Columbus Blue Jackets

GP: 59 | W: 33 | L: 23 | OTL: 3 | P: 69
GF: 188 | GA: 181 | PP%: 19.18% | PK%: 83.81%
DG: Patrick Auger | Morale : 65 | Moyenne d'Équipe : 79
Prochain matchs #943 vs Ottawa Senators
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Astuces sur les Filtres (Anglais seulement)
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
# 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 TA SP
1David PastrnakXX98.00815585968290949657919389558078170840
2Evgeni DadonovXX97.20705596928888919550898991558078167830
3Ryan Nugent-HopkinsXX98.00645587918686909085858887558080178810
4Chris KreiderX100.00965583929191878761828080558284160800
5Alex Galchenyuk (A)XXX100.00705587938285879071857980557586163790
6Kyle TurrisX100.00705583908585869088887777558182138790
7Jonathan DrouinXXX100.00765590958180888977877377558073177780
8Zach HymanXXX100.00935586807881878562807588558078161770
9Phillip DanaultX100.00785577848585848489797181557370159750
10Marian Gaborik (C)XX100.00705580868282807950717770559192170740
11Matt NietoXX100.00705581837580807960687583557574176730
12Brendan LeipsicXX100.00725577827271758064796872557669177710
13Matt DumbaX100.00885587948894889425897494558180152840
14Mattias EkholmX100.00805585919194959225807098558280177840
15Nate SchmidtX100.00735597908291739225886595558280158810
16Marco ScandellaX100.00835588848693838625736590558279177800
17Travis HamonicX100.00835573888788878525676190558381176800
18Ian ColeX100.00855573768882878525736685558480164770
Rayé
MOYENNE D'ÉQUIPE99.6178558488848686885481758555807916779
Astuces sur les Filtres (Anglais seulement)
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
# Nom du Gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Braden Holtby98.0085859088868884878786559089151850
2Jaroslav Halak100.0083878986818482868485558887141830
Rayé
MOYENNE D'ÉQUIPE99.008486908784868387868655898814684
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Bob Boughner77828384756076CAN4751,000,000$


Astuces sur les Filtres (Anglais seulement)
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
# Nom du Joueur Nom de l'ÉquipePOS 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 FL FT S1 S2 S3
1Evgeni DadonovColumbus Blue JacketsLW/RW59273865610039962146318412.62%17129221.91512175321100072126133.33%9300111.0126000656
2David PastrnakColumbus Blue JacketsLW/RW5727336074751341182267416211.95%11108719.084711511970001703239.47%11400011.1012001374
3Ryan Nugent-HopkinsColumbus Blue JacketsC/LW59212849102210291311474110514.29%6126221.3957123619800031434349.17%120400000.7815200152
4Alex GalchenyukColumbus Blue JacketsC/LW/RW552027471317524951413410514.18%5101318.434913261820001284447.28%86300000.9311001325
5Mattias EkholmColumbus Blue JacketsD5911324375315857797377111.34%91138023.4051116551870001199100.00%000000.6200102051
6Nate SchmidtColumbus Blue JacketsD5843943-729554768725404.60%92136023.4511213461940000200000.00%000000.6300010112
7Matt DumbaColumbus Blue JacketsD511223354400907396306312.50%68116222.78841257187000067320.00%000000.6000000200
8Zach HymanColumbus Blue JacketsC/LW/RW621420341227566641334810410.53%890714.6313412570000551343.81%10500000.7500010124
9Kyle TurrisColumbus Blue JacketsC59102333-1241029111113401048.85%3108918.463811261840000323049.89%132100000.6100011111
10Jonathan DrouinColumbus Blue JacketsC/LW/RW591219310235289213025859.23%788515.01371023113000003047.14%43700000.7026100202
11Marco ScandellaColumbus Blue JacketsD6182129-449151025958153813.79%76119119.5331426890111166010.00%000000.4900201020
12Chris KreiderColumbus Blue JacketsLW5791827473515071141481056.38%799317.4413424178000072142.86%7700000.5412010222
13Ian ColeColumbus Blue JacketsD5851419-35810843245194111.11%5195916.5423520111000058100.00%000000.4000010012
14Phillip DanaultColumbus Blue JacketsC5912719-71357213582245114.63%596416.3501122500001690052.84%123200100.3902000120
15Travis HamonicColumbus Blue JacketsD5931215-5555105453212229.38%6897916.60000090000165000.00%000000.3100010010
16Marian GaborikColumbus Blue JacketsLW/RW56606-480233244123113.64%562911.2500003000012127.27%3300000.1900000110
17Matt NietoColumbus Blue JacketsLW/RW59426-1213512295213247.69%54868.250000000021260045.45%4400000.2501010001
18Jake VirtanenMonsters (Clb)RW30123-8200168193135.26%21735.7800001000000040.00%1000000.3500000000
19Brendan LeipsicColumbus Blue JacketsC/LW57033-13801526208260.00%23175.5600000000000040.11%35900000.1900000000
20Dylan StromeMonsters (Clb)C4011000248020.00%05614.0900002000040029.17%7200000.3500000000
21Madison BoweyMonsters (Clb)D3000200101100.00%0196.520000000000000.00%000000.0000000000
22Nick CousinsMonsters (Clb)C2000000000100.00%0105.080000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne10832063625681589105116013741886573137610.92%5291822316.8345881334572138011161710331848.11%596400220.62825676243732
Astuces sur les Filtres (Anglais seulement)
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
# Nom du Gardien Nom de l'ÉquipeGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Braden HoltbyColumbus Blue Jackets53292130.9023.0730322315515830310.75024527731
2Jaroslav HalakColumbus Blue Jackets184710.9043.2289401484980000.66731149110
Stats d'équipe Total ou en Moyenne71332840.9023.1039262420320810310.741276356841


