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
1	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
2	Remi Elie		X			100.00	84	45	95	72	77	57	75	57	25	56	55	78	25	47	47	64	50	62		0
3	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
4	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
5	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
6	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
7	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
8	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
9	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
10	Yannick Weber				X	100.00	75	43	90	77	72	59	72	59	25	50	48	63	75	69	70	59	50	64		0
11	Dakota Mermis				X	100.00	70	67	78	67	67	75	81	52	25	47	41	61	39	53	53	54	50	60		0
12	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
13	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	66	80	69	74	59	71	58	37	54	54	63	38	51	51	60	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	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	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Trevor Smith	Americans (BUF)	C/LW	82	53	75	128	102	50	10	110	165	329	100	226	16.11%	29	1778	21.69	7	15	22	47	221	3	3	6	9	243	10	3	70.69%	1269	0	4	1.44	2	6	1	0	1	12	7	4
2	Ross Johnston	Americans (BUF)	LW	82	44	68	112	83	159	35	233	86	265	84	184	16.60%	15	1400	17.08	2	10	12	15	145	0	2	2	2	99	9	1	56.44%	101	0	3	1.60	0	1	1	1	5	12	6	2
3	Turner Elson	Americans (BUF)	LW/RW	82	44	57	101	80	61	15	125	91	311	94	213	14.15%	23	1437	17.53	1	1	2	14	57	0	0	0	0	63	8	2	69.26%	270	1	0	1.41	0	2	1	1	0	3	6	11
4	Michael Amadio	Americans (BUF)	C/RW	73	50	48	98	77	8	0	27	71	236	56	193	21.19%	11	1435	19.67	7	7	14	34	193	4	1	5	10	152	6	1	68.33%	180	0	1	1.37	0	1	0	0	0	8	6	4
5	Justin Bailey	Americans (BUF)	RW	82	35	61	96	74	23	5	41	65	214	59	166	16.36%	15	1324	16.15	1	5	6	15	113	1	1	2	2	52	8	1	60.00%	120	0	1	1.45	1	1	0	0	0	5	9	5
6	Zac Rinaldo	Americans (BUF)	LW/RW	74	37	44	81	56	52	0	168	79	248	71	185	14.92%	13	1344	18.17	6	6	12	35	185	1	1	2	4	95	8	0	54.90%	102	0	3	1.21	0	1	0	0	0	7	9	4
7	Jacob Nilsson	Americans (BUF)	C	73	18	35	53	53	27	5	59	71	141	37	88	12.77%	26	1221	16.74	2	1	3	10	92	0	0	0	1	86	2	2	50.78%	772	0	0	0.87	0	0	0	0	1	1	1	4
8	Remi Elie	Americans (BUF)	LW	39	24	28	52	33	24	0	62	62	157	50	108	15.29%	15	783	20.10	5	6	11	22	98	0	2	2	3	90	1	0	59.65%	114	0	1	1.33	1	2	0	0	0	3	3	5
9	Mario Kempe	Americans (BUF)	C/LW/RW	44	14	37	51	35	50	0	66	76	147	41	130	9.52%	29	946	21.52	3	5	8	20	115	1	2	3	6	130	1	1	69.86%	836	0	0	1.08	2	4	0	0	0	1	3	2
10	Cole Schneider	Sabres	LW/RW	33	22	26	48	36	29	5	68	67	159	42	105	13.84%	5	776	23.53	3	7	10	15	83	2	0	2	4	130	3	1	66.38%	354	0	1	1.24	1	3	0	1	0	5	6	2
11	Taylor Fedun	Sabres	D	38	9	39	48	36	12	0	25	29	62	22	34	14.52%	24	726	19.13	3	6	9	30	77	0	1	1	1	103	0	1	0.00%	0	0	0	1.32	0	0	0	0	0	2	2	2
12	Yannick Weber	Americans (BUF)	D	61	10	36	46	38	42	0	68	36	78	16	55	12.82%	36	1256	20.61	7	5	12	34	155	0	2	2	1	178	2	0	100.00%	1	0	0	0.73	0	1	0	0	0	1	2	4
13	Dakota Mermis	Americans (BUF)	D	80	10	35	45	58	53	5	83	51	61	22	41	16.39%	33	1402	17.53	2	8	10	25	133	0	1	1	0	134	0	1	62.50%	8	0	0	0.64	0	1	0	0	0	0	2	2
14	Kurtis MacDermid	Americans (BUF)	D	82	7	30	37	57	95	15	246	22	54	21	30	12.96%	42	1379	16.83	1	5	6	20	151	0	0	0	0	159	0	0	0.00%	0	0	0	0.54	0	0	1	2	0	1	1	6
15	Tyler Lewington	Americans (BUF)	D	82	6	27	33	82	76	0	177	37	45	18	48	13.33%	35	1447	17.66	0	2	2	8	127	0	1	1	0	115	2	1	49.10%	279	0	0	0.46	1	1	0	0	0	0	0	4
16	Dan Hamhuis	Sabres	D	25	8	13	21	12	14	0	26	22	42	14	23	19.05%	24	550	22.01	2	2	4	23	67	0	0	0	0	76	1	0	0.00%	0	0	0	0.76	0	0	0	0	0	1	1	0
17	Chad Ruhwedel	Sabres	D	15	1	10	11	10	8	0	16	12	18	7	13	5.56%	9	332	22.19	0	5	5	9	33	0	0	0	1	50	0	0	0.00%	0	0	0	0.66	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1047	392	669	1061	922	783	95	1600	1042	2567	754	1842	15.27%	384	19546	18.67	52	96	148	376	2052	12	17	29	44	1963	61	15	63.87%	4406	1	14	1.09	8	24	4	5	7	62	64	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	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)	78	61	9	7	0.896	1.86	4658	2	10	144	1381	0	5	0	0.724	29	78	0	2	1	1
Stats d'équipe Total ou en Moyenne			78	61	9	7	0.896	1.86	4658	2	10	144	1381	0	5	0	0.724	29	78	0	2	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	Salaire Année 5	Link
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	23	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
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
14	27.07	198 Lbs	6 ft1	2.29	726,310$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Trevor Smith	Mario Kempe	Michael Amadio	40	1	2	2
2	Remi Elie	Jacob Nilsson	Zac Rinaldo	30	1	2	2
3	Ross Johnston	Turner Elson	Justin Bailey	20	1	2	2
4	Turner Elson	Mario Kempe	Trevor Smith	10	1	2	2

