Connexion

Chicago Wolves
GP: 24 | W: 8 | L: 13 | OTL: 3 | P: 19
GF: 66 | GA: 91 | PP%: 23.21% | PK%: 70.37%
DG: Francis Lachance | Morale : 99 | Moyenne d’équipe : 65
Prochains matchs #341 vs San Jose Barracuda
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

Centre de jeu
Chicago Wolves
8-13-3, 19pts
1
FINAL
3 Rockford IceHogs
13-11-1, 27pts
Team Stats
OTL1SéquenceL1
1-8-2Fiche domicile8-7-1
7-5-1Fiche domicile5-4-0
3-6-1Derniers 10 matchs4-5-1
2.75Buts par match 3.32
3.79Buts contre par match 3.08
23.21%Pourcentage en avantage numérique25.37%
70.37%Pourcentage en désavantage numérique85.51%
Utica Comets
12-11-2, 26pts
4
FINAL
3 Chicago Wolves
8-13-3, 19pts
Team Stats
W3SéquenceOTL1
4-3-1Fiche domicile1-8-2
8-8-1Fiche domicile7-5-1
7-3-0Derniers 10 matchs3-6-1
3.00Buts par match 2.75
3.80Buts contre par match 3.79
12.16%Pourcentage en avantage numérique23.21%
75.00%Pourcentage en désavantage numérique70.37%
Chicago Wolves
8-13-3, 19pts
Jour 58
San Jose Barracuda
11-10-2, 24pts
Statistiques d’équipe
OTL1SéquenceW1
1-8-2Fiche domicile5-7-1
7-5-1Fiche visiteur6-3-1
3-6-110 derniers matchs6-3-1
2.75Buts par match 3.35
3.79Buts contre par match 3.35
23.21%Pourcentage en avantage numérique17.91%
70.37%Pourcentage en désavantage numérique78.46%
Ontario Reign
9-11-3, 21pts
Jour 60
Chicago Wolves
8-13-3, 19pts
Statistiques d’équipe
W3SéquenceOTL1
6-6-2Fiche domicile1-8-2
3-5-1Fiche visiteur7-5-1
4-5-110 derniers matchs3-6-1
2.74Buts par match 2.75
2.91Buts contre par match 2.75
17.39%Pourcentage en avantage numérique23.21%
73.53%Pourcentage en désavantage numérique70.37%
San Diego Gulls
13-10-2, 28pts
Jour 63
Chicago Wolves
8-13-3, 19pts
Statistiques d’équipe
W4SéquenceOTL1
8-4-1Fiche domicile1-8-2
5-6-1Fiche visiteur7-5-1
7-3-010 derniers matchs3-6-1
3.28Buts par match 2.75
3.28Buts contre par match 2.75
13.41%Pourcentage en avantage numérique23.21%
86.67%Pourcentage en désavantage numérique70.37%
Meneurs d'équipe
Buts
Terik Parascak
9
Passes
Terik Parascak
14
Points
Terik Parascak
23
Plus/Moins
Mitchell Wheaton
3
Victoires
Topias Leinonen
6
Pourcentage d’arrêts
Topias Leinonen
0.911

Statistiques d’équipe
Buts pour
66
2.75 GFG
Tirs pour
839
34.96 Avg
Pourcentage en avantage numérique
23.2%
13 GF
Début de zone offensive
38.4%
Buts contre
91
3.79 GAA
Tirs contre
910
37.92 Avg
Pourcentage en désavantage numérique
70.4%%
8 GA
Début de la zone défensive
38.3%
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$
4Nicholas HenryX97.0075387682757778725671716868626359996702511,000,000$
5Artyom ManyukanX100.006124808765757770506565606564804699650262800,000$
6Anthony SalinitriX100.006128787771677165795765626872764599630262510,000$
7Tyler SoyX100.005115888671748160865664606866714099630271510,000$
8Alex DostieX100.005216878674788161875760656358555599630271600,000$
9Christopher Lalancette X100.00418998775828358875558586367713999630301510,000$
10Reid DukeX100.005625837776737758865260626875764399620283510,000$
11Connor Carrick X100.005324908777868566566866626476903399680301750,000$
12Henry Thrun (R)X100.006633818777838364526353625548586399650231725,000$
13Mitchell WheatonX99.005520977883848556545453685561654099650292880,000$
14Luke Mittelstadt (R)X100.006533757770727269507069626843525799640212500,000$
15Jakub VotjaX100.007439647168606057516464666382821799630371500,000$
16Matthew CairnsX100.006933776976687148494848715052555799620262625,000$
17Yann SauveX100.004811998781807936483537714871712299620342500,001$
