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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.

Sort by
PTS PointsG GoalsA AssistsSOG Shots on goalPPP Power-play pointsHIT HitsBLK Blocked shotsPIM Penalty minutes
View
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.

912 skaters · sorted by points · assumes no games missed

#
Skater
PTS
G
A
HIT
BLK
PIM
551
Mikey AndersonLAK · D
22.5
4.5
18.0
79.4
0.2
139.1
139.9
26.2
84
552
Ryan WintertonSEA · C
22.4
4.5
17.9
111.1
0.2
93.1
42.5
17.8
84
553
Mario FerraroWPG · D
22.4
7.0
15.3
98.7
0.2
145.3
158.2
40.3
84
554
Mike ReillyCAR · D
22.4
3.6
18.7
139.4
2.0
47.1
73.2
43.2
84
555
Timothy LiljegrenWSH · D
22.3
4.6
17.8
93.1
4.6
91.1
145.0
43.1
84
556
Logan StanleyNYI · D
22.3
6.4
15.9
89.7
0.8
128.3
98.3
139.2
84
557
Juha JaaskaCAR · L18 sample
22.3
2.6
19.7
66.2
1.5
95.2
24.0
41.8
84
558
Lars EllerFLA · C
22.2
8.6
13.7
105.0
2.1
68.4
43.5
25.4
84
559
Adam WilsbyNSH · D
22.2
2.1
20.1
89.9
0.2
45.1
72.2
37.7
84
560
Fedor SvechkovCOL · C
22.2
7.0
15.2
88.3
2.3
67.6
37.5
25.2
84
561
Noel AcciariPHI · C
22.2
11.0
11.2
100.9
0.1
151.6
92.2
32.5
84
562
Mark KastelicBOS · C
22.0
10.7
11.2
97.0
0.7
234.2
61.9
137.4
84
563
Mason ShawMIN · C
21.9
8.5
13.4
117.5
1.1
120.9
38.0
113.4
84
564
Luca Del Bel BelluzCBJ · C30 sample
21.8
5.6
16.2
83.7
2.5
26.4
62.4
17.6
84
565
Matt LuffNYI · R
21.7
13.8
7.9
95.5
1.5
116.7
54.5
9.5
84
566
Sean KuralyBOS · C
21.6
7.6
14.0
107.0
0.2
137.8
48.9
46.2
84
567
Radek FaksaDAL · C
21.5
5.3
16.2
71.0
0.1
125.1
63.8
31.4
84
568
Tanner JeannotBOS · L
21.5
8.2
13.3
85.7
1.0
275.6
57.1
89.7
84
569
Elmer SoderblomPIT · L
21.5
11.0
10.5
105.4
0.2
144.2
27.1
28.1
84
570
Berkly CattonSEA · C
21.5
8.8
12.7
99.8
2.6
12.6
38.0
38.4
84
571
Nico SturmMIN · C
21.5
9.1
12.4
81.1
0.2
118.2
40.8
22.9
84
572
Nick LeddySJS · D
21.4
3.4
18.0
62.2
0.8
34.3
99.2
15.6
84
573
Joel EdmundsonLAK · D
21.4
3.8
17.6
102.0
1.5
116.9
120.8
32.1
84
574
Kaedan KorczakPIT · D
21.4
2.4
18.9
67.9
0.3
118.1
94.7
20.4
84
575
Jan JenikLAK · C22 sample
21.4
7.4
14.0
79.8
3.1
111.1
61.6
53.9
84
576
Zac JonesUTA · D
21.4
3.5
17.9
98.3
1.6
54.0
78.6
36.6
84
577
Lenni HameenahoNJD · R33 sample
21.4
5.6
15.8
120.4
0.5
53.9
42.3
35.9
84
578
William CarrierCAR · L
21.4
7.8
13.5
100.8
0.2
254.4
26.3
25.8
84
579
Ilya SolovyovPIT · D
21.3
2.8
18.5
66.5
0.4
109.1
94.3
39.8
84
580
Ben HuttonVGK · D
21.3
7.1
14.2
111.2
0.6
45.6
92.3
29.6
84
581
Yakov TreninMIN · C
21.3
7.7
13.5
100.8
0.2
341.6
38.9
44.8
84
582
Brett LeasonSJS · R
21.2
8.4
12.8
97.6
1.6
90.3
55.5
22.6
84
583
Matthew RobertsonNYR · D
21.2
7.1
14.1
93.2
0.2
123.7
92.0
43.6
84
584
Adam PelechNYI · D
21.2
3.3
17.9
126.4
0.4
84.0
130.0
47.6
84
585
Jalen ChatfieldCAR · D
21.1
4.9
16.2
113.5
0.1
61.8
83.3
36.9
84
586
Ivan MiroshnichenkoWSH · L
21.1
9.5
11.6
85.9
2.7
138.7
36.7
12.7
84
587
Max CrozierTBL · D
21.1
2.5
18.6
111.5
0.4
98.2
73.7
83.5
84
588
Zayne ParekhCGY · D39 sample
21.1
9.8
11.3
111.7
12.5
40.4
69.1
20.2
84
589
Matt KierstedMIN · D38 sample
21.1
3.7
17.4
66.6
1.4
43.0
97.5
19.7
84
590
Nathan WalkerSTL · L
21.1
9.6
11.5
78.5
0.1
294.6
67.3
61.5
84
591
Kevin StenlundUTA · C
21.0
8.1
12.8
82.2
0.1
56.6
62.2
34.3
84
592
Jordan GreenwayCHI · L
20.9
8.6
12.3
95.0
0.9
167.2
56.5
66.1
84
593
Uvis BalinskisFLA · D
20.9
6.5
14.5
99.7
6.6
106.6
64.3
49.2
84
594
Ethan BearNYI · D
20.9
5.6
15.3
107.4
1.1
64.5
96.9
34.3
84
595
Joshua RoyUTA · R38 sample
20.9
11.7
9.2
103.7
1.0
72.5
54.6
19.9
84
596
Cole KoepkeWPG · L
20.9
10.4
10.5
104.5
0.1
221.2
26.6
19.9
84
597
Anton BlidhNYR · L
20.8
3.9
16.9
86.5
1.7
168.7
24.8
29.2
84
598
Jack St. IvanyWPG · D
20.8
0.8
20.0
69.4
0.5
184.7
99.9
38.3
84
599
Nate DanielsonDET · C29 sample
20.8
6.1
14.6
95.0
8.4
32.7
27.9
23.6
84
600
Ben MeyersSEA · C
20.8
9.8
10.9
89.1
0.2
102.6
22.7
24.7
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 2026-10-03.

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