Profi League - Senators

Senators
Formation
Points
Informations Joueurs
Lignes
Statistiques d'Équipe
Calendrier
Finance
Profondeur
Historique
Blessure/Suspension

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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	Jonathan Toews (C)	X				100.00	61	40	92	83	85	94	92	89	90	55	52	69	73	90	99	0	48	74	0
2	Jason Chimera		X	X		100.00	72	37	93	74	83	79	99	81	56	44	49	68	59	99	99	0	48	71	0
3	Zach Parise (A)		X			100.00	62	30	93	79	82	89	88	85	61	49	52	68	62	95	99	0	48	71	0
4	Kyle Turris	X				100.00	58	34	91	79	82	92	91	84	86	49	53	63	79	83	88	0	48	71	0
5	Leo Komarov		X			100.00	88	34	94	73	82	86	95	82	69	45	47	73	59	71	76	0	48	70	0
6	Nick Bonino	X				100.00	61	32	96	73	80	85	93	82	83	46	48	77	60	79	79	0	48	69	0
7	Tyler Toffoli (R)	X		X		100.00	63	30	95	77	82	85	86	83	52	47	51	68	59	74	74	0	48	68	0
8	Mikkel Boedker		X	X		100.00	63	30	97	74	81	82	96	79	48	46	45	65	64	84	84	0	48	68	0
9	Robby Fabbri (R)		X			100.00	65	37	93	74	80	81	77	82	55	48	48	60	58	61	61	0	48	65	0
10	Brad Richardson	X	X	X		100.00	63	40	88	69	74	83	66	73	77	43	47	71	57	86	86	0	48	65	0
11	Lance Bouma	X	X			100.00	75	43	91	64	74	74	79	72	51	39	39	71	57	75	75	0	48	63	0
12	Tom Kuhnhackl (R)		X	X		100.00	63	30	94	68	75	72	73	76	50	44	41	71	57	59	59	0	48	62	0
13	Alex Pietrangelo (A)				X	100.00	68	30	95	86	87	93	96	89	34	52	46	82	61	83	98	0	48	77	0
14	Jake Muzzin				X	100.00	81	32	91	81	85	90	99	85	34	47	44	78	60	78	78	0	48	74	0
15	Radko Gudas				X	100.00	95	50	80	76	81	86	86	80	34	46	42	79	59	72	72	0	48	72	0
16	Jay Bouwmeester				X	100.00	70	30	95	71	80	90	96	79	34	44	38	80	57	99	99	0	48	72	0
17	Matt Irwin				X	100.00	77	30	95	71	78	83	83	76	33	42	40	77	57	69	69	0	48	68	0
Rayé
1	Niklas Kronwall				X	72.75	75	30	92	75	79	88	80	81	34	45	39	75	58	94	99	0	37	71	0

	MOYENNE D'ÉQUIPE					98.44	70	34	93	75	81	85	88	81	55	46	46	72	61	81	83	0	47	70

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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	Cory Schneider	100.00	75	96	98	89	73	74	75	74	73	73	83	83	83	0	48	79	0
2	Thomas Greiss	99.00	76	96	89	85	73	77	77	78	78	76	84	80	80	0	48	79	0
Rayé

	MOYENNE D'ÉQUIPE	99.50	76	96	94	87	73	76	76	76	76	75	84	82	82	0	48	79

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Peter Laviolette	82	84	92	85	85	81	66	USA	52	3	1,000,000$

