Ligue de hockey Simulée Ste-Flanelle

Winnipeg
Roster
Scoring
Players Info
Lines
Team Stats
Schedule
Finance
Career Team Stat
Web Lines Editor

Show or Hide Column

Filter Tips

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

#	Player Name	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	Travis Moen		X	X		100.00	59	50	78	64	75	57	50	47	53	46	48	63	48	72	64	0	56	56	0
2	Cory Conacher		X	X		100.00	50	35	77	75	54	56	41	54	59	53	55	60	44	44	37	0	66	55	0
3	Sam Carrick	X	X	X		100.00	62	43	76	70	60	59	36	47	67	43	50	68	48	35	32	0	66	53	0
4	Zac Rinaldo		X	X		100.00	77	65	60	71	58	53	53	44	50	42	46	59	48	49	42	0	60	53	0
5	Andrew Agozzino (R)	X	X			100.00	51	35	95	72	58	53	35	46	54	56	35	64	48	35	32	0	66	52	0
6	Frederik Gauthier (R)	X				100.00	47	35	95	60	87	55	35	42	48	48	35	70	48	35	32	0	67	51	0
7	Michael Sgarbossa	X				100.00	55	35	59	72	58	52	35	43	50	51	35	61	48	39	36	0	81	51	0
8	Bryan Lerg	X	X			100.00	49	35	95	73	52	55	35	42	55	35	48	70	48	35	32	0	64	51	0
9	Stanislav Galiev		X	X		100.00	52	35	90	68	60	54	37	45	35	46	44	63	48	35	32	0	57	51	0
10	Pavel Zacha	X	X			100.00	47	35	95	63	73	59	35	38	35	40	35	58	48	35	32	0	61	48	0
11	Brett Bulmer		X	X		100.00	60	43	50	64	74	47	35	35	35	35	35	58	48	37	34	0	54	47	0
12	Patrik Nemeth				X	100.00	70	35	86	61	78	65	46	47	35	53	41	72	48	42	37	0	52	59	0
13	Michal Jordan				X	100.00	57	35	87	62	63	58	44	40	35	36	43	74	48	41	36	0	64	55	0
14	Keaton Ellerby				X	100.00	53	35	93	59	75	56	34	41	35	41	41	63	47	50	43	0	57	54	0
15	Patrick Sieloff				X	100.00	54	35	55	64	67	55	35	35	35	30	39	79	48	35	32	0	59	54	0
16	Mark Alt				X	100.00	47	35	94	59	67	42	33	33	35	33	33	64	47	35	32	0	36	49	0
17	Josh Jacobs (R)				X	100.00	45	45	45	45	62	45	45	45	45	45	45	45	45	32	30	0	21	45	0
Scratches
1	Justin Hodgman	X				100.00	48	35	84	68	70	49	33	37	57	33	40	60	47	35	32	0	19	48	0
2	David Wolf		X	X		100.00	64	35	78	66	75	46	33	33	49	33	33	58	47	35	33	0	26	46	0
3	Teemu Hartikainen	X	X	X		100.00	32	73	47	47	74	33	50	33	35	33	33	47	47	41	36	0	19	42	0
4	Johan Sundstrom	X				100.00	32	84	36	40	70	33	46	33	35	33	33	35	47	35	32	0	20	38	0
5	Saku Koivu	X				100.00	20	20	20	20	20	20	20	20	20	20	20	20	20	20	20	0	20	23	0
6	Marcus Pettersson (R)				X	100.00	45	45	45	45	51	45	45	45	45	45	45	45	45	32	30	0	20	44	0
7	Alex Plante				X	100.00	52	90	30	34	79	33	43	33	35	33	33	33	47	39	36	0	20	40	0
8	Yann Sauve				X	100.00	32	85	35	35	69	33	46	33	35	33	33	35	47	37	34	0	20	39	0
9	Jonathan Racine				X	100.00	32	85	35	35	63	33	51	33	35	33	33	35	47	35	32	0	20	39	0
10	Kimmo Timonen				X	100.00	20	20	20	20	20	20	20	20	20	20	20	20	20	20	20	0	20	23	0

	TEAM AVERAGE					100.00	49	46	65	56	63	47	39	39	42	39	38	55	45	38	34	0	44	47

Show or Hide Column

Filter Tips

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

#	Goalie Name	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Richard Bachman	100.00	45	45	66	65	46	49	47	47	50	65	70	46	42	0	33	51	0
2	Jeff Zatkoff	100.00	46	45	77	65	48	49	52	50	46	65	45	40	39	0	18	51	0
Scratches
1	John Curry	100.00	44	45	45	66	45	47	51	45	43	62	60	41	38	0	19	48	0
2	CJ Motte (R)	100.00	45	45	45	63	45	45	45	45	45	45	45	32	30	0	19	45	0
3	Martin Ouellette (R)	100.00	37	37	37	57	37	37	37	37	37	37	37	32	30	0	20	39	0

	TEAM AVERAGE	100.00	43	43	54	63	44	45	46	45	44	55	51	38	36	0	22	47

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Kurt Kleinendorst	36	63	52	40	75	71	56	USA	55	2	500,000$

