Association Québécoise de Hockey Simulé

Association Québécoise de Hockey Simulé - Bandits

Bandits

GP: 12 | W: 8 | L: 3 | OTL: 1 | P: 17
GF: 47 | GA: 42 | PP%: 30.61% | PK%: 76.67%
DG: Guillaume Blais-Lortie | Morale : 90 | Moyenne d'Équipe : 61
Prochain matchs #195 vs Hunters

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Ottawa Lumberjacks
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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	Kirill Marchenko (R)		X			100.00	59	45	88	83	70	81	71	62	30	46	79	62	85	82	75	0	90	66	0
2	Phillip Di Giuseppe		X			100.00	86	45	82	84	62	73	40	61	30	56	66	74	69	89	81	0	90	65	0
3	Josh Archibald		X			100.00	99	48	76	81	50	50	75	53	30	48	58	87	66	90	77	0	90	64	0
4	Jay Beagle	X				100.00	80	48	73	74	77	69	40	47	87	42	52	75	50	96	87	0	90	63	0
5	Sam Carrick	X				100.00	89	69	50	77	66	53	63	51	79	46	55	67	65	91	79	0	90	62	0
6	Joey Anderson (R)			X		100.00	67	45	95	78	69	59	46	55	30	46	63	78	66	84	73	0	90	62	0
7	Jack Studnicka (R)			X		100.00	75	45	86	79	61	53	58	52	78	47	57	64	66	84	72	0	90	61	0
8	Nils Hoglander (R)			X		100.00	65	45	88	84	52	60	40	60	30	60	60	60	68	82	71	0	90	61	0
9	Aliaksei Protas (R)	X				100.00	61	45	89	76	90	58	70	56	30	56	56	58	67	82	71	0	90	61	0
10	Rasmus Asplund (R)	X				100.00	57	45	93	80	56	55	56	52	30	51	54	66	66	85	73	0	90	58	0
11	Rudolfs Balcers			X		100.00	53	45	90	82	55	51	40	55	30	48	62	55	67	86	73	0	90	58	0
12	Sean Walker				X	100.00	71	45	81	80	56	62	85	53	30	52	55	69	66	88	77	0	90	65	0
13	Riley Stillman				X	100.00	83	57	75	79	61	61	60	52	30	51	52	64	66	85	74	0	90	63	0
14	Nikita Okhotyuk (R)				X	100.00	81	45	92	76	60	50	40	48	30	40	56	66	50	82	70	0	90	60	0
15	Ronald Attard				X	100.00	50	45	95	74	71	70	40	45	30	40	50	68	50	84	75	0	90	60	0
16	Chris Wideman				X	100.00	58	48	47	80	47	56	56	50	30	51	50	61	65	93	81	0	90	60	0
17	Declan Chisholm (R)				X	100.00	50	45	95	78	55	50	40	45	30	40	50	55	50	83	70	0	90	56	0
Rayé
1	Trevor Moore			X		98.00	69	45	89	85	59	85	71	65	30	66	64	72	86	88	82	0	90	67	0
2	Brett Leason			X		100.00	60	45	88	75	85	55	65	52	30	45	59	55	66	83	71	0	90	58	0
3	Jeffrey Viel (R)		X			100.00	52	45	92	75	72	50	40	45	30	40	50	62	50	86	73	0	90	54	0
4	Tristen Robins (R)	X				100.00	50	45	95	79	50	69	40	45	30	40	50	61	50	81	72	0	90	54	0
5	Kyle Burroughs				X	100.00	99	69	60	78	57	72	58	50	30	45	55	78	65	87	78	0	90	66	0
6	Matt Irwin				X	100.00	90	57	79	77	65	54	74	49	30	44	54	69	50	95	83	0	90	65	0
7	Joey Keane (R)				X	100.00	50	45	95	77	54	50	40	45	30	40	50	55	50	84	71	0	90	56	0
8	Jordan Spence (R)				X	100.00	50	45	95	78	47	58	40	47	30	44	50	56	50	82	70	0	90	56	0
9	Ben Gleason (R)				X	100.00	50	45	95	78	53	50	40	45	30	40	50	55	50	85	72	0	90	56	0

