LHSRSM - Senators

Senateurs
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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	Matt Beleskey		X			100.00	62	49	85	61	76	78	80	62	55	59	59	63	61	80	72	0	50	63	0	31	1	3,800,000$
2	Matt Puempel		X	X		100.00	62	45	89	64	78	82	79	62	57	61	61	63	65	73	67	0	50	63	0	26	1	675,000$
3	Alex Barre-Boulet	X				100.00	51	43	89	67	56	88	91	65	63	62	64	56	67	65	63	0	50	62	0	22	2	759,258$
4	Kyle Rau	X	X			100.00	56	39	84	63	64	79	80	62	56	61	60	59	63	75	68	0	50	62	0	26	1	700,000$
5	Michael Bunting		X	X		100.00	59	48	84	63	72	76	73	61	58	62	60	59	63	69	65	0	50	62	0	24	2	737,500$
6	Paul Bittner		X			100.00	73	51	87	59	90	85	82	58	55	57	56	60	59	67	64	0	50	62	0	22	1	863,333$
7	Isac Lundestrom	X				100.00	59	38	86	63	72	79	77	62	74	61	57	59	62	61	63	0	50	61	0	19	2	925,000$
8	Graham Knott	X				100.00	67	46	88	56	83	76	78	54	51	53	52	57	56	65	63	0	50	59	0	22	1	935,833$
9	Manuel Wiederer			X		100.00	56	43	89	58	72	77	76	57	53	55	56	59	58	67	64	0	50	59	0	22	1	736,667$
10	Dylan Coghlan				X	100.00	62	45	90	59	78	87	89	58	30	57	57	60	45	63	62	0	50	61	0	21	2	715,556$
11	Jordan Schmaltz				X	100.00	62	43	89	61	80	78	72	59	30	58	57	60	51	73	67	0	50	61	0	26	1	700,000$
12	Keegan Lowe				X	100.00	63	56	81	57	79	87	89	56	30	55	51	54	46	73	77	0	50	60	0	26	1	675,000$
13	Jack Dougherty				X	100.00	64	49	85	57	80	86	88	55	30	54	53	56	45	67	64	0	50	59	0	23	1	650,000$
14	Patrick Sieloff				X	100.00	65	54	80	56	78	81	83	54	30	53	52	57	45	71	66	0	50	59	0	25	1	700,000$
Rayé

	MOYENNE D'ÉQUIPE					100.00	62	46	86	60	76	81	81	59	48	58	57	59	56	69	66	0	50	61

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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	Laurent Brossoit	100.00	81	85	83	84	80	79	81	80	79	81	80	73	77	0	50	69	0
2	Spencer Martin	100.00	68	77	75	83	67	66	68	67	66	68	67	69	73	0	50	62	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	75	81	79	84	74	73	75	74	73	75	74	71	75	0	50	66

