CHICAGO Wolves

GP: 38 | W: 13 | L: 21 | OTL: 4 | P: 30
GF: 91 | GA: 122 | PP%: 7.14% | PK%: 78.08%
DG: Lukas Tremblay | Morale : 99 | Moyenne d'Équipe : 65
Prochain matchs #522 vs UTICA Comets
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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
1Tom Kuhnhackl0XX100.006742836481746763596261696475665399680
2Alexander Volkov0X100.006146886376827962566159606265637299670
3Dominic Turgeon0X100.006347886280837660745957636167646699670
4Otto Koivula (R)0X100.006847886190787262656060646163625999670
5Tommy Novak (R)0X100.005744846373868761756256576365626499660
6Blaine Byron0X100.005345875969888657605858565769656099650
7Connor Bunnaman (R)0X100.006343876079787758565759615863626199650
8Fabian Zetterlund (R)0X100.005339895960828157625556585961636899630
9Lucas Carlsson (R)0X100.005943896372827962306058655265676399670
10Jake Dotchin0X100.006953705985737158305757605271665999650
11Joe Hicketts0X100.005545886364857462306157655367635499650
12Mark Friedman0X100.005845876069817958305957615069645899650
13Sean Day (R)0X100.007546875888777656305553574563626799650
Rayé
MOYENNE D'ÉQUIPE100.00624586617681776051595861576664629966
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)100.00455265776047484949505560497199490
Rayé
MOYENNE D'ÉQUIPE100.0045526577604748494950556049719949
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ralph Krueger69696974797948CAN613400,000$


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
1Otto KoivulaCHICAGO Wolves (STL)LW38161834-61205567169491229.47%22100126.3602221920002510151.83%16400000.6801000232
2Connor BunnamanCHICAGO Wolves (STL)C38141529-61205060126318611.11%1194724.942021692000002146.34%46400000.6100000111
3Lucas CarlssonCHICAGO Wolves (STL)D3842529-10415735510724593.74%8295425.131455410700005201100.00%100000.6100000210
4Dominic TurgeonCHICAGO Wolves (STL)C3882028-820597714732965.44%11102627.0103323930110582055.86%75900000.5501000112
5Alexander VolkovCHICAGO Wolves (STL)LW3871623-181205760154361124.55%1698125.8402210980000390048.70%11500000.4701000111
6Blaine ByronCHICAGO Wolves (STL)C3813922-12804056117379211.11%1099826.26213161011011294056.21%50700000.4400000211
7Tommy NovakCHICAGO Wolves (STL)C3891120-20120427612331877.32%499926.2922418980000372056.80%74300000.4001000121
8Mark FriedmanCHICAGO Wolves (STL)D3841519-910014426316456.35%3471518.841122886011241000.00%000000.5300000012
9Joe HickettsCHICAGO Wolves (STL)D3831215-4801139465276.52%3465517.2400031400004000.00%700000.4600000001
10Sean DayCHICAGO Wolves (STL)D3821113-82406716435294.65%3377620.45011159000014310100.00%200000.3300000100
11Jake DotchinCHICAGO Wolves (STL)D383811-327556262971310.34%3359515.6800035000022100.00%000000.3700001011
12Fabian ZetterlundCHICAGO Wolves (STL)C388311120163453203815.09%43699.72000321000081049.03%15500000.6000000111
13Xavier OuelletST-LOUIS BluesD1011100211120.00%42525.500001100001000.00%000000.7800000001
Stats d'équipe Total ou en Moyenne45791164255-1021701054260911782948087.72%2981004821.9981624211902123639013353.69%291700000.5104001121314
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)38132140.8903.1222322111610580100.7504380220
Stats d'équipe Total ou en Moyenne38132140.8903.1222322111610580100.7504380220


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 RestantSalaire MoyenSalaire Moyen RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Alexander VolkovCHICAGO Wolves (STL)LW231997-08-02No87 Kg185 CMNoNoNo3Pro & Farm850,000$444,495$850,000$444,495$0$0$No850,000$850,000$Lien
