OTHL - Thunderbirds

Panthers
Formation
Points
Informations Joueurs
Lignes
Statistiques d'Équipe
Calendrier
Finance
Client Web pour Lignes

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

#	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	Âge	Contrat	Salaire
1	Max Jones		X	X		100.00	87	46	78	73	80	67	84	68	44	59	68	71	25	59	59	71	50	66	0	23	1	863,333$
2	Sam Steel	X	X			100.00	75	43	93	81	67	68	81	67	88	62	66	66	25	59	59	68	50	66	0	23	1	925,000$
3	Alexander Nylander (R)		X	X		100.00	63	41	94	84	68	62	80	68	33	70	68	61	75	60	60	69	50	66	0	23	2	1,775,000$
4	Emil Bemstrom (R)	X	X	X		100.00	71	43	99	82	70	63	61	70	25	60	68	62	25	54	55	0	50	63	0	22	2	1,633,333$
5	Josh Leivo		X	X		100.00	73	43	91	71	72	57	64	63	33	58	70	56	63	63	63	66	50	62	0	28	2	2,000,000$
6	Luke Johnson	X				100.00	86	45	88	67	70	56	68	58	73	50	58	69	25	47	47	62	50	59	0	27	1	925,000$
7	Michael McCarron	X		X		100.00	74	84	50	65	88	58	55	56	70	48	59	63	25	50	50	59	50	58	0	26	2	800,000$
8	Justin Richards (R)	X				100.00	74	69	84	64	69	56	55	60	75	58	58	63	55	44	44	61	50	58	0	23	2	1,500,000$
9	Jackson Cates (R)	X	X	X		100.00	51	55	55	55	55	55	55	55	55	55	55	55	55	55	55	1	50	53	0	24	2	1,000,000$
10	Erik Brannstrom (R)				X	100.00	73	42	77	83	64	69	71	76	25	67	49	67	25	51	51	60	50	66	0	22	2	1,375,000$
11	Brendan Guhle				X	100.00	72	73	70	75	73	61	63	55	25	50	42	64	40	58	58	55	50	61	0	24	1	1,000,000$
12	Dan Renouf				X	100.00	76	44	75	62	74	54	62	55	25	52	47	70	25	55	55	56	50	61	0	27	1	750,000$
13	Carl Dahlstrom				X	100.00	85	83	91	61	83	47	46	56	25	53	41	71	39	59	59	57	50	61	0	26	2	925,000$
14	Lucas Carlsson (R)				X	100.00	65	42	94	65	70	61	66	59	25	47	47	73	25	45	46	57	50	61	0	24	2	925,000$
15	Tyler Wotherspoon				X	100.00	77	76	79	61	76	60	63	49	25	43	39	62	37	44	44	52	50	57	0	28	3	800,000$
16	Parker Wotherspoon				X	100.00	65	68	59	63	68	61	66	46	25	36	40	55	38	44	44	49	50	54	0	24	2	854,722$
Rayé

	MOYENNE D'ÉQUIPE					100.00	73	56	80	70	72	60	65	60	42	54	55	64	38	53	53	53	50	61

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

#	Nom du Gardien	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Jake Oettinger	100.00	73	70	66	92	76	71	81	70	81	74	45	46	47	74	50	72	0
2	Dan Vladar (R)	100.00	64	54	68	80	66	67	68	72	71	70	30	44	45	66	50	65	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	69	62	67	86	71	69	75	71	76	72	38	45	46	70	50	69

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Chris Taylor	60	66	64	73	74	69	76	CAN	49	2	700,000$

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

Deprecated: number_format(): Passing null to parameter #1 ($num) of type float is deprecated in /home/othlca/history.othl.ca/public_html/outputs/2021-22/pre-season/PlayersStatSub.php on line 105

Deprecated: number_format(): Passing null to parameter #1 ($num) of type float is deprecated in /home/othlca/history.othl.ca/public_html/outputs/2021-22/pre-season/PlayersStatSub.php on line 105

Deprecated: number_format(): Passing null to parameter #1 ($num) of type float is deprecated in /home/othlca/history.othl.ca/public_html/outputs/2021-22/pre-season/PlayersStatSub.php on line 105

Deprecated: number_format(): Passing null to parameter #1 ($num) of type float is deprecated in /home/othlca/history.othl.ca/public_html/outputs/2021-22/pre-season/PlayersStatSub.php on line 105

Deprecated: number_format(): Passing null to parameter #1 ($num) of type float is deprecated in /home/othlca/history.othl.ca/public_html/outputs/2021-22/pre-season/PlayersStatSub.php on line 105

