Ultimate Hockey League - Today's Games Farm

Roster

Player	#	POS	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	AGE	CONTRACT
Gabe Perreault (R)	0	RW	99.00	65	65	85	64	64	56	79	59	52	56	57	60	54	33	33	64	75	64	20	875,000$/2yrs
Quinn Hutson (R)	0	RW	99.00	64	63	79	64	62	57	82	59	43	54	61	58	58	35	35	64	75	64	23	450,000$/2yrs
Carter Mazur (R)	0	LW	100.00	65	64	90	63	64	57	67	62	57	58	62	50	59	36	36	63	75	63	23	905,833$/2yrs
David Gustafsson (R)	0	C	100.00	73	66	93	68	74	47	43	58	78	62	60	77	54	58	58	62	75	62	25	835,000$/2yrs
Dylan Peterson (R)	0	C/RW	96.36	64	72	67	64	72	54	75	55	52	48	56	53	53	34	34	61	75	61	23	867,500$/2yrs
Michael Milne (R)	0	LW	100.00	65	66	83	63	65	56	73	56	36	48	58	47	55	38	38	61	75	61	22	861,667$/1yrs
Daniel Ljungman (R)	0	C/RW	100.00	65	65	91	63	65	52	74	52	34	47	53	59	49	37	37	60	75	60	23	450,000$/1yrs
Mason Primeau (R)	0	C	100.00	66	76	69	63	76	53	67	50	63	45	49	46	47	38	38	58	75	58	23	475,000$/1yrs
Ben MacDonald (R)	0	C	100.00	65	68	84	63	68	53	72	50	45	46	49	52	46	31	31	58	75	58	21	475,000$/1yrs
Michael Callow (R)	0	LW/RW	100.00	67	75	83	63	76	52	74	47	48	42	47	50	45	32	32	58	75	58	21	475,000$/1yrs
Justin Kipkie (R)	0	D	100.00	65	76	80	64	76	54	86	48	25	39	41	57	39	35	35	60	75	60	19	450,000$/1yrs
Tyson Hinds (R)	0	D	100.00	65	71	82	64	71	53	87	47	25	38	41	55	39	39	39	59	75	59	22	829,444$/2yrs
David Spacek (R)	0	D	100.00	65	68	84	66	68	56	85	51	25	45	41	50	39	37	37	59	75	59	22	550,000$/1yrs
Guillaume Richard (R)	0	D	100.00	65	68	85	64	68	53	81	47	25	37	41	58	39	34	34	58	75	58	22	475,000$/1yrs
Angus Booth (R)	0	D	100.00	65	66	79	64	66	53	67	47	25	39	40	65	38	39	39	58	75	58	21	826,667$/3yrs
Dylan MacKinnon (R)	0	D	100.00	65	73	67	64	72	53	83	44	25	33	40	58	37	39	39	58	75	58	20	550,000$/1yrs
Matthew Andonovski (R)	0	D	100.00	65	74	59	64	74	51	86	45	25	34	40	54	38	38	38	58	75	58	20	475,000$/1yrs
Terrell Goldsmith (R)	0	D	100.00	65	80	59	63	80	53	83	44	25	33	40	54	38	35	35	57	75	57	20	500,000$/2yrs
Scratches
Fyodor Svechkov (R)	0	C/LW	100.00	54	54	54	54	54	54	69	54	54	54	54	54	54	54	54	57	75	57	22	925,000$/2yrs
Ilya Fedotov (R)	0	LW	100.00	64	65	81	63	65	54	55	54	34	47	57	45	54	37	37	57	75	57	22	475,000$/2yrs
Connor Lockhart (R)	0	C	100.00	64	62	81	62	62	50	80	48	25	44	47	39	44	40	40	57	75	57	22	475,000$/1yrs
Jakub Stancl (R)	0	LW	100.00	66	73	86	63	72	52	84	48	43	44	47	39	45	31	31	56	75	56	20	500,000$/1yrs
Matthew Perkins (R)	0	C	100.00	65	64	88	62	64	49	75	46	25	41	46	42	43	33	33	56	75	56	21	500,000$/1yrs
Jan Kana	0	LW	100.00	65	65	90	62	65	49	63	46	25	42	45	43	43	46	46	55	75	55	33	450,000$/1yrs
Filip Barklund (R)	0	C/RW	100.00	40	40	40	40	40	40	40	40	40	40	40	40	40	40	40	40	75	40	22	450,000$/1yrs
Josh Pillar (R)	0	C/RW	100.00	40	40	40	40	40	40	40	40	40	40	40	40	40	40	40	40	75	40	23	450,000$/1yrs
Mason Langenbrunner (R)	0	D	100.00	65	72	80	64	72	52	75	46	25	36	41	55	39	33	33	57	75	57	22	450,000$/1yrs
George Fegaras (R)	0	D	100.00	65	76	84	63	76	54	74	47	25	37	40	53	38	32	32	57	75	57	21	475,000$/1yrs
Nolan Collins (R)	0	D	100.00	65	78	61	63	78	53	76	46	25	36	40	56	38	35	35	57	75	57	21	475,000$/1yrs
Will Francis (R)	0	D	100.00	65	78	73	65	78	50	43	43	25	31	39	42	37	33	33	51	75	51	24	450,000$/1yrs

