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Minnesota Lynx at Golden State Valkyries

MIN 81 – GS 75

June 19, 2026 · Final

Vince Chambers

Best model for this game

Vince Chambers
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 MIN at GS

All 12 models’ predicted scores

MIN — one dot per model GS — one dot per model Actual: MIN 81, GS 75
Vince Chambers
MIN 85.6–90.3 GS 79.0–84.8 No overlap Actual: MIN 81, GS 75

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over Golden State Valkyries (avg. 81.9) — by 6.0 points. The 95% ranges don't overlap at all — a confident model.

MIN 85.9–89.9 GS 79.5–84.4 No overlap Actual: MIN 81, GS 75

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over Golden State Valkyries (avg. 81.9) — by 6.0 points. The 90% ranges don't overlap at all — a confident model.

MIN 86.2–89.7 GS 79.8–84.1 No overlap Actual: MIN 81, GS 75

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over Golden State Valkyries (avg. 81.9) — by 6.0 points. The 85% ranges don't overlap at all — a confident model.

MIN 86.4–89.5 GS 80.0–83.8 No overlap Actual: MIN 81, GS 75

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over Golden State Valkyries (avg. 81.9) — by 6.0 points. The 80% ranges don't overlap at all — a confident model.

MIN 86.5–89.3 GS 80.2–83.6 No overlap Actual: MIN 81, GS 75

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over Golden State Valkyries (avg. 81.9) — by 6.0 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Vince Chambers (#1)
t-statistic
32.65
p-value
7.16e-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.

Reg
MIN 85.2–91.0 GS 78.9–85.3 Overlap 0.07 pts Actual: MIN 81, GS 75

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over Golden State Valkyries (avg. 82.1) — by 6.0 points. The ranges barely touch.

MIN 85.7–90.5 GS 79.4–84.8 No overlap Actual: MIN 81, GS 75

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over Golden State Valkyries (avg. 82.1) — by 6.0 points. The 90% ranges don't overlap at all — a confident model.

MIN 86.0–90.2 GS 79.8–84.4 No overlap Actual: MIN 81, GS 75

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over Golden State Valkyries (avg. 82.1) — by 6.0 points. The 85% ranges don't overlap at all — a confident model.

MIN 86.2–90.0 GS 80.0–84.2 No overlap Actual: MIN 81, GS 75

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over Golden State Valkyries (avg. 82.1) — by 6.0 points. The 80% ranges don't overlap at all — a confident model.

MIN 86.4–89.8 GS 80.2–84.0 No overlap Actual: MIN 81, GS 75

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over Golden State Valkyries (avg. 82.1) — by 6.0 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Reg (#2)
t-statistic
28.55
p-value
2.65e-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.

Dr. Wallace Tol Warning
MIN 86.0–89.1 GS 79.6–84.3 No overlap Actual: MIN 81, GS 75

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.5) over Golden State Valkyries (avg. 81.9) — by 5.6 points. The 95% ranges don't overlap at all — a confident model.

MIN 86.0–88.9 GS 79.9–83.9 No overlap Actual: MIN 81, GS 75

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.5) over Golden State Valkyries (avg. 81.9) — by 5.6 points. The 90% ranges don't overlap at all — a confident model.

MIN 86.3–88.9 GS 80.2–83.7 No overlap Actual: MIN 81, GS 75

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.5) over Golden State Valkyries (avg. 81.9) — by 5.6 points. The 85% ranges don't overlap at all — a confident model.

MIN 86.3–88.7 GS 80.4–83.5 No overlap Actual: MIN 81, GS 75

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.5) over Golden State Valkyries (avg. 81.9) — by 5.6 points. The 80% ranges don't overlap at all — a confident model.

MIN 86.4–88.5 GS 80.5–83.3 No overlap Actual: MIN 81, GS 75

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.5) over Golden State Valkyries (avg. 81.9) — by 5.6 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Wallace (#3)
t-statistic
35.87
p-value
1.11e-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 Tol Warning
MIN 85.7–89.7 GS 80.1–83.8 No overlap Actual: MIN 81, GS 75

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.8) — by 5.9 points. The 95% ranges don't overlap at all — a confident model.

