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
1	Eeli Tolvanen		X	X		100.00	75	68	90	67	68	76	80	60	50	52	63	64	60	44	44	65	50	61	0
2	Carsen Twarynski (R)		X			100.00	92	46	91	66	73	57	75	56	26	50	58	64	25	45	45	62	50	59	0
3	Jansen Harkins (R)	X				100.00	61	41	94	67	68	57	82	57	26	63	58	58	25	53	53	61	50	59	0
4	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
5	Clark Bishop	X				100.00	69	70	68	61	70	70	75	54	68	53	48	62	46	56	57	55	50	58	0
6	Joona Koppanen	X	X			100.00	78	73	89	63	73	63	65	56	70	50	58	64	55	44	44	60	50	58	0
7	Ryan Gropp		X			100.00	79	72	94	68	72	66	70	51	50	49	48	63	46	44	44	57	50	57	0
8	Brett Pollock		X	X		100.00	78	74	87	68	74	49	50	51	50	48	46	65	44	54	54	54	50	56	0
9	Rasmus Kupari (R)	X				100.00	75	69	89	65	69	55	56	53	66	43	58	62	55	44	44	59	50	56	0
10	Brett Pollock (R)		X	X		100.00	55	55	55	55	55	55	55	55	55	55	55	55	55	55	55	55	50	54	1
11	Ryan Lindgren				X	100.00	81	55	78	61	72	70	86	58	25	56	47	79	25	51	51	62	50	65	0
12	Guillaume Brisebois				X	100.00	70	67	78	68	67	65	70	49	25	41	41	60	39	51	51	53	50	58	0
13	Olli Juolevi				X	100.00	74	69	84	68	69	54	54	54	25	54	40	62	38	44	44	54	50	58	0
14	Joni Tuulola				X	100.00	75	70	88	66	70	65	71	45	25	35	40	60	38	44	44	52	50	57	0
15	Brian Strait				X	100.00	76	75	77	65	75	53	57	42	25	28	39	62	37	54	54	49	50	56	0
Rayé
1	Scott Wilson		X			100.00	71	66	83	73	66	58	58	62	50	56	61	66	58	58	59	63	50	61	0
2	Markus Hannikainen		X	X		100.00	79	72	94	64	72	59	59	62	50	58	60	67	57	49	50	64	50	60	0
3	David Kase (R)	X	X	X		100.00	71	63	91	62	63	63	66	55	69	52	53	60	50	44	44	58	50	56	0
4	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

	MOYENNE D'ÉQUIPE					100.00	74	66	84	65	70	61	67	54	45	49	51	63	45	49	49	58	50	58

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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	Connor Ingram	100.00	69	64	80	76	70	71	72	77	73	73	30	44	44	70	50	68	0
2	Vitek Vanecek	100.00	63	63	79	68	63	65	64	70	65	65	30	44	44	64	50	63	0
Rayé
1	Veini Vehvilainen	100.00	54	65	81	69	51	59	53	59	56	55	30	44	44	56	50	57	0
2	Jeremy Helvig (R)	100.00	47	52	65	84	43	45	53	55	47	48	30	44	44	49	50	52	0

	MOYENNE D'ÉQUIPE	100.00	58	61	76	74	57	60	61	65	60	60	30	44	44	60	50	60

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Sheldon Brookbank	34	44	32	54	47	35	41	CAN	30	1	700,000$

