NSLNH - Montreal

Montreal

GP: 23 | W: 14 | L: 8 | OTL: 1 | P: 29
GF: 80 | GA: 75 | PP%: 15.48% | PK%: 83.72%
DG: Sebastien Michaud | Morale : 50 | Moyenne d'Équipe : 74
Prochain matchs #375 vs Caroline

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Laval Rocket
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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP
1	Evgeni Malkin	X		X		100.00	67	53	69	91	75	80	87	90	81	96	95	54	69	80	87	0	99	78	0
2	Jack Eichel	X				100.00	71	43	85	93	73	84	81	91	79	89	86	63	36	63	63	0	99	77	0
3	Steven Stamkos	X	X	X		100.00	71	57	74	88	71	79	65	88	89	98	85	58	55	76	79	0	99	76	0
4	Adam Lowry	X	X			100.00	93	47	93	78	79	70	81	71	97	74	71	84	25	65	66	0	99	75	0
5	Joe Thornton	X				100.00	69	74	77	72	84	79	80	92	85	84	79	57	63	99	99	0	99	74	0
6	Brandon Dubinsky	X	X			100.00	88	56	84	81	80	70	88	60	96	63	59	84	53	79	81	0	99	73	0
7	Sam Reinhart	X		X		100.00	67	42	89	84	69	76	98	91	43	75	81	56	69	64	64	0	99	73	0
8	Mark Letestu	X		X		100.00	71	43	95	70	69	64	96	74	90	64	60	84	70	73	74	0	99	72	0
9	Alex DeBrincat		X	X		100.00	65	40	97	82	57	69	90	76	39	74	85	56	75	59	59	0	99	70	0
10	Brian Gibbons	X	X	X		100.00	67	41	89	70	60	68	82	60	40	69	72	92	25	58	59	0	99	70	0
11	Pierre-Edouard Bellemare	X	X			100.00	67	42	93	79	71	63	94	61	85	62	58	81	25	66	67	0	99	70	0
12	Tobias Rieder			X		100.00	77	43	97	86	67	68	96	61	42	63	68	75	25	66	66	0	99	70	0
13	Ryan McDonagh				X	100.00	76	44	89	86	77	88	87	74	25	70	48	97	25	72	77	0	99	80	0
14	Patrik Nemeth				X	100.00	75	55	82	71	85	79	71	60	25	54	48	99	25	61	62	0	99	76	0
15	Noah Juulsen				X	100.00	90	46	94	76	70	78	69	62	25	49	48	85	25	46	46	0	99	72	0
16	Troy Stecher				X	100.00	81	54	85	83	68	77	89	61	25	52	47	78	25	59	59	0	99	71	0
17	David Schlemko				X	100.00	73	43	94	72	69	75	68	65	25	50	48	77	75	69	70	0	99	69	0
18	Rob O'Gara				X	99.00	79	45	93	74	78	67	83	55	25	50	47	79	25	47	47	0	99	69	0
Rayé
1	Brendan Gaunce	X	X			100.00	78	44	91	71	76	65	69	62	48	55	60	87	25	57	57	0	99	68	0
2	Adam Larsson				X	100.00	99	48	84	82	77	85	88	60	25	52	48	88	25	69	70	0	99	77	0

	MOYENNE D'ÉQUIPE					99.95	76	48	88	79	73	74	83	71	54	67	65	77	42	66	68	0	99	73

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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	Pekka Rinne	98.00	94	90	87	86	99	90	76	91	92	94	67	73	76	0	99	88	0
2	Philipp Grubauer	100.00	85	59	59	70	93	77	75	83	89	85	73	56	57	0	99	76	0
Rayé

