Chicago Sky at Toronto Tempo
CHI 68 – TOR 85
June 7, 2026 · Final
Best model for this game
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.
All 12 models’ predicted scores
In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.0) — by 1.6 points. The ranges overlap almost entirely, so one game could go either way.
In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.0) — by 1.6 points. The ranges overlap some — there's real uncertainty here.
In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.0) — by 1.6 points. The ranges overlap some — there's real uncertainty here.
In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.0) — by 1.6 points. The ranges overlap some — there's real uncertainty here.
In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.0) — by 1.6 points. The ranges overlap some — there's real uncertainty here.
Show the math
- Model
- Vince Chambers (#1)
- t-statistic
- -9.04
- p-value
- 5.82e-16
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.
In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.5) over Chicago Sky (avg. 83.2) — by 1.3 points. The ranges overlap almost entirely, so one game could go either way.
In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.5) over Chicago Sky (avg. 83.2) — by 1.3 points. The ranges overlap almost entirely, so one game could go either way.
In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.5) over Chicago Sky (avg. 83.2) — by 1.3 points. The ranges overlap some — there's real uncertainty here.
In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.5) over Chicago Sky (avg. 83.2) — by 1.3 points. The ranges overlap some — there's real uncertainty here.
In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.5) over Chicago Sky (avg. 83.2) — by 1.3 points. The ranges overlap some — there's real uncertainty here.
Show the math
- Model
- Reg (#2)
- t-statistic
- -6.61
- p-value
- 5.26e-10
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.
In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.2) — by 1.7 points. The ranges overlap almost entirely, so one game could go either way.
In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.2) — by 1.7 points. The ranges overlap almost entirely, so one game could go either way.
In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.2) — by 1.7 points. The ranges overlap some — there's real uncertainty here.
In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.2) — by 1.7 points. The ranges overlap some — there's real uncertainty here.
In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.2) — by 1.7 points. The ranges overlap some — there's real uncertainty here.
Show the math
- Model
- Dr. Wallace (#3)
- t-statistic
- -8.33
- p-value
- 7.68e-14
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.
In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.4) — by 1.5 points. The ranges overlap almost entirely, so one game could go either way.
In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.4) — by 1.5 points. The ranges overlap almost entirely, so one game could go either way.
In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.4) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.4) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.4) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
Show the math
- Model
- Kevin (#4)
- t-statistic
- -7.99
- p-value
- 2.97e-13
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.
In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Chicago Sky (avg. 82.7) — by 2.3 points. The ranges overlap almost entirely, so one game could go either way.
In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Chicago Sky (avg. 82.7) — by 2.3 points. The ranges overlap some — there's real uncertainty here.
In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Chicago Sky (avg. 82.7) — by 2.3 points. The ranges overlap some — there's real uncertainty here.
In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Chicago Sky (avg. 82.7) — by 2.3 points. The ranges overlap some — there's real uncertainty here.
In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 85.0) over Chicago Sky (avg. 82.7) — by 2.3 points. The ranges overlap some — there's real uncertainty here.
Show the math
- Model
- Dr. Lila Shah (#5)
- t-statistic
- -11.20
- p-value
- 3.61e-21
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.
In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.3) — by 1.3 points. The ranges overlap almost entirely, so one game could go either way.
In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.3) — by 1.3 points. The ranges overlap almost entirely, so one game could go either way.
In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.3) — by 1.3 points. The ranges overlap almost entirely, so one game could go either way.
In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.3) — by 1.3 points. The ranges overlap some — there's real uncertainty here.
In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.3) — by 1.3 points. The ranges overlap some — there's real uncertainty here.
Show the math
- Model
- Ice (#6)
- t-statistic
- -6.47
- p-value
- 1.06e-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.
In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.3) — by 1.3 points. The ranges overlap almost entirely, so one game could go either way.
In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.3) — by 1.3 points. The ranges overlap almost entirely, so one game could go either way.
In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.3) — by 1.3 points. The ranges overlap some — there's real uncertainty here.
In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.3) — by 1.3 points. The ranges overlap some — there's real uncertainty here.
In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.6) over Chicago Sky (avg. 83.3) — by 1.3 points. The ranges overlap some — there's real uncertainty here.
Show the math
- Model
- Jamal (#7)
- t-statistic
- -6.66
- p-value
- 4.20e-10
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.
In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.3) — by 1.5 points. The ranges overlap almost entirely, so one game could go either way.
In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.3) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.3) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.3) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.9) over Chicago Sky (avg. 83.3) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
Show the math
- Model
- Jordan (#8)
- t-statistic
- -8.55
- p-value
- 1.97e-14
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.
In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.3) — by 1.5 points. The ranges overlap almost entirely, so one game could go either way.
