Counting stats
NHL Power-Play Points per 60 Leaders
2025-26All situationsThrough 83 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 2025-26: Leon Draisaitl (EDM), 1.80 PPP/60.
Power-Play Points per 60 leaderboard
| # | Player | Team | PPP/60 | PPP | ||
|---|---|---|---|---|---|---|
| 1 | Leon DraisaitlFEDM | EDM | 1.80 | 1,402 | 42 | 100% |
| 2 | Connor McDavidFEDM | EDM | 1.72 | 1,885 | 54 | 100%▲1.5 |
| 3 | Mikko RantanenFDAL | DAL | 1.58 | 1,291 | 34 | 99%▲0.5 |
| 4 | Wyatt JohnstonFDAL | DAL | 1.53 | 1,650 | 42 | 100%▲0.9 |
| 5 | Nick SuzukiFMTL | MTL | 1.51 | 1,707 | 43 | 100%▲0.5 |
| 6 | Jason RobertsonFDAL | DAL | 1.48 | 1,661 | 41 | 100% |
| 7 | Mark StoneFVGK | VGK | 1.46 | 1,153 | 28 | 93%▲9.6 |
| 8 | Nikita KucherovFTBL | TBL | 1.44 | 1,545 | 37 | 100% |
| 9 | Matthew TkachukFFLA | FLA | 1.37 | 567 | 13 | 100%▲2.6 |
| 10 | Brad MarchandFFLA | FLA | 1.37 | 922 | 21 | 73%▲0.7 |
| 11 | Evgeni MalkinFPIT | PIT | 1.34 | 985 | 22 | 82%▲11 |
| 12 | Drake BathersonFOTT | OTT | 1.31 | 1,371 | 30 | 97%▲7.2 |
| 13 | Ryan Nugent-HopkinsFEDM | EDM | 1.27 | 1,372 | 29 | 77%▲15 |
| 14 | Andrei SvechnikovFCAR | CAR | 1.25 | 1,342 | 28 | 97%▲8.8 |
| 15 | Pavel DorofeyevFVGK | VGK | 1.25 | 1,444 | 30 | 92%▲1.8 |
| 16 | Dylan CozensFOTT | OTT | 1.25 | 1,397 | 29 | 90%▲3.9 |
| 17 | Mika ZibanejadFNYR | NYR | 1.24 | 1,693 | 35 | 98%▲1.4 |
| 18 | Roope HintzFDAL | DAL | 1.24 | 919 | 19 | 84%▲7.1 |
| 19 | Nikolaj EhlersFCAR | CAR | 1.23 | 1,361 | 28 | 93%▲7.5 |
| 20 | David PastrnakFBOS | BOS | 1.21 | 1,590 | 32 | 100%▲1.1 |
| 21 | Cole CaufieldFMTL | MTL | 1.18 | 1,473 | 29 | 100%▲1.2 |
| 22 | Brady TkachukFOTT | OTT | 1.18 | 1,018 | 20 | 100%▲2 |
| 23 | Matt BoldyFMIN | MIN | 1.15 | 1,563 | 30 | 100% |
| 24 | Mats ZuccarelloFMIN | MIN | 1.15 | 1,100 | 21 | 51%▲29 |
| 25 | Macklin CelebriniFSJS | SJS | 1.13 | 1,748 | 33 | 100%▲1 |
| 26 | Tomas HertlFVGK | VGK | 1.12 | 1,397 | 26 | 84%▲3.2 |
| 27 | Kirill KaprizovFMIN | MIN | 1.11 | 1,727 | 32 | 98%▼0.9 |
| 28 | Jack EichelFVGK | VGK | 1.11 | 1,569 | 29 | 99%▲1.4 |
| 29 | Adam FoxDNYR | NYR | 1.11 | 1,300 | 24 | 99%▲6.8 |
| 30 | Juraj SlafkovskýFMTL | MTL | 1.11 | 1,520 | 28 | 100%▲1.5 |
| 31 | Sam ReinhartFFLA | FLA | 1.10 | 1,362 | 25 | 99% |
