LHSRSM - Predators

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Blessure/Suspension
Stats d'équipe en Carrière
Client Web pour Formation
Client Web pour Lignes

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
1	Mika Zibanejad	X				100.00	79	45	81	83	82	90	85	81	88	82	87	86	84	73	77	0	50	77	0
2	Leon Draisaitl	X				100.00	59	43	79	86	82	90	85	87	83	90	91	66	89	69	75	0	50	76	0
3	Sean Couturier	X				100.00	62	42	83	80	86	91	89	78	88	81	79	83	77	75	78	0	50	74	0
4	Sebastian Aho	X				100.00	66	39	88	83	70	85	89	82	86	81	84	79	83	65	71	0	50	74	0
5	Jordan Eberle			X		100.00	58	42	89	76	70	82	86	75	52	73	73	61	76	78	72	0	50	69	0
6	Jesper Fast			X		100.00	83	39	84	67	76	81	85	66	54	68	65	83	66	77	67	0	50	68	0
7	Marcus Foligno		X			100.00	91	64	76	65	88	78	86	64	55	66	63	80	64	77	69	0	50	68	0
8	Radek Faksa	X				100.00	79	48	74	68	86	81	88	66	84	64	67	78	66	71	69	0	50	68	0
9	Drake Caggiula	X				100.00	87	50	75	68	66	73	76	67	56	65	71	67	69	70	66	0	50	67	0
10	Daniel Carr		X			100.00	62	42	88	65	73	80	77	63	61	64	64	62	65	77	69	0	50	64	0
11	Markus Granlund	X				100.00	58	39	85	63	70	79	81	64	75	61	62	68	64	73	68	0	50	63	0
12	Alex Pietrangelo (C)				X	100.00	65	42	86	75	85	91	86	74	30	81	76	84	53	78	88	0	50	74	0
13	Mattias Ekholm				X	100.00	65	46	78	71	89	90	88	69	30	80	68	87	55	78	74	0	50	71	0
14	John Klingberg				X	100.00	59	41	86	78	81	90	82	77	30	83	70	62	59	75	68	0	50	71	0
15	Ryan Graves				X	100.00	81	47	79	68	93	82	76	67	30	73	70	89	56	69	65	0	50	70	0
16	John Moore				X	100.00	79	48	81	66	82	86	72	65	30	68	62	77	52	78	68	0	50	67	0
17	Trevor Daley (A)				X	100.00	54	39	83	65	72	82	69	64	30	70	56	68	51	87	77	0	50	64	0
Rayé
1	Nikolaj Ehlers		X			100.00	57	48	84	79	69	81	85	77	52	75	78	63	79	67	70	0	50	70	0
2	Eetu Tuulola			X		100.00	73	48	88	58	85	84	83	57	55	56	56	59	58	63	62	0	50	61	0
3	Evgeny Svechnikov			X		100.00	65	49	84	60	85	74	72	57	52	58	59	60	59	67	64	0	50	61	0

	MOYENNE D'ÉQUIPE					100.00	69	45	83	71	80	84	82	70	56	72	70	73	66	73	71	0	50	69

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	Marc-Andre Fleury	100.00	97	95	93	77	96	95	97	96	95	97	96	86	90	0	50	78	0
2	Jake Allen	100.00	88	95	93	81	87	86	88	87	86	88	87	78	84	0	50	73	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	93	95	93	79	92	91	93	92	91	93	92	82	87	0	50	76

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Paul Maurice	82	87	88	83	80	74	69	CAN	53	2	100,000$