Show or Hide Column

Filter Tips

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

#	Player Name	Team Name	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	TA	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Cory Conacher	IceCaps (Win)	LW/RW	82	32	41	73	-6	38	0	62	127	274	0	11.68%	7	1503	18.34	17	16	33	88	316	0	0	0	4	132	2	1	61.83%	131	0	0	0	0.97	1	2	0	0	0	2	3	5
2	Sam Carrick	IceCaps (Win)	C/LW/RW	82	28	42	70	-15	75	15	170	166	232	0	12.07%	15	1647	20.09	15	22	37	68	331	0	1	1	8	256	5	2	61.05%	1263	0	0	0	0.85	1	2	0	0	3	2	4	2
3	Travis Moen	IceCaps (Win)	LW/RW	82	28	30	58	13	69	25	110	96	188	0	14.89%	12	1389	16.94	4	6	10	29	167	0	1	1	2	141	3	3	52.78%	108	0	0	0	0.84	1	5	1	2	2	3	6	4
4	Andrew Agozzino	IceCaps (Win)	C/LW	82	11	41	52	-1	10	0	20	131	115	0	9.57%	5	1190	14.52	4	17	21	34	277	0	0	0	1	62	1	0	54.42%	1040	0	0	0	0.87	0	7	0	0	0	2	4	1
5	Michal Jordan	IceCaps (Win)	D	82	11	32	43	2	60	0	85	78	105	0	10.48%	95	1662	20.27	7	10	17	42	239	0	0	0	4	221	1	0	0.00%	0	0	0	0	0.52	0	1	0	0	0	2	1	4
6	Zac Rinaldo	IceCaps (Win)	LW/RW	82	21	21	42	-4	127	35	184	86	155	0	13.55%	9	1143	13.94	4	4	8	20	164	0	0	0	2	83	2	1	55.29%	85	0	1	0	0.73	1	1	1	2	4	3	3	5
7	Patrick Sieloff	IceCaps (Win)	D	82	11	29	40	-11	90	0	178	74	102	0	10.78%	95	1708	20.83	5	7	12	49	257	0	1	1	3	249	2	0	0.00%	0	0	1	0	0.47	0	0	0	0	0	3	1	0
8	Frederik Gauthier	IceCaps (Win)	C	79	11	27	38	-13	8	0	20	115	98	0	11.22%	24	1222	15.48	2	8	10	24	177	1	0	1	5	125	2	2	51.50%	1334	0	0	0	0.62	0	3	0	0	0	1	0	3
9	Keaton Ellerby	IceCaps (Win)	D	82	9	28	37	-6	38	0	44	56	71	0	12.68%	69	1637	19.96	6	12	18	36	301	0	0	0	3	130	1	0	0.00%	0	0	0	0	0.45	0	0	0	0	0	0	3	1
10	Stanislav Galiev	IceCaps (Win)	LW/RW	82	7	24	31	-21	11	5	12	84	134	0	5.22%	9	969	11.82	1	7	8	12	113	0	0	0	2	44	0	0	39.76%	83	0	0	0	0.64	0	0	0	1	0	0	0	1
11	Bryan Lerg	IceCaps (Win)	C/LW	82	19	11	30	-16	4	0	23	154	148	0	12.84%	13	932	11.37	0	0	0	4	8	0	0	0	4	199	3	1	49.88%	846	0	1	0	0.64	0	0	0	0	0	1	1	1
12	Pavel Zacha	IceCaps (Win)	C/LW	81	7	22	29	-3	8	0	23	64	86	0	8.14%	10	1054	13.01	0	7	7	18	226	0	0	0	0	17	0	1	38.39%	422	0	0	0	0.55	1	7	0	0	0	1	1	2
13	Patrik Nemeth	IceCaps (Win)	D	52	7	20	27	-6	58	0	97	60	61	0	11.48%	54	1181	22.72	3	5	8	37	212	0	0	0	1	162	0	0	0.00%	0	0	0	0	0.46	0	0	0	0	0	3	1	2
14	Michael Sgarbossa	IceCaps (Win)	C	79	5	15	20	-5	45	5	87	99	78	0	6.41%	6	842	10.67	0	0	0	0	14	0	0	0	0	18	2	0	52.45%	652	0	0	0	0.47	0	3	0	0	1	1	0	1
15	Brett Bulmer	IceCaps (Win)	LW/RW	75	7	5	12	5	54	10	91	33	53	0	13.21%	5	823	10.98	0	1	1	1	17	0	0	0	0	20	1	0	37.50%	48	0	0	0	0.29	0	0	0	0	2	1	2	0
16	David Wolf	IceCaps (Win)	LW/RW	49	4	6	10	-22	22	0	52	15	32	0	12.50%	4	478	9.76	0	0	0	3	8	0	0	0	0	0	2	0	50.00%	28	0	0	0	0.42	0	0	0	0	0	0	0	1
17	Mark Alt	IceCaps (Win)	D	56	3	7	10	-7	15	5	21	25	25	0	12.00%	50	900	16.08	2	1	3	5	41	0	0	0	0	62	0	1	0.00%	0	0	0	0	0.22	0	0	0	0	1	0	1	0
18	Josh Jacobs	IceCaps (Win)	D	31	1	3	4	0	60	10	76	16	9	0	11.11%	9	492	15.87	1	0	1	3	20	0	0	0	0	16	0	0	0.00%	0	0	0	0	0.16	0	0	1	1	0	0	0	0
19	Teemu Hartikainen	IceCaps (Win)	C/LW/RW	31	1	3	4	-3	15	5	26	3	5	0	20.00%	3	304	9.81	0	0	0	0	0	0	0	0	0	0	0	0	45.00%	20	0	0	0	0.26	0	0	1	0	0	0	0	0
20	Justin Hodgman	IceCaps (Win)	C	17	0	3	3	-3	4	0	9	24	20	0	0.00%	1	161	9.49	0	0	0	0	1	0	0	0	0	0	0	0	58.72%	172	0	0	0	0.37	0	0	0	0	0	0	0	0
Team Total or Average			1370	223	410	633	-122	811	115	1390	1506	1991	0	11.20%	495	21244	15.51	71	123	194	473	2898	1	3	4	39	1946	27	12	53.11%	6232	0	3	0	0.60	5	31	4	6	13	25	31	33

