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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	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP
1	Austin Poganski		X		100.00	80	75	90	65	75	73	77	60	50	59	57	66	54	44	44	64	50	61	0
2	Matthew Highmore	X	X		100.00	76	43	94	70	66	55	62	59	31	60	57	70	25	47	47	63	50	60	0
3	Morgan Klimchuk	X			100.00	75	68	90	66	68	61	62	60	50	56	60	64	57	44	44	63	50	59	0
4	Otto Koivula	X	X		100.00	75	45	94	66	83	50	76	55	59	50	55	71	25	45	45	60	50	59	0
5	Miikka Salomaki	X	X		100.00	74	72	78	73	72	62	64	56	50	52	53	65	50	57	59	59	50	59	0
6	Vince Dunn			X	100.00	69	53	88	85	73	69	92	72	25	54	54	58	25	60	61	63	50	66	0
7	Ilya Lyubushkin			X	100.00	95	47	89	70	76	64	64	62	25	47	47	67	25	55	55	59	50	64	0
8	Seth Helgeson			X	100.00	74	80	60	61	80	77	86	46	25	37	39	61	37	48	48	52	50	59	0
9	Josh Teves (R)			X	100.00	69	64	79	61	64	51	53	44	25	33	39	57	37	44	44	49	50	53	0
Rayé

	MOYENNE D'ÉQUIPE				100.00	76	61	85	69	73	62	71	57	38	50	51	64	37	49	50	59	50	60

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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	Matt Tomkins (R)	100.00	52	63	79	79	49	53	50	57	49	49	30	44	44	53	50	55	0
2	Francois Brassard	100.00	51	55	55	55	55	55	55	55	55	55	55	55	55	55	50	54	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	52	59	67	67	52	54	53	56	52	52	43	50	50	54	50	55

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Steve Ott	50	68	59	66	45	46	56	CAN	38	1	700,000$

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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	PIM5	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	PSS	FW	FL	FT	S1	S2	S3
1	Austin Poganski	Crunch (TBL)	RW	28	23	31	54	32	24	10	76	45	98	29	70	23.47%	9	583	20.83	0	8	8	7	66	2	0	2	2	82	4	3	57.78%	45	0	1.85	1	0	1	1	2	8	1
2	Matthew Highmore	Crunch (TBL)	LW/RW	28	28	24	52	28	22	0	59	32	116	25	82	24.14%	11	521	18.62	3	3	6	12	59	0	1	1	1	23	0	0	54.05%	37	5	1.99	1	0	0	0	6	1	3
3	Morgan Klimchuk	Crunch (TBL)	LW	28	30	18	48	21	10	0	73	39	142	44	109	21.13%	19	537	19.21	3	6	9	19	60	1	0	1	4	58	3	1	68.42%	38	3	1.78	0	0	0	0	5	3	1
4	Miikka Salomaki	Crunch (TBL)	LW/RW	26	14	29	43	19	27	5	84	36	128	34	87	10.94%	8	447	17.20	0	5	5	10	59	0	0	0	0	10	1	0	66.67%	18	0	1.92	0	0	0	1	3	2	2
5	Otto Koivula	Crunch (TBL)	LW/RW	28	32	8	40	10	16	0	104	49	158	49	98	20.25%	40	509	18.19	0	1	1	2	18	1	1	2	3	35	6	2	68.00%	25	4	1.57	0	0	0	0	4	2	4
6	Seth Helgeson	Crunch (TBL)	D	30	7	25	32	17	58	10	61	14	39	10	26	17.95%	22	499	16.66	5	5	10	15	67	0	0	0	0	70	2	0	100.00%	1	0	1.28	0	1	0	1	0	1	3
7	Vince Dunn	Crunch (TBL)	D	28	8	20	28	10	2	0	19	22	36	11	25	22.22%	19	580	20.73	4	2	6	19	68	1	1	2	2	86	2	0	0.00%	2	0	0.96	0	0	0	0	0	1	2
8	Josh Teves	Crunch (TBL)	D	30	3	16	19	18	6	0	16	13	21	12	19	14.29%	30	497	16.58	1	2	3	7	62	0	2	2	1	80	0	0	0.00%	1	0	0.76	0	0	0	0	0	0	1
9	Ilya Lyubushkin	Crunch (TBL)	D	28	3	15	18	11	64	0	105	17	22	10	15	13.64%	29	535	19.11	2	1	3	11	67	0	1	1	0	58	0	0	0.00%	0	0	0.67	0	0	0	0	0	0	3
Stats d'équipe Total ou en Moyenne				254	148	186	334	166	229	25	597	267	760	224	531	19.47%	187	4711	18.55	18	33	51	102	530	5	6	11	13	507	18	6	61.08%	167	12	1.42	2	1	1	3	20	18	20

