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 (A)	X				100.00	67	57	79	86	81	91	99	88	99	51	54	71	87	96	96	0	54	76	0
2	Zach Parise (C)		X	X		100.00	68	43	82	89	83	92	82	91	63	52	55	63	78	87	90	0	54	74	0
3	Tyler Toffoli		X	X		100.00	67	43	89	85	72	87	89	89	62	49	55	71	50	64	66	0	54	71	0
4	Mikkel Boedker		X	X		100.00	66	43	86	93	73	89	75	92	63	52	49	59	63	77	77	0	54	71	0
5	Kyle Turris	X				100.00	64	43	80	83	66	92	83	86	97	48	48	63	75	70	72	0	54	69	0
6	Brad Boyes			X		100.00	61	41	95	75	84	74	80	78	64	47	45	61	81	86	82	0	54	68	0
7	Leo Komarov		X	X		100.00	92	47	80	80	73	87	75	72	62	47	50	74	50	59	59	0	54	68	0
8	Nick Bonino	X	X			100.00	61	51	81	82	69	84	80	69	93	49	45	77	80	67	69	0	54	68	0
9	Brad Richardson	X	X			100.00	66	56	80	77	67	83	78	66	95	46	45	72	50	74	77	0	54	66	0
10	Jacob Josefson	X	X			100.00	68	43	86	79	63	82	71	72	87	42	40	70	90	64	65	0	54	65	0
11	Steve Bernier			X		100.00	71	76	67	75	92	73	68	65	57	42	41	58	53	75	79	0	54	64	0
12	Joonas Donskoi		X	X		100.00	62	41	89	83	70	79	68	69	62	49	45	61	63	54	54	0	54	63	0
13	Alex Pietrangelo (A)				X	100.00	70	43	87	88	89	99	99	82	25	52	43	81	50	80	79	0	54	76	0
14	Jake Muzzin				X	100.00	84	46	77	88	82	93	95	78	25	51	43	78	50	77	68	0	54	74	0
15	Jay Bouwmeester				X	100.00	71	44	87	90	78	93	88	69	25	45	40	80	50	85	86	0	54	72	0
16	Radko Gudas				X	100.00	93	80	61	79	99	81	73	69	25	41	41	79	50	62	63	0	54	70	0
17	Eric Gryba				X	100.00	82	99	65	73	96	77	80	69	25	41	38	77	50	63	64	0	54	68	0
18	Nate Prosser				X	100.00	67	77	77	74	72	57	77	58	25	40	38	76	50	64	65	0	54	61	0
Rayé

	MOYENNE D'ÉQUIPE					100.00	71	54	80	82	78	84	81	76	59	47	45	71	62	72	73	0	54	69

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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	79	86	98	93	82	81	83	81	79	81	72	85	91	0	54	82	0
2	Thomas Greiss	100.00	80	83	83	86	78	77	80	76	77	79	69	77	73	0	54	77	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	80	85	91	90	80	79	82	79	78	80	71	81	82	0	54	80

