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Connexion

Blues
GP: 82 | W: 44 | L: 30 | OTL: 8 | P: 96
GF: 269 | GA: 269 | PP%: 16.81% | PK%: 77.66%
DG: Daniel Duchesne | Morale : 67 | Moyenne d’équipe : 66
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Centre de jeu
Flames
31-42-9, 71pts
3
FINAL
4 Blues
44-30-8, 96pts
Team Stats
W1SéquenceL1
16-24-1Fiche domicile25-12-4
15-18-8Fiche domicile19-18-4
4-5-1Derniers 10 matchs5-4-1
2.93Buts par match 3.28
3.51Buts contre par match 3.28
15.32%Pourcentage en avantage numérique16.81%
79.52%Pourcentage en désavantage numérique77.66%
Blues
44-30-8, 96pts
2
FINAL
5 Capitals
43-33-6, 92pts
Team Stats
L1SéquenceW1
25-12-4Fiche domicile23-16-2
19-18-4Fiche domicile20-17-4
5-4-1Derniers 10 matchs7-2-1
3.28Buts par match 3.16
3.28Buts contre par match 3.21
16.81%Pourcentage en avantage numérique18.85%
77.66%Pourcentage en désavantage numérique84.30%
Meneurs d'équipe
Buts
Nicolas Roy
42
Passes
Austin Czarnik
58
Points
Nicolas Roy
91
Plus/Moins
Nicolas Roy
30
Victoires
Malcolm Subban
41
Pourcentage d’arrêts
Malcolm Subban
0.911

Statistiques d’équipe
Buts pour
269
3.28 GFG
Tirs pour
2561
31.23 Avg
Pourcentage en avantage numérique
16.8%
40 GF
Début de zone offensive
36.1%
Buts contre
269
3.28 GAA
Tirs contre
2695
32.87 Avg
Pourcentage en désavantage numérique
77.7%%
61 GA
Début de la zone défensive
39.8%
Informations de l'équipe

Directeur généralDaniel Duchesne
EntraîneurDave Cameron
DivisionCentrale
ConférenceOuest
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,950
Billets de saison1,800


Informations de la formation

Équipe Pro39
Équipe Mineure18
Limite contact 57 / 60
Espoirs25


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
1Austin Czarnik (R)X100.0063408175698277907391836625707967777403132,000,000$
2Nicolas Roy (R)X100.007745797885878481838176772578766480740271800,000$
3Tomas Hyka (R)X100.0072545478675287963596885550786534797403132,000,000$
4Drake Caggiula (R)X100.0077448571765682864784816955798430687302911,500,000$
5Kirby Dach (R)X100.0070556976908781826278747125786654797202332,000,000$
6Yakov Trenin (R)X100.0082557177838683805072727425786654807102731,500,000$
7Lukas Sedlak (R)X100.006945797381847770716563702570796773670313700,000$
8Kevin Roy (R)X100.004837857368639972467069665181654880670303600,000$
9Logan Shaw (R)X100.008581876677646564786561685982726225640313575,000$
10Dmytro Timashov (R)X100.006920996871798457566060626876735080630273575,000$
11Matthew Highmore (R)X100.005640697061666765667066612576726179630283575,000$
12Kenny Agostino (R)X100.008249676574548864516456646170673579620322575,000$
13Braden Schneider (R)X100.007860897788847877407366782574594979732223925,000$
14Jaycob Megna (R)X100.0071557871888782724071627625697967767103131,500,000$
15Nils Lundkvist (R)X100.006850778080857677406969702576594969702233925,000$
16Nick Blankenburg (R)X100.006745777973886873406966712574594972692253825,000$
17Jake Christiansen (R)X100.006240827582846868406459662568594973662243925,000$
18Wyatt Kalynuk (R)X100.006233997273787958305961655472734865650271925,000$
Rayé
1Maksim Sushko (R)X100.004825996575768272676870586367696634650251775,000$
2Garrett Pilon (R)X100.008270696872626154807066635970686120620261750,000$
3Nolan Foote (R)X100.006445706966626264437268602565685019620231863,333$
4Justin Danforth (R)X100.005540757374846367506162622567585020622313750,000$
5John Quenneville (R)X100.004429996674748058725756686378756619610283575,000$
6Maxim Letunov (R)X100.004526997374707956715449686374716919600283575,000$
7Trey Fix-Wolansky (R)X100.005440667156636469456664572568525020602243750,000$
8Carson Meyer (R)X100.006040656961626161426154602561535020570262750,000$
9Jonathan Gruden (R)X100.005459637059626262586059522564515019572243788,333$
10Luke Witkowski (R)X100.008969606278687361565854686592884041660343700,000$
11Marc-Andre GragnaniX100.0072996675607158695341905199961820640371575,000$
12Gustav Olofsson (R)X100.006140996776626870306759672558585118630292575,000$
13Paul LaDue (R)X100.005315956775616672307168635865633220630313575,000$
14Dillon Heatherington (R)X100.006646626271676862405854732565616220620292575,000$
15Adam Clendening (R)X100.006556606573439356304535715279796119610313575,000$
16Adam Ginning (R)X100.006946627066626363406054692562515020612243883,750$
17Austin Strand (R)X100.007142846579606267256965562548485420600271771,500$
18Dmitri Samorukov (R)X100.006040707064636464406054672563525020602243775,000$
MOYENNE D’ÉQUIPE100.00644478717470746951676367397267524765
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
1Malcolm Subban (R)100.008282807880999999998278838762818603012,000,000$
2Spencer Martin (R)100.008285868087837978818556807871408002821,000,000$
Rayé
1Ivan Prosvetov (R)100.00748083777882787776737266705670750251809,167$
MOYENNE D’ÉQUIPE100.0079828378828885858580697678636480
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dave Cameron72626747857257CAN641800,000$


