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Dallas Wings at Golden State Valkyries

DAL 73 – GS 77

October 2, 2026 · Final

Coach Sarah Watanabe

Best model for this game

Coach Sarah Watanabe
All models: 0-12
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 DAL at GS

All 12 models’ predicted scores

DAL — one dot per model GS — one dot per model Actual: DAL 73, GS 77
Vince Chambers
DAL 84.7–88.8 GS 78.2–83.6 No overlap Actual: DAL 73, GS 77

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.9) — by 6.0 points. The 95% ranges don't overlap at all — a confident model.

DAL 85.1–88.6 GS 78.7–83.1 No overlap Actual: DAL 73, GS 77

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.9) — by 6.0 points. The 90% ranges don't overlap at all — a confident model.

DAL 85.3–88.4 GS 78.9–82.8 No overlap Actual: DAL 73, GS 77

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.9) — by 6.0 points. The 85% ranges don't overlap at all — a confident model.

DAL 85.5–88.2 GS 79.2–82.6 No overlap Actual: DAL 73, GS 77

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.9) — by 6.0 points. The 80% ranges don't overlap at all — a confident model.

DAL 85.7–88.1 GS 79.3–82.5 No overlap Actual: DAL 73, GS 77

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.9) — by 6.0 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Vince Chambers (#1)
t-statistic
50.08
p-value
1.90e-168

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
DAL 84.6–89.0 GS 77.7–84.1 No overlap Actual: DAL 73, GS 77

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.

DAL 85.2–88.7 GS 78.2–83.6 No overlap Actual: DAL 73, GS 77

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.

DAL 85.6–88.5 GS 78.5–83.2 No overlap Actual: DAL 73, GS 77

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.

DAL 85.8–88.4 GS 78.8–83.0 No overlap Actual: DAL 73, GS 77

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.

DAL 86.0–88.3 GS 79.0–82.8 No overlap Actual: DAL 73, GS 77

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
Reg (#2)
t-statistic
47.00
p-value
8.87e-152

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
DAL 84.9–89.1 GS 78.3–82.9 No overlap Actual: DAL 73, GS 77

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.6) — by 6.3 points. The 95% ranges don't overlap at all — a confident model.

DAL 85.2–88.7 GS 78.8–82.6 No overlap Actual: DAL 73, GS 77

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.6) — by 6.3 points. The 90% ranges don't overlap at all — a confident model.

DAL 85.4–88.5 GS 79.2–82.4 No overlap Actual: DAL 73, GS 77

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.6) — by 6.3 points. The 85% ranges don't overlap at all — a confident model.

DAL 85.6–88.3 GS 79.3–82.2 No overlap Actual: DAL 73, GS 77

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.6) — by 6.3 points. The 80% ranges don't overlap at all — a confident model.

DAL 85.7–88.2 GS 79.4–82.0 No overlap Actual: DAL 73, GS 77

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.6) — by 6.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Wallace (#3)
t-statistic
56.89
p-value
8.97e-184

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
DAL 84.9–88.4 GS 78.1–83.0 No overlap Actual: DAL 73, GS 77

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.6) — by 6.3 points. The 95% ranges don't overlap at all — a confident model.

DAL 85.5–88.2 GS 78.5–82.6 No overlap Actual: DAL 73, GS 77

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.6) — by 6.3 points. The 90% ranges don't overlap at all — a confident model.

DAL 85.8–88.2 GS 78.8–82.4 No overlap Actual: DAL 73, GS 77

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.6) — by 6.3 points. The 85% ranges don't overlap at all — a confident model.

DAL 85.9–88.0 GS 79.0–82.2 No overlap Actual: DAL 73, GS 77

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.6) — by 6.3 points. The 80% ranges don't overlap at all — a confident model.

DAL 86.0–87.9 GS 79.1–82.0 No overlap Actual: DAL 73, GS 77

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.9) over Golden State Valkyries (avg. 80.6) — by 6.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Kevin (#4)
t-statistic
57.79
p-value
9.51e-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.

Dr. Lila Shah
DAL 84.8–88.6 GS 77.7–83.5 No overlap Actual: DAL 73, GS 77

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 81.0) — by 5.7 points. The 95% ranges don't overlap at all — a confident model.

