PIFFPACK - Jets

Moose
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Points
Informations Joueurs
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Calendrier
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Historique
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Blessure/Suspension
Stats d'équipe en Carrière
Client Web pour Formation
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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	Aleksander Barkov	X				95.00	55	36	92	80	86	89	95	87	90	88	82	83	85	67	84	88	46	87	0
2	Gustav Nyquist		X	X		100.00	57	36	91	80	69	85	94	77	53	79	74	58	76	78	73	48	53	79	0
3	Pierre-Luc Dubois	X				99.00	80	43	72	78	85	83	95	76	80	77	77	68	79	61	66	89	53	79	0
4	Tomas Hertl	X	X			99.00	62	37	88	79	83	85	90	78	82	80	84	83	77	71	73	79	53	78	0
5	Travis Zajac	X				100.00	67	37	87	73	77	85	93	71	86	74	72	80	69	84	77	53	53	76	0
6	Derek Ryan	X				100.00	53	38	86	69	67	75	94	68	76	73	65	81	68	82	74	26	53	73	0
7	Jesper Bratt		X	X		100.00	63	36	92	73	65	78	64	72	53	80	65	57	69	61	62	49	53	73	0
8	Brendan Leipsic		X	X		99.00	70	39	83	68	67	75	76	66	53	71	62	56	64	69	66	61	53	71	0
9	Devin Shore	X	X			100.00	79	42	88	66	78	77	89	64	70	72	63	77	65	69	71	65	53	71	0
10	Tage Thompson		X	X		100.00	74	37	87	68	93	70	73	67	59	63	69	62	64	63	62	80	53	71	0
11	Andrew Cogliano	X	X			100.00	68	38	86	70	67	73	91	66	54	62	59	71	63	80	73	50	45	69	0
12	Dustin Byfuglien				X	98.00	84	53	56	76	98	91	65	74	30	88	66	75	63	84	75	36	53	78	0
13	Rasmus Ristolainen				X	99.00	93	40	80	72	89	91	92	71	30	82	63	74	56	69	67	84	53	76	0
14	Nikita Zadorov				X	100.00	95	60	65	66	95	83	84	66	30	67	67	78	54	67	64	82	53	75	0
15	Alex Goligoski				X	100.00	73	37	89	65	69	87	89	65	30	77	57	78	51	84	74	36	53	74	0
16	Matt Dumba				X	95.41	84	47	74	78	71	90	50	77	30	76	85	73	65	69	66	84	40	74	0
17	Mark Pysyk				X	100.00	84	39	83	60	77	83	84	59	30	70	53	75	47	73	67	69	53	71	0
Rayé
1	Gabriel Landeskog		X			93.00	82	47	73	79	80	87	86	78	72	82	85	73	81	74	91	77	50	85	0

	MOYENNE D'ÉQUIPE					98.72	74	41	82	72	79	83	84	71	56	76	69	72	66	73	71	64	51	76

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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	Mikko Koskinen	98.00	89	95	93	96	88	87	89	88	87	89	88	79	85	61	53	86	0
2	Craig Anderson	100.00	86	94	92	77	85	84	86	85	84	86	85	88	92	27	53	83	0
Rayé

	MOYENNE D'ÉQUIPE	99.00	88	95	93	87	87	86	88	87	86	88	87	84	89	44	53	85

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Todd Richards	75	80	85	69	78	73	71	USA	52	1	1,000,000$