#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	HT	P/20	PSS	FW	S1	S2	S3
1	Luke Johnson	Thunderbirds (FLA)	C	16	17	10	27	20	14	0	40	40	87	30	78	19.54%	17	260	16.31	1	0	1	3	8	2	1	3	2	30	1	0	73.63%	311	1	2.07	0	0	2	2	3
2	Tyler Wotherspoon	Thunderbirds (FLA)	D	16	8	19	27	14	16	0	60	16	66	14	34	12.12%	19	290	18.14	4	2	6	34	34	0	1	1	0	20	3	0	0.00%	0	0	1.86	0	0	3	1	1
3	Parker Wotherspoon	Thunderbirds (FLA)	D	16	9	17	26	18	14	0	65	17	48	27	35	18.75%	25	315	19.69	3	1	4	21	29	0	2	2	1	30	0	0	0.00%	0	1	1.65	0	0	1	4	3
4	Alexander Nylander	Thunderbirds (FLA)	LW/RW	9	10	10	20	17	0	0	2	17	54	14	23	18.52%	4	151	16.80	0	1	1	4	6	1	1	2	3	22	3	0	40.00%	5	2	2.65	1	0	3	0	1
5	Michael Dal Colle	Panthers	LW/RW	14	11	8	19	19	4	0	0	15	38	16	32	28.95%	1	139	9.93	0	0	0	0	0	0	0	0	0	2	0	0	66.67%	12	0	2.73	0	0	1	1	1
6	Michael McCarron	Thunderbirds (FLA)	C/RW	16	10	8	18	19	8	0	32	24	61	20	48	16.39%	2	187	11.70	0	0	0	0	0	0	0	0	2	29	2	0	74.63%	205	0	1.92	0	0	0	3	2
7	Lucas Carlsson	Thunderbirds (FLA)	D	16	1	7	8	7	0	0	10	10	16	6	8	6.25%	7	187	11.72	1	1	2	6	2	0	0	0	0	0	0	0	0.00%	0	0	0.85	0	0	1	0	0
8	Dan Renouf	Thunderbirds (FLA)	D	16	1	5	6	7	25	5	40	7	8	3	6	12.50%	4	195	12.20	0	0	0	0	0	0	0	0	1	13	0	0	0.00%	0	0	0.61	0	1	0	0	1
9	Emil Bemstrom	Thunderbirds (FLA)	C/LW/RW	3	3	1	4	2	0	0	5	6	15	5	13	20.00%	0	55	18.44	0	0	0	3	4	0	0	0	1	1	1	1	40.00%	5	0	1.45	0	0	0	2	0
10	Max Jones	Thunderbirds (FLA)	LW/RW	2	1	1	2	1	0	0	2	3	5	2	1	20.00%	1	29	14.55	0	0	0	0	3	0	0	0	0	3	0	0	0.00%	2	0	1.37	0	0	0	0	0
11	Sam Steel	Thunderbirds (FLA)	C/LW	2	1	0	1	1	2	0	4	7	9	2	3	11.11%	0	35	17.54	0	0	0	1	3	0	0	0	0	0	0	0	70.27%	37	0	0.57	1	0	0	0	0
12	Erik Brannstrom	Thunderbirds (FLA)	D	1	0	1	1	1	0	0	1	0	1	0	0	0.00%	2	23	23.67	0	0	0	1	1	0	0	0	0	3	0	0	0.00%	0	0	0.85	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				127	72	87	159	126	83	5	261	162	408	139	281	17.65%	82	1869	14.72	9	5	14	73	96	3	5	8	10	157	10	1	72.79%	577	4	1.70	2	1	11	13	12

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

#	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	Dan Vladar	Thunderbirds (FLA)	12	9	2	1	0.907	2.16	695	0	2	25	270	0	0	0	0.667	3	12	0	0	0	1
Stats d'équipe Total ou en Moyenne			12	9	2	1	0.907	2.16	695	0	2	25	270	0	0	0	0.667	3	12	0	0	0	1

