Stanley Cup Winners Hockey League

ARIZONA Coyotes
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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	#	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP
1	Tage Thompson	0	X		X		100.00	67	35	73	64	93	75	86	63	66	62	63	59	63	54	51	80	91	67	0
2	Saku Maenalanen (R)	0			X		100.00	66	35	70	66	88	63	67	65	54	61	61	58	62	51	50	56	97	64	0
3	Alan Quine	95	X	X			100.00	54	35	70	70	75	56	56	69	68	67	68	53	69	54	51	47	97	62	0
4	Ryan Kuffner	0		X			100.00	55	35	77	59	76	76	55	59	50	60	60	60	60	50	50	44	97	61	0
5	Adam Helewka	34		X			100.00	53	89	68	70	77	50	50	70	50	64	64	50	64	50	50	43	97	60	0
6	Filip Chlapik	0	X				100.00	52	35	67	68	77	53	52	68	69	63	63	52	63	51	50	73	96	60	0
7	German Rubtsov (R)	0	X				100.00	50	89	73	67	76	50	50	67	70	62	62	52	62	50	50	44	96	59	0
8	Adam Brooks (R)	0	X				100.00	50	89	66	70	56	50	50	70	70	64	64	50	64	50	50	44	97	58	0
9	Glenn Gawdin (R)	0	X				100.00	51	89	60	70	76	50	50	70	70	57	57	51	57	50	50	44	97	58	0
10	Sheldon Rempal	0			X		100.00	50	35	67	69	63	53	53	69	50	61	61	51	62	50	50	43	97	58	0
11	Graham Knott	75	X				100.00	54	89	67	60	82	48	50	60	70	53	53	50	53	50	50	44	99	56	0
12	Mitch Hults	10	X				100.00	57	89	72	63	82	50	50	63	70	52	52	50	52	50	50	42	97	56	0
13	Nolan Stevens (R)	0	X				100.00	52	89	70	63	80	50	50	63	50	51	46	51	56	50	50	44	99	55	0
14	Slater Koekkoek	15				X	100.00	72	35	78	63	79	74	65	62	30	60	58	71	65	54	51	83	97	65	0
15	Jacob Larsson (R)	0				X	100.00	62	35	76	61	80	70	84	61	30	56	50	65	61	52	51	80	97	63	0
16	Haydn Fleury	0				X	100.00	61	35	70	62	85	59	60	62	31	51	47	58	58	53	51	86	94	59	0
17	Josh Teves (R)	0				X	100.00	98	35	77	50	68	74	50	50	30	53	55	65	58	50	50	43	97	59	0
18	Nicolas Hague (R)	0				X	100.00	66	89	64	67	95	50	50	67	30	52	47	59	57	50	50	44	97	59	0
Rayé
1	Daniel Zaar	46			X		100.00	47	35	77	72	66	47	43	68	30	64	60	50	55	58	51	79	93	58	0
2	Deven Sideroff (R)	0			X		100.00	50	89	72	60	67	50	50	60	50	50	50	50	50	50	50	44	93	54	0
3	Andreas Borgman	0				X	100.00	54	89	63	65	77	50	50	65	30	49	44	50	54	52	51	43	94	55	0
4	Jalen Chatfield (R)	0				X	100.00	50	89	70	57	75	46	50	57	30	45	40	50	50	50	50	44	93	52	0

	MOYENNE D'ÉQUIPE					100.00	58	62	70	64	77	57	56	64	50	57	56	55	59	51	50	54	96	59

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Adin Hill	100.00	79	78	80	93	78	77	79	78	77	78	73	51	65	65	97	69	0
2	Sam Brittain	100.00	45	50	62	77	60	52	50	51	50	52	55	62	51	63	97	50	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	62	64	71	85	69	65	65	65	64	65	64	57	58	64	97	60

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Bruce Boudreau	79	85	84	80	93	93	44	CAN	65	1	1,000,000$