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	GA	TA	EG	P/20	PSG	PSS	S1	S2	S3
1	Gabriel Landeskog	Jets	LW	32	22	19	41	2	22	61	40	120	33	62	18.33%	14	741	23.16	12	11	23	28	110	1	0	1	4	106	3	1	48.98%	98	19	15	0	1.11	2	3	5	2	1
2	Aleksander Barkov	Jets	C	25	14	21	35	2	0	26	64	125	39	73	11.20%	17	670	26.81	6	9	15	18	92	0	1	1	2	92	1	0	53.19%	957	17	12	0	1.04	1	2	3	1	1
3	Gustav Nyquist	Jets	LW/RW	32	8	22	30	3	2	24	39	116	38	61	6.90%	16	658	20.57	3	10	13	19	110	0	0	0	1	51	1	2	40.00%	60	21	7	1	0.91	0	2	1	0	2
4	Pierre-Luc Dubois	Jets	C	32	8	13	21	-9	36	54	57	96	33	64	8.33%	15	616	19.28	3	9	12	15	88	0	1	1	1	57	1	0	52.23%	538	11	10	0	0.68	1	3	0	1	2
5	Dustin Byfuglien	Jets	D	32	2	10	12	-12	70	73	52	72	22	34	2.78%	47	896	28.01	0	1	1	15	127	0	2	2	4	87	1	1	0.00%	0	17	27	0	0.27	0	0	0	1	0
6	Rasmus Ristolainen	Jets	D	32	4	6	10	-11	12	53	49	55	15	19	7.27%	64	882	27.58	1	3	4	4	127	0	0	0	2	118	0	1	0.00%	0	8	28	0	0.23	0	0	0	0	1
7	Tomas Hertl	Jets	C/LW	32	5	5	10	-9	10	33	33	106	34	63	4.72%	10	548	17.12	4	2	6	12	84	1	0	1	5	10	0	0	61.73%	81	14	7	0	0.36	0	1	0	1	0
8	Matt Dumba	Jets	D	31	1	8	9	-10	24	36	27	42	20	21	2.38%	25	503	16.24	1	0	1	3	41	0	0	0	0	42	0	0	0.00%	0	9	9	0	0.36	0	0	0	0	0
9	Jesper Bratt	Jets	LW/RW	32	3	4	7	-10	2	19	24	55	14	42	5.45%	11	536	16.77	1	2	3	4	84	0	0	0	0	0	0	0	38.10%	21	14	6	0	0.26	0	0	0	0	1
10	Travis Zajac	Jets	C	32	2	5	7	-12	6	14	35	74	26	56	2.70%	9	396	12.40	0	0	0	0	2	0	0	0	0	0	0	0	56.16%	203	10	7	0	0.35	1	1	0	0	0
11	Alex Goligoski	Jets	D	32	0	5	5	-1	2	22	28	15	7	11	0.00%	33	492	15.38	0	0	0	0	29	0	0	0	0	38	0	0	100.00%	1	4	18	0	0.20	0	0	0	0	0
12	Derek Ryan	Jets	C	32	2	3	5	-1	2	11	20	25	12	15	8.00%	3	270	8.46	0	0	0	0	0	0	0	0	1	29	0	0	52.04%	98	3	4	0	0.37	0	0	0	0	0
13	Nikita Zadorov	Jets	D	32	2	3	5	-10	34	57	41	23	14	15	8.70%	35	631	19.73	1	1	2	3	69	0	0	0	0	72	2	0	0.00%	0	4	21	0	0.16	0	0	0	0	1
14	Andrew Cogliano	Jets	C/LW	26	2	2	4	0	0	8	4	4	0	3	50.00%	2	96	3.73	0	1	1	0	3	0	0	0	0	26	1	0	40.00%	15	0	1	0	0.83	0	0	0	1	1
15	Brendan Leipsic	Jets	LW/RW	32	2	2	4	-11	14	31	32	51	12	35	3.92%	3	434	13.57	0	0	0	1	14	0	0	0	0	13	1	0	37.50%	16	6	7	0	0.18	0	0	0	1	0
16	Tage Thompson	Jets	LW/RW	32	2	1	3	-12	2	28	24	42	15	22	4.76%	11	398	12.46	0	0	0	0	0	0	0	0	0	14	1	0	60.00%	15	9	9	0	0.15	0	0	0	0	0
17	Devin Shore	Jets	C/LW	32	2	0	2	1	2	7	11	8	1	6	25.00%	0	168	5.28	0	0	0	0	0	0	0	0	0	1	0	0	20.00%	5	2	2	0	0.24	0	0	0	1	0
18	Noah Juulsen	Moose (WPG)	D	13	0	1	1	-2	4	7	12	4	2	1	0.00%	10	158	12.21	0	0	0	0	0	0	0	0	0	18	0	0	0.00%	0	0	5	0	0.13	0	0	0	0	0
19	Brock McGinn	Moose (WPG)	LW/RW	1	0	0	0	-2	0	0	1	0	1	1	0.00%	0	15	15.17	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0	0	0.00	0	0	0	0	0
20	Mark Pysyk	Jets	D	32	0	0	0	3	18	13	25	15	2	5	0.00%	27	311	9.74	0	0	0	0	0	0	0	0	1	37	0	0	0.00%	0	0	7	0	0.00	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				576	81	130	211	-101	262	577	618	1048	340	609	7.73%	352	9429	16.37	32	49	81	122	990	2	4	6	21	821	12	5	52.56%	2108	168	202	1	0.45	5	12	9	9	10

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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
1	Mikko Koskinen	Jets	30	12	15	3	0.916	2.70	1799	2	1	81	964	445	4	3	0.667	12	30	2	3	5
2	Craig Anderson	Jets	3	2	0	0	0.925	2.65	136	2	0	6	80	33	0	0	0.000	0	2	30	0	1
Stats d'équipe Total ou en Moyenne			33	14	15	3	0.917	2.70	1935	4	1	87	1044	478	4	3	0.667	12	32	32	3	6

