OTHL - Americans

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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	Âge	Contrat	Salaire
1	Laurent Dauphin	X	X	X		100.00	75	69	88	64	69	63	63	63	79	62	60	65	57	47	47	64	50	61		0	26	2	750,000$
2	Remi Elie		X			100.00	79	78	81	60	78	59	58	63	50	57	65	67	62	47	47	65	50	61		0	26	2	750,000$
3	Andrew Poturalski	X				100.00	73	65	92	59	65	61	60	66	80	68	58	67	55	55	55	63	50	61		0	27	2	750,000$
4	Michael Amadio	X		X		100.00	61	42	94	73	74	63	71	67	78	61	55	59	25	59	60	59	50	61		0	25	3	750,000$
5	Ryan Fitzgerald	X	X			100.00	70	61	90	65	61	67	68	64	80	57	67	62	64	44	44	66	50	61		0	27	2	750,000$
6	Sean Malone	X				100.00	74	71	81	64	71	63	64	61	76	60	58	63	55	44	44	62	50	60		0	26	2	750,000$
7	Keegan Kolesar (R)			X		100.00	89	46	80	65	79	54	66	57	52	68	58	54	25	50	50	62	50	59		0	24	2	905,000$
8	Mikey Eyssimont	X	X			100.00	67	67	66	68	67	71	75	59	74	56	58	59	55	44	44	60	50	59		0	25	2	925,000$
9	Ross Johnston		X			100.00	99	49	31	68	88	52	50	52	33	58	55	61	25	51	52	58	50	58	X	0	27	1	1,000,000$
10	Turner Elson		X	X		100.00	70	67	78	65	67	67	70	58	50	60	51	61	48	44	44	59	50	58	X	0	29	3	750,000$
11	Joona Luoto (R)		X	X		100.00	74	73	77	73	73	51	50	55	50	48	57	62	54	45	45	58	50	57		0	24	1	758,333$
12	Dalton Smith		X			100.00	66	76	44	63	76	55	58	45	50	38	46	55	44	44	44	49	50	51		0	29	2	750,000$
13	Christian Djoos				X	100.00	61	41	88	80	67	66	70	77	25	59	48	52	75	61	63	58	50	62		0	27	1	1,275,000$
14	Taylor Fedun				X	100.00	67	42	90	71	72	62	66	61	25	60	49	64	25	58	59	61	50	62		0	33	2	750,000$
15	Andy Welinski				X	100.00	76	44	99	68	74	66	53	69	25	39	47	56	70	58	59	56	50	60		0	28	4	750,000$
16	Tyler Lewington				X	100.00	78	69	99	62	69	49	52	41	25	28	39	60	37	44	44	49	50	54		0	26	3	750,000$
Rayé

	MOYENNE D'ÉQUIPE					100.00	74	60	80	67	72	61	62	60	53	55	54	60	49	50	50	59	50	59

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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	Ilya Samsonov (R)	100.00	70	61	59	80	75	64	73	70	75	70	75	48	48	65	50	67	0
2	Jonas Johansson (R)	100.00	53	53	52	90	56	50	73	55	63	54	75	45	45	57	50	59	0
Rayé
1	Jon Gillies	100.00	54	51	64	91	52	52	61	62	56	57	30	45	45	56	50	58	0

