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Centre de jeu
Blues
6-1-0, 12pts
5
FINAL
3 Canadiens
2-4-1, 5pts
Team Stats
W6StreakOTL1
3-1-0Home Record0-4-0
3-0-0Away Record2-0-1
6-1-0Last 10 Games2-4-1
5.57Goals Per Game3.14
2.29Goals Against Per Game3.86
29.79%Power Play Percentage21.21%
96.43%Penalty Kill Percentage73.53%
Blues
6-1-0, 12pts
5
FINAL
2 MapleLeafs
2-6-1, 5pts
Team Stats
W6StreakL2
3-1-0Home Record1-3-1
3-0-0Away Record1-3-0
6-1-0Last 10 Games2-6-1
5.57Goals Per Game2.78
2.29Goals Against Per Game4.22
29.79%Power Play Percentage12.90%
96.43%Penalty Kill Percentage69.39%
Blues
6-1-0, 12pts
Jour 19
Jets
4-3-1, 9pts
Stats Équipe
W6SéquenceW1
3-1-0Fiche domicile3-2-0
3-0-0Fiche visiteur1-1-1
6-1-010 derniers matchs4-3-1
5.57Buts par match 3.50
2.29Buts contre par match 3.13
29.79%Pourcentage en avantage numérique12.50%
96.43%Pourcentage en désavantage numérique81.08%
BlueJacket
7-0-0, 14pts
Jour 22
Blues
6-1-0, 12pts
Stats Équipe
W5SéquenceW6
4-0-0Fiche domicile3-1-0
3-0-0Fiche visiteur3-0-0
7-0-010 derniers matchs6-1-0
5.57Buts par match 5.57
2.43Buts contre par match 2.29
28.21%Pourcentage en avantage numérique29.79%
92.31%Pourcentage en désavantage numérique96.43%
Blackhawks
2-5-1, 5pts
Jour 24
Blues
6-1-0, 12pts
Stats Équipe
W1SéquenceW6
2-1-1Fiche domicile3-1-0
0-4-0Fiche visiteur3-0-0
2-5-110 derniers matchs6-1-0
3.13Buts par match 5.57
4.63Buts contre par match 2.29
19.05%Pourcentage en avantage numérique29.79%
65.96%Pourcentage en désavantage numérique96.43%
Meneurs d'équipe
Sam ReinhartButs
Sam Reinhart
9
Claude GirouxPasses
Claude Giroux
16
Sam ReinhartPoints
Sam Reinhart
22
Sam ReinhartPlus/Moins
Sam Reinhart
10
Ilya SorokinVictoires
Ilya Sorokin
6
Ilya SorokinPourcentage d’arrêts
Ilya Sorokin
0.915

Stats Équipe
Buts pour
39
5.57 GFG
Tirs pour
289
41.29 Avg
Pourcentage en avantage numérique
29.8%
14 GF
Début de zone offensive
46.5%
Buts contre
16
2.29 GAA
Tirs contre
188
26.86 Avg
Pourcentage en désavantage numérique
96.4%
1 GA
Début de la zone défensive
34.3%
Blessure/Suspension
Pas de blessure ou de suspension.
Information d’équipe
Directeur généralMaxime Barabe
EntraîneurTodd McLellan
DivisionCentral
ConférenceWestern
Capitaine
Assistant #1
Assistant #2
Uniformes
Informations de l’aréna
NomAnheuser-Busch Center
Capacité25,000
Assistance20,732
Billets de saison10,000
Information formation
Équipe Pro20
Équipe Mineure28
Limite contact 48 / 50
Espoirs4
Plafond salarial
Cap Salarial de la Saison estimé84,452,888$
Plafond salarial disponible547,112$
Valeur du plafond salarial spécial0$
Joueurs Inclus dans le plafond salarial20
Finance
Revenu annuel à ce jour7,370,798$
Dépenses annuelles à ce jour8,896,049$
Revenus de la saison estimés68,179,882$
Dépenses de la saison estimées78,556,812$
Compte bancaire actuel279,892,765$
Compte bancaire projeté266,944,332$
Historique d'équipe
Saison actuelle6-1-0 (12PTS)
Historique736-698-139 (0.468%)
Apparitions séries éliminatoires 9
Historique séries éliminatoires (W-L)51-44
Stanley Cup0


