SHAretro

Northstars
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Centre de jeu
	As 28-45-2, 65pts	2	FINAL	2	Snipers 36-35-2, 83pts

Team Stats
W1	Streak	W1
15-22-0	Home Record	19-15-0
13-23-2	Away Record	17-20-2
4-5-0	Last 10 Games	6-3-0
2.93	Goals Per Game	3.28
3.45	Goals Against Per Game	3.32
19.94%	Power Play Percentage	20.44%
83.33%	Penalty Kill Percentage	83.63%

Croque-Morts
27-39-2, 70pts

FINAL

As
28-45-2, 65pts

Team Stats
L5	Streak	W1
13-17-1	Home Record	15-22-0
14-22-1	Away Record	13-23-2
0-7-1	Last 10 Games	4-5-0
2.99	Goals Per Game	2.93
3.29	Goals Against Per Game	3.45
18.34%	Power Play Percentage	19.94%
79.75%	Penalty Kill Percentage	83.33%

Meneurs d'équipe
	Buts Viktor Kozlov 24	Passes Viktor Kozlov 33

	Points Viktor Kozlov 57	Plus/Moins Viktor Kozlov -29

	Victoires Trevor Kidd 20	Pourcentage d’arrêts Peter Sidorkiewicz 0.909

Statistiques d’équipe
Buts pour 240 2.93 GFG	Tirs pour 2145 26.16 Avg	Pourcentage en avantage numérique 19.9% 68 GF	Début de zone offensive 38.4%
Buts contre 283 3.45 GAA	Tirs contre 2431 29.65 Avg	Pourcentage en désavantage numérique 83.3% 70 GA	Début de la zone défensive 41.6%

Information d’équipe
	Directeur général	Christian Nolet
	Entraîneur	Brian Sutter
	Division	Division 4
	Conférence	Campbell
	Capitaine
	Assistant #1
	Assistant #2
Informations de l’aréna
	Capacité	3,000
	Assistance	0
	Billets de saison	300
Information formation
	Équipe Pro	24
	Équipe Mineure	19
	Limite contact	43 / 65
	Espoirs	5

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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	Neil Brady	X				98.00	67	58	61	64	77	64	67	77	66	70	62	76	56	64	62	62	38	66	0	26	1	400,000$
2	Kris King		X			100.00	89	85	38	62	74	73	76	61	60	64	59	82	60	64	63	49	52	65	0	28	2	560,000$
3	Danton Cole			X		100.00	71	58	71	68	72	74	75	69	63	68	69	64	68	60	63	54	53	65	0	27	1	512,500$
4	Andrei Lomakin		X			100.00	55	39	83	71	69	68	68	71	65	71	73	61	70	49	48	35	53	64	0	30	1	500,000$
5	Curtis Brown (R)		X			99.00	62	59	75	70	67	73	75	75	62	68	68	72	66	35	35	90	40	64	0	18	3	450,000$
6	Troy Mallette		X			100.00	86	85	29	64	78	65	70	63	59	69	63	71	58	39	56	76	51	63	0	24	2	402,000$
7	Todd Harvey (R)			X		100.00	81	75	50	67	77	74	77	69	59	66	60	66	65	35	35	95	43	63	0	19	3	450,000$
8	Jim Hiller			X		100.00	67	59	55	68	73	63	63	65	60	66	69	60	66	44	48	69	53	62	0	25	3	441,000$
9	Neil Eisenhut	X				99.00	65	51	66	66	74	68	68	68	62	69	69	58	66	41	45	54	53	62	0	27	3	456,000$
10	Jim McKenzie		X			100.00	80	76	36	62	79	67	72	66	60	66	58	77	55	39	39	69	50	62	0	25	3	406,000$
11	Rob Gaudreau (R)			X		100.00	41	31	89	69	70	57	60	65	62	70	69	58	66	39	33	77	51	60	0	24	3	357,000$
12	Jim Campbell	X				100.00	56	46	68	67	76	58	56	65	61	65	68	59	65	31	31	94	23	59	0	21	3	339,000$
13	Sylvain Lefebvre				X	100.00	67	49	78	64	75	79	82	66	64	70	57	88	55	45	45	56	42	68	0	27	2	680,000$
14	Robert Dirk				X	100.00	81	73	55	66	78	73	74	61	55	61	52	79	50	56	60	50	45	67	0	28	1	425,000$
15	Bobby Dollas				X	100.00	66	53	77	60	79	64	67	60	60	72	58	80	56	55	45	44	26	64	0	29	2	425,000$
16	Oleg Tverdovsky (R)				X	100.00	71	64	75	67	71	72	72	70	35	70	65	75	65	35	35	95	46	64	0	18	3	450,000$
17	Jamie Heward				X	100.00	70	53	67	68	76	62	62	69	64	70	50	69	48	38	48	86	53	62	0	23	3	450,000$
18	Enrico Ciccone (R)				X	100.00	88	83	34	62	81	62	66	56	54	60	42	74	40	33	33	77	22	61	0	24	3	389,000$
Rayé
1	Brad May		X			100.00	77	71	54	64	75	59	64	55	65	55	56	76	58	37	37	86	19	59	0	23	2	275,000$
2	Allen Pedersen				X	100.00	71	61	54	66	79	68	68	52	48	54	58	78	55	59	65	41	48	64	0	29	1	250,000$

