Ligue de hockey simulé de Maniwaki

Mariners
Roster
Scoring
Players Info
Lines
Team Stats
Schedule
Finance
Career Team Stat

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	Victor Rask	X				99.00	76	62	96	80	80	81	76	76	80	75	77	75	58	73	76	0	80	73	0
2	Andre Burakovsky		X			100.00	73	64	89	87	82	79	59	77	64	74	79	74	59	74	76	0	79	73	0
3	J.T. Compher (R)		X			100.00	72	61	93	87	79	82	75	73	69	69	76	79	57	69	71	0	80	72	0
4	Jacob De La Rose (R)		X			100.00	92	69	89	84	87	77	57	69	64	69	68	80	51	70	71	0	69	71	0
5	Brendan Leipsic (R)		X			100.00	71	64	94	85	75	79	61	74	50	78	69	74	52	68	70	0	72	70	0
6	Matthew Peca (R)	X				100.00	80	61	98	85	77	79	35	73	70	75	70	81	53	65	65	0	80	70	0
7	Brett Ritchie (R)			X		100.00	92	73	87	84	90	76	73	69	50	67	70	71	53	70	74	0	54	70	0
8	Shea Theodore (R)				X	100.00	69	64	95	86	80	86	69	76	50	81	70	72	62	71	75	0	57	72	0
9	Chris Wideman (R)				X	100.00	79	63	92	80	78	77	35	75	50	75	75	64	56	71	73	0	45	69	0
Scratches

	TEAM AVERAGE					99.89	78	65	93	84	81	80	60	74	61	74	73	74	56	70	72	0	68	71

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	Alex Stalock	100.00	75	70	78	83	73	73	75	72	73	74	73	70	72	0	77	73	0
Scratches

	TEAM AVERAGE	100.00	75	70	78	83	73	73	75	72	73	74	73	70	72	0	77	73

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
John Hynes	82	83	86	91	73	68	99	USA	43	3	550,000$

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	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	GA	TA	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Victor Rask	Distraction (MRS)	C	43	53	77	130	36	17	5	55	78	264	86	164	20.08%	25	929	21.61	19	33	52	37	109	1	1	2	2	20	3	1	71.49%	898	45	36	4	2.80	0	2	0	0	1	14	5	7
2	Brian Gibbons	Mariners	LW	25	36	41	77	33	13	5	40	38	167	47	94	21.56%	19	616	24.65	9	14	23	19	57	1	0	1	3	55	6	1	65.66%	198	31	22	5	2.50	0	2	0	0	1	6	5	3
3	Andre Burakovsky	Distraction (MRS)	LW	37	28	38	66	17	18	0	39	32	159	47	106	17.61%	24	648	17.54	6	8	14	12	54	0	0	0	0	15	3	1	67.50%	40	49	26	0	2.03	2	2	0	0	0	5	0	3
4	Matthew Peca	Distraction (MRS)	C	43	24	35	59	19	6	0	53	58	147	64	92	16.33%	21	727	16.91	8	8	16	11	60	0	0	0	1	3	2	0	70.32%	721	38	22	0	1.62	0	0	0	0	0	0	5	2
5	J.T. Compher	Distraction (MRS)	LW	43	23	33	56	21	2	0	39	30	154	49	70	14.94%	14	600	13.96	3	1	4	4	15	0	1	1	2	12	0	0	68.18%	22	35	27	0	1.87	0	0	0	0	0	2	3	4
6	Oliver Bjorkstrand	Mariners	LW/RW	30	20	29	49	13	2	0	29	21	88	27	47	22.73%	18	545	18.18	4	9	13	9	47	0	0	0	4	27	0	1	55.32%	47	18	19	1	1.80	1	1	0	0	0	2	2	3
7	Brendan Leipsic	Distraction (MRS)	LW	43	2	37	39	21	7	5	22	25	69	32	34	2.90%	42	708	16.48	2	2	4	3	33	0	0	0	0	0	0	1	0.00%	0	16	44	0	1.10	0	0	0	0	1	0	2	3
8	Luke Glendening	Mariners	RW	18	16	22	38	27	18	10	21	14	69	22	51	23.19%	15	429	23.84	5	6	11	7	37	0	1	1	1	36	4	1	73.53%	34	7	12	2	1.77	1	2	1	1	0	1	5	0
9	Jacob De La Rose	Distraction (MRS)	LW	37	15	17	32	7	4	0	58	27	103	36	72	14.56%	16	567	15.34	0	0	0	0	0	0	0	0	0	0	2	1	67.10%	231	20	24	1	1.13	0	0	0	0	0	1	2	2
10	Shea Theodore	Distraction (MRS)	D	15	4	17	21	12	9	5	17	15	41	19	14	9.76%	15	405	27.01	3	4	7	7	41	0	0	0	0	22	0	0	0.00%	0	13	29	0	1.04	1	1	1	0	0	0	1	2
11	Brett Ritchie	Distraction (MRS)	RW	19	8	9	17	11	4	0	18	16	41	13	19	19.51%	7	269	14.18	0	1	1	1	6	0	0	0	0	1	2	0	83.33%	6	8	8	0	1.26	0	0	0	0	0	0	1	2
12	Chris Wideman	Distraction (MRS)	D	6	2	4	6	8	5	5	10	6	9	3	2	22.22%	12	145	24.20	1	2	3	1	14	1	0	1	1	11	0	0	0.00%	0	5	8	0	0.83	0	0	0	0	1	0	0	1
Team Total or Average				359	231	359	590	225	105	35	401	360	1311	445	765	17.62%	228	6592	18.36	60	88	148	111	478	3	3	6	14	207	22	7	69.73%	2197	285	277	13	1.79	5	10	2	1	4	31	31	32

