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Toronto Tempo at Minnesota Lynx

TOR 93 – MIN 100

July 28, 2026 · Final

Coach Sarah Watanabe

Best model for this game

Coach Sarah Watanabe
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 MIN

All 12 models’ predicted scores

TOR — one dot per model MIN — one dot per model Actual: TOR 93, MIN 100
Vince Chambers
TOR 82.2–88.6 MIN 86.7–92.5 Overlap 1.82 pts Actual: TOR 93, MIN 100

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.1) over Toronto Tempo (avg. 85.4) — by 3.7 points. The ranges overlap some — there's real uncertainty here.

TOR 82.7–88.0 MIN 86.8–92.0 Overlap 1.23 pts Actual: TOR 93, MIN 100

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.1) over Toronto Tempo (avg. 85.4) — by 3.7 points. The ranges overlap some — there's real uncertainty here.

TOR 83.0–87.7 MIN 87.1–91.7 Overlap 0.58 pts Actual: TOR 93, MIN 100

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.1) over Toronto Tempo (avg. 85.4) — by 3.7 points. The ranges barely touch.

TOR 83.3–87.5 MIN 87.3–91.5 Overlap 0.11 pts Actual: TOR 93, MIN 100

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.1) over Toronto Tempo (avg. 85.4) — by 3.7 points. The ranges barely touch.

TOR 83.5–87.2 MIN 87.5–91.4 No overlap Actual: TOR 93, MIN 100

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.1) over Toronto Tempo (avg. 85.4) — by 3.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Vince Chambers (#1)
t-statistic
-17.78
p-value
4.91e-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.

Reg
TOR 82.2–88.3 MIN 86.0–92.9 Overlap 2.32 pts Actual: TOR 93, MIN 100

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.4) over Toronto Tempo (avg. 85.8) — by 3.7 points. The ranges overlap some — there's real uncertainty here.

TOR 82.6–88.1 MIN 86.5–92.3 Overlap 1.54 pts Actual: TOR 93, MIN 100

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.4) over Toronto Tempo (avg. 85.8) — by 3.7 points. The ranges overlap some — there's real uncertainty here.

TOR 83.0–88.0 MIN 86.9–92.0 Overlap 1.06 pts Actual: TOR 93, MIN 100

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.4) over Toronto Tempo (avg. 85.8) — by 3.7 points. The ranges overlap some — there's real uncertainty here.

TOR 83.4–87.7 MIN 87.2–91.7 Overlap 0.51 pts Actual: TOR 93, MIN 100

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.4) over Toronto Tempo (avg. 85.8) — by 3.7 points. The ranges barely touch.

TOR 83.9–87.4 MIN 87.4–91.5 No overlap Actual: TOR 93, MIN 100

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.4) over Toronto Tempo (avg. 85.8) — by 3.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Reg (#2)
t-statistic
-16.64
p-value
1.08e-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.

Dr. Wallace
TOR 82.9–88.0 MIN 86.5–93.0 Overlap 1.56 pts Actual: TOR 93, MIN 100

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.9) over Toronto Tempo (avg. 85.7) — by 3.2 points. The ranges overlap some — there's real uncertainty here.

TOR 83.4–88.0 MIN 86.9–92.6 Overlap 1.12 pts Actual: TOR 93, MIN 100

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.9) over Toronto Tempo (avg. 85.7) — by 3.2 points. The ranges overlap some — there's real uncertainty here.

TOR 83.6–87.5 MIN 87.0–91.5 Overlap 0.55 pts Actual: TOR 93, MIN 100

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.9) over Toronto Tempo (avg. 85.7) — by 3.2 points. The ranges barely touch.

TOR 83.7–87.4 MIN 87.1–91.1 Overlap 0.26 pts Actual: TOR 93, MIN 100

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.9) over Toronto Tempo (avg. 85.7) — by 3.2 points. The ranges barely touch.