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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	Eeli Tolvanen	Moose (WPG)	LW/RW	30	24	20	44	37	26	0	50	53	135	42	102	17.78%	2	703	23.45	3	4	7	9	74	3	1	4	7	115	6	0	63.67%	245	2	1.25	0	1	0	0	0	5	5	2
2	Jansen Harkins	Moose (WPG)	C	30	17	26	43	29	4	0	10	48	96	26	73	17.71%	0	583	19.45	3	6	9	13	76	1	0	1	2	75	1	0	53.80%	526	0	1.47	0	1	0	0	0	2	3	3
3	Eetu Luostarinen	Jets	C	30	12	30	42	37	8	0	31	66	98	30	63	12.24%	5	645	21.52	1	5	6	5	77	1	3	4	8	124	4	0	68.49%	568	0	1.30	0	1	0	0	0	3	4	4
4	Beck Malenstyn	Moose (WPG)	LW	30	15	25	40	36	10	0	28	35	106	24	59	14.15%	3	526	17.55	0	4	4	1	13	0	2	2	3	71	2	0	45.10%	51	1	1.52	0	0	0	0	0	2	3	3
5	Joona Koppanen	Moose (WPG)	C/LW	30	15	21	36	31	8	0	27	61	103	25	63	14.56%	5	477	15.93	1	0	1	1	14	0	0	0	0	25	1	1	68.97%	348	1	1.51	0	1	0	0	0	3	1	2
6	Ryan Lindgren	Moose (WPG)	D	30	11	24	35	33	30	0	62	25	52	16	30	21.15%	26	664	22.17	6	2	8	27	78	0	1	1	1	103	2	0	0.00%	0	0	1.05	0	0	0	0	0	2	2	2
7	Brett Pollock	Moose (WPG)	LW/RW	30	8	22	30	33	23	5	41	18	57	13	56	14.04%	2	498	16.62	1	4	5	5	66	0	0	0	0	3	2	0	57.89%	19	0	1.20	0	0	0	0	1	2	0	1
8	Carsen Twarynski	Moose (WPG)	LW	30	12	16	28	27	50	0	86	42	107	28	73	11.21%	6	570	19.02	1	6	7	7	77	0	0	0	3	59	1	0	56.67%	30	0	0.98	0	1	0	0	0	2	2	1
9	Brett Pollock	Moose (WPG)	LW/RW	30	11	14	25	27	8	0	26	18	63	18	47	17.46%	2	502	16.75	2	2	4	9	75	0	0	0	0	1	3	0	79.31%	29	0	0.99	1	1	0	0	0	1	1	1
10	Clark Bishop	Moose (WPG)	C	30	8	17	25	34	20	0	41	27	61	19	33	13.11%	5	507	16.93	0	0	0	0	3	0	0	0	0	0	0	0	66.36%	110	0	0.98	0	0	0	0	0	0	2	1
11	Guillaume Brisebois	Moose (WPG)	D	30	2	18	20	34	20	0	51	21	25	11	23	8.00%	20	635	21.18	1	6	7	7	70	0	2	2	2	108	0	0	0.00%	0	0	0.63	0	0	0	0	0	0	0	1
12	Ryan Gropp	Moose (WPG)	LW	30	1	18	19	31	18	0	40	16	18	3	18	5.56%	7	494	16.47	0	0	0	0	1	0	0	0	0	0	1	0	75.00%	4	0	0.77	0	0	0	0	0	0	0	1
13	Joni Tuulola	Moose (WPG)	D	30	4	6	10	32	24	0	47	8	27	9	14	14.81%	12	640	21.36	2	3	5	10	72	0	0	0	0	107	0	0	0.00%	0	0	0.31	0	0	0	0	0	0	0	1
14	Olli Juolevi	Moose (WPG)	D	30	1	9	10	35	14	0	27	10	13	7	9	7.69%	11	637	21.24	0	2	2	6	72	0	0	0	0	97	0	0	100.00%	1	0	0.31	0	0	0	0	0	0	0	0
15	Brian Strait	Moose (WPG)	D	30	3	6	9	30	48	20	60	8	15	5	9	20.00%	22	510	17.02	0	0	0	2	24	0	0	0	0	49	0	0	0.00%	0	0	0.35	0	0	2	2	0	0	1	0
16	Rasmus Kupari	Moose (WPG)	C	30	4	0	4	2	2	0	9	9	20	2	8	20.00%	4	143	4.77	3	0	3	8	25	0	0	0	1	32	0	1	64.00%	25	0	0.56	0	1	0	0	0	0	1	0
Stats d'équipe Total ou en Moyenne				480	148	272	420	488	313	25	636	465	996	278	680	14.86%	132	8743	18.22	24	44	68	110	823	5	9	14	27	979	23	2	63.14%	1956	4	0.96	1	7	2	2	1	22	25	23

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

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	PCT	GAA	MP	SO	GA	SA	A	PS %	PSA	ST	BG	S1
1	Connor Ingram	Moose (WPG)	30	24	6	0.912	1.32	1771	8	39	444	2	1.000	7	30	0	2
2	Vitek Vanecek	Moose (WPG)	1	0	0	0.938	1.58	38	0	1	16	0	0.000	0	0	30	0
Stats d'équipe Total ou en Moyenne			31	24	6	0.913	1.33	1809	8	40	460	2	1.000	7	30	30	2

