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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	Cody Glass (R)	X		X		100.00	63	41	94	80	67	65	61	74	53	64	64	59	25	47	47	66	50	63	0	22	3	1,713,333$
2	Steven Lorentz	X				100.00	79	77	82	61	77	71	73	64	80	59	65	67	62	44	44	66	50	62	0	25	2	728,333$
3	Liam O'Brien	X				100.00	72	76	62	67	76	79	84	59	74	57	56	62	53	45	45	61	50	61	0	26	3	700,000$
4	Jeremy Bracco			X		100.00	74	64	98	60	64	73	77	61	50	71	47	64	45	47	47	60	50	60	0	24	2	925,000$
5	Barrett Hayton (R)	X	X			100.00	69	42	80	84	71	58	54	61	49	62	57	52	25	45	45	61	50	59	0	21	3	2,644,167$
6	Martin Kaut			X		100.00	69	67	73	73	67	67	70	59	50	59	54	60	51	44	44	59	50	59	0	21	3	1,319,167$
7	Adam Mascherin		X			100.00	75	73	80	61	73	66	70	53	50	51	51	62	48	44	44	57	50	57	0	23	3	880,000$
8	Tyler Gaudet	X	X			100.00	78	77	81	60	77	67	71	53	66	56	46	64	44	45	45	56	50	57	0	28	3	700,000$
9	Justin Auger			X		100.00	86	87	84	64	87	57	59	50	50	38	57	67	54	45	45	59	50	57	0	27	3	700,000$
10	Emile Poirier		X	X		100.00	73	73	73	61	73	58	60	52	50	47	50	63	48	52	52	56	50	56	0	26	3	700,000$
11	Nic Hague (R)				X	100.00	83	82	84	68	82	82	89	54	25	43	51	66	48	44	44	60	50	64	0	22	3	863,333$
12	Cody Goloubef				X	100.00	82	45	90	68	74	66	59	56	25	43	48	72	25	64	64	59	50	63	0	31	1	650,000$
13	Keaton Middleton				X	100.00	82	88	67	61	88	64	68	49	25	40	42	64	40	44	44	53	50	59	0	23	3	750,000$
14	Oleg Sosunov (R)				X	100.00	90	91	89	64	91	58	63	42	25	28	41	67	39	44	44	52	50	59	0	23	3	721,600$
15	Ryan Stanton				X	100.00	75	73	78	62	73	63	68	47	25	34	41	64	39	58	58	52	50	59	0	31	1	650,000$
16	Jeremy Davies (R)				X	100.00	70	66	79	68	66	64	67	52	25	49	41	59	39	44	44	54	50	58	0	24	3	1,325,000$
17	Stepan Falkovsky (R)				X	100.00	85	87	81	66	87	47	48	45	25	34	41	65	39	44	44	52	50	57	0	24	3	698,333$
Rayé
1	Jonathan Davidsson (R)			X		100.00	74	67	89	76	67	52	53	50	50	47	48	61	46	44	44	55	50	55	0	24	3	850,000$
2	Spencer Smallman			X		100.00	77	73	85	62	73	57	59	50	50	50	46	62	44	44	44	54	50	55	0	24	2	758,333$
3	Sean Day				X	100.00	82	84	77	53	84	51	53	48	25	39	41	64	39	44	44	51	50	56	0	23	3	700,000$
4	Joseph Cecconi				X	100.00	81	76	91	61	76	52	54	44	25	34	39	63	37	44	44	51	50	56	0	24	3	1,293,750$
5	Brandon Crawley				X	100.00	77	75	81	51	75	49	52	42	25	28	39	63	37	55	55	48	50	54	0	24	3	866,666$

