Connexion

Chicago Wolves
GP: 28 | W: 20 | L: 6 | OTL: 2 | P: 42
GF: 115 | GA: 75 | PP%: 32.81% | PK%: 78.00%
DG: Yannick Masse | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #438 vs Belleville Senators
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Centre de jeu
LeHigh Valley Phantoms
9-20-0, 18pts
3
FINAL
6 Chicago Wolves
20-6-2, 42pts
Team Stats
W1SéquenceL1
7-6-0Fiche domicile11-1-1
2-14-0Fiche domicile9-5-1
3-7-0Derniers 10 matchs7-1-2
2.21Buts par match 4.11
3.86Buts contre par match 2.68
6.12%Pourcentage en avantage numérique32.81%
70.83%Pourcentage en désavantage numérique78.00%
Chicago Wolves
20-6-2, 42pts
1
FINAL
5 Henderson Silver Knights
22-1-2, 46pts
Team Stats
L1SéquenceW4
11-1-1Fiche domicile12-1-1
9-5-1Fiche domicile10-0-1
7-1-2Derniers 10 matchs8-0-2
4.11Buts par match 3.40
2.68Buts contre par match 0.40
32.81%Pourcentage en avantage numérique14.29%
78.00%Pourcentage en désavantage numérique96.20%
Chicago Wolves
20-6-2, 42pts
Jour 65
Belleville Senators
9-17-0, 18pts
Statistiques d’équipe
L1SéquenceL1
11-1-1Fiche domicile4-9-0
9-5-1Fiche visiteur5-8-0
7-1-210 derniers matchs5-5-0
4.11Buts par match 2.23
2.68Buts contre par match 2.23
32.81%Pourcentage en avantage numérique14.00%
78.00%Pourcentage en désavantage numérique79.49%
Providence Bruins
16-10-1, 33pts
Jour 66
Chicago Wolves
20-6-2, 42pts
Statistiques d’équipe
L1SéquenceL1
5-7-1Fiche domicile11-1-1
11-3-0Fiche visiteur9-5-1
6-3-110 derniers matchs7-1-2
3.37Buts par match 4.11
3.07Buts contre par match 4.11
6.78%Pourcentage en avantage numérique32.81%
82.00%Pourcentage en désavantage numérique78.00%
Chicago Wolves
20-6-2, 42pts
Jour 68
Hartford Wolf Pack
3-23-0, 6pts
Statistiques d’équipe
L1SéquenceL1
11-1-1Fiche domicile3-10-0
9-5-1Fiche visiteur0-13-0
7-1-210 derniers matchs2-8-0
4.11Buts par match 1.85
2.68Buts contre par match 1.85
32.81%Pourcentage en avantage numérique5.71%
78.00%Pourcentage en désavantage numérique79.41%
Meneurs d'équipe
Buts
Michael Mersch
21
Passes
Robin Salo
27
Points
Michael Mersch
43
Plus/Moins
Charles Hudon
32

Statistiques d’équipe
Buts pour
115
4.11 GFG
Tirs pour
977
34.89 Avg
Pourcentage en avantage numérique
32.8%
21 GF
Début de zone offensive
47.0%
Buts contre
75
2.68 GAA
Tirs contre
525
18.75 Avg
Pourcentage en désavantage numérique
78.0%%
11 GA
Début de la zone défensive
24.4%
Informations de l'équipe

Directeur généralYannick Masse
DivisionSOUTHEAST
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,924
Billets de saison300