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	GW	GT	FO%	FOT	HT	P/20	PSS	S1	S2	S3
1	Ryan Kuffner	TUSCON Roadrunners (ARZ)	LW	6	8	13	21	19	2	5	4	45	16	31	17.78%	2	115	19.17	1	0	1	5	11	1	8	0	0	66.67%	3	1	3.65	1	2	1	1
2	Slater Koekkoek	TUSCON Roadrunners (ARZ)	D	6	6	14	20	17	4	14	4	34	19	15	17.65%	5	143	23.94	1	2	3	9	15	0	9	0	0	0.00%	0	0	2.78	0	1	1	1
3	Filip Chlapik	TUSCON Roadrunners (ARZ)	C	6	10	6	16	19	2	7	7	50	11	21	20.00%	0	104	17.50	0	1	1	5	11	0	0	3	0	72.92%	96	2	3.05	0	1	1	0
4	Alan Quine	TUSCON Roadrunners (ARZ)	C/LW	6	5	9	14	13	0	3	2	51	4	35	9.80%	3	98	16.47	0	2	2	4	12	0	8	0	1	73.68%	19	0	2.83	1	0	0	1
5	Tage Thompson	TUSCON Roadrunners (ARZ)	C/RW	5	5	8	13	12	4	5	13	38	6	22	13.16%	1	119	24.00	1	1	2	2	12	2	10	0	0	71.21%	132	0	2.17	1	0	1	1
6	Jacob Larsson	TUSCON Roadrunners (ARZ)	D	6	1	8	9	13	2	4	3	13	7	7	7.69%	0	107	17.91	0	0	0	3	9	1	7	1	0	0.00%	0	0	1.68	0	0	0	0
7	Adam Helewka	TUSCON Roadrunners (ARZ)	LW	6	6	3	9	7	4	8	3	35	10	32	17.14%	0	88	14.75	0	0	0	0	0	0	0	0	0	33.33%	6	1	2.03	0	0	0	0
8	Josh Teves	TUSCON Roadrunners (ARZ)	D	6	1	7	8	12	6	11	2	17	8	9	5.88%	5	101	16.87	0	0	0	0	0	0	0	0	0	0.00%	0	0	1.58	0	0	0	0
9	Nicolas Hague	TUSCON Roadrunners (ARZ)	D	6	0	8	8	13	0	9	2	8	2	10	0.00%	1	108	18.04	0	0	0	4	9	0	8	0	0	0.00%	0	0	1.48	0	0	0	0
10	Saku Maenalanen	TUSCON Roadrunners (ARZ)	RW	6	3	5	8	13	0	12	3	34	7	23	8.82%	1	103	17.20	0	0	0	4	12	0	10	0	0	42.86%	7	0	1.55	1	0	0	0
11	German Rubtsov	TUSCON Roadrunners (ARZ)	C	6	2	5	7	7	2	2	1	26	7	16	7.69%	1	86	14.44	0	0	0	0	0	0	0	0	0	67.68%	99	0	1.62	0	0	0	1
12	Sheldon Rempal	TUSCON Roadrunners (ARZ)	RW	6	1	6	7	7	0	2	8	25	10	20	4.00%	0	86	14.45	0	0	0	0	0	0	0	0	0	0.00%	0	0	1.62	0	0	0	0
13	Adam Brooks	TUSCON Roadrunners (ARZ)	C	6	4	1	5	3	0	5	2	28	16	22	14.29%	0	54	9.05	0	0	0	0	0	0	0	0	0	76.09%	46	0	1.84	0	0	0	1
14	Haydn Fleury	TUSCON Roadrunners (ARZ)	D	3	0	3	3	2	2	3	2	5	1	2	0.00%	1	41	13.96	0	0	0	1	3	0	1	0	0	0.00%	0	0	1.43	0	0	0	0
15	Glenn Gawdin	TUSCON Roadrunners (ARZ)	C	6	0	0	0	0	0	0	0	1	0	0	0.00%	0	6	1.08	0	0	0	1	0	0	0	0	0	20.00%	5	0	0.00	0	0	0	0
Stats d'équipe Total ou en Moyenne				86	52	96	148	157	28	90	56	410	124	265	12.68%	20	1367	15.90	3	6	9	38	100	4	66	4	1	69.73%	413	4	2.17	4	4	4	6

