On-ice results

Sequence xG (sxGF%) Leaders

2025-26Even strengthThrough 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: Jordan Spence (OTT), 62.6% sxGF%.

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

Strength5-on-5 Even strength All situations

602 qualified

Show

Sequence xG (sxGF%) Leaders, 2025-26, Even strength
#	Player	Team
1	Jordan SpenceDOTT	OTT	62.6%	1,243	3.13	1.87	62.6%	54.8%	49.7%	21%▲17
2	Sam MalinskiDCOL	COL	61.5%	1,351	3.11	1.95	61.7%	56.6%	49.6%	56%▲33
3	Mark StoneFVGK	VGK	61.5%	840	3.14	1.97	61.5%	55.6%	49.1%	93%▲9
4	Brady TkachukFOTT	OTT	61.4%	773	3.41	2.15	61.4%	55.5%	50.1%	100%▲2.2
5	Jordan KyrouFSTL	STL	60.4%	952	3.00	1.97	60.9%	50.9%	49.9%	79%▲2.9
6	Devon ToewsDCOL	COL	60.3%	1,226	3.36	2.21	60.3%	57.5%	49.7%	60%▼2.3
7	Mark JankowskiFCAR	CAR	60.3%	658	2.50	1.65	60.5%	55.4%	49.4%	0.2%
8	Brock NelsonFCOL	COL	59.9%	1,124	3.23	2.16	60.1%	56.9%	49.9%	87%▼4
9	Dylan CozensFOTT	OTT	59.7%	1,087	2.91	1.97	59.3%	55.3%	49.8%	90%▲3.6
10	Valeri NichushkinFCOL	COL	59.3%	977	3.18	2.18	59.4%	57.3%	50.0%	60%
11	Nathan MacKinnonFCOL	COL	59.2%	1,370	3.66	2.52	59.4%	57.3%	49.8%	100%▲0.8
12	Artturi LehkonenFCOL	COL	59.0%	1,014	3.35	2.33	59.0%	57.7%	49.7%	54%▲37
13	Brandon HagelFTBL	TBL	58.9%	1,030	3.60	2.51	59.1%	54.8%	50.0%	100%▲1.9
14	Shayne GostisbehereDCAR	CAR	58.9%	860	3.18	2.22	59.0%	55.3%	49.3%	96%▲16
15	Jack DruryFCOL	COL	58.8%	988	2.48	1.73	59.5%	56.5%	49.5%	5.6%▲5.4
16	Evan BouchardDEDM	EDM	58.8%	1,520	3.40	2.38	58.8%	53.5%	49.9%	100%
17	William CarrierFCAR	CAR	58.8%	741	2.51	1.76	58.8%	55.3%	49.5%	0.1%
18	Mattias EkholmDEDM	EDM	58.6%	1,460	3.29	2.33	58.6%	53.4%	49.9%	77%▲9.7
19	Gabriel LandeskogFCOL	COL	58.5%	798	3.38	2.39	58.7%	57.5%	49.9%	50%▲32
20	Claude GirouxFOTT	OTT	58.5%	986	2.72	1.93	58.1%	54.9%	50.0%	30%▲20
21	Danton HeinenFCBJ/PIT	CBJ/PIT	58.4%	501	2.36	1.68	58.4%	50.3%	49.9%	0.0%
22	Logan StankovenFCAR	CAR	58.3%	1,107	3.21	2.30	58.3%	55.9%	49.7%	67%▲42
23	Jackson BlakeFCAR	CAR	58.2%	1,138	3.24	2.33	57.9%	56.0%	49.6%	68%▲21
24	Jack EichelFVGK	VGK	58.0%	1,154	3.26	2.36	58.3%	55.7%	49.7%	99%▲1.4
25	Clayton KellerFUTA	UTA	58.0%	1,241	3.04	2.20	58.0%	53.4%	50.0%	100%▲2
26	Parker KellyFCOL	COL	57.7%	855	2.44	1.79	58.0%	56.1%	49.3%	11%▲5.7
27	Ross ColtonFCOL	COL	57.6%	842	3.02	2.22	58.1%	56.8%	49.6%	8.1%▲7.8
28	Nikita KucherovFTBL	TBL	57.3%	1,156	3.54	2.64	57.2%	55.0%	50.0%	100%
29	Connor McDavidFEDM	EDM	57.2%	1,439	3.48	2.60	57.1%	53.3%	50.0%	100%▲1.5
30	Hendrix LapierreFWSH	WSH	57.2%	639	2.64	1.97	57.4%	50.2%	49.7%	7.3%▲7.2
31	Jake SandersonDOTT	OTT	57.1%	1,186	2.76	2.07	56.8%	55.1%	50.3%	99%▲3.2