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 SPÂgeContratSalaire
1Sam ReinhartX100.0062518296628999927977999481828645318302941$
2Zach HymanX100.0065517891668798844064997840888830317803247,000,000$
3Brad MarchandX100.0073447193438799794078797862969210317603638,750,000$
4Claude GirouxX100.0051448491538899779383718069969210317603627,000,000$
5Jonathan Audy-MarchessaultX100.0071428093488499804067926769928820317503426,500,000$
6Nick SchmaltzX100.0045448790528797777680737480808450317402866,375,000$
7Logan CoutureX100.0077538589666050798280778881947715347403516,500,000$
8Yegor SharangovichX100.0044498887638499757468817799768060317302633,000,000$
9Lars EllerX100.0056528279688199618756658675948815387003522,750,000$
10Nic DowdX100.0083517580608087598353658740928620316903411,500,000$
11Keegan KolesarX100.0099677875737397544050586940787655316502711,000,000$
12Nick BoninoX100.0045498675627574508647528476968610316303632,000,000$
13Kristopher LetangX100.007949758762919973408165887398955317903717,000,000$
14Darnell NurseX100.0089597079778698644062657940828445317502927,500,000$
15Radko GudasX100.0099625179658288584055618840928720317503411,750,000$
16Christopher TanevX100.0054498478628294564059539440948815317303514,500,000$
17Jeff PetryX100.008856797771819359406455764098905317303724,000,000$
18Spencer StastneyX100.004244867953765755404862804072747031640241750,000$
Rayé
Équipe Mineure
1Jordan MartinookX100.0057478181597999618658647890888430226803212,000,000$
2Michael EyssimontX100.0079646480627498584054617140807750226502831,250,000$
3Lane PedersonX100.0099617880567565577057577040787755226402711,050,000$
4Matthew NietoX100.0055448678537458524051547540888130226103212,000,000$
5Drake CaggiulaX100.006240768251605060406655594084724020600302900,000$
6Liam FoudyX100.0054498777627152544059506140727270225802411,017,500$
7Brett MurrayX100.006171777589635349404356564076706022570261851,000$
8Will BittenX100.004742817551776745403951506976776022540261860,000$
9Calvin deHaanX100.007847837759778353405056774090842520680332975,000$
10Egor ZamulaX100.0053518078677788604060597340727570326702411,200,000$
11Nikita OkhotyukX100.0099487276617679524053527040727470226702411,018,000$
12Alexander EdlerX100.00795579757455505340525462639977022630381975,000$
13Patrik NemethX100.007660827584555048404550654088723022620324975,000$
14Jack RathboneX100.005541837550736843403946704074746522600251825,000$
15Markus NiemelainenX100.009952807575555031402934624076666022590261930,000$
16Noel HoefenmayerX100.007153637565555044403948664074656522590251930,000$
17Samuel LabergeX100.0072705975686858384038386140787355205402711,500,000$
18Carsen TwarynskiX100.009950757564605037403242614078695520530271860,000$
19Josh LopinaX100.005649837565786839703147504070747520530231696,000$
20Serron NoelX100.007167677574605038403936554072667020520241825,000$
21Tyler AngleX100.005360797545605041703646504072667020510241770,000$
22Jack BadiniX100.007361817562605031702934504076686020490261930,000$
23Grant MismashX100.005045837555605034402939504074676520480251825,000$
24Dmitry SemykinX100.006454907573555025402030514072647020530241825,000$
MOYENNE D’ÉQUIPE100.00695278806373745652535870518378432665
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 SPÂgeContratSalaire
1Ilya Sorokin100.008998999076787980777883828045358102926,000,000$
2Mike Smith100.0081506099616566666771829982033710421575,000$
Rayé
Équipe Mineure
1Martin Jones100.00855760957475767476759692842029750343900,000$
2Aaron Dell100.00815060895861616061599394781524650352575,000$
3Landon Bow100.00755060965050505050508382664524580292600,000$
4Beck Warm100.00775060805050505050504074626520560252600,000$
MOYENNE D’ÉQUIPE100.0081596792626364636464808775322868
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Todd McLellan78978489878956CAN5743,000,000$


