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Golden State Valkyries at Dallas Wings

GS 100 – DAL 108

September 30, 2026 · Final

Kevin

Best model for this game

Kevin
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 GS at DAL

All 12 models’ predicted scores

GS — one dot per model DAL — one dot per model Actual: GS 100, DAL 108
Vince Chambers
GS 77.9–83.0 DAL 84.9–89.3 No overlap Actual: GS 100, DAL 108

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Golden State Valkyries (avg. 80.9) — by 6.2 points. The 95% ranges don't overlap at all — a confident model.

GS 79.0–82.7 DAL 85.2–88.9 No overlap Actual: GS 100, DAL 108

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Golden State Valkyries (avg. 80.9) — by 6.2 points. The 90% ranges don't overlap at all — a confident model.

GS 79.2–82.4 DAL 85.4–88.7 No overlap Actual: GS 100, DAL 108

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Golden State Valkyries (avg. 80.9) — by 6.2 points. The 85% ranges don't overlap at all — a confident model.

GS 79.3–82.3 DAL 85.6–88.5 No overlap Actual: GS 100, DAL 108

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Golden State Valkyries (avg. 80.9) — by 6.2 points. The 80% ranges don't overlap at all — a confident model.

GS 79.6–82.2 DAL 85.8–88.3 No overlap Actual: GS 100, DAL 108

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Golden State Valkyries (avg. 80.9) — by 6.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Vince Chambers (#1)
t-statistic
-54.00
p-value
2.30e-178

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
GS 78.0–83.9 DAL 84.8–89.7 No overlap Actual: GS 100, DAL 108

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 87.2) over Golden State Valkyries (avg. 81.0) — by 6.3 points. The 95% ranges don't overlap at all — a confident model.

GS 78.5–83.4 DAL 85.2–89.3 No overlap Actual: GS 100, DAL 108

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 87.2) over Golden State Valkyries (avg. 81.0) — by 6.3 points. The 90% ranges don't overlap at all — a confident model.

GS 78.8–83.1 DAL 85.4–89.1 No overlap Actual: GS 100, DAL 108

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 87.2) over Golden State Valkyries (avg. 81.0) — by 6.3 points. The 85% ranges don't overlap at all — a confident model.

GS 79.0–82.9 DAL 85.6–88.9 No overlap Actual: GS 100, DAL 108

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 87.2) over Golden State Valkyries (avg. 81.0) — by 6.3 points. The 80% ranges don't overlap at all — a confident model.

GS 79.2–82.7 DAL 85.8–88.7 No overlap Actual: GS 100, DAL 108

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 87.2) over Golden State Valkyries (avg. 81.0) — by 6.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Reg (#2)
t-statistic
-48.74
p-value
5.92e-164

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
GS 78.4–83.0 DAL 84.4–89.0 No overlap Actual: GS 100, DAL 108

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.7) — by 6.3 points. The 95% ranges don't overlap at all — a confident model.

GS 78.8–82.6 DAL 85.0–88.7 No overlap Actual: GS 100, DAL 108

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.7) — by 6.3 points. The 90% ranges don't overlap at all — a confident model.

GS 79.0–82.4 DAL 85.7–88.4 No overlap Actual: GS 100, DAL 108

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.7) — by 6.3 points. The 85% ranges don't overlap at all — a confident model.

GS 79.2–82.2 DAL 85.9–88.2 No overlap Actual: GS 100, DAL 108

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.7) — by 6.3 points. The 80% ranges don't overlap at all — a confident model.

GS 79.4–82.1 DAL 86.0–88.0 No overlap Actual: GS 100, DAL 108

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.7) — by 6.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Wallace (#3)
t-statistic
-56.75
p-value
9.72e-189

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
GS 78.4–83.1 DAL 84.8–88.7 No overlap Actual: GS 100, DAL 108

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Golden State Valkyries (avg. 80.7) — by 6.4 points. The 95% ranges don't overlap at all — a confident model.

GS 78.8–82.7 DAL 85.4–88.4 No overlap Actual: GS 100, DAL 108

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Golden State Valkyries (avg. 80.7) — by 6.4 points. The 90% ranges don't overlap at all — a confident model.

GS 79.0–82.5 DAL 85.8–88.3 No overlap Actual: GS 100, DAL 108

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Golden State Valkyries (avg. 80.7) — by 6.4 points. The 85% ranges don't overlap at all — a confident model.

GS 79.2–82.3 DAL 86.1–88.3 No overlap Actual: GS 100, DAL 108

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Golden State Valkyries (avg. 80.7) — by 6.4 points. The 80% ranges don't overlap at all — a confident model.

