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Projections

Every headline stat per skater over the full 2026-27 regular season (Sep 29, 2026 – Apr 10, 2027), ranked league-wide by points. Each total assumes the skater plays every one of his team’s games.

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PTS PointsG GoalsA AssistsSOG Shots on goalPPP Power-play pointsHIT HitsBLK Blocked shotsPIM Penalty minutes
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Average weekFull-season pace
Position
AllF ForwardsC CentresLW Left wingsRW Right wingsD Defencemen
How the shading works — a stronger shade means more, not better, and a skater on a thin sample is left plain

Each figure sits on a tile shaded by its share of that stat’s leading projection in this view, in five steps from zero to the leader. Hits and penalty minutes shade the way points do. The leader is the league’s, among skaters whose rate rests on at least 41 real games, so a shade means the same on every page and under every filter. A skater with fewer is left unshaded, his sample marked beside his name.

911 skaters · sorted by points · assumes no games missed

#
Skater
PTS
G
A
HIT
BLK
PIM
651
Jacob MacDonaldWSH · D
19.2
10.2
9.0
119.0
6.1
99.7
52.7
44.8
84
652
Declan ChisholmNJD · D
19.2
3.7
15.5
82.0
2.9
39.1
85.0
17.1
84
653
Tyler MyersDAL · D
19.1
3.2
15.9
104.1
0.4
110.2
146.9
70.6
84
654
Colin MillerWPG · D
19.1
4.6
14.5
103.9
3.5
130.0
69.1
44.5
84
655
Guillaume BriseboisVAN · D21 sample
19.1
6.9
12.2
89.4
2.9
71.4
104.6
25.4
84
656
Nils LundkvistDAL · D
19.1
3.8
15.3
88.7
1.0
49.5
74.3
29.6
84
657
Liam FoudyNYI · C
19.1
6.8
12.3
82.9
1.1
72.6
35.6
13.8
84
658
Braden SchneiderNYR · D
19.0
3.8
15.3
101.9
0.1
164.6
141.4
28.1
84
659
Tyler TuckerSTL · D
19.0
4.8
14.3
80.1
0.2
142.0
69.0
104.4
84
660
Marc Del GaizoNYR · D
19.0
4.1
14.9
133.1
0.6
132.4
94.5
36.9
84
661
Isaac HowardEDM · L31 sample
19.0
5.6
13.4
113.2
0.5
27.5
15.9
31.1
84
662
Trevor van RiemsdykPIT · D
19.0
2.7
16.3
69.8
0.2
18.1
138.0
26.1
84
663
Arttu HyryDAL · R29 sample
18.9
9.8
9.1
96.3
0.6
128.1
32.8
8.8
84
664
Chris TanevTOR · D
18.9
2.9
16.0
58.8
0.3
39.8
204.6
21.9
84
665
Emil AndraeCBJ · D
18.8
2.6
16.2
61.1
2.5
95.7
84.1
32.3
84
666
Jonathan AspirotBOS · D
18.8
4.0
14.9
65.3
1.4
122.4
115.5
54.4
84
667
Nick DeSimoneUTA · D
18.8
4.6
14.2
79.4
0.3
49.5
69.7
16.8
84
668
Colin BlackwellDAL · C
18.8
6.6
12.2
87.6
0.6
129.2
38.6
34.5
84
669
Mattias JanmarkEDM · C
18.8
4.8
13.9
62.0
0.1
47.1
31.4
38.4
84
670
Dante FabbroCBJ · D
18.8
6.7
12.1
91.0
0.2
79.5
144.7
41.1
84
671
Bo GroulxTOR · C
18.7
9.7
9.1
83.6
0.6
195.4
44.0
18.7
84
672
Corey SchuenemanANA · D35 sample
18.7
6.1
12.5
106.1
3.4
58.0
120.5
19.4
84
673
Logan MaillouxSTL · D
18.7
7.3
11.3
103.5
1.4
115.7
71.5
60.0
84
674
Cole SchwindtFLA · C
18.6
9.1
9.5
69.8
0.3
99.4
33.7
5.4
84
675
Sam CarrickBUF · C
18.6
8.9
9.7
88.0
0.3
138.8
40.0
79.1
84
676
Cam DineenPHI · D38 sample
18.6
4.7
13.9
143.0
2.7
59.5
101.4
16.8
84
677
Brett KulakCOL · D
18.5
3.5
15.1
103.8
0.2
41.5
116.2
33.7
84
678
Riley TufteNJD · L28 sample
18.5
12.3
6.2
73.6
8.9
125.3
29.1
27.8
