Wild

GP: 73 | W: 46 | L: 19 | OTL: 8 | P: 100
GF: 227 | GA: 125 | PP%: 23.77% | PK%: 89.13%
DG: Kevin Bourassa | Morale : 72 | Moyenne d'Équipe : 64
Prochain matchs #1109 vs Griffins
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

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
1Jack RoslovicXX100.005735946875659066776964616865628180640
2Steve BernierX100.007442746188928860545761625984745181640
3Phil VaroneX100.005736916472706663766665626177695280630
4Mackenzie MacEachernX100.007238866178726360545863605869666480610
5Nicholas BaptisteX100.006536915778949356585554565567646580600
6Vitaly Abramov (R)X100.005636926264857161555860546361638080600
7Nikita ScherbakX100.005937896179746259555758565567647880590
8Adam BrooksX100.005037896057928859625759525965636280590
9Zach RedmondX100.006937876283918761306260635179715480660
10Juuso Valimaki (R)X100.006539836383797162306458725661638480650
11Victor MeteX100.005335946865798266307054655361637280640
12Rinat ValievX100.007239825686918654305752584567646582630
13Sebastien AhoX100.005237876068939059306354585265635677620
14Ludwig BystromX100.005435935771949256305951544669657180610
Rayé
MOYENNE D'ÉQUIPE100.00613788617584816048615860566865678062
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
1Anders Nilsson100.00848482988382848382848377835581820
2Parker Milner100.00776462777675777675777677834480730
Rayé
MOYENNE D'ÉQUIPE100.0081747288807981807981807783508178
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Joel Bouchard70696475706580CAN4551,000,000$


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
1Phil VaroneWild (Min)C7330417133180511552386315112.61%10158021.656202640234112711610064.26%142400010.9027000823
2Steve BernierWild (Min)RW7330396915136202591072878219910.45%15190626.1115142972265123112175158.71%57400100.7228004965
3Victor MeteWild (Min)D73135265201002679113498811.50%59160922.05101525792410331203200.00%200000.8100000252
4Juuso ValimakiWild (Min)D73184765176951127518437949.78%86164422.52925341192561122204310.00%000000.7900001333
5Mackenzie MacEachernWild (Min)LW732241631944012385232561799.48%8158221.68817254126900031274157.04%13500010.8014000456
6Zach RedmondWild (Min)D7312435515100012678129501029.30%97184125.2362228772850000196400.00%000000.6000000217
7Nicholas BaptisteWild (Min)RW7324204421460148501523510115.79%9146320.0596153225610181353051.88%16000000.6012000263
8Adam BrooksWild (Min)C731523381518054130184531418.15%4137018.77167141331012651158.65%112200000.5500000043
9Vitaly AbramovWild (Min)RW732315382929566711866115612.37%6152020.8363925183000073166.36%10700000.5001001156
10Rinat ValievWild (Min)D73822302789151454067234711.94%47140819.2954920139011210032100.00%100000.4300111022
11Nikita ScherbakWild (Min)RW73915246215454114422956.25%6104514.331561289000001054.79%7300000.4600010200
12Ludwig BystromWild (Min)D73319221722024503210309.38%52120816.550003270000112000.00%000000.3600000101
13Jack RoslovicWild (Min)C/RW189817040114672185012.50%343724.332468500003521159.62%42100010.7812000211
14Sebastien AhoWild (Min)D404913-222029295116257.84%3480920.251233594000386100.00%100000.3200000010
15Lucas WallmarkMinnesota WildC30222806813480.00%17926.440110100001120065.82%7900000.5011000000
16Gemel SmithMinnesota WildC1011100121110.00%11616.2200000000000054.55%1100001.2300000000
Stats d'équipe Total ou en Moyenne93822039761723563650122610462085580146710.55%4381952520.82791442235772537581343163841860.61%411000130.63825127364142
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
1Anders NilssonWild (Min)73461980.9231.64438541612015580200.72429730853
2Parker MilnerWild (Min)10000.9171.6237001120000.0000073000
Stats d'équipe Total ou en Moyenne74461980.9231.64442241612115700200.724297373853