DAL 85.1–88.3 GS 78.5–83.0 No overlap Actual: DAL 73, GS 77

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 81.0) — by 5.7 points. The 90% ranges don't overlap at all — a confident model.

DAL 85.3–88.1 GS 78.8–82.7 No overlap Actual: DAL 73, GS 77

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 81.0) — by 5.7 points. The 85% ranges don't overlap at all — a confident model.

DAL 85.4–87.9 GS 79.4–82.4 No overlap Actual: DAL 73, GS 77

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 81.0) — by 5.7 points. The 80% ranges don't overlap at all — a confident model.

DAL 85.5–87.8 GS 79.5–82.4 No overlap Actual: DAL 73, GS 77

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 81.0) — 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
49.64
p-value
1.61e-156

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
DAL 83.2–88.8 GS 78.1–83.6 Overlap 0.4 pts Actual: DAL 73, GS 77

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 80.8) — by 5.8 points. The ranges barely touch.

DAL 84.6–88.6 GS 78.5–83.2 No overlap Actual: DAL 73, GS 77

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 80.8) — by 5.8 points. The 90% ranges don't overlap at all — a confident model.

DAL 84.7–88.4 GS 78.8–82.9 No overlap Actual: DAL 73, GS 77

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 80.8) — by 5.8 points. The 85% ranges don't overlap at all — a confident model.

DAL 85.1–88.2 GS 79.0–82.6 No overlap Actual: DAL 73, GS 77

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 80.8) — by 5.8 points. The 80% ranges don't overlap at all — a confident model.

DAL 85.2–88.1 GS 79.2–82.5 No overlap Actual: DAL 73, GS 77

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 80.8) — by 5.8 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Ice (#6)
t-statistic
43.49
p-value
1.64e-149

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
DAL 83.4–88.4 GS 77.9–83.2 No overlap Actual: DAL 73, GS 77

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 80.7) — by 6.0 points. The 95% ranges don't overlap at all — a confident model.

DAL 84.7–88.1 GS 78.7–82.5 No overlap Actual: DAL 73, GS 77

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 80.7) — by 6.0 points. The 90% ranges don't overlap at all — a confident model.

DAL 85.0–88.0 GS 79.0–82.3 No overlap Actual: DAL 73, GS 77

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 80.7) — by 6.0 points. The 85% ranges don't overlap at all — a confident model.

DAL 85.5–87.8 GS 79.2–82.1 No overlap Actual: DAL 73, GS 77

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 80.7) — by 6.0 points. The 80% ranges don't overlap at all — a confident model.

DAL 85.6–87.7 GS 79.3–82.1 No overlap Actual: DAL 73, GS 77

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 86.7) over Golden State Valkyries (avg. 80.7) — by 6.0 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jamal (#7)
t-statistic
45.36
p-value
2.76e-155

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
DAL 84.0–88.8 GS 78.2–83.3 No overlap Actual: DAL 73, GS 77

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.

DAL 84.7–88.2 GS 78.6–82.9 No overlap Actual: DAL 73, GS 77

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.

DAL 85.1–88.1 GS 78.9–82.7 No overlap Actual: DAL 73, GS 77

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.

DAL 85.4–88.0 GS 79.1–82.4 No overlap Actual: DAL 73, GS 77

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.

DAL 85.6–87.9 GS 79.3–82.3 No overlap Actual: DAL 73, GS 77

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
Jordan (#8)
t-statistic
49.18
p-value
7.72e-167

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
DAL 84.9–88.8 GS 78.2–82.9 No overlap Actual: DAL 73, GS 77

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.

DAL 85.2–88.5 GS 78.7–82.7 No overlap Actual: DAL 73, GS 77

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.

DAL 85.4–88.3 GS 79.1–82.4 No overlap Actual: DAL 73, GS 77

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.

DAL 85.6–88.2 GS 79.2–82.2 No overlap Actual: DAL 73, GS 77

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.

DAL 85.8–88.1 GS 79.3–81.9 No overlap Actual: DAL 73, GS 77

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
Darren "Dimes" Lin (#9)
t-statistic
53.07
p-value
1.34e-177

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
DAL 84.7–89.2 GS 78.1–83.3 No overlap Actual: DAL 73, GS 77

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.7) — by 6.2 points. The 95% ranges don't overlap at all — a confident model.

