Association Québécoise de Hockey Simulé

Association Québécoise de Hockey Simulé - Marmots

Home
Main
Pro League
Farm League
League
- Coaches
- Transactions
- Waivers
- Team/GM
- Trade History
- Prospects
- RSS Feed
- Unassigned
  - Players
  - Goalies
- Available For Trade
  - Players
  - Goalies
- Free Agents
  - Players
  - Goalies
History
Team's Link
- Pro Team
  - Conférence Canadienne
  - Conférence Américaine
- Farm Team
  - Conference 1
    - Bandits
    - CoolFm
    - Farmers
    - Goons
    - Grizzlies
    - Hunters
    - Husky
    - Igloos
    - Marlies
    - Marmots
    - Rockets
    - Smirnoff Ice
    - TigersCats
    - Warriors
    - Xpress
  - Conference 2
    - Barracudas
    - Bayou
    - Chiwawa
    - Outlaws
    - Predateurs
    - Raptors
    - Saguenéens
    - Scorpions
    - Snowbirds
    - Spartans
    - Supreme
    - Thugs
    - Twins
    - Vandals
    - Vipers
    - Wolves
Search
Legacy Pages
Help
- Latest STHS Client
- STHS Client Manual

Marmots

GP: 29 | W: 15 | L: 11 | OTL: 3 | P: 33
GF: 108 | GA: 114 | PP%: 26.67% | PK%: 72.50%
GM : Patrick Gagnon | Morale : 90 | Team Overall : 57
Next Games #453 vs CoolFm

Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

London Spartiates
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	Tanner Pearson			X		97.00	68	48	66	80	68	68	40	55	30	56	54	60	67	90	81	0	90	60	0
2	Kristian Reichel (R)	X				96.00	50	45	95	77	66	53	40	47	30	44	50	56	50	84	72	0	90	54	0
3	Mathieu Perreault		X			100.00	50	45	95	77	57	50	40	45	30	40	50	55	50	95	82	0	90	53	0
4	Andrew Poturalski	X				100.00	50	45	95	78	54	50	40	45	30	40	50	55	50	89	76	0	90	53	0
5	Max McCormick			X		99.00	50	45	95	77	58	50	40	45	30	40	50	55	50	91	78	0	90	53	0
6	Alex Formenton		X			98.00	50	45	95	76	70	50	40	45	30	40	50	55	50	84	71	0	90	53	0
7	Vinni Lettieri	X				97.00	50	45	95	78	54	50	40	45	30	40	50	55	50	88	75	0	90	53	0
8	Vitaly Abramov (R)			X		100.00	50	45	95	78	52	50	40	45	30	40	50	55	50	85	72	0	90	52	0
9	Kevin Gravel				X	96.00	68	45	90	75	71	59	40	47	30	44	50	68	50	91	79	0	90	62	0
10	Dylan McIlrath				X	97.00	61	48	85	71	87	50	40	47	30	44	50	58	50	90	78	0	90	60	0
11	Taylor Fedun				X	100.00	50	45	95	76	63	50	40	45	30	40	50	59	50	94	82	0	90	58	0
12	Brogan Rafferty (R)				X	100.00	50	45	95	76	58	50	40	45	30	40	50	55	50	88	75	0	90	56	0
Scratches
1	Mason Shaw (R)			X		100.00	80	66	58	82	54	56	71	57	30	54	60	78	67	84	72	0	90	63	0
2	Hunter McKown (R)	X				100.00	59	45	84	76	70	61	40	49	85	48	50	64	50	80	69	0	90	59	0
3	Nic Petan			X		100.00	50	45	92	81	47	58	40	51	30	48	54	59	65	88	77	0	90	56	0
4	Cedric Paquette		X			100.00	50	45	95	75	69	50	40	45	30	40	50	55	50	90	77	0	90	53	0
5	Brian Pinho	X				100.00	50	45	95	77	63	50	40	45	30	40	50	55	50	88	75	0	90	53	0
6	Kole Sherwood			X		100.00	50	45	95	74	74	50	40	45	30	40	50	55	50	86	73	0	90	53	0
7	Paul Byron		X			100.00	50	45	95	80	40	50	40	45	30	40	50	55	50	94	81	0	90	52	0
8	Sheldon Rempal			X		100.00	50	45	95	80	44	50	40	45	30	40	50	55	50	87	74	0	90	52	0
9	Zach Bogosian				X	100.00	99	45	70	74	76	62	56	50	30	47	53	61	50	92	81	0	90	65	0
10	Mark Friedman				X	100.00	98	48	77	80	51	60	40	51	30	47	55	76	65	87	75	0	90	64	0
11	Alex Goligoski				X	100.00	62	45	85	81	45	74	56	51	30	47	55	68	65	97	89	0	90	63	0

