Profi League - Today's Games Farm

Roster

Player	POS	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	MO	OV	AGE	CONTRACT
Matthew Highmore	C	96.00	64	36	89	48	74	81	76	48	63	50	50	68	64	66	67	53	53	27	800,000$/2yrs
Jan Jenik (R)	RW	96.00	70	46	80	50	76	84	82	50	64	49	51	56	72	62	63	53	52	22	800,000$/3yrs
Jackson Cates	C	98.00	56	35	85	48	75	75	80	49	80	47	49	60	62	65	67	56	51	25	1,600,000$/1yrs
Marc McLaughlin	C	98.00	66	36	78	47	76	78	78	48	63	47	48	56	61	64	65	46	51	23	1,900,000$/2yrs
Gemel Smith	C	99.00	72	71	74	40	71	84	75	39	80	45	45	64	58	67	70	50	50	28	900,000$/1yrs
Jonatan Berggren (R)	LW	98.00	62	37	84	46	71	89	85	45	73	48	47	59	69	62	64	56	50	22	100,000$/8yrs
Ben Jones	C	100.00	71	39	73	40	72	80	87	39	66	42	46	60	62	64	65	53	49	24	100,000$/8yrs
Josh Dunne	C	100.00	81	42	76	38	88	81	66	38	73	41	44	60	57	64	66	59	49	24	3,000,000$/1yrs
Lucas Elvenes	C	100.00	63	38	80	42	72	78	81	42	70	46	43	62	63	65	66	56	49	23	100,000$/8yrs
Simon Benoit	D	100.00	88	80	91	35	83	80	75	36	30	47	47	73	45	64	66	58	53	24	1,900,000$/1yrs
Daniil Miromanov	D	100.00	66	35	82	35	80	79	79	36	30	49	49	70	52	65	67	58	52	25	2,400,000$/1yrs
Lucas Carlsson	D	100.00	69	37	91	36	76	80	78	36	30	49	47	71	53	65	67	43	52	25	700,000$/1yrs
Chris Bigras	D	100.00	67	39	87	33	76	66	71	33	30	42	42	65	46	67	69	56	50	28	600,000$/1yrs
Zachary Hayes	D	100.00	84	42	80	31	87	74	81	30	30	42	39	64	48	63	65	54	50	23	2,400,000$/1yrs
Brady Lyle	D	100.00	69	39	87	32	78	69	86	32	30	41	40	64	48	63	65	55	49	23	2,400,000$/1yrs
Cole Hults	D	100.00	63	38	84	33	72	69	81	33	30	41	42	65	50	64	66	56	49	24	100,000$/8yrs
Declan Chisholm	D	100.00	60	37	85	34	74	78	79	33	30	45	43	66	50	62	64	47	49	23	100,000$/8yrs
Hunter Skinner (R)	D	100.00	68	39	81	32	78	72	73	32	30	41	40	65	46	61	63	49	49	21	100,000$/8yrs
Scratches
Valtteri Puustinen (R)	RW	100.00	63	35	91	41	65	87	82	41	53	44	45	62	68	63	65	29	49	23	100,000$/8yrs
Aarne Talvitie	C	100.00	63	37	92	38	72	68	88	37	61	41	43	62	58	63	65	20	48	24	100,000$/8yrs
Cameron Morrison (R)	LW	100.00	66	38	94	38	85	73	69	38	52	42	41	61	57	64	66	19	48	24	100,000$/8yrs
Owen Sillinger	C	100.00	58	36	93	40	67	79	61	40	66	44	43	62	58	65	67	20	48	25	1,900,000$/1yrs
Mathias Laferriere (R)	RW	100.00	69	37	91	36	78	69	84	35	56	40	39	58	53	62	64	19	47	22	100,000$/8yrs
Ryan McGregor	C	100.00	59	37	88	37	68	72	69	37	66	42	39	62	58	63	65	20	47	24	3,000,000$/1yrs
Matej Pekar	LW	100.00	65	53	62	36	74	73	76	35	56	39	39	57	51	62	64	20	46	23	100,000$/8yrs
Linus Hogberg (R)	D	100.00	62	37	80	31	73	82	79	31	30	41	40	65	53	64	66	20	48	24	100,000$/8yrs
Jack Dougherty	D	100.00	61	38	94	30	80	61	68	30	30	39	38	60	45	66	68	20	47	26	100,000$/8yrs

