Stanley Cup Winners Hockey League

ANAHEIM Ducks
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Stats d'équipe en Carrière
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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	Riley Sheahan	0	X				100.00	61	43	89	63	86	73	88	64	82	61	63	80	62	77	67	65	99	71	0	28	3	1,500,000$
2	Warren Foegele	0		X			100.00	79	41	83	67	80	73	87	65	56	63	66	71	64	67	65	63	99	71	0	24	1	2,100,000$
3	Tyler Motte	0		X			100.00	93	39	89	66	69	73	79	62	56	61	63	79	64	69	65	56	99	70	0	25	2	800,000$
4	Julien Gauthier	0			X		100.00	69	49	87	65	92	78	80	64	56	61	63	62	64	65	63	81	99	69	0	22	3	850,000$
5	Christian Fischer	0			X		100.00	86	45	84	62	83	77	82	61	53	56	63	58	62	65	64	77	99	68	0	23	4	900,000$
6	Evgeny Svechnikov	0		X	X		100.00	65	49	84	60	85	74	72	57	52	58	59	60	59	67	64	81	99	65	0	23	3	850,000$
7	Chris Bigras	0				X	100.00	61	48	86	60	76	82	81	58	30	59	53	56	46	69	65	74	99	65	0	25	3	750,000$
8	Ville Pokka	0				X	100.00	62	42	72	50	73	55	86	58	30	47	37	60	54	50	50	75	99	56	0	26	4	1,000,000$
Rayé

	MOYENNE D'ÉQUIPE					100.00	72	45	84	62	81	73	82	61	52	58	58	66	59	66	63	72	99	67

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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
Rayé

	MOYENNE D'ÉQUIPE	0.00	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Dave Cameron	67	67	67	67	80	80	48	CAN	62	3	400,000$

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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	PPM	PKS	PKM	FO%	FOT	GA	TA	HT	P/20	S1
1	Evgeny Svechnikov	SAN DIEGO Gulls (ANH)	LW/RW	2	4	1	5	1	0	2	2	11	4	11	36.36%	9	46	23.42	2	2	2	32.00%	25	3	0	1	2.14	0
2	Julien Gauthier	SAN DIEGO Gulls (ANH)	RW	2	2	1	3	-5	0	3	3	12	4	8	16.67%	5	52	26.13	1	0	3	0.00%	0	0	0	0	1.15	1
3	Chris Bigras	SAN DIEGO Gulls (ANH)	D	2	0	1	1	-3	0	4	1	3	2	2	0.00%	4	39	19.77	1	0	2	0.00%	0	2	0	0	0.51	0
4	Ville Pokka	SAN DIEGO Gulls (ANH)	D	2	0	1	1	-3	4	5	4	1	0	0	0.00%	7	38	19.43	1	0	1	0.00%	0	0	1	0	0.51	0
Stats d'équipe Total ou en Moyenne				8	6	4	10	-10	4	14	10	27	10	21	22.22%	25	177	22.19	7	2	8	32.00%	25	5	1	1	1.13	1

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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
Stats d'équipe Total ou en Moyenne							0.000	0.00	0								0.000

