Blues

GP: 67 | W: 38 | L: 24 | OTL: 5 | P: 81
GF: 187 | GA: 171 | PP%: 22.13% | PK%: 82.17%
DG: Martin Raby | Morale : 64 | Moyenne d'Équipe : 75
Prochain matchs #768 vs Ducks
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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
1Evgenii DadonovX97.005941879165908788607981637555555378820
2Craig SmithX99.006342858076849479696576667570625179790
3Max PaciorettyX100.007743828277919374616771647275706679790
4Derick BrassardX100.007143818374899477886573707378696879760
5Kevin FialaX100.005941858265849576506474697555558579760
6Chris KunitzX100.007343777370799870625663757188741779740
7Pavel BuchnevichX100.006441868173829075587067607054526579740
8Mark LetestuX100.006441827366809668835559786972612679710
9Troy BrouwerXX100.007544727482829368715757706580652979710
10Nicolas DeslauriersX100.009143787284758771654964717060605573690
11Brock NelsonX100.006143747381829869785569647265586679680
12Trent Frederic (R)X100.005941776086654258675561606150504520600
13Marco ScandellaX97.006842897980949875305755856768615879770
14Aaron EkbladX100.006545797984949571306167797562699279750
15Deryk EngellandX100.007342896880859675305955846771632479750
16John KlingbergX98.006242898974949880308860716762585579750
17Nick HoldenX100.007941866984838973305554826564613479740
18Joel EdmundsonX100.007444817084858575305259837058587179730
Rayé
1Patrice BergeronX99.006442839172928491888086888288804473860
2Austin WatsonX100.008448607281799577714765747458567940690
3Luke SchennX100.009442836684778367305052756278697120720
MOYENNE D'ÉQUIPE99.52704381777784907456616573706762557174
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 Hellebuyck97.00949797869593969394918860775573880
2Keith Kinkaid100.00788187828586838484767557683679780
Rayé
1Ken Appleby100.00766770868788858889767250634420770
MOYENNE D'ÉQUIPE99.0083828585898988888981785669455781
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 BergeronBluesC58244872-36601061263171141927.57%39149925.85818265419101131763054.39%20177532000.9609000366
2Evgenii DadonovBluesRW67333568-320077803289118210.06%37152122.711417315621310162266245.41%1859331010.89310000546
3Craig SmithBluesRW67222749416089772046112310.78%29126618.90713202716512371145141.98%814026000.7749000415
4Derick BrassardBluesC67222345-2500111981795911912.29%18119517.8410818311690001136354.92%10564217000.7523000522
5Kevin FialaBluesLW6717244112008762190701208.95%20121818.195813231642024543040.00%506230000.6702000432
6John KlingbergBluesD6733033112806410316477701.83%103184927.6011011212230225227000.00%04869000.3601000130
7Marco ScandellaBluesD6762026142008213512043485.00%113190828.49358162320003237120.00%0972000.2700000021
8Chris KunitzBluesLW671312256380816814052799.29%2195514.26000010112992042.55%943216000.5211000102
9Max PaciorettyBluesLW67131225080011671101266112.87%30134520.08426122131127833150.00%1101929000.3726000022
10Aaron EkbladBluesD6731619-464054766440304.69%63136020.3031451490110142000.00%03145000.2802000010
11Mark LetestuBluesC6751116822051738229516.10%2385712.79033017000000148.51%538916000.3700000001
12Pavel BuchnevichBluesRW67115167100535211445769.65%1183112.4000003000000228.57%281514000.3900000122
13Deryk EngellandBluesD67211130100521006034313.33%76142021.2112351580002161010.00%0450000.1800000000
14Brock NelsonBluesC67347-610031265625465.36%114907.32000100000450150.00%244145000.2922000001
15Joel EdmundsonBluesD67044-82404665369200.00%4681312.1400001000049000.00%0219000.1001000000
16Troy BrouwerBluesLW/RW67202-52003920286187.14%93555.3000003000001042.86%736000.1100000001
17Austin WatsonBluesLW61010202420050.00%0152.55000000001410100.00%100001.3100000000
18Nick HoldenBluesD67011-810043493714130.00%4175511.280000100003000.00%0131000.0300000000
19Nicolas DeslauriersBluesLW61000-3201970220.00%11081.7800004000000056.52%2300000.0000000000
20Trent FredericBluesC9000-100331210.00%0465.2000000000000033.33%2100000.0000000000
Stats d'équipe Total ou en Moyenne12061802834638512012061295222379912828.10%6911981516.43568714325119155813411639311452.19%4455499508010.471446000242631
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 HellebuyckBlues60342240.9312.293641401392022857210.778366011295
2Keith KinkaidBlues74210.9033.544070024247107000.7508760010
3Ken ApplebyBlues10000.78913.3318004197000.000006000
Stats d'équipe Total ou en Moyenne68382450.9272.464066401672288971210.77344676712105


