Stanley Cup Winners Hockey League

NASHVILLE Predators
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Lignes
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Calendrier
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Stats d'équipe en Carrière
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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	Dmitrij Jaskin	0		X	X		100.00	83	35	76	66	84	75	68	65	50	66	62	62	64	62	54	71	97	68	0
2	Pontus Aberg	0		X	X		100.00	64	35	77	70	72	79	74	69	50	69	68	60	69	55	52	73	95	68	0
3	William Carrier	0		X			100.00	99	41	71	65	83	74	67	64	50	61	66	60	65	55	52	67	97	67	0
4	Brendan Lemieux (R)	0		X			100.00	79	59	48	67	80	73	76	66	61	63	68	61	67	53	51	78	97	67	0
5	Beau Bennett	0			X		100.00	60	43	73	61	74	66	83	65	30	70	58	60	58	58	54	70	97	65	0
6	Markus Hannikainen (R)	0		X			100.00	72	35	73	64	77	74	57	63	50	63	64	62	64	54	51	42	97	64	0
7	Carter Verhaeghe	0	X				100.00	52	89	65	70	78	50	50	70	70	67	67	57	67	50	50	43	97	61	0
8	Mark Letestu	0	X				100.00	50	35	69	70	69	50	51	70	70	64	64	52	64	72	57	23	97	61	0
9	Tomas Hyka (R)	0			X		100.00	51	35	73	69	64	58	58	68	56	66	65	57	66	51	50	47	97	61	0
10	Sergey Tolchinsky	0		X			100.00	48	42	74	60	54	53	60	60	50	62	57	60	57	50	50	44	97	57	0
11	Dylan DeMelo	0				X	100.00	74	35	75	67	76	83	90	66	30	66	61	77	69	58	53	47	92	70	0
12	Christian Folin	0				X	100.00	88	41	76	63	84	77	58	63	30	61	55	72	64	59	53	36	97	66	0
13	Thomas Schemitsch (R)	0				X	100.00	58	89	66	67	86	50	50	67	30	57	57	51	57	50	50	44	97	59	0
14	John Ramage	0				X	100.00	50	89	60	66	72	50	50	66	30	52	47	50	57	50	50	51	97	55	0
Rayé
1	Dalton Smith	0		X			100.00	56	89	48	57	82	50	50	57	50	52	52	50	52	50	50	66	97	55	0

	MOYENNE D'ÉQUIPE					100.00	66	53	68	65	76	64	63	65	47	63	61	59	63	55	52	53	97	63

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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	Aaron Dell	100.00	81	74	75	75	80	79	81	80	79	80	74	56	69	35	92	69	0
2	Thatcher Demko	100.00	74	70	79	85	73	73	74	73	73	73	68	51	63	74	97	65	0
Rayé
1	Charlie Lindgren	100.00	71	65	73	74	70	70	71	70	70	70	66	51	61	42	97	62	0
2	Samuel Montembeault (R)	100.00	67	68	72	81	69	71	70	69	69	66	66	50	59	44	97	61	0

	MOYENNE D'ÉQUIPE	100.00	73	69	75	79	73	73	74	73	73	72	69	52	63	49	96	64

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Davis Payne	70	70	70	70	75	75	74	CAN	50	2	650,000$

