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Connexion

Marlies
GP: 82 | W: 57 | L: 21 | OTL: 4 | P: 118
GF: 369 | GA: 259 | PP%: 26.00% | PK%: 75.73%
DG: Eug Sorokin | Morale : 98 | Moyenne d’équipe : 64

Centre de jeu
Marlies
57-21-4, 118pts
8
FINAL
2 Bruins
24-47-11, 59pts
Team Stats
W2SéquenceW1
30-8-3Fiche domicile10-25-6
27-13-1Fiche domicile14-22-5
7-2-1Derniers 10 matchs2-7-1
4.50Buts par match 3.70
3.16Buts contre par match 4.82
26.00%Pourcentage en avantage numérique24.70%
75.73%Pourcentage en désavantage numérique72.25%
Aces
56-19-7, 119pts
0
FINAL
2 Marlies
57-21-4, 118pts
Team Stats
L2SéquenceW2
29-11-1Fiche domicile30-8-3
27-8-6Fiche domicile27-13-1
6-3-1Derniers 10 matchs7-2-1
3.71Buts par match 4.50
2.93Buts contre par match 3.16
23.78%Pourcentage en avantage numérique26.00%
80.31%Pourcentage en désavantage numérique75.73%
Meneurs d'équipe
Mark JankowskiButs
Mark Jankowski
41
Lars EllerPasses
Lars Eller
61
Lars EllerPoints
Lars Eller
93
Lars EllerPlus/Moins
Lars Eller
64
Philipp GrubauerVictoires
Philipp Grubauer
55
Marcus HogbergPourcentage d’arrêts
Marcus Hogberg
0.903

Statistiques d’équipe
Buts pour
369
4.50 GFG
Tirs pour
2794
34.07 Avg
Pourcentage en avantage numérique
26.0%
52 GF
Début de zone offensive
40.8%
Buts contre
259
3.16 GAA
Tirs contre
2382
29.05 Avg
Pourcentage en désavantage numérique
75.7%%
50 GA
Début de la zone défensive
37.8%
Informations de l'équipe

Directeur généralEug Sorokin
EntraîneurSheldon Keefe
DivisionAtlantic
ConférenceEastern Conference
CapitaineErik Johnson
Assistant #1Jack Johnson
Assistant #2Lars Eller


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro17
Équipe Mineure18
Limite contact 35 / 50
Espoirs14


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
1Maxim Tsyplakov (R)X100.00806178687676886950736260556769088650272750,000$
2Lars Eller (A)X100.00675878647373906974676468548580089650361500,000$
3Mark JankowskiXX100.00636085667771746968607175517574091650312500,000$
4Philip TomasinoX100.00695593756972757550697059516163088650244500,000$
5Mitchell ChaffeeX100.00806188707470787150646860516767089640281500,000$
6Mattias JanmarkX100.00645786657473906456685272507676087640332500,000$
7Vasily PodkolzinXX100.00826184677072926750666067506164088640244500,000$
8Linus Karlsson (R)XXX100.00685687676366557150606159506362088600263750,000$
9Jan RuttaX100.00686075627471726950615475558381088660351500,000$
10Calvin de HaanX100.00755786626867687150655472558179088650341500,000$
11Erik Johnson (C)X100.00776885597965626550575575558784088650381500,000$
12Jack Johnson (A)X100.00645797607864646950645472558884088650391500,000$
13Travis HamonicX100.00736488616871766850605572558380088650351500,000$
14Justin HollX100.00625789617067856750595372557978088640341500,000$
15Marc Del Gaizo (R)X100.00726484636670686550585068556567088620261500,000$
Rayé
MOYENNE D’ÉQUIPE100.0071608665727076695363596853757408864
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
1Philipp Grubauer100.0064736971726766686450707777080660341500,000$
2Marcus Hogberg100.0061676684576357565450666969089610311500,000$
Rayé
MOYENNE D’ÉQUIPE100.006370687865656262595068737308564
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Sheldon Keefe7585859075751CAN456500,000$