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	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	MO	OV	AGE	CONTRACT
Nico Daws	98.00	82	88	76	93	77	82	83	82	81	80	79	62	67	36	68	22	800,000$/3yrs
Mads Sogaard	100.00	74	85	81	96	70	73	73	74	75	72	72	62	67	28	63	22	100,000$/8yrs
Scratches
Zach Fucale	100.00	74	85	78	91	69	73	75	73	75	72	71	67	77	19	63	27	100,000$/8yrs
Joseph Woll	100.00	73	81	73	93	68	72	76	72	73	71	70	64	71	20	63	24	100,000$/8yrs
Joel Hofer	100.00	73	86	83	94	72	72	76	72	73	71	72	62	67	20	63	22	100,000$/8yrs
Brandon Bussi	100.00	69	80	70	94	67	68	71	70	68	67	68	64	71	20	60	24	1,600,000$/1yrs

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Chris Taylor	61	61	64	69	75	70	76	CAN	50	2	200,000$

General Manager

Player Stats

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	SHT	OSB	OSM	SHT%	SB	MP	PPG	PPA	PPP	PKG	PKA	PKP	PKM	GW	GT	FO%	FOT	HT	P/20	PSG	PSS
1	Matthew Highmore	Admirals (NSH)	C	81	42	44	86	-8	8	0	122	364	78	248	11.54%	31	24.:.12	4	6	10	0	0	0	80	11	2	45.69%	2248	2	0.88	1	6
2	Jan Jenik	Admirals (NSH)	RW	82	26	37	63	-7	32	10	186	291	86	194	8.93%	12	22.:.53	3	4	7	0	0	0	24	4	0	53.63%	179	0	0.67	0	7
3	Jonatan Berggren	Admirals (NSH)	LW	82	20	40	60	-8	16	0	112	244	70	199	8.20%	21	23.:.48	2	7	9	0	0	0	149	2	3	52.30%	174	0	0.61	0	2
4	Marc McLaughlin	Admirals (NSH)	C	82	20	38	58	-2	24	0	109	268	68	175	7.46%	7	21.:.35	5	8	13	0	0	0	96	3	2	45.96%	1162	1	0.66	0	4
5	Jackson Cates	Admirals (NSH)	C	82	22	28	50	-3	6	0	30	271	75	198	8.12%	20	17.:.58	3	8	11	1	0	1	66	7	0	54.52%	1902	0	0.68	4	8
6	Gemel Smith	Admirals (NSH)	C	82	19	19	38	-17	38	10	108	202	61	146	9.41%	10	15.:.48	3	3	6	0	0	0	27	1	1	52.90%	1121	0	0.59	0	4
7	Josh Dunne	Admirals (NSH)	C	82	13	21	34	-10	35	5	202	150	40	117	8.67%	13	19.:.10	0	0	0	0	0	0	0	1	0	48.78%	123	0	0.43	0	1
8	Simon Benoit	Admirals (NSH)	D	78	9	20	29	-17	35	15	121	72	23	57	12.50%	89	16.:.36	3	3	6	0	1	1	55	1	2	0.00%	0	0	0.45	0	0
9	Ben Jones	Admirals (NSH)	C	82	11	17	28	-12	19	5	77	129	43	106	8.53%	10	13.:.21	0	0	0	0	0	0	31	0	0	44.34%	106	0	0.51	1	2
10	Daniil Miromanov	Admirals (NSH)	D	79	7	20	27	-4	8	0	39	90	36	57	7.78%	81	14.:.17	1	3	4	0	0	0	21	0	1	0.00%	0	0	0.48	0	1
11	Declan Chisholm	Admirals (NSH)	D	73	3	23	26	9	10	0	42	42	21	30	7.14%	77	15.:.05	0	0	0	0	0	0	76	0	0	0.00%	0	0	0.47	0	1
12	Chris Bigras	Admirals (NSH)	D	82	4	21	25	-2	20	0	124	74	15	50	5.41%	110	21.:.32	1	5	6	0	0	0	106	1	0	0.00%	0	0	0.28	0	0
13	Lucas Elvenes	Admirals (NSH)	C	82	9	11	20	-2	10	0	38	88	20	62	10.23%	6	08.:.30	0	2	2	0	0	0	0	0	1	54.55%	77	0	0.57	1	2
14	Cole Hults	Admirals (NSH)	D	82	5	14	19	-3	22	0	93	64	19	50	7.81%	119	21.:.29	2	3	5	0	0	0	109	1	0	0.00%	0	0	0.22	0	1
15	Zachary Hayes	Admirals (NSH)	D	79	2	16	18	-18	46	0	204	63	20	36	3.17%	100	23.:.52	2	0	2	0	0	0	89	0	0	0.00%	0	0	0.19	0	1
16	Valtteri Puustinen	Admirals (NSH)	RW	57	2	11	13	6	0	0	21	69	20	43	2.90%	2	07.:.04	0	0	0	0	0	0	0	0	0	38.55%	179	0	0.64	0	1
17	Brady Lyle	Admirals (NSH)	D	75	0	7	7	11	14	0	47	18	9	12	0.00%	38	07.:.59	0	1	1	0	0	0	32	0	0	0.00%	1	0	0.23	0	0
18	Cameron Morrison	Admirals (NSH)	LW	35	5	2	7	3	8	0	14	28	11	19	17.86%	4	08.:.16	0	0	0	0	0	0	26	2	0	16.67%	18	0	0.48	0	1
19	Lucas Carlsson	Admirals (NSH)	D	13	1	4	5	-12	0	0	10	18	5	9	5.56%	14	22.:.55	1	1	2	0	0	0	4	0	0	0.00%	0	0	0.34	0	0
20	Mathias Laferriere	Admirals (NSH)	RW	13	0	1	1	2	2	0	12	8	2	12	0.00%	0	11.:.44	0	0	0	0	0	0	0	0	0	28.57%	7	0	0.13	0	1
21	Hunter Skinner	Admirals (NSH)	D	69	0	0	0	-2	0	0	4	1	0	1	0.00%	7	01.:.27	0	0	0	0	0	0	22	0	0	0.00%	0	0	0.00	0	0
22	Linus Hogberg	Admirals (NSH)	D	3	0	0	0	0	0	0	0	0	0	0	0.00%	0	00.:.11	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.00	0	0
23	Owen Sillinger	Admirals (NSH)	C	1	0	0	0	0	0	0	0	0	1	0	0.00%	0	02.:.13	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.00	0	0
Team Total or Average			1476	220	394	614	-96	353	45	1715	2554	723	1821	8.61%	771	16.59	30	54	84	1791	1	1	2	1020	34	12	49.35%	7297	3	0.50	7	43

