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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	Simon Holmstrom			X		100.00	61	41	93	78	70	65	88	63	34	61	72	82	53	58	58	0	54	68	0	23	2	863,333$
2	Jesper Boqvist	X	X			97.00	80	44	94	85	67	58	91	65	48	63	64	69	25	64	65	0	53	68	0	25	3	775,000$
3	James Malatesta (R)		X			100.00	99	97	86	66	65	56	69	68	25	64	71	64	25	45	45	0	58	66	0	21	3	841,667$
4	Keegan Kolesar			X		100.00	99	90	82	75	81	57	94	65	36	61	59	72	25	65	67	0	59	66	0	27	2	2,100,000$
5	Vasily Podkolzin		X	X		100.00	99	47	87	79	69	57	62	67	37	60	55	63	25	59	59	0	57	65	0	23	1	925,000$
6	Lias Andersson	X	X			100.00	74	71	81	62	71	73	76	66	80	61	65	68	62	57	57	0	56	65	0	25	3	775,000$
7	Connor Brown		X	X		100.00	65	42	95	74	68	63	58	67	39	60	57	85	25	72	73	0	53	65	0	30	2	3,600,000$
8	Jesse Ylonen		X	X		100.00	69	43	93	72	74	56	84	71	52	57	58	70	70	56	56	0	54	65	0	25	1	880,833$
9	Ben Meyers	X	X			100.00	80	44	91	70	69	56	79	62	57	59	56	67	25	52	53	0	56	62	0	25	2	912,500$
10	Erik Brannstrom		X		X	99.00	67	42	86	83	66	70	92	66	25	56	48	79	25	65	65	0	49	69	0	25	1	2,000,000$
11	Dante Fabbro				X	100.00	71	42	87	82	68	69	85	61	25	53	48	79	25	66	67	0	59	68	0	26	1	2,400,000$
12	Travis Dermott				X	99.00	75	44	84	81	74	72	54	63	25	49	48	89	25	66	68	0	51	68	0	27	2	1,500,000$
13	Caleb Jones				X	99.00	79	44	89	77	71	59	72	64	25	54	47	74	75	66	66	0	52	67	0	27	2	3,100,000$
14	Andreas Englund				X	100.00	88	99	73	70	75	61	89	60	25	49	47	73	25	59	59	0	52	65	0	28	3	1,000,000$
15	Alec Regula				X	100.00	78	77	79	65	77	67	71	53	25	49	41	64	39	46	46	0	59	60	0	24	1	866,667$
Rayé
1	Ryan Poehling	X	X			100.00	71	43	97	78	76	68	82	66	84	67	66	81	25	63	63	0	53	70	0	25	2	1,400,000$

	MOYENNE D'ÉQUIPE					99.63	78	57	87	75	71	63	78	64	40	58	56	74	36	60	60	0	55	66

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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	Elvis Merzlikins	100.00	63	65	65	73	65	60	71	66	65	63	95	62	63	0	58	65	0
2	Matt Murray	100.00	67	59	74	74	68	63	68	67	67	65	45	44	44	0	42	65	0
Rayé
1	Michael Hutchinson	100.00	48	47	59	80	48	50	51	54	51	51	30	60	61	0	48	52	0

	MOYENNE D'ÉQUIPE	100.00	59	57	66	76	60	58	63	62	61	60	57	55	56	0	49	61

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Adam Foote	40	40	40	40	40	40	40	TUR	80	2	500,000$

