Wolf Pack

GP: 8 | W: 2 | L: 5 | OTL: 1 | P: 5
GF: 18 | GA: 22 | PP%: 19.57% | PK%: 86.84%
DG: Sebastien Regnier | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #97 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
10Gabriel Vilardi (R)X100.00574187807663486887757554254444695000
11Joachim Blichfeld (R)X100.00736983666972756450596564624444655000
12Vladislav KamenevXXX100.00734392807252566462645661255151625000
13Brendan LemieuxXX100.00939650837963786738655971755959675000
14Matt RoyX100.00844595627475876225544875255656625000
15Victor MeteX100.00634188816568826025514974256060625000
16Adam Boqvist (R)X100.00714294806469727425565060254747625000
17Ryan GravesX100.00815581818376815925595489255656685000
18Christian DjoosX100.00594099806277677925535070255961635000
19Alex 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'ÉQUIPE100.0073558771706572635059556538505062500
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)100.0069636071776288697769754545714500
Rayé
MOYENNE D'ÉQUIPE100.006964707474678073757153454571480
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
1Gabriel VilardiWolf Pack (NYR)C8257-12019101820.00%013316.62134237000000058.28%15100001.0500000010
2Kaapo KakkoWolf Pack (NYR)RW8426-100392251318.18%014317.94224837000000050.00%800000.8411000011
3Ryan GravesWolf Pack (NYR)D8325-31201215113227.27%618423.042241030000026100.00%000000.5400000010
4Jack HughesWolf Pack (NYR)C/LW8134-400414117139.09%013617.07033337000000062.50%800000.5900000001
5Victor MeteWolf Pack (NYR)D8314-3604982737.50%1117421.81314535000030000.00%000000.4600000100
6Logan BrownWolf Pack (NYR)C8123-3006590411.11%113016.36123431000000061.47%10900000.4600000000
7Adam BoqvistWolf Pack (NYR)D8033-21201065230.00%615819.83000436000110000.00%000000.3800000000
8Christian DjoosWolf Pack (NYR)D8033-42015104100.00%419123.96022934000031000.00%000000.3100000000
9Brendan LemieuxWolf Pack (NYR)LW/RW8033-1315271111590.00%114217.780223290000230063.64%1100000.4200001000
10Alexander TrueWolf Pack (NYR)C81120606850320.00%0769.5100008000000053.85%6500000.5300000000
11Rudolfs BalcersWolf Pack (NYR)LW81120002382212.50%0617.6300000000000066.67%300000.6600000000
12Vitaly AbramovWolf Pack (NYR)LW/RW8022-460256360.00%011514.46011333000000036.36%1100000.3500000000
13Joachim BlichfeldWolf Pack (NYR)RW8022055553160.00%0779.6700000000017000.00%200000.5200100000
14Matt RoyWolf Pack (NYR)D8011-41352373130.00%815219.11000210000031000.00%000000.1300001000
15Johan LarssonWolf Pack (NYR)C8011-46041810380.00%212515.73000010001330058.09%13600000.1611000000
16Sam LaffertyWolf Pack (NYR)C/LW/RW8101-46071084312.50%110112.66000010000160066.67%1200000.2000000000
17Vladislav KamenevWolf Pack (NYR)C/LW/RW8011-3008410140.00%19311.7100003000000025.00%400000.2100000000
18Alex AlexeyevWolf Pack (NYR)D7000-3402000000.00%610014.380000200001000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne143173350-44111151451431504410411.33%47229916.08918275337000022211057.69%52000000.4322102132
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
1Connor IngramWolf Pack (NYR)31010.8842.03148005430000.667328000
2Igor ShesterkinWolf Pack (NYR)61500.8433.0133900171080000.000060000
Stats d'équipe Total ou en Moyenne92510.8542.7148800221510000.667388000


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$1,744,167$1,744,167$1,744,167$0$0$No1,744,167$1,744,167$
Aleksi HeponiemiWolf Pack (NYR)C/RW211999-01-09Yes150 Lbs5 ft10NoNoNo3Pro & Farm1,775,000$1,775,000$1,775,000$1,775,000$0$0$No1,775,000$1,775,000$