DAL 85.1–88.8 GS 78.7–82.7 No overlap Actual: DAL 73, GS 77

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.7) — by 6.2 points. The 90% ranges don't overlap at all — a confident model.

DAL 85.3–88.6 GS 78.9–82.3 No overlap Actual: DAL 73, GS 77

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.7) — by 6.2 points. The 85% ranges don't overlap at all — a confident model.

DAL 85.5–88.4 GS 79.1–82.0 No overlap Actual: DAL 73, GS 77

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) over Golden State Valkyries (avg. 80.7) — by 6.2 points. The 80% ranges don't overlap at all — a confident model.

DAL 85.6–88.3 GS 79.5–81.9 No overlap Actual: DAL 73, GS 77

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 87.0) 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
Maya Jefferson (#10)
t-statistic
53.26
p-value
8.18e-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.

Lexi
DAL 84.5–88.6 GS 78.1–83.1 No overlap Actual: DAL 73, GS 77

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.

DAL 85.0–88.3 GS 78.6–82.8 No overlap Actual: DAL 73, GS 77

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.

DAL 85.4–88.2 GS 79.0–82.5 No overlap Actual: DAL 73, GS 77

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.

DAL 85.6–88.1 GS 79.2–82.4 No overlap Actual: DAL 73, GS 77

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.

DAL 85.7–88.0 GS 79.4–82.2 No overlap Actual: DAL 73, GS 77

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
Lexi (#11)
t-statistic
48.73
p-value
3.40e-161

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
DAL 85.5–89.6 GS 79.7–84.6 No overlap Actual: DAL 73, GS 77

In 95 out of 100 simulated runs, leans Dallas Wings (avg. 87.7) over Golden State Valkyries (avg. 82.2) — by 5.5 points. The 95% ranges don't overlap at all — a confident model.

DAL 86.0–89.3 GS 80.1–84.2 No overlap Actual: DAL 73, GS 77

In 90 out of 100 simulated runs, leans Dallas Wings (avg. 87.7) over Golden State Valkyries (avg. 82.2) — by 5.5 points. The 90% ranges don't overlap at all — a confident model.

DAL 86.2–89.3 GS 80.3–84.0 No overlap Actual: DAL 73, GS 77

In 85 out of 100 simulated runs, leans Dallas Wings (avg. 87.7) over Golden State Valkyries (avg. 82.2) — by 5.5 points. The 85% ranges don't overlap at all — a confident model.

DAL 86.4–89.1 GS 80.5–83.8 No overlap Actual: DAL 73, GS 77

In 80 out of 100 simulated runs, leans Dallas Wings (avg. 87.7) over Golden State Valkyries (avg. 82.2) — by 5.5 points. The 80% ranges don't overlap at all — a confident model.

DAL 86.5–88.8 GS 80.7–83.6 No overlap Actual: DAL 73, GS 77

In 75 out of 100 simulated runs, leans Dallas Wings (avg. 87.7) over Golden State Valkyries (avg. 82.2) — by 5.5 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
47.76
p-value
1.40e-162

