Online Hockey League - Schedule Pro Stars

Roster

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	#	POS	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	AGE	CONTRACT
Nazem Kadri (A)	0	C	100.00	83	54	74	74	73	72	86	94	66	92	91	54	68	83	84	48	33	76	29	3,150,000$/4yrs
Reilly Smith	0	LW/RW	100.00	33	24	99	74	72	80	83	96	21	95	95	53	76	78	68	59	33	75	28	4,362,000$/3yrs
Brendan Gallagher	0	RW	100.00	74	53	74	75	72	86	84	86	40	79	86	66	76	76	70	67	33	73	27	4,018,000$/4yrs
Viktor Arvidsson (C)	0	LW/RW	100.00	53	15	84	77	74	88	85	82	49	76	86	73	70	58	58	77	33	72	26	4,302,000$/2yrs
Jussi Jokinen	0	C/LW/RW	100.00	65	47	76	70	72	78	87	78	83	78	75	59	80	99	99	1	33	71	36	4,500,000$/1yrs
Brandon Sutter	0	C/RW	100.00	31	23	99	73	75	77	90	70	82	68	72	72	77	86	87	39	33	69	30	2,000,000$/1yrs
Brock Nelson	0	C/LW	100.00	61	29	85	72	77	85	84	68	70	60	72	72	78	80	76	57	23	68	28	3,804,000$/2yrs
Robby Fabbri	0	C/RW	100.00	20	1	79	75	71	73	70	82	78	80	74	66	64	63	63	82	33	68	23	1,584,000$/1yrs
Kasperi Kapanen	0	LW/RW	100.00	49	6	80	77	68	73	75	81	47	76	76	56	67	62	62	83	30	67	23	1,950,000$/2yrs
Danton Heinen (R)	0	C/LW/RW	100.00	61	29	74	73	71	82	70	73	76	72	71	63	64	59	59	81	33	66	24	1,250,000$/2yrs
Freddie Hamilton	0	C/LW	100.00	64	30	87	75	77	86	80	74	77	63	66	60	63	62	62	68	28	66	27	1,183,000$/1yrs
Tim Bozon	0	LW	100.00	17	1	96	69	76	71	70	78	46	67	81	56	74	67	67	73	26	65	25	685,000$/3yrs
Jeff Petry	1	D	98.00	98	58	80	71	76	88	91	58	26	61	58	80	52	92	87	21	33	74	31	4,532,000$/3yrs
Tyson Barrie	0	D	98.00	51	35	82	79	74	99	74	84	30	77	83	77	72	77	80	60	33	74	28	7,453,000$/3yrs
Matt Niskanen	0	D	100.00	74	50	66	71	76	85	87	68	30	69	63	75	59	97	93	10	33	72	32	4,151,000$/1yrs
Brandon Gormley	0	D	99.00	55	26	95	71	74	80	70	60	5	67	68	82	63	74	73	56	23	68	27	945,000$/1yrs
Dylan Demelo	0	D	100.00	73	22	70	69	76	86	80	62	5	64	66	77	60	63	63	72	21	68	26	1,750,000$/2yrs
Dillon Simpson	0	D	100.00	61	25	83	78	72	81	75	65	15	66	61	74	59	57	57	73	12	67	26	685,000$/2yrs
Scratches
Jason Akeson	0	RW	100.00	33	27	86	68	73	70	70	60	20	58	58	64	62	81	83	50	19	60	29	685,000$/1yrs
Anton Stralman	0	D	100.00	50	27	99	71	72	93	88	96	30	99	84	78	63	95	92	12	21	78	33	6,500,000$/2yrs
Adam Clendening	0	D	100.00	55	20	66	66	74	79	72	68	5	75	71	74	64	63	63	72	20	66	26	1,565,000$/2yrs

	TEAM AVERAGE		99.76	55	29	83	73	74	82	80	75	43	73	74	68	67	75	74	55	28	70

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
Tuukka Rask	0	100.00	83	91	86	76	82	97	99	99	99	96	79	89	99	24	32	88	32	6,725,000$/1yrs
Jordan Binnington	0	96.00	87	80	85	80	88	87	89	86	87	82	86	63	63	72	31	80	26	1,500,000$/1yrs
Scratches

	TEAM AVERAGE	98.00	85	86	86	78	85	92	94	93	93	89	83	76	81	48	32	84

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Paul Maurice	97	80	85	90	99	99	39	CAN	56	3	2,000,000$