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’équipePOSGP 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
1Sam ReinhartBluesRW7913221020151960183415.00%115221.7437101333000003141.67%1200012.8900000220
2Claude GirouxBluesC74162010005241971621.05%215422.111910432000000056.62%21900002.5800000004
3Zach HymanBluesLW777141010018104562415.56%015622.314261132000032146.15%1300001.7900000120
4Jonathan Audy-MarchessaultBluesRW7639000692021930.00%011216.13325928000000125.00%400011.5900000101
5Brad MarchandBluesLW735804026263416248.82%015221.75123932000091027.27%1100001.0500000010
6Nick SchmaltzBluesC7077000012205160.00%113118.730227350000110056.15%13000001.0700000000
7Yegor SharangovichBluesRW76170000112071530.00%010314.85202832000000060.00%500011.3500000200
8Logan CoutureBluesLW70550951013156130.00%111216.02011731000190051.92%15600000.8900100010
9Kristopher LetangBluesD7044660161477150.00%618326.16022436000018000.00%000000.4400000000
10Jeff PetryBluesD703341001571010.00%410815.4300000000018000.00%000000.5600000000
11Christopher TanevBluesD72025002660233.33%413819.7900011000023000.00%000000.2900000000
12Nic DowdBluesLW7112060184106710.00%29814.11000000000230054.55%1100000.4000000000
13Darnell NurseBluesD7022120535040.00%413619.5000012800000000.00%000000.2900000000
14Spencer StastneyBluesD7022200133110.00%68812.5900000000012000.00%000000.4500000000
15Nick BoninoBluesC70110200121110.00%1537.64000000000260049.35%7700000.3700000000
16Radko GudasBluesD7101214022914037.14%512017.2800000000014000.00%000000.1700000000
17Keegan KolesarBluesRW7000000000000.00%000.140000000000000.00%000000.0000000000
18Lars EllerBluesC7000000239180.00%0375.4000012000010073.08%2600000.0000000000
Statistiques d’équipe totales ou en moyenne1263970109506551611852898320313.49%37204116.201427417532700011736354.07%66400031.0700100665
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
1Ilya SorokinBlues76100.9152.2942000161880100.000070000
Statistiques d’équipe totales ou en moyenne76100.9152.2942000161880100.000070000


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 Type 2038 Plafond salarial Plafond salarial restant Exclus du plafond salarial 2039 204020412042204320442045Salaire annuel 9Salaire annuel 10Link
Brad MarchandBluesLW361988-05-11No176 Lbs5 ft9NoNoYes3Pro Only8,750,000$8,750,000$7,860,169$No8,750,000$8,750,000$
UFA
Lien / Lien NHL
Christopher TanevBluesD351989-12-20No193 Lbs6 ft2NoNoYes1Pro & Farm4,500,000$4,500,000$4,042,373$No
UFA
Lien / Lien NHL
Claude GirouxBluesC361988-01-12No188 Lbs5 ft11NoNoYes2Pro Only7,000,000$7,000,000$6,288,136$No7,000,000$
UFA
Lien / Lien NHL
Darnell NurseBluesD291995-02-04No215 Lbs6 ft4NoNoYes2Pro Only7,500,000$7,500,000$6,737,288$No7,500,000$
UFA
Lien / Lien NHL
Ilya SorokinBluesG291995-08-04No190 Lbs6 ft3NoNoYes2Pro Only6,000,000$6,000,000$5,389,831$No6,000,000$
UFA
Lien / Lien NHL
Jeff PetryBluesD371987-12-09No208 Lbs6 ft3NoNoYes2Pro & Farm4,000,000$4,000,000$3,593,220$No4,000,000$
UFA
Lien / Lien NHL
Jonathan Audy-MarchessaultBluesRW341990-12-27No185 Lbs5 ft9NoNoYes2Pro Only6,500,000$6,500,000$5,838,983$No6,500,000$
UFA
Lien / Lien NHL
Keegan KolesarBluesRW271997-04-08No216 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$1,000,000$898,305$No
UFA
Lien / Lien NHL
Kristopher LetangBluesD371987-04-24No201 Lbs6 ft0NoNoYes1Pro Only7,000,000$7,000,000$6,288,136$No
UFA
Lien / Lien NHL
Lars EllerBluesC351989-05-08No205 Lbs6 ft2NoNoYes2Pro & Farm2,750,000$2,750,000$2,470,339$No2,750,000$
UFA
Lien / Lien NHL
Logan CoutureBluesLW351989-03-28No206 Lbs6 ft1NoNoYes1Pro Only6,500,000$6,500,000$5,838,983$No
UFA
Lien / Lien NHL
Mike SmithBluesG421982-02-22No210 Lbs6 ft3NoNoNo1Pro & Farm575,000$575,000$516,525$No
UFA
Lien / Lien NHL
Nic DowdBluesLW341990-05-27No193 Lbs6 ft1NoNoNo1Pro & Farm1,500,000$1,500,000$1,347,458$No
UFA
Lien / Lien NHL
Nick BoninoBluesC361988-04-20No198 Lbs6 ft1NoNoNo3Pro & Farm2,000,000$2,000,000$1,796,610$No2,000,000$2,000,000$
UFA
Lien / Lien NHL
Nick SchmaltzBluesC281996-02-23No181 Lbs6 ft0NoNoYes6Pro Only6,375,000$6,375,000$5,726,695$No6,375,000$6,375,000$6,375,000$6,375,000$6,375,000$
UFA
Lien / Lien NHL
Radko GudasBluesD341990-06-05No208 Lbs6 ft0NoNoNo1Pro & Farm1,750,000$1,750,000$1,572,034$No
UFA
Lien / Lien NHL
Sam ReinhartBluesRW291995-11-06No193 Lbs6 ft2YesNoYes4Pro Only1$1$1$No7,200,000$7,200,000$7,200,000$
UFA
Lien / Lien NHL
Spencer StastneyBluesD242000-01-04No184 Lbs6 ft0NoNoNo1Pro & Farm750,000$750,000$673,729$No
RFA
Lien / Lien NHL
Yegor SharangovichBluesRW261998-06-06No196 Lbs6 ft2NoNoYes3Pro & Farm3,000,000$3,000,000$2,694,915$No3,000,000$3,000,000$
UFA
Lien / Lien NHL
Zach HymanBluesLW321992-06-09No206 Lbs6 ft1NoNoYes4Pro Only7,000,000$7,000,000$6,288,136$No7,000,000$7,000,000$7,000,000$
UFA
Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2032.75198 Lbs6 ft12.154,222,500$

