Day : 95

WPG - 2
UTA - 4

DAL - 3
OTT - 7

LOS - 4
BUF - 3

SJS - 3
CAR - 2

TOR - 3
TBL - 0

CLB - 4
WSH - 8

VAN - 4
PHI - 2

ANH - 3
NJD - 4

MIN - 2
NYR - 3

FLA - 3
PIT - 2

GRG - 2
SAR - 5

PRO - 6
NOR - 1

HAM - 3
GAT - 2

CTW - 6
SJS - 5

Day : 96

(20-23-1) - L2
(9-33-5) - L2

(34-10-2) - W2
(22-21-4) - L2

(27-16-3) - L2
(10-34-4) - L2

(23-20-4) - W4
(33-6-3) - W2

(19-23-3) - L2
(14-27-1) - L3

(15-23-7) - W3
(24-17-2) - W2

(25-15-7) - OTL1
(25-14-5) - W1

(24-19-3) - L1
(14-26-4) - L1

(25-17-3) - OTL1
(31-8-5) - W5

(24-18-6) - W3
(28-15-2) - W4

(26-12-1) - W1
(26-18-2) - L1

(25-11-5) - W1
(25-19-6) - L2

(26-19-2) - W3
(26-14-3) - W1

(31-6-6) - L1
(31-27-1) - L1

(26-10-6) - W2
(26-19-4) - W2

(31-7-4) - W8
(31-11-4) - L3

(27-12-1) - W2
(27-18-5) - OTL1

(16-26-4) - L1
(16-19-2) - L1

(15-22-4) - W1
(15-23-4) - L1

(16-20-5) - W1
(16-30-0) - W1

(14-26-4) - L1
(14-19-1) - W1

Game Center
	Charlotte Checkers 26-10-6, 58pts	5	FINAL	2	Danbury Trashers 16-20-5, 37pts

Team Stats
W2	Streak	W1
13-5-3	Home Record	10-9-3
13-5-3	Home Record	6-11-2
7-1-2	Last 10 Games	4-6-0
4.26	Goals Per Game	3.39
3.19	Goals Against Per Game	3.88
24.70%	Power Play Percentage	19.05%
81.25%	Penalty Kill Percentage	77.69%

Chicoutimi Saguenéens
16-23-4, 36pts

1

FINAL

3

Danbury Trashers
16-20-5, 37pts

Team Stats
L1	Streak	W1
7-12-2	Home Record	10-9-3
9-11-2	Home Record	6-11-2
3-6-1	Last 10 Games	4-6-0
3.28	Goals Per Game	3.39
4.49	Goals Against Per Game	3.88
21.13%	Power Play Percentage	19.05%
75.80%	Penalty Kill Percentage	77.69%

Danbury Trashers
16-20-5, 37pts

Day 96

Albany Devils
14-30-0, 28pts

Team Stats
W1	Streak	W1
10-9-3	Home Record	8-13-0
6-11-2	Away Record	6-17-0
4-6-0	Last 10 Games	2-8-0
3.39	Goals Per Game	3.05
3.88	Goals Against Per Game	3.05
19.05%	Power Play Percentage	16.92%
77.69%	Penalty Kill Percentage	70.16%

Danbury Trashers
16-20-5, 37pts

Day 97

Milwaukee Admirals
31-6-6, 68pts

Team Stats
W1	Streak	L1
10-9-3	Home Record	17-1-3
6-11-2	Away Record	14-5-3
4-6-0	Last 10 Games	5-3-2
3.39	Goals Per Game	4.65
3.88	Goals Against Per Game	4.65
19.05%	Power Play Percentage	25.58%
77.69%	Penalty Kill Percentage	83.87%

Trois-Rivières Lions
28-11-4, 60pts

Day 99

Danbury Trashers
16-20-5, 37pts

Team Stats
L3	Streak	W1
17-3-1	Home Record	10-9-3
11-8-3	Away Record	6-11-2
7-3-0	Last 10 Games	4-6-0
4.44	Goals Per Game	3.39
3.42	Goals Against Per Game	3.39
21.32%	Power Play Percentage	19.05%
74.71%	Penalty Kill Percentage	77.69%

Team Leaders
	Goals Michael Joly 17	Assists Matt Puempel 22

	Points Michael Joly 32	Plus/Minus Martin Gernat 8

	Wins Steve Mason 14	Save Percentage Steve Mason 0.882

Team Stats
Goals For 139 3.39 GFG	Shots For 1189 29.00 Avg	Power Play Percentage 19.0% 24 GF	Offensive Zone Start 35.5%
Goals Against 159 3.88 GAA	Shots Against 1305 31.83 Avg	Penalty Kill Percentage 77.7%% 29 GA	Defensive Zone Start 38.5%

Team Info
	General Manager	Mathieu Veilleux
	Coach	Dan Bylsma
	Division	Nilan
	Conference	Fortunus
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Capacity	3,000
	Attendance	2,895
	Season Tickets	300
Roster Info
	Pro Team	26
	Farm Team	20
	Contract Limit	46 / 50
	Prospects	13