General Manager
Jason Wirstiuk

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	AMG	PPG	PPA	PPP	PPM	PKG	PKA	PKP	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG
1	Brendan Gallagher	Stars	0	RW	70	23	34	57	-3	32	0	103	241	78	144	9.54%	40	19.33	7	8	15	157	0	0	0	136	2	1	39.91%	233	47	18	0	0	0.84	0	1
2	Viktor Arvidsson	Stars	0	LW/RW	70	23	34	57	-1	10	0	49	221	75	118	10.41%	25	19.98	6	12	18	159	1	0	1	146	2	3	38.16%	76	41	22	0	0	0.81	0	0
3	Jussi Jokinen	Stars	0	C/LW/RW	70	13	32	45	-3	38	0	107	116	50	77	11.21%	25	20.32	3	13	16	198	0	1	1	128	2	0	54.92%	1209	11	16	0	0	0.63	3	7
4	Reilly Smith	Stars	0	LW/RW	70	18	22	40	-21	2	0	38	206	74	157	8.74%	29	20.32	3	11	14	161	0	0	0	146	3	1	22.54%	71	53	17	0	1	0.56	2	7
5	Nazem Kadri	Stars	0	C	70	12	23	35	-21	38	0	128	198	62	104	6.06%	18	18.06	6	6	12	160	0	0	0	0	4	1	46.99%	1198	46	20	0	0	0.55	0	7
6	Anton Stralman	Stars	0	D	52	6	21	27	3	0	0	17	86	23	39	6.98%	79	22.03	4	3	7	130	0	0	0	67	1	0	0.00%	0	36	34	0	0	0.47	0	0
7	Brandon Sutter	Stars	0	C/RW	70	13	14	27	-1	4	0	20	148	38	86	8.78%	15	15.45	2	0	2	108	0	0	0	31	2	0	52.60%	979	27	12	0	0	0.50	0	0
8	Danton Heinen	Stars	0	C/LW/RW	70	11	11	22	-2	34	0	73	142	63	84	7.75%	16	12.28	0	1	1	1	0	0	0	0	2	1	42.11%	57	28	7	0	0	0.51	0	0
9	Tyson Barrie	Stars	0	D	70	5	15	20	-11	22	0	40	113	42	51	4.42%	93	22.16	1	0	1	128	0	0	0	149	0	1	0.00%	0	48	53	0	0	0.26	0	0
10	Robby Fabbri	Stars	0	C/RW	70	3	13	16	-7	12	0	8	86	38	64	3.49%	11	8.90	0	1	1	11	0	0	0	0	1	0	51.52%	33	16	9	0	0	0.51	0	0
11	Brock Nelson	Stars	0	C/LW	70	9	5	14	-8	12	0	118	107	26	63	8.41%	32	19.01	1	0	1	12	0	0	0	16	0	1	46.88%	64	14	27	0	0	0.21	0	0
12	Jeff Petry	Stars	1	D	68	2	9	11	1	28	0	140	66	27	28	3.03%	104	23.40	2	2	4	153	0	0	0	133	1	1	0.00%	0	7	55	0	0	0.14	0	0
13	Matt Niskanen	Stars	0	D	70	0	10	10	-12	60	0	111	54	20	13	0.00%	73	20.35	0	4	4	158	0	0	0	136	0	0	0.00%	0	8	28	0	0	0.14	0	0
14	Dylan Demelo	Stars	0	D	67	2	5	7	-17	56	0	75	36	20	18	5.56%	58	16.61	1	0	1	28	0	0	0	22	0	0	0.00%	0	6	41	0	0	0.13	0	0
15	Brandon Gormley	Stars	0	D	68	0	6	6	-15	8	0	19	37	22	19	0.00%	63	17.77	0	1	1	33	0	0	0	85	0	0	0.00%	0	12	43	0	0	0.10	0	0
16	Freddie Hamilton	Stars	0	C/LW	62	3	1	4	-3	0	0	9	13	1	6	23.08%	4	3.06	0	0	0	0	0	0	0	0	1	0	45.54%	112	1	5	0	0	0.42	0	0
17	Tim Bozon	Stars	0	LW	48	1	1	2	-13	0	0	9	14	9	6	7.14%	9	11.47	0	0	0	0	0	0	0	1	0	0	48.39%	31	1	6	0	0	0.07	0	0
18	Adam Clendening	Stars	0	D	2	0	2	2	-2	2	0	3	1	1	1	0.00%	1	15.36	0	0	0	0	0	0	0	0	0	0	0.00%	0	1	3	0	0	1.30	0	0
19	Kasperi Kapanen	Stars	0	LW/RW	34	2	0	2	-2	16	0	21	16	6	8	12.50%	10	15.54	0	0	0	1	0	0	0	0	1	0	45.00%	20	5	9	0	0	0.08	0	0
20	Dillon Simpson	Stars	0	D	23	0	1	1	-7	4	0	14	11	5	6	0.00%	22	17.05	0	0	0	15	0	0	0	12	0	0	0.00%	0	10	4	0	0	0.05	0	0
21	Jason Akeson	Stars	0	RW	4	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	0.00%	0	0	0	0	0	0.00	0	0
Team Total or Average				1198	146	259	405	-145	378	0	1102	1912	680	1092	7.64%	727	17.10	36	62	98	1622	1	1	2	1215	22	10	49.62%	4083	418	429	0	1	0.40	5	22

