Columbus
Home
Roster
Scoring
Players Info
Lines
Team Stats
Schedule
Finance

Game Center
	Monsters 6-7-0, 12pts	2	FINAL	4	Spiders 11-9-0, 22pts

Team Stats
L2	Streak	OTL1
3-3-0	Home Record	6-5-0
3-4-0	Away Record	5-4-0
5-5-0	Last 10 Games	5-3-2
2.62	Goals Per Game	3.10
2.62	Goals Against Per Game	2.80
20.93%	Power Play Percentage	20.55%
78.57%	Penalty Kill Percentage	83.05%

Spiders
11-9-0, 22pts

FINAL

Monsters
6-7-0, 12pts

Team Stats
OTL1	Streak	L2
6-5-0	Home Record	3-3-0
5-4-0	Away Record	3-4-0
5-3-2	Last 10 Games	5-5-0
3.10	Goals Per Game	2.62
2.80	Goals Against Per Game	2.62
20.55%	Power Play Percentage	20.93%
83.05%	Penalty Kill Percentage	78.57%

Team Leaders
	Goals Sheldon Dries 6	Assists Benoit-Olivier Groulx 10

	Points Benoit-Olivier Groulx 14	Plus/Minus Benoit-Olivier Groulx 5

	Wins Mads Sogaard 6	Save Percentage Mads Sogaard 0.923

Team Stats
Goals For 34 2.62 GFG	Shots For 472 36.31 Avg	Power Play Percentage 20.9% 9 GF	Offensive Zone Start 42.0%
Goals Against 34 2.62 GAA	Shots Against 428 32.92 Avg	Penalty Kill Percentage 78.6%% 9 GA	Defensive Zone Start 41.0%

Team Info
	General Manager	Benoit Toupin
	Division	Nord-Est
	Conference	Est
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Capacity	3,000
	Attendance	3,000
	Season Tickets	300
Roster Info
	Pro Team	25
	Farm Team	20
	Contract Limit	45 / 50
	Prospects	16

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	Age	Contract	Salary Average
1	Wayne Simmonds		X	X		100.00	86	94	64	72	73	54	81	56	44	62	58	60	61	84	87	0	50	62	0	33	4	750,000$
2	Sheldon Dries	X	X			100.00	71	42	99	74	64	56	69	68	42	59	71	65	25	50	50	0	50	61	0	27	3	700,000$
3	Brandon Pirri	X	X	X		100.00	63	68	61	67	68	53	51	65	79	52	69	66	68	67	68	0	50	60	0	30	2	650,000$
4	Benoit-Olivier Groulx (R)	X				100.00	76	44	96	67	73	59	76	58	60	60	57	77	25	45	45	0	50	60	0	21	3	822,500$
5	Julien Gauthier			X		100.00	85	46	94	77	84	56	65	60	34	58	57	61	25	57	57	0	50	60	0	23	2	990,900$
6	Luke Philp	X				100.00	73	65	91	63	65	64	65	62	78	58	62	63	59	44	44	0	50	59	0	25	1	600,000$
7	Cole Fonstad (R)	X	X			100.00	70	60	93	70	60	50	49	57	71	52	58	60	55	44	44	0	50	55	0	21	1	900,000$
8	Dominik Bokk (R)		X	X		100.00	76	69	91	67	69	52	53	51	50	50	47	62	45	44	44	0	50	54	0	21	3	863,333$
9	Kasper Bjorkqvist		X	X		100.00	76	72	84	64	72	58	60	51	50	43	54	62	51	44	44	0	50	54	0	24	3	800,000$
10	Matt Kiersted				X	100.00	75	43	93	71	67	64	66	57	25	49	50	78	25	45	45	0	50	62	0	23	1	858,750$
11	Kurtis MacDermid				X	100.00	83	99	59	69	90	46	69	55	25	44	48	67	25	60	60	0	50	61	0	27	2	650,000$
12	Nils Lundkvist (R)				X	100.00	67	42	99	76	66	64	58	64	25	50	48	66	25	46	46	0	50	60	0	21	3	925,000$
13	Connor Mackey				X	100.00	68	72	58	71	72	67	70	55	25	54	42	59	40	44	44	0	50	58	0	25	3	925,000$
14	Chase Priskie				X	100.00	73	68	85	65	68	61	63	57	25	50	49	62	47	44	44	0	50	57	0	25	2	675,000$
15	Jake Christiansen (R)				X	100.00	76	44	99	66	72	54	62	54	25	39	54	64	25	44	44	0	50	57	0	22	2	925,000$
16	Keaton Middleton				X	100.00	81	91	59	61	91	55	58	47	25	38	40	63	38	44	44	0	50	56	0	23	1	650,000$
17	Adam Ginning (R)				X	100.00	58	58	70	61	77	58	83	38	25	33	35	66	38	50	52	0	50	56	0	21	3	825,000$
18	Wyatte Wylie (R)				X	100.00	75	70	88	63	70	59	62	48	25	39	41	61	39	44	44	0	50	55	0	21	3	820,833$
Scratches
1	Tim Soderlund		X	X		100.00	72	64	98	64	58	53	49	52	54	51	45	63	41	44	44	0	50	53	0	23	2	825,834$
2	Matt Filipe	X	X			100.00	73	72	75	60	72	56	58	51	64	47	50	60	48	44	44	0	50	53	0	23	1	600,000$
3	Brandon Coe (R)			X		100.00	75	74	88	62	74	55	57	48	49	48	43	62	43	44	44	0	50	52	0	19	3	650,000$
4	Chad Yetman (R)	X		X		100.00	72	64	92	64	64	45	44	49	61	47	46	59	44	44	44	0	50	51	0	21	3	560,000$
5	Drew Helleson (R)				X	100.00	78	73	91	69	73	38	37	45	25	36	39	61	37	44	44	0	50	53	0	20	4	925,000$

