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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	Lawson Crouse		X			100.00	95	78	85	83	84	65	91	60	49	62	74	78	25	64	64	75	50	70	0	23	2	1,700,000$
2	Gabriel Bourque (C)		X	X		100.00	89	46	95	75	72	52	71	57	35	58	56	66	41	69	71	63	50	62	0	30	1	1,400,000$
3	Anthony Angello	X				100.00	76	79	69	66	79	74	78	58	73	49	63	64	60	44	44	63	50	61	0	25	2	833,750$
4	Nathan Walker		X			100.00	68	62	82	64	62	71	73	62	50	55	66	61	63	44	45	64	50	60	0	27	2	700,000$
5	Kole Sherwood			X		100.00	72	74	66	65	74	66	70	53	50	43	59	60	56	44	44	58	50	57	0	24	1	1,000,000$
6	Jens Looke		X	X		100.00	74	66	92	65	66	71	76	52	50	46	53	62	50	47	47	58	50	57	0	24	3	750,000$
7	Gabriel Fontaine	X				100.00	77	71	90	51	71	58	61	50	63	47	46	64	44	50	50	54	50	54	0	24	3	736,667$
8	Manuel Wiederer	X		X		100.00	71	64	86	61	64	56	58	52	65	53	47	60	45	44	44	55	50	54	0	24	3	736,667$
9	Giorgio Estephan (R)	X				100.00	79	71	99	52	71	58	60	51	64	46	51	63	48	44	44	56	50	54	0	24	3	700,000$
10	Jaycob Megna				X	100.00	85	86	81	60	86	73	80	47	25	36	41	67	39	52	52	54	50	62	0	28	2	800,000$
11	Ben Harpur (A)				X	100.00	81	85	72	65	85	61	64	51	25	44	39	68	37	59	59	54	50	61	0	26	2	800,000$
12	Chris Bigras (A)				X	100.00	75	71	83	63	71	60	63	54	25	49	41	65	39	57	57	55	50	60	0	26	1	900,000$
13	Michael Anderson (R)				X	100.00	76	71	89	77	71	63	67	49	25	41	41	61	39	44	44	54	50	59	0	22	3	1,775,000$
14	Gustav Olofsson (R)				X	100.00	78	73	89	72	73	52	54	49	25	43	39	62	37	44	44	53	50	58	0	26	2	800,000$
15	Devante Stephens (R)				X	100.00	77	72	88	67	72	65	71	46	25	37	39	61	37	44	44	52	50	58	0	24	3	743,333$
16	Jake Dotchin				X	100.00	70	79	49	65	79	56	59	48	25	39	40	61	38	56	56	51	50	57	0	27	1	650,000$
17	Ryan Collins				X	100.00	82	81	84	52	81	55	57	48	25	38	42	64	40	44	44	53	50	56	0	25	3	880,833$
Rayé

	MOYENNE D'ÉQUIPE					100.00	78	72	82	65	74	62	68	52	41	46	49	64	43	50	50	57	50	59

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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	Connor Ingram	100.00	69	64	80	76	70	71	72	77	73	73	30	44	44	70	50	68	0
2	Matthew Villalta (R)	100.00	55	55	55	55	55	55	55	55	55	55	55	55	55	55	50	55	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	62	60	68	66	63	63	64	66	64	64	43	50	50	63	50	62

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Andrew Brewer	44	56	71	74	45	46	56	CAN	34	2	700,000$