	MOYENNE D’ÉQUIPE					99.80	71	61	61	66	75	67	69	65	59	66	61	71	59	45	46	68	43	63

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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	Trevor Kidd (R)	99.00	72	74	75	78	75	79	84	87	83	70	68	31	31	93	19	71	0
2	Peter Sidorkiewicz	100.00	74	70	70	69	71	72	70	87	77	72	73	41	43	58	48	68	0
Rayé
1	Jason Muzzatti	100.00	68	70	72	75	72	58	69	74	67	68	67	41	38	78	19	64	0
2	Mike Fountain (R)	100.00	74	66	72	75	74	53	65	71	62	68	64	38	42	92	20	62	0

	MOYENNE D’ÉQUIPE	99.75	72	70	72	74	73	66	72	80	72	70	68	38	39	80	27	66

Nom de l’entraîneur	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Brian Sutter	74	76	68	65	80	85	79	CAN	39	1	95,000$

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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	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	EG	HT	P/20	FW	FL	FT	S1	S2	S3
1	Viktor Kozlov	Northstars	C	70	24	33	57	-29	6	0	34	229	227	51	147	10.57%	8	1504	21.50	4	17	21	43	225	0	1	1	4	215	3	0	54.35%	1978	0	0	0.76	0	0	0	2	3	1
2	Sylvain Lefebvre	As (MIN)	D	80	8	46	54	-14	18	0	61	159	110	34	79	7.27%	126	1942	24.28	4	6	10	66	269	0	1	1	2	357	1	0	0.00%	0	1	0	0.56	0	0	0	2	1	3
3	Curtis Brown	As (MIN)	LW	78	29	25	54	-10	25	5	31	118	208	54	132	13.94%	14	1359	17.43	10	6	16	41	158	0	0	0	2	126	5	2	43.40%	106	0	2	0.79	0	0	1	4	2	2
4	Oleg Tverdovsky	As (MIN)	D	69	13	40	53	-7	58	10	99	91	119	26	67	10.92%	76	1403	20.34	9	11	20	69	196	0	0	0	2	197	0	1	0.00%	0	0	0	0.76	1	0	1	4	2	1
5	Danton Cole	As (MIN)	RW	82	27	23	50	-16	10	0	34	80	194	46	138	13.92%	12	1526	18.62	14	8	22	44	278	0	0	0	3	214	4	1	52.05%	146	0	1	0.65	0	0	0	2	3	2
6	Kris King	As (MIN)	LW	81	21	26	47	-17	182	30	286	114	164	48	126	12.80%	19	1473	18.19	4	14	18	46	248	0	0	0	6	215	2	3	46.77%	248	2	1	0.64	2	2	2	7	3	1
7	Andrei Lomakin	As (MIN)	LW	82	27	20	47	-9	12	0	15	108	217	45	145	12.44%	7	1216	14.84	3	4	7	37	144	0	0	0	0	24	3	2	47.25%	91	0	1	0.77	0	0	0	2	2	3
8	Neil Brady	As (MIN)	C	71	15	30	45	-12	14	0	48	178	151	34	122	9.93%	15	1498	21.10	2	19	21	35	222	0	0	0	5	296	3	1	50.47%	1827	1	0	0.60	0	0	0	2	3	0
9	Neil Eisenhut	As (MIN)	C	82	10	33	43	-9	18	0	76	135	109	27	102	9.17%	4	1214	14.81	2	3	5	7	73	0	0	0	0	53	0	0	46.85%	1381	1	0	0.71	0	0	0	1	2	3
10	Robert Dirk	As (MIN)	D	76	9	24	33	-18	153	5	279	94	73	25	47	12.33%	89	1748	23.01	3	5	8	44	237	1	0	1	1	267	1	0	0.00%	0	0	0	0.38	0	0	1	0	2	4
11	Bobby Dollas	As (MIN)	D	71	3	29	32	0	34	0	70	58	54	17	34	5.56%	74	1322	18.62	1	6	7	31	147	0	0	0	0	199	1	0	0.00%	0	0	0	0.48	0	0	0	0	1	1
12	Todd Harvey	As (MIN)	RW	61	8	16	24	-16	84	10	171	65	86	30	77	9.30%	7	1049	17.21	3	6	9	23	187	0	0	0	0	54	1	0	37.67%	146	0	0	0.46	1	0	1	0	4	1
13	Jim Hiller	As (MIN)	RW	82	16	7	23	-3	60	0	124	68	122	33	97	13.11%	3	1137	13.88	1	0	1	11	86	0	0	0	0	2	4	0	51.72%	58	0	0	0.40	0	0	0	1	1	0
14	Jamie Heward	As (MIN)	D	82	2	20	22	-15	44	0	53	69	28	12	19	7.14%	59	1261	15.38	1	1	2	6	25	0	0	0	0	94	0	0	0.00%	0	0	0	0.35	0	0	0	0	0	0
15	Rob Gaudreau	As (MIN)	RW	77	5	12	17	-3	0	0	2	31	57	20	40	8.77%	2	571	7.42	0	0	0	1	5	0	0	0	0	0	0	0	60.00%	40	0	0	0.60	0	0	0	0	0	1
16	Troy Mallette	As (MIN)	LW	81	8	5	13	-2	76	10	109	52	46	21	40	17.39%	5	615	7.60	0	0	0	0	4	0	0	0	0	118	0	0	41.35%	104	0	0	0.42	0	0	2	0	1	0
17	Allen Pedersen	As (MIN)	D	15	1	9	10	4	19	5	41	12	20	2	12	5.00%	20	303	20.24	1	1	2	9	40	0	0	0	0	50	0	0	0.00%	0	0	0	0.66	0	0	1	0	1	0
18	Jim Campbell	As (MIN)	C	47	4	4	8	0	12	0	14	58	43	20	29	9.30%	4	544	11.59	0	0	0	1	5	0	0	0	0	31	0	0	45.05%	606	0	0	0.29	0	0	0	0	2	0
19	Jim McKenzie	As (MIN)	LW	75	1	7	8	4	7	5	26	21	27	7	17	3.70%	4	322	4.29	1	1	2	5	36	0	0	0	1	67	0	0	55.34%	103	0	0	0.50	1	0	0	0	0	0
20	Enrico Ciccone	As (MIN)	D	40	1	3	4	-12	102	10	150	21	12	8	8	8.33%	36	617	15.43	0	0	0	2	6	0	0	0	0	55	0	0	0.00%	0	0	0	0.13	1	0	1	0	0	0
21	Brad May	As (MIN)	LW	15	0	1	1	1	2	0	2	2	2	1	3	0.00%	1	37	2.52	0	1	1	2	9	0	0	0	0	11	0	0	66.67%	6	0	0	0.53	0	0	0	0	0	0
Statistiques d’équipe totales ou en moyenne				1417	232	413	645	-183	936	90	1725	1763	2069	561	1481	11.21%	585	22672	16.00	63	109	172	523	2609	1	2	3	26	2655	28	10	49.87%	6840	5	5	0.57	6	2	10	27	33	23