	MOYENNE D'ÉQUIPE	99.00	90	75	73	78	96	84	76	87	91	90	70	65	67	0	99	82

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Peter Laviolette	69	97	90	55	63	73	75	USA	50	3	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	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	GW	GT	FO%	FOT	GA	TA	EG	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Evgeni Malkin	Montreal	C/RW	23	12	17	29	5	45	15	33	22	86	14	47	13.95%	13	493	21.47	0	6	6	15	76	0	71	4	3	54.91%	275	21	7	1	1.17	1	2	0	1	2	3	3	1
2	Jack Eichel	Montreal	C	23	12	14	26	0	8	0	21	42	66	20	36	18.18%	14	477	20.78	3	2	5	4	58	1	78	5	0	50.00%	456	14	7	0	1.09	0	2	0	0	0	2	2	2
3	Steven Stamkos	Montreal	C/LW/RW	23	10	14	24	1	18	0	21	23	67	24	33	14.93%	9	421	18.31	3	4	7	14	78	1	4	1	1	56.25%	32	21	4	1	1.14	1	1	0	0	0	1	0	3
4	Sam Reinhart	Montreal	C/RW	23	10	12	22	7	12	0	31	25	79	34	55	12.66%	10	396	17.25	4	1	5	11	78	0	0	1	1	25.00%	20	12	7	0	1.11	0	0	0	0	0	1	4	1
5	Joe Thornton	Montreal	C	23	3	10	13	1	32	10	22	26	48	13	24	6.25%	2	317	13.79	0	0	0	0	0	2	5	0	0	56.83%	322	4	5	0	0.82	0	0	1	1	0	0	0	0
6	Adam Lowry	Montreal	C/LW	23	5	7	12	-1	6	0	35	22	69	16	45	7.25%	10	367	15.96	0	2	2	6	59	3	46	0	0	58.51%	188	14	8	0	0.65	0	0	0	0	0	0	1	1
7	Alex DeBrincat	Montreal	LW/RW	23	7	5	12	3	0	0	20	23	36	8	25	19.44%	11	376	16.36	0	1	1	0	6	1	54	0	0	38.46%	52	8	4	0	0.64	0	0	0	0	0	1	0	0
8	Mark Letestu	Montreal	C/RW	23	5	6	11	1	10	0	23	24	56	15	33	8.93%	5	308	13.40	2	0	2	3	58	0	0	0	0	54.55%	11	7	3	0	0.71	0	0	0	0	0	0	0	0
9	Noah Juulsen	Montreal	D	23	1	10	11	6	8	0	36	20	20	8	12	5.00%	25	447	19.46	0	3	3	1	76	0	62	0	0	0.00%	0	4	13	1	0.49	0	0	0	0	0	0	0	0
10	Ryan McDonagh	Montreal	D	22	2	7	9	-6	4	0	41	42	53	19	15	3.77%	33	554	25.21	1	3	4	7	87	0	23	0	1	0.00%	0	6	23	0	0.32	0	0	0	0	0	0	1	0
11	Troy Stecher	Montreal	D	23	0	8	8	4	4	0	23	38	16	10	8	0.00%	30	431	18.77	0	0	0	0	50	0	48	0	0	0.00%	0	4	18	0	0.37	0	0	0	0	0	0	0	0
12	David Schlemko	Montreal	D	23	0	7	7	5	4	0	11	28	15	12	7	0.00%	28	335	14.60	0	0	0	0	4	1	20	0	0	0.00%	0	1	9	0	0.42	0	0	0	0	0	0	0	0
13	Pierre-Edouard Bellemare	Montreal	C/LW	23	3	3	6	-3	0	0	14	18	33	13	20	9.09%	6	196	8.53	0	0	0	0	0	0	6	0	1	0.00%	5	10	3	0	0.61	0	0	0	0	0	0	0	0
14	Brandon Dubinsky	Montreal	C/LW	23	4	2	6	-3	8	0	30	18	33	10	28	12.12%	6	214	9.32	0	0	0	0	10	0	0	1	0	61.80%	89	6	6	0	0.56	0	0	0	0	0	0	0	2
15	Brian Gibbons	Montreal	C/LW/RW	23	2	3	5	-3	4	0	9	12	32	4	22	6.25%	5	219	9.54	0	0	0	0	2	0	15	0	0	50.00%	8	7	2	0	0.46	0	0	0	0	0	0	1	1
16	Patrik Nemeth	Montreal	D	23	0	5	5	-4	20	0	32	36	21	4	15	0.00%	37	491	21.37	0	0	0	0	46	0	42	0	0	0.00%	0	4	24	0	0.20	0	0	0	0	0	0	0	1
17	Tobias Rieder	Montreal	RW	23	2	1	3	2	5	5	20	21	18	12	8	11.11%	9	245	10.67	0	0	0	0	0	0	0	0	0	20.00%	5	5	7	0	0.24	0	0	0	0	1	0	0	0
18	Adam Larsson	Montreal	D	6	0	1	1	-1	12	0	9	15	8	5	0	0.00%	15	164	27.41	0	1	1	1	21	0	16	0	0	0.00%	0	1	3	0	0.12	0	0	0	0	0	0	0	0
19	Rob O'Gara	Montreal	D	18	0	0	0	0	2	0	21	28	10	7	2	0.00%	24	351	19.54	0	0	0	0	0	0	69	0	0	0.00%	0	2	14	0	0.00	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				414	78	132	210	14	202	30	452	483	766	248	435	10.18%	292	6810	16.45	13	23	36	62	717	9	568	12	7	53.38%	1463	151	167	3	0.62	2	5	1	2	3	8	12	12

