LAAHS - Seattle Thunderbirds

Penguins
Formation
Points
Informations Joueurs
Lignes
Statistiques d'Équipe
Calendrier
Finance
Stats d'équipe en Carrière

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	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	Jesperi Kotkaniemi (R)	X	X			100.00	71	43	89	83	70	66	85	75	77	68	67	51	25	54	54	68	36	64		0
2	Josh Leivo		X	X		100.00	67	57	87	71	78	67	64	80	37	61	71	56	63	59	59	68	78	64		0
3	Sam Carrick	X				100.00	65	68	59	65	68	80	83	69	80	64	71	61	67	46	46	68	80	63		0
4	Stefan Noesen		X	X		100.00	88	46	80	74	75	64	74	64	41	61	58	69	25	55	56	65	79	62		0
5	T.J. Tynan	X		X		100.00	67	58	88	62	58	83	87	67	80	74	56	61	53	44	44	65	80	62		0
6	Logan Brown (R)	X				100.00	85	85	86	62	85	62	62	64	80	68	56	70	57	44	44	65	56	61		0
7	Brooks Macek (R)	X		X		100.00	74	66	93	58	66	72	74	67	80	65	66	65	63	44	44	67	78	61		0
8	Matt Read (C)	X	X	X		100.00	73	43	94	77	66	61	78	61	36	50	58	66	57	69	70	63	79	61		0
9	Peter Cehlarik		X			100.00	61	42	90	67	75	63	73	69	26	60	72	52	25	46	46	67	79	60		0
10	Emil Pettersson	X				100.00	70	63	86	63	63	78	83	62	78	62	57	63	54	51	51	63	76	60		0
11	Brett Sutter	X	X			100.00	75	73	79	63	73	55	54	63	79	59	62	67	59	54	54	64	42	59		0
12	Jacob Larsson				X	100.00	71	43	89	77	73	72	76	60	25	50	47	75	25	56	56	61	48	65		0
13	Jacob MacDonald				X	100.00	78	74	88	70	74	83	90	58	25	49	52	66	49	49	49	62	80	64		0
14	Yannick Weber			X	X	100.00	75	43	90	77	72	59	72	59	25	48	47	63	75	69	70	59	39	62		0
15	Joey LaLeggia				X	100.00	71	64	86	68	64	79	85	59	45	52	52	62	49	46	46	61	75	61		0
16	Matt Irwin				X	100.00	83	75	76	73	77	57	64	58	25	51	46	61	25	65	67	58	53	61		0
17	Matt Tennyson				X	100.00	75	76	74	70	76	69	74	54	25	49	42	65	40	57	57	56	77	61		0
18	Logan Stanley (R)				X	100.00	83	87	72	64	87	75	83	48	25	39	41	65	39	44	44	55	78	60		0
19	Andrew Campbell				X	100.00	78	78	77	68	78	71	78	47	25	34	41	65	39	58	58	53	78	60		0
Rayé
1	Rourke Chartier	X				100.00	76	43	94	71	69	54	55	58	65	50	58	69	25	45	45	61	19	57		0
2	Landon Ferraro	X		X		100.00	68	68	68	65	68	54	54	58	73	53	56	62	53	54	55	59	20	56	X	0
3	Hampus Gustafsson	X	X			100.00	81	78	87	62	78	63	68	47	59	43	44	65	42	49	49	54	20	54		0
4	Rob O'Gara				X	100.00	76	81	63	70	81	70	77	47	25	37	41	61	39	44	44	53	48	58		0
5	Vincent LoVerde				X	100.00	77	73	85	60	73	75	83	46	25	36	40	61	38	44	44	52	22	57		0

	MOYENNE D'ÉQUIPE					100.00	75	64	83	68	73	68	74	60	48	53	54	63	45	52	52	61	59	61

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	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Mitch Gillam (R)	100.00	67	53	66	62	70	66	72	76	71	71	30	44	44	68	79	64	0
2	John Muse	100.00	62	55	69	65	65	72	60	67	72	70	30	44	44	65	79	62	0
Rayé
1	Zane McIntyre	100.00	57	75	94	79	51	59	58	64	56	56	30	44	44	59	20	59	0
2	Jake Paterson	100.00	44	51	64	66	40	43	50	52	44	45	30	44	44	46	20	48	0