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	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
Alex Pietrangelo	Predators	D	28	1990-01-18	No	210 Lbs	6 ft3	No	No	No	1	Pro & Farm	6,500,000$	6,500,000$	6,500,000$	No						Lien / Lien NHL
Daniel Carr	Predators	LW	26	1991-11-01	No	193 Lbs	6 ft0	No	No	No	0	Pro & Farm		0$	0$	No						Lien / Lien NHL
Drake Caggiula	Predators	C	24	1994-06-20	No	176 Lbs	5 ft10	No	No	No	1	Pro & Farm	1,500,000$	1,500,000$	1,500,000$	No						Lien / Lien NHL
Eetu Tuulola	Predators	RW	20	1998-03-17	No	224 Lbs	6 ft2	No	No	No	1	Pro & Farm		0$	0$	No						Lien
Evgeny Svechnikov	Predators	RW	21	1996-10-31	No	208 Lbs	6 ft3	No	No	No	1	Pro & Farm		0$	0$	No						Lien
Jake Allen	Predators	G	28	1990-08-07	No	203 Lbs	6 ft2	No	No	No	2	Pro & Farm	4,350,000$	4,350,000$	4,350,000$	No	4,350,000$					Lien / Lien NHL
Jesper Fast	Predators	RW	26	1991-12-02	No	191 Lbs	6 ft1	No	No	No	1	Pro & Farm	1,850,000$	1,850,000$	1,850,000$	No						Lien / Lien NHL
John Klingberg	Predators	D	26	1992-08-14	No	190 Lbs	6 ft3	No	No	No	3	Pro & Farm	4,250,000$	4,250,000$	4,250,000$	No	4,250,000$	4,250,000$				Lien / Lien NHL
John Moore	Predators	D	27	1990-11-19	No	210 Lbs	6 ft2	No	No	No	4	Pro & Farm	2,750,000$	2,750,000$	2,750,000$	No	2,750,000$	2,750,000$	2,750,000$			Lien / Lien NHL
Jordan Eberle	Predators	RW	28	1990-05-15	No	187 Lbs	5 ft11	No	No	No	0	Pro & Farm		0$	0$	No						Lien / Lien NHL
Leon Draisaitl	Predators	C	22	1995-10-27	No	208 Lbs	6 ft2	No	No	No	6	Pro & Farm	8,500,000$	8,500,000$	8,500,000$	No	8,500,000$	8,500,000$	8,500,000$	8,500,000$	8,500,000$	Lien / Lien NHL
Marc-Andre Fleury	Predators	G	33	1984-11-28	No	185 Lbs	6 ft2	No	No	No	0	Pro & Farm		0$	0$	No						Lien / Lien NHL
Marcus Foligno	Predators	LW	27	1991-08-10	No	224 Lbs	6 ft3	No	No	No	2	Pro & Farm	2,875,000$	2,875,000$	2,875,000$	No	2,875,000$					Lien / Lien NHL
Markus Granlund	Predators	C	25	1993-04-16	No	180 Lbs	6 ft0	No	No	No	0	Pro & Farm		0$	0$	No						Lien / Lien NHL
Mattias Ekholm	Predators	D	28	1990-05-24	No	215 Lbs	6 ft4	No	No	No	3	Pro & Farm	3,750,000$	3,750,000$	3,750,000$	No	3,750,000$	3,750,000$				Lien / Lien NHL
Mika Zibanejad	Predators	C	25	1993-04-18	No	208 Lbs	6 ft2	No	No	No	3	Pro & Farm	5,350,000$	5,350,000$	5,350,000$	No	5,350,000$	5,350,000$				Lien / Lien NHL
Nikolaj Ehlers	Predators	LW	22	1996-02-14	No	172 Lbs	6 ft0	No	No	No	6	Pro & Farm	6,000,000$	6,000,000$	6,000,000$	No	6,000,000$	6,000,000$	6,000,000$	6,000,000$	6,000,000$	Lien / Lien NHL
Radek Faksa	Predators	C	24	1994-01-09	No	220 Lbs	6 ft3	No	No	No	1	Pro & Farm	2,200,000$	2,200,000$	2,200,000$	No						Lien / Lien NHL
Ryan Graves	Predators	D	23	1995-05-21	No	220 Lbs	6 ft5	No	No	No	0	Pro & Farm		0$	0$	No						Lien / Lien NHL
Sean Couturier	Predators	C	25	1992-12-07	No	211 Lbs	6 ft3	No	No	No	3	Pro & Farm	4,333,333$	4,333,333$	4,333,333$	No	4,333,333$	4,333,333$				Lien / Lien NHL
Sebastian Aho	Predators	C	21	1997-07-26	No	176 Lbs	6 ft0	No	No	No	0	Pro & Farm		0$	0$	No						Lien / Lien NHL
Trevor Daley	Predators	D	35	1983-10-09	No	199 Lbs	5 ft11	No	No	No	1	Pro & Farm	3,166,666$	3,166,666$	3,166,666$	No						Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
22	25.64	200 Lbs	6 ft2	1.77	2,607,955$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
57,374,999$	42,158,333$	34,933,333$	17,250,000$	14,500,000$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Sebastian Aho	Sean Couturier	Leon Draisaitl	30	1	1	3
2		Mika Zibanejad	Jordan Eberle	30	1	1	3
3	Daniel Carr	Radek Faksa	Jesper Fast	25	1	2	2
4	Marcus Foligno	Drake Caggiula	Markus Granlund	15	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	Mattias Ekholm	32	1	2	2
2	John Klingberg	John Moore	32	1	2	2
3	Trevor Daley	Ryan Graves	25	1	2	2
4	Alex Pietrangelo	John Klingberg	11	0	2	3

