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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP	Âge	Contrat	Salaire
1	Matthew Poitras (R)	X				100.00	65	41	93	77	64	65	57	67	72	75	68	65	25	47	47	0	52	68	0	20	3	870,000$
2	Joshua Roy (R)			X		98.00	65	42	99	78	68	62	69	70	34	67	70	66	25	46	46	0	55	68	0	21	3	835,000$
3	Jujhar Khaira	X	X			100.00	82	80	86	78	80	59	58	66	80	65	59	74	56	65	66	0	50	68	0	30	2	975,000$
4	Noah Cates	X	X			100.00	73	42	99	77	63	66	88	68	63	65	59	80	25	59	59	0	55	67	0	25	1	925,000$
5	Tomas Tatar			X		100.00	67	42	90	79	65	62	93	67	33	66	64	67	59	79	82	0	56	67	0	33	1	5,900,000$
6	Trevor Lewis	X		X		100.00	76	44	91	76	74	59	99	64	54	60	59	75	63	83	88	0	49	67	0	37	1	700,000$
7	Alex Belzile	X		X		100.00	70	70	69	65	70	75	78	65	80	62	62	66	59	58	58	0	50	64	0	33	2	750,000$
8	Fredrik Olofsson	X	X			100.00	71	43	95	67	73	54	87	65	68	60	57	80	25	55	56	0	54	64	0	28	3	1,100,000$
9	Brad Lambert (R)	X		X		100.00	72	68	82	71	68	60	59	64	80	63	62	63	59	44	44	0	38	64	0	20	3	918,333$
10	John Leonard			X		100.00	73	67	88	72	67	81	87	59	50	57	57	63	54	45	45	0	50	62	0	26	1	750,000$
11	Rasmus Asplund	X	X			100.00	75	69	89	61	69	70	73	61	76	62	53	68	50	61	61	0	53	61	0	26	1	825,000$
12	Oskar Steen	X		X		100.00	88	45	95	68	65	53	79	66	25	50	56	69	25	50	50	0	48	60	0	26	2	750,000$
13	Luke Schenn				X	100.00	97	95	80	72	85	66	84	63	25	49	47	80	25	84	87	0	49	69	0	34	1	850,000$
14	Ryker Evans				X	100.00	82	44	83	73	70	77	82	74	25	56	48	68	25	47	47	0	47	68	0	22	3	897,500$
15	Noah Juulsen				X	100.00	95	46	87	74	72	65	75	62	25	49	47	85	25	56	56	0	52	68	0	27	1	775,000$
16	Lassi Thomson				X	100.00	72	70	76	73	70	72	78	49	25	41	42	60	40	45	45	0	48	58	0	24	1	863,333$
17	Riley Stillman				X	100.00	72	72	71	65	72	61	66	46	25	34	40	63	38	60	60	0	57	55	0	26	1	800,000$
Rayé
1	Kasperi Kapanen			X		100.00	73	43	93	88	71	67	87	68	36	67	58	77	25	70	72	0	52	69	0	28	2	3,200,000$
2	Brendan Gaunce	X	X			91.97	85	46	91	67	79	59	64	65	84	58	58	75	25	50	50	0	41	64	0	30	3	762,500$
3	Tobias Bjornfot				X	100.00	77	73	87	74	73	54	58	43	25	28	39	64	37	58	58	0	47	55	0	23	3	775,000$

	MOYENNE D'ÉQUIPE					99.45	77	57	87	73	71	64	76	63	49	57	55	70	38	58	59	0	50	64

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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	Pheonix Copley	99.00	65	58	73	83	68	65	70	68	68	67	45	54	55	0	49	66	0
2	Arvid Soderblom	100.00	62	68	65	73	65	58	69	63	65	62	75	48	48	0	53	64	0
Rayé
1	Cal Petersen	100.00	51	57	71	70	49	53	52	57	52	52	30	57	58	0	45	55	0

	MOYENNE D'ÉQUIPE	99.67	59	61	70	75	61	59	64	63	62	60	50	53	54	0	49	62

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Alex Westlund	40	40	40	40	40	40	40	TUR	80	2	500,000$

