On-ice results

Sequence xG (sxGF%) Leaders

2024-255-on-5Through 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 2024-25: Jackson Blake (CAR), 60.9% sxGF%.

Season2026-27 2025-26 2024-25 2023-24

Strength5-on-5 Even strength All situations

595 qualified

Show

Sequence xG (sxGF%) Leaders, 2024-25, 5-on-5
#	Player	Team
1	Jackson BlakeFCAR	CAR	60.9%	914	2.92	1.88	61.3%	68%▲21
2	Leon DraisaitlFEDM	EDM	60.8%	1,182	3.46	2.23	61.1%	100%
3	Aleksander BarkovFFLA	FLA	59.9%	936	2.64	1.77	60.1%	97%▲7.2
4	Nathan MacKinnonFCOL	COL	59.8%	1,350	3.41	2.29	59.9%	100%▲0.8
5	Connor McDavidFEDM	EDM	59.7%	1,153	3.57	2.41	60.2%	100%▲1.5
6	Mattias EkholmDEDM	EDM	59.3%	1,171	3.24	2.22	59.8%	77%▲9.7
7	Anthony CirelliFTBL	TBL	59.2%	1,138	3.03	2.09	59.5%	51%▲19
8	Zach HymanFEDM	EDM	59.1%	1,080	3.38	2.34	59.7%	98%▼1.4
9	Seth JarvisFCAR	CAR	58.9%	957	2.95	2.06	59.6%	95%▲1.5
10	Shayne GostisbehereDCAR	CAR	58.7%	994	3.01	2.12	59.2%	96%▲16
11	Brandon HagelFTBL	TBL	58.5%	1,232	2.97	2.11	58.7%	100%▲1.9
12	Alex LaferriereFLAK	LAK	58.2%	1,086	2.68	1.92	58.6%	68%▲3.5
13	Evan BouchardDEDM	EDM	58.2%	1,524	3.20	2.30	58.4%	100%
14	Jack HughesFNJD	NJD	58.2%	952	3.01	2.17	58.2%	100%
15	Sam ReinhartFFLA	FLA	58.2%	1,122	2.45	1.76	58.2%	99%
16	Mark JankowskiFNSH/CAR	NSH/CAR	57.9%	622	2.56	1.86	58.3%	0.2%
17	Nate SchmidtDFLA	FLA	57.9%	1,139	2.47	1.80	58.2%	4.9%▲4.5
18	Josh DoanFUTA	UTA	57.9%	600	2.50	1.82	58.7%	61%▲44
19	Kevin FialaFLAK	LAK	57.8%	1,181	2.66	1.94	58.0%	67%▼8.4
20	Cale MakarDCOL	COL	57.6%	1,457	3.05	2.25	57.6%	100%▲1
21	Artturi LehkonenFCOL	COL	57.6%	1,100	3.13	2.31	57.5%	54%▲37
22	Robert ThomasFSTL	STL	57.5%	1,032	3.07	2.26	57.4%	93%▲20
23	Warren FoegeleFLAK	LAK	57.5%	1,098	2.50	1.85	58.2%	4.0%▲3.9
24	Carter VerhaegheFFLA	FLA	57.2%	1,148	2.86	2.14	57.3%	73%▲1
25	Phillip DanaultFLAK	LAK	57.2%	1,095	2.59	1.94	57.6%	4.9%▲4.5
26	Mackie SamoskevichFFLA	FLA	57.2%	808	2.59	1.94	57.3%	—
27	Nikolaj EhlersFWPG	WPG	57.0%	858	2.67	2.01	57.1%	93%▲7.9
28	Nikita KucherovFTBL	TBL	57.0%	1,263	3.28	2.47	56.6%	100%
29	Jordan SpenceDLAK	LAK	56.9%	1,147	2.41	1.83	57.2%	21%▲17
30	Victor OlofssonFVGK	VGK	56.8%	715	2.28	1.73	56.7%	12%▲12
31	Vasily PodkolzinFEDM	EDM	56.8%	1,009	2.61	1.98	56.9%	64%▲55
