NorthEastern Hockey League - Binghamton Roadrunners

Elmira Roadrunners
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Statistiques d'Équipe
Calendrier
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Historique
Dernière Transactions
Blessure/Suspension
Stats d'équipe en Carrière

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
1	Ryan Hughes	12		X			100.00	37	1	99	66	75	91	74	99	99	99	99	87	99	99	99	1	69	83	0
2	Howard Frisco	73			X		99.50	99	33	27	53	83	78	61	99	99	99	97	83	89	99	99	24	63	81	0
3	Cameron Hain	18	X				100.00	1	1	99	64	75	72	62	99	85	99	99	69	81	99	99	5	64	78	0
4	Jesse Nimmo	23			X		100.00	99	47	21	75	74	89	68	86	87	87	95	58	70	94	99	33	40	77	0
5	Jarvis Goral	10		X			100.00	92	13	86	58	76	65	80	89	90	92	89	32	50	99	84	19	66	72	0
6	Jason Mills (R)	0	X				100.00	33	26	97	70	57	84	53	83	85	83	97	43	50	99	99	72	62	71	0
7	Alan Stepp	17	X				100.00	25	6	99	68	79	95	65	79	1	81	92	61	70	88	63	49	36	71	0
8	Brendan Pomerleau	0		X			100.00	13	1	99	74	77	98	88	81	83	65	92	46	50	99	75	16	42	70	0
9	Drew Kagel	9	X				100.00	90	33	4	64	79	73	52	79	48	72	84	69	70	99	66	25	58	70	0
10	Shaun Pearson	0		X			100.00	99	24	13	71	75	91	47	77	36	65	91	60	70	80	99	61	46	70	0
11	Anthony Comans	28			X		100.00	1	1	99	80	68	53	44	82	31	82	80	73	50	99	82	55	24	69	0
12	Eric Trussell	0			X		100.00	19	2	99	64	79	79	69	87	83	82	95	12	50	99	67	30	59	67	0
13	Vaughn Felber	14				X	100.00	2	1	99	74	77	99	82	99	36	97	98	87	82	99	99	1	40	79	0
14	Corey Thorne	4				X	100.00	72	27	48	79	77	85	83	80	50	76	62	60	70	81	99	28	54	71	0
15	Kirk Simms	44				X	100.00	47	13	80	65	75	83	80	72	13	54	79	79	50	99	99	48	47	70	0
16	Brandon Lesage	0				X	100.00	83	26	54	69	79	73	65	80	63	60	82	69	70	87	93	38	31	70	0
17	Ryan McCord	0				X	100.00	73	14	79	66	73	69	75	88	50	81	96	35	50	99	89	33	49	69	0
18	Chris Bradley	43				X	100.00	48	17	83	63	77	79	90	67	18	42	25	84	55	99	84	37	20	68	0
Rayé
1	Wesley Olsen	7		X			63.36	71	51	34	70	67	85	61	77	11	81	82	82	70	88	74	47	55	72	0
2	Ty Schiefer	0	X				100.00	13	1	99	70	79	80	71	75	95	85	91	31	50	99	68	27	68	68	0
3	Mike Harwood	0				X	100.00	12	1	99	63	77	46	56	91	72	87	69	85	47	99	99	17	20	68	0
4	Brett Sanft	53				X	100.00	71	18	72	66	81	70	67	77	36	60	69	64	50	99	90	23	19	67	0

	MOYENNE D'ÉQUIPE					98.31	50	16	72	68	75	79	68	84	58	79	85	62	63	96	88	31	47	72

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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	Scot Wickersham	100.00	71	92	72	84	76	84	81	78	85	72	62	72	96	40	62	79	0
2	Kyle Cavagnaro	100.00	76	84	84	74	79	85	84	70	86	62	55	75	98	38	53	77	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	74	88	78	79	78	85	83	74	86	67	59	74	97	39	58	78