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Adin Hill	TUSCON Roadrunners (ARZ)	6	4	1	1	0.908	1.64	365	0	1	10	109	0	0	0	0.750	4	6	0	1	0	0
Stats d'équipe Total ou en Moyenne			6	4	1	1	0.908	1.64	365	0	1	10	109	0	0	0	0.750	4	6	0	1	0	0

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Astuces sur les Filtres (Anglais seulement)

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

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Type	Salaire Actuel	Salaire Restant	Salaire Moyen	Salaire Moyen Restant	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Salaire Année 4	Link
Adam Brooks	TUSCON Roadrunners (ARZ)	C	23	1996-05-06	Yes	80 Kg	155 CM	No	No	No	2	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No	750,000$			Lien
Adam Helewka	TUSCON Roadrunners (ARZ)	LW	24	1995-07-21	No	91 Kg	185 CM	No	No	No	1	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No				Lien
Adin Hill	TUSCON Roadrunners (ARZ)	G	23	1996-05-11	No	92 Kg	198 CM	No	No	No	1	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No				Lien
Alan Quine	TUSCON Roadrunners (ARZ)	C/LW	26	1993-02-25	No	92 Kg	183 CM	No	No	No	1	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No				Lien
Andreas Borgman	TUSCON Roadrunners (ARZ)	D	24	1995-06-18	No	96 Kg	183 CM	No	No	No	4	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No	750,000$	750,000$	750,000$	Lien
Daniel Zaar	TUSCON Roadrunners (ARZ)	RW	25	1994-04-24	No	81 Kg	183 CM	No	No	No	0	Pro & Farm					0$	0$	No
Deven Sideroff	TUSCON Roadrunners (ARZ)	RW	22	1997-04-14	Yes	78 Kg	180 CM	No	No	No	2	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No	750,000$			Lien
Filip Chlapik	TUSCON Roadrunners (ARZ)	C	22	1997-06-03	No	89 Kg	185 CM	No	No	No	1	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No				Lien
German Rubtsov	TUSCON Roadrunners (ARZ)	C	21	1998-06-27	Yes	81 Kg	188 CM	No	No	No	2	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No	750,000$			Lien
Glenn Gawdin	TUSCON Roadrunners (ARZ)	C	22	1997-03-25	Yes	87 Kg	185 CM	No	No	No	2	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No	750,000$			Lien
Graham Knott	TUSCON Roadrunners (ARZ)	C	22	1997-01-13	No	87 Kg	191 CM	No	No	No	2	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No	750,000$			Lien
Haydn Fleury	TUSCON Roadrunners (ARZ)	D	23	1996-07-08	No	95 Kg	191 CM	No	No	No	1	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No				Lien
Jacob Larsson	TUSCON Roadrunners (ARZ)	D	22	1997-04-29	Yes	90 Kg	188 CM	No	No	No	2	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No	750,000$			Lien
Jalen Chatfield	TUSCON Roadrunners (ARZ)	D	23	1996-05-16	Yes	85 Kg	185 CM	No	No	No	2	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No	750,000$			Lien
Josh Teves	TUSCON Roadrunners (ARZ)	D	24	1995-02-18	Yes	77 Kg	183 CM	No	No	No	2	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No	750,000$			Lien
Mitch Hults	TUSCON Roadrunners (ARZ)	C	23	1995-11-13	No	95 Kg	188 CM	No	No	No	1	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No				Lien
Nicolas Hague	TUSCON Roadrunners (ARZ)	D	20	1998-12-05	Yes	98 Kg	198 CM	No	No	No	2	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No	750,000$			Lien