18Will BorgenX100.005722817975737749544641665063844999620271500,001$
Rayé
1Filip SveningssonX76.4783506587767276775167755868707046996802531,100,000$
2Cutter Gauthier (R)XX85.747534768078727270836774707337388599660201925,000$
3Tristan Luneau (R)X90.306936767174727278587268676847617699660203500,000$
MOYENNE D’ÉQUIPE97.48642981817575776463616265646166529965
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)99.00807881858180808079777841398199620192650,000$
3Topias Leinonen (R)100.00777885857483837373726841407899610201650,000$
Rayé
MOYENNE D’ÉQUIPE99.6780808283827878767673705351639963
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)RW2491423-142025379830609.18%1744818.702791347000000030.77%26206101.0301000011
2Juraj SlafkovskyChicago Wolves (CAR)LW2461319-1610039318924566.74%2045518.991671047000021043.48%231512000.8311000100
3Tyler SoyChicago Wolves (CAR)C2461016-70043950202912.00%1144318.481013150001231152.63%361106000.7200000002
4Christopher Lalancette Chicago Wolves (CAR)C248614-700112863224112.70%2451821.61112739000002058.04%317106000.5400000111
5Cutter GauthierChicago Wolves (CAR)C/LW164913-1140212728111914.29%430919.35347833000000046.34%369910000.8400000001
6Martin Frk Chicago Wolves (CAR)RW246612-40043288621546.98%1542917.880221040000000035.71%14177010.5600000110
7Filip SveningssonChicago Wolves (CAR)LW236612-46040349033676.67%1238216.62000000000132050.00%181512000.6300000012
8Alex DostieChicago Wolves (CAR)C24358-92013193810257.89%1626310.9600001000000057.26%24174000.6100000001
9Nicholas HenryChicago Wolves (CAR)RW24268-56033316527463.08%1239416.42000000000200044.12%136118000.4111000101
10Mitchell WheatonChicago Wolves (CAR)D2435830014341151627.27%1541117.14213230000014000%0223000.3900000010
11Artyom ManyukanChicago Wolves (CAR)RW24358-42010225820365.17%630112.55000000001120030.77%13197000.5300000000
12Anthony SalinitriChicago Wolves (CAR)C24336-8202421378248.11%928211.7900000000050023.81%2187000.4200000000
13Tristan LuneauChicago Wolves (CAR)D24156-226024253313113.03%2348620.2502255200000010%01015000.2500000000
14Henry ThrunChicago Wolves (CAR)D23055-200141717880%2238116.57000031000122000%0516000.2600000000
15Will BorgenChicago Wolves (CAR)D24055-5004136330%182219.210000600004000%008000.4500000000
16Jakub VotjaChicago Wolves (CAR)D24123-3403121195105.26%2738816.19000030000014000%0110000.1500000000
17Connor Carrick Chicago Wolves (CAR)D24033-22401333259110%3442017.5300000000019000%0711000.1400000000
18Reid DukeChicago Wolves (CAR)C24213-10032200100.00%1592.49213240000001050.00%1610001.0100000000
19Luke MittelstadtChicago Wolves (CAR)D10123120131812848.33%1319519.5310142100000000%046000.3100000000
20Yann SauveChicago Wolves (CAR)D24112-60011481212.50%81948.120000000001000%026000.2100000010
21Matthew CairnsChicago Wolves (CAR)D24000-320884230%71988.280000400003000%01700000000000
Statistiques d’équipe totales ou en moyenne48065112177-1495203885028392805257.75%314718614.971324376444600031617250.93%1555174187110.4923000469
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)156620.9113.2188020475282591000146310
2Frans Tuohimaa Chicago Wolves (CAR)41300.8525.91203002013570101.000241000
3Michael HrabalChicago Wolves (CAR)71410.9073.8136200232461130100617100
Statistiques d’équipe totales ou en moyenne2681330.9013.73144620909094422122424410


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$420,942$0$0$No------------------
Anthony SalinitriChicago Wolves (CAR)C261988-08-31No186 Lbs5 ft11NoNoFree AgentNoNo22024-09-02Pro & Farm510,000$357,801$0$0$No510,000$--------No--------