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

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	Link
Beck Malenstyn	Moose (WPG)	LW	22	1998-02-04	Yes	194 Lbs	6 ft2	No	No	No	3	Pro & Farm	736,666$	736,666$	0$	0$	No	736,666$	736,666$	Lien / Lien NHL
Brett Pollock	Moose (WPG)	LW/RW	24	1996-03-17 3:34:58 PM	Yes	194 Lbs	6 ft3	No	No	No	3	Pro & Farm	894,167$	894,167$	0$	0$	No	894,167$	894,167$
Brett Pollock	Moose (WPG)	LW/RW	24	1996-03-17	No	195 Lbs	6 ft3	No	No	No	3	Pro & Farm	894,167$	894,167$	0$	0$	No	894,167$	894,167$	Lien
Brian Strait	Moose (WPG)	D	32	1988-01-03	No	206 Lbs	6 ft1	No	No	No	1	Pro & Farm	675,000$	675,000$	0$	0$	No			Lien
Carsen Twarynski	Moose (WPG)	LW	22	1997-11-24	Yes	198 Lbs	6 ft2	No	No	No	3	Pro & Farm	775,833$	775,833$	0$	0$	No	775,833$	775,833$	Lien / Lien NHL
Clark Bishop	Moose (WPG)	C	24	1996-03-29	No	194 Lbs	6 ft0	No	No	No	2	Pro & Farm	713,333$	713,333$	0$	0$	No	713,333$		Lien / Lien NHL
Connor Ingram	Moose (WPG)	G	23	1997-03-31	No	204 Lbs	6 ft1	No	No	No	3	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	925,000$	Lien / Lien NHL
David Kase	Moose (WPG)	C/LW/RW	23	1997-01-28	Yes	170 Lbs	5 ft11	No	No	No	3	Pro & Farm	768,333$	768,333$	0$	0$	No	768,333$	768,333$	Lien / Lien NHL
Eeli Tolvanen	Moose (WPG)	LW/RW	21	1999-04-22	No	191 Lbs	5 ft10	No	No	No	1	Pro & Farm	3,115,000$	3,115,000$	0$	0$	No			Lien / Lien NHL
Guillaume Brisebois	Moose (WPG)	D	23	1997-07-21	No	175 Lbs	6 ft2	No	No	No	2	Pro & Farm	888,333$	888,333$	0$	0$	No	888,333$		Lien / Lien NHL
Jansen Harkins	Moose (WPG)	C	23	1997-05-23	Yes	182 Lbs	6 ft1	No	No	No	3	Pro & Farm	767,500$	767,500$	0$	0$	No	767,500$	767,500$	Lien / Lien NHL
Jeremy Helvig	Moose (WPG)	G	23	1997-05-24	Yes	207 Lbs	6 ft4	No	No	No	3	Pro & Farm	785,000$	785,000$	0$	0$	No	785,000$	785,000$	Lien / Lien NHL
Joni Tuulola	Moose (WPG)	D	24	1996-01-01	No	181 Lbs	6 ft3	No	No	No	3	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	925,000$	Lien / Lien NHL
Joona Koppanen	Moose (WPG)	C/LW	22	1998-02-25	No	192 Lbs	6 ft3	No	No	No	3	Pro & Farm	910,833$	910,833$	0$	0$	No	910,833$	910,833$	Lien / Lien NHL
Markus Hannikainen	Moose (WPG)	LW/RW	27	1993-03-25	No	190 Lbs	6 ft2	No	No	No	1	Pro & Farm	825,000$	825,000$	0$	0$	No			Lien / Lien NHL
Matheson Iacopelli	Moose (WPG)	LW/RW	26	1994-05-15	No	207 Lbs	6 ft2	No	No	No	3	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	925,000$	Lien
Olli Juolevi	Moose (WPG)	D	22	1998-05-04	No	182 Lbs	6 ft2	No	No	No	3	Pro & Farm	1,913,333$	1,913,333$	0$	0$	No	1,913,333$	1,913,333$	Lien / Lien NHL