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire

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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	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	EG	HT	P/20	PSG	PSS	FW	FT	S1	S2	S3
1	Matt Puempel	Senators (OTT)	LW/RW	48	45	38	83	44	22	0	76	105	349	66	208	12.89%	16	1091	22.73	8	3	11	48	107	0	0	0	0	5	4	3	48.89%	90	0	3	1.52	0	4	0	0	11	3	3
2	Kyle Rau	Senators (OTT)	C/LW	48	24	42	66	41	2	0	72	138	186	48	136	12.90%	14	978	20.38	2	14	16	21	107	1	1	2	8	135	3	0	50.09%	1579	1	1	1.35	1	3	0	0	3	3	4
3	Alex Barre-Boulet	Senators (OTT)	C	48	23	39	62	16	4	0	39	162	252	61	194	9.13%	18	937	19.52	4	9	13	32	97	0	0	0	0	63	2	2	50.60%	1257	0	1	1.32	0	0	0	0	3	3	1
4	Matt Beleskey	Senators (OTT)	LW	48	21	34	55	41	15	5	89	99	212	55	165	9.91%	17	968	20.19	5	11	16	23	107	1	1	2	7	128	3	0	44.33%	97	0	0	1.14	2	4	1	0	1	3	7
5	Michael Bunting	Senators (OTT)	LW/RW	48	21	31	52	16	10	0	70	91	210	53	166	10.00%	17	926	19.30	3	3	6	25	96	0	0	0	1	57	4	0	52.94%	68	0	1	1.12	2	4	0	0	4	3	2
6	Jordan Schmaltz	Senators (OTT)	D	48	11	36	47	45	22	0	103	54	97	32	73	11.34%	81	1164	24.26	5	3	8	39	102	0	0	0	0	96	1	0	0.00%	0	0	0	0.81	0	0	0	0	1	5	0
7	Dylan Coghlan	Senators (OTT)	D	48	6	35	41	44	34	0	102	57	99	34	76	6.06%	76	1159	24.15	2	5	7	45	102	0	1	1	0	92	3	0	0.00%	0	0	0	0.71	0	0	0	0	1	3	1
8	MacKenzie Entwistle	Senateurs	RW	46	16	24	40	19	15	5	110	54	178	45	128	8.99%	10	818	17.79	3	6	9	28	94	0	0	0	0	0	2	0	43.06%	72	0	1	0.98	0	0	0	1	2	3	3
9	Isac Lundestrom	Senators (OTT)	C	48	16	22	38	18	6	0	46	120	172	60	113	9.30%	12	689	14.36	0	0	0	0	0	0	0	0	0	0	2	3	58.53%	873	0	0	1.10	0	0	0	0	0	1	4
10	Keegan Lowe	Senators (OTT)	D	48	7	30	37	25	44	0	141	42	87	20	42	8.05%	83	983	20.49	2	9	11	31	102	0	0	0	0	93	1	0	0.00%	0	0	0	0.75	0	0	0	0	0	3	0
11	Manuel Wiederer	Senators (OTT)	RW	48	17	19	36	19	4	0	24	69	149	39	119	11.41%	15	690	14.39	0	0	0	0	0	0	0	0	0	0	4	1	43.55%	62	1	0	1.04	0	0	0	0	2	2	1
12	Cody McLeod	Senateurs	LW	28	9	14	23	17	23	5	78	44	89	23	64	10.11%	7	407	14.54	0	0	0	0	0	0	0	0	0	12	2	1	35.14%	37	0	1	1.13	0	0	1	0	2	2	0
13	Patrick Sieloff	Senators (OTT)	D	48	1	17	18	13	37	5	79	29	38	20	33	2.63%	55	731	15.24	0	0	0	0	0	0	0	0	0	2	0	0	0.00%	0	0	0	0.49	0	0	0	1	0	0	0
14	Sebastien Aho	Senateurs	D	18	4	11	15	9	6	0	15	26	25	11	16	16.00%	31	367	20.43	1	3	4	11	38	0	0	0	0	39	1	1	0.00%	0	0	0	0.82	0	0	0	0	0	0	0
15	Jack Dougherty	Senators (OTT)	D	48	4	10	14	12	30	0	77	21	43	9	27	9.30%	42	780	16.26	0	0	0	0	1	0	1	1	1	38	0	0	0.00%	0	0	0	0.36	0	0	0	0	0	0	1
16	Paul Bittner	Senators (OTT)	LW	48	6	5	11	6	21	5	32	17	73	14	34	8.22%	3	288	6.01	0	0	0	0	0	0	0	0	0	0	1	0	44.44%	18	0	0	0.76	0	0	0	0	0	0	1
17	Graham Knott	Senators (OTT)	C	48	1	9	10	6	2	0	19	25	30	13	28	3.33%	5	287	5.99	0	0	0	0	0	0	0	0	0	0	0	0	47.33%	393	0	0	0.70	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				764	232	416	648	391	297	25	1172	1153	2289	603	1622	10.14%	502	13268	17.37	35	66	101	303	959	2	4	6	17	766	33	11	51.17%	4546	2	8	0.98	5	15	2	2	30	34	28

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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	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Laurent Brossoit	Senators (OTT)	48	35	10	3	0.921	2.78	2811	6	3	130	1652	2	2	0.667	15	48	0	4	3	5
2	Spencer Martin	Senators (OTT)	2	0	0	0	0.947	2.05	88	0	0	3	57	0	0	0.000	0	0	48	0	0	0
Stats d'équipe Total ou en Moyenne			50	35	10	3	0.922	2.75	2900	6	3	133	1709	2	2	0.667	15	48	48	4	3	5

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Astuces sur les Filtres (Anglais seulement)

