OTHL - Penguins

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP	Âge	Contrat	Salaire
1	Tyson Jost	X	X			100.00	73	43	89	85	69	63	90	72	51	67	62	67	25	61	62	68	50	67	0	23	1	1,673,333$
2	Micheal Ferland		X	X		100.00	94	92	85	80	79	55	62	58	26	74	58	57	25	65	66	65	50	63	0	29	3	3,250,000$
3	Michael Rasmussen	X	X	X		100.00	84	85	83	68	85	66	67	62	78	61	58	70	55	51	51	64	50	63	0	22	2	1,710,833$
4	Steven Fogarty	X		X		100.00	79	77	83	62	77	81	86	63	79	62	60	67	57	45	45	65	50	63	0	28	1	750,000$
5	Anthony Greco		X	X		100.00	70	62	90	67	62	75	79	60	50	55	59	64	56	55	55	62	50	61	0	27	1	725,000$
6	Gabriel Gagne			X		100.00	78	73	90	64	73	61	62	61	50	56	61	67	58	50	50	64	50	60	0	24	3	750,000$
7	Alexandre Fortin		X	X		100.00	73	65	91	61	65	71	75	57	50	49	57	65	54	57	57	61	50	59	0	24	2	700,000$
8	Tomas Jurco		X	X		100.00	61	41	89	77	70	55	51	60	45	63	55	52	25	62	63	59	50	59	0	28	1	950,000$
9	Dante Fabbro (R)				X	100.00	71	42	83	86	68	77	70	63	25	48	49	70	25	51	51	61	50	65	0	23	3	1,491,000$
10	Aaron Ness				X	100.00	69	42	99	69	66	60	72	58	25	43	47	59	25	52	52	57	50	59	0	31	2	750,000$
Rayé

	MOYENNE D'ÉQUIPE					100.00	75	62	88	72	71	66	71	61	48	58	57	64	41	55	55	63	50	62

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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	Tom McCollum	100.00	56	52	65	85	56	55	61	64	58	59	30	44	44	58	50	59	0
Rayé
1	Matej Tomek (R)	100.00	55	55	55	55	55	55	55	55	55	55	55	55	55	55	50	55	1

	MOYENNE D'ÉQUIPE	100.00	56	54	60	70	56	55	58	60	57	57	43	50	50	57	50	57

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Jay Leach	60	75	77	52	50	47	60	USA	40	2	800,000$

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Astuces sur les Filtres (Anglais seulement)

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

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#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	P/20	FL	FT	S1	S2	S3
1	Alexandre Fortin	Penguins (PIT)	LW/RW	7	4	4	8	2	8	0	2	11	27	6	14	14.81%	6	148	21.25	1	1	2	6	16	0	0	0	1	27	0	0	25.00%	8	1.08	0	0	0	1	0
2	Steven Fogarty	Penguins (PIT)	C/RW	7	2	5	7	3	13	5	9	21	17	6	17	11.76%	3	117	16.72	0	0	0	0	0	0	1	1	0	15	1	0	71.07%	121	1.20	1	0	0	1	1
3	Tyson Jost	Penguins (PIT)	C/LW	7	2	4	6	1	0	0	3	14	23	3	9	8.70%	5	139	19.91	0	0	0	6	20	0	1	1	0	17	1	1	58.23%	158	0.86	0	0	1	0	1
4	Anthony Greco	Penguins (PIT)	LW/RW	7	2	4	6	2	0	0	4	15	24	7	15	8.33%	3	128	18.40	0	0	0	6	18	0	0	0	0	0	0	0	28.57%	7	0.93	0	0	1	0	0
5	Gabriel Gagne	Penguins (PIT)	RW	7	3	3	6	-3	13	5	16	18	15	5	17	20.00%	7	117	16.83	1	1	2	1	14	0	0	0	0	0	1	0	42.86%	7	1.02	0	1	0	1	0
6	Michael Rasmussen	Penguins (PIT)	C/LW/RW	7	2	3	5	2	4	0	6	13	15	5	13	13.33%	9	140	20.06	0	1	1	2	16	0	0	0	1	31	0	0	72.86%	70	0.71	0	0	1	1	0
7	Micheal Ferland	Penguins (PIT)	LW/RW	7	1	2	3	1	10	0	9	8	9	2	6	11.11%	0	95	13.66	0	0	0	0	0	0	0	0	0	0	0	0	22.22%	9	0.63	0	0	0	0	1
8	Tomas Jurco	Penguins (PIT)	LW/RW	7	2	1	3	-3	0	0	3	14	18	6	8	11.11%	4	123	17.62	0	0	0	3	17	0	0	0	0	0	0	0	71.43%	7	0.49	0	0	1	0	0
9	Aaron Ness	Penguins (PIT)	D	7	1	1	2	-1	2	0	10	3	3	3	6	33.33%	6	126	18.07	0	1	1	1	14	1	0	1	1	10	0	0	0.00%	0	0.32	0	0	0	0	0
10	Dante Fabbro	Penguins (PIT)	D	7	0	1	1	-2	10	0	13	6	12	3	5	0.00%	6	137	19.67	0	0	0	7	14	0	0	0	0	21	0	0	0.00%	0	0.15	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				70	19	28	47	2	60	10	75	123	163	46	110	11.66%	49	1275	18.22	2	4	6	32	131	1	2	3	3	124	3	1	62.79%	387	0.74	1	1	4	4	3