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
1Nicolas RoyBlues (STL)RW824249913085351961552497715516.87%53169720.711011213319212371946149.78%2276221101.07112232497
2Austin CzarnikBlues (STL)C622558831730101061702215614011.31%28131121.15612182915321361835149.83%17702625001.2719002665
3Drake CaggiulaBlues (STL)LW792946753035151441162387512712.18%38152319.28512173219910141033638.71%1244624000.9815003445
4Tomas HykaBlues (STL)RW823037674169651931182908315810.34%35154418.833581916801161205231.20%1256219010.87511454801
5Kirby DachBlues (STL)C8227366314133551321732155713412.56%35143717.547714181700000122244.23%15422533000.8805236416
6Kevin RoyBlues (STL)RW82302454110047842075414214.49%30107413.10011017000014249.28%694328011.0101000354
7Yakov TreninBlues (STL)LW82222042-3103551641191726810712.79%33140817.1845919155000083140.43%943435000.6003335323
8Lukas SedlakBlues (STL)C78162036-23210144144173581069.25%35113114.510330530003384048.46%8442014000.6400101522
9Nick BlankenburgBlues (STL)D775212644210781317941426.33%83159920.7810121310002126100%12952000.3300101000
10Jaycob MegnaBlues (STL)D8242125-581451201477528405.33%111197324.06358112280000246100%01962000.2500234001
11Nils LundkvistBlues (STL)D6731821465251001149842453.06%78147722.0510141250001149100%02758000.2811221000
12Matthew HighmoreBlues (STL)C829918-1618058649234769.78%167058.61011040001140043.09%3761910000.5100000311
13Jake ChristiansenBlues (STL)D770171724631554945928160%75134617.49000460000046000%0853000.2500102002
14Dmytro TimashovBlues (STL)LW826915420957753153711.32%22101012.32000010000112137.50%48814000.3024000020
15Braden SchneiderBlues (STL)D6001515-28050731149039330%80139423.2403371600001159000%03050000.2200604000
16Wyatt KalynukBlues (STL)D730141416151541694114160%56114815.7300001000057000%01235000.2401111000
17Kenny AgostinoBlues (STL)LW82549-1314090484272911.90%116838.34000030000730041.18%1757000.2602000002
18Maksim SushkoBlues (STL)RW46448-8006268118374.94%94028.74000030002410058.54%41163000.4000000000
19Logan ShawBlues (STL)RW36347-61010232925112112.00%83078.53000000001390154.55%11115000.4611002001
20Luke WitkowskiBlues (STL)D5305511115591733417120%4993517.66000141000157000%0326000.1101542000
21Garrett PilonBlues (STL)C202133402815154813.33%71718.5600000000001058.90%7343000.3500000000
22Maxim LetunovBlues (STL)C41011001341025.00%0317.9800000000020063.64%1110000.6300000000
23Nolan FooteBlues (STL)LW3011-220737060%13913.160000000000000%110000.5100000000
24Dillon HeatheringtonBlues (STL)D1000-100111000%31414.220000000001000%00000000000000
25Gustav OlofssonBlues (STL)D2000-300100000%32713.630000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne1476263433696921104470199320872561827148710.27%8992439816.5340651051791873448351691381746.74%5374511577120.571256302440403240
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
1Malcolm SubbanBlues (STL)68411950.9112.903973401922148901320.818446418585
2Spencer MartinBlues (STL)82500.8315.463740034201940000817000
3Ivan ProsvetovBlues (STL)121630.8983.246482035344154000.545111047010
Statistiques d’équipe totales ou en moyenne88443080.9033.144996602612693114932558282595