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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	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Type	Salaire Actuel	Salaire Restant	Salaire Moyen	Salaire Moyen Restant	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Salaire Année 4	Link
Chris Bigras	SAN DIEGO Gulls (ANH)	D	25	2/22/1995	No	87 Kg	185 CM	No	No	No	3	Pro & Farm	750,000$	737,288$	750,000$	737,288$	0$	0$	No	750,000$	750,000$		Lien
Christian Fischer	SAN DIEGO Gulls (ANH)	RW	23	4/15/1997	No	97 Kg	188 CM	No	No	No	4	Pro & Farm	900,000$	884,746$	750,000$	737,288$	0$	0$	No	900,000$	900,000$	900,000$	Lien
Evgeny Svechnikov	SAN DIEGO Gulls (ANH)	LW/RW	23	10/31/1996	No	95 Kg	191 CM	No	No	No	3	Pro & Farm	850,000$	835,593$	850,000$	835,593$	0$	0$	No	850,000$	850,000$		Lien
Julien Gauthier	SAN DIEGO Gulls (ANH)	RW	22	10/15/1997	No	103 Kg	193 CM	No	No	No	3	Pro & Farm	850,000$	835,593$	850,000$	835,593$	0$	0$	No	850,000$	850,000$		Lien
Riley Sheahan	SAN DIEGO Gulls (ANH)	C	28	12/7/1991	No	97 Kg	191 CM	No	No	No	3	Pro & Farm	1,500,000$	1,474,576$	1,500,000$	1,474,576$	0$	0$	No	1,500,000$	1,500,000$		Lien
Tyler Motte	SAN DIEGO Gulls (ANH)	LW	25	3/10/1995	No	87 Kg	178 CM	No	No	No	2	Pro & Farm	800,000$	786,441$	800,000$	786,441$	0$	0$	No	800,000$			Lien
Ville Pokka	SAN DIEGO Gulls (ANH)	D	26	3/6/1994	No	94 Kg	183 CM	No	No	No	4	Pro & Farm	1,000,000$	983,051$	1,000,000$	983,051$	0$	0$	No	1,000,000$	1,000,000$	1,000,000$	Lien
Warren Foegele	SAN DIEGO Gulls (ANH)	LW	24	4/1/1996	No	90 Kg	188 CM	No	No	No	1	Pro & Farm	2,100,000$	2,064,407$	750,000$	737,288$	0$	0$	No				Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
8	24.50	94 Kg	188 CM	2.88	1,093,750$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1			Julien Gauthier	31	1	2	2
2	Evgeny Svechnikov			26	1	2	2
3	Julien Gauthier			23	1	2	2
4		Evgeny Svechnikov		20	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Chris Bigras	Ville Pokka	31	1	2	2
2			26	1	2	2
3	Chris Bigras	Ville Pokka	23	1	2	2
4			20	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1			Julien Gauthier	55	1	2	2
2	Evgeny Svechnikov			45	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Chris Bigras	Ville Pokka	55	1	2	2
2			45	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1		Julien Gauthier	55	1	2	2
2		Evgeny Svechnikov	45	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Chris Bigras	Ville Pokka	55	1	2	2
2			45	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1		55	1	2	2	Chris Bigras	Ville Pokka	55	1	2	2
2	Julien Gauthier	45	1	2	2			45	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1		Julien Gauthier	55	1	2	2
2		Evgeny Svechnikov	45	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Chris Bigras	Ville Pokka	55	1	2	2
2			45	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
		Julien Gauthier	Chris Bigras	Ville Pokka

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
		Julien Gauthier	Chris Bigras	Ville Pokka

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, Evgeny Svechnikov,	, Evgeny Svechnikov

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Chris Bigras, Ville Pokka,	Chris Bigras	Ville Pokka,

Tirs de Pénalité
, Julien Gauthier, , Evgeny Svechnikov,

Gardien
#1 : , #2 :

Lignes d'Attaque Perso. en Prol.
, Julien Gauthier, , Evgeny Svechnikov, , , , , , ,

