Connexion

Chicago Wolves
GP: 22 | W: 16 | L: 6
GF: 75 | GA: 58 | PP%: 18.18% | PK%: 71.88%
DG: Kevin Fedigan | Morale : 99 | Moyenne d’équipe : 61
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Centre de jeu
Chicago Wolves
16-6-0, 32pts
5
FINAL
3 Tuscon Roadrunners
13-8-0, 26pts
Team Stats
W2SéquenceL2
10-2-0Fiche domicile8-3-0
6-4-0Fiche domicile5-5-0
9-0-1Derniers 10 matchs5-4-1
3.41Buts par match 3.24
2.64Buts contre par match 2.52
18.18%Pourcentage en avantage numérique25.71%
71.88%Pourcentage en désavantage numérique76.00%
Tuscon Roadrunners
13-8-0, 26pts
2
FINAL
4 Chicago Wolves
16-6-0, 32pts
Team Stats
L2SéquenceW2
8-3-0Fiche domicile10-2-0
5-5-0Fiche domicile6-4-0
5-4-1Derniers 10 matchs9-0-1
3.24Buts par match 3.41
2.52Buts contre par match 2.64
25.71%Pourcentage en avantage numérique18.18%
76.00%Pourcentage en désavantage numérique71.88%
Meneurs d'équipe
Buts
Aliaksei Protas
15
Passes
Aliaksei Protas
14
Points
Aliaksei Protas
29
Nils LundkvistPlus/Moins
Nils Lundkvist
23
Victoires
Adam Huska
16
Pourcentage d’arrêts
Adam Huska
0.92

Statistiques d’équipe
Buts pour
75
3.41 GFG
Tirs pour
801
36.41 Avg
Pourcentage en avantage numérique
18.2%
6 GF
Début de zone offensive
39.1%
Buts contre
58
2.64 GAA
Tirs contre
715
32.50 Avg
Pourcentage en désavantage numérique
71.9%%
9 GA
Début de la zone défensive
37.3%
Informations de l'équipe

Directeur généralKevin Fedigan
DivisionWest Division
ConférenceWestern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison1,650