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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	Nathan Walker	Bruins (BOS)	LW	82	62	39	101	62	36	0	83	124	354	101	260	17.51%	13	1817	22.17	14	9	23	59	233	1	5	6	19	377	9	3	57.31%	253	4	1.11	1	5	0	0	0	10	7	8
2	Kole Sherwood	Bruins (BOS)	RW	82	32	43	75	54	132	20	166	79	230	54	154	13.91%	16	1513	18.46	10	10	20	41	220	0	1	1	2	147	5	2	44.62%	130	1	0.99	1	1	1	0	3	4	6	7
3	Ben Harpur	Bruins (BOS)	D	82	14	50	64	45	107	15	177	58	87	20	49	16.09%	58	1690	20.62	6	13	19	47	233	0	2	2	4	342	4	0	0.00%	0	0	0.76	0	0	1	0	2	3	4	4
4	Jens Looke	Bruins (BOS)	LW/RW	82	25	38	63	35	32	0	96	93	199	52	160	12.56%	11	1720	20.98	6	9	15	41	257	1	2	3	11	282	3	2	54.92%	193	1	0.73	3	5	0	0	0	4	4	9
5	Gabriel Bourque	Bruins (BOS)	LW/RW	56	18	28	46	28	56	0	134	113	172	47	102	10.47%	10	1196	21.36	2	4	6	27	148	2	3	5	14	231	2	0	46.19%	591	0	0.77	1	3	0	0	0	3	4	2
6	Chris Bigras	Bruins (BOS)	D	82	7	38	45	39	95	5	98	59	49	16	40	14.29%	45	1330	16.23	2	5	7	16	128	2	2	4	4	229	1	0	0.00%	1	0	0.68	0	0	0	0	0	0	3	5
7	Giorgio Estephan	Bruins (BOS)	C	82	17	26	43	42	75	5	80	131	126	34	96	13.49%	7	1408	17.18	2	4	6	8	144	1	1	2	1	152	4	1	62.11%	1272	0	0.61	0	0	0	0	1	3	5	1
8	Anthony Angello	Bruins (BOS)	C	35	18	19	37	27	62	0	77	77	104	28	71	17.31%	8	801	22.91	0	5	5	15	118	2	2	4	6	176	6	0	65.98%	729	1	0.92	1	1	0	0	0	4	3	3
9	Gabriel Fontaine	Bruins (BOS)	C	82	11	23	34	34	56	0	91	100	116	28	106	9.48%	13	1367	16.67	3	6	9	11	127	0	0	0	2	82	3	0	65.68%	1014	0	0.50	0	0	0	0	0	0	1	1
10	Jaycob Megna	Bruins (BOS)	D	82	7	25	32	19	136	20	225	54	71	32	57	9.86%	77	1822	22.22	3	8	11	35	260	1	1	2	5	362	0	0	0.00%	0	0	0.35	0	0	2	0	2	0	4	1
11	Gustav Olofsson	Bruins (BOS)	D	82	8	20	28	18	80	10	108	69	66	21	40	12.12%	23	1215	14.82	0	0	0	3	16	0	2	2	1	77	0	0	59.84%	127	0	0.46	0	0	0	1	1	0	1	1
12	Manuel Wiederer	Bruins (BOS)	C/RW	61	5	23	28	6	45	5	40	89	91	37	72	5.49%	6	1021	16.74	1	8	9	9	118	0	0	0	0	69	1	0	63.43%	834	0	0.55	0	0	0	0	0	1	1	0
13	Michael Anderson	Bruins (BOS)	D	50	4	14	18	16	30	0	75	32	36	15	27	11.11%	31	831	16.64	1	2	3	13	74	0	1	1	0	148	0	0	0.00%	0	0	0.43	0	0	0	0	0	0	2	1
14	Jake Dotchin	Bruins (BOS)	D	62	5	9	14	7	80	10	83	26	47	9	30	10.64%	13	628	10.13	0	0	0	0	2	0	0	0	0	4	1	0	47.06%	17	0	0.45	0	0	0	1	1	1	0	2
15	Devante Stephens	Bruins (BOS)	D	62	0	13	13	23	49	5	62	30	23	7	26	0.00%	15	829	13.37	0	0	0	1	24	0	0	0	1	67	0	0	25.00%	12	0	0.31	0	0	0	0	1	0	0	0
16	Lawson Crouse	Bruins (BOS)	LW	1	3	0	3	3	0	0	1	2	6	0	4	50.00%	0	23	23.03	0	0	0	0	2	2	0	2	2	12	1	0	58.33%	24	1	2.60	0	0	0	0	0	1	0	0
17	Ryan Collins	Bruins (BOS)	D	62	0	1	1	8	10	0	19	4	6	3	5	0.00%	6	281	4.54	0	0	0	3	30	0	0	0	0	46	0	0	25.00%	4	0	0.07	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1127	236	409	645	466	1081	95	1615	1140	1783	504	1299	13.24%	352	19498	17.30	50	83	133	329	2142	12	22	34	72	2812	40	8	60.57%	5201	8	0.66	7	15	4	2	11	34	45	45

