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Chicago Wolves
GP: 22 | W: 8 | L: 13 | OTL: 1 | P: 17
GF: 121 | GA: 122 | PP%: 36.67% | PK%: 66.20%
DG: Camil Costandi | Morale : 44 | Moyenne d’équipe : 56
Prochains matchs #350 vs Buffalo Bisons

Centre de jeu
Chicago Wolves
8-13-1, 17pts
4
5 Brampton Battalion
11-10-0, 22pts
Team Stats
L3SéquenceL1
4-6-0Fiche domicile9-2-0
4-7-1Fiche domicile2-8-0
3-7-0Derniers 10 matchs5-5-0
5.50Buts par match 5.90
5.55Buts contre par match 4.90
36.67%Pourcentage en avantage numérique37.31%
66.20%Pourcentage en désavantage numérique59.21%
Chicago Wolves
8-13-1, 17pts
3
9 Lowell Devils
7-12-3, 17pts
Team Stats
L3SéquenceW1
4-6-0Fiche domicile3-6-2
4-7-1Fiche domicile4-6-1
3-7-0Derniers 10 matchs3-5-2
5.50Buts par match 4.09
5.55Buts contre par match 4.73
36.67%Pourcentage en avantage numérique31.94%
66.20%Pourcentage en désavantage numérique52.08%
Buffalo Bisons
11-8-2, 24pts
2025-11-15
Chicago Wolves
8-13-1, 17pts
Statistiques d’équipe
L1SéquenceL3
7-4-0Fiche domicile4-6-0
4-4-2Fiche visiteur4-7-1
4-6-010 derniers matchs3-7-0
4.81Buts par match 5.50
4.14Buts contre par match 5.50
31.94%Pourcentage en avantage numérique36.67%
57.69%Pourcentage en désavantage numérique66.20%
Quebec Rempart
7-11-3, 17pts
2025-11-18
Chicago Wolves
8-13-1, 17pts
Statistiques d’équipe
W1SéquenceL3
4-5-2Fiche domicile4-6-0
3-6-1Fiche visiteur4-7-1
2-6-210 derniers matchs3-7-0
4.24Buts par match 5.50
4.43Buts contre par match 5.50
48.21%Pourcentage en avantage numérique36.67%
53.45%Pourcentage en désavantage numérique66.20%
Chicago Wolves
8-13-1, 17pts
2025-11-19
Toronto Marlies
10-11-1, 21pts
Statistiques d’équipe
L3SéquenceL1
4-6-0Fiche domicile5-5-0
4-7-1Fiche visiteur5-6-1
3-7-010 derniers matchs4-5-1
5.50Buts par match 5.68
5.55Buts contre par match 5.68
36.67%Pourcentage en avantage numérique40.30%
66.20%Pourcentage en désavantage numérique66.23%
Meneurs d'équipe
Buts
Valtteri Puustinen
31
Mitchell StephensPasses
Mitchell Stephens
33
Points
Valtteri Puustinen
50
Plus/Moins
Ryan Gagnier
15
Victoires
Drew Commesso
0
Pourcentage d’arrêts
Drew Commesso
0.814

Statistiques d’équipe
Buts pour
121
5.50 GFG
Tirs pour
602
27.36 Avg
Pourcentage en avantage numérique
36.7%
22 GF
Début de zone offensive
28.8%
Buts contre
122
5.55 GAA
Tirs contre
695
31.59 Avg
Pourcentage en désavantage numérique
66.2%%
24 GA
Début de la zone défensive
35.1%
Informations de l'équipe

Directeur généralCamil Costandi
EntraîneurStephane Robidas
DivisionMarcel Dionne
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,913
Billets de saison300


Informations de la formation

Équipe Pro21
Équipe Mineure19
Limite contact 40 / 63
Espoirs32


Historique d'équipe

Saison actuelle8-13-1 (17PTS)
Historique187-195-29 (0.455%)
Apparitions en séries éliminatoires 1
Historique en séries éliminatoires (W-L)5 - 4 (0.556%)
Coupe Stanley0