Astuces sur les Filtres (Anglais seulement)
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
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Alex GalchenyukColumbus Blue JacketsC/LW/RW221994-02-11No198 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm2,690,000$2,690,000$699,096$No
Braden HoltbyColumbus Blue JacketsG271989-09-15No217 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm6,500,000$6,500,000$1,689,266$No
Brendan LeipsicColumbus Blue JacketsC/LW221994-05-18No165 Lbs5 ft9NoNoNo1Contrat d'EntréePro & Farm500,000$500,000$129,944$No
Chris KreiderColumbus Blue JacketsLW251991-04-30No226 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm3,500,000$3,500,000$909,605$No
David PastrnakColumbus Blue JacketsLW/RW201996-05-25No167 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm900,000$900,000$233,898$No
Evgeni DadonovColumbus Blue JacketsLW/RW271989-03-12No185 Lbs5 ft10NoNoNo1Avec RestrictionPro & Farm5,000,000$5,000,000$1,299,435$No
Ian ColeColumbus Blue JacketsD271989-02-21No219 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm2,500,000$2,500,000$649,718$No
Jaroslav HalakColumbus Blue JacketsG311985-05-13No186 Lbs5 ft11NoNoNo2Sans RestrictionPro & Farm3,500,000$3,500,000$909,605$No
Jonathan DrouinColumbus Blue JacketsC/LW/RW211995-03-28No186 Lbs5 ft11NoNoNo1Contrat d'EntréePro & Farm900,000$900,000$233,898$No
Kyle TurrisColumbus Blue JacketsC271989-08-14No191 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm1,000,000$1,000,000$259,887$No
Marco ScandellaColumbus Blue JacketsD261990-02-23No205 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm2,500,000$2,500,000$649,718$No
Marian GaborikColumbus Blue JacketsLW/RW341982-02-14No204 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm880,024$880,024$228,707$No
Matt DumbaColumbus Blue JacketsD221994-07-24No189 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm3,500,000$3,500,000$909,605$No
Matt NietoColumbus Blue JacketsLW/RW241992-11-04No190 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm500,000$500,000$129,944$No
Mattias EkholmColumbus Blue JacketsD261990-05-23No204 Lbs6 ft4NoNoNo3Avec RestrictionPro & Farm5,000,000$5,000,000$1,299,435$No
Nate SchmidtColumbus Blue JacketsD251991-07-15No185 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm2,500,000$2,500,000$649,718$No
Phillip DanaultColumbus Blue JacketsC231993-02-23No201 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm900,000$900,000$233,898$No
Ryan Nugent-HopkinsColumbus Blue JacketsC/LW231993-04-11No190 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm2,500,000$2,500,000$649,718$No
Travis HamonicColumbus Blue JacketsD261990-08-15No217 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm2,500,000$2,500,000$649,718$No
Zach HymanColumbus Blue JacketsC/LW/RW241992-06-09No197 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm1,000,000$1,000,000$259,887$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2025.10196 Lbs6 ft01.852,438,501$