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Astuces sur les Filtres (Anglais seulement)

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

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#	Nom du 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	Tom McCollum	Penguins (PIT)	7	3	3	1	0.884	2.96	406	0	0	20	172	0	0	0	0.000	0	7	0	0	0	0
Stats d'équipe Total ou en Moyenne			7	3	3	1	0.884	2.96	406	0	0	20	172	0	0	0	0.000	0	7	0	0	0	0

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Astuces sur les Filtres (Anglais seulement)

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

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Link
Aaron Ness	Penguins (PIT)	D	31	1990-05-18	No	184 Lbs	5 ft11	No	No	No	2	Pro & Farm	750,000$	0$	0$	No	750,000$		Lien / Lien NHL
Alexandre Fortin	Penguins (PIT)	LW/RW	24	1997-02-25	No	175 Lbs	6 ft0	No	No	No	2	Pro & Farm	700,000$	0$	0$	No	700,000$		Lien / Lien NHL
Anthony Greco	Penguins (PIT)	LW/RW	27	1993-09-30	No	172 Lbs	5 ft10	No	No	No	1	Pro & Farm	725,000$	0$	0$	No			Lien / Lien NHL
Dante Fabbro	Penguins (PIT)	D	23	1998-06-20	Yes	189 Lbs	6 ft0	No	No	No	3	Pro & Farm	1,491,000$	0$	0$	No	1,491,000$	1,491,000$	Lien / Lien NHL
Gabriel Gagne	Penguins (PIT)	RW	24	1996-11-11	No	186 Lbs	6 ft5	No	No	No	3	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$	Lien / Lien NHL
Matej Tomek	Penguins (PIT)	G	26	1995-02-10 11:42:25 AM	Yes	181 Lbs	6 ft3	No	No	No	2	Pro & Farm	700,000$	0$	0$	No	700,000$
Michael Rasmussen	Penguins (PIT)	C/LW/RW	22	1999-04-17	No	220 Lbs	6 ft6	No	No	No	2	Pro & Farm	1,710,833$	0$	0$	No	1,710,833$		Lien / Lien NHL
Micheal Ferland	Penguins (PIT)	LW/RW	29	1992-04-19	No	208 Lbs	6 ft2	No	No	No	3	Pro & Farm	3,250,000$	0$	0$	No	3,250,000$	3,250,000$	Lien / Lien NHL
Steven Fogarty	Penguins (PIT)	C/RW	28	1993-04-18	No	206 Lbs	6 ft3	No	No	No	1	Pro & Farm	750,000$	0$	0$	No			Lien / Lien NHL
Tom McCollum	Penguins (PIT)	G	31	1989-12-06	No	226 Lbs	6 ft2	No	No	No	1	Pro & Farm	700,000$	0$	0$	No			Lien / Lien NHL
Tomas Jurco	Penguins (PIT)	LW/RW	28	1992-12-27	No	188 Lbs	6 ft2	No	No	No	1	Pro & Farm	950,000$	0$	0$	No			Lien / Lien NHL
Tyson Jost	Penguins (PIT)	C/LW	23	1998-03-14	No	191 Lbs	5 ft11	No	No	No	1	Pro & Farm	1,673,333$	0$	0$	No			Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
12	26.33	194 Lbs	6 ft2	1.83	1,179,181$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Michael Rasmussen	Tyson Jost	Micheal Ferland	40	1	1	3
2	Anthony Greco	Steven Fogarty	Alexandre Fortin	30	0	2	3
3	Tomas Jurco		Gabriel Gagne	20	1	2	2
4	Anthony Greco	Tyson Jost	Tomas Jurco	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Aaron Ness	Dante Fabbro	40	1	2	2
2			30	1	2	2
3			20	1	2	2
4	Aaron Ness	Dante Fabbro	10	1	1	3