MIN 86.0–89.3 GS 80.2–83.4 No overlap Actual: MIN 81, GS 75

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.8) — by 5.9 points. The 90% ranges don't overlap at all — a confident model.

MIN 86.2–89.1 GS 80.2–83.1 No overlap Actual: MIN 81, GS 75

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.8) — by 5.9 points. The 85% ranges don't overlap at all — a confident model.

MIN 86.4–89.0 GS 80.4–83.1 No overlap Actual: MIN 81, GS 75

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.8) — by 5.9 points. The 80% ranges don't overlap at all — a confident model.

MIN 86.5–88.8 GS 80.5–83.0 No overlap Actual: MIN 81, GS 75

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.8) — by 5.9 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Kevin (#4)
t-statistic
37.34
p-value
3.63e-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
MIN 84.7–89.1 GS 79.0–84.4 No overlap Actual: MIN 81, GS 75

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 86.9) over Golden State Valkyries (avg. 81.7) — by 5.2 points. The 95% ranges don't overlap at all — a confident model.

MIN 85.0–88.7 GS 79.4–84.0 No overlap Actual: MIN 81, GS 75

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 86.9) over Golden State Valkyries (avg. 81.7) — by 5.2 points. The 90% ranges don't overlap at all — a confident model.

MIN 85.3–88.5 GS 79.7–83.7 No overlap Actual: MIN 81, GS 75

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 86.9) over Golden State Valkyries (avg. 81.7) — by 5.2 points. The 85% ranges don't overlap at all — a confident model.

MIN 85.5–88.3 GS 79.9–83.5 No overlap Actual: MIN 81, GS 75

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 86.9) over Golden State Valkyries (avg. 81.7) — by 5.2 points. The 80% ranges don't overlap at all — a confident model.

MIN 85.6–88.2 GS 80.1–83.3 No overlap Actual: MIN 81, GS 75

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 86.9) over Golden State Valkyries (avg. 81.7) — by 5.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
30.37
p-value
8.07e-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.

Ice Tol Warning
MIN 85.6–89.9 GS 80.3–83.2 No overlap Actual: MIN 81, GS 75

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.8) over Golden State Valkyries (avg. 81.9) — by 5.9 points. The 95% ranges don't overlap at all — a confident model.

MIN 86.0–89.6 GS 80.5–83.0 No overlap Actual: MIN 81, GS 75

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.8) over Golden State Valkyries (avg. 81.9) — by 5.9 points. The 90% ranges don't overlap at all — a confident model.

MIN 86.2–89.3 GS 80.6–82.9 No overlap Actual: MIN 81, GS 75

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.8) over Golden State Valkyries (avg. 81.9) — by 5.9 points. The 85% ranges don't overlap at all — a confident model.

MIN 86.4–89.2 GS 80.8–82.8 No overlap Actual: MIN 81, GS 75

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.8) over Golden State Valkyries (avg. 81.9) — by 5.9 points. The 80% ranges don't overlap at all — a confident model.

MIN 86.5–89.0 GS 80.8–82.8 No overlap Actual: MIN 81, GS 75

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.8) over Golden State Valkyries (avg. 81.9) — by 5.9 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Ice (#6)
t-statistic
39.86
p-value
5.35e-85

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
MIN 85.4–90.0 GS 79.3–84.7 No overlap Actual: MIN 81, GS 75

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 82.0) — by 5.7 points. The 95% ranges don't overlap at all — a confident model.

MIN 85.8–89.6 GS 79.8–84.3 No overlap Actual: MIN 81, GS 75

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 82.0) — by 5.7 points. The 90% ranges don't overlap at all — a confident model.