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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	Pekka Rinne	Montreal	23	14	8	1	0.902	3.22	1396	0	0	75	768	327	0	0	1.000	6	23	0	3	1	0
Stats d'équipe Total ou en Moyenne			23	14	8	1	0.902	3.22	1396	0	0	75	768	327	0	0	1.000	6	23	0	3	1	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	Status	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Link
Adam Larsson	Montreal	D	25	1993-01-01	No	215 Lbs	6 ft3	No	No	No	1	Avec Restriction	Pro & Farm	3,400,000$	3,400,000$	2,482,000$	No	Lien
Adam Lowry	Montreal	C/LW	24	1994-01-01	No	210 Lbs	6 ft5	No	No	No	3	Avec Restriction	Pro & Farm	2,900,000$	2,900,000$	2,117,000$	No	Lien
Alex DeBrincat	Montreal	LW/RW	21	1997-12-18 2:16:13 PM	No	165 Lbs	5 ft7	No	No	No	4	Avec Restriction	Pro & Farm	925,000$	925,000$	675,250$	No	Lien / Lien NHL
Brandon Dubinsky	Montreal	C/LW	32	1987-01-01	No	218 Lbs	6 ft2	No	No	No	2	Sans Restriction	Pro & Farm	1,900,000$	1,900,000$	1,387,000$	No	Lien
Brendan Gaunce	Montreal	C/LW	24	1995-01-01	No	217 Lbs	6 ft2	No	No	No	4	Avec Restriction	Pro & Farm	950,000$	950,000$	693,500$	No	Lien
Brian Gibbons	Montreal	C/LW/RW	29	1989-01-01	No	175 Lbs	5 ft8	No	No	No	1	Sans Restriction	Pro & Farm	1,100,000$	1,100,000$	803,000$	No	Lien
David Schlemko	Montreal	D	31	1988-01-01	No	190 Lbs	6 ft0	No	No	No	1	Sans Restriction	Pro & Farm	4,000,000$	4,000,000$	2,920,000$	No	Lien
Evgeni Malkin	Montreal	C/RW	32	1986-01-01	No	195 Lbs	6 ft3	No	No	No	3	Sans Restriction	Pro & Farm	9,500,000$	9,500,000$	6,935,000$	No	Lien
Jack Eichel	Montreal	C	21	1997-01-01	No	196 Lbs	6 ft2	No	No	No	1	Avec Restriction	Pro & Farm	925,000$	925,000$	675,250$	No	Lien
Joe Thornton	Montreal	C	39	1980-01-01	No	220 Lbs	6 ft4	No	No	No	1	Sans Restriction	Pro & Farm	7,000,000$	7,000,000$	5,110,000$	No	Lien
Mark Letestu	Montreal	C/RW	33	1985-01-01	No	197 Lbs	5 ft10	No	No	No	1	Sans Restriction	Pro & Farm	2,000,000$	2,000,000$	1,460,000$	No	Lien
Noah Juulsen	Montreal	D	21	1997-04-02 12:44:23 AM	No	175 Lbs	6 ft2	No	No	No	4	Avec Restriction	Pro & Farm	925,000$	925,000$	675,250$	No	Lien / Lien NHL
Patrik Nemeth	Montreal	D	25	1993-01-01	No	215 Lbs	6 ft3	No	No	No	1	Avec Restriction	Pro & Farm	2,500,000$	2,500,000$	1,825,000$	No	Lien
Pekka Rinne	Montreal	G	36	1983-01-01	No	217 Lbs	6 ft5	No	No	No	3	Sans Restriction	Pro & Farm	7,000,000$	7,000,000$	5,110,000$	No	Lien
Philipp Grubauer	Montreal	G	27	1992-01-01	No	182 Lbs	6 ft1	No	No	No	1	Sans Restriction	Pro & Farm	3,330,000$	3,330,000$	2,430,900$	No	Lien
Pierre-Edouard Bellemare	Montreal	C/LW	32	1986-01-01	No	198 Lbs	6 ft0	No	No	No	3	Sans Restriction	Pro & Farm	1,700,000$	1,700,000$	1,241,000$	No	Lien
Rob O'Gara	Montreal	D	24	1994-01-01	No	207 Lbs	6 ft4	No	No	No	4	Avec Restriction	Pro & Farm	875,000$	875,000$	638,750$	No	Lien
Ryan McDonagh	Montreal	D	28	1990-01-01	No	216 Lbs	6 ft1	No	No	No	5	Sans Restriction	Pro & Farm	6,000,000$	6,000,000$	4,380,000$	No	Lien
Sam Reinhart	Montreal	C/RW	23	1996-01-01	No	193 Lbs	6 ft1	No	No	No	4	Avec Restriction	Pro & Farm	3,650,000$	3,650,000$	2,664,500$	No	Lien
Steven Stamkos	Montreal	C/LW/RW	28	1990-01-01	No	194 Lbs	6 ft1	No	No	No	3	Sans Restriction	Pro & Farm	8,500,000$	8,500,000$	6,205,000$	No	Lien
Tobias Rieder	Montreal	RW	24	1994-01-01	No	185 Lbs	5 ft11	No	No	No	1	Avec Restriction	Pro & Farm	2,000,000$	2,000,000$	1,460,000$	No	Lien
Troy Stecher	Montreal	D	24	1995-01-01	No	190 Lbs	5 ft10	No	No	No	3	Avec Restriction	Pro & Farm	925,000$	925,000$	675,250$	No	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
22	27.41	199 Lbs	6 ft1	2.45	3,272,955$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
72,005,000$	45,750,000$	43,850,000$	13,325,000$	6,000,000$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Steven Stamkos	Jack Eichel	Evgeni Malkin	33	0	1	4
2	Alex DeBrincat	Joe Thornton	Sam Reinhart	30	0	1	4
3	Tobias Rieder	Adam Lowry	Mark Letestu	24	1	2	2
4	Pierre-Edouard Bellemare	Brandon Dubinsky	Brian Gibbons	13	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Rob O'Gara	Ryan McDonagh	33	0	2	3
2	Patrik Nemeth	Troy Stecher	30	1	2	2
3	Noah Juulsen	David Schlemko	24	1	2	2
4	Patrik Nemeth	Ryan McDonagh	13	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Steven Stamkos	Evgeni Malkin	Sam Reinhart	70	0	0	5
2	Adam Lowry	Jack Eichel	Mark Letestu	30	0	0	5

