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Toronto Marlies
GP: 4 | W: 0 | L: 4
GF: 7 | GA: 15 | PP%: 31.25% | PK%: 58.33%
DG: Alexandre Dame | Morale : 15 | Moyenne d’équipe : 58

Centre de jeu
Chicago Wolves
8-6-0, 16pts
2
0 Toronto Marlies
0-4-0, 0pts
Team Stats
L3SéquenceL4
4-3-0Fiche domicile0-2-0
4-3-0Fiche domicile0-2-0
4-5-1Derniers 10 matchs0-4-0
2.64Buts par match 1.75
2.57Buts contre par match 3.75
53.33%Pourcentage en avantage numérique31.25%
74.07%Pourcentage en désavantage numérique58.33%
Chicago Wolves
8-6-0, 16pts
4
2 Toronto Marlies
0-4-0, 0pts
Team Stats
L3SéquenceL4
4-3-0Fiche domicile0-2-0
4-3-0Fiche domicile0-2-0
4-5-1Derniers 10 matchs0-4-0
2.64Buts par match 1.75
2.57Buts contre par match 3.75
53.33%Pourcentage en avantage numérique31.25%
74.07%Pourcentage en désavantage numérique58.33%
Meneurs d'équipe
Buts
Michael Amadio
2
Passes
Nils Hoglander
3
Points
Joshua Ho-Sang
3
Plus/Moins
David Reinbacher
0
Victoires
Dan Vladar
0
Pourcentage d’arrêts
Dan Vladar
0.892

Statistiques d’équipe
Buts pour
7
1.75 GFG
Tirs pour
67
16.75 Avg
Pourcentage en avantage numérique
31.3%
5 GF
Début de zone offensive
36.2%
Buts contre
15
3.75 GAA
Tirs contre
93
23.25 Avg
Pourcentage en désavantage numérique
58.3%%
5 GA
Début de la zone défensive
39.4%
Informations de l'équipe

Directeur généralAlexandre Dame
DivisionNORD-EST
ConférenceConference 1
CapitaineMax Lajoie
Assistant #1Mitchell Stephens
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,311
Billets de saison300


