LHSDB - IceHogs

Chicago Blackhawks
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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	Matt Martin		X			98.00	99	55	59	77	98	85	74	69	64	68	65	70	55	82	74	1	52	70	0
2	Matthew Highmore (R)	X				98.00	66	55	81	70	66	71	82	64	50	60	63	61	55	50	50	1	38	61	0
3	Darren Kramer		X			98.00	58	55	58	62	79	74	66	55	50	55	55	57	55	73	66	1	38	58	0
4	Brody Sutter	X				98.00	56	55	55	55	57	58	58	55	50	55	55	55	55	74	74	1	24	55	0
5	Sergey Tolchinsky			X		98.00	57	55	66	63	59	59	69	55	50	55	55	57	55	50	50	1	38	55	0
6	Thomas Di Pauli (R)			X		98.00	60	55	69	63	68	63	54	55	50	55	55	57	55	50	50	1	38	55	0
7	Noah Juulsen (R)				X	100.00	81	55	92	81	56	78	55	68	25	61	61	80	55	70	67	1	38	68	0
8	Viktor Svedberg				X	100.00	59	55	59	61	59	59	74	59	25	59	59	59	55	53	53	1	39	57	0
9	Keith Aulie (R)				X	100.00	55	55	55	60	55	55	58	55	25	55	55	55	55	63	63	1	39	55	0
10	Josh Jacobs (R)				X	100.00	55	55	55	60	55	55	66	55	25	55	55	55	55	53	53	1	38	54	0
11	Ryan Collins (R)				X	100.00	55	55	55	60	55	55	55	55	25	55	55	55	55	55	55	1	35	54	0
12	Stu Bickel				X	100.00	55	55	55	60	55	55	58	55	25	55	55	55	55	56	57	1	38	54	0
Rayé

	MOYENNE D'ÉQUIPE					99.00	63	55	63	64	64	64	64	58	39	57	57	60	55	61	59	1	38	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	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Justin Peters	97.00	57	81	83	78	60	60	63	63	67	61	55	76	71	1	19	65	0
2	Jean-Francois Berube	100.00	58	66	56	67	66	66	60	57	61	69	55	60	62	1	38	61	0
Rayé

	MOYENNE D'ÉQUIPE	98.50	58	74	70	73	63	63	62	60	64	65	55	68	67	1	29	63

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Brent Thompson	67	89	72	81	73	58	76	CAN	47	5	100,000$

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	GW	FO%	FOT	HT	P/20	PSS	FL	FT	S1	S2	S3
1	Matthew Highmore	IceHogs (Chi)	C	26	11	9	20	-9	14	0	29	84	78	22	71	14.10%	9	639	24.60	3	4	7	13	107	2	95	1	45.39%	824	1	0.63	1	0	0	4	0	0
2	Noah Juulsen	IceHogs (Chi)	D	26	7	13	20	-6	44	0	65	72	99	25	47	7.07%	34	644	24.81	6	4	10	66	116	2	77	1	33.33%	6	0	0.62	0	0	0	2	1	1
3	Josh Jacobs	IceHogs (Chi)	D	26	5	9	14	-16	14	0	28	36	27	13	12	18.52%	14	479	18.42	4	1	5	11	56	0	42	1	28.26%	46	0	0.58	0	0	0	0	2	1
4	Sergey Tolchinsky	IceHogs (Chi)	RW	26	5	7	12	-7	14	0	36	26	34	12	42	14.71%	7	578	22.25	1	2	3	6	97	0	51	0	38.30%	94	0	0.41	1	0	0	0	1	1
5	Viktor Svedberg	IceHogs (Chi)	D	26	2	10	12	-4	27	5	28	26	24	6	27	8.33%	23	587	22.59	1	5	6	10	103	0	82	0	28.57%	7	0	0.41	0	0	1	0	1	1
6	Brody Sutter	IceHogs (Chi)	C	19	4	7	11	-2	14	0	38	40	31	11	30	12.90%	3	415	21.87	2	5	7	15	71	1	46	0	46.79%	421	0	0.53	0	0	0	0	0	1
7	Thomas Di Pauli	IceHogs (Chi)	RW	26	4	7	11	-11	18	0	58	35	53	15	45	7.55%	4	573	22.05	2	2	4	15	111	1	24	1	40.91%	66	0	0.38	0	0	0	1	0	0
8	Ryan Collins	IceHogs (Chi)	D	26	5	6	11	-13	29	5	46	28	39	13	24	12.82%	20	552	21.24	1	4	5	17	105	0	55	0	40.74%	27	0	0.40	0	1	0	0	0	0
9	Darren Kramer	IceHogs (Chi)	LW	26	3	6	9	-12	28	0	52	34	56	12	28	5.36%	3	651	25.07	1	2	3	16	111	1	90	0	61.29%	62	0	0.28	1	0	0	0	0	1
10	Stu Bickel	IceHogs (Chi)	D	26	2	6	8	-6	32	10	29	22	40	6	29	5.00%	21	537	20.65	1	1	2	28	90	0	65	1	18.75%	32	0	0.30	0	0	0	0	0	0
11	Keith Aulie	IceHogs (Chi)	D	26	2	5	7	-9	35	5	34	20	41	10	20	4.88%	23	551	21.23	1	3	4	27	98	0	67	0	22.22%	18	0	0.25	0	0	1	0	1	0
12	Nick Jensen	Chicago Blackhawks	D	9	4	3	7	1	4	0	15	9	20	7	6	20.00%	11	216	24.07	2	3	5	15	40	0	43	2	0.00%	0	0	0.65	0	0	0	1	1	1
13	Matt Martin	IceHogs (Chi)	LW	4	1	2	3	-1	10	0	30	10	7	5	7	14.29%	0	107	26.86	0	2	2	1	22	0	11	0	45.90%	61	0	0.56	0	0	0	0	0	1
Stats d'équipe Total ou en Moyenne				292	55	90	145	-95	283	25	488	442	549	157	388	10.02%	172	6535	22.38	25	38	63	240	1132	7	754	7	44.35%	1664	1	0.44	3	1	2	8	7	8

