Profi League - Senators

Senators
Formation
Points
Informations Joueurs
Lignes
Statistiques d'Équipe
Calendrier
Finance

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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	Miikka Salomaki (R)		X	X		100.00	82	46	83	77	65	74	68	65	60	40	42	68	50	51	51	0	51	62	0
2	Robby Fabbri (R)	X	X	X		100.00	65	52	86	83	60	77	68	69	61	46	49	60	50	53	53	0	49	62	0
3	Sergei Plotnikov		X	X		100.00	77	46	66	77	58	53	67	65	60	37	38	60	50	48	48	0	48	57	0
4	Tom Kuhnhackl		X	X		100.00	68	44	66	70	55	58	73	64	60	44	42	65	50	47	47	0	51	57	0
5	Michael McCarron (R)	X		X		100.00	76	99	58	66	60	56	61	63	79	39	40	57	50	45	45	0	54	56	0
6	Viktor Tikhonov	X	X	X		100.00	66	43	66	72	54	56	60	63	60	39	41	60	50	57	57	0	48	56	0
7	Zack Mitchell (R)			X		100.00	72	68	75	62	53	70	65	61	69	33	39	58	56	44	44	0	51	55	0
8	Daniel Catenacci	X	X			100.00	72	44	77	73	52	50	60	60	58	37	38	57	50	45	45	0	51	54	0
9	Stefan Noesen (R)		X	X		100.00	62	76	63	69	58	62	62	58	76	36	34	60	50	44	44	0	48	54	0
10	Jordan Weal	X		X		100.00	56	41	68	69	50	50	62	62	74	37	38	58	50	45	45	0	46	53	0
11	Tanner Richard (R)	X				100.00	56	65	59	62	50	69	66	60	74	43	34	56	50	44	44	0	50	53	0
12	Felix Girard (R)	X				100.00	57	66	59	60	51	68	65	55	65	32	30	54	50	44	44	0	47	50	0
13	Klas Dahlbeck				X	100.00	85	46	85	75	73	70	88	61	25	41	39	78	50	56	56	0	48	65	0
14	Chris Wideman				X	100.00	69	42	81	74	66	66	85	69	25	41	43	73	50	51	51	0	51	62	0
15	Scott Harrington (R)				X	100.00	72	45	88	73	72	62	66	68	25	39	37	71	50	60	60	0	51	61	0
16	Dylan Blujus (R)				X	100.00	83	73	95	70	69	79	78	51	25	30	32	62	50	55	55	0	49	60	0
17	Jakub Nakladal				X	100.00	74	45	67	67	61	65	65	69	25	38	40	69	50	46	46	0	48	58	0
18	Oliver Kylington (R)				X	100.00	59	67	67	73	57	58	63	56	25	32	35	59	50	55	55	0	51	54	0
Rayé
1	Brian Hart (R)		X	X		100.00	60	75	62	63	56	48	57	52	59	25	31	55	50	44	44	0	46	49	0
2	Mark MacMillan (R)	X		X		100.00	56	64	59	63	50	53	60	55	64	31	32	52	50	44	44	0	46	49	0
3	Danny Biega				X	100.00	57	74	64	71	59	65	68	58	25	29	32	57	50	46	46	0	46	53	0
4	Joey LaLeggia (R)				X	100.00	55	64	61	72	55	61	65	66	25	34	32	54	50	44	44	0	46	53	0
5	Matt Finn (R)				X	100.00	56	71	62	64	58	61	65	66	25	32	33	57	50	46	46	0	46	53	0
6	Patrick McNally (R)				X	100.00	59	69	67	61	57	57	63	53	25	24	27	58	50	46	46	0	46	50	0

	MOYENNE D'ÉQUIPE					100.00	66	59	70	69	58	62	67	61	49	36	37	61	50	48	48	0	49	56

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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	Jason Kasdorf (R)	100.00	66	68	65	75	66	79	65	72	73	66	48	55	55	0	51	66	0
2	Richard Bachman	99.00	67	72	64	70	68	74	69	71	69	66	53	59	59	0	48	66	0
Rayé
1	Rasmus Tirronen	100.00	58	70	72	65	66	68	64	62	60	61	49	55	55	0	46	61	0