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

Nom du 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	Link
Alex Barre-Boulet	Senators (OTT)	C	22	1997-05-21	No	170 Lbs	5 ft1	No	No	No	2	Pro & Farm	759,258$	0$	0$	No	759,258$	Lien / Lien NHL
Dylan Coghlan	Senators (OTT)	D	21	1998-02-19	No	190 Lbs	6 ft2	No	No	No	2	Pro & Farm	715,556$	0$	0$	No	715,556$	Lien / Lien NHL
Graham Knott	Senators (OTT)	C	22	1997-01-13	No	199 Lbs	6 ft3	No	No	No	1	Pro & Farm	935,833$	0$	0$	No		Lien / Lien NHL
Isac Lundestrom	Senators (OTT)	C	19	1999-11-06	No	187 Lbs	6 ft0	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$	Lien / Lien NHL
Jack Dougherty	Senators (OTT)	D	23	1996-05-25	No	196 Lbs	6 ft2	No	No	No	1	Pro & Farm	650,000$	0$	0$	No		Lien / Lien NHL
Jordan Schmaltz	Senators (OTT)	D	26	1993-10-08	No	196 Lbs	6 ft2	No	No	No	1	Pro & Farm	700,000$	0$	0$	No		Lien / Lien NHL
Keegan Lowe	Senators (OTT)	D	26	1993-03-29	No	191 Lbs	6 ft2	No	No	No	1	Pro & Farm	675,000$	0$	0$	No		Lien / Lien NHL
Kyle Rau	Senators (OTT)	C/LW	26	1992-10-24	No	176 Lbs	5 ft8	No	No	No	1	Pro & Farm	700,000$	0$	0$	No		Lien / Lien NHL
Laurent Brossoit	Senators (OTT)	G	26	1993-03-23	No	204 Lbs	6 ft3	No	No	No	1	Pro & Farm	1,225,000$	0$	0$	No		Lien / Lien NHL
Manuel Wiederer	Senators (OTT)	RW	22	1996-11-21	No	175 Lbs	6 ft1	No	No	No	1	Pro & Farm	736,667$	0$	0$	No		Lien / Lien NHL
Matt Beleskey	Senators (OTT)	LW	31	1988-06-07	No	207 Lbs	6 ft0	No	No	No	1	Pro & Farm	3,800,000$	0$	0$	No		Lien / Lien NHL
Matt Puempel	Senators (OTT)	LW/RW	26	1993-01-24	No	201 Lbs	6 ft1	No	No	No	1	Pro & Farm	675,000$	0$	0$	No		Lien / Lien NHL
Michael Bunting	Senators (OTT)	LW/RW	24	1995-09-17	No	197 Lbs	5 ft11	No	No	No	2	Pro & Farm	737,500$	0$	0$	No	737,500$	Lien / Lien NHL
Patrick Sieloff	Senators (OTT)	D	25	1994-05-15	No	205 Lbs	6 ft1	No	No	No	1	Pro & Farm	700,000$	0$	0$	No		Lien / Lien NHL
Paul Bittner	Senators (OTT)	LW	22	1996-11-04	No	205 Lbs	6 ft5	No	No	No	1	Pro & Farm	863,333$	0$	0$	No		Lien
Spencer Martin	Senators (OTT)	G	24	1995-06-08	No	200 Lbs	6 ft3	No	No	No	1	Pro & Farm	700,000$	0$	0$	No		Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
16	24.06	194 Lbs	6 ft1	1.25	968,634$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Matt Beleskey	Kyle Rau	Matt Puempel	35	1	0	4
2	Michael Bunting	Alex Barre-Boulet		27	1	1	3
3		Isac Lundestrom	Manuel Wiederer	23	1	3	1
4	Paul Bittner	Graham Knott	Matt Puempel	15	1	4	0

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dylan Coghlan	Jordan Schmaltz	35	1	3	1
2		Keegan Lowe	26	1	3	1
3	Jack Dougherty	Patrick Sieloff	24	1	3	1
4	Dylan Coghlan	Jordan Schmaltz	15	1	3	1

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Matt Beleskey	Kyle Rau	Matt Puempel	60	1	0	4
2	Michael Bunting	Alex Barre-Boulet		40	1	0	4

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dylan Coghlan	Jordan Schmaltz	60	1	0	4
2		Keegan Lowe	40	1	0	4

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Kyle Rau	Matt Beleskey	60	1	4	0
2	Alex Barre-Boulet	Michael Bunting	40	1	4	0

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dylan Coghlan	Jordan Schmaltz	60	1	4	0
2		Keegan Lowe	40	1	4	0

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Kyle Rau	60	1	4	0	Dylan Coghlan	Jordan Schmaltz	60	1	4	0
2	Alex Barre-Boulet	40	1	4	0		Keegan Lowe	40	1	4	0

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Kyle Rau	Matt Beleskey	60	1	2	2
2	Alex Barre-Boulet	Michael Bunting	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dylan Coghlan	Jordan Schmaltz	60	1	2	2
2		Keegan Lowe	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Matt Beleskey	Kyle Rau	Matt Puempel	Dylan Coghlan	Jordan Schmaltz

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Matt Beleskey	Kyle Rau	Matt Puempel	Dylan Coghlan	Jordan Schmaltz

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, Paul Bittner, Alex Barre-Boulet	, Paul Bittner

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Keegan Lowe, Jack Dougherty, Patrick Sieloff	Keegan Lowe	Keegan Lowe, Jack Dougherty