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Noah Juulsen	Ryan McDonagh	70	0	2	3
2	Patrik Nemeth	Troy Stecher	30	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Evgeni Malkin	Jack Eichel	70	1	2	2
2	Steven Stamkos	Joe Thornton	30	1	3	1

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Rob O'Gara	Noah Juulsen	70	1	2	2
2	Patrik Nemeth	Troy Stecher	30	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Evgeni Malkin	70	1	2	2	Noah Juulsen	Rob O'Gara	70	1	2	2
2	Jack Eichel	30	1	2	2	Patrik Nemeth	Troy Stecher	30	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Evgeni Malkin	Jack Eichel	70	1	2	2
2	Steven Stamkos	Joe Thornton	30	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	David Schlemko	Noah Juulsen	70	1	2	2
2	Patrik Nemeth	Troy Stecher	30	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Steven Stamkos	Evgeni Malkin	Sam Reinhart	Rob O'Gara	Ryan McDonagh

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Steven Stamkos	Evgeni Malkin	Sam Reinhart	Rob O'Gara	Ryan McDonagh

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Evgeni Malkin, Brandon Dubinsky, Alex DeBrincat	Evgeni Malkin, Brandon Dubinsky	Alex DeBrincat

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Noah Juulsen, David Schlemko, Patrik Nemeth	Noah Juulsen	David Schlemko, Patrik Nemeth

Tirs de Pénalité
Evgeni Malkin, Jack Eichel, Steven Stamkos, Joe Thornton, Adam Lowry

Gardien
#1 : Pekka Rinne, #2 : Philipp Grubauer

Lignes d'Attaque Perso. en Prol.
Evgeni Malkin, Jack Eichel, Steven Stamkos, Joe Thornton, Adam Lowry, Sam Reinhart, Sam Reinhart, Brandon Dubinsky, Mark Letestu, Alex DeBrincat, Pierre-Edouard Bellemare

Lignes de Défense Perso. en Prol.
David Schlemko, Ryan McDonagh, Patrik Nemeth, Troy Stecher, Noah Juulsen