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	Tuukka Rask	Stars	35	11	16	6	0.921	2.48	2060	2	0	85	1070	443	0	1	0.778	9	33	31	1	1	5
2	Jordan Binnington	Stars	29	10	14	5	0.913	2.71	1702	0	0	77	884	393	2	1	0.750	12	29	20	2	3	2
Team Total or Average		64	21	30	11	0.917	2.58	3762	2	0	162	1954	836	2	2	0.762	21	62	51	3	4	7

Cap Hit


	Projected Total Cap Hit	69,279,000$
	Projected Cap Space	10,221,000$
	Retains And Buyout Cap Hit	0$
	Salary Cap To Date	56,986,043$
	Players In Salary Cap	23
	LTIR Players	0

Player Name	Pos	Age	Cap Hit	2019-2020	2020-2021	2021-2022	2022-2023
Adam Clendening	D	26	1,565,000$	1,565,000$	1,565,000$
Anton Stralman	D	33	6,500,000$	6,500,000$	6,500,000$
Brandon Gormley	D	27	945,000$	945,000$
Brandon Sutter	C/RW	30	2,000,000$	2,000,000$
Brendan Gallagher	RW	27	4,018,000$	4,018,000$	4,018,000$	4,018,000$	4,018,000$
Brock Nelson	C/LW	28	3,804,000$	3,804,000$	3,804,000$
Danton Heinen	C/LW/RW	24	1,250,000$	1,250,000$	1,250,000$
Dillon Simpson	D	26	685,000$	685,000$	685,000$
Dylan Demelo	D	26	1,750,000$	1,750,000$	1,750,000$
Freddie Hamilton	C/LW	27	1,183,000$	1,183,000$
Jason Akeson	RW	29	685,000$	685,000$
Jeff Petry	D	31	4,532,000$	4,532,000$	4,532,000$	4,532,000$
Jordan Binnington	C/LW/RW	26	1,500,000$	1,500,000$
Jussi Jokinen	C/LW/RW	36	4,500,000$	4,500,000$
Kasperi Kapanen	LW/RW	23	1,950,000$	1,950,000$	1,950,000$
Matt Niskanen	D	32	4,151,000$	4,151,000$
Nazem Kadri	C	29	3,150,000$	3,150,000$	3,150,000$	3,150,000$	3,150,000$
Reilly Smith	LW/RW	28	4,362,000$	4,362,000$	4,362,000$	4,362,000$
Robby Fabbri	C/RW	23	1,584,000$	1,584,000$
Tim Bozon	LW	25	685,000$	685,000$	685,000$	685,000$
Tuukka Rask	C/LW	32	6,725,000$	6,725,000$
Tyson Barrie	D	28	7,453,000$	7,453,000$	7,453,000$	7,453,000$
Viktor Arvidsson	LW/RW	26	4,302,000$	4,302,000$	4,302,000$

Lines

Forward Lines
#0 - Reilly Smith	#0 - Nazem Kadri	#0 - Kasperi Kapanen
#0 - Viktor Arvidsson	#0 - Jussi Jokinen	#0 - Brendan Gallagher
#0 - Brock Nelson	#0 - Brandon Sutter	#0 - Danton Heinen
#0 - Brock Nelson	#0 - Freddie Hamilton	#0 - Robby Fabbri

Defensive Pairings
#0 - Dillon Simpson	#1 - Jeff Petry
#0 - Tyson Barrie	#0 - Matt Niskanen
#0 - Brandon Gormley	#0 - Dylan Demelo

1st Power Play Unit
#0 - Reilly Smith		#0 - Nazem Kadri		#0 - Jussi Jokinen
#1 - Jeff Petry			#0 - Brandon Gormley

2nd Power Play Unit
#0 - Viktor Arvidsson		#0 - Jussi Jokinen		#0 - Brendan Gallagher
#0 - Tyson Barrie			#0 - Matt Niskanen