Nolan Stevens	TUSCON Roadrunners (ARZ)	C	23	1996-07-22	Yes	83 Kg	191 CM	No	No	No	2	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No	750,000$			Lien
Ryan Kuffner	TUSCON Roadrunners (ARZ)	LW	23	1996-06-12	No	89 Kg	185 CM	No	No	No	2	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No	750,000$			Lien
Saku Maenalanen	TUSCON Roadrunners (ARZ)	RW	25	1994-05-29	Yes	94 Kg	193 CM	No	No	No	2	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No	750,000$			Lien
Sam Brittain	TUSCON Roadrunners (ARZ)	G	27	1992-05-10	No	100 Kg	191 CM	No	No	No	1	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No
Sheldon Rempal	TUSCON Roadrunners (ARZ)	RW	24	1995-08-07	No	75 Kg	178 CM	No	No	No	2	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No	750,000$			Lien
Slater Koekkoek	TUSCON Roadrunners (ARZ)	D	25	1994-02-18	No	88 Kg	188 CM	No	No	No	1	Pro & Farm	925,000$	858,333$	925,000$	858,333$	0$	0$	No				Lien
Tage Thompson	TUSCON Roadrunners (ARZ)	C/RW	21	1997-10-30	No	93 Kg	198 CM	No	No	No	1	Pro & Farm	750,000$	695,945$	750,000$	695,945$	0$	0$	No				Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
24	23.21	88 Kg	185 CM	1.63	726,042$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Alan Quine	Tage Thompson	Saku Maenalanen	31	1	2	2
2	Ryan Kuffner	Filip Chlapik		26	1	2	2
3	Adam Helewka	German Rubtsov	Sheldon Rempal	23	1	2	2
4		Adam Brooks	Tage Thompson	20	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Slater Koekkoek	31	1	2	2
2	Jacob Larsson	Nicolas Hague	26	1	2	2
3	Josh Teves		23	1	2	2
4		Slater Koekkoek	20	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Alan Quine	Tage Thompson	Saku Maenalanen	55	1	2	2
2	Ryan Kuffner	Filip Chlapik		45	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Slater Koekkoek	55	1	2	2
2	Jacob Larsson	Nicolas Hague	45	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Tage Thompson	Saku Maenalanen	55	1	2	2
2	Alan Quine	Ryan Kuffner	45	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Slater Koekkoek	55	1	2	2
2	Jacob Larsson	Nicolas Hague	45	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Tage Thompson	55	1	2	2		Slater Koekkoek	55	1	2	2
2	Saku Maenalanen	45	1	2	2	Jacob Larsson	Nicolas Hague	45	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Tage Thompson	Saku Maenalanen	55	1	2	2
2	Alan Quine	Ryan Kuffner	45	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Slater Koekkoek	55	1	2	2
2	Jacob Larsson	Nicolas Hague	45	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Alan Quine	Tage Thompson	Saku Maenalanen		Slater Koekkoek

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Alan Quine	Tage Thompson	Saku Maenalanen		Slater Koekkoek

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Glenn Gawdin, Adam Helewka,	Glenn Gawdin, Adam Helewka

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Josh Teves, , Jacob Larsson	Josh Teves	, Jacob Larsson

Tirs de Pénalité
Tage Thompson, Saku Maenalanen, Alan Quine, Ryan Kuffner, Adam Helewka

Gardien
#1 : Adin Hill, #2 : Sam Brittain

Lignes d'Attaque Perso. en Prol.
Tage Thompson, Saku Maenalanen, Alan Quine, Ryan Kuffner, Adam Helewka, Filip Chlapik, Filip Chlapik, , German Rubtsov, Adam Brooks,

