Carolina Hurricanes vs Philadelphia Flyers prediction, odds, win probability, and matchup analysis for May 7, 2026
Get the playerWON NHL prediction for the Carolina Hurricanes at Philadelphia Flyers matchup on May 7, 2026. playerWONโs machine-learning model currently gives the Carolina Hurricanes a 64.5% win probability.
๐ค Model favours Carolina Hurricanes
(64.5%)
Compare market odds, fair odds, and value below.
May 7, 2026
Visitor Model vs Market
Carolina Hurricanes
64.5%
Fair American: -182
Fair Decimal: 1.55
Best Market: -160 ยท BetUS
Market Implied: 61.5%
Edge: +3.0%
EV: +4.8%
Calculate Value โ
Home Model vs Market
Philadelphia Flyers
35.5%
Fair American: +182
Fair Decimal: 2.82
Best Market: +145 ยท Bovada
Market Implied: 40.8%
Edge: -5.3%
EV: -13.0%
Calculate Value โ
๐ Season Overview
|
|
Metric |
|
|---|---|---|
| 113 | Points | 98 |
| 0.689 | Points % | 0.598 |
| 296 | Goals For | 250 |
| 240 | Goals Against | 243 |
| 56 | Goal Differential | 7 |
| W1 | Current Streak | W3 |
๐ Road vs ๐ Home
|
|
Metric |
|
|---|---|---|
| 41 | Games | 41 |
| 24 | Wins | 20 |
| 53 | Points | 48 |
| 21 | Goal Differential | -2 |
๐ฅ Last 10 Games
|
|
Metric |
|
|---|---|---|
| 7-2-1 | Record | 7-3-0 |
| 15 | Points | 14 |
| 39 | Goals For | 36 |
| 27 | Goals Against | 25 |
| 12 | Goal Differential | 11 |
๐ฅ
Last 10 Head-to-Head Games
|
|
H2H Summary |
|
|---|---|---|
| 8-2 | Record | 2-8 |
| 36 | Total Goals | 22 |
| +14 | Goal Differential | -14 |
| 3.6 | Goals / Game | 2.2 |
| 32.1 | Shots / Game | 23.6 |
| Date | Matchup | Score | Shots | Details |
|---|---|---|---|---|
| Apr 13, 2026 |
|
2 - 3 | 26 - 23 | View |
| Dec 14, 2025 |
|
2 - 3 | 26 - 32 | View |
| Dec 13, 2025 |
|
4 - 3 | 21 - 18 | View |
| Oct 11, 2025 |
|
3 - 4 | 23 - 39 | View |
| Mar 15, 2025 |
|
5 - 0 | 30 - 26 | View |
| Nov 20, 2024 |
|
4 - 1 | 37 - 19 | View |
| Nov 5, 2024 |
|
4 - 6 | 16 - 35 | View |
| Mar 21, 2024 |
|
2 - 3 | 32 - 33 | View |
| Nov 28, 2023 |
|
4 - 1 | 36 - 29 | View |
| Nov 15, 2023 |
|
3 - 1 | 24 - 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.