	MOYENNE D'ÉQUIPE	100.00	59	55	58	87	61	55	69	62	65	60	60	46	46	59	50	61

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Scott Arniel	68	70	76	63	87	81	59	CAN	58	2	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	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Michael Amadio	Americans (BUF)	C/RW	16	5	18	23	14	5	5	8	40	43	12	23	11.63%	2	285	17.86	0	4	4	8	27	0	1	1	1	32	2	0	64.26%	319	0	1.61	0	1	1	0	0	0	1	1
2	Laurent Dauphin	Americans (BUF)	C/LW/RW	16	13	9	22	18	21	5	30	11	45	15	41	28.89%	5	225	14.07	0	1	1	2	16	0	0	0	0	0	3	1	76.92%	13	1	1.96	0	1	0	0	0	2	3	1
3	Taylor Fedun	Americans (BUF)	D	16	0	18	18	11	8	0	14	11	12	7	10	0.00%	15	290	18.13	0	3	3	6	17	0	0	0	0	34	0	0	0.00%	0	0	1.24	0	0	0	0	0	0	0	1
4	Andy Welinski	Americans (BUF)	D	16	4	10	14	18	17	5	16	7	13	2	7	30.77%	13	269	16.83	3	0	3	7	18	0	0	0	1	29	1	0	0.00%	0	0	1.04	1	1	0	1	0	1	0	1
5	Ryan Fitzgerald	Americans (BUF)	C/LW	8	10	4	14	9	0	0	24	16	59	10	37	16.95%	0	165	20.68	0	2	2	6	17	0	0	0	1	5	0	1	65.96%	141	1	1.69	0	0	0	0	0	3	1	1
6	Sean Malone	Americans (BUF)	C	16	4	8	12	11	25	5	16	6	18	6	14	22.22%	6	178	11.14	0	0	0	0	0	0	0	0	0	0	1	0	62.90%	62	0	1.35	0	0	0	0	1	1	1	0
7	Christian Djoos	Americans (BUF)	D	8	4	7	11	9	2	0	8	5	11	5	6	36.36%	3	177	22.23	2	1	3	4	17	0	0	0	0	31	1	0	0.00%	0	0	1.24	0	0	0	0	0	1	0	0
8	Cole Schneider	Sabres	LW/RW	9	5	6	11	7	4	0	16	11	26	5	30	19.23%	1	143	15.90	0	1	1	4	13	0	0	0	0	1	2	0	58.33%	12	0	1.54	0	0	0	0	0	1	0	2
9	Andrew Poturalski	Americans (BUF)	C	8	3	7	10	9	0	0	5	7	24	12	18	12.50%	1	107	13.43	0	0	0	0	0	0	0	0	0	0	0	0	80.26%	76	0	1.86	0	0	0	0	0	0	0	2
10	Keegan Kolesar	Americans (BUF)	RW	16	4	6	10	9	24	0	27	12	29	3	19	13.79%	3	179	11.23	0	0	0	0	0	0	0	0	0	0	0	0	100.00%	5	0	1.11	0	0	0	0	0	0	0	1
11	Tage Thompson	Sabres	LW/RW	5	6	3	9	5	0	0	13	9	23	9	23	26.09%	3	93	18.71	1	1	2	8	20	1	0	1	1	10	1	0	60.00%	5	0	1.92	0	0	0	0	0	2	2	0
12	Chris Terry	Sabres	LW/RW	7	5	3	8	3	4	0	11	6	19	7	26	26.32%	7	143	20.53	2	0	2	4	9	1	1	2	4	26	1	0	50.00%	16	0	1.11	0	0	0	0	0	1	1	0
13	Remi Elie	Americans (BUF)	LW	8	4	3	7	7	8	0	3	2	21	8	8	19.05%	2	108	13.55	0	0	0	1	4	0	0	0	0	11	0	0	66.67%	9	0	1.29	0	0	0	0	0	0	0	0
14	Mikey Eyssimont	Americans (BUF)	C/LW	16	1	6	7	12	2	0	15	9	20	5	13	5.00%	3	194	12.15	0	0	0	0	0	0	0	0	0	0	0	0	100.00%	2	0	0.72	0	0	0	0	0	0	0	0
15	Ross Johnston	Americans (BUF)	LW	16	2	2	4	5	8	0	33	3	12	2	7	16.67%	5	107	6.74	0	0	0	0	3	0	0	0	0	6	0	0	55.56%	27	0	0.74	0	0	0	0	0	0	0	1
16	Tyler Lewington	Americans (BUF)	D	16	0	4	4	15	18	0	23	10	6	4	6	0.00%	7	220	13.79	0	1	1	1	17	0	0	0	0	21	0	0	0.00%	0	0	0.36	0	0	0	0	0	0	0	0
17	Turner Elson	Americans (BUF)	LW/RW	4	1	2	3	2	4	0	4	1	4	2	2	25.00%	0	39	9.97	0	0	0	0	0	0	0	0	0	0	0	0	100.00%	1	0	1.51	0	0	0	0	0	0	1	0
Stats d'équipe Total ou en Moyenne				201	71	116	187	164	150	20	266	166	385	114	290	18.44%	76	2930	14.58	8	14	22	51	184	2	2	4	8	210	12	2	66.13%	688	2	1.28	1	3	1	1	1	12	10	11

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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	A	PS %	PSA	ST	BG	S2	S3
1	Ilya Samsonov	Americans (BUF)	16	12	1	2	0.931	1.51	956	6	5	24	348	1	0.571	7	16	0	2	2
2	Jonas Johansson	Americans (BUF)	1	1	0	0	1.000	0.00	17	0	0	0	7	1	1.000	3	0	16	0	0
Stats d'équipe Total ou en Moyenne			17	13	1	2	0.932	1.48	974	6	5	24	355	2	0.700	10	16	16	2	2

