On-ice results
Sequence xG (sxGF%) Leaders
2025-26All situationsThrough 82 team games
Plain expected goals add up every shot in a scramble as if each one were a fresh chance, even though only one goal can come out of it. Sequence xG discounts each follow-up attempt by the chance the play was already over: a shot worth 0.30 after a 0.25 rebound counts as 0.30 × 0.75.
That takes about 5.5% out of the league total, but it moves individual players much more: skaters whose lines live on second and third whacks drop, and clean one-shot rush lines rise.
Leader in 2025-26: Brady Tkachuk (OTT), 68.0% sxGF%.
Sequence xG leaderboard
| # | Player | Team | |||||
|---|---|---|---|---|---|---|---|
| 1 | Brady TkachukFOTT | OTT | 68.0% | 1,018 | 4.80 | 2.25 | 100%▲2 |
| 2 | Nathan MacKinnonFCOL | COL | 66.1% | 1,781 | 4.96 | 2.55 | 100%▲0.9 |
| 3 | Nikita KucherovFTBL | TBL | 65.8% | 1,545 | 5.13 | 2.67 | 100% |
| 4 | Mark StoneFVGK | VGK | 65.7% | 1,153 | 4.58 | 2.40 | 93%▲9.6 |
| 5 | Jason RobertsonFDAL | DAL | 65.6% | 1,661 | 4.49 | 2.35 | 100% |
| 6 | Gabriel LandeskogFCOL | COL | 65.4% | 985 | 4.47 | 2.37 | 50%▲32 |
| 7 | Dylan CozensFOTT | OTT | 65.3% | 1,397 | 3.96 | 2.10 | 90%▲3.9 |
| 8 | Zach HymanFEDM | EDM | 65.3% | 1,159 | 5.10 | 2.71 | 98%▼1.8 |
| 9 | Roope HintzFDAL | DAL | 65.2% | 919 | 4.15 | 2.21 | 84%▲7.1 |
| 10 | Denver BarkeyFPHI | PHI | 64.6% | 577 | 3.36 | 1.84 | 15%▲14 |
| 11 | Oliver BjorkstrandFTBL | TBL | 64.1% | 1,091 | 3.45 | 1.93 | 20% |
| 12 | Shayne GostisbehereDCAR | CAR | 64.1% | 1,058 | 4.07 | 2.28 | 96%▲16 |
| 13 | Pavel DorofeyevFVGK | VGK | 63.9% | 1,444 | 4.00 | 2.26 | 92%▲1.8 |
| 14 | Leon DraisaitlFEDM | EDM | 63.9% | 1,402 | 4.67 | 2.64 | 100% |
| 15 | Tomas HertlFVGK | VGK | 63.8% | 1,397 | 4.25 | 2.41 | 84%▲3.2 |
| 16 | Martin NecasFCOL | COL | 63.8% | 1,677 | 4.45 | 2.53 | 100%▲1.8 |
| 17 | Josh NorrisFBUF | BUF | 63.7% | 697 | 4.41 | 2.51 | 39%▲32 |
| 18 | Connor McDavidFEDM | EDM | 63.7% | 1,885 | 4.85 | 2.76 | 100%▲1.5 |
| 19 | Mats ZuccarelloFMIN | MIN | 63.4% | 1,100 | 4.12 | 2.38 | 51%▲29 |
| 20 | Barrett HaytonFUTA | UTA | 63.4% | 998 | 3.52 | 2.03 | 11%▲11 |
| 21 | Drake BathersonFOTT | OTT | 63.3% | 1,371 | 3.91 | 2.27 | 97%▲7.2 |
| 22 | Jordan SpenceDOTT | OTT | 63.0% | 1,367 | 3.39 | 1.99 | 21%▲17 |
| 23 | Alex DeBrincatFDET | DET | 63.0% | 1,517 | 4.55 | 2.68 | 100%▲2.5 |
| 24 | Mikko RantanenFDAL | DAL | 63.0% | 1,291 | 4.28 | 2.52 | 99%▲0.5 |
| 25 | Nikolaj EhlersFCAR | CAR | 62.9% | 1,361 | 3.98 | 2.35 | 93%▲7.5 |
| 26 | Kirill KaprizovFMIN | MIN | 62.8% | 1,727 | 4.18 | 2.47 | 98%▼0.9 |
| 27 | Clayton KellerFUTA | UTA | 62.4% | 1,565 | 4.04 | 2.44 | 100%▲2.1 |
| 28 | Darren RaddyshDTBL | TBL | 62.2% | 1,657 | 4.15 | 2.52 | 99%▲3.2 |
| 29 | Victor OlofssonFCOL/CGY | COL/CGY | 61.9% | 1,058 | 3.30 | 2.03 | 14%▲14 |
| 30 | Brayden PointFTBL | TBL | 61.8% | 1,150 | 4.00 | 2.47 | 95%▲7.5 |