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	SHT	OSB	OSM	SHT%	SB	MP	PPG	PKA	PKP	PKM	GW	FO%	FOT	GA	TA	EG	HT	P/20	PSG
1	Jonathan Toews	Senators	C	4	2	3	5	0	0	0	3	14	2	5	14.29%	4	18.:.57	0	0	0	0	0	57.63%	59	7	0	0	0	1.32	0
2	Zach Parise	Senators	LW	4	2	2	4	0	0	0	1	10	3	4	20.00%	2	18.:.44	0	0	0	0	0	50.00%	2	9	2	0	0	1.07	0
3	Tyler Toffoli	Senators	C/RW	4	2	1	3	1	0	0	2	10	1	7	20.00%	3	18.:.34	0	0	0	0	1	50.00%	2	3	2	0	0	0.81	0
4	Jay Bouwmeester	Senators	D	4	0	2	2	-2	0	0	8	6	3	3	0.00%	5	20.:.53	0	0	0	0	0	0.00%	0	0	4	0	0	0.48	0
5	Leo Komarov	Senators	LW	4	1	1	2	-5	0	0	7	15	3	9	6.67%	2	14.:.08	0	0	0	1	0	100.00%	1	5	2	0	0	0.71	0
6	Jake Muzzin	Senators	D	4	0	2	2	4	0	0	7	8	4	2	0.00%	9	21.:.40	0	0	0	0	0	0.00%	0	3	2	0	0	0.46	0
7	Robby Fabbri	Senators	LW	4	1	0	1	0	0	0	6	7	2	4	14.29%	3	16.:.37	0	0	0	0	0	33.33%	3	6	1	0	0	0.30	0
8	Radko Gudas	Senators	D	4	0	1	1	-4	2	0	18	2	0	3	0.00%	7	21.:.47	0	0	0	1	0	0.00%	0	0	7	0	0	0.23	0
9	Kyle Turris	Senators	C	4	0	1	1	0	0	0	4	7	7	10	0.00%	1	16.:.37	0	0	0	0	0	41.30%	46	7	2	0	0	0.30	0
10	Tom Kuhnhackl	Senators	LW/RW	4	0	1	1	0	0	0	3	3	1	3	0.00%	1	11.:.54	0	0	0	0	0	0.00%	1	1	0	0	0	0.42	0
11	Nick Bonino	Senators	C	4	1	0	1	-5	0	0	0	7	3	5	14.29%	0	13.:.55	0	0	0	1	0	47.06%	34	2	0	0	0	0.36	0
12	Jason Chimera	Senators	LW/RW	4	0	0	0	-1	0	0	7	7	1	4	0.00%	4	17.:.00	0	0	0	0	0	50.00%	2	1	0	0	0	0.00	0
13	Niklas Kronwall	Senators	D	4	0	0	0	0	0	0	7	4	1	3	0.00%	3	14.:.08	0	0	0	0	0	0.00%	0	0	2	0	0	0.00	0
14	Brad Richardson	Senators	C/LW/RW	4	0	0	0	-1	0	0	3	5	0	3	0.00%	2	10.:.29	0	0	0	0	0	34.48%	29	2	2	0	0	0.00	0
15	Mikkel Boedker	Senators	LW/RW	4	0	0	0	-6	0	0	1	5	2	7	0.00%	1	12.:.14	0	0	0	0	0	0.00%	3	4	0	0	0	0.00	0
16	Alex Pietrangelo	Senators	D	4	0	0	0	-9	0	0	6	13	8	9	0.00%	13	24.:.17	0	0	0	1	0	0.00%	0	3	8	0	0	0.00	0
17	Matt Irwin	Senators	D	4	0	0	0	-1	2	0	6	2	2	4	0.00%	7	17.:.12	0	0	0	0	0	0.00%	0	0	5	0	0	0.00	0
18	Lance Bouma	Senators	C/LW	4	0	0	0	-1	0	0	5	4	0	0	0.00%	1	10.:.21	0	0	0	0	0	0.00%	0	1	1	0	0	0.00	0
Stats d'équipe Total ou en Moyenne			72	9	14	23	-30	4	0	94	74	129	43	85	6.98%	68	1198	16.64	6	39	0	0	0	6	1	0	46.15%	182	54	40	0	0.38	0	0	0	0	0	0	1	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	PCT	GAA	MP	GA	SA	SAR	PS %	ST	BG	S1
1	Cory Schneider	Senators	2	1	0	91.2%	3.87	93	6	68	46	0.0%	2	2	1
2	Thomas Greiss	Senators	3	0	3	86.7%	4.55	145	11	83	47	0.0%	2	2	0
Stats d'équipe Total ou en Moyenne			5	1	3	0.887	4.27	239	17	151	93	0.000	4	4	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	Status	Type	Salaire Actuel	Salaire Restant	Salaire Année 2	Salaire Année 3