Informations de la formation

Équipe Pro27
Équipe Mineure21
Limite contact 48 / 250
Espoirs33


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
1Gabriel DumontXX100.006054726369837961676062646174793050003321,999,999$
2Charles HudonX100.005939756769948365726664636870724750003021,750,000$
3Michael MerschX100.007439866283818361646260635972773750003121,999,999$
4Lias AnderssonXX100.00753881647389826268616360646768835000251750,000$
5Alex TurcotteX100.00603785666977766571636062666465875000232832,500$
6Jakob Pelletier (R)X100.00633687666385766560636261666465805000231832,500$
7Danil Gushchin (R)X100.00613788676292846563666461676365665000222867,500$
8Emil Heineman (R)X100.00683884637586716258576159626365745000222925,000$
9Steven KampferX100.00633978617277795830635456477681305000361800,000$
10Josh MahuraX100.00723581667383816530725663516667604600263750,000$
11Robin SaloX100.00683886677876826430666561546668705000252842,500$
12Cameron CrottyX100.00793985598075825830575662516567625000252775,000$
13Nikita OkhotiukX100.00756071657683766130645963506465665000234775,000$
14Tyler Tucker (R)X100.00726761637880785830625961536466485000243800,000$
15Victor SoderstromX100.00623781656985866330665861506365845000232832,500$
16Zac Jones (R)X100.00593786656783796430666062526465675000231925,000$
17Simon LundmarkX100.00723991578165845530565358466466695000232867,500$
Rayé
1Daniel O'ReganX100.004035404035809040204040403025251150003011,999,999$
2Jonathan Davidsson (R)X100.00403540403580904020404040302525115000271787,500$
3Arttu RuotsalainenX100.00403540403580904020404040302525115000262925,000$
4Emilio PettersenX100.00573882616682845866635956606466485000244775,000$
5Keean WashkurakX100.00564071576771805659545552536465495000231835,000$
6Simon RyforsX100.00403540643580904020404040306668115000272842,500$
7Tommy CrossX100.004035405635809040204040403074791150003621,999,999$
8Gianni FairbrotherX100.00403540403580904020404040302525115000241842,500$
9Emil Andrae (R)X100.00653872636779736230615758496264715000222892,500$
MOYENNE D’ÉQUIPE100.0060407160638182564157555650606250500
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
1Dylan Garand (R)100.0066957970675960596050746269625000222775,000$
Rayé
MOYENNE D’ÉQUIPE100.006695797067596059605074626962500
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
1Michael MerschChicago Wolves (CAR)LW282122431622088591726014012.21%1159621.290555281013341179.00%10000021.4425000474
2Robin SaloChicago Wolves (CAR)D28152742132551373378294419.23%3456520.2183113249000135300%000001.4800001912
3Charles HudonChicago Wolves (CAR)LW2820163632552321109228018.35%430510.9000000000005366.67%1500022.3611100312
4Alex TurcotteChicago Wolves (CAR)C281323363260143088266514.77%630510.9100000000003082.50%24000002.3601000054
5Gabriel DumontChicago Wolves (CAR)C/RW2814213581202843128419310.94%639614.15246928000101380.00%39000001.7733000134
6Nikita OkhotiukChicago Wolves (CAR)D287243114195892440102517.50%3237913.5412381300000100%000001.6400100333
7Victor SoderstromChicago Wolves (CAR)D281110212100661351193521.57%2248617.367183236000023300%000000.8600000103
8Zac JonesChicago Wolves (CAR)D2821214216103116459224.44%948517.331672735000024000%000000.5800200010
9Simon RyforsChicago Wolves (CAR)C4011000002040%0235.8100000000030070.00%2000000.8600000000
10Emilio PettersenChicago Wolves (CAR)LW4000000001000%010.30000000000000100.00%10000000000000
Statistiques d’équipe totales ou en moyenne2321031562591191152547623971421650814.43%124354415.28192140113193101512117780.16%76600041.46610401212122
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


