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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 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.

322 defencemen · sorted by points · assumes no games missed

#
Skater
PTS
G
A
HIT
BLK
PIM
251
Erik GudbransonCBJ · D
15.4
3.4
12.0
89.3
0.2
109.9
149.3
53.6
84
252
Kevin KorchinskiCHI · D
15.3
4.2
11.2
80.8
3.9
27.9
84.3
27.9
84
253
Colton WhiteCBJ · D
15.3
0.9
14.4
57.1
0.5
80.8
59.9
11.6
84
254
Charles Alexis LegaultCAR · D13 sample
15.3
7.0
8.3
90.2
1.0
91.7
71.6
83.9
84
255
Connor MackeyCHI · D39 sample
15.3
5.9
9.4
82.9
1.6
120.3
70.7
122.4
84
256
Connor CliftonBOS · D
15.2
3.1
12.1
73.6
0.1
256.8
130.3
71.6
84
257
Ilya LyubushkinNSH · D
15.2
1.4
13.8
54.7
0.1
123.3
141.3
50.4
84
258
Ian MooreANA · D
15.0
5.6
9.5
87.8
0.2
70.9
93.0
28.1
84
259
Ty EmbersonEDM · D
14.8
2.3
12.5
60.4
0.3
141.2
113.5
22.3
84
260
Carson SoucyCBJ · D
14.8
5.3
9.5
78.7
0.5
128.3
107.7
48.0
84
261
Pierre-Olivier JosephVAN · D
14.6
2.6
12.0
75.0
0.6
65.4
67.3
43.1
84
262
Elias SalomonssonWPG · D32 sample
14.6
3.3
11.3
99.3
3.0
129.6
70.8
32.0
84
263
Jack AhcanNSH · D22 sample
14.4
1.9
12.4
58.0
1.3
69.9
74.7
19.2
84
264
Brayden PachalCGY · D
14.4
3.0
11.4
69.5
0.2
186.9
92.0
95.7
84
265
Alexander PetrovicFLA · D
14.3
3.4
10.9
83.6
0.2
145.8
108.2
63.0
84
266
Troy StecherTOR · D
14.2
3.6
10.6
79.5
0.1
53.7
95.4
31.5
84
267
Kyle CapobiancoDAL · D
14.1
5.7
8.4
53.4
0.7
40.3
68.0
29.5
84
268
Jacob BrysonDET · D
14.0
2.4
11.6
39.0
0.6
31.1
68.8
17.1
84
269
Justin HollWSH · D
13.9
3.2
10.7
53.9
0.2
80.9
94.8
34.3
84
270
Joshua MahuraSEA · D
13.8
2.1
11.8
70.0
0.2
106.8
96.7
44.7
84
271
Nick SeelerPHI · D
13.8
3.9
9.9
93.8
0.1
139.6
182.3
59.9
84
272
Zach BogosianMIN · D
13.7
3.6
10.1
75.5
0.1
107.1
80.4
47.2
84
273
Dakota MermisTOR · D
13.7
6.5
7.2
67.7
0.6
73.2
86.2
65.7
84
274
Jake BeanCGY · D
13.6
4.4
9.2
92.4
0.7
31.4
98.5
35.6
84
275
Lian BichselDAL · D
13.6
6.2
7.4
58.3
0.2
264.2
61.2
74.7
84
276
Zach MetsaBUF · D
13.6
5.7
7.8
48.3
2.0
12.8
64.5
32.5
84
277
Joshua BrownEDM · D
13.5
4.2
9.4
78.6
0.5
176.6
136.3
100.6
84
278
Tobias BjornfotFLA · D
13.4
5.7
7.8
60.6
0.5
71.0
88.3
13.6
84
279
Ryan JohnsonBUF · D
13.4
1.7
11.7
67.3
1.0
34.9
82.2
40.0
84
280
Spencer StastneyEDM · D
13.3
2.8
10.5
69.0
0.2
19.7
83.0
23.6
84
281
Noah JuulsenCOL · D
13.2
1.4
11.7
46.2
0.2
197.4
98.5
33.5
84
282
William LagessonDET · D
13.1
1.6
11.4
59.7
0.9
129.0
99.9
56.4
84
283
Brandon CarloSTL · D
12.9
2.0
10.9
94.8
0.1
110.3
152.3
47.1
84
284
Jeremy LauzonVGK · D
12.8
2.1
10.7
90.3
0.1
323.0
117.8
97.7
84
285
Riley StillmanEDM · D
12.4
2.8
9.7
57.7
0.9
145.7
73.9
52.4
84
286
Luke SchennVAN · D
12.4
1.8
10.6
78.7
0.1
288.9
101.1
71.4
84
287
Ethan Del MastroCHI · D
12.3
3.4
9.0
76.9
0.5
105.2
85.6
55.1
84
288
Haydn FleuryWPG · D
12.3
3.0
9.3
70.6
0.2
116.1
120.5
30.6
84
289
Albert JohanssonDET · D
12.1
3.5
8.5
64.7
0.1
68.6
99.9
23.4
84
290
Ryan GravesPIT · D
12.0
3.8
8.2
84.9
0.2
93.6
136.6
36.9
84
291
Elias PetterssonVAN · D
11.6
3.6
8.0
58.5
0.2
153.0
97.7
49.0
84
292
Tim BerniCBJ · D
11.6
4.2
7.4
93.4
1.8
158.7
97.6
46.8
84
293
Travis HamonicDET · D
11.5
2.4
9.1
97.6
0.3
105.7
135.0
61.0
84
294
Steven SantiniTBL · D18 sample
11.4
1.9
9.5
46.3
1.1
70.9
60.8
18.0
84
295
Cale FleurySEA · D
11.1
3.3
7.8
85.5
0.5
178.5
127.7
20.1
84
296
Owen PickeringPIT · D29 sample
11.0
3.8
7.2
53.0
0.9
45.2
59.7
27.1
84
297
Vincent IorioNYR · D37 sample
10.9
0.9
10.0
54.1
0.5
49.8
112.7
35.0
84
298
Matthew KesselNYI · D
10.8
3.9
6.9
59.1
0.3
68.8
84.0
28.7
84
299
Declan CarlilePIT · D
10.8
3.1
7.7
72.1
0.3
108.4
72.8
82.7
84
300
Jacob Bernard-DockerDET · D
10.8
2.6
8.1
60.3
0.2
81.0
123.9
33.6
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