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	Moose
	GP: 5 \| W: 1 \| L: 4 GF: 8 \| GA: 16 \| PP%: 18.75% \| PK%: 80.00% DG: Trevor Sifton \| Morale : 50 \| Moyenne d'�quipe : 65

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Jets
Formation
Points
Informations Joueurs
Lignes
Statistiques d'�quipe
Calendrier
Finance
Client Web pour Lignes


	Thunderbirds 5-5-0, 10pts	4	FINAL	3	Moose 1-4-0, 2pts

Team Stats
L1	Streak	L4
3-2-0	Home Record	0-2-0
2-3-0	Away Record	1-2-0
5-4-1	Last 10 Games	1-4-0
2.80		1.60
2.50		3.20
15.38%		18.75%
84.62%		80.00%

Moose
1-4-0, 2pts

FINAL

Thunderbirds
5-5-0, 10pts

Team Stats
L4	Streak	L1
0-2-0	Home Record	3-2-0
1-2-0	Away Record	2-3-0
1-4-0	Last 10 Games	5-4-1
1.60		2.80
3.20		2.50
18.75%		15.38%
80.00%		84.62%


	Buts Reese Johnson 3			Passes Lane Pederson 3

	Points Lane Pederson 4			Plus/Moins Axel Jonsson-Fjallby 2

	Victoires Joseph Woll 1			Pourcentage d'Arr�ts Joseph Woll 0.922

Statistiques d'�quipe
8 1.60 GFG	Tirs Pour 166 33.20 Avg	18.8% 3 GF	38.9%
Buts Contre 16 3.20 GAA	Tirs Contre 206 41.20 Avg	80.0% 1 GA	37.7%


	Directeur g�n�ral	Trevor Sifton
		Central Division
		Western Conference
		Declan Chisholm

		Lukas Reichel

	Capacit� de l'Ar�na	5,000
	Assistance	5,000
		5,000

		20
		19
		39 / 55
	�spoirs	25

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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	�ge	Contrat	Salaire Moyen
1	Lukas Reichel (R) (A)	0		X	X		100.00	67	51	97	70	84	66	55	64	43	72	73	55	68	68	68	0	50	76	0	21	2	925,000$
2	Reese Johnson (R)	24	X		X		100.00	91	52	94	71	82	47	65	55	55	66	69	72	62	62	62	0	50	76	0	24	2	907,258$
3	Lane Pederson (R)	18	X				100.00	82	55	91	72	83	50	55	58	56	67	70	55	64	64	64	0	50	73	0	25	3	990,675$
4	Axel Jonsson-Fjallby (R)	0		X			100.00	72	51	97	71	83	47	60	58	40	68	70	60	64	64	64	0	50	73	0	25	3	813,750$
5	Will Bitten (R)	14	X				100.00	52	64	83	55	54	80	93	42	65	59	64	44	53	25	40	0	50	62	0	24	2	952,750$
6	Chase De Leo	58	X	X	X		100.00	52	58	84	55	58	65	75	42	65	60	64	44	53	25	40	0	50	61	0	27	2	840,000$
7	Chris Wagner	0	X		X		100.00	54	61	81	54	54	73	84	41	65	57	64	41	53	25	40	0	50	60	0	32	1	775,000$
8	Travis Barron	0		X			100.00	55	62	79	52	53	75	87	38	36	57	64	39	51	25	40	0	50	60	0	24	1	925,000$
9	Cole Fonstad (R)	0		X			100.00	52	53	84	55	55	58	61	43	36	59	64	38	54	25	40	0	50	59	0	23	2	925,000$
10	Mike Hardman (R)	86		X	X		100.00	53	52	82	54	55	58	58	42	36	59	64	40	53	25	40	0	50	59	0	24	2	952,750$
11	Chase Pearson	22	X				100.00	53	55	82	52	53	59	68	39	65	57	64	36	51	25	40	0	50	57	0	25	2	909,090$
12	Stelio Mattheos (R)	0	X				100.00	52	60	83	51	53	69	80	36	65	56	63	33	50	25	40	0	50	57	0	24	3	841,533$
13	Ville Heinola (R)	0				X	100.00	70	53	94	71	79	51	55	60	40	69	68	55	64	64	64	0	50	72	0	22	2	925,000$
14	Declan Chisholm (R) (C)	20				X	100.00	52	57	83	56	56	62	72	43	36	62	64	43	54	25	40	0	50	61	0	23	1	925,000$
15	William Villeneuve (R)	0				X	100.00	53	57	82	54	54	63	73	40	36	60	63	44	52	25	40	0	50	60	0	21	2	817,778$
16	Matt Bartkowski	0				X	100.00	54	63	81	52	52	76	88	37	36	57	63	36	50	25	40	0	50	59	0	35	1	750,000$
17	Simon Lundmark (R)	0				X	100.00	52	59	84	52	53	67	77	38	36	58	63	39	51	25	40	0	50	58	0	22	2	850,833$
18	Mikko Kokkonen (R)	0				X	100.00	53	48	82	51	53	58	49	37	36	57	63	37	50	25	40	0	50	57	0	22	2	846,667$
Ray�

	MOYENNE D'�QUIPE						100.00	59	56	86	58	62	62	70	45	47	61	65	45	55	36	47	0	50	63

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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	�ge	Contrat	Salaire Moyen
1	Joseph Woll (R)	100.00	86	65	53	70	80	72	74	81	87	48	84	26	51	0	50	79	0	24	3	797,333$
2	Nico Daws (R)	100.00	73	65	68	77	76	75	73	76	77	74	76	25	55	0	50	77	0	22	2	850,833$
Ray�

	MOYENNE D'�QUIPE	100.00	80	65	61	74	78	74	74	79	82	61	80	26	53	0	50	78

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	�ge	Contrat	Salaire

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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'�quipe	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	GA	TA	P/20	FW	FL	FT	S1	S3
1	Lane Pederson	Moose (WIN)	C	5	1	3	4	2	0	0	13	8	16	8	11	6.25%	4	95	19.13	0	1	1	2	11	0	3	0	19.13	70	8	4	0.84	0	0	0	1	0
2	Reese Johnson	Moose (WIN)	C/RW	5	3	1	4	-4	0	0	13	17	29	7	20	10.34%	11	107	21.55	1	1	2	4	12	0	3	0	21.55	62	19	6	0.74	0	0	0	0	0
3	Axel Jonsson-Fjallby	Moose (WIN)	LW	5	3	1	4	2	0	0	8	9	27	4	17	11.11%	5	95	19.13	1	0	1	4	11	1	3	1	19.13	11	8	5	0.84	0	0	0	0	2
4	Lukas Reichel	Moose (WIN)	LW/RW	5	1	2	3	-1	0	0	7	6	15	9	16	6.67%	1	82	16.53	1	1	2	1	14	0	4	0	16.53	9	13	6	0.73	0	0	0	0	0
5	Chris Wagner	Moose (WIN)	C/RW	5	0	1	1	2	17	15	3	1	0	1	1	0.00%	1	86	17.28	0	0	0	0	11	0	0	0	17.28	5	0	0	0.23	0	0	3	0	0
6	Cole Fonstad	Moose (WIN)	LW	5	0	1	1	-3	2	0	1	2	8	4	0	0.00%	0	43	8.61	0	0	0	0	0	0	0	0	8.61	4	3	0	0.46	0	0	0	0	0
7	Stelio Mattheos	Moose (WIN)	C	5	0	1	1	-3	0	0	1	1	2	0	2	0.00%	0	43	8.62	0	0	0	0	0	0	0	0	8.62	28	3	1	0.46	0	0	0	0	0
8	Chase De Leo	Moose (WIN)	C/LW/RW	5	0	0	0	0	5	5	4	3	5	0	4	0.00%	0	75	15.09	0	0	0	2	14	0	0	0	15.09	4	1	1	0.00%	0	0	1	0	0
9	Chase Pearson	Moose (WIN)	C	5	0	0	0	-2	0	0	2	4	2	0	0	0.00%	0	32	6.40	0	0	0	0	2	0	0	0	6.40	16	0	1	0.00%	0	0	0	0	0
10	Simon Lundmark	Moose (WIN)	D	5	0	0	0	-2	2	0	1	6	2	2	2	0.00%	3	77	15.46	0	0	0	0	0	0	0	0	0.00%	0	2	2	0.00%	0	0	0	0	0
11	Matt Bartkowski	Moose (WIN)	D	5	0	0	0	-5	7	5	3	1	1	0	2	0.00%	3	101	20.38	0	0	0	1	12	0	3	0	0.00%	0	0	2	0.00%	0	1	0	0	0
12	Mikko Kokkonen	Moose (WIN)	D	5	0	0	0	-2	0	0	3	8	4	0	1	0.00%	5	76	15.29	0	0	0	0	0	0	2	0	0.00%	0	0	2	0.00%	0	0	0	0	0
13	Travis Barron	Moose (WIN)	LW	5	0	0	0	-8	0	0	5	8	8	4	3	0.00%	3	79	15.97	0	0	0	0	0	0	0	0	15.97	4	4	2	0.00%	0	0	0	0	0
14	Ville Heinola	Moose (WIN)	D	5	0	0	0	-3	0	0	8	15	14	12	12	0.00%	8	120	24.01	0	0	0	1	12	0	3	0	0.00%	0	6	6	0.00%	0	0	0	0	0
15	Will Bitten	Moose (WIN)	C	5	0	0	0	-7	35	35	4	5	10	3	10	0.00%	0	70	14.12	0	0	0	0	0	0	0	0	14.12	41	7	4	0.00%	2	1	4	0	0
16	Mike Hardman	Moose (WIN)	LW/RW	5	0	0	0	-8	0	0	6	9	15	5	4	0.00%	2	78	15.72	0	0	0	0	0	0	0	0	15.72	3	5	2	0.00%	0	0	0	0	0
17	William Villeneuve	Moose (WIN)	D	5	0	0	0	-5	2	0	6	6	4	4	0	0.00%	13	105	21.00	0	0	0	0	13	0	3	0	0.00%	0	2	6	0.00%	0	0	0	0	0
18	Declan Chisholm	Moose (WIN)	D	5	0	0	0	-3	0	0	4	3	4	3	3	0.00%	8	120	24.01	0	0	0	2	12	0	3	0	0.00%	0	0	2	0.00%	0	0	0	0	0
Stats d'�quipe Total ou en Moyenne				90	8	10	18	-50	70	60	92	112	166	66	108	4.82%	67	1491	16.57	3	3	6	17	131	1	32	1	51.75%	257	81	52	0.24	2	2	8	1	2

