OTHL - Phantoms

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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	Jordan Weal	X	X	X		100.00	69	42	90	71	63	65	73	76	61	62	70	64	75	61	62	69	50	65	0	29	2	1,250,000$
2	Ross Colton	X	X			100.00	73	74	72	65	74	77	81	62	78	64	57	63	54	44	44	63	50	62	0	24	3	925,000$
3	Adam Johnson	X	X			100.00	72	64	91	62	64	77	81	63	79	64	58	63	55	45	45	63	50	61	0	27	1	925,000$
4	Nolan Stevens	X				100.00	76	70	90	65	70	70	72	62	78	62	57	65	54	44	44	63	50	61	0	24	3	700,000$
5	Trey Fix-Wolansky (R)			X		100.00	68	63	79	61	63	69	71	62	50	57	63	61	60	44	44	63	50	59	0	22	3	925,000$
6	Mason Shaw	X				100.00	71	64	86	58	64	62	64	55	69	48	57	60	54	44	44	58	50	56	0	22	3	925,000$
7	Brandon Duhaime (R)		X	X		100.00	73	75	69	68	75	66	70	51	50	50	47	60	45	44	44	55	50	56	0	24	3	925,000$
8	Luke Gazdic (C)		X			100.00	86	84	90	58	84	44	45	45	50	38	44	69	42	60	60	53	50	54	0	31	1	750,000$
9	Jan Rutta				X	100.00	67	43	87	77	76	67	65	61	25	53	48	72	25	57	58	60	50	64	0	30	1	2,300,000$
10	Cameron Gaunce				X	100.00	76	75	79	67	75	71	75	56	25	55	41	66	39	56	56	57	50	63	0	31	1	845,833$
11	Dillon Simpson				X	100.00	77	72	89	66	72	79	86	53	25	41	49	65	47	53	53	59	50	62	0	28	1	750,000$
12	Joel Hanley (A)				X	100.00	77	70	93	72	70	72	78	49	25	43	39	64	37	53	54	54	50	61	0	30	1	900,000$
13	Brandon Manning				X	100.00	74	78	63	67	78	57	59	55	25	51	39	67	37	65	66	54	50	61	0	31	2	750,000$
14	Erik Burgdoerfer				X	100.00	73	75	68	61	75	71	78	46	25	36	40	61	38	52	52	51	50	58	0	32	1	750,000$
15	Josiah Didier				X	100.00	72	75	65	64	75	63	68	48	25	39	41	59	39	45	45	52	50	57	0	28	3	750,000$
Rayé
1	Byron Froese	X		X		100.00	74	74	73	62	74	73	75	68	80	64	66	69	63	59	59	67	50	65	0	30	1	900,000$

	MOYENNE D'ÉQUIPE					100.00	74	69	80	65	72	68	71	57	48	52	51	64	48	52	52	59	50	60

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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	100.00	53	61	61	81	57	48	50	55	58	53	78	59	59	55	50	57	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	53	61	61	81	57	48	50	55	58	53	78	59	59	55	50	57

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Tim Army	50	60	65	49	49	42	52	USA	53	4	725,000$

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Astuces sur les Filtres (Anglais seulement)

