2022-23 NHL Predictions
Updated after every game.
Completed games
Tuesday, June 13Stanley Cup Finals
| Game 5•final | win prob. | score |
|---|---|---|
| Panthers | 36% | 3 |
| Golden Knights4-1 | 64% | ✓9 |
Panthers
Golden Knights| quality The harmonic mean of the teams’ Elo ratings | importance How much the result altered league projections | overall The average of quality and importance | 100 | 100 | 100 |
|---|
Saturday, June 10Stanley Cup Finals
| Game 4•final | win prob. | score |
|---|---|---|
| Golden Knights3-1 | 45% | ✓3 |
| Panthers | 55% | 2 |
| quality The harmonic mean of the teams’ Elo ratings | importance How much the result altered league projections | overall The average of quality and importance | 100 | 100 | 100 |
|---|
Thursday, June 8Stanley Cup Finals
| Game 3•final/OT | win prob. | score |
|---|---|---|
| Golden Knights2-1 | 46% | 2 |
| Panthers | 54% | ✓3 |
| quality The harmonic mean of the teams’ Elo ratings | importance How much the result altered league projections | overall The average of quality and importance | 100 | 100 | 100 |
|---|
Monday, June 5Stanley Cup Finals
| Game 2•final | win prob. | score |
|---|---|---|
| Panthers | 38% | 2 |
| Golden Knights2-0 | 62% | ✓7 |
| quality The harmonic mean of the teams’ Elo ratings | importance How much the result altered league projections | overall The average of quality and importance | 100 | 100 | 100 |
|---|
More NHL coverage
How this works These forecasts are based on 50,000 simulations of the rest of the season. Elo ratings are a measure of team strength based on head-to-head results, margin of victory and quality of opponent. Read more »
Design and development by Ryan Best and Elena Mejía. Edited by Maya Sweedler, Julia Wolfe and Sara Ziegler. Statistical model by Ryan Best and Neil Paine. Additional contributions by Jay Boice.
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