OTHL - Eagles

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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	Mike Vecchione	X		X		100.00	73	68	84	63	68	78	83	60	75	58	58	63	55	44	44	62	50	61	0
2	Joseph Cramarossa		X	X		100.00	63	70	48	65	70	71	77	51	50	50	46	56	44	46	46	52	50	55	0
Rayé
1	Mike Sgarbossa (R)	X				100.00	67	68	66	65	68	82	87	66	80	62	66	61	63	44	44	66	50	63	0
2	Kurtis Gabriel (R)			X		100.00	99	99	35	65	80	48	65	58	25	59	59	68	25	46	46	63	50	60	0
3	Cameron Gaunce				X	100.00	76	78	71	67	78	76	80	63	25	57	52	68	49	56	56	62	50	65	0
4	Adam Clendening				X	100.00	63	71	43	67	71	62	63	61	25	63	42	61	40	55	55	55	50	60	0
5	Julian Melchiori				X	100.00	80	81	76	68	81	63	67	48	25	34	45	64	43	48	48	54	50	60	0
6	Kevin Czuczman				X	100.00	75	76	74	65	76	77	84	50	25	44	41	62	39	46	46	55	50	60	0
7	Keegan Lowe				X	100.00	73	73	72	65	73	70	76	50	25	45	39	60	37	45	45	53	50	59	0
8	Mark Alt				X	100.00	79	77	85	68	77	63	67	49	25	40	42	63	40	44	44	54	50	59	0

	MOYENNE D'ÉQUIPE					100.00	75	76	65	66	74	69	75	56	38	51	49	63	44	47	47	58	50	60

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
Rayé
1	Chris Driedger	100.00	63	58	73	84	66	65	57	66	63	62	30	44	44	62	50	62	0

	MOYENNE D'ÉQUIPE	100.00	63	58	73	84	66	65	57	66	63	62	30	44	44	62	50	62

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Darryl Sydor	50	68	59	66	45	46	56	CAN	42	3	600,000$

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	Status	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Link
Adam Clendening	Eagles (COL)	D	27	1992-10-26	No	196 Lbs	6 ft0	No	No	No	2	Avec Restriction	Pro & Farm	900,000$	0$	0$	No	Lien
Cameron Gaunce	Eagles (COL)	D	29	1990-03-19	No	204 Lbs	6 ft2	No	No	No	2	Sans Restriction	Pro & Farm	845,833$	0$	0$	No	Lien
Chris Driedger	Eagles (COL)	G	25	1994-05-18	No	205 Lbs	6 ft4	No	No	No	1	Avec Restriction	Pro & Farm	700,000$	0$	0$	No	Lien
Joseph Cramarossa	Eagles (COL)	LW/RW	27	1992-10-26	No	192 Lbs	6 ft0	No	No	No	2	Avec Restriction	Pro & Farm	952,000$	0$	0$	No	Lien
Julian Melchiori	Eagles (COL)	D	27	1991-12-06	No	214 Lbs	6 ft5	No	No	No	1	Avec Restriction	Pro & Farm	700,000$	0$	0$	No	Lien
Keegan Lowe	Eagles (COL)	D	26	1993-03-29	No	195 Lbs	6 ft2	No	No	No	1	Avec Restriction	Pro & Farm	750,000$	0$	0$	No	Lien
Kevin Czuczman	Eagles (COL)	D	28	1991-01-09	No	206 Lbs	6 ft2	No	No	No	1	Avec Restriction	Pro & Farm	700,000$	0$	0$	No	Lien
Kurtis Gabriel	Eagles (COL)	RW	26	1993-04-20	Yes	200 Lbs	6 ft4	No	No	No	3	Avec Restriction	Pro & Farm	750,000$	0$	0$	No	Lien
Mark Alt	Eagles (COL)	D	28	1991-10-17	No	201 Lbs	6 ft4	No	No	No	1	Avec Restriction	Pro & Farm	700,000$	0$	0$	No	Lien
Mike Sgarbossa	Eagles (COL)	C	27	1992-07-24	Yes	186 Lbs	6 ft0	No	No	No	1	Avec Restriction	Pro & Farm	650,000$	0$	0$	No	Lien
Mike Vecchione	Eagles (COL)	C/RW	26	1993-02-25	No	194 Lbs	5 ft10	No	No	No	1	Avec Restriction	Pro & Farm	1,000,000$	0$	0$	No	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
11	26.91	199 Lbs	6 ft2	1.45	786,167$