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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	GW	GT	FO%	FOT	HT	P/20	PSG	PSS	S1	S2	S3
1	Dante Fabbro	Checkers (SEA)	D	8	2	8	10	-1	6	6	11	22	5	12	9.09%	6	178	22.28	1	3	4	14	36	0	25	0	0	0.00%	0	0	1.12	0	0	0	1	0
2	Simon Holmstrom	Checkers (SEA)	RW	8	4	4	8	1	6	6	14	44	7	23	9.09%	3	145	18.16	0	3	3	17	37	0	13	0	0	53.85%	26	0	1.10	0	1	0	0	1
3	Jakub Vrana	Kraken	LW	8	2	6	8	2	0	0	19	27	6	15	7.41%	1	153	19.19	0	2	2	7	38	0	12	0	0	33.33%	12	0	1.04	0	2	0	0	1
4	Jesper Boqvist	Checkers (SEA)	C/LW	8	1	6	7	-1	4	25	8	22	4	17	4.55%	0	168	21.02	1	2	3	5	35	0	31	0	0	61.11%	18	0	0.83	0	2	1	0	0
5	Lias Andersson	Checkers (SEA)	C/LW	8	3	4	7	2	2	3	15	15	5	13	20.00%	1	140	17.51	2	1	3	5	38	0	1	1	0	62.37%	194	0	1.00	0	0	0	0	0
6	Travis Dermott	Checkers (SEA)	D	8	0	6	6	-5	10	20	10	17	5	17	0.00%	17	186	23.29	0	2	2	9	39	0	26	0	0	0.00%	0	0	0.64	0	0	0	1	0
7	Keegan Kolesar	Checkers (SEA)	RW	8	4	2	6	2	10	31	10	30	6	13	13.33%	3	137	17.22	1	2	3	9	38	0	0	1	0	12.50%	8	0	0.87	0	0	1	0	1
8	Andreas Englund	Checkers (SEA)	D	8	3	2	5	3	6	23	6	8	1	4	37.50%	10	123	15.40	1	0	1	1	5	0	3	0	0	0.00%	0	0	0.81	0	0	0	1	1
9	James Malatesta	Checkers (SEA)	LW	8	4	1	5	-4	6	25	9	20	5	11	20.00%	1	112	14.04	1	0	1	2	5	1	1	0	1	36.36%	11	1	0.89	0	0	1	0	0
10	Connor Brown	Checkers (SEA)	LW/RW	8	0	5	5	-5	0	2	19	19	3	17	0.00%	1	105	13.13	0	1	1	0	3	0	0	0	0	44.44%	9	0	0.95	0	0	0	0	0
11	Caleb Jones	Checkers (SEA)	D	8	2	3	5	-2	14	16	13	17	3	13	11.76%	6	171	21.44	1	2	3	9	35	0	20	1	1	0.00%	0	0	0.58	1	2	0	0	1
12	Ryan Poehling	Checkers (SEA)	C/LW	4	2	2	4	-1	2	3	16	7	6	12	28.57%	2	99	24.75	2	2	4	2	21	2	19	0	1	55.06%	158	0	0.81	0	1	0	1	0
13	Erik Brannstrom	Checkers (SEA)	LW/D	8	1	2	3	-5	4	8	13	22	7	9	4.55%	21	188	23.57	1	1	2	19	39	0	28	0	0	0.00%	0	0	0.32	0	2	0	0	0
14	Ben Meyers	Checkers (SEA)	C/LW	8	1	1	2	-5	2	3	12	4	3	8	25.00%	2	99	12.42	0	0	0	0	0	0	0	0	0	50.81%	124	0	0.40	0	0	0	0	0
15	Jesse Ylonen	Checkers (SEA)	LW/RW	8	1	1	2	-1	0	3	7	8	4	10	12.50%	2	62	7.85	0	0	0	0	0	0	14	0	0	36.36%	11	0	0.64	0	0	0	0	0
16	Alec Regula	Checkers (SEA)	D	8	0	2	2	2	6	10	3	2	1	2	0.00%	10	129	16.19	0	1	1	2	3	0	11	0	0	0.00%	0	0	0.31	0	0	0	0	0
17	Vasily Podkolzin	Checkers (SEA)	LW/RW	5	0	0	0	-1	2	5	5	3	1	1	0.00%	0	22	4.41	0	0	0	0	0	0	0	0	0	50.00%	2	0	0.00	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				129	30	55	85	-19	80	189	190	287	72	197	10.45%	86	2222	17.23	11	22	33	101	376	3	211	3	3	54.80%	573	1	0.76	1	10	3	4	5

