Vancouver Canucks vs San Jose Sharks prediction, odds, win probability, and matchup analysis for April 11, 2026
Get the playerWON NHL prediction for the Vancouver Canucks at San Jose Sharks matchup on April 11, 2026. playerWONโs machine-learning model currently gives the San Jose Sharks a 57.8% win probability.
๐ค Model favours San Jose Sharks
(57.8%)
Compare market odds, fair odds, and value below.
April 11, 2026
Visitor Model vs Market
Vancouver Canucks
42.2%
Fair American: +137
Fair Decimal: 2.37
Best Market: +185 ยท BetRivers
Market Implied: 35.1%
Edge: +7.1%
EV: +20.3%
Calculate Value โ
Home Model vs Market
San Jose Sharks
57.8%
Fair American: -137
Fair Decimal: 1.73
Best Market: -194 ยท BetOnline.ag
Market Implied: 66.0%
Edge: -8.2%
EV: -12.4%
Calculate Value โ
๐ Season Overview
|
|
Metric |
|
|---|---|---|
| 58 | Points | 86 |
| 0.354 | Points % | 0.524 |
| 216 | Goals For | 251 |
| 316 | Goals Against | 292 |
| -100 | Goal Differential | -41 |
| L1 | Current Streak | W1 |
๐ Road vs ๐ Home
|
|
Metric |
|
|---|---|---|
| 41 | Games | 41 |
| 16 | Wins | 21 |
| 35 | Points | 48 |
| -41 | Goal Differential | -16 |
๐ฅ Last 10 Games
|
|
Metric |
|
|---|---|---|
| 4-6-0 | Record | 5-4-1 |
| 8 | Points | 11 |
| 31 | Goals For | 31 |
| 43 | Goals Against | 35 |
| -12 | Goal Differential | -4 |
๐ฅ
Last 10 Head-to-Head Games
|
|
H2H Summary |
|
|---|---|---|
| 6-4 | Record | 4-6 |
| 31 | Total Goals | 30 |
| +1 | Goal Differential | -1 |
| 3.1 | Goals / Game | 3.0 |
| 29.5 | Shots / Game | 27.1 |
| Date | Matchup | Score | Shots | Details |
|---|---|---|---|---|
| Jan 27, 2026 |
|
5 - 2 | 33 - 25 | View |
| Dec 27, 2025 |
|
6 - 3 | 37 - 27 | View |
| Nov 28, 2025 |
|
2 - 3 | 34 - 24 | View |
| Apr 14, 2025 |
|
1 - 2 | 16 - 37 | View |
| Feb 6, 2025 |
|
2 - 1 | 24 - 34 | View |
| Dec 23, 2024 |
|
3 - 4 | 29 - 24 | View |
| Nov 2, 2024 |
|
3 - 2 | 28 - 23 | View |
| Dec 23, 2023 |
|
4 - 7 | 25 - 26 | View |
| Nov 25, 2023 |
|
3 - 4 | 33 - 22 | View |
| Nov 20, 2023 |
|
1 - 3 | 28 - 37 | View |
This matchup prediction is generated using playerWONโs machine-learning model, incorporating team performance, recent form, and home/away effects. View full model performance to compare results across games.