Rochester Americans
Home
Roster
Players Stats
Players Info
Lines
Team Stats
Schedule
Finance
Depth
News
History
Injury / Suspension
Web Roster Editor
Web Lines Editor

Game Center
	New Jersey Devils 9-7-2, 28pts	4	Box score	2	Pittsburgh Penguins 9-9-0, 23pts

Team Stats
W2	Streak	W1
4-4-2	Home Record	3-6-0
5-3-0	Away Record	6-3-0
6-3-1	Last 10 Games	6-4-0
2.50	Goals Per Game	2.83
2.39	Goals Against Per Game	3.00
11.11%	Power Play Percentage	12.90%
85.29%	Penalty Kill Percentage	79.45%

Pittsburgh Penguins
9-9-0, 23pts

Box score

New York Rangers
6-8-4, 21pts

Team Stats
W1	Streak	L2
3-6-0	Home Record	1-6-2
6-3-0	Away Record	5-2-2
6-4-0	Last 10 Games	4-5-1
2.83	Goals Per Game	2.28
3.00	Goals Against Per Game	3.11
12.90%	Power Play Percentage	20.83%
79.45%	Penalty Kill Percentage	84.13%

Pittsburgh Penguins
9-9-0, 23pts

Day 48

New York Islanders
8-9-1, 23pts

Team Stats
W1	Streak	W1
3-6-0	Home Record	3-4-1
6-3-0	Away Record	5-5-0
6-4-0	Last 10 Games	5-5-0
2.83	Goals Per Game	2.28
3.00	Goals Against Per Game	2.28
12.90%	Power Play Percentage	15.49%
79.45%	Penalty Kill Percentage	80.65%

Pittsburgh Penguins
9-9-0, 23pts

Day 50

Carolina Hurricanes
13-4-1, 36pts

Team Stats
W1	Streak	W2
3-6-0	Home Record	5-2-1
6-3-0	Away Record	8-2-0
6-4-0	Last 10 Games	7-2-1
2.83	Goals Per Game	2.72
3.00	Goals Against Per Game	2.72
12.90%	Power Play Percentage	18.84%
79.45%	Penalty Kill Percentage	92.16%

Florida Panthers
9-8-1, 27pts

Day 53

Pittsburgh Penguins
9-9-0, 23pts

Team Stats
W1	Streak	W1
5-4-0	Home Record	3-6-0
4-4-1	Away Record	6-3-0
6-3-1	Last 10 Games	6-4-0
2.56	Goals Per Game	2.83
2.67	Goals Against Per Game	2.83
20.25%	Power Play Percentage	12.90%
82.61%	Penalty Kill Percentage	79.45%

Team Leaders
Goals Matt Boldy 8			Assists Kasperi Kapanen 14

Points Kasperi Kapanen 17			Plus/Minus Vladislav Gavrikov 6

Wins Connor Hellebuyck 7			Save Percentage Petr Mrazek 0.908

Team Stats
Goals For 51 2.83 GFG	Shots For 559 31.06 Avg	Power Play Percentage 12.9% 8 GF	Offensive Zone Start 38.7%
Goals Against 54 3.00 GAA	Shots Against 535 29.72 Avg	Penalty Kill Percentage 79.5%% 15 GA	Defensive Zone Start 37.0%

Team Info
	General Manager	Jeff
	Division	Northeast Division
	Conference	Eastern Conference
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Name	PPG Paints Arena
	Capacity	18,000
	Attendance	14,473
	Season Tickets	7,740
Roster Info
	Pro Team	21
	Farm Team	28
	Contract Limit	49 / 250
	Prospects	62
Finance
	Year to Date Revenue	9,529,388$
	Year To Date Expenses	16,170,255$
	Estimated Season Revenue	32,823,448$
	Estimated Season Expenses	51,385,477$
	Current Bank Account	133,291,189$
	Projected Bank Account	115,007,733$