Show or Hide Column

Filter Tips

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

#	Goalie Name	Team Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Richard Bachman	IceCaps (Win)	50	18	19	5	0.870	3.18	2660	0	1	141	1084	0	3	1	0.579	19	42	36	1	0	2
2	Jeff Zatkoff	IceCaps (Win)	30	13	13	2	0.854	3.63	1522	2	2	92	631	0	1	1	0.778	9	29	3	2	0	1
3	John Curry	IceCaps (Win)	16	4	5	3	0.873	3.30	746	0	1	41	324	0	0	0	0.429	7	11	40	0	1	0
4	CJ Motte	IceCaps (Win)	1	0	0	0	0.833	5.22	46	0	0	4	24	0	0	0	0.000	0	0	3	0	0	0
Team Total or Average		97	35	37	10	0.865	3.35	4977	2	4	278	2063	0	4	2	0.600	35	82	82	3	1	3

Show or Hide Column

Filter Tips

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

Player Name	Team Name	POS	Age	Birthday	Rookie	Weight	Height	No Trade	Force Waivers	Contract	Status	Type	Current Salary	Salary Year 2	Salary Year 3	Salary Year 4	Link
Alex Plante	IceCaps (Win)	D	26	1989-05-09	No	230 Lbs	6 ft4	No	No	1	RFA	Pro & Farm	725,000$				Link
Andrew Agozzino	IceCaps (Win)	C/LW	24	1991-01-03	Yes	187 Lbs	5 ft10	No	No	3	RFA	Pro & Farm	590,000$	590,000$	590,000$		Link
Brett Bulmer	IceCaps (Win)	LW/RW	23	1992-04-26	No	212 Lbs	6 ft4	No	No	3	RFA	Pro & Farm	750,000$	760,000$	775,000$		Link
Bryan Lerg	IceCaps (Win)	C/LW	29	1986-01-20	No	175 Lbs	5 ft10	No	No	1	RFA	Pro & Farm	750,000$				Link
CJ Motte	IceCaps (Win)	G	23	1991-12-10	Yes	175 Lbs	6 ft0	No	No	4	RFA	Pro & Farm	825,000$	825,000$	825,000$	825,000$	Link
Cory Conacher	IceCaps (Win)	LW/RW	25	1989-12-14	No	182 Lbs	5 ft8	No	No	1	RFA	Pro & Farm	818,000$				Link
David Wolf	IceCaps (Win)	LW/RW	26	1989-09-15	No	215 Lbs	6 ft3	No	No	3	RFA	Pro & Farm	975,000$	975,000$	975,000$		Link
Frederik Gauthier	IceCaps (Win)	C	20	1995-04-26	Yes	238 Lbs	6 ft5	No	No	4	ELC	Pro & Farm	925,000$	925,000$	925,000$	925,000$	Link
Jeff Zatkoff	IceCaps (Win)	G	28	1987-06-09	No	179 Lbs	6 ft2	No	No	2	RFA	Pro & Farm	525,000$	525,000$			Link
Johan Sundstrom	IceCaps (Win)	C	23	1992-09-21	No	201 Lbs	6 ft3	No	No	2	RFA	Pro & Farm	743,000$	743,000$			Link
John Curry	IceCaps (Win)	G	31	1984-02-27	No	185 Lbs	5 ft11	No	No	2	UFA	Pro & Farm	450,000$	450,000$			Link
Jonathan Racine	IceCaps (Win)	D	22	1993-05-28	No	194 Lbs	6 ft2	No	No	2	RFA	Pro & Farm	665,000$	665,000$			Link
Josh Jacobs	IceCaps (Win)	D	19	1996-02-15	Yes	193 Lbs	6 ft1	No	No	4	ELC	Pro & Farm	825,000$	825,000$	825,000$	825,000$	Link
Justin Hodgman	IceCaps (Win)	C	27	1988-06-27	No	203 Lbs	6 ft1	No	No	3	RFA	Pro & Farm	750,000$	750,000$	750,000$		Link
Keaton Ellerby	IceCaps (Win)	D	26	1988-11-05	No	220 Lbs	6 ft5	No	No	2	RFA	Pro & Farm	875,000$	875,000$			Link
Kimmo Timonen (1 Way Contract)	IceCaps (Win)	D	40	1975-03-18	No	194 Lbs	5 ft10	Yes	No	2	UFA	Pro & Farm	4,000,000$	4,000,000$			Link
Marcus Pettersson	IceCaps (Win)	D	19	1996-05-08	Yes	167 Lbs	6 ft4	No	No	4	ELC	Pro & Farm	725,000$	725,000$	725,000$	725,000$	Link
Mark Alt	IceCaps (Win)	D	23	1991-10-18	No	201 Lbs	6 ft4	No	No	3	RFA	Pro & Farm	790,000$	790,000$	790,000$		Link
Martin Ouellette	IceCaps (Win)	G	23	1991-12-30	Yes	160 Lbs	6 ft1	No	No	4	RFA	Pro & Farm	525,000$	525,000$	525,000$	525,000$	Link
Michael Sgarbossa	IceCaps (Win)	C	23	1992-07-25	No	186 Lbs	6 ft0	No	No	1	RFA	Pro & Farm	570,000$				Link