Informations de la formation

Équipe Pro33
Équipe Mineure20
Limite contact 53 / 59
Espoirs26


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
1Michael Amadio0X100.0070359371778387688167696366727151506302732,600,000$
2Nils Hoglander0X100.0071338374668089725166706371666972506302311,100,000$
3Joshua Ho-Sang0X100.006036836770817573537270556872727050620282775,000$
4Jackson Blake (R)0X100.005634887068837569596466616862656350600201775,000$
5Klim Kostin0X100.0082677265937776646263616664686574506002412,000,000$
6Rafael Harvey-Pinard0X100.0066369367658076635864617662656847506002521,100,000$
7Samuel Helenius0X100.008248746593738662716160645863656850600212880,000$
8Jack Finley0X100.008251826196777863696058645963656950590211863,333$
9Landon Slaggert0X100.0063378566707976645862596561636466505802121,350,000$
10Marc-Edouard Vlasic0X100.0062369065788675623066647452927932506203713,250,000$
11Will Borgen0X100.0077727966848890633071587650717050506202732,700,000$
12Denton Mateychuk (R)0X100.006136897169877368306963655861658550610191775,000$
13Nick Blankenburg0X100.006736856865878066306962765267683750610252825,000$
14Ryker Evans0X100.007340826973888568307360645265667450610221925,000$
15Philippe Myers0X100.008354746793847965306260665168703650610273775,000$
16Justin Holl0X100.0069378966858381623067536948757342506003223,400,000$
17Max Lajoie (C)0X100.007038846476788462306554634868704850590261775,000$
Rayé
1Mitchell Stephens (A)0X100.006638896275788558786059675668706450580273775,000$
2Ty Ronning0X100.006336906165907859595761555968704550570261775,000$
3Tyler Benson0X100.006338876072767859656357586266687350570261863,333$
4Connor Bunnaman0X100.006940865981838455715158566067695650560261775,000$
5Samuel Honzek (R)0X100.007339895884797057605655595762638450560191775,000$
6Ty Mueller (R)0X100.006136886069807259696058635962646550560211775,000$
7Matej Pekar0X100.006542706274766558676150565364666150550241863,334$
8David Goyette (R)0X100.005637885865697056635755545861636850540201775,000$
9Gavin Hayes (R)0X100.006437945773816854585655575361636750540191775,000$
10Jakub Stancl (R)0X100.007539945684696054595350585260626450540191775,000$
11Antti Saarela (R)0X100.006037935669676453585455525763655850530222925,000$
12David Reinbacher0X100.0076427965856864623060596452616388505801922,085,000$
MOYENNE D’ÉQUIPE100.00684185647680776253625963576667615059
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
1Dan Vladar0100.008580759184838584838584698154506102612,200,000$
2Jakub Dobes0100.00788783897776787776787764715550570222925,000$
3Dennis Hildeby0100.00778682987675777675777664715750560221843,333$
Rayé
1Talyn Boyko (R)0100.00697167946867696867696863696050520211775,000$
MOYENNE D’ÉQUIPE100.0077817793767577767577766573575057
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Joshua Ho-SangToronto Marlies (TOR)RW4123-3005193711.11%37719.3011211000000000%021000.7800000000
2Marc-Edouard VlasicToronto Marlies (TOR)D4123-4202481112.50%410025.1311261400008000%013000.6000000000
3Michael AmadioToronto Marlies (TOR)RW4213-42067124616.67%38721.81112412000000028.57%730000.6900000000
4Nils HoglanderToronto Marlies (TOR)LW4033-320269370%29824.71022312000080038.46%1331000.6100000000
5Rafael Harvey-PinardToronto Marlies (TOR)LW4213-3204752740.00%18320.76112110000050057.14%730000.7200000000
6Samuel HeleniusToronto Marlies (TOR)C4033-240765110%38020.05022210000040054.72%5301000.7500000000
7Klim KostinToronto Marlies (TOR)C4022-380846110%29122.77022312000040044.32%8802000.4400000000
8Will BorgenToronto Marlies (TOR)D3101-3208531133.33%37826.1110111300008000%011000.2600000000
9Jack FinleyToronto Marlies (TOR)C4000-320371230%16115.2500010000020043.75%161000000000000
10Denton MateychukToronto Marlies (TOR)D4000-100440300%28120.310000900005000%00200000000000
11Nick BlankenburgToronto Marlies (TOR)D4000000422010%17418.570000800004000%00200000000000
12David ReinbacherToronto Marlies (TOR)D1000000000000%066.800000000000000%00000000000000
13Jackson BlakeToronto Marlies (TOR)RW4000-100403030%05814.550000000000000%00200000000000
14Ryker EvansToronto Marlies (TOR)D4000-100112110%15313.500000000000000%00000000000000
15Landon SlaggertToronto Marlies (TOR)LW1000-200121120%01616.7000000000000050.00%21000000000000
16Justin HollToronto Marlies (TOR)D4000-300211020%15413.730000100003000%01000000000000
17Max LajoieToronto Marlies (TOR)D4000-100000000%1276.950000000000000%20000000000000
18Philippe MyersToronto Marlies (TOR)D4000-300230000%15313.490000000001000%01200000000000
Statistiques d’équipe totales ou en moyenne6571421-40240636067234310.45%29118518.2451015221190000550046.28%1881717000.3500000000
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
1Dan VladarToronto Marlies (TOR)30300.8922.351790076524020030000
2Jakub DobesToronto Marlies (TOR)10100.8005.0959005259010013000
Statistiques d’équipe totales ou en moyenne40400.8673.032380012903303043000