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
1Logan StankovenToronto Maple LeafsC/RW73306595540221782597718611.58%8149220.4531720391530001656154.40%192100001.2702000734
2Lars EllerMarlies (TOR)C8232619364260782252637921412.17%13175121.3669152614700041305462.92%219000111.06120003132
3Philip TomasinoMarlies (TOR)RW8237478432240741083039221012.21%12153618.74268251210110542345.39%14100011.0912000965
4Jan RuttaMarlies (TOR)D811652685034014259104367815.38%76164320.297111847164000181100%000110.8300000328
5Mitchell ChaffeeMarlies (TOR)RW8225426742240123862427718510.33%4148218.08448231360001282148.18%11000000.9000000655
6Calvin de HaanMarlies (TOR)D829576635520141709932799.09%101168020.503912291681012121200%000000.7900000162
7Mattias JanmarkMarlies (TOR)C822244663510079156181519812.15%19148918.1702231802251194153.47%178800000.8900000175
8Vasily PodkolzinMarlies (TOR)LW/RW8230366619340177802276317113.22%17167520.4345914911011824147.90%11900000.7900000707
9Maxim TsyplakovMarlies (TOR)RW8218466418460183101238621597.56%9155719.0031013301500220134254.05%11100000.8233000333
10Mark JankowskiMarlies (TOR)C/LW49412162308043691876413621.93%14105921.621348440001888155.81%8600011.1701000555
11Viktor ArvidssonToronto Maple LeafsLW493524593710022551765012619.89%797819.98651121950005756146.84%7900001.2101000852
12Travis HamonicMarlies (TOR)D821539542647151316186254717.44%83155618.9934715741011120010%000000.6900201344
13Jack JohnsonMarlies (TOR)D82742492722064798332448.43%83160119.5324631911012134310%000000.6100000014
14Erik JohnsonMarlies (TOR)D821532474054018967109348313.76%89165820.23751248154000068100%000000.5700000224
15Justin HollMarlies (TOR)D828354329400855455144414.55%72141317.24101590112134100%000000.6100000102
16Linus KarlssonMarlies (TOR)C/LW/RW72161430241607250128388212.50%394713.160002100000265150.68%22100000.6300000243
17Marc Del GaizoMarlies (TOR)D8228108602714133815.38%253384.1300000000032100%000000.5900000001
Statistiques d’équipe totales ou en moyenne1308358665102352145715165215122753829195013.00%6352386518.25529414636616354610261380551856.31%676600240.86511201616666
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
1Philipp GrubauerMarlies (TOR)82551930.8913.1546304424322370100.4297820512
2Marcus HogbergMarlies (TOR)92210.9032.7230900141450000.5004082000
Statistiques d’équipe totales ou en moyenne91572140.8923.124939442572382010118282512