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
Aaron EkbladBluesD211996-02-07No216 Lbs6 ft4NoNoNo7Contrat d'EntréePro & Farm7,500,000$7,500,000$1,827,731$NoLien
Austin WatsonBluesLW251992-01-13No204 Lbs6 ft4NoNoNo2Contrat d'EntréePro & Farm1,100,000$1,100,000$268,067$NoLien
Brock NelsonBluesC251991-10-15No212 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm4,250,000$4,250,000$1,035,714$NoLien
Chris KunitzBluesLW381979-09-26No195 Lbs6 ft0NoNoNo1Sans RestrictionPro & Farm1,000,000$1,000,000$243,697$NoLien
Connor HellebuyckBluesG241993-05-19No207 Lbs6 ft4NoNoNo6Contrat d'EntréePro & Farm6,166,666$6,166,666$1,502,801$NoLien
Craig SmithBluesRW281989-09-05No208 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm4,250,000$4,250,000$1,035,714$NoLien
Derick BrassardBluesC301987-09-22No202 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm5,000,000$5,000,000$1,218,487$NoLien
Deryk EngellandBluesD351982-04-03No214 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm1,500,000$1,500,000$365,546$NoLien
Evgenii DadonovBluesRW281989-03-12No185 Lbs5 ft11NoNoNo2Sans RestrictionPro & Farm4,000,000$4,000,000$974,790$NoLien
Joel EdmundsonBluesD241993-06-28No215 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm3,000,000$3,000,000$731,092$NoLien
John KlingbergBluesD251992-08-14No177 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm4,250,000$4,250,000$1,035,714$NoLien
Keith KinkaidBluesG281989-07-04No195 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm1,250,000$1,250,000$304,622$NoLien
Ken ApplebyBluesG221995-04-10No210 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm750,000$750,000$182,773$NoLien
Kevin FialaBluesLW211996-07-22No193 Lbs5 ft10NoNoNo1Contrat d'EntréePro & Farm863,333$863,333$210,392$NoLien
Luke SchennBluesD271989-11-02No229 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm1,250,000$1,250,000$304,622$NoLien
Marco ScandellaBluesD271990-02-23No208 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm4,000,000$4,000,000$974,790$NoLien
Mark LetestuBluesC321985-02-04No195 Lbs5 ft10NoNoNo1Sans RestrictionPro & Farm1,000,000$1,000,000$243,697$NoLien
Max PaciorettyBluesLW281988-11-20No206 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm4,500,000$4,500,000$1,096,639$NoLien
Nick HoldenBluesD301987-05-15No214 Lbs6 ft4NoNoNo2Sans RestrictionPro & Farm2,200,000$2,200,000$536,134$NoLien
Nicolas DeslauriersBluesLW261991-02-22No215 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm950,000$950,000$231,513$NoLien
Patrice BergeronBluesC321985-07-24No195 Lbs6 ft1NoNoNo4Sans RestrictionPro & Farm6,875,000$6,875,000$1,675,420$NoLien
Pavel BuchnevichBluesRW221995-04-17No191 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm925,000$925,000$225,420$NoLien
Trent FredericBluesC191998-02-11Yes203 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm750,000$750,000$182,773$NoLien
Troy BrouwerBluesLW/RW321985-08-17No215 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm750,000$750,000$182,773$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2427.04204 Lbs6 ft21.962,836,667$