GS 79.4–82.1 DAL 86.2–88.2 No overlap Actual: GS 100, DAL 108

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 87.1) over Golden State Valkyries (avg. 80.7) — by 6.4 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Kevin (#4)
t-statistic
-61.90
p-value
1.28e-199

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
GS 78.6–83.6 DAL 84.7–89.0 No overlap Actual: GS 100, DAL 108

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Golden State Valkyries (avg. 81.1) — by 5.7 points. The 95% ranges don't overlap at all — a confident model.

GS 79.0–83.2 DAL 85.0–88.6 No overlap Actual: GS 100, DAL 108

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Golden State Valkyries (avg. 81.1) — by 5.7 points. The 90% ranges don't overlap at all — a confident model.

GS 79.3–83.0 DAL 85.3–88.4 No overlap Actual: GS 100, DAL 108

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Golden State Valkyries (avg. 81.1) — by 5.7 points. The 85% ranges don't overlap at all — a confident model.

GS 79.5–82.8 DAL 85.4–88.2 No overlap Actual: GS 100, DAL 108

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Golden State Valkyries (avg. 81.1) — by 5.7 points. The 80% ranges don't overlap at all — a confident model.

GS 79.6–82.6 DAL 85.6–88.1 No overlap Actual: GS 100, DAL 108

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Golden State Valkyries (avg. 81.1) — by 5.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
-51.41
p-value
1.93e-171

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
GS 78.0–83.6 DAL 83.8–88.7 No overlap Actual: GS 100, DAL 108

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.8) — by 6.1 points. The 95% ranges don't overlap at all — a confident model.

GS 78.4–83.1 DAL 85.1–88.4 No overlap Actual: GS 100, DAL 108

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.8) — by 6.1 points. The 90% ranges don't overlap at all — a confident model.

GS 78.7–82.8 DAL 85.4–88.2 No overlap Actual: GS 100, DAL 108

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.8) — by 6.1 points. The 85% ranges don't overlap at all — a confident model.

GS 78.9–82.6 DAL 85.7–88.1 No overlap Actual: GS 100, DAL 108

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.8) — by 6.1 points. The 80% ranges don't overlap at all — a confident model.

GS 79.1–82.4 DAL 85.8–87.9 No overlap Actual: GS 100, DAL 108

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.8) — by 6.1 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Ice (#6)
t-statistic
-49.40
p-value
2.65e-166

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
GS 78.0–83.4 DAL 84.7–88.8 No overlap Actual: GS 100, DAL 108

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.7) — by 6.3 points. The 95% ranges don't overlap at all — a confident model.

GS 78.4–83.0 DAL 85.2–88.5 No overlap Actual: GS 100, DAL 108

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.7) — by 6.3 points. The 90% ranges don't overlap at all — a confident model.

GS 78.7–82.7 DAL 85.5–88.3 No overlap Actual: GS 100, DAL 108

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.7) — by 6.3 points. The 85% ranges don't overlap at all — a confident model.

GS 78.9–82.5 DAL 85.8–88.2 No overlap Actual: GS 100, DAL 108

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.7) — by 6.3 points. The 80% ranges don't overlap at all — a confident model.

GS 79.1–82.3 DAL 85.9–88.1 No overlap Actual: GS 100, DAL 108

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.7) — by 6.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jamal (#7)
t-statistic
-53.57
p-value
1.98e-176

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
GS 78.5–83.2 DAL 84.8–88.7 No overlap Actual: GS 100, DAL 108

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.8) — by 6.1 points. The 95% ranges don't overlap at all — a confident model.

GS 78.8–82.8 DAL 85.2–88.5 No overlap Actual: GS 100, DAL 108

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.8) — by 6.1 points. The 90% ranges don't overlap at all — a confident model.

GS 79.1–82.6 DAL 85.5–88.4 No overlap Actual: GS 100, DAL 108

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.8) — by 6.1 points. The 85% ranges don't overlap at all — a confident model.

GS 79.3–82.4 DAL 85.8–88.1 No overlap Actual: GS 100, DAL 108

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.8) — by 6.1 points. The 80% ranges don't overlap at all — a confident model.

GS 79.4–82.2 DAL 85.9–88.0 No overlap Actual: GS 100, DAL 108

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.8) — by 6.1 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jordan (#8)
t-statistic
-57.69
p-value
1.15e-189

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
GS 78.4–83.2 DAL 84.1–89.3 No overlap Actual: GS 100, DAL 108

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Golden State Valkyries (avg. 80.8) — by 6.0 points. The 95% ranges don't overlap at all — a confident model.

GS 78.8–82.7 DAL 85.0–88.4 No overlap Actual: GS 100, DAL 108

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Golden State Valkyries (avg. 80.8) — by 6.0 points. The 90% ranges don't overlap at all — a confident model.

