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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	Âge	Contrat	Salaire
1	Max Comtois (R)		X			100.00	86	90	77	78	78	66	67	73	32	66	70	61	75	46	46	70	50	65	0	22	2	925,000$
2	Dominik Simon		X	X		100.00	73	43	93	77	69	67	85	62	37	68	60	56	25	63	64	65	50	63	0	26	3	895,000$
3	Glenn Gawdin	X				100.00	75	71	84	64	71	74	76	66	80	67	61	65	58	44	44	65	50	63	0	24	3	925,000$
4	Joseph Blandisi	X	X			100.00	77	43	85	73	66	51	74	56	53	62	59	71	25	58	58	65	50	62	0	26	2	650,000$
5	Kiefer Sherwood		X	X		100.00	89	45	82	72	66	65	80	58	57	60	55	72	25	50	50	64	50	62	0	26	1	925,000$
6	Logan Brown (C)	X				100.00	67	44	94	62	85	59	69	72	62	75	56	57	25	46	46	63	50	62	0	23	2	1,573,333$
7	Jesper Boqvist (R)		X			100.00	76	43	92	86	63	57	70	66	35	50	60	61	75	47	47	64	50	61	0	22	3	925,000$
8	Zac Dalpe	X		X		100.00	79	73	92	54	73	58	58	61	76	50	65	69	62	58	59	64	50	60	0	31	1	850,000$
9	Valentin Zykov		X	X		100.00	78	45	87	71	80	62	59	64	25	65	58	56	25	48	48	62	50	60	0	26	1	775,000$
10	Carsen Twarynski (R)		X			100.00	92	46	91	66	73	57	75	56	26	50	58	64	25	45	45	62	50	59	0	23	3	775,833$
11	Skyler McKenzie		X			100.00	70	61	90	66	61	71	75	56	50	52	56	60	53	44	44	60	50	58	0	23	3	741,666$
12	Griffen Molino	X	X			100.00	71	63	88	60	63	52	52	54	68	54	47	62	45	51	51	55	50	55	0	27	1	800,000$
13	Cameron Schilling				X	100.00	74	69	86	64	69	72	78	54	25	48	42	64	40	55	55	56	50	61	0	32	1	700,000$
14	Matt Bartkowski				X	100.00	72	72	72	65	72	58	61	52	25	46	40	65	38	64	65	53	50	60	0	33	1	675,000$
15	Mitch Vande Sompel (R)				X	100.00	55	55	55	55	55	55	55	55	55	55	55	55	55	55	55	55	50	54	1	24	3	935,833$
16	Ville Pokka (R)				X	100.00	55	55	55	55	55	55	55	55	55	55	55	55	55	55	55	55	50	54	1	27	3	750,000$
Rayé
1	Max Veronneau			X		100.00	76	67	96	64	67	59	61	53	50	47	53	63	50	45	45	58	50	56	0	25	1	925,000$

	MOYENNE D'ÉQUIPE					100.00	74	58	83	67	69	61	68	60	48	57	56	62	44	51	52	61	50	60

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

#	Nom du Gardien	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
Rayé
1	Colton Point (R)	100.00	45	52	65	88	41	44	50	52	45	46	30	44	44	47	50	51	0

	MOYENNE D'ÉQUIPE	100.00	45	52	65	88	41	44	50	52	45	46	30	44	44	47	50	51

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Mike Van Ryn	50	68	59	66	45	46	56	CAN	40	1	1,340,000$

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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