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

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Trevor Smith	Mario Kempe	Michael Amadio	60	1	2	2
2	Remi Elie	Jacob Nilsson	Zac Rinaldo	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Yannick Weber	Kurtis MacDermid	60	1	2	2
2	Dakota Mermis	Tyler Lewington	40	1	2	2

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

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Yannick Weber	Kurtis MacDermid	60	1	2	2
2	Dakota Mermis	Tyler Lewington	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Mario Kempe	60	1	2	2	Yannick Weber	Kurtis MacDermid	60	1	2	2
2	Trevor Smith	40	1	2	2	Dakota Mermis	Tyler Lewington	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Mario Kempe	Trevor Smith	60	1	2	2
2	Remi Elie	Michael Amadio	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Yannick Weber	Kurtis MacDermid	60	1	2	2
2	Dakota Mermis	Tyler Lewington	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Trevor Smith	Mario Kempe	Michael Amadio	Yannick Weber	Kurtis MacDermid

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Trevor Smith	Mario Kempe	Michael Amadio	Yannick Weber	Kurtis MacDermid

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Ross Johnston, Justin Bailey, Zac Rinaldo	Ross Johnston, Justin Bailey	Zac Rinaldo

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Dakota Mermis, Tyler Lewington, Yannick Weber	Dakota Mermis	Tyler Lewington, Yannick Weber

Tirs de Pénalité
Mario Kempe, Trevor Smith, Remi Elie, Michael Amadio, Ross Johnston