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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	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	FO%	FOT	P/20
1	Markus Hannikainen	MILWAUKEE Admirals (NSH)	LW	2	0	3	3	2	0	0	0	2	3	0	0.00%	0	25	12.98	0	0	0	0	0	0	2	0.00%	1	2.31
2	Dmitrij Jaskin	MILWAUKEE Admirals (NSH)	LW/RW	2	1	1	2	-1	0	5	5	8	4	7	12.50%	2	51	25.67	0	1	1	4	9	0	6	37.04%	27	0.78
3	Christian Folin	MILWAUKEE Admirals (NSH)	D	2	2	0	2	-2	6	5	4	7	0	6	28.57%	4	46	23.41	1	0	1	5	10	0	1	0.00%	0	0.85
4	Beau Bennett	MILWAUKEE Admirals (NSH)	RW	2	0	2	2	-2	0	3	6	2	1	4	0.00%	2	44	22.16	0	0	0	0	7	1	3	50.00%	4	0.90
5	Brendan Lemieux	MILWAUKEE Admirals (NSH)	LW	2	2	0	2	2	0	6	4	6	1	3	33.33%	1	35	17.68	0	0	0	0	0	0	4	35.71%	14	1.13
6	John Ramage	MILWAUKEE Admirals (NSH)	D	2	0	1	1	-2	2	3	0	1	0	0	0.00%	5	36	18.30	0	0	0	0	1	0	2	0.00%	0	0.55
7	William Carrier	MILWAUKEE Admirals (NSH)	LW	2	0	1	1	-4	0	9	7	3	1	8	0.00%	1	48	24.18	0	0	0	0	8	0	5	40.00%	10	0.41
8	Dylan DeMelo	MILWAUKEE Admirals (NSH)	D	1	0	1	1	0	0	0	2	1	0	1	0.00%	0	27	27.75	0	1	1	0	3	0	0	0.00%	0	0.72
9	Tomas Hyka	MILWAUKEE Admirals (NSH)	RW	2	0	1	1	-3	2	2	2	3	2	4	0.00%	1	35	17.87	0	0	0	0	6	0	0	66.67%	3	0.56
10	Sergey Tolchinsky	MILWAUKEE Admirals (NSH)	LW	2	0	0	0	0	0	0	2	1	0	0	0.00%	0	23	11.71	0	0	0	0	2	0	0	20.00%	5	0.00
11	Carter Verhaeghe	MILWAUKEE Admirals (NSH)	C	2	0	0	0	-5	2	0	4	3	5	4	0.00%	1	33	16.87	0	0	0	3	8	0	0	40.00%	40	0.00
12	Mark Letestu	MILWAUKEE Admirals (NSH)	C	2	0	0	0	-3	0	0	6	5	1	1	0.00%	0	33	16.56	0	0	0	2	6	0	0	48.94%	47	0.00
13	Pontus Aberg	MILWAUKEE Admirals (NSH)	LW/RW	1	0	0	0	-1	0	0	1	3	1	1	0.00%	1	26	26.53	0	0	0	0	3	0	2	25.00%	16	0.00
14	Thomas Schemitsch	MILWAUKEE Admirals (NSH)	D	2	0	0	0	-4	6	7	1	1	0	3	0.00%	3	39	19.59	0	0	0	1	6	0	2	0.00%	0	0.00
Stats d'équipe Total ou en Moyenne				26	5	10	15	-23	18	40	44	46	19	42	10.87%	21	508	19.55	1	2	3	15	74	1	34	40.12%	167	0.59

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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	L	PCT	GAA	MP	GA	SA	ST	BG
1	Aaron Dell	MILWAUKEE Admirals (NSH)	2	2	0.804	7.14	84	10	51	2	0
2	Thatcher Demko	MILWAUKEE Admirals (NSH)	1	0	0.909	3.43	35	2	22	0	2
Stats d'équipe Total ou en Moyenne			3	2	0.836	6.00	120	12	73	2	2

