CHICAGO Wolves

GP: 75 | W: 26 | L: 48 | OTL: 1 | P: 53
GF: 259 | GA: 372 | PP%: 15.29% | PK%: 71.30%
DG: Lukas Tremblay | Morale : 87 | Moyenne d'Équipe : 58
Prochain matchs #976 vs BROOKLYN Wolfpack
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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 SP
1Kyle Baun0X100.006943716080588855505753605350504281620
2Shane Prince0XX100.005941826967773558305959596455536482600
3Alexander Volkov0X100.005189597076505070506363586350504482600
4Rourke Chartier0X100.005435726870585668705960556151505482600
5Blaine Byron0X100.005089717069505070506363516350504382590
6Taylor Beck0XX100.005135767176484262305857565764615582590
7Justin Auger0X100.007089725599505055505555505550505977580
8Alexander Khokhlachev0XX100.004535807561494162425958596558497982570
9Jake Dotchin0X100.007150636385616063305552636354514782610
10Xavier Ouellet0X100.005650726874595968305449586056526981600
11Joe Hicketts0X100.005335626664555566304844575551504482550
12Mark Friedman0X100.005035576469505064304843505350506282530
Rayé
MOYENNE D'ÉQUIPE100.00575270677455536341575556595351558159
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 SP
1Stephon Williams (R)100.00455265776047484949505560497169490
Rayé
MOYENNE D'ÉQUIPE100.0045526577604748494950556049716949
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ralph Krueger66666666777752CAN60381,800$


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
1Shane PrinceCHICAGO Wolves (STL)C/LW58295584431804997319902369.09%34141424.39369291232029768149.13%80800011.1900000563
2Rourke ChartierCHICAGO Wolves (STL)C594140813380431193118122013.18%16125321.24088261140004616066.64%114800061.2900000543
3Alexander VolkovCHICAGO Wolves (STL)LW5932407236195601053148224010.19%13124521.11123261020001535156.94%14400011.1600100443
4Taylor BeckCHICAGO Wolves (STL)LW/RW5928427025402471283691889.89%12116319.73871526113000052048.44%6400011.2000000122
5Alexander KhokhlachevCHICAGO Wolves (STL)C/LW5917365316601366244721896.97%16103617.5812311481012260047.66%10700001.0200000102
6Blaine ByronCHICAGO Wolves (STL)C5924285291204080252582039.52%19107318.2023515520001312058.84%80900020.9700000402
7Jake DotchinCHICAGO Wolves (STL)D58113849213001155390386912.22%49137423.71123151060110620033.33%600000.7100000113
8Kyle BaunCHICAGO Wolves (STL)RW582029497360143611885011610.64%18131322.642359990112611148.07%23300010.7500000221
9Joe HickettsCHICAGO Wolves (STL)D5910344416220644292225910.87%58130922.20336191030000610045.45%1100000.6700000112
10Xavier OuelletCHICAGO Wolves (STL)D58835431824020399832468.16%57135523.3734742102000263010.00%100000.6300000010
11Dominic TurgeonST-LOUIS BluesC59122941421206670134321088.96%15107018.140116520111622061.26%75900000.7700000121
12Justin AugerCHICAGO Wolves (STL)RW591720372347510434138378312.32%9113519.2414512113000000054.41%6800010.6500010020
13Mark FriedmanCHICAGO Wolves (STL)D5921517158048204616384.35%43125721.32101208901106000100.00%100000.2700000001
Stats d'équipe Total ou en Moyenne763251441692304246107898572509679179510.00%3591600520.9826457125612233472262726458.28%4159000130.8600110252523
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
1Stephon WilliamsCHICAGO Wolves (STL)59263210.8713.0334060717213300300.0000590001
Stats d'équipe Total ou en Moyenne59263210.8713.0334060717213300300.0000590001


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Alexander KhokhlachevCHICAGO Wolves (STL)C/LW251993-09-09No82 Kg178 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$No
Alexander VolkovCHICAGO Wolves (STL)LW221997-08-02No87 Kg185 CMNoNoNo1Avec RestrictionPro & Farm735,000$0$0$NoLien
Blaine ByronCHICAGO Wolves (STL)C241995-02-21No78 Kg183 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Jake DotchinCHICAGO Wolves (STL)D251994-03-24No95 Kg191 CMNoNoNo1Avec RestrictionPro & Farm750,000$0$0$NoLien
