OTHL - Comets

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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	Chris Terry		X	X		100.00	74	69	85	71	69	79	82	68	50	63	67	68	64	54	54	68	50	66	0
2	Jamie McGinn		X			100.00	83	45	89	78	75	57	67	65	25	63	72	55	25	75	77	69	50	65	0
3	Joshua Ho-Sang			X		100.00	55	40	82	81	64	68	75	82	25	60	59	67	25	48	48	65	50	64	0
4	Valeri Nichushkin (R)		X	X		100.00	77	44	99	70	78	62	71	63	44	64	55	68	25	61	61	64	50	63	0
5	Rudolfs Balcers (R)		X			100.00	65	41	90	65	61	62	89	67	29	70	66	62	25	47	47	67	50	62	0
6	Gabriel Dumont	X		X		100.00	66	65	68	70	65	68	70	65	80	62	61	64	58	58	59	63	50	62	0
7	Joel L'Esperance (R)	X		X		100.00	77	44	89	73	75	62	78	68	53	50	60	58	25	45	45	62	50	60	0
8	Logan O'Connor (R)			X		100.00	71	64	86	64	64	69	71	62	50	59	60	62	57	44	44	63	50	60	0
9	Nic Petan	X	X	X		100.00	57	40	96	79	62	48	62	62	45	60	57	51	25	56	56	59	50	58	0
10	Matt Lorito		X	X		100.00	67	61	82	66	61	59	59	62	50	60	61	60	58	44	44	62	50	58	0
11	Jacob Larsson (R)				X	100.00	71	43	89	77	73	72	76	60	25	50	47	77	25	56	56	61	50	66	0
12	Haydn Fleury				X	100.00	78	45	96	72	82	60	76	58	25	45	47	67	75	53	53	59	50	63	0
13	Ben Gleason (R)				X	100.00	74	69	85	60	69	78	85	54	25	52	41	62	39	44	44	56	50	60	0
14	Jacob Middleton (R)				X	100.00	73	76	67	60	76	74	80	51	25	43	42	62	40	49	49	54	50	59	0
15	Brogan Rafferty (R)				X	100.00	50	50	50	50	50	50	50	50	50	50	50	50	50	50	59	50	50	50	0
Rayé
1	J.T. Brown	X		X		100.00	83	55	84	73	61	53	63	57	33	59	57	71	25	68	71	63	50	61	0
2	Brett Seney (R)	X	X			100.00	73	54	82	77	57	57	58	57	58	63	59	64	25	49	49	63	50	60	0
3	Anton Blidh		X	X		100.00	71	73	65	69	73	82	90	53	50	47	51	63	48	56	56	58	50	59	0
4	Steven Fogarty	X		X		100.00	67	43	99	62	77	48	86	53	45	50	55	55	25	44	44	58	50	56	0
5	Danick Martel		X			100.00	58	57	60	67	57	56	58	52	50	53	44	56	42	55	55	52	50	54	0

	MOYENNE D'ÉQUIPE					100.00	70	54	82	69	67	63	72	60	42	56	56	62	39	53	54	61	50	60

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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	Cory Schneider	100.00	64	67	67	80	65	63	57	65	71	64	72	68	69	65	50	66	0
2	Landon Bow (R)	100.00	54	77	96	86	48	56	51	59	50	50	30	44	44	55	50	58	0
Rayé
1	Hunter Miska (R)	100.00	51	61	76	63	48	51	50	56	49	49	30	44	44	52	50	53	0