Somme Salaire 1e Année Somme Salaire 2e Année Somme Salaire 3e Année Somme Salaire 4e Année Somme Salaire 5e Année
48,770,024$27,880,024$12,380,024$3,500,000$0$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Evgeni DadonovRyan Nugent-HopkinsDavid Pastrnak36023
2Chris KreiderKyle TurrisAlex Galchenyuk31113
3Jonathan DrouinPhillip DanaultZach Hyman26122
4Matt NietoBrendan LeipsicMarian Gaborik7122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt DumbaMattias Ekholm35122
2Nate SchmidtMarco Scandella35122
3Travis HamonicIan Cole25122
4Matt DumbaNate Schmidt5023
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Evgeni DadonovRyan Nugent-HopkinsDavid Pastrnak60005
2Chris KreiderKyle TurrisAlex Galchenyuk40005
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt DumbaNate Schmidt60113
2Ian ColeMattias Ekholm40113
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Phillip DanaultMatt Nieto60131
2Zach HymanEvgeni Dadonov40131
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nate SchmidtMattias Ekholm60140
2Matt DumbaTravis Hamonic40140
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Phillip Danault60140Nate SchmidtMattias Ekholm60140
2Zach Hyman40140Matt DumbaTravis Hamonic40140
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Ryan Nugent-HopkinsDavid Pastrnak60122
2Kyle TurrisEvgeni Dadonov40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt DumbaMattias Ekholm60122
2Nate SchmidtMarco Scandella40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Evgeni DadonovRyan Nugent-HopkinsDavid PastrnakNate SchmidtMatt Dumba
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Evgeni DadonovRyan Nugent-HopkinsDavid PastrnakNate SchmidtMattias Ekholm
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Alex Galchenyuk, Ryan Nugent-Hopkins, Evgeni DadonovAlex Galchenyuk, Evgeni DadonovDavid Pastrnak
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nate Schmidt, Matt Dumba, Mattias EkholmIan ColeMarco Scandella, Mattias Ekholm
Tirs de Pénalité
Jonathan Drouin, Evgeni Dadonov, Ryan Nugent-Hopkins, Phillip Danault, Alex Galchenyuk
Gardien
#1 : Braden Holtby, #2 : Jaroslav Halak


Astuces sur les Filtres (Anglais seulement)
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
LigueDomicileVisiteur
# 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
1Anaheim Ducks2020000039-61010000036-31010000003-300.00035800111045112014079184345700.00%13192.31%0994205348.42%986210646.82%45595647.59%473248142310
2Buffalo Sabres21000001541210000015410000000000030.7505914001310621930124561019407228.57%80100.00%0994205348.42%986210646.82%45595647.59%564144132412
3Calgary Flames10001000431100010004310000000000021.000471100021125414613858205120.00%40100.00%0994205348.42%986210646.82%45595647.59%2517237147
4Carolina Hurricanes31200000810-21010000026-42110000064220.333816240024207418263008317265312216.67%13376.92%0994205348.42%986210646.82%45595647.59%664576233617
5Chicago Blackhawks21100000752110000003031010000045-120.50071320013220552319130511410449222.22%5180.00%0994205348.42%986210646.82%45595647.59%503643132512
6Colorado Avalanche201010005501010000023-11000100032120.500510150011214811181727919505410440.00%15286.67%0994205348.42%986210646.82%45595647.59%473151142412
7Dallas Stars2110000067-11010000014-31100000053220.500691500321056151922077171845400.00%9188.89%0994205348.42%986210646.82%45595647.59%433052132311
8Detroit Red Wings31100001911-2110000003212010000169-330.500913220032409830283948518385813215.38%6350.00%0994205348.42%986210646.82%45595647.59%775469223819
9Florida Panthers3300000012661100000021122000000105561.0001223350064209026392508825168111218.18%8275.00%0994205348.42%986210646.82%45595647.59%735268213719
10Los Angeles Kings22000000945110000004131100000053241.0009182700234059231719059193139800.00%7185.71%0994205348.42%986210646.82%45595647.59%432851152512
11Minnesota Wild211000006601010000035-21100000031220.5006121800510030101190852426437228.57%13284.62%0994205348.42%986210646.82%45595647.59%382357162411
12Montreal Canadiens2020000036-31010000034-11010000002-200.00036910120057152616058181227700.00%6183.33%0994205348.42%986210646.82%45595647.59%473248142411
13Nashville Predators11000000532110000005320000000000021.0005101500122022868029212179444.44%60100.00%0994205348.42%986210646.82%45595647.59%2416227126
14New Jersey Devils3120000079-22020000025-31100000054120.333714210041207633202301052419718112.50%6183.33%0994205348.42%986210646.82%45595647.59%654576213719
15New York Islanders22000000826110000006151100000021141.0008142200134064252118043116255120.00%30100.00%0994205348.42%986210646.82%45595647.59%493545142413
16New York Rangers3120000068-22020000048-41100000020220.33361117013210752334180863718521000.00%9188.89%0994205348.42%986210646.82%45595647.59%725069213818
17Ottawa Senators11000000633110000006330000000000021.00069150015004212102002552165120.00%10100.00%0994205348.42%986210646.82%45595647.59%2719196126
18Philadelphia Flyers300000211312110000010321200000111010050.83313213400524479351922131073457713266.67%12375.00%0994205348.42%986210646.82%45595647.59%684586234019
19Phoenix Coyotes22000000835110000005321100000030341.00081321013320662122230561412387114.29%6183.33%0994205348.42%986210646.82%45595647.59%493545132512
20Pittsburgh Penguins11000000422000000000001100000042221.000471100211039111315029914215120.00%70100.00%0994205348.42%986210646.82%45595647.59%2518226125
21San Jose Sharks1010000038-5000000000001010000038-500.00036900300039141312033111422500.00%7357.14%0994205348.42%986210646.82%45595647.59%2416237125
22St. Louis Blues20100010611-51010000017-61000001054120.500681400212263142325691301646010.00%4250.00%0994205348.42%986210646.82%45595647.59%442954142612
23Tampa Bay Lightning31200000610-41010000025-32110000045-120.3336814014110972834350823122451417.14%11190.91%0994205348.42%986210646.82%45595647.59%725070213718
24Toronto Maple Leafs32100000862211000006511100000021140.6678132100503011040304007019286513323.08%9277.78%0994205348.42%986210646.82%45595647.59%816059203819
Total592723020431881817301215010119196-52915801032978512690.5851883305181474555310174656259957238185251657311922194219.18%2103483.81%0994205348.42%986210646.82%45595647.59%143210021408425741370
26Vancouver Canucks1010000025-31010000025-30000000000000.00023500110022868042111220100.00%6183.33%0994205348.42%986210646.82%45595647.59%2014277115
27Vegas Golden Knights220000001064110000004221100000064241.000101626004330682323220451512358337.50%6266.67%0994205348.42%986210646.82%45595647.59%564138132513
28Washington Capitals42100010181352110000010822100001085360.750183452007282153514850813742289122627.27%90100.00%0994205348.42%986210646.82%45595647.59%1077888274925
29Winnipeg Jets1010000014-3000000000001010000014-300.000123000100321110110341748400.00%10100.00%0994205348.42%986210646.82%45595647.59%2417227125
_Since Last GM Reset592723020431881817301215010119196-52915801032978512690.5851883305181474555310174656259957238185251657311922194219.18%2103483.81%0994205348.42%986210646.82%45595647.59%143210021408425741370
_Vs Conference3617130003311310211187900011545401810400022594811430.59711319831112453233611163663783632910543003057161352417.78%1081784.26%0994205348.42%986210646.82%45595647.59%891630844258453229
_Vs Division19870003164568926000102730-3106100021372611230.6056411718101241522656019618117621590174168384651320.00%59886.44%0994205348.42%986210646.82%45595647.59%456319464138239120