TOR 84.0–87.2 MIN 87.3–90.8 No overlap Actual: TOR 93, MIN 100

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.9) over Toronto Tempo (avg. 85.7) — by 3.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Wallace (#3)
t-statistic
-14.41
p-value
7.93e-33

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 82.7–88.7 MIN 86.8–93.1 Overlap 1.95 pts Actual: TOR 93, MIN 100

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.7) — by 3.3 points. The ranges overlap some — there's real uncertainty here.

TOR 83.2–88.2 MIN 87.3–91.6 Overlap 0.94 pts Actual: TOR 93, MIN 100

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.7) — by 3.3 points. The ranges barely touch.

TOR 83.5–87.9 MIN 87.3–91.0 Overlap 0.56 pts Actual: TOR 93, MIN 100

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.7) — by 3.3 points. The ranges barely touch.

TOR 83.7–87.7 MIN 87.4–90.8 Overlap 0.23 pts Actual: TOR 93, MIN 100

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.7) — by 3.3 points. The ranges barely touch.

TOR 83.9–87.5 MIN 87.5–90.5 No overlap Actual: TOR 93, MIN 100

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.7) — by 3.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Kevin (#4)
t-statistic
-15.94
p-value
3.35e-37

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 82.4–88.5 MIN 86.8–91.1 Overlap 1.74 pts Actual: TOR 93, MIN 100

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.4) — by 3.4 points. The ranges overlap some — there's real uncertainty here.

TOR 82.8–88.0 MIN 86.8–91.0 Overlap 1.2 pts Actual: TOR 93, MIN 100

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.4) — by 3.4 points. The ranges overlap some — there's real uncertainty here.

TOR 83.2–87.7 MIN 87.0–90.9 Overlap 0.73 pts Actual: TOR 93, MIN 100

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.4) — by 3.4 points. The ranges barely touch.

TOR 83.4–87.5 MIN 87.0–90.8 Overlap 0.4 pts Actual: TOR 93, MIN 100

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.4) — by 3.4 points. The ranges barely touch.

TOR 83.6–87.2 MIN 87.3–90.6 No overlap Actual: TOR 93, MIN 100

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.4) — by 3.4 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
-17.34
p-value
7.59e-42

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 82.4–88.5 MIN 85.2–91.9 Overlap 3.29 pts Actual: TOR 93, MIN 100

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.5) over Toronto Tempo (avg. 85.4) — by 3.1 points. The ranges overlap almost entirely, so one game could go either way.

TOR 82.9–88.0 MIN 85.7–91.4 Overlap 2.26 pts Actual: TOR 93, MIN 100

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.5) over Toronto Tempo (avg. 85.4) — by 3.1 points. The ranges overlap some — there's real uncertainty here.

TOR 83.2–87.7 MIN 86.1–91.0 Overlap 1.59 pts Actual: TOR 93, MIN 100

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.5) over Toronto Tempo (avg. 85.4) — by 3.1 points. The ranges overlap some — there's real uncertainty here.

TOR 83.5–87.4 MIN 86.3–90.8 Overlap 1.07 pts Actual: TOR 93, MIN 100

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.5) over Toronto Tempo (avg. 85.4) — by 3.1 points. The ranges overlap some — there's real uncertainty here.

TOR 83.7–87.2 MIN 86.6–90.5 Overlap 0.64 pts Actual: TOR 93, MIN 100

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.5) over Toronto Tempo (avg. 85.4) — by 3.1 points. The ranges barely touch.

Show the math
Model
Ice (#6)
t-statistic
-15.47
p-value
5.37e-36

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 82.2–88.0 MIN 86.3–93.0 Overlap 1.73 pts Actual: TOR 93, MIN 100

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.2) — by 3.6 points. The ranges overlap some — there's real uncertainty here.

TOR 82.7–87.6 MIN 86.8–91.8 Overlap 0.75 pts Actual: TOR 93, MIN 100

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.2) — by 3.6 points. The ranges barely touch.

