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Toronto Tempo at Golden State Valkyries

TOR 81 – GS 92

August 4, 2026 · Final

Vince Chambers

Best model for this game

Vince Chambers
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 TOR at GS

All 12 models’ predicted scores

TOR — one dot per model GS — one dot per model Actual: TOR 81, GS 92
Vince Chambers
TOR 80.5–87.3 GS 76.7–83.4 Overlap 2.93 pts Actual: TOR 81, GS 92

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 83.9) over Golden State Valkyries (avg. 80.1) — by 3.9 points. The ranges overlap some — there's real uncertainty here.

TOR 81.1–86.8 GS 77.2–82.9 Overlap 1.84 pts Actual: TOR 81, GS 92

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 83.9) over Golden State Valkyries (avg. 80.1) — by 3.9 points. The ranges overlap some — there's real uncertainty here.

TOR 81.4–86.4 GS 77.6–82.5 Overlap 1.13 pts Actual: TOR 81, GS 92

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 83.9) over Golden State Valkyries (avg. 80.1) — by 3.9 points. The ranges overlap some — there's real uncertainty here.

TOR 81.7–86.1 GS 77.9–82.3 Overlap 0.59 pts Actual: TOR 81, GS 92

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 83.9) over Golden State Valkyries (avg. 80.1) — by 3.9 points. The ranges barely touch.

TOR 81.9–85.9 GS 78.1–82.0 Overlap 0.13 pts Actual: TOR 81, GS 92

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 83.9) over Golden State Valkyries (avg. 80.1) — by 3.9 points. The ranges barely touch.

Show the math
Model
Vince Chambers (#1)
t-statistic
14.52
p-value
5.11e-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.

Reg
TOR 79.6–89.5 GS 76.8–83.8 Overlap 4.23 pts Actual: TOR 81, GS 92

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.4) over Golden State Valkyries (avg. 80.3) — by 4.1 points. The ranges overlap almost entirely, so one game could go either way.

TOR 80.3–88.7 GS 77.3–83.2 Overlap 2.91 pts Actual: TOR 81, GS 92

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.4) over Golden State Valkyries (avg. 80.3) — by 4.1 points. The ranges overlap some — there's real uncertainty here.

TOR 80.8–88.1 GS 77.7–82.9 Overlap 2.04 pts Actual: TOR 81, GS 92

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.4) over Golden State Valkyries (avg. 80.3) — by 4.1 points. The ranges overlap some — there's real uncertainty here.

TOR 81.2–87.7 GS 78.0–82.6 Overlap 1.37 pts Actual: TOR 81, GS 92

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.4) over Golden State Valkyries (avg. 80.3) — by 4.1 points. The ranges overlap some — there's real uncertainty here.

TOR 81.5–87.4 GS 78.2–82.3 Overlap 0.82 pts Actual: TOR 81, GS 92

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.4) over Golden State Valkyries (avg. 80.3) — by 4.1 points. The ranges barely touch.

Show the math
Model
Reg (#2)
t-statistic
12.29
p-value
4.39e-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.

Dr. Wallace Tol Warning
TOR 80.6–89.5 GS 76.8–82.2 Overlap 1.6 pts Actual: TOR 81, GS 92

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 85.1) over Golden State Valkyries (avg. 79.9) — by 5.1 points. The ranges overlap some — there's real uncertainty here.

TOR 81.3–88.8 GS 78.2–81.9 Overlap 0.55 pts Actual: TOR 81, GS 92

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 85.1) over Golden State Valkyries (avg. 79.9) — by 5.1 points. The ranges barely touch.

TOR 81.8–88.3 GS 78.4–81.6 No overlap Actual: TOR 81, GS 92

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 85.1) over Golden State Valkyries (avg. 79.9) — by 5.1 points. The 85% ranges don't overlap at all — a confident model.

TOR 82.2–88.0 GS 78.6–81.2 No overlap Actual: TOR 81, GS 92

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 85.1) over Golden State Valkyries (avg. 79.9) — by 5.1 points. The 80% ranges don't overlap at all — a confident model.