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 Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Type Salaire actuel Salaire restantPlafond salarial Non Activé Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Non-échange Année 2Non-échange Année 3Non-échange Année 4Non-échange Année 5Non-échange Année 6Non-échange Année 7Non-échange Année 8Non-échange Année 9Non-échange Année 10Lien
Adam ClendeningBlues (STL)D311992-10-26 05:11:13Yes196 Lbs6 ft0NoNoN/ANoNo3Pro & Farm575,000$0$0$No575,000$575,000$-------NoNo-------
Adam GinningBlues (STL)D242000-01-13 05:49:08Yes196 Lbs6 ft3NoNoN/ANoNo3Pro & Farm883,750$0$0$No883,750$883,750$-------NoNo-------
Austin CzarnikBlues (STL)C311992-12-12 09:09:24Yes170 Lbs5 ft9NoNoN/ANoNo3Pro & Farm2,000,000$0$0$No2,000,000$2,000,000$-------NoNo-------
Austin StrandBlues (STL)D271997-02-17 13:11:19Yes216 Lbs6 ft4NoNoN/ANoNo1Pro & Farm771,500$0$0$No------------------
Braden SchneiderBlues (STL)D222001-09-20 05:51:08Yes208 Lbs6 ft3NoNoN/ANoNo3Pro & Farm925,000$0$0$No925,000$925,000$-------NoNo-------
Carson MeyerBlues (STL)RW261997-08-18 10:28:02Yes181 Lbs5 ft11NoNoN/ANoNo2Pro & Farm750,000$0$0$No750,000$--------No--------
Dillon HeatheringtonBlues (STL)D291995-05-09 08:01:04Yes220 Lbs6 ft4NoNoN/ANoNo2Pro & Farm575,000$0$0$No575,000$--------No--------
Dmitri SamorukovBlues (STL)D241999-06-16 05:53:14Yes187 Lbs6 ft3NoNoN/ANoNo3Pro & Farm775,000$0$0$No775,000$775,000$-------NoNo-------
Dmytro TimashovBlues (STL)LW271996-10-01 01:52:21Yes187 Lbs5 ft10NoNoN/ANoNo3Pro & Farm575,000$0$0$No575,000$575,000$-------NoNo-------
Drake CaggiulaBlues (STL)LW291994-06-20 09:04:53Yes176 Lbs5 ft10NoNoN/ANoNo1Pro & Farm1,500,000$0$0$No------------------
Garrett PilonBlues (STL)C261998-04-13 14:43:50Yes187 Lbs5 ft11NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------
Gustav OlofssonBlues (STL)D291994-11-30 12:34:40Yes198 Lbs6 ft2NoNoN/ANoNo2Pro & Farm575,000$0$0$No575,000$--------No--------
Ivan ProsvetovBlues (STL)G251999-03-05 14:46:51Yes174 Lbs6 ft5NoNoN/ANoNo1Pro & Farm809,167$0$0$No------------------
Jake ChristiansenBlues (STL)D241999-09-12 03:40:14Yes193 Lbs6 ft0NoNoN/ANoNo3Pro & Farm925,000$0$0$No925,000$925,000$-------NoNo-------
Jaycob MegnaBlues (STL)D311992-12-10 13:13:17Yes220 Lbs6 ft6NoNoN/ANoNo3Pro & Farm1,500,000$0$0$No1,500,000$1,500,000$-------NoNo-------
John QuennevilleBlues (STL)RW281996-04-16 03:53:59Yes195 Lbs6 ft1NoNoN/ANoNo3Pro & Farm575,000$0$0$No575,000$575,000$-------NoNo-------
Jonathan GrudenBlues (STL)LW242000-05-04 05:55:07Yes172 Lbs6 ft0NoNoN/ANoNo3Pro & Farm788,333$0$0$No788,333$788,333$-------NoNo-------
