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	Chris Terry		X	X		100.00	73	69	83	66	69	77	80	68	50	65	65	67	62	54	54	68	50	65		0	32	2	700,000$
2	Tage Thompson		X	X		100.00	81	79	85	78	79	63	63	65	50	59	65	70	62	52	52	67	50	64		0	23	1	1,137,500$
3	Cole Schneider		X	X		100.00	79	74	90	60	74	72	74	67	50	65	63	70	60	54	54	67	50	64		0	30	2	700,000$
4	Michael Amadio	X		X		100.00	61	41	94	73	71	64	85	71	74	62	59	62	25	57	58	64	50	63		0	25	1	715,000$
5	Trevor Moore	X	X	X		100.00	79	43	95	66	61	63	75	62	34	60	66	72	25	52	53	68	50	62		0	26	3	800,000$
6	Carter Verhaeghe	X	X	X		100.00	67	42	94	64	68	54	81	61	40	58	70	61	25	59	59	66	50	61		0	25	2	894,167$
7	Laurent Dauphin	X	X	X		100.00	71	68	79	64	68	72	76	60	75	56	60	62	57	47	47	63	50	60		0	26	3	700,000$
8	Keegan Kolesar (R)			X		100.00	82	82	81	65	82	68	71	57	50	62	47	67	45	45	45	59	50	60		0	24	3	905,000$
9	Sean Malone	X				100.00	75	70	86	64	70	63	64	59	74	56	58	63	55	44	44	61	50	59		0	26	3	750,000$
10	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	24	3	925,000$
11	Remi Elie		X			100.00	81	77	90	60	77	57	58	56	50	47	60	66	57	47	47	61	50	58		0	26	3	700,000$
12	Ross Johnston		X			100.00	94	99	38	68	92	50	49	55	25	53	59	61	25	48	48	60	50	58	X	0	27	2	1,000,000$
13	Turner Elson		X	X		100.00	71	67	79	65	67	78	84	54	50	50	54	60	51	44	44	59	50	58	X	0	28	4	650,000$
14	Dakota Mermis				X	100.00	85	44	87	67	67	77	80	65	25	50	50	75	79	55	55	63	50	66		0	27	1	700,000$
15	Ilya Lyubushkin				X	100.00	95	47	89	70	76	64	64	62	25	47	47	67	25	55	55	59	50	64		0	27	2	985,000$
16	Andy Welinski				X	100.00	80	75	91	68	75	62	64	58	25	46	52	69	49	57	58	61	50	63		0	28	1	1,775,000$
17	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	3	700,000$
18	Alexander Yelesin (R)				X	100.00	98	47	99	68	69	59	66	58	25	39	47	57	25	44	44	57	50	59		0	25	1	1,350,000$
19	Tyler Lewington				X	100.00	67	73	53	62	73	69	75	49	25	40	42	57	40	44	44	51	50	56		0	26	1	665,000$
Rayé
1	Andrew Poturalski	X				100.00	74	69	86	59	69	61	63	56	70	56	50	65	48	55	55	58	50	58		0	27	3	650,000$
2	Ryan Fitzgerald	X	X			100.00	70	61	90	65	61	73	77	57	71	51	58	60	55	44	44	61	50	58		0	26	3	700,000$
3	Joona Luoto (R)		X	X		100.00	67	42	95	73	70	46	64	52	25	50	55	72	25	45	45	60	50	57		0	23	2	758,333$
4	Dalton Smith		X			100.00	71	76	60	64	76	59	63	47	50	45	44	58	42	44	44	51	50	53		0	29	3	700,000$

	MOYENNE D'ÉQUIPE					100.00	76	63	83	66	72	65	70	59	46	54	56	65	44	50	50	61	50	60

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Ilya Samsonov (R)	100.00	77	63	60	80	82	72	75	76	82	77	75	46	46	75	50	71	0
2	Jonas Johansson (R)	100.00	64	60	75	84	65	68	63	70	68	67	30	44	44	65	50	65	0
3	Jon Gillies	100.00	58	67	84	91	57	61	54	62	57	56	30	45	45	59	50	61	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	66	63	73	85	68	67	64	69	69	67	45	45	45	66	50	66

