Stanley Cup Winners Hockey League

WASHINGTON Capitals
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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du Joueur	#	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP
1	Chandler Stephenson	0	X				100.00	62	43	88	66	76	78	83	65	76	64	63	79	65	71	68	62	99	71	0
2	Jesper Bratt	0		X			100.00	59	38	87	76	65	82	85	74	56	75	70	59	78	63	64	59	99	71	0
3	Nick Paul	0		X			100.00	79	47	86	65	87	77	72	65	78	66	63	67	65	69	66	59	99	70	0
4	Martin Necas (R)	0	X				100.00	63	39	88	71	78	80	77	69	70	68	67	63	72	62	66	85	99	70	0
5	Dmytro Timashov (R)	0		X			100.00	72	39	88	67	69	77	80	65	58	63	66	64	68	67	65	57	99	69	0
6	Anders Bjork	0		X			100.00	62	40	88	64	72	74	75	62	60	65	61	63	62	67	64	58	99	67	0
7	Valentin Zykov (R)	0		X	X		100.00	64	45	82	63	78	80	75	62	53	58	61	59	64	69	65	73	99	66	0
8	Joshua Ho-Sang	0		X	X		100.00	57	39	89	66	69	78	75	64	59	62	58	61	66	67	64	78	99	66	0
9	Kevin Roy	0		X			100.00	54	38	86	62	64	80	77	63	54	61	58	60	64	73	67	53	99	65	0
10	Alexandre Fortin	0		X			100.00	58	43	89	61	71	80	76	59	54	57	58	56	61	65	63	62	99	64	0
11	Lukas Sedlak	0	X				100.00	72	35	71	64	75	73	60	63	73	62	63	66	63	56	52	47	99	64	0
12	Taro Hirose (R)	0		X			100.00	56	39	87	64	65	75	71	63	58	64	59	57	63	67	64	52	99	64	0
13	Matt Grzelcyk	0				X	100.00	64	42	73	70	64	84	86	68	30	74	59	72	53	71	66	58	97	71	0
14	Mike Reilly	0				X	100.00	68	39	83	66	77	84	78	64	30	74	57	63	50	73	68	53	99	70	0
15	Tim Heed	0				X	100.00	54	39	89	66	68	77	71	64	30	70	58	61	50	77	69	47	99	67	0
16	Sami Niku	0				X	100.00	58	42	88	66	73	75	69	64	30	65	58	63	54	67	64	56	99	66	0
17	Sebastian D Aho	0				X	100.00	50	89	64	70	64	50	50	70	30	51	46	51	56	51	50	56	99	55	0
Rayé

	MOYENNE D'ÉQUIPE					100.00	62	43	84	66	71	77	74	65	53	65	60	63	62	67	64	60	99	67

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du Gardien	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Michael Hutchinson	100.00	76	69	67	83	75	74	76	75	74	76	75	78	84	52	99	69	0
2	Ukko-Pekka Luukkonen (R)	100.00	72	56	54	86	71	70	72	71	70	72	71	61	65	71	99	64	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	74	63	61	85	73	72	74	73	72	74	73	70	75	62	99	67

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Jeff Daniels	69	69	69	69	73	73	66	CAN	52	3	300,000$