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
1Valtteri Puustinen0XX97.007142908565557767255868642552526847620261775,000$
2Mitchell Stephens0X98.007343927973537959825756712558596443610281775,000$
3Ivan Miroshnichenko (R)0X100.008144997769548668256357662547486549610211950,000$
4Lukas Rousek0XX100.007572826872818757506247634544446052590261800,000$
5Pavol Regenda0XX99.007880746780565660505957655444446132570251775,000$
6Jackson Cates0XX100.007570886470737952654554625144445950560271775,000$
7Will Lockwood0X100.007467896567515056705058625544445948550271775,000$
8Ben Steeves (R)0X100.006461726661535258505656585344445844540232950,000$
9Wilmer Skoog0X100.007473756573555651645048614644445551530251775,000$
10Ryan Gagnier0X100.007568906168404045563846604444445152490221775,000$
11Sawyer Boulton (R)0XXX100.006174326074383744553844534244444649460201800,000$
12Jordan Harris0X100.006942937267575561255048732560605950610241825,000$
13Elias Pettersson2 (R)0X100.007966828171608359254648652546465949610213838,333$
14Seamus Casey (R)0X100.006941996959606264256368632545456946590213950,000$
15Cavan Fitzgerald0X100.007874866574525349254043624144445359550281775,000$
16David Reinbacher (R)0X100.007677756277423954254053635044445637540202918,333$
17Djibril Toure0X100.007380556280606445253441593944445047540223805,000$
18Chad Nychuk0X100.007471816171414146253739603744445047510241775,000$
19Joe Fleming (R)0X100.006780376180444444253439563744444749500221775,000$
Rayé
MOYENNE D’ÉQUIPE99.68736478687154605542485162394646574756
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
1Drew Commesso (R)0100.00585366706063566363623044445956580221925,000$
2Nico Daws0100.00505468844851505550503049495153540241812,500$
Rayé
MOYENNE D’ÉQUIPE100.0054546777545753595756304747555556
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Stephane Robidas7270676758541CAN48266,000$


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
1Valtteri PuustinenChicago Wolves (QUE)LW/RW213119501602638106296029.25%2249123.41641011411011534134.78%463210042.0301000541
2Mitchell StephensChicago Wolves (QUE)C2217335041810225875274022.67%1247421.55312155450111500158.11%6232411022.1101020212
3Seamus CaseyChicago Wolves (QUE)D2252227155162844151311.36%1448221.91426435000146000%01420001.1200010201
4Lukas RousekChicago Wolves (QUE)LW/RW227192634325282530162523.33%1242419.28358444000051046.67%3057011.2300113012
5Ivan MiroshnichenkoChicago Wolves (QUE)LW22101626-800293352163919.23%636716.721341320001270037.50%16265001.4101000010
6Jackson CatesChicago Wolves (QUE)C/LW2211819-729152832306836.67%1339417.932022330001311051.01%24733000.9600111001
7Ben SteevesChicago Wolves (QUE)LW2210919-11715232250122820.00%428613.0100003000030058.33%1244001.3300021000
8Pavol RegendaChicago Wolves (QUE)LW/RW177613-124620382751113013.73%832118.900112260002130050.00%1668000.8100022001
9Will LockwoodChicago Wolves (QUE)RW227613-11715232434102020.59%428112.8000004000001166.67%985010.9200012001
10Jordan HarrisChicago Wolves (QUE)D222101275520393712105.41%3758126.41134148000457010%0926000.4100001000
11Ryan GagnierChicago Wolves (QUE)C216612157518221781135.29%1226412.6000000000000144.87%78713000.9100100200
12Cavan FitzgeraldChicago Wolves (QUE)D2217864620243014127.14%2342319.25011031000036000%0521000.3800301000
13Elias Pettersson2Chicago Wolves (QUE)D12358-335152420257812.00%1028824.03202434000125000%0010000.5500003000
14Wilmer SkoogChicago Wolves (QUE)C22246-6161031231421414.29%625311.5000002000090054.47%12348000.4700002000
15Sawyer BoultonChicago Wolves (QUE)C/LW/RW21235848202311103720.00%422710.8500000000001057.14%755000.4400013000
16David ReinbacherChicago Wolves (QUE)D15044-119151025020%1317011.360000200000000%034000.4700111000
17Djibril ToureChicago Wolves (QUE)D22044-4221022164210%1732014.5500006000017000%0112000.2500011000
18Chad NychukChicago Wolves (QUE)D190222406121120%1021411.29000010000140060.00%509000.1900000000
19Joe FlemingChicago Wolves (QUE)D22011444201683110%52029.220000100004000%215000.1000013000
Statistiques d’équipe totales ou en moyenne390121184305842722542747060217932120.10%232646916.5922315334397112123988553.87%1214157186080.9403714241179
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
1Sebastian CossaNordiques198810.8464.9010530086559306100.5002190100
2Drew CommessoChicago Wolves (QUE)50400.8145.731990019102521000221000
Statistiques d’équipe totales ou en moyenne2481210.8415.031253001056613582022121100