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Sebastian Aho	Mika Zibanejad	Leon Draisaitl	60	0	1	4
2	Jordan Eberle	Sean Couturier		40	0	1	4

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	John Klingberg	60	0	1	4
2	Mattias Ekholm	John Moore	40	0	1	4

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Radek Faksa	Markus Granlund	60	1	3	1
2	Sean Couturier	Jesper Fast	40	1	3	1

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	Mattias Ekholm	60	1	3	1
2	John Klingberg	John Moore	40	1	3	1

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Radek Faksa	60	1	4	0	Alex Pietrangelo	Mattias Ekholm	60	1	4	0
2	Sebastian Aho	40	1	4	0	John Klingberg	John Moore	40	1	4	0

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Sebastian Aho	Leon Draisaitl	60	1	2	2
2	Mika Zibanejad	Radek Faksa	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	Mattias Ekholm	60	1	2	2
2	John Klingberg	John Moore	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Sebastian Aho	Jordan Eberle	Leon Draisaitl	Alex Pietrangelo	John Klingberg

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Markus Granlund	Jordan Eberle	Radek Faksa	Alex Pietrangelo	Mattias Ekholm

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Mika Zibanejad, Leon Draisaitl,	Sebastian Aho, Mika Zibanejad	Leon Draisaitl

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
John Moore, Trevor Daley, Ryan Graves	John Moore	John Moore, Trevor Daley

Tirs de Pénalité
Leon Draisaitl, Mika Zibanejad, Jordan Eberle, Sebastian Aho, Markus Granlund

Gardien
#1 : Marc-Andre Fleury, #2 : Jake Allen

Lignes d'Attaque Perso. en Prol.
Leon Draisaitl, Mika Zibanejad, Jordan Eberle, Sebastian Aho, Sean Couturier, Markus Granlund, Markus Granlund, , Radek Faksa, Jesper Fast, Marcus Foligno

Lignes de Défense Perso. en Prol.
Alex Pietrangelo, Mattias Ekholm, John Klingberg, John Moore, Trevor Daley

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	ST	OT	SO	RI	Lien

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2	Niveau 3	Niveau 4	Luxe
Capacité de l'Aréna	6000	5000	2000	4000	1000
Prix des Billets	100	60	35	25	200
Assistance	0.00%	0.00%	0.00%	0.00%	0.00%
Attendance PCT	0.00%	0.00%	0.00%	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
41	0 - 0.00%	0$	0$	18000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs	Valeur du Cap Salarial Spécial
0$	57,374,999$	57,374,998$	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
0$	0$	0$	16	0

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

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Compte Bancaire Actuel	Compte Bancaire Projeté
0$	52,306,399$	52,306,399$

Cap Salarial de la Saison Éstimé	Cap Salarial Disponible	Cap Salarial Maximum	Au dessus du Plafond Salarial Minimum
0$	79,500,000$	79,500,000$	-58,800,000$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Nikolaj Ehlers	AGE:22	PO:0	OV:70
Marcus Foligno	AGE:27	PO:0	OV:68
Victor Olofsson	AGE:23	PO:0	OV:66
Dmytro Timashov	AGE:22	PO:0	OV:65
Daniel Carr	AGE:26	PO:0	OV:64
Adam Erne	AGE:23	PO:0	OV:63
Carsen Twarynski	AGE:20	PO:0	OV:61