Blaine ByronCHICAGO Wolves (STL)C251995-02-21No78 Kg183 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$Lien
Connor BunnamanCHICAGO Wolves (STL)C221998-04-16Yes94 Kg185 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Dominic TurgeonCHICAGO Wolves (STL)C241996-02-25No90 Kg188 CMNoNoNo3Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$Lien
Fabian ZetterlundCHICAGO Wolves (STL)C211999-08-25Yes89 Kg155 CMNoNoNo1Pro & Farm750,000$392,201$750,000$392,201$0$0$No
Jake DotchinCHICAGO Wolves (STL)D261994-03-24No95 Kg191 CMNoNoNo3Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$Lien
Joe HickettsCHICAGO Wolves (STL)D241996-05-04No82 Kg173 CMNoNoNo2Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$Lien
Lucas CarlssonCHICAGO Wolves (STL)D231997-07-05Yes86 Kg183 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Mark FriedmanCHICAGO Wolves (STL)D241995-12-25No84 Kg180 CMNoNoNo1Pro & Farm750,000$392,201$750,000$392,201$0$0$NoLien
Otto KoivulaCHICAGO Wolves (STL)LW221998-09-01Yes100 Kg193 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Sean DayCHICAGO Wolves (STL)D221998-01-09Yes102 Kg191 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Stephon WilliamsCHICAGO Wolves (STL)G271993-04-28Yes89 Kg191 CMNoNoNo1Pro & Farm750,000$392,201$750,000$392,201$0$0$No
Tom KuhnhacklCHICAGO Wolves (STL)LW/RW281992-01-21No89 Kg188 CMNoNoNo3Pro & Farm850,000$444,495$850,000$444,495$0$0$No850,000$850,000$Lien
Tommy NovakCHICAGO Wolves (STL)C231997-04-28Yes81 Kg185 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1423.8689 Kg183 CM2.93764,286$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Otto KoivulaDominic TurgeonConnor Bunnaman31122
2Alexander VolkovTommy NovakBlaine Byron26122
3Otto KoivulaConnor BunnamanDominic Turgeon23122
4Alexander VolkovBlaine ByronTommy Novak20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Lucas Carlsson31122
2Sean DayMark Friedman26122
3Joe HickettsJake Dotchin23122
4Lucas Carlsson20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Otto KoivulaDominic TurgeonConnor Bunnaman55122
2Alexander VolkovTommy NovakBlaine Byron45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Lucas Carlsson55122
2Sean DayMark Friedman45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Otto KoivulaDominic Turgeon55122
2Alexander VolkovTommy Novak45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Lucas Carlsson55122
2Sean DayMark Friedman45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Otto Koivula55122Lucas Carlsson55122
2Dominic Turgeon45122Sean DayMark Friedman45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Otto KoivulaDominic Turgeon55122
2Alexander VolkovTommy Novak45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Lucas Carlsson55122
2Sean DayMark Friedman45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Otto KoivulaDominic TurgeonConnor BunnamanLucas Carlsson
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Otto KoivulaDominic TurgeonConnor BunnamanLucas Carlsson
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Fabian Zetterlund, Connor Bunnaman, Blaine ByronFabian Zetterlund, Connor BunnamanBlaine Byron
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Joe Hicketts, Jake Dotchin, Sean DayJoe HickettsJake Dotchin, Sean Day
Tirs de Pénalité
Otto Koivula, Dominic Turgeon, Alexander Volkov, Tommy Novak, Connor Bunnaman
Gardien
#1 : Stephon Williams, #2 :
Lignes d'Attaque Perso. en Prol.
Otto Koivula, Dominic Turgeon, Alexander Volkov, Tommy Novak, Connor Bunnaman, Blaine Byron, Blaine Byron, Fabian Zetterlund, , ,
Lignes de Défense Perso. en Prol.