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	GA	SA	A	PS %	PSA	ST	BG	S2	S3
1	Justin Peters	IceHogs (Chi)	26	5	17	4	0.870	3.43	1434	82	629	1	0.500	2	26	0	1	2
2	Jean-Francois Berube	IceHogs (Chi)	5	0	0	0	0.920	1.85	130	4	50	0	0.000	0	0	26	0	0
Stats d'équipe Total ou en Moyenne			31	5	17	4	0.873	3.30	1564	86	679	1	0.500	2	26	26	1	2

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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	Salaire Année 2	Salaire Année 3	Salaire Année 4
Brody Sutter	IceHogs (Chi)	C	25	1991-09-25	No	203 Lbs	6 ft5	No	No	No	3	Avec Restriction	Pro & Farm	300,000$	0$	0$	No	300,000$	300,000$
Darren Kramer	IceHogs (Chi)	LW	25	1991-11-19	No	210 Lbs	6 ft1	No	No	No	1	Avec Restriction	Pro & Farm	300,000$	0$	0$	No
Jean-Francois Berube	IceHogs (Chi)	G	25	1991-07-13	No	177 Lbs	6 ft1	No	No	No	1	Avec Restriction	Pro & Farm	300,000$	0$	0$	No
Josh Jacobs	IceHogs (Chi)	D	20	1996-02-14	Yes	200 Lbs	6 ft2	No	No	No	3	Contrat d'Entrée	Pro & Farm	300,000$	0$	0$	No	300,000$	300,000$
Justin Peters	IceHogs (Chi)	G	30	1986-08-30	No	210 Lbs	6 ft1	No	No	No	1	Sans Restriction	Pro & Farm	300,000$	0$	0$	No
Keith Aulie	IceHogs (Chi)	D	27	1989-06-11	Yes	222 Lbs	6 ft6	No	No	No	3	Avec Restriction	Pro & Farm	300,000$	0$	0$	No	300,000$	300,000$
Matt Martin	IceHogs (Chi)	LW	27	1989-05-07	No	215 Lbs	6 ft3	No	No	No	1	Avec Restriction	Pro & Farm	1,000,000$	0$	0$	No
Matthew Highmore	IceHogs (Chi)	C	20	1996-02-27	Yes	181 Lbs	5 ft11	No	No	No	4	Contrat d'Entrée	Pro & Farm	300,000$	0$	0$	No	300,000$	300,000$	300,000$
Noah Juulsen	IceHogs (Chi)	D	19	1997-04-02	Yes	185 Lbs	6 ft2	No	No	No	4	Contrat d'Entrée	Pro & Farm	500,000$	0$	0$	No	500,000$	500,000$	500,000$
Ryan Collins	IceHogs (Chi)	D	20	1996-05-06	Yes	216 Lbs	6 ft5	No	No	No	4	Contrat d'Entrée	Pro & Farm	300,000$	0$	0$	No	300,000$	300,000$	300,000$
Sergey Tolchinsky	IceHogs (Chi)	RW	21	1995-02-03	No	165 Lbs	5 ft8	No	No	No	1	Contrat d'Entrée	Pro & Farm	608,000$	0$	0$	No
Stu Bickel	IceHogs (Chi)	D	30	1986-10-01	No	210 Lbs	6 ft4	No	No	No	1	Sans Restriction	Pro & Farm	300,000$	0$	0$	No
Thomas Di Pauli	IceHogs (Chi)	RW	22	1994-04-28	Yes	188 Lbs	5 ft11	No	No	No	3	Contrat d'Entrée	Pro & Farm	300,000$	0$	0$	No	300,000$	300,000$
Viktor Svedberg	IceHogs (Chi)	D	25	1991-05-23	No	238 Lbs	6 ft8	No	No	No	3	Avec Restriction	Pro & Farm	300,000$	0$	0$	No	300,000$	300,000$

