Wolf Pack

GP: 8 | W: 7 | L: 0 | OTL: 1 | P: 15
GF: 27 | GA: 18 | PP%: 20.37% | PK%: 96.88%
DG: Sebastien Regnier | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #91 vs Monsters
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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
1Alexander TrueX100.00844594677855776365705556255656635000
2Kaapo Kakko (R)X100.00614192827267787434656861755252685000
3Rudolfs BalcersX100.00784399656162817326615859254949635000
4Johan LarssonX100.00794487817068856380655984256767695000
5Jack Hughes (R)XX100.00594094826272758469686055485151655000
6Isac LundestromX100.00614199806866687276725564254646645000
7Logan BrownX100.00674494628559697262755657254646635000
8Sam LaffertyXXX100.00845786677154806165626276254848675000
9Vitaly AbramovXX100.00686183696176796550626461614444655000
10Joachim Blichfeld (R)X100.00736983666972756450596564624444655000
11Vladislav KamenevXXX100.00734392807252566462645661255151625000
12Brendan LemieuxXX100.00939650837963786738655971755959675000
13Matt RoyX100.00844595627475876225544875255656625000
14Victor MeteX100.00634188816568826025514974256060625000
15Adam Boqvist (R)X100.00714294806469727425565060254747625000
16Ryan GravesX100.00815581818376815925595489255656685000
17Christian DjoosX100.00594099806277677925535070255961635000
18Alex Alexeyev (R)X100.00817790637767715125464164394444555000
Rayé
1Aleksi SaarelaX100.00767091667076806379616166584748655000
2Hayden VerbeekXX100.00726589546550524455384458424444505000
3Ryan Poehling (R)XX100.00794494776956675733545668254646625000
4Aleksi Heponiemi (R)XX100.00665689615663675063504657444444535000
5Rem Pitlick (R)XX100.00747082657066686075536263594444625000
6Kody Clark (R)X100.00716683606659625050494759454444545000
7Logan StanleyX100.00788756628768744725374162394444525000
MOYENNE D'ÉQUIPE100.0073558771706573634858556539505062500
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
1Kaapo KakkoWolf Pack (NYR)RW8459-600112244916.67%214317.912461044000001031.25%1600001.2612000111
2Jack HughesWolf Pack (NYR)C/LW8257-1005221721711.76%114217.801455400000110037.50%800000.9800000002
3Johan LarssonWolf Pack (NYR)C8336300722123725.00%212315.41000010001331054.36%14900000.9712000200
4Victor MeteWolf Pack (NYR)D81561202884912.50%317421.78123640000024000.00%000000.6900000101
5Vitaly AbramovWolf Pack (NYR)LW/RW824640011531040.00%011514.46123139000000116.67%600001.0400000010
6Brendan LemieuxWolf Pack (NYR)LW/RW8426-360196195921.05%115919.952028381013251027.27%1100000.7501000010
7Adam BoqvistWolf Pack (NYR)D8055020468660.00%416320.43011643000015000.00%000000.6100000010
8Ryan GravesWolf Pack (NYR)D8235-51002215153713.33%318322.972131034000024010.00%000000.5400000011
9Gabriel VilardiRangersC6224-400116122316.67%09816.39224530000001066.04%10600000.8100000001
10Logan BrownWolf Pack (NYR)C80330404116120.00%013516.93011139000170043.51%13100000.4400000000
11Sam LaffertyWolf Pack (NYR)C/LW/RW82135408891622.22%09211.62000000110151050.00%1200000.6500000100
12Alex AlexeyevWolf Pack (NYR)D512316052100100.00%16913.950000100002000.00%000000.8600000000
13Alexander TrueWolf Pack (NYR)C81120603881212.50%09311.73000011000010055.17%5800000.4300000000
14Matt RoyWolf Pack (NYR)D802242551751110.00%814518.2301109000018000.00%000000.2700001000
15Rudolfs BalcersWolf Pack (NYR)LW8022020472550.00%1779.740000000000000.00%200000.5100000000