Aleksi SaarelaWolf Pack (NYR)C231997-01-07No198 Lbs5 ft11NoNoNo3Pro & Farm1,152,500$1,152,500$902,500$902,500$0$0$No902,500$902,500$Lien
Alex AlexeyevWolf Pack (NYR)D201999-11-15Yes201 Lbs6 ft4NoNoNo3Pro & Farm894,167$894,167$450,000$450,000$0$0$No894,167$894,167$
Alexander TrueWolf Pack (NYR)C221997-07-17No201 Lbs6 ft5NoNoNo3Pro & Farm1,050,000$1,050,000$800,000$800,000$0$0$No800,000$800,000$Lien
Brendan LemieuxWolf Pack (NYR)LW/RW241996-03-14No210 Lbs6 ft1NoNoNo1Pro & Farm1,039,167$1,039,167$1,039,167$1,039,167$0$0$NoLien
Christian DjoosWolf Pack (NYR)D251994-08-06No169 Lbs6 ft0NoNoNo1Pro & Farm650,000$650,000$650,000$650,000$0$0$NoLien
Connor IngramWolf Pack (NYR)G231997-03-31No204 Lbs6 ft1NoNoNo2Pro & Farm925,000$925,000$925,000$925,000$0$0$No925,000$Lien
Gabriel VilardiWolf Pack (NYR)C201999-08-15Yes201 Lbs6 ft3NoNoNo3Pro & Farm1,627,000$1,627,000$1,627,000$1,627,000$0$0$No1,627,000$1,627,000$
Hayden VerbeekWolf Pack (NYR)C/LW221997-10-17No183 Lbs5 ft10NoNoNo3Pro & Farm776,666$776,666$776,666$776,666$0$0$No776,666$776,666$Lien
Igor ShesterkinWolf Pack (NYR)G241995-12-30Yes187 Lbs6 ft1NoNoNo2Pro & Farm3,775,000$3,775,000$3,775,000$3,775,000$0$0$No3,775,000$
Isac LundestromWolf Pack (NYR)C201999-11-06No185 Lbs6 ft0NoNoNo2Pro & Farm925,000$925,000$450,000$450,000$0$0$No925,000$Lien
Jack HughesWolf Pack (NYR)C/LW192001-05-13Yes171 Lbs5 ft10NoNoNo3Pro & Farm3,775,000$3,775,000$3,775,000$3,775,000$0$0$No3,775,000$3,775,000$
Joachim BlichfeldWolf Pack (NYR)RW211998-07-16Yes180 Lbs6 ft2NoNoNo3Pro & Farm1,290,000$1,290,000$790,000$790,000$0$0$No790,000$790,000$Lien
Johan LarssonWolf Pack (NYR)C271992-07-25No198 Lbs5 ft11NoNoNo3Pro & Farm1,475,000$1,475,000$1,475,000$1,475,000$0$0$No1,475,000$1,475,000$Lien
Kaapo KakkoWolf Pack (NYR)RW192001-02-13Yes190 Lbs6 ft2NoNoNo3Pro & Farm3,575,000$3,575,000$3,575,000$3,575,000$0$0$No3,575,000$3,575,000$
Kody ClarkWolf Pack (NYR)RW201999-10-12Yes179 Lbs6 ft1NoNoNo3Pro & Farm894,167$894,167$894,167$894,167$0$0$No894,167$894,167$
Logan BrownWolf Pack (NYR)C221998-03-04No220 Lbs6 ft6NoNoNo2Pro & Farm1,573,333$1,573,333$1,573,333$1,573,333$0$0$No1,573,333$Lien
Logan StanleyWolf Pack (NYR)D221998-05-25No228 Lbs6 ft7NoNoNo2Pro & Farm1,075,833$1,075,833$1,075,833$1,075,833$0$0$No1,075,833$Lien
Matt RoyWolf Pack (NYR)D251995-02-28No200 Lbs6 ft1NoNoNo3Pro & Farm1,200,000$1,200,000$700,000$700,000$0$0$No700,000$700,000$Lien
Rem PitlickWolf Pack (NYR)C/LW231997-04-01Yes196 Lbs5 ft11NoNoNo3Pro & Farm925,000$925,000$925,000$925,000$0$0$No925,000$925,000$
Rudolfs BalcersWolf Pack (NYR)LW231997-04-08No165 Lbs5 ft11NoNoNo2Pro & Farm925,000$925,000$925,000$925,000$0$0$No925,000$Lien
Ryan GravesWolf Pack (NYR)D251995-05-20No216 Lbs6 ft5NoNoNo2Pro & Farm650,000$650,000$650,000$650,000$0$0$No650,000$Lien
Ryan PoehlingWolf Pack (NYR)C/LW211999-01-02Yes183 Lbs6 ft2NoNoNo3Pro & Farm1,491,667$1,491,667$1,491,667$1,491,667$0$0$No1,491,667$1,491,667$
Sam LaffertyWolf Pack (NYR)C/LW/RW251995-03-06No194 Lbs6 ft1NoNoNo3Pro & Farm975,000$975,000$925,000$925,000$0$0$No925,000$925,000$Lien
Victor MeteWolf Pack (NYR)D221998-06-07No184 Lbs5 ft10NoNoNo1Pro & Farm870,000$870,000$870,000$870,000$0$0$NoLien
Vitaly AbramovWolf Pack (NYR)LW/RW221998-05-08No172 Lbs5 ft9NoNoNo2Pro & Farm880,000$880,000$880,000$880,000$0$0$No880,000$Lien