Gardien
#1 : Ken Appleby, #2 :

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

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

Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

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

	Ligue												Domicile											Visiteur
#	VS Équipe	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	PCT	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
1	Admirals	2	2	0	0	0	0	0	0	12	2	10	1	1	0	0	0	0	0	0	6	1	5	1	1	0	0	0	0	0	0	6	1	5	4	1.000	12	21	33	0	0	165	140	95	8	97	896	846	884	42	14	5	16	27	3	1	33.33%	7	0	100.00%	1	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
2	Barracudas	2	1	0	0	0	0	0	1	10	5	5	1	1	0	0	0	0	0	0	7	1	6	1	0	0	0	0	0	0	1	3	4	-1	3	0.750	10	18	28	0	0	165	140	95	8	53	896	846	884	42	65	24	24	38	6	1	16.67%	12	1	91.67%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
3	Bears	3	2	0	0	0	1	0	0	20	10	10	2	1	0	0	0	1	0	0	11	8	3	1	1	0	0	0	0	0	0	9	2	7	5	0.833	20	38	58	0	0	165	140	95	8	113	896	846	884	42	53	16	41	72	9	1	11.11%	8	2	75.00%	1	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
4	Bruins	4	4	0	0	0	0	0	0	18	10	8	2	2	0	0	0	0	0	0	9	5	4	2	2	0	0	0	0	0	0	9	5	4	8	1.000	18	31	49	0	0	165	140	95	8	99	896	846	884	42	81	33	61	83	20	7	35.00%	17	3	82.35%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
5	Checkers	3	2	0	0	0	0	1	0	10	5	5	2	1	0	0	0	0	1	0	7	4	3	1	1	0	0	0	0	0	0	3	1	2	6	1.000	10	16	26	0	0	165	140	95	8	55	896	846	884	42	85	17	37	72	13	3	23.08%	11	1	90.91%	1	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
6	Comets	2	1	0	0	0	1	0	0	6	6	0	1	1	0	0	0	0	0	0	2	1	1	1	0	0	0	0	1	0	0	4	5	-1	3	0.750	6	11	17	0	0	165	140	95	8	40	896	846	884	42	55	12	28	36	8	0	0.00%	13	3	76.92%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
7	Condors	2	0	1	0	0	0	0	1	3	8	-5	1	0	0	0	0	0	0	1	2	3	-1	1	0	1	0	0	0	0	0	1	5	-4	1	0.250	3	4	7	0	0	165	140	95	8	35	896	846	884	42	47	14	20	39	14	1	7.14%	10	2	80.00%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
8	Crunch	4	4	0	0	0	0	0	0	15	8	7	2	2	0	0	0	0	0	0	8	3	5	2	2	0	0	0	0	0	0	7	5	2	8	1.000	15	28	43	0	0	165	140	95	8	126	896	846	884	42	52	13	37	80	18	1	5.56%	14	0	100.00%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
9	Devils	3	3	0	0	0	0	0	0	20	4	16	2	2	0	0	0	0	0	0	13	1	12	1	1	0	0	0	0	0	0	7	3	4	6	1.000	20	36	56	0	1	165	140	95	8	116	896	846	884	42	30	16	16	54	4	1	25.00%	8	0	100.00%	1	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
10	Eagles	2	2	0	0	0	0	0	0	16	2	14	1	1	0	0	0	0	0	0	8	1	7	1	1	0	0	0	0	0	0	8	1	7	4	1.000	16	28	44	0	0	165	140	95	8	100	896	846	884	42	15	9	14	41	3	0	0.00%	6	0	100.00%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