In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.3) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.3) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.3) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.3) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
Show the math
- Model
- Darren "Dimes" Lin (#9)
- t-statistic
- -8.71
- p-value
- 3.33e-15
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.
In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.2) — by 1.5 points. The ranges overlap almost entirely, so one game could go either way.
In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.2) — by 1.5 points. The ranges overlap almost entirely, so one game could go either way.
In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.2) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.2) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.2) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
Show the math
- Model
- Maya Jefferson (#10)
- t-statistic
- -7.60
- p-value
- 2.89e-12
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.
In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.2) — by 1.5 points. The ranges overlap almost entirely, so one game could go either way.
In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.2) — by 1.5 points. The ranges overlap almost entirely, so one game could go either way.
In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.2) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.2) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 84.7) over Chicago Sky (avg. 83.2) — by 1.5 points. The ranges overlap some — there's real uncertainty here.
Show the math
- Model
- Lexi (#11)
- t-statistic
- -7.76
- p-value
- 1.04e-12
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.
In 95 out of 100 simulated runs, leans Toronto Tempo (avg. 85.5) over Chicago Sky (avg. 82.9) — by 2.6 points. The ranges overlap almost entirely, so one game could go either way.
In 90 out of 100 simulated runs, leans Toronto Tempo (avg. 85.5) over Chicago Sky (avg. 82.9) — by 2.6 points. The ranges overlap some — there's real uncertainty here.
In 85 out of 100 simulated runs, leans Toronto Tempo (avg. 85.5) over Chicago Sky (avg. 82.9) — by 2.6 points. The ranges overlap some — there's real uncertainty here.
In 80 out of 100 simulated runs, leans Toronto Tempo (avg. 85.5) over Chicago Sky (avg. 82.9) — by 2.6 points. The ranges overlap some — there's real uncertainty here.
In 75 out of 100 simulated runs, leans Toronto Tempo (avg. 85.5) over Chicago Sky (avg. 82.9) — by 2.6 points. The ranges barely touch.
Show the math
- Model
- Coach Sarah Watanabe (#12)
- t-statistic
- -12.92
- p-value
- 8.10e-27
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
| Level | CHI range | TOR range | Overlap | Tol Warning | Actual landed in range? |
|---|---|---|---|---|---|
| 95% | 80.9–85.2 | 81.7–87.5 | 3.5 pts | — | No |
| 90% | 81.2–84.9 | 82.2–87.0 | 2.68 pts | — | No |
| 85% | 81.4–84.6 | 82.5–86.7 | 2.15 pts | — | No |
| 80% | 81.6–84.5 | 82.7–86.5 | 1.75 pts | — | No |
| 75% | 81.8–84.3 | 82.9–86.3 | 1.41 pts | — | No |
| Level | CHI range | TOR range | Overlap | Tol Warning | Actual landed in range? |
|---|---|---|---|---|---|
| 95% | 81.4–85.9 | 81.3–87.6 | 4.45 pts | Yes | No |
| 90% | 81.6–85.1 | 81.8–87.1 | 3.29 pts | Yes | No |
| 85% | 81.8–84.5 | 82.1–86.8 | 2.36 pts | Yes | No |
| 80% | 81.9–84.3 | 82.4–86.5 | 1.87 pts | Yes | No |
| 75% | 82.0–84.2 | 82.6–86.3 | 1.58 pts | Yes | No |
| Level | CHI range | TOR range | Overlap | Tol Warning | Actual landed in range? |