Mika Zibanejad	AGE:25	PO:0	OV:77
Leon Draisaitl	AGE:22	PO:0	OV:76
Sean Couturier	AGE:25	PO:0	OV:74
Sebastian Aho	AGE:21	PO:0	OV:74
Radek Faksa	AGE:24	PO:0	OV:68
Drake Caggiula	AGE:24	PO:0	OV:67
Markus Granlund	AGE:25	PO:0	OV:63
Dillon Dube	AGE:20	PO:0	OV:63
Tyler Graovac	AGE:25	PO:0	OV:63
Zac Rinaldo	AGE:28	PO:0	OV:62
Tyler Gaudet	AGE:25	PO:0	OV:62

Jordan Eberle	AGE:28	PO:0	OV:69
Jesper Fast	AGE:26	PO:0	OV:68
Eetu Tuulola	AGE:20	PO:0	OV:61
Evgeny Svechnikov	AGE:21	PO:0	OV:61
Axel Jonsson-Fjallby	AGE:20	PO:0	OV:59

Défense #1

Défense #2

Gardien

Alex Pietrangelo	AGE:28	PO:0	OV:74
Mattias Ekholm	AGE:28	PO:0	OV:71
John Klingberg	AGE:26	PO:0	OV:71
Ryan Graves	AGE:23	PO:0	OV:70
John Moore	AGE:27	PO:0	OV:67
Trevor Daley	AGE:35	PO:0	OV:64

Joakim Ryan	AGE:25	PO:0	OV:63
Roland McKeown	AGE:22	PO:0	OV:61
Ryan Collins	AGE:22	PO:0	OV:60
Luke Green	AGE:20	PO:0	OV:59
Hubert Labrie	AGE:27	PO:0	OV:58

Marc-Andre Fleury	AGE:33	PO:0	OV:78
Jake Allen	AGE:28	PO:0	OV:73
Connor Ingram	AGE:21	PO:0	OV:66

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	Lien
Adam Beckman	Predators	9	26
Al Montoya	Predators			Lien
Andrey Makarov	Predators
Artem Sergeev	Predators
Axel Bergkvist	Predators	9	119
B.J. Crombeen	Predators
Brett Bulmer	Predators
Brett Pollock	Predators			Lien
Brian Fahey	Predators
Brian O'Hanley	Predators
Bryan Allen	Predators
Bryan Helmer	Predators
Casey Wellman	Predators
Christian Hanson	Predators
Christophe Lalancette	Predators	2	110
Christopher Paquette	Predators	6	161
Colin Greening	Predators			Lien
Dalton Thrower	Predators	2	50
David Clarkson	Predators
David Legwand	Predators
David Liffiton	Predators
Declan Chisholm	Predators	8	151
Eric Nystrom	Predators
Fabrice Herzog	Predators	3	70
Filip Berglund	Predators	6	89
Fredric Larsson	Predators	2	80
Greg Zanon	Predators
Ivan Chukarov	Predators	5	168
Jackson Houck	Predators	3	90
Jared Boll	Predators
Jason DeSantis	Predators
Jean-Philippe Cote	Predators
Jesper Pettersson	Predators
Jim Vandermeer	Predators
Joey Dudek	Predators	4	169
Joey Mormina	Predators
Jordan Leopold	Predators
Josh Green	Predators
Kimmo Timonen	Predators
Louis-Marc Aubry	Predators
Lukas Parik	Predators	9	88
Lukas Sedlak	Predators			Lien
Luke Stevens	Predators	5	109
Martin Havlat	Predators
Matt Smaby	Predators
Maxwell Crozier	Predators	9	150
Nathan Horton	Predators
Nik Antropov	Predators
Nikita Soshnikov	Predators			Lien
Olivier Archambault	Predators
Olle Eriksson-Ek	Predators	7	69
Paul Bissonnette	Predators
Paul Szczechura	Predators
Peter Delmas	Predators
Petr Straka	Predators
Ryan Culkin	Predators			Lien
Ryan Malone	Predators
Ryan Tesink	Predators			Lien
Sami Aittokallio	Predators
Scott Hartnell	Predators
Sebastian Collberg	Predators
Sebastien Piche	Predators
Shawn Thornton	Predators
Thomas Vanek	Predators			Lien
Travis Moen	Predators
Trevor Ludwig	Predators
Tyler Tucker	Predators	8	120
Tyler Weiss	Predators	8	168
Vladimir Bobylev	Predators	6	125

