SIM4 - Pittsburgh Penguins

Wilkes-Barre/Scranton Penguins
Roster
Scoring
Players Info
Lines
Team Stats
Schedule
Finance
Depth
History
Last Transactions
Injury / Suspension
Career Team Stat
Web Roster Editor
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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	Tyler Seguin	X				100.00	59	38	86	85	72	85	84	92	84	83	92	62	89	60	64	71	40	76	0
2	Zach Parise		X			100.00	62	39	79	83	67	84	83	84	32	72	84	65	80	76	81	7	40	73	0
3	Tomas Plekanec	X				100.00	54	36	77	80	66	83	95	78	76	82	69	69	64	80	76	5	40	72	0
4	Mats Zuccarello			X		100.00	58	38	77	86	55	78	90	82	34	79	77	63	89	70	66	31	40	71	0
5	Ryan Nugent-Hopkins	X				100.00	55	37	83	77	68	83	72	75	66	73	68	71	77	58	60	79	40	68	0
6	Nino Niederreiter		X	X		100.00	78	45	78	75	77	61	88	75	35	67	76	62	66	60	60	71	40	67	0
7	Marian Gaborik		X	X		100.00	51	35	78	76	74	60	59	74	31	60	72	59	86	80	78	5	40	65	0
8	Erik Haula	X				100.00	58	37	73	74	69	48	77	69	79	65	66	77	61	62	48	63	40	64	0
9	Oscar Lindberg	X				100.00	71	45	68	74	72	46	64	71	70	63	68	63	62	62	55	63	40	63	0
10	Jay Beagle	X		X		100.00	58	37	73	67	80	48	59	64	91	57	60	73	57	74	64	15	40	62	0
11	Matt Martin		X			100.00	97	96	65	69	82	49	85	65	32	57	63	58	58	66	60	47	40	62	0
12	Dion Phaneuf				X	100.00	76	60	61	69	83	83	83	59	30	66	51	76	54	74	83	15	40	70	0
13	Jay Bouwmeester				X	100.00	58	37	85	69	82	85	85	49	30	55	48	83	50	78	75	5	40	68	0
14	Zach Bogosian				X	100.00	69	49	72	68	81	82	71	56	30	56	54	78	53	64	64	55	40	67	0
15	Marc Staal				X	100.00	61	39	75	64	81	71	85	49	31	54	48	79	50	70	71	31	40	65	0
16	Marek Zidlicky				X	100.00	56	37	72	73	66	54	66	60	30	57	53	66	56	90	77	5	40	63	0
17	Tom Gilbert				X	100.00	58	37	79	61	75	56	55	46	30	46	45	78	48	78	69	5	40	61	0
18	Martin Marincin				X	100.00	53	36	70	61	80	55	65	45	30	47	45	82	52	60	47	71	40	60	0
Scratches

	TEAM AVERAGE					100.00	63	43	75	73	74	67	76	66	47	63	63	70	64	70	67	36	40	67

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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	Kari Lehtonen	100.00	88	83	85	81	79	82	79	79	79	98	68	78	79	5	40	80	0
2	Jeff Zatkoff	100.00	69	57	70	73	77	71	72	75	74	69	55	70	64	31	40	69	0
Scratches