32	Uvis BalinskisDFLA	FLA	56.8%	997	2.32	1.77	57.0%	4.0%▲3.9
33	Sean MonahanFCBJ	CBJ	56.7%	743	2.98	2.28	56.7%	19%▲13
34	Brady TkachukFOTT	OTT	56.7%	985	2.80	2.14	56.8%	100%▲2.2
35	Barrett HaytonFUTA	UTA	56.7%	1,028	2.94	2.25	57.0%	11%▲11
36	Mark StoneFVGK	VGK	56.7%	953	2.84	2.17	56.9%	93%▲9
37	Jesperi KotkaniemiFCAR	CAR	56.6%	968	2.73	2.09	56.5%	3.2%▲3.1
38	Matthew TkachukFFLA	FLA	56.5%	716	2.95	2.26	57.1%	100%▲2.7
39	Quinton ByfieldFLAK	LAK	56.4%	1,141	2.50	1.94	57.0%	86%▲18
40	Sebastian AhoFCAR	CAR	56.3%	1,075	3.09	2.40	56.8%	99%▲0.9
41	Joel KivirantaFCOL	COL	56.2%	854	2.19	1.71	56.3%	0.1%
42	Auston MatthewsFTOR	TOR	56.2%	954	2.98	2.33	56.2%	99%
43	Jack EichelFVGK	VGK	56.1%	1,149	2.94	2.30	56.1%	99%▲1.4
44	Pavel DorofeyevFVGK	VGK	56.1%	1,124	2.65	2.07	56.0%	92%▲1.7
45	Alex TurcotteFLAK	LAK	56.0%	737	2.34	1.84	56.3%	8.8%▲8.8
46	Kaedan KorczakDVGK	VGK	56.0%	588	2.40	1.88	56.4%	6.7%▲6.5
47	Tomas NosekFFLA	FLA	56.0%	509	2.39	1.87	56.3%	—
48	Eric RobinsonFCAR	CAR	56.0%	935	2.79	2.19	55.9%	3.2%▲3.1
49	Nico HischierFNJD	NJD	55.9%	1,073	2.73	2.16	56.1%	98%▲3
50	Jesper BrattFNJD	NJD	55.8%	1,079	2.88	2.28	55.8%	96%▲11
51	Brayden McNabbDVGK	VGK	55.8%	1,439	2.54	2.01	55.7%	23%▲20
52	Chris TanevDTOR	TOR	55.7%	1,229	2.33	1.85	55.9%	6.0%▲5
53	Sean WalkerDCAR	CAR	55.6%	1,237	2.75	2.20	55.9%	60%▼11
54	Emil AndraeDPHI	PHI	55.6%	642	2.48	1.98	55.4%	8.8%▲8.6
55	William KarlssonFVGK	VGK	55.6%	707	2.47	1.97	55.8%	24%▲20
56	Tomas HertlFVGK	VGK	55.6%	985	2.71	2.17	55.5%	83%▲2.9
57	Devon ToewsDCOL	COL	55.6%	1,506	2.78	2.22	55.5%	60%▼2.3
58	Pierre-Luc DuboisFWSH	WSH	55.5%	1,147	2.84	2.27	55.7%	41%▲32
59	Vladislav GavrikovDLAK	LAK	55.5%	1,537	2.29	1.84	55.9%	41%▼5.7
60	Mikey AndersonDLAK	LAK	55.5%	1,429	2.22	1.79	55.8%	7.3%▲6.9
61	Morgan BarronFWPG	WPG	55.4%	668	2.09	1.68	55.7%	4.8%▲4.7
62	Jordan KyrouFSTL	STL	55.4%	1,157	2.66	2.15	55.2%	79%▲2.9
63	Mitch MarnerFTOR	TOR	55.3%	1,183	2.75	2.22	55.4%	99%▲1.1
64	Ross ColtonFCOL	COL	55.2%	748	2.47	2.01	55.5%	8.1%▲7.8
65	Martin NecasFCAR/COL	CAR/COL	55.2%	1,113	2.93	2.37	55.0%	100%▲1.3
66	Adam PelechDNYI	NYI	55.2%	1,093	2.41	1.96	55.1%	3.2%▲3
67	Dmitry OrlovDCAR	CAR	55.1%	1,316	2.57	2.09	55.0%	35%▲21
