Ligue de hockey Simulée Ste-Flanelle

Ottawa
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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 Moyen
1	Alex Formenton (R)		X			100.00	72	73	71	76	73	67	68	66	50	61	68	64	65	44	44	0	50	62	0	20	2	742,500$
2	Brendan Perlini		X	X		100.00	69	44	90	84	79	59	71	66	26	58	59	60	75	64	64	0	50	62	0	23	2	850,000$
3	Alexandre Texier (R)	X				100.00	67	42	90	83	71	63	67	64	42	65	70	60	25	47	47	0	50	62	0	20	3	925,000$
4	Kevin Rooney	X				100.00	79	65	87	68	73	62	81	60	66	58	58	79	25	56	56	0	50	62	0	26	3	850,000$
5	Jayce Hawryluk	X		X		100.00	87	46	82	67	67	58	54	61	38	67	62	60	25	57	57	0	50	59	0	23	2	1,300,000$
6	Jaret Anderson-Dolan (R)	X	X			100.00	72	67	83	79	67	63	64	59	74	59	54	62	51	44	44	0	50	59	0	20	3	792,500$
7	Mackenzie MacEachern		X			100.00	81	64	83	62	72	53	74	62	32	54	62	67	25	55	55	0	50	59	0	25	4	560,000$
8	Jeremy Bracco			X		100.00	75	65	96	60	64	73	77	58	50	69	49	64	45	47	47	0	50	59	0	22	1	700,000$
9	Anthony Richard	X	X			100.00	70	62	87	62	59	80	85	54	67	48	58	63	56	55	55	0	50	58	0	22	1	860,000$
10	Jansen Harkins	X				100.00	67	50	91	67	68	60	82	54	36	58	56	61	25	53	53	0	50	58	0	22	1	825,000$
11	Isaac Ratcliffe (R)		X			100.00	79	79	79	67	79	70	76	50	50	47	48	63	46	44	44	0	50	56	0	20	4	780,833$
12	Matthew Strome (R)		X			100.00	82	78	92	55	78	61	64	49	50	45	48	64	46	44	44	0	50	54	0	20	3	990,000$
13	Andrew Peeke (R)				X	100.00	76	44	93	76	74	63	63	57	25	48	48	63	25	46	46	0	50	60	0	21	2	825,000$
14	Grant Hutton (R)				X	100.00	79	77	83	65	77	64	68	51	25	44	43	63	41	44	44	0	50	58	0	24	1	560,000$
15	Thomas Schemitsch				X	100.00	79	77	81	60	77	68	74	50	25	38	42	62	39	44	44	0	50	57	0	22	1	700,000$
16	Tyler Lewington				X	100.00	68	71	52	62	73	72	75	48	25	39	41	59	40	44	44	0	50	56	0	24	1	525,000$
17	Joseph Cecconi				X	100.00	81	76	91	61	76	52	54	44	25	34	39	63	37	44	44	0	50	55	0	22	2	925,000$
Rayé
1	Kristian Reichel	X				100.00	71	65	86	67	65	62	64	56	70	46	62	61	59	44	44	0	50	56	0	21	1	560,000$
2	Dmitrij Jaskin		X	X		100.00	70	35	88	63	75	52	45	47	35	47	47	58	47	49	46	0	50	52	0	26	2	560,000$
3	Cam Morrison (R)		X			100.00	41	45	45	45	74	39	39	41	45	41	41	45	43	32	30	0	50	42	0	21	2	825,000$
4	Luke Martin (R)				X	100.00	57	55	85	60	78	54	76	35	25	34	30	50	32	58	58	0	50	52	0	21	4	700,000$

	MOYENNE D'ÉQUIPE					100.00	72	61	83	66	72	62	68	54	42	50	52	61	42	48	48	0	50	57

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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	Kasimir Kaskisuo	100.00	56	59	73	78	57	59	53	59	56	58	30	44	44	0	50	57	0
2	Filip Gustavsson	100.00	55	57	71	72	49	58	51	61	57	53	30	44	44	0	50	55	0
Rayé
1	Maksim Zhukov (R)	100.00	45	66	62	70	40	47	40	44	40	43	43	54	54	0	50	49	0
2	Kent Simpson	100.00	37	45	41	74	36	33	33	34	33	33	33	35	32	0	50	39	0