Goalies
#0 - Jordan Binnington		#17 - Tuukka Rask

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	Sharks	3	1	2	0	0	0	0	7	10	-3	2	0.333	7	12	19	1	0	2	4	1	0	84	17	39	28	0	103	42	14	57	5	1	20.00%	7	1	85.71%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	56	30	68	26	54	27	40.0%	8.3%	90.3%	98.6	Unlucky
2	Penguins	2	0	1	0	1	0	0	4	6	-2	1	0.250	4	7	11	0	0	1	1	2	0	55	18	16	21	0	78	28	16	29	1	1	100.00%	8	2	75.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	37	21	47	18	35	16	42.9%	7.3%	92.3%	99.6	DULL
3	Lightning	2	0	2	0	0	0	0	3	7	-4	0	0.000	3	4	7	0	0	1	1	1	0	54	20	14	20	0	60	16	10	32	6	0	0.00%	5	2	60.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	40	23	44	17	34	17	37.5%	5.6%	88.3%	93.9	Unlucky
4	Wild	6	1	2	1	0	2	0	16	15	1	8	0.667	16	25	41	0	0	5	4	4	5	163	48	50	56	15	165	64	40	95	24	5	20.83%	20	4	80.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	121	66	135	57	113	55	50.0%	9.8%	90.9%	100.7	FUN
5	Bruins	2	1	1	0	0	0	0	5	5	0	2	0.500	5	9	14	1	0	3	0	2	0	48	18	16	14	0	57	24	12	34	7	2	28.57%	6	1	83.33%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	37	19	45	18	36	18	42.9%	10.4%	91.2%	101.6	LUCKY
6	Flames	2	0	2	0	0	0	0	3	5	-2	0	0.000	3	5	8	0	0	0	2	1	0	50	13	27	10	0	80	16	6	27	3	0	0.00%	3	0	100.00%	1	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	36	20	50	17	32	15	37.5%	6.0%	93.8%	99.8	DULL
7	Coyotes	1	0	0	0	1	0	0	1	2	-1	1	0.500	1	1	2	0	0	0	0	1	0	29	7	13	8	1	29	10	6	15	4	0	0.00%	3	0	100.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	21	10	23	9	20	10	33.3%	3.4%	93.1%	96.6	DULL
8	Hurricanes	1	0	1	0	0	0	0	2	3	-1	0	0.000	2	3	5	0	0	0	2	0	0	33	10	12	11	0	34	12	10	16	1	0	0.00%	5	2	60.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	20	11	21	9	18	8	66.7%	6.1%	91.2%	97.2	DULL
9	Avalanche	3	0	2	0	0	0	1	5	11	-6	1	0.167	5	9	14	0	0	1	3	1	0	95	26	39	30	3	108	24	18	55	3	0	0.00%	9	1	88.89%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	62	36	71	26	51	24	33.3%	5.3%	89.8%	95.1	Unlucky
10	Canadiens	2	1	1	0	0	0	0	7	7	0	2	0.500	7	13	20	0	0	0	5	2	0	53	16	25	12	0	63	21	16	26	3	1	33.33%	8	4	50.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	37	19	43	18	38	19	66.7%	13.2%	88.9%	102.1	FUN
11	Blue Jackets	3	0	2	0	1	0	0	4	7	-3	1	0.167	4	5	9	0	0	1	2	1	0	77	19	22	35	1	104	32	28	47	5	1	20.00%	14	1	92.86%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	56	28	69	27	54	26	33.3%	5.2%	93.3%	98.5	DULL
12	Predators	7	2	3	0	1	0	1	13	18	-5	6	0.429	13	24	37	0	0	3	7	3	0	174	57	59	57	4	212	65	38	107	21	3	14.29%	19	3	84.21%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	143	76	156	64	127	65	40.0%	7.5%	91.5%	99.0	DULL
13	Flyers	1	0	1	0	0	0	0	2	4	-2	0	0.000	2	4	6	0	0	0	2	0	0	27	6	12	9	0	35	12	4	13	2	0	0.00%	2	0	100.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	18	10	23	8	17	8	33.3%	7.4%	88.6%	96.0	Unlucky
14	Golden Knights	2	2	0	0	0	0	0	7	3	4	4	1.000	7	9	16	0	0	0	2	5	0	57	14	17	26	0	70	14	4	36	6	4	66.67%	2	0	100.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	39	22	45	17	35	18	50.0%	12.3%	95.7%	108.0	LUCKY
15	Red Wings	1	0	1	0	0	0	0	2	4	-2	0	0.000	2	4	6	0	0	1	0	1	0	30	9	12	9	0	35	18	2	13	1	0	0.00%	1	0	100.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	19	11	23	8	17	8	33.3%	6.7%	88.6%	95.2	Unlucky
16	Kings	3	1	1	0	1	0	0	8	7	1	3	0.500	8	16	24	0	0	2	3	3	0	92	24	34	33	1	90	30	8	51	11	3	27.27%	4	1	75.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	63	35	62	27	56	29	45.5%	8.7%	92.2%	100.9	DULL