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Scott Arniel	59	57	70	53	49	44	55	CAN	54	3	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	P/20	FL	S1	S2	S3
1	Chris Terry	Americans (BUF)	LW/RW	11	4	7	11	4	14	0	14	26	26	10	14	15.38%	2	269	24.48	2	1	3	9	58	1	0	1	1	57	1	1	40.30%	134	0.82	0	1	0	1
2	Cole Schneider	Americans (BUF)	LW/RW	11	5	5	10	-4	14	0	27	16	32	8	19	15.63%	3	240	21.83	4	3	7	14	59	0	0	0	1	45	0	0	25.71%	35	0.83	0	0	2	0
3	Carter Verhaeghe	Americans (BUF)	C/LW/RW	10	3	4	7	-2	6	0	4	15	17	5	11	17.65%	0	175	17.58	1	2	3	8	52	0	0	0	0	5	2	0	35.29%	153	0.80	0	0	0	0
4	Michael Amadio	Americans (BUF)	C/RW	11	4	3	7	-1	0	0	4	27	21	7	15	19.05%	2	222	20.24	1	2	3	10	55	0	0	0	0	34	2	0	49.32%	219	0.63	0	1	2	0
5	Laurent Dauphin	Americans (BUF)	C/LW/RW	11	0	6	6	-1	6	0	14	15	21	4	16	0.00%	2	187	17.05	0	2	2	4	35	0	0	0	1	15	0	0	47.69%	65	0.64	0	0	1	0
6	Sean Malone	Americans (BUF)	C	11	1	5	6	3	4	0	5	12	12	2	11	8.33%	0	167	15.26	0	0	0	3	4	0	0	0	0	22	0	0	58.54%	82	0.71	0	1	0	0
7	Turner Elson	Americans (BUF)	LW/RW	9	4	2	6	4	0	0	4	2	7	0	4	57.14%	2	62	6.91	0	0	0	0	3	0	0	0	0	0	1	1	33.33%	3	1.93	0	3	0	0
8	Alexander Yelesin	Americans (BUF)	D	11	1	3	4	-3	18	0	20	4	2	2	4	50.00%	10	228	20.78	1	2	3	2	46	0	0	0	0	46	0	0	0.00%	0	0.35	0	0	0	0
9	Mikey Eyssimont	Americans (BUF)	C/LW	11	1	3	4	1	6	0	14	10	15	7	15	6.67%	3	150	13.71	0	0	0	1	4	0	0	0	0	11	0	0	50.00%	16	0.53	0	0	1	3
10	Ilya Lyubushkin	Americans (BUF)	D	11	0	3	3	1	20	0	29	8	12	2	8	0.00%	9	256	23.32	0	1	1	5	59	0	0	0	0	55	0	0	0.00%	0	0.23	0	0	0	0
11	Andy Welinski	Americans (BUF)	D	11	1	2	3	2	14	0	15	6	9	2	8	11.11%	10	249	22.70	0	1	1	6	57	0	0	0	0	50	0	0	0.00%	0	0.24	0	0	0	1
12	Tage Thompson	Americans (BUF)	LW/RW	11	1	2	3	3	29	5	17	18	22	6	22	4.55%	3	214	19.52	0	0	0	4	49	0	1	1	0	42	0	1	18.18%	11	0.28	1	0	0	0
13	Keegan Kolesar	Americans (BUF)	RW	11	3	0	3	3	12	0	10	12	14	1	4	21.43%	1	165	15.04	0	0	0	1	27	0	0	0	0	3	1	0	50.00%	12	0.36	0	0	0	0
14	Remi Elie	Americans (BUF)	LW	9	1	1	2	3	4	0	2	2	7	0	1	14.29%	2	77	8.56	0	0	0	1	15	0	0	0	0	22	0	0	38.46%	13	0.52	0	0	0	0
15	Dakota Mermis	Americans (BUF)	D	2	0	1	1	0	2	0	4	5	3	1	0	0.00%	2	49	24.63	0	0	0	3	10	0	1	1	0	11	0	0	0.00%	0	0.41	0	0	0	0
16	Tyler Lewington	Americans (BUF)	D	9	0	1	1	4	4	0	5	2	5	2	4	0.00%	6	171	19.03	0	1	1	3	24	0	0	0	0	27	0	0	0.00%	0	0.12	0	0	0	0
17	Ryan Fitzgerald	Americans (BUF)	C/LW	2	0	1	1	1	0	0	0	1	0	0	0	0.00%	0	5	2.69	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	3.72	0	0	0	0
18	Taylor Fedun	Americans (BUF)	D	8	0	1	1	-3	4	0	1	6	5	2	6	0.00%	7	171	21.50	0	1	1	4	36	0	0	0	0	39	0	0	0.00%	0	0.12	0	0	0	0
19	Ross Johnston	Americans (BUF)	LW	9	0	0	0	3	24	0	33	2	1	2	0	0.00%	4	126	14.01	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0.00	0	0	0	0
20	Andrew Poturalski	Americans (BUF)	C	2	0	0	0	1	0	0	0	1	0	1	0	0.00%	1	8	4.33	0	0	0	0	1	0	0	0	0	2	0	0	33.33%	9	0.00	0	0	0	0
21	Trevor Moore	Americans (BUF)	C/LW/RW	3	0	0	0	-1	0	0	7	6	6	1	5	0.00%	1	51	17.07	0	0	0	2	15	0	0	0	0	2	0	0	23.53%	51	0.00	0	0	0	0
Stats d'équipe Total ou en Moyenne				184	29	50	79	18	181	5	229	196	237	65	167	12.24%	70	3252	17.67	9	16	25	80	620	1	2	3	3	495	7	3	42.47%	803	0.49	1	6	6	5

