New Jersey Devils
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Team tables carry the record, scoring, shooting, possession and both halves of special teams, with the league rank beside each. The record is three numbers because a club collects a standings point for losing in overtime, and the standings are ordered on points rather than wins. The roster is everyone who played for the club that season, and each line is what he did HERE rather than his whole year, so a player traded in March appears on both clubs with the games he played for each. Every rate is per sixty minutes of ice time, because a first-line forward plays twice the minutes of a fourth-line one. A dash means no number for that cell.
New Jersey Devils
2023-24 · Regular Season
| Player | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
 Luke HughesD | 82 | 21.5 | 9 | 38 | 47 | 4 | 135 | 6.7% | 24 | 55 | 42 | 69 | 28 | -25 |
 Dougie HamiltonD | 20 | 21.0 | 5 | 11 | 16 | 4 | 61 | 8.2% | 18 | 24 | 5 | 14 | 20 | -8 |
 Jack HughesC | 62 | 21.0 | 27 | 47 | 74 | 9 | 274 | 9.9% | 10 | 24 | 64 | 71 | 12 | -12 |
 John MarinoD | 75 | 21.0 | 4 | 21 | 25 | — | 57 | 7% | 39 | 89 | 41 | 33 | 41 | -6 |
 Simon NemecD | 60 | 19.9 | 3 | 16 | 19 | — | 73 | 4.1% | 22 | 105 | 18 | 25 | 33 | -7 |
 Nico HischierC | 71 | 19.5 | 27 | 40 | 67 | 6 | 182 | 14.8% | 44 | 42 | 55 | 28 | 12 | -5 |
 Jonas SiegenthalerD | 57 | 19.3 | 1 | 8 | 9 | — | 63 | 1.6% | 87 | 97 | 9 | 30 | 20 | -7 |
 Jesper BrattL | 82 | 19.3 | 27 | 56 | 83 | 7 | 248 | 10.9% | 66 | 33 | 39 | 45 | 12 | -6 |
 Timo MeierR | 69 | 17.6 | 28 | 24 | 52 | 10 | 207 | 13.5% | 111 | 42 | 34 | 29 | 45 | -28 |
 Tyler ToffoliC | 61 | 17.5 | 26 | 18 | 44 | 8 | 179 | 14.5% | 62 | 8 | 23 | 29 | 12 | -15 |
 Kevin BahlD | 82 | 17.4 | 1 | 10 | 11 | — | 63 | 1.6% | 151 | 103 | 19 | 24 | 82 | 1 |
 Dawson MercerC | 82 | 17.2 | 20 | 13 | 33 | 4 | 134 | 14.9% | 30 | 43 | 40 | 37 | 29 | -26 |
 Erik HaulaL | 76 | 16.9 | 16 | 19 | 35 | 1 | 155 | 10.3% | 94 | 49 | 27 | 28 | 54 | -1 |
 Nick DeSimoneD | 11 | 16.5 | 1 | 1 | 2 | — | 9 | 11.1% | 14 | 21 | 1 | 4 | 2 | 7 |
| B. SmithD | 63 | 16.1 | 5 | 10 | 15 | — | 60 | 8.3% | 117 | 101 | 16 | 29 | 61 | -3 |
| C. MillerD | 41 | 15.9 | 4 | 4 | 8 | — | 65 | 6.2% | 79 | 33 | 13 | 16 | 24 | 10 |
 Ondrej PalatL | 71 | 15.6 | 11 | 20 | 31 | 1 | 108 | 10.2% | 92 | 49 | 23 | 26 | 37 | -9 |
| M. McLeodC | 45 | 15.1 | 10 | 9 | 19 | — | 73 | 13.7% | 101 | 22 | 20 | 18 | 10 | 6 |
| C. FooteD | 4 | 14.8 | — | 1 | 1 | — | — | — | 3 | 9 | — | — | 16 | 3 |
| S. HatakkaD | 12 | 14.6 | — | 2 | 2 | — | 12 | 0% | 14 | 12 | 1 | 6 | 4 | 5 |
| C. LazarC | 71 | 12.4 | 7 | 18 | 25 | — | 74 | 9.5% | 179 | 64 | 18 | 16 | 44 | 10 |
| T. NosekL | 36 | 11.8 | 2 | 4 | 6 | — | 38 | 5.3% | 33 | 20 | 16 | 7 | 6 | -11 |
 Alexander HoltzR | 82 | 11.6 | 16 | 12 | 28 | 1 | 122 | 13.1% | 44 | 17 | 10 | 21 | 14 | -15 |
| G. ClarkeR | 3 | 11.4 | — | — | — | — | 2 | 0% | 6 | — | 1 | — | 2 | -2 |
 Justin DowlingC | 2 | 10.5 | 1 | — | 1 | — | 3 | 33.3% | 1 | 1 | 1 | — | — | -2 |
 Nathan BastianR | 54 | 10.2 | 5 | 7 | 12 | — | 57 | 8.8% | 143 | 27 | 8 | 5 | 32 | -10 |
 Nolan FooteL | 4 | 10.1 | 1 | — | 1 | — | 6 | 16.7% | 3 | 2 | — | — | — | -1 |
| S. BowersC | 8 | 9.5 | — | — | — | — | 7 | 0% | 3 | 3 | — | — | — | 1 |
| C. TierneyC | 52 | 9.0 | 4 | 8 | 12 | — | 26 | 15.4% | 20 | 12 | 14 | 9 | 21 | 3 |
| M. WillmanC | 18 | 8.3 | 3 | 1 | 4 | — | 17 | 17.6% | 23 | 7 | 3 | 1 | 2 | 1 |
 Brian HalonenL | 2 | 8.3 | — | — | — | — | 2 | 0% | 2 | — | 1 | — | — | — |
 Kurtis MacDermidL | 16 | 4.4 | — | 1 | 1 | — | 4 | 0% | 29 | 2 | 1 | — | 50 | 1 |
| S. LabergeL | 2 | 3.1 | — | — | — | — | — | — | 3 | — | — | — | — | — |
 Vitek VanecekG | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
 Nico DawsG | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
 Akira SchmidG | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
 Jake AllenG | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
| K. KahkonenG | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
About NHL Research
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Every number the site holds for an NHL club and the players who played for it, in one place. Pick a club, a season and a set of games, and read it. Nothing here needs an account.
Where the numbers come from
The same tables the boards read, resolved through one shared definition per stat. A rate is computed over the whole window rather than averaged across games, so a season figure is not the mean of the nightly ones.