Explore player impact ratings, advanced statistics, and league-wide performance trends.
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Established samples only: at least 50 weighted games and 300 weighted five-on-five minutes. Scores are position-adjusted indices, not additive wins. New and old scores are not directly comparable.
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Projected Impact leaders
Highest experimental impact scores in the selected population. This ranking measures modeled impact, not a calibrated measure of wins.
Talent Distribution
Projected Impact distribution
Score above 50Score 50 or below
A population view of modeled impact. Filters update every chart and summary metric on this page.
Research & Projects
Player impact. Hockey insights.
Explore our player analysis and research archive. Archived projects reflect earlier model versions, not current player impact ratings.
Research libraryPlayer analysisTwo archived projects
Archived research: these figures use the earlier experimental WAR proxy, not a newly validated wins-above-replacement model.
Breakout Forecast • August 2026
20 NHL Breakout Candidates for 2026–27
A model-driven search for young skaters with the projected impact, offensive skill, recent momentum, and development runway to take a meaningful step forward.
Model leaderSchaefer80.6 breakout score
Candidate pool142Eligible skaters age 25 or younger
Headline board2018 Tier 1 • 2 Tier 2
Top projected WAR2.73Matvei Michkov
01 • Methodology
Finding the space between prospect status and established stardom.
The breakout screen starts with skaters age 25 or younger who carry at least 60 weighted games, 0.65 projected WAR, and a 48th-percentile overall rating in the current Wolff Analytics model. Players already projecting at 3.0 WAR—or with a substantial sample and a 90th-percentile WAR or overall rating—are tracked separately as established young stars.
The 0–100 breakout score is an index, not a literal probability. It weights projected impact (25%), offensive skill (20%), age runway (15%), experience runway (15%), recent offense and finishing momentum (15%), and overall NHL floor (10%). The purpose is to identify strong research candidates, not to replace role, health, or roster-context analysis.
Projected impact
WAR percentile anchors the ranking in the core player model.
Offensive skill
Offense, goals, primary assists, power play, and finishing reveal different paths to a leap.
Development runway
Younger, less-established players retain more room for a genuine breakout.
Recent momentum
The two latest seasons test whether offense and finishing are moving in the right direction.
Two calibration safeguards matter. First, a 0.65 projected-WAR floor prevents eye-catching skill percentiles from overwhelming weak projected impact. Second, “already established” requires elite impact plus meaningful experience rather than relying on a single overall percentile.
02 • The top 20
Schaefer leads a board rich in young skill and immediate opportunity.
Rank
Player
Team
Pos
Age
Score
Proj. WAR
1
Matthew Schaefer
NYI
D
18
80.6
2.09
2
Beckett Sennecke
ANA
R
20
80.0
2.47
3
Ryan Leonard
WSH
R
21
78.1
2.10
4
Jimmy Snuggerud
STL
R
22
77.7
1.83
5
Matthew Wood
NSH
R
21
77.1
1.64
6
Ben Kindel
PIT
C
19
76.0
1.91
7
Alexander Nikishin
CAR
D
24
75.0
2.27
8
Ivan Demidov
MTL
R
20
74.6
2.35
9
Easton Cowan
TOR
RW
21
74.6
1.39
10
Zeev Buium
VAN
D
20
72.5
1.81
11
Axel Sandin-Pellikka
DET
D
21
72.4
1.47
12
Matvei Michkov
PHI
R
21
72.1
2.73
13
Gabe Perreault
NYR
R
21
72.1
0.97
14
Michael Misa
SJS
C
19
72.1
0.65
15
Calum Ritchie
NYI
C
21
71.6
1.68
16
Noah Ostlund
BUF
C
22
71.3
0.97
17
Arseny Gritsyuk
NJD
R
25
71.2
1.36
18
Denver Barkey
PHI
C
21
70.9
0.77
19
Mavrik Bourque
NSH
C
24
69.0
2.44
20
Denton Mateychuk
CBJ
D
22
69.0
1.48
03 • Leading cases
Five different routes to a breakout.