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	4	8	-4	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	4	8	-4	0	0.000	4	8	12	0	0	9	6	4	0	46	65	83	76	0	52	16	4	11	2	1	50.00%	2	2	0.00%	0	69	158	43.67%	84	234	35.90%	39	122	31.97%	115	79	228	51	76	30
2	Bruins	1	0	1	0	0	0	0	0	0	7	-7	1	0	1	0	0	0	0	0	0	7	-7	0	0	0	0	0	0	0	0	0	0	0	0	0.000	0	0	0	0	0	9	6	4	0	16	65	83	76	0	31	9	6	12	5	0	0.00%	3	0	100.00%	0	69	158	43.67%	84	234	35.90%	39	122	31.97%	115	79	228	51	76	30
3	Heat	1	0	1	0	0	0	0	0	0	16	-16	1	0	1	0	0	0	0	0	0	16	-16	0	0	0	0	0	0	0	0	0	0	0	0	0.000	0	0	0	0	0	9	6	4	0	15	65	83	76	0	76	23	2	17	0	0	0.00%	1	0	100.00%	0	69	158	43.67%	84	234	35.90%	39	122	31.97%	115	79	228	51	76	30
4	Penguins	1	0	1	0	0	0	0	0	2	6	-4	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	2	6	-4	0	0.000	2	3	5	0	0	9	6	4	0	21	65	83	76	0	53	9	2	13	4	0	0.00%	1	0	100.00%	0	69	158	43.67%	84	234	35.90%	39	122	31.97%	115	79	228	51	76	30
5	Roadrunners	1	1	0	0	0	0	0	0	4	2	2	1	1	0	0	0	0	0	0	4	2	2	0	0	0	0	0	0	0	0	0	0	0	2	1.000	4	8	12	0	0	9	6	4	0	42	65	83	76	0	39	12	5	21	1	1	100.00%	0	0	0.00%	0	69	158	43.67%	84	234	35.90%	39	122	31.97%	115	79	228	51	76	30
6	Thunderbirds	1	0	1	0	0	0	0	0	2	7	-5	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	2	7	-5	0	0.000	2	4	6	0	0	9	6	4	0	20	65	83	76	0	31	12	2	14	2	0	0.00%	1	0	100.00%	0	69	158	43.67%	84	234	35.90%	39	122	31.97%	115	79	228	51	76	30
	Total	7	2	5	0	0	0	0	0	19	50	-31	4	2	2	0	0	0	0	0	11	29	-18	3	0	3	0	0	0	0	0	8	21	-13	4	0.286	19	37	56	0	0	9	6	4	0	224	65	83	76	0	332	97	21	118	14	2	14.29%	8	2	75.00%	0	69	158	43.67%	84	234	35.90%	39	122	31.97%	115	79	228	51	76	30
8	Wild	1	1	0	0	0	0	0	0	7	4	3	1	1	0	0	0	0	0	0	7	4	3	0	0	0	0	0	0	0	0	0	0	0	2	1.000	7	14	21	0	0	9	6	4	0	64	65	83	76	0	50	16	0	30	0	0	0.00%	0	0	0.00%	0	69	158	43.67%	84	234	35.90%	39	122	31.97%	115	79	228	51	76	30
	_Since Last GM Reset	7	2	5	0	0	0	0	0	19	50	-31	4	2	2	0	0	0	0	0	11	29	-18	3	0	3	0	0	0	0	0	8	21	-13	4	0.286	19	37	56	0	0	9	6	4	0	224	65	83	76	0	332	97	21	118	14	2	14.29%	8	2	75.00%	0	69	158	43.67%	84	234	35.90%	39	122	31.97%	115	79	228	51	76	30
	_Vs Conference	3	2	1	0	0	0	0	0	11	22	-11	3	2	1	0	0	0	0	0	11	22	-11	0	0	0	0	0	0	0	0	0	0	0	4	0.667	11	22	33	0	0	9	6	4	0	121	65	83	76	0	165	51	7	68	1	1	100.00%	1	0	100.00%	0	69	158	43.67%	84	234	35.90%	39	122	31.97%	115	79	228	51	76	30