	MOYENNE D'ÉQUIPE					99.92	67	48	84	79	62	60	53	52	36	47	56	65	62	86	75	0	90	61

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Justus Annunen (R)	100.00	70	50	62	91	70	70	70	70	70	70	70	82	69	0	90	62	0
2	Mikko Koskinen	100.00	70	40	40	90	65	65	65	65	65	65	65	93	90	0	90	60	0
Rayé
1	Adam Wilcox	100.00	70	40	40	83	65	65	65	65	65	65	65	85	70	0	90	58	0

	MOYENNE D'ÉQUIPE	100.00	70	43	47	88	67	67	67	67	67	67	67	87	76	0	90	60

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Andrew Brunette	65	65	65	65	84	78	72	CAN	50	4	1,800,000$

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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

#	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	GT	FO%	FOT	GA	TA	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Trevor Moore	Bandits (OTT)	RW	12	8	10	18	2	0	0	19	21	41	20	37	19.51%	9	259	21.63	1	3	4	9	36	0	24	1	1	51.06%	47	27	3	0	1.39	1	2	0	0	0	0	4	1
2	Phillip Di Giuseppe	Bandits (OTT)	LW	12	2	12	14	0	7	5	25	15	50	18	35	4.00%	5	232	19.41	1	7	8	7	33	2	15	0	0	50.00%	16	14	4	0	1.20	0	1	0	0	1	0	0	1
3	Sam Carrick	Bandits (OTT)	C	12	4	9	13	-2	12	0	26	16	20	4	13	20.00%	9	203	16.97	3	3	6	5	30	0	0	0	0	61.15%	139	5	6	0	1.28	0	0	0	0	0	0	0	0
4	Jay Beagle	Bandits (OTT)	C	11	4	6	10	2	10	0	19	24	11	3	9	36.36%	6	199	18.12	2	3	5	3	36	0	0	0	0	64.36%	275	3	2	0	1.00	0	1	0	0	0	2	0	1
5	Kirill Marchenko	Bandits (OTT)	LW	7	3	6	9	3	17	5	9	11	42	16	19	7.14%	1	154	22.11	0	2	2	4	20	0	11	2	0	33.33%	9	7	3	0	1.16	1	1	1	0	0	1	0	2
6	Conor Garland	Ottawa Lumberjacks	RW	5	5	4	9	0	4	0	7	11	30	7	17	16.67%	0	118	23.72	3	2	5	6	16	1	9	0	0	57.69%	26	6	3	1	1.52	0	1	0	0	0	1	0	1
7	Joey Anderson	Bandits (OTT)	RW	12	4	5	9	-2	7	5	14	12	28	10	15	14.29%	4	181	15.16	1	0	1	2	17	0	0	1	0	71.43%	7	8	4	0	0.99	0	0	0	1	0	1	0	0
8	Aliaksei Protas	Bandits (OTT)	C	12	3	5	8	-5	2	0	16	11	22	6	19	13.64%	4	179	14.97	0	0	0	0	4	1	4	0	1	37.35%	83	6	4	0	0.89	0	1	0	0	0	0	1	0
9	Matt Irwin	Bandits (OTT)	D	10	2	6	8	2	4	0	13	13	16	6	3	12.50%	10	227	22.70	2	1	3	6	30	2	13	0	0	0.00%	0	5	9	0	0.70	0	0	0	0	0	0	0	0
10	Josh Archibald	Bandits (OTT)	LW	12	4	2	6	-5	4	0	30	23	20	10	15	20.00%	6	207	17.28	1	2	3	2	14	0	14	1	0	50.00%	2	7	4	0	0.58	0	1	0	0	0	1	1	0
