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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP	Âge	Contrat	Salaire
1	Joel Farabee (R)		X			100.00	67	81	79	84	63	67	64	67	34	70	68	63	53	49	49	69	50	64	0	21	3	1,425,000$
2	Michael McLeod (R)	X				100.00	81	44	89	79	70	56	85	59	74	63	55	72	25	47	47	64	50	63	0	23	3	1,363,333$
3	Brett Seney	X	X			100.00	60	56	70	77	56	82	87	63	79	60	62	58	59	49	49	64	50	62	0	25	2	825,000$
4	Alexander True	X				100.00	84	45	94	67	78	55	77	63	65	70	55	56	25	56	56	63	50	62	0	23	1	800,000$
5	Boris Katchouk		X			100.00	75	71	84	61	71	80	85	60	50	56	59	64	56	44	44	63	50	61	0	23	3	894,166$
6	Garrett Pilon	X				100.00	71	63	90	68	63	78	83	61	76	56	61	62	58	44	44	64	50	61	0	23	3	894,166$
7	Brian Pinho	X				100.00	72	64	92	66	64	80	85	60	75	54	62	62	59	44	44	64	50	61	0	26	3	700,000$
8	Joshua Ho-Sang (R)			X		100.00	74	64	96	77	64	61	62	61	50	60	57	63	54	44	44	62	50	60	0	25	4	875,000$
9	Logan O'Connor			X		100.00	78	43	95	64	64	51	80	62	25	50	64	63	25	45	45	64	50	59	0	24	4	925,000$
10	Tyler Steenbergen	X	X	X		100.00	73	66	89	68	66	73	77	57	71	57	53	62	50	44	44	60	50	59	0	23	3	875,000$
11	Anton Blidh		X	X		100.00	59	73	25	69	73	60	62	58	50	38	70	58	67	57	57	59	50	57	0	26	3	750,000$
12	Jacob Larsson				X	100.00	67	42	93	77	73	69	85	57	25	51	48	75	25	60	60	62	50	66	0	24	2	894,166$
13	Haydn Fleury				X	100.00	76	45	93	72	82	62	64	58	25	56	50	72	75	58	59	62	50	65	0	25	1	1,713,333$
14	Gabriel Carlsson				X	100.00	79	75	89	78	75	69	75	50	25	42	41	65	39	52	52	56	50	62	0	24	3	894,166$
15	Jacob Middleton				X	100.00	83	99	75	68	79	55	68	58	25	54	47	68	25	51	51	60	50	62	0	25	2	735,000$
16	Gavin Bayreuther				X	100.00	76	72	86	63	72	77	83	53	25	49	42	63	40	45	45	56	50	61	0	27	2	955,000$
17	Frederic Allard				X	100.00	73	66	90	61	66	73	79	51	25	46	40	62	38	50	50	54	50	59	0	23	3	921,666$
Rayé
1	Rudolfs Balcers		X			100.00	78	43	99	65	61	62	81	73	26	61	58	59	25	49	49	63	50	61	0	24	2	925,000$
2	Jonathan Ang	X				100.00	68	61	85	60	61	74	79	57	71	56	53	59	50	44	44	58	50	58	0	23	3	910,833$
3	Dennis Yan		X			100.00	75	72	82	63	72	66	69	56	50	47	58	65	55	52	52	60	50	58	0	24	3	935,833$
4	Tanner Kaspick	X				100.00	77	75	83	65	75	68	73	50	63	47	47	62	45	44	44	55	50	56	0	23	3	822,222$
5	Ben Gleason				X	100.00	71	69	76	62	69	69	75	48	25	39	41	59	39	44	44	52	50	57	0	23	2	761,666$

	MOYENNE D'ÉQUIPE					100.00	74	63	84	69	69	68	76	58	47	54	54	63	45	49	49	61	50	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	Alexandar Georgiev	100.00	73	72	69	66	74	72	66	72	80	73	68	55	55	72	50	69	0
2	Hunter Miska	100.00	63	56	70	63	67	67	58	67	66	64	30	44	44	63	50	61	0
Rayé
1	Landon Bow	100.00	53	69	86	86	48	54	50	57	50	50	30	44	44	54	50	57	0

	MOYENNE D'ÉQUIPE	100.00	63	66	75	72	63	64	58	65	65	62	43	48	48	63	50	62

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Trent Cull	71	40	53	58	50	41	52	CAN	43	1	750,000$