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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	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	P/20	PSS	S1	S2	S3
1	Jujhar Khaira	Titans (Bos)	C/LW	8	3	5	8	1	2	16	29	36	10	26	8.33%	2	150	18.84	1	3	4	8	34	0	0	0	1	10	0	0	62.38%	202	1.06	2	0	0	1
2	Trevor Lewis	Titans (Bos)	C/RW	8	4	4	8	7	0	10	15	28	4	7	14.29%	1	108	13.59	0	1	1	3	2	0	0	0	0	0	2	1	57.43%	101	1.47	0	2	0	0
3	Noah Juulsen	Titans (Bos)	D	8	0	6	6	3	6	21	12	23	6	19	0.00%	16	172	21.60	0	1	1	17	25	0	0	0	1	14	0	0	0.00%	0	0.69	0	0	0	1
4	Matthew Poitras	Titans (Bos)	C	7	1	4	5	1	0	8	18	12	6	15	8.33%	0	129	18.54	0	0	0	1	22	0	0	0	0	8	0	0	58.78%	148	0.77	1	0	1	0
5	Noah Cates	Titans (Bos)	C/LW	7	2	3	5	1	6	7	10	31	11	25	6.45%	5	116	16.59	2	2	4	11	28	0	0	0	0	0	0	0	85.71%	7	0.86	0	1	0	0
6	Alex Belzile	Titans (Bos)	C/RW	8	0	4	4	3	6	9	13	8	3	10	0.00%	1	59	7.49	0	0	0	0	2	0	0	0	0	0	0	0	52.33%	86	1.34	0	0	1	0
7	Fredrik Olofsson	Titans (Bos)	C/LW	8	2	2	4	-2	10	10	8	22	8	13	9.09%	4	121	15.17	0	0	0	9	22	0	0	0	0	0	1	0	62.50%	8	0.66	0	0	0	0
8	Joshua Roy	Titans (Bos)	RW	7	4	0	4	0	6	5	8	22	8	16	18.18%	3	146	20.99	0	0	0	4	21	1	0	1	1	21	0	0	42.86%	14	0.54	2	1	0	0
9	Luke Schenn	Titans (Bos)	D	7	1	3	4	0	8	36	10	14	1	6	7.14%	7	162	23.16	1	1	2	9	27	0	0	0	0	13	0	0	0.00%	0	0.49	0	0	1	1
10	Ryker Evans	Titans (Bos)	D	7	1	2	3	4	2	10	8	13	2	6	7.69%	7	156	22.31	0	0	0	6	22	0	0	0	0	17	1	0	0.00%	0	0.38	0	0	0	2
11	Riley Stillman	Titans (Bos)	D	8	1	2	3	4	4	25	6	8	0	2	12.50%	5	128	16.11	0	0	0	1	5	0	0	0	0	8	0	0	0.00%	0	0.47	0	1	0	0
12	Rasmus Asplund	Titans (Bos)	C/LW	7	2	1	3	5	2	7	3	7	0	4	28.57%	3	92	13.17	0	0	0	0	0	0	0	0	0	0	0	0	66.67%	6	0.65	0	0	1	0
13	Tomas Tatar	Titans (Bos)	RW	7	0	3	3	5	4	0	12	18	4	12	0.00%	1	100	14.39	0	0	0	1	0	0	0	0	0	7	0	0	28.57%	7	0.60	0	0	0	0
14	Kasperi Kapanen	Titans (Bos)	RW	4	2	1	3	-1	0	5	11	17	4	13	11.76%	4	96	24.19	0	0	0	1	16	0	0	0	0	12	0	0	41.86%	43	0.62	1	0	0	0
15	Simon Nemec	Bruins	D	3	0	2	2	-2	0	0	3	5	2	5	0.00%	4	71	23.97	0	0	0	2	9	0	1	1	0	9	0	0	0.00%	0	0.56	0	0	0	0
16	Brendan Gaunce	Titans (Bos)	C/LW	1	1	0	1	0	0	0	3	4	1	1	25.00%	0	10	10.00	1	0	1	2	1	0	0	0	0	0	0	0	100.00%	2	2.00	0	0	0	0
17	Brad Lambert	Titans (Bos)	C/RW	7	0	1	1	1	2	2	1	5	6	6	0.00%	1	39	5.69	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0.50	0	0	0	0
18	Oskar Steen	Titans (Bos)	C/RW	7	0	0	0	0	0	0	0	1	0	1	0.00%	0	7	1.05	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	1	0.00	0	0	0	0
19	John Leonard	Titans (Bos)	RW	7	0	0	0	0	0	0	2	1	0	0	0.00%	0	16	2.31	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	3	0.00	0	0	0	0
20	Lassi Thomson	Titans (Bos)	D	7	0	0	0	4	6	14	5	2	1	1	0.00%	4	105	15.12	0	0	0	0	2	0	0	0	0	1	0	0	0.00%	0	0.00	0	0	0	0
Stats d'équipe Total ou en Moyenne				133	24	43	67	34	64	185	177	277	77	188	8.66%	68	1994	14.99	5	8	13	75	247	1	1	2	3	130	4	1	57.17%	628	0.67	6	5	4	5

