St Louis Blues
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How to read this page
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.
St. Louis Blues
2021-22 · Regular Season
| Player | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
 Colton ParaykoD | 80 | 23.6 | 6 | 29 | 35 | — | 135 | 4.4% | 72 | 169 | 51 | 53 | 18 | 16 |
 Justin FaulkD | 76 | 23.2 | 16 | 31 | 47 | 1 | 167 | 9.6% | 149 | 101 | 37 | 40 | 43 | 41 |
| N. LeddyD | 20 | 21.0 | 2 | 6 | 8 | — | 19 | 10.5% | 6 | 18 | 9 | 10 | 6 | 3 |
| T. KrugD | 64 | 20.6 | 9 | 34 | 43 | 3 | 119 | 7.6% | 53 | 70 | 16 | 32 | 48 | 23 |
 Ryan O'ReillyC | 78 | 19.1 | 21 | 37 | 58 | 9 | 168 | 12.5% | 20 | 38 | 50 | 26 | 12 | 11 |
 Robert ThomasC | 72 | 18.8 | 20 | 57 | 77 | 3 | 115 | 17.4% | 13 | 25 | 60 | 50 | 16 | 17 |
 Pavel BuchnevichL | 73 | 18.3 | 30 | 46 | 76 | 8 | 199 | 15.1% | 57 | 15 | 46 | 41 | 34 | 29 |
| M. ScandellaD | 70 | 18.1 | 3 | 11 | 14 | — | 76 | 3.9% | 106 | 70 | 18 | 38 | 18 | 17 |
 Brayden SchennC | 62 | 17.8 | 24 | 34 | 58 | 7 | 111 | 21.6% | 119 | 17 | 42 | 28 | 33 | 21 |
| D. PerronL | 67 | 17.0 | 27 | 30 | 57 | 11 | 177 | 15.3% | 80 | 11 | 37 | 18 | 48 | 8 |
 Niko MikkolaD | 54 | 17.0 | 3 | 10 | 13 | — | 58 | 5.2% | 109 | 81 | 7 | 25 | 55 | -6 |
| V. TarasenkoR | 75 | 16.9 | 34 | 48 | 82 | 5 | 230 | 14.8% | 83 | 45 | 17 | 31 | 32 | 7 |
 Jordan KyrouR | 74 | 16.6 | 27 | 48 | 75 | 5 | 188 | 14.4% | 6 | 23 | 36 | 32 | 20 | 10 |
 Ivan BarbashevL | 81 | 16.4 | 26 | 34 | 60 | 4 | 111 | 23.4% | 160 | 28 | 44 | 46 | 40 | 4 |
| B. SaadL | 78 | 16.3 | 24 | 25 | 49 | 8 | 158 | 15.2% | 20 | 20 | 45 | 25 | 10 | 11 |
 Scott PerunovichD | 19 | 15.5 | — | 6 | 6 | — | 14 | 0% | 5 | 12 | 6 | 7 | 8 | 2 |
 Calle RosenD | 18 | 14.3 | 2 | 5 | 7 | — | 18 | 11.1% | 6 | 16 | 3 | 11 | 4 | -2 |
| R. BortuzzoD | 73 | 13.7 | 1 | 5 | 6 | — | 47 | 2.1% | 135 | 98 | 8 | 20 | 36 | -4 |
 Oskar SundqvistC | 41 | 13.4 | 4 | 11 | 15 | — | 50 | 8% | 49 | 19 | 10 | 17 | 12 | 4 |
| T. BozakC | 50 | 12.2 | 3 | 9 | 12 | — | 46 | 6.5% | 20 | 21 | 20 | 13 | 14 | -11 |
 Jake WalmanD | 32 | 12.0 | 3 | 3 | 6 | — | 48 | 6.3% | 21 | 26 | 5 | 11 | 6 | 3 |
| J. NealL | 19 | 12.0 | 2 | 2 | 4 | 1 | 31 | 6.5% | 17 | 3 | 2 | 4 | — | -1 |
 Nathan WalkerL | 30 | 11.5 | 8 | 4 | 12 | — | 38 | 21.1% | 58 | 22 | 8 | 6 | 2 | 1 |
| K. CliffordL | 2 | 11.2 | — | 1 | 1 | — | 5 | 0% | 2 | — | — | 1 | — | -1 |
 Alexey ToropchenkoR | 28 | 10.7 | 2 | — | 2 | — | 43 | 4.7% | 69 | 21 | 5 | 5 | 15 | -9 |
| L. BrownC | 39 | 10.2 | 4 | 7 | 11 | — | 34 | 11.8% | 22 | 13 | 7 | 13 | 8 | -3 |
| M. PecaC | 5 | 9.6 | — | 1 | 1 | — | 3 | 0% | 3 | 1 | — | 2 | — | -1 |
 Jake NeighboursL | 9 | 9.3 | 1 | 1 | 2 | — | 8 | 12.5% | 10 | 1 | — | 1 | 2 | -2 |
| K. KostinC | 40 | 9.0 | 4 | 5 | 9 | — | 31 | 12.9% | 90 | 9 | 9 | 16 | 23 | -3 |
 Dakota JoshuaC | 30 | 8.5 | 3 | 5 | 8 | — | 31 | 9.7% | 77 | 10 | 7 | 8 | 16 | 6 |
 Mackenzie MacEachernL | 14 | 8.0 | — | 2 | 2 | — | 14 | 0% | 19 | 1 | 7 | 2 | 4 | -1 |
 Ville HussoG | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
 Jordan BinningtonG | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
 Charlie LindgrenG | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
 Joel HoferG | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
| J. GilliesG | — | — | — | — | — | — | — | — | — | — | — | — | — | — |
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.