	MOYENNE D'ÉQUIPE	99.67	64	70	67	70	67	74	66	68	67	64	50	56	56	0	48	64

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Kurt Kleinendorst	54	61	63	65	60	58	60	USA	55	5	100,000$

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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	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS
1	Chris Wideman	Senators (OTT)		D	4	6	7	13	10	2	0	4	19	11	11	31.58%	6	25.:.24	0	1	1	0	13	0	0	0.00%	0	6	4	0	1	2.56	0	0
2	Robby Fabbri	Senators (OTT)		C/LW/RW	4	6	4	10	3	5	5	5	14	5	13	42.86%	2	21.:.24	2	0	2	0	14	0	0	48.00%	25	25	4	0	1	2.34	0	0
3	Jakub Nakladal	Senators (OTT)		D	4	5	4	9	9	0	0	2	12	3	6	41.67%	4	20.:.20	0	0	0	0	8	1	0	0.00%	0	2	6	0	1	2.21	0	0
4	Scott Harrington	Senators (OTT)		D	4	1	7	8	9	0	0	8	15	7	6	6.67%	6	20.:.24	0	0	0	0	8	0	0	0.00%	0	2	7	0	0	1.96	0	0
5	Klas Dahlbeck	Senators (OTT)		D	4	3	4	7	10	0	0	16	8	3	6	37.50%	14	25.:.26	0	0	0	0	14	0	0	0.00%	0	1	5	0	1	1.38	0	0
6	Miikka Salomaki	Senators (OTT)		LW/RW	4	3	2	5	6	0	0	5	13	3	10	23.08%	2	15.:.01	0	0	0	0	5	1	0	50.00%	2	14	0	0	0	1.66	0	0
7	Michael McCarron	Senators (OTT)		C/RW	4	3	2	5	5	56	30	6	8	4	9	37.50%	0	11.:.29	0	0	0	0	0	0	0	62.50%	24	6	1	0	1	2.18	0	0
8	Viktor Tikhonov	Senators (OTT)		C/LW/RW	4	2	3	5	4	0	0	6	6	0	3	33.33%	2	17.:.19	0	1	1	0	0	0	0	41.03%	78	0	3	0	0	1.44	0	0
9	Sergei Plotnikov	Senators (OTT)		LW/RW	4	0	3	3	4	6	0	8	8	1	3	0.00%	1	17.:.26	0	1	1	0	0	0	0	25.00%	4	6	2	0	0	0.86	0	0
10	Daniel Catenacci	Senators (OTT)		C/LW	4	0	3	3	4	0	0	9	0	3	5	0.00%	0	11.:.52	0	0	0	0	3	0	0	57.89%	19	6	0	0	0	1.26	0	0
11	Zack Mitchell	Senators (OTT)		RW	4	2	1	3	4	2	0	5	2	2	2	100.00%	3	10.:.26	0	0	0	0	0	0	0	50.00%	2	2	3	0	0	1.44	0	0
12	Tom Kuhnhackl	Senators (OTT)		LW/RW	4	1	2	3	6	2	0	4	11	4	7	9.09%	1	16.:.48	0	0	0	0	15	0	0	100.00%	1	10	3	0	0	0.89	0	0
13	Tanner Richard	Senators (OTT)		C	4	0	2	2	8	39	15	5	2	1	1	0.00%	0	15.:.47	0	0	0	0	0	0	0	41.67%	48	0	1	0	0	0.63	0	0
14	Oliver Kylington	Senators (OTT)		D	4	0	1	1	3	2	0	4	2	3	0	0.00%	4	14.:.37	0	0	0	0	0	0	0	0.00%	0	2	2	0	0	0.34	0	0
15	Dylan Blujus	Senators (OTT)		D	4	0	1	1	3	10	10	6	5	4	3	0.00%	2	13.:.45	0	0	0	0	0	0	0	0.00%	0	1	6	0	0	0.36	0	0
16	Stefan Noesen	Senators (OTT)		LW/RW	4	0	1	1	4	5	5	1	1	0	1	0.00%	0	10.:.13	0	0	0	0	0	0	0	0.00%	1	4	0	0	0	0.49	0	0
17	Jordan Weal	Senators (OTT)		C/RW	1	0	0	0	-3	0	0	1	0	1	0	0.00%	2	12.:.41	0	0	0	0	1	0	0	66.67%	3	1	1	0	0	0.00	0	0
Stats d'équipe Total ou en Moyenne		65	32	47	79	89	129	65	95	110	126	55	86	25.40%	49	1083	16.67	2	3	5	9	28	0	1	86	2	0	46.38%	207	88	48	0	5	1.46	0	0	4	4	5	2	2	2

