Stanley Cup Winners Hockey League

CAROLINA Huricanes
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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	Âge	Contrat	Salaire
1	Devante Smith-Pelly	0			X		100.00	68	41	74	66	79	69	87	65	60	62	62	68	64	66	55	63	99	68	0	28	1	1,000,000$
2	Stefan Matteau	0	X	X			100.00	72	51	85	60	84	79	73	61	67	59	60	63	61	71	66	75	99	67	0	26	1	750,000$
3	Ryan Poehling	0	X				100.00	71	42	89	63	81	74	72	62	76	59	58	64	59	61	64	82	99	66	0	21	1	750,000$
4	Kalle Kossila (R)	0	X	X			100.00	57	39	83	61	69	76	73	62	72	60	60	63	61	73	67	58	99	65	0	27	4	750,000$
5	Gabriel Fontaine	0	X				100.00	64	43	87	58	78	79	81	57	53	56	54	59	60	65	63	62	99	65	0	23	3	750,000$
6	Bokondji Imama (R)	0		X			100.00	70	67	65	56	82	80	79	55	51	53	54	57	53	67	64	61	99	64	0	24	4	750,000$
7	Patrick Russell (R)	0			X		100.00	68	39	82	55	78	69	66	53	51	54	50	62	55	73	67	38	99	62	0	27	3	750,000$
8	Maxime Fortier (R)	0			X		100.00	53	39	87	57	58	78	77	55	52	53	53	54	57	65	63	64	99	61	0	22	4	750,000$
9	Tobias Lindberg	0		X	X		100.00	61	89	66	62	86	48	50	62	50	53	53	50	53	50	50	60	99	57	0	25	1	750,000$
10	Mason Geertsen (R)	0				X	100.00	73	73	67	55	89	86	87	56	30	54	52	59	45	69	65	58	99	66	0	25	4	750,000$
11	Noah Dobson (R)	0				X	100.00	58	42	87	68	83	74	61	66	30	69	54	62	51	60	63	87	99	66	0	20	3	750,000$
12	Colton White	0				X	100.00	63	43	87	62	74	81	78	61	30	59	57	58	53	65	63	62	99	65	0	23	1	750,000$
13	David Quenneville (R)	0				X	100.00	53	41	87	56	66	73	72	54	30	55	52	53	45	63	62	64	99	60	0	22	4	775,000$
14	Jake Chelios	0				X	100.00	52	35	68	61	77	48	52	61	30	46	42	56	52	50	50	36	99	54	0	29	1	750,000$
15	Griffin Reinhart	0				X	100.00	62	89	67	59	89	45	50	59	30	47	42	50	52	51	50	86	99	54	0	26	2	750,000$
Rayé

	MOYENNE D'ÉQUIPE					100.00	63	52	79	60	78	71	71	59	47	56	54	59	55	63	61	64	99	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
Rayé

	MOYENNE D'ÉQUIPE	0.00	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Adam Oates	62	62	62	62	76	76	54	CAN	59	2	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	PKM	FO%	FOT	GA	TA	P/20	FL	S3
1	Devante Smith-Pelly	CAROLINA Checkers (CAR)	RW	3	5	2	7	0	2	0	4	10	16	5	10	31.25%	5	63	21.12	1	1	2	5	9	2	48.48%	33	1	1	2.21	0	0
2	Ryan Poehling	CAROLINA Checkers (CAR)	C	3	2	5	7	0	0	0	2	4	11	7	16	18.18%	5	67	22.54	1	1	2	1	9	3	55.41%	74	1	0	2.07	0	1
3	Jake Chelios	CAROLINA Checkers (CAR)	D	3	0	2	2	-10	4	0	7	4	10	8	3	0.00%	13	65	21.78	0	2	2	7	9	2	0.00%	0	2	2	0.61	0	0
4	Gabriel Fontaine	CAROLINA Checkers (CAR)	C	3	2	0	2	-11	0	0	8	10	13	6	13	15.38%	8	75	25.29	2	0	2	5	11	2	49.02%	51	2	2	0.53	0	0
5	Tobias Lindberg	CAROLINA Checkers (CAR)	LW/RW	3	0	1	1	-7	7	5	10	6	8	2	6	0.00%	2	64	21.57	0	0	0	0	5	1	25.93%	27	2	0	0.31	1	0
6	Griffin Reinhart	CAROLINA Checkers (CAR)	D	3	0	0	0	-4	2	0	7	7	2	3	3	0.00%	7	69	23.04	0	0	0	0	6	3	0.00%	0	0	1	0.00	0	0
7	Colton White	CAROLINA Checkers (CAR)	D	3	0	0	0	-7	0	0	2	5	5	1	5	0.00%	16	78	26.32	0	0	0	3	7	3	0.00%	0	1	3	0.00	0	0
Stats d'équipe Total ou en Moyenne				21	9	10	19	-39	15	5	40	46	65	32	56	13.85%	56	485	23.10	4	4	8	21	59	19	48.11%	185	9	9	0.78	1	1