Somme Salaire 1e Année Somme Salaire 2e Année Somme Salaire 3e Année Somme Salaire 4e Année Somme Salaire 5e Année
68,079,999$41,291,666$24,791,666$24,791,666$13,666,666$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Max PaciorettyDerick BrassardEvgenii Dadonov40122
2Kevin FialaMark LetestuCraig Smith30122
3Chris KunitzBrock NelsonPavel Buchnevich20122
4Troy BrouwerTrent FredericEvgenii Dadonov10122
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 PaciorettyDerick BrassardEvgenii Dadonov60122
2Kevin FialaMark LetestuCraig Smith40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marco ScandellaJohn Klingberg60122
2Deryk EngellandAaron Ekblad40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Evgenii DadonovCraig Smith60122
2Max PaciorettyDerick Brassard40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marco ScandellaJohn Klingberg60122
2Deryk EngellandAaron Ekblad40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Evgenii Dadonov60122Marco ScandellaJohn Klingberg60122
2Craig Smith40122Deryk EngellandAaron Ekblad40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Evgenii DadonovCraig Smith60122
2Max PaciorettyDerick Brassard40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marco ScandellaJohn Klingberg60122
2Deryk EngellandAaron Ekblad40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Max PaciorettyDerick BrassardEvgenii DadonovMarco ScandellaJohn Klingberg
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Max PaciorettyDerick BrassardEvgenii 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
Evgenii Dadonov, Craig Smith, Max Pacioretty, Derick Brassard, 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
1Avalanche613000111116-541200010810-22010000136-350.4171118290016311804063757209544011123417.39%21290.48%0906169253.55%917179950.97%50293753.58%123691385910752
2Blackhawks422000001073110000003123120000076140.500101525004330137512957012245367215640.00%19384.21%0906169253.55%917179950.97%50293753.58%854988366632
3Blue Jackets2110000045-11010000024-21100000021120.5004610000220802629250602718405120.00%9277.78%0906169253.55%917179950.97%50293753.58%432542173416
4Bruins21000010633110000004221000001021141.0006814003201682613284631418306116.67%9188.89%0906169253.55%917179950.97%50293753.58%422444203817
5Canadiens2010001067-1100000104311010000024-220.5006101600113181243126473146329333.33%30100.00%0906169253.55%917179950.97%50293753.58%452644173518
6Capitals11000000211000000000001100000021121.00022400200029105140369819300.00%40100.00%1906169253.55%917179950.97%50293753.58%189239178
7Devils311000101073110000005232010001055040.66710142400252212138374681042485615213.33%40100.00%0906169253.55%917179950.97%50293753.58%684063265327
8Ducks2010001025-3000000000002010001025-320.50022400010264122032366202439400.00%12191.67%0906169253.55%917179950.97%50293753.58%382050193516
9Flames431000001174220000008442110000033060.750111425004520112434722011731266311327.27%13376.92%0906169253.55%917179950.97%50293753.58%784388377234
10Flyers3020001058-32010001046-21010000012-120.33355100012128835322059830325710110.00%16381.25%0906169253.55%917179950.97%50293753.58%613468295527
11Golden Knights3210000010731010000024-22200000083540.66710172710325010925364809730266519421.05%13376.92%0906169253.55%917179950.97%50293753.58%643763275226
12Islanders22000000844110000004311100000041341.00081321001160512114160761912369222.22%6266.67%1906169253.55%917179950.97%50293753.58%392143193718
13Jets64001100241593300000013583100110011101110.917243862006981221737371421670489724833.33%23482.61%0906169253.55%917179950.97%50293753.58%129731285210352
14Kings41200100916-72010010037-42110000069-330.3759142300531014245514601474432731119.09%16662.50%0906169253.55%917179950.97%50293753.58%865188366633
15Lightning2110000045-1110000002111010000024-220.5004711001300691634190662418355240.00%9188.89%0906169253.55%917179950.97%50293753.58%422341173617
16Oilers3110000179-2210000014401010000035-230.50071118002233973737231010231246210110.00%12375.00%0906169253.55%917179950.97%50293753.58%653767265226
17Panthers21100000770110000005321010000024-220.50071017002410521715200642312239333.33%6183.33%0906169253.55%917179950.97%50293753.58%362048193416
18Penguins11000000532000000000001100000053221.00057120021202611114033910223133.33%50100.00%1906169253.55%917179950.97%50293753.58%199219199
19Predateurs5320000014122211000006423210000088060.6001421350047301636458410179593210324833.33%16381.25%0906169253.55%917179950.97%50293753.58%10860104428746
20Senateurs21100000550110000003121010000024-220.5005914002210732326240732010358112.50%5180.00%0906169253.55%917179950.97%50293753.58%452740163318
21Sharks40300001914-52010000146-22020000058-310.1259132200135113044454141475438669222.22%19384.21%0906169253.55%917179950.97%50293753.58%865188356935
22Stars4300001018810210000109542200000093681.00018294700863113053433431414038702129.52%18477.78%2906169253.55%917179950.97%50293753.58%854785397337
Total67302401273187171163116800142937518361416011319496-2810.6041872834701055705415222373474973252228969151612062535622.13%2584682.17%5906169253.55%917179950.97%50293753.58%141580414746171182590
_Since Last GM Reset67302401273187171163116800142937518361416011319496-2810.6041872834701055705415222373474973252228969151612062535622.13%2584682.17%5906169253.55%917179950.97%50293753.58%141580414746171182590
_Vs Conference4520160123312511692110600122605010241010011116566-1530.58912519231710384736914854875024903115434783648211713922.81%1823580.77%2906169253.55%917179950.97%50293753.58%952542992413787394
_Vs Division251370112177581912730002039251413640110138335340.68077121198002331203831281266278148672681944531072826.17%971683.51%2906169253.55%917179950.97%50293753.58%531300545230438221