Rasmus Kupari	Moose (WPG)	C	20	2000-03-15	Yes	185 Lbs	6 ft1	No	No	No	3	Pro & Farm	1,081,667$	1,081,667$	0$	0$	No	1,081,667$	1,081,667$	Lien / Lien NHL
Ryan Gropp	Moose (WPG)	LW	24	1996-09-16	No	190 Lbs	6 ft2	No	No	No	3	Pro & Farm	888,333$	888,333$	0$	0$	No	888,333$	888,333$	Lien / Lien NHL
Ryan Lindgren	Moose (WPG)	D	22	1998-02-10	No	198 Lbs	6 ft0	No	No	No	2	Pro & Farm	1,100,000$	1,100,000$	0$	0$	No	1,100,000$		Lien / Lien NHL
Scott Wilson	Moose (WPG)	LW	28	1992-04-24	No	183 Lbs	5 ft11	No	No	No	1	Pro & Farm	1,200,000$	1,200,000$	0$	0$	No			Lien / Lien NHL
Veini Vehvilainen	Moose (WPG)	G	23	1997-02-13	No	183 Lbs	6 ft1	No	No	No	3	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	925,000$	Lien / Lien NHL
Vitek Vanecek	Moose (WPG)	G	24	1996-01-08	No	180 Lbs	6 ft1	No	No	No	3	Pro & Farm	1,000,000$	1,000,000$	0$	0$	No	1,000,000$	1,000,000$	Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
23	23.74	190 Lbs	6 ft1	2.52	1,027,500$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Eeli Tolvanen		Brett Pollock	40	1	2	2
2	Carsen Twarynski	Jansen Harkins	Brett Pollock	30	1	2	2
3	Beck Malenstyn	Joona Koppanen	Clark Bishop	20	1	2	2
4	Ryan Gropp	Clark Bishop	Eeli Tolvanen	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Ryan Lindgren	Olli Juolevi	40	1	2	2
2	Guillaume Brisebois	Joni Tuulola	30	1	2	2
3	Brian Strait	Ryan Gropp	20	1	2	2
4	Ryan Lindgren	Olli Juolevi	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Eeli Tolvanen		Brett Pollock	60	1	2	2
2	Carsen Twarynski	Jansen Harkins	Brett Pollock	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Ryan Lindgren	Olli Juolevi	60	1	2	2
2	Guillaume Brisebois	Joni Tuulola	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Eeli Tolvanen		60	1	2	2
2	Jansen Harkins	Carsen Twarynski	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Ryan Lindgren	Olli Juolevi	60	1	2	2
2	Guillaume Brisebois	Joni Tuulola	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Eeli Tolvanen	60	1	2	2	Ryan Lindgren	Olli Juolevi	60	1	2	2
2		40	1	2	2	Guillaume Brisebois	Joni Tuulola	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Eeli Tolvanen		60	1	2	2
2	Jansen Harkins	Carsen Twarynski	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Ryan Lindgren	Olli Juolevi	60	1	2	2
2	Guillaume Brisebois	Joni Tuulola	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Eeli Tolvanen		Brett Pollock	Ryan Lindgren	Olli Juolevi