16Joachim BlichfeldWolf Pack (NYR)RW82020406362433.33%09111.45000000002131050.00%200000.4400000000
17Isac LundestromWolf Pack (NYR)C2011-100053030.00%03216.13011112000000054.29%3500000.6200000000
18Christian DjoosWolf Pack (NYR)D8011-2002715280.00%319224.100111442000029000.00%000000.1000000000
19Vladislav KamenevWolf Pack (NYR)C/LW/RW8000020563130.00%19011.3400002000030050.00%200000.0000000000
Stats d'équipe Total ou en Moyenne141264773-47351161701744611114.94%30232716.501120316743211272276251.86%53800000.6325001556
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)87010.8612.0849000171220000.800580000
Stats d'équipe Total ou en Moyenne87010.8612.0849000171220000.800580000


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$1,561,311$1,744,167$1,561,311$0$0$No1,744,167$1,744,167$
Aleksi HeponiemiWolf Pack (NYR)C/RW211999-01-09Yes150 Lbs5 ft10NoNoNo3Pro & Farm1,775,000$1,588,911$1,775,000$1,588,911$0$0$No1,775,000$1,775,000$
Aleksi SaarelaWolf Pack (NYR)C231997-01-07No198 Lbs5 ft11NoNoNo3Pro & Farm1,152,500$1,031,673$902,500$807,883$0$0$No902,500$902,500$Lien
Alex AlexeyevWolf Pack (NYR)D201999-11-15Yes201 Lbs6 ft4NoNoNo3Pro & Farm894,167$800,424$450,000$402,823$0$0$No894,167$894,167$
Alexander TrueWolf Pack (NYR)C221997-07-17No201 Lbs6 ft5NoNoNo3Pro & Farm1,050,000$939,919$800,000$716,129$0$0$No800,000$800,000$Lien
Brendan LemieuxWolf Pack (NYR)LW/RW241996-03-14No210 Lbs6 ft1NoNoNo1Pro & Farm1,039,167$930,222$1,039,167$930,222$0$0$NoLien
Christian DjoosWolf Pack (NYR)D251994-08-06No169 Lbs6 ft0NoNoNo1Pro & Farm650,000$581,855$650,000$581,855$0$0$NoLien
Connor IngramWolf Pack (NYR)G231997-03-31No204 Lbs6 ft1NoNoNo2Pro & Farm925,000$828,024$925,000$828,024$0$0$No925,000$Lien
Hayden VerbeekWolf Pack (NYR)C/LW221997-10-17No183 Lbs5 ft10NoNoNo3Pro & Farm776,666$695,241$776,666$695,241$0$0$No776,666$776,666$Lien
Igor ShesterkinWolf Pack (NYR)G241995-12-30Yes187 Lbs6 ft1NoNoNo2Pro & Farm3,775,000$3,379,234$3,775,000$3,379,234$0$0$No3,775,000$
Isac LundestromWolf Pack (NYR)C201999-11-06No185 Lbs6 ft0NoNoNo2Pro & Farm925,000$828,024$450,000$402,823$0$0$No925,000$Lien
Jack HughesWolf Pack (NYR)C/LW192001-05-13Yes171 Lbs5 ft10NoNoNo3Pro & Farm3,775,000$3,379,234$3,775,000$3,379,234$0$0$No3,775,000$3,775,000$
Joachim BlichfeldWolf Pack (NYR)RW211998-07-16Yes180 Lbs6 ft2NoNoNo3Pro & Farm1,290,000$1,154,758$790,000$707,177$0$0$No790,000$790,000$Lien
Johan LarssonWolf Pack (NYR)C271992-07-25No198 Lbs5 ft11NoNoNo3Pro & Farm1,475,000$1,320,363$1,475,000$1,320,363$0$0$No1,475,000$1,475,000$Lien
Kaapo KakkoWolf Pack (NYR)RW192001-02-13Yes190 Lbs6 ft2NoNoNo3Pro & Farm3,575,000$3,200,202$3,575,000$3,200,202$0$0$No3,575,000$3,575,000$
Kody ClarkWolf Pack (NYR)RW201999-10-12Yes179 Lbs6 ft1NoNoNo3Pro & Farm894,167$800,424$894,167$800,424$0$0$No894,167$894,167$
Logan BrownWolf Pack (NYR)C221998-03-04No220 Lbs6 ft6NoNoNo2Pro & Farm1,573,333$1,408,387$1,573,333$1,408,387$0$0$No1,573,333$Lien
Logan StanleyWolf Pack (NYR)D221998-05-25No228 Lbs6 ft7NoNoNo2Pro & Farm1,075,833$963,044$1,075,833$963,044$0$0$No1,075,833$Lien
Matt RoyWolf Pack (NYR)D251995-02-28No200 Lbs6 ft1NoNoNo3Pro & Farm1,200,000$1,074,194$700,000$626,613$0$0$No700,000$700,000$Lien
Rem PitlickWolf Pack (NYR)C/LW231997-04-01Yes196 Lbs5 ft11NoNoNo3Pro & Farm925,000$828,024$925,000$828,024$0$0$No925,000$925,000$
Rudolfs BalcersWolf Pack (NYR)LW231997-04-08No165 Lbs5 ft11NoNoNo2Pro & Farm925,000$828,024$925,000$828,024$0$0$No925,000$Lien