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
14	24.00	201 Lbs	6 ft2	2.36	386,286$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Matt Martin	Matthew Highmore	Thomas Di Pauli	40	1	2	2
2	Darren Kramer	Brody Sutter	Sergey Tolchinsky	30	1	2	2
3	Matthew Highmore	Matt Martin	Darren Kramer	20	1	2	2
4	Sergey Tolchinsky	Thomas Di Pauli	Brody Sutter	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Noah Juulsen	Viktor Svedberg	40	1	2	2
2	Keith Aulie	Ryan Collins	30	1	2	2
3	Josh Jacobs	Stu Bickel	20	1	2	2
4	Noah Juulsen	Viktor Svedberg	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Matt Martin	Matthew Highmore	Thomas Di Pauli	60	1	2	2
2	Darren Kramer	Brody Sutter	Sergey Tolchinsky	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Noah Juulsen	Viktor Svedberg	60	1	2	2
2	Keith Aulie	Ryan Collins	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Matt Martin	Matthew Highmore	60	1	2	2
2	Darren Kramer	Thomas Di Pauli	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Noah Juulsen	Viktor Svedberg	60	1	2	2
2	Keith Aulie	Ryan Collins	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Matt Martin	60	1	2	2	Noah Juulsen	Viktor Svedberg	60	1	2	2
2	Matthew Highmore	40	1	2	2	Keith Aulie	Ryan Collins	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Matt Martin	Matthew Highmore	60	1	2	2
2	Darren Kramer	Thomas Di Pauli	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Noah Juulsen	Viktor Svedberg	60	1	2	2
2	Keith Aulie	Ryan Collins	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Matt Martin	Matthew Highmore	Thomas Di Pauli	Noah Juulsen	Viktor Svedberg

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Matt Martin	Matthew Highmore	Thomas Di Pauli	Noah Juulsen	Viktor Svedberg

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Sergey Tolchinsky, Brody Sutter, Darren Kramer	Sergey Tolchinsky, Brody Sutter	Darren Kramer

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Josh Jacobs, Stu Bickel, Keith Aulie	Josh Jacobs	Stu Bickel, Keith Aulie

Tirs de Pénalité
Matt Martin, Matthew Highmore, Darren Kramer, Thomas Di Pauli, Sergey Tolchinsky

Gardien
#1 : Justin Peters, #2 : Jean-Francois Berube

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

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

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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