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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
Aleksander Barkov (Sur la Masse Salariale)	Jets	C	22	1995-09-02	No	213 Lbs	6 ft3	No	No	No	3	Contrat d'Entrée	Pro & Farm	5,900,000$	5,900,000$	3,683,598$	No	Lien
Alex Goligoski	Jets	D	32	1985-07-30	No	185 Lbs	5 ft11	No	No	No	2	Sans Restriction	Pro & Farm	5,475,000$	5,475,000$	3,418,254$	No	Lien
Andrew Cogliano	Jets	C/LW	30	1987-06-14	No	177 Lbs	5 ft10	No	No	No	2	Sans Restriction	Pro & Farm	3,250,000$	3,250,000$	2,029,101$	No	Lien
Brendan Leipsic	Jets	LW/RW	23	1994-05-19	No	182 Lbs	5 ft10	No	No	No	1	Contrat d'Entrée	Pro & Farm	750,000$	750,000$	468,254$	No	Lien
Craig Anderson	Jets	G	36	1981-05-21	No	185 Lbs	6 ft2	No	No	No	1	Sans Restriction	Pro & Farm	1,175,000$	1,175,000$	733,598$	No	Lien
Derek Ryan	Jets	C	30	1986-12-29	No	185 Lbs	5 ft10	No	No	No	2	Sans Restriction	Pro & Farm	3,125,000$	3,125,000$	1,951,058$	No	Lien
Devin Shore	Jets	C/LW	23	1994-07-19	No	205 Lbs	6 ft1	No	No	No	1	Contrat d'Entrée	Pro & Farm	2,300,000$	2,300,000$	1,435,979$	No	Lien
Dustin Byfuglien	Jets	D	32	1985-03-27	No	260 Lbs	6 ft5	No	No	No	2	Sans Restriction	Pro & Farm	7,600,000$	7,600,000$	4,744,974$	No	Lien
Gabriel Landeskog (Sur la Masse Salariale)	Jets	LW	24	1992-11-23	No	215 Lbs	6 ft1	No	No	No	2	Contrat d'Entrée	Pro & Farm	5,571,428$	5,571,428$	3,478,458$	No	Lien
Gustav Nyquist	Jets	LW/RW	28	1989-09-01	No	184 Lbs	5 ft11	No	No	No	1	Sans Restriction	Pro & Farm	5,500,000$	5,500,000$	3,433,862$	No	Lien
Jesper Bratt	Jets	LW/RW	19	1998-07-30	No	175 Lbs	5 ft10	No	No	No	1	Contrat d'Entrée	Pro & Farm	750,000$	750,000$	468,254$	No	Lien
Mark Pysyk	Jets	D	25	1992-01-11	No	200 Lbs	6 ft1	No	No	No	1	Contrat d'Entrée	Pro & Farm	2,733,333$	2,733,333$	1,706,525$	No	Lien
Matt Dumba (Sur la Masse Salariale)	Jets	D	23	1994-07-25	No	182 Lbs	6 ft0	No	No	No	4	Contrat d'Entrée	Pro & Farm	6,000,000$	6,000,000$	3,746,032$	No	Lien
Mikko Koskinen	Jets	G	29	1988-07-18	No	202 Lbs	6 ft7	No	No	No	3	Sans Restriction	Pro & Farm	3,575,000$	3,575,000$	2,232,011$	No	Lien
Nikita Zadorov	Jets	D	22	1995-04-16	No	230 Lbs	6 ft5	No	No	No	1	Contrat d'Entrée	Pro & Farm	3,200,000$	3,200,000$	1,997,884$	No	Lien
Pierre-Luc Dubois	Jets	C	19	1998-06-24	No	207 Lbs	6 ft3	No	No	No	1	Contrat d'Entrée	Pro & Farm	894,166$	894,166$	558,262$	No	Lien
Rasmus Ristolainen	Jets	D	22	1994-10-27	No	215 Lbs	6 ft4	No	No	No	3	Contrat d'Entrée	Pro & Farm	5,400,000$	5,400,000$	3,371,429$	No	Lien
Tage Thompson	Jets	LW/RW	19	1997-10-30	No	205 Lbs	6 ft6	No	No	No	1	Contrat d'Entrée	Pro & Farm	925,000$	925,000$	577,513$	No	Lien
Tomas Hertl	Jets	C/LW	23	1993-11-12	No	215 Lbs	6 ft2	No	No	No	3	Contrat d'Entrée	Pro & Farm	5,625,000$	5,625,000$	3,511,905$	No	Lien
Travis Zajac	Jets	C	32	1985-05-13	No	185 Lbs	6 ft2	No	No	No	2	Sans Restriction	Pro & Farm	4,125,000$	4,125,000$	2,575,397$	No	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
20	25.65	200 Lbs	6 ft2	1.85	3,693,696$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
73,873,927$	55,646,428$	26,500,000$	6,000,000$	0$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1		Aleksander Barkov	Gustav Nyquist	40	1	2	2
2	Tomas Hertl	Pierre-Luc Dubois	Jesper Bratt	30	1	2	2
3	Tage Thompson	Travis Zajac	Brendan Leipsic	20	1	2	2
4	Devin Shore	Derek Ryan	Aleksander Barkov	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dustin Byfuglien	Rasmus Ristolainen	40	1	2	2
2	Nikita Zadorov	Matt Dumba	30	1	2	2
3	Alex Goligoski	Mark Pysyk	20	1	2	2
4	Dustin Byfuglien	Rasmus Ristolainen	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1		Aleksander Barkov	Gustav Nyquist	60	1	2	2
2	Tomas Hertl	Pierre-Luc Dubois	Jesper Bratt	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dustin Byfuglien	Rasmus Ristolainen	60	1	2	2
2	Nikita Zadorov	Matt Dumba	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Aleksander Barkov		60	1	2	2
2	Pierre-Luc Dubois	Gustav Nyquist	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dustin Byfuglien	Rasmus Ristolainen	60	1	2	2
2	Nikita Zadorov	Matt Dumba	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Aleksander Barkov	60	1	2	2	Dustin Byfuglien	Rasmus Ristolainen	60	1	2	2
2		40	1	2	2	Nikita Zadorov	Matt Dumba	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Aleksander Barkov		60	1	2	2
2	Pierre-Luc Dubois	Gustav Nyquist	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dustin Byfuglien	Rasmus Ristolainen	60	1	2	2
2	Nikita Zadorov	Matt Dumba	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
	Aleksander Barkov	Gustav Nyquist	Dustin Byfuglien	Rasmus Ristolainen

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
	Aleksander Barkov	Gustav Nyquist	Dustin Byfuglien	Rasmus Ristolainen

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Andrew Cogliano, Travis Zajac, Derek Ryan	Andrew Cogliano, Travis Zajac	Derek Ryan

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Alex Goligoski, Mark Pysyk, Nikita Zadorov	Alex Goligoski	Mark Pysyk, Nikita Zadorov

Tirs de Pénalité
Aleksander Barkov, , Pierre-Luc Dubois, Gustav Nyquist, Tomas Hertl