Tirs de Pénalité
Matt Puempel, Matt Beleskey, Michael Bunting, Kyle Rau,

Gardien
#1 : Laurent Brossoit, #2 : Spencer Martin

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	Admirals	1	1	0	0	0	0	0	0	7	3	4	1	1	0	0	0	0	0	0	7	3	4	0	0	0	0	0	0	0	0	0	0	0	2	1.000	7	12	19	0	0	103	70	60	5	57	731	724	855	25	39	9	4	34	3	1	33.33%	2	0	100.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
2	Americans	1	1	0	0	0	0	0	0	9	2	7	1	1	0	0	0	0	0	0	9	2	7	0	0	0	0	0	0	0	0	0	0	0	2	1.000	9	15	24	0	0	103	70	60	5	52	731	724	855	25	43	18	10	32	2	2	100.00%	5	1	80.00%	1	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
3	Barracuda	1	1	0	0	0	0	0	0	6	1	5	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	6	1	5	2	1.000	6	11	17	0	0	103	70	60	5	27	731	724	855	25	34	6	4	13	1	0	0.00%	2	0	100.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
4	Bears	2	1	1	0	0	0	0	0	11	6	5	1	0	1	0	0	0	0	0	3	5	-2	1	1	0	0	0	0	0	0	8	1	7	2	0.500	11	18	29	0	0	103	70	60	5	119	731	724	855	25	63	15	7	50	1	1	100.00%	1	0	100.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
5	Bruins	4	3	0	0	0	1	0	0	16	5	11	2	1	0	0	0	1	0	0	6	5	1	2	2	0	0	0	0	0	0	10	0	10	7	0.875	16	27	43	0	2	103	70	60	5	163	731	724	855	25	144	49	18	91	15	1	6.67%	9	0	100.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
6	Checkers	2	1	1	0	0	0	0	0	9	9	0	2	1	1	0	0	0	0	0	9	9	0	0	0	0	0	0	0	0	0	0	0	0	2	0.500	9	14	23	0	0	103	70	60	5	104	731	724	855	25	53	14	8	49	6	1	16.67%	4	2	50.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
7	Comets	2	2	0	0	0	0	0	0	18	3	15	1	1	0	0	0	0	0	0	10	1	9	1	1	0	0	0	0	0	0	8	2	6	4	1.000	18	33	51	0	0	103	70	60	5	173	731	724	855	25	44	15	4	54	2	1	50.00%	2	0	100.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
8	Condors	1	1	0	0	0	0	0	0	10	3	7	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	10	3	7	2	1.000	10	18	28	0	0	103	70	60	5	89	731	724	855	25	29	5	2	19	1	0	0.00%	0	0	0.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
9	Crunch	3	1	2	0	0	0	0	0	11	14	-3	2	0	2	0	0	0	0	0	5	9	-4	1	1	0	0	0	0	0	0	6	5	1	2	0.333	11	19	30	0	0	103	70	60	5	114	731	724	855	25	140	55	24	64	9	4	44.44%	12	1	91.67%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
10	Devils	2	1	0	0	0	0	1	0	9	6	3	1	1	0	0	0	0	0	0	5	3	2	1	0	0	0	0	0	1	0	4	3	1	4	1.000	9	16	25	0	0	103	70	60	5	89	731	724	855	25	92	32	14	54	5	1	20.00%	7	1	85.71%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
11	Eagles	2	2	0	0	0	0	0	0	13	3	10	1	1	0	0	0	0	0	0	5	3	2	1	1	0	0	0	0	0	0	8	0	8	4	1.000	13	26	39	0	1	103	70	60	5	93	731	724	855	25	71	15	10	53	3	2	66.67%	3	1	66.67%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
12	Griffins	2	0	2	0	0	0	0	0	5	8	-3	2	0	2	0	0	0	0	0	5	8	-3	0	0	0	0	0	0	0	0	0	0	0	0	0.000	5	9	14	1	0	103	70	60	5	92	731	724	855	25	64	25	19	61	7	2	28.57%	7	2	71.43%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
13	Heat	3	2	1	0	0	0	0	0	15	11	4	1	0	1	0	0	0	0	0	1	5	-4	2	2	0	0	0	0	0	0	14	6	8	4	0.667	15	28	43	0	0	103	70	60	5	180	731	724	855	25	116	30	15	75	6	3	50.00%	4	2	50.00%	1	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
14	IceHogs	1	0	1	0	0	0	0	0	3	5	-2	1	0	1	0	0	0	0	0	3	5	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	3	5	8	0	0	103	70	60	5	21	731	724	855	25	53	9	10	25	1	0	0.00%	5	2	60.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
15	Marlies	3	2	0	0	0	0	1	0	13	9	4	1	0	0	0	0	0	1	0	4	3	1	2	2	0	0	0	0	0	0	9	6	3	6	1.000	13	24	37	0	0	103	70	60	5	126	731	724	855	25	109	44	22	80	5	0	0.00%	10	1	90.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
16	Monsters	3	2	0	0	0	0	0	1	17	12	5	1	1	0	0	0	0	0	0	5	4	1	2	1	0	0	0	0	0	1	12	8	4	5	0.833	17	30	47	0	0	103	70	60	5	139	731	724	855	25	86	29	18	54	12	6	50.00%	7	2	71.43%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