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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	ST	BG	S1	S2	S3
1	Trevor Kidd	As (MIN)	66	20	35	6	0.877	3.60	3655	2	2	219	1786	7	4	65	16	4	2	0
2	Peter Sidorkiewicz	As (MIN)	29	8	12	1	0.909	2.68	1297	2	2	58	639	1	2	17	65	1	0	1
Statistiques d’équipe totales ou en moyenne			95	28	47	7	0.886	3.36	4953	4	4	277	2425	8	6	82	81	5	2	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	Plafond salarial	Plafond salarial restant	Exclus du plafond salarial	Salaire annuel 2	Salaire annuel 3
Allen Pedersen	As (MIN)	D	29	1992-02-09 9:08:37 PM	No	210 Lbs	6 ft5	No	No	No	1	Pro & Farm	250,000$	25,000$	203$	No
Andrei Lomakin	As (MIN)	LW	30	1991-02-09 9:08:37 PM	No	176 Lbs	5 ft10	No	No	No	1	Pro & Farm	500,000$	50,000$	407$	No
Bobby Dollas	As (MIN)	D	29	1992-02-09 9:08:37 PM	No	220 Lbs	6 ft2	No	No	No	2	Pro & Farm	425,000$	42,500$	346$	No	425,000$
Brad May	As (MIN)	LW	23	1998-02-09 9:08:37 PM	No	209 Lbs	6 ft0	No	No	No	2	Pro & Farm	275,000$	27,500$	224$	No	275,000$
Curtis Brown	As (MIN)	LW	18	2003-04-19 7:05:10 AM	Yes	205 Lbs	6 ft0	No	No	No	3	Pro & Farm	450,000$	45,000$	366$	No	450,000$	450,000$
Danton Cole	As (MIN)	RW	27	1994-02-09 9:08:37 PM	No	185 Lbs	5 ft11	No	No	No	1	Pro & Farm	512,500$	51,250$	417$	No
Enrico Ciccone	As (MIN)	D	24	1997-02-09 9:08:37 PM	Yes	220 Lbs	6 ft5	No	No	No	3	Pro & Farm	389,000$	38,900$	316$	No	389,000$	389,000$
Jamie Heward	As (MIN)	D	23	1998-02-09 9:08:37 PM	No	198 Lbs	6 ft2	No	No	No	3	Pro & Farm	450,000$	45,000$	366$	No	450,000$	450,000$
Jason Muzzatti	As (MIN)	G	24	1997-02-09 9:08:37 PM	No	190 Lbs	6 ft1	No	No	No	3	Pro & Farm	425,000$	42,500$	346$	No	425,000$	425,000$
Jim Campbell	As (MIN)	C	21	2000-02-09 9:08:37 PM	No	205 Lbs	6 ft2	No	No	No	3	Pro & Farm	339,000$	33,900$	276$	No	339,000$	339,000$
Jim Hiller	As (MIN)	RW	25	1996-02-09 9:08:37 PM	No	190 Lbs	6 ft0	No	No	No	3	Pro & Farm	441,000$	44,100$	359$	No	441,000$	441,000$
Jim McKenzie	As (MIN)	LW	25	1996-02-09 9:08:37 PM	No	221 Lbs	6 ft4	No	No	No	3	Pro & Farm	406,000$	40,600$	330$	No	406,000$	406,000$
Kris King	As (MIN)	LW	28	1993-02-09 9:08:37 PM	No	202 Lbs	5 ft11	No	No	No	2	Pro & Farm	560,000$	56,000$	455$	No	560,000$
Mike Fountain	As (MIN)	G	22	1999-02-09 9:08:37 PM	Yes	176 Lbs	6 ft1	No	No	No	2	Pro & Farm	450,000$	45,000$	366$	No	450,000$
Neil Brady	As (MIN)	C	26	1995-02-09 9:08:37 PM	No	205 Lbs	6 ft3	No	No	No	1	Pro & Farm	400,000$	40,000$	325$	No
Neil Eisenhut	As (MIN)	C	27	1994-02-09 9:08:37 PM	No	195 Lbs	6 ft1	No	No	No	3	Pro & Farm	456,000$	45,600$	371$	No	456,000$	456,000$
Oleg Tverdovsky	As (MIN)	D	18	2003-04-19 7:01:44 AM	Yes	185 Lbs	6 ft0	No	No	No	3	Pro & Farm	450,000$	45,000$	366$	No	450,000$	450,000$
Peter Sidorkiewicz	As (MIN)	G	27	1994-02-09 9:08:37 PM	No	165 Lbs	5 ft9	No	No	No	3	Pro & Farm	497,000$	49,700$	404$	No	497,000$	497,000$
Rob Gaudreau	As (MIN)	RW	24	1997-02-09 9:08:37 PM	Yes	185 Lbs	5 ft11	No	No	No	3	Pro & Farm	357,000$	35,700$	290$	No	357,000$	357,000$
Robert Dirk	As (MIN)	D	28	1993-02-09 9:08:37 PM	No	207 Lbs	6 ft4	No	No	No	1	Pro & Farm	425,000$	42,500$	346$	No
Sylvain Lefebvre	As (MIN)	D	27	1994-02-09 9:08:37 PM	No	204 Lbs	6 ft2	No	No	No	2	Pro & Farm	680,000$	68,000$	553$	No	680,000$
Todd Harvey	As (MIN)	RW	19	2002-04-19 6:56:57 AM	Yes	195 Lbs	6 ft0	No	No	No	3	Pro & Farm	450,000$	45,000$	366$	No	450,000$	450,000$
Trevor Kidd	As (MIN)	G	22	1999-02-09 9:08:37 PM	Yes	190 Lbs	6 ft2	No	No	No	3	Pro & Farm	705,000$	70,500$	573$	No	705,000$	705,000$
Troy Mallette	As (MIN)	LW	24	1997-02-09 9:08:37 PM	No	219 Lbs	6 ft3	No	No	No	2	Pro & Farm	402,000$	40,200$	327$	No	402,000$