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

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	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Link
Alexander Nylander	Thunderbirds (FLA)	LW/RW	23	1998-03-01	Yes	180 Lbs	6 ft1	No	No	No	2	Pro & Farm	1,775,000$	1,775,000$	0$	0$	No	1,775,000$		Lien
Brendan Guhle	Thunderbirds (FLA)	D	24	1997-07-29	No	197 Lbs	6 ft2	No	No	No	1	Pro & Farm	1,000,000$	1,000,000$	0$	0$	No			Lien / Lien NHL
Carl Dahlstrom	Thunderbirds (FLA)	D	26	1995-01-28	No	221 Lbs	6 ft4	No	No	No	2	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$		Lien / Lien NHL
Dan Renouf	Thunderbirds (FLA)	D	27	1994-06-01	No	198 Lbs	6 ft3	No	No	No	1	Pro & Farm	750,000$	750,000$	0$	0$	No			Lien / Lien NHL
Dan Vladar	Thunderbirds (FLA)	G	24	1997-08-20	Yes	185 Lbs	6 ft5	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$		Lien / Lien NHL
Emil Bemstrom	Thunderbirds (FLA)	C/LW/RW	22	1999-06-01	Yes	193 Lbs	6 ft0	No	No	No	2	Pro & Farm	1,633,333$	1,633,333$	0$	0$	No	1,633,333$		Lien / Lien NHL
Erik Brannstrom	Thunderbirds (FLA)	D	22	1999-09-02	Yes	181 Lbs	5 ft9	No	No	No	2	Pro & Farm	1,375,000$	1,375,000$	0$	0$	No	1,375,000$		Lien / Lien NHL
Jackson Cates	Thunderbirds (FLA)	C/LW/RW	24	1997-09-28 3:44:48 AM	Yes	190 Lbs	6 ft0	Yes	No	No	2	Pro & Farm	1,000,000$	1,000,000$	0$	0$	No	1,000,000$
Jake Oettinger	Thunderbirds (FLA)	G	22	1998-12-18	No	225 Lbs	6 ft5	No	No	No	1	Pro & Farm	925,000$	925,000$	0$	0$	No			Lien / Lien NHL
Josh Leivo	Thunderbirds (FLA)	LW/RW	28	1993-05-26	No	192 Lbs	6 ft2	No	No	No	2	Pro & Farm	2,000,000$	2,000,000$	0$	0$	No	2,000,000$		Lien / Lien NHL
Justin Richards	Thunderbirds (FLA)	C	23	1998-03-17	Yes	190 Lbs	5 ft11	Yes	No	No	2	Pro & Farm	1,500,000$	1,500,000$	0$	0$	No	1,500,000$		Lien
Lucas Carlsson	Thunderbirds (FLA)	D	24	1997-07-05	Yes	190 Lbs	6 ft0	No	No	No	2	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$		Lien / Lien NHL
Luke Johnson	Thunderbirds (FLA)	C	27	1994-09-18	No	198 Lbs	5 ft11	No	No	No	1	Pro & Farm	925,000$	925,000$	0$	0$	No			Lien / Lien NHL
Max Jones	Thunderbirds (FLA)	LW/RW	23	1998-02-17	No	220 Lbs	6 ft1	No	No	No	1	Pro & Farm	863,333$	863,333$	0$	0$	No			Lien / Lien NHL
Michael McCarron	Thunderbirds (FLA)	C/RW	26	1995-03-07	No	232 Lbs	6 ft6	No	No	No	2	Pro & Farm	800,000$	800,000$	0$	0$	No	800,000$		Lien / Lien NHL
Parker Wotherspoon	Thunderbirds (FLA)	D	24	1997-08-24	No	181 Lbs	6 ft1	No	No	No	2	Pro & Farm	854,722$	854,722$	0$	0$	No	854,722$		Lien / Lien NHL
Sam Steel	Thunderbirds (FLA)	C/LW	23	1998-02-03	No	189 Lbs	5 ft11	No	No	No	1	Pro & Farm	925,000$	925,000$	0$	0$	No			Lien / Lien NHL
Tyler Wotherspoon	Thunderbirds (FLA)	D	28	1993-03-12	No	207 Lbs	6 ft2	No	No	No	3	Pro & Farm	800,000$	800,000$	0$	0$	No	800,000$	800,000$	Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
18	24.44	198 Lbs	6 ft1	1.72	1,095,910$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1				40	0	1	4
2		Luke Johnson		30	0	1	4
3		Michael McCarron		20	1	2	2
4				10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Parker Wotherspoon		40	1	2	2
2		Tyler Wotherspoon	30	1	2	2
3	Lucas Carlsson	Dan Renouf	20	1	2	2
4			10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1				60	0	0	5
2		Luke Johnson		40	0	0	5