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Astuces sur les Filtres (Anglais seulement)

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

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#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	GW	GT	FO%	FOT	P/20	FW	S1	S2	S3
1	Joel Farabee	Comets (VAN)	LW	21	8	11	19	4	18	0	22	59	46	18	32	17.39%	5	514	24.51	3	6	9	12	94	2	96	1	1	28.86%	201	0.74	0	0	2	1
2	Michael McLeod	Comets (VAN)	C	21	6	13	19	4	8	0	29	54	33	12	21	18.18%	7	446	21.25	2	8	10	11	95	1	102	1	1	51.34%	372	0.85	0	2	1	2
3	Brett Seney	Comets (VAN)	C/LW	21	5	8	13	8	12	0	13	55	33	13	39	15.15%	6	475	22.65	2	4	6	15	101	1	79	1	1	55.77%	208	0.55	0	2	2	1
4	Alexander True	Comets (VAN)	C	21	4	7	11	2	14	0	32	33	24	9	14	16.67%	2	379	18.05	0	4	4	3	30	0	68	1	0	46.71%	304	0.58	0	1	1	4
5	Jacob Larsson	Comets (VAN)	D	16	4	7	11	-1	12	0	11	19	23	10	12	17.39%	10	376	23.52	3	3	6	17	68	0	78	1	0	0.00%	0	0.58	0	1	2	0
6	Jacob Middleton	Comets (VAN)	D	21	1	9	10	6	41	5	48	18	11	9	8	9.09%	20	450	21.45	1	4	5	9	89	0	74	1	0	0.00%	0	0.44	1	0	0	1
7	Boris Katchouk	Comets (VAN)	LW	21	5	4	9	4	14	0	27	24	29	6	25	17.24%	2	335	15.97	1	2	3	7	69	0	23	1	0	42.31%	26	0.54	0	1	1	1
8	Gavin Bayreuther	Comets (VAN)	D	21	1	8	9	4	28	0	28	14	12	6	14	8.33%	14	490	23.34	1	4	5	9	101	0	94	1	0	0.00%	0	0.37	0	0	1	1
9	Tyler Steenbergen	Comets (VAN)	C/LW/RW	21	4	5	9	2	2	0	17	25	31	10	19	12.90%	2	374	17.82	2	1	3	7	41	0	49	0	0	60.87%	46	0.48	0	1	1	1
10	Logan O'Connor	Comets (VAN)	RW	21	6	2	8	4	8	0	19	16	31	11	25	19.35%	0	349	16.62	2	0	2	4	60	0	0	1	0	38.46%	26	0.46	0	2	0	1
11	Joshua Ho-Sang	Comets (VAN)	RW	21	3	5	8	0	6	0	6	21	16	5	14	18.75%	1	258	12.33	3	3	6	4	60	0	0	1	1	15.38%	13	0.62	0	0	0	1
12	Garrett Pilon	Comets (VAN)	C	21	1	5	6	0	16	0	15	33	13	13	11	7.69%	2	315	15.02	0	0	0	0	0	0	1	1	0	47.14%	140	0.38	0	0	1	0
13	Haydn Fleury	Comets (VAN)	D	21	2	3	5	1	32	0	28	18	24	11	16	8.33%	12	488	23.25	2	3	5	18	94	0	84	2	0	0.00%	0	0.20	0	0	1	0
14	Gabriel Carlsson	Comets (VAN)	D	9	0	5	5	7	12	0	26	3	5	1	2	0.00%	0	142	15.79	0	0	0	1	1	0	7	0	0	0.00%	0	0.70	0	0	0	0
15	Brian Pinho	Comets (VAN)	C	21	1	4	5	1	10	0	8	17	19	6	11	5.26%	2	220	10.51	0	2	2	5	30	1	20	1	0	53.52%	142	0.45	0	1	0	0
16	Anton Blidh	Comets (VAN)	LW/RW	9	3	0	3	6	10	0	15	7	6	3	4	50.00%	1	129	14.37	1	0	1	1	39	0	0	2	0	44.44%	9	0.46	0	0	1	1
17	Rudolfs Balcers	Comets (VAN)	LW	12	1	1	2	0	8	0	8	30	17	6	12	5.88%	1	201	16.81	0	0	0	1	10	0	13	0	0	28.00%	25	0.20	0	0	0	0
18	Frederic Allard	Comets (VAN)	D	21	0	2	2	7	32	0	34	9	6	1	7	0.00%	11	376	17.92	0	0	0	4	24	0	40	0	0	0.00%	0	0.11	0	0	0	0
19	Dennis Yan	Comets (VAN)	LW	7	0	0	0	1	2	0	3	3	5	1	1	0.00%	0	33	4.75	0	0	0	0	0	0	0	0	0	100.00%	1	0.00	0	0	0	0
Stats d'équipe Total ou en Moyenne				347	55	99	154	60	285	5	389	458	384	151	287	14.32%	98	6357	18.32	23	44	67	128	1016	5	835	16	4	47.06%	1513	0.48	1	11	14	15