MIN 86.0–89.4 GS 80.0–84.0 No overlap Actual: MIN 81, GS 75

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 82.0) — by 5.7 points. The 85% ranges don't overlap at all — a confident model.

MIN 86.2–89.2 GS 80.3–83.8 No overlap Actual: MIN 81, GS 75

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 82.0) — by 5.7 points. The 80% ranges don't overlap at all — a confident model.

MIN 86.3–89.0 GS 80.4–83.6 No overlap Actual: MIN 81, GS 75

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 82.0) — by 5.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jamal (#7)
t-statistic
32.56
p-value
1.84e-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.

Jordan Tol Warning
MIN 85.6–89.4 GS 79.3–84.4 No overlap Actual: MIN 81, GS 75

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.6) over Golden State Valkyries (avg. 81.8) — by 5.7 points. The 95% ranges don't overlap at all — a confident model.

MIN 85.8–89.1 GS 79.7–84.0 No overlap Actual: MIN 81, GS 75

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.6) over Golden State Valkyries (avg. 81.8) — by 5.7 points. The 90% ranges don't overlap at all — a confident model.

MIN 85.9–88.9 GS 80.0–83.7 No overlap Actual: MIN 81, GS 75

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.6) over Golden State Valkyries (avg. 81.8) — by 5.7 points. The 85% ranges don't overlap at all — a confident model.

MIN 86.0–88.8 GS 80.2–83.5 No overlap Actual: MIN 81, GS 75

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.6) over Golden State Valkyries (avg. 81.8) — by 5.7 points. The 80% ranges don't overlap at all — a confident model.

MIN 86.1–88.5 GS 80.3–83.4 No overlap Actual: MIN 81, GS 75

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.6) over Golden State Valkyries (avg. 81.8) — by 5.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jordan (#8)
t-statistic
33.72
p-value
1.32e-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.

Darren "Dimes" Lin
MIN 85.6–89.5 GS 79.7–84.3 No overlap Actual: MIN 81, GS 75

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.6) over Golden State Valkyries (avg. 82.0) — by 5.6 points. The 95% ranges don't overlap at all — a confident model.

MIN 85.9–89.2 GS 80.1–84.0 No overlap Actual: MIN 81, GS 75

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.6) over Golden State Valkyries (avg. 82.0) — by 5.6 points. The 90% ranges don't overlap at all — a confident model.

MIN 86.1–89.0 GS 80.3–83.7 No overlap Actual: MIN 81, GS 75

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.6) over Golden State Valkyries (avg. 82.0) — by 5.6 points. The 85% ranges don't overlap at all — a confident model.

MIN 86.3–88.9 GS 80.5–83.5 No overlap Actual: MIN 81, GS 75

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.6) over Golden State Valkyries (avg. 82.0) — by 5.6 points. The 80% ranges don't overlap at all — a confident model.

MIN 86.4–88.7 GS 80.6–83.4 No overlap Actual: MIN 81, GS 75

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.6) over Golden State Valkyries (avg. 82.0) — by 5.6 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
37.05
p-value
1.75e-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.

Maya Jefferson Tol Warning
MIN 86.1–89.8 GS 79.5–84.3 No overlap Actual: MIN 81, GS 75

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.9) — by 5.8 points. The 95% ranges don't overlap at all — a confident model.

MIN 86.3–89.5 GS 79.8–83.9 No overlap Actual: MIN 81, GS 75

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.9) — by 5.8 points. The 90% ranges don't overlap at all — a confident model.

MIN 86.4–89.2 GS 80.1–83.7 No overlap Actual: MIN 81, GS 75

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.9) — by 5.8 points. The 85% ranges don't overlap at all — a confident model.

MIN 86.5–89.0 GS 80.3–83.5 No overlap Actual: MIN 81, GS 75

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.9) — by 5.8 points. The 80% ranges don't overlap at all — a confident model.

