Wild

GP: 45 | W: 31 | L: 9 | OTL: 5 | P: 67
GF: 154 | GA: 70 | PP%: 25.46% | PK%: 87.93%
DG: Kevin Bourassa | Morale : 70 | Moyenne d'Équipe : 64
Prochain matchs #694 vs Condors
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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
1Steve BernierX100.007442746188928860545761625984745176640
2Phil VaroneX100.005736916472706663766665626177695281630
3Mackenzie MacEachernX100.007238866178726360545863605869666481610
4Nicholas BaptisteX100.006536915778949356585554565567646581600
5Vitaly Abramov (R)X100.005636926264857161555860546361638081600
6Nikita ScherbakX100.005937896179746259555758565567647881590
7Adam BrooksX100.005037896057928859625759525965636281590
8Zach RedmondX100.006937876283918761306260635179715481660
9Gustav ForslingX100.006439816872756266307262715365636837650
10Juuso Valimaki (R)X100.006539836383797162306458725661638481650
11Victor MeteX100.005335946865798266307054655361637281640
12Rinat ValievX100.007239825686918654305752584567646579630
13Sebastien AhoX100.005237876068939059306354585265635667620
14Ludwig BystromX100.005435935771949256305951544669657181610
Rayé
MOYENNE D'ÉQUIPE100.00623787617584796045615860556865667662
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 Milner100.00776462777675777675777677834481730
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)C4523315429803096159409014.47%897521.6741822221511127847067.30%94200011.1115000613
2Juuso ValimakiWild (Min)D45153247143806837125246612.00%53101622.5971623851571122132310.00%000000.9200000333
3Steve BernierWild (Min)RW4517274417951517769182531289.34%12115125.5989174115812381344063.69%32500000.7615003543
4Mackenzie MacEachernWild (Min)LW451824422430080521563610611.54%6100222.276814321680002762163.74%9100010.8413000336
5Victor MeteWild (Min)D45735421860174868325410.29%40102022.6971219511520330128200.00%000000.8200000022
6Zach RedmondWild (Min)D45629351666074527726827.79%49115825.7541418451710000120200.00%000000.6000000112
7Nicholas BaptisteWild (Min)RW45161531202608829101226815.84%589319.86549201611015851049.44%8900000.6911000132
8Rinat ValievWild (Min)D4581725275610932545153017.78%3189619.91538148701105832100.00%100000.5600011021
9Adam BrooksWild (Min)C4512132514120398613034969.23%288719.72145101031012481062.03%74000000.5600000033
10Vitaly AbramovWild (Min)RW45151025251803536123419512.20%585919.113251497000071171.21%6600000.5800000153
11Gustav ForslingWild (Min)D2351520728036315224339.62%3553823.434373888000077110.00%000000.7400000122
12Ludwig BystromWild (Min)D4531518168016352451812.50%3976016.91000326000069000.00%000000.4700000101
13Nikita ScherbakWild (Min)RW456101646032259614546.25%471815.971561177000001064.10%3900000.4500000100
14Sebastien AhoWild (Min)D22369-216021204413176.82%2251623.491233488000381100.00%000000.3500000010
15Lucas WallmarkMinnesota WildC30222806813480.00%17926.440110100001120065.82%7900000.5011000000
16Gemel SmithMinnesota WildC1011100121110.00%11616.2200000000000054.55%1100001.2300000000
Stats d'équipe Total ou en Moyenne58915428243623242125813651139638494611.03%3131249221.21561011574201701581330111629664.33%238300020.70515014233031
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)4531950.9331.4827234116710020100.61118450741
Stats d'équipe Total ou en Moyenne4531950.9331.4827234116710020100.61118450741