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 Cap 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 BrooksWild (Min)C231996-05-06No180 Lbs5 ft1NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Anders NilssonWild (Min)G291990-03-19No232 Lbs6 ft6NoNoNo3Pro & Farm3,000,000$0$0$No3,000,000$3,000,000$Lien
Jack RoslovicWild (Min)C/RW221997-01-29No187 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Juuso ValimakiWild (Min)D201998-10-06Yes212 Lbs6 ft2NoNoNo4Pro & Farm900,000$0$0$No900,000$900,000$900,000$Lien
Ludwig BystromWild (Min)D241994-07-20No169 Lbs6 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Mackenzie MacEachernWild (Min)LW251994-03-09No190 Lbs6 ft2NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Nicholas BaptisteWild (Min)RW231995-08-04No205 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$NoLien
Nikita ScherbakWild (Min)RW231995-12-30No192 Lbs6 ft2NoNoNo1Pro & Farm900,000$0$0$NoLien
Parker MilnerWild (Min)G281990-09-06No196 Lbs6 ft1NoNoNo1Pro & Farm300,000$0$0$NoLien
Phil VaroneWild (Min)C281990-12-04No193 Lbs5 ft10NoNoNo2Pro & Farm1,000,000$0$0$No1,000,000$Lien
Rinat ValievWild (Min)D241995-05-11No215 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$NoLien
Sebastien AhoWild (Min)D231996-02-17No177 Lbs5 ft11NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Steve BernierWild (Min)RW341985-03-31No222 Lbs6 ft3NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Victor MeteWild (Min)D211998-06-07No183 Lbs5 ft9NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Vitaly AbramovWild (Min)RW211998-05-08Yes171 Lbs5 ft9NoNoNo4Pro & Farm900,000$0$0$No900,000$900,000$900,000$Lien
Zach RedmondWild (Min)D301988-07-26No212 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1624.88196 Lbs6 ft02.44725,000$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Mackenzie MacEachernJack RoslovicSteve Bernier40122
2Vitaly AbramovPhil VaroneNicholas Baptiste30122
3Jack RoslovicAdam BrooksVitaly Abramov20122
4Phil VaroneSteve BernierNikita Scherbak10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Zach RedmondJuuso Valimaki40122
2Victor MeteRinat Valiev30122
3Sebastien AhoLudwig Bystrom20122
4Zach RedmondJuuso Valimaki10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Mackenzie MacEachernJack RoslovicSteve Bernier60122
2Vitaly AbramovPhil VaroneNicholas Baptiste40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Zach RedmondJuuso Valimaki60122
2Victor MeteRinat Valiev40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Jack RoslovicSteve Bernier60122
2Phil VaroneMackenzie MacEachern40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Zach RedmondJuuso Valimaki60122
2Victor MeteRinat Valiev40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Jack Roslovic60122Zach RedmondJuuso Valimaki60122
2Steve Bernier40122Victor MeteRinat Valiev40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Jack RoslovicSteve Bernier60122
2Phil VaroneMackenzie MacEachern40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Zach RedmondJuuso Valimaki60122
2Victor MeteRinat Valiev40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Mackenzie MacEachernJack RoslovicSteve BernierZach RedmondJuuso Valimaki
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Mackenzie MacEachernJack RoslovicSteve BernierZach RedmondJuuso Valimaki
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Adam Brooks, Nikita Scherbak, Nicholas BaptisteAdam Brooks, Nikita ScherbakNicholas Baptiste
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Sebastien Aho, Ludwig Bystrom, Victor MeteSebastien AhoLudwig Bystrom, Victor Mete
Tirs de Pénalité
Jack Roslovic, Steve Bernier, Phil Varone, Mackenzie MacEachern, Nicholas Baptiste
Gardien
#1 : Anders Nilsson, #2 : Parker Milner