	TEAM AVERAGE	100.00	79	70	78	77	78	77	76	77	77	84	62	74	72	18	40	75

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

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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	P/20	PSS	FW	FL	FT	S1	S2	S3
1	Tyler Seguin	Pittsburgh Penguins	C	9	3	5	8	4	2	0	9	18	24	0	3	12.50%	1	224	24.98	1	2	3	7	42	0	45	1	0	52.71%	258	0.71	1	0	0	0	0	2	1
2	Zach Parise	Pittsburgh Penguins	LW	9	3	3	6	4	8	0	10	16	21	1	3	14.29%	0	219	24.43	0	2	2	7	42	0	40	1	1	37.50%	16	0.55	1	0	0	0	1	0	0
3	Mats Zuccarello	Pittsburgh Penguins	RW	9	1	4	5	0	2	0	5	15	15	0	2	6.67%	3	169	18.79	1	1	2	4	42	1	24	0	0	25.00%	8	0.59	0	0	0	0	0	0	0
4	Ryan Nugent-Hopkins	Pittsburgh Penguins	C	9	1	2	3	-2	0	0	1	13	9	0	3	11.11%	0	128	14.33	0	0	0	1	5	0	0	0	0	44.83%	87	0.47	0	0	0	0	0	0	0
5	Dion Phaneuf	Pittsburgh Penguins	D	9	0	2	2	2	32	10	23	6	6	0	1	0.00%	3	212	23.64	0	0	0	4	39	0	32	0	0	0.00%	0	0.19	0	0	1	1	0	0	0
6	Jay Beagle	Pittsburgh Penguins	C/RW	9	0	2	2	-2	0	0	0	10	8	0	0	0.00%	1	124	13.86	0	0	0	1	1	0	1	0	0	66.67%	3	0.32	0	0	0	0	0	0	0
7	Jay Bouwmeester	Pittsburgh Penguins	D	9	1	1	2	2	2	0	0	12	11	0	2	9.09%	10	197	21.98	1	1	2	6	43	0	42	0	0	0.00%	0	0.20	0	0	0	0	0	0	0
8	Marian Gaborik	Pittsburgh Penguins	LW/RW	9	2	0	2	-5	0	0	5	9	12	0	0	16.67%	0	162	18.04	0	0	0	6	34	0	9	0	0	14.29%	7	0.25	0	0	0	0	0	0	0
9	Matt Martin	Pittsburgh Penguins	LW	9	0	2	2	-2	15	5	19	2	8	1	3	0.00%	2	120	13.40	0	0	0	0	0	0	0	0	0	20.00%	5	0.33	0	1	0	0	0	0	1
10	Erik Haula	Pittsburgh Penguins	C	9	0	1	1	2	2	0	1	2	2	0	1	0.00%	0	50	5.66	0	0	0	0	0	0	14	0	0	55.56%	36	0.39	0	0	0	0	0	0	0
11	Marek Zidlicky	Pittsburgh Penguins	D	9	1	0	1	-2	10	0	18	2	2	0	0	50.00%	6	125	13.98	0	0	0	0	7	0	1	1	0	0.00%	0	0.16	0	0	0	0	0	1	0
12	Martin Marincin	Pittsburgh Penguins	D	9	1	0	1	1	0	0	1	3	3	0	0	33.33%	2	53	5.89	0	0	0	0	1	0	7	0	0	0.00%	0	0.38	0	0	0	0	0	0	1
13	Nino Niederreiter	Pittsburgh Penguins	LW/RW	9	0	1	1	-4	14	0	20	4	16	1	0	0.00%	1	152	16.89	0	0	0	3	34	0	0	0	0	40.00%	10	0.13	0	0	0	0	0	0	0
14	Tom Gilbert	Pittsburgh Penguins	D	9	1	0	1	-2	12	0	13	4	2	0	0	50.00%	7	126	14.08	0	0	0	0	0	0	12	0	0	0.00%	0	0.16	0	0	0	0	0	0	0
15	Tomas Plekanec	Pittsburgh Penguins	C	9	0	1	1	-4	6	0	4	14	21	0	1	0.00%	1	181	20.15	0	0	0	3	37	0	23	0	0	45.51%	167	0.11	0	0	0	0	0	0	0
16	Marc Staal	Pittsburgh Penguins	D	9	0	0	0	-4	4	0	3	3	4	0	2	0.00%	9	186	20.76	0	0	0	4	37	0	35	0	0	0.00%	0	0.00	0	0	0	0	0	0	0
17	Oscar Lindberg	Pittsburgh Penguins	C	9	0	0	0	-1	0	0	0	1	1	0	0	0.00%	1	10	1.19	0	0	0	1	6	0	0	0	0	50.00%	6	0.00	0	0	0	0	0	0	0
18	Zach Bogosian	Pittsburgh Penguins	D	9	0	0	0	-4	13	5	12	3	5	0	3	0.00%	8	183	20.36	0	0	0	4	36	0	31	0	0	0.00%	0	0.00	0	1	0	0	0	0	0
Team Total or Average				162	14	24	38	-17	122	20	144	137	170	3	24	8.24%	55	2631	16.25	3	6	9	51	413	1	326	3	1	48.09%	603	0.29	2	2	1	1	1	3	3

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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	SO	GA	SA	PS %	PSA	ST	BG	S1	S2
1	Kari Lehtonen	Pittsburgh Penguins	9	3	5	1	0.874	2.31	520	2	20	159	0.333	3	9	0	2	1
2	Jeff Zatkoff	Pittsburgh Penguins	1	0	0	0	0.800	2.40	25	0	1	5	0.000	0	0	9	0	0
Team Total or Average			10	3	5	1	0.872	2.31	545	2	21	164	0.333	3	9	9	2	1

