Kodo Hockey

TOI Breakouts · per-60 × ice time

Pick any skater in the league and drag their ice time to see what the role is worth — production scales at their own rate per 60 minutes. Below, the breakout board ranks who already produces at a high rate and is projected for more minutes in 2026-27: +pts is what the minutes change alone adds.

Team
Player
76
projected points
0 vs model
8 min30 min
18.1 min/gamelast season 17.3 → model 18.1 · L1·PP1games
76
Points
3.15/60
45
Goals
1.87/60
31
Assists
1.28/60
314
Shots
13.01/60
21
PP pts
0.87/60
70
Hits
2.92/60
22
Blocks
0.91/60
31
PIM
1.28/60
Rates are last season's per 60 minutes (76 GP). Totals scale linearly with ice time and games — a rate this good over a small sample is a bet, not a guarantee. A dash for last season means no NHL history, so that player is shown at his role's baseline. Full profile →
sortBiggest opportunityPer-60 rate
#PlayerTmProj roleP/60iSCF/6025-26 TOI26-27 TOIΔ minProj pts+pts
1Linus Karlsson · RVANL1·PP12.134.9212.515.5+3.035+7.0
2Jack Quinn · RBUFL2·PP12.386.0615.717.7+2.053+6.0
3Gage Goncalves · RTBLL1·PP22.043.8413.115.7+2.635+6.0
4Ross Colton · LNSHL3·PP21.58512.515.5+3.031+6.0
5Isaac Howard · LEDML4·PP214.4210.313.7+3.423+6.0
6Egor Chinakhov · RPITL2·PP22.595.4913.515.9+2.439+6.0
7Calum Ritchie · CNYIL2·PP22.054.0313.515.8+2.338+5.0
8Viktor Arvidsson · LDETL2·PP13.225.8414.616+1.455+5.0
9Fedor Svechkov · CCOLL31.23.1912.115+2.921+4.0
10Connor Dewar · CPITL41.663.6513.915.9+2.029+4.0
11Jordan Martinook · LCARL31.533.3714.816.7+1.931+4.0
12Jamie Benn · LDALL3·PP22.714.2913.314.8+1.541+4.0
13Danila Yurov · CMINL1·PP21.674.0213.315.3+2.032+4.0
14Matthew Wood · RNSHL2·PP12.064.5312.313.8+1.535+4.0
15Ryan Winterton · CSEAL31.323.461214.8+2.824+4.0
16Morgan Barron · CWPGL31.663.3912.815.3+2.525+4.0
17Keegan Kolesar · RDETL31.082.4811.514.8+3.319+4.0
18Hendrix Lapierre · CPITL3·PP21.473.228.811.6+2.818+4.0
19Justin Hryckowian · CDALL1·PP21.672.913.315.3+2.032+4.0
20Ryan Strome · CCGYL1·PP21.822.4313.315.5+2.232+4.0
21Jake DeBrusk · LVANL1·PP11.846.7916.918.6+1.746+4.0
22Drew O'Connor · LVANL31.454.4614.616.9+2.329+4.0
23Oliver Bjorkstrand · RNYRL2·PP21.765.7913.615.2+1.638+4.0
24Lars Eller · CFLAL41.163.0211.413.7+2.315+3.0
25Warren Foegele · LOTTL11.093.9613.815.6+1.824+3.0
26Nikolaj Ehlers · LCARL3·PP13.133.9716.617.5+0.968+3.0
27Eric Robinson · LCARL41.414.0111.413.5+2.120+3.0
28Jesperi Kotkaniemi · CCARL41.133.0111.413.4+2.019+3.0
29Logan Stankoven · CCARL2·PP22.15.7315.516.4+0.949+3.0
30Cutter Gauthier · LANAL1·PP13.156.5317.318.1+0.873+3.0
31Sam Carrick · CBUFL41.253.0510.513.6+3.113+3.0
32Beck Malenstyn · LBUFL40.932.6511.214.3+3.113+3.0
33Radek Faksa · CDALL41.51.7711.714.3+2.617+3.0
34Peyton Krebs · CBUFL32.072.2813.814.8+1.038+3.0
35Sam Steel · CDALL3·PP21.683.3216.117.4+1.335+3.0
36Nick Lardis · LCHIL31.735.1912.714.7+2.021+3.0
37Yegor Sharangovich · CCGYL1·PP21.393.411617.9+1.932+3.0
38Connor Zary · CCGYL2·PP21.414.0514.416.2+1.828+3.0
39Sean Monahan · CCBJL2·PP11.623.8717.118.5+1.439+3.0
40Bobby Brink · RMINL3·PP21.744.4115.216.6+1.436+3.0
41Isak Rosen · RWPGL21.412.6811.514+2.513+3.0
42Michael Misa · CSJSL22.194.5812.814.3+1.530+3.0
43Pavel Zacha · CBOSL2·PP12.984.916.817.6+0.867+3.0
44Tanner Jeannot · LBOSL41.363.0312.614.3+1.722+3.0
45Mark Kastelic · CBOSL41.283.0812.614.4+1.821+3.0
46Anders Lee · LUTAL2·PP21.976.4315.616.9+1.343+3.0
47Zachary Bolduc · RMTLL4·PP21.74.1313.614.8+1.233+3.0
48Denton Mateychuk · DCBJD1·PP21.290.9219.221+1.830+3.0
49Paul Cotter · LVANL2·PP21.063.4810.713.6+2.916+3.0
50Tom Willander · DVAND2·PP21.060.451719.1+2.125+3.0
51Fabian Zetterlund · LOTTL2·PP21.874.4212.913.9+1.036+3.0
52Louis Crevier · DBUFD31.120.7217.118.5+1.421+2.0
53Jordan Staal · CCARL3·PP21.784.5916.217.3+1.133+2.0
54Nick Jensen · DANAD20.980.231718.3+1.318+2.0
55Jonatan Berggren · RSTLL31.882.913.814.9+1.125+2.0
56Cole Smith · RCHIL40.863.6513.315.3+2.013+2.0
57Oliver Moore · CCHIL3·PP21.752.7612.814.2+1.426+2.0
58Joel Farabee · LCGYL3·PP11.653.4216.917.8+0.938+2.0
59Michael McCarron · CMINL40.922.221415.5+1.516+2.0
60Nick Paul · CTORL3·PP21.293.9513.715+1.325+2.0

per-60 x projected TOI (2026-27 role) x projected GP; pts_gain = points added by the minutes change alone. All-situations rates from last season, shrunk toward the projection model by sample size (p60 is the raw measured rate, p60_used drives the total). Projected minutes are normalised so each club's lineup fits the 300 skater-minutes a game actually has. iSCF/60 is individual scoring chances per 60 — shot attempts our xG model prices at 0.08 or better. Points per 60 can ride good linemates; chance rate is the player's own, so the two agreeing is the stronger breakout signal.

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