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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	SO	GA	SA	A	ST	BG	S1	S3
1	Alexandar Georgiev	Comets (VAN)	21	16	4	1	0.902	1.66	1336	5	37	376	2	21	0	5	1
2	Hunter Miska	Comets (VAN)	1	0	0	0	0.900	2.86	21	0	1	10	0	0	21	0	0
Stats d'équipe Total ou en Moyenne			22	16	4	1	0.902	1.68	1358	5	38	386	2	21	21	5	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	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Salaire Année 4	Link
Alexandar Georgiev	Comets (VAN)	G	25	1996-02-10	No	176 Lbs	6 ft1	No	No	No	1	Pro & Farm	925,000$	0$	0$	No				Lien / Lien NHL
Alexander True	Comets (VAN)	C	23	1997-07-17	No	201 Lbs	6 ft5	No	No	No	1	Pro & Farm	800,000$	0$	0$	No				Lien / Lien NHL
Anton Blidh	Comets (VAN)	LW/RW	26	1995-03-14	No	201 Lbs	6 ft0	No	No	No	3	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$		Lien / Lien NHL
Ben Gleason	Comets (VAN)	D	23	1998-03-25	No	185 Lbs	6 ft1	No	No	No	2	Pro & Farm	761,666$	0$	0$	No	761,666$			Lien / Lien NHL
Boris Katchouk	Comets (VAN)	LW	23	1998-06-18	No	192 Lbs	6 ft1	No	No	No	3	Pro & Farm	894,166$	0$	0$	No	894,166$	894,166$		Lien / Lien NHL
Brett Seney	Comets (VAN)	C/LW	25	1996-02-28	No	156 Lbs	5 ft9	No	No	No	2	Pro & Farm	825,000$	0$	0$	No	825,000$			Lien / Lien NHL
Brian Pinho	Comets (VAN)	C	26	1995-05-10	No	173 Lbs	6 ft0	No	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$		Lien / Lien NHL
Dennis Yan	Comets (VAN)	LW	24	1997-04-14	No	197 Lbs	6 ft1	No	No	No	3	Pro & Farm	935,833$	0$	0$	No	935,833$	935,833$		Lien / Lien NHL
Frederic Allard	Comets (VAN)	D	23	1997-12-27	No	179 Lbs	6 ft1	No	No	No	3	Pro & Farm	921,666$	0$	0$	No	921,666$	921,666$		Lien / Lien NHL
Gabriel Carlsson	Comets (VAN)	D	24	1997-01-02	No	192 Lbs	6 ft5	No	No	No	3	Pro & Farm	894,166$	0$	0$	No	894,166$	894,166$		Lien / Lien NHL
Garrett Pilon	Comets (VAN)	C	23	1998-04-13	No	175 Lbs	5 ft10	No	No	No	3	Pro & Farm	894,166$	0$	0$	No	894,166$	894,166$		Lien / Lien NHL
Gavin Bayreuther	Comets (VAN)	D	27	1994-05-12	No	195 Lbs	6 ft1	No	No	No	2	Pro & Farm	955,000$	0$	0$	No	955,000$			Lien / Lien NHL
Haydn Fleury	Comets (VAN)	D	25	1996-07-08	No	221 Lbs	6 ft3	No	No	No	1	Pro & Farm	1,713,333$	0$	0$	No				Lien / Lien NHL
Hunter Miska	Comets (VAN)	G	26	1995-07-06	No	170 Lbs	6 ft1	No	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$		Lien / Lien NHL
Jacob Larsson	Comets (VAN)	D	24	1997-04-29	No	195 Lbs	6 ft2	No	No	No	2	Pro & Farm	894,166$	0$	0$	No	894,166$			Lien / Lien NHL
Jacob Middleton	Comets (VAN)	D	25	1996-01-01	No	200 Lbs	6 ft3	No	No	No	2	Pro & Farm	735,000$	0$	0$	No	735,000$			Lien / Lien NHL
Joel Farabee	Comets (VAN)	LW	21	2000-02-24	Yes	164 Lbs	6 ft0	No	No	No	3	Pro & Farm	1,425,000$	0$	0$	No	1,425,000$	1,425,000$		Lien / Lien NHL
Jonathan Ang	Comets (VAN)	C	23	1998-01-31	No	165 Lbs	5 ft11	No	No	No	3	Pro & Farm	910,833$	0$	0$	No	910,833$	910,833$		Lien / Lien NHL
Joshua Ho-Sang	Comets (VAN)	RW	25	1996-01-22	Yes	173 Lbs	6 ft0	No	No	No	4	Pro & Farm	875,000$	0$	0$	No	875,000$	875,000$	875,000$	Lien / Lien NHL
Landon Bow	Comets (VAN)	G	25	1995-08-23	No	214 Lbs	6 ft4	No	No	No	1	Pro & Farm	700,000$	0$	0$	No				Lien / Lien NHL
Logan O'Connor	Comets (VAN)	RW	24	1996-08-14	No	174 Lbs	6 ft0	No	No	No	4	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$	925,000$	Lien / Lien NHL
Michael McLeod	Comets (VAN)	C	23	1998-02-03	Yes	187 Lbs	6 ft2	No	No	No	3	Pro & Farm	1,363,333$	0$	0$	No	1,363,333$	1,363,333$		Lien / Lien NHL
Rudolfs Balcers	Comets (VAN)	LW	24	1997-04-08	No	165 Lbs	5 ft11	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$			Lien / Lien NHL
Tanner Kaspick	Comets (VAN)	C	23	1998-01-28	No	205 Lbs	6 ft1	No	No	No	3	Pro & Farm	822,222$	0$	0$	No	822,222$	822,222$		Lien / Lien NHL
Tyler Steenbergen	Comets (VAN)	C/LW/RW	23	1998-01-07	No	187 Lbs	5 ft10	No	No	No	3	Pro & Farm	875,000$	0$	0$	No	875,000$	875,000$		Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
25	24.12	186 Lbs	6 ft1	2.52	924,822$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Joel Farabee	Michael McLeod	Anton Blidh	55	0	2	3
2	Brett Seney	Alexander True	Logan O'Connor	25	0	2	3
3	Boris Katchouk	Garrett Pilon	Tyler Steenbergen	15	0	2	3
4	Joel Farabee	Brian Pinho	Joshua Ho-Sang	5	0	2	3