Informations de la formation

Équipe Pro37
Équipe Mineure20
Limite contact 57 / 65
Espoirs51


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
1Ryan Reaves0X100.009074717084789272496965696988780826903611,700,000$
2Aliaksei Protas0XX100.00694787719382737356706467695650089660232789,167$
3Ondrej Kase0X100.005943777576837570436464677077670856502831,100,000$
4Justin Danforth0X100.00624378747383656958626464695750087630303975,000$
5Dylan Guenther (R)0X100.00604075717378646940676562695150087620201775,000$
6Cody Eakin0X100.00503586876287836280505562557567089620324900,000$
7Colton Sceviour0XXX100.00645975826074995955475557558368087610344850,000$
8Dmitrij Jaskin0XXX100.00883586857167655555455069557374089610304790,000$
9Michael Ferland0XX100.008143818571676567555654575570640906103113,500,000$
10Spencer Smallman (R)0XX100.00645167696466666242595664625450089590272775,000$
11Max Willman0X100.00604771686572666541605760645651046590284790,000$
12Kyle Clifford0X100.00634959627172746341595659607264089590324850,000$
13Remi Elie0X100.00503595826867706250455055556866046570284775,000$
14Robin Kovacs (R)0XX100.00665566626662695550555556555050047550271775,000$
15Nils Lundkvist (R)0X100.00655079787984737540686769735650089670234925,000$
16Sebastian Aho (D)0X100.00583587885385936340635866406568089660273825,000$
17Nick Perbix (R)0X100.00704873727678697240686371695350088650251775,000$
18Akito Hirose (R)0X100.005740717170806065406260656651500896102444,350,000$
19Michael Kesselring (R)0X100.00665764696763636640586068655150086600232925,000$
20Mitchell Vande Sompel (R)0X100.00604767696466656140605466615450046590261775,000$
21Parker Wotherspoon (R)0X100.00615463706364626140585268615350046590262775,000$
22Jacob Moverare (R)0X100.00614865686563636240595466615250089590252775,000$
23Jake Massie (R)0X100.00594469686262625940565465605350046580261775,000$
24Nikolai Knyzhov (R)0X100.006240685968605956405453605652500475602541,250,000$
Rayé
1Jakob Pelletier (R)0X100.00644578756979646842646365695150080620221775,000$
2Casey Bailey0X100.00643575766466685347495448526048026550324775,000$
3Michael Chaput0X100.00573575706370695453545350456048025550314775,000$
4Sebastian Collberg0X100.00686773695259615565555059504444026540294775,000$
5Andrew Miller0X100.00523575745868695254525153476048026540354775,000$
6Michael Spacek (R)0X100.00643575715465685055554955466048026540261775,000$
7Maxim Cajkovic (R)0XX100.00534652565453525240505151525050026500232850,833$
MOYENNE D’ÉQUIPE100.0063467472677169624758576259605506660
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
1Adam Huska (R)0100.0082705696877575757587506369087750261775,000$
2Veini Vehvilainen (R)0100.0075757585806771667070487272053710261925,000$
Rayé
1Lukas Dostal (R)0100.0078717272757574747675745651084700231822,500$
2Jonathan Bernier0100.00717068656566656767686690800346703512,500,000$
3Ivan Prosvetov (R)0100.0072646863686970686969585250034640241775,000$
4Filip Lindberg (R)0100.0055555555555555555555555050034530242925,000$
MOYENNE D’ÉQUIPE100.007268667372686868697159646205467
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
1Aliaksei ProtasChicago Wolves (CAR)C/RW22151429410103640115265513.04%1448822.21314728011030051.17%6391311401.1901101222
2Ryan ReavesChicago Wolves (CAR)RW2210132354620453390264911.11%1240518.45000290110261155.00%201813001.1300022223
3Ondrej KaseChicago Wolves (CAR)RW229112015175363075233612.00%938717.61011021000002050.00%121910001.0300010212
4Cody EakinChicago Wolves (CAR)C22613191600353143102613.95%540118.25000021101291065.56%270156000.9500000211
5Dylan GuentherChicago Wolves (CAR)RW22611172161034277527618.00%1448021.85145128000003037.50%241512000.7100020110
6Michael FerlandChicago Wolves (CAR)LW/RW22107171675422065173515.38%638917.72011122000000138.46%13156000.8700100021
7Nick PerbixChicago Wolves (CAR)D22111122217531304010152.50%2855225.13112230000023100%0922000.4300001011
8Nils LundkvistChicago Wolves (CAR)D22110112311524365020102.00%3655625.31011331000126100%02719000.4000001011
9Jakob PelletierChicago Wolves (CAR)LW13459-37527184713328.51%827020.78011119000051133.33%18158000.6700001102
10Colton SceviourChicago Wolves (CAR)C/LW/RW22257-110101923489214.17%829813.55000120002131050.00%16876000.4700011100
11Sebastian Aho (D)Chicago Wolves (CAR)D22167-6009202513154.00%1140618.4710122100000000%01311000.3400000010
12Jacob MoverareChicago Wolves (CAR)D2215651610152016426.25%1838217.3900000000015000%0213000.3100002000
13Kyle CliffordChicago Wolves (CAR)LW22246-3402212269207.69%126011.8400000000000061.54%1348000.4600000000
14Justin DanforthChicago Wolves (CAR)RW223364201261681018.75%61848.3600000000002050.00%1022000.6500000010
15Spencer SmallmanChicago Wolves (CAR)C/LW223252751014131423.08%31757.9900001101172033.33%636000.5700100100
16Akito HiroseChicago Wolves (CAR)D22022-8601822161090%2441018.67000121000012000%0310000.1000000000
17Dmitrij JaskinChicago Wolves (CAR)C/LW/RW221122001918147117.14%424010.91000000000281060.00%12074000.1700000001
18Michael KesselringChicago Wolves (CAR)D220114161019232711120%1238117.3300000000016000%01014000.0500020000
19Jake MassieChicago Wolves (CAR)D22000000000000%0100.460000000002000%00000000000000
20Robin KovacsChicago Wolves (CAR)LW/RW22000-100200000%0170.780000100001000%00000000000000
21Mitchell Vande SompelChicago Wolves (CAR)D22000000000000%000.030000000000000%00000000000000
22Max WillmanChicago Wolves (CAR)C22000000100000%000.030000000000000%00000000000000
23Remi ElieChicago Wolves (CAR)LW22000000000000%000.010000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne49775124199981921004564238012444239.36%219670113.486101621264224619116354.23%1313197181400.5901389121314
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
1Adam HuskaChicago Wolves (CAR)2216330.9202.55131900567023512000220332
2Veini VehvilainenChicago Wolves (CAR)20000.8464.14290021390000022000
Statistiques d’équipe totales ou en moyenne2416330.9192.58134800587153602002222332


