Pittsburgh Penguins vs New Jersey Devils prediction, odds, win probability, and matchup analysis for April 9, 2026
Get the playerWON NHL prediction for the Pittsburgh Penguins at New Jersey Devils matchup on April 9, 2026. playerWONโs machine-learning model currently gives the New Jersey Devils a 52.7% win probability.
๐ค Model favours New Jersey Devils
(52.7%)
Compare market odds, fair odds, and value below.
April 9, 2026
Visitor Model vs Market
Pittsburgh Penguins
47.3%
Fair American: +111
Fair Decimal: 2.11
Best Market: -109 ยท BetOnline.ag
Market Implied: 52.2%
Edge: -4.9%
EV: -9.3%
Calculate Value โ
Home Model vs Market
New Jersey Devils
52.7%
Fair American: -111
Fair Decimal: 1.9
Best Market: -105 ยท BetOnline.ag
Market Implied: 51.2%
Edge: +1.5%
EV: +2.9%
Calculate Value โ
๐ Season Overview
|
|
Metric |
|
|---|---|---|
| 98 | Points | 87 |
| 0.598 | Points % | 0.530 |
| 293 | Goals For | 230 |
| 268 | Goals Against | 254 |
| 25 | Goal Differential | -24 |
| L3 | Current Streak | L1 |
๐ Road vs ๐ Home
|
|
Metric |
|
|---|---|---|
| 41 | Games | 41 |
| 21 | Wins | 21 |
| 50 | Points | 45 |
| 18 | Goal Differential | -3 |
๐ฅ Last 10 Games
|
|
Metric |
|
|---|---|---|
| 5-5-0 | Record | 5-4-1 |
| 10 | Points | 11 |
| 46 | Goals For | 31 |
| 40 | Goals Against | 34 |
| 6 | Goal Differential | -3 |
๐ฅ
Last 10 Head-to-Head Games
|
|
H2H Summary |
|
|---|---|---|
| 5-5 | Record | 5-5 |
| 32 | Total Goals | 28 |
| +4 | Goal Differential | -4 |
| 3.2 | Goals / Game | 2.8 |
| 26.7 | Shots / Game | 28.0 |
| Date | Matchup | Score | Shots | Details |
|---|---|---|---|---|
| Feb 26, 2026 |
|
1 - 4 | 29 - 35 | View |
| Jan 8, 2026 |
|
1 - 4 | 29 - 29 | View |
| Nov 8, 2025 |
|
1 - 2 | 34 - 24 | View |
| Apr 11, 2025 |
|
4 - 2 | 24 - 28 | View |
| Mar 15, 2025 |
|
3 - 7 | 27 - 24 | View |
| Feb 4, 2025 |
|
3 - 2 | 21 - 27 | View |
| Dec 21, 2024 |
|
0 - 3 | 12 - 27 | View |
| Apr 2, 2024 |
|
6 - 3 | 21 - 26 | View |
| Mar 19, 2024 |
|
2 - 5 | 38 - 38 | View |
| Nov 16, 2023 |
|
5 - 2 | 31 - 23 | 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.