Show or Hide Column

Filter Tips

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

#	Player Name	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	TA	SP	Age	Contract	Salary Average
1	Mike Winther	X				100.00	72	35	89	87	72	80	74	76	78	72	70	65	77	81	81	1	50	0		0	30	2	775,000$
2	Alexander Barabanov			X		100.00	63	28	99	84	77	82	82	78	68	73	73	69	77	75	73	1	50	0		0	30	2	775,000$
3	Mikael Backlund	X		X		100.00	61	35	94	78	79	83	81	77	78	72	71	71	76	99	99	1	50	0		0	35	1	750,000$
4	Tyler Johnson	X	X	X		100.00	47	25	99	79	69	79	78	80	76	75	74	65	81	99	99	1	50	0		0	34	2	900,000$
5	Reid Boucher		X	X		100.00	77	35	91	83	77	78	78	78	64	73	72	69	78	94	93	1	50	0		0	31	2	775,000$
6	Sebastian Collberg		X	X		100.00	75	30	85	82	72	81	77	81	62	74	73	66	80	82	82	1	50	0	N	0	30	2	800,000$
7	Michael Joly			X		100.00	77	33	89	85	79	86	80	81	65	74	74	69	75	86	86	1	50	0	N	0	29	3	900,000$
8	Matt Puempel		X	X		100.00	81	40	87	82	80	81	81	81	70	74	74	67	75	83	84	1	50	0	N	0	31	3	800,000$
9	Alex Iafallo	X	X			100.00	67	30	97	81	76	79	77	78	74	73	73	71	70	87	85	1	50	0	N	0	31	3	800,000$
10	Radovan Bondra		X	X		100.00	87	48	75	74	85	74	69	74	64	69	68	67	66	69	67	3	50	0		0	27	2	800,000$
11	Keegan Kolesar			X		100.00	89	46	78	75	91	78	81	78	65	70	72	65	71	73	73	4	50	0		0	27	2	800,000$
12	Jason Demers				X	100.00	71	35	91	75	77	81	79	78	50	73	63	84	72	99	99	1	50	0	N	0	36	2	775,000$
13	Jordan Gross				X	100.00	75	40	90	78	77	81	74	78	50	71	66	83	65	70	67	70	50	0		0	29	2	775,000$
14	Daniel Brickley				X	100.00	93	43	73	75	87	80	76	76	50	74	70	86	62	73	75	5	50	0		0	29	1	1,500,000$
15	Martin Gernat				X	100.00	81	45	82	74	83	78	70	76	50	73	65	89	53	90	91	1	50	0		0	31	2	900,000$
16	Mark Barberio				X	100.00	83	42	80	76	79	78	75	78	50	73	65	85	63	91	95	1	50	0		0	34	2	775,000$
17	Joey Laleggia				X	100.00	73	35	82	81	75	81	76	82	53	77	74	85	68	87	88	1	50	0	N	0	32	2	1,250,000$
18	Brenden Kichton				X	100.00	80	38	82	75	81	81	81	77	50	73	65	88	59	67	67	5	50	0		0	32	2	775,000$
19	Markus Niemelainen				X	100.00	84	46	78	76	85	79	76	77	50	72	64	87	58	72	70	5	50	0		0	26	1	1,400,000$
20	Chris Martenet				X	100.00	95	46	73	72	92	76	73	71	50	69	64	86	58	74	72	4	50	0		0	28	1	900,000$
Scratches
1	Taro Hirose		X			77.64	65	30	94	87	71	80	75	80	68	76	73	65	74	80	80	6	50	0	N	0	28	3	975,000$
2	Joel Edmundson				X	100.00	95	45	71	72	90	81	78	76	50	72	65	94	62	89	88	1	50	0		0	31	1	900,000$

	TEAM AVERAGE					98.95	77	38	85	79	80	80	77	78	61	73	69	76	69	83	82	5	50	0

Show or Hide Column

Filter Tips

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

#	Goalie Name	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	TA	SP	Age	Contract	Salary Average
1	Steve Mason	100.00	83	86	83	89	88	88	93	86	86	89	90	99	99	1	50	0	N	0	36	3	800,000$
2	Frederik Andersen	100.00	85	81	81	87	90	87	88	86	86	89	87	89	86	1	50	0		0	35	1	950,000$
3	David Rittich	100.00	83	83	84	91	89	90	91	89	88	91	88	86	87	1	50	0		0	32	1	800,000$
Scratches
1	Tuukka Rask	100.00	84	79	80	85	93	84	89	85	86	87	88	99	99	1	50	0		0	36	2	775,000$

	TEAM AVERAGE	100.00	84	82	82	88	90	87	90	87	87	89	88	93	93	1	50	0

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Dan Bylsma	79	81	83	80	88	86	70	USA	53	2	1,250,000$

