OTHL - Moose

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP	Âge	Contrat	Salaire
1	Eeli Tolvanen		X	X		100.00	85	45	96	67	68	68	78	77	30	73	79	58	25	48	48	72	50	66	0	22	4	3,426,500$
2	Eetu Luostarinen (R)	X				100.00	78	44	91	77	73	64	78	58	77	60	58	80	25	49	49	66	50	64	0	23	2	897,500$
3	Taylor Raddysh	X		X		100.00	82	80	88	63	80	68	68	68	80	65	68	69	65	44	44	69	50	64	0	23	2	894,166$
4	Clark Bishop	X				100.00	83	45	90	61	72	54	62	64	71	68	55	76	25	57	58	62	50	62	0	25	1	750,000$
5	Rasmus Kupari (R)	X				100.00	71	68	79	65	68	61	61	63	79	62	61	62	58	44	44	63	50	60	0	21	2	1,081,667$
6	Lukas Vejdemo (R)	X	X	X		100.00	74	72	79	64	72	62	64	58	73	50	62	63	59	44	44	62	50	59	0	25	2	925,000$
7	Jansen Harkins (R)	X				100.00	63	41	94	67	68	51	66	59	58	54	56	68	25	56	57	60	50	59	0	24	2	767,500$
8	Beck Malenstyn (R)		X			100.00	77	72	87	65	72	73	79	53	50	47	54	63	51	44	44	59	50	58	0	23	2	750,000$
9	Joona Koppanen	X	X			100.00	81	75	96	63	75	57	59	52	65	47	53	65	50	44	44	58	50	57	0	23	2	910,833$
10	Matheson Iacopelli		X	X		100.00	77	76	80	67	76	59	62	47	50	43	46	61	44	44	44	53	50	54	0	27	2	925,000$
11	John Quenneville	X	X	X		100.00	69	72	61	63	72	51	53	47	59	42	46	58	44	47	48	50	50	52	0	25	1	894,167$
12	Olli Juolevi				X	100.00	75	43	99	68	69	61	59	55	25	43	50	78	25	46	47	60	50	62	0	23	2	1,913,333$
13	Juuso Riikola				X	100.00	82	43	89	73	68	60	46	65	24	49	46	55	25	53	53	57	50	59	0	28	2	1,150,000$
14	Guillaume Brisebois				X	100.00	75	67	92	68	67	54	56	47	25	37	41	62	39	51	51	52	50	57	0	24	1	888,333$
Rayé

	MOYENNE D'ÉQUIPE					100.00	77	60	87	67	71	60	64	58	55	53	55	66	40	48	48	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	SP
1	Jeremy Helvig (R)	100.00	61	52	65	79	65	62	58	65	62	61	30	44	44	61	50	61	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	61	52	65	79	65	62	58	65	62	61	30	44	44	61	50	61

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Sheldon Brookbank	67	66	68	71	60	56	85	CAN	40	3	850,000$

