Nashville Predators vs San Jose Sharks prediction, odds, win probability, and matchup analysis for April 4, 2026
Get the playerWON NHL prediction for the Nashville Predators at San Jose Sharks matchup on April 4, 2026. playerWONโs machine-learning model currently gives the Nashville Predators a 55.3% win probability.
๐ค Model favours Nashville Predators
(55.3%)
Compare market odds, fair odds, and value below.
April 4, 2026
Visitor Model vs Market
Nashville Predators
55.3%
Fair American: -124
Fair Decimal: 1.81
Best Market: +102 ยท BetOnline.ag
Market Implied: 49.5%
Edge: +5.8%
EV: +11.7%
Calculate Value โ
Home Model vs Market
San Jose Sharks
44.7%
Fair American: +124
Fair Decimal: 2.24
Best Market: -115 ยท DraftKings
Market Implied: 53.5%
Edge: -8.8%
EV: -16.4%
Calculate Value โ
๐ Season Overview
|
|
Metric |
|
|---|---|---|
| 86 | Points | 86 |
| 0.524 | Points % | 0.524 |
| 247 | Goals For | 251 |
| 269 | Goals Against | 292 |
| -22 | Goal Differential | -41 |
| L2 | Current Streak | W1 |
๐ Road vs ๐ Home
|
|
Metric |
|
|---|---|---|
| 41 | Games | 41 |
| 17 | Wins | 21 |
| 41 | Points | 48 |
| -17 | Goal Differential | -16 |
๐ฅ Last 10 Games
|
|
Metric |
|
|---|---|---|
| 4-5-1 | Record | 5-4-1 |
| 9 | Points | 11 |
| 30 | Goals For | 31 |
| 30 | Goals Against | 35 |
| 0 | Goal Differential | -4 |
๐ฅ
Last 10 Head-to-Head Games
|
|
H2H Summary |
|
|---|---|---|
| 10-0 | Record | 0-10 |
| 52 | Total Goals | 25 |
| +27 | Goal Differential | -27 |
| 5.2 | Goals / Game | 2.5 |
| 30.7 | Shots / Game | 28.1 |
| Date | Matchup | Score | Shots | Details |
|---|---|---|---|---|
| Mar 24, 2026 |
|
3 - 6 | 30 - 19 | View |
| Mar 11, 2025 |
|
3 - 2 | 19 - 27 | View |
| Jan 23, 2025 |
|
6 - 5 | 38 - 35 | View |
| Jan 21, 2025 |
|
5 - 7 | 24 - 41 | View |
| Mar 19, 2024 |
|
2 - 8 | 20 - 40 | View |
| Feb 24, 2024 |
|
4 - 2 | 35 - 25 | View |
| Oct 21, 2023 |
|
1 - 5 | 32 - 34 | View |
| Feb 23, 2023 |
|
6 - 2 | 31 - 24 | View |
| Oct 8, 2022 |
|
3 - 2 | 18 - 33 | View |
| Oct 7, 2022 |
|
1 - 4 | 31 - 32 | 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.