Show or Hide Columns

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	TA	SP	Age	Contract	Salary
1	Jake Guentzel	0		X			99.00	92	44	83	96	55	90	92	88	69	86	91	72	89	74	80	55	40	81		0	30	1	5,250,000$
2	Jack Hughes	0		X			100.00	58	38	91	96	58	93	99	91	75	91	90	66	92	88	74	40	40	81		0	24	1	4,680,000$
3	Jordan Kyrou	0			X		100.00	57	45	84	88	75	88	93	89	67	90	90	70	87	74	74	55	40	80		0	27	1	7,500,000$
4	Kasperi Kapanen	0	X				99.00	78	44	85	91	70	86	86	83	79	90	90	70	82	77	79	55	40	80		0	28	1	7,500,000$
5	Matt Boldy	0		X			100.00	63	52	85	84	75	89	95	85	70	85	90	72	85	69	78	55	40	79		0	24	1	4,680,000$
6	Seth Jarvis (R)	0			X		99.00	81	42	86	99	53	92	94	78	73	83	85	70	83	67	70	55	40	78		0	23	2	4,680,000$
7	Ryan Nugent-Hopkins	0	X				99.00	56	43	95	94	67	90	95	81	90	81	81	71	79	80	77	55	40	77		0	32	1	3,600,000$
8	Joel Eriksson Ek	0	X				99.00	89	50	84	76	82	89	90	74	92	80	78	75	73	77	84	55	40	76		0	28	2	1,350,000$
9	Nick Ritchie	0			X		100.00	92	64	68	62	93	84	84	73	70	77	71	71	67	78	78	55	40	72		0	29	2	550,000$
10	Rasmus Asplund	0			X		100.00	61	45	84	82	73	81	80	66	67	69	73	73	71	72	74	55	40	70		0	27	2	500,000$
11	Tom Kuhnhackl	0		X			100.00	76	43	76	74	72	80	75	69	63	73	69	65	69	81	67	55	40	69		0	33	1	850,000$
12	Dominic Toninato	0	X				100.00	78	47	74	72	76	77	79	64	78	67	65	70	66	80	72	55	40	68		0	31	2	500,000$
13	Josh Morrissey	0				X	99.00	93	46	78	85	80	98	98	79	69	84	74	88	73	79	74	55	40	82		0	30	3	4,285,715$
14	Brandon Carlo	0				X	100.00	91	58	90	77	99	89	94	75	74	83	67	84	66	77	89	55	40	80		0	28	1	3,000,000$
15	Martin Fehervary	0				X	100.00	99	50	84	83	85	91	99	75	50	77	70	83	69	71	86	55	40	80	N	0	25	1	3,480,000$
16	Calen Addison	0				X	100.00	59	38	85	99	63	82	90	82	53	87	73	72	78	73	75	55	40	76		0	25	1	700,000$
17	Vladislav Gavrikov	0				X	100.00	73	52	87	73	93	85	86	73	50	75	67	82	66	78	75	55	40	75		0	29	1	1,350,000$
18	Jonas Siegenthaler	0				X	100.00	62	55	84	73	95	81	84	70	50	73	66	80	64	77	84	55	40	74		0	28	1	1,200,000$
Scratches
1	Juuso Valimaki	0				X	100.00	58	53	81	75	89	79	82	73	50	76	64	76	64	71	70	55	40	72		0	26	3	500,000$
Farm Team
1	Kirill Marchenko (R)	0			X		99.00	59	42	84	84	75	90	82	80	60	82	85	71	81	70	80	55	40	76		0	24	3	800,000$
2	Marco Rossi (R)	0	X				100.00	61	40	83	89	55	89	89	75	82	80	78	64	78	68	78	55	40	74		0	23	3	1,750,000$
3	Ridly Greig (R)	0	X				99.00	88	49	66	89	69	85	93	69	80	73	75	77	75	65	68	55	40	74		0	22	2	1,000,000$
4	Bobby Brink (R)	0		X			99.00	58	33	84	93	50	83	83	69	73	73	77	71	76	68	69	55	40	72		0	23	2	1,000,000$
5	Matt Coronato (R)	0			X		100.00	55	45	83	88	61	88	80	71	70	72	77	70	77	65	75	55	40	72		0	22	3	1,500,000$
6	Axel Jonsson-Fjallby	0		X			100.00	69	44	79	75	73	77	85	63	58	66	65	72	67	76	77	55	40	68		0	27	1	800,000$
7	Dominik Simon	0		X			100.00	75	44	75	77	64	75	76	65	67	69	69	67	69	78	66	55	40	68		0	30	1	560,000$
8	Jiri Kulich (R)	0	X				100.00	56	35	78	89	58	80	80	63	77	68	71	64	72	63	63	55	40	68		0	21	3	1,250,000$
9	Greg McKegg	0	X				100.00	64	46	75	68	67	77	76	64	79	68	64	63	65	81	72	55	40	66		0	33	1	500,000$
10	Oskar Sundqvist	0		X			100.00	70	50	76	68	79	72	72	63	75	67	64	65	65	77	70	55	40	66		0	31	2	500,000$
11	Martin Frk	0			X		100.00	58	46	75	65	78	75	69	62	55	63	66	65	65	78	70	55	40	65		0	31	1	700,000$
12	Trey Fix-Wolansky	0			X		100.00	57	35	80	77	57	70	70	60	52	62	61	73	64	75	69	55	40	65		0	26	2	600,000$
13	Joe Morrow	0				X	99.00	67	47	86	71	90	80	82	72	50	73	66	76	63	80	83	55	40	73		0	32	1	950,000$
14	Kris Letang	0				X	100.00	81	50	67	66	90	81	82	63	50	67	59	72	57	88	86	55	40	72		0	38	1	650,000$
15	Nick DeSimone	0				X	100.00	60	44	81	74	77	71	79	70	50	72	64	74	62	79	79	55	40	70		0	30	3	800,000$
16	NICLAS ALMARI	0				X	99.00	55	45	82	78	76	60	60	65	48	73	63	84	62	72	82	52	40	70		0	27	1	250,000$
17	Paul LaDue	0				X	100.00	71	48	78	68	83	71	71	66	50	67	62	66	60	79	72	55	40	67		0	32	1	650,000$
18	Juuso Riikola	0				X	100.00	88	40	82	74	50	69	71	62	50	64	61	67	58	78	67	55	40	66		0	31	2	500,000$
19	Dennis Rasmussen	0	X				100.00	60	47	81	64	77	73	81	61	77	64	63	65	62	81	76	55	40	65		0	34	1	750,000$
20	Tomas Nosek	0	X				100.00	59	47	75	64	81	76	78	60	72	66	64	68	62	78	68	55	40	65		0	32	2	700,000$
21	Jack Studnicka	0		X			100.00	73	42	79	70	75	72	80	60	69	56	61	67	63	75	68	55	40	64		0	26	2	700,000$
22	Kyle Criscuolo	0			X		100.00	60	35	75	77	50	68	77	57	61	66	61	68	63	79	60	55	40	64		0	33	1	675,000$
23	EETU PELTOLA	0				X	100.00	56	48	74	69	86	60	60	62	48	69	63	74	59	69	69	52	40	66		0	25	1	275,000$
24	Jack Rathbone	0				X	100.00	54	35	81	84	58	68	76	61	50	61	61	64	62	73	70	55	40	65		0	26	1	600,000$
25	Ethan Prow	0				X	100.00	51	40	84	75	60	65	73	60	50	56	62	65	59	78	72	55	40	64		0	32	1	650,000$
26	Ashton Sautner	0				X	100.00	67	15	82	76	55	68	67	60	50	60	59	64	58	65	60	75	40	63		0	31	1	650,000$

	TEAM AVERAGE						99.76	69	44	81	79	72	80	82	70	64	73	71	71	69	75	74	55	40	72

Show or Hide Columns

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
1	Connor Hellebuyck	0	100.00	74	87	87	86	83	85	86	84	84	85	84	81	68	55	40	81	0	32	3	7,000,000$
2	Petr Mrazek	0	98.00	82	82	85	82	84	84	85	84	87	84	83	82	68	55	40	80	0	33	2	3,600,000$
Scratches
Farm Team
1	Reto Berra	0	96.00	70	65	70	86	77	81	81	78	77	81	79	89	70	55	40	76	0	38	1	1,050,000$
2	STEFANOS LEKKAS	0	100.00	79	60	60	74	78	77	78	78	78	77	78	74	62	52	40	72	0	29	1	275,000$

