Connexion

Chicago Wolves
GP: 12 | W: 4 | L: 7 | OTL: 1 | P: 9
GF: 29 | GA: 39 | PP%: 22.58% | PK%: 70.59%
DG: Francis Lachance | Morale : 99 | Moyenne d’équipe : 65
Prochains matchs #181 vs Springfield Thunderbirds
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Centre de jeu
Chicago Wolves
4-7-1, 9pts
2
FINAL
4 Ontario Reign
5-4-1, 11pts
Team Stats
W1SéquenceW1
0-4-0Fiche domicile4-2-1
4-3-1Fiche domicile1-2-0
4-5-1Derniers 10 matchs5-4-1
2.42Buts par match 3.50
3.25Buts contre par match 3.20
22.58%Pourcentage en avantage numérique21.21%
70.59%Pourcentage en désavantage numérique78.57%
Chicago Wolves
4-7-1, 9pts
3
FINAL
1 Colorado Eagles
7-3-2, 16pts
Team Stats
W1SéquenceL1
0-4-0Fiche domicile5-2-1
4-3-1Fiche domicile2-1-1
4-5-1Derniers 10 matchs7-3-0
2.42Buts par match 4.17
3.25Buts contre par match 3.58
22.58%Pourcentage en avantage numérique33.33%
70.59%Pourcentage en désavantage numérique84.21%
Chicago Wolves
4-7-1, 9pts
Jour 30
Springfield Thunderbirds
6-3-1, 13pts
Statistiques d’équipe
W1SéquenceW1
0-4-0Fiche domicile2-2-0
4-3-1Fiche visiteur4-1-1
4-5-110 derniers matchs6-3-1
2.42Buts par match 3.60
3.25Buts contre par match 3.60
22.58%Pourcentage en avantage numérique26.32%
70.59%Pourcentage en désavantage numérique79.17%
Toronto Marlies
3-4-5, 11pts
Jour 33
Chicago Wolves
4-7-1, 9pts
Statistiques d’équipe
W1SéquenceW1
2-2-2Fiche domicile0-4-0
1-2-3Fiche visiteur4-3-1
3-2-510 derniers matchs4-5-1
3.17Buts par match 2.42
3.75Buts contre par match 2.42
20.00%Pourcentage en avantage numérique22.58%
81.97%Pourcentage en désavantage numérique70.59%
Chicago Wolves
4-7-1, 9pts
Jour 34
Hartford Wolfpack
5-6-0, 10pts
Statistiques d’équipe
W1SéquenceL3
0-4-0Fiche domicile2-2-0
4-3-1Fiche visiteur3-4-0
4-5-110 derniers matchs5-5-0
2.42Buts par match 3.55
3.25Buts contre par match 3.55
22.58%Pourcentage en avantage numérique17.24%
70.59%Pourcentage en désavantage numérique68.42%
Meneurs d'équipe
Buts
Christopher Lalancette
5
Passes
Terik Parascak
8
Points
Terik Parascak
11
Plus/Moins
Nicholas Henry
1
Victoires
Topias Leinonen
4
Pourcentage d’arrêts
Topias Leinonen
0.923

Statistiques d’équipe
Buts pour
29
2.42 GFG
Tirs pour
430
35.83 Avg
Pourcentage en avantage numérique
22.6%
7 GF
Début de zone offensive
39.1%
Buts contre
39
3.25 GAA
Tirs contre
479
39.92 Avg
Pourcentage en désavantage numérique
70.6%%
5 GA
Début de la zone défensive
39.6%
Informations de l'équipe

Directeur généralFrancis Lachance
EntraîneurPaul Maurice
DivisionEastern
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité10,000
Assistance10,000
Billets de saison4,000