Show or Hide Column

Filter Tips

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

#	Goalie Name	Team Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Nico Daws	Admirals (NSH)	39	15	19	5	91.8%	2.64	2338	8	3	103	1263	0	0	1	78.4%	37	39	33	4	3	3
2	Mads Sogaard	Admirals (NSH)	24	12	10	2	89.9%	3.19	1447	2	1	77	764	0	1	0	0.0%	0	24	25	1	0	0
3	Zach Fucale	Admirals (NSH)	11	5	4	1	90.2%	2.93	636	0	0	31	316	0	0	0	33.3%	3	10	24	0	1	0
4	Joel Hofer	Admirals (NSH)	9	4	4	1	90.8%	2.86	545	2	1	26	283	0	0	0	50.0%	2	9	0	1	1	0
Team Total or Average		83	36	37	9	0.910	2.86	4967	12	5	237	2626	0	1	1	0.738	42	82	82	6	5	3

Lines

Forward Lines
# - Jonatan Berggren	# - Matthew Highmore	# - Jan Jenik
# - Marc McLaughlin	# - Jackson Cates	# - Gemel Smith
# - Matthew Highmore	# - Marc McLaughlin	# - Jan Jenik
# - Jackson Cates	# - Gemel Smith	# - Jonatan Berggren

Defensive Pairings
# - Simon Benoit	# - Lucas Carlsson
# - Daniil Miromanov	# - Chris Bigras
# - Zachary Hayes	# - Hunter Skinner

1st Power Play Unit
# - Jonatan Berggren		# - Matthew Highmore		# - Jan Jenik
# - Simon Benoit			# - Lucas Carlsson

2nd Power Play Unit
# - Marc McLaughlin		# - Jackson Cates		# - Gemel Smith
# - Daniil Miromanov			# - Chris Bigras