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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	Link
Aaron Dell	MILWAUKEE Admirals (NSH)	G	30	1989-05-04	No	93 Kg	183 CM	No	No	No	1	Pro & Farm	750,000$	736,486$	750,000$	736,486$	0$	0$	No				Lien
Beau Bennett	MILWAUKEE Admirals (NSH)	RW	27	1991-11-27	No	89 Kg	188 CM	No	No	No	2	Pro & Farm	750,000$	736,486$	750,000$	736,486$	0$	0$	No	750,000$			Lien
Brendan Lemieux	MILWAUKEE Admirals (NSH)	LW	23	1996-03-15	Yes	98 Kg	185 CM	No	No	No	2	Pro & Farm	750,000$	736,486$	325,000$	319,144$	0$	0$	No	750,000$			Lien
Carter Verhaeghe	MILWAUKEE Admirals (NSH)	C	24	1995-08-14	No	86 Kg	188 CM	No	No	No	2	Pro & Farm	750,000$	736,486$	750,000$	736,486$	0$	0$	No	750,000$			Lien
Charlie Lindgren	MILWAUKEE Admirals (NSH)	G	25	1993-12-18	No	83 Kg	185 CM	No	No	No	2	Pro & Farm	750,000$	736,486$	750,000$	736,486$	0$	0$	No	750,000$			Lien
Christian Folin	MILWAUKEE Admirals (NSH)	D	28	1991-02-09	No	93 Kg	191 CM	No	No	No	1	Pro & Farm	1,000,000$	981,981$	1,000,000$	981,981$	0$	0$	No				Lien
Dalton Smith	MILWAUKEE Admirals (NSH)	LW	27	1992-06-30	No	94 Kg	188 CM	No	No	No	2	Pro & Farm	750,000$	736,486$	750,000$	736,486$	0$	0$	No	750,000$			Lien
Dmitrij Jaskin	MILWAUKEE Admirals (NSH)	LW/RW	26	1993-03-23	No	98 Kg	188 CM	No	No	No	1	Pro & Farm	750,000$	736,486$	750,000$	736,486$	0$	0$	No				Lien
Dylan DeMelo	MILWAUKEE Admirals (NSH)	D	26	1993-05-01	No	89 Kg	185 CM	No	No	No	2	Pro & Farm	900,000$	883,783$	900,000$	883,783$	0$	0$	No	900,000$			Lien
John Ramage	MILWAUKEE Admirals (NSH)	D	28	1991-02-07	No	86 Kg	183 CM	No	No	No	3	Pro & Farm	750,000$	736,486$	750,000$	736,486$	0$	0$	No	750,000$	750,000$		Lien
Mark Letestu	MILWAUKEE Admirals (NSH)	C	34	1985-02-04	No	89 Kg	178 CM	No	No	No	1	Pro & Farm	1,500,000$	1,472,972$	1,500,000$	1,472,972$	0$	0$	No				Lien
Markus Hannikainen	MILWAUKEE Admirals (NSH)	LW	26	1993-03-26	Yes	91 Kg	185 CM	No	No	No	2	Pro & Farm	750,000$	736,486$	750,000$	736,486$	0$	0$	No	750,000$			Lien
Pontus Aberg	MILWAUKEE Admirals (NSH)	LW/RW	25	1993-09-23	No	89 Kg	180 CM	No	No	No	1	Pro & Farm	750,000$	736,486$	750,000$	736,486$	0$	0$	No				Lien
Samuel Montembeault (Contrat à 1 Volet)	MILWAUKEE Admirals (NSH)	G	22	1996-10-30	Yes	87 Kg	191 CM	No	No	No	4	Pro & Farm	750,000$	736,607$	750,000$	736,607$	750,000$	736,607$	No	750,000$	750,000$	750,000$	Lien
Sergey Tolchinsky	MILWAUKEE Admirals (NSH)	LW	24	1995-02-03	No	77 Kg	173 CM	No	No	No	2	Pro & Farm	750,000$	736,486$	750,000$	736,486$	0$	0$	No	750,000$			Lien
Thatcher Demko	MILWAUKEE Admirals (NSH)	G	23	1995-12-08	No	87 Kg	193 CM	No	No	No	1	Pro & Farm	750,000$	736,486$	750,000$	736,486$	0$	0$	No				Lien
Thomas Schemitsch	MILWAUKEE Admirals (NSH)	D	22	1996-10-26	Yes	91 Kg	193 CM	No	No	No	3	Pro & Farm	750,000$	736,486$	750,000$	736,486$	0$	0$	No	750,000$	750,000$		Lien
Tomas Hyka	MILWAUKEE Admirals (NSH)	RW	26	1993-03-23	Yes	73 Kg	180 CM	No	No	No	2	Pro & Farm	750,000$	736,486$	750,000$	736,486$	0$	0$	No	750,000$			Lien
William Carrier	MILWAUKEE Admirals (NSH)	LW	24	1994-12-20	No	96 Kg	188 CM	No	No	No	1	Pro & Farm	750,000$	736,486$	750,000$	736,486$	0$	0$	No				Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
19	25.79	89 Kg	185 CM	1.84	810,526$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Pontus Aberg	Carter Verhaeghe	Dmitrij Jaskin	31	1	2	2
2	William Carrier	Mark Letestu	Beau Bennett	26	1	2	2
3	Brendan Lemieux	Pontus Aberg	Tomas Hyka	23	1	2	2
4	Markus Hannikainen	Dmitrij Jaskin	William Carrier	20	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dylan DeMelo	Christian Folin	31	1	2	2
2	Thomas Schemitsch	John Ramage	26	1	2	2
3	Dylan DeMelo	Christian Folin	23	1	2	2
4	Thomas Schemitsch	John Ramage	20	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Pontus Aberg	Carter Verhaeghe	Dmitrij Jaskin	55	1	2	2
2	William Carrier	Mark Letestu	Beau Bennett	45	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dylan DeMelo	Christian Folin	55	1	2	2
2	Thomas Schemitsch	John Ramage	45	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Pontus Aberg	Dmitrij Jaskin	55	1	2	2
2	William Carrier	Brendan Lemieux	45	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dylan DeMelo	Christian Folin	55	1	2	2
2	Thomas Schemitsch	John Ramage	45	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Pontus Aberg	55	1	2	2	Dylan DeMelo	Christian Folin	55	1	2	2
2	Dmitrij Jaskin	45	1	2	2	Thomas Schemitsch	John Ramage	45	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Pontus Aberg	Dmitrij Jaskin	55	1	2	2
2	William Carrier	Brendan Lemieux	45	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dylan DeMelo	Christian Folin	55	1	2	2
2	Thomas Schemitsch	John Ramage	45	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Pontus Aberg	Carter Verhaeghe	Dmitrij Jaskin	Dylan DeMelo	Christian Folin