11	Sean Walker	Bandits (OTT)	D	11	1	4	5	-1	9	5	15	19	17	7	6	5.88%	7	257	23.41	1	2	3	3	36	0	21	1	0	0.00%	0	4	15	0	0.39	0	0	0	0	1	0	0	0
12	Jeffrey Viel	Bandits (OTT)	LW	5	1	2	3	0	2	0	6	5	1	0	2	100.00%	0	70	14.01	0	0	0	0	0	0	3	0	0	40.00%	5	2	1	0	0.86	0	0	0	0	0	0	0	0
13	Kyle Burroughs	Bandits (OTT)	D	7	0	3	3	-2	2	0	12	9	8	6	7	0.00%	12	176	25.14	0	0	0	0	20	0	14	0	0	0.00%	0	6	10	0	0.34	0	0	0	0	0	0	1	0
14	Rasmus Asplund	Bandits (OTT)	C	7	0	2	2	-2	0	0	6	3	2	0	4	0.00%	1	58	8.35	0	0	0	0	0	0	3	0	0	36.00%	25	2	1	0	0.68	0	0	0	0	0	0	0	0
15	Ronald Attard	Bandits (OTT)	D	12	2	0	2	-1	0	0	2	6	11	3	2	18.18%	6	189	15.79	0	0	0	0	7	0	5	0	0	0.00%	0	0	7	0	0.21	0	0	0	0	0	1	0	0
16	Riley Stillman	Bandits (OTT)	D	12	1	1	2	-3	11	5	15	15	4	6	6	25.00%	13	227	19.00	0	1	1	0	25	0	11	0	0	0.00%	0	1	12	0	0.18	0	0	1	0	0	0	0	1
17	Jack Studnicka	Bandits (OTT)	RW	9	1	0	1	-2	0	0	7	3	5	0	2	20.00%	1	62	6.95	0	0	0	0	2	0	0	0	1	80.00%	5	1	1	0	0.32	0	0	0	0	0	0	0	0
18	Jordan Spence	Bandits (OTT)	D	1	0	1	1	1	0	0	1	2	1	0	1	0.00%	1	15	15.40	0	0	0	0	0	0	1	0	0	0.00%	0	0	0	0	1.30	0	0	0	0	0	0	0	0
19	Chris Wideman	Bandits (OTT)	D	9	0	1	1	-1	2	0	10	5	5	2	2	0.00%	5	157	17.47	0	0	0	0	14	0	8	0	0	0.00%	0	2	8	0	0.13	0	0	0	0	0	0	0	0
20	Josh Mahura	Ottawa Lumberjacks	D	3	0	1	1	-2	0	0	2	11	6	1	0	0.00%	7	77	25.68	0	1	1	1	10	0	8	0	0	0.00%	0	2	3	0	0.26	0	1	0	0	0	0	0	0
21	Rudolfs Balcers	Bandits (OTT)	RW	7	1	0	1	3	0	0	2	2	2	1	0	50.00%	0	38	5.44	0	0	0	0	4	0	0	1	0	50.00%	14	0	0	0	0.52	0	0	0	0	0	0	0	0
22	Nils Hoglander	Bandits (OTT)	RW	12	0	0	0	-4	2	0	15	5	20	7	10	0.00%	0	138	11.55	0	0	0	1	1	0	2	0	0	33.33%	6	3	2	0	0.00	0	1	0	0	0	0	0	0
23	Brett Leason	Bandits (OTT)	RW	6	0	0	0	0	0	0	0	0	1	0	0	0.00%	0	19	3.32	0	0	0	0	0	0	0	0	0	33.33%	3	0	0	0	0.00	0	0	0	0	0	0	0	0
24	Declan Chisholm	Bandits (OTT)	D	1	0	0	0	0	0	0	1	1	0	0	0	0.00%	0	13	13.45	0	0	0	0	0	0	1	0	0	0.00%	0	0	2	0	0.00	0	0	0	0	0	0	0	0
25	Nikita Okhotyuk	Bandits (OTT)	D	9	0	0	0	-1	0	0	11	5	6	2	3	0.00%	4	119	13.30	0	0	0	1	3	0	5	0	0	100.00%	1	2	6	0	0.00	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				216	46	80	126	-20	95	25	283	248	369	135	227	12.47%	111	3586	16.60	15	27	42	50	370	6	181	7	3	56.56%	663	113	110	1	0.70	2	10	2	1	2	7	7	7

