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Connecticut Sun at Indiana Fever

CON 88 – IND 123

July 22, 2026 · Final

Coach Sarah Watanabe

Best model for this game

Coach Sarah Watanabe
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 CON at IND

All 12 models’ predicted scores

CON — one dot per model IND — one dot per model Actual: CON 88, IND 123
Vince Chambers
CON 80.6–84.7 IND 87.9–92.8 No overlap Actual: CON 88, IND 123

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Connecticut Sun (avg. 82.6) — by 7.7 points. The 95% ranges don't overlap at all — a confident model.

CON 81.0–84.3 IND 88.3–92.4 No overlap Actual: CON 88, IND 123

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Connecticut Sun (avg. 82.6) — by 7.7 points. The 90% ranges don't overlap at all — a confident model.

CON 81.2–84.1 IND 88.6–92.1 No overlap Actual: CON 88, IND 123

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Connecticut Sun (avg. 82.6) — by 7.7 points. The 85% ranges don't overlap at all — a confident model.

CON 81.3–84.0 IND 88.8–91.9 No overlap Actual: CON 88, IND 123

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Connecticut Sun (avg. 82.6) — by 7.7 points. The 80% ranges don't overlap at all — a confident model.

CON 81.5–83.8 IND 88.9–91.8 No overlap Actual: CON 88, IND 123

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Connecticut Sun (avg. 82.6) — by 7.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Vince Chambers (#1)
t-statistic
-54.05
p-value
3.12e-116

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
CON 80.2–85.1 IND 87.5–93.3 No overlap Actual: CON 88, IND 123

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Connecticut Sun (avg. 82.8) — by 7.6 points. The 95% ranges don't overlap at all — a confident model.

CON 81.2–84.7 IND 88.1–92.8 No overlap Actual: CON 88, IND 123

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Connecticut Sun (avg. 82.8) — by 7.6 points. The 90% ranges don't overlap at all — a confident model.

CON 81.4–84.5 IND 88.6–92.5 No overlap Actual: CON 88, IND 123

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Connecticut Sun (avg. 82.8) — by 7.6 points. The 85% ranges don't overlap at all — a confident model.

CON 81.5–84.4 IND 88.6–92.1 No overlap Actual: CON 88, IND 123

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Connecticut Sun (avg. 82.8) — by 7.6 points. The 80% ranges don't overlap at all — a confident model.

CON 81.7–84.2 IND 88.9–91.9 No overlap Actual: CON 88, IND 123

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Connecticut Sun (avg. 82.8) — by 7.6 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Reg (#2)
t-statistic
-37.48
p-value
2.96e-90

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
CON 79.3–84.5 IND 88.2–93.6 No overlap Actual: CON 88, IND 123

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Connecticut Sun (avg. 82.5) — by 7.8 points. The 95% ranges don't overlap at all — a confident model.

CON 80.0–84.2 IND 88.5–92.3 No overlap Actual: CON 88, IND 123

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Connecticut Sun (avg. 82.5) — by 7.8 points. The 90% ranges don't overlap at all — a confident model.

CON 80.8–84.0 IND 88.6–92.0 No overlap Actual: CON 88, IND 123

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Connecticut Sun (avg. 82.5) — by 7.8 points. The 85% ranges don't overlap at all — a confident model.

CON 81.0–83.8 IND 88.8–91.6 No overlap Actual: CON 88, IND 123

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Connecticut Sun (avg. 82.5) — by 7.8 points. The 80% ranges don't overlap at all — a confident model.

CON 81.3–83.7 IND 89.1–91.4 No overlap Actual: CON 88, IND 123

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.3) over Connecticut Sun (avg. 82.5) — by 7.8 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Wallace (#3)
t-statistic
-41.67
p-value
2.83e-98

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
CON 80.1–85.2 IND 88.2–92.8 No overlap Actual: CON 88, IND 123

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.4) over Connecticut Sun (avg. 82.6) — by 7.7 points. The 95% ranges don't overlap at all — a confident model.

CON 80.5–84.8 IND 88.6–92.3 No overlap Actual: CON 88, IND 123

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.4) over Connecticut Sun (avg. 82.6) — by 7.7 points. The 90% ranges don't overlap at all — a confident model.

CON 80.8–84.5 IND 88.8–91.9 No overlap Actual: CON 88, IND 123

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.4) over Connecticut Sun (avg. 82.6) — by 7.7 points. The 85% ranges don't overlap at all — a confident model.

CON 81.0–84.3 IND 89.1–91.8 No overlap Actual: CON 88, IND 123

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.4) over Connecticut Sun (avg. 82.6) — by 7.7 points. The 80% ranges don't overlap at all — a confident model.