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	Nom de l'�quipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Joseph Woll	Moose (WIN)	5	1	4	0	0.922	3.21	299	0	1	16	206	125	0	0	0.00%	0	5	0	1	1	0
Stats d'�quipe Total ou en Moyenne			5	1	4	0	0.922	3.21	299	0	1	16	206	125	0	0	0.000	0	5	0	1	1	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'�quipe	POS	�ge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-�change	Disponible pour �change	Ballotage Forc�	Contrat	Type	Salaire Actuel	Salaire Restant	Salaire Moyen	Salaire Moyen Restant	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Ann�e 2	Salaire Ann�e 3	Link
Axel Jonsson-Fjallby	Moose (WIN)	LW	25	1998-02-10	Yes	194 Lbs	6 ft1	No	No	No	3	Pro & Farm	813,750$	271,250$	813,750$	271,250$	0$	0$	No	813,750$	813,750$	Lien / Lien NHL
Chase De Leo	Moose (WIN)	C/LW/RW	27	1995-10-25	No	185 Lbs	5 ft9	No	No	No	2	Pro & Farm	840,000$	280,000$	840,000$	280,000$	0$	0$	No	840,000$		Lien / Lien NHL
Chase Pearson	Moose (WIN)	C	25	1997-08-23	No	202 Lbs	6 ft3	No	No	No	2	Pro & Farm	909,090$	303,030$	909,090$	303,030$	0$	0$	No	909,090$		Lien / Lien NHL
Chris Wagner	Moose (WIN)	C/RW	32	1991-05-27	No	191 Lbs	6 ft0	No	No	No	1	Pro & Farm	775,000$	258,333$	775,000$	258,333$	0$	0$	No			Lien / Lien NHL
Cole Fonstad	Moose (WIN)	LW	23	2000-04-24	Yes	165 Lbs	5 ft10	No	No	No	2	Pro & Farm	925,000$	308,333$	925,000$	308,333$	0$	0$	No	925,000$		Lien / Lien NHL
Declan Chisholm	Moose (WIN)	D	23	2000-01-12	Yes	185 Lbs	6 ft1	No	No	No	1	Pro & Farm	925,000$	308,333$	925,000$	308,333$	0$	0$	No			Lien / Lien NHL
Joseph Woll	Moose (WIN)	G	24	1998-07-12	Yes	203 Lbs	6 ft4	No	No	No	3	Pro & Farm	797,333$	265,778$	797,333$	265,778$	0$	0$	No	797,333$	797,333$	Lien / Lien NHL
Lane Pederson	Moose (WIN)	C	25	1997-08-04	Yes	190 Lbs	6 ft0	No	No	No	3	Pro & Farm	990,675$	330,225$	990,675$	330,225$	0$	0$	No	990,675$	990,675$	Lien / Lien NHL