	MOYENNE D'ÉQUIPE	100.00	58	59	73	68	57	60	60	65	61	61	30	44	44	60	50	58

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Dave Hakstol	60	46	60	57	72	58	59	USA	50	1	60,000$

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	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	S2	S3
1	Josh Leivo	Seattle Thunderbirds (PIT)	LW/RW	7	4	8	12	-1	9	5	13	9	33	15	24	12.12%	7	164	23.49	1	4	5	4	6	0	17	0	39.39%	33	6	7	1.46	1	0	0	2	0	0
2	Jesperi Kotkaniemi	Seattle Thunderbirds (PIT)	C/LW	7	3	7	10	-6	2	0	7	15	26	10	12	11.54%	4	146	20.91	2	4	6	4	6	1	17	1	55.08%	187	7	2	1.37	0	0	0	1	0	0
3	Logan Brown	Seattle Thunderbirds (PIT)	C	7	3	3	6	1	2	0	10	8	18	6	9	16.67%	2	101	14.43	0	0	0	0	0	0	0	0	48.08%	52	3	0	1.19	0	0	0	0	0	0
4	T.J. Tynan	Seattle Thunderbirds (PIT)	C/RW	7	3	2	5	-2	9	5	8	9	27	8	13	11.11%	1	119	17.12	0	1	1	0	4	0	0	0	40.00%	5	4	4	0.83	0	0	1	0	0	1
5	Jacob Larsson	Seattle Thunderbirds (PIT)	D	7	2	3	5	-8	7	5	11	11	10	3	9	20.00%	14	194	27.76	2	1	3	2	6	0	19	0	0.00%	0	6	12	0.51	0	1	0	0	1	0
6	Sam Carrick	Seattle Thunderbirds (PIT)	C	7	1	3	4	-6	7	5	15	9	17	10	14	5.88%	2	126	18.04	1	1	2	1	4	0	7	1	61.61%	112	5	4	0.63	1	0	0	0	0	0
7	Yannick Weber	Seattle Thunderbirds (PIT)	RW/D	7	2	1	3	-4	4	0	10	8	9	4	7	22.22%	5	142	20.33	0	1	1	0	5	0	11	0	31.25%	16	2	7	0.42	0	0	0	0	0	1
8	Jacob MacDonald	Seattle Thunderbirds (PIT)	D	7	1	2	3	-8	10	10	8	8	8	4	3	12.50%	11	166	23.82	1	2	3	2	6	0	18	0	0.00%	0	3	6	0.36	2	0	0	0	0	0
9	Matt Read	Seattle Thunderbirds (PIT)	C/LW/RW	7	1	2	3	-1	0	0	7	7	13	4	9	7.69%	5	89	12.74	0	0	0	0	0	0	6	0	20.00%	5	3	4	0.67	0	0	0	0	0	0
10	Stefan Noesen	Seattle Thunderbirds (PIT)	LW/RW	7	2	0	2	-7	21	5	18	13	18	7	15	11.11%	3	126	18.06	1	0	1	2	4	2	8	1	28.57%	7	2	2	0.32	0	0	1	0	0	1
11	Brooks Macek	Seattle Thunderbirds (PIT)	C/RW	7	0	2	2	-1	0	0	6	5	16	2	7	0.00%	6	98	14.02	0	0	0	0	0	0	1	0	100.00%	1	4	3	0.41	0	0	0	0	0	0
12	Brett Sutter	Seattle Thunderbirds (PIT)	C/LW	7	0	1	1	-1	0	0	4	0	1	0	2	0.00%	0	38	5.56	0	0	0	0	0	0	7	0	0.00%	1	2	0	0.51	0	0	0	0	0	0
13	Peter Cehlarik	Seattle Thunderbirds (PIT)	LW	7	1	0	1	-1	2	0	3	2	5	5	2	20.00%	1	53	7.69	0	0	0	0	0	0	1	0	66.67%	3	1	1	0.37	0	0	0	0	0	0
14	Andrew Campbell	Seattle Thunderbirds (PIT)	D	7	0	1	1	2	0	0	5	8	1	2	1	0.00%	6	94	13.52	0	0	0	0	0	0	4	0	0.00%	0	0	4	0.21	0	0	0	0	0	0
15	Joey LaLeggia	Seattle Thunderbirds (PIT)	D	6	0	1	1	-3	5	5	6	6	9	3	3	0.00%	9	113	18.84	0	0	0	0	3	0	10	0	0.00%	0	3	3	0.18	0	1	0	0	0	0
16	Matt Tennyson	Seattle Thunderbirds (PIT)	D	7	0	1	1	2	22	20	3	1	2	4	1	0.00%	4	88	12.63	0	0	0	0	0	0	0	0	0.00%	0	0	1	0.23	1	2	1	0	0	0
17	Emil Pettersson	Seattle Thunderbirds (PIT)	C	7	0	0	0	-1	0	0	2	4	2	2	4	0.00%	1	43	6.16	0	0	0	0	0	0	0	0	71.43%	14	0	0	0.00	0	0	0	0	0	0
18	Rourke Chartier	Seattle Thunderbirds (PIT)	C	1	0	0	0	0	0	0	5	0	1	1	0	0.00%	1	18	18.20	0	0	0	0	0	0	0	0	33.33%	9	1	0	0.00	0	0	0	0	0	0
19	Logan Stanley	Seattle Thunderbirds (PIT)	D	7	0	0	0	-2	0	0	3	3	0	0	0	0.00%	0	39	5.67	0	0	0	0	0	0	1	0	0.00%	0	0	0	0.00	0	0	0	0	0	0
20	Matt Irwin	Seattle Thunderbirds (PIT)	D	7	0	0	0	-3	10	0	10	5	3	1	4	0.00%	7	123	17.68	0	0	0	0	4	0	1	0	0.00%	0	0	7	0.00	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				133	23	37	60	-50	110	60	154	131	219	91	139	10.50%	89	2088	15.70	8	14	22	15	55	3	136	3	53.03%	445	52	67	0.57	5	4	3	3	1	3