	TEAM AVERAGE					99.13	58	46	89	77	60	54	43	47	32	43	51	59	53	89	77	0	90	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
1	Nico Daws (R)	95.00	70	40	40	89	65	65	65	65	65	65	65	81	73	0	90	58	0
Scratches
1	Ivan Prosvetov (R)	100.00	70	50	77	87	70	70	70	70	70	70	70	83	72	0	90	62	0

	TEAM AVERAGE	97.50	70	45	59	88	68	68	68	68	68	68	68	82	73	0	90	60

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Tony Granato	65	65	65	65	93	74	54	USA	59	2	700,000$

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	PKS	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Tanner Pearson	Marmots (LON)	RW	29	18	20	38	-9	45	15	55	25	151	48	84	11.92%	18	582	20.09	6	9	15	26	67	4	37	2	1	47.78%	90	34	17	1	1	1.30	2	4	1	1	1	3	2	2
2	Derek Stepan	London Spartiates	C	12	7	15	22	6	2	0	16	29	43	19	28	16.28%	8	281	23.50	2	8	10	9	31	0	24	1	0	60.40%	346	15	18	0	0	1.56	2	4	0	0	0	0	5	1
3	Vinni Lettieri	Marmots (LON)	C	26	5	12	17	-7	4	0	23	34	51	15	18	9.80%	7	342	13.17	2	0	2	3	6	1	15	1	0	47.55%	204	11	9	0	0	0.99	0	0	0	0	0	1	1	1
4	Hunter McKown	Marmots (LON)	C	19	3	12	15	-7	4	0	22	48	38	13	34	7.89%	8	343	18.08	1	1	2	3	32	1	20	0	0	65.00%	320	8	9	0	0	0.87	0	1	0	0	0	0	1	1
5	Max McCormick	Marmots (LON)	RW	19	2	12	14	0	2	0	14	19	37	8	23	5.41%	9	293	15.42	0	2	2	4	28	0	1	0	0	43.75%	16	13	3	0	0	0.96	0	0	0	0	0	0	1	2
6	Mason Shaw	Marmots (LON)	RW	7	5	7	12	-1	11	5	15	10	39	11	20	12.82%	6	148	21.23	2	0	2	5	12	1	15	0	1	40.74%	27	11	4	0	0	1.62	0	1	0	0	1	1	1	0
7	Mathieu Perreault	Marmots (LON)	LW	27	6	5	11	-9	0	0	29	32	58	19	28	10.34%	5	441	16.34	0	1	1	3	36	5	11	1	1	52.00%	25	15	12	0	1	0.50	0	0	0	0	0	2	0	0
8	Kristian Reichel	Marmots (LON)	C	19	8	3	11	-4	2	0	20	30	44	14	33	18.18%	11	326	17.18	1	2	3	3	34	0	22	1	0	40.15%	264	10	12	0	0	0.67	1	1	0	0	0	1	0	0
9	Dylan McIlrath	Marmots (LON)	D	29	2	8	10	-9	14	0	25	30	29	15	5	6.90%	28	617	21.28	0	2	2	4	56	1	51	0	0	50.00%	2	16	25	0	0	0.32	0	0	0	0	0	0	0	2
10	Alex Goligoski	Marmots (LON)	D	15	3	7	10	-9	4	0	25	20	27	9	8	11.11%	23	397	26.47	0	2	2	1	37	2	40	0	0	0.00%	0	11	26	0	0	0.50	0	0	0	0	0	0	0	0
11	Kevin Gravel	Marmots (LON)	D	29	3	6	9	-9	2	0	35	39	27	15	17	11.11%	35	629	21.70	3	1	4	6	56	0	59	0	0	100.00%	1	11	33	0	0	0.29	0	0	0	0	0	0	0	0
12	Alex Formenton	Marmots (LON)	LW	19	6	1	7	4	0	0	12	11	28	5	18	21.43%	10	313	16.52	2	0	2	3	25	0	31	1	0	37.04%	27	5	7	0	0	0.45	0	0	0	0	0	1	0	2