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
Ben SteevesChicago Wolves (QUE)LW232002-05-10USAYes170 Lbs5 ft9NoNoAssign ManuallyNoNo22025-06-15FalseFalsePro & Farm950,000$0$0$No950,000$--------950,000$--------No--------Lien
Cavan FitzgeraldChicago Wolves (QUE)D281996-08-23USANo200 Lbs6 ft1NoNoN/ANoNo12025-09-05FalseFalsePro & Farm775,000$0$0$No---------------------------Lien / Lien NHL
Chad NychukChicago Wolves (QUE)D242001-03-06MANNo194 Lbs6 ft1NoNoAssign ManuallyNoNo12025-10-08FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
David ReinbacherChicago Wolves (QUE)D202004-10-25AUTYes209 Lbs6 ft3NoNoProspectNoNo22024-06-21FalseFalsePro & Farm918,333$0$0$No918,333$--------918,333$--------No--------Lien
Djibril ToureChicago Wolves (QUE)D222003-06-05CANNo203 Lbs6 ft7NoNoAssign ManuallyNoNo32025-06-15FalseFalsePro & Farm805,000$0$0$No805,000$805,000$-------805,000$805,000$-------NoNo-------Lien
Drew CommessoChicago Wolves (QUE)G222002-07-19USAYes180 Lbs6 ft2NoNoProspectNoNo12024-06-21FalseFalsePro & Farm925,000$0$0$No---------------------------Lien
Elias Pettersson2Chicago Wolves (QUE)D212004-02-16SWEYes185 Lbs6 ft2NoNoTrade2025-06-25NoNo32025-06-15FalseFalsePro & Farm838,333$0$0$No838,333$838,333$-------838,333$838,333$-------NoNo-------Lien
Ivan MiroshnichenkoChicago Wolves (QUE)LW212004-02-04RUSYes185 Lbs6 ft1NoNoProspectNoNo12024-06-21FalseFalsePro & Farm950,000$0$0$No---------------------------Lien
Jackson CatesChicago Wolves (QUE)C/LW271997-09-26USANo190 Lbs6 ft0NoNoN/ANoNo12025-09-05FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Joe FlemingChicago Wolves (QUE)D222003-06-19USAYes223 Lbs6 ft1NoNoAssign ManuallyNoNo12025-06-15FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Jordan HarrisChicago Wolves (QUE)D242000-07-07USANo187 Lbs5 ft11NoNoN/ANoNo12025-07-03FalseFalsePro & Farm825,000$0$0$No---------------------------Lien
Lukas RousekChicago Wolves (QUE)LW/RW261999-04-20CZENo202 Lbs5 ft11NoNoN/ANoNo12025-09-05FalseFalsePro & Farm800,000$0$0$No---------------------------Lien
Mitchell StephensChicago Wolves (QUE)C281997-02-05CANNo203 Lbs6 ft0NoNoN/ANoNo12024-07-02FalseFalsePro & Farm775,000$0$0$No---------------------------Lien / Lien NHL
Nico DawsChicago Wolves (QUE)G242000-12-22GERNo205 Lbs6 ft4NoNoN/ANoNo12024-07-30FalseFalsePro & Farm812,500$0$0$No---------------------------Lien
Pavol RegendaChicago Wolves (QUE)LW/RW251999-07-12SVKNo219 Lbs6 ft3NoNoN/ANoNo12025-07-03FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Ryan GagnierChicago Wolves (QUE)C222002-07-16ONNo185 Lbs6 ft0NoNoAssign ManuallyNoNo12025-06-15FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Sawyer BoultonChicago Wolves (QUE)C/LW/RW202004-07-12USAYes209 Lbs6 ft0NoNoFree AgentNoNo12025-10-08FalseFalsePro & Farm800,000$0$0$No---------------------------Lien
Seamus CaseyChicago Wolves (QUE)D212004-01-08USAYes162 Lbs5 ft10NoNoProspectNoNo32025-06-15FalseFalsePro & Farm950,000$0$0$No950,000$950,000$-------950,000$950,000$-------NoNo-------Lien
Valtteri PuustinenChicago Wolves (QUE)LW/RW261999-06-04FINNo182 Lbs5 ft10NoNoN/ANoNo12024-06-21FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Will LockwoodChicago Wolves (QUE)RW271998-06-10USANo185 Lbs5 ft11NoNoAssign ManuallyNoNo12025-06-17FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Wilmer SkoogChicago Wolves (QUE)C251999-07-17SWENo197 Lbs6 ft2NoNoAssign ManuallyNoNo12025-07-21FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2123.71194 Lbs6 ft11.38824,960$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Valtteri PuustinenMitchell StephensLukas Rousek40122
2Ivan MiroshnichenkoJackson CatesPavol Regenda30122
3Pavol RegendaWilmer SkoogWill Lockwood20122
4Ben SteevesRyan GagnierSawyer Boulton10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan HarrisElias Pettersson240122
2Seamus CaseyCavan Fitzgerald30122
3David ReinbacherDjibril Toure20122
4Chad NychukJoe Fleming10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Valtteri PuustinenMitchell StephensLukas Rousek60122
2Ivan MiroshnichenkoJackson CatesPavol Regenda40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan HarrisElias Pettersson260122
2Seamus CaseyCavan Fitzgerald40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Mitchell StephensValtteri Puustinen60122
2Jackson CatesIvan Miroshnichenko40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan HarrisElias Pettersson260122
2Seamus CaseyCavan Fitzgerald40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Mitchell Stephens60122Jordan HarrisElias Pettersson260122
2Jackson Cates40122Seamus CaseyCavan Fitzgerald40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Mitchell StephensValtteri Puustinen60122
2Jackson CatesIvan Miroshnichenko40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan HarrisElias Pettersson260122
2Seamus CaseyCavan Fitzgerald40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Valtteri PuustinenMitchell StephensLukas RousekJordan HarrisElias Pettersson2
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Valtteri PuustinenMitchell StephensLukas RousekJordan HarrisElias Pettersson2
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Pavol Regenda, Jackson Cates, Will LockwoodPavol Regenda, Jackson CatesPavol Regenda
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Djibril Toure, Chad Nychuk, Joe FlemingDjibril ToureDjibril Toure, Chad Nychuk
Tirs de pénalité
Valtteri Puustinen, Ivan Miroshnichenko, Mitchell Stephens, Lukas Rousek, Pavol Regenda
Gardien
#1 : , #2 : Drew Commesso