	TEAM AVERAGE		98.50	76	74	76	82	81	82	83	81	82	82	81	82	67	54	40	77

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

Show or Hide Columns

Filter Tips

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Player Name	Team Name	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	GA	TA	EG	P/20	PSS	FW	FL	FT	S1	S2	S3
1	Kasperi Kapanen	Pittsburgh Penguins	C	18	3	14	17	-5	13	5	23	25	49	8	17	6.12%	7	292	16.26	1	5	6	9	52	0	0	0	1	2	2	1	48.08%	287	7	6	0	1.16	0	0	0	1	1	0	0
2	Matt Boldy	Pittsburgh Penguins	LW	18	8	9	17	5	29	15	12	32	66	22	46	12.12%	5	353	19.67	0	0	0	1	44	0	3	3	6	59	0	0	45.00%	20	9	7	0	0.96	0	3	0	0	1	2	0
3	Jake Guentzel	Pittsburgh Penguins	LW	18	4	10	14	-3	8	0	37	23	45	13	33	8.89%	9	317	17.65	2	5	7	8	54	0	0	0	3	21	0	0	30.43%	23	14	7	0	0.88	0	0	0	0	1	0	1
4	Jack Hughes	Pittsburgh Penguins	LW	18	6	8	14	-3	0	0	11	19	53	18	45	11.32%	5	291	16.18	3	3	6	7	54	0	0	0	0	0	2	0	60.00%	10	11	3	0	0.96	0	0	0	0	1	0	1
5	Joel Eriksson Ek	Pittsburgh Penguins	C	18	6	5	11	4	33	15	34	31	36	15	20	16.67%	9	351	19.52	0	0	0	1	43	1	1	2	3	64	2	0	49.17%	421	3	4	0	0.63	0	0	2	1	0	1	0
6	Josh Morrissey	Pittsburgh Penguins	D	18	3	6	9	2	52	10	56	30	40	10	13	7.50%	21	448	24.89	2	1	3	8	59	1	2	3	3	55	0	2	0%	0	8	21	0	0.40	0	1	0	1	0	1	2
7	Ryan Nugent-Hopkins	Pittsburgh Penguins	C	18	4	5	9	4	0	0	12	30	32	7	23	12.50%	7	334	18.57	0	0	0	3	60	0	2	2	7	32	1	0	54.11%	231	4	5	1	0.54	0	0	0	0	1	2	0
8	Seth Jarvis	Pittsburgh Penguins	RW	18	4	4	8	-7	10	0	23	21	36	17	19	11.11%	4	285	15.84	0	0	0	0	39	0	0	0	0	0	0	0	60.00%	10	4	3	0	0.56	0	0	0	0	0	0	1
9	Jordan Kyrou	Pittsburgh Penguins	RW	18	3	4	7	0	6	0	17	20	41	8	22	7.32%	5	288	16.00	0	0	0	3	45	0	0	0	0	0	1	0	25.00%	8	11	8	0	0.49	0	0	0	0	1	2	0
10	Rasmus Asplund	Pittsburgh Penguins	RW	18	3	3	6	3	4	0	10	12	18	4	14	16.67%	8	243	13.51	0	0	0	0	1	0	0	0	0	0	1	0	50.00%	12	4	3	0	0.49	0	0	0	0	0	0	0
11	Calen Addison	Pittsburgh Penguins	D	18	0	4	4	-5	0	0	9	20	17	9	11	0%	18	285	15.84	0	0	0	1	41	0	0	0	0	3	0	0	0%	0	10	8	0	0.28	0	0	0	0	0	0	0
12	Martin Fehervary	Pittsburgh Penguins	D	18	0	4	4	1	12	0	44	29	17	7	13	0%	24	340	18.93	0	0	0	0	2	0	0	0	0	37	0	0	0%	0	6	9	0	0.23	0	0	0	0	0	0	0
13	Nick Ritchie	Pittsburgh Penguins	RW	18	3	1	4	1	27	5	27	12	24	7	13	12.50%	6	181	10.08	0	0	0	0	7	2	0	2	4	30	0	0	77.78%	9	3	2	0	0.44	0	0	0	1	1	1	0
14	Tom Kuhnhackl	Pittsburgh Penguins	LW	18	3	1	4	2	27	5	12	5	21	7	11	14.29%	1	139	7.73	0	0	0	0	4	1	0	1	3	3	0	0	100.00%	1	1	0	0	0.57	0	0	0	1	1	0	0
15	Vladislav Gavrikov	Pittsburgh Penguins	D	18	0	4	4	6	11	5	9	25	14	7	3	0%	22	321	17.87	0	0	0	0	0	0	0	0	0	38	0	0	0%	0	2	8	0	0.25	0	0	0	1	0	0	0
16	Brandon Carlo	Pittsburgh Penguins	D	18	0	3	3	4	2	0	25	42	25	11	9	0%	21	392	21.83	0	0	0	0	2	0	0	0	2	71	0	0	0%	0	1	17	0	0.15	1	0	0	0	0	0	0
17	Jonas Siegenthaler	Pittsburgh Penguins	D	18	0	2	2	-4	2	0	7	23	17	3	4	0%	13	263	14.63	0	0	0	0	0	0	1	1	2	24	0	0	0%	0	3	11	0	0.15	0	0	0	0	0	0	0
18	Dominic Toninato	Pittsburgh Penguins	C	18	1	0	1	2	11	5	9	16	8	2	11	12.50%	4	156	8.68	0	0	0	0	2	0	0	0	0	15	0	0	44.23%	52	2	1	0	0.13	0	0	0	1	0	0	0
Team Total or Average				324	51	87	138	7	247	65	377	415	559	175	327	9.12%	189	5286	16.32	8	14	22	41	518	5	9	14	34	460	9	3	49.54%	1084	103	123	1	0.52	1	4	2	7	8	9	5

Show or Hide Columns

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	PCT	GAA	MP	PIM	GA	SA	SAR	PS %	ST	BG	S1	S2
1	Connor Hellebuyck	Pittsburgh Penguins	11	7	4	0.893	3.18	661	2	35	328	136	0	11	7	1	0
2	Petr Mrazek	Pittsburgh Penguins	7	2	5	0.908	2.72	419	0	19	207	108	0	7	11	1	1
Team Total or Average			18	9	9	0.899	3.00	1081	2	54	535	244		18	18	2	1