Informations de la formation

Équipe Pro24
Équipe Mineure21
Limite contact 45 / 75
Espoirs2


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
1Juraj Slafkovsky (R)X100.008143747883707081637576727355548999690201925,000$
2Terik Parascak (R)X100.007329818573767681637774727429418299680183925,000$
3Martin Frk X100.007741768578858567526468666584735099680301750,000$
4Filip SveningssonX100.0083506587767276775167755868707046996802531,100,000$
5Nicholas HenryX100.0075387682757778725671716868626359996702511,000,000$
6Cutter Gauthier (R)XX100.007534768078727270836774707337388599660201925,000$
7Artyom ManyukanX100.006124808765757770506565606564804699650262800,000$
8Anthony SalinitriX100.006128787771677165795765626872764599630262510,000$
9Tyler SoyX99.005115888671748160865664606866714099630271510,000$
10Alex DostieX100.005216878674788161875760656358555599630271600,000$
11Christopher Lalancette X98.00418998775828358875558586367713999630301510,000$
12Reid DukeX100.005625837776737758865260626875764399620283510,000$
13Connor Carrick X100.005324908777868566566866626476903399680301750,000$
14Tristan Luneau (R)X98.006936767174727278587268676847617699660203500,000$
15Henry Thrun (R)X100.006633818777838364526353625548586399650231725,000$
16Mitchell WheatonX100.005520977883848556545453685561654099650292880,000$
17Jakub VotjaX100.007439647168606057516464666382821799630371500,000$
18Matthew CairnsX100.006933776976687148494848715052555799620262625,000$
19Yann SauveX100.004811998781807936483537714871712299620342500,001$
20Will BorgenX100.005722817975737749544641665063844999620271500,001$
Rayé
1Luke Mittelstadt (R)X89.416533757770727269507069626843525799640212500,000$
MOYENNE D’ÉQUIPE99.24642981817575776463616265646166529965
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
1Frans Tuohimaa 100.008285817992717176766965787530996503311,000,000$
2Michael Hrabal (R)98.00807881858180808079777841398199620192650,000$
3Topias Leinonen (R)97.00777885857483837373726841407899610201650,000$
Rayé
MOYENNE D’ÉQUIPE98.3380808283827878767673705351639963
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Paul Maurice69898672949578CAN564250,000$


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
1Terik ParascakChicago Wolves (CAR)RW123811-42013155320425.66%1122919.09156826000000036.84%19111100.9600000001
2Christopher Lalancette Chicago Wolves (CAR)C12549-40071937141613.51%1425521.30011421000001057.86%14054000.7000000110
3Cutter GauthierChicago Wolves (CAR)C/LW12369-44015212281613.64%323019.22325726000000047.22%28857000.7800000001
4Tyler SoyChicago Wolves (CAR)C12347-40021824121612.50%621117.59000010001140056.32%17433000.6600000000
5Juraj SlafkovskyChicago Wolves (CAR)LW12426-48018165312307.55%822819.04123725000001036.36%1196000.5300000000
6Artyom ManyukanChicago Wolves (CAR)RW12055100511309190%415412.8400000000180020.00%5105000.6500000000
7Tristan LuneauChicago Wolves (CAR)D12044-460101317490%1424720.6302242800000000%059000.3200000000
8Martin Frk Chicago Wolves (CAR)RW12224-30018104113274.88%820617.2400072200000000%362000.3900000010
9Nicholas HenryChicago Wolves (CAR)RW122241201810239258.70%315312.76000000000140054.55%1123000.5200000101
10Filip SveningssonChicago Wolves (CAR)LW12224-22017204713444.26%519616.4100000000091054.55%1183000.4100000002
11Alex DostieChicago Wolves (CAR)C12123-5007715376.67%101189.8900001000000055.04%12924000.5100000001
12Anthony SalinitriChicago Wolves (CAR)C12202-6001491341015.38%512510.4600000000030033.33%964000.3200000000
13Henry ThrunChicago Wolves (CAR)D11022-300687450%618817.10000016000113000%036000.2100000000
14Jakub VotjaChicago Wolves (CAR)D12022-14016813250%1419416.1700001600007000%005000.2100000000
15Luke MittelstadtChicago Wolves (CAR)D9112020131712838.33%1318120.1310142000000000%045000.2200000000
16Connor Carrick Chicago Wolves (CAR)D12011-32091412720%1419316.1600000000012000%044000.1000000000
17Mitchell WheatonChicago Wolves (CAR)D12011-2009132050%1019015.880000600007000%0012000.1000000000
18Will BorgenChicago Wolves (CAR)D12011-300132210%4534.470000500003000%001000.3700000000
19Reid DukeChicago Wolves (CAR)C12101-10030100100.00%0231.95101122000001042.86%700000.8600000000
20Matthew CairnsChicago Wolves (CAR)D12000-200541220%1968.060000400002000%00400000000000
21Yann SauveChicago Wolves (CAR)D12000-500075100%2978.110000000001000%01200000000000
Statistiques d’équipe totales ou en moyenne248294978-583202062434301472846.74%155357614.42712194224500031014051.55%8078490100.4400000226
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
1Topias LeinonenChicago Wolves (CAR)104510.9233.0159920303921980000102310
2Michael HrabalChicago Wolves (CAR)20200.9074.071180088634010029000
Statistiques d’équipe totales ou en moyenne124710.9213.1871820384782320101211310


