OTHL - Wolf Pack

Rangers
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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	Kevin Porter	X				100.00	73	69	81	72	69	75	78	65	80	64	57	69	54	65	65	65	50	65	0
2	Robby Fabbri	X	X			100.00	73	43	93	73	68	63	44	62	34	61	57	59	25	60	61	62	50	59	0
3	Kevin Roy		X	X		100.00	68	61	84	71	61	59	61	55	50	59	47	59	45	45	45	57	50	56	0
4	Ian McCoshen				X	100.00	87	46	87	77	80	62	66	53	25	45	48	66	25	53	53	59	50	63	0
5	Zach Trotman				X	100.00	80	45	90	71	80	67	63	63	25	48	47	66	25	55	55	59	50	63	0
6	Matt Taormina				X	100.00	72	66	86	65	66	60	64	48	25	41	39	59	37	44	44	51	50	56	0
Rayé

	MOYENNE D'ÉQUIPE					100.00	76	55	87	72	71	64	63	58	40	53	49	63	35	54	54	59	50	60

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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	Charlie Lindgren	100.00	52	72	90	75	46	53	51	58	48	49	30	45	45	53	50	55	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	52	72	90	75	46	53	51	58	48	49	30	45	45	53	50	55

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Pascal Vincent	62	46	71	73	53	43	58	CAN	44	4	900,000$

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3

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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
Charlie Lindgren	Wolf Pack (NYR)	G	25	1993-12-17	No	190 Lbs	6 ft2	No	No	No	2	Avec Restriction	Pro & Farm	1,000,000$	0$	0$	No	Lien
Ian McCoshen	Wolf Pack (NYR)	D	24	1995-08-05	No	217 Lbs	6 ft3	No	No	No	2	Avec Restriction	Pro & Farm	1,025,000$	0$	0$	No	Lien
Kevin Porter	Wolf Pack (NYR)	C	33	1986-03-12	No	191 Lbs	5 ft11	No	No	No	1	Sans Restriction	Pro & Farm	800,000$	0$	0$	No	Lien
Kevin Roy	Wolf Pack (NYR)	LW/RW	26	1993-05-20	No	174 Lbs	5 ft9	No	No	No	2	Avec Restriction	Pro & Farm	925,000$	0$	0$	No	Lien
Matt Taormina	Wolf Pack (NYR)	D	33	1986-10-20	No	188 Lbs	5 ft10	No	No	No	1	Sans Restriction	Pro & Farm	650,000$	0$	0$	No	Lien
Robby Fabbri	Wolf Pack (NYR)	C/LW	23	1996-01-22	No	190 Lbs	5 ft10	No	No	No	1	Avec Restriction	Pro & Farm	900,000$	0$	0$	No	Lien
Zach Trotman	Wolf Pack (NYR)	D	29	1990-08-26	No	217 Lbs	6 ft3	No	No	No	1	Sans Restriction	Pro & Farm	975,000$	0$	0$	No	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
7	27.57	195 Lbs	6 ft0	1.43	896,429$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1				40	1	2	2
2				30	1	2	2
3				20	1	2	2
4				10	1	2	2

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

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1				60	1	2	2
2				40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

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

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, ,	,

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, ,		,

Tirs de Pénalité
, , , ,

Gardien
#1 : , #2 :