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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	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Link
Dion Phaneuf	Pittsburgh Penguins	D	33	4/10/1985	No	227 Lbs	6 ft3	No	No	No	4	UFA	Pro & Farm	0$	0$	No	NHL Link
Erik Haula	Pittsburgh Penguins	C	27	3/23/1991	No	193 Lbs	6 ft0	No	No	No	4	RFA	Pro & Farm	0$	0$	No	NHL Link
Jay Beagle	Pittsburgh Penguins	C/RW	32	10/16/1985	No	210 Lbs	6 ft3	No	No	No	4	UFA	Pro & Farm	0$	0$	No	NHL Link
Jay Bouwmeester	Pittsburgh Penguins	D	34	9/27/1983	No	212 Lbs	6 ft4	No	No	No	1	UFA	Pro & Farm	0$	0$	No	NHL Link
Jeff Zatkoff	Pittsburgh Penguins	G	30	6/9/1987	No	179 Lbs	6 ft2	No	No	No	4	UFA	Pro & Farm	0$	0$	No
Kari Lehtonen	Pittsburgh Penguins	G	34	11/16/1983	No	205 Lbs	6 ft4	No	No	No	5	UFA	Pro & Farm	0$	0$	No	NHL Link
Marc Staal	Pittsburgh Penguins	D	31	1/13/1987	No	207 Lbs	6 ft4	No	No	No	5	UFA	Pro & Farm	0$	0$	No	NHL Link
Marek Zidlicky	Pittsburgh Penguins	D	41	2/3/1977	No	190 Lbs	5 ft11	No	No	No	2	UFA	Pro & Farm	0$	0$	No
Marian Gaborik	Pittsburgh Penguins	LW/RW	36	2/14/1982	No	205 Lbs	6 ft1	No	No	No	3	UFA	Pro & Farm	0$	0$	No	NHL Link
Martin Marincin	Pittsburgh Penguins	D	26	2/18/1992	No	201 Lbs	6 ft4	No	No	No	2	RFA	Pro & Farm	0$	0$	No	NHL Link
Mats Zuccarello	Pittsburgh Penguins	RW	30	9/1/1987	No	179 Lbs	5 ft7	No	No	No	4	UFA	Pro & Farm	0$	0$	No	NHL Link
Matt Martin	Pittsburgh Penguins	LW	29	5/8/1989	No	220 Lbs	6 ft3	No	No	No	2	UFA	Pro & Farm	0$	0$	No	NHL Link
Nino Niederreiter	Pittsburgh Penguins	LW/RW	25	9/8/1992	No	211 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	0$	0$	No	NHL Link
Oscar Lindberg	Pittsburgh Penguins	C	26	10/29/1991	No	195 Lbs	6 ft1	No	No	No	2	RFA	Pro & Farm	0$	0$	No	NHL Link
Ryan Nugent-Hopkins	Pittsburgh Penguins	C	25	4/12/1993	No	189 Lbs	6 ft0	No	No	No	3	RFA	Pro & Farm	0$	0$	No	NHL Link
Tom Gilbert	Pittsburgh Penguins	D	35	1/10/1983	No	202 Lbs	6 ft2	No	No	No	2	UFA	Pro & Farm	0$	0$	No
Tomas Plekanec	Pittsburgh Penguins	C	35	10/31/1982	No	195 Lbs	5 ft11	No	No	No	2	UFA	Pro & Farm	0$	0$	No	NHL Link
Tyler Seguin	Pittsburgh Penguins	C	26	1/31/1992	No	200 Lbs	6 ft1	No	No	No	4	RFA	Pro & Farm	0$	0$	No	NHL Link
Zach Bogosian	Pittsburgh Penguins	D	27	7/15/1990	No	219 Lbs	6 ft3	No	No	No	3	RFA	Pro & Farm	0$	0$	No	NHL Link
Zach Parise	Pittsburgh Penguins	LW	33	7/28/1984	No	196 Lbs	5 ft11	No	No	No	4	UFA	Pro & Farm	0$	0$	No	NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
20	30.75	202 Lbs	6 ft1	3.15	0$