	MOYENNE D'ÉQUIPE	100.00	56	68	80	76	54	57	53	60	57	54	44	52	52	57	50	59

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Trent Cull	71	40	53	58	50	41	52	CAN	42	2	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	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Joshua Ho-Sang	Comets (VAN)	RW	80	54	73	127	96	6	0	26	139	369	117	265	14.63%	22	1657	20.72	10	6	16	44	220	0	2	2	11	201	11	3	50.75%	400	3	1.53	0	2	0	0	0	6	13	8
2	Rudolfs Balcers	Comets (VAN)	LW	82	56	56	112	98	6	0	28	75	276	74	152	20.29%	9	1315	16.05	4	2	6	13	63	1	0	1	4	96	10	2	58.97%	117	5	1.70	0	0	0	0	0	12	6	4
3	Valeri Nichushkin	Comets (VAN)	LW/RW	82	49	49	98	71	28	0	99	94	263	66	176	18.63%	16	1589	19.39	5	13	18	25	205	2	1	3	7	194	9	1	52.94%	136	2	1.23	1	3	0	0	0	4	11	6
4	Joel L'Esperance	Comets (VAN)	C/RW	82	48	47	95	95	44	0	85	91	260	56	144	18.46%	6	1209	14.74	2	1	3	7	35	0	0	0	1	88	5	0	68.09%	937	3	1.57	0	0	0	0	0	8	5	5
5	Gabriel Dumont	Comets (VAN)	C/RW	82	26	69	95	71	38	0	99	104	204	59	161	12.75%	10	1424	17.38	0	19	19	15	219	1	1	2	5	95	3	1	75.28%	1351	1	1.33	1	1	0	0	0	5	2	2
6	Logan O'Connor	Comets (VAN)	RW	82	34	56	90	93	35	5	64	58	202	50	142	16.83%	9	1199	14.63	4	5	9	19	97	0	0	0	0	11	5	0	65.28%	72	1	1.50	0	0	0	1	0	1	5	7
7	J.T. Brown	Comets (VAN)	C/RW	76	26	62	88	70	85	5	161	74	186	55	149	13.98%	9	1220	16.06	6	13	19	21	186	0	0	0	0	2	4	0	54.52%	840	0	1.44	0	0	0	0	1	4	2	6
8	Chris Terry	Comets (VAN)	LW/RW	55	37	40	77	46	38	0	93	107	229	77	163	16.16%	8	1319	23.99	8	5	13	36	169	2	1	3	11	197	4	1	63.17%	448	3	1.17	2	4	0	0	0	8	3	3
9	Brett Seney	Comets (VAN)	C/LW	59	17	38	55	53	20	0	50	41	106	29	70	16.04%	4	633	10.74	0	0	0	0	3	0	0	0	4	62	1	0	66.80%	256	0	1.74	0	0	0	0	0	1	3	4
10	Haydn Fleury	Comets (VAN)	D	82	5	42	47	50	65	5	138	32	63	26	45	7.94%	51	1763	21.51	3	11	14	30	202	0	1	1	1	231	2	1	0.00%	0	0	0.53	0	0	0	1	0	0	1	1
11	Ben Gleason	Comets (VAN)	D	82	3	38	41	88	49	5	107	26	46	21	39	6.52%	64	1737	21.18	1	6	7	24	195	0	1	1	0	246	2	0	0.00%	0	0	0.47	0	0	1	0	0	1	1	1
12	Jacob Larsson	Comets (VAN)	D	44	9	32	41	24	16	0	59	27	49	20	34	18.37%	39	1006	22.88	5	7	12	27	134	1	1	2	2	150	0	0	0.00%	0	0	0.81	0	0	0	0	0	2	0	1
13	Matt Lorito	Comets (VAN)	LW/RW	81	22	13	35	31	19	5	26	30	112	28	72	19.64%	4	530	6.54	0	0	0	0	0	0	0	0	0	2	1	1	43.48%	23	0	1.32	0	0	0	0	1	0	0	3
14	Anton Blidh	Comets (VAN)	LW/RW	53	12	21	33	44	52	10	63	31	101	27	59	11.88%	5	619	11.68	0	0	0	0	1	0	0	0	1	23	3	2	64.71%	34	1	1.07	0	0	1	0	1	2	3	0
15	Jacob Middleton	Comets (VAN)	D	61	3	29	32	71	98	30	129	16	30	11	18	10.00%	36	1126	18.47	0	2	2	10	80	0	0	0	0	96	1	0	0.00%	0	0	0.57	0	0	1	2	2	0	1	3
16	Jamie McGinn	Comets (VAN)	LW	27	15	16	31	18	28	0	47	25	86	20	60	17.44%	3	542	20.08	5	3	8	18	71	0	0	0	3	74	1	0	55.56%	27	1	1.14	1	2	0	0	0	2	3	0
17	Brogan Rafferty	Comets (VAN)	D	72	4	14	18	113	48	0	69	6	23	9	7	17.39%	24	1164	16.17	0	0	0	1	32	0	0	0	0	78	2	0	0.00%	0	0	0.31	0	0	0	0	0	1	1	2
18	Nic Petan	Comets (VAN)	C/LW/RW	23	2	16	18	31	10	0	15	9	14	4	7	14.29%	5	314	13.66	0	0	0	0	1	0	0	0	0	3	0	0	58.62%	58	0	1.15	0	0	0	0	0	0	2	1
19	Steven Fogarty	Comets (VAN)	C/RW	23	3	9	12	10	12	0	7	11	29	9	16	10.34%	1	195	8.50	0	0	0	0	0	0	0	0	0	0	0	0	69.43%	157	0	1.23	0	0	0	0	0	0	0	1
Stats d'équipe Total ou en Moyenne				1228	425	720	1145	1173	697	65	1365	996	2648	758	1779	16.05%	325	20571	16.75	53	93	146	290	1919	7	8	15	50	1856	64	12	64.83%	4856	20	1.11	5	12	3	4	5	57	62	58