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	EG	HT	P/20	PSG	PSS	FW	FL	S1	S2	S3
1	Martin Necas	HERSEY Bears (WSH)	C	40	12	22	34	5	10	0	38	107	153	41	108	7.84%	9	960	24.02	1	5	6	21	112	0	1	1	1	70	6	2	56.18%	1068	0	0	0.71	0	1	0	0	2	1	3
2	Chandler Stephenson	HERSEY Bears (WSH)	C	40	17	16	33	3	6	0	53	88	179	53	124	9.50%	15	928	23.20	3	5	8	32	115	0	1	1	3	95	3	1	57.57%	1176	0	1	0.71	1	4	0	0	4	5	1
3	Nick Paul	HERSEY Bears (WSH)	LW	40	15	17	32	8	39	5	112	54	148	33	109	10.14%	9	930	23.25	3	2	5	22	111	1	0	1	3	56	1	1	57.75%	71	0	1	0.69	0	2	0	1	1	4	1
4	Matt Grzelcyk	HERSEY Bears (WSH)	D	38	6	23	29	1	32	0	69	50	57	20	40	10.53%	60	1045	27.52	3	3	6	32	109	0	1	1	0	75	1	0	0.00%	0	0	0	0.55	0	0	0	0	2	2	1
5	Mike Reilly	HERSEY Bears (WSH)	D	40	4	19	23	-9	32	0	60	28	36	10	25	11.11%	55	1039	25.98	2	4	6	20	118	0	0	0	0	76	1	0	0.00%	0	1	0	0.44	0	0	0	0	1	0	2
6	Jesper Bratt	HERSEY Bears (WSH)	LW	40	13	10	23	-1	18	0	40	72	113	47	84	11.50%	9	804	20.11	3	3	6	17	116	1	0	1	2	95	2	1	43.10%	58	1	0	0.57	0	4	0	0	1	2	0
7	Dmytro Timashov	HERSEY Bears (WSH)	LW	40	8	11	19	4	4	0	39	35	113	28	69	7.08%	9	658	16.46	0	1	1	3	13	0	0	0	0	38	1	2	48.00%	50	0	0	0.58	1	1	0	0	2	0	0
8	Sami Niku	HERSEY Bears (WSH)	D	40	6	12	18	9	14	0	26	25	49	15	21	12.24%	39	880	22.01	3	3	6	27	109	0	0	0	0	88	0	0	0.00%	0	0	0	0.41	0	0	0	0	0	2	1
9	Tim Heed	HERSEY Bears (WSH)	D	40	2	15	17	2	4	0	21	26	36	18	42	5.56%	35	1016	25.42	0	3	3	15	104	0	1	1	1	81	0	0	0.00%	0	0	0	0.33	0	0	0	0	0	0	0
10	Lukas Sedlak	HERSEY Bears (WSH)	C	40	5	7	12	-1	16	0	57	53	65	24	49	7.69%	12	534	13.37	0	0	0	0	0	0	0	0	0	3	1	0	58.15%	509	0	0	0.45	0	0	0	0	0	0	2
11	Joshua Ho-Sang	HERSEY Bears (WSH)	LW/RW	40	7	5	12	-1	4	0	17	37	104	26	71	6.73%	8	873	21.85	0	0	0	16	110	0	0	0	0	0	1	0	70.00%	50	0	1	0.27	0	0	0	0	0	0	3
12	Anders Bjork	HERSEY Bears (WSH)	LW	40	2	8	10	6	12	0	15	25	45	9	46	4.44%	6	454	11.36	0	1	1	0	11	0	0	0	0	8	0	0	50.00%	32	0	0	0.44	0	0	0	0	0	1	0
13	Valentin Zykov	HERSEY Bears (WSH)	LW/RW	40	3	6	9	4	31	5	64	27	61	19	43	4.92%	3	985	24.63	0	1	1	10	106	0	0	0	0	2	0	0	46.97%	66	0	0	0.18	0	0	1	0	0	0	1
14	Sebastian D Aho	HERSEY Bears (WSH)	D	40	0	4	4	11	16	0	25	8	12	6	5	0.00%	16	645	16.13	0	0	0	2	15	0	0	0	0	24	0	0	0.00%	0	0	0	0.12	0	0	0	0	0	0	1
15	Kevin Roy	HERSEY Bears (WSH)	LW	40	1	1	2	0	0	0	0	2	3	2	3	33.33%	2	76	1.90	1	1	2	1	4	0	0	0	0	1	1	0	57.14%	7	0	0	0.53	0	0	0	0	0	0	0
16	Alexandre Fortin	HERSEY Bears (WSH)	LW	40	0	1	1	0	0	0	2	1	6	1	1	0.00%	2	41	1.03	0	0	0	1	2	0	0	0	0	3	0	0	0.00%	1	0	0	0.49	0	0	0	0	0	0	0
17	Taro Hirose	HERSEY Bears (WSH)	LW	2	0	0	0	0	0	0	0	0	0	1	0	0.00%	0	9	4.64	0	0	0	0	0	0	0	0	0	0	0	0	50.00%	2	0	0	0.00	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				640	101	177	278	41	238	10	638	638	1180	353	840	8.56%	289	11884	18.57	19	32	51	219	1162	2	4	6	10	724	18	7	56.63%	3090	2	3	0.47	2	12	1	1	13	17	16

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Michael Hutchinson	HERSEY Bears (WSH)	40	20	17	3	0.907	2.23	2399	4	4	89	962	1	1	0.750	12	40	0	6	2	3
2	Ukko-Pekka Luukkonen	HERSEY Bears (WSH)	2	0	0	0	1.000	0.00	26	0	0	0	13	0	0	0.000	0	0	40	0	0	0
Stats d'équipe Total ou en Moyenne			42	20	17	3	0.909	2.20	2426	4	4	89	975	1	1	0.750	12	40	40	6	2	3