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Pontus Aberg	Carter Verhaeghe	Dmitrij Jaskin	Dylan DeMelo	Christian Folin

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Sergey Tolchinsky, Markus Hannikainen, Tomas Hyka	Sergey Tolchinsky, Markus Hannikainen	Tomas Hyka

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Dylan DeMelo, Christian Folin, Thomas Schemitsch	Dylan DeMelo	Christian Folin, Thomas Schemitsch

Tirs de Pénalité
Pontus Aberg, Dmitrij Jaskin, William Carrier, Brendan Lemieux, Beau Bennett

Gardien
#1 : Aaron Dell, #2 : Thatcher Demko

Lignes d'Attaque Perso. en Prol.
Pontus Aberg, Dmitrij Jaskin, William Carrier, Brendan Lemieux, Beau Bennett, Markus Hannikainen, Markus Hannikainen, Carter Verhaeghe, Tomas Hyka, Mark Letestu, Sergey Tolchinsky

Lignes de Défense Perso. en Prol.
Dylan DeMelo, Christian Folin, Thomas Schemitsch, John Ramage,

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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

	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	BRIDGEPORT Sound Tigers	1	0	1	0	0	0	0	0	3	5	-2	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	3	5	-2	0	0.000	3	6	9	0	0	0	2	3	0	23	8	18	20	0	32	10	8	22	4	1	25.00%	3	1	66.67%	0	19	53	35.85%	32	79	40.51%	16	36	44.44%	40	28	56	13	23	10
	Total	2	0	2	0	0	0	0	0	5	12	-7	0	0	0	0	0	0	0	0	0	0	0	2	0	2	0	0	0	0	0	5	12	-7	0	0.000	5	10	15	0	0	0	2	3	0	46	8	18	20	0	73	22	18	40	12	1	8.33%	8	3	62.50%	0	19	53	35.85%	32	79	40.51%	16	36	44.44%	40	28	56	13	23	10
3	UTICA Comets	1	0	1	0	0	0	0	0	2	7	-5	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	2	7	-5	0	0.000	2	4	6	0	0	0	2	3	0	23	8	18	20	0	41	12	10	18	8	0	0.00%	5	2	60.00%	0	19	53	35.85%	32	79	40.51%	16	36	44.44%	40	28	56	13	23	10
	_Since Last GM Reset	2	0	2	0	0	0	0	0	5	12	-7	0	0	0	0	0	0	0	0	0	0	0	2	0	2	0	0	0	0	0	5	12	-7	0	0.000	5	10	15	0	0	0	2	3	0	46	8	18	20	0	73	22	18	40	12	1	8.33%	8	3	62.50%	0	19	53	35.85%	32	79	40.51%	16	36	44.44%	40	28	56	13	23	10
	_Vs Conference	2	0	2	0	0	0	0	0	5	12	-7	0	0	0	0	0	0	0	0	0	0	0	2	0	2	0	0	0	0	0	5	12	-7	0	0.000	5	10	15	0	0	0	2	3	0	46	8	18	20	0	73	22	18	40	12	1	8.33%	8	3	62.50%	0	19	53	35.85%	32	79	40.51%	16	36	44.44%	40	28	56	13	23	10

			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
2	0	L2	5	10	15	46	73	22	18	40	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	0	2	0	0	0	0	5	12

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
0	0	0	0	0	0	0	0	0

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	0	2	0	0	0	0	5	12

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
0	2	0	0	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
12	1	8.33%	8	3	62.50%	0

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
8	18	20	0	0	2	3	0

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
19	53	35.85%	32	79	40.51%	16	36	44.44%

