Blue JacketsColumbus Blue Jackets
9-9-0, 18pts · 1st in Eastern Conference
Player Stats
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# 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
1Aleksander BarkovBlue JacketsBlue Jackets16C/LW18818268402679204810.13%322.:.45202000222052.03%54200001.2700
2Mika ZibanejadBlue JacketsBlue Jackets93C/RW1831417340217014314.29%321.:.2604400070054.14%49500000.8800
3Claude GirouxBlue JacketsBlue Jackets28C/LW/RW1889174201554124314.81%521.:.07112000112059.55%8900100.8900
4Neal PionkBlue JacketsBlue Jackets4D185101531404728101417.86%3223.:.2312300024000.00%000000.7100
5Patrick KaneBlue JacketsBlue Jackets88RW187714-120857144312.28%019.:.2913400003129.17%2400000.8000
6Alex OvechkinBlue JacketsBlue Jackets8LW/RW178513-2403078214610.26%319.:.4702200001031.03%2900000.7700
7Mattias EkholmBlue JacketsBlue Jackets14D1801111111530204180.00%2422.:.4002200030000.00%000000.5400
8Chris KreiderBlue JacketsBlue Jackets20LW/RW186410-7802547103312.77%115.:.3122400001054.29%3500000.7200
9Brandon TanevBlue JacketsBlue Jackets73LW/RW18448020454043110.00%318.:.32000000410051.52%3300000.4800
10Jaccob SlavinBlue JacketsBlue Jackets74D18246640171731811.76%3822.:.4110101137000.00%000000.2900
11Jordan StaalBlue JacketsBlue Jackets11C/LW18336-520264013247.50%215.:.58101011330051.61%37200000.4200
12Parker KellyBlue JacketsBlue Jackets17C/LW18246-39513247188.33%312.:.00000101200058.06%9300000.5600
13Devon ToewsBlue JacketsBlue Jackets7D17055-8201121760.00%2821.:.5300000026000.00%000000.2700
14Cole CaufieldBlue JacketsBlue Jackets13LW/RW90441409293120.00%217.:.1801100010036.36%1100000.5100
15Matt RoyBlue JacketsBlue Jackets3D1813411002892511.11%1818.:.1300000023000.00%000000.2400
16Kevin BahlBlue JacketsBlue Jackets89D18134-41403391611.11%2416.:.2900000012010.00%000000.2700
17Garnet HathawayBlue JacketsBlue Jackets19LW/RW1502201353111550.00%207.:.3100000090037.50%1600000.3500
18Marc GatcombBlue JacketsBlue Jackets61C/RW8101-120251520.00%105.:.5200000000066.67%600000.4300
19Benoit-Olivier GroulxBlue JacketsMonsters (CBJ)24C/LW4000-10011020.00%002.:.5400000000054.55%1100000.0000
20Carson SoucyBlue JacketsBlue Jackets9D11000-10036130.00%204.:.050000000000.00%100000.0000
21Kaedan KorczakBlue JacketsBlue Jackets6D900000031210.00%003.:.020000000000.00%100000.0000
Team Total or Average32059110169-5111154236451544109.15%19417:30917261233049252.38%174700100.6000
Filter Tips
PriorityTypeDescription
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
10textAny text entered in the filter will match text found within the column
# Goalie Name Team NameGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Lukas DostalBlue JacketsBlue Jackets1887290.2%2.9499921495020000.0%0180120
2Jake AllenBlue JacketsBlue Jackets610089.4%2.98141007660000.0%0018000
Team Total or Average2497290.1%2.95114021565680000.00001818120
Filter Tips
PriorityTypeDescription
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
10textAny 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
1Blue JacketsPenguins642000002320380.66723446701895123266836914187633912316318.75%11190.91%040978352.23%35367352.45%15930252.65%15310413745824251.3%9.9%89.3%99.2FUN
2Blue JacketsDevils743000002517880.57125457000888124772786730239754217815426.67%19289.47%140978352.23%35367352.45%15930252.65%186126176581045258.3%10.1%92.9%103.0LUCKY
3Blue JacketsPanthers514000001119-820.2001121320026301675568440142563212316212.50%15286.67%040978352.23%35367352.45%15930252.65%1248110537703534.6%6.6%86.6%93.2Unlucky
_Vs Division138500000483711160.6154889137011617132479138161136444261388130131722.58%30390.00%140978352.23%35367352.45%15930252.65%3402313131031879554.7%10.0%91.3%101.3LUCKY
_Vs Conference18990000059563180.500591101690118231626461932291804456819411342447919.15%45588.89%140978352.23%35367352.45%15930252.65%46431341914125713049.5%9.1%90.1%99.3FUN
_Since Last GM Reset18990000059563180.500591101690118231626461932291804456819411342447919.15%45588.89%140978352.23%35367352.45%15930252.65%46431341914125713049.5%9.1%90.1%99.3FUN
Total18990000059563180.500591101690118231626461932291804456819411342447919.15%45588.89%140978352.23%35367352.45%15930252.65%46431341914125713049.5%9.1%90.1%99.3FUN

Puck Time
Offensive Zone 25
Neutral Zone 14
Defensive Zone 23
Puck Time
Offensive Zone Start 783
Neutral Zone Start 302
Defensive Zone Start 673
Puck Time
With Puck 32
Without Puck 30
Faceoffs
Faceoffs Won 921
Faceoffs Lost 837
Team Average Shots after League Average Shots after
1st Period 10.710.69
2nd Period 23.421.35
3rd Period 33.432.03
Overtime 35.932.64
Goals in Team Average Goals after League Average Goals after
1st Period 1.01.08
2nd Period 2.32.13
3rd Period 3.22.97
Overtime 3.33.07
Even Strenght Goal 49
PP Goal 9
PK Goal 1
Empty Net Goal 0
Home Away
Win 54
Lost 54
Overtime Lost 00
PP Attempt 47
PP Goal 9
PK Attempt 45
PK Goal Against 5
Home
Shots For 35.9
Shots Against 31.6
Goals For 3.3
Goals Against 3.1
Hits 23.6
Shots Blocked 10.8
Pim 6.3