11	Griffins	4	1	0	0	0	2	0	1	15	13	2	2	1	0	0	0	1	0	0	9	5	4	2	0	0	0	0	1	0	1	6	8	-2	5	0.625	15	26	41	0	1	165	140	95	8	145	896	846	884	42	72	6	34	78	15	3	20.00%	17	4	76.47%	1	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
12	Gulls	2	1	0	0	0	0	0	1	7	6	1	1	0	0	0	0	0	0	1	4	5	-1	1	1	0	0	0	0	0	0	3	1	2	3	0.750	7	12	19	0	0	165	140	95	8	71	896	846	884	42	46	17	12	36	8	4	50.00%	5	1	80.00%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
13	Heat	2	1	0	0	0	1	0	0	8	7	1	1	0	0	0	0	1	0	0	4	5	-1	1	1	0	0	0	0	0	0	4	2	2	3	0.750	8	13	21	0	0	165	140	95	8	56	896	846	884	42	37	22	20	25	6	0	0.00%	10	3	70.00%	1	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
14	IceHogs	2	1	1	0	0	0	0	0	6	5	1	1	1	0	0	0	0	0	0	5	2	3	1	0	1	0	0	0	0	0	1	3	-2	2	0.500	6	11	17	0	0	165	140	95	8	38	896	846	884	42	45	11	18	38	10	1	10.00%	8	0	100.00%	1	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
15	Marlies	4	4	0	0	0	0	0	0	27	8	19	2	2	0	0	0	0	0	0	12	2	10	2	2	0	0	0	0	0	0	15	6	9	8	1.000	27	46	73	0	1	165	140	95	8	131	896	846	884	42	57	14	62	104	21	10	47.62%	30	5	83.33%	1	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
16	Monsters	3	1	2	0	0	0	0	0	8	10	-2	2	0	2	0	0	0	0	0	3	8	-5	1	1	0	0	0	0	0	0	5	2	3	2	0.333	8	13	21	0	0	165	140	95	8	58	896	846	884	42	73	25	28	37	12	2	16.67%	13	1	92.31%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
17	Moose	2	2	0	0	0	0	0	0	8	4	4	1	1	0	0	0	0	0	0	4	1	3	1	1	0	0	0	0	0	0	4	3	1	4	1.000	8	15	23	0	0	165	140	95	8	48	896	846	884	42	31	5	20	48	8	3	37.50%	10	2	80.00%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
18	Penguins	3	2	1	0	0	0	0	0	7	3	4	1	0	1	0	0	0	0	0	0	2	-2	2	2	0	0	0	0	0	0	7	1	6	4	0.667	7	13	20	0	1	165	140	95	8	108	896	846	884	42	56	14	36	66	2	0	0.00%	15	1	93.33%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
19	Phantoms	3	1	1	0	0	0	1	0	8	5	3	1	0	1	0	0	0	0	0	1	2	-1	2	1	0	0	0	0	1	0	7	3	4	4	0.667	8	11	19	0	0	165	140	95	8	85	896	846	884	42	62	21	52	62	13	1	7.69%	13	0	100.00%	1	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
20	Rampage	2	2	0	0	0	0	0	0	18	3	15	1	1	0	0	0	0	0	0	9	1	8	1	1	0	0	0	0	0	0	9	2	7	4	1.000	18	31	49	0	0	165	140	95	8	94	896	846	884	42	26	5	12	47	7	1	14.29%	6	0	100.00%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
21	Reign	2	2	0	0	0	0	0	0	17	1	16	1	1	0	0	0	0	0	0	9	0	9	1	1	0	0	0	0	0	0	8	1	7	4	1.000	17	29	46	0	1	165	140	95	8	95	896	846	884	42	28	7	19	37	5	1	20.00%	7	0	100.00%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
22	Roadrunners	2	2	0	0	0	0	0	0	13	3	10	1	1	0	0	0	0	0	0	6	2	4	1	1	0	0	0	0	0	0	7	1	6	4	1.000	13	23	36	0	0	165	140	95	8	51	896	846	884	42	35	8	18	47	9	3	33.33%	8	1	87.50%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