17	Moose	2	2	0	0	0	0	0	0	14	6	8	1	1	0	0	0	0	0	0	10	3	7	1	1	0	0	0	0	0	0	4	3	1	4	1.000	14	23	37	0	0	103	70	60	5	118	731	724	855	25	62	22	8	62	1	0	0.00%	4	2	50.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
18	Penguins	1	1	0	0	0	0	0	0	9	5	4	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	9	5	4	2	1.000	9	18	27	0	0	103	70	60	5	59	731	724	855	25	45	10	0	20	3	2	66.67%	0	0	0.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
19	Phantoms	1	0	1	0	0	0	0	0	1	3	-2	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	1	2	3	1	0	103	70	60	5	47	731	724	855	25	43	11	12	30	3	0	0.00%	5	1	80.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
20	Rampage	1	1	0	0	0	0	0	0	4	2	2	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	4	2	2	2	1.000	4	8	12	0	0	103	70	60	5	44	731	724	855	25	43	12	6	26	4	1	25.00%	3	0	100.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
21	Reign	1	1	0	0	0	0	0	0	4	3	1	1	1	0	0	0	0	0	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	4	6	10	0	0	103	70	60	5	35	731	724	855	25	39	6	4	24	4	2	50.00%	2	0	100.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
22	Roadrunners	1	1	0	0	0	0	0	0	2	1	1	1	1	0	0	0	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	2	3	5	0	0	103	70	60	5	40	731	724	855	25	37	6	6	16	4	0	0.00%	2	0	100.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
23	Rocket	2	1	1	0	0	0	0	0	5	4	1	1	0	1	0	0	0	0	0	2	3	-1	1	1	0	0	0	0	0	0	3	1	2	2	0.500	5	9	14	0	0	103	70	60	5	57	731	724	855	25	64	17	38	48	3	0	0.00%	9	1	88.89%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
24	Sound Tigers	2	1	0	0	0	0	0	1	7	7	0	0	0	0	0	0	0	0	0	0	0	0	2	1	0	0	0	0	0	1	7	7	0	3	0.750	7	14	21	0	0	103	70	60	5	72	731	724	855	25	74	21	16	55	7	1	14.29%	5	0	100.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
25	Thunderbirds	2	2	0	0	0	0	0	0	9	3	6	1	1	0	0	0	0	0	0	5	2	3	1	1	0	0	0	0	0	0	4	1	3	4	1.000	9	17	26	0	0	103	70	60	5	85	731	724	855	25	68	18	12	49	9	3	33.33%	4	0	100.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
	Total	49	33	11	0	0	1	2	2	235	150	85	24	12	10	0	0	1	1	0	101	90	11	25	21	1	0	0	0	1	2	134	60	74	73	0.745	235	418	653	2	3	103	70	60	5	2320	731	724	855	25	1792	542	307	1193	130	35	26.92%	121	21	82.64%	2	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
26	Wild	1	1	0	0	0	0	0	0	4	1	3	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	4	1	3	2	1.000	4	6	10	0	0	103	70	60	5	40	731	724	855	25	30	7	4	26	4	1	25.00%	2	0	100.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
27	Wolf Pack	1	0	1	0	0	0	0	0	1	13	-12	1	0	1	0	0	0	0	0	1	13	-12	0	0	0	0	0	0	0	0	0	0	0	0	0.000	1	2	3	0	0	103	70	60	5	29	731	724	855	25	81	34	4	14	2	0	0.00%	1	1	0.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
28	Wolves	1	1	0	0	0	0	0	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	3	2	1	2	1.000	3	5	8	0	0	103	70	60	5	56	731	724	855	25	26	8	8	15	7	0	0.00%	4	1	75.00%	0	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
	_Since Last GM Reset	49	33	11	0	0	1	2	2	235	150	85	24	12	10	0	0	1	1	0	101	90	11	25	21	1	0	0	0	1	2	134	60	74	73	0.745	235	418	653	2	3	103	70	60	5	2320	731	724	855	25	1792	542	307	1193	130	35	26.92%	121	21	82.64%	2	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
	_Vs Conference	28	17	7	0	0	1	2	1	128	89	39	14	6	6	0	0	1	1	0	59	55	4	14	11	1	0	0	0	1	1	69	34	35	40	0.714	128	228	356	1	2	103	70	60	5	1289	731	724	855	25	1063	353	189	690	72	17	23.61%	74	9	87.84%	1	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
	_Vs Division	17	8	3	0	0	0	2	0	68	45	23	10	3	3	0	0	0	1	0	36	32	4	7	5	0	0	0	0	1	0	32	13	19	20	0.588	68	120	188	1	2	103	70	60	5	689	731	724	855	25	632	226	143	425	50	12	24.00%	56	6	89.29%	1	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312