Somme salaire 1e année Somme salaire 2e année Somme salaire 3e année Somme salaire 4e année Somme salaire 5e année
84,450,001$68,075,000$34,325,000$20,575,000$6,375,000$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Zach HymanClaude GirouxSam Reinhart40122
2Brad MarchandNick SchmaltzJonathan Audy-Marchessault30122
3Nic DowdLogan CoutureYegor Sharangovich20122
4Brad MarchandNick BoninoLars Eller10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kristopher LetangChristopher Tanev40122
2Darnell NurseRadko Gudas30122
3Spencer StastneyJeff Petry20122
4Kristopher LetangJeff Petry10122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Zach HymanClaude GirouxSam Reinhart60122
2Brad MarchandLogan CoutureYegor Sharangovich40122
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kristopher LetangNick Schmaltz60122
2Darnell NurseJonathan Audy-Marchessault40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Nick BoninoNic Dowd60122
2Logan CoutureBrad Marchand40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kristopher LetangChristopher Tanev60122
2Radko GudasJeff Petry40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Nick Bonino60122Kristopher LetangChristopher Tanev60122
2Lars Eller40122Radko GudasJeff Petry40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Lars EllerNic Dowd60122
2Logan CoutureClaude Giroux40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kristopher LetangJeff Petry60122
2Radko GudasDarnell Nurse40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Zach HymanClaude GirouxJonathan Audy-MarchessaultKristopher LetangDarnell Nurse
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nic DowdLogan CoutureYegor SharangovichKristopher LetangChristopher Tanev
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Yegor Sharangovich, Lars Eller, Keegan KolesarLars Eller, Nic DowdNick Schmaltz
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Spencer Stastney, Jeff Petry, Darnell NurseChristopher TanevSpencer Stastney, Radko Gudas
Tirs de pénalité
Nick Schmaltz, Zach Hyman, Brad Marchand, Claude Giroux, Jonathan Audy-Marchessault
Gardien
#1 : Ilya Sorokin, #2 : Mike Smith


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
TotalDomicileVisiteur
# 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
1Blackhawks220000001248110000007251100000052341.0001221330052507926252804613184213430.77%8187.50%016530953.40%12622855.26%6812753.54%523641142513
2Canadiens11000000532000000000001100000053221.00058130031103191210031512197228.57%60100.00%016530953.40%12622855.26%6812753.54%2113259136
3Ducks11000000716110000007160000000000021.000713200041204623419032415248337.50%40100.00%016530953.40%12622855.26%6812753.54%2720206126
4Flames11000000817110000008170000000000021.000814220023305716221901852246116.67%10100.00%016530953.40%12622855.26%6812753.54%3122157128
5Jets1010000025-31010000025-30000000000000.00024600110049221710034414354125.00%70100.00%016530953.40%12622855.26%6812753.54%2819196126
6MapleLeafs11000000523000000000001100000052321.0005101500005027841502764179333.33%20100.00%016530953.40%12622855.26%6812753.54%2619208126
Total761000003916234310000024915330000001578120.8573970109001581602891048410101883765161471429.79%28196.43%016530953.40%12622855.26%6812753.54%187132143518847
_Since Last GM Reset761000003916234310000024915330000001578120.8573970109001581602891048410101883765161471429.79%28196.43%016530953.40%12622855.26%6812753.54%187132143518847
_Vs Conference5410000029111843100000249151100000052380.800295281001271002318768760130264912531929.03%20195.00%016530953.40%12622855.26%6812753.54%13910097346334
_Vs Division321000001495211000009721100000052340.66714253900635012848423808017327717529.41%15193.33%016530953.40%12622855.26%6812753.54%805661203820

