Connexion

Chicago Wolves
GP: 32 | W: 14 | L: 15 | OTL: 3 | P: 31
GF: 97 | GA: 113 | PP%: 24.42% | PK%: 72.73%
DG: Francis Lachance | Morale : 99 | Moyenne d’équipe : 65
Prochains matchs #451 vs Calgary Wranglers
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Centre de jeu
Chicago Wolves
14-15-3, 31pts
4
FINAL
6 Utica Comets
14-16-2, 30pts
Team Stats
L2SéquenceL1
4-9-2Fiche domicile6-5-1
10-6-1Fiche domicile8-11-1
6-3-1Derniers 10 matchs5-5-0
3.03Buts par match 2.94
3.53Buts contre par match 3.97
24.42%Pourcentage en avantage numérique16.84%
72.73%Pourcentage en désavantage numérique72.15%
Bridgeport's Islanders
13-15-3, 29pts
4
FINAL
2 Chicago Wolves
14-15-3, 31pts
Team Stats
W1SéquenceL2
7-5-2Fiche domicile4-9-2
6-10-1Fiche domicile10-6-1
3-5-2Derniers 10 matchs6-3-1
2.81Buts par match 3.03
3.06Buts contre par match 3.53
12.50%Pourcentage en avantage numérique24.42%
78.65%Pourcentage en désavantage numérique72.73%
Calgary Wranglers
13-13-6, 32pts
Jour 77
Chicago Wolves
14-15-3, 31pts
Statistiques d’équipe
W1SéquenceL2
7-7-2Fiche domicile4-9-2
6-6-4Fiche visiteur10-6-1
5-3-210 derniers matchs6-3-1
3.34Buts par match 3.03
3.50Buts contre par match 3.03
21.28%Pourcentage en avantage numérique24.42%
72.12%Pourcentage en désavantage numérique72.73%
Chicago Wolves
14-15-3, 31pts
Jour 79
Hershey Bears
13-17-2, 28pts
Statistiques d’équipe
L2SéquenceL3
4-9-2Fiche domicile6-9-1
10-6-1Fiche visiteur7-8-1
6-3-110 derniers matchs4-6-0
3.03Buts par match 2.66
3.53Buts contre par match 2.66
24.42%Pourcentage en avantage numérique18.18%
72.73%Pourcentage en désavantage numérique80.56%
Chicago Wolves
14-15-3, 31pts
Jour 80
Rochester Americans
20-10-3, 43pts
Statistiques d’équipe
L2SéquenceL1
4-9-2Fiche domicile11-6-1
10-6-1Fiche visiteur9-4-2
6-3-110 derniers matchs6-3-1
3.03Buts par match 2.97
3.53Buts contre par match 2.97
24.42%Pourcentage en avantage numérique18.10%
72.73%Pourcentage en désavantage numérique84.21%
Meneurs d'équipe
Buts
Terik Parascak
14
Passes
Terik Parascak
22
Points
Terik Parascak
36
Plus/Moins
Mitchell Wheaton
4
Victoires
Topias Leinonen
6
Pourcentage d’arrêts
Michael Hrabal
0.918

Statistiques d’équipe
Buts pour
97
3.03 GFG
Tirs pour
1109
34.66 Avg
Pourcentage en avantage numérique
24.4%
21 GF
Début de zone offensive
39.0%
Buts contre
113
3.53 GAA
Tirs contre
1197
37.41 Avg
Pourcentage en désavantage numérique
72.7%%
9 GA
Début de la zone défensive
37.1%
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)X99.008143747883707081637576727355548999690201925,000$
2Terik Parascak (R)X100.007329818573767681637774727429418299680183925,000$
3Martin Frk X100.007741768578858567526468666584735099680301750,000$
4Nicholas HenryX100.0075387682757778725671716868626359996702511,000,000$
5Cutter Gauthier (R)XX100.007534768078727270836774707337388599660201925,000$
6Artyom ManyukanX100.006124808765757770506565606564804699650262800,000$
7Anthony SalinitriX100.006128787771677165795765626872764599630262510,000$
8Tyler SoyX100.005115888671748160865664606866714099630271510,000$
9Alex DostieX100.005216878674788161875760656358555599630271600,000$
10Christopher Lalancette X100.00418998775828358875558586367713999630301510,000$
11Reid DukeX100.005625837776737758865260626875764399620283510,000$
12Connor Carrick X100.005324908777868566566866626476903399680301750,000$
13Tristan Luneau (R)X100.006936767174727278587268676847617699660203500,000$
14Henry Thrun (R)X100.006633818777838364526353625548586399650231725,000$
15Luke Mittelstadt (R)X100.006533757770727269507069626843525799640212500,000$
16Jakub VotjaX100.007439647168606057516464666382821799630371500,000$
17Matthew CairnsX100.006933776976687148494848715052555799620262625,000$
18Yann SauveX100.004811998781807936483537714871712299620342500,001$
19Will BorgenX100.005722817975737749544641665063844999620271500,001$
Rayé
1Filip SveningssonX95.4783506587767276775167755868707046996802531,100,000$