32	Thomas ChabotDOTT	OTT	57.0%	1,033	2.91	2.20	57.0%	55.1%	49.5%	83%▼11
33	K'Andre MillerDCAR	CAR	56.9%	1,381	2.94	2.23	56.8%	55.6%	50.0%	64%▲26
34	Cale MakarDCOL	COL	56.9%	1,350	3.09	2.35	56.8%	57.6%	49.8%	100%▲1
35	Joel NystromDCAR	CAR	56.8%	529	3.01	2.29	57.1%	55.5%	49.2%	4.0%▲4
36	Jason RobertsonFDAL	DAL	56.8%	1,278	3.02	2.29	56.8%	52.6%	50.0%	100%▲0.5
37	Drake BathersonFOTT	OTT	56.8%	1,072	2.79	2.12	56.6%	55.5%	49.8%	97%▲7.4
38	Roope HintzFDAL	DAL	56.7%	691	2.56	1.95	56.9%	53.0%	50.1%	85%▲7.6
39	Martin NecasFCOL	COL	56.7%	1,307	3.35	2.55	56.8%	57.9%	49.9%	100%▲1.3
40	Anthony CirelliFTBL	TBL	56.7%	911	3.26	2.49	56.8%	55.3%	50.1%	51%▲19
41	Robert ThomasFSTL	STL	56.7%	927	3.03	2.32	57.0%	51.4%	50.0%	93%▲20
42	Josh MansonDCOL	COL	56.7%	1,222	2.80	2.14	57.0%	56.5%	49.7%	32%▲16
43	Troy TerryFANA	ANA	56.7%	836	3.17	2.43	56.5%	51.4%	49.7%	47%▲34
44	Fabian ZetterlundFOTT	OTT	56.6%	948	2.79	2.14	56.7%	54.6%	49.6%	13%▲6.6
45	Nikolaj EhlersFCAR	CAR	56.6%	1,083	2.90	2.23	56.9%	55.2%	49.9%	93%▲7.9
46	Eric RobinsonFCAR	CAR	56.6%	686	2.54	1.95	56.4%	55.7%	49.1%	3.2%▲3.1
47	Kaedan KorczakDVGK	VGK	56.5%	1,201	2.55	1.96	56.7%	53.9%	49.6%	6.7%▲6.5
48	Denver BarkeyFPHI	PHI	56.5%	501	2.43	1.87	56.5%	52.5%	49.7%	15%▲14
49	Ivan BarbashevFVGK	VGK	56.4%	1,234	2.97	2.29	56.5%	56.0%	49.8%	67%▲26
50	Nick CousinsFOTT	OTT	56.4%	916	2.34	1.81	56.2%	54.3%	49.7%	0.1%
51	Damon SeversonDCBJ	CBJ	56.4%	1,351	2.81	2.17	56.4%	51.1%	50.1%	9.4%▲6.2
52	Leon DraisaitlFEDM	EDM	56.3%	1,089	3.22	2.49	56.4%	51.9%	49.8%	100%
53	Kailer YamamotoFUTA	UTA	56.3%	662	2.51	1.95	56.2%	51.7%	49.6%	0.2%
54	Miro HeiskanenDDAL	DAL	56.3%	1,391	2.63	2.04	56.4%	52.5%	50.1%	100%▲4.5
55	Shea TheodoreDVGK	VGK	56.3%	1,356	2.85	2.21	56.5%	54.9%	49.8%	91%▲28
56	Michael CarconeFUTA	UTA	56.3%	919	2.77	2.15	56.2%	52.2%	49.5%	5.0%▲4
57	Samuel GirardDCOL/PIT	COL/PIT	56.2%	1,017	2.81	2.19	56.7%	54.8%	50.0%	8.2%▲7.8
58	Tommy NovakFPIT	PIT	56.2%	1,060	3.23	2.51	56.0%	50.7%	50.0%	11%▲9.1
59	Darren RaddyshDTBL	TBL	56.2%	1,273	2.94	2.29	56.3%	54.3%	49.9%	100%▲3.5
60	Mitch MarnerFVGK	VGK	56.2%	1,171	2.66	2.07	56.2%	55.1%	49.6%	99%▲1.1
61	Taylor HallFCAR	CAR	56.2%	1,015	3.12	2.43	56.2%	56.2%	49.5%	28%▲21
62	Adam FoxDNYR	NYR	56.2%	1,034	2.61	2.04	56.2%	48.1%	50.1%	99%▲6.5
63	Gage GoncalvesFTBL	TBL	56.1%	871	2.53	1.98	56.7%	53.8%	49.9%	11%▲11
64	Sean WalkerDCAR	CAR	56.1%	1,510	2.88	2.25	56.2%	55.6%	49.9%	60%▼11
65	Nick SchmaltzFUTA	UTA	56.1%	1,188	2.84	2.22	56.1%	53.7%	50.0%	94%▲4.7
66	Maxwell CrozierDTBL	TBL	55.9%	511	2.56	2.02	56.0%	53.0%	49.7%	5.6%▲5.5
67	Jaccob SlavinDCAR	CAR	55.8%	689	2.64	2.10	55.5%	54.8%	50.2%	15%▲3.8
