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Indiana Fever at Seattle Storm

IND 105 – SEA 95

July 28, 2026 · Final

Dr. Lila Shah

Best model for this game

Dr. Lila Shah
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 IND at SEA

All 12 models’ predicted scores

IND — one dot per model SEA — one dot per model Actual: IND 105, SEA 95
Vince Chambers
IND 88.0–93.3 SEA 82.6–88.5 Overlap 0.47 pts Actual: IND 105, SEA 95

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.6) over Seattle Storm (avg. 84.9) — by 5.8 points. The ranges barely touch.

IND 88.4–92.9 SEA 82.8–87.9 No overlap Actual: IND 105, SEA 95

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.6) over Seattle Storm (avg. 84.9) — by 5.8 points. The 90% ranges don't overlap at all — a confident model.

IND 88.7–92.6 SEA 83.0–87.0 No overlap Actual: IND 105, SEA 95

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.6) over Seattle Storm (avg. 84.9) — by 5.8 points. The 85% ranges don't overlap at all — a confident model.

IND 88.9–92.4 SEA 83.2–86.6 No overlap Actual: IND 105, SEA 95

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.6) over Seattle Storm (avg. 84.9) — by 5.8 points. The 80% ranges don't overlap at all — a confident model.

IND 89.1–92.2 SEA 83.4–86.4 No overlap Actual: IND 105, SEA 95

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.6) over Seattle Storm (avg. 84.9) — by 5.8 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Vince Chambers (#1)
t-statistic
30.01
p-value
7.02e-74

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
IND 87.7–93.1 SEA 82.5–87.6 No overlap Actual: IND 105, SEA 95

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.7) over Seattle Storm (avg. 85.0) — by 5.7 points. The 95% ranges don't overlap at all — a confident model.

IND 88.6–92.9 SEA 83.2–87.0 No overlap Actual: IND 105, SEA 95

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.7) over Seattle Storm (avg. 85.0) — by 5.7 points. The 90% ranges don't overlap at all — a confident model.

IND 88.8–92.8 SEA 83.4–86.8 No overlap Actual: IND 105, SEA 95

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.7) over Seattle Storm (avg. 85.0) — by 5.7 points. The 85% ranges don't overlap at all — a confident model.

IND 89.2–92.4 SEA 83.5–86.6 No overlap Actual: IND 105, SEA 95

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.7) over Seattle Storm (avg. 85.0) — by 5.7 points. The 80% ranges don't overlap at all — a confident model.

IND 89.3–92.3 SEA 83.5–86.5 No overlap Actual: IND 105, SEA 95

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.7) over Seattle Storm (avg. 85.0) — by 5.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Reg (#2)
t-statistic
27.59
p-value
2.13e-70

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
IND 86.7–94.1 SEA 80.6–87.2 Overlap 0.48 pts Actual: IND 105, SEA 95

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.4) over Seattle Storm (avg. 84.4) — by 6.0 points. The ranges barely touch.

IND 87.3–93.5 SEA 81.5–86.6 No overlap Actual: IND 105, SEA 95

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.4) over Seattle Storm (avg. 84.4) — by 6.0 points. The 90% ranges don't overlap at all — a confident model.

IND 87.7–93.1 SEA 82.4–86.2 No overlap Actual: IND 105, SEA 95

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.4) over Seattle Storm (avg. 84.4) — by 6.0 points. The 85% ranges don't overlap at all — a confident model.

IND 88.0–92.8 SEA 82.8–86.2 No overlap Actual: IND 105, SEA 95

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.4) over Seattle Storm (avg. 84.4) — by 6.0 points. The 80% ranges don't overlap at all — a confident model.

IND 88.3–92.6 SEA 83.1–86.0 No overlap Actual: IND 105, SEA 95

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.4) over Seattle Storm (avg. 84.4) — by 6.0 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Wallace (#3)
t-statistic
26.78
p-value
2.73e-68

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
IND 87.1–93.5 SEA 79.7–86.9 No overlap Actual: IND 105, SEA 95

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Seattle Storm (avg. 84.1) — by 6.2 points. The 95% ranges don't overlap at all — a confident model.

IND 87.6–93.0 SEA 80.3–86.5 No overlap Actual: IND 105, SEA 95

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Seattle Storm (avg. 84.1) — by 6.2 points. The 90% ranges don't overlap at all — a confident model.

IND 88.0–92.7 SEA 81.3–86.3 No overlap Actual: IND 105, SEA 95

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Seattle Storm (avg. 84.1) — by 6.2 points. The 85% ranges don't overlap at all — a confident model.

IND 88.2–92.4 SEA 81.7–86.1 No overlap Actual: IND 105, SEA 95

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Seattle Storm (avg. 84.1) — by 6.2 points. The 80% ranges don't overlap at all — a confident model.