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	PO	MO	OV	AGE	CONTRACT
Melvin Strahl	0	98.00	48	85	69	66	48	55	48	48	48	48	41	32	32	49	75	49	20	450,000$/1yrs
Hunter Miska	0	100.00	44	64	60	61	44	51	44	44	44	44	37	44	44	45	75	45	29	450,000$/1yrs
Scratches
Lukas Parik	0	100.00	40	58	58	69	40	47	40	40	40	40	33	38	38	44	75	44	24	450,000$/1yrs
Will Cranley	0	100.00	38	63	60	68	38	45	38	38	38	38	31	35	35	43	75	43	23	841,667$/1yrs

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

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	PSS
1	Ben MacDonald	Checkers (SLA)	C	48	19	21	40	-31	18	0	63	114	22	76	16.67%	4	17.54	2	6	8	0	0	0	38	0	0	42.13%	781	1	0.95	0
2	Quinn Hutson	Checkers (SLA)	RW	47	15	20	35	-22	16	0	67	144	30	108	10.42%	17	17.06	4	1	5	0	1	1	69	2	2	33.07%	254	0	0.87	0
3	Mason Primeau	Checkers (SLA)	C	49	11	23	34	-43	41	5	92	99	19	52	11.11%	8	19.86	1	10	11	0	0	0	71	0	0	51.32%	1177	0	0.70	0
4	Michael Milne	Checkers (SLA)	LW	50	14	14	28	-35	22	0	83	118	26	73	11.86%	14	21.46	3	6	9	0	0	0	125	1	0	28.14%	231	0	0.52	0
5	Carter Mazur	Checkers (SLA)	LW	48	13	14	27	-41	10	0	49	143	25	95	9.09%	13	20.17	2	4	6	0	0	0	113	1	0	42.98%	121	0	0.56	1
6	Michael Callow	Checkers (SLA)	LW/RW	52	8	16	24	-30	26	0	68	91	29	70	8.79%	8	19.32	2	6	8	0	0	0	68	0	0	40.22%	92	0	0.48	0
7	Daniel Ljungman	Checkers (SLA)	C/RW	46	10	13	23	-39	6	0	48	116	43	83	8.62%	18	18.74	1	3	4	0	0	0	65	0	0	30.31%	584	0	0.53	0
8	Gabe Perreault	Checkers (SLA)	RW	50	12	11	23	-18	4	0	45	101	30	64	11.88%	6	11.77	3	1	4	1	0	1	54	1	0	36.84%	76	0	0.78	0
9	Tyson Hinds	Checkers (SLA)	D	49	6	16	22	-43	40	0	81	64	15	41	9.38%	69	19.42	3	2	5	0	1	1	122	0	0	0.00%	2	0	0.46	0
10	Angus Booth	Checkers (SLA)	D	49	5	16	21	-27	30	0	67	57	18	41	8.77%	79	15.38	3	3	6	0	0	0	77	0	0	50.00%	8	0	0.56	0
11	Justin Kipkie	Checkers (SLA)	D	52	5	15	20	-50	42	0	112	68	31	47	7.35%	84	19.94	2	7	9	0	0	0	136	0	0	0.00%	0	0	0.39	0
12	Guillaume Richard	Checkers (SLA)	D	52	6	11	17	-42	14	0	77	71	20	50	8.45%	66	18.99	1	6	7	0	0	0	122	0	0	37.50%	8	0	0.34	0
13	David Gustafsson	Checkers (SLA)	C	43	7	8	15	-5	8	0	19	63	21	51	11.11%	7	6.61	1	0	1	0	0	0	0	1	0	60.28%	282	0	1.05	0
14	Dylan MacKinnon	Checkers (SLA)	D	52	1	13	14	-37	24	0	80	45	12	30	2.22%	61	14.50	1	2	3	0	0	0	55	0	0	0.00%	2	0	0.37	0