Michal Jordan	IceCaps (Win)	D	25	1990-07-17	No	195 Lbs	6 ft1	No	No	1	RFA	Pro & Farm	632,000$				Link
Patrick Sieloff	IceCaps (Win)	D	21	1994-05-15	No	205 Lbs	6 ft1	No	No	4	ELC	Pro & Farm	925,000$	925,000$	925,000$	925,000$	Link
Patrik Nemeth	IceCaps (Win)	D	23	1992-02-08	No	230 Lbs	6 ft3	No	No	2	RFA	Pro & Farm	790,000$	790,000$			Link
Pavel Zacha	IceCaps (Win)	C/LW	18	1997-04-06	No	210 Lbs	6 ft3	No	No	4	ELC	Pro & Farm	925,000$	925,000$	925,000$	925,000$	Link
Richard Bachman	IceCaps (Win)	G	28	1987-07-25	No	183 Lbs	5 ft10	Yes	No	1	RFA	Pro & Farm	2,000,000$				Link
Saku Koivu (1 Way Contract)	IceCaps (Win)	C	40	1974-11-23	No	181 Lbs	5 ft10	Yes	No	2	UFA	Pro & Farm	2,000,000$	2,000,000$			Link
Sam Carrick	IceCaps (Win)	C/LW/RW	23	1992-02-04	No	188 Lbs	6 ft0	No	No	3	RFA	Pro & Farm	1,010,000$	1,010,000$	1,010,000$		Link
Stanislav Galiev	IceCaps (Win)	LW/RW	23	1992-01-17	No	187 Lbs	6 ft1	No	No	3	RFA	Pro & Farm	550,000$	550,000$	550,000$		Link
Teemu Hartikainen	IceCaps (Win)	C/LW/RW	25	1990-05-03	No	214 Lbs	6 ft1	No	No	3	RFA	Pro & Farm	875,000$	875,000$	875,000$		Link
Travis Moen	IceCaps (Win)	LW/RW	33	1982-04-06	No	215 Lbs	6 ft2	Yes	No	3	UFA	Pro & Farm	500,000$	500,000$	500,000$		Link
Yann Sauve	IceCaps (Win)	D	25	1990-02-18	No	209 Lbs	6 ft3	No	No	3	RFA	Pro & Farm	762,000$	762,000$	762,000$		Link
Zac Rinaldo	IceCaps (Win)	LW/RW	25	1990-06-15	No	188 Lbs	5 ft10	No	No	2	RFA	Pro & Farm	600,000$	600,000$			Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
32	25.28	197 Lbs	6 ft1	2.56	917,813$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Sam Carrick	Frederik Gauthier	Cory Conacher	40	0	1	4
2	Travis Moen	Michael Sgarbossa		35	0	2	3
3	Zac Rinaldo	Pavel Zacha	Stanislav Galiev	15	0	2	3
4	Bryan Lerg	Andrew Agozzino	Brett Bulmer	10	0	2	3

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Patrik Nemeth	Patrick Sieloff	40	0	3	2
2	Michal Jordan	Keaton Ellerby	30	0	4	1
3	Josh Jacobs	Mark Alt	20	1	3	1
4	Patrik Nemeth	Patrick Sieloff	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Pavel Zacha	Sam Carrick	Cory Conacher	60	0	0	5
2	Andrew Agozzino	Frederik Gauthier		40	0	1	4

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Patrik Nemeth	Patrick Sieloff	60	0	1	4
2	Michal Jordan	Keaton Ellerby	40	0	1	4

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Frederik Gauthier	Sam Carrick	60	0	5	0
2	Bryan Lerg	Travis Moen	40	0	5	0

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Patrick Sieloff	Michal Jordan	60	1	4	0
2	Keaton Ellerby	Patrik Nemeth	40	1	4	0

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Frederik Gauthier	60	0	5	0	Patrik Nemeth	Patrick Sieloff	60	0	5	0
2	Sam Carrick	40	0	5	0	Mark Alt	Keaton Ellerby	40	0	5	0

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Frederik Gauthier	Sam Carrick	60	1	1	3
2	Andrew Agozzino		40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Patrick Sieloff	Patrik Nemeth	60	0	3	2
2	Keaton Ellerby	Michal Jordan	40	0	3	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Andrew Agozzino	Frederik Gauthier		Patrik Nemeth	Patrick Sieloff

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Andrew Agozzino	Frederik Gauthier	Travis Moen	Michal Jordan	Patrick Sieloff

Extra Forwards
Normal	PowerPlay	Penalty Kill
Zac Rinaldo, , Cory Conacher	, Sam Carrick	Cory Conacher

