Columbus Blue Jackets

GP: 5 | W: 2 | L: 3 | OTL: 0 | P: 4
GF: 12 | GA: 16 | PP%: 22.73% | PK%: 75.00%
DG: Patrick Auger | Morale : 47 | Moyenne d'Équipe : N/A
Prochain matchs #90 vs Philadelphia Flyers
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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
1Evgeni DadonovXX100.0070559692888891955089899155807814900
2Alex GalchenyukXXX100.0070558793828587907185798055758614900
3Jesse PuljujarviX100.0080557788807880825068747355727214900
4Chris KreiderX100.0096558392919187876182808055828414900
5Alex TuchX100.0096558485858590876278758055787214900
6Marian Gaborik (C)XX100.0070558086828280795071777055919214900
7Matt NietoXX100.0070558183758080796068758355757414900
8Phillip DanaultX100.0078557784858584848979718155737014900
9Ryan DzingelXXX100.0081558688798581856274848255807714900
10Brendan LeipsicXX100.0072557782727175806479687255766914900
11David PastrnakXX100.0081558596829094965791938955807814900
12Jonathan DrouinXXX100.0076559095818088897787737755807314900
13Ian ColeX100.0085557376888287852573668555848014900
14Matt DumbaX100.0088558794889488942589749455818014900
15Nick Holden (A)X100.0091559682898588822571658755858514900
16Mattias EkholmX100.0080558591919495922580709855828014900
17Nate SchmidtX100.0073559790829173922588659555828014900
18Travis HamonicX100.0083557388878887852567619055838114900
Rayé
MOYENNE D'ÉQUIPE100.008055848884858587507974845580781490
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
1Jacob Markstrom100.008785908886888788878855848214900
Rayé
1Braden Holtby100.008585908886888487878655908914800
MOYENNE D'ÉQUIPE100.00868590888688868887875587861490
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
1Mattias EkholmColumbus Blue JacketsD523506037114418.18%710420.80112514000016100.00%000000.9600000020
2Jonathan DrouinColumbus Blue JacketsC/LW/RW5325020113131723.08%18116.26022114000001047.06%11900001.2300000100
3Matt DumbaColumbus Blue JacketsD5134-16013312458.33%313026.041121021000018000.00%000000.6100000000
4Ryan DzingelColumbus Blue JacketsC/LW/RW522412028112518.18%19018.171123140001100041.18%1700000.8800000010
5Evgeni DadonovColumbus Blue JacketsLW/RW5213-220162071910.00%111122.33202720000023000.00%300000.5400000000
6Nate SchmidtColumbus Blue JacketsD5033-2207105520.00%612725.47022420000019000.00%000000.4700000000
7Alex GalchenyukColumbus Blue JacketsC/LW/RW5112-120413104810.00%09218.46011120000030042.40%12500000.4300000000
8Ian ColeColumbus Blue JacketsD5022-140536240.00%58817.7701131300008000.00%000000.4500000000
9David PastrnakColumbus Blue JacketsLW/RW5022-1001811166180.00%010120.260114200000120022.22%900000.3900000000
10Chris KreiderColumbus Blue JacketsLW501114017311480.00%18116.36000214000010040.00%500000.2400000000
11Nick HoldenColumbus Blue JacketsD5011-1601242010.00%59318.62000000000240026.42%5300000.2100000000
12Phillip DanaultColumbus Blue JacketsC5011-120666470.00%07014.0500000000000045.98%8700000.2800000000
13Travis HamonicColumbus Blue JacketsD5101-1805741225.00%78016.0600000000015000.00%000000.2500000000
14Jesse PuljujarviColumbus Blue JacketsRW5000-100100130.00%0224.580000000000000.00%100000.0000000000
15Alex TuchColumbus Blue JacketsRW5000-120637270.00%26813.6800000000000033.33%600000.0000000000
16Marian GaborikColumbus Blue JacketsLW/RW5000-100149110.00%06813.720000000000000.00%400000.0000000000
17Matt NietoColumbus Blue JacketsLW/RW5000-100013000.00%0224.500000000000000.00%000000.0000000000
18Brendan LeipsicColumbus Blue JacketsC/LW5000-100321010.00%0224.5000000000000030.77%2600000.0000000000
Stats d'équipe Total ou en Moyenne90122234-14480105104147481028.16%39145816.20510154017700011542040.44%45500000.4700000130
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 Jackets52300.9113.2129901161800000.000050110
Stats d'équipe Total ou en Moyenne52300.9113.2129901161800000.000050110