13	Sheldon Rempal	Marmots (LON)	RW	8	6	1	7	1	2	0	10	10	27	5	12	22.22%	5	114	14.25	0	0	0	0	1	0	0	1	0	71.43%	7	6	2	0	1	1.23	0	0	0	0	0	1	0	0
14	Cedric Paquette	Marmots (LON)	LW	17	4	2	6	0	0	0	8	14	20	8	11	20.00%	3	213	12.56	0	0	0	0	4	1	5	1	0	55.56%	9	8	9	0	0	0.56	0	0	0	0	0	0	1	0
15	Andrew Poturalski	Marmots (LON)	C	16	3	3	6	4	4	0	4	22	26	8	12	11.54%	8	243	15.23	0	0	0	0	4	0	6	0	0	44.05%	84	8	5	0	0	0.49	0	0	0	0	0	0	0	1
16	Taylor Fedun	Marmots (LON)	D	29	0	5	5	13	4	0	9	25	19	9	9	0.00%	20	480	16.56	0	1	1	1	24	0	20	0	0	0.00%	1	3	19	0	0	0.21	0	0	0	0	0	0	0	0
17	Nic Petan	Marmots (LON)	RW	10	2	3	5	-1	0	0	7	7	42	11	31	4.76%	4	166	16.70	1	0	1	3	10	1	0	0	0	33.33%	6	12	3	0	0	0.60	0	0	0	0	0	0	0	0
18	Brogan Rafferty	Marmots (LON)	D	19	0	5	5	12	4	0	8	18	15	3	1	0.00%	16	325	17.12	0	0	0	1	19	0	22	0	0	0.00%	0	3	14	0	0	0.31	0	0	0	0	0	0	0	0
19	Mark Friedman	Marmots (LON)	D	15	0	4	4	-9	14	0	33	22	35	9	10	0.00%	35	391	26.11	0	1	1	2	37	0	36	0	0	0.00%	0	6	22	0	0	0.20	0	0	0	0	0	0	0	0
20	Zach Bogosian	Marmots (LON)	D	8	0	3	3	-1	6	0	12	9	11	5	6	0.00%	9	174	21.76	0	1	1	2	25	0	14	0	0	0.00%	0	5	7	0	0	0.34	0	0	0	0	0	0	0	1
21	Kole Sherwood	Marmots (LON)	RW	9	2	1	3	-3	0	0	6	8	12	3	10	16.67%	3	132	14.67	0	0	0	0	0	0	0	0	0	33.33%	12	5	4	0	0	0.45	0	0	0	0	0	0	0	0
22	Klim Kostin	London Spartiates	LW	1	2	0	2	1	2	0	1	0	4	1	0	50.00%	0	17	17.27	0	0	0	0	2	0	0	0	0	0.00%	0	0	1	0	0	2.32	0	0	0	0	0	0	0	1
23	Brian Pinho	Marmots (LON)	C	8	0	2	2	-1	2	0	11	12	7	7	7	0.00%	2	131	16.39	0	0	0	0	0	0	0	0	0	37.04%	27	8	2	0	0	0.31	0	0	0	0	0	0	0	0
24	Vitaly Abramov	Marmots (LON)	RW	10	0	1	1	-2	0	0	6	5	9	7	6	0.00%	2	111	11.16	0	0	0	0	3	0	0	0	0	0.00%	1	3	5	0	0	0.18	0	0	0	0	0	0	0	0
Team Total or Average				400	87	138	225	-40	128	20	406	479	799	267	431	10.89%	275	7218	18.05	20	31	51	79	562	17	439	9	3	52.35%	1469	227	268	1	3	0.62	5	11	1	1	2	10	12	14

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	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2
1	Ivan Prosvetov	Marmots (LON)	19	11	6	2	0.887	3.91	1106	0	72	639	323	0	1	0.667	15	19	1	2	0
2	Nico Daws	Marmots (LON)	12	4	5	1	0.882	3.52	665	2	39	331	184	1	0	0.000	0	10	21	0	1
Team Total or Average			31	15	11	3	0.886	3.76	1771	2	111	970	507	1	1	0.667	15	29	22	2	1