	MOYENNE D'ÉQUIPE					100.00	77	72	82	65	76	62	64	53	42	47	48	63	42	47	47	56	50	58

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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	Jared Coreau	100.00	56	66	83	93	55	58	50	59	53	52	30	45	45	56	50	59	0
2	Calvin Pickard	100.00	54	58	73	77	53	58	52	58	57	56	30	57	57	56	50	58	0
Rayé
1	Dylan Wells	100.00	45	44	55	70	44	44	50	52	46	47	30	44	44	47	50	49	0

	MOYENNE D'ÉQUIPE	100.00	52	56	70	80	51	53	51	56	52	52	30	49	49	53	50	55

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Rocky Thompson	65	59	51	59	50	48	55	CAN	43	3	750,000$

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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

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#	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	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	P/20	FW	FT	S1	S2	S3
1	Steven Lorentz	Marlies (TOR)	C	11	4	7	11	4	10	0	14	34	36	8	18	11.11%	1	238	21.68	2	1	3	8	49	0	2	2	0	38	1	0	67.52%	234	0.92	0	0	2	1	0
2	Cody Glass	Marlies (TOR)	C/RW	11	3	3	6	0	6	0	8	38	28	10	19	10.71%	2	260	23.67	0	0	0	9	54	0	1	1	5	55	2	0	58.84%	328	0.46	0	0	1	0	0
3	Barrett Hayton	Marlies (TOR)	C/LW	11	2	4	6	0	8	0	16	15	22	4	11	9.09%	3	256	23.30	0	1	1	4	52	1	0	1	4	55	0	0	33.33%	18	0.47	0	0	0	1	1
4	Nic Hague	Marlies (TOR)	D	11	2	3	5	-3	8	0	26	8	16	3	10	12.50%	9	294	26.78	1	1	2	7	51	0	0	0	0	52	0	1	0.00%	0	0.34	0	0	0	1	0
5	Jeremy Bracco	Marlies (TOR)	RW	11	2	3	5	2	0	0	11	19	13	8	10	15.38%	0	194	17.68	0	2	2	4	50	0	0	0	0	0	0	0	33.33%	6	0.51	0	0	0	0	0
6	Jeremy Davies	Marlies (TOR)	D	11	0	5	5	1	6	0	10	13	3	1	1	0.00%	8	222	20.27	0	1	1	1	18	0	0	0	0	24	0	0	0.00%	0	0.45	0	0	0	0	0
7	Cody Goloubef	Marlies (TOR)	D	11	1	4	5	-5	10	0	27	11	8	3	2	12.50%	12	250	22.75	1	1	2	4	48	0	0	0	0	11	0	0	0.00%	0	0.40	0	0	0	0	0
8	Martin Kaut	Marlies (TOR)	RW	11	2	2	4	-2	12	0	25	11	22	4	8	9.09%	2	228	20.75	0	0	0	4	53	0	0	0	0	22	0	0	47.37%	19	0.35	0	0	0	1	0
9	Tyler Gaudet	Marlies (TOR)	C/LW	11	3	1	4	0	8	0	17	17	22	6	7	13.64%	0	187	17.05	0	1	1	6	46	2	0	2	3	39	1	0	57.14%	70	0.43	0	0	0	0	3
10	Adam Mascherin	Marlies (TOR)	LW	11	1	1	2	2	2	0	8	8	9	4	6	11.11%	0	158	14.37	0	0	0	0	7	0	0	0	0	6	0	0	30.00%	10	0.25	0	0	0	0	1
11	Ryan Stanton	Marlies (TOR)	D	11	0	2	2	3	14	0	17	11	6	4	3	0.00%	11	264	24.06	0	0	0	3	45	0	0	0	0	44	0	0	0.00%	0	0.15	0	0	0	0	0
12	Emile Poirier	Marlies (TOR)	LW/RW	11	0	1	1	-1	4	0	2	6	10	3	7	0.00%	1	144	13.13	0	0	0	0	0	0	0	0	0	0	0	0	33.33%	6	0.14	0	0	0	0	0
13	Keaton Middleton	Marlies (TOR)	D	11	1	0	1	3	15	5	30	7	9	1	4	11.11%	5	225	20.54	0	0	0	2	7	0	0	0	0	43	0	0	0.00%	0	0.09	0	1	0	0	0
14	Oleg Sosunov	Marlies (TOR)	D	11	0	1	1	3	27	5	33	9	4	5	3	0.00%	8	253	23.07	0	0	0	0	40	0	0	0	0	40	0	0	0.00%	0	0.08	1	0	0	0	0
15	Justin Auger	Marlies (TOR)	RW	11	1	0	1	-1	18	0	9	7	12	3	13	8.33%	2	154	14.02	0	0	0	0	4	0	0	0	0	0	0	0	80.00%	10	0.13	0	0	0	0	0
16	Liam O'Brien	Marlies (TOR)	C	11	0	0	0	-1	10	0	10	19	11	4	12	0.00%	3	151	13.74	0	0	0	0	2	0	0	0	0	2	0	0	56.73%	104	0.00	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				176	22	37	59	5	158	10	263	233	231	71	134	9.52%	67	3485	19.80	4	8	12	52	535	3	3	6	12	439	4	1	59.63%	805	0.34	1	1	3	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	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Jared Coreau	Marlies (TOR)	11	4	3	4	0.874	2.20	764	0	1	28	222	0	0	0	0.000	0	11	0	1	0	0
Stats d'équipe Total ou en Moyenne			11	4	3	4	0.874	2.20	764	0	1	28	222	0	0	0	0.000	0	11	0	1	0	0