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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	PKS	PKM	GW	FO%	FOT	HT	P/20	PSG	PSS	FL	FT	S1	S2	S3
1	Eeli Tolvanen	Moose (WPG)	LW/RW	16	19	19	38	29	4	0	17	22	98	24	89	19.39%	3	259	16.23	3	1	4	12	34	0	0	2	45.45%	11	1	2.93	0	1	0	0	4	3	2
2	Taylor Raddysh	Moose (WPG)	C/RW	16	19	16	35	29	22	10	27	37	81	26	60	23.46%	2	234	14.63	0	1	1	1	8	0	0	1	75.00%	212	1	2.99	0	1	1	1	3	1	5
3	Eetu Luostarinen	Moose (WPG)	C	16	10	13	23	21	4	0	20	44	87	21	53	11.49%	9	320	20.02	1	1	2	13	53	2	40	1	75.21%	355	0	1.44	0	1	0	0	3	0	1
4	Olli Juolevi	Moose (WPG)	D	16	5	18	23	24	26	0	28	8	26	6	13	19.23%	11	219	13.74	1	1	2	5	6	0	2	1	0.00%	0	0	2.09	0	0	0	0	1	1	1
5	Juuso Riikola	Moose (WPG)	D	16	2	19	21	24	24	0	35	13	10	5	10	20.00%	14	261	16.32	0	0	0	0	0	0	0	0	0.00%	0	0	1.61	0	0	0	0	0	0	1
6	Clark Bishop	Moose (WPG)	C	16	10	8	18	20	2	0	24	17	44	8	38	22.73%	4	224	14.02	0	0	0	0	0	0	0	1	66.67%	9	0	1.60	0	0	0	0	0	5	0
7	Joona Koppanen	Moose (WPG)	C/LW	16	7	6	13	12	6	0	11	17	31	9	27	22.58%	9	201	12.57	2	2	4	4	35	0	15	1	66.23%	228	0	1.29	1	1	0	0	0	1	1
8	Rasmus Kupari	Moose (WPG)	C	16	6	7	13	4	0	0	20	34	59	20	47	10.17%	11	191	11.96	1	4	5	8	35	0	0	1	75.45%	110	0	1.36	0	1	0	0	0	0	1
9	Lukas Vejdemo	Moose (WPG)	C/LW/RW	16	5	7	12	12	8	0	17	11	46	15	30	10.87%	1	152	9.51	0	0	0	0	0	0	0	3	70.00%	10	0	1.58	0	0	0	0	0	0	0
10	Jansen Harkins	Moose (WPG)	C	16	5	7	12	12	0	0	5	13	41	9	36	12.20%	2	151	9.47	0	0	0	0	0	0	0	0	54.55%	11	0	1.58	0	0	0	0	0	1	1
11	Guillaume Brisebois	Moose (WPG)	D	16	1	8	9	11	12	0	28	5	13	4	10	7.69%	9	157	9.86	0	0	0	0	0	0	1	0	0.00%	0	0	1.14	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				176	89	128	217	198	108	10	232	221	536	147	413	16.60%	75	2373	13.48	8	10	18	43	174	2	59	11	72.30%	946	2	1.83	1	5	1	1	11	12	13

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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	Jeremy Helvig	Moose (WPG)	16	11	4	1	0.897	1.92	936	0	2	30	291	0	0	0	0.714	7	16	16	0	0	0
Stats d'équipe Total ou en Moyenne			16	11	4	1	0.897	1.92	936	0	2	30	291	0	0	0	0.714	7	16	16	0	0	0

