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Indiana Fever at Toronto Tempo

IND 103 – TOR 85

September 18, 2026 · Final

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 TOR

All 10 models’ predicted scores

IND — one dot per model TOR — one dot per model Actual: IND 103, TOR 85
Vince Chambers Tol Warning
IND 90.4–94.9 TOR 77.2–88.9 No overlap Actual: IND 103, TOR 85

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 92.0) over Toronto Tempo (avg. 83.1) — by 8.9 points. The 95% ranges don't overlap at all — a confident model.

IND 90.4–94.8 TOR 78.1–88.0 No overlap Actual: IND 103, TOR 85

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 92.0) over Toronto Tempo (avg. 83.1) — by 8.9 points. The 90% ranges don't overlap at all — a confident model.

IND 90.5–94.8 TOR 78.7–87.4 No overlap Actual: IND 103, TOR 85

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 92.0) over Toronto Tempo (avg. 83.1) — by 8.9 points. The 85% ranges don't overlap at all — a confident model.

IND 90.5–94.8 TOR 79.2–86.9 No overlap Actual: IND 103, TOR 85

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 92.0) over Toronto Tempo (avg. 83.1) — by 8.9 points. The 80% ranges don't overlap at all — a confident model.

IND 90.5–94.7 TOR 79.6–86.5 No overlap Actual: IND 103, TOR 85

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 92.0) over Toronto Tempo (avg. 83.1) — by 8.9 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Vince Chambers (#1)
t-statistic
11.10
p-value
6.53e-09

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 Tol Warning
IND 87.1–96.2 TOR 78.8–89.1 Overlap 1.98 pts Actual: IND 103, TOR 85

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 91.7) over Toronto Tempo (avg. 84.0) — by 7.7 points. The ranges overlap some — there's real uncertainty here.

IND 87.8–95.5 TOR 79.6–88.3 Overlap 0.45 pts Actual: IND 103, TOR 85

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 91.7) over Toronto Tempo (avg. 84.0) — by 7.7 points. The ranges barely touch.

IND 88.3–95.0 TOR 80.2–87.7 No overlap Actual: IND 103, TOR 85

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 91.7) over Toronto Tempo (avg. 84.0) — by 7.7 points. The 85% ranges don't overlap at all — a confident model.

IND 88.7–94.7 TOR 80.6–87.3 No overlap Actual: IND 103, TOR 85

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 91.7) over Toronto Tempo (avg. 84.0) — by 7.7 points. The 80% ranges don't overlap at all — a confident model.

IND 89.0–94.4 TOR 80.9–87.0 No overlap Actual: IND 103, TOR 85

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 91.7) over Toronto Tempo (avg. 84.0) — by 7.7 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Reg (#2)
t-statistic
11.95
p-value
2.56e-09

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 Tol Warning
IND 85.9–97.5 TOR 80.3–87.1 Overlap 1.16 pts Actual: IND 103, TOR 85

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 91.7) over Toronto Tempo (avg. 83.7) — by 8.0 points. The ranges overlap some — there's real uncertainty here.

IND 86.8–96.6 TOR 80.9–86.5 No overlap Actual: IND 103, TOR 85

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 91.7) over Toronto Tempo (avg. 83.7) — by 8.0 points. The 90% ranges don't overlap at all — a confident model.

IND 87.4–96.0 TOR 81.2–86.2 No overlap Actual: IND 103, TOR 85

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 91.7) over Toronto Tempo (avg. 83.7) — by 8.0 points. The 85% ranges don't overlap at all — a confident model.

IND 87.9–95.5 TOR 81.5–85.9 No overlap Actual: IND 103, TOR 85

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 91.7) over Toronto Tempo (avg. 83.7) — by 8.0 points. The 80% ranges don't overlap at all — a confident model.

IND 88.3–95.1 TOR 81.7–85.7 No overlap Actual: IND 103, TOR 85

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 91.7) over Toronto Tempo (avg. 83.7) — by 8.0 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Wallace (#3)
t-statistic
12.71
p-value
1.16e-08

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 Tol Warning
IND 86.2–95.7 TOR 80.2–85.9 No overlap Actual: IND 103, TOR 85

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 91.0) over Toronto Tempo (avg. 83.0) — by 8.0 points. The 95% ranges don't overlap at all — a confident model.

IND 86.9–95.0 TOR 80.6–85.4 No overlap Actual: IND 103, TOR 85

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 91.0) over Toronto Tempo (avg. 83.0) — by 8.0 points. The 90% ranges don't overlap at all — a confident model.

IND 87.4–94.5 TOR 80.9–85.1 No overlap Actual: IND 103, TOR 85

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 91.0) over Toronto Tempo (avg. 83.0) — by 8.0 points. The 85% ranges don't overlap at all — a confident model.