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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	PCT	GAA	MP	SO	GA	SA	ST	BG	S1	S2
1	Jonas Johansson	Americans (BUF)	9	6	3	0.880	2.55	541	1	23	192	9	2	1	0
2	Ilya Samsonov	Americans (BUF)	2	1	1	0.941	1.51	119	0	3	51	2	0	0	1
3	Jon Gillies	Americans (BUF)	1	0	0	1.000	0.00	20	0	0	9	0	9	0	0
Stats d'équipe Total ou en Moyenne			12	7	4	0.897	2.29	681	1	26	252	11	11	1	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	Link
Alexander Yelesin	Americans (BUF)	D	25	1996-02-07	Yes	192 Lbs	5 ft11	No	No	No	1	Pro & Farm	1,350,000$	0$	0$	No				Lien / Lien NHL
Andrew Poturalski	Americans (BUF)	C	27	1994-01-14	No	190 Lbs	5 ft11	Yes	No	No	3	Pro & Farm	650,000$	0$	0$	No	650,000$	650,000$		Lien / Lien NHL
Andy Welinski	Americans (BUF)	D	28	1993-04-27	No	206 Lbs	6 ft1	No	No	No	1	Pro & Farm	1,775,000$	0$	0$	No				Lien / Lien NHL
Carter Verhaeghe	Americans (BUF)	C/LW/RW	25	1995-08-14	No	181 Lbs	6 ft1	No	No	No	2	Pro & Farm	894,167$	0$	0$	No	894,167$			Lien / Lien NHL
Chris Terry	Americans (BUF)	LW/RW	32	1989-04-07	No	195 Lbs	5 ft10	Yes	No	No	2	Pro & Farm	700,000$	0$	0$	No	700,000$			Lien / Lien NHL
Cole Schneider	Americans (BUF)	LW/RW	30	1990-08-26	No	200 Lbs	6 ft1	Yes	No	No	2	Pro & Farm	700,000$	0$	0$	No	700,000$			Lien / Lien NHL
Dakota Mermis	Americans (BUF)	D	27	1994-01-05	No	188 Lbs	5 ft11	No	No	No	1	Pro & Farm	700,000$	0$	0$	No				Lien / Lien NHL
Dalton Smith	Americans (BUF)	LW	29	1992-06-30	No	206 Lbs	6 ft2	Yes	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$		Lien / Lien NHL
Ilya Lyubushkin	Americans (BUF)	D	27	1994-04-06	No	209 Lbs	6 ft2	No	No	No	2	Pro & Farm	985,000$	0$	0$	No	985,000$			Lien / Lien NHL
Ilya Samsonov	Americans (BUF)	G	24	1997-02-21	Yes	200 Lbs	6 ft3	No	No	No	3	Pro & Farm	1,475,000$	0$	0$	No	1,475,000$	1,475,000$		Lien / Lien NHL
Jon Gillies	Americans (BUF)	G	27	1994-01-21	No	223 Lbs	6 ft6	No	No	No	1	Pro & Farm	925,000$	0$	0$	No				Lien / Lien NHL
Jonas Johansson	Americans (BUF)	G	25	1995-09-18	Yes	206 Lbs	6 ft4	No	No	No	3	Pro & Farm	635,236$	0$	0$	No	635,236$	635,236$		Lien / Lien NHL
Joona Luoto	Americans (BUF)	LW/RW	23	1997-09-26	Yes	185 Lbs	6 ft2	No	No	No	2	Pro & Farm	758,333$	0$	0$	No	758,333$			Lien / Lien NHL
Keegan Kolesar	Americans (BUF)	RW	24	1997-04-08	Yes	227 Lbs	6 ft2	No	No	No	3	Pro & Farm	905,000$	0$	0$	No	905,000$	905,000$		Lien / Lien NHL
Laurent Dauphin	Americans (BUF)	C/LW/RW	26	1995-03-27	No	180 Lbs	6 ft1	Yes	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$		Lien / Lien NHL
Michael Amadio	Americans (BUF)	C/RW	25	1996-05-13	No	190 Lbs	6 ft1	No	No	No	1	Pro & Farm	715,000$	0$	0$	No				Lien / Lien NHL
Mikey Eyssimont	Americans (BUF)	C/LW	24	1996-09-09	No	181 Lbs	6 ft0	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$		Lien / Lien NHL