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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
Beck Malenstyn	Moose (WPG)	LW	23	1998-02-04	Yes	194 Lbs	6 ft2	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$			Lien / Lien NHL
Clark Bishop	Moose (WPG)	C	25	1996-03-28	No	199 Lbs	6 ft1	No	No	No	1	Pro & Farm	750,000$	750,000$	0$	0$	No				Lien / Lien NHL
Eeli Tolvanen	Moose (WPG)	LW/RW	22	1999-04-22	No	191 Lbs	5 ft10	No	No	No	4	Pro & Farm	3,426,500$	3,426,500$	0$	0$	No	3,426,500$	3,426,500$	3,426,500$	Lien / Lien NHL
Eetu Luostarinen	Moose (WPG)	C	23	1998-09-02	Yes	190 Lbs	6 ft3	No	No	No	2	Pro & Farm	897,500$	897,500$	0$	0$	No	897,500$			Lien / Lien NHL
Guillaume Brisebois	Moose (WPG)	D	24	1997-07-21	No	175 Lbs	6 ft2	No	No	No	1	Pro & Farm	888,333$	888,333$	0$	0$	No				Lien / Lien NHL
Jansen Harkins	Moose (WPG)	C	24	1997-05-23	Yes	182 Lbs	6 ft1	No	No	No	2	Pro & Farm	767,500$	767,500$	0$	0$	No	767,500$			Lien / Lien NHL
Jeremy Helvig	Moose (WPG)	G	24	1997-05-24	Yes	188 Lbs	6 ft4	No	No	No	2	Pro & Farm	785,000$	785,000$	0$	0$	No	785,000$			Lien / Lien NHL
John Quenneville	Moose (WPG)	C/LW/RW	25	1996-04-16	No	195 Lbs	6 ft1	No	No	No	1	Pro & Farm	894,167$	894,167$	0$	0$	No				Lien / Lien NHL
Joona Koppanen	Moose (WPG)	C/LW	23	1998-02-25	No	192 Lbs	6 ft5	No	No	No	2	Pro & Farm	910,833$	910,833$	0$	0$	No	910,833$			Lien / Lien NHL
Juuso Riikola	Moose (WPG)	D	28	1993-11-09	No	189 Lbs	6 ft0	No	No	No	2	Pro & Farm	1,150,000$	1,150,000$	0$	0$	No	1,150,000$			Lien / Lien NHL
Lukas Vejdemo	Moose (WPG)	C/LW/RW	25	1996-01-25	Yes	194 Lbs	6 ft2	No	No	No	2	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$			Lien / Lien NHL
Matheson Iacopelli	Moose (WPG)	LW/RW	27	1994-05-15	No	207 Lbs	6 ft2	No	No	No	2	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$			Lien
Olli Juolevi	Moose (WPG)	D	23	1998-05-05	No	182 Lbs	6 ft2	No	No	No	2	Pro & Farm	1,913,333$	1,913,333$	0$	0$	No	1,913,333$			Lien / Lien NHL
Rasmus Kupari	Moose (WPG)	C	21	2000-03-15	Yes	183 Lbs	6 ft1	No	No	No	2	Pro & Farm	1,081,667$	1,081,667$	0$	0$	No	1,081,667$			Lien / Lien NHL
Taylor Raddysh	Moose (WPG)	C/RW	23	1998-02-18	No	216 Lbs	6 ft3	No	No	No	2	Pro & Farm	894,166$	894,166$	0$	0$	No	894,166$			Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
15	24.00	192 Lbs	6 ft2	1.93	1,130,600$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1		Eetu Luostarinen	Clark Bishop	40	1	2	2
2	Eeli Tolvanen	Taylor Raddysh		30	1	2	2
3	Jansen Harkins	Joona Koppanen	Lukas Vejdemo	20	1	2	2
4		Rasmus Kupari		10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Juuso Riikola	40	1	2	2
2	Olli Juolevi		30	1	2	2
3		Guillaume Brisebois	20	1	2	2
4			10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Eeli Tolvanen	Joona Koppanen	Rasmus Kupari	60	1	2	2
2		Eetu Luostarinen		40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			60	1	2	2
2	Olli Juolevi		40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Eetu Luostarinen		60	1	2	2
2	Joona Koppanen		40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			60	1	2	2
2	Olli Juolevi		40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Joona Koppanen	60	1	2	2			60	1	2	2
2		40	1	2	2	Olli Juolevi		40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Eetu Luostarinen		60	1	2	2
2	Joona Koppanen		40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			60	1	2	2
2	Olli Juolevi		40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
	Eetu Luostarinen

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
	Eetu Luostarinen		Juuso Riikola

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Rasmus Kupari, Joona Koppanen,	Rasmus Kupari, Joona Koppanen

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, Olli Juolevi, Guillaume Brisebois		Olli Juolevi, Guillaume Brisebois

Tirs de Pénalité
Eeli Tolvanen, Eetu Luostarinen, , , Joona Koppanen

Gardien
#1 : , #2 : Jeremy Helvig

Lignes d'Attaque Perso. en Prol.
, Taylor Raddysh, , Joona Koppanen, Eetu Luostarinen, Eeli Tolvanen, Eeli Tolvanen, Rasmus Kupari, Jansen Harkins, Lukas Vejdemo, Clark Bishop