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Type	Salaire Actuel	Salaire Restant	Salaire Moyen	Salaire Moyen Restant	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Salaire Année 4	Salaire Année 5	Salaire Année 6	Link
Alexandre Fortin	HERSEY Bears (WSH)	LW	23	1997-02-25	No	84 Kg	183 CM	No	No	No	1	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No						Lien
Anders Bjork	HERSEY Bears (WSH)	LW	24	1996-08-05	No	86 Kg	183 CM	No	No	No	1	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No						Lien
Chandler Stephenson	HERSEY Bears (WSH)	C	26	1994-04-22	No	95 Kg	183 CM	No	No	No	4	Pro & Farm	1,000,000$	522,935$	1,000,000$	522,935$	0$	0$	No	1,000,000$	1,000,000$	1,000,000$			Lien
Dmytro Timashov	HERSEY Bears (WSH)	LW	23	1996-10-01	Yes	87 Kg	178 CM	No	No	No	4	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No	750,000$	750,000$	750,000$
Jesper Bratt	HERSEY Bears (WSH)	LW	22	1998-07-30	No	80 Kg	178 CM	No	No	No	6	Pro & Farm	2,000,000$	1,045,871$	2,000,000$	1,045,871$	0$	0$	No	2,000,000$	2,000,000$	2,000,000$	2,000,000$	2,000,000$	Lien
Joshua Ho-Sang	HERSEY Bears (WSH)	LW/RW	24	1996-01-22	No	79 Kg	183 CM	No	No	No	2	Pro & Farm	900,000$	470,642$	900,000$	470,642$	0$	0$	No	900,000$					Lien
Kevin Roy	HERSEY Bears (WSH)	LW	27	1993-05-20	No	78 Kg	175 CM	No	No	No	1	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No						Lien
Lukas Sedlak	HERSEY Bears (WSH)	C	27	1993-02-25	No	93 Kg	183 CM	No	No	No	2	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No	750,000$					Lien
Martin Necas	HERSEY Bears (WSH)	C	21	1999-01-15	Yes	86 Kg	188 CM	No	No	No	4	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No	750,000$	750,000$	750,000$
Matt Grzelcyk	HERSEY Bears (WSH)	D	26	1994-01-05	No	79 Kg	175 CM	No	No	No	1	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No						Lien
Michael Hutchinson	HERSEY Bears (WSH)	G	30	1990-03-02	No	90 Kg	191 CM	No	No	No	4	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No	750,000$	750,000$	750,000$			Lien
Mike Reilly	HERSEY Bears (WSH)	D	27	1993-07-13	No	91 Kg	185 CM	No	No	No	2	Pro & Farm	1,500,000$	784,403$	1,500,000$	784,403$	0$	0$	No	1,500,000$					Lien
Nick Paul	HERSEY Bears (WSH)	LW	25	1995-03-20	No	100 Kg	191 CM	No	No	No	4	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No	750,000$	750,000$	750,000$			Lien
Sami Niku	HERSEY Bears (WSH)	D	23	1996-10-10	No	80 Kg	185 CM	No	No	No	1	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No						Lien
Sebastian D Aho	HERSEY Bears (WSH)	D	24	1996-02-17	No	77 Kg	178 CM	No	No	No	1	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No						Lien
Taro Hirose	HERSEY Bears (WSH)	LW	24	1996-06-30	Yes	74 Kg	178 CM	No	No	No	4	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No	750,000$	750,000$	750,000$
Tim Heed	HERSEY Bears (WSH)	D	29	1991-01-27	No	82 Kg	180 CM	No	No	No	1	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No						Lien
Ukko-Pekka Luukkonen	HERSEY Bears (WSH)	G	21	1999-03-09	Yes	89 Kg	193 CM	No	No	No	4	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No	750,000$	750,000$	750,000$
Valentin Zykov	HERSEY Bears (WSH)	LW/RW	25	1995-05-15	Yes	100 Kg	183 CM	No	No	No	4	Pro & Farm	750,000$	392,201$	750,000$	392,201$	0$	0$	No	750,000$	750,000$	750,000$

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
19	24.79	86 Kg	183 CM	2.68	876,316$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Jesper Bratt	Chandler Stephenson	Valentin Zykov	31	1	2	2
2	Nick Paul	Martin Necas	Joshua Ho-Sang	26	1	2	2
3	Dmytro Timashov	Lukas Sedlak	Valentin Zykov	23	1	2	2
4	Anders Bjork	Chandler Stephenson	Valentin Zykov	20	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Matt Grzelcyk	Mike Reilly	31	1	2	2
2	Tim Heed	Sami Niku	26	1	2	2
3	Sebastian D Aho	Matt Grzelcyk	23	1	2	2
4	Mike Reilly	Tim Heed	20	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Jesper Bratt	Chandler Stephenson	Valentin Zykov	55	1	2	2
2	Nick Paul	Martin Necas	Joshua Ho-Sang	45	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Matt Grzelcyk	Mike Reilly	55	1	2	2
2	Tim Heed	Sami Niku	45	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Chandler Stephenson	Jesper Bratt	55	1	2	2
2	Martin Necas	Nick Paul	45	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Matt Grzelcyk	Mike Reilly	55	1	2	2
2	Tim Heed	Sami Niku	45	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Chandler Stephenson	55	1	2	2	Matt Grzelcyk	Mike Reilly	55	1	2	2
2	Martin Necas	45	1	2	2	Tim Heed	Sami Niku	45	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Chandler Stephenson	Jesper Bratt	55	1	2	2
2	Martin Necas	Nick Paul	45	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Matt Grzelcyk	Mike Reilly	55	1	2	2
2	Tim Heed	Sami Niku	45	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Jesper Bratt	Chandler Stephenson	Valentin Zykov	Matt Grzelcyk	Mike Reilly