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#	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	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	HT	P/20	S1	S2	S3
1	Dominik Simon	IceHogs (CHI)	LW/RW	11	5	12	17	7	6	7	7	25	7	20	20.00%	3	221	20.14	1	5	6	8	46	0	0	0	1	23	0	1	75.00%	24	1	1.53	0	3	0
2	Max Comtois	IceHogs (CHI)	LW	11	8	8	16	0	12	34	25	49	11	25	16.33%	3	247	22.51	4	2	6	18	43	1	0	1	2	36	1	0	49.38%	81	1	1.29	2	0	0
3	Jesper Boqvist	IceHogs (CHI)	LW	11	5	10	15	5	4	9	12	29	9	19	17.24%	1	170	15.53	0	1	1	2	10	0	1	1	0	10	1	1	62.50%	8	1	1.76	1	0	0
4	Joseph Blandisi	IceHogs (CHI)	C/LW	11	5	9	14	1	6	8	23	28	9	13	17.86%	5	186	16.93	0	1	1	2	13	0	0	0	0	18	0	0	65.74%	108	0	1.50	1	0	0
5	Glenn Gawdin	IceHogs (CHI)	C	11	6	7	13	4	10	11	22	25	9	19	24.00%	5	239	21.80	0	2	2	3	48	0	0	0	1	40	0	0	70.79%	202	1	1.08	0	0	1
6	Valentin Zykov	IceHogs (CHI)	LW/RW	11	2	9	11	-3	2	9	19	25	3	15	8.00%	2	193	17.60	0	1	1	6	37	0	0	0	0	0	0	0	50.00%	6	0	1.14	0	1	1
7	Kiefer Sherwood	IceHogs (CHI)	LW/RW	11	6	4	10	1	10	16	5	24	8	24	25.00%	3	197	17.94	1	0	1	6	39	0	0	0	1	3	2	0	62.50%	8	1	1.01	2	0	0
8	Logan Brown	IceHogs (CHI)	C	11	5	5	10	2	0	4	16	28	5	21	17.86%	2	216	19.65	1	1	2	4	36	0	0	0	1	25	0	0	68.29%	164	0	0.93	0	1	2
9	Matt Bartkowski	IceHogs (CHI)	D	11	1	8	9	5	14	20	10	11	3	12	9.09%	6	235	21.38	1	2	3	5	44	0	1	1	0	31	0	0	0.00%	0	0	0.77	0	0	0
10	Zac Dalpe	IceHogs (CHI)	C/RW	11	5	3	8	8	0	11	11	23	13	13	21.74%	4	185	16.89	1	0	1	4	13	0	0	0	1	26	0	0	77.78%	27	0	0.86	0	2	0
11	Ville Pokka	IceHogs (CHI)	D	11	0	5	5	7	10	20	5	4	2	5	0.00%	11	220	20.02	0	0	0	4	37	0	0	0	0	35	0	0	0.00%	0	0	0.45	0	0	0
12	Mitch Vande Sompel	IceHogs (CHI)	D	11	1	3	4	5	6	18	3	4	2	3	25.00%	8	219	19.93	0	0	0	2	36	0	0	0	0	35	0	0	0.00%	0	0	0.36	0	0	0
13	Griffen Molino	IceHogs (CHI)	C/LW	11	2	1	3	-5	2	1	7	9	2	3	22.22%	1	55	5.00	0	1	1	0	1	0	0	0	1	0	0	1	66.67%	33	0	1.09	0	0	0
14	Carsen Twarynski	IceHogs (CHI)	LW	11	0	3	3	-9	18	28	3	3	1	2	0.00%	4	170	15.48	0	0	0	0	1	0	0	0	0	0	0	0	50.00%	2	0	0.35	0	0	0
15	Cameron Schilling	IceHogs (CHI)	D	11	0	3	3	5	6	17	6	8	7	5	0.00%	8	251	22.86	0	1	1	5	46	0	0	0	0	39	0	0	0.00%	0	0	0.24	0	0	0
16	Skyler McKenzie	IceHogs (CHI)	LW	11	1	1	2	-7	0	4	3	3	0	0	33.33%	9	169	15.37	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.24	0	0	0
Stats d'équipe Total ou en Moyenne				176	52	91	143	26	106	217	177	298	91	199	17.45%	75	3179	18.06	9	17	26	69	457	1	2	3	8	326	4	3	66.52%	663	5	0.90	6	7	4

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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	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
Stats d'équipe Total ou en Moyenne							0.000	0.00	0								0.000