Lukas Reichel	Moose (WIN)	LW/RW	21	2002-05-17	Yes	170 Lbs	6 ft0	No	No	No	2	Pro & Farm	925,000$	308,333$	925,000$	308,333$	0$	0$	No	925,000$		Lien / Lien NHL
Matt Bartkowski	Moose (WIN)	D	35	1988-06-04	No	201 Lbs	6 ft1	No	No	No	1	Pro & Farm	750,000$	250,000$	750,000$	250,000$	0$	0$	No			Lien / Lien NHL
Mike Hardman	Moose (WIN)	LW/RW	24	1999-02-05	Yes	205 Lbs	6 ft2	No	No	No	2	Pro & Farm	952,750$	317,583$	952,750$	317,583$	0$	0$	No	952,750$		Lien / Lien NHL
Mikko Kokkonen	Moose (WIN)	D	22	2001-01-18	Yes	198 Lbs	6 ft2	No	No	No	2	Pro & Farm	846,667$	282,222$	846,667$	282,222$	0$	0$	No	846,667$		Lien / Lien NHL
Nico Daws	Moose (WIN)	G	22	2000-12-22	Yes	203 Lbs	6 ft4	No	No	No	2	Pro & Farm	850,833$	283,611$	850,833$	283,611$	0$	0$	No	850,833$		Lien / Lien NHL
Reese Johnson	Moose (WIN)	C/RW	24	1998-07-10	Yes	193 Lbs	6 ft1	No	No	No	2	Pro & Farm	907,258$	302,419$	907,258$	302,419$	0$	0$	No	907,258$		Lien / Lien NHL
Simon Lundmark	Moose (WIN)	D	22	2000-10-08	Yes	201 Lbs	6 ft2	No	No	No	2	Pro & Farm	850,833$	283,611$	850,833$	283,611$	0$	0$	No	850,833$		Lien / Lien NHL
Stelio Mattheos	Moose (WIN)	C	24	1999-06-14	Yes	196 Lbs	6 ft1	No	No	No	3	Pro & Farm	841,533$	280,511$	841,533$	280,511$	0$	0$	No	841,533$	841,533$	Lien / Lien NHL
Travis Barron	Moose (WIN)	LW	24	1998-08-17	No	205 Lbs	6 ft1	No	No	No	1	Pro & Farm	925,000$	308,333$	925,000$	308,333$	0$	0$	No			Lien / Lien NHL
Ville Heinola	Moose (WIN)	D	22	2001-03-02	Yes	178 Lbs	5 ft11	No	No	No	2	Pro & Farm	925,000$	308,333$	925,000$	308,333$	0$	0$	No	925,000$		Lien / Lien NHL
Will Bitten	Moose (WIN)	C	24	1998-07-10	Yes	180 Lbs	5 ft11	No	No	No	2	Pro & Farm	952,750$	317,583$	952,750$	317,583$	0$	0$	No	952,750$		Lien / Lien NHL
William Villeneuve	Moose (WIN)	D	21	2002-03-20	Yes	184 Lbs	6 ft2	No	No	No	2	Pro & Farm	817,778$	272,593$	817,778$	272,593$	0$	0$	No	817,778$		Lien / Lien NHL