			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	4	L3	19	37	56	224	332	97	21	118	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
7	2	5	0	0	0	0	19	50

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	2	2	0	0	0	0	11	29

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	0	3	0	0	0	0	8	21

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
2	5	0	0	0	0

Tentatives en Avantage Numérique	Buts en Avantage Numérique	% en Avantage Numérique	Tentatives en Désavantage Numérique	Buts Contre en Désavantage Numérique	% en Désavantage Numérique	Buts Pour en Désavantage Numérique
14	2	14.29%	8	2	75.00%	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
65	83	76	0	9	6	4	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
69	158	43.67%	84	234	35.90%	39	122	31.97%

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
115	79	228	51	76	30

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	7	Heat	16	Eagles	0	L	Sommaire du Match
4 - 2019-10-07	22	Wild	4	Eagles	7	W	Sommaire du Match
9 - 2019-10-12	49	Bruins	7	Eagles	0	L	Sommaire du Match
11 - 2019-10-14	64	Roadrunners	2	Eagles	4	W	Sommaire du Match
13 - 2019-10-16	84	Eagles	4	Bears	8	L	Sommaire du Match
15 - 2019-10-18	95	Eagles	2	Penguins	6	L	Sommaire du Match
17 - 2019-10-20	110	Eagles	2	Thunderbirds	7	L	Sommaire du Match
18 - 2019-10-21	122	Eagles	-	Crunch	-
20 - 2019-10-23	131	Eagles	-	Rampage	-
24 - 2019-10-27	160	Eagles	-	Wolves	-
25 - 2019-10-28	163	Gulls	-	Eagles	-
29 - 2019-11-01	190	Thunderbirds	-	Eagles	-
31 - 2019-11-03	198	Stars	-	Eagles	-
32 - 2019-11-04	204	Eagles	-	Roadrunners	-
35 - 2019-11-07	227	Eagles	-	Stars	-
37 - 2019-11-09	241	Admirals	-	Eagles	-
39 - 2019-11-11	254	Monsters	-	Eagles	-
42 - 2019-11-14	280	Eagles	-	Moose	-
44 - 2019-11-16	288	Eagles	-	Condors	-
46 - 2019-11-18	313	Eagles	-	Comets	-
49 - 2019-11-21	320	Eagles	-	Heat	-
51 - 2019-11-23	341	Eagles	-	Wild	-
53 - 2019-11-25	350	Marlies	-	Eagles	-
57 - 2019-11-29	380	Condors	-	Eagles	-
59 - 2019-12-01	396	Eagles	-	IceHogs	-
60 - 2019-12-02	405	IceHogs	-	Eagles	-
64 - 2019-12-06	437	Eagles	-	Marlies	-
65 - 2019-12-07	443	Eagles	-	Rocket	-
67 - 2019-12-09	452	Eagles	-	Bruins	-
69 - 2019-12-11	468	Heat	-	Eagles	-
71 - 2019-12-13	484	Phantoms	-	Eagles	-
73 - 2019-12-15	499	Devils	-	Eagles	-
76 - 2019-12-18	523	Eagles	-	Rampage	-
78 - 2019-12-20	535	Eagles	-	IceHogs	-
79 - 2019-12-21	542	Checkers	-	Eagles	-
81 - 2019-12-23	556	IceHogs	-	Eagles	-
83 - 2019-12-25	580	Eagles	-	Wolves	-
87 - 2019-12-29	585	Wild	-	Eagles	-
88 - 2019-12-30	594	Eagles	-	Stars	-
91 - 2020-01-02	618	Moose	-	Eagles	-
93 - 2020-01-04	631	Rampage	-	Eagles	-