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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	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Link
Cameron Schilling	IceHogs (CHI)	D	32	1988-10-07	No	182 Lbs	6 ft2	No	No	No	1	Pro & Farm	700,000$	0$	0$	No			Lien / Lien NHL
Carsen Twarynski	IceHogs (CHI)	LW	23	1997-11-24	Yes	198 Lbs	6 ft2	No	No	No	3	Pro & Farm	775,833$	0$	0$	No	775,833$	775,833$	Lien / Lien NHL
Colton Point	IceHogs (CHI)	G	23	1998-03-04	Yes	220 Lbs	6 ft4	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$	Lien / Lien NHL
Dominik Simon	IceHogs (CHI)	LW/RW	26	1994-08-08	No	190 Lbs	5 ft11	No	No	No	3	Pro & Farm	895,000$	0$	0$	No	895,000$	895,000$	Lien / Lien NHL
Glenn Gawdin	IceHogs (CHI)	C	24	1997-03-25	No	191 Lbs	6 ft1	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$	Lien / Lien NHL
Griffen Molino	IceHogs (CHI)	C/LW	27	1994-01-21	No	171 Lbs	5 ft11	No	No	No	1	Pro & Farm	800,000$	0$	0$	No			Lien / Lien NHL
Jesper Boqvist	IceHogs (CHI)	LW	22	1998-10-30	Yes	174 Lbs	5 ft11	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$	Lien / Lien NHL
Joseph Blandisi	IceHogs (CHI)	C/LW	26	1994-07-18	No	182 Lbs	5 ft11	No	No	No	2	Pro & Farm	650,000$	0$	0$	No	650,000$		Lien / Lien NHL
Kiefer Sherwood	IceHogs (CHI)	LW/RW	26	1995-03-31	No	180 Lbs	5 ft11	No	No	No	1	Pro & Farm	925,000$	0$	0$	No			Lien / Lien NHL
Logan Brown	IceHogs (CHI)	C	23	1998-03-04	No	220 Lbs	6 ft6	No	No	No	2	Pro & Farm	1,573,333$	0$	0$	No	1,573,333$		Lien / Lien NHL
Matt Bartkowski	IceHogs (CHI)	D	33	1988-06-04	No	196 Lbs	6 ft1	No	No	No	1	Pro & Farm	675,000$	0$	0$	No			Lien / Lien NHL
Max Comtois	IceHogs (CHI)	LW	22	1999-01-08	Yes	207 Lbs	6 ft2	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$		Lien / Lien NHL
Max Veronneau	IceHogs (CHI)	RW	25	1995-12-11	No	181 Lbs	6 ft0	No	No	No	1	Pro & Farm	925,000$	0$	0$	No			Lien / Lien NHL
Mitch Vande Sompel	IceHogs (CHI)	D	24	1997-02-11 10:37:52 AM	Yes	198 Lbs	5 ft11	No	No	No	3	Pro & Farm	935,833$	0$	0$	No	935,833$	935,833$
Skyler McKenzie	IceHogs (CHI)	LW	23	1998-01-20	No	170 Lbs	5 ft9	No	No	No	3	Pro & Farm	741,666$	0$	0$	No	741,666$	741,666$	Lien / Lien NHL
Valentin Zykov	IceHogs (CHI)	LW/RW	26	1995-05-14	No	224 Lbs	6 ft1	No	No	No	1	Pro & Farm	775,000$	0$	0$	No			Lien / Lien NHL
Ville Pokka	IceHogs (CHI)	D	27	1994-06-03 10:45:39 AM	Yes	214 Lbs	6 ft0	No	No	No	3	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$
Zac Dalpe	IceHogs (CHI)	C/RW	31	1989-10-31	No	199 Lbs	6 ft2	No	No	No	1	Pro & Farm	850,000$	0$	0$	No			Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
18	25.72	194 Lbs	6 ft1	2.06	870,648$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Max Comtois	Glenn Gawdin	Dominik Simon	40	1	2	2
2	Kiefer Sherwood	Logan Brown	Valentin Zykov	30	1	2	2
3	Jesper Boqvist	Joseph Blandisi	Zac Dalpe	20	1	2	2
4	Carsen Twarynski	Griffen Molino	Max Comtois	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Cameron Schilling	Matt Bartkowski	40	1	2	2
2	Ville Pokka	Mitch Vande Sompel	30	1	2	2
3	Carsen Twarynski	Skyler McKenzie	20	1	2	2
4	Cameron Schilling	Matt Bartkowski	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Max Comtois	Glenn Gawdin	Dominik Simon	60	1	2	2
2	Kiefer Sherwood	Logan Brown	Valentin Zykov	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Cameron Schilling	Matt Bartkowski	60	1	2	2
2	Ville Pokka	Mitch Vande Sompel	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Max Comtois	Glenn Gawdin	60	1	2	2
2	Dominik Simon	Logan Brown	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Cameron Schilling	Matt Bartkowski	60	1	2	2
2	Ville Pokka	Mitch Vande Sompel	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Max Comtois	60	1	2	2	Cameron Schilling	Matt Bartkowski	60	1	2	2
2	Glenn Gawdin	40	1	2	2	Ville Pokka	Mitch Vande Sompel	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Max Comtois	Glenn Gawdin	60	1	2	2
2	Dominik Simon	Logan Brown	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Cameron Schilling	Matt Bartkowski	60	1	2	2
2	Ville Pokka	Mitch Vande Sompel	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Max Comtois	Glenn Gawdin	Dominik Simon	Cameron Schilling	Matt Bartkowski