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
Alex TurcotteChicago Wolves (CAR)C232001-02-26USANo185 Lbs5 ft11NoNoN/ANoNo22024-05-19FalseFalsePro & Farm832,500$570,735$0$0$No832,500$--------832,500$--------No--------Lien
Arttu RuotsalainenChicago Wolves (CAR)C261997-10-29FINNo187 Lbs5 ft9NoNoN/ANoNo2FalseFalsePro & Farm925,000$634,149$0$0$No925,000$--------600,000$--------No--------Lien
Cameron CrottyChicago Wolves (CAR)D251999-05-05CANNo182 Lbs6 ft3NoNoN/ANoNo22024-05-19FalseFalsePro & Farm775,000$531,314$0$0$No775,000$--------775,000$--------No--------Lien
Charles HudonChicago Wolves (CAR)LW301994-06-23CANNo190 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm1,750,000$1,199,742$0$0$No1,750,000$--------600,000$--------No--------Lien
Daniel O'ReganChicago Wolves (CAR)C301994-01-30GERNo180 Lbs5 ft9NoNoN/ANoNo1FalseFalsePro & Farm1,999,999$1,371,133$0$0$No---------------------------Lien
Danil GushchinChicago Wolves (CAR)LW222002-02-06RUSYes165 Lbs5 ft8NoNoAssign ManuallyNoNo22024-08-20FalseFalsePro & Farm867,500$594,729$0$0$No867,500$--------600,000$--------No--------Lien
Dylan GarandChicago Wolves (CAR)G222002-06-07CANYes173 Lbs6 ft0NoNoAssign ManuallyNoNo22024-08-20FalseFalsePro & Farm775,000$531,314$0$0$No775,000$--------600,000$--------No--------Lien
Emil AndraeChicago Wolves (CAR)D222002-02-23SWEYes189 Lbs5 ft9NoNoAssign ManuallyNoNo22024-08-20FalseFalsePro & Farm892,500$611,869$0$0$No892,500$--------600,000$--------No--------Lien
Emil HeinemanChicago Wolves (CAR)LW222001-10-26SWEYes202 Lbs6 ft0NoNoAssign ManuallyNoNo22024-08-20FalseFalsePro & Farm925,000$634,149$0$0$No925,000$--------600,000$--------No--------Lien
Emilio PettersenChicago Wolves (CAR)LW242000-04-03NORNo170 Lbs5 ft11NoNoN/ANoNo42024-05-19FalseFalsePro & Farm775,000$531,314$0$0$No775,000$775,000$775,000$------775,000$775,000$775,000$------NoNoNo------Lien
Gabriel DumontChicago Wolves (CAR)C/RW331990-10-06CANNo195 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm1,999,999$1,371,133$0$0$No1,999,999$--------600,000$--------No--------Lien
Gianni FairbrotherChicago Wolves (CAR)D242000-09-03CANNo192 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm842,500$577,590$0$0$No---------------------------Lien
Jakob PelletierChicago Wolves (CAR)LW232001-03-07CANYes170 Lbs5 ft9NoNoN/ANoNo1FalseFalsePro & Farm832,500$570,735$0$0$No---------------------------Lien
Jonathan DavidssonChicago Wolves (CAR)RW271997-03-12SWEYes185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm787,500$539,884$0$0$No---------------------------Lien
Josh MahuraChicago Wolves (CAR)D261998-05-05CANNo193 Lbs6 ft0NoNoN/ANoNo3FalseFalsePro & Farm750,000$514,175$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien
Keean WashkurakChicago Wolves (CAR)C232001-08-16CANNo184 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm835,000$572,448$0$0$No---------------------------Lien
Lias AnderssonChicago Wolves (CAR)C/LW251998-10-13SWENo185 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm750,000$514,175$0$0$No---------------------------Lien
Michael MerschChicago Wolves (CAR)LW311992-10-02USANo213 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm1,999,999$1,371,133$0$0$No1,999,999$--------600,000$--------No--------Lien
