Profi League - Schedule Pro Blue Jackets

Final
CBJ	2
NJD	4

Final
FLA	5
TOR	2

Final/OT
TBL	5
PIT	6

Final
VGK	2
UTA	4

Final
EDM	2
LAK	3

May
2

Saturday, May 2
NJD
CBJ

Saturday, May 2
UTA
VGK

Blue Jackets

Columbus Blue Jackets
3-3-0, 6pts · 1st in Eastern Conference

Player Stats

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3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
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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.
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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	Team Name	#	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	SHT	OSB	OSM	SHT%	SB	MP	PPG	PPA	PPP	PKG	PKA	PKP	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS
1	Aleksander Barkov	Blue Jackets	16	C/LW	6	1	7	8	6	0	0	12	26	6	9	3.85%	3	21.:.05	0	0	0	0	0	0	1	1	0	50.00%	166	0	0	0	0	1.26	0	0
2	Alex Ovechkin	Blue Jackets	8	LW/RW	6	4	3	7	7	4	0	10	22	8	18	18.18%	1	19.:.58	0	1	1	0	0	0	0	0	0	33.33%	9	0	0	0	0	1.17	0	0
3	Claude Giroux	Blue Jackets	28	C/LW/RW	6	2	4	6	4	0	0	4	14	6	14	14.29%	2	20.:.44	1	0	1	0	0	0	6	0	0	55.81%	43	0	0	1	0	0.96	0	0
4	Mattias Ekholm	Blue Jackets	14	D	6	0	6	6	0	2	0	10	7	1	9	0.00%	8	22.:.48	0	2	2	0	0	0	9	0	0	0.00%	0	0	0	0	0	0.88	0	0
5	Neal Pionk	Blue Jackets	4	D	6	2	3	5	2	4	0	23	7	3	5	28.57%	12	24.:.22	1	1	2	0	0	0	13	0	0	0.00%	0	0	0	0	0	0.68	0	0
6	Patrick Kane	Blue Jackets	88	RW	6	4	0	4	2	2	0	4	18	5	7	22.22%	0	21.:.25	1	0	1	0	0	0	0	2	0	11.11%	9	0	0	0	0	0.62	0	0
7	Mika Zibanejad	Blue Jackets	93	C/RW	6	0	4	4	-1	2	0	10	20	3	14	0.00%	0	23.:.43	0	1	1	0	0	0	2	0	0	55.11%	176	0	0	0	0	0.56	0	0
8	Jordan Staal	Blue Jackets	11	C/LW	6	2	1	3	-1	2	0	9	14	1	10	14.29%	1	16.:.34	0	0	0	0	1	1	15	0	0	55.38%	130	0	0	0	0	0.60	0	0
9	Parker Kelly	Blue Jackets	17	C/LW	6	2	1	3	0	0	0	2	4	2	4	50.00%	2	08.:.01	0	0	0	1	0	1	8	0	0	56.36%	55	0	0	0	0	1.25	0	0
10	Jaccob Slavin	Blue Jackets	74	D	6	0	2	2	3	4	0	7	2	1	8	0.00%	11	22.:.50	0	0	0	0	1	1	14	0	0	0.00%	0	0	0	0	0	0.29	0	0
11	Chris Kreider	Blue Jackets	20	LW/RW	6	1	1	2	-5	2	0	5	18	3	11	5.56%	1	16.:.38	1	1	2	0	0	0	0	0	0	62.50%	8	0	0	0	0	0.40	0	0
12	Devon Toews	Blue Jackets	7	D	6	0	1	1	-3	2	0	2	7	2	3	0.00%	11	24.:.30	0	0	0	0	0	0	14	0	0	0.00%	0	0	0	0	0	0.14	0	0
13	Cole Caufield	Blue Jackets	13	LW/RW	6	0	1	1	-2	2	0	7	21	3	9	0.00%	2	19.:.19	0	1	1	0	0	0	0	0	0	33.33%	9	0	0	0	0	0.17	0	0
14	Garnet Hathaway	Blue Jackets	19	LW/RW	6	0	1	1	-2	4	0	13	8	3	5	0.00%	0	08.:.03	0	0	0	0	0	0	3	0	0	75.00%	4	0	0	0	0	0.41	0	0
15	Kevin Bahl	Blue Jackets	89	D	6	1	0	1	1	6	0	16	4	0	1	25.00%	9	19.:.20	0	0	0	0	0	0	0	0	1	0.00%	0	0	0	0	0	0.17	0	0
16	Brandon Tanev	Blue Jackets	73	LW/RW	6	0	0	0	-5	0	0	11	14	1	11	0.00%	1	16.:.39	0	0	0	0	0	0	19	0	0	41.18%	17	0	0	0	0	0.00	0	0
17	Matt Roy	Blue Jackets	3	D	6	0	0	0	-1	2	0	8	2	1	2	0.00%	4	20.:.44	0	0	0	0	0	0	9	0	0	0.00%	0	0	0	0	0	0.00	0	0
18	Marc Gatcomb	Blue Jackets	61	C/RW	6	0	0	0	-1	2	0	0	4	1	5	0.00%	1	06.:.31	0	0	0	0	0	0	0	0	0	60.00%	5	0	0	0	0	0.00	0	0
Team Total or Average					102	19	35	54	5	38	0	153	208	49	140	9.13%	68	19:13	4	7	11	1	2	3	119	3	1	52.56%	626	0	0	1	0	0.55	0	0