Joe HickettsCHICAGO Wolves (STL)D231996-05-04No82 Kg173 CMNoNoNo4Avec RestrictionPro & Farm750,000$0$0$NoLien
Justin AugerCHICAGO Wolves (STL)RW251994-05-14No105 Kg198 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Kyle BaunCHICAGO Wolves (STL)RW271992-05-04No95 Kg188 CMNoNoNo1Avec RestrictionPro & Farm750,000$0$0$NoLien
Mark FriedmanCHICAGO Wolves (STL)D231995-12-25No84 Kg180 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Rourke ChartierCHICAGO Wolves (STL)C231996-04-03No86 Kg180 CMNoNoNo1Avec RestrictionPro & Farm735,000$0$0$NoLien
Shane PrinceCHICAGO Wolves (STL)C/LW261992-11-16No88 Kg180 CMNoNoNo1Avec RestrictionPro & Farm700,000$0$0$NoLien
Stephon WilliamsCHICAGO Wolves (STL)G261993-04-28Yes89 Kg191 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$No
Taylor BeckCHICAGO Wolves (STL)LW/RW281991-05-13No92 Kg188 CMNoNoNo1Sans RestrictionPro & Farm750,000$0$0$No
Xavier OuelletCHICAGO Wolves (STL)D261993-07-29No89 Kg183 CMNoNoNo1Avec RestrictionPro & Farm750,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1324.8589 Kg185 CM1.77743,846$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Alexander VolkovShane PrinceKyle Baun31122
2Taylor BeckRourke ChartierJustin Auger26122
3Alexander KhokhlachevBlaine ByronKyle Baun23122
4Shane PrinceAlexander Volkov20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jake DotchinXavier Ouellet31122
2Joe HickettsMark Friedman26122
3Jake DotchinXavier Ouellet23122
4Joe HickettsMark Friedman20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Alexander VolkovShane PrinceKyle Baun55122
2Taylor BeckRourke ChartierJustin Auger45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jake DotchinXavier Ouellet55122
2Joe HickettsMark Friedman45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Kyle BaunShane Prince55122
2Alexander VolkovRourke Chartier45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jake DotchinXavier Ouellet55122
2Joe HickettsMark Friedman45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Kyle Baun55122Jake DotchinXavier Ouellet55122
2Shane Prince45122Joe HickettsMark Friedman45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Kyle BaunShane Prince55122
2Alexander VolkovRourke Chartier45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jake DotchinXavier Ouellet55122
2Joe HickettsMark Friedman45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Alexander VolkovShane PrinceKyle BaunJake DotchinXavier Ouellet
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Alexander VolkovShane PrinceKyle BaunJake DotchinXavier Ouellet
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Blaine Byron, Alexander Khokhlachev, Blaine Byron, Alexander Khokhlachev
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jake Dotchin, Xavier Ouellet, Joe HickettsJake DotchinXavier Ouellet, Joe Hicketts
Tirs de Pénalité
Kyle Baun, Shane Prince, Alexander Volkov, Rourke Chartier, Blaine Byron
Gardien
#1 : Stephon Williams, #2 :
Lignes d'Attaque Perso. en Prol.
Kyle Baun, Shane Prince, Alexander Volkov, Rourke Chartier, Blaine Byron, Taylor Beck, Taylor Beck, Justin Auger, Alexander Khokhlachev, ,
Lignes de Défense Perso. en Prol.
Jake Dotchin, Xavier Ouellet, Joe Hicketts, Mark Friedman,


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
LigueDomicileVisiteur
# 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
1BELLEVILLE Senators220000001631311000000523110000001111041.0001629450012671593134851899917338154352150.00%000.00%01221205659.39%724177940.70%627125450.00%183014071893425782388
2BRIDGEPORT Sound Tigers41300000927-1820200000511-621100000416-1220.25091726001267159383851899917316948105116637.50%5180.00%01221205659.39%724177940.70%627125450.00%183014071893425782388
3BROOKLYN Wolfpack330000003203222000000240241100000080861.00032589003126715932758518999173174429100.00%20100.00%11221205659.39%724177940.70%627125450.00%183014071893425782388