TOR 82.5–87.7 GS 78.7–81.2 No overlap Actual: TOR 81, GS 92

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 85.1) over Golden State Valkyries (avg. 79.9) — by 5.1 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Wallace (#3)
t-statistic
16.97
p-value
4.21e-32

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 Tol Warning
TOR 81.8–88.6 GS 77.5–83.3 Overlap 1.56 pts Actual: TOR 81, GS 92

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 85.8) over Golden State Valkyries (avg. 80.2) — by 5.7 points. The ranges overlap some — there's real uncertainty here.

TOR 82.4–88.1 GS 78.2–82.3 No overlap Actual: TOR 81, GS 92

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 85.8) over Golden State Valkyries (avg. 80.2) — by 5.7 points. The 90% ranges don't overlap at all — a confident model.

TOR 83.1–88.0 GS 78.8–81.9 No overlap Actual: TOR 81, GS 92

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 85.8) over Golden State Valkyries (avg. 80.2) — by 5.7 points. The 85% ranges don't overlap at all — a confident model.

TOR 83.7–87.8 GS 79.0–81.6 No overlap Actual: TOR 81, GS 92

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 85.8) over Golden State Valkyries (avg. 80.2) — by 5.7 points. The 80% ranges don't overlap at all — a confident model.

TOR 83.9–87.7 GS 79.1–81.3 No overlap Actual: TOR 81, GS 92

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 85.8) over Golden State Valkyries (avg. 80.2) — by 5.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Kevin (#4)
t-statistic
20.16
p-value
2.76e-38

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

Dr. Lila Shah Tol Warning
TOR 81.9–87.5 GS 76.9–82.6 Overlap 0.67 pts Actual: TOR 81, GS 92

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 85.6) over Golden State Valkyries (avg. 79.8) — by 5.8 points. The ranges barely touch.

TOR 82.1–87.4 GS 77.2–82.2 Overlap 0.11 pts Actual: TOR 81, GS 92

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 85.6) over Golden State Valkyries (avg. 79.8) — by 5.8 points. The ranges barely touch.

TOR 83.4–87.3 GS 77.6–82.1 No overlap Actual: TOR 81, GS 92

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 85.6) over Golden State Valkyries (avg. 79.8) — by 5.8 points. The 85% ranges don't overlap at all — a confident model.

TOR 83.6–87.1 GS 77.8–81.8 No overlap Actual: TOR 81, GS 92

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 85.6) over Golden State Valkyries (avg. 79.8) — by 5.8 points. The 80% ranges don't overlap at all — a confident model.

TOR 84.1–87.0 GS 78.3–81.4 No overlap Actual: TOR 81, GS 92

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 85.6) over Golden State Valkyries (avg. 79.8) — by 5.8 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
19.99
p-value
1.21e-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.

Ice Tol Warning
TOR 82.3–87.7 GS 77.1–82.6 Overlap 0.26 pts Actual: TOR 81, GS 92

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.0) over Golden State Valkyries (avg. 79.8) — by 6.1 points. The ranges barely touch.

TOR 83.2–87.6 GS 77.5–82.2 No overlap Actual: TOR 81, GS 92

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.0) over Golden State Valkyries (avg. 79.8) — by 6.1 points. The 90% ranges don't overlap at all — a confident model.

TOR 83.5–87.5 GS 77.8–81.9 No overlap Actual: TOR 81, GS 92

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.0) over Golden State Valkyries (avg. 79.8) — by 6.1 points. The 85% ranges don't overlap at all — a confident model.

TOR 83.6–87.4 GS 78.0–81.7 No overlap Actual: TOR 81, GS 92

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.0) over Golden State Valkyries (avg. 79.8) — by 6.1 points. The 80% ranges don't overlap at all — a confident model.

TOR 84.4–87.3 GS 78.2–81.5 No overlap Actual: TOR 81, GS 92

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.0) over Golden State Valkyries (avg. 79.8) — by 6.1 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Ice (#6)
t-statistic
25.39
p-value
1.14e-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.

Jamal Tol Warning
TOR 81.9–88.4 GS 77.0–82.9 Overlap 0.97 pts Actual: TOR 81, GS 92

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Golden State Valkyries (avg. 80.0) — by 6.3 points. The ranges barely touch.

TOR 83.1–88.2 GS 77.5–82.4 No overlap Actual: TOR 81, GS 92

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Golden State Valkyries (avg. 80.0) — by 6.3 points. The 90% ranges don't overlap at all — a confident model.

