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Toronto Tempo at Connecticut Sun

TOR 101 – CON 97

June 19, 2026 · Final

Dr. Lila Shah

Best model for this game

Dr. Lila Shah
All models: 12-0
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 CON

All 12 models’ predicted scores

TOR — one dot per model CON — one dot per model Actual: TOR 101, CON 97
Vince Chambers Tol Warning
TOR 84.0–88.5 CON 78.7–82.5 No overlap Actual: TOR 101, CON 97

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 95% ranges don't overlap at all — a confident model.

TOR 84.4–88.2 CON 78.8–82.1 No overlap Actual: TOR 101, CON 97

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 90% ranges don't overlap at all — a confident model.

TOR 84.6–87.9 CON 78.9–81.5 No overlap Actual: TOR 101, CON 97

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 85% ranges don't overlap at all — a confident model.

TOR 84.8–87.8 CON 78.9–81.3 No overlap Actual: TOR 101, CON 97

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 80% ranges don't overlap at all — a confident model.

TOR 85.0–87.6 CON 78.9–81.2 No overlap Actual: TOR 101, CON 97

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Vince Chambers (#1)
t-statistic
39.46
p-value
2.31e-84

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 83.6–89.1 CON 77.7–82.2 No overlap Actual: TOR 101, CON 97

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 80.0) — by 6.4 points. The 95% ranges don't overlap at all — a confident model.

TOR 84.1–88.6 CON 78.1–81.9 No overlap Actual: TOR 101, CON 97

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 80.0) — by 6.4 points. The 90% ranges don't overlap at all — a confident model.

TOR 84.4–88.4 CON 78.3–81.6 No overlap Actual: TOR 101, CON 97

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 80.0) — by 6.4 points. The 85% ranges don't overlap at all — a confident model.

TOR 84.6–88.1 CON 78.5–81.4 No overlap Actual: TOR 101, CON 97

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 80.0) — by 6.4 points. The 80% ranges don't overlap at all — a confident model.

TOR 84.8–88.0 CON 78.6–81.3 No overlap Actual: TOR 101, CON 97

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 80.0) — by 6.4 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Reg (#2)
t-statistic
36.87
p-value
1.37e-78

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 84.3–88.9 CON 78.4–81.1 No overlap Actual: TOR 101, CON 97

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 79.8) — by 6.4 points. The 95% ranges don't overlap at all — a confident model.

TOR 84.6–88.6 CON 78.6–80.9 No overlap Actual: TOR 101, CON 97

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 79.8) — by 6.4 points. The 90% ranges don't overlap at all — a confident model.

TOR 84.8–87.9 CON 78.7–80.8 No overlap Actual: TOR 101, CON 97

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 79.8) — by 6.4 points. The 85% ranges don't overlap at all — a confident model.

TOR 85.0–87.6 CON 78.8–80.8 No overlap Actual: TOR 101, CON 97

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 79.8) — by 6.4 points. The 80% ranges don't overlap at all — a confident model.

TOR 85.1–87.5 CON 78.9–80.8 No overlap Actual: TOR 101, CON 97

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 79.8) — by 6.4 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Wallace (#3)
t-statistic
39.74
p-value
3.50e-77

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 84.1–88.8 CON 78.1–81.7 No overlap Actual: TOR 101, CON 97

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.5) over Connecticut Sun (avg. 79.9) — by 6.6 points. The 95% ranges don't overlap at all — a confident model.

TOR 84.5–88.4 CON 78.4–81.5 No overlap Actual: TOR 101, CON 97

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.5) over Connecticut Sun (avg. 79.9) — by 6.6 points. The 90% ranges don't overlap at all — a confident model.

TOR 84.8–88.2 CON 78.6–81.3 No overlap Actual: TOR 101, CON 97

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.5) over Connecticut Sun (avg. 79.9) — by 6.6 points. The 85% ranges don't overlap at all — a confident model.

TOR 84.9–88.0 CON 78.7–81.1 No overlap Actual: TOR 101, CON 97

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.5) over Connecticut Sun (avg. 79.9) — by 6.6 points. The 80% ranges don't overlap at all — a confident model.

TOR 85.1–87.8 CON 78.8–81.0 No overlap Actual: TOR 101, CON 97

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.5) over Connecticut Sun (avg. 79.9) — by 6.6 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Kevin (#4)
t-statistic
45.19
p-value
7.10e-90

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 83.3–89.1 CON 78.9–82.3 No overlap Actual: TOR 101, CON 97

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Connecticut Sun (avg. 80.2) — by 6.1 points. The 95% ranges don't overlap at all — a confident model.

