Connexion

CHICAGO Wolves
GP: 1 | W: 0 | L: 1
GF: 1 | GA: 3 | PP%: 0.00% | PK%: 100.00%
DG: Ralph Beauchamp | Morale : 99 | Moyenne d’équipe : 66
Prochains matchs #15 vs IOWA Wild
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Centre de jeu
CHICAGO Wolves
0-1-0, 0pts
1
FINAL
3 IOWA Wild
1-0-0, 2pts
Team Stats
L1StreakW1
0-0-0Home Record1-0-0
0-1-0Away Record0-0-0
0-1-0Last 10 Games1-0-0
1.00Buts par match 3.00
3.00Buts contre par match 1.00
0.00%Pourcentage en avantage numérique0.00%
100.00%Pourcentage en désavantage numérique100.00%
CHICAGO Wolves
0-1-0, 0pts
2022-06-25
IOWA Wild
1-0-0, 2pts
Statistiques d’équipe
L1SéquenceW1
0-0-0Fiche domicile1-0-0
0-1-0Fiche visiteur0-0-0
0-1-010 derniers matchs1-0-0
1.00Buts par match 3.00
3.00Buts contre par match 1.00
0.00%Pourcentage en avantage numérique0.00%
100.00%Pourcentage en désavantage numérique100.00%
IOWA Wild
1-0-0, 2pts
2022-06-27
CHICAGO Wolves
0-1-0, 0pts
Statistiques d’équipe
W1SéquenceL1
1-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-1-0
1-0-010 derniers matchs0-1-0
3.00Buts par match 1.00
1.00Buts contre par match 3.00
0.00%Pourcentage en avantage numérique0.00%
100.00%Pourcentage en désavantage numérique100.00%
IOWA Wild
1-0-0, 2pts
2022-06-29
CHICAGO Wolves
0-1-0, 0pts
Statistiques d’équipe
W1SéquenceL1
1-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-1-0
1-0-010 derniers matchs0-1-0
3.00Buts par match 1.00
1.00Buts contre par match 3.00
0.00%Pourcentage en avantage numérique0.00%
100.00%Pourcentage en désavantage numérique100.00%
Meneurs d'équipe
Buts
Joe Veleno
1
Passes
Kyle Capobianco
1
Points
Kyle Capobianco
1
Plus/Moins
Kyle Capobianco
1
Victoires
Callum Booth
0
Pourcentage d’arrêts
Callum Booth
0.917

Statistiques d’équipe
Buts pour
1
1.00 GFG
Tirs pour
24
24.00 Avg
Pourcentage en avantage numérique
0.0%
0 GF
Début de zone offensive
32.1%
Buts contre
3
3.00 GAA
Tirs contre
36
36.00 Avg
Pourcentage en désavantage numérique
100.0%
0 GA
Début de la zone défensive
39.6%
Informations de l'équipe

Directeur généralRalph Beauchamp
EntraîneurTroy Mann
DivisionGuitard
ConférenceConference B
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance
Billets de saison300


Informations de la formation

Équipe Pro23
Équipe Mineure21
Limite contact 44 / 55
Espoirs57


Historique d'équipe

Saison actuelle0-1
Historique153-75-14 (0.632%)
Apparitions en séries éliminatoires 0
Historique en séries éliminatoires (W-L)0-1
Coupe Stanley0