Artyom ManyukanChicago Wolves (CAR)RW261988-09-04No159 Lbs5 ft7NoNoFree AgentNoNo22024-09-02Pro & Farm800,000$561,257$0$0$No800,000$--------No--------
Christopher Lalancette Chicago Wolves (CAR)C301984-10-14No197 Lbs6 ft1NoNoN/ANoNo1Pro & Farm510,000$357,801$0$0$No------------------
Connor Carrick Chicago Wolves (CAR)D301984-10-14No206 Lbs6 ft1NoNoN/ANoNo1Pro & Farm750,000$526,178$0$0$No------------------
Cutter Gauthier (sur la masse salariale)Chicago Wolves (CAR)C/LW201994-09-01Yes206 Lbs6 ft4NoNoN/ANoNo1Pro & Farm925,000$648,953$0$0$Yes------------------
Filip Sveningsson (sur la masse salariale)Chicago Wolves (CAR)LW251989-09-07No196 Lbs6 ft3NoNoFree AgentNoNo32024-09-02Pro & Farm1,100,000$771,728$0$0$Yes1,100,000$1,100,000$-------NoNo-------
Frans Tuohimaa Chicago Wolves (CAR)G331981-10-14No190 Lbs6 ft2NoNoN/ANoNo1Pro & Farm1,000,000$701,571$0$0$No------------------
Henry ThrunChicago Wolves (CAR)D231991-08-31Yes207 Lbs6 ft3NoNoN/ANoNo1Pro & Farm725,000$508,639$0$0$No------------------
Jakub VotjaChicago Wolves (CAR)D371977-08-31No35 Lbs1 ft7NoNoN/ANoNo1Pro & Farm500,000$350,785$0$0$No------------------
Juraj SlafkovskyChicago Wolves (CAR)LW201994-09-01Yes235 Lbs6 ft5NoNoN/ANoNo1Pro & Farm925,000$648,953$0$0$No------------------
Luke MittelstadtChicago Wolves (CAR)D211993-09-09Yes175 Lbs6 ft1NoNoN/ANoNo2Pro & Farm500,000$350,785$0$0$No500,000$--------No--------
Martin Frk Chicago Wolves (CAR)RW301984-10-14No219 Lbs6 ft1NoNoN/ANoNo1Pro & Farm750,000$526,178$0$0$No------------------
Matthew CairnsChicago Wolves (CAR)D261988-08-31No210 Lbs6 ft2NoNoN/ANoNo2Pro & Farm625,000$438,482$0$0$No625,000$--------No--------
Michael HrabalChicago Wolves (CAR)G191995-09-09Yes220 Lbs6 ft9NoNoN/ANoNo2Pro & Farm650,000$456,021$0$0$No650,000$--------No--------
Mitchell WheatonChicago Wolves (CAR)D291985-10-05No237 Lbs6 ft5NoNoN/ANoNo2Pro & Farm880,000$617,382$0$0$No880,000$--------No--------
Nicholas HenryChicago Wolves (CAR)RW251989-10-04No205 Lbs5 ft11NoNoTrade2024-01-05NoNo1Pro & Farm1,000,000$701,571$0$0$No------------------
Reid DukeChicago Wolves (CAR)C281986-09-07No205 Lbs6 ft0NoNoFree AgentNoNo32024-09-02Pro & Farm510,000$357,801$0$0$No510,000$510,000$-------NoNo-------
Terik ParascakChicago Wolves (CAR)RW181996-09-03Yes179 Lbs5 ft11NoNoProspectNoNo32024-09-02Pro & Farm925,000$648,953$0$0$No925,000$925,000$-------NoNo-------
Topias LeinonenChicago Wolves (CAR)G201994-09-01Yes238 Lbs6 ft7NoNoN/ANoNo1Pro & Farm650,000$456,021$0$0$No------------------
Tristan Luneau (sur la masse salariale)Chicago Wolves (CAR)D201994-09-03Yes192 Lbs6 ft2NoNoProspectNoNo32024-09-02Pro & Farm500,000$350,785$0$0$Yes500,000$500,000$-------NoNo-------
Tyler SoyChicago Wolves (CAR)C271987-10-09No186 Lbs6 ft0NoNoN/ANoNo1Pro & Farm510,000$357,801$0$0$No------------------
Will BorgenChicago Wolves (CAR)D271987-09-04No202 Lbs6 ft2NoNoN/ANoNo1Pro & Farm500,001$350,786$0$0$No------------------
Yann SauveChicago Wolves (CAR)D341980-08-06No229 Lbs6 ft2NoNoN/ANoNo2Pro & Farm500,001$350,786$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 SlafkovskyNicholas HenryTerik Parascak31014
2Reid DukeTyler SoyMartin Frk 28023
3Nicholas HenryChristopher Lalancette Artyom Manyukan22023
4Christopher Lalancette Alex DostieAnthony Salinitri19032
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Henry ThrunConnor Carrick 33122
2Mitchell WheatonLuke Mittelstadt27122
3Mitchell WheatonJakub Votja26122
