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Insights

Where the numbers say something a scoring table does not: postseason production, finishing and goaltending against the xG model, and scoring on the power play.

Season
2025-262024-252023-242022-232021-22
Hottest finisherAuston Matthews+20.8goals above expected · 69 on 48.2 expectedColdest finisherJosh Anderson−9.7goals below expected · 9 on 18.7 expectedBest goaltendingConnor Hellebuyck+21.8goals saved above expected · 2,570 attempts faced

Playoff scoring, 2023-24

Points in the postseason

The games every other board on this site leaves out, ranked on the total with games played on the row.

#
Skater
GP
G
A
PTS
P/GP
1
Connor McDavidC
25
8
34
42
1.68
2
Evan BouchardD
25
6
26
32
1.28
3
Leon DraisaitlC
25
10
21
31
1.24
4
Zach HymanL
25
16
6
22
0.88
5
Aleksander BarkovC
24
8
14
22
0.92
6
Ryan Nugent-HopkinsC
25
7
15
22
0.88
7
Matthew TkachukL
24
6
16
22
0.92
8
Carter VerhaegheC
24
11
10
21
0.88
9
Vincent TrocheckC
16
8
12
20
1.25
10
Anton LundellC
24
3
14
17
0.71
Why the total, not points per game — a per-game sort crowns a two-point sweep
A per-game sort with no minimum puts a two-point sweep above a twenty-nine-point run, and games played vary more than fivefold across a field decided by elimination. So the board ranks the total, and the games are on every row.

Finishing against expectation, 2023-24

How these boards are built — regular season only, and not comparable across seasons
Expected goals come from the xG model over open-play unblocked attempts. League expected goals run 0.956 to 1.010 of actual goals by season, so totals are not comparable across seasons and each board ranks within its own. Boards sort on the total rather than the per-attempt rate, because a rate board with no minimum is a list of players with one attempt.

Above expected

Skaters who scored the most goals above what the model expected from their attempts.

#
Skater
GP
Att
G
xG
GAx
GAx / att
1
Auston MatthewsC
81
534
69
48.2
+20.8
+0.039
2
Sam ReinhartC
81
358
57
37.3
+19.7
+0.055
3
Artemi PanarinL
81
431
49
33.6
+15.4
+0.036
4
Brayden PointC
80
321
46
33.3
+12.7
+0.039
5
Nathan MacKinnonC
82
526
51
39.1
+11.9
+0.023
6
Jonathan MarchessaultC
80
355
42
30.1
+11.9
+0.033
7
Frank VatranoR
80
349
37
25.2
+11.8
+0.034
8
MacKenzie WeegarD
82
285
20
9.4
+10.6
+0.037
9
Filip ForsbergL
82
499
48
37.6
+10.4
+0.021
10
Nick SuzukiC
79
266
33
22.6
+10.4
+0.039

Below expected

The same column sorted the other way, because a board that ranks one direction only implies the other end is not a measurement.

#
Skater
GP
Att
G
xG
GAx
GAx / att
1
Josh AndersonR
68
224
9
18.7
−9.7
−0.043
2
Matthew TkachukL
79
395
26
35.5
−9.5
−0.024
3
Miles WoodL
70
228
9
17.7
−8.7
−0.038
4
John TavaresC
79
385
29
37.6
−8.6
−0.022
5
Taylor RaddyshR
65
173
5
13.4
−8.4
−0.049
6
James van RiemsdykL
65
189
11
19.3
−8.3
−0.044
7
Sean CouturierC
72
248
10
18.1
−8.1
−0.033
8
Jake GuentzelC
67
338
30
37.8
−7.8
−0.023
9
Adam LowryC
69
192
11
18.3
−7.3
−0.038
10
Ryan Nugent-HopkinsC
77
264
18
25.3
−7.3
−0.028

Goaltending against expectation, 2023-24

What the goalie boards count — unblocked attempts, not the box score's shots against
Attempts here are open-play and unblocked, deliberately not the box score's shots against, which counts a different set of pucks. Save percentage is not shown for the same reason: the game log already gives it over that other set.

Above expected

Goalies who conceded fewer goals than the model expected from the attempts they faced.

