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Injury cascade

Who benefits when Mark Jankowski is out?

Mark Jankowski (C, Carolina Hurricanes) plays 13:17 a night on L4 and PP2, with 11% of the team's power-play time over his last 10 games. He has missed the team's last 2 games.

Based on 14 games without Mark Jankowski and 96 with him. Through games of Oct 20, 2026.

Expected change per game without him

Ranked beneficiaries

Show
Players whose ice time and power-play share rose without the injured player, ranked by expected fantasy opportunity.
PlayerGamesExp. Δ TOIRost %Basis
Mike ReillyDIn 10 games without Mark Jankowski, Mike Reilly played 15:55 (+1:45) and PP share went 0% → 7%.1014:10 → 15:55+1:280% → 8%0/103.2%Games without him
Jackson BlakeRIn 13 games without Mark Jankowski, Jackson Blake played 17:33 (+0:43), took PP1 in 9 of them (32% of games with him) and moved up to his L4 slot in 1.1316:50 → 17:33+0:3740% → 49%9/1382%▲1.1Games without him
Sean WalkerDIn 14 games without Mark Jankowski, Sean Walker played 23:08 (+1:24) and PP share went 9% → 16%.1421:44 → 23:08+1:149% → 16%2/1471%▲7.7Games without him
K'Andre MillerDIn 12 games without Mark Jankowski, K'Andre Miller played 22:31 (−0:12) and took PP1 in 3 of them (6% of games with him).1222:43 → 22:31−0:1017% → 24%3/1258%▼1.8Games without him
Sebastian AhoRIn 14 games without Mark Jankowski, Sebastian Aho played 19:59 (+0:10) and moved up to his L4 slot in 2.1419:49 → 19:59+0:0953% → 57%13/14100%Games without him
Eric RobinsonLIn 14 games without Mark Jankowski, Eric Robinson played 11:46 (+0:20).1411:26 → 11:46+0:171% → 2%0/146.5%▲3.3Games without him

FAQ

Who benefits when Mark Jankowski is out?

Mike Reilly projects to gain the most (+1:28 a game). In 10 games without Mark Jankowski, Mike Reilly played 15:55 (+1:45) and PP share went 0% → 7%.

How many games has CAR played without Mark Jankowski?

14 games in the loaded seasons while he was on the roster, against 96 with him.

How it works

  1. 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.
  2. 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.
  3. 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.
  4. 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.

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