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 Salaire Année 2 Salaire Année 3 Salaire Année 4 Salaire Année 5 Salaire Année 6 Salaire Année 7 Salaire Année 8 Salaire Année 9 Salaire Année 10 Link
Alex GalchenyukColumbus Blue JacketsC/LW/RW221994-02-11No198 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm2,690,000$2,690,000$2,492,429$No
Alex TuchColumbus Blue JacketsRW201996-05-10No225 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm900,000$900,000$833,898$No900,000$900,000$
Braden HoltbyColumbus Blue JacketsG271989-09-15No217 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm6,500,000$6,500,000$6,022,599$No
Brendan LeipsicColumbus Blue JacketsC/LW221994-05-18No165 Lbs5 ft9NoNoNo1Contrat d'EntréePro & Farm500,000$500,000$463,277$No
Chris KreiderColumbus Blue JacketsLW251991-04-30No226 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm3,500,000$3,500,000$3,242,938$No3,500,000$
David PastrnakColumbus Blue JacketsLW/RW201996-05-25No167 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm900,000$900,000$833,898$No
Evgeni DadonovColumbus Blue JacketsLW/RW271989-03-12No185 Lbs5 ft10NoNoNo1Avec RestrictionPro & Farm5,000,000$5,000,000$4,632,768$No
Ian ColeColumbus Blue JacketsD271989-02-21No219 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm2,500,000$2,500,000$2,316,384$No2,500,000$
Jacob MarkstromColumbus Blue JacketsG261990-01-31No196 Lbs6 ft6NoNoNo1Avec RestrictionPro & Farm5,000,000$5,000,000$4,632,768$No
Jesse PuljujarviColumbus Blue JacketsRW181998-05-07No203 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm900,000$900,000$833,898$No900,000$900,000$
Jonathan DrouinColumbus Blue JacketsC/LW/RW211995-03-28No186 Lbs5 ft11NoNoNo1Contrat d'EntréePro & Farm900,000$900,000$833,898$No
Marian GaborikColumbus Blue JacketsLW/RW341982-02-14No204 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm880,024$880,024$815,389$No880,024$880,024$
Matt DumbaColumbus Blue JacketsD221994-07-24No189 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm3,500,000$3,500,000$3,242,938$No3,500,000$3,500,000$3,500,000$
Matt NietoColumbus Blue JacketsLW/RW241992-11-04No190 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm500,000$500,000$463,277$No500,000$500,000$
Mattias EkholmColumbus Blue JacketsD261990-05-23No204 Lbs6 ft4NoNoNo3Avec RestrictionPro & Farm5,000,000$5,000,000$4,632,768$No5,000,000$5,000,000$
Nate SchmidtColumbus Blue JacketsD251991-07-15No185 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm2,500,000$2,500,000$2,316,384$No2,500,000$2,500,000$
Nick HoldenColumbus Blue JacketsD291987-05-14No210 Lbs6 ft4NoNoNo3Sans RestrictionPro & Farm2,500,000$2,500,000$2,316,384$No2,500,000$2,500,000$
Phillip DanaultColumbus Blue JacketsC231993-02-23No201 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm900,000$900,000$833,898$No
Ryan DzingelColumbus Blue JacketsC/LW/RW241992-08-03No188 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm1,000,000$1,000,000$926,554$No1,000,000$1,000,000$
Travis HamonicColumbus Blue JacketsD261990-08-15No217 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm2,500,000$2,500,000$2,316,384$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2024.40199 Lbs6 ft12.052,428,501$

