Injury cascade
Who benefits when Marcus Foligno is out?
Marcus Foligno (L, Minnesota Wild) plays 11:15 a night on L4, with 0% of the team's power-play time over his last 10 games. He has missed the team's last 3 games.
Based on 29 games without Marcus Foligno and 71 with him. Through games of Oct 13, 2026.
Expected change per game without him
+1:44 TOI, +11 PP% · 4.0% rost
+1:52 TOI, +7 PP% · 0.1% rost
+2:20 TOI · 0.0% rost
+1:27 TOI, +4 PP% · 0.0% rost
+1:55 TOI · 0.0% rost
+0:45 TOI, +8 PP% · 33% rost
Ranked beneficiaries
Show
| Player | Games | Exp. Δ TOI | Rost % | Basis | |||
|---|---|---|---|---|---|---|---|
| Hunter HaightCIn 4 games without Marcus Foligno, Hunter Haight played 12:17 (+2:37), PP share went 0% → 17% and moved up to his L4 slot in 2. | 4 | 9:41 → 12:17 | +1:44 | 0% → 17% | 0/4 | 4.0% | Games without him |
| Daemon HuntDIn 12 games without Marcus Foligno, Daemon Hunt played 14:03 (+2:10) and PP share went 0% → 8%. | 12 | 11:53 → 14:03 | +1:52 | 0% → 8% | 0/12 | 0.1% | Games without him |
| Jeff PetryDIn 3 games without Marcus Foligno, Jeff Petry played 15:41 (+3:53). | 3 | 11:48 → 15:41 | +2:20 | 0% → 0% | 0/3 | 0.0% | Games without him |
| David SpacekDIn 2 games without Marcus Foligno, David Spacek played 12:51 (+2:53) and PP share went 0% → 8%. | 2 | 9:58 → 12:51 | +1:27 | 0% → 8% | 0/2 | 0.0% | Games without him |
| Matt KierstedDIn 3 games without Marcus Foligno, Matt Kiersted played 17:19 (+3:11). | 3 | 14:08 → 17:19 | +1:55 | 0% → 0% | 0/3 | 0.0% | Games without him |
| Danila YurovRIn 27 games without Marcus Foligno, Danila Yurov played 13:43 (+0:48), PP share went 8% → 17% and moved up to his L4 slot in 1. | 27 | 12:55 → 13:43 | +0:45 | 8% → 17% | 2/27 | 33%▲0.9 | Games without him |
FAQ
Who benefits when Marcus Foligno is out?
Hunter Haight projects to gain the most (+1:44 a game). In 4 games without Marcus Foligno, Hunter Haight played 12:17 (+2:37), PP share went 0% → 17% and moved up to his L4 slot in 2.
How many games has MIN played without Marcus Foligno?
29 games in the loaded seasons while he was on the roster, against 71 with him.
How it works
- We find every game the injured player missed while on the team's roster this season and last (including the current absence), and compare each teammate's ice time, power-play share and PP1 usage in those games with the games the injured player dressed.
- Changes are shrunk toward zero when the sample is small (a change over n games counts n / (n + 2) of its size), so one odd game does not crown a beneficiary.
- When there is little or no absence history, we fall back to line adjacency from our shift-based line detection: the next man up on his power-play unit (the top PP2 player at his position) and the best player one line or pair below his.
- Players are ranked by expected fantasy opportunity: TOI minutes, plus power-play share (10 points of PP share ≈ 1.2 minutes of even-strength TOI), plus PP1 gains.