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 Pays 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 Forcer UFA Rappel d'urgence Type Salaire actuel Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 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
Calvin de HaanMarlies (TOR)D341991-05-09CANNo192 Lbs6 ft1NoNoFree AgentNoNo12025-08-24FalseFalsePro & Farm500,000$50,000$0$No---------------------------Lien / Lien NHL
Erik JohnsonMarlies (TOR)D381988-03-21USANo225 Lbs6 ft4NoNoFree AgentNoNo12025-08-24FalseFalsePro & Farm500,000$50,000$0$No---------------------------Lien / Lien NHL
Jack JohnsonMarlies (TOR)D391987-01-13USANo225 Lbs6 ft2NoNoFree AgentNoNo12025-08-24FalseFalsePro & Farm500,000$50,000$0$No---------------------------Lien / Lien NHL
Jan RuttaMarlies (TOR)D351990-07-29CZENo204 Lbs6 ft3NoNoFree AgentNoNo12025-08-24FalseFalsePro & Farm500,000$50,000$0$No---------------------------Lien / Lien NHL
Justin HollMarlies (TOR)D341992-01-30USANo194 Lbs6 ft4NoNoFree AgentNoNo12025-08-24FalseFalsePro & Farm500,000$50,000$0$No---------------------------Lien / Lien NHL
Lars EllerMarlies (TOR)C361989-05-08DNKNo208 Lbs6 ft2NoNoFree Agent2025-03-02NoNo12025-08-17FalseFalsePro & Farm500,000$50,000$0$No---------------------------Lien / Lien NHL
Linus KarlssonMarlies (TOR)C/LW/RW261999-11-16SWEYes178 Lbs6 ft1NoNoFree AgentNoNo32024-09-12FalseFalsePro & Farm750,000$75,000$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien / Lien NHL
Marc Del GaizoMarlies (TOR)D261999-10-11USAYes188 Lbs5 ft11NoNoFree AgentNoNo12025-08-24FalseFalsePro & Farm500,000$50,000$0$No---------------------------Lien
Marcus HogbergMarlies (TOR)G311994-11-25SWENo234 Lbs6 ft5NoNoFree AgentNoNo12025-08-24FalseFalsePro & Farm500,000$50,000$0$No---------------------------Lien / Lien NHL
Mark JankowskiMarlies (TOR)C/LW311994-09-13CANNo212 Lbs6 ft4NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$0$No500,000$--------500,000$--------No--------Lien / Lien NHL
Mattias JanmarkMarlies (TOR)C331992-12-08SWENo205 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$0$No500,000$--------500,000$--------No--------Lien / Lien NHL
Maxim TsyplakovMarlies (TOR)RW271998-09-19RUSYes210 Lbs6 ft3NoNoFree AgentNoNo22025-08-08FalseFalsePro & Farm750,000$75,000$0$No750,000$--------750,000$--------No--------Lien / Lien NHL
Mitchell ChaffeeMarlies (TOR)RW281998-01-26USANo204 Lbs6 ft1NoNoFree AgentNoNo12025-08-24FalseFalsePro & Farm500,000$50,000$0$No---------------------------Lien / Lien NHL
Philip TomasinoMarlies (TOR)RW242001-07-28CANNo190 Lbs6 ft0NoNoFree AgentNoNo42025-07-23FalseFalsePro & Farm500,000$50,000$0$No500,000$500,000$500,000$------500,000$500,000$500,000$------NoNoNo------Lien / Lien NHL
Philipp GrubauerMarlies (TOR)G341991-11-25DEUNo188 Lbs6 ft1NoNoFree AgentNoNo12025-08-17FalseFalsePro & Farm500,000$50,000$0$No---------------------------Lien / Lien NHL
Travis HamonicMarlies (TOR)D351990-08-16CANNo195 Lbs6 ft0NoNoFree AgentNoNo12025-08-24FalseFalsePro & Farm500,000$50,000$0$No---------------------------Lien / Lien NHL
Vasily PodkolzinMarlies (TOR)LW/RW242001-06-24RUSNo190 Lbs6 ft1NoNoFree AgentNoNo42025-07-23FalseFalsePro & Farm500,000$50,000$0$No500,000$500,000$500,000$------500,000$500,000$500,000$------NoNoNo------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1731.47202 Lbs6 ft21.65529,412$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Mark JankowskiLars EllerMaxim Tsyplakov35122
2Vasily PodkolzinMattias JanmarkPhilip Tomasino35122
3Mark JankowskiLinus KarlssonMitchell Chaffee25122
4Mark JankowskiLars EllerLinus Karlsson5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jan RuttaCalvin de Haan35122
2Erik JohnsonJack Johnson35122
3Travis HamonicJustin Holl30122
4Marc Del GaizoJan Rutta0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Mark JankowskiLars EllerMaxim Tsyplakov60122
2Vasily PodkolzinMattias JanmarkPhilip Tomasino40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jan RuttaCalvin de Haan60122
2Erik JohnsonJack Johnson40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Lars EllerMark Jankowski60122
2Mattias JanmarkVasily Podkolzin40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jan RuttaCalvin de Haan60122
2Erik JohnsonJack Johnson40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Lars Eller60122Jan RuttaCalvin de Haan60122
2Mattias Janmark40122Erik JohnsonJack Johnson40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Lars EllerMark Jankowski60122
2Mattias JanmarkVasily Podkolzin40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jan RuttaCalvin de Haan60122
2Erik JohnsonJack Johnson40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Mark JankowskiLars EllerMaxim TsyplakovJan RuttaCalvin de Haan
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Mark JankowskiLars EllerMaxim TsyplakovJan RuttaCalvin de Haan
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Vasily Podkolzin, Mitchell Chaffee, Mattias JanmarkVasily Podkolzin, Mitchell ChaffeeVasily Podkolzin
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Travis Hamonic, Justin Holl, Marc Del GaizoTravis HamonicTravis Hamonic, Justin Holl
Tirs de pénalité
Maxim Tsyplakov, Philip Tomasino, Mark Jankowski, Lars Eller, Vasily Podkolzin
Gardien
#1 : Philipp Grubauer, #2 : Marcus Hogberg