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Type Salaire actuel Salaire restantPlafond salarial Non Activé Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Non-échange Année 2Non-échange Année 3Non-échange Année 4Non-échange Année 5Non-échange Année 6Non-échange Année 7Non-échange Année 8Non-échange Année 9Non-échange Année 10Lien
Alex DostieChicago Wolves (CAR)C271987-10-09No187 Lbs6 ft1NoNoN/ANoNo1Pro & Farm600,000$518,325$0$0$No------------------
Anthony SalinitriChicago Wolves (CAR)C261988-08-31No186 Lbs5 ft11NoNoFree AgentNoNo22024-09-02Pro & Farm510,000$440,576$0$0$No510,000$--------No--------
Artyom ManyukanChicago Wolves (CAR)RW261988-09-04No159 Lbs5 ft7NoNoFree AgentNoNo22024-09-02Pro & Farm800,000$691,099$0$0$No800,000$--------No--------
Christopher Lalancette Chicago Wolves (CAR)C301984-10-14No197 Lbs6 ft1NoNoN/ANoNo1Pro & Farm510,000$440,576$0$0$No------------------
Connor Carrick Chicago Wolves (CAR)D301984-10-14No206 Lbs6 ft1NoNoN/ANoNo1Pro & Farm750,000$647,906$0$0$No------------------
Cutter GauthierChicago Wolves (CAR)C/LW201994-09-01Yes206 Lbs6 ft4NoNoN/ANoNo1Pro & Farm925,000$799,084$0$0$No------------------
Filip SveningssonChicago Wolves (CAR)LW251989-09-07No196 Lbs6 ft3NoNoFree AgentNoNo32024-09-02Pro & Farm1,100,000$950,262$0$0$No1,100,000$1,100,000$-------NoNo-------
Frans Tuohimaa Chicago Wolves (CAR)G331981-10-14No190 Lbs6 ft2NoNoN/ANoNo1Pro & Farm1,000,000$863,874$0$0$No------------------
Henry ThrunChicago Wolves (CAR)D231991-08-31Yes207 Lbs6 ft3NoNoN/ANoNo1Pro & Farm725,000$626,309$0$0$No------------------
Jakub VotjaChicago Wolves (CAR)D371977-08-31No35 Lbs1 ft7NoNoN/ANoNo1Pro & Farm500,000$431,937$0$0$No------------------
Juraj SlafkovskyChicago Wolves (CAR)LW201994-09-01Yes235 Lbs6 ft5NoNoN/ANoNo1Pro & Farm925,000$799,084$0$0$No------------------
Luke Mittelstadt (sur la masse salariale)Chicago Wolves (CAR)D211993-09-09Yes175 Lbs6 ft1NoNoN/ANoNo2Pro & Farm500,000$431,937$0$0$Yes500,000$--------No--------
Martin Frk Chicago Wolves (CAR)RW301984-10-14No219 Lbs6 ft1NoNoN/ANoNo1Pro & Farm750,000$647,906$0$0$No------------------
Matthew CairnsChicago Wolves (CAR)D261988-08-31No210 Lbs6 ft2NoNoN/ANoNo2Pro & Farm625,000$539,921$0$0$No625,000$--------No--------
Michael HrabalChicago Wolves (CAR)G191995-09-09Yes220 Lbs6 ft9NoNoN/ANoNo2Pro & Farm650,000$561,518$0$0$No650,000$--------No--------
Mitchell WheatonChicago Wolves (CAR)D291985-10-05No237 Lbs6 ft5NoNoN/ANoNo2Pro & Farm880,000$760,209$0$0$No880,000$--------No--------
Nicholas HenryChicago Wolves (CAR)RW251989-10-04No205 Lbs5 ft11NoNoTrade2024-01-05NoNo1Pro & Farm1,000,000$863,874$0$0$No------------------
Reid DukeChicago Wolves (CAR)C281986-09-07No205 Lbs6 ft0NoNoFree AgentNoNo32024-09-02Pro & Farm510,000$440,576$0$0$No510,000$510,000$-------NoNo-------
Terik ParascakChicago Wolves (CAR)RW181996-09-03Yes179 Lbs5 ft11NoNoProspectNoNo32024-09-02Pro & Farm925,000$799,084$0$0$No925,000$925,000$-------NoNo-------
Topias LeinonenChicago Wolves (CAR)G201994-09-01Yes238 Lbs6 ft7NoNoN/ANoNo1Pro & Farm650,000$561,518$0$0$No------------------