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	SO	GA	SA	A	PS %	PSA	ST	BG	S1	S2	S3
1	Pheonix Copley	Titans (Bos)	7	3	2	2	0.928	2.25	427	1	16	222	0	0.667	6	7	0	1	2	1
2	Arvid Soderblom	Titans (Bos)	1	1	0	0	0.917	3.00	60	0	3	36	1	0.000	0	1	8	0	0	0
Stats d'équipe Total ou en Moyenne			8	4	2	2	0.926	2.34	487	1	19	258	1	0.667	6	8	8	1	2	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	Type	Salaire Actuel	Salaire Restant	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Link
Alex Belzile	Titans (Bos)	C/RW	33	1991-08-31	No	194 Lbs	6 ft0	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$		Lien / Lien NHL
Arvid Soderblom	Titans (Bos)	G	25	1999-08-19	No	180 Lbs	6 ft3	No	No	No	1	Pro & Farm	883,750$	883,750$	0$	0$	No			Lien
Brad Lambert	Titans (Bos)	C/RW	20	2003-12-19	Yes	183 Lbs	6 ft1	No	No	No	3	Pro & Farm	918,333$	918,333$	0$	0$	No	918,333$	918,333$	Lien
Brendan Gaunce (Sur la Masse Salariale)	Titans (Bos)	C/LW	30	1994-03-25	No	216 Lbs	6 ft2	No	No	No	3	Pro & Farm	762,500$	762,500$	0$	0$	No	762,500$	762,500$	Lien / Lien NHL
Cal Petersen	Titans (Bos)	G	29	1994-10-19	No	185 Lbs	6 ft1	No	No	No	1	Pro & Farm	858,333$	858,333$	0$	0$	No			Lien
Fredrik Olofsson	Titans (Bos)	C/LW	28	1996-05-27	No	196 Lbs	6 ft2	No	No	No	3	Pro & Farm	1,100,000$	1,100,000$	0$	0$	No	1,100,000$	1,100,000$	Lien
John Leonard	Titans (Bos)	RW	26	1998-08-07	No	185 Lbs	5 ft11	No	No	No	1	Pro & Farm	750,000$	750,000$	0$	0$	No			Lien
Joshua Roy	Titans (Bos)	RW	21	2003-08-06	Yes	189 Lbs	6 ft0	No	No	No	3	Pro & Farm	835,000$	835,000$	0$	0$	No	835,000$	835,000$	Lien
Jujhar Khaira	Titans (Bos)	C/LW	30	1994-08-13	No	211 Lbs	6 ft4	No	No	No	2	Pro & Farm	975,000$	975,000$	0$	0$	No	975,000$		Lien / Lien NHL
Kasperi Kapanen	Titans (Bos)	RW	28	1996-07-23	No	194 Lbs	6 ft1	No	No	No	2	Pro & Farm	3,200,000$	3,200,000$	0$	0$	No	3,200,000$		Lien / Lien NHL
Lassi Thomson	Titans (Bos)	D	24	2000-09-24	No	192 Lbs	6 ft0	No	No	No	1	Pro & Farm	863,333$	863,333$	0$	0$	No			Lien
Luke Schenn	Titans (Bos)	D	34	1989-11-01	No	227 Lbs	6 ft2	No	No	No	1	Pro & Farm	850,000$	850,000$	0$	0$	No			Lien / Lien NHL
Matthew Poitras	Titans (Bos)	C	20	2004-03-10	Yes	176 Lbs	5 ft11	No	No	No	3	Pro & Farm	870,000$	870,000$	0$	0$	No	870,000$	870,000$	Lien
Noah Cates	Titans (Bos)	C/LW	25	1999-02-05	No	169 Lbs	6 ft1	No	No	No	1	Pro & Farm	925,000$	925,000$	0$	0$	No			Lien
Noah Juulsen	Titans (Bos)	D	27	1997-04-02	No	194 Lbs	6 ft2	No	No	No	1	Pro & Farm	775,000$	775,000$	0$	0$	No			Lien / Lien NHL