TOR 83.8–88.7 CON 78.9–81.8 No overlap Actual: TOR 101, CON 97

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Connecticut Sun (avg. 80.2) — by 6.1 points. The 90% ranges don't overlap at all — a confident model.

TOR 84.1–88.4 CON 79.0–81.5 No overlap Actual: TOR 101, CON 97

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Connecticut Sun (avg. 80.2) — by 6.1 points. The 85% ranges don't overlap at all — a confident model.

TOR 84.3–88.1 CON 79.1–81.3 No overlap Actual: TOR 101, CON 97

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Connecticut Sun (avg. 80.2) — by 6.1 points. The 80% ranges don't overlap at all — a confident model.

TOR 84.5–87.9 CON 79.2–81.2 No overlap Actual: TOR 101, CON 97

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Connecticut Sun (avg. 80.2) — by 6.1 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
34.87
p-value
7.05e-72

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 84.2–88.8 CON 78.1–81.7 No overlap Actual: TOR 101, CON 97

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.5) over Connecticut Sun (avg. 79.9) — by 6.5 points. The 95% ranges don't overlap at all — a confident model.

TOR 84.5–88.4 CON 78.4–81.5 No overlap Actual: TOR 101, CON 97

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.5) over Connecticut Sun (avg. 79.9) — by 6.5 points. The 90% ranges don't overlap at all — a confident model.

TOR 84.8–88.1 CON 78.6–81.3 No overlap Actual: TOR 101, CON 97

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.5) over Connecticut Sun (avg. 79.9) — by 6.5 points. The 85% ranges don't overlap at all — a confident model.

TOR 84.9–88.0 CON 78.7–81.1 No overlap Actual: TOR 101, CON 97

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.5) over Connecticut Sun (avg. 79.9) — by 6.5 points. The 80% ranges don't overlap at all — a confident model.

TOR 85.1–87.8 CON 78.8–81.0 No overlap Actual: TOR 101, CON 97

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.5) over Connecticut Sun (avg. 79.9) — by 6.5 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Ice (#6)
t-statistic
45.39
p-value
1.84e-90

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 84.1–88.7 CON 78.0–81.8 No overlap Actual: TOR 101, CON 97

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 79.9) — by 6.6 points. The 95% ranges don't overlap at all — a confident model.

TOR 84.5–88.4 CON 78.3–81.5 No overlap Actual: TOR 101, CON 97

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 79.9) — by 6.6 points. The 90% ranges don't overlap at all — a confident model.

TOR 84.8–88.1 CON 78.5–81.3 No overlap Actual: TOR 101, CON 97

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 79.9) — by 6.6 points. The 85% ranges don't overlap at all — a confident model.

TOR 84.9–87.9 CON 78.6–81.1 No overlap Actual: TOR 101, CON 97

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 79.9) — by 6.6 points. The 80% ranges don't overlap at all — a confident model.

TOR 85.1–87.8 CON 78.8–81.0 No overlap Actual: TOR 101, CON 97

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 79.9) — by 6.6 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jamal (#7)
t-statistic
44.81
p-value
1.50e-90

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 83.8–88.7 CON 77.9–82.3 No overlap Actual: TOR 101, CON 97

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 95% ranges don't overlap at all — a confident model.

TOR 84.2–88.3 CON 78.2–81.9 No overlap Actual: TOR 101, CON 97

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 90% ranges don't overlap at all — a confident model.

TOR 84.4–88.1 CON 78.4–81.7 No overlap Actual: TOR 101, CON 97

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 85% ranges don't overlap at all — a confident model.

TOR 84.6–87.9 CON 78.6–81.5 No overlap Actual: TOR 101, CON 97

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 80% ranges don't overlap at all — a confident model.

TOR 84.8–87.7 CON 78.8–81.4 No overlap Actual: TOR 101, CON 97

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jordan (#8)
t-statistic
38.16
p-value
4.78e-81

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 83.8–89.1 CON 78.0–81.8 No overlap Actual: TOR 101, CON 97

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 79.9) — by 6.5 points. The 95% ranges don't overlap at all — a confident model.

TOR 84.2–88.6 CON 78.3–81.5 No overlap Actual: TOR 101, CON 97

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 79.9) — by 6.5 points. The 90% ranges don't overlap at all — a confident model.