2Mitchell WheatonX75.975520977883848556545453685561654099650292880,000$
MOYENNE D’ÉQUIPE98.52642981817575776463616265646166529965
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)100.00777885857483837373726841407899610201650,000$
Rayé
MOYENNE D’ÉQUIPE99.3380808283827878767673705351639963
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)RW32142236-18203847138428510.14%2161119.11310132573000030033.33%362410111.1801000133
2Juraj SlafkovskyChicago Wolves (CAR)LW32102131-21100543711033839.09%2662119.43210121873000072048.65%372215101.0011000300
3Tyler SoyChicago Wolves (CAR)C3291726-500105673224112.33%1559918.722357400002301152.61%4981610000.8700000002
4Christopher Lalancette Chicago Wolves (CAR)C32111021-300153482255413.41%2767921.233141259000002056.13%4081310000.6200000123
5Martin Frk Chicago Wolves (CAR)RW3291120-420643411728767.69%1857017.830441460000000250.00%22238010.7000000110
6Nicholas HenryChicago Wolves (CAR)RW327815-160544410040677.00%1855317.30000000000211144.38%1692010000.5411000211
7Artyom ManyukanChicago Wolves (CAR)RW32681422014277928507.59%1040212.58000000001131033.33%24238000.7000000100
8Cutter GauthierChicago Wolves (CAR)C/LW174913-1460232730112013.33%433019.47347838000000046.63%386911000.7900000001
9Filip SveningssonChicago Wolves (CAR)LW236612-46040349033676.67%1238216.62000000000132050.00%181512000.6300000012
10Alex DostieChicago Wolves (CAR)C324610-72014255111327.84%1733910.6100003000021056.44%30374000.5900000001
11Anthony SalinitriChicago Wolves (CAR)C32369-72032314510306.67%1541012.8400000000070041.18%1191011000.4400000000
12Mitchell WheatonChicago Wolves (CAR)D2936940016421391623.08%2552218.02213236000015000%0427000.3400000010
13Tristan LuneauChicago Wolves (CAR)D28268-256028273814125.26%2856820.2902277200002010%01220000.2800000000
14Henry ThrunChicago Wolves (CAR)D3108800024222210100%3252316.89000036000124000%0820000.3100000000
15Connor Carrick Chicago Wolves (CAR)D32066-264017383812160%4660218.82011420000022000%0917000.2000000000
16Luke MittelstadtChicago Wolves (CAR)D183363402727219614.29%2133818.8230385000001100%0710000.3500000001
17Jakub VotjaChicago Wolves (CAR)D32235-1603926297106.90%3550115.68101443000014100%0114000.2000000000
18Will BorgenChicago Wolves (CAR)D32055-3004146330%192467.710000600008000%008000.4100000000
19Reid DukeChicago Wolves (CAR)C32235-2201114134515.38%32066.44235456000011048.78%4174000.4900000000
20Yann SauveChicago Wolves (CAR)D32134-52021791311.11%92778.660000000006000%028000.2900000010
21Matthew CairnsChicago Wolves (CAR)D32000-22011115340%132858.920000500008000%01900000000000
Statistiques d’équipe totales ou en moyenne62696167263-13964053763411093556908.66%414957415.29213960113677000420813550.66%2061233246220.552300091014
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)156620.9113.21880204752825910001411310
2Michael HrabalChicago Wolves (CAR)125510.9183.17662003542621101001120111
3Frans Tuohimaa Chicago Wolves (CAR)73400.8764.703830030242126201.000271000
Statistiques d’équipe totales ou en moyenne34141530.9063.4919262011211965963123232421


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$361,257$0$0$No------------------
Anthony SalinitriChicago Wolves (CAR)C261988-08-31No186 Lbs5 ft11NoNoFree AgentNoNo22024-09-02Pro & Farm510,000$307,068$0$0$No510,000$--------No--------
Artyom ManyukanChicago Wolves (CAR)RW261988-09-04No159 Lbs5 ft7NoNoFree AgentNoNo22024-09-02Pro & Farm800,000$481,675$0$0$No800,000$--------No--------
Christopher Lalancette Chicago Wolves (CAR)C301984-10-14No197 Lbs6 ft1NoNoN/ANoNo1Pro & Farm510,000$307,068$0$0$No------------------
Connor Carrick Chicago Wolves (CAR)D301984-10-14No206 Lbs6 ft1NoNoN/ANoNo1Pro & Farm750,000$451,571$0$0$No------------------
Cutter GauthierChicago Wolves (CAR)C/LW201994-09-01Yes206 Lbs6 ft4NoNoN/ANoNo1Pro & Farm925,000$556,937$0$0$No------------------
Filip SveningssonChicago Wolves (CAR)LW251989-09-07No196 Lbs6 ft3NoNoFree AgentNoNo32024-09-02Pro & Farm1,100,000$662,304$0$0$No1,100,000$1,100,000$-------NoNo-------
