Bands show position percentiles; axis labels show current rolling values.
Dashed outline: peer average in the fixed reference. Outside = above average; inside = below average. All axes point outward for stronger results.
Player value: 2.89 Peer range: 1.68 – 4.20 xGF/60
MeanClayton Keller
Lower Higher (better)
Player 2.89 · mean 2.54. Higher raw values rank higher.
Rolling profile against a fixed reference group
Fixed rolling-profile reference · 430 players. Values use the same history and smoothing as the radar.
History, sample sizes & calculation
Higher radar percentiles mean stronger recorded results against the fixed reference, including older seasons. These are separate from this season’s league percentile. Each player has a different amount of covered history. Weighted minutes and attempts give recent games more influence. “Prior” is the share contributed by a frozen league baseline: it is higher when a player has less evidence, and differs by metric because each uses its own smoothing strength. It is not a confidence score.
On-ice offense · xGF/60
1330.8 weighted minutes · 13% prior
On-ice defense · xGA/60
1330.8 weighted minutes · 23% prior
Chance generation · ixG/60
1330.8 weighted minutes · 13% prior
Shot quality · ixG/attempt
255.1 weighted attempts · 9% prior
Finishing · goals above expected/60
255.1 weighted attempts · 14% prior
History through Oct 19, 2026. Recent games count more than older games. History carries across seasons and stays unchanged while inactive. On-ice results are shared; finishing describes results rather than established talent.
Recent scoring against his own season
Recent scoring against his own season
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Every metric name opens its definition; the full list lives in Metrics.
Traditional statistics cover all situations. Supporting five-on-five analyses use completed games, raw adjustment and exposure from xG model v4. The two samples can differ.
An em dash means unavailable, not zero. A partial season remains partial. Where a panel reports evidence coverage, its rates use only the covered games. History never substitutes a different model, and a missing appearance interrupts a rolling model window.
Shot maps use the same shot model as Game Center and show which model version scored recent shots beside the rink. Older seasons can use earlier model versions. High danger means a model scoring probability of at least 0.20 on an unblocked attempt; for goalies, medium danger is 0.08 to 0.20 and low is below 0.08.
Special-team buckets include the wider recorded man-advantage and man-down states, read from the player’s own team; for a goalie, penalty kill means facing a power play. Their ranks need 100 recorded minutes and at least 30 qualified peers; below 100 minutes, penalty-kill percentiles are provisional. Playoff values have no ranks or percentiles. Team share is player ice time divided by team ice time in that situation, over the games the player dressed. Zone starts describe faceoff-started five-on-five shifts and exclude on-the-fly starts.
Penalties count events, including one for a double minor; bench and served-by roles are excluded, and victimless infractions have no drawn role. EPV added sums changes in the probability that the possessing team scores next; it is not standings points or an isolated player grade. Rolling windows never cross seasons or season types, and a missed game is not a zero-performance appearance. Career rates use summed counts and exposure, never an average of season rates; a missing contributing season withholds its career metric, and Performance begins in 2023–24.
Most often with Derek Stepan: 622 five-on-five minutes, 47.7% xG share together
Most often with Derek Stepan: 622 five-on-five minutes, 47.7% xG share together
Five-on-five · time together from shift charts (1,125:02 of his 5v5 ice time) · xG share together and apart
Teammate
Pos
TOI together
xG share together
GF–GA
CF%
Him without
Teammate without
Derek Stepan
C
621:31
47.7%
20–28
49.4%
44.2%
45.3%
Oliver Ekman-Larsson
D
423:35
55.1%
13–15
54.5%
40.6%
45.4%
Alex Goligoski
D
387:54
40.9%
9–11
46.5%
48.9%
45.0%
Max Domi
C
371:48
48.8%
11–20
50.5%
44.7%
44.6%
Jason Demers
D
327:59
54.3%
11–12
53.6%
42.8%
46.9%
Kevin Connauton
D
287:57
39.3%
8–11
44.0%
48.4%
42.2%
Jakob Chychrun
D
250:58
43.0%
8–8
45.3%
47.0%
50.6%
Luke Schenn
D
241:16
36.9%
7–10
42.1%
48.7%
43.4%
Christian Fischer
R
237:44
43.8%
4–9
44.6%
46.7%
49.1%
Niklas Hjalmarsson
D
208:16
48.0%
10–13
47.5%
45.7%
53.5%
Richard Panik
R
196:51
49.0%
7–9
51.2%
45.5%
51.3%
Brendan Perlini
L
195:21
43.7%
8–5
45.6%
46.5%
45.3%
Without columns are five-on-five xG share apart: him on the ice without that teammate, and the teammate without him (with this club). Bars are centred on an even 50%.