Joueurs Total	�ge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Ann�e
20	24.45	191 Lbs	6 ft1	2.00	876,063$

Attaque � 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Lukas Reichel	Reese Johnson	Chase De Leo	30	1	2	2
2	Axel Jonsson-Fjallby	Lane Pederson	Chris Wagner	30	1	2	2
3	Travis Barron	Will Bitten	Mike Hardman	20	1	2	2
4	Cole Fonstad	Stelio Mattheos	Reese Johnson	20	1	2	2

D�fense � 5 contre 5
Ligne #	D�fense	D�fense	% Temps	PHY	DF	OF
1	Ville Heinola	Declan Chisholm	30	1	2	2
2	William Villeneuve	Matt Bartkowski	30	1	2	2
3	Simon Lundmark	Mikko Kokkonen	20	1	2	2
4	Ville Heinola	Declan Chisholm	20	1	2	2

Attaque en Avantage Num�rique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Lukas Reichel	Reese Johnson	Chase De Leo	50	1	2	2
2	Axel Jonsson-Fjallby	Lane Pederson	Chris Wagner	50	1	2	2

D�fense en Avantage Num�rique
Ligne #	D�fense	D�fense	% Temps	PHY	DF	OF
1	Ville Heinola	Declan Chisholm	50	1	2	2
2	William Villeneuve	Matt Bartkowski	50	1	2	2

Attaque � 4 en D�savantage Num�rique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Reese Johnson	Lukas Reichel	50	1	2	2
2	Axel Jonsson-Fjallby	Lane Pederson	50	1	2	2

D�fense � 4 en D�savantage Num�rique
Ligne #	D�fense	D�fense	% Temps	PHY	DF	OF
1	Ville Heinola	Declan Chisholm	50	1	2	2
2	William Villeneuve	Matt Bartkowski	50	1	2	2

3 joueurs en D�savantage Num�rique
Ligne #	Ailier	% Temps	PHY	DF	OF	D�fense	D�fense	% Temps	PHY	DF	OF
1	Reese Johnson	50	1	2	2	Ville Heinola	Declan Chisholm	50	1	2	2
2	Lukas Reichel	50	1	2	2	William Villeneuve	Matt Bartkowski	50	1	2	2

Attaque � 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Reese Johnson	Lukas Reichel	50	1	2	2
2	Axel Jonsson-Fjallby	Lane Pederson	50	1	2	2

D�fense � 4 contre 4
Ligne #	D�fense	D�fense	% Temps	PHY	DF	OF
1	Ville Heinola	Declan Chisholm	50	1	2	2
2	William Villeneuve	Matt Bartkowski	50	1	2	2

Attaque Derni�re Minute
Ailier Gauche	Centre	Ailier Droit	D�fense	D�fense
Lukas Reichel	Reese Johnson	Chase De Leo	Ville Heinola	Declan Chisholm

D�fense Derni�re Minute
Ailier Gauche	Centre	Ailier Droit	D�fense	D�fense
Lukas Reichel	Reese Johnson	Chase De Leo	Ville Heinola	Declan Chisholm

Attaquants Suppl�mentaires
Normal	Avantage Num�rique	D�savantage Num�rique
Chase Pearson, Will Bitten, Travis Barron	Chase Pearson, Will Bitten	Travis Barron

D�fenseurs Suppl�mentaires
Normal	Avantage Num�rique	D�savantage Num�rique
Simon Lundmark, Mikko Kokkonen, William Villeneuve	Simon Lundmark	Mikko Kokkonen, William Villeneuve

Tirs de P�nalit�
Reese Johnson, Lukas Reichel, Axel Jonsson-Fjallby, Lane Pederson, Will Bitten