	TEAM AVERAGE					100.00	74	65	84	67	71	56	61	54	43	49	51	64	40	49	49	0	50	57

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	Age	Contract	Salary Average
1	Mads Sogaard (R)	100.00	54	42	53	86	58	54	52	58	56	55	30	44	44	0	50	56	0	20	2	925,000$
2	Jakub Skarek (R)	100.00	48	44	55	81	49	49	50	54	50	50	30	44	44	0	50	52	0	21	3	764,167$
Scratches

	TEAM AVERAGE	100.00	51	43	54	84	54	52	51	56	53	53	30	44	44	0	50	54

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary

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	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	FO%	FOT	EG	HT	P/20	S1	S2	S3
1	Benoit-Olivier Groulx	Monsters (Clb)	C	13	4	10	14	5	4	15	43	54	20	47	7.41%	2	245	18.90	1	4	5	13	34	0	0	0	0	39	1	48.10%	368	0	0	1.14	1	2	0
2	Sheldon Dries	Monsters (Clb)	C/LW	13	6	4	10	-1	0	5	32	51	15	39	11.76%	7	272	20.94	4	0	4	13	36	0	0	0	1	37	1	33.74%	326	0	1	0.73	1	0	0
3	Jake Christiansen	Monsters (Clb)	D	13	5	5	10	4	14	20	8	19	12	13	26.32%	19	272	21.00	3	1	4	8	34	0	0	0	0	28	2	0.00%	0	0	0	0.73	0	0	2
4	Brandon Pirri	Monsters (Clb)	C/LW/RW	13	5	4	9	4	0	16	25	52	19	43	9.62%	5	230	17.74	0	1	1	7	35	0	0	0	2	25	2	68.63%	51	1	0	0.78	0	0	2
5	Matt Kiersted	Monsters (Clb)	D	13	2	5	7	-5	0	7	20	32	13	20	6.25%	25	292	22.51	1	0	1	20	37	0	0	0	0	35	0	0.00%	0	0	0	0.48	0	0	0
6	Cole Fonstad	Monsters (Clb)	C/LW	13	2	4	6	-3	4	12	12	28	9	13	7.14%	3	175	13.48	0	0	0	0	4	1	0	1	1	15	0	46.43%	28	0	0	0.68	0	1	0
7	Luke Philp	Monsters (Clb)	C	13	2	4	6	-4	8	3	17	30	8	23	6.67%	1	158	12.21	0	0	0	0	2	0	0	0	0	0	0	61.02%	177	0	0	0.76	1	0	0
8	Connor Mackey	Monsters (Clb)	D	13	0	5	5	2	8	27	9	17	5	8	0.00%	8	251	19.36	0	2	2	10	34	0	1	1	0	15	0	0.00%	0	0	0	0.40	0	0	0
9	Dominik Bokk	Monsters (Clb)	LW/RW	13	2	3	5	4	6	14	11	24	3	13	8.33%	0	203	15.63	0	1	1	7	34	0	0	0	0	0	0	35.71%	14	0	0	0.49	0	1	0
10	Julien Gauthier	Monsters (Clb)	RW	13	1	4	5	-1	6	17	20	44	13	33	2.27%	2	252	19.46	0	1	1	6	36	0	0	0	0	18	0	23.08%	13	0	0	0.40	0	0	0
11	Nils Lundkvist	Monsters (Clb)	D	13	0	5	5	2	6	9	16	16	5	7	0.00%	12	250	19.24	0	0	0	3	3	0	0	0	0	31	0	0.00%	0	0	0	0.40	0	0	0
12	Wayne Simmonds	Monsters (Clb)	LW/RW	13	2	1	3	-1	10	61	10	27	9	19	7.41%	4	234	18.01	0	1	1	6	36	0	0	0	0	0	0	41.67%	24	0	0	0.26	0	1	0
13	Chad Yetman	Monsters (Clb)	C/RW	13	1	1	2	0	2	5	7	10	4	9	10.00%	0	116	9.00	0	0	0	0	2	0	0	0	0	3	0	50.00%	6	0	0	0.34	0	0	1
14	Tim Soderlund	Monsters (Clb)	LW/RW	13	1	1	2	0	2	5	11	14	2	14	7.14%	2	113	8.72	0	0	0	0	0	0	0	0	0	2	0	40.00%	5	0	0	0.35	0	0	0
15	Kurtis MacDermid	Monsters (Clb)	D	13	0	2	2	-3	14	43	6	11	5	9	0.00%	15	281	21.65	0	1	1	3	36	0	0	0	0	26	0	0.00%	0	0	0	0.14	0	0	0
16	Kasper Bjorkqvist	Monsters (Clb)	LW/RW	13	1	0	1	-4	4	20	7	21	6	10	4.76%	2	155	11.98	0	0	0	0	0	0	0	0	0	0	0	33.33%	6	0	0	0.13	0	0	0
17	Matt Filipe	Monsters (Clb)	C/LW	13	0	0	0	0	0	16	10	13	2	9	0.00%	1	110	8.52	0	0	0	0	0	0	0	0	0	0	0	51.56%	128	0	0	0.00%	0	0	0
18	Adam Ginning	Monsters (Clb)	D	13	0	0	0	0	0	17	4	9	0	6	0.00%	15	206	15.87	0	0	0	0	0	0	0	0	0	2	0	0.00%	0	0	0	0.00%	0	0	0
Team Total or Average				234	34	58	92	-1	88	312	268	472	150	335	7.20%	123	3824	16.34	9	12	21	96	370	1	1	2	4	282	6	46.60%	1146	1	1	0.48	3	5	5