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
5969L318833051817461852516573119214
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
5927232043188181
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
30121510119196
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2915810329785
Derniers 10 Matchs
WLOTWOTL SOWSOL
361000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2194219.18%2103483.81%0
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
5625995723874555310
Mises en Jeu
Gagnées en Zone OffensiveTotal en Zone Offensive% Gagnées en Zone Offensive Gagnées en Zone DéfensiveTotal en Zone Défensive% Gagnées en Zone DéfensiveGagnées en Zone NeutreTotal en Zone Neutre% Gagnées en Zone Neutre
994205348.42%986210646.82%45595647.59%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
143210021408425741370


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
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
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
2 - 2018-09-069Columbus Blue Jackets2Detroit Red Wings4LSommaire du Match
3 - 2018-09-0715Carolina Hurricanes6Columbus Blue Jackets2LSommaire du Match
7 - 2018-09-1137Colorado Avalanche3Columbus Blue Jackets2LR3Sommaire du Match
9 - 2018-09-1348Columbus Blue Jackets5Florida Panthers3WSommaire du Match
10 - 2018-09-1469Columbus Blue Jackets1Tampa Bay Lightning0WSommaire du Match
15 - 2018-09-1990Philadelphia Flyers2Columbus Blue Jackets3WXXSommaire du Match
17 - 2018-09-21103Chicago Blackhawks0Columbus Blue Jackets3WSommaire du Match
20 - 2018-09-24122Phoenix Coyotes3Columbus Blue Jackets5WSommaire du Match
22 - 2018-09-26143Columbus Blue Jackets5St. Louis Blues4WXXSommaire du Match
24 - 2018-09-28150Buffalo Sabres2Columbus Blue Jackets4WSommaire du Match
27 - 2018-10-01171Detroit Red Wings2Columbus Blue Jackets3WSommaire du Match
29 - 2018-10-03188Columbus Blue Jackets3San Jose Sharks8LSommaire du Match
31 - 2018-10-05198Columbus Blue Jackets5Los Angeles Kings3WSommaire du Match
32 - 2018-10-06207Columbus Blue Jackets0Anaheim Ducks3LSommaire du Match
34 - 2018-10-08215Dallas Stars4Columbus Blue Jackets1LSommaire du Match
37 - 2018-10-11241Columbus Blue Jackets5Washington Capitals3WSommaire du Match
38 - 2018-10-12245New York Rangers5Columbus Blue Jackets3LSommaire du Match
40 - 2018-10-14262Columbus Blue Jackets5Dallas Stars3WSommaire du Match
43 - 2018-10-17278Florida Panthers1Columbus Blue Jackets2WSommaire du Match
45 - 2018-10-19293Columbus Blue Jackets4Carolina Hurricanes1WSommaire du Match
47 - 2018-10-21315Columbus Blue Jackets2Toronto Maple Leafs1WSommaire du Match
50 - 2018-10-24337Toronto Maple Leafs2Columbus Blue Jackets4WSommaire du Match
51 - 2018-10-25354Columbus Blue Jackets4Pittsburgh Penguins2WSommaire du Match
53 - 2018-10-27362Columbus Blue Jackets4Detroit Red Wings5LXXSommaire du Match
56 - 2018-10-30383Minnesota Wild5Columbus Blue Jackets3LSommaire du Match
58 - 2018-11-01403Columbus Blue Jackets2New York Islanders1WSommaire du Match
61 - 2018-11-04417Calgary Flames3Columbus Blue Jackets4WXSommaire du Match
63 - 2018-11-06434Columbus Blue Jackets5Philadelphia Flyers4WXXSommaire du Match
65 - 2018-11-08447Washington Capitals5Columbus Blue Jackets8WSommaire du Match
68 - 2018-11-11468Vancouver Canucks5Columbus Blue Jackets2LSommaire du Match
70 - 2018-11-13480Los Angeles Kings1Columbus Blue Jackets4WSommaire du Match
72 - 2018-11-15495Anaheim Ducks6Columbus Blue Jackets3LSommaire du Match
74 - 2018-11-17512Vegas Golden Knights2Columbus Blue Jackets4WSommaire du Match
77 - 2018-11-20533New Jersey Devils3Columbus Blue Jackets1LSommaire du Match
79 - 2018-11-22554Columbus Blue Jackets5Philadelphia Flyers6LXXSommaire du Match
80 - 2018-11-23562Columbus Blue Jackets5New Jersey Devils4WSommaire du Match
81 - 2018-11-24572Columbus Blue Jackets2New York Rangers0WSommaire du Match
