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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 assists. 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 assists · assumes no games missed

#
Skater
PTS
G
A
HIT
BLK
PIM
251
Dawson MercerNJD · C
40.6
20.5
20.1
154.5
6.9
40.2
50.8
28.7
84
252
Alexander KerfootNSH · C
32.8
12.7
20.1
96.8
2.9
74.8
67.1
33.8
84
253
Pius SuterSTL · C
39.3
19.3
20.0
132.3
4.5
57.0
36.3
22.3
84
254
Stephen HallidayOTT · C30 sample
31.3
11.4
19.9
97.6
8.4
85.2
25.3
7.8
84
255
Ryan DonatoCHI · C
38.7
18.9
19.8
147.4
5.3
91.4
21.1
48.4
84
256
Hunter McKownMTL · C12 sample
28.0
8.2
19.8
115.2
4.8
95.1
54.4
47.3
84
257
Philip TomasinoOTT · R
32.1
12.3
19.8
129.5
9.0
76.2
39.6
18.5
84
258
Juha JaaskaCAR · L18 sample
22.3
2.6
19.7
66.3
1.5
95.2
24.0
41.8
84
259
Jonathan ToewsWPG · C
31.9
12.3
19.6
112.1
8.9
19.6
35.3
41.3
84
260
Brendan BrissonNYR · C27 sample
24.8
5.3
19.5
86.7
4.4
71.1
23.1
9.3
84
261
Ilya MikheyevTBL · R
38.2
18.8
19.4
140.9
0.5
39.0
23.7
16.6
84
262
Jordan MartinookCAR · L
32.3
12.9
19.4
129.6
0.1
121.3
52.0
37.7
84
263
Jordan StaalCAR · C
38.6
19.3
19.3
126.3
3.9
210.6
50.2
33.4
84
264
Teddy BluegerTOR · C
30.9
11.7
19.3
106.4
0.9
116.9
46.3
40.9
84
265
Adam LowryWPG · C
31.2
12.0
19.2
105.2
0.7
188.7
61.0
44.6
84
266
Connor ZaryCGY · C
34.7
15.5
19.2
134.4
8.8
47.1
27.1
24.7
84
267
Matt SavoieEDM · C
35.9
16.7
19.2
140.4
6.5
19.1
39.3
24.6
84
268
Vasily PodkolzinEDM · R
37.5
18.4
19.1
135.6
4.9
248.8
48.8
57.5
84
269
Jonatan BerggrenSTL · R
32.9
13.8
19.1
99.7
5.6
55.2
23.8
18.5
84
270
Danila YurovMIN · R
32.1
13.0
19.1
92.0
6.1
77.6
44.6
36.1
84
271
Alexandre TexierMTL · L
33.3
14.2
19.1
114.1
2.0
92.0
28.2
37.4
84
272
Joel FarabeeCGY · L
37.0
17.9
19.1
153.1
3.9
68.1
53.8
37.3
84
273
Frederick GaudreauSEA · C
32.2
13.1
19.1
105.9
5.0
46.6
63.8
12.0
84
274
Victor OlofssonVGK · R
37.0
18.1
19.0
156.3
10.5
28.6
22.6
10.0
84
275
Yegor SharangovichCGY · C
37.9
19.0
18.9
154.9
8.6
23.2
36.1
12.3
84
276
Oskar SundqvistSTL · C
27.3
8.5
18.8
71.9
4.8
108.8
50.2
41.2
84
277
Nikita NesterenkoANA · C
26.0
7.3
18.8
95.6
0.4
158.6
26.0
19.5
84
278
Jesperi KotkaniemiCAR · C
28.3
9.5
18.7
112.3
2.6
98.7
34.4
39.3
84
279
Otto StenbergSTL · C32 sample
27.0
8.3
18.7
84.4
0.5
127.1
41.1
14.8
84
280
Ryan GreeneCHI · C
30.5
11.8
18.7
109.5
4.0
50.1
40.2
14.3
84
281
Anthony DuclairNYI · L
36.2
17.6
18.7
121.3
8.7
32.8
50.1
22.0
84
282
Zachary BolducMTL · R
34.7
16.1
18.6
114.0
7.5
163.7
42.7
45.2
84
283
Ross ColtonNSH · C
33.2
14.6
18.6
166.8
3.2
195.9
38.2
33.7
84
284
Michael AmadioOTT · R
33.2
14.7
18.5
104.1
1.2
109.1
49.6
20.0
84
285
Nick FolignoMIN · L
31.5
13.0
18.4
103.2
5.4
209.8
44.1
61.0
84
286
Noah LabaNYR · C
28.3
9.8
18.4
80.0
5.5
122.3
49.0
42.0
84
287
Mavrik BourqueNSH · C
35.7
17.3
18.4
139.8
4.3
88.8
28.7
23.1
84
288
Vladislav NamestnikovWPG · C
30.3
11.9
18.4
104.3
6.2
105.6
50.8
43.4
84
289
Ben KindelPIT · C
35.5
17.1
18.4
161.3
10.1
42.0
64.9
18.8
84
290
Kasperi KapanenEDM · R
33.7
15.5
18.2
125.7
2.2
139.3
29.5
28.9
84
291
Olle LycksellOTT · R
23.8
5.6
18.2
80.7
2.4
42.3
35.1
15.7
84
292
Will CuylleNYR · L
36.7
18.5
18.2
154.4
5.6
294.9
56.1
59.1
84
293
Lawson CrouseUTA · L
40.2
22.0
18.2
147.2
3.8
222.5
53.0
43.2
84
294
Alex NewhookMTL · C
39.2
21.0
18.1
124.8
5.1
93.5
38.1
32.6
84
295
Justin BrazeauPIT · R
35.9
17.8
18.1
119.2
6.0
136.2
51.8
20.1
84
296
Fabian ZetterlundOTT · L
35.5
17.4
18.1
157.0
8.3
150.2
49.5
18.6
84
297
Mathieu JosephEDM · R
24.0
6.1
17.9
89.3
0.4
178.7
57.5
37.9
84
298
Ryan WintertonSEA · C
22.4
4.5
17.9
111.1
0.2
93.1
42.5
17.8
84
299
Hendrix LapierrePIT · C
24.6
6.9
17.8
65.3
2.3
58.9
31.0
27.9
84
300
Kiefer SherwoodSJS · L
39.9
22.2
17.7
172.6
8.2
406.6
33.4
55.0
84

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