Wolf Pack

GP: 49 | W: 32 | L: 14 | OTL: 3 | P: 67
GF: 125 | GA: 99 | PP%: 13.49% | PK%: 86.67%
DG: Sebastien Regnier | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #553 vs Moose
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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
1Aleksi SaarelaX100.007670916670768063796161665847486550002331,152,500$
2Alexander TrueX100.008445946778557763657055562556566350002231,050,000$
3Kaapo Kakko (R)X100.006141928272677874346568617552526850001933,575,000$
4Rudolfs BalcersX100.00784399656162817326615859254949635000232925,000$
5Jack Hughes (R)XX100.005940948262727584696860554851516550001933,775,000$
6Isac LundestromX100.00614199806866687276725564254646645000202925,000$
7Logan BrownX100.006744946285596972627556572546466350002221,573,333$
8Sam LaffertyXXX100.00845786677154806165626276254848675000253975,000$
9Vitaly AbramovXX100.00686183696176796550626461614444655000222880,000$
10Gabriel Vilardi (R)X100.005741878076634868877575542544446954002031,627,000$
11Joachim Blichfeld (R)X100.007369836669727564505965646244446550002131,290,000$
12Rem Pitlick (R)XX100.00747082657066686075536263594444625000233925,000$
13Vladislav KamenevXXX100.00734392807252566462645661255151625000233800,000$
14Brendan LemieuxXX100.009396508379637867386559717559596750002411,039,167$
15Matt RoyX100.008445956274758762255448752556566250002531,200,000$
16Adam Boqvist (R)X100.007142948064697274255650602547476250001931,744,167$
17Ryan GravesX100.00815581818376815925595489255656685000252650,000$
18Christian DjoosX100.00594099806277677925535070255961635000251650,000$
Rayé
1Hayden VerbeekXX100.00726589546550524455384458424444505000223776,666$
2Aleksi Heponiemi (R)XX100.006656896156636750635046574444445350002131,775,000$
3Kody Clark (R)X100.00716683606659625050494759454444545000203894,167$
4Logan StanleyX100.007887566287687447253741623944445250002221,075,833$
5Alex Alexeyev (R)X100.00817790637767715125464164394444555000203894,167$
MOYENNE D'ÉQUIPE100.0073568770716672645059566440494962500
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
1Connor Ingram100.0069648076707172777373304444705000
2Igor Shesterkin (R)100.0069636071776288697769754545715000
Rayé
MOYENNE D'ÉQUIPE100.006964707474678073757153454571500
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Steve Ott70656067545089CAN393975,000$


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
1Jack HughesWolf Pack (NYR)C/LW4918183641002269100177618.00%488718.115914322540000905243.48%4600000.8101000623
2Kaapo KakkoWolf Pack (NYR)RW49141731-2001161106295913.21%684017.15591428243000004337.25%5100000.7425000542
3Ryan GravesWolf Pack (NYR)D496202611760118606917458.70%32104221.274610492190000151010.00%000100.5000000241
4Brendan LemieuxWolf Pack (NYR)LW/RW4914122628601457888237015.91%1195719.5373103123011261593236.49%7400000.5413000152
5Logan BrownWolf Pack (NYR)C49619256321048624263114.29%484117.181111282430002581251.38%83500000.5900011131
6Adam BoqvistWolf Pack (NYR)D4932124-1212027324316326.98%2591118.603101334264000075000.00%000000.5300000012
7Sam LaffertyWolf Pack (NYR)C/LW/RW4911112212300565366195616.67%1165213.33000050110961051.85%5400000.6700000235