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 — DAL at GS — Actual: DAL 73, GS 77
Level DAL range GS range Overlap Tol Warning Actual landed in range?
95% 84.7–88.8 78.2–83.6 — pts — No
90% 85.1–88.6 78.7–83.1 — pts — No
85% 85.3–88.4 78.9–82.8 — pts — No
80% 85.5–88.2 79.2–82.6 — pts — No
75% 85.7–88.1 79.3–82.5 — pts — No
Reg — DAL at GS — Actual: DAL 73, GS 77
Level DAL range GS range Overlap Tol Warning Actual landed in range?
95% 84.6–89.0 77.7–84.1 — pts — No
90% 85.2–88.7 78.2–83.6 — pts — No
85% 85.6–88.5 78.5–83.2 — pts — No
80% 85.8–88.4 78.8–83.0 — pts — No
75% 86.0–88.3 79.0–82.8 — pts — No
Dr. Wallace — DAL at GS — Actual: DAL 73, GS 77
Level DAL range GS range Overlap Tol Warning Actual landed in range?
95% 84.9–89.1 78.3–82.9 — pts — No
90% 85.2–88.7 78.8–82.6 — pts — No
85% 85.4–88.5 79.2–82.4 — pts — No
80% 85.6–88.3 79.3–82.2 — pts — No
75% 85.7–88.2 79.4–82.0 — pts — No
Kevin — DAL at GS — Actual: DAL 73, GS 77
Level DAL range GS range Overlap Tol Warning Actual landed in range?
95% 84.9–88.4 78.1–83.0 — pts — No
90% 85.5–88.2 78.5–82.6 — pts — No
85% 85.8–88.2 78.8–82.4 — pts — No
80% 85.9–88.0 79.0–82.2 — pts — No
75% 86.0–87.9 79.1–82.0 — pts — No
Dr. Lila Shah — DAL at GS — Actual: DAL 73, GS 77
Level DAL range GS range Overlap Tol Warning Actual landed in range?
95% 84.8–88.6 77.7–83.5 — pts — No
90% 85.1–88.3 78.5–83.0 — pts — No
85% 85.3–88.1 78.8–82.7 — pts — No
80% 85.4–87.9 79.4–82.4 — pts — No
75% 85.5–87.8 79.5–82.4 — pts — No
Ice — DAL at GS — Actual: DAL 73, GS 77
Level DAL range GS range Overlap Tol Warning Actual landed in range?
95% 83.2–88.8 78.1–83.6 0.4 pts — No
90% 84.6–88.6 78.5–83.2 — pts — No
85% 84.7–88.4 78.8–82.9 — pts — No
80% 85.1–88.2 79.0–82.6 — pts — No
75% 85.2–88.1 79.2–82.5 — pts — No
Jamal — DAL at GS — Actual: DAL 73, GS 77
Level DAL range GS range Overlap Tol Warning Actual landed in range?
95% 83.4–88.4 77.9–83.2 — pts — No
90% 84.7–88.1 78.7–82.5 — pts — No
85% 85.0–88.0 79.0–82.3 — pts — No
80% 85.5–87.8 79.2–82.1 — pts — No
75% 85.6–87.7 79.3–82.1 — pts — No
Jordan — DAL at GS — Actual: DAL 73, GS 77
Level DAL range GS range Overlap Tol Warning Actual landed in range?
95% 84.0–88.8 78.2–83.3 — pts — No
90% 84.7–88.2 78.6–82.9 — pts — No
85% 85.1–88.1 78.9–82.7 — pts — No
80% 85.4–88.0 79.1–82.4 — pts — No
75% 85.6–87.9 79.3–82.3 — pts — No
Darren "Dimes" Lin — DAL at GS — Actual: DAL 73, GS 77
Level DAL range GS range Overlap Tol Warning Actual landed in range?
95% 84.9–88.8 78.2–82.9 — pts — No
90% 85.2–88.5 78.7–82.7 — pts — No
85% 85.4–88.3 79.1–82.4 — pts — No
80% 85.6–88.2 79.2–82.2 — pts — No
75% 85.8–88.1 79.3–81.9 — pts — No
Maya Jefferson — DAL at GS — Actual: DAL 73, GS 77
Level DAL range GS range Overlap Tol Warning Actual landed in range?
95% 84.7–89.2 78.1–83.3 — pts — No
90% 85.1–88.8 78.7–82.7 — pts — No
85% 85.3–88.6 78.9–82.3 — pts — No
80% 85.5–88.4 79.1–82.0 — pts — No
75% 85.6–88.3 79.5–81.9 — pts — No
Lexi — DAL at GS — Actual: DAL 73, GS 77
Level DAL range GS range Overlap Tol Warning Actual landed in range?
95% 84.5–88.6 78.1–83.1 — pts — No
90% 85.0–88.3 78.6–82.8 — pts — No
85% 85.4–88.2 79.0–82.5 — pts — No
80% 85.6–88.1 79.2–82.4 — pts — No
75% 85.7–88.0 79.4–82.2 — pts — No
Coach Sarah Watanabe — DAL at GS — Actual: DAL 73, GS 77
Level DAL range GS range Overlap Tol Warning Actual landed in range?
95% 85.5–89.6 79.7–84.6 — pts — No
90% 86.0–89.3 80.1–84.2 — pts — No
85% 86.2–89.3 80.3–84.0 — pts — No
80% 86.4–89.1 80.5–83.8 — pts — No
75% 86.5–88.8 80.7–83.6 — pts — No