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
1Binghampton Senators1010000026-4000000000001010000026-400.00022400375133026171236195337131820300.00%4250.00%019735156.13%20442747.78%25343957.63%437214438210448236
2Brampton Battalion1010000045-1000000000001010000045-100.000461000375133030171236195334836184125.00%3166.67%019735156.13%20442747.78%25343957.63%437214438210448236
3Chicoutimi Sagueneens1010000049-5000000000001010000049-500.000471100375133027171236195340146185120.00%30100.00%019735156.13%20442747.78%25343957.63%437214438210448236
4Grand Rapids Griffins2110000012660000000000021100000126620.500121931003751330551712361953469323366100.00%6183.33%019735156.13%20442747.78%25343957.63%437214438210448236
5Hamilton Bulldogs110000001541111000000154110000000000021.000152439003751330251712361953349162722100.00%3166.67%019735156.13%20442747.78%25343957.63%437214438210448236
6Hartford Wolf Pack21100000972211000009720000000000020.50091221003751330621712361953612433437228.57%9366.67%019735156.13%20442747.78%25343957.63%437214438210448236
7Hershey Bears22000000281018110000001468110000001441041.000283866003751330751712361953501042475480.00%6183.33%119735156.13%20442747.78%25343957.63%437214438210448236
8Laval Rockets312000001519-4312000001519-40000000000020.3331523380037513308517123619531154360486116.67%10370.00%019735156.13%20442747.78%25343957.63%437214438210448236
9London Knights11000000431000000000001100000043121.00046100037513302217123619531459193133.33%2150.00%019735156.13%20442747.78%25343957.63%437214438210448236
10Lowell Devils1010000039-6000000000001010000039-600.000347003751330271712361953271019215120.00%7442.86%019735156.13%20442747.78%25343957.63%437214438210448236
11Philadelphia Phantoms1010000046-21010000046-20000000000000.00046100037513302817123619534414918000%2150.00%019735156.13%20442747.78%25343957.63%437214438210448236
12Rochester Americans1010000036-31010000036-30000000000000.00035800375133024171236195334101822200.00%4250.00%019735156.13%20442747.78%25343957.63%437214438210448236
13Victoriaville Tigres311000011716100000000000311000011716130.5001731480037513309217123619531052857549333.33%6266.67%019735156.13%20442747.78%25343957.63%437214438210448236
14Worcester Sharks20200000116-1510100000112-111010000004-400.00012300375133024171236195354357239300.00%6266.67%019735156.13%20442747.78%25343957.63%437214438210448236
Total2281300001121122-1104600000616011247000016062-2170.3861211853060037513306021712361953695232427427602236.67%712466.20%119735156.13%20442747.78%25343957.63%437214438210448236
_Since Last GM Reset2281300001121122-1104600000616011247000016062-2170.3861211853060037513306021712361953695232427427602236.67%712466.20%119735156.13%20442747.78%25343957.63%437214438210448236
_Vs Conference14680000088771194500000585445230000030237120.429881312190037513303811712361953444158270273341647.06%451273.33%119735156.13%20442747.78%25343957.63%437214438210448236

