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Connecticut Sun at Toronto Tempo

CON 102 – TOR 106

June 10, 2026 · Final

Reg

Best model for this game

Reg
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 CON at TOR

All 12 models’ predicted scores

CON — one dot per model TOR — one dot per model Actual: CON 102, TOR 106
Vince Chambers Tol Warning
CON 77.9–81.6 TOR 82.2–87.3 No overlap Actual: CON 102, TOR 106

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.7) — by 5.0 points. The 95% ranges don't overlap at all — a confident model.

CON 78.3–81.0 TOR 82.6–86.9 No overlap Actual: CON 102, TOR 106

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.7) — by 5.0 points. The 90% ranges don't overlap at all — a confident model.

CON 78.5–80.9 TOR 82.9–86.7 No overlap Actual: CON 102, TOR 106

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.7) — by 5.0 points. The 85% ranges don't overlap at all — a confident model.

CON 78.6–80.8 TOR 83.1–86.5 No overlap Actual: CON 102, TOR 106

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.7) — by 5.0 points. The 80% ranges don't overlap at all — a confident model.

CON 78.7–80.7 TOR 83.3–86.3 No overlap Actual: CON 102, TOR 106

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.7) — by 5.0 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Vince Chambers (#1)
t-statistic
-30.56
p-value
6.13e-69

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
CON 76.8–82.6 TOR 81.6–87.6 Overlap 0.98 pts Actual: CON 102, TOR 106

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Connecticut Sun (avg. 79.7) — by 4.9 points. The ranges barely touch.

CON 77.2–82.2 TOR 82.1–87.1 Overlap 0.03 pts Actual: CON 102, TOR 106

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Connecticut Sun (avg. 79.7) — by 4.9 points. The ranges barely touch.

CON 77.6–81.9 TOR 82.4–86.8 No overlap Actual: CON 102, TOR 106

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Connecticut Sun (avg. 79.7) — by 4.9 points. The 85% ranges don't overlap at all — a confident model.

CON 77.8–81.6 TOR 82.7–86.5 No overlap Actual: CON 102, TOR 106

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Connecticut Sun (avg. 79.7) — by 4.9 points. The 80% ranges don't overlap at all — a confident model.

CON 78.0–81.4 TOR 82.9–86.3 No overlap Actual: CON 102, TOR 106

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Connecticut Sun (avg. 79.7) — by 4.9 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Reg (#2)
t-statistic
-24.34
p-value
2.62e-56

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
CON 78.0–81.7 TOR 82.1–87.4 No overlap Actual: CON 102, TOR 106

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.8) — by 5.0 points. The 95% ranges don't overlap at all — a confident model.

CON 78.3–81.4 TOR 82.6–87.0 No overlap Actual: CON 102, TOR 106

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.8) — by 5.0 points. The 90% ranges don't overlap at all — a confident model.

CON 78.4–81.2 TOR 82.8–86.7 No overlap Actual: CON 102, TOR 106

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.8) — by 5.0 points. The 85% ranges don't overlap at all — a confident model.

CON 78.6–81.0 TOR 83.0–86.5 No overlap Actual: CON 102, TOR 106

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.8) — by 5.0 points. The 80% ranges don't overlap at all — a confident model.

CON 78.7–80.9 TOR 83.2–86.3 No overlap Actual: CON 102, TOR 106

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.8) — by 5.0 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Wallace (#3)
t-statistic
-31.70
p-value
1.11e-67

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
CON 77.9–81.6 TOR 82.7–87.4 No overlap Actual: CON 102, TOR 106

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Connecticut Sun (avg. 79.7) — by 5.3 points. The 95% ranges don't overlap at all — a confident model.

CON 78.2–81.3 TOR 83.0–87.0 No overlap Actual: CON 102, TOR 106

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Connecticut Sun (avg. 79.7) — by 5.3 points. The 90% ranges don't overlap at all — a confident model.

CON 78.4–81.1 TOR 83.3–86.7 No overlap Actual: CON 102, TOR 106

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Connecticut Sun (avg. 79.7) — by 5.3 points. The 85% ranges don't overlap at all — a confident model.

CON 78.5–80.9 TOR 83.5–86.5 No overlap Actual: CON 102, TOR 106

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Connecticut Sun (avg. 79.7) — by 5.3 points. The 80% ranges don't overlap at all — a confident model.

CON 78.7–80.8 TOR 83.6–86.4 No overlap Actual: CON 102, TOR 106

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Connecticut Sun (avg. 79.7) — by 5.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Kevin (#4)
t-statistic
-36.55
p-value
3.33e-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. Lila Shah
CON 77.3–81.4 TOR 81.9–88.5 No overlap Actual: CON 102, TOR 106

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Connecticut Sun (avg. 79.3) — by 5.8 points. The 95% ranges don't overlap at all — a confident model.