Lignes de Défense Perso. en Prol.
, Slater Koekkoek, Jacob Larsson, Nicolas Hague, Josh Teves

Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

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

	Ligue												Domicile											Visiteur
#	VS Équipe	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	CHICAGO Wolves	2	2	0	0	0	0	0	0	23	1	22	2	2	0	0	0	0	0	0	23	1	22	0	0	0	0	0	0	0	0	0	0	0	4	1.000	23	40	63	0	1	26	15	11	0	196	127	147	137	7	7	3	4	27	0	0	0.00%	2	0	100.00%	0	132	184	71.74%	80	132	60.61%	86	114	75.44%	215	181	90	27	58	33
2	IOWA Wild	1	0	1	0	0	0	0	0	2	4	-2	1	0	1	0	0	0	0	0	2	4	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	4	6	0	0	26	15	11	0	35	127	147	137	7	33	3	4	17	3	1	33.33%	1	1	0.00%	0	132	184	71.74%	80	132	60.61%	86	114	75.44%	215	181	90	27	58	33
3	Marlies de Toronto	1	1	0	0	0	0	0	0	13	1	12	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	13	1	12	2	1.000	13	26	39	0	0	26	15	11	0	98	127	147	137	7	8	3	6	26	0	0	0.00%	3	1	66.67%	0	132	184	71.74%	80	132	60.61%	86	114	75.44%	215	181	90	27	58	33
4	ROCKFORD IceHogs	1	1	0	0	0	0	0	0	12	2	10	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	12	2	10	2	1.000	12	23	35	0	0	26	15	11	0	58	127	147	137	7	19	4	2	5	8	2	25.00%	1	1	0.00%	0	132	184	71.74%	80	132	60.61%	86	114	75.44%	215	181	90	27	58	33
	Total	6	4	1	0	0	0	0	1	52	11	41	4	2	1	0	0	0	0	1	27	8	19	2	2	0	0	0	0	0	0	25	3	22	9	0.750	52	96	148	0	1	26	15	11	0	414	127	147	137	7	109	19	28	87	15	3	20.00%	13	3	76.92%	0	132	184	71.74%	80	132	60.61%	86	114	75.44%	215	181	90	27	58	33
6	UTICA Comets	1	0	0	0	0	0	0	1	2	3	-1	1	0	0	0	0	0	0	1	2	3	-1	0	0	0	0	0	0	0	0	0	0	0	1	0.500	2	3	5	0	0	26	15	11	0	27	127	147	137	7	42	6	12	12	4	0	0.00%	6	0	100.00%	0	132	184	71.74%	80	132	60.61%	86	114	75.44%	215	181	90	27	58	33
	_Since Last GM Reset	6	4	1	0	0	0	0	1	52	11	41	4	2	1	0	0	0	0	1	27	8	19	2	2	0	0	0	0	0	0	25	3	22	9	0.750	52	96	148	0	1	26	15	11	0	414	127	147	137	7	109	19	28	87	15	3	20.00%	13	3	76.92%	0	132	184	71.74%	80	132	60.61%	86	114	75.44%	215	181	90	27	58	33
	_Vs Conference	5	4	0	0	0	0	0	1	50	7	43	3	2	0	0	0	0	0	1	25	4	21	2	2	0	0	0	0	0	0	25	3	22	9	0.900	50	92	142	0	1	26	15	11	0	379	127	147	137	7	76	16	24	70	12	2	16.67%	12	2	83.33%	0	132	184	71.74%	80	132	60.61%	86	114	75.44%	215	181	90	27	58	33
	_Vs Division	1	1	0	0	0	0	0	1	2	3	-1	1	0	0	0	0	0	0	1	2	3	-1	0	1	0	0	0	0	0	0	0	0	0	3	1.500	2	3	5	0	0	26	15	11	0	27	127	147	137	7	42	6	12	12	4	0	0.00%	6	0	100.00%	0	132	184	71.74%	80	132	60.61%	86	114	75.44%	215	181	90	27	58	33

