LHP - Today's Games Farm

Roster

Player	#	POS	CON	Age	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	Overall	Condition	Contract
Scratches
Mason Shaw	0	C	100.00	23	74	76	82	64	74	62	70	61	60	72	64	77	54	56	58	0	40	69	100.00	750,000$/3yrs
Juuso Parssinen	0	C	100.00	21	74	63	84	63	80	67	64	64	74	75	62	68	54	55	57	0	40	69	100.00	925,000$/2yrs
Justin Danforth	0	RW	100.00	29	64	40	71	57	80	70	63	58	53	73	73	61	54	56	58	0	40	68	100.00	975,000$/3yrs
Dave Gust	0	C	100.00	28	55	58	64	63	58	67	65	64	55	60	64	61	54	68	60	0	40	64	100.00	762,500$/3yrs
Hugh McGing	0	LW	100.00	24	56	57	64	60	57	68	66	60	55	58	60	61	54	60	56	0	40	62	100.00	750,000$/3yrs
Lauri Pajuniemi	0	C	100.00	23	55	60	66	61	63	67	65	60	55	58	61	62	54	59	55	0	40	62	100.00	925,000$/3yrs
Adam Klapka	0	RW	100.00	22	56	55	62	59	78	66	64	58	55	56	59	60	54	57	54	0	40	62	100.00	832,500$/3yrs
Ville Petman	0	C	100.00	22	54	55	66	58	59	68	66	59	70	57	59	62	54	57	54	0	40	61	100.00	925,000$/3yrs
Henri Nikkanen	0	C	100.00	21	55	55	66	57	69	67	65	57	70	56	56	59	54	55	53	0	40	60	100.00	925,000$/2yrs
Tyson Kozak	0	C	100.00	19	55	55	65	57	56	65	63	56	70	55	56	60	54	54	52	0	40	59	100.00	850,000$/1yrs
Lukas Svejkovsky	0	RW	100.00	20	54	57	67	58	56	63	61	56	55	56	55	58	60	55	53	0	40	59	100.00	925,000$/2yrs
Will Borgen	0	D	100.00	25	79	67	82	71	78	74	84	60	40	74	59	60	54	58	58	0	40	69	100.00	900,000$/3yrs
Declan Carlile	0	D	100.00	22	55	57	65	58	64	67	65	58	40	57	57	66	54	57	54	0	40	62	100.00	925,000$/2yrs
Mac Hollowell	0	D	100.00	23	57	51	69	59	62	60	57	56	40	62	54	62	54	59	56	0	40	61	100.00	750,000$/3yrs
Philip Kemp	0	D	100.00	23	55	57	64	57	69	68	66	57	40	57	56	63	54	59	55	0	40	61	100.00	786,667$/2yrs
Griffin Mendel	0	D	100.00	23	55	55	66	58	73	68	66	57	40	56	57	58	54	59	55	0	40	61	100.00	750,000$/3yrs
Santtu Kinnunen	0	D	100.00	23	55	54	66	62	57	67	65	60	40	59	57	59	54	59	55	0	40	61	100.00	925,000$/3yrs
Adam Wilsby	0	D	100.00	22	55	54	66	57	63	68	66	57	40	57	54	60	54	57	54	0	40	60	100.00	842,500$/3yrs

	TEAM AVERAGE		100.00

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Priority	Type	Description
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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`)
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7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
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	AGE	DI	ST	EN	DU	PA	DF	PS	EX	LD	PO	MO	Overall
Scratches
Pheonix Copley	0	100.00	30	76	74	74	74	80	83	62	57	0	40	75	825,000$/3yrs
Dustin Tokarski	0	100.00	33	60	64	63	64	68	62	77	65	0	40	64	775,000$/3yrs
Jet Greaves	0	100.00	21	61	66	66	60	67	61	54	51	0	40	63	758,333$/1yrs
Jaxson Stauber	0	100.00	23	61	59	58	57	71	58	57	54	0	40	63	925,000$/3yrs
Hunter Shepard	0	100.00	26	62	64	63	59	67	61	66	59	0	40	62	750,000$/3yrs

	TEAM AVERAGE	100.00

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Mike Eaves	72	64	69	64	99	94	46	USA	65	3	250,000$

General Manager

Player Stats

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

#	Player Name	Team Name	#	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPM	PKG	PKA	PKP	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS

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

#	Goalie Name	Team Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3

Salary


	Projected Total Cap Hit	0$
	Projected Cap Space	0$
	Retains And Buyout Cap Hit	0$
	Salary Cap To Date	0$
	Players In Salary Cap	0
	LTIR Players	0