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 Formenton	Marmots (LON)	LW	24	1999-09-13	No	195 Lbs	6 ft3	No	No	No	5	RFA	Pro & Farm	775,000$	0$	0$	No
Alex Goligoski	Marmots (LON)	D	38	1985-07-30	No	173 Lbs	5 ft11	No	No	No	1	UFA	Pro & Farm	4,500,000$	0$	0$	No
Andrew Poturalski	Marmots (LON)	C	29	1994-01-14	No	183 Lbs	5 ft10	No	No	No	5	UFA	Pro & Farm	775,000$	0$	0$	No
Brian Pinho	Marmots (LON)	C	28	1995-05-11	No	190 Lbs	6 ft1	No	No	No	1	UFA	Pro & Farm	750,000$	0$	0$	No
Brogan Rafferty	Marmots (LON)	D	27	1995-10-12	Yes	195 Lbs	6 ft0	No	No	No	5	RFA	Pro & Farm	775,000$	0$	0$	No
Cedric Paquette	Marmots (LON)	LW	30	1993-08-13	No	205 Lbs	6 ft0	No	No	No	2	UFA	Pro & Farm	3,500,000$	0$	0$	No
Dylan McIlrath	Marmots (LON)	D	31	1992-04-20	No	232 Lbs	6 ft5	No	No	No	3	UFA	Pro & Farm	750,000$	0$	0$	No
Hunter McKown	Marmots (LON)	C	21	2002-08-18	Yes	205 Lbs	6 ft1	No	No	No	4	RFA	Pro & Farm	2,650,000$	0$	0$	No
Ivan Prosvetov	Marmots (LON)	G	24	1999-03-05	Yes	195 Lbs	6 ft5	No	No	No	3	RFA	Pro & Farm	700,000$	0$	0$	No
Kevin Gravel	Marmots (LON)	D	31	1992-03-06	No	205 Lbs	6 ft4	No	No	No	3	UFA	Pro & Farm	750,000$	0$	0$	No
Kole Sherwood	Marmots (LON)	RW	26	1997-01-22	No	212 Lbs	6 ft1	No	No	No	4	RFA	Pro & Farm	750,000$	0$	0$	No
Kristian Reichel	Marmots (LON)	C	25	1998-06-11	Yes	192 Lbs	6 ft2	No	No	No	5	RFA	Pro & Farm	775,000$	0$	0$	No
Mark Friedman	Marmots (LON)	D	27	1995-12-25	No	185 Lbs	5 ft11	No	No	No	5	RFA	Pro & Farm	3,000,000$	0$	0$	No
Mason Shaw	Marmots (LON)	RW	24	1998-11-03	Yes	184 Lbs	5 ft10	No	No	No	2	RFA	Pro & Farm	800,000$	0$	0$	No
Mathieu Perreault	Marmots (LON)	LW	35	1988-01-05	No	189 Lbs	5 ft10	No	No	No	2	UFA	Pro & Farm	4,000,000$	0$	0$	No
Max McCormick	Marmots (LON)	RW	31	1992-05-01	No	188 Lbs	5 ft11	No	No	No	5	UFA	Pro & Farm	775,000$	0$	0$	No
Nic Petan	Marmots (LON)	RW	28	1995-03-22	No	175 Lbs	5 ft9	No	No	No	3	UFA	Pro & Farm	700,000$	0$	0$	No
Nico Daws	Marmots (LON)	G	22	2000-12-22	Yes	205 Lbs	6 ft4	No	No	No	2	RFA	Pro & Farm	1,100,000$	0$	0$	No
Paul Byron	Marmots (LON)	LW	34	1989-04-27	No	158 Lbs	5 ft9	No	No	No	2	UFA	Pro & Farm	4,000,000$	0$	0$	No
Sheldon Rempal	Marmots (LON)	RW	28	1995-08-07	No	165 Lbs	5 ft10	No	No	No	5	UFA	Pro & Farm	775,000$	0$	0$	No
Tanner Pearson	Marmots (LON)	RW	31	1992-08-10	No	201 Lbs	6 ft1	No	No	No	2	UFA	Pro & Farm	2,500,000$	0$	0$	No
Taylor Fedun	Marmots (LON)	D	35	1988-06-04	No	200 Lbs	6 ft1	No	No	No	3	UFA	Pro & Farm	750,000$	0$	0$	No
Vinni Lettieri	Marmots (LON)	C	28	1995-02-06	No	184 Lbs	5 ft10	No	No	No	4	UFA	Pro & Farm	900,000$	0$	0$	No
Vitaly Abramov	Marmots (LON)	RW	25	1998-05-08	Yes	180 Lbs	5 ft10	No	No	No	5	RFA	Pro & Farm	775,000$	0$	0$	No
Zach Bogosian	Marmots (LON)	D	33	1990-07-15	No	222 Lbs	6 ft2	No	No	No	1	UFA	Pro & Farm	950,000$	0$	0$	No