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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	GA	SA	SAR	PS %	PSA	ST	BG	S2
1	Justus Annunen	Bandits (OTT)	12	8	3	1	0.868	3.44	698	40	303	166	0.818	11	12	0	1
2	Mikko Koskinen	Bandits (OTT)	2	0	0	0	0.917	1.88	32	1	12	4	0.000	0	0	12	0
Stats d'équipe Total ou en Moyenne			14	8	3	1	0.870	3.37	730	41	315	170	0.818	11	12	12	1

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Astuces sur les Filtres (Anglais seulement)

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

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Status	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial
Adam Wilcox	Bandits (OTT)	G	30	1992-10-12	No	189 Lbs	6 ft0	No	No	No	1	Sans Restriction	Pro & Farm	500,000$	0$	0$	No
Aliaksei Protas	Bandits (OTT)	C	22	2001-01-06	Yes	225 Lbs	6 ft6	No	No	No	2	Avec Restriction	Pro & Farm	950,000$	0$	0$	No
Ben Gleason	Bandits (OTT)	D	24	1998-10-12	Yes	180 Lbs	6 ft1	No	No	No	4	Avec Restriction	Pro & Farm	800,000$	0$	0$	No
Brett Leason	Bandits (OTT)	RW	24	1999-04-30	No	218 Lbs	6 ft5	No	No	No	2	Avec Restriction	Pro & Farm	950,000$	0$	0$	No
Chris Wideman	Bandits (OTT)	D	33	1990-01-07	No	181 Lbs	5 ft10	No	No	No	3	Sans Restriction	Pro & Farm	950,000$	0$	0$	No
Declan Chisholm	Bandits (OTT)	D	23	2000-01-12	Yes	185 Lbs	6 ft1	No	No	No	2	Avec Restriction	Pro & Farm	800,000$	0$	0$	No
Jack Studnicka	Bandits (OTT)	RW	24	1999-02-18	Yes	187 Lbs	6 ft1	No	No	No	4	Avec Restriction	Pro & Farm	800,000$	0$	0$	No
Jay Beagle	Bandits (OTT)	C	38	1984-10-16	No	210 Lbs	6 ft3	No	No	No	1	Sans Restriction	Pro & Farm	800,000$	0$	0$	No
Jeffrey Viel	Bandits (OTT)	LW	26	1997-01-28	Yes	205 Lbs	6 ft2	No	No	No	3	Avec Restriction	Pro & Farm	800,000$	0$	0$	No
Joey Anderson	Bandits (OTT)	RW	25	1998-06-19	Yes	207 Lbs	6 ft0	No	No	No	4	Avec Restriction	Pro & Farm	800,000$	0$	0$	No
Joey Keane	Bandits (OTT)	D	24	1999-07-02	Yes	187 Lbs	6 ft0	No	No	No	1	Avec Restriction	Pro & Farm	800,000$	0$	0$	No
Jordan Spence	Bandits (OTT)	D	22	2001-02-24	Yes	180 Lbs	5 ft10	No	No	No	2	Avec Restriction	Pro & Farm	1,000,000$	0$	0$	No
Josh Archibald	Bandits (OTT)	LW	30	1992-10-06	No	176 Lbs	5 ft10	No	No	No	3	Sans Restriction	Pro & Farm	1,000,000$	0$	0$	No
Justus Annunen	Bandits (OTT)	G	23	2000-03-11	Yes	210 Lbs	6 ft4	No	No	No	2	Avec Restriction	Pro & Farm	800,000$	0$	0$	No
Kirill Marchenko	Bandits (OTT)	LW	23	2000-07-21	Yes	197 Lbs	6 ft3	No	No	No	4	Avec Restriction	Pro & Farm	1,200,000$	0$	0$	No
Kyle Burroughs	Bandits (OTT)	D	28	1995-07-12	No	193 Lbs	6 ft0	No	No	No	3	Sans Restriction	Pro & Farm	900,000$	0$	0$	No
Matt Irwin	Bandits (OTT)	D	35	1987-11-29	No	200 Lbs	6 ft2	No	No	No	1	Sans Restriction	Pro & Farm	800,000$	0$	0$	No
Mikko Koskinen	Bandits (OTT)	G	35	1988-07-18	No	202 Lbs	6 ft7	No	No	No	2	Sans Restriction	Pro & Farm	3,500,000$	0$	0$	No
Nikita Okhotyuk	Bandits (OTT)	D	22	2000-12-04	Yes	195 Lbs	6 ft1	No	No	No	2	Avec Restriction	Pro & Farm	800,000$	0$	0$	No
Nils Hoglander	Bandits (OTT)	RW	22	2000-12-20	Yes	185 Lbs	5 ft9	No	No	No	3	Avec Restriction	Pro & Farm	1,000,000$	0$	0$	No
Phillip Di Giuseppe	Bandits (OTT)	LW	29	1993-10-09	No	193 Lbs	6 ft0	No	No	No	3	Sans Restriction	Pro & Farm	900,000$	0$	0$	No
Rasmus Asplund	Bandits (OTT)	C	25	1997-12-03	Yes	185 Lbs	5 ft11	No	No	No	1	Avec Restriction	Pro & Farm	1,250,000$	0$	0$	No
Riley Stillman	Bandits (OTT)	D	25	1998-03-09	No	196 Lbs	6 ft1	No	No	No	4	Avec Restriction	Pro & Farm	1,000,000$	0$	0$	No
Ronald Attard	Bandits (OTT)	D	24	1999-03-20	No	208 Lbs	6 ft3	No	No	No	3	Avec Restriction	Pro & Farm	1,025,000$	0$	0$	No
Rudolfs Balcers	Bandits (OTT)	RW	26	1997-04-08	No	182 Lbs	5 ft11	No	No	No	4	Avec Restriction	Pro & Farm	900,000$	0$	0$	No
Sam Carrick	Bandits (OTT)	C	31	1992-02-04	No	200 Lbs	6 ft0	No	No	No	3	Sans Restriction	Pro & Farm	850,000$	0$	0$	No
Sean Walker	Bandits (OTT)	D	28	1994-11-13	No	195 Lbs	5 ft11	No	No	No	4	Sans Restriction	Pro & Farm	750,000$	0$	0$	No
Trevor Moore	Bandits (OTT)	RW	28	1995-03-31	No	195 Lbs	5 ft10	No	No	No	4	Sans Restriction	Pro & Farm	2,000,000$	0$	0$	No
Tristen Robins	Bandits (OTT)	C	21	2001-11-15	Yes	176 Lbs	5 ft10	No	No	No	4	Avec Restriction	Pro & Farm	800,000$	0$	0$	No