TOR 84.5–88.4 CON 78.5–81.3 No overlap Actual: TOR 101, CON 97

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 79.9) — by 6.5 points. The 85% ranges don't overlap at all — a confident model.

TOR 84.7–88.1 CON 78.7–81.1 No overlap Actual: TOR 101, CON 97

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 79.9) — by 6.5 points. The 80% ranges don't overlap at all — a confident model.

TOR 84.9–88.0 CON 78.8–81.0 No overlap Actual: TOR 101, CON 97

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.4) over Connecticut Sun (avg. 79.9) — by 6.5 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
40.60
p-value
2.16e-80

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 84.1–88.5 CON 78.1–82.1 No overlap Actual: TOR 101, CON 97

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 95% ranges don't overlap at all — a confident model.

TOR 84.5–88.1 CON 78.4–81.7 No overlap Actual: TOR 101, CON 97

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 90% ranges don't overlap at all — a confident model.

TOR 84.7–87.9 CON 78.6–81.5 No overlap Actual: TOR 101, CON 97

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 85% ranges don't overlap at all — a confident model.

TOR 84.9–87.7 CON 78.8–81.4 No overlap Actual: TOR 101, CON 97

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 80% ranges don't overlap at all — a confident model.

TOR 85.0–87.6 CON 78.9–81.2 No overlap Actual: TOR 101, CON 97

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.3) over Connecticut Sun (avg. 80.1) — by 6.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Maya Jefferson (#10)
t-statistic
42.93
p-value
1.46e-88

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 83.5–89.0 CON 77.7–82.0 No overlap Actual: TOR 101, CON 97

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Connecticut Sun (avg. 79.9) — by 6.4 points. The 95% ranges don't overlap at all — a confident model.

TOR 84.0–88.5 CON 78.1–81.6 No overlap Actual: TOR 101, CON 97

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Connecticut Sun (avg. 79.9) — by 6.4 points. The 90% ranges don't overlap at all — a confident model.

TOR 84.2–88.2 CON 78.3–81.4 No overlap Actual: TOR 101, CON 97

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Connecticut Sun (avg. 79.9) — by 6.4 points. The 85% ranges don't overlap at all — a confident model.

TOR 84.5–88.0 CON 78.5–81.3 No overlap Actual: TOR 101, CON 97

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Connecticut Sun (avg. 79.9) — by 6.4 points. The 80% ranges don't overlap at all — a confident model.

TOR 84.6–87.8 CON 78.6–81.1 No overlap Actual: TOR 101, CON 97

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Connecticut Sun (avg. 79.9) — by 6.4 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Lexi (#11)
t-statistic
37.54
p-value
7.84e-78

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 83.6–88.9 CON 78.0–81.7 No overlap Actual: TOR 101, CON 97

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 86.2) over Connecticut Sun (avg. 79.8) — by 6.4 points. The 95% ranges don't overlap at all — a confident model.