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
Gustav ForslingWild (Min)D231996-06-12No186 Lbs6 ft0NoNoNo2Pro & 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$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1624.94196 Lbs6 ft02.44725,000$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Mackenzie MacEachernSteve Bernier40122
2Vitaly AbramovPhil VaroneNicholas Baptiste30122
3Adam BrooksVitaly Abramov20122
4Phil VaroneSteve BernierNikita Scherbak10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Zach RedmondGustav Forsling40122
2Juuso ValimakiVictor Mete30122
3Rinat ValievLudwig Bystrom20122
4Zach RedmondGustav Forsling10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Mackenzie MacEachernSteve Bernier60122
2Vitaly AbramovPhil VaroneNicholas Baptiste40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Zach RedmondGustav Forsling60122
2Juuso ValimakiVictor Mete40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Steve Bernier60122
2Phil VaroneMackenzie MacEachern40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Zach RedmondGustav Forsling60122
2Juuso ValimakiVictor Mete40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Zach RedmondGustav Forsling60122
2Steve Bernier40122Juuso ValimakiVictor Mete40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Steve Bernier60122
2Phil VaroneMackenzie MacEachern40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Zach RedmondGustav Forsling60122
2Juuso ValimakiVictor Mete40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Mackenzie MacEachernSteve BernierZach RedmondGustav Forsling
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Mackenzie MacEachernSteve BernierZach RedmondGustav Forsling
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Adam Brooks, Nikita Scherbak, Nicholas BaptisteAdam Brooks, Nikita ScherbakNicholas Baptiste
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Rinat Valiev, Ludwig Bystrom, Juuso ValimakiRinat ValievLudwig Bystrom, Juuso Valimaki
Tirs de Pénalité
, 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
1Admirals5130010056-13030000014-32100010042230.300591401605239698436470440291213768822428.33%21385.71%0819142857.35%657124952.60%37160960.92%1321978876283529291
2Condors220000001211122000000121110000000000041.0001221330160523967643647044029287123514535.71%6183.33%0819142857.35%657124952.60%37160960.92%1321978876283529291
3Eagles430010002361722000000112921001000124881.000234164016052396184436470440298732285819736.84%14192.86%4819142857.35%657124952.60%37160960.92%1321978876283529291
4Griffins32100000936220000008081010000013-240.667917260260523966043647044029471230586233.33%140100.00%0819142857.35%657124952.60%37160960.92%1321978876283529291
5Gulls11000000321110000003210000000000021.0003690060523963043647044029271216176233.33%7185.71%0819142857.35%657124952.60%37160960.92%1321978876283529291
6Heat2020000058-32020000058-30000000000000.00058130060523966743647044029612022373133.33%11190.91%0819142857.35%657124952.60%37160960.92%1321978876283529291
7IceHogs880000003983144000000245194400000015312161.0003977116026052396310436470440291614860158351131.43%27485.19%1819142857.35%657124952.60%37160960.92%1321978876283529291
8Moose43000001197122100000110552200000092770.875193352016052396133436470440297025206820945.00%10190.00%0819142857.35%657124952.60%37160960.92%1321978876283529291
9Rampage4300001012750000000000043000010127581.00012203200605239689436470440298726567826830.77%18194.44%0819142857.35%657124952.60%37160960.92%1321978876283529291
10Reign2200000010282200000010280000000000041.0001018280160523969043647044029371110467228.57%5180.00%0819142857.35%657124952.60%37160960.92%1321978876283529291
11Stars51100102710-31000000134-14110010146-250.50071320016052396117436470440291232227883026.67%10190.00%0819142857.35%657124952.60%37160960.92%1321978876283529291
Total4528901223154708424156000129540552113301211593029670.744154280434011605239613584364704402910022944137972165525.46%1742187.93%5819142857.35%657124952.60%37160960.92%1321978876283529291
13Wolves5220001010100311000108712110000023-160.6001017270160523961044364704402915342647226415.38%31680.65%0819142857.35%657124952.60%37160960.92%1321978876283529291
_Since Last GM Reset4528901223154708424156000129540552113301211593029670.744154280434011605239613584364704402910022944137972165525.46%1742187.93%5819142857.35%657124952.60%37160960.92%1321978876283529291
_Vs Conference3822901222122596319116000117231411911301211502822540.7111222233450960523961105436470440298682463676661834222.95%1521888.16%5819142857.35%657124952.60%37160960.92%1321978876283529291

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4567W115428043413581002294413797011
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
45289122315470
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2415600129540
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2113312115930
Derniers 10 Matchs
WLOTWOTL SOWSOL
800200
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2165525.46%1742187.93%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
436470440296052396
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
819142857.35%657124952.60%37160960.92%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1321978876283529291


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 - 2020-01-01694Wild-Condors-
123 - 2020-01-02710Wild-Gulls-
126 - 2020-01-05715Wild-Barracuda-
129 - 2020-01-08729Rampage-Wild-
130 - 2020-01-09743Rampage-Wild-
137 - 2020-01-16785Wild-IceHogs-
138 - 2020-01-17798Wild-Wolves-
140 - 2020-01-19807Stars-Wild-
142 - 2020-01-21815Barracuda-Wild-
143 - 2020-01-22826Barracuda-Wild-
147 - 2020-01-26849Wild-Barracuda-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29865Wild-Condors-
151 - 2020-01-30878Wild-Reign-
152 - 2020-01-31887Wild-Reign-
157 - 2020-02-05900Wild-Griffins-
158 - 2020-02-06918Wild-Wolves-
161 - 2020-02-09932Rampage-Wild-
164 - 2020-02-12952Rampage-Wild-
168 - 2020-02-16976Wild-Roadrunners-
169 - 2020-02-17983Wild-Roadrunners-
171 - 2020-02-19992Wild-Heat-
173 - 2020-02-211015Wild-Heat-
175 - 2020-02-231017Griffins-Wild-
178 - 2020-02-261034Stars-Wild-
179 - 2020-02-271046Stars-Wild-
182 - 2020-03-011062Roadrunners-Wild-
183 - 2020-03-021069Roadrunners-Wild-
186 - 2020-03-051091Wild-Admirals-
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
14 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
680,741$ 116,000$ 30,380$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 67,300$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 75 5,753$ 431,475$




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
14452890122315470842415600012954055211330121159302967154280434011605239613584364704402910022944137972165525.46%1742187.93%5819142857.35%657124952.60%37160960.92%1321978876283529291
Total Saison Régulière452890122315470842415600012954055211330121159302967154280434011605239613584364704402910022944137972165525.46%1742187.93%5819142857.35%657124952.60%37160960.92%1321978876283529291