Blues

GP: 27 | W: 15 | L: 10 | OTL: 2 | P: 32
GF: 68 | GA: 68 | PP%: 19.23% | PK%: 81.31%
DG: Martin Raby | Morale : 55 | Moyenne d'Équipe : 75
Prochain matchs #356 vs Golden Knights
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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
1Patrice BergeronX99.006442839172928491888086888288804460860
2Evgenii DadonovX100.005941879165908788607981637555555361820
3Craig SmithX100.006342858076849479696576667570625161790
4Max PaciorettyX100.007743828277919374616771647275706661790
5Derick BrassardX100.007143818374899477886573707378696861760
6Kevin FialaX100.005941858265849576506474697555558561760
7Pavel BuchnevichX100.006441868173829075587067607054526561740
8Chris KunitzX100.007343777370799870625663757188741761730
9Troy BrouwerXX100.007544727482829368715757706580652961710
10Mark LetestuX100.006441827366809668835559786972612661700
11Nicolas DeslauriersX100.009143787284758771654964717060605561690
12Brock NelsonX100.006143747381829869785569647265586661680
13Marco ScandellaX100.006842897980949875305755856768615861760
14Aaron EkbladX100.006545797984949571306167797562699261750
15Deryk EngellandX100.007342896880859675305955846771632461750
16John KlingbergX100.006242898974949880308860716762585561750
17Nick HoldenX100.007941866984838973305554826564613461740
18Joel EdmundsonX100.007444817084858575305259837058587161730
Rayé
1Josh AndersonX100.007743797684889173705371697556556123690
2Trent Frederic (R)X100.005941776086654258675561606150504523600
3Luke SchennX100.009442836684778367305052756278697123720
MOYENNE D'ÉQUIPE99.95704282777785907456626573706762545674
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
1Connor Hellebuyck100.00949797869593969394918860775561880
2Keith Kinkaid100.00788187828586838484767557683661780
Rayé
1Ken Appleby100.00766770868788858889767250634423770
MOYENNE D'ÉQUIPE100.0083828585898988888981785669454881
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jack Capuano55757478805868USA5121,000,000$


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
1Patrice BergeronBluesC2714193322204758134509310.45%2070626.1836917920002881054.87%9553618000.9304000333
2Evgenii DadonovBluesRW27916257100333312336707.32%1160622.4636922920002921053.45%583412000.8214000214
3Derick BrassardBluesC279716-5240523785265310.59%346617.285271371000133254.62%368186000.6911000312
4Craig SmithBluesRW277815-380383261254111.48%1149818.483588710114392046.88%32129000.6034000002
5Kevin FialaBluesLW274812-48033346626426.06%648718.0523510711011211042.86%212015000.4901000110
6Chris KunitzBluesLW275611120035285920318.47%438214.16000000110411045.45%33125000.5811000000
7Max PaciorettyBluesLW277411836050243882418.42%1554720.272025921014333150.94%53911000.4012000011
8John KlingbergBluesD2701010618028426732230.00%4976228.2504410102011095000.00%01629000.2600000010
9Aaron EkbladBluesD27167-318023282719133.70%2555120.43112362000062000.00%01416000.2501000010
10Marco ScandellaBluesD27257610034664418154.55%5076828.4612341020000100010.00%0325000.1800000010
11Pavel BuchnevichBluesRW27606140192355213710.91%233012.2500001000000141.67%1275000.3600000011
12Deryk EngellandBluesD27134-26020432014135.00%2354820.31011062000163010.00%0217000.1500000000
13Joel EdmundsonBluesD27033-560192311290.00%1932812.1800000000018000.00%017000.1801000000
14Mark LetestuBluesC2703318021282910170.00%932812.1800000000000049.43%17439000.1800000000
15Brock NelsonBluesC27011-720511196130.00%51706.31000100000180047.95%7342000.1211000000
16Nick HoldenBluesD27000-540172413590.00%1730611.360000000000000.00%0014000.0000000000
17Nicolas DeslauriersBluesLW27000-2201130000.00%0481.8100001000000057.14%700000.0000000000
18Troy BrouwerBluesLW/RW27000-68018616360.00%31415.2300001000000075.00%421000.0000000000
Stats d'équipe Total ou en Moyenne4866599164-1021405035438673215097.50%272798216.42203050938292351567912653.35%1790193201000.4182000091113
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
1Connor HellebuyckBlues27151020.9252.4516402067891374100.73719270542
Stats d'équipe Total ou en Moyenne27151020.9252.4516402067891374100.73719270542