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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	A	PS %	PSA	ST	BG	S2	S3
1	Matt Tomkins	Crunch (TBL)	30	18	9	1	0.877	3.16	1594	2	3	84	683	1	0.500	2	30	0	2	1
2	Francois Brassard	Crunch (TBL)	6	2	0	0	0.896	2.02	208	0	0	7	67	0	0.000	0	0	28	0	0
Stats d'équipe Total ou en Moyenne			36	20	9	1	0.879	3.03	1803	2	3	91	750	1	0.500	2	30	28	2	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 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
Austin Poganski	Crunch (TBL)	RW	24	1996-02-16	No	201 Lbs	6 ft2	No	No	No	3	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$	750,000$	Lien / Lien NHL
Francois Brassard	Crunch (TBL)	G	26	1994-01-31 2:16:29 PM	No	172 Lbs	6 ft1	No	No	No	1	Pro & Farm	700,000$	700,000$	0$	0$	No
Ilya Lyubushkin	Crunch (TBL)	D	26	1994-04-06	No	209 Lbs	6 ft2	No	No	No	2	Pro & Farm	985,000$	985,000$	0$	0$	No	985,000$		Lien / Lien NHL
Josh Teves	Crunch (TBL)	D	25	1995-02-18	Yes	170 Lbs	6 ft0	No	No	No	1	Pro & Farm	700,000$	700,000$	0$	0$	No			Lien / Lien NHL
Matt Tomkins	Crunch (TBL)	G	26	1994-06-19	Yes	194 Lbs	6 ft3	No	No	No	1	Pro & Farm	925,000$	925,000$	0$	0$	No			Lien / Lien NHL
Matthew Highmore	Crunch (TBL)	LW/RW	24	1996-02-27	No	181 Lbs	5 ft11	No	No	No	1	Pro & Farm	925,000$	925,000$	0$	0$	No			Lien / Lien NHL
Miikka Salomaki	Crunch (TBL)	LW/RW	27	1993-03-08	No	203 Lbs	5 ft11	No	No	No	1	Pro & Farm	900,000$	900,000$	0$	0$	No			Lien / Lien NHL
Morgan Klimchuk	Crunch (TBL)	LW	25	1995-03-01	No	185 Lbs	6 ft0	No	No	No	1	Pro & Farm	863,333$	863,333$	0$	0$	No			Lien / Lien NHL
Otto Koivula	Crunch (TBL)	LW/RW	22	1998-10-01	No	220 Lbs	6 ft4	No	No	No	3	Pro & Farm	786,666$	786,666$	0$	0$	No	786,666$	786,666$	Lien / Lien NHL
Seth Helgeson	Crunch (TBL)	D	30	1990-10-08	No	210 Lbs	6 ft4	No	No	No	1	Pro & Farm	900,000$	900,000$	0$	0$	No			Lien / Lien NHL
Vince Dunn	Crunch (TBL)	D	24	1996-10-28	No	203 Lbs	6 ft0	No	No	No	1	Pro & Farm	888,333$	888,333$	0$	0$	No			Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
11	25.36	195 Lbs	6 ft1	1.45	847,576$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Matthew Highmore		Austin Poganski	40	1	2	2
2	Morgan Klimchuk		Miikka Salomaki	30	1	2	2
3	Otto Koivula			20	1	2	2
4	Matthew Highmore	Austin Poganski	Morgan Klimchuk	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Vince Dunn	Ilya Lyubushkin	40	1	2	2
2	Seth Helgeson	Josh Teves	30	1	2	2
3			20	1	2	2
4	Vince Dunn	Ilya Lyubushkin	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Matthew Highmore		Austin Poganski	60	1	2	2
2	Morgan Klimchuk		Miikka Salomaki	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Vince Dunn	Ilya Lyubushkin	60	1	2	2
2	Seth Helgeson	Josh Teves	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Austin Poganski	Matthew Highmore	60	1	2	2
2	Morgan Klimchuk	Miikka Salomaki	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Vince Dunn	Ilya Lyubushkin	60	1	2	2
2	Seth Helgeson	Josh Teves	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Austin Poganski	60	1	2	2	Vince Dunn	Ilya Lyubushkin	60	1	2	2
2	Matthew Highmore	40	1	2	2	Seth Helgeson	Josh Teves	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Austin Poganski	Matthew Highmore	60	1	2	2
2	Morgan Klimchuk	Miikka Salomaki	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Vince Dunn	Ilya Lyubushkin	60	1	2	2
2	Seth Helgeson	Josh Teves	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Matthew Highmore		Austin Poganski	Vince Dunn	Ilya Lyubushkin