8Christian DjoosWolf Pack (NYR)D492182014808406724352.99%25110122.481910582540001182000.00%000000.3600000010
9Isac LundestromWolf Pack (NYR)C431181922012786018401.67%261914.400448460000740058.47%53700000.6101000001
10Vitaly AbramovWolf Pack (NYR)LW/RW4981018100143348125416.67%060712.40741126238000001146.67%3000000.5900000011
11Vladislav KamenevWolf Pack (NYR)C/LW/RW4951318720053343592514.29%756611.571013220000192269.57%2300000.6400000113
12Gabriel VilardiWolf Pack (NYR)C41411152001815617567.14%168816.7924617193000071063.72%75800000.4400000002
13Rem PitlickWolf Pack (NYR)C/LW35113147235222657103519.30%742412.1400037000017070.00%2000100.6600001322
14Johan LarssonRangersC/LW4849134120331044719448.51%1665613.6901134900012082057.99%73800000.4025000211
15Matt RoyWolf Pack (NYR)D492810-1751586233511175.71%3993419.07145241801011163000.00%000000.2100012001
16Rudolfs BalcersWolf Pack (NYR)LW49459-2120182725112616.00%23727.6010110000002113.33%1500000.4800000200
17Alex AlexeyevWolf Pack (NYR)D212460200266204100.00%631415.00101115000011000.00%000000.3800000100
18Alexander TrueWolf Pack (NYR)C142241801010121316.67%016211.58000018000030151.00%10000000.4900000001
19Joachim BlichfeldWolf Pack (NYR)RW142131401271241016.67%015911.42000000002231025.00%400000.3800000000
20Logan StanleyWolf Pack (NYR)D101014261024120050.00%815915.9400000000025000.00%000000.1300002001
Stats d'équipe Total ou en Moyenne814120220340614564074688597226371812.35%2061290115.8539741133262489224131354301556.19%328500200.53515026262829
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
1Igor ShesterkinWolf Pack (NYR)49321430.8861.97289803958320200.71414490300
2Connor IngramWolf Pack (NYR)30000.9500.9166001200000.0000049000
Stats d'équipe Total ou en Moyenne52321430.8871.94296403968520200.714144949300


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
Adam BoqvistWolf Pack (NYR)D192000-08-14Yes179 Lbs5 ft11NoNoNo3Pro & Farm1,744,167$661,096$1,744,167$661,096$0$0$No1,744,167$1,744,167$
Aleksi HeponiemiWolf Pack (NYR)C/RW211999-01-09Yes150 Lbs5 ft10NoNoNo3Pro & Farm1,775,000$672,782$1,775,000$672,782$0$0$No1,775,000$1,775,000$
Aleksi SaarelaWolf Pack (NYR)C231997-01-07No198 Lbs5 ft11NoNoNo3Pro & Farm1,152,500$436,835$902,500$342,077$0$0$No902,500$902,500$Lien
Alex AlexeyevWolf Pack (NYR)D201999-11-15Yes201 Lbs6 ft4NoNoNo3Pro & Farm894,167$338,918$450,000$170,565$0$0$No894,167$894,167$
Alexander TrueWolf Pack (NYR)C221997-07-17No201 Lbs6 ft5NoNoNo3Pro & Farm1,050,000$397,984$800,000$303,226$0$0$No800,000$800,000$Lien
Brendan LemieuxWolf Pack (NYR)LW/RW241996-03-14No210 Lbs6 ft1NoNoNo1Pro & Farm1,039,167$393,878$1,039,167$393,878$0$0$NoLien
Christian DjoosWolf Pack (NYR)D251994-08-06No169 Lbs6 ft0NoNoNo1Pro & Farm650,000$246,371$650,000$246,371$0$0$NoLien
Connor IngramWolf Pack (NYR)G231997-03-31No204 Lbs6 ft1NoNoNo2Pro & Farm925,000$350,605$925,000$350,605$0$0$No925,000$Lien
Gabriel VilardiWolf Pack (NYR)C201999-08-15Yes201 Lbs6 ft3NoNoNo3Pro & Farm1,627,000$616,685$1,627,000$616,685$0$0$No1,627,000$1,627,000$