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Phil Bailey	86	72	88	73	84	84	51	USA	44	2	400,000$

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

#	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

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

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	Status	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial
Alan Stepp	Binghamton Roadrunners	C	21	5/19/1997	No	202 Lbs	6 ft4	No	No	No	1	Contrat d'Entrée	Pro & Farm	538,462$	538,462$	538,462$	No
Anthony Comans	Binghamton Roadrunners	RW	26	12/3/1992	No	162 Lbs	6 ft0	No	No	No	1	Avec Restriction	Pro & Farm	425,000$	425,000$	425,000$	No
Brandon Lesage	Binghamton Roadrunners	D	25	1/5/1994	No	203 Lbs	6 ft5	No	No	No	1	Avec Restriction	Pro & Farm	400,000$	400,000$	400,000$	No
Brendan Pomerleau	Binghamton Roadrunners	LW	26	7/19/1992	No	190 Lbs	6 ft6	No	No	No	1	Avec Restriction	Pro & Farm	502,920$	502,920$	502,920$	No
Brett Sanft	Binghamton Roadrunners	D	25	6/9/1993	No	213 Lbs	6 ft7	No	No	No	1	Avec Restriction	Pro & Farm	375,000$	375,000$	375,000$	No
Cameron Hain	Binghamton Roadrunners	C	30	11/1/1988	No	202 Lbs	6 ft2	No	No	No	1	Sans Restriction	Pro & Farm	1,350,000$	1,350,000$	1,350,000$	No
Chris Bradley	Binghamton Roadrunners	D	25	5/20/1993	No	210 Lbs	6 ft2	No	No	No	1	Avec Restriction	Pro & Farm	468,606$	468,606$	468,606$	No
Corey Thorne	Binghamton Roadrunners	D	21	5/27/1997	No	181 Lbs	6 ft6	No	No	No	1	Contrat d'Entrée	Pro & Farm	437,885$	437,885$	437,885$	No
Drew Kagel	Binghamton Roadrunners	C	24	9/24/1994	No	225 Lbs	6 ft5	No	No	No	1	Avec Restriction	Pro & Farm	376,750$	376,750$	376,750$	No
Eric Trussell	Binghamton Roadrunners	RW	26	9/28/1992	No	213 Lbs	6 ft4	No	No	No	2	Avec Restriction	Pro & Farm	300,000$	300,000$	300,000$	No
Howard Frisco	Binghamton Roadrunners	RW	34	1/26/1985	No	248 Lbs	6 ft3	No	No	No	2	Sans Restriction	Pro & Farm	2,825,000$	2,825,000$	2,825,000$	No
Jarvis Goral	Binghamton Roadrunners	LW	29	3/10/1989	No	215 Lbs	5 ft11	No	No	No	3	Sans Restriction	Pro & Farm	1,100,000$	1,100,000$	1,100,000$	No
Jason Mills	Binghamton Roadrunners	C	19	7/18/1999	Yes	173 Lbs	6 ft3	No	No	No	4	Contrat d'Entrée	Pro & Farm	613,462$	613,462$	613,462$	No
Jesse Nimmo	Binghamton Roadrunners	RW	20	5/18/1998	No	187 Lbs	6 ft6	No	No	No	2	Contrat d'Entrée	Pro & Farm	594,231$	594,231$	594,231$	No
Kirk Simms	Binghamton Roadrunners	D	26	2/20/1992	No	200 Lbs	6 ft1	No	No	No	1	Avec Restriction	Pro & Farm	650,000$	650,000$	650,000$	No
Kyle Cavagnaro	Binghamton Roadrunners	G	24	10/27/1994	No	182 Lbs	6 ft1	No	No	No	3	Avec Restriction	Pro & Farm	525,000$	525,000$	525,000$	No
Mike Harwood	Binghamton Roadrunners	D	36	12/15/1982	No	207 Lbs	6 ft1	No	No	No	1	Sans Restriction	Pro & Farm	540,000$	540,000$	540,000$	No
Ryan Hughes	Binghamton Roadrunners	LW	39	11/12/1979	No	202 Lbs	6 ft3	No	No	No	1	Sans Restriction	Pro & Farm	3,500,000$	3,500,000$	3,500,000$	No
Ryan McCord	Binghamton Roadrunners	D	27	10/21/1991	No	194 Lbs	5 ft11	No	No	No	1	Avec Restriction	Pro & Farm	515,000$	515,000$	515,000$	No
Scot Wickersham	Binghamton Roadrunners	G	24	6/1/1994	No	214 Lbs	6 ft8	No	No	No	2	Avec Restriction	Pro & Farm	450,000$	450,000$	450,000$	No
Shaun Pearson	Binghamton Roadrunners	LW	23	11/9/1995	No	187 Lbs	6 ft3	No	No	No	2	Avec Restriction	Pro & Farm	533,500$	533,500$	533,500$	No
Ty Schiefer	Binghamton Roadrunners	C	26	6/30/1992	No	197 Lbs	6 ft7	No	No	No	2	Avec Restriction	Pro & Farm	400,000$	400,000$	400,000$	No
Vaughn Felber	Binghamton Roadrunners	D	28	5/15/1990	No	189 Lbs	6 ft7	No	No	No	2	Sans Restriction	Pro & Farm	2,200,000$	2,200,000$	2,200,000$	No
Wesley Olsen (Sur la Masse Salariale)	Binghamton Roadrunners	LW	20	11/4/1998	No	195 Lbs	6 ft2	No	No	No	3	Contrat d'Entrée	Pro & Farm	593,269$	593,269$	593,269$	No