Nikita OkhotiukChicago Wolves (CAR)D232000-12-04RUSNo195 Lbs6 ft1NoNoN/ANoNo42024-05-19FalseFalsePro & Farm775,000$531,314$0$0$No775,000$775,000$775,000$------775,000$775,000$775,000$------NoNoNo------Lien
Robin SaloChicago Wolves (CAR)D251998-10-13FINNo190 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm842,500$577,590$0$0$No842,500$--------600,000$--------No--------Lien
Simon LundmarkChicago Wolves (CAR)D232000-10-08SWENo201 Lbs6 ft2NoNoN/ANoNo22024-05-19FalseFalsePro & Farm867,500$594,729$0$0$No867,500$--------867,500$--------No--------Lien
Simon RyforsChicago Wolves (CAR)C271997-08-16SWENo181 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm842,500$577,590$0$0$No842,500$--------600,000$--------No--------Lien
Steven KampferChicago Wolves (CAR)D361988-09-24USANo198 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm800,000$548,454$0$0$No---------------------------Lien
Tommy CrossChicago Wolves (CAR)D361988-09-14USANo205 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm1,999,999$1,371,133$0$0$No1,999,999$--------600,000$--------No--------Lien
Tyler TuckerChicago Wolves (CAR)D242000-03-01CANYes204 Lbs6 ft1NoNoAssign ManuallyNoNo32024-08-20FalseFalsePro & Farm800,000$548,454$0$0$No800,000$800,000$-------600,000$600,000$-------NoNo-------Lien
Victor SoderstromChicago Wolves (CAR)D232001-02-26SWENo184 Lbs5 ft11NoNoN/ANoNo22024-05-19FalseFalsePro & Farm832,500$570,735$0$0$No832,500$--------832,500$--------No--------Lien
Zac JonesChicago Wolves (CAR)D232000-10-18USAYes176 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm925,000$634,149$0$0$No---------------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2725.85188 Lbs5 ft111.931,037,037$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Michael MerschGabriel Dumont38122
230122
3Michael Mersch22122
4Charles HudonAlex Turcotte10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Robin Salo38122
2Zac JonesVictor Soderstrom30122
3Nikita Okhotiuk22122
410122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Michael MerschGabriel Dumont60122
240122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Robin Salo60122
2Zac JonesVictor Soderstrom40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Michael Mersch60122
240122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Robin Salo60122
2Zac JonesVictor Soderstrom40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Michael Mersch60122Robin Salo60122
240122Zac JonesVictor Soderstrom40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Michael Mersch60122
240122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Robin Salo60122
2Zac JonesVictor Soderstrom40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Michael MerschGabriel DumontRobin Salo
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Michael MerschGabriel DumontRobin Salo
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, Charles Hudon, , Charles Hudon
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Nikita Okhotiuk, , Nikita Okhotiuk,
Tirs de pénalité
Michael Mersch, , , , Gabriel Dumont
Gardien
#1 : , #2 :