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 Plafond 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
Adam HuskaChicago Wolves (CAR)G265/12/1997Yes214 Lbs6 ft4NoNoN/ANoNo1Pro & Farm775,000$0$0$No------------------Lien
Akito Hirose (contrat à 1 volet)Chicago Wolves (CAR)D244/9/1999Yes170 Lbs6 ft0NoNoN/ANoNo4Pro & Farm4,350,000$4,350,000$0$No4,350,000$4,350,000$4,350,000$------NoNoNo------
Aliaksei ProtasChicago Wolves (CAR)C/RW231/6/2001No225 Lbs6 ft6NoNoN/ANoNo2Pro & Farm789,167$0$0$No789,167$--------No--------
Andrew MillerChicago Wolves (CAR)RW359/18/1988No181 Lbs5 ft10NoNoN/ANoNo4Pro & Farm775,000$0$0$No775,000$775,000$775,000$------NoNoNo------Lien
Casey BaileyChicago Wolves (CAR)C3210/27/1991No195 Lbs6 ft3NoNoN/ANoNo4Pro & Farm775,000$0$0$No775,000$775,000$775,000$------NoNoNo------Lien
Cody EakinChicago Wolves (CAR)C325/24/1991No196 Lbs6 ft0NoNoN/ANoNo4Pro & Farm900,000$0$0$No900,000$900,000$900,000$------NoNoNo------Lien
Colton SceviourChicago Wolves (CAR)C/LW/RW344/20/1989No190 Lbs6 ft0NoNoN/ANoNo4Pro & Farm850,000$0$0$No850,000$850,000$850,000$------NoNoNo------Lien
Dmitrij JaskinChicago Wolves (CAR)C/LW/RW303/23/1993No216 Lbs6 ft2NoNoN/ANoNo4Pro & Farm790,000$0$0$No790,000$790,000$790,000$------NoNoNo------Lien
Dylan GuentherChicago Wolves (CAR)RW204/10/2003Yes175 Lbs6 ft2NoNoN/ANoNo1Pro & Farm775,000$0$0$No------------------
Filip LindbergChicago Wolves (CAR)G241/31/1999Yes180 Lbs6 ft0NoNoN/ANoNo2Pro & Farm925,000$0$0$No925,000$--------No--------Lien
Ivan ProsvetovChicago Wolves (CAR)G243/5/1999Yes174 Lbs6 ft5NoNoN/ANoNo1Pro & Farm775,000$0$0$No------------------
Jacob MoverareChicago Wolves (CAR)D258/31/1998Yes198 Lbs6 ft3NoNoN/ANoNo2Pro & Farm775,000$0$0$No775,000$--------No--------
Jake MassieChicago Wolves (CAR)D261/21/1997 4:24:13 PMYes179 Lbs6 ft1NoNoN/ANoNo1Pro & Farm775,000$0$0$No------------------
Jakob PelletierChicago Wolves (CAR)LW223/7/2001Yes170 Lbs5 ft9NoNoN/ANoNo1Pro & Farm775,000$0$0$No------------------
Jonathan BernierChicago Wolves (CAR)G358/7/1988No185 Lbs6 ft0NoNoN/ANoNo1Pro & Farm2,500,000$0$0$No------------------Lien NHL
Justin DanforthChicago Wolves (CAR)RW303/15/1993No190 Lbs5 ft9NoNoN/ANoNo3Pro & Farm975,000$0$0$No975,000$975,000$-------NoNo-------Lien NHL
Kyle CliffordChicago Wolves (CAR)LW321/13/1991No212 Lbs6 ft2NoNoN/ANoNo4Pro & Farm850,000$0$0$No850,000$850,000$850,000$------NoNoNo------
Lukas DostalChicago Wolves (CAR)G236/22/2000Yes174 Lbs6 ft2NoNoN/ANoNo1Pro & Farm822,500$0$0$No------------------Lien NHL
Max WillmanChicago Wolves (CAR)C282/13/1995No183 Lbs6 ft0NoNoN/ANoNo4Pro & Farm790,000$0$0$No790,000$790,000$790,000$------NoNoNo------
Maxim CajkovicChicago Wolves (CAR)LW/RW231/3/2001Yes185 Lbs5 ft11NoNoN/ANoNo2Pro & Farm850,833$0$0$No850,833$--------No--------
Michael ChaputChicago Wolves (CAR)C314/9/1992No199 Lbs6 ft2NoNoN/ANoNo4Pro & Farm775,000$0$0$No775,000$775,000$775,000$------NoNoNo------Lien
Michael Ferland (contrat à 1 volet)Chicago Wolves (CAR)LW/RW314/20/1992No215 Lbs6 ft0NoNoN/ANoNo1Pro & Farm3,500,000$3,500,000$0$No------------------
Michael KesselringChicago Wolves (CAR)D231/13/2000Yes190 Lbs6 ft4NoNoN/ANoNo2Pro & Farm925,000$0$0$No925,000$--------No--------
Michael SpacekChicago Wolves (CAR)C264/9/1997Yes187 Lbs5 ft11NoNoN/ANoNo1Pro & Farm775,000$0$0$No------------------Lien
Mitchell Vande SompelChicago Wolves (CAR)D262/11/1997Yes198 Lbs5 ft11NoNoN/ANoNo1Pro & Farm775,000$0$0$No------------------
Nick PerbixChicago Wolves (CAR)D256/15/1998Yes191 Lbs6 ft2NoNoN/ANoNo1Pro & Farm775,000$0$0$No------------------
Nikolai KnyzhovChicago Wolves (CAR)D253/20/1998Yes218 Lbs6 ft2NoNoN/ANoNo4Pro & Farm1,250,000$0$0$No1,250,000$1,250,000$1,250,000$------NoNoNo------
Nils LundkvistChicago Wolves (CAR)D237/27/2000Yes190 Lbs5 ft11NoNoN/ANoNo4Pro & Farm925,000$0$0$No925,000$925,000$925,000$------NoNoNo------Lien NHL
Ondrej KaseChicago Wolves (CAR)RW2811/8/1995No187 Lbs6 ft0NoNoN/ANoNo3Pro & Farm1,100,000$0$0$No1,100,000$1,100,000$-------NoNo-------Lien NHL
Parker WotherspoonChicago Wolves (CAR)D268/24/1997Yes181 Lbs6 ft1NoNoN/ANoNo2Pro & Farm775,000$0$0$No775,000$--------No--------Lien NHL
Remi ElieChicago Wolves (CAR)LW284/16/1995No215 Lbs6 ft1NoNoN/ANoNo4Pro & Farm775,000$0$0$No775,000$775,000$775,000$------NoNoNo------Lien
Robin KovacsChicago Wolves (CAR)LW/RW2711/16/1996Yes176 Lbs6 ft0NoNoN/ANoNo1Pro & Farm775,000$0$0$No------------------
Ryan ReavesChicago Wolves (CAR)RW361/20/1987No225 Lbs6 ft2NoNoN/ANoNo1Pro & Farm1,700,000$0$0$No------------------Lien NHL
Sebastian Aho (D)Chicago Wolves (CAR)D272/17/1996No184 Lbs5 ft10NoNoN/ANoNo3Pro & Farm825,000$0$0$No825,000$825,000$-------NoNo-------Lien
Sebastian CollbergChicago Wolves (CAR)RW292/22/1994No186 Lbs5 ft11NoNoN/ANoNo4Pro & Farm775,000$0$0$No775,000$775,000$775,000$------NoNoNo------
Spencer SmallmanChicago Wolves (CAR)C/LW279/3/1996Yes198 Lbs6 ft1NoNoN/ANoNo2Pro & Farm775,000$0$0$No775,000$--------No--------
Veini VehvilainenChicago Wolves (CAR)G262/13/1997Yes181 Lbs6 ft0NoNoN/ANoNo1Pro & Farm925,000$0$0$No------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3727.35192 Lbs6 ft12.411,073,446$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Justin DanforthAliaksei ProtasDylan Guenther40122
2Michael FerlandCody EakinOndrej Kase30122
3Kyle CliffordColton SceviourRyan Reaves20122
4Spencer SmallmanDmitrij JaskinRyan Reaves10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nick PerbixNils Lundkvist40122
2Sebastian Aho (D)Akito Hirose30122
3Michael KesselringJacob Moverare20122
4Michael KesselringJacob Moverare10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Ryan ReavesAliaksei ProtasDylan Guenther60122
2Michael FerlandCody EakinOndrej Kase40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nick PerbixNils Lundkvist60122
2Sebastian Aho (D)Akito Hirose40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Dmitrij JaskinRyan Reaves60122
2Cody EakinAliaksei Protas40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nick PerbixNils Lundkvist60122
2Michael KesselringJacob Moverare40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Dmitrij Jaskin60122Nick PerbixNils Lundkvist60122
2Cody Eakin40122Michael KesselringJacob Moverare40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Dmitrij JaskinMichael Ferland60122
2Colton SceviourRyan Reaves40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Sebastian Aho (D)Nick Perbix60122
2Akito HiroseNils Lundkvist40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ryan ReavesAliaksei ProtasDylan GuentherNick PerbixNils Lundkvist
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ryan ReavesDmitrij JaskinAliaksei ProtasNick PerbixNils Lundkvist
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Dmitrij Jaskin, Dylan Guenther, Spencer SmallmanMichael Ferland, Ryan ReavesColton Sceviour
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Sebastian Aho (D), Jacob Moverare, Nick PerbixSebastian Aho (D)Akito Hirose, Nils Lundkvist
Tirs de pénalité
Nils Lundkvist, Aliaksei Protas, Dylan Guenther, Dmitrij Jaskin, Ryan Reaves
Gardien
#1 : Adam Huska, #2 : Veini Vehvilainen
Lignes d’attaque personnalisées en prolongation
Dylan Guenther, Colton Sceviour, Justin Danforth, Michael Ferland, Cody Eakin, Dmitrij Jaskin, Dmitrij Jaskin, Ryan Reaves, Spencer Smallman, Aliaksei Protas, Ondrej Kase
Lignes de défense personnalisées en prolongation
Sebastian Aho (D), Akito Hirose, Nils Lundkvist, Nick Perbix, Michael Kesselring