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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	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
Bokondji Imama	CAROLINA Checkers (CAR)	LW	24	8/3/1996	Yes	100 Kg	185 CM	No	No	No	4	Pro & Farm	750,000$	724,576$	750,000$	724,576$	0$	0$	No	750,000$	750,000$	750,000$
Colton White	CAROLINA Checkers (CAR)	D	23	5/3/1997	No	84 Kg	185 CM	No	No	No	1	Pro & Farm	750,000$	724,576$	750,000$	724,576$	0$	0$	No				Lien
David Quenneville	CAROLINA Checkers (CAR)	D	22	3/13/1998	Yes	86 Kg	173 CM	No	No	No	4	Pro & Farm	775,000$	748,729$	750,000$	724,576$	0$	0$	No	775,000$	775,000$	775,000$
Devante Smith-Pelly	CAROLINA Checkers (CAR)	RW	28	6/14/1992	No	101 Kg	183 CM	No	No	No	1	Pro & Farm	1,000,000$	966,102$	1,000,000$	966,102$	0$	0$	No				Lien
Gabriel Fontaine	CAROLINA Checkers (CAR)	C	23	4/30/1997	No	91 Kg	185 CM	No	No	No	3	Pro & Farm	750,000$	724,576$	750,000$	724,576$	0$	0$	No	750,000$	750,000$		Lien
Griffin Reinhart	CAROLINA Checkers (CAR)	D	26	1/24/1994	No	96 Kg	193 CM	No	No	No	2	Pro & Farm	750,000$	724,576$	750,000$	724,576$	0$	0$	No	750,000$			Lien
Jake Chelios	CAROLINA Checkers (CAR)	D	29	3/8/1991	No	84 Kg	188 CM	No	No	No	1	Pro & Farm	750,000$	724,576$	750,000$	724,576$	0$	0$	No				Lien
Kalle Kossila	CAROLINA Checkers (CAR)	C/LW	27	4/14/1993	Yes	83 Kg	180 CM	No	No	No	4	Pro & Farm	750,000$	724,576$	750,000$	724,576$	0$	0$	No	750,000$	750,000$	750,000$
Mason Geertsen	CAROLINA Checkers (CAR)	D	25	4/19/1995	Yes	96 Kg	193 CM	No	No	No	4	Pro & Farm	750,000$	724,576$	750,000$	724,576$	0$	0$	No	750,000$	750,000$	750,000$
Maxime Fortier	CAROLINA Checkers (CAR)	RW	22	12/15/1997	Yes	83 Kg	155 CM	No	No	No	4	Pro & Farm	750,000$	724,576$	750,000$	724,576$	0$	0$	No	750,000$	750,000$	750,000$
Noah Dobson	CAROLINA Checkers (CAR)	D	20	1/7/2000	Yes	84 Kg	193 CM	No	No	No	3	Pro & Farm	750,000$	724,576$	750,000$	724,576$	0$	0$	No	750,000$	750,000$
Patrick Russell	CAROLINA Checkers (CAR)	RW	27	1/4/1993	Yes	92 Kg	185 CM	No	No	No	3	Pro & Farm	750,000$	724,576$	750,000$	724,576$	0$	0$	No	750,000$	750,000$
Ryan Poehling	CAROLINA Checkers (CAR)	C	21	1/3/1999	No	93 Kg	188 CM	No	No	No	1	Pro & Farm	750,000$	724,576$	750,000$	724,576$	0$	0$	No				Lien
Stefan Matteau	CAROLINA Checkers (CAR)	C/LW	26	2/23/1994	No	100 Kg	188 CM	No	No	No	1	Pro & Farm	750,000$	724,576$	650,000$	627,966$	0$	0$	No				Lien
Tobias Lindberg	CAROLINA Checkers (CAR)	LW/RW	25	7/22/1995	No	98 Kg	191 CM	No	No	No	1	Pro & Farm	750,000$	724,576$	750,000$	724,576$	0$	0$	No				Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
15	24.53	91 Kg	185 CM	2.47	768,333$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Tobias Lindberg	Ryan Poehling	Devante Smith-Pelly	31	1	2	2
2		Gabriel Fontaine		26	1	2	2
3	Ryan Poehling	Devante Smith-Pelly	Gabriel Fontaine	23	1	2	2
4		Tobias Lindberg		20	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Colton White	Griffin Reinhart	31	1	2	2
2	Jake Chelios		26	1	2	2
3	Colton White	Griffin Reinhart	23	1	2	2
4	Jake Chelios		20	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Tobias Lindberg	Ryan Poehling	Devante Smith-Pelly	55	1	2	2
2		Gabriel Fontaine		45	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Colton White	Griffin Reinhart	55	1	2	2
2	Jake Chelios		45	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Devante Smith-Pelly	Ryan Poehling	55	1	2	2
2	Gabriel Fontaine	Tobias Lindberg	45	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Colton White	Griffin Reinhart	55	1	2	2
2	Jake Chelios		45	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Devante Smith-Pelly	55	1	2	2	Colton White	Griffin Reinhart	55	1	2	2
2	Ryan Poehling	45	1	2	2	Jake Chelios		45	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Devante Smith-Pelly	Ryan Poehling	55	1	2	2
2	Gabriel Fontaine	Tobias Lindberg	45	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Colton White	Griffin Reinhart	55	1	2	2
2	Jake Chelios		45	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Tobias Lindberg	Ryan Poehling	Devante Smith-Pelly	Colton White	Griffin Reinhart