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Matthew Highmore		Austin Poganski	Vince Dunn	Ilya Lyubushkin

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Otto Koivula, Miikka Salomaki, Morgan Klimchuk	Otto Koivula, Miikka Salomaki	Morgan Klimchuk

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Seth Helgeson, Josh Teves, Vince Dunn	Seth Helgeson	Josh Teves, Vince Dunn

Tirs de Pénalité
Austin Poganski, Matthew Highmore, Morgan Klimchuk, Miikka Salomaki, Otto Koivula

Gardien
#1 : Matt Tomkins, #2 : Francois Brassard

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

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

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Astuces sur les Filtres (Anglais seulement)

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

	Ligue												Domicile											Visiteur
#	VS Équipe	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	PCT	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
1	Bears	2	2	0	0	0	0	0	0	12	1	11	1	1	0	0	0	0	0	0	7	1	6	1	1	0	0	0	0	0	0	5	0	5	4	1.000	12	20	32	0	1	70	38	52	0	79	351	305	336	5	40	7	18	54	3	2	66.67%	8	1	87.50%	1	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
2	Bruins	2	1	1	0	0	0	0	0	5	6	-1	1	0	1	0	0	0	0	0	2	4	-2	1	1	0	0	0	0	0	0	3	2	1	2	0.500	5	9	14	0	0	70	38	52	0	40	351	305	336	5	44	18	17	38	15	2	13.33%	6	1	83.33%	0	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
3	Checkers	2	2	0	0	0	0	0	0	11	2	9	1	1	0	0	0	0	0	0	6	0	6	1	1	0	0	0	0	0	0	5	2	3	4	1.000	11	17	28	0	1	70	38	52	0	66	351	305	336	5	55	12	18	57	2	1	50.00%	9	0	100.00%	4	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
4	Comets	2	0	2	0	0	0	0	0	2	7	-5	1	0	1	0	0	0	0	0	1	5	-4	1	0	1	0	0	0	0	0	1	2	-1	0	0.000	2	3	5	0	0	70	38	52	0	36	351	305	336	5	42	9	43	32	9	0	0.00%	13	2	84.62%	0	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
5	Devils	2	2	0	0	0	0	0	0	15	4	11	1	1	0	0	0	0	0	0	10	0	10	1	1	0	0	0	0	0	0	5	4	1	4	1.000	15	24	39	0	1	70	38	52	0	88	351	305	336	5	50	7	10	58	3	1	33.33%	4	1	75.00%	0	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
6	Griffins	2	1	0	0	0	0	0	1	10	5	5	1	1	0	0	0	0	0	0	7	1	6	1	0	0	0	0	0	0	1	3	4	-1	3	0.750	10	15	25	0	0	70	38	52	0	92	351	305	336	5	46	14	4	49	1	0	0.00%	1	0	100.00%	0	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
7	Marlies	2	2	0	0	0	0	0	0	18	11	7	1	1	0	0	0	0	0	0	10	6	4	1	1	0	0	0	0	0	0	8	5	3	4	1.000	18	31	49	0	0	70	38	52	0	81	351	305	336	5	52	17	16	32	4	2	50.00%	7	0	100.00%	0	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
8	Monsters	2	0	2	0	0	0	0	0	5	9	-4	1	0	1	0	0	0	0	0	1	4	-3	1	0	1	0	0	0	0	0	4	5	-1	0	0.000	5	8	13	0	0	70	38	52	0	21	351	305	336	5	60	19	22	32	12	1	8.33%	11	2	81.82%	0	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