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	Mads Sogaard	Monsters (Clb)	13	6	7	0	0.923	2.54	779	0	1	33	427	0	0	1	0.00%	0	13	0	2	2	0
Team Total or Average			13	6	7	0	0.923	2.54	779	0	1	33	427	0	0	1		0	13	0	2	2	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	Type	Current Salary	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Salary Year 2	Salary Year 3	Salary Year 4	Link
Adam Ginning	Monsters (Clb)	D	21	2000-01-13	Yes	206 Lbs	6 ft4	No	No	No	3	Pro & Farm	825,000$	0$	0$	No	825,000$	825,000$		Link
Benoit-Olivier Groulx	Monsters (Clb)	C	21	2000-02-05	Yes	195 Lbs	6 ft2	No	No	No	3	Pro & Farm	822,500$	0$	0$	No	822,500$	822,500$		Link
Brandon Coe	Monsters (Clb)	RW	19	2001-12-01	Yes	190 Lbs	6 ft4	No	No	No	3	Pro & Farm	650,000$	0$	0$	No	650,000$	650,000$		Link
Brandon Pirri (1 Way Contract)	Monsters (Clb)	C/LW/RW	30	1991-04-10	No	186 Lbs	6 ft0	Yes	No	Yes	2	Pro & Farm	650,000$	0$	0$	No	650,000$			Link
Chad Yetman	Monsters (Clb)	C/RW	21	2000-02-18	Yes	179 Lbs	5 ft11	No	No	No	3	Pro & Farm	560,000$	0$	0$	No	560,000$	560,000$		Link
Chase Priskie	Monsters (Clb)	D	25	1996-03-18	No	185 Lbs	6 ft0	No	No	Yes	2	Pro & Farm	675,000$	0$	0$	No	675,000$			Link
Cole Fonstad	Monsters (Clb)	C/LW	21	2000-04-24	Yes	165 Lbs	5 ft10	Yes	No	No	1	Pro & Farm	900,000$	0$	0$	No				Link
Connor Mackey	Monsters (Clb)	D	25	1996-09-12	No	190 Lbs	6 ft2	No	No	Yes	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$		Link
Dominik Bokk	Monsters (Clb)	LW/RW	21	2000-02-03	Yes	181 Lbs	6 ft2	No	No	No	3	Pro & Farm	863,333$	0$	0$	No	863,333$	863,333$		Link
Drew Helleson	Monsters (Clb)	D	20	2001-03-26	Yes	190 Lbs	6 ft3	No	No	No	4	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$	925,000$	Link
Jake Christiansen	Monsters (Clb)	D	22	1999-09-12	Yes	195 Lbs	6 ft1	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$			Link
Jakub Skarek	Monsters (Clb)	G	21	1999-11-10	Yes	202 Lbs	6 ft3	No	No	No	3	Pro & Farm	764,167$	0$	0$	No	764,167$	764,167$		Link
Julien Gauthier	Monsters (Clb)	RW	23	1997-10-15	No	227 Lbs	6 ft4	No	No	No	2	Pro & Farm	990,900$	0$	0$	No	990,900$			Link
Kasper Bjorkqvist	Monsters (Clb)	LW/RW	24	1997-07-10	No	198 Lbs	6 ft1	No	No	Yes	3	Pro & Farm	800,000$	0$	0$	No	800,000$	800,000$		Link
Keaton Middleton	Monsters (Clb)	D	23	1998-02-10	No	240 Lbs	6 ft6	No	No	No	1	Pro & Farm	650,000$	0$	0$	No				Link
Kurtis MacDermid (1 Way Contract)	Monsters (Clb)	D	27	1994-03-25	No	233 Lbs	6 ft5	No	No	Yes	2	Pro & Farm	650,000$	0$	0$	No	650,000$			Link
Luke Philp	Monsters (Clb)	C	25	1995-11-06	No	181 Lbs	5 ft10	No	No	Yes	1	Pro & Farm	600,000$	0$	0$	No				Link