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Parker Wotherspoon		60	1	2	2
2		Tyler Wotherspoon	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Luke Johnson		60	1	2	2
2	Michael McCarron		40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Parker Wotherspoon		60	1	2	2
2		Tyler Wotherspoon	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Luke Johnson	60	1	2	2	Parker Wotherspoon		60	1	2	2
2	Michael McCarron	40	1	2	2		Tyler Wotherspoon	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Luke Johnson		60	1	2	2
2			40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Parker Wotherspoon		60	1	2	2
2		Tyler Wotherspoon	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
			Parker Wotherspoon

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
	Luke Johnson	Michael McCarron	Parker Wotherspoon

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Luke Johnson, , Michael McCarron	Luke Johnson,	Michael McCarron

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Lucas Carlsson, Dan Renouf,	Lucas Carlsson	Dan Renouf,

Tirs de Pénalité
, , , ,

Gardien
#1 : , #2 :

Lignes d'Attaque Perso. en Prol.
, , , , , Luke Johnson, Luke Johnson, , , Michael McCarron,

Lignes de Défense Perso. en Prol.
Parker Wotherspoon, , , Tyler Wotherspoon, Lucas Carlsson

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	Barracudas	1	1	0	0	0	0	0	0	6	4	2	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	6	4	2	2	1.000	6	9	15	0	0	37	26	17	0	27	195	183	202	7	28	10	6	19	3	2	66.67%	3	1	66.67%	0	249	454	54.85%	231	399	57.89%	152	250	60.80%	494	384	293	88	176	98
2	Bears	2	2	0	0	0	0	0	0	11	3	8	1	1	0	0	0	0	0	0	3	2	1	1	1	0	0	0	0	0	0	8	1	7	4	1.000	11	17	28	0	0	37	26	17	0	79	195	183	202	7	32	8	8	56	2	1	50.00%	4	0	100.00%	0	249	454	54.85%	231	399	57.89%	152	250	60.80%	494	384	293	88	176	98
3	Bruins	2	0	2	0	0	0	0	0	5	11	-6	1	0	1	0	0	0	0	0	3	4	-1	1	0	1	0	0	0	0	0	2	7	-5	0	0.000	5	9	14	0	0	37	26	17	0	59	195	183	202	7	55	26	10	36	10	3	30.00%	5	4	20.00%	0	249	454	54.85%	231	399	57.89%	152	250	60.80%	494	384	293	88	176	98
4	Checkers	2	1	1	0	0	0	0	0	11	9	2	1	1	0	0	0	0	0	0	7	4	3	1	0	1	0	0	0	0	0	4	5	-1	2	0.500	11	18	29	0	0	37	26	17	0	65	195	183	202	7	75	13	17	39	4	1	25.00%	6	0	100.00%	0	249	454	54.85%	231	399	57.89%	152	250	60.80%	494	384	293	88	176	98
5	Penguins	2	2	0	0	0	0	0	0	16	2	14	1	1	0	0	0	0	0	0	8	0	8	1	1	0	0	0	0	0	0	8	2	6	4	1.000	16	28	44	0	1	37	26	17	0	79	195	183	202	7	46	14	18	36	8	1	12.50%	8	1	87.50%	2	249	454	54.85%	231	399	57.89%	152	250	60.80%	494	384	293	88	176	98
6	Phantoms	3	1	1	0	0	0	0	1	5	8	-3	2	0	1	0	0	0	0	1	3	7	-4	1	1	0	0	0	0	0	0	2	1	1	3	0.500	5	10	15	0	0	37	26	17	0	68	195	183	202	7	76	27	18	52	6	0	0.00%	8	1	87.50%	0	249	454	54.85%	231	399	57.89%	152	250	60.80%	494	384	293	88	176	98
7	Sound Tigers	2	2	0	0	0	0	0	0	14	1	13	1	1	0	0	0	0	0	0	7	0	7	1	1	0	0	0	0	0	0	7	1	6	4	1.000	14	19	33	0	1	37	26	17	0	99	195	183	202	7	33	8	8	50	6	3	50.00%	4	0	100.00%	0	249	454	54.85%	231	399	57.89%	152	250	60.80%	494	384	293	88	176	98
8	Wolf Pack	2	2	0	0	0	0	0	0	12	4	8	1	1	0	0	0	0	0	0	4	2	2	1	1	0	0	0	0	0	0	8	2	6	4	1.000	12	20	32	0	0	37	26	17	0	108	195	183	202	7	36	13	12	48	2	1	50.00%	6	0	100.00%	1	249	454	54.85%	231	399	57.89%	152	250	60.80%	494	384	293	88	176	98
	Total	16	11	4	0	0	0	0	1	80	42	38	8	5	2	0	0	0	0	1	35	19	16	8	6	2	0	0	0	0	0	45	23	22	23	0.719	80	130	210	0	2	37	26	17	0	584	195	183	202	7	381	119	97	336	41	12	29.27%	44	7	84.09%	3	249	454	54.85%	231	399	57.89%	152	250	60.80%	494	384	293	88	176	98
	_Since Last GM Reset	16	11	4	0	0	0	0	1	80	42	38	8	5	2	0	0	0	0	1	35	19	16	8	6	2	0	0	0	0	0	45	23	22	23	0.719	80	130	210	0	2	37	26	17	0	584	195	183	202	7	381	119	97	336	41	12	29.27%	44	7	84.09%	3	249	454	54.85%	231	399	57.89%	152	250	60.80%	494	384	293	88	176	98
	_Vs Conference	15	10	4	0	0	0	0	1	74	38	36	8	5	2	0	0	0	0	1	35	19	16	7	5	2	0	0	0	0	0	39	19	20	21	0.700	74	121	195	0	2	37	26	17	0	557	195	183	202	7	353	109	91	317	38	10	26.32%	41	6	85.37%	3	249	454	54.85%	231	399	57.89%	152	250	60.80%	494	384	293	88	176	98
	_Vs Division	13	10	4	0	0	0	0	1	69	27	42	7	5	2	0	0	0	0	1	32	15	17	6	5	2	0	0	0	0	0	37	12	25	21	0.808	69	112	181	0	2	37	26	17	0	498	195	183	202	7	298	83	81	281	28	7	25.00%	36	2	94.44%	3	249	454	54.85%	231	399	57.89%	152	250	60.80%	494	384	293	88	176	98