Alex Pietrangelo	Senators	D	27	18.01.1990	No	205 Lbs	6 ft3	Yes	No	No	3	Sans Restriction	Pro & Farm	5,400,000$	5,400,000$	5,400,000$	5,400,000$
Brad Richardson	Senators	C/LW/RW	32	04.02.1985	No	197 Lbs	6 ft0	No	No	No	1	Sans Restriction	Pro Only	1,500,000$	1,500,000$
Cory Schneider	Senators	G	31	18.03.1986	No	200 Lbs	6 ft2	Yes	No	No	3	Sans Restriction	Pro & Farm	6,200,000$	6,200,000$	6,200,000$	6,200,000$
Jake Muzzin	Senators	D	28	21.02.1989	No	216 Lbs	6 ft3	No	No	No	2	Sans Restriction	Pro & Farm	3,500,000$	3,500,000$	3,500,000$
Jason Chimera	Senators	LW/RW	38	02.05.1979	No	216 Lbs	6 ft3	No	No	No	2	Sans Restriction	Pro & Farm	2,100,000$	2,100,000$	2,100,000$
Jay Bouwmeester	Senators	D	34	27.09.1983	No	221 Lbs	6 ft4	Yes	No	No	3	Sans Restriction	Pro & Farm	3,500,000$	3,500,000$	3,500,000$	3,500,000$
Jonathan Toews	Senators	C	29	29.04.1988	No	201 Lbs	6 ft2	No	No	No	2	Sans Restriction	Pro & Farm	8,000,000$	8,000,000$	8,000,000$
Kyle Turris	Senators	C	28	14.08.1989	No	190 Lbs	6 ft1	No	No	No	1	Sans Restriction	Pro & Farm	4,000,000$	4,000,000$
Lance Bouma	Senators	C/LW	27	25.03.1990	No	208 Lbs	6 ft2	No	No	No	2	Sans Restriction	Pro Only	1,200,000$	1,200,000$	1,200,000$
Leo Komarov	Senators	LW	30	23.01.1987 2:45:34	No	210 Lbs	5 ft11	No	No	No	2	Sans Restriction	Pro & Farm	2,900,000$	2,900,000$	2,900,000$
Matt Irwin	Senators	D	29	29.11.1987	No	207 Lbs	6 ft1	No	No	No	1	Sans Restriction	Pro Only	1,200,000$	1,200,000$
Mikkel Boedker	Senators	LW/RW	27	16.12.1989	No	210 Lbs	6 ft0	No	No	No	2	Sans Restriction	Pro & Farm	3,900,000$	3,900,000$	3,900,000$
Nick Bonino	Senators	C	29	20.04.1988	No	196 Lbs	6 ft1	No	No	No	2	Sans Restriction	Pro & Farm	2,500,000$	2,500,000$	2,500,000$
Niklas Kronwall (Sur la Masse Salariale)	Senators	D	36	12.01.1981	No	194 Lbs	6 ft0	No	No	No	1	Sans Restriction	Pro & Farm	1,800,000$	1,800,000$
Radko Gudas	Senators	D	27	05.06.1990	No	204 Lbs	6 ft0	No	No	No	1	Sans Restriction	Pro & Farm	2,600,000$	2,600,000$
Robby Fabbri	Senators	LW	21	22.01.1996 16:54:46	Yes	195 Lbs	5 ft10	No	No	No	2	Contrat d'Entrée	Pro & Farm	1,600,000$	1,600,000$	1,600,000$
Thomas Greiss	Senators	G	31	29.01.1986	No	220 Lbs	6 ft1	No	No	No	1	Sans Restriction	Pro & Farm	3,000,000$	3,000,000$
Tom Kuhnhackl	Senators	LW/RW	25	21.02.1992 11:31:02	Yes	196 Lbs	6 ft2	No	No	No	1	Avec Restriction	Pro Only	900,000$	900,000$
Tyler Toffoli	Senators	C/RW	25	24.04.1992 14:40:36	Yes	201 Lbs	6 ft0	No	No	No	1	Avec Restriction	Pro & Farm	4,000,000$	4,000,000$
Zach Parise	Senators	LW	33	28.07.1984	No	196 Lbs	5 ft11	No	No	No	3	Sans Restriction	Pro & Farm	6,000,000$	6,000,000$	6,000,000$	6,000,000$

