Anatomy of a player card

The numbered markers explain each element; every card in the team decks and the UFA deck reads the same way.

Nathan MacKinnon
C · #29 · COL · 30 · First-line star
Average career stats over an 82-game season 1
36
G
62
A
99
P
+20
+/−
37
PIM
20:40
TOI/GP
3:35
PP TOI/GP
0:16
SH TOI/GP
2'14'15'16'17'18'19'20'21'22'23'24'25'26CAREERWEIGHTEDAVERAGETeam rank7/249/262/2720/271/284/253/245/273/282/311/298/332/273/20League rank130/751282/730158/736582/73634/759136/76735/73542/72840/80841/77412/772134/76113/77835/716Age rank3/76/158/2830/431/5914/676/624/644/684/641/5911/551/501/50Overall+3.982 GP+0.364 GP+2.972 GP-4.282 GP+9.974 GP+3.982 GP+10.269 GP+10.948 GP+11.765 GP+10.171 GP+15.082 GP+4.179 GP+13.980 GP+6.4950 GPEV offenseEV defense+1.0-1.614:56+0.9-1.614:33+0.5-1.615:21+0.6-0.915:25+1.0-1.215:59+2.4-1.317:53+2.8-0.517:01+3.0+2.616:12+3.6-1.317:20+3.2-1.118:08+6.1+0.418:14+9.2-0.518:53+6.3-1.017:55+3.0-0.7Power play+0.62:20+0.12:26-0.42:55+0.22:46-1.03:36-0.44:05+0.44:07+4.64:06+2.13:40+1.84:05+1.14:30+0.73:49+1.54:17+0.6Penalty kill+0.00:04+0.10:02+0.10:34-0.01:44+0.10:18-0.50:06+0.10:04+0.30:02-0.20:03+0.10:05+0.20:03-0.30:03+0.80:02+0.0Finishing+1.1-2.0+1.5-6.7+11.8-0.5+4.7-2.9+3.6+3.7+5.3-7.4+4.5+1.0Penalties+3.5+3.1+3.3+2.4+1.3+5.7+4.1+3.5+4.8+3.9+2.9+2.4+1.5+3.1Faceoffs-0.6-0.3-0.4+0.2-2.1-1.5-1.4-0.3-1.0-1.5-1.0-0.0+0.3-0.7
3ON-ICE CONTEXT — TOI-WEIGHTED OPPONENT / TEAMMATE NET GOALS/82Competition+0.4+0.9+0.3+0.8+0.3+0.3+0.1-0.3+0.2+0.3+0.1+0.3+0.0+0.3Teammates+1.1-1.1-0.6-1.6+0.5+2.4+3.8+10.4+8.9+4.7+7.1+5.9+5.6+3.6Landeskog 49%Johnson 37%Benoit 36%Barrie 30%Landeskog 64%O'Reilly 42%Barrie 38%Johnson 32%Duchene 48%Landeskog 44%Beauchem. 43%Barrie 42%Rantanen 57%Landeskog 47%Barrie 42%Beauchem. 30%Rantanen 86%Landeskog 73%Barrie 44%Johnson 32%Rantanen 74%Landeskog 71%Barrie 52%Girard 36%Landeskog 59%Makar 49%Rantanen 46%Girard 42%Landeskog 82%Rantanen 81%Makar 59%Toews 42%Rantanen 78%Makar 70%Landeskog 43%Toews 41%Rantanen 72%Toews 53%Lehkonen 52%Makar 50%Rantanen 84%Makar 68%Toews 55%Drouin 50%Makar 74%Lehkonen 53%Toews 53%Rantanen 49%Necas 80%Makar 62%Lehkonen 48%Toews 38%Rantanen 49%Landeskog 38%Makar 34%Toews 23%
4NHL EDGE (2021+)Hardest shot94.293.388.887.991.094.2Top speed23.824.024.123.824.824.8Bursts/GP7.37.78.76.95.78.7
540-gameform'14'15'16'17'18'19'20'21'22'23'24'25'26+27.1-10.2+1.1
6Careernet goals'14'15'16'17'18'19'20'21'22'23'24'25'26+82
7SHOT MIX — TYPE (BARS) & LOCATION VS FORWARDS (MAP)Wrist61%+0.7Snap13%+0.1Slap12%+1.4Backhand9%-1.0Tip-in3%-0.0Deflection1%Other1%net goals/82shot-mix share vs forwards (±0.35pp)
$12.60M
CAP HIT 2026-27
12.1%
SHARE OF TEAM CAP
+0.50
NET GOALS/82 PER $M 8
The numbered elements
1
Basic stats
Average career stats over an 82-game season: G, A, P, +/− and PIM are per-82 rates (so players with different career lengths compare directly); the TOI entries are averages per game (total, power play, short-handed). The header’s subtitle line ends with the player’s archetype — a k-means career style cluster (icon + name; 8 forward types, 6 defense types, era-adjusted features; the full icon glossary is on the Reference page). Skaters need 150 career GP to be typed.