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
Aaron EkbladBluesD211996-02-07No216 Lbs6 ft4NoNoNo7Contrat d'EntréePro & Farm7,500,000$7,500,000$4,852,941$No7,500,000$7,500,000$7,500,000$7,500,000$7,500,000$7,500,000$Lien
Brock NelsonBluesC251991-10-15No212 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm4,250,000$4,250,000$2,750,000$NoLien
Chris KunitzBluesLW381979-09-26No195 Lbs6 ft0NoNoNo1Sans RestrictionPro & Farm1,000,000$1,000,000$647,059$NoLien
Connor HellebuyckBluesG241993-05-19No207 Lbs6 ft4NoNoNo6Contrat d'EntréePro & Farm6,166,666$6,166,666$3,990,196$No6,166,666$6,166,666$6,166,666$6,166,666$6,166,666$Lien
Craig SmithBluesRW281989-09-05No208 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm4,250,000$4,250,000$2,750,000$No4,250,000$Lien
Derick BrassardBluesC301987-09-22No202 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm5,000,000$5,000,000$3,235,294$NoLien
Deryk EngellandBluesD351982-04-03No214 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm1,500,000$1,500,000$970,588$NoLien
Evgenii DadonovBluesRW281989-03-12No185 Lbs5 ft11NoNoNo2Sans RestrictionPro & Farm4,000,000$4,000,000$2,588,235$No4,000,000$Lien
Joel EdmundsonBluesD241993-06-28No215 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm3,000,000$3,000,000$1,941,176$NoLien
John KlingbergBluesD251992-08-14No177 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm4,250,000$4,250,000$2,750,000$No4,250,000$4,250,000$4,250,000$Lien
Josh AndersonBluesRW231994-05-07No221 Lbs6 ft3NoNoNo2Contrat d'EntréePro & Farm1,850,000$1,850,000$1,197,059$No1,850,000$Lien
Keith KinkaidBluesG281989-07-04No195 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm1,250,000$1,250,000$808,824$NoLien
Ken ApplebyBluesG221995-04-10No210 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm750,000$750,000$485,294$NoLien
Kevin FialaBluesLW211996-07-22No193 Lbs5 ft10NoNoNo1Contrat d'EntréePro & Farm863,333$863,333$558,627$NoLien
Luke SchennBluesD271989-11-02No229 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm1,250,000$1,250,000$808,824$NoLien
Marco ScandellaBluesD271990-02-23No208 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm4,000,000$4,000,000$2,588,235$No4,000,000$Lien
Mark LetestuBluesC321985-02-04No195 Lbs5 ft10NoNoNo1Sans RestrictionPro & Farm1,000,000$1,000,000$647,059$NoLien
Max PaciorettyBluesLW281988-11-20No206 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm4,500,000$4,500,000$2,911,765$NoLien
Nick HoldenBluesD301987-05-15No214 Lbs6 ft4NoNoNo2Sans RestrictionPro & Farm2,200,000$2,200,000$1,423,529$No2,200,000$Lien
Nicolas DeslauriersBluesLW261991-02-22No215 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm950,000$950,000$614,706$No950,000$Lien
Patrice BergeronBluesC321985-07-24No195 Lbs6 ft1NoNoNo4Sans RestrictionPro & Farm6,875,000$6,875,000$4,448,529$No6,875,000$6,875,000$6,875,000$Lien
Pavel BuchnevichBluesRW221995-04-17No191 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm925,000$925,000$598,529$NoLien
Trent FredericBluesC191998-02-11Yes203 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm750,000$750,000$485,294$NoLien
Troy BrouwerBluesLW/RW321985-08-17No215 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm750,000$750,000$485,294$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2426.96205 Lbs6 ft21.962,867,917$

