OTHL - Senators

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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	Michael Bunting	X	X	X		100.00	72	70	76	68	70	73	75	65	50	69	58	63	55	44	44	64	50	62	0
2	Nick Moutrey	X	X	X		100.00	81	80	82	65	80	69	74	49	61	46	47	64	45	44	44	56	50	57	0
3	Ryan Kuffner		X			100.00	79	71	97	60	71	58	59	54	50	47	56	64	53	44	44	59	50	56	0
4	Jonathan Ericsson				X	100.00	78	45	92	71	83	64	60	56	25	39	47	76	25	75	79	59	50	66	0
5	Fredrik Claesson				X	100.00	78	74	88	76	74	60	63	54	25	48	41	68	39	60	60	56	50	63	0
6	Trevor Carrick				X	100.00	73	74	69	66	74	74	79	56	25	44	53	62	50	44	44	59	50	61	0
7	Jordan Gross				X	100.00	75	68	91	66	68	72	77	56	25	46	52	63	49	44	44	60	50	60	0
8	Mitch Reinke				X	100.00	72	66	87	63	66	73	78	53	25	49	43	60	41	44	44	55	50	59	0
9	Dean Kukan				X	100.00	69	42	88	68	70	68	54	65	25	50	48	55	25	59	60	56	50	59	0
Rayé

	MOYENNE D'ÉQUIPE					100.00	75	66	86	67	73	68	69	56	35	49	49	64	42	51	51	58	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

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#	Nom du Gardien	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV
Rayé

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

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Jay Pandolfo	59	71	63	43	45	46	55	USA	45	1	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	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	GW	GT	FO%	FOT	HT	P/20	PSS	FT	S1	S2	S3
1	Michael Bunting	Senators (OTT)	C/LW/RW	30	37	36	73	23	10	0	39	95	188	38	119	19.68%	23	584	19.48	2	4	6	15	43	2	44	3	0	66.43%	694	8	2.50	2	0	3	1	3
2	Nick Moutrey	Senators (OTT)	C/LW/RW	30	32	39	71	24	23	5	60	72	195	65	128	16.41%	26	576	19.22	2	3	5	15	42	1	38	1	2	73.17%	41	5	2.46	2	1	1	4	4
3	Mitch Reinke	Senators (OTT)	D	1	1	0	1	0	2	0	1	1	2	1	0	50.00%	2	18	18.10	1	0	1	1	3	0	0	1	0	0.00%	0	0	1.10	0	0	0	0	0
4	Ryan Kuffner	Senators (OTT)	LW	1	1	0	1	1	0	0	2	1	3	1	6	33.33%	0	16	16.92	0	0	0	0	1	0	0	0	0	0.00%	1	0	1.18	0	0	1	0	0
5	Dmytro Timashov	Senators	LW	1	0	0	0	0	0	0	2	4	4	0	0	0.00%	2	20	20.88	0	0	0	0	3	0	0	0	0	0.00%	0	0	0.00	0	0	0	0	0
6	Klim Kostin	Senators	C/LW/RW	1	0	0	0	0	2	0	1	6	4	0	4	0.00%	1	18	18.15	0	0	0	1	3	0	2	0	0	54.55%	22	0	0.00	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				64	71	75	146	48	37	5	105	179	396	105	257	17.93%	54	1235	19.30	5	7	12	32	98	3	87	5	2	66.36%	758	13	2.36	4	1	5	5	7