Nombre de joueurs	Âge moyen	Poids moyen	Taille moyenne	Contrat moyen	Salaire moyen 1e année
24	24.58	198 Lbs	6 ft1	2.33	445,604$

Attaque à 5 contre 5
Ligne #	Ailier gauche	Centre	Ailier droit	% temps	PHY	DF	OF
1	Kris King	Neil Brady	Danton Cole	35	1	2	2
2	Curtis Brown	Neil Eisenhut	Todd Harvey	30	1	2	2
3	Andrei Lomakin	Jim Campbell	Jim Hiller	20	1	2	2
4	Troy Mallette	Jim Campbell	Rob Gaudreau	15	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% temps	PHY	DF	OF
1	Sylvain Lefebvre	Oleg Tverdovsky	35	1	2	2
2	Robert Dirk	Bobby Dollas	30	1	2	2
3	Jamie Heward	Enrico Ciccone	20	1	2	2
4	Sylvain Lefebvre	Robert Dirk	15	1	2	2

Attaque en svantage numérique
Ligne #	Ailier gauche	Centre	Ailier droit	% temps	PHY	DF	OF
1	Kris King	Neil Brady	Danton Cole	60	1	2	2
2	Curtis Brown	Neil Eisenhut	Todd Harvey	40	1	2	2

Défense en svantage numérique
Ligne #	Défense	Défense	% temps	PHY	DF	OF
1	Sylvain Lefebvre	Oleg Tverdovsky	60	1	2	2
2	Robert Dirk	Bobby Dollas	40	1	2	2

Attaque à 4 en désavantage numérique
Ligne #	Centre	Ailier	% temps	PHY	DF	OF
1	Neil Brady	Kris King	60	1	2	2
2	Danton Cole	Curtis Brown	40	1	2	2

Défense à 4 en désavantage numérique
Ligne #	Défense	Défense	% temps	PHY	DF	OF
1	Sylvain Lefebvre	Robert Dirk	60	1	2	2
2	Oleg Tverdovsky	Bobby Dollas	40	1	2	2

3 joueurs en désavantage numérique
Ligne #	Ailier	% temps	PHY	DF	OF	Défense	Défense	% temps	PHY	DF	OF
1	Neil Brady	60	1	2	2	Sylvain Lefebvre	Robert Dirk	60	1	2	2
2	Kris King	40	1	2	2	Oleg Tverdovsky	Bobby Dollas	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% temps	PHY	DF	OF
1	Neil Brady	Kris King	60	1	2	2
2	Danton Cole	Curtis Brown	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% temps	PHY	DF	OF
1	Sylvain Lefebvre	Robert Dirk	60	1	2	2
2	Oleg Tverdovsky	Bobby Dollas	40	1	2	2

Attaque dernière minute
Ailier gauche	Centre	Ailier droit	Défense	Défense
Kris King	Neil Brady	Danton Cole	Sylvain Lefebvre	Robert Dirk

Défense dernière minute
Ailier gauche	Centre	Ailier droit	Défense	Défense
Kris King	Neil Brady	Danton Cole	Sylvain Lefebvre	Robert Dirk

Attaquants supplémentaires
Normal	Avantage numérique	Désavantage numérique
Jim McKenzie, Andrei Lomakin, Troy Mallette	Jim McKenzie, Andrei Lomakin	Troy Mallette

Défenseurs supplémentaires
Normal	Avantage numérique	Désavantage numérique
Jamie Heward, Enrico Ciccone, Oleg Tverdovsky	Jamie Heward	Enrico Ciccone, Oleg Tverdovsky

Tirs de pénalité
Neil Brady, Kris King, Danton Cole, Curtis Brown, Andrei Lomakin

