Stanley Cup Winners Hockey League

TORONTO Maple Leafs
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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

#	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	Casey Mittelstadt	0	X				100.00	62	39	88	66	77	81	83	64	71	63	62	65	66	63	65	87	99	69	0	21	1	875,000$
2	Adam Erne	0		X			100.00	89	47	77	63	80	74	87	62	58	61	59	57	63	68	65	74	99	68	0	25	3	800,000$
3	Henrik Borgstrom	0	X				100.00	64	43	86	64	83	80	77	66	73	61	59	63	66	65	62	81	99	68	0	23	6	1,250,000$
4	Brett Ritchie	0			X		100.00	84	50	78	61	89	73	75	59	52	57	58	60	59	73	68	62	99	67	0	27	1	1,750,000$
5	John Quenneville (R)	0	X				100.00	61	45	86	63	76	83	80	61	73	60	62	64	63	67	64	76	99	67	0	24	3	750,000$
6	Paul Bittner (R)	0	X	X			100.00	73	51	87	59	90	85	82	58	55	57	56	60	59	67	64	73	99	67	0	23	3	750,000$
7	Dominic Toninato (R)	0	X				100.00	63	47	82	61	79	80	78	59	65	58	60	62	59	71	66	57	99	67	0	26	3	750,000$
8	Jordan Kyrou (R)	0	X				100.00	57	39	89	67	69	77	76	66	58	63	64	65	68	63	64	76	99	67	0	22	3	750,000$
9	Lukas Vejdemo (R)	0	X				100.00	62	45	90	62	79	78	83	63	74	61	58	64	65	67	64	62	99	67	0	24	3	750,000$
10	Rasmus Asplund (R)	0	X				100.00	58	39	82	66	70	81	78	63	72	64	61	65	63	65	66	77	99	67	0	22	3	750,000$
11	Isaac Ratcliffe (R)	0		X			100.00	74	52	83	56	92	85	87	55	51	54	54	59	53	61	62	76	99	66	0	21	3	750,000$
12	Nicholas Merkley (R)	0			X		100.00	58	42	89	60	69	77	73	62	57	61	59	58	62	65	63	78	99	64	0	23	3	750,000$
13	Matthew Phillips (R)	0			X		100.00	53	39	87	61	57	83	78	62	58	60	59	57	62	63	61	64	99	64	0	22	3	750,000$
14	Spencer Smallman (R)	0			X		100.00	63	45	84	60	77	75	73	61	55	59	52	58	61	67	63	52	99	64	0	23	3	750,000$
15	Daniel O'Regan (R)	0	X				100.00	44	35	82	76	58	47	41	61	48	58	58	58	58	58	49	79	99	57	0	26	3	750,000$
16	Ryan Collins (R)	0				X	100.00	77	49	87	55	93	76	78	56	30	53	54	60	45	67	64	70	99	65	0	24	3	750,000$
17	Martin Fehervary (R)	0				X	100.00	64	45	87	60	81	84	74	58	30	57	57	59	46	61	63	74	99	65	0	20	6	800,000$
18	Nick Ebert	0				X	100.00	62	47	86	57	74	82	81	56	30	55	54	58	46	71	66	59	99	64	0	26	1	750,000$
19	Jesper Lindgren (R)	0				X	100.00	53	41	83	58	67	75	74	57	30	56	52	54	51	65	63	66	99	61	0	23	3	750,000$
20	Andrew Welinski (R)	0				X	100.00	48	35	81	65	75	47	43	50	30	41	40	56	49	60	50	71	99	52	0	27	3	750,000$
Rayé

	MOYENNE D'ÉQUIPE					100.00	63	44	85	62	77	76	75	60	54	58	57	60	58	65	63	71	99	65

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

#	Nom du Gardien	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Ville Husso (R)	100.00	74	84	82	84	73	72	74	73	72	74	73	69	73	61	99	68	0
2	Marcus Hogberg (R)	100.00	73	75	73	91	72	71	73	72	71	73	72	71	75	62	99	67	0
Rayé
1	Veini Vehvilainen (R)	100.00	71	82	80	71	70	69	71	70	69	71	70	65	69	62	99	64	0
2	Brandon Halverson (R)	100.00	60	58	56	88	59	58	60	59	58	60	59	67	71	67	99	58	0