IND 87.8–94.1 TOR 81.1–84.9 No overlap Actual: IND 103, TOR 85

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 91.0) over Toronto Tempo (avg. 83.0) — by 8.0 points. The 80% ranges don't overlap at all — a confident model.

IND 88.1–93.8 TOR 81.3–84.7 No overlap Actual: IND 103, TOR 85

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 91.0) over Toronto Tempo (avg. 83.0) — by 8.0 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Kevin (#4)
t-statistic
15.20
p-value
1.11e-09

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 Tol Warning
IND 85.5–96.0 TOR 79.5–84.7 No overlap Actual: IND 103, TOR 85

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.7) over Toronto Tempo (avg. 82.1) — by 8.6 points. The 95% ranges don't overlap at all — a confident model.

IND 86.3–95.1 TOR 79.9–84.3 No overlap Actual: IND 103, TOR 85

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.7) over Toronto Tempo (avg. 82.1) — by 8.6 points. The 90% ranges don't overlap at all — a confident model.

IND 86.8–94.6 TOR 80.2–84.0 No overlap Actual: IND 103, TOR 85

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.7) over Toronto Tempo (avg. 82.1) — by 8.6 points. The 85% ranges don't overlap at all — a confident model.

IND 87.3–94.2 TOR 80.4–83.8 No overlap Actual: IND 103, TOR 85

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.7) over Toronto Tempo (avg. 82.1) — by 8.6 points. The 80% ranges don't overlap at all — a confident model.

IND 87.6–93.8 TOR 80.6–83.6 No overlap Actual: IND 103, TOR 85

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.7) over Toronto Tempo (avg. 82.1) — by 8.6 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Dr. Lila Shah (#5)
t-statistic
15.69
p-value
3.44e-09

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 Tol Warning
IND 88.3–92.7 TOR 78.6–87.3 No overlap Actual: IND 103, TOR 85

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Toronto Tempo (avg. 83.0) — by 7.6 points. The 95% ranges don't overlap at all — a confident model.

IND 88.6–92.4 TOR 79.3–86.6 No overlap Actual: IND 103, TOR 85

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Toronto Tempo (avg. 83.0) — by 7.6 points. The 90% ranges don't overlap at all — a confident model.

IND 88.9–92.2 TOR 79.7–86.2 No overlap Actual: IND 103, TOR 85

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Toronto Tempo (avg. 83.0) — by 7.6 points. The 85% ranges don't overlap at all — a confident model.

IND 89.0–92.0 TOR 80.1–85.8 No overlap Actual: IND 103, TOR 85

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Toronto Tempo (avg. 83.0) — by 7.6 points. The 80% ranges don't overlap at all — a confident model.

IND 89.2–91.8 TOR 80.4–85.5 No overlap Actual: IND 103, TOR 85

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.5) over Toronto Tempo (avg. 83.0) — by 7.6 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Ice (#6)
t-statistic
16.47
p-value
1.38e-09

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 Tol Warning
IND 86.2–94.0 TOR 79.5–85.9 No overlap Actual: IND 103, TOR 85

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 90.1) over Toronto Tempo (avg. 82.7) — by 7.4 points. The 95% ranges don't overlap at all — a confident model.

IND 86.8–93.4 TOR 80.0–85.4 No overlap Actual: IND 103, TOR 85

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 90.1) over Toronto Tempo (avg. 82.7) — by 7.4 points. The 90% ranges don't overlap at all — a confident model.

IND 87.2–93.0 TOR 80.4–85.1 No overlap Actual: IND 103, TOR 85

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 90.1) over Toronto Tempo (avg. 82.7) — by 7.4 points. The 85% ranges don't overlap at all — a confident model.

IND 87.5–92.7 TOR 80.6–84.8 No overlap Actual: IND 103, TOR 85

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 90.1) over Toronto Tempo (avg. 82.7) — by 7.4 points. The 80% ranges don't overlap at all — a confident model.

IND 87.8–92.4 TOR 80.8–84.6 No overlap Actual: IND 103, TOR 85

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 90.1) over Toronto Tempo (avg. 82.7) — by 7.4 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jamal (#7)
t-statistic
15.45
p-value
9.09e-11

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 Tol Warning
IND 87.2–95.5 TOR 81.5–84.2 No overlap Actual: IND 103, TOR 85

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 91.4) over Toronto Tempo (avg. 83.4) — by 8.0 points. The 95% ranges don't overlap at all — a confident model.

IND 87.9–94.9 TOR 81.8–84.2 No overlap Actual: IND 103, TOR 85

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 91.4) over Toronto Tempo (avg. 83.4) — by 8.0 points. The 90% ranges don't overlap at all — a confident model.