TOR 84.5–87.9 GS 77.8–82.1 No overlap Actual: TOR 81, GS 92

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Golden State Valkyries (avg. 80.0) — by 6.3 points. The 85% ranges don't overlap at all — a confident model.

TOR 84.9–87.8 GS 78.1–81.9 No overlap Actual: TOR 81, GS 92

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Golden State Valkyries (avg. 80.0) — by 6.3 points. The 80% ranges don't overlap at all — a confident model.

TOR 85.2–87.6 GS 78.3–81.7 No overlap Actual: TOR 81, GS 92

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Golden State Valkyries (avg. 80.0) — by 6.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jamal (#7)
t-statistic
24.84
p-value
8.11e-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.

Jordan Tol Warning
TOR 82.5–89.5 GS 76.6–83.5 Overlap 0.94 pts Actual: TOR 81, GS 92

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.6) over Golden State Valkyries (avg. 80.0) — by 6.5 points. The ranges barely touch.

TOR 83.1–89.0 GS 77.2–82.9 No overlap Actual: TOR 81, GS 92

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.6) over Golden State Valkyries (avg. 80.0) — by 6.5 points. The 90% ranges don't overlap at all — a confident model.

TOR 83.7–88.7 GS 77.5–82.6 No overlap Actual: TOR 81, GS 92

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.6) over Golden State Valkyries (avg. 80.0) — by 6.5 points. The 85% ranges don't overlap at all — a confident model.

TOR 84.0–88.6 GS 77.8–82.3 No overlap Actual: TOR 81, GS 92

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.6) over Golden State Valkyries (avg. 80.0) — by 6.5 points. The 80% ranges don't overlap at all — a confident model.

TOR 84.7–88.4 GS 78.0–82.1 No overlap Actual: TOR 81, GS 92

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.6) over Golden State Valkyries (avg. 80.0) — by 6.5 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jordan (#8)
t-statistic
22.19
p-value
2.66e-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.

Darren "Dimes" Lin Tol Warning
TOR 82.9–88.9 GS 77.4–82.7 No overlap Actual: TOR 81, GS 92

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Golden State Valkyries (avg. 80.1) — by 6.4 points. The 95% ranges don't overlap at all — a confident model.

TOR 83.3–88.2 GS 77.8–82.3 No overlap Actual: TOR 81, GS 92

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Golden State Valkyries (avg. 80.1) — by 6.4 points. The 90% ranges don't overlap at all — a confident model.

TOR 83.6–88.1 GS 78.1–82.0 No overlap Actual: TOR 81, GS 92

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Golden State Valkyries (avg. 80.1) — by 6.4 points. The 85% ranges don't overlap at all — a confident model.

TOR 83.7–88.0 GS 78.3–81.8 No overlap Actual: TOR 81, GS 92

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Golden State Valkyries (avg. 80.1) — by 6.4 points. The 80% ranges don't overlap at all — a confident model.

TOR 85.2–87.9 GS 78.5–81.6 No overlap Actual: TOR 81, GS 92

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Golden State Valkyries (avg. 80.1) — by 6.4 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
26.07
p-value
8.87e-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
TOR 82.4–89.9 GS 76.7–82.8 Overlap 0.48 pts Actual: TOR 81, GS 92

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Golden State Valkyries (avg. 79.8) — by 6.4 points. The ranges barely touch.

TOR 83.0–89.3 GS 77.2–82.4 No overlap Actual: TOR 81, GS 92

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Golden State Valkyries (avg. 79.8) — by 6.4 points. The 90% ranges don't overlap at all — a confident model.

TOR 83.4–88.9 GS 77.5–82.0 No overlap Actual: TOR 81, GS 92

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Golden State Valkyries (avg. 79.8) — by 6.4 points. The 85% ranges don't overlap at all — a confident model.

TOR 83.7–88.6 GS 77.8–81.8 No overlap Actual: TOR 81, GS 92

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Golden State Valkyries (avg. 79.8) — by 6.4 points. The 80% ranges don't overlap at all — a confident model.

TOR 83.9–88.4 GS 78.0–81.6 No overlap Actual: TOR 81, GS 92

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Golden State Valkyries (avg. 79.8) — by 6.4 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Maya Jefferson (#10)
t-statistic
23.64
p-value
1.44e-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.