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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	GA	SA	EG	PS %	PSA	ST	BG	S1
1	Matt Murray	Checkers (SEA)	7	4	2	0	0.881	3.63	397	24	202	0	1.000	6	7	0	1
2	Elvis Merzlikins	Checkers (SEA)	3	0	1	1	0.937	2.67	90	4	63	2	0.800	5	1	8	0
Stats d'équipe Total ou en Moyenne			10	4	3	1	0.894	3.45	487	28	265	2	0.909	11	8	8	1

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 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	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Link
Alec Regula	Checkers (SEA)	D	24	2000-08-05	No	203 Lbs	6 ft4	No	No	No	1	Pro & Farm	866,667$	866,667$	0$	0$	No			Lien
Andreas Englund	Checkers (SEA)	D	28	1996-01-21	No	189 Lbs	6 ft3	No	No	No	3	Pro & Farm	1,000,000$	1,000,000$	0$	0$	No	1,000,000$	1,000,000$	Lien
Ben Meyers	Checkers (SEA)	C/LW	25	1998-11-15	No	194 Lbs	5 ft11	No	No	No	2	Pro & Farm	912,500$	912,500$	0$	0$	No	912,500$		Lien
Caleb Jones	Checkers (SEA)	D	27	1997-06-05	No	194 Lbs	6 ft1	No	No	No	2	Pro & Farm	3,100,000$	3,100,000$	0$	0$	No	3,100,000$		Lien / Lien NHL
Connor Brown	Checkers (SEA)	LW/RW	30	1994-01-14	No	186 Lbs	6 ft0	No	No	No	2	Pro & Farm	3,600,000$	3,600,000$	0$	0$	No	3,600,000$		Lien / Lien NHL
Dante Fabbro	Checkers (SEA)	D	26	1998-06-20	No	189 Lbs	6 ft0	No	No	No	1	Pro & Farm	2,400,000$	2,400,000$	0$	0$	No			Lien / Lien NHL
Elvis Merzlikins	Checkers (SEA)	G	30	1994-04-13	No	180 Lbs	6 ft3	No	No	No	2	Pro & Farm	5,400,000$	5,400,000$	0$	0$	No	5,400,000$		Lien / Lien NHL
Erik Brannstrom	Checkers (SEA)	LW/D	25	1999-09-02	No	185 Lbs	5 ft10	No	No	No	1	Pro & Farm	2,000,000$	2,000,000$	0$	0$	No			Lien / Lien NHL
James Malatesta	Checkers (SEA)	LW	21	2003-05-31	Yes	178 Lbs	5 ft9	No	No	No	3	Pro & Farm	841,667$	841,667$	0$	0$	No	841,667$	841,667$	Lien
Jesper Boqvist	Checkers (SEA)	C/LW	25	1998-10-30	No	180 Lbs	6 ft0	No	No	No	3	Pro & Farm	775,000$	775,000$	0$	0$	No	775,000$	775,000$	Lien / Lien NHL
Jesse Ylonen	Checkers (SEA)	LW/RW	25	1999-10-03	No	200 Lbs	6 ft1	No	No	No	1	Pro & Farm	880,833$	880,833$	0$	0$	No			Lien
Keegan Kolesar	Checkers (SEA)	RW	27	1997-04-08	No	216 Lbs	6 ft2	No	No	No	2	Pro & Farm	2,100,000$	2,100,000$	0$	0$	No	2,100,000$		Lien / Lien NHL
Lias Andersson	Checkers (SEA)	C/LW	25	1998-10-13	No	190 Lbs	6 ft1	No	No	No	3	Pro & Farm	775,000$	775,000$	0$	0$	No	775,000$	775,000$	Lien / Lien NHL