| 31 | Andrei SvechnikovFCAR | CAR | 61.7% | 1,342 | 4.38 | 2.72 | 97%▲8.8 |
| 32 | Jack EichelFVGK | VGK | 61.7% | 1,569 | 4.39 | 2.73 | 99%▲1.4 |
| 33 | Mitch MarnerFVGK | VGK | 61.7% | 1,617 | 3.94 | 2.45 | 99%▲1.3 |
| 34 | Logan StankovenFCAR | CAR | 61.6% | 1,251 | 3.71 | 2.31 | 67%▲42 |
| 35 | Evgeni MalkinFPIT | PIT | 61.6% | 985 | 4.37 | 2.73 | 82%▲11 |
| 36 | Cole CaufieldFMTL | MTL | 61.5% | 1,473 | 4.29 | 2.68 | 100%▲1.2 |
| 37 | Jordan KyrouFSTL | STL | 61.5% | 1,133 | 3.40 | 2.13 | 80%▲3.7 |
| 38 | Patrick KaneFDET | DET | 61.2% | 1,186 | 4.31 | 2.74 | 80%▲0.9 |
| 39 | Wyatt JohnstonFDAL | DAL | 61.1% | 1,650 | 4.34 | 2.77 | 100%▲0.9 |
| 40 | Jackson BlakeFCAR | CAR | 61.1% | 1,336 | 3.96 | 2.53 | 69%▲21 |
| 41 | Jack HughesFNJD | NJD | 60.8% | 1,300 | 4.31 | 2.78 | 100% |
| 42 | Jesper BrattFNJD | NJD | 60.7% | 1,539 | 4.40 | 2.85 | 97%▲11 |
| 43 | Cale MakarDCOL | COL | 60.7% | 1,864 | 4.09 | 2.65 | 100%▲1 |
| 44 | Nick SuzukiFMTL | MTL | 60.7% | 1,707 | 4.25 | 2.76 | 100%▲0.5 |
| 45 | Seth JarvisFCAR | CAR | 60.6% | 1,340 | 4.41 | 2.86 | 95%▲1.4 |
| 46 | Evan BouchardDEDM | EDM | 60.6% | 2,024 | 4.45 | 2.89 | 100% |
| 47 | Jake GuentzelFTBL | TBL | 60.4% | 1,640 | 4.23 | 2.78 | 100% |
| 48 | Trevor ZegrasFPHI | PHI | 60.3% | 1,516 | 3.78 | 2.49 | 86%▲18 |
| 49 | Lucas RaymondFDET | DET | 60.3% | 1,504 | 4.11 | 2.71 | 96%▲10 |
| 50 | Quinn HughesDMIN/VAN | MIN/VAN | 60.1% | 2,053 | 4.04 | 2.68 | 100% |
| 51 | Ivan DemidovFMTL | MTL | 60.1% | 1,271 | 4.13 | 2.74 | 91%▲22 |
| 52 | Josh DoanFBUF | BUF | 60.1% | 1,301 | 3.85 | 2.56 | 61%▲44 |
| 53 | Brock NelsonFCOL | COL | 59.9% | 1,592 | 3.99 | 2.67 | 88%▼3.6 |
| 54 | Andrei KuzmenkoFLAK | LAK | 59.9% | 776 | 3.46 | 2.32 | 11%▲9.8 |
| 55 | Mackie SamoskevichFFLA | FLA | 59.8% | 1,114 | 3.39 | 2.28 | — |
| 56 | Troy TerryFANA | ANA | 59.7% | 1,119 | 4.18 | 2.82 | 47%▲34 |
| 57 | Lane HutsonDMTL | MTL | 59.7% | 1,949 | 3.83 | 2.58 | 99%▲3.1 |
| 58 | Taylor HallFCAR | CAR | 59.7% | 1,162 | 3.63 | 2.45 | 28%▲20 |
| 59 | Alex OvechkinFWSH | WSH | 59.6% | 1,431 | 4.20 | 2.85 | 96%▲1.2 |
| 60 | Matthew TkachukFFLA | FLA | 59.5% | 567 | 4.52 | 3.07 | 100%▲2.6 |
| 61 | Jared McCannFSEA | SEA | 59.5% | 855 | 3.98 | 2.70 | 72%▲1.9 |
| 62 | Ross ColtonFCOL | COL | 59.5% | 914 | 3.18 | 2.16 | 8.1%▲7.8 |
| 63 | Danton HeinenFCBJ/PIT | CBJ/PIT | 59.4% | 522 | 2.56 | 1.75 | 0.0% |
| 64 | Sebastian AhoFCAR | CAR | 59.4% | 1,549 | 4.39 | 3.00 | 99%▲1.2 |
| 65 | Kevin FialaFLAK | LAK | 59.3% | 1,071 | 3.56 | 2.45 | 67%▼8.3 |
| 66 | Artturi LehkonenFCOL | COL | 59.2% | 1,294 | 3.76 | 2.59 | 57%▲40 |
| 67 | Dylan GuentherFUTA | UTA | 59.2% | 1,374 | 3.97 | 2.74 | 99%▲1.7 |
| 68 | Bobby BrinkFPHI/MIN | PHI/MIN | 59.2% | 1,031 | 2.99 | 2.07 | 14%▲12 |
| 69 | Michael CarconeFUTA | UTA | 59.2% | 1,005 | 3.10 | 2.14 | 5.0%▲4 |
| 70 | Juraj SlafkovskýFMTL | MTL | 59.1% | 1,520 | 4.31 | 2.98 | 100%▲1.5 |
