NorthEastern Hockey League Testing - Pittsburgh Yellow Jackets

Johnstown Yellow Jackets
Formation
Points
Informations Joueurs
Lignes
Statistiques d'Équipe
Calendrier
Finance
Profondeur
Historique
Dernière Transactions
Blessure/Suspension
Stats d'équipe en Carrière

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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	Sam Brauer		X			100.00	79	47	45	81	62	87	50	87	71	79	99	93	70	77	91	76	48	78	0
2	Jeff Clifton	X				100.00	99	54	41	64	75	54	44	86	87	99	88	90	88	99	99	14	48	77	0
3	Timothy Jett		X			100.00	43	1	99	65	76	26	28	83	85	96	91	78	92	99	99	44	49	73	0
4	Ralph Valles			X		100.00	1	1	99	76	73	55	53	99	88	98	89	45	45	99	99	42	48	73	0
5	Avery Lajoie	X				100.00	45	40	97	68	64	85	75	74	66	66	97	74	70	99	87	66	48	72	0
6	Scot Godek		X			100.00	56	23	92	72	74	76	75	75	61	77	88	49	70	99	69	48	48	70	0
7	Dean Helmers		X			100.00	1	1	99	58	79	58	67	95	77	65	84	79	76	99	84	41	51	69	0
8	Roy Sousa	X				100.00	95	26	74	62	74	2	18	83	69	78	93	84	92	80	95	42	51	69	0
9	Carey Stecklein	X				100.00	41	38	70	70	80	79	43	71	87	87	83	56	70	87	89	66	51	69	0
10	Brent Heneisen			X		100.00	38	9	87	71	75	78	67	66	64	44	84	81	83	99	99	29	48	68	0
11	John Silvis			X		100.00	14	1	97	64	78	41	41	68	87	72	92	69	99	92	66	14	48	66	0
12	Mason Sade			X		100.00	21	3	99	63	80	79	67	51	55	71	51	91	50	99	96	51	48	65	0
13	Jason Abbruzesse				X	100.00	99	47	41	63	79	42	40	99	78	97	99	96	86	96	99	20	49	78	0
14	Marc Roethler				X	100.00	99	40	59	65	84	19	13	84	28	86	92	97	77	99	99	27	48	73	0
15	Sebastian Boore				X	100.00	1	1	99	56	82	65	68	98	46	82	85	90	59	99	99	12	49	71	0
16	Rick Krause				X	100.00	31	36	99	84	70	83	69	52	53	76	74	77	50	99	74	42	48	69	0
17	Neil Mabra				X	100.00	89	50	13	66	77	79	82	61	23	79	55	74	70	72	68	47	48	69	0
18	Glenn Brantley				X	100.00	1	1	99	55	80	45	61	95	46	75	75	95	50	99	76	23	48	68	0
Rayé

	MOYENNE D'ÉQUIPE					100.00	47	23	78	67	76	59	53	79	65	79	84	79	72	94	88	39	49	71

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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 Messer	100.00	69	53	78	82	73	90	89	92	90	71	74	72	99	54	49	79	0
2	Ray Judd	100.00	69	1	82	85	75	81	74	99	83	64	70	67	99	65	48	74	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	69	27	80	84	74	86	82	96	87	68	72	70	99	60	49	77

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Jeff Daniels	75	68	71	85	73	63	57	USA	41	1	600,000$