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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	Connor Ingram	Bruins (BOS)	54	42	8	2	0.904	1.58	3154	0	9	83	867	2	1	0.833	18	52	30	1	1	1
2	Matthew Villalta	Bruins (BOS)	9	2	1	1	0.895	2.03	384	2	0	13	124	0	0	0.667	3	4	79	0	0	0
Stats d'équipe Total ou en Moyenne			63	44	9	3	0.903	1.63	3538	2	9	96	991	2	1	0.810	21	56	109	1	1	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	Link
Anthony Angello	Bruins (BOS)	C	25	1996-03-06	No	209 Lbs	6 ft5	No	No	No	2	Pro & Farm	833,750$	0$	0$	No	833,750$		Lien / Lien NHL
Ben Harpur	Bruins (BOS)	D	26	1995-01-12	No	222 Lbs	6 ft6	No	No	No	2	Pro & Farm	800,000$	0$	0$	No	800,000$		Lien / Lien NHL
Chris Bigras	Bruins (BOS)	D	26	1995-02-22	No	190 Lbs	6 ft1	No	No	No	1	Pro & Farm	900,000$	0$	0$	No			Lien / Lien NHL
Connor Ingram	Bruins (BOS)	G	24	1997-03-31	No	204 Lbs	6 ft1	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$	Lien / Lien NHL
Devante Stephens	Bruins (BOS)	D	24	1997-01-02	Yes	190 Lbs	6 ft2	No	No	No	3	Pro & Farm	743,333$	0$	0$	No	743,333$	743,333$	Lien / Lien NHL
Gabriel Bourque	Bruins (BOS)	LW/RW	30	1990-09-23	No	206 Lbs	5 ft10	No	No	No	1	Pro & Farm	1,400,000$	0$	0$	No			Lien / Lien NHL
Gabriel Fontaine	Bruins (BOS)	C	24	1997-04-30	No	191 Lbs	6 ft1	No	No	No	3	Pro & Farm	736,667$	0$	0$	No	736,667$	736,667$	Lien / Lien NHL
Giorgio Estephan	Bruins (BOS)	C	24	1997-02-03	Yes	196 Lbs	6 ft0	No	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$	Lien
Gustav Olofsson	Bruins (BOS)	D	26	1994-12-01	Yes	194 Lbs	6 ft3	No	No	No	2	Pro & Farm	800,000$	0$	0$	No	800,000$		Lien / Lien NHL
Jake Dotchin	Bruins (BOS)	D	27	1994-03-24	No	210 Lbs	6 ft3	No	No	No	1	Pro & Farm	650,000$	0$	0$	No			Lien / Lien NHL
Jaycob Megna	Bruins (BOS)	D	28	1992-12-10	No	225 Lbs	6 ft6	No	No	No	2	Pro & Farm	800,000$	0$	0$	No	800,000$		Lien / Lien NHL
Jens Looke	Bruins (BOS)	LW/RW	24	1997-04-11	No	180 Lbs	5 ft11	No	No	No	3	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$	Lien
Kole Sherwood	Bruins (BOS)	RW	24	1997-01-22	No	201 Lbs	6 ft1	No	No	No	1	Pro & Farm	1,000,000$	0$	0$	No			Lien / Lien NHL
Lawson Crouse	Bruins (BOS)	LW	23	1997-06-23	No	220 Lbs	6 ft4	No	No	No	2	Pro & Farm	1,700,000$	0$	0$	No	1,700,000$		Lien / Lien NHL
Manuel Wiederer	Bruins (BOS)	C/RW	24	1996-11-21	No	170 Lbs	6 ft0	No	No	No	3	Pro & Farm	736,667$	0$	0$	No	736,667$	736,667$	Lien / Lien NHL
Matthew Villalta	Bruins (BOS)	G	21	1999-06-03 12:28:47 PM	Yes	187 Lbs	6 ft4	No	No	No	2	Pro & Farm	778,333$	0$	0$	No	778,333$
Michael Anderson	Bruins (BOS)	D	22	1999-05-25	Yes	196 Lbs	6 ft0	No	No	No	3	Pro & Farm	1,775,000$	0$	0$	No	1,775,000$	1,775,000$	Lien
Nathan Walker	Bruins (BOS)	LW	27	1994-02-06	No	175 Lbs	5 ft9	No	No	No	2	Pro & Farm	700,000$	0$	0$	No	700,000$		Lien / Lien NHL
Ryan Collins	Bruins (BOS)	D	25	1996-05-06	No	212 Lbs	6 ft5	No	No	No	3	Pro & Farm	880,833$	0$	0$	No	880,833$	880,833$	Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
19	24.95	199 Lbs	6 ft2	2.21	926,820$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Lawson Crouse	Anthony Angello	Gabriel Bourque	40	1	2	2
2	Nathan Walker	Manuel Wiederer	Jens Looke	30	1	2	2
3	Giorgio Estephan	Gabriel Fontaine	Kole Sherwood	20	1	2	2
4	Lawson Crouse	Giorgio Estephan	Gabriel Bourque	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jaycob Megna	Ben Harpur	40	1	2	2
2	Chris Bigras	Michael Anderson	30	1	2	2
3	Devante Stephens	Gustav Olofsson	20	1	2	2
4	Jake Dotchin	Ryan Collins	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Lawson Crouse	Anthony Angello	Gabriel Bourque	60	1	2	2
2	Nathan Walker	Manuel Wiederer	Jens Looke	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jaycob Megna	Ben Harpur	60	1	2	2
2	Chris Bigras	Michael Anderson	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Lawson Crouse	Gabriel Bourque	60	1	2	2
2	Anthony Angello	Nathan Walker	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jaycob Megna	Ben Harpur	60	1	2	2
2	Chris Bigras	Michael Anderson	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Lawson Crouse	60	1	2	2	Jaycob Megna	Ben Harpur	60	1	2	2
2	Gabriel Bourque	40	1	2	2	Chris Bigras	Michael Anderson	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Lawson Crouse	Gabriel Bourque	60	1	2	2
2	Anthony Angello	Nathan Walker	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jaycob Megna	Ben Harpur	60	1	2	2
2	Chris Bigras	Michael Anderson	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Lawson Crouse	Anthony Angello	Gabriel Bourque	Jaycob Megna	Ben Harpur