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
712W63970109289188376516100
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
76100003916
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4310000249
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3300000157
Derniers 10 matchs
WLOTWOTL SOWSOL
610000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
471429.79%28196.43%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
104841010158160
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
16530953.40%12622855.26%6812753.54%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
187132143518847


Derniers matchs 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
213Jets5Blues2BLSommaire du match
426Blackhawks2Blues7BWSommaire du match
955Flames1Blues8BWSommaire du match
1059Blues5Blackhawks2AWSommaire du match
1172Ducks1Blues7BWSommaire du match
1488Blues5Canadiens3AWSommaire du match
17111Blues5MapleLeafs2AWSommaire du match
19121Blues-Jets-
22143BlueJacket-Blues-
24156Blackhawks-Blues-
29189GoldenKnights-Blues-
31204Wild-Blues-
34221Hurricanes-Blues-
37238Sharks-Blues-
39257Wild-Blues-
42273Blues-Blackhawks-
44290Blues-GoldenKnights-
45301Blues-Sharks-
47314Kings-Blues-
49327Blues-Predators-
50343Predators-Blues-
51355Jets-Blues-
55379Blues-RedWings-
57392Blues-Avalanche-
58395Blues-Coyotes-
62428Oilers-Blues-
64443Blues-Jets-
66458Canucks-Blues-
68472Panthers-Blues-
71494Avalanche-Blues-
73509Flames-Blues-
75521Blues-Oilers-
77540Blues-Canucks-
79549Blues-Flames-
81575Sabres-Blues-
83594Penguins-Blues-
85610Rangers-Blues-
88627Capitals-Blues-
90643Islanders-Blues-
92654Blues-Flyers-
93663Stars-Blues-
95679Canadiens-Blues-
97689Blues-Stars-
99710Blues-Capitals-
100717Blues-Islanders-
102726Blues-Bruins-
104748Senators-Blues-
106758Blues-Kings-
108765Blues-Ducks-
114789Blues-BlueJacket-
117813Blues-Panthers-
119835Blues-Lightning-
121847Predators-Blues-
122857Blues-Predators-
124871Devils-Blues-
126877Blues-Coyotes-
128895Blues-Avalanche-
129907Blues-Wild-
131924MapleLeafs-Blues-
133929Blues-Stars-
135953Bruins-Blues-
136959Blues-Wild-
138975Predators-Blues-
141993Blues-Hurricanes-
1421006Stars-Blues-
1461029Blues-Ducks-
1471039Blues-Kings-
1491057Blues-Sharks-
1521078Coyotes-Blues-
1541089Blues-Senators-
1561107Blues-Penguins-
1571112Blues-Sabres-
1591131Oilers-Blues-
1611146RedWings-Blues-
1631159Lightning-Blues-
1651174GoldenKnights-Blues-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1691200Blues-Rangers-
1701207Blues-Devils-
1721227Avalanche-Blues-
1741240Blues-Blackhawks-
1751250Flyers-Blues-
1771270Canucks-Blues-


