Counting stats
NHL Power-Play Points per 60 Leaders
2019-20All situationsThrough 71 team games
This board ranks skaters by power-play points per 60 minutes of ice time in all situations, so a fourth-liner who plays 9 minutes is compared fairly with a top-pair defenseman who plays 25. Players under the minimum-minutes cutoff are hidden.
Power-play points are goals and assists scored with the man advantage. They belong almost entirely to first-unit (PP1) players, so the board doubles as a map of who runs each power play. Rates surface low-minute players who already produce; they are the ones to grab when an injury opens up ice time.
Leader in 2019-20: Connor McDavid (EDM), 1.76 PPP/60.
Power-Play Points per 60 leaderboard
| # | Player | Team | PPP/60 | PPP | ||
|---|---|---|---|---|---|---|
| 1 | Connor McDavidFEDM | EDM | 1.76 | 1,399 | 41 | 100%▲1.5 |
| 2 | David PastrnakFBOS | BOS | 1.63 | 1,327 | 36 | 100%▲1.1 |
| 3 | Leon DraisaitlFEDM | EDM | 1.61 | 1,605 | 43 | 100% |
| 4 | Mika ZibanejadFNYR | NYR | 1.31 | 1,233 | 27 | 98%▲1.4 |
| 5 | Jonathan HuberdeauFFLA | FLA | 1.30 | 1,295 | 28 | 17%▲12 |
| 6 | Torey KrugDBOS | BOS | 1.30 | 1,250 | 27 | 0.0% |
| 7 | Evgeni MalkinFPIT | PIT | 1.29 | 1,074 | 23 | 82%▲11 |
| 8 | Travis KonecnyFPHI | PHI | 1.24 | 1,109 | 23 | 92%▲9.6 |
| 9 | Sidney CrosbyFPIT | PIT | 1.23 | 831 | 17 | 100%▲2.4 |
| 10 | Brad MarchandFBOS | BOS | 1.19 | 1,362 | 27 | 73%▲0.7 |
| 11 | Nathan MacKinnonFCOL | COL | 1.19 | 1,464 | 29 | 100%▲0.9 |
| 12 | Elias PetterssonFVAN | VAN | 1.14 | 1,260 | 24 | 87%▼5.5 |
| 13 | Nikita KucherovFTBL | TBL | 1.12 | 1,283 | 24 | 100% |
| 14 | David PerronFSTL | STL | 1.11 | 1,300 | 24 | 0.2% |
| 15 | Kevin FialaFMIN | MIN | 1.10 | 986 | 18 | 67%▼8.3 |
| 16 | Ryan Nugent-HopkinsFEDM | EDM | 1.08 | 1,330 | 24 | 77%▲15 |
| 17 | Auston MatthewsFTOR | TOR | 1.06 | 1,468 | 26 | 99% |
| 18 | J.T. MillerFVAN | VAN | 1.04 | 1,387 | 24 | 92%▲7.7 |
| 19 | Mitch MarnerFTOR | TOR | 1.04 | 1,272 | 22 | 99%▲1.3 |
| 20 | Nicklas BackstromFWSH | WSH | 1.03 | 1,160 | 20 | — |
| 21 | Mike HoffmanFFLA | FLA | 1.03 | 1,162 | 20 | — |
| 22 | Steven StamkosFTBL | TBL | 1.03 | 1,050 | 18 | 94%▼4.2 |
| 23 | James NealFEDM | EDM | 1.00 | 897 | 15 | — |
| 24 | Andrei SvechnikovFCAR | CAR | 1.00 | 1,138 | 19 | 97%▲8.8 |
| 25 | Jack EichelFBUF | BUF | 1.00 | 1,503 | 25 | 99%▲1.4 |
| 26 | Artemi PanarinFNYR | NYR | 0.97 | 1,422 | 23 | 97%▼1.8 |
| 27 | Jakub VoracekFPHI | PHI | 0.97 | 1,176 | 19 | — |