Ryan GravesWolf Pack (NYR)D251995-05-20No216 Lbs6 ft5NoNoNo2Pro & Farm650,000$581,855$650,000$581,855$0$0$No650,000$Lien
Ryan PoehlingWolf Pack (NYR)C/LW211999-01-02Yes183 Lbs6 ft2NoNoNo3Pro & Farm1,491,667$1,335,283$1,491,667$1,335,283$0$0$No1,491,667$1,491,667$
Sam LaffertyWolf Pack (NYR)C/LW/RW251995-03-06No194 Lbs6 ft1NoNoNo3Pro & Farm975,000$872,782$925,000$828,024$0$0$No925,000$925,000$Lien
Victor MeteWolf Pack (NYR)D221998-06-07No184 Lbs5 ft10NoNoNo1Pro & Farm870,000$778,790$870,000$778,790$0$0$NoLien
Vitaly AbramovWolf Pack (NYR)LW/RW221998-05-08No172 Lbs5 ft9NoNoNo2Pro & Farm880,000$787,742$880,000$787,742$0$0$No880,000$Lien
Vladislav KamenevWolf Pack (NYR)C/LW/RW231996-08-12No194 Lbs6 ft2NoNoNo3Pro & Farm800,000$716,129$750,000$671,371$0$0$No750,000$750,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2722.30190 Lbs6 ft12.481,373,395$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Brendan LemieuxLogan BrownKaapo Kakko35023
2Jack HughesIsac LundestromVladislav Kamenev30023
3Sam LaffertyJohan LarssonVitaly Abramov25032
4Rudolfs BalcersAlexander TrueJoachim Blichfeld10032
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan GravesChristian Djoos35122
2Matt RoyVictor Mete30122
3Adam BoqvistAlex Alexeyev25122
4Ryan GravesChristian Djoos10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jack HughesLogan BrownKaapo Kakko60122
2Brendan LemieuxIsac LundestromVitaly Abramov40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Adam BoqvistChristian Djoos60122
2Ryan GravesVictor Mete40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Johan LarssonBrendan Lemieux60122
2Sam LaffertyJoachim Blichfeld40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan GravesChristian Djoos60122
2Matt RoyVictor Mete40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Johan Larsson60122Ryan GravesChristian Djoos60122
2Sam Lafferty40122Matt RoyVictor Mete40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Johan LarssonKaapo Kakko60122
2Brendan LemieuxJack Hughes40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan GravesChristian Djoos60122
2Matt RoyVictor Mete40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jack HughesLogan BrownKaapo KakkoRyan GravesChristian Djoos
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Brendan LemieuxJohan LarssonKaapo KakkoRyan GravesMatt Roy
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Logan Brown, Alexander True, Johan LarssonLogan Brown, Alexander TrueJohan Larsson
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Adam Boqvist, Matt Roy, Victor MeteAdam BoqvistMatt Roy, Victor Mete
Tirs de Pénalité
Johan Larsson, 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
1Penguins11000000532000000000001100000053221.0005101500119622452625961334115240.00%20100.00%011822951.53%10519354.40%5611648.28%216155178589449
2Phantoms3200000110821000000145-12200000063350.83310192900119626852625965516324322522.73%150100.00%011822951.53%10519354.40%5611648.28%216155178589449
3Sound Tigers11000000321110000003210000000000021.00036900119622852625962161215900.00%6183.33%011822951.53%10519354.40%5611648.28%216155178589449
Total86000011271894200001112102440000001587150.938274774001196217452625961223373117541120.37%32196.88%111822951.53%10519354.40%5611648.28%216155178589449
5Wolves32000010954210000105321100000042261.000912210011962545262596338254818422.22%90100.00%111822951.53%10519354.40%5611648.28%216155178589449