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Lawson Crouse	Anthony Angello	Gabriel Bourque	Jaycob Megna	Ben Harpur

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Kole Sherwood, Gabriel Fontaine, Jens Looke	Kole Sherwood, Gabriel Fontaine	Jens Looke

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Devante Stephens, Gustav Olofsson, Jake Dotchin	Devante Stephens	Gustav Olofsson, Jake Dotchin

Tirs de Pénalité
Lawson Crouse, Gabriel Bourque, Anthony Angello, Nathan Walker, Jens Looke

Gardien
#1 : Connor Ingram, #2 : Matthew Villalta

Lignes d'Attaque Perso. en Prol.
Lawson Crouse, Gabriel Bourque, Anthony Angello, Nathan Walker, Jens Looke, Kole Sherwood, Kole Sherwood, Manuel Wiederer, Gabriel Fontaine, Giorgio Estephan,

Lignes de Défense Perso. en Prol.
Jaycob Megna, Ben Harpur, Chris Bigras, Michael Anderson, Devante Stephens

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	4	1	1	0	0	2	0	0	10	14	-4	2	0	0	0	0	2	0	0	3	5	-2	2	1	1	0	0	0	0	0	7	9	-2	4	0.500	10	17	27	0	0	108	82	70	9	70	673	678	656	29	94	34	56	101	20	3	15.00%	23	2	91.30%	1	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
2	Admirals	2	0	2	0	0	0	0	0	3	6	-3	1	0	1	0	0	0	0	0	3	4	-1	1	0	1	0	0	0	0	0	0	2	-2	0	0.000	3	6	9	0	0	108	82	70	9	27	673	678	656	29	34	18	35	38	14	1	7.14%	14	4	71.43%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
3	Barracudas	2	2	0	0	0	0	0	0	5	2	3	1	1	0	0	0	0	0	0	3	1	2	1	1	0	0	0	0	0	0	2	1	1	4	1.000	5	10	15	0	0	108	82	70	9	45	673	678	656	29	44	7	38	48	7	2	28.57%	15	1	93.33%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
4	Bears	3	3	0	0	0	0	0	0	14	4	10	2	2	0	0	0	0	0	0	10	2	8	1	1	0	0	0	0	0	0	4	2	2	6	1.000	14	26	40	0	1	108	82	70	9	99	673	678	656	29	37	19	44	76	7	1	14.29%	22	1	95.45%	2	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
5	Checkers	3	2	1	0	0	0	0	0	10	5	5	2	2	0	0	0	0	0	0	9	2	7	1	0	1	0	0	0	0	0	1	3	-2	4	0.667	10	20	30	0	0	108	82	70	9	94	673	678	656	29	59	8	65	65	6	1	16.67%	30	2	93.33%	2	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
6	Comets	2	0	2	0	0	0	0	0	1	6	-5	1	0	1	0	0	0	0	0	1	4	-3	1	0	1	0	0	0	0	0	0	2	-2	0	0.000	1	1	2	0	0	108	82	70	9	34	673	678	656	29	43	11	39	44	14	0	0.00%	17	3	82.35%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
7	Condors	2	0	2	0	0	0	0	0	2	7	-5	1	0	1	0	0	0	0	0	1	3	-2	1	0	1	0	0	0	0	0	1	4	-3	0	0.000	2	4	6	0	0	108	82	70	9	24	673	678	656	29	33	16	28	51	5	1	20.00%	13	3	76.92%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
8	Crunch	4	3	1	0	0	0	0	0	15	6	9	2	1	1	0	0	0	0	0	6	6	0	2	2	0	0	0	0	0	0	9	0	9	6	0.750	15	27	42	0	2	108	82	70	9	94	673	678	656	29	84	27	41	95	13	4	30.77%	17	1	94.12%	1	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
9	Devils	3	0	3	0	0	0	0	0	1	7	-6	1	0	1	0	0	0	0	0	0	1	-1	2	0	2	0	0	0	0	0	1	6	-5	0	0.000	1	2	3	0	0	108	82	70	9	43	673	678	656	29	54	19	52	66	6	0	0.00%	25	4	84.00%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