	MOYENNE D'ÉQUIPE	100.00	48	57	62	74	46	49	44	50	47	47	34	44	44	0	50	50

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	PKS	PKM	GW	GT	FO%	FOT	P/20	FW	S1	S2	S3
1	Alexandre Texier	Senators (Ott)	C	8	4	4	8	1	0	0	1	24	43	12	23	9.30%	0	157	19.65	0	3	3	5	15	0	17	0	0	34.03%	191	1.02	0	1	0	0
2	Jayce Hawryluk	Senators (Ott)	C/RW	8	3	3	6	0	2	0	23	10	20	5	19	15.00%	0	139	17.44	2	0	2	7	15	0	0	0	2	57.14%	14	0.86	0	0	0	0
3	Jaret Anderson-Dolan	Senators (Ott)	C/LW	8	4	2	6	-2	6	0	11	26	22	7	14	18.18%	1	129	16.15	0	0	0	0	1	0	2	1	0	55.56%	135	0.93	0	1	0	0
4	Mackenzie MacEachern	Senators (Ott)	LW	8	1	5	6	0	4	0	16	6	21	6	21	4.76%	1	139	17.40	1	2	3	3	15	0	0	0	0	50.00%	8	0.86	0	0	0	0
5	Alex Formenton	Senators (Ott)	LW	8	5	0	5	0	4	0	16	19	40	8	20	12.50%	3	187	23.44	1	0	1	9	14	4	30	3	0	55.41%	74	0.53	0	0	1	1
6	Tyler Lewington	Senators (Ott)	D	8	0	5	5	2	12	0	18	3	5	1	4	0.00%	8	174	21.86	0	1	1	2	15	0	23	0	0	0.00%	0	0.57	0	0	1	0
7	Andrew Peeke	Senators (Ott)	D	8	1	3	4	-3	4	0	11	10	12	2	4	8.33%	13	187	23.41	0	1	1	5	14	0	27	0	1	0.00%	0	0.43	0	0	1	0
8	Jeremy Bracco	Senators (Ott)	RW	8	1	3	4	-3	4	0	11	15	12	2	11	8.33%	0	140	17.61	0	0	0	0	2	0	14	0	0	50.00%	22	0.57	0	0	0	1
9	Kevin Rooney	Senators (Ott)	C	8	1	3	4	-3	6	0	11	22	24	9	12	4.17%	5	154	19.32	0	0	0	4	14	1	16	0	0	60.91%	197	0.52	0	0	0	0
10	Brendan Perlini	Senators (Ott)	LW/RW	8	0	3	3	-2	2	0	2	11	22	5	8	0.00%	2	168	21.02	0	0	0	3	14	2	31	0	0	30.77%	13	0.36	0	0	0	0
11	Jansen Harkins	Senators (Ott)	C	8	0	2	2	-2	2	0	4	4	4	3	5	0.00%	10	121	15.17	0	0	0	0	0	0	0	0	0	34.62%	26	0.33	0	0	0	0
12	Joseph Cecconi	Senators (Ott)	D	8	1	1	2	-2	8	0	23	3	3	3	4	33.33%	6	127	15.89	0	0	0	0	2	0	14	0	0	0.00%	0	0.31	0	0	0	0
13	Grant Hutton	Senators (Ott)	D	8	0	2	2	-2	2	0	20	3	6	0	6	0.00%	9	188	23.51	0	1	1	2	14	0	28	0	0	0.00%	0	0.21	0	0	0	0
14	Anthony Richard	Senators (Ott)	C/LW	8	0	1	1	-2	2	0	10	13	15	4	10	0.00%	0	122	15.27	0	0	0	0	0	0	0	0	0	58.33%	12	0.16	0	0	0	0
15	Isaac Ratcliffe	Senators (Ott)	LW	8	0	1	1	2	0	0	4	0	3	0	4	0.00%	1	25	3.13	0	0	0	0	0	0	0	0	0	100.00%	1	0.80	0	0	0	0
16	Thomas Schemitsch	Senators (Ott)	D	8	0	1	1	2	23	5	16	4	10	3	3	0.00%	14	169	21.22	0	0	0	6	14	0	26	0	0	0.00%	0	0.12	1	0	0	0
17	Matthew Strome	Senators (Ott)	LW	8	0	0	0	-1	2	0	2	4	0	1	1	0.00%	1	25	3.19	0	0	0	0	1	0	9	0	0	50.00%	12	0.00	0	0	0	0
Stats d'équipe Total ou en Moyenne				136	21	39	60	-15	83	5	199	177	262	71	169	8.02%	74	2357	17.33	4	8	12	46	156	7	243	4	3	49.79%	705	0.51	1	2	3	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	SO	GA	SA	A	EG	ST	BG	S1	S2	S3
1	Kasimir Kaskisuo	Senators (Ott)	8	4	3	0.923	3.09	446	1	23	298	1	1	8	0	2	1	2
2	Filip Gustavsson	Senators (Ott)	1	0	1	0.900	3.33	36	0	2	20	0	0	0	8	0	0	0