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
29	26.55	195 Lbs	6 ft1	2.72	1,014,655$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Kirill Marchenko	Jay Beagle		35	1	2	2
2	Phillip Di Giuseppe	Sam Carrick	Joey Anderson	30	1	2	2
3	Josh Archibald	Aliaksei Protas	Nils Hoglander	25	1	2	2
4		Rasmus Asplund	Jack Studnicka	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Sean Walker	Riley Stillman	35	1	2	2
2	Chris Wideman	Ronald Attard	30	1	2	2
3	Nikita Okhotyuk	Declan Chisholm	25	1	2	2
4	Sean Walker	Riley Stillman	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Kirill Marchenko	Jay Beagle		55	1	2	2
2	Phillip Di Giuseppe	Sam Carrick	Joey Anderson	45	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Sean Walker	Riley Stillman	55	1	2	2
2	Chris Wideman	Ronald Attard	45	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1		Kirill Marchenko	55	1	2	2
2	Phillip Di Giuseppe	Josh Archibald	45	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Sean Walker	Riley Stillman	55	1	2	2
2	Chris Wideman	Ronald Attard	45	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1		55	1	2	2	Sean Walker	Riley Stillman	55	1	2	2
2	Kirill Marchenko	45	1	2	2	Chris Wideman	Ronald Attard	45	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1		Kirill Marchenko	55	1	2	2
2	Phillip Di Giuseppe	Josh Archibald	45	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Sean Walker	Riley Stillman	55	1	2	2
2	Chris Wideman	Ronald Attard	45	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Kirill Marchenko	Jay Beagle		Sean Walker	Riley Stillman

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Kirill Marchenko	Jay Beagle		Sean Walker	Riley Stillman

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Rudolfs Balcers, Aliaksei Protas, Nils Hoglander	Rudolfs Balcers, Aliaksei Protas	Nils Hoglander

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Nikita Okhotyuk, Declan Chisholm, Chris Wideman	Nikita Okhotyuk	Declan Chisholm, Chris Wideman

Tirs de Pénalité
, Kirill Marchenko, Phillip Di Giuseppe, Josh Archibald, Jay Beagle