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Peter Laviolette	80	81	83	85	84	81	68	USA	51	4	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	PPA	PPP	PKG	PKA	PKP	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS
1	Jonathan Toews	Senators		C	4	3	2	5	4	0	0	7	17	6	7	17.65%	2	19.:.25	1	0	1	0	0	0	0	1	0	52.24%	67	7	2	0	0	1.29	1	1
2	Zach Parise	Senators		LW/RW	4	3	2	5	4	0	0	4	20	4	12	15.00%	2	19.:.46	1	0	1	0	0	0	0	1	0	33.33%	3	14	1	0	0	1.26	0	1
3	Mikkel Boedker	Senators		LW/RW	4	1	2	3	3	0	0	3	13	5	12	7.69%	1	18.:.00	0	0	0	0	0	0	0	0	0	75.00%	4	23	0	0	0	0.83	0	1
4	Tyler Toffoli	Senators		LW/RW	4	2	0	2	1	0	0	1	11	4	10	18.18%	4	17.:.30	0	0	0	0	0	0	0	1	0	50.00%	4	10	0	0	0	0.57	0	1
5	Kyle Turris	Senators		C	4	0	2	2	1	0	0	6	10	6	8	0.00%	1	16.:.51	0	1	1	0	0	0	0	0	0	58.14%	43	3	0	0	0	0.59	0	1
6	Alex Pietrangelo	Senators		D	4	0	2	2	1	2	0	7	14	9	7	0.00%	10	26.:.29	0	1	1	0	0	0	10	0	0	0.00%	0	1	10	0	0	0.38	0	0
7	Eric Gryba	Senators		D	4	0	2	2	2	2	0	4	3	0	5	0.00%	8	14.:.12	0	0	0	0	1	1	3	0	0	0.00%	0	0	4	0	0	0.70	0	0
8	Nate Prosser	Senators		D	4	0	1	1	1	2	0	3	1	2	3	0.00%	5	12.:.56	0	0	0	0	0	0	0	0	0	0.00%	0	0	2	0	0	0.39	0	0
9	Jay Bouwmeester	Senators		D	4	0	1	1	1	2	0	2	8	6	4	0.00%	7	24.:.35	0	0	0	0	1	1	11	0	0	0.00%	0	1	6	0	0	0.20	0	0
10	Brad Richardson	Senators		C/LW	4	1	0	1	-1	0	0	4	7	3	1	14.29%	4	14.:.33	0	0	0	1	0	1	2	0	0	65.00%	20	1	0	0	0	0.34	0	0
11	Radko Gudas	Senators		D	4	0	0	0	1	6	0	4	5	2	5	0.00%	7	19.:.45	0	0	0	0	0	0	7	0	0	0.00%	0	0	4	0	0	0.00	0	0
12	Joonas Donskoi	Senators		LW/RW	4	0	0	0	-1	0	0	1	8	3	7	0.00%	1	12.:.57	0	0	0	0	0	0	3	0	0	0.00%	1	7	0	0	0	0.00	0	0
13	Jacob Josefson	Senators		C/LW	4	0	0	0	0	0	0	3	3	1	4	0.00%	2	11.:.01	0	0	0	0	0	0	6	0	0	33.33%	9	6	0	0	0	0.00	0	1
14	Brad Boyes	Senators		RW	4	0	0	0	0	0	0	1	3	1	2	0.00%	0	05.:.29	0	0	0	0	0	0	0	0	0	0.00%	0	3	1	0	0	0.00	1	1
15	Steve Bernier	Senators		RW	4	0	0	0	-1	2	0	0	0	0	1	0.00%	0	08.:.26	0	0	0	0	0	0	0	0	0	100.00%	2	1	1	0	0	0.00	0	0
16	Leo Komarov	Senators		LW/RW	4	0	0	0	1	4	0	15	5	3	5	0.00%	1	20.:.31	0	0	0	0	0	0	12	0	0	25.00%	4	3	4	0	0	0.00	0	0
17	Nick Bonino	Senators		C/LW	4	0	0	0	-1	0	0	2	7	1	3	0.00%	3	15.:.27	0	0	0	0	0	0	16	0	0	52.00%	50	6	1	0	0	0.00	0	1
18	Jake Muzzin	Senators		D	4	0	0	0	1	2	0	10	6	3	9	0.00%	5	21.:.55	0	0	0	0	0	0	8	0	0	0.00%	0	0	12	0	0	0.00	0	0
Stats d'équipe Total ou en Moyenne		72	10	14	24	17	22	0	77	90	141	59	105	7.09%	63	1199	16.66	2	2	4	20	85	1	2	3	2	83	3	0	53.62%	207	86	48	0	0	0.40	2	8	0	0	0	2	3	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 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	Cory Schneider	Senators	3	3	0	0	94.6%	1.66	181	0	0	5	93	55	0	0	0.0%	0	3	1	1	0	1