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Jesper Bratt	Chandler Stephenson	Valentin Zykov	Matt Grzelcyk	Mike Reilly

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Dmytro Timashov, Anders Bjork, Valentin Zykov	Dmytro Timashov, Anders Bjork	Dmytro Timashov

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Tim Heed, Sami Niku, Sebastian D Aho	Tim Heed	Tim Heed, Sami Niku

Tirs de Pénalité
Jesper Bratt, Chandler Stephenson, Nick Paul, Martin Necas, Dmytro Timashov

Gardien
#1 : Michael Hutchinson, #2 : Ukko-Pekka Luukkonen

Lignes d'Attaque Perso. en Prol.
Jesper Bratt, Chandler Stephenson, Nick Paul, Martin Necas, Dmytro Timashov, Anders Bjork, Anders Bjork, Valentin Zykov, Joshua Ho-Sang, Kevin Roy, Alexandre Fortin

Lignes de Défense Perso. en Prol.
Matt Grzelcyk, Mike Reilly, Tim Heed, Sami Niku, Sebastian D Aho

Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

	Ligue												Domicile											Visiteur
#	VS Équipe	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	PCT	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
1	BELLEVILLE Senators	1	0	0	0	0	0	0	1	1	2	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	1	2	-1	1	0.500	1	2	3	0	0	42	30	24	7	14	378	370	403	41	42	15	8	10	2	0	0.00%	4	0	100.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
2	BRIDGEPORT Sound Tigers	1	0	1	0	0	0	0	0	2	4	-2	1	0	1	0	0	0	0	0	2	4	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	4	6	1	0	42	30	24	7	26	378	370	403	41	18	4	2	15	7	0	0.00%	1	1	0.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
3	BROOKLYN Wolfpack	2	0	2	0	0	0	0	0	2	6	-4	1	0	1	0	0	0	0	0	0	1	-1	1	0	1	0	0	0	0	0	2	5	-3	0	0.000	2	4	6	0	0	42	30	24	7	41	378	370	403	41	41	7	10	29	3	1	33.33%	4	1	75.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
4	Binghampton Devils	1	1	0	0	0	0	0	0	4	2	2	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	4	2	2	2	1.000	4	7	11	0	0	42	30	24	7	41	378	370	403	41	20	9	15	19	6	1	16.67%	3	0	100.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
5	CHICAGO Wolves	2	1	1	0	0	0	0	0	5	6	-1	1	1	0	0	0	0	0	0	4	3	1	1	0	1	0	0	0	0	0	1	3	-2	2	0.500	5	8	13	0	0	42	30	24	7	48	378	370	403	41	68	17	14	38	2	0	0.00%	7	0	100.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
6	COLORADO Eagles	2	0	1	0	1	0	0	0	8	8	0	1	0	0	0	1	0	0	0	5	4	1	1	0	1	0	0	0	0	0	3	4	-1	2	0.500	8	12	20	0	0	42	30	24	7	51	378	370	403	41	55	12	18	32	7	1	14.29%	7	4	42.86%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
7	HOLLYWOOD Oscar	1	0	0	0	1	0	0	0	3	2	1	1	0	0	0	1	0	0	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	3	5	8	0	0	42	30	24	7	31	378	370	403	41	19	11	2	16	5	2	40.00%	1	0	100.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
8	IOWA Wild	1	0	1	0	0	0	0	0	1	3	-2	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	1	2	3	0	0	42	30	24	7	23	378	370	403	41	24	6	4	13	3	0	0.00%	2	1	50.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
9	LEHIGH VALLEY Phantoms	3	1	1	0	0	0	1	0	5	4	1	1	0	0	0	0	0	1	0	2	1	1	2	1	1	0	0	0	0	0	3	3	0	4	0.667	5	8	13	0	0	42	30	24	7	93	378	370	403	41	70	17	20	64	6	2	33.33%	10	1	90.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
10	MILWAUKEE Admirals	2	1	1	0	0	0	0	0	3	2	1	2	1	1	0	0	0	0	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	2	0.500	3	5	8	0	0	42	30	24	7	50	378	370	403	41	42	17	14	25	3	0	0.00%	7	0	100.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
11	MONT-LAURIER Sommet	1	0	1	0	0	0	0	0	2	3	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	2	3	-1	0	0.000	2	3	5	0	0	42	30	24	7	38	378	370	403	41	25	6	7	22	3	1	33.33%	1	0	100.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