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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	P/20	FW	FT	S1	S2	S3
1	Scot Godek	Pittsburgh Yellow Jackets	LW	7	2	5	7	-2	0	0	3	3	12	2	10	16.67%	0	88	12.70	0	0	0	1	4	0	0	0	0	0	0	0	38.89%	18	4	2	1.57	0	0	1	0	0
2	Willie Middaugh	Johnstown Yellow Jackets (Pit)	LW	6	4	2	6	6	0	0	1	7	17	3	11	23.53%	2	93	15.54	0	0	0	3	16	0	0	0	0	2	0	0	33.33%	6	2	1	1.29	0	0	1	0	2
3	Avery Lajoie	Pittsburgh Yellow Jackets	C	7	2	2	4	6	0	0	15	22	10	4	14	20.00%	3	128	18.40	0	0	0	2	21	0	0	0	0	14	0	1	48.28%	87	4	2	0.62	0	0	0	1	0
4	Heath Speier	Johnstown Yellow Jackets (Pit)	C	6	4	0	4	1	0	0	13	4	13	1	16	30.77%	0	72	12.15	0	0	0	0	2	0	0	0	0	0	1	0	60.00%	40	1	1	1.10	0	0	0	2	0
5	Brent Heneisen	Pittsburgh Yellow Jackets	RW	7	0	3	3	6	0	0	4	1	3	0	6	0.00%	3	108	15.54	0	0	0	0	21	0	0	0	0	0	0	0	50.00%	2	0	2	0.55	0	0	0	0	1
6	Jason Abbruzesse	Pittsburgh Yellow Jackets	D	7	0	3	3	5	30	10	32	13	17	7	7	0.00%	11	180	25.76	0	0	0	2	24	0	0	0	0	18	0	0	0.00%	0	9	3	0.33	0	2	0	0	0
7	John Silvis	Pittsburgh Yellow Jackets	RW	7	0	3	3	2	0	0	1	4	8	1	5	0.00%	1	72	10.39	0	0	0	0	0	0	0	0	0	0	0	0	60.00%	5	3	0	0.83	0	0	0	0	0
8	Marc Roethler	Pittsburgh Yellow Jackets	D	7	0	3	3	4	4	0	28	10	6	1	4	0.00%	11	190	27.15	0	0	0	1	25	0	0	0	0	24	0	0	0.00%	0	3	5	0.32	0	0	0	1	0
9	Damian Lowrie	Johnstown Yellow Jackets (Pit)	C	6	3	0	3	-1	0	0	10	3	13	1	7	23.08%	0	59	9.87	0	0	0	0	0	1	0	1	1	12	0	1	42.86%	28	1	1	1.01	0	0	1	0	0
10	Neil Mabra	Pittsburgh Yellow Jackets	D	7	1	2	3	-3	18	0	24	12	7	0	1	14.29%	8	141	20.27	0	0	0	2	18	0	0	0	0	12	0	0	0.00%	0	1	5	0.42	0	0	0	0	0
11	Sam Brauer	Pittsburgh Yellow Jackets	LW	7	1	1	2	-3	4	0	13	6	16	5	6	6.25%	6	167	23.93	0	0	0	2	24	1	1	2	1	26	0	0	42.47%	73	6	2	0.24	0	0	0	0	0
12	Brett Kerson	Johnstown Yellow Jackets (Pit)	LW	6	0	2	2	-1	0	0	1	2	9	1	6	0.00%	1	51	8.64	0	0	0	0	0	0	0	0	0	9	0	0	0.00%	1	0	1	0.77	0	0	0	0	0
13	Glenn Brantley	Pittsburgh Yellow Jackets	D	7	0	2	2	4	0	0	0	6	10	4	5	0.00%	4	97	14.00	0	0	0	0	0	0	0	0	0	14	0	0	0.00%	0	2	1	0.41	0	0	0	0	0
14	Rick Krause	Pittsburgh Yellow Jackets	D	7	0	2	2	1	0	0	7	9	3	2	0	0.00%	10	101	14.52	0	0	0	0	5	0	0	0	0	4	0	0	0.00%	0	3	1	0.39	0	0	0	0	0
15	Jeff Clifton	Pittsburgh Yellow Jackets	C	7	0	1	1	-2	32	10	14	8	8	3	6	0.00%	3	154	22.04	0	0	0	2	23	0	1	1	0	18	0	0	57.75%	187	4	3	0.13	1	1	0	0	0
16	Timothy Jett	Pittsburgh Yellow Jackets	LW	1	0	1	1	0	0	0	0	1	1	3	2	0.00%	1	17	17.12	0	1	1	0	4	0	0	0	0	1	0	0	0.00%	0	0	0	1.17	0	0	0	0	0
17	Sebastian Boore	Pittsburgh Yellow Jackets	D	7	1	0	1	-4	0	0	0	12	10	5	7	10.00%	15	158	22.67	1	0	1	1	22	0	0	0	0	22	0	0	0.00%	0	3	4	0.13	0	0	0	0	0
18	Mason Sade	Pittsburgh Yellow Jackets	RW	7	1	0	1	-1	0	0	1	0	4	0	2	25.00%	1	46	6.71	0	0	0	0	1	0	0	0	0	0	0	0	0.00%	2	0	2	0.43	0	0	0	0	0
19	Dean Helmers	Pittsburgh Yellow Jackets	LW	1	0	0	0	0	0	0	0	0	3	2	1	0.00%	0	8	8.52	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	1	0	0.00	0	0	0	0	0
20	Roy Sousa	Pittsburgh Yellow Jackets	C	1	0	0	0	0	0	0	3	1	1	1	0	0.00%	0	11	11.37	0	0	0	0	0	0	0	0	0	0	0	0	36.36%	11	0	0	0.00	0	0	0	0	0
21	Ralph Valles	Pittsburgh Yellow Jackets	RW	7	0	0	0	-4	0	0	1	8	21	7	12	0.00%	2	144	20.62	0	0	0	1	24	0	0	0	0	10	0	0	66.67%	18	7	0	0.00	0	0	0	0	0
22	Carey Stecklein	Pittsburgh Yellow Jackets	C	1	0	0	0	0	0	0	2	0	2	0	1	0.00%	0	7	7.03	0	0	0	0	0	0	0	0	0	0	0	0	75.00%	4	0	0	0.00	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				126	19	32	51	14	88	20	173	132	194	53	129	9.79%	82	2104	16.70	1	1	2	17	244	2	2	4	2	193	1	2	51.66%	482	54	36	0.48	1	3	3	4	3