Sum Year 1 Salary	Sum Year 2 Salary	Sum Year 3 Salary	Sum Year 4 Salary	Sum Year 5 Salary
0$	0$	0$	0$	0$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Zach Parise	Tyler Seguin	Mats Zuccarello	40	1	2	2
2	Nino Niederreiter	Tomas Plekanec	Marian Gaborik	30	1	2	2
3	Matt Martin	Ryan Nugent-Hopkins	Jay Beagle	20	1	2	2
4	Tyler Seguin	Erik Haula	Zach Parise	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Dion Phaneuf	Jay Bouwmeester	40	1	2	2
2	Zach Bogosian	Marc Staal	30	1	2	2
3	Marek Zidlicky	Tom Gilbert	20	1	2	2
4	Martin Marincin	Dion Phaneuf	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Zach Parise	Tyler Seguin	Mats Zuccarello	60	1	2	2
2	Nino Niederreiter	Tomas Plekanec	Marian Gaborik	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Dion Phaneuf	Jay Bouwmeester	60	1	2	2
2	Zach Bogosian	Marc Staal	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Tyler Seguin	Zach Parise	60	1	2	2
2	Tomas Plekanec	Mats Zuccarello	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Dion Phaneuf	Jay Bouwmeester	60	1	2	2
2	Zach Bogosian	Marc Staal	40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Tyler Seguin	60	1	2	2	Dion Phaneuf	Jay Bouwmeester	60	1	2	2
2	Zach Parise	40	1	2	2	Zach Bogosian	Marc Staal	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Tyler Seguin	Zach Parise	60	1	2	2
2	Tomas Plekanec	Mats Zuccarello	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Dion Phaneuf	Jay Bouwmeester	60	1	2	2
2	Zach Bogosian	Marc Staal	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Zach Parise	Tyler Seguin	Mats Zuccarello	Dion Phaneuf	Jay Bouwmeester

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Zach Parise	Tyler Seguin	Mats Zuccarello	Dion Phaneuf	Jay Bouwmeester

Extra Forwards
Normal	PowerPlay	Penalty Kill
Oscar Lindberg, Ryan Nugent-Hopkins, Erik Haula	Oscar Lindberg, Ryan Nugent-Hopkins	Erik Haula

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Marek Zidlicky, Tom Gilbert, Martin Marincin	Marek Zidlicky	Tom Gilbert, Martin Marincin

Penalty Shots
Tyler Seguin, Zach Parise, Tomas Plekanec, Mats Zuccarello, Ryan Nugent-Hopkins

Goalie
#1 : Kari Lehtonen, #2 : Jeff Zatkoff

Custom OT Lines Forwards
Tyler Seguin, Zach Parise, Tomas Plekanec, Mats Zuccarello, Ryan Nugent-Hopkins, Nino Niederreiter, Nino Niederreiter, Marian Gaborik, Erik Haula, Oscar Lindberg, Jay Beagle

Custom OT Lines Defensemen
Dion Phaneuf, Jay Bouwmeester, Zach Bogosian, Marc Staal, Marek Zidlicky

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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	Carolina Hurricanes	2	0	2	0	0	0	0	0	2	4	-2	1	0	1	0	0	0	0	0	0	1	-1	1	0	1	0	0	0	0	0	2	3	-1	0	0.000	2	4	6	0	0	1	0	1	0	48	19	12	17	0	21	6	19	23	11	1	9.09%	7	1	85.71%	0	120	235	51.06%	120	240	50.00%	50	111	45.05%	52	38	42	14	24	12
2	Columbus Blue Jackets	2	1	0	0	1	0	0	0	3	1	2	1	1	0	0	0	0	0	0	1	0	1	1	0	0	0	1	0	0	0	2	1	1	4	1.000	3	5	8	0	1	1	0	1	1	32	16	7	6	3	43	17	28	22	9	1	11.11%	14	1	92.86%	0	120	235	51.06%	120	240	50.00%	50	111	45.05%	39	25	59	14	22	10
3	New York Islanders	2	1	1	0	0	0	0	0	2	5	-3	1	1	0	0	0	0	0	0	1	0	1	1	0	1	0	0	0	0	0	1	5	-4	2	0.500	2	4	6	0	1	0	1	1	0	32	12	6	14	0	40	11	16	41	8	0	0.00%	8	0	100.00%	0	120	235	51.06%	120	240	50.00%	50	111	45.05%	42	28	52	15	24	12
4	Philadelphia Flyers	2	0	1	0	0	0	0	1	5	8	-3	1	0	0	0	0	0	0	1	2	3	-1	1	0	1	0	0	0	0	0	3	5	-2	1	0.250	5	8	13	0	0	3	1	1	0	47	10	16	17	6	36	16	47	38	11	1	9.09%	12	2	83.33%	0	120	235	51.06%	120	240	50.00%	50	111	45.05%	47	32	52	16	25	12
	Total	9	2	5	0	1	0	0	1	14	22	-8	4	2	1	0	0	0	0	1	4	4	0	5	0	4	0	1	0	0	0	10	18	-8	7	0.389	14	24	38	0	2	5	3	5	1	170	59	47	57	9	164	55	122	144	45	3	6.67%	47	7	85.11%	0	120	235	51.06%	120	240	50.00%	50	111	45.05%	207	142	229	67	110	54
6	Washington Capitals	1	0	1	0	0	0	0	0	2	4	-2	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	2	4	-2	0	0.000	2	3	5	0	0	0	1	1	0	11	2	6	3	0	24	5	12	20	6	0	0.00%	6	3	50.00%	0	120	235	51.06%	120	240	50.00%	50	111	45.05%	24	16	22	7	12	6
	_Since Last GM Reset	9	2	5	0	1	0	0	1	14	22	-8	4	2	1	0	0	0	0	1	4	4	0	5	0	4	0	1	0	0	0	10	18	-8	7	0.389	14	24	38	0	2	5	3	5	1	170	59	47	57	9	164	55	122	144	45	3	6.67%	47	7	85.11%	0	120	235	51.06%	120	240	50.00%	50	111	45.05%	207	142	229	67	110	54
	_Vs Conference	9	2	5	0	1	0	0	1	14	22	-8	4	2	1	0	0	0	0	1	4	4	0	5	0	4	0	1	0	0	0	10	18	-8	7	0.389	14	24	38	0	2	5	3	5	1	170	59	47	57	9	164	55	122	144	45	3	6.67%	47	7	85.11%	0	120	235	51.06%	120	240	50.00%	50	111	45.05%	207	142	229	67	110	54
	_Vs Division	9	2	5	0	1	0	0	1	14	22	-8	4	2	1	0	0	0	0	1	4	4	0	5	0	4	0	1	0	0	0	10	18	-8	7	0.389	14	24	38	0	2	5	3	5	1	170	59	47	57	9	164	55	122	144	45	3	6.67%	47	7	85.11%	0	120	235	51.06%	120	240	50.00%	50	111	45.05%	207	142	229	67	110	54