17	Sabres	1	1	0	0	0	0	0	6	5	1	2	1.000	6	8	14	0	0	1	3	2	0	40	18	15	7	0	35	8	6	15	2	0	0.00%	3	2	33.33%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	20	13	22	8	16	8	66.7%	15.0%	85.7%	100.7	FUN
18	Islanders	1	1	0	0	0	0	0	4	1	3	2	1.000	4	8	12	0	0	2	1	1	0	33	22	3	8	0	27	10	2	10	6	2	33.33%	1	0	100.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	20	10	18	9	20	11	66.7%	12.1%	96.3%	108.4	LUCKY
19	Oilers	2	0	2	0	0	0	0	2	5	-3	0	0.000	2	3	5	0	0	1	0	1	0	48	19	12	17	0	64	21	2	39	4	1	25.00%	1	0	100.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	39	22	46	16	33	17	16.7%	4.2%	92.2%	96.4	DULL
20	Devils	1	0	0	0	1	0	0	2	3	-1	1	0.500	2	3	5	0	0	0	1	1	0	32	6	12	12	2	25	8	4	14	5	1	20.00%	2	0	100.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	22	11	19	9	19	10	25.0%	6.3%	88.0%	94.3	Unlucky
21	Canucks	2	0	1	0	0	0	1	4	6	-2	1	0.250	4	7	11	0	0	0	3	1	0	58	15	26	16	5	66	20	2	36	3	0	0.00%	1	0	100.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	45	26	43	16	36	20	40.0%	6.9%	90.9%	97.8	Unlucky
22	Jets	6	4	1	1	0	0	0	15	10	5	10	0.833	15	26	41	0	1	3	6	5	1	163	49	61	50	3	193	60	30	94	21	4	19.05%	15	2	86.67%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	121	65	129	52	109	56	57.9%	9.2%	94.8%	104.0	LUCKY
23	Maple Leafs	1	0	1	0	0	0	0	1	8	-7	0	0.000	1	2	3	0	0	0	1	0	0	20	4	7	9	0	40	16	10	16	4	0	0.00%	5	2	60.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	17	9	25	9	17	7	14.3%	5.0%	80.0%	85.0	Unlucky
24	Blackhawks	5	0	2	1	1	0	1	7	12	-5	4	0.400	7	12	19	0	0	1	3	2	1	163	64	58	39	5	159	56	34	79	13	1	7.69%	17	4	76.47%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	106	62	115	45	86	42	42.9%	4.3%	92.5%	96.7	DULL
25	Ducks	5	2	2	0	1	0	0	10	11	-1	5	0.500	10	19	29	0	0	5	1	4	0	119	52	28	37	2	152	60	22	79	21	3	14.29%	11	3	72.73%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	100	51	109	46	90	47	46.7%	8.4%	92.8%	101.2	DULL
26	Capitals	2	1	1	0	0	0	0	6	6	0	2	0.500	6	11	17	0	0	2	2	2	0	60	26	21	13	0	50	11	12	33	8	3	37.50%	6	2	66.67%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	42	23	42	18	35	17	42.9%	10.0%	88.0%	98.0	FUN
27	Rangers	1	0	1	0	0	0	0	1	2	-1	0	0.000	1	2	3	0	0	1	0	0	0	34	14	14	6	0	33	9	8	20	2	0	0.00%	4	0	100.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	21	11	20	9	18	9	33.3%	2.9%	93.9%	96.9	DULL
28	Senators	2	1	0	0	0	1	0	6	3	3	4	1.000	6	9	15	0	0	1	3	1	1	58	21	18	19	3	56	24	16	31	6	0	0.00%	8	0	100.00%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	43	25	45	19	36	18	66.7%	10.3%	94.6%	105.0	LUCKY
	_Vs Division	30	8	11	3	3	2	3	64	73	-9	32	0.533	64	112	176	0	1	15	26	18	7	850	268	301	265	31	927	299	168	481	93	16	17.20%	84	15	82.14%	0	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	619	342	670	274	545	274	45.3%	7.5%	92.1%	99.7	DULL
	_Vs Conference	47	13	20	3	5	2	4	98	115	-17	45	0.479	98	168	266	1	1	23	38	32	7	1295	405	463	407	39	1491	482	224	770	139	25	17.99%	112	19	83.04%	1	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	959	527	1056	424	849	432	43.2%	7.6%	92.3%	99.9	DULL
	_Since Last GM Reset	70	19	33	3	8	3	4	153	186	-33	62	0.443	153	260	413	2	1	37	62	48	8	1949	632	682	612	45	2223	731	380	1119	198	36	18.18%	190	37	80.53%	1	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	1417	778	1569	635	1266	640	44.0%	7.9%	91.6%	99.5	DULL
	Total	70	19	33	3	8	3	4	153	186	-33	62	0.443	153	260	413	2	1	37	62	48	8	1949	632	682	612	45	2223	731	380	1119	198	36	18.18%	190	37	80.53%	1	831	1597	52.04%	825	1689	48.85%	453	933	48.55%	1417	778	1569	635	1266	640	44.0%	7.9%	91.6%	99.5	DULL

