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
Jesper Boqvist	20	C/LW	100.00	78	40	90	76	70	58	94	63	67	64	67	68	58	63	59	74	75	74	25	450,000$/2yrs
Luke Glendening	13	C/RW	100.00	74	40	91	71	69	52	93	57	89	60	61	74	54	79	66	70	75	70	35
David Tomasek	96	C/RW	100.00	65	70	80	67	70	59	86	64	75	60	65	53	62	47	47	68	75	68	28	450,000$/3yrs
Jonathan Dahlen	54	LW	100.00	66	68	91	65	68	57	85	63	68	59	64	55	60	45	45	67	75	67	26
Yegor Sokolov (R)	43	LW/RW	100.00	67	76	89	63	76	56	88	61	80	56	61	44	58	42	42	66	75	66	24
Ethan Cardwell (R)	15	C/RW	100.00	65	64	85	65	64	58	85	61	59	59	58	58	55	39	39	66	75	66	21
Ty Rattie	39	RW	100.00	66	68	92	63	68	55	88	60	61	56	61	52	57	59	59	66	75	66	31
Nick Abruzzese (R)	26	C/LW	100.00	66	65	93	65	65	56	87	60	57	57	57	48	54	40	40	65	75	65	25	775,000$/1yrs
Cameron Hughes	56	C/LW	100.00	65	67	81	63	67	56	86	61	61	57	61	50	58	46	46	65	75	65	27
Filip Bystedt (R)	25	C/LW	100.00	66	70	86	63	69	56	76	58	57	53	61	55	58	34	34	63	75	63	20	875,000$/1yrs
Jesse Ylonen (R)	58	LW/RW	100.00	66	67	90	63	67	55	70	59	59	56	57	54	54	43	43	62	75	62	24
Jere Innala (R)	32	LW/RW	100.00	58	55	78	61	65	65	21	59	55	59	61	66	55	62	59	57	75	57	26
Parker Wotherspoon	5	D	100.00	63	40	90	77	71	69	66	56	40	62	57	88	54	57	58	72	75	72	26
Troy Stecher	51	D	100.00	60	64	85	73	66	59	80	55	40	61	58	78	54	70	59	69	75	69	30	625,000$/1yrs
Ville Ottavainen (R)	6	D	100.00	65	78	80	63	77	53	86	47	25	38	41	64	39	38	38	61	75	61	21	867,500$/2yrs
Sebastian Aho1	33	D	100.00	65	64	85	65	64	54	66	51	25	45	41	57	39	49	49	58	75	58	28
Johnny Kovacevic	97	D	100.00	11	11	11	11	11	11	11	11	11	11	11	11	11	11	11	11	75	11	26	766,667$/1yrs
Scratches
Tyler Motte	17	C/LW/RW	100.00	69	40	94	72	69	53	66	59	66	62	62	73	54	67	59	66	75	66	29
Jiri Smejkal	75	C/LW	100.00	67	78	82	65	78	56	72	57	66	48	59	60	56	46	46	63	75	63	27	500,000$/1yrs
Brett Berard (R)	11	LW	100.00	64	49	80	76	62	57	42	61	55	62	64	63	57	57	57	62	75	62	21	867,500$/2yrs
Gunnarwolfe Fontaine (R)	81	C/LW	100.00	65	64	93	63	64	54	79	55	32	47	58	52	55	36	36	61	75	61	23
Noel Gunler (R)	18	LW/RW	100.00	65	69	84	63	69	55	69	56	45	48	59	51	55	37	37	61	75	61	22	862,500$/1yrs
Gabriel Szturc (R)	67	C/LW	100.00	66	67	90	63	67	52	80	52	34	45	52	56	49	37	37	60	75	60	20
Matyas Sapovaliv (R)	42	C	100.00	66	71	88	62	71	53	83	51	49	45	52	48	48	37	37	60	75	60	20
Anton Lundmark (R)	92	LW/RW	100.00	67	71	91	62	72	52	83	49	43	44	48	58	45	33	33	60	75	60	23
Ludwig Persson (R)	0	C/LW	100.00	65	67	86	63	67	52	84	49	36	46	47	46	45	36	36	59	75	59	20
Chaz Lucius (R)	19	C	100.00	66	68	91	63	68	54	54	53	49	48	50	44	48	32	32	57	75	57	21
Joel Nystrom (R)	62	D	100.00	65	65	88	65	65	58	85	53	25	46	44	74	42	38	38	65	75	65	22	600,000$/3yrs
Calle Rosen	48	D	100.00	65	66	85	66	66	57	82	54	25	45	49	71	46	54	54	64	75	64	30	450,000$/2yrs
Nikita Novikov (R)	50	D	100.00	65	73	80	64	73	54	84	48	25	39	41	75	39	40	40	63	75	63	20	867,500$/2yrs
Adam Wilsby (R)	61	D	100.00	59	46	82	74	70	66	28	57	41	63	57	80	55	58	58	63	75	63	23
Jonathan Pudas	64	D	100.00	65	64	83	66	64	59	85	54	25	46	48	61	45	49	49	63	75	63	31
Samuel Johannesson (R)	2	D	100.00	65	66	88	66	66	58	82	51	25	45	42	51	40	38	38	59	75	59	23
Jorian Donovan (R)	37	D	100.00	65	73	67	63	74	51	73	46	25	35	41	55	38	38	38	56	75	56	20