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
9	7	OTW1	14	24	38	170	164	55	122	144	0	2

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
9	2	5	1	0	0	1	14	22

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	2	1	0	0	0	1	4	4

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	0	4	1	0	0	0	10	18

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

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
45	3	6.67%	47	7	85.11%	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
59	47	57	9	5	3	5	1

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
120	235	51.06%	120	240	50.00%	50	111	45.05%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
207	142	229	67	110	54

Last Played Games

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Day	Game	Visitor Team	Score	Home Team	Score	ST	OT	SO	Link
3 - 2017-05-15	12	Pittsburgh Penguins	1	New York Islanders	5	L			BoxScore
5 - 2017-05-17	24	New York Islanders	0	Pittsburgh Penguins	1	W			BoxScore
8 - 2017-05-20	39	Pittsburgh Penguins	3	Philadelphia Flyers	5	L			BoxScore
10 - 2017-05-22	52	Carolina Hurricanes	1	Pittsburgh Penguins	0	L			BoxScore
13 - 2017-05-25	69	Pittsburgh Penguins	2	Washington Capitals	4	L			BoxScore
16 - 2017-05-28	82	Philadelphia Flyers	3	Pittsburgh Penguins	2	L	X	X	BoxScore
19 - 2017-05-31	98	Pittsburgh Penguins	2	Carolina Hurricanes	3	L			BoxScore
22 - 2017-06-03	108	Columbus Blue Jackets	0	Pittsburgh Penguins	1	W			BoxScore
24 - 2017-06-05	120	Pittsburgh Penguins	2	Columbus Blue Jackets	1	W	X		BoxScore
29 - 2017-06-10	142	Washington Capitals	-	Pittsburgh Penguins	-
34 - 2017-06-15	163	Pittsburgh Penguins	-	New Jersey Devils	-
36 - 2017-06-17	172	New Jersey Devils	-	Pittsburgh Penguins	-
Trade Deadline --- Trades can’t be done after this day is simulated!
39 - 2017-06-20	187	Pittsburgh Penguins	-	New York Rangers	-
42 - 2017-06-23	200	New York Rangers	-	Pittsburgh Penguins	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2	Level 3	Level 4	Luxury
Arena Capacity	6000	5000	2000	4000	1000
Ticket Price	100	60	35	25	200
Attendance	0	0	0	0	0
Attendance PCT	0.00%	0.00%	0.00%	0.00%	0.00%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
3	0 - 0.00%	0$	0$	18000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries	Special Salary Cap Value
0$	0$	0$	0$	0$

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

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	22	0$	0$

Team Total Estimate
Estimated Season Expenses	Estimated Season Salary Cap	Current Bank Account	Projected Bank Account
0$	0$	10,000,000$	10,000,000$

