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Statistiques de l'Équipe de Carrière

Centre de jeu
	Pittsburgh Pollen Jocks 6-7-0, 18pts	2	Sommaire du match	3	Alberta Riggers 8-2-0, 24pts

Team Stats
OTL2	Séquence	W6
5-2-0	Fiche domicile	5-0-0
1-5-0	Fiche visiteur	3-2-0
4-4-2	Derniers 10 matchs	8-2-0
2.77	Buts par match	2.80
2.85	Buts contre par match	2.20
14.49%	Pourcentage en avantage numérique	15.91%
76.00%	Pourcentage en désavantage numérique	90.38%

Alberta Riggers
8-2-0, 24pts

Sommaire du match

Pittsburgh Pollen Jocks
6-7-0, 18pts

Team Stats
W6	Séquence	OTL2
5-0-0	Fiche domicile	5-2-0
3-2-0	Fiche visiteur	1-5-0
8-2-0	Derniers 10 matchs	4-4-2
2.80	Buts par match	2.77
2.20	Buts contre par match	2.85
15.91%	Pourcentage en avantage numérique	14.49%
90.38%	Pourcentage en désavantage numérique	76.00%

Meneurs d'équipe
Buts Xhekajs middletoe 8			Passes Bobby Voss 12

Points Bobby Voss 17			Plus/Moins Andrew Brochacho 7

Victoires Diego Adam 6			Pourcentage d’arrêts Diego Adam 0.921

Statistiques d’équipe
Buts pour 36 2.77 GFG	Tirs pour 525 40.38 Avg	Pourcentage en avantage numérique 14.5% 10 GF	Début de zone offensive 43.6%
Buts contre 37 2.85 GAA	Tirs contre 469 36.08 Avg	Pourcentage en désavantage numérique 76.0%% 12 GA	Début de la zone défensive 40.8%

Informations de l'équipe
	Directeur général	Kermit
	Division	Blue
	Conférence	East
	Capitaine
	Assistant #1
	Assistant #2
Informations de l’aréna
	Nom
	Capacité	18,000
	Assistance	0
	Billets de saison	7,200
Informations de la formation
	Équipe Pro	20
	Équipe Mineure	0
	Limite Contrat	20 / 250
	Espoirs	0
Finance
	Revenu annuel à ce jour	0$
	Dépenses annuelles à ce jour	0$
	Revenus de la saison estimés	0$
	Dépenses de la saison estimées	0$
	Compte bancaire actuel	0$
	Compte bancaire projeté	0$

Afficher ou masquer des colonnes

Astuces sur les filtres (anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du joueur	#	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP	Âge	Contrat	Salaire
1	Pelayo Bolivar	0	X				100.00	50	40	40	93	99	99	99	93	83	70	91	90	83	99	90	50	40	81	0	21	3	0$
2	Oppai Bumu	0		X			100.00	47	40	40	93	97	99	99	95	69	69	90	91	80	73	43	50	40	78	0	26	3	0$
3	Xhekajs middletoe	0			X		100.00	51	40	40	88	99	99	99	88	78	69	90	90	80	96	40	50	40	77	0	18	3	0$
4	Kyle Kyleson	0	X				100.00	40	40	50	89	99	99	99	94	82	63	82	87	75	40	46	50	40	74	0	24	3	0$
5	Andrew Brochacho (R)	0		X			100.00	40	40	40	64	67	99	99	78	40	61	67	76	40	46	40	50	40	64	0	17	3	0$
6	Chad Mashpots (R)	0	X				100.00	40	40	40	52	51	99	99	45	45	61	61	62	40	40	40	50	40	55	0	19	3	0$
7	B-TM1 LW1	0		X			100.00	40	40	40	40	40	99	99	40	40	40	40	40	40	40	40	50	40	45	0	26	1	0$
8	B-TM1 LW2	0		X			100.00	40	40	40	40	40	99	99	40	40	40	40	40	40	40	40	50	40	45	0	26	1	0$
9	B-TM1 RW1	0			X		100.00	40	40	40	40	40	99	99	40	40	40	40	40	40	40	40	50	40	45	0	26	1	0$
10	B-TM1 RW2	0			X		100.00	40	40	40	40	40	99	99	40	40	40	40	40	40	40	40	50	40	45	0	26	1	0$
11	B-TM1 LW3	0		X			100.00	40	40	40	40	40	99	99	40	40	40	40	40	40	40	40	50	40	45	0	26	1	0$
12	B-TM1 RW3	0			X		100.00	40	40	40	40	40	99	99	40	40	40	40	40	40	40	40	50	40	45	0	26	1	0$
13	Rudy Howitzer	0				X	100.00	56	40	40	88	80	99	99	88	40	65	84	90	76	56	40	50	40	75	0	16	3	0$
14	Hugh Neutron	0				X	100.00	40	40	47	83	73	99	99	86	40	65	78	84	67	99	44	50	40	73	0	30	3	0$
15	Bobby Voss	0				X	100.00	40	40	40	73	79	99	99	88	40	66	85	87	77	53	40	50	40	71	0	17	3	0$
16	Yo Gurt	0				X	100.00	40	40	40	70	74	99	99	85	40	69	79	80	76	49	40	50	40	68	0	21	3	0$
17	B-TM1 D1	0				X	100.00	40	40	40	40	40	99	99	40	40	40	40	40	40	40	40	50	40	47	0	26	1	0$
18	B-TM1 D2	0				X	100.00	40	40	40	40	40	99	99	40	40	40	40	40	40	40	40	50	40	47	0	26	1	0$
Rayé