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
25	28.60	193 Lbs	6 ft0	3.28	1,539,000$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Alex Formenton	Kristian Reichel	Tanner Pearson	35	1	2	2
2	Mathieu Perreault	Vinni Lettieri	Max McCormick	30	1	2	2
3		Andrew Poturalski	Vitaly Abramov	25	1	2	2
4	Kristian Reichel	Tanner Pearson	Vinni Lettieri	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Kevin Gravel	Dylan McIlrath	35	1	2	2
2	Taylor Fedun	Brogan Rafferty	30	1	2	2
3			25	1	2	2
4	Kevin Gravel	Dylan McIlrath	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Alex Formenton	Kristian Reichel	Tanner Pearson	55	1	2	2
2	Mathieu Perreault	Vinni Lettieri	Max McCormick	45	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Kevin Gravel	Dylan McIlrath	55	1	2	2
2	Taylor Fedun	Brogan Rafferty	45	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Tanner Pearson	Kristian Reichel	55	1	2	2
2	Vinni Lettieri	Alex Formenton	45	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Kevin Gravel	Dylan McIlrath	55	1	2	2
2	Taylor Fedun	Brogan Rafferty	45	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Tanner Pearson	55	1	2	2	Kevin Gravel	Dylan McIlrath	55	1	2	2
2	Kristian Reichel	45	1	2	2	Taylor Fedun	Brogan Rafferty	45	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Tanner Pearson	Kristian Reichel	55	1	2	2
2	Vinni Lettieri	Alex Formenton	45	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Kevin Gravel	Dylan McIlrath	55	1	2	2
2	Taylor Fedun	Brogan Rafferty	45	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Alex Formenton	Kristian Reichel	Tanner Pearson	Kevin Gravel	Dylan McIlrath

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Alex Formenton	Kristian Reichel	Tanner Pearson	Kevin Gravel	Dylan McIlrath

Extra Forwards
Normal	PowerPlay	Penalty Kill
Andrew Poturalski, Vitaly Abramov, Max McCormick	Andrew Poturalski, Vitaly Abramov	Max McCormick

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Taylor Fedun, Brogan Rafferty, Kevin Gravel	Taylor Fedun	Brogan Rafferty, Kevin Gravel

Penalty Shots
Tanner Pearson, Kristian Reichel, Vinni Lettieri, Alex Formenton, Max McCormick