Lignes de Défense Perso. en Prol.
Chris Bigras, Ville Pokka, , ,

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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	ROCKFORD IceHogs	1	0	1	0	0	0	0	0	4	13	-9	1	0	1	0	0	0	0	0	4	13	-9	0	0	0	0	0	0	0	0	0	0	0	0	0.000	4	6	10	0	0	4	2	2	0	33	28	19	7	0	63	17	8	15	2	0	0.00%	4	3	25.00%	0	8	25	32.00%	7	41	17.07%	8	51	15.69%	25	14	65	16	28	11
2	SAN ANTONIO Rampage	1	0	1	0	0	0	0	0	4	6	-2	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	4	6	-2	0	0.000	4	8	12	0	0	4	2	2	0	21	28	19	7	0	58	20	2	9	0	0	0.00%	1	0	100.00%	0	8	25	32.00%	7	41	17.07%	8	51	15.69%	25	14	65	16	28	11
	Total	2	0	2	0	0	0	0	0	8	19	-11	1	0	1	0	0	0	0	0	4	13	-9	1	0	1	0	0	0	0	0	4	6	-2	0	0.000	8	14	22	0	0	4	2	2	0	54	28	19	7	0	121	37	10	24	2	0	0.00%	5	3	40.00%	0	8	25	32.00%	7	41	17.07%	8	51	15.69%	25	14	65	16	28	11
	_Since Last GM Reset	2	0	2	0	0	0	0	0	8	19	-11	1	0	1	0	0	0	0	0	4	13	-9	1	0	1	0	0	0	0	0	4	6	-2	0	0.000	8	14	22	0	0	4	2	2	0	54	28	19	7	0	121	37	10	24	2	0	0.00%	5	3	40.00%	0	8	25	32.00%	7	41	17.07%	8	51	15.69%	25	14	65	16	28	11
	_Vs Conference	2	0	2	0	0	0	0	0	8	19	-11	1	0	1	0	0	0	0	0	4	13	-9	1	0	1	0	0	0	0	0	4	6	-2	0	0.000	8	14	22	0	0	4	2	2	0	54	28	19	7	0	121	37	10	24	2	0	0.00%	5	3	40.00%	0	8	25	32.00%	7	41	17.07%	8	51	15.69%	25	14	65	16	28	11
	_Vs Division	2	0	2	0	0	0	0	0	8	19	-11	1	0	1	0	0	0	0	0	4	13	-9	1	0	1	0	0	0	0	0	4	6	-2	0	0.000	8	14	22	0	0	4	2	2	0	54	28	19	7	0	121	37	10	24	2	0	0.00%	5	3	40.00%	0	8	25	32.00%	7	41	17.07%	8	51	15.69%	25	14	65	16	28	11

			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
2	0	L2	8	14	22	54	121	37	10	24	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	0	2	0	0	0	0	8	19

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
1	0	1	0	0	0	0	4	13

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
1	0	1	0	0	0	0	4	6

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
0	2	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
2	0	0.00%	5	3	40.00%	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
28	19	7	0	4	2	2	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
8	25	32.00%	7	41	17.07%	8	51	15.69%

