Winnipeg Jets vs Columbus Blue Jackets prediction, odds, win probability, and matchup analysis for April 4, 2026
Get the playerWON NHL prediction for the Winnipeg Jets at Columbus Blue Jackets matchup on April 4, 2026. playerWONโs machine-learning model currently gives the Columbus Blue Jackets a 59.0% win probability.
๐ค Model favours Columbus Blue Jackets
(59.0%)
Compare market odds, fair odds, and value below.
April 4, 2026
Visitor Model vs Market
Winnipeg Jets
41.0%
Fair American: +144
Fair Decimal: 2.44
Best Market: +130 ยท BetRivers
Market Implied: 43.5%
Edge: -2.5%
EV: -5.7%
Calculate Value โ
Home Model vs Market
Columbus Blue Jackets
59.0%
Fair American: -144
Fair Decimal: 1.69
Best Market: -142 ยท DraftKings
Market Implied: 58.7%
Edge: +0.3%
EV: +0.5%
Calculate Value โ
๐ Season Overview
|
|
Metric |
|
|---|---|---|
| 82 | Points | 92 |
| 0.500 | Points % | 0.561 |
| 231 | Goals For | 253 |
| 260 | Goals Against | 253 |
| -29 | Goal Differential | 0 |
| L4 | Current Streak | L2 |
๐ Road vs ๐ Home
|
|
Metric |
|
|---|---|---|
| 41 | Games | 41 |
| 16 | Wins | 20 |
| 38 | Points | 48 |
| -26 | Goal Differential | 9 |
๐ฅ Last 10 Games
|
|
Metric |
|
|---|---|---|
| 5-5-0 | Record | 2-7-1 |
| 10 | Points | 5 |
| 26 | Goals For | 21 |
| 37 | Goals Against | 34 |
| -11 | Goal Differential | -13 |
๐ฅ
Last 10 Head-to-Head Games
|
|
H2H Summary |
|
|---|---|---|
| 5-5 | Record | 5-5 |
| 32 | Total Goals | 26 |
| +6 | Goal Differential | -6 |
| 3.2 | Goals / Game | 2.6 |
| 32.4 | Shots / Game | 27.9 |
| Date | Matchup | Score | Shots | Details |
|---|---|---|---|---|
| Nov 18, 2025 |
|
2 - 5 | 22 - 30 | View |
| Dec 8, 2024 |
|
4 - 1 | 28 - 25 | View |
| Nov 1, 2024 |
|
6 - 2 | 44 - 22 | View |
| Mar 17, 2024 |
|
6 - 1 | 27 - 31 | View |
| Jan 9, 2024 |
|
0 - 5 | 29 - 23 | View |
| Feb 16, 2023 |
|
1 - 3 | 38 - 24 | View |
| Dec 2, 2022 |
|
4 - 1 | 26 - 38 | View |
| Mar 25, 2022 |
|
3 - 4 | 36 - 33 | View |
| Nov 24, 2021 |
|
0 - 3 | 36 - 32 | View |
| Jan 22, 2020 |
|
3 - 4 | 30 - 29 | 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.