Charte de profondeur
Ailier gaucheCentreAilier droit
Zach Hyman
Zach Hyman
AGE:32
SK:91
EN:87
DU:98
PH:84
PA:64
SC:99
DF:78
Brad Marchand
Brad Marchand
AGE:36
SK:93
EN:87
DU:99
PH:79
PA:78
SC:79
DF:78
Logan Couture
Logan Couture
AGE:35
SK:89
EN:60
DU:50
PH:79
PA:80
SC:77
DF:88
Nic Dowd
Nic Dowd
AGE:34
SK:80
EN:80
DU:87
PH:59
PA:53
SC:65
DF:87
Jordan Martinook
Jordan Martinook
AGE:32
SK:81
EN:79
DU:99
PH:61
PA:58
SC:64
DF:78
Matthew Nieto
Matthew Nieto
AGE:32
SK:78
EN:74
DU:58
PH:52
PA:51
SC:54
DF:75
Drake Caggiula
Drake Caggiula
AGE:30
SK:82
EN:60
DU:50
PH:60
PA:66
SC:55
DF:59
Brett Murray
Brett Murray
AGE:26
SK:75
EN:63
DU:53
PH:49
PA:43
SC:56
DF:56
Samuel Laberge
Samuel Laberge
AGE:27
SK:75
EN:68
DU:58
PH:38
PA:38
SC:38
DF:61
Carsen Twarynski
Carsen Twarynski
AGE:27
SK:75
EN:60
DU:50
PH:37
PA:32
SC:42
DF:61
Grant Mismash
Grant Mismash
AGE:25
SK:75
EN:60
DU:50
PH:34
PA:29
SC:39
DF:50
Claude Giroux
Claude Giroux
AGE:36
SK:91
EN:88
DU:99
PH:77
PA:83
SC:71
DF:80
Nick Schmaltz
Nick Schmaltz
AGE:28
SK:90
EN:87
DU:97
PH:77
PA:80
SC:73
DF:74
Lars Eller
Lars Eller
AGE:35
SK:79
EN:81
DU:99
PH:61
PA:56
SC:65
DF:86
Michael Eyssimont
Michael Eyssimont
AGE:28
SK:80
EN:74
DU:98
PH:58
PA:54
SC:61
DF:71
Lane Pederson
Lane Pederson
AGE:27
SK:80
EN:75
DU:65
PH:57
PA:57
SC:57
DF:70
Nick Bonino
Nick Bonino
AGE:36
SK:75
EN:75
DU:74
PH:50
PA:47
SC:52
DF:84
Liam Foudy
Liam Foudy
AGE:24
SK:77
EN:71
DU:52
PH:54
PA:59
SC:50
DF:61
Josh Lopina
Josh Lopina
AGE:23
SK:75
EN:78
DU:68
PH:39
PA:31
SC:47
DF:50
Tyler Angle
Tyler Angle
AGE:24
SK:75
EN:60
DU:50
PH:41
PA:36
SC:46
DF:50
Jack Badini
Jack Badini
AGE:26
SK:75
EN:60
DU:50
PH:31
PA:29
SC:34
DF:50
Sam Reinhart
Sam Reinhart
AGE:29
SK:96
EN:89
DU:99
PH:92
PA:77
SC:99
DF:94
Jonathan Audy-Marchessault
Jonathan Audy-Marchessault
AGE:34
SK:93
EN:84
DU:99
PH:80
PA:67
SC:92
DF:67
Yegor Sharangovich
Yegor Sharangovich
AGE:26
SK:87
EN:84
DU:99
PH:75
PA:68
SC:81
DF:77
Keegan Kolesar
Keegan Kolesar
AGE:27
SK:75
EN:73
DU:97
PH:54
PA:50
SC:58
DF:69
Will Bitten
Will Bitten
AGE:26
SK:75
EN:77
DU:67
PH:45
PA:39
SC:51
DF:50
Serron Noel
Serron Noel
AGE:24
SK:75
EN:60
DU:50
PH:38
PA:39
SC:36
DF:55

Défense #1Défense #2Gardien
Kristopher Letang
Kristopher Letang
AGE:37
SK:87
EN:91
DU:99
PH:73
PA:81
SC:65
DF:88
Darnell Nurse
Darnell Nurse
AGE:29
SK:79
EN:86
DU:98
PH:64
PA:62
SC:65
DF:79
Radko Gudas
Radko Gudas
AGE:34
SK:79
EN:82
DU:88
PH:58
PA:55
SC:61
DF:88
Christopher Tanev
Christopher Tanev
AGE:35
SK:78
EN:82
DU:94
PH:56
PA:59
SC:53
DF:94
Jeff Petry
Jeff Petry
AGE:37
SK:77
EN:81
DU:93
PH:59
PA:64
SC:55
DF:76
Calvin deHaan
Calvin deHaan
AGE:33
SK:77
EN:77
DU:83
PH:53
PA:50
SC:56
DF:77
Egor Zamula
Egor Zamula
AGE:24
SK:78
EN:77
DU:88
PH:60
PA:60
SC:59
DF:73
Nikita Okhotyuk
Nikita Okhotyuk
AGE:24
SK:76
EN:76
DU:79
PH:52
PA:53
SC:52
DF:70
Spencer Stastney
Spencer Stastney
AGE:24
SK:79
EN:76
DU:57
PH:55
PA:48
SC:62
DF:80
Alexander Edler
Alexander Edler
AGE:38
SK:75
EN:55
DU:50
PH:53
PA:52
SC:54
DF:62
Patrik Nemeth
Patrik Nemeth
AGE:32
SK:75
EN:55
DU:50
PH:48
PA:45
SC:50
DF:65
Jack Rathbone
Jack Rathbone
AGE:25
SK:75
EN:73
DU:68
PH:43
PA:39
SC:46
DF:70
Noel Hoefenmayer
Noel Hoefenmayer
AGE:25
SK:75
EN:55
DU:50
PH:44
PA:39
SC:48
DF:66
Markus Niemelainen
Markus Niemelainen
AGE:26
SK:75
EN:55
DU:50
PH:31
PA:29
SC:34
DF:62
Dmitry Semykin
Dmitry Semykin
AGE:24
SK:75
EN:55
DU:50
PH:25
PA:20
SC:30
DF:51
Ilya Sorokin
Ilya Sorokin
AGE:29
SK:89
AG:76
RB:78
SC:79
HS:80
RT:77
DF:78
Martin Jones
Martin Jones
AGE:34
SK:85
AG:74
RB:75
SC:76
HS:74
RT:76
DF:75
Mike Smith
Mike Smith
AGE:42
SK:81
AG:61
RB:65
SC:66
HS:66
RT:67
DF:71
Aaron Dell
Aaron Dell
AGE:35
SK:81
AG:58
RB:61
SC:61
HS:60
RT:61
DF:59
Landon Bow
Landon Bow
AGE:29
SK:75
AG:50
RB:50
SC:50
HS:50
RT:50
DF:50
Beck Warm
Beck Warm
AGE:25
SK:77
AG:50
RB:50
SC:50
HS:50
RT:50
DF:50
Espoirs
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
Espoir Nom de l’équipeAnnée de repêchage Choix total Information Lien
Adam EngstromBlues2036104
Jacob LeguerrierBlues2033161
Lukas FischerBlues203882
Patrick HolwayBlues2032168