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	GA	SA	SAR	ST	BG	S2
1	Mitch Gillam	Seattle Thunderbirds (PIT)	7	3	4	0.900	4.06	399	27	271	146	7	0	2
2	John Muse	Seattle Thunderbirds (PIT)	1	0	0	0.857	4.80	25	2	14	7	0	7	0
Stats d'équipe Total ou en Moyenne			8	3	4	0.898	4.10	424	29	285	153	7	7	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	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Link
Andrew Campbell	Seattle Thunderbirds (PIT)	D	30	1988-02-04	No	205 Lbs	6 ft4	No	No	No	1	Pro & Farm	715,000$	0$	0$	No			Lien
Brett Sutter	Seattle Thunderbirds (PIT)	C/LW	31	1987-06-02	No	200 Lbs	6 ft0	Yes	No	No	1	Pro & Farm	660,000$	0$	0$	No			Lien
Brooks Macek	Seattle Thunderbirds (PIT)	C/RW	26	1992-05-15	Yes	181 Lbs	5 ft11	Yes	No	No	1	Pro & Farm	900,000$	0$	0$	No			Lien
Emil Pettersson	Seattle Thunderbirds (PIT)	C	24	1994-01-14	No	164 Lbs	6 ft2	No	No	No	1	Pro & Farm	700,000$	0$	0$	No			Lien
Hampus Gustafsson	Seattle Thunderbirds (PIT)	C/LW	24	1993-10-26	No	205 Lbs	6 ft4	No	No	No	1	Pro & Farm	925,000$	0$	0$	No			Lien
Jacob Larsson	Seattle Thunderbirds (PIT)	D	21	1997-04-29	No	195 Lbs	6 ft2	No	No	No	1	Pro & Farm	894,166$	0$	0$	No			Lien
Jacob MacDonald	Seattle Thunderbirds (PIT)	D	25	1993-02-26	No	207 Lbs	6 ft0	No	No	No	1	Pro & Farm	750,000$	0$	0$	No			Lien
Jake Paterson	Seattle Thunderbirds (PIT)	G	24	1994-05-02	No	176 Lbs	6 ft1	No	No	No	0	Pro & Farm		0$	0$	No			Lien
Jesperi Kotkaniemi	Seattle Thunderbirds (PIT)	C/LW	17	2000-07-06	Yes	188 Lbs	6 ft2	No	No	No	2	Pro & Farm	900,000$	0$	0$	No	900,000$		Lien
Joey LaLeggia	Seattle Thunderbirds (PIT)	D	26	1992-06-24	No	182 Lbs	5 ft9	No	No	No	1	Pro & Farm	675,000$	0$	0$	No			Lien
John Muse	Seattle Thunderbirds (PIT)	G	29	1988-08-01	No	185 Lbs	5 ft11	Yes	No	No	1	Pro & Farm	1,000,000$	0$	0$	No			Lien
Josh Leivo	Seattle Thunderbirds (PIT)	LW/RW	25	1993-05-26	No	210 Lbs	6 ft2	No	No	No	1	Pro & Farm	1,500,000$	0$	0$	No			Lien
Landon Ferraro	Seattle Thunderbirds (PIT)	C/RW	26	1991-08-07	No	186 Lbs	6 ft0	No	Yes	No	0	Pro & Farm		0$	0$	No			Lien
Logan Brown	Seattle Thunderbirds (PIT)	C	20	1998-03-04	Yes	220 Lbs	6 ft6	No	No	No	3	Pro & Farm	875,000$	0$	0$	No	875,000$	875,000$	Lien
Logan Stanley	Seattle Thunderbirds (PIT)	D	20	1998-05-25	Yes	228 Lbs	6 ft7	No	No	No	3	Pro & Farm	863,333$	0$	0$	No	863,333$	863,333$	Lien
Matt Irwin	Seattle Thunderbirds (PIT)	D	30	1987-11-29	No	207 Lbs	6 ft1	No	No	No	1	Pro & Farm	675,000$	0$	0$	No			Lien
Matt Read	Seattle Thunderbirds (PIT)	C/LW/RW	32	1986-06-13	No	185 Lbs	5 ft10	No	No	No	1	Pro & Farm	715,000$	0$	0$	No			Lien
Matt Tennyson	Seattle Thunderbirds (PIT)	D	28	1990-04-23	No	205 Lbs	6 ft2	No	No	No	2	Pro & Farm	700,000$	0$	0$	No	700,000$		Lien
Mitch Gillam	Seattle Thunderbirds (PIT)	G	25	1992-09-24	Yes	174 Lbs	6 ft0	No	No	No	1	Pro & Farm	575,000$	0$	0$	No			Lien