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jacob Larsson	Haydn Fleury	40	1	2	2
2	Jacob Middleton	Gavin Bayreuther	30	1	2	2
3	Frederic Allard	Gabriel Carlsson	20	1	2	2
4	Jacob Larsson	Haydn Fleury	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Joel Farabee	Michael McLeod	Anton Blidh	60	0	1	4
2	Boris Katchouk	Brett Seney	Logan O'Connor	40	0	1	4

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jacob Larsson	Haydn Fleury	60	0	2	3
2	Jacob Middleton	Gavin Bayreuther	40	0	2	3

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Joel Farabee	Michael McLeod	60	1	2	2
2	Brett Seney	Alexander True	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jacob Larsson	Haydn Fleury	60	1	2	2
2	Jacob Middleton	Gavin Bayreuther	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Joel Farabee	60	1	2	2	Jacob Larsson	Haydn Fleury	60	1	2	2
2	Michael McLeod	40	1	2	2	Jacob Middleton	Gavin Bayreuther	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Joel Farabee	Michael McLeod	60	1	2	2
2	Brett Seney	Alexander True	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jacob Larsson	Haydn Fleury	60	1	2	2
2	Jacob Middleton	Gavin Bayreuther	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Joel Farabee	Michael McLeod	Anton Blidh	Jacob Larsson	Haydn Fleury

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Joel Farabee	Michael McLeod	Joshua Ho-Sang	Jacob Larsson	Haydn Fleury

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Brian Pinho, Alexander True, Tyler Steenbergen	Brian Pinho, Logan O'Connor	Tyler Steenbergen

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Frederic Allard, Jacob Middleton, Gavin Bayreuther	Frederic Allard	Jacob Middleton, Gavin Bayreuther