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Josh Jacobs, Patrick Sieloff, Michal Jordan	Patrick Sieloff	Michal Jordan, Patrick Sieloff

Penalty Shots
, Frederik Gauthier, Michael Sgarbossa, Sam Carrick, Cory Conacher

Goalie
#1 : Jeff Zatkoff, #2 : Richard Bachman

Custom OT Lines Forwards
, , , , , , , , , ,

Custom OT Lines Defensemen
, , , ,

Show or Hide Column

Filter Tips

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

	Overall											Home											Visitor
VS Team	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
Admirals	3	1	1	0	1	0	0	0	13	10	3	2	1	0	0	1	0	0	0	9	5	4	1	0	1	0	0	0	0	0	4	5	-1	4	0.667	13	23	36	0	0	109	81	77	11	90	730	755	786	57	96	28	35	49	16	4	25.00%	14	3	78.57%	1	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Falcons	2	1	0	0	0	0	1	0	12	9	3	1	1	0	0	0	0	0	0	5	3	2	1	0	0	0	0	0	1	0	7	6	1	4	1.000	12	19	31	0	0	109	81	77	11	65	730	755	786	57	48	9	24	42	20	3	15.00%	11	2	81.82%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Bruins	2	0	1	0	0	0	0	1	8	14	-6	1	0	1	0	0	0	0	0	3	8	-5	1	0	0	0	0	0	0	1	5	6	-1	1	0.250	8	14	22	0	0	109	81	77	11	60	730	755	786	57	61	19	41	39	10	5	50.00%	13	3	76.92%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Crunch	2	1	1	0	0	0	0	0	4	5	-1	1	1	0	0	0	0	0	0	3	2	1	1	0	1	0	0	0	0	0	1	3	-2	2	0.500	4	6	10	1	0	109	81	77	11	53	730	755	786	57	42	9	18	32	10	2	20.00%	8	1	87.50%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Heat	3	0	3	0	0	0	0	0	7	10	-3	2	0	2	0	0	0	0	0	4	6	-2	1	0	1	0	0	0	0	0	3	4	-1	0	0.000	7	14	21	0	0	109	81	77	11	85	730	755	786	57	62	21	32	57	16	2	12.50%	16	3	81.25%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Phantoms	2	0	2	0	0	0	0	0	3	6	-3	1	0	1	0	0	0	0	0	2	4	-2	1	0	1	0	0	0	0	0	1	2	-1	0	0.000	3	6	9	0	0	109	81	77	11	47	730	755	786	57	56	15	24	36	19	2	10.53%	11	2	81.82%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Baby Hawks	5	1	3	0	0	0	0	1	11	19	-8	2	1	1	0	0	0	0	0	6	7	-1	3	0	2	0	0	0	0	1	5	12	-7	3	0.300	11	16	27	0	0	109	81	77	11	91	730	755	786	57	136	43	73	94	26	4	15.38%	29	4	86.21%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Monsters	5	2	2	0	0	0	0	1	13	18	-5	2	0	1	0	0	0	0	1	4	8	-4	3	2	1	0	0	0	0	0	9	10	-1	5	0.500	13	23	36	0	0	109	81	77	11	123	730	755	786	57	156	42	70	85	28	3	10.71%	23	5	78.26%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Jayhawks	5	0	5	0	0	0	0	0	11	21	-10	3	0	3	0	0	0	0	0	6	11	-5	2	0	2	0	0	0	0	0	5	10	-5	0	0.000	11	20	31	0	0	109	81	77	11	111	730	755	786	57	161	34	55	94	18	3	16.67%	24	8	66.67%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Cougars	2	0	1	0	0	0	0	1	6	9	-3	1	0	1	0	0	0	0	0	3	5	-2	1	0	0	0	0	0	0	1	3	4	-1	1	0.250	6	10	16	0	0	109	81	77	11	51	730	755	786	57	46	17	12	24	12	1	8.33%	6	1	83.33%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Oil Kings	3	2	1	0	0	0	0	0	11	10	1	2	1	1	0	0	0	0	0	7	7	0	1	1	0	0	0	0	0	0	4	3	1	4	0.667	11	18	29	0	0	109	81	77	11	96	730	755	786	57	71	19	27	57	16	4	25.00%	11	4	63.64%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Sound Tigers	2	0	2	0	0	0	0	0	4	8	-4	1	0	1	0	0	0	0	0	3	5	-2	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	4	7	11	1	0	109	81	77	11	60	730	755	786	57	51	18	17	29	12	2	16.67%	6	1	83.33%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Monarchs	3	1	0	0	0	1	0	1	11	11	0	1	0	0	0	0	1	0	0	3	4	-1	2	1	0	0	0	0	0	1	8	7	1	4	0.667	11	20	31	0	0	109	81	77	11	71	730	755	786	57	77	25	37	51	6	3	50.00%	16	3	81.25%	1	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Minnesota	5	2	3	0	0	0	0	0	18	16	2	3	1	2	0	0	0	0	0	8	10	-2	2	1	1	0	0	0	0	0	10	6	4	4	0.400	18	32	50	0	0	109	81	77	11	195	730	755	786	57	128	32	48	116	27	3	11.11%	18	4	77.78%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Spiders	2	0	1	0	1	0	0	0	9	10	-1	1	0	0	0	1	0	0	0	5	4	1	1	0	1	0	0	0	0	0	4	6	-2	2	0.500	9	16	25	0	0	109	81	77	11	70	730	755	786	57	56	16	20	42	15	5	33.33%	10	3	70.00%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Senators	2	2	0	0	0	0	0	0	9	7	2	1	1	0	0	0	0	0	0	4	3	1	1	1	0	0	0	0	0	0	5	4	1	4	1.000	9	18	27	0	0	109	81	77	11	70	730	755	