	MOYENNE D'ÉQUIPE	100.00	70	75	73	84	69	68	70	69	68	70	69	68	72	63	99	64

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Darryl Sutter	71	71	70	70	86	86	46	CAN	63	3	300,000$

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

#	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	GA	TA	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3

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

#	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

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

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	Salaire Moyen	Salaire Moyen Restant	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Salaire Année 4	Salaire Année 5	Salaire Année 6	Link
Adam Erne	TORONTO Marlies (TOR)	LW	25	4/20/1995	No	96 Kg	185 CM	No	No	No	3	Pro & Farm	800,000$	800,000$	800,000$	800,000$	0$	0$	No	800,000$	800,000$				Lien
Andrew Welinski	TORONTO Marlies (TOR)	D	27	4/27/1993	Yes	91 Kg	188 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Brandon Halverson	TORONTO Marlies (TOR)	G	24	3/29/1996	Yes	95 Kg	193 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Brett Ritchie	TORONTO Marlies (TOR)	RW	27	7/1/1993	No	100 Kg	193 CM	No	No	No	1	Pro & Farm	1,750,000$	1,750,000$	1,750,000$	1,750,000$	0$	0$	No						Lien
Casey Mittelstadt	TORONTO Marlies (TOR)	C	21	11/22/1998	No	90 Kg	185 CM	No	No	No	1	Pro & Farm	875,000$	875,000$	750,000$	750,000$	0$	0$	No						Lien
Daniel O'Regan	TORONTO Marlies (TOR)	C	26	1/30/1994	Yes	82 Kg	175 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Dominic Toninato	TORONTO Marlies (TOR)	C	26	3/9/1994	Yes	87 Kg	188 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Henrik Borgstrom	TORONTO Marlies (TOR)	C	23	8/6/1997	No	90 Kg	191 CM	No	No	No	6	Pro & Farm	1,250,000$	1,250,000$	750,000$	750,000$	0$	0$	No	1,250,000$	1,250,000$	1,250,000$	1,250,000$	1,250,000$	Lien
Isaac Ratcliffe	TORONTO Marlies (TOR)	LW	21	2/15/1999	Yes	91 Kg	198 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Jesper Lindgren	TORONTO Marlies (TOR)	D	23	5/19/1997	Yes	75 Kg	183 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
John Quenneville	TORONTO Marlies (TOR)	C	24	4/16/1996	Yes	89 Kg	185 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Jordan Kyrou	TORONTO Marlies (TOR)	C	22	5/5/1998	Yes	80 Kg	183 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Lukas Vejdemo	TORONTO Marlies (TOR)	C	24	1/25/1996	Yes	88 Kg	188 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Marcus Hogberg	TORONTO Marlies (TOR)	G	25	11/25/1994	Yes	95 Kg	196 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Martin Fehervary	TORONTO Marlies (TOR)	D	20	10/6/1999	Yes	91 Kg	188 CM	No	No	No	6	Pro & Farm	800,000$	800,000$	750,000$	750,000$	0$	0$	No	800,000$	800,000$	800,000$	800,000$	800,000$
Matthew Phillips	TORONTO Marlies (TOR)	RW	22	4/6/1998	Yes	64 Kg	170 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Nicholas Merkley	TORONTO Marlies (TOR)	RW	23	5/23/1997	Yes	88 Kg	178 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Nick Ebert	TORONTO Marlies (TOR)	D	26	5/11/1994	No	91 Kg	183 CM	No	No	No	1	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No						Lien
Paul Bittner	TORONTO Marlies (TOR)	C/LW	23	11/4/1996	Yes	93 Kg	196 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Rasmus Asplund	TORONTO Marlies (TOR)	C	22	12/3/1997	Yes	86 Kg	180 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Ryan Collins	TORONTO Marlies (TOR)	D	24	5/6/1996	Yes	98 Kg	196 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Spencer Smallman	TORONTO Marlies (TOR)	RW	23	9/9/1996	Yes	90 Kg	185 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Veini Vehvilainen	TORONTO Marlies (TOR)	G	23	2/13/1997	Yes	82 Kg	183 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$
Ville Husso	TORONTO Marlies (TOR)	G	25	2/6/1995	Yes	93 Kg	191 CM	No	No	No	3	Pro & Farm	750,000$	750,000$	750,000$	750,000$	0$	0$	No	750,000$	750,000$

