Chicago Wolves — Manitoba Moose
☆ Save matchModel prediction for 27 October
Preliminary forecast: the match is more than a week away. Closer to it the model takes in fresh form, injuries and line-ups, and the numbers may move.
In short
Close to a coin flip: Chicago Wolves 52%, Manitoba Moose 48% including overtime.
5.5 goals expected in total — close to the competition average (5.8).
Over 5.5 goals in regulation — 52%.
Why
- The teams are almost level on expected goals: 2.8 and 2.7.
Probabilities
| Expected goals: Chicago Wolves — Manitoba Moose | 2.8–2.7 | |
| Chicago Wolves to win (incl. OT and shootout) | 52% | |
| Manitoba Moose to win (incl. OT and shootout) | 48% | |
| Total over 5.5 (regulation) | 52% | |
| Total under 5.5 (regulation) | 48% |
111 more model lines in Premium
All totals and handicaps, team totals, the score grid, every factor and how the estimate moved before kick-off.
- All totals
- Totals incl. OT
- Handicap Chicago Wolves
- Chicago Wolves goals
- Overtime chance
- Full score grid
Form
- 11.10away · Grand Rapids Griffins1:5
- 11.10Manitoba Moose1:6
- 04.10away · Manitoba Moose3:8
- 03.10away · Manitoba Moose0:3
- 20.06away · Toronto Marlies3:4
- 11.10away · Chicago Wolves6:1
- 10.10away · Grand Rapids Griffins1:2
- 04.10Chicago Wolves8:3
- 03.10Chicago Wolves3:0
- 09.05away · Grand Rapids Griffins2:5
Head to head
- 11.10.2026Chicago Wolves — Manitoba Moose1:6
- 04.10.2026Manitoba Moose — Chicago Wolves8:3
- 03.10.2026Manitoba Moose — Chicago Wolves3:0
- 16.04.2026Chicago Wolves — Manitoba Moose3:2 SO
- 12.01.2026Chicago Wolves — Manitoba Moose4:3 OT
Table
| # | Team | P | W | +/− | Pts | P% |
|---|---|---|---|---|---|---|
| 2 | Milwaukee Admirals | 2 | 2 | +5 | 4 | 1.000 |
| 3 | Manitoba Moose | 4 | 3 | +12 | 6 | .750 |
| 4 | Laval Rocket | 4 | 3 | +9 | 6 | .750 |
| 31 | Lehigh Valley Phantoms | 3 | 0 | -7 | 1 | .167 |
| 32 | Chicago Wolves | 4 | 0 | -17 | 0 | .000 |
This is the model’s statistical estimate, not a recommendation. An outcome at 41% will not happen in roughly 59 matches out of 100. How to read probabilities →