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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	Richard Messer	Pittsburgh Yellow Jackets	7	1	3	3	0.912	3.04	434	0	0	22	251	101	0	0	0.000	0	7	0	0	0	0
Stats d'équipe Total ou en Moyenne			7	1	3	3	0.912	3.04	434	0	0	22	251	101	0	0	0.000	0	7	0	0	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	CONT	Status	Type	Salaire Actuel	Salaire Année 2	Salaire Année 3
Avery Lajoie	Pittsburgh Yellow Jackets	C	19	10/5/1997	No	205 Lbs	6 ft4	No	No	No	3	Contrat d'Entrée	Pro & Farm	568,269$	568,269$	568,269$
Brent Heneisen	Pittsburgh Yellow Jackets	RW	25	4/4/1992	No	185 Lbs	6 ft0	No	No	No	1	Avec Restriction	Pro & Farm	550,000$
Carey Stecklein	Pittsburgh Yellow Jackets	C	21	10/23/1995	No	213 Lbs	6 ft9	No	No	No	1	Contrat d'Entrée	Pro & Farm	383,350$
Dean Helmers	Pittsburgh Yellow Jackets	LW	33	3/30/1984	No	224 Lbs	6 ft2	No	No	No	3	Sans Restriction	Pro & Farm	522,000$	522,000$	522,000$
Glenn Brantley	Pittsburgh Yellow Jackets	D	28	3/29/1989	No	238 Lbs	6 ft1	No	No	No	1	Sans Restriction	Pro & Farm	615,000$
Jason Abbruzesse	Pittsburgh Yellow Jackets	D	36	6/28/1980	No	218 Lbs	6 ft5	No	No	No	3	Sans Restriction	Pro & Farm	1,778,000$	1,778,000$	1,778,000$
Jeff Clifton	Pittsburgh Yellow Jackets	C	37	3/29/1980	No	205 Lbs	6 ft2	No	No	No	1	Sans Restriction	Pro & Farm	2,250,000$
John Silvis	Pittsburgh Yellow Jackets	RW	26	3/28/1991	No	209 Lbs	6 ft3	No	No	No	3	Avec Restriction	Pro & Farm	393,000$	393,000$	393,000$
Marc Roethler	Pittsburgh Yellow Jackets	D	26	10/17/1990	No	220 Lbs	6 ft9	No	No	No	3	Avec Restriction	Pro & Farm	740,000$	740,000$	740,000$
Mason Sade	Pittsburgh Yellow Jackets	RW	24	4/18/1993	No	215 Lbs	6 ft3	No	No	No	3	Avec Restriction	Pro & Farm	375,000$	375,000$	375,000$
Neil Mabra	Pittsburgh Yellow Jackets	D	20	11/5/1996	No	226 Lbs	6 ft8	No	No	No	2	Contrat d'Entrée	Pro & Farm	338,260$	338,260$
Ralph Valles	Pittsburgh Yellow Jackets	RW	30	12/23/1986	No	176 Lbs	6 ft4	No	No	No	1	Sans Restriction	Pro & Farm	1,000,000$
Ray Judd	Pittsburgh Yellow Jackets	D	30	2/23/1987	No	234 Lbs	6 ft5	No	No	No	3	Sans Restriction	Pro & Farm	340,000$	340,000$	340,000$
Richard Messer	Pittsburgh Yellow Jackets	LW	33	12/7/1983	No	225 Lbs	6 ft2	No	No	No	1	Sans Restriction	Pro & Farm	750,000$
Rick Krause	Pittsburgh Yellow Jackets	D	24	9/23/1992	No	155 Lbs	6 ft0	No	No	No	3	Avec Restriction	Pro & Farm	625,000$	625,000$	625,000$
Roy Sousa	Pittsburgh Yellow Jackets	C	29	8/19/1987	No	202 Lbs	5 ft9	No	No	No	3	Sans Restriction	Pro & Farm	553,000$	553,000$	553,000$
Sam Brauer	Pittsburgh Yellow Jackets	LW	20	12/24/1996	No	167 Lbs	6 ft2	No	No	No	2	Contrat d'Entrée	Pro & Farm	584,615$	584,615$
Scot Godek	Pittsburgh Yellow Jackets	LW	21	6/7/1996	No	203 Lbs	6 ft0	No	No	No	1	Contrat d'Entrée	Pro & Farm	368,475$
Sebastian Boore	Pittsburgh Yellow Jackets	D	29	2/20/1988	No	234 Lbs	6 ft3	No	No	No	3	Sans Restriction	Pro & Farm	1,650,000$	1,650,000$	1,650,000$
Timothy Jett	Pittsburgh Yellow Jackets	LW	29	8/5/1987	No	201 Lbs	6 ft2	No	No	No	2	Sans Restriction	Pro & Farm	1,000,000$	1,000,000$

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
20	27.00	208 Lbs	6 ft3	2.15	769,198$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
15,383,969$	9,467,144$	7,544,269$	0$	0$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Sam Brauer	Jeff Clifton	Ralph Valles	40	1	2	2
2	Timothy Jett	Avery Lajoie	Brent Heneisen	30	1	2	2
3	Scot Godek	Roy Sousa	John Silvis	20	1	2	2
4	Dean Helmers	Carey Stecklein	Mason Sade	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jason Abbruzesse	Marc Roethler	40	1	2	2
2	Sebastian Boore	Rick Krause	30	1	2	2
3	Neil Mabra	Glenn Brantley	20	1	2	2
4	Jason Abbruzesse	Marc Roethler	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Sam Brauer	Jeff Clifton	Ralph Valles	60	1	2	2
2	Timothy Jett	Avery Lajoie	Brent Heneisen	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jason Abbruzesse	Marc Roethler	60	1	2	2
2	Sebastian Boore	Rick Krause	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Sam Brauer	Jeff Clifton	60	1	2	2
2	Timothy Jett	Ralph Valles	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jason Abbruzesse	Marc Roethler	60	1	2	2
2	Sebastian Boore	Rick Krause	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Sam Brauer	60	1	2	2	Jason Abbruzesse	Marc Roethler	60	1	2	2
2	Jeff Clifton	40	1	2	2	Sebastian Boore	Rick Krause	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Sam Brauer	Jeff Clifton	60	1	2	2
2	Timothy Jett	Ralph Valles	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jason Abbruzesse	Marc Roethler	60	1	2	2
2	Sebastian Boore	Rick Krause	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Sam Brauer	Jeff Clifton	Ralph Valles	Jason Abbruzesse	Marc Roethler

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Sam Brauer	Jeff Clifton	Ralph Valles	Jason Abbruzesse	Marc Roethler

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Scot Godek, Dean Helmers, Roy Sousa	Scot Godek, Dean Helmers	Roy Sousa

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Neil Mabra, Glenn Brantley, Sebastian Boore	Neil Mabra	Glenn Brantley, Sebastian Boore

Tirs de Pénalité
Sam Brauer, Jeff Clifton, Timothy Jett, Ralph Valles, Avery Lajoie