2
Net goals grid
One column per season ('11 = 2010-11) with the team(s) played for under each header. The three small rows above the grid place each season's Overall rate in context: Team rank among the skaters on the team he finished the season with, League rank among every skater with a rated season (10+ GP), and Age rank among skaters the same age (as of Oct 1 of the season's start year). In the CAREER column the same three rows rank his career rate within the deck's current roster, all active skaters (played 2025-26, 40+ career GP), and active skaters his age. Every box below them is the player's net goals added per 82 games vs a league-average player, in calibrated model units — blue adds goals, red costs them, on fixed scales (−41 → +41 for the Overall row, a tighter −12.3 → +12.3 for the component rows, so seasons and players compare directly); gray text under a row is TOI per game in that situation (GP for the Overall row) — situation here means skater advantage: 6v5 with the goalie pulled counts as PP time and defending it counts as PK time, so these splits run a little higher than the official PP/SH TOI in the header row (the totals agree); a plain gray box = fewer than 10 GP that season. The CAREER column is the games-played-weighted career rate with small samples regressed toward the league mean (each component carries an empirical-Bayes prior, so a hot 20-game stint doesn't read as a career skill; the per-season boxes stay raw). The Overall row and the CAREER column are set in bold with outlined boxes:
Overall — the sum of the seven component rows below; the CAREER box is the numerator of the contract-efficiency tile.
EV offense — on-ice expected-goal creation at even strength vs league-average context (score, time, zone starts), scaled to its calibrated marginal value — five skaters share the same flow, so the marginal is ~4.4× smaller than face value.
EV defense — the same flow suppressed: on-ice expected goals against vs context, same marginal scaling.
Power play / Penalty kill — priced chance flow above (PP) or suppressed below (PK) league-average context in situation, same marginal scaling.
Finishing — goals above expected (xG) on the shooter's own shots on goal — individual credit, at face value.
Penalties — penalties drawn − taken, priced at that season's measured value of a drawn minor (≈0.16–0.20 goals: the average net goals scored in the two minutes after a penalty is drawn, measured league-wide per season).
Faceoffs — net faceoff wins × 0.010 goals (fixed-effects calibration). Shown for context: faceoff value flows through possession, so it partly overlaps the on-ice rows and is not part of the headline rating.
3
On-ice context
Who the player skated with and against, season by season. Competition is the shared-TOI-weighted average Overall net goals/82 of the opposing skaters he faced; Teammates the same for his own linemates (goalies excluded on both sides; skaters too small a sample to rate that season count as league-average). Competition spreads far less than teammate quality, so the rows use different color scales (±1.5 and ±5; stated here rather than on the card). Under the Teammates row, each season lists his four most common teammates with the share of his ice time they were on for; the career column aggregates across seasons.
4
NHL EDGE (2021+)
Puck-and-player tracking from NHL EDGE, which only exists from 2021-22 on (long careers start blank): hardest shot and top skating speed in mph, and 20+ mph speed bursts per game. Boxes are colored by where the number ranks within that season's tracked cohort (skaters with ≥50 shots on goal); the career column is the career best (bursts: the career rate).
5
40-game form
The career's shape in one line: a trailing 40-game moving average of the Overall row, in the same net-goals-per-82 units. The x-axis is career games and is shared with the Career net goals line below, so the line starts blank until the 40th game. The dot marks the career peak, the number at the right end is the current value, and faint vertical lines are season boundaries. Even elite careers dip below zero here — 40 games is a small sample. Goalie cards draw the same line for GSAx/82 over the last 40 appearances.