	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	Admirals	4	1	3	0	0	0	0	0	14	17	-3	1	0	1	0	0	0	0	0	3	4	-1	3	1	2	0	0	0	0	0	11	13	-2	2	0.250	14	25	39	0	0	21	19	11	0	78	186	171	200	5	100	25	49	76	30	7	23.33%	20	4	80.00%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
2	Bears	1	0	1	0	0	0	0	0	0	2	-2	1	0	1	0	0	0	0	0	0	2	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	0	0	0	0	0	21	19	11	0	22	186	171	200	5	25	12	12	17	5	0	0.00%	6	2	66.67%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
3	Griffins	2	2	0	0	0	0	0	0	6	3	3	1	1	0	0	0	0	0	0	3	2	1	1	1	0	0	0	0	0	0	3	1	2	4	1.000	6	11	17	0	0	21	19	11	0	39	186	171	200	5	43	9	26	33	10	3	30.00%	12	2	83.33%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
4	Monsters	3	0	3	0	0	0	0	0	1	8	-7	1	0	1	0	0	0	0	0	1	2	-1	2	0	2	0	0	0	0	0	0	6	-6	0	0.000	1	2	3	0	0	21	19	11	0	64	186	171	200	5	73	20	26	46	18	1	5.56%	11	4	63.64%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
5	Moose	1	0	0	0	0	1	0	0	3	4	-1	1	0	0	0	0	1	0	0	3	4	-1	0	0	0	0	0	0	0	0	0	0	0	1	0.500	3	4	7	0	0	21	19	11	0	41	186	171	200	5	26	4	8	18	4	1	25.00%	4	1	75.00%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
6	Rampage	4	1	2	0	0	1	0	0	7	12	-5	2	1	1	0	0	0	0	0	2	5	-3	2	0	1	0	0	1	0	0	5	7	-2	3	0.375	7	12	19	0	0	21	19	11	0	87	186	171	200	5	81	29	48	83	20	2	10.00%	14	3	78.57%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
7	Roadrunners	2	0	1	0	0	0	0	1	2	5	-3	0	0	0	0	0	0	0	0	0	0	0	2	0	1	0	0	0	0	1	2	5	-3	1	0.250	2	4	6	0	0	21	19	11	0	35	186	171	200	5	59	14	20	33	11	1	9.09%	7	2	71.43%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
8	Stars	2	1	0	0	0	1	0	0	6	5	1	1	0	0	0	0	1	0	0	2	3	-1	1	1	0	0	0	0	0	0	4	2	2	3	0.750	6	12	18	0	0	21	19	11	0	55	186	171	200	5	42	9	28	43	11	2	18.18%	14	3	78.57%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
	Total	26	5	17	0	0	3	0	1	51	87	-36	12	2	8	0	0	2	0	0	20	40	-20	14	3	9	0	0	1	0	1	31	47	-16	14	0.269	51	92	143	0	0	21	19	11	0	559	186	171	200	5	679	169	293	499	150	23	15.33%	122	29	76.23%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
10	Wild	3	0	3	0	0	0	0	0	9	15	-6	2	0	2	0	0	0	0	0	5	9	-4	1	0	1	0	0	0	0	0	4	6	-2	0	0.000	9	17	26	0	0	21	19	11	0	71	186	171	200	5	97	17	30	66	17	4	23.53%	14	5	64.29%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
11	Wolves	4	0	4	0	0	0	0	0	3	16	-13	2	0	2	0	0	0	0	0	1	9	-8	2	0	2	0	0	0	0	0	2	7	-5	0	0.000	3	5	8	0	0	21	19	11	0	67	186	171	200	5	133	30	46	84	24	2	8.33%	20	3	85.00%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
	_Since Last GM Reset	26	5	17	0	0	3	0	1	51	87	-36	12	2	8	0	0	2	0	0	20	40	-20	14	3	9	0	0	1	0	1	31	47	-16	14	0.269	51	92	143	0	0	21	19	11	0	559	186	171	200	5	679	169	293	499	150	23	15.33%	122	29	76.23%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
	_Vs Conference	19	5	12	0	0	2	0	0	45	68	-23	9	2	6	0	0	1	0	0	16	32	-16	10	3	6	0	0	1	0	0	29	36	-7	12	0.316	45	82	127	0	0	21	19	11	0	397	186	171	200	5	496	119	227	385	112	20	17.86%	94	20	78.72%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
	_Vs Division	6	4	9	0	0	1	0	0	5	21	-16	2	2	4	0	0	0	0	0	1	9	-8	4	2	5	0	0	1	0	0	4	12	-8	9	0.750	5	9	14	0	0	21	19	11	0	102	186	171	200	5	192	44	66	117	35	3	8.57%	27	5	81.48%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154

			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
26	14	L1	51	92	143	559	679	169	293	499	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
26	5	17	0	3	0	1	51	87

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
12	2	8	0	2	0	0	20	40

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
14	3	9	0	1	0	1	31	47

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
3	6	0	1	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
150	23	15.33%	122	29	76.23%	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
186	171	200	5	21	19	11	0

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
336	743	45.22%	327	793	41.24%	144	382	37.70%