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	Alex Stalock	Distraction (MRS)	16	14	1	1	0.909	2.72	969	2	1	44	481	242	0	1	0.500	10	16	0	0	1	0
Team Total or Average			16	14	1	1	0.909	2.72	969	2	1	44	481	242	0	1	0.500	10	16	0	0	1	0

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	Available For Trade	Force Waivers	Contract	Status	Type	Current Salary	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap
Alex Stalock	Distraction (MRS)	G	31	1988-03-22 09:26:20	No	190 Lbs	6 ft0	Yes	No	No	2	UFA	Pro & Farm	1,000,000$	0$	0$	No
Andre Burakovsky	Distraction (MRS)	LW	23	1996-03-22 09:26:19	No	205 Lbs	6 ft3	No	No	No	1	ELC	Pro & Farm	2,250,000$	0$	0$	No
Brendan Leipsic	Distraction (MRS)	LW	25	1994-05-19 10:23:05	Yes	179 Lbs	5 ft10	No	No	No	2	ELC	Pro & Farm	650,000$	0$	0$	No
Brett Ritchie	Distraction (MRS)	RW	25	1994-03-22 21:26:19	Yes	220 Lbs	6 ft3	No	No	No	2	ELC	Pro & Farm	1,750,000$	0$	0$	No
Chris Wideman	Distraction (MRS)	D	28	1991-03-23 03:26:19	Yes	180 Lbs	5 ft10	No	No	No	1	UFA	Pro & Farm	1,262,000$	0$	0$	No
J.T. Compher	Distraction (MRS)	LW	24	1995-04-08 10:32:11	Yes	193 Lbs	6 ft0	No	No	No	2	ELC	Pro & Farm	1,000,000$	0$	0$	No
Jacob De La Rose	Distraction (MRS)	LW	23	1996-03-22 09:26:19	Yes	214 Lbs	6 ft3	No	No	No	1	ELC	Pro & Farm	925,000$	0$	0$	No
Matthew Peca	Distraction (MRS)	C	26	1993-04-27 16:53:37	Yes	182 Lbs	5 ft9	Yes	No	No	1	ELC	Pro & Farm	650,000$	0$	0$	No
Shea Theodore	Distraction (MRS)	D	23	1996-03-22 09:26:19	Yes	195 Lbs	6 ft2	No	No	No	1	ELC	Pro & Farm	863,000$	0$	0$	No
Victor Rask	Distraction (MRS)	C	25	1994-03-22 21:26:19	No	200 Lbs	6 ft2	Yes	No	No	5	ELC	Pro & Farm	2,500,000$	0$	0$	No