| 28 | Claude GirouxFPHI | PHI | 0.96 | 1,310 | 21 | 30%▲20 |
| 29 | Rasmus DahlinDBUF | BUF | 0.95 | 1,138 | 18 | 100%▲1 |
| 30 | Quinn HughesDVAN | VAN | 0.93 | 1,488 | 23 | 100% |
| 31 | John TavaresFTOR | TOR | 0.93 | 1,232 | 19 | 96%▲9.3 |
| 32 | Teuvo TeravainenFCAR | CAR | 0.92 | 1,305 | 20 | 13%▲8.6 |
| 33 | Alex ChiassonFEDM | EDM | 0.91 | 853 | 13 | — |
| 34 | Zach PariseFMIN | MIN | 0.91 | 1,187 | 18 | — |
| 35 | Victor OlofssonFBUF | BUF | 0.91 | 993 | 15 | 14%▲14 |
| 36 | Mikko RantanenFCOL | COL | 0.90 | 796 | 12 | 99%▲0.5 |
| 37 | Adam GaudetteFVAN | VAN | 0.90 | 731 | 11 | 0.1% |
| 38 | Cale MakarDCOL | COL | 0.90 | 1,198 | 18 | 100%▲1 |
| 39 | Gabriel LandeskogFCOL | COL | 0.89 | 1,082 | 16 | 50%▲32 |
| 40 | Patrick KaneFCHI | CHI | 0.88 | 1,494 | 22 | 80%▲0.9 |
| 41 | Jaden SchwartzFSTL | STL | 0.88 | 1,291 | 19 | 11%▲11 |
| 42 | Bryan RustFPIT | PIT | 0.88 | 1,087 | 16 | 85%▲2.5 |
| 43 | Keith YandleDFLA | FLA | 0.88 | 1,359 | 20 | — |
| 44 | Brayden SchennFSTL | STL | 0.87 | 1,311 | 19 | 28%▲7.8 |
| 45 | Evander KaneFSJS | SJS | 0.86 | 1,250 | 18 | 5.7%▲0.8 |
| 46 | Kyle PalmieriFNJD | NJD | 0.86 | 1,112 | 16 | 19%▲10 |
| 47 | Matthew TkachukFCGY | CGY | 0.85 | 1,263 | 18 | 100%▲2.6 |
| 48 | Sean MonahanFCGY | CGY | 0.85 | 1,267 | 18 | 19%▲13 |
| 49 | Patrice BergeronFBOS | BOS | 0.84 | 1,142 | 16 | — |
| 50 | Blake WheelerFWPG | WPG | 0.83 | 1,372 | 19 | — |
| 51 | Tony DeAngeloDNYR | NYR | 0.82 | 1,312 | 18 | 24%▲18 |
| 52 | Aleksander BarkovFFLA | FLA | 0.82 | 1,321 | 18 | 97%▲7 |
| 53 | Andre BurakovskyFCOL | COL | 0.82 | 882 | 12 | 5.6%▲5.4 |
| 54 | John CarlsonDWSH | WSH | 0.81 | 1,700 | 23 | 99%▲2.4 |
| 55 | Nikita GusevFNJD | NJD | 0.80 | 970 | 13 | — |
| 56 | Max PaciorettyFVGK | VGK | 0.80 | 1,272 | 17 | — |
| 57 | Elias LindholmFCGY | CGY | 0.78 | 1,381 | 18 | 43%▲4.7 |
| 58 | Johnny GaudreauFCGY | CGY | 0.78 | 1,315 | 17 | — |
| 59 | William NylanderFTOR | TOR | 0.78 | 1,238 | 16 | 99%▼0.8 |
| 60 | Alex OvechkinFWSH | WSH | 0.77 | 1,405 | 18 | 96%▲1.2 |
| 61 | Kaapo KakkoFNYR | NYR | 0.76 | 942 | 12 | 18%▲16 |
| 62 | Evgenii DadonovFFLA | FLA | 0.76 | 1,180 | 15 | 0.1% |
| 63 | Mark StoneFVGK | VGK | 0.76 | 1,262 | 16 | 93%▲9.6 |
| 64 | Neal PionkDWPG | WPG | 0.76 | 1,660 | 21 | 32%▲31 |
| 65 | Tomas TatarFMTL | MTL | 0.76 | 1,108 | 14 | — |
| 66 | Victor HedmanDTBL | TBL | 0.76 | 1,588 | 20 | 93%▲11 |
| 67 | Phil KesselFARI | ARI | 0.75 | 1,200 | 15 | — |
