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Chicago WolfChicago Chicago Wolf
36-31-7, 79pts · 13th in Conference Est

Chicago Wolf
GP: 74 | W: 36 | L: 31 | OTL: 7 | P: 79
GF: 105 | GA: 104 | PP%: 18.82% | PK%: 81.56%
DG: Anthony Bourgouin | Morale : 47 | Moyenne d’équipe : N/A
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Centre de jeu
Chicago Wolf
36-31-7, 79pts
1
FINAL
0 Rochester
33-26-15, 81pts
Team Stats
L1StreakOTL1
19-15-3Home Record16-10-11
17-16-4Away Record17-16-4
4-4-2Last 10 Games5-4-1
1.42Buts par match 1.45
1.41Buts contre par match 1.54
18.82%Pourcentage en avantage numérique18.75%
81.56%Pourcentage en désavantage numérique78.05%
Chicago Wolf
36-31-7, 79pts
1
FINAL
2 Milwaukee
34-30-10, 78pts
Team Stats
L1StreakW1
19-15-3Home Record21-13-3
17-16-4Away Record13-17-7
4-4-2Last 10 Games5-3-2
1.42Buts par match 1.35
1.41Buts contre par match 1.57
18.82%Pourcentage en avantage numérique19.80%
81.56%Pourcentage en désavantage numérique77.78%
Meneurs d'équipe

Statistiques d’équipe
Buts pour
105
1.42 GFG
Tirs pour
917
12.39 Avg
Pourcentage en avantage numérique
18.8%
54 GF
Début de zone offensive
32.2%
Buts contre
104
1.41 GAA
Tirs contre
985
13.31 Avg
Pourcentage en désavantage numérique
81.6%%
59 GA
Début de la zone défensive
34.5%
Informations de l'équipe

Directeur généralAnthony Bourgouin
DivisionAtlantique
ConférenceConference Est
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro11
Équipe Mineure21
Limite contact 32 / 250
Espoirs29


Historique d'équipe

Saison actuelle36-31-7 (79PTS)
Historique0-0-0


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
1Maxime ComtoisX100.00717856727877816450596267596363656800241775,000$
2Denis GurianovXX100.00714399857662617125565763256667646600261850,000$
3Pierre-Olivier JosephX100.00734391747066826325524874256060626800241825,000$
4Brandt Clarke (R)X100.00634182787062697225595465254545636800203863,333$
5Haydn FleuryX100.00784477767769526425524882756465626600271762,500$
Rayé
1Samuel BlaisX100.009959838277548262316055637565676420002711,000,000$
2Zachary SanfordX100.00714392777857776653665567256769642000291800,000$
3Nick CousinsXX100.008464747767629166516159675572756620003011,100,000$
4Nicolas Aube-KubelX100.009257887668627966356359742565666720002711,225,000$
5Noah GregorX100.00885591796959776855605977756464672000251775,000$
6Ethan BearX100.006942878170656164255048692566676020002622,062,500$
MOYENNE D’ÉQUIPE100.0078528478736374663658557044636464410
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
Rayé
MOYENNE D’ÉQUIPE0.000000000000000000
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’équipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du gardien Nom de l’équipeGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Nouveau joueur Poids Taille Non-échange Disponible pour échange Ballotage forcé Contrat Type Salaire actuel Salaire restantPlafond salarial 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 10Link
Brandt ClarkeChicago Wolf (VGK)D202003-02-09Yes185 Lbs6 ft2NoNoNo3Pro & Farm863,333$0$0$No863,333$863,333$Lien
Denis GurianovChicago Wolf (VGK)LW/RW261997-06-07No200 Lbs6 ft3NoNoNo1Pro & Farm850,000$0$0$NoLien / Lien NHL
Ethan BearChicago Wolf (VGK)D261997-06-26No196 Lbs5 ft11NoNoNo2Pro & Farm2,062,500$0$0$No2,062,500$Lien / Lien NHL
Haydn FleuryChicago Wolf (VGK)D271996-07-08No207 Lbs6 ft3NoNoNo1Pro & Farm762,500$0$0$NoLien / Lien NHL
Maxime ComtoisChicago Wolf (VGK)LW241999-08-01No214 Lbs6 ft2NoNoNo1Pro & Farm775,000$0$0$NoLien
Nick CousinsChicago Wolf (VGK)C/LW301993-07-19No183 Lbs5 ft11NoNoNo1Pro & Farm1,100,000$0$0$NoLien / Lien NHL
Nicolas Aube-KubelChicago Wolf (VGK)RW271996-05-09No187 Lbs5 ft11NoNoNo1Pro & Farm1,225,000$0$0$NoLien / Lien NHL
Noah GregorChicago Wolf (VGK)RW251998-07-28No189 Lbs6 ft0NoNoNo1Pro & Farm775,000$0$0$NoLien / Lien NHL
Pierre-Olivier JosephChicago Wolf (VGK)D241999-07-01No185 Lbs6 ft2NoNoNo1Pro & Farm825,000$0$0$NoLien / Lien NHL
Samuel BlaisChicago Wolf (VGK)RW271996-06-17No205 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$0$0$NoLien
Zachary SanfordChicago Wolf (VGK)RW291994-09-11No207 Lbs6 ft4NoNoNo1Pro & Farm800,000$0$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1125.91196 Lbs6 ft11.271,003,485$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
140122
230122
320122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
140122
230122
320122
410122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
160122
240122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
240122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
160122
240122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
240122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
16012260122
24012240122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
160122
240122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
240122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, , ,
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
, , ,
Tirs de pénalité
, , , ,
Gardien
#1 : , #2 :


