Profi League - Checkers

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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	Erik Condra		X	X		100.00	59	41	66	77	81	72	69	67	61	41	43	68	50	67	69	0	53	62	0
2	Dustin Jeffrey	X	X			100.00	75	75	78	60	57	67	70	66	85	44	41	65	56	59	59	0	53	60	0
3	Austin Watson	X		X		100.00	69	66	66	77	57	52	72	64	58	41	39	65	50	51	51	0	53	58	0
4	Bobby Farnham		X	X		100.00	74	99	58	72	54	52	69	66	60	38	43	60	50	51	51	0	63	57	0
5	Corey Tropp (R)		X	X		100.00	58	68	60	73	52	67	66	59	71	36	36	57	50	60	61	0	50	55	0
6	Chris Bourque		X			100.00	55	60	59	67	49	71	66	63	69	43	42	57	59	49	49	0	53	55	0
7	John Albert	X				100.00	75	69	75	64	53	67	66	59	71	35	35	58	50	45	45	0	53	55	0
8	Eric O'Dell	X				100.00	71	54	53	64	54	51	66	65	56	37	40	60	47	57	63	0	51	55	0
9	Adrian Kempe (R)		X	X		100.00	66	75	72	72	57	53	60	56	73	34	35	62	50	44	44	0	55	54	0
10	Brian Ferlin			X		100.00	61	76	63	63	58	60	61	58	76	34	35	60	50	44	44	0	51	53	0
11	Justin Vaive		X			100.00	65	78	63	62	59	66	64	55	66	28	34	58	50	44	44	0	51	52	0
12	Emile Poirier (R)		X	X		100.00	58	69	60	68	53	66	63	57	69	33	35	56	50	44	44	0	53	52	0
13	Derek Forbort				X	100.00	65	88	69	77	79	55	76	64	25	39	40	70	50	59	59	0	53	62	0
14	Michal Jordan				X	100.00	67	43	85	78	69	69	74	64	25	38	39	72	50	53	53	0	53	61	0
15	Michael Kostka				X	100.00	64	42	87	67	73	69	83	57	25	39	37	71	90	55	56	0	50	60	0
16	Matt Taormina				X	100.00	70	65	89	71	66	85	84	52	25	40	36	61	50	50	50	0	53	60	0
17	Gustav Olofsson (R)				X	100.00	61	74	69	74	60	60	64	60	25	33	29	63	50	55	55	0	54	55	0
18	Rasmus Rissanen				X	100.00	60	80	66	73	63	66	69	58	25	29	29	59	50	47	47	0	56	54	0
Rayé
1	Mario Lucia (R)		X			100.00	73	73	75	61	56	64	63	54	65	28	33	55	50	50	50	0	46	53	0
2	Brennan Evans				X	100.00	60	83	66	59	64	63	67	53	25	24	26	59	50	47	47	0	46	51	0

	MOYENNE D'ÉQUIPE					100.00	65	69	69	69	61	64	69	60	53	36	36	62	53	52	52	0	53	56

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Michael Hutchinson	97.00	69	76	86	79	68	84	69	70	72	83	50	72	66	0	53	72	0
2	Michael Leighton	100.00	73	86	79	77	80	71	65	69	64	75	54	55	55	0	53	69	0
Rayé
1	Patrick Killeen	100.00	60	50	56	86	72	65	61	60	60	63	71	47	63	0	46	63	0

	MOYENNE D'ÉQUIPE	99.00	67	71	74	81	73	73	65	66	65	74	58	58	61	0	51	68

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Bill Peters	92	77	73	88	73	72	70	CAN	50	5	100,000$