TOR 84.0–88.5 CON 78.3–81.4 No overlap Actual: TOR 101, CON 97

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

TOR 84.3–88.2 CON 78.4–81.2 No overlap Actual: TOR 101, CON 97

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

TOR 84.5–88.0 CON 78.6–81.0 No overlap Actual: TOR 101, CON 97

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

TOR 84.7–87.8 CON 78.7–80.9 No overlap Actual: TOR 101, CON 97

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

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
40.09
p-value
5.94e-79

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 CON — Actual: TOR 101, CON 97
Level TOR range CON range Overlap Tol Warning Actual landed in range?
95% 84.0–88.5 78.7–82.5 — pts Yes No
90% 84.4–88.2 78.8–82.1 — pts Yes No
85% 84.6–87.9 78.9–81.5 — pts Yes No
80% 84.8–87.8 78.9–81.3 — pts Yes No
75% 85.0–87.6 78.9–81.2 — pts Yes No
Reg — TOR at CON — Actual: TOR 101, CON 97
Level TOR range CON range Overlap Tol Warning Actual landed in range?
95% 83.6–89.1 77.7–82.2 — pts — No
90% 84.1–88.6 78.1–81.9 — pts — No
85% 84.4–88.4 78.3–81.6 — pts — No
80% 84.6–88.1 78.5–81.4 — pts — No
75% 84.8–88.0 78.6–81.3 — pts — No
Dr. Wallace — TOR at CON — Actual: TOR 101, CON 97
Level TOR range CON range Overlap Tol Warning Actual landed in range?
95% 84.3–88.9 78.4–81.1 — pts Yes No
90% 84.6–88.6 78.6–80.9 — pts Yes No
85% 84.8–87.9 78.7–80.8 — pts Yes No
80% 85.0–87.6 78.8–80.8 — pts Yes No
75% 85.1–87.5 78.9–80.8 — pts Yes No
Kevin — TOR at CON — Actual: TOR 101, CON 97
Level TOR range CON range Overlap Tol Warning Actual landed in range?
95% 84.1–88.8 78.1–81.7 — pts — No
90% 84.5–88.4 78.4–81.5 — pts — No
85% 84.8–88.2 78.6–81.3 — pts — No
80% 84.9–88.0 78.7–81.1 — pts — No
75% 85.1–87.8 78.8–81.0 — pts — No
Dr. Lila Shah — TOR at CON — Actual: TOR 101, CON 97
Level TOR range CON range Overlap Tol Warning Actual landed in range?
95% 83.3–89.1 78.9–82.3 — pts Yes No
90% 83.8–88.7 78.9–81.8 — pts Yes No
85% 84.1–88.4 79.0–81.5 — pts Yes No
80% 84.3–88.1 79.1–81.3 — pts Yes No
75% 84.5–87.9 79.2–81.2 — pts Yes No
Ice — TOR at CON — Actual: TOR 101, CON 97
Level TOR range CON range Overlap Tol Warning Actual landed in range?
95% 84.2–88.8 78.1–81.7 — pts — No
90% 84.5–88.4 78.4–81.5 — pts — No
85% 84.8–88.1 78.6–81.3 — pts — No
80% 84.9–88.0 78.7–81.1 — pts — No
75% 85.1–87.8 78.8–81.0 — pts — No
Jamal — TOR at CON — Actual: TOR 101, CON 97
Level TOR range CON range Overlap Tol Warning Actual landed in range?
95% 84.1–88.7 78.0–81.8 — pts — No
90% 84.5–88.4 78.3–81.5 — pts — No
85% 84.8–88.1 78.5–81.3 — pts — No
80% 84.9–87.9 78.6–81.1 — pts — No
75% 85.1–87.8 78.8–81.0 — pts — No
Jordan — TOR at CON — Actual: TOR 101, CON 97
Level TOR range CON range Overlap Tol Warning Actual landed in range?
95% 83.8–88.7 77.9–82.3 — pts — No
90% 84.2–88.3 78.2–81.9 — pts — No
85% 84.4–88.1 78.4–81.7 — pts — No
80% 84.6–87.9 78.6–81.5 — pts — No
75% 84.8–87.7 78.8–81.4 — pts — No
Darren "Dimes" Lin — TOR at CON — Actual: TOR 101, CON 97
Level TOR range CON range Overlap Tol Warning Actual landed in range?
95% 83.8–89.1 78.0–81.8 — pts — No
90% 84.2–88.6 78.3–81.5 — pts — No
85% 84.5–88.4 78.5–81.3 — pts — No
80% 84.7–88.1 78.7–81.1 — pts — No
75% 84.9–88.0 78.8–81.0 — pts — No
Maya Jefferson — TOR at CON — Actual: TOR 101, CON 97
Level TOR range CON range Overlap Tol Warning Actual landed in range?
95% 84.1–88.5 78.1–82.1 — pts — No
90% 84.5–88.1 78.4–81.7 — pts — No
85% 84.7–87.9 78.6–81.5 — pts — No
80% 84.9–87.7 78.8–81.4 — pts — No
75% 85.0–87.6 78.9–81.2 — pts — No
Lexi — TOR at CON — Actual: TOR 101, CON 97
Level TOR range CON range Overlap Tol Warning Actual landed in range?
95% 83.5–89.0 77.7–82.0 — pts — No
90% 84.0–88.5 78.1–81.6 — pts — No
85% 84.2–88.2 78.3–81.4 — pts — No
80% 84.5–88.0 78.5–81.3 — pts — No
75% 84.6–87.8 78.6–81.1 — pts — No
Coach Sarah Watanabe — TOR at CON — Actual: TOR 101, CON 97
Level TOR range CON range Overlap Tol Warning Actual landed in range?
95% 83.6–88.9 78.0–81.7 — pts — No
90% 84.0–88.5 78.3–81.4 — pts — No
85% 84.3–88.2 78.4–81.2 — pts — No
80% 84.5–88.0 78.6–81.0 — pts — No
75% 84.7–87.8 78.7–80.9 — pts — No