			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
16	23	W2	80	130	210	584	381	119	97	336	0	2

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
16	11	4	0	0	0	1	80	42

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	5	2	0	0	0	1	35	19

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	6	2	0	0	0	0	45	23

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
7	3	0	0	0	0

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
41	12	29.27%	44	7	84.09%	3

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
195	183	202	7	37	26	17	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
249	454	54.85%	231	399	57.89%	152	250	60.80%

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
494	384	293	88	176	98

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
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
1 - 2021-10-18	8	Thunderbirds	2	Phantoms	1	W			Sommaire du Match
2 - 2021-10-19	21	Phantoms	4	Thunderbirds	3	L	X	X	Sommaire du Match
4 - 2021-10-21	43	Thunderbirds	8	Wolf Pack	2	W			Sommaire du Match
5 - 2021-10-22	57	Thunderbirds	8	Bears	1	W			Sommaire du Match
6 - 2021-10-23	61	Phantoms	3	Thunderbirds	0	L			Sommaire du Match
7 - 2021-10-24	81	Sound Tigers	0	Thunderbirds	7	W			Sommaire du Match
8 - 2021-10-25	102	Thunderbirds	6	Barracudas	4	W			Sommaire du Match
9 - 2021-10-26	111	Thunderbirds	8	Penguins	2	W			Sommaire du Match
10 - 2021-10-27	123	Penguins	0	Thunderbirds	8	W			Sommaire du Match
12 - 2021-10-29	144	Thunderbirds	7	Sound Tigers	1	W			Sommaire du Match
13 - 2021-10-30	153	Thunderbirds	2	Bruins	7	L			Sommaire du Match
14 - 2021-10-31	164	Checkers	4	Thunderbirds	7	W			Sommaire du Match
16 - 2021-11-02	188	Bruins	4	Thunderbirds	3	L			Sommaire du Match
18 - 2021-11-04	209	Thunderbirds	4	Checkers	5	L			Sommaire du Match
19 - 2021-11-05	223	Bears	2	Thunderbirds	3	W			Sommaire du Match
22 - 2021-11-08	255	Wolf Pack	2	Thunderbirds	4	W			Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité	2000	1000
Prix des Billets	55	0
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	Popularité de l'Équipe
0	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
0$	1,972,638$	1,840,472$	0$

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

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	0	0$	0$

Afficher ou Masquer des Colonnes

Warning: Undefined variable $TeamCareerSumSeasonOnly in /home/othlca/history.othl.ca/public_html/outputs/2021-22/pre-season/FarmTeam.php on line 1324

	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

	Thunderbirds
	GP: 16 \| W: 11 \| L: 4 \| OTL: 1 \| P: 23 GF: 80 \| GA: 42 \| PP%: 29.27% \| PK%: 84.09% DG: Scott \| Morale : 50 \| Moyenne d'Équipe : 62