Depth Chart

Left Wing

Center

Right Wing

Zach Parise	AGE:33	PO:7	OV:73
Nino Niederreiter	AGE:25	PO:71	OV:67
Marian Gaborik	AGE:36	PO:5	OV:65
Matt Martin	AGE:29	PO:47	OV:62
Dwight King	AGE:28	PO:47	OV:60
Ryan Dzingel	AGE:26	PO:71	OV:58
Scott Wilson	AGE:26	PO:71	OV:57
Antoine Laganiere	AGE:27	PO:55	OV:56
Jeff Hoggan	AGE:40	PO:5	OV:55
Mitch Moroz	AGE:24	PO:87	OV:53
Ben Thomson	AGE:25	PO:79	OV:53
Yannick Veilleux	AGE:25	PO:79	OV:53
*Emerson Clark	AGE:25	PO:71	OV:51

Tyler Seguin	AGE:26	PO:71	OV:76
Tomas Plekanec	AGE:35	PO:5	OV:72
Ryan Nugent-Hopkins	AGE:25	PO:79	OV:68
Erik Haula	AGE:27	PO:63	OV:64
Oscar Lindberg	AGE:26	PO:63	OV:63
Jay Beagle	AGE:32	PO:15	OV:62
Ryan Carpenter	AGE:27	PO:63	OV:58
Antoine Laganiere	AGE:27	PO:55	OV:56
Jeremy Welsh	AGE:30	PO:39	OV:56
James Wright	AGE:28	PO:55	OV:55
Ryan Rupert	AGE:23	PO:87	OV:54
Joe Pendenza	AGE:27	PO:55	OV:52
*Andrew Poturalski	AGE:24	PO:87	OV:51
Matt Leitner	AGE:27	PO:55	OV:51
Kevin Lynch	AGE:27	PO:63	OV:50

Mats Zuccarello	AGE:30	PO:31	OV:71
Nino Niederreiter	AGE:25	PO:71	OV:67
Marian Gaborik	AGE:36	PO:5	OV:65
Jay Beagle	AGE:32	PO:15	OV:62
Iiro Pakarinen	AGE:26	PO:63	OV:59
Ty Rattie	AGE:25	PO:79	OV:57
Justin Shugg	AGE:26	PO:63	OV:56
Antoine Laganiere	AGE:27	PO:55	OV:56
Adam Payerl	AGE:27	PO:63	OV:54
Brian Ferlin	AGE:25	PO:71	OV:53
*Jiri Fronk	AGE:24	PO:87	OV:51

Defense #1

Defense #2

Goalie

Dion Phaneuf	AGE:33	PO:15	OV:70
Jay Bouwmeester	AGE:34	PO:5	OV:68
Zach Bogosian	AGE:27	PO:55	OV:67
Marc Staal	AGE:31	PO:31	OV:65
Marek Zidlicky	AGE:41	PO:5	OV:63
Tom Gilbert	AGE:35	PO:5	OV:61
Martin Marincin	AGE:26	PO:71	OV:60
Rinat Valiev	AGE:23	PO:95	OV:58
Nate Prosser	AGE:32	PO:23	OV:58

Cody Goloubef	AGE:28	PO:47	OV:56
*Robbie Russo	AGE:25	PO:79	OV:55
Bobby Sanguinetti	AGE:30	PO:39	OV:55
Matt Clark	AGE:27	PO:55	OV:54
*Julius Bergman	AGE:22	PO:95	OV:53
C.J. Ludwig	AGE:27	PO:55	OV:52
Benjamin Dieude-Fauvel	AGE:31	PO:23	OV:52
*Mason Geertsen	AGE:23	PO:95	OV:51
James Melindy	AGE:24	PO:79	OV:51

Kari Lehtonen	AGE:34	PO:5	OV:80
Jeff Zatkoff	AGE:30	PO:31	OV:69
Michael Leighton	AGE:37	PO:5	OV:65
Scott Greenham	AGE:31	PO:31	OV:58
*Ken Appleby	AGE:23	PO:95	OV:53
*Clay Witt	AGE:26	PO:63	OV:52

Prospects

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7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
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Prospect	Team Name	Draft Year	Overall Pick	Information	Lien

Draft Picks

Year	R1	R2	R3	R4	R5
5	PIT	PIT	PIT	PIT	PIT
6	PIT	PIT	PIT	PIT	PIT
7	PIT	PIT	PIT	PIT	PIT
8	PIT	PIT	PIT	PIT	PIT
9	PIT	PIT	PIT	PIT	PIT