| 32 | Jake GuentzelFTBL | TBL | 1.10 | 1,640 | 30 | 100% |
| 33 | Lucas RaymondFDET | DET | 1.08 | 1,504 | 27 | 96%▲10 |
| 34 | Tim StützleFOTT | OTT | 1.07 | 1,621 | 29 | 99%▲0.8 |
| 35 | Steven StamkosFNSH | NSH | 1.07 | 1,462 | 26 | 94%▼4.2 |
| 36 | Jack HughesFNJD | NJD | 1.06 | 1,300 | 23 | 100% |
| 37 | Sidney CrosbyFPIT | PIT | 1.06 | 1,308 | 23 | 100%▲2.4 |
| 38 | Jake DeBruskFVAN | VAN | 1.05 | 1,366 | 24 | 49%▼20 |
| 39 | Dylan GuentherFUTA | UTA | 1.05 | 1,374 | 24 | 99%▲1.7 |
| 40 | Clayton KellerFUTA | UTA | 1.04 | 1,565 | 27 | 100%▲2.1 |
| 41 | Shayne GostisbehereDCAR | CAR | 1.02 | 1,058 | 18 | 96%▲16 |
| 42 | Nathan MacKinnonFCOL | COL | 1.01 | 1,781 | 30 | 100%▲0.9 |
| 43 | Filip ForsbergFNSH | NSH | 1.01 | 1,549 | 26 | 99%▲1.7 |
| 44 | Sebastian AhoFCAR | CAR | 1.01 | 1,549 | 26 | 99%▲1.2 |
| 45 | Andrei KuzmenkoFLAK | LAK | 1.01 | 776 | 13 | 11%▲9.8 |
| 46 | Pavel ZachaFBOS | BOS | 1.00 | 1,314 | 22 | 78%▲13 |
| 47 | Bryan RustFPIT | PIT | 1.00 | 1,436 | 24 | 85%▲2.5 |
| 48 | William NylanderFTOR | TOR | 1.00 | 1,262 | 21 | 99%▼0.8 |
| 49 | Quinn HughesDMIN | MIN | 0.99 | 2,053 | 34 | 100% |
| 50 | Jason ZuckerFBUF | BUF | 0.99 | 969 | 16 | 23%▲17 |
| 51 | Morgan GeekieFBOS | BOS | 0.98 | 1,410 | 23 | 96%▲7.9 |
| 52 | Evan BouchardDEDM | EDM | 0.98 | 2,024 | 33 | 100% |
| 53 | Elias LindholmFBOS | BOS | 0.97 | 1,234 | 20 | 43%▲4.7 |
| 54 | Dylan LarkinFDET | DET | 0.96 | 1,494 | 24 | 96% |
| 55 | Patrick KaneFDET | DET | 0.96 | 1,186 | 19 | 80%▲0.9 |
| 56 | Marco RossiFVAN | VAN | 0.96 | 874 | 14 | 60%▲14 |
| 57 | Kirill MarchenkoFCBJ | CBJ | 0.96 | 1,440 | 23 | 98%▲7.4 |
| 58 | Kevin FialaFLAK | LAK | 0.95 | 1,071 | 17 | 67%▼8.3 |
| 59 | Ivan DemidovFMTL | MTL | 0.94 | 1,271 | 20 | 91%▲22 |
| 60 | Darren RaddyshDTBL | TBL | 0.94 | 1,657 | 26 | 99%▲3.2 |
| 61 | Elias PetterssonFVAN | VAN | 0.94 | 1,403 | 22 | 87%▼5.5 |
| 62 | Seth JarvisFCAR | CAR | 0.94 | 1,340 | 21 | 95%▲1.4 |
| 63 | Gabriel VilardiFWPG | WPG | 0.94 | 1,537 | 24 | 80%▲7.7 |
| 64 | Cale MakarDCOL | COL | 0.93 | 1,864 | 29 | 100%▲1 |
| 65 | Tage ThompsonFBUF | BUF | 0.92 | 1,559 | 24 | 100%▲1.3 |
| 66 | Jared McCannFSEA | SEA | 0.91 | 855 | 13 | 72%▲1.9 |
| 67 | Trevor ZegrasFPHI | PHI | 0.91 | 1,516 | 23 | 86%▲18 |