	MOYENNE D’ÉQUIPE						100.00	42	40	41	62	63	99	99	64	49	54	63	64	56	54	44	50	40	60

Afficher ou masquer des colonnes

Astuces sur les filtres (anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du gardien	#	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP	Âge	Contrat	Salaire
1	Diego Adam	0	100.00	99	99	99	99	96	99	99	99	99	35	35	72	40	50	40	85	0	26	3	0$
2	Brian S	0	100.00	81	99	99	82	84	92	90	94	95	35	48	43	45	50	40	78	0	24	3	0$
Rayé

	MOYENNE D’ÉQUIPE		100.00	90	99	99	91	90	96	95	97	97	35	42	58	43	50	40	82

Nom de l’entraîneur	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire

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	PKS	PKM	GW	GT	FO%	FOT	EG	HT	P/20	FL	S1	S2	S3
1	Bobby Voss	Pittsburgh Pollen Jocks	D	13	5	12	17	7	12	0	18	20	57	15	34	8.77%	33	383	29.47	3	3	6	33	55	0	41	2	0	0%	0	0	0	0.89	0	1	2	0
2	Xhekajs middletoe	Pittsburgh Pollen Jocks	RW	13	8	6	14	6	23	5	29	71	97	27	71	8.25%	12	358	27.55	0	1	1	13	56	4	37	0	0	56.80%	456	0	0	0.78	1	1	0	2
3	Kyle Kyleson	Pittsburgh Pollen Jocks	C	13	2	10	12	-5	4	0	6	19	64	18	59	3.13%	1	308	23.75	1	6	7	23	55	1	37	0	0	55.22%	134	0	0	0.78	0	0	0	0
4	Yo Gurt	Pittsburgh Pollen Jocks	D	13	1	11	12	7	20	0	17	11	44	9	23	2.27%	29	348	26.78	1	1	2	23	55	1	31	0	0	0%	0	0	0	0.69	0	0	1	1
5	Rudy Howitzer	Pittsburgh Pollen Jocks	D	13	1	9	10	-4	26	0	39	22	35	12	30	2.86%	26	400	30.77	1	0	1	21	56	2	33	0	0	0%	0	0	0	0.50	0	0	1	0
6	Pelayo Bolivar	Pittsburgh Pollen Jocks	C	13	7	3	10	-5	13	5	39	55	95	16	64	7.37%	2	400	30.83	0	2	2	13	56	3	37	1	1	60.57%	634	0	1	0.50	1	2	0	0
7	Andrew Brochacho	Pittsburgh Pollen Jocks	LW	13	6	2	8	7	6	0	14	12	31	6	13	19.35%	1	317	24.44	2	1	3	8	55	0	2	1	0	24.14%	29	1	0	0.50	0	1	1	2
8	Oppai Bumu	Pittsburgh Pollen Jocks	LW	13	4	3	7	-5	2	0	17	25	71	18	61	5.63%	7	310	23.85	0	2	2	14	56	7	41	2	1	48.00%	25	0	0	0.45	0	0	0	1
9	Hugh Neutron	Pittsburgh Pollen Jocks	D	13	2	5	7	-5	2	0	7	20	23	3	17	8.70%	19	399	30.77	2	1	3	8	56	0	45	0	0	0%	0	0	0	0.35	0	0	0	1
10	Chad Mashpots	Pittsburgh Pollen Jocks	C	13	0	1	1	7	4	0	16	7	4	5	5	0%	2	335	25.80	0	0	0	0	55	0	8	0	0	26.42%	53	0	0	0.06	0	0	0	0
11	B-TM1 RW3	Pittsburgh Pollen Jocks	RW	13	0	1	1	0	4	0	4	1	1	0	2	0%	0	119	9.16	0	0	0	0	0	0	0	0	0	40.00%	10	0	0	0.17	0	0	0	0
12	B-TM1 D1	Pittsburgh Pollen Jocks	D	13	0	0	0	-1	0	0	1	0	0	0	0	0%	1	10	0.83	0	0	0	0	0	0	0	0	0	0%	1	0	0	0	0	0	0	0
13	B-TM1 D2	Pittsburgh Pollen Jocks	D	13	0	0	0	-2	0	0	6	0	0	0	3	0%	4	45	3.50	0	0	0	0	1	0	12	0	0	0%	0	0	0	0	0	0	0	0
14	B-TM1 LW1	Pittsburgh Pollen Jocks	LW	13	0	0	0	0	8	0	3	2	2	3	4	0%	0	120	9.28	0	0	0	0	0	0	0	0	0	50.00%	6	0	0	0	0	0	0	0
15	B-TM1 LW2	Pittsburgh Pollen Jocks	LW	13	0	0	0	-1	0	0	0	1	1	0	0	0%	0	3	0.27	0	0	0	0	0	0	0	0	0	0%	0	0	0	0	0	0	0	0
16	B-TM1 RW1	Pittsburgh Pollen Jocks	RW	13	0	0	0	-1	0	0	0	0	0	0	0	0%	0	6	0.51	0	0	0	0	2	0	0	0	0	0%	1	0	0	0	0	0	0	0
17	B-TM1 RW2	Pittsburgh Pollen Jocks	RW	13	0	0	0	0	0	0	0	0	0	0	0	0%	0	0	0.05	0	0	0	0	0	0	0	0	0	0%	0	0	0	0	0	0	0	0
Statistiques d’équipe totales ou en moyenne				221	36	63	99	5	124	10	216	266	525	132	386	6.86%	137	3868	17.51	10	17	27	156	564	18	328	6	2	56.12%	1349	1	1	0.51	2	5	5	7

Afficher ou masquer des colonnes

Astuces sur les filtres (anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du gardien	Nom de l’équipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Diego Adam	Pittsburgh Pollen Jocks	13	6	5	2	0.921	2.81	791	0	1	37	469	0	0	0	0	0	13	0	1	1	0
Statistiques d’équipe totales ou en moyenne			13	6	5	2	0.921	2.81	791	0	1	37	469	0	0	0		0	13	0	1	1	0

