.4–87.1 4.75 pts No
85% 81.6–87.9 82.7–86.8 4.16 pts No
80% 81.9–87.6 82.9–86.7 3.76 pts No
75% 82.0–87.5 83.0–86.6 3.59 pts No
Jordan — TOR at PHX — Actual: TOR 69, PHX 101
Level TOR range PHX range Overlap Tol Warning Actual landed in range?
95% 81.2–88.9 82.3–88.2 5.97 pts No
90% 81.8–88.6 82.5–87.6 5.03 pts No
85% 82.0–88.1 82.8–87.3 4.55 pts No
80% 82.3–88.0 82.9–86.6 3.67 pts No
75% 82.4–87.9 83.0–86.5 3.43 pts No
Darren "Dimes" Lin — TOR at PHX — Actual: TOR 69, PHX 101
Level TOR range PHX range Overlap Tol Warning Actual landed in range?
95% 81.6–89.0 81.1–88.0 6.31 pts No
90% 82.1–88.6 81.6–87.4 5.35 pts No
85% 82.3–88.1 82.0–87.0 4.74 pts No
80% 82.4–88.0 82.3–86.8 4.35 pts No
75% 82.6–87.8 82.5–86.5 3.92 pts No
Maya Jefferson — TOR at PHX — Actual: TOR 69, PHX 101
Level TOR range PHX range Overlap Tol Warning Actual landed in range?
95% 81.1–88.7 81.2–88.0 6.79 pts No
90% 81.6–88.3 81.7–87.4 5.7 pts No
85% 81.9–87.9 82.1–87.1 4.99 pts No
80% 82.1–87.6 82.4–86.8 4.44 pts No
75% 82.4–87.5 82.6–86.6 3.98 pts No
Lexi — TOR at PHX — Actual: TOR 69, PHX 101
Level TOR range PHX range Overlap Tol Warning Actual landed in range?
95% 81.2–88.6 81.5–88.2 6.72 pts No
90% 81.7–88.1 82.0–87.7 5.64 pts No
85% 81.9–87.7 82.4–87.3 4.93 pts No
80% 82.1–87.3 82.6–87.0 4.39 pts No
75% 82.2–87.1 82.9–86.8 3.94 pts No
Coach Sarah Watanabe — TOR at PHX — Actual: TOR 69, PHX 101
Level TOR range PHX range Overlap Tol Warning Actual landed in range?
95% 82.1–88.4 81.8–87.7 5.58 pts No
90% 82.4–88.1 82.3–87.2 4.77 pts No
85% 82.6–87.6 82.6–86.9 4.31 pts No
80% 82.8–87.5 82.8–86.7 3.84 pts No
75% 82.9–87.2 83.0–86.5 3.44 pts No