23	Rocket	4	1	2	0	0	0	1	0	8	8	0	2	0	1	0	0	0	1	0	4	4	0	2	1	1	0	0	0	0	0	4	4	0	4	0.500	8	12	20	0	0	165	140	95	8	69	896	846	884	42	119	40	45	70	18	2	11.11%	16	1	93.75%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
24	Senators	4	4	0	0	0	0	0	0	30	3	27	2	2	0	0	0	0	0	0	12	2	10	2	2	0	0	0	0	0	0	18	1	17	8	1.000	30	55	85	0	1	165	140	95	8	142	896	846	884	42	47	14	32	94	8	1	12.50%	14	1	92.86%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
25	Sound Tigers	3	3	0	0	0	0	0	0	24	3	21	1	1	0	0	0	0	0	0	7	0	7	2	2	0	0	0	0	0	0	17	3	14	6	1.000	24	41	65	0	1	165	140	95	8	161	896	846	884	42	30	10	14	66	8	1	12.50%	6	0	100.00%	1	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
26	Stars	2	2	0	0	0	0	0	0	13	4	9	1	1	0	0	0	0	0	0	6	1	5	1	1	0	0	0	0	0	0	7	3	4	4	1.000	13	21	34	0	0	165	140	95	8	81	896	846	884	42	34	12	31	61	3	0	0.00%	8	2	75.00%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
27	Thunderbirds	4	4	0	0	0	0	0	0	19	6	13	2	2	0	0	0	0	0	0	11	4	7	2	2	0	0	0	0	0	0	8	2	6	8	1.000	19	31	50	0	0	165	140	95	8	99	896	846	884	42	78	28	47	78	15	2	13.33%	20	2	90.00%	1	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
	Total	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	137	0.835	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
29	Wild	2	2	0	0	0	0	0	0	11	0	11	1	1	0	0	0	0	0	0	5	0	5	1	1	0	0	0	0	0	0	6	0	6	4	1.000	11	18	29	0	2	165	140	95	8	79	896	846	884	42	28	5	8	35	5	2	40.00%	4	0	100.00%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
30	Wolf Pack	3	3	0	0	0	0	0	0	20	1	19	1	1	0	0	0	0	0	0	7	0	7	2	2	0	0	0	0	0	0	13	1	12	6	1.000	20	32	52	0	2	165	140	95	8	125	896	846	884	42	28	0	21	82	3	1	33.33%	7	0	100.00%	1	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
31	Wolves	2	1	1	0	0	0	0	0	6	4	2	1	0	1	0	0	0	0	0	1	2	-1	1	1	0	0	0	0	0	0	5	2	3	2	0.500	6	11	17	0	0	165	140	95	8	69	896	846	884	42	44	7	23	36	9	2	22.22%	8	0	100.00%	0	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
	_Since Last GM Reset	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	137	0.835	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
	_Vs Conference	28	21	3	0	0	1	0	3	148	54	94	14	10	1	0	0	1	0	2	76	25	51	14	11	2	0	0	0	0	1	72	29	43	46	0.821	148	255	403	0	3	165	140	95	8	967	896	846	884	42	495	151	255	555	96	20	20.83%	109	12	88.99%	3	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535
	_Vs Division	14	12	2	0	0	0	0	0	84	20	64	7	6	1	0	0	0	0	0	43	7	36	7	6	1	0	0	0	0	0	41	13	28	24	0.857	84	145	229	0	2	165	140	95	8	537	896	846	884	42	193	52	119	297	39	8	20.51%	49	4	91.84%	2	1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%	2635	2038	1412	441	917	535