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Tobias Lindberg	Ryan Poehling	Devante Smith-Pelly	Colton White	Griffin Reinhart

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Gabriel Fontaine, Tobias Lindberg, Devante Smith-Pelly	Gabriel Fontaine, Tobias Lindberg	Devante Smith-Pelly

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Colton White, Griffin Reinhart, Jake Chelios	Colton White	Griffin Reinhart, Jake Chelios

Tirs de Pénalité
Devante Smith-Pelly, Ryan Poehling, Gabriel Fontaine, Tobias Lindberg,

Gardien
#1 : , #2 :

Lignes d'Attaque Perso. en Prol.
Devante Smith-Pelly, Ryan Poehling, Gabriel Fontaine, Tobias Lindberg, , , , , , ,

Lignes de Défense Perso. en Prol.
Colton White, Griffin Reinhart, Jake Chelios, ,

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	1	0	0	0	0	0	6	9	-3	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	6	9	-3	0	0.000	6	7	13	0	0	3	4	2	0	26	17	30	26	0	53	27	0	13	5	3	60.00%	0	0	0.00%	0	34	69	49.28%	24	60	40.00%	31	69	44.93%	52	33	89	23	37	17
2	GRAND RAPIDS Griffins	1	0	1	0	0	0	0	0	2	12	-10	1	0	1	0	0	0	0	0	2	12	-10	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	2	4	0	0	3	4	2	0	32	17	30	26	0	56	14	21	27	5	1	20.00%	8	6	25.00%	0	34	69	49.28%	24	60	40.00%	31	69	44.93%	52	33	89	23	37	17
	Total	3	0	3	0	0	0	0	0	9	32	-23	1	0	1	0	0	0	0	0	2	12	-10	2	0	2	0	0	0	0	0	7	20	-13	0	0.000	9	10	19	0	0	3	4	2	0	73	17	30	26	0	179	63	21	49	14	4	28.57%	8	6	25.00%	0	34	69	49.28%	24	60	40.00%	31	69	44.93%	52	33	89	23	37	17
3	UTICA Comets	1	0	1	0	0	0	0	0	1	11	-10	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	11	-10	0	0.000	1	1	2	0	0	3	4	2	0	15	17	30	26	0	70	22	0	9	4	0	0.00%	0	0	0.00%	0	34	69	49.28%	24	60	40.00%	31	69	44.93%	52	33	89	23	37	17
	_Since Last GM Reset	3	0	3	0	0	0	0	0	9	32	-23	1	0	1	0	0	0	0	0	2	12	-10	2	0	2	0	0	0	0	0	7	20	-13	0	0.000	9	10	19	0	0	3	4	2	0	73	17	30	26	0	179	63	21	49	14	4	28.57%	8	6	25.00%	0	34	69	49.28%	24	60	40.00%	31	69	44.93%	52	33	89	23	37	17
	_Vs Conference	2	0	2	0	0	0	0	0	8	21	-13	1	0	1	0	0	0	0	0	2	12	-10	1	0	1	0	0	0	0	0	6	9	-3	0	0.000	8	9	17	0	0	3	4	2	0	58	17	30	26	0	109	41	21	40	10	4	40.00%	8	6	25.00%	0	34	69	49.28%	24	60	40.00%	31	69	44.93%	52	33	89	23	37	17

			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
3	0	L3	9	10	19	73	179	63	21	49	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	0	3	0	0	0	0	9	32

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
1	0	1	0	0	0	0	2	12

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	0	2	0	0	0	0	7	20

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
0	3	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
14	4	28.57%	8	6	25.00%	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
17	30	26	0	3	4	2	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
34	69	49.28%	24	60	40.00%	31	69	44.93%