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
24	26.00	200 Lbs	6 ft4	1.67	842,254$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
20,214,085$	10,134,462$	2,831,731$	613,462$	0$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Ryan Hughes	Cameron Hain	Howard Frisco	40	1	2	2
2	Jarvis Goral	Alan Stepp	Jesse Nimmo	30	1	2	2
3	Shaun Pearson	Jason Mills	Anthony Comans	20	1	2	2
4	Brendan Pomerleau	Drew Kagel	Eric Trussell	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Vaughn Felber	Corey Thorne	40	1	2	2
2	Kirk Simms	Brandon Lesage	30	1	2	2
3	Ryan McCord	Chris Bradley	20	1	2	2
4	Vaughn Felber	Corey Thorne	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Ryan Hughes	Cameron Hain	Howard Frisco	60	1	2	2
2	Jarvis Goral	Alan Stepp	Jesse Nimmo	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Vaughn Felber	Corey Thorne	60	1	2	2
2	Kirk Simms	Brandon Lesage	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Ryan Hughes	Howard Frisco	60	1	2	2
2	Cameron Hain	Jesse Nimmo	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Vaughn Felber	Corey Thorne	60	1	2	2
2	Kirk Simms	Brandon Lesage	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Ryan Hughes	60	1	2	2	Vaughn Felber	Corey Thorne	60	1	2	2
2	Howard Frisco	40	1	2	2	Kirk Simms	Brandon Lesage	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Ryan Hughes	Howard Frisco	60	1	2	2
2	Cameron Hain	Jesse Nimmo	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Vaughn Felber	Corey Thorne	60	1	2	2
2	Kirk Simms	Brandon Lesage	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Ryan Hughes	Cameron Hain	Howard Frisco	Vaughn Felber	Corey Thorne

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Ryan Hughes	Cameron Hain	Howard Frisco	Vaughn Felber	Corey Thorne

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Jason Mills, Drew Kagel, Shaun Pearson	Jason Mills, Drew Kagel	Shaun Pearson

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Ryan McCord, Chris Bradley, Kirk Simms	Ryan McCord	Chris Bradley, Kirk Simms