786	57	49	20	22	38	8	5	62.50%	11	4	63.64%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Manchots	2	2	0	0	0	0	0	0	4	1	3	1	1	0	0	0	0	0	0	2	1	1	1	1	0	0	0	0	0	0	2	0	2	4	1.000	4	8	12	0	1	109	81	77	11	60	730	755	786	57	28	7	41	39	15	1	6.67%	13	0	100.00%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Wolf Pack	2	1	1	0	0	0	0	0	10	9	1	1	1	0	0	0	0	0	0	7	5	2	1	0	1	0	0	0	0	0	3	4	-1	2	0.500	10	19	29	0	0	109	81	77	11	82	730	755	786	57	40	26	16	39	8	4	50.00%	8	0	100.00%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Sharks	3	0	2	0	1	0	0	0	6	9	-3	2	0	1	0	1	0	0	0	4	5	-1	1	0	1	0	0	0	0	0	2	4	-2	2	0.333	6	9	15	0	0	109	81	77	11	59	730	755	786	57	82	19	24	53	16	1	6.25%	12	3	75.00%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Chiefs	5	3	2	0	0	0	0	0	18	19	-1	2	2	0	0	0	0	0	0	8	3	5	3	1	2	0	0	0	0	0	10	16	-6	6	0.600	18	32	50	0	1	109	81	77	11	114	730	755	786	57	126	39	47	98	14	4	28.57%	20	4	80.00%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Thunder	2	0	2	0	0	0	0	0	7	10	-3	1	0	1	0	0	0	0	0	4	6	-2	1	0	1	0	0	0	0	0	3	4	-1	0	0.000	7	12	19	0	0	109	81	77	11	49	730	755	786	57	43	13	25	31	10	2	20.00%	9	0	100.00%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Marlies	2	2	0	0	0	0	0	0	11	5	6	1	1	0	0	0	0	0	0	4	3	1	1	1	0	0	0	0	0	0	7	2	5	4	1.000	11	20	31	0	0	109	81	77	11	68	730	755	786	57	32	8	8	45	9	4	44.44%	4	1	75.00%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Comets	3	2	0	0	0	0	0	1	14	11	3	1	1	0	0	0	0	0	0	5	3	2	2	1	0	0	0	0	0	1	9	8	1	5	0.833	14	26	40	0	0	109	81	77	11	78	730	755	786	57	65	22	26	53	12	3	25.00%	13	2	84.62%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Cabaret Lady Mary Ann	2	1	0	0	0	0	0	1	7	5	2	1	1	0	0	0	0	0	0	3	0	3	1	0	0	0	0	0	0	1	4	5	-1	3	0.750	7	13	20	0	1	109	81	77	11	59	730	755	786	57	47	21	24	47	8	3	37.50%	12	3	75.00%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Chill	3	0	1	0	0	0	0	2	9	13	-4	1	0	0	0	0	0	0	1	2	3	-1	2	0	1	0	0	0	0	1	7	10	-3	2	0.333	9	18	27	0	0	109	81	77	11	90	730	755	786	57	98	22	29	60	16	3	18.75%	12	2	83.33%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Rocket	2	0	2	0	0	0	0	0	3	8	-5	1	0	1	0	0	0	0	0	2	3	-1	1	0	1	0	0	0	0	0	1	5	-4	0	0.000	3	6	9	0	0	109	81	77	11	44	730	755	786	57	41	11	24	35	8	1	12.50%	12	4	66.67%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Bears	2	1	0	0	0	0	1	0	7	5	2	1	1	0	0	0	0	0	0	2	1	1	1	0	0	0	0	0	1	0	5	4	1	4	1.000	7	10	17	0	0	109	81	77	11	52	730	755	786	57	42	13	22	47	11	0	0.00%	10	2	80.00%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Caroline	2	1	0	0	1	0	0	0	12	5	7	1	1	0	0	0	0	0	0	9	3	6	1	0	0	0	1	0	0	0	3	2	1	4	1.000	12	22	34	0	0	109	81	77	11	51	730	755	786	57	54	15	39	34	11	3	27.27%	11	0	100.00%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Las Vegas	4	2	1	0	0	0	1	0	16	6	10	2	2	0	0	0	0	0	0	11	1	10	2	0	1	0	0	0	1	0	5	5	0	6	0.750	16	26	42	0	1	109	81	77	11	147	730	755	786	57	71	23	25	73	29	6	20.69%	9	1	88.89%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Vs Division	16	1	4	0	1	1	0	4	55	63	-8	8	0	2	0	1	1	0	1	26	30	-4	8	1	2	0	0	0	0	3	29	33	-4	9	0.281	55	99	154	1	1	109	81	77	11	454	730	755	786	57	361	118	174	291	75	23	30.67%	75	17	77.33%	0	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Vs Conference	32	9	13	0	3	1	2	4	112	122	-10	16	6	5	0	3	1	0	1	55	57	-2	16	3	8	0	0	0	2	3	57	65	-8	33	0.516	112	199	311	1	1	109	81	77	11	925	730	755	786	57	827	250	377	595	182	40	21.98%	156	28	82.05%	2	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Since Last GM Reset	82	28	37	0	4	1	3	9	274	289	-15	41	18	17	0	3	1	0	2	138	129	9	41	10	20	0	1	0	3	7	136	160	-24	80	0.488	274	483	757	2	4	109	81	77	11	2291	730	755	786	57	2065	606	905	1539	426	86	20.19%	372	73	80.38%	2	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Total	82	28	37	0	4	1	3	9	274	289	-15	41	18	17	0	3	1	0	2	138	129	9	41	10	20	0	1	0	3	7	136	160	-24	80	0.488	274	483	757	2	4	109	81	77	11	2291	730	755	786	57	2065	606	905	1539	426	86	20.19%	372	73	80.38%	2	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
82	80	W1	274	483	757	2291	2065	606	905	1539	2	4