Goalies
# - Nico Daws		# - Mads Sogaard

Team Stats

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

#	VS Team	GP	W	L	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	GF%	SH%	SV%	PDO	PDOBRK
1	Penguins	2	1	1	0	0	0	0	6	11	-5	2	0.500	6	11	17	0	0	87	69	59	12	72	850	812	854	81	90	15	6	42	4	1	25.00%	2	1	50.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	33.3%	8.3%	87.8%	96.1	Unlucky
2	Islanders	2	0	1	1	0	0	0	5	5	0	2	0.500	5	9	14	0	0	87	69	59	12	68	850	812	854	81	56	18	4	50	5	1	20.00%	2	1	50.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	50.0%	7.4%	91.1%	98.4	Unlucky
3	Wolf Pack	2	1	1	0	0	0	0	3	3	0	2	0.500	3	5	8	0	1	87	69	59	12	41	850	812	854	81	73	17	12	33	0	0	0.00%	6	0	100.00%	1	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	50.0%	7.3%	95.9%	103.2	DULL
4	Comets	2	0	1	1	0	0	0	6	7	-1	2	0.500	6	10	16	0	0	87	69	59	12	71	850	812	854	81	52	24	9	47	4	2	50.00%	2	1	50.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	40.0%	8.5%	86.5%	95.0	Unlucky
5	Phantoms	2	1	1	0	0	0	0	8	7	1	2	0.500	8	15	23	0	0	87	69	59	12	65	850	812	854	81	63	18	8	46	3	1	33.33%	3	1	66.67%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	53.8%	12.3%	88.9%	101.2	FUN
6	Wolves	2	0	1	1	0	0	0	6	8	-2	2	0.500	6	10	16	0	0	87	69	59	12	69	850	812	854	81	53	14	2	39	8	2	25.00%	1	0	100.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	33.3%	8.7%	84.9%	93.6	Unlucky
7	Crunch	2	1	1	0	0	0	0	1	1	0	2	0.500	1	1	2	0	1	87	69	59	12	47	850	812	854	81	52	19	16	50	3	0	0.00%	8	0	100.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	50.0%	2.1%	98.1%	100.2	DULL
8	Moose	4	3	1	0	0	0	0	16	9	7	6	0.750	16	31	47	0	0	87	69	59	12	127	850	812	854	81	127	50	18	96	5	0	0.00%	9	2	77.78%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	69.6%	12.6%	92.9%	105.5	LUCKY
9	Bears	2	0	2	0	0	0	0	4	8	-4	0	0.000	4	8	12	1	0	87	69	59	12	63	850	812	854	81	88	29	4	38	4	0	0.00%	2	0	100.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	33.3%	6.3%	90.9%	97.3	Unlucky
10	Checkers	2	1	1	0	0	0	0	6	6	0	2	0.500	6	9	15	0	0	87	69	59	12	53	850	812	854	81	84	19	39	34	1	0	0.00%	5	0	100.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	50.0%	11.3%	92.9%	104.2	LUCKY
11	Bruins	2	0	1	0	0	0	1	5	8	-3	1	0.250	5	10	15	0	0	87	69	59	12	66	850	812	854	81	72	21	12	40	3	1	33.33%	6	1	83.33%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	36.4%	7.6%	88.9%	96.5	Unlucky
12	Senators	2	1	1	0	0	0	0	5	3	2	2	0.500	5	10	15	0	0	87	69	59	12	55	850	812	854	81	60	15	8	37	8	3	37.50%	4	1	75.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	50.0%	9.1%	95.0%	104.1	LUCKY
13	Rocket	2	2	0	0	0	0	0	7	4	3	4	1.000	7	11	18	0	0	87	69	59	12	71	850	812	854	81	59	21	4	37	8	0	0.00%	1	1	0.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	70.0%	9.9%	93.2%	103.1	LUCKY
14	Americans	2	1	0	0	1	0	0	4	4	0	3	0.750	4	8	12	0	0	87	69	59	12	55	850	812	854	81	54	11	6	37	7	1	14.29%	2	0	100.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	42.9%	7.3%	92.6%	99.9	DULL
15	Marlies	2	0	2	0	0	0	0	1	7	-6	0	0.000	1	2	3	0	0	87	69	59	12	61	850	812	854	81	61	18	15	45	8	0	0.00%	5	2	60.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	16.7%	1.6%	88.5%	90.2	Unlucky
16	Thunderbirds	4	0	4	0	0	0	0	6	15	-9	0	0.000	6	12	18	0	0	87	69	59	12	126	850	812	854	81	145	34	20	92	13	1	7.69%	10	4	60.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	31.3%	4.8%	89.7%	94.4	Unlucky
17	Griffins	2	1	1	0	0	0	0	8	8	0	2	0.500	8	14	22	0	0	87	69	59	12	70	850	812	854	81	66	10	17	31	8	0	0.00%	6	1	83.33%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	53.3%	11.4%	87.9%	99.3	FUN