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
20	29.35	204 Lbs	6 ft1	1.80	3,290,000$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
65,800,000$	46,800,000$	21,100,000$	0$	0$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Zach Parise	Jonathan Toews	Tyler Toffoli	40	1	2	2
2	Robby Fabbri	Kyle Turris	Jason Chimera	30	1	2	2
3	Leo Komarov	Nick Bonino	Tom Kuhnhackl	20	1	2	2
4	Lance Bouma	Brad Richardson	Mikkel Boedker	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	Jay Bouwmeester	40	1	2	2
2	Jake Muzzin	Radko Gudas	35	1	2	2
3		Matt Irwin	25	1	3	1
4	Alex Pietrangelo	Jake Muzzin	0	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Zach Parise	Jonathan Toews	Tyler Toffoli	60	0	1	4
2	Robby Fabbri	Kyle Turris	Jason Chimera	40	1	1	3

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	Jake Muzzin	60	0	2	3
2		Radko Gudas	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Nick Bonino	Leo Komarov	55	1	3	1
2	Brad Richardson	Tom Kuhnhackl	45	1	3	1

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	Radko Gudas	55	1	3	1
2	Jake Muzzin	Jay Bouwmeester	45	1	3	1

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Nick Bonino	50	1	3	1	Alex Pietrangelo	Radko Gudas	50	1	3	1
2	Jonathan Toews	50	1	3	1	Jay Bouwmeester	Matt Irwin	50	1	3	1

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Jonathan Toews	Zach Parise	50	1	2	2
2	Kyle Turris	Tyler Toffoli	50	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	Radko Gudas	55	1	2	2
2	Jake Muzzin		45	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Zach Parise	Jonathan Toews	Tyler Toffoli	Alex Pietrangelo	Jake Muzzin

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Leo Komarov	Jonathan Toews	Tyler Toffoli	Alex Pietrangelo	Jay Bouwmeester

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Zach Parise, Tyler Toffoli, Nick Bonino	Nick Bonino, Leo Komarov	Jonathan Toews

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Alex Pietrangelo, Jake Muzzin,	Matt Irwin	Matt Irwin,

Tirs de Pénalité
Kyle Turris, Jonathan Toews, Tyler Toffoli, Zach Parise, Nick Bonino