, Lucas Carlsson, Sean Day, Mark Friedman, Joe Hicketts


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 Senators1010000003-31010000003-30000000000000.00000000312828425365386413212411618400.00%20100.00%0677125254.07%540105950.99%35059658.72%935665890260476241
2BRIDGEPORT Sound Tigers2010100045-1100010003211010000013-220.50047110031282845136538641321559142810110.00%6183.33%0677125254.07%540105950.99%35059658.72%935665890260476241
3BROOKLYN Wolfpack320010001358210010006241100000073461.0001322350131282849636538641321732510366116.67%50100.00%0677125254.07%540105950.99%35059658.72%935665890260476241
4COLORADO Eagles1010000024-21010000024-20000000000000.0002460031282842636538641321289612300.00%3233.33%0677125254.07%540105950.99%35059658.72%935665890260476241
5HERSEY Bears21100000651110000003121010000034-120.5006111700312828468365386413214819427700.00%20100.00%0677125254.07%540105950.99%35059658.72%935665890260476241
6HOLLYWOOD Oscar1010000034-1000000000001010000034-100.00034700312828432365386413213041018300.00%5260.00%0677125254.07%540105950.99%35059658.72%935665890260476241
7IOWA Wild2110000058-3000000000002110000058-320.50051015003128284663653864132152178218112.50%20100.00%1677125254.07%540105950.99%35059658.72%935665890260476241
8LEHIGH VALLEY Phantoms21100000914-521100000914-50000000000020.50091625003128284793653864132175198436233.33%4175.00%0677125254.07%540105950.99%35059658.72%935665890260476241
9MONT-LAURIER Sommet1010000004-4000000000001010000004-400.0000000031282843536538641321225025100.00%000.00%0677125254.07%540105950.99%35059658.72%935665890260476241
10Manitoba Moose30200100513-81000010023-120200000310-710.1675101500312828484365386413211163122341200.00%11372.73%0677125254.07%540105950.99%35059658.72%935665890260476241
11Marlies de Toronto1010000023-1000000000001010000023-100.00023500312828433365386413213517616200.00%3166.67%0677125254.07%540105950.99%35059658.72%935665890260476241
12PROVIDENCE Bruins1000010012-1000000000001000010012-110.500123003128284313653864132141610277114.29%50100.00%0677125254.07%540105950.99%35059658.72%935665890260476241
13PV Sharapovas20101000610-420101000610-40000000000020.50061016003128284453653864132163710297228.57%5260.00%0677125254.07%540105950.99%35059658.72%935665890260476241
14Quebec Nordiques21001000532210010005320000000000041.000591400312828410536538641321408636100.00%3166.67%0677125254.07%540105950.99%35059658.72%935665890260476241
15ROCKFORD IceHogs2010010038-51010000015-41000010023-110.25035800312828467365386413216319024500.00%000.00%0677125254.07%540105950.99%35059658.72%935665890260476241
16SAN DIEGO Gulls220000001531222000000153120000000000041.00015294400312828410136538641321297422300.00%20100.00%0677125254.07%540105950.99%35059658.72%935665890260476241
17STOCKTON Flames4120000148-42110000034-12010000114-330.375481200312828492365386413211234523551200.00%5180.00%0677125254.07%540105950.99%35059658.72%935665890260476241
18TUSCON Roadrunners1010000002-21010000002-20000000000000.000000003128284273653864132123629200.00%10100.00%0677125254.07%540105950.99%35059658.72%935665890260476241
Total389210430191122-312078041005659-318213002013563-28300.39591164255013128284118136538641321108829817254211287.14%731678.08%1677125254.07%540105950.99%35059658.72%935665890260476241
20UTICA Comets1010000014-3000000000001010000014-300.0001120031282842036538641321322410200.00%20100.00%0677125254.07%540105950.99%35059658.72%935665890260476241
21VICTORIAVILLE Tigres40400000714-71010000013-230300000611-500.0007132000312828498365386413211163219521100.00%7271.43%0677125254.07%540105950.99%35059658.72%935665890260476241
_Since Last GM Reset389210430191122-312078041005659-318213002013563-28300.39591164255013128284118136538641321108829817254211287.14%731678.08%1677125254.07%540105950.99%35059658.72%935665890260476241
_Vs Conference1657022004741694302000301911714002001722-5160.500478413101312828452036538641321427119602114736.38%29486.21%0677125254.07%540105950.99%35059658.72%935665890260476241
_Vs Division1223011002247-2542201000615-9801001001632-1670.29222426400312828434136538641321375108551433912.56%23769.57%1677125254.07%540105950.99%35059658.72%935665890260476241

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
3830W1911642551181108829817254201
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
38921430191122
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
207841005659
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
1821302013563
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
11287.14%731678.08%1
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
365386413213128284
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
677125254.07%540105950.99%35059658.72%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
935665890260476241


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 - 2020-08-029BROOKLYN Wolfpack2CHICAGO Wolves3WXSommaire du Match
3 - 2020-08-0428SAN DIEGO Gulls2CHICAGO Wolves6WSommaire du Match
5 - 2020-08-0647CHICAGO Wolves1STOCKTON Flames2LXXSommaire du Match
6 - 2020-08-0754SAN DIEGO Gulls1CHICAGO Wolves9WSommaire du Match
7 - 2020-08-0872CHICAGO Wolves3HOLLYWOOD Oscar4LSommaire du Match
9 - 2020-08-1081PV Sharapovas4CHICAGO Wolves5WXSommaire du Match
11 - 2020-08-12103CHICAGO Wolves3HERSEY Bears4LSommaire du Match
12 - 2020-08-13113ROCKFORD IceHogs5CHICAGO Wolves1LSommaire du Match
13 - 2020-08-14126CHICAGO Wolves2IOWA Wild6LSommaire du Match
14 - 2020-08-15139BRIDGEPORT Sound Tigers2CHICAGO Wolves3WXSommaire du Match
16 - 2020-08-17152CHICAGO Wolves1Manitoba Moose4LSommaire du Match
17 - 2020-08-18163STOCKTON Flames1CHICAGO Wolves2WSommaire du Match
19 - 2020-08-20179CHICAGO Wolves4VICTORIAVILLE Tigres5LSommaire du Match
20 - 2020-08-21191Quebec Nordiques2CHICAGO Wolves3WSommaire du Match
21 - 2020-08-22206CHICAGO Wolves1VICTORIAVILLE Tigres3LSommaire du Match
22 - 2020-08-23213COLORADO Eagles4CHICAGO Wolves2LSommaire du Match
24 - 2020-08-25236TUSCON Roadrunners2CHICAGO Wolves0LSommaire du Match
25 - 2020-08-26251CHICAGO Wolves2Manitoba Moose6LSommaire du Match
26 - 2020-08-27260Manitoba Moose3CHICAGO Wolves2LXSommaire du Match
27 - 2020-08-28270CHICAGO Wolves7BROOKLYN Wolfpack3WSommaire du Match
29 - 2020-08-30286CHICAGO Wolves1VICTORIAVILLE Tigres3LSommaire du Match
30 - 2020-08-31293STOCKTON Flames3CHICAGO Wolves1LSommaire du Match
32 - 2020-09-02313CHICAGO Wolves2Marlies de Toronto3LSommaire du Match
33 - 2020-09-03319VICTORIAVILLE Tigres3CHICAGO Wolves1LSommaire du Match
34 - 2020-09-04335CHICAGO Wolves2ROCKFORD IceHogs3LXSommaire du Match
35 - 2020-09-05344Quebec Nordiques1CHICAGO Wolves2WXSommaire du Match
37 - 2020-09-07361CHICAGO Wolves0STOCKTON Flames2LSommaire du Match
38 - 2020-09-08370LEHIGH VALLEY Phantoms4CHICAGO Wolves6WSommaire du Match
40 - 2020-09-10388PV Sharapovas6CHICAGO Wolves1LSommaire du Match
41 - 2020-09-11403CHICAGO Wolves3IOWA Wild2WSommaire du Match
42 - 2020-09-12415BELLEVILLE Senators3CHICAGO Wolves0LSommaire du Match
44 - 2020-09-14426CHICAGO Wolves1UTICA Comets4LSommaire du Match
46 - 2020-09-16443LEHIGH VALLEY Phantoms10CHICAGO Wolves3LSommaire du Match
47 - 2020-09-17456CHICAGO Wolves1BRIDGEPORT Sound Tigers3LSommaire du Match
48 - 2020-09-18467CHICAGO Wolves1PROVIDENCE Bruins2LXR3Sommaire du Match
49 - 2020-09-19476HERSEY Bears1CHICAGO Wolves3WSommaire du Match
50 - 2020-09-20492CHICAGO Wolves0MONT-LAURIER Sommet4LSommaire du Match
52 - 2020-09-22502BROOKLYN Wolfpack0CHICAGO Wolves3WSommaire du Match
54 - 2020-09-24522UTICA Comets-CHICAGO Wolves-
55 - 2020-09-25534CHICAGO Wolves-TUSCON Roadrunners-
56 - 2020-09-26544CHICAGO Wolves-MONT-LAURIER Sommet-
57 - 2020-09-27553SAN DIEGO Gulls-CHICAGO Wolves-
58 - 2020-09-28571BRIDGEPORT Sound Tigers-CHICAGO Wolves-
60 - 2020-09-30584CHICAGO Wolves-Quebec Nordiques-
61 - 2020-10-01597CHICAGO Wolves-PV Sharapovas-
62 - 2020-10-02606HOLLYWOOD Oscar-CHICAGO Wolves-
64 - 2020-10-04626MONT-LAURIER Sommet-CHICAGO Wolves-
65 - 2020-10-05638CHICAGO Wolves-TUSCON Roadrunners-
66 - 2020-10-06647CHICAGO Wolves-HOLLYWOOD Oscar-
67 - 2020-10-07655CHICAGO Wolves-MILWAUKEE Admirals-
68 - 2020-10-08666ROCKFORD IceHogs-CHICAGO Wolves-
69 - 2020-10-09681CHICAGO Wolves-LAVAL Rockets-
70 - 2020-10-10690WILKIES-BARRIE Penguins-CHICAGO Wolves-
72 - 2020-10-12707SAN DIEGO Gulls-CHICAGO Wolves-
73 - 2020-10-13726CHICAGO Wolves-MILWAUKEE Admirals-
74 - 2020-10-14733IOWA Wild-CHICAGO Wolves-
76 - 2020-10-16748CHICAGO Wolves-HERSEY Bears-
77 - 2020-10-17756CHICAGO Wolves-WILKIES-BARRIE Penguins-
78 - 2020-10-18766Marlies de Toronto-CHICAGO Wolves-
79 - 2020-10-19780CHICAGO Wolves-Binghampton Devils-
80 - 2020-10-20791Binghampton Devils-CHICAGO Wolves-
82 - 2020-10-22811CHICAGO Wolves-Marlies de Toronto-
83 - 2020-10-23816MILWAUKEE Admirals-CHICAGO Wolves-
85 - 2020-10-25839UTICA Comets-CHICAGO Wolves-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
87 - 2020-10-27861MONT-LAURIER Sommet-CHICAGO Wolves-
88 - 2020-10-28869CHICAGO Wolves-Syracruse Crunch-
89 - 2020-10-29884CHICAGO Wolves-COLORADO Eagles-
90 - 2020-10-30892CHICAGO Wolves-LEHIGH VALLEY Phantoms-
91 - 2020-10-31897PROVIDENCE Bruins-CHICAGO Wolves-
92 - 2020-11-01914CHICAGO Wolves-COLORADO Eagles-
93 - 2020-11-02921LAVAL Rockets-CHICAGO Wolves-
94 - 2020-11-03936CHICAGO Wolves-LAVAL Rockets-
96 - 2020-11-05948PROVIDENCE Bruins-CHICAGO Wolves-
97 - 2020-11-06965CHICAGO Wolves-BELLEVILLE Senators-
99 - 2020-11-08975Syracruse Crunch-CHICAGO Wolves-
101 - 2020-11-10993CHICAGO Wolves-WILKIES-BARRIE Penguins-
102 - 2020-11-11996Syracruse Crunch-CHICAGO Wolves-
103 - 2020-11-121001CHICAGO Wolves-BELLEVILLE Senators-
105 - 2020-11-141020Binghampton Devils-CHICAGO Wolves-
108 - 2020-11-171040CHICAGO Wolves-SAN DIEGO Gulls-



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
20 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
514,061$ 1,070,000$ 1,070,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 510,392$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 57 9,817$ 559,569$




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
Saison Régulière
3382284702212315323-841142300211152157-541142402001163166-356315542857191449474430479891012102828284983626511692213716.74%1073567.29%11385237358.36%918212143.28%712135952.39%209616051955479893452
34389210430191122-312078041005659-318213002013563-283091164255013128284118136538641321108829817254211287.14%731678.08%1677125254.07%540105950.99%35059658.72%935665890260476241
Total Saison Régulière120376806513406445-3961213104311208216-859163702202198229-3186406706111211017512210284228135413981441493937113443717113334513.51%1805171.67%22062362556.88%1458318045.85%1062195554.32%3032227128467401369693