Remi Elie	Americans (BUF)	LW	26	1995-04-15	No	210 Lbs	6 ft1	No	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$		Lien / Lien NHL
Ross Johnston	Americans (BUF)	LW	27	1994-02-18	No	235 Lbs	6 ft5	No	Yes	No	2	Pro & Farm	1,000,000$	0$	0$	No	1,000,000$			Lien / Lien NHL
Ryan Fitzgerald	Americans (BUF)	C/LW	26	1994-10-19	No	172 Lbs	5 ft9	No	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$		Lien / Lien NHL
Sean Malone	Americans (BUF)	C	26	1995-04-30	No	190 Lbs	6 ft0	No	No	No	3	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$		Lien / Lien NHL
Tage Thompson	Americans (BUF)	LW/RW	23	1997-10-30	No	205 Lbs	6 ft5	No	No	No	1	Pro & Farm	1,137,500$	0$	0$	No				Lien / Lien NHL
Taylor Fedun	Americans (BUF)	D	33	1988-06-04	No	198 Lbs	6 ft1	No	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$		Lien / Lien NHL
Trevor Moore	Americans (BUF)	C/LW/RW	26	1995-03-31	No	170 Lbs	5 ft9	No	No	No	3	Pro & Farm	800,000$	0$	0$	No	800,000$	800,000$		Lien / Lien NHL
Turner Elson	Americans (BUF)	LW/RW	28	1992-09-12	No	184 Lbs	6 ft0	No	Yes	No	4	Pro & Farm	650,000$	0$	0$	No	650,000$	650,000$	650,000$	Lien / Lien NHL
Tyler Lewington	Americans (BUF)	D	26	1994-12-05	No	189 Lbs	6 ft1	No	No	No	1	Pro & Farm	665,000$	0$	0$	No				Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
26	26.50	197 Lbs	6 ft1	2.27	869,048$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Chris Terry	Michael Amadio	Cole Schneider	40	1	2	2
2	Tage Thompson	Trevor Moore	Keegan Kolesar	30	1	2	2
3	Laurent Dauphin	Carter Verhaeghe	Turner Elson	20	1	2	2
4	Mikey Eyssimont	Sean Malone	Ross Johnston	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dakota Mermis	Ilya Lyubushkin	40	1	2	2
2	Andy Welinski	Taylor Fedun	30	1	2	2
3	Alexander Yelesin	Tyler Lewington	20	1	2	2
4	Dakota Mermis	Ilya Lyubushkin	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Chris Terry	Michael Amadio	Cole Schneider	60	1	2	2
2	Trevor Moore	Carter Verhaeghe	Tage Thompson	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dakota Mermis	Ilya Lyubushkin	60	1	2	2
2	Andy Welinski	Taylor Fedun	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Michael Amadio	Chris Terry	60	1	2	2
2	Carter Verhaeghe	Tage Thompson	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dakota Mermis	Ilya Lyubushkin	60	1	2	2
2	Andy Welinski	Taylor Fedun	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Michael Amadio	60	1	2	2	Dakota Mermis	Ilya Lyubushkin	60	1	2	2
2	Carter Verhaeghe	40	1	2	2	Andy Welinski	Taylor Fedun	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Michael Amadio	Chris Terry	60	1	2	2
2	Carter Verhaeghe	Tage Thompson	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dakota Mermis	Ilya Lyubushkin	60	1	2	2
2	Andy Welinski	Taylor Fedun	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Chris Terry	Michael Amadio	Cole Schneider	Dakota Mermis	Ilya Lyubushkin