9	Penguins	2	1	1	0	0	0	0	0	6	9	-3	1	1	0	0	0	0	0	0	4	3	1	1	0	1	0	0	0	0	0	2	6	-4	2	0.500	6	9	15	0	0	70	38	52	0	52	351	305	336	5	71	16	18	44	7	1	14.29%	9	2	77.78%	0	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
10	Phantoms	2	2	0	0	0	0	0	0	14	5	9	1	1	0	0	0	0	0	0	7	3	4	1	1	0	0	0	0	0	0	7	2	5	4	1.000	14	24	38	0	0	70	38	52	0	68	351	305	336	5	53	24	21	54	6	3	50.00%	8	0	100.00%	0	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
11	Rocket	2	0	2	0	0	0	0	0	3	7	-4	1	0	1	0	0	0	0	0	2	5	-3	1	0	1	0	0	0	0	0	1	2	-1	0	0.000	3	6	9	0	0	70	38	52	0	34	351	305	336	5	44	17	10	33	10	2	20.00%	5	0	100.00%	0	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
12	Senators	2	2	0	0	0	0	0	0	17	6	11	1	1	0	0	0	0	0	0	9	3	6	1	1	0	0	0	0	0	0	8	3	5	4	1.000	17	29	46	0	0	70	38	52	0	87	351	305	336	5	45	10	21	38	5	0	0.00%	8	2	75.00%	0	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
13	Sound Tigers	2	2	0	0	0	0	0	0	13	7	6	1	1	0	0	0	0	0	0	4	3	1	1	1	0	0	0	0	0	0	9	4	5	4	1.000	13	22	35	0	0	70	38	52	0	101	351	305	336	5	62	15	8	70	3	1	33.33%	4	0	100.00%	0	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
14	Thunderbirds	2	1	1	0	0	0	0	0	7	10	-3	1	0	1	0	0	0	0	0	3	7	-4	1	1	0	0	0	0	0	0	4	3	1	2	0.500	7	12	19	0	0	70	38	52	0	36	351	305	336	5	50	16	18	39	13	2	15.38%	8	2	75.00%	0	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
	Total	30	20	9	0	0	0	0	1	160	92	68	15	10	5	0	0	0	0	0	84	46	38	15	10	4	0	0	0	0	1	76	46	30	41	0.683	160	265	425	0	3	70	38	52	0	994	351	305	336	5	750	218	269	695	96	19	19.79%	106	14	86.79%	5	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
16	Wolf Pack	2	2	0	0	0	0	0	0	22	3	19	1	1	0	0	0	0	0	0	11	1	10	1	1	0	0	0	0	0	0	11	2	9	4	1.000	22	36	58	0	0	70	38	52	0	113	351	305	336	5	36	17	25	65	3	1	33.33%	5	1	80.00%	0	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
	_Since Last GM Reset	30	20	9	0	0	0	0	1	160	92	68	15	10	5	0	0	0	0	0	84	46	38	15	10	4	0	0	0	0	1	76	46	30	41	0.683	160	265	425	0	3	70	38	52	0	994	351	305	336	5	750	218	269	695	96	19	19.79%	106	14	86.79%	5	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
	_Vs Conference	30	20	9	0	0	0	0	1	160	92	68	15	10	5	0	0	0	0	0	84	46	38	15	10	4	0	0	0	0	1	76	46	30	41	0.683	160	265	425	0	3	70	38	52	0	994	351	305	336	5	750	218	269	695	96	19	19.79%	106	14	86.79%	5	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
	_Vs Division	12	7	6	0	0	0	0	1	60	45	15	6	4	3	0	0	0	0	0	33	26	7	6	3	3	0	0	0	0	1	27	19	8	15	0.625	60	102	162	0	0	70	38	52	0	370	351	305	336	5	281	92	86	229	48	8	16.67%	35	5	85.71%	0	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173