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
82	28	37	4	1	3	9	274	289

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	18	17	3	1	0	2	138	129

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	10	20	1	0	3	7	136	160

Last 10 Games
W	L	OTW	OTL	SOW	SOL
5	2	1	0	1	1

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
426	86	20.19%	372	73	80.38%	2

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
730	755	786	57	109	81	77	11

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
2099	1418	1772	637	1114	573

Last Played Games

Filter Tips

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

Day	Game	Visitor Team	Score	Home Team	Score	ST	OT	SO	Link
2 - 2016-10-13	8	Caroline	3	IceCaps	9	W			BoxScore
4 - 2016-10-15	25	IceCaps	3	Minnesota	4	L			BoxScore
6 - 2016-10-17	36	Bruins	8	IceCaps	3	L			BoxScore
8 - 2016-10-19	50	Marlies	3	IceCaps	4	W			BoxScore
12 - 2016-10-23	79	Oil Kings	4	IceCaps	3	L			BoxScore
14 - 2016-10-25	90	IceCaps	3	Jayhawks	5	L			BoxScore
16 - 2016-10-27	104	Jayhawks	2	IceCaps	1	L			BoxScore
17 - 2016-10-28	109	IceCaps	4	Monsters	3	W			BoxScore
19 - 2016-10-30	123	Crunch	2	IceCaps	3	W			BoxScore
21 - 2016-11-01	134	Bears	1	IceCaps	2	W			BoxScore
23 - 2016-11-03	152	IceCaps	5	Bears	4	W	X	X	BoxScore
24 - 2016-11-04	160	IceCaps	3	Cougars	4	L	X	X	BoxScore
26 - 2016-11-06	177	IceCaps	3	Wolf Pack	4	L			BoxScore
28 - 2016-11-08	191	Jayhawks	3	IceCaps	2	L			BoxScore
30 - 2016-11-10	202	IceCaps	4	Chill	6	L			BoxScore
31 - 2016-11-11	210	IceCaps	2	Monsters	5	L			BoxScore
33 - 2016-11-13	223	Monarchs	4	IceCaps	3	L	X		BoxScore
35 - 2016-11-15	234	Baby Hawks	3	IceCaps	5	W			BoxScore
37 - 2016-11-17	254	IceCaps	1	Phantoms	2	L			BoxScore
39 - 2016-11-19	267	IceCaps	5	Bruins	6	L	X	X	BoxScore
40 - 2016-11-20	273	IceCaps	3	Caroline	2	W	X		BoxScore
43 - 2016-11-23	293	IceCaps	7	Minnesota	2	W			BoxScore
45 - 2016-11-25	303	IceCaps	4	Las Vegas	3	W	X	X	BoxScore
47 - 2016-11-27	322	Las Vegas	0	IceCaps	6	W			BoxScore
49 - 2016-11-29	335	Spiders	4	IceCaps	5	W	X		BoxScore
51 - 2016-12-01	352	Oil Kings	3	IceCaps	4	W			BoxScore
53 - 2016-12-03	361	IceCaps	3	Chiefs	7	L			BoxScore
54 - 2016-12-04	374	IceCaps	0	Baby Hawks	4	L			BoxScore
56 - 2016-12-06	386	Cougars	5	IceCaps	3	L			BoxScore
58 - 2016-12-08	401	Wolf Pack	5	IceCaps	7	W			BoxScore
60 - 2016-12-10	415	IceCaps	3	Heat	4	L			BoxScore
61 - 2016-12-11	428	IceCaps	4	Oil Kings	3	W			BoxScore
65 - 2016-12-15	451	Cabaret Lady Mary Ann	0	IceCaps	3	W			BoxScore
68 - 2016-12-18	474	Monsters	4	IceCaps	1	L			BoxScore
70 - 2016-12-20	491	IceCaps	3	Comets	4	L	X	X	BoxScore
72 - 2016-12-22	504	IceCaps	6	Comets	4	W			BoxScore
77 - 2016-12-27	523	IceCaps	3	Baby Hawks	4	L	X	X	BoxScore
79 - 2016-12-29	539	Falcons	3	IceCaps	5	W			BoxScore
81 - 2016-12-31	557	Sound Tigers	5	IceCaps	3	L			BoxScore
84 - 2017-01-03	569	IceCaps	3	Thunder	4	L			BoxScore
85 - 2017-01-04	575	IceCaps	4	Cabaret Lady Mary Ann	5	L	X	X	BoxScore
88 - 2017-01-07	600	IceCaps	1	Crunch	3	L			BoxScore
90 - 2017-01-09	611	Heat	2	IceCaps	1	L			BoxScore
92 - 2017-01-11	621	Rocket	3	IceCaps	2	L			BoxScore
94 - 2017-01-13	639	IceCaps	3	Chill	4	L	X	X	BoxScore
95 - 2017-01-14	650	IceCaps	5	Monarchs	3	W			BoxScore