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
24	23.71	89 Kg	188 CM	3.00	821,875$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Adam Erne		Brett Ritchie	31	1	2	2
2	Paul Bittner			26	1	2	2
3	Isaac Ratcliffe		Matthew Phillips	23	1	2	2
4		John Quenneville		20	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Ryan Collins	31	1	2	2
2			26	1	2	2
3	Jesper Lindgren	Andrew Welinski	23	1	2	2
4		Ryan Collins	20	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Adam Erne		Brett Ritchie	55	1	2	2
2	Paul Bittner			45	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Ryan Collins	55	1	2	2
2			45	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1			55	1	2	2
2		Adam Erne	45	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Ryan Collins	55	1	2	2
2			45	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1		55	1	2	2		Ryan Collins	55	1	2	2
2		45	1	2	2			45	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1			55	1	2	2
2		Adam Erne	45	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Ryan Collins	55	1	2	2
2			45	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Adam Erne		Brett Ritchie		Ryan Collins

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Adam Erne		Brett Ritchie		Ryan Collins

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Dominic Toninato, Jordan Kyrou, Lukas Vejdemo	Dominic Toninato, Jordan Kyrou	Lukas Vejdemo

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Jesper Lindgren, Andrew Welinski,	Jesper Lindgren	Andrew Welinski,

Tirs de Pénalité
, , , Adam Erne, Brett Ritchie

Gardien
#1 : , #2 : Marcus Hogberg

Lignes d'Attaque Perso. en Prol.
, , , Adam Erne, Brett Ritchie, John Quenneville, John Quenneville, Paul Bittner, Dominic Toninato, Jordan Kyrou, Lukas Vejdemo

Lignes de Défense Perso. en Prol.
, Ryan Collins, , , Jesper Lindgren

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
	Total	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.000	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.00%	0	0	0	0.00%	0	0	0.00%	0	0	0.00%	0	0	0	0	0	0

			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
0	0	N/A	0	0	0	0	0	0	0	0	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
0	0	0	0	0	0	0	0	0

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

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

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
0	0	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
0	0	0.00%	0	0	0.00%	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
0	0	0	0	0	0	0	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
0	0	0.00%	0	0	0.00%	0	0	0.00%