			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
30	41	W3	160	265	425	994	750	218	269	695	0	3

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
30	20	9	0	0	0	1	160	92

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
15	10	5	0	0	0	0	84	46

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
15	10	4	0	0	0	1	76	46

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
7	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
96	19	19.79%	106	14	86.79%	5

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
351	305	336	5	70	38	52	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
326	843	38.67%	292	761	38.37%	199	486	40.95%

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
839	634	639	176	326	173

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
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
1 - 2020-10-24	4	Sound Tigers	3	Crunch	4	W			Sommaire du Match
2 - 2020-10-25	29	Crunch	5	Devils	4	W			Sommaire du Match
3 - 2020-10-26	45	Crunch	4	Thunderbirds	3	W			Sommaire du Match
4 - 2020-10-27	50	Crunch	1	Comets	2	L			Sommaire du Match
5 - 2020-10-28	62	Marlies	6	Crunch	10	W			Sommaire du Match
6 - 2020-10-29	83	Crunch	1	Rocket	2	L			Sommaire du Match
7 - 2020-10-30	94	Senators	3	Crunch	9	W			Sommaire du Match
9 - 2020-11-01	116	Checkers	0	Crunch	6	W			Sommaire du Match
10 - 2020-11-02	128	Penguins	3	Crunch	4	W			Sommaire du Match
12 - 2020-11-04	154	Crunch	2	Penguins	6	L			Sommaire du Match
13 - 2020-11-05	170	Crunch	3	Griffins	4	L	X	X	Sommaire du Match
14 - 2020-11-06	181	Thunderbirds	7	Crunch	3	L			Sommaire du Match
15 - 2020-11-07	199	Griffins	1	Crunch	7	W			Sommaire du Match
17 - 2020-11-09	218	Bears	1	Crunch	7	W			Sommaire du Match
19 - 2020-11-11	246	Crunch	8	Senators	3	W			Sommaire du Match
20 - 2020-11-12	256	Bruins	4	Crunch	2	L			Sommaire du Match
22 - 2020-11-14	281	Rocket	5	Crunch	2	L			Sommaire du Match
23 - 2020-11-15	291	Crunch	7	Phantoms	2	W			Sommaire du Match
24 - 2020-11-16	311	Wolf Pack	1	Crunch	11	W			Sommaire du Match
25 - 2020-11-17	329	Crunch	3	Bruins	2	W			Sommaire du Match
26 - 2020-11-18	341	Crunch	4	Monsters	5	L			Sommaire du Match
27 - 2020-11-19	349	Devils	0	Crunch	10	W			Sommaire du Match
28 - 2020-11-20	365	Crunch	8	Marlies	5	W			Sommaire du Match
29 - 2020-11-21	380	Comets	5	Crunch	1	L			Sommaire du Match
32 - 2020-11-24	405	Phantoms	3	Crunch	7	W			Sommaire du Match
33 - 2020-11-25	421	Crunch	11	Wolf Pack	2	W			Sommaire du Match
36 - 2020-11-28	438	Monsters	4	Crunch	1	L			Sommaire du Match
37 - 2020-11-29	445	Crunch	5	Checkers	2	W			Sommaire du Match
38 - 2020-11-30	456	Crunch	5	Bears	0	W			Sommaire du Match
39 - 2020-12-01	461	Crunch	9	Sound Tigers	4	W			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	30	0
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$	932,333$	932,333$	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

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	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
2020	30	20	9	0	0	0	0	1	160	92	68	15	10	5	0	0	0	0	0	84	46	38	15	10	4	0	0	0	0	1	76	46	30	41	160	265	425	0	3	70	38	52	0	994	351	305	336	5	750	218	269	695	96	19	19.79%	106	14	86.79%	5	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173
Total Saison Régulière	30	20	9	0	0	0	0	1	160	92	68	15	10	5	0	0	0	0	0	84	46	38	15	10	4	0	0	0	0	1	76	46	30	41	160	265	425	0	3	70	38	52	0	994	351	305	336	5	750	218	269	695	96	19	19.79%	106	14	86.79%	5	326	843	38.67%	292	761	38.37%	199	486	40.95%	839	634	639	176	326	173