			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
49	73	W1	235	418	653	2320	1792	542	307	1193	2	3

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
49	33	11	0	1	2	2	235	150

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
24	12	10	0	1	1	0	101	90

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
25	21	1	0	0	1	2	134	60

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
7	2	0	0	0	1

Tentatives en Avantage Numérique	Buts en Avantage Numérique	% en Avantage Numérique	Tentatives en Désavantage Numérique	Buts Contre en Désavantage Numérique	% en Désavantage Numérique	Buts Pour en Désavantage Numérique
130	35	26.92%	121	21	82.64%	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
731	724	855	25	103	70	60	5

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
1068	2045	52.22%	863	1767	48.84%	417	844	49.41%

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
1234	892	1118	332	611	312

Derniers Match Joués Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

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

Jour	Match	Équipe Visiteuse	Score	Équipe Locale	Score	ST	OT	SO	Lien
2 - 2020-10-06	7	Wolf Pack	13	Senators	1	L			Sommaire du Match
4 - 2020-10-08	30	Senators	4	Bruins	0	W			Sommaire du Match
6 - 2020-10-10	39	Crunch	6	Senators	3	L			Sommaire du Match
8 - 2020-10-12	57	Senators	6	Bruins	0	W			Sommaire du Match
10 - 2020-10-14	71	IceHogs	5	Senators	3	L			Sommaire du Match
12 - 2020-10-16	84	Senators	3	Rocket	1	W			Sommaire du Match
14 - 2020-10-18	101	Roadrunners	1	Senators	2	W			Sommaire du Match
16 - 2020-10-20	115	Senators	3	Sound Tigers	2	W			Sommaire du Match
18 - 2020-10-22	126	Senators	4	Marlies	3	W			Sommaire du Match
20 - 2020-10-24	139	Senators	4	Thunderbirds	1	W			Sommaire du Match
21 - 2020-10-25	152	Checkers	5	Senators	6	W			Sommaire du Match
24 - 2020-10-28	169	Senators	8	Bears	1	W			Sommaire du Match
25 - 2020-10-29	179	Senators	1	Phantoms	3	L			Sommaire du Match
27 - 2020-10-31	189	Americans	2	Senators	9	W			Sommaire du Match
30 - 2020-11-03	211	Griffins	5	Senators	3	L			Sommaire du Match
31 - 2020-11-04	223	Senators	9	Heat	5	W			Sommaire du Match
34 - 2020-11-07	244	Bruins	4	Senators	3	L	X		Sommaire du Match
35 - 2020-11-08	254	Senators	4	Monsters	5	L	X	X	Sommaire du Match
38 - 2020-11-11	272	Moose	3	Senators	10	W			Sommaire du Match
40 - 2020-11-13	290	Senators	3	Wolves	2	W			Sommaire du Match
41 - 2020-11-14	299	Senators	6	Crunch	5	W			Sommaire du Match
43 - 2020-11-16	310	Reign	3	Senators	4	W			Sommaire du Match
46 - 2020-11-19	329	Senators	4	Wild	1	W			Sommaire du Match
47 - 2020-11-20	340	Admirals	3	Senators	7	W			Sommaire du Match
50 - 2020-11-23	365	Eagles	3	Senators	5	W			Sommaire du Match
52 - 2020-11-25	375	Senators	8	Eagles	0	W			Sommaire du Match
54 - 2020-11-27	394	Marlies	3	Senators	4	W	X	X	Sommaire du Match