Gardien
#1 : Justus Annunen, #2 : Mikko Koskinen

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	CoolFm	2	0	1	0	0	0	1	0	5	8	-3	1	0	0	0	0	0	1	0	4	3	1	1	0	1	0	0	0	0	0	1	5	-4	2	0.500	5	6	11	0	0	5	23	15	5	73	110	131	117	21	46	13	10	47	6	0	0.00%	5	3	40.00%	0	147	261	56.32%	121	213	56.81%	107	181	59.12%	237	122	256	117	236	119
2	Goons	1	0	0	0	1	0	0	0	3	2	1	1	0	0	0	1	0	0	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	3	5	8	0	0	5	23	15	5	26	110	131	117	21	36	13	11	21	2	0	0.00%	3	0	100.00%	0	147	261	56.32%	121	213	56.81%	107	181	59.12%	237	122	256	117	236	119
3	Hunters	1	0	0	0	1	0	0	0	6	5	1	1	0	0	0	1	0	0	0	6	5	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	6	11	17	0	0	5	23	15	5	34	110	131	117	21	22	4	6	22	6	2	33.33%	3	0	100.00%	0	147	261	56.32%	121	213	56.81%	107	181	59.12%	237	122	256	117	236	119
4	Husky	2	2	0	0	0	0	0	0	14	6	8	0	0	0	0	0	0	0	0	0	0	0	2	2	0	0	0	0	0	0	14	6	8	4	1.000	14	23	37	0	0	5	23	15	5	68	110	131	117	21	61	20	16	59	11	6	54.55%	3	0	100.00%	0	147	261	56.32%	121	213	56.81%	107	181	59.12%	237	122	256	117	236	119
5	Igloos	1	1	0	0	0	0	0	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	4	3	1	2	1.000	4	7	11	0	0	5	23	15	5	24	110	131	117	21	22	7	9	23	8	2	25.00%	2	0	100.00%	0	147	261	56.32%	121	213	56.81%	107	181	59.12%	237	122	256	117	236	119
6	Marmots	1	1	0	0	0	0	0	0	3	1	2	1	1	0	0	0	0	0	0	3	1	2	0	0	0	0	0	0	0	0	0	0	0	2	1.000	3	5	8	0	0	5	23	15	5	39	110	131	117	21	11	8	2	24	3	1	33.33%	1	0	100.00%	0	147	261	56.32%	121	213	56.81%	107	181	59.12%	237	122	256	117	236	119
7	Spartans	1	0	0	0	1	0	0	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	3	2	1	2	1.000	3	6	9	0	0	5	23	15	5	21	110	131	117	21	31	17	0	17	3	1	33.33%	0	0	0.00%	0	147	261	56.32%	121	213	56.81%	107	181	59.12%	237	122	256	117	236	119
	Total	12	4	3	0	3	0	1	1	47	42	5	6	1	1	0	2	0	1	1	24	24	0	6	3	2	0	1	0	0	0	23	18	5	17	0.708	47	80	127	0	0	5	23	15	5	369	110	131	117	21	315	111	95	283	49	15	30.61%	30	7	76.67%	0	147	261	56.32%	121	213	56.81%	107	181	59.12%	237	122	256	117	236	119
9	Xpress	3	0	2	0	0	0	0	1	9	15	-6	2	0	1	0	0	0	0	1	8	13	-5	1	0	1	0	0	0	0	0	1	2	-1	1	0.167	9	17	26	0	0	5	23	15	5	84	110	131	117	21	86	29	41	70	10	3	30.00%	13	4	69.23%	0	147	261	56.32%	121	213	56.81%	107	181	59.12%	237	122	256	117	236	119
	_Since Last GM Reset	12	4	3	0	3	0	1	1	47	42	5	6	1	1	0	2	0	1	1	24	24	0	6	3	2	0	1	0	0	0	23	18	5	17	0.708	47	80	127	0	0	5	23	15	5	369	110	131	117	21	315	111	95	283	49	15	30.61%	30	7	76.67%	0	147	261	56.32%	121	213	56.81%	107	181	59.12%	237	122	256	117	236	119
	_Vs Conference	11	4	3	0	2	0	1	1	44	40	4	6	1	1	0	2	0	1	1	24	24	0	5	3	2	0	0	0	0	0	20	16	4	15	0.682	44	74	118	0	0	5	23	15	5	348	110	131	117	21	284	94	95	266	46	14	30.43%	30	7	76.67%	0	147	261	56.32%	121	213	56.81%	107	181	59.12%	237	122	256	117	236	119
	_Vs Division	10	3	3	0	2	0	1	1	41	39	2	5	0	1	0	2	0	1	1	21	23	-2	5	3	2	0	0	0	0	0	20	16	4	13	0.650	41	69	110	0	0	5	23	15	5	309	110	131	117	21	273	86	93	242	43	13	30.23%	29	7	75.86%	0	147	261	56.32%	121	213	56.81%	107	181	59.12%	237	122	256	117	236	119

			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
12	17	L1	47	80	127	369	315	111	95	283	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
12	4	3	3	0	1	1	47	42

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
6	1	1	2	0	1	1	24	24

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
6	3	2	1	0	0	0	23	18

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
3	3	3	0	1	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
49	15	30.61%	30	7	76.67%	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
110	131	117	21	5	23	15	5