84
679
Vinni LettieriTOR · C
18.5
10.0
8.5
129.9
1.5
142.9
51.3
30.4
84
680
Trent FredericEDM · C
18.5
9.7
8.8
102.5
1.1
220.9
36.4
68.7
84
681
Emil LillebergTBL · D
18.4
3.7
14.8
62.4
0.1
158.2
74.6
95.4
84
682
Radko GudasFLA · D
18.4
2.9
15.5
97.1
0.7
273.5
154.5
100.5
84
683
Johnathan KovacevicNJD · D
18.3
2.2
16.1
77.7
0.2
117.5
99.0
74.3
84
684
Libor HajekSJS · D33 sample
18.3
7.7
10.6
92.1
3.3
83.4
95.7
32.7
84
685
Colton DachEDM · C
18.3
6.3
12.0
86.2
2.2
293.7
39.4
65.1
84
686
Hunter BrzustewiczCGY · D35 sample
18.2
5.4
12.8
85.5
2.8
62.0
56.7
13.7
84
687
David KampfWSH · C
18.2
6.7
11.5
81.7
0.1
87.9
41.0
21.0
84
688
Alexey ToropchenkoSTL · R
18.2
7.2
11.0
96.2
0.1
190.1
63.6
33.4
84
689
Matt BenningTOR · D
18.2
1.6
16.5
74.7
1.1
106.3
129.4
42.8
84
690
Noah GregorWPG · L
18.2
8.7
9.4
115.2
1.5
131.4
39.3
46.2
84
691
Brendan GaunceBOS · C
18.2
6.4
11.8
96.3
0.4
143.4
58.6
35.4
84
692
Nick PerbixNSH · D
18.2
4.1
14.0
81.3
0.1
50.7
97.2
23.7
84
693
Jaroslav ChmelarNYR · R29 sample
18.1
11.4
6.8
74.0
0.5
150.8
46.3
31.4
84
694
Wyatt KaiserCHI · D
18.1
5.8
12.3
83.2
0.1
56.1
96.0
33.4
84
695
Andre LeeLAK · L27 sample
18.1
7.5
10.6
78.6
0.8
161.7
39.5
42.9
84
696
Carson MeyerBUF · R
18.0
6.8
11.2
89.7
2.1
173.5
31.4
27.1
84
697
Taylor WardLAK · R38 sample
17.9
8.2
9.7
94.0
1.5
89.2
22.6
16.9
84
698
Will BorgenBOS · D
17.8
5.0
12.8
82.4
0.1
143.6
110.2
47.4
84
699
Tyler KlevenOTT · D
17.8
3.8
14.1
97.0
0.5
141.1
108.2
51.4
84
700
Justin BarronNSH · D
17.8
4.7
13.2
75.1
1.0
83.0
101.0
29.5
84

No consistency figure for points: it has not passed the check this site requires, which is not a finding that points is inconsistent.

Why there is no figure — a figure must repeat across a skater’s own games before it is shown

Before it shows a consistency figure, the site checks that the figure from a skater’s odd-numbered games agrees with the one from his even-numbered games, across skaters, more than chance would. That check withholds a figure both when a stat is measurably no better than chance and when the evidence is too split to call, and from here the two cannot be told apart. Sort by another stat to see the tag where it holds. Measured 2026-10-02.

How the projections are built — a rate over every season since 2021-22, recent games weighted more, times the club’s schedule

A skater’s rate is his per-game output over every season since 2021-22, each season weighted half as much as the one after it, and pulled a little toward the league rate so a handful of games cannot top the board. The weighting was chosen by testing which one best predicted the rest of a season from the games before it. A skater needs ten games to appear here.

Each total is that rate times his club’s scheduled games. A full-season pace counts every scheduled game, played or not.

Availability is not projected: Team games is the club’s schedule, not a forecast of how many games the player dresses for, and injuries, scratches and trades are not modelled.

How well does projection ordering hold? View the ordering study

Scoring per dollar of cap hit has a board of its own: Cap efficiency