Gardien
#1 : Richard Messer, #2 : Ray Judd

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	Buffalo Wings	2	1	1	0	0	0	0	0	5	4	1	1	0	1	0	0	0	0	0	1	2	-1	1	1	0	0	0	0	0	0	4	2	2	2	0.500	5	9	14	0	0	3	1	1	0	58	25	17	16	0	69	22	24	45	11	1	9.09%	7	1	85.71%	0	87	167	52.10%	108	220	49.09%	54	95	56.84%	42	23	44	18	33	17
2	Cincinnati Clippers	1	0	1	0	0	0	0	0	1	3	-2	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	1	1	2	0	0	0	0	1	0	19	3	9	7	0	35	8	14	27	3	0	0.00%	7	1	85.71%	1	87	167	52.10%	108	220	49.09%	54	95	56.84%	19	10	22	9	18	8
3	Indianapolis Racers	1	0	0	1	0	0	0	0	5	5	0	1	0	0	1	0	0	0	0	5	5	0	0	0	0	0	0	0	0	0	0	0	0	1	0.500	5	9	14	0	0	2	2	1	0	44	15	13	15	1	39	16	12	16	5	0	0.00%	6	2	66.67%	0	87	167	52.10%	108	220	49.09%	54	95	56.84%	25	15	20	9	19	10
4	Richmond Robins	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	3	5	0	0	1	0	1	0	24	11	9	4	0	36	15	6	22	4	0	0.00%	3	0	100.00%	1	87	167	52.10%	108	220	49.09%	54	95	56.84%	20	10	22	9	16	8
5	Rochester Lakers	1	0	0	1	0	0	0	0	2	2	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	2	2	0	1	0.500	2	4	6	0	0	0	0	2	0	25	8	4	7	6	32	9	12	38	3	0	0.00%	6	1	83.33%	0	87	167	52.10%	108	220	49.09%	54	95	56.84%	21	10	24	9	19	9
	Since Last GM Reset	7	4	3	0	0	0	0	0	19	22	-3	3	0	2	1	0	0	0	0	8	11	-3	4	4	1	-1	0	0	0	0	11	11	0	8	0.571	19	32	51	0	0	8	4	7	0	194	71	58	57	8	251	82	88	173	29	1	3.45%	34	7	79.41%	2	87	167	52.10%	108	220	49.09%	54	95	56.84%	151	82	156	66	127	64
7	Toronto Royals	1	0	0	1	0	0	0	0	4	4	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	4	4	0	1	0.500	4	6	10	0	0	2	1	1	0	24	9	6	8	1	40	12	20	25	3	0	0.00%	5	2	60.00%	0	87	167	52.10%	108	220	49.09%	54	95	56.84%	22	12	22	9	20	10
	Total	7	1	3	3	0	0	0	0	19	22	-3	3	0	2	1	0	0	0	0	8	11	-3	4	1	1	2	0	0	0	0	11	11	0	5	0.357	19	32	51	0	0	8	4	7	0	194	71	58	57	8	251	82	88	173	29	1	3.45%	34	7	79.41%	2	87	167	52.10%	108	220	49.09%	54	95	56.84%	151	82	156	66	127	64
	Vs Conference	7	1	3	3	0	0	0	0	19	22	-3	3	0	2	1	0	0	0	0	8	11	-3	4	1	1	2	0	0	0	0	11	11	0	5	0.357	19	32	51	0	0	8	4	7	0	194	71	58	57	8	251	82	88	173	29	1	3.45%	34	7	79.41%	2	87	167	52.10%	108	220	49.09%	54	95	56.84%	151	82	156	66	127	64
	Vs Division	6	1	2	3	0	0	0	0	17	18	-1	2	0	1	1	0	0	0	0	6	7	-1	4	1	1	2	0	0	0	0	11	11	0	5	0.417	17	29	46	0	0	7	4	6	0	170	60	49	53	8	215	67	82	151	25	1	4.00%	31	7	77.42%	1	87	167	52.10%	108	220	49.09%	54	95	56.84%	131	72	133	57	110	55

			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	5	L1	19	32	51	194	251	82	88	173	0	0

Tous les Matchs
GP	W	L	OTW	OTL	T	GF	GA
7	1	3	0	0	3	19	22

Matchs locaux
GP	W	L	OTW	OTL	T	GF	GA
3	0	2	0	0	1	8	11

Matchs Éxtérieurs
GP	W	L	OTW	OTL	T	GF	GA
4	1	1	0	0	2	11	11

Derniers 10 Matchs
W	L	OTW	OTL	T
1	3	0	0	3

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
29	1	3.45%	34	7	79.41%	2

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
71	58	57	8	8	4	7	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
87	167	52.10%	108	220	49.09%	54	95	56.84%