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Anthony Greco	Tyson Jost	Tomas Jurco	60	0	1	4
2	Alexandre Fortin	Michael Rasmussen	Gabriel Gagne	40	1	1	3

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dante Fabbro	Aaron Ness	60	0	1	3
2			40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Michael Rasmussen	Alexandre Fortin	60	1	2	2
2	Steven Fogarty	Tyson Jost	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dante Fabbro	Aaron Ness	60	1	2	2
2			40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Michael Rasmussen	60	1	2	2	Aaron Ness	Dante Fabbro	60	1	2	2
2	Gabriel Gagne	40	1	2	2			40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Tyson Jost	Alexandre Fortin	60	1	2	2
2	Michael Rasmussen	Gabriel Gagne	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dante Fabbro	Aaron Ness	60	1	2	2
2			40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Tyson Jost	Michael Rasmussen	Gabriel Gagne	Aaron Ness	Dante Fabbro

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Tyson Jost	Michael Rasmussen	Gabriel Gagne	Aaron Ness	Dante Fabbro

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, ,	,

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, ,		,

Tirs de Pénalité
, , , ,

Gardien
#1 : Tom McCollum, #2 :

Lignes d'Attaque Perso. en Prol.
Tyson Jost, Michael Rasmussen, Micheal Ferland, Steven Fogarty, Anthony Greco, Tomas Jurco, Tomas Jurco, Alexandre Fortin, Gabriel Gagne, ,

Lignes de Défense Perso. en Prol.
Dante Fabbro, Aaron Ness, , ,

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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

	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	Monsters	7	3	4	0	0	0	0	0	19	21	-2	3	0	3	0	0	0	0	0	5	12	-7	4	3	1	0	0	0	0	0	14	9	5	6	0.429	19	31	50	0	0	8	5	5	1	164	56	51	53	4	181	59	86	99	23	2	8.70%	36	5	86.11%	1	108	213	50.70%	99	188	52.66%	53	98	54.08%	166	121	180	46	81	39
	Total	7	3	4	0	0	0	0	0	19	21	-2	3	0	3	0	0	0	0	0	5	12	-7	4	3	1	0	0	0	0	0	14	9	5	6	0.429	19	31	50	0	0	8	5	5	1	164	56	51	53	4	181	59	86	99	23	2	8.70%	36	5	86.11%	1	108	213	50.70%	99	188	52.66%	53	98	54.08%	166	121	180	46	81	39
	_Since Last GM Reset	7	3	4	0	0	0	0	0	19	21	-2	3	0	3	0	0	0	0	0	5	12	-7	4	3	1	0	0	0	0	0	14	9	5	6	0.429	19	31	50	0	0	8	5	5	1	164	56	51	53	4	181	59	86	99	23	2	8.70%	36	5	86.11%	1	108	213	50.70%	99	188	52.66%	53	98	54.08%	166	121	180	46	81	39
	_Vs Conference	7	3	4	0	0	0	0	0	19	21	-2	3	0	3	0	0	0	0	0	5	12	-7	4	3	1	0	0	0	0	0	14	9	5	6	0.429	19	31	50	0	0	8	5	5	1	164	56	51	53	4	181	59	86	99	23	2	8.70%	36	5	86.11%	1	108	213	50.70%	99	188	52.66%	53	98	54.08%	166	121	180	46	81	39
	_Vs Division	7	0	0	0	0	0	0	0	19	21	-2	3	0	0	0	0	0	0	0	5	12	-7	4	0	0	0	0	0	0	0	14	9	5	0	0.000	19	31	50	0	0	8	5	5	1	164	56	51	53	4	181	59	86	99	23	2	8.70%	36	5	86.11%	1	108	213	50.70%	99	188	52.66%	53	98	54.08%	166	121	180	46	81	39