			Total Pour les Joueurs
Matchs Joués	Points	Séquence	Buts	Passes	Points	Tirs Pour	Tirs Contre	Tirs Bloqués	Minutes de Pénalité	Mises en Échec	Buts en Filet Désert	Blanchissage
6	9	W2	52	96	148	414	109	19	28	87	0	1

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
6	4	1	0	0	0	1	52	11

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	2	1	0	0	0	1	27	8

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	2	0	0	0	0	0	25	3

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	1	0	0	0	1

Tentatives en Avantage Numérique	Buts en Avantage Numérique	% en Avantage Numérique	Tentatives en Désavantage Numérique	Buts Contre en Désavantage Numérique	% en Désavantage Numérique	Buts Pour en Désavantage Numérique
15	3	20.00%	13	3	76.92%	0

Tirs en 1e Période	Tirs en 2e Période	Tirs en 3e Période	Tirs en 4e Période	Buts en 1e Période	Buts en 2e Période	Buts en 3e Période	Buts en 4e Période
127	147	137	7	26	15	11	0

Mises en Jeu
Gagnées en Zone Offensive	Total en Zone Offensive	% Gagnées en Zone Offensive	Gagnées en Zone Défensive	Total en Zone Défensive	% Gagnées en Zone Défensive	Gagnées en Zone Neutre	Total en Zone Neutre	% Gagnées en Zone Neutre
132	184	71.74%	80	132	60.61%	86	114	75.44%

Temps Avec la Rondelle
En Zone Offensive	Contrôle en Zone Offensive	En Zone Défensive	Contrôle en Zone Défensive	En Zone Neutre	Contrôle en Zone Neutre
215	181	90	27	58	33