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
151	82	156	66	127	64

Derniers Match Joués

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	Lien
1 - 2017-12-09	6	Pittsburgh Yellow Jackets	4	Toronto Royals	4	T	X	Sommaire du Match
3 - 2017-12-11	15	Pittsburgh Yellow Jackets	2	Rochester Lakers	2	T	X	Sommaire du Match
5 - 2017-12-13	23	Indianapolis Racers	5	Pittsburgh Yellow Jackets	5	T	X	Sommaire du Match
9 - 2017-12-17	38	Pittsburgh Yellow Jackets	1	Cincinnati Clippers	3	L		Sommaire du Match
11 - 2017-12-19	50	Richmond Robins	4	Pittsburgh Yellow Jackets	2	L		Sommaire du Match
13 - 2017-12-21	60	Pittsburgh Yellow Jackets	4	Buffalo Wings	2	W		Sommaire du Match
15 - 2017-12-23	77	Buffalo Wings	2	Pittsburgh Yellow Jackets	1	L		Sommaire du Match
19 - 2017-12-27	94	Pittsburgh Yellow Jackets	-	Brooklyn Dragons	-
21 - 2017-12-29	106	Indianapolis Racers	-	Pittsburgh Yellow Jackets	-
24 - 2018-01-01	126	Louisville Red Devils	-	Pittsburgh Yellow Jackets	-
26 - 2018-01-03	133	Pittsburgh Yellow Jackets	-	Louisville Red Devils	-
28 - 2018-01-05	148	Pittsburgh Yellow Jackets	-	Cincinnati Clippers	-
30 - 2018-01-07	156	Binghamton Roadrunners	-	Pittsburgh Yellow Jackets	-
33 - 2018-01-10	168	Pittsburgh Yellow Jackets	-	Providence Englishmen	-
35 - 2018-01-12	183	Pittsburgh Yellow Jackets	-	Virginia Mariners	-
36 - 2018-01-13	188	Philadelphia Patriots	-	Pittsburgh Yellow Jackets	-
39 - 2018-01-16	206	Pittsburgh Yellow Jackets	-	Toronto Royals	-
40 - 2018-01-17	212	Montreal Voyageurs	-	Pittsburgh Yellow Jackets	-
45 - 2018-01-22	237	Cincinnati Clippers	-	Pittsburgh Yellow Jackets	-
47 - 2018-01-24	249	Pittsburgh Yellow Jackets	-	Buffalo Wings	-
49 - 2018-01-26	261	Louisville Red Devils	-	Pittsburgh Yellow Jackets	-
51 - 2018-01-28	269	Pittsburgh Yellow Jackets	-	Louisville Red Devils	-
55 - 2018-02-01	290	Buffalo Wings	-	Pittsburgh Yellow Jackets	-
57 - 2018-02-03	299	Pittsburgh Yellow Jackets	-	Brooklyn Dragons	-
59 - 2018-02-05	311	Pittsburgh Yellow Jackets	-	Burlington Cougars	-
61 - 2018-02-07	320	Baltimore Tigers	-	Pittsburgh Yellow Jackets	-
63 - 2018-02-09	333	Pittsburgh Yellow Jackets	-	Quebec Cavaliers	-
65 - 2018-02-11	345	Pittsburgh Yellow Jackets	-	Ottawa Spartans	-
66 - 2018-02-12	350	Brooklyn Dragons	-	Pittsburgh Yellow Jackets	-
69 - 2018-02-15	365	Pittsburgh Yellow Jackets	-	Washington Americans	-
71 - 2018-02-17	377	Cincinnati Clippers	-	Pittsburgh Yellow Jackets	-
74 - 2018-02-20	393	Pittsburgh Yellow Jackets	-	Baltimore Tigers	-
75 - 2018-02-21	401	Rochester Lakers	-	Pittsburgh Yellow Jackets	-
79 - 2018-02-25	427	Rochester Lakers	-	Pittsburgh Yellow Jackets	-
82 - 2018-02-28	439	Pittsburgh Yellow Jackets	-	Rochester Lakers	-
85 - 2018-03-03	456	Albany Indians	-	Pittsburgh Yellow Jackets	-
87 - 2018-03-05	468	Pittsburgh Yellow Jackets	-	Indianapolis Racers	-
89 - 2018-03-07	480	Worcester Plainsmen	-	Pittsburgh Yellow Jackets	-
93 - 2018-03-11	501	Pittsburgh Yellow Jackets	-	Indianapolis Racers	-
94 - 2018-03-12	509	Richmond Robins	-	Pittsburgh Yellow Jackets	-
98 - 2018-03-16	534	Lehigh Valley Rockets	-	Pittsburgh Yellow Jackets	-
99 - 2018-03-17	540	Pittsburgh Yellow Jackets	-	Richmond Robins	-
103 - 2018-03-21	561	Saint John Winterhawks	-	Pittsburgh Yellow Jackets	-
105 - 2018-03-23	570	Pittsburgh Yellow Jackets	-	Boston Eagles	-
109 - 2018-03-27	585	Toronto Royals	-	Pittsburgh Yellow Jackets	-
111 - 2018-03-29	600	Pittsburgh Yellow Jackets	-	Lehigh Valley Rockets	-
112 - 2018-03-30	606	Pittsburgh Yellow Jackets	-	Philadelphia Patriots	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
114 - 2018-04-01	615	Pittsburgh Yellow Jackets	-	Syracuse Bulls	-
115 - 2018-04-02	620	Indianapolis Racers	-	Pittsburgh Yellow Jackets	-
120 - 2018-04-07	646	Washington Americans	-	Pittsburgh Yellow Jackets	-
125 - 2018-04-12	667	Virginia Mariners	-	Pittsburgh Yellow Jackets	-
127 - 2018-04-14	676	Pittsburgh Yellow Jackets	-	Portland Wolves	-
134 - 2018-04-21	702	Toronto Royals	-	Pittsburgh Yellow Jackets	-
141 - 2018-04-28	728	Halifax Kings	-	Pittsburgh Yellow Jackets	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2	Niveau 3	Niveau 4	Luxe
Capacité de l'Aréna	4225	2500	1805	2200	1250
Prix des Billets	95	67	50	35	180
Assistance	9507	5625	4062	4950	2831
Attendance PCT	75.01%	75.00%	75.01%	75.00%	75.49%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
24	8992 - 75.06%	721,990$	2,165,970$	11980	100

Dépenses
Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs	Valeur du Cap Salarial Spécial
15,383,969$	15,383,969$	0$	0$