Show or Hide Column

Filter Tips

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

#	Player Name	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	S1	S2	S3
1	Michael Joly	RW	41	17	15	32	-13	12	0	51	43	104	33	54	16.35%	8	624	15.23	4	6	10	23	112	0	0	0	0	1	3	0	47.22%	504	72	4	0	0	1.02	0	1	0	1	3	0
2	Matt Puempel	LW/RW	41	10	22	32	-16	22	0	74	35	94	27	62	10.64%	15	910	22.20	2	8	10	8	109	0	1	1	7	129	0	0	53.69%	244	42	19	0	0	0.70	1	3	0	2	0	0
3	Mike Winther	C	41	9	22	31	6	8	0	31	32	86	32	51	10.47%	10	759	18.53	0	0	0	0	0	1	1	2	2	37	0	0	51.65%	364	48	9	1	0	0.82	0	0	0	2	2	3
4	Tyler Johnson	C/LW/RW	41	12	18	30	-7	0	0	8	40	92	28	57	13.04%	10	723	17.65	3	4	7	18	97	0	0	0	0	6	1	0	48.86%	481	42	5	0	0	0.83	0	0	0	1	0	1
5	Reid Boucher	LW/RW	41	9	21	30	-7	12	0	86	39	78	32	63	11.54%	11	709	17.29	0	6	6	7	98	0	0	0	0	0	1	1	42.31%	26	64	7	0	0	0.85	0	0	0	2	1	1
6	Taro Hirose	LW	36	11	17	28	-13	4	0	26	27	85	30	56	12.94%	6	690	19.18	3	5	8	12	85	0	0	0	4	52	2	0	44.19%	43	70	4	0	0	0.81	1	2	0	0	2	1
7	Sebastian Collberg	LW/RW	41	9	16	25	1	20	0	56	24	79	37	56	11.39%	13	565	13.78	0	1	1	0	4	0	0	0	0	0	0	0	62.96%	27	74	8	0	0	0.88	0	0	0	0	1	2
8	Mikael Backlund	C/RW	41	6	17	23	-12	2	0	23	40	85	27	54	7.06%	10	719	17.55	2	3	5	16	111	0	0	0	2	42	1	3	57.50%	40	54	18	0	0	0.64	1	1	0	1	0	2
9	Alex Iafallo	C/LW	41	15	8	23	3	2	0	18	56	90	34	51	16.67%	20	693	16.92	1	0	1	1	13	2	1	3	6	148	0	0	50.91%	385	61	21	0	0	0.66	0	0	0	4	0	1
10	Keegan Kolesar	RW	41	9	12	21	3	4	0	38	13	52	20	46	17.31%	9	377	9.20	0	0	0	0	0	0	0	0	0	0	1	0	56.25%	16	32	4	0	0	1.11	0	0	0	1	1	2
11	Joey Laleggia	D	31	4	12	16	-9	26	0	44	52	37	18	14	10.81%	46	699	22.58	2	4	6	9	81	0	0	0	1	73	0	0	0.00%	0	18	35	0	0	0.46	0	0	0	0	1	0
12	Jason Demers	D	38	2	13	15	-6	2	0	36	78	41	20	19	4.88%	75	873	23.00	0	0	0	5	60	0	0	0	0	87	1	0	0.00%	0	4	48	0	0	0.34	0	0	0	0	2	0
13	Daniel Brickley	D	34	6	8	14	-11	18	0	50	51	37	17	17	16.22%	35	534	15.73	4	1	5	8	54	0	1	1	2	66	1	0	0.00%	0	5	23	0	0	0.52	0	0	0	0	0	1
14	Alexander Barabanov	RW	38	5	7	12	-3	0	0	3	12	31	15	20	16.13%	3	229	6.05	0	0	0	0	0	0	0	0	0	7	0	0	40.00%	15	21	1	0	0	1.04	1	2	0	0	0	0
15	Martin Gernat	D	32	1	10	11	8	14	0	34	49	42	16	20	2.38%	38	523	16.35	0	1	1	6	26	0	0	0	0	27	1	0	0.00%	0	4	29	0	0	0.42	0	0	0	0	0	0
16	Chris Martenet	D	38	4	7	11	4	30	0	53	56	28	10	15	14.29%	38	469	12.35	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	4	27	0	0	0.47	0	0	0	0	0	2
17	Mark Barberio	D	30	2	8	10	-9	20	0	59	73	43	19	20	4.65%	46	693	23.11	1	2	3	8	72	0	0	0	0	51	0	0	0.00%	0	7	38	0	0	0.29	0	0	0	0	0	1
18	Markus Niemelainen	D	41	4	5	9	-8	24	0	67	84	38	19	19	10.53%	58	763	18.63	2	0	2	11	100	0	0	0	0	92	2	0	0.00%	0	4	34	0	0	0.24	0	0	0	0	0	0
19	Radovan Bondra	LW/RW	19	2	5	7	7	12	0	24	7	15	7	9	13.33%	3	174	9.21	0	0	0	0	0	0	0	0	0	0	0	0	44.44%	9	6	3	0	0	0.80	0	0	0	0	1	0
20	Joel Edmundson	D	11	0	2	2	-5	12	0	18	30	17	8	8	0.00%	15	228	20.76	0	0	0	2	23	0	0	0	1	20	0	0	0.00%	0	2	11	0	0	0.18	0	0	0	0	0	0
21	Daniel O'Regan	C	6	0	2	2	3	0	0	2	0	2	0	4	0.00%	0	18	3.13	0	0	0	0	0	0	0	0	0	3	0	0	53.33%	15	2	0	0	0	2.13	0	0	0	0	0	0
22	Brenden Kichton	D	20	0	1	1	2	10	0	17	21	12	2	5	0.00%	7	166	8.32	0	0	0	0	0	0	0	0	0	7	0	0	0.00%	0	0	11	0	0	0.12	0	0	0	0	0	0
23	Jordan Gross	D	38	0	0	0	-1	0	0	0	2	1	2	0	0.00%	5	17	0.46	0	0	0	0	3	0	0	0	0	4	0	0	0.00%	0	0	1	0	0	0.00	0	0	0	0	0	0
24	Ryan Dzingel	C/LW/RW	5	0	0	0	0	0	0	0	1	0	0	0	0.00%	0	4	0.86	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0	0	0	0.00	0	0	0	0	0	0
Team Total or Average				786	137	248	385	-83	254	0	818	865	1189	453	720	11.52%	481	12171	15.48	24	41	65	134	1056	3	4	7	25	864	14	4	50.02%	2169	636	360	1	0	0.63	4	9	0	14	14	17

Show or Hide Column

Filter Tips

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

#	Goalie Name	Team Name	GP	W	L	OTL	PCT	GAA	MP	PIM	GA	SA	SAR	A	PS %	PSA	ST	BG	S1	S2
1	Steve Mason	Danbury Trashers (PHI)	36	14	18	4	0.882	3.70	1979	4	122	1037	528	0	0.667	9	36	0	1	2
2	Frederik Andersen	Danbury Trashers (PHI)	12	2	2	1	0.868	4.22	483	2	34	258	142	1	0.000	0	5	31	1	0
3	David Rittich	Danbury Trashers (PHI)	1	0	0	0	0.800	4.62	26	0	2	10	4	0	0.000	0	0	5	0	0
Team Total or Average			49	16	20	5	0.879	3.81	2489	6	158	1305	674	1		9	41	36	2	2