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	PS %	PSA	ST	BG	S2	S3
1	Richard Bachman	Senators (OTT)	4	2	2	0	92.6%	2.47	194	0	0	8	108	65	2	0.0%	0	4	0	1	0
2	Jason Kasdorf	Senators (OTT)	1	0	0	0	87.5%	4.00	45	0	0	3	24	15	1	0.0%	0	0	4	0	0
Stats d'équipe Total ou en Moyenne	5	2	2	0	0.917	2.76	239	0	0	11	132	80	3	0	0.000	4	4	0	1

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Astuces sur les Filtres (Anglais seulement)

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

Nom du Joueur	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	Salaire Année 5	Salaire Année 6	Salaire Année 7	Salaire Année 8	Salaire Année 9	Salaire Année 10	Link
Brian Hart	LW/RW	22	25.11.1993	Yes	203 Lbs	6 ft2	No	No	10	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	Lien
Chris Wideman	D	26	07.01.1990 11:24:59	No	180 Lbs	5 ft10	No	No	1	Pro & Farm	1,300,000$	0$										Lien
Daniel Catenacci	C/LW	23	09.03.1993	No	192 Lbs	5 ft9	No	No	2	Pro & Farm	900,000$	0$	900,000$									Lien
Danny Biega	D	25	29.09.1991 15:13:00	No	205 Lbs	6 ft0	No	No	1	Pro & Farm	1,000,000$	0$										Lien
Dylan Blujus	D	22	22.01.1994	Yes	191 Lbs	6 ft3	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Lien
Felix Girard	C	22	09.05.1994	Yes	185 Lbs	5 ft10	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Lien
Jakub Nakladal	D	28	29.12.1987	No	205 Lbs	6 ft2	No	No	1	Pro & Farm	1,500,000$	0$										Lien
Jason Kasdorf	G	24	08.05.1992 17:28:26	Yes	178 Lbs	6 ft3	No	No	9	Pro & Farm	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Lien
Joey LaLeggia	D	24	24.06.1992 15:05:47	Yes	183 Lbs	5 ft9	No	No	9	Pro & Farm	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Lien
Jordan Weal	C/RW	24	15.04.1992 14:38:36	No	179 Lbs	5 ft10	No	No	1	Pro & Farm	1,000,000$	0$										Lien
Klas Dahlbeck	D	25	06.07.1991 11:27:27	No	207 Lbs	6 ft3	No	No	1	Pro & Farm	1,200,000$	0$										Lien
Mark MacMillan	C/RW	24	23.01.1992	Yes	172 Lbs	6 ft0	No	No	10	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	Lien
Matt Finn	D	22	24.02.1994	Yes	199 Lbs	6 ft0	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Lien
Michael McCarron	C/RW	21	07.03.1995 15:07:56	Yes	237 Lbs	6 ft5	No	No	3	Pro & Farm	1,200,000$	0$	1,200,000$	1,200,000$								Lien
Miikka Salomaki	LW/RW	23	09.03.1993 15:09:23	Yes	198 Lbs	5 ft11	No	No	2	Farm Only	900,000$	0$	900,000$									Lien
Oliver Kylington	D	19	19.05.1997 15:04:29	Yes	181 Lbs	6 ft0	No	No	9	Pro & Farm	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Lien
Patrick McNally	D	24	04.12.1991	Yes	181 Lbs	6 ft2	No	No	10	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	Lien
Rasmus Tirronen	G	25	09.11.1990 0:01:39	No	200 Lbs	6 ft3	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Lien
Richard Bachman	G	29	25.07.1987	No	183 Lbs	5 ft10	No	No	2	Pro & Farm	900,000$	0$	900,000$									Lien
Robby Fabbri	C/LW/RW	20	22.01.1996 16:54:46	Yes	170 Lbs	5 ft10	No	No	3	Pro & Farm	1,600,000$	0$	1,600,000$	1,600,000$								Lien
Scott Harrington	D	23	01.01.1993 15:15:41	Yes	201 Lbs	6 ft2	No	No	1	Pro & Farm	1,000,000$	0$										Lien
Sergei Plotnikov	LW/RW	26	03.06.1990 3:23:02	No	205 Lbs	6 ft2	No	No	1	Pro & Farm	1,000,000$	0$										Lien
Stefan Noesen	LW/RW	23	12.02.1993	Yes	205 Lbs	6 ft2	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Lien
Tanner Richard	C	23	06.04.1993 11:30:09	Yes	176 Lbs	6 ft0	No	No	7	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$				Lien
Tom Kuhnhackl	LW/RW	24	21.02.1992 11:31:02	No	196 Lbs	6 ft2	No	No	1	Pro & Farm	1,200,000$	0$										Lien
Viktor Tikhonov	C/LW/RW	28	12.05.1988 4:06:53	No	189 Lbs	6 ft2	No	No	1	Pro & Farm	1,100,000$	0$										Lien
Zack Mitchell	RW	23	07.01.1993	Yes	185 Lbs	6 ft0	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
27	23.78	192 Lbs	6 ft1	5.1481481481481	633,333$