68	Jordan MartinookFCAR	CAR	55.1%	1,007	2.61	2.13	54.9%	4.3%▲2.7
69	Ivan BarbashevFVGK	VGK	55.1%	1,070	2.88	2.34	55.3%	67%▲26
70	Pavel BuchnevichFSTL	STL	55.1%	1,090	2.94	2.39	55.1%	36%▲7.7
71	Jalen ChatfieldDCAR	CAR	55.1%	1,314	2.63	2.14	55.0%	4.1%▲3.4
72	Kirill KaprizovFMIN	MIN	55.0%	725	2.47	2.02	55.5%	98%▼0.8
73	Noah DobsonDNYI	NYI	55.0%	1,299	2.56	2.09	55.2%	97%▼1.3
74	Timo MeierFNJD	NJD	55.0%	1,204	2.67	2.19	55.4%	82%▼8
75	Jonas SiegenthalerDNJD	NJD	54.9%	922	2.15	1.76	55.4%	3.3%▲2.9
76	Jake McCabeDTOR	TOR	54.9%	1,164	2.48	2.04	54.9%	34%▼15
77	Alex IafalloFWPG	WPG	54.9%	813	2.21	1.81	55.4%	4.3%▲3
78	Brandt ClarkeDLAK	LAK	54.9%	1,091	2.61	2.14	55.3%	96%▲11
79	Artem ZubDOTT	OTT	54.8%	952	2.28	1.87	54.9%	10%▲6.1
80	Cody GlassFPIT/NJD	PIT/NJD	54.8%	741	2.19	1.80	54.8%	4.9%▲4.5
81	Jake GuentzelFTBL	TBL	54.8%	1,212	2.94	2.43	54.4%	100%
82	Vladislav NamestnikovFWPG	WPG	54.8%	981	2.43	2.00	55.1%	0.1%
83	Viktor ArvidssonFEDM	EDM	54.8%	880	2.82	2.33	55.3%	32%▲23
84	Dylan HollowayFSTL	STL	54.8%	1,089	2.42	1.99	55.3%	95%▲9.2
85	A.J. GreerFFLA	FLA	54.7%	728	2.27	1.88	55.0%	7.5%▲5.8
86	Zachary BolducFSTL	STL	54.7%	804	2.16	1.79	55.3%	21%▲19
87	Gustav ForslingDFLA	FLA	54.7%	1,490	2.55	2.12	55.0%	42%▲18
88	Dylan SambergDWPG	WPG	54.7%	1,078	2.48	2.06	54.8%	4.0%▲3.9
89	Victor HedmanDTBL	TBL	54.6%	1,366	2.77	2.30	54.9%	93%▲11
90	Jordan StaalFCAR	CAR	54.6%	946	2.71	2.25	54.4%	20%▲13
91	Zach WhitecloudDVGK	VGK	54.5%	1,201	2.47	2.06	54.5%	7.3%▲6.7
92	Jacob MoverareDLAK	LAK	54.5%	567	2.32	1.93	54.8%	0.0%
93	Jayden StrubleDMTL	MTL	54.5%	792	2.49	2.08	54.4%	3.3%▲2.9
94	Cole PerfettiFWPG	WPG	54.5%	1,070	2.38	1.99	54.6%	36%▲32
95	Darnell NurseDEDM	EDM	54.4%	1,429	2.64	2.21	54.4%	70%▼12
96	Josh MorrisseyDWPG	WPG	54.3%	1,567	2.56	2.15	54.3%	99%▲3.3
97	Joel Eriksson EkFMIN	MIN	54.3%	623	2.26	1.90	54.1%	82%▲11
98	Miro HeiskanenDDAL	DAL	54.3%	972	2.87	2.42	54.3%	100%▲4.5
99	Kirill MarchenkoFCBJ	CBJ	54.2%	1,181	2.87	2.43	53.9%	98%▲7
100	Matthew KniesFTOR	TOR	54.2%	1,088	2.73	2.31	54.4%	94%▲14

Minimum sample: 492 min (it scales with games played and sequence coverage). 325 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.

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