Jets
Home
Roster
Scoring
Players Info
Lines
Team Stats
Schedule
Finance
Career Team Stat
Web Lines Editor

Game Center
	Milwaukee Admirals 2-7-1, 5pts	4	FINAL	5	Binghampton Senators 4-5-1, 9pts

Team Stats
L1	Streak	SOW1
1-4-0	Home Record	3-2-0
1-3-1	Away Record	1-3-1
2-7-1	Last 10 Games	4-5-1
5.50	Goals Per Game	4.90
7.40	Goals Against Per Game	4.60
48.28%	Power Play Percentage	27.27%
55.17%	Penalty Kill Percentage	75.00%

Milwaukee Admirals
2-7-1, 5pts

FINAL

Toronto Marlies
6-3-1, 13pts

Team Stats
L1	Streak	W1
1-4-0	Home Record	4-0-1
1-3-1	Away Record	2-3-0
2-7-1	Last 10 Games	6-3-1
5.50	Goals Per Game	6.70
7.40	Goals Against Per Game	5.30
48.28%	Power Play Percentage	41.18%
55.17%	Penalty Kill Percentage	67.65%

Team Leaders
	Goals Trent Frederic 9	Assists Bowen Byram 13

	Points Calen Addison 15	Plus/Minus Dennis Yan 3

	Wins Felix Sandstrom 0	Save Percentage Isaiah Saville 0.971

Team Stats
Goals For 55 5.50 GFG	Shots For 391 39.10 Avg	Power Play Percentage 48.3% 14 GF	Offensive Zone Start 35.7%
Goals Against 74 7.40 GAA	Shots Against 369 36.90 Avg	Penalty Kill Percentage 55.2% 13 GA	Defensive Zone Start 26.7%

Team Info
	General Manager	Sebastien Doyon
	Coach	Neil Graham
	Division	Steve Yzerman
	Conference	Conference 2
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Capacity	3,000
	Attendance	0
	Season Tickets	300
Roster Info
	Pro Team	24
	Farm Team	23
	Contract Limit	47 / 50
	Prospects	54
Team History
	This Season	2-7-1 (5PTS)
	History	96-125-19 (0.400%)
	Playoff Appearances	2
	Playoff Record (W-L)	0-0
	Stanley Cup	0

Show or Hide Column

Filter Tips

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

#	Player Name	#	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP	Age	Contract	Salary
1	Trent Frederic	0	X	X			100.00	85	94	74	76	77	62	77	59	42	63	64	75	25	58	58	68	50	64	0	24	1	1,050,000$
2	Reese Johnson	0			X		100.00	99	80	87	63	72	57	61	55	71	62	56	80	25	47	47	65	50	60	0	23	2	800,000$
3	Cody McLeod	0		X	X		100.00	64	75	39	61	75	59	63	51	50	43	46	65	44	80	82	52	50	55	0	38	1	700,000$
4	Jamieson Rees (R)	0	X				100.00	69	63	83	64	63	61	63	54	68	55	48	59	46	44	44	55	50	54	0	21	2	910,833$
5	Dennis Yan (R)	0		X			100.00	75	73	79	63	73	52	52	52	50	47	53	62	50	44	44	57	50	54	0	25	1	700,000$
6	Brian Halonen (R)	0		X			100.00	79	74	89	67	74	38	35	52	50	44	56	64	53	44	44	58	50	53	0	23	1	700,000$
7	Vincent Marleau (R)	0	X		X		100.00	77	72	89	64	72	45	45	47	59	44	45	61	43	44	44	53	50	51	0	22	1	700,000$
8	Calen Addison (R)	0				X	100.00	71	42	95	81	66	63	72	76	25	50	54	64	25	45	46	63	50	62	0	22	1	795,000$
9	Nils Lundkvist (R)	0				X	100.00	67	42	99	76	66	64	58	64	25	50	48	66	25	46	46	59	50	60	0	21	2	925,000$
10	Connor Mackey (R)	0				X	100.00	68	72	58	71	72	67	70	55	25	54	42	59	40	44	44	54	50	58	0	25	1	912,500$
11	Jordan Gross	0				X	100.00	71	68	79	66	68	62	62	63	25	61	51	62	48	44	44	60	50	58	0	27	2	762,500$
12	Dakota Mermis	0				X	100.00	68	71	61	67	71	58	60	54	25	49	41	61	39	55	55	53	50	57	0	28	1	750,000$
13	Tobias Geisser (R)	0				X	100.00	81	77	90	63	77	54	56	46	25	37	40	63	38	44	44	52	50	56	0	23	1	700,000$
14	Quinn Wichers	0				X	100.00	84	81	91	64	81	37	37	41	25	28	39	63	37	44	44	49	50	53	0	24	1	700,000$
Scratches
1	Evan Weinger	0			X		100.00	76	70	90	64	70	64	66	56	50	49	58	63	55	44	44	60	50	57	0	25	0	0$
2	Drake Rymsha (R)	0	X				100.00	68	68	67	60	68	49	50	48	60	47	44	57	42	44	44	50	50	50	0	23	0	0$
3	Bowen Byram	0				X	100.00	83	45	87	86	71	77	56	67	25	68	60	71	25	48	48	69	50	66	0	21	1	894,167$
4	Chris Bigras	0				X	100.00	76	71	86	63	71	52	53	51	25	39	46	65	44	57	57	55	50	57	0	27	0	0$
5	Tarmo Reunanen (R)	0				X	100.00	73	65	90	68	65	56	57	52	25	48	41	61	39	44	44	54	50	56	0	24	0	0$
6	Logan Day	0				X	100.00	79	75	88	63	75	61	65	47	25	38	41	62	39	44	44	53	50	56	0	27	0	0$