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
52	33	89	23	37	17

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	RI	Lien
1 - 2021-01-17	1	GRAND RAPIDS Griffins	12	CAROLINA Checkers	2	L	R3	Sommaire du Match
2 - 2021-01-18	19	CAROLINA Checkers	6	BELLEVILLE Senators	9	L		Sommaire du Match
4 - 2021-01-20	31	CAROLINA Checkers	1	UTICA Comets	11	L		Sommaire du Match
5 - 2021-01-21	40	CAROLINA Checkers	-	BINGHAMTON Devils	-
6 - 2021-01-22	49	GRAND RAPIDS Griffins	-	CAROLINA Checkers	-
7 - 2021-01-23	66	BROOKLYN Wolfpack	-	CAROLINA Checkers	-
8 - 2021-01-24	76	CAROLINA Checkers	-	SAN ANTONIO Rampage	-
11 - 2021-01-27	95	SCRANTON Penguins	-	CAROLINA Checkers	-
12 - 2021-01-28	102	CAROLINA Checkers	-	MANITOBA Moose	-
14 - 2021-01-30	122	SYRACUSE Crunch	-	CAROLINA Checkers	-
15 - 2021-01-31	132	CAROLINA Checkers	-	BELLEVILLE Senators	-
17 - 2021-02-02	143	GRAND RAPIDS Griffins	-	CAROLINA Checkers	-
19 - 2021-02-04	162	ONTARIO Reign	-	CAROLINA Checkers	-
20 - 2021-02-05	170	CAROLINA Checkers	-	SAN ANTONIO Rampage	-
21 - 2021-02-06	187	MANITOBA Moose	-	CAROLINA Checkers	-
22 - 2021-02-07	192	CAROLINA Checkers	-	SCRANTON Penguins	-
24 - 2021-02-09	211	CAROLINA Checkers	-	LEHIGH VALLEY Phantoms	-
26 - 2021-02-11	224	LAVAL Rocket	-	CAROLINA Checkers	-
27 - 2021-02-12	236	CAROLINA Checkers	-	TORONTO Marlies	-
28 - 2021-02-13	246	SYRACUSE Crunch	-	CAROLINA Checkers	-
30 - 2021-02-15	265	CAROLINA Checkers	-	IOWA Wild	-
31 - 2021-02-16	273	CAROLINA Checkers	-	STOCKTON Flames	-
32 - 2021-02-17	284	UTICA Comets	-	CAROLINA Checkers	-
34 - 2021-02-19	300	COLORADO Eagles	-	CAROLINA Checkers	-
35 - 2021-02-20	315	CAROLINA Checkers	-	ROCKFORD IceHogs	-
37 - 2021-02-22	326	MILWAUKEE Admirals	-	CAROLINA Checkers	-
38 - 2021-02-23	337	CAROLINA Checkers	-	TUSCON Roadrunners	-
40 - 2021-02-25	355	CAROLINA Checkers	-	SYRACUSE Crunch	-
41 - 2021-02-26	362	SAN DIEGO Gulls	-	CAROLINA Checkers	-
43 - 2021-02-28	379	LEHIGH VALLEY Phantoms	-	CAROLINA Checkers	-
44 - 2021-03-01	388	CAROLINA Checkers	-	BROOKLYN Wolfpack	-
46 - 2021-03-03	407	HERSEY Bears	-	CAROLINA Checkers	-
47 - 2021-03-04	419	CAROLINA Checkers	-	LEHIGH VALLEY Phantoms	-
48 - 2021-03-05	430	SAN ANTONIO Rampage	-	CAROLINA Checkers	-
50 - 2021-03-07	441	CAROLINA Checkers	-	GRAND RAPIDS Griffins	-
51 - 2021-03-08	457	CAROLINA Checkers	-	GRAND RAPIDS Griffins	-
52 - 2021-03-09	467	BRIDGEPORT Sound Tigers	-	CAROLINA Checkers	-
54 - 2021-03-11	484	MANITOBA Moose	-	CAROLINA Checkers	-
55 - 2021-03-12	499	CAROLINA Checkers	-	SAN ANTONIO Rampage	-