Attaque à 5 contre 5
Ligne #	Centre	Ailier Gauche	Ailier Droit	% Temps	PHY	DF	OF
1	Viktor Tikhonov	Robby Fabbri	Sergei Plotnikov	40	0	0	5
2	Tanner Richard	Miikka Salomaki	Tom Kuhnhackl	30	1	2	2
3	Tanner Richard	Jordan Weal	Michael McCarron	20	1	3	1
4	Daniel Catenacci	Stefan Noesen	Zack Mitchell	10	2	3	0

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Klas Dahlbeck	Chris Wideman	43	1	2	2
2	Scott Harrington	Jakub Nakladal	34	1	2	2
3	Dylan Blujus	Oliver Kylington	23	2	3	0
4	Klas Dahlbeck	Chris Wideman	0	1	2	2

Attaque en Avantage Numérique
Ligne #	Centre	Ailier Gauche	Ailier Droit	% Temps	PHY	DF	OF
1	Viktor Tikhonov	Sergei Plotnikov	Robby Fabbri	60	0	0	5
2	Tanner Richard	Miikka Salomaki	Tom Kuhnhackl	40	1	1	3

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Klas Dahlbeck	Chris Wideman	60	0	1	4
2	Scott Harrington	Jakub Nakladal	40	0	3	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Robby Fabbri	Tom Kuhnhackl	60	1	2	2
2	Daniel Catenacci	Miikka Salomaki	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Klas Dahlbeck	Chris Wideman	60	1	2	2
2	Scott Harrington	Jakub Nakladal	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Robby Fabbri	60	1	2	2	Klas Dahlbeck	Chris Wideman	60	1	2	2
2	Michael McCarron	40	1	2	2	Scott Harrington	Jakub Nakladal	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Robby Fabbri	Tom Kuhnhackl	60	1	1	3
2	Viktor Tikhonov	Miikka Salomaki	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Klas Dahlbeck	Chris Wideman	60	1	2	2
2	Scott Harrington	Dylan Blujus	40	1	2	2

Attaque Dernière Minute
Centre	Ailier Gauche	Ailier Droit	Défense	Défense
Viktor Tikhonov	Robby Fabbri	Tom Kuhnhackl	Klas Dahlbeck	Chris Wideman

Défense Dernière Minute
Centre	Ailier Gauche	Ailier Droit	Défense	Défense
Robby Fabbri	Miikka Salomaki	Tom Kuhnhackl	Klas Dahlbeck	Chris Wideman