MIN 86.6–88.7 GS 80.5–83.3 No overlap Actual: MIN 81, GS 75

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.9) — by 5.8 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Maya Jefferson (#10)
t-statistic
34.96
p-value
3.18e-76

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
MIN 85.2–90.2 GS 79.7–84.0 No overlap Actual: MIN 81, GS 75

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.9) — by 5.8 points. The 95% ranges don't overlap at all — a confident model.

MIN 85.6–89.8 GS 80.1–83.7 No overlap Actual: MIN 81, GS 75

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.9) — by 5.8 points. The 90% ranges don't overlap at all — a confident model.

MIN 85.9–89.5 GS 80.3–83.5 No overlap Actual: MIN 81, GS 75

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.9) — by 5.8 points. The 85% ranges don't overlap at all — a confident model.

MIN 86.1–89.3 GS 80.5–83.3 No overlap Actual: MIN 81, GS 75

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.9) — by 5.8 points. The 80% ranges don't overlap at all — a confident model.

MIN 86.3–89.2 GS 80.6–83.2 No overlap Actual: MIN 81, GS 75

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.7) over Golden State Valkyries (avg. 81.9) — by 5.8 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Lexi (#11)
t-statistic
36.07
p-value
2.13e-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.

Coach Sarah Watanabe
MIN 85.8–90.5 GS 79.9–85.0 No overlap Actual: MIN 81, GS 75

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over Golden State Valkyries (avg. 82.4) — by 5.7 points. The 95% ranges don't overlap at all — a confident model.

MIN 86.2–90.1 GS 80.3–84.6 No overlap Actual: MIN 81, GS 75

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over Golden State Valkyries (avg. 82.4) — by 5.7 points. The 90% ranges don't overlap at all — a confident model.

MIN 86.4–89.9 GS 80.6–84.3 No overlap Actual: MIN 81, GS 75

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over Golden State Valkyries (avg. 82.4) — by 5.7 points. The 85% ranges don't overlap at all — a confident model.

MIN 86.6–89.7 GS 80.8–84.1 No overlap Actual: MIN 81, GS 75

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over Golden State Valkyries (avg. 82.4) — by 5.7 points. The 80% ranges don't overlap at all — a confident model.