			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
7	6	OTL1	19	31	50	164	181	59	86	99	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
7	3	4	0	0	0	0	19	21

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	0	3	0	0	0	0	5	12

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	3	1	0	0	0	0	14	9

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
2	3	1	1	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
23	2	8.70%	36	5	86.11%	1

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
56	51	53	4	8	5	5	1

Mises en Jeu
Gagnées en Zone Offensive	Total en Zone Offensive	% Gagnées en Zone Offensive	Gagnées en Zone Défensive	Total en Zone Défensive	% Gagnées en Zone Défensive	Gagnées en Zone Neutre	Total en Zone Neutre	% Gagnées en Zone Neutre
108	213	50.70%	99	188	52.66%	53	98	54.08%

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
166	121	180	46	81	39

Derniers Match Joués Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

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

Jour	Match	Équipe Visiteuse	Score	Équipe Locale	Score	ST	OT	Lien
1 - 2020-10-24	3	Penguins	4	Monsters	3	W	X	Sommaire du Match
3 - 2020-10-26	11	Penguins	5	Monsters	1	W		Sommaire du Match
5 - 2020-10-28	19	Monsters	3	Penguins	2	L		Sommaire du Match
7 - 2020-10-30	27	Monsters	6	Penguins	2	L		Sommaire du Match
9 - 2020-11-01	35	Penguins	3	Monsters	2	W		Sommaire du Match
11 - 2020-11-03	43	Monsters	3	Penguins	1	L		Sommaire du Match
13 - 2020-11-05	51	Penguins	2	Monsters	3	L	X	Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité	2000	1000
Prix des Billets	85	0
Assistance	3,993	2,991
Assistance PCT	66.55%	99.70%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité	Popularité de l'Équipe
38	2328 - 77.60%	113,135$	339,405$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
0$	1,415,016$	1,358,416$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	0$	0	0

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

Afficher ou Masquer des Colonnes

	Ligue											Domicile											Visiteur
Année	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
Saison Régulière
2020	82	47	28	0	2	1	0	4	373	235	138	41	24	14	0	0	1	0	2	181	112	69	41	23	14	0	2	0	0	2	192	123	69	103	373	586	959	0	3	164	108	99	4	2578	860	811	897	24	2056	560	648	1482	350	56	16.00%	262	45	82.82%	3	1188	2191	54.22%	1022	2168	47.14%	724	1306	55.44%	2167	1673	1912	498	867	436
Total Saison Régulière	82	47	28	0	2	1	0	4	373	235	138	41	24	14	0	0	1	0	2	181	112	69	41	23	14	0	2	0	0	2	192	123	69	103	373	586	959	0	3	164	108	99	4	2578	860	811	897	24	2056	560	648	1482	350	56	16.00%	262	45	82.82%	3	1188	2191	54.22%	1022	2168	47.14%	724	1306	55.44%	2167	1673	1912	498	867	436
2020	7	3	4	0	0	0	0	0	19	21	-2	3	0	3	0	0	0	0	0	5	12	-7	4	3	1	0	0	0	0	0	14	9	5	6	19	31	50	0	0	8	5	5	1	164	56	51	53	4	181	59	86	99	23	2	8.70%	36	5	86.11%	1	108	213	50.70%	99	188	52.66%	53	98	54.08%	166	121	180	46	81	39
Total Séries	7	3	4	0	0	0	0	0	19	21	-2	3	0	3	0	0	0	0	0	5	12	-7	4	3	1	0	0	0	0	0	14	9	5	6	19	31	50	0	0	8	5	5	1	164	56	51	53	4	181	59	86	99	23	2	8.70%	36	5	86.11%	1	108	213	50.70%	99	188	52.66%	53	98	54.08%	166	121	180	46	81	39

	Penguins
	GP: 7 \| W: 3 \| L: 4 GF: 19 \| GA: 21 \| PP%: 8.70% \| PK%: 86.11% DG: Nick \| Morale : 50 \| Moyenne d'Équipe : 61