Gardien
#1 : Mikko Koskinen, #2 : Craig Anderson

Lignes d'Attaque Perso. en Prol.
, , , , , , , , , ,

Lignes de Défense Perso. en Prol.
, , , ,

Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

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

	Ligue												Domicile											Visiteur
#	VS Équipe	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	PCT	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
1	Avalanche	2	0	1	0	1	0	0	0	5	5	0	1	0	0	0	1	0	0	0	3	2	1	1	0	1	0	0	0	0	0	2	3	-1	2	0.500	5	7	12	0	0	1	2	1	1	66	19	27	18	2	37	18	12	37	10	2	20.00%	6	1	83.33%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	48	27	34	18	38	19
2	Blackhawks	4	2	2	0	0	0	0	0	12	11	1	1	1	0	0	0	0	0	0	4	3	1	3	1	2	0	0	0	0	0	8	8	0	4	0.500	12	18	30	1	0	2	3	7	0	123	41	30	52	0	134	54	32	74	15	6	40.00%	16	2	87.50%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	83	46	86	38	70	35
3	Blue Jackets	2	0	2	0	0	0	0	0	4	11	-7	1	0	1	0	0	0	0	0	1	4	-3	1	0	1	0	0	0	0	0	3	7	-4	0	0.000	4	5	9	0	0	1	1	2	0	50	24	15	11	0	83	26	20	35	8	0	0.00%	10	3	70.00%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	42	23	43	17	34	17
4	Blues	4	1	2	0	0	0	0	1	9	11	-2	2	0	2	0	0	0	0	0	3	5	-2	2	1	0	0	0	0	0	1	6	6	0	3	0.375	9	17	26	0	0	3	2	4	2	129	38	42	47	6	149	36	40	72	23	3	13.04%	20	2	90.00%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	85	45	86	38	72	37
5	Bruins	2	0	0	0	1	1	0	0	8	8	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	1	1	0	0	8	8	0	3	0.750	8	14	22	0	0	1	1	5	1	66	2	31	32	1	49	18	10	38	8	4	50.00%	5	0	100.00%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	41	21	36	19	42	20
6	Ducks	2	0	2	0	0	0	0	0	3	6	-3	2	0	2	0	0	0	0	0	3	6	-3	0	0	0	0	0	0	0	0	0	0	0	0	0.000	3	6	9	0	0	0	1	2	0	64	18	14	32	0	66	18	20	48	4	1	25.00%	10	2	80.00%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	42	22	39	18	38	19
7	Flyers	1	0	1	0	0	0	0	0	1	2	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	2	-1	0	0.000	1	2	3	0	0	0	1	0	0	35	14	15	6	0	25	9	4	12	2	0	0.00%	2	0	100.00%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	21	12	20	9	17	9
8	Islanders	1	0	0	0	0	0	1	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	4	3	1	2	1.000	4	5	9	0	0	1	0	2	2	36	13	4	18	6	37	15	6	10	5	3	60.00%	3	0	100.00%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	20	12	24	10	19	9
9	Kings	1	1	0	0	0	0	0	0	3	2	1	1	1	0	0	0	0	0	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	3	6	9	0	0	1	0	2	0	35	16	3	16	0	37	13	8	25	3	1	33.33%	4	1	75.00%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	19	11	22	9	17	8
10	Lightning	1	1	0	0	0	0	0	0	2	0	2	1	1	0	0	0	0	0	0	2	0	2	0	0	0	0	0	0	0	0	0	0	0	2	1.000	2	2	4	0	1	0	1	1	0	38	9	14	15	0	26	7	4	14	6	1	16.67%	2	0	100.00%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	20	11	22	9	17	8
11	Maple Leafs	1	1	0	0	0	0	0	0	3	1	2	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	3	1	2	2	1.000	3	4	7	0	0	1	0	2	0	22	12	5	5	0	29	17	12	20	3	1	33.33%	6	1	83.33%	1	447	841	53.15%	435	802	54.24%	226	449	50.33%	18	9	23	10	18	8
12	Penguins	1	0	1	0	0	0	0	0	2	4	-2	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	2	4	-2	0	0.000	2	4	6	1	0	1	1	0	0	27	6	7	14	0	33	17	12	15	3	0	0.00%	6	2	66.67%	1	447	841	53.15%	435	802	54.24%	226	449	50.33%	19	10	22	9	17	8
13	Predateurs	6	2	3	0	0	0	1	0	17	18	-1	3	1	1	0	0	0	1	0	11	11	0	3	1	2	0	0	0	0	0	6	7	-1	6	0.500	17	24	41	0	0	4	5	7	1	206	64	72	69	4	211	62	52	109	26	5	19.23%	26	6	76.92%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	124	69	130	57	110	54
14	Senateurs	1	0	0	0	0	1	0	0	2	3	-1	1	0	0	0	0	1	0	0	2	3	-1	0	0	0	0	0	0	0	0	0	0	0	1	0.500	2	2	4	0	0	0	1	1	0	36	17	10	9	0	36	11	10	23	3	2	66.67%	5	1	80.00%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	21	12	23	9	16	8
15	Sharks	1	1	0	0	0	0	0	0	4	1	3	1	1	0	0	0	0	0	0	4	1	3	0	0	0	0	0	0	0	0	0	0	0	2	1.000	4	7	11	0	0	1	1	2	0	31	9	7	15	0	36	16	6	16	5	1	20.00%	3	0	100.00%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	23	14	20	7	16	9
16	Stars	2	1	1	0	0	0	0	0	4	5	-1	1	0	1	0	0	0	0	0	2	4	-2	1	1	0	0	0	0	0	0	2	1	1	2	0.500	4	7	11	1	0	0	2	2	0	84	22	28	34	0	59	15	18	29	11	2	18.18%	9	0	100.00%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	46	27	38	17	34	17
	Total	32	10	15	0	2	2	2	1	83	91	-8	15	5	7	0	1	1	1	0	38	41	-3	17	5	8	0	1	1	1	1	45	50	-5	31	0.484	83	130	213	3	1	17	22	40	7	1048	324	324	393	19	1047	352	266	577	135	32	23.70%	133	21	84.21%	2	447	841	53.15%	435	802	54.24%	226	449	50.33%	680	378	677	300	582	292
	_Since Last GM Reset	32	10	15	0	2	2	2	1	83	91	-8	15	5	7	0	1	1	1	0	38	41	-3	17	5	8	0	1	1	1	1	45	50	-5	31	0.484	83	130	213	3	1	17	22	40	7	1048	324	324	393	19	1047	352	266	577	135	32	23.70%	133	21	84.21%	2	447	841	53.15%	435	802	54.24%	226	449	50.33%	680	378	677	300	582	292
	_Vs Conference	22	8	11	0	1	0	1	1	57	59	-2	12	4	6	0	1	0	1	0	33	34	-1	10	4	5	0	0	0	0	1	24	25	-1	21	0.477	57	92	149	2	0	12	16	27	4	738	227	223	283	12	729	232	188	410	97	21	21.65%	94	14	85.11%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	474	264	459	206	398	201
	_Vs Division	18	6	9	0	1	0	1	1	47	50	-3	8	2	4	0	1	0	1	0	23	25	-2	10	4	5	0	0	0	0	1	24	25	-1	17	0.472	47	73	120	2	0	10	14	21	4	608	184	199	220	12	590	185	154	321	85	18	21.18%	77	11	85.71%	0	447	841	53.15%	435	802	54.24%	226	449	50.33%	388	216	377	170	326	164