Gardien
#1 : Trevor Kidd, #2 : Peter Sidorkiewicz

Lignes d’attaque personnalisées en prolongation
, , , , , , , , , ,

Lignes de défense personnalisées en prolongation
, , , ,

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

	Total												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	Ailes Rouges	9	4	3	0	1	1	0	0	32	24	8	4	4	0	0	0	0	0	0	22	9	13	5	0	3	0	1	1	0	0	10	15	-5	11	0.611	32	61	93	1	0	101	66	72	1	231	729	674	727	15	270	55	119	193	37	9	24.32%	52	7	86.54%	0	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
2	Banshees	4	1	2	1	0	0	0	0	9	12	-3	2	0	1	1	0	0	0	0	5	7	-2	2	1	1	0	0	0	0	0	4	5	-1	3	0.375	9	17	26	0	0	101	66	72	1	65	729	674	727	15	129	45	74	93	5	0	0.00%	26	4	84.62%	0	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
3	Canadiens	4	1	3	0	0	0	0	0	16	17	-1	2	1	1	0	0	0	0	0	9	6	3	2	0	2	0	0	0	0	0	7	11	-4	2	0.250	16	30	46	1	1	101	66	72	1	129	729	674	727	15	126	33	43	91	19	6	31.58%	19	3	84.21%	0	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
4	Chiefs	4	0	4	0	0	0	0	0	5	17	-12	2	0	2	0	0	0	0	0	2	9	-7	2	0	2	0	0	0	0	0	3	8	-5	0	0.000	5	9	14	0	0	101	66	72	1	102	729	674	727	15	114	33	47	90	18	2	11.11%	15	5	66.67%	0	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
5	Citadelles	4	3	1	0	0	0	0	0	18	13	5	2	1	1	0	0	0	0	0	7	6	1	2	2	0	0	0	0	0	0	11	7	4	6	0.750	18	33	51	0	0	101	66	72	1	112	729	674	727	15	123	33	38	104	22	8	36.36%	19	0	100.00%	0	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
6	Croque-Morts	8	5	3	0	0	0	0	0	31	22	9	4	4	0	0	0	0	0	0	18	7	11	4	1	3	0	0	0	0	0	13	15	-2	10	0.625	31	55	86	0	1	101	66	72	1	237	729	674	727	15	236	64	112	173	40	13	32.50%	38	5	86.84%	1	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
7	Harvard	4	3	0	1	0	0	0	0	22	14	8	2	1	0	1	0	0	0	0	10	8	2	2	2	0	0	0	0	0	0	12	6	6	7	0.875	22	38	60	0	0	101	66	72	1	106	729	674	727	15	108	31	46	80	19	6	31.58%	17	4	76.47%	0	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
8	Isotopes	4	1	1	2	0	0	0	0	12	12	0	2	0	1	1	0	0	0	0	3	5	-2	2	1	0	1	0	0	0	0	9	7	2	4	0.500	12	23	35	0	0	101	66	72	1	113	729	674	727	15	143	28	60	92	21	2	9.52%	30	5	83.33%	0	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
9	Mooses	6	2	4	0	0	0	0	0	13	18	-5	3	1	2	0	0	0	0	0	8	8	0	3	1	2	0	0	0	0	0	5	10	-5	4	0.333	13	25	38	0	1	101	66	72	1	152	729	674	727	15	161	47	68	136	25	4	16.00%	34	2	94.12%	0	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
10	Pacifiques de la route	6	2	4	0	0	0	0	0	17	21	-4	3	1	2	0	0	0	0	0	11	13	-2	3	1	2	0	0	0	0	0	6	8	-2	4	0.333	17	31	48	1	1	101	66	72	1	171	729	674	727	15	149	47	68	144	31	7	22.58%	28	7	75.00%	0	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
11	Riverman	6	0	5	1	0	0	0	0	8	24	-16	3	0	3	0	0	0	0	0	2	12	-10	3	0	2	1	0	0	0	0	6	12	-6	1	0.083	8	15	23	0	0	101	66	72	1	142	729	674	727	15	174	45	65	119	26	3	11.54%	30	7	76.67%	0	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
12	Snipers	6	2	2	1	0	1	0	0	21	22	-1	3	1	2	0	0	0	0	0	12	15	-3	3	1	0	1	0	1	0	0	9	7	2	6	0.500	21	39	60	1	0	101	66	72	1	162	729	674	727	15	163	54	70	154	18	4	22.22%	27	6	77.78%	0	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
13	Spoonman's	4	1	3	0	0	0	0	0	10	14	-4	2	0	2	0	0	0	0	0	5	8	-3	2	1	1	0	0	0	0	0	5	6	-1	2	0.250	10	15	25	1	0	101	66	72	1	91	729	674	727	15	116	37	43	95	15	2	13.33%	14	1	92.86%	0	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
14	Weetouches	4	1	2	1	0	0	0	0	9	13	-4	2	0	1	1	0	0	0	0	2	4	-2	2	1	1	0	0	0	0	0	7	9	-2	3	0.375	9	16	25	0	0	101	66	72	1	113	729	674	727	15	130	40	43	77	15	0	0.00%	19	6	68.42%	0	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
15	Wolves	9	1	8	0	0	0	0	0	17	40	-23	5	1	4	0	0	0	0	0	12	19	-7	4	0	4	0	0	0	0	0	5	21	-16	2	0.111	17	30	47	1	0	101	66	72	1	219	729	674	727	15	289	71	118	223	30	2	6.67%	52	8	84.62%	0	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
	Total	82	27	45	7	1	2	0	0	240	283	-43	41	15	22	4	0	0	0	0	128	136	-8	41	12	23	3	1	2	0	0	112	147	-35	65	0.396	240	437	677	6	4	101	66	72	1	2145	729	674	727	15	2431	663	1014	1864	341	68	19.94%	420	70	83.33%	1	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
	_Since Last GM Reset	82	34	45	0	1	2	0	0	240	283	-43	41	15	22	4	0	0	0	0	128	136	-8	41	19	23	-4	1	2	0	0	112	147	-35	72	0.439	240	437	677	6	4	101	66	72	1	2145	729	674	727	15	2431	663	1014	1864	341	68	19.94%	420	70	83.33%	1	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
	_Vs Conference	50	18	29	0	1	2	0	0	139	171	-32	25	12	13	0	0	0	0	0	85	83	2	25	6	16	0	1	2	0	0	54	88	-34	40	0.400	139	256	395	4	3	101	66	72	1	1314	729	674	727	15	1442	383	620	1142	207	42	20.29%	261	42	83.91%	1	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530
	_Vs Division	26	10	14	0	1	1	0	0	80	86	-6	13	9	4	0	0	0	0	0	52	35	17	13	1	10	0	1	1	0	0	28	51	-23	23	0.442	80	146	226	2	1	101	66	72	1	687	729	674	727	15	795	190	349	589	107	24	22.43%	142	20	85.92%	1	1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%	1872	1242	2004	644	1082	530