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
TotalDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1Albany2010010035-21010000012-11000010023-110.25036900163646132315435638650205137118225.00%11281.82%143390947.63%47997449.18%47693950.69%177512721823500890439
2Binghamton21100000330110000003211010000001-120.500369001636461323154356386503487587228.57%10370.00%043390947.63%47997449.18%47693950.69%177512721823500890439
3Bridgeport4010101167-12010000125-32000101042250.625610160016364613461543563865065111552313215.38%15566.67%043390947.63%47997449.18%47693950.69%177512721823500890439
4Charlotte Checkers22000000404110000001011100000030341.00047110216364613261543563865022773811218.18%90100.00%143390947.63%47997449.18%47693950.69%177512721823500890439
5Chicago2020000002-21010000001-11010000001-100.000000001636461325154356386502571467600.00%8275.00%043390947.63%47997449.18%47693950.69%177512721823500890439
6Grand Rapids2020000026-41010000013-21010000013-200.00024600163646132315435638650246501412216.67%10460.00%043390947.63%47997449.18%47693950.69%177512721823500890439
7Hamilton21001000413100010002111100000020241.0004812011636461325154356386502111761313215.38%7185.71%043390947.63%47997449.18%47693950.69%177512721823500890439
8Hartford4220000068-2211000003302110000035-240.500611170016364613471543563865055171772716318.75%26676.92%043390947.63%47997449.18%47693950.69%177512721823500890439
9Hersey2020000004-41010000001-11010000003-300.000000001636461325154356386502066217700.00%6266.67%043390947.63%47997449.18%47693950.69%177512721823500890439
10Hershey21000001642110000005231000000112-130.750612180016364613251543563865023713887457.14%9188.89%043390947.63%47997449.18%47693950.69%177512721823500890439
11Houston21001000413110000002021000100021141.0004812011636461327154356386502316878225.00%40100.00%043390947.63%47997449.18%47693950.69%177512721823500890439
12Iowa200010013301000000112-11000100021130.7503690016364613291543563865024494129111.11%120100.00%043390947.63%47997449.18%47693950.69%177512721823500890439
13Lake Erie2020000014-31010000002-21010000012-100.00012310163646133215435638650492113612400.00%8362.50%043390947.63%47997449.18%47693950.69%177512721823500890439
14Lowell42200000550220000005232020000003-340.50057120116364613591543563865046141593011218.18%17476.47%043390947.63%47997449.18%47693950.69%177512721823500890439
15Manchester21100000220110000001011010000012-120.5002460116364613211543563865020523109222.22%4175.00%043390947.63%47997449.18%47693950.69%177512721823500890439
16Manitoba2010000102-21010000001-11000000101-110.250000001636461331154356386502382213600.00%6183.33%043390947.63%47997449.18%47693950.69%177512721823500890439
17Milwaukee21100000321110000002021010000012-120.5003690116364613291543563865027516116800.00%13192.31%043390947.63%47997449.18%47693950.69%177512721823500890439
18Norfolk21000010413110000003121000001010141.00046100116364613451543563865018495127114.29%5180.00%043390947.63%47997449.18%47693950.69%177512721823500890439
19Peroria211000002201010000012-11100000010120.5002460116364613211543563865025430105120.00%5180.00%043390947.63%47997449.18%47693950.69%177512721823500890439
20Philadelphie42100100752210001001102110000064250.62571320011636461350154356386506517822215320.00%16287.50%043390947.63%47997449.18%47693950.69%177512721823500890439
21Portland21100000211110000002021010000001-120.5002460116364613171543563865015722148225.00%6183.33%043390947.63%47997449.18%47693950.69%177512721823500890439
22Providence211000004401010000023-11100000021120.500481200163646133015435638650221425106116.67%10280.00%043390947.63%47997449.18%47693950.69%177512721823500890439
23Quad City21000010422100000102111100000021141.0004610001636461319154356386502844891218.33%9188.89%043390947.63%47997449.18%47693950.69%177512721823500890439
24Rochester22000000413110000003121100000010141.000481201163646132115435638650255130177228.57%100100.00%043390947.63%47997449.18%47693950.69%177512721823500890439
25Rochester42200000651211000003212110000033040.500611170116364613361543563865058201532118633.33%19194.74%043390947.63%47997449.18%47693950.69%177512721823500890439
26Rockford Icehogs211000003301010000012-11100000021120.500369001636461312154356386502987186233.33%8187.50%043390947.63%47997449.18%47693950.69%177512721823500890439
27Springfield2020000025-31010000012-11010000013-200.000246001636461325154356386504319102116116.67%11554.55%043390947.63%47997449.18%47693950.69%177512721823500890439
28Syracuse21000100431110000003121000010012-130.750481200163646133215435638650266155126233.33%10280.00%043390947.63%47997449.18%47693950.69%177512721823500890439
29Toronto21100000220110000002111010000001-120.50024600163646132515435638650281622107114.29%6183.33%043390947.63%47997449.18%47693950.69%177512721823500890439
30Wilkes Barre42200000871211000005412110000033040.500814220116364613441543563865050172222822418.18%21385.71%043390947.63%47997449.18%47693950.69%177512721823500890439
31Worchester2110000014-31010000004-41100000010120.50011201163646132415435638650321133117114.29%9277.78%043390947.63%47997449.18%47693950.69%177512721823500890439
Total7429310433410510413717150111258526371216032224752-5790.534105194299115163646139171543563865098529529424312875418.82%3205981.56%243390947.63%47997449.18%47693950.69%177512721823500890439
_Since Last GM Reset7429310433410510413717150111258526371216032224752-5790.534105194299115163646139171543563865098529529424312875418.82%3205981.56%243390947.63%47997449.18%47693950.69%177512721823500890439
_Vs Conference42181602222686082111701101403192179011212829-1480.5716812419207163646135241543563865055517317922471633521.47%1903482.11%143390947.63%47997449.18%47693950.69%177512721823500890439
_Vs Division188801111292369530010119145935010101091220.61129558404163646132281543563865023084626105771722.08%771383.12%043390947.63%47997449.18%47693950.69%177512721823500890439