			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
32	31	SOW1	83	130	213	1048	1047	352	266	577	3	1

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
32	10	15	2	2	2	1	83	91

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
15	5	7	1	1	1	0	38	41

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
17	5	8	1	1	1	1	45	50

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	5	0	0	1	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
135	32	23.70%	133	21	84.21%	2

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
324	324	393	19	17	22	40	7

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
447	841	53.15%	435	802	54.24%	226	449	50.33%

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
680	378	677	300	582	292

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
2 - 2019-10-05	9	Jets	2	Avalanche	3	L			Sommaire du Match
4 - 2019-10-07	20	Stars	4	Jets	2	L			Sommaire du Match
5 - 2019-10-08	22	Jets	3	Blues	2	W			Sommaire du Match
8 - 2019-10-11	38	Sharks	1	Jets	4	W			Sommaire du Match
11 - 2019-10-14	56	Blues	2	Jets	1	L			Sommaire du Match
15 - 2019-10-18	76	Avalanche	2	Jets	3	W	X		Sommaire du Match
16 - 2019-10-19	83	Jets	2	Stars	1	W			Sommaire du Match
19 - 2019-10-22	96	Jets	2	Predateurs	3	L			Sommaire du Match
21 - 2019-10-24	105	Predateurs	7	Jets	2	L			Sommaire du Match
25 - 2019-10-28	123	Blackhawks	3	Jets	4	W			Sommaire du Match
27 - 2019-10-30	136	Jets	3	Blues	4	L	X	X	Sommaire du Match
28 - 2019-10-31	147	Jets	4	Blackhawks	1	W			Sommaire du Match
30 - 2019-11-02	156	Predateurs	2	Jets	3	W	X	X	Sommaire du Match
33 - 2019-11-05	172	Kings	2	Jets	3	W			Sommaire du Match
35 - 2019-11-07	186	Jets	4	Bruins	5	L	X		Sommaire du Match
37 - 2019-11-09	195	Jets	3	Blackhawks	5	L			Sommaire du Match
39 - 2019-11-11	201	Senateurs	3	Jets	2	L	X		Sommaire du Match
41 - 2019-11-13	211	Jets	4	Bruins	3	W	X		Sommaire du Match
44 - 2019-11-16	226	Ducks	2	Jets	1	L			Sommaire du Match
46 - 2019-11-18	233	Jets	1	Flyers	2	L			Sommaire du Match
48 - 2019-11-20	244	Jets	1	Blackhawks	2	L			Sommaire du Match
50 - 2019-11-22	256	Blue Jackets	4	Jets	1	L			Sommaire du Match
52 - 2019-11-24	263	Jets	3	Blue Jackets	7	L			Sommaire du Match
54 - 2019-11-26	272	Jets	2	Predateurs	3	L			Sommaire du Match
56 - 2019-11-28	283	Ducks	4	Jets	2	L			Sommaire du Match
58 - 2019-11-30	299	Jets	3	Maple Leafs	1	W			Sommaire du Match
60 - 2019-12-02	307	Blues	3	Jets	2	L			Sommaire du Match
62 - 2019-12-04	320	Jets	2	Penguins	4	L			Sommaire du Match
65 - 2019-12-07	330	Predateurs	2	Jets	6	W			Sommaire du Match
67 - 2019-12-09	344	Jets	2	Predateurs	1	W			Sommaire du Match
69 - 2019-12-11	354	Lightning	0	Jets	2	W			Sommaire du Match
71 - 2019-12-13	366	Jets	4	Islanders	3	W	X	X	Sommaire du Match
73 - 2019-12-15	375	Jets	-	Senateurs	-
74 - 2019-12-16	384	Stars	-	Jets	-
78 - 2019-12-20	401	Canadiens	-	Jets	-
80 - 2019-12-22	414	Jets	-	Panthers	-
82 - 2019-12-24	426	Flyers	-	Jets	-
86 - 2019-12-28	446	Devils	-	Jets	-
88 - 2019-12-30	458	Jets	-	Golden Knights	-
90 - 2020-01-01	466	Golden Knights	-	Jets	-
93 - 2020-01-04	484	Jets	-	Canadiens	-
94 - 2020-01-05	496	Maple Leafs	-	Jets	-
98 - 2020-01-09	515	Capitals	-	Jets	-
100 - 2020-01-11	525	Jets	-	Blues	-
102 - 2020-01-13	536	Islanders	-	Jets	-
103 - 2020-01-14	547	Jets	-	Capitals	-
106 - 2020-01-17	560	Penguins	-	Jets	-
110 - 2020-01-21	581	Bruins	-	Jets	-
113 - 2020-01-24	594	Jets	-	Blues	-
115 - 2020-01-26	604	Jets	-	Golden Knights	-
116 - 2020-01-27	610	Blackhawks	-	Jets	-
119 - 2020-01-30	628	Flames	-	Jets	-
121 - 2020-02-01	642	Jets	-	Stars	-
123 - 2020-02-03	651	Flames	-	Jets	-
125 - 2020-02-05	662	Jets	-	Devils	-
128 - 2020-02-08	675	Blues	-	Jets	-
130 - 2020-02-10	686	Jets	-	Lightning	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
133 - 2020-02-13	701	Sharks	-	Jets	-
137 - 2020-02-17	722	Jets	-	Kings	-
138 - 2020-02-18	726	Stars	-	Jets	-
141 - 2020-02-21	743	Jets	-	Stars	-
142 - 2020-02-22	748	Sharks	-	Jets	-
146 - 2020-02-26	771	Avalanche	-	Jets	-
148 - 2020-02-28	782	Jets	-	Sharks	-
150 - 2020-03-01	793	Avalanche	-	Jets	-
153 - 2020-03-04	808	Jets	-	Avalanche	-
155 - 2020-03-06	820	Panthers	-	Jets	-
157 - 2020-03-08	828	Jets	-	Kings	-
159 - 2020-03-10	837	Jets	-	Sharks	-
160 - 2020-03-11	844	Jets	-	Oilers	-
162 - 2020-03-13	851	Golden Knights	-	Jets	-
165 - 2020-03-16	869	Jets	-	Oilers	-
166 - 2020-03-17	874	Blackhawks	-	Jets	-
169 - 2020-03-20	892	Oilers	-	Jets	-
171 - 2020-03-22	900	Jets	-	Ducks	-
173 - 2020-03-24	916	Kings	-	Jets	-
174 - 2020-03-25	922	Jets	-	Avalanche	-
175 - 2020-03-26	926	Jets	-	Ducks	-
179 - 2020-03-30	943	Oilers	-	Jets	-
183 - 2020-04-03	955	Jets	-	Flames	-
184 - 2020-04-04	964	Kings	-	Jets	-
185 - 2020-04-05	970	Jets	-	Flames	-