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
6781L118728347022232289691516120610
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
6730241273187171
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3116801429375
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
36141611319496
Derniers 10 Matchs
WLOTWOTL SOWSOL
250021
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2535622.13%2584682.17%5
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
7347497325255705415
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
906169253.55%917179950.97%50293753.58%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
141580414746171182590


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 - 2019-01-02356Blues5Golden Knights2WSommaire du Match
88 - 2019-01-04366Jets1Blues3WSommaire du Match
90 - 2019-01-06375Blues3Oilers5LSommaire du Match
92 - 2019-01-08383Blues5Penguins3WSommaire du Match
94 - 2019-01-10390Avalanche1Blues2WXXSommaire du Match
97 - 2019-01-13402Blues1Flyers2LSommaire du Match
99 - 2019-01-15415Oilers2Blues3WSommaire du Match
103 - 2019-01-19427Blues3Predateurs2WSommaire du Match
105 - 2019-01-21437Blues2Blue Jackets1WSommaire du Match
106 - 2019-01-22442Jets2Blues5WSommaire du Match
110 - 2019-01-26456Blues4Jets5LXSommaire du Match
112 - 2019-01-28463Blues2Canadiens4LSommaire du Match
113 - 2019-01-29470Devils2Blues5WSommaire du Match
116 - 2019-02-01480Blues4Jets3WXSommaire du Match
119 - 2019-02-04493Blues1Kings8LSommaire du Match
121 - 2019-02-06500Islanders3Blues4WSommaire du Match
125 - 2019-02-10516Blues2Sharks3LSommaire du Match
126 - 2019-02-11523Flames2Blues4WSommaire du Match
129 - 2019-02-14537Blues2Panthers4LSommaire du Match
131 - 2019-02-16544Blues4Islanders1WSommaire du Match
132 - 2019-02-17549Golden Knights4Blues2LSommaire du Match
137 - 2019-02-22567Canadiens3Blues4WXXSommaire du Match
140 - 2019-02-25585Blues2Avalanche3LXXSommaire du Match
142 - 2019-02-27594Avalanche1Blues4WSommaire du Match
146 - 2019-03-03611Lightning1Blues2WSommaire du Match
149 - 2019-03-06626Blues6Stars1WSommaire du Match
151 - 2019-03-08633Blues2Lightning4LSommaire du Match
152 - 2019-03-09641Blue Jackets4Blues2LSommaire du Match
156 - 2019-03-13657Blues3Golden Knights1WSommaire du Match
158 - 2019-03-15664Stars2Blues5WSommaire du Match
160 - 2019-03-17672Blues2Bruins1WXXSommaire du Match
162 - 2019-03-19687Predateurs1Blues4WSommaire du Match
166 - 2019-03-23698Blues0Blackhawks2LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
168 - 2019-03-25706Blues1Devils2LSommaire du Match
170 - 2019-03-27717Sharks2Blues1LSommaire du Match
172 - 2019-03-29725Blues3Sharks5LSommaire du Match
174 - 2019-03-31734Blues4Devils3WXXSommaire du Match
176 - 2019-04-02743Sharks4Blues3LXXSommaire du Match
178 - 2019-04-04752Blues5Kings1WSommaire du Match
180 - 2019-04-06763Blues0Flames2LSommaire du Match
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
Assistance179,602148,17060,007120,90029,611
Attendance PCT96.56%95.59%96.79%97.50%95.52%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
10 17364 - 96.47% 1,632,492$50,607,254$18000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des CoachsValeur du Cap Salarial Spécial
52,305,560$ 68,079,999$ 67,771,666$ 0$ 0$
Cap Salarial Par JourCap salarial à ce jourTaxe de Luxe TotaleJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
68,079,999$ 51,549,306$ 0$ 24 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
16,324,921$ 58 290,252$ 16,834,616$