TOR 83.2–87.2 MIN 86.9–91.0 Overlap 0.27 pts Actual: TOR 93, MIN 100

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.2) — by 3.6 points. The ranges barely touch.

TOR 83.6–87.1 MIN 87.0–90.8 Overlap 0.1 pts Actual: TOR 93, MIN 100

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.2) — by 3.6 points. The ranges barely touch.

TOR 83.8–87.0 MIN 87.0–90.5 Overlap 0.03 pts Actual: TOR 93, MIN 100

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.2) — by 3.6 points. The ranges barely touch.

Show the math
Model
Jamal (#7)
t-statistic
-15.02
p-value
1.00e-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.

Jordan
TOR 82.7–88.5 MIN 86.9–92.8 Overlap 1.62 pts Actual: TOR 93, MIN 100

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.6) — by 3.3 points. The ranges overlap some — there's real uncertainty here.

TOR 83.2–88.1 MIN 87.2–91.6 Overlap 0.91 pts Actual: TOR 93, MIN 100

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.6) — by 3.3 points. The ranges barely touch.

TOR 83.5–87.8 MIN 87.3–91.1 Overlap 0.51 pts Actual: TOR 93, MIN 100

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.6) — by 3.3 points. The ranges barely touch.

TOR 83.8–87.5 MIN 87.3–91.0 Overlap 0.23 pts Actual: TOR 93, MIN 100

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.6) — by 3.3 points. The ranges barely touch.

TOR 83.9–87.3 MIN 87.4–90.8 No overlap Actual: TOR 93, MIN 100

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.6) — by 3.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jordan (#8)
t-statistic
-16.23
p-value
5.61e-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.

Darren "Dimes" Lin
TOR 82.6–87.5 MIN 86.8–92.4 Overlap 0.72 pts Actual: TOR 93, MIN 100

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.5) — by 3.3 points. The ranges barely touch.

TOR 83.1–87.4 MIN 87.0–92.1 Overlap 0.36 pts Actual: TOR 93, MIN 100

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.5) — by 3.3 points. The ranges barely touch.

TOR 83.6–87.2 MIN 87.1–91.5 Overlap 0.15 pts Actual: TOR 93, MIN 100

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.5) — by 3.3 points. The ranges barely touch.

TOR 83.7–87.2 MIN 87.1–90.8 Overlap 0.08 pts Actual: TOR 93, MIN 100

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.5) — by 3.3 points. The ranges barely touch.

TOR 84.0–86.9 MIN 87.3–90.7 No overlap Actual: TOR 93, MIN 100

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.5) — by 3.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
-16.23
p-value
3.22e-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.

Maya Jefferson
TOR 82.8–88.0 MIN 87.1–92.9 Overlap 0.86 pts Actual: TOR 93, MIN 100

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.5) — by 3.6 points. The ranges barely touch.

TOR 83.2–87.8 MIN 87.2–91.9 Overlap 0.56 pts Actual: TOR 93, MIN 100

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.5) — by 3.6 points. The ranges barely touch.

TOR 83.4–87.5 MIN 87.3–91.1 Overlap 0.2 pts Actual: TOR 93, MIN 100

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.5) — by 3.6 points. The ranges barely touch.

TOR 83.7–87.0 MIN 87.4–90.8 No overlap Actual: TOR 93, MIN 100

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.5) — by 3.6 points. The 80% ranges don't overlap at all — a confident model.

TOR 83.8–86.9 MIN 87.6–90.6 No overlap Actual: TOR 93, MIN 100

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 85.5) — by 3.6 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Maya Jefferson (#10)
t-statistic
-16.43
p-value
5.05e-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.

Lexi
TOR 82.6–88.9 MIN 86.7–92.5 Overlap 2.13 pts Actual: TOR 93, MIN 100

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.7) — by 3.0 points. The ranges overlap some — there's real uncertainty here.