82 - 2018-11-25580Toronto Maple Leafs3Columbus Blue Jackets2LSommaire du Match
85 - 2018-11-28602Ottawa Senators3Columbus Blue Jackets6WSommaire du Match
89 - 2018-12-02631Columbus Blue Jackets2Carolina Hurricanes3LSommaire du Match
90 - 2018-12-03637Columbus Blue Jackets5Florida Panthers2WSommaire du Match
93 - 2018-12-06664Columbus Blue Jackets3Tampa Bay Lightning5LSommaire du Match
95 - 2018-12-08672Nashville Predators3Columbus Blue Jackets5WSommaire du Match
97 - 2018-12-10698Columbus Blue Jackets3Washington Capitals2WXXSommaire du Match
98 - 2018-12-11700New York Rangers3Columbus Blue Jackets1LSommaire du Match
100 - 2018-12-13711New Jersey Devils2Columbus Blue Jackets1LSommaire du Match
103 - 2018-12-16735Montreal Canadiens4Columbus Blue Jackets3LSommaire du Match
104 - 2018-12-17744Columbus Blue Jackets3Minnesota Wild1WSommaire du Match
110 - 2018-12-23774Buffalo Sabres2Columbus Blue Jackets1LXXSommaire du Match
112 - 2018-12-25780Columbus Blue Jackets1Winnipeg Jets4LSommaire du Match
114 - 2018-12-27789St. Louis Blues7Columbus Blue Jackets1LSommaire du Match
117 - 2018-12-30811Columbus Blue Jackets3Colorado Avalanche2WXR3Sommaire du Match
119 - 2019-01-01823Columbus Blue Jackets3Phoenix Coyotes0WSommaire du Match
121 - 2019-01-03850Columbus Blue Jackets6Vegas Golden Knights4WSommaire du Match
124 - 2019-01-06865Washington Capitals3Columbus Blue Jackets2LSommaire du Match
126 - 2019-01-08878New York Islanders1Columbus Blue Jackets6WSommaire du Match
128 - 2019-01-10894Columbus Blue Jackets4Chicago Blackhawks5LSommaire du Match
130 - 2019-01-12910Tampa Bay Lightning5Columbus Blue Jackets2LSommaire du Match
131 - 2019-01-13921Columbus Blue Jackets0Montreal Canadiens2LSommaire du Match
134 - 2019-01-16943Columbus Blue Jackets-Ottawa Senators-
135 - 2019-01-17946San Jose Sharks-Columbus Blue Jackets-
138 - 2019-01-20971Pittsburgh Penguins-Columbus Blue Jackets-
140 - 2019-01-22986Philadelphia Flyers-Columbus Blue Jackets-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
142 - 2019-01-241001Edmonton Oilers-Columbus Blue Jackets-
143 - 2019-01-251010Winnipeg Jets-Columbus Blue Jackets-
145 - 2019-01-271024Columbus Blue Jackets-New Jersey Devils-
147 - 2019-01-291041Columbus Blue Jackets-Pittsburgh Penguins-
149 - 2019-01-311050Pittsburgh Penguins-Columbus Blue Jackets-
151 - 2019-02-021069Columbus Blue Jackets-New York Islanders-
152 - 2019-02-031074Boston Bruins-Columbus Blue Jackets-
155 - 2019-02-061093Carolina Hurricanes-Columbus Blue Jackets-
156 - 2019-02-071100Columbus Blue Jackets-Boston Bruins-
159 - 2019-02-101123Columbus Blue Jackets-Calgary Flames-
161 - 2019-02-121140Columbus Blue Jackets-Edmonton Oilers-
164 - 2019-02-151167Columbus Blue Jackets-Vancouver Canucks-
166 - 2019-02-171179New York Islanders-Columbus Blue Jackets-
168 - 2019-02-191191Montreal Canadiens-Columbus Blue Jackets-
170 - 2019-02-211208Columbus Blue Jackets-Nashville Predators-
171 - 2019-02-221216Columbus Blue Jackets-Buffalo Sabres-
173 - 2019-02-241231Boston Bruins-Columbus Blue Jackets-
176 - 2019-02-271256Columbus Blue Jackets-New York Rangers-
177 - 2019-02-281266Columbus Blue Jackets-Ottawa Senators-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2Niveau 3Niveau 4Luxe
Capacité de l'Aréna60005000200040001000
Prix des Billets100603520200
Assistance174,329144,17557,589113,47928,841
Attendance PCT96.85%96.12%95.98%94.57%96.14%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
11 17280 - 96.00% 1,084,104$32,523,113$18000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des CoachsValeur du Cap Salarial Spécial
36,556,996$ 48,770,024$ 24,600,000$ 0$ 0$
Cap Salarial Par JourCap salarial à ce jourTaxe de Luxe TotaleJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
48,770,024$ 35,701,231$ 0$ 20 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
11,925,141$ 46 281,187$ 12,934,602$