Justin DanforthBlues (STL)RW311993-03-15 05:57:01Yes190 Lbs5 ft9NoNoN/ANoNo3Pro & Farm750,000$0$0$No750,000$750,000$-------NoNo-------
Kenny AgostinoBlues (STL)LW321992-04-30 03:56:04Yes199 Lbs6 ft0NoNoN/ANoNo2Pro & Farm575,000$0$0$No575,000$--------No--------
Kevin RoyBlues (STL)RW301993-05-20 09:32:15Yes170 Lbs5 ft9NoNoN/ANoNo3Pro & Farm600,000$0$0$No600,000$600,000$-------NoNo-------
Kirby DachBlues (STL)C232001-01-21 01:49:17Yes212 Lbs6 ft4NoNoN/ANoNo3Pro & Farm2,000,000$0$0$No2,000,000$2,000,000$-------NoNo-------
Logan ShawBlues (STL)RW311992-10-05 12:38:48Yes204 Lbs6 ft3NoNoN/ANoNo3Pro & Farm575,000$0$0$No575,000$575,000$-------NoNo-------
Lukas SedlakBlues (STL)C311993-02-25 03:54:42Yes205 Lbs6 ft0NoNoN/ANoNo3Pro & Farm700,000$0$0$No700,000$700,000$-------NoNo-------
Luke WitkowskiBlues (STL)D341990-04-14 17:11:13Yes210 Lbs6 ft2NoNoN/ANoNo3Pro & Farm700,000$0$0$No700,000$700,000$-------NoNo-------
Maksim SushkoBlues (STL)RW251999-02-10 14:49:46Yes198 Lbs6 ft0NoNoN/ANoNo1Pro & Farm775,000$0$0$No------------------
Malcolm SubbanBlues (STL)G301993-12-21 12:40:46Yes200 Lbs6 ft2NoNoN/ANoNo1Pro & Farm2,000,000$0$0$No------------------
Marc-Andre GragnaniBlues (STL)D371987-03-11 23:11:13No195 Lbs6 ft1NoNoN/ANoNo1Pro & Farm575,000$0$0$No------------------
Matthew HighmoreBlues (STL)C281996-02-27 03:58:58Yes187 Lbs5 ft11NoNoN/ANoNo3Pro & Farm575,000$0$0$No575,000$575,000$-------NoNo-------
Maxim LetunovBlues (STL)C281996-02-20 01:46:09Yes185 Lbs6 ft4NoNoN/ANoNo3Pro & Farm575,000$0$0$No575,000$575,000$-------NoNo-------
Nick BlankenburgBlues (STL)D251998-05-12 03:48:18Yes177 Lbs5 ft9NoNoN/ANoNo3Pro & Farm825,000$0$0$No825,000$825,000$-------NoNo-------
Nicolas RoyBlues (STL)RW271997-02-05 11:36:36Yes202 Lbs6 ft4NoNoN/ANoNo1Pro & Farm800,000$0$0$No------------------
Nils LundkvistBlues (STL)D232000-07-27 05:58:41Yes190 Lbs5 ft11NoNoN/ANoNo3Pro & Farm925,000$0$0$No925,000$925,000$-------NoNo-------
Nolan FooteBlues (STL)LW232000-11-29 14:53:20Yes196 Lbs6 ft3NoNoN/ANoNo1Pro & Farm863,333$0$0$No------------------
Paul LaDueBlues (STL)D311992-09-06 08:46:42Yes200 Lbs6 ft2NoNoN/ANoNo3Pro & Farm575,000$0$0$No575,000$575,000$-------NoNo-------
Spencer MartinBlues (STL)G281995-06-08 05:53:37Yes191 Lbs6 ft3NoNoTrade2024-03-03NoNo2Pro & Farm1,000,000$0$0$No1,000,000$--------No--------
Tomas HykaBlues (STL)RW311993-03-23 13:27:01Yes160 Lbs5 ft11NoNoN/ANoNo3Pro & Farm2,000,000$0$0$No2,000,000$2,000,000$-------NoNo-------
Trey Fix-WolanskyBlues (STL)RW241999-05-26 03:16:15Yes179 Lbs5 ft7NoNoN/ANoNo3Pro & Farm750,000$0$0$No750,000$750,000$-------NoNo-------