| 68 | David KrejciFBOS | BOS | 0.74 | 1,048 | 13 | — |
| 69 | Eric StaalFMIN | MIN | 0.74 | 1,131 | 14 | — |
| 70 | Nazem KadriFCOL | COL | 0.74 | 889 | 11 | 71%▼9 |
| 71 | Nick SuzukiFMTL | MTL | 0.74 | 1,135 | 14 | 100%▲0.5 |
| 72 | Mark ScheifeleFWPG | WPG | 0.74 | 1,548 | 19 | 99% |
| 73 | Anze KopitarFLAK | LAK | 0.73 | 1,473 | 18 | 0.5% |
| 74 | Sebastian AhoFCAR | CAR | 0.73 | 1,321 | 16 | 99%▲1.2 |
| 75 | Nick SchmaltzFARI | ARI | 0.72 | 1,087 | 13 | 94%▲4.4 |
| 76 | Alex PietrangeloDSTL | STL | 0.71 | 1,693 | 20 | 4.0%▲3.7 |
| 77 | Roman JosiDNSH | NSH | 0.71 | 1,779 | 21 | 98%▼0.5 |
| 78 | Sean CouturierFPHI | PHI | 0.70 | 1,368 | 16 | 9.2%▲7.2 |
| 79 | Emil BemstromFCBJ | CBJ | 0.70 | 687 | 8 | — |
| 80 | Ryan O'ReillyFSTL | STL | 0.70 | 1,461 | 17 | 84%▲5 |
| 81 | Cody GlassFVGK | VGK | 0.69 | 521 | 6 | 4.9%▲4.5 |
| 82 | Jamie BennFDAL | DAL | 0.69 | 1,134 | 13 | 22%▲18 |
| 83 | Nico HischierFNJD | NJD | 0.69 | 1,048 | 12 | 97%▲2.3 |
| 84 | Alex DeBrincatFCHI | CHI | 0.69 | 1,225 | 14 | 100%▲2.5 |
| 85 | Alex TuchFVGK | VGK | 0.68 | 614 | 7 | 94%▼5.5 |
| 86 | Clayton KellerFARI | ARI | 0.68 | 1,141 | 13 | 100%▲2.1 |
| 87 | Mike ReillyDOTT | OTT | 0.68 | 793 | 9 | 0.1% |
| 88 | Roope HintzFDAL | DAL | 0.68 | 885 | 10 | 84%▲7.1 |
| 89 | Taylor HallFARI | ARI | 0.67 | 1,246 | 14 | 28%▲20 |
| 90 | Brayden PointFTBL | TBL | 0.67 | 1,248 | 14 | 95%▲7.5 |
| 91 | Jason ZuckerFPIT | PIT | 0.67 | 980 | 11 | 23%▲17 |
| 92 | Brad HuntDMIN | MIN | 0.67 | 893 | 10 | — |
| 93 | Jake GuentzelFPIT | PIT | 0.67 | 805 | 9 | 100% |
| 94 | Kevin StenlundFCBJ | CBJ | 0.67 | 447 | 5 | 0.1% |
| 95 | Chris KreiderFNYR | NYR | 0.66 | 1,087 | 12 | 62%▲29 |
| 96 | Bo HorvatFVAN | VAN | 0.66 | 1,362 | 15 | 90%▲1.2 |
| 97 | Filip ForsbergFNSH | NSH | 0.66 | 1,093 | 12 | 99%▲1.7 |
| 98 | Dougie HamiltonDCAR | CAR | 0.66 | 1,094 | 12 | 84%▲12 |
| 99 | Ryan StromeFNYR | NYR | 0.66 | 1,371 | 15 | 4.0%▲3.9 |
| 100 | John KlingbergDDAL | DAL | 0.65 | 1,286 | 14 | 0.2% |
Minimum sample: 426 minutes (it scales with games played). 286 below the minimum are hidden.
How to read it
Power-Play Points per 60 minutes of ice time, all situations.
How reliable is it?
Rates settle faster than totals but need minutes: early in the season, low-minute players swing the most.
About our data sources →Projected next
Our fantasy projections for power-play points: who should lead the coming games.
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