Peter Cehlarik	Seattle Thunderbirds (PIT)	LW	23	1995-05-12	No	202 Lbs	6 ft2	No	No	No	1	Pro & Farm	700,000$	0$	0$	No			Lien
Rob O'Gara	Seattle Thunderbirds (PIT)	D	24	1993-07-06	No	215 Lbs	6 ft4	No	No	No	1	Pro & Farm	700,000$	0$	0$	No			Lien
Rourke Chartier	Seattle Thunderbirds (PIT)	C	22	1996-04-02	No	190 Lbs	5 ft11	No	No	No	1	Pro & Farm	697,500$	0$	0$	No			Lien
Sam Carrick	Seattle Thunderbirds (PIT)	C	26	1992-02-04	No	188 Lbs	6 ft0	No	No	No	1	Pro & Farm	700,000$	0$	0$	No			Lien
Stefan Noesen	Seattle Thunderbirds (PIT)	LW/RW	25	1993-02-12	No	205 Lbs	6 ft1	No	No	No	1	Pro & Farm	1,500,000$	0$	0$	No			Lien
T.J. Tynan	Seattle Thunderbirds (PIT)	C/RW	26	1992-02-24	No	165 Lbs	5 ft8	No	No	No	1	Pro & Farm	700,000$	0$	0$	No			Lien
Vincent LoVerde	Seattle Thunderbirds (PIT)	D	29	1989-04-13	No	205 Lbs	5 ft11	No	No	No	1	Pro & Farm	797,500$	0$	0$	No			Lien
Yannick Weber	Seattle Thunderbirds (PIT)	RW/D	29	1988-09-23	No	200 Lbs	5 ft11	No	No	No	1	Pro & Farm	675,000$	0$	0$	No			Lien
Zane McIntyre	Seattle Thunderbirds (PIT)	G	25	1992-08-20	No	206 Lbs	6 ft2	No	No	No	1	Pro & Farm	700,000$	0$	0$	No			Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
28	25.43	196 Lbs	6 ft1	1.14	756,875$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Josh Leivo	Jesperi Kotkaniemi	Stefan Noesen	37	0	1	4
2	Matt Read	Sam Carrick	T.J. Tynan	30	1	2	2
3	Peter Cehlarik	Logan Brown	Brooks Macek	23	1	2	2
4	Brett Sutter	Emil Pettersson	Yannick Weber	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jacob Larsson	Jacob MacDonald	36	1	2	2
2	Yannick Weber	Joey LaLeggia	30	1	2	2
3	Matt Irwin	Matt Tennyson	24	1	2	2
4	Andrew Campbell	Logan Stanley	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Josh Leivo	Jesperi Kotkaniemi	Stefan Noesen	60	1	2	2
2	Matt Read	Sam Carrick	T.J. Tynan	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jacob Larsson	Jacob MacDonald	60	1	2	2
2	Yannick Weber	Joey LaLeggia	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Jesperi Kotkaniemi	Josh Leivo	60	1	2	2
2	Sam Carrick	Stefan Noesen	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jacob Larsson	Jacob MacDonald	60	1	2	2
2	Yannick Weber	Joey LaLeggia	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Jesperi Kotkaniemi	60	1	2	2	Jacob Larsson	Jacob MacDonald	60	1	2	2
2	Josh Leivo	40	1	2	2	Yannick Weber	Joey LaLeggia	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Jesperi Kotkaniemi	Josh Leivo	60	1	2	2
2	Sam Carrick	Stefan Noesen	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jacob Larsson	Jacob MacDonald	60	1	2	2
2	Yannick Weber	Joey LaLeggia	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Josh Leivo	Jesperi Kotkaniemi	Stefan Noesen	Jacob Larsson	Jacob MacDonald