			Total pour les joueurs
Matchs joués	Points	Séquence	Buts	Passes	Points	Tirs pour	Tirs contre	Tirs bloqués	Minutes de pénalités	Mises en échec	Buts en filet désert	Blanchissages
82	65	W1	240	437	677	2145	2431	663	1014	1864	6	4

Tous les matchs
GP	W	L	OTW	OTL	T	GF	GA
82	27	45	1	2	7	240	283

Matchs locaux
GP	W	L	OTW	OTL	T	GF	GA
41	15	22	0	0	4	128	136

Matchs extérieurs
GP	W	L	OTW	OTL	T	GF	GA
41	12	23	1	2	3	112	147

Derniers 10 matchs
W	L	OTW	OTL	T
4	5	0	0	1

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
341	68	19.94%	420	70	83.33%	1

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
729	674	727	15	101	66	72	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
1299	2624	49.50%	1426	2845	50.12%	686	1371	50.04%

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
1872	1242	2004	644	1082	530

Derniers matchs joués Afficher ou masquer des colonnes

Astuces sur les filtres (anglais seulement)

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

Jour	Match	Équipe visiteuse	Score	Équipe locale	Score	ST	OT	Lien
1 - 2021-05-04	2	As	2	Ailes Rouges	3	L	X	Sommaire du match
2 - 2021-05-05	10	As	0	Wolves	7	L		Sommaire du match
3 - 2021-05-06	16	Wolves	3	As	1	L		Sommaire du match
5 - 2021-05-08	26	As	2	Ailes Rouges	1	W	X	Sommaire du match
6 - 2021-05-09	32	Ailes Rouges	3	As	4	W		Sommaire du match
7 - 2021-05-10	44	Wolves	2	As	4	W		Sommaire du match
8 - 2021-05-11	51	As	4	Croque-Morts	2	W		Sommaire du match
9 - 2021-05-12	57	Croque-Morts	0	As	3	W		Sommaire du match
11 - 2021-05-14	63	As	2	Snipers	3	L	X	Sommaire du match
13 - 2021-05-16	75	Pacifiques de la route	7	As	5	L		Sommaire du match
15 - 2021-05-18	85	Mooses	4	As	2	L		Sommaire du match
17 - 2021-05-20	94	As	1	Wolves	5	L		Sommaire du match
19 - 2021-05-22	102	Wolves	2	As	1	L		Sommaire du match
21 - 2021-05-24	110	Harvard	5	As	5	T	X	Sommaire du match
23 - 2021-05-26	117	As	2	Wolves	4	L		Sommaire du match
25 - 2021-05-28	121	As	3	Croque-Morts	4	L		Sommaire du match
28 - 2021-05-31	132	Isotopes	2	As	2	T	X	Sommaire du match
29 - 2021-06-01	139	As	2	Pacifiques de la route	5	L		Sommaire du match
31 - 2021-06-03	150	As	3	Spoonman's	2	W		Sommaire du match
32 - 2021-06-04	156	As	1	Pacifiques de la route	3	L		Sommaire du match
33 - 2021-06-05	158	Wolves	7	As	3	L		Sommaire du match
34 - 2021-06-06	170	Ailes Rouges	4	As	6	W		Sommaire du match
35 - 2021-06-07	175	As	4	Ailes Rouges	5	L		Sommaire du match
37 - 2021-06-09	184	As	1	Banshees	4	L		Sommaire du match
39 - 2021-06-11	192	Mooses	4	As	2	L		Sommaire du match
41 - 2021-06-13	201	Pacifiques de la route	1	As	2	W		Sommaire du match
43 - 2021-06-15	210	As	5	Croque-Morts	6	L		Sommaire du match
45 - 2021-06-17	217	Citadelles	4	As	2	L		Sommaire du match
47 - 2021-06-19	228	As	1	Ailes Rouges	3	L		Sommaire du match
49 - 2021-06-21	233	As	6	Canadiens	8	L		Sommaire du match
51 - 2021-06-23	241	Spoonman's	3	As	1	L		Sommaire du match
53 - 2021-06-25	251	Banshees	3	As	3	T	X	Sommaire du match