12	Manitoba Moose	3	1	1	0	0	1	0	0	6	5	1	1	0	0	0	0	1	0	0	3	4	-1	2	1	1	0	0	0	0	0	3	1	2	3	0.500	6	10	16	0	1	42	30	24	7	71	378	370	403	41	91	26	18	45	11	0	0.00%	8	1	87.50%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
13	Marlies de Toronto	2	0	2	0	0	0	0	0	4	8	-4	2	0	2	0	0	0	0	0	4	8	-4	0	0	0	0	0	0	0	0	0	0	0	0	0.000	4	8	12	0	0	42	30	24	7	60	378	370	403	41	44	16	12	41	3	0	0.00%	6	3	50.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
14	PV Sharapovas	1	0	0	0	1	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	2	1	1	2	1.000	2	4	6	0	0	42	30	24	7	19	378	370	403	41	25	2	4	20	2	0	0.00%	1	0	100.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
15	Quebec Nordiques	1	1	0	0	0	0	0	0	5	1	4	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	5	1	4	2	1.000	5	10	15	0	0	42	30	24	7	44	378	370	403	41	20	4	6	30	5	0	0.00%	3	0	100.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
16	SAN DIEGO Gulls	1	1	0	0	0	0	0	0	9	2	7	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	9	2	7	2	1.000	9	16	25	0	0	42	30	24	7	62	378	370	403	41	12	3	4	12	0	0	0.00%	2	0	100.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
17	STOCKTON Flames	3	2	0	0	0	0	0	1	8	5	3	2	1	0	0	0	0	0	1	7	5	2	1	1	0	0	0	0	0	0	1	0	1	5	0.833	8	14	22	0	1	42	30	24	7	92	378	370	403	41	80	25	20	50	13	3	23.08%	9	1	88.89%	1	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
18	Syracruse Crunch	2	1	0	0	0	0	1	0	7	4	3	1	0	0	0	0	0	1	0	3	2	1	1	1	0	0	0	0	0	0	4	2	2	4	1.000	7	10	17	0	0	42	30	24	7	97	378	370	403	41	48	15	10	23	7	3	42.86%	5	0	100.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
19	TUSCON Roadrunners	2	1	1	0	0	0	0	0	3	1	2	0	0	0	0	0	0	0	0	0	0	0	2	1	1	0	0	0	0	0	3	1	2	2	0.500	3	6	9	0	1	42	30	24	7	52	378	370	403	41	32	11	2	25	9	2	22.22%	1	1	0.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
	Total	40	13	17	0	5	1	2	2	103	92	11	19	4	8	0	3	1	2	1	50	52	-2	21	9	9	0	2	0	0	1	53	40	13	43	0.538	103	177	280	1	4	42	30	24	7	1180	378	370	403	41	976	289	242	638	134	19	14.18%	104	18	82.69%	2	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
21	UTICA Comets	3	1	1	0	1	0	0	0	11	11	0	1	0	1	0	0	0	0	0	2	5	-3	2	1	0	0	1	0	0	0	9	6	3	4	0.667	11	22	33	0	0	42	30	24	7	73	378	370	403	41	67	20	16	40	16	3	18.75%	6	1	83.33%	1	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
22	VICTORIAVILLE Tigres	3	1	1	0	1	0	0	0	9	6	3	3	1	1	0	1	0	0	0	9	6	3	0	0	0	0	0	0	0	0	0	0	0	4	0.667	9	12	21	0	1	42	30	24	7	97	378	370	403	41	80	17	16	35	11	0	0.00%	7	0	100.00%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
23	WILKIES-BARRIE Penguins	2	0	2	0	0	0	0	0	3	6	-3	1	0	1	0	0	0	0	0	3	5	-2	1	0	1	0	0	0	0	0	0	1	-1	0	0.000	3	5	8	0	0	42	30	24	7	57	378	370	403	41	53	29	20	34	10	0	0.00%	9	3	66.67%	0	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
	_Since Last GM Reset	40	13	17	0	5	1	2	2	103	92	11	19	4	8	0	3	1	2	1	50	52	-2	21	9	9	0	2	0	0	1	53	40	13	43	0.538	103	177	280	1	4	42	30	24	7	1180	378	370	403	41	976	289	242	638	134	19	14.18%	104	18	82.69%	2	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
	_Vs Conference	17	5	10	0	2	0	0	0	47	48	-1	9	2	6	0	1	0	0	0	20	27	-7	8	3	4	0	1	0	0	0	27	21	6	14	0.412	47	85	132	1	1	42	30	24	7	463	378	370	403	41	379	107	92	257	50	7	14.00%	41	11	73.17%	1	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
	_Vs Division	11	2	6	0	1	0	0	0	36	24	12	4	0	4	0	0	0	0	0	12	12	0	7	2	2	0	1	0	0	0	24	12	12	6	0.273	36	66	102	0	2	42	30	24	7	348	378	370	403	41	235	76	51	165	46	11	23.91%	20	3	85.00%	2	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266