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
25	14	65	16	28	11

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
1 - 2021-01-17	5	ROCKFORD IceHogs	13	SAN DIEGO Gulls	4	L	Sommaire du Match
2 - 2021-01-18	20	SAN DIEGO Gulls	4	SAN ANTONIO Rampage	6	L	Sommaire du Match
4 - 2021-01-20	32	SAN DIEGO Gulls	-	LAVAL Rocket	-
5 - 2021-01-21	42	BRIDGEPORT Sound Tigers	-	SAN DIEGO Gulls	-
6 - 2021-01-22	56	SAN DIEGO Gulls	-	PROVIDENCE Bruins	-
7 - 2021-01-23	68	CHICAGO Wolves	-	SAN DIEGO Gulls	-
9 - 2021-01-25	85	BRIDGEPORT Sound Tigers	-	SAN DIEGO Gulls	-
12 - 2021-01-28	104	BAKERSFIELD Condors	-	SAN DIEGO Gulls	-
13 - 2021-01-29	112	SAN DIEGO Gulls	-	TUSCON Roadrunners	-
15 - 2021-01-31	130	SAN DIEGO Gulls	-	UTICA Comets	-
16 - 2021-02-01	140	SAN DIEGO Gulls	-	BINGHAMTON Devils	-
18 - 2021-02-03	151	COLORADO Eagles	-	SAN DIEGO Gulls	-
19 - 2021-02-04	159	SAN DIEGO Gulls	-	MILWAUKEE Admirals	-
20 - 2021-02-05	173	SAN DIEGO Gulls	-	LAVAL Rocket	-
21 - 2021-02-06	182	SAN ANTONIO Rampage	-	SAN DIEGO Gulls	-
23 - 2021-02-08	199	BROOKLYN Wolfpack	-	SAN DIEGO Gulls	-
25 - 2021-02-10	217	SAN DIEGO Gulls	-	PROVIDENCE Bruins	-
26 - 2021-02-11	226	LEHIGH VALLEY Phantoms	-	SAN DIEGO Gulls	-
28 - 2021-02-13	241	BELLEVILLE Senators	-	SAN DIEGO Gulls	-
29 - 2021-02-14	255	SAN DIEGO Gulls	-	SCRANTON Penguins	-
30 - 2021-02-15	266	SAN DIEGO Gulls	-	HERSEY Bears	-
31 - 2021-02-16	278	SCRANTON Penguins	-	SAN DIEGO Gulls	-
33 - 2021-02-18	294	SAN DIEGO Gulls	-	ONTARIO Reign	-
34 - 2021-02-19	308	SAN DIEGO Gulls	-	CHICAGO Wolves	-
36 - 2021-02-21	317	GRAND RAPIDS Griffins	-	SAN DIEGO Gulls	-
37 - 2021-02-22	333	BINGHAMTON Devils	-	SAN DIEGO Gulls	-
39 - 2021-02-24	344	HERSEY Bears	-	SAN DIEGO Gulls	-
41 - 2021-02-26	362	SAN DIEGO Gulls	-	CAROLINA Checkers	-
42 - 2021-02-27	373	BAKERSFIELD Condors	-	SAN DIEGO Gulls	-
43 - 2021-02-28	387	HERSEY Bears	-	SAN DIEGO Gulls	-
45 - 2021-03-02	400	SAN DIEGO Gulls	-	BELLEVILLE Senators	-
47 - 2021-03-04	414	SAN DIEGO Gulls	-	BROOKLYN Wolfpack	-
48 - 2021-03-05	424	SAN DIEGO Gulls	-	MANITOBA Moose	-
49 - 2021-03-06	437	ONTARIO Reign	-	SAN DIEGO Gulls	-
51 - 2021-03-08	451	ONTARIO Reign	-	SAN DIEGO Gulls	-
52 - 2021-03-09	466	SAN DIEGO Gulls	-	LAVAL Rocket	-
53 - 2021-03-10	478	BAKERSFIELD Condors	-	SAN DIEGO Gulls	-
55 - 2021-03-12	491	SAN DIEGO Gulls	-	STOCKTON Flames	-
56 - 2021-03-13	500	SAN DIEGO Gulls	-	BELLEVILLE Senators	-
57 - 2021-03-14	513	UTICA Comets	-	SAN DIEGO Gulls	-
58 - 2021-03-15	527	SAN DIEGO Gulls	-	UTICA Comets	-
60 - 2021-03-17	539	MILWAUKEE Admirals	-	SAN DIEGO Gulls	-
61 - 2021-03-18	553	SAN DIEGO Gulls	-	BINGHAMTON Devils	-
63 - 2021-03-20	567	MILWAUKEE Admirals	-	SAN DIEGO Gulls	-
64 - 2021-03-21	580	SAN DIEGO Gulls	-	BAKERSFIELD Condors	-
66 - 2021-03-23	593	MANITOBA Moose	-	SAN DIEGO Gulls	-
67 - 2021-03-24	604	SAN DIEGO Gulls	-	SAN ANTONIO Rampage	-
68 - 2021-03-25	617	PROVIDENCE Bruins	-	SAN DIEGO Gulls	-
70 - 2021-03-27	633	CAROLINA Checkers	-	SAN DIEGO Gulls	-
72 - 2021-03-29	646	SAN DIEGO Gulls	-	LEHIGH VALLEY Phantoms	-
73 - 2021-03-30	659	TORONTO Marlies	-	SAN DIEGO Gulls	-
75 - 2021-04-01	673	SAN DIEGO Gulls	-	TORONTO Marlies	-
76 - 2021-04-02	685	STOCKTON Flames	-	SAN DIEGO Gulls	-
78 - 2021-04-04	704	TORONTO Marlies	-	SAN DIEGO Gulls	-
79 - 2021-04-05	714	SAN DIEGO Gulls	-	COLORADO Eagles	-
81 - 2021-04-07	725	SAN DIEGO Gulls	-	IOWA Wild	-
82 - 2021-04-08	739	COLORADO Eagles	-	SAN DIEGO Gulls	-
84 - 2021-04-10	757	BROOKLYN Wolfpack	-	SAN DIEGO Gulls	-
85 - 2021-04-11	765	SAN DIEGO Gulls	-	TORONTO Marlies	-
87 - 2021-04-13	777	SAN DIEGO Gulls	-	TUSCON Roadrunners	-
88 - 2021-04-14	790	IOWA Wild	-	SAN DIEGO Gulls	-
89 - 2021-04-15	803	SAN DIEGO Gulls	-	BRIDGEPORT Sound Tigers	-
91 - 2021-04-17	814	TUSCON Roadrunners	-	SAN DIEGO Gulls	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
93 - 2021-04-19	829	SAN DIEGO Gulls	-	SAN ANTONIO Rampage	-
94 - 2021-04-20	839	SAN DIEGO Gulls	-	GRAND RAPIDS Griffins	-
95 - 2021-04-21	851	SAN ANTONIO Rampage	-	SAN DIEGO Gulls	-
96 - 2021-04-22	863	SAN DIEGO Gulls	-	MILWAUKEE Admirals	-
98 - 2021-04-24	877	SYRACUSE Crunch	-	SAN DIEGO Gulls	-
99 - 2021-04-25	893	BRIDGEPORT Sound Tigers	-	SAN DIEGO Gulls	-
101 - 2021-04-27	907	SAN DIEGO Gulls	-	SYRACUSE Crunch	-
102 - 2021-04-28	919	COLORADO Eagles	-	SAN DIEGO Gulls	-
104 - 2021-04-30	931	SAN DIEGO Gulls	-	COLORADO Eagles	-
105 - 2021-05-01	941	SAN DIEGO Gulls	-	MILWAUKEE Admirals	-
106 - 2021-05-02	952	SAN DIEGO Gulls	-	BRIDGEPORT Sound Tigers	-
107 - 2021-05-03	962	LAVAL Rocket	-	SAN DIEGO Gulls	-
109 - 2021-05-05	975	LAVAL Rocket	-	SAN DIEGO Gulls	-
111 - 2021-05-07	989	SAN DIEGO Gulls	-	ROCKFORD IceHogs	-
113 - 2021-05-09	1010	ROCKFORD IceHogs	-	SAN DIEGO Gulls	-
115 - 2021-05-11	1022	ROCKFORD IceHogs	-	SAN DIEGO Gulls	-
116 - 2021-05-12	1036	SAN DIEGO Gulls	-	ROCKFORD IceHogs	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	35	15
Assistance	0	0
Assistance PCT	0.00%	0.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
39	0 - 0.00%	0$	0$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
14,830$	875,000$	725,000$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	14,830$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	116	7,415$	860,140$