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	Pays	Recrue	Poids	Taille	Non-échange	Disponible pour échange	Acquis Par	Ballotage forcé	Waiver Possible	Contrat	Date du Signature du Contrat	Forcer UFA	Rappel d'urgence	Type	Plafond salarial	Plafond salarial restant	Exclus du plafond salarial	Salaire année 2	Salaire année 3	Salaire année 4	Salaire année 5	Salaire année 6	Salaire année 7	Salaire année 8	Salaire année 9	Salaire année 10	Plafond salarial année 2	Plafond salarial année 3	Plafond salarial année 4	Plafond salarial année 5	Plafond salarial année 6	Plafond salarial année 7	Plafond salarial année 8	Plafond salarial année 9	Plafond salarial année 10	Non-échange année 2	Non-échange année 3	Non-échange année 4	Non-échange année 5	Non-échange année 6	Non-échange année 7	Non-échange année 8	Non-échange année 9	Non-échange année 10	Lien
Andrew Brochacho	Pittsburgh Pollen Jocks	LW	17	2009-07-16	ISL	Yes	210 Lbs	6 ft2	No	No	Assign Manually	No	No	3	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Lien
B-TM1 D1	Pittsburgh Pollen Jocks	D	26	2000-01-01	VHL	No	185 Lbs	6 ft1	No	No	Assign Manually	No	No	1	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
B-TM1 D2	Pittsburgh Pollen Jocks	D	26	2000-01-01	VHL	No	185 Lbs	6 ft1	No	No	Assign Manually	No	No	1	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
B-TM1 LW1	Pittsburgh Pollen Jocks	LW	26	2000-01-01	VHL	No	185 Lbs	6 ft1	No	No	Assign Manually	No	No	1	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
B-TM1 LW2	Pittsburgh Pollen Jocks	LW	26	2000-01-01	VHL	No	185 Lbs	6 ft1	No	No	Assign Manually	No	No	1	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
B-TM1 LW3	Pittsburgh Pollen Jocks	LW	26	2000-01-01	VHL	No	185 Lbs	6 ft1	No	No	Assign Manually	No	No	1	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
B-TM1 RW1	Pittsburgh Pollen Jocks	RW	26	2000-01-01	VHL	No	185 Lbs	6 ft1	No	No	Assign Manually	No	No	1	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
B-TM1 RW2	Pittsburgh Pollen Jocks	RW	26	2000-01-01	VHL	No	185 Lbs	6 ft1	No	No	Assign Manually	No	No	1	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
B-TM1 RW3	Pittsburgh Pollen Jocks	RW	26	2000-01-01	VHL	No	185 Lbs	6 ft1	No	No	Assign Manually	No	No	1	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
Bobby Voss	Pittsburgh Pollen Jocks	D	17	2009-07-16	USA	No	185 Lbs	6 ft2	No	No	Assign Manually	No	No	3	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Lien