Oskar Steen	Titans (Bos)	C/RW	26	1998-03-09	No	187 Lbs	5 ft9	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$		Lien / Lien NHL
Pheonix Copley	Titans (Bos)	G	32	1992-01-18	No	200 Lbs	6 ft4	No	No	No	3	Pro & Farm	1,500,000$	1,500,000$	0$	0$	No	1,500,000$	1,500,000$	Lien / Lien NHL
Rasmus Asplund	Titans (Bos)	C/LW	26	1997-12-03	No	190 Lbs	5 ft11	No	No	No	1	Pro & Farm	825,000$	825,000$	0$	0$	No			Lien / Lien NHL
Riley Stillman	Titans (Bos)	D	26	1998-03-09	No	196 Lbs	6 ft1	No	No	No	1	Pro & Farm	800,000$	800,000$	0$	0$	No			Lien / Lien NHL
Ryker Evans	Titans (Bos)	D	22	2001-12-13	No	191 Lbs	6 ft0	No	No	No	3	Pro & Farm	897,500$	897,500$	0$	0$	No	897,500$	897,500$	Lien
Tobias Bjornfot	Titans (Bos)	D	23	2001-04-06	No	202 Lbs	6 ft0	No	No	No	3	Pro & Farm	775,000$	775,000$	0$	0$	No	775,000$	775,000$	Lien
Tomas Tatar	Titans (Bos)	RW	33	1990-11-30	No	183 Lbs	5 ft10	No	No	No	1	Pro & Farm	5,900,000$	5,900,000$	0$	0$	No			Lien / Lien NHL
Trevor Lewis	Titans (Bos)	C/RW	37	1987-01-07	No	202 Lbs	6 ft1	No	No	No	1	Pro & Farm	700,000$	700,000$	0$	0$	No			Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
23	27.17	193 Lbs	6 ft1	1.87	1,194,076$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Noah Cates	Jujhar Khaira		35	1	2	2
2	Fredrik Olofsson	Matthew Poitras	Joshua Roy	35	1	2	2
3	Rasmus Asplund	Trevor Lewis	Tomas Tatar	25	1	2	2
4		Alex Belzile	Brad Lambert	5	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Luke Schenn	35	1	2	2
2	Ryker Evans	Noah Juulsen	35	1	2	2
3	Lassi Thomson	Riley Stillman	25	1	2	2
4		Luke Schenn	5	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Noah Cates	Jujhar Khaira		60	1	2	2
2	Fredrik Olofsson	Matthew Poitras	Joshua Roy	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Luke Schenn	60	1	2	2
2	Ryker Evans	Noah Juulsen	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1		Joshua Roy	60	1	2	2
2	Jujhar Khaira	Matthew Poitras	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Luke Schenn	60	1	2	2
2	Ryker Evans	Noah Juulsen	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1		60	1	2	2		Luke Schenn	60	1	2	2
2	Joshua Roy	40	1	2	2	Ryker Evans	Noah Juulsen	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1		Joshua Roy	60	1	2	2
2	Jujhar Khaira	Matthew Poitras	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Luke Schenn	60	1	2	2
2	Ryker Evans	Noah Juulsen	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Noah Cates	Jujhar Khaira			Luke Schenn