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
40	28	56	13	23	10

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	Lien
1 - 2020-01-15	1	MILWAUKEE Admirals	2	UTICA Comets	7	L	Sommaire du Match
2 - 2020-01-16	14	MILWAUKEE Admirals	3	BRIDGEPORT Sound Tigers	5	L	Sommaire du Match
3 - 2020-01-17	26	BRIDGEPORT Sound Tigers	-	MILWAUKEE Admirals	-
4 - 2020-01-18	39	MILWAUKEE Admirals	-	BRIDGEPORT Sound Tigers	-
5 - 2020-01-19	55	HERSEY Bears	-	MILWAUKEE Admirals	-
7 - 2020-01-21	72	Marlies de Toronto	-	MILWAUKEE Admirals	-
9 - 2020-01-23	90	MILWAUKEE Admirals	-	Marlies de Toronto	-
11 - 2020-01-25	93	BROOKLYN Wolfpack	-	MILWAUKEE Admirals	-
13 - 2020-01-27	109	MILWAUKEE Admirals	-	ROCKFORD IceHogs	-
15 - 2020-01-29	126	STOCKTON Flames	-	MILWAUKEE Admirals	-
17 - 2020-01-31	133	MILWAUKEE Admirals	-	SAN DIEGO Gulls	-
19 - 2020-02-02	146	MILWAUKEE Admirals	-	PROVIDENCE Bruins	-
20 - 2020-02-03	153	BRIDGEPORT Sound Tigers	-	MILWAUKEE Admirals	-
21 - 2020-02-04	169	MILWAUKEE Admirals	-	LAVAL Rockets	-
23 - 2020-02-06	181	PROVIDENCE Bruins	-	MILWAUKEE Admirals	-
24 - 2020-02-07	200	LAVAL Rockets	-	MILWAUKEE Admirals	-
26 - 2020-02-09	215	MILWAUKEE Admirals	-	Syracruse Crunch	-
27 - 2020-02-10	220	MILWAUKEE Admirals	-	VICTORIAVILLE Tigres	-
28 - 2020-02-11	233	LEHIGH VALLEY Phantoms	-	MILWAUKEE Admirals	-
29 - 2020-02-12	248	MILWAUKEE Admirals	-	UTICA Comets	-
30 - 2020-02-13	257	MILWAUKEE Admirals	-	ROCKFORD IceHogs	-
31 - 2020-02-14	260	VICTORIAVILLE Tigres	-	MILWAUKEE Admirals	-
33 - 2020-02-16	284	IOWA Wild	-	MILWAUKEE Admirals	-
34 - 2020-02-17	299	MILWAUKEE Admirals	-	CORNWALL Aces	-
35 - 2020-02-18	307	PROVIDENCE Bruins	-	MILWAUKEE Admirals	-
37 - 2020-02-20	326	LAVAL Rockets	-	MILWAUKEE Admirals	-
38 - 2020-02-21	343	MILWAUKEE Admirals	-	WILKIES-BARRIE Penguins	-
39 - 2020-02-22	351	SAN DIEGO Gulls	-	MILWAUKEE Admirals	-
40 - 2020-02-23	361	MILWAUKEE Admirals	-	TUSCON Roadrunners	-
42 - 2020-02-25	380	MILWAUKEE Admirals	-	PROVIDENCE Bruins	-
43 - 2020-02-26	388	HOLLYWOOD Oscar	-	MILWAUKEE Admirals	-
44 - 2020-02-27	405	MILWAUKEE Admirals	-	TUSCON Roadrunners	-
45 - 2020-02-28	411	Binghampton Devils	-	MILWAUKEE Admirals	-
46 - 2020-02-29	430	MILWAUKEE Admirals	-	LAVAL Rockets	-
47 - 2020-03-01	440	STOCKTON Flames	-	MILWAUKEE Admirals	-
49 - 2020-03-03	448	MILWAUKEE Admirals	-	BRIDGEPORT Sound Tigers	-
50 - 2020-03-04	467	MONT-LAURIER Sommet	-	MILWAUKEE Admirals	-
52 - 2020-03-06	484	CORNWALL Aces	-	MILWAUKEE Admirals	-
53 - 2020-03-07	494	MILWAUKEE Admirals	-	BRIDGEPORT Sound Tigers	-
54 - 2020-03-08	502	MILWAUKEE Admirals	-	BELLEVILLE Senators	-