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	Anaheim	2	0	1	0	0	0	1	0	5	7	-2	0	0	0	0	0	0	0	0	0	0	0	2	0	1	0	0	0	1	0	5	7	-2	2	0.500	5	7	12	0	0	0	3	1	1	60	14	23	22	4	61	28	25	36	3	0	0.00%	10	1	90.00%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	37	19	51	21	36	16
2	Buffalo	1	0	0	0	1	0	0	0	2	1	1	1	0	0	0	1	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	2	2	4	0	0	1	0	0	1	34	7	8	16	3	36	11	8	26	1	0	0.00%	4	0	100.00%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	20	10	20	9	19	9
3	Caroline	1	0	0	0	1	0	0	0	6	5	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	6	5	1	2	1.000	6	9	15	0	0	1	3	1	1	26	9	7	9	1	44	24	8	18	2	1	50.00%	4	0	100.00%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	21	12	24	9	18	8
4	Detroit	1	1	0	0	0	0	0	0	4	1	3	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	4	1	3	2	1.000	4	5	9	0	0	1	3	0	0	27	9	6	12	0	29	16	20	23	3	0	0.00%	5	0	100.00%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	20	10	20	10	19	9
5	Floride	2	1	1	0	0	0	0	0	8	6	2	1	1	0	0	0	0	0	0	6	1	5	1	0	1	0	0	0	0	0	2	5	-3	2	0.500	8	15	23	0	0	2	3	3	0	80	20	23	37	0	68	23	10	39	1	0	0.00%	5	1	80.00%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	44	27	44	16	30	15
6	Minnesota	1	1	0	0	0	0	0	0	5	4	1	1	1	0	0	0	0	0	0	5	4	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	5	10	15	0	0	2	0	3	0	37	12	7	18	0	38	5	8	14	3	0	0.00%	4	1	75.00%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	21	12	20	9	17	7
7	NY Rangers	2	0	2	0	0	0	0	0	4	7	-3	1	0	1	0	0	0	0	0	3	5	-2	1	0	1	0	0	0	0	0	1	2	-1	0	0.000	4	7	11	0	0	1	0	3	0	66	19	22	25	0	61	25	8	45	9	0	0.00%	4	1	75.00%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	43	24	38	18	37	19
8	New Jersey	1	0	0	0	1	0	0	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	3	2	1	2	1.000	3	5	8	0	0	0	0	2	1	30	6	16	7	1	31	15	8	15	5	0	0.00%	4	1	75.00%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	19	9	21	10	19	9
9	Ottawa	1	0	0	0	0	1	0	0	4	5	-1	1	0	0	0	0	1	0	0	4	5	-1	0	0	0	0	0	0	0	0	0	0	0	1	0.500	4	7	11	0	0	0	2	2	0	31	11	9	9	2	44	7	10	23	6	1	16.67%	5	2	60.00%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	22	11	21	9	19	10
10	Pittsburgh	3	0	2	0	1	0	0	0	9	12	-3	2	0	2	0	0	0	0	0	4	8	-4	1	0	0	0	1	0	0	0	5	4	1	2	0.333	9	18	27	0	0	4	2	2	1	88	35	28	23	2	110	37	31	48	16	3	18.75%	13	2	84.62%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	64	37	64	27	50	25
11	San Jose	1	0	1	0	0	0	0	0	2	3	-1	1	0	1	0	0	0	0	0	2	3	-1	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	4	6	0	0	0	1	1	0	36	18	12	6	0	29	10	6	26	3	0	0.00%	3	0	100.00%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	23	13	19	7	16	8
12	St. Louis	1	1	0	0	0	0	0	0	6	4	2	1	1	0	0	0	0	0	0	6	4	2	0	0	0	0	0	0	0	0	0	0	0	2	1.000	6	11	17	0	0	1	1	4	0	29	9	8	12	0	35	14	12	19	2	2	100.00%	6	1	83.33%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	18	10	25	8	15	7
13	Tampa Bay	3	3	0	0	0	0	0	0	13	8	5	1	1	0	0	0	0	0	0	3	2	1	2	2	0	0	0	0	0	0	10	6	4	6	1.000	13	22	35	0	0	4	3	6	0	113	37	36	40	0	90	38	28	63	17	4	23.53%	9	3	66.67%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	67	38	59	27	53	28
14	Toronto	2	1	0	0	0	0	1	0	7	5	2	1	0	0	0	0	0	1	0	4	3	1	1	1	0	0	0	0	0	0	3	2	1	4	1.000	7	8	15	0	0	0	2	4	1	71	11	15	45	2	63	27	14	38	9	2	22.22%	7	1	85.71%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	44	23	44	20	36	18
	Total	23	8	8	0	4	1	2	0	80	75	5	12	4	5	0	1	1	1	0	41	41	0	11	4	3	0	3	0	1	0	39	34	5	29	0.630	80	132	212	0	0	17	24	33	6	766	230	230	296	15	768	292	202	452	84	13	15.48%	86	14	83.72%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	494	278	495	216	408	203
16	Vegas	1	0	1	0	0	0	0	0	2	5	-3	1	0	1	0	0	0	0	0	2	5	-3	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	2	4	0	0	0	1	1	0	38	13	10	15	0	29	12	6	19	4	0	0.00%	3	0	100.00%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	23	14	18	8	17	9
	_Since Last GM Reset	23	8	8	0	4	1	2	0	80	75	5	12	4	5	0	1	1	1	0	41	41	0	11	4	3	0	3	0	1	0	39	34	5	29	0.630	80	132	212	0	0	17	24	33	6	766	230	230	296	15	768	292	202	452	84	13	15.48%	86	14	83.72%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	494	278	495	216	408	203
	_Vs Conference	17	6	5	0	4	1	1	0	60	52	8	8	2	3	0	1	1	1	0	26	25	1	9	4	2	0	3	0	0	0	34	27	7	23	0.676	60	98	158	0	0	14	18	23	5	566	164	170	223	11	576	223	145	338	69	11	15.94%	60	11	81.67%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	368	208	359	160	304	153
	_Vs Division	10	6	1	0	1	1	1	0	38	26	12	5	2	0	0	1	1	1	0	19	12	7	5	4	1	0	0	0	0	0	19	14	5	17	0.850	38	59	97	0	0	8	13	15	2	356	95	97	159	7	330	122	90	212	37	7	18.92%	35	7	80.00%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	219	123	210	94	179	90

			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
23	29	W3	80	132	212	766	768	292	202	452	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
23	8	8	4	1	2	0	80	75

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
12	4	5	1	1	1	0	41	41

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
11	4	3	3	0	1	0	39	34

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
5	5	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
84	13	15.48%	86	14	83.72%	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
230	230	296	15	17	24	33	6

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
303	534	56.74%	307	580	52.93%	171	323	52.94%