IND 88.3–94.4 TOR 82.1–84.2 No overlap Actual: IND 103, TOR 85

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 91.4) over Toronto Tempo (avg. 83.4) — by 8.0 points. The 85% ranges don't overlap at all — a confident model.

IND 88.6–94.1 TOR 82.3–84.2 No overlap Actual: IND 103, TOR 85

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 91.4) over Toronto Tempo (avg. 83.4) — by 8.0 points. The 80% ranges don't overlap at all — a confident model.

IND 88.9–93.8 TOR 82.6–84.2 No overlap Actual: IND 103, TOR 85

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 91.4) over Toronto Tempo (avg. 83.4) — by 8.0 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Jordan (#8)
t-statistic
15.43
p-value
6.79e-11

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 Tol Warning
IND 81.9–101.0 TOR 77.9–86.9 Overlap 5.01 pts Actual: IND 103, TOR 85

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 91.5) over Toronto Tempo (avg. 82.4) — by 9.1 points. The ranges overlap almost entirely, so one game could go either way.

IND 83.4–99.6 TOR 78.6–86.2 Overlap 2.81 pts Actual: IND 103, TOR 85

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 91.5) over Toronto Tempo (avg. 82.4) — by 9.1 points. The ranges overlap some — there's real uncertainty here.

IND 84.4–98.6 TOR 79.1–85.8 Overlap 1.37 pts Actual: IND 103, TOR 85

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 91.5) over Toronto Tempo (avg. 82.4) — by 9.1 points. The ranges overlap some — there's real uncertainty here.

IND 85.2–97.8 TOR 79.4–85.4 Overlap 0.26 pts Actual: IND 103, TOR 85

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 91.5) over Toronto Tempo (avg. 82.4) — by 9.1 points. The ranges barely touch.

IND 85.8–97.2 TOR 79.7–85.1 No overlap Actual: IND 103, TOR 85

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 91.5) over Toronto Tempo (avg. 82.4) — by 9.1 points. The 75% ranges don't overlap at all — a confident model.

Show the math
Model
Darren "Dimes" Lin (#9)
t-statistic
9.29
p-value
3.09e-05

A low p-value means the two teams' average scores are statistically distinguishable — even when their ranges above overlap. Overlap describes where the final score could land; the test above is about whether the two averages differ. They are different claims, and either can hold without the other.

Maya Jefferson Tol Warning
IND 85.8–97.3 TOR 72.9–94.9 Overlap 9.09 pts Actual: IND 103, TOR 85

In 95 out of 100 simulated runs, leans Indiana Fever (avg. 91.6) over Toronto Tempo (avg. 83.9) — by 7.7 points. The ranges overlap almost entirely, so one game could go either way.

IND 86.7–96.4 TOR 74.6–93.2 Overlap 6.5 pts Actual: IND 103, TOR 85

In 90 out of 100 simulated runs, leans Indiana Fever (avg. 91.6) over Toronto Tempo (avg. 83.9) — by 7.7 points. The ranges overlap almost entirely, so one game could go either way.

IND 87.3–95.8 TOR 75.7–92.1 Overlap 4.8 pts Actual: IND 103, TOR 85

In 85 out of 100 simulated runs, leans Indiana Fever (avg. 91.6) over Toronto Tempo (avg. 83.9) — by 7.7 points. The ranges overlap almost entirely, so one game could go either way.

IND 87.7–95.4 TOR 76.6–91.2 Overlap 3.48 pts Actual: IND 103, TOR 85

In 80 out of 100 simulated runs, leans Indiana Fever (avg. 91.6) over Toronto Tempo (avg. 83.9) — by 7.7 points. The ranges overlap almost entirely, so one game could go either way.

IND 88.1–95.0 TOR 77.3–90.5 Overlap 2.38 pts Actual: IND 103, TOR 85

In 75 out of 100 simulated runs, leans Indiana Fever (avg. 91.6) over Toronto Tempo (avg. 83.9) — by 7.7 points. The ranges overlap some — there's real uncertainty here.

Show the math
Model
Maya Jefferson (#10)
t-statistic
7.01
p-value
4.10e-04

A low p-value means the two teams' average scores are statistically distinguishable — even when their ranges above overlap. Overlap describes where the final score could land; the test above is about whether the two averages differ. They are different claims, and either can hold without the other.

