Soldiers

GP: 46 | W: 27 | L: 18 | OTL: 1 | P: 55
GF: 122 | GA: 106 | PP%: 13.25% | PK%: 86.67%
DG: Louis-Philippe Fraser | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #522 vs IceHogs
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Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPÂgeContratSalaire
1Chris WagnerXXX100.009476807773628959555659826366676750002921,600,000$
2Dmitry SokolovXX100.00837893627866685850476567624444645000222830,000$
3Josh AndersonX100.00917081808373786938615673256465675000261678,333$
4Yakov Trenin (R)X100.00877787637654816156655966254545645000233863,333$
5Justin KirklandX100.00727077617075805750614862464545585000232925,000$
6Kieffer BellowsX100.007271746971778259504767626444446450002221,106,666$
7Klim KostinXXX100.007274677074737662785862635945456450002121,075,833$
8Joel Kellman (R)X100.00734395776959685874615974254646655000262937,500$
9Joseph BlandisiXX100.00774385736651745653625971255858655000251680,000$
10Tanner KeroX100.00746887626871746379645666535151635000271750,000$
11Joseph Veleno (R)X100.007671897271707456705058635544446150002031,243,750$
12Eetu Tuulola (R)X100.00838286658269725850535867554444625000223925,000$
13Eeli Tolvanen (R)XX100.007568906768768060505263646044446550002133,115,000$
14Anthony BitettoX100.00937082707866625725524776756465625000291621,500$
15Jack DoughertyX100.00736983636969754825394161394949535000242902,000$
16Jake BeanX100.007369836769788362255951634844446250002221,363,333$
17Mario Ferraro (R)X100.008544858067686861255148712551516150002131,137,500$
18Xavier OuelletX100.008545897469637657255247682561626050002611,250,000$
19Erik GustafssonX100.00785387836680908025665061756465665000281650,000$
Rayé
1Adam MascherinX100.00757380617366705350515162484444575000222880,000$
2Ty RonningX100.00696189626155574750444557434444525000222750,833$
3Kale ClagueX100.00716584716567705725485161484444595000222894,166$
4Maxime Lajoie (R)X100.00736885776869745125444162395151555000223780,000$
5Teemu Kivihalme (R)X100.00736786666769755025434160394444535000253925,000$
MOYENNE D'ÉQUIPE100.0078668470716875584554536647505061500
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
1Hunter Miska100.0063567063676758676664304444633700
2Calvin Petersen100.0059779670566450615756304444595000
Rayé
MOYENNE D'ÉQUIPE100.006167836762665464626030444461440
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
John Hynes83808081666281USA4731,356,000$


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
1Joel KellmanSoldiers (VGK)C4618183622200249586166120.93%869315.080333370000556257.55%55600001.0422000542
2Erik GustafssonSoldiers (VGK)D46524294260615241252512.20%23110424.0241014342100110245100.00%000000.5211000023
3Eeli TolvanenSoldiers (VGK)LW/RW46141428-3200462571275319.72%374116.11591428197000031146.81%4700010.7600000222
4Josh AndersonSoldiers (VGK)RW4671926138069917820598.97%10101622.090882219501132582046.60%47000000.5125000133
5Joseph BlandisiSoldiers (VGK)C/LW46715221180416457144812.28%1183918.2547112017900041151049.38%56300000.5212000011
6Chris WagnerSoldiers (VGK)C/LW/RW461462025558197100194514.00%1184518.383032419610131601154.36%83700000.4712010301
7Jake BeanSoldiers (VGK)D464162018415413774957.14%2677416.851011320001106100.00%000000.5200100012
8Anthony BitettoSoldiers (VGK)D467121931020983342162716.67%29100021.74459291940000193200.00%000000.3800000022
9Eetu TuulolaSoldiers (VGK)RW4661218178020503451253911.76%460313.1200037000000042.86%2800000.6000120111
10Klim KostinSoldiers (VGK)C/LW/RW368917-56925472147193717.02%256215.63551016146000052048.15%2700000.6000112122
11Kieffer BellowsSoldiers (VGK)LW46881617655324056134114.29%260913.2600002000012151.43%3500000.5200010221
12Brock McGinnGolden KnightsLW/RW366713-214025507014608.57%1175120.873253315710121832041.03%7800000.3534000011
13Yakov TreninSoldiers (VGK)C464812548060352651915.38%1454211.7900013000001050.52%19200000.4411000310
14Xavier OuelletSoldiers (VGK)D4621012-343551313210236.25%2395420.75257221730001198000.00%000000.2500000100
15Danton HeinenGolden KnightsLW/RW10189100017304203.33%023123.1612313400001470031.15%12200000.7801000100
16Mario FerraroSoldiers (VGK)D46077-348068413314270.00%4192520.12022221470000173000.00%000000.1500000000
17Cody CeciGolden KnightsD704408012145640.00%1016523.61022333000033000.00%000000.4800000000
18Dmitry SokolovSoldiers (VGK)LW/RW4640421001371041140.00%11753.8200001000000066.67%900000.4500000020
19Maxime LajoieSoldiers (VGK)D1004410160932110.00%1016616.6700002000022000.00%000000.4800000011
20Tanner KeroSoldiers (VGK)C461230801119188115.56%42204.800115370000340062.04%13700000.2700000010
21Joseph VelenoSoldiers (VGK)C46101-1001480312.50%1641.41101423000060164.29%1400000.3100000000
22Justin KirklandSoldiers (VGK)LW3000020020000.00%0155.23000010000100075.00%400000.0000000000
23Ty RonningSoldiers (VGK)RW5000-200200000.00%0316.38000000000000100.00%100000.0000000000
Stats d'équipe Total ou en Moyenne843117203320847316584281287026462313.45%2441303815.47336194283202322415185522651.54%312000010.491118352202622
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
1Calvin PetersenSoldiers (VGK)34191310.8672.47189704785870410.800153336320
2Hunter MiskaSoldiers (VGK)138500.8981.8176223232250000.40051310300
Stats d'équipe Total ou en Moyenne47271810.8762.282659271018120410.700204646620