4CLEVELAND Monsters5410000046123432100000241014220000002222080.800468613201126715933628518999173119314602150.00%20100.00%01221205659.39%724177940.70%627125450.00%183014071893425782388
5COLORADO Eagles40400000514-92020000039-62020000025-300.000581300126715938985189991731193634541700.00%14378.57%01221205659.39%724177940.70%627125450.00%183014071893425782388
6CORNWALL Aces2200000022220110000001101111000000112941.00022396101126715931308518999173224720100.00%10100.00%01221205659.39%724177940.70%627125450.00%183014071893425782388
7HERSEY Bears503020001232-2020200000319-1630102000913-440.400122032001267159310485189991731775022618225.00%11554.55%21221205659.39%724177940.70%627125450.00%183014071893425782388
8HOLLYWOOD Oscar220000002231911000000132111100000091841.00022355700126715932018518999173225422000.00%20100.00%01221205659.39%724177940.70%627125450.00%183014071893425782388
9IOWA Wild2110000069-3110000004311010000026-420.500611170012671593808518999173552412226116.67%6433.33%01221205659.39%724177940.70%627125450.00%183014071893425782388
10LAVAL Rockets50500000622-162020000019-830300000513-800.000611170012671593105851899917316938246913215.38%9455.56%01221205659.39%724177940.70%627125450.00%183014071893425782388
11LEHIGH VALLEY Phantoms2010100057-2100010003211010000025-320.500510150012671593448518999173621863310220.00%3233.33%01221205659.39%724177940.70%627125450.00%183014071893425782388
12MANITOBA Moose20200000410-61010000025-31010000025-300.00047110012671593788518999173681229361417.14%60100.00%01221205659.39%724177940.70%627125450.00%183014071893425782388
13MILWAUKEE Admirals30300000631-2510100000410-620200000221-1900.0006111700126715935385189991731793362310220.00%3166.67%01221205659.39%724177940.70%627125450.00%183014071893425782388
14MONT-LAURIER Sommet1010000024-2000000000001010000024-200.0002350012671593298518999173249212400.00%10100.00%01221205659.39%724177940.70%627125450.00%183014071893425782388
15PROVIDENCE Bruins41200100161332020000039-621000100134930.3751630460012671593163851899917311031265417423.53%13469.23%01221205659.39%724177940.70%627125450.00%183014071893425782388
16PV Sharapovas31200000515-1020200000213-111100000032120.33359140012671593428518999173136456276116.67%30100.00%01221205659.39%724177940.70%627125450.00%183014071893425782388
17ROCKFORD IceHogs40400000427-2320200000212-1020200000215-1300.00047110012671593678518999173187506351119.09%3166.67%01221205659.39%724177940.70%627125450.00%183014071893425782388
18SAN DIEGO Gulls4400000017413220000008172200000093681.000173249011267159330785189991732882812150.00%10100.00%01221205659.39%724177940.70%627125450.00%183014071893425782388
19STOCKTON Flames20200000219-171010000026-410100000013-1300.000235001267159319851899917312739818100.00%4175.00%01221205659.39%724177940.70%627125450.00%183014071893425782388
20SYRACUSE Crunch20200000117-1610100000013-131010000014-300.0001230012671593298518999173135361014700.00%40100.00%01221205659.39%724177940.70%627125450.00%183014071893425782388
21TORONTO Marlies20200000025-2510100000014-1410100000011-1100.00000000126715939851899917319947013000.00%000.00%01221205659.39%724177940.70%627125450.00%183014071893425782388
22TUSCON Roadrunners41300000322-1920200000117-162110000025-320.2503690012671593858518999173170471658700.00%8362.50%01221205659.39%724177940.70%627125450.00%183014071893425782388
Total75234803100259372-11337112501000135186-5138122302100124186-62530.35325946772607126715932670851899917328327542588991702615.29%1083171.30%31221205659.39%724177940.70%627125450.00%183014071893425782388
24UTICA Comets40400000622-162020000058-320200000114-1300.0006111700126715936685189991732205316401516.67%7271.43%01221205659.39%724177940.70%627125450.00%183014071893425782388
25VICTORIAVILLE Tigres20200000025-2510100000011-1110100000014-1400.00000000126715931485189991732235807000.00%000.00%01221205659.39%724177940.70%627125450.00%183014071893425782388