Somme Salaire 1e Année Somme Salaire 2e Année Somme Salaire 3e Année Somme Salaire 4e Année Somme Salaire 5e Année
48,570,024$23,680,024$17,680,024$3,500,000$0$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Evgeni DadonovAlex GalchenyukDavid Pastrnak30023
2Chris KreiderJonathan DrouinRyan Dzingel30023
3Alex TuchPhillip DanaultMarian Gaborik30023
4Jesse PuljujarviBrendan LeipsicMatt Nieto10023
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt DumbaMattias Ekholm30122
2Nate SchmidtNick Holden30122
3Travis HamonicIan Cole25122
4Matt DumbaNate Schmidt15023
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Evgeni DadonovAlex GalchenyukDavid Pastrnak60005
2Chris KreiderJonathan DrouinRyan Dzingel40005
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt DumbaNate Schmidt60113
2Mattias EkholmIan Cole40113
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Nick HoldenEvgeni Dadonov60131
2Ryan DzingelDavid Pastrnak40140
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
2Ryan Dzingel40140Matt DumbaTravis Hamonic40140
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Alex GalchenyukDavid Pastrnak60122
2Jonathan DrouinEvgeni Dadonov40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt DumbaMattias Ekholm60122
2Nate SchmidtNick Holden40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Evgeni DadonovAlex GalchenyukDavid PastrnakMatt DumbaNate Schmidt
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
David PastrnakPhillip DanaultEvgeni DadonovMattias EkholmNick Holden
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Alex Galchenyuk, David Pastrnak, Phillip DanaultDavid Pastrnak, Phillip DanaultDavid Pastrnak
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Matt Dumba, Nate Schmidt, Nick HoldenTravis HamonicMatt Dumba, Ian Cole
Tirs de Pénalité
David Pastrnak, Phillip Danault, Jonathan Drouin, Evgeni Dadonov, Alex Galchenyuk
Gardien
#1 : , #2 : Jacob Markstrom


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
1Carolina Hurricanes1010000026-41010000026-40000000000000.00024600011030510150398816200.00%4250.00%07318040.56%8520641.26%266937.68%2115257125
2Colorado Avalanche1010000023-11010000023-10000000000000.00024600011021696051818283266.67%9188.89%07318040.56%8520641.26%266937.68%2013277126
3Detroit Red Wings1010000024-2000000000001010000024-200.0002350011004412161603266189111.11%3233.33%07318040.56%8520641.26%266937.68%2719207126
4Florida Panthers11000000532000000000001100000053221.000591400230034619903296276116.67%3166.67%07318040.56%8520641.26%266937.68%2317256115
5Tampa Bay Lightning11000000101000000000001100000010121.00012301100018765026810162150.00%50100.00%07318040.56%8520641.26%266937.68%1912288115
Total523000001216-42020000049-53210000087140.4001222340146201473660510180394810522522.73%24675.00%07318040.56%8520641.26%266937.68%11277126376029
_Since Last GM Reset523000001216-42020000049-53210000087140.4001222340146201473660510180394810522522.73%24675.00%07318040.56%8520641.26%266937.68%11277126376029
_Vs Conference422000001013-31010000026-43210000087140.500101828014510126305145012931307719315.79%15566.67%07318040.56%8520641.26%266937.68%926499304823
_Vs Division1010000026-41010000026-40000000000000.00024600011030510150398816200.00%4250.00%07318040.56%8520641.26%266937.68%2115257125

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
54W2122234147180394810501
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
52300001216
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
202000049
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
321000087
Derniers 10 Matchs
WLOTWOTL SOWSOL
230000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
22522.73%24675.00%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
36605104620
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
7318040.56%8520641.26%266937.68%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
11277126376029