10	Eagles	2	2	0	0	0	0	0	0	14	1	13	1	1	0	0	0	0	0	0	9	1	8	1	1	0	0	0	0	0	0	5	0	5	4	1.000	14	28	42	0	1	108	82	70	9	95	673	678	656	29	26	4	18	54	3	1	33.33%	9	1	88.89%	2	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
11	Griffins	4	3	0	0	0	0	1	0	15	5	10	2	2	0	0	0	0	0	0	7	3	4	2	1	0	0	0	0	1	0	8	2	6	8	1.000	15	25	40	0	2	108	82	70	9	139	673	678	656	29	69	26	74	93	10	1	10.00%	25	4	84.00%	1	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
12	Gulls	2	0	2	0	0	0	0	0	3	5	-2	1	0	1	0	0	0	0	0	1	2	-1	1	0	1	0	0	0	0	0	2	3	-1	0	0.000	3	5	8	0	0	108	82	70	9	38	673	678	656	29	32	7	28	43	6	0	0.00%	14	3	78.57%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
13	Heat	2	0	1	0	0	0	0	1	4	6	-2	1	0	0	0	0	0	0	1	3	4	-1	1	0	1	0	0	0	0	0	1	2	-1	1	0.250	4	7	11	0	0	108	82	70	9	30	673	678	656	29	47	13	41	47	4	0	0.00%	16	1	93.75%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
14	IceHogs	2	1	0	0	1	0	0	0	9	5	4	1	0	0	0	1	0	0	0	3	2	1	1	1	0	0	0	0	0	0	6	3	3	4	1.000	9	17	26	0	0	108	82	70	9	44	673	678	656	29	49	10	32	47	7	2	28.57%	15	3	80.00%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
15	Marlies	4	0	2	0	1	0	1	0	12	15	-3	2	0	1	0	1	0	0	0	6	6	0	2	0	1	0	0	0	1	0	6	9	-3	4	0.500	12	21	33	0	0	108	82	70	9	76	673	678	656	29	77	17	54	66	33	4	12.12%	26	7	73.08%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
16	Monsters	3	0	3	0	0	0	0	0	5	9	-4	2	0	2	0	0	0	0	0	4	6	-2	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	5	10	15	0	0	108	82	70	9	54	673	678	656	29	58	11	53	72	15	3	20.00%	23	2	91.30%	1	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
17	Moose	2	0	2	0	0	0	0	0	1	5	-4	1	0	1	0	0	0	0	0	0	2	-2	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	1	2	3	0	0	108	82	70	9	23	673	678	656	29	34	10	20	40	7	1	14.29%	8	1	87.50%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
18	Penguins	3	1	2	0	0	0	0	0	6	9	-3	2	1	1	0	0	0	0	0	5	5	0	1	0	1	0	0	0	0	0	1	4	-3	2	0.333	6	12	18	0	0	108	82	70	9	70	673	678	656	29	63	23	35	83	11	4	36.36%	15	2	86.67%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
19	Phantoms	3	2	1	0	0	0	0	0	8	4	4	1	0	1	0	0	0	0	0	1	2	-1	2	2	0	0	0	0	0	0	7	2	5	4	0.667	8	13	21	0	1	108	82	70	9	44	673	678	656	29	42	13	65	57	17	1	5.88%	23	1	95.65%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
20	Rampage	2	2	0	0	0	0	0	0	10	1	9	1	1	0	0	0	0	0	0	7	0	7	1	1	0	0	0	0	0	0	3	1	2	4	1.000	10	17	27	0	1	108	82	70	9	61	673	678	656	29	27	1	18	65	2	1	50.00%	9	0	100.00%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
21	Reign	2	2	0	0	0	0	0	0	8	3	5	1	1	0	0	0	0	0	0	6	2	4	1	1	0	0	0	0	0	0	2	1	1	4	1.000	8	16	24	0	0	108	82	70	9	54	673	678	656	29	32	12	45	40	5	2	40.00%	19	1	94.74%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
22	Roadrunners	2	2	0	0	0	0	0	0	12	4	8	1	1	0	0	0	0	0	0	6	1	5	1	1	0	0	0	0	0	0	6	3	3	4	1.000	12	20	32	0	0	108	82	70	9	75	673	678	656	29	35	13	35	57	8	2	25.00%	12	1	91.67%	1	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