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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	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Salaire Année 4	Link
Andrew Poturalski	Americans (BUF)	C	27	1994-01-14	No	183 Lbs	5 ft10	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$			Lien / Lien NHL
Andy Welinski	Americans (BUF)	D	28	1993-04-27	No	201 Lbs	6 ft1	No	No	No	4	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$	750,000$	750,000$	Lien / Lien NHL
Christian Djoos	Americans (BUF)	D	27	1994-08-05	No	180 Lbs	6 ft0	No	No	No	1	Pro & Farm	1,275,000$	1,275,000$	0$	0$	No				Lien / Lien NHL
Dalton Smith	Americans (BUF)	LW	29	1992-06-30	No	206 Lbs	6 ft2	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$			Lien / Lien NHL
Ilya Samsonov	Americans (BUF)	G	24	1997-02-21	Yes	200 Lbs	6 ft3	No	No	No	2	Pro & Farm	1,475,000$	1,475,000$	0$	0$	No	1,475,000$			Lien / Lien NHL
Jon Gillies	Americans (BUF)	G	27	1994-01-21	No	223 Lbs	6 ft6	No	No	No	3	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$	750,000$		Lien / Lien NHL
Jonas Johansson	Americans (BUF)	G	26	1995-09-18	Yes	220 Lbs	6 ft5	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$			Lien / Lien NHL
Joona Luoto	Americans (BUF)	LW/RW	24	1997-09-26	Yes	192 Lbs	6 ft3	No	No	No	1	Pro & Farm	758,333$	758,333$	0$	0$	No				Lien / Lien NHL
Keegan Kolesar	Americans (BUF)	RW	24	1997-04-08	Yes	217 Lbs	6 ft2	No	No	No	2	Pro & Farm	905,000$	905,000$	0$	0$	No	905,000$			Lien / Lien NHL
Laurent Dauphin	Americans (BUF)	C/LW/RW	26	1995-03-27	No	189 Lbs	6 ft1	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$			Lien / Lien NHL
Michael Amadio	Americans (BUF)	C/RW	25	1996-05-13	No	204 Lbs	6 ft1	No	No	No	3	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$	750,000$		Lien / Lien NHL
Mikey Eyssimont	Americans (BUF)	C/LW	25	1996-09-09	No	181 Lbs	6 ft0	No	No	No	2	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$			Lien / Lien NHL
Remi Elie	Americans (BUF)	LW	26	1995-04-16	No	215 Lbs	6 ft1	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$			Lien / Lien NHL
Ross Johnston	Americans (BUF)	LW	27	1994-02-18	No	235 Lbs	6 ft5	No	Yes	No	1	Pro & Farm	1,000,000$	1,000,000$	0$	0$	No				Lien / Lien NHL
Ryan Fitzgerald	Americans (BUF)	C/LW	27	1994-10-19	No	172 Lbs	5 ft9	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$			Lien / Lien NHL
Sean Malone	Americans (BUF)	C	26	1995-04-30	No	197 Lbs	6 ft0	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$			Lien / Lien NHL
Taylor Fedun	Americans (BUF)	D	33	1988-06-04	No	198 Lbs	6 ft1	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$			Lien / Lien NHL
Turner Elson	Americans (BUF)	LW/RW	29	1992-09-12	No	184 Lbs	6 ft0	No	Yes	No	3	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$	750,000$		Lien / Lien NHL
Tyler Lewington	Americans (BUF)	D	26	1994-12-05	No	189 Lbs	6 ft1	No	No	No	3	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$	750,000$		Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
19	26.63	199 Lbs	6 ft1	2.16	846,754$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1		Ryan Fitzgerald		40	1	2	2
2		Michael Amadio	Laurent Dauphin	30	1	2	2
3	Remi Elie	Andrew Poturalski	Keegan Kolesar	20	1	2	2
4	Mikey Eyssimont	Sean Malone		10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Taylor Fedun	Christian Djoos	40	1	2	2
2	Andy Welinski	Tyler Lewington	30	1	2	2
3	Sean Malone	Mikey Eyssimont	20	1	2	2
4	Taylor Fedun	Christian Djoos	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1		Ryan Fitzgerald		60	1	2	2
2		Michael Amadio	Laurent Dauphin	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Taylor Fedun	Christian Djoos	60	1	2	2
2	Andy Welinski	Tyler Lewington	40	1	2	2