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Max Comtois	Glenn Gawdin	Dominik Simon	Cameron Schilling	Matt Bartkowski

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Joseph Blandisi, Jesper Boqvist, Zac Dalpe	Joseph Blandisi, Jesper Boqvist	Zac Dalpe

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Ville Pokka, Mitch Vande Sompel, Cameron Schilling	Ville Pokka	Mitch Vande Sompel, Cameron Schilling

Tirs de Pénalité
Max Comtois, Glenn Gawdin, Dominik Simon, Logan Brown, Kiefer Sherwood

Gardien
#1 : , #2 :

Lignes d'Attaque Perso. en Prol.
Max Comtois, Glenn Gawdin, Dominik Simon, Logan Brown, Kiefer Sherwood, Joseph Blandisi, Joseph Blandisi, Jesper Boqvist, Valentin Zykov, Zac Dalpe, Carsen Twarynski

Lignes de Défense Perso. en Prol.
Cameron Schilling, Matt Bartkowski, Ville Pokka, Mitch Vande Sompel,

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	Barracudas	7	4	3	0	0	0	0	0	44	33	11	4	3	1	0	0	0	0	0	28	16	12	3	1	2	0	0	0	0	0	16	17	-1	8	0.571	44	78	122	0	0	21	16	15	0	216	115	88	95	0	159	63	70	141	26	7	26.92%	31	7	77.42%	1	194	282	68.79%	122	188	64.89%	125	195	64.10%	316	240	226	67	122	66
2	Condors	4	0	4	0	0	0	0	0	8	15	-7	2	0	2	0	0	0	0	0	4	8	-4	2	0	2	0	0	0	0	0	4	7	-3	0	0.000	8	13	21	0	0	21	16	15	0	82	115	88	95	0	57	12	36	77	29	2	6.90%	17	4	76.47%	0	194	282	68.79%	122	188	64.89%	125	195	64.10%	316	240	226	67	122	66
	Total	11	4	7	0	0	0	0	0	52	48	4	6	3	3	0	0	0	0	0	32	24	8	5	1	4	0	0	0	0	0	20	24	-4	8	0.364	52	91	143	0	0	21	16	15	0	298	115	88	95	0	216	75	106	218	55	9	16.36%	48	11	77.08%	1	194	282	68.79%	122	188	64.89%	125	195	64.10%	316	240	226	67	122	66
	_Since Last GM Reset	11	4	7	0	0	0	0	0	52	48	4	6	3	3	0	0	0	0	0	32	24	8	5	1	4	0	0	0	0	0	20	24	-4	8	0.364	52	91	143	0	0	21	16	15	0	298	115	88	95	0	216	75	106	218	55	9	16.36%	48	11	77.08%	1	194	282	68.79%	122	188	64.89%	125	195	64.10%	316	240	226	67	122	66
	_Vs Conference	11	4	7	0	0	0	0	0	52	48	4	6	3	3	0	0	0	0	0	32	24	8	5	1	4	0	0	0	0	0	20	24	-4	8	0.364	52	91	143	0	0	21	16	15	0	298	115	88	95	0	216	75	106	218	55	9	16.36%	48	11	77.08%	1	194	282	68.79%	122	188	64.89%	125	195	64.10%	316	240	226	67	122	66