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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	Gilles Senn	Senators	1	1	0	0	0.950	1.00	60	0	0	1	20	0	0	0	0.000	0	1	0	0	0	1
Stats d'équipe Total ou en Moyenne			1	1	0	0	0.950	1.00	60	0	0	1	20	0	0	0	0.000	0	1	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	Salaire Restant	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Link
Dean Kukan	Senators (OTT)	D	27	1993-07-08	No	186 Lbs	6 ft2	No	No	No	1	Pro & Farm	800,000$	800,000$	0$	0$	No		Lien / Lien NHL
Fredrik Claesson	Senators (OTT)	D	27	1992-11-24	No	200 Lbs	6 ft1	No	No	No	1	Pro & Farm	1,000,000$	1,000,000$	0$	0$	No		Lien / Lien NHL
Jonathan Ericsson	Senators (OTT)	D	36	1984-03-02	No	220 Lbs	6 ft4	No	No	No	2	Pro & Farm	3,000,000$	3,000,000$	0$	0$	No	3,000,000$	Lien / Lien NHL
Jordan Gross	Senators (OTT)	D	25	1995-05-09	No	190 Lbs	5 ft10	No	No	No	1	Pro & Farm	1,775,000$	1,775,000$	0$	0$	No		Lien / Lien NHL
Michael Bunting	Senators (OTT)	C/LW/RW	25	1995-09-17	No	197 Lbs	5 ft11	No	No	No	2	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	Lien / Lien NHL
Mitch Reinke	Senators (OTT)	D	24	1996-02-04	No	181 Lbs	5 ft11	No	No	No	1	Pro & Farm	925,000$	925,000$	0$	0$	No		Lien / Lien NHL
Nick Moutrey	Senators (OTT)	C/LW/RW	25	1995-06-23	No	218 Lbs	6 ft3	No	No	No	2	Pro & Farm	525,000$	525,000$	0$	0$	No	525,000$	Lien / Lien NHL
Ryan Kuffner	Senators (OTT)	LW	24	1996-06-11	No	194 Lbs	6 ft1	No	No	No	1	Pro & Farm	925,000$	925,000$	0$	0$	No		Lien / Lien NHL
Trevor Carrick	Senators (OTT)	D	26	1994-07-04	No	186 Lbs	6 ft2	No	No	No	1	Pro & Farm	800,000$	800,000$	0$	0$	No		Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
9	26.56	197 Lbs	6 ft1	1.33	1,186,111$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Nick Moutrey	Michael Bunting		40	1	2	2
2				30	1	2	2
3				20	1	2	2
4	Nick Moutrey	Michael Bunting		10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			40	1	2	2
2			30	1	2	2
3			20	1	2	2
4			10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Nick Moutrey	Michael Bunting		60	1	2	2
2				40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Michael Bunting	Nick Moutrey	60	1	2	2
2			40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Michael Bunting	60	1	2	2			60	1	2	2
2	Nick Moutrey	40	1	2	2			40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Michael Bunting	Nick Moutrey	60	1	2	2
2			40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Nick Moutrey	Michael Bunting

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Nick Moutrey	Michael Bunting

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Michael Bunting, Nick Moutrey,	Michael Bunting, Nick Moutrey

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, ,		,

Tirs de Pénalité
Michael Bunting, Nick Moutrey, , ,

Gardien
#1 : , #2 :