Dépenses Annuelles à Ce Jour	Cap Salarial Par Jour	Cap salarial à ce jour	Taxe de Luxe Totale
1,776,612$	108,338$	1,776,612$	0$

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
17,327,760$	125	108,338$	13,542,250$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Cap Salarial de la Saison Éstimé	Compte Bancaire Actuel	Compte Bancaire Projeté
15,971,530$	15,318,862$	42,063,134$	43,419,364$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Sam Brauer	AGE:20	PO:76	OV:78
Timothy Jett	AGE:29	PO:44	OV:73
Scot Godek	AGE:21	PO:48	OV:70
Willie Middaugh	AGE:26	PO:33	OV:70
Dean Helmers	AGE:33	PO:41	OV:69
Brett Kerson	AGE:27	PO:14	OV:69
Trevor Mingoia	AGE:25	PO:40	OV:68
Paul Vickers	AGE:19	PO:51	OV:66
Trevor Weilbacher	AGE:22	PO:58	OV:61
Simon Jurek	AGE:19	PO:42	OV:61
Greg Baltzer	AGE:21	PO:62	OV:60
Ben Shibley	AGE:19	PO:63	OV:58

Jeff Clifton	AGE:37	PO:14	OV:77
Avery Lajoie	AGE:19	PO:66	OV:72
Damian Lowrie	AGE:24	PO:25	OV:70
Carey Stecklein	AGE:21	PO:66	OV:69
Roy Sousa	AGE:29	PO:42	OV:69
Cole Langenbach	AGE:26	PO:36	OV:69
Heath Speier	AGE:26	PO:35	OV:69
Nathan Morea	AGE:22	PO:36	OV:66
Richard McMurtry	AGE:21	PO:47	OV:62
Lance Tedford	AGE:25	PO:23	OV:62
Clayton Barrett	AGE:19	PO:65	OV:60

Ralph Valles	AGE:30	PO:42	OV:73
Brent Heneisen	AGE:25	PO:29	OV:68
John Silvis	AGE:26	PO:14	OV:66
Mason Sade	AGE:24	PO:51	OV:65
Edward Zirk	AGE:20	PO:36	OV:62
Michael Billerbeck	AGE:19	PO:58	OV:61
Jared Shoen	AGE:19	PO:63	OV:60
Martin Meldahl	AGE:20	PO:48	OV:59
Trevor Bjelland	AGE:19	PO:45	OV:59
Keith Lewis	AGE:19	PO:41	OV:58

Défense #1

Défense #2

Gardien

Jason Abbruzesse	AGE:36	PO:20	OV:78
Marc Roethler	AGE:26	PO:27	OV:73
Sebastian Boore	AGE:29	PO:12	OV:71
Neil Mabra	AGE:20	PO:47	OV:69
Rick Krause	AGE:24	PO:42	OV:69
Mike Harwood	AGE:34	PO:28	OV:68
Glenn Brantley	AGE:28	PO:23	OV:68
Will Hetrick	AGE:29	PO:20	OV:68
Tyler Wieneke	AGE:27	PO:13	OV:68

Morgan Bruington	AGE:25	PO:44	OV:66
Will Rayner	AGE:27	PO:59	OV:65
Vaughn Weisgerber	AGE:20	PO:52	OV:65
Anton Jenness	AGE:19	PO:53	OV:64
Ellis Mulhall	AGE:20	PO:44	OV:63
Arron Sanghani	AGE:20	PO:49	OV:62
Dylan Zukoski	AGE:27	PO:7	OV:60
Lucas Eichele	AGE:20	PO:50	OV:58

Richard Messer	AGE:33	PO:54	OV:79
Ben Lampitt	AGE:20	PO:75	OV:74
Ray Judd	AGE:30	PO:65	OV:74
Loren McTeer	AGE:25	PO:52	OV:73
Kevin Krach	AGE:22	PO:57	OV:72
Bryce Ludlum	AGE:19	PO:54	OV:72
Todd Belasco	AGE:20	PO:48	OV:72

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
1002	Pit	Pit	Pit	Pit	Pit	Pit	Pit	Pit
1003	Pit	Pit	Pit	Pit	Pit	Pit	Pit	Pit
1004	Pit	Pit	Pit	Pit	Pit	Pit	Pit	Pit
1005	Pit	Pit	Pit	Pit	Pit	Pit	Pit	Pit
1006	Pit	Pit	Pit	Pit	Pit	Pit	Pit	Pit