_Since Last GM Reset86000011271894200001112102440000001587150.938274774001196217452625961223373117541120.37%32196.88%111822951.53%10519354.40%5611648.28%216155178589449
_Vs Conference43000001151141000000145-133000000116570.87515294400119629252625966819365427725.93%170100.00%011822951.53%10519354.40%5611648.28%216155178589449
_Vs Division53000001181352000000177033000000116570.700183553001196212052625968925486936719.44%23195.65%011822951.53%10519354.40%5611648.28%216155178589449

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
815W7274774174122337311700
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
86000112718
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
42000111210
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4400000158
Derniers 10 Matchs
WLOTWOTL SOWSOL
700001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
541120.37%32196.88%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
526259611962
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
11822951.53%10519354.40%5611648.28%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
216155178589449


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 - 2020-10-1091Monsters-Wolf Pack-
17 - 2020-10-13110IceHogs-Wolf Pack-
19 - 2020-10-15120Wolf Pack-Bruins-
21 - 2020-10-17134Penguins-Wolf Pack-
22 - 2020-10-18140Wolf Pack-Sound Tigers-
24 - 2020-10-20156Phantoms-Wolf Pack-
26 - 2020-10-22172Wolf Pack-Flames-
27 - 2020-10-23181Senators-Wolf Pack-
28 - 2020-10-24188Wolf Pack-Sound Tigers-
30 - 2020-10-26198Wolf Pack-Admirals-
32 - 2020-10-28209Wolves-Wolf Pack-
34 - 2020-10-30224Phantoms-Wolf Pack-
36 - 2020-11-01232Wolf Pack-Flames-
38 - 2020-11-03244Sound Tigers-Wolf Pack-
40 - 2020-11-05260Marlies-Wolf Pack-
42 - 2020-11-07268Wolf Pack-Sound Tigers-
44 - 2020-11-09280Wolf Pack-Marlies-
45 - 2020-11-10287Wolf Pack-Phantoms-
46 - 2020-11-11295Monsters-Wolf Pack-
48 - 2020-11-13309Monsters-Wolf Pack-
49 - 2020-11-14318Wolf Pack-Penguins-
51 - 2020-11-16334Rocket-Wolf Pack-
52 - 2020-11-17347Wolf Pack-Monsters-
53 - 2020-11-18356Griffins-Wolf Pack-
54 - 2020-11-19362Wolf Pack-Monsters-
55 - 2020-11-20377Bruins-Wolf Pack-
57 - 2020-11-22390Wolf Pack-Admirals-
58 - 2020-11-23399Wolf Pack-Wolves-
59 - 2020-11-24408Crunch-Wolf Pack-
60 - 2020-11-25421Stars-Wolf Pack-
62 - 2020-11-27433Condors-Wolf Pack-
64 - 2020-11-29445Wolf Pack-Condors-
65 - 2020-11-30457Wolf Pack-Crunch-
66 - 2020-12-01465Sharks-Wolf Pack-
68 - 2020-12-03479Wolf Pack-Griffins-
69 - 2020-12-04487Rocket-Wolf Pack-
71 - 2020-12-06498Wolf Pack-Rocket-
72 - 2020-12-07509Wolf Pack-Flames-
73 - 2020-12-08518Phantoms-Wolf Pack-
74 - 2020-12-09529Wolf Pack-Marlies-
76 - 2020-12-11541Penguins-Wolf Pack-
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
37 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
501,475$ 3,708,168$ 3,456,251$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 399,261$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 111 37,767$ 4,192,137$




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
20208600001127189420000111210244000000158715274774001196217452625961223373117541120.37%32196.88%111822951.53%10519354.40%5611648.28%216155178589449
Total Saison Régulière8600001127189420000111210244000000158715274774001196217452625961223373117541120.37%32196.88%111822951.53%10519354.40%5611648.28%216155178589449