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Josh Leivo	Jesperi Kotkaniemi	Stefan Noesen	Jacob Larsson	Jacob MacDonald

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Emil Pettersson, Brooks Macek, Logan Brown	Emil Pettersson, Brooks Macek	Logan Brown

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Matt Irwin, Matt Tennyson, Andrew Campbell	Matt Irwin	Matt Tennyson, Andrew Campbell

Tirs de Pénalité
Jesperi Kotkaniemi, Josh Leivo, Sam Carrick, Stefan Noesen, T.J. Tynan

Gardien
#1 : Mitch Gillam, #2 : John Muse

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	Manitoba Moose	7	3	4	0	0	0	0	0	23	29	-6	4	1	3	0	0	0	0	0	11	17	-6	3	2	1	0	0	0	0	0	12	12	0	6	0.429	23	37	60	0	0	6	8	8	1	219	63	79	74	3	285	89	110	154	12	8	66.67%	20	4	80.00%	0	79	156	50.64%	92	177	51.98%	65	112	58.04%	140	74	150	63	132	66
	Total	7	3	4	0	0	0	0	0	23	29	-6	4	1	3	0	0	0	0	0	11	17	-6	3	2	1	0	0	0	0	0	12	12	0	6	0.429	23	37	60	0	0	6	8	8	1	219	63	79	74	3	285	89	110	154	12	8	66.67%	20	4	80.00%	0	79	156	50.64%	92	177	51.98%	65	112	58.04%	140	74	150	63	132	66
	_Since Last GM Reset	7	3	4	0	0	0	0	0	23	29	-6	4	1	3	0	0	0	0	0	11	17	-6	3	2	1	0	0	0	0	0	12	12	0	6	0.429	23	37	60	0	0	6	8	8	1	219	63	79	74	3	285	89	110	154	12	8	66.67%	20	4	80.00%	0	79	156	50.64%	92	177	51.98%	65	112	58.04%	140	74	150	63	132	66
	_Vs Conference	7	3	4	0	0	0	0	0	23	29	-6	4	1	3	0	0	0	0	0	11	17	-6	3	2	1	0	0	0	0	0	12	12	0	6	0.429	23	37	60	0	0	6	8	8	1	219	63	79	74	3	285	89	110	154	12	8	66.67%	20	4	80.00%	0	79	156	50.64%	92	177	51.98%	65	112	58.04%	140	74	150	63	132	66

			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
7	6	L1	23	37	60	219	285	89	110	154	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
7	3	4	0	0	0	0	23	29

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	1	3	0	0	0	0	11	17

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	2	1	0	0	0	0	12	12

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
2	4	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
12	8	66.67%	20	4	80.00%	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
63	79	74	3	6	8	8	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
79	156	50.64%	92	177	51.98%	65	112	58.04%