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2217L312118530660269523242742700
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
228130001121122
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
104600006160
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
124700016062
Derniers 10 matchs
WLOTWOTL SOWSOL
370000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
602236.67%712466.20%1
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
17123619533751330
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
19735156.13%20442747.78%25343957.63%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
437214438210448236


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
1 - 2025-10-085Worcester Sharks12Chicago Wolves1LSommaire du match
2 - 2025-10-0916Chicago Wolves2Victoriaville Tigres3LXXSommaire du match
4 - 2025-10-1135Chicago Wolves6Victoriaville Tigres7LSommaire du match
6 - 2025-10-1353Laval Rockets7Chicago Wolves5LSommaire du match
7 - 2025-10-1461Chicago Wolves11Grand Rapids Griffins3WSommaire du match
9 - 2025-10-1682Rochester Americans6Chicago Wolves3LSommaire du match
11 - 2025-10-1896Chicago Wolves0Worcester Sharks4LSommaire du match
13 - 2025-10-20113Chicago Wolves4Chicoutimi Sagueneens9LSommaire du match
14 - 2025-10-21125Hershey Bears6Chicago Wolves14WSommaire du match
16 - 2025-10-23144Chicago Wolves14Hershey Bears4WSommaire du match
17 - 2025-10-24155Laval Rockets3Chicago Wolves4WSommaire du match
19 - 2025-10-26179Hamilton Bulldogs4Chicago Wolves15WSommaire du match
22 - 2025-10-29200Philadelphia Phantoms6Chicago Wolves4LSommaire du match
23 - 2025-10-30216Chicago Wolves9Victoriaville Tigres6WSommaire du match
24 - 2025-10-31219Chicago Wolves1Grand Rapids Griffins3LSommaire du match
27 - 2025-11-03244Hartford Wolf Pack4Chicago Wolves3LSommaire du match
29 - 2025-11-05263Laval Rockets9Chicago Wolves6LSommaire du match
30 - 2025-11-06271Chicago Wolves4London Knights3WSommaire du match
32 - 2025-11-08295Hartford Wolf Pack3Chicago Wolves6WSommaire du match
34 - 2025-11-10307Chicago Wolves2Binghampton Senators6LSommaire du match
37 - 2025-11-13325Chicago Wolves4Brampton Battalion5LSommaire du match
38 - 2025-11-14335Chicago Wolves3Lowell Devils9LSommaire du match
39 - 2025-11-15350Buffalo Bisons-Chicago Wolves-
42 - 2025-11-18371Quebec Rempart-Chicago Wolves-
43 - 2025-11-19388Chicago Wolves-Toronto Marlies-
44 - 2025-11-20403Manchester Monarchs-Chicago Wolves-
46 - 2025-11-22422Chicago Wolves-Boisbriand Armada-
47 - 2025-11-23434Chicago Wolves-Victoriaville Tigres-
49 - 2025-11-25449Calgary Hitman-Chicago Wolves-
51 - 2025-11-27467Drummondville Voltigeurs-Chicago Wolves-
52 - 2025-11-28487Seattle Thunderbirds-Chicago Wolves-
54 - 2025-11-30502Chicago Wolves-Quebec Rempart-
56 - 2025-12-02516Chicago Wolves-Buffalo Bisons-
58 - 2025-12-04533Sherbrooke Phoenix-Chicago Wolves-
59 - 2025-12-05552Chicago Wolves-Hamilton Bulldogs-
60 - 2025-12-06558Chicago Wolves-Hershey Bears-