56 - 2021-03-13	505	CAROLINA Checkers	-	STOCKTON Flames	-
57 - 2021-03-14	518	ONTARIO Reign	-	CAROLINA Checkers	-
59 - 2021-03-16	536	CAROLINA Checkers	-	LAVAL Rocket	-
60 - 2021-03-17	542	UTICA Comets	-	CAROLINA Checkers	-
62 - 2021-03-19	562	TORONTO Marlies	-	CAROLINA Checkers	-
64 - 2021-03-21	574	CAROLINA Checkers	-	COLORADO Eagles	-
65 - 2021-03-22	586	BROOKLYN Wolfpack	-	CAROLINA Checkers	-
67 - 2021-03-24	603	CAROLINA Checkers	-	BRIDGEPORT Sound Tigers	-
68 - 2021-03-25	614	GRAND RAPIDS Griffins	-	CAROLINA Checkers	-
69 - 2021-03-26	628	CAROLINA Checkers	-	MILWAUKEE Admirals	-
70 - 2021-03-27	633	CAROLINA Checkers	-	SAN DIEGO Gulls	-
72 - 2021-03-29	647	BAKERSFIELD Condors	-	CAROLINA Checkers	-
73 - 2021-03-30	665	IOWA Wild	-	CAROLINA Checkers	-
75 - 2021-04-01	677	CAROLINA Checkers	-	UTICA Comets	-
76 - 2021-04-02	686	CAROLINA Checkers	-	BAKERSFIELD Condors	-
78 - 2021-04-04	697	CHICAGO Wolves	-	CAROLINA Checkers	-
80 - 2021-04-06	717	TUSCON Roadrunners	-	CAROLINA Checkers	-
81 - 2021-04-07	728	CAROLINA Checkers	-	BINGHAMTON Devils	-
82 - 2021-04-08	738	CAROLINA Checkers	-	UTICA Comets	-
84 - 2021-04-10	752	SCRANTON Penguins	-	CAROLINA Checkers	-
85 - 2021-04-11	762	CAROLINA Checkers	-	BINGHAMTON Devils	-
87 - 2021-04-13	775	HERSEY Bears	-	CAROLINA Checkers	-
88 - 2021-04-14	789	CAROLINA Checkers	-	BELLEVILLE Senators	-
89 - 2021-04-15	802	BELLEVILLE Senators	-	CAROLINA Checkers	-
92 - 2021-04-18	820	ROCKFORD IceHogs	-	CAROLINA Checkers	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
93 - 2021-04-19	833	CAROLINA Checkers	-	CHICAGO Wolves	-
94 - 2021-04-20	840	CAROLINA Checkers	-	PROVIDENCE Bruins	-
96 - 2021-04-22	857	BELLEVILLE Senators	-	CAROLINA Checkers	-
97 - 2021-04-23	873	PROVIDENCE Bruins	-	CAROLINA Checkers	-
99 - 2021-04-25	891	BAKERSFIELD Condors	-	CAROLINA Checkers	-
101 - 2021-04-27	903	CAROLINA Checkers	-	ONTARIO Reign	-
102 - 2021-04-28	917	BINGHAMTON Devils	-	CAROLINA Checkers	-
103 - 2021-04-29	927	CAROLINA Checkers	-	HERSEY Bears	-
104 - 2021-04-30	937	CAROLINA Checkers	-	CHICAGO Wolves	-
106 - 2021-05-02	950	BINGHAMTON Devils	-	CAROLINA Checkers	-
108 - 2021-05-04	970	CAROLINA Checkers	-	SCRANTON Penguins	-
109 - 2021-05-05	974	CAROLINA Checkers	-	MANITOBA Moose	-
110 - 2021-05-06	984	IOWA Wild	-	CAROLINA Checkers	-
112 - 2021-05-08	1003	CAROLINA Checkers	-	MANITOBA Moose	-
113 - 2021-05-09	1011	SCRANTON Penguins	-	CAROLINA Checkers	-
116 - 2021-05-12	1030	STOCKTON Flames	-	CAROLINA Checkers	-