	Puck Time
Offensive Zone	20
Neutral Zone	18
Defensive Zone	22

	Puck Time
Offensive Zone Start	1597
Neutral Zone Start	933
Defensive Zone Start	1689

	Puck Time
With Puck	29
Without Puck	31

	Faceoffs
Faceoffs Won	2109
Faceoffs Lost	2110

	Team Average Shots after	League Average Shots after
1st Period	9.0	9.57
2nd Period	18.8	20.31
3rd Period	27.5	30.68
Overtime	28.2	31.4

Goals in	Team Average Goals after	League Average Goals after
1st Period	0.5	0.64
2nd Period	1.4	1.65
3rd Period	2.1	2.67
Overtime	2.2	2.83


Even Strenght Goal	114
PP Goal	36
PK Goal	1
Empty Net Goal	2

	Home	Away
Win	15	10
Lost	13	20
Overtime Lost	8	4


PP Attempt	198
PP Goal	36
PK Attempt	190
PK Goal Against	37

	Home
Shots For	27.8
Shots Against	31.8
Goals For	2.2
Goals Against	2.7
Hits	16.0
Shots Blocked	10.4
Pim	5.4

Schedule

Date	Matchup			Result	Detail
2019-06-11	Predators	@	Stars	Predators3,Stars4	RECAP
2019-06-13	Stars	@	Jets	Stars4,Jets1	RECAP
2019-06-14	Stars	@	Predators	Stars0,Predators2	RECAP
2019-06-16	Predators	@	Stars	Predators3,Stars2 (OT)	RECAP
2019-06-18	Wild	@	Stars	Wild1,Stars2	RECAP
2019-06-19	Stars	@	Jets	Stars1,Jets0	RECAP
2019-06-21	Jets	@	Stars	Jets4,Stars1	RECAP
2019-06-23	Stars	@	Avalanche	Stars1,Avalanche4	RECAP
2019-06-25	Kings	@	Stars	Kings3,Stars2 (OT)	RECAP
2019-06-27	Stars	@	Ducks	Stars1,Ducks4	RECAP
2019-06-29	Blackhawks	@	Stars	Blackhawks3,Stars2 (SO)	RECAP
2019-06-30	Stars	@	Ducks	Stars1,Ducks3	RECAP
2019-07-02	Stars	@	Bruins	Stars3,Bruins1	RECAP
2019-07-03	Predators	@	Stars	Predators2,Stars3	RECAP
2019-07-05	Stars	@	Penguins	Stars2,Penguins3	RECAP
2019-07-07	Stars	@	Predators	Stars1,Predators2	RECAP
2019-07-08	Ducks	@	Stars	Ducks1,Stars0 (OT)	RECAP
2019-07-11	Stars	@	Bruins	Stars2,Bruins4	RECAP
2019-07-12	Capitals	@	Stars	Capitals3,Stars5	RECAP
2019-07-14	Blue Jackets	@	Stars	Blue Jackets3,Stars2	RECAP
2019-07-16	Stars	@	Blue Jackets	Stars1,Blue Jackets2 (OT)	RECAP
2019-07-18	Senators	@	Stars	Senators2,Stars3 (SO)	RECAP
2019-07-20	Wild	@	Stars	Wild3,Stars1	RECAP
2019-07-21	Stars	@	Lightning	Stars1,Lightning4	RECAP
2019-07-23	Stars	@	Blackhawks	Stars1,Blackhawks2	RECAP
2019-07-25	Senators	@	Stars	Senators1,Stars3	RECAP
2019-07-28	Blackhawks	@	Stars	Blackhawks4,Stars1	RECAP
2019-07-30	Stars	@	Jets	Stars4,Jets2	RECAP
2019-08-01	Stars	@	Wild	Stars3,Wild2 (SO)	RECAP
2019-08-02	Stars	@	Coyotes	Stars1,Coyotes2 (OT)	RECAP
2019-08-04	Kings	@	Stars	Kings2,Stars1	RECAP
2019-08-06	Jets	@	Stars	Jets1,Stars2	RECAP
2019-08-08	Stars	@	Blue Jackets	Stars1,Blue Jackets2	RECAP
2019-08-09	Flyers	@	Stars	Flyers4,Stars2	RECAP
2019-08-12	Ducks	@	Stars	Ducks1,Stars5	RECAP
2019-08-14	Stars	@	Sharks	Stars4,Sharks3	RECAP
2019-08-16	Avalanche	@	Stars	Avalanche3,Stars1	RECAP
2019-08-18	Stars	@	Canucks	Stars2,Canucks3	RECAP
2019-08-20	Canadiens	@	Stars	Canadiens5,Stars2	RECAP
2019-08-22	Islanders	@	Stars	Islanders1,Stars4	RECAP
2019-08-23	Stars	@	Predators	Stars1,Predators2 (SO)	RECAP
2019-08-25	Stars	@	Capitals	Stars1,Capitals3	RECAP
2019-08-26	Stars	@	Lightning	Stars2,Lightning3	RECAP
2019-08-28	Stars	@	Kings	Stars5,Kings2	RECAP
2019-08-30	Canadiens	@	Stars	Canadiens2,Stars5	RECAP
2019-08-31	Golden Knights	@	Stars	Golden Knights2,Stars4	RECAP
2019-09-03	Stars	@	Maple Leafs	Stars1,Maple Leafs8	RECAP
2019-09-04	Stars	@	Wild	Stars4,Wild3 (SO)	RECAP
2019-09-06	Rangers	@	Stars	Rangers2,Stars1	RECAP
2019-09-08	Devils	@	Stars	Devils3,Stars2 (OT)	RECAP
2019-09-10	Wild	@	Stars	Wild3,Stars4 (OT)	RECAP
2019-09-12	Stars	@	Ducks	Stars3,Ducks2	RECAP
2019-09-13	Stars	@	Blackhawks	Stars2,Blackhawks1 (OT)	RECAP
2019-09-15	Stars	@	Red Wings	Stars2,Red Wings4	RECAP
2019-09-17	Canucks	@	Stars	Canucks3,Stars2 (SO)	RECAP
2019-09-19	Sharks	@	Stars	Sharks3,Stars1	RECAP
2019-09-22	Stars	@	Wild	Stars2,Wild3	RECAP
2019-09-23	Golden Knights	@	Stars	Golden Knights1,Stars3	RECAP
2019-09-25	Jets	@	Stars	Jets2,Stars3 (OT)	RECAP
2019-09-27	Stars	@	Flames	Stars2,Flames3	RECAP
2019-09-29	Stars	@	Penguins	Stars2,Penguins3 (OT)	RECAP
2019-09-30	Flames	@	Stars	Flames2,Stars1	RECAP
2019-10-02	Oilers	@	Stars	Oilers2,Stars1	RECAP
2019-10-05	Stars	@	Hurricanes	Stars2,Hurricanes3	RECAP
2019-10-06	Stars	@	Oilers	Stars1,Oilers3	RECAP
2019-10-08	Blackhawks	@	Stars	Blackhawks2,Stars1 (OT)	RECAP
2019-10-10	Predators	@	Stars	Predators4,Stars2	RECAP
Trade Deadline --- Trades can�t be done after this day is simulated!
2019-10-13	Avalanche	@	Stars	Avalanche4,Stars3 (SO)	RECAP
2019-10-17	Stars	@	Sharks	Stars2,Sharks4	RECAP
2019-10-18	Sabres	@	Stars	Sabres5,Stars6	RECAP
2019-10-21	Stars	@	Jets
2019-10-22	Avalanche	@	Stars
2019-10-25	Kings	@	Stars
2019-10-27	Stars	@	Kings
2019-10-29	Ducks	@	Stars
2019-10-30	Stars	@	Avalanche
2019-11-01	Stars	@	Kings
2019-11-03	Coyotes	@	Stars
2019-11-05	Stars	@	Blackhawks
2019-11-07	Lightning	@	Stars
2019-11-09	Stars	@	Golden Knights
2019-11-10	Stars	@	Avalanche