IND 88.4–92.2 SEA 82.1–86.0 No overlap Actual: IND 105, SEA 95

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Seattle Storm (avg. 84.1) — by 6.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Kevin (#4)
t-statistic
27.22
p-value
5.78e-68

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
IND 86.4–93.0 SEA 79.1–85.7 No overlap Actual: IND 105, SEA 95

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 89.7) over Seattle Storm (avg. 82.8) — by 6.9 points. The 95% ranges don't overlap at all — a confident model.

IND 87.0–92.4 SEA 79.7–85.3 No overlap Actual: IND 105, SEA 95

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 89.7) over Seattle Storm (avg. 82.8) — by 6.9 points. The 90% ranges don't overlap at all — a confident model.

IND 87.3–92.1 SEA 79.9–84.8 No overlap Actual: IND 105, SEA 95

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 89.7) over Seattle Storm (avg. 82.8) — by 6.9 points. The 85% ranges don't overlap at all — a confident model.

IND 87.6–91.8 SEA 80.0–84.5 No overlap Actual: IND 105, SEA 95

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 89.7) over Seattle Storm (avg. 82.8) — by 6.9 points. The 80% ranges don't overlap at all — a confident model.

IND 87.8–91.6 SEA 80.7–84.3 No overlap Actual: IND 105, SEA 95

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 89.7) over Seattle Storm (avg. 82.8) — by 6.9 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
30.69
p-value
1.13e-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.

Ice
IND 86.8–93.0 SEA 79.4–87.0 Overlap 0.18 pts Actual: IND 105, SEA 95

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.1) — by 5.8 points. The ranges barely touch.

IND 87.3–92.5 SEA 80.6–86.1 No overlap Actual: IND 105, SEA 95

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.1) — by 5.8 points. The 90% ranges don't overlap at all — a confident model.

IND 87.6–92.2 SEA 80.9–86.0 No overlap Actual: IND 105, SEA 95

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.1) — by 5.8 points. The 85% ranges don't overlap at all — a confident model.

IND 87.9–91.9 SEA 81.8–85.8 No overlap Actual: IND 105, SEA 95

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.1) — by 5.8 points. The 80% ranges don't overlap at all — a confident model.

IND 88.1–91.7 SEA 82.4–85.7 No overlap Actual: IND 105, SEA 95

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.1) — by 5.8 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Ice (#6)
t-statistic
26.62
p-value
2.16e-66

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
IND 86.8–92.9 SEA 80.4–87.5 Overlap 0.68 pts Actual: IND 105, SEA 95

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.2) — by 5.7 points. The ranges barely touch.

IND 87.3–92.4 SEA 80.7–87.2 No overlap Actual: IND 105, SEA 95

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.2) — by 5.7 points. The 90% ranges don't overlap at all — a confident model.

IND 87.6–92.1 SEA 81.2–86.3 No overlap Actual: IND 105, SEA 95

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.2) — by 5.7 points. The 85% ranges don't overlap at all — a confident model.

IND 87.9–91.9 SEA 81.9–85.8 No overlap Actual: IND 105, SEA 95

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.2) — by 5.7 points. The 80% ranges don't overlap at all — a confident model.

IND 88.1–91.7 SEA 82.3–85.5 No overlap Actual: IND 105, SEA 95

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.2) — by 5.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jamal (#7)
t-statistic
25.76
p-value
5.19e-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.

Jordan
IND 87.1–92.6 SEA 79.8–87.7 Overlap 0.61 pts Actual: IND 105, SEA 95

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.2) — by 5.8 points. The ranges barely touch.

IND 87.4–92.2 SEA 80.1–87.2 No overlap Actual: IND 105, SEA 95

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.2) — by 5.8 points. The 90% ranges don't overlap at all — a confident model.

IND 88.2–92.0 SEA 81.0–86.7 No overlap Actual: IND 105, SEA 95

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.2) — by 5.8 points. The 85% ranges don't overlap at all — a confident model.

IND 88.6–91.8 SEA 81.6–86.2 No overlap Actual: IND 105, SEA 95

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.2) — by 5.8 points. The 80% ranges don't overlap at all — a confident model.

IND 88.8–91.5 SEA 82.0–86.0 No overlap Actual: IND 105, SEA 95

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.2) — by 5.8 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jordan (#8)
t-statistic
25.00
p-value
3.42e-60

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
IND 87.0–92.9 SEA 80.0–87.7 Overlap 0.73 pts Actual: IND 105, SEA 95

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.3) — by 5.8 points. The ranges barely touch.