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
10	25.30	196 Lbs	6 ft1	1.80	1,285,000$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1		Victor Rask		40	1	2	2
2	Andre Burakovsky	Matthew Peca		30	1	2	2
3	J.T. Compher	Jacob De La Rose		20	1	2	2
4	Jacob De La Rose			10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			40	1	2	2
2	Brendan Leipsic		30	1	2	2
3			20	1	2	2
4			10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1		Victor Rask		60	1	2	2
2	Andre Burakovsky	Matthew Peca		40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2	Brendan Leipsic		40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1			60	1	2	2
2	Andre Burakovsky	Victor Rask	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1		60	1	2	2			60	1	2	2
2		40	1	2	2			40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1			60	1	2	2
2	Andre Burakovsky	Victor Rask	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
	Victor Rask

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
	Victor Rask

Extra Forwards
Normal	PowerPlay	Penalty Kill
J.T. Compher, ,	J.T. Compher,

Extra Defensemen
Normal	PowerPlay	Penalty Kill
, ,		,

Penalty Shots
, , Andre Burakovsky, Victor Rask,

Goalie
#1 : , #2 :

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
1	Chiefs	1	1	0	0	0	0	0	0	8	4	4	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	8	4	4	2	1.000	8	14	22	0	0	77	115	119	7	32	547	522	592	14	35	16	17	19	3	2	66.67%	4	2	50.00%	0	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
2	Cobra	4	4	0	0	0	0	0	0	34	13	21	3	3	0	0	0	0	0	0	26	6	20	1	1	0	0	0	0	0	0	8	7	1	8	1.000	34	57	91	0	1	77	115	119	7	144	547	522	592	14	87	31	40	66	17	10	58.82%	10	3	70.00%	0	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
3	Cyclone	3	2	0	0	0	1	0	0	21	14	7	0	0	0	0	0	0	0	0	0	0	0	3	2	0	0	0	1	0	0	21	14	7	5	0.833	21	35	56	0	0	77	115	119	7	100	547	522	592	14	100	33	12	51	10	7	70.00%	6	2	66.67%	1	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
4	Destroyers	3	2	1	0	0	0	0	0	14	17	-3	2	1	1	0	0	0	0	0	7	11	-4	1	1	0	0	0	0	0	0	7	6	1	4	0.667	14	27	41	0	0	77	115	119	7	137	547	522	592	14	117	44	34	38	8	2	25.00%	12	6	50.00%	0	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
5	Dynamos	2	1	0	0	1	0	0	0	15	11	4	0	0	0	0	0	0	0	0	0	0	0	2	1	0	0	1	0	0	0	15	11	4	4	1.000	15	28	43	0	0	77	115	119	7	88	547	522	592	14	55	14	10	29	10	5	50.00%	5	1	80.00%	0	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
6	Falcons	2	2	0	0	0	0	0	0	11	5	6	2	2	0	0	0	0	0	0	11	5	6	0	0	0	0	0	0	0	0	0	0	0	4	1.000	11	18	29	0	0	77	115	119	7	64	547	522	592	14	43	18	2	43	4	1	25.00%	1	1	0.00%	0	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
7	Intrepides	1	1	0	0	0	0	0	0	7	2	5	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	7	2	5	2	1.000	7	10	17	0	0	77	115	119	7	35	547	522	592	14	27	5	18	20	4	2	50.00%	4	2	50.00%	1	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
8	L'Euphorie	3	2	1	0	0	0	0	0	18	12	6	2	1	1	0	0	0	0	0	11	10	1	1	1	0	0	0	0	0	0	7	2	5	4	0.667	18	30	48	0	0	77	115	119	7	97	547	522	592	14	112	44	14	42	6	4	66.67%	7	5	28.57%	0	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
9	Monkeys	2	0	2	0	0	0	0	0	8	16	-8	1	0	1	0	0	0	0	0	4	9	-5	1	0	1	0	0	0	0	0	4	7	-3	0	0.000	8	12	20	0	0	77	115	119	7	80	547	522	592	14	86	25	16	34	6	2	33.33%	8	5	37.50%	0	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
10	Monsters	1	0	0	0	0	0	0	1	1	2	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	1	2	-1	1	0.500	1	2	3	0	0	77	115	119	7	20	547	522	592	14	18	6	2	18	1	0	0.00%	1	0	100.00%	0	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