18	IceHogs	3	3	0	0	0	0	0	13	8	5	6	1.000	13	19	32	0	0	87	69	59	12	100	850	812	854	81	105	28	6	62	4	2	50.00%	3	0	100.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	57.9%	13.0%	92.4%	105.4	LUCKY
19	Monsters	2	0	0	0	1	1	0	6	6	0	3	0.750	6	9	15	0	0	87	69	59	12	61	850	812	854	81	61	28	6	35	6	2	33.33%	3	0	100.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	40.0%	9.8%	90.2%	100.0	FUN
20	Wild	3	2	0	0	0	0	1	15	9	6	5	0.833	15	28	43	0	0	87	69	59	12	116	850	812	854	81	97	28	6	66	16	3	18.75%	3	1	66.67%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	60.0%	12.9%	90.7%	103.7	FUN
21	Condors	3	0	2	0	0	0	1	3	10	-7	1	0.167	3	6	9	0	0	87	69	59	12	96	850	812	854	81	89	30	15	81	6	0	0.00%	4	1	75.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	25.0%	3.1%	88.8%	91.9	Unlucky
22	Heat	3	1	0	0	0	1	1	10	7	3	5	0.833	10	18	28	0	0	87	69	59	12	117	850	812	854	81	87	31	12	53	11	1	9.09%	6	1	83.33%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	60.0%	8.5%	92.0%	100.5	DULL
23	Canucks	3	2	0	0	1	0	0	12	8	4	5	0.833	12	23	35	0	0	87	69	59	12	74	850	812	854	81	88	38	14	56	8	2	25.00%	7	1	85.71%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	58.8%	16.2%	90.9%	107.1	FUN
24	Eagles	4	1	2	1	0	0	0	12	16	-4	4	0.500	12	21	33	0	0	87	69	59	12	117	850	812	854	81	160	34	16	95	10	2	20.00%	7	1	85.71%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	40.0%	10.3%	90.0%	100.3	FUN
25	Reign	3	1	2	0	0	0	0	6	9	-3	2	0.333	6	10	16	0	1	87	69	59	12	78	850	812	854	81	114	26	16	60	4	0	0.00%	8	1	87.50%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	42.9%	7.7%	92.1%	99.8	DULL
26	Roadrunners	4	1	3	0	0	0	0	8	10	-2	2	0.250	8	14	22	0	1	87	69	59	12	102	850	812	854	81	105	31	12	78	14	2	14.29%	6	0	100.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	37.5%	7.8%	90.5%	98.3	Unlucky
27	Stars	4	1	2	0	0	0	1	8	10	-2	3	0.375	8	13	21	0	1	87	69	59	12	125	850	812	854	81	122	46	14	84	7	0	0.00%	7	0	100.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	44.4%	6.4%	91.8%	98.2	DULL
28	Gulls	3	1	1	0	0	0	1	10	9	1	3	0.500	10	19	29	0	0	87	69	59	12	91	850	812	854	81	83	35	6	57	7	1	14.29%	3	2	33.33%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	56.3%	11.0%	89.2%	100.1	FUN
29	Barracuda	3	2	0	1	0	0	0	12	8	4	6	1.000	12	22	34	0	0	87	69	59	12	110	850	812	854	81	82	18	13	49	10	1	10.00%	4	1	75.00%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	61.1%	10.9%	90.2%	101.2	FUN
30	Firebirds	3	1	2	0	0	0	0	4	7	-3	2	0.333	4	6	10	0	0	87	69	59	12	93	850	812	854	81	65	13	12	78	4	0	0.00%	6	1	83.33%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	40.0%	4.3%	89.2%	93.5	Unlucky
31	Silver Knights	3	0	3	0	0	0	0	6	13	-7	0	0.000	6	10	16	0	0	87	69	59	12	94	850	812	854	81	114	32	17	67	9	1	11.11%	6	4	33.33%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	35.7%	6.4%	88.6%	95.0	Unlucky
	_Vs Division	26	11	12	1	0	0	2	78	77	1	26	0.500	78	138	216	0	2	87	69	59	12	813	850	812	854	81	861	251	92	573	69	10	14.49%	45	8	82.22%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	49.6%	9.6%	91.1%	100.7	Unlucky
	_Vs Conference	50	19	22	2	1	1	5	141	148	-7	50	0.500	141	252	393	0	3	87	69	59	12	1566	850	812	854	81	1583	474	197	1074	128	16	12.50%	89	20	77.53%	0	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	49.4%	9.0%	90.7%	99.7	FUN
	_Since Last GM Reset	82	29	37	5	3	2	6	222	244	-22	81	0.494	222	394	616	1	5	87	69	59	12	2554	850	812	854	81	2627	771	365	1715	208	30	14.42%	147	30	79.59%	1	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	47.3%	8.7%	90.7%	99.4	Unlucky
	Total	82	29	37	5	3	2	6	222	244	-22	81	0.494	222	394	616	1	5	87	69	59	12	2554	850	812	854	81	2627	771	365	1715	208	30	14.42%	147	30	79.59%	1	1425	2878	49.51%	1481	2971	49.85%	695	1362	51.03%	1842	1191	1929	678	1202	586	47.3%	8.7%	90.7%	99.4	Unlucky