CON 81.1–84.1 IND 89.2–91.6 No overlap Actual: CON 88, IND 123

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.4) over Connecticut Sun (avg. 82.6) — by 7.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Kevin (#4)
t-statistic
-45.58
p-value
4.03e-105

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
CON 79.6–83.6 IND 86.8–92.0 No overlap Actual: CON 88, IND 123

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 89.4) over Connecticut Sun (avg. 82.0) — by 7.4 points. The 95% ranges don't overlap at all — a confident model.

CON 80.4–83.3 IND 87.2–91.6 No overlap Actual: CON 88, IND 123

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 89.4) over Connecticut Sun (avg. 82.0) — by 7.4 points. The 90% ranges don't overlap at all — a confident model.

CON 80.5–83.3 IND 87.5–91.3 No overlap Actual: CON 88, IND 123

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 89.4) over Connecticut Sun (avg. 82.0) — by 7.4 points. The 85% ranges don't overlap at all — a confident model.

CON 80.9–83.2 IND 87.7–91.1 No overlap Actual: CON 88, IND 123

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 89.4) over Connecticut Sun (avg. 82.0) — by 7.4 points. The 80% ranges don't overlap at all — a confident model.

CON 81.1–83.2 IND 87.9–91.0 No overlap Actual: CON 88, IND 123

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 89.4) over Connecticut Sun (avg. 82.0) — by 7.4 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
-46.42
p-value
2.24e-106

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
CON 80.8–84.3 IND 86.4–92.1 No overlap Actual: CON 88, IND 123

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 89.8) over Connecticut Sun (avg. 82.7) — by 7.1 points. The 95% ranges don't overlap at all — a confident model.

CON 81.4–84.0 IND 87.2–91.9 No overlap Actual: CON 88, IND 123

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 89.8) over Connecticut Sun (avg. 82.7) — by 7.1 points. The 90% ranges don't overlap at all — a confident model.

CON 81.5–83.9 IND 87.8–91.6 No overlap Actual: CON 88, IND 123

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 89.8) over Connecticut Sun (avg. 82.7) — by 7.1 points. The 85% ranges don't overlap at all — a confident model.

CON 81.7–83.8 IND 88.0–91.3 No overlap Actual: CON 88, IND 123

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 89.8) over Connecticut Sun (avg. 82.7) — by 7.1 points. The 80% ranges don't overlap at all — a confident model.

CON 81.7–83.8 IND 88.4–91.1 No overlap Actual: CON 88, IND 123

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 89.8) over Connecticut Sun (avg. 82.7) — by 7.1 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Ice (#6)
t-statistic
-40.92
p-value
3.57e-90

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
CON 80.0–85.2 IND 86.9–93.0 No overlap Actual: CON 88, IND 123

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.6) — by 7.3 points. The 95% ranges don't overlap at all — a confident model.

CON 80.4–84.8 IND 87.4–92.5 No overlap Actual: CON 88, IND 123

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.6) — by 7.3 points. The 90% ranges don't overlap at all — a confident model.

CON 80.7–84.5 IND 87.7–92.2 No overlap Actual: CON 88, IND 123

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.6) — by 7.3 points. The 85% ranges don't overlap at all — a confident model.

CON 80.9–84.3 IND 88.0–92.0 No overlap Actual: CON 88, IND 123

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.6) — by 7.3 points. The 80% ranges don't overlap at all — a confident model.

CON 81.1–84.1 IND 88.2–91.7 No overlap Actual: CON 88, IND 123

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.6) — by 7.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jamal (#7)
t-statistic
-40.50
p-value
3.27e-95

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
CON 80.6–84.8 IND 86.5–93.2 No overlap Actual: CON 88, IND 123

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Connecticut Sun (avg. 82.7) — by 7.2 points. The 95% ranges don't overlap at all — a confident model.

CON 80.9–84.4 IND 87.0–92.7 No overlap Actual: CON 88, IND 123

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Connecticut Sun (avg. 82.7) — by 7.2 points. The 90% ranges don't overlap at all — a confident model.

CON 81.1–84.2 IND 87.4–92.3 No overlap Actual: CON 88, IND 123

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Connecticut Sun (avg. 82.7) — by 7.2 points. The 85% ranges don't overlap at all — a confident model.

CON 81.3–84.0 IND 87.7–92.1 No overlap Actual: CON 88, IND 123

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Connecticut Sun (avg. 82.7) — by 7.2 points. The 80% ranges don't overlap at all — a confident model.

CON 81.4–83.9 IND 87.9–91.9 No overlap Actual: CON 88, IND 123

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 89.9) over Connecticut Sun (avg. 82.7) — by 7.2 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jordan (#8)
t-statistic
-40.05
p-value
3.49e-86

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
CON 80.0–85.0 IND 86.9–93.0 No overlap Actual: CON 88, IND 123

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.5) — by 7.5 points. The 95% ranges don't overlap at all — a confident model.