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
147	261	56.32%	121	213	56.81%	107	181	59.12%

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
237	122	256	117	236	119

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
1 - 2024-04-06	7	Bandits	10	Husky	3	W			Sommaire du Match
3 - 2024-04-08	24	Xpress	6	Bandits	5	L	X	X	Sommaire du Match
4 - 2024-04-09	37	Marmots	1	Bandits	3	W			Sommaire du Match
7 - 2024-04-12	67	Hunters	5	Bandits	6	W	X		Sommaire du Match
9 - 2024-04-14	88	Bandits	4	Husky	3	W			Sommaire du Match
10 - 2024-04-15	96	Bandits	1	CoolFm	5	L			Sommaire du Match
11 - 2024-04-16	108	CoolFm	3	Bandits	4	W	X	X	Sommaire du Match
12 - 2024-04-17	129	Goons	2	Bandits	3	W	X		Sommaire du Match
14 - 2024-04-19	141	Bandits	1	Xpress	2	L			Sommaire du Match
15 - 2024-04-20	158	Bandits	4	Igloos	3	W			Sommaire du Match
16 - 2024-04-21	167	Bandits	3	Spartans	2	W	X		Sommaire du Match
17 - 2024-04-22	182	Xpress	7	Bandits	3	L			Sommaire du Match
19 - 2024-04-24	195	Bandits	-	Hunters	-
20 - 2024-04-25	212	Hunters	-	Bandits	-
22 - 2024-04-27	232	Husky	-	Bandits	-
24 - 2024-04-29	248	Bandits	-	Saguenéens	-
25 - 2024-04-30	262	Twins	-	Bandits	-
27 - 2024-05-02	281	Vandals	-	Bandits	-
28 - 2024-05-03	300	Bandits	-	Marmots	-
29 - 2024-05-04	309	Bandits	-	Vipers	-
31 - 2024-05-06	324	Igloos	-	Bandits	-
32 - 2024-05-07	342	CoolFm	-	Bandits	-
34 - 2024-05-09	353	Bandits	-	Thugs	-
35 - 2024-05-10	373	Wolves	-	Bandits	-
37 - 2024-05-12	395	Bandits	-	Raptors	-
38 - 2024-05-13	406	Chiwawa	-	Bandits	-
39 - 2024-05-14	416	Bandits	-	Igloos	-
42 - 2024-05-17	440	TigersCats	-	Bandits	-
43 - 2024-05-18	455	Bandits	-	Scorpions	-
44 - 2024-05-19	471	Bandits	-	Supreme	-
45 - 2024-05-20	475	Bandits	-	Farmers	-
46 - 2024-05-21	490	Scorpions	-	Bandits	-
47 - 2024-05-22	507	Bandits	-	Spartans	-
48 - 2024-05-23	519	Supreme	-	Bandits	-
50 - 2024-05-25	539	Igloos	-	Bandits	-
52 - 2024-05-27	560	Xpress	-	Bandits	-
54 - 2024-05-29	579	Bandits	-	Husky	-
56 - 2024-05-31	595	Bandits	-	Barracudas	-
57 - 2024-06-01	602	Husky	-	Bandits	-
59 - 2024-06-03	622	Saguenéens	-	Bandits	-
60 - 2024-06-04	638	Bandits	-	Grizzlies	-
62 - 2024-06-06	655	Smirnoff Ice	-	Bandits	-
63 - 2024-06-07	668	Bandits	-	Smirnoff Ice	-
64 - 2024-06-08	683	Bandits	-	Snowbirds	-
65 - 2024-06-09	694	Bandits	-	Predateurs	-
66 - 2024-06-10	707	Predateurs	-	Bandits	-
67 - 2024-06-11	720	Bandits	-	Vandals	-
69 - 2024-06-13	738	Thugs	-	Bandits	-
71 - 2024-06-15	759	Barracudas	-	Bandits	-
72 - 2024-06-16	778	Bandits	-	Wolves	-
73 - 2024-06-17	788	Goons	-	Bandits	-
75 - 2024-06-19	811	Marlies	-	Bandits	-
76 - 2024-06-20	821	Bandits	-	Hunters	-
77 - 2024-06-21	839	Outlaws	-	Bandits	-
79 - 2024-06-23	856	Bandits	-	Marlies	-
80 - 2024-06-24	870	Grizzlies	-	Bandits	-
82 - 2024-06-26	885	Bandits	-	TigersCats	-
83 - 2024-06-27	903	Marmots	-	Bandits	-
84 - 2024-06-28	914	Bandits	-	Warriors	-
86 - 2024-06-30	930	Warriors	-	Bandits	-
87 - 2024-07-01	943	Bandits	-	Xpress	-
89 - 2024-07-03	957	Bandits	-	Rockets	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
90 - 2024-07-04	973	Bandits	-	CoolFm	-
91 - 2024-07-05	982	Snowbirds	-	Bandits	-
92 - 2024-07-06	999	Bandits	-	Twins	-
94 - 2024-07-08	1015	Raptors	-	Bandits	-
96 - 2024-07-10	1032	Bandits	-	Chiwawa	-
97 - 2024-07-11	1043	Bayou	-	Bandits	-
99 - 2024-07-13	1064	Spartans	-	Bandits	-
100 - 2024-07-14	1070	Bandits	-	Outlaws	-
103 - 2024-07-17	1093	Bandits	-	Bayou	-
104 - 2024-07-18	1102	Farmers	-	Bandits	-
106 - 2024-07-20	1124	Rockets	-	Bandits	-
107 - 2024-07-21	1137	Bandits	-	Goons	-
110 - 2024-07-24	1156	Bandits	-	Goons	-
112 - 2024-07-26	1170	Vipers	-	Bandits	-