Tirs de Pénalité
Ryan Hughes, Howard Frisco, Cameron Hain, Jesse Nimmo, Jarvis Goral

Gardien
#1 : Kyle Cavagnaro, #2 : Scot Wickersham

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
	Total	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.000	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.00%	0	0	0	0.00%	0	0	0.00%	0	0	0.00%	0	0	0	0	0	0

			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
0	0	N/A	0	0	0	0	0	0	0	0	0	0

Tous les Matchs
GP	W	L	OTW	OTL	T	GF	GA
0	0	0	0	0	0	0	0

Matchs locaux
GP	W	L	OTW	OTL	T	GF	GA
0	0	0	0	0	0	0	0

Matchs Éxtérieurs
GP	W	L	OTW	OTL	T	GF	GA
0	0	0	0	0	0	0	0

Derniers 10 Matchs
W	L	OTW	OTL	T
0	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
0	0	0.00%	0	0	0.00%	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
0	0	0	0	0	0	0	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
0	0	0.00%	0	0	0.00%	0	0	0.00%

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
0	0	0	0	0	0

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	RI	Lien

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2	Niveau 3	Niveau 4	Luxe
Capacité de l'Aréna	1675	1100	850	660	570
Prix des Billets	143	106	70	53	308
Assistance	0.00%	0.00%	0.00%	0.00%	0.00%
Attendance PCT	0.00%	0.00%	0.00%	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
40	0 - 0.00%	0$	0$	4855	70

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs	Valeur du Cap Salarial Spécial
0$	19,620,816$	19,620,816$	0$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Taxe de Luxe Totale	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	0$	0$	23	1

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	14	0$	0$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Cap Salarial de la Saison Éstimé	Compte Bancaire Actuel	Compte Bancaire Projeté
0$	0$	49,954,959$	49,954,959$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Ryan Hughes	AGE:39	PO:1	OV:83
Wesley Olsen	AGE:20	PO:47	OV:72
Jarvis Goral	AGE:29	PO:19	OV:72
Lee Demeglio	AGE:21	PO:44	OV:71
Shaun Pearson	AGE:23	PO:61	OV:70
Brendan Pomerleau	AGE:26	PO:16	OV:70
Erik Dickman	AGE:30	PO:1	OV:69
Nicolas Perrault	AGE:25	PO:44	OV:67
Dave Sankar	AGE:21	PO:54	OV:63
*Craig Balsinger	AGE:18	PO:61	OV:61
*Brandon Kupka	AGE:19	PO:46	OV:59
Andy Cibula	AGE:22	PO:47	OV:57

Cameron Hain	AGE:30	PO:5	OV:78
*Jason Mills	AGE:19	PO:72	OV:71
Alan Stepp	AGE:21	PO:49	OV:71
Drew Kagel	AGE:24	PO:25	OV:70
Cris Passalacqua	AGE:29	PO:11	OV:69
Ty Schiefer	AGE:26	PO:27	OV:68
Max Hoven	AGE:29	PO:1	OV:68
Nickolas Dushaj	AGE:20	PO:38	OV:67
*Zeb Knutson	AGE:25	PO:92	OV:62
Jamal Hall	AGE:20	PO:63	OV:60
Gavin Morrow	AGE:20	PO:55	OV:59
Andreas Scheinost	AGE:22	PO:53	OV:58

Howard Frisco	AGE:34	PO:24	OV:81
Jesse Nimmo	AGE:20	PO:33	OV:77
Anthony Comans	AGE:26	PO:55	OV:69
Eric Trussell	AGE:26	PO:30	OV:67
*Dylan Hinkle	AGE:19	PO:66	OV:66
*Garrett Tuffey	AGE:18	PO:54	OV:66
Aron Suttell	AGE:29	PO:1	OV:66
Brad McGowan	AGE:28	PO:78	OV:65
Joey Tognazzini	AGE:21	PO:80	OV:59
Craig Daniels	AGE:20	PO:60	OV:59
Nolan Bouwens	AGE:21	PO:57	OV:58
Colin Beaton	AGE:20	PO:40	OV:58