54 - 2021-06-26	259	As	0	Mooses	4	L		Sommaire du match
56 - 2021-06-28	264	As	3	Banshees	1	W		Sommaire du match
57 - 2021-06-29	270	Weetouches	1	As	1	T	X	Sommaire du match
58 - 2021-06-30	278	As	3	Weetouches	7	L		Sommaire du match
59 - 2021-07-01	285	As	5	Snipers	2	W		Sommaire du match
60 - 2021-07-02	293	Snipers	4	As	1	L		Sommaire du match
61 - 2021-07-03	303	Chiefs	3	As	1	L		Sommaire du match
63 - 2021-07-05	312	Ailes Rouges	1	As	5	W		Sommaire du match
65 - 2021-07-07	325	Harvard	3	As	5	W		Sommaire du match
66 - 2021-07-08	332	As	1	Riverman	4	L		Sommaire du match
67 - 2021-07-09	340	Ailes Rouges	1	As	7	W		Sommaire du match
70 - 2021-07-12	350	As	2	Spoonman's	4	L		Sommaire du match
71 - 2021-07-13	357	Wolves	5	As	3	L		Sommaire du match
72 - 2021-07-14	364	As	1	Croque-Morts	3	L		Sommaire du match
74 - 2021-07-16	366	As	7	Harvard	3	W		Sommaire du match
76 - 2021-07-18	376	Canadiens	0	As	7	W		Sommaire du match
77 - 2021-07-19	387	As	1	Ailes Rouges	3	L		Sommaire du match
78 - 2021-07-20	395	Citadelles	2	As	5	W		Sommaire du match
79 - 2021-07-21	402	As	6	Citadelles	4	W		Sommaire du match
81 - 2021-07-23	411	Riverman	4	As	1	L		Sommaire du match
82 - 2021-07-24	418	As	5	Citadelles	3	W		Sommaire du match
84 - 2021-07-26	428	Croque-Morts	2	As	5	W		Sommaire du match
86 - 2021-07-28	437	Banshees	4	As	2	L		Sommaire du match
88 - 2021-07-30	445	As	3	Pacifiques de la route	0	W		Sommaire du match
89 - 2021-07-31	452	As	5	Harvard	3	W		Sommaire du match
90 - 2021-08-01	460	Spoonman's	5	As	4	L		Sommaire du match
91 - 2021-08-02	467	As	2	Chiefs	4	L		Sommaire du match
92 - 2021-08-03	475	Weetouches	3	As	1	L		Sommaire du match
94 - 2021-08-05	484	As	1	Chiefs	4	L		Sommaire du match
95 - 2021-08-06	492	Canadiens	6	As	2	L		Sommaire du match
97 - 2021-08-08	502	Pacifiques de la route	5	As	4	L		Sommaire du match
98 - 2021-08-09	507	As	3	Isotopes	3	T	X	Sommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
99 - 2021-08-10	515	As	4	Weetouches	2	W		Sommaire du match
100 - 2021-08-11	522	As	4	Mooses	3	W		Sommaire du match
101 - 2021-08-12	528	Riverman	5	As	1	L		Sommaire du match
102 - 2021-08-13	536	As	5	Riverman	5	T	X	Sommaire du match
103 - 2021-08-14	543	Riverman	3	As	0	L		Sommaire du match
105 - 2021-08-16	553	Chiefs	6	As	1	L		Sommaire du match
106 - 2021-08-17	564	As	2	Wolves	5	L		Sommaire du match
107 - 2021-08-18	569	As	6	Isotopes	4	W		Sommaire du match
108 - 2021-08-19	575	Mooses	0	As	4	W		Sommaire du match
110 - 2021-08-21	588	Isotopes	3	As	1	L		Sommaire du match
111 - 2021-08-22	592	As	1	Mooses	3	L		Sommaire du match
112 - 2021-08-23	601	As	1	Canadiens	3	L		Sommaire du match
113 - 2021-08-24	607	Croque-Morts	2	As	4	W		Sommaire du match
114 - 2021-08-25	615	As	0	Riverman	3	L		Sommaire du match
115 - 2021-08-26	621	Snipers	5	As	7	W		Sommaire du match
118 - 2021-08-29	636	Snipers	6	As	4	L		Sommaire du match
119 - 2021-08-30	640	As	2	Snipers	2	T	X	Sommaire du match
122 - 2021-09-02	656	Croque-Morts	3	As	6	W		Sommaire du match

