On-ice results

Sequence xG (sxGF%) Leaders

2024-25All 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 2024-25: Jackson Blake (CAR), 66.8% sxGF%.

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

Strength5-on-5 Even strength All situations

613 qualified

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Sequence xG (sxGF%) Leaders, 2024-25, All situations
#	Player	Team
1	Jackson BlakeFCAR	CAR	66.8%	1,108	3.77	1.87	66.6%	68%▲21
2	Leon DraisaitlFEDM	EDM	66.8%	1,528	4.81	2.39	67.1%	100%
3	Connor McDavidFEDM	EDM	65.6%	1,476	4.75	2.49	65.9%	100%▲1.5
4	Shayne GostisbehereDCAR	CAR	64.9%	1,296	4.16	2.25	65.7%	96%▲16
5	Jack HughesFNJD	NJD	64.7%	1,296	4.51	2.47	64.8%	100%
6	Zach HymanFEDM	EDM	64.6%	1,379	4.47	2.45	65.1%	98%▼1.4
7	Nathan MacKinnonFCOL	COL	64.3%	1,800	4.75	2.64	64.5%	100%▲0.8
8	Mackie SamoskevichFFLA	FLA	64.3%	959	3.45	1.92	64.3%	—
9	Tomas HertlFVGK	VGK	64.2%	1,250	4.14	2.31	64.2%	83%▲2.9
10	Evan BouchardDEDM	EDM	63.6%	1,924	4.20	2.40	64.0%	100%
11	Victor OlofssonFVGK	VGK	63.5%	812	3.08	1.77	63.6%	12%▲12
12	Nikita KucherovFTBL	TBL	63.5%	1,653	4.63	2.66	63.4%	100%
13	Brady TkachukFOTT	OTT	63.0%	1,313	4.04	2.38	63.3%	100%▲2.2
14	Matthew TkachukFFLA	FLA	62.9%	948	4.48	2.65	64.0%	100%▲2.7
15	Mathew BarzalFNYI	NYI	62.8%	610	4.05	2.40	63.9%	83%▲10
16	Kirill KaprizovFMIN	MIN	62.6%	921	3.79	2.26	63.1%	98%▼0.8
17	Nikolaj EhlersFWPG	WPG	62.5%	1,090	3.99	2.39	62.7%	93%▲7.9
18	Martin NecasFCAR/COL	CAR/COL	62.5%	1,501	4.30	2.58	62.1%	100%▲1.3
19	Pavel DorofeyevFVGK	VGK	62.4%	1,355	3.63	2.18	62.3%	92%▲1.7
20	Cole PerfettiFWPG	WPG	62.4%	1,245	3.24	1.95	62.8%	36%▲32
21	Dougie HamiltonDNJD	NJD	62.3%	1,271	4.08	2.46	62.4%	84%▲12
22	Kevin FialaFLAK	LAK	62.3%	1,500	3.51	2.13	62.4%	67%▼8.4
23	Shea TheodoreDVGK	VGK	62.3%	1,473	3.64	2.21	62.2%	91%▲28
24	Carter VerhaegheFFLA	FLA	62.0%	1,447	4.12	2.52	62.6%	73%▲1
25	Jake GuentzelFTBL	TBL	61.9%	1,599	4.32	2.65	61.8%	100%
26	Mark StoneFVGK	VGK	61.5%	1,271	4.02	2.52	61.5%	93%▲9
27	Brayden PointFTBL	TBL	61.5%	1,500	4.40	2.76	61.3%	95%▲7.7
28	Josh DoanFUTA	UTA	61.5%	689	2.98	1.87	62.5%	61%▲44
29	Mikko RantanenFCOL/DAL/CAR	COL/DAL/CAR	61.4%	1,742	4.49	2.83	61.6%	99%▲0.7
30	Jesperi KotkaniemiFCAR	CAR	60.9%	1,097	3.16	2.03	60.7%	3.2%▲3.1
