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New York Liberty at Minnesota Lynx

NY 85 – MIN 90

July 11, 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 NY at MIN

All 12 models’ predicted scores

NY — one dot per model MIN — one dot per model Actual: NY 85, MIN 90
Vince Chambers
NY 85.5–89.9 MIN 85.7–90.2 Overlap 4.22 pts Actual: NY 85, MIN 90

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over New York Liberty (avg. 87.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 85.9–89.5 MIN 86.0–89.8 Overlap 3.5 pts Actual: NY 85, MIN 90

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over New York Liberty (avg. 87.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 86.1–89.3 MIN 86.3–89.6 Overlap 3.03 pts Actual: NY 85, MIN 90

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over New York Liberty (avg. 87.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 86.3–89.1 MIN 86.5–89.4 Overlap 2.68 pts Actual: NY 85, MIN 90

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over New York Liberty (avg. 87.7) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.4–89.0 MIN 86.6–89.3 Overlap 2.38 pts Actual: NY 85, MIN 90

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over New York Liberty (avg. 87.7) — by under a point. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Vince Chambers (#1)
t-statistic
-1.69
p-value
9.33e-02

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
NY 85.1–89.7 MIN 85.2–91.0 Overlap 4.44 pts Actual: NY 85, MIN 90

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.4) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 85.4–89.3 MIN 85.7–90.5 Overlap 3.61 pts Actual: NY 85, MIN 90

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.4) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 85.7–89.0 MIN 86.0–90.2 Overlap 3.07 pts Actual: NY 85, MIN 90

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.4) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 85.9–88.9 MIN 86.2–90.0 Overlap 2.65 pts Actual: NY 85, MIN 90

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.4) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.0–88.7 MIN 86.4–89.8 Overlap 2.3 pts Actual: NY 85, MIN 90

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.4) — by under a point. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Reg (#2)
t-statistic
-4.43
p-value
1.61e-05

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
NY 85.9–89.8 MIN 86.0–90.3 Overlap 3.82 pts Actual: NY 85, MIN 90

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 86.2–89.5 MIN 86.3–90.0 Overlap 3.16 pts Actual: NY 85, MIN 90

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 86.4–89.3 MIN 86.5–89.7 Overlap 2.73 pts Actual: NY 85, MIN 90

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.6–89.1 MIN 86.7–89.6 Overlap 2.4 pts Actual: NY 85, MIN 90

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.7–89.0 MIN 86.9–89.4 Overlap 2.12 pts Actual: NY 85, MIN 90

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Dr. Wallace (#3)
t-statistic
-2.22
p-value
2.78e-02

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
NY 85.6–90.1 MIN 86.9–90.1 Overlap 3.19 pts Actual: NY 85, MIN 90

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.3) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 85.9–89.7 MIN 86.9–89.6 Overlap 2.77 pts Actual: NY 85, MIN 90

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.3) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.2–89.5 MIN 87.0–89.4 Overlap 2.46 pts Actual: NY 85, MIN 90

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.3) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.4–89.3 MIN 87.2–89.4 Overlap 2.05 pts Actual: NY 85, MIN 90

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.3) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.5–89.1 MIN 87.3–89.3 Overlap 1.79 pts Actual: NY 85, MIN 90

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.3) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Kevin (#4)
t-statistic
-3.82
p-value
1.78e-04

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
NY 85.5–89.5 MIN 85.7–90.2 Overlap 3.79 pts Actual: NY 85, MIN 90

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over New York Liberty (avg. 87.5) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 85.8–89.2 MIN 86.0–89.8 Overlap 3.11 pts Actual: NY 85, MIN 90

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over New York Liberty (avg. 87.5) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 86.0–89.0 MIN 86.3–89.6 Overlap 2.67 pts Actual: NY 85, MIN 90

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over New York Liberty (avg. 87.5) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.2–88.8 MIN 86.5–89.4 Overlap 2.33 pts Actual: NY 85, MIN 90

