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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 goals. 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
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.

322 defencemen · sorted by goals · assumes no games missed

#
Skater
PTS
G
A
HIT
BLK
PIM
101
Alexandre CarrierMTL · D
28.1
7.0
21.1
75.2
0.4
65.6
179.1
49.2
84
102
Sean WalkerCAR · D
24.5
7.0
17.5
160.2
0.8
146.3
121.0
56.2
84
103
Jared SpurgeonMIN · D
28.7
7.0
21.7
111.7
7.4
81.3
153.2
18.9
84
104
Adam LarssonSEA · D
25.9
7.0
18.9
116.6
0.1
133.5
160.8
42.2
84
105
Cam FowlerSTL · D
39.8
6.9
32.9
104.7
12.4
16.8
92.0
16.4
84
106
Charle-Edouard D'AstousTBL · D
33.7
6.9
26.8
96.2
3.5
119.4
89.1
125.4
84
107
Guillaume BriseboisVAN · D21 sample
19.1
6.9
12.2
89.4
2.9
71.4
104.6
25.4
84
108
Samuel BolducOTT · D
16.0
6.8
9.1
87.5
2.8
107.3
85.7
20.2
84
109
Aaron EkbladFLA · D
37.8
6.8
31.0
138.2
11.0
125.7
109.4
73.5
84
110
Ryan SheaEDM · D
30.8
6.8
24.0
67.6
0.5
44.7
94.5
23.6
84
111
Dante FabbroCBJ · D
18.8
6.7
12.1
91.0
0.2
79.5
144.7
41.1
84
112
Dakota MermisTOR · D
13.7
6.5
7.2
67.7
0.6
73.2
86.2
65.7
84
113
Uvis BalinskisFLA · D
20.9
6.5
14.5
99.7
6.6
106.6
64.3
49.2
84
114
J.J. MoserTBL · D
28.2
6.5
21.8
100.3
2.2
72.0
109.2
57.9
84
115
Hampus LindholmBOS · D
34.4
6.4
28.0
127.1
5.8
35.0
119.3
66.5
84
116
Logan StanleyNYI · D
22.3
6.4
15.9
89.7
0.8
128.3
98.3
139.2
84
117
Zeev BuiumVAN · D
27.4
6.3
21.1
85.2
13.7
32.0
61.1
44.0
84
118
Ronnie AttardDET · D29 sample
22.6
6.3
16.3
112.7
2.7
133.5
87.6
40.4
84
119
Jordan OesterleNSH · D
19.2
6.3
12.9
86.4
0.5
67.7
119.5
15.3
84
120
Vladislav KolyachonokNJD · D
20.1
6.2
13.9
65.7
0.5
57.5
79.7
25.3
84
121
Lian BichselDAL · D
13.6
6.2
7.4
58.3
0.2
264.2
61.2
74.7
84
122
Jordan SpenceOTT · D
31.4
6.2
25.3
108.5
4.3
75.3
74.9
21.3
84
123
Corey SchuenemanANA · D35 sample
18.7
6.1
12.5
106.1
3.4
58.0
120.5
19.4
84
124
Mario FerraroWPG · D
21.6
6.1
15.5
96.7
0.2
146.1
157.0
40.8
84
125
Yan KuznetsovCGY · D
17.7
6.0
11.8
95.6
0.3
117.2
145.2
39.7
84
126
Ryan McDonaghTBL · D
32.2
5.9
26.3
81.1
1.1
47.8
149.4
23.2
84
127
Connor MackeyCHI · D39 sample
15.3
5.9
9.4
82.9
1.6
120.3
70.7
122.4
84
128
Tom WillanderVAN · D
26.4
5.9
20.5
68.7
3.5
41.4
92.5
36.4
84
129
Daniil MiromanovCGY · D
20.0
5.9
14.2
111.4
2.7
37.4
104.6
23.5
84
130
Jonas BrodinMIN · D
27.0
5.8
21.1
113.7
1.3
30.4
179.4
25.6
84
131
Jamie OleksiakVAN · D
20.2
5.8
14.4
82.9
0.1
116.8
138.2
42.0
84
132
Esa LindellDAL · D
28.0
5.8
22.2
99.4
1.3
51.4
177.6
19.8
84
133
Derrick PouliotCHI · D24 sample
24.1
5.8
18.3
92.3
3.4
90.8
83.2
33.5
84
134
Wyatt KaiserCHI · D
18.1
5.8
12.3
83.2
0.1
56.1
96.0
33.4
84
135
Zach MetsaBUF · D
13.6
5.7
7.8
48.3
2.0
12.8
64.5
32.5
84
136
Kyle CapobiancoDAL · D
14.1
5.7
8.4
53.4
0.7
40.3
68.0
29.5
84
137
Cam YorkPHI · D
26.5
5.7
20.9
103.5
5.2
55.3
164.7
34.0
84
138
Tobias BjornfotFLA · D
13.4
5.7
7.8
60.6
0.5
71.0
88.3
13.6
84
139
Josh MansonCOL · D
31.6
5.7
25.9
132.4
0.4
199.4
104.7
86.8
84
140
Sam RinzelCHI · D
22.7
5.7
17.0
137.0
3.5
77.4
92.0
58.6
84
141
Martin FehérváryWSH · D
26.2
5.6
20.6
80.8
0.1
151.0
166.1
35.3
84
142
Ethan BearNYI · D
20.9
5.6
15.3
107.4
1.1
64.5
96.9
34.2
84
143
Ian MooreANA · D
15.0
5.6
9.5
87.8
0.2
70.9
93.0
28.1
84
144
Connor MurphyEDM · D
19.3
5.5
13.7
89.0
0.1
123.8
173.6
66.5
84
145
Kaiden GuhleMTL · D
27.3
5.5
21.8
91.8
0.1
177.3
165.2
97.3
84
146
Nate SchmidtUTA · D
24.0
5.4
18.6
89.7
3.2
83.8
91.5
22.9
84
147
Hunter BrzustewiczCGY · D35 sample
18.2
5.4
12.8
85.5
2.8
62.0
56.7
13.7
84
148
Carson SoucyCBJ · D
14.8
5.3
9.5
78.7
0.5
128.3
107.7
48.0
84
149
Rasmus RistolainenPHI · D
26.8
5.3
21.5
123.4
2.5
129.5
124.9
39.0
84
150
Jordan HarrisBOS · D
20.2
5.3
15.0
71.4
0.5
56.4
102.9
22.1
84

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