4Matthew CairnsYann Sauve14122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Juraj SlafkovskyTyler SoyTerik Parascak53005
2Christopher Lalancette Reid DukeMartin Frk 47014
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Luke MittelstadtConnor Carrick 53014
2Henry ThrunMitchell Wheaton47113
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Tyler SoyNicholas Henry55131
2Reid DukeArtyom 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
1Reid DukeJuraj Slafkovsky55113
2Tyler SoyTerik Parascak45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Luke MittelstadtConnor Carrick 55122
2Henry ThrunMitchell Wheaton45122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Juraj SlafkovskyReid DukeTerik ParascakConnor Carrick Luke Mittelstadt
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Juraj SlafkovskyTyler SoyTerik ParascakHenry ThrunConnor Carrick
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 BorgenWill Borgen, Matthew Cairns
Tirs de pénalité
Terik Parascak, Juraj Slafkovsky, Nicholas Henry, Luke Mittelstadt, Tyler Soy
Gardien
#1 : Frans Tuohimaa , #2 : Michael Hrabal, #3 : Topias Leinonen
Lignes d’attaque personnalisées en prolongation
Juraj Slafkovsky, Artyom Manyukan, Anthony Salinitri, Tyler Soy, Terik Parascak, Nicholas Henry, Nicholas Henry, Reid Duke, Martin Frk , Christopher Lalancette , Alex Dostie
Lignes de défense personnalisées en prolongation
Luke Mittelstadt, 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
1Abbotsford's Canucks1010000025-3000000000001010000025-300.00024600191927240293263279739120193266.67%000%032559454.71%28259147.72%18536051.39%500287510215437219
2Bakersfield Condors1010000036-31010000036-30000000000000.00036900191927237293263279743114172150.00%2150.00%032559454.71%28259147.72%18536051.39%500287510215437219
3Belleville Senators1010000026-41010000026-40000000000000.0002240019192723829326327973413016100.00%000%032559454.71%28259147.72%18536051.39%500287510215437219
4Bridgeport's Islanders11000000211000000000001100000021121.00023500191927239293263279735126153133.33%3166.67%032559454.71%28259147.72%18536051.39%500287510215437219
5Calgary Wranglers11000000422000000000001100000042221.000471100191927242293263279742132183133.33%10100.00%032559454.71%28259147.72%18536051.39%500287510215437219
6Charlotte Checkers1010000023-1000000000001010000023-100.0002460019192723829326327973613019500.00%000%032559454.71%28259147.72%18536051.39%500287510215437219
7Colorado Eagles11000000312000000000001100000031221.000358001919272312932632797475415100.00%20100.00%032559454.71%28259147.72%18536051.39%500287510215437219
8Grand Rapids Griffins1010000013-21010000013-20000000000000.0001120019192723129326327973412620100.00%3166.67%032559454.71%28259147.72%18536051.39%500287510215437219
9Hartford Wolfpack11000000862000000000001100000086221.0008142200191927241293263279734210203133.33%000%032559454.71%28259147.72%18536051.39%500287510215437219
10Henderson Silver Knights1010000035-21010000035-20000000000000.00033610191927238293263279740154222150.00%2150.00%032559454.71%28259147.72%18536051.39%500287510215437219
11Iowa Wild1010000047-31010000047-30000000000000.000471100191927229293263279733112152150.00%10100.00%032559454.71%28259147.72%18536051.39%500287510215437219
12Laval Rocket11000000413110000004130000000000021.00046100019192723429326327974218212100.00%10100.00%032559454.71%28259147.72%18536051.39%500287510215437219