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Landon Bow	Comets (VAN)	42	31	7	1	0.884	1.79	2379	2	10	71	612	0	1	1.000	4	40	44	1	2	1
2	Alexandar Georgiev	Canucks	22	17	3	2	0.897	1.49	1326	2	5	33	319	2	0	0.500	2	22	0	0	0	2
3	Cory Schneider	Comets (VAN)	16	13	3	0	0.872	1.96	920	0	2	30	234	0	0	0.800	5	16	0	0	0	0
4	Hunter Miska	Comets (VAN)	3	1	0	0	1.000	0.00	81	0	0	0	29	0	0	0.000	0	0	34	0	0	0
Stats d'équipe Total ou en Moyenne			83	62	13	3	0.888	1.71	4707	4	17	134	1194	2	1	0.818	11	78	78	1	2	3

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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	Link
Anton Blidh	Comets (VAN)	LW/RW	25	1995-03-14	No	201 Lbs	6 ft0	No	No	No	1	Pro & Farm	925,000$	0$	0$	No			Lien
Ben Gleason	Comets (VAN)	D	22	1998-03-25	Yes	185 Lbs	6 ft1	No	No	No	3	Pro & Farm	761,666$	0$	0$	No	761,666$	761,666$	Lien
Brett Seney	Comets (VAN)	C/LW	24	1996-02-28	Yes	156 Lbs	5 ft9	No	No	No	3	Pro & Farm	825,000$	0$	0$	No	825,000$	825,000$	Lien
Brogan Rafferty	Comets (VAN)	D	24	1995-05-28 8:07:10 AM	Yes	195 Lbs	6 ft0	Yes	No	No	2	Pro & Farm	700,000$	0$	0$	No	700,000$
Chris Terry	Comets (VAN)	LW/RW	31	1989-04-07	No	195 Lbs	5 ft10	No	No	No	1	Pro & Farm	850,000$	0$	0$	No			Lien
Cory Schneider	Comets (VAN)	G	34	1986-03-18	No	200 Lbs	6 ft3	Yes	No	No	3	Pro & Farm	4,000,000$	0$	0$	No	4,000,000$	4,000,000$	Lien
Danick Martel	Comets (VAN)	LW	25	1994-12-12	No	162 Lbs	5 ft8	No	No	No	2	Pro & Farm	700,000$	0$	0$	No	700,000$		Lien
Gabriel Dumont	Comets (VAN)	C/RW	29	1990-10-06	No	181 Lbs	5 ft10	No	No	No	1	Pro & Farm	650,000$	0$	0$	No			Lien
Haydn Fleury	Comets (VAN)	D	23	1996-07-08	No	221 Lbs	6 ft3	No	No	No	2	Pro & Farm	1,713,333$	0$	0$	No	1,713,333$		Lien
Hunter Miska	Comets (VAN)	G	24	1995-07-06	Yes	170 Lbs	6 ft1	No	No	No	1	Pro & Farm	625,000$	0$	0$	No			Lien
J.T. Brown	Comets (VAN)	C/RW	29	1990-07-02	No	169 Lbs	5 ft10	No	No	No	2	Pro & Farm	1,250,000$	0$	0$	No	1,250,000$		Lien
Jacob Larsson	Comets (VAN)	D	22	1997-04-29	Yes	195 Lbs	6 ft2	No	No	No	3	Pro & Farm	894,166$	0$	0$	No	894,166$	894,166$	Lien
Jacob Middleton	Comets (VAN)	D	24	1996-01-01	Yes	200 Lbs	6 ft3	No	No	No	3	Pro & Farm	735,000$	0$	0$	No	735,000$	735,000$	Lien
Jamie McGinn	Comets (VAN)	LW	31	1988-08-05	No	205 Lbs	6 ft1	Yes	No	No	1	Pro & Farm	950,000$	0$	0$	No			Lien
Joel L'Esperance	Comets (VAN)	C/RW	24	1995-08-18	Yes	201 Lbs	6 ft2	No	No	No	2	Pro & Farm	722,500$	0$	0$	No	722,500$		Lien
Joshua Ho-Sang	Comets (VAN)	RW	24	1996-01-22	No	173 Lbs	6 ft0	No	No	No	1	Pro & Farm	1,075,833$	0$	0$	No			Lien
Landon Bow	Comets (VAN)	G	24	1995-08-23	Yes	214 Lbs	6 ft4	No	No	No	1	Pro & Farm	625,000$	0$	0$	No			Lien
Logan O'Connor	Comets (VAN)	RW	23	1996-08-14	Yes	174 Lbs	6 ft0	Yes	No	No	1	Pro & Farm	950,000$	0$	0$	No			Lien
Matt Lorito	Comets (VAN)	LW/RW	29	1990-07-03	No	170 Lbs	5 ft9	No	No	No	2	Pro & Farm	800,000$	0$	0$	No	800,000$		Lien
Nic Petan	Comets (VAN)	C/LW/RW	25	1995-03-21	No	179 Lbs	5 ft9	No	No	No	1	Pro & Farm	863,333$	0$	0$	No			Lien
Rudolfs Balcers	Comets (VAN)	LW	23	1997-04-08	Yes	165 Lbs	5 ft11	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$	Lien
Steven Fogarty	Comets (VAN)	C/RW	27	1993-04-18	No	206 Lbs	6 ft3	No	No	No	2	Pro & Farm	750,000$	0$	0$	No	750,000$		Lien
Valeri Nichushkin	Comets (VAN)	LW/RW	25	1995-03-04	Yes	205 Lbs	6 ft4	No	No	No	2	Pro & Farm	2,950,000$	0$	0$	No	2,950,000$		Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
23	25.70	188 Lbs	6 ft0	1.87	1,097,427$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Chris Terry	Gabriel Dumont	Joshua Ho-Sang	40	1	2	2
2	Jamie McGinn		Valeri Nichushkin	30	1	2	2
3	Rudolfs Balcers	Joel L'Esperance	Logan O'Connor	20	1	2	2
4	Matt Lorito	Nic Petan	Chris Terry	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Haydn Fleury	40	1	2	2
2	Ben Gleason	Jacob Middleton	30	1	2	2
3	Brogan Rafferty	Nic Petan	20	1	2	2
4		Haydn Fleury	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Chris Terry	Gabriel Dumont	Joshua Ho-Sang	60	1	2	2
2	Jamie McGinn		Valeri Nichushkin	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Haydn Fleury	60	1	2	2
2	Ben Gleason	Jacob Middleton	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Chris Terry	Jamie McGinn	60	1	2	2
2	Joshua Ho-Sang	Valeri Nichushkin	40	1	2	2