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	85	65	35	200
Assistance	85,166	46,095	15,671	42,343	14,067
Attendance PCT	94.63%	61.46%	52.24%	70.57%	93.78%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
26	13556 - 75.31%	1,609,215$	24,138,226$	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
27,071,172$	68,302,499$	68,239,999$	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
68,302,499$	26,695,511$	0$	19	1

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
41,839,592$	118	366,680$	43,268,240$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Cap Salarial de la Saison Éstimé	Compte Bancaire Actuel	Compte Bancaire Projeté
44,185,880$	68,302,499$	3,847,136$	1,500,848$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Gabriel Landeskog	AGE:24	PO:77	OV:85
Gustav Nyquist	AGE:28	PO:48	OV:79
Tomas Hertl	AGE:23	PO:79	OV:78
Jesper Bratt	AGE:19	PO:49	OV:73
Tage Thompson	AGE:19	PO:80	OV:71
Devin Shore	AGE:23	PO:65	OV:71
Brendan Leipsic	AGE:23	PO:61	OV:71
Filip Chytil	AGE:18	PO:84	OV:70
Brock McGinn	AGE:23	PO:70	OV:70
Andrew Cogliano	AGE:30	PO:50	OV:69
Stefan Noesen	AGE:24	PO:78	OV:67
Max Comtois	AGE:18	PO:78	OV:67
Janne Kuokkanen	AGE:19	PO:74	OV:63
Remi Elie	AGE:22	PO:73	OV:63

Aleksander Barkov	AGE:22	PO:88	OV:87
Pierre-Luc Dubois	AGE:19	PO:89	OV:79
Tomas Hertl	AGE:23	PO:79	OV:78
Travis Zajac	AGE:32	PO:53	OV:76
Derek Ryan	AGE:30	PO:26	OV:73
Devin Shore	AGE:23	PO:65	OV:71
Filip Chytil	AGE:18	PO:84	OV:70
Kyle Brodziak	AGE:33	PO:34	OV:70
Andrew Cogliano	AGE:30	PO:50	OV:69
Janne Kuokkanen	AGE:19	PO:74	OV:63

Gustav Nyquist	AGE:28	PO:48	OV:79
Jesper Bratt	AGE:19	PO:49	OV:73
Tage Thompson	AGE:19	PO:80	OV:71
Brendan Leipsic	AGE:23	PO:61	OV:71
Filip Chytil	AGE:18	PO:84	OV:70
Brock McGinn	AGE:23	PO:70	OV:70
Stefan Noesen	AGE:24	PO:78	OV:67