13Lehigh Valley Phantoms10000010541000000000001000001054121.000581300191927228293263279747152114250.00%110.00%032559454.71%28259147.72%18536051.39%500287510215437219
14Ontario Reign1010000024-2000000000001010000024-200.00022400191927236293263279747140132150.00%000%032559454.71%28259147.72%18536051.39%500287510215437219
15Providence Bruins1010000014-31010000014-30000000000000.00012300191927231293263279730144145120.00%20100.00%032559454.71%28259147.72%18536051.39%500287510215437219
16Rockford IceHogs1010000013-2000000000001010000013-200.0001230019192722629326327973510211300.00%10100.00%032559454.71%28259147.72%18536051.39%500287510215437219
17Springfield Thunderbirds2110000058-31010000027-51100000031220.500510150019192727229326327975021433500.00%220.00%032559454.71%28259147.72%18536051.39%500287510215437219
18Syracuse Crunch2010010038-51010000015-41000010023-110.2503690019192726229326327977329234300.00%10100.00%032559454.71%28259147.72%18536051.39%500287510215437219
19Texas Stars1010000025-3000000000001010000025-300.00024600191927231293263279753172212150.00%110.00%032559454.71%28259147.72%18536051.39%500287510215437219
20Toronto Marlies1000010023-11000010023-10000000000010.5002350019192723729326327973611216200.00%10100.00%032559454.71%28259147.72%18536051.39%500287510215437219
21Utica Comets1000010034-11000010034-10000000000010.5003580019192723729326327974213413100.00%20100.00%032559454.71%28259147.72%18536051.39%500287510215437219
22Wilkes-Barre/Scranton Penguins11000000422000000000001100000042221.00048120019192724129326327973814214200.00%10100.00%032559454.71%28259147.72%18536051.39%500287510215437219
Total24713003106691-251118002002651-2513650011040400190.39666112178101919272839293263279791031454388561323.21%27870.37%032559454.71%28259147.72%18536051.39%500287510215437219
_Since Last GM Reset24713003106691-251118002002651-2513650011040400190.39666112178101919272839293263279791031454388561323.21%27870.37%032559454.71%28259147.72%18536051.39%500287510215437219
_Vs Conference24713003106691-251118002002651-2513650011040400190.39666112178101919272839293263279791031454388561323.21%27870.37%032559454.71%28259147.72%18536051.39%500287510215437219
_Vs Division1334003103745-8713002001426-126210011023194110.42337629900191927245729326327974811853020431516.13%15380.00%032559454.71%28259147.72%18536051.39%500287510215437219

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2419OTL1661121788399103145438810
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
2471303106691
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
111802002651
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
136501104040
Derniers 10 matchs
WLOTWOTL SOWSOL
360100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
561323.21%27870.37%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
29326327971919272
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
32559454.71%28259147.72%18536051.39%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
500287510215437219


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 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
Assistance55,00055,000
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
30 10000 - 100.00% 372,500$4,097,500$10000110

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,046,672$ 2,864,000$ 2,864,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 972,059$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
11,175,000$ 134 16,304$ 2,184,736$




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