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

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Chris Terry	60	1	2	2		Haydn Fleury	60	1	2	2
2	Jamie McGinn	40	1	2	2	Ben Gleason	Jacob Middleton	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Chris Terry	Jamie McGinn	60	1	2	2
2	Joshua Ho-Sang	Valeri Nichushkin	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Haydn Fleury	60	1	2	2
2	Ben Gleason	Jacob Middleton	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Chris Terry	Gabriel Dumont	Joshua Ho-Sang		Haydn Fleury

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Chris Terry	Gabriel Dumont	Joshua Ho-Sang		Haydn Fleury

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Rudolfs Balcers, Logan O'Connor, Joel L'Esperance	Rudolfs Balcers, Logan O'Connor	Joel L'Esperance

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Brogan Rafferty, Ben Gleason, Jacob Middleton	Brogan Rafferty	Ben Gleason, Jacob Middleton

Tirs de Pénalité
Chris Terry, Jamie McGinn, Joshua Ho-Sang, Valeri Nichushkin, Gabriel Dumont

Gardien
#1 : Cory Schneider, #2 : Landon Bow

Lignes d'Attaque Perso. en Prol.
, , , , , , , , , ,

Lignes de Défense Perso. en Prol.
, , , ,

Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

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

	Ligue												Domicile											Visiteur
#	VS Équipe	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	PCT	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
1	Americans	2	0	1	0	1	0	0	0	6	6	0	1	0	0	0	1	0	0	0	5	4	1	1	0	1	0	0	0	0	0	1	2	-1	2	0.500	6	11	17	0	0	179	132	119	9	55	895	909	933	27	40	10	18	28	13	3	23.08%	8	0	100.00%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
2	Admirals	3	3	0	0	0	0	0	0	22	7	15	2	2	0	0	0	0	0	0	16	2	14	1	1	0	0	0	0	0	0	6	5	1	6	1.000	22	39	61	0	1	179	132	119	9	108	895	909	933	27	44	16	31	55	5	1	20.00%	13	3	76.92%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
3	Barracudas	5	4	1	0	0	0	0	0	23	9	14	2	2	0	0	0	0	0	0	12	1	11	3	2	1	0	0	0	0	0	11	8	3	8	0.800	23	39	62	0	2	179	132	119	9	156	895	909	933	27	85	31	97	102	23	3	13.04%	27	4	85.19%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
4	Bears	2	1	0	0	0	0	1	0	12	5	7	1	1	0	0	0	0	0	0	8	2	6	1	0	0	0	0	0	1	0	4	3	1	4	1.000	12	20	32	0	0	179	132	119	9	73	895	909	933	27	34	8	24	42	5	1	20.00%	12	1	91.67%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
5	Bruins	2	2	0	0	0	0	0	0	12	3	9	1	1	0	0	0	0	0	0	9	2	7	1	1	0	0	0	0	0	0	3	1	2	4	1.000	12	20	32	0	0	179	132	119	9	62	895	909	933	27	36	7	14	36	13	3	23.08%	7	1	85.71%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
6	Checkers	2	0	1	0	0	0	0	1	6	8	-2	1	0	1	0	0	0	0	0	3	4	-1	1	0	0	0	0	0	0	1	3	4	-1	1	0.250	6	10	16	0	0	179	132	119	9	37	895	909	933	27	29	5	22	50	11	3	27.27%	10	1	90.00%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
7	Condors	4	1	3	0	0	0	0	0	6	11	-5	2	0	2	0	0	0	0	0	2	6	-4	2	1	1	0	0	0	0	0	4	5	-1	2	0.250	6	11	17	1	0	179	132	119	9	86	895	909	933	27	72	20	49	68	27	1	3.70%	20	4	80.00%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