Wyatt KalynukBlues (STL)D271997-04-14 04:11:48Yes181 Lbs6 ft1NoNoN/ANoNo1Pro & Farm925,000$0$0$No------------------
Yakov TreninBlues (STL)LW271997-01-13 01:40:29Yes201 Lbs6 ft2NoNoN/ANoNo3Pro & Farm1,500,000$0$0$No1,500,000$1,500,000$-------NoNo-------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3927.77193 Lbs6 ft12.36918,361$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Drake CaggiulaAustin CzarnikNicolas Roy35122
2Yakov TreninKirby DachTomas Hyka35122
3Dmytro TimashovLukas SedlakKevin Roy25122
4Kenny AgostinoMatthew HighmoreLogan Shaw5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Braden SchneiderJaycob Megna35122
2Nils LundkvistNick Blankenburg35122
3Jake ChristiansenWyatt Kalynuk30122
4Braden SchneiderJaycob Megna0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Drake CaggiulaAustin CzarnikNicolas Roy60122
2Yakov TreninKirby DachTomas Hyka40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Braden SchneiderJaycob Megna60122
2Nils LundkvistNick Blankenburg40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Austin CzarnikNicolas Roy60122
2Tomas HykaDrake Caggiula40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Braden SchneiderJaycob Megna60122
2Nils LundkvistNick Blankenburg40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Austin Czarnik60122Braden SchneiderJaycob Megna60122
2Nicolas Roy40122Nils LundkvistNick Blankenburg40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Austin CzarnikNicolas Roy60122
2Tomas HykaDrake Caggiula40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Braden SchneiderJaycob Megna60122
2Nils LundkvistNick Blankenburg40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Drake CaggiulaAustin CzarnikNicolas RoyBraden SchneiderJaycob Megna
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Drake CaggiulaAustin CzarnikNicolas RoyBraden SchneiderJaycob Megna
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Lukas Sedlak, Kevin Roy, Logan ShawLukas Sedlak, Kevin RoyLogan Shaw
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Jake Christiansen, Wyatt Kalynuk, Nils LundkvistJake ChristiansenWyatt Kalynuk, Nils Lundkvist
Tirs de pénalité
Austin Czarnik, Nicolas Roy, Tomas Hyka, Drake Caggiula, Kirby Dach
Gardien
#1 : Malcolm Subban, #2 : Spencer Martin
Lignes d’attaque personnalisées en prolongation
Austin Czarnik, Nicolas Roy, Tomas Hyka, Drake Caggiula, Kirby Dach, Yakov Trenin, Yakov Trenin, Lukas Sedlak, Kevin Roy, Logan Shaw, Matthew Highmore
Lignes de défense personnalisées en prolongation
Braden Schneider, Jaycob Megna, Nils Lundkvist, Nick Blankenburg, Jake Christiansen


