OTHL - Americans

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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	TA	SP
1	Cole Schneider		X	X		100.00	77	74	83	71	74	80	84	65	50	60	65	68	62	54	54	67	50	65	X	0
2	Mario Kempe	X	X	X		100.00	85	45	89	80	68	59	82	59	64	60	58	70	25	53	53	66	50	63	X	0
3	Remi Elie		X			100.00	84	45	95	72	77	57	75	57	25	56	55	78	25	47	47	64	50	62		0
4	Trevor Smith	X	X			100.00	76	72	84	68	72	72	76	59	74	53	57	67	54	57	57	62	50	62	X	0
5	Michael Amadio	X		X		100.00	63	42	95	73	71	56	67	64	60	63	66	54	25	47	48	65	50	61		0
6	Zac Rinaldo		X	X		100.00	85	95	76	68	70	47	59	55	31	59	56	69	25	66	67	62	50	60	X	0
7	Ross Johnston		X			100.00	90	99	64	68	92	51	59	59	25	64	57	65	25	45	45	62	50	60	X	0
8	Justin Bailey			X		100.00	71	44	93	75	79	43	74	56	25	59	55	62	25	52	52	60	50	59	X	0
9	Turner Elson		X	X		100.00	67	67	68	61	67	61	61	61	50	56	61	60	58	44	44	61	50	58	X	0
10	Jacob Nilsson (R)	X				100.00	73	66	88	58	66	56	56	58	25	46	56	62	53	44	44	59	50	55		0
11	Yannick Weber				X	100.00	75	43	90	77	72	59	72	59	25	50	48	63	75	69	70	59	50	64		0
12	Taylor Fedun				X	100.00	63	42	91	71	72	63	76	63	25	51	49	75	25	56	56	61	50	64		0
13	Dakota Mermis				X	100.00	70	67	78	67	67	75	81	52	25	47	41	61	39	53	53	54	50	60		0
14	Kurtis MacDermid				X	100.00	89	98	72	66	82	51	80	62	25	49	47	57	25	45	45	57	50	60	X	0
15	Tyler Lewington				X	100.00	66	73	50	62	73	77	85	48	25	39	41	56	39	44	44	51	50	57		0
Rayé

	MOYENNE D'ÉQUIPE					100.00	76	65	81	69	73	60	72	58	37	54	54	64	39	52	52	61	50	61

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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	TA	SP
1	Ken Appleby	100.00	48	52	65	84	46	52	50	54	52	52	30	44	44	51	50	54	X	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	48	52	65	84	46	52	50	54	52	52	30	44	44	51	50	54

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Scott Arniel	59	57	70	53	49	44	55	CAN	53	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