Mads Sogaard	Monsters (Clb)	G	20	2000-12-13	Yes	201 Lbs	6 ft7	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$			Link
Matt Filipe	Monsters (Clb)	C/LW	23	1997-12-31	No	193 Lbs	6 ft2	No	No	No	1	Pro & Farm	600,000$	0$	0$	No				Link
Matt Kiersted	Monsters (Clb)	D	23	1998-04-14	No	181 Lbs	6 ft0	No	No	No	1	Pro & Farm	858,750$	0$	0$	No				Link
Nils Lundkvist	Monsters (Clb)	D	21	2000-07-27	Yes	187 Lbs	5 ft10	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$		Link
Sheldon Dries (1 Way Contract)	Monsters (Clb)	C/LW	27	1994-04-23	No	180 Lbs	5 ft9	No	No	Yes	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$		Link
Tim Soderlund	Monsters (Clb)	LW/RW	23	1998-01-23	No	163 Lbs	5 ft9	No	No	No	2	Pro & Farm	825,834$	0$	0$	No	825,834$			Link
Wayne Simmonds (1 Way Contract)	Monsters (Clb)	LW/RW	33	1988-08-26	No	185 Lbs	6 ft2	Yes	No	Yes	4	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$	750,000$	Link
Wyatte Wylie	Monsters (Clb)	D	21	1999-11-02	Yes	190 Lbs	6 ft0	No	No	No	3	Pro & Farm	820,833$	0$	0$	No	820,833$	820,833$		Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
25	23.20	193 Lbs	6 ft1	2.40	783,253$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Wayne Simmonds	Sheldon Dries	Brandon Pirri	40	1	2	2
2	Cole Fonstad	Benoit-Olivier Groulx	Julien Gauthier	30	1	2	2
3	Dominik Bokk	Luke Philp	Kasper Bjorkqvist	20	1	2	2
4	Sheldon Dries	Wayne Simmonds	Brandon Pirri	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Matt Kiersted	Kurtis MacDermid	40	1	2	2
2	Nils Lundkvist	Connor Mackey	30	1	2	2
3	Jake Christiansen	Chase Priskie	20	1	2	2
4	Adam Ginning	Keaton Middleton	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Wayne Simmonds	Sheldon Dries	Brandon Pirri	60	1	2	2
2	Cole Fonstad	Benoit-Olivier Groulx	Julien Gauthier	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Matt Kiersted	Kurtis MacDermid	60	1	2	2
2	Nils Lundkvist	Connor Mackey	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Wayne Simmonds	Sheldon Dries	60	1	2	2
2	Brandon Pirri	Benoit-Olivier Groulx	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Matt Kiersted	Kurtis MacDermid	60	1	2	2
2	Nils Lundkvist	Connor Mackey	40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Wayne Simmonds	60	1	2	2	Matt Kiersted	Kurtis MacDermid	60	1	2	2
2	Sheldon Dries	40	1	2	2	Nils Lundkvist	Connor Mackey	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Wayne Simmonds	Sheldon Dries	60	1	2	2
2	Brandon Pirri	Benoit-Olivier Groulx	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Matt Kiersted	Kurtis MacDermid	60	1	2	2
2	Nils Lundkvist	Connor Mackey	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Wayne Simmonds	Sheldon Dries	Brandon Pirri	Matt Kiersted	Kurtis MacDermid