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
1Carl GrundstromX100.008342856675847865586467656866677199710231750,000$
2Cody GlassX100.005635947285798271806866637364678899710221750,000$
3Troy TerryX100.005135927170818573677067627668645399700241750,000$
4Kevin StenlundXX100.005935936489818565766667616569646799700242750,000$
5Joe VelenoX100.006236746577848264796362686762667899690211750,000$
6David Cotton (R)X100.007152766380828766775867596668655899690243750,000$
7Trent FredericX100.0078825965817483647161635762656779996802311,050,000$
8Garrett PilonX100.005035956272847262766261635965636399660233750,000$
9Rem PitlickXX100.005739876272847365746263566467656699660242750,000$
10Maksim SushkoX100.005835956276818263575961586362647199660221750,000$
11Lukas JasekX100.005637886065818660756358575967644899650243850,000$
12Antoine MorandX100.005746786069869159685856546164636899650221750,000$
13Evan Barratt (R)X100.006648786372837859716059565863626499650223750,000$
14Brayden Tracey (R)X100.006138885871696456535555575961638199610203750,000$
15Linus Olund (R)X100.005089716271475062705454525450504499550241750,000$
16Pierre-Olivier JosephX100.007438887177827864306859655263648199700222750,000$
17Christian JarosX100.008572876188787962306657645169635699690253800,000$
18Kyle CapobiancoX100.007137896677767263306459585267646699670241750,000$
19Chad KrysX100.006342856071837859305652585065667399640232750,000$
20Donovan Sebrango (R)X100.006636805875778256305450574559616999630193750,000$
Rayé
MOYENNE D’ÉQUIPE100.00644584647679786360626060606464679967
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
1Callum Booth100.00777579837675777675777667716199690241750,000$
2Oscar Dansk100.00748382847372747372747373776699680271750,000$
3Jakub Skarek100.00677876836665676665676663676699620211750,000$
Rayé
MOYENNE D’ÉQUIPE100.0073797983727173727173726872649966
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Troy Mann68656968797473CAN526300,000$


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
1Kyle CapobiancoCHICAGO Wolves (VGK)D1011100120200.00%12424.950000200001000.00%011000.8000000000
2Kevin StenlundCHICAGO Wolves (VGK)C/RW1011000233200.00%01818.02000020001100100.00%200001.1100000000
3Joe VelenoCHICAGO Wolves (VGK)C11010002330333.33%01616.1300000000110042.86%701001.2400000000
4Brayden TraceyCHICAGO Wolves (VGK)LW1000020111300.00%01717.130000200000000.00%000000.0000000000
5Christian JarosCHICAGO Wolves (VGK)D1000000630010.00%12626.300000300002000.00%001000.0000000000
6Trent FredericCHICAGO Wolves (VGK)C1000000100000.00%033.130000000000000.00%000000.0000000000
7Troy TerryCHICAGO Wolves (VGK)RW1000-200025120.00%11616.680001200000000.00%100000.0000000000
8Carl GrundstromCHICAGO Wolves (VGK)RW1000-100122000.00%11818.4500013000000033.33%300000.0000000000
9Linus OlundCHICAGO Wolves (VGK)C1000-200231010.00%01313.8300000000000025.00%400000.0000000000
10Lukas JasekCHICAGO Wolves (VGK)RW1000-200211000.00%01313.83000000000000100.00%110000.0000000000
11Rem PitlickCHICAGO Wolves (VGK)C/LW1000000311100.00%12424.530000300002000.00%212000.0000000000
12Chad KrysCHICAGO Wolves (VGK)D1000-100200000.00%02121.800000200001000.00%001000.0000000000
13Cody GlassCHICAGO Wolves (VGK)C1000000433040.00%11919.6200003000020046.15%2600000.0000000000
14Maksim SushkoCHICAGO Wolves (VGK)RW1000000112010.00%077.530000000000000.00%100000.0000000000
15Pierre-Olivier JosephCHICAGO Wolves (VGK)D1000-200222000.00%32828.800000300002000.00%011000.0000000000
16David CottonCHICAGO Wolves (VGK)C1000020200020.00%099.1500000000000066.67%610000.0000000000
17Donovan SebrangoCHICAGO Wolves (VGK)D1000-100010000.00%11616.100000000000000.00%001000.0000000000
Statistiques d’équipe totales ou en moyenne17123-10403228249144.17%1029617.410002290002150045.28%5358000.2000000000
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
1Callum BoothCHICAGO Wolves (VGK)10100.9173.00600033623000.000010000
Statistiques d’équipe totales ou en moyenne10100.9173.00600033623000.000010000


