Edmonton Oilers vs San Jose Sharks prediction, odds, win probability, and matchup analysis for April 8, 2026
Get the playerWON NHL prediction for the Edmonton Oilers at San Jose Sharks matchup on April 8, 2026. playerWONโs machine-learning model currently gives the Edmonton Oilers a 57.6% win probability.
๐ค Model favours Edmonton Oilers
(57.6%)
Compare market odds, fair odds, and value below.
April 8, 2026
Visitor Model vs Market
Edmonton Oilers
57.6%
Fair American: -136
Fair Decimal: 1.74
Best Market: -120 ยท BetOnline.ag
Market Implied: 54.5%
Edge: +3.1%
EV: +5.6%
Calculate Value โ
Home Model vs Market
San Jose Sharks
42.4%
Fair American: +136
Fair Decimal: 2.36
Best Market: +106 ยท BetOnline.ag
Market Implied: 48.5%
Edge: -6.1%
EV: -12.7%
Calculate Value โ
๐ Season Overview
|
|
Metric |
|
|---|---|---|
| 93 | Points | 86 |
| 0.567 | Points % | 0.524 |
| 282 | Goals For | 251 |
| 269 | Goals Against | 292 |
| 13 | Goal Differential | -41 |
| W1 | Current Streak | W1 |
๐ Road vs ๐ Home
|
|
Metric |
|
|---|---|---|
| 41 | Games | 41 |
| 19 | Wins | 21 |
| 44 | Points | 48 |
| 10 | Goal Differential | -16 |
๐ฅ Last 10 Games
|
|
Metric |
|
|---|---|---|
| 6-2-2 | Record | 5-4-1 |
| 14 | Points | 11 |
| 32 | Goals For | 31 |
| 23 | Goals Against | 35 |
| 9 | Goal Differential | -4 |
๐ฅ
Last 10 Head-to-Head Games
|
|
H2H Summary |
|
|---|---|---|
| 8-2 | Record | 2-8 |
| 42 | Total Goals | 22 |
| +20 | Goal Differential | -20 |
| 4.2 | Goals / Game | 2.2 |
| 34.4 | Shots / Game | 24.0 |
| Date | Matchup | Score | Shots | Details |
|---|---|---|---|---|
| Mar 17, 2026 |
|
3 - 5 | 30 - 37 | View |
| Feb 28, 2026 |
|
4 - 5 | 24 - 33 | View |
| Jan 29, 2026 |
|
3 - 4 | 20 - 32 | View |
| Apr 16, 2025 |
|
3 - 0 | 28 - 18 | View |
| Apr 11, 2025 |
|
2 - 4 | 24 - 34 | View |
| Apr 3, 2025 |
|
3 - 2 | 38 - 29 | View |
| Dec 21, 2024 |
|
2 - 3 | 22 - 42 | View |
| Apr 15, 2024 |
|
2 - 9 | 21 - 38 | View |
| Dec 28, 2023 |
|
5 - 0 | 30 - 25 | View |
| Nov 9, 2023 |
|
2 - 3 | 41 - 18 | 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.