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
34	80	0	80	0	0	0	0	0	124	743	-619	40	0	40	0	0	0	0	0	62	362	-300	40	0	40	0	0	0	0	0	62	381	-319	0	124	192	316	0	0	45	48	31	0	1321	437	442	442	0	4956	1438	217	886	159	18	11.32%	92	44	52.17%	0	283	1438	19.68%	360	2113	17.04%	271	1589	17.05%	989	649	2975	531	835	314
34	80	0	80	0	0	0	0	0	124	743	-619	40	0	40	0	0	0	0	0	62	362	-300	40	0	40	0	0	0	0	0	62	381	-319	0	124	192	316	0	0	45	48	31	0	1321	437	442	442	0	4956	1438	217	886	159	18	11.32%	92	44	52.17%	0	283	1438	19.68%	360	2113	17.04%	271	1589	17.05%	989	649	2975	531	835	314
36	2	0	2	0	0	0	0	0	8	19	-11	1	0	1	0	0	0	0	0	4	13	-9	1	0	1	0	0	0	0	0	4	6	-2	0	8	14	22	0	0	4	2	2	0	54	28	19	7	0	121	37	10	24	2	0	0.00%	5	3	40.00%	0	8	25	32.00%	7	41	17.07%	8	51	15.69%	25	14	65	16	28	11
Total Saison Régulière	162	0	162	0	0	0	0	0	256	1505	-1249	81	0	81	0	0	0	0	0	128	737	-609	81	0	81	0	0	0	0	0	128	768	-640	0	256	398	654	0	0	94	98	64	0	2696	902	903	891	0	10033	2913	444	1796	320	36	11.25%	189	91	51.85%	0	574	2901	19.79%	727	4267	17.04%	550	3229	17.03%	2003	1313	6015	1080	1700	640