2	Thomas Greiss	Senators	1	0	0	1	96.9%	0.92	65	0	0	1	32	21	0	0	62.5%	8	1	3	0	1	0
Stats d'équipe Total ou en Moyenne	4	3	0	1	0.952	1.46	246	0	0	6	125	76	0	0	0.625	8	4	4	1	1	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	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Ballotage Forcé	Contrat	Type	Salaire Actuel	Salaire Restant	Salaire Année 2	Salaire Année 3	Salaire Année 4	Link
Alex Pietrangelo	D	26	18.01.1990	No	201 Lbs	6 ft3	Yes	No	4	Pro & Farm	5,400,000$	0$	5,400,000$	5,400,000$	5,400,000$	Lien
Brad Boyes	RW	34	17.04.1982	No	195 Lbs	6 ft0	No	No	1	Pro Only	1,300,000$	0$				Lien
Brad Richardson	C/LW	31	04.02.1985	No	197 Lbs	6 ft0	No	No	2	Pro Only	1,500,000$	0$	1,500,000$			Lien
Cory Schneider	G	30	18.03.1986	No	205 Lbs	6 ft2	Yes	No	4	Pro & Farm	6,200,000$	0$	6,200,000$	6,200,000$	6,200,000$	Lien
Eric Gryba	D	28	18.04.1988	No	225 Lbs	6 ft4	No	No	1	Pro Only	1,500,000$	0$				Lien
Jacob Josefson	C/LW	25	02.03.1991	No	190 Lbs	5 ft11	No	No	1	Pro Only	1,000,000$	0$				Lien
Jake Muzzin	D	27	21.02.1989	No	214 Lbs	6 ft3	No	No	3	Pro & Farm	3,500,000$	0$	3,500,000$	3,500,000$		Lien
Jay Bouwmeester	D	33	27.09.1983	No	212 Lbs	6 ft4	Yes	No	4	Pro & Farm	3,500,000$	0$	3,500,000$	3,500,000$	3,500,000$	Lien
Jonathan Toews	C	28	29.04.1988	No	201 Lbs	6 ft2	No	No	3	Pro & Farm	8,000,000$	0$	8,000,000$	8,000,000$		Lien
Joonas Donskoi (Contrat à 1 Volet)	LW/RW	24	13.04.1992 16:57:20	No	180 Lbs	6 ft0	No	No	1	Pro & Farm	1,700,000$	0$				Lien
Kyle Turris	C	27	14.08.1989	No	191 Lbs	6 ft1	No	No	2	Pro & Farm	4,000,000$	0$	4,000,000$			Lien
Leo Komarov	LW/RW	29	23.01.1987 2:45:34	No	198 Lbs	5 ft11	No	No	3	Pro & Farm	2,900,000$	0$	2,900,000$	2,900,000$		Lien
Mikkel Boedker	LW/RW	26	16.12.1989	No	211 Lbs	6 ft0	No	No	3	Pro & Farm	3,900,000$	0$	3,900,000$	3,900,000$		Lien
Nate Prosser	D	30	07.05.1986	No	203 Lbs	6 ft2	No	No	1	Pro Only	1,400,000$	0$				Lien
Nick Bonino	C/LW	28	20.04.1988	No	196 Lbs	6 ft1	No	No	3	Pro & Farm	2,500,000$	0$	2,500,000$	2,500,000$		Lien
Radko Gudas	D	26	05.06.1990	No	204 Lbs	6 ft0	No	No	2	Pro & Farm	2,600,000$	0$	2,600,000$			Lien
Steve Bernier	RW	31	31.03.1985	No	215 Lbs	6 ft3	No	No	2	Pro & Farm	1,200,000$	0$	1,200,000$			Lien
Thomas Greiss	G	30	29.01.1986	No	220 Lbs	6 ft1	No	No	1	Pro Only	1,000,000$	0$				Lien
Tyler Toffoli	LW/RW	24	24.04.1992 14:40:36	No	196 Lbs	6 ft1	No	No	2	Pro & Farm	4,400,000$	0$	4,000,000$			Lien
Zach Parise	LW/RW	32	28.07.1984	No	197 Lbs	5 ft11	No	No	4	Pro & Farm	6,000,000$	0$	6,000,000$	6,000,000$	6,000,000$	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
20	28.45	203 Lbs	6 ft1	2.35	3,175,000$