26WILKIES-BARRIE Penguins21100000127511000000100101010000027-520.500122234011267159310285189991735713025000.00%000.00%01221205659.39%724177940.70%627125450.00%183014071893425782388
_Since Last GM Reset75234803100259372-11337112501000135186-5138122302100124186-62530.35325946772607126715932670851899917328327542588991702615.29%1083171.30%31221205659.39%724177940.70%627125450.00%183014071893425782388
_Vs Conference49143202100162226-64246180000083115-32258140210079111-32330.33716229745905126715931759851899917316644291706151192016.81%782469.23%31221205659.39%724177940.70%627125450.00%183014071893425782388
_Vs Division175190000025116-91829000001550-359310000001066-56100.29425446900126715933818518999173831213871775858.62%32971.88%01221205659.39%724177940.70%627125450.00%183014071893425782388

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7553W32594677262670283275425889907
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7523483100259372
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3711251000135186
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3812232100124186
Derniers 10 Matchs
WLOTWOTL SOWSOL
640000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1702615.29%1083171.30%3
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
851899917312671593
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
1221205659.39%724177940.70%627125450.00%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
183014071893425782388


Derniers Match 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
1 - 2019-07-301CHICAGO Wolves2TUSCON Roadrunners1WSommaire du Match
2 - 2019-07-3122COLORADO Eagles5CHICAGO Wolves1LSommaire du Match
3 - 2019-08-0131CHICAGO Wolves11PROVIDENCE Bruins1WR3Sommaire du Match
4 - 2019-08-0242CHICAGO Wolves2LAVAL Rockets3LSommaire du Match
5 - 2019-08-0354CLEVELAND Monsters0CHICAGO Wolves10WSommaire du Match
6 - 2019-08-0459CHICAGO Wolves2HERSEY Bears8LSommaire du Match
8 - 2019-08-0677HERSEY Bears10CHICAGO Wolves3LSommaire du Match
10 - 2019-08-08101PV Sharapovas3CHICAGO Wolves2LSommaire du Match
12 - 2019-08-10117UTICA Comets4CHICAGO Wolves3LSommaire du Match
13 - 2019-08-11130CHICAGO Wolves0UTICA Comets11LSommaire du Match
14 - 2019-08-12135ROCKFORD IceHogs7CHICAGO Wolves0LSommaire du Match
16 - 2019-08-14156CHICAGO Wolves0MILWAUKEE Admirals12LSommaire du Match
17 - 2019-08-15165CHICAGO Wolves0BRIDGEPORT Sound Tigers13LSommaire du Match
18 - 2019-08-16171CLEVELAND Monsters9CHICAGO Wolves5LSommaire du Match
20 - 2019-08-18194TUSCON Roadrunners14CHICAGO Wolves1LSommaire du Match
22 - 2019-08-20208CHICAGO Wolves2WILKIES-BARRIE Penguins7LSommaire du Match
23 - 2019-08-21220TORONTO Marlies14CHICAGO Wolves0LSommaire du Match
24 - 2019-08-22233SYRACUSE Crunch13CHICAGO Wolves0LSommaire du Match
25 - 2019-08-23246CHICAGO Wolves0TORONTO Marlies11LSommaire du Match
26 - 2019-08-24259CHICAGO Wolves0VICTORIAVILLE Tigres14LSommaire du Match
28 - 2019-08-26273HERSEY Bears9CHICAGO Wolves0LSommaire du Match
29 - 2019-08-27287CHICAGO Wolves0STOCKTON Flames13LSommaire du Match
30 - 2019-08-28297PV Sharapovas10CHICAGO Wolves0LSommaire du Match
31 - 2019-08-29312CHICAGO Wolves0ROCKFORD IceHogs12LSommaire du Match
32 - 2019-08-30324VICTORIAVILLE Tigres11CHICAGO Wolves0LSommaire du Match
33 - 2019-08-31338CHICAGO Wolves8BROOKLYN Wolfpack0WSommaire du Match
34 - 2019-09-01349SAN DIEGO Gulls1CHICAGO Wolves2WSommaire du Match
35 - 2019-09-02363CHICAGO Wolves3SAN DIEGO Gulls1WSommaire du Match
37 - 2019-09-04377SAN DIEGO Gulls0CHICAGO Wolves6WSommaire du Match
38 - 2019-09-05391LAVAL Rockets5CHICAGO Wolves0LSommaire du Match
39 - 2019-09-06402CHICAGO Wolves1SYRACUSE Crunch4LSommaire du Match
41 - 2019-09-08416CHICAGO Wolves2MILWAUKEE Admirals9LSommaire du Match
42 - 2019-09-09427CHICAGO Wolves2ROCKFORD IceHogs3LSommaire du Match