Tristan LuneauChicago Wolves (CAR)D201994-09-03Yes192 Lbs6 ft2NoNoProspectNoNo32024-09-02Pro & Farm500,000$431,937$0$0$No500,000$500,000$-------NoNo-------
Tyler SoyChicago Wolves (CAR)C271987-10-09No186 Lbs6 ft0NoNoN/ANoNo1Pro & Farm510,000$440,576$0$0$No------------------
Will BorgenChicago Wolves (CAR)D271987-09-04No202 Lbs6 ft2NoNoN/ANoNo1Pro & Farm500,001$431,938$0$0$No------------------
Yann SauveChicago Wolves (CAR)D341980-08-06No229 Lbs6 ft2NoNoN/ANoNo2Pro & Farm500,001$431,938$0$0$No500,001$--------No--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2425.88196 Lbs6 ft01.63701,875$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Juraj SlafkovskyCutter GauthierTerik Parascak31014
2Filip SveningssonTyler SoyMartin Frk 28023
3Nicholas HenryChristopher Lalancette Artyom Manyukan22023
4Christopher Lalancette Alex DostieAnthony Salinitri19032
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Tristan LuneauConnor Carrick 33122
2Mitchell WheatonHenry Thrun27122
3Will BorgenJakub Votja26122
4Matthew CairnsYann Sauve14122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Juraj SlafkovskyCutter GauthierTerik Parascak53005
2Christopher Lalancette Reid DukeMartin Frk 47014
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mitchell WheatonTristan Luneau53014
2Henry ThrunJakub Votja47113
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Tyler SoyNicholas Henry55131
2Filip SveningssonArtyom Manyukan45131
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Henry ThrunConnor Carrick 55140
2Mitchell WheatonJakub Votja45140
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Tyler Soy55140Henry ThrunConnor Carrick 54140
2Nicholas Henry45140Will BorgenMitchell Wheaton46140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Cutter GauthierJuraj Slafkovsky55113
2Tyler SoyTerik Parascak45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mitchell WheatonTristan Luneau55122
2Henry ThrunJakub Votja45122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Juraj SlafkovskyCutter GauthierTerik ParascakTristan LuneauHenry Thrun
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Juraj SlafkovskyCutter GauthierTerik ParascakTristan LuneauHenry Thrun
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Tyler Soy, Cutter Gauthier, Artyom ManyukanTyler Soy, Alex DostieTyler Soy
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Connor Carrick , Will Borgen, Matthew CairnsWill BorgenWill Borgen, Matthew Cairns
Tirs de pénalité
Terik Parascak, Juraj Slafkovsky, Cutter Gauthier, Filip Sveningsson, Tyler Soy
Gardien
#1 : Topias Leinonen, #2 : Michael Hrabal, #3 : Frans Tuohimaa
Lignes d’attaque personnalisées en prolongation
Cutter Gauthier, Artyom Manyukan, Anthony Salinitri, Tyler Soy, Terik Parascak, Nicholas Henry, Nicholas Henry, Filip Sveningsson, Martin Frk , Christopher Lalancette , Alex Dostie
Lignes de défense personnalisées en prolongation
Tristan Luneau, Connor Carrick , Henry Thrun, Mitchell Wheaton, Jakub Votja