Stats d'équipe Total ou en Moyenne			9	4	4	0.921	3.11	483	1	25	318	1	1	8	8	2	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 Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Type	Salaire Actuel	Salaire Restant	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Salaire Année 4	Link
Alex Formenton	Senators (Ott)	LW	20	1999-09-13	Yes	190 Lbs	6 ft3	No	No	No	2	Pro & Farm	742,500$	265,178$	74,250$	26,518$	No	742,500$			Lien
Alexandre Texier	Senators (Ott)	C	20	1999-09-13	Yes	192 Lbs	6 ft1	No	No	No	3	Pro & Farm	925,000$	330,357$	92,500$	33,036$	No	925,000$	925,000$		Lien
Andrew Peeke	Senators (Ott)	D	21	1998-03-17	Yes	198 Lbs	6 ft3	No	No	No	2	Pro & Farm	825,000$	294,642$	82,500$	29,464$	No	825,000$			Lien
Anthony Richard	Senators (Ott)	C/LW	22	1996-12-19	No	163 Lbs	5 ft10	Yes	No	No	1	Pro & Farm	860,000$	307,142$	86,000$	30,714$	No				Lien
Brendan Perlini	Senators (Ott)	LW/RW	23	1996-04-27	No	212 Lbs	6 ft3	No	No	No	2	Pro & Farm	850,000$	303,571$	85,000$	30,357$	No	850,000$			Lien
Cam Morrison	Senators (Ott)	LW	21	1998-08-27	Yes	212 Lbs	6 ft3	No	No	No	2	Pro & Farm	825,000$	294,642$	82,500$	29,464$	No	825,000$			Lien
Dmitrij Jaskin	Senators (Ott)	LW/RW	26	1993-03-23	No	216 Lbs	6 ft2	No	No	No	2	Pro & Farm	560,000$	200,000$	56,000$	20,000$	No	560,000$			Lien
Filip Gustavsson	Senators (Ott)	G	21	1998-06-07	No	184 Lbs	6 ft2	No	No	No	2	Pro & Farm	742,500$	265,178$	74,250$	26,518$	No	742,500$			Lien
Grant Hutton	Senators (Ott)	D	24	1995-07-25	Yes	205 Lbs	6 ft3	Yes	No	No	1	Pro & Farm	560,000$	200,000$	56,000$	20,000$	No				Lien
Isaac Ratcliffe	Senators (Ott)	LW	20	1999-02-15	Yes	201 Lbs	6 ft6	No	No	No	4	Pro & Farm	780,833$	278,868$	78,083$	27,887$	No	780,833$	780,833$	780,833$	Lien
Jansen Harkins	Senators (Ott)	C	22	1997-05-23	No	182 Lbs	6 ft1	No	No	No	1	Pro & Farm	825,000$	294,642$	82,500$	29,464$	No				Lien
Jaret Anderson-Dolan	Senators (Ott)	C/LW	20	1999-09-11	Yes	188 Lbs	5 ft11	No	No	No	3	Pro & Farm	792,500$	283,035$	79,250$	28,304$	No	792,500$	792,500$		Lien
Jayce Hawryluk	Senators (Ott)	C/RW	23	1996-01-01	No	186 Lbs	5 ft11	No	No	No	2	Pro & Farm	1,300,000$	464,285$	130,000$	46,429$	No	1,300,000$			Lien
Jeremy Bracco	Senators (Ott)	RW	22	1997-03-17	No	180 Lbs	5 ft9	No	No	No	1	Pro & Farm	700,000$	250,000$	70,000$	25,000$	No				Lien
Joseph Cecconi	Senators (Ott)	D	22	1997-05-23	No	209 Lbs	6 ft2	No	No	No	2	Pro & Farm	925,000$	330,357$	92,500$	33,036$	No	925,000$			Lien
Kasimir Kaskisuo	Senators (Ott)	G	26	1993-10-01	No	201 Lbs	6 ft2	No	No	No	2	Pro & Farm	925,000$	330,357$	92,500$	33,036$	No	925,000$			Lien
Kent Simpson	Senators (Ott)	G	27	1992-03-26	No	198 Lbs	6 ft2	No	No	No	1	Pro & Farm	550,000$	196,428$	55,000$	19,643$	No				Lien
Kevin Rooney	Senators (Ott)	C	26	1993-05-21	No	190 Lbs	6 ft2	No	No	No	3	Pro & Farm	850,000$	303,571$	85,000$	30,357$	No	850,000$	850,000$		Lien