TOR 83.1–88.4 MIN 87.0–92.1 Overlap 1.4 pts Actual: TOR 93, MIN 100

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.7) — by 3.0 points. The ranges overlap some — there's real uncertainty here.

TOR 83.4–88.0 MIN 87.1–91.6 Overlap 0.91 pts Actual: TOR 93, MIN 100

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.7) — by 3.0 points. The ranges barely touch.

TOR 83.7–87.8 MIN 87.3–90.5 Overlap 0.51 pts Actual: TOR 93, MIN 100

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.7) — by 3.0 points. The ranges barely touch.

TOR 83.9–87.6 MIN 87.3–90.4 Overlap 0.23 pts Actual: TOR 93, MIN 100

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.8) over Toronto Tempo (avg. 85.7) — by 3.0 points. The ranges barely touch.

Show the math
Model
Lexi (#11)
t-statistic
-15.02
p-value
1.05e-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.

Coach Sarah Watanabe
TOR 79.6–88.7 MIN 85.6–92.5 Overlap 3.09 pts Actual: TOR 93, MIN 100

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 84.1) — by 4.9 points. The ranges overlap almost entirely, so one game could go either way.

TOR 80.3–88.0 MIN 86.2–91.9 Overlap 1.8 pts Actual: TOR 93, MIN 100

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 84.1) — by 4.9 points. The ranges overlap some — there's real uncertainty here.

TOR 80.8–87.5 MIN 86.5–91.6 Overlap 0.97 pts Actual: TOR 93, MIN 100

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 84.1) — by 4.9 points. The ranges barely touch.

TOR 81.2–87.1 MIN 86.8–91.3 Overlap 0.32 pts Actual: TOR 93, MIN 100

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 84.1) — by 4.9 points. The ranges barely touch.

TOR 81.5–86.8 MIN 87.0–91.0 No overlap Actual: TOR 93, MIN 100

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 89.0) over Toronto Tempo (avg. 84.1) — by 4.9 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
-19.34
p-value
1.51e-46