56 - 2020-03-10	517	WILKIES-BARRIE Penguins	-	MILWAUKEE Admirals	-
58 - 2020-03-12	533	MILWAUKEE Admirals	-	BROOKLYN Wolfpack	-
59 - 2020-03-13	541	Marlies de Toronto	-	MILWAUKEE Admirals	-
60 - 2020-03-14	554	MILWAUKEE Admirals	-	IOWA Wild	-
61 - 2020-03-15	566	MILWAUKEE Admirals	-	Manitoba Moose	-
62 - 2020-03-16	576	UTICA Comets	-	MILWAUKEE Admirals	-
63 - 2020-03-17	597	TUSCON Roadrunners	-	MILWAUKEE Admirals	-
64 - 2020-03-18	607	MILWAUKEE Admirals	-	SAN DIEGO Gulls	-
65 - 2020-03-19	617	BROOKLYN Wolfpack	-	MILWAUKEE Admirals	-
67 - 2020-03-21	629	MILWAUKEE Admirals	-	MONT-LAURIER Sommet	-
68 - 2020-03-22	644	MILWAUKEE Admirals	-	HOLLYWOOD Oscar	-
69 - 2020-03-23	653	MILWAUKEE Admirals	-	PV Sharapovas	-
70 - 2020-03-24	665	HERSEY Bears	-	MILWAUKEE Admirals	-
71 - 2020-03-25	679	ROCKFORD IceHogs	-	MILWAUKEE Admirals	-
72 - 2020-03-26	694	MILWAUKEE Admirals	-	Marlies de Toronto	-
73 - 2020-03-27	702	UTICA Comets	-	MILWAUKEE Admirals	-
74 - 2020-03-28	716	MILWAUKEE Admirals	-	UTICA Comets	-
75 - 2020-03-29	728	ROCKFORD IceHogs	-	MILWAUKEE Admirals	-
77 - 2020-03-31	750	MILWAUKEE Admirals	-	Binghampton Devils	-
78 - 2020-04-01	754	Syracruse Crunch	-	MILWAUKEE Admirals	-
79 - 2020-04-02	772	MILWAUKEE Admirals	-	LEHIGH VALLEY Phantoms	-
80 - 2020-04-03	780	Syracruse Crunch	-	MILWAUKEE Admirals	-
82 - 2020-04-05	802	BELLEVILLE Senators	-	MILWAUKEE Admirals	-
84 - 2020-04-07	818	MILWAUKEE Admirals	-	CHICAGO Wolves	-
85 - 2020-04-08	829	Manitoba Moose	-	MILWAUKEE Admirals	-
86 - 2020-04-09	843	MILWAUKEE Admirals	-	HERSEY Bears	-
87 - 2020-04-10	854	PV Sharapovas	-	MILWAUKEE Admirals	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
88 - 2020-04-11	862	MILWAUKEE Admirals	-	COLORADO Eagles	-
90 - 2020-04-13	879	TUSCON Roadrunners	-	MILWAUKEE Admirals	-
91 - 2020-04-14	890	MILWAUKEE Admirals	-	CHICAGO Wolves	-
92 - 2020-04-15	906	SAN DIEGO Gulls	-	MILWAUKEE Admirals	-
93 - 2020-04-16	920	MILWAUKEE Admirals	-	COLORADO Eagles	-
94 - 2020-04-17	930	MILWAUKEE Admirals	-	STOCKTON Flames	-
95 - 2020-04-18	937	BRIDGEPORT Sound Tigers	-	MILWAUKEE Admirals	-
96 - 2020-04-19	947	MILWAUKEE Admirals	-	BROOKLYN Wolfpack	-
97 - 2020-04-20	961	CHICAGO Wolves	-	MILWAUKEE Admirals	-
98 - 2020-04-21	977	MILWAUKEE Admirals	-	LAVAL Rockets	-
99 - 2020-04-22	987	BRIDGEPORT Sound Tigers	-	MILWAUKEE Admirals	-
102 - 2020-04-25	1012	CHICAGO Wolves	-	MILWAUKEE Admirals	-
104 - 2020-04-27	1024	MILWAUKEE Admirals	-	HERSEY Bears	-
106 - 2020-04-29	1040	COLORADO Eagles	-	MILWAUKEE Admirals	-
109 - 2020-05-02	1061	COLORADO Eagles	-	MILWAUKEE Admirals	-