95 - 2020-01-06	648	Eagles	-	Devils	-
97 - 2020-01-08	661	Eagles	-	Sound Tigers	-
98 - 2020-01-09	670	Eagles	-	Wolf Pack	-
101 - 2020-01-12	690	Penguins	-	Eagles	-
105 - 2020-01-16	717	Stars	-	Eagles	-
107 - 2020-01-18	729	Barracudas	-	Eagles	-
109 - 2020-01-20	744	Rampage	-	Eagles	-
111 - 2020-01-22	759	Griffins	-	Eagles	-
123 - 2020-02-03	802	Eagles	-	Phantoms	-
126 - 2020-02-06	814	Eagles	-	Americans	-
128 - 2020-02-08	835	Eagles	-	Senators	-
130 - 2020-02-10	844	Eagles	-	Monsters	-
131 - 2020-02-11	857	Eagles	-	Wild	-
133 - 2020-02-13	868	Senators	-	Eagles	-
135 - 2020-02-15	882	Bears	-	Eagles	-
137 - 2020-02-17	898	Reign	-	Eagles	-
139 - 2020-02-19	917	Crunch	-	Eagles	-
141 - 2020-02-21	929	Sound Tigers	-	Eagles	-
143 - 2020-02-23	941	Eagles	-	Gulls	-
144 - 2020-02-24	949	Eagles	-	Reign	-
148 - 2020-02-28	981	Americans	-	Eagles	-
150 - 2020-03-01	995	Eagles	-	Checkers	-
151 - 2020-03-02	1004	Eagles	-	Admirals	-
153 - 2020-03-04	1017	Eagles	-	Griffins	-
155 - 2020-03-06	1030	Gulls	-	Eagles	-
157 - 2020-03-08	1047	Eagles	-	Comets	-
159 - 2020-03-10	1064	Eagles	-	Barracudas	-
160 - 2020-03-11	1068	Eagles	-	Reign	-
162 - 2020-03-13	1080	Wolf Pack	-	Eagles	-
164 - 2020-03-15	1095	Comets	-	Eagles	-
166 - 2020-03-17	1111	Wolves	-	Eagles	-
168 - 2020-03-19	1124	Barracudas	-	Eagles	-
170 - 2020-03-21	1143	Eagles	-	Admirals	-
172 - 2020-03-23	1156	Rocket	-	Eagles	-
174 - 2020-03-25	1172	Eagles	-	Wild	-
176 - 2020-03-27	1187	Eagles	-	Condors	-
178 - 2020-03-29	1204	Eagles	-	Moose	-
180 - 2020-03-31	1217	Admirals	-	Eagles	-
182 - 2020-04-02	1231	Roadrunners	-	Eagles	-
184 - 2020-04-04	1245	Moose	-	Eagles	-
186 - 2020-04-06	1261	Rampage	-	Eagles	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	50	0
Assistance	5,929	2,939
Assistance PCT	74.11%	73.48%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
37	2217 - 73.90%	74,113$	296,450$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
160,265$	864,783$	864,783$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
4,649$	105,423$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
2,742,162$	169	7,875$	1,330,875$

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	7	2	5	0	0	0	0	0	19	50	-31	4	2	2	0	0	0	0	0	11	29	-18	3	0	3	0	0	0	0	0	8	21	-13	4	19	37	56	0	0	9	6	4	0	224	65	83	76	0	332	97	21	118	14	2	14.29%	8	2	75.00%	0	69	158	43.67%	84	234	35.90%	39	122	31.97%	115	79	228	51	76	30
Total Saison Régulière	7	2	5	0	0	0	0	0	19	50	-31	4	2	2	0	0	0	0	0	11	29	-18	3	0	3	0	0	0	0	0	8	21	-13	4	19	37	56	0	0	9	6	4	0	224	65	83	76	0	332	97	21	118	14	2	14.29%	8	2	75.00%	0	69	158	43.67%	84	234	35.90%	39	122	31.97%	115	79	228	51	76	30