57 - 2020-11-30	414	Senators	4	Moose	3	W			Sommaire du Match
58 - 2020-12-01	427	Rocket	3	Senators	2	L			Sommaire du Match
61 - 2020-12-04	447	Senators	4	Devils	3	W	X	X	Sommaire du Match
62 - 2020-12-05	458	Monsters	4	Senators	5	W			Sommaire du Match
66 - 2020-12-09	483	Heat	5	Senators	1	L			Sommaire du Match
68 - 2020-12-11	496	Senators	10	Condors	3	W			Sommaire du Match
70 - 2020-12-13	511	Senators	8	Comets	2	W			Sommaire du Match
71 - 2020-12-14	520	Bears	5	Senators	3	L			Sommaire du Match
74 - 2020-12-17	542	Griffins	3	Senators	2	L			Sommaire du Match
76 - 2020-12-19	554	Senators	9	Penguins	5	W			Sommaire du Match
79 - 2020-12-22	577	Thunderbirds	2	Senators	5	W			Sommaire du Match
81 - 2020-12-24	587	Senators	8	Monsters	3	W			Sommaire du Match
83 - 2020-12-26	600	Senators	4	Sound Tigers	5	L	X	X	Sommaire du Match
84 - 2020-12-27	615	Checkers	4	Senators	3	L			Sommaire du Match
87 - 2020-12-30	631	Senators	6	Barracuda	1	W			Sommaire du Match
88 - 2020-12-31	644	Bruins	1	Senators	3	W			Sommaire du Match
91 - 2021-01-03	660	Senators	4	Rampage	2	W			Sommaire du Match
92 - 2021-01-04	674	Devils	3	Senators	5	W			Sommaire du Match
96 - 2021-01-08	700	Comets	1	Senators	10	W			Sommaire du Match
99 - 2021-01-11	718	Senators	5	Marlies	3	W			Sommaire du Match
101 - 2021-01-13	731	Crunch	3	Senators	2	L			Sommaire du Match
102 - 2021-01-14	746	Senators	5	Heat	1	W			Sommaire du Match
104 - 2021-01-16	762	Americans	-	Senators	-
107 - 2021-01-19	775	Senators	-	Rocket	-
109 - 2021-01-21	788	Senators	-	Reign	-
111 - 2021-01-23	800	Penguins	-	Senators	-
113 - 2021-01-25	816	Senators	-	Bears	-
114 - 2021-01-26	829	Senators	-	Americans	-
116 - 2021-01-28	835	Stars	-	Senators	-
119 - 2021-01-31	857	Senators	-	Gulls	-
120 - 2021-02-01	865	Condors	-	Senators	-
123 - 2021-02-04	883	Senators	-	Phantoms	-
125 - 2021-02-06	896	Wild	-	Senators	-
127 - 2021-02-08	912	Senators	-	Stars	-
129 - 2021-02-10	924	Phantoms	-	Senators	-
132 - 2021-02-13	948	Senators	-	IceHogs	-
134 - 2021-02-15	957	Roadrunners	-	Senators	-
136 - 2021-02-17	972	Senators	-	Thunderbirds	-
138 - 2021-02-19	986	Wolves	-	Senators	-
139 - 2021-02-20	1002	Senators	-	Roadrunners	-
142 - 2021-02-23	1020	Senators	-	Checkers	-
143 - 2021-02-24	1028	Sound Tigers	-	Senators	-
146 - 2021-02-27	1049	Gulls	-	Senators	-
148 - 2021-03-01	1064	Senators	-	Bruins	-
150 - 2021-03-03	1081	Wolf Pack	-	Senators	-
153 - 2021-03-06	1100	Senators	-	Wolf Pack	-
155 - 2021-03-08	1114	Wolf Pack	-	Senators	-
158 - 2021-03-11	1137	Rampage	-	Senators	-
160 - 2021-03-13	1152	Senators	-	Admirals	-
162 - 2021-03-15	1169	Penguins	-	Senators	-
167 - 2021-03-20	1197	IceHogs	-	Senators	-
169 - 2021-03-22	1207	Senators	-	Griffins	-
173 - 2021-03-26	1227	Barracuda	-	Senators	-
174 - 2021-03-27	1234	Senators	-	Wolf Pack	-
180 - 2021-04-02	1266	Devils	-	Senators	-