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 Flyers-Columbus Blue Jackets-
17 - 2018-09-21103Chicago Blackhawks-Columbus Blue Jackets-
20 - 2018-09-24122Phoenix Coyotes-Columbus Blue Jackets-
22 - 2018-09-26143Columbus Blue Jackets-St. Louis Blues-
24 - 2018-09-28150Buffalo Sabres-Columbus Blue Jackets-
27 - 2018-10-01171Detroit Red Wings-Columbus Blue Jackets-
29 - 2018-10-03188Columbus Blue Jackets-San Jose Sharks-
31 - 2018-10-05198Columbus Blue Jackets-Los Angeles Kings-
32 - 2018-10-06207Columbus Blue Jackets-Anaheim Ducks-
34 - 2018-10-08215Dallas Stars-Columbus Blue Jackets-
37 - 2018-10-11241Columbus Blue Jackets-Washington Capitals-
38 - 2018-10-12245New York Rangers-Columbus Blue Jackets-
40 - 2018-10-14262Columbus Blue Jackets-Dallas Stars-
43 - 2018-10-17278Florida Panthers-Columbus Blue Jackets-
45 - 2018-10-19293Columbus Blue Jackets-Carolina Hurricanes-
47 - 2018-10-21315Columbus Blue Jackets-Toronto Maple Leafs-
50 - 2018-10-24337Toronto Maple Leafs-Columbus Blue Jackets-
51 - 2018-10-25354Columbus Blue Jackets-Pittsburgh Penguins-
53 - 2018-10-27362Columbus Blue Jackets-Detroit Red Wings-
56 - 2018-10-30383Minnesota Wild-Columbus Blue Jackets-
58 - 2018-11-01403Columbus Blue Jackets-New York Islanders-
61 - 2018-11-04417Calgary Flames-Columbus Blue Jackets-
63 - 2018-11-06434Columbus Blue Jackets-Philadelphia Flyers-
65 - 2018-11-08447Washington Capitals-Columbus Blue Jackets-
68 - 2018-11-11468Vancouver Canucks-Columbus Blue Jackets-
70 - 2018-11-13480Los Angeles Kings-Columbus Blue Jackets-
72 - 2018-11-15495Anaheim Ducks-Columbus Blue Jackets-
74 - 2018-11-17512Vegas Golden Knights-Columbus Blue Jackets-
77 - 2018-11-20533New Jersey Devils-Columbus Blue Jackets-
79 - 2018-11-22554Columbus Blue Jackets-Philadelphia Flyers-
80 - 2018-11-23562Columbus Blue Jackets-New Jersey Devils-
81 - 2018-11-24572Columbus Blue Jackets-New York Rangers-
82 - 2018-11-25580Toronto Maple Leafs-Columbus Blue Jackets-
85 - 2018-11-28602Ottawa Senators-Columbus Blue Jackets-
89 - 2018-12-02631Columbus Blue Jackets-Carolina Hurricanes-
90 - 2018-12-03637Columbus Blue Jackets-Florida Panthers-
93 - 2018-12-06664Columbus Blue Jackets-Tampa Bay Lightning-
95 - 2018-12-08672Nashville Predators-Columbus Blue Jackets-
97 - 2018-12-10698Columbus Blue Jackets-Washington Capitals-
98 - 2018-12-11700New York Rangers-Columbus Blue Jackets-
100 - 2018-12-13711New Jersey Devils-Columbus Blue Jackets-
103 - 2018-12-16735Montreal Canadiens-Columbus Blue Jackets-
104 - 2018-12-17744Columbus Blue Jackets-Minnesota Wild-
110 - 2018-12-23774Buffalo Sabres-Columbus Blue Jackets-
112 - 2018-12-25780Columbus Blue Jackets-Winnipeg Jets-
114 - 2018-12-27789St. Louis Blues-Columbus Blue Jackets-
117 - 2018-12-30811Columbus Blue Jackets-Colorado Avalanche-
119 - 2019-01-01823Columbus Blue Jackets-Phoenix Coyotes-
121 - 2019-01-03850Columbus Blue Jackets-Vegas Golden Knights-
124 - 2019-01-06865Washington Capitals-Columbus Blue Jackets-
126 - 2019-01-08878New York Islanders-Columbus Blue Jackets-
128 - 2019-01-10894Columbus Blue Jackets-Chicago Blackhawks-
130 - 2019-01-12910Tampa Bay Lightning-Columbus Blue Jackets-
131 - 2019-01-13921Columbus Blue Jackets-Montreal Canadiens-
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
Assistance10,9309,8053,7967,4691,835
Attendance PCT91.08%98.05%94.90%93.36%91.75%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
39 16918 - 93.99% 1,048,743$2,097,486$18000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des CoachsValeur du Cap Salarial Spécial
3,640,741$ 48,570,024$ 18,700,000$ 0$ 0$
Cap Salarial Par JourCap salarial à ce jourTaxe de Luxe TotaleJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
48,570,024$ 3,530,568$ 0$ 20 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
40,900,977$ 164 280,057$ 45,929,348$

Total de l'Équipe Éstimé
Dépenses de la Saison ÉstiméesCap Salarial de la Saison ÉstiméCompte Bancaire ActuelCompte Bancaire Projeté
46,233,066$ 48,570,024$ 177,813,446$ 172,481,357$