62 - 2025-12-08576London Knights-Chicago Wolves-
64 - 2025-12-10596Manitoba Moose-Chicago Wolves-
66 - 2025-12-12615Chicago Wolves-Drummondville Voltigeurs-
68 - 2025-12-14630Chicago Wolves-Grand Rapids Griffins-
69 - 2025-12-15639Worcester Sharks-Chicago Wolves-
71 - 2025-12-17659Philadelphia Phantoms-Chicago Wolves-
72 - 2025-12-18674Chicago Wolves-Rochester Americans-
74 - 2025-12-20691Drummondville Voltigeurs-Chicago Wolves-
76 - 2025-12-22711Chicago Wolves-Chicoutimi Sagueneens-
77 - 2025-12-23722Chicago Wolves-Calgary Hitman-
79 - 2025-12-25734Rochester Americans-Chicago Wolves-
81 - 2025-12-27759TroisRivieres Lions-Chicago Wolves-
83 - 2025-12-29772Chicago Wolves-Sherbrooke Phoenix-
85 - 2025-12-31789Boisbriand Armada-Chicago Wolves-
87 - 2026-01-02805Chicago Wolves-Manchester Monarchs-
88 - 2026-01-03820Chicago Wolves-Manitoba Moose-
89 - 2026-01-04831Lake Erie Monsters-Chicago Wolves-
90 - 2026-01-05847Chicago Wolves-Rimouski Oceanic-
92 - 2026-01-07862Milwaukee Admirals-Chicago Wolves-
94 - 2026-01-09878Chicago Wolves-Hartford Wolf Pack-
95 - 2026-01-10894Brampton Battalion-Chicago Wolves-
97 - 2026-01-12919Chicago Wolves-Seattle Thunderbirds-
98 - 2026-01-13925Peoria Riverman-Chicago Wolves-
100 - 2026-01-15949Toronto Marlies-Chicago Wolves-
103 - 2026-01-18969Chicago Wolves-Philadelphia Phantoms-
104 - 2026-01-19984Rimouski Oceanic-Chicago Wolves-
105 - 2026-01-20993Chicago Wolves-Texas Stars-
107 - 2026-01-221014Hamilton Bulldogs-Chicago Wolves-
108 - 2026-01-231027Chicago Wolves-Peoria Riverman-
110 - 2026-01-251045Victoriaville Tigres-Chicago Wolves-
112 - 2026-01-271063Chicago Wolves-TroisRivieres Lions-
113 - 2026-01-281079Chicago Wolves-Philadelphia Phantoms-
114 - 2026-01-291085Hershey Bears-Chicago Wolves-
117 - 2026-02-011109Chicoutimi Sagueneens-Chicago Wolves-
119 - 2026-02-031128Binghampton Senators-Chicago Wolves-
122 - 2026-02-061153Lowell Devils-Chicago Wolves-
123 - 2026-02-071164Chicago Wolves-Bridgeport Sound Tigers-
125 - 2026-02-091184Chicago Wolves-Laval Rockets-
127 - 2026-02-111200Bridgeport Sound Tigers-Chicago Wolves-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
129 - 2026-02-131220Grand Rapids Griffins-Chicago Wolves-
130 - 2026-02-141230Chicago Wolves-Milwaukee Admirals-
132 - 2026-02-161248Chicago Wolves-Lake Erie Monsters-
134 - 2026-02-181259Bridgeport Sound Tigers-Chicago Wolves-
136 - 2026-02-201276Chicago Wolves-Worcester Sharks-
140 - 2026-02-241299Texas Stars-Chicago Wolves-
141 - 2026-02-251312Chicago Wolves-Worcester Sharks-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets2510
Assistance19,3359,790
Assistance PCT96.68%97.90%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
31 2913 - 97.08% 86,610$866,100$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
492,398$ 1,732,416$ 1,732,416$ 66,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 492,398$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
2,684,910$ 104 12,665$ 1,317,160$