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Eeli Tolvanen		Brett Pollock	Ryan Lindgren	Olli Juolevi

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

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Brian Strait, Guillaume Brisebois, Joni Tuulola	Brian Strait	Guillaume Brisebois, Joni Tuulola

Tirs de Pénalité
Eeli Tolvanen, , Jansen Harkins, Carsen Twarynski, Joona Koppanen

Gardien
#1 : Connor Ingram, #2 : Vitek Vanecek

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	Americans	2	1	0	0	0	0	1	0	5	3	2	1	1	0	0	0	0	0	0	2	1	1	1	0	0	0	0	0	1	0	3	2	1	4	1.000	5	6	11	0	0	74	41	32	2	32	336	342	315	10	41	18	25	41	13	1	7.69%	10	2	80.00%	0	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
2	Admirals	2	2	0	0	0	0	0	0	13	0	13	1	1	0	0	0	0	0	0	9	0	9	1	1	0	0	0	0	0	0	4	0	4	4	1.000	13	23	36	0	2	74	41	32	2	84	336	342	315	10	16	5	20	41	3	2	66.67%	10	0	100.00%	0	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
3	Barracudas	2	0	1	0	1	0	0	0	6	7	-1	1	0	1	0	0	0	0	0	3	5	-2	1	0	0	0	1	0	0	0	3	2	1	2	0.500	6	10	16	0	0	74	41	32	2	56	336	342	315	10	60	19	18	35	12	2	16.67%	9	1	88.89%	0	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
4	Condors	2	0	2	0	0	0	0	0	2	6	-4	1	0	1	0	0	0	0	0	1	3	-2	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	2	4	6	0	0	74	41	32	2	22	336	342	315	10	50	6	41	39	12	0	0.00%	11	2	81.82%	1	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
5	Eagles	2	2	0	0	0	0	0	0	20	3	17	1	1	0	0	0	0	0	0	9	2	7	1	1	0	0	0	0	0	0	11	1	10	4	1.000	20	38	58	0	0	74	41	32	2	97	336	342	315	10	15	4	24	37	3	1	33.33%	12	1	91.67%	0	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
6	Gulls	4	4	0	0	0	0	0	0	23	1	22	2	2	0	0	0	0	0	0	11	0	11	2	2	0	0	0	0	0	0	12	1	11	8	1.000	23	42	65	0	3	74	41	32	2	172	336	342	315	10	54	14	33	105	9	1	11.11%	13	1	92.31%	2	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
7	Heat	2	0	2	0	0	0	0	0	3	7	-4	1	0	1	0	0	0	0	0	1	4	-3	1	0	1	0	0	0	0	0	2	3	-1	0	0.000	3	6	9	0	0	74	41	32	2	29	336	342	315	10	49	12	22	27	9	2	22.22%	10	3	70.00%	0	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
8	IceHogs	2	1	1	0	0	0	0	0	4	4	0	1	1	0	0	0	0	0	0	3	2	1	1	0	1	0	0	0	0	0	1	2	-1	2	0.500	4	8	12	0	0	74	41	32	2	42	336	342	315	10	33	9	34	47	8	1	12.50%	15	3	80.00%	0	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
9	Rampage	2	2	0	0	0	0	0	0	13	2	11	1	1	0	0	0	0	0	0	5	1	4	1	1	0	0	0	0	0	0	8	1	7	4	1.000	13	25	38	0	0	74	41	32	2	77	336	342	315	10	18	6	6	41	4	1	25.00%	3	1	66.67%	0	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
10	Reign	2	2	0	0	0	0	0	0	15	2	13	1	1	0	0	0	0	0	0	8	1	7	1	1	0	0	0	0	0	0	7	1	6	4	1.000	15	29	44	0	0	74	41	32	2	97	336	342	315	10	14	8	14	51	3	2	66.67%	7	0	100.00%	1	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
11	Roadrunners	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	22	34	0	0	74	41	32	2	83	336	342	315	10	29	9	28	52	9	5	55.56%	13	1	92.31%	1	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
12	Stars	2	2	0	0	0	0	0	0	14	1	13	1	1	0	0	0	0	0	0	7	0	7	1	1	0	0	0	0	0	0	7	1	6	4	1.000	14	25	39	0	1	74	41	32	2	86	336	342	315	10	20	9	14	33	10	3	30.00%	7	0	100.00%	0	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
	Total	30	22	6	0	1	0	1	0	149	40	109	15	12	3	0	0	0	0	0	76	21	55	15	10	3	0	1	0	1	0	73	19	54	48	0.800	149	272	421	0	8	74	41	32	2	996	336	342	315	10	460	132	313	636	105	24	22.86%	137	15	89.05%	5	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
14	Wild	2	2	0	0	0	0	0	0	15	2	13	1	1	0	0	0	0	0	0	9	1	8	1	1	0	0	0	0	0	0	6	1	5	4	1.000	15	28	43	0	0	74	41	32	2	89	336	342	315	10	31	8	12	55	2	1	50.00%	6	0	100.00%	0	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
15	Wolves	2	2	0	0	0	0	0	0	4	0	4	1	1	0	0	0	0	0	0	2	0	2	1	1	0	0	0	0	0	0	2	0	2	4	1.000	4	6	10	0	2	74	41	32	2	30	336	342	315	10	30	5	22	32	8	2	25.00%	11	0	100.00%	0	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
	_Since Last GM Reset	30	22	6	0	1	0	1	0	149	40	109	15	12	3	0	0	0	0	0	76	21	55	15	10	3	0	1	0	1	0	73	19	54	48	0.800	149	272	421	0	8	74	41	32	2	996	336	342	315	10	460	132	313	636	105	24	22.86%	137	15	89.05%	5	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
	_Vs Conference	30	22	6	0	1	0	1	0	149	40	109	15	12	3	0	0	0	0	0	76	21	55	15	10	3	0	1	0	1	0	73	19	54	48	0.800	149	272	421	0	8	74	41	32	2	996	336	342	315	10	460	132	313	636	105	24	22.86%	137	15	89.05%	5	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
	_Vs Division	12	12	1	0	0	0	1	0	79	12	67	6	7	0	0	0	0	0	0	42	6	36	6	5	1	0	0	0	1	0	37	6	31	26	1.083	79	147	226	0	3	74	41	32	2	475	336	342	315	10	133	41	110	254	30	9	30.00%	53	5	90.57%	0	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203