Somme Salaire 1e Année Somme Salaire 2e Année Somme Salaire 3e Année Somme Salaire 4e Année Somme Salaire 5e Année
68,829,999$42,041,666$24,791,666$24,791,666$13,666,666$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Max PaciorettyPatrice BergeronEvgenii Dadonov40122
2Kevin FialaDerick BrassardCraig Smith30122
3Chris KunitzMark LetestuPavel Buchnevich20122
4Troy BrouwerBrock NelsonPatrice Bergeron10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marco ScandellaJohn Klingberg40122
2Deryk EngellandAaron Ekblad30122
3Nick HoldenJoel Edmundson20122
4Marco ScandellaJohn Klingberg10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Max PaciorettyPatrice BergeronEvgenii Dadonov60122
2Kevin FialaDerick BrassardCraig Smith40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marco ScandellaJohn Klingberg60122
2Deryk EngellandAaron Ekblad40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Patrice BergeronEvgenii Dadonov60122
2Craig SmithMax Pacioretty40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marco ScandellaJohn Klingberg60122
2Deryk EngellandAaron Ekblad40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Patrice Bergeron60122Marco ScandellaJohn Klingberg60122
2Evgenii Dadonov40122Deryk EngellandAaron Ekblad40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Patrice BergeronEvgenii Dadonov60122
2Craig SmithMax Pacioretty40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marco ScandellaJohn Klingberg60122
2Deryk EngellandAaron Ekblad40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Max PaciorettyPatrice BergeronEvgenii DadonovMarco ScandellaJohn Klingberg
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Max PaciorettyPatrice BergeronEvgenii DadonovMarco ScandellaJohn Klingberg
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nicolas Deslauriers, Pavel Buchnevich, Chris KunitzNicolas Deslauriers, Pavel BuchnevichChris Kunitz
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nick Holden, Joel Edmundson, Deryk EngellandNick HoldenJoel Edmundson, Deryk Engelland
Tirs de Pénalité
Patrice Bergeron, Evgenii Dadonov, Craig Smith, Max Pacioretty, Kevin Fiala
Gardien
#1 : Connor Hellebuyck, #2 : Keith Kinkaid


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
1Avalanche30300000311-82020000028-61010000013-200.00035800021083153038010724305510110.00%15193.33%037168853.92%38271553.43%20237953.30%573069295225
2Blackhawks321000001055110000003122110000074340.66710152500433011143244408832245614642.86%12375.00%037168853.92%38271553.43%20237953.30%663963274925
3Bruins11000000422110000004220000000000021.0004711003100331561203068154125.00%4175.00%037168853.92%38271553.43%20237953.30%2011218179
4Capitals11000000211000000000001100000021121.00022400200029105140369819300.00%40100.00%137168853.92%38271553.43%20237953.30%189239178
5Ducks2010001025-3000000000002010001025-320.50022400010264122032366202439400.00%12191.67%037168853.92%38271553.43%20237953.30%382050193516
6Flames22000000734110000004221100000031241.000791600241063192618057176365120.00%3166.67%037168853.92%38271553.43%20237953.30%402341183717
7Flyers2010001046-22010001046-20000000000020.500448001112501919115602324428112.50%12375.00%037168853.92%38271553.43%20237953.30%402145203919
8Jets22000000844110000005231100000032141.00081220003320742229230711814327228.57%7185.71%037168853.92%38271553.43%20237953.30%432441183517
9Kings2010010037-42010010037-40000000000010.25035800111072153027074251842700.00%9366.67%037168853.92%38271553.43%20237953.30%442442183418
10Oilers1000000112-11000000112-10000000000010.50012300010321711310329821300.00%4175.00%037168853.92%38271553.43%20237953.30%20924102010
11Panthers11000000532110000005320000000000021.00057120013103481214031126113266.67%30100.00%037168853.92%38271553.43%20237953.30%1912229177
12Predateurs3120000079-21010000023-12110000056-120.333710170034009638362209736266515426.67%13284.62%037168853.92%38271553.43%20237953.30%623263275428
13Senateurs21100000550110000003121010000024-220.5005914002210732326240732010358112.50%5180.00%037168853.92%38271553.43%20237953.30%452740163318
14Stars21000010752100000104311100000032141.00071017003211642422183692110351317.69%4250.00%137168853.92%38271553.43%20237953.30%422444193819
Total27121000131686801565001214040012650001028280320.5936899167002528128867270296300218912722165031042019.23%1072081.31%237168853.92%38271553.43%20237953.30%563311595254483243
_Since Last GM Reset27121000131686801565001214040012650001028280320.5936899167002528128867270296300218912722165031042019.23%1072081.31%237168853.92%38271553.43%20237953.30%563311595254483243
_Vs Conference2088001214851-31034001112428-410540001024231220.55048701180016219664819522822516661202160381781519.23%791581.01%137168853.92%38271553.43%20237953.30%417229441189357179
_Vs Division13660001035341623000101617-17430000019172140.538355287001314714281421411453432131104243591423.73%51982.35%137168853.92%38271553.43%20237953.30%273151281121229117