Show or Hide Columns

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	Country	Rookie	Weight	Height	No Trade	Available For Trade	Acquired By	Force Waivers	Waiver Possible	Contract	Contract Signature Date	Force UFA	Emergency Recall	Type	Current Salary	Salary Remaining	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Salary Year 2	Salary Year 3	Salary Year 4	Salary Year 5	Salary Year 6	Salary Year 7	Salary Year 8	Salary Year 9	Salary Year 10	Salary Cap Year 2	Salary Cap Year 3	Salary Cap Year 4	Salary Cap Year 5	Salary Cap Year 6	Salary Cap Year 7	Salary Cap Year 8	Salary Cap Year 9	Salary Cap Year 10	No Trade Year 2	No Trade Year 3	No Trade Year 4	No Trade Year 5	No Trade Year 6	No Trade Year 7	No Trade Year 8	No Trade Year 9	No Trade Year 10	Link
Brandon Carlo (1 Way Contract)	Pittsburgh Penguins	D	28	1996-11-26	USA	No	216 Lbs	6 ft5	No	No	Assign Manually	No	No	1	2025-09-30	False	False	Pro & Farm	3,000,000$	2,281,915$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Calen Addison	Pittsburgh Penguins	D	25	2000-04-11	CAN	No	172 Lbs	5 ft11	No	No	Assign Manually	No	No	1	2025-09-30	False	False	Pro & Farm	700,000$	532,447$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Connor Hellebuyck (1 Way Contract)	Pittsburgh Penguins	G	32	1993-05-19	USA	No	207 Lbs	6 ft4	No	No	Free Agent	No	No	3	2025-10-03	False	False	Pro & Farm	7,000,000$	5,324,468$	0$	0$	No	7,000,000$	7,000,000$	-	-	-	-	-	-	-	7,000,000$	7,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Dominic Toninato	Pittsburgh Penguins	C	31	1994-03-09	USA	No	201 Lbs	6 ft2	No	No	Assign Manually	No	No	2	2025-09-30	False	False	Pro & Farm	500,000$	380,319$	0$	0$	No	500,000$	-	-	-	-	-	-	-	-	500,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Jack Hughes (1 Way Contract)	Pittsburgh Penguins	LW	24	2001-05-14	USA	No	176 Lbs	5 ft11	No	No	Prospect	No	No	1	2025-09-30	False	False	Pro & Farm	4,680,000$	3,559,787$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Jake Guentzel (1 Way Contract)	Pittsburgh Penguins	LW	30	1994-10-06	USA	No	181 Lbs	5 ft11	No	No	Assign Manually	No	No	1	2025-09-30	False	False	Pro & Farm	5,250,000$	3,993,351$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Joel Eriksson Ek	Pittsburgh Penguins	C	28	1997-01-29	SWE	No	207 Lbs	6 ft2	No	No	Assign Manually	No	No	2	2025-09-30	False	False	Pro & Farm	1,350,000$	1,026,862$	0$	0$	No	1,350,000$	-	-	-	-	-	-	-	-	1,350,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Jonas Siegenthaler	Pittsburgh Penguins	D	28	1997-05-06	CHE	No	218 Lbs	6 ft2	No	No	Assign Manually	No	No	1	2025-09-30	False	False	Pro & Farm	1,200,000$	912,766$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Jordan Kyrou (1 Way Contract)	Pittsburgh Penguins	RW	27	1998-05-05	CAN	No	174 Lbs	6 ft0	No	No	Free Agent	No	No	1	2025-10-13	False	False	Pro & Farm	7,500,000$	5,704,787$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Josh Morrissey (1 Way Contract)	Pittsburgh Penguins	D	30	1995-03-28	CAN	No	194 Lbs	6 ft0	No	No	Assign Manually	No	No	3	2025-09-30	False	False	Pro & Farm	4,285,715$	3,259,879$	0$	0$	No	4,285,715$	4,285,715$	-	-	-	-	-	-	-	4,285,715$	4,285,715$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Juuso Valimaki	Pittsburgh Penguins	D	26	1998-10-06	FIN	No	212 Lbs	6 ft2	No	No	Assign Manually	No	No	3	2025-09-30	False	False	Pro & Farm	500,000$	380,319$	0$	0$	No	500,000$	500,000$	-	-	-	-	-	-	-	500,000$	500,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Kasperi Kapanen (1 Way Contract)	Pittsburgh Penguins	C	28	1996-07-23	FIN	No	194 Lbs	6 ft1	No	No	Assign Manually	No	No	1	2025-09-30	False	False	Pro & Farm	7,500,000$	5,704,787$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Martin Fehervary (1 Way Contract)	Pittsburgh Penguins	D	25	1999-10-06	SVK	No	203 Lbs	6 ft2	Yes	No	Free Agent	No	No	1	2025-10-19	False	False	Pro Only	3,480,000$	2,647,021$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Matt Boldy (1 Way Contract)	Pittsburgh Penguins	LW	24	2001-04-05	USA	No	201 Lbs	6 ft2	No	No	Assign Manually	No	No	1	2025-09-30	False	False	Pro & Farm	4,680,000$	3,559,787$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Nick Ritchie	Pittsburgh Penguins	RW	29	1995-12-05	CAN	No	236 Lbs	6 ft3	No	No	Free Agent	No	No	2	2025-11-01	False	False	Pro & Farm	550,000$	418,351$	0$	0$	No	550,000$	-	-	-	-	-	-	-	-	550,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-
Petr Mrazek (1 Way Contract)	Pittsburgh Penguins	G	33	1992-02-14	CZE	No	187 Lbs	6 ft2	No	No	Free Agent	No	No	2	2025-10-03	False	False	Pro & Farm	3,600,000$	2,738,298$	0$	0$	No	3,600,000$	-	-	-	-	-	-	-	-	3,600,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Rasmus Asplund	Pittsburgh Penguins	RW	27	1997-12-03	SWE	No	185 Lbs	5 ft11	No	No	Assign Manually	No	No	2	2025-09-30	False	False	Pro & Farm	500,000$	380,319$	0$	0$	No	500,000$	-	-	-	-	-	-	-	-	500,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Ryan Nugent-Hopkins (1 Way Contract)	Pittsburgh Penguins	C	32	1993-04-12	CAN	No	194 Lbs	6 ft0	No	No	Assign Manually	No	No	1	2025-09-30	False	False	Pro & Farm	3,600,000$	2,738,298$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Seth Jarvis (1 Way Contract)	Pittsburgh Penguins	RW	23	2002-02-01	CAN	Yes	174 Lbs	5 ft10	No	No	Prospect	No	No	2	2025-10-07	False	False	Pro & Farm	4,680,000$	3,559,787$	0$	0$	No	4,680,000$	-	-	-	-	-	-	-	-	4,680,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Tom Kuhnhackl	Pittsburgh Penguins	LW	33	1992-01-21	DEU	No	196 Lbs	6 ft2	No	No	Free Agent	No	No	1	2025-10-24	False	False	Pro & Farm	850,000$	646,543$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
Vladislav Gavrikov	Pittsburgh Penguins	D	29	1995-11-21	RUS	No	214 Lbs	6 ft3	No	No	Assign Manually	No	No	1	2025-09-30	False	False	Pro & Farm	1,350,000$	1,026,862$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
21	28.19	197 Lbs	6 ft1	1.57	3,178,844$

Sum Year 1 Salary	Sum Year 2 Salary	Sum Year 3 Salary	Sum Year 4 Salary	Sum Year 5 Salary
66,755,715$	22,965,715$	11,785,715$	0$	0$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Jake Guentzel	Kasperi Kapanen	Seth Jarvis	31	0	0	5
2	Jack Hughes	Ryan Nugent-Hopkins	Jordan Kyrou	31	0	0	5
3	Matt Boldy	Joel Eriksson Ek	Rasmus Asplund	31	0	0	5
4	Tom Kuhnhackl	Dominic Toninato	Nick Ritchie	7	0	2	3

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Josh Morrissey	Brandon Carlo	40	0	2	3
2	Martin Fehervary	Vladislav Gavrikov	34	0	2	3
3	Jonas Siegenthaler	Calen Addison	26	0	2	3
4	Jonas Siegenthaler	Calen Addison	0	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Jake Guentzel	Kasperi Kapanen	Jack Hughes	60	0	0	5
2	Matt Boldy	Joel Eriksson Ek	Jordan Kyrou	40	0	0	5

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Ryan Nugent-Hopkins	Josh Morrissey	60	0	1	4
2	Seth Jarvis	Calen Addison	40	0	1	4

