OTHL - Bruins

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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	Karson Kuhlman (R)	X		X		100.00	65	41	93	65	66	62	75	60	25	64	70	66	25	45	45	68	50	61	0
2	Nathan Walker		X			100.00	65	62	72	64	62	71	74	62	50	59	62	59	59	44	45	63	50	59	0
3	Kole Sherwood (R)			X		100.00	71	74	63	65	74	69	73	57	50	47	62	61	59	44	44	61	50	58	0
4	Justin Auger			X		100.00	86	87	84	64	87	57	59	50	50	38	57	67	54	45	45	59	50	57	0
5	Madison Bowey				X	100.00	79	67	74	77	74	67	72	59	25	53	48	74	25	49	49	61	50	65	0
6	Gustav Olofsson				X	100.00	67	42	89	73	74	60	73	60	25	55	47	70	25	49	49	60	50	63	0
7	Radim Simek (R)				X	100.00	81	44	93	66	72	67	71	60	25	55	47	67	25	47	47	61	50	62	0
8	Chris Bigras				X	100.00	74	71	80	69	71	66	70	54	25	49	41	65	39	57	57	55	50	61	0
9	Luca Sbisa				X	100.00	83	76	99	77	76	45	46	44	25	28	39	70	37	71	73	52	50	61	0
10	Colton White (R)				X	100.00	74	69	87	66	69	75	82	52	25	46	42	64	40	54	54	56	50	61	0
11	Jake Dotchin				X	100.00	92	79	49	72	80	58	61	52	25	45	47	62	25	56	56	56	50	61	0
Rayé

	MOYENNE D'ÉQUIPE					100.00	76	65	80	69	73	63	69	55	32	49	51	66	38	51	51	59	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	Adin Hill	100.00	57	73	69	86	60	54	64	55	67	57	45	45	45	60	50	61	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	57	73	69	86	60	54	64	55	67	57	45	45	45	60	50	61

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Andrew Brewer	44	56	71	74	45	46	56	CAN	33	3	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	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	GW	GT	FO%	FOT	HT	P/20	PSG	PSS	S1	S2	S3
1	Trevor Moore	Bruins	LW	7	9	7	16	12	2	4	6	34	7	26	26.47%	0	130	18.62	1	3	4	7	14	3	30	2	0	50.00%	12	2	2.46	0	1	4	1	0
2	Karson Kuhlman	Bruins (BOS)	C/RW	7	2	12	14	12	4	2	11	25	11	24	8.00%	1	134	19.23	1	3	4	2	14	2	29	1	0	71.82%	181	0	2.08	0	1	0	1	3
3	Kole Sherwood	Bruins (BOS)	RW	7	4	4	8	12	10	20	5	16	8	12	25.00%	1	118	16.97	0	1	1	0	14	0	15	1	0	75.00%	16	1	1.35	0	0	1	0	0
4	Justin Auger	Bruins (BOS)	RW	7	2	5	7	10	0	8	3	18	5	15	11.11%	0	91	13.11	0	0	0	1	14	0	7	0	1	55.56%	9	0	1.53	0	0	1	1	0
5	Chris Bigras	Bruins (BOS)	D	7	2	4	6	12	6	9	6	7	3	6	28.57%	2	115	16.50	0	0	0	0	13	0	12	0	0	70.00%	50	0	1.04	0	0	0	0	2
6	Radim Simek	Bruins (BOS)	D	5	1	5	6	5	2	15	2	5	5	3	20.00%	3	101	20.39	1	0	1	3	12	0	20	0	0	0.00%	0	0	1.18	0	0	0	1	1
7	Nathan Walker	Bruins (BOS)	LW	7	4	2	6	8	2	0	7	29	10	11	13.79%	1	113	16.24	0	1	1	3	14	2	27	0	0	67.74%	31	0	1.06	1	1	0	0	0
8	Colton White	Bruins (BOS)	D	7	1	4	5	9	2	3	3	9	3	5	11.11%	1	131	18.80	0	0	0	0	0	0	12	0	0	0.00%	0	0	0.76	0	0	0	0	1
9	Jake Dotchin	Bruins (BOS)	D	7	0	5	5	6	20	37	7	7	2	6	0.00%	3	119	17.08	0	0	0	1	3	0	5	0	0	68.18%	22	0	0.84	0	0	0	0	0
10	Gustav Olofsson	Bruins (BOS)	D	7	2	2	4	4	2	6	3	10	3	9	20.00%	4	137	19.70	2	0	2	6	14	0	26	0	0	0.00%	0	0	0.58	0	0	0	0	0
11	Madison Bowey	Bruins (BOS)	D	7	0	4	4	3	14	20	7	12	2	3	0.00%	6	149	21.32	0	2	2	3	15	0	22	0	0	0.00%	0	0	0.54	0	0	0	0	0
12	Luca Sbisa	Bruins (BOS)	D	7	1	1	2	7	8	9	4	9	3	11	11.11%	1	128	18.34	0	1	1	1	12	0	21	0	0	0.00%	0	0	0.31	0	0	0	0	0
13	Matt Roy	Bruins	D	2	1	0	1	-1	0	2	0	4	1	3	25.00%	1	45	22.88	1	0	1	2	2	0	5	0	0	0.00%	0	0	0.44	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				84	29	55	84	99	72	135	64	185	63	134	15.68%	24	1519	18.08	6	11	17	29	147	7	236	4	1	69.78%	321	3	1.11	1	3	6	4	7

