Final
SEA4
CBJ2

Aug
27
Blue JacketsColumbus Blue Jackets
7-3-4, 18pts · 2nd in Group B
Player Stats
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
# 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
1William NylanderBlue JacketsBlue Jackets88LW/RW1871421900661175411.48%217.3924600001042.42%3300001.3400
2Morgan RiellyBlue JacketsBlue Jackets0D18412162803927122114.81%1923.102460001110.00%000000.7700
3Matthew TkachukBlue JacketsBlue Jackets19LW/RW186915180406517479.23%319.81246000160044.83%2900000.8412
4Mikael GranlundBlue JacketsBlue Jackets0C1831215700215315355.66%017.4213400061048.40%37400000.9600
5Nathan MacKinnonBlue JacketsBlue Jackets29C/RW185813020278021576.25%419.7014500052049.36%39300000.7302
6David PastrnakBlue JacketsBlue Jackets88RW1810313-8801077174512.99%317.8943700000048.28%2900000.8112
7Tony DeAngeloBlue JacketsBlue Jackets77D18279-1180201661212.50%2018.2513400018000.00%000000.5500
8Max PaciorettyBlue JacketsBlue Jackets67LW184591120215310327.55%217.0321300000037.50%2400000.5900
9Colton ParaykoBlue JacketsBlue Jackets55D18448112019165825.00%3023.2200000059100.00%000000.3800
10Phillip DanaultBlue JacketsBlue Jackets24C/LW18538420203283215.63%416.92123000200045.93%24600000.5300
11Esa LindellBlue JacketsBlue Jackets23D18257016028133715.38%2819.1100000070000.00%000000.4100
12Frederick GaudreauBlue JacketsBlue Jackets89C/RW18235-5004255208.00%414.92000000311051.10%27200000.3700
13Adam LarssonBlue JacketsBlue Jackets6D1805541404114380.00%2817.2800001162000.00%000000.3200
14Tanner JeannotBlue JacketsBlue Jackets0LW/RW182354255603211186.25%515.34011000171036.84%1900000.3600
15Logan O'ConnorBlue JacketsBlue Jackets25RW18123140712178.33%68.4100010173100.00%500000.4000
16Austin WatsonBlue JacketsBlue Jackets0C/LW/RW18022060199550.00%15.05000000130040.00%500000.4400
17Ben ChiarotBlue JacketsBlue Jackets8D1811242752176314.29%1916.1100000046000.00%000000.1400
18Lars EllerBlue JacketsBlue Jackets20C180111208125100.00%18.26000011720047.53%26300000.1300
Team Total or Average324589915725164104116041674219.60%17916.401629451235159147.93%169200000.5926
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
1Marc-Andre FleuryBlue JacketsBlue Jackets1710340.9212.6896401435440110.6676171322
2John GibsonBlue JacketsBlue Jackets30100.9331.88128004600000.0000117000
Team Total or Average2010440.9222.58109201476040110.66761818322
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 JacketsHurricanes2110000075220.50071219003220642130130662020483266.67%10190.00%125352847.92%29158449.83%10522347.09%48334515251155.6%10.9%92.4%103.4LUCKY
2Blue JacketsJets2200000073441.00071421003220522117140872227422150.00%100100.00%025352847.92%29158449.83%10522347.09%41275114261266.7%13.5%96.6%110.0LUCKY
3Blue JacketsCanadiens20000200810-220.50081523002330922931284651712465360.00%6266.67%025352847.92%29158449.83%10522347.09%53374414271338.5%8.7%84.6%93.3Unlucky
4Blue JacketsSabres2200000081741.00081220012510721829250682112413266.67%60100.00%025352847.92%29158449.83%10522347.09%51354214261385.7%11.1%98.5%109.6LUCKY
5Blue JacketsBlues2110000064220.50061117104020582322130722018425120.00%9188.89%025352847.92%29158449.83%10522347.09%44294816271262.5%10.3%94.4%104.8LUCKY
6Blue JacketsOilers2000011055030.7505712000132701726255612210489111.11%50100.00%025352847.92%29158449.83%10522347.09%49334915261344.4%7.1%91.8%98.9DULL
7Blue JacketsGolden Knights20100001510-510.2505611002210682521223671720457228.57%10460.00%025352847.92%29158449.83%10522347.09%49344817261333.3%7.4%85.1%92.4Unlucky
_Vs Division14630031146388180.643467712311161514247615417614012486139119312341235.29%56885.71%125352847.92%29158449.83%10522347.09%3392323301081869153.1%9.7%92.2%101.8LUCKY
_Vs Conference14630031146388180.643467712311161514247615417614012486139119312341235.29%56885.71%125352847.92%29158449.83%10522347.09%3392323301081869153.1%9.7%92.2%101.8LUCKY
_Since Last GM Reset14630031146388180.643467712311161514247615417614012486139119312341235.29%56885.71%125352847.92%29158449.83%10522347.09%3392323301081869153.1%9.7%92.2%101.8LUCKY
Total14630031146388180.643467712311161514247615417614012486139119312341235.29%56885.71%125352847.92%29158449.83%10522347.09%3392323301081869153.1%9.7%92.2%101.8LUCKY

Puck Time
Offensive Zone 24
Neutral Zone 13
Defensive Zone 23
Puck Time
Offensive Zone Start 528
Neutral Zone Start 223
Defensive Zone Start 584
Puck Time
With Puck 30
Without Puck 30
Faceoffs
Faceoffs Won 649
Faceoffs Lost 686
Team Average Shots after League Average Shots after
1st Period 11.010.69
2nd Period 23.621.35
3rd Period 33.632.03
Overtime 34.432.64
Goals in Team Average Goals after League Average Goals after
1st Period 1.11.08
2nd Period 2.22.13
3rd Period 3.22.97
Overtime 3.43.07
Even Strenght Goal 32
PP Goal 12
PK Goal 1
Empty Net Goal 1
Home Away
Win 43
Lost 03
Overtime Lost 31
PP Attempt 34
PP Goal 12
PK Attempt 56
PK Goal Against 8
Home
Shots For 34.0
Shots Against 34.7
Goals For 3.3
Goals Against 2.7
Hits 22.3
Shots Blocked 9.9
Pim 8.5