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
494	278	495	216	408	203

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 - 2019-04-05	14	Buffalo	1	Montreal	2	W	X		Sommaire du Match
2 - 2019-04-06	17	Montreal	4	Tampa Bay	2	W			Sommaire du Match
3 - 2019-04-07	39	Montreal	2	Floride	5	L			Sommaire du Match
4 - 2019-04-08	55	Pittsburgh	5	Montreal	2	L			Sommaire du Match
5 - 2019-04-09	71	Ottawa	5	Montreal	4	L	X		Sommaire du Match
6 - 2019-04-10	78	Montreal	4	Anaheim	3	W	X	X	Sommaire du Match
8 - 2019-04-12	101	Montreal	3	Toronto	2	W			Sommaire du Match
9 - 2019-04-13	120	Vegas	5	Montreal	2	L			Sommaire du Match
10 - 2019-04-14	133	Minnesota	4	Montreal	5	W			Sommaire du Match
11 - 2019-04-15	141	Montreal	4	Detroit	1	W			Sommaire du Match
12 - 2019-04-16	165	Tampa Bay	2	Montreal	3	W			Sommaire du Match
14 - 2019-04-18	188	Floride	1	Montreal	6	W			Sommaire du Match
15 - 2019-04-19	205	Montreal	3	New Jersey	2	W	X		Sommaire du Match
16 - 2019-04-20	213	Montreal	6	Tampa Bay	4	W			Sommaire du Match
17 - 2019-04-21	228	Toronto	3	Montreal	4	W	X	X	Sommaire du Match
19 - 2019-04-23	249	Pittsburgh	3	Montreal	2	L			Sommaire du Match
20 - 2019-04-24	266	Montreal	1	NY Rangers	2	L			Sommaire du Match
21 - 2019-04-25	284	Montreal	1	Anaheim	4	L			Sommaire du Match
22 - 2019-04-26	289	San Jose	3	Montreal	2	L			Sommaire du Match
24 - 2019-04-28	315	NY Rangers	5	Montreal	3	L			Sommaire du Match
25 - 2019-04-29	329	Montreal	6	Caroline	5	W	X		Sommaire du Match
26 - 2019-04-30	341	Montreal	5	Pittsburgh	4	W	X		Sommaire du Match
27 - 2019-05-01	351	St. Louis	4	Montreal	6	W			Sommaire du Match
28 - 2019-05-02	375	Caroline	-	Montreal	-
29 - 2019-05-03	389	Montreal	-	Vancouver	-
30 - 2019-05-04	405	Floride	-	Montreal	-
31 - 2019-05-05	424	Vancouver	-	Montreal	-
32 - 2019-05-06	428	Montreal	-	NY Islanders	-
33 - 2019-05-07	449	Montreal	-	Vegas	-
34 - 2019-05-08	462	Montreal	-	Winnipeg	-
35 - 2019-05-09	478	Montreal	-	San Jose	-
36 - 2019-05-10	490	Ottawa	-	Montreal	-
37 - 2019-05-11	505	Calgary	-	Montreal	-
38 - 2019-05-12	525	Montreal	-	Calgary	-
39 - 2019-05-13	537	Washington	-	Montreal	-
40 - 2019-05-14	556	Colorado	-	Montreal	-
41 - 2019-05-15	568	Montreal	-	Tampa Bay	-
43 - 2019-05-17	592	Detroit	-	Montreal	-
44 - 2019-05-18	601	Montreal	-	Colorado	-
45 - 2019-05-19	619	Anaheim	-	Montreal	-
47 - 2019-05-21	647	Montreal	-	Los Angeles	-
48 - 2019-05-22	657	Tampa Bay	-	Montreal	-
49 - 2019-05-23	678	Toronto	-	Montreal	-
50 - 2019-05-24	689	Montreal	-	Arizona	-
51 - 2019-05-25	705	Montreal	-	Detroit	-
52 - 2019-05-26	719	NY Islanders	-	Montreal	-
53 - 2019-05-27	732	Montreal	-	Toronto	-
54 - 2019-05-28	748	New Jersey	-	Montreal	-
56 - 2019-05-30	775	Columbus	-	Montreal	-
57 - 2019-05-31	788	Montreal	-	Boston	-
58 - 2019-06-01	795	Montreal	-	Buffalo	-
59 - 2019-06-02	812	New Jersey	-	Montreal	-
60 - 2019-06-03	829	Montreal	-	St. Louis	-
61 - 2019-06-04	842	Chicago	-	Montreal	-
62 - 2019-06-05	857	Montreal	-	Philadelphie	-
63 - 2019-06-06	872	Philadelphie	-	Montreal	-
65 - 2019-06-08	893	Montreal	-	Boston	-
66 - 2019-06-09	907	Detroit	-	Montreal	-
67 - 2019-06-10	931	Dallas	-	Montreal	-
68 - 2019-06-11	937	Montreal	-	Buffalo	-
69 - 2019-06-12	948	Montreal	-	Chicago	-
70 - 2019-06-13	965	Edmonton	-	Montreal	-
71 - 2019-06-14	979	Montreal	-	Floride	-
72 - 2019-06-15	998	Buffalo	-	Montreal	-
73 - 2019-06-16	1005	Montreal	-	Edmonton	-
74 - 2019-06-17	1028	Nashville	-	Montreal	-
75 - 2019-06-18	1041	Montreal	-	Columbus	-
76 - 2019-06-19	1058	Los Angeles	-	Montreal	-
78 - 2019-06-21	1075	Montreal	-	Dallas	-
79 - 2019-06-22	1084	Montreal	-	Ottawa	-
80 - 2019-06-23	1095	Boston	-	Montreal	-
81 - 2019-06-24	1113	Montreal	-	Minnesota	-
82 - 2019-06-25	1122	Montreal	-	New Jersey	-
83 - 2019-06-26	1136	Pittsburgh	-	Montreal	-
85 - 2019-06-28	1158	Montreal	-	Washington	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
86 - 2019-06-29	1164	Boston	-	Montreal	-
88 - 2019-07-01	1190	Winnipeg	-	Montreal	-
89 - 2019-07-02	1205	Montreal	-	Nashville	-
91 - 2019-07-04	1219	Montreal	-	Ottawa	-
92 - 2019-07-05	1229	Montreal	-	Washington	-
93 - 2019-07-06	1235	Arizona	-	Montreal	-
99 - 2019-07-12	1265	Arizona	-	Montreal	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2	Niveau 3	Niveau 4	Luxe
Capacité de l'Aréna	7000	6000	3000	5000	2000
Prix des Billets	250	175	125	80	300
Assistance	62,786	56,833	27,840	46,908	18,456
Attendance PCT	74.75%	78.93%	77.33%	78.18%	76.90%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
29	17735 - 77.11%	1,632,498$	19,589,973$	23000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs	Valeur du Cap Salarial Spécial
19,300,600$	72,005,000$	48,825,000$	0$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Taxe de Luxe Totale	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
720,050$	19,165,600$	0$	22	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
47,342,435$	73	725,050$	52,928,650$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Cap Salarial de la Saison Éstimé	Compte Bancaire Actuel	Compte Bancaire Projeté
54,405,664$	71,729,250$	27,164,342$	20,101,113$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Steven Stamkos	AGE:28	PO:0	OV:76
Adam Lowry	AGE:24	PO:0	OV:75
Brandon Dubinsky	AGE:32	PO:0	OV:73
Alex DeBrincat	AGE:21	PO:0	OV:70
Brian Gibbons	AGE:29	PO:0	OV:70
Pierre-Edouard Bellemare	AGE:32	PO:0	OV:70
Brendan Gaunce	AGE:24	PO:0	OV:68
Nicklas Jensen	AGE:24	PO:0	OV:61
Markus Hannikainen	AGE:24	PO:0	OV:60
Tobias Lindberg	AGE:24	PO:0	OV:59
Troy Bourke	AGE:24	PO:0	OV:55
Austen Brassard	AGE:24	PO:0	OV:54
Troy Josephs	AGE:24	PO:0	OV:53
Evan Campbell	AGE:24	PO:0	OV:50
Sam Lafferty	AGE:23	PO:0	OV:47