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Adin Hill	Bruins (BOS)	7	5	2	0	0.926	1.13	424	0	2	8	108	0	0	0	1.000	3	7	0	0	0	0
Stats d'équipe Total ou en Moyenne			7	5	2	0	0.926	1.13	424	0	2	8	108	0	0	0	1.000	3	7	0	0	0	0

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Astuces sur les Filtres (Anglais seulement)

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

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Status	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Link
Adin Hill	Bruins (BOS)	G	23	1996-05-11	No	202 Lbs	6 ft6	No	No	No	1	Avec Restriction	Pro & Farm	925,000$	0$	0$	No	Lien
Chris Bigras	Bruins (BOS)	D	24	1995-02-22	No	190 Lbs	6 ft1	No	No	No	2	Avec Restriction	Pro & Farm	900,000$	0$	0$	No	Lien
Colton White	Bruins (BOS)	D	22	1997-05-03	Yes	185 Lbs	6 ft1	No	No	No	3	Avec Restriction	Pro & Farm	935,833$	0$	0$	No	Lien
Gustav Olofsson	Bruins (BOS)	D	24	1994-11-30	No	195 Lbs	6 ft3	No	No	No	1	Avec Restriction	Pro & Farm	1,200,000$	0$	0$	No	Lien
Jake Dotchin	Bruins (BOS)	D	25	1994-03-24	No	210 Lbs	6 ft3	No	No	No	2	Avec Restriction	Pro & Farm	650,000$	0$	0$	No	Lien
Justin Auger	Bruins (BOS)	RW	25	1994-05-14	No	229 Lbs	6 ft7	No	No	No	1	Avec Restriction	Pro & Farm	650,000$	0$	0$	No	Lien
Karson Kuhlman	Bruins (BOS)	C/RW	24	1995-09-26	Yes	180 Lbs	5 ft11	No	No	No	2	Avec Restriction	Pro & Farm	750,000$	0$	0$	No	Lien
Kole Sherwood	Bruins (BOS)	RW	22	1997-01-22	Yes	201 Lbs	6 ft1	Yes	No	No	2	Avec Restriction	Pro & Farm	1,000,000$	0$	0$	No	Lien
Luca Sbisa	Bruins (BOS)	D	29	1990-01-30	No	209 Lbs	6 ft2	No	No	No	1	Sans Restriction	Pro & Farm	3,600,000$	0$	0$	No	Lien
Madison Bowey	Bruins (BOS)	D	24	1995-04-22	No	198 Lbs	6 ft2	No	No	No	1	Avec Restriction	Pro & Farm	902,500$	0$	0$	No	Lien
Nathan Walker	Bruins (BOS)	LW	25	1994-02-06	No	175 Lbs	5 ft9	No	No	No	1	Avec Restriction	Pro & Farm	683,333$	0$	0$	No	Lien
Radim Simek	Bruins (BOS)	D	27	1992-09-20	Yes	205 Lbs	5 ft10	No	No	No	1	Avec Restriction	Pro & Farm	625,000$	0$	0$	No	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
12	24.50	198 Lbs	6 ft2	1.50	1,068,472$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1		Karson Kuhlman	Kole Sherwood	40	1	2	2
2	Nathan Walker	Chris Bigras	Justin Auger	30	1	2	2
3				20	1	2	2
4		Karson Kuhlman	Nathan Walker	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Madison Bowey	Gustav Olofsson	40	1	2	2
2	Radim Simek	Luca Sbisa	30	1	2	2
3	Jake Dotchin	Colton White	20	1	2	2
4	Chris Bigras	Madison Bowey	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1		Karson Kuhlman	Kole Sherwood	60	1	2	2
2	Nathan Walker	Chris Bigras	Justin Auger	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Madison Bowey	Gustav Olofsson	60	1	2	2
2	Radim Simek	Luca Sbisa	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Karson Kuhlman		60	1	2	2
2	Nathan Walker	Kole Sherwood	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Madison Bowey	Gustav Olofsson	60	1	2	2
2	Radim Simek	Luca Sbisa	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Karson Kuhlman	60	1	2	2	Madison Bowey	Gustav Olofsson	60	1	2	2
2		40	1	2	2	Radim Simek	Luca Sbisa	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Karson Kuhlman		60	1	2	2
2	Nathan Walker	Kole Sherwood	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Madison Bowey	Gustav Olofsson	60	1	2	2
2	Radim Simek	Luca Sbisa	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
	Karson Kuhlman	Kole Sherwood	Madison Bowey	Gustav Olofsson