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
1Milwaukee Admirals743000002523243100000191543120000068-280.571254267001229322272211326244202397010015614321.43%10460.00%127851454.09%26549054.08%16930954.69%488276437202424215
2Toronto Marlies64200000181533210000012843210000067-180.6671830480012293221822113262442014642401478225.00%10190.00%027851454.09%26549054.08%16930954.69%488276437202424215
3Tuscon Roadrunners54100000191363300000011652110000087180.800193251001229322204211326244201996717836116.67%7271.43%127851454.09%26549054.08%16930954.69%488276437202424215
4Utica Comets440000001376220000006332200000074381.00013203300122932214321132624420131403570500.00%5260.00%027851454.09%26549054.08%16930954.69%488276437202424215
Total2216600000755817121020000048321610640000027261320.727751241990012293228012113262442071521919245633618.18%32971.88%227851454.09%26549054.08%16930954.69%488276437202424215
_Since Last GM Reset2216600000755817121020000048321610640000027261320.727751241990012293228012113262442071521919245633618.18%32971.88%227851454.09%26549054.08%16930954.69%488276437202424215
_Vs Conference1712500000564511972000003726118530000019190240.70656921480012293225972113262442051615217537327518.52%25772.00%127851454.09%26549054.08%16930954.69%488276437202424215