Evgeni Malkin	AGE:32	PO:0	OV:78
Jack Eichel	AGE:21	PO:0	OV:77
Steven Stamkos	AGE:28	PO:0	OV:76
Adam Lowry	AGE:24	PO:0	OV:75
Joe Thornton	AGE:39	PO:0	OV:74
Brandon Dubinsky	AGE:32	PO:0	OV:73
Sam Reinhart	AGE:23	PO:0	OV:73
Mark Letestu	AGE:33	PO:0	OV:72
Brian Gibbons	AGE:29	PO:0	OV:70
Pierre-Edouard Bellemare	AGE:32	PO:0	OV:70
Brendan Gaunce	AGE:24	PO:0	OV:68
Patrick Brown	AGE:25	PO:0	OV:61
Nicholas Baptiste	AGE:24	PO:0	OV:60
Troy Bourke	AGE:24	PO:0	OV:55
Austen Brassard	AGE:24	PO:0	OV:54
Troy Josephs	AGE:24	PO:0	OV:53
Cody Payne	AGE:24	PO:0	OV:50
Avery Peterson	AGE:23	PO:0	OV:47
Sam Lafferty	AGE:23	PO:0	OV:47

Evgeni Malkin	AGE:32	PO:0	OV:78
Steven Stamkos	AGE:28	PO:0	OV:76
Sam Reinhart	AGE:23	PO:0	OV:73
Mark Letestu	AGE:33	PO:0	OV:72
Alex DeBrincat	AGE:21	PO:0	OV:70
Brian Gibbons	AGE:29	PO:0	OV:70
Tobias Rieder	AGE:24	PO:0	OV:70
Nicklas Jensen	AGE:24	PO:0	OV:61
Patrick Brown	AGE:25	PO:0	OV:61
Markus Hannikainen	AGE:24	PO:0	OV:60
Nicholas Baptiste	AGE:24	PO:0	OV:60
Tobias Lindberg	AGE:24	PO:0	OV:59
Brian Hart	AGE:24	PO:0	OV:55
Austen Brassard	AGE:24	PO:0	OV:54
Christophe Lalancette	AGE:24	PO:0	OV:51
Evan Campbell	AGE:24	PO:0	OV:50