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
	Karson Kuhlman	Kole Sherwood	Madison Bowey	Gustav Olofsson

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Justin Auger, Kole Sherwood, Nathan Walker	Justin Auger, Kole Sherwood	Nathan Walker

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Jake Dotchin, Colton White, Chris Bigras	Jake Dotchin	Colton White, Chris Bigras

Tirs de Pénalité
Karson Kuhlman, , Nathan Walker, Kole Sherwood, Justin Auger

Gardien
#1 : Adin Hill, #2 :

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
	Total	7	4	2	0	0	0	1	0	30	8	22	3	2	0	0	0	0	1	0	14	2	12	4	2	2	0	0	0	0	0	16	6	10	10	0.714	30	55	85	0	2	11	12	6	1	188	52	76	58	5	108	24	76	141	20	6	30.00%	34	4	88.24%	0	128	199	64.32%	90	141	63.83%	60	94	63.83%	264	207	86	30	73	48
	_Since Last GM Reset	7	4	2	0	0	0	1	0	30	8	22	3	2	0	0	0	0	1	0	14	2	12	4	2	2	0	0	0	0	0	16	6	10	10	0.714	30	55	85	0	2	11	12	6	1	188	52	76	58	5	108	24	76	141	20	6	30.00%	34	4	88.24%	0	128	199	64.32%	90	141	63.83%	60	94	63.83%	264	207	86	30	73	48
	_Vs Conference	2	1	0	0	0	0	1	0	10	2	8	2	1	0	0	0	0	1	0	10	2	8	0	0	0	0	0	0	0	0	0	0	0	4	1.000	10	17	27	0	0	11	12	6	1	68	52	76	58	5	30	7	22	44	10	2	20.00%	9	0	100.00%	0	128	199	64.32%	90	141	63.83%	60	94	63.83%	264	207	86	30	73	48
	_Vs Division	1	0	0	0	0	0	0	0	8	1	7	1	0	0	0	0	0	0	0	8	1	7	0	0	0	0	0	0	0	0	0	0	0	0	0.000	8	15	23	0	0	11	12	6	1	49	52	76	58	5	12	3	6	25	3	2	66.67%	2	0	100.00%	0	128	199	64.32%	90	141	63.83%	60	94	63.83%	264	207	86	30	73	48