8	Crunch	2	2	0	0	0	0	0	0	11	4	7	1	1	0	0	0	0	0	0	6	1	5	1	1	0	0	0	0	0	0	5	3	2	4	1.000	11	20	31	0	0	179	132	119	9	76	895	909	933	27	15	2	8	37	11	3	27.27%	4	1	75.00%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
9	Devils	2	2	0	0	0	0	0	0	19	3	16	1	1	0	0	0	0	0	0	11	2	9	1	1	0	0	0	0	0	0	8	1	7	4	1.000	19	36	55	0	0	179	132	119	9	119	895	909	933	27	23	6	18	38	2	0	0.00%	9	1	88.89%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
10	Eagles	3	3	0	0	0	0	0	0	27	2	25	2	2	0	0	0	0	0	0	16	1	15	1	1	0	0	0	0	0	0	11	1	10	6	1.000	27	53	80	0	1	179	132	119	9	148	895	909	933	27	37	6	8	60	8	5	62.50%	3	0	100.00%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
11	Griffins	2	1	1	0	0	0	0	0	10	3	7	1	1	0	0	0	0	0	0	8	0	8	1	0	1	0	0	0	0	0	2	3	-1	2	0.500	10	19	29	0	1	179	132	119	9	75	895	909	933	27	29	10	12	33	5	0	0.00%	5	0	100.00%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
12	Gulls	4	2	2	0	0	0	0	0	12	8	4	2	1	1	0	0	0	0	0	7	4	3	2	1	1	0	0	0	0	0	5	4	1	4	0.500	12	23	35	0	2	179	132	119	9	119	895	909	933	27	81	26	26	72	10	3	30.00%	13	1	92.31%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
13	Heat	4	2	1	0	0	0	1	0	10	9	1	2	1	0	0	0	0	1	0	5	3	2	2	1	1	0	0	0	0	0	5	6	-1	6	0.750	10	17	27	0	0	179	132	119	9	95	895	909	933	27	77	22	54	74	16	2	12.50%	25	2	92.00%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
14	IceHogs	3	0	2	0	0	1	0	0	4	7	-3	2	0	1	0	0	1	0	0	2	4	-2	1	0	1	0	0	0	0	0	2	3	-1	1	0.167	4	7	11	0	0	179	132	119	9	68	895	909	933	27	65	18	39	78	7	0	0.00%	16	1	93.75%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
15	Marlies	2	2	0	0	0	0	0	0	11	2	9	1	1	0	0	0	0	0	0	7	0	7	1	1	0	0	0	0	0	0	4	2	2	4	1.000	11	18	29	0	1	179	132	119	9	63	895	909	933	27	30	9	18	37	5	3	60.00%	9	0	100.00%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
16	Monsters	2	1	0	0	0	0	1	0	9	4	5	1	1	0	0	0	0	0	0	6	2	4	1	0	0	0	0	0	1	0	3	2	1	4	1.000	9	14	23	0	0	179	132	119	9	39	895	909	933	27	34	11	18	33	12	0	0.00%	9	0	100.00%	1	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
17	Moose	3	1	1	0	1	0	0	0	6	4	2	1	0	1	0	0	0	0	0	1	3	-2	2	1	0	0	1	0	0	0	5	1	4	4	0.667	6	11	17	0	1	179	132	119	9	106	895	909	933	27	57	13	55	64	10	1	10.00%	20	3	85.00%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
18	Penguins	2	2	0	0	0	0	0	0	7	4	3	1	1	0	0	0	0	0	0	3	1	2	1	1	0	0	0	0	0	0	4	3	1	4	1.000	7	12	19	0	0	179	132	119	9	68	895	909	933	27	32	9	14	44	10	2	20.00%	7	0	100.00%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
19	Phantoms	2	1	1	0	0	0	0	0	10	6	4	1	1	0	0	0	0	0	0	8	3	5	1	0	1	0	0	0	0	0	2	3	-1	2	0.500	10	18	28	0	0	179	132	119	9	87	895	909	933	27	26	7	14	34	5	2	40.00%	7	2	71.43%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
20	Rampage	3	3	0	0	0	0	0	0	25	6	19	2	2	0	0	0	0	0	0	16	4	12	1	1	0	0	0	0	0	0	9	2	7	6	1.000	25	45	70	0	0	179	132	119	9	110	895	909	933	27	35	10	32	73	7	3	42.86%	15	3	80.00%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
21	Reign	4	4	0	0	0	0	0	0	36	5	31	2	2	0	0	0	0	0	0	19	2	17	2	2	0	0	0	0	0	0	17	3	14	8	1.000	36	66	102	0	1	179	132	119	9	175	895	909	933	27	39	10	26	84	4	2	50.00%	13	3	76.92%	1	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