[12/9/2017 3:18:09 PM] - New Record for Team's Most Hits (38) in 1 Game for Pittsburgh Yellow Jackets!
[12/3/2017 2:18:01 PM] - Kevin Krach resigned with Pittsburgh Yellow Jackets for $264,000 for 3 year(s).
[12/3/2017 2:18:01 PM] - Ray Judd resigned with Pittsburgh Yellow Jackets for $340,000 for 3 year(s).
[12/3/2017 2:18:01 PM] - Nathan Morea resigned with Pittsburgh Yellow Jackets for $387,000 for 3 year(s).
[12/3/2017 2:18:01 PM] - Mason Sade resigned with Pittsburgh Yellow Jackets for $375,000 for 3 year(s).
[12/3/2017 2:18:01 PM] - Heath Speier resigned with Pittsburgh Yellow Jackets for $498,000 for 3 year(s).
[12/3/2017 2:18:01 PM] - Marc Roethler resigned with Pittsburgh Yellow Jackets for $740,000 for 3 year(s).
[12/3/2017 2:18:01 PM] - Willie Middaugh resigned with Pittsburgh Yellow Jackets for $523,000 for 3 year(s).
[12/3/2017 2:18:01 PM] - John Silvis resigned with Pittsburgh Yellow Jackets for $393,000 for 3 year(s).
[12/3/2017 2:18:01 PM] - Dylan Zukoski resigned with Pittsburgh Yellow Jackets for $257,000 for 3 year(s).
[12/3/2017 2:18:01 PM] - Tyler Wieneke resigned with Pittsburgh Yellow Jackets for $446,000 for 3 year(s).
[12/3/2017 2:18:00 PM] - Roy Sousa resigned with Pittsburgh Yellow Jackets for $553,000 for 3 year(s).
[12/3/2017 2:18:00 PM] - Dean Helmers resigned with Pittsburgh Yellow Jackets for $522,000 for 3 year(s).
[12/3/2017 2:18:00 PM] - Lance Tedford resigned with Pittsburgh Yellow Jackets for $278,000 for 3 year(s).
[12/3/2017 2:18:00 PM] - Jason Abbruzesse resigned with Pittsburgh Yellow Jackets for $1,778,000 for 3 year(s).
[12/3/2017 2:18:00 PM] - Mike Harwood resigned with Pittsburgh Yellow Jackets for $510,000 for 3 year(s).
[9/30/2017 4:53:47 PM] - Toby Burkett was released.
[9/30/2017 4:53:47 PM] - Toby Burkett was forced to retire by Pittsburgh Yellow Jackets
[9/4/2017 8:23:36 PM] - Pittsburgh Yellow Jackets was eliminated at round 1 of year 14.
[9/3/2017 1:47:39 PM] - Johnstown Yellow Jackets didn't make playoff for year 14.
[9/3/2017 10:46:06 AM] - Dylan Zukoski signed with Pittsburgh Yellow Jackets for $200,000 for 1 year(s) with $0 in bonus.
[9/3/2017 10:46:06 AM] - Dylan Zukoski was added to Pittsburgh Yellow Jackets.
[9/1/2017 9:01:22 PM] - New Record for Team's Most Shots Blocked (22) in 1 Game for Pittsburgh Yellow Jackets!
[8/8/2017 7:28:53 PM] - TRADE : From Pittsburgh Yellow Jackets to Brooklyn Dragons : Todd Poderis (69).
[8/8/2017 7:28:53 PM] - TRADE : From Brooklyn Dragons to Pittsburgh Yellow Jackets : John Silvis (66), Willie Middaugh (70).
[8/8/2017 7:28:52 PM] - Willie Middaugh was added to Pittsburgh Yellow Jackets.
[8/8/2017 7:28:52 PM] - John Silvis was added to Pittsburgh Yellow Jackets.
[7/28/2017 10:06:22 PM] - TRADE : From Syracuse Bulls to Pittsburgh Yellow Jackets : Ellis Mulhall (63), Richard McMurtry (62).
[7/28/2017 10:06:22 PM] - TRADE : From Pittsburgh Yellow Jackets to Syracuse Bulls : Joel Eatman (65), Greg Brown (63).
[7/28/2017 10:06:21 PM] - Richard McMurtry was added to Pittsburgh Yellow Jackets.
[7/28/2017 10:06:21 PM] - Ellis Mulhall was added to Pittsburgh Yellow Jackets.
[7/10/2017 8:23:23 PM] - New Record for Team's Most Hits (36) in 1 Game for Pittsburgh Yellow Jackets!