CON 80.4–84.6 IND 87.4–92.5 No overlap Actual: CON 88, IND 123

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.5) — by 7.5 points. The 90% ranges don't overlap at all — a confident model.

CON 80.6–84.3 IND 87.7–92.2 No overlap Actual: CON 88, IND 123

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.5) — by 7.5 points. The 85% ranges don't overlap at all — a confident model.

CON 80.8–84.1 IND 88.0–92.0 No overlap Actual: CON 88, IND 123

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.5) — by 7.5 points. The 80% ranges don't overlap at all — a confident model.

CON 81.0–83.9 IND 88.2–91.7 No overlap Actual: CON 88, IND 123

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.5) — by 7.5 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
-42.09
p-value
3.35e-97

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
CON 80.0–84.0 IND 87.2–92.7 No overlap Actual: CON 88, IND 123

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.4) — by 7.6 points. The 95% ranges don't overlap at all — a confident model.

CON 80.6–83.9 IND 87.7–92.3 No overlap Actual: CON 88, IND 123

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.4) — by 7.6 points. The 90% ranges don't overlap at all — a confident model.

CON 80.8–83.8 IND 87.9–92.0 No overlap Actual: CON 88, IND 123

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.4) — by 7.6 points. The 85% ranges don't overlap at all — a confident model.

CON 81.0–83.7 IND 88.2–91.8 No overlap Actual: CON 88, IND 123

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.4) — by 7.6 points. The 80% ranges don't overlap at all — a confident model.

CON 81.2–83.7 IND 88.4–91.6 No overlap Actual: CON 88, IND 123

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.4) — by 7.6 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Maya Jefferson (#10)
t-statistic
-46.51
p-value
2.15e-105

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
CON 79.0–84.5 IND 87.5–93.4 No overlap Actual: CON 88, IND 123

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.4) — by 7.7 points. The 95% ranges don't overlap at all — a confident model.

CON 80.1–84.0 IND 87.8–92.4 No overlap Actual: CON 88, IND 123

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.4) — by 7.7 points. The 90% ranges don't overlap at all — a confident model.

CON 80.6–83.9 IND 88.0–92.1 No overlap Actual: CON 88, IND 123

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.4) — by 7.7 points. The 85% ranges don't overlap at all — a confident model.

CON 80.8–83.8 IND 88.1–91.9 No overlap Actual: CON 88, IND 123

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.4) — by 7.7 points. The 80% ranges don't overlap at all — a confident model.

CON 80.9–83.7 IND 88.4–91.6 No overlap Actual: CON 88, IND 123

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.0) over Connecticut Sun (avg. 82.4) — by 7.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Lexi (#11)
t-statistic
-37.52
p-value
1.96e-90

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
CON 79.4–85.0 IND 87.9–93.1 No overlap Actual: CON 88, IND 123

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Connecticut Sun (avg. 82.2) — by 8.3 points. The 95% ranges don't overlap at all — a confident model.

CON 79.8–84.6 IND 87.9–92.8 No overlap Actual: CON 88, IND 123

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Connecticut Sun (avg. 82.2) — by 8.3 points. The 90% ranges don't overlap at all — a confident model.

CON 80.1–84.3 IND 88.3–92.5 No overlap Actual: CON 88, IND 123

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Connecticut Sun (avg. 82.2) — by 8.3 points. The 85% ranges don't overlap at all — a confident model.

CON 80.4–84.1 IND 88.6–91.9 No overlap Actual: CON 88, IND 123

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Connecticut Sun (avg. 82.2) — by 8.3 points. The 80% ranges don't overlap at all — a confident model.

CON 80.6–83.9 IND 89.0–91.8 No overlap Actual: CON 88, IND 123

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Connecticut Sun (avg. 82.2) — by 8.3 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Coach Sarah Watanabe (#12)
t-statistic
-42.24
p-value
3.80e-98