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	18	9	9	1	1	0	0	0	0	0	0	9	5	4	1	1	0	0	0	0	0	0	9	4	5	4	1.000	18	26	44	0	0	55	32	28	0	117	324	346	290	7	65	21	6	34	7	1	14.29%	3	0	100.00%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
2	Bruins	2	0	2	0	0	0	0	0	1	14	-13	1	0	1	0	0	0	0	0	0	9	-9	1	0	1	0	0	0	0	0	1	5	-4	0	0.000	1	2	3	0	0	55	32	28	0	26	324	346	290	7	69	11	16	26	9	0	0.00%	6	1	83.33%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
3	Checkers	2	0	2	0	0	0	0	0	7	11	-4	1	0	1	0	0	0	0	0	3	4	-1	1	0	1	0	0	0	0	0	4	7	-3	0	0.000	7	10	17	0	0	55	32	28	0	78	324	346	290	7	90	30	10	41	2	1	50.00%	5	2	60.00%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
4	Comets	2	0	2	0	0	0	0	0	6	18	-12	1	0	1	0	0	0	0	0	4	8	-4	1	0	1	0	0	0	0	0	2	10	-8	0	0.000	6	7	13	0	0	55	32	28	0	22	324	346	290	7	80	20	20	20	5	0	0.00%	9	3	66.67%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
5	Crunch	2	0	2	0	0	0	0	0	6	17	-11	1	0	1	0	0	0	0	0	3	8	-5	1	0	1	0	0	0	0	0	3	9	-6	0	0.000	6	10	16	0	0	55	32	28	0	45	324	346	290	7	87	26	15	29	8	2	25.00%	5	0	100.00%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
6	Devils	2	2	0	0	0	0	0	0	11	5	6	1	1	0	0	0	0	0	0	4	3	1	1	1	0	0	0	0	0	0	7	2	5	4	1.000	11	16	27	0	0	55	32	28	0	130	324	346	290	7	68	15	5	46	2	0	0.00%	0	0	0.00%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
7	Griffins	2	0	2	0	0	0	0	0	10	14	-4	1	0	1	0	0	0	0	0	6	8	-2	1	0	1	0	0	0	0	0	4	6	-2	0	0.000	10	13	23	0	0	55	32	28	0	89	324	346	290	7	89	26	4	56	2	1	50.00%	2	1	50.00%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
8	Marlies	2	0	2	0	0	0	0	0	8	11	-3	1	0	1	0	0	0	0	0	4	6	-2	1	0	1	0	0	0	0	0	4	5	-1	0	0.000	8	14	22	0	0	55	32	28	0	64	324	346	290	7	88	23	2	27	2	1	50.00%	1	0	100.00%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
9	Monsters	2	0	1	0	0	0	0	1	5	9	-4	1	0	1	0	0	0	0	0	2	5	-3	1	0	0	0	0	0	0	1	3	4	-1	1	0.250	5	8	13	0	0	55	32	28	0	34	324	346	290	7	54	16	10	19	13	1	7.69%	5	1	80.00%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
10	Penguins	2	0	2	0	0	0	0	0	2	13	-11	1	0	1	0	0	0	0	0	2	7	-5	1	0	1	0	0	0	0	0	0	6	-6	0	0.000	2	2	4	0	0	55	32	28	0	44	324	346	290	7	77	21	18	33	4	0	0.00%	9	5	44.44%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
11	Phantoms	2	0	2	0	0	0	0	0	11	18	-7	1	0	1	0	0	0	0	0	5	10	-5	1	0	1	0	0	0	0	0	6	8	-2	0	0.000	11	16	27	0	0	55	32	28	0	52	324	346	290	7	91	30	6	21	3	1	33.33%	3	2	33.33%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
12	Rocket	2	0	2	0	0	0	0	0	2	17	-15	1	0	1	0	0	0	0	0	1	8	-7	1	0	1	0	0	0	0	0	1	9	-8	0	0.000	2	3	5	0	0	55	32	28	0	32	324	346	290	7	69	21	8	26	7	0	0.00%	4	2	50.00%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
13	Sound Tigers	2	2	0	0	0	0	0	0	15	7	8	1	1	0	0	0	0	0	0	8	4	4	1	1	0	0	0	0	0	0	7	3	4	4	1.000	15	22	37	0	0	55	32	28	0	99	324	346	290	7	77	13	10	55	2	0	0.00%	5	1	80.00%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
14	Thunderbirds	2	1	1	0	0	0	0	0	2	11	-9	1	1	0	0	0	0	0	0	2	1	1	1	0	1	0	0	0	0	0	0	10	-10	2	0.500	2	4	6	0	0	55	32	28	0	38	324	346	290	7	58	21	8	24	8	1	12.50%	4	1	75.00%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
	Total	30	7	21	0	0	0	0	2	115	188	-73	15	4	10	0	0	0	0	1	59	93	-34	15	3	11	0	0	0	0	1	56	95	-39	16	0.267	115	170	285	0	0	55	32	28	0	961	324	346	290	7	1178	321	147	498	75	9	12.00%	64	19	70.31%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
16	Wolf Pack	2	0	1	0	0	0	0	1	11	14	-3	1	0	0	0	0	0	0	1	6	7	-1	1	0	1	0	0	0	0	0	5	7	-2	1	0.250	11	17	28	0	0	55	32	28	0	91	324	346	290	7	116	27	9	41	1	0	0.00%	3	0	100.00%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
	_Since Last GM Reset	30	7	21	0	0	0	0	2	115	188	-73	15	4	10	0	0	0	0	1	59	93	-34	15	3	11	0	0	0	0	1	56	95	-39	16	0.267	115	170	285	0	0	55	32	28	0	961	324	346	290	7	1178	321	147	498	75	9	12.00%	64	19	70.31%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
	_Vs Conference	30	7	21	0	0	0	0	2	115	188	-73	15	4	10	0	0	0	0	1	59	93	-34	15	3	11	0	0	0	0	1	56	95	-39	16	0.267	115	170	285	0	0	55	32	28	0	961	324	346	290	7	1178	321	147	498	75	9	12.00%	64	19	70.31%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
	_Vs Division	12	2	11	0	0	0	0	1	29	84	-55	6	1	6	0	0	0	0	0	16	40	-24	6	1	5	0	0	0	0	1	13	44	-31	5	0.208	29	46	75	0	0	55	32	28	0	294	324	346	290	7	460	128	53	188	36	5	13.89%	22	5	77.27%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142