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

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#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	GW	FO%	FOT	P/20	S1	S2	S3
1	Jordan Weal	Phantoms (PHL)	C/LW/RW	7	3	4	7	0	4	5	28	29	6	15	10.34%	2	187	26.81	0	3	3	5	32	3	41	1	51.26%	238	0.75	1	1	0
2	Jan Rutta	Phantoms (PHL)	D	7	1	5	6	0	10	9	8	5	4	8	20.00%	10	187	26.84	1	2	3	4	30	0	36	0	0.00%	0	0.64	0	0	1
3	Ross Colton	Phantoms (PHL)	C/LW	7	3	2	5	0	10	12	14	17	4	6	17.65%	3	190	27.25	2	2	4	5	33	1	43	0	42.86%	14	0.52	2	0	0
4	Nolan Stevens	Phantoms (PHL)	C	7	4	1	5	1	4	7	19	19	3	17	21.05%	1	176	25.18	1	1	2	4	33	0	28	1	60.78%	153	0.57	0	2	1
5	Trey Fix-Wolansky	Phantoms (PHL)	RW	7	1	3	4	0	6	16	9	10	6	12	10.00%	0	163	23.29	1	1	2	4	33	0	19	1	43.48%	23	0.49	0	1	0
6	Mason Shaw	Phantoms (PHL)	C	7	1	2	3	1	4	7	12	9	5	8	11.11%	2	128	18.31	0	1	1	1	9	0	8	0	53.06%	98	0.47	0	0	0
7	Cameron Gaunce	Phantoms (PHL)	D	7	0	3	3	0	14	13	6	1	1	4	0.00%	8	181	25.87	0	1	1	1	33	0	37	0	0.00%	0	0.33	0	0	0
8	Erik Burgdoerfer	Phantoms (PHL)	D	7	1	2	3	3	18	23	5	3	0	1	33.33%	6	134	19.17	0	0	0	0	2	0	19	0	0.00%	0	0.45	0	0	0
9	Luke Gazdic	Phantoms (PHL)	LW	7	0	2	2	1	6	10	3	11	3	9	0.00%	1	123	17.67	0	0	0	0	6	0	9	0	53.85%	13	0.32	0	0	0
10	Josiah Didier	Phantoms (PHL)	D	7	1	0	1	1	12	12	3	3	2	5	33.33%	2	131	18.72	1	0	1	2	8	0	14	0	37.50%	8	0.15	0	0	0
11	Adam Johnson	Phantoms (PHL)	C/LW	7	1	0	1	1	6	6	8	16	1	9	6.25%	1	177	25.33	1	0	1	7	34	0	29	0	57.14%	7	0.11	0	0	0
12	Brandon Duhaime	Phantoms (PHL)	LW/RW	7	0	1	1	1	6	7	4	10	1	3	0.00%	0	143	20.46	0	0	0	3	35	0	0	0	33.33%	9	0.14	0	0	0
13	Dillon Simpson	Phantoms (PHL)	D	7	0	1	1	-1	6	10	9	7	2	6	0.00%	4	179	25.57	0	1	1	2	35	0	40	0	0.00%	0	0.11	0	0	0
14	Joel Hanley	Phantoms (PHL)	D	7	0	0	0	3	4	9	6	1	1	1	0.00%	6	131	18.84	0	0	0	0	10	1	6	0	0.00%	0	0.00	0	0	0
15	Brandon Manning	Phantoms (PHL)	D	7	0	0	0	-1	14	18	8	5	0	3	0.00%	10	164	23.46	0	0	0	4	31	0	31	0	0.00%	0	0.00	0	0	0
Stats d'équipe Total ou en Moyenne				105	16	26	42	10	124	164	142	146	39	107	10.96%	56	2399	22.85	7	12	19	42	369	5	366	3	53.29%	563	0.35	3	4	2