	Puck Time
Offensive Zone	22
Neutral Zone	14
Defensive Zone	23

	Puck Time
Offensive Zone Start	2878
Neutral Zone Start	1362
Defensive Zone Start	2971

	Puck Time
With Puck	29
Without Puck	30

	Faceoffs
Faceoffs Won	3601
Faceoffs Lost	3610

	Team Average Shots after	League Average Shots after
1st Period	10.4	9.57
2nd Period	20.3	20.31
3rd Period	30.7	30.68
Overtime	31.7	31.4

Goals in	Team Average Goals after	League Average Goals after
1st Period	1.1	0.64
2nd Period	1.9	1.65
3rd Period	2.6	2.67
Overtime	2.8	2.83


Even Strenght Goal	190
PP Goal	30
PK Goal	1
Empty Net Goal	1

	Home	Away
Win	17	19
Lost	22	15
Overtime Lost	2	7


PP Attempt	208
PP Goal	30
PK Attempt	147
PK Goal Against	30

	Home
Shots For	31.1
Shots Against	32.0
Goals For	2.7
Goals Against	3.0
Hits	20.9
Shots Blocked	9.4
Pim	4.5

Schedule

Date	Matchup			Result	Detail
Thu, Oct 13	TEX	@	MIL	TEX5,MIL3	RECAP
Sat, Oct 15	MIL	@	TEX	MIL2,TEX3 (SO)	RECAP
Sun, Oct 16	SJB	@	MIL	SJB3,MIL4	RECAP
Tue, Oct 18	ONT	@	MIL	ONT0,MIL2	RECAP
Thu, Oct 20	MIL	@	CLV	MIL1,CLV2 (OT)	RECAP
Sat, Oct 22	LVP	@	MIL	LVP2,MIL5	RECAP
Thu, Oct 27	SPR	@	MIL	SPR2,MIL0	RECAP
Sat, Oct 29	HER	@	MIL	HER4,MIL2	RECAP
Tue, Nov 1	MIL	@	BKS	MIL2,BKS3 (SO)	RECAP
Thu, Nov 3	MIL	@	STC	MIL3,STC4 (SO)	RECAP
Sat, Nov 5	MIL	@	ABB	MIL4,ABB1	RECAP
Tue, Nov 8	MIL	@	CVF	MIL0,CVF1	RECAP
Thu, Nov 10	MIL	@	COE	MIL2,COE6	RECAP
Sat, Nov 12	HWP	@	MIL	HWP3,MIL2	RECAP
Tue, Nov 15	IOW	@	MIL	IOW3,MIL9	RECAP
Thu, Nov 17	BRI	@	MIL	BRI1,MIL0	RECAP
Sat, Nov 19	SYR	@	MIL	SYR1,MIL0	RECAP
Mon, Nov 21	TUC	@	MIL	TUC3,MIL1	RECAP
Wed, Nov 23	MIL	@	GRG	MIL3,GRG5	RECAP
Thu, Nov 24	MIL	@	SJB	MIL4,SJB3 (OT)	RECAP
Fri, Nov 25	COE	@	MIL	COE3,MIL4 (OT)	RECAP
Sat, Nov 26	CLV	@	MIL	CLV4,MIL5 (SO)	RECAP
Tue, Nov 29	SDG	@	MIL	SDG2,MIL5	RECAP
Thu, Dec 1	MIL	@	UTI	MIL2,UTI4	RECAP
Fri, Dec 2	MIL	@	BRI	MIL5,BRI4 (OT)	RECAP
Thu, Dec 8	MIL	@	SYR	MIL1,SYR0	RECAP
Sat, Dec 10	BEL	@	MIL	BEL2,MIL1	RECAP
Mon, Dec 12	MIL	@	SPR	MIL2,SPR4	RECAP
Tue, Dec 13	BKS	@	MIL	BKS4,MIL1	RECAP
Thu, Dec 15	MIL	@	MAN	MIL6,MAN1	RECAP
Sat, Dec 17	MIL	@	COE	MIL5,COE4	RECAP