Goalie
#1 : Nico Daws, #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	Bandits	2	0	2	0	0	0	0	0	5	11	-6	1	0	1	0	0	0	0	0	4	8	-4	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	5	7	12	0	0	16	40	46	9	44	192	324	395	20	75	17	24	56	3	0	0.00%	7	3	57.14%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
2	Farmers	2	0	0	0	0	0	2	0	8	6	2	1	0	0	0	0	0	1	0	5	4	1	1	0	0	0	0	0	1	0	3	2	1	4	1.000	8	8	16	0	0	16	40	46	9	62	192	324	395	20	73	33	14	42	8	1	12.50%	7	2	71.43%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
3	Goons	1	0	1	0	0	0	0	0	3	6	-3	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	3	6	-3	0	0.000	3	4	7	0	0	16	40	46	9	28	192	324	395	20	40	12	6	14	1	1	100.00%	3	2	33.33%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
4	Grizzlies	3	2	0	0	0	0	0	1	14	12	2	2	2	0	0	0	0	0	0	10	7	3	1	0	0	0	0	0	0	1	4	5	-1	5	0.833	14	22	36	0	0	16	40	46	9	103	192	324	395	20	85	22	14	62	9	2	22.22%	7	1	85.71%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
5	Husky	2	1	0	0	1	0	0	0	10	7	3	1	1	0	0	0	0	0	0	4	2	2	1	0	0	0	1	0	0	0	6	5	1	4	1.000	10	17	27	0	0	16	40	46	9	59	192	324	395	20	56	19	8	41	13	3	23.08%	4	1	75.00%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
6	Marlies	2	0	2	0	0	0	0	0	2	7	-5	1	0	1	0	0	0	0	0	1	4	-3	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	2	3	5	0	0	16	40	46	9	75	192	324	395	20	76	29	12	42	3	0	0.00%	6	1	83.33%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
7	Predateurs	2	0	2	0	0	0	0	0	7	13	-6	1	0	1	0	0	0	0	0	4	6	-2	1	0	1	0	0	0	0	0	3	7	-4	0	0.000	7	11	18	0	0	16	40	46	9	73	192	324	395	20	86	31	22	34	5	2	40.00%	11	4	63.64%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
8	Raptors	1	1	0	0	0	0	0	0	7	3	4	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	7	3	4	2	1.000	7	10	17	0	0	16	40	46	9	43	192	324	395	20	38	10	6	17	4	2	50.00%	3	1	66.67%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
9	Rockets	1	0	0	0	0	0	0	1	5	6	-1	1	0	0	0	0	0	0	1	5	6	-1	0	0	0	0	0	0	0	0	0	0	0	1	0.500	5	8	13	0	0	16	40	46	9	42	192	324	395	20	37	13	6	18	6	3	50.00%	3	1	66.67%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
10	Scorpions	1	1	0	0	0	0	0	0	5	3	2	1	1	0	0	0	0	0	0	5	3	2	0	0	0	0	0	0	0	0	0	0	0	2	1.000	5	7	12	0	0	16	40	46	9	35	192	324	395	20	30	8	4	12	5	1	20.00%	2	1	50.00%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
11	Smirnoff Ice	3	0	1	0	1	0	1	0	9	9	0	1	0	1	0	0	0	0	0	1	3	-2	2	0	0	0	1	0	1	0	8	6	2	4	0.667	9	11	20	1	0	16	40	46	9	90	192	324	395	20	92	21	10	54	7	3	42.86%	5	2	60.00%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
12	Supreme	1	0	1	0	0	0	0	0	1	4	-3	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	4	-3	0	0.000	1	2	3	0	0	16	40	46	9	16	192	324	395	20	36	9	4	10	0	0	0.00%	2	0	100.00%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
13	Thugs	1	0	0	0	1	0	0	0	6	5	1	1	0	0	0	1	0	0	0	6	5	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	6	10	16	0	0	16	40	46	9	45	192	324	395	20	34	22	11	25	1	0	0.00%	3	0	100.00%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
14	TigersCats	3	2	1	0	0	0	0	0	13	12	1	1	0	1	0	0	0	0	0	4	7	-3	2	2	0	0	0	0	0	0	9	5	4	4	0.667	13	24	37	0	0	16	40	46	9	88	192	324	395	20	114	50	27	56	10	3	30.00%	11	3	72.73%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
	Total	29	9	11	0	3	1	3	2	108	114	-6	14	5	5	0	1	1	1	1	54	59	-5	15	4	6	0	2	0	2	1	54	55	-1	33	0.569	108	165	273	1	0	16	40	46	9	915	192	324	395	20	971	326	180	548	90	24	26.67%	80	22	72.50%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
16	Warriors	2	1	0	0	0	1	0	0	8	5	3	1	0	0	0	0	1	0	0	2	3	-1	1	1	0	0	0	0	0	0	6	2	4	3	0.750	8	15	23	0	0	16	40	46	9	79	192	324	395	20	56	13	2	40	4	1	25.00%	1	0	100.00%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
17	Wolves	2	1	1	0	0	0	0	0	5	5	0	1	1	0	0	0	0	0	0	3	1	2	1	0	1	0	0	0	0	0	2	4	-2	2	0.500	5	6	11	0	0	16	40	46	9	33	192	324	395	20	43	17	10	25	11	2	18.18%	5	0	100.00%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
	_Since Last GM Reset	29	9	11	0	3	1	3	2	108	114	-6	14	5	5	0	1	1	1	1	54	59	-5	15	4	6	0	2	0	2	1	54	55	-1	33	0.569	108	165	273	1	0	16	40	46	9	915	192	324	395	20	971	326	180	548	90	24	26.67%	80	22	72.50%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
	_Vs Conference	21	6	7	0	2	1	3	2	77	81	-4	10	3	4	0	0	1	1	1	36	44	-8	11	3	3	0	2	0	2	1	41	37	4	25	0.595	77	119	196	1	0	16	40	46	9	670	192	324	395	20	704	229	123	425	64	17	26.56%	54	16	70.37%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
	_Vs Division	16	5	4	0	1	1	3	2	59	57	2	8	2	3	0	0	1	1	1	28	34	-6	8	3	1	0	1	0	2	1	31	23	8	21	0.656	59	91	150	1	0	16	40	46	9	539	192	324	395	20	533	181	85	314	47	13	27.66%	40	10	75.00%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
29	33	L2	108	165	273	915	971	326	180	548	1	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
29	9	11	3	1	3	2	108	114