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
17	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
954,706$	1,549,815$	1,132,232$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	954,706$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	80	8,515$	681,200$

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
2	82	43	25	0	2	4	4	4	286	234	52	41	24	9	0	0	1	4	3	143	116	27	41	19	16	0	2	3	0	1	143	118	25	86	286	498	784	3	6	101	101	78	9	2653	844	855	923	56	2587	729	922	1501	346	73	21.10%	371	67	81.94%	6	1454	2735	53.16%	1386	2728	50.81%	652	1313	49.66%	1986	1360	1924	619	1065	530
3	82	52	23	0	1	1	3	2	265	166	99	41	26	12	0	0	1	1	1	137	83	54	41	26	11	0	1	0	2	1	128	83	45	104	265	459	724	0	10	93	84	84	6	3046	1013	1046	972	30	2220	662	1041	1653	366	75	20.49%	417	63	84.89%	6	1982	3153	62.86%	1588	2756	57.62%	723	1193	60.60%	2171	1523	1744	590	1033	539
4	82	45	20	0	1	1	7	8	266	189	77	41	22	11	0	0	1	5	2	131	89	42	41	23	9	0	1	0	2	6	135	100	35	90	266	482	748	1	9	102	95	61	15	3004	968	1055	937	99	2226	716	1505	1986	615	88	14.31%	603	90	85.07%	10	1837	3353	54.79%	1646	2939	56.01%	713	1260	56.59%	2121	1438	1822	650	1059	542
5	82	54	21	0	2	0	4	1	318	172	146	41	29	8	0	1	0	2	1	169	77	92	41	25	13	0	1	0	2	0	149	95	54	108	318	560	878	0	13	114	113	85	11	3212	1017	1068	1110	33	2191	648	580	2083	221	45	20.36%	260	42	83.85%	2	1864	3051	61.09%	1543	2591	59.55%	743	1285	57.82%	2222	1627	1714	544	1009	530
6	82	54	14	0	4	2	4	4	397	199	198	41	30	5	0	2	1	1	2	197	80	117	41	24	9	0	2	1	3	2	200	119	81	108	397	718	1115	0	10	166	120	103	14	4191	1359	1361	1427	78	2380	648	523	1989	276	61	22.10%	241	43	82.16%	2	2250	3527	63.79%	1518	2546	59.62%	827	1357	60.94%	2405	1805	1586	528	987	528
7	82	33	33	0	2	5	2	7	297	291	6	41	13	18	0	2	2	1	5	133	150	-17	41	20	15	0	0	3	1	2	164	141	23	66	297	485	782	4	1	122	97	74	8	3550	1153	1173	1180	78	4140	1227	417	2092	187	33	17.65%	185	38	79.46%	1	1461	3090	47.28%	1656	3898	42.48%	661	1376	48.04%	1750	1251	2270	570	960	449
8	82	8	73	0	0	1	0	0	239	644	-405	41	5	36	0	0	0	0	0	123	308	-185	41	3	37	0	0	1	0	0	116	336	-220	16	239	402	641	0	0	124	70	45	0	3066	1032	1010	1024	0	5769	1620	254	1847	149	16	10.74%	109	44	59.63%	0	906	2452	36.95%	1101	3323	33.13%	534	1568	34.06%	1255	864	2764	562	900	365
8	82	8	73	0	0	1	0	0	239	644	-405	41	5	36	0	0	0	0	0	123	308	-185	41	3	37	0	0	1	0	0	116	336	-220	16	239	402	641	0	0	124	70	45	0	3066	1032	1010	1024	0	5769	1620	254	1847	149	16	10.74%	109	44	59.63%	0	906	2452	36.95%	1101	3323	33.13%	534	1568	34.06%	1255	864	2764	562	900	365
9	49	33	11	0	0	1	2	2	235	150	85	24	12	10	0	0	1	1	0	101	90	11	25	21	1	0	0	0	1	2	134	60	74	73	235	418	653	2	3	103	70	60	5	2320	731	724	855	25	1792	542	307	1193	130	35	26.92%	121	21	82.64%	2	1068	2045	52.22%	863	1767	48.84%	417	844	49.41%	1234	892	1118	332	611	312
Total Saison Régulière	705	330	293	0	12	16	26	28	2542	2689	-147	352	166	145	0	5	7	15	14	1257	1301	-44	353	164	148	0	7	9	11	14	1285	1388	-103	667	2542	4424	6966	10	52	1049	820	635	68	28108	9149	9302	9452	399	29074	8412	5803	16191	2439	442	18.12%	2416	452	81.29%	29	13728	25858	53.09%	12402	25871	47.94%	5804	11764	49.34%	16403	11627	17710	4963	8527	4163
Séries
2	5	1	4	0	0	0	0	0	13	19	-6	2	1	1	0	0	0	0	0	8	8	0	3	0	3	0	0	0	0	0	5	11	-6	2	13	25	38	0	0	4	5	3	1	159	44	52	57	6	173	47	30	85	34	4	11.76%	12	5	58.33%	0	71	164	43.29%	61	151	40.40%	39	92	42.39%	120	83	121	38	69	34
3	6	2	4	0	0	0	0	0	10	12	-2	3	1	2	0	0	0	0	0	6	8	-2	3	1	2	0	0	0	0	0	4	4	0	4	10	17	27	0	2	3	4	3	0	193	63	65	65	0	178	46	75	142	20	1	5.00%	37	5	86.49%	0	104	215	48.37%	116	217	53.46%	39	78	50.00%	136	90	145	48	77	37
4	5	1	4	0	0	0	0	0	10	14	-4	3	1	2	0	0	0	0	0	6	8	-2	2	0	2	0	0	0	0	0	4	6	-2	2	10	19	29	0	0	3	3	4	0	168	54	49	47	18	173	48	105	128	46	5	10.87%	38	3	92.11%	0	107	208	51.44%	106	216	49.07%	38	74	51.35%	132	88	129	46	70	36
5	23	16	7	0	0	0	0	0	72	59	13	12	9	3	0	0	0	0	0	41	31	10	11	7	4	0	0	0	0	0	31	28	3	32	72	126	198	0	1	28	26	16	2	740	235	270	222	13	685	202	177	552	99	12	12.12%	82	14	82.93%	2	425	820	51.83%	446	832	53.61%	164	357	45.94%	570	395	539	180	299	149
6	13	8	5	0	0	0	0	0	39	42	-3	7	5	2	0	0	0	0	0	20	20	0	6	3	3	0	0	0	0	0	19	22	-3	16	39	68	107	0	0	12	14	12	1	497	169	174	150	4	401	114	84	325	46	10	21.74%	40	7	82.50%	0	313	549	57.01%	246	445	55.28%	116	199	58.29%	337	239	283	92	161	82
Total Séries	52	28	24	0	0	0	0	0	144	146	-2	27	17	10	0	0	0	0	0	81	75	6	25	11	14	0	0	0	0	0	63	71	-8	56	144	255	399	0	3	50	52	38	4	1757	565	610	541	41	1610	457	471	1232	245	32	13.06%	209	34	83.73%	2	1020	1956	52.15%	975	1861	52.39%	396	800	49.50%	1298	896	1219	406	678	340