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#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	GW	GT	FO%	FOT	HT	P/20	S1	S2	S3
1	Cole Schneider	Americans (BUF)	LW/RW	10	3	9	12	1	4	12	19	29	10	24	10.34%	3	209	20.96	0	2	2	5	28	0	2	0	0	43.75%	16	0	1.14	1	0	0
2	Yannick Weber	Americans (BUF)	D	10	2	9	11	2	12	5	9	6	1	8	33.33%	8	218	21.84	2	3	5	4	26	0	40	0	1	0.00%	0	0	1.01	1	0	0
3	Mario Kempe	Americans (BUF)	C/LW/RW	10	0	9	9	4	4	14	22	17	6	18	0.00%	1	208	20.82	0	4	4	2	27	1	50	0	0	54.61%	282	0	0.86	1	0	0
4	Ross Johnston	Americans (BUF)	LW	10	4	4	8	1	22	23	7	17	2	12	23.53%	1	202	20.22	3	0	3	7	25	0	11	0	1	45.45%	11	0	0.79	0	0	0
5	Zac Rinaldo	Americans (BUF)	LW/RW	10	1	6	7	5	4	21	6	13	5	11	7.69%	2	185	18.58	0	3	3	2	28	0	29	0	0	37.50%	8	0	0.75	0	1	1
6	Trevor Smith	Americans (BUF)	C/LW	10	2	5	7	-4	8	14	17	21	4	9	9.52%	1	188	18.86	0	0	0	1	3	2	42	0	0	60.87%	161	0	0.74	0	2	0
7	Chad Ruhwedel	Sabres	D	10	4	3	7	-1	20	35	7	20	4	7	20.00%	16	238	23.87	1	2	3	12	28	0	45	2	0	0.00%	0	0	0.59	1	1	1
8	Taylor Fedun	Americans (BUF)	D	10	1	5	6	-1	8	7	5	11	1	5	9.09%	11	237	23.77	0	1	1	7	28	0	48	1	0	0.00%	0	0	0.50	0	1	0
9	Justin Bailey	Americans (BUF)	RW	10	0	5	5	-4	2	3	10	8	3	9	0.00%	1	149	14.93	0	0	0	1	7	0	1	0	0	42.86%	14	0	0.67	0	0	1
10	Dakota Mermis	Americans (BUF)	D	10	4	1	5	3	22	17	3	7	1	1	57.14%	5	182	18.27	0	0	0	0	7	0	11	1	0	0.00%	0	0	0.55	0	0	0
11	Michael Amadio	Americans (BUF)	C/RW	10	4	1	5	-1	0	0	17	21	5	13	19.05%	1	204	20.48	1	0	1	2	26	0	5	0	0	55.51%	227	0	0.49	0	0	0
12	Turner Elson	Americans (BUF)	LW/RW	10	3	1	4	6	6	8	11	22	1	18	13.64%	0	188	18.84	1	0	1	2	29	0	24	1	0	66.67%	18	1	0.42	0	1	0
13	Remi Elie	Americans (BUF)	LW	10	1	2	3	-5	12	16	13	17	5	17	5.88%	9	190	19.01	0	0	0	0	1	2	51	0	0	35.29%	17	0	0.32	0	0	0
14	Tyler Lewington	Americans (BUF)	D	10	3	0	3	0	4	19	2	6	1	0	50.00%	10	168	16.89	0	0	0	0	2	0	31	0	0	0.00%	0	0	0.36	0	0	0
15	Kurtis MacDermid	Americans (BUF)	D	10	0	2	2	-3	18	24	2	2	1	2	0.00%	10	189	18.99	0	0	0	2	26	0	40	0	0	0.00%	0	0	0.21	0	0	0
Stats d'équipe Total ou en Moyenne				150	32	62	94	3	146	218	150	217	50	154	14.75%	79	2963	19.76	8	15	23	47	298	5	439	5	2	55.31%	754	1	0.63	4	6	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

#	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	Ken Appleby	Americans (BUF)	10	5	4	1	0.877	3.19	583	0	1	31	253	0	0	0	0.000	0	10	0	1	0	1
Stats d'équipe Total ou en Moyenne			10	5	4	1	0.877	3.19	583	0	1	31	253	0	0	0	0.000	0	10	0	1	0	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 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	Salaire Année 4	Salaire Année 5	Link
Cole Schneider	Americans (BUF)	LW/RW	29	1990-08-26	No	200 Lbs	6 ft1	No	Yes	No	1	Pro & Farm	1,000,000$	0$	0$	No					Lien
Dakota Mermis	Americans (BUF)	D	26	1994-01-05	No	188 Lbs	5 ft11	No	No	No	2	Pro & Farm	700,000$	0$	0$	No	700,000$				Lien
Jacob Nilsson	Americans (BUF)	C	26	1993-10-12	Yes	181 Lbs	5 ft11	No	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$			Lien
Justin Bailey	Americans (BUF)	RW	24	1995-07-01	No	214 Lbs	6 ft3	No	Yes	No	2	Pro & Farm	894,167$	0$	0$	No	894,167$				Lien
Ken Appleby	Americans (BUF)	G	25	1995-04-09	No	207 Lbs	6 ft4	No	Yes	No	2	Pro & Farm	650,000$	0$	0$	No	650,000$				Lien
Kurtis MacDermid	Americans (BUF)	D	26	1994-03-25	No	208 Lbs	6 ft5	No	Yes	No	2	Pro & Farm	650,000$	0$	0$	No	650,000$				Lien
Mario Kempe	Americans (BUF)	C/LW/RW	31	1988-09-19	No	185 Lbs	6 ft0	No	Yes	No	2	Pro & Farm	650,000$	0$	0$	No	650,000$				Lien
Michael Amadio	Americans (BUF)	C/RW	24	1996-05-13	No	190 Lbs	6 ft1	No	No	No	2	Pro & Farm	715,000$	0$	0$	No	715,000$				Lien
Remi Elie	Americans (BUF)	LW	25	1995-04-15	No	210 Lbs	6 ft1	No	No	No	1	Pro & Farm	894,167$	0$	0$	No					Lien
Ross Johnston	Americans (BUF)	LW	26	1994-02-18	No	235 Lbs	6 ft5	No	Yes	No	3	Pro & Farm	1,000,000$	0$	0$	No	1,000,000$	1,000,000$			Lien
Taylor Fedun	Americans (BUF)	D	32	1988-06-04	No	198 Lbs	6 ft1	Yes	No	No	4	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$	700,000$		Lien
Trevor Smith	Americans (BUF)	C/LW	35	1985-02-08	No	195 Lbs	6 ft1	No	Yes	No	1	Pro & Farm	650,000$	0$	0$	No					Lien
Turner Elson	Americans (BUF)	LW/RW	27	1992-09-12	No	184 Lbs	6 ft0	No	Yes	No	5	Pro & Farm	650,000$	0$	0$	No	650,000$	650,000$	650,000$	650,000$	Lien
Tyler Lewington	Americans (BUF)	D	25	1994-12-05	No	189 Lbs	6 ft1	No	No	No	2	Pro & Farm	665,000$	0$	0$	No	665,000$				Lien
Yannick Weber	Americans (BUF)	D	31	1988-09-23	No	200 Lbs	5 ft11	Yes	No	No	4	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$	700,000$		Lien
Zac Rinaldo	Americans (BUF)	LW/RW	29	1990-06-15	No	192 Lbs	5 ft10	No	Yes	No	1	Pro & Farm	650,000$	0$	0$	No					Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
16	27.56	199 Lbs	6 ft1	2.31	741,771$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Ross Johnston	Michael Amadio	Cole Schneider	40	0	1	4
2	Turner Elson	Mario Kempe	Zac Rinaldo	25	0	2	3
3	Remi Elie	Trevor Smith	Justin Bailey	25	1	3	1
4	Ross Johnston	Michael Amadio	Cole Schneider	10	0	2	3