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
1Aces3120000035-2211000003211010000003-320.3333470114213388107291398387831621712549111.11%6183.33%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
2Admirals4310000014113220000008622110000065160.7501425390014213388101039139838783110630385310220.00%18572.22%11540275855.84%1442255056.55%837144657.88%2238162116675461039552
3Americiens6330000026233321000001376312000001316-360.50026477300142133881021791398387831227633013914321.43%12558.33%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
4Barons22000000954110000004311100000052341.0009142300142133881076913983878315114838300.00%4250.00%11540275855.84%1442255056.55%837144657.88%2238162116675461039552
5Barracuda3300000021101122000000177101100000043161.00021396000142133881012791398387831681716687342.86%8275.00%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
6Broncos53101000201283110100087122000000125780.8002038580014213388101469139838783112633228615533.33%7185.71%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
7Bruins6310200028161231101000131213200100015411100.83328517901142133881019791398387831150452610316318.75%11372.73%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
8Canucks22000000743110000004221100000032141.0007132000142133881065913983878314081225300.00%60100.00%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
9Fighting Pandas7410000229254310000021617-1431000001385100.71429548301142133881020491398387831175494413920420.00%20955.00%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
10Firebirds5400010025141132000100147722000000117490.9002547720014213388101709139838783110334107412541.67%4175.00%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
11Griffins211000001073110000005141010000056-120.5001018280014213388106991398387831721710364250.00%50100.00%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
12Ice Bats220000001055110000005321100000052341.000101929001421338810679139838783174206456116.67%3166.67%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
13Lions210000101174100000107611100000041341.0001115260014213388108891398387831761410434125.00%3166.67%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
14Lynx6420000026111532100000137632100000134980.66726477301142133881021891398387831124383311010220.00%140100.00%11540275855.84%1442255056.55%837144657.88%2238162116675461039552
15Nordiks2110000079-21010000037-41100000042220.50071421001421338810869139838783175202343100.00%9455.56%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
16Quacken22000000963110000003121100000065141.0009172600142133881049913983878315218143711100.00%7357.14%11540275855.84%1442255056.55%837144657.88%2238162116675461039552
17Roadrunners4220000020155211000001055211000001010040.5002037570014213388101019139838783111122359512650.00%15753.33%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
18Rocket1063001005239133210000014957420010038308130.650529614800142133881037891398387831390987024232825.00%33487.88%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
19Tomahawks2110000011101110000006331010000057-220.5001120310014213388109791398387831692310557228.57%4175.00%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
20Wombats42101000191362100100096321100000107360.750193453001421338810133913983878311203420957228.57%90100.00%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
21Wranglers31101000121202100100011921010000013-240.667122436001421338810131913983878311112318837114.29%80100.00%01540275855.84%1442255056.55%837144657.88%2238162116675461039552
Total8251210521236925911041258041121861275941261301100183132511180.7203696731042041421338810279491398387831238263746716632005226.00%2065075.73%41540275855.84%1442255056.55%837144657.88%2238162116675461039552
_Since Last GM Reset8251210521236925911041258041121861275941261301100183132511180.7203696731042041421338810279491398387831238263746716632005226.00%2065075.73%41540275855.84%1442255056.55%837144657.88%2238162116675461039552
_Vs Conference57341504202259179802715603102118833530199011001419645800.702259476735031421338810186791398387831163244632811361484027.03%1433575.52%21540275855.84%1442255056.55%837144657.88%2238162116675461039552
_Vs Division35201002102161114471584010026952172012601100926230470.6711612954560314213388101214913983878311066293203733922021.74%902176.67%11540275855.84%1442255056.55%837144657.88%2238162116675461039552

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
82118W2369673104227942382637467166304
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8251215212369259
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
412584112186127
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4126131100183132
Derniers 10 matchs
WLOTWOTL SOWSOL
720001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2005226.00%2065075.73%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
913983878311421338810
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
1540275855.84%1442255056.55%837144657.88%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2238162116675461039552