11	Patriotes	1	1	0	0	0	0	0	0	8	2	6	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	8	2	6	2	1.000	8	15	23	0	0	77	115	119	7	39	547	522	592	14	27	6	11	17	5	1	20.00%	3	0	100.00%	0	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
12	Prospects	2	1	1	0	0	0	0	0	7	6	1	2	1	1	0	0	0	0	0	7	6	1	0	0	0	0	0	0	0	0	0	0	0	2	0.500	7	12	19	1	0	77	115	119	7	51	547	522	592	14	74	28	16	17	4	1	25.00%	8	4	50.00%	1	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
13	Senators	2	2	0	0	0	0	0	0	16	7	9	1	1	0	0	0	0	0	0	8	3	5	1	1	0	0	0	0	0	0	8	4	4	4	1.000	16	25	41	0	0	77	115	119	7	80	547	522	592	14	59	12	4	31	8	5	62.50%	2	0	100.00%	0	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
14	Sharks	4	1	2	0	0	0	1	0	26	31	-5	2	1	1	0	0	0	0	0	16	16	0	2	0	1	0	0	0	1	0	10	15	-5	4	0.500	26	47	73	0	0	77	115	119	7	156	547	522	592	14	157	43	28	57	14	7	50.00%	14	8	42.86%	0	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
15	Sheriefs	1	1	0	0	0	0	0	0	12	3	9	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	12	3	9	2	1.000	12	22	34	0	0	77	115	119	7	48	547	522	592	14	23	10	4	15	5	2	40.00%	2	0	100.00%	0	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
	Total	44	30	9	0	2	1	1	1	314	214	100	21	14	6	0	1	0	0	0	145	99	46	23	16	3	0	1	1	1	1	169	115	54	68	0.773	314	533	847	1	1	77	115	119	7	1665	547	522	592	14	1494	489	309	669	156	82	52.56%	120	52	56.67%	4	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
17	Viking	4	2	2	0	0	0	0	0	29	29	0	2	1	1	0	0	0	0	0	15	13	2	2	1	1	0	0	0	0	0	14	16	-2	4	0.500	29	49	78	0	0	77	115	119	7	137	547	522	592	14	189	58	29	56	13	7	53.85%	12	6	50.00%	0	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
18	Warriors	3	3	0	0	0	0	0	0	35	14	21	1	1	0	0	0	0	0	0	12	4	8	2	2	0	0	0	0	0	0	23	10	13	6	1.000	35	57	92	0	0	77	115	119	7	142	547	522	592	14	110	26	21	36	18	14	77.78%	8	4	50.00%	0	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
19	Youngblood	5	4	0	0	1	0	0	0	44	26	18	3	2	0	0	1	0	0	0	28	16	12	2	2	0	0	0	0	0	0	16	10	6	10	1.000	44	73	117	0	0	77	115	119	7	215	547	522	592	14	175	70	31	80	20	10	50.00%	13	3	76.92%	1	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
	_Since Last GM Reset	44	30	9	0	2	1	1	1	314	214	100	21	14	6	0	1	0	0	0	145	99	46	23	16	3	0	1	1	1	1	169	115	54	68	0.773	314	533	847	1	1	77	115	119	7	1665	547	522	592	14	1494	489	309	669	156	82	52.56%	120	52	56.67%	4	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
	_Vs Conference	24	16	6	0	1	0	1	0	177	122	55	14	9	4	0	1	0	0	0	103	67	36	10	7	2	0	0	0	1	0	74	55	19	36	0.750	177	300	477	1	1	77	115	119	7	883	547	522	592	14	844	289	180	353	83	43	51.81%	70	31	55.71%	3	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
	_Vs Division	11	10	0	0	1	0	0	0	97	44	53	6	5	0	0	1	0	0	0	54	22	32	5	5	0	0	0	0	0	0	43	22	21	22	1.000	97	162	259	0	1	77	115	119	7	442	547	522	592	14	312	116	93	181	46	24	52.17%	29	8	72.41%	2	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
44	68	W4	314	533	847	1665	1494	489	309	669	1	1

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
44	30	9	2	1	1	1	314	214

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
21	14	6	1	0	0	0	145	99

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
23	16	3	1	1	1	1	169	115

Last 10 Games
W	L	OTW	OTL	SOW	SOL
6	2	1	1	0	0

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
156	82	52.56%	120	52	56.67%	4

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
547	522	592	14	77	115	119	7

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
541	787	68.74%	479	750	63.87%	658	984	66.87%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
1032	630	882	335	742	414