Chicago Wolves 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
1Mitchell Stephens51022038160133300571924147814.88%373878317.2226781047767131322855.89%171.37214
2Adam Johnson338245346591-84470496704168514.54%311809623.95531381911594042223056.42%151.46524
3Morgan Klimchuk32820024044032292512440116817.12%208611618.6560681281440008241241.43%81.4400
4C.J. Smith276155241396-11026839466295316.26%253599721.733457918700097943.04%41.32416
5Patrick Brown304144240384-9228850856088816.22%228609620.05406010096808812849.52%81.26812

Chicago Wolves 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
1Pat Nagle2129680240.8924.2012339008648004440420160.25016
2Kyle Keyser1494473220.8725.047958160669523832101100.54951
3Daniel Vladar56351350.8844.4731856023720441196510.71421
4Devin Cooley3223420.8714.7617660014010886242000
5Sebastian Cossa45171720.8494.912345001921272685100.60010

Chicago Wolves Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
Saison régulière
202082303902614388393-541171900203211203841132002411177190-1376388614100250901581376270375510189113532561118107914442149242.99%2057563.41%5776155649.87%889182948.61%739154047.99%155779017977761605821
202082303902614388393-541171900203211203841132002411177190-1376388614100250901581376270375510189113532561118107914442149242.99%2057563.41%5776155649.87%889182948.61%739154047.99%155779017977761605821
202178155003415335467-1323952601313155239-8439102402102180228-484733554487920691311316287077510131057412930991156315511888243.62%2449162.70%3798165748.16%700149346.89%748153848.63%154482216687491510734
20238253170243359638121541277011322891771124126100130130720410312359697315691018623616993190999109710862931331078123218352026632.67%1122974.11%9789158449.81%853166051.39%928175352.94%1770100116607231524796
202476313701142412348643816160013221715562381521010101951932754126631075508718613492135518822787282674834109612801946634.02%1525365.13%3674125353.79%826156252.88%726142251.05%146672815967091529820
20252281300001121122-1104600000616011247000016062-2171211853060037513306021712361953695232427427602236.67%712466.20%119735156.13%20442747.78%25343957.63%437214438210448236
Total Saison régulière42216719501021101922402104136210869302971311441037107212811020812361096106729414224035935833180559920741361420339735204494717115944537164767981107242039.18%98934764.91%264010795750.40%4361880049.56%4133823250.21%833343468959394582254231
Séries éliminatoires
20239540000045301553200000251694220000020146104579124001316160364118138108035810915618422522.73%18761.11%08718347.54%10521050.00%8916952.66%1871051858316885
Total Séries éliminatoires9540000045301553200000251694220000020146104579124001316160364118138108035810915618422522.73%18761.11%08718347.54%10521050.00%8916952.66%1871051858316885

Chicago Wolves 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
1Hudson Fasching9711180210184316.28%819221.34033300000048.21%01.8700
2Tyson Foerster9691531115113517.14%116218.06112300002054.50%01.8500
3Mitchell Stephens9481211920202218.18%215216.99022300001058.40%01.5700
4Jordan Harris92911801116229.09%1821724.1321320000000%01.0100
5Saku Maenalanen965113518131735.29%315517.33112200000023.53%01.4100

Chicago Wolves 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
1Daniel Vladar64200.9203.1835820192371361000
2Devin Cooley31110.9093.671800011121681000