Défense #1

Défense #2

Gardien

Dustin Byfuglien	AGE:32	PO:36	OV:78
Rasmus Ristolainen	AGE:22	PO:84	OV:76
Nikita Zadorov	AGE:22	PO:82	OV:75
Matt Dumba	AGE:23	PO:84	OV:74
Alex Goligoski	AGE:32	PO:36	OV:74

Noah Juulsen	AGE:20	PO:80	OV:71
Mark Pysyk	AGE:25	PO:69	OV:71
Juuso Valimaki	AGE:18	PO:84	OV:68
Gustav Forsling	AGE:21	PO:68	OV:66

Mikko Koskinen	AGE:29	PO:61	OV:86
Craig Anderson	AGE:36	PO:27	OV:83
Tristan Jarry	AGE:22	PO:75	OV:75

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
Albin Eriksson	Jets	2018	67
Cameron Hillis	Jets	2018	91
Cole Caufield	Jets	3	8
Connor Timmins	Jets	2017	32
Dominic Moore	Jets
Jacob Olofsson	Jets	2018	43
Jason Robertson	Jets	2017	39
John Beecher	Jets	3	55
Kiefer Bellows	Jets	2016	19
Linus Karlsson	Jets	2018	115
Marcus Davidsson	Jets
Mattias Norlinder	Jets	3	79
Michael Cammalleri	Jets
Nolan Foote	Jets	3	31
Owen Tippett	Jets
Robert Mastrosimone	Jets	3	103
Shane Bowers	Jets
Ty Dellandrea	Jets	2018	12

Choix au Repêchage

Année	R1	R2	R3	R4	R5
4	WPG	WPG	WPG		WPG
5	WPG	WPG	WPG	WPG	WPG
6	WPG	WPG	WPG	WPG	WPG
7	WPG	WPG	WPG	WPG	WPG
8	WPG	WPG	WPG	WPG	WPG

[2019-10-02 21:41:10] - Moose hired Joe Sacco for 500 000 $ for 2 year(s).
[2019-09-26 21:59:54] - TRADE : From Islanders to Jets : Dustin Byfuglien (78).
[2019-09-26 21:59:34] - TRADE : From Jets to Senateurs : Y:4-RND:4-WPG.
[2019-09-26 21:59:34] - TRADE : From Senateurs to Jets : Gustav Nyquist (79).
[2019-09-20 21:37:46] - Mikko Koskinen was added to Jets.
[2019-09-16 21:53:25] - Cam Talbot was released.
[2019-09-16 21:53:25] - Jonathan Ericsson was released.
[2019-09-16 21:53:25] - Jason Pominville was released.
[2019-08-26 22:48:11] - Jets drafts Robert Mastrosimone as the #103 overall pick in the Entry Draft of year 3.
[2019-07-12 23:13:22] - Jets drafts Mattias Norlinder as the #79 overall pick in the Entry Draft of year 3.
[2019-07-03 23:43:00] - Jets drafts John Beecher as the #55 overall pick in the Entry Draft of year 3.
[2019-07-03 23:34:35] - Jets drafts Nolan Foote as the #31 overall pick in the Entry Draft of year 3.
[2019-07-01 15:15:21] - Jets drafts Cole Caufield as the #8 overall pick in the Entry Draft of year 3.
[2019-06-21 22:09:44] - Juuso Valimaki was added to Jets.
[2019-06-21 22:09:27] - Juuso Valimaki has been deleted from Jets.
[2019-06-21 22:02:31] - Maxim Comtois has been deleted from Jets.
[2019-06-21 22:02:21] - Max Comtois was added to Jets.
[2019-05-26 21:53:43] - Ron Wilson contract with Moose has ended.
[2019-04-19 21:22:29] - Moose was eliminated at round 1 of year 2.
[2019-04-03 21:21:12] - Jets didn't make playoff for year 2.
[2019-03-08 19:57:56] - New Record for Team's Most Hits (34) in 1 Game for Jets!
[2019-03-07 22:31:57] - New Record for Team's Most Points (19) in 1 Game for Jets!
[2019-03-07 22:31:57] - New Record for Team's Most Assists (12) in 1 Game for Jets!