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2732W3689916786789127221650300
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
27121001316868
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
156501214040
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
126500102828
Derniers 10 Matchs
WLOTWOTL SOWSOL
720001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1042019.23%1072081.31%2
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
270296300212528128
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
37168853.92%38271553.43%20237953.30%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
563311595254483243


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
3 - 2018-10-1110Avalanche5Blues1LSommaire du Match
5 - 2018-10-1321Blues1Avalanche3LSommaire du Match
7 - 2018-10-1530Blues3Jets2WSommaire du Match
11 - 2018-10-1945Jets2Blues5WSommaire du Match
13 - 2018-10-2155Blackhawks1Blues3WSommaire du Match
15 - 2018-10-2367Blues3Stars2WSommaire du Match
19 - 2018-10-2779Blues2Predateurs4LSommaire du Match
22 - 2018-10-3092Avalanche3Blues1LSommaire du Match
24 - 2018-11-01103Predateurs3Blues2LSommaire du Match
27 - 2018-11-04117Blues6Blackhawks2WSommaire du Match
30 - 2018-11-07129Stars3Blues4WXXSommaire du Match
34 - 2018-11-11145Blues2Ducks1WXXSommaire du Match
36 - 2018-11-13151Flyers5Blues2LSommaire du Match
42 - 2018-11-19175Kings4Blues1LSommaire du Match
45 - 2018-11-22190Blues1Blackhawks2LSommaire du Match
46 - 2018-11-23198Kings3Blues2LXSommaire du Match
52 - 2018-11-29219Flyers1Blues2WXXSommaire du Match
54 - 2018-12-01228Blues2Senateurs4LSommaire du Match
56 - 2018-12-03237Blues3Predateurs2WSommaire du Match
60 - 2018-12-07246Flames2Blues4WSommaire du Match
64 - 2018-12-11265Blues2Capitals1WSommaire du Match
65 - 2018-12-12270Bruins2Blues4WSommaire du Match
71 - 2018-12-18292Oilers2Blues1LXXSommaire du Match
73 - 2018-12-20303Blues0Ducks4LSommaire du Match
76 - 2018-12-23315Panthers3Blues5WSommaire du Match
78 - 2018-12-25325Blues3Flames1WSommaire du Match
82 - 2018-12-29340Senateurs1Blues3WSommaire du Match
86 - 2019-01-02356Blues-Golden Knights-
88 - 2019-01-04366Jets-Blues-
90 - 2019-01-06375Blues-Oilers-
92 - 2019-01-08383Blues-Penguins-
94 - 2019-01-10390Avalanche-Blues-
97 - 2019-01-13402Blues-Flyers-
99 - 2019-01-15415Oilers-Blues-
103 - 2019-01-19427Blues-Predateurs-
105 - 2019-01-21437Blues-Blue Jackets-
106 - 2019-01-22442Jets-Blues-
110 - 2019-01-26456Blues-Jets-
112 - 2019-01-28463Blues-Canadiens-
113 - 2019-01-29470Devils-Blues-
116 - 2019-02-01480Blues-Jets-
119 - 2019-02-04493Blues-Kings-
121 - 2019-02-06500Islanders-Blues-
125 - 2019-02-10516Blues-Sharks-
126 - 2019-02-11523Flames-Blues-
129 - 2019-02-14537Blues-Panthers-
131 - 2019-02-16544Blues-Islanders-
132 - 2019-02-17549Golden Knights-Blues-
137 - 2019-02-22567Canadiens-Blues-
140 - 2019-02-25585Blues-Avalanche-
142 - 2019-02-27594Avalanche-Blues-
146 - 2019-03-03611Lightning-Blues-
149 - 2019-03-06626Blues-Stars-
151 - 2019-03-08633Blues-Lightning-
152 - 2019-03-09641Blue Jackets-Blues-
156 - 2019-03-13657Blues-Golden Knights-
158 - 2019-03-15664Stars-Blues-
160 - 2019-03-17672Blues-Bruins-
162 - 2019-03-19687Predateurs-Blues-
166 - 2019-03-23698Blues-Blackhawks-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
168 - 2019-03-25706Blues-Devils-
170 - 2019-03-27717Sharks-Blues-
172 - 2019-03-29725Blues-Sharks-
174 - 2019-03-31734Blues-Devils-
176 - 2019-04-02743Sharks-Blues-
178 - 2019-04-04752Blues-Kings-
180 - 2019-04-06763Blues-Flames-
182 - 2019-04-08768Ducks-Blues-
184 - 2019-04-10779Blues-Maple Leafs-
187 - 2019-04-13791Ducks-Blues-
189 - 2019-04-15800Blues-Oilers-
193 - 2019-04-19813Blues-Flyers-
194 - 2019-04-20818Penguins-Blues-
199 - 2019-04-25834Blues-Avalanche-
201 - 2019-04-27840Capitals-Blues-
208 - 2019-05-04864Golden Knights-Blues-
213 - 2019-05-09887Stars-Blues-
215 - 2019-05-11897Blues-Stars-
217 - 2019-05-13912Blackhawks-Blues-
222 - 2019-05-18934Blackhawks-Blues-
230 - 2019-05-26957Maple Leafs-Blues-
236 - 2019-06-01979Predateurs-Blues-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2Niveau 3Niveau 4Luxe
Capacité de l'Aréna60005000200040001000
Prix des Billets100603525200
Assistance87,67771,34328,85058,69414,279
Attendance PCT97.42%95.12%96.17%97.82%95.19%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
26 17390 - 96.61% 1,617,544$24,263,157$18000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des CoachsValeur du Cap Salarial Spécial
24,645,852$ 68,829,999$ 68,521,666$ 0$ 0$
Cap Salarial Par JourCap salarial à ce jourTaxe de Luxe TotaleJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
68,829,999$ 24,292,968$ 0$ 24 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
42,056,139$ 154 293,403$ 45,184,062$

