On-ice results

5v5 Expected Goals Share (xGF%) Leaders

2023-24All situationsThrough 82 team games

Expected goals share is the best single on-ice number for "does the play tilt toward the right net when this player is out there?" It weighs every unblocked shot attempt by its chance of scoring, so a point shot through traffic counts for less than a backdoor tap-in.

The board ranks the share, not the raw total, and uses only 5-on-5 play, where every team has the same number of skaters. Rows below the ice-time minimum are hidden; it rises as the season goes on.

Leader in 2023-24: Zach Hyman (EDM), 69.6% xGF%.

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

Strength5-on-5 Even strength All situations

617 qualified

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5v5 Expected Goals Share (xGF%) Leaders, 2023-24, All situations
#	Player	Team
1	Zach HymanFEDM	EDM	69.6%	1,560	5.67	2.48	65.3%	98%▼1.4
2	Connor McDavidFEDM	EDM	68.6%	1,623	5.64	2.58	64.4%	100%▲1.5
3	Evan BouchardDEDM	EDM	67.4%	1,863	5.15	2.49	64.8%	100%
4	Matthew TkachukFFLA	FLA	67.2%	1,492	5.29	2.58	66.1%	100%▲2.7
5	Matt BoldyFMIN	MIN	66.9%	1,418	4.57	2.26	64.5%	100%
6	Evan RodriguesFFLA	FLA	66.2%	1,213	3.73	1.91	62.5%	8.3%▲6.5
7	Jason RobertsonFDAL	DAL	66.1%	1,503	4.20	2.16	62.1%	100%▲0.5
8	Kirill KaprizovFMIN	MIN	66.0%	1,618	4.61	2.38	62.4%	98%▼0.8
9	Nathan MacKinnonFCOL	COL	65.8%	1,871	4.93	2.56	62.8%	100%▲0.8
10	Carter VerhaegheFFLA	FLA	65.7%	1,365	4.85	2.53	65.0%	73%▲1
11	James van RiemsdykFBOS	BOS	65.5%	959	4.06	2.14	57.7%	0.3%
12	Stefan NoesenFCAR	CAR	65.3%	961	3.66	1.95	64.9%	0.1%
13	Shane PintoFOTT	OTT	65.0%	742	4.05	2.18	57.3%	37%▲22
14	Mats ZuccarelloFMIN	MIN	64.9%	1,304	4.37	2.36	62.2%	50%▲28
15	Aleksander BarkovFFLA	FLA	64.6%	1,433	4.80	2.62	62.1%	97%▲7.2
16	Artemi PanarinFNYR	NYR	64.3%	1,650	4.98	2.76	64.2%	98%▼1.2
17	Brock BoeserFVAN	VAN	64.2%	1,507	4.40	2.45	59.0%	63%▼5.5
18	Brady TkachukFOTT	OTT	64.2%	1,551	4.35	2.42	62.3%	100%▲2.2
19	Leon DraisaitlFEDM	EDM	63.9%	1,676	5.08	2.87	61.1%	100%
20	Andrei KuzmenkoFVAN/CGY	VAN/CGY	63.9%	1,072	4.27	2.41	62.7%	11%▲9.8
21	Sam ReinhartFFLA	FLA	63.8%	1,665	4.52	2.57	61.5%	99%
22	John TavaresFTOR	TOR	63.8%	1,429	4.60	2.61	60.1%	96%▲9.3
23	Jake GuentzelFPIT/CAR	PIT/CAR	63.8%	1,341	5.42	3.08	62.7%	100%
24	Auston MatthewsFTOR	TOR	63.8%	1,698	4.80	2.72	60.4%	99%
25	Roope HintzFDAL	DAL	63.5%	1,379	4.40	2.53	60.2%	85%▲7.6
26	Miro HeiskanenDDAL	DAL	63.4%	1,742	4.03	2.33	60.9%	100%▲4.5
27	Mikko RantanenFCOL	COL	63.3%	1,832	4.61	2.67	61.1%	99%▲0.7