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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	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Link
Adam Mascherin	Marlies (TOR)	LW	23	1998-06-05	No	206 Lbs	5 ft11	No	No	No	3	Pro & Farm	880,000$	0$	0$	No	880,000$	880,000$	Lien / Lien NHL
Barrett Hayton	Marlies (TOR)	C/LW	21	2000-06-08	Yes	190 Lbs	6 ft1	No	No	No	3	Pro & Farm	2,644,167$	0$	0$	No	2,644,167$	2,644,167$	Lien / Lien NHL
Brandon Crawley	Marlies (TOR)	D	24	1997-02-02	No	203 Lbs	6 ft2	No	No	No	3	Pro & Farm	866,666$	0$	0$	No	866,666$	866,666$	Lien
Calvin Pickard	Marlies (TOR)	G	29	1992-04-14	No	207 Lbs	6 ft1	Yes	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$	Lien / Lien NHL
Cody Glass	Marlies (TOR)	C/RW	22	1999-03-31	Yes	178 Lbs	6 ft2	No	No	No	3	Pro & Farm	1,713,333$	0$	0$	No	1,713,333$	1,713,333$	Lien / Lien NHL
Cody Goloubef	Marlies (TOR)	D	31	1989-11-30	No	200 Lbs	6 ft1	No	No	No	1	Pro & Farm	650,000$	0$	0$	No			Lien / Lien NHL
Dylan Wells	Marlies (TOR)	G	23	1998-01-03	No	185 Lbs	6 ft1	No	No	No	2	Pro & Farm	910,833$	0$	0$	No	910,833$		Lien / Lien NHL
Emile Poirier	Marlies (TOR)	LW/RW	26	1994-12-14	No	196 Lbs	6 ft2	Yes	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$	Lien / Lien NHL
Jared Coreau	Marlies (TOR)	G	29	1991-11-04	No	235 Lbs	6 ft4	No	No	No	2	Pro & Farm	700,000$	0$	0$	No	700,000$		Lien / Lien NHL
Jeremy Bracco	Marlies (TOR)	RW	24	1997-03-17	No	180 Lbs	5 ft9	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$		Lien / Lien NHL
Jeremy Davies	Marlies (TOR)	D	24	1996-12-04	Yes	181 Lbs	5 ft11	No	No	No	3	Pro & Farm	1,325,000$	0$	0$	No	1,325,000$	1,325,000$	Lien / Lien NHL
Jonathan Davidsson	Marlies (TOR)	RW	24	1997-03-12	Yes	185 Lbs	5 ft11	No	No	No	3	Pro & Farm	850,000$	0$	0$	No	850,000$	850,000$	Lien / Lien NHL
Joseph Cecconi	Marlies (TOR)	D	24	1997-05-23	No	209 Lbs	6 ft2	No	No	No	3	Pro & Farm	1,293,750$	0$	0$	No	1,293,750$	1,293,750$	Lien / Lien NHL
Justin Auger	Marlies (TOR)	RW	27	1994-05-14	No	229 Lbs	6 ft7	Yes	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$	Lien