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
1Avalanche522010001619-3311010001012-22110000067-160.6001624400079918520141838853834911756113612817317.65%33584.85%1901191447.07%995211247.11%616127948.16%171398718657491424695
2Blackhawks52201000151323200100012752020000036-360.6001527420079918520152838853834911575011313325520.00%25484.00%0901191447.07%995211247.11%616127948.16%171398718657491424695
3Bruins31100010910-11010000036-32100001064240.667910190079918520898388538349110232464500.00%2150.00%0901191447.07%995211247.11%616127948.16%171398718657491424695
4Canadiens320000011257110000007162100000154150.833122032007991852095838853834911094241678225.00%80100.00%0901191447.07%995211247.11%616127948.16%171398718657491424695
5Canucks31200000917-821100000710-31010000027-520.3339162500799185208583885383491933483669222.22%13653.85%0901191447.07%995211247.11%616127948.16%171398718657491424695
6Capitals3120000068-2110000003122020000037-420.333681410799185201098388538349111033686400.00%30100.00%0901191447.07%995211247.11%616127948.16%171398718657491424695
7Devils311000011011-11000000156-12110000055030.50010152500799185207983885383491111312769300.00%6183.33%0901191447.07%995211247.11%616127948.16%171398718657491424695
8Ducks30201000910-1201010005501010000045-120.33391726007991852087838853834918136347314214.29%7442.86%0901191447.07%995211247.11%616127948.16%171398718657491424695
9Flames320000101165100000104312200000073461.00011193000799185209683885383491944732594125.00%11463.64%0901191447.07%995211247.11%616127948.16%171398718657491424695
10Flyers31100100981110000004132010010057-230.500918270079918520958388538349199326703266.67%30100.00%0901191447.07%995211247.11%616127948.16%171398718657491424695
11Islanders31000002910-1210000017701000000123-140.66791221007991852011183885383491982615774250.00%50100.00%0901191447.07%995211247.11%616127948.16%171398718657491424695
12Kings312000001012-21010000035-22110000077020.33310162600799185208683885383491993123724125.00%9277.78%1901191447.07%995211247.11%616127948.16%171398718657491424695
13Maple Leafs3110001014131110000007522010001078-140.66714223600799185209783885383491116308622150.00%4175.00%0901191447.07%995211247.11%616127948.16%171398718657491424695
14Oilers310011001293210001009721000100032150.83312172900799185209883885383491992246721119.09%17570.59%1901191447.07%995211247.11%616127948.16%171398718657491424695
15Penguins32100000761110000003212110000044040.6677101710799185208683885383491843320586116.67%5260.00%0901191447.07%995211247.11%616127948.16%171398718657491424695
16Predators53100001191542110000045-1320000011510570.7001933520079918520150838853834911436715111229620.69%28775.00%0901191447.07%995211247.11%616127948.16%171398718657491424695
17Rangers320010001394110000006422100100075261.000132134007991852010383885383491100301786500.00%6183.33%0901191447.07%995211247.11%616127948.16%171398718657491424695
18Red Wings30001020131031000001032120001010108261.000131932007991852010083885383491117353477400.00%7185.71%0901191447.07%995211247.11%616127948.16%171398718657491424695
19Sabres51400000918-941300000815-71010000013-220.2009172600799185201588388538349116451431238112.50%9366.67%0901191447.07%995211247.11%616127948.16%171398718657491424695
20Senateurs32100000972211000006601100000031240.667913220079918520107838853834911002926758112.50%8275.00%0901191447.07%995211247.11%616127948.16%171398718657491424695
21Sharks30101001810-2200010015501010000035-230.5008142200799185209183885383491934540759111.11%10280.00%0901191447.07%995211247.11%616127948.16%171398718657491424695
22Stars624000002528-3321000001614230300000914-540.3332540650079918520194838853834912084912616330620.00%33778.79%1901191447.07%995211247.11%616127948.16%171398718657491424695
23Wild5120101015150311010008802010001077060.60015254000799185201528388538349114353791262627.69%21385.71%0901191447.07%995211247.11%616127948.16%171398718657491424695
Total82303008266269269041181205123145137841121803143124132-8960.58526943370220799185202561838853834912695899111019932384016.81%2736177.66%4901191447.07%995211247.11%616127948.16%171398718657491424695
_Since Last GM Reset82303008266269269041181205123145137841121803143124132-8960.58526943370220799185202561838853834912695899111019932384016.81%2736177.66%4901191447.07%995211247.11%616127948.16%171398718657491424695
_Vs Conference44151806122149154-52497051118381220611010116673-7490.5571492483970079918520133283885383491138549586310791783016.85%2074976.33%4901191447.07%995211247.11%616127948.16%171398718657491424695
_Vs Division2610110301190900147403000504641237000114044-4290.558901492390079918520789838853834918262806056621272217.32%1402681.43%2901191447.07%995211247.11%616127948.16%171398718657491424695