Hayden VerbeekWolf Pack (NYR)C/LW221997-10-17No183 Lbs5 ft10NoNoNo3Pro & Farm776,666$294,381$776,666$294,381$0$0$No776,666$776,666$Lien
Igor ShesterkinWolf Pack (NYR)G241995-12-30Yes187 Lbs6 ft1NoNoNo2Pro & Farm3,775,000$1,430,847$3,775,000$1,430,847$0$0$No3,775,000$
Isac LundestromWolf Pack (NYR)C201999-11-06No185 Lbs6 ft0NoNoNo2Pro & Farm925,000$350,605$450,000$170,565$0$0$No925,000$Lien
Jack HughesWolf Pack (NYR)C/LW192001-05-13Yes171 Lbs5 ft10NoNoNo3Pro & Farm3,775,000$1,430,847$3,775,000$1,430,847$0$0$No3,775,000$3,775,000$
Joachim BlichfeldWolf Pack (NYR)RW211998-07-16Yes180 Lbs6 ft2NoNoNo3Pro & Farm1,290,000$488,952$790,000$299,435$0$0$No790,000$790,000$Lien
Kaapo KakkoWolf Pack (NYR)RW192001-02-13Yes190 Lbs6 ft2NoNoNo3Pro & Farm3,575,000$1,355,040$3,575,000$1,355,040$0$0$No3,575,000$3,575,000$
Kody ClarkWolf Pack (NYR)RW201999-10-12Yes179 Lbs6 ft1NoNoNo3Pro & Farm894,167$338,918$894,167$338,918$0$0$No894,167$894,167$
Logan BrownWolf Pack (NYR)C221998-03-04No220 Lbs6 ft6NoNoNo2Pro & Farm1,573,333$596,344$1,573,333$596,344$0$0$No1,573,333$Lien
Logan StanleyWolf Pack (NYR)D221998-05-25No228 Lbs6 ft7NoNoNo2Pro & Farm1,075,833$407,775$1,075,833$407,775$0$0$No1,075,833$Lien
Matt RoyWolf Pack (NYR)D251995-02-28No200 Lbs6 ft1NoNoNo3Pro & Farm1,200,000$454,839$700,000$265,323$0$0$No700,000$700,000$Lien
Rem PitlickWolf Pack (NYR)C/LW231997-04-01Yes196 Lbs5 ft11NoNoNo3Pro & Farm925,000$350,605$925,000$350,605$0$0$No925,000$925,000$
Rudolfs BalcersWolf Pack (NYR)LW231997-04-08No165 Lbs5 ft11NoNoNo2Pro & Farm925,000$350,605$925,000$350,605$0$0$No925,000$Lien
Ryan GravesWolf Pack (NYR)D251995-05-20No216 Lbs6 ft5NoNoNo2Pro & Farm650,000$246,371$650,000$246,371$0$0$No650,000$Lien
Sam LaffertyWolf Pack (NYR)C/LW/RW251995-03-06No194 Lbs6 ft1NoNoNo3Pro & Farm975,000$369,556$925,000$350,605$0$0$No925,000$925,000$Lien
Vitaly AbramovWolf Pack (NYR)LW/RW221998-05-08No172 Lbs5 ft9NoNoNo2Pro & Farm880,000$333,548$880,000$333,548$0$0$No880,000$Lien
Vladislav KamenevWolf Pack (NYR)C/LW/RW231996-08-12No194 Lbs6 ft2NoNoNo3Pro & Farm800,000$303,226$750,000$284,274$0$0$No750,000$750,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2522.08191 Lbs6 ft12.521,394,880$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Brendan LemieuxGabriel VilardiKaapo Kakko35023
2Jack HughesLogan BrownVladislav Kamenev30023
3Rem PitlickIsac LundestromSam Lafferty25032
4Rudolfs BalcersVitaly Abramov10032
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan GravesChristian Djoos35122
2Matt RoyAdam Boqvist30122
325122
4Ryan GravesChristian Djoos10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jack HughesLogan BrownKaapo Kakko60122
2Brendan LemieuxGabriel VilardiVitaly Abramov40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Adam BoqvistChristian Djoos60122
2Ryan GravesMatt Roy40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Brendan Lemieux60122
2Isac LundestromSam Lafferty40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan GravesChristian Djoos60122
2Matt Roy40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Ryan GravesChristian Djoos60122
2Sam Lafferty40122Matt Roy40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Gabriel VilardiKaapo Kakko60122