GS 79.0–82.5 DAL 85.3–88.1 No overlap Actual: GS 100, DAL 108

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Golden State Valkyries (avg. 80.8) — by 6.0 points. The 85% ranges don't overlap at all — a confident model.

GS 79.4–82.2 DAL 85.5–87.9 No overlap Actual: GS 100, DAL 108

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Golden State Valkyries (avg. 80.8) — by 6.0 points. The 80% ranges don't overlap at all — a confident model.

GS 79.6–81.9 DAL 85.6–87.9 No overlap Actual: GS 100, DAL 108

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.8) over Golden State Valkyries (avg. 80.8) — by 6.0 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
-50.12
p-value
1.71e-170

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
GS 78.6–83.3 DAL 84.8–89.2 No overlap Actual: GS 100, DAL 108

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.8) — by 6.2 points. The 95% ranges don't overlap at all — a confident model.

GS 79.0–82.8 DAL 85.2–88.8 No overlap Actual: GS 100, DAL 108

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.8) — by 6.2 points. The 90% ranges don't overlap at all — a confident model.

GS 79.3–82.4 DAL 85.4–88.6 No overlap Actual: GS 100, DAL 108

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.8) — by 6.2 points. The 85% ranges don't overlap at all — a confident model.

GS 79.4–82.3 DAL 85.6–88.4 No overlap Actual: GS 100, DAL 108

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.8) — by 6.2 points. The 80% ranges don't overlap at all — a confident model.

GS 79.7–82.2 DAL 85.7–88.3 No overlap Actual: GS 100, DAL 108

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.8) — by 6.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Maya Jefferson (#10)
t-statistic
-54.34
p-value
3.01e-179

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
GS 77.8–82.6 DAL 85.0–88.8 No overlap Actual: GS 100, DAL 108

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.7) — by 6.2 points. The 95% ranges don't overlap at all — a confident model.

GS 78.7–82.4 DAL 85.3–88.5 No overlap Actual: GS 100, DAL 108

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.7) — by 6.2 points. The 90% ranges don't overlap at all — a confident model.

GS 78.9–82.3 DAL 85.5–88.3 No overlap Actual: GS 100, DAL 108

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.7) — by 6.2 points. The 85% ranges don't overlap at all — a confident model.

GS 79.2–82.2 DAL 85.7–88.1 No overlap Actual: GS 100, DAL 108

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.7) — by 6.2 points. The 80% ranges don't overlap at all — a confident model.

GS 79.5–82.1 DAL 85.8–88.0 No overlap Actual: GS 100, DAL 108

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.7) — by 6.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Lexi (#11)
t-statistic
-59.02
p-value
1.66e-185

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
GS 79.5–84.9 DAL 85.2–89.9 No overlap Actual: GS 100, DAL 108

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 87.8) over Golden State Valkyries (avg. 82.2) — by 5.6 points. The 95% ranges don't overlap at all — a confident model.

GS 79.9–84.5 DAL 86.1–89.7 No overlap Actual: GS 100, DAL 108

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 87.8) over Golden State Valkyries (avg. 82.2) — by 5.6 points. The 90% ranges don't overlap at all — a confident model.

GS 80.2–84.2 DAL 86.2–89.4 No overlap Actual: GS 100, DAL 108

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 87.8) over Golden State Valkyries (avg. 82.2) — by 5.6 points. The 85% ranges don't overlap at all — a confident model.

GS 80.4–84.0 DAL 86.4–89.2 No overlap Actual: GS 100, DAL 108

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 87.8) over Golden State Valkyries (avg. 82.2) — by 5.6 points. The 80% ranges don't overlap at all — a confident model.

GS 80.6–83.8 DAL 86.8–89.1 No overlap Actual: GS 100, DAL 108

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 87.8) over Golden State Valkyries (avg. 82.2) — by 5.6 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
-46.29
p-value
4.28e-158