15	Dylan Peterson	Checkers (SLA)	C/RW	19	2	11	13	-13	8	0	46	42	10	33	4.76%	4	19.33	0	2	2	0	0	0	35	1	0	41.20%	432	0	0.71	0
16	George Fegaras	Checkers (SLA)	D	48	3	8	11	-21	8	0	20	27	13	18	11.11%	28	8.44	1	0	1	0	0	0	16	1	0	40.00%	5	0	0.54	0
17	Nolan Collins	Checkers (SLA)	D	43	2	9	11	-17	20	0	57	25	7	10	8.00%	36	9.35	0	0	0	0	0	0	9	0	0	100.00%	1	0	0.55	0
18	Matthew Andonovski	Checkers (SLA)	D	52	2	9	11	-46	44	0	129	37	20	33	5.41%	56	15.40	1	2	3	0	0	0	66	0	0	0.00%	0	0	0.27	0
19	Terrell Goldsmith	Checkers (SLA)	D	42	1	9	10	-12	14	0	44	14	10	13	7.14%	14	7.66	0	0	0	0	0	0	0	0	0	100.00%	1	0	0.62	0
20	Jakub Stancl	Checkers (SLA)	LW	33	4	5	9	-44	4	0	50	32	20	25	12.50%	3	18.74	1	0	1	0	0	0	30	0	0	48.19%	83	0	0.29	0
21	Connor Lockhart	Checkers (SLA)	C	40	3	5	8	-58	14	0	44	37	8	30	8.11%	3	18.21	1	1	2	0	0	0	21	0	0	29.75%	558	0	0.22	0
22	David Spacek	Checkers (SLA)	D	34	0	7	7	-9	20	0	33	12	3	11	0.00%	21	14.57	0	1	1	0	0	0	37	0	0	0.00%	0	0	0.28	0
23	Filip Barklund	Checkers (SLA)	C/RW	16	1	1	2	-9	4	0	11	5	1	1	20.00%	1	17.35	0	0	0	0	0	0	5	0	0	36.76%	68	0	0.14	0
24	Jan Kana	Checkers (SLA)	LW	10	1	1	2	-19	4	0	7	15	1	8	6.67%	4	18.34	0	0	0	0	0	0	6	0	0	28.57%	14	0	0.22	0
25	Matthew Perkins	Checkers (SLA)	C	16	2	0	2	-16	4	0	21	16	1	8	12.50%	0	14.29	0	0	0	0	0	0	2	0	0	20.18%	109	0	0.17	0
26	Will Francis	Checkers (SLA)	D	17	0	0	0	-9	8	0	7	4	0	2	0.00%	1	5.82	0	0	0	0	0	0	21	0	0	18.18%	11	0	0.00	0
27	Fyodor Svechkov	Checkers (SLA)	C/LW	1	0	0	0	0	0	0	0	0	0	0	0.00%	0	0.23	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.00	0
28	Josh Pillar	Checkers (SLA)	C/RW	6	0	0	0	-7	2	0	1	3	0	2	0.00%	0	18.47	0	0	0	0	0	0	0	0	0	28.57%	7	0	0.00	0
Team Total or Average			1064	153	276	429	-743	455	5	1421	1563	435	1075	9.79%	625	15.90	33	63	96	1274	1	2	3	1376	8	2	40.68%	4907	1	0.51	1

Show or Hide Column

Filter Tips

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

#	Goalie Name	Team Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S3
1	Melvin Strahl	Checkers (SLA)	48	4	39	2	0.853	6.30	2230	4	0	234	1590	0	2	1	0.000	0	46	5	1	0
2	Lukas Parik	Checkers (SLA)	4	1	1	0	0.867	5.17	151	0	0	13	98	0	0	0	0.000	0	1	5	0	0
3	Hunter Miska	Checkers (SLA)	21	0	5	0	0.886	4.93	743	4	0	61	533	0	1	0	0.000	0	5	42	0	0
Team Total or Average		73	5	45	2	0.861	5.91	3125	8	0	308	2221	0	3	1	0.000	0	52	52	1	0