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
140	74	150	63	132	66

Derniers Match Joués Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

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

Jour	Match	Équipe Visiteuse	Score	Équipe Locale	Score	ST	OT	Lien
1 - 2019-10-04	2	Manitoba Moose	2	Seattle Thunderbirds	3	W	X	Sommaire du Match
2 - 2019-10-05	10	Manitoba Moose	4	Seattle Thunderbirds	2	L		Sommaire du Match
3 - 2019-10-06	18	Seattle Thunderbirds	6	Manitoba Moose	3	W		Sommaire du Match
4 - 2019-10-07	26	Seattle Thunderbirds	3	Manitoba Moose	7	L		Sommaire du Match
5 - 2019-10-08	34	Manitoba Moose	5	Seattle Thunderbirds	3	L		Sommaire du Match
6 - 2019-10-09	42	Seattle Thunderbirds	3	Manitoba Moose	2	W		Sommaire du Match
7 - 2019-10-10	50	Manitoba Moose	6	Seattle Thunderbirds	3	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	35	15
Assistance	7,416	3,727
Assistance PCT	92.70%	93.18%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
37	2786 - 92.86%	117,511$	470,042$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
0$	2,119,250$	2,114,250$	0$

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

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	0	0$	0$

Afficher ou Masquer des Colonnes

	Ligue											Domicile											Visiteur
Année	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
Saison Régulière
2016	82	22	38	0	7	9	4	2	354	410	-56	41	14	15	0	3	5	3	1	204	207	-3	41	8	23	0	4	4	1	1	150	203	-53	44	354	569	923	2	2	86	127	130	14	2415	648	898	832	56	2952	1012	1367	1493	216	72	33.33%	221	68	69.23%	2	752	1530	49.15%	895	1746	51.26%	712	1488	47.85%	1576	740	1696	790	1706	892
2017	82	45	27	0	2	4	1	3	393	356	37	41	21	13	0	1	4	1	1	203	183	20	41	24	14	0	1	0	0	2	190	173	17	90	393	637	1030	0	0	103	150	137	7	3097	966	1129	994	18	2903	973	1171	1720	241	80	33.20%	213	75	64.79%	4	972	1752	55.48%	881	1638	53.79%	829	1487	55.75%	1744	968	1654	755	1553	786
2018	82	40	30	0	4	3	4	1	375	324	51	41	23	14	0	2	1	1	0	198	154	44	41	17	16	0	2	2	3	1	177	170	7	80	375	616	991	5	2	91	142	134	10	2855	809	989	1034	35	2925	968	1000	1597	199	53	26.63%	232	73	68.53%	5	753	1644	45.80%	821	1801	45.59%	617	1445	42.70%	1667	886	1688	772	1599	810
2019	82	44	25	0	4	3	2	4	378	302	76	41	25	12	0	1	1	0	2	191	147	44	41	19	13	0	3	2	2	2	187	155	32	88	378	604	982	2	1	87	177	108	11	2701	758	1103	824	42	2991	1020	1290	1533	199	73	36.68%	209	62	70.33%	7	938	1631	57.51%	1026	1839	55.79%	808	1448	55.80%	1667	876	1697	767	1598	824
Total Saison Régulière	328	151	120	0	17	19	11	10	1500	1392	108	164	83	54	0	7	11	5	4	796	691	105	164	68	66	0	10	8	6	6	704	701	3	302	1500	2426	3926	9	5	367	596	509	42	11068	3181	4119	3684	151	11771	3973	4828	6343	855	278	32.51%	875	278	68.23%	18	3415	6557	52.08%	3623	7024	51.58%	2966	5868	50.55%	6655	3472	6737	3085	6458	3314
2019	7	3	4	0	0	0	0	0	23	29	-6	4	1	3	0	0	0	0	0	11	17	-6	3	2	1	0	0	0	0	0	12	12	0	6	23	37	60	0	0	6	8	8	1	219	63	79	74	3	285	89	110	154	12	8	66.67%	20	4	80.00%	0	79	156	50.64%	92	177	51.98%	65	112	58.04%	140	74	150	63	132	66
Total Séries	7	3	4	0	0	0	0	0	23	29	-6	4	1	3	0	0	0	0	0	11	17	-6	3	2	1	0	0	0	0	0	12	12	0	6	23	37	60	0	0	6	8	8	1	219	63	79	74	3	285	89	110	154	12	8	66.67%	20	4	80.00%	0	79	156	50.64%	92	177	51.98%	65	112	58.04%	140	74	150	63	132	66