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 restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Antoine MorandCHICAGO Wolves (VGK)C222/18/1999No84 Kg180 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Brayden TraceyCHICAGO Wolves (VGK)LW205/28/2001Yes80 Kg183 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Callum BoothCHICAGO Wolves (VGK)G245/21/1997No84 Kg193 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Carl GrundstromCHICAGO Wolves (VGK)RW2312/1/1997No91 Kg183 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Chad KrysCHICAGO Wolves (VGK)D234/10/1998No84 Kg180 CMNoNoNo2Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$Lien
Christian JarosCHICAGO Wolves (VGK)D254/2/1996No101 Kg191 CMNoNoNo3Pro & Farm800,000$685,714$800,000$685,714$0$0$No800,000$800,000$Lien
Cody GlassCHICAGO Wolves (VGK)C224/1/1999No94 Kg191 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
David CottonCHICAGO Wolves (VGK)C247/9/1997Yes91 Kg188 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Donovan SebrangoCHICAGO Wolves (VGK)D191/12/2002Yes86 Kg185 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Evan BarrattCHICAGO Wolves (VGK)C222/18/1999Yes85 Kg183 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Garrett PilonCHICAGO Wolves (VGK)C234/13/1998No86 Kg183 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$Lien
Jakub SkarekCHICAGO Wolves (VGK)G2111/10/1999No89 Kg191 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Joe VelenoCHICAGO Wolves (VGK)C211/13/2000No90 Kg185 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Kevin StenlundCHICAGO Wolves (VGK)C/RW249/20/1996No98 Kg193 CMNoNoNo2Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$Lien
Kyle CapobiancoCHICAGO Wolves (VGK)D248/13/1997No89 Kg185 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Linus OlundCHICAGO Wolves (VGK)C246/5/1997Yes84 Kg183 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Lukas JasekCHICAGO Wolves (VGK)RW248/28/1997No75 Kg180 CMNoNoNo3Pro & Farm850,000$728,571$850,000$728,571$0$0$No850,000$850,000$Lien
Maksim SushkoCHICAGO Wolves (VGK)RW222/10/1999No94 Kg183 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Oscar DanskCHICAGO Wolves (VGK)G272/28/1994No93 Kg191 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Pierre-Olivier JosephCHICAGO Wolves (VGK)D227/1/1999No84 Kg188 CMNoNoNo2Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$Lien
Rem PitlickCHICAGO Wolves (VGK)C/LW244/2/1997No89 Kg180 CMNoNoNo2Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$Lien
Trent FredericCHICAGO Wolves (VGK)C232/11/1998No92 Kg188 CMNoNoNo1Pro & Farm1,050,000$900,000$1,050,000$900,000$0$0$NoLien
Troy TerryCHICAGO Wolves (VGK)RW249/10/1997No82 Kg183 CMNoNoNo1Pro & Farm750,000$642,857$750,000$642,857$0$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2322.9188 Kg185 CM1.78769,565$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Rem PitlickCody GlassCarl Grundstrom31122
2Brayden TraceyJoe VelenoKevin Stenlund26122
3Troy TerryLinus OlundLukas Jasek23122
4Rem PitlickDavid CottonMaksim Sushko20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Pierre-Olivier JosephChristian Jaros31122
2Kyle CapobiancoChad Krys26122
3Donovan SebrangoPierre-Olivier Joseph23122
4Christian JarosKyle Capobianco20122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Rem PitlickCody GlassCarl Grundstrom55122
2Brayden TraceyKevin StenlundTroy Terry45122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Pierre-Olivier JosephChristian Jaros55122
2Kyle CapobiancoChad Krys45122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Cody GlassRem Pitlick55122
2Kevin StenlundBrayden Tracey45122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Pierre-Olivier JosephChristian Jaros55122
2Kyle CapobiancoChad Krys45122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Cody Glass55122Pierre-Olivier JosephChristian Jaros55122
2Kevin Stenlund45122Kyle CapobiancoChad Krys45122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Cody GlassRem Pitlick55122
2Kevin StenlundBrayden Tracey45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Pierre-Olivier JosephChristian Jaros55122
2Kyle CapobiancoChad Krys45122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Rem PitlickCody GlassCarl GrundstromPierre-Olivier JosephChristian Jaros
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Rem PitlickCody GlassCarl GrundstromPierre-Olivier JosephChristian Jaros
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Joe Veleno, David Cotton, Trent FredericJoe Veleno, David CottonJoe Veleno
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Kyle Capobianco, Chad Krys, Donovan SebrangoKyle CapobiancoKyle Capobianco, Chad Krys
Tirs de pénalité
Carl Grundstrom, Cody Glass, Kevin Stenlund, Troy Terry, Joe Veleno
Gardien
#1 : Callum Booth, #2 : Oscar Dansk, #3 : Jakub Skarek
Lignes d’attaque personnalisées en prolongation
Carl Grundstrom, Cody Glass, Kevin Stenlund, Troy Terry, Joe Veleno, David Cotton, David Cotton, Trent Frederic, Maksim Sushko, Rem Pitlick, Garrett Pilon
Lignes de défense personnalisées en prolongation
Pierre-Olivier Joseph, Christian Jaros, Kyle Capobianco, Chad Krys, Donovan Sebrango


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
1IOWA Wild1010000013-2000000000001010000013-200.00012300100024137403610432300.00%20100.00%071741.18%102147.62%71546.67%19920102010
Total1010000013-2000000000001010000013-200.00012300100024137403610432300.00%20100.00%071741.18%102147.62%71546.67%19920102010
_Since Last GM Reset1010000013-2000000000001010000013-200.00012300100024137403610432300.00%20100.00%071741.18%102147.62%71546.67%19920102010
_Vs Conference1010000013-2000000000001010000013-200.00012300100024137403610432300.00%20100.00%071741.18%102147.62%71546.67%19920102010
_Vs Division1010000013-2000000000001010000013-200.00012300100024137403610432300.00%20100.00%071741.18%102147.62%71546.67%19920102010

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
10L112324361043200
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
101000013
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
101000013
Derniers 10 matchs
WLOTWOTL SOWSOL
010000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
300.00%20100.00%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
137401000
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
71741.18%102147.62%71546.67%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
19920102010


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
2 - 2022-06-237CHICAGO Wolves1IOWA Wild3ALSommaire du match
4 - 2022-06-2515CHICAGO Wolves-IOWA Wild-
6 - 2022-06-2723IOWA Wild-CHICAGO Wolves-
8 - 2022-06-2931IOWA Wild-CHICAGO Wolves-
10 - 2022-07-0139CHICAGO Wolves-IOWA Wild-
12 - 2022-07-0347IOWA Wild-CHICAGO Wolves-
14 - 2022-07-0555CHICAGO Wolves-IOWA Wild-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance0.00%0.00%
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
40 0 - 0.00%0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 1,770,000$ 1,770,000$ 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$ 12 0$ 0$




CHICAGO Wolves Leaders statistiques (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS
140035244079217836428480261013.49%233818220.461792033824278101864411155.50%321.9416
232128845073817832247212223212.90%177634719.771542023564000002421863.69%122.3344
340022924847710622288317180212.71%185595314.88668615219300018281758.43%101.6004
44008137645720617268455316774.83%8001158828.97601221822110131353500.00%00.7902
540013920634598258487503100613.82%117517712.94456110689000018657.46%11.3300

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
1400254124140.9163.352376042413251582380075680.47621
2124040.8005.49306002814068000.0000

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
Saison régulière
37805025022014242791454027100210021112883402315001012131516210742473011542111015415834208155113921258103220979512105030913744.34%2389858.82%61043236344.14%841211839.71%739155247.62%1887124816156881307621
37805124022014292801494027100210021112883402414001012181526610942973811672111215516034215156513881255103209985510106131114045.02%2379759.07%61043236344.14%841212139.65%741155847.56%1889125016146871306621
38804026064223212497240221202211159120394018140421116212933102321526847006414110810313210181124963373113103545421032509538.00%2266571.24%71142198757.47%1101202054.50%724121059.83%173093116047221505781
Total Saison régulière24014175010824117480836612076320641158137620512065430441359343216131811741994316842286450426161155541343904347657954229991476421487037242.76%70126062.91%193228671348.09%2783625944.46%2204432051.02%550834294834209841192025
381010000013-2000000000001010000013-2012300100024137403610432300.00%20100.00%071741.18%102147.62%71546.67%19920102010
Total Séries éliminatoires1010000013-2000000000001010000013-2012300100024137403610432300.00%20100.00%071741.18%102147.62%71546.67%19920102010

CHICAGO Wolves Leaders statistiques (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS
1Kyle Capobianco1011101200.00%12424.9500000000000.00%00.8000
2Kevin Stenlund1011002330.00%01818.020000000100100.00%01.1100
3Joe Veleno11010023333.33%01616.13000000010042.86%01.2400
4Christian Jaros1000006300.00%12626.3000000000000.00%00.0000
5Trent Frederic1000001000.00%033.1300000000000.00%00.0000

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
1Callum Booth10100.9173.00600033623000.0000