Total de l'Équipe Éstimé
Dépenses de la Saison ÉstiméesCap Salarial de la Saison ÉstiméCompte Bancaire ActuelCompte Bancaire Projeté
13,031,055$ 48,770,024$ 175,139,043$ 174,033,129$



Charte de Profondeur

Ailier GaucheCentreAilier Droit
David PastrnakAGE:20PO:1OV:84
Evgeni DadonovAGE:27PO:1OV:83
Ryan Nugent-HopkinsAGE:23PO:1OV:81
Chris KreiderAGE:25PO:1OV:80
Alex GalchenyukAGE:22PO:1OV:79
Jonathan DrouinAGE:21PO:1OV:78
Zach HymanAGE:24PO:1OV:77
Marian GaborikAGE:34PO:1OV:74
Matt NietoAGE:24PO:1OV:73
Brendan LeipsicAGE:22PO:1OV:71
*Oskar LindblomAGE:20PO:1OV:67
Daniel AudetteAGE:20PO:1OV:58
Nick TarnaskyAGE:32PO:1OV:58
Tim BozonAGE:22PO:1OV:56
Lauri KorpikoskiAGE:30PO:1OV:54
Joshua WinquistAGE:23PO:1OV:52
*Olivier ArchambaultAGE:23PO:1OV:52
Ryan Nugent-HopkinsAGE:23PO:1OV:81
Alex GalchenyukAGE:22PO:1OV:79
Kyle TurrisAGE:27PO:1OV:79
Jonathan DrouinAGE:21PO:1OV:78
Zach HymanAGE:24PO:1OV:77
Phillip DanaultAGE:23PO:1OV:75
Brendan LeipsicAGE:22PO:1OV:71
Oscar LindbergAGE:25PO:1OV:70
*Dylan StromeAGE:19PO:1OV:69
Nick CousinsAGE:23PO:1OV:68
Chris KellyAGE:36PO:1OV:63
Zack StortiniAGE:31PO:1OV:58
*Colin WhiteAGE:19PO:1OV:56
Quinton HowdenAGE:24PO:1OV:56
*Matt BucklesAGE:21PO:1OV:55
*Emil PetterssonAGE:22PO:1OV:54
*Stephen MacAulayAGE:24PO:1OV:54
David PastrnakAGE:20PO:1OV:84
Evgeni DadonovAGE:27PO:1OV:83
Alex GalchenyukAGE:22PO:1OV:79
Jonathan DrouinAGE:21PO:1OV:78
Zach HymanAGE:24PO:1OV:77
Marian GaborikAGE:34PO:1OV:74
Matt NietoAGE:24PO:1OV:73
Jake VirtanenAGE:20PO:1OV:71
Nikita SoshnikovAGE:23PO:1OV:62
Daniel CatenacciAGE:23PO:1OV:58
Mike BrownAGE:31PO:1OV:58
Ryan HaggertyAGE:23PO:1OV:57
*Akim AliuAGE:27PO:1OV:55
Brandon AldersonAGE:24PO:1OV:54
Buddy RobinsonAGE:25PO:1OV:54
*Cody KunykAGE:26PO:1OV:54
*Zach O'BrienAGE:24PO:1OV:54
Mike SisloAGE:28PO:1OV:52