22	Roadrunners	4	3	0	0	0	1	0	0	22	11	11	2	1	0	0	0	1	0	0	14	6	8	2	2	0	0	0	0	0	0	8	5	3	7	0.875	22	39	61	0	0	179	132	119	9	98	895	909	933	27	71	30	43	75	13	4	30.77%	17	4	76.47%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
23	Rocket	2	2	0	0	0	0	0	0	6	4	2	1	1	0	0	0	0	0	0	3	2	1	1	1	0	0	0	0	0	0	3	2	1	4	1.000	6	10	16	0	0	179	132	119	9	34	895	909	933	27	39	10	42	46	12	3	25.00%	19	2	89.47%	1	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
24	Senators	2	2	0	0	0	0	0	0	13	1	12	1	1	0	0	0	0	0	0	10	0	10	1	1	0	0	0	0	0	0	3	1	2	4	1.000	13	23	36	0	1	179	132	119	9	88	895	909	933	27	14	4	8	40	7	1	14.29%	4	0	100.00%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
25	Sound Tigers	2	2	0	0	0	0	0	0	13	4	9	1	1	0	0	0	0	0	0	8	2	6	1	1	0	0	0	0	0	0	5	2	3	4	1.000	13	22	35	0	0	179	132	119	9	76	895	909	933	27	42	15	20	51	5	2	40.00%	10	0	100.00%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
26	Stars	3	3	0	0	0	0	0	0	23	2	21	1	1	0	0	0	0	0	0	2	0	2	2	2	0	0	0	0	0	0	21	2	19	6	1.000	23	41	64	0	1	179	132	119	9	135	895	909	933	27	45	6	12	68	8	1	12.50%	6	0	100.00%	1	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
27	Thunderbirds	2	1	0	0	1	0	0	0	11	3	8	1	1	0	0	0	0	0	0	8	1	7	1	0	0	0	1	0	0	0	3	2	1	4	1.000	11	22	33	0	0	179	132	119	9	47	895	909	933	27	35	11	21	39	7	1	14.29%	7	2	71.43%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
	Total	82	59	14	0	3	2	3	1	436	147	289	41	31	6	0	1	2	1	0	247	65	182	41	28	8	0	2	0	2	1	189	82	107	133	0.811	436	776	1212	1	17	179	132	119	9	2751	895	909	933	27	1280	365	828	1630	281	59	21.00%	343	41	88.05%	7	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
29	Wild	3	3	0	0	0	0	0	0	27	0	27	1	1	0	0	0	0	0	0	10	0	10	2	2	0	0	0	0	0	0	17	0	17	6	1.000	27	48	75	0	3	179	132	119	9	130	895	909	933	27	26	10	26	55	5	4	80.00%	12	0	100.00%	2	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
30	Wolf Pack	2	2	0	0	0	0	0	0	16	1	15	1	1	0	0	0	0	0	0	8	0	8	1	1	0	0	0	0	0	0	8	1	7	4	1.000	16	27	43	0	1	179	132	119	9	98	895	909	933	27	20	3	6	41	3	1	33.33%	2	0	100.00%	0	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
31	Wolves	4	4	0	0	0	0	0	0	21	5	16	2	2	0	0	0	0	0	0	14	3	11	2	2	0	0	0	0	0	0	7	2	5	8	1.000	21	35	56	0	1	179	132	119	9	120	895	909	933	27	68	20	53	73	12	1	8.33%	14	2	85.71%	1	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
	_Since Last GM Reset	82	59	14	0	3	2	3	1	436	147	289	41	31	6	0	1	2	1	0	247	65	182	41	28	8	0	2	0	2	1	189	82	107	133	0.811	436	776	1212	1	17	179	132	119	9	2751	895	909	933	27	1280	365	828	1630	281	59	21.00%	343	41	88.05%	7	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
	_Vs Conference	30	23	3	0	1	0	2	1	166	55	111	15	14	1	0	0	0	0	0	106	22	84	15	9	2	0	1	0	2	1	60	33	27	53	0.883	166	291	457	0	4	179	132	119	9	1042	895	909	933	27	438	117	259	601	113	25	22.12%	121	11	90.91%	2	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
	_Vs Division	16	12	1	0	0	0	1	0	80	26	54	8	7	0	0	0	0	0	0	56	10	46	8	5	1	0	0	0	1	0	24	16	8	26	0.813	80	143	223	0	3	179	132	119	9	500	895	909	933	27	238	63	141	296	73	17	23.29%	63	6	90.48%	1	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527