CON 77.6–81.1 TOR 82.4–87.9 No overlap Actual: CON 102, TOR 106

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Connecticut Sun (avg. 79.3) — by 5.8 points. The 90% ranges don't overlap at all — a confident model.

CON 77.8–80.9 TOR 82.7–87.6 No overlap Actual: CON 102, TOR 106

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Connecticut Sun (avg. 79.3) — by 5.8 points. The 85% ranges don't overlap at all — a confident model.

CON 78.0–80.7 TOR 83.0–87.3 No overlap Actual: CON 102, TOR 106

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Connecticut Sun (avg. 79.3) — by 5.8 points. The 80% ranges don't overlap at all — a confident model.

CON 78.1–80.6 TOR 83.2–87.1 No overlap Actual: CON 102, TOR 106

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 85.2) over Connecticut Sun (avg. 79.3) — 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
-30.77
p-value
8.45e-64

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
CON 77.7–81.7 TOR 82.2–87.8 No overlap Actual: CON 102, TOR 106

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Connecticut Sun (avg. 79.7) — by 5.3 points. The 95% ranges don't overlap at all — a confident model.

CON 78.0–81.4 TOR 82.6–87.4 No overlap Actual: CON 102, TOR 106

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Connecticut Sun (avg. 79.7) — by 5.3 points. The 90% ranges don't overlap at all — a confident model.

CON 78.2–81.2 TOR 82.9–87.1 No overlap Actual: CON 102, TOR 106

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Connecticut Sun (avg. 79.7) — by 5.3 points. The 85% ranges don't overlap at all — a confident model.

CON 78.4–81.0 TOR 83.1–86.8 No overlap Actual: CON 102, TOR 106

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Connecticut Sun (avg. 79.7) — by 5.3 points. The 80% ranges don't overlap at all — a confident model.

CON 78.5–80.9 TOR 83.3–86.7 No overlap Actual: CON 102, TOR 106

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Connecticut Sun (avg. 79.7) — by 5.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Ice (#6)
t-statistic
-31.25
p-value
3.43e-67

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
CON 77.4–81.7 TOR 82.1–87.6 No overlap Actual: CON 102, TOR 106

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.5) — by 5.3 points. The 95% ranges don't overlap at all — a confident model.

CON 77.7–81.4 TOR 82.6–87.2 No overlap Actual: CON 102, TOR 106

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.5) — by 5.3 points. The 90% ranges don't overlap at all — a confident model.

CON 77.9–81.1 TOR 82.8–86.9 No overlap Actual: CON 102, TOR 106

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.5) — by 5.3 points. The 85% ranges don't overlap at all — a confident model.

CON 78.1–81.0 TOR 83.1–86.6 No overlap Actual: CON 102, TOR 106

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.5) — by 5.3 points. The 80% ranges don't overlap at all — a confident model.

CON 78.3–80.8 TOR 83.3–86.5 No overlap Actual: CON 102, TOR 106

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.5) — by 5.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jamal (#7)
t-statistic
-31.50
p-value
1.69e-69

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
CON 77.6–81.9 TOR 82.4–87.4 No overlap Actual: CON 102, TOR 106

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.8) — by 5.1 points. The 95% ranges don't overlap at all — a confident model.

CON 77.9–81.6 TOR 82.8–87.0 No overlap Actual: CON 102, TOR 106

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.8) — by 5.1 points. The 90% ranges don't overlap at all — a confident model.

CON 78.2–81.4 TOR 83.0–86.7 No overlap Actual: CON 102, TOR 106

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.8) — by 5.1 points. The 85% ranges don't overlap at all — a confident model.

CON 78.3–81.2 TOR 83.2–86.5 No overlap Actual: CON 102, TOR 106

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.8) — by 5.1 points. The 80% ranges don't overlap at all — a confident model.

CON 78.5–81.0 TOR 83.4–86.4 No overlap Actual: CON 102, TOR 106

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.8) — by 5.1 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jordan (#8)
t-statistic
-31.85
p-value
2.61e-71

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
CON 77.8–81.6 TOR 82.3–87.3 No overlap Actual: CON 102, TOR 106

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.7) — by 5.1 points. The 95% ranges don't overlap at all — a confident model.

CON 78.1–81.3 TOR 82.7–86.9 No overlap Actual: CON 102, TOR 106

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.7) — by 5.1 points. The 90% ranges don't overlap at all — a confident model.