Lignes de Défense Perso. en Prol.
Guillaume Brisebois, , Olli Juolevi, ,

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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	Americans	2	1	1	0	0	0	0	0	5	4	1	1	1	0	0	0	0	0	0	3	0	3	1	0	1	0	0	0	0	0	2	4	-2	2	0.500	5	8	13	0	1	42	27	20	1	60	216	184	198	8	34	14	16	19	10	1	10.00%	8	1	87.50%	0	318	447	71.14%	237	344	68.90%	158	236	66.95%	493	389	305	92	166	88
2	Admirals	2	0	1	0	0	0	0	1	5	10	-5	1	0	0	0	0	0	0	1	3	4	-1	1	0	1	0	0	0	0	0	2	6	-4	1	0.250	5	9	14	0	0	42	27	20	1	53	216	184	198	8	55	14	27	26	10	1	10.00%	11	5	54.55%	0	318	447	71.14%	237	344	68.90%	158	236	66.95%	493	389	305	92	166	88
3	IceHogs	2	0	2	0	0	0	0	0	2	6	-4	1	0	1	0	0	0	0	0	0	1	-1	1	0	1	0	0	0	0	0	2	5	-3	0	0.000	2	3	5	0	0	42	27	20	1	41	216	184	198	8	37	12	18	23	7	0	0.00%	9	3	66.67%	0	318	447	71.14%	237	344	68.90%	158	236	66.95%	493	389	305	92	166	88
4	Mariners	2	2	0	0	0	0	0	0	15	5	10	1	1	0	0	0	0	0	0	7	3	4	1	1	0	0	0	0	0	0	8	2	6	4	1.000	15	23	38	0	0	42	27	20	1	69	216	184	198	8	56	17	17	37	7	1	14.29%	5	3	40.00%	0	318	447	71.14%	237	344	68.90%	158	236	66.95%	493	389	305	92	166	88
5	Rampage	2	2	0	0	0	0	0	0	17	2	15	1	1	0	0	0	0	0	0	10	1	9	1	1	0	0	0	0	0	0	7	1	6	4	1.000	17	30	47	0	0	42	27	20	1	100	216	184	198	8	29	5	10	34	7	1	14.29%	5	2	60.00%	0	318	447	71.14%	237	344	68.90%	158	236	66.95%	493	389	305	92	166	88
6	Stars	2	2	0	0	0	0	0	0	23	1	22	1	1	0	0	0	0	0	0	12	1	11	1	1	0	0	0	0	0	0	11	0	11	4	1.000	23	37	60	0	1	42	27	20	1	108	216	184	198	8	34	14	6	54	4	3	75.00%	3	0	100.00%	0	318	447	71.14%	237	344	68.90%	158	236	66.95%	493	389	305	92	166	88
7	Wild	2	2	0	0	0	0	0	0	13	3	10	1	1	0	0	0	0	0	0	6	1	5	1	1	0	0	0	0	0	0	7	2	5	4	1.000	13	22	35	0	0	42	27	20	1	107	216	184	198	8	30	10	8	35	4	0	0.00%	4	1	75.00%	0	318	447	71.14%	237	344	68.90%	158	236	66.95%	493	389	305	92	166	88
8	Wolves	2	2	0	0	0	0	0	0	9	2	7	1	1	0	0	0	0	0	0	6	1	5	1	1	0	0	0	0	0	0	3	1	2	4	1.000	9	12	21	0	0	42	27	20	1	61	216	184	198	8	33	13	20	36	5	1	20.00%	8	2	75.00%	0	318	447	71.14%	237	344	68.90%	158	236	66.95%	493	389	305	92	166	88
	Total	16	11	4	0	0	0	0	1	89	33	56	8	6	1	0	0	0	0	1	47	12	35	8	5	3	0	0	0	0	0	42	21	21	23	0.719	89	144	233	0	2	42	27	20	1	599	216	184	198	8	308	99	122	264	54	8	14.81%	53	17	67.92%	0	318	447	71.14%	237	344	68.90%	158	236	66.95%	493	389	305	92	166	88
	_Since Last GM Reset	16	11	4	0	0	0	0	1	89	33	56	8	6	1	0	0	0	0	1	47	12	35	8	5	3	0	0	0	0	0	42	21	21	23	0.719	89	144	233	0	2	42	27	20	1	599	216	184	198	8	308	99	122	264	54	8	14.81%	53	17	67.92%	0	318	447	71.14%	237	344	68.90%	158	236	66.95%	493	389	305	92	166	88
	_Vs Conference	16	11	4	0	0	0	0	1	89	33	56	8	6	1	0	0	0	0	1	47	12	35	8	5	3	0	0	0	0	0	42	21	21	23	0.719	89	144	233	0	2	42	27	20	1	599	216	184	198	8	308	99	122	264	54	8	14.81%	53	17	67.92%	0	318	447	71.14%	237	344	68.90%	158	236	66.95%	493	389	305	92	166	88
	_Vs Division	10	11	4	0	0	0	0	1	60	22	38	5	6	1	0	0	0	0	1	31	8	23	5	5	3	0	0	0	0	0	29	14	15	23	1.150	60	101	161	0	1	42	27	20	1	409	216	184	198	8	185	55	69	172	32	5	15.63%	32	11	65.63%	0	318	447	71.14%	237	344	68.90%	158	236	66.95%	493	389	305	92	166	88