IND 87.3–92.6 SEA 81.1–87.1 No overlap Actual: IND 105, SEA 95

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.3) — by 5.8 points. The 90% ranges don't overlap at all — a confident model.

IND 87.8–92.1 SEA 82.0–86.7 No overlap Actual: IND 105, SEA 95

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.3) — by 5.8 points. The 85% ranges don't overlap at all — a confident model.

IND 88.4–91.9 SEA 82.4–86.5 No overlap Actual: IND 105, SEA 95

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.3) — by 5.8 points. The 80% ranges don't overlap at all — a confident model.

IND 88.7–91.6 SEA 82.6–86.4 No overlap Actual: IND 105, SEA 95

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.3) — by 5.8 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
24.62
p-value
6.19e-62

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
IND 86.9–93.4 SEA 80.4–87.6 Overlap 0.71 pts Actual: IND 105, SEA 95

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.2) over Seattle Storm (avg. 84.2) — by 5.9 points. The ranges barely touch.

IND 87.5–92.9 SEA 81.1–87.3 No overlap Actual: IND 105, SEA 95

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.2) over Seattle Storm (avg. 84.2) — by 5.9 points. The 90% ranges don't overlap at all — a confident model.

IND 87.8–92.6 SEA 82.0–86.5 No overlap Actual: IND 105, SEA 95

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.2) over Seattle Storm (avg. 84.2) — by 5.9 points. The 85% ranges don't overlap at all — a confident model.

IND 88.1–92.3 SEA 82.4–86.0 No overlap Actual: IND 105, SEA 95

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.2) over Seattle Storm (avg. 84.2) — by 5.9 points. The 80% ranges don't overlap at all — a confident model.

IND 88.3–92.1 SEA 83.0–85.9 No overlap Actual: IND 105, SEA 95

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.2) over Seattle Storm (avg. 84.2) — by 5.9 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Maya Jefferson (#10)
t-statistic
27.10
p-value
1.45e-68

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
IND 87.3–93.4 SEA 80.0–87.8 Overlap 0.42 pts Actual: IND 105, SEA 95

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.4) — by 5.6 points. The ranges barely touch.

IND 87.5–92.9 SEA 80.6–87.1 No overlap Actual: IND 105, SEA 95

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.4) — by 5.6 points. The 90% ranges don't overlap at all — a confident model.

IND 88.0–92.2 SEA 81.3–86.9 No overlap Actual: IND 105, SEA 95

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.4) — by 5.6 points. The 85% ranges don't overlap at all — a confident model.

IND 88.1–91.8 SEA 82.1–86.6 No overlap Actual: IND 105, SEA 95

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.4) — by 5.6 points. The 80% ranges don't overlap at all — a confident model.

IND 88.3–91.5 SEA 82.4–86.3 No overlap Actual: IND 105, SEA 95

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Seattle Storm (avg. 84.4) — by 5.6 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Lexi (#11)
t-statistic
22.88
p-value
3.48e-57

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
IND 86.4–93.4 SEA 81.1–87.3 Overlap 0.9 pts Actual: IND 105, SEA 95

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.3) — by 5.6 points. The ranges barely touch.

IND 87.0–92.9 SEA 81.7–86.8 No overlap Actual: IND 105, SEA 95

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.3) — by 5.6 points. The 90% ranges don't overlap at all — a confident model.

IND 87.4–92.5 SEA 82.1–86.2 No overlap Actual: IND 105, SEA 95

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.3) — by 5.6 points. The 85% ranges don't overlap at all — a confident model.

IND 87.6–92.2 SEA 82.4–86.0 No overlap Actual: IND 105, SEA 95

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.3) — by 5.6 points. The 80% ranges don't overlap at all — a confident model.

IND 87.9–92.0 SEA 82.9–85.7 No overlap Actual: IND 105, SEA 95

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Seattle Storm (avg. 84.3) — 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
26.08
p-value
1.58e-66