Player Name	POS	Age	Birthday	Terms	Contract	Cap %	Year 2024	Year 2025	Year 2026	Year 2027	Year 2028	Year 2029	Year 2030
Forward
Alex Iafallo	C/LW	31	1993-01-22	NT TW	3	0.00%	800,000$	800,000$	800,000$	UFA [Age: 34]
Alexander Barabanov	RW	30	1994-01-22	TW	2	0.00%	775,000$	775,000$	UFA [Age: 32]
Keegan Kolesar	RW	27	1997-01-22	TW	2	0.00%	800,000$	800,000$	UFA [Age: 29]
Matt Puempel	LW/RW	31	1993-01-22	NT TW	3	0.00%	800,000$	800,000$	800,000$	UFA [Age: 34]
Michael Joly	RW	29	1995-01-22	NT TW	3	0.00%	900,000$	900,000$	900,000$	UFA [Age: 32]
Mikael Backlund	C/RW	35	1989-01-22	TW	1	0.00%	750,000$	UFA [Age: 36]
Mike Winther	C	30	1994-01-22	TW	2	0.00%	775,000$	775,000$	UFA [Age: 32]
Radovan Bondra	LW/RW	27	1997-01-22	TW	2	0.00%	800,000$	800,000$	UFA [Age: 29]
Reid Boucher	LW/RW	31	1993-01-22	TW	2	0.00%	775,000$	775,000$	UFA [Age: 33]
Sebastian Collberg	LW/RW	30	1994-01-22	NT TW	2	0.00%	800,000$	800,000$	UFA [Age: 32]
Taro Hirose	LW	28	1996-01-22	NT IN TW	3	0.00%	975,000$	975,000$	975,000$	UFA [Age: 31]
Tyler Johnson	C/LW/RW	34	1990-01-22	TW	2	0.00%	900,000$	900,000$	UFA [Age: 36]
AVERAGE (12)		30.25				0.00%	0$	9,100,000$	3,475,000$	0$	0$	0$	0$
Defenseman
Brenden Kichton	D	32	1992-01-22	TW	2	0.00%	775,000$	775,000$	UFA [Age: 34]
Chris Martenet	D	28	1996-01-22	TW	1	0.00%	900,000$	UFA [Age: 29]
Daniel Brickley	D	29	1995-01-22	TW	1	0.00%	1,500,000$	UFA [Age: 30]
Jason Demers	D	36	1988-01-02	NT TW	2	0.00%	775,000$	775,000$	UFA [Age: 38]
Joel Edmundson	D	31	1993-01-22	TW	1	0.00%	900,000$	UFA [Age: 32]
Joey Laleggia	D	32	1992-01-22	NT TW	2	0.00%	1,250,000$	1,250,000$	UFA [Age: 34]
Jordan Gross	D	29	1995-01-02	TW	2	0.00%	775,000$	775,000$	UFA [Age: 31]
Mark Barberio	D	34	1990-01-22	TW	2	0.00%	775,000$	775,000$	UFA [Age: 36]
Markus Niemelainen	D	26	1998-01-22	TW	1	0.00%	1,400,000$	RFA ( Groupe: 2 ) [Age: 27]
Martin Gernat	D	31	1993-01-22	TW	2	0.00%	900,000$	900,000$	UFA [Age: 33]
AVERAGE (10)		30.80				0.00%	0$	5,250,000$	0$	0$	0$	0$	0$
Goalies
David Rittich	G	32	1992-01-22	TW	1	0.00%	800,000$	UFA [Age: 33]
Frederik Andersen	G	35	1989-01-22	TW	1	0.00%	950,000$	UFA [Age: 36]
Steve Mason	G	36	1988-01-22	NT TW	3	0.00%	800,000$	800,000$	800,000$	UFA [Age: 39]
Tuukka Rask	G	36	1988-01-22	TW	2	0.00%	775,000$	775,000$	UFA [Age: 38]

Terms Legends : FV = Force Waiver / NT = No Trade / IN = Injured / TW = Two Way Contract (Can Play Pro + Can Play Farm)

Note: The salary cap amounts for the current year and the % of salary cap are based on a calculation of the simple salary cap calculation (Average Salary or Salary for the year depending on your salary options). If your salary cap is based on complex calculation, the results of this analysis could be incorrect by a small margin. The Current Year Pro Salary Cap is : 89,000,050$.

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Matt Puempel	Michael Joly	Mikael Backlund	25	1	2	2
2	Alexander Barabanov	Tyler Johnson	Reid Boucher	25	1	2	2
3	Sebastian Collberg	Alex Iafallo	Mike Winther	25	1	2	2
4	Matt Puempel	Mike Winther	Keegan Kolesar	25	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Martin Gernat	Chris Martenet	25	1	2	2
2	Joey Laleggia	Mark Barberio	25	1	2	2
3	Markus Niemelainen	Jason Demers	25	1	2	2
4	Mark Barberio	Jason Demers	25	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Matt Puempel	Michael Joly	Mikael Backlund	60	1	2	2
2	Alex Iafallo	Tyler Johnson	Reid Boucher	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Mark Barberio	Markus Niemelainen	60	1	2	2
2	Joey Laleggia	Jason Demers	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Matt Puempel	Alex Iafallo	60	1	2	2
2	Michael Joly	Mikael Backlund	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Jason Demers	Markus Niemelainen	60	1	2	2
2	Joey Laleggia	Mark Barberio	40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Matt Puempel	60	1	2	2	Mark Barberio	Markus Niemelainen	60	1	2	2
2	Mikael Backlund	40	1	2	2	Martin Gernat	Jason Demers	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Matt Puempel	Sebastian Collberg	60	1	2	2
2	Michael Joly	Mikael Backlund	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Mark Barberio	Jason Demers	60	1	2	2
2	Joey Laleggia	Markus Niemelainen	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Matt Puempel	Michael Joly	Mikael Backlund	Joey Laleggia	Mark Barberio