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Joel Eriksson Ek	Matt Boldy	60	0	4	1
2	Ryan Nugent-Hopkins	Nick Ritchie	40	0	4	1

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Josh Morrissey	Brandon Carlo	60	1	4	0
2	Martin Fehervary	Vladislav Gavrikov	40	1	4	0

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Joel Eriksson Ek	60	0	5	0	Josh Morrissey	Brandon Carlo	60	1	4	0
2	Ryan Nugent-Hopkins	40	0	5	0	Martin Fehervary	Vladislav Gavrikov	40	1	4	0

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Joel Eriksson Ek	Seth Jarvis	60	0	1	4
2	Ryan Nugent-Hopkins	Matt Boldy	40	0	1	4

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Josh Morrissey	Martin Fehervary	60	0	2	3
2	Calen Addison	Brandon Carlo	40	0	2	3

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Jack Hughes	Kasperi Kapanen	Jake Guentzel	Ryan Nugent-Hopkins	Josh Morrissey

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Jake Guentzel	Ryan Nugent-Hopkins	Jordan Kyrou	Brandon Carlo	Josh Morrissey

Extra Forwards
Normal	PowerPlay	Penalty Kill
Nick Ritchie, Matt Boldy, Jordan Kyrou	Nick Ritchie, Jordan Kyrou	Matt Boldy

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Jonas Siegenthaler, Calen Addison, Vladislav Gavrikov	Martin Fehervary	Jonas Siegenthaler, Vladislav Gavrikov

Penalty Shots
Jack Hughes, Jake Guentzel, Jordan Kyrou, Matt Boldy, Seth Jarvis

Goalie
#1 : Petr Mrazek, #2 : Connor Hellebuyck

Custom OT Lines Forwards
Kasperi Kapanen, Jack Hughes, Ryan Nugent-Hopkins, Jake Guentzel, Joel Eriksson Ek, Matt Boldy, Seth Jarvis, Jordan Kyrou, Dominic Toninato, Nick Ritchie

Custom OT Lines Defensemen
Josh Morrissey, Calen Addison, Brandon Carlo, Martin Fehervary, Vladislav Gavrikov

Show or Hide Columns

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	Boston Bruins	1	1	0	0	0	0	0	0	4	2	2	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	4	2	2	3	1.000	4	6	10	0	0	0	0	4	0	26	10	6	10	0	29	11	13	13	6	1	16.67%	4	0	100.00%	0	213	416	51.20%	192	398	48.24%	132	262	50.38%	20	10	22	9	16	8
2	Carolina Hurricanes	1	0	1	0	0	0	0	0	2	3	-1	1	0	1	0	0	0	0	0	2	3	-1	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	3	5	0	0	0	0	2	0	31	7	14	10	0	32	10	18	32	3	0	0.00%	4	2	50.00%	0	213	416	51.20%	192	398	48.24%	132	262	50.38%	23	14	18	8	17	8
3	Chicago Blackhawks	1	0	1	0	0	0	0	0	1	3	-2	1	0	1	0	0	0	0	0	1	3	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	1	2	3	0	0	0	0	1	0	19	6	5	8	0	32	11	10	20	1	0	0.00%	5	0	100.00%	0	213	416	51.20%	192	398	48.24%	132	262	50.38%	19	9	22	9	18	8
4	Florida Panthers	1	0	1	0	0	0	0	0	3	4	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	3	4	-1	0	0.000	3	6	9	0	0	0	3	0	0	39	14	13	12	0	30	8	8	19	7	0	0.00%	4	2	50.00%	2	213	416	51.20%	192	398	48.24%	132	262	50.38%	21	11	20	9	18	10
5	Hamilton Mustangs	1	0	1	0	0	0	0	0	3	4	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	3	4	-1	0	0.000	3	5	8	0	0	1	0	2	0	36	12	11	13	0	33	15	6	17	5	1	20.00%	3	2	33.33%	0	213	416	51.20%	192	398	48.24%	132	262	50.38%	21	13	22	8	15	7
6	Montreal Canadiens	1	1	0	0	0	0	0	0	6	4	2	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	6	4	2	3	1.000	6	11	17	0	0	1	2	3	0	46	11	10	25	0	24	10	45	19	2	1	50.00%	5	2	60.00%	0	213	416	51.20%	192	398	48.24%	132	262	50.38%	23	14	20	7	16	8
7	New Jersey Devils	2	0	1	0	1	0	0	0	4	5	-1	1	0	1	0	0	0	0	0	2	4	-2	1	0	0	0	1	0	0	0	2	1	1	2	0.333	4	7	11	0	0	1	1	1	1	63	20	20	21	2	68	18	19	41	6	1	16.67%	8	0	100.00%	1	213	416	51.20%	192	398	48.24%	132	262	50.38%	41	23	44	17	35	17
8	New York Islanders	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	3	1.000	5	8	13	0	0	2	2	1	0	37	12	13	12	0	34	8	10	20	4	1	25.00%	5	1	80.00%	0	213	416	51.20%	192	398	48.24%	132	262	50.38%	22	14	21	8	15	7
9	New York Rangers	2	1	1	0	0	0	0	0	3	3	0	1	0	1	0	0	0	0	0	0	2	-2	1	1	0	0	0	0	0	0	3	1	2	3	0.500	3	6	9	0	0	1	2	0	0	52	20	23	9	0	51	19	17	35	9	1	11.11%	6	2	66.67%	0	213	416	51.20%	192	398	48.24%	132	262	50.38%	41	23	42	18	36	18
10	Ottawa Senators	1	0	0	0	1	0	0	0	5	4	1	1	0	0	0	1	0	0	0	5	4	1	0	0	0	0	0	0	0	0	0	0	0	2	0.667	5	7	12	0	0	3	0	1	1	28	14	6	5	3	34	9	27	17	2	0	0.00%	6	1	83.33%	0	213	416	51.20%	192	398	48.24%	132	262	50.38%	22	12	21	9	16	8
11	Philadelphia Flyers	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	1	2	0	0	0	0	1	0	27	9	9	9	0	26	12	11	13	3	0	0.00%	3	0	100.00%	0	213	416	51.20%	192	398	48.24%	132	262	50.38%	20	11	23	9	16	7
12	Quebec Nordiques	1	0	1	0	0	0	0	0	3	5	-2	1	0	1	0	0	0	0	0	3	5	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	3	5	8	0	0	1	0	2	0	37	10	7	20	0	33	7	9	33	4	1	25.00%	2	0	100.00%	0	213	416	51.20%	192	398	48.24%	132	262	50.38%	24	14	19	8	16	7
13	St Louis Blues	1	1	0	0	0	0	0	0	4	3	1	1	1	0	0	0	0	0	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	3	1.000	4	7	11	0	0	3	1	0	0	24	6	14	4	0	30	10	17	26	2	0	0.00%	6	1	83.33%	1	213	416	51.20%	192	398	48.24%	132	262	50.38%	21	12	21	9	17	8
14	Tampa Bay Lightning	1	0	1	0	0	0	0	0	2	4	-2	1	0	1	0	0	0	0	0	2	4	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	4	6	0	0	1	1	0	0	34	13	15	6	0	23	8	6	25	2	0	0.00%	3	1	66.67%	0	213	416	51.20%	192	398	48.24%	132	262	50.38%	24	15	18	7	16	8
15	Toronto Maple Leafs	1	0	0	0	1	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	2	1	1	2	0.667	2	3	5	0	0	0	0	1	1	25	3	11	10	1	28	19	23	22	3	0	0.00%	4	1	75.00%	1	213	416	51.20%	192	398	48.24%	132	262	50.38%	18	9	23	8	17	8
16	Winnipeg Jets	1	0	0	0	1	0	0	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	3	2	1	2	0.667	3	6	9	0	0	1	1	0	1	35	7	15	8	5	28	14	10	25	3	1	33.33%	5	0	100.00%	0	213	416	51.20%	192	398	48.24%	132	262	50.38%	24	14	19	8	17	8
	Total	18	5	9	0	4	0	0	0	51	54	-3	9	2	6	0	1	0	0	0	24	31	-7	9	3	3	0	3	0	0	0	27	23	4	23	0.426	51	87	138	0	0	15	13	19	4	559	174	192	182	11	535	189	249	377	62	8	12.90%	73	15	79.45%	5	213	416	51.20%	192	398	48.24%	132	262	50.38%	391	227	382	159	309	154
	_Since Last GM Reset	18	5	9	0	4	0	0	0	51	54	-3	9	2	6	0	1	0	0	0	24	31	-7	9	3	3	0	3	0	0	0	27	23	4	23	0.426	51	87	138	0	0	15	13	19	4	559	174	192	182	11	535	189	249	377	62	8	12.90%	73	15	79.45%	5	213	416	51.20%	192	398	48.24%	132	262	50.38%	391	227	382	159	309	154
	_Vs Conference	15	4	8	0	3	0	0	0	43	46	-3	7	1	5	0	1	0	0	0	19	25	-6	8	3	3	0	2	0	0	0	24	21	3	18	0.400	43	72	115	0	0	11	11	18	3	481	155	158	162	6	445	154	212	306	56	7	12.50%	57	14	75.44%	4	213	416	51.20%	192	398	48.24%	132	262	50.38%	325	190	319	131	256	129
	_Vs Division	6	1	3	0	2	0	0	0	20	22	-2	2	0	1	0	1	0	0	0	8	9	-1	4	1	2	0	1	0	0	0	12	13	-1	7	0.389	20	32	52	0	0	6	2	10	2	199	59	54	82	4	178	72	121	121	19	3	15.79%	23	6	73.91%	1	213	416	51.20%	192	398	48.24%	132	262	50.38%	130	77	130	51	99	48