Brian S	Pittsburgh Pollen Jocks	G	24	2002-07-16	JEY	No	245 Lbs	6 ft8	No	No	Assign Manually	No	No	3	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Lien
Chad Mashpots	Pittsburgh Pollen Jocks	C	19	2007-07-16	USA	Yes	210 Lbs	6 ft3	No	No	Assign Manually	No	No	3	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Lien
Diego Adam	Pittsburgh Pollen Jocks	G	26	2000-07-16	CAN	No	225 Lbs	6 ft4	No	No	Assign Manually	No	No	3	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Lien
Hugh Neutron	Pittsburgh Pollen Jocks	D	30	1996-07-16	USA	No	150 Lbs	6 ft1	No	No	Assign Manually	No	No	3	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Lien
Kyle Kyleson	Pittsburgh Pollen Jocks	C	24	2002-07-16	HMD	No	220 Lbs	6 ft3	No	No	Assign Manually	No	No	3	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Lien
Oppai Bumu	Pittsburgh Pollen Jocks	LW	26	2000-07-16	JPN	No	210 Lbs	6 ft5	No	No	Assign Manually	No	No	3	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Lien
Pelayo Bolivar	Pittsburgh Pollen Jocks	C	21	2005-07-16	ESP	No	200 Lbs	6 ft0	No	No	Assign Manually	No	No	3	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Lien
Rudy Howitzer	Pittsburgh Pollen Jocks	D	16	2010-07-16	CAN	No	210 Lbs	6 ft4	No	No	Assign Manually	No	No	3	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Lien
Xhekajs middletoe	Pittsburgh Pollen Jocks	RW	18	2008-07-16	TUV	No	160 Lbs	6 ft0	No	No	Assign Manually	No	No	3	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Lien
Yo Gurt	Pittsburgh Pollen Jocks	D	21	2005-07-16	UMI	No	169 Lbs	5 ft9	No	No	Assign Manually	No	No	3	2026-09-07	False	False	Pro & Farm	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Lien

Nombre de joueurs	Âge moyen	Poids moyen	Taille moyenne	Contrat moyen	Salaire moyen 1e année
20	23.35	194 Lbs	6 ft2	2.20	0$

Somme salaire 1e année	Somme salaire 2e année	Somme salaire 3e année	Somme salaire 4e année	Somme salaire 5e année
0$	0$	0$	0$	0$

Attaque à 5 contre 5
Ligne #	Ailier gauche	Centre	Ailier droit	% temps	PHY	DF	OF
1	Oppai Bumu	Pelayo Bolivar	Kyle Kyleson	40	0	1	4
2	Andrew Brochacho	Xhekajs middletoe	Chad Mashpots	40	0	1	4
3	Kyle Kyleson	Pelayo Bolivar	Oppai Bumu	20	0	0	5
4	B-TM1 LW1	Pelayo Bolivar	B-TM1 RW3	0	0	3	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% temps	PHY	DF	OF
1	Rudy Howitzer	Hugh Neutron	40	0	1	4
2	Bobby Voss	Yo Gurt	40	0	1	4
3	Bobby Voss	Rudy Howitzer	20	0	1	4
4	Rudy Howitzer	Hugh Neutron	0	1	2	2