	TEAM AVERAGE						100.00	76	69	81	68	71	57	58	55	39	49	49	64	39	48	48	57	50	57

Show or Hide Column

Filter Tips

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

#	Goalie Name	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP	Age	Contract	Salary
Scratches
1	Felix Sandstrom (R)	100.00	50	45	56	75	52	52	51	56	54	53	30	44	44	52	50	53	0	25	2	775,000$
2	Tommy Nappier (R)	100.00	48	41	51	81	49	49	52	55	52	52	30	44	44	50	50	52	0	24	0	0$
3	Mat Robson (R)	100.00	44	40	50	78	43	42	50	51	46	47	30	44	44	46	50	49	0	26	0	0$
4	Isaiah Saville (R)	100.00	44	40	50	74	45	44	45	49	45	45	45	44	44	45	50	48	0	21	1	700,000$

	TEAM AVERAGE	100.00	47	42	52	77	47	47	50	53	49	49	34	44	44	48	50	51

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Neil Graham	64	63	69	72	55	52	90	CAN	36	3	70,000$

Show or Hide Column

Filter Tips

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

#	Player Name	Team Name	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	GA	TA	HT	P/20	PSS	FW	FL	FT	S1	S2	S3
1	Calen Addison	Milwaukee Admirals (WIN)	D	8	3	12	15	-5	0	0	5	7	39	16	11	7.69%	8	167	20.94	2	2	4	5	12	0	0	0	1	13	0	0	0.00%	0	6	6	0	1.79	0	0	0	0	0	0	0
2	Bowen Byram	Milwaukee Admirals (WIN)	D	7	1	13	14	-3	2	0	12	14	42	16	24	2.38%	6	160	23.00	1	4	5	6	12	0	1	1	4	18	0	0	0.00%	0	12	5	0	1.74	0	0	0	0	0	1	1
3	Reese Johnson	Milwaukee Admirals (WIN)	RW	8	8	6	14	-11	7	5	14	12	42	12	30	19.05%	8	185	23.13	2	4	6	4	11	0	0	0	0	8	0	0	23.13	37	8	9	1	1.51	1	1	0	0	1	0	0
4	Trent Frederic	Milwaukee Admirals (WIN)	C/LW	4	9	2	11	-6	17	15	4	4	22	5	8	40.91%	2	83	20.90	5	2	7	7	7	0	0	0	0	4	1	0	20.90	97	1	5	1	2.63	1	2	0	1	1	0	0
5	Dennis Yan	Milwaukee Admirals (WIN)	LW	5	6	3	9	3	2	0	7	7	31	8	12	19.35%	0	114	22.85	1	0	1	2	7	1	0	1	1	7	1	0	22.85	8	1	5	1	1.58	0	0	0	0	1	0	1
6	Vincent Marleau	Milwaukee Admirals (WIN)	C/RW	5	0	7	7	-1	5	5	6	8	21	12	16	0.00%	4	110	22.15	0	2	2	2	7	0	0	0	0	1	0	0	22.15	25	2	2	0	1.26	0	1	0	0	0	0	1