			Total Pour les Joueurs
Matchs Joués	Points	Séquence	Buts	Passes	Points	Tirs Pour	Tirs Contre	Tirs Bloqués	Minutes de Pénalité	Mises en Échec	Buts en Filet Désert	Blanchissage
40	43	W1	103	177	280	1180	976	289	242	638	1	4

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
40	13	17	5	1	2	2	103	92

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
19	4	8	3	1	2	1	50	52

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
21	9	9	2	0	0	1	53	40

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	5	0	1	0	0

Tentatives en Avantage Numérique	Buts en Avantage Numérique	% en Avantage Numérique	Tentatives en Désavantage Numérique	Buts Contre en Désavantage Numérique	% en Désavantage Numérique	Buts Pour en Désavantage Numérique
134	19	14.18%	104	18	82.69%	2

Tirs en 1e Période	Tirs en 2e Période	Tirs en 3e Période	Tirs en 4e Période	Buts en 1e Période	Buts en 2e Période	Buts en 3e Période	Buts en 4e Période
378	370	403	41	42	30	24	7

Mises en Jeu
Gagnées en Zone Offensive	Total en Zone Offensive	% Gagnées en Zone Offensive	Gagnées en Zone Défensive	Total en Zone Défensive	% Gagnées en Zone Défensive	Gagnées en Zone Neutre	Total en Zone Neutre	% Gagnées en Zone Neutre
795	1322	60.14%	617	1142	54.03%	338	578	58.48%

Temps Avec la Rondelle
En Zone Offensive	Contrôle en Zone Offensive	En Zone Défensive	Contrôle en Zone Défensive	En Zone Neutre	Contrôle en Zone Neutre
1077	774	846	272	510	266