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Wayne Simmonds	Sheldon Dries	Brandon Pirri	Matt Kiersted	Kurtis MacDermid

Extra Forwards
Normal	PowerPlay	Penalty Kill
Luke Philp, Dominik Bokk, Kasper Bjorkqvist	Luke Philp, Dominik Bokk	Kasper Bjorkqvist

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Wyatte Wylie, Jake Christiansen, Chase Priskie	Wyatte Wylie	Jake Christiansen, Chase Priskie

Penalty Shots
Wayne Simmonds, Sheldon Dries, Brandon Pirri, Benoit-Olivier Groulx, Julien Gauthier

Goalie
#1 : Mads Sogaard, #2 : Jakub Skarek

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	Sound Tigers	7	4	3	0	0	0	0	0	23	18	5	3	2	1	0	0	0	0	0	12	8	4	4	2	2	0	0	0	0	0	11	10	1	8	0.571	23	37	60	1	0	14	11	9	0	271	154	165	153	0	233	72	44	157	24	9	37.50%	21	4	80.95%	1	226	481	46.99%	211	470	44.89%	97	195	49.74%	311	209	295	99	172	86
2	Spiders	6	2	4	0	0	0	0	0	11	16	-5	3	1	2	0	0	0	0	0	5	8	-3	3	1	2	0	0	0	0	0	6	8	-2	4	0.333	11	21	32	0	1	14	11	9	0	201	154	165	153	0	195	51	44	155	19	0	0.00%	21	5	76.19%	0	226	481	46.99%	211	470	44.89%	97	195	49.74%	311	209	295	99	172	86
	Total	13	6	7	0	0	0	0	0	34	34	0	6	3	3	0	0	0	0	0	17	16	1	7	3	4	0	0	0	0	0	17	18	-1	12	0.462	34	58	92	1	1	14	11	9	0	472	154	165	153	0	428	123	88	312	43	9	20.93%	42	9	78.57%	1	226	481	46.99%	211	470	44.89%	97	195	49.74%	311	209	295	99	172	86
	_Since Last GM Reset	13	6	7	0	0	0	0	0	34	34	0	6	3	3	0	0	0	0	0	17	16	1	7	3	4	0	0	0	0	0	17	18	-1	12	0.462	34	58	92	1	1	14	11	9	0	472	154	165	153	0	428	123	88	312	43	9	20.93%	42	9	78.57%	1	226	481	46.99%	211	470	44.89%	97	195	49.74%	311	209	295	99	172	86
	_Vs Conference	13	6	7	0	0	0	0	0	34	34	0	6	3	3	0	0	0	0	0	17	16	1	7	3	4	0	0	0	0	0	17	18	-1	12	0.462	34	58	92	1	1	14	11	9	0	472	154	165	153	0	428	123	88	312	43	9	20.93%	42	9	78.57%	1	226	481	46.99%	211	470	44.89%	97	195	49.74%	311	209	295	99	172	86
	_Vs Division	13	6	7	0	0	0	0	0	34	34	0	6	3	3	0	0	0	0	0	17	16	1	7	3	4	0	0	0	0	0	17	18	-1	12	0.462	34	58	92	1	1	14	11	9	0	472	154	165	153	0	428	123	88	312	43	9	20.93%	42	9	78.57%	1	226	481	46.99%	211	470	44.89%	97	195	49.74%	311	209	295	99	172	86

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
13	12	L2	34	58	92	472	428	123	88	312	1	1

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
13	6	7	0	0	0	0	34	34

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
6	3	3	0	0	0	0	17	16

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