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over New York Liberty (avg. 87.5) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.3–88.7 MIN 86.6–89.3 Overlap 2.05 pts Actual: NY 85, MIN 90

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.9) over New York Liberty (avg. 87.5) — by under a point. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
-3.29
p-value
1.18e-03

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
NY 85.6–89.6 MIN 85.6–90.4 Overlap 3.94 pts Actual: NY 85, MIN 90

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 85.9–89.2 MIN 86.0–90.0 Overlap 3.23 pts Actual: NY 85, MIN 90

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 86.1–89.0 MIN 86.3–89.8 Overlap 2.77 pts Actual: NY 85, MIN 90

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.3–88.9 MIN 86.5–89.6 Overlap 2.41 pts Actual: NY 85, MIN 90

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.4–88.7 MIN 86.6–89.4 Overlap 2.12 pts Actual: NY 85, MIN 90

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Ice (#6)
t-statistic
-3.29
p-value
1.21e-03

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
NY 85.4–89.7 MIN 86.0–90.6 Overlap 3.68 pts Actual: NY 85, MIN 90

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 85.7–89.4 MIN 86.4–89.7 Overlap 3.02 pts Actual: NY 85, MIN 90

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 86.0–89.1 MIN 86.5–89.5 Overlap 2.64 pts Actual: NY 85, MIN 90

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.1–89.0 MIN 86.6–89.4 Overlap 2.35 pts Actual: NY 85, MIN 90

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.3–88.8 MIN 86.7–89.2 Overlap 2.12 pts Actual: NY 85, MIN 90

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Jamal (#7)
t-statistic
-2.86
p-value
4.71e-03

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
NY 86.1–89.5 MIN 86.3–90.4 Overlap 3.17 pts Actual: NY 85, MIN 90

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 86.2–89.3 MIN 86.6–89.6 Overlap 2.72 pts Actual: NY 85, MIN 90

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.4–89.1 MIN 86.8–89.5 Overlap 2.22 pts Actual: NY 85, MIN 90

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.5–89.0 MIN 87.0–89.3 Overlap 2.01 pts Actual: NY 85, MIN 90

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.6–88.8 MIN 87.1–89.1 Overlap 1.69 pts Actual: NY 85, MIN 90

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.8) — by under a point. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Jordan (#8)
t-statistic
-2.18
p-value
3.06e-02

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
NY 85.7–89.8 MIN 85.6–90.5 Overlap 4.09 pts Actual: NY 85, MIN 90

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 86.0–89.4 MIN 86.0–90.1 Overlap 3.43 pts Actual: NY 85, MIN 90

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 86.2–89.2 MIN 86.2–89.9 Overlap 3.0 pts Actual: NY 85, MIN 90

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.7) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 86.4–89.1 MIN 86.4–89.7 Overlap 2.64 pts Actual: NY 85, MIN 90

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.7) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.5–88.9 MIN 86.6–89.5 Overlap 2.33 pts Actual: NY 85, MIN 90

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.7) — by under a point. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
-2.20
p-value
2.88e-02

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
NY 85.3–89.8 MIN 85.7–90.3 Overlap 4.1 pts Actual: NY 85, MIN 90

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 85.7–89.5 MIN 86.1–89.9 Overlap 3.37 pts Actual: NY 85, MIN 90

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 85.9–89.2 MIN 86.3–89.7 Overlap 2.9 pts Actual: NY 85, MIN 90

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.1–89.1 MIN 86.5–89.5 Overlap 2.54 pts Actual: NY 85, MIN 90

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.3–88.9 MIN 86.7–89.3 Overlap 2.24 pts Actual: NY 85, MIN 90

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.0) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Maya Jefferson (#10)
t-statistic
-2.89
p-value
4.30e-03

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
NY 85.8–89.6 MIN 85.6–90.6 Overlap 3.86 pts Actual: NY 85, MIN 90