Frans Tuohimaa Chicago Wolves (CAR)G331981-10-14No190 Lbs6 ft2NoNoN/ANoNo1Pro & Farm1,000,000$602,094$0$0$No------------------
Henry ThrunChicago Wolves (CAR)D231991-08-31Yes207 Lbs6 ft3NoNoN/ANoNo1Pro & Farm725,000$436,518$0$0$No------------------
Jakub VotjaChicago Wolves (CAR)D371977-08-31No35 Lbs1 ft7NoNoN/ANoNo1Pro & Farm500,000$301,047$0$0$No------------------
Juraj SlafkovskyChicago Wolves (CAR)LW201994-09-01Yes235 Lbs6 ft5NoNoN/ANoNo1Pro & Farm925,000$556,937$0$0$No------------------
Luke MittelstadtChicago Wolves (CAR)D211993-09-09Yes175 Lbs6 ft1NoNoN/ANoNo2Pro & Farm500,000$301,047$0$0$No500,000$--------No--------
Martin Frk Chicago Wolves (CAR)RW301984-10-14No219 Lbs6 ft1NoNoN/ANoNo1Pro & Farm750,000$451,571$0$0$No------------------
Matthew CairnsChicago Wolves (CAR)D261988-08-31No210 Lbs6 ft2NoNoN/ANoNo2Pro & Farm625,000$376,309$0$0$No625,000$--------No--------
Michael HrabalChicago Wolves (CAR)G191995-09-09Yes220 Lbs6 ft9NoNoN/ANoNo2Pro & Farm650,000$391,361$0$0$No650,000$--------No--------
Mitchell Wheaton (sur la masse salariale)Chicago Wolves (CAR)D291985-10-05No237 Lbs6 ft5NoNoN/ANoNo2Pro & Farm880,000$529,843$0$0$Yes880,000$--------No--------
Nicholas HenryChicago Wolves (CAR)RW251989-10-04No205 Lbs5 ft11NoNoTrade2024-01-05NoNo1Pro & Farm1,000,000$602,094$0$0$No------------------
Reid DukeChicago Wolves (CAR)C281986-09-07No205 Lbs6 ft0NoNoFree AgentNoNo32024-09-02Pro & Farm510,000$307,068$0$0$No510,000$510,000$-------NoNo-------
Terik ParascakChicago Wolves (CAR)RW181996-09-03Yes179 Lbs5 ft11NoNoProspectNoNo32024-09-02Pro & Farm925,000$556,937$0$0$No925,000$925,000$-------NoNo-------
Topias LeinonenChicago Wolves (CAR)G201994-09-01Yes238 Lbs6 ft7NoNoN/ANoNo1Pro & Farm650,000$391,361$0$0$No------------------
Tristan LuneauChicago Wolves (CAR)D201994-09-03Yes192 Lbs6 ft2NoNoProspectNoNo32024-09-02Pro & Farm500,000$301,047$0$0$No500,000$500,000$-------NoNo-------
Tyler SoyChicago Wolves (CAR)C271987-10-09No186 Lbs6 ft0NoNoN/ANoNo1Pro & Farm510,000$307,068$0$0$No------------------
Will BorgenChicago Wolves (CAR)D271987-09-04No202 Lbs6 ft2NoNoN/ANoNo1Pro & Farm500,001$301,048$0$0$No------------------
Yann SauveChicago Wolves (CAR)D341980-08-06No229 Lbs6 ft2NoNoN/ANoNo2Pro & Farm500,001$301,048$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
2Reid DukeTyler SoyMartin Frk 28023
3Nicholas HenryAnthony SalinitriArtyom Manyukan22023
4Christopher Lalancette Reid DukeNicholas Henry19032
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Connor Carrick Tristan Luneau33122
2Luke MittelstadtHenry Thrun27122
3Will BorgenJakub Votja26122
4Matthew CairnsYann Sauve14122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Juraj SlafkovskyCutter GauthierTerik Parascak53005
2Christopher Lalancette Tyler SoyMartin Frk 47014
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Tristan LuneauLuke Mittelstadt53014
2Connor Carrick Jakub Votja47113
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Tyler SoyJuraj Slafkovsky55131
2Christopher Lalancette Terik Parascak45131
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Matthew CairnsYann Sauve55140
2Matthew CairnsWill Borgen45140
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Tyler Soy55140Matthew CairnsYann Sauve54140
2Anthony Salinitri45140Will BorgenJakub Votja46140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Cutter GauthierJuraj Slafkovsky55113
2Tyler SoyTerik Parascak45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Connor Carrick Tristan Luneau55122
2Henry ThrunLuke Mittelstadt45122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Juraj SlafkovskyCutter GauthierTerik ParascakTristan LuneauLuke Mittelstadt
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Juraj SlafkovskyCutter GauthierTerik ParascakTristan LuneauLuke Mittelstadt
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Tyler Soy, Juraj Slafkovsky, Artyom ManyukanTyler Soy, Alex DostieTyler Soy