Average 0.68 individual expected goals per 60 (61st of 105)
Average 0.68 individual expected goals per 60 (61st of 105)
45.5%85th of 105
Weak 45.5% on-ice expected goal share at five-on-five (85th of 105)
Weak 45.5% on-ice expected goal share at five-on-five (85th of 105)
Weak 2.81 on-ice expected goals against per 60 (87th of 105)
Weak 2.81 on-ice expected goals against per 60 (87th of 105)
Defensive metrics
Five-on-five on-ice suppression; individual events in all situations.
Suppression
Player
Percentile
Rank
61.39
90 / 10514th
—
—
—
0.060
55 / 10548th
Puck management
Player
Percentile
Rank
—
—
—
—
—
—
—
—
—
Physical style
Player
Percentile
Rank
—
—
—
—
—
—
Context · not graded
Player value: 61.39 Peer range: 46.87 – 66.61 / 60
MeanClayton Keller
Lower (better)Higher
Player 61.39 · mean 57.01. Lower raw values are better.
On-ice attempts against per 60, including blocks.
Discipline & puck management
Recorded season event counts · all situations
Penaltiesnet —
Taken —Drawn —
Puck eventsnet —
Giveaways —Takeaways —
Blocks
—
all situations
Hits
—
all situations
Average 4.82 power-play points per 60 (18th of 53)
Average 4.82 power-play points per 60 (18th of 53)
Power play
249:01 recorded ice time · peers need 100 minutes
Share of team PP
—
in games dressed
PP points
20
goals + assists
Unit xGF / 60
7.19
team without: —
Power play rates
Player
Percentile
Rank
4.82
18 / 5367th
—
—
—
15.18
11 / 5381st
1.74
17 / 5369th
7.19
24 / 5356th
—
—
—
Player value: 4.82 Peer range: 1.42 – 9.35 / 60
MeanClayton Keller
Lower Higher (better)
Player 4.82 · mean 4.42. Higher raw values rank higher.
Recorded goals plus assists per 60 in this scope; widened power-play and penalty-kill scopes.
Penalty kill
10:48 recorded ice time · peers need 100 minutes
Share of team PK
—
in games dressed
SH points
1
goals + assists
Unit xGA / 60
4.36
team without: —
Penalty kill rates
Player
Percentile
Rank
4.36
—
—
—
—
55.56
—
—
—
—
0.32
—
No rank yet
Player value: 4.36 Peer range: 4.36 – 8.20 / 60
MeanClayton Keller
Lower (better)Higher
Player 4.36 · mean 7.02. Lower raw values are better. Fewer than 30 qualified peers.
Raw on-ice expected goals against per 60; the Season metrics sample.
Fewer than 30 qualified peers.
18:05 TOI per game (13:50 at five-on-five · 3:02 PP · 0:08 PK)
18:05 TOI per game (13:50 at five-on-five · 3:02 PP · 0:08 PK)
Results vs expected
Five-on-five · what happened beside the chances created and allowed
Chances
Player
Percentile
Rank
2.35
72 / 10532nd
2.81
87 / 10517th
45.5
85 / 10519th
Goals
Player
Percentile
Rank
—
—
—
—
—
—
—
—
—
Luck & variance
Player
Percentile
Rank
—
—
—
—
—
—
—
—
—
Context · not graded
Player value: 2.35 Peer range: 1.62 – 3.33 / 60
MeanClayton Keller
Lower Higher (better)
Player 2.35 · mean 2.51. Higher raw values rank higher.
Raw on-ice expected goals for per 60; the Season metrics sample.
5v5 goals
—
for–against
5v5 expected
44.5–53.2
xG for–against
EPV added
+0.62
82 attributed games · all situations
On ice vs off ice
Arizona's share with Clayton Keller on the ice against the same team without him.
Share
On ice and off ice
On-minus-off gap in percentage points
xGF%
On ice 45.5% · Off ice unavailable
—
CF%
On ice 48.4% · Off ice unavailable
—
GF%
On ice unavailable · Off ice unavailable
—
On iceOff ice
Scale 40–65% · marker at 50% · right column is the on-minus-off gap in points
Hot 12 points in the last 10 games (1.20 per game vs 0.79 this season)
Hot 12 points in the last 10 games (1.20 per game vs 0.79 this season)
0.76 points per game at home · 0.83 away
0.76 points per game at home · 0.83 away
82 games · most recent vs ANA, L 0–3: 0 G, 0 A
82 games · most recent vs ANA, L 0–3: 0 G, 0 A
Clayton Keller
309 attempts24.58 xG25 G
Goal25Shot on goal191Missed shot93Blocked shot0Larger dot = higher xG
Shooting by zone
Zone
Att
G
xG
Goal rate / exp.