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Taylor Fedun	40	0	3	2
2	Dakota Mermis	Yannick Weber	30	0	4	1
3	Kurtis MacDermid	Tyler Lewington	20	0	4	1
4		Taylor Fedun	10	0	3	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Ross Johnston	Michael Amadio	Cole Schneider	70	0	1	4
2	Turner Elson	Mario Kempe	Zac Rinaldo	30	0	1	4

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Taylor Fedun	70	0	2	3
2	Yannick Weber	Kurtis MacDermid	30	0	2	3

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Mario Kempe	Remi Elie	60	0	4	1
2	Trevor Smith	Zac Rinaldo	40	0	4	1

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Taylor Fedun	75	0	4	1
2	Yannick Weber	Kurtis MacDermid	25	0	4	1

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Remi Elie	60	0	4	1		Taylor Fedun	75	0	4	1
2	Mario Kempe	40	0	4	1	Yannick Weber	Kurtis MacDermid	25	0	4	1

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Michael Amadio	Cole Schneider	70	0	2	3
2	Mario Kempe	Ross Johnston	30	0	2	3

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Taylor Fedun	70	0	3	2
2	Yannick Weber	Kurtis MacDermid	30	0	3	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Ross Johnston	Michael Amadio	Cole Schneider		Taylor Fedun

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Remi Elie	Mario Kempe	Zac Rinaldo		Taylor Fedun

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Ross Johnston, Justin Bailey, Turner Elson	Ross Johnston, Justin Bailey	Turner Elson

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Dakota Mermis, Tyler Lewington, Taylor Fedun	Dakota Mermis	Tyler Lewington, Taylor Fedun

Tirs de Pénalité
Yannick Weber, Cole Schneider, Turner Elson, Trevor Smith, Michael Amadio

Gardien
#1 : Ken Appleby, #2 :