Défense #1

Défense #2

Gardien

Vaughn Felber	AGE:28	PO:1	OV:79
Corey Thorne	AGE:21	PO:28	OV:71
Kirk Simms	AGE:26	PO:48	OV:70
Brandon Lesage	AGE:25	PO:38	OV:70
Roderick Rose	AGE:24	PO:62	OV:69
Ryan McCord	AGE:27	PO:33	OV:69
Chris Bradley	AGE:25	PO:37	OV:68
Dustin Trivisonno	AGE:25	PO:25	OV:68
Mike Harwood	AGE:36	PO:17	OV:68
Brett Sanft	AGE:25	PO:23	OV:67

Kyle Couture	AGE:29	PO:11	OV:66
*Garrett Minard	AGE:19	PO:39	OV:65
*Drew Gaeddert	AGE:19	PO:50	OV:64
Harry Deveney	AGE:21	PO:44	OV:62
Ian Brady	AGE:24	PO:69	OV:61
Rick Hudelson	AGE:20	PO:60	OV:61
*Stewart White	AGE:19	PO:57	OV:61
Rory Van Steenwyk	AGE:23	PO:56	OV:60
Peyton Carkhuff	AGE:20	PO:53	OV:60
Kris Meisner	AGE:21	PO:37	OV:58

Scot Wickersham	AGE:24	PO:40	OV:79
Kyle Cavagnaro	AGE:24	PO:38	OV:77
Dion Neubert	AGE:25	PO:50	OV:76
Joe Wilson	AGE:29	PO:21	OV:76
*Chris Rayl	AGE:19	PO:63	OV:72
*Nate Ferber	AGE:21	PO:50	OV:71
Mark Bollis	AGE:29	PO:29	OV:71

Éspoirs

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

Éspoir	Nom de l'Équipe	Année de Repêchage	Choix Total	Information	Lien

Choix au Repêchage

Année	R1	R2	R3	R4	R5	R6	R7	R8
17	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
18	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
19	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
20	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
21	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin

[9/2/2019 1:31:47 PM] - Binghamton Roadrunners didn't make playoff for year 16.
[6/13/2019 8:35:24 PM] - Derrick Ellen was released.
[6/13/2019 8:35:24 PM] - Binghamton Roadrunners paid $0 to release Derrick Ellen.
[6/13/2019 8:35:21 PM] - Carmen Penwell was released.
[6/13/2019 8:35:21 PM] - Binghamton Roadrunners paid $0 to release Carmen Penwell.
[6/10/2019 9:50:06 PM] - Mark Hannon was released.
[6/9/2019 11:34:50 AM] - Joe Wilson signed with Binghamton Roadrunners for $600,000 for 2 year(s).
[6/9/2019 11:34:50 AM] - Joe Wilson was added to Binghamton Roadrunners.
[6/2/2019 2:59:45 PM] - Chris Rayl was added to Binghamton Roadrunners.