28	Kevin FialaFLAK	LAK	63.3%	1,479	3.91	2.27	61.8%	67%▼8.4
29	Joe PavelskiFDAL	DAL	63.2%	1,378	4.11	2.39	59.1%	—
30	Jonathan DrouinFCOL	COL	63.1%	1,437	4.35	2.54	62.3%	0.5%
31	Nikita KucherovFTBL	TBL	63.1%	1,755	5.07	2.96	61.1%	100%
32	David PastrnakFBOS	BOS	62.9%	1,634	4.44	2.62	59.0%	100%▲1.2
33	Quinn HughesDVAN	VAN	62.8%	2,024	4.10	2.43	62.3%	100%
34	Arthur KaliyevFLAK	LAK	62.7%	602	3.45	2.06	61.4%	—
35	Conor GarlandFVAN	VAN	62.6%	1,192	3.59	2.14	59.5%	10%▲7.4
36	Kailer YamamotoFSEA	SEA	62.2%	708	3.04	1.85	59.4%	0.2%
37	Ryan Nugent-HopkinsFEDM	EDM	62.1%	1,570	4.99	3.04	59.6%	77%▲15
38	Jordan EberleFSEA	SEA	62.0%	1,361	3.83	2.34	60.2%	30%▲2.6
39	Quinton ByfieldFLAK	LAK	62.0%	1,319	3.52	2.15	59.8%	86%▲18
40	Luke EvangelistaFNSH	NSH	61.5%	1,116	3.67	2.30	60.3%	70%▲23
41	Brandon MontourDFLA	FLA	61.5%	1,548	3.95	2.48	61.8%	83%▲10
42	Filip ForsbergFNSH	NSH	61.2%	1,550	4.59	2.91	61.7%	99%▲1.4
43	Sam BennettFFLA	FLA	61.2%	1,146	4.27	2.70	61.9%	83%▲4
44	Tommy NovakFNSH	NSH	61.2%	1,008	3.94	2.50	61.2%	11%▲9.1
45	Josh MorrisseyDWPG	WPG	61.1%	1,959	3.85	2.45	57.4%	99%▲3.3
46	Morgan FrostFPHI	PHI	61.1%	1,124	3.52	2.24	58.5%	23%▲17
47	Andrei SvechnikovFCAR	CAR	61.1%	1,002	4.43	2.82	64.0%	97%▲8.5
48	J.T. MillerFVAN	VAN	61.0%	1,579	4.44	2.84	56.6%	92%▲7.9
49	Valeri NichushkinFCOL	COL	61.0%	1,153	4.22	2.70	58.4%	60%
50	Valtteri PuustinenFPIT	PIT	60.8%	611	3.20	2.06	57.0%	—
51	Adam FoxDNYR	NYR	60.8%	1,688	4.05	2.62	59.4%	99%▲6.5
52	Ben HuttonDVGK	VGK	60.5%	667	3.05	1.99	53.8%	—
53	Rickard RakellFPIT	PIT	60.5%	1,156	3.95	2.58	59.3%	82%▲9.9
54	Vincent TrocheckFNYR	NYR	60.5%	1,759	4.58	2.99	58.7%	88%▼5.5
55	Elias PetterssonFVAN	VAN	60.5%	1,611	4.39	2.87	57.9%	87%▼5.8
56	Sebastian AhoFCAR	CAR	60.5%	1,531	4.39	2.87	61.4%	99%▲0.9
57	Jack DruryFCAR	CAR	60.5%	909	3.08	2.01	62.4%	5.6%▲5.4
58	Sidney CrosbyFPIT	PIT	60.4%	1,647	5.12	3.35	61.0%	100%▲2.4
59	Drake BathersonFOTT	OTT	60.4%	1,490	3.83	2.51	58.2%	97%▲7.4
60	Nikolaj EhlersFWPG	WPG	60.4%	1,302	3.85	2.53	58.9%	93%▲7.9
61	Tyler BertuzziFTOR	TOR	60.3%	1,284	3.88	2.56	56.7%	62%▼3.2
62	Matt DucheneFDAL	DAL	60.3%	1,341	4.04	2.67	54.0%	62%▼17
63	Gabriel VilardiFWPG	WPG	60.2%	799	3.96	2.62	55.8%	80%▲7.7
64	William NylanderFTOR	TOR	60.2%	1,634	4.65	3.07	56.5%	99%▼0.9
65	Brayden PointFTBL	TBL	60.1%	1,623	4.72	3.14	59.9%	95%▲7.7
66	Roman JosiDNSH	NSH	59.9%	2,020	4.16	2.79	59.7%	98%
67	Declan ChisholmDMIN/WPG	MIN/WPG	59.7%	512	2.99	2.02	55.9%	0.1%
68	Teuvo TeravainenFCAR	CAR	59.7%	1,247	3.77	2.54	62.5%	13%▲8.6