Attaque en avantage numérique
Ligne #	Ailier gauche	Centre	Ailier droit	% temps	PHY	DF	OF
1	Oppai Bumu	Pelayo Bolivar	Xhekajs middletoe	80	0	0	5
2	Andrew Brochacho	Kyle Kyleson	Chad Mashpots	20	0	0	5

Défense en avantage numérique
Ligne #	Défense	Défense	% temps	PHY	DF	OF
1	Rudy Howitzer	Hugh Neutron	80	0	0	5
2	Bobby Voss	Yo Gurt	20	0	0	5

Attaque à 4 en désavantage numérique
Ligne #	Centre	Ailier	% temps	PHY	DF	OF
1	Pelayo Bolivar	Oppai Bumu	60	0	5	0
2	Xhekajs middletoe	Kyle Kyleson	40	0	5	0

Défense à 4 en désavantage numérique
Ligne #	Défense	Défense	% temps	PHY	DF	OF
1	Rudy Howitzer	Hugh Neutron	60	0	5	0
2	Bobby Voss	Yo Gurt	40	0	5	0

3 joueurs en désavantage numérique
Ligne #	Ailier	% temps	PHY	DF	OF	Défense	Défense	% temps	PHY	DF	OF
1	Pelayo Bolivar	60	0	5	0	Rudy Howitzer	Hugh Neutron	60	0	5	0
2	Oppai Bumu	40	0	5	0	Bobby Voss	Yo Gurt	40	0	5	0

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% temps	PHY	DF	OF
1	Pelayo Bolivar	Oppai Bumu	60	0	2	3
2	Xhekajs middletoe	Kyle Kyleson	40	0	2	3

Défense à 4 contre 4
Ligne #	Défense	Défense	% temps	PHY	DF	OF
1	Rudy Howitzer	Hugh Neutron	60	0	2	3
2	Bobby Voss	Yo Gurt	40	0	2	3

Attaque dernière minute
Ailier gauche	Centre	Ailier droit	Défense	Défense
Oppai Bumu	Pelayo Bolivar	Xhekajs middletoe	Rudy Howitzer	Hugh Neutron

Défense dernière minute
Ailier gauche	Centre	Ailier droit	Défense	Défense
Oppai Bumu	Pelayo Bolivar	Xhekajs middletoe	Rudy Howitzer	Hugh Neutron

Attaquants supplémentaires
Normal	Avantage numérique	Désavantage numérique
Xhekajs middletoe, Chad Mashpots, Oppai Bumu	Andrew Brochacho, Chad Mashpots	Pelayo Bolivar

Défenseurs supplémentaires
Normal	Avantage numérique	Désavantage numérique
Hugh Neutron, Rudy Howitzer, Bobby Voss	B-TM1 D2	Yo Gurt, Rudy Howitzer

Tirs de pénalité
Pelayo Bolivar, Oppai Bumu, Xhekajs middletoe, Kyle Kyleson, Andrew Brochacho

Gardien
#1 : Diego Adam, #2 : Brian S

Lignes d’attaque personnalisées en prolongation
Pelayo Bolivar, Oppai Bumu, Xhekajs middletoe, Kyle Kyleson, Andrew Brochacho, Chad Mashpots, B-TM1 RW1, B-TM1 LW2, B-TM1 LW1, B-TM1 LW3

Lignes de défense personnalisées en prolongation
Rudy Howitzer, Hugh Neutron, Bobby Voss, Yo Gurt, B-TM1 D2