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
Jonas Johansson	31	100.00	72	57	68	92	90	75	77	70	80	71	78	59	55	74	75	74	28	450,000$/2yrs
Clay Stevenson	0	100.00	49	53	64	68	49	56	49	49	49	49	42	35	35	49	75	49	25
Scratches
Magnus Chrona	30	100.00	52	52	62	71	52	59	52	52	52	52	45	35	35	50	75	50	23	867,500$/1yrs
Hugo Alnefelt	34	100.00	52	53	61	67	52	59	52	52	52	52	45	35	35	50	75	50	23
Kaidan Mbereko	35	100.00	38	54	62	59	38	45	38	38	38	38	31	35	35	43	75	43	20

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	GA	TA	EG	HT	P/20	PSG	PSS

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

Salary

Player Name	POS	Age	Cap Hit	2017-18	2018-19	2019-20	2020-21
Adam Wilsby	D	23	0$	RFA
Anton Lundmark	LW/RW	23	0$	RFA
Brett Berard	LW	21	867,500$	867,500$	867,500$
Calle Rosen	D	30	450,000$	450,000$	450,000$	RFA
Cameron Hughes	C/LW	27	0$	RFA
Chaz Lucius	C	21	0$
Clay Stevenson	G	25	0$	RFA
David Tomasek	C/RW	28	450,000$	450,000$	450,000$	450,000$	RFA
Ethan Cardwell	C/RW	21	0$
Filip Bystedt	C/LW	20	875,000$	875,000$
Gabriel Szturc	C/LW	20	0$
Gunnarwolfe Fontaine	C/LW	23	0$	RFA
Hugo Alnefelt	G	23	0$	RFA
Jere Innala	LW/RW	26	0$	RFA
Jesper Boqvist	C/LW	25	450,000$	450,000$	450,000$	RFA
Jesse Ylonen	LW/RW	24	0$	RFA
Jiri Smejkal	C/LW	27	500,000$	500,000$	RFA
Joel Nystrom	D	22	600,000$	600,000$	600,000$	600,000$
Johnny Kovacevic	D	26	766,667$	766,667$	RFA
Jonas Johansson	G	28	450,000$	450,000$	450,000$	RFA
Jonathan Dahlen	LW	26	0$	RFA
Jonathan Pudas	D	31	0$	RFA
Jorian Donovan	D	20	0$
Kaidan Mbereko	G	20	0$
Ludwig Persson	C/LW	20	0$
Luke Glendening	C/RW	35	0$	UFA
Magnus Chrona	G	23	867,500$	867,500$	RFA
Matyas Sapovaliv	C	20	0$
Nick Abruzzese	C/LW	25	775,000$	775,000$	RFA
Nikita Novikov	D	20	867,500$	867,500$	867,500$
Noel Gunler	LW/RW	22	862,500$	862,500$	RFA
Parker Wotherspoon	D	26	0$	RFA
Samuel Johannesson	D	23	0$	RFA
Sebastian Aho1	D	28	0$	RFA
Troy Stecher	D	30	625,000$	625,000$	RFA
Ty Rattie	RW	31	0$	RFA
Tyler Motte	C/LW/RW	29	0$	RFA
Ville Ottavainen	D	21	867,500$	867,500$	867,500$
Yegor Sokolov	LW/RW	24	0$	RFA

Lines

Forward Lines
# - Jesper Boqvist	# - Luke Glendening	# - Jesse Ylonen
# - Jere Innala	# - Cameron Hughes	# - David Tomasek
# - Yegor Sokolov	# - Nick Abruzzese	# - Ty Rattie
# - Jonathan Dahlen	# - Filip Bystedt	# - Ethan Cardwell

Defensive Pairings
# - Parker Wotherspoon	# - Johnny Kovacevic
# - Sebastian Aho1	# - Troy Stecher
# - Ville Ottavainen

1st Power Play Unit
# - Jesper Boqvist		# - Cameron Hughes		# - David Tomasek
# - Johnny Kovacevic			# - Parker Wotherspoon

2nd Power Play Unit
# - Jere Innala		# - Luke Glendening		# - Jesse Ylonen
# - Sebastian Aho1

Goalies
# - Jonas Johansson		# - Clay Stevenson

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	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	nan	nan	nan	0	0.000	nan	nan	nan	0	0	0	0	0	0	nan	0	0	0	0	nan	nan	nan	nan	nan	nan	0.00%	nan	nan	0.00%	0	0	0	0.00%	0	0	0.00%	0	0	0.00%	nan	nan	nan	nan	nan	nan	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
1,027,417$	0$	0$	75,000,000$

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

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
41	0 - 0.00%	0$	0$	3000	100

Expenses
Players Total Salaries	Players Total Average Salaries	Coaches Salaries	Special Salary Cap Value
1,027,417$	1,027,417$	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
	Division	Salming
	City	Sundsvall
	Stadium Capacity	3,000

Vikings Affiliation


	General Manager	Fredrik Pahlsson
	Head Coach
	Stadium
	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