Derniers Match Joués Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

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

Jour	Match	Équipe Visiteuse	Score	Équipe Locale	Score	ST	OT	SO	Lien
1 - 2020-01-15	6	CHICAGO Wolves	1	TUSCON Roadrunners	11	W			Sommaire du Match
2 - 2020-01-16	25	IOWA Wild	4	TUSCON Roadrunners	2	L			Sommaire du Match
3 - 2020-01-17	36	TUSCON Roadrunners	12	ROCKFORD IceHogs	2	W			Sommaire du Match
4 - 2020-01-18	49	UTICA Comets	3	TUSCON Roadrunners	2	L	X	X	Sommaire du Match
5 - 2020-01-19	63	TUSCON Roadrunners	13	Marlies de Toronto	1	W			Sommaire du Match
7 - 2020-01-21	76	CHICAGO Wolves	0	TUSCON Roadrunners	12	W			Sommaire du Match
9 - 2020-01-23	84	TUSCON Roadrunners	-	UTICA Comets	-
11 - 2020-01-25	100	TUSCON Roadrunners	-	LEHIGH VALLEY Phantoms	-
13 - 2020-01-27	105	TUSCON Roadrunners	-	SAN DIEGO Gulls	-
15 - 2020-01-29	124	Marlies de Toronto	-	TUSCON Roadrunners	-
17 - 2020-01-31	139	BROOKLYN Wolfpack	-	TUSCON Roadrunners	-
20 - 2020-02-03	154	TUSCON Roadrunners	-	BROOKLYN Wolfpack	-
21 - 2020-02-04	164	TUSCON Roadrunners	-	PROVIDENCE Bruins	-
22 - 2020-02-05	175	ROCKFORD IceHogs	-	TUSCON Roadrunners	-
23 - 2020-02-06	183	TUSCON Roadrunners	-	CHICAGO Wolves	-
24 - 2020-02-07	196	BRIDGEPORT Sound Tigers	-	TUSCON Roadrunners	-
26 - 2020-02-09	214	TUSCON Roadrunners	-	UTICA Comets	-
27 - 2020-02-10	224	Syracruse Crunch	-	TUSCON Roadrunners	-
28 - 2020-02-11	240	TUSCON Roadrunners	-	WILKIES-BARRIE Penguins	-
29 - 2020-02-12	249	Manitoba Moose	-	TUSCON Roadrunners	-
30 - 2020-02-13	258	TUSCON Roadrunners	-	Binghampton Devils	-
32 - 2020-02-15	279	Manitoba Moose	-	TUSCON Roadrunners	-
33 - 2020-02-16	289	TUSCON Roadrunners	-	VICTORIAVILLE Tigres	-
34 - 2020-02-17	297	TUSCON Roadrunners	-	MONT-LAURIER Sommet	-
35 - 2020-02-18	309	CHICAGO Wolves	-	TUSCON Roadrunners	-
37 - 2020-02-20	323	TUSCON Roadrunners	-	CHICAGO Wolves	-
38 - 2020-02-21	335	CORNWALL Aces	-	TUSCON Roadrunners	-
39 - 2020-02-22	354	TUSCON Roadrunners	-	LAVAL Rockets	-
40 - 2020-02-23	361	MILWAUKEE Admirals	-	TUSCON Roadrunners	-
42 - 2020-02-25	381	TUSCON Roadrunners	-	COLORADO Eagles	-
43 - 2020-02-26	385	CORNWALL Aces	-	TUSCON Roadrunners	-
44 - 2020-02-27	405	MILWAUKEE Admirals	-	TUSCON Roadrunners	-
45 - 2020-02-28	409	TUSCON Roadrunners	-	CORNWALL Aces	-
46 - 2020-02-29	428	MONT-LAURIER Sommet	-	TUSCON Roadrunners	-
48 - 2020-03-02	446	TUSCON Roadrunners	-	BROOKLYN Wolfpack	-
49 - 2020-03-03	457	CHICAGO Wolves	-	TUSCON Roadrunners	-
50 - 2020-03-04	468	TUSCON Roadrunners	-	STOCKTON Flames	-
52 - 2020-03-06	475	TUSCON Roadrunners	-	PV Sharapovas	-
53 - 2020-03-07	488	TUSCON Roadrunners	-	LAVAL Rockets	-
54 - 2020-03-08	497	Binghampton Devils	-	TUSCON Roadrunners	-
56 - 2020-03-10	513	BROOKLYN Wolfpack	-	TUSCON Roadrunners	-
58 - 2020-03-12	534	UTICA Comets	-	TUSCON Roadrunners	-
59 - 2020-03-13	546	TUSCON Roadrunners	-	PV Sharapovas	-
60 - 2020-03-14	561	LEHIGH VALLEY Phantoms	-	TUSCON Roadrunners	-
61 - 2020-03-15	571	TUSCON Roadrunners	-	BRIDGEPORT Sound Tigers	-
62 - 2020-03-16	586	BRIDGEPORT Sound Tigers	-	TUSCON Roadrunners	-
63 - 2020-03-17	597	TUSCON Roadrunners	-	MILWAUKEE Admirals	-