23	Rocket	4	1	1	0	0	1	0	1	8	9	-1	2	1	0	0	0	0	0	1	4	3	1	2	0	1	0	0	1	0	0	4	6	-2	4	0.500	8	15	23	0	1	108	82	70	9	87	673	678	656	29	71	14	56	58	23	4	17.39%	21	6	71.43%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
24	Senators	4	2	0	0	0	1	1	0	14	9	5	2	2	0	0	0	0	0	0	9	4	5	2	0	0	0	0	1	1	0	5	5	0	7	0.875	14	25	39	0	0	108	82	70	9	102	673	678	656	29	70	24	43	77	18	3	16.67%	18	5	72.22%	2	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
25	Sound Tigers	3	3	0	0	0	0	0	0	24	2	22	1	1	0	0	0	0	0	0	8	1	7	2	2	0	0	0	0	0	0	16	1	15	6	1.000	24	41	65	0	1	108	82	70	9	142	673	678	656	29	31	6	17	69	4	2	50.00%	6	0	100.00%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
26	Stars	2	1	1	0	0	0	0	0	7	4	3	1	1	0	0	0	0	0	0	4	0	4	1	0	1	0	0	0	0	0	3	4	-1	2	0.500	7	13	20	0	1	108	82	70	9	50	673	678	656	29	37	13	24	45	8	1	12.50%	12	3	75.00%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
27	Thunderbirds	4	2	2	0	0	0	0	0	3	8	-5	2	1	1	0	0	0	0	0	2	4	-2	2	1	1	0	0	0	0	0	1	4	-3	4	0.500	3	6	9	0	1	108	82	70	9	47	673	678	656	29	77	21	99	71	16	1	6.25%	38	4	89.47%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
28	Wild	2	2	0	0	0	0	0	0	15	1	14	1	1	0	0	0	0	0	0	6	1	5	1	1	0	0	0	0	0	0	9	0	9	4	1.000	15	28	43	0	1	108	82	70	9	72	673	678	656	29	22	6	14	47	5	0	0.00%	7	1	85.71%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
29	Wolf Pack	3	3	0	0	0	0	0	0	18	2	16	1	1	0	0	0	0	0	0	8	0	8	2	2	0	0	0	0	0	0	10	2	8	6	1.000	18	33	51	0	2	108	82	70	9	140	673	678	656	29	45	14	22	58	7	3	42.86%	11	0	100.00%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
30	Wolves	2	2	0	0	0	0	0	0	8	6	2	1	1	0	0	0	0	0	0	2	1	1	1	1	0	0	0	0	0	0	6	5	1	4	1.000	8	15	23	0	0	108	82	70	9	46	673	678	656	29	25	6	26	23	14	5	35.71%	12	2	83.33%	0	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
	Total	82	42	29	0	2	4	3	2	265	170	95	41	22	13	0	2	2	0	2	137	78	59	41	20	16	0	0	2	3	0	128	92	36	100	0.610	265	482	747	0	15	108	82	70	9	2019	673	678	656	29	1451	423	1217	1796	315	54	17.14%	515	69	86.60%	13	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
	_Since Last GM Reset	82	42	29	0	2	4	3	2	265	170	95	41	22	13	0	2	2	0	2	137	78	59	41	20	16	0	0	2	3	0	128	92	36	100	0.610	265	482	747	0	15	108	82	70	9	2019	673	678	656	29	1451	423	1217	1796	315	54	17.14%	515	69	86.60%	13	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
	_Vs Conference	50	25	18	0	1	2	3	1	154	100	54	25	14	9	0	1	0	0	1	80	49	31	25	11	9	0	0	2	3	0	74	51	23	61	0.610	154	277	431	0	11	108	82	70	9	1265	673	678	656	29	880	253	759	1050	200	32	16.00%	317	42	86.75%	9	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541
	_Vs Division	24	16	6	0	0	0	0	0	86	42	44	12	8	3	0	0	0	0	0	45	19	26	12	8	3	0	0	0	0	0	41	23	18	32	0.667	86	157	243	0	5	108	82	70	9	686	673	678	656	29	389	113	353	546	73	15	20.55%	155	12	92.26%	5	1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%	2330	1682	1642	527	986	541