			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
11	8	L1	52	91	143	298	216	75	106	218	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
11	4	7	0	0	0	0	52	48

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
6	3	3	0	0	0	0	32	24

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	1	4	0	0	0	0	20	24

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
55	9	16.36%	48	11	77.08%	1

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
115	88	95	0	21	16	15	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
194	282	68.79%	122	188	64.89%	125	195	64.10%

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
316	240	226	67	122	66

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	Lien
2 - 2020-10-25	7	Barracudas	5	IceHogs	4	L	X	Sommaire du Match
4 - 2020-10-27	15	Barracudas	4	IceHogs	7	W		Sommaire du Match
6 - 2020-10-29	23	IceHogs	2	Barracudas	4	L		Sommaire du Match
8 - 2020-10-31	31	IceHogs	8	Barracudas	6	W		Sommaire du Match
10 - 2020-11-02	39	Barracudas	3	IceHogs	5	W		Sommaire du Match
12 - 2020-11-04	47	IceHogs	6	Barracudas	7	L		Sommaire du Match
14 - 2020-11-06	55	Barracudas	4	IceHogs	12	W		Sommaire du Match
16 - 2020-11-08	60	IceHogs	2	Condors	4	L		Sommaire du Match
18 - 2020-11-10	64	IceHogs	2	Condors	3	L		Sommaire du Match
20 - 2020-11-12	68	Condors	4	IceHogs	3	L	X	Sommaire du Match
22 - 2020-11-14	72	Condors	4	IceHogs	1	L		Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité	2000	1000
Prix des Billets	50	0
Assistance	12,000	5,977
Assistance PCT	100.00%	99.62%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité	Popularité de l'Équipe
35	2996 - 99.87%	100,000$	600,000$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
0$	1,567,166$	1,556,666$	0$

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

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	0	0$	0$

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
2020	82	59	16	0	2	2	1	2	371	128	243	41	31	8	0	0	1	1	0	200	59	141	41	28	8	0	2	1	0	2	171	69	102	128	371	659	1030	0	24	155	126	87	5	2614	853	898	850	24	1385	394	742	1534	344	58	16.86%	330	28	91.52%	4	1507	2368	63.64%	1018	1836	55.45%	788	1202	65.56%	2547	1962	1481	472	912	518
Total Saison Régulière	82	59	16	0	2	2	1	2	371	128	243	41	31	8	0	0	1	1	0	200	59	141	41	28	8	0	2	1	0	2	171	69	102	128	371	659	1030	0	24	155	126	87	5	2614	853	898	850	24	1385	394	742	1534	344	58	16.86%	330	28	91.52%	4	1507	2368	63.64%	1018	1836	55.45%	788	1202	65.56%	2547	1962	1481	472	912	518
2020	11	4	7	0	0	0	0	0	52	48	4	6	3	3	0	0	0	0	0	32	24	8	5	1	4	0	0	0	0	0	20	24	-4	8	52	91	143	0	0	21	16	15	0	298	115	88	95	0	216	75	106	218	55	9	16.36%	48	11	77.08%	1	194	282	68.79%	122	188	64.89%	125	195	64.10%	316	240	226	67	122	66
Total Séries	11	4	7	0	0	0	0	0	52	48	4	6	3	3	0	0	0	0	0	32	24	8	5	1	4	0	0	0	0	0	20	24	-4	8	52	91	143	0	0	21	16	15	0	298	115	88	95	0	216	75	106	218	55	9	16.36%	48	11	77.08%	1	194	282	68.79%	122	188	64.89%	125	195	64.10%	316	240	226	67	122	66

	IceHogs
	GP: 11 \| W: 4 \| L: 7 GF: 52 \| GA: 48 \| PP%: 16.36% \| PK%: 77.08% DG: Mark \| Morale : 50 \| Moyenne d'Équipe : 59