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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	Phantoms (PHL)	7	3	2	2	0.893	1.91	502	0	1	16	150	0	0	0	0.000	0	7	0	0	0	1
Stats d'équipe Total ou en Moyenne			7	3	2	2	0.893	1.91	502	0	1	16	150	0	0	0	0.000	0	7	0	0	0	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	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Link
Adam Johnson	Phantoms (PHL)	C/LW	27	1994-06-22	No	174 Lbs	6 ft0	No	No	No	1	Pro & Farm	925,000$	0$	0$	No			Lien / Lien NHL
Brandon Duhaime	Phantoms (PHL)	LW/RW	24	1997-05-22	Yes	201 Lbs	6 ft2	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$	Lien / Lien NHL
Brandon Manning	Phantoms (PHL)	D	31	1990-06-03	No	205 Lbs	6 ft1	Yes	No	No	2	Pro & Farm	750,000$	0$	0$	No	750,000$		Lien / Lien NHL
Byron Froese	Phantoms (PHL)	C/RW	30	1991-03-12	No	202 Lbs	6 ft1	No	No	No	1	Pro & Farm	900,000$	0$	0$	No			Lien / Lien NHL
Cameron Gaunce	Phantoms (PHL)	D	31	1990-03-19	No	204 Lbs	6 ft2	No	No	No	1	Pro & Farm	845,833$	0$	0$	No			Lien / Lien NHL
Dillon Simpson	Phantoms (PHL)	D	28	1993-02-09	No	194 Lbs	6 ft2	No	No	No	1	Pro & Farm	750,000$	0$	0$	No			Lien / Lien NHL
Erik Burgdoerfer	Phantoms (PHL)	D	32	1988-12-11	No	207 Lbs	6 ft1	Yes	No	No	1	Pro & Farm	750,000$	0$	0$	No			Lien / Lien NHL
Jan Rutta	Phantoms (PHL)	D	30	1990-07-29	No	200 Lbs	6 ft3	No	No	No	1	Pro & Farm	2,300,000$	0$	0$	No			Lien / Lien NHL
Joel Hanley	Phantoms (PHL)	D	30	1991-06-08	No	193 Lbs	6 ft0	No	No	No	1	Pro & Farm	900,000$	0$	0$	No			Lien / Lien NHL
Jordan Weal	Phantoms (PHL)	C/LW/RW	29	1992-04-14	No	179 Lbs	5 ft10	No	No	No	2	Pro & Farm	1,250,000$	0$	0$	No	1,250,000$		Lien / Lien NHL
Josiah Didier	Phantoms (PHL)	D	28	1993-04-08	No	202 Lbs	6 ft2	No	No	No	3	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$	Lien / Lien NHL
Luke Gazdic	Phantoms (PHL)	LW	31	1989-07-24	No	225 Lbs	6 ft4	No	No	No	1	Pro & Farm	750,000$	0$	0$	No			Lien
Mason Shaw	Phantoms (PHL)	C	22	1998-11-02	No	180 Lbs	5 ft9	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$	Lien / Lien NHL
Michael Hutchinson	Phantoms (PHL)	G	31	1990-03-01	No	202 Lbs	6 ft3	Yes	No	No	2	Pro & Farm	800,000$	0$	0$	No	800,000$		Lien / Lien NHL
Nolan Stevens	Phantoms (PHL)	C	24	1996-07-21	No	183 Lbs	6 ft3	No	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$	Lien / Lien NHL
Ross Colton	Phantoms (PHL)	C/LW	24	1996-09-11	No	209 Lbs	6 ft0	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$	Lien / Lien NHL
Trey Fix-Wolansky	Phantoms (PHL)	RW	22	1999-05-26	Yes	187 Lbs	5 ft7	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$	Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
17	27.88	197 Lbs	6 ft1	1.88	945,343$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Ross Colton	Jordan Weal	Trey Fix-Wolansky	40	1	2	2
2	Adam Johnson	Nolan Stevens	Brandon Duhaime	30	1	2	2
3	Luke Gazdic	Mason Shaw	Josiah Didier	20	1	2	2
4	Ross Colton	Jordan Weal	Nolan Stevens	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jan Rutta	Cameron Gaunce	40	1	2	2
2	Dillon Simpson	Brandon Manning	30	1	2	2
3	Joel Hanley	Erik Burgdoerfer	20	1	2	2
4	Josiah Didier	Jan Rutta	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Ross Colton	Jordan Weal	Trey Fix-Wolansky	60	1	2	2
2	Adam Johnson	Nolan Stevens	Brandon Duhaime	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jan Rutta	Cameron Gaunce	60	1	2	2
2	Dillon Simpson	Brandon Manning	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Jordan Weal	Ross Colton	60	1	2	2
2	Nolan Stevens	Adam Johnson	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jan Rutta	Cameron Gaunce	60	1	2	2
2	Dillon Simpson	Brandon Manning	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Jordan Weal	60	1	2	2	Jan Rutta	Cameron Gaunce	60	1	2	2
2	Ross Colton	40	1	2	2	Dillon Simpson	Brandon Manning	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Jordan Weal	Ross Colton	60	1	2	2
2	Nolan Stevens	Adam Johnson	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jan Rutta	Cameron Gaunce	60	1	2	2
2	Dillon Simpson	Brandon Manning	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Ross Colton	Jordan Weal	Trey Fix-Wolansky	Jan Rutta	Cameron Gaunce

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Ross Colton	Jordan Weal	Trey Fix-Wolansky	Jan Rutta	Cameron Gaunce

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Mason Shaw, Luke Gazdic, Trey Fix-Wolansky	Mason Shaw, Luke Gazdic	Trey Fix-Wolansky

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Joel Hanley, Erik Burgdoerfer, Josiah Didier	Joel Hanley	Erik Burgdoerfer, Josiah Didier

Tirs de Pénalité
Jordan Weal, Ross Colton, Nolan Stevens, Adam Johnson, Trey Fix-Wolansky

Gardien
#1 : Michael Hutchinson, #2 :

Lignes d'Attaque Perso. en Prol.
Jordan Weal, Ross Colton, Nolan Stevens, Adam Johnson, Trey Fix-Wolansky, Brandon Duhaime, Brandon Duhaime, Mason Shaw, Luke Gazdic, ,

Lignes de Défense Perso. en Prol.
Jan Rutta, Cameron Gaunce, Dillon Simpson, Brandon Manning, Joel Hanley