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

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

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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	Gulls	5	4	1	0	0	0	0	0	22	12	10	3	3	0	0	0	0	0	0	18	8	10	2	1	1	0	0	0	0	0	4	4	0	8	0.800	22	42	64	0	1	9	11	11	1	130	50	78	84	5	131	45	72	109	23	7	30.43%	33	4	87.88%	0	165	296	55.74%	152	287	52.96%	100	171	58.48%	264	188	234	67	121	62
2	Heat	5	1	4	0	0	0	0	0	10	22	-12	2	1	1	0	0	0	0	0	5	9	-4	3	0	3	0	0	0	0	0	5	13	-8	2	0.200	10	20	30	0	0	9	11	11	1	87	50	78	84	5	135	34	74	109	14	1	7.14%	33	6	81.82%	0	165	296	55.74%	152	287	52.96%	100	171	58.48%	264	188	234	67	121	62
	Total	10	5	5	0	0	0	0	0	32	34	-2	5	4	1	0	0	0	0	0	23	17	6	5	1	4	0	0	0	0	0	9	17	-8	10	0.500	32	62	94	0	1	9	11	11	1	217	50	78	84	5	266	79	146	218	37	8	21.62%	66	10	84.85%	0	165	296	55.74%	152	287	52.96%	100	171	58.48%	264	188	234	67	121	62
	_Since Last GM Reset	10	5	5	0	0	0	0	0	32	34	-2	5	4	1	0	0	0	0	0	23	17	6	5	1	4	0	0	0	0	0	9	17	-8	10	0.500	32	62	94	0	1	9	11	11	1	217	50	78	84	5	266	79	146	218	37	8	21.62%	66	10	84.85%	0	165	296	55.74%	152	287	52.96%	100	171	58.48%	264	188	234	67	121	62
	_Vs Conference	10	5	5	0	0	0	0	0	32	34	-2	5	4	1	0	0	0	0	0	23	17	6	5	1	4	0	0	0	0	0	9	17	-8	10	0.500	32	62	94	0	1	9	11	11	1	217	50	78	84	5	266	79	146	218	37	8	21.62%	66	10	84.85%	0	165	296	55.74%	152	287	52.96%	100	171	58.48%	264	188	234	67	121	62

			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
10	10	L1	32	62	94	217	266	79	146	218	0	1

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
10	5	5	0	0	0	0	32	34

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	4	1	0	0	0	0	23	17

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	1	4	0	0	0	0	9	17

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	4	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
37	8	21.62%	66	10	84.85%	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
50	78	84	5	9	11	11	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
165	296	55.74%	152	287	52.96%	100	171	58.48%

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
264	188	234	67	121	62

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
2 - 2019-10-05	8	Gulls	5	Americans	6	W	X	Sommaire du Match
4 - 2019-10-07	16	Gulls	0	Americans	5	W		Sommaire du Match
6 - 2019-10-09	24	Americans	2	Gulls	1	W		Sommaire du Match
8 - 2019-10-11	32	Americans	2	Gulls	3	L	X	Sommaire du Match
10 - 2019-10-13	40	Gulls	3	Americans	7	W		Sommaire du Match
16 - 2019-10-19	59	Americans	2	Heat	4	L		Sommaire du Match
18 - 2019-10-21	63	Americans	3	Heat	4	L		Sommaire du Match
20 - 2019-10-23	67	Heat	7	Americans	1	L		Sommaire du Match
22 - 2019-10-25	71	Heat	2	Americans	4	W		Sommaire du Match
24 - 2019-10-27	75	Americans	0	Heat	5	L		Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	100	0
Assistance	5,767	5,000
Assistance PCT	57.67%	100.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
36	2153 - 71.78%	115,340$	576,700$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
0$	1,186,834$	1,186,834$	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
2019	82	61	9	0	0	5	3	4	403	157	246	41	28	6	0	0	3	2	2	192	76	116	41	33	3	0	0	2	1	2	211	81	130	122	403	695	1098	0	11	165	140	95	8	2639	896	846	884	42	1473	430	846	1689	283	56	19.79%	331	36	89.12%	12	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
Total Saison Régulière	82	61	9	0	0	5	3	4	403	157	246	41	28	6	0	0	3	2	2	192	76	116	41	33	3	0	0	2	1	2	211	81	130	122	403	695	1098	0	11	165	140	95	8	2639	896	846	884	42	1473	430	846	1689	283	56	19.79%	331	36	89.12%	12	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
2019	10	5	5	0	0	0	0	0	32	34	-2	5	4	1	0	0	0	0	0	23	17	6	5	1	4	0	0	0	0	0	9	17	-8	10	32	62	94	0	1	9	11	11	1	217	50	78	84	5	266	79	146	218	37	8	21.62%	66	10	84.85%	0	165	296	55.74%	152	287	52.96%	100	171	58.48%	264	188	234	67	121	62
Total Séries	10	5	5	0	0	0	0	0	32	34	-2	5	4	1	0	0	0	0	0	23	17	6	5	1	4	0	0	0	0	0	9	17	-8	10	32	62	94	0	1	9	11	11	1	217	50	78	84	5	266	79	146	218	37	8	21.62%	66	10	84.85%	0	165	296	55.74%	152	287	52.96%	100	171	58.48%	264	188	234	67	121	62