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
18	23	W1	51	87	138	559	535	189	249	377	0	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
18	5	9	4	0	0	0	51	54

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
9	2	6	1	0	0	0	24	31

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
9	3	3	3	0	0	0	27	23

Last 10 Games
W	L	OTW	OTL	SOW	SOL
6	4	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
62	8	12.90%	73	15	79.45%	5

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
174	192	182	11	15	13	19	4

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
213	416	51.20%	192	398	48.24%	132	262	50.38%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
391	227	382	159	309	154

Last Played Games Show or Hide Columns

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	Link
1	3	Pittsburgh Penguins	6	Montreal Canadiens	4	W		Box score
3	17	Pittsburgh Penguins	3	Hamilton Mustangs	4	L		Box score
5	31	Pittsburgh Penguins	1	Philadelphia Flyers	4	L		Box score
7	45	Ottawa Senators	4	Pittsburgh Penguins	5	W	X	Box score
9	63	Tampa Bay Lightning	4	Pittsburgh Penguins	2	L		Box score
11	71	Pittsburgh Penguins	2	Toronto Maple Leafs	1	W	X	Box score
13	87	Quebec Nordiques	5	Pittsburgh Penguins	3	L		Box score
15	103	Chicago Blackhawks	3	Pittsburgh Penguins	1	L		Box score
17	114	St Louis Blues	3	Pittsburgh Penguins	4	W		Box score
19	128	Pittsburgh Penguins	3	Winnipeg Jets	2	W	X	Box score
23	147	Pittsburgh Penguins	4	Boston Bruins	2	W		Box score
26	160	Pittsburgh Penguins	3	Florida Panthers	4	L		Box score
29	174	Carolina Hurricanes	3	Pittsburgh Penguins	2	L		Box score
32	190	New York Islanders	3	Pittsburgh Penguins	5	W		Box score
36	208	New York Rangers	2	Pittsburgh Penguins	0	L		Box score
39	222	Pittsburgh Penguins	2	New Jersey Devils	1	W	X	Box score
42	236	New Jersey Devils	4	Pittsburgh Penguins	2	L		Box score
45	247	Pittsburgh Penguins	3	New York Rangers	1	W		Box score
48	261	Pittsburgh Penguins	-	New York Islanders	-
50	272	Pittsburgh Penguins	-	Carolina Hurricanes	-
53	286	Florida Panthers	-	Pittsburgh Penguins	-
56	302	Boston Bruins	-	Pittsburgh Penguins	-
60	320	Pittsburgh Penguins	-	Columbus Blue Jackets	-
62	331	Los Angeles Kings	-	Pittsburgh Penguins	-
64	344	Seattle Kraken	-	Pittsburgh Penguins	-
66	362	Pittsburgh Penguins	-	Vegas Golden Knights	-
68	367	Toronto Maple Leafs	-	Pittsburgh Penguins	-
70	387	Pittsburgh Penguins	-	Tampa Bay Lightning	-
72	402	Pittsburgh Penguins	-	Ottawa Senators	-
73	409	Philadelphia Flyers	-	Pittsburgh Penguins	-
77	433	Edmonton Oilers	-	Pittsburgh Penguins	-
79	447	Pittsburgh Penguins	-	Colorado Avalanche	-
81	461	Pittsburgh Penguins	-	Detroit Red Wings	-
83	468	New York Islanders	-	Pittsburgh Penguins	-
85	479	New York Rangers	-	Pittsburgh Penguins	-
88	495	Pittsburgh Penguins	-	New Jersey Devils	-
92	517	Pittsburgh Penguins	-	Anaheim Mighty Ducks	-
93	524	Anaheim Mighty Ducks	-	Pittsburgh Penguins	-
95	538	California Golden Seals	-	Pittsburgh Penguins	-
98	559	Pittsburgh Penguins	-	California Golden Seals	-
100	573	Pittsburgh Penguins	-	San Jose Sharks	-
102	587	Vancouver Canucks	-	Pittsburgh Penguins	-
105	601	Hamilton Mustangs	-	Pittsburgh Penguins	-
108	616	Montreal Canadiens	-	Pittsburgh Penguins	-
111	630	Pittsburgh Penguins	-	Quebec Nordiques	-
113	639	Pittsburgh Penguins	-	Boston Bruins	-
116	653	Pittsburgh Penguins	-	Florida Panthers	-
120	672	Carolina Hurricanes	-	Pittsburgh Penguins	-
122	679	Pittsburgh Penguins	-	Seattle Kraken	-
123	691	Pittsburgh Penguins	-	Los Angeles Kings	-
125	707	Columbus Blue Jackets	-	Pittsburgh Penguins	-
127	721	Winnipeg Jets	-	Pittsburgh Penguins	-
130	739	Pittsburgh Penguins	-	St Louis Blues	-
132	751	Pittsburgh Penguins	-	Chicago Blackhawks	-
134	757	Toronto Maple Leafs	-	Pittsburgh Penguins	-