Choix au repêchage

Choix au repêchage
Année R1R2R3R4R5R6R7
2040
2041



Blues Leaders statistiques (saison régulière)
# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS
1Jared Spurgeon762196467663-1094174791465193410.13%13431855224.351261682941274112133322130.00%50.7102
2Alan Letang1308223419642-598201731177624409.14%8212302717.6048871352424101452301855.08%20.561031
3Mika Zibanejad708186282468-1055951133123019319.63%1401346819.0249127176487381148191051.38%20.691137
4Shane Doan527183243426-11963814101138182910.01%1801329925.245610115752594136622735.24%00.64750
5Morgan Rielly391612773387140263647756110.87%439883422.60498813739008821310.00%10.7700

Blues Leaders des statistiques des gardiens (saison régulière)
# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA
1John Gibson387200130360.8983.0822076281211341115302050.754171
2Roberto Luongo359117200220.8973.662017749101229119090870.693101
3Juuse Saros19710667170.9032.9911573128576593201010.73861
4Devan Dubnyk1437251180.9102.90850614141145431903820.72892
5Jaroslav Halak93522730.9013.00505816525325480510.91323

Blues Statistiques de l'Équipe de Carrière
TotalDomicileVisiteur
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
Saison régulière
20178231400025425724710411421001321271261411719001221301219642574126691006010092258707848898932509810132219522895017.30%2634981.37%71000199350.18%994208347.72%688136650.37%1789101518338201507762
201882323404543230237-741132101411104128-24411913031321261091777230366596040569274250707819397622510808107420622284419.30%2554383.14%5946193848.81%999201949.48%688135550.77%167190817507831554757
201982302905468237244-741151602242120125-541151303226117119-274237375612120447910325280650870956261079789016362285423.68%2154380.00%31029201651.04%988207047.73%581118549.03%163086918077811563782
202082293502286235267-3241171601043130135-541121901243105132-2764235368603000597789257207429898112605904115317302374619.41%2314281.82%11076208851.53%1052208950.36%667127852.19%165188918067751539769
202182274204225210255-4541142001114112126-144113220311198129-3164210380590230648060231807787827312562766118918844247417.45%4808482.50%31524286053.29%1444316345.65%645125551.39%1853124320796321036506
202282214807042217265-4841112105031121138-174110270201196127-3156217386603330686573230207687337722777789105719374356414.71%4438880.14%31415291948.48%1478327645.12%593127546.51%1847123720836321029502
202382264601144220323-10341142101122111154-4341122500022109169-6055220385605230847061242208097628313007845126820024348419.35%52012176.73%21534300151.12%1605341746.97%686135150.78%1734112622046491027490
202482125602237215369-1544192401115111163-524133201122104206-10243215380595320756768216507056897443159873128420423748221.93%55713975.04%61246273345.59%1522345744.03%593139942.39%1709110322246531048490
202582126100324181363-182414310031288188-100418300001293175-8235181320501210556064213206986817423133902140121943745213.90%60415274.83%41062266239.89%1333348438.26%539131341.05%1747113621716421038485
202682245000260257362-10541181800230140158-184163200030117204-8762257451708110958670233607707667933104902142021233697520.33%59716472.53%41242281044.20%1368345539.59%601141542.47%1753115621826321019477
202782165005245233363-1304172802202113189-764192203043120174-5457233411644100827963231408227347332943822120320954038721.59%51614372.29%61100281939.02%1266316240.04%522140337.21%1789118121446411044497
20308235300534528025624412111030331551233241141902312125133-8962804947742109110080280708599739372436721974184144310122.80%4168380.05%61677322751.97%1530294351.99%628130348.20%1947131719796311053523
20318239240326829224943412310012231391033641161402045153146710629252081200010294872775085592595424897781056182842510023.53%4268081.22%11668319152.27%1543304350.71%648130149.81%2025139419396181036520
20328241240337427021753412211011511289830411913022231421192310927046973917098818125930801881879227767084317424047117.57%3474886.17%41578303551.99%1435276751.86%667128951.75%2135149618185991033536