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 — CON at IND — Actual: CON 88, IND 123
Level CON range IND range Overlap Tol Warning Actual landed in range?
95% 80.6–84.7 87.9–92.8 — pts — No
90% 81.0–84.3 88.3–92.4 — pts — No
85% 81.2–84.1 88.6–92.1 — pts — No
80% 81.3–84.0 88.8–91.9 — pts — No
75% 81.5–83.8 88.9–91.8 — pts — No
Reg — CON at IND — Actual: CON 88, IND 123
Level CON range IND range Overlap Tol Warning Actual landed in range?
95% 80.2–85.1 87.5–93.3 — pts — No
90% 81.2–84.7 88.1–92.8 — pts — No
85% 81.4–84.5 88.6–92.5 — pts — No
80% 81.5–84.4 88.6–92.1 — pts — No
75% 81.7–84.2 88.9–91.9 — pts — No
Dr. Wallace — CON at IND — Actual: CON 88, IND 123
Level CON range IND range Overlap Tol Warning Actual landed in range?
95% 79.3–84.5 88.2–93.6 — pts — No
90% 80.0–84.2 88.5–92.3 — pts — No
85% 80.8–84.0 88.6–92.0 — pts — No
80% 81.0–83.8 88.8–91.6 — pts — No
75% 81.3–83.7 89.1–91.4 — pts — No
Kevin — CON at IND — Actual: CON 88, IND 123
Level CON range IND range Overlap Tol Warning Actual landed in range?
95% 80.1–85.2 88.2–92.8 — pts — No
90% 80.5–84.8 88.6–92.3 — pts — No
85% 80.8–84.5 88.8–91.9 — pts — No
80% 81.0–84.3 89.1–91.8 — pts — No
75% 81.1–84.1 89.2–91.6 — pts — No
Dr. Lila Shah — CON at IND — Actual: CON 88, IND 123
Level CON range IND range Overlap Tol Warning Actual landed in range?
95% 79.6–83.6 86.8–92.0 — pts — No
90% 80.4–83.3 87.2–91.6 — pts — No
85% 80.5–83.3 87.5–91.3 — pts — No
80% 80.9–83.2 87.7–91.1 — pts — No
75% 81.1–83.2 87.9–91.0 — pts — No
Ice — CON at IND — Actual: CON 88, IND 123
Level CON range IND range Overlap Tol Warning Actual landed in range?
95% 80.8–84.3 86.4–92.1 — pts — No
90% 81.4–84.0 87.2–91.9 — pts — No
85% 81.5–83.9 87.8–91.6 — pts — No
80% 81.7–83.8 88.0–91.3 — pts — No
75% 81.7–83.8 88.4–91.1 — pts — No
Jamal — CON at IND — Actual: CON 88, IND 123
Level CON range IND range Overlap Tol Warning Actual landed in range?
95% 80.0–85.2 86.9–93.0 — pts — No
90% 80.4–84.8 87.4–92.5 — pts — No
85% 80.7–84.5 87.7–92.2 — pts — No
80% 80.9–84.3 88.0–92.0 — pts — No
75% 81.1–84.1 88.2–91.7 — pts — No
Jordan — CON at IND — Actual: CON 88, IND 123
Level CON range IND range Overlap Tol Warning Actual landed in range?
95% 80.6–84.8 86.5–93.2 — pts — No
90% 80.9–84.4 87.0–92.7 — pts — No
85% 81.1–84.2 87.4–92.3 — pts — No
80% 81.3–84.0 87.7–92.1 — pts — No
75% 81.4–83.9 87.9–91.9 — pts — No
Darren "Dimes" Lin — CON at IND — Actual: CON 88, IND 123
Level CON range IND range Overlap Tol Warning Actual landed in range?
95% 80.0–85.0 86.9–93.0 — pts — No
90% 80.4–84.6 87.4–92.5 — pts — No
85% 80.6–84.3 87.7–92.2 — pts — No
80% 80.8–84.1 88.0–92.0 — pts — No
75% 81.0–83.9 88.2–91.7 — pts — No
Maya Jefferson — CON at IND — Actual: CON 88, IND 123
Level CON range IND range Overlap Tol Warning Actual landed in range?
95% 80.0–84.0 87.2–92.7 — pts — No
90% 80.6–83.9 87.7–92.3 — pts — No
85% 80.8–83.8 87.9–92.0 — pts — No
80% 81.0–83.7 88.2–91.8 — pts — No
75% 81.2–83.7 88.4–91.6 — pts — No
Lexi — CON at IND — Actual: CON 88, IND 123
Level CON range IND range Overlap Tol Warning Actual landed in range?
95% 79.0–84.5 87.5–93.4 — pts — No
90% 80.1–84.0 87.8–92.4 — pts — No
85% 80.6–83.9 88.0–92.1 — pts — No
80% 80.8–83.8 88.1–91.9 — pts — No
75% 80.9–83.7 88.4–91.6 — pts — No
Coach Sarah Watanabe — CON at IND — Actual: CON 88, IND 123
Level CON range IND range Overlap Tol Warning Actual landed in range?
95% 79.4–85.0 87.9–93.1 — pts — No
90% 79.8–84.6 87.9–92.8 — pts — No
85% 80.1–84.3 88.3–92.5 — pts — No
80% 80.4–84.1 88.6–91.9 — pts — No
75% 80.6–83.9 89.0–91.8 — pts — No