Matthew Schaefer • NYI
An 80.6 score pairs 2.09 projected WAR with 91st-percentile finishing, 86th-percentile offense, and the strongest age runway on the board.
Beckett Sennecke • ANA
The highest projected WAR among the top five (2.47), supported by 97th-percentile offense and 89th-percentile primary-assist creation.
Ryan Leonard • WSH
A balanced scoring profile—92nd-percentile primary assists and 91st-percentile finishing—creates more than one path to a larger role.
Jimmy Snuggerud • STL
Goal generation and primary-assist creation both sit in the 89th percentile, while recent momentum supplies another positive signal.
Alexander Nikishin • CAR
The leading older breakout case combines 2.27 projected WAR with 97th-percentile offense and 90th-percentile power-play impact from defense.
Matvei Michkov • PHI
The board’s highest projected WAR at 2.73. His 93rd-percentile primary-assist creation and 89th-percentile goal generation create the clearest immediate star-upside case.
04 • How to read the list
A breakout score identifies where to investigate next.
The list does not directly project points, awards, or a guaranteed role. Line assignment, power-play deployment, injuries, coaching changes, shooting regression, and roster openings can materially change the outcome. A lower-ranked player with a major opportunity gain can outperform a higher-ranked player whose path is blocked.
The next stage is contextual review and historical backtesting: testing what would have counted as a successful breakout in prior seasons, then adding opportunity variables before converting this board into player-specific production forecasts.
Source: Wolff Analytics’ current three-season weighted player model and 2026–27 projection snapshot. Breakout score and eligibility methodology developed August 17, 2026.
Archived research: these figures use the earlier experimental WAR proxy, not a newly validated wins-above-replacement model.
Projected WAR Leaders • August 2026
The NHL’s Top 10 Players at Every Position by Projected WAR
A model-driven look at the skaters expected to create the most wins above replacement at center, left wing, right wing, and defense.
Model leaderMacKinnon4.28 projected WAR
Highest projection4.28Nathan MacKinnon
Closest elite race0.06Separates the top three centers
Youngest top-ten skater22Lane Hutson
01 • Methodology
A projection of impact—not a subjective talent ranking.
WAR estimates a player’s total contribution relative to a replacement-level NHL skater. These rankings use Wolff Analytics’ current three-season weighted projection and require a minimum 50-game weighted sample. Players are assigned to their model-listed primary position, with left- and right-wing labels normalized across data sources.
The results are best read as a forecast of expected on-ice impact under the model—not a trophy ballot, trade-value ranking, or prediction of career value. Goaltenders are excluded because the current projected-WAR pipeline is built for skaters.
02 • Centers
Three superstars are separated by six hundredths of a win.
MacKinnon leads the entire model, but Draisaitl and McDavid are effectively alongside him. Crosby’s fifth decade of NHL life remains extraordinary: even after aging considerations, his recent impact keeps him fourth among centers. Jack Hughes is the youngest member of the group.
Rank
Player
Team
Age
Projected WAR
1
Nathan MacKinnon
COL
30
4.28
2
Leon Draisaitl
EDM
30
4.23
3
Connor McDavid
EDM
29
4.22
4
Sidney Crosby
PIT
38
3.86
5
Martin Necas
COL
27
3.80
6
Jack Hughes
NJD
25
3.70
7
Brayden Point
TBL
30
3.65
8
Sam Reinhart
FLA
30
3.59
9
John Tavares
TOR
35
3.59
10
Mark Scheifele
WPG
33
3.58
03 • Left wings
Robertson leads a deep and tightly packed group.
Jason Robertson moves to the top after the audit, followed by Panarin, Kaprizov, and Matthew Tkachuk. Ehlers’ balanced five-on-five profile keeps him sixth. Hyman remains a top-ten left wing, but age and availability regression move him from first to tenth.