Tirs de Pénalité
Joel Farabee, Michael McLeod, Brett Seney, Alexander True, Garrett Pilon

Gardien
#1 : Alexandar Georgiev, #2 : Hunter Miska

Lignes d'Attaque Perso. en Prol.
Joel Farabee, Michael McLeod, Brett Seney, Alexander True, Garrett Pilon, Boris Katchouk, Boris Katchouk, Brian Pinho, , , Logan O'Connor

Lignes de Défense Perso. en Prol.
Jacob Larsson, Haydn Fleury, Jacob Middleton, Gavin Bayreuther, Frederic Allard

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	Condors	4	4	0	0	0	0	0	0	16	8	8	2	2	0	0	0	0	0	0	6	3	3	2	2	0	0	0	0	0	0	10	5	5	8	1.000	16	29	45	0	0	13	24	13	5	73	109	146	98	31	55	13	51	64	27	8	29.63%	22	4	81.82%	0	288	584	49.32%	274	624	43.91%	150	305	49.18%	545	372	534	169	279	141
2	Marlies	4	4	0	0	0	0	0	0	11	4	7	2	2	0	0	0	0	0	0	5	1	4	2	2	0	0	0	0	0	0	6	3	3	8	1.000	11	20	31	0	2	13	24	13	5	66	109	146	98	31	47	12	48	71	21	4	19.05%	21	1	95.24%	0	288	584	49.32%	274	624	43.91%	150	305	49.18%	545	372	534	169	279	141
3	Phantoms	7	4	3	0	0	0	0	0	16	16	0	4	3	1	0	0	0	0	0	10	5	5	3	1	2	0	0	0	0	0	6	11	-5	8	0.571	16	30	46	0	1	13	24	13	5	150	109	146	98	31	146	39	96	142	59	9	15.25%	45	7	84.44%	0	288	584	49.32%	274	624	43.91%	150	305	49.18%	545	372	534	169	279	141
4	Thunderbirds	6	4	2	0	0	0	0	0	12	10	2	3	2	1	0	0	0	0	0	7	7	0	3	2	1	0	0	0	0	0	5	3	2	8	0.667	12	20	32	0	2	13	24	13	5	95	109	146	98	31	138	34	90	113	25	2	8.00%	44	6	86.36%	0	288	584	49.32%	274	624	43.91%	150	305	49.18%	545	372	534	169	279	141
	Total	21	16	5	0	0	0	0	0	55	38	17	11	9	2	0	0	0	0	0	28	16	12	10	7	3	0	0	0	0	0	27	22	5	32	0.762	55	99	154	0	5	13	24	13	5	384	109	146	98	31	386	98	285	390	132	23	17.42%	132	18	86.36%	0	288	584	49.32%	274	624	43.91%	150	305	49.18%	545	372	534	169	279	141
	_Since Last GM Reset	21	16	5	0	0	0	0	0	55	38	17	11	9	2	0	0	0	0	0	28	16	12	10	7	3	0	0	0	0	0	27	22	5	32	0.762	55	99	154	0	5	13	24	13	5	384	109	146	98	31	386	98	285	390	132	23	17.42%	132	18	86.36%	0	288	584	49.32%	274	624	43.91%	150	305	49.18%	545	372	534	169	279	141
	_Vs Conference	17	12	5	0	0	0	0	0	39	30	9	9	7	2	0	0	0	0	0	22	13	9	8	5	3	0	0	0	0	0	17	17	0	24	0.706	39	70	109	0	5	13	24	13	5	311	109	146	98	31	331	85	234	326	105	15	14.29%	110	14	87.27%	0	288	584	49.32%	274	624	43.91%	150	305	49.18%	545	372	534	169	279	141
	_Vs Division	10	4	0	0	0	0	0	0	23	14	9	5	2	0	0	0	0	0	0	12	8	4	5	2	0	0	0	0	0	0	11	6	5	8	0.400	23	40	63	0	4	13	24	13	5	161	109	146	98	31	185	46	138	184	46	6	13.04%	65	7	89.23%	0	288	584	49.32%	274	624	43.91%	150	305	49.18%	545	372	534	169	279	141

			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
21	32	W4	55	99	154	384	386	98	285	390	0	5

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
21	16	5	0	0	0	0	55	38

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
11	9	2	0	0	0	0	28	16

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
10	7	3	0	0	0	0	27	22

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
7	2	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
132	23	17.42%	132	18	86.36%	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
109	146	98	31	13	24	13	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
288	584	49.32%	274	624	43.91%	150	305	49.18%