7	Jamieson Rees	Milwaukee Admirals (WIN)	C	10	3	4	7	-6	7	5	10	17	29	7	22	10.34%	5	169	16.91	0	1	1	0	4	0	0	0	0	9	0	1	16.91	110	7	3	0	0.83	0	0	0	1	1	0	0
8	Nils Lundkvist	Milwaukee Admirals (WIN)	D	8	0	6	6	-3	0	0	8	10	21	8	8	0.00%	14	175	21.99	0	1	1	1	9	0	0	0	1	16	0	0	0.00%	0	2	13	0	0.68	0	0	0	0	0	0	0
9	Dakota Mermis	Milwaukee Admirals (WIN)	D	10	0	6	6	-5	12	0	10	6	15	7	3	0.00%	5	152	15.29	0	0	0	0	2	0	0	0	1	4	0	0	0.00%	0	2	5	0	0.79	0	0	0	0	0	0	0
10	Cody McLeod	Milwaukee Admirals (WIN)	LW/RW	5	1	4	5	-6	4	0	10	7	16	2	11	6.25%	3	112	22.53	0	0	0	2	9	0	0	0	0	6	0	0	22.53	7	2	2	0	0.89	0	0	0	0	0	1	0
11	Brian Halonen	Milwaukee Admirals (WIN)	LW	5	1	1	2	-2	0	0	1	3	8	3	4	12.50%	3	75	15.15	0	0	0	0	0	1	0	1	2	3	0	0	0.00%	5	3	1	0	0.53	0	0	0	0	0	0	0
12	Jordan Gross	Milwaukee Admirals (WIN)	D	10	0	2	2	-2	5	5	1	7	1	2	2	0.00%	3	56	5.61	0	0	0	0	0	0	1	1	0	1	0	0	0.00%	0	0	0	0	0.71	0	1	0	0	0	0	0
13	Tanner Kero	Jets	C/LW	1	1	0	1	0	0	0	2	2	2	1	3	50.00%	0	20	20.40	0	0	0	0	2	0	0	0	0	0	0	0	20.40	15	3	1	0	0.98	0	0	0	0	0	0	0
14	Connor Mackey	Milwaukee Admirals (WIN)	D	9	0	0	0	-2	7	5	5	10	5	1	4	0.00%	8	101	11.29	0	0	0	1	5	0	0	0	1	3	0	0	0.00%	1	3	6	0	0.00%	0	0	0	1	0	0	0
15	Quinn Wichers	Milwaukee Admirals (WIN)	D	5	0	0	0	-3	0	0	2	5	2	0	1	0.00%	2	39	7.85	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	1	0	0.00%	0	0	0	0	0	0	0
16	Tobias Geisser	Milwaukee Admirals (WIN)	D	5	0	0	0	-6	5	5	3	6	3	1	2	0.00%	3	51	10.29	0	0	0	0	0	0	0	0	0	1	0	0	0.00%	0	0	3	0	0.00%	0	0	1	0	0	0	0
Team Total or Average				105	33	66	99	-58	73	45	100	125	299	101	161	11.04%	74	1777	16.93	11	16	27	30	94	2	2	4	11	100	2	1	53.44%	305	52	67	3	1.11	2	5	1	3	4	2	3

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	L	PCT	GAA	MP	GA	SA	SAR	PS %	ST	BG
1	Felix Sandstrom	Milwaukee Admirals (WIN)	2	1	0.826	6.23	77	8	46	32	0.00%	2	0
2	Isaiah Saville	Milwaukee Admirals (WIN)	2	0	0.971	0.98	61	1	34	22	0.00%	1	2
Team Total or Average			4	1	0.888	3.91	138	9	80	54		3	2