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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	SHT	OSB	OSM	SHT%	SB	MP	PPG	PPA	PPP	PKG	PKA	PKP	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS
1	Erik Condra	Checkers (CAR)		LW/RW	4	4	8	12	7	2	0	5	18	6	20	22.22%	2	21.:.54	0	1	1	1	0	1	10	1	0	61.54%	13	21	3	0	1	2.74	0	0
2	Austin Watson	Checkers (CAR)		C/RW	4	5	4	9	5	0	0	7	17	2	7	29.41%	5	17.:.54	1	1	2	0	1	1	3	0	0	64.86%	37	17	5	0	1	2.51	0	0
3	Michal Jordan	Checkers (CAR)		D	4	2	3	5	6	0	0	4	11	5	8	18.18%	9	26.:.35	0	1	1	0	0	0	9	1	0	0.00%	0	3	8	0	0	0.94	0	0
4	Michael Kostka	Checkers (CAR)		D	4	1	4	5	9	0	0	4	11	1	6	9.09%	5	21.:.54	0	0	0	0	0	0	5	0	0	0.00%	0	5	3	0	0	1.14	0	0
5	Corey Tropp	Checkers (CAR)		LW/RW	4	1	4	5	4	0	0	8	5	2	5	20.00%	0	15.:.16	1	0	1	0	0	0	0	0	0	100.00%	1	6	2	0	0	1.64	0	0
6	Dustin Jeffrey	Checkers (CAR)		C/LW	4	2	3	5	5	5	5	9	11	1	8	18.18%	1	19.:.52	0	1	1	0	0	0	6	0	0	60.58%	104	3	5	0	0	1.26	0	0
7	John Albert	Checkers (CAR)		C	4	3	2	5	5	2	0	7	7	1	5	42.86%	0	11.:.08	0	0	0	0	0	0	3	0	0	54.17%	24	7	1	0	1	2.24	0	0
8	Bobby Farnham	Checkers (CAR)		LW/RW	4	3	2	5	6	40	30	9	11	3	10	27.27%	1	13.:.45	0	0	0	1	0	1	0	0	0	100.00%	5	14	0	0	0	1.82	0	0
9	Eric O'Dell	Checkers (CAR)		C	3	1	3	4	3	6	0	11	5	4	2	20.00%	5	15.:.25	0	0	0	0	0	0	0	0	0	64.00%	25	6	2	0	0	1.73	0	0
10	Emile Poirier	Checkers (CAR)		LW/RW	4	1	2	3	4	0	0	1	9	0	3	11.11%	0	08.:.45	0	0	0	0	0	0	0	0	0	0.00%	0	3	1	0	0	1.71	0	0
11	Matt Taormina	Checkers (CAR)		D	4	0	3	3	9	5	5	5	4	1	2	0.00%	2	20.:.54	0	0	0	0	0	0	5	0	0	0.00%	0	1	4	0	0	0.72	0	0
12	Chris Bourque	Checkers (CAR)		LW	4	2	1	3	3	0	0	4	20	3	9	10.00%	0	12.:.13	0	0	0	0	0	0	0	1	0	42.86%	7	10	0	0	0	1.23	0	0
13	Derek Forbort	Checkers (CAR)		D	4	1	2	3	1	30	20	5	8	8	7	12.50%	5	22.:.06	0	0	0	0	1	1	9	0	0	0.00%	0	4	6	0	0	0.68	0	0
14	Justin Vaive	Checkers (CAR)		LW	3	0	2	2	4	0	0	4	1	1	2	0.00%	2	08.:.47	0	0	0	0	0	0	0	0	0	100.00%	2	1	0	0	0	1.52	0	0
15	Gustav Olofsson	Checkers (CAR)		D	4	0	2	2	6	5	5	2	3	1	4	0.00%	8	16.:.07	0	0	0	0	0	0	0	0	0	0.00%	0	0	4	0	0	0.62	0	0
16	Rasmus Rissanen	Checkers (CAR)		D	4	0	1	1	5	15	15	1	2	0	1	0.00%	3	11.:.58	0	0	0	0	0	0	0	0	0	0.00%	0	0	2	0	0	0.42	0	0
17	Brian Ferlin	Checkers (CAR)		RW	2	1	0	1	1	0	0	2	2	0	0	50.00%	1	10.:.40	0	0	0	0	0	0	0	0	0	0.00%	0	2	0	0	0	0.94	0	0
18	Adrian Kempe	Checkers (CAR)		LW/RW	4	0	0	0	4	24	10	3	2	0	1	0.00%	0	13.:.12	0	0	0	0	0	0	0	0	0	50.00%	2	2	1	0	0	0.00	0	0
19	Mario Lucia	Checkers (CAR)		LW	1	0	0	0	0	2	0	2	1	1	3	0.00%	1	14.:.04	0	0	0	0	0	0	0	0	0	40.00%	5	0	1	0	0	0.00	0	0
Stats d'équipe Total ou en Moyenne		69	27	46	73	87	136	90	93	76	148	40	103	18.24%	50	1122	16.27	2	4	6	4	55	2	2	4	4	55	3	0	61.33%	225	105	48	0	3	1.30	0	0	8	1	9	2	2	3

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du 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
1	Michael Hutchinson	Checkers (CAR)	4	3	1	0	94.4%	2.00	240	0	0	8	143	75	0	0	0.0%	0	4	0	1	2	0
Stats d'équipe Total ou en Moyenne	4	3	1	0	0.944	2.00	240	0	0	8	143	75	0	0	0.000	0	4	0	1	2	0