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	11,949	6,000
Assistance PCT	99.58%	100.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
32	2992 - 99.72%	101,643$	609,858$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
777,345$	2,942,500$	2,942,500$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	487,432$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
3,252,576$	95	41,969$	3,987,055$

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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
Saison Régulière
45	82	39	29	0	6	4	4	0	325	269	56	41	20	13	0	3	1	4	0	168	129	39	41	19	16	0	3	3	0	0	157	140	17	102	325	547	872	0	2	67	132	116	12	2824	744	1049	1001	42	2221	656	775	1271	253	78	30.83%	254	53	79.13%	9	954	1745	54.67%	788	1503	52.43%	715	1331	53.72%	1908	1261	1802	631	1243	628
46	82	29	34	0	4	5	3	7	334	342	-8	41	20	9	0	2	2	2	6	188	172	16	41	9	25	0	2	3	1	1	146	170	-24	84	334	538	872	0	1	67	119	141	10	2552	732	890	904	71	2399	784	740	1675	257	75	29.18%	299	86	71.24%	5	886	1622	54.62%	848	1643	51.61%	749	1315	56.96%	1482	748	2017	738	1482	744
47	12	4	3	0	3	0	1	1	47	42	5	6	1	1	0	2	0	1	1	24	24	0	6	3	2	0	1	0	0	0	23	18	5	17	47	80	127	0	0	5	23	15	5	369	110	131	117	21	315	111	95	283	49	15	30.61%	30	7	76.67%	0	147	261	56.32%	121	213	56.81%	107	181	59.12%	237	122	256	117	236	119
Total Saison Régulière	176	72	66	0	13	9	8	8	706	653	53	88	41	23	0	7	3	7	7	380	325	55	88	31	43	0	6	6	1	1	326	328	-2	203	706	1165	1871	0	3	139	274	272	27	5745	1586	2070	2022	134	4935	1551	1610	3229	559	168	30.05%	583	146	74.96%	14	1987	3628	54.77%	1757	3359	52.31%	1571	2827	55.57%	3628	2131	4077	1487	2963	1492
Séries
45	13	6	7	0	0	0	0	0	41	51	-10	7	4	3	0	0	0	0	0	20	24	-4	6	2	4	0	0	0	0	0	21	27	-6	12	41	66	107	0	0	9	17	15	0	388	108	134	143	3	409	140	131	207	41	14	34.15%	54	14	74.07%	0	121	258	46.90%	123	290	42.41%	95	219	43.38%	230	118	353	110	221	113
Total Séries	13	6	7	0	0	0	0	0	41	51	-10	7	4	3	0	0	0	0	0	20	24	-4	6	2	4	0	0	0	0	0	21	27	-6	12	41	66	107	0	0	9	17	15	0	388	108	134	143	3	409	140	131	207	41	14	34.15%	54	14	74.07%	0	121	258	46.90%	123	290	42.41%	95	219	43.38%	230	118	353	110	221	113

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