[2019-12-13 20:55:21] Matt Dumba from Jets is back from Strained Right Elbow Injury.
[2019-12-13 20:55:21] Aleksander Barkov from Jets is back from Exhaustion.
[2019-12-13 20:55:21] Noah Juulsen of Jets was sent to farm.
[2019-12-13 20:55:21] Brock McGinn of Jets was sent to farm.
[2019-12-13 20:55:21] Kyle Brodziak from Moose is injured from Exhaustion.
[2019-12-13 20:55:21] Gabriel Landeskog from Jets is injured from Exhaustion.
[2019-12-13 20:55:01] Auto Lines Function has been run for Jets.
[2019-12-13 20:55:01] Auto Roster Partial Function has been run for Jets.
[2019-12-13 20:55:01] Brock McGinn of Jets was sent to pro.
[2019-12-13 20:55:01] Noah Juulsen of Jets was sent to pro.
[2019-12-13 20:54:17] Successfully loaded Jets lines done with STHS Client - 3.1.9.9
[2019-12-13 20:54:16] Noah Juulsen of Jets was sent down to farm.
[2019-12-13 20:54:15] Brock McGinn of Jets was sent down to farm.
[2019-12-13 20:53:40] Auto Lines Function has been run for Jets.
[2019-12-13 20:53:40] Auto Roster Partial Function has been run for Jets.
[2019-12-13 20:53:40] Brock McGinn of Jets was sent to pro.
[2019-12-13 20:53:40] Noah Juulsen of Jets was sent to pro.
[2019-12-12 18:18:26] Gabriel Landeskog from Jets is back from Exhaustion.
[2019-12-12 18:18:26] Last 7 Days Pro Star : 1 - Jacob Markstrom of Stars (0,964) / 2 - Mikko Koskinen of Jets (0,965) / 3 - Derek Stepan of Penguins (4-3-7)
[2019-12-11 19:33:17] Jets are expected to be under the minimum salary cap by 3 597 501 $!
[2019-12-11 19:32:51] Tristan Jarry from Moose is back from Exhaustion.
[2019-12-11 19:32:51] Kyle Brodziak from Moose is back from Exhaustion.
[2019-12-11 19:32:50] Gabriel Landeskog from Jets is injured from Exhaustion.
[2019-12-11 19:32:50] Aleksander Barkov from Jets is injured from Exhaustion.
[2019-12-11 19:32:50] Game 354 - Matt Dumba from Jets is injured (Strained Right Elbow) and is out for 1 week.
[2019-12-11 19:32:23] Successfully loaded Jets lines done with STHS Client - 3.1.9.9
[2019-12-11 19:32:03] Auto Lines Function has been run for Jets.
[2019-12-11 19:32:03] Auto Roster Partial Function has been run for Jets.
[2019-12-10 12:35:31] Juuso Valimaki from Moose is back from Exhaustion.
[2019-12-10 12:35:31] Gabriel Landeskog from Jets is back from Exhaustion.
[2019-12-10 12:35:31] Aleksander Barkov from Jets is back from Exhaustion.
[2019-12-10 12:35:30] Kyle Brodziak from Moose is injured from Exhaustion.
[2019-12-09 21:39:24] Tristan Jarry from Moose injured (Exhaustion)
[2019-12-09 21:39:24] Juuso Valimaki from Moose is injured from Exhaustion.
[2019-12-09 21:39:24] Gabriel Landeskog from Jets is injured from Exhaustion.
[2019-12-09 21:39:24] Aleksander Barkov from Jets is injured from Exhaustion.
[2019-12-09 21:39:09] Successfully loaded Jets lines done with STHS Client - 3.1.9.9
[2019-12-09 21:38:58] Auto Lines Function has been run for Jets.
[2019-12-09 21:38:58] Auto Roster Partial Function has been run for Jets.
[2019-12-09 00:19:46] Tristan Jarry from Moose is back from Exhaustion.
[2019-12-09 00:19:46] Juuso Valimaki from Moose is back from Exhaustion.
[2019-12-09 00:19:46] Gabriel Landeskog from Jets is back from Exhaustion.
[2019-12-07 20:07:17] Tristan Jarry from Moose injured (Exhaustion)
[2019-12-07 20:07:17] Juuso Valimaki from Moose is injured from Exhaustion.
[2019-12-07 20:07:17] Gabriel Landeskog from Jets is injured from Exhaustion.
[2019-12-07 20:07:01] Successfully loaded Jets lines done with STHS Client - 3.1.9.9
[2019-12-07 20:06:47] Auto Lines Function has been run for Jets.
[2019-12-07 20:06:47] Auto Roster Partial Function has been run for Jets.
[2019-12-06 22:53:42] Tristan Jarry from Moose is back from Exhaustion.
[2019-12-06 22:53:42] Juuso Valimaki from Moose is back from Exhaustion.

Gabriel Landeskog est dehors pour 2 jours à cause de Exhaustion.
Kyle Brodziak est dehors pour 1 jours à cause de Exhaustion.

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
3	32	10	15	0	2	2	2	1	83	91	-8	15	5	7	0	1	1	1	0	38	41	-3	17	5	8	0	1	1	1	1	45	50	-5	31	83	130	213	3	1	17	22	40	7	1048	324	324	393	19	1047	352	266	577	135	32	23.70%	133	21	84.21%	2	447	841	53.15%	435	802	54.24%	226	449	50.33%	680	378	677	300	582	292
Total Saison Régulière	32	10	15	0	2	2	2	1	83	91	-8	15	5	7	0	1	1	1	0	38	41	-3	17	5	8	0	1	1	1	1	45	50	-5	31	83	130	213	3	1	17	22	40	7	1048	324	324	393	19	1047	352	266	577	135	32	23.70%	133	21	84.21%	2	447	841	53.15%	435	802	54.24%	226	449	50.33%	680	378	677	300	582	292

Année	R1	R2	R3	R4	R5
4	WPG	WPG	WPG		WPG
5	WPG	WPG	WPG	WPG	WPG
6	WPG	WPG	WPG	WPG	WPG
7	WPG	WPG	WPG	WPG	WPG
8	WPG	WPG	WPG	WPG	WPG

Année	R1	R2	R3	R4	R5
4	WPG	WPG	WPG		WPG
5	WPG	WPG	WPG	WPG	WPG
6	WPG	WPG	WPG	WPG	WPG
7	WPG	WPG	WPG	WPG	WPG
8	WPG	WPG	WPG	WPG	WPG

Année	R1	R2	R3	R4	R5
4	WPG	WPG	WPG		WPG
5	WPG	WPG	WPG	WPG	WPG
6	WPG	WPG	WPG	WPG	WPG
7	WPG	WPG	WPG	WPG	WPG
8	WPG	WPG	WPG	WPG	WPG