Défense #1Défense #2Gardien
Matt DumbaAGE:22PO:1OV:84
Mattias EkholmAGE:26PO:1OV:84
Nate SchmidtAGE:25PO:1OV:81
Marco ScandellaAGE:26PO:1OV:80
Travis HamonicAGE:26PO:1OV:80
Ian ColeAGE:27PO:1OV:77
Madison BoweyAGE:21PO:1OV:71
Ryan SproulAGE:24PO:1OV:66
Brian LashoffAGE:26PO:1OV:56
Ville PokkaAGE:22PO:1OV:56
Mike WeberAGE:29PO:1OV:55
Kyle BurroughsAGE:21PO:1OV:54
*Robin NorellAGE:21PO:1OV:54
*Jeremy RoyAGE:19PO:1OV:54
Will O'NeillAGE:28PO:1OV:54
Josiah DidierAGE:23PO:1OV:53
John NegrinAGE:27PO:1OV:53
*Brennan MenellAGE:19PO:1OV:53
Braden HoltbyAGE:27PO:1OV:85
Jaroslav HalakAGE:31PO:1OV:83
Jack CampbellAGE:25PO:1OV:70
Eamon McAdamAGE:22PO:1OV:65
Jeff MalcolmAGE:27PO:1OV:58
Marcus HogbergAGE:22PO:1OV:55
*Filip GustavssonAGE:18PO:1OV:54

Éspoirs

Astuces sur les Filtres (Anglais seulement)
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
Éspoir Nom de l'ÉquipeAnnée de Repêchage Choix Total Information Lien
Alexei LipanovColumbus Blue Jackets1380
Cal HeeterColumbus Blue Jackets
Carter HartColumbus Blue Jackets1231
Casey MittelstadtColumbus Blue Jackets136
David KaseColumbus Blue Jackets11178
Evan CormierColumbus Blue Jackets12172
Filip WesterlundColumbus Blue Jackets13109
Jake EvansColumbus Blue Jackets10157
Jake LeschyshynColumbus Blue Jackets1395
Jonah GadjovichColumbus Blue Jackets1359
Kasper BjorkqvistColumbus Blue Jackets12121
Leon GawankeColumbus Blue Jackets13171
Marcus HögbergColumbus Blue Jackets992

Choix au Repêchage

Année R1R2R3R4R5R6
14Clb Clb Clb Clb Clb
15Clb Clb Clb Clb
16Clb Clb Clb Clb
17Clb Clb Clb Chi Clb Clb Clb
18Clb Clb Clb Clb



[2019-02-02 19:22:44] - TRADE : From Phoenix Coyotes to Columbus Blue Jackets : Marco Scandella (80).
[2019-02-02 19:22:44] - TRADE : From Columbus Blue Jackets to Phoenix Coyotes : Nick Holden (79), Y:18-RND:2-Clb, Y:18-RND:3-Clb.
[2019-01-27 13:48:01] - Alex Galchenyuk has been selected as assistant for Columbus Blue Jackets.
[2019-01-27 13:48:01] - Unknown Player is no longer as assistant for Columbus Blue Jackets.
[2019-01-23 11:18:43] - TRADE : From Columbus Blue Jackets to Chicago Blackhawks : David Kampf (68), Jayce Hawryluk (55).
[2019-01-23 11:18:43] - TRADE : From Chicago Blackhawks to Columbus Blue Jackets : Zach Hyman (77), Y:17-RND:3-Chi.
[2019-01-02 20:45:49] - TRADE : From Columbus Blue Jackets to Calgary Flames : Jesse Puljujarvi (73), Mike Reilly (71), Y:15-RND:2-Chi.
[2019-01-02 20:45:49] - TRADE : From Calgary Flames to Columbus Blue Jackets : Kyle Turris (79).
[2018-12-08 15:10:25] - New Record for Team's Most Points (24) in 1 Game for Columbus Blue Jackets!
[2018-12-08 15:10:25] - New Record for Team's Most Assists (16) in 1 Game for Columbus Blue Jackets!
[2018-11-19 12:25:36] - TRADE : From Vegas Golden Knights to Columbus Blue Jackets : Jaroslav Halak (82).
[2018-11-19 12:25:36] - TRADE : From Columbus Blue Jackets to Vegas Golden Knights : Jacob Markstrom (85).
[2018-11-14 11:55:28] - TRADE : From Columbus Blue Jackets to Chicago Blackhawks : Alex Tuch (77), Ryan Dzingel (77), Nick Jensen (74).
[2018-11-14 11:55:28] - TRADE : From Chicago Blackhawks to Columbus Blue Jackets : Ryan Nugent-Hopkins (81), David Kampf (69), Y:15-RND:2-Chi.
[2018-09-29 10:53:20] - Team Name Change : Springfield Falcons changed name to Monsters
[2018-09-01 11:33:07] - Brennan Menell was added to Columbus Blue Jackets.
[2018-08-30 15:47:01] - TRADE : From Columbus Blue Jackets to Ottawa Senateurs : Brad Richardson.
[2018-08-30 15:46:50] - TRADE : From Columbus Blue Jackets to Boston Bruins : Andrej Sekera.
[2018-08-30 15:46:41] - TRADE : From Columbus Blue Jackets to Edmonton Oilers : Valtteri Filppula.
[2018-08-28 16:11:18] - TRADE : From Columbus Blue Jackets to Phoenix Coyotes : Dustin Tokarski.