Keaton Middleton	Marlies (TOR)	D	23	1998-02-10	No	233 Lbs	6 ft6	No	No	No	3	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$	Lien / Lien NHL
Liam O'Brien	Marlies (TOR)	C	26	1994-07-29	No	215 Lbs	5 ft11	Yes	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$	Lien / Lien NHL
Martin Kaut	Marlies (TOR)	RW	21	1999-10-02	No	176 Lbs	6 ft2	No	No	No	3	Pro & Farm	1,319,167$	0$	0$	No	1,319,167$	1,319,167$	Lien / Lien NHL
Nic Hague	Marlies (TOR)	D	22	1998-12-05	Yes	214 Lbs	6 ft6	No	No	No	3	Pro & Farm	863,333$	0$	0$	No	863,333$	863,333$	Lien
Oleg Sosunov	Marlies (TOR)	D	23	1998-04-13	Yes	236 Lbs	6 ft8	No	No	No	3	Pro & Farm	721,600$	0$	0$	No	721,600$	721,600$	Lien
Ryan Stanton	Marlies (TOR)	D	31	1989-07-20	No	196 Lbs	6 ft2	No	No	No	1	Pro & Farm	650,000$	0$	0$	No			Lien / Lien NHL
Sean Day	Marlies (TOR)	D	23	1998-01-08	No	231 Lbs	6 ft2	No	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$	Lien / Lien NHL
Spencer Smallman	Marlies (TOR)	RW	24	1996-09-08	No	200 Lbs	6 ft0	No	No	No	2	Pro & Farm	758,333$	0$	0$	No	758,333$		Lien / Lien NHL
Stepan Falkovsky	Marlies (TOR)	D	24	1996-12-18	Yes	224 Lbs	6 ft7	No	No	No	3	Pro & Farm	698,333$	0$	0$	No	698,333$	698,333$	Lien
Steven Lorentz	Marlies (TOR)	C	25	1996-04-12	No	201 Lbs	6 ft4	No	No	No	2	Pro & Farm	728,333$	0$	0$	No	728,333$		Lien / Lien NHL
Tyler Gaudet	Marlies (TOR)	C/LW	28	1993-03-04	No	205 Lbs	6 ft3	Yes	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$	Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
25	24.84	205 Lbs	6 ft2	2.64	937,914$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Barrett Hayton	Cody Glass	Martin Kaut	40	0	1	4
2	Adam Mascherin	Steven Lorentz	Jeremy Bracco	30	1	2	2
3	Emile Poirier	Liam O'Brien	Justin Auger	20	1	2	2
4		Tyler Gaudet		10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Nic Hague	Cody Goloubef	35	1	3	1
2	Oleg Sosunov	Ryan Stanton	35	1	3	1
3	Jeremy Davies	Keaton Middleton	30	1	3	1
4	Nic Hague	Cody Goloubef	0	1	3	1