2Brendan LemieuxJack Hughes40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan GravesChristian Djoos60122
2Matt RoyAdam Boqvist40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jack HughesGabriel VilardiKaapo KakkoRyan GravesChristian Djoos
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Brendan LemieuxKaapo KakkoRyan GravesMatt Roy
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Logan Brown, Gabriel Vilardi, Logan Brown,
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Adam Boqvist, Matt Roy, Adam BoqvistMatt Roy, Adam Boqvist
Tirs de Pénalité
, Kaapo Kakko, Brendan Lemieux, Jack Hughes, Isac Lundestrom
Gardien
#1 : Igor Shesterkin, #2 : Connor Ingram


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
1Admirals2110000023-1000000000002110000023-120.5002460044453363132633932122309412610110.00%11281.82%0764138155.32%721125357.54%36666854.79%12869111094353586304
2Bruins21000001440110000002111000000123-130.75048120044453364132633932122391214271417.14%70100.00%0764138155.32%721125357.54%36666854.79%12869111094353586304
3Condors22000000725110000003121100000041341.0007121900444533652326339321223411162721314.29%8187.50%0764138155.32%721125357.54%36666854.79%12869111094353586304
4Crunch21100000844110000005051010000034-120.5008122001444533645326339321224411182915213.33%90100.00%1764138155.32%721125357.54%36666854.79%12869111094353586304
5Flames32100000633000000000003210000063340.667611170144453365832633932122571938492229.09%19289.47%0764138155.32%721125357.54%36666854.79%12869111094353586304
6Griffins22000000642110000004311100000021141.00061218004445336453263393212239132928900.00%10370.00%0764138155.32%721125357.54%36666854.79%12869111094353586304
7IceHogs1010000013-21010000013-20000000000000.000123004445336193263393212217212176116.67%6183.33%0764138155.32%721125357.54%36666854.79%12869111094353586304
8Marlies330000001165110000004222200000074361.0001120310044453367232633932122521132621516.67%16381.25%0764138155.32%721125357.54%36666854.79%12869111094353586304
9Monsters541000001394330000009542110000044080.80013253800444533691326339321226723377729620.69%15286.67%0764138155.32%721125357.54%36666854.79%12869111094353586304
10Penguins41200010990201000103302110000066040.5009152400444533690326339321226516487822313.64%24387.50%0764138155.32%721125357.54%36666854.79%12869111094353586304
11Phantoms742000012015542100001131033210000075290.64320385801444533613432633932122119357110749816.33%31293.55%0764138155.32%721125357.54%36666854.79%12869111094353586304
12Rocket3020000138-52020000026-41000000112-110.1673690044453365732633932122661126621616.25%11190.91%0764138155.32%721125357.54%36666854.79%12869111094353586304
13Senators11000000321110000003210000000000021.00036900444533624326339321221346147114.29%30100.00%0764138155.32%721125357.54%36666854.79%12869111094353586304
14Sharks1010000025-31010000025-30000000000000.0002460044453362132633932122211010185120.00%5260.00%0764138155.32%721125357.54%36666854.79%12869111094353586304
15Sound Tigers522010001012-2210010006423120000048-460.60010203000444533696326339321221033052992926.90%25772.00%0764138155.32%721125357.54%36666854.79%12869111094353586304