MIN 86.8–89.5 GS 80.9–83.9 No overlap Actual: MIN 81, GS 75

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over Golden State Valkyries (avg. 82.4) — by 5.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
33.46
p-value
2.38e-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 — MIN at GS — Actual: MIN 81, GS 75
Level MIN range GS range Overlap Tol Warning Actual landed in range?
95% 85.6–90.3 79.0–84.8 — pts — No
90% 85.9–89.9 79.5–84.4 — pts — No
85% 86.2–89.7 79.8–84.1 — pts — No
80% 86.4–89.5 80.0–83.8 — pts — No
75% 86.5–89.3 80.2–83.6 — pts — No
Reg — MIN at GS — Actual: MIN 81, GS 75
Level MIN range GS range Overlap Tol Warning Actual landed in range?
95% 85.2–91.0 78.9–85.3 0.07 pts — No
90% 85.7–90.5 79.4–84.8 — pts — No
85% 86.0–90.2 79.8–84.4 — pts — No
80% 86.2–90.0 80.0–84.2 — pts — No
75% 86.4–89.8 80.2–84.0 — pts — No
Dr. Wallace — MIN at GS — Actual: MIN 81, GS 75
Level MIN range GS range Overlap Tol Warning Actual landed in range?
95% 86.0–89.1 79.6–84.3 — pts Yes No
90% 86.0–88.9 79.9–83.9 — pts Yes No
85% 86.3–88.9 80.2–83.7 — pts Yes No
80% 86.3–88.7 80.4–83.5 — pts Yes No
75% 86.4–88.5 80.5–83.3 — pts Yes No
Kevin — MIN at GS — Actual: MIN 81, GS 75
Level MIN range GS range Overlap Tol Warning Actual landed in range?
95% 85.7–89.7 80.1–83.8 — pts Yes No
90% 86.0–89.3 80.2–83.4 — pts Yes No
85% 86.2–89.1 80.2–83.1 — pts Yes No
80% 86.4–89.0 80.4–83.1 — pts Yes No
75% 86.5–88.8 80.5–83.0 — pts Yes No
Dr. Lila Shah — MIN at GS — Actual: MIN 81, GS 75
Level MIN range GS range Overlap Tol Warning Actual landed in range?
95% 84.7–89.1 79.0–84.4 — pts — No
90% 85.0–88.7 79.4–84.0 — pts — No
85% 85.3–88.5 79.7–83.7 — pts — No
80% 85.5–88.3 79.9–83.5 — pts — No
75% 85.6–88.2 80.1–83.3 — pts — No
Ice — MIN at GS — Actual: MIN 81, GS 75
Level MIN range GS range Overlap Tol Warning Actual landed in range?
95% 85.6–89.9 80.3–83.2 — pts Yes No
90% 86.0–89.6 80.5–83.0 — pts Yes No
85% 86.2–89.3 80.6–82.9 — pts Yes No
80% 86.4–89.2 80.8–82.8 — pts Yes No
75% 86.5–89.0 80.8–82.8 — pts Yes No
Jamal — MIN at GS — Actual: MIN 81, GS 75
Level MIN range GS range Overlap Tol Warning Actual landed in range?
95% 85.4–90.0 79.3–84.7 — pts — No
90% 85.8–89.6 79.8–84.3 — pts — No
85% 86.0–89.4 80.0–84.0 — pts — No
80% 86.2–89.2 80.3–83.8 — pts — No
75% 86.3–89.0 80.4–83.6 — pts — No
Jordan — MIN at GS — Actual: MIN 81, GS 75
Level MIN range GS range Overlap Tol Warning Actual landed in range?
95% 85.6–89.4 79.3–84.4 — pts Yes No
90% 85.8–89.1 79.7–84.0 — pts Yes No
85% 85.9–88.9 80.0–83.7 — pts Yes No
80% 86.0–88.8 80.2–83.5 — pts Yes No
75% 86.1–88.5 80.3–83.4 — pts Yes No
Darren "Dimes" Lin — MIN at GS — Actual: MIN 81, GS 75
Level MIN range GS range Overlap Tol Warning Actual landed in range?
95% 85.6–89.5 79.7–84.3 — pts — No
90% 85.9–89.2 80.1–84.0 — pts — No
85% 86.1–89.0 80.3–83.7 — pts — No
80% 86.3–88.9 80.5–83.5 — pts — No
75% 86.4–88.7 80.6–83.4 — pts — No
Maya Jefferson — MIN at GS — Actual: MIN 81, GS 75
Level MIN range GS range Overlap Tol Warning Actual landed in range?
95% 86.1–89.8 79.5–84.3 — pts Yes No
90% 86.3–89.5 79.8–83.9 — pts Yes No
85% 86.4–89.2 80.1–83.7 — pts Yes No
80% 86.5–89.0 80.3–83.5 — pts Yes No
75% 86.6–88.7 80.5–83.3 — pts Yes No
Lexi — MIN at GS — Actual: MIN 81, GS 75
Level MIN range GS range Overlap Tol Warning Actual landed in range?
95% 85.2–90.2 79.7–84.0 — pts — No
90% 85.6–89.8 80.1–83.7 — pts — No
85% 85.9–89.5 80.3–83.5 — pts — No
80% 86.1–89.3 80.5–83.3 — pts — No
75% 86.3–89.2 80.6–83.2 — pts — No
Coach Sarah Watanabe — MIN at GS — Actual: MIN 81, GS 75
Level MIN range GS range Overlap Tol Warning Actual landed in range?
95% 85.8–90.5 79.9–85.0 — pts — No
90% 86.2–90.1 80.3–84.6 — pts — No
85% 86.4–89.9 80.6–84.3 — pts — No
80% 86.6–89.7 80.8–84.1 — pts — No
75% 86.8–89.5 80.9–83.9 — pts — No