Charte de Profondeur

Ailier GaucheCentreAilier Droit
Evgeni DadonovAGE:27PO:1OV:0
Alex GalchenyukAGE:22PO:1OV:0
*Oskar LindblomAGE:20PO:1OV:0
*Jayce HawrylukAGE:21PO:1OV:0
Chris KreiderAGE:25PO:1OV:0
Marian GaborikAGE:34PO:1OV:0
Daniel AudetteAGE:20PO:1OV:0
Tim BozonAGE:22PO:1OV:0
Joshua WinquistAGE:23PO:1OV:0
*Olivier ArchambaultAGE:23PO:1OV:0
Matt NietoAGE:24PO:1OV:0
Nick TarnaskyAGE:32PO:1OV:0
Lauri KorpikoskiAGE:30PO:1OV:0
Ryan DzingelAGE:24PO:1OV:0
Brendan LeipsicAGE:22PO:1OV:0
David PastrnakAGE:20PO:1OV:0
Jonathan DrouinAGE:21PO:1OV:0
Alex GalchenyukAGE:22PO:1OV:0
*Dylan StromeAGE:19PO:1OV:0
Chris KellyAGE:36PO:1OV:0
*Colin WhiteAGE:19PO:1OV:0
*Matt BucklesAGE:21PO:1OV:0
*Emil PetterssonAGE:22PO:1OV:0
*Stephen MacAulayAGE:24PO:1OV:0
Nick CousinsAGE:23PO:1OV:0
Quinton HowdenAGE:24PO:1OV:0
Oscar LindbergAGE:25PO:1OV:0
Phillip DanaultAGE:23PO:1OV:0
Ryan DzingelAGE:24PO:1OV:0
Brendan LeipsicAGE:22PO:1OV:0
Zack StortiniAGE:31PO:1OV:0
Jonathan DrouinAGE:21PO:1OV:0
Evgeni DadonovAGE:27PO:1OV:0
Alex GalchenyukAGE:22PO:1OV:0
Brandon AldersonAGE:24PO:1OV:0
Daniel CatenacciAGE:23PO:1OV:0
Jesse PuljujarviAGE:18PO:1OV:0
Buddy RobinsonAGE:25PO:1OV:0
*Cody KunykAGE:26PO:1OV:0
Jake VirtanenAGE:20PO:1OV:0
Alex TuchAGE:20PO:1OV:0
Marian GaborikAGE:34PO:1OV:0
*Zach O'BrienAGE:24PO:1OV:0
Nikita SoshnikovAGE:23PO:1OV:0
*Akim AliuAGE:27PO:1OV:0
Matt NietoAGE:24PO:1OV:0
Mike SisloAGE:28PO:1OV:0
Mike BrownAGE:31PO:1OV:0
Ryan DzingelAGE:24PO:1OV:0
David PastrnakAGE:20PO:1OV:0
Jonathan DrouinAGE:21PO:1OV:0
Ryan HaggertyAGE:23PO:1OV:0

Défense #1Défense #2Gardien
Josiah DidierAGE:23PO:1OV:0
Kyle BurroughsAGE:21PO:1OV:0
Madison BoweyAGE:21PO:1OV:0
Brian LashoffAGE:26PO:1OV:0
Mike ReillyAGE:23PO:1OV:0
Ian ColeAGE:27PO:1OV:0
Matt DumbaAGE:22PO:1OV:0
*Robin NorellAGE:21PO:1OV:0
Nick HoldenAGE:29PO:1OV:0
John NegrinAGE:27PO:1OV:0
Mattias EkholmAGE:26PO:1OV:0
Nate SchmidtAGE:25PO:1OV:0
Nick JensenAGE:26PO:1OV:0
*Jeremy RoyAGE:19PO:1OV:0
Ryan SproulAGE:24PO:1OV:0
Travis HamonicAGE:26PO:1OV:0
*Brennan MenellAGE:19PO:1OV:0
Mike WeberAGE:29PO:1OV:0
Will O'NeillAGE:28PO:1OV:0
Ville PokkaAGE:22PO:1OV:0
Jack CampbellAGE:25PO:1OV:0
Braden HoltbyAGE:27PO:1OV:0
Marcus HogbergAGE:22PO:1OV:0
Eamon McAdamAGE:22PO:1OV:0
Jacob MarkstromAGE:26PO:1OV:0
*Filip GustavssonAGE:18PO:1OV:0
Jeff MalcolmAGE:27PO:1OV:0