136	777	Tampa Bay Lightning	-	Pittsburgh Penguins	-
138	787	Ottawa Senators	-	Pittsburgh Penguins	-
140	801	Pittsburgh Penguins	-	Philadelphia Flyers	-
144	821	Vegas Golden Knights	-	Pittsburgh Penguins	-
146	832	Pittsburgh Penguins	-	Edmonton Oilers	-
149	848	Colorado Avalanche	-	Pittsburgh Penguins	-
151	859	Detroit Red Wings	-	Pittsburgh Penguins	-
154	881	San Jose Sharks	-	Pittsburgh Penguins	-
156	895	Pittsburgh Penguins	-	Vancouver Canucks	-
159	909	Pittsburgh Penguins	-	New York Islanders	-
161	921	Pittsburgh Penguins	-	New York Rangers	-
163	937	New Jersey Devils	-	Pittsburgh Penguins	-
165	951	Pittsburgh Penguins	-	Carolina Hurricanes	-
167	965	Florida Panthers	-	Pittsburgh Penguins	-
169	980	Boston Bruins	-	Pittsburgh Penguins	-
Trade Deadline --- Trades can’t be done after this day is simulated!
172	988	Pittsburgh Penguins	-	Toronto Maple Leafs	-
174	1006	Pittsburgh Penguins	-	Tampa Bay Lightning	-
176	1021	Pittsburgh Penguins	-	Ottawa Senators	-
178	1032	Philadelphia Flyers	-	Pittsburgh Penguins	-
180	1039	Hamilton Mustangs	-	Pittsburgh Penguins	-
181	1053	Pittsburgh Penguins	-	Hamilton Mustangs	-
183	1067	Pittsburgh Penguins	-	Montreal Canadiens	-
184	1081	Montreal Canadiens	-	Pittsburgh Penguins	-
186	1095	Quebec Nordiques	-	Pittsburgh Penguins	-
187	1116	Pittsburgh Penguins	-	Quebec Nordiques	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2	Level 3	Level 4	Luxury
Capacity	5940	4860	1980	3960	1260
Ticket Price	92	51	30	23	186
Attendance	43,774	34,970	14,917	27,487	9,111
Attendance PCT	81.88%	79.95%	83.71%	77.12%	80.34%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
31	14473 - 80.41%	1,058,821$	9,529,388$	18000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Salaries Cap	Coaches Salaries	Special Salary Cap Value
16,170,255$	67,555,715$	0$	0$	0$

Salary Cap Per Days	Salary Cap To Date	Luxury Taxe Total	Players In Salary Cap	Players Out of Salary Cap
0$	16,170,255$	0$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
32,823,448$	143	359,339$	51,385,477$

Team Total Estimate
Estimated Season Expenses	Current Bank Account	Projected Bank Account
52,928,447$	133,291,189$	115,007,733$

Depth Chart

Left Wing

Center

Right Wing

Jake Guentzel	AGE:30	PO:55	OV:81
Jack Hughes	AGE:24	PO:40	OV:81
Matt Boldy	AGE:24	PO:55	OV:79
Bobby Brink (R)	AGE:23	PO:55	OV:72
Tom Kuhnhackl	AGE:33	PO:55	OV:69
Axel Jonsson-Fjallby	AGE:27	PO:55	OV:68
Dominik Simon	AGE:30	PO:55	OV:68
Oskar Sundqvist	AGE:31	PO:55	OV:66
Jack Studnicka	AGE:26	PO:55	OV:64

Kasperi Kapanen	AGE:28	PO:55	OV:80
Ryan Nugent-Hopkins	AGE:32	PO:55	OV:77
Joel Eriksson Ek	AGE:28	PO:55	OV:76
Marco Rossi (R)	AGE:23	PO:55	OV:74
Ridly Greig (R)	AGE:22	PO:55	OV:74
Dominic Toninato	AGE:31	PO:55	OV:68
Jiri Kulich (R)	AGE:21	PO:55	OV:68
Greg McKegg	AGE:33	PO:55	OV:66
Dennis Rasmussen	AGE:34	PO:55	OV:65
Tomas Nosek	AGE:32	PO:55	OV:65

Jordan Kyrou	AGE:27	PO:55	OV:80
Seth Jarvis (R)	AGE:23	PO:55	OV:78
Kirill Marchenko (R)	AGE:24	PO:55	OV:76
Matt Coronato (R)	AGE:22	PO:55	OV:72
Nick Ritchie	AGE:29	PO:55	OV:72
Rasmus Asplund	AGE:27	PO:55	OV:70
Martin Frk	AGE:31	PO:55	OV:65
Trey Fix-Wolansky	AGE:26	PO:55	OV:65
Kyle Criscuolo	AGE:33	PO:55	OV:64

Defense #1

Defense #2

Goalie

Josh Morrissey	AGE:30	PO:55	OV:82
Brandon Carlo	AGE:28	PO:55	OV:80
Martin Fehervary	AGE:25	PO:55	OV:80
Calen Addison	AGE:25	PO:55	OV:76
Vladislav Gavrikov	AGE:29	PO:55	OV:75
Jonas Siegenthaler	AGE:28	PO:55	OV:74
Joe Morrow	AGE:32	PO:55	OV:73
Juuso Valimaki	AGE:26	PO:55	OV:72
Kris Letang	AGE:38	PO:55	OV:72

Nick DeSimone	AGE:30	PO:55	OV:70
NICLAS ALMARI	AGE:27	PO:52	OV:70
Paul LaDue	AGE:32	PO:55	OV:67
Juuso Riikola	AGE:31	PO:55	OV:66
EETU PELTOLA	AGE:25	PO:52	OV:66
Jack Rathbone	AGE:26	PO:55	OV:65
Ethan Prow	AGE:32	PO:55	OV:64
Ashton Sautner	AGE:31	PO:75	OV:63