Gardien
#1 : Joseph Woll, #2 : Nico Daws

Lignes d'Attaque Perso. en Prol.
Reese Johnson, Lukas Reichel, Axel Jonsson-Fjallby, Lane Pederson, Will Bitten, Chase De Leo, Chase De Leo, Travis Barron, Chris Wagner, Cole Fonstad, Mike Hardman

Lignes de D�fense Perso. en Prol.
Ville Heinola, Declan Chisholm, William Villeneuve, Matt Bartkowski, Simon Lundmark

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 �quipe	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	Thunderbirds	5	1	4	0	0	0	0	0	8	16	-8	2	0	2	0	0	0	0	0	4	6	-2	3	1	2	0	0	0	0	0	4	10	-6	2	0.200	8	10	18	0	1	4	2	2	0	166	72	38	56	0	206	67	70	92	16	3	18.75%	5	1	80.00%	0	51	100	51.00%	54	97	55.67%	28	60	46.67%	104	65	120	39	75	37
	Total	5	1	4	0	0	0	0	0	8	16	-8	2	0	2	0	0	0	0	0	4	6	-2	3	1	2	0	0	0	0	0	4	10	-6	2	0.200	8	10	18	0	1	4	2	2	0	166	72	38	56	0	206	67	70	92	16	3	18.75%	5	1	80.00%	0	51	100	51.00%	54	97	55.67%	28	60	46.67%	104	65	120	39	75	37
	_Since Last GM Reset	5	1	4	0	0	0	0	0	8	16	-8	2	0	2	0	0	0	0	0	4	6	-2	3	1	2	0	0	0	0	0	4	10	-6	2	0.200	8	10	18	0	1	4	2	2	0	166	72	38	56	0	206	67	70	92	16	3	18.75%	5	1	80.00%	0	51	100	51.00%	54	97	55.67%	28	60	46.67%	104	65	120	39	75	37
	_Vs Conference	5	1	4	0	0	0	0	0	8	16	-8	2	0	2	0	0	0	0	0	4	6	-2	3	1	2	0	0	0	0	0	4	10	-6	2	0.200	8	10	18	0	1	4	2	2	0	166	72	38	56	0	206	67	70	92	16	3	18.75%	5	1	80.00%	0	51	100	51.00%	54	97	55.67%	28	60	46.67%	104	65	120	39	75	37
	_Vs Division	5	1	4	0	0	0	0	0	8	16	-8	2	0	2	0	0	0	0	0	4	6	-2	3	1	2	0	0	0	0	0	4	10	-6	2	0.200	8	10	18	0	1	4	2	2	0	166	72	38	56	0	206	67	70	92	16	3	18.75%	5	1	80.00%	0	51	100	51.00%	54	97	55.67%	28	60	46.67%	104	65	120	39	75	37

			Total Pour les Joueurs
Matchs Jou�s	Points	S�quence	Buts	Passes	Points	Tirs Pour	Tirs Contre	Tirs Bloqu�s	Minutes de P�nalit�	Mises en �chec	Buts en Filet D�sert	Blanchissage
5	2	L4	8	10	18	166	206	67	70	92	0	1

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	1	4	0	0	0	0	8	16

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	0	2	0	0	0	0	4	6

Matchs �xt�rieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	1	2	0	0	0	0	4	10

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
1	4	0	0	0	0

Tentatives en Avantage Num�rique	Buts en Avantage Num�rique	% en Avantage Num�rique	Tentatives en D�savantage Num�rique	Buts Contre en D�savantage Num�rique	% en D�savantage Num�rique	Buts Pour en D�savantage Num�rique
16	3	18.75%	5	1	80.00%	0

Tirs en 1e P�riode	Tirs en 2e P�riode	Tirs en 3e P�riode	Tirs en 4e P�riode	Buts en 1e P�riode	Buts en 2e P�riode	Buts en 3e P�riode	Buts en 4e P�riode
72	38	56	0	4	2	2	0