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

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Taylor Fedun	Christian Djoos	60	1	2	2
2	Andy Welinski	Tyler Lewington	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	Taylor Fedun	Christian Djoos	60	1	2	2
2		40	1	2	2	Andy Welinski	Tyler Lewington	40	1	2	2

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

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Taylor Fedun	Christian Djoos	60	1	2	2
2	Andy Welinski	Tyler Lewington	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
	Ryan Fitzgerald		Taylor Fedun	Christian Djoos

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
	Ryan Fitzgerald		Taylor Fedun	Christian Djoos

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Ross Johnston, Andrew Poturalski, Remi Elie	Ross Johnston, Andrew Poturalski	Remi Elie

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Andy Welinski, Tyler Lewington, Taylor Fedun	Andy Welinski	Tyler Lewington, Taylor Fedun

Tirs de Pénalité
, , , Ryan Fitzgerald, Michael Amadio

Gardien
#1 : Ilya Samsonov, #2 : Jonas Johansson

Lignes d'Attaque Perso. en Prol.
, , , Ryan Fitzgerald, Michael Amadio, Andrew Poturalski, Andrew Poturalski, Remi Elie, Laurent Dauphin, Sean Malone, Mikey Eyssimont

Lignes de Défense Perso. en Prol.
Taylor Fedun, Christian Djoos, Andy Welinski, Tyler Lewington,

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	Admirals	2	0	0	0	0	1	0	1	6	8	-2	1	0	0	0	0	1	0	0	3	4	-1	1	0	0	0	0	0	0	1	3	4	-1	2	0.500	6	11	17	0	0	32	20	23	3	32	142	131	147	17	64	22	26	39	6	1	16.67%	7	0	100.00%	0	192	368	52.17%	209	403	51.86%	136	228	59.65%	446	335	347	97	179	96
2	IceHogs	2	2	0	0	0	0	0	0	6	2	4	1	1	0	0	0	0	0	0	3	1	2	1	1	0	0	0	0	0	0	3	1	2	4	1.000	6	7	13	0	0	32	20	23	3	43	142	131	147	17	53	12	24	34	9	1	11.11%	12	1	91.67%	0	192	368	52.17%	209	403	51.86%	136	228	59.65%	446	335	347	97	179	96
3	Mariners	2	1	0	0	0	0	1	0	10	5	5	1	1	0	0	0	0	0	0	5	1	4	1	0	0	0	0	0	1	0	5	4	1	4	1.000	10	14	24	0	0	32	20	23	3	43	142	131	147	17	45	9	20	46	10	3	30.00%	9	1	88.89%	0	192	368	52.17%	209	403	51.86%	136	228	59.65%	446	335	347	97	179	96
4	Moose	2	1	1	0	0	0	0	0	4	5	-1	1	1	0	0	0	0	0	0	4	2	2	1	0	1	0	0	0	0	0	0	3	-3	2	0.500	4	6	10	0	0	32	20	23	3	34	142	131	147	17	60	15	33	40	8	1	12.50%	10	1	90.00%	0	192	368	52.17%	209	403	51.86%	136	228	59.65%	446	335	347	97	179	96
5	Rampage	2	2	0	0	0	0	0	0	16	1	15	1	1	0	0	0	0	0	0	9	0	9	1	1	0	0	0	0	0	0	7	1	6	4	1.000	16	29	45	0	1	32	20	23	3	80	142	131	147	17	32	11	8	44	4	0	0.00%	4	0	100.00%	0	192	368	52.17%	209	403	51.86%	136	228	59.65%	446	335	347	97	179	96
6	Stars	2	2	0	0	0	0	0	0	18	4	14	1	1	0	0	0	0	0	0	11	2	9	1	1	0	0	0	0	0	0	7	2	5	4	1.000	18	33	51	0	0	32	20	23	3	78	142	131	147	17	50	12	20	54	5	2	40.00%	10	1	90.00%	1	192	368	52.17%	209	403	51.86%	136	228	59.65%	446	335	347	97	179	96
7	Wild	2	2	0	0	0	0	0	0	10	0	10	1	1	0	0	0	0	0	0	4	0	4	1	1	0	0	0	0	0	0	6	0	6	4	1.000	10	17	27	0	2	32	20	23	3	76	142	131	147	17	22	4	25	37	3	1	33.33%	5	0	100.00%	1	192	368	52.17%	209	403	51.86%	136	228	59.65%	446	335	347	97	179	96
8	Wolves	2	2	0	0	0	0	0	0	6	0	6	1	1	0	0	0	0	0	0	3	0	3	1	1	0	0	0	0	0	0	3	0	3	4	1.000	6	10	16	0	2	32	20	23	3	41	142	131	147	17	29	10	20	18	9	1	11.11%	10	0	100.00%	0	192	368	52.17%	209	403	51.86%	136	228	59.65%	446	335	347	97	179	96
	Total	16	12	1	0	0	1	1	1	76	25	51	8	7	0	0	0	1	0	0	42	10	32	8	5	1	0	0	0	1	1	34	15	19	28	0.875	76	127	203	0	5	32	20	23	3	427	142	131	147	17	355	95	176	312	54	10	18.52%	67	4	94.03%	2	192	368	52.17%	209	403	51.86%	136	228	59.65%	446	335	347	97	179	96
	_Since Last GM Reset	16	12	1	0	0	1	1	1	76	25	51	8	7	0	0	0	1	0	0	42	10	32	8	5	1	0	0	0	1	1	34	15	19	28	0.875	76	127	203	0	5	32	20	23	3	427	142	131	147	17	355	95	176	312	54	10	18.52%	67	4	94.03%	2	192	368	52.17%	209	403	51.86%	136	228	59.65%	446	335	347	97	179	96
	_Vs Conference	16	12	1	0	0	1	1	1	76	25	51	8	7	0	0	0	1	0	0	42	10	32	8	5	1	0	0	0	1	1	34	15	19	28	0.875	76	127	203	0	5	32	20	23	3	427	142	131	147	17	355	95	176	312	54	10	18.52%	67	4	94.03%	2	192	368	52.17%	209	403	51.86%	136	228	59.65%	446	335	347	97	179	96
	_Vs Division	12	12	1	0	0	1	1	1	60	20	40	6	7	0	0	0	1	0	0	34	9	25	6	5	1	0	0	0	1	1	26	11	15	28	1.167	60	103	163	0	3	32	20	23	3	343	142	131	147	17	281	76	136	248	35	6	17.14%	48	3	93.75%	2	192	368	52.17%	209	403	51.86%	136	228	59.65%	446	335	347	97	179	96