Choix au Repêchage

Année	R1	R2	R3	R4	R5	R6
9						NSH
10	NSH	NSH		NSH	NSH	LAK NSH
11	NSH	NSH	NSH	NSH	NSH	NSH
12	NSH	NSH	NSH	NSH	NSH	NSH
13	NSH	NSH	NSH	NSH	NSH	NSH

La base de donnée des nouvelles n'a pas été trouvée

[2020-07-12 2:55:15 PM] - Predators drafts Maxwell Crozier as the #150 overall pick in the Entry Draft of year 9.
[2020-07-12 2:47:14 PM] - Predators drafts Axel Bergkvist as the #119 overall pick in the Entry Draft of year 9.
[2020-07-12 2:42:16 PM] - Predators drafts Lukas Parik as the #88 overall pick in the Entry Draft of year 9.
[2020-06-04 6:52:41 PM] - Predators drafts Adam Beckman as the #26 overall pick in the Entry Draft of year 9.
[2020-05-30 7:52:43 PM] - Eetu Tuulola was added to Predators.
[2020-05-30 7:52:43 PM] - Evgeny Svechnikov was added to Predators.
[2020-04-21 8:45:18 PM] - Predators was eliminated at round 1 of year 8.
[2020-04-05 11:48:32 AM] - Admirals didn't make playoff for year 8.
[2020-02-02 10:22:23 PM] - TRADE : From Blue Jackets to Predators : Daniel Carr (65).

[2020-07-12 2:55:15 PM] Predators drafts Maxwell Crozier as the #150 overall pick in the Entry Draft of year 9.
[2020-07-12 2:47:14 PM] Predators drafts Axel Bergkvist as the #119 overall pick in the Entry Draft of year 9.
[2020-07-12 2:42:16 PM] Predators drafts Lukas Parik as the #88 overall pick in the Entry Draft of year 9.
[2020-06-04 6:52:41 PM] Predators drafts Adam Beckman as the #26 overall pick in the Entry Draft of year 9.
[2020-05-30 7:52:43 PM] Eetu Tuulola was added to Predators.
[2020-05-30 7:52:43 PM] Evgeny Svechnikov was added to Predators.