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Chris Terry	Michael Amadio	Cole Schneider	Dakota Mermis	Ilya Lyubushkin

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Carter Verhaeghe, Trevor Moore, Laurent Dauphin	Carter Verhaeghe, Trevor Moore	Carter Verhaeghe

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Taylor Fedun, Alexander Yelesin, Tyler Lewington	Taylor Fedun	Taylor Fedun, Alexander Yelesin

Tirs de Pénalité
Chris Terry, Tage Thompson, Cole Schneider, Michael Amadio, Carter Verhaeghe

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

Lignes d'Attaque Perso. en Prol.
Chris Terry, Tage Thompson, Cole Schneider, Michael Amadio, Carter Verhaeghe, Trevor Moore, Trevor Moore, Laurent Dauphin, Keegan Kolesar, Mikey Eyssimont, Sean Malone

Lignes de Défense Perso. en Prol.
Dakota Mermis, Ilya Lyubushkin, Andy Welinski, Taylor Fedun, Alexander Yelesin

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	7	3	4	0	0	0	0	0	16	19	-3	3	2	1	0	0	0	0	0	6	6	0	4	1	3	0	0	0	0	0	10	13	-3	6	0.429	16	28	44	0	0	11	8	8	2	140	82	71	75	9	167	48	127	137	42	6	14.29%	51	7	86.27%	1	134	308	43.51%	140	332	42.17%	67	163	41.10%	260	171	281	86	140	70
2	Moose	4	4	0	0	0	0	0	0	13	7	6	2	2	0	0	0	0	0	0	5	3	2	2	2	0	0	0	0	0	0	8	4	4	8	1.000	13	22	35	0	1	11	8	8	2	97	82	71	75	9	85	22	54	92	32	3	9.38%	24	3	87.50%	0	134	308	43.51%	140	332	42.17%	67	163	41.10%	260	171	281	86	140	70
	Total	11	7	4	0	0	0	0	0	29	26	3	5	4	1	0	0	0	0	0	11	9	2	6	3	3	0	0	0	0	0	18	17	1	14	0.636	29	50	79	0	1	11	8	8	2	237	82	71	75	9	252	70	181	229	74	9	12.16%	75	10	86.67%	1	134	308	43.51%	140	332	42.17%	67	163	41.10%	260	171	281	86	140	70
	_Since Last GM Reset	11	7	4	0	0	0	0	0	29	26	3	5	4	1	0	0	0	0	0	11	9	2	6	3	3	0	0	0	0	0	18	17	1	14	0.636	29	50	79	0	1	11	8	8	2	237	82	71	75	9	252	70	181	229	74	9	12.16%	75	10	86.67%	1	134	308	43.51%	140	332	42.17%	67	163	41.10%	260	171	281	86	140	70
	_Vs Conference	11	7	4	0	0	0	0	0	29	26	3	5	4	1	0	0	0	0	0	11	9	2	6	3	3	0	0	0	0	0	18	17	1	14	0.636	29	50	79	0	1	11	8	8	2	237	82	71	75	9	252	70	181	229	74	9	12.16%	75	10	86.67%	1	134	308	43.51%	140	332	42.17%	67	163	41.10%	260	171	281	86	140	70
	_Vs Division	11	7	4	0	0	0	0	0	29	26	3	5	4	1	0	0	0	0	0	11	9	2	6	3	3	0	0	0	0	0	18	17	1	14	0.636	29	50	79	0	1	11	8	8	2	237	82	71	75	9	252	70	181	229	74	9	12.16%	75	10	86.67%	1	134	308	43.51%	140	332	42.17%	67	163	41.10%	260	171	281	86	140	70