			Total Pour les Joueurs
Matchs Joués	Points	Séquence	Buts	Passes	Points	Tirs Pour	Tirs Contre	Tirs Bloqués	Minutes de Pénalité	Mises en Échec	Buts en Filet Désert	Blanchissage
7	10	SOW1	30	55	85	188	108	24	76	141	0	2

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
7	4	2	0	0	1	0	30	8

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	2	0	0	0	1	0	14	2

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	2	2	0	0	0	0	16	6

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	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
20	6	30.00%	34	4	88.24%	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
52	76	58	5	11	12	6	1

Mises en Jeu
Gagnées en Zone Offensive	Total en Zone Offensive	% Gagnées en Zone Offensive	Gagnées en Zone Défensive	Total en Zone Défensive	% Gagnées en Zone Défensive	Gagnées en Zone Neutre	Total en Zone Neutre	% Gagnées en Zone Neutre
128	199	64.32%	90	141	63.83%	60	94	63.83%

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
264	207	86	30	73	48

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 - 2019-10-05	8	Bruins	1	Stars	2	L			Sommaire du Match
4 - 2019-10-07	19	Bruins	6	Roadrunners	1	W			Sommaire du Match
7 - 2019-10-10	42	Bruins	2	Wolves	3	L			Sommaire du Match
9 - 2019-10-12	49	Bruins	7	Eagles	0	W			Sommaire du Match
11 - 2019-10-14	61	Devils	1	Bruins	8	W			Sommaire du Match
13 - 2019-10-16	78	Gulls	0	Bruins	4	W			Sommaire du Match
16 - 2019-10-19	99	Crunch	1	Bruins	2	W	X	X	Sommaire du Match
18 - 2019-10-21	123	Bruins	-	Marlies	-
21 - 2019-10-24	133	Marlies	-	Bruins	-
25 - 2019-10-28	161	Rampage	-	Bruins	-
26 - 2019-10-29	174	Bruins	-	Wolf Pack	-
28 - 2019-10-31	180	Barracudas	-	Bruins	-
32 - 2019-11-04	205	Senators	-	Bruins	-
34 - 2019-11-06	220	Penguins	-	Bruins	-
35 - 2019-11-07	228	Bruins	-	Rocket	-
38 - 2019-11-10	249	Bruins	-	Griffins	-
40 - 2019-11-12	264	Phantoms	-	Bruins	-
42 - 2019-11-14	273	Thunderbirds	-	Bruins	-
45 - 2019-11-17	297	Bruins	-	Marlies	-
46 - 2019-11-18	300	Bears	-	Bruins	-
49 - 2019-11-21	325	Bruins	-	Devils	-
51 - 2019-11-23	334	Americans	-	Bruins	-
53 - 2019-11-25	348	Wild	-	Bruins	-
56 - 2019-11-28	375	Bruins	-	Rocket	-
57 - 2019-11-29	385	Bruins	-	Senators	-
59 - 2019-12-01	392	Wolf Pack	-	Bruins	-
61 - 2019-12-03	416	Rocket	-	Bruins	-
63 - 2019-12-05	424	Checkers	-	Bruins	-
65 - 2019-12-07	438	IceHogs	-	Bruins	-
67 - 2019-12-09	452	Eagles	-	Bruins	-
69 - 2019-12-11	469	Bruins	-	Senators	-
71 - 2019-12-13	486	Bruins	-	Bears	-
72 - 2019-12-14	497	Bruins	-	Crunch	-
74 - 2019-12-16	505	Bruins	-	Thunderbirds	-
77 - 2019-12-19	524	Reign	-	Bruins	-
79 - 2019-12-21	539	Sound Tigers	-	Bruins	-
81 - 2019-12-23	552	Admirals	-	Bruins	-
83 - 2019-12-25	569	Bears	-	Bruins	-