Matt Murray	Checkers (SEA)	G	30	1994-05-25	No	178 Lbs	6 ft4	No	No	No	3	Pro & Farm	6,250,000$	6,250,000$	0$	0$	No	6,250,000$	6,250,000$	Lien / Lien NHL
Michael Hutchinson	Checkers (SEA)	G	34	1990-03-01	No	198 Lbs	6 ft3	No	No	No	3	Pro & Farm	1,000,100$	1,000,100$	0$	0$	No	1,000,100$	1,000,100$	Lien / Lien NHL
Ryan Poehling	Checkers (SEA)	C/LW	25	1999-01-03	No	205 Lbs	6 ft2	No	No	No	2	Pro & Farm	1,400,000$	1,400,000$	0$	0$	No	1,400,000$		Lien / Lien NHL
Simon Holmstrom	Checkers (SEA)	RW	23	2001-05-24	No	194 Lbs	6 ft0	No	No	No	2	Pro & Farm	863,333$	863,333$	0$	0$	No	863,333$		Lien
Travis Dermott	Checkers (SEA)	D	27	1996-12-21	No	205 Lbs	6 ft0	No	No	No	2	Pro & Farm	1,500,000$	1,500,000$	0$	0$	No	1,500,000$		Lien / Lien NHL
Vasily Podkolzin	Checkers (SEA)	LW/RW	23	2001-06-24	No	189 Lbs	6 ft1	No	No	No	1	Pro & Farm	925,000$	925,000$	0$	0$	No			Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
19	26.32	192 Lbs	6 ft1	2.05	1,925,795$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Jesper Boqvist		Simon Holmstrom	35	1	2	2
2		Lias Andersson	Keegan Kolesar	35	1	2	2
3	James Malatesta	Ben Meyers	Connor Brown	25	1	2	2
4	Jesse Ylonen			5	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Erik Brannstrom	Travis Dermott	35	1	2	2
2	Dante Fabbro	Caleb Jones	35	1	2	2
3	Andreas Englund	Alec Regula	25	1	2	2
4	Erik Brannstrom	Travis Dermott	5	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Jesper Boqvist		Simon Holmstrom	60	1	2	2
2		Lias Andersson	Keegan Kolesar	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Erik Brannstrom	Travis Dermott	60	1	2	2
2	Dante Fabbro	Caleb Jones	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1		Jesper Boqvist	60	1	2	2
2	Simon Holmstrom		40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Erik Brannstrom	Travis Dermott	60	1	2	2
2	Dante Fabbro	Caleb Jones	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1		60	1	2	2	Erik Brannstrom	Travis Dermott	60	1	2	2
2	Jesper Boqvist	40	1	2	2	Dante Fabbro	Caleb Jones	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1		Jesper Boqvist	60	1	2	2
2	Simon Holmstrom		40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Erik Brannstrom	Travis Dermott	60	1	2	2
2	Dante Fabbro	Caleb Jones	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Jesper Boqvist		Simon Holmstrom	Erik Brannstrom	Travis Dermott