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Matt Puempel	Michael Joly	Mikael Backlund	Joey Laleggia	Mark Barberio

Extra Forwards
Normal	PowerPlay	Penalty Kill
Sebastian Collberg, Alex Iafallo, Mikael Backlund	Sebastian Collberg, Alex Iafallo	Matt Puempel

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Markus Niemelainen, Jason Demers, Mark Barberio	Markus Niemelainen	Markus Niemelainen, Mark Barberio

Penalty Shots
Matt Puempel, Michael Joly, Sebastian Collberg, Mikael Backlund, Tyler Johnson

Goalie
#1 : Steve Mason, #2 : David Rittich, #3 : Frederik Andersen

Custom OT Lines Forwards
Matt Puempel, Michael Joly, Alexander Barabanov, Mikael Backlund, Tyler Johnson, Reid Boucher, Reid Boucher, Sebastian Collberg, Alex Iafallo, Keegan Kolesar, Mike Winther

Custom OT Lines Defensemen
Jason Demers, Chris Martenet, Joey Laleggia, Mark Barberio, Markus Niemelainen

Show or Hide Column

Filter Tips

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

	Overall												Home											Visitor
#	VS Team	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	Albany Devils	2	1	0	0	0	1	0	0	9	4	5	2	1	0	0	0	1	0	0	9	4	5	0	0	0	0	0	0	0	0	0	0	0	3	0.750	9	16	25	0	0	47	44	42	8	73	391	387	392	28	69	15	16	51	9	3	33.33%	8	1	87.50%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
2	Blainville-Boisbriand Armada	2	0	1	0	0	0	1	0	8	13	-5	0	0	0	0	0	0	0	0	0	0	0	2	0	1	0	0	0	1	0	8	13	-5	2	0.500	8	12	20	0	0	47	44	42	8	54	391	387	392	28	81	30	16	30	1	1	100.00%	8	4	50.00%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
3	Bridgeport Sound Tigers	1	1	0	0	0	0	0	0	6	2	4	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	6	2	4	2	1.000	6	11	17	0	0	47	44	42	8	33	391	387	392	28	35	16	4	28	6	2	33.33%	2	0	100.00%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
4	Charlotte Checkers	2	0	2	0	0	0	0	0	4	9	-5	1	0	1	0	0	0	0	0	2	5	-3	1	0	1	0	0	0	0	0	2	4	-2	0	0.000	4	6	10	0	0	47	44	42	8	40	391	387	392	28	71	25	6	37	3	1	33.33%	3	0	100.00%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
5	Chicago Wolves	1	1	0	0	0	0	0	0	8	1	7	1	1	0	0	0	0	0	0	8	1	7	0	0	0	0	0	0	0	0	0	0	0	2	1.000	8	15	23	0	0	47	44	42	8	36	391	387	392	28	19	6	2	32	5	2	40.00%	1	0	100.00%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
6	Chicoutimi Saguenéens	3	2	0	0	0	1	0	0	11	8	3	3	2	0	0	0	1	0	0	11	8	3	0	0	0	0	0	0	0	0	0	0	0	5	0.833	11	21	32	0	0	47	44	42	8	78	391	387	392	28	77	45	24	59	7	2	28.57%	12	0	100.00%	1	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
7	Chisinau Pelicans	1	0	0	0	0	1	0	0	3	4	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	3	4	-1	1	0.500	3	6	9	0	0	47	44	42	8	33	391	387	392	28	21	5	2	23	5	1	20.00%	1	0	100.00%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
8	Connecticut Whale	5	1	4	0	0	0	0	0	12	24	-12	2	1	1	0	0	0	0	0	6	7	-1	3	0	3	0	0	0	0	0	6	17	-11	2	0.200	12	22	34	0	0	47	44	42	8	135	391	387	392	28	170	58	36	86	18	2	11.11%	18	7	61.11%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
9	Grand Rapids Griffins	3	1	2	0	0	0	0	0	14	11	3	0	0	0	0	0	0	0	0	0	0	0	3	1	2	0	0	0	0	0	14	11	3	2	0.333	14	25	39	0	0	47	44	42	8	94	391	387	392	28	97	19	16	70	6	2	33.33%	8	2	75.00%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
10	Hamilton Bulldogs	1	0	1	0	0	0	0	0	2	4	-2	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	2	4	-2	0	0.000	2	4	6	0	0	47	44	42	8	23	391	387	392	28	29	15	8	11	3	0	0.00%	4	0	100.00%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
11	Henderson Silver Knights	2	0	1	0	0	0	0	1	5	7	-2	1	0	1	0	0	0	0	0	2	3	-1	1	0	0	0	0	0	0	1	3	4	-1	1	0.250	5	10	15	0	0	47	44	42	8	66	391	387	392	28	59	26	10	47	6	0	0.00%	5	2	60.00%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
12	Houston Aeros	2	1	0	0	0	1	0	0	8	8	0	2	1	0	0	0	1	0	0	8	8	0	0	0	0	0	0	0	0	0	0	0	0	3	0.750	8	16	24	0	0	47	44	42	8	70	391	387	392	28	63	28	8	46	9	1	11.11%	4	0	100.00%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