Rank
Player
Team
Age
Projected WAR
1
Jason Robertson
DAL
27
3.97
2
Artemi Panarin
LAK
34
3.90
3
Kirill Kaprizov
MIN
29
3.89
4
Matthew Tkachuk
FLA
28
3.89
5
Jesper Bratt
NJD
28
3.67
6
Nikolaj Ehlers
CAR
30
3.48
7
Lucas Raymond
DET
24
3.46
8
Filip Forsberg
NSH
31
3.44
9
Brady Tkachuk
FLA
26
3.39
10
Zach Hyman
EDM
34
3.38
04 • Right wings
Kucherov owns the clearest positional lead.
Kucherov is the only right wing above four projected wins. DeBrincat remains fourth after a deeper review of his 41-goal season and strong five-on-five expected-goal results. Caufield’s 51-goal breakout supports seventh, while age regression moves Patrick Kane outside the top ten.
Rank
Player
Team
Age
Projected WAR
1
Nikita Kucherov
TBL
33
4.10
2
Pavel Dorofeyev
NYR
25
3.74
3
Mikko Rantanen
DAL
29
3.70
4
Alex DeBrincat
DET
28
3.68
5
David Pastrnak
BOS
30
3.67
6
Clayton Keller
UTA
28
3.65
7
Cole Caufield
MTL
25
3.62
8
William Nylander
TOR
30
3.58
9
Mitch Marner
VGK
29
3.47
10
Drake Batherson
OTT
28
3.47
05 • Defense
Hughes and Bouchard form a distinct leading tier.
Quinn Hughes leads the position, with Bouchard comfortably second. Makar moves to third after the audit. Karlsson’s offensive value remains substantial, but age and defensive regression move him outside this top ten. Hutson is the youngest player in any positional ranking.
Rank
Player
Team
Age
Projected WAR
1
Quinn Hughes
MIN
26
3.89
2
Evan Bouchard
EDM
26
3.73
3
Cale Makar
COL
27
3.40
4
Shayne Gostisbehere
CAR
33
3.35
5
Adam Fox
NYR
28
3.34
6
Josh Morrissey
WPG
31
3.33
7
Miro Heiskanen
DAL
27
3.30
8
Jakob Chychrun
WSH
28
3.30
9
Lane Hutson
MTL
22
3.27
10
Darren Raddysh
TOR
30
3.21
06 • Takeaways
Recent impact remains powerful, but context matters.
Center owns the strongest summit
MacKinnon, Draisaitl, and McDavid all exceed 4.20 projected WAR.
Right wing has the clearest leader
Kucherov holds a 0.36-WAR advantage over second place.
The audit changed the story
Verhaeghe moved to left wing, while Hyman, Karlsson, and Kane received stronger age and role regression.
Age is not destiny
Veterans remain prominent when recent results support them, but projections distinguish demonstrated impact from likely future availability.
Data sources: Wolff Analytics’ three-season weighted skater model, built from MoneyPuck season summaries, official NHL roster information, and reviewed player-level calibrations. Snapshot generated August 6, 2026.
Trade Builder & Grader
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Compare two- or three-team exchanges without contract dollars or cap calculations. Picks are hypothetical selections—not verified current ownership. Unused third teams can stay empty.
Scenario points and limitations
Established players receive max(0, (Projected Impact − 40) × 2) points. Hypothetical rounds 1–7 receive 30, 12, 6, 3, 2, 1 and 0.5 points. These are transparent, illustrative assumptions, not empirically calibrated trade prices. No adjustment is made for contract control, age beyond the impact model, prospect upside, pick position, year discount, conditions or trade protections. Players with insufficient samples cannot receive a grade.
A package is “similar” when each team's absolute net difference is at most five points or 10% of total exchanged points, whichever is larger. This compares scenario points—not actual trade fairness or team fit. Changing a team clears all selections to prevent stale ownership assignments.
Questions, feedback, or collaboration?
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