7	3	4	0	0	0	0	17	18

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

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
43	9	20.93%	42	9	78.57%	1

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
154	165	153	0	14	11	9	0

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
226	481	46.99%	211	470	44.89%	97	195	49.74%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
311	209	295	99	172	86

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	Link
1 - 2023-04-17	4	Monsters	3	Sound Tigers	4	AL	BoxScore
3 - 2023-04-19	12	Monsters	2	Sound Tigers	1	AW	BoxScore
5 - 2023-04-21	20	Sound Tigers	6	Monsters	4	BL	BoxScore
7 - 2023-04-23	28	Sound Tigers	1	Monsters	3	BW	BoxScore
9 - 2023-04-25	36	Monsters	3	Sound Tigers	4	AL	BoxScore
11 - 2023-04-27	44	Sound Tigers	1	Monsters	5	BW	BoxScore
13 - 2023-04-29	52	Monsters	3	Sound Tigers	1	AW	BoxScore
15 - 2023-05-01	57	Monsters	4	Spiders	2	AW	BoxScore
17 - 2023-05-03	61	Monsters	0	Spiders	2	AL	BoxScore
19 - 2023-05-05	65	Spiders	3	Monsters	0	BL	BoxScore
21 - 2023-05-07	69	Spiders	0	Monsters	2	BW	BoxScore
23 - 2023-05-09	73	Monsters	2	Spiders	4	AL	BoxScore
25 - 2023-05-11	77	Spiders	5	Monsters	3	BL	BoxScore

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	2000	1000
Ticket Price	35	15
Attendance	12,000	6,000
Attendance PCT	100.00%	100.00%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
35	3000 - 100.00%	85,000$	510,000$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
0$	1,683,131$	1,683,131$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	0$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	0	0$	0$

Monsters Stat Leaders (Regular Season)

Show or Hide Column

#	Player Name	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS

Monsters Goalies Stat Leaders (Regular Season)

Show or Hide Column

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA

Monsters Career Team Stats

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

Monsters Stat Leaders (Play-Off)

Show or Hide Column

#	Player Name	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS

Monsters Goalies Stat Leaders (Play-Off)

Show or Hide Column

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA

	Monsters
	GP: 13 \| W: 6 \| L: 7 GF: 34 \| GA: 34 \| PP%: 20.93% \| PK%: 78.57% GM : Benoit Toupin \| Morale : 50 \| Team Overall : 57