65 - 2020-03-19	612	LAVAL Rockets	-	TUSCON Roadrunners	-
66 - 2020-03-20	625	TUSCON Roadrunners	-	IOWA Wild	-
67 - 2020-03-21	639	HERSEY Bears	-	TUSCON Roadrunners	-
68 - 2020-03-22	650	TUSCON Roadrunners	-	ROCKFORD IceHogs	-
69 - 2020-03-23	664	TUSCON Roadrunners	-	Syracruse Crunch	-
70 - 2020-03-24	674	VICTORIAVILLE Tigres	-	TUSCON Roadrunners	-
72 - 2020-03-26	691	HERSEY Bears	-	TUSCON Roadrunners	-
73 - 2020-03-27	706	TUSCON Roadrunners	-	HERSEY Bears	-
74 - 2020-03-28	715	LAVAL Rockets	-	TUSCON Roadrunners	-
76 - 2020-03-30	730	TUSCON Roadrunners	-	HERSEY Bears	-
77 - 2020-03-31	741	PROVIDENCE Bruins	-	TUSCON Roadrunners	-
78 - 2020-04-01	757	TUSCON Roadrunners	-	PROVIDENCE Bruins	-
79 - 2020-04-02	770	PROVIDENCE Bruins	-	TUSCON Roadrunners	-
80 - 2020-04-03	783	TUSCON Roadrunners	-	Marlies de Toronto	-
81 - 2020-04-04	790	TUSCON Roadrunners	-	ROCKFORD IceHogs	-
82 - 2020-04-05	805	STOCKTON Flames	-	TUSCON Roadrunners	-
84 - 2020-04-07	817	TUSCON Roadrunners	-	BRIDGEPORT Sound Tigers	-
85 - 2020-04-08	826	TUSCON Roadrunners	-	SAN DIEGO Gulls	-
86 - 2020-04-09	839	BELLEVILLE Senators	-	TUSCON Roadrunners	-
87 - 2020-04-10	855	HOLLYWOOD Oscar	-	TUSCON Roadrunners	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
89 - 2020-04-12	871	COLORADO Eagles	-	TUSCON Roadrunners	-
90 - 2020-04-13	879	TUSCON Roadrunners	-	MILWAUKEE Admirals	-
91 - 2020-04-14	897	COLORADO Eagles	-	TUSCON Roadrunners	-
92 - 2020-04-15	903	TUSCON Roadrunners	-	Manitoba Moose	-
93 - 2020-04-16	917	TUSCON Roadrunners	-	LEHIGH VALLEY Phantoms	-
94 - 2020-04-17	929	TUSCON Roadrunners	-	HOLLYWOOD Oscar	-
95 - 2020-04-18	939	ROCKFORD IceHogs	-	TUSCON Roadrunners	-
97 - 2020-04-20	958	Marlies de Toronto	-	TUSCON Roadrunners	-
98 - 2020-04-21	968	TUSCON Roadrunners	-	COLORADO Eagles	-
99 - 2020-04-22	984	PV Sharapovas	-	TUSCON Roadrunners	-
101 - 2020-04-24	1003	WILKIES-BARRIE Penguins	-	TUSCON Roadrunners	-
104 - 2020-04-27	1019	TUSCON Roadrunners	-	BELLEVILLE Senators	-
106 - 2020-04-29	1034	SAN DIEGO Gulls	-	TUSCON Roadrunners	-
107 - 2020-04-30	1043	TUSCON Roadrunners	-	BELLEVILLE Senators	-
110 - 2020-05-03	1064	SAN DIEGO Gulls	-	TUSCON Roadrunners	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	35	15
Assistance	0	0
Assistance PCT	0.00%	0.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
37	0 - 0.00%	0$	0$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
195,631$	1,742,500$	1,742,500$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	123,559$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	103	24,707$	2,544,821$

Afficher ou Masquer des Colonnes

	Ligue											Domicile											Visiteur
Année	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
33	6	4	1	0	0	0	0	1	52	11	41	4	2	1	0	0	0	0	1	27	8	19	2	2	0	0	0	0	0	0	25	3	22	9	52	96	148	0	1	26	15	11	0	414	127	147	137	7	109	19	28	87	15	3	20.00%	13	3	76.92%	0	132	184	71.74%	80	132	60.61%	86	114	75.44%	215	181	90	27	58	33
Total Saison Régulière	6	4	1	0	0	0	0	1	52	11	41	4	2	1	0	0	0	0	1	27	8	19	2	2	0	0	0	0	0	0	25	3	22	9	52	96	148	0	1	26	15	11	0	414	127	147	137	7	109	19	28	87	15	3	20.00%	13	3	76.92%	0	132	184	71.74%	80	132	60.61%	86	114	75.44%	215	181	90	27	58	33