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
585	398	665	197	315	154

Derniers Match Joués

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
3 - 2018-09-07	2	IceHogs	0	Monsters	5	L			Sommaire du Match
4 - 2018-09-08	10	IceHogs	0	Monsters	1	L			Sommaire du Match
11 - 2018-09-15	50	Stars	3	IceHogs	2	L	X		Sommaire du Match
12 - 2018-09-16	62	Bears	2	IceHogs	0	L			Sommaire du Match
17 - 2018-09-21	81	IceHogs	0	Roadrunners	2	L			Sommaire du Match
18 - 2018-09-22	95	IceHogs	2	Roadrunners	3	L	X	X	Sommaire du Match
22 - 2018-09-26	106	Rampage	4	IceHogs	0	L			Sommaire du Match
25 - 2018-09-29	120	Monsters	2	IceHogs	1	L			Sommaire du Match
26 - 2018-09-30	135	Moose	4	IceHogs	3	L	X		Sommaire du Match
31 - 2018-10-05	149	IceHogs	3	Admirals	5	L			Sommaire du Match
32 - 2018-10-06	160	Wild	4	IceHogs	2	L			Sommaire du Match
33 - 2018-10-07	170	IceHogs	4	Wild	6	L			Sommaire du Match
36 - 2018-10-10	175	Wild	5	IceHogs	3	L			Sommaire du Match
38 - 2018-10-12	188	IceHogs	5	Admirals	2	W			Sommaire du Match
39 - 2018-10-13	200	IceHogs	2	Wolves	5	L			Sommaire du Match
43 - 2018-10-17	216	IceHogs	3	Griffins	1	W			Sommaire du Match
45 - 2018-10-19	231	IceHogs	4	Stars	2	W			Sommaire du Match
46 - 2018-10-20	247	IceHogs	1	Rampage	2	L	X		Sommaire du Match
49 - 2018-10-23	254	IceHogs	4	Rampage	5	L			Sommaire du Match
52 - 2018-10-26	272	Wolves	4	IceHogs	1	L			Sommaire du Match
53 - 2018-10-27	280	IceHogs	3	Admirals	6	L			Sommaire du Match
54 - 2018-10-28	294	IceHogs	0	Wolves	2	L			Sommaire du Match
60 - 2018-11-03	326	Admirals	4	IceHogs	3	L			Sommaire du Match
61 - 2018-11-04	337	Rampage	1	IceHogs	2	W			Sommaire du Match
66 - 2018-11-09	356	Griffins	2	IceHogs	3	W			Sommaire du Match
67 - 2018-11-10	367	Wolves	5	IceHogs	0	L			Sommaire du Match
73 - 2018-11-16	392	IceHogs	-	Griffins	-
74 - 2018-11-17	407	Stars	-	IceHogs	-
75 - 2018-11-18	420	Griffins	-	IceHogs	-
78 - 2018-11-21	431	Admirals	-	IceHogs	-
80 - 2018-11-23	443	IceHogs	-	Wolves	-
85 - 2018-11-28	466	IceHogs	-	Wild	-
87 - 2018-11-30	483	Wolves	-	IceHogs	-
88 - 2018-12-01	495	IceHogs	-	Wolves	-
90 - 2018-12-03	507	IceHogs	-	Griffins	-
92 - 2018-12-05	516	Admirals	-	IceHogs	-
94 - 2018-12-07	527	IceHogs	-	Wild	-
96 - 2018-12-09	550	Wild	-	IceHogs	-
101 - 2018-12-14	569	IceHogs	-	Stars	-
103 - 2018-12-16	589	IceHogs	-	Rampage	-
106 - 2018-12-19	602	IceHogs	-	Rampage	-
108 - 2018-12-21	611	Griffins	-	IceHogs	-
109 - 2018-12-22	627	IceHogs	-	Wolves	-
111 - 2018-12-24	637	IceHogs	-	Wild	-
115 - 2018-12-28	663	Moose	-	IceHogs	-
116 - 2018-12-29	676	Wild	-	IceHogs	-
122 - 2019-01-04	691	Wolves	-	IceHogs	-
123 - 2019-01-05	706	IceHogs	-	Admirals	-
127 - 2019-01-09	720	Penguins	-	IceHogs	-
129 - 2019-01-11	730	Roadrunners	-	IceHogs	-
130 - 2019-01-12	744	Roadrunners	-	IceHogs	-
133 - 2019-01-15	759	Stars	-	IceHogs	-
137 - 2019-01-19	785	Wild	-	IceHogs	-
138 - 2019-01-20	800	Rampage	-	IceHogs	-
141 - 2019-01-23	810	IceHogs	-	Griffins	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
144 - 2019-01-26	833	IceHogs	-	Bears	-
145 - 2019-01-27	843	IceHogs	-	Penguins	-
147 - 2019-01-29	847	IceHogs	-	Wolves	-
151 - 2019-02-02	873	Griffins	-	IceHogs	-
158 - 2019-02-09	911	IceHogs	-	Moose	-
159 - 2019-02-10	924	IceHogs	-	Moose	-
164 - 2019-02-15	948	IceHogs	-	Griffins	-
165 - 2019-02-16	960	Monsters	-	IceHogs	-
166 - 2019-02-17	970	Stars	-	IceHogs	-
169 - 2019-02-20	981	Wolves	-	IceHogs	-
171 - 2019-02-22	989	IceHogs	-	Admirals	-
172 - 2019-02-23	998	Admirals	-	IceHogs	-
176 - 2019-02-27	1023	Admirals	-	IceHogs	-
179 - 2019-03-02	1045	Griffins	-	IceHogs	-
180 - 2019-03-03	1056	Wolves	-	IceHogs	-
182 - 2019-03-05	1060	Rampage	-	IceHogs	-
185 - 2019-03-08	1080	IceHogs	-	Stars	-
186 - 2019-03-09	1094	IceHogs	-	Stars	-
189 - 2019-03-12	1106	IceHogs	-	Admirals	-
193 - 2019-03-16	1132	IceHogs	-	Wild	-
194 - 2019-03-17	1149	Admirals	-	IceHogs	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	35	15
Assistance	0	0
Assistance PCT	0.00%	0.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
26	0 - 0.00%	0$	0$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
53,168$	54,080$	15,080$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	18,661$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	127	794$	100,838$