			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	100	W2	265	482	747	2019	1451	423	1217	1796	0	15

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
82	42	29	2	4	3	2	265	170

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	22	13	2	2	0	2	137	78

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	20	16	0	2	3	0	128	92

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
7	3	0	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
315	54	17.14%	515	69	86.60%	13

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
673	678	656	29	108	82	70	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
1385	2280	60.75%	1154	2061	55.99%	735	1208	60.84%

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
2330	1682	1642	527	986	541

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
2 - 2020-10-25	8	Bruins	3	Stars	4	L			Sommaire du Match
4 - 2020-10-27	19	Bruins	6	Roadrunners	3	W			Sommaire du Match
7 - 2020-10-30	42	Bruins	6	Wolves	5	W			Sommaire du Match
9 - 2020-11-01	49	Bruins	5	Eagles	0	W			Sommaire du Match
11 - 2020-11-03	61	Devils	1	Bruins	0	L			Sommaire du Match
13 - 2020-11-05	78	Gulls	2	Bruins	1	L			Sommaire du Match
16 - 2020-11-08	99	Crunch	4	Bruins	2	L			Sommaire du Match
18 - 2020-11-10	123	Bruins	4	Marlies	3	W	X	X	Sommaire du Match
21 - 2020-11-13	133	Marlies	3	Bruins	2	L			Sommaire du Match
25 - 2020-11-17	161	Rampage	0	Bruins	7	W			Sommaire du Match
26 - 2020-11-18	174	Bruins	4	Wolf Pack	2	W			Sommaire du Match
28 - 2020-11-20	180	Barracudas	1	Bruins	3	W			Sommaire du Match
32 - 2020-11-24	205	Senators	2	Bruins	5	W			Sommaire du Match
34 - 2020-11-26	220	Penguins	2	Bruins	4	W			Sommaire du Match
35 - 2020-11-27	228	Bruins	3	Rocket	4	L			Sommaire du Match
38 - 2020-11-30	249	Bruins	5	Griffins	0	W			Sommaire du Match
40 - 2020-12-02	264	Phantoms	2	Bruins	1	L			Sommaire du Match
42 - 2020-12-04	273	Thunderbirds	3	Bruins	0	L			Sommaire du Match
45 - 2020-12-07	297	Bruins	2	Marlies	6	L			Sommaire du Match
46 - 2020-12-08	300	Bears	2	Bruins	5	W			Sommaire du Match
49 - 2020-12-11	325	Bruins	0	Devils	3	L			Sommaire du Match
51 - 2020-12-13	334	Americans	3	Bruins	2	L	X		Sommaire du Match
53 - 2020-12-15	348	Wild	1	Bruins	6	W			Sommaire du Match
56 - 2020-12-18	375	Bruins	1	Rocket	2	L	X		Sommaire du Match
57 - 2020-12-19	385	Bruins	2	Senators	3	L	X		Sommaire du Match
59 - 2020-12-21	392	Wolf Pack	0	Bruins	8	W			Sommaire du Match
61 - 2020-12-23	416	Rocket	3	Bruins	2	L	X	X	Sommaire du Match
63 - 2020-12-25	424	Checkers	1	Bruins	5	W			Sommaire du Match
65 - 2020-12-27	438	IceHogs	2	Bruins	3	W	X		Sommaire du Match
67 - 2020-12-29	452	Eagles	1	Bruins	9	W			Sommaire du Match
69 - 2020-12-31	469	Bruins	3	Senators	2	W	X	X	Sommaire du Match
71 - 2021-01-02	486	Bruins	4	Bears	2	W			Sommaire du Match
72 - 2021-01-03	497	Bruins	3	Crunch	0	W			Sommaire du Match
74 - 2021-01-05	505	Bruins	0	Thunderbirds	4	L			Sommaire du Match
77 - 2021-01-08	524	Reign	2	Bruins	6	W			Sommaire du Match
79 - 2021-01-10	539	Sound Tigers	1	Bruins	8	W			Sommaire du Match
81 - 2021-01-12	552	Admirals	4	Bruins	3	L			Sommaire du Match
83 - 2021-01-14	569	Bears	0	Bruins	5	W			Sommaire du Match
87 - 2021-01-18	583	Bruins	1	Americans	4	L			Sommaire du Match
89 - 2021-01-20	604	Americans	2	Bruins	1	L	X		Sommaire du Match