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Barrett Hayton	Cody Glass	Martin Kaut	60	0	0	5
2	Tyler Gaudet	Steven Lorentz	Jeremy Bracco	40	0	1	4

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Nic Hague	Cody Goloubef	60	0	1	4
2	Oleg Sosunov	Ryan Stanton	40	0	1	4

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Cody Glass	Barrett Hayton	60	1	2	2
2	Steven Lorentz	Tyler Gaudet	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Nic Hague	Keaton Middleton	60	1	2	2
2	Oleg Sosunov	Ryan Stanton	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Barrett Hayton	60	1	2	2	Nic Hague	Cody Goloubef	60	1	2	2
2	Steven Lorentz	40	1	2	2	Oleg Sosunov	Ryan Stanton	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Cody Glass	Barrett Hayton	60	1	2	2
2	Steven Lorentz	Martin Kaut	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Nic Hague	Cody Goloubef	60	1	2	2
2	Oleg Sosunov	Ryan Stanton	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Barrett Hayton	Cody Glass	Martin Kaut	Nic Hague	Cody Goloubef

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Barrett Hayton	Cody Glass	Martin Kaut	Nic Hague	Cody Goloubef

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Martin Kaut, Barrett Hayton, Justin Auger	Martin Kaut, Barrett Hayton	Martin Kaut

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Ryan Stanton, Jeremy Davies, Nic Hague	Ryan Stanton	Ryan Stanton, Jeremy Davies

Tirs de Pénalité
Cody Glass, Steven Lorentz, Barrett Hayton, Jeremy Bracco, Martin Kaut

Gardien
#1 : Jared Coreau, #2 : Calvin Pickard

Lignes d'Attaque Perso. en Prol.
Cody Glass, Steven Lorentz, Liam O'Brien, Jeremy Bracco, Martin Kaut, Barrett Hayton, Barrett Hayton, Justin Auger, Tyler Gaudet, Adam Mascherin, Emile Poirier

Lignes de Défense Perso. en Prol.
Nic Hague, Cody Goloubef, Oleg Sosunov, Ryan Stanton, Jeremy Davies

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	Checkers	7	4	3	0	0	0	0	0	18	17	1	4	3	1	0	0	0	0	0	13	9	4	3	1	2	0	0	0	0	0	5	8	-3	8	0.571	18	31	49	0	1	10	7	4	1	184	83	56	62	30	156	42	110	164	40	3	7.50%	46	7	84.78%	3	194	322	60.25%	186	317	58.68%	101	173	58.38%	310	219	301	90	152	75
2	Comets	4	0	4	0	0	0	0	0	4	11	-7	2	0	2	0	0	0	0	0	3	6	-3	2	0	2	0	0	0	0	0	1	5	-4	0	0.000	4	6	10	0	0	10	7	4	1	47	83	56	62	30	66	26	48	99	21	1	4.76%	21	4	80.95%	0	194	322	60.25%	186	317	58.68%	101	173	58.38%	310	219	301	90	152	75
	Total	11	4	7	0	0	0	0	0	22	28	-6	6	3	3	0	0	0	0	0	16	15	1	5	1	4	0	0	0	0	0	6	13	-7	8	0.364	22	37	59	0	1	10	7	4	1	231	83	56	62	30	222	68	158	263	61	4	6.56%	67	11	83.58%	3	194	322	60.25%	186	317	58.68%	101	173	58.38%	310	219	301	90	152	75
	_Since Last GM Reset	11	4	7	0	0	0	0	0	22	28	-6	6	3	3	0	0	0	0	0	16	15	1	5	1	4	0	0	0	0	0	6	13	-7	8	0.364	22	37	59	0	1	10	7	4	1	231	83	56	62	30	222	68	158	263	61	4	6.56%	67	11	83.58%	3	194	322	60.25%	186	317	58.68%	101	173	58.38%	310	219	301	90	152	75
	_Vs Conference	11	4	7	0	0	0	0	0	22	28	-6	6	3	3	0	0	0	0	0	16	15	1	5	1	4	0	0	0	0	0	6	13	-7	8	0.364	22	37	59	0	1	10	7	4	1	231	83	56	62	30	222	68	158	263	61	4	6.56%	67	11	83.58%	3	194	322	60.25%	186	317	58.68%	101	173	58.38%	310	219	301	90	152	75

