Injury cascade
Who benefits when Nick Foligno is out?
Nick Foligno (L, Minnesota Wild) plays 11:05 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 4 games.
Based on 6 games without Nick Foligno and 31 with him. Through games of Oct 13, 2026.
Expected change per game without him
+3:08 TOI · 0.3% rost
+1:27 TOI · 5.0% rost
+0:30 TOI, +6 PP% · 41% rost
+1:31 TOI, −4 PP% · 52% rost
+0:58 TOI · 4.8% rost
+0:34 TOI · 41% rost
Ranked beneficiaries
Show
| Player | Games | Exp. Δ TOI | Rost % | Basis | |||
|---|---|---|---|---|---|---|---|
| Zach BogosianDIn 4 games without Nick Foligno, Zach Bogosian played 17:49 (+4:41). | 4 | 13:08 → 17:49 | +3:08 | 0% → 1% | 0/4 | 0.3% | Games without him |
| Jonas BrodinDIn 6 games without Nick Foligno, Jonas Brodin played 20:44 (+1:55). | 6 | 18:49 → 20:44 | +1:27 | 2% → 4% | 0/6 | 5.0% | Games without him |
| Blake ColemanLIn 4 games without Nick Foligno, Blake Coleman played 15:46 (+0:46) and PP share went 16% → 25%. | 4 | 15:01 → 15:46 | +0:30 | 16% → 25% | 0/4 | 41%▲4.7 | Games without him |
| Jared SpurgeonDIn 5 games without Nick Foligno, Jared Spurgeon played 21:47 (+2:07) and PP share went 15% → 10%. | 5 | 19:40 → 21:47 | +1:31 | 15% → 10% | 0/5 | 52%▲39 | Games without him |
| Jake MiddletonDIn 2 games without Nick Foligno, Jake Middleton played 18:12 (+1:56). | 2 | 16:17 → 18:12 | +0:58 | 0% → 0% | 0/2 | 4.8% | Games without him |
| Mats ZuccarelloRIn 2 games without Nick Foligno, Mats Zuccarello played 19:15 (+1:08) and PP share went 64% → 70%. | 2 | 18:07 → 19:15 | +0:34 | 64% → 70% | 2/2 | 41%▼6.2 | Games without him |
FAQ
Who benefits when Nick Foligno is out?
Zach Bogosian projects to gain the most (+3:08 a game). In 4 games without Nick Foligno, Zach Bogosian played 17:49 (+4:41).
How many games has MIN played without Nick Foligno?
6 games in the loaded seasons while he was on the roster, against 31 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.