| 68 | Alex DeBrincatFDET | DET | 0.91 | 1,517 | 23 | 100%▲2.5 |
| 69 | Matt DucheneFDAL | DAL | 0.89 | 941 | 14 | 62%▼17 |
| 70 | Mitch MarnerFVGK | VGK | 0.89 | 1,617 | 24 | 99%▲1.3 |
| 71 | Erik KarlssonDPIT | PIT | 0.88 | 1,770 | 26 | 95% |
| 72 | Connor BedardFCHI | CHI | 0.88 | 1,440 | 21 | 98%▲3.6 |
| 73 | Dylan StromeFWSH | WSH | 0.87 | 1,443 | 21 | 83%▲11 |
| 74 | Cutter GauthierFANA | ANA | 0.87 | 1,311 | 19 | 98%▲1.3 |
| 75 | Tyler BertuzziFCHI | CHI | 0.86 | 1,457 | 21 | 62%▼3.5 |
| 76 | Miro HeiskanenDDAL | DAL | 0.86 | 1,961 | 28 | 99%▲4.3 |
| 77 | Teuvo TeravainenFCHI | CHI | 0.86 | 1,331 | 19 | 13%▲8.6 |
| 78 | Roman JosiDNSH | NSH | 0.85 | 1,692 | 24 | 98%▼0.5 |
| 79 | Artemi PanarinFLAK | LAK | 0.85 | 1,626 | 23 | 97%▼1.8 |
| 80 | Chris KreiderFANA | ANA | 0.84 | 1,279 | 18 | 62%▲29 |
| 81 | Rickard RakellFPIT | PIT | 0.84 | 1,137 | 16 | 83%▲11 |
| 82 | J.T. MillerFNYR | NYR | 0.83 | 1,370 | 19 | 92%▲7.7 |
| 83 | Mikhail SergachevDUTA | UTA | 0.82 | 1,895 | 26 | 98%▲5.2 |
| 84 | Martin NecasFCOL | COL | 0.82 | 1,677 | 23 | 100%▲1.8 |
| 85 | Will SmithFSJS | SJS | 0.81 | 1,255 | 17 | 95%▲23 |
| 86 | Nico HischierFNJD | NJD | 0.81 | 1,699 | 23 | 97%▲2.3 |
| 87 | Leo CarlssonFANA | ANA | 0.81 | 1,341 | 18 | 94%▲11 |
| 88 | John TavaresFTOR | TOR | 0.81 | 1,491 | 20 | 96%▲9.3 |
| 89 | Moritz SeiderDDET | DET | 0.80 | 2,105 | 28 | 100%▲0.6 |
| 90 | Brock BoeserFVAN | VAN | 0.80 | 1,429 | 19 | 64%▼4.5 |
| 91 | Alex OvechkinFWSH | WSH | 0.80 | 1,431 | 19 | 96%▲1.2 |
| 92 | Jake SandersonDOTT | OTT | 0.79 | 1,664 | 22 | 99%▲2.9 |
| 93 | Corey PerryFTBL | TBL | 0.79 | 984 | 13 | 7.4%▲5.9 |
| 94 | Charlie McAvoyDBOS | BOS | 0.78 | 1,683 | 22 | 97%▲6.2 |
| 95 | Josh DoanFBUF | BUF | 0.78 | 1,301 | 17 | 61%▲44 |
| 96 | James van RiemsdykFDET | DET | 0.78 | 846 | 11 | 0.3% |
| 97 | Jesper BrattFNJD | NJD | 0.78 | 1,539 | 20 | 97%▲11 |
| 98 | Seth JonesDFLA | FLA | 0.78 | 1,232 | 16 | 80%▲32 |
| 99 | Nazem KadriFCOL | COL | 0.78 | 1,466 | 19 | 71%▼9 |
| 100 | Ryan LeonardFWSH | WSH | 0.78 | 1,081 | 14 | 66%▲42 |
Minimum sample: 498 minutes (it scales with games played). 324 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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