13	Lake Erie Monsters	1	0	1	0	0	0	0	0	4	6	-2	1	0	1	0	0	0	0	0	4	6	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	4	7	11	0	0	47	44	42	8	26	391	387	392	28	31	8	12	17	3	0	0.00%	6	2	66.67%	1	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
14	Manitoba Moose	1	1	0	0	0	0	0	0	5	1	4	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	5	1	4	2	1.000	5	8	13	0	0	47	44	42	8	33	391	387	392	28	36	15	4	16	5	2	40.00%	2	0	100.00%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
15	Norfolk Admirals	2	0	1	0	1	0	0	0	4	7	-3	1	0	0	0	1	0	0	0	3	2	1	1	0	1	0	0	0	0	0	1	5	-4	2	0.500	4	7	11	0	0	47	44	42	8	73	391	387	392	28	69	15	8	35	6	0	0.00%	4	1	75.00%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
16	Portland Crying Chiwawas	1	1	0	0	0	0	0	0	5	3	2	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	5	3	2	2	1.000	5	9	14	0	0	47	44	42	8	31	391	387	392	28	24	10	2	26	3	2	66.67%	1	0	100.00%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
17	Providence Bruins	3	0	2	0	0	0	1	0	8	13	-5	2	0	1	0	0	0	1	0	5	5	0	1	0	1	0	0	0	0	0	3	8	-5	2	0.333	8	12	20	0	0	47	44	42	8	83	391	387	392	28	99	36	22	50	6	0	0.00%	11	2	81.82%	1	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
18	Roberval Dwarfs	2	0	2	0	0	0	0	0	5	12	-7	2	0	2	0	0	0	0	0	5	12	-7	0	0	0	0	0	0	0	0	0	0	0	0	0.000	5	10	15	0	0	47	44	42	8	55	391	387	392	28	61	19	14	33	7	1	14.29%	7	2	71.43%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
19	San Jose Barracuda	3	0	1	0	2	0	0	0	8	8	0	2	0	0	0	2	0	0	0	6	4	2	1	0	1	0	0	0	0	0	2	4	-2	4	0.667	8	13	21	0	0	47	44	42	8	76	391	387	392	28	87	38	20	53	9	0	0.00%	10	2	80.00%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
20	Springfield Falcons	1	0	1	0	0	0	0	0	3	5	-2	1	0	1	0	0	0	0	0	3	5	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	3	6	9	0	0	47	44	42	8	28	391	387	392	28	28	13	12	29	5	0	0.00%	6	1	83.33%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
21	The Nuuk Vikings	1	0	1	0	0	0	0	0	3	6	-3	1	0	1	0	0	0	0	0	3	6	-3	0	0	0	0	0	0	0	0	0	0	0	0	0.000	3	6	9	0	0	47	44	42	8	27	391	387	392	28	40	18	14	20	3	2	66.67%	7	2	71.43%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
22	Verdun Junior	1	0	0	0	1	0	0	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	4	3	1	2	1.000	4	6	10	0	0	47	44	42	8	22	391	387	392	28	39	21	4	19	1	0	0.00%	2	1	50.00%	0	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
	Total	41	10	20	0	4	4	2	1	139	159	-20	22	6	9	0	3	3	1	0	75	76	-1	19	4	11	0	1	1	1	1	64	83	-19	37	0.451	139	248	387	0	0	47	44	42	8	1189	391	387	392	28	1305	481	260	818	126	24	19.05%	130	29	77.69%	3	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
	_Since Last GM Reset	41	10	20	0	4	4	2	1	139	159	-20	22	6	9	0	3	3	1	0	75	76	-1	19	4	11	0	1	1	1	1	64	83	-19	37	0.451	139	248	387	0	0	47	44	42	8	1189	391	387	392	28	1305	481	260	818	126	24	19.05%	130	29	77.69%	3	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
	_Vs Conference	25	6	12	0	3	2	1	1	77	91	-14	14	3	5	0	3	2	1	0	44	43	1	11	3	7	0	0	0	0	1	33	48	-15	23	0.460	77	136	213	0	0	47	44	42	8	741	391	387	392	28	810	295	148	504	85	13	15.29%	74	16	78.38%	1	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322
	_Vs Division	10	3	7	0	0	1	1	0	43	42	1	3	2	3	0	0	1	1	0	12	14	-2	7	1	4	0	0	0	0	0	31	28	3	9	0.450	43	74	117	0	0	47	44	42	8	299	391	387	392	28	347	121	60	198	25	6	24.00%	30	9	70.00%	1	385	760	50.66%	411	825	49.82%	289	556	51.98%	907	575	942	339	642	322

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
41	37	W1	139	248	387	1189	1305	481	260	818	0	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	10	20	4	4	2	1	139	159

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
22	6	9	3	3	1	0	75	76

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
19	4	11	1	1	1	1	64	83

Last 10 Games
W	L	OTW	OTL	SOW	SOL
4	6	0	0	0	0

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
126	24	19.05%	130	29	77.69%	3

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
391	387	392	28	47	44	42	8

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
385	760	50.66%	411	825	49.82%	289	556	51.98%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
907	575	942	339	642	322