Last Played Games 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

Day	Game	Visitor Team	Score	Home Team	Score	ST	OT	SO	Link
1 - 2019-05-06	6	Distraction	6	Cyclone	3	W			BoxScore
2 - 2019-05-07	15	Distraction	7	Intrepides	2	W			BoxScore
4 - 2019-05-09	21	Cobra	0	Distraction	10	W			BoxScore
6 - 2019-05-11	37	Sharks	4	Distraction	6	W			BoxScore
8 - 2019-05-13	49	Viking	9	Distraction	7	L			BoxScore
10 - 2019-05-15	59	Falcons	4	Distraction	5	W			BoxScore
13 - 2019-05-18	70	Distraction	10	Warriors	3	W			BoxScore
15 - 2019-05-20	79	Destroyers	7	Distraction	1	L			BoxScore
16 - 2019-05-21	84	Distraction	12	Sheriefs	3	W			BoxScore
18 - 2019-05-23	98	Distraction	8	Patriotes	2	W			BoxScore
20 - 2019-05-25	103	Distraction	8	Chiefs	4	W			BoxScore
22 - 2019-05-27	115	Youngblood	4	Distraction	9	W			BoxScore
24 - 2019-05-29	128	Distraction	1	Monsters	2	L	X	X	BoxScore
26 - 2019-05-31	132	Cobra	2	Distraction	10	W			BoxScore
28 - 2019-06-02	149	Prospects	3	Distraction	6	W			BoxScore
30 - 2019-06-04	153	Distraction	8	Youngblood	6	W			BoxScore
32 - 2019-06-06	165	Distraction	8	Cyclone	3	W			BoxScore
34 - 2019-06-08	172	Viking	4	Distraction	8	W			BoxScore
36 - 2019-06-10	181	Distraction	5	Sharks	4	W	X	X	BoxScore
38 - 2019-06-12	194	Prospects	3	Distraction	1	L			BoxScore
40 - 2019-06-14	205	Senators	3	Distraction	8	W			BoxScore
42 - 2019-06-16	219	Falcons	1	Distraction	6	W			BoxScore
45 - 2019-06-19	230	L'Euphorie	3	Distraction	6	W			BoxScore
47 - 2019-06-21	236	Distraction	2	Viking	8	L			BoxScore
49 - 2019-06-23	249	Distraction	12	Viking	8	W			BoxScore
50 - 2019-06-24	259	Distraction	7	Dynamos	4	W			BoxScore
52 - 2019-06-26	266	Distraction	5	Sharks	11	L			BoxScore
54 - 2019-06-28	272	Distraction	8	Youngblood	4	W			BoxScore
56 - 2019-06-30	283	Destroyers	4	Distraction	6	W			BoxScore
58 - 2019-07-02	293	Distraction	13	Warriors	7	W			BoxScore
60 - 2019-07-04	303	Monkeys	9	Distraction	4	L			BoxScore
62 - 2019-07-06	313	Warriors	4	Distraction	12	W			BoxScore
65 - 2019-07-09	328	L'Euphorie	7	Distraction	5	L			BoxScore
66 - 2019-07-10	339	Youngblood	7	Distraction	8	W	X		BoxScore
69 - 2019-07-13	349	Distraction	8	Dynamos	7	W	X		BoxScore
70 - 2019-07-14	355	Distraction	8	Cobra	7	W			BoxScore
72 - 2019-07-16	366	Cobra	4	Distraction	6	W			BoxScore
74 - 2019-07-18	370	Distraction	7	Cyclone	8	L	X		BoxScore
76 - 2019-07-20	384	Sharks	12	Distraction	10	L			BoxScore
77 - 2019-07-21	392	Distraction	4	Monkeys	7	L			BoxScore
78 - 2019-07-22	402	Youngblood	5	Distraction	11	W			BoxScore
80 - 2019-07-24	414	Distraction	7	Destroyers	6	W			BoxScore
82 - 2019-07-26	423	Distraction	7	L'Euphorie	2	W			BoxScore
84 - 2019-07-28	429	Distraction	8	Senators	4	W			BoxScore
85 - 2019-07-29	440	Sharks	-	Distraction	-
87 - 2019-07-31	450	Distraction	-	Senators	-
88 - 2019-08-01	460	Sheriefs	-	Distraction	-
90 - 2019-08-03	471	Distraction	-	Sheriefs	-
91 - 2019-08-04	478	Monsters	-	Distraction	-
93 - 2019-08-06	490	Distraction	-	Prospects	-
95 - 2019-08-08	499	Sheriefs	-	Distraction	-
97 - 2019-08-10	510	Senators	-	Distraction	-
99 - 2019-08-12	522	Distraction	-	Chiefs	-
100 - 2019-08-13	530	Distraction	-	Prospects	-
101 - 2019-08-14	537	Cyclone	-	Distraction	-
103 - 2019-08-16	546	Distraction	-	Destroyers	-
104 - 2019-08-17	557	Chiefs	-	Distraction	-
106 - 2019-08-19	568	Distraction	-	L'Euphorie	-
108 - 2019-08-21	578	Wildcats	-	Distraction	-
109 - 2019-08-22	586	Distraction	-	Sheriefs	-
111 - 2019-08-24	595	Distraction	-	Monsters	-
112 - 2019-08-25	600	Chiefs	-	Distraction	-
114 - 2019-08-27	615	Monsters	-	Distraction	-
116 - 2019-08-29	628	Distraction	-	Patriotes	-
117 - 2019-08-30	635	Patriotes	-	Distraction	-
119 - 2019-09-01	650	Distraction	-	Cobra	-
120 - 2019-09-02	657	Distraction	-	Monkeys	-
121 - 2019-09-03	663	Cyclone	-	Distraction	-
123 - 2019-09-05	678	Intrepides	-	Distraction	-
125 - 2019-09-07	692	Distraction	-	Intrepides	-
126 - 2019-09-08	699	Intrepides	-	Distraction	-
127 - 2019-09-09	706	Distraction	-	Falcons	-
128 - 2019-09-10	717	Wildcats	-	Distraction	-
130 - 2019-09-12	733	Patriotes	-	Distraction	-
Trade Deadline --- Trades can’t be done after this day is simulated!
133 - 2019-09-15	746	Warriors	-	Distraction	-
134 - 2019-09-16	751	Distraction	-	Intrepides	-
135 - 2019-09-17	760	Distraction	-	Wildcats	-
138 - 2019-09-20	773	Monkeys	-	Distraction	-
139 - 2019-09-21	783	Distraction	-	Falcons	-
140 - 2019-09-22	790	Distraction	-	Wildcats	-
141 - 2019-09-23	797	Dynamos	-	Distraction	-
144 - 2019-09-26	814	Dynamos	-	Distraction	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	35	15
Attendance	0	0
Attendance PCT	0.00%	0.00%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
20	0 - 0.00%	0$	0$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
1,231,595$	1,285,000$	1,198,700$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
8,801$	915,141$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	62	12,568$	779,216$