Show or Hide Column

Filter Tips

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

Player Name	Team Name	POS	Age	Birthday	Rookie	Weight	Height	No Trade	Available For Trade	Force Waivers	Contract	Type	Current Salary	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Salary Year 2	Link
Bowen Byram	Milwaukee Admirals (WIN)	D	21	2001-06-12	No	190 Lbs	6 ft1	No	No	No	1	Pro & Farm	894,167$	0$	0$	No		Link / NHL Link
Brian Halonen	Milwaukee Admirals (WIN)	LW	23	1999-01-11	Yes	207 Lbs	6 ft0	No	No	No	1	Pro & Farm	700,000$	0$	0$	No		Link
Calen Addison	Milwaukee Admirals (WIN)	D	22	2000-04-10	Yes	180 Lbs	5 ft11	No	No	No	1	Pro & Farm	795,000$	0$	0$	No		Link / NHL Link
Chris Bigras	Milwaukee Admirals (WIN)	D	27	1995-02-22	No	191 Lbs	6 ft1	No	No	No	0	Pro & Farm		0$	0$	No		Link / NHL Link
Cody McLeod	Milwaukee Admirals (WIN)	LW/RW	38	1984-06-26	No	204 Lbs	6 ft2	Yes	No	No	1	Pro & Farm	700,000$	0$	0$	No		Link / NHL Link
Connor Mackey	Milwaukee Admirals (WIN)	D	25	1996-09-12	Yes	190 Lbs	6 ft2	No	No	No	1	Pro & Farm	912,500$	0$	0$	No		Link / NHL Link
Dakota Mermis	Milwaukee Admirals (WIN)	D	28	1994-01-05	No	196 Lbs	6 ft0	No	No	No	1	Pro & Farm	750,000$	0$	0$	No		Link / NHL Link
Dennis Yan	Milwaukee Admirals (WIN)	LW	25	1997-04-14	Yes	197 Lbs	6 ft2	No	No	No	1	Pro & Farm	700,000$	0$	0$	No		Link
Drake Rymsha	Milwaukee Admirals (WIN)	C	23	1998-08-06	Yes	187 Lbs	6 ft0	No	No	No	0	Pro & Farm		0$	0$	No		Link / NHL Link
Evan Weinger	Milwaukee Admirals (WIN)	RW	25	1997-04-18	No	194 Lbs	6 ft0	No	No	No	0	Pro & Farm		0$	0$	No		Link / NHL Link
Felix Sandstrom	Milwaukee Admirals (WIN)	G	25	1997-01-12	Yes	191 Lbs	6 ft2	No	No	No	2	Pro & Farm	775,000$	0$	0$	No	775,000$	Link / NHL Link
Isaiah Saville	Milwaukee Admirals (WIN)	G	21	2000-09-21	Yes	196 Lbs	6 ft1	No	No	No	1	Pro & Farm	700,000$	0$	0$	No
Jamieson Rees	Milwaukee Admirals (WIN)	C	21	2001-02-26	Yes	172 Lbs	5 ft11	No	No	No	2	Pro & Farm	910,833$	0$	0$	No	910,833$	Link / NHL Link
Jordan Gross	Milwaukee Admirals (WIN)	D	27	1995-05-09	No	190 Lbs	5 ft10	No	No	No	2	Pro & Farm	762,500$	0$	0$	No	762,500$	Link / NHL Link
Logan Day	Milwaukee Admirals (WIN)	D	27	1994-09-19	No	209 Lbs	6 ft1	No	No	No	0	Pro & Farm		0$	0$	No		Link / NHL Link
Mat Robson	Milwaukee Admirals (WIN)	G	26	1996-03-26	Yes	190 Lbs	6 ft3	No	No	No	0	Pro & Farm		0$	0$	No		Link / NHL Link
Nils Lundkvist	Milwaukee Admirals (WIN)	D	21	2000-07-27	Yes	187 Lbs	5 ft10	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$	Link
Quinn Wichers	Milwaukee Admirals (WIN)	D	24	1997-08-19	No	216 Lbs	6 ft4	No	No	No	1	Pro & Farm	700,000$	0$	0$	No		Link
Reese Johnson	Milwaukee Admirals (WIN)	RW	23	1998-07-10	No	193 Lbs	6 ft1	No	No	No	2	Pro & Farm	800,000$	0$	0$	No	800,000$	Link / NHL Link
Tarmo Reunanen	Milwaukee Admirals (WIN)	D	24	1998-03-01	Yes	179 Lbs	6 ft0	No	No	No	0	Pro & Farm		0$	0$	No		Link / NHL Link
Tobias Geisser	Milwaukee Admirals (WIN)	D	23	1999-02-13	Yes	201 Lbs	6 ft4	No	No	No	1	Pro & Farm	700,000$	0$	0$	No		Link
Tommy Nappier	Milwaukee Admirals (WIN)	G	24	1998-06-22	Yes	214 Lbs	6 ft2	No	No	No	0	Pro & Farm		0$	0$	No		Link / NHL Link
Trent Frederic	Milwaukee Admirals (WIN)	C/LW	24	1998-02-11	No	203 Lbs	6 ft2	No	No	No	1	Pro & Farm	1,050,000$	0$	0$	No		Link / NHL Link
Vincent Marleau	Milwaukee Admirals (WIN)	C/RW	22	1999-07-05	Yes	190 Lbs	6 ft2	No	No	No	1	Pro & Farm	700,000$	0$	0$	No		Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
24	24.54	194 Lbs	6 ft1	0.92	561,458$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Cody McLeod			40	1	2	2
2	Dennis Yan		Vincent Marleau	30	1	2	2
3	Brian Halonen	Jamieson Rees		20	1	2	2
4	Cody McLeod	Vincent Marleau		10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			40	1	2	2
2		Connor Mackey	30	1	2	2
3	Jordan Gross	Dakota Mermis	20	1	2	2
4	Tobias Geisser	Quinn Wichers	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Cody McLeod			60	1	2	2
2	Dennis Yan		Vincent Marleau	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2		Connor Mackey	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1		Cody McLeod	60	1	2	2
2		Dennis Yan	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2		Connor Mackey	40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1		60	1	2	2			60	1	2	2
2		40	1	2	2		Connor Mackey	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1		Cody McLeod	60	1	2	2
2		Dennis Yan	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2		Connor Mackey	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Cody McLeod