Salary

Player Name	POS	Age	Cap Hit	2017-18	2018-19	2019-20
Angus Booth	D	21	826,667$	826,667$	826,667$	826,667$
Ben MacDonald	C	21	475,000$	475,000$
Carter Mazur	LW	23	905,833$	905,833$	905,833$
Connor Lockhart	C	22	475,000$	475,000$
Daniel Ljungman	C/RW	23	450,000$	450,000$
David Gustafsson	C	25	835,000$	835,000$	835,000$	RFA
David Spacek	D	22	550,000$	550,000$
Dylan MacKinnon	D	20	550,000$	550,000$
Dylan Peterson	C/RW	23	867,500$	867,500$	867,500$
Filip Barklund	C/RW	22	450,000$	450,000$
Fyodor Svechkov	C/LW	22	925,000$	925,000$	925,000$
Gabe Perreault	RW	20	875,000$	875,000$	875,000$
George Fegaras	D	21	475,000$	475,000$
Guillaume Richard	D	22	475,000$	475,000$
Hunter Miska	G	29	450,000$	450,000$	RFA
Ilya Fedotov	LW	22	475,000$	475,000$	475,000$
Jakub Stancl	LW	20	500,000$	500,000$
Jan Kana	LW	33	450,000$	450,000$	UFA
Josh Pillar	C/RW	23	450,000$	450,000$
Justin Kipkie	D	19	450,000$	450,000$
Lukas Parik	G	24	450,000$	450,000$	RFA
Mason Langenbrunner	D	22	450,000$	450,000$
Mason Primeau	C	23	475,000$	475,000$	RFA
Matthew Andonovski	D	20	475,000$	475,000$
Matthew Perkins	C	21	500,000$	500,000$
Melvin Strahl	G	20	450,000$	450,000$
Michael Callow	LW/RW	21	475,000$	475,000$
Michael Milne	LW	22	861,667$	861,667$
Nolan Collins	D	21	475,000$	475,000$
Quinn Hutson	RW	23	450,000$	450,000$	450,000$
Terrell Goldsmith	D	20	500,000$	500,000$	500,000$
Tyson Hinds	D	22	829,444$	829,444$	829,444$
Will Cranley	G	23	841,667$	841,667$
Will Francis	D	24	450,000$	450,000$	RFA

Lines

Forward Lines
# - Carter Mazur	# - Dylan Peterson	# - Quinn Hutson
# - Michael Milne	# - Daniel Ljungman	# - Gabe Perreault
# - Michael Callow	# - Mason Primeau	# - Ben MacDonald
# - Quinn Hutson	# - Ben MacDonald	# - Gabe Perreault

Defensive Pairings
# - Justin Kipkie	# - Tyson Hinds
# - Angus Booth	# - Guillaume Richard
# - Dylan MacKinnon	# - Matthew Andonovski

1st Power Play Unit
# - Carter Mazur		# - Dylan Peterson		# - Quinn Hutson
# - Justin Kipkie			# - Tyson Hinds

2nd Power Play Unit
# - Michael Milne		# - Daniel Ljungman		# - Gabe Perreault
# - Angus Booth			# - Guillaume Richard