Kristian Reichel	Senators (Ott)	C	21	1998-06-11	No	176 Lbs	6 ft0	Yes	No	No	1	Pro & Farm	560,000$	200,000$	56,000$	20,000$	No				Lien
Luke Martin	Senators (Ott)	D	21	1998-09-20	Yes	218 Lbs	6 ft2	No	No	No	4	Pro & Farm	700,000$	250,000$	70,000$	25,000$	No	700,000$	700,000$	700,000$	Lien
Mackenzie MacEachern	Senators (Ott)	LW	25	1994-03-08	No	190 Lbs	6 ft2	Yes	No	No	4	Pro & Farm	560,000$	200,000$	56,000$	20,000$	No	560,000$	560,000$	560,000$	Lien
Maksim Zhukov	Senators (Ott)	G	20	1999-07-22	Yes	187 Lbs	6 ft3	Yes	No	No	1	Pro & Farm	560,000$	200,000$	56,000$	20,000$	No				Lien
Matthew Strome	Senators (Ott)	LW	20	1999-01-05	Yes	206 Lbs	6 ft4	Yes	No	No	3	Pro & Farm	990,000$	353,571$	99,000$	35,357$	No	990,000$	990,000$		Lien
Thomas Schemitsch	Senators (Ott)	D	22	1996-10-25	No	200 Lbs	6 ft4	No	No	No	1	Pro & Farm	700,000$	250,000$	70,000$	25,000$	No				Lien
Tyler Lewington	Senators (Ott)	D	24	1994-12-05	No	189 Lbs	6 ft1	No	No	No	1	Pro & Farm	525,000$	187,500$	52,500$	18,750$	No				Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
25	22.36	195 Lbs	6 ft2	2.04	765,333$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Alex Formenton	Kevin Rooney	Brendan Perlini	40	1	2	2
2	Mackenzie MacEachern	Alexandre Texier	Jayce Hawryluk	30	1	2	2
3	Anthony Richard	Jaret Anderson-Dolan	Jeremy Bracco	20	1	2	2
4	Isaac Ratcliffe	Jansen Harkins	Alex Formenton	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Andrew Peeke	Grant Hutton	40	1	2	2
2	Thomas Schemitsch	Tyler Lewington	30	1	2	2
3	Joseph Cecconi	Jansen Harkins	20	1	2	2
4	Andrew Peeke	Grant Hutton	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Alex Formenton	Kevin Rooney	Brendan Perlini	60	1	2	2
2	Mackenzie MacEachern	Alexandre Texier	Jayce Hawryluk	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Andrew Peeke	Grant Hutton	60	1	2	2
2	Thomas Schemitsch	Tyler Lewington	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Alex Formenton	Brendan Perlini	60	1	2	2
2	Kevin Rooney	Alexandre Texier	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Andrew Peeke	Grant Hutton	60	1	2	2
2	Thomas Schemitsch	Tyler Lewington	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Formenton	60	1	2	2	Andrew Peeke	Grant Hutton	60	1	2	2
2	Brendan Perlini	40	1	2	2	Thomas Schemitsch	Tyler Lewington	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Alex Formenton	Brendan Perlini	60	1	2	2
2	Kevin Rooney	Alexandre Texier	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Andrew Peeke	Grant Hutton	60	1	2	2
2	Thomas Schemitsch	Tyler Lewington	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Alex Formenton	Kevin Rooney	Brendan Perlini	Andrew Peeke	Grant Hutton