Attaque à 5 contre 5
Ligne #	Centre	Ailier Gauche	Ailier Droit	% Temps	PHY	DF	OF
1	Jonathan Toews	Zach Parise	Mikkel Boedker	43	0	2	3
2	Kyle Turris	Tyler Toffoli	Leo Komarov	36	0	2	3
3	Nick Bonino	Brad Richardson	Joonas Donskoi	17	0	3	2
4	Jacob Josefson	Brad Boyes	Steve Bernier	4	1	4	0

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	Jay Bouwmeester	45	0	3	2
2	Jake Muzzin	Radko Gudas	35	1	2	2
3	Eric Gryba	Nate Prosser	20	2	3	0
4	Alex Pietrangelo	Jake Muzzin	0	1	4	0

Attaque en Avantage Numérique
Ligne #	Centre	Ailier Gauche	Ailier Droit	% Temps	PHY	DF	OF
1	Jonathan Toews	Tyler Toffoli	Mikkel Boedker	60	0	1	4
2	Kyle Turris	Leo Komarov	Joonas Donskoi	40	1	1	3

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Zach Parise	Alex Pietrangelo	60	0	2	3
2	Jake Muzzin	Jay Bouwmeester	40	1	3	1

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Nick Bonino	Leo Komarov	60	2	3	0
2	Brad Richardson	Jacob Josefson	40	1	4	0

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	Jay Bouwmeester	60	1	4	0
2	Jake Muzzin	Radko Gudas	40	1	4	0

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Nick Bonino	50	1	4	0	Alex Pietrangelo	Jay Bouwmeester	50	1	4	0
2	Jonathan Toews	50	1	4	0	Jake Muzzin	Radko Gudas	50	1	4	0

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Jonathan Toews	Zach Parise	55	0	1	4
2	Nick Bonino	Tyler Toffoli	45	0	2	3

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	Jay Bouwmeester	55	0	3	2
2	Jake Muzzin	Radko Gudas	45	1	3	1

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

Défense Dernière Minute
Centre	Ailier Gauche	Ailier Droit	Défense	Défense
Jonathan Toews	Nick Bonino	Leo Komarov	Alex Pietrangelo	Jay Bouwmeester

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Zach Parise, Tyler Toffoli, Nick Bonino	Joonas Donskoi, Nick Bonino	Jacob Josefson

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Alex Pietrangelo, Jake Muzzin, Eric Gryba	Eric Gryba	Jay Bouwmeester, Eric Gryba

Tirs de Pénalité
Zach Parise, Jonathan Toews, Tyler Toffoli, Mikkel Boedker, Kyle Turris