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
0	0	0	0	0	0

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
1 - 2021-01-16	4	TORONTO Marlies	-	BROOKLYN Wolfpack	-
2 - 2021-01-17	9	TORONTO Marlies	-	LAVAL Rocket	-
5 - 2021-01-20	25	SCRANTON Penguins	-	TORONTO Marlies	-
7 - 2021-01-22	41	HERSEY Bears	-	TORONTO Marlies	-
10 - 2021-01-25	52	TORONTO Marlies	-	BRIDGEPORT Sound Tigers	-
13 - 2021-01-28	65	TORONTO Marlies	-	TUSCON Roadrunners	-
14 - 2021-01-29	74	UTICA Comets	-	TORONTO Marlies	-
19 - 2021-02-03	92	UTICA Comets	-	TORONTO Marlies	-
21 - 2021-02-05	103	TORONTO Marlies	-	LAVAL Rocket	-
23 - 2021-02-07	108	TORONTO Marlies	-	BROOKLYN Wolfpack	-
25 - 2021-02-09	122	PROVIDENCE Bruins	-	TORONTO Marlies	-
30 - 2021-02-14	144	MANITOBA Moose	-	TORONTO Marlies	-
31 - 2021-02-15	152	TORONTO Marlies	-	HERSEY Bears	-
34 - 2021-02-18	170	TUSCON Roadrunners	-	TORONTO Marlies	-
36 - 2021-02-20	177	TORONTO Marlies	-	BRIDGEPORT Sound Tigers	-
38 - 2021-02-22	189	TORONTO Marlies	-	COLORADO Eagles	-
40 - 2021-02-24	204	PROVIDENCE Bruins	-	TORONTO Marlies	-
42 - 2021-02-26	212	TORONTO Marlies	-	ROCKFORD IceHogs	-
45 - 2021-03-01	225	TORONTO Marlies	-	CHICAGO Wolves	-
46 - 2021-03-02	234	ONTARIO Reign	-	TORONTO Marlies	-
50 - 2021-03-06	254	BINGHAMTON Devils	-	TORONTO Marlies	-
52 - 2021-03-08	266	TORONTO Marlies	-	BROOKLYN Wolfpack	-
54 - 2021-03-10	276	TORONTO Marlies	-	CAROLINA Checkers	-
55 - 2021-03-11	282	LEHIGH VALLEY Phantoms	-	TORONTO Marlies	-
60 - 2021-03-16	305	TUSCON Roadrunners	-	TORONTO Marlies	-
63 - 2021-03-19	326	LAVAL Rocket	-	TORONTO Marlies	-
65 - 2021-03-21	335	TORONTO Marlies	-	UTICA Comets	-
68 - 2021-03-24	354	TORONTO Marlies	-	BINGHAMTON Devils	-
69 - 2021-03-25	359	UTICA Comets	-	TORONTO Marlies	-
73 - 2021-03-29	380	COLORADO Eagles	-	TORONTO Marlies	-
75 - 2021-03-31	390	TORONTO Marlies	-	MILWAUKEE Admirals	-
77 - 2021-04-02	400	TORONTO Marlies	-	HERSEY Bears	-
78 - 2021-04-03	409	MANITOBA Moose	-	TORONTO Marlies	-
83 - 2021-04-08	428	TORONTO Marlies	-	ONTARIO Reign	-
84 - 2021-04-09	436	BELLEVILLE Senators	-	TORONTO Marlies	-
87 - 2021-04-12	453	TORONTO Marlies	-	COLORADO Eagles	-
89 - 2021-04-14	458	PROVIDENCE Bruins	-	TORONTO Marlies	-
91 - 2021-04-16	471	TORONTO Marlies	-	UTICA Comets	-
93 - 2021-04-18	484	BELLEVILLE Senators	-	TORONTO Marlies	-
95 - 2021-04-20	499	TORONTO Marlies	-	BAKERSFIELD Condors	-
97 - 2021-04-22	511	TORONTO Marlies	-	SCRANTON Penguins	-
98 - 2021-04-23	518	BAKERSFIELD Condors	-	TORONTO Marlies	-
101 - 2021-04-26	532	TORONTO Marlies	-	HERSEY Bears	-
103 - 2021-04-28	543	BROOKLYN Wolfpack	-	TORONTO Marlies	-
105 - 2021-04-30	561	TORONTO Marlies	-	BRIDGEPORT Sound Tigers	-
107 - 2021-05-02	569	CAROLINA Checkers	-	TORONTO Marlies	-
110 - 2021-05-05	588	GRAND RAPIDS Griffins	-	TORONTO Marlies	-
112 - 2021-05-07	597	TORONTO Marlies	-	BELLEVILLE Senators	-
116 - 2021-05-11	615	ROCKFORD IceHogs	-	TORONTO Marlies	-
118 - 2021-05-13	628	TORONTO Marlies	-	STOCKTON Flames	-
120 - 2021-05-15	636	TORONTO Marlies	-	LEHIGH VALLEY Phantoms	-
121 - 2021-05-16	646	CHICAGO Wolves	-	TORONTO Marlies	-
124 - 2021-05-19	665	TORONTO Marlies	-	IOWA Wild	-
126 - 2021-05-21	672	ROCKFORD IceHogs	-	TORONTO Marlies	-
128 - 2021-05-23	684	TORONTO Marlies	-	SAN DIEGO Gulls	-
131 - 2021-05-26	697	ST-ANTONIO Rampage	-	TORONTO Marlies	-
134 - 2021-05-29	714	TORONTO Marlies	-	ST-ANTONIO Rampage	-
136 - 2021-05-31	724	SYRACUSE Crunch	-	TORONTO Marlies	-
139 - 2021-06-03	741	TORONTO Marlies	-	PROVIDENCE Bruins	-
142 - 2021-06-06	750	SAN DIEGO Gulls	-	TORONTO Marlies	-
145 - 2021-06-09	770	TORONTO Marlies	-	PROVIDENCE Bruins	-
146 - 2021-06-10	775	BROOKLYN Wolfpack	-	TORONTO Marlies	-
151 - 2021-06-15	797	HERSEY Bears	-	TORONTO Marlies	-
155 - 2021-06-19	819	SCRANTON Penguins	-	TORONTO Marlies	-
157 - 2021-06-21	832	TORONTO Marlies	-	SYRACUSE Crunch	-
160 - 2021-06-24	848	STOCKTON Flames	-	TORONTO Marlies	-
163 - 2021-06-27	861	TORONTO Marlies	-	MANITOBA Moose	-
165 - 2021-06-29	873	TORONTO Marlies	-	GRAND RAPIDS Griffins	-
167 - 2021-07-01	879	MILWAUKEE Admirals	-	TORONTO Marlies	-
170 - 2021-07-04	898	ST-ANTONIO Rampage	-	TORONTO Marlies	-
172 - 2021-07-06	904	TORONTO Marlies	-	LAVAL Rocket	-
175 - 2021-07-09	922	TORONTO Marlies	-	TUSCON Roadrunners	-
177 - 2021-07-11	929	GRAND RAPIDS Griffins	-	TORONTO Marlies	-
181 - 2021-07-15	948	TORONTO Marlies	-	GRAND RAPIDS Griffins	-
182 - 2021-07-16	958	SAN DIEGO Gulls	-	TORONTO Marlies	-
186 - 2021-07-20	978	IOWA Wild	-	TORONTO Marlies	-
187 - 2021-07-21	979	TORONTO Marlies	-	TUSCON Roadrunners	-
189 - 2021-07-23	994	TORONTO Marlies	-	LAVAL Rocket	-
192 - 2021-07-26	1011	MILWAUKEE Admirals	-	TORONTO Marlies	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
198 - 2021-08-01	1036	BRIDGEPORT Sound Tigers	-	TORONTO Marlies	-