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
13Marlies2Rocket4LSommaire du match
27Marlies6Fighting Pandas1WSommaire du match
621Bruins4Marlies2LSommaire du match
730Marlies5Rocket6LXSommaire du match
941Rocket4Marlies3LSommaire du match
1256Marlies2Lynx3LSommaire du match
1360Marlies4Rocket5LSommaire du match
1466Firebirds4Marlies3LXSommaire du match
1883Marlies7Rocket3WSommaire du match
1990Broncos1Marlies2WSommaire du match
22107Americiens3Marlies2LSommaire du match
25118Marlies7Rocket3WSommaire du match
27128Lynx4Marlies3LSommaire du match
29140Marlies3Bruins2WXSommaire du match
31147Marlies3Fighting Pandas0WSommaire du match
32154Fighting Pandas8Marlies7LXXSommaire du match
33161Marlies6Americiens4WSommaire du match
37176Wranglers6Marlies7WSommaire du match
40188Marlies1Wranglers3LSommaire du match
42197Tomahawks3Marlies6WSommaire du match
45213Marlies4Barracuda3WSommaire du match
46218Wombats2Marlies4WSommaire du match
49232Marlies5Barons2WSommaire du match
50241Rocket2Marlies6WSommaire du match
53258Americiens2Marlies6WSommaire du match
54268Marlies3Admirals4LSommaire du match
56275Marlies5Tomahawks7LSommaire du match
58285Nordiks7Marlies3LSommaire du match
61300Marlies7Firebirds5WSommaire du match
62307Broncos3Marlies2LSommaire du match
63314Marlies6Broncos2WSommaire du match
66328Wombats4Marlies5WXSommaire du match
69342Marlies5Wombats1WSommaire du match
70350Broncos3Marlies4WXSommaire du match
74365Marlies4Fighting Pandas3WSommaire du match
75373Admirals4Marlies5WSommaire du match
79393Roadrunners1Marlies7WSommaire du match
81405Marlies4Lions1WSommaire du match
82415Firebirds1Marlies7WSommaire du match
85427Marlies8Lynx1WSommaire du match
87437Firebirds2Marlies4WSommaire du match
89449Marlies0Aces3LSommaire du match
91455Marlies4Nordiks2WSommaire du match
93462Bruins4Marlies5WXSommaire du match
96477Wranglers3Marlies4WXSommaire du match
98486Marlies5Wombats6LSommaire du match
100497Marlies6Quacken5WSommaire du match
101505Quacken1Marlies3WSommaire du match
103515Marlies3Canucks2WSommaire du match
105526Lynx2Marlies4WSommaire du match
107541Marlies4Firebirds2WSommaire du match
108548Barons3Marlies4WSommaire du match
112566Bruins4Marlies6WSommaire du match
113573Marlies3Americiens5LSommaire du match
116586Admirals2Marlies3WSommaire du match
118594Marlies6Broncos3WSommaire du match
120605Marlies5Griffins6LSommaire du match
121613Rocket3Marlies5WSommaire du match
124633Ice Bats3Marlies5WSommaire du match
126642Marlies5Rocket3WSommaire du match
128652Marlies0Fighting Pandas4LSommaire du match
130658Roadrunners4Marlies3LSommaire du match
131664Marlies3Lynx0WSommaire du match
133680Americiens2Marlies5WSommaire du match
135690Marlies8Rocket6WSommaire du match
138701Lynx1Marlies6WSommaire du match
139710Marlies5Ice Bats2WSommaire du match
141721Lions6Marlies7WXXSommaire du match
146739Griffins1Marlies5WSommaire du match
147749Marlies4Americiens7LSommaire du match
149758Marlies7Roadrunners4WSommaire du match
150768Barracuda3Marlies9WSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
154787Barracuda4Marlies8WSommaire du match
158803Marlies3Admirals1WSommaire du match
159809Fighting Pandas4Marlies5WSommaire du match
163827Canucks2Marlies4WSommaire du match
167846Fighting Pandas5Marlies4LXXSommaire du match
168853Marlies4Bruins0WSommaire du match
171865Aces2Marlies1LSommaire du match
173874Marlies3Roadrunners6LSommaire du match
176889Marlies8Bruins2WSommaire du match
178896Aces0Marlies2WSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,493,064$ 900,000$ 900,000$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
900,000$ 993,057$ 17 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 7,778$ 0$




Marlies 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

Marlies 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

Marlies 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

Marlies 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

Marlies 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