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Tanner Richard, Michael McCarron, Jordan Weal	Tanner Richard, Michael McCarron	Jordan Weal

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Jakub Nakladal, Oliver Kylington, Scott Harrington	Jakub Nakladal	Oliver Kylington, Scott Harrington

Tirs de Pénalité
Robby Fabbri, Miikka Salomaki, Tom Kuhnhackl, Viktor Tikhonov, Sergei Plotnikov

Gardien
#1 : Richard Bachman, #2 : Jason Kasdorf

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	PPG	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
1	Crunch	1	0	1	2	7	-5	0	0.000	2	3	5	12	13	8	38	52	31	46	29	20	28	19	2	1	50.00%	4	1	75.00%	27	58	46.55%	35	78	44.87%	38	77	49.35%	82	51	92	35	65	31
2	Bears	1	0	1	1	2	-1	0	0.000	1	2	3	12	13	8	22	52	31	46	42	9	29	24	1	0	0.00%	2	0	100.00%	27	58	46.55%	35	78	44.87%	38	77	49.35%	82	51	92	35	65	31
3	Marlies	1	1	0	6	1	5	2	1.000	6	11	17	12	13	8	34	52	31	46	32	7	16	27	0	0	0.00%	3	1	66.67%	27	58	46.55%	35	78	44.87%	38	77	49.35%	82	51	92	35	65	31
4	Heat	1	1	0	24	1	23	2	1.000	24	34	58	12	13	8	35	52	31	46	29	13	58	26	1	1	100.00%	4	0	100.00%	27	58	46.55%	35	78	44.87%	38	77	49.35%	82	51	92	35	65	31
	Vs Division	1	1	0	6	1	5	2	1.000	6	11	17	12	13	8	34	52	31	46	32	7	16	27	0	0	0.00%	3	1	66.67%	27	58	46.55%	35	78	44.87%	38	77	49.35%	82	51	92	35	65	31
	Vs Conference	3	1	2	9	10	-1	2	0.333	9	16	25	12	13	8	94	52	31	46	103	36	73	70	3	1	33.33%	9	2	77.78%	27	58	46.55%	35	78	44.87%	38	77	49.35%	82	51	92	35	65	31
	Since Last GM Reset	4	2	2	33	11	22	4	0.500	33	50	83	12	13	8	129	52	31	46	132	49	131	96	4	2	50.00%	13	2	84.62%	27	58	46.55%	35	78	44.87%	38	77	49.35%	82	51	92	35	65	31
	Total	4	2	2	33	11	22	4	0.500	33	50	83	12	13	8	129	52	31	46	132	49	131	96	4	2	50.00%	13	2	84.62%	27	58	46.55%	35	78	44.87%	38	77	49.35%	82	51	92	35	65	31

			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	4	L2	33	50	83	129	132	49	131	96	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	2	2	0	0	0	0	33	11

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	2	0	0	0	0	0	30	2

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	0	2	0	0	0	0	3	9

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
2	2	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	2	50.00%	13	2	84.62%	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
52	31	46	0	12	13	8	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
27	58	46.55%	35	78	44.87%	38	77	49.35%

Temps Avec la Rondelle
En Zone Offensive	Contrôle en Zone Offensive	En Zone Défensive	Contrôle en Zone Défensive	En Zone Neutre	Contrôle en Zone Neutre
82	51	92	35	65	31

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!
Mon, Apr 21	@	Heat1,Senators24	RECAP
Tue, Apr 22	@	Marlies1,Senators6	RECAP
Fri, Apr 25	@	Senators1,Bears2	RECAP
Sat, Apr 26	@	Senators2,Crunch7	RECAP

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
0	0 - 0.00%	0$	0$	3000	100

Dépenses
Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
1,710,000$	680,000$	0$

Dépenses Annuelles à Ce Jour	Cap Salarial Par Jour	Cap salarial à ce jour
0$	0$	0$

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

Afficher ou Masquer des Colonnes

	Ligue											Domicile											Visiteur
Année	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT