CHICAGO Wolves
GP: 1 | W: 1 | L: 0
GF: 5 | GA: 2 | PP%: 20.00% | PK%: 100.00%
DG: Ralph Beauchamp | Morale : 99 | Moyenne d'Équipe : 64
Prochain matchs #11 vs ONTARIO Reign
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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 SPÂgeContratSalaire
1Kevin Stenlund (R)0X100.006646896288837861725959606267636899680234750,000$
2Troy Terry0X100.005839856770767369576863617265665499670223750,000$
3Carl Grundstrom0X100.006545886475847862576060636665637299670223750,000$
4Sam Steel0X100.005639856770797366837064616763647899670221900,000$
5Garrett Pilon0X100.005843826072889059685857615963626499660221750,000$
6Cody Glass (R)0X100.005639896979746167736563586661628899660213750,000$
7Joe Veleno (R)0X100.006345856277848759715556635862648099660203750,000$
8Mason Appleton0X100.006243876079737762665958616067645699650244750,000$
9Trent Frederic0X100.006356796081757458715959616063657999650222925,000$
10Rem Pitlick (R)0X100.005449856072878958555659545865636499650234750,000$
11Brandon Gignac0X100.005542856166797759546058576165636499640221750,000$
12Lukas Jasek0X100.005443865855878959545757605865616399640231750,000$
13Maksim Sushko (R)0X100.005847855971858756525457535961636299640213750,000$
14Antoine Morand (R)0X100.005344865758858755665454525361626899620213750,000$
15Brandon Hagel (R)0X100.005643885667787354515760575463625799620223750,000$
16Linus Olund (R)0X100.005089716271475062705454525450504499550233750,000$
17Travis Barron (R)0X100.005389645577505055505353515350504499540211750,000$
18Jonne Tammela0X100.005089715768445057705252515250504499530232750,000$
19Kyle Capobianco0X100.006147846477797362306359615565626899660233750,000$
20Olli Juolevi0X100.006338896577807663306453624563628899660221900,000$
21Pierre-Olivier Joseph (R)0X100.006148855977858457305653584661638099650214750,000$
22Nicolas Beaudin (R)0X100.005642885966837458305757564561628099630203750,000$
23Chad Krys (R)0X100.005441885658797854305353525063627499600224750,000$
Rayé
MOYENNE D'ÉQUIPE100.00585084617277756056585758576261679963
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
1Oscar Dansk100.00767068827574767574767571757499680
2Callum Booth (R)100.00715654837069717069717065696299630
3Jakub Skarek (R)100.00676563836665676665676661656499610
Rayé
MOYENNE D'ÉQUIPE100.0071646283706971706971706670679964
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ross Yates62626262757548CAN622300,000$


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
1Sam SteelCHICAGO Wolves (VGK)C11342000213477.69%01616.7001113000100093.75%3200004.7900000100
2Carl GrundstromCHICAGO Wolves (VGK)RW11232002313067.69%01515.971014300000000.00%000003.7600000010
3Brandon GignacCHICAGO Wolves (VGK)LW1022200027320.00%01515.97011130000000100.00%100002.5100000000
4Kyle CapobiancoCHICAGO Wolves (VGK)D11011000250020.00%01515.170001100000000.00%000001.3200000000
5Mason AppletonCHICAGO Wolves (VGK)RW1101-1000030333.33%21111.150000000000000.00%100001.7900000000
6Troy TerryCHICAGO Wolves (VGK)RW1011100039260.00%22222.10000350000000100.00%400000.9000000000
7Garrett PilonCHICAGO Wolves (VGK)C1011-100003110.00%01111.1500000000000085.00%2000001.7900000000
8Kevin StenlundCHICAGO Wolves (VGK)C10111002210490.00%02222.6200035000010086.21%2900000.8800000000
9Chad KrysCHICAGO Wolves (VGK)D110100000100100.00%199.150000000000100.00%000002.1900000000
10Lukas JasekCHICAGO Wolves (VGK)RW1000000003020.00%199.53000000000000100.00%100000.0000000000
11Olli JuoleviCHICAGO Wolves (VGK)D1000100101200.00%01515.170000100000000.00%000000.0000000000
12Brandon HagelCHICAGO Wolves (VGK)LW1000-100013010.00%11111.15000000000000100.00%200000.0000000000
13Joe VelenoCHICAGO Wolves (VGK)C1000000101000.00%199.5300000000000088.89%900000.0000000000
14Nicolas BeaudinCHICAGO Wolves (VGK)D1000020001120.00%21111.200000000000000.00%000000.0000000000
15Pierre-Olivier JosephCHICAGO Wolves (VGK)D1000000311020.00%11111.220000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne15510157209167417416.76%1120713.851231325000131088.89%9900001.4400000110
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
1Oscar DanskCHICAGO Wolves (VGK)11000.9172.0060002240000.000010000
Stats d'équipe Total ou en Moyenne11000.9172.0060002240000.000010000


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
Antoine MorandCHICAGO Wolves (VGK)C212/18/1999Yes84 Kg155 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Brandon GignacCHICAGO Wolves (VGK)LW2211/7/1997No77 Kg180 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Brandon HagelCHICAGO Wolves (VGK)LW228/27/1998Yes79 Kg180 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Callum BoothCHICAGO Wolves (VGK)G235/21/1997Yes84 Kg193 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Carl GrundstromCHICAGO Wolves (VGK)RW2212/1/1997No91 Kg183 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$Lien
Chad KrysCHICAGO Wolves (VGK)D224/10/1998Yes84 Kg155 CMNoNoNo4Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$750,000$
Cody GlassCHICAGO Wolves (VGK)C214/1/1999Yes87 Kg188 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Garrett PilonCHICAGO Wolves (VGK)C224/13/1998No85 Kg183 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Jakub SkarekCHICAGO Wolves (VGK)G2011/10/1999Yes89 Kg191 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Joe VelenoCHICAGO Wolves (VGK)C201/13/2000Yes90 Kg185 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Jonne TammelaCHICAGO Wolves (VGK)C238/5/1997No85 Kg178 CMNoNoNo2Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$Lien
Kevin StenlundCHICAGO Wolves (VGK)C239/20/1996Yes95 Kg193 CMNoNoNo4Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$750,000$
Kyle CapobiancoCHICAGO Wolves (VGK)D238/13/1997No89 Kg185 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$Lien
Linus OlundCHICAGO Wolves (VGK)C236/5/1997Yes84 Kg183 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$Lien
Lukas JasekCHICAGO Wolves (VGK)RW238/28/1997No75 Kg155 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Maksim SushkoCHICAGO Wolves (VGK)RW212/10/1999Yes82 Kg183 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Mason AppletonCHICAGO Wolves (VGK)RW241/15/1996No88 Kg188 CMNoNoNo4Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$750,000$Lien
Nicolas BeaudinCHICAGO Wolves (VGK)D2010/7/1999Yes76 Kg180 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Olli JuoleviCHICAGO Wolves (VGK)D225/5/1998No83 Kg188 CMNoNoNo1Pro & Farm900,000$771,429$750,000$642,857$0$0$NoLien
Oscar DanskCHICAGO Wolves (VGK)G262/28/1994No89 Kg191 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$Lien
Pierre-Olivier JosephCHICAGO Wolves (VGK)D217/1/1999Yes84 Kg188 CMNoNoNo4Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$750,000$
Rem PitlickCHICAGO Wolves (VGK)C234/2/1997Yes89 Kg180 CMNoNoNo4Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$750,000$
Sam SteelCHICAGO Wolves (VGK)C222/3/1998No86 Kg180 CMNoNoNo1Pro & Farm900,000$771,429$750,000$642,857$0$0$NoLien
Travis BarronCHICAGO Wolves (VGK)LW2111/17/1998Yes91 Kg185 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Trent FredericCHICAGO Wolves (VGK)C222/11/1998No92 Kg188 CMNoNoNo2Pro & Farm925,000$792,857$925,000$792,857$0$0$No925,000$Lien
Troy TerryCHICAGO Wolves (VGK)RW229/10/1997No82 Kg183 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2622.0885 Kg183 CM2.65768,269$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kevin StenlundTroy Terry31122
2Brandon GignacSam SteelCarl Grundstrom26122
3Brandon HagelGarrett PilonMason Appleton23122
4Joe VelenoLukas Jasek20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
131122
2Kyle CapobiancoOlli Juolevi26122
3Pierre-Olivier JosephNicolas Beaudin23122
4Chad Krys20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kevin StenlundTroy Terry55122
2Brandon GignacSam SteelCarl Grundstrom45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
2Kyle CapobiancoOlli Juolevi45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Kevin Stenlund55122
2Sam SteelTroy Terry45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
2Kyle CapobiancoOlli Juolevi45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
15512255122
2Kevin Stenlund45122Kyle CapobiancoOlli Juolevi45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Kevin Stenlund55122
2Sam SteelTroy Terry45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
2Kyle CapobiancoOlli Juolevi45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kevin StenlundTroy Terry
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kevin StenlundTroy Terry
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Cody Glass, Trent Frederic, Rem PitlickCody Glass, Trent FredericRem Pitlick
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Pierre-Olivier Joseph, Nicolas Beaudin, Chad KrysPierre-Olivier JosephNicolas Beaudin, Chad Krys
Tirs de Pénalité
, Kevin Stenlund, Sam Steel, Troy Terry, Carl Grundstrom
Gardien
#1 : Oscar Dansk, #2 : Callum Booth, #3 : Jakub Skarek
Lignes d'Attaque Perso. en Prol.
, Kevin Stenlund, Sam Steel, Troy Terry, Carl Grundstrom, Garrett Pilon, Garrett Pilon, Joe Veleno, Cody Glass, Mason Appleton, Trent Frederic
Lignes de Défense Perso. en Prol.
, , Kyle Capobianco, Olli Juolevi, Pierre-Olivier Joseph


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
1ONTARIO Reign11000000523110000005230000000000021.0005101500113074262424024112125120.00%10100.00%0526086.67%242788.89%141593.33%332817495
Total11000000523110000005230000000000021.0005101500113074262424024112125120.00%10100.00%0526086.67%242788.89%141593.33%332817495
_Since Last GM Reset11000000523110000005230000000000021.0005101500113074262424024112125120.00%10100.00%0526086.67%242788.89%141593.33%332817495
_Vs Conference11000000523110000005230000000000021.0005101500113074262424024112125120.00%10100.00%0526086.67%242788.89%141593.33%332817495

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
12W15101574241121200
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
110000052
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
110000052
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
000000000
Derniers 10 Matchs
WLOTWOTL SOWSOL
100000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
5120.00%10100.00%0
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
26242401130
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
526086.67%242788.89%141593.33%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
332817495


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 - 2021-05-153ONTARIO Reign2CHICAGO Wolves5WSommaire du Match
3 - 2021-05-1711ONTARIO Reign-CHICAGO Wolves-
5 - 2021-05-1919CHICAGO Wolves-ONTARIO Reign-
7 - 2021-05-2127CHICAGO Wolves-ONTARIO Reign-
9 - 2021-05-2335ONTARIO Reign-CHICAGO Wolves-
11 - 2021-05-2543CHICAGO Wolves-ONTARIO Reign-
13 - 2021-05-2751ONTARIO Reign-CHICAGO Wolves-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacitéPopularité de l'Équipe
39 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 1,997,500$ 1,967,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 0$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 12 0$ 0$




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