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Connor Carrick , Will Borgen, Matthew CairnsWill BorgenLuke Mittelstadt, Tristan Luneau
Tirs de pénalité
Terik Parascak, Juraj Slafkovsky, Cutter Gauthier, Luke Mittelstadt, Nicholas Henry
Gardien
#1 : Michael Hrabal, #2 : Topias Leinonen, #3 : Frans Tuohimaa
Lignes d’attaque personnalisées en prolongation
Juraj Slafkovsky, Cutter Gauthier, Anthony Salinitri, Terik Parascak, Tyler Soy, Nicholas Henry, Nicholas Henry, Reid Duke, Martin Frk , Christopher Lalancette , Alex Dostie
Lignes de défense personnalisées en prolongation
Luke Mittelstadt, Connor Carrick , Henry Thrun, Tristan Luneau, 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
1Abbotsford's Canucks1010000025-3000000000001010000025-300.00024600293037240388358359739120193266.67%000%042480053.00%37276048.95%24849150.51%662372675287591299
2Bakersfield Condors1010000036-31010000036-30000000000000.00036900293037237388358359743114172150.00%2150.00%042480053.00%37276048.95%24849150.51%662372675287591299
3Belleville Senators1010000026-41010000026-40000000000000.0002240029303723838835835973413016100.00%000%042480053.00%37276048.95%24849150.51%662372675287591299
4Bridgeport's Islanders2110000045-11010000024-21100000021120.50045900293037269388358359782268337114.29%4175.00%042480053.00%37276048.95%24849150.51%662372675287591299
5Calgary Wranglers11000000422000000000001100000042221.000471100293037242388358359742132183133.33%10100.00%042480053.00%37276048.95%24849150.51%662372675287591299
6Charlotte Checkers1010000023-1000000000001010000023-100.0002460029303723838835835973613019500.00%000%042480053.00%37276048.95%24849150.51%662372675287591299
7Colorado Eagles11000000312000000000001100000031221.000358002930372313883583597475415100.00%20100.00%042480053.00%37276048.95%24849150.51%662372675287591299
8Grand Rapids Griffins1010000013-21010000013-20000000000000.0001120029303723138835835973412620100.00%3166.67%042480053.00%37276048.95%24849150.51%662372675287591299
9Hartford Wolfpack11000000862000000000001100000086221.0008142200293037241388358359734210203133.33%000%042480053.00%37276048.95%24849150.51%662372675287591299
10Henderson Silver Knights211000008801010000035-21100000053220.5008122010293037276388358359772336446233.33%3166.67%042480053.00%37276048.95%24849150.51%662372675287591299
11Hershey Bears11000000211110000002110000000000021.0002460029303723038835835972690152150.00%000%042480053.00%37276048.95%24849150.51%662372675287591299
12Iowa Wild211000008801010000047-31100000041320.5008152300293037257388358359754172369222.22%10100.00%042480053.00%37276048.95%24849150.51%662372675287591299
13Laval Rocket11000000413110000004130000000000021.00046100029303723438835835974218212100.00%10100.00%042480053.00%37276048.95%24849150.51%662372675287591299
14Lehigh Valley Phantoms10000010541000000000001000001054121.000581300293037228388358359747152114250.00%110.00%042480053.00%37276048.95%24849150.51%662372675287591299
15Ontario Reign21100000651110000004131010000024-220.500691500293037272388358359781272285120.00%10100.00%042480053.00%37276048.95%24849150.51%662372675287591299
16Providence Bruins1010000014-31010000014-30000000000000.00012300293037231388358359730144145120.00%20100.00%042480053.00%37276048.95%24849150.51%662372675287591299
17Rockford IceHogs1010000013-2000000000001010000013-200.0001230029303722638835835973510211300.00%10100.00%042480053.00%37276048.95%24849150.51%662372675287591299
18San Diego Gulls 11000000633110000006330000000000021.0006111700293037228388358359741170263266.67%000%042480053.00%37276048.95%24849150.51%662372675287591299
19San Jose Barracuda11000000431000000000001100000043121.000471100293037240388358359734122143266.67%10100.00%042480053.00%37276048.95%24849150.51%662372675287591299
20Springfield Thunderbirds2110000058-31010000027-51100000031220.500510150029303727238835835975021433500.00%220.00%042480053.00%37276048.95%24849150.51%662372675287591299