			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
82	133	W3	436	776	1212	2751	1280	365	828	1630	1	17

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
82	59	14	3	2	3	1	436	147

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	31	6	1	2	1	0	247	65

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	28	8	2	0	2	1	189	82

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
7	2	0	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
281	59	21.00%	343	41	88.05%	7

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
895	909	933	27	179	132	119	9

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
1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%

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
2777	2184	1283	422	890	527

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 - 2019-10-04	1	Comets	2	Condors	4	L			Sommaire du Match
4 - 2019-10-07	21	Comets	1	Heat	5	L			Sommaire du Match
8 - 2019-10-11	46	Reign	1	Comets	11	W			Sommaire du Match
11 - 2019-10-14	73	Phantoms	3	Comets	8	W			Sommaire du Match
14 - 2019-10-17	89	Griffins	0	Comets	8	W			Sommaire du Match
16 - 2019-10-19	104	Comets	9	Rampage	2	W			Sommaire du Match
18 - 2019-10-21	116	Comets	8	Devils	1	W			Sommaire du Match
19 - 2019-10-22	127	Comets	8	Wolf Pack	1	W			Sommaire du Match
21 - 2019-10-24	137	Comets	2	Griffins	3	L			Sommaire du Match
24 - 2019-10-27	159	Bears	2	Comets	8	W			Sommaire du Match
27 - 2019-10-30	178	Thunderbirds	1	Comets	8	W			Sommaire du Match
29 - 2019-11-01	191	Comets	9	Reign	0	W			Sommaire du Match
31 - 2019-11-03	196	Comets	2	Gulls	0	W			Sommaire du Match
32 - 2019-11-04	216	Comets	5	Barracudas	3	W			Sommaire du Match
35 - 2019-11-07	233	Rampage	2	Comets	6	W			Sommaire du Match
37 - 2019-11-09	240	Comets	2	IceHogs	3	L			Sommaire du Match
38 - 2019-11-10	251	Comets	2	Moose	1	W	X		Sommaire du Match
40 - 2019-11-12	268	Devils	2	Comets	11	W			Sommaire du Match
42 - 2019-11-14	279	Admirals	0	Comets	7	W			Sommaire du Match
44 - 2019-11-16	293	Stars	0	Comets	2	W			Sommaire du Match
46 - 2019-11-18	313	Eagles	1	Comets	9	W			Sommaire du Match
49 - 2019-11-21	322	Comets	10	Stars	1	W			Sommaire du Match
51 - 2019-11-23	342	Comets	6	Admirals	5	W			Sommaire du Match
53 - 2019-11-25	361	Comets	4	Bears	3	W	X	X	Sommaire du Match
55 - 2019-11-27	371	Comets	2	Phantoms	3	L			Sommaire du Match
57 - 2019-11-29	386	Comets	4	Penguins	3	W			Sommaire du Match
60 - 2019-12-02	407	Comets	2	Condors	1	W			Sommaire du Match
61 - 2019-12-03	418	Condors	3	Comets	1	L			Sommaire du Match
63 - 2019-12-05	432	Senators	0	Comets	10	W			Sommaire du Match
67 - 2019-12-09	462	Americans	4	Comets	5	W	X		Sommaire du Match
70 - 2019-12-12	481	Marlies	0	Comets	7	W			Sommaire du Match
72 - 2019-12-14	498	Checkers	4	Comets	3	L			Sommaire du Match
74 - 2019-12-16	512	Comets	2	Barracudas	5	L			Sommaire du Match
75 - 2019-12-17	517	Comets	3	Wolves	2	W			Sommaire du Match
77 - 2019-12-19	532	Rocket	2	Comets	3	W			Sommaire du Match
79 - 2019-12-21	546	Wolves	2	Comets	7	W			Sommaire du Match
81 - 2019-12-23	563	Penguins	1	Comets	3	W			Sommaire du Match
83 - 2019-12-25	579	Condors	3	Comets	1	L			Sommaire du Match
88 - 2019-12-30	600	Reign	1	Comets	8	W			Sommaire du Match
89 - 2019-12-31	606	Comets	4	Heat	1	W			Sommaire du Match
93 - 2020-01-04	636	IceHogs	2	Comets	1	L			Sommaire du Match
95 - 2020-01-06	651	Wolf Pack	0	Comets	8	W			Sommaire du Match
98 - 2020-01-09	672	Comets	5	Crunch	3	W			Sommaire du Match
100 - 2020-01-11	682	Comets	3	Thunderbirds	2	W	X		Sommaire du Match