Goalies
# - Melvin Strahl		# - Hunter Miska

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	OTL	GF	GA	Diff	P	PCT	G	A	TP	SO	GP1	GP2	GP3	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	HK	2	0	2	0	3.50	5.50	-2.00	0	0.000	3.5	6.5	10.0	1	58	45	41	30.5	482	433	451	4	46.0	9.0	9.00	24.0	3.00	2.00	66.67%	4.50	0.50	88.89%	1	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	505.50	321.00	711.50	207.50	346.00	158.50	23.1%	11.5%	88.0%	99.5	FUN
2	Ninjas	1	0	1	0	3.00	6.00	-3.00	0	0.000	3.0	6.0	9.0	0	58	45	41	27.0	482	433	451	4	45.0	13.0	8.00	28.0	3.00	0.00	0.00%	4.00	1.00	75.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	1,011.00	642.00	1,423.00	415.00	692.00	317.00	37.5%	11.1%	86.7%	97.8	FUN
3	Junior Wolves	1	0	1	0	1.00	6.00	-5.00	0	0.000	1.0	1.0	2.0	0	58	45	41	15.0	482	433	451	4	48.0	14.0	10.00	22.0	1.00	0.00	0.00%	5.00	1.00	80.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	1,011.00	642.00	1,423.00	415.00	692.00	317.00	16.7%	6.7%	87.5%	94.2	Unlucky
4	Shockers	2	0	2	0	2.00	8.00	-6.00	0	0.000	2.0	3.5	5.5	0	58	45	41	23.5	482	433	451	4	39.0	13.0	10.00	29.5	1.50	0.00	0.00%	4.50	2.00	55.56%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	505.50	321.00	711.50	207.50	346.00	158.50	25.0%	8.5%	79.5%	88.0	Unlucky
5	Gargoyles	6	1	5	0	1.67	5.17	-3.50	2	0.167	1.7	3.0	4.7	0	58	45	41	24.0	482	433	451	4	42.2	13.2	8.33	24.0	1.83	0.00	0.00%	4.00	0.83	79.17%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	168.50	107.00	237.17	69.17	115.33	52.83	27.8%	6.9%	87.7%	94.7	Unlucky
6	Sailors	2	0	2	0	3.00	6.00	-3.00	0	0.000	3.0	5.5	8.5	0	58	45	41	25.5	482	433	451	4	38.5	14.0	10.00	26.0	4.00	1.50	37.50%	4.00	1.00	75.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	505.50	321.00	711.50	207.50	346.00	158.50	23.1%	11.8%	84.4%	96.2	FUN
7	Devils	2	0	2	0	3.50	6.50	-3.00	0	0.000	3.5	5.0	8.5	0	58	45	41	30.5	482	433	451	4	42.0	13.5	8.00	25.0	2.50	1.00	40.00%	4.00	2.00	50.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	505.50	321.00	711.50	207.50	346.00	158.50	35.7%	11.5%	84.5%	96.0	FUN
8	Eagles	2	0	2	0	2.50	5.00	-2.50	0	0.000	2.5	5.0	7.5	0	58	45	41	34.5	482	433	451	4	37.5	12.0	3.00	28.0	5.50	1.00	18.18%	1.50	0.50	66.67%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	505.50	321.00	711.50	207.50	346.00	158.50	25.0%	7.2%	86.7%	93.9	Unlucky
9	Ravens	1	0	1	0	1.00	4.00	-3.00	0	0.000	1.0	2.0	3.0	0	58	45	41	18.0	482	433	451	4	44.0	10.0	8.00	24.0	2.00	1.00	50.00%	4.00	1.00	75.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	1,011.00	642.00	1,423.00	415.00	692.00	317.00	0.0%	5.6%	90.9%	96.5	Unlucky
10	Venom	2	0	2	0	2.50	5.50	-3.00	0	0.000	2.5	4.5	7.0	0	58	45	41	26.0	482	433	451	4	46.5	17.5	11.00	25.5	2.50	1.00	40.00%	5.50	1.00	81.82%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	505.50	321.00	711.50	207.50	346.00	158.50	25.0%	9.6%	88.2%	97.8	FUN
11	Indians	1	1	0	0	4.00	3.00	1.00	2	1.000	4.0	7.0	11.0	0	58	45	41	24.0	482	433	451	4	40.0	10.0	10.00	17.0	3.00	0.00	0.00%	4.00	3.00	25.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	1,011.00	642.00	1,423.00	415.00	692.00	317.00	100.0%	16.7%	92.5%	109.2	LUCKY
12	Squirrels	2	0	2	0	3.00	6.00	-3.00	0	0.000	3.0	4.5	7.5	0	58	45	41	26.5	482	433	451	4	41.0	7.5	6.00	29.5	3.50	1.00	28.57%	2.50	0.50	80.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	505.50	321.00	711.50	207.50	346.00	158.50	26.7%	11.3%	85.4%	96.7	FUN
13	Blades	1	0	0	1	4.00	5.00	-1.00	1	0.500	4.0	7.0	11.0	0	58	45	41	25.0	482	433	451	4	46.0	15.0	13.00	23.0	5.00	0.00	0.00%	4.00	1.00	75.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	1,011.00	642.00	1,423.00	415.00	692.00	317.00	50.0%	16.0%	89.1%	105.1	FUN
14	Sharknado	4	1	3	0	2.75	5.75	-3.00	2	0.250	2.8	5.0	7.8	0	58	45	41	26.5	482	433	451	4	40.3	9.0	6.00	24.8	3.00	0.50	16.67%	2.75	0.75	72.73%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	252.75	160.50	355.75	103.75	173.00	79.25	31.0%	10.4%	85.7%	96.1	FUN
15	Barking Spiders	1	0	1	0	2.00	7.00	-5.00	0	0.000	2.0	3.0	5.0	0	58	45	41	27.0	482	433	451	4	31.0	4.0	10.00	16.0	4.00	1.00	25.00%	5.00	2.00	60.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	1,011.00	642.00	1,423.00	415.00	692.00	317.00	16.7%	7.4%	77.4%	84.8	Unlucky