Derniers Match Joués Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

Jour	Match	Équipe Visiteuse	Score	Équipe Locale	Score	ST	OT	SO	Lien
1 - 2020-08-02	5	VICTORIAVILLE Tigres	3	HERSEY Bears	4	W	X		Sommaire du Match
2 - 2020-08-03	20	HERSEY Bears	2	BROOKLYN Wolfpack	5	L			Sommaire du Match
4 - 2020-08-05	34	STOCKTON Flames	4	HERSEY Bears	3	L	X	X	Sommaire du Match
5 - 2020-08-06	45	HERSEY Bears	3	Manitoba Moose	0	W			Sommaire du Match
6 - 2020-08-07	58	HERSEY Bears	0	Manitoba Moose	1	L			Sommaire du Match
7 - 2020-08-08	67	HERSEY Bears	2	PV Sharapovas	1	W	X		Sommaire du Match
8 - 2020-08-09	78	COLORADO Eagles	4	HERSEY Bears	5	W	X		Sommaire du Match
10 - 2020-08-11	91	HERSEY Bears	9	SAN DIEGO Gulls	2	W			Sommaire du Match
11 - 2020-08-12	103	CHICAGO Wolves	3	HERSEY Bears	4	W			Sommaire du Match
12 - 2020-08-13	118	VICTORIAVILLE Tigres	0	HERSEY Bears	3	W			Sommaire du Match
14 - 2020-08-15	137	HERSEY Bears	4	Binghampton Devils	2	W			Sommaire du Match
15 - 2020-08-16	145	HERSEY Bears	2	MONT-LAURIER Sommet	3	L			Sommaire du Match
16 - 2020-08-17	150	Marlies de Toronto	3	HERSEY Bears	0	L			Sommaire du Match
18 - 2020-08-19	169	WILKIES-BARRIE Penguins	5	HERSEY Bears	3	L			Sommaire du Match
19 - 2020-08-20	187	Syracruse Crunch	2	HERSEY Bears	3	W	X	X	Sommaire du Match
20 - 2020-08-21	192	HERSEY Bears	0	TUSCON Roadrunners	1	L			Sommaire du Match
22 - 2020-08-23	215	HERSEY Bears	3	LEHIGH VALLEY Phantoms	2	W			Sommaire du Match
23 - 2020-08-24	219	HERSEY Bears	1	IOWA Wild	3	L			Sommaire du Match
24 - 2020-08-25	231	STOCKTON Flames	1	HERSEY Bears	4	W			Sommaire du Match
25 - 2020-08-26	247	HERSEY Bears	3	COLORADO Eagles	4	L			Sommaire du Match
26 - 2020-08-27	254	HERSEY Bears	4	UTICA Comets	3	W	X		Sommaire du Match
27 - 2020-08-28	266	MILWAUKEE Admirals	1	HERSEY Bears	0	L			Sommaire du Match
29 - 2020-08-30	282	BRIDGEPORT Sound Tigers	4	HERSEY Bears	2	L			Sommaire du Match
31 - 2020-09-01	303	LEHIGH VALLEY Phantoms	1	HERSEY Bears	2	W	X	X	Sommaire du Match
32 - 2020-09-02	315	HERSEY Bears	1	BELLEVILLE Senators	2	L	X	X	Sommaire du Match
33 - 2020-09-03	323	HERSEY Bears	0	WILKIES-BARRIE Penguins	1	L			Sommaire du Match
34 - 2020-09-04	331	VICTORIAVILLE Tigres	3	HERSEY Bears	2	L			Sommaire du Match
36 - 2020-09-06	350	HERSEY Bears	3	TUSCON Roadrunners	0	W			Sommaire du Match
37 - 2020-09-07	358	HOLLYWOOD Oscar	2	HERSEY Bears	3	W	X		Sommaire du Match
38 - 2020-09-08	368	HERSEY Bears	5	Quebec Nordiques	1	W			Sommaire du Match
40 - 2020-09-10	386	Manitoba Moose	4	HERSEY Bears	3	L	X		Sommaire du Match
41 - 2020-09-11	395	HERSEY Bears	1	STOCKTON Flames	0	W			Sommaire du Match
42 - 2020-09-12	412	UTICA Comets	5	HERSEY Bears	2	L			Sommaire du Match
44 - 2020-09-14	422	HERSEY Bears	0	LEHIGH VALLEY Phantoms	1	L			Sommaire du Match
45 - 2020-09-15	433	HERSEY Bears	4	Syracruse Crunch	2	W			Sommaire du Match
46 - 2020-09-16	442	MILWAUKEE Admirals	1	HERSEY Bears	3	W			Sommaire du Match
48 - 2020-09-18	463	BROOKLYN Wolfpack	1	HERSEY Bears	0	L			Sommaire du Match
49 - 2020-09-19	476	HERSEY Bears	1	CHICAGO Wolves	3	L			Sommaire du Match
50 - 2020-09-20	488	Marlies de Toronto	5	HERSEY Bears	4	L			Sommaire du Match
52 - 2020-09-22	506	HERSEY Bears	5	UTICA Comets	3	W			Sommaire du Match
53 - 2020-09-23	516	Syracruse Crunch	-	HERSEY Bears	-
54 - 2020-09-24	523	HERSEY Bears	-	Binghampton Devils	-
56 - 2020-09-26	538	Binghampton Devils	-	HERSEY Bears	-
57 - 2020-09-27	548	HERSEY Bears	-	HOLLYWOOD Oscar	-
58 - 2020-09-28	563	HERSEY Bears	-	BROOKLYN Wolfpack	-
59 - 2020-09-29	574	COLORADO Eagles	-	HERSEY Bears	-
60 - 2020-09-30	591	PV Sharapovas	-	HERSEY Bears	-
62 - 2020-10-02	605	HERSEY Bears	-	MILWAUKEE Admirals	-
63 - 2020-10-03	615	ROCKFORD IceHogs	-	HERSEY Bears	-
64 - 2020-10-04	629	HERSEY Bears	-	Marlies de Toronto	-
65 - 2020-10-05	642	HERSEY Bears	-	PV Sharapovas	-
66 - 2020-10-06	648	COLORADO Eagles	-	HERSEY Bears	-
68 - 2020-10-08	669	LAVAL Rockets	-	HERSEY Bears	-
69 - 2020-10-09	679	HERSEY Bears	-	PROVIDENCE Bruins	-
70 - 2020-10-10	692	HERSEY Bears	-	VICTORIAVILLE Tigres	-
71 - 2020-10-11	698	Quebec Nordiques	-	HERSEY Bears	-
72 - 2020-10-12	717	PROVIDENCE Bruins	-	HERSEY Bears	-
75 - 2020-10-15	739	HERSEY Bears	-	LAVAL Rockets	-
76 - 2020-10-16	748	CHICAGO Wolves	-	HERSEY Bears	-
77 - 2020-10-17	761	HERSEY Bears	-	BRIDGEPORT Sound Tigers	-
78 - 2020-10-18	771	WILKIES-BARRIE Penguins	-	HERSEY Bears	-
80 - 2020-10-20	792	Quebec Nordiques	-	HERSEY Bears	-
81 - 2020-10-21	799	HERSEY Bears	-	MONT-LAURIER Sommet	-
82 - 2020-10-22	806	HERSEY Bears	-	SAN DIEGO Gulls	-
83 - 2020-10-23	824	IOWA Wild	-	HERSEY Bears	-
84 - 2020-10-24	831	HERSEY Bears	-	HOLLYWOOD Oscar	-
86 - 2020-10-26	849	HERSEY Bears	-	BRIDGEPORT Sound Tigers	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
87 - 2020-10-27	855	BELLEVILLE Senators	-	HERSEY Bears	-
88 - 2020-10-28	872	HERSEY Bears	-	LAVAL Rockets	-
89 - 2020-10-29	880	PROVIDENCE Bruins	-	HERSEY Bears	-
91 - 2020-10-31	903	HERSEY Bears	-	ROCKFORD IceHogs	-
92 - 2020-11-01	909	BELLEVILLE Senators	-	HERSEY Bears	-
93 - 2020-11-02	920	HERSEY Bears	-	SAN DIEGO Gulls	-
94 - 2020-11-03	935	IOWA Wild	-	HERSEY Bears	-
95 - 2020-11-04	944	HERSEY Bears	-	Manitoba Moose	-
97 - 2020-11-06	960	MONT-LAURIER Sommet	-	HERSEY Bears	-
99 - 2020-11-08	981	SAN DIEGO Gulls	-	HERSEY Bears	-
103 - 2020-11-12	1004	TUSCON Roadrunners	-	HERSEY Bears	-
104 - 2020-11-13	1012	HERSEY Bears	-	ROCKFORD IceHogs	-
107 - 2020-11-16	1031	TUSCON Roadrunners	-	HERSEY Bears	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	35	15
Assistance	0	0
Assistance PCT	0.00%	0.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
21	0 - 0.00%	0$	0$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
790,401$	1,665,000$	1,665,000$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	787,649$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	57	15,275$	870,675$