			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	16	L2	115	170	285	961	1178	321	147	498	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
30	7	21	0	0	0	2	115	188

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
15	4	10	0	0	0	1	59	93

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
15	3	11	0	0	0	1	56	95

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
2	8	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
75	9	12.00%	64	19	70.31%	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
324	346	290	7	55	32	28	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
358	727	49.24%	342	762	44.88%	276	552	50.00%

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
631	472	853	192	325	142

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	6	Thunderbirds	1	Senators	2	W			Sommaire du Match
2 - 2020-10-25	19	Senators	9	Bears	4	W			Sommaire du Match
3 - 2020-10-26	33	Senators	1	Rocket	9	L			Sommaire du Match
4 - 2020-10-27	54	Senators	4	Marlies	5	L			Sommaire du Match
5 - 2020-10-28	64	Wolf Pack	7	Senators	6	L	X	X	Sommaire du Match
6 - 2020-10-29	78	Phantoms	10	Senators	5	L			Sommaire du Match
7 - 2020-10-30	94	Senators	3	Crunch	9	L			Sommaire du Match
9 - 2020-11-01	109	Senators	2	Comets	10	L			Sommaire du Match
10 - 2020-11-02	124	Devils	3	Senators	4	W			Sommaire du Match
11 - 2020-11-03	142	Bruins	9	Senators	0	L			Sommaire du Match
12 - 2020-11-04	165	Senators	0	Thunderbirds	10	L			Sommaire du Match
13 - 2020-11-05	172	Comets	8	Senators	4	L			Sommaire du Match
15 - 2020-11-07	191	Senators	3	Monsters	4	L	X	X	Sommaire du Match
16 - 2020-11-08	203	Senators	5	Wolf Pack	7	L			Sommaire du Match
17 - 2020-11-09	214	Marlies	6	Senators	4	L			Sommaire du Match
18 - 2020-11-10	234	Senators	1	Bruins	5	L			Sommaire du Match
19 - 2020-11-11	246	Crunch	8	Senators	3	L			Sommaire du Match
20 - 2020-11-12	259	Senators	7	Devils	2	W			Sommaire du Match
21 - 2020-11-13	276	Sound Tigers	4	Senators	8	W			Sommaire du Match
23 - 2020-11-15	292	Senators	4	Checkers	7	L			Sommaire du Match
24 - 2020-11-16	304	Rocket	8	Senators	1	L			Sommaire du Match
25 - 2020-11-17	327	Penguins	7	Senators	2	L			Sommaire du Match
26 - 2020-11-18	333	Senators	4	Griffins	6	L			Sommaire du Match
27 - 2020-11-19	357	Senators	7	Sound Tigers	3	W			Sommaire du Match
28 - 2020-11-20	367	Griffins	8	Senators	6	L			Sommaire du Match
29 - 2020-11-21	375	Senators	6	Phantoms	8	L			Sommaire du Match
31 - 2020-11-23	398	Senators	0	Penguins	6	L			Sommaire du Match
32 - 2020-11-24	403	Bears	5	Senators	9	W			Sommaire du Match
33 - 2020-11-25	427	Monsters	5	Senators	2	L			Sommaire du Match
38 - 2020-11-30	451	Checkers	4	Senators	3	L			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	75	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$	1,067,500$	1,005,000$	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	7	21	0	0	0	0	2	115	188	-73	15	4	10	0	0	0	0	1	59	93	-34	15	3	11	0	0	0	0	1	56	95	-39	16	115	170	285	0	0	55	32	28	0	961	324	346	290	7	1178	321	147	498	75	9	12.00%	64	19	70.31%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142
Total Saison Régulière	30	7	21	0	0	0	0	2	115	188	-73	15	4	10	0	0	0	0	1	59	93	-34	15	3	11	0	0	0	0	1	56	95	-39	16	115	170	285	0	0	55	32	28	0	961	324	346	290	7	1178	321	147	498	75	9	12.00%	64	19	70.31%	0	358	727	49.24%	342	762	44.88%	276	552	50.00%	631	472	853	192	325	142