Gardien
#1 : Thomas Greiss, #2 : Cory Schneider

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

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

Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

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

#	VS Équipe	GP	W	L	GF	GA	Diff	P	PCT	G	A	TP	GP1	GP2	GP3	SHF	SH1	SP2	SP3	SHA	SHB	Pim	Hit	PPA	PP%	PKA	PK GA	PK%	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	GF%	SH%	SV%	PDO	PDOBRK
1	Hurricanes	1	0	1	2	3	-1	0	0.000	2	4	6	1	0	1	36	13	14	9	34	17	0	26	1	0.00%	0	0	0.00%	26	61	42.62%	32	65	49.23%	26	56	46.43%	23	16	22	7	14	7	40.0%	5.6%	91.2%	96.7	DULL
2	Penguins	1	1	0	2	1	1	2	1.000	2	2	4	1	1	0	29	8	12	9	40	23	0	27	1	0.00%	0	0	0.00%	26	61	42.62%	32	65	49.23%	26	56	46.43%	19	12	25	8	15	7	66.7%	6.9%	97.5%	104.4	DULL
3	Predators	1	0	1	1	5	-4	0	0.000	1	2	3	0	1	0	31	9	12	10	38	14	0	24	0	0.00%	0	0	0.00%	26	61	42.62%	32	65	49.23%	26	56	46.43%	20	12	25	7	14	6	16.7%	3.2%	86.8%	90.1	Unlucky
4	Sabres	1	0	1	4	8	-4	0	0.000	4	6	10	1	2	1	33	11	18	4	39	14	4	17	2	0.00%	2	2	0.00%	26	61	42.62%	32	65	49.23%	26	56	46.43%	20	13	24	6	15	7	40.0%	12.1%	79.5%	91.6	FUN
	Since Last GM Reset	4	1	3	9	17	-8	2	0.250	9	14	23	3	4	2	129	41	56	32	151	68	4	94	4	0.00%	2	2	0.00%	26	61	42.62%	32	65	49.23%	26	56	46.43%	83	54	97	29	59	29	37.5%	7.0%	88.7%	95.7	Unlucky
	Total	4	1	3	9	17	-8	2	0.250	9	14	23	3	4	2	129	41	56	32	151	68	4	94	4	0.00%	2	2	0.00%	26	61	42.62%	32	65	49.23%	26	56	46.43%	83	54	97	29	59	29	37.5%	7.0%	88.7%	95.7	Unlucky
	Vs Conference	4	1	3	9	17	-8	2	0.250	9	14	23	3	4	2	129	41	56	32	151	68	4	94	4	0.00%	2	2	0.00%	26	61	42.62%	32	65	49.23%	26	56	46.43%	83	54	97	29	59	29	37.5%	7.0%	88.7%	95.7	Unlucky
	Vs Division	4	1	3	9	17	-8	2	0.250	9	14	23	3	4	2	129	41	56	32	151	68	4	94	4	0.00%	2	2	0.00%	26	61	42.62%	32	65	49.23%	26	56	46.43%	83	54	97	29	59	29	37.5%	7.0%	88.7%	95.7	Unlucky

			Total Pour les Joueurs
Matchs Joués	Points	Séquence	Buts	Passes	Points	Tirs Pour	Tirs Contre	Tirs Bloqués	Minutes de Pénalité	Mises en Échec	Buts en Filet Désert	Blanchissage
4	2	L1	9	14	23	129	151	68	4	94	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	1	3	0	0	0	0	9	17

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

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	0	3	0	0	0	0	7	16

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
1	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
4	0	0.00%	2	2	0.00%	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
41	56	32	0	3	4	2	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
26	61	42.62%	32	65	49.23%	26	56	46.43%

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
83	54	97	29	59	29

Derniers Match Joués

Astuces sur les Filtres (Anglais seulement)

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

Date		Result	Detail
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
Sun, Apr 20	@	Senators4,Sabres8	RECAP
Mon, Apr 21	@	Senators1,Predators5	RECAP
Wed, Apr 23	@	Penguins1,Senators2	RECAP
Fri, Apr 25	@	Senators2,Hurricanes3	RECAP

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2	Niveau 3	Niveau 4	Luxe
Capacité de l'Aréna	7278	3831	4788	1915	1341
Prix des Billets	80	60	40	20	160
Assistance	0	0	0	0	0
Attendance PCT	0.00%	0.00%	0.00%	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$	19153	100

Dépenses
Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs	Valeur du Cap Salarial Spécial
64,000,000$	7,800,000$	0$	0$

Dépenses Annuelles à Ce Jour	Cap Salarial Par Jour	Cap salarial à ce jour	Taxe de Luxe Totale
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$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Cap Salarial de la Saison Éstimé	Compte Bancaire Actuel	Compte Bancaire Projeté
0$	0$	47,111,931$	47,111,931$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Jason Chimera	AGE:38	PO:0	OV:71
Zach Parise	AGE:33	PO:0	OV:71
Leo Komarov	AGE:30	PO:0	OV:70
Mikkel Boedker	AGE:27	PO:0	OV:68
*Robby Fabbri	AGE:21	PO:0	OV:65
Brad Richardson	AGE:32	PO:0	OV:65
Cody McLeod	AGE:33	PO:0	OV:63
Lance Bouma	AGE:27	PO:0	OV:63
*Tom Kuhnhackl	AGE:25	PO:0	OV:62
*Stefan Noesen	AGE:24	PO:0	OV:58
Joey LaLeggia	AGE:25	PO:0	OV:57
Tye McGinn	AGE:27	PO:0	OV:56
*Denis Guryanov	AGE:20	PO:0	OV:55
*Dmytro Timashov	AGE:21	PO:0	OV:54
Daniel Catenacci	AGE:24	PO:0	OV:52
Brendan Woods	AGE:25	PO:0	OV:52
Mark MacMillan	AGE:25	PO:0	OV:52
*Michael Carcone	AGE:21	PO:0	OV:51