31	Sebastian AhoFCAR	CAR	60.8%	1,588	4.48	2.88	61.0%	99%▲0.9
32	Vinnie HinostrozaFMIN/NSH	MIN/NSH	60.7%	495	2.92	1.89	61.1%	0.0%
33	Nate SchmidtDFLA	FLA	60.7%	1,322	2.84	1.84	61.3%	4.9%▲4.5
34	Jesper BrattFNJD	NJD	60.7%	1,535	4.29	2.78	60.4%	96%▲11
35	Clayton KellerFUTA	UTA	60.6%	1,549	3.97	2.58	61.2%	100%▲2
36	Andrei SvechnikovFCAR	CAR	60.6%	1,232	4.29	2.79	60.5%	97%▲8.5
37	Dylan GuentherFUTA	UTA	60.5%	1,190	3.96	2.58	61.3%	99%▲2
38	Tim StützleFOTT	OTT	60.5%	1,625	3.66	2.39	60.4%	100%▲0.8
39	Jason RobertsonFDAL	DAL	60.5%	1,459	4.09	2.67	60.8%	100%▲0.5
40	Alex LaferriereFLAK	LAK	60.5%	1,273	3.23	2.11	60.7%	68%▲3.5
41	Seth JarvisFCAR	CAR	60.4%	1,413	4.22	2.77	60.3%	95%▲1.5
42	Brandon HagelFTBL	TBL	60.2%	1,701	4.02	2.65	60.5%	100%▲1.9
43	Aleksander BarkovFFLA	FLA	60.2%	1,357	4.09	2.71	60.8%	97%▲7.2
44	Quinn HughesDVAN	VAN	60.1%	1,750	3.46	2.30	60.2%	100%
45	Miro HeiskanenDDAL	DAL	60.0%	1,258	3.92	2.61	60.4%	100%▲4.5
46	Zachary BolducFSTL	STL	60.0%	922	2.67	1.78	60.7%	21%▲19
47	Jordan KyrouFSTL	STL	59.9%	1,434	3.46	2.31	60.5%	79%▲2.9
48	Stefan NoesenFNJD	NJD	59.6%	1,243	3.72	2.52	60.0%	0.1%
49	Drake BathersonFOTT	OTT	59.6%	1,488	3.63	2.46	59.6%	97%▲7.4
50	Sam BennettFFLA	FLA	59.4%	1,326	3.90	2.66	60.4%	83%▲4
51	Jonathan DrouinFCOL	COL	59.3%	782	3.84	2.63	59.6%	0.5%
52	Nick SchmaltzFUTA	UTA	59.3%	1,524	4.05	2.78	59.8%	94%▲4.7
53	Brandt ClarkeDLAK	LAK	59.2%	1,270	3.14	2.16	60.1%	96%▲11
54	Mats ZuccarelloFMIN	MIN	59.2%	1,356	3.53	2.43	59.5%	50%▲28
55	Ross ColtonFCOL	COL	59.1%	880	3.20	2.21	59.3%	8.1%▲7.8
56	Lucas RaymondFDET	DET	59.0%	1,540	3.98	2.76	59.3%	96%▲10
57	Alex TurcotteFLAK	LAK	59.0%	798	2.63	1.83	59.4%	8.8%▲8.8
58	Sam ReinhartFFLA	FLA	59.0%	1,620	3.77	2.62	59.5%	99%
59	Kirill MarchenkoFCBJ	CBJ	59.0%	1,468	3.85	2.67	58.8%	98%▲7
60	Dylan HollowayFSTL	STL	59.0%	1,295	3.07	2.13	59.5%	95%▲9.2
61	Jack EichelFVGK	VGK	58.9%	1,581	4.13	2.88	58.9%	99%▲1.4
62	Alex DeBrincatFDET	DET	58.9%	1,465	3.86	2.69	59.4%	100%▲2.6
63	Corey PerryFEDM	EDM	58.9%	967	3.28	2.29	59.3%	7.4%▲5.9
64	Andrei KuzmenkoFCGY/LAK/PHI	CGY/LAK/PHI	58.9%	1,032	3.12	2.18	59.1%	11%▲9.8
65	Adam GaudetteFOTT	OTT	58.8%	844	2.79	1.95	58.9%	0.1%
66	Bobby BrinkFPHI	PHI	58.8%	1,172	3.13	2.19	59.2%	14%▲12
67	Matt BoldyFMIN	MIN	58.7%	1,664	3.59	2.53	59.0%	100%