Lexi Tol Warning
TOR 82.2–88.6 GS 77.4–82.8 Overlap 0.6 pts Actual: TOR 81, GS 92

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.0) over Golden State Valkyries (avg. 80.1) — by 5.9 points. The ranges barely touch.

TOR 82.5–88.0 GS 77.9–82.3 No overlap Actual: TOR 81, GS 92

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.0) over Golden State Valkyries (avg. 80.1) — by 5.9 points. The 90% ranges don't overlap at all — a confident model.

TOR 83.5–87.8 GS 78.1–82.1 No overlap Actual: TOR 81, GS 92

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.0) over Golden State Valkyries (avg. 80.1) — by 5.9 points. The 85% ranges don't overlap at all — a confident model.

TOR 83.9–87.8 GS 78.4–81.8 No overlap Actual: TOR 81, GS 92

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.0) over Golden State Valkyries (avg. 80.1) — by 5.9 points. The 80% ranges don't overlap at all — a confident model.

TOR 84.0–87.7 GS 78.5–81.7 No overlap Actual: TOR 81, GS 92

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.0) over Golden State Valkyries (avg. 80.1) — by 5.9 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Lexi (#11)
t-statistic
22.43
p-value
1.17e-41

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 Tol Warning
TOR 80.7–88.5 GS 76.9–83.1 Overlap 2.36 pts Actual: TOR 81, GS 92

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 85.5) over Golden State Valkyries (avg. 80.0) — by 5.6 points. The ranges overlap some — there's real uncertainty here.

TOR 81.5–88.0 GS 77.4–82.6 Overlap 1.1 pts Actual: TOR 81, GS 92

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 85.5) over Golden State Valkyries (avg. 80.0) — by 5.6 points. The ranges overlap some — there's real uncertainty here.

TOR 82.6–87.8 GS 77.7–82.3 No overlap Actual: TOR 81, GS 92

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 85.5) over Golden State Valkyries (avg. 80.0) — by 5.6 points. The 85% ranges don't overlap at all — a confident model.

TOR 83.0–87.6 GS 77.9–82.0 No overlap Actual: TOR 81, GS 92

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 85.5) over Golden State Valkyries (avg. 80.0) — by 5.6 points. The 80% ranges don't overlap at all — a confident model.

TOR 83.3–87.4 GS 78.1–81.8 No overlap Actual: TOR 81, GS 92

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 85.5) over Golden State Valkyries (avg. 80.0) — by 5.6 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
18.19
p-value
4.98e-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.