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 — GS at DAL — Actual: GS 100, DAL 108
Level GS range DAL range Overlap Tol Warning Actual landed in range?
95% 77.9–83.0 84.9–89.3 — pts — No
90% 79.0–82.7 85.2–88.9 — pts — No
85% 79.2–82.4 85.4–88.7 — pts — No
80% 79.3–82.3 85.6–88.5 — pts — No
75% 79.6–82.2 85.8–88.3 — pts — No
Reg — GS at DAL — Actual: GS 100, DAL 108
Level GS range DAL range Overlap Tol Warning Actual landed in range?
95% 78.0–83.9 84.8–89.7 — pts — No
90% 78.5–83.4 85.2–89.3 — pts — No
85% 78.8–83.1 85.4–89.1 — pts — No
80% 79.0–82.9 85.6–88.9 — pts — No
75% 79.2–82.7 85.8–88.7 — pts — No
Dr. Wallace — GS at DAL — Actual: GS 100, DAL 108
Level GS range DAL range Overlap Tol Warning Actual landed in range?
95% 78.4–83.0 84.4–89.0 — pts — No
90% 78.8–82.6 85.0–88.7 — pts — No
85% 79.0–82.4 85.7–88.4 — pts — No
80% 79.2–82.2 85.9–88.2 — pts — No
75% 79.4–82.1 86.0–88.0 — pts — No
Kevin — GS at DAL — Actual: GS 100, DAL 108
Level GS range DAL range Overlap Tol Warning Actual landed in range?
95% 78.4–83.1 84.8–88.7 — pts — No
90% 78.8–82.7 85.4–88.4 — pts — No
85% 79.0–82.5 85.8–88.3 — pts — No
80% 79.2–82.3 86.1–88.3 — pts — No
75% 79.4–82.1 86.2–88.2 — pts — No
Dr. Lila Shah — GS at DAL — Actual: GS 100, DAL 108
Level GS range DAL range Overlap Tol Warning Actual landed in range?
95% 78.6–83.6 84.7–89.0 — pts — No
90% 79.0–83.2 85.0–88.6 — pts — No
85% 79.3–83.0 85.3–88.4 — pts — No
80% 79.5–82.8 85.4–88.2 — pts — No
75% 79.6–82.6 85.6–88.1 — pts — No
Ice — GS at DAL — Actual: GS 100, DAL 108
Level GS range DAL range Overlap Tol Warning Actual landed in range?
95% 78.0–83.6 83.8–88.7 — pts — No
90% 78.4–83.1 85.1–88.4 — pts — No
85% 78.7–82.8 85.4–88.2 — pts — No
80% 78.9–82.6 85.7–88.1 — pts — No
75% 79.1–82.4 85.8–87.9 — pts — No
Jamal — GS at DAL — Actual: GS 100, DAL 108
Level GS range DAL range Overlap Tol Warning Actual landed in range?
95% 78.0–83.4 84.7–88.8 — pts — No
90% 78.4–83.0 85.2–88.5 — pts — No
85% 78.7–82.7 85.5–88.3 — pts — No
80% 78.9–82.5 85.8–88.2 — pts — No
75% 79.1–82.3 85.9–88.1 — pts — No
Jordan — GS at DAL — Actual: GS 100, DAL 108
Level GS range DAL range Overlap Tol Warning Actual landed in range?
95% 78.5–83.2 84.8–88.7 — pts — No
90% 78.8–82.8 85.2–88.5 — pts — No
85% 79.1–82.6 85.5–88.4 — pts — No
80% 79.3–82.4 85.8–88.1 — pts — No
75% 79.4–82.2 85.9–88.0 — pts — No
Darren "Dimes" Lin — GS at DAL — Actual: GS 100, DAL 108
Level GS range DAL range Overlap Tol Warning Actual landed in range?
95% 78.4–83.2 84.1–89.3 — pts — No
90% 78.8–82.7 85.0–88.4 — pts — No
85% 79.0–82.5 85.3–88.1 — pts — No
80% 79.4–82.2 85.5–87.9 — pts — No
75% 79.6–81.9 85.6–87.9 — pts — No
Maya Jefferson — GS at DAL — Actual: GS 100, DAL 108
Level GS range DAL range Overlap Tol Warning Actual landed in range?
95% 78.6–83.3 84.8–89.2 — pts — No
90% 79.0–82.8 85.2–88.8 — pts — No
85% 79.3–82.4 85.4–88.6 — pts — No
80% 79.4–82.3 85.6–88.4 — pts — No
75% 79.7–82.2 85.7–88.3 — pts — No
Lexi — GS at DAL — Actual: GS 100, DAL 108
Level GS range DAL range Overlap Tol Warning Actual landed in range?
95% 77.8–82.6 85.0–88.8 — pts — No
90% 78.7–82.4 85.3–88.5 — pts — No
85% 78.9–82.3 85.5–88.3 — pts — No
80% 79.2–82.2 85.7–88.1 — pts — No
75% 79.5–82.1 85.8–88.0 — pts — No
Coach Sarah Watanabe — GS at DAL — Actual: GS 100, DAL 108
Level GS range DAL range Overlap Tol Warning Actual landed in range?
95% 79.5–84.9 85.2–89.9 — pts — No
90% 79.9–84.5 86.1–89.7 — pts — No
85% 80.2–84.2 86.2–89.4 — pts — No
80% 80.4–84.0 86.4–89.2 — pts — No
75% 80.6–83.8 86.8–89.1 — pts — No