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
1Bakersfield Condors21100000981000000000002110000098120.50091625004632347802793403442937106624250.00%30100.00%045172662.12%19937652.93%29444266.52%974794452129278159
2Belleville Senators3300000016881100000053222000000115661.00016304600463234711027934034429531612827342.86%5260.00%045172662.12%19937652.93%29444266.52%974794452129278159
3Bridgeport Islanders10000010431100000104310000000000021.0004590046323474927934034429215427200.00%2150.00%045172662.12%19937652.93%29444266.52%974794452129278159
4Calgary Wranglers11000000606000000000001100000060621.000691501463234753279340344298402733100.00%000%045172662.12%19937652.93%29444266.52%974794452129278159
5Charlotte Checkers22000000844110000002111100000063341.00081624004632347562793403442934138392150.00%40100.00%045172662.12%19937652.93%29444266.52%974794452129278159
6Coachella Valley Firebirds1000000156-11000000156-10000000000010.500591400463234726279340344292984164250.00%220.00%045172662.12%19937652.93%29444266.52%974794452129278159
7Colorado Eagles2010000148-4000000000002010000148-410.250471100463234753279340344295116956100.00%110.00%045172662.12%19937652.93%29444266.52%974794452129278159
8Henderson Silver Knights1010000015-4000000000001010000015-400.00012300463234714279340344293491311300.00%4175.00%045172662.12%19937652.93%29444266.52%974794452129278159
9Hershey Bears440000002041622000000111102200000093681.00020365601463234714827934034429712010759222.22%6183.33%045172662.12%19937652.93%29444266.52%974794452129278159
10LeHigh Valley Phantoms11000000633110000006330000000000021.0006111700463234739279340344291752214250.00%10100.00%045172662.12%19937652.93%29444266.52%974794452129278159
11Manitoba Moose10000010541100000105410000000000021.0005712004632347472793403442914293122100.00%2150.00%045172662.12%19937652.93%29444266.52%974794452129278159
12Rockford IceHogs11000000808110000008080000000000021.000811190146323475527934034429774143266.67%20100.00%145172662.12%19937652.93%29444266.52%974794452129278159
13San Jose Barracuda1010000024-2000000000001010000024-200.00023510463234740279340344292291119300.00%30100.00%045172662.12%19937652.93%29444266.52%974794452129278159
14Syracuse Crunch22000000963220000009630000000000041.00091625004632347642793403442935101742200.00%6183.33%045172662.12%19937652.93%29444266.52%974794452129278159
15Texas Stars1010000013-2000000000001010000013-200.000123004632347212793403442923844500.00%20100.00%045172662.12%19937652.93%29444266.52%974794452129278159
16Toronto Marlies10000010321000000000001000001032121.00034700463234740279340344299561911100.00%30100.00%045172662.12%19937652.93%29444266.52%974794452129278159
17Tucson Roadrunners11000000422000000000001100000042221.0004711004632347382793403442919702611100.00%000%045172662.12%19937652.93%29444266.52%974794452129278159
18Utica Comets11000000211110000002110000000000021.0002240046323472327934034429178812400.00%3166.67%045172662.12%19937652.93%29444266.52%974794452129278159
19Wilkes-Barre/Scranton Penguins1010000024-21010000024-20000000000000.0002460046323472127934034429247423400.00%10100.00%045172662.12%19937652.93%29444266.52%974794452129278159
Total28176000321157540139100021593227158500011564313420.75011519731213463234797727934034429525169131606642132.81%501178.00%145172662.12%19937652.93%29444266.52%974794452129278159
_Since Last GM Reset28176000321157540139100021593227158500011564313420.75011519731213463234797727934034429525169131606642132.81%501178.00%145172662.12%19937652.93%29444266.52%974794452129278159
_Vs Conference171310003075393611810002046262065000010291316320.94175131206014632347597279340344292959180371371129.73%33778.79%045172662.12%19937652.93%29444266.52%974794452129278159