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

	Total												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	RI
1	Alberta Riggers	6	2	4	0	0	0	0	0	15	16	-1	3	2	1	0	0	0	0	0	10	6	4	3	0	3	0	0	0	0	0	5	10	-5	6	0.333	15	26	41	0	1	3	7	5	0	205	58	76	64	7	223	69	68	91	35	4	11.43%	28	6	78.57%	0	335	588	56.97%	308	550	56.00%	114	211	54.03%	144	99	150	46	78	38
2	Vancouver Vandals	7	4	3	0	0	0	0	0	21	21	0	4	3	1	0	0	0	0	0	15	13	2	3	1	2	0	0	0	0	0	6	8	-2	12	0.571	21	37	58	0	0	9	6	6	0	320	113	95	112	0	246	68	56	125	34	6	17.65%	22	6	72.73%	0	335	588	56.97%	308	550	56.00%	114	211	54.03%	176	126	151	50	91	46
	Total	13	6	7	0	0	0	0	0	36	37	-1	7	5	2	0	0	0	0	0	25	19	6	6	1	5	0	0	0	0	0	11	18	-7	18	0.462	36	63	99	0	1	12	13	11	0	525	171	171	176	7	469	137	124	216	69	10	14.49%	50	12	76.00%	0	335	588	56.97%	308	550	56.00%	114	211	54.03%	321	226	301	97	170	85
	_Since Last GM Reset	13	6	7	0	0	0	0	0	36	37	-1	7	5	2	0	0	0	0	0	25	19	6	6	1	5	0	0	0	0	0	11	18	-7	18	0.462	36	63	99	0	1	12	13	11	0	525	171	171	176	7	469	137	124	216	69	10	14.49%	50	12	76.00%	0	335	588	56.97%	308	550	56.00%	114	211	54.03%	321	226	301	97	170	85
	_Vs Conference	13	6	7	0	0	0	0	0	36	37	-1	7	5	2	0	0	0	0	0	25	19	6	6	1	5	0	0	0	0	0	11	18	-7	18	0.462	36	63	99	0	1	12	13	11	0	525	171	171	176	7	469	137	124	216	69	10	14.49%	50	12	76.00%	0	335	588	56.97%	308	550	56.00%	114	211	54.03%	321	226	301	97	170	85
	_Vs Division	13	6	7	0	0	0	0	0	36	37	-1	7	5	2	0	0	0	0	0	25	19	6	6	1	5	0	0	0	0	0	11	18	-7	18	0.462	36	63	99	0	1	12	13	11	0	525	171	171	176	7	469	137	124	216	69	10	14.49%	50	12	76.00%	0	335	588	56.97%	308	550	56.00%	114	211	54.03%	321	226	301	97	170	85

			Total pour les joueurs
Matchs joués	Points	Séquence	Buts	Passes	Points	Tirs pour	Tirs contre	Tirs bloqués	Minutes de pénalités	Mises en échec	Buts en filet désert	Blanchissages
13	18	OTL2	36	63	99	525	469	137	124	216	0	1

Tous les matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
13	6	7	0	0	0	0	36	37

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
7	5	2	0	0	0	0	25	19

Matchs extérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
6	1	5	0	0	0	0	11	18

Derniers 10 matchs
W	L	OTW	OTL	SOW	SOL
4	4	0	2	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
69	10	14.49%	50	12	76.00%	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
171	171	176	7	12	13	11	0

Mises en jeu
Gagnées en zone offensive	Total en zone offensive	% gagnées en zone offensive	Gagnées en zone défensive	Total en zone défensive	% gagnées en zone défensive	Gagnées en zone neutre	Total en zone neutre	% gagnées en zone neutre
335	588	56.97%	308	550	56.00%	114	211	54.03%

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
321	226	301	97	170	85

Derniers matchs 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	Lien
1	2	Vancouver Vandals	4	Pittsburgh Pollen Jocks	5	W		Sommaire du match
3	6	Vancouver Vandals	2	Pittsburgh Pollen Jocks	3	W		Sommaire du match
5	10	Pittsburgh Pollen Jocks	2	Vancouver Vandals	5	L		Sommaire du match
7	14	Pittsburgh Pollen Jocks	0	Vancouver Vandals	1	L		Sommaire du match
9	18	Vancouver Vandals	4	Pittsburgh Pollen Jocks	3	L		Sommaire du match
11	22	Pittsburgh Pollen Jocks	4	Vancouver Vandals	2	W		Sommaire du match
13	26	Vancouver Vandals	3	Pittsburgh Pollen Jocks	4	W		Sommaire du match
15	29	Pittsburgh Pollen Jocks	1	Alberta Riggers	3	L		Sommaire du match
17	31	Pittsburgh Pollen Jocks	2	Alberta Riggers	4	L		Sommaire du match
19	33	Alberta Riggers	3	Pittsburgh Pollen Jocks	6	W		Sommaire du match
21	35	Alberta Riggers	0	Pittsburgh Pollen Jocks	2	W		Sommaire du match
23	37	Pittsburgh Pollen Jocks	2	Alberta Riggers	3	L	X	Sommaire du match
25	39	Alberta Riggers	3	Pittsburgh Pollen Jocks	2	L	X	Sommaire du match