Mon, Dec 19	BKS	@	MIL	BKS3,MIL0	RECAP
Wed, Dec 21	MIL	@	RFD	MIL5,RFD3	RECAP
Fri, Dec 23	COE	@	MIL	COE3,MIL1	RECAP
Tue, Dec 27	TEX	@	MIL	TEX2,MIL1	RECAP
Fri, Dec 30	MIL	@	SDG	MIL2,SDG3 (SO)	RECAP
Sat, Dec 31	MIL	@	HSK	MIL2,HSK4	RECAP
Tue, Jan 3	LAV	@	MIL	LAV2,MIL4	RECAP
Thu, Jan 5	MIL	@	CHW	MIL5,CHW4 (OT)	RECAP
Fri, Jan 6	MIL	@	HER	MIL2,HER4	RECAP
Mon, Jan 9	MIL	@	BEL	MIL4,BEL1	RECAP
Wed, Jan 11	MIL	@	TOM	MIL1,TOM3	RECAP
Thu, Jan 12	MIL	@	LAV	MIL3,LAV2	RECAP
Sat, Jan 14	ROC	@	MIL	ROC3,MIL2 (OT)	RECAP
Mon, Jan 16	STC	@	MIL	STC1,MIL4	RECAP
Thu, Jan 19	MIL	@	SPR	MIL2,SPR5	RECAP
Sat, Jan 21	ONT	@	MIL	ONT5,MIL3	RECAP
Tue, Jan 24	MAN	@	MIL	MAN2,MIL5	RECAP
Thu, Jan 26	UTI	@	MIL	UTI3,MIL4 (OT)	RECAP
Tue, Feb 7	HSK	@	MIL	HSK5,MIL2	RECAP
Sat, Feb 11	MIL	@	LVP	MIL3,LVP5	RECAP
Mon, Feb 13	TUC	@	MIL	TUC4,MIL3	RECAP
Thu, Feb 16	PVD	@	MIL	PVD4,MIL2	RECAP
Sat, Feb 18	CHA	@	MIL	CHA3,MIL4	RECAP
Sun, Feb 19	MIL	@	IOW	MIL4,IOW3	RECAP
Tue, Feb 21	ABB	@	MIL	ABB4,MIL6	RECAP
Thu, Feb 23	MIL	@	SJB	MIL4,SJB2	RECAP
Sun, Feb 26	MIL	@	TUC	MIL2,TUC0	RECAP
Tue, Feb 28	WIL	@	MIL	WIL7,MIL0	RECAP
Thu, Mar 2	MIL	@	CHA	MIL2,CHA3	RECAP
Sat, Mar 4	MIL	@	RFD	MIL4,RFD2	RECAP
Mon, Mar 6	MIL	@	ABB	MIL2,ABB3 (OT)	RECAP
Trade Deadline --- Trades can�t be done after this day is simulated!
Thu, Mar 9	MIL	@	TUC	MIL2,TUC3	RECAP
Sat, Mar 11	MIL	@	ONT	MIL1,ONT4	RECAP
Sun, Mar 12	MIL	@	SDG	MIL3,SDG4	RECAP
Tue, Mar 14	GRG	@	MIL	GRG3,MIL5	RECAP
Thu, Mar 16	RFD	@	MIL	RFD3,MIL4	RECAP
Sat, Mar 18	MAN	@	MIL	MAN2,MIL5	RECAP
Sun, Mar 19	MIL	@	HWP	MIL1,HWP0	RECAP
Tue, Mar 21	MIL	@	ROC	MIL2,ROC1	RECAP
Thu, Mar 23	CVF	@	MIL	CVF4,MIL1	RECAP
Sat, Mar 25	CVF	@	MIL	CVF2,MIL3	RECAP
Sun, Mar 26	TOM	@	MIL	TOM4,MIL0	RECAP
Tue, Mar 28	MIL	@	PVD	MIL3,PVD4 (SO)	RECAP
Thu, Mar 30	MIL	@	WIL	MIL6,WIL4	RECAP
Sat, Apr 1	SPR	@	MIL	SPR4,MIL2	RECAP
Mon, Apr 3	MIL	@	TEX	MIL2,TEX0	RECAP
Tue, Apr 4	HSK	@	MIL	HSK4,MIL2	RECAP
Thu, Apr 6	CHW	@	MIL	CHW4,MIL1	RECAP
Sat, Apr 8	MIL	@	MAN	MIL0,MAN4	RECAP
Mon, Apr 10	MIL	@	STC	MIL3,STC2 (SO)	RECAP
Thu, Apr 13	IOW	@	MIL	IOW3,MIL2 (SO)	RECAP