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8296L1269433702256126958991110199320
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8230308266269269
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4118125123145137
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4112183143124132
Derniers 10 matchs
WLOTWOTL SOWSOL
540001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2384016.81%2736177.66%4
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
8388538349179918520
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
901191447.07%995211247.11%616127948.16%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
171398718657491424695


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
29Sabres5Blues3BLSommaire du match
425Blues3Penguins1AWSommaire du match
532Canucks3Blues4BWR2Sommaire du match
846Blues3Flames1AWR2Sommaire du match
1059Sabres4Blues2BLSommaire du match
1160Blues5Predators4AWSommaire du match
1578Wild1Blues2BWXR5Sommaire du match
19100Blackhawks2Blues5BWSommaire du match
21109Blues3Canadiens1AWSommaire du match
23122Blues2Flyers3ALXSommaire du match
24128Blues4Stars5ALSommaire du match
26137Avalanche4Blues5BWR5Sommaire du match
29152Blues2Blackhawks4ALSommaire du match
30162Stars6Blues5BLSommaire du match
33173Blues5Red Wings4AWXXSommaire du match
35185Sharks4Blues3BLXXR2Sommaire du match
38198Blues3Kings1AWSommaire du match
40209Blackhawks2Blues3BWSommaire du match
42220Blues2Islanders3ALXXSommaire du match
44229Blues4Flames2AWR2Sommaire du match
45238Canucks7Blues3BLSommaire du match
48251Blues3Senateurs1AWSommaire du match
50259Flyers1Blues4BWSommaire du match
52275Blues3Oilers2AWXSommaire du match
54283Kings5Blues3BLR2Sommaire du match
56298Blues2Canadiens3ALXXSommaire du match
57306Canadiens1Blues7BWSommaire du match
61322Blues2Stars4ALSommaire du match
63333Red Wings2Blues3BWXXSommaire du match
65343Blues1Penguins3ALSommaire du match
67355Capitals1Blues3BWSommaire du match
69369Blues1Sabres3ALSommaire du match
71379Sabres1Blues2BWSommaire du match
75397Ducks2Blues3BWXR2Sommaire du match
79413Blues2Canucks7ALR2Sommaire du match
81418Blues1Blackhawks2ALSommaire du match
82428Sharks1Blues2BWXR2Sommaire du match
85443Blues5Red Wings4AWXSommaire du match
87450Blackhawks3Blues4BWXSommaire du match
89458Blues3Flyers4ALSommaire du match
92475Oilers2Blues5BWSommaire du match
96493Rangers4Blues6BWSommaire du match
98503Blues7Predators2AWSommaire du match
100516Devils6Blues5BLXXSommaire du match
102529Blues3Sharks5ALR2Sommaire du match
104541Predators3Blues1BLSommaire du match
109560Predators2Blues3BWSommaire du match
113579Blues4Kings6ALR2Sommaire du match
115586Penguins2Blues3BWSommaire du match
118606Sabres5Blues1BLSommaire du match
121619Blues3Stars5ALSommaire du match
122630Avalanche3Blues4BWXR5Sommaire du match
125645Blues1Devils3ALSommaire du match
127654Stars4Blues5BWSommaire du match
129664Blues5Avalanche2AWR5Sommaire du match
132678Senateurs4Blues3BLSommaire du match
135691Blues3Bruins2AWSommaire du match
136700Blues1Avalanche5ALR5Sommaire du match
138707Stars4Blues6BWSommaire du match
141725Wild1Blues2BWR5Sommaire du match
144739Blues4Ducks5ALSommaire du match
146750Senateurs2Blues3BWSommaire du match
148764Blues4Devils2AWSommaire du match
151775Ducks3Blues2BLR2Sommaire du match
153791Blues3Rangers2AWSommaire du match
154798Wild6Blues4BLR5Sommaire du match
156804Blues4Wild3AWXXSommaire du match
158819Oilers5Blues4BLXSommaire du match
160827Blues3Wild4ALR5Sommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
163846Bruins6Blues3BLSommaire du match
165857Blues3Predators4ALXXSommaire du match
167867Blues5Maple Leafs4AWXXSommaire du match
168874Islanders3Blues4BWSommaire du match
170887Blues4Rangers3AWXSommaire du match
172899Islanders4Blues3BLXXSommaire du match
174908Blues1Capitals2ALSommaire du match
175915Blues2Maple Leafs4ALSommaire du match
177926Avalanche5Blues1BLR5Sommaire du match
179931Blues3Bruins2AWXXSommaire du match
183953Maple Leafs5Blues7BWSommaire du match
189967Flames3Blues4BWXXR2Sommaire du match
190974Blues2Capitals5ALSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3525
Assistance80,85740,108
Assistance PCT98.61%97.82%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2950 - 98.35% 126,198$5,174,138$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
4,411,563$ 3,581,608$ 2,021,608$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 3,611,578$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 22,703$ 0$




Blues Leaders statistiques des joueurs (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

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

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

Blues Leaders statistiques des joueurs (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

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