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

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

#	VS Équipe	GP	W	OTW	SOL	GF	GA	Diff	P	PCT	G	A	TP	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	Lightning	1	1	0	0	3	1	2	2	1.000	3	5	8	2	1	0	0	44	21	10	13	0	24	12	8	17	3	1	33.33%	4	1	75.00%	0	48	86	55.81%	35	75	46.67%	28	46	60.87%	26	17	18	7	14	7
2	Capitals	1	0	0	1	1	2	-1	1	0.500	1	1	2	1	0	0	2	35	7	17	7	12	32	24	2	19	4	1	25.00%	1	0	100.00%	0	48	86	55.81%	35	75	46.67%	28	46	60.87%	26	18	23	7	15	8
3	Maple Leafs	1	0	1	0	2	1	1	2	1.000	2	3	5	0	1	0	1	37	10	14	11	2	30	15	6	17	3	0	0.00%	3	0	100.00%	1	48	86	55.81%	35	75	46.67%	28	46	60.87%	26	18	21	7	14	7
4	Flames	1	1	0	0	4	3	1	2	1.000	4	5	9	1	2	1	0	25	7	11	7	0	39	12	6	24	0	0	0.00%	3	1	66.67%	0	48	86	55.81%	35	75	46.67%	28	46	60.87%	19	12	27	7	13	6
	Vs Division	1	0	1	0	2	1	1	2	1.000	2	3	5	0	1	0	1	37	10	14	11	2	30	15	6	17	3	0	0.00%	3	0	100.00%	1	48	86	55.81%	35	75	46.67%	28	46	60.87%	26	18	21	7	14	7
	Vs Conference	3	1	1	1	6	4	2	5	0.833	6	9	15	3	2	0	3	116	38	41	31	14	86	51	16	53	10	2	20.00%	8	1	87.50%	1	48	86	55.81%	35	75	46.67%	28	46	60.87%	79	54	63	22	44	23
	Since Last GM Reset	4	2	1	1	10	7	3	7	0.875	10	14	24	4	4	1	3	141	45	52	38	14	125	63	22	77	10	2	20.00%	11	2	81.82%	1	48	86	55.81%	35	75	46.67%	28	46	60.87%	98	66	90	29	58	30
	Total	4	2	1	1	10	7	3	7	0.875	10	14	24	4	4	1	3	141	45	52	38	14	125	63	22	77	10	2	20.00%	11	2	81.82%	1	48	86	55.81%	35	75	46.67%	28	46	60.87%	98	66	90	29	58	30

			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	7	W1	10	14	24	141	125	63	22	77	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	2	0	1	0	0	1	10	7

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	1	0	1	0	0	0	6	4

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	1	0	0	0	0	1	4	3

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
2	0	1	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
10	2	20.00%	11	2	81.82%	1

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
45	52	38	14	4	4	1	3

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
48	86	55.81%	35	75	46.67%	28	46	60.87%

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
98	66	90	29	58	30

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	@	Flames3,Senators4	RECAP
Mon, Apr 21	@	Maple Leafs1,Senators2 (OT)	RECAP
Thu, Apr 24	@	Senators1,Capitals2 (SO)	RECAP
Fri, Apr 25	@	Senators3,Lightning1	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	108	63	38	24	220
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
63,500,000$	5,500,000$	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$	23,365,111$	23,365,111$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Zach Parise	AGE:32	PO:0	OV:74
Tyler Toffoli	AGE:24	PO:0	OV:71
Mikkel Boedker	AGE:26	PO:0	OV:71
Leo Komarov	AGE:29	PO:0	OV:68
Nick Bonino	AGE:28	PO:0	OV:68
Brad Richardson	AGE:31	PO:0	OV:66
Jacob Josefson	AGE:25	PO:0	OV:65
Joonas Donskoi	AGE:24	PO:0	OV:63
*Miikka Salomaki	AGE:23	PO:0	OV:62
*Robby Fabbri	AGE:20	PO:0	OV:62
Sergei Plotnikov	AGE:26	PO:0	OV:57
Tom Kuhnhackl	AGE:24	PO:0	OV:57
Viktor Tikhonov	AGE:28	PO:0	OV:56
Daniel Catenacci	AGE:23	PO:0	OV:54
*Stefan Noesen	AGE:23	PO:0	OV:54
*Brian Hart	AGE:22	PO:0	OV:49