[9/2/2019 1:31:47 PM] Lee Demeglio from Elmira Roadrunners is back from Bruised Left Foot Injury.
[9/2/2019 1:31:47 PM] Dustin Trivisonno from Elmira Roadrunners is back from Exhaustion.
[9/2/2019 1:26:50 PM] Cris Passalacqua from Elmira Roadrunners is back from Exhaustion.
[9/2/2019 1:26:50 PM] Erik Dickman from Elmira Roadrunners is back from Exhaustion.
[9/2/2019 1:26:50 PM] Elmira Roadrunners lines for next game are empty. Current rosters/lines are not erased.
[9/2/2019 1:26:50 PM] Dustin Trivisonno from Elmira Roadrunners is injured from Exhaustion.
[9/2/2019 1:26:50 PM] Max Hoven from Elmira Roadrunners has scored a Hat Trick!
[9/2/2019 1:26:50 PM] Game 1079 - Jamal Hall from Elmira Roadrunners is injured (Sprained Left Knee) and is out for 2 weeks.
[9/2/2019 1:26:48 PM] Auto Lines Function has been run for Elmira Roadrunners.
[9/2/2019 1:26:48 PM] Auto Roster Farm Only Function has been run for Binghamton Roadrunners.
[9/2/2019 1:26:48 PM] Elmira Roadrunners lines for next game are empty. Current rosters/lines are not erased.
[9/2/2019 1:26:48 PM] Cris Passalacqua from Elmira Roadrunners is injured from Exhaustion.
[9/2/2019 1:26:48 PM] Erik Dickman from Elmira Roadrunners is injured from Exhaustion.
[9/2/2019 1:26:39 PM] Auto Lines Function has been run for Elmira Roadrunners.
[9/2/2019 1:26:39 PM] Auto Lines Function has been run for Binghamton Roadrunners.

Wesley Olsen est dehors pour 1 mois à cause de Left Knee Injury.
Jamal Hall est dehors pour 6 jours à cause de Sprained Left Knee Injury.
Zeb Knutson est dehors pour le reste de la saison à cause de Torn Right ACL Injury - Dec 2019.