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 Condors1010000036-31010000036-30000000000000.000369008516037155126148143114172150.00%2150.00%017931556.83%14831946.39%8917251.74%255148256104208104
2Bridgeport's Islanders11000000211000000000001100000021121.000235008516039155126148135126153133.33%3166.67%017931556.83%14831946.39%8917251.74%255148256104208104
3Calgary Wranglers11000000422000000000001100000042221.0004711008516042155126148142132183133.33%10100.00%017931556.83%14831946.39%8917251.74%255148256104208104
4Charlotte Checkers1010000023-1000000000001010000023-100.00024600851603815512614813613019500.00%000%017931556.83%14831946.39%8917251.74%255148256104208104
5Colorado Eagles11000000312000000000001100000031221.0003580085160311551261481475415100.00%20100.00%017931556.83%14831946.39%8917251.74%255148256104208104
6Grand Rapids Griffins1010000013-21010000013-20000000000000.00011200851603115512614813412620100.00%3166.67%017931556.83%14831946.39%8917251.74%255148256104208104
7Henderson Silver Knights1010000035-21010000035-20000000000000.000336108516038155126148140154222150.00%2150.00%017931556.83%14831946.39%8917251.74%255148256104208104
8Ontario Reign1010000024-2000000000001010000024-200.000224008516036155126148147140132150.00%000%017931556.83%14831946.39%8917251.74%255148256104208104
9Providence Bruins1010000014-31010000014-30000000000000.000123008516031155126148130144145120.00%20100.00%017931556.83%14831946.39%8917251.74%255148256104208104
10Syracuse Crunch1000010023-1000000000001000010023-110.50024600851603515512614813415018300.00%000%017931556.83%14831946.39%8917251.74%255148256104208104
11Texas Stars1010000025-3000000000001010000025-300.000246008516031155126148153172212150.00%110.00%017931556.83%14831946.39%8917251.74%255148256104208104
12Wilkes-Barre/Scranton Penguins11000000422000000000001100000042221.000481200851604115512614813814214200.00%10100.00%017931556.83%14831946.39%8917251.74%255148256104208104
Total1247001002939-1040400000818-10843001002121090.375294978108516043015512614814791553420631722.58%17570.59%017931556.83%14831946.39%8917251.74%255148256104208104
_Since Last GM Reset1247001002939-1040400000818-10843001002121090.375294978108516043015512614814791553420631722.58%17570.59%017931556.83%14831946.39%8917251.74%255148256104208104
_Vs Conference1247001002939-1040400000818-10843001002121090.375294978108516043015512614814791553420631722.58%17570.59%017931556.83%14831946.39%8917251.74%255148256104208104
_Vs Division612001001216-42010000027-541100100109130.25012223400851602151551261481207801810019210.53%9277.78%017931556.83%14831946.39%8917251.74%255148256104208104