Jonathan Toews	AGE:29	PO:0	OV:74
Kyle Turris	AGE:28	PO:0	OV:71
Nick Bonino	AGE:29	PO:0	OV:69
*Tyler Toffoli	AGE:25	PO:0	OV:68
Brad Richardson	AGE:32	PO:0	OV:65
Lance Bouma	AGE:27	PO:0	OV:63
Jacob Josefson	AGE:26	PO:0	OV:62
*Michael McCarron	AGE:22	PO:0	OV:58
*Jordan Weal	AGE:25	PO:0	OV:57
*Samuel Henley	AGE:24	PO:0	OV:56
*Tanner Richard	AGE:24	PO:0	OV:56
Felix Girard	AGE:23	PO:0	OV:54
Daniel Catenacci	AGE:24	PO:0	OV:52
Mark MacMillan	AGE:25	PO:0	OV:52

Jason Chimera	AGE:38	PO:0	OV:71
*Tyler Toffoli	AGE:25	PO:0	OV:68
Mikkel Boedker	AGE:27	PO:0	OV:68
Brad Richardson	AGE:32	PO:0	OV:65
Cody McLeod	AGE:33	PO:0	OV:63
Joonas Donskoi	AGE:25	PO:0	OV:62
*Tom Kuhnhackl	AGE:25	PO:0	OV:62
Steve Bernier	AGE:32	PO:0	OV:59
*Stefan Noesen	AGE:24	PO:0	OV:58
Tye McGinn	AGE:27	PO:0	OV:56
*Denis Guryanov	AGE:20	PO:0	OV:55
*Zack Mitchell	AGE:24	PO:0	OV:55
Mark MacMillan	AGE:25	PO:0	OV:52
Brian Hart	AGE:23	PO:0	OV:49

Défense #1

Défense #2

Gardien

Alex Pietrangelo	AGE:27	PO:0	OV:77
Jake Muzzin	AGE:28	PO:0	OV:74
Radko Gudas	AGE:27	PO:0	OV:72
Jay Bouwmeester	AGE:34	PO:0	OV:72
Niklas Kronwall	AGE:36	PO:0	OV:71
Matt Irwin	AGE:29	PO:0	OV:68
Michal Rozsival	AGE:39	PO:0	OV:67

Klas Dahlbeck	AGE:26	PO:0	OV:65
*Scott Harrington	AGE:24	PO:0	OV:61
Nate Prosser	AGE:31	PO:0	OV:61
Oliver Kylington	AGE:20	PO:0	OV:55
Dylan Blujus	AGE:23	PO:0	OV:53
Patrick McNally	AGE:25	PO:0	OV:52

Cory Schneider	AGE:31	PO:0	OV:79
Thomas Greiss	AGE:31	PO:0	OV:79
Richard Bachman	AGE:30	PO:0	OV:71
Casey DeSmith	AGE:26	PO:0	OV:61
Adin Hill	AGE:21	PO:0	OV:53

Éspoirs

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

Éspoir	Nom de l'Équipe	Année de Repêchage	Choix Total
Artur Tyanulin	Senators	2016	178
Brennan Menell	Senators	2017	178
Cam Johnson	Senators	2016	230
Casey Fitzgerald	Senators	2015	185
Cavan Fitzgerald	Senators	2016	244
Chase Pearson	Senators	2016	190
Cody Glass	Senators	2017	7
Eero Elo	Senators
Jack Glover	Senators	2014	53
Jake Morrissey	Senators	2015	201
Jason Kasdorf	Senators
Jason Robertson	Senators	2017	28
Jens Looke	Senators	2015	94
John McCarron	Senators	2012	231
John Piccinich	Senators	2014	101
Jonas Johansson	Senators	2014	85
Joren Van Pottelberghe	Senators	2015	239
Kendall McFaull	Senators
Luc Snuggerud	Senators	2014	125
Markus Phillips	Senators	2017	80
Matt Finn	Senators
Miikka Salomaki	Senators
Nikita Filatov	Senators
Niklas Hansson	Senators	2013	65
Niklas Lundstrom	Senators	2011	154
Ondrej Vala	Senators	2016	243
Pavel Jenys	Senators	2014	191
Roberts Lipsbergs	Senators	2013	157
Roope Hintz	Senators	2015	47
Samuel Kurker	Senators	2012	142
Taylor Cammarata	Senators	2013	97
Tim Soderlund	Senators	2017	107
Tyler Kelleher	Senators	2016	222
Ziyat Paigin	Senators	2016	104