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 86.0–89.1 MIN 86.0–90.2 Overlap 3.1 pts Actual: NY 85, MIN 90

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 86.2–88.9 MIN 86.2–89.9 Overlap 2.64 pts Actual: NY 85, MIN 90

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.4–88.8 MIN 86.4–89.7 Overlap 2.41 pts Actual: NY 85, MIN 90

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.8–88.8 MIN 86.6–89.6 Overlap 2.02 pts Actual: NY 85, MIN 90

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 88.1) over New York Liberty (avg. 87.6) — by under a point. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Lexi (#11)
t-statistic
-2.92
p-value
3.98e-03

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
NY 84.9–89.2 MIN 85.3–90.2 Overlap 3.91 pts Actual: NY 85, MIN 90

In 95 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.8) over New York Liberty (avg. 87.2) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 85.6–88.9 MIN 85.7–89.9 Overlap 3.2 pts Actual: NY 85, MIN 90

In 90 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.8) over New York Liberty (avg. 87.2) — by under a point. The ranges overlap almost entirely, so one game could go either way.

NY 85.8–88.7 MIN 86.0–89.6 Overlap 2.69 pts Actual: NY 85, MIN 90

In 85 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.8) over New York Liberty (avg. 87.2) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.1–88.5 MIN 86.2–89.4 Overlap 2.34 pts Actual: NY 85, MIN 90

In 80 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.8) over New York Liberty (avg. 87.2) — by under a point. The ranges overlap some — there's real uncertainty here.

NY 86.2–88.4 MIN 86.3–89.2 Overlap 2.06 pts Actual: NY 85, MIN 90

In 75 out of 100 simulated runs, leans Minnesota Lynx (avg. 87.8) over New York Liberty (avg. 87.2) — by under a point. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
-3.69
p-value
2.88e-04