Finance

Salary Cap
Players Total Salaries	Retained Salary	Total Cap Hit	Estimated Cap Space
69,279,000$	0$	69,279,000$	10,221,000$

Arena	Goal Horn	About us
		Name	American Airlines Center
		City	Dallas
		Capacity	18000
		Season Ticket Holders	40%

Arena Capacity - Ticket Price Attendance - %

Arena Capacity	6000	5000	2000	4000	1000
Ticket Price	100$	55$	30$	20$	200$
Attendance	210303	175363	71073	143182	34671
Attendance PCT	97.36%	97.42%	98.71%	99.43%	96.31%

Income

Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
5	17628 - 97.93%	1,763,386$	63,481,890$	18000	100

Expenses
Players Total Salaries	Players Total Average Salaries	Coaches Salaries	Special Salary Cap Value
69,279,000$	69,279,000$	0$	0$

Year To Date Expenses	Salary Cap Per Days	Salary Cap To Date	Luxury Taxe Total
58,948,426$	69,279,000$	56,986,043$	0$

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
8,816,929$	25	456,917$	11,422,925$

Team Total Estimate
Estimated Season Expenses	Estimated Season Salary Cap	Current Bank Account	Projected Bank Account
11,882,747$	69,279,000$	38,692,383$	36,383,260$

Depth Chart

Rookie

Injured

Cold Streak

Hot Streak

Left Wing

Center

Right Wing

Kasperi Kapanen	AGE:23	FIN
Danton Heinen	AGE:24	CAN
Viktor Arvidsson	AGE:26	SWE
Tim Bozon	AGE:25	SUI
Freddie Hamilton	AGE:27	CAN
Reilly Smith	AGE:28	CAN
Brock Nelson	AGE:28	USA
Jussi Jokinen	AGE:36	FIN
Janne Kuokkanen	AGE:18	FIN
Kailer Yamamoto	AGE:18	USA
C.J. Smith	AGE:24	USA
Anton Slepyshev	AGE:25	RUS
Joseph Cramarossa	AGE:26	CAN
Cal Clutterbuck	AGE:31	CAN
Jannik Hansen	AGE:33	DNK
Matt Puempel	AGE:26	CAN

Robby Fabbri	AGE:23	CAN
Danton Heinen	AGE:24	CAN
Freddie Hamilton	AGE:27	CAN
Brock Nelson	AGE:28	USA
Nazem Kadri	AGE:29	CAN
Brandon Sutter	AGE:30	USA
Jussi Jokinen	AGE:36	FIN
Janne Kuokkanen	AGE:18	FIN
Kailer Yamamoto	AGE:18	USA
Nicholas Merkley	AGE:18	CAN
Adam Tambellini	AGE:24	CAN
Joseph Cramarossa	AGE:26	CAN
Trevor Lewis	AGE:32	USA