43 - 2019-09-10438LAVAL Rockets4CHICAGO Wolves1LSommaire du Match
45 - 2019-09-12454CHICAGO Wolves3PV Sharapovas2WSommaire du Match
46 - 2019-09-13464COLORADO Eagles4CHICAGO Wolves2LSommaire du Match
48 - 2019-09-15479CHICAGO Wolves6SAN DIEGO Gulls2WSommaire du Match
49 - 2019-09-16492PROVIDENCE Bruins4CHICAGO Wolves0LR3Sommaire du Match
50 - 2019-09-17505MILWAUKEE Admirals10CHICAGO Wolves4LSommaire du Match
51 - 2019-09-18518CHICAGO Wolves2COLORADO Eagles4LSommaire du Match
52 - 2019-09-19532CORNWALL Aces0CHICAGO Wolves11WSommaire du Match
54 - 2019-09-21545CHICAGO Wolves11CLEVELAND Monsters1WSommaire du Match
55 - 2019-09-22557IOWA Wild3CHICAGO Wolves4WSommaire du Match
57 - 2019-09-24576BELLEVILLE Senators2CHICAGO Wolves5WSommaire du Match
59 - 2019-09-26586CHICAGO Wolves2MONT-LAURIER Sommet4LSommaire du Match
60 - 2019-09-27601STOCKTON Flames6CHICAGO Wolves2LSommaire du Match
62 - 2019-09-29612CHICAGO Wolves0COLORADO Eagles1LSommaire du Match
64 - 2019-10-01627UTICA Comets4CHICAGO Wolves2LSommaire du Match
66 - 2019-10-03640CHICAGO Wolves4BRIDGEPORT Sound Tigers3WSommaire du Match
67 - 2019-10-04652CHICAGO Wolves11CORNWALL Aces2WSommaire du Match
68 - 2019-10-05660BROOKLYN Wolfpack0CHICAGO Wolves11WSommaire du Match
70 - 2019-10-07679PROVIDENCE Bruins5CHICAGO Wolves3LR3Sommaire du Match
72 - 2019-10-09693CHICAGO Wolves2PROVIDENCE Bruins3LXSommaire du Match
73 - 2019-10-10702CHICAGO Wolves1UTICA Comets3LSommaire du Match
74 - 2019-10-11715ROCKFORD IceHogs5CHICAGO Wolves2LSommaire du Match
75 - 2019-10-12730CHICAGO Wolves2IOWA Wild6LSommaire du Match
76 - 2019-10-13740BROOKLYN Wolfpack0CHICAGO Wolves13WSommaire du Match
77 - 2019-10-14747CHICAGO Wolves11BELLEVILLE Senators1WSommaire du Match
79 - 2019-10-16765BRIDGEPORT Sound Tigers8CHICAGO Wolves4LSommaire du Match
80 - 2019-10-17783WILKIES-BARRIE Penguins0CHICAGO Wolves10WSommaire du Match
82 - 2019-10-19793CHICAGO Wolves2LEHIGH VALLEY Phantoms5LSommaire du Match
83 - 2019-10-20803CHICAGO Wolves0TUSCON Roadrunners4LSommaire du Match
84 - 2019-10-21817MANITOBA Moose5CHICAGO Wolves2LR3Sommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
85 - 2019-10-22833HOLLYWOOD Oscar2CHICAGO Wolves13WSommaire du Match
86 - 2019-10-23836CHICAGO Wolves2MANITOBA Moose5LR3Sommaire du Match
87 - 2019-10-24854CHICAGO Wolves11CLEVELAND Monsters1WSommaire du Match
89 - 2019-10-26866TUSCON Roadrunners3CHICAGO Wolves0LSommaire du Match
90 - 2019-10-27879CHICAGO Wolves1LAVAL Rockets5LSommaire du Match
91 - 2019-10-28888CHICAGO Wolves9HOLLYWOOD Oscar1WSommaire du Match
92 - 2019-10-29902BRIDGEPORT Sound Tigers3CHICAGO Wolves1LSommaire du Match
95 - 2019-11-01923LEHIGH VALLEY Phantoms2CHICAGO Wolves3WXSommaire du Match
96 - 2019-11-02929CHICAGO Wolves2LAVAL Rockets5LSommaire du Match
97 - 2019-11-03940CHICAGO Wolves4HERSEY Bears3WXSommaire du Match
99 - 2019-11-05955CLEVELAND Monsters1CHICAGO Wolves9WSommaire du Match
100 - 2019-11-06963CHICAGO Wolves3HERSEY Bears2WXSommaire du Match
102 - 2019-11-08976CHICAGO Wolves-BROOKLYN Wolfpack-
103 - 2019-11-09985MONT-LAURIER Sommet-CHICAGO Wolves-
105 - 2019-11-111003MILWAUKEE Admirals-CHICAGO Wolves-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
2 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,067,794$ 967,000$ 967,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 990,529$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 6 9,802$ 58,812$




LigueDomicileVisiteur
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
3275234803100259372-11337112501000135186-5138122302100124186-625325946772607126715932670851899917328327542588991702615.29%1083171.30%31221205659.39%724177940.70%627125450.00%183014071893425782388
Total Saison Régulière75234803100259372-11337112501000135186-5138122302100124186-625325946772607126715932670851899917328327542588991702615.29%1083171.30%31221205659.39%724177940.70%627125450.00%183014071893425782388