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
1Admirals6140010058-33030000014-33110010044030.250591401927257101236977136744614339811022727.41%25484.00%01287231955.50%1015200950.52%57198258.15%207315161478476875472
2Barracuda411001107702010001034-12100010043150.6257111800927257108169771367446922626699333.33%110100.00%01287231955.50%1015200950.52%57198258.15%207315161478476875472
3Condors430001001731422000000121112100010052370.8751731480292725710117697713674466519386423834.78%19194.74%01287231955.50%1015200950.52%57198258.15%207315161478476875472
4Eagles430010002361722000000112921001000124881.0002341640192725710184697713674468732285819736.84%14192.86%41287231955.50%1015200950.52%57198258.15%207315161478476875472
5Griffins541000001751233000000120122110000055080.8001732490392725710122697713674467722469712325.00%22195.45%01287231955.50%1015200950.52%57198258.15%207315161478476875472
6Gulls2110000056-1110000003211010000024-220.50051015009272571049697713674465417243813430.77%10190.00%01287231955.50%1015200950.52%57198258.15%207315161478476875472
7Heat412000011011-12020000058-32100000153230.37510162600927257101626977136744610427477813323.08%20385.00%01287231955.50%1015200950.52%57198258.15%207315161478476875472
8IceHogs990000004393444000000245195500000019415181.00043851280292725710346697713674461865666179401435.00%30486.67%11287231955.50%1015200950.52%57198258.15%207315161478476875472
9Moose43000001197122100000110552200000092770.8751933520192725710133697713674467025206820945.00%10190.00%01287231955.50%1015200950.52%57198258.15%207315161478476875472
10Rampage843000101818041300000611-5430000101275100.625183149019272571019869771367446166537614353916.98%27196.30%01287231955.50%1015200950.52%57198258.15%207315161478476875472
11Reign440000002261622000000102822000000124881.0002240620192725710175697713674467621207915320.00%9277.78%01287231955.50%1015200950.52%57198258.15%207315161478476875472
12Roadrunners421000101147201000104402200000070760.750111930029272571083697713674465522444224625.00%150100.00%01287231955.50%1015200950.52%57198258.15%207315161478476875472
13Stars822011021617-141101001121114110010146-290.563163147019272571019369771367446183376413143511.63%26388.46%01287231955.50%1015200950.52%57198258.15%207315161478476875472
Total73401902444227125102361812010321216655372270141210659471000.68522741464101692725710210269771367446157046065812573458223.77%2763089.13%51287231955.50%1015200950.52%57198258.15%207315161478476875472
15Wolves724000101418-43110001087141300000611-560.429142539019272571013669771367446212647810934617.65%38878.95%01287231955.50%1015200950.52%57198258.15%207315161478476875472
_Since Last GM Reset73401902444227125102361812010321216655372270141210659471000.68522741464101692725710210269771367446157046065812573458223.77%2763089.13%51287231955.50%1015200950.52%57198258.15%207315161478476875472
_Vs Conference552916023231639568271410010119149422815601312724626720.6551633014640129272571015816977136744612233495249612645721.59%2212688.24%51287231955.50%1015200950.52%57198258.15%207315161478476875472

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
73100L1227414641210215704606581257016
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7340192444227125
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
361812103212166
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
37227141210659
Derniers 10 Matchs
WLOTWOTL SOWSOL
431011
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3458223.77%2763089.13%5
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
6977136744692725710
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
1287231955.50%1015200950.52%57198258.15%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
207315161478476875472