Capacité de l’aréna - Tendance du prix des billets - %
	Niveau 1	Niveau 2
Capacité	2000	1000
Prix des billets	35	15
Assistance	0	0
Assistance PCT	0.00%	0.00%

Revenu
Matchs à domicile restants	Assistance moyenne - %	Revenu moyen par match	Revenu annuel à ce jour	Capacité	Popularité de l’équipe
0	0 - 0.00%	0$	0$	3000	100

Dépenses
Dépenses annuelles à ce jour	Salaire total des joueurs	Salaire total moyen des joueurs	Salaire des entraineurs
1,185,527$	1,069,450$	1,054,450$	0$

Plafond salarial par jour	Plafond salarial à ce jour	Joueurs Inclus dans le plafond salarial	Joueurs exclut du plafond Salarial
1,069,450$	1,185,527$	24	0

Estimation
Revenus de la saison estimés	Jours restants de la saison	Dépenses par jour	Dépenses de la saison estimées
0$	1	9,467$	9,467$

Afficher ou masquer des colonnes

	Total											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

	As
	GP: 82 \| W: 28 \| L: 45 \| T: 7 \| P: 65 GF: 240 \| GA: 283 \| PP%: 19.94% \| PK%: 83.33% DG: Christian Nolet \| Morale : 33 \| Moyenne d’équipe : 64