Florida Panthers vs Toronto Maple Leafs prediction, odds, win probability, and matchup analysis for April 11, 2026
Get the playerWON NHL prediction for the Florida Panthers at Toronto Maple Leafs matchup on April 11, 2026. playerWONโs machine-learning model currently gives the Florida Panthers a 55.7% win probability.
๐ค Model favours Florida Panthers
(55.7%)
Compare market odds, fair odds, and value below.
April 11, 2026
Visitor Model vs Market
Florida Panthers
55.7%
Fair American: -126
Fair Decimal: 1.8
Best Market: +112 ยท BetOnline.ag
Market Implied: 47.2%
Edge: +8.5%
EV: +18.1%
Calculate Value โ
Home Model vs Market
Toronto Maple Leafs
44.3%
Fair American: +126
Fair Decimal: 2.26
Best Market: -122 ยท FanDuel
Market Implied: 55.0%
Edge: -10.7%
EV: -19.4%
Calculate Value โ
๐ Season Overview
|
|
Metric |
|
|---|---|---|
| 84 | Points | 78 |
| 0.512 | Points % | 0.476 |
| 251 | Goals For | 253 |
| 276 | Goals Against | 299 |
| -25 | Goal Differential | -46 |
| W3 | Current Streak | L5 |
๐ Road vs ๐ Home
|
|
Metric |
|
|---|---|---|
| 41 | Games | 41 |
| 17 | Wins | 18 |
| 35 | Points | 44 |
| -35 | Goal Differential | -10 |
๐ฅ Last 10 Games
|
|
Metric |
|
|---|---|---|
| 5-4-1 | Record | 2-7-1 |
| 11 | Points | 5 |
| 36 | Goals For | 28 |
| 35 | Goals Against | 47 |
| 1 | Goal Differential | -19 |
๐ฅ
Last 10 Head-to-Head Games
|
|
H2H Summary |
|
|---|---|---|
| 5-5 | Record | 5-5 |
| 30 | Total Goals | 26 |
| +4 | Goal Differential | -4 |
| 3.0 | Goals / Game | 2.6 |
| 32.3 | Shots / Game | 25.7 |
| Date | Matchup | Score | Shots | Details |
|---|---|---|---|---|
| Feb 26, 2026 |
|
1 - 5 | 29 - 37 | View |
| Jan 6, 2026 |
|
1 - 4 | 32 - 23 | View |
| Dec 2, 2025 |
|
4 - 1 | 31 - 26 | View |
| Apr 8, 2025 |
|
1 - 3 | 18 - 37 | View |
| Apr 2, 2025 |
|
2 - 3 | 31 - 26 | View |
| Mar 13, 2025 |
|
3 - 2 | 25 - 25 | View |
| Nov 27, 2024 |
|
1 - 5 | 24 - 24 | View |
| Apr 16, 2024 |
|
2 - 5 | 26 - 42 | View |
| Apr 1, 2024 |
|
4 - 6 | 30 - 23 | View |
| Nov 28, 2023 |
|
1 - 2 | 39 - 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.