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	0.00%	0.00%
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
41	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
36,622$	1,465,000$	1,422,500$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	24,910$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	109	19,054$	2,076,886$

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
33	2	0	2	0	0	0	0	0	5	12	-7	0	0	0	0	0	0	0	0	0	0	0	2	0	2	0	0	0	0	0	5	12	-7	0	5	10	15	0	0	0	2	3	0	46	8	18	20	0	73	22	18	40	12	1	8.33%	8	3	62.50%	0	19	53	35.85%	32	79	40.51%	16	36	44.44%	40	28	56	13	23	10
Total Saison Régulière	2	0	2	0	0	0	0	0	5	12	-7	0	0	0	0	0	0	0	0	0	0	0	2	0	2	0	0	0	0	0	5	12	-7	0	5	10	15	0	0	0	2	3	0	46	8	18	20	0	73	22	18	40	12	1	8.33%	8	3	62.50%	0	19	53	35.85%	32	79	40.51%	16	36	44.44%	40	28	56	13	23	10
Séries
32	5	1	4	0	0	0	0	0	10	12	-2	3	0	3	0	0	0	0	0	4	8	-4	2	1	1	0	0	0	0	0	6	4	2	2	10	17	27	0	0	5	3	2	0	122	44	34	44	0	153	57	58	96	13	3	23.08%	27	5	81.48%	0	77	163	47.24%	69	171	40.35%	34	66	51.52%	106	69	129	38	64	31
Total Séries	5	1	4	0	0	0	0	0	10	12	-2	3	0	3	0	0	0	0	0	4	8	-4	2	1	1	0	0	0	0	0	6	4	2	2	10	17	27	0	0	5	3	2	0	122	44	34	44	0	153	57	58	96	13	3	23.08%	27	5	81.48%	0	77	163	47.24%	69	171	40.35%	34	66	51.52%	106	69	129	38	64	31