OTHL - Reign

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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	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP
1	Mason Appleton	X	X		100.00	71	43	96	74	72	51	92	60	25	65	58	60	25	47	47	64	50	61	0
2	Calle Rosen			X	100.00	70	65	81	70	65	75	79	62	25	62	46	64	44	55	55	60	50	63	0
3	Andreas Borgman			X	100.00	71	70	72	77	70	70	75	52	25	45	42	62	40	55	55	55	50	61	0
4	Duncan Siemens			X	100.00	72	79	56	65	79	65	70	46	25	35	40	61	38	52	53	51	50	58	0
Rayé

	MOYENNE D'ÉQUIPE				100.00	71	64	76	72	72	65	79	55	25	52	47	62	37	52	53	58	50	61

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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	Richard Bachman	100.00	48	52	65	62	46	48	50	54	48	48	30	48	48	49	50	51	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	48	52	65	62	46	48	50	54	48	48	30	48	48	49	50	51

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Spencer Carbery	59	62	75	67	49	48	60	CAN	38	3	700,000$

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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	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3

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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

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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	Status	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Link
Andreas Borgman	Reign (LAK)	D	24	1995-06-18	No	191 Lbs	6 ft0	No	No	No	2	Avec Restriction	Pro & Farm	1,775,000$	0$	0$	No	Lien
Calle Rosen	Reign (LAK)	D	25	1994-02-02	No	176 Lbs	6 ft0	No	No	No	2	Avec Restriction	Pro & Farm	1,775,000$	0$	0$	No	Lien
Duncan Siemens	Reign (LAK)	D	26	1993-09-07	No	210 Lbs	6 ft3	No	No	No	2	Avec Restriction	Pro & Farm	1,388,333$	0$	0$	No	Lien
Mason Appleton	Reign (LAK)	C/RW	23	1996-01-15	No	193 Lbs	6 ft2	No	No	No	2	Avec Restriction	Pro & Farm	758,000$	0$	0$	No	Lien
Richard Bachman	Reign (LAK)	G	32	1987-07-25	No	183 Lbs	5 ft10	No	No	No	1	Sans Restriction	Pro & Farm	900,000$	0$	0$	No	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
5	26.00	191 Lbs	6 ft1	1.80	1,319,267$

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

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			40	1	2	2
2			30	1	2	2
3			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	1	2	2
2				40	1	2	2

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

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

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

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1		60	1	2	2			60	1	2	2
2		40	1	2	2			40	1	2	2

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

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

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, ,	,

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, ,		,

Tirs de Pénalité
, , , ,

Gardien
#1 : , #2 :