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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	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Ballotage Forcé	Contrat	Type	Salaire Actuel	Salaire Restant	Salaire Année 2	Salaire Année 3	Salaire Année 4	Salaire Année 5	Salaire Année 6	Salaire Année 7	Salaire Année 8	Salaire Année 9	Salaire Année 10	Link
Adrian Kempe	LW/RW	20	13.09.1996	Yes	203 Lbs	6 ft2	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Lien
Austin Watson	C/RW	24	13.01.1992 4:27:35	No	193 Lbs	6 ft4	No	No	2	Pro & Farm	1,000,000$	0$	1,000,000$									Lien
Bobby Farnham	LW/RW	27	21.01.1989	No	190 Lbs	5 ft10	No	No	1	Pro & Farm	800,000$	0$										Lien
Brennan Evans	D	34	06.01.1982	No	223 Lbs	6 ft4	No	No	5	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$						Lien
Brian Ferlin	RW	24	03.06.1992 0:52:08	No	209 Lbs	6 ft2	No	No	1	Pro & Farm	900,000$	0$										Lien
Chris Bourque	LW	30	29.01.1986	No	174 Lbs	5 ft8	No	No	1	Pro & Farm	700,000$	0$										Lien
Corey Tropp	LW/RW	27	25.07.1989	Yes	185 Lbs	6 ft0	No	No	2	Pro & Farm	900,000$	0$	900,000$									Lien
Derek Forbort	D	24	04.03.1992 2:35:10	No	212 Lbs	6 ft4	No	No	1	Pro & Farm	1,300,000$	0$										Lien
Dustin Jeffrey	C/LW	28	27.02.1988	No	205 Lbs	6 ft1	No	No	1	Pro & Farm	800,000$	0$										Lien
Emile Poirier	LW/RW	21	14.12.1994 0:53:48	Yes	185 Lbs	6 ft1	No	No	2	Pro & Farm	800,000$	0$	800,000$									Lien
Eric O'Dell	C	25	21.06.1991 18:51:31	No	185 Lbs	6 ft0	No	No	2	Pro & Farm	700,000$	0$	700,000$									Lien
Erik Condra	LW/RW	30	06.08.1986	No	190 Lbs	6 ft0	No	No	2	Pro & Farm	1,000,000$	0$	1,000,000$									Lien
Gustav Olofsson	D	21	30.11.1994	Yes	191 Lbs	6 ft4	No	No	10	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	Lien
John Albert	C	27	19.01.1989 5:01:18	No	190 Lbs	5 ft11	No	No	2	Pro & Farm	900,000$	0$	900,000$									Lien
Justin Vaive	LW	27	08.07.1989 23:57:27	No	209 Lbs	6 ft4	No	No	6	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$					Lien
Mario Lucia	LW	23	25.08.1993 23:56:43	Yes	205 Lbs	6 ft3	No	No	10	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$
Matt Taormina	D	30	20.10.1986	No	182 Lbs	5 ft10	No	No	2	Pro & Farm	800,000$	0$	800,000$									Lien
Michael Hutchinson (Contrat à 1 Volet)	G	26	02.03.1990	No	202 Lbs	6 ft3	No	No	2	Pro & Farm	1,700,000$	0$	1,700,000$									Lien
Michael Kostka	D	30	28.11.1985	No	210 Lbs	6 ft1	No	No	2	Pro & Farm	1,100,000$	0$	1,100,000$									Lien
Michael Leighton	G	35	19.01.1981	No	186 Lbs	6 ft3	No	No	1	Pro & Farm	700,000$	0$										Lien
Michal Jordan	D	26	17.07.1990	No	195 Lbs	6 ft1	No	No	1	Pro & Farm	1,500,000$	0$										Lien
Patrick Killeen	G	26	15.04.1990 15:04:03	No	205 Lbs	6 ft4	No	No	5	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$
Rasmus Rissanen	D	25	13.07.1991 9:01:01	No	217 Lbs	6 ft3	No	No	1	Pro & Farm	900,000$	0$										Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
23	26.52	198 Lbs	6 ft2	3.0869565217391	743,478$

Attaque à 5 contre 5
Ligne #	Centre	Ailier Gauche	Ailier Droit	% Temps	PHY	DF	OF
1	Dustin Jeffrey	Erik Condra	Bobby Farnham	40	1	2	2
2	Austin Watson	Corey Tropp	Adrian Kempe	30	1	2	2
3	Eric O'Dell	Chris Bourque	Brian Ferlin	20	1	2	2
4	John Albert	Justin Vaive	Emile Poirier	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Derek Forbort	Michal Jordan	40	1	2	2
2	Michael Kostka	Matt Taormina	30	1	2	2
3	Gustav Olofsson	Rasmus Rissanen	20	1	2	2
4	Derek Forbort	Michal Jordan	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Centre	Ailier Gauche	Ailier Droit	% Temps	PHY	DF	OF
1	Dustin Jeffrey	Erik Condra	Bobby Farnham	60	1	2	2
2	Austin Watson	Corey Tropp	Adrian Kempe	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Derek Forbort	Michal Jordan	60	1	2	2
2	Michael Kostka	Matt Taormina	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Erik Condra	Dustin Jeffrey	60	1	2	2
2	Bobby Farnham	Austin Watson	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Derek Forbort	Michal Jordan	60	1	2	2
2	Michael Kostka	Matt Taormina	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Erik Condra	60	1	2	2	Derek Forbort	Michal Jordan	60	1	2	2
2	Dustin Jeffrey	40	1	2	2	Michael Kostka	Matt Taormina	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Erik Condra	Dustin Jeffrey	60	1	2	2
2	Bobby Farnham	Austin Watson	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Derek Forbort	Michal Jordan	60	1	2	2
2	Michael Kostka	Matt Taormina	40	1	2	2