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 — NY at MIN — Actual: NY 85, MIN 90
Level NY range MIN range Overlap Tol Warning Actual landed in range?
95% 85.5–89.9 85.7–90.2 4.22 pts — No
90% 85.9–89.5 86.0–89.8 3.5 pts — No
85% 86.1–89.3 86.3–89.6 3.03 pts — No
80% 86.3–89.1 86.5–89.4 2.68 pts — No
75% 86.4–89.0 86.6–89.3 2.38 pts — No
Reg — NY at MIN — Actual: NY 85, MIN 90
Level NY range MIN range Overlap Tol Warning Actual landed in range?
95% 85.1–89.7 85.2–91.0 4.44 pts — No
90% 85.4–89.3 85.7–90.5 3.61 pts — No
85% 85.7–89.0 86.0–90.2 3.07 pts — No
80% 85.9–88.9 86.2–90.0 2.65 pts — No
75% 86.0–88.7 86.4–89.8 2.3 pts — No
Dr. Wallace — NY at MIN — Actual: NY 85, MIN 90
Level NY range MIN range Overlap Tol Warning Actual landed in range?
95% 85.9–89.8 86.0–90.3 3.82 pts — No
90% 86.2–89.5 86.3–90.0 3.16 pts — No
85% 86.4–89.3 86.5–89.7 2.73 pts — No
80% 86.6–89.1 86.7–89.6 2.4 pts — No
75% 86.7–89.0 86.9–89.4 2.12 pts — No
Kevin — NY at MIN — Actual: NY 85, MIN 90
Level NY range MIN range Overlap Tol Warning Actual landed in range?
95% 85.6–90.1 86.9–90.1 3.19 pts — No
90% 85.9–89.7 86.9–89.6 2.77 pts — No
85% 86.2–89.5 87.0–89.4 2.46 pts — No
80% 86.4–89.3 87.2–89.4 2.05 pts — No
75% 86.5–89.1 87.3–89.3 1.79 pts — No
Dr. Lila Shah — NY at MIN — Actual: NY 85, MIN 90
Level NY range MIN range Overlap Tol Warning Actual landed in range?
95% 85.5–89.5 85.7–90.2 3.79 pts — No
90% 85.8–89.2 86.0–89.8 3.11 pts — No
85% 86.0–89.0 86.3–89.6 2.67 pts — No
80% 86.2–88.8 86.5–89.4 2.33 pts — No
75% 86.3–88.7 86.6–89.3 2.05 pts — No
Ice — NY at MIN — Actual: NY 85, MIN 90
Level NY range MIN range Overlap Tol Warning Actual landed in range?
95% 85.6–89.6 85.6–90.4 3.94 pts — No
90% 85.9–89.2 86.0–90.0 3.23 pts — No
85% 86.1–89.0 86.3–89.8 2.77 pts — No
80% 86.3–88.9 86.5–89.6 2.41 pts — No
75% 86.4–88.7 86.6–89.4 2.12 pts — No
Jamal — NY at MIN — Actual: NY 85, MIN 90
Level NY range MIN range Overlap Tol Warning Actual landed in range?
95% 85.4–89.7 86.0–90.6 3.68 pts — No
90% 85.7–89.4 86.4–89.7 3.02 pts — No
85% 86.0–89.1 86.5–89.5 2.64 pts — No
80% 86.1–89.0 86.6–89.4 2.35 pts — No
75% 86.3–88.8 86.7–89.2 2.12 pts — No
Jordan — NY at MIN — Actual: NY 85, MIN 90
Level NY range MIN range Overlap Tol Warning Actual landed in range?
95% 86.1–89.5 86.3–90.4 3.17 pts — No
90% 86.2–89.3 86.6–89.6 2.72 pts — No
85% 86.4–89.1 86.8–89.5 2.22 pts — No
80% 86.5–89.0 87.0–89.3 2.01 pts — No
75% 86.6–88.8 87.1–89.1 1.69 pts — No
Darren "Dimes" Lin — NY at MIN — Actual: NY 85, MIN 90
Level NY range MIN range Overlap Tol Warning Actual landed in range?
95% 85.7–89.8 85.6–90.5 4.09 pts — No
90% 86.0–89.4 86.0–90.1 3.43 pts — No
85% 86.2–89.2 86.2–89.9 3.0 pts — No
80% 86.4–89.1 86.4–89.7 2.64 pts — No
75% 86.5–88.9 86.6–89.5 2.33 pts — No
Maya Jefferson — NY at MIN — Actual: NY 85, MIN 90
Level NY range MIN range Overlap Tol Warning Actual landed in range?
95% 85.3–89.8 85.7–90.3 4.1 pts — No
90% 85.7–89.5 86.1–89.9 3.37 pts — No
85% 85.9–89.2 86.3–89.7 2.9 pts — No
80% 86.1–89.1 86.5–89.5 2.54 pts — No
75% 86.3–88.9 86.7–89.3 2.24 pts — No
Lexi — NY at MIN — Actual: NY 85, MIN 90
Level NY range MIN range Overlap Tol Warning Actual landed in range?
95% 85.8–89.6 85.6–90.6 3.86 pts — No
90% 86.0–89.1 86.0–90.2 3.1 pts — No
85% 86.2–88.9 86.2–89.9 2.64 pts — No
80% 86.4–88.8 86.4–89.7 2.41 pts — No
75% 86.8–88.8 86.6–89.6 2.02 pts — No
Coach Sarah Watanabe — NY at MIN — Actual: NY 85, MIN 90
Level NY range MIN range Overlap Tol Warning Actual landed in range?
95% 84.9–89.2 85.3–90.2 3.91 pts — Yes
90% 85.6–88.9 85.7–89.9 3.2 pts — No
85% 85.8–88.7 86.0–89.6 2.69 pts — No
80% 86.1–88.5 86.2–89.4 2.34 pts — No
75% 86.2–88.4 86.3–89.2 2.06 pts — No