Jonathan Toews	AGE:28	PO:0	OV:76
Kyle Turris	AGE:27	PO:0	OV:69
Nick Bonino	AGE:28	PO:0	OV:68
Brad Richardson	AGE:31	PO:0	OV:66
Jacob Josefson	AGE:25	PO:0	OV:65
*Robby Fabbri	AGE:20	PO:0	OV:62
*Michael McCarron	AGE:21	PO:0	OV:56
Viktor Tikhonov	AGE:28	PO:0	OV:56
Daniel Catenacci	AGE:23	PO:0	OV:54
Jordan Weal	AGE:24	PO:0	OV:53
*Tanner Richard	AGE:23	PO:0	OV:53
*Felix Girard	AGE:22	PO:0	OV:50
*Mark MacMillan	AGE:24	PO:0	OV:49

Zach Parise	AGE:32	PO:0	OV:74
Tyler Toffoli	AGE:24	PO:0	OV:71
Mikkel Boedker	AGE:26	PO:0	OV:71
Brad Boyes	AGE:34	PO:0	OV:68
Leo Komarov	AGE:29	PO:0	OV:68
Steve Bernier	AGE:31	PO:0	OV:64
Joonas Donskoi	AGE:24	PO:0	OV:63
*Miikka Salomaki	AGE:23	PO:0	OV:62
*Robby Fabbri	AGE:20	PO:0	OV:62
Sergei Plotnikov	AGE:26	PO:0	OV:57
Tom Kuhnhackl	AGE:24	PO:0	OV:57
*Michael McCarron	AGE:21	PO:0	OV:56
Viktor Tikhonov	AGE:28	PO:0	OV:56
*Zack Mitchell	AGE:23	PO:0	OV:55
*Stefan Noesen	AGE:23	PO:0	OV:54
Jordan Weal	AGE:24	PO:0	OV:53
*Brian Hart	AGE:22	PO:0	OV:49
*Mark MacMillan	AGE:24	PO:0	OV:49

Défense #1

Défense #2

Gardien

Alex Pietrangelo	AGE:26	PO:0	OV:76
Jake Muzzin	AGE:27	PO:0	OV:74
Jay Bouwmeester	AGE:33	PO:0	OV:72
Radko Gudas	AGE:26	PO:0	OV:70
Eric Gryba	AGE:28	PO:0	OV:68
Klas Dahlbeck	AGE:25	PO:0	OV:65
Chris Wideman	AGE:26	PO:0	OV:62
*Scott Harrington	AGE:23	PO:0	OV:61

Nate Prosser	AGE:30	PO:0	OV:61
*Dylan Blujus	AGE:22	PO:0	OV:60
Jakub Nakladal	AGE:28	PO:0	OV:58
*Oliver Kylington	AGE:19	PO:0	OV:54
Danny Biega	AGE:25	PO:0	OV:53
*Joey LaLeggia	AGE:24	PO:0	OV:53
*Matt Finn	AGE:22	PO:0	OV:53
*Patrick McNally	AGE:24	PO:0	OV:50

Cory Schneider	AGE:30	PO:0	OV:82
Thomas Greiss	AGE:30	PO:0	OV:77
*Jason Kasdorf	AGE:24	PO:0	OV:66
Richard Bachman	AGE:29	PO:0	OV:66
Rasmus Tirronen	AGE:25	PO:0	OV:61

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
Adin Hill	Senators	2015	95
Alexander Salak	Senators
Artur Tyanulin	Senators	2016	178
Cam Johnson	Senators	2016	230
Casey DeSmith	Senators	2016	229
Casey Fitzgerald	Senators	2015	185
Cavan Fitzgerald	Senators	2016	244
Chase Pearson	Senators	2016	190
Daniel Brodin	Senators
Denis Guryanov	Senators	2015	31
Dmytro Timashov	Senators	2015	65
Eero Elo	Senators
Jack Glover	Senators	2014	53
Jake Morrissey	Senators	2015	201
Jeff Costello	Senators
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
Michael Carcone	Senators	2016	221
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
Troy Rutkowski	Senators
Tyler Kelleher	Senators	2016	222
Ziyat Paigin	Senators	2016	104