16	Space Invaders	3	0	3	0	3.33	6.00	-2.67	0	0.000	3.3	5.7	9.0	0	58	45	41	23.3	482	433	451	4	50.0	10.3	8.00	23.7	2.33	0.33	14.29%	3.67	1.67	54.55%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	337.00	214.00	474.33	138.33	230.67	105.67	40.9%	14.3%	88.0%	102.3	FUN
17	Vikings	2	0	2	0	3.00	6.50	-3.50	0	0.000	3.0	5.5	8.5	0	58	45	41	24.5	482	433	451	4	56.5	14.0	5.00	26.5	1.00	0.50	50.00%	2.50	0.50	80.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	505.50	321.00	711.50	207.50	346.00	158.50	29.4%	12.2%	88.5%	100.7	FUN
18	Kangaroos	2	0	2	0	3.00	7.00	-4.00	0	0.000	3.0	5.0	8.0	0	58	45	41	27.5	482	433	451	4	37.0	6.0	5.00	20.5	2.00	0.00	0.00%	2.00	0.50	75.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	505.50	321.00	711.50	207.50	346.00	158.50	31.6%	10.9%	81.1%	92.0	FUN
19	Thistles	2	2	0	0	5.50	3.50	2.00	4	1.000	5.5	9.5	15.0	0	58	45	41	29.0	482	433	451	4	32.5	8.5	7.00	27.5	3.00	2.50	83.33%	3.00	0.50	83.33%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	505.50	321.00	711.50	207.50	346.00	158.50	50.0%	19.0%	89.2%	108.2	FUN
20	Barracudas	1	0	1	0	3.00	5.00	-2.00	0	0.000	3.0	6.0	9.0	0	58	45	41	39.0	482	433	451	4	35.0	14.0	4.00	18.0	4.00	0.00	0.00%	1.00	1.00	0.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	1,011.00	642.00	1,423.00	415.00	692.00	317.00	42.9%	7.7%	85.7%	93.4	Unlucky
21	Senators	1	0	1	0	3.00	8.00	-5.00	0	0.000	3.0	5.0	8.0	0	58	45	41	19.0	482	433	451	4	50.0	14.0	4.00	22.0	2.00	0.00	0.00%	2.00	1.00	50.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	1,011.00	642.00	1,423.00	415.00	692.00	317.00	30.0%	15.8%	84.0%	99.8	FUN
22	Pimps	2	0	2	0	2.00	6.00	-4.00	0	0.000	2.0	3.5	5.5	0	58	45	41	27.0	482	433	451	4	36.5	10.0	9.00	28.5	5.00	1.50	30.00%	4.50	1.50	66.67%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	505.50	321.00	711.50	207.50	346.00	158.50	10.0%	7.4%	83.6%	91.0	Unlucky
23	Wolf Pack	2	0	1	1	3.50	6.50	-3.00	1	0.250	3.5	6.5	10.0	0	58	45	41	32.0	482	433	451	4	47.0	11.5	11.00	31.5	2.50	1.00	40.00%	5.50	2.50	54.55%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	505.50	321.00	711.50	207.50	346.00	158.50	38.5%	10.9%	86.2%	97.1	FUN
24	Assassins	1	0	1	0	3.00	6.00	-3.00	0	0.000	3.0	6.0	9.0	0	58	45	41	25.0	482	433	451	4	54.0	10.0	10.00	16.0	2.00	0.00	0.00%	4.00	1.00	75.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	1,011.00	642.00	1,423.00	415.00	692.00	317.00	37.5%	12.0%	88.9%	100.9	FUN
25	Zolos	5	0	5	0	2.20	7.60	-5.40	0	0.000	2.2	4.0	6.2	0	58	45	41	25.0	482	433	451	4	45.0	12.6	9.60	30.2	3.60	0.60	16.67%	4.60	1.60	65.22%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	202.20	128.40	284.60	83.00	138.40	63.40	21.1%	8.8%	83.1%	91.9	Unlucky
26	Huskies	1	0	1	0	4.00	5.00	-1.00	0	0.000	4.0	6.0	10.0	0	58	45	41	32.0	482	433	451	4	40.0	6.0	10.00	21.0	3.00	1.00	33.33%	5.00	1.00	80.00%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	1,011.00	642.00	1,423.00	415.00	692.00	317.00	42.9%	12.5%	87.5%	100.0	FUN
	_Vs Division	22	4	18	0	2.59	6.05	-3.45	8	0.182	2.6	4.6	7.2	0	58	45	41	25.0	482	433	451	4	42.4	11.5	8.18	26.3	2.59	0.50	19.30%	3.82	1.18	69.05%	0	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	45.95	29.18	64.68	18.86	31.45	14.41	30.1%	10.4%	85.7%	96.1	FUN
	_Vs Conference	36	4	31	1	2.75	5.97	-3.22	9	0.125	2.8	4.9	7.7	1	58	45	41	26.4	482	433	451	4	43.3	11.8	8.06	26.7	2.81	0.75	26.73%	3.78	1.08	71.32%	1	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	28.08	17.83	39.53	11.53	19.22	8.81	29.0%	10.4%	86.2%	96.6	FUN
	_Since Last GM Reset	52	5	45	2	2.77	5.94	-3.17	12	0.115	2.8	4.9	7.6	1	58	45	41	26.3	482	433	451	4	42.7	11.4	8.10	25.3	2.87	0.67	23.49%	3.75	1.15	69.23%	1	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	19.44	12.35	27.37	7.98	13.31	6.10	30.4%	10.5%	86.1%	96.6	FUN
	Total	52	5	45	2	2.77	5.94	-3.17	12	0.115	2.8	4.9	7.6	1	58	45	41	26.3	482	433	451	4	42.7	11.4	8.10	25.3	2.87	0.67	23.49%	3.75	1.15	69.23%	1	623	1517	41.07%	817	2034	40.17%	353	978	36.09%	19.44	12.35	27.37	7.98	13.31	6.10	30.4%	10.5%	86.1%	96.6	FUN