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Noah Cates	Jujhar Khaira			Luke Schenn

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
John Leonard, Oskar Steen, Tomas Tatar	John Leonard, Oskar Steen	Tomas Tatar

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Lassi Thomson, Riley Stillman, Ryker Evans	Lassi Thomson	Riley Stillman, Ryker Evans

Tirs de Pénalité
, Joshua Roy, Jujhar Khaira, Matthew Poitras, Tomas Tatar

Gardien
#1 : Pheonix Copley, #2 : Arvid Soderblom

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	Bulldogs	2	1	1	0	0	0	0	0	6	4	2	1	0	1	0	0	0	0	0	2	3	-1	1	1	0	0	0	0	0	0	4	1	3	2	0.500	6	10	16	0	0	5	11	11	0	76	105	90	91	13	51	18	12	51	10	1	10.00%	6	1	83.33%	0	179	311	57.56%	139	267	52.06%	69	124	55.65%	196	137	195	58	98	50
2	Hit Man	2	1	0	0	0	0	0	1	9	8	1	1	0	0	0	0	0	0	1	4	5	-1	1	1	0	0	0	0	0	0	5	3	2	3	0.750	9	17	26	0	0	5	11	11	0	83	105	90	91	13	84	20	10	54	11	3	27.27%	4	2	50.00%	0	179	311	57.56%	139	267	52.06%	69	124	55.65%	196	137	195	58	98	50
3	Phantoms	2	1	0	0	0	0	0	1	5	4	1	1	1	0	0	0	0	0	0	3	1	2	1	0	0	0	0	0	0	1	2	3	-1	3	0.750	5	8	13	0	0	5	11	11	0	64	105	90	91	13	61	20	16	47	7	0	0.00%	6	0	100.00%	0	179	311	57.56%	139	267	52.06%	69	124	55.65%	196	137	195	58	98	50
4	Saints	2	1	1	0	0	0	0	0	7	5	2	1	0	1	0	0	0	0	0	4	5	-1	1	1	0	0	0	0	0	0	3	0	3	2	0.500	7	12	19	0	1	5	11	11	0	69	105	90	91	13	62	22	26	46	8	1	12.50%	10	3	70.00%	1	179	311	57.56%	139	267	52.06%	69	124	55.65%	196	137	195	58	98	50
	Total	8	4	2	0	0	0	0	2	27	21	6	4	1	2	0	0	0	0	1	13	14	-1	4	3	0	0	0	0	0	1	14	7	7	10	0.625	27	47	74	0	1	5	11	11	0	292	105	90	91	13	258	80	64	198	36	5	13.89%	26	6	76.92%	1	179	311	57.56%	139	267	52.06%	69	124	55.65%	196	137	195	58	98	50
	_Since Last GM Reset	8	4	2	0	0	0	0	2	27	21	6	4	1	2	0	0	0	0	1	13	14	-1	4	3	0	0	0	0	0	1	14	7	7	10	0.625	27	47	74	0	1	5	11	11	0	292	105	90	91	13	258	80	64	198	36	5	13.89%	26	6	76.92%	1	179	311	57.56%	139	267	52.06%	69	124	55.65%	196	137	195	58	98	50
	_Vs Conference	8	4	2	0	0	0	0	2	27	21	6	4	1	2	0	0	0	0	1	13	14	-1	4	3	0	0	0	0	0	1	14	7	7	10	0.625	27	47	74	0	1	5	11	11	0	292	105	90	91	13	258	80	64	198	36	5	13.89%	26	6	76.92%	1	179	311	57.56%	139	267	52.06%	69	124	55.65%	196	137	195	58	98	50
	_Vs Division	2	4	2	0	0	0	0	2	6	4	2	1	1	2	0	0	0	0	1	2	3	-1	1	3	0	0	0	0	0	1	4	1	3	10	2.500	6	10	16	0	0	5	11	11	0	76	105	90	91	13	51	18	12	51	10	1	10.00%	6	1	83.33%	0	179	311	57.56%	139	267	52.06%	69	124	55.65%	196	137	195	58	98	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	10	SOL1	27	47	74	292	258	80	64	198	0	1

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	4	2	0	0	0	2	27	21

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	1	2	0	0	0	1	13	14

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	3	0	0	0	0	1	14	7

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	2	0	0	0	2

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
36	5	13.89%	26	6	76.92%	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
105	90	91	13	5	11	11	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
179	311	57.56%	139	267	52.06%	69	124	55.65%

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
196	137	195	58	98	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	SO	Lien
1 - 2024-09-17	4	Titans	5	Hit Man	3	W			Sommaire du Match
3 - 2024-09-19	13	Bulldogs	3	Titans	2	L			Sommaire du Match
5 - 2024-09-21	25	Saints	5	Titans	4	L			Sommaire du Match
6 - 2024-09-22	30	Titans	2	Phantoms	3	L	X	X	Sommaire du Match
7 - 2024-09-23	40	Titans	4	Bulldogs	1	W			Sommaire du Match
9 - 2024-09-25	49	Titans	3	Saints	0	W			Sommaire du Match
11 - 2024-09-27	58	Phantoms	1	Titans	3	W			Sommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
15 - 2024-10-01	79	Hit Man	5	Titans	4	L	X	X	Sommaire du Match

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
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
0$	2,670,124$	2,936,208$	0$

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

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	1	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
Séries
2021	7	3	4	0	0	0	0	0	28	26	2	4	2	2	0	0	0	0	0	16	13	3	3	1	2	0	0	0	0	0	12	13	-1	6	28	50	78	0	1	15	7	6	0	298	92	98	108	0	278	99	97	181	43	6	13.95%	42	7	83.33%	0	183	298	61.41%	156	284	54.93%	70	131	53.44%	183	129	156	48	82	43
Total Séries	7	3	4	0	0	0	0	0	28	26	2	4	2	2	0	0	0	0	0	16	13	3	3	1	2	0	0	0	0	0	12	13	-1	6	28	50	78	0	1	15	7	6	0	298	92	98	108	0	278	99	97	181	43	6	13.95%	42	7	83.33%	0	183	298	61.41%	156	284	54.93%	70	131	53.44%	183	129	156	48	82	43