View as table
Vince Chambers — TOR at GS — Actual: TOR 81, GS 92
Level TOR range GS range Overlap Tol Warning Actual landed in range?
95% 80.5–87.3 76.7–83.4 2.93 pts — No
90% 81.1–86.8 77.2–82.9 1.84 pts — No
85% 81.4–86.4 77.6–82.5 1.13 pts — No
80% 81.7–86.1 77.9–82.3 0.59 pts — No
75% 81.9–85.9 78.1–82.0 0.13 pts — No
Reg — TOR at GS — Actual: TOR 81, GS 92
Level TOR range GS range Overlap Tol Warning Actual landed in range?
95% 79.6–89.5 76.8–83.8 4.23 pts — No
90% 80.3–88.7 77.3–83.2 2.91 pts — No
85% 80.8–88.1 77.7–82.9 2.04 pts — No
80% 81.2–87.7 78.0–82.6 1.37 pts — No
75% 81.5–87.4 78.2–82.3 0.82 pts — No
Dr. Wallace — TOR at GS — Actual: TOR 81, GS 92
Level TOR range GS range Overlap Tol Warning Actual landed in range?
95% 80.6–89.5 76.8–82.2 1.6 pts Yes No
90% 81.3–88.8 78.2–81.9 0.55 pts Yes No
85% 81.8–88.3 78.4–81.6 — pts Yes No
80% 82.2–88.0 78.6–81.2 — pts Yes No
75% 82.5–87.7 78.7–81.2 — pts Yes No
Kevin — TOR at GS — Actual: TOR 81, GS 92
Level TOR range GS range Overlap Tol Warning Actual landed in range?
95% 81.8–88.6 77.5–83.3 1.56 pts Yes No
90% 82.4–88.1 78.2–82.3 — pts Yes No
85% 83.1–88.0 78.8–81.9 — pts Yes No
80% 83.7–87.8 79.0–81.6 — pts Yes No
75% 83.9–87.7 79.1–81.3 — pts Yes No
Dr. Lila Shah — TOR at GS — Actual: TOR 81, GS 92
Level TOR range GS range Overlap Tol Warning Actual landed in range?
95% 81.9–87.5 76.9–82.6 0.67 pts Yes No
90% 82.1–87.4 77.2–82.2 0.11 pts Yes No
85% 83.4–87.3 77.6–82.1 — pts Yes No
80% 83.6–87.1 77.8–81.8 — pts Yes No
75% 84.1–87.0 78.3–81.4 — pts Yes No
Ice — TOR at GS — Actual: TOR 81, GS 92
Level TOR range GS range Overlap Tol Warning Actual landed in range?
95% 82.3–87.7 77.1–82.6 0.26 pts Yes No
90% 83.2–87.6 77.5–82.2 — pts Yes No
85% 83.5–87.5 77.8–81.9 — pts Yes No
80% 83.6–87.4 78.0–81.7 — pts Yes No
75% 84.4–87.3 78.2–81.5 — pts Yes No
Jamal — TOR at GS — Actual: TOR 81, GS 92
Level TOR range GS range Overlap Tol Warning Actual landed in range?
95% 81.9–88.4 77.0–82.9 0.97 pts Yes No
90% 83.1–88.2 77.5–82.4 — pts Yes No
85% 84.5–87.9 77.8–82.1 — pts Yes No
80% 84.9–87.8 78.1–81.9 — pts Yes No
75% 85.2–87.6 78.3–81.7 — pts Yes No
Jordan — TOR at GS — Actual: TOR 81, GS 92
Level TOR range GS range Overlap Tol Warning Actual landed in range?
95% 82.5–89.5 76.6–83.5 0.94 pts Yes No
90% 83.1–89.0 77.2–82.9 — pts Yes No
85% 83.7–88.7 77.5–82.6 — pts Yes No
80% 84.0–88.6 77.8–82.3 — pts Yes No
75% 84.7–88.4 78.0–82.1 — pts Yes No
Darren "Dimes" Lin — TOR at GS — Actual: TOR 81, GS 92
Level TOR range GS range Overlap Tol Warning Actual landed in range?
95% 82.9–88.9 77.4–82.7 — pts Yes No
90% 83.3–88.2 77.8–82.3 — pts Yes No
85% 83.6–88.1 78.1–82.0 — pts Yes No
80% 83.7–88.0 78.3–81.8 — pts Yes No
75% 85.2–87.9 78.5–81.6 — pts Yes No
Maya Jefferson — TOR at GS — Actual: TOR 81, GS 92
Level TOR range GS range Overlap Tol Warning Actual landed in range?
95% 82.4–89.9 76.7–82.8 0.48 pts — No
90% 83.0–89.3 77.2–82.4 — pts — No
85% 83.4–88.9 77.5–82.0 — pts — No
80% 83.7–88.6 77.8–81.8 — pts — No
75% 83.9–88.4 78.0–81.6 — pts — No
Lexi — TOR at GS — Actual: TOR 81, GS 92
Level TOR range GS range Overlap Tol Warning Actual landed in range?
95% 82.2–88.6 77.4–82.8 0.6 pts Yes No
90% 82.5–88.0 77.9–82.3 — pts Yes No
85% 83.5–87.8 78.1–82.1 — pts Yes No
80% 83.9–87.8 78.4–81.8 — pts Yes No
75% 84.0–87.7 78.5–81.7 — pts Yes No
Coach Sarah Watanabe — TOR at GS — Actual: TOR 81, GS 92
Level TOR range GS range Overlap Tol Warning Actual landed in range?
95% 80.7–88.5 76.9–83.1 2.36 pts Yes No
90% 81.5–88.0 77.4–82.6 1.1 pts Yes No
85% 82.6–87.8 77.7–82.3 — pts Yes No
80% 83.0–87.6 77.9–82.0 — pts Yes No
75% 83.3–87.4 78.1–81.8 — pts Yes No