View as table
Vince Chambers — IND at TOR — Actual: IND 103, TOR 85
Level IND range TOR range Overlap Tol Warning Actual landed in range?
95% 90.4–94.9 77.2–88.9 — pts Yes No
90% 90.4–94.8 78.1–88.0 — pts Yes No
85% 90.5–94.8 78.7–87.4 — pts Yes No
80% 90.5–94.8 79.2–86.9 — pts Yes No
75% 90.5–94.7 79.6–86.5 — pts Yes No
Reg — IND at TOR — Actual: IND 103, TOR 85
Level IND range TOR range Overlap Tol Warning Actual landed in range?
95% 87.1–96.2 78.8–89.1 1.98 pts Yes No
90% 87.8–95.5 79.6–88.3 0.45 pts Yes No
85% 88.3–95.0 80.2–87.7 — pts Yes No
80% 88.7–94.7 80.6–87.3 — pts Yes No
75% 89.0–94.4 80.9–87.0 — pts Yes No
Dr. Wallace — IND at TOR — Actual: IND 103, TOR 85
Level IND range TOR range Overlap Tol Warning Actual landed in range?
95% 85.9–97.5 80.3–87.1 1.16 pts Yes No
90% 86.8–96.6 80.9–86.5 — pts Yes No
85% 87.4–96.0 81.2–86.2 — pts Yes No
80% 87.9–95.5 81.5–85.9 — pts Yes No
75% 88.3–95.1 81.7–85.7 — pts Yes No
Kevin — IND at TOR — Actual: IND 103, TOR 85
Level IND range TOR range Overlap Tol Warning Actual landed in range?
95% 86.2–95.7 80.2–85.9 — pts Yes No
90% 86.9–95.0 80.6–85.4 — pts Yes No
85% 87.4–94.5 80.9–85.1 — pts Yes No
80% 87.8–94.1 81.1–84.9 — pts Yes No
75% 88.1–93.8 81.3–84.7 — pts Yes No
Dr. Lila Shah — IND at TOR — Actual: IND 103, TOR 85
Level IND range TOR range Overlap Tol Warning Actual landed in range?
95% 85.5–96.0 79.5–84.7 — pts Yes No
90% 86.3–95.1 79.9–84.3 — pts Yes No
85% 86.8–94.6 80.2–84.0 — pts Yes No
80% 87.3–94.2 80.4–83.8 — pts Yes No
75% 87.6–93.8 80.6–83.6 — pts Yes No
Ice — IND at TOR — Actual: IND 103, TOR 85
Level IND range TOR range Overlap Tol Warning Actual landed in range?
95% 88.3–92.7 78.6–87.3 — pts Yes No
90% 88.6–92.4 79.3–86.6 — pts Yes No
85% 88.9–92.2 79.7–86.2 — pts Yes No
80% 89.0–92.0 80.1–85.8 — pts Yes No
75% 89.2–91.8 80.4–85.5 — pts Yes No
Jamal — IND at TOR — Actual: IND 103, TOR 85
Level IND range TOR range Overlap Tol Warning Actual landed in range?
95% 86.2–94.0 79.5–85.9 — pts Yes No
90% 86.8–93.4 80.0–85.4 — pts Yes No
85% 87.2–93.0 80.4–85.1 — pts Yes No
80% 87.5–92.7 80.6–84.8 — pts Yes No
75% 87.8–92.4 80.8–84.6 — pts Yes No
Jordan — IND at TOR — Actual: IND 103, TOR 85
Level IND range TOR range Overlap Tol Warning Actual landed in range?
95% 87.2–95.5 81.5–84.2 — pts Yes No
90% 87.9–94.9 81.8–84.2 — pts Yes No
85% 88.3–94.4 82.1–84.2 — pts Yes No
80% 88.6–94.1 82.3–84.2 — pts Yes No
75% 88.9–93.8 82.6–84.2 — pts Yes No
Darren "Dimes" Lin — IND at TOR — Actual: IND 103, TOR 85
Level IND range TOR range Overlap Tol Warning Actual landed in range?
95% 81.9–101.0 77.9–86.9 5.01 pts Yes No
90% 83.4–99.6 78.6–86.2 2.81 pts Yes No
85% 84.4–98.6 79.1–85.8 1.37 pts Yes No
80% 85.2–97.8 79.4–85.4 0.26 pts Yes No
75% 85.8–97.2 79.7–85.1 — pts Yes No
Maya Jefferson — IND at TOR — Actual: IND 103, TOR 85
Level IND range TOR range Overlap Tol Warning Actual landed in range?
95% 85.8–97.3 72.9–94.9 9.09 pts Yes No
90% 86.7–96.4 74.6–93.2 6.5 pts Yes No
85% 87.3–95.8 75.7–92.1 4.8 pts Yes No
80% 87.7–95.4 76.6–91.2 3.48 pts Yes No
75% 88.1–95.0 77.3–90.5 2.38 pts Yes No