97 - 2017-01-16	660	IceCaps	2	Sharks	4	L			BoxScore
99 - 2017-01-18	673	Chill	3	IceCaps	2	L	X	X	BoxScore
102 - 2017-01-21	701	Chiefs	3	IceCaps	7	W			BoxScore
104 - 2017-01-23	708	Admirals	1	IceCaps	4	W			BoxScore
105 - 2017-01-24	721	Sharks	2	IceCaps	0	L			BoxScore
107 - 2017-01-26	734	IceCaps	2	Baby Hawks	4	L			BoxScore
112 - 2017-01-31	754	IceCaps	2	Chiefs	5	L			BoxScore
114 - 2017-02-02	763	IceCaps	2	Jayhawks	5	L			BoxScore
116 - 2017-02-04	773	IceCaps	3	Monsters	2	W			BoxScore
119 - 2017-02-07	799	Minnesota	5	IceCaps	1	L			BoxScore
122 - 2017-02-10	814	Baby Hawks	4	IceCaps	1	L			BoxScore
123 - 2017-02-11	825	Thunder	6	IceCaps	4	L			BoxScore
126 - 2017-02-14	841	Jayhawks	6	IceCaps	3	L			BoxScore
128 - 2017-02-16	849	IceCaps	2	Manchots	0	W			BoxScore
130 - 2017-02-18	858	IceCaps	1	Rocket	5	L			BoxScore
131 - 2017-02-19	879	IceCaps	5	Senators	4	W			BoxScore
133 - 2017-02-21	885	IceCaps	7	Marlies	2	W			BoxScore
140 - 2017-02-28	932	Minnesota	2	IceCaps	1	L			BoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
143 - 2017-03-03	950	Chiefs	0	IceCaps	1	W			BoxScore
144 - 2017-03-04	958	Monsters	4	IceCaps	3	L	X	X	BoxScore
146 - 2017-03-06	972	Sharks	3	IceCaps	4	W	X		BoxScore
148 - 2017-03-08	984	Manchots	1	IceCaps	2	W			BoxScore
151 - 2017-03-11	1007	Heat	4	IceCaps	3	L			BoxScore
153 - 2017-03-13	1019	IceCaps	1	Las Vegas	2	L			BoxScore
154 - 2017-03-14	1029	IceCaps	4	Spiders	6	L			BoxScore
156 - 2017-03-16	1040	IceCaps	1	Sound Tigers	3	L			BoxScore
159 - 2017-03-19	1068	Minnesota	3	IceCaps	6	W			BoxScore
161 - 2017-03-21	1083	Phantoms	4	IceCaps	2	L			BoxScore
163 - 2017-03-23	1100	IceCaps	3	Monarchs	4	L	X	X	BoxScore
164 - 2017-03-24	1104	IceCaps	4	Admirals	5	L			BoxScore
166 - 2017-03-26	1120	Comets	3	IceCaps	5	W			BoxScore
170 - 2017-03-30	1144	Admirals	4	IceCaps	5	W	X		BoxScore
172 - 2017-04-01	1163	Senators	3	IceCaps	4	W			BoxScore
175 - 2017-04-04	1179	IceCaps	5	Chiefs	4	W			BoxScore
177 - 2017-04-06	1200	IceCaps	7	Falcons	6	W	X	X	BoxScore
179 - 2017-04-08	1215	Las Vegas	1	IceCaps	5	W			BoxScore

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	30	15
Attendance	61396	30222
Attendance PCT	74.87%	73.71%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
0	2235 - 74.49%	55,981$	2,295,210$	3000	100

Expenses
Players Total Salaries	Players Total Average Salaries	Coaches Salaries
2,337,000$	2,338,167$	0$

Year To Date Expenses	Salary Cap Per Days	Salary Cap To Date
2,908,991$	12,912$	2,399,290$

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	0	15,674$	0$

Show or Hide Column

	Overall											Home											Visitor
Year	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
Regular Season
2016	82	28	37	0	4	1	3	9	274	289	-15	41	18	17	0	3	1	0	2	138	129	9	41	10	20	0	1	0	3	7	136	160	-24	56	274	483	757	2	4	109	81	77	11	2291	730	755	786	57	2065	606	905	1539	426	86	20.19%	372	73	80.38%	2	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573
Total Regular Season	82	28	37	0	4	1	3	9	274	289	-15	41	18	17	0	3	1	0	2	138	129	9	41	10	20	0	1	0	3	7	136	160	-24	56	274	483	757	2	4	109	81	77	11	2291	730	755	786	57	2065	606	905	1539	426	86	20.19%	372	73	80.38%	2	1370	2587	52.96%	1204	2338	51.50%	737	1422	51.83%	2099	1418	1772	637	1114	573