Player Name	POS	Age	Cap Hit	2017-18	2018-19	2019-20
Adam Klapka	RW	22	832,500$	832,500$	832,500$	832,500$
Adam Wilsby	D	22	842,500$	842,500$	842,500$	842,500$
Dave Gust	C	28	762,500$	762,500$	762,500$	762,500$
Declan Carlile	D	22	925,000$	925,000$	925,000$
			0$	0$
Griffin Mendel	D	23	750,000$	750,000$	750,000$	750,000$
Henri Nikkanen	C	21	925,000$	925,000$	925,000$
Hugh McGing	LW	24	750,000$	750,000$	750,000$	750,000$
			0$	0$
			0$	0$
			0$	0$
Justin Danforth	RW	29	975,000$	975,000$	975,000$	975,000$
Juuso Parssinen	C	21	925,000$	925,000$	925,000$
Lauri Pajuniemi	C	23	925,000$	925,000$	925,000$	925,000$
Lukas Svejkovsky	RW	20	925,000$	925,000$	925,000$
Mac Hollowell	D	23	750,000$	750,000$	750,000$	750,000$
Mason Shaw	C	23	750,000$	750,000$	750,000$	750,000$
			0$	0$
Philip Kemp	D	23	786,667$	786,667$	786,667$
Santtu Kinnunen	D	23	925,000$	925,000$	925,000$	925,000$
Tyson Kozak	C	19	850,000$	850,000$
Ville Petman	C	22	925,000$	925,000$	925,000$	925,000$
Will Borgen	D	25	900,000$	900,000$	900,000$	900,000$

Lines

Forward Lines

Defensive Pairings

1st Power Play Unit

2nd Power Play Unit

Goalies

Team Stats

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

#	VS Team	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	GF%	SH%	SV%	PDO	PDOBRK
	Total	0	0	0	0	0	0	0	0	0	0	0	0	0.000	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	nan%	nan%	nan%	nan	Unlucky

	Puck Time
Offensive Zone	NAN
Neutral Zone	NAN
Defensive Zone	NAN

	Puck Time
Offensive Zone Start	0
Neutral Zone Start	0
Defensive Zone Start	0

	Puck Time
With Puck	NAN
Without Puck	NAN

	Faceoffs
Faceoffs Won	0
Faceoffs Lost	0

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

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


Even Strenght Goal	0
PP Goal	0
PK Goal	0
Empty Net Goal	0

	Home	Away
Win	0	0
Lost	0	0
Overtime Lost	0	0


PP Attempt	0
PP Goal	0
PK Attempt	0
PK Goal Against	0

	Home
Shots For	nan
Shots Against	nan
Goals For	nan
Goals Against	nan
Hits	nan
Shots Blocked	nan
Pim	nan

Schedule

Date	Matchup			Result	Detail

Finance

Salary Cap
Players Total Salaries	Retained Salary	Total Cap Hit	Estimated Cap Space
19,457,500$	0$	0$	75,000,000$

Arena	About us
	Name
	City	San Diego
	Capacity	3000
	Season Ticket Holders	0%

Arena Capacity - Ticket Price Attendance - %

Arena Capacity	2000	1000
Ticket Price	35$	15$	$	$	$
Attendance	0.00%	0.00%	0.00%	0.00%	0.00%
Attendance PCT	0.00%	0.00%	0.00%	0.00%	0.00%

Income

Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
5	0 - 0.00%	0$	0$	3000	100

Expenses
Players Total Salaries	Players Total Average Salaries	Coaches Salaries	Special Salary Cap Value
19,457,500$	19,457,500$	0$	0$

Year To Date Expenses	Salary Cap Per Days	Salary Cap To Date	Luxury Taxe Total
0$	0$	0$	0$

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

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

TRANSACTIONS

Team Info


	Head Coach	Mike Eaves
	Division	North Division
	City	San Diego
	Stadium Capacity	3,000

Gulls Affiliation


	General Manager	Christophe Jadot
	Head Coach	Claude Julien
	Stadium	Honda Center
	Capacity	18,000

Team Leaders

Expanded Player Leaderboard

Team Stats

Goals For 0 nan GFG	Goals Against 0 nan GAA
Power Play Percentage nan% 0 GF	Penalty Kill Percentage nan% 0 GA
Expanded Team Stats

Team Captain - Alternate Captains

Captain

Alternate Captain