102 - 2020-01-13	692	Comets	1	Americans	2	L			Sommaire du Match
103 - 2020-01-14	706	Comets	8	Wild	0	W			Sommaire du Match
105 - 2020-01-16	724	Comets	3	Moose	0	W			Sommaire du Match
107 - 2020-01-18	738	Roadrunners	1	Comets	10	W			Sommaire du Match
109 - 2020-01-20	754	Barracudas	0	Comets	8	W			Sommaire du Match
118 - 2020-01-29	773	Rampage	2	Comets	10	W			Sommaire du Match
120 - 2020-01-31	780	Comets	4	Barracudas	0	W			Sommaire du Match
123 - 2020-02-03	801	Comets	5	Sound Tigers	2	W			Sommaire du Match
124 - 2020-02-04	806	Comets	3	Checkers	4	L	X	X	Sommaire du Match
126 - 2020-02-06	813	Comets	3	Bruins	1	W			Sommaire du Match
128 - 2020-02-08	832	Comets	9	Wild	0	W			Sommaire du Match
130 - 2020-02-10	851	Heat	1	Comets	2	W			Sommaire du Match
132 - 2020-02-12	864	Admirals	2	Comets	9	W			Sommaire du Match
134 - 2020-02-14	879	IceHogs	2	Comets	1	L	X		Sommaire du Match
138 - 2020-02-18	913	Gulls	0	Comets	5	W			Sommaire du Match
141 - 2020-02-21	932	Wild	0	Comets	10	W			Sommaire du Match
144 - 2020-02-24	957	Bruins	2	Comets	9	W			Sommaire du Match
147 - 2020-02-27	974	Comets	3	Rocket	2	W			Sommaire du Match
149 - 2020-02-29	989	Comets	3	Senators	1	W			Sommaire du Match
151 - 2020-03-02	1010	Comets	4	Marlies	2	W			Sommaire du Match
152 - 2020-03-03	1012	Comets	3	Monsters	2	W	X	X	Sommaire du Match
155 - 2020-03-06	1031	Roadrunners	5	Comets	4	L	X		Sommaire du Match
157 - 2020-03-08	1047	Eagles	0	Comets	7	W			Sommaire du Match
159 - 2020-03-10	1065	Monsters	2	Comets	6	W			Sommaire du Match
161 - 2020-03-12	1078	Sound Tigers	2	Comets	8	W			Sommaire du Match
163 - 2020-03-14	1083	Comets	4	Roadrunners	3	W			Sommaire du Match
164 - 2020-03-15	1095	Comets	11	Eagles	1	W			Sommaire du Match
166 - 2020-03-17	1117	Moose	3	Comets	1	L			Sommaire du Match
169 - 2020-03-20	1136	Crunch	1	Comets	6	W			Sommaire du Match
171 - 2020-03-22	1146	Comets	3	Gulls	4	L			Sommaire du Match
172 - 2020-03-23	1158	Comets	8	Reign	3	W			Sommaire du Match
174 - 2020-03-25	1175	Comets	4	Wolves	0	W			Sommaire du Match
176 - 2020-03-27	1189	Barracudas	1	Comets	4	W			Sommaire du Match
178 - 2020-03-29	1203	Heat	2	Comets	3	W	X	X	Sommaire du Match
179 - 2020-03-30	1215	Gulls	4	Comets	2	L			Sommaire du Match
181 - 2020-04-01	1226	Comets	11	Stars	1	W			Sommaire du Match
184 - 2020-04-04	1242	Comets	4	Roadrunners	2	W			Sommaire du Match
186 - 2020-04-06	1271	Wolves	1	Comets	7	W			Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	100	0
Assistance	43,752	36,514
Assistance PCT	53.36%	89.06%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
0	1958 - 65.26%	106,712$	4,375,200$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
2,994,752$	2,524,083$	2,511,583$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
13,570$	2,244,698$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	0	17,603$	0$

Afficher ou Masquer des Colonnes

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	Ligue											Domicile											Visiteur
Année	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
2019	82	59	14	0	3	2	3	1	436	147	289	41	31	6	0	1	2	1	0	247	65	182	41	28	8	0	2	0	2	1	189	82	107	133	436	776	1212	1	17	179	132	119	9	2751	895	909	933	27	1280	365	828	1630	281	59	21.00%	343	41	88.05%	7	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527
Total Saison Régulière	82	59	14	0	3	2	3	1	436	147	289	41	31	6	0	1	2	1	0	247	65	182	41	28	8	0	2	0	2	1	189	82	107	133	436	776	1212	1	17	179	132	119	9	2751	895	909	933	27	1280	365	828	1630	281	59	21.00%	343	41	88.05%	7	1539	2379	64.69%	944	1620	58.27%	840	1276	65.83%	2777	2184	1283	422	890	527