| 71 | Sam MalinskiDCOL | COL | 59.1% | 1,445 | 3.05 | 2.11 | 55%▲32 |
| 72 | Gage GoncalvesFTBL | TBL | 59.0% | 969 | 2.81 | 1.95 | 11%▲11 |
| 73 | Zach BensonFBUF | BUF | 58.9% | 1,033 | 3.47 | 2.42 | 56%▲44 |
| 74 | Brandon HagelFTBL | TBL | 58.8% | 1,403 | 4.51 | 3.16 | 99%▲1.4 |
| 75 | Adam FoxDNYR | NYR | 58.8% | 1,300 | 3.74 | 2.63 | 99%▲6.8 |
| 76 | Matvei MichkovFPHI | PHI | 58.7% | 1,202 | 3.32 | 2.34 | 86%▲23 |
| 77 | Owen TippettFPHI | PHI | 58.7% | 1,364 | 3.50 | 2.47 | 78%▼7 |
| 78 | Tyson FoersterFPHI | PHI | 58.4% | 502 | 3.08 | 2.19 | 42%▲38 |
| 79 | Leo CarlssonFANA | ANA | 58.4% | 1,341 | 4.26 | 3.04 | 94%▲11 |
| 80 | Noah CatesFPHI | PHI | 58.3% | 1,332 | 2.97 | 2.12 | 18%▲15 |
| 81 | Damon SeversonDCBJ | CBJ | 58.3% | 1,496 | 3.13 | 2.24 | 9.4%▲6.2 |
| 82 | Tim StützleFOTT | OTT | 58.2% | 1,621 | 3.94 | 2.83 | 99%▲0.8 |
| 83 | Kirill MarchenkoFCBJ | CBJ | 58.2% | 1,440 | 3.80 | 2.73 | 98%▲7.4 |
| 84 | Fabian ZetterlundFOTT | OTT | 58.2% | 1,059 | 3.03 | 2.18 | 13%▲6.6 |
| 85 | William CarrierFCAR | CAR | 58.1% | 753 | 2.48 | 1.79 | 0.1% |
| 86 | Jason ZuckerFBUF | BUF | 58.1% | 969 | 3.90 | 2.81 | 23%▲17 |
| 87 | Ethen FrankFWSH | WSH | 58.1% | 759 | 2.94 | 2.12 | 3.2%▲3.1 |
| 88 | Luke EvangelistaFNSH | NSH | 58.0% | 1,346 | 3.61 | 2.61 | 70%▲23 |
| 89 | Mason MarchmentFCBJ/SEA | CBJ/SEA | 57.9% | 1,181 | 3.31 | 2.41 | 47%▲34 |
| 90 | Mathew BarzalFNYI | NYI | 57.8% | 1,674 | 3.93 | 2.87 | 84%▲11 |
| 91 | Ryan HartmanFMIN | MIN | 57.7% | 1,273 | 3.37 | 2.47 | 40%▼17 |
| 92 | Dylan HollowayFSTL | STL | 57.6% | 1,077 | 3.51 | 2.58 | 95%▲9.4 |
| 93 | Jamie DrysdaleDPHI | PHI | 57.6% | 1,681 | 3.16 | 2.32 | 55%▲46 |
| 94 | Matt BoldyFMIN | MIN | 57.6% | 1,563 | 3.98 | 2.93 | 100% |
| 95 | Tage ThompsonFBUF | BUF | 57.6% | 1,559 | 3.92 | 2.88 | 100%▲1.3 |
| 96 | Moritz SeiderDDET | DET | 57.6% | 2,105 | 3.66 | 2.70 | 100%▲0.6 |
| 97 | Valeri NichushkinFCOL | COL | 57.5% | 1,276 | 3.67 | 2.71 | 60% |
| 98 | Zachary BolducFMTL | MTL | 57.5% | 1,063 | 3.05 | 2.25 | 21%▲19 |
| 99 | Viktor ArvidssonFBOS | BOS | 57.5% | 1,007 | 3.54 | 2.61 | 33%▲23 |
| 100 | Mavrik BourqueFDAL | DAL | 57.5% | 1,270 | 3.01 | 2.22 | 34%▲30 |
Minimum sample: 492 min (it scales with games played and sequence coverage). 321 below the minimum are hidden.
How to read it
Read it like xGF%: 50% is even. Compare it with the plain xGF% column to see whose numbers are inflated by flurries.
How reliable is it?
Shares the stability of on-ice xGF%. The flurry discount itself is mechanical (no fitted parameters), so it adds no noise.
How Sequence xG is calculated →Related leaderboards
- 5v5 xGF%50% is break-even. 55% means the skater's team took 55% of the expected goals while he was on the ice.
- Shot DietExpected goals per unblocked attempt. League average is about 0.06-0.07; 0.10+ is an elite diet.
- HDCF/60League average at 5-on-5 is roughly 10-12 HDCF/60 per team; the leaders sit well above that.