G−xG
Inner slot
74
16
9.9
21.6% / 13.4%
+6.1
Below goal line
1
0
0.0
0.0% / 1.7%
0.0
Point
60
1
1.7
1.7% / 2.8%
−0.7
Outer slot
23
1
1.8
4.3% / 7.8%
−0.8
Left circle
29
0
0.8
0.0% / 2.8%
−0.8
Right circle
21
0
0.9
0.0% / 4.5%
−0.9
High slot
101
7
9.5
6.9% / 9.4%
−2.5
All zones
309
25
24.6
8.1% / 8.0%
+0.4
Sorted by goals minus expected goals. Goal rate is goals per unblocked attempt against the expected rate. Hover a row to light up those attempts on the rink.
Finishing evidence. Scoring 8.1% on chances against 8.0% expected, tracking the model across 7 zones.
Shot types309 attempts
Type
Share
Sh%
G−xG
Wrist
67.6%
11.4%
+0.1
Backhand
7.8%
22.2%
+1.5
Slap
7.1%
0.0%
−1.1
Tip-in
7.1%
16.7%
+0.5
Snap
6.5%
12.5%
+0.7
Deflected
2.9%
0.0%
−1.0
Other
1.0%
—
−0.2
Share is context, not a grade. Sh% counts shots on goal only.
High-danger chancesmodel probability ≥ 0.20
Attempts5.8% of the selected attempts
18
Goals
5
Expected goals
4.6
Conversion
27.8%25.7% expected
Shot profilecontext · not graded
On-net rate216 of 309 attempts on goal
69.9%
Slot share175 of 309 from the inner or high slot
56.6%
Average distancefrom the centre of the net
29.7 ft
Rebound attempts / 6021 this season · all situations
0.85
Usage by situation
Ice time, share of team ice time, scoring and scoring rate, with where shifts start.
Scope
TOI/GP
Team share
G
A
P
P/60
Five-on-five
13:50
—
13
24
37
1.96
Power play
3:02
—
6
14
20
4.82
Penalty kill
0:08
—
0
1
1
5.56
Other
1:05
—
6
3
9
6.10
All situations
18:05
—
25
42
67
2.71
Where the 67 points come from · All situations
Goals25 · 1.01/60
Primary assists— · —/60
Secondary assists— · —/60
Zone starts — offensive of OZ + DZ
Offensive —Neutral —Defensive —
Shifts
— a game · — average
Zone starts: five-on-five · Shifts: all situations
11 NHL seasons: 693 games, 609 points
11 NHL seasons: 693 games, 609 points
Totals cover all situations; rates are five-on-five.
Elite90+Strong70–89Average30–69Weak10–29Poor<10Bar length is the peer percentile, so longer is always better · tick at the 50th
Player value: 1.96 Peer range: 0.40 – 2.89 / 60
MeanClayton Keller
Lower Higher (better)
Player 1.96 · mean 1.56. Higher raw values rank higher.
Recorded five-on-five goals plus assists per 60 minutes.
How to read these comparisons
Player values are recorded season results. Peer averages are arithmetic means of qualified players in the selected group; each row uses the same peers for its average and rank. Ranks use unrounded values, with tied players sharing a rank and the next rank skipped. Lower xG against ranks better. Bar colours are the five performance tiers; context rows are blue and not graded. Differences from the average describe the season, not isolated player impact.
Goals above expected is the raw goals-minus-xG rate, without the shrinkage used in the older finishing comparison. On-ice measures include teammates, opponents and deployment. These recorded metrics describe different quantities from the adjusted Season score components beside them.
Skaters need 20 appearances and 300 five-on-five minutes; quality and finishing also need 75 unblocked attempts. Early in a season these minimums scale down with games played so far. At least 30 peers must qualify. Playoff ranks are withheld. A reviewed axis whose own evidence fails is withheld and shown with its reason rather than ranked. These workload rules do not express statistical confidence.
Position uses the NHL listed primary position available now; it does not establish historical position or actual deployment. Broad groups are forwards, defence and goalies. This version uses the current model’s covered games only.
Season vs reference
Per game · all situations
Metric2017–18ReferenceDiff
0.280.00+0.28
0.510.67-0.15
0.790.67+0.13
2.590.00+2.59
Reference: 2016–17 · 3 games.
Each game against his own season
Points in each game, coloured by how good the game wasTrailing 10 games, per gameSeason 0.79