[2019-02-10 10:44:03] Evgeni Dadonov from Columbus Blue Jackets is back from Left Foot Injury.
[2019-02-10 10:44:01] Game 878 - Evgeni Dadonov from Columbus Blue Jackets is injured (Left Foot) and is out for 1 days.
[2019-02-07 10:16:56] Successfully loaded Columbus Blue Jackets lines done with STHS Client - 3.1.6.6
[2019-02-07 10:16:56] Columbus Blue Jackets Email Address was changed to patauger1@gmail.com.
[2019-02-07 10:16:54] Jake Virtanen of Columbus Blue Jackets was sent down to farm.
[2019-02-03 22:03:54] Chris Kreider from Columbus Blue Jackets completes suspension
[2019-02-03 22:03:16] Successfully loaded Columbus Blue Jackets lines done with STHS Client - 3.1.6.6
[2019-02-03 22:03:16] Jake Virtanen of Columbus Blue Jackets was sent to pro.
[2019-02-02 19:22:44] TRADE : From Phoenix Coyotes to Columbus Blue Jackets : Marco Scandella (80).
[2019-02-02 19:22:44] TRADE : From Columbus Blue Jackets to Phoenix Coyotes : Nick Holden (79), Y:18-RND:2-Clb, Y:18-RND:3-Clb.
[2019-02-01 08:54:33] Game 811 - Chris Kreider from Columbus Blue Jackets suspended for 1 game(s)
[2019-02-01 08:51:44] Successfully loaded Columbus Blue Jackets lines done with STHS Client - 3.1.6.6
[2019-01-30 09:36:04] Ryan Sproul from Monsters is back from Broken Nose Injury.
[2019-01-28 18:06:45] Jake Virtanen from Monsters has scored a Hat Trick!
[2019-01-27 13:48:01] Successfully loaded Columbus Blue Jackets lines done with STHS Client - 3.1.6.6
[2019-01-24 17:30:42] Successfully loaded Columbus Blue Jackets lines done with STHS Client - 3.1.6.6
[2019-01-24 17:30:42] Jake Virtanen of Columbus Blue Jackets was sent down to farm.
[2019-01-23 11:18:43] TRADE : From Columbus Blue Jackets to Chicago Blackhawks : David Kampf (68), Jayce Hawryluk (55).
[2019-01-23 11:18:43] TRADE : From Chicago Blackhawks to Columbus Blue Jackets : Zach Hyman (77), Y:17-RND:3-Chi.
[2019-01-18 19:21:08] Successfully loaded Columbus Blue Jackets lines done with STHS Client - 3.1.6.6
[2019-01-18 19:21:08] Madison Bowey of Columbus Blue Jackets was sent down to farm.
[2019-01-17 17:48:37] Game 582 - Ryan Sproul from Monsters is injured (Broken Nose) and is out for 2 weeks.



Pas de Blessure ou de Suspension.


LigueDomicileVisiteur
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
13592723020431881817301215010119196-52915801032978512691883305181474555310174656259957238185251657311922194219.18%2103483.81%0994205348.42%986210646.82%45595647.59%143210021408425741370
Total Saison Régulière592723020431881817301215010119196-52915801032978512691883305181474555310174656259957238185251657311922194219.18%2103483.81%0994205348.42%986210646.82%45595647.59%143210021408425741370
Séries
1273400000181803120000078-1422000001110161835530054901845755657246676215924520.83%24579.17%010423045.22%13128446.13%4010637.74%158106180549345
1273400000181803120000078-1422000001110161835530054901845755657246676215924520.83%24579.17%010423045.22%13128446.13%4010637.74%158106180549345
Total Séries14680000036360624000001416-284400000222021236701060010818036811411013014492134124318481020.83%481079.17%020846045.22%26256846.13%8021237.74%31621236110918690