[5/13/2017 1:27:46 PM] - Wilkes-Barre/Scranton Penguins was eliminated at round 1 of year 3.
[5/13/2017 1:27:09 PM] - Pittsburgh Penguins didn't make playoff for year 3.
[5/13/2017 1:02:52 PM] - New Record for Team's Most Points (16) in 1 Game for Pittsburgh Penguins!
[5/13/2017 1:02:52 PM] - New Record for Team's Most Goals (6) in 1 Game for Pittsburgh Penguins!
[5/13/2017 1:01:19 PM] - New Record for Team's Most Penalties Minutes (53) in 1 Game for Pittsburgh Penguins!
[5/13/2017 1:01:19 PM] - New Record for Team's Most Penalties Minutes (53) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:59:11 PM] - Wilkes-Barre/Scranton Penguinsare the Farm Playoffs Champions for year 2!
[5/13/2017 12:59:08 PM] - Pittsburgh Penguins was eliminated at round 3 of year 2.
[5/13/2017 12:57:40 PM] - New Record for Team's Most Shots Blocked (10) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:55:15 PM] - New Record for Team's Most Shots (37) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:53:30 PM] - New Record for Team's Most Points (15) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:53:30 PM] - New Record for Team's Most Assists (10) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:51:35 PM] - Wilkes-Barre/Scranton Penguins was eliminated at round 3 of year 1.
[5/13/2017 12:51:30 PM] - Pittsburgh Penguins was eliminated at round 2 of year 1.
[5/13/2017 12:16:53 PM] - New Record for Team's Most Penalties Minutes (37) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:16:27 PM] - New Record for Team's Most Shots Blocked (9) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:16:20 PM] - New Record for Team's Most Hits (27) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:16:00 PM] - New Record for Team's Most Shots (32) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:15:32 PM] - New Record for Team's Most Shots Blocked (8) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:14:52 PM] - New Record for Team's Most Hits (25) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:14:41 PM] - New Record for Team's Most Shots Blocked (7) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:14:13 PM] - New Record for Team's Most Hits (24) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:14:13 PM] - New Record for Team's Most Points (13) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:14:13 PM] - New Record for Team's Most Assists (8) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:14:13 PM] - New Record for Team's Most Goals (5) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:14:05 PM] - New Record for Team's Most Penalties Minutes (29) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:13:57 PM] - New Record for Team's Most Penalties Minutes (27) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:13:57 PM] - New Record for Team's Most Shots Blocked (6) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:13:54 PM] - New Record for Team's Most Penalties Minutes (12) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:13:54 PM] - New Record for Team's Most Shots Blocked (1) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:13:54 PM] - New Record for Team's Most Shots (30) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:13:54 PM] - New Record for Team's Most Points (11) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:13:54 PM] - New Record for Team's Most Assists (7) in 1 Game for Pittsburgh Penguins!
[5/13/2017 12:13:54 PM] - New Record for Team's Most Goals (4) in 1 Game for Pittsburgh Penguins!

[5/23/2018 9:37:50 PM] Pittsburgh Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/20/2018 2:22:50 PM] Both Pittsburgh Penguins and Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 2:21:34 PM] Pittsburgh Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 2:21:32 PM] Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 2:21:30 PM] Both Pittsburgh Penguins and Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 2:21:26 PM] Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 2:21:25 PM] Pittsburgh Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 2:21:22 PM] Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 2:21:20 PM] Pittsburgh Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 2:21:16 PM] Both Pittsburgh Penguins and Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 2:21:12 PM] Pittsburgh Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 2:21:11 PM] Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 2:21:09 PM] Pittsburgh Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 1:27:46 PM] Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 1:27:44 PM] Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 1:27:41 PM] Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 1:27:41 PM] Last 7 Days Farm Star : 1 - Matt Puempel of Binghamton Senators (4-1-5) / 2 - Paul Thompson of Abbotsford Heat (1-3-4) / 3 - Justin Shugg of Wilkes-Barre/Scranton Penguins (3-1-4)
[5/13/2017 1:27:39 PM] Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 1:27:36 PM] Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 1:27:30 PM] Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 1:07:19 PM] Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 1:07:14 PM] Both Pittsburgh Penguins and Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 1:07:08 PM] Pittsburgh Penguins lines for next game are empty. Current rosters/lines are not erased.
[5/13/2017 1:07:03 PM] Wilkes-Barre/Scranton Penguins lines for next game are empty. Current rosters/lines are not erased.

No Injury or Suspension.