Afficher ou Masquer des Colonnes

	Ligue											Domicile											Visiteur
Année	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
13	26	5	17	0	0	3	0	1	51	87	-36	12	2	8	0	0	2	0	0	20	40	-20	14	3	9	0	0	1	0	1	31	47	-16	14	51	92	143	0	0	21	19	11	0	559	186	171	200	5	679	169	293	499	150	23	15.33%	122	29	76.23%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
Total Saison Régulière	26	5	17	0	0	3	0	1	51	87	-36	12	2	8	0	0	2	0	0	20	40	-20	14	3	9	0	0	1	0	1	31	47	-16	14	51	92	143	0	0	21	19	11	0	559	186	171	200	5	679	169	293	499	150	23	15.33%	122	29	76.23%	0	336	743	45.22%	327	793	41.24%	144	382	37.70%	585	398	665	197	315	154
Séries
12	4	0	4	0	0	0	0	0	6	24	-18	2	0	2	0	0	0	0	0	6	10	-4	2	0	2	0	0	0	0	0	0	14	-14	0	6	11	17	0	0	2	2	2	0	88	30	32	26	0	143	31	40	78	17	2	11.76%	20	6	70.00%	0	52	123	42.28%	34	119	28.57%	27	67	40.30%	82	56	114	27	44	21
12	4	0	4	0	0	0	0	0	6	24	-18	2	0	2	0	0	0	0	0	6	10	-4	2	0	2	0	0	0	0	0	0	14	-14	0	6	11	17	0	0	2	2	2	0	88	30	32	26	0	143	31	40	78	17	2	11.76%	20	6	70.00%	0	52	123	42.28%	34	119	28.57%	27	67	40.30%	82	56	114	27	44	21
Total Séries	8	0	8	0	0	0	0	0	12	48	-36	4	0	4	0	0	0	0	0	12	20	-8	4	0	4	0	0	0	0	0	0	28	-28	0	12	22	34	0	0	4	4	4	0	176	60	64	52	0	286	62	80	156	34	4	11.76%	40	12	70.00%	0	104	246	42.28%	68	238	28.57%	54	134	40.30%	165	112	229	54	88	42

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Pro Team Schedule	Team Finance	Team Prospects	Team History	Team Injury Suspension	Pro Team Stats	Pro Team Stats VS
Coaches	Waivers	Today Transactions	Transactions	Schedule	Pro Leaders	Pro Individual Leaders
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Farm Team Stats	Farm Team StatsVS	Farm Leaders	Farm Individual Leaders	Teams And GM Info	Pro Power Ranking	Farm Power Ranking
Free Agents	Rerate Difference	Pro All Players Stats	Farm All Players Stats	Trade History