Last Played Games Show or Hide Column

Filter Tips

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

Day	Game	Visitor Team	Score	Home Team	Score	ST	OT	SO	Link
Day:1
1	10	Danbury Trashers	7	Grand Rapids Griffins	1	W			BoxScore
Day:2
2	20	Danbury Trashers	2	Blainville-Boisbriand Armada	8	L			BoxScore
Day:5
5	31	Chicoutimi Saguenéens	2	Danbury Trashers	4	W			BoxScore
Day:8
8	52	Albany Devils	1	Danbury Trashers	7	W			BoxScore
Day:11
11	75	Danbury Trashers	3	Connecticut Whale	8	L			BoxScore
Day:13
13	90	Providence Bruins	3	Danbury Trashers	4	W	X	X	BoxScore
Day:17
17	111	Danbury Trashers	3	Chisinau Pelicans	4	L	X		BoxScore
Day:18
18	121	Danbury Trashers	6	Blainville-Boisbriand Armada	5	W	X	X	BoxScore
Day:20
20	134	Norfolk Admirals	2	Danbury Trashers	3	W	X		BoxScore
Day:22
22	154	Springfield Falcons	5	Danbury Trashers	3	L			BoxScore
Day:24
24	172	Danbury Trashers	2	Grand Rapids Griffins	4	L			BoxScore
Day:26
26	189	Chicoutimi Saguenéens	5	Danbury Trashers	4	L	X		BoxScore
Day:27
27	200	Danbury Trashers	2	Connecticut Whale	5	L			BoxScore
Day:29
29	219	Roberval Dwarfs	6	Danbury Trashers	4	L			BoxScore
Day:31
31	242	Danbury Trashers	5	Grand Rapids Griffins	6	L			BoxScore
Day:32
32	251	Danbury Trashers	1	Connecticut Whale	4	L			BoxScore
Day:34
34	260	San Jose Barracuda	2	Danbury Trashers	3	W	X		BoxScore
Day:39
39	286	Houston Aeros	5	Danbury Trashers	4	L	X		BoxScore
Day:41
41	303	Danbury Trashers	5	Portland Crying Chiwawas	3	W			BoxScore
Day:43
43	315	Connecticut Whale	4	Danbury Trashers	2	L			BoxScore
Day:45
45	334	Danbury Trashers	2	Hamilton Bulldogs	4	L			BoxScore
Day:46
46	347	San Jose Barracuda	2	Danbury Trashers	3	W	X		BoxScore
Day:49
49	362	Danbury Trashers	3	Providence Bruins	8	L			BoxScore
Day:51
51	383	Providence Bruins	2	Danbury Trashers	1	L			BoxScore
Day:54
54	409	Albany Devils	3	Danbury Trashers	2	L	X		BoxScore
Day:56
56	430	Danbury Trashers	3	Henderson Silver Knights	4	L	X	X	BoxScore
Day:57
57	440	Danbury Trashers	2	San Jose Barracuda	4	L			BoxScore
Day:59
59	453	Connecticut Whale	3	Danbury Trashers	4	W			BoxScore
Day:62
62	476	Chicago Wolves	1	Danbury Trashers	8	W			BoxScore
Day:64
64	498	Danbury Trashers	5	Manitoba Moose	1	W			BoxScore
Day:67
67	509	Danbury Trashers	2	Charlotte Checkers	4	L			BoxScore
Day:68
68	518	The Nuuk Vikings	6	Danbury Trashers	3	L			BoxScore
Day:71
71	541	Houston Aeros	3	Danbury Trashers	4	W			BoxScore
Day:72
72	558	Danbury Trashers	1	Norfolk Admirals	5	L			BoxScore
Day:75
75	575	Henderson Silver Knights	3	Danbury Trashers	2	L			BoxScore
Day:78
78	599	Danbury Trashers	4	Verdun Junior	3	W	X		BoxScore
Day:79
79	610	Lake Erie Monsters	6	Danbury Trashers	4	L			BoxScore
Day:83
83	630	Danbury Trashers	6	Bridgeport Sound Tigers	2	W			BoxScore
Day:84
84	643	Roberval Dwarfs	6	Danbury Trashers	1	L			BoxScore
Day:89
89	668	Charlotte Checkers	5	Danbury Trashers	2	L			BoxScore
Day:94
94	697	Chicoutimi Saguenéens	1	Danbury Trashers	3	W			BoxScore
Day:96
96	715	Danbury Trashers	-	Albany Devils	-
Day:97
97	721	Danbury Trashers	-	Milwaukee Admirals	-
Day:99
99	737	Trois-Rivières Lions	-	Danbury Trashers	-
Day:101
101	764	Rochester Americans	-	Danbury Trashers	-
Day:104
104	782	Danbury Trashers	-	Albany Devils	-
Day:107
107	796	Manitoba Moose	-	Danbury Trashers	-
Day:109
109	814	Danbury Trashers	-	Rochester Americans	-
Day:110
110	827	Quebec Stars	-	Danbury Trashers	-
Day:111
111	843	Danbury Trashers	-	Manitoba Moose	-
Day:114
114	860	Springfield Falcons	-	Danbury Trashers	-
Day:116
116	868	Danbury Trashers	-	Charlotte Checkers	-
Day:118
118	887	Danbury Trashers	-	Milwaukee Admirals	-
Day:120
120	900	Wilkes-Barre/Scranton Penguins	-	Danbury Trashers	-
Day:123
123	912	Danbury Trashers	-	Trois-Rivières Lions	-
Day:125
125	927	Danbury Trashers	-	Grand Rapids Griffins	-
Day:126
126	940	Norfolk Admirals	-	Danbury Trashers	-
Day:128
128	961	San Antonio Rampage	-	Danbury Trashers	-
Day:132
132	993	Laval Chiefs	-	Danbury Trashers	-
Day:133
133	1003	Danbury Trashers	-	Houston Aeros	-
Day:135
135	1015	Danbury Trashers	-	Joliette Sportif	-
Day:137
137	1032	Joliette Sportif	-	Danbury Trashers	-
Day:141
Trade Deadline --- Trades can’t be done after this day is simulated!
141	1056	Danbury Trashers	-	Wilkes-Barre/Scranton Penguins	-
Day:143
143	1064	Binghamton Senators	-	Danbury Trashers	-
Day:148
148	1094	Lake Erie Monsters	-	Danbury Trashers	-
Day:150
150	1111	Danbury Trashers	-	Chisinau Pelicans	-
Day:152
152	1127	Bridgeport Sound Tigers	-	Danbury Trashers	-
Day:153
153	1137	Danbury Trashers	-	San Antonio Rampage	-
Day:155
155	1154	Danbury Trashers	-	Bridgeport Sound Tigers	-
Day:156
156	1164	Albany Devils	-	Danbury Trashers	-
Day:159
159	1177	Danbury Trashers	-	Blainville-Boisbriand Armada	-
Day:161
161	1196	Danbury Trashers	-	Connecticut Whale	-
Day:162
162	1203	Quebec Stars	-	Danbury Trashers	-
Day:165
165	1227	Danbury Trashers	-	Connecticut Whale	-
Day:167
167	1235	Portland Crying Chiwawas	-	Danbury Trashers	-
Day:171
171	1261	Wilkes-Barre/Scranton Penguins	-	Danbury Trashers	-
Day:174
174	1277	Danbury Trashers	-	Blainville-Boisbriand Armada	-
Day:176
176	1292	Gatineau Olympiques	-	Danbury Trashers	-
Day:177
177	1300	Danbury Trashers	-	Chisinau Pelicans	-
Day:178
178	1313	Danbury Trashers	-	Springfield Falcons	-
Day:182
182	1333	Gatineau Olympiques	-	Danbury Trashers	-
Day:186
186	1350	Danbury Trashers	-	Springfield Falcons	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses

Danbury Trashers Players Stat Leaders (Regular Season)

Show or Hide Column

#	Player Name	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

Danbury Trashers Goalies Stat Leaders (Regular Season)

Show or Hide Column

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA

Danbury Trashers Career Team Stats

Show or Hide Column

	Overall											Home											Visitor
Year	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

Danbury Trashers Players Stat Leaders (Play-Off)

Show or Hide Column

#	Player Name	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

Danbury Trashers Goalies Stat Leaders (Play-Off)

Show or Hide Column

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA



	WC Home Main STHS Client League File ProToday's Games FarmToday's Games Today's Transactions Search League News Management Upload Lines Web Client Email General Manager Today's Information Teams Pro Team Eastern Conference Boston Bruins Buffalo Sabres Carolina Hurricanes Columbus Blue Jackets Florida Panthers Montreal Canadiens New Jersey Devils New York Islanders New York Rangers Ottawa Senators Philadelphia Flyers Pittsburgh Penguins Quebec Nordiques Tampa Bay Lightning Toronto Maple Leafs Washington Capitals Western Conference Anaheim Ducks Calgary Flames Chicago Blackhawks Colorado Avalanche Dallas Stars Detroit Red Wings Edmonton Oilers Los Angeles Kings Minnesota Wild Nashville Predators San Jose Sharks Seattle Kraken St. Louis Blues Utah Hockey Club Vancouver Canucks Vegas Golden Knights Winnipeg Jets Farm Team Hamel Binghamton Senators Blainville-Boisbriand Armada Chicago Wolves Chicoutimi Saguenéens Chisinau Pelicans Gatineau Olympiques Grand Rapids Griffins Hamilton Bulldogs Joliette Sportif Lake Erie Monsters Laval Chiefs Milwaukee Admirals Quebec Stars Roberval Dwarfs The Nuuk Vikings Trois-Rivières Lions Verdun Junior Fortunus Albany Devils Bridgeport Sound Tigers Charlotte Checkers Connecticut Whale Danbury Trashers Henderson Silver Knights Houston Aeros Manitoba Moose Norfolk Admirals Portland Crying Chiwawas Providence Bruins Rochester Americans San Antonio Rampage San Jose Barracuda Springfield Falcons Wilkes-Barre/Scranton Penguins Pro League Standing Schedule Players Leader Goalies Leader Individual Leaders All Players Stats All Goalies Stats Teams Stats Finance Power Ranking Farm League Standing Schedule Players Leader Goalies Leader Individual Leaders All Players Stats All Goalies Stats Teams Stats Finance Power Ranking League Entry Draft Projection Coaches Transactions Waivers Team/GM Trade History Prospects RSS Feed Unassigned Players Goalies Available For Trade Players Goalies Compares Players Players Goalies Free Agents Players Goalies Retire Players Players Goalies Records League Records Team Records Search Legacy Pages Coaches Free Agents Pro All Players Stats Pro Individual Leaders Pro Leaders Pro Power Ranking Pro Standing Pro Team Lines Pro Team PlayersInfo Pro Team Roster Pro Team Schedule Pro Team Scoring Pro Team Stats Pro Team Stats VS Rerate Difference Schedule Team Finance Team History Team Injury Suspension Team Prospects Teams And GM Info Today Games Today Transactions Trade History Transactions Unassigned Waivers Help Latest STHS Client STHS Client Manual Log in

	Danbury Trashers
	GP: 41 \| W: 16 \| L: 20 \| OTL: 5 \| P: 37 GF: 139 \| GA: 159 \| PP%: 19.05% \| PK%: 77.69% GM : Mathieu Veilleux \| Morale : 50 \| Team Overall : N/A Next Games #715 vs Albany Devils