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
Saison Régulière
2	82	29	30	0	4	4	6	9	219	212	7	41	16	14	0	2	2	3	4	109	105	4	41	13	16	0	2	2	3	5	110	107	3	58	219	365	584	1	5	68	79	62	15	2421	758	811	805	102	2423	755	1026	1735	344	52	15.12%	409	55	86.55%	5	1451	2897	50.09%	1475	3003	49.12%	645	1286	50.16%	1970	1349	1988	622	1051	519
3	82	19	46	0	4	4	3	6	156	232	-76	41	10	20	0	3	3	1	4	87	121	-34	41	9	26	0	1	1	2	2	69	111	-42	38	156	267	423	2	6	49	50	50	11	1886	620	614	627	56	2598	756	1153	1880	262	36	13.74%	476	72	84.87%	4	1176	2460	47.80%	1463	3135	46.67%	573	1169	49.02%	1770	1164	2171	643	1044	491
4	82	17	47	0	5	5	3	5	179	269	-90	41	7	24	0	1	4	2	3	87	130	-43	41	10	23	0	4	1	1	2	92	139	-47	34	179	318	497	2	2	71	57	43	15	2012	698	675	613	59	2590	729	504	1838	184	30	16.30%	226	48	78.76%	2	1200	2475	48.48%	1351	2895	46.67%	600	1282	46.80%	1748	1168	2161	623	1071	506
5	82	28	45	0	1	4	1	3	212	275	-63	41	13	22	0	0	4	0	2	104	141	-37	41	15	23	0	1	0	1	1	108	134	-26	56	212	379	591	4	2	74	59	77	3	2259	740	737	768	30	2614	802	568	1723	236	42	17.80%	237	57	75.95%	4	1246	2652	46.98%	1356	2884	47.02%	601	1285	46.77%	1854	1267	2055	610	1042	508
6	82	26	41	0	6	5	2	2	197	246	-49	41	15	19	0	4	2	1	0	102	116	-14	41	11	22	0	2	3	1	2	95	130	-35	52	197	343	540	5	4	69	66	54	10	2440	800	815	797	41	2473	742	613	1882	289	50	17.30%	250	56	77.60%	2	1401	2844	49.26%	1431	2808	50.96%	601	1191	50.46%	2013	1420	1932	583	1019	513
7	82	43	26	0	3	4	2	4	256	216	40	41	25	10	0	2	2	0	2	142	96	46	41	18	16	0	1	2	2	2	114	120	-6	86	256	458	714	1	7	84	94	73	8	2652	889	865	878	40	2357	697	605	1952	270	68	25.19%	258	49	81.01%	3	1536	2931	52.41%	1407	2749	51.18%	709	1312	54.04%	2032	1438	1917	570	1011	514
8	82	38	24	0	4	3	8	5	254	212	42	41	22	11	0	3	1	2	2	134	107	27	41	16	13	0	1	2	6	3	120	105	15	108	254	453	707	0	10	82	87	73	20	2510	788	843	832	94	2175	625	669	1775	338	62	18.34%	275	53	80.73%	2	1501	2916	51.47%	1359	2629	51.69%	623	1227	50.77%	2042	1428	1907	600	1045	533
8	82	38	24	0	4	3	8	5	254	212	42	41	22	11	0	3	1	2	2	134	107	27	41	16	13	0	1	2	6	3	120	105	15	108	254	453	707	0	10	82	87	73	20	2510	788	843	832	94	2175	625	669	1775	338	62	18.34%	275	53	80.73%	2	1501	2916	51.47%	1359	2629	51.69%	623	1227	50.77%	2042	1428	1907	600	1045	533
Total Saison Régulière	656	238	283	0	31	32	33	39	1727	1874	-147	328	130	131	0	18	19	11	19	899	923	-24	328	108	152	0	13	13	22	20	828	951	-123	540	1727	3036	4763	15	46	579	579	505	102	18690	6081	6203	6152	516	19405	5731	5807	14560	2261	402	17.78%	2406	443	81.59%	24	11012	22091	49.85%	11201	22732	49.27%	4975	9979	49.85%	15474	10665	16042	4855	8333	4120
Séries
7	11	5	6	0	0	0	0	0	32	35	-3	6	3	3	0	0	0	0	0	21	21	0	5	2	3	0	0	0	0	0	11	14	-3	10	32	58	90	2	1	12	10	10	0	390	124	137	117	12	333	104	80	262	40	7	17.50%	31	8	74.19%	0	223	426	52.35%	214	392	54.59%	84	176	47.73%	272	193	260	78	141	70
8	7	3	4	0	0	0	0	0	15	15	0	4	1	3	0	0	0	0	0	5	8	-3	3	2	1	0	0	0	0	0	10	7	3	6	15	29	44	0	0	3	3	9	0	201	56	67	65	13	187	63	48	186	38	7	18.42%	19	4	78.95%	0	142	272	52.21%	121	250	48.40%	51	99	51.52%	180	124	178	54	93	47
Total Séries	18	8	10	0	0	0	0	0	47	50	-3	10	4	6	0	0	0	0	0	26	29	-3	8	4	4	0	0	0	0	0	21	21	0	16	47	87	134	2	1	15	13	19	0	591	180	204	182	25	520	167	128	448	78	14	17.95%	50	12	76.00%	0	365	698	52.29%	335	642	52.18%	135	275	49.09%	453	318	439	133	235	117