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Cody McLeod

Extra Forwards
Normal	PowerPlay	Penalty Kill
Dennis Yan, Jamieson Rees, Brian Halonen	Dennis Yan, Jamieson Rees	Dennis Yan

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Dakota Mermis, Tobias Geisser, Quinn Wichers	Dakota Mermis	Dakota Mermis, Tobias Geisser

Penalty Shots
, , , Cody McLeod, Dennis Yan

Goalie
#1 : , #2 :

Custom OT Lines Forwards
, , , , , , , , , ,

Custom OT Lines Defensemen
, , , ,

Show or Hide Column

Filter Tips

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

	Overall												Home											Visitor
#	VS Team	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	PCT	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
1	Binghampton Senators	2	1	0	0	0	0	0	1	9	8	1	1	1	0	0	0	0	0	0	5	3	2	1	0	0	0	0	0	0	1	4	5	-1	3	0.750	9	15	24	0	0	17	15	23	0	75	127	104	159	4	80	29	25	37	7	3	42.86%	4	1	75.00%	0	95	206	46.12%	59	154	38.31%	87	217	40.09%	201	115	218	94	185	89
2	Boisbriand Armada	2	0	2	0	0	0	0	0	13	16	-3	1	0	1	0	0	0	0	0	5	7	-2	1	0	1	0	0	0	0	0	8	9	-1	0	0.000	13	24	37	0	0	17	15	23	0	85	127	104	159	4	74	27	16	27	2	1	50.00%	8	4	50.00%	1	95	206	46.12%	59	154	38.31%	87	217	40.09%	201	115	218	94	185	89
3	Brampton Battalion	2	1	1	0	0	0	0	0	11	10	1	1	0	1	0	0	0	0	0	3	6	-3	1	1	0	0	0	0	0	0	8	4	4	2	0.500	11	18	29	0	0	17	15	23	0	70	127	104	159	4	64	14	33	29	7	3	42.86%	4	2	50.00%	2	95	206	46.12%	59	154	38.31%	87	217	40.09%	201	115	218	94	185	89
4	Lowell Devils	2	0	2	0	0	0	0	0	9	17	-8	1	0	1	0	0	0	0	0	5	11	-6	1	0	1	0	0	0	0	0	4	6	-2	0	0.000	9	18	27	0	0	17	15	23	0	66	127	104	159	4	70	26	14	29	6	2	33.33%	7	3	57.14%	0	95	206	46.12%	59	154	38.31%	87	217	40.09%	201	115	218	94	185	89
5	Toronto Marlies	2	0	2	0	0	0	0	0	13	23	-10	1	0	1	0	0	0	0	0	5	11	-6	1	0	1	0	0	0	0	0	8	12	-4	0	0.000	13	23	36	0	0	17	15	23	0	95	127	104	159	4	81	24	17	25	7	5	71.43%	6	3	50.00%	0	95	206	46.12%	59	154	38.31%	87	217	40.09%	201	115	218	94	185	89
	Total	10	2	7	0	0	0	0	1	55	74	-19	5	1	4	0	0	0	0	0	23	38	-15	5	1	3	0	0	0	0	1	32	36	-4	5	0.250	55	98	153	0	0	17	15	23	0	391	127	104	159	4	369	120	105	147	29	14	48.28%	29	13	55.17%	3	95	206	46.12%	59	154	38.31%	87	217	40.09%	201	115	218	94	185	89
	_Since Last GM Reset	10	2	7	0	0	0	0	1	55	74	-19	5	1	4	0	0	0	0	0	23	38	-15	5	1	3	0	0	0	0	1	32	36	-4	5	0.250	55	98	153	0	0	17	15	23	0	391	127	104	159	4	369	120	105	147	29	14	48.28%	29	13	55.17%	3	95	206	46.12%	59	154	38.31%	87	217	40.09%	201	115	218	94	185	89