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 — IND at SEA — Actual: IND 105, SEA 95
Level IND range SEA range Overlap Tol Warning Actual landed in range?
95% 88.0–93.3 82.6–88.5 0.47 pts — No
90% 88.4–92.9 82.8–87.9 — pts — No
85% 88.7–92.6 83.0–87.0 — pts — No
80% 88.9–92.4 83.2–86.6 — pts — No
75% 89.1–92.2 83.4–86.4 — pts — No
Reg — IND at SEA — Actual: IND 105, SEA 95
Level IND range SEA range Overlap Tol Warning Actual landed in range?
95% 87.7–93.1 82.5–87.6 — pts — No
90% 88.6–92.9 83.2–87.0 — pts — No
85% 88.8–92.8 83.4–86.8 — pts — No
80% 89.2–92.4 83.5–86.6 — pts — No
75% 89.3–92.3 83.5–86.5 — pts — No
Dr. Wallace — IND at SEA — Actual: IND 105, SEA 95
Level IND range SEA range Overlap Tol Warning Actual landed in range?
95% 86.7–94.1 80.6–87.2 0.48 pts — No
90% 87.3–93.5 81.5–86.6 — pts — No
85% 87.7–93.1 82.4–86.2 — pts — No
80% 88.0–92.8 82.8–86.2 — pts — No
75% 88.3–92.6 83.1–86.0 — pts — No
Kevin — IND at SEA — Actual: IND 105, SEA 95
Level IND range SEA range Overlap Tol Warning Actual landed in range?
95% 87.1–93.5 79.7–86.9 — pts — No
90% 87.6–93.0 80.3–86.5 — pts — No
85% 88.0–92.7 81.3–86.3 — pts — No
80% 88.2–92.4 81.7–86.1 — pts — No
75% 88.4–92.2 82.1–86.0 — pts — No
Dr. Lila Shah — IND at SEA — Actual: IND 105, SEA 95
Level IND range SEA range Overlap Tol Warning Actual landed in range?
95% 86.4–93.0 79.1–85.7 — pts — No
90% 87.0–92.4 79.7–85.3 — pts — No
85% 87.3–92.1 79.9–84.8 — pts — No
80% 87.6–91.8 80.0–84.5 — pts — No
75% 87.8–91.6 80.7–84.3 — pts — No
Ice — IND at SEA — Actual: IND 105, SEA 95
Level IND range SEA range Overlap Tol Warning Actual landed in range?
95% 86.8–93.0 79.4–87.0 0.18 pts — No
90% 87.3–92.5 80.6–86.1 — pts — No
85% 87.6–92.2 80.9–86.0 — pts — No
80% 87.9–91.9 81.8–85.8 — pts — No
75% 88.1–91.7 82.4–85.7 — pts — No
Jamal — IND at SEA — Actual: IND 105, SEA 95
Level IND range SEA range Overlap Tol Warning Actual landed in range?
95% 86.8–92.9 80.4–87.5 0.68 pts — No
90% 87.3–92.4 80.7–87.2 — pts — No
85% 87.6–92.1 81.2–86.3 — pts — No
80% 87.9–91.9 81.9–85.8 — pts — No
75% 88.1–91.7 82.3–85.5 — pts — No
Jordan — IND at SEA — Actual: IND 105, SEA 95
Level IND range SEA range Overlap Tol Warning Actual landed in range?
95% 87.1–92.6 79.8–87.7 0.61 pts — No
90% 87.4–92.2 80.1–87.2 — pts — No
85% 88.2–92.0 81.0–86.7 — pts — No
80% 88.6–91.8 81.6–86.2 — pts — No
75% 88.8–91.5 82.0–86.0 — pts — No
Darren "Dimes" Lin — IND at SEA — Actual: IND 105, SEA 95
Level IND range SEA range Overlap Tol Warning Actual landed in range?
95% 87.0–92.9 80.0–87.7 0.73 pts — No
90% 87.3–92.6 81.1–87.1 — pts — No
85% 87.8–92.1 82.0–86.7 — pts — No
80% 88.4–91.9 82.4–86.5 — pts — No
75% 88.7–91.6 82.6–86.4 — pts — No
Maya Jefferson — IND at SEA — Actual: IND 105, SEA 95
Level IND range SEA range Overlap Tol Warning Actual landed in range?
95% 86.9–93.4 80.4–87.6 0.71 pts — No
90% 87.5–92.9 81.1–87.3 — pts — No
85% 87.8–92.6 82.0–86.5 — pts — No
80% 88.1–92.3 82.4–86.0 — pts — No
75% 88.3–92.1 83.0–85.9 — pts — No
Lexi — IND at SEA — Actual: IND 105, SEA 95
Level IND range SEA range Overlap Tol Warning Actual landed in range?
95% 87.3–93.4 80.0–87.8 0.42 pts — No
90% 87.5–92.9 80.6–87.1 — pts — No
85% 88.0–92.2 81.3–86.9 — pts — No
80% 88.1–91.8 82.1–86.6 — pts — No
75% 88.3–91.5 82.4–86.3 — pts — No
Coach Sarah Watanabe — IND at SEA — Actual: IND 105, SEA 95
Level IND range SEA range Overlap Tol Warning Actual landed in range?
95% 86.4–93.4 81.1–87.3 0.9 pts — No
90% 87.0–92.9 81.7–86.8 — pts — No
85% 87.4–92.5 82.1–86.2 — pts — No
80% 87.6–92.2 82.4–86.0 — pts — No
75% 87.9–92.0 82.9–85.7 — pts — No