			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
11	14	L1	29	50	79	237	252	70	181	229	0	1

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
11	7	4	0	0	0	0	29	26

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	4	1	0	0	0	0	11	9

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
6	3	3	0	0	0	0	18	17

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	4	2	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
74	9	12.16%	75	10	86.67%	1

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
82	71	75	9	11	8	8	2

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
134	308	43.51%	140	332	42.17%	67	163	41.10%

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
260	171	281	86	140	70

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 - 2020-10-25	8	Moose	0	Americans	1	W		Sommaire du Match
4 - 2020-10-27	16	Moose	3	Americans	4	W	X	Sommaire du Match
6 - 2020-10-29	24	Americans	3	Moose	2	W		Sommaire du Match
8 - 2020-10-31	32	Americans	5	Moose	2	W		Sommaire du Match
16 - 2020-11-08	59	Americans	2	Admirals	3	L		Sommaire du Match
18 - 2020-11-10	63	Americans	4	Admirals	3	W	X	Sommaire du Match
20 - 2020-11-12	67	Admirals	1	Americans	2	W		Sommaire du Match
22 - 2020-11-14	71	Admirals	4	Americans	2	L		Sommaire du Match
24 - 2020-11-16	75	Americans	3	Admirals	5	L		Sommaire du Match
26 - 2020-11-18	79	Admirals	1	Americans	2	W		Sommaire du Match
28 - 2020-11-20	83	Americans	1	Admirals	2	L		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	6,180	5,000
Assistance PCT	61.80%	100.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité	Popularité de l'Équipe
36	2236 - 74.53%	123,600$	618,000$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
0$	2,259,524$	2,160,358$	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
2020	82	52	17	0	5	2	4	2	362	174	188	41	25	11	0	2	1	2	0	183	86	97	41	27	6	0	3	1	2	2	179	88	91	126	362	635	997	1	16	138	120	95	13	2510	775	865	831	61	1372	379	1109	1619	358	47	13.13%	458	56	87.77%	6	1562	2410	64.81%	1150	1882	61.11%	844	1250	67.52%	2491	1867	1539	505	940	520
Total Saison Régulière	82	52	17	0	5	2	4	2	362	174	188	41	25	11	0	2	1	2	0	183	86	97	41	27	6	0	3	1	2	2	179	88	91	126	362	635	997	1	16	138	120	95	13	2510	775	865	831	61	1372	379	1109	1619	358	47	13.13%	458	56	87.77%	6	1562	2410	64.81%	1150	1882	61.11%	844	1250	67.52%	2491	1867	1539	505	940	520
2020	11	7	4	0	0	0	0	0	29	26	3	5	4	1	0	0	0	0	0	11	9	2	6	3	3	0	0	0	0	0	18	17	1	14	29	50	79	0	1	11	8	8	2	237	82	71	75	9	252	70	181	229	74	9	12.16%	75	10	86.67%	1	134	308	43.51%	140	332	42.17%	67	163	41.10%	260	171	281	86	140	70
Total Séries	11	7	4	0	0	0	0	0	29	26	3	5	4	1	0	0	0	0	0	11	9	2	6	3	3	0	0	0	0	0	18	17	1	14	29	50	79	0	1	11	8	8	2	237	82	71	75	9	252	70	181	229	74	9	12.16%	75	10	86.67%	1	134	308	43.51%	140	332	42.17%	67	163	41.10%	260	171	281	86	140	70

	Americans
	GP: 11 \| W: 7 \| L: 4 GF: 29 \| GA: 26 \| PP%: 12.16% \| PK%: 86.67% DG: Jason \| Morale : 50 \| Moyenne d'Équipe : 61