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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	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Lukas Dostal	Blue Jackets	6	3	2	1	92.5%	2.30	391	0	0	15	201	0	0	0	0.0%	0	6	0	0	2	0
2	Jake Allen	Blue Jackets	1	0	0	0	90.0%	3.75	16	0	0	1	10	0	0	0	0.0%	0	0	6	0	0	0
Team Total or Average			7	3	2	1	92.4%	2.36	407	0	0	16	211	0	0	0	0.000	0	6	6	0	2	0

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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

#	VS Team	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	GF%	SH%	SV%	PDO	PDOBRK
1	Devils	6	3	3	0	0	0	0	0	19	16	3	6	0.500	19	35	54	0	0	6	4	8	1	212	59	63	60	30	211	69	40	153	11	4	36.36%	18	2	88.89%	1	144	279	51.61%	142	257	55.25%	46	95	48.42%	159	108	157	51	90	44	51.7%	9.0%	92.4%	101.4	LUCKY
	_Vs Division	6	3	3	0	0	0	0	0	19	16	3	6	0.500	19	35	54	0	0	6	4	8	1	212	59	63	60	30	211	69	40	153	11	4	36.36%	18	2	88.89%	1	144	279	51.61%	142	257	55.25%	46	95	48.42%	159	108	157	51	90	44	51.7%	9.0%	92.4%	101.4	LUCKY
	_Vs Conference	6	3	3	0	0	0	0	0	19	16	3	6	0.500	19	35	54	0	0	6	4	8	1	212	59	63	60	30	211	69	40	153	11	4	36.36%	18	2	88.89%	1	144	279	51.61%	142	257	55.25%	46	95	48.42%	159	108	157	51	90	44	51.7%	9.0%	92.4%	101.4	LUCKY
	_Since Last GM Reset	6	3	3	0	0	0	0	0	19	16	3	6	0.500	19	35	54	0	0	6	4	8	1	212	59	63	60	30	211	69	40	153	11	4	36.36%	18	2	88.89%	1	144	279	51.61%	142	257	55.25%	46	95	48.42%	159	108	157	51	90	44	51.7%	9.0%	92.4%	101.4	LUCKY
	Total	6	3	3	0	0	0	0	0	19	16	3	6	0.500	19	35	54	0	0	6	4	8	1	212	59	63	60	30	211	69	40	153	11	4	36.36%	18	2	88.89%	1	144	279	51.61%	142	257	55.25%	46	95	48.42%	159	108	157	51	90	44	51.7%	9.0%	92.4%	101.4	LUCKY

	Puck Time
Offensive Zone	26
Neutral Zone	15
Defensive Zone	26

	Puck Time
Offensive Zone Start	279
Neutral Zone Start	95
Defensive Zone Start	257

	Puck Time
With Puck	34
Without Puck	33

	Faceoffs
Faceoffs Won	332
Faceoffs Lost	299

	Team Average Shots after	League Average Shots after
1st Period	9.8	10.69
2nd Period	20.3	21.35
3rd Period	30.3	32.03
Overtime	35.3	32.64

Goals in	Team Average Goals after	League Average Goals after
1st Period	1.0	1.08
2nd Period	1.7	2.13
3rd Period	3.0	2.97
Overtime	3.2	3.07


Even Strenght Goal	14
PP Goal	4
PK Goal	1
Empty Net Goal	0

	Home	Away
Win	1	2
Lost	2	1
Overtime Lost	0	0


PP Attempt	11
PP Goal	4
PK Attempt	18
PK Goal Against	2

	Home
Shots For	35.3
Shots Against	35.2
Goals For	3.2
Goals Against	2.7
Hits	25.5
Shots Blocked	11.5
Pim	6.7