Choix au Repêchage

Année	R1	R2	R3	R4	R5	R6	R7
2018	OTT	OTT	OTT				OTT
2019	OTT	OTT	OTT	OTT	OTT	OTT	OTT
2020	OTT	OTT	OTT	OTT	OTT	OTT	OTT
2021	OTT	OTT	OTT	OTT	OTT	OTT	OTT
2022	OTT	OTT	OTT	OTT	OTT	OTT	OTT

[10.10.2017 20:54:08] - Jacob Josefson has been selected as assistant for Senators.
[10.10.2017 20:54:08] - Unknown Player is no longer as assistant for Senators.
[10.10.2017 20:54:08] - Michal Rozsival has been selected as captain for Senators.
[10.10.2017 20:54:08] - Unknown Player is no longer captain for Senators.
[10.10.2017 20:49:56] - Miikka Salomaki has been added to Senators.
[10.10.2017 20:49:49] - Miikka Salomaki was released.
[10.10.2017 20:49:49] - Senators paid 0 Kč to release Miikka Salomaki.
[03.10.2017 10:10:56] - Senators drafts Brennan Menell as the #178 overall pick in the Entry Draft of year 2017.
[01.10.2017 10:52:19] - Tye McGinn signed with Senators for 800 000 Kč for 2 year(s) with 0 Kč in bonus.
[01.10.2017 10:52:19] - Tye McGinn was added to Senators.
[01.10.2017 10:52:06] - Samuel Henley signed with Senators for 600 000 Kč for 2 year(s) with 0 Kč in bonus.
[01.10.2017 10:52:06] - Samuel Henley was added to Senators.
[23.09.2017 8:14:39] - Nate Prosser signed with Senators for 800 000 Kč for 2 year(s) with 0 Kč in bonus.
[23.09.2017 8:14:39] - Nate Prosser was added to Senators.
[23.09.2017 8:08:46] - Brendan Woods signed with Senators for 800 000 Kč for 2 year(s) with 0 Kč in bonus.
[23.09.2017 8:08:46] - Brendan Woods was added to Senators.
[23.09.2017 8:08:28] - Cody McLeod signed with Senators for 600 000 Kč for 2 year(s) with 0 Kč in bonus.
[23.09.2017 8:08:28] - Cody McLeod was added to Senators.
[22.09.2017 5:12:12] - Senators drafts Tim Soderlund as the #107 overall pick in the Entry Draft of year 2017.
[16.09.2017 16:49:32] - Senators drafts Markus Phillips as the #80 overall pick in the Entry Draft of year 2017.

Pas de Blessure ou de Suspension.

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
2017	4	1	3	0	0	0	0	0	9	17	-8	1	1	0	0	0	0	0	0	2	1	1	3	0	3	0	0	0	0	0	7	16	-9	2	9	14	23	0	0	3	4	2	0	129	41	56	32	0	151	68	4	94	4	0	0.00%	2	2	0.00%	0	26	61	42.62%	32	65	49.23%	26	56	46.43%	83	54	97	29	59	29
Total Saison Régulière	4	1	3	0	0	0	0	0	9	17	-8	1	1	0	0	0	0	0	0	2	1	1	3	0	3	0	0	0	0	0	7	16	-9	2	9	14	23	0	0	3	4	2	0	129	41	56	32	0	151	68	4	94	4	0	0.00%	2	2	0.00%	0	26	61	42.62%	32	65	49.23%	26	56	46.43%	83	54	97	29	59	29