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2232W27512419980171521919245600
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
2216600007558
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
1210200004832
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
106400002726
Derniers 10 matchs
WLOTWOTL SOWSOL
900100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
33618.18%32971.88%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
211326244201229322
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
27851454.09%26549054.08%16930954.69%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
488276437202424215


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
16Milwaukee Admirals5Chicago Wolves7BWSommaire du match
214Milwaukee Admirals2Chicago Wolves4BWSommaire du match
322Chicago Wolves2Milwaukee Admirals5ALSommaire du match
430Chicago Wolves1Milwaukee Admirals2ALSommaire du match
538Milwaukee Admirals4Chicago Wolves3BLXSommaire du match
646Chicago Wolves3Milwaukee Admirals1AWSommaire du match
754Milwaukee Admirals4Chicago Wolves5BWXSommaire du match
860Toronto Marlies3Chicago Wolves2BLXSommaire du match
964Toronto Marlies2Chicago Wolves5BWSommaire du match
1068Chicago Wolves1Toronto Marlies5ALSommaire du match
1172Chicago Wolves3Toronto Marlies1AWSommaire du match
1276Toronto Marlies3Chicago Wolves5BWSommaire du match
1380Chicago Wolves2Toronto Marlies1AWSommaire du match
1586Chicago Wolves4Utica Comets3AWXSommaire du match
1688Chicago Wolves3Utica Comets1AWSommaire du match
1790Utica Comets2Chicago Wolves4BWSommaire du match
1892Utica Comets1Chicago Wolves2BWSommaire du match
2299Tuscon Roadrunners1Chicago Wolves3BWSommaire du match
23100Tuscon Roadrunners3Chicago Wolves4BWSommaire du match
24101Chicago Wolves3Tuscon Roadrunners4ALXSommaire du match
25102Chicago Wolves5Tuscon Roadrunners3AWSommaire du match
26103Tuscon Roadrunners2Chicago Wolves4BWSommaire 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
29 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 3,186,750$ 3,158,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

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




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