			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
16	28	W2	76	127	203	427	355	95	176	312	0	5

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
16	12	1	0	1	1	1	76	25

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	7	0	0	1	0	0	42	10

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	5	1	0	0	1	1	34	15

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
8	0	0	0	1	1

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
54	10	18.52%	67	4	94.03%	2

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
142	131	147	17	32	20	23	3

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
192	368	52.17%	209	403	51.86%	136	228	59.65%

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
446	335	347	97	179	96

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	SO	Lien
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
1 - 2021-10-18	14	Americans	7	Stars	2	W			Sommaire du Match
2 - 2021-10-19	27	Americans	7	Rampage	1	W			Sommaire du Match
3 - 2021-10-20	33	Mariners	1	Americans	5	W			Sommaire du Match
4 - 2021-10-21	48	Americans	3	IceHogs	1	W			Sommaire du Match
6 - 2021-10-23	60	Admirals	4	Americans	3	L	X		Sommaire du Match
7 - 2021-10-24	83	Americans	0	Moose	3	L			Sommaire du Match
8 - 2021-10-25	90	IceHogs	1	Americans	3	W			Sommaire du Match
9 - 2021-10-26	113	Americans	3	Admirals	4	L	X	X	Sommaire du Match
10 - 2021-10-27	124	Wild	0	Americans	4	W			Sommaire du Match
11 - 2021-10-28	139	Americans	6	Wild	0	W			Sommaire du Match
13 - 2021-10-30	157	Rampage	0	Americans	9	W			Sommaire du Match
14 - 2021-10-31	172	Americans	3	Wolves	0	W			Sommaire du Match
16 - 2021-11-02	191	Wolves	0	Americans	3	W			Sommaire du Match
17 - 2021-11-03	206	Americans	5	Mariners	4	W	X	X	Sommaire du Match
19 - 2021-11-05	221	Moose	2	Americans	4	W			Sommaire du Match
22 - 2021-11-08	250	Stars	2	Americans	11	W			Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité	2000	1000
Prix des Billets	100	0
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	Popularité de l'Équipe
0	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
0$	1,608,833$	1,552,167$	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

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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

	Americans
	GP: 16 \| W: 13 \| L: 1 \| OTL: 2 \| P: 28 GF: 76 \| GA: 25 \| PP%: 18.52% \| PK%: 94.03% DG: Jason \| Morale : 50 \| Moyenne d'Équipe : 59