91 - 2021-01-22	623	Bruins	1	Devils	3	L			Sommaire du Match
93 - 2021-01-24	628	Monsters	4	Bruins	3	L			Sommaire du Match
95 - 2021-01-26	642	Condors	3	Bruins	1	L			Sommaire du Match
98 - 2021-01-29	669	Bruins	0	Admirals	2	L			Sommaire du Match
100 - 2021-01-31	679	Moose	2	Bruins	0	L			Sommaire du Match
102 - 2021-02-02	696	Bruins	9	Sound Tigers	0	W			Sommaire du Match
104 - 2021-02-04	711	Bruins	3	Phantoms	0	W			Sommaire du Match
105 - 2021-02-05	716	Bruins	1	Monsters	3	L			Sommaire du Match
107 - 2021-02-07	727	Penguins	3	Bruins	1	L			Sommaire du Match
110 - 2021-02-10	758	Bruins	1	Penguins	4	L			Sommaire du Match
112 - 2021-02-12	761	Wolves	1	Bruins	2	W			Sommaire du Match
122 - 2021-02-22	791	Bruins	1	Moose	3	L			Sommaire du Match
123 - 2021-02-23	797	Bruins	9	Wild	0	W			Sommaire du Match
126 - 2021-02-26	813	Comets	4	Bruins	1	L			Sommaire du Match
127 - 2021-02-27	825	Bruins	6	IceHogs	3	W			Sommaire du Match
130 - 2021-03-02	843	Roadrunners	1	Bruins	6	W			Sommaire du Match
131 - 2021-03-03	856	Bruins	3	Griffins	2	W	X	X	Sommaire du Match
134 - 2021-03-06	877	Rocket	0	Bruins	2	W			Sommaire du Match
137 - 2021-03-09	896	Griffins	3	Bruins	4	W			Sommaire du Match
138 - 2021-03-10	910	Bruins	6	Wolf Pack	0	W			Sommaire du Match
141 - 2021-03-13	931	Bruins	1	Condors	4	L			Sommaire du Match
143 - 2021-03-15	943	Bruins	1	Heat	2	L			Sommaire du Match
144 - 2021-03-16	957	Bruins	0	Comets	2	L			Sommaire du Match
147 - 2021-03-19	970	Heat	4	Bruins	3	L	X	X	Sommaire du Match
149 - 2021-03-21	984	Stars	0	Bruins	4	W			Sommaire du Match
151 - 2021-03-23	1005	Bruins	7	Sound Tigers	1	W			Sommaire du Match
154 - 2021-03-26	1026	Bruins	6	Crunch	0	W			Sommaire du Match
156 - 2021-03-28	1035	Bruins	1	Thunderbirds	0	W			Sommaire du Match
158 - 2021-03-30	1049	Crunch	2	Bruins	4	W			Sommaire du Match
161 - 2021-04-02	1075	Bruins	4	Phantoms	2	W			Sommaire du Match
164 - 2021-04-05	1093	Bruins	6	Americans	5	W			Sommaire du Match
165 - 2021-04-06	1099	Marlies	3	Bruins	4	W	X		Sommaire du Match
167 - 2021-04-08	1119	Monsters	2	Bruins	1	L			Sommaire du Match
169 - 2021-04-10	1132	Bruins	2	Gulls	3	L			Sommaire du Match
170 - 2021-04-11	1141	Bruins	2	Reign	1	W			Sommaire du Match
172 - 2021-04-13	1161	Bruins	2	Barracudas	1	W			Sommaire du Match
175 - 2021-04-16	1176	Griffins	0	Bruins	3	W			Sommaire du Match
177 - 2021-04-18	1191	Senators	2	Bruins	4	W			Sommaire du Match
179 - 2021-04-20	1206	Thunderbirds	1	Bruins	2	W			Sommaire du Match
182 - 2021-04-23	1228	Bruins	1	Checkers	3	L			Sommaire du Match
184 - 2021-04-25	1252	Bruins	3	Rampage	1	W			Sommaire du Match
186 - 2021-04-27	1258	Checkers	1	Bruins	4	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	36,506	38,927
Assistance PCT	44.52%	94.94%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité	Popularité de l'Équipe
0	1840 - 61.33%	89,039$	3,650,600$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
2,553,777$	1,760,958$	1,675,958$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
9,468$	1,853,812$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	0	13,231$	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

	Bruins
	GP: 82 \| W: 47 \| L: 29 \| OTL: 6 \| P: 100 GF: 265 \| GA: 170 \| PP%: 17.14% \| PK%: 86.60% DG: Chris \| Morale : 50 \| Moyenne d'Équipe : 59