Mises en Jeu
Gagn�es en Zone Offensive	Total en Zone Offensive	% Gagn�es en Zone Offensive	Gagn�es en Zone D�fensive	Total en Zone D�fensive	% Gagn�es en Zone D�fensive	Gagn�es en Zone Neutre	Total en Zone Neutre	% Gagn�es en Zone Neutre
51	100	51.00%	54	97	55.67%	28	60	46.67%

Temps Avec la Rondelle
En Zone Offensive	Contr�le en Zone Offensive	En Zone D�fensive	Contr�le en Zone D�fensive	En Zone Neutre	Contr�le en Zone Neutre
104	65	120	39	75	37

Derniers Match Jou�s 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	�quipe Visiteuse	Score	�quipe Locale	Score	ST	Lien
2 - 2024-04-19	6	Moose	1	Thunderbirds	0	AW	Sommaire du Match
4 - 2024-04-21	14	Moose	2	Thunderbirds	6	AL	Sommaire du Match
6 - 2024-04-23	22	Thunderbirds	2	Moose	1	BL	Sommaire du Match
8 - 2024-04-25	30	Thunderbirds	4	Moose	3	BL	Sommaire du Match
10 - 2024-04-27	38	Moose	1	Thunderbirds	4	AL	Sommaire du Match

Capacit� de l'Ar�na - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacit� de l'Ar�na	3500	1500
Prix des Billets	50	25
Assistance	7,000	3,000
Assistance PCT	100.00%	100.00%

Revenus
Matchs � domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels � ce Jour	Capacit� de l'Ar�na	Popularit� de l'�quipe
39	5000 - 100.00%	108,375$	216,750$	5000	100

D�penses
D�penses Annuelles � Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
0$	17,521,250$	17,521,250$	0$

Cap Salarial Par Jour	Cap salarial � ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	0$	0	0

�stimation
Revenus de la Saison �stim�s	Jours Restants de la Saison	D�penses Par Jour	D�penses de la Saison �stim�es
0$	14	0$	0$

Moose

Afficher ou Masquer des Colonnes

#	Nom du Joueur	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS
1	Lane Pederson	246	189	259	448	159	18	535	312	914	20.68%	184	5068	20.60	27	49	76	108	7	9	16	26	22	7	51.21%	17	1.77	5	12
2	Sebastien Aho	164	195	165	360	168	49	174	134	553	35.26%	143	3566	21.75	29	24	53	82	7	6	13	19	13	4	0.00%	23	2.02	1	2
3	Mike Hardman	246	85	172	257	100	42	367	175	617	13.78%	82	4141	16.84	10	20	30	35	1	3	4	5	8	2	42.46%	5	1.24	0	0
4	Morgan Geekie	92	102	131	233	136	18	135	110	282	36.17%	59	1688	18.35	11	23	34	32	4	0	4	6	9	2	53.12%	15	2.76	0	1
5	Chase De Leo	203	64	166	230	195	249	241	219	261	24.52%	80	3376	16.63	5	22	27	26	2	3	5	6	4	4	57.02%	2	1.36	3	6

Moose

Afficher ou Masquer des Colonnes

#	Nom du Gardien	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA
1	Beck Warm	75	54	17	3	0.805	5.25	4381	0	5	383	1968	1088	6	1	0.727	11
2	Nico Daws	92	46	41	5	0.905	3.32	5551	10	3	307	3223	1865	4	2	0.706	34
3	Joseph Woll	72	43	22	7	0.931	2.58	4344	4	1	187	2719	1702	0	1	0.643	14
4	Sam Montembeault	1	1	0	0	0.731	7.00	60	0	0	7	26	12	0	0	0.000	0