	Puck Time
Offensive Zone	19
Neutral Zone	13
Defensive Zone	27

	Puck Time
Offensive Zone Start	1517
Neutral Zone Start	978
Defensive Zone Start	2034

	Puck Time
With Puck	26
Without Puck	33

	Faceoffs
Faceoffs Won	1793
Faceoffs Lost	2736

	Team Average Shots after	League Average Shots after
1st Period	9.3	9.57
2nd Period	17.6	20.31
3rd Period	26.3	30.68
Overtime	26.3	31.4

Goals in	Team Average Goals after	League Average Goals after
1st Period	1.1	0.64
2nd Period	2.0	1.65
3rd Period	2.8	2.67
Overtime	2.8	2.83


Even Strenght Goal	107
PP Goal	35
PK Goal	1
Empty Net Goal	1

	Home	Away
Win	3	2
Lost	22	23
Overtime Lost	2	0


PP Attempt	149
PP Goal	35
PK Attempt	195
PK Goal Against	60

	Home
Shots For	26.3
Shots Against	42.7
Goals For	2.8
Goals Against	5.9
Hits	25.3
Shots Blocked	11.4
Pim	8.1

Schedule

Date	Matchup			Result	Detail
1	THI	@	CHE	THI4,CHE5	RECAP
3	SHA	@	CHE	SHA7,CHE4	RECAP
5	EAG	@	CHE	EAG5,CHE3	RECAP
9	PIM	@	CHE	PIM7,CHE2	RECAP
12	CHE	@	GRG	CHE1,GRG5	RECAP
14	CHE	@	NIN	CHE3,NIN6	RECAP
16	CHE	@	THI	CHE6,THI3	RECAP
19	CHE	@	SHO	CHE2,SHO8	RECAP
22	KAN	@	CHE	KAN5,CHE4	RECAP
23	ZOL	@	CHE	ZOL8,CHE1	RECAP
26	GRG	@	CHE	GRG3,CHE2	RECAP
28	VIK	@	CHE	VIK5,CHE3	RECAP
31	CHE	@	RAV	CHE1,RAV4	RECAP
34	CHE	@	GRG	CHE1,GRG9	RECAP
37	CHE	@	PIM	CHE2,PIM5	RECAP
40	SPA	@	CHE	SPA6,CHE3	RECAP
41	ZOL	@	CHE	ZOL6,CHE1	RECAP
44	CHE	@	KAN	CHE2,KAN9	RECAP
46	CHE	@	JWO	CHE1,JWO6	RECAP
49	CHE	@	SHA	CHE1,SHA6	RECAP
51	CHE	@	SPA	CHE5,SPA6	RECAP
53	CHE	@	ZOL	CHE1,ZOL8	RECAP
56	CHE	@	GRG	CHE1,GRG7	RECAP
59	CHE	@	BAR	CHE3,BAR5	RECAP
61	SHA	@	CHE	SHA6,CHE1	RECAP
62	CHE	@	SEN	CHE3,SEN8	RECAP
64	CHE	@	ZOL	CHE4,ZOL8	RECAP
67	IND	@	CHE	IND3,CHE4	RECAP
69	GRG	@	CHE	GRG6,CHE2	RECAP
72	CHE	@	BKS	CHE2,BKS7	RECAP
74	CHE	@	DEV	CHE5,DEV7	RECAP
76	BLA	@	CHE	BLA5,CHE4 (OT)	RECAP
78	SQU	@	CHE	SQU6,CHE4	RECAP
80	CAN	@	CHE	CAN5,CHE4	RECAP
82	SHO	@	CHE	SHO8,CHE2	RECAP
84	WPK	@	CHE	WPK5,CHE4 (OT)	RECAP
85	VEN	@	CHE	VEN6,CHE4	RECAP
89	CHE	@	EAG	CHE2,EAG5	RECAP
91	CHE	@	VIK	CHE3,VIK8	RECAP
95	CHE	@	VEN	CHE1,VEN5	RECAP
97	CHE	@	SAI	CHE4,SAI6	RECAP
100	CHE	@	WPK	CHE3,WPK8	RECAP
102	CHE	@	OHK	CHE4,OHK6	RECAP
106	CHE	@	SHA	CHE5,SHA4	RECAP
109	SAI	@	CHE	SAI6,CHE2	RECAP
111	SPA	@	CHE	SPA6,CHE2	RECAP
112	SQU	@	CHE	SQU6,CHE2	RECAP
114	DEV	@	CHE	DEV6,CHE2	RECAP
117	GRG	@	CHE	GRG1,CHE3	RECAP
120	ASS	@	CHE	ASS6,CHE3	RECAP
123	ZOL	@	CHE	ZOL8,CHE4	RECAP
125	OHK	@	CHE	OHK5,CHE3	RECAP
127	CHE	@	THI
130	THI	@	CHE
133	SAI	@	CHE
136	CHE	@	THI
138	RAV	@	CHE
142	CHE	@	THI
143	CHE	@	ASS
145	CHE	@	BUL
147	CHE	@	SHO
150	NIN	@	CHE
152	BKS	@	CHE
154	VIK	@	CHE
155	VEN	@	CHE
158	SHO	@	CHE
159	BAR	@	CHE
161	SPA	@	CHE
162	JWO	@	CHE
Trade Deadline --- Trades can�t be done after this day is simulated!
166	BUL	@	CHE
169	CHE	@	SHA
171	CHE	@	IND
173	CHE	@	CAN
174	SHO	@	CHE
176	SEN	@	CHE
179	CHE	@	SPA
181	CHE	@	BLA
185	CHE	@	VEN
187	CHE	@	WPK
189	CHE	@	SQU
191	CHE	@	OHK
194	CHE	@	EAG