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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	Comets	7	3	4	0	0	0	0	0	16	16	0	3	2	1	0	0	0	0	0	11	6	5	4	1	3	0	0	0	0	0	5	10	-5	6	0.429	16	26	42	0	1	7	5	3	1	146	54	37	36	19	150	56	124	164	45	7	15.56%	59	9	84.75%	0	144	238	60.50%	113	221	51.13%	43	104	41.35%	197	135	202	62	103	50
	Total	7	3	4	0	0	0	0	0	16	16	0	3	2	1	0	0	0	0	0	11	6	5	4	1	3	0	0	0	0	0	5	10	-5	6	0.429	16	26	42	0	1	7	5	3	1	146	54	37	36	19	150	56	124	164	45	7	15.56%	59	9	84.75%	0	144	238	60.50%	113	221	51.13%	43	104	41.35%	197	135	202	62	103	50
	_Since Last GM Reset	7	3	4	0	0	0	0	0	16	16	0	3	2	1	0	0	0	0	0	11	6	5	4	1	3	0	0	0	0	0	5	10	-5	6	0.429	16	26	42	0	1	7	5	3	1	146	54	37	36	19	150	56	124	164	45	7	15.56%	59	9	84.75%	0	144	238	60.50%	113	221	51.13%	43	104	41.35%	197	135	202	62	103	50
	_Vs Conference	7	3	4	0	0	0	0	0	16	16	0	3	2	1	0	0	0	0	0	11	6	5	4	1	3	0	0	0	0	0	5	10	-5	6	0.429	16	26	42	0	1	7	5	3	1	146	54	37	36	19	150	56	124	164	45	7	15.56%	59	9	84.75%	0	144	238	60.50%	113	221	51.13%	43	104	41.35%	197	135	202	62	103	50

			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
7	6	OTL1	16	26	42	146	150	56	124	164	0	1

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
7	3	4	0	0	0	0	16	16

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	2	1	0	0	0	0	11	6

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	1	3	0	0	0	0	5	10

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
2	2	1	2	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
45	7	15.56%	59	9	84.75%	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
54	37	36	19	7	5	3	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
144	238	60.50%	113	221	51.13%	43	104	41.35%

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
197	135	202	62	103	50

Derniers Match Joués Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

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

Jour	Match	Équipe Visiteuse	Score	Équipe Locale	Score	ST	OT	Lien
1 - 2020-10-24	1	Phantoms	2	Comets	1	W		Sommaire du Match
3 - 2020-10-26	9	Phantoms	1	Comets	2	L		Sommaire du Match
5 - 2020-10-28	17	Comets	4	Phantoms	3	L	X	Sommaire du Match
7 - 2020-10-30	25	Comets	2	Phantoms	3	W	X	Sommaire du Match
9 - 2020-11-01	33	Phantoms	2	Comets	6	L		Sommaire du Match
11 - 2020-11-03	41	Comets	0	Phantoms	5	W		Sommaire du Match
13 - 2020-11-05	49	Phantoms	0	Comets	1	L	X	Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité	2000	1000
Prix des Billets	45	0
Assistance	6,000	3,000
Assistance PCT	100.00%	100.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité	Popularité de l'Équipe
38	3000 - 100.00%	90,000$	270,000$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
0$	1,607,083$	1,607,083$	0$

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

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

Afficher ou Masquer des Colonnes

	Ligue											Domicile											Visiteur
Année	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
Saison Régulière
2020	82	40	32	0	5	2	3	0	321	234	87	41	21	15	0	1	2	2	0	160	123	37	41	19	17	0	4	0	1	0	161	111	50	98	321	563	884	0	8	134	86	93	10	2248	782	685	758	30	1485	452	1036	1613	354	59	16.67%	438	68	84.47%	11	1621	2331	69.54%	1100	1743	63.11%	866	1285	67.39%	2430	1812	1565	507	956	530
Total Saison Régulière	82	40	32	0	5	2	3	0	321	234	87	41	21	15	0	1	2	2	0	160	123	37	41	19	17	0	4	0	1	0	161	111	50	98	321	563	884	0	8	134	86	93	10	2248	782	685	758	30	1485	452	1036	1613	354	59	16.67%	438	68	84.47%	11	1621	2331	69.54%	1100	1743	63.11%	866	1285	67.39%	2430	1812	1565	507	956	530
2020	7	3	4	0	0	0	0	0	16	16	0	3	2	1	0	0	0	0	0	11	6	5	4	1	3	0	0	0	0	0	5	10	-5	6	16	26	42	0	1	7	5	3	1	146	54	37	36	19	150	56	124	164	45	7	15.56%	59	9	84.75%	0	144	238	60.50%	113	221	51.13%	43	104	41.35%	197	135	202	62	103	50
Total Séries	7	3	4	0	0	0	0	0	16	16	0	3	2	1	0	0	0	0	0	11	6	5	4	1	3	0	0	0	0	0	5	10	-5	6	16	26	42	0	1	7	5	3	1	146	54	37	36	19	150	56	124	164	45	7	15.56%	59	9	84.75%	0	144	238	60.50%	113	221	51.13%	43	104	41.35%	197	135	202	62	103	50

	Phantoms
	GP: 7 \| W: 3 \| L: 4 GF: 16 \| GA: 16 \| PP%: 15.56% \| PK%: 84.75% DG: Matt \| Morale : 50 \| Moyenne d'Équipe : 60