Vladislav KamenevWolf Pack (NYR)C/LW/RW231996-08-12No194 Lbs6 ft2NoNoNo3Pro & Farm800,000$800,000$750,000$750,000$0$0$No750,000$750,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2822.21191 Lbs6 ft12.501,382,452$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Brendan LemieuxGabriel VilardiKaapo Kakko35023
2Jack HughesLogan BrownVladislav 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 HughesGabriel VilardiKaapo Kakko60122
2Brendan LemieuxLogan BrownVitaly 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 HughesGabriel VilardiKaapo 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, Logan Brown, Alexander True
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, Gabriel Vilardi
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
1IceHogs2010001067-1100000104311010000024-220.50069150076423845594533913303910110.00%140100.00%013022059.09%11020254.46%6611358.41%213149178579849
2Monsters1010000002-21010000002-20000000000000.0000000076421145594531761021400.00%50100.00%013022059.09%11020254.46%6611358.41%213149178579849
3Penguins1010000034-1000000000001010000034-100.00036900764213455945319645186233.33%6266.67%013022059.09%11020254.46%6611358.41%213149178579849
4Phantoms21100000752110000004131010000034-120.500714210076424445594534212164213538.46%7271.43%013022059.09%11020254.46%6611358.41%213149178579849
5Sound Tigers2010010024-21000010012-11010000012-110.250246007642444559453341212271317.69%6183.33%013022059.09%11020254.46%6611358.41%213149178579849
Total815001101822-44110011098140400000914-550.31318335100764215045594531514911314746919.57%38586.84%013022059.09%11020254.46%6611358.41%213149178579849
_Since Last GM Reset815001101822-44110011098140400000914-550.31318335100764215045594531514911314746919.57%38586.84%013022059.09%11020254.46%6611358.41%213149178579849
_Vs Conference413000001011-1211000004312020000068-220.2501020300076426845594537824718123730.43%18477.78%013022059.09%11020254.46%6611358.41%213149178579849
_Vs Division613000001215-33110000055030200000710-320.1671224360076421124559453112368310836822.22%24579.17%013022059.09%11020254.46%6611358.41%213149178579849

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
85L21833511501514911314700
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
81501101822
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
411011098
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4040000914
Derniers 10 Matchs
WLOTWOTL SOWSOL
250100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
46919.57%38586.84%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
45594537642
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
13022059.09%11020254.46%6611358.41%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
213149178579849


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 - 2020-09-033Wolf Pack1Sound Tigers2LSommaire du Match
2 - 2020-09-0415Sound Tigers2Wolf Pack1LXSommaire du Match
4 - 2020-09-0630IceHogs3Wolf Pack4WXXSommaire du Match
5 - 2020-09-0742Wolf Pack2IceHogs4LSommaire du Match
7 - 2020-09-0953Wolf Pack3Penguins4LSommaire du Match
8 - 2020-09-1060Phantoms1Wolf Pack4WSommaire du Match
9 - 2020-09-1167Wolf Pack3Phantoms4LSommaire du Match
10 - 2020-09-1279Monsters2Wolf Pack0LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
13 - 2020-09-1597Wolf Pack-Monsters-
14 - 2020-09-16110Penguins-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
1 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 3,870,868$ 3,618,951$ 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$ 5 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