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	Bears	1	0	1	0	0	0	0	0	3	6	-3	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	3	6	-3	0	0.000	3	6	9	0	0	8	4	6	0	60	79	47	64	0	56	20	0	22	0	0	0.00%	0	0	0.00%	0	48	111	43.24%	59	165	35.76%	36	89	40.45%	86	62	161	32	52	22
2	Condors	1	0	1	0	0	0	0	0	0	8	-8	1	0	1	0	0	0	0	0	0	8	-8	0	0	0	0	0	0	0	0	0	0	0	0	0.000	0	0	0	0	0	8	4	6	0	4	79	47	64	0	40	11	8	13	1	0	0.00%	3	1	66.67%	0	48	111	43.24%	59	165	35.76%	36	89	40.45%	86	62	161	32	52	22
3	Devils	1	1	0	0	0	0	0	0	7	3	4	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	7	3	4	2	1.000	7	14	21	0	0	8	4	6	0	53	79	47	64	0	41	9	2	28	1	0	0.00%	1	0	100.00%	0	48	111	43.24%	59	165	35.76%	36	89	40.45%	86	62	161	32	52	22
4	Moose	1	0	1	0	0	0	0	0	3	8	-5	1	0	1	0	0	0	0	0	3	8	-5	0	0	0	0	0	0	0	0	0	0	0	0	0.000	3	6	9	0	0	8	4	6	0	18	79	47	64	0	58	12	14	14	2	0	0.00%	7	3	57.14%	0	48	111	43.24%	59	165	35.76%	36	89	40.45%	86	62	161	32	52	22
5	Senators	1	1	0	0	0	0	0	0	5	4	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	5	4	1	2	1.000	5	10	15	0	0	8	4	6	0	55	79	47	64	0	45	12	0	18	2	0	0.00%	0	0	0.00%	0	48	111	43.24%	59	165	35.76%	36	89	40.45%	86	62	161	32	52	22
	Total	5	2	3	0	0	0	0	0	18	29	-11	2	0	2	0	0	0	0	0	3	16	-13	3	2	1	0	0	0	0	0	15	13	2	4	0.400	18	36	54	0	0	8	4	6	0	190	79	47	64	0	240	64	24	95	6	0	0.00%	11	4	63.64%	0	48	111	43.24%	59	165	35.76%	36	89	40.45%	86	62	161	32	52	22
	_Since Last GM Reset	5	2	3	0	0	0	0	0	18	29	-11	2	0	2	0	0	0	0	0	3	16	-13	3	2	1	0	0	0	0	0	15	13	2	4	0.400	18	36	54	0	0	8	4	6	0	190	79	47	64	0	240	64	24	95	6	0	0.00%	11	4	63.64%	0	48	111	43.24%	59	165	35.76%	36	89	40.45%	86	62	161	32	52	22
	_Vs Conference	3	2	1	0	0	0	0	0	15	13	2	0	0	0	0	0	0	0	0	0	0	0	3	2	1	0	0	0	0	0	15	13	2	4	0.667	15	30	45	0	0	8	4	6	0	168	79	47	64	0	142	41	2	68	3	0	0.00%	1	0	100.00%	0	48	111	43.24%	59	165	35.76%	36	89	40.45%	86	62	161	32	52	22
	_Vs Division	2	0	1	0	0	0	0	0	10	9	1	0	0	0	0	0	0	0	0	0	0	0	2	0	1	0	0	0	0	0	10	9	1	0	0.000	10	20	30	0	0	8	4	6	0	113	79	47	64	0	97	29	2	50	1	0	0.00%	1	0	100.00%	0	48	111	43.24%	59	165	35.76%	36	89	40.45%	86	62	161	32	52	22

			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
5	4	L1	18	36	54	190	240	64	24	95	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	2	3	0	0	0	0	18	29

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	0	2	0	0	0	0	3	16

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	2	1	0	0	0	0	15	13

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
2	3	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
6	0	0.00%	11	4	63.64%	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
79	47	64	0	8	4	6	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
48	111	43.24%	59	165	35.76%	36	89	40.45%