Capacité de l’aréna - Tendance du prix des billets - %
	Niveau 1	Niveau 2	Niveau 3	Niveau 4	Luxe
Capacité	6000	5000	2000	4000	1000
Prix des billets	100	60	35	25	200
Assistance	0	0	0	0	0
Attendance PCT	0.00%	0.00%	0.00%	0.00%	0.00%

Revenu
Matchs à domicile restants	Assistance moyenne - %	Revenu moyen par match	Revenu annuel à ce jour	Capacité de l’aréna	Popularité de l’équipe
8	0 - 0.00%	0$	0$	18000	100

Dépenses
Dépenses annuelles à ce jour	Salaire total des joueurs	Plafond Salariale total des joueurs	Salaire des entraineurs	Valeur du plafond salarial spécial
0$	0$	0$	0$	0$

Plafond salarial par jour	Plafond salarial à ce jour	Taxe de luxe totale	Joueurs Inclus dans le plafond salarial	Joueurs exclut du plafond Salarial
0$	0$	0$	0	0

Estimation
Revenus de la saison estimés	Jours restants de la saison	Dépenses par jour	Dépenses de la saison estimées
0$	0	0$	0$

Total de l’équipe estimé
Dépenses de la saison estimées	Compte bancaire actuel	Compte bancaire projeté
0$	0$	0$

Charte de profondeur

Ailier gauche

Centre

Ailier droit

Oppai Bumu	AGE:26	PO:50	OV:78
Andrew Brochacho (R)	AGE:17	PO:50	OV:64
B-TM1 LW1	AGE:26	PO:50	OV:45
B-TM1 LW2	AGE:26	PO:50	OV:45
B-TM1 LW3	AGE:26	PO:50	OV:45

Pelayo Bolivar	AGE:21	PO:50	OV:81
Kyle Kyleson	AGE:24	PO:50	OV:74
Chad Mashpots (R)	AGE:19	PO:50	OV:55

Xhekajs middletoe	AGE:18	PO:50	OV:77
B-TM1 RW1	AGE:26	PO:50	OV:45
B-TM1 RW2	AGE:26	PO:50	OV:45
B-TM1 RW3	AGE:26	PO:50	OV:45

Défense #1

Défense #2

Gardien

Rudy Howitzer	AGE:16	PO:50	OV:75
Hugh Neutron	AGE:30	PO:50	OV:73
Bobby Voss	AGE:17	PO:50	OV:71

Yo Gurt	AGE:21	PO:50	OV:68
B-TM1 D1	AGE:26	PO:50	OV:47
B-TM1 D2	AGE:26	PO:50	OV:47

Diego Adam	AGE:26	PO:50	OV:85
Brian S	AGE:24	PO:50	OV:78

Espoirs

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

Espoir	Nom de l’équipe	Année de repêchage	Choix total	Information	Date de la Dernière Transaction	Lien

Choix au repêchage

Année	R1	R2	R3	R4	R5
2	PPJ	PPJ	PPJ	PPJ	PPJ
3	PPJ	PPJ	PPJ	PPJ	PPJ
4	PPJ	PPJ	PPJ	PPJ	PPJ
5	PPJ	PPJ	PPJ	PPJ	PPJ
6	PPJ	PPJ	PPJ	PPJ	PPJ
Choix au repêchage conditionnel

La base de données des nouvelles du STHS n'a pas été trouvée ou corrompu. Veuillez en créer une de la section Gestion des nouvelles de la ligue du site web en étant connecté comme commissaire.