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 Salaire restantPlafond 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
Antti SaarelaToronto Marlies (TOR)C222001-06-27FINYes183 Lbs5 ft11NoNoFree AgentNoNo22025-10-13FalseFalsePro & Farm925,000$0$0$No925,000$--------925,000$--------No--------Lien
Connor BunnamanToronto Marlies (TOR)C261998-04-16CANNo207 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Dan VladarToronto Marlies (TOR)G261997-08-20CZENo209 Lbs6 ft5NoNoFree AgentNoNo12024-09-16FalseFalsePro & Farm2,200,000$0$0$No---------------------------Lien
David GoyetteToronto Marlies (TOR)C202004-03-27CANYes172 Lbs5 ft10NoNoProspectNoNo12025-09-06FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
David ReinbacherToronto Marlies (TOR)D192004-10-25AUTNo209 Lbs6 ft3NoNoFree Agent2025-09-16NoNo22025-10-13FalseFalsePro & Farm2,085,000$0$0$No2,085,000$--------2,085,000$--------No--------Lien
Dennis HildebyToronto Marlies (TOR)G222001-08-19SWENo224 Lbs6 ft7NoNoFree AgentNoNo12024-09-16FalseFalsePro & Farm843,333$0$0$No---------------------------Lien
Denton MateychukToronto Marlies (TOR)D192004-07-12CANYes185 Lbs5 ft11NoNoProspectNoNo12025-09-06FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Gavin HayesToronto Marlies (TOR)LW192004-05-14USAYes177 Lbs6 ft1NoNoProspectNoNo12025-09-06FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Jack FinleyToronto Marlies (TOR)C212002-09-02CANNo220 Lbs6 ft6NoNoFree AgentNoNo12024-09-16FalseFalsePro & Farm863,333$0$0$No---------------------------Lien
Jackson BlakeToronto Marlies (TOR)RW202003-08-03USAYes178 Lbs5 ft11NoNoProspectNoNo12025-09-06FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Jakub DobesToronto Marlies (TOR)G222001-05-27CZENo215 Lbs6 ft4NoNoFree AgentNoNo22025-10-13FalseFalsePro & Farm925,000$0$0$No925,000$--------925,000$--------No--------Lien
Jakub StanclToronto Marlies (TOR)C192005-04-10CZEYes201 Lbs6 ft3NoNoDraftNoNo12025-09-06FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Joshua Ho-SangToronto Marlies (TOR)RW281996-01-22CANNo173 Lbs6 ft0NoNoFree AgentNoNo22024-09-16FalseFalsePro & Farm775,000$0$0$No775,000$--------700,000$--------No--------Lien
Justin HollToronto Marlies (TOR)D321992-01-30USANo194 Lbs6 ft4NoNoFree AgentNoNo22024-09-16FalseFalsePro & Farm3,400,000$0$0$No3,400,000$--------3,400,000$--------No--------Lien
Klim KostinToronto Marlies (TOR)C241999-05-05RUSNo232 Lbs6 ft4NoNoFree AgentNoNo12024-09-16FalseFalsePro & Farm2,000,000$0$0$No---------------------------Lien
Landon SlaggertToronto Marlies (TOR)LW212002-06-25USANo180 Lbs6 ft0NoNoFree AgentNoNo22025-10-13FalseFalsePro & Farm1,350,000$0$0$No1,350,000$--------1,350,000$--------No--------Lien
Marc-Edouard VlasicToronto Marlies (TOR)D371987-03-30CANNo205 Lbs6 ft1NoNoFree AgentNoNo12024-10-10FalseFalsePro & Farm3,250,000$0$0$No---------------------------Lien / Lien NHL
Matej PekarToronto Marlies (TOR)C242000-02-10CZENo185 Lbs6 ft1NoNoFree AgentNoNo12024-09-16FalseFalsePro & Farm863,334$0$0$No---------------------------Lien
Max LajoieToronto Marlies (TOR)D261997-11-05CANNo191 Lbs6 ft1NoNoFree AgentNoNo12024-09-16FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Michael AmadioToronto Marlies (TOR)RW271996-05-13CANNo199 Lbs6 ft1NoNoFree AgentNoNo32025-10-13FalseFalsePro & Farm2,600,000$0$0$No2,600,000$2,600,000$-------2,600,000$2,600,000$-------NoNo-------Lien
Mitchell StephensToronto Marlies (TOR)C271997-02-05CANNo203 Lbs6 ft0NoNoFree AgentNoNo32025-10-13FalseFalsePro & Farm775,000$0$0$No775,000$775,000$-------775,000$775,000$-------NoNo-------Lien
Nick BlankenburgToronto Marlies (TOR)D251998-05-12USANo177 Lbs5 ft9NoNoFree AgentNoNo22024-09-16FalseFalsePro & Farm825,000$0$0$No825,000$--------825,000$--------No--------Lien
Nils HoglanderToronto Marlies (TOR)LW232000-12-20SWENo185 Lbs5 ft9NoNoFree AgentNoNo12024-09-16FalseFalsePro & Farm1,100,000$0$0$No---------------------------Lien
Philippe MyersToronto Marlies (TOR)D271997-01-25CANNo219 Lbs6 ft5NoNoFree Agent2024-09-17NoNo32025-10-13FalseFalsePro & Farm775,000$0$0$No775,000$775,000$-------775,000$775,000$-------NoNo-------Lien
Rafael Harvey-PinardToronto Marlies (TOR)LW251999-01-06CANNo181 Lbs5 ft9NoNoFree AgentNoNo22024-09-16FalseFalsePro & Farm1,100,000$0$0$No1,100,000$--------1,100,000$--------No--------Lien
Ryker EvansToronto Marlies (TOR)D222001-12-13CANNo195 Lbs6 ft0NoNoFree AgentNoNo12024-09-16FalseFalsePro & Farm925,000$0$0$No---------------------------Lien
Samuel HeleniusToronto Marlies (TOR)C212002-11-26FINNo201 Lbs6 ft6NoNoFree AgentNoNo22025-10-13FalseFalsePro & Farm880,000$0$0$No880,000$--------880,000$--------No--------Lien
Samuel HonzekToronto Marlies (TOR)LW192004-11-12SVKYes186 Lbs6 ft4NoNoDraftNoNo12025-09-06FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Talyn BoykoToronto Marlies (TOR)G212002-10-16CANYes206 Lbs6 ft6NoNoProspectNoNo12025-09-06FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Ty MuellerToronto Marlies (TOR)C212003-02-26CANYes185 Lbs5 ft11NoNoDraftNoNo12025-09-06FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Ty RonningToronto Marlies (TOR)RW261997-10-20CANNo167 Lbs5 ft9NoNoN/ANoNo1FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Tyler BensonToronto Marlies (TOR)LW261998-03-15CANNo190 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm863,333$0$0$No---------------------------Lien
Will BorgenToronto Marlies (TOR)D271996-12-19USANo204 Lbs6 ft3NoNoFree AgentNoNo32025-10-13FalseFalsePro & Farm2,700,000$0$0$No2,700,000$2,700,000$-------2,700,000$2,700,000$-------NoNo-------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3323.76195 Lbs6 ft11.521,228,737$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nils HoglanderKlim KostinMichael Amadio40122
2Rafael Harvey-PinardSamuel HeleniusJoshua Ho-Sang30122
3Nils HoglanderJack FinleyJackson Blake20122
4Nils HoglanderKlim KostinMichael Amadio10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Will BorgenMarc-Edouard Vlasic40122
2Denton MateychukNick Blankenburg30122
3Ryker EvansPhilippe Myers20122
4Justin HollMax Lajoie10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nils HoglanderKlim KostinMichael Amadio60122
2Rafael Harvey-PinardSamuel HeleniusJoshua Ho-Sang40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Will BorgenMarc-Edouard Vlasic60122
2Denton MateychukNick Blankenburg40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Klim KostinNils Hoglander60122
2Samuel HeleniusRafael Harvey-Pinard40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Will BorgenMarc-Edouard Vlasic60122
2Denton MateychukNick Blankenburg40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Klim Kostin60122Will BorgenMarc-Edouard Vlasic60122
2Samuel Helenius40122Denton MateychukNick Blankenburg40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Klim KostinNils Hoglander60122
2Samuel HeleniusRafael Harvey-Pinard40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Will BorgenMarc-Edouard Vlasic60122
2Denton MateychukNick Blankenburg40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nils HoglanderKlim KostinMichael AmadioWill BorgenMarc-Edouard Vlasic
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nils HoglanderKlim KostinMichael AmadioWill BorgenMarc-Edouard Vlasic
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Rafael Harvey-Pinard, Klim Kostin, Samuel HeleniusRafael Harvey-Pinard, Klim KostinRafael Harvey-Pinard
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Philippe Myers, Justin Holl, Max LajoiePhilippe MyersPhilippe Myers, Justin Holl
Tirs de pénalité
Michael Amadio, Nils Hoglander, Joshua Ho-Sang, Jackson Blake, Rafael Harvey-Pinard
Gardien
#1 : Dan Vladar, #2 : Jakub Dobes
Lignes d’attaque personnalisées en prolongation
Michael Amadio, Nils Hoglander, Joshua Ho-Sang, Jackson Blake, Rafael Harvey-Pinard, Klim Kostin, Samuel Helenius, Jack Finley, Will Borgen, Philippe Myers
Lignes de défense personnalisées en prolongation
Will Borgen, Marc-Edouard Vlasic, Denton Mateychuk, Nick Blankenburg, Ryker Evans