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
7479L11051942999179852952942431115
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
7429314334105104
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
37171511125852
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
37121632224752
Derniers 10 matchs
WLOTWOTL SOWSOL
440002
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2875418.82%3205981.56%2
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
1543563865016364613
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
43390947.63%47997449.18%47693950.69%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
177512721823500890439


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")
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JourMatch Équipe visiteuse Score Équipe locale Score ST OT SO RI Lien
2 - 2024-10-0116Rochester0Chicago Wolf2BWSommaire du match
4 - 2024-10-0334Lowell0Chicago Wolf2BWSommaire du match
7 - 2024-10-0663Philadelphie1Chicago Wolf0BLXSommaire du match
9 - 2024-10-0883Chicago Wolf1Philadelphie3ALSommaire du match
10 - 2024-10-0988Chicago Wolf2Bridgeport1AWXXSommaire du match
12 - 2024-10-11104Hartford2Chicago Wolf1BLSommaire du match
14 - 2024-10-13120Chicago Wolf0Wilkes Barre1ALSommaire du match
15 - 2024-10-14134Wilkes Barre4Chicago Wolf3BLSommaire du match
17 - 2024-10-16149Chicago Wolf0Hartford3ALSommaire du match
18 - 2024-10-17166Philadelphie0Chicago Wolf1BWSommaire du match
20 - 2024-10-19186Wilkes Barre0Chicago Wolf2BWSommaire du match
21 - 2024-10-20191Chicago Wolf0Lowell1ALSommaire du match
23 - 2024-10-22218Hartford1Chicago Wolf2BWSommaire du match
25 - 2024-10-24228Chicago Wolf1Rochester2ALSommaire du match
27 - 2024-10-26249Chicago Wolf2Albany3ALXSommaire du match
28 - 2024-10-27261Toronto1Chicago Wolf2BWSommaire du match
31 - 2024-10-30280Chicago Wolf3Charlotte Checkers0AWSommaire du match
32 - 2024-10-31295Manitoba1Chicago Wolf0BLSommaire du match
34 - 2024-11-02313Chicago Wolf2Providence1AWSommaire du match
36 - 2024-11-04327Providence3Chicago Wolf2BLSommaire du match
38 - 2024-11-06344Chicago Wolf3Wilkes Barre2AWSommaire du match
40 - 2024-11-08358Lake Erie2Chicago Wolf0BLSommaire du match
42 - 2024-11-10374Chicago Wolf2Iowa1AWXSommaire du match
44 - 2024-11-12391Iowa2Chicago Wolf1BLXXSommaire du match
46 - 2024-11-14409Chicago Wolf0Chicago1ALSommaire du match
47 - 2024-11-15422Hamilton1Chicago Wolf2BWXSommaire du match
49 - 2024-11-17440Chicago Wolf2Houston1AWXSommaire du match
51 - 2024-11-19455Rochester1Chicago Wolf3BWSommaire du match
53 - 2024-11-21472Chicago Wolf0Toronto1ALSommaire du match
54 - 2024-11-22485Albany2Chicago Wolf1BLSommaire du match
56 - 2024-11-24498Chicago Wolf2Hamilton0AWSommaire du match
58 - 2024-11-26516Chicago1Chicago Wolf0BLSommaire du match
59 - 2024-11-27530Chicago Wolf2Rochester1AWSommaire du match
60 - 2024-11-28548Grand Rapids3Chicago Wolf1BLSommaire du match
62 - 2024-11-30565Chicago Wolf1Manchester2ALSommaire du match