Total de l'Équipe Éstimé
Dépenses de la Saison ÉstiméesCap Salarial de la Saison ÉstiméCompte Bancaire ActuelCompte Bancaire Projeté
46,434,225$ 68,829,999$ 16,104,442$ 11,726,356$



Charte de Profondeur

Ailier GaucheCentreAilier Droit
Max PaciorettyAGE:28PO:66OV:79
Kevin FialaAGE:21PO:85OV:76
Chris KunitzAGE:38PO:17OV:73
Troy BrouwerAGE:32PO:29OV:71
Austin WatsonAGE:25PO:79OV:69
Nicolas DeslauriersAGE:26PO:55OV:69
Jordan MartinookAGE:25PO:66OV:67
Pierre-Edouard BellemareAGE:32PO:26OV:67
Patrice BergeronAGE:32PO:44OV:86
Derick BrassardAGE:30PO:68OV:76
Mark LetestuAGE:32PO:26OV:70
Brock NelsonAGE:25PO:66OV:68
*Trent FredericAGE:19PO:45OV:60
Evgenii DadonovAGE:28PO:53OV:82
Craig SmithAGE:28PO:51OV:79
Pavel BuchnevichAGE:22PO:65OV:74
Troy BrouwerAGE:32PO:29OV:71
Josh AndersonAGE:23PO:61OV:69
Miikka SalomakiAGE:24PO:69OV:64

Défense #1Défense #2Gardien
Marco ScandellaAGE:27PO:58OV:76
Aaron EkbladAGE:21PO:92OV:75
John KlingbergAGE:25PO:55OV:75
Deryk EngellandAGE:35PO:24OV:75
Nick HoldenAGE:30PO:34OV:74
Joel EdmundsonAGE:24PO:71OV:73
Luke SchennAGE:27PO:71OV:72
Slater KoekkoekAGE:23PO:84OV:67
Matt GrzelcykAGE:23PO:62OV:67
Connor HellebuyckAGE:24PO:55OV:88
Keith KinkaidAGE:28PO:36OV:78
Ken ApplebyAGE:22PO:44OV:77

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
Alexander AlexeyevBlues201840
Brett HowdenBlues201627
Eeli TolvanenBlues201730
Erik BrannstromBlues201715
Grant MismashBlues2018112
Jacob Bernard-DockerBlues201820
Jayden HalbgewachsBlues201888