			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
82	137	L1	403	695	1098	2639	1473	430	846	1689	0	11

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
82	61	9	0	5	3	4	403	157

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	28	6	0	3	2	2	192	76

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	33	3	0	2	1	2	211	81

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
9	1	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
283	56	19.79%	331	36	89.12%	12

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
896	846	884	42	165	140	95	8

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
1420	2242	63.34%	932	1702	54.76%	802	1329	60.35%

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
2635	2038	1412	441	917	535

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
2 - 2019-10-05	11	Americans	5	Penguins	0	W			Sommaire du Match
4 - 2019-10-07	20	Devils	0	Americans	7	W			Sommaire du Match
6 - 2019-10-09	34	Americans	5	Monsters	2	W			Sommaire du Match
8 - 2019-10-11	44	Rocket	1	Americans	2	W	X	X	Sommaire du Match
10 - 2019-10-13	58	Thunderbirds	3	Americans	5	W			Sommaire du Match
13 - 2019-10-16	79	Stars	1	Americans	6	W			Sommaire du Match
15 - 2019-10-18	92	Americans	3	Gulls	1	W			Sommaire du Match
16 - 2019-10-19	101	Americans	8	Reign	1	W			Sommaire du Match
18 - 2019-10-21	120	Americans	3	Barracudas	4	L	X	X	Sommaire du Match
21 - 2019-10-24	134	Barracudas	1	Americans	7	W			Sommaire du Match
23 - 2019-10-26	153	Americans	5	Wolf Pack	1	W			Sommaire du Match
24 - 2019-10-27	155	Americans	2	Griffins	3	L	X		Sommaire du Match
27 - 2019-10-30	177	Roadrunners	2	Americans	6	W			Sommaire du Match
31 - 2019-11-03	203	Americans	9	Bears	2	W			Sommaire du Match
32 - 2019-11-04	206	Sound Tigers	0	Americans	7	W			Sommaire du Match
38 - 2019-11-10	248	Crunch	2	Americans	4	W			Sommaire du Match
39 - 2019-11-11	260	Americans	3	Crunch	2	W			Sommaire du Match
44 - 2019-11-16	287	Checkers	2	Americans	3	W	X	X	Sommaire du Match
46 - 2019-11-18	301	Senators	1	Americans	6	W			Sommaire du Match
47 - 2019-11-19	314	Americans	1	IceHogs	3	L			Sommaire du Match
49 - 2019-11-21	318	Wild	0	Americans	5	W			Sommaire du Match
51 - 2019-11-23	334	Americans	6	Bruins	3	W			Sommaire du Match
54 - 2019-11-26	364	Americans	2	Thunderbirds	1	W			Sommaire du Match
55 - 2019-11-27	373	Americans	4	Crunch	3	W			Sommaire du Match
57 - 2019-11-29	378	Heat	5	Americans	4	L	X		Sommaire du Match
59 - 2019-12-01	393	Marlies	2	Americans	6	W			Sommaire du Match
60 - 2019-12-02	415	Americans	7	Marlies	4	W			Sommaire du Match
62 - 2019-12-04	420	Devils	1	Americans	6	W			Sommaire du Match
65 - 2019-12-07	441	Americans	4	Heat	2	W			Sommaire du Match
67 - 2019-12-09	462	Americans	4	Comets	5	L	X		Sommaire du Match
68 - 2019-12-10	464	Americans	1	Condors	5	L			Sommaire du Match
70 - 2019-12-12	473	Rampage	1	Americans	9	W			Sommaire du Match
72 - 2019-12-14	489	Admirals	1	Americans	6	W			Sommaire du Match
74 - 2019-12-16	509	Americans	8	Sound Tigers	1	W			Sommaire du Match
77 - 2019-12-19	531	Americans	8	Marlies	2	W			Sommaire du Match
79 - 2019-12-21	544	Americans	5	Phantoms	2	W			Sommaire du Match
81 - 2019-12-23	553	Reign	0	Americans	9	W			Sommaire du Match
83 - 2019-12-25	575	Americans	7	Senators	1	W			Sommaire du Match
87 - 2019-12-29	583	Bruins	1	Americans	3	W			Sommaire du Match
89 - 2019-12-31	604	Americans	3	Bruins	2	W			Sommaire du Match