69	Jordan SpenceDLAK	LAK	59.7%	1,024	3.26	2.20	60.2%	21%▲17
70	Jonathan MarchessaultFVGK	VGK	59.6%	1,467	3.85	2.61	57.3%	24%▼21
71	Pavel DorofeyevFVGK	VGK	59.5%	624	3.06	2.08	53.5%	92%▲1.7
72	Seth JarvisFCAR	CAR	59.5%	1,519	3.94	2.68	60.0%	95%▲1.5
73	Oliver Ekman-LarssonDFLA	FLA	59.5%	1,472	3.63	2.47	58.8%	43%▲32
74	Kevin ShattenkirkDBOS	BOS	59.4%	963	3.37	2.30	52.8%	—
75	Jamie BennFDAL	DAL	59.4%	1,240	4.08	2.79	56.4%	22%▲18
76	Shea TheodoreDVGK	VGK	59.4%	1,038	3.59	2.46	57.5%	91%▲28
77	Mark ScheifeleFWPG	WPG	59.3%	1,494	4.12	2.82	54.5%	100%
78	Thomas ChabotDOTT	OTT	59.1%	1,175	3.61	2.50	56.4%	83%▼11
79	Cole PerfettiFWPG	WPG	59.1%	965	3.02	2.09	58.5%	36%▲32
80	Mason MarchmentFDAL	DAL	59.1%	1,220	3.50	2.42	54.2%	47%▲34
81	Mattias EkholmDEDM	EDM	59.1%	1,663	4.11	2.85	57.1%	77%▲9.7
82	Steven StamkosFTBL	TBL	58.9%	1,440	4.32	3.01	58.7%	94%▼3.7
83	Erik KarlssonDPIT	PIT	58.9%	1,990	4.20	2.93	59.8%	95%
84	Nino NiederreiterFWPG	WPG	58.8%	1,152	3.09	2.17	55.6%	4.0%▲3.8
85	Artturi LehkonenFCOL	COL	58.8%	831	4.11	2.89	58.7%	54%▲37
86	Mitch MarnerFTOR	TOR	58.6%	1,468	4.40	3.11	56.6%	99%▲1.1
87	Marco RossiFMIN	MIN	58.6%	1,372	3.23	2.28	56.9%	58%▲12
88	Dylan StromeFWSH	WSH	58.5%	1,472	3.88	2.75	57.4%	82%▲10
89	Vince DunnDSEA	SEA	58.5%	1,362	3.26	2.31	57.2%	88%▲11
90	Jalen ChatfieldDCAR	CAR	58.1%	1,094	2.83	2.04	60.0%	4.1%▲3.4
91	Nick PaulFTBL	TBL	58.1%	1,415	3.93	2.83	57.2%	8.1%▲7.7
92	Casey MittelstadtFBUF/COL	BUF/COL	58.1%	1,418	3.70	2.67	56.9%	14%▲12
93	Oliver BjorkstrandFSEA	SEA	58.1%	1,327	3.38	2.44	59.1%	20%
94	Mark StoneFVGK	VGK	57.9%	1,087	3.93	2.85	53.4%	93%▲9
95	Pius SuterFVAN	VAN	57.9%	1,038	2.97	2.16	54.3%	4.1%▲3.3
96	Jack HughesFNJD	NJD	57.9%	1,300	4.46	3.25	63.6%	100%
97	Tyler ToffoliFNJD/WPG	NJD/WPG	57.8%	1,340	4.47	3.27	64.0%	38%▼17
98	Marcus JohanssonFMIN	MIN	57.6%	1,240	3.30	2.42	55.0%	0.7%
99	Anthony ManthaFWSH/VGK	WSH/VGK	57.6%	1,053	3.05	2.24	55.8%	53%▲16
100	Thomas HarleyDDAL	DAL	57.6%	1,660	3.24	2.38	56.1%	88%▲8.9

Minimum sample: 492 min (it scales with games played and sequence coverage). 307 below the minimum are hidden.

How to read it

50% is break-even. 55% means the skater's team took 55% of the expected goals while he was on the ice.

How reliable is it?

On-ice xGF% is moderately repeatable: split-half r ≈ 0.29 at about 7 xG per half. Treat gaps of 2-3 points between players as noise before about 500 minutes.

How our expected goals model works →

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5v5 xGF% leaderboard

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