Défense #1

Défense #2

Gardien

Ryan McDonagh	AGE:28	PO:0	OV:80
Adam Larsson	AGE:25	PO:0	OV:77
Patrik Nemeth	AGE:25	PO:0	OV:76
Noah Juulsen	AGE:21	PO:0	OV:72
Troy Stecher	AGE:24	PO:0	OV:71
David Schlemko	AGE:31	PO:0	OV:69
Rob O'Gara	AGE:24	PO:0	OV:69

Ethan Bear	AGE:21	PO:0	OV:64
Dean Kukan	AGE:24	PO:0	OV:60
Michael Paliotta	AGE:24	PO:0	OV:58
Michael Brodzinski	AGE:23	PO:0	OV:56
James Melindy	AGE:25	PO:0	OV:54
Taylor Doherty	AGE:27	PO:0	OV:53
Dmitry Sinitsyn	AGE:24	PO:0	OV:50

Pekka Rinne	AGE:36	PO:0	OV:88
Philipp Grubauer	AGE:27	PO:0	OV:76
Laurent Brossoit	AGE:24	PO:0	OV:57
David Honzík	AGE:24	PO:0	OV:48

Éspoirs

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

Éspoir	Nom de l'Équipe	Année de Repêchage	Choix Total
Beck Malenstyn	Montreal	2025	174
Brady Tkachuk	Montreal	2029	2
Brandon Baddock	Montreal	2021	88
Brandon Hagel	Montreal	2025	103
Brett Seney	Montreal	2023	104
Carter Hart	Montreal	2025	23
Chase Lang	Montreal	2021	68
Dante Fabbro	Montreal	2025	17
David Gustafsson	Montreal	2029	31
Evan Bouchard	Montreal	2029	7
Henri Kiviaho	Montreal	2018	91
Isac Lundestrom	Montreal	2028	17
Ivan Lodnia	Montreal	2026	22
Jack Mcbain	Montreal	2028	30
Jacob Bernard-Docker	Montreal	2029	18
Jacob Moverare	Montreal	2025	84
Jake Paterson	Montreal	2018	45
Jake Wise	Montreal	2028	26
Joe Masonius	Montreal	2025	204
MacKenzie Entwistle	Montreal	2026	32
Martin Pospisil	Montreal	2028	58
Matthew Phillips	Montreal	2025	114
Max Zimmer	Montreal	2025	144
Maxime Comtois	Montreal	2027	19
Michael Anderson	Montreal	2026	38
Michael Clarke	Montreal	2018	77
Mikael Hakkarainen	Montreal	2028	64
Nicholas Caamano	Montreal	2025	80
Niko Mikkola	Montreal	2023	74
Noah Gregor	Montreal	2025	65
Oskari Laaksonen	Montreal	2026	91
Rem Pitlick	Montreal	2025	85
Riley Stillman	Montreal	2025	121
Serron Noel	Montreal	2029	15
Stelio Mattheos	Montreal	2026	35
Steven Spinner	Montreal	2021	87
Trent Frederic	Montreal	2025	255
Tyler Steenbergen	Montreal	2027	23
Wade Allison	Montreal	2025	50
Wyatte Wylie	Montreal	2028	60

Choix au Repêchage

Année	R1	R2	R3	R4	R5
2030	MTL		MTL		MTL
2031	MTL	CAR	MTL	MTL	MTL
2032	MTL	MTL	MTL ANA	MTL	MTL
2033	MTL	MTL	MTL	MTL	MTL
2034	MTL	MTL	MTL	MTL MTL	MTL MTL

Pas de Blessure ou de Suspension.

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
2029	23	8	8	0	4	1	2	0	80	75	5	12	4	5	0	1	1	1	0	41	41	0	11	4	3	0	3	0	1	0	39	34	5	29	80	132	212	0	0	17	24	33	6	766	230	230	296	15	768	292	202	452	84	13	15.48%	86	14	83.72%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	494	278	495	216	408	203
Total Saison Régulière	23	8	8	0	4	1	2	0	80	75	5	12	4	5	0	1	1	1	0	41	41	0	11	4	3	0	3	0	1	0	39	34	5	29	80	132	212	0	0	17	24	33	6	766	230	230	296	15	768	292	202	452	84	13	15.48%	86	14	83.72%	0	303	534	56.74%	307	580	52.93%	171	323	52.94%	494	278	495	216	408	203
Séries
2028	9	5	4	0	0	0	0	0	30	28	2	4	2	2	0	0	0	0	0	10	11	-1	5	3	2	0	0	0	0	0	20	17	3	10	30	50	80	0	0	6	16	6	2	296	77	111	94	14	299	99	72	168	20	5	25.00%	36	8	77.78%	1	111	214	51.87%	112	261	42.91%	69	137	50.36%	191	108	212	89	164	79
Total Séries	9	5	4	0	0	0	0	0	30	28	2	4	2	2	0	0	0	0	0	10	11	-1	5	3	2	0	0	0	0	0	20	17	3	10	30	50	80	0	0	6	16	6	2	296	77	111	94	14	299	99	72	168	20	5	25.00%	36	8	77.78%	1	111	214	51.87%	112	261	42.91%	69	137	50.36%	191	108	212	89	164	79

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