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
Saison Régulière
16	80	32	27	12	0	9	0	0	247	249	-2	40	18	11	5	0	6	0	0	134	124	10	40	14	16	7	0	3	0	0	113	125	-12	76	247	422	669	2	1	89	84	74	0	2523	966	837	701	19	2493	790	605	1588	337	58	17.21%	279	45	83.87%	5	1042	2026	51.43%	1020	1922	53.07%	626	1193	52.47%	1778	1040	1707	721	1392	701
07-08	80	31	32	12	1	4	0	0	243	232	11	40	18	12	6	1	3	0	0	126	108	18	40	13	20	6	0	1	0	0	117	124	-7	74	243	410	653	0	1	75	93	74	1	2481	895	874	699	13	2693	844	2447	1882	300	44	14.67%	321	41	87.23%	3	1022	1946	52.52%	1005	1950	51.54%	680	1363	49.89%	1629	845	1671	809	1570	767
08-09	80	31	36	8	2	3	0	0	279	310	-31	40	14	17	4	2	3	0	0	139	153	-14	40	17	19	4	0	0	0	0	140	157	-17	70	279	477	756	0	0	88	105	84	2	2914	1016	964	914	20	2858	968	662	1795	279	46	16.49%	233	42	81.97%	6	1015	2008	50.55%	928	1807	51.36%	724	1436	50.42%	1696	940	3783	1774	1489	751
09-10	80	31	34	6	7	2	0	0	258	272	-14	40	14	15	3	7	1	0	0	147	147	0	40	17	19	3	0	1	0	0	111	125	-14	68	258	436	694	3	1	90	90	71	7	2739	986	949	775	29	2832	924	911	1781	263	39	14.83%	288	45	84.38%	12	1027	2003	51.27%	939	1891	49.66%	721	1392	51.80%	1631	881	5706	2641	1509	738
10-11	80	33	27	15	0	5	0	0	281	281	0	40	17	14	7	0	2	0	0	140	138	2	40	16	13	8	0	3	0	0	141	143	-2	81	281	483	764	1	1	92	92	97	0	2839	1006	907	916	10	2724	917	671	1746	270	48	17.78%	255	45	82.35%	2	1045	2062	50.68%	1073	2050	52.34%	647	1244	52.01%	1692	939	1711	771	1481	728
11-12	80	32	30	8	3	7	0	0	262	270	-8	40	16	17	4	0	3	0	0	128	130	-2	40	16	13	4	3	4	0	0	134	140	-6	72	262	447	709	3	1	73	96	90	3	2680	952	854	854	20	2712	863	550	1739	342	63	18.42%	259	54	79.15%	3	1058	2090	50.62%	999	1999	49.97%	662	1256	52.71%	1724	958	1700	733	1430	734
12-13	80	35	28	11	4	2	0	0	287	258	29	40	18	14	4	2	2	0	0	144	130	14	40	17	14	7	2	0	0	0	143	128	15	81	287	471	758	1	0	98	94	91	4	2780	1081	867	815	17	2707	889	409	1700	273	47	17.22%	185	30	83.78%	3	993	1978	50.20%	994	2029	48.99%	608	1215	50.04%	1741	997	1692	734	1430	728
13-14	80	36	26	14	1	3	0	0	251	226	25	40	20	12	5	1	2	0	0	131	112	19	40	16	14	9	0	1	0	0	120	114	6	86	251	417	668	1	1	88	68	94	1	2675	968	840	836	31	2636	859	620	1719	372	47	12.63%	295	41	86.10%	9	1092	2106	51.85%	1034	1930	53.58%	624	1155	54.03%	1750	971	1673	756	1453	744
14-15	80	37	35	7	0	1	0	0	261	260	1	40	18	19	2	0	1	0	0	130	129	1	40	19	16	5	0	0	0	0	131	131	0	81	261	428	689	0	1	89	89	83	0	2744	1016	908	812	8	2563	813	870	1647	378	53	14.02%	365	61	83.29%	6	1202	2161	55.62%	1080	1980	54.55%	648	1167	55.53%	1761	987	1653	755	1424	722
15-16	80	25	36	11	4	4	0	0	280	309	-29	40	10	21	5	2	2	0	0	130	149	-19	40	15	15	6	2	2	0	0	150	160	-10	61	280	458	738	2	0	92	90	94	4	2761	1040	871	824	26	2687	962	680	1702	372	72	19.35%	335	66	80.30%	9	961	2124	45.24%	941	2015	46.70%	553	1250	44.24%	1723	962	1715	755	1423	713
16-17	80	26	29	12	7	6	0	0	261	271	-10	40	13	11	7	5	4	0	0	135	128	7	40	13	18	5	2	2	0	0	126	143	-17	64	261	446	707	3	1	85	78	91	7	2534	905	819	767	43	2575	869	603	1603	327	57	17.43%	267	39	85.39%	7	878	1966	44.66%	824	1843	44.71%	557	1222	45.58%	1716	981	1767	736	1401	702
17-18	80	28	36	10	2	4	0	0	245	269	-24	40	11	20	7	1	1	0	0	121	142	-21	40	17	16	3	1	3	0	0	124	127	-3	66	245	420	665	1	2	76	87	80	2	2381	825	783	748	25	2562	793	820	1642	282	45	15.96%	326	51	84.36%	4	905	1863	48.58%	937	1921	48.78%	638	1238	51.53%	1717	974	1751	735	1402	699
Total Saison Régulière	960	377	376	126	31	50	0	0	3155	3207	-52	480	187	183	59	21	30	0	0	1605	1590	15	480	190	193	67	10	20	0	0	1550	1617	-67	880	3155	5315	8470	17	10	1035	1066	1023	31	32051	11656	10473	9661	261	32042	10491	9848	20544	3795	619	16.31%	3408	560	83.57%	69	12240	24333	50.30%	11774	23337	50.45%	7688	15131	50.81%	20563	11481	26534	11925	17409	8731

Année	R1	R2	R3	R4	R5	R6	R7	R8
17	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
18	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
19	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
20	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
21	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin

Année	R1	R2	R3	R4	R5	R6	R7	R8
17	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
18	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
19	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
20	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
21	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin

Année	R1	R2	R3	R4	R5	R6	R7	R8
17	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
18	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
19	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
20	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin
21	Bin	Bin	Bin	Bin	Bin	Bin	Bin	Bin