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
129W12949784304791553420610
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
124701002939
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4040000818
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
84301002121
Derniers 10 matchs
WLOTWOTL SOWSOL
450100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
31722.58%17570.59%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
155126148185160
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
17931556.83%14831946.39%8917251.74%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
255148256104208104


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
114Providence Bruins4Chicago Wolves1BLSommaire du match
424Henderson Silver Knights5Chicago Wolves3BLSommaire du match
640Chicago Wolves2Charlotte Checkers3ALSommaire du match
853Bakersfield Condors6Chicago Wolves3BLSommaire du match
1063Chicago Wolves4Wilkes-Barre/Scranton Penguins2AWSommaire du match
1277Chicago Wolves4Calgary Wranglers2AWSommaire du match
1490Chicago Wolves2Syracuse Crunch3ALXSommaire du match
17103Chicago Wolves2Bridgeport's Islanders1AWSommaire du match
20122Chicago Wolves2Texas Stars5ALSommaire du match
22132Grand Rapids Griffins3Chicago Wolves1BLSommaire du match
25147Chicago Wolves2Ontario Reign4ALSommaire du match
26155Chicago Wolves3Colorado Eagles1AWSommaire du match
30181Chicago Wolves-Springfield Thunderbirds-
33195Toronto Marlies-Chicago Wolves-
34203Chicago Wolves-Hartford Wolfpack-
36216Chicago Wolves-Abbotsford's Canucks-
38226Iowa Wild-Chicago Wolves-
41242Syracuse Crunch-Chicago Wolves-
43253Belleville Senators-Chicago Wolves-
45268Chicago Wolves-Lehigh Valley Phantoms-
47281Laval Rocket-Chicago Wolves-
51305Springfield Thunderbirds-Chicago Wolves-
53314Chicago Wolves-Rockford IceHogs-
56330Utica Comets-Chicago Wolves-
58341Chicago Wolves-San Jose Barracuda-
60354Ontario Reign-Chicago Wolves-
63371San Diego Gulls -Chicago Wolves-
65384Hershey Bears-Chicago Wolves-
68399Chicago Wolves-Henderson Silver Knights-
70409Chicago Wolves-Iowa Wild-
71416Chicago Wolves-Utica Comets-
75439Bridgeport's Islanders-Chicago Wolves-
77451Calgary Wranglers-Chicago Wolves-
79464Chicago Wolves-Hershey Bears-
80472Chicago Wolves-Rochester Americans-
84495Colorado Eagles-Chicago Wolves-
86506Texas Stars-Chicago Wolves-
88517San Jose Barracuda-Chicago Wolves-
91533Charlotte Checkers-Chicago Wolves-
93547Chicago Wolves-Belleville Senators-
95558Hartford Wolfpack-Chicago Wolves-
97567Chicago Wolves-Laval Rocket-
99581Chicago Wolves-Grand Rapids Griffins-
102596Chicago Wolves-Providence Bruins-
104606Chicago Wolves-Bakersfield Condors-
107627Abbotsford's Canucks-Chicago Wolves-
109638Lehigh Valley Phantoms-Chicago Wolves-
110647Chicago Wolves-Manitoba Moose-
112656Chicago Wolves-San Diego Gulls -
115674Rockford IceHogs-Chicago Wolves-
117685Wilkes-Barre/Scranton Penguins-Chicago Wolves-
120703Rochester Americans-Chicago Wolves-
123720Chicago Wolves-Toronto Marlies-
127738Manitoba Moose-Chicago Wolves-
131759San Jose Barracuda-Chicago Wolves-
132770Lehigh Valley Phantoms-Chicago Wolves-
135788Wilkes-Barre/Scranton Penguins-Chicago Wolves-
138809Chicago Wolves-Syracuse Crunch-
141827Chicago Wolves-Grand Rapids Griffins-
144842Chicago Wolves-Ontario Reign-
147862Chicago Wolves-Laval Rocket-
149877Charlotte Checkers-Chicago Wolves-
150882Chicago Wolves-Hershey Bears-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
153896Utica Comets-Chicago Wolves-
154908San Diego Gulls -Chicago Wolves-
157930Bakersfield Condors-Chicago Wolves-
159941Chicago Wolves-Calgary Wranglers-
161952Iowa Wild-Chicago Wolves-
163969Chicago Wolves-Abbotsford's Canucks-
165977Chicago Wolves-Toronto Marlies-
166985Chicago Wolves-Bridgeport's Islanders-
168998Chicago Wolves-Springfield Thunderbirds-
1711017Rochester Americans-Chicago Wolves-
1731032Rockford IceHogs-Chicago Wolves-
1751045Chicago Wolves-Henderson Silver Knights-
1761048Colorado Eagles-Chicago Wolves-
1781066Chicago Wolves-Hartford Wolfpack-
1811087Providence Bruins-Chicago Wolves-
1841103Chicago Wolves-Texas Stars-
1861114Belleville Senators-Chicago Wolves-
1881128Chicago Wolves-Manitoba Moose-
1901135Laval Rocket-Chicago Wolves-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité50005000
Prix des billets3515
Assistance20,00020,000
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
37 10000 - 100.00% 372,500$1,490,000$10000110

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
490,028$ 3,269,000$ 3,269,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 455,994$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
13,782,500$ 165 18,424$ 3,039,960$




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