Winnipeg Jets vs Vegas Golden Knights prediction, odds, win probability, and matchup analysis for April 13, 2026
Get the playerWON NHL prediction for the Winnipeg Jets at Vegas Golden Knights matchup on April 13, 2026. playerWONโs machine-learning model currently gives the Vegas Golden Knights a 57.2% win probability.
๐ค Model favours Vegas Golden Knights
(57.2%)
Compare market odds, fair odds, and value below.
April 13, 2026
Visitor Model vs Market
Winnipeg Jets
42.8%
Fair American: +134
Fair Decimal: 2.34
Best Market: +155 ยท FanDuel
Market Implied: 39.2%
Edge: +3.6%
EV: +9.1%
Calculate Value โ
Home Model vs Market
Vegas Golden Knights
57.2%
Fair American: -134
Fair Decimal: 1.75
Best Market: -162 ยท BetOnline.ag
Market Implied: 61.8%
Edge: -4.6%
EV: -7.5%
Calculate Value โ
๐ Season Overview
|
|
Metric |
|
|---|---|---|
| 82 | Points | 95 |
| 0.500 | Points % | 0.579 |
| 231 | Goals For | 265 |
| 260 | Goals Against | 250 |
| -29 | Goal Differential | 15 |
| L4 | Current Streak | W3 |
๐ Road vs ๐ Home
|
|
Metric |
|
|---|---|---|
| 41 | Games | 41 |
| 16 | Wins | 20 |
| 38 | Points | 49 |
| -26 | Goal Differential | 19 |
๐ฅ Last 10 Games
|
|
Metric |
|
|---|---|---|
| 5-5-0 | Record | 7-0-3 |
| 10 | Points | 17 |
| 26 | Goals For | 40 |
| 37 | Goals Against | 25 |
| -11 | Goal Differential | 15 |
๐ฅ
Last 10 Head-to-Head Games
|
|
H2H Summary |
|
|---|---|---|
| 2-8 | Record | 8-2 |
| 28 | Total Goals | 34 |
| -6 | Goal Differential | +6 |
| 2.8 | Goals / Game | 3.4 |
| 27.6 | Shots / Game | 31.1 |
| Date | Matchup | Score | Shots | Details |
|---|---|---|---|---|
| Mar 24, 2026 |
|
1 - 4 | 27 - 21 | View |
| Jan 6, 2026 |
|
4 - 3 | 31 - 20 | View |
| Apr 3, 2025 |
|
4 - 0 | 22 - 26 | View |
| Dec 12, 2024 |
|
3 - 2 | 36 - 20 | View |
| Nov 29, 2024 |
|
3 - 4 | 25 - 30 | View |
| Mar 28, 2024 |
|
4 - 1 | 27 - 40 | View |
| Nov 2, 2023 |
|
2 - 5 | 31 - 26 | View |
| Oct 19, 2023 |
|
5 - 3 | 27 - 39 | View |
| Dec 13, 2022 |
|
6 - 5 | 33 - 34 | View |
| Oct 30, 2022 |
|
1 - 2 | 24 - 48 | 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.