|---|---|---|---|---|---|
| 95% | 81.1–85.4 | 81.4–88.4 | 3.99 pts | — | No |
| 90% | 81.5–85.0 | 81.9–87.8 | 3.09 pts | — | No |
| 85% | 81.7–84.8 | 82.3–87.5 | 2.49 pts | — | No |
| 80% | 81.8–84.6 | 82.6–87.2 | 2.04 pts | — | No |
| 75% | 82.0–84.5 | 82.8–87.0 | 1.66 pts | — | No |
| Level | CHI range | TOR range | Overlap | Tol Warning | Actual landed in range? |
|---|---|---|---|---|---|
| 95% | 81.1–85.7 | 81.8–88.0 | 3.93 pts | — | No |
| 90% | 81.5–85.4 | 82.3–87.5 | 3.06 pts | — | No |
| 85% | 81.7–85.1 | 82.6–87.2 | 2.49 pts | — | No |
| 80% | 81.9–84.9 | 82.9–86.9 | 2.05 pts | — | No |
| 75% | 82.1–84.8 | 83.1–86.7 | 1.69 pts | — | No |
| Level | CHI range | TOR range | Overlap | Tol Warning | Actual landed in range? |
|---|---|---|---|---|---|
| 95% | 80.4–85.0 | 81.4–88.7 | 3.63 pts | — | No |
| 90% | 80.8–84.6 | 81.9–88.1 | 2.67 pts | — | No |
| 85% | 81.0–84.4 | 82.3–87.7 | 2.04 pts | — | No |
| 80% | 81.2–84.2 | 82.6–87.4 | 1.56 pts | — | No |
| 75% | 81.3–84.0 | 82.9–87.2 | 1.17 pts | — | No |
| Level | CHI range | TOR range | Overlap | Tol Warning | Actual landed in range? |
|---|---|---|---|---|---|
| 95% | 80.5–86.0 | 81.5–87.7 | 4.58 pts | — | No |
| 90% | 81.0–85.6 | 82.0–87.2 | 3.63 pts | — | No |
| 85% | 81.3–85.3 | 82.3–86.9 | 3.02 pts | — | No |
| 80% | 81.5–85.1 | 82.5–86.6 | 2.54 pts | — | No |
| 75% | 81.7–84.9 | 82.7–86.4 | 2.15 pts | — | No |
| Level | CHI range | TOR range | Overlap | Tol Warning | Actual landed in range? |
|---|---|---|---|---|---|
| 95% | 80.7–85.8 | 81.5–87.6 | 4.32 pts | — | No |
| 90% | 81.2–85.4 | 82.0–87.1 | 3.42 pts | — | No |
| 85% | 81.4–85.1 | 82.3–86.8 | 2.84 pts | — | No |
| 80% | 81.6–84.9 | 82.5–86.6 | 2.38 pts | — | No |
| 75% | 81.8–84.8 | 82.7–86.4 | 2.01 pts | — | No |
| Level | CHI range | TOR range | Overlap | Tol Warning | Actual landed in range? |
|---|---|---|---|---|---|
| 95% | 81.4–85.3 | 81.7–88.0 | 3.56 pts | — | No |
| 90% | 81.7–85.0 | 82.2–87.5 | 2.74 pts | — | No |
| 85% | 81.9–84.8 | 82.6–87.2 | 2.21 pts | — | No |
| 80% | 82.1–84.6 | 82.8–86.9 | 1.8 pts | — | No |
| 75% | 82.2–84.5 | 83.0–86.7 | 1.46 pts | — | No |
| Level | CHI range | TOR range | Overlap | Tol Warning | Actual landed in range? |
|---|---|---|---|---|---|
| 95% | 80.9–85.6 | 82.1–87.4 | 3.5 pts | — | No |
| 90% | 81.3–85.2 | 82.5–87.0 | 2.7 pts | — | No |
| 85% | 81.6–85.0 | 82.8–86.7 | 2.18 pts | — | No |
| 80% | 81.7–84.8 | 83.0–86.5 | 1.78 pts | — | No |
| 75% | 81.9–84.6 | 83.2–86.3 | 1.44 pts | — | No |
| Level | CHI range | TOR range | Overlap | Tol Warning | Actual landed in range? |
|---|---|---|---|---|---|
| 95% | 80.8–85.6 | 81.3–88.1 | 4.31 pts | — | No |
| 90% | 81.2–85.2 | 81.9–87.6 | 3.37 pts | — | No |
| 85% | 81.4–85.0 | 82.2–87.2 | 2.76 pts | — | No |
| 80% | 81.6–84.8 | 82.5–87.0 | 2.29 pts | — | No |
| 75% | 81.8–84.6 | 82.7–86.7 | 1.9 pts | — | No |
| Level | CHI range | TOR range | Overlap | Tol Warning | Actual landed in range? |
|---|---|---|---|---|---|
| 95% | 80.9–85.6 | 81.6–87.8 | 4.02 pts | — | No |
| 90% | 81.2–85.2 | 82.1–87.3 | 3.13 pts | — | No |
| 85% | 81.5–85.0 | 82.4–87.0 | 2.56 pts | — | No |
| 80% | 81.7–84.8 | 82.7–86.7 | 2.12 pts | — | No |
| 75% | 81.8–84.6 | 82.9–86.5 | 1.75 pts | — | No |
| Level | CHI range | TOR range | Overlap | Tol Warning | Actual landed in range? |
|---|---|---|---|---|---|
| 95% | 80.1–85.7 | 82.4–88.6 | 3.29 pts | — | No |
| 90% | 80.5–85.3 | 82.9–88.1 | 2.34 pts | — | No |
| 85% | 80.8–85.0 | 83.2–87.8 | 1.73 pts | — | No |
| 80% | 81.1–84.7 | 83.5–87.5 | 1.25 pts | — | No |
| 75% | 81.3–84.6 | 83.7–87.3 | 0.86 pts | — | No |