91 - 2020-01-02	614	Crunch	1	Americans	4	W			Sommaire du Match
93 - 2020-01-04	629	Condors	3	Americans	2	L	X	X	Sommaire du Match
95 - 2020-01-06	643	Thunderbirds	1	Americans	6	W			Sommaire du Match
100 - 2020-01-11	686	Americans	9	Rampage	2	W			Sommaire du Match
102 - 2020-01-13	692	Comets	1	Americans	2	W			Sommaire du Match
103 - 2020-01-14	704	Americans	4	Griffins	5	L	X	X	Sommaire du Match
105 - 2020-01-16	715	Wolves	2	Americans	1	L			Sommaire du Match
107 - 2020-01-18	730	Americans	7	Stars	3	W			Sommaire du Match
109 - 2020-01-20	749	Americans	6	Admirals	1	W			Sommaire du Match
119 - 2020-01-30	774	Senators	1	Americans	6	W			Sommaire du Match
121 - 2020-02-01	783	Rocket	3	Americans	2	L			Sommaire du Match
123 - 2020-02-03	793	Monsters	3	Americans	1	L			Sommaire du Match
126 - 2020-02-06	814	Eagles	1	Americans	8	W			Sommaire du Match
128 - 2020-02-08	828	Griffins	5	Americans	4	L	X		Sommaire du Match
129 - 2020-02-09	841	Americans	8	Wolf Pack	0	W			Sommaire du Match
131 - 2020-02-11	855	Gulls	5	Americans	4	L	X	X	Sommaire du Match
133 - 2020-02-13	867	Griffins	0	Americans	5	W			Sommaire du Match
135 - 2020-02-15	881	Monsters	5	Americans	2	L			Sommaire du Match
138 - 2020-02-18	906	Marlies	0	Americans	6	W			Sommaire du Match
140 - 2020-02-20	922	Americans	11	Senators	0	W			Sommaire du Match
144 - 2020-02-24	955	Americans	2	Penguins	1	W			Sommaire du Match
145 - 2020-02-25	960	Moose	1	Americans	4	W			Sommaire du Match
148 - 2020-02-28	981	Americans	8	Eagles	1	W			Sommaire du Match
150 - 2020-03-01	998	Americans	5	Wolves	2	W			Sommaire du Match
151 - 2020-03-02	999	Americans	7	Roadrunners	1	W			Sommaire du Match
154 - 2020-03-05	1028	Americans	4	Moose	3	W			Sommaire du Match
156 - 2020-03-07	1033	Penguins	2	Americans	0	L			Sommaire du Match
158 - 2020-03-09	1056	Americans	2	Phantoms	1	W	X	X	Sommaire du Match
160 - 2020-03-11	1066	Bears	4	Americans	3	L	X		Sommaire du Match
163 - 2020-03-14	1088	Americans	1	Rocket	2	L			Sommaire du Match
164 - 2020-03-15	1093	Bruins	4	Americans	6	W			Sommaire du Match
166 - 2020-03-17	1110	Checkers	2	Americans	4	W			Sommaire du Match
168 - 2020-03-19	1123	Americans	3	Checkers	1	W			Sommaire du Match
170 - 2020-03-21	1140	Americans	6	Thunderbirds	1	W			Sommaire du Match
172 - 2020-03-23	1153	IceHogs	2	Americans	5	W			Sommaire du Match
173 - 2020-03-24	1164	Wolf Pack	0	Americans	7	W			Sommaire du Match
175 - 2020-03-26	1178	Americans	3	Rocket	2	W			Sommaire du Match
177 - 2020-03-28	1197	Americans	9	Sound Tigers	2	W			Sommaire du Match
179 - 2020-03-30	1210	Americans	6	Wild	0	W			Sommaire du Match
181 - 2020-04-01	1224	Bears	4	Americans	8	W			Sommaire du Match
184 - 2020-04-04	1247	Americans	7	Devils	3	W			Sommaire du Match
186 - 2020-04-06	1259	Phantoms	2	Americans	1	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	44,835	36,342
Assistance PCT	54.68%	88.64%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
0	1980 - 66.00%	109,354$	4,483,500$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
2,141,557$	1,016,834$	1,016,834$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
5,467$	1,241,553$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	0	10,306$	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
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	137	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	137	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