Lignes d'Attaque Perso. en Prol.
, , , , , , , , , ,

Lignes de Défense Perso. en Prol.
, , , ,

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	Americans	1	0	1	0	0	0	0	0	1	8	-7	1	0	1	0	0	0	0	0	1	8	-7	0	0	0	0	0	0	0	0	0	0	0	0	0.000	1	2	3	0	0	5	4	2	1	20	42	41	38	9	34	7	2	10	5	0	0.00%	1	0	100.00%	0	41	118	34.75%	57	225	25.33%	34	116	29.31%	87	56	268	48	73	26
2	Admirals	1	0	0	0	1	0	0	0	6	5	1	1	0	0	0	1	0	0	0	6	5	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	6	12	18	0	0	5	4	2	1	38	42	41	38	9	55	17	4	26	0	0	0.00%	2	1	50.00%	0	41	118	34.75%	57	225	25.33%	34	116	29.31%	87	56	268	48	73	26
3	Checkers	1	0	0	0	0	0	0	1	3	4	-1	1	0	0	0	0	0	0	1	3	4	-1	0	0	0	0	0	0	0	0	0	0	0	1	0.500	3	6	9	0	0	5	4	2	1	35	42	41	38	9	75	23	11	44	2	0	0.00%	3	1	66.67%	0	41	118	34.75%	57	225	25.33%	34	116	29.31%	87	56	268	48	73	26
4	Comets	1	0	1	0	0	0	0	0	1	11	-10	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	11	-10	0	0.000	1	2	3	0	0	5	4	2	1	8	42	41	38	9	56	13	2	10	2	1	50.00%	1	0	100.00%	0	41	118	34.75%	57	225	25.33%	34	116	29.31%	87	56	268	48	73	26
5	Condors	1	0	1	0	0	0	0	0	0	4	-4	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	4	-4	0	0.000	0	0	0	0	0	5	4	2	1	5	42	41	38	9	49	12	4	5	2	0	0.00%	2	0	100.00%	0	41	118	34.75%	57	225	25.33%	34	116	29.31%	87	56	268	48	73	26
6	Heat	1	0	1	0	0	0	0	0	0	11	-11	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	11	-11	0	0.000	0	0	0	0	0	5	4	2	1	4	42	41	38	9	87	31	4	8	1	0	0.00%	2	0	100.00%	0	41	118	34.75%	57	225	25.33%	34	116	29.31%	87	56	268	48	73	26
	Total	7	0	5	0	1	0	0	1	12	49	-37	4	0	2	0	1	0	0	1	11	23	-12	3	0	3	0	0	0	0	0	1	26	-25	3	0.214	12	24	36	0	0	5	4	2	1	127	42	41	38	9	390	111	29	109	13	1	7.69%	12	2	83.33%	0	41	118	34.75%	57	225	25.33%	34	116	29.31%	87	56	268	48	73	26
8	Wolves	1	0	1	0	0	0	0	0	1	6	-5	1	0	1	0	0	0	0	0	1	6	-5	0	0	0	0	0	0	0	0	0	0	0	0	0.000	1	2	3	0	0	5	4	2	1	17	42	41	38	9	34	8	2	6	1	0	0.00%	1	0	100.00%	0	41	118	34.75%	57	225	25.33%	34	116	29.31%	87	56	268	48	73	26
	_Since Last GM Reset	7	0	5	0	1	0	0	1	12	49	-37	4	0	2	0	1	0	0	1	11	23	-12	3	0	3	0	0	0	0	0	1	26	-25	3	0.214	12	24	36	0	0	5	4	2	1	127	42	41	38	9	390	111	29	109	13	1	7.69%	12	2	83.33%	0	41	118	34.75%	57	225	25.33%	34	116	29.31%	87	56	268	48	73	26
	_Vs Conference	5	0	4	0	1	0	0	0	8	34	-26	3	0	2	0	1	0	0	0	8	19	-11	2	0	2	0	0	0	0	0	0	15	-15	2	0.200	8	16	24	0	0	5	4	2	1	84	42	41	38	9	259	75	16	55	9	0	0.00%	8	1	87.50%	0	41	118	34.75%	57	225	25.33%	34	116	29.31%	87	56	268	48	73	26

			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
7	3	L1	12	24	36	127	390	111	29	109	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
7	0	5	1	0	0	1	12	49

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	0	2	1	0	0	1	11	23

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	0	3	0	0	0	0	1	26

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
0	5	1	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
13	1	7.69%	12	2	83.33%	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
42	41	38	9	5	4	2	1

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
41	118	34.75%	57	225	25.33%	34	116	29.31%