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 Clb Clb Clb
18Clb Clb Clb Clb Clb Clb



[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.
[2018-08-25 10:15:54] - Columbus Blue Jackets hired Bob Boughner for 1 000 000 $ for 5 year(s).
[2018-08-25 10:15:44] - Columbus Blue Jackets fired Bob Hartley.
[2018-07-25 17:22:54] - Travis Brown has been deleted from Columbus Blue Jackets.
[2018-07-25 17:22:52] - Tom Nilsson has been deleted from Columbus Blue Jackets.
[2018-07-25 17:22:49] - Niklas Lundstrom has been deleted from Columbus Blue Jackets.
[2018-07-25 17:22:42] - Matt DeBlouw has been deleted from Columbus Blue Jackets.
[2018-07-25 17:22:31] - Martin Gernat has been deleted from Columbus Blue Jackets.
[2018-07-25 17:22:25] - Collin Olson has been deleted from Columbus Blue Jackets.
[2018-07-19 23:00:38] - Stephen MacAulay was added to Columbus Blue Jackets.
[2018-07-19 22:59:17] - Marcus Hogberg was added to Columbus Blue Jackets.
[2018-07-19 22:53:57] - Columbus Blue Jackets drafts Leon Gawanke as the #171 overall pick in the Entry Draft of year 13.
[2018-07-17 15:15:30] - Evgeni Dadonov was added to Columbus Blue Jackets.
[2018-07-16 20:16:14] - Zach O'Brien was added to Columbus Blue Jackets.
[2018-07-16 20:16:14] - Matt Buckles was added to Columbus Blue Jackets.
[2018-07-16 20:16:14] - Filip Gustavsson was added to Columbus Blue Jackets.
[2018-07-16 20:16:14] - Emil Pettersson was added to Columbus Blue Jackets.
[2018-07-16 20:16:14] - Dylan Strome was added to Columbus Blue Jackets.
[2018-07-16 20:16:14] - Olivier Archambault was added to Columbus Blue Jackets.
[2018-07-16 20:16:14] - Oskar Lindblom was added to Columbus Blue Jackets.
[2018-07-16 20:16:14] - Jeremy Roy was added to Columbus Blue Jackets.
[2018-07-16 20:16:14] - Colin White was added to Columbus Blue Jackets.



[2018-10-14 14:41:30] Braden Holtby from Columbus Blue Jackets is back from Exhaustion.
[2018-10-13 15:15:43] Braden Holtby from Columbus Blue Jackets injured (Exhaustion)
[2018-10-09 11:59:35] Last 7 Days Farm Star : 1 - Lukas Sedlak of Admirals (4-3-7) / 2 - Oscar Lindberg of Monsters (4-1-5) / 3 - Hudson Fasching of Eagles (2-3-5)
[2018-10-09 11:58:57] Successfully loaded Columbus Blue Jackets lines done with STHS Client - 3.1.3.0
[2018-10-08 12:10:20] Oscar Lindberg from Monsters has scored a Hat Trick!
[2018-10-04 17:10:57] Successfully loaded Columbus Blue Jackets lines done with STHS Client - 3.1.3.0
[2018-09-25 15:34:51] Ryan Donato from Lake Erie Monsters is back from Sore Right Knee Injury.
[2018-09-25 15:34:51] Game 153 - Ryan Donato from Lake Erie Monsters is injured (Sore Right Knee) and is out for the game.
[2018-09-18 09:14:45] Successfully loaded Columbus Blue Jackets lines done with STHS Client - 3.1.3.0
[2018-09-12 14:30:13] Auto Lines Farm Function has been run for Lake Erie Monsters.



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
13523000001216-42020000049-53210000087141222340146201473660510180394810522522.73%24675.00%07318040.56%8520641.26%266937.68%11277126376029
Total Saison Régulière523000001216-42020000049-53210000087141222340146201473660510180394810522522.73%24675.00%07318040.56%8520641.26%266937.68%11277126376029
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