			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	23	W1	89	144	233	599	308	99	122	264	0	2

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
16	11	4	0	0	0	1	89	33

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	6	1	0	0	0	1	47	12

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	5	3	0	0	0	0	42	21

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
6	4	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
54	8	14.81%	53	17	67.92%	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
216	184	198	8	42	27	20	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
318	447	71.14%	237	344	68.90%	158	236	66.95%

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
493	389	305	92	166	88

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	12	Wild	1	Moose	6	W			Sommaire du Match
2 - 2021-10-19	25	Moose	3	Wolves	1	W			Sommaire du Match
4 - 2021-10-21	37	Admirals	4	Moose	3	L	X	X	Sommaire du Match
5 - 2021-10-22	52	Moose	11	Stars	0	W			Sommaire du Match
6 - 2021-10-23	64	Moose	7	Rampage	1	W			Sommaire du Match
7 - 2021-10-24	83	Americans	0	Moose	3	W			Sommaire du Match
8 - 2021-10-25	103	Moose	7	Wild	2	W			Sommaire du Match
9 - 2021-10-26	116	Wolves	1	Moose	6	W			Sommaire du Match
10 - 2021-10-27	128	Moose	8	Mariners	2	W			Sommaire du Match
12 - 2021-10-29	146	IceHogs	1	Moose	0	L			Sommaire du Match
13 - 2021-10-30	156	Moose	2	Admirals	6	L			Sommaire du Match
14 - 2021-10-31	166	Moose	2	IceHogs	5	L			Sommaire du Match
16 - 2021-11-02	187	Stars	1	Moose	12	W			Sommaire du Match
18 - 2021-11-04	211	Rampage	1	Moose	10	W			Sommaire du Match
19 - 2021-11-05	221	Moose	2	Americans	4	L			Sommaire du Match
22 - 2021-11-08	251	Mariners	3	Moose	7	W			Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité	2000	1000
Prix des Billets	33	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$	1,695,900$	1,682,650$	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

	Moose
	GP: 16 \| W: 11 \| L: 4 \| OTL: 1 \| P: 23 GF: 89 \| GA: 33 \| PP%: 14.81% \| PK%: 67.92% DG: Mika \| Morale : 50 \| Moyenne d'Équipe : 60