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
545	372	534	169	279	141

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 - 2020-10-24	1	Phantoms	2	Comets	1	L		Sommaire du Match
3 - 2020-10-26	9	Phantoms	1	Comets	2	W		Sommaire du Match
5 - 2020-10-28	17	Comets	4	Phantoms	3	W	X	Sommaire du Match
7 - 2020-10-30	25	Comets	2	Phantoms	3	L	X	Sommaire du Match
9 - 2020-11-01	33	Phantoms	2	Comets	6	W		Sommaire du Match
11 - 2020-11-03	41	Comets	0	Phantoms	5	L		Sommaire du Match
13 - 2020-11-05	49	Phantoms	0	Comets	1	W	X	Sommaire du Match
15 - 2020-11-07	57	Marlies	0	Comets	3	W		Sommaire du Match
17 - 2020-11-09	61	Marlies	1	Comets	2	W	X	Sommaire du Match
19 - 2020-11-11	65	Comets	2	Marlies	0	W		Sommaire du Match
21 - 2020-11-13	69	Comets	4	Marlies	3	W	X	Sommaire du Match
29 - 2020-11-21	85	Thunderbirds	0	Comets	2	W		Sommaire du Match
31 - 2020-11-23	87	Thunderbirds	5	Comets	1	L		Sommaire du Match
33 - 2020-11-25	89	Comets	2	Thunderbirds	0	W		Sommaire du Match
35 - 2020-11-27	91	Comets	1	Thunderbirds	2	L		Sommaire du Match
37 - 2020-11-29	93	Thunderbirds	2	Comets	4	W		Sommaire du Match
39 - 2020-12-01	95	Comets	2	Thunderbirds	1	W	X	Sommaire du Match
43 - 2020-12-05	99	Condors	1	Comets	2	W		Sommaire du Match
44 - 2020-12-06	100	Condors	2	Comets	4	W		Sommaire du Match
45 - 2020-12-07	101	Comets	5	Condors	3	W		Sommaire du Match
46 - 2020-12-08	102	Comets	5	Condors	2	W		Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité	2000	1000
Prix des Billets	100	0
Assistance	14,938	10,967
Assistance PCT	67.90%	99.70%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité	Popularité de l'Équipe
30	2355 - 78.50%	135,800$	1,493,800$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
0$	2,312,056$	2,185,723$	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
2020	82	59	15	0	1	1	3	3	347	120	227	41	30	6	0	1	0	3	1	188	63	125	41	29	9	0	0	1	0	2	159	57	102	130	347	627	974	1	23	143	97	103	9	2315	806	686	803	49	1237	354	888	1525	349	57	16.33%	373	33	91.15%	7	1464	2316	63.21%	1076	1847	58.26%	756	1210	62.48%	2596	1981	1437	477	920	525
Total Saison Régulière	82	59	15	0	1	1	3	3	347	120	227	41	30	6	0	1	0	3	1	188	63	125	41	29	9	0	0	1	0	2	159	57	102	130	347	627	974	1	23	143	97	103	9	2315	806	686	803	49	1237	354	888	1525	349	57	16.33%	373	33	91.15%	7	1464	2316	63.21%	1076	1847	58.26%	756	1210	62.48%	2596	1981	1437	477	920	525
2020	21	16	5	0	0	0	0	0	55	38	17	11	9	2	0	0	0	0	0	28	16	12	10	7	3	0	0	0	0	0	27	22	5	32	55	99	154	0	5	13	24	13	5	384	109	146	98	31	386	98	285	390	132	23	17.42%	132	18	86.36%	0	288	584	49.32%	274	624	43.91%	150	305	49.18%	545	372	534	169	279	141
Total Séries	21	16	5	0	0	0	0	0	55	38	17	11	9	2	0	0	0	0	0	28	16	12	10	7	3	0	0	0	0	0	27	22	5	32	55	99	154	0	5	13	24	13	5	384	109	146	98	31	386	98	285	390	132	23	17.42%	132	18	86.36%	0	288	584	49.32%	274	624	43.91%	150	305	49.18%	545	372	534	169	279	141

	Comets
	GP: 21 \| W: 16 \| L: 5 GF: 55 \| GA: 38 \| PP%: 17.42% \| PK%: 86.36% DG: Rob \| Morale : 50 \| Moyenne d'Équipe : 61