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2842L111519731297752516913160613
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
28176003211575
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
139100215932
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
158500115643
Derniers 10 matchs
WLOTWOTL SOWSOL
610012
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
642132.81%501178.00%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
279340344294632347
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
45172662.12%19937652.93%29444266.52%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
974794452129278159


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
518Manitoba Moose4Chicago Wolves5WXXSommaire du match
730Chicago Wolves6Charlotte Checkers3WSommaire du match
943Utica Comets1Chicago Wolves2WSommaire du match
1161Chicago Wolves6Belleville Senators3WSommaire du match
1371Chicago Wolves1Colorado Eagles4LSommaire du match
1584Hershey Bears1Chicago Wolves4WSommaire du match
17105Charlotte Checkers1Chicago Wolves2WSommaire du match
20118Chicago Wolves4Bakersfield Condors5LSommaire du match
23138Rockford IceHogs0Chicago Wolves8WSommaire du match
25161Chicago Wolves2San Jose Barracuda4LSommaire du match
27173Wilkes-Barre/Scranton Penguins4Chicago Wolves2LSommaire du match
29187Chicago Wolves4Hershey Bears2WSommaire du match
30202Chicago Wolves5Belleville Senators2WSommaire du match
32218Hershey Bears0Chicago Wolves7WSommaire du match
35233Chicago Wolves4Tucson Roadrunners2WSommaire du match
37244Bridgeport Islanders3Chicago Wolves4WXXSommaire du match
38262Chicago Wolves5Bakersfield Condors3WSommaire du match
40274Chicago Wolves1Texas Stars3LSommaire du match
42283Coachella Valley Firebirds6Chicago Wolves5LXXSommaire du match
44305Syracuse Crunch2Chicago Wolves3WSommaire du match
47329Chicago Wolves6Calgary Wranglers0WSommaire du match
48342Chicago Wolves3Toronto Marlies2WXXSommaire du match
50347Syracuse Crunch4Chicago Wolves6WSommaire du match
53368Chicago Wolves3Colorado Eagles4LXXSommaire du match
55377Chicago Wolves5Hershey Bears1WSommaire du match
57384Belleville Senators3Chicago Wolves5WSommaire du match
60407LeHigh Valley Phantoms3Chicago Wolves6WSommaire du match
61418Chicago Wolves1Henderson Silver Knights5LSommaire du match
65438Chicago Wolves-Belleville Senators-
66448Providence Bruins-Chicago Wolves-
68466Chicago Wolves-Hartford Wolf Pack-
71477Cleveland Monsters-Chicago Wolves-
73492Chicago Wolves-Rochester Americans-
75508Rochester Americans-Chicago Wolves-
80534Manitoba Moose-Chicago Wolves-
88564Rockford IceHogs-Chicago Wolves-
90587Chicago Wolves-Utica Comets-
91594Chicago Wolves-Iowa Wild-
93607San Jose Barracuda-Chicago Wolves-
95626Wilkes-Barre/Scranton Penguins-Chicago Wolves-
98644Chicago Wolves-Springfield Thunderbirds-
99655Chicago Wolves-Wilkes-Barre/Scranton Penguins-
101671Ontario Reign-Chicago Wolves-
103691Utica Comets-Chicago Wolves-
106711Chicago Wolves-Laval Rocket-
108722Charlotte Checkers-Chicago Wolves-
110743Chicago Wolves-Manitoba Moose-
112753Charlotte Checkers-Chicago Wolves-
114772Chicago Wolves-Manitoba Moose-
116787Chicago Wolves-Providence Bruins-
117793Colorado Eagles-Chicago Wolves-
122820Hershey Bears-Chicago Wolves-
124832Chicago Wolves-LeHigh Valley Phantoms-
126850Laval Rocket-Chicago Wolves-
128861Chicago Wolves-Abbotsford Canucks-
142877Chicago Wolves-Syracuse Crunch-
143889Toronto Marlies-Chicago Wolves-
147912Chicago Wolves-Syracuse Crunch-
149921Hartford Wolf Pack-Chicago Wolves-
151946Texas Stars-Chicago Wolves-
153956Chicago Wolves-Charlotte Checkers-
157981San Diego Gulls-Chicago Wolves-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
158988Chicago Wolves-Abbotsford Canucks-
1631011Milwaukee Admirals-Chicago Wolves-
1701039Utica Comets-Chicago Wolves-
1711045Chicago Wolves-Charlotte Checkers-
1741068Grand Rapids Griffins-Chicago Wolves-
1781093Milwaukee Admirals-Chicago Wolves-
1801099Chicago Wolves-Bridgeport Islanders-
1831113Chicago Wolves-San Jose Barracuda-
1871131Manitoba Moose-Chicago Wolves-
1931152Chicago Wolves-Bridgeport Islanders-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3010
Assistance25,07512,936
Assistance PCT96.44%99.51%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
23 2924 - 97.46% 80,023$1,040,301$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
900,118$ 2,800,000$ 1,814,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
14,433$ 900,118$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,840,533$ 133 14,433$ 1,919,589$




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

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

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

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

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