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
2018	44	30	9	0	2	1	1	1	314	214	100	21	14	6	0	1	0	0	0	145	99	46	23	16	3	0	1	1	1	1	169	115	54	68	314	533	847	1	1	77	115	119	7	1665	547	522	592	14	1494	489	309	669	156	82	52.56%	120	52	56.67%	4	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
Total Regular Season	44	30	9	0	2	1	1	1	314	214	100	21	14	6	0	1	0	0	0	145	99	46	23	16	3	0	1	1	1	1	169	115	54	68	314	533	847	1	1	77	115	119	7	1665	547	522	592	14	1494	489	309	669	156	82	52.56%	120	52	56.67%	4	541	787	68.74%	479	750	63.87%	658	984	66.87%	1032	630	882	335	742	414
Playoff
2017	19	14	5	0	0	0	0	0	104	74	30	10	6	4	0	0	0	0	0	52	46	6	9	8	1	0	0	0	0	0	52	28	24	28	104	190	294	0	0	17	39	46	2	792	225	278	279	10	626	194	279	390	67	34	50.75%	62	17	72.58%	6	129	431	29.93%	123	369	33.33%	128	385	33.25%	430	264	404	169	322	153
Total Playoff	19	14	5	0	0	0	0	0	104	74	30	10	6	4	0	0	0	0	0	52	46	6	9	8	1	0	0	0	0	0	52	28	24	28	104	190	294	0	0	17	39	46	2	792	225	278	279	10	626	194	279	390	67	34	50.75%	62	17	72.58%	6	129	431	29.93%	123	369	33.33%	128	385	33.25%	430	264	404	169	322	153