Choix au Repêchage

Année	R1	R2	R3	R4	R5	R6	R7
2017	OTT NJD	OTT	FLA	OTT	OTT	OTT
2018	OTT	OTT	OTT	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

[14.09.2016 7:09:37] - Brad Richardson was added to Senators.
[14.09.2016 7:09:37] - Brad Richardson signed with Senators for 1 500 000 Kč for 2 year(s) with 0 Kč in bonus.
[20.09.2016 6:02:07] - TRADE : From Senators to Jets : Y:2016-RND:6-COL, Y:2017-RND:4-BUF.
[20.09.2016 6:02:07] - TRADE : From Jets to Senators : Y:2016-RND:4-WPG.
[22.09.2016 7:41:41] - Senators drafts Ziyat Paigin as the #104 overall pick in the Entry Draft of year 2016.
[24.09.2016 5:47:19] - Senators hired Kurt Kleinendorst for 100 000 Kč for 5 year(s).
[02.10.2016 7:08:27] - Brad Boyes was added to Senators.
[02.10.2016 7:08:27] - Brad Boyes signed with Senators for 1 300 000 Kč for 1 year(s) with 0 Kč in bonus.
[02.10.2016 7:08:41] - Richard Bachman was added to Senators.
[02.10.2016 7:08:41] - Richard Bachman signed with Senators for 900 000 Kč for 2 year(s) with 0 Kč in bonus.
[06.10.2016 6:22:27] - TRADE : From Capitals to Senators : Y:2016-RND:6-WSH.
[06.10.2016 6:22:27] - TRADE : From Senators to Capitals : Y:2017-RND:6-BUF.
[06.10.2016 7:00:38] - Senators drafts Artur Tyanulin as the #178 overall pick in the Entry Draft of year 2016.
[08.10.2016 6:04:28] - Senators drafts Chase Pearson as the #190 overall pick in the Entry Draft of year 2016.
[08.10.2016 6:15:29] - Steve Bernier was added to Senators.
[08.10.2016 6:15:29] - Steve Bernier signed with Senators for 1 200 000 Kč for 2 year(s) with 0 Kč in bonus.
[08.10.2016 6:15:46] - Sergei Plotnikov was added to Senators.
[08.10.2016 6:15:46] - Sergei Plotnikov signed with Senators for 1 000 000 Kč for 1 year(s) with 0 Kč in bonus.
[08.10.2016 6:15:59] - Viktor Tikhonov was added to Senators.
[08.10.2016 6:15:59] - Viktor Tikhonov signed with Senators for 1 100 000 Kč for 1 year(s) with 0 Kč in bonus.
[10.10.2016 12:22:13] - Jakub Nakladal was added to Senators.
[10.10.2016 12:22:13] - Jakub Nakladal signed with Senators for 1 500 000 Kč for 1 year(s) with 0 Kč in bonus.
[12.10.2016 6:21:45] - TRADE : From Maple Leafs to Senators : MISSED PICK (P), MISSED PICK (P).
[12.10.2016 6:21:45] - TRADE : From Senators to Maple Leafs : 3 000 000 Kč (Money).
[12.10.2016 6:38:01] - MISSED PICK has been deleted from Senators.
[12.10.2016 6:38:03] - MISSED PICK has been deleted from Senators.
[12.10.2016 6:38:34] - Michael Carcone has been added to Senators.
[12.10.2016 6:38:44] - Tyler Kelleher has been added to Senators.
[15.10.2016 22:22:14] - TRADE : From Senators to Flyers : Curtis Hamilton (54), Jim O'Brien (56).
[20.10.2016 5:20:38] - Casey DeSmith has been added to Senators.
[20.10.2016 5:20:53] - Cam Johnson has been added to Senators.
[20.10.2016 5:21:10] - Ondrej Vala has been added to Senators.
[20.10.2016 5:21:20] - Cavan Fitzgerald has been added to Senators.

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