Afficher ou Masquer des Colonnes

	Ligue											Domicile											Visiteur
Année	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
Saison Régulière
33	82	45	21	0	8	4	2	2	362	162	200	41	22	11	0	4	2	2	0	173	78	95	41	23	10	0	4	2	0	2	189	84	105	90	362	636	998	1	20	175	101	76	13	3608	1178	1182	1205	57	1788	480	286	1110	260	45	17.31%	118	19	83.90%	2	1772	2845	62.28%	1043	2001	52.12%	827	1288	64.21%	2602	2043	1460	453	905	507
34	40	13	17	0	5	1	2	2	103	92	11	19	4	8	0	3	1	2	1	50	52	-2	21	9	9	0	2	0	0	1	53	40	13	43	103	177	280	1	4	42	30	24	7	1180	378	370	403	41	976	289	242	638	134	19	14.18%	104	18	82.69%	2	795	1322	60.14%	617	1142	54.03%	338	578	58.48%	1077	774	846	272	510	266
Total Saison Régulière	122	58	38	0	13	5	4	4	465	254	211	60	26	19	0	7	3	4	1	223	130	93	62	32	19	0	6	2	0	3	242	124	118	133	465	813	1278	2	24	217	131	100	20	4788	1556	1552	1608	98	2764	769	528	1748	394	64	16.24%	222	37	83.33%	4	2567	4167	61.60%	1660	3143	52.82%	1165	1866	62.43%	3680	2817	2307	726	1415	774
Séries
33	6	2	4	0	0	0	0	0	11	16	-5	3	0	3	0	0	0	0	0	4	10	-6	3	2	1	0	0	0	0	0	7	6	1	4	11	20	31	1	0	6	3	1	1	170	56	41	44	29	181	46	36	92	33	6	18.18%	18	3	83.33%	0	117	235	49.79%	92	226	40.71%	45	113	39.82%	166	113	179	55	91	46
Total Séries	6	2	4	0	0	0	0	0	11	16	-5	3	0	3	0	0	0	0	0	4	10	-6	3	2	1	0	0	0	0	0	7	6	1	4	11	20	31	1	0	6	3	1	1	170	56	41	44	29	181	46	36	92	33	6	18.18%	18	3	83.33%	0	117	235	49.79%	92	226	40.71%	45	113	39.82%	166	113	179	55	91	46