68	Barrett HaytonFUTA	UTA	55.7%	831	2.65	2.10	55.9%	53.4%	49.8%	11%▲11
69	Zach HymanFEDM	EDM	55.6%	900	3.36	2.69	55.7%	53.7%	49.8%	98%▼1.4
70	Brayden McNabbDVGK	VGK	55.6%	1,114	2.62	2.09	55.8%	55.2%	50.0%	23%▲20
71	Ben HuttonDVGK	VGK	55.5%	785	2.62	2.10	55.8%	54.0%	49.0%	—
72	David PerronFOTT/DET	OTT/DET	55.5%	742	2.31	1.85	55.4%	53.1%	49.8%	0.2%
73	Tom WilsonFWSH	WSH	55.5%	987	2.93	2.35	55.4%	50.5%	50.4%	95%▲6.5
74	J.J. MoserDTBL	TBL	55.5%	1,465	2.93	2.35	55.6%	54.2%	50.1%	22%▲20
75	Lane HutsonDMTL	MTL	55.5%	1,588	2.97	2.39	55.3%	50.0%	50.2%	99%▲3.1
76	Mike ReillyDCAR	CAR	55.4%	575	2.83	2.28	55.4%	55.3%	49.1%	0.1%
77	Jesper BrattFNJD	NJD	55.3%	1,173	3.18	2.57	55.3%	49.9%	50.2%	96%▲11
78	Leo CarlssonFANA	ANA	55.3%	994	3.17	2.56	55.3%	51.4%	49.9%	94%▲10
79	Tim StützleFOTT	OTT	55.3%	1,135	2.98	2.40	55.1%	55.6%	49.9%	100%▲0.8
80	Mackie SamoskevichFFLA	FLA	55.3%	932	2.63	2.13	55.9%	50.9%	49.9%	—
81	Nate SchmidtDUTA	UTA	55.2%	1,384	2.79	2.26	55.0%	53.2%	49.8%	4.9%▲4.5
82	Pavel DorofeyevFVGK	VGK	55.2%	1,117	2.54	2.06	55.7%	54.5%	49.4%	92%▲1.7
83	John MarinoDUTA	UTA	55.2%	1,453	2.64	2.14	55.0%	53.2%	49.8%	18%▲13
84	Noah HanifinDVGK	VGK	55.2%	1,406	2.61	2.12	55.4%	53.6%	49.3%	52%▼23
85	Charle-Edouard D'AstousDTBL	TBL	55.1%	1,187	2.59	2.10	55.7%	53.4%	49.7%	22%▲17
86	Brent BurnsDCOL	COL	55.1%	1,281	2.87	2.33	55.3%	56.7%	49.7%	50%▼14
87	Michael AmadioFOTT	OTT	54.9%	1,167	2.38	1.95	54.8%	55.0%	50.2%	3.3%▲2.6
88	Moritz SeiderDDET	DET	54.9%	1,640	2.66	2.18	55.0%	48.5%	50.3%	100%▲0.6
89	Sebastian AhoFCAR	CAR	54.9%	1,109	3.31	2.72	54.8%	55.0%	50.1%	99%▲0.9
90	Brandon SaadFVGK	VGK	54.9%	604	2.64	2.17	55.3%	53.8%	49.7%	—
91	Josh NorrisFBUF	BUF	54.8%	535	2.83	2.33	54.6%	51.4%	49.9%	39%▲32
92	Chris KreiderFANA	ANA	54.8%	953	3.00	2.47	55.0%	51.3%	49.7%	62%▲29
93	Esa LindellDDAL	DAL	54.7%	1,480	2.44	2.02	54.9%	52.5%	50.1%	37%▼32
94	Mavrik BourqueFDAL	DAL	54.7%	1,144	2.62	2.17	54.8%	52.3%	50.0%	35%▲31
95	Jake GuentzelFTBL	TBL	54.6%	1,147	2.94	2.44	54.9%	54.4%	50.0%	100%
96	Nick DeSimoneDUTA	UTA	54.6%	559	2.45	2.03	54.0%	52.5%	49.8%	0.1%
97	Quinn HughesDMIN/VAN	MIN/VAN	54.6%	1,680	3.05	2.54	54.5%	49.2%	49.9%	100%
98	Evgeni MalkinFPIT	PIT	54.5%	778	3.31	2.76	54.2%	51.0%	49.5%	82%▲10
99	Seth JarvisFCAR	CAR	54.5%	965	3.10	2.59	54.3%	55.0%	50.1%	95%▲1.5
100	Victor OlofssonFCOL/CGY	COL/CGY	54.5%	881	2.57	2.15	54.7%	54.7%	50.0%	12%▲12

Minimum sample: 492 min (it scales with games played and sequence coverage). 338 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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