Attaque Dernière Minute
Centre	Ailier Gauche	Ailier Droit	Défense	Défense
Dustin Jeffrey	Erik Condra	Bobby Farnham	Derek Forbort	Michal Jordan

Défense Dernière Minute
Centre	Ailier Gauche	Ailier Droit	Défense	Défense
Dustin Jeffrey	Erik Condra	Bobby Farnham	Derek Forbort	Michal Jordan

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Eric O'Dell, Chris Bourque, John Albert	Eric O'Dell, Chris Bourque	John Albert

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Gustav Olofsson, Rasmus Rissanen, Michael Kostka	Gustav Olofsson	Rasmus Rissanen, Michael Kostka

Tirs de Pénalité
Erik Condra, Dustin Jeffrey, Bobby Farnham, Austin Watson, Corey Tropp

Gardien
#1 : Michael Hutchinson, #2 : Michael Leighton

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

#	VS Équipe	GP	W	L	GF	GA	Diff	P	PCT	G	A	TP	GP1	GP2	GP3	SHF	SH1	SP2	SP3	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	Sound Tigers	1	1	0	2	1	1	2	1.000	2	3	5	15	5	7	34	63	28	61	24	12	15	32	5	0	0.00%	0	0	0.00%	0	47	79	59.49%	67	97	69.07%	38	69	55.07%	96	64	83	29	60	31
2	IceCaps	1	1	0	20	4	16	2	1.000	20	35	55	15	5	7	38	63	28	61	39	14	84	22	3	2	66.67%	2	0	100.00%	1	47	79	59.49%	67	97	69.07%	38	69	55.07%	96	64	83	29	60	31
3	Falcons	1	0	1	1	2	-1	0	0.000	1	2	3	15	5	7	33	63	28	61	44	11	60	22	0	0	0.00%	5	1	80.00%	0	47	79	59.49%	67	97	69.07%	38	69	55.07%	96	64	83	29	60	31
4	Wild	1	1	0	4	1	3	2	1.000	4	6	10	15	5	7	47	63	28	61	36	14	2	27	1	0	0.00%	1	0	100.00%	1	47	79	59.49%	67	97	69.07%	38	69	55.07%	96	64	83	29	60	31
	Vs Conference	1	1	0	2	1	1	2	1.000	2	3	5	15	5	7	34	63	28	61	24	12	15	32	5	0	0.00%	0	0	0.00%	0	47	79	59.49%	67	97	69.07%	38	69	55.07%	96	64	83	29	60	31
	Since Last GM Reset	4	3	1	27	8	19	6	0.750	27	46	73	15	5	7	152	63	28	61	143	51	161	103	9	2	22.22%	8	1	87.50%	2	47	79	59.49%	67	97	69.07%	38	69	55.07%	96	64	83	29	60	31
	Total	4	3	1	27	8	19	6	0.750	27	46	73	15	5	7	152	63	28	61	143	51	161	103	9	2	22.22%	8	1	87.50%	2	47	79	59.49%	67	97	69.07%	38	69	55.07%	96	64	83	29	60	31

			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
4	6	W3	27	46	73	152	143	51	161	103	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	3	1	0	0	0	0	27	8

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	2	0	0	0	0	0	6	2

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	1	1	0	0	0	0	21	6

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
3	1	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
9	2	22.22%	8	1	87.50%	2

Tirs en 1e Période	Tirs en 2e Période	Tirs en 3e Période	Tirs en 4e Période	Buts en 1e Période	Buts en 2e Période	Buts en 3e Période	Buts en 4e Période
63	28	61	0	15	5	7	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
47	79	59.49%	67	97	69.07%	38	69	55.07%

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
96	64	83	29	60	31

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

Date		Result	Detail
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
Fri, Nov 22	@	Checkers1,Falcons2	RECAP
Sun, Nov 24	@	Sound Tigers1,Checkers2	RECAP
Mon, Nov 25	@	Wild1,Checkers4	RECAP
Fri, Nov 29	@	Checkers20,IceCaps4	RECAP

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
Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
1,540,000$	780,000$	0$

Dépenses Annuelles à Ce Jour	Cap Salarial Par Jour	Cap salarial à ce jour
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