Depth Chart

Rookie

Injured

Cold Streak

Hot Streak

Left Wing

Center

Right Wing

Defense #1

Defense #2

Goalie

Transactions

Injuries

No Injury or Suspension.

Game Center

Admirals36-37-9, 81pts

32Final

Heat28-41-13, 69pts

Wild39-39-4, 82pts

32Final

Admirals36-37-9, 81pts

Wild39-39-4, 82pts

Fri, Apr 14

Admirals36-37-9, 81pts

Sun, Oct 16

Stars37-37-8, 82pts

Barracuda32-39-11, 75pts

Mon, Oct 17

Admirals36-37-9, 81pts

Team Info


	Head Coach	Chris Taylor
	Division	Central Division
	City	Milwaukee
	Stadium Capacity	3,000

Admirals Affiliation


	General Manager	Roman Chrencik
	Head Coach	Peter DeBoer
	Stadium	Bridgestone Arena
	Capacity	17,159

Team Leaders

GOALS Matthew Highmore Admirals	42 GOALS
POINTS Matthew Highmore Admirals	86 POINTS
WINS Nico Daws Admirals	15 WINS
Expanded Player Leaderboard

Team Stats

Goals For 222 2.71 GFG	Goals Against 244 2.98 GAA
Power Play Percentage 14.4% 30 GF	Penalty Kill Percentage 79.6% 30 GA
Expanded Team Stats