Pittsburgh Pollen Jocks Historique de transactions

[9/19/2026 8:36:06 PM] Pittsburgh Pollen Jocks was eliminated at round 2 of year 1.
[9/15/2026 11:10:27 PM] New Record for Team's Most Points (15) in 1 Game for Pittsburgh Pollen Jocks!
[9/15/2026 11:10:27 PM] New Record for Team's Most Assists (10) in 1 Game for Pittsburgh Pollen Jocks!
[9/11/2026 6:55:30 PM] New Record for Team's Most Points (13) in 1 Game for Pittsburgh Pollen Jocks!
[9/11/2026 6:55:30 PM] New Record for Team's Most Assists (8) in 1 Game for Pittsburgh Pollen Jocks!
[9/11/2026 6:55:30 PM] New Record for Team's Most Goals (5) in 1 Game for Pittsburgh Pollen Jocks!
[9/11/2026 6:54:38 PM] New Record for Team's Most Points (11) in 1 Game for Pittsburgh Pollen Jocks!
[9/11/2026 6:54:38 PM] New Record for Team's Most Assists (7) in 1 Game for Pittsburgh Pollen Jocks!
[9/11/2026 6:54:38 PM] New Record for Team's Most Goals (4) in 1 Game for Pittsburgh Pollen Jocks!
[9/10/2026 10:29:00 PM] New Record for Team's Most Penalties Minutes (15) in 1 Game for Pittsburgh Pollen Jocks!
[9/10/2026 10:29:00 PM] New Record for Team's Most Shots (54) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:31:35 AM] New Record for Team's Most Hits (27) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:31:14 AM] New Record for Team's Most Shots (42) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:31:14 AM] New Record for Team's Most Points (8) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:31:14 AM] New Record for Team's Most Assists (5) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:30:33 AM] New Record for Team's Most Points (7) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:30:33 AM] New Record for Team's Most Assists (4) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:30:33 AM] New Record for Team's Most Goals (3) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:29:48 AM] New Record for Team's Most Hits (22) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:29:48 AM] New Record for Team's Most Penalties Minutes (14) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:29:48 AM] New Record for Team's Most Shots Blocked (18) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:29:48 AM] New Record for Team's Most Shots (38) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:29:48 AM] New Record for Team's Most Points (4) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:29:48 AM] New Record for Team's Most Assists (2) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:29:48 AM] New Record for Team's Most Goals (2) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:29:48 AM] New Record for Team's Most Penalties Minutes (14) in 1 Game for Pittsburgh Pollen Jocks!
[9/9/2026 7:29:48 AM] New Record for Team's Most Shots Blocked (18) in 1 Game for Pittsburgh Pollen Jocks!
[9/7/2026 9:45:50 AM] Brian S was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:45:44 AM] Diego Adam was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:45:40 AM] Hugh Neutron was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:45:34 AM] Yo Gurt was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:45:30 AM] Bobby Voss was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:45:26 AM] Rudy Howitzer was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:45:22 AM] Chad Mashpots was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:45:18 AM] Andrew Brochacho was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:45:14 AM] Xhekajs middletoe was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:45:09 AM] Kyle Kyleson was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:45:05 AM] Oppai Bumu was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:45:01 AM] Pelayo Bolivar was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:39:51 AM] B-TM1 RW3 was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:39:50 AM] B-TM1 RW2 was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:39:50 AM] B-TM1 RW1 was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:39:49 AM] B-TM1 LW3 was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:39:49 AM] B-TM1 LW2 was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:39:48 AM] B-TM1 LW1 was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:39:48 AM] B-TM1 D2 was added to Pittsburgh Pollen Jocks.
[9/7/2026 9:39:48 AM] B-TM1 D1 was added to Pittsburgh Pollen Jocks.
[9/7/2026 8:51:55 AM] General Manager Change : Pittsburgh Pollen Jocks hired general manager Kermit
[9/7/2026 8:51:55 AM] General Manager Change : Pittsburgh Pollen Jocks fired general manager Pitt
[9/7/2026 8:51:47 AM] Team Name Change : Team 1 changed name to Pittsburgh Pollen Jocks
[9/7/2026 8:51:41 AM] General Manager Change : Team 1 hired general manager Pitt

Pas de blessure ou de suspension.

Pittsburgh Pollen Jocks Leaders statistiques des joueurs (saison régulière)

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#	Nom du joueur	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS

Pittsburgh Pollen Jocks Leaders des statistiques des gardiens (saison régulière)

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#	Nom du gardien	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA

Pittsburgh Pollen Jocks Statistiques de l'Équipe de Carrière

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	Total											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

Pittsburgh Pollen Jocks Leaders statistiques des joueurs (séries éliminatoires)

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#	Nom du joueur	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS

Pittsburgh Pollen Jocks Leaders des statistiques des gardiens (séries éliminatoires)

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#	Nom du gardien	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA

	Pittsburgh Pollen Jocks
	GP: 13 \| W: 6 \| L: 7 GF: 36 \| GA: 37 \| PP%: 14.49% \| PK%: 76.00% DG: Kermit \| Morale : 40 \| Moyenne d’équipe : 62