	_Vs Conference	10	2	7	0	0	0	0	1	55	74	-19	5	1	4	0	0	0	0	0	23	38	-15	5	1	3	0	0	0	0	1	32	36	-4	5	0.250	55	98	153	0	0	17	15	23	0	391	127	104	159	4	369	120	105	147	29	14	48.28%	29	13	55.17%	3	95	206	46.12%	59	154	38.31%	87	217	40.09%	201	115	218	94	185	89

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
10	5	L1	55	98	153	391	369	120	105	147	0	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
10	2	7	0	0	0	1	55	74

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	1	4	0	0	0	0	23	38

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	1	3	0	0	0	1	32	36

Last 10 Games
W	L	OTW	OTL	SOW	SOL
2	7	0	0	0	1

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
29	14	48.28%	29	13	55.17%	3

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
127	104	159	4	17	15	23	0

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
95	206	46.12%	59	154	38.31%	87	217	40.09%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
201	115	218	94	185	89

Last Played Games Show or Hide Column

Filter Tips

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

Day	Game	Visitor Team	Score	Home Team	Score	ST	OT	SO	Link
1 - 2022-09-25	7	Lowell Devils	11	Milwaukee Admirals	5	BL			BoxScore
2 - 2022-09-26	24	Milwaukee Admirals	4	Lowell Devils	6	AL			BoxScore
4 - 2022-09-28	39	Toronto Marlies	11	Milwaukee Admirals	5	BL			BoxScore
6 - 2022-09-30	62	Milwaukee Admirals	8	Boisbriand Armada	9	AL			BoxScore
7 - 2022-10-01	77	Boisbriand Armada	7	Milwaukee Admirals	5	BL			BoxScore
9 - 2022-10-03	99	Brampton Battalion	6	Milwaukee Admirals	3	BL			BoxScore
12 - 2022-10-06	125	Milwaukee Admirals	8	Brampton Battalion	4	AW			BoxScore
13 - 2022-10-07	133	Binghampton Senators	3	Milwaukee Admirals	5	BW			BoxScore
14 - 2022-10-08	145	Milwaukee Admirals	4	Binghampton Senators	5	AL	X	X	BoxScore
15 - 2022-10-09	152	Milwaukee Admirals	8	Toronto Marlies	12	AL			BoxScore

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	2000	1000
Ticket Price	24	10
Attendance	0	0
Attendance PCT	0.00%	0.00%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
0	0 - 0.00%	0$	0$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
0$	1,347,500$	1,330,000$	0$

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

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

Milwaukee Admirals Stat Leaders (Regular Season)