203382551703421344211133412970122018910782412610022011551045112534462096414013110510328150933931933219460977516764399722.10%3146080.89%41696316753.55%1408265053.13%683130252.46%2195155917295791031546
2034824326034332952395641231201221144102424120140221215113714105295523818040116878628090917918944242265397917794259121.41%4065686.21%101737314355.27%1542288453.47%716133953.47%2034140318846131040526
20358235330444226725413411915031211451261941161801321122128-6922674827491401158262263209069147922645778103617943895814.91%4147083.09%51631300354.31%1463307947.52%678131151.72%1988137019526011027514
20368233310574229027911411718004111431367411613053311471434932905047940301099478269508699398492550779102816724449320.95%4227582.23%61603302652.97%1493291051.31%673133450.45%2016139619336101031514
203782472107313341263784123140210117313835412470521216812543116341601942321331029882727898906889562563763913178043610223.39%3958279.24%61507295850.95%1406301946.57%649128250.62%2046143818995921014520
2038761000003916234310000024915330000001578123970109001581602891048410101883765161471429.79%28196.43%016530953.40%12622855.26%6812753.54%187132143518847
Total Saison régulière156559469806355797649105279-36978331633602630403525172572-5578227836203725394123932707-314150549108517134272444148161416121402483251002154371630515112506831500620930359307247143919.86%7849162379.32%86264365289849.98%259955519847.09%122132518348.50%357552337737568125442176910771
Séries éliminatoires
2019734000001921-231200000912-342200000109161932510004771970478160248695614413538.46%15193.33%18116150.31%9519249.48%459547.37%135681717214472
2030137600000363606420000019172734000001719-21436661020101012143710110109142446140185330711521.13%801285.00%021949843.98%27953951.76%8821041.90%28918734710417283
203118108000006061-1945000002936-7963000003125620601021620002019195810195178191585166201404892426.97%861681.40%130866446.39%31367646.30%17030855.19%435296449136233117
20321510500000643925844000003626107610000028131520641161800002525145090159162153431115141320961515.63%641379.69%030260050.33%27256847.89%13526850.37%412289350115195105
203311650000043331063300000221755320000021165124380123000132184110118151130323104111244681319.12%45784.44%023948249.59%18437049.73%8818846.81%3032112418214274
2034514000001820-230300000812-421100000108221832500004861580396257172556011326726.92%29775.86%110218654.84%10118554.59%479251.09%12082113366532
2035624000001719-232100000119230300000610-441728451006561850586655180608215424520.83%33681.82%111623050.43%11423149.35%5310351.46%13993154457536
2036514000001316-32020000047-3312000009902132437000382145049563818369589917211.76%29582.76%07716646.39%9419548.21%408547.06%11376127376230
20371511400000595187520000031274862000002824422591061650019231525371871961468502151163326881517.05%58984.48%127557647.74%25355745.42%11925546.67%38226934310918794
Total Séries éliminatoires955144000003292963347232400000169163648282000000160133271023295869151119108120783094187971101183430709291057213449210120.53%4397682.69%51719356348.25%1705351348.53%785160448.94%2333157622997401279647

Blues Leaders statistiques (séries éliminatoires)
# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS
1Drew Doughty4694049-471151801217.44%68118125.6851823860112100.00%00.8300
2Jared Spurgeon469394871234881137.96%70106923.2671118730003200.00%00.9000
3Morgan Rielly396323811303945738.22%5588622.7201111481011000.00%00.8600
4Mika Zibanejad37132134431388710612.26%572719.6639122210122051.26%00.9300
5Sam Reinhart46181634-72286811815.25%886218.7467132500005150.59%00.7900

Blues Leaders des statistiques des gardiens (séries éliminatoires)
# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA
1John Gibson55311860.9052.9033950116417180300.0000
2Connor Hellebuyck1511300.8993.2285800464570000.0000
3Devan Dubnyk73220.9152.794510021248108100.0000
4Juuse Saros113530.9063.0467200343620010.0000
5Mike Condon42000.9221.83164005640100.0000