87 - 2019-12-29	583	Bruins	-	Americans	-
89 - 2019-12-31	604	Americans	-	Bruins	-
91 - 2020-01-02	623	Bruins	-	Devils	-
93 - 2020-01-04	628	Monsters	-	Bruins	-
95 - 2020-01-06	642	Condors	-	Bruins	-
98 - 2020-01-09	669	Bruins	-	Admirals	-
100 - 2020-01-11	679	Moose	-	Bruins	-
102 - 2020-01-13	696	Bruins	-	Sound Tigers	-
104 - 2020-01-15	711	Bruins	-	Phantoms	-
105 - 2020-01-16	716	Bruins	-	Monsters	-
107 - 2020-01-18	727	Penguins	-	Bruins	-
110 - 2020-01-21	758	Bruins	-	Penguins	-
112 - 2020-01-23	761	Wolves	-	Bruins	-
122 - 2020-02-02	791	Bruins	-	Moose	-
123 - 2020-02-03	797	Bruins	-	Wild	-
126 - 2020-02-06	813	Comets	-	Bruins	-
127 - 2020-02-07	825	Bruins	-	IceHogs	-
130 - 2020-02-10	843	Roadrunners	-	Bruins	-
131 - 2020-02-11	856	Bruins	-	Griffins	-
134 - 2020-02-14	877	Rocket	-	Bruins	-
137 - 2020-02-17	896	Griffins	-	Bruins	-
138 - 2020-02-18	910	Bruins	-	Wolf Pack	-
141 - 2020-02-21	931	Bruins	-	Condors	-
143 - 2020-02-23	943	Bruins	-	Heat	-
144 - 2020-02-24	957	Bruins	-	Comets	-
147 - 2020-02-27	970	Heat	-	Bruins	-
149 - 2020-02-29	984	Stars	-	Bruins	-
151 - 2020-03-02	1005	Bruins	-	Sound Tigers	-
154 - 2020-03-05	1026	Bruins	-	Crunch	-
156 - 2020-03-07	1035	Bruins	-	Thunderbirds	-
158 - 2020-03-09	1049	Crunch	-	Bruins	-
161 - 2020-03-12	1075	Bruins	-	Phantoms	-
164 - 2020-03-15	1093	Bruins	-	Americans	-
165 - 2020-03-16	1099	Marlies	-	Bruins	-
167 - 2020-03-18	1119	Monsters	-	Bruins	-
169 - 2020-03-20	1132	Bruins	-	Gulls	-
170 - 2020-03-21	1141	Bruins	-	Reign	-
172 - 2020-03-23	1161	Bruins	-	Barracudas	-
175 - 2020-03-26	1176	Griffins	-	Bruins	-
177 - 2020-03-28	1191	Senators	-	Bruins	-
179 - 2020-03-30	1206	Thunderbirds	-	Bruins	-
182 - 2020-04-02	1228	Bruins	-	Checkers	-
184 - 2020-04-04	1252	Bruins	-	Rampage	-
186 - 2020-04-06	1258	Checkers	-	Bruins	-

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	4,559	2,161
Assistance PCT	75.98%	72.03%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
38	2240 - 74.67%	151,967$	455,900$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
189,447$	1,282,166$	1,272,166$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
6,893$	125,469$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
5,774,733$	169	10,657$	1,801,033$

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	7	4	2	0	0	0	1	0	30	8	22	3	2	0	0	0	0	1	0	14	2	12	4	2	2	0	0	0	0	0	16	6	10	10	30	55	85	0	2	11	12	6	1	188	52	76	58	5	108	24	76	141	20	6	30.00%	34	4	88.24%	0	128	199	64.32%	90	141	63.83%	60	94	63.83%	264	207	86	30	73	48
Total Saison Régulière	7	4	2	0	0	0	1	0	30	8	22	3	2	0	0	0	0	1	0	14	2	12	4	2	2	0	0	0	0	0	16	6	10	10	30	55	85	0	2	11	12	6	1	188	52	76	58	5	108	24	76	141	20	6	30.00%	34	4	88.24%	0	128	199	64.32%	90	141	63.83%	60	94	63.83%	264	207	86	30	73	48