Show or Hide Column

#	Player Name	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS
1	Frederick Gaudreau	288	200	256	456	-64	104	448	652	1260	15.87%	216	6006	20.86	44	84	128	124	4	0	4	16	8	12	57.17	12	1.52	8	20
2	Troy Terry	240	172	252	424	-92	56	312	500	928	18.53%	188	5842	24.34	52	56	108	116	0	0	0	16	16	4	38.02	4	1.45	4	20
3	Evan Weinger	397	176	202	378	-149	224	513	629	1321	13.32%	242	7452	18.77	22	35	57	97	0	0	0	9	15	6	45.14	0	1.01	8	8
4	Brett Ritchie	252	132	232	364	-120	484	464	376	772	17.10%	224	5238	20.79	16	76	92	76	0	4	4	12	24	8	34.69	0	1.39	4	20
5	Axel Jonsson-Fjallby	328	140	160	300	-108	188	452	424	784	17.86%	200	5881	17.93	28	36	64	76	4	4	8	8	0	4	37.50	12	1.02	0	4

Milwaukee Admirals Goalies Stat Leaders (Regular Season)

Show or Hide Column

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	GA	SA	SAR	A	EG	PS %	PSA
1	Anton Forsberg	257	110	93	27	0.871	4.62	14107	18	1085	8379	4553	14	2	0.711	76
2	Mat Robson	108	24	56	0	0.858	5.29	4676	8	412	2896	1624	4	4	0.00%	0
3	Mat Robson	33	11	17	2	0.871	4.93	1778	2	146	1133	674	1	1	0.800	5
4	Felix Sandstrom	15	3	9	1	0.857	5.39	813	2	73	510	296	1	0	0.00%	0

Milwaukee Admirals Career Team Stats

Show or Hide Column

	Overall											Home											Visitor
Year	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
Regular Season
2020	82	26	41	0	5	4	3	3	371	433	-62	41	14	20	0	2	2	2	1	186	200	-14	41	12	21	0	3	2	1	2	185	233	-48	75	371	602	973	1	0	87	124	152	13	2534	699	874	941	43	3005	1002	1265	1650	214	84	39.25%	220	83	62.27%	6	657	1471	44.66%	808	1754	46.07%	622	1488	41.80%	1518	736	1775	813	1667	837
2020	82	26	41	0	5	4	3	3	371	433	-62	41	14	20	0	2	2	2	1	186	200	-14	41	12	21	0	3	2	1	2	185	233	-48	75	371	602	973	1	0	87	124	152	13	2534	699	874	941	43	3005	1002	1265	1650	214	84	39.25%	220	83	62.27%	6	657	1471	44.66%	808	1754	46.07%	622	1488	41.80%	1518	736	1775	813	1667	837
2021	78	24	43	0	1	5	3	2	276	370	-94	39	13	20	0	1	2	3	0	148	182	-34	39	11	23	0	0	3	0	2	128	188	-60	63	276	466	742	3	0	61	107	104	5	2382	623	878	852	43	2916	957	1072	1362	210	88	41.90%	202	72	64.36%	6	627	1443	43.45%	752	1661	45.27%	608	1348	45.10%	1425	675	1693	767	1593	816
Total Regular Season	242	76	125	0	11	13	9	8	1018	1236	-218	121	41	60	0	5	6	7	2	520	582	-62	121	35	65	0	6	7	2	6	498	654	-156	213	1018	1670	2688	5	0	235	355	408	31	7450	2021	2626	2734	129	8926	2961	3602	4662	638	256	40.13%	642	238	62.93%	18	1941	4385	44.26%	2368	5169	45.81%	1852	4324	42.83%	4463	2148	5244	2394	4929	2491
Playoff
Total Playoff	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.00%	0	0	0	0.00%	0	0	0.00%	0	0	0.00%	0	0	0	0	0	0

Milwaukee Admirals Stat Leaders (Play-Off)

Show or Hide Column

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

Milwaukee Admirals Goalies Stat Leaders (Play-Off)

Show or Hide Column

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

	Milwaukee Admirals
	GP: 10 \| W: 2 \| L: 7 \| OTL: 1 \| P: 5 GF: 55 \| GA: 74 \| PP%: 48.28% \| PK%: 55.17% GM : Sebastien Doyon \| Morale : 45 \| Team Overall : 56