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Projections

Every headline stat per skater over the full 2026-27 regular season (Sep 29, 2026 – Apr 10, 2027), ranked by shots on goal. 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.

589 forwards · sorted by shots on goal · assumes no games missed

#
Skater
PTS
G
A
HIT
BLK
PIM
401
Nils HoglanderNSH · L
23.6
10.6
12.9
96.4
0.7
98.5
22.0
30.8
84
402
Arttu HyryDAL · R29 sample
18.9
9.8
9.1
96.3
0.6
128.1
32.8
8.8
84
403
Brendan GaunceBOS · C
18.2
6.4
11.8
96.3
0.4
143.4
58.6
35.4
84
404
Alexey ToropchenkoSTL · R
18.2
7.2
11.0
96.2
0.1
190.1
63.6
33.4
84
405
Nate DanielsonDET · C28 sample
22.2
6.5
15.6
95.7
8.9
29.3
29.8
13.9
84
406
Nikita NesterenkoANA · C
26.0
7.3
18.8
95.6
0.4
158.6
26.0
19.5
84
407
Matt LuffNYI · R
21.7
13.8
7.9
95.6
1.5
116.7
54.5
9.5
84
408
Luke KuninFLA · C
17.8
9.1
8.7
95.5
1.3
182.9
70.3
69.7
84
409
Sonny MilanoWSH · L
29.3
14.5
14.8
95.5
3.4
33.7
16.4
14.5
84
410
Marcus FolignoMIN · L
26.6
14.3
12.4
95.4
1.9
289.6
58.8
93.3
84
411
Vinnie HinostrozaCOL · C
23.9
8.8
15.1
95.1
3.3
59.6
33.4
35.6
84
412
Nick CousinsOTT · C
23.3
8.9
14.4
95.0
0.3
164.1
41.6
80.4
84
413
Jordan GreenwayCHI · L
20.9
8.6
12.3
95.0
0.9
167.2
56.5
66.1
84
414
Jakob PelletierTBL · L
26.8
9.9
16.9
94.4
1.3
85.3
37.0
15.0
84
415
Gavin BrindleyCOL · C
20.1
9.2
10.9
94.0
0.3
56.9
24.0
12.9
84
416
Taylor WardLAK · R38 sample
17.9
8.2
9.7
94.0
1.5
89.2
22.6
16.9
84
417
Dryden HuntCGY · L
20.4
6.4
14.0
93.6
0.7
200.4
35.6
38.3
84
418
Zemgus GirgensonsTBL · C
16.4
7.6
8.8
93.4
0.3
200.4
51.3
36.3
84
419
Sam SteelDAL · C
31.4
10.1
21.2
92.8
1.9
83.7
32.9
31.6
84
420
Danila YurovMIN · R
32.1
13.0
19.1
92.0
6.1
77.6
44.6
36.1
84
421
Casey CizikasNYI · C
19.7
9.5
10.3
91.1
0.5
173.9
63.9
35.2
84
422
John LeonardDET · L37 sample
28.2
14.5
13.7
91.1
11.8
83.5
67.2
6.4
84
423
Taylor RaddyshNYR · R
25.0
9.9
15.0
91.0
2.6
72.0
40.1
18.4
84
424
Nolan FootePHI · L36 sample
13.0
8.1
4.9
90.9
0.8
157.2
30.2
29.7
84
425
Kailer YamamotoUTA · R
33.6
16.5
17.2
90.8
2.6
86.8
28.9
25.3
84
426
Ville KoivunenPIT · R
24.0
7.8
16.2
90.6
10.2
14.2
35.1
23.2
84
427
James MalatestaCBJ · L13 sample
28.0
12.3
15.7
90.2
2.9
229.5
38.6
32.5
84
428
Alex TurcotteLAK · C
23.6
6.3
17.3
90.0
0.5
69.9
43.6
29.6
84
429
Jake EvansMTL · C
32.6
11.9
20.7
90.0
0.2
117.4
63.3
34.3
84
430
Carson MeyerBUF · R
18.0
6.8
11.2
89.7
2.1
173.5
31.4
27.1
84
431
Rodrigo AbolsPHI · C
20.5
6.6
13.9
89.6
0.3
97.7
48.3
38.1
84
432
Lucas CondottaMTL · L11 sample
20.3
12.7
7.6
89.6
2.6
119.7
44.7
12.8
84
433
Mathieu JosephEDM · R
24.0
6.1
17.9
89.3
0.4
178.7
57.5
37.9
84
434
Adam KlapkaCGY · R
20.3
8.1
12.2
89.2
1.9
306.4
55.4
114.4
84
435
Georgii MerkulovCOL · C11 sample
17.0
4.1
12.9
89.1
2.4
47.5
73.7
23.7
84
436
Ben MeyersSEA · C
20.8
9.8
10.9
89.1
0.2
102.6
22.7
24.7
84
437
Noah OstlundBUF · C
40.1
14.6
25.5
88.9
7.3
9.4
40.4
21.3
84
438
Fedor SvechkovCOL · C
22.2
7.0
15.2
88.3
2.3
67.6
37.5
25.2
84
439
Zack MacEwenTOR · C
11.4
5.8
5.6
88.3
0.5
172.9
31.1
93.8
84
440
Sam CarrickBUF · C
18.6
8.9
9.7
88.0
0.3
138.8
40.0
79.1
84
441
Brad LambertWPG · C31 sample
21.6
9.4
12.2
88.0
3.4
76.1
27.9
22.5
84
442
Alex Barré-BouletSJS · C
25.2
11.3
13.9
87.8
4.2
78.2
21.3
26.2
84
443
Nikita ChibrikovWPG · R16 sample
14.7
8.8
5.9
87.7
3.9
133.4
47.6
82.5
84
444
Colin BlackwellDAL · C
18.8
6.6
12.2
87.6
0.6
129.2
38.6
34.5
84
445
Zachary Aston-ReesePHI · C
17.3
6.0
11.2
87.5
0.2
207.7
56.2
31.9
84
446
Lukas ReichelBOS · L
25.0
9.2
15.9
87.4
2.0
30.1
39.1
16.2
84
447
John HaydenSEA · C
10.2
5.2
5.1
87.4
0.8
166.3
64.7
104.3
84
448
Gage GoncalvesTBL · C
34.8
12.0
22.8
87.3
3.0
101.8
31.8
36.6
84
449
Jonathan LekkerimäkiVAN · R39 sample
29.6
15.8
13.8
87.2
3.2
55.5
26.1
5.3
84
450
Tanner JeannotBOS · L
21.8
8.3
13.5
86.8
1.1
273.6
57.8
90.9
84

No consistency figure for shots on goal: it has not passed the check this site requires, which is not a finding that shots on goal 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