Finance

Salary Cap
Players Total Salaries	Retained Salary	Total Cap Hit	Estimated Cap Space
1,959,278$	0$	0$	75,000,000$

Arena	About us
	Name
	City	Astoria
	Capacity	3000
	Season Ticket Holders	10%

Arena Capacity - Ticket Price Attendance - %

Arena Capacity	2000	1000
Ticket Price	35$	15$	$	$	$
Attendance	44237	22508
Attendance PCT	81.92%	83.36%	0.00%	0.00%	0.00%

Income

Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
14	2472 - 82.40%	69,849$	1,885,915$	3000	100

Expenses
Players Total Salaries	Players Total Average Salaries	Coaches Salaries	Special Salary Cap Value
1,959,278$	1,959,278$	0$	0$

Year To Date Expenses	Salary Cap Per Days	Salary Cap To Date	Luxury Taxe Total
1,029,343$	10,099$	959,211$	0$

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
977,882$	69	10,099$	696,831$

Team Total Estimate
Estimated Season Expenses	Estimated Season Salary Cap	Current Bank Account	Projected Bank Account
696,831$	0$	0$	0$

Sponsors
TV Rights	Primary Sponsor	Secondary Sponsor	Secondary Sponsor

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

Zolos36-14-1, 73pts

84Final

Checkers5-45-2, 12pts

HK33-15-3, 69pts

53Final

Checkers5-45-2, 12pts

HK33-15-3, 69pts

Tue, Apr 14

Checkers5-45-2, 12pts

Sharknado37-14-1, 75pts

Sat, Dec 13

Checkers5-45-2, 12pts

Eagles30-18-5, 65pts

Mon, Dec 15

Checkers5-45-2, 12pts

TRANSACTIONS

Team Info


	Head Coach
	Division	LaFontaine
	City	Astoria
	Stadium Capacity	3,000

Checkers Affiliation


	General Manager	UHL (Bruce)
	Head Coach
	Stadium
	Capacity	18,000

Team Leaders

GOALS Ben MacDonald Checkers	19 GOALS
POINTS Ben MacDonald Checkers	40 POINTS
WINS Melvin Strahl Checkers	4 WINS
Expanded Player Leaderboard

Team Stats

Goals For 144 2.77 GFG	Goals Against 309 5.94 GAA
Power Play Percentage 23.5% 35 GF	Penalty Kill Percentage 69.2% 60 GA
Expanded Team Stats

Team Captain - Alternate Captains

Captain

Alternate Captain