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Alex Formenton	Kevin Rooney	Brendan Perlini	Andrew Peeke	Grant Hutton

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Matthew Strome, Jaret Anderson-Dolan, Jeremy Bracco	Matthew Strome, Jaret Anderson-Dolan	Jeremy Bracco

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Joseph Cecconi, Thomas Schemitsch, Tyler Lewington	Joseph Cecconi	Thomas Schemitsch, Tyler Lewington

Tirs de Pénalité
Alex Formenton, Brendan Perlini, Kevin Rooney, Alexandre Texier, Mackenzie MacEachern

Gardien
#1 : Kasimir Kaskisuo, #2 : Filip Gustavsson

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

	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	Marlies	6	4	2	0	0	0	0	0	15	16	-1	3	2	1	0	0	0	0	0	5	3	2	3	2	1	0	0	0	0	0	10	13	-3	8	0.667	15	28	43	0	1	7	6	7	1	204	81	86	94	1	238	56	54	157	14	3	21.43%	27	4	85.19%	0	139	269	51.67%	152	302	50.33%	60	134	44.78%	174	115	202	61	106	50
2	Phantoms	2	0	2	0	0	0	0	0	6	10	-4	0	0	0	0	0	0	0	0	0	0	0	2	0	2	0	0	0	0	0	6	10	-4	0	0.000	6	11	17	1	0	7	6	7	1	58	81	86	94	1	81	18	29	42	4	1	25.00%	7	2	71.43%	0	139	269	51.67%	152	302	50.33%	60	134	44.78%	174	115	202	61	106	50
	Total	8	4	4	0	0	0	0	0	21	26	-5	3	2	1	0	0	0	0	0	5	3	2	5	2	3	0	0	0	0	0	16	23	-7	8	0.500	21	39	60	1	1	7	6	7	1	262	81	86	94	1	319	74	83	199	18	4	22.22%	34	6	82.35%	0	139	269	51.67%	152	302	50.33%	60	134	44.78%	174	115	202	61	106	50
	_Since Last GM Reset	8	4	4	0	0	0	0	0	21	26	-5	3	2	1	0	0	0	0	0	5	3	2	5	2	3	0	0	0	0	0	16	23	-7	8	0.500	21	39	60	1	1	7	6	7	1	262	81	86	94	1	319	74	83	199	18	4	22.22%	34	6	82.35%	0	139	269	51.67%	152	302	50.33%	60	134	44.78%	174	115	202	61	106	50
	_Vs Conference	8	4	4	0	0	0	0	0	21	26	-5	3	2	1	0	0	0	0	0	5	3	2	5	2	3	0	0	0	0	0	16	23	-7	8	0.500	21	39	60	1	1	7	6	7	1	262	81	86	94	1	319	74	83	199	18	4	22.22%	34	6	82.35%	0	139	269	51.67%	152	302	50.33%	60	134	44.78%	174	115	202	61	106	50

			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
8	8	L2	21	39	60	262	319	74	83	199	1	1

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	4	4	0	0	0	0	21	26

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	2	1	0	0	0	0	5	3

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	2	3	0	0	0	0	16	23

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	4	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
18	4	22.22%	34	6	82.35%	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
81	86	94	1	7	6	7	1

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
139	269	51.67%	152	302	50.33%	60	134	44.78%

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
174	115	202	61	106	50

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	Lien
1 - 2021-04-27	1	Senators	3	Marlies	2	W		Sommaire du Match
3 - 2021-04-29	9	Senators	2	Marlies	7	L		Sommaire du Match
5 - 2021-05-01	17	Marlies	0	Senators	2	W		Sommaire du Match
7 - 2021-05-03	25	Marlies	2	Senators	1	L		Sommaire du Match
9 - 2021-05-05	33	Senators	5	Marlies	4	W	X	Sommaire du Match
11 - 2021-05-07	41	Marlies	1	Senators	2	W		Sommaire du Match
15 - 2021-05-11	57	Senators	4	Phantoms	6	L		Sommaire du Match
17 - 2021-05-13	61	Senators	2	Phantoms	4	L		Sommaire du Match
19 - 2021-05-15	65	Phantoms	-	Senators	-
21 - 2021-05-17	69	Phantoms	-	Senators	-
23 - 2021-05-19	73	Senators	-	Phantoms	-
25 - 2021-05-21	77	Phantoms	-	Senators	-
27 - 2021-05-23	81	Senators	-	Phantoms	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	50	20
Assistance	4,242	2,170
Assistance PCT	70.70%	72.33%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
-3	2137 - 71.24%	85,167$	255,500$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
0$	1,913,333$	1,913,333$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	0$	25	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	10	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