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
1	44	20	17	0	2	0	4	1	89	78	11	22	10	9	0	1	0	2	0	40	32	8	22	10	8	0	1	0	2	1	49	46	3	40	89	146	235	0	8	29	21	33	8	806	262	273	263	21	796	217	593	731	204	18	8.82%	233	22	90.56%	1	633	1224	51.72%	618	1235	50.04%	275	557	49.37%	1054	730	1074	328	541	263
2	62	29	20	0	1	5	4	3	129	112	17	31	15	9	0	1	3	2	1	65	49	16	31	14	11	0	0	2	2	2	64	63	1	58	129	221	350	0	9	41	49	34	5	1191	370	428	375	38	1047	294	747	1009	318	38	11.95%	322	30	90.68%	2	942	1748	53.89%	886	1669	53.09%	420	812	51.72%	1512	1047	1482	463	769	384
3	78	29	35	0	2	0	5	7	160	157	3	39	13	20	0	0	0	1	5	65	78	-13	39	16	15	0	2	0	4	2	95	79	16	58	160	264	424	0	11	53	52	48	14	1414	439	465	498	55	1357	385	880	1258	384	45	11.72%	364	44	87.91%	2	1108	2099	52.79%	1074	2048	52.44%	517	993	52.06%	1896	1321	1881	580	964	475
4	14	5	7	0	0	0	0	2	27	35	-8	7	4	1	0	0	0	0	2	16	13	3	7	1	6	0	0	0	0	0	11	22	-11	10	27	48	75	1	2	11	6	10	0	256	84	80	87	10	237	70	174	239	74	5	6.76%	68	10	85.29%	0	187	383	48.83%	174	348	50.00%	89	191	46.60%	337	233	336	104	176	88
4	9	2	5	0	1	0	0	1	14	22	-8	4	2	1	0	0	0	0	1	4	4	0	5	0	4	0	1	0	0	0	10	18	-8	7	14	24	38	0	2	5	3	5	1	170	59	47	57	9	164	55	122	144	45	3	6.67%	47	7	85.11%	0	120	235	51.06%	120	240	50.00%	50	111	45.05%	207	142	229	67	110	54
Total Regular Season	207	85	84	0	6	5	13	14	419	404	15	103	44	40	0	2	3	5	9	190	176	14	104	41	44	0	4	2	8	5	229	228	1	173	419	703	1122	1	32	139	131	130	28	3837	1214	1293	1280	133	3601	1021	2516	3381	1025	109	10.63%	1034	113	89.07%	5	2990	5689	52.56%	2872	5540	51.84%	1351	2664	50.71%	5008	3475	5004	1544	2560	1265
Playoff
1	13	6	7	0	0	0	0	0	21	22	-1	6	4	2	0	0	0	0	0	9	7	2	7	2	5	0	0	0	0	0	12	15	-3	12	21	36	57	0	4	6	9	5	1	298	91	94	81	32	253	96	165	223	56	3	5.36%	77	7	90.91%	1	197	417	47.24%	188	385	48.83%	91	180	50.56%	339	235	374	107	175	86
2	17	8	9	0	0	0	0	0	29	36	-7	8	4	4	0	0	0	0	0	15	18	-3	9	4	5	0	0	0	0	0	14	18	-4	16	29	48	77	0	1	9	10	9	1	333	93	96	107	37	358	119	235	321	76	6	7.89%	98	6	93.88%	2	239	487	49.08%	270	554	48.74%	125	260	48.08%	431	299	501	144	235	110
Total Playoff	30	14	16	0	0	0	0	0	50	58	-8	14	8	6	0	0	0	0	0	24	25	-1	16	6	10	0	0	0	0	0	26	33	-7	28	50	84	134	0	5	15	19	14	2	631	184	190	188	69	611	215	400	544	132	9	6.82%	175	13	92.57%	3	436	904	48.23%	458	939	48.78%	216	440	49.09%	771	534	875	252	410	196

Year	R1	R2	R3	R4	R5
5	PIT	PIT	PIT	PIT	PIT
6	PIT	PIT	PIT	PIT	PIT
7	PIT	PIT	PIT	PIT	PIT
8	PIT	PIT	PIT	PIT	PIT
9	PIT	PIT	PIT	PIT	PIT

Year	R1	R2	R3	R4	R5
5	PIT	PIT	PIT	PIT	PIT
6	PIT	PIT	PIT	PIT	PIT
7	PIT	PIT	PIT	PIT	PIT
8	PIT	PIT	PIT	PIT	PIT
9	PIT	PIT	PIT	PIT	PIT

Year	R1	R2	R3	R4	R5
5	PIT	PIT	PIT	PIT	PIT
6	PIT	PIT	PIT	PIT	PIT
7	PIT	PIT	PIT	PIT	PIT
8	PIT	PIT	PIT	PIT	PIT
9	PIT	PIT	PIT	PIT	PIT