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
14	5	5	1	1	1	1	54	59

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
15	4	6	2	0	2	1	54	55

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

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
90	24	26.67%	80	22	72.50%	0

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
192	324	395	20	16	40	46	9

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
319	591	53.98%	323	633	51.03%	230	455	50.55%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
563	297	655	275	554	276

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 - 2024-04-06	3	Grizzlies	3	Marmots	4	W			BoxScore
2 - 2024-04-07	19	Marmots	4	Grizzlies	5	L	X	X	BoxScore
4 - 2024-04-09	37	Marmots	1	Bandits	3	L			BoxScore
6 - 2024-04-11	49	Rockets	6	Marmots	5	L	X	X	BoxScore
7 - 2024-04-12	70	Smirnoff Ice	3	Marmots	1	L			BoxScore
8 - 2024-04-13	80	Marmots	1	Marlies	3	L			BoxScore
9 - 2024-04-14	85	Marmots	3	Farmers	2	W	X	X	BoxScore
10 - 2024-04-15	104	Marmots	6	Warriors	2	W			BoxScore
12 - 2024-04-17	122	Marlies	4	Marmots	1	L			BoxScore
14 - 2024-04-19	143	Warriors	3	Marmots	2	L	X		BoxScore
16 - 2024-04-21	164	Farmers	4	Marmots	5	W	X	X	BoxScore
17 - 2024-04-22	174	Marmots	3	TigersCats	1	W			BoxScore
18 - 2024-04-23	192	TigersCats	7	Marmots	4	L			BoxScore
19 - 2024-04-24	203	Marmots	3	Smirnoff Ice	2	W	X		BoxScore
21 - 2024-04-26	225	Grizzlies	4	Marmots	6	W			BoxScore
22 - 2024-04-27	235	Marmots	6	TigersCats	4	W			BoxScore
24 - 2024-04-29	254	Husky	2	Marmots	4	W			BoxScore
25 - 2024-04-30	270	Marmots	7	Raptors	3	W			BoxScore
27 - 2024-05-02	286	Marmots	5	Smirnoff Ice	4	W	X	X	BoxScore
28 - 2024-05-03	300	Bandits	8	Marmots	4	L			BoxScore
30 - 2024-05-05	311	Marmots	1	Supreme	4	L			BoxScore
31 - 2024-05-06	329	Wolves	1	Marmots	3	W			BoxScore
33 - 2024-05-08	348	Marmots	3	Predateurs	7	L			BoxScore
34 - 2024-05-09	359	Marmots	6	Husky	5	W	X		BoxScore
35 - 2024-05-10	369	Thugs	5	Marmots	6	W	X		BoxScore
36 - 2024-05-11	386	Marmots	2	Wolves	4	L			BoxScore
38 - 2024-05-13	398	Scorpions	3	Marmots	5	W			BoxScore
40 - 2024-05-15	419	Marmots	3	Goons	6	L			BoxScore
41 - 2024-05-16	432	Predateurs	6	Marmots	4	L			BoxScore
43 - 2024-05-18	453	CoolFm	-	Marmots	-
44 - 2024-05-19	470	Marmots	-	Warriors	-
46 - 2024-05-21	485	Snowbirds	-	Marmots	-
47 - 2024-05-22	503	Twins	-	Marmots	-
48 - 2024-05-23	516	Marmots	-	Chiwawa	-
50 - 2024-05-25	534	Raptors	-	Marmots	-
51 - 2024-05-26	547	Marmots	-	Grizzlies	-
52 - 2024-05-27	555	Marmots	-	Hunters	-
53 - 2024-05-28	571	Marmots	-	Outlaws	-
55 - 2024-05-30	583	Spartans	-	Marmots	-
57 - 2024-06-01	608	Marmots	-	Marlies	-
58 - 2024-06-02	614	Rockets	-	Marmots	-
61 - 2024-06-05	642	Farmers	-	Marmots	-
62 - 2024-06-06	657	TigersCats	-	Marmots	-
63 - 2024-06-07	667	Marmots	-	Igloos	-
65 - 2024-06-09	688	Marmots	-	Xpress	-
66 - 2024-06-10	698	Smirnoff Ice	-	Marmots	-
67 - 2024-06-11	719	Marmots	-	Barracudas	-
68 - 2024-06-12	730	Bayou	-	Marmots	-
70 - 2024-06-14	745	Marmots	-	Snowbirds	-
71 - 2024-06-15	762	Marmots	-	Vandals	-
72 - 2024-06-16	769	Warriors	-	Marmots	-
73 - 2024-06-17	784	Marmots	-	Thugs	-
74 - 2024-06-18	800	Goons	-	Marmots	-
76 - 2024-06-20	822	Marlies	-	Marmots	-
77 - 2024-06-21	840	Marmots	-	Saguenéens	-
78 - 2024-06-22	849	Marmots	-	Scorpions	-
79 - 2024-06-23	862	Supreme	-	Marmots	-
82 - 2024-06-26	888	Vandals	-	Marmots	-
83 - 2024-06-27	903	Marmots	-	Bandits	-
85 - 2024-06-29	920	Outlaws	-	Marmots	-
87 - 2024-07-01	937	Marmots	-	Spartans	-
88 - 2024-07-02	952	Hunters	-	Marmots	-
89 - 2024-07-03	965	Marmots	-	Farmers	-
Trade Deadline --- Trades can’t be done after this day is simulated!
91 - 2024-07-05	979	Marmots	-	Twins	-
92 - 2024-07-06	991	Igloos	-	Marmots	-
93 - 2024-07-07	1009	Marmots	-	Vipers	-
95 - 2024-07-09	1022	Chiwawa	-	Marmots	-
96 - 2024-07-10	1040	Vipers	-	Marmots	-
98 - 2024-07-12	1058	Marmots	-	Bayou	-
99 - 2024-07-13	1066	Marmots	-	CoolFm	-
101 - 2024-07-15	1079	Barracudas	-	Marmots	-
103 - 2024-07-17	1097	Marmots	-	Rockets	-
105 - 2024-07-19	1112	Saguenéens	-	Marmots	-
108 - 2024-07-22	1143	Xpress	-	Marmots	-
111 - 2024-07-25	1162	Xpress	-	Marmots	-
112 - 2024-07-26	1169	Marmots	-	Rockets	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	75	30
Attendance	13,702	7,497
Attendance PCT	48.94%	53.55%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
24	1514 - 50.47%	107,362$	1,503,072$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
1,647,430$	3,847,500$	3,847,500$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	1,393,449$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
2,576,695$	72	40,243$	2,897,496$