Kasperi Kapanen	AGE:23	FIN
Robby Fabbri	AGE:23	CAN
Danton Heinen	AGE:24	CAN
Viktor Arvidsson	AGE:26	SWE
Brendan Gallagher	AGE:27	CAN
Reilly Smith	AGE:28	CAN
Brandon Sutter	AGE:30	USA
Jussi Jokinen	AGE:36	FIN
Jason Akeson	AGE:29	CAN
Kailer Yamamoto	AGE:18	USA
Denis Gurianov	AGE:18	RUS
Nicholas Merkley	AGE:18	CAN
Joey Anderson	AGE:19	USA
Anton Slepyshev	AGE:25	RUS
Cal Clutterbuck	AGE:31	CAN
Trevor Lewis	AGE:32	USA
Jannik Hansen	AGE:33	DNK
Matt Puempel	AGE:26	CAN

Defense #1

Defense #2

Goalie

Dillon Simpson	AGE:26	CAN
Dylan Demelo	AGE:26	CAN
Tyson Barrie	AGE:28	CAN
Brandon Gormley	AGE:27	CAN
Jeff Petry	AGE:31	USA
Matt Niskanen	AGE:32	USA
Adam Clendening	AGE:26	USA

Anton Stralman	AGE:33	SWE
Julius Bergman	AGE:23	SWE
Gavin Bayreuther	AGE:25	USA
Jonathan Racine	AGE:26	CAN
Joakim Ryan	AGE:26	USA
Ilya Lyubushkin	AGE:25	RUS
Keith Aulie	AGE:30	CAN

Tuukka Rask	AGE:32	FIN
Jordan Binnington	AGE:26	CAN
Sean Maguire	AGE:27	CAN
Ville Husso	AGE:22	FIN
Ken Appleby	AGE:24	CAN

Draft Picks

Year	Round 1	Round 2	Round 3
10
11
12
13
14

** Conditional Draft Pick That Have Been Traded

Prospects

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

Prospect	Team Name	Draft Year	Overall Pick	Information
Alfons Malmstrom	Stars	7	68	5.0B Defence
Cole Hults	Stars	8	84	7.0C Defence
Connor Bunnaman	Stars	7	69	6.0C Center
Cooper Marody	Stars	7	59	6.0B Center
Filip Ahl	Stars			recreate once signed
Ryan Sproul	Stars	6	58	7.0C Defence

Transactions

Jason Akeson signed with Stars for $685,000 for 1 year(s).

Ken Appleby signed with Stars for $685,000 for 1 year(s).

Sean Maguire signed with Stars for $685,000 for 2 year(s).

Injuries

No Injury or Suspension.

Game Center

Stars25-33-12, 62pts

24Final

Sharks42-20-11, 95pts

Sabres27-39-5, 59pts

56Final

Stars25-33-12, 62pts

Mon, Oct 21Bell MTS Place

Jets40-27-4, 84pts

Avalanche41-20-9, 91pts

Tue, Oct 22American Airlines Center

Stars25-33-12, 62pts

Kings28-32-11, 67pts

Fri, Oct 25American Airlines Center

Stars25-33-12, 62pts

Team Leaders

	GOALS Brendan Gallagher 23			ASSISTS Brendan Gallagher 34
	POINTS Brendan Gallagher 57			PLUS/MINUS Anton Stralman 3
	WINS Tuukka Rask 11			SV% Sean Maguire 0.933

Team Stats

Goals For 153 2.19 GFG	Shots For 1949 27.84 Avg	Power Play Percentage 18.2% 36 GF	Offensive Zone Start 48.6%
Goals Against 186 2.66 GAA	Shots Against 2223 31.76 Avg	Penalty Kill Percentage 80.5% 37 GA	Defensive Zone Start 51.4%

Team Info


	General Manager	Jason Wirstiuk
	Head Coach	Paul Maurice
	Captain	Viktor Arvidsson
	Division	Central

Stars Affiliation


	Team Name	Stars
	City	Texas
	Head Coach	Jarrod Skalde
	Division	Pacific

Arena Info


	Stadium	American Airlines Center
	Capacity	18,000
	Attendance	17,628
	Season Tickets	7,200

Salary Cap


	Total Cap Hit	69,279,000$
	Cap Space	10,221,000$
	Retains & Buyout	0$
	Players In Salary Cap	23

Finance


	Team Revenue	63,481,890$
	Estimated Revenue	73,055,514$
	Estimated Expenses	70,371,351$
	Operating Income	2,684,163$
	Bank Account	38,692,383$

Team Captain - Alternate Captains

Captain	Alternate Captain	Alternate Captain
Viktor Arvidsson	Nazem Kadri