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	0.00%	0.00%
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
40	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$	1,972,500$	1,905,000$	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$	200	9,862$	1,972,400$

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
34	80	27	37	0	2	8	4	2	219	258	-39	40	9	18	0	1	7	4	1	105	133	-28	40	18	19	0	1	1	0	1	114	125	-11	76	219	367	586	2	2	68	85	60	9	2419	780	835	794	37	2914	838	550	1478	265	49	18.49%	247	54	78.14%	2	1015	2485	40.85%	1116	2939	37.97%	474	1189	39.87%	1809	1293	2106	559	942	452
34	80	27	37	0	2	8	4	2	219	258	-39	40	9	18	0	1	7	4	1	105	133	-28	40	18	19	0	1	1	0	1	114	125	-11	76	219	367	586	2	2	68	85	60	9	2419	780	835	794	37	2914	838	550	1478	265	49	18.49%	247	54	78.14%	2	1015	2485	40.85%	1116	2939	37.97%	474	1189	39.87%	1809	1293	2106	559	942	452
Total Saison Régulière	160	54	74	0	4	16	8	4	438	516	-78	80	18	36	0	2	14	8	2	210	266	-56	80	36	38	0	2	2	0	2	228	250	-22	152	438	734	1172	4	4	136	170	120	18	4838	1560	1670	1588	74	5828	1676	1100	2956	530	98	18.49%	494	108	78.14%	4	2030	4970	40.85%	2232	5878	37.97%	948	2378	39.87%	3619	2587	4212	1119	1885	905