			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
11	8	OTL1	22	37	59	231	222	68	158	263	0	1

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
11	4	7	0	0	0	0	22	28

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
6	3	3	0	0	0	0	16	15

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	1	4	0	0	0	0	6	13

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
3	3	1	3	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
61	4	6.56%	67	11	83.58%	3

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
83	56	62	30	10	7	4	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
194	322	60.25%	186	317	58.68%	101	173	58.38%

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
310	219	301	90	152	75

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 - 2020-10-24	4	Checkers	2	Marlies	1	L	X	Sommaire du Match
3 - 2020-10-26	12	Checkers	2	Marlies	5	W		Sommaire du Match
5 - 2020-10-28	20	Marlies	3	Checkers	4	L	X	Sommaire du Match
7 - 2020-10-30	28	Marlies	1	Checkers	0	W		Sommaire du Match
9 - 2020-11-01	36	Checkers	2	Marlies	3	W		Sommaire du Match
11 - 2020-11-03	44	Marlies	1	Checkers	4	L		Sommaire du Match
13 - 2020-11-05	52	Checkers	3	Marlies	4	W	X	Sommaire du Match
15 - 2020-11-07	57	Marlies	0	Comets	3	L		Sommaire du Match
17 - 2020-11-09	61	Marlies	1	Comets	2	L	X	Sommaire du Match
19 - 2020-11-11	65	Comets	2	Marlies	0	L		Sommaire du Match
21 - 2020-11-13	69	Comets	4	Marlies	3	L	X	Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité	2000	1000
Prix des Billets	35	0
Assistance	12,000	5,928
Assistance PCT	100.00%	98.80%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité	Popularité de l'Équipe
35	2988 - 99.60%	70,000$	420,000$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
0$	2,344,784$	2,255,702$	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$	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
Saison Régulière
2020	82	54	22	0	1	2	1	2	298	165	133	41	25	12	0	1	1	0	2	154	87	67	41	29	10	0	0	1	1	0	144	78	66	116	298	530	828	0	13	115	82	99	3	2134	721	688	714	19	1498	453	1303	1799	308	46	14.94%	575	69	88.00%	5	1606	2343	68.54%	1287	2099	61.31%	795	1179	67.43%	2390	1772	1612	511	941	510
Total Saison Régulière	82	54	22	0	1	2	1	2	298	165	133	41	25	12	0	1	1	0	2	154	87	67	41	29	10	0	0	1	1	0	144	78	66	116	298	530	828	0	13	115	82	99	3	2134	721	688	714	19	1498	453	1303	1799	308	46	14.94%	575	69	88.00%	5	1606	2343	68.54%	1287	2099	61.31%	795	1179	67.43%	2390	1772	1612	511	941	510
2020	11	4	7	0	0	0	0	0	22	28	-6	6	3	3	0	0	0	0	0	16	15	1	5	1	4	0	0	0	0	0	6	13	-7	8	22	37	59	0	1	10	7	4	1	231	83	56	62	30	222	68	158	263	61	4	6.56%	67	11	83.58%	3	194	322	60.25%	186	317	58.68%	101	173	58.38%	310	219	301	90	152	75
Total Séries	11	4	7	0	0	0	0	0	22	28	-6	6	3	3	0	0	0	0	0	16	15	1	5	1	4	0	0	0	0	0	6	13	-7	8	22	37	59	0	1	10	7	4	1	231	83	56	62	30	222	68	158	263	61	4	6.56%	67	11	83.58%	3	194	322	60.25%	186	317	58.68%	101	173	58.38%	310	219	301	90	152	75

	Marlies
	GP: 11 \| W: 4 \| L: 7 GF: 22 \| GA: 28 \| PP%: 6.56% \| PK%: 83.58% DG: Garrett \| Morale : 50 \| Moyenne d'Équipe : 58