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
86	62	161	32	52	22

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	Lien
2 - 2019-10-05	10	Moose	8	Wolf Pack	3	L	Sommaire du Match
4 - 2019-10-07	26	Wolf Pack	5	Senators	4	W	Sommaire du Match
11 - 2019-10-14	71	Condors	8	Wolf Pack	0	L	Sommaire du Match
16 - 2019-10-19	103	Wolf Pack	7	Devils	3	W	Sommaire du Match
17 - 2019-10-20	112	Wolf Pack	3	Bears	6	L	Sommaire du Match
19 - 2019-10-22	127	Comets	-	Wolf Pack	-
21 - 2019-10-24	141	Roadrunners	-	Wolf Pack	-
23 - 2019-10-26	153	Americans	-	Wolf Pack	-
26 - 2019-10-29	174	Bruins	-	Wolf Pack	-
28 - 2019-10-31	185	Crunch	-	Wolf Pack	-
32 - 2019-11-04	213	Wolf Pack	-	Admirals	-
34 - 2019-11-06	223	Senators	-	Wolf Pack	-
36 - 2019-11-08	236	Griffins	-	Wolf Pack	-
37 - 2019-11-09	238	Wolf Pack	-	Checkers	-
40 - 2019-11-12	267	Thunderbirds	-	Wolf Pack	-
42 - 2019-11-14	276	Penguins	-	Wolf Pack	-
44 - 2019-11-16	292	Wolf Pack	-	Crunch	-
46 - 2019-11-18	303	Wolf Pack	-	Thunderbirds	-
50 - 2019-11-22	332	Bears	-	Wolf Pack	-
52 - 2019-11-24	346	Wolf Pack	-	Senators	-
53 - 2019-11-25	353	Wolf Pack	-	Rocket	-
55 - 2019-11-27	370	Wild	-	Wolf Pack	-
57 - 2019-11-29	384	Checkers	-	Wolf Pack	-
59 - 2019-12-01	392	Wolf Pack	-	Bruins	-
60 - 2019-12-02	411	Wolf Pack	-	Devils	-
62 - 2019-12-04	423	Wolves	-	Wolf Pack	-
65 - 2019-12-07	440	Wolf Pack	-	Monsters	-
66 - 2019-12-08	450	Rocket	-	Wolf Pack	-
68 - 2019-12-10	466	Wolf Pack	-	Wolves	-
70 - 2019-12-12	477	Wolf Pack	-	Reign	-
72 - 2019-12-14	495	Wolf Pack	-	Barracudas	-
74 - 2019-12-16	501	Wolf Pack	-	Gulls	-
76 - 2019-12-18	522	Admirals	-	Wolf Pack	-
80 - 2019-12-22	551	Marlies	-	Wolf Pack	-
82 - 2019-12-24	567	Gulls	-	Wolf Pack	-
83 - 2019-12-25	576	Wolf Pack	-	Phantoms	-
87 - 2019-12-29	589	Checkers	-	Wolf Pack	-
88 - 2019-12-30	599	Wolf Pack	-	Marlies	-
91 - 2020-01-02	620	Wolf Pack	-	Condors	-
93 - 2020-01-04	630	Wolf Pack	-	Heat	-
95 - 2020-01-06	651	Wolf Pack	-	Comets	-
98 - 2020-01-09	670	Eagles	-	Wolf Pack	-
100 - 2020-01-11	684	Devils	-	Wolf Pack	-
102 - 2020-01-13	700	Wolf Pack	-	Rampage	-
104 - 2020-01-15	710	Sound Tigers	-	Wolf Pack	-
107 - 2020-01-18	734	Wolf Pack	-	Sound Tigers	-
110 - 2020-01-21	757	Monsters	-	Wolf Pack	-
112 - 2020-01-23	764	Sound Tigers	-	Wolf Pack	-
122 - 2020-02-02	788	Griffins	-	Wolf Pack	-
123 - 2020-02-03	795	Wolf Pack	-	Griffins	-
125 - 2020-02-05	810	Stars	-	Wolf Pack	-
127 - 2020-02-07	826	Marlies	-	Wolf Pack	-
129 - 2020-02-09	841	Americans	-	Wolf Pack	-
131 - 2020-02-11	858	Reign	-	Wolf Pack	-
133 - 2020-02-13	876	Wolf Pack	-	Moose	-
135 - 2020-02-15	884	Wolf Pack	-	Wild	-
136 - 2020-02-16	892	Wolf Pack	-	Monsters	-
138 - 2020-02-18	910	Bruins	-	Wolf Pack	-
141 - 2020-02-21	928	Wolf Pack	-	IceHogs	-
143 - 2020-02-23	942	Wolf Pack	-	Checkers	-
144 - 2020-02-24	952	Barracudas	-	Wolf Pack	-
147 - 2020-02-27	976	Wolf Pack	-	Sound Tigers	-
149 - 2020-02-29	987	Wolf Pack	-	Rocket	-
150 - 2020-03-01	997	Wolf Pack	-	Phantoms	-
152 - 2020-03-03	1015	Phantoms	-	Wolf Pack	-
154 - 2020-03-05	1023	Rampage	-	Wolf Pack	-
156 - 2020-03-07	1038	Bears	-	Wolf Pack	-
158 - 2020-03-09	1055	Devils	-	Wolf Pack	-
161 - 2020-03-12	1071	Wolf Pack	-	Stars	-
162 - 2020-03-13	1080	Wolf Pack	-	Eagles	-
165 - 2020-03-16	1098	Wolf Pack	-	Roadrunners	-
167 - 2020-03-18	1121	Heat	-	Wolf Pack	-
169 - 2020-03-20	1134	Penguins	-	Wolf Pack	-
171 - 2020-03-22	1150	Wolf Pack	-	Penguins	-
173 - 2020-03-24	1164	Wolf Pack	-	Americans	-
175 - 2020-03-26	1180	Monsters	-	Wolf Pack	-
177 - 2020-03-28	1198	Wolf Pack	-	Bears	-
179 - 2020-03-30	1214	Wolf Pack	-	Crunch	-
181 - 2020-04-01	1227	Wolf Pack	-	Thunderbirds	-
183 - 2020-04-03	1241	Phantoms	-	Wolf Pack	-
184 - 2020-04-04	1250	Wolf Pack	-	Penguins	-
186 - 2020-04-06	1267	IceHogs	-	Wolf Pack	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	19	0
Assistance	2,915	1,607
Assistance PCT	72.88%	80.35%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
39	2261 - 75.37%	27,693$	55,385$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
139,604$	627,500$	627,500$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
3,374$	57,358$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
1,080,008$	169	8,212$	1,387,828$

Afficher ou Masquer des Colonnes

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	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
2019	5	2	3	0	0	0	0	0	18	29	-11	2	0	2	0	0	0	0	0	3	16	-13	3	2	1	0	0	0	0	0	15	13	2	4	18	36	54	0	0	8	4	6	0	190	79	47	64	0	240	64	24	95	6	0	0.00%	11	4	63.64%	0	48	111	43.24%	59	165	35.76%	36	89	40.45%	86	62	161	32	52	22
Total Saison Régulière	5	2	3	0	0	0	0	0	18	29	-11	2	0	2	0	0	0	0	0	3	16	-13	3	2	1	0	0	0	0	0	15	13	2	4	18	36	54	0	0	8	4	6	0	190	79	47	64	0	240	64	24	95	6	0	0.00%	11	4	63.64%	0	48	111	43.24%	59	165	35.76%	36	89	40.45%	86	62	161	32	52	22