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
45	82	28	41	0	2	2	4	5	298	331	-33	41	14	19	0	0	1	2	5	150	163	-13	41	14	22	0	2	1	2	0	148	168	-20	75	298	479	777	2	1	55	108	129	11	2350	565	847	914	60	2619	774	585	1332	251	66	26.29%	239	57	76.15%	5	629	1505	41.79%	706	1653	42.71%	604	1345	44.91%	1433	760	2170	704	1373	678
46	82	31	30	0	7	6	5	3	289	276	13	41	16	13	0	3	4	4	1	146	136	10	41	15	17	0	4	2	1	2	143	140	3	95	289	475	764	1	1	50	111	116	18	2282	540	889	834	45	2467	787	563	1249	245	75	30.61%	217	56	74.19%	3	743	1523	48.79%	726	1600	45.38%	668	1297	51.50%	1544	858	2029	708	1403	703
47	29	9	11	0	3	1	3	2	108	114	-6	14	5	5	0	1	1	1	1	54	59	-5	15	4	6	0	2	0	2	1	54	55	-1	33	108	165	273	1	0	16	40	46	9	915	192	324	395	20	971	326	180	548	90	24	26.67%	80	22	72.50%	0	319	591	53.98%	323	633	51.03%	230	455	50.55%	563	297	655	275	554	276
Total Regular Season	193	68	82	0	12	9	12	10	695	721	-26	96	35	37	0	4	6	7	7	350	358	-8	97	33	45	0	8	3	5	3	345	363	-18	203	695	1119	1814	4	2	121	259	291	38	5547	1297	2060	2143	125	6057	1887	1328	3129	586	165	28.16%	536	135	74.81%	8	1691	3619	46.73%	1755	3886	45.16%	1502	3097	48.50%	3540	1916	4855	1688	3331	1658

Back to the Top