Moose

Afficher ou Masquer des Colonnes

	Ligue											Domicile											Visiteur
Ann�e	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 R�guli�re
2021	82	54	18	0	4	2	3	1	789	418	371	41	30	7	0	0	1	2	1	430	208	222	41	24	11	0	4	1	1	0	359	210	149	125	789	1291	2080	1	7	0	345	261	176	2517	0	826	882	790	2166	872	1656	1484	205	97	47.32%	254	59	76.77%	25	668	1224	54.58%	648	1223	52.98%	999	1789	55.84%	1784	1142	1895	596	1263	660
2022	82	33	37	0	4	2	3	3	270	280	-10	41	20	16	0	2	1	0	2	139	128	11	41	13	21	0	2	1	3	1	131	152	-21	85	270	460	730	1	2	99	89	75	14	2696	943	885	852	50	2871	1024	349	1611	176	43	24.43%	171	40	76.61%	10	607	1366	44.44%	728	1562	46.61%	464	1063	43.65%	1719	1048	1893	677	1344	670
2023	82	44	26	0	4	3	1	4	282	224	58	41	25	10	0	3	1	1	1	149	98	51	41	19	16	0	1	2	0	3	133	126	7	105	282	414	696	2	2	100	101	76	6	2721	914	920	867	34	3074	1214	520	1631	141	35	24.82%	117	21	82.05%	5	724	1456	49.73%	818	1583	51.67%	515	1040	49.52%	1713	1060	1907	679	1328	651
Total Saison R�guli�re	246	131	81	0	12	7	7	8	1341	922	419	123	75	33	0	5	3	3	4	718	434	284	123	56	48	0	7	4	4	4	623	488	135	315	1341	2165	3506	4	11	199	535	412	196	7934	1857	2631	2601	874	8111	3110	2525	4726	522	175	33.52%	542	120	77.86%	40	1999	4046	49.41%	2194	4368	50.23%	1978	3892	50.82%	5218	3251	5697	1953	3936	1982
S�ries
2021	11	5	6	0	0	0	0	0	85	76	9	5	3	2	0	0	0	0	0	45	31	14	6	2	4	0	0	0	0	0	40	45	-5	10	85	136	221	1	0	0	42	28	14	321	0	106	119	92	375	165	152	142	32	15	46.88%	21	5	76.19%	2	97	176	55.11%	114	173	65.90%	138	242	57.02%	237	156	258	80	164	84
2023	5	1	4	0	0	0	0	0	8	16	-8	2	0	2	0	0	0	0	0	4	6	-2	3	1	2	0	0	0	0	0	4	10	-6	2	8	10	18	0	1	4	2	2	0	166	72	38	56	0	206	67	70	92	16	3	18.75%	5	1	80.00%	0	51	100	51.00%	54	97	55.67%	28	60	46.67%	104	65	120	39	75	37
Total S�ries	16	6	10	0	0	0	0	0	93	92	1	7	3	4	0	0	0	0	0	49	37	12	9	3	6	0	0	0	0	0	44	55	-11	12	93	146	239	1	1	4	44	30	14	487	72	144	175	92	581	232	222	234	48	18	37.50%	26	6	76.92%	2	148	276	53.62%	168	270	62.22%	166	302	54.97%	341	222	378	120	240	121

Moose

Afficher ou Masquer des Colonnes

#	Nom du Joueur	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20
1	Lane Pederson	16	20	20	40	1	0	24	26	79	25.32%	18	348	21.76	6	4	10	21	0	1	1	1	3	0	47.67%	4	2.30
2	Chase De Leo	16	11	17	28	2	9	25	28	43	25.58%	14	332	20.79	2	5	7	6	1	0	1	4	0	0	60.08%	0	1.68
3	Sebastien Aho	11	8	19	27	17	2	6	12	23	34.78%	10	170	15.51	0	1	1	0	0	0	0	0	0	0	0.00%	0	3.16
4	Morgan Geekie	11	14	11	25	4	2	5	16	34	41.18%	15	217	19.76	3	4	7	6	0	1	1	0	1	2	54.93%	1	2.30
5	Eetu Luostarinen	11	8	17	25	2	0	16	20	27	29.63%	6	221	20.17	0	5	5	7	1	0	1	1	0	0	69.23%	0	2.25

Moose

Afficher ou Masquer des Colonnes

#	Nom du Gardien	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA
1	Beck Warm	11	5	6	0	0.799	6.83	659	0	0	75	374	208	4	1	0.000	0
2	Joseph Woll	5	1	4	0	0.922	3.21	299	0	1	16	206	125	0	0	0.000	0

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