63 - 2024-12-01580Chicago Wolf1Peroria0AWSommaire du match
65 - 2024-12-03591Lowell2Chicago Wolf3BWSommaire du match
67 - 2024-12-05612Portland0Chicago Wolf2BWSommaire du match
69 - 2024-12-07631Chicago Wolf1Lake Erie2ALSommaire du match
70 - 2024-12-08643Chicago Wolf2Rockford Icehogs1AWSommaire du match
72 - 2024-12-10656Worchester4Chicago Wolf0BLSommaire du match
74 - 2024-12-12674Chicago Wolf1Worchester0AWSommaire du match
75 - 2024-12-13686Hershey2Chicago Wolf5BWSommaire du match
77 - 2024-12-15707Chicago Wolf1Syracuse2ALXSommaire du match
78 - 2024-12-16720Binghamton2Chicago Wolf3BWSommaire du match
81 - 2024-12-19742Springfield2Chicago Wolf1BLSommaire du match
83 - 2024-12-21764Chicago Wolf0Lowell2ALSommaire du match
84 - 2024-12-22775Peroria2Chicago Wolf1BLSommaire du match
86 - 2024-12-24791Chicago Wolf3Hartford2AWSommaire du match
88 - 2024-12-26809Charlotte Checkers0Chicago Wolf1BWSommaire du match
89 - 2024-12-27824Chicago Wolf5Philadelphie1AWSommaire du match
91 - 2024-12-29839Manchester0Chicago Wolf1BWSommaire du match
93 - 2024-12-31858Chicago Wolf0Portland1ALSommaire du match
94 - 2025-01-01871Norfolk1Chicago Wolf3BWSommaire du match
96 - 2025-01-03892Chicago Wolf1Norfolk0AWXXSommaire du match
97 - 2025-01-04903Milwaukee0Chicago Wolf2BWSommaire du match
100 - 2025-01-07923Chicago Wolf1Grand Rapids3ALSommaire du match
101 - 2025-01-08935Quad City1Chicago Wolf2BWXXSommaire du match
103 - 2025-01-10948Chicago Wolf0Hersey3ALSommaire du match
105 - 2025-01-12968Syracuse1Chicago Wolf3BWSommaire du match
107 - 2025-01-14993Hersey1Chicago Wolf0BLSommaire du match
110 - 2025-01-171022Chicago Wolf1Hershey2ALXXSommaire du match
111 - 2025-01-181026Rochester2Chicago Wolf1BLSommaire du match
113 - 2025-01-201047Chicago Wolf1Springfield3ALSommaire du match
114 - 2025-01-211056Chicago Wolf2Bridgeport1AWXSommaire du match
116 - 2025-01-231071Houston0Chicago Wolf2BWSommaire du match
118 - 2025-01-251092Rockford Icehogs2Chicago Wolf1BLSommaire du match
123 - 2025-01-301122Bridgeport2Chicago Wolf1BLXXSommaire du match
125 - 2025-02-011137Chicago Wolf2Quad City1AWSommaire du match
127 - 2025-02-031153Bridgeport3Chicago Wolf1BLSommaire du match
128 - 2025-02-041155Chicago Wolf0Binghamton1ALSommaire du match
129 - 2025-02-051157Chicago Wolf0Manitoba1ALXXSommaire du match
130 - 2025-02-061166Chicago Wolf1Rochester0AWSommaire du match
131 - 2025-02-071178Chicago Wolf1Milwaukee2ALSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
9,546,138$ 11,038,333$ 11,038,333$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 9,546,138$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 83,624$ 0$




Chicago Wolf Leaders statistiques (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 Wolf 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 Wolf 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 Wolf Leaders statistiques (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 Wolf 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