Injury cascade
Who benefits when Liam O'Brien is out?
Liam O'Brien (C, Utah Mammoth) plays 9:00 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 10 games.
Based on 51 games without Liam O'Brien and 41 with him. Through games of Oct 19, 2026.
Expected change per game without him
+0:16 TOI, +8 PP% · 11% rost
+0:10 TOI, +4 PP% · 4.9% rost
+0:14 TOI · 100% rost
+0:05 TOI · 100% rost
−0:07 TOI · 100% rost
−0:30 TOI · 18% rost
Ranked beneficiaries
Show
| Player | Games | Exp. Δ TOI | Rost % | Basis | |||
|---|---|---|---|---|---|---|---|
| Kailer YamamotoRIn 43 games without Liam O'Brien, Kailer Yamamoto played 12:18 (+0:16) and PP share went 1% → 8%. | 43 | 12:01 → 12:18 | +0:16 | 1% → 9% | 1/43 | 11%▲7.1 | Games without him |
| Nate SchmidtDIn 51 games without Liam O'Brien, Nate Schmidt played 19:54 (+0:11). | 51 | 19:43 → 19:54 | +0:10 | 6% → 10% | 1/51 | 4.9% | Games without him |
| Mikhail SergachevDIn 47 games without Liam O'Brien, Mikhail Sergachev played 24:15 (+0:15). | 47 | 24:01 → 24:15 | +0:14 | 55% → 56% | 42/47 | 100%▲1.4 | Games without him |
| Clayton KellerRIn 51 games without Liam O'Brien, Clayton Keller played 18:55 (+0:05) and moved up to his L4 slot in 1. | 51 | 18:49 → 18:55 | +0:05 | 59% → 60% | 47/51 | 100% | Games without him |
| Dylan GuentherRIn 51 games without Liam O'Brien, Dylan Guenther played 17:14 (−0:08) and moved up to his L4 slot in 3. | 51 | 17:22 → 17:14 | −0:07 | 57% → 59% | 47/51 | 100% | Games without him |
| Barrett HaytonCIn 45 games without Liam O'Brien, Barrett Hayton played 14:42 (−0:31), took PP1 in 22 of them (27% of games with him) and moved up to his L4 slot in 3. | 45 | 15:13 → 14:42 | −0:30 | 32% → 34% | 22/45 | 18%▲7.6 | Games without him |
FAQ
Who benefits when Liam O'Brien is out?
Kailer Yamamoto projects to gain the most (+0:16 a game). In 43 games without Liam O'Brien, Kailer Yamamoto played 12:18 (+0:16) and PP share went 1% → 8%.
How many games has UTA played without Liam O'Brien?
51 games in the loaded seasons while he was on the roster, against 41 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.