			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
30	48	W8	149	272	421	996	460	132	313	636	0	8

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
30	22	6	1	0	1	0	149	40

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
15	12	3	0	0	0	0	76	21

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
15	10	3	1	0	1	0	73	19

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
9	0	1	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
105	24	22.86%	137	15	89.05%	5

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
336	342	315	10	74	41	32	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
568	856	66.36%	387	665	58.20%	280	436	64.22%

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
981	750	484	164	344	203

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 - 2020-10-24	7	Moose	4	Gulls	1	W			Sommaire du Match
2 - 2020-10-25	18	Gulls	0	Moose	8	W			Sommaire du Match
3 - 2020-10-26	41	Moose	8	Gulls	0	W			Sommaire du Match
4 - 2020-10-27	49	Admirals	0	Moose	9	W			Sommaire du Match
5 - 2020-10-28	75	Wild	1	Moose	9	W			Sommaire du Match
6 - 2020-10-29	84	Moose	4	Admirals	0	W			Sommaire du Match
7 - 2020-10-30	96	Moose	2	Heat	3	L			Sommaire du Match
9 - 2020-11-01	111	Condors	3	Moose	1	L			Sommaire du Match
10 - 2020-11-02	131	Moose	1	Condors	3	L			Sommaire du Match
11 - 2020-11-03	146	Wolves	0	Moose	2	W			Sommaire du Match
12 - 2020-11-04	158	Moose	7	Stars	1	W			Sommaire du Match
13 - 2020-11-05	168	Moose	11	Eagles	1	W			Sommaire du Match
14 - 2020-11-06	185	Gulls	0	Moose	3	W			Sommaire du Match
16 - 2020-11-08	209	Barracudas	5	Moose	3	L			Sommaire du Match
17 - 2020-11-09	225	Moose	6	Wild	1	W			Sommaire du Match
18 - 2020-11-10	232	Americans	1	Moose	2	W			Sommaire du Match
19 - 2020-11-11	250	Moose	1	IceHogs	2	L			Sommaire du Match
20 - 2020-11-12	264	Rampage	1	Moose	5	W			Sommaire du Match
22 - 2020-11-14	279	Moose	3	Americans	2	W	X	X	Sommaire du Match
23 - 2020-11-15	300	Heat	4	Moose	1	L			Sommaire du Match
24 - 2020-11-16	305	Moose	8	Rampage	1	W			Sommaire du Match
25 - 2020-11-17	326	Moose	3	Barracudas	2	W	X		Sommaire du Match
26 - 2020-11-18	338	Roadrunners	1	Moose	6	W			Sommaire du Match
28 - 2020-11-20	358	Reign	1	Moose	8	W			Sommaire du Match
29 - 2020-11-21	371	Moose	2	Wolves	0	W			Sommaire du Match
30 - 2020-11-22	390	Stars	0	Moose	7	W			Sommaire du Match
32 - 2020-11-24	413	Eagles	2	Moose	9	W			Sommaire du Match
33 - 2020-11-25	424	Moose	7	Reign	1	W			Sommaire du Match
37 - 2020-11-29	442	IceHogs	2	Moose	3	W			Sommaire du Match
38 - 2020-11-30	453	Moose	6	Roadrunners	1	W			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	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 de l'Aréna	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$	2,363,249$	2,363,249$	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
2020	30	22	6	0	1	0	1	0	149	40	109	15	12	3	0	0	0	0	0	76	21	55	15	10	3	0	1	0	1	0	73	19	54	48	149	272	421	0	8	74	41	32	2	996	336	342	315	10	460	132	313	636	105	24	22.86%	137	15	89.05%	5	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203
Total Saison Régulière	30	22	6	0	1	0	1	0	149	40	109	15	12	3	0	0	0	0	0	76	21	55	15	10	3	0	1	0	1	0	73	19	54	48	149	272	421	0	8	74	41	32	2	996	336	342	315	10	460	132	313	636	105	24	22.86%	137	15	89.05%	5	568	856	66.36%	387	665	58.20%	280	436	64.22%	981	750	484	164	344	203