68	Vladislav NamestnikovFWPG	WPG	58.6%	1,177	3.01	2.12	59.1%	0.1%
69	Artturi LehkonenFCOL	COL	58.6%	1,406	3.92	2.77	58.3%	54%▲37
70	Maxim TsyplakovFNYI	NYI	58.6%	1,152	2.94	2.08	58.0%	14%
71	Timo MeierFNJD	NJD	58.5%	1,429	3.53	2.50	59.2%	82%▼8
72	Logan StankovenFDAL/CAR	DAL/CAR	58.4%	1,177	3.59	2.56	58.9%	67%▲42
73	Pierre-Luc DuboisFWSH	WSH	58.1%	1,419	3.62	2.61	58.4%	41%▲32
74	Josh MorrisseyDWPG	WPG	58.0%	1,951	3.47	2.51	58.3%	99%▲3.3
75	Gabriel VilardiFWPG	WPG	58.0%	1,288	3.65	2.64	58.3%	80%▲7.7
76	Erik GustafssonDDET	DET	57.9%	979	2.90	2.11	59.1%	3.2%▲3.2
77	Tommy NovakFNSH/PIT	NSH/PIT	57.9%	714	3.08	2.24	58.2%	11%▲9.1
78	Viktor ArvidssonFEDM	EDM	57.9%	1,005	3.23	2.35	58.4%	32%▲23
79	David PastrnakFBOS	BOS	57.8%	1,655	3.93	2.87	57.6%	100%▲1.2
80	Cale MakarDCOL	COL	57.8%	2,057	4.07	2.98	57.5%	100%▲1
81	Nico HischierFNJD	NJD	57.7%	1,529	4.11	3.02	57.7%	98%▲3
82	Mason MarchmentFDAL	DAL	57.6%	951	3.81	2.81	57.7%	47%▲34
83	Mark ScheifeleFWPG	WPG	57.6%	1,676	3.76	2.77	57.9%	100%
84	Victor HedmanDTBL	TBL	57.5%	1,823	3.80	2.81	57.8%	93%▲11
85	Barrett HaytonFUTA	UTA	57.5%	1,320	3.64	2.69	57.8%	11%▲11
86	Alex OvechkinFWSH	WSH	57.5%	1,152	4.09	3.03	57.3%	96%▲1.3
87	Jordan SpenceDLAK	LAK	57.4%	1,326	2.73	2.03	57.5%	21%▲17
88	Tom WilsonFWSH	WSH	57.3%	1,517	3.74	2.79	57.2%	95%▲6.5
89	Artemi PanarinFNYR	NYR	57.1%	1,575	3.95	2.96	57.5%	98%▼1.2
90	William KarlssonFVGK	VGK	57.1%	902	3.13	2.35	57.0%	24%▲20
91	Jakob ChychrunDWSH	WSH	57.1%	1,559	3.33	2.51	57.1%	99%▼0.6
92	Darren RaddyshDTBL	TBL	57.0%	1,263	3.28	2.47	57.5%	100%▲3.5
93	Ivan BarbashevFVGK	VGK	57.0%	1,176	3.20	2.41	57.3%	67%▲26
94	William NylanderFTOR	TOR	57.0%	1,600	4.16	3.14	57.1%	99%▼0.9
95	Dylan LarkinFDET	DET	56.9%	1,646	3.91	2.96	57.5%	96%
96	Matt DucheneFDAL	DAL	56.8%	1,406	3.99	3.03	57.3%	62%▼17
97	Kyle ConnorFWPG	WPG	56.7%	1,672	3.76	2.86	57.1%	99%▲1
98	Brad MarchandFBOS/FLA	BOS/FLA	56.7%	1,301	3.90	2.97	56.6%	73%▲0.9
99	Uvis BalinskisDFLA	FLA	56.7%	1,129	2.57	1.96	57.1%	4.0%▲3.9
100	Conor GarlandFVAN	VAN	56.7%	1,511	3.30	2.53	57.3%	10%▲7.4

Minimum sample: 492 min (it scales with games played and sequence coverage). 307 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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