#
Goalie
GP
Att
GA
xGA
GSAx
GSAx / 100
1
Connor Hellebuyck
60
2,570
142
163.8
+21.8
+0.85
2
David Rittich
24
912
49
63.8
+14.8
+1.63
3
Anthony Stolarz
27
1,022
51
65.4
+14.4
+1.41
4
Jordan Binnington
57
2,572
156
169.9
+13.9
+0.54
5
Thatcher Demko
51
2,090
122
135.8
+13.8
+0.66
6
Jacob Markstrom
48
2,007
130
143.2
+13.2
+0.66
7
Frederik Andersen
16
594
28
40.7
+12.7
+2.14
8
Jeremy Swayman
44
1,897
108
120.6
+12.6
+0.67
9
Linus Ullmark
40
1,766
103
114.2
+11.2
+0.64
10
Laurent Brossoit
23
922
45
56.0
+11.0
+1.19

Below expected

The same column sorted the other way; a goalie on a heavily outshot team can sit here on volume alone, which is why the attempts faced are on the row.

#
Goalie
GP
Att
GA
xGA
GSAx
GSAx / 100
1
Joonas Korpisalo
55
2,170
168
141.4
−26.6
−1.23
2
Arvid Soderblom
32
1,345
114
93.4
−20.6
−1.53
3
Alexandar Georgiev
63
2,526
183
166.8
−16.2
−0.64
4
Marc-Andre Fleury
40
1,543
111
95.2
−15.8
−1.02
5
Ilya Samsonov
40
1,657
118
103.4
−14.6
−0.88
6
Jonas Johansson
26
1,021
83
69.7
−13.3
−1.31
7
Dan Vladar
20
837
68
54.9
−13.1
−1.57
8
Vitek Vanecek
32
1,211
95
82.5
−12.5
−1.03
9
Dustin Wolf
17
655
50
38.1
−11.9
−1.82
10
John Gibson
46
1,968
151
139.3
−11.7
−0.59

Power-play points, 2023-24

With the man advantage

Points recorded while the skater's side had the extra man, read from the on-ice strength state of every event.

#
Skater
G
A
PTS
SOG
1
Nikita KucherovR
13
40
53
78
2
Nathan MacKinnonC
10
38
48
120
3
Artemi PanarinL
11
33
44
85
5
Kirill KaprizovL
19
23
42
94
6
Mikko RantanenR
14
26
40
78
7
J.T. MillerC
11
29
40
68
8
Leon DraisaitlC
21
18
39
87
9
Steven StamkosC
19
20
39
112
10
Cale MakarD
7
32
39
71
Shots here — shots on goal, not the attempts on the finishing boards
The shots column on this board counts shots on goal. The finishing boards count open-play unblocked attempts, a larger population, so the two are not the same number and should not be compared.
Why no club is shown — the club we hold is today's, not the season's
We hold each player's CURRENT club, not the one they played for in the season a board describes. Among the top 50 finishers that would be wrong for 8 of 50 in 2025-26 and 29 of 50 in 2021-22, so the column is left off rather than shown wrong. Follow a name to the player's page for club and history. The club we hold, like every board on this page, is updated once a day.

Does finishing persist?

Yes, partly — it beat both simpler rules, so far on a backtest only: no live projection has been graded yet.

The finishing boards above show who out-scored the model. The projection says how much of a hot season should carry into the next, and this is where that forecast is graded, two ways that are not interchangeable.

Tested on 2025-26 — a season the rule never saw

a backtest, not a track record

483 of 490 projections scored · 7 unscoreable

The unscoreable ones are players who did not play 2025-26. They are counted rather than dropped — a rule that only looks good on the players who came back would otherwise look the same as one that works.

vs. assuming it all goes awaybetter

2.7% lower prediction error

A small margin is the honest outcome here, not a weak one — the rule keeps under a fifth of a hot season, so its forecast is close to this baseline by construction. A large number would be evidence of a bug.

average error 1.7634 against 1.8124 — a paired difference of −0.0490 [−0.0804, −0.0176]

vs. assuming last season repeatsbetter

18.3% lower prediction error

average error 1.7634 against 2.1593 — a paired difference of −0.3959 [−0.5184, −0.2734]

The live record

Nothing graded yet. Every projection is recorded on the day it is made, but none has come due yet — these are forecasts about next season, so the first ones can be graded once it has been played.

The difference from the backtest above matters. A backtest can be re-run until it flatters; a prediction recorded before the season it describes cannot be, because the data it will be scored against does not exist yet.