16Stars11000000422110000004220000000000021.000481200444533621326339321222251012500.00%50100.00%0764138155.32%721125357.54%36666854.79%12869111094353586304
Total4929140102312599262515601021695118241480000256488670.684125228353034445336993326339321228522395168233044113.49%2253086.67%2764138155.32%721125357.54%36666854.79%12869111094353586304
17Wolves5400001016883200001084422000000844101.00016254100444533696326339321226417569130826.67%20195.00%1764138155.32%721125357.54%36666854.79%12869111094353586304
_Since Last GM Reset4929140102312599262515601021695118241480000256488670.684125228353034445336993326339321228522395168233044113.49%2253086.67%2764138155.32%721125357.54%36666854.79%12869111094353586304
_Vs Conference301790001377601715940001141291215850000236315390.65077141218034445336612326339321225221422905051892513.23%1351390.37%1764138155.32%721125357.54%36666854.79%12869111094353586304
_Vs Division211160001152457115200011312291064000002123-2250.5955298150014445336411326339321223541042083611291914.73%951485.26%0764138155.32%721125357.54%36666854.79%12869111094353586304

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4967L112522835399385223951682303
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
492914102312599
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2515610216951
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2414800025648
Derniers 10 Matchs
WLOTWOTL SOWSOL
540001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3044113.49%2253086.67%2
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
326339321224445336
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
764138155.32%721125357.54%36666854.79%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
12869111094353586304


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 - 2020-09-271Phantoms5Wolf Pack4LXXSommaire du Match
3 - 2020-09-2923Wolves1Wolf Pack2WSommaire du Match
4 - 2020-09-3031Wolf Pack4Wolves2WSommaire du Match
5 - 2020-10-0143Wolves2Wolf Pack3WXXSommaire du Match
7 - 2020-10-0354Wolf Pack5Penguins3WSommaire du Match
8 - 2020-10-0461Wolf Pack2Phantoms1WSommaire du Match
10 - 2020-10-0675Wolf Pack4Phantoms2WSommaire du Match
12 - 2020-10-0885Sound Tigers2Wolf Pack3WSommaire du Match
14 - 2020-10-1091Monsters3Wolf Pack5WSommaire du Match
17 - 2020-10-13110IceHogs3Wolf Pack1LSommaire du Match
19 - 2020-10-15120Wolf Pack2Bruins3LXXSommaire du Match
21 - 2020-10-17134Penguins2Wolf Pack3WXXSommaire du Match
22 - 2020-10-18140Wolf Pack3Sound Tigers1WSommaire du Match
24 - 2020-10-20156Phantoms3Wolf Pack2LSommaire du Match
26 - 2020-10-22172Wolf Pack1Flames2LSommaire du Match
27 - 2020-10-23181Senators2Wolf Pack3WSommaire du Match
28 - 2020-10-24188Wolf Pack0Sound Tigers4LSommaire du Match
30 - 2020-10-26198Wolf Pack2Admirals1WSommaire du Match
32 - 2020-10-28209Wolves1Wolf Pack3WSommaire du Match
34 - 2020-10-30224Phantoms0Wolf Pack3WSommaire du Match
36 - 2020-11-01232Wolf Pack3Flames1WSommaire du Match
38 - 2020-11-03244Sound Tigers2Wolf Pack3WXSommaire du Match
40 - 2020-11-05260Marlies2Wolf Pack4WSommaire du Match
42 - 2020-11-07268Wolf Pack1Sound Tigers3LSommaire du Match
44 - 2020-11-09280Wolf Pack4Marlies2WSommaire du Match
45 - 2020-11-10287Wolf Pack1Phantoms2LSommaire du Match
46 - 2020-11-11295Monsters1Wolf Pack2WSommaire du Match
48 - 2020-11-13309Monsters1Wolf Pack2WSommaire du Match
49 - 2020-11-14318Wolf Pack1Penguins3LSommaire du Match
51 - 2020-11-16334Rocket2Wolf Pack1LSommaire du Match
52 - 2020-11-17347Wolf Pack1Monsters2LSommaire du Match
53 - 2020-11-18356Griffins3Wolf Pack4WSommaire du Match
54 - 2020-11-19362Wolf Pack3Monsters2WSommaire du Match
55 - 2020-11-20377Bruins1Wolf Pack2WSommaire du Match
57 - 2020-11-22390Wolf Pack0Admirals2LSommaire du Match
58 - 2020-11-23399Wolf Pack4Wolves2WSommaire du Match
59 - 2020-11-24408Crunch0Wolf Pack5WSommaire du Match
60 - 2020-11-25421Stars2Wolf Pack4WSommaire du Match
62 - 2020-11-27433Condors1Wolf Pack3WSommaire du Match
64 - 2020-11-29445Wolf Pack4Condors1WSommaire du Match
65 - 2020-11-30457Wolf Pack3Crunch4LSommaire du Match
66 - 2020-12-01465Sharks5Wolf Pack2LSommaire du Match
68 - 2020-12-03479Wolf Pack2Griffins1WSommaire du Match
69 - 2020-12-04487Rocket4Wolf Pack1LSommaire du Match
71 - 2020-12-06498Wolf Pack1Rocket2LXXSommaire du Match
72 - 2020-12-07509Wolf Pack2Flames0WSommaire du Match
73 - 2020-12-08518Phantoms2Wolf Pack4WSommaire du Match
74 - 2020-12-09529Wolf Pack3Marlies2WSommaire du Match
76 - 2020-12-11541Penguins1Wolf Pack0LSommaire du Match
78 - 2020-12-13553Wolf Pack-Moose-
79 - 2020-12-14560Monarchs-Wolf Pack-
80 - 2020-12-15571Wolf Pack-Monarchs-
81 - 2020-12-16583Wolf Pack-Wolves-
83 - 2020-12-18594Rampage-Wolf Pack-
85 - 2020-12-20607Crunch-Wolf Pack-
86 - 2020-12-21618Penguins-Wolf Pack-
87 - 2020-12-22629Wolf Pack-Bruins-
89 - 2020-12-24638Wolf Pack-IceHogs-
91 - 2020-12-26648Flames-Wolf Pack-
92 - 2020-12-27663Sound Tigers-Wolf Pack-
94 - 2020-12-29672Wolf Pack-Stars-
95 - 2020-12-30680Wolf Pack-Sharks-
96 - 2020-12-31694Moose-Wolf Pack-
97 - 2021-01-01705Wolf Pack-Monsters-
98 - 2021-01-02712Monsters-Wolf Pack-
99 - 2021-01-03724Wolf Pack-Rampage-
101 - 2021-01-05735Griffins-Wolf Pack-
102 - 2021-01-06748Wolf Pack-Phantoms-
103 - 2021-01-07754Wolf Pack-Penguins-
104 - 2021-01-08765Penguins-Wolf Pack-
105 - 2021-01-09776Wolf Pack-Penguins-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
107 - 2021-01-11787Admirals-Wolf Pack-
108 - 2021-01-12798Wolf Pack-Senators-
109 - 2021-01-13804Wolf Pack-Sound Tigers-
111 - 2021-01-15816Senators-Wolf Pack-
112 - 2021-01-16830Griffins-Wolf Pack-
113 - 2021-01-17838Wolf Pack-Soldiers-
115 - 2021-01-19849Wolves-Wolf Pack-
117 - 2021-01-21864Sound Tigers-Wolf Pack-
118 - 2021-01-22871Wolf Pack-Crunch-
119 - 2021-01-23882Wolf Pack-Monsters-
122 - 2021-01-26894Soldiers-Wolf Pack-



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
16 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,881,713$ 3,487,201$ 3,235,284$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 2,276,280$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 47 35,985$ 1,691,295$




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