21Syracuse Crunch2010010038-51010000015-41000010023-110.2503690029303726238835835977329234300.00%10100.00%042480053.00%37276048.95%24849150.51%662372675287591299
22Texas Stars1010000025-3000000000001010000025-300.00024600293037231388358359753172212150.00%110.00%042480053.00%37276048.95%24849150.51%662372675287591299
23Toronto Marlies1000010023-11000010023-10000000000010.5002350029303723738835835973611216200.00%10100.00%042480053.00%37276048.95%24849150.51%662372675287591299
24Utica Comets20100100710-31000010034-11010000046-210.2507121900293037277388358359794248315120.00%4175.00%042480053.00%37276048.95%24849150.51%662372675287591299
25Wilkes-Barre/Scranton Penguins11000000422000000000001100000042221.00048120029303724138835835973814214200.00%10100.00%042480053.00%37276048.95%24849150.51%662372675287591299
Total3213150031097113-161549002004060-2017960011057534310.4849716726410293037211093883583597119741466537862124.42%33972.73%042480053.00%37276048.95%24849150.51%662372675287591299
_Since Last GM Reset3213150031097113-161549002004060-2017960011057534310.4849716726410293037211093883583597119741466537862124.42%33972.73%042480053.00%37276048.95%24849150.51%662372675287591299
_Vs Conference3213150031097113-161549002004060-2017960011057534310.4849716726410293037211093883583597119741466537862124.42%33972.73%042480053.00%37276048.95%24849150.51%662372675287591299
_Vs Division1646003104556-11924002001831-137220011027252130.406457512000293037255738835835976062193625541717.07%18477.78%042480053.00%37276048.95%24849150.51%662372675287591299

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
3231L297167264110911974146653710
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
321315031097113
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
154902004060
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
179601105753
Derniers 10 matchs
WLOTWOTL SOWSOL
630100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
862124.42%33972.73%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
38835835972930372
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
42480053.00%37276048.95%24849150.51%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
662372675287591299


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 Wolves3Springfield Thunderbirds1AWSommaire du match
33195Toronto Marlies3Chicago Wolves2BLXSommaire du match
34203Chicago Wolves8Hartford Wolfpack6AWSommaire du match
36216Chicago Wolves2Abbotsford's Canucks5ALSommaire du match
38226Iowa Wild7Chicago Wolves4BLSommaire du match
41242Syracuse Crunch5Chicago Wolves1BLSommaire du match
43253Belleville Senators6Chicago Wolves2BLSommaire du match
45268Chicago Wolves5Lehigh Valley Phantoms4AWXXSommaire du match
47281Laval Rocket1Chicago Wolves4BWSommaire du match
51305Springfield Thunderbirds7Chicago Wolves2BLSommaire du match
53314Chicago Wolves1Rockford IceHogs3ALSommaire du match
56330Utica Comets4Chicago Wolves3BLXSommaire du match
58341Chicago Wolves4San Jose Barracuda3AWSommaire du match
60354Ontario Reign1Chicago Wolves4BWSommaire du match
63371San Diego Gulls 3Chicago Wolves6BWSommaire du match
65384Hershey Bears1Chicago Wolves2BWSommaire du match
68399Chicago Wolves5Henderson Silver Knights3AWSommaire du match
70409Chicago Wolves4Iowa Wild1AWSommaire du match
71416Chicago Wolves4Utica Comets6ALSommaire du match
75439Bridgeport's Islanders4Chicago Wolves2BLSommaire du match
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
Assistance75,00075,000
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
26 10000 - 100.00% 372,500$5,587,500$10000110

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,366,837$ 3,193,000$ 3,193,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 1,267,353$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
9,685,000$ 115 18,026$ 2,072,990$




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