Choix au Repêchage

Année R1R2R3R4R5
3STL STL STL STL STL
4STL STL STL STL STL
5STL STL STL STL STL
6STL STL STL STL STL
7STL STL STL STL STL



[2018-10-06 19:49:56] - Troy Brouwer was added to Blues.
[2018-10-05 21:40:45] - Mark Letestu was added to Blues.
[2018-10-01 23:41:05] - Chris Kunitz was added to Blues.
[2018-09-12 22:17:03] - Matt Hendricks was released.
[2018-09-12 22:17:03] - Blues paid 0 $ to release Matt Hendricks.
[2018-09-12 22:16:58] - Michael Frolik was released.
[2018-09-12 22:16:58] - Blues paid 0 $ to release Michael Frolik.
[2018-09-12 22:09:54] - Henrik Sedin was released.
[2018-09-12 22:09:54] - Blues paid 0 $ to release Henrik Sedin.
[2018-09-12 22:09:50] - Daniel Sedin was released.
[2018-09-12 22:09:50] - Blues paid 0 $ to release Daniel Sedin.
[2018-08-29 21:47:00] - Trent Frederic was added to Blues.
[2018-08-29 20:49:39] - Grant Mismash has been added to Blues.
[2018-08-29 20:37:12] - Jayden Halbgewachs has been added to Blues.
[2018-08-29 20:23:42] - Trent Frederic has been added to Blues.
[2018-08-19 21:53:22] - Alexander Alexeyev has been added to Blues.
[2018-08-19 21:36:43] - Jacob Bernard-Docker has been added to Blues.
[2018-06-08 22:56:16] - Blues was eliminated at round 2 of year 1.
[2018-05-31 22:42:24] - Wolves was eliminated at round 1 of year 1.
[2018-05-11 21:00:05] - New Record for Team's Most Hits (28) in 1 Game for Blues!
[2018-04-30 22:27:14] - New Record for Team's Most Goals (8) in 1 Game for Blues!



[2018-12-10 20:52:22] Wolves lines for next game are empty. Current rosters/lines are not erased.
[2018-12-07 22:26:01] Blues lines for next game are empty. Current rosters/lines are not erased.
[2018-12-06 22:34:13] Wolves lines for next game are empty. Current rosters/lines are not erased.
[2018-12-05 21:03:43] Both Blues and Wolves lines for next game are empty. Current rosters/lines are not erased.
[2018-12-04 23:44:28] Blues lines for next game are empty. Current rosters/lines are not erased.
[2018-12-03 21:39:01] Wolves lines for next game are empty. Current rosters/lines are not erased.
[2018-12-03 21:37:56] Both Blues and Wolves lines for next game are empty. Current rosters/lines are not erased.
[2018-11-30 21:13:00] Blues lines for next game are empty. Current rosters/lines are not erased.
[2018-11-29 22:36:57] Wolves lines for next game are empty. Current rosters/lines are not erased.
[2018-11-27 22:49:19] Wolves lines for next game are empty. Current rosters/lines are not erased.
[2018-11-27 22:48:48] Blues lines for next game are empty. Current rosters/lines are not erased.
[2018-11-26 20:42:15] Blues lines for next game are empty. Current rosters/lines are not erased.
[2018-11-23 23:34:37] Wolves lines for next game are empty. Current rosters/lines are not erased.
[2018-11-22 22:42:51] Blues lines for next game are empty. Current rosters/lines are not erased.
[2018-11-20 21:24:28] Wolves lines for next game are empty. Current rosters/lines are not erased.
[2018-11-20 21:23:07] Blues lines for next game are empty. Current rosters/lines are not erased.
[2018-11-19 21:55:42] Blues lines for next game are empty. Current rosters/lines are not erased.
[2018-11-16 22:19:02] Both Blues and Wolves lines for next game are empty. Current rosters/lines are not erased.
[2018-11-15 22:24:52] Wolves lines for next game are empty. Current rosters/lines are not erased.



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
227121000131686801565001214040012650001028280326899167002528128867270296300218912722165031042019.23%1072081.31%237168853.92%38271553.43%20237953.30%563311595254483243
Total Saison Régulière27121000131686801565001214040012650001028280326899167002528128867270296300218912722165031042019.23%1072081.31%237168853.92%38271553.43%20237953.30%563311595254483243