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Jesper Boqvist		Simon Holmstrom	Erik Brannstrom	Travis Dermott

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
James Malatesta, Connor Brown, Jesse Ylonen	James Malatesta, Connor Brown	Jesse Ylonen

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Andreas Englund, Alec Regula, Dante Fabbro	Andreas Englund	Alec Regula, Dante Fabbro

Tirs de Pénalité
, Erik Brannstrom, Jesper Boqvist, Simon Holmstrom,

Gardien
#1 : Matt Murray, #2 : Elvis Merzlikins

Lignes d'Attaque Perso. en Prol.
, , , , , , , , , ,

Lignes de Défense Perso. en Prol.
, , , ,

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	Drag	2	1	0	0	0	0	0	1	8	7	1	1	1	0	0	0	0	0	0	3	1	2	1	0	0	0	0	0	0	1	5	6	-1	3	0.750	8	16	24	0	0	11	8	11	1	75	84	94	107	16	74	21	28	44	21	6	28.57%	13	4	69.23%	0	176	335	52.54%	153	286	53.50%	71	148	47.97%	206	143	179	60	103	52
2	Hurricanes	2	1	0	0	0	0	1	0	11	7	4	1	1	0	0	0	0	0	0	6	3	3	1	0	0	0	0	0	1	0	5	4	1	4	1.000	11	19	30	0	0	11	8	11	1	92	84	94	107	16	71	22	16	50	8	2	25.00%	7	1	85.71%	0	176	335	52.54%	153	286	53.50%	71	148	47.97%	206	143	179	60	103	52
3	IceHogs	2	1	1	0	0	0	0	0	8	8	0	1	1	0	0	0	0	0	0	5	3	2	1	0	1	0	0	0	0	0	3	5	-2	2	0.500	8	16	24	1	0	11	8	11	1	67	84	94	107	16	75	21	20	63	10	3	30.00%	9	2	77.78%	0	176	335	52.54%	153	286	53.50%	71	148	47.97%	206	143	179	60	103	52
	Total	8	3	3	0	0	0	1	1	31	31	0	4	3	1	0	0	0	0	0	17	12	5	4	0	2	0	0	0	1	1	14	19	-5	9	0.563	31	56	87	2	0	11	8	11	1	290	84	94	107	16	267	86	80	191	49	11	22.45%	36	7	80.56%	0	176	335	52.54%	153	286	53.50%	71	148	47.97%	206	143	179	60	103	52
4	Wilkes-Barre	2	0	2	0	0	0	0	0	4	9	-5	1	0	1	0	0	0	0	0	3	5	-2	1	0	1	0	0	0	0	0	1	4	-3	0	0.000	4	5	9	1	0	11	8	11	1	56	84	94	107	16	47	22	16	34	10	0	0.00%	7	0	100.00%	0	176	335	52.54%	153	286	53.50%	71	148	47.97%	206	143	179	60	103	52
	_Since Last GM Reset	8	3	3	0	0	0	1	1	31	31	0	4	3	1	0	0	0	0	0	17	12	5	4	0	2	0	0	0	1	1	14	19	-5	9	0.563	31	56	87	2	0	11	8	11	1	290	84	94	107	16	267	86	80	191	49	11	22.45%	36	7	80.56%	0	176	335	52.54%	153	286	53.50%	71	148	47.97%	206	143	179	60	103	52
	_Vs Conference	8	3	3	0	0	0	1	1	31	31	0	4	3	1	0	0	0	0	0	17	12	5	4	0	2	0	0	0	1	1	14	19	-5	9	0.563	31	56	87	2	0	11	8	11	1	290	84	94	107	16	267	86	80	191	49	11	22.45%	36	7	80.56%	0	176	335	52.54%	153	286	53.50%	71	148	47.97%	206	143	179	60	103	52
	_Vs Division	6	3	3	0	0	0	1	1	27	22	5	3	3	1	0	0	0	0	0	14	7	7	3	0	2	0	0	0	1	1	13	15	-2	9	0.750	27	51	78	1	0	11	8	11	1	234	84	94	107	16	220	64	64	157	39	11	28.21%	29	7	75.86%	0	176	335	52.54%	153	286	53.50%	71	148	47.97%	206	143	179	60	103	52

			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
8	9	W1	31	56	87	290	267	86	80	191	2	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	3	3	0	0	1	1	31	31

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	3	1	0	0	0	0	17	12

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	0	2	0	0	1	1	14	19

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	3	0	0	0	1

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
49	11	22.45%	36	7	80.56%	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
84	94	107	16	11	8	11	1

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
176	335	52.54%	153	286	53.50%	71	148	47.97%

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
206	143	179	60	103	52

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
2 - 2024-09-18	6	Drag	1	Checkers	3	W			Sommaire du Match
4 - 2024-09-20	21	IceHogs	3	Checkers	5	W			Sommaire du Match
5 - 2024-09-21	28	Checkers	1	Wilkes-Barre	4	L			Sommaire du Match
7 - 2024-09-23	36	Checkers	5	Drag	6	L	X	X	Sommaire du Match
9 - 2024-09-25	48	Checkers	3	IceHogs	5	L			Sommaire du Match
11 - 2024-09-27	57	Hurricanes	3	Checkers	6	W			Sommaire du Match
12 - 2024-09-28	67	Wilkes-Barre	5	Checkers	3	L			Sommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
14 - 2024-09-30	73	Checkers	5	Hurricanes	4	W	X	X	Sommaire du Match

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
0	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
0$	3,659,010$	2,421,618$	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$	1	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