Connor Hellebuyck	AGE:32	PO:55	OV:81
Petr Mrazek	AGE:33	PO:55	OV:80
Reto Berra	AGE:38	PO:55	OV:76
STEFANOS LEKKAS	AGE:29	PO:52	OV:72

Prospects

Show or Hide Columns

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

Prospect	Team Name	Draft Year	Overall Pick	Information	Link
0x LTCs	Pittsburgh Penguins	0	0	0	Link
1 000 000 NSHL25 Waiver Bucks	Pittsburgh Penguins	0	0
1x NSHL26 ODW Claim	Pittsburgh Penguins	0	0	0	Link
1x RFA Tag	Pittsburgh Penguins	0	0	0	Link
20x TC PTS	Pittsburgh Penguins	0	0	0	Link
Aaron Huglen	Pittsburgh Penguins	19	125	0	Link
Adam Jiricek	Pittsburgh Penguins	24	23	0	Link
Adam Sykora	Pittsburgh Penguins	22	53	0	Link
Akil Thomas	Pittsburgh Penguins	18	46	0	Link
Aleksandr Kisakov	Pittsburgh Penguins	21	69	0	Link
Aleksi Heimosalmi	Pittsburgh Penguins	21	60	0	Link
Alexander Nikishin	Pittsburgh Penguins	22	26	0	Link
Andrew Strathmann	Pittsburgh Penguins	23	152	0	Link
Anton Johansson	Pittsburgh Penguins	25	192	0	Link
Beau Akey	Pittsburgh Penguins	23	96	0	Link
Ben Danford	Pittsburgh Penguins	24	63	0	Link
Brandon Svoboda	Pittsburgh Penguins	23	169	0	Link
Daemon Hunt	Pittsburgh Penguins	21	63	0	Link
Daniil Prokhorov	Pittsburgh Penguins	25	49	0	Link
David Edstrom	Pittsburgh Penguins	23	46	0	Link
Dmitry Ovchinnikov	Pittsburgh Penguins	20	103	0	Link
Donovan Sebrango	Pittsburgh Penguins	22	160	0	Link
Elmer Soderblom	Pittsburgh Penguins	21	113	0	Link
Eriks Mateiko	Pittsburgh Penguins	24	107	0	Link
Ethan Gauthier	Pittsburgh Penguins	23	47	0	Link
Etienne Morin	Pittsburgh Penguins	23	67	0	Link
Filip Lindberg	Pittsburgh Penguins	21	115	0	Link
Grigori Denisenko	Pittsburgh Penguins	18	29	0	Link
Helge Grans	Pittsburgh Penguins	20	36	0	Link
Hendrix Lapierre	Pittsburgh Penguins	20	24	0	Link
Ilya Fedotov	Pittsburgh Penguins	21	116	0	Link
Isak Rosen	Pittsburgh Penguins	21	18	0	Link
Jack Hughes DOB 2003	Pittsburgh Penguins	22	51	0	Link
Jayden Perron	Pittsburgh Penguins	23	72	0	Link
Jordan Gustafson	Pittsburgh Penguins	22	135	0	Link
Jordy Bellerive	Pittsburgh Penguins	18	51	0	Link
Julius Miettinen	Pittsburgh Penguins	24	49	0	Link
Julius Sumpf	Pittsburgh Penguins	25	135	0	Link
Juraj Pekarcik	Pittsburgh Penguins	23	120	0	Link
Justin Kipkie	Pittsburgh Penguins	25	164	0	Link
Kirill Kirsanov	Pittsburgh Penguins	22	48	0	Link
Ludwig Persson	Pittsburgh Penguins	22	137	0	Link
Martin Chromiak	Pittsburgh Penguins	20	88	0	Link
Matej Blumel	Pittsburgh Penguins	22	152	0	Link
Matyas Sapovaliv	Pittsburgh Penguins	22	89	0	Link
Max Plante	Pittsburgh Penguins	24	87	0	Link
Miroslav Holinka	Pittsburgh Penguins	25	78	0	Link
Oliver Moore	Pittsburgh Penguins	23	16	0	Link
Peyton Kettles	Pittsburgh Penguins	25	57	0	Link
Philippe Desrosiers	Pittsburgh Penguins	13	87	0	Link
Prokhor Poltapov	Pittsburgh Penguins	21	50	0	Link
Radim Mrtka	Pittsburgh Penguins	25	25	0	Link
Raphael Lavoie	Pittsburgh Penguins	19	23	0	Link
Ryan Chesley	Pittsburgh Penguins	22	41	0	Link
Ryan Greene	Pittsburgh Penguins	22	112	0	Link
Sam O'Reilly	Pittsburgh Penguins	24	38	0	Link
Sampo Ranta	Pittsburgh Penguins	18	105	0	Link
Samuel Poulin	Pittsburgh Penguins	19	34	0	Link
Yegor Borikov	Pittsburgh Penguins	25	106	0	Link
Yevgeni Volokhin	Pittsburgh Penguins	24	111	0	Link
Zach Nehring	Pittsburgh Penguins	23	162	0	Link
Zion Nybeck	Pittsburgh Penguins	20	77	0	Link

Draft Picks

Year	R1	R2	R3	R4	R5	R6	R7
26
27
28
29
30
Conditional Draft Picks

The STHS News Database File was not found or corrupted. Please create one in the League News Management section of the website logged in as a Commissioner.

Pittsburgh Penguins Trade History

[2026-02-07 3:08:51 PM] New Record for Team's Most Hits (33) in 1 Game for Pittsburgh Penguins!
[2026-02-05 1:28:01 PM] New Record for Team's Most Shots Blocked (19) in 1 Game for Pittsburgh Penguins!
[2026-02-05 1:28:01 PM] New Record for Team's Most Shots Blocked (19) in 1 Game for Pittsburgh Penguins!
[2026-02-03 3:12:01 PM] New Record for Team's Most Hits (25) in 1 Game for Pittsburgh Penguins!

No Injury or Suspension.

Pittsburgh Penguins Players Stat Leaders (Regular Season)

Show or Hide Columns

#	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

Pittsburgh Penguins Goalies Stat Leaders (Regular Season)

Show or Hide Columns

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

Pittsburgh Penguins Career Team Stats

Show or Hide Columns

	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

Pittsburgh Penguins Players Stat Leaders (Play-Off)

Show or Hide Columns

#	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

Pittsburgh Penguins Goalies Stat Leaders (Play-Off)

Show or Hide Columns

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

	Pittsburgh Penguins
	GP: 18 \| W: 9 \| L: 9 \| OTL: 0 \| P: 23 GF: 51 \| GA: 54 \| PP%: 12.90% \| PK%: 79.45% GM : Jeff \| Morale : 40 \| Team Overall : 77 Next Games #261 vs New York Islanders