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
39	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
39,068$	1,152,500$	1,140,000$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	39,068$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	114	9,767$	1,113,438$

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
34	80	11	56	0	3	3	3	4	175	351	-176	40	7	28	0	2	1	1	1	82	167	-85	40	4	28	0	1	2	2	3	93	184	-91	41	175	271	446	1	2	72	43	54	9	1903	623	608	633	69	3152	966	332	1035	224	42	18.75%	131	22	83.21%	1	1015	2079	48.82%	1241	2631	47.17%	667	1269	52.56%	1629	1144	2297	541	925	433
34	80	11	56	0	3	3	3	4	175	351	-176	40	7	28	0	2	1	1	1	82	167	-85	40	4	28	0	1	2	2	3	93	184	-91	41	175	271	446	1	2	72	43	54	9	1903	623	608	633	69	3152	966	332	1035	224	42	18.75%	131	22	83.21%	1	1015	2079	48.82%	1241	2631	47.17%	667	1269	52.56%	1629	1144	2297	541	925	433
36	3	0	3	0	0	0	0	0	9	32	-23	1	0	1	0	0	0	0	0	2	12	-10	2	0	2	0	0	0	0	0	7	20	-13	0	9	10	19	0	0	3	4	2	0	73	17	30	26	0	179	63	21	49	14	4	28.57%	8	6	25.00%	0	34	69	49.28%	24	60	40.00%	31	69	44.93%	52	33	89	23	37	17
Total Saison Régulière	163	22	115	0	6	6	6	8	359	734	-375	81	14	57	0	4	2	2	2	166	346	-180	82	8	58	0	2	4	4	6	193	388	-195	82	359	552	911	2	4	147	90	110	18	3879	1263	1246	1292	138	6483	1995	685	2119	462	88	19.05%	270	50	81.48%	2	2064	4227	48.83%	2506	5322	47.09%	1365	2607	52.36%	3311	2323	4684	1106	1889	885