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
3 - 2019-09-046Moose5Wild4LXXSommaire du Match
5 - 2019-09-0625Moose0Wild6WSommaire du Match
10 - 2019-09-1139Stars4Wild3LXXSommaire du Match
17 - 2019-09-1878Wild1Stars0WSommaire du Match
18 - 2019-09-1991Wild0Stars1LSommaire du Match
24 - 2019-09-25114Eagles1Wild4WSommaire du Match
25 - 2019-09-26128Eagles1Wild7WSommaire du Match
31 - 2019-10-02142Wild1Griffins3LSommaire du Match
32 - 2019-10-03160Wild6IceHogs2WSommaire du Match
33 - 2019-10-04170IceHogs1Wild4WSommaire du Match
36 - 2019-10-07175Wild1IceHogs0WSommaire du Match
37 - 2019-10-08179Condors0Wild7WSommaire du Match
39 - 2019-10-10202Condors1Wild5WSommaire du Match
43 - 2019-10-14221Admirals1Wild0LSommaire du Match
45 - 2019-10-16232Admirals2Wild1LSommaire du Match
46 - 2019-10-17246Wild1Wolves3LSommaire du Match
50 - 2019-10-21261Wild3Admirals0WSommaire du Match
52 - 2019-10-23271Wild5Moose1WSommaire du Match
53 - 2019-10-24277Wild4Moose1WSommaire du Match
55 - 2019-10-26298Griffins0Wild5WSommaire du Match
59 - 2019-10-30315Wild5Eagles4WXSommaire du Match
60 - 2019-10-31330Wild7Eagles0WSommaire du Match
64 - 2019-11-04346Wolves2Wild3WXXSommaire du Match
66 - 2019-11-06358Wolves4Wild3LSommaire du Match
67 - 2019-11-07372Griffins0Wild3WSommaire du Match
71 - 2019-11-11388Wild1Stars2LXXSommaire du Match
73 - 2019-11-13399Wild2Rampage1WXXSommaire du Match
75 - 2019-11-15418Wild4Rampage2WSommaire du Match
80 - 2019-11-20445Heat3Wild2LSommaire du Match
81 - 2019-11-21461Heat5Wild3LSommaire du Match
85 - 2019-11-25466IceHogs2Wild8WSommaire du Match
88 - 2019-11-28493Admirals1Wild0LSommaire du Match
90 - 2019-11-30505Wolves1Wild2WSommaire du Match
92 - 2019-12-02514Wild1Wolves0WSommaire du Match
94 - 2019-12-04527IceHogs1Wild5WSommaire du Match
96 - 2019-12-06550Wild4IceHogs1WSommaire du Match
99 - 2019-12-09556Wild2Rampage1WSommaire du Match
101 - 2019-12-11570Wild4Rampage3WSommaire du Match
102 - 2019-12-12583Wild2Stars3LXSommaire du Match
104 - 2019-12-14593Gulls2Wild3WSommaire du Match
108 - 2019-12-18612Reign0Wild4WSommaire du Match
109 - 2019-12-19623Reign2Wild6WSommaire du Match
111 - 2019-12-21637IceHogs1Wild7WSommaire du Match
115 - 2019-12-25662Wild1Admirals2LXSommaire du Match
116 - 2019-12-26676Wild4IceHogs0WSommaire du Match
122 - 2020-01-01694Wild4Condors0WSommaire du Match
123 - 2020-01-02710Wild2Gulls4LSommaire du Match
126 - 2020-01-05715Wild1Barracuda2LXSommaire du Match
129 - 2020-01-08729Rampage5Wild3LSommaire du Match
130 - 2020-01-09743Rampage0Wild1WSommaire du Match
137 - 2020-01-16785Wild4IceHogs1WSommaire du Match
138 - 2020-01-17798Wild2Wolves4LSommaire du Match
140 - 2020-01-19807Stars1Wild3WSommaire du Match
142 - 2020-01-21815Barracuda2Wild0LSommaire du Match
143 - 2020-01-22826Barracuda2Wild3WXXSommaire du Match
147 - 2020-01-26849Wild3Barracuda1WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29865Wild1Condors2LXSommaire du Match
151 - 2020-01-30878Wild3Reign2WSommaire du Match
152 - 2020-01-31887Wild9Reign2WSommaire du Match
157 - 2020-02-05900Wild4Griffins2WSommaire du Match
158 - 2020-02-06918Wild2Wolves4LSommaire du Match
161 - 2020-02-09932Rampage4Wild1LSommaire du Match
164 - 2020-02-12952Rampage2Wild1LSommaire du Match
168 - 2020-02-16976Wild2Roadrunners0WSommaire du Match
169 - 2020-02-17983Wild5Roadrunners0WSommaire du Match
171 - 2020-02-19992Wild4Heat1WSommaire du Match
173 - 2020-02-211015Wild1Heat2LXXSommaire du Match
175 - 2020-02-231017Griffins0Wild4WSommaire du Match
178 - 2020-02-261034Stars4Wild3LSommaire du Match
179 - 2020-02-271046Stars2Wild3WXSommaire du Match
182 - 2020-03-011062Roadrunners1Wild0LSommaire du Match
183 - 2020-03-021069Roadrunners3Wild4WXXSommaire du Match
186 - 2020-03-051091Wild0Admirals2LSommaire du Match
190 - 2020-03-091109Wild-Griffins-
192 - 2020-03-111123Wolves-Wild-
193 - 2020-03-121132IceHogs-Wild-



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
2 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,065,677$ 116,000$ 30,380$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 106,852$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 8 5,753$ 46,024$




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
14734019024442271251023618120103212166553722701412106594710022741464101692725710210269771367446157046065812573458223.77%2763089.13%51287231955.50%1015200950.52%57198258.15%207315161478476875472
Total Saison Régulière734019024442271251023618120103212166553722701412106594710022741464101692725710210269771367446157046065812573458223.77%2763089.13%51287231955.50%1015200950.52%57198258.15%207315161478476875472