CON 78.3–81.1 TOR 82.9–86.6 No overlap Actual: CON 102, TOR 106

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.7) — by 5.1 points. The 85% ranges don't overlap at all — a confident model.

CON 78.5–80.9 TOR 83.1–86.4 No overlap Actual: CON 102, TOR 106

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.7) — by 5.1 points. The 80% ranges don't overlap at all — a confident model.

CON 78.6–80.8 TOR 83.3–86.2 No overlap Actual: CON 102, TOR 106

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.8) over Connecticut Sun (avg. 79.7) — by 5.1 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
-33.50
p-value
3.22e-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.

Maya Jefferson
CON 77.7–81.7 TOR 82.1–87.8 No overlap Actual: CON 102, TOR 106

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.7) — by 5.2 points. The 95% ranges don't overlap at all — a confident model.

CON 78.0–81.4 TOR 82.5–87.3 No overlap Actual: CON 102, TOR 106

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.7) — by 5.2 points. The 90% ranges don't overlap at all — a confident model.

CON 78.2–81.2 TOR 82.8–87.0 No overlap Actual: CON 102, TOR 106

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.7) — by 5.2 points. The 85% ranges don't overlap at all — a confident model.

CON 78.4–81.0 TOR 83.0–86.8 No overlap Actual: CON 102, TOR 106

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.7) — by 5.2 points. The 80% ranges don't overlap at all — a confident model.

CON 78.5–80.9 TOR 83.2–86.6 No overlap Actual: CON 102, TOR 106

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.7) — by 5.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Maya Jefferson (#10)
t-statistic
-30.79
p-value
3.13e-66

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
CON 77.9–81.8 TOR 81.3–88.5 Overlap 0.44 pts Actual: CON 102, TOR 106

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.8) — by 5.1 points. The ranges barely touch.

CON 78.2–81.5 TOR 81.9–87.9 No overlap Actual: CON 102, TOR 106

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.8) — by 5.1 points. The 90% ranges don't overlap at all — a confident model.

CON 78.4–81.3 TOR 82.3–87.5 No overlap Actual: CON 102, TOR 106

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.8) — by 5.1 points. The 85% ranges don't overlap at all — a confident model.

CON 78.6–81.1 TOR 82.6–87.2 No overlap Actual: CON 102, TOR 106

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.8) — by 5.1 points. The 80% ranges don't overlap at all — a confident model.

CON 78.7–81.0 TOR 82.8–87.0 No overlap Actual: CON 102, TOR 106

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Connecticut Sun (avg. 79.8) — by 5.1 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Lexi (#11)
t-statistic
-25.74
p-value
3.93e-52

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
CON 77.3–81.9 TOR 82.9–89.0 No overlap Actual: CON 102, TOR 106

In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 85.9) over Connecticut Sun (avg. 79.6) — by 6.3 points. The 95% ranges don't overlap at all — a confident model.

CON 77.7–81.5 TOR 83.4–88.5 No overlap Actual: CON 102, TOR 106

In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 85.9) over Connecticut Sun (avg. 79.6) — by 6.3 points. The 90% ranges don't overlap at all — a confident model.

CON 77.9–81.3 TOR 83.7–88.2 No overlap Actual: CON 102, TOR 106

In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 85.9) over Connecticut Sun (avg. 79.6) — by 6.3 points. The 85% ranges don't overlap at all — a confident model.

CON 78.1–81.1 TOR 83.9–87.9 No overlap Actual: CON 102, TOR 106

In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 85.9) over Connecticut Sun (avg. 79.6) — by 6.3 points. The 80% ranges don't overlap at all — a confident model.

CON 78.2–81.0 TOR 84.1–87.7 No overlap Actual: CON 102, TOR 106

In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 85.9) over Connecticut Sun (avg. 79.6) — by 6.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
-34.19
p-value
1.56e-73