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
1Chicago Wolves40400000715-82020000026-42020000059-400.000714213023206718183109329246316531.25%12558.33%0306844.12%357447.30%224647.83%733071419448
Total40400000715-82020000026-42020000059-400.000714213023206718183109329246316531.25%12558.33%0306844.12%357447.30%224647.83%733071419448
_Since Last GM Reset40400000715-82020000026-42020000059-400.000714213023206718183109329246316531.25%12558.33%0306844.12%357447.30%224647.83%733071419448
_Vs Conference40400000715-82020000026-42020000059-400.000714213023206718183109329246316531.25%12558.33%0306844.12%357447.30%224647.83%733071419448

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
40L471421679329246330
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
4040000715
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
202000026
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
202000059
Derniers 10 matchs
WLOTWOTL SOWSOL
040000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
16531.25%12558.33%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
18183102320
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
306844.12%357447.30%224647.83%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
733071419448


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
12Toronto Marlies4Chicago Wolves6LSommaire du match
310Toronto Marlies1Chicago Wolves3LSommaire du match
518Chicago Wolves2Toronto Marlies0LSommaire du match
726Chicago Wolves4Toronto Marlies2LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4525
Assistance3,0121,610
Assistance PCT75.30%80.50%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
39 2311 - 77.03% 89,653$179,306$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
0$ 4,054,833$ 4,054,833$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

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




Toronto 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

Toronto 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

Toronto 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

Toronto 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

Toronto 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