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 MIN — Actual: TOR 93, MIN 100
Level TOR range MIN range Overlap Tol Warning Actual landed in range?
95% 82.2–88.6 86.7–92.5 1.82 pts — No
90% 82.7–88.0 86.8–92.0 1.23 pts — No
85% 83.0–87.7 87.1–91.7 0.58 pts — No
80% 83.3–87.5 87.3–91.5 0.11 pts — No
75% 83.5–87.2 87.5–91.4 — pts — No
Reg — TOR at MIN — Actual: TOR 93, MIN 100
Level TOR range MIN range Overlap Tol Warning Actual landed in range?
95% 82.2–88.3 86.0–92.9 2.32 pts — No
90% 82.6–88.1 86.5–92.3 1.54 pts — No
85% 83.0–88.0 86.9–92.0 1.06 pts — No
80% 83.4–87.7 87.2–91.7 0.51 pts — No
75% 83.9–87.4 87.4–91.5 — pts — No
Dr. Wallace — TOR at MIN — Actual: TOR 93, MIN 100
Level TOR range MIN range Overlap Tol Warning Actual landed in range?
95% 82.9–88.0 86.5–93.0 1.56 pts — No
90% 83.4–88.0 86.9–92.6 1.12 pts — No
85% 83.6–87.5 87.0–91.5 0.55 pts — No
80% 83.7–87.4 87.1–91.1 0.26 pts — No
75% 84.0–87.2 87.3–90.8 — pts — No
Kevin — TOR at MIN — Actual: TOR 93, MIN 100
Level TOR range MIN range Overlap Tol Warning Actual landed in range?
95% 82.7–88.7 86.8–93.1 1.95 pts — No
90% 83.2–88.2 87.3–91.6 0.94 pts — No
85% 83.5–87.9 87.3–91.0 0.56 pts — No
80% 83.7–87.7 87.4–90.8 0.23 pts — No
75% 83.9–87.5 87.5–90.5 — pts — No
Dr. Lila Shah — TOR at MIN — Actual: TOR 93, MIN 100
Level TOR range MIN range Overlap Tol Warning Actual landed in range?
95% 82.4–88.5 86.8–91.1 1.74 pts — No
90% 82.8–88.0 86.8–91.0 1.2 pts — No
85% 83.2–87.7 87.0–90.9 0.73 pts — No
80% 83.4–87.5 87.0–90.8 0.4 pts — No
75% 83.6–87.2 87.3–90.6 — pts — No
Ice — TOR at MIN — Actual: TOR 93, MIN 100
Level TOR range MIN range Overlap Tol Warning Actual landed in range?
95% 82.4–88.5 85.2–91.9 3.29 pts — No
90% 82.9–88.0 85.7–91.4 2.26 pts — No
85% 83.2–87.7 86.1–91.0 1.59 pts — No
80% 83.5–87.4 86.3–90.8 1.07 pts — No
75% 83.7–87.2 86.6–90.5 0.64 pts — No
Jamal — TOR at MIN — Actual: TOR 93, MIN 100
Level TOR range MIN range Overlap Tol Warning Actual landed in range?
95% 82.2–88.0 86.3–93.0 1.73 pts — No
90% 82.7–87.6 86.8–91.8 0.75 pts — No
85% 83.2–87.2 86.9–91.0 0.27 pts — No
80% 83.6–87.1 87.0–90.8 0.1 pts — No
75% 83.8–87.0 87.0–90.5 0.03 pts — No
Jordan — TOR at MIN — Actual: TOR 93, MIN 100
Level TOR range MIN range Overlap Tol Warning Actual landed in range?
95% 82.7–88.5 86.9–92.8 1.62 pts — No
90% 83.2–88.1 87.2–91.6 0.91 pts — No
85% 83.5–87.8 87.3–91.1 0.51 pts — No
80% 83.8–87.5 87.3–91.0 0.23 pts — No
75% 83.9–87.3 87.4–90.8 — pts — No
Darren "Dimes" Lin — TOR at MIN — Actual: TOR 93, MIN 100
Level TOR range MIN range Overlap Tol Warning Actual landed in range?
95% 82.6–87.5 86.8–92.4 0.72 pts — No
90% 83.1–87.4 87.0–92.1 0.36 pts — No
85% 83.6–87.2 87.1–91.5 0.15 pts — No
80% 83.7–87.2 87.1–90.8 0.08 pts — No
75% 84.0–86.9 87.3–90.7 — pts — No
Maya Jefferson — TOR at MIN — Actual: TOR 93, MIN 100
Level TOR range MIN range Overlap Tol Warning Actual landed in range?
95% 82.8–88.0 87.1–92.9 0.86 pts — No
90% 83.2–87.8 87.2–91.9 0.56 pts — No
85% 83.4–87.5 87.3–91.1 0.2 pts — No
80% 83.7–87.0 87.4–90.8 — pts — No
75% 83.8–86.9 87.6–90.6 — pts — No
Lexi — TOR at MIN — Actual: TOR 93, MIN 100
Level TOR range MIN range Overlap Tol Warning Actual landed in range?
95% 82.6–88.9 86.7–92.5 2.13 pts — No
90% 83.1–88.4 87.0–92.1 1.4 pts — No
85% 83.4–88.0 87.1–91.6 0.91 pts — No
80% 83.7–87.8 87.3–90.5 0.51 pts — No
75% 83.9–87.6 87.3–90.4 0.23 pts — No
Coach Sarah Watanabe — TOR at MIN — Actual: TOR 93, MIN 100
Level TOR range MIN range Overlap Tol Warning Actual landed in range?
95% 79.6–88.7 85.6–92.5 3.09 pts — No
90% 80.3–88.0 86.2–91.9 1.8 pts — No
85% 80.8–87.5 86.5–91.6 0.97 pts — No
80% 81.2–87.1 86.8–91.3 0.32 pts — No
75% 81.5–86.8 87.0–91.0 — pts — No