6
Career net goals
The running career total of the same per-game net goals the form line averages: how much value the career has banked versus a league-average player, in goals. A flat stretch means league-average play, a rising slope means value being added; the red dot marks the career high-water mark when the current total has slipped below it. Goalie cards accumulate GSAx instead.
7
Shot mix — type & location
Left: the career shot diet by type — each bar is the share of his shots on goal of that type, and the box prices it as net goals per 82 (goals above xG on those shots; types with fewer than 100 career shots stay gray). Right: where the shots come from — each zone of the offensive half is colored by his share of shots from that spot vs the league average for his position (blue = more than a typical F or D, red = less, ±0.35 percentage points per zone). Goalie cards show a save map instead: each zone colored by save percentage above or below what that zone's shots predict.
8
Team value
Contract efficiency: cap hit, share of the 2026-27 team cap, and career net goals added per 82 games per $M of cap hit — the grid's CAREER Overall box divided by the cap hit, so the tile and the grid always agree (goalies: GSAx/82 per $M). Cards for unsigned free agents (the UFA deck) have no contract, so this block is absent there.
G
Goalie cards
Goalie cards read the same way with goalie panels: the header row shows career shot-quality totals — shots faced, GA, xGA, GSAx (goals saved above expected), Sv%, xSv% and Reb/100 (rebounds yielded per 100 shots faced; lower is better). The season grid is GSAx per 82 games with a Reb/100 row, then the 40-appearance form line, the cumulative career GSAx line, and the save map described above.
Glossary of statistical terms
xG (expected goals) — the probability that a given shot becomes a goal, based on its location, type, and game situation. Game situation is the manpower state when the shot is taken (even strength, power play, short-handed, or empty net). The same shot from the same spot converts far more often with a man advantage than it does 5 on 5; rebound shots (within 3 seconds of a prior shot) and rush shots are also priced separately. A rush is inferred from the play-by-play sequence: the attempt comes within 4 seconds of a faceoff, hit, giveaway, or takeaway that happened in the shooting team’s neutral or defensive zone — the puck was at the far end of the ice moments earlier, so the defense never got set. Rushes that start by winning a turnover (a takeaway, or an opponent’s giveaway) are priced apart from those following a hit or faceoff, since a true counter-rush converts very differently from a fling after a dump-in or neutral-zone draw. Summed over shots, xG says how many goals a shooter “should” have scored — or a goalie/team should have allowed (xGA).
WPA (win probability added) — a weight on each chance for how much it moves the odds of winning the game: a chance in a tied third period counts more than one in a blowout. “Priced” chance flow means xG weighted this way.
rel (relative to context) — measured against what a league-average player would produce in the same circumstances: score state, home/road, zone starts, and situation.
Elo — a rating updated game by game: it rises when the player outperforms expectation and falls when he doesn’t, so it rewards sustained performance over a hot stretch.
rel-xG-WPA Elo — the engine behind the on-ice rows (EV offense/defense, PP, PK): win-probability-priced expected-goal flow, measured relative to league-average context. A per-season Elo run on it drives the model’s validation.
Empirical-Bayes shrinkage — small samples are pulled toward the league average before being called skill: each component’s career rate is blended with the league mean using a prior worth a component-specific number of games, so 40 hot games move a career number far less than 400 do. The per-season boxes are never shrunk.
Per 60 — a rate per 60 minutes of ice time in that situation, so heavy- and light-usage players compare fairly.
Deployment-adjusted — corrected for how the player is used (zone starts, score, time on ice) so sheltered minutes don’t inflate a score.
Ridge attribution / teammate-adjusted — a ridge regression over on-ice lineups that separates the player’s own contribution from that of the linemates he shares the ice with.
Exposure-weighted — an average weighted by playing time (games or minutes), so a 20-game season counts less than a full one.
GSAx (goals saved above expected) — xGA − GA: positive means the goalie stopped more than the quality of shots he faced predicted. xSv% is the save percentage those shots implied.
Reb/100 — rebounds yielded per 100 shots faced; lower is better.