Total de l'Équipe Éstimé
Dépenses de la Saison ÉstiméesCap Salarial de la Saison ÉstiméCompte Bancaire ActuelCompte Bancaire Projeté
17,318,375$ 68,079,999$ 13,981,031$ 12,987,577$



Charte de Profondeur

Ailier GaucheCentreAilier Droit
Max PaciorettyAGE:28PO:66OV:79
Kevin FialaAGE:21PO:85OV:76
Chris KunitzAGE:38PO:17OV:74
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:71
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:77
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.



[2019-02-21 20:00:11] Both Blues and Wolves lines for next game are empty. Current rosters/lines are not erased.
[2019-02-21 20:00:11] Last 30 Days Pro Star : 1 - Johnny Gaudreau of Sharks (9-7-16) / 2 - Frederik Andersen of Blue Jackets (0,933) / 3 - Connor Hellebuyck of Blues (0,928)
[2019-02-20 21:03:06] Both Blues and Wolves lines for next game are empty. Current rosters/lines are not erased.
[2019-02-19 21:53:45] Patrice Bergeron from Blues is back from Exhaustion.
[2019-02-19 21:53:45] Blues lines for next game are empty. Current rosters/lines are not erased.
[2019-02-19 21:53:40] Auto Lines Function has been run for Blues.
[2019-02-19 21:53:40] Auto Roster Partial Function has been run for Blues.
[2019-02-18 23:15:22] Both Blues and Wolves lines for next game are empty. Current rosters/lines are not erased.
[2019-02-18 23:15:22] Patrice Bergeron from Blues is injured from Exhaustion.
[2019-02-18 23:15:13] Auto Lines Function has been run for Blues.
[2019-02-18 23:15:13] Auto Roster Partial Function has been run for Blues.
[2019-02-18 23:15:03] Patrice Bergeron from Blues is back from Exhaustion.
[2019-02-15 21:08:04] Blues lines for next game are empty. Current rosters/lines are not erased.
[2019-02-15 21:08:03] Patrice Bergeron from Blues is injured from Exhaustion.
[2019-02-15 21:07:25] Auto Lines Function has been run for Blues.
[2019-02-15 21:07:25] Auto Roster Partial Function has been run for Blues.
[2019-02-15 21:06:44] Patrice Bergeron from Blues is back from Exhaustion.
[2019-02-14 21:50:05] Blues lines for next game are empty. Current rosters/lines are not erased.
[2019-02-14 21:50:04] Patrice Bergeron from Blues is injured from Exhaustion.
[2019-02-14 21:49:38] Wolves lines for next game are empty. Current rosters/lines are not erased.
[2019-02-14 00:07:03] Both Blues and Wolves lines for next game are empty. Current rosters/lines are not erased.
[2019-02-14 00:07:02] Game 717 - Unknown Player from Wolves is injured (Strained Right Elbow) and is out for 1 week.
[2019-02-12 22:30:49] Blues lines for next game are empty. Current rosters/lines are not erased.
[2019-02-11 22:52:21] Wolves lines for next game are empty. Current rosters/lines are not erased.
[2019-02-08 21:00:29] Both Blues and Wolves lines for next game are empty. Current rosters/lines are not erased.
[2019-02-07 21:41:46] Blues lines for next game are empty. Current rosters/lines are not erased.
[2019-02-06 20:58:54] Blues lines for next game are empty. Current rosters/lines are not erased.
[2019-02-05 21:07:20] Both Blues and Wolves lines for next game are empty. Current rosters/lines are not erased.
[2019-02-05 21:05:28] Wolves lines for next game are empty. Current rosters/lines are not erased.
[2019-02-01 20:07:49] Both Blues and Wolves lines for next game are empty. Current rosters/lines are not erased.
[2019-02-01 20:07:26] Both Blues and 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
267302401273187171163116800142937518361416011319496-2811872834701055705415222373474973252228969151612062535622.13%2584682.17%5906169253.55%917179950.97%50293753.58%141580414746171182590
Total Saison Régulière67302401273187171163116800142937518361416011319496-2811872834701055705415222373474973252228969151612062535622.13%2584682.17%5906169253.55%917179950.97%50293753.58%141580414746171182590