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
87	56	268	48	73	26

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
4 - 2019-10-07	23	Reign	0	Condors	4	L			Sommaire du Match
7 - 2019-10-10	36	Reign	0	Heat	11	L			Sommaire du Match
8 - 2019-10-11	46	Reign	1	Comets	11	L			Sommaire du Match
11 - 2019-10-14	67	Admirals	5	Reign	6	W	X		Sommaire du Match
12 - 2019-10-15	75	Wolves	6	Reign	1	L			Sommaire du Match
14 - 2019-10-17	86	Checkers	4	Reign	3	L	X	X	Sommaire du Match
16 - 2019-10-19	101	Americans	8	Reign	1	L			Sommaire du Match
18 - 2019-10-21	115	Heat	-	Reign	-
21 - 2019-10-24	142	Reign	-	Moose	-
23 - 2019-10-26	154	Reign	-	Rampage	-
25 - 2019-10-28	165	Reign	-	Wild	-
26 - 2019-10-29	170	Reign	-	IceHogs	-
29 - 2019-11-01	191	Comets	-	Reign	-
32 - 2019-11-04	211	IceHogs	-	Reign	-
35 - 2019-11-07	232	Reign	-	Marlies	-
37 - 2019-11-09	244	Reign	-	Senators	-
39 - 2019-11-11	255	Reign	-	Rocket	-
42 - 2019-11-14	274	Wild	-	Reign	-
44 - 2019-11-16	290	Griffins	-	Reign	-
46 - 2019-11-18	304	Wolves	-	Reign	-
48 - 2019-11-20	316	Reign	-	Roadrunners	-
51 - 2019-11-23	340	Condors	-	Reign	-
53 - 2019-11-25	352	Roadrunners	-	Reign	-
55 - 2019-11-27	368	Barracudas	-	Reign	-
57 - 2019-11-29	382	Sound Tigers	-	Reign	-
59 - 2019-12-01	400	Reign	-	Barracudas	-
60 - 2019-12-02	409	Moose	-	Reign	-
62 - 2019-12-04	419	Reign	-	Gulls	-
64 - 2019-12-06	435	Bears	-	Reign	-
66 - 2019-12-08	448	Reign	-	Condors	-
67 - 2019-12-09	454	Reign	-	Heat	-
70 - 2019-12-12	477	Wolf Pack	-	Reign	-
72 - 2019-12-14	487	Reign	-	Gulls	-
74 - 2019-12-16	511	Reign	-	Penguins	-
75 - 2019-12-17	516	Reign	-	Griffins	-
77 - 2019-12-19	524	Reign	-	Bruins	-
79 - 2019-12-21	540	Reign	-	Monsters	-
81 - 2019-12-23	553	Reign	-	Americans	-
83 - 2019-12-25	571	Rampage	-	Reign	-
87 - 2019-12-29	590	Reign	-	Barracudas	-
88 - 2019-12-30	600	Reign	-	Comets	-
91 - 2020-01-02	621	Phantoms	-	Reign	-
95 - 2020-01-06	645	Admirals	-	Reign	-
97 - 2020-01-08	659	Monsters	-	Reign	-
99 - 2020-01-10	675	Stars	-	Reign	-
100 - 2020-01-11	688	Reign	-	Wolves	-
102 - 2020-01-13	693	Reign	-	Checkers	-
105 - 2020-01-16	722	Reign	-	Crunch	-
107 - 2020-01-18	731	Reign	-	Thunderbirds	-
109 - 2020-01-20	752	Reign	-	Phantoms	-
120 - 2020-01-31	779	Crunch	-	Reign	-
121 - 2020-02-01	782	Reign	-	Roadrunners	-
123 - 2020-02-03	796	Gulls	-	Reign	-
126 - 2020-02-06	824	Reign	-	Bears	-
128 - 2020-02-08	834	Reign	-	Sound Tigers	-
130 - 2020-02-10	848	Reign	-	Devils	-
131 - 2020-02-11	858	Reign	-	Wolf Pack	-
134 - 2020-02-14	878	Heat	-	Reign	-
137 - 2020-02-17	898	Reign	-	Eagles	-
140 - 2020-02-20	926	Reign	-	Moose	-
142 - 2020-02-22	934	Thunderbirds	-	Reign	-
144 - 2020-02-24	949	Eagles	-	Reign	-
145 - 2020-02-25	963	Condors	-	Reign	-
148 - 2020-02-28	982	Penguins	-	Reign	-
151 - 2020-03-02	1002	Devils	-	Reign	-
152 - 2020-03-03	1016	Reign	-	Wolves	-
156 - 2020-03-07	1036	Marlies	-	Reign	-
158 - 2020-03-09	1053	Wild	-	Reign	-
160 - 2020-03-11	1068	Eagles	-	Reign	-
162 - 2020-03-13	1082	Senators	-	Reign	-
165 - 2020-03-16	1105	Gulls	-	Reign	-
168 - 2020-03-19	1125	Rocket	-	Reign	-
170 - 2020-03-21	1141	Bruins	-	Reign	-
172 - 2020-03-23	1158	Comets	-	Reign	-
173 - 2020-03-24	1167	Roadrunners	-	Reign	-
175 - 2020-03-26	1177	Reign	-	Stars	-
177 - 2020-03-28	1196	Reign	-	Admirals	-
178 - 2020-03-29	1201	Reign	-	Rampage	-
180 - 2020-03-31	1216	Reign	-	IceHogs	-
182 - 2020-04-02	1233	Barracudas	-	Reign	-
185 - 2020-04-05	1255	Reign	-	Gulls	-
186 - 2020-04-06	1264	Stars	-	Reign	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	40	0
Assistance	6,165	2,986
Assistance PCT	77.06%	74.65%

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	2288 - 76.26%	61,650$	246,600$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
124,270$	659,633$	659,633$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
3,546$	60,282$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
2,281,050$	169	7,310$	1,235,390$

Afficher ou Masquer des Colonnes

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	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
2019	7	0	5	0	1	0	0	1	12	49	-37	4	0	2	0	1	0	0	1	11	23	-12	3	0	3	0	0	0	0	0	1	26	-25	3	12	24	36	0	0	5	4	2	1	127	42	41	38	9	390	111	29	109	13	1	7.69%	12	2	83.33%	0	41	118	34.75%	57	225	25.33%	34	116	29.31%	87	56	268	48	73	26
Total Saison Régulière	7	0	5	0	1	0	0	1	12	49	-37	4	0	2	0	1	0	0	1	11	23	-12	3	0	3	0	0	0	0	0	1	26	-25	3	12	24	36	0	0	5	4	2	1	127	42	41	38	9	390	111	29	109	13	1	7.69%	12	2	83.33%	0	41	118	34.75%	57	225	25.33%	34	116	29.31%	87	56	268	48	73	26