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 — CON at TOR — Actual: CON 102, TOR 106
Level CON range TOR range Overlap Tol Warning Actual landed in range?
95% 77.9–81.6 82.2–87.3 — pts Yes No
90% 78.3–81.0 82.6–86.9 — pts Yes No
85% 78.5–80.9 82.9–86.7 — pts Yes No
80% 78.6–80.8 83.1–86.5 — pts Yes No
75% 78.7–80.7 83.3–86.3 — pts Yes No
Reg — CON at TOR — Actual: CON 102, TOR 106
Level CON range TOR range Overlap Tol Warning Actual landed in range?
95% 76.8–82.6 81.6–87.6 0.98 pts — No
90% 77.2–82.2 82.1–87.1 0.03 pts — No
85% 77.6–81.9 82.4–86.8 — pts — No
80% 77.8–81.6 82.7–86.5 — pts — No
75% 78.0–81.4 82.9–86.3 — pts — No
Dr. Wallace — CON at TOR — Actual: CON 102, TOR 106
Level CON range TOR range Overlap Tol Warning Actual landed in range?
95% 78.0–81.7 82.1–87.4 — pts — No
90% 78.3–81.4 82.6–87.0 — pts — No
85% 78.4–81.2 82.8–86.7 — pts — No
80% 78.6–81.0 83.0–86.5 — pts — No
75% 78.7–80.9 83.2–86.3 — pts — No
Kevin — CON at TOR — Actual: CON 102, TOR 106
Level CON range TOR range Overlap Tol Warning Actual landed in range?
95% 77.9–81.6 82.7–87.4 — pts — No
90% 78.2–81.3 83.0–87.0 — pts — No
85% 78.4–81.1 83.3–86.7 — pts — No
80% 78.5–80.9 83.5–86.5 — pts — No
75% 78.7–80.8 83.6–86.4 — pts — No
Dr. Lila Shah — CON at TOR — Actual: CON 102, TOR 106
Level CON range TOR range Overlap Tol Warning Actual landed in range?
95% 77.3–81.4 81.9–88.5 — pts — No
90% 77.6–81.1 82.4–87.9 — pts — No
85% 77.8–80.9 82.7–87.6 — pts — No
80% 78.0–80.7 83.0–87.3 — pts — No
75% 78.1–80.6 83.2–87.1 — pts — No
Ice — CON at TOR — Actual: CON 102, TOR 106
Level CON range TOR range Overlap Tol Warning Actual landed in range?
95% 77.7–81.7 82.2–87.8 — pts — No
90% 78.0–81.4 82.6–87.4 — pts — No
85% 78.2–81.2 82.9–87.1 — pts — No
80% 78.4–81.0 83.1–86.8 — pts — No
75% 78.5–80.9 83.3–86.7 — pts — No
Jamal — CON at TOR — Actual: CON 102, TOR 106
Level CON range TOR range Overlap Tol Warning Actual landed in range?
95% 77.4–81.7 82.1–87.6 — pts — No
90% 77.7–81.4 82.6–87.2 — pts — No
85% 77.9–81.1 82.8–86.9 — pts — No
80% 78.1–81.0 83.1–86.6 — pts — No
75% 78.3–80.8 83.3–86.5 — pts — No
Jordan — CON at TOR — Actual: CON 102, TOR 106
Level CON range TOR range Overlap Tol Warning Actual landed in range?
95% 77.6–81.9 82.4–87.4 — pts — No
90% 77.9–81.6 82.8–87.0 — pts — No
85% 78.2–81.4 83.0–86.7 — pts — No
80% 78.3–81.2 83.2–86.5 — pts — No
75% 78.5–81.0 83.4–86.4 — pts — No
Darren "Dimes" Lin — CON at TOR — Actual: CON 102, TOR 106
Level CON range TOR range Overlap Tol Warning Actual landed in range?
95% 77.8–81.6 82.3–87.3 — pts — No
90% 78.1–81.3 82.7–86.9 — pts — No
85% 78.3–81.1 82.9–86.6 — pts — No
80% 78.5–80.9 83.1–86.4 — pts — No
75% 78.6–80.8 83.3–86.2 — pts — No
Maya Jefferson — CON at TOR — Actual: CON 102, TOR 106
Level CON range TOR range Overlap Tol Warning Actual landed in range?
95% 77.7–81.7 82.1–87.8 — pts — No
90% 78.0–81.4 82.5–87.3 — pts — No
85% 78.2–81.2 82.8–87.0 — pts — No
80% 78.4–81.0 83.0–86.8 — pts — No
75% 78.5–80.9 83.2–86.6 — pts — No
Lexi — CON at TOR — Actual: CON 102, TOR 106
Level CON range TOR range Overlap Tol Warning Actual landed in range?
95% 77.9–81.8 81.3–88.5 0.44 pts — No
90% 78.2–81.5 81.9–87.9 — pts — No
85% 78.4–81.3 82.3–87.5 — pts — No
80% 78.6–81.1 82.6–87.2 — pts — No
75% 78.7–81.0 82.8–87.0 — pts — No
Coach Sarah Watanabe — CON at TOR — Actual: CON 102, TOR 106
Level CON range TOR range Overlap Tol Warning Actual landed in range?
95% 77.3–81.9 82.9–89.0 — pts — No
90% 77.7–81.5 83.4–88.5 — pts — No
85% 77.9–81.3 83.7–88.2 — pts — No
80% 78.1–81.1 83.9–87.9 — pts — No
75% 78.2–81.0 84.1–87.7 — pts — No