[1/4/2018 5:21:01 PM] Johnstown Yellow Jackets lines for next game are empty. Current rosters/lines are not erased.
[1/4/2018 5:20:59 PM] Game 86 - Morgan Bruington from Johnstown Yellow Jackets is injured (Fractured Orbital Bone) and is out for 2 weeks.
[1/4/2018 5:20:58 PM] Auto Lines Function has been run for Johnstown Yellow Jackets.
[1/4/2018 5:20:58 PM] Auto Roster Farm Only Function has been run for Pittsburgh Yellow Jackets.
[1/4/2018 5:20:55 PM] Timothy Jett from Pittsburgh Yellow Jackets is back from Strained Groin Injury.
[1/4/2018 5:20:55 PM] Both Pittsburgh Yellow Jackets and Johnstown Yellow Jackets lines for next game are empty. Current rosters/lines are not erased.
[1/4/2018 5:20:54 PM] Game 76 - Mike Harwood from Johnstown Yellow Jackets is injured (Right Foot) and is out for 1 week.
[1/4/2018 5:20:45 PM] Auto Lines Function has been run for Johnstown Yellow Jackets.
[1/4/2018 5:20:45 PM] Auto Lines Function has been run for Pittsburgh Yellow Jackets.
[1/4/2018 5:20:41 PM] Auto Roster Function has been run for Pittsburgh Yellow Jackets.
[1/4/2018 5:20:41 PM] Willie Middaugh of Pittsburgh Yellow Jackets was sent to farm.
[1/4/2018 5:20:41 PM] Heath Speier of Pittsburgh Yellow Jackets was sent to farm.
[1/4/2018 5:20:41 PM] Damian Lowrie of Pittsburgh Yellow Jackets was sent to farm.
[1/4/2018 5:20:41 PM] Brett Kerson of Pittsburgh Yellow Jackets was sent to farm.
[1/4/2018 5:20:41 PM] Dean Helmers of Pittsburgh Yellow Jackets was sent to pro.
[1/4/2018 5:20:41 PM] Roy Sousa of Pittsburgh Yellow Jackets was sent to pro.
[1/4/2018 5:20:41 PM] Carey Stecklein of Pittsburgh Yellow Jackets was sent to pro.
[12/9/2017 3:18:44 PM] Marc Roethler from Pittsburgh Yellow Jackets is back from Exhaustion.
[12/9/2017 3:18:41 PM] Pittsburgh Yellow Jackets lines for next game are empty. Current rosters/lines are not erased.
[12/9/2017 3:18:38 PM] Marc Roethler from Pittsburgh Yellow Jackets is injured from Exhaustion.
[12/9/2017 3:18:35 PM] John Silvis from Pittsburgh Yellow Jackets is back from Left Hip Injury.
[12/9/2017 3:18:35 PM] Both Pittsburgh Yellow Jackets and Johnstown Yellow Jackets lines for next game are empty. Current rosters/lines are not erased.
[12/9/2017 3:18:32 PM] Game 50 - John Silvis from Pittsburgh Yellow Jackets is injured (Left Hip) and is out for 5 days.
[12/9/2017 3:18:28 PM] Pittsburgh Yellow Jackets lines for next game are empty. Current rosters/lines are not erased.
[12/9/2017 3:18:24 PM] Auto Lines Function has been run for Pittsburgh Yellow Jackets.
[12/9/2017 3:18:24 PM] Auto Roster Partial Function has been run for Pittsburgh Yellow Jackets.
[12/9/2017 3:18:24 PM] Johnstown Yellow Jackets lines for next game are empty. Current rosters/lines are not erased.
[12/9/2017 3:18:20 PM] Johnstown Yellow Jackets lines for next game are empty. Current rosters/lines are not erased.
[12/9/2017 3:18:17 PM] Marc Roethler from Pittsburgh Yellow Jackets is back from Exhaustion.
[12/9/2017 3:18:15 PM] Pittsburgh Yellow Jackets lines for next game are empty. Current rosters/lines are not erased.
[12/9/2017 3:18:14 PM] Marc Roethler from Pittsburgh Yellow Jackets is injured from Exhaustion.
[12/9/2017 3:18:13 PM] Johnstown Yellow Jackets lines for next game are empty. Current rosters/lines are not erased.
[12/9/2017 3:18:09 PM] Pittsburgh Yellow Jackets lines for next game are empty. Current rosters/lines are not erased.
[12/9/2017 3:18:09 PM] New Record for Team's Most Hits (38) in 1 Game for Pittsburgh Yellow Jackets!
[12/9/2017 3:18:05 PM] Pittsburgh Yellow Jackets lines for next game are empty. Current rosters/lines are not erased.
[12/9/2017 3:17:48 PM] Auto Lines Function has been run for Johnstown Yellow Jackets.
[12/9/2017 3:17:48 PM] Auto Lines Function has been run for Pittsburgh Yellow Jackets.
[12/9/2017 3:17:44 PM] Auto Roster Function has been run for Pittsburgh Yellow Jackets.
[12/9/2017 3:17:44 PM] Ben Lampitt of Pittsburgh Yellow Jackets was sent to farm.
[12/9/2017 3:17:44 PM] Ray Judd of Pittsburgh Yellow Jackets was sent to pro.
[12/9/2017 3:17:44 PM] Roy Sousa of Pittsburgh Yellow Jackets was sent to farm.
[12/9/2017 3:17:44 PM] Dean Helmers of Pittsburgh Yellow Jackets was sent to farm.
[12/9/2017 3:17:44 PM] Carey Stecklein of Pittsburgh Yellow Jackets was sent to farm.
[12/9/2017 3:17:44 PM] Brett Kerson of Pittsburgh Yellow Jackets was sent to pro.
[12/9/2017 3:17:44 PM] Heath Speier of Pittsburgh Yellow Jackets was sent to pro.
[12/9/2017 3:17:44 PM] Damian Lowrie of Pittsburgh Yellow Jackets was sent to pro.

Mike Harwood est dehors pour 1 jours à cause de Right Foot Injury.
Morgan Bruington est dehors pour 1 semaine à cause de Fractured Orbital Bone Injury.

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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
Saison Régulière
15-16	80	32	33	10	2	3	0	0	288	275	13	40	21	12	4	1	2	0	0	171	139	32	40	11	21	6	1	1	0	0	117	136	-19	74	288	484	772	2	1	83	97	106	2	2577	919	859	777	22	2678	875	751	1723	383	69	18.02%	322	66	79.50%	6	1004	2046	49.07%	952	2017	47.20%	577	1240	46.53%	1677	902	1732	763	1451	743
16-17	80	32	30	15	3	0	0	0	251	240	11	40	16	13	10	1	0	0	0	122	114	8	40	16	17	5	2	0	0	0	129	126	3	79	251	415	666	1	2	100	82	66	3	2446	902	756	771	17	2445	828	618	1667	367	62	16.89%	233	45	80.69%	5	1082	1986	54.48%	1014	1943	52.19%	634	1172	54.10%	1743	984	1700	739	1437	749
1001	7	1	3	3	0	0	0	0	19	22	-3	3	0	2	1	0	0	0	0	8	11	-3	4	1	1	2	0	0	0	0	11	11	0	5	19	32	51	0	0	8	4	7	0	194	71	58	57	8	251	82	88	173	29	1	3.45%	34	7	79.41%	2	87	167	52.10%	108	220	49.09%	54	95	56.84%	151	82	156	66	127	64
Total Saison Régulière	167	65	66	28	5	3	0	0	558	537	21	83	37	27	15	2	2	0	0	301	264	37	84	28	39	13	3	1	0	0	257	273	-16	158	558	931	1489	3	3	191	183	179	5	5217	1892	1673	1605	47	5374	1785	1457	3563	779	132	16.94%	589	118	79.97%	13	2173	4199	51.75%	2074	4180	49.62%	1265	2507	50.46%	3573	1970	3588	1570	3016	1556