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 MascherinSoldiers (VGK)LW221998-06-05No206 Lbs5 ft11NoNoNo2Pro & Farm880,000$361,935$450,000$185,081$0$0$No880,000$Lien
Anthony BitettoSoldiers (VGK)D291990-07-14No210 Lbs6 ft1NoNoNo1Pro & Farm621,500$255,617$621,500$255,617$0$0$NoLien
Calvin PetersenSoldiers (VGK)G251994-10-19No185 Lbs6 ft1NoNoNo3Pro & Farm1,108,333$455,847$858,333$353,024$0$0$No858,333$858,333$Lien
Chris WagnerSoldiers (VGK)C/LW/RW291991-05-27No198 Lbs6 ft0NoNoNo2Pro & Farm1,600,000$658,065$1,350,000$555,242$0$0$No1,350,000$Lien
Dmitry SokolovSoldiers (VGK)LW/RW221998-04-13No221 Lbs5 ft11NoNoNo2Pro & Farm830,000$341,371$450,000$185,081$0$0$No830,000$Lien
Eeli TolvanenSoldiers (VGK)LW/RW211999-04-22Yes191 Lbs5 ft10NoNoNo3Pro & Farm3,115,000$1,281,169$3,115,000$1,281,169$0$0$No3,115,000$3,115,000$
Eetu TuulolaSoldiers (VGK)RW221998-03-17Yes225 Lbs6 ft2NoNoNo3Pro & Farm925,000$380,444$925,000$380,444$0$0$No925,000$925,000$
Erik GustafssonSoldiers (VGK)D281992-03-14No176 Lbs6 ft0NoNoNo1Pro & Farm650,000$267,339$650,000$267,339$0$0$NoLien
Hunter MiskaSoldiers (VGK)G241995-07-06No170 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$411,290$1,000,000$411,290$0$0$NoLien
Jack DoughertySoldiers (VGK)D241996-05-24No186 Lbs6 ft1NoNoNo2Pro & Farm902,000$370,984$450,000$185,081$0$0$No902,000$Lien
Jake BeanSoldiers (VGK)D221998-06-09No187 Lbs6 ft1NoNoNo2Pro & Farm1,363,333$560,726$450,000$185,081$0$0$No1,363,333$Lien
Joel KellmanSoldiers (VGK)C261994-05-25Yes192 Lbs5 ft11NoNoNo2Pro & Farm937,500$385,585$925,000$380,444$0$0$No925,000$Lien
Joseph BlandisiSoldiers (VGK)C/LW251994-07-18No182 Lbs5 ft11NoNoNo1Pro & Farm680,000$279,677$680,000$279,677$0$0$NoLien
Joseph VelenoSoldiers (VGK)C202000-01-13Yes194 Lbs6 ft1NoNoNo3Pro & Farm1,243,750$511,542$1,243,750$511,542$0$0$No1,243,750$1,243,750$
Josh AndersonSoldiers (VGK)RW261994-05-06No221 Lbs6 ft3NoNoNo1Pro & Farm678,333$278,992$678,333$278,992$0$0$NoLien
Justin KirklandSoldiers (VGK)LW231996-08-02No183 Lbs6 ft3NoNoNo2Pro & Farm925,000$380,444$450,000$185,081$0$0$No925,000$Lien
Kale ClagueSoldiers (VGK)D221998-06-05No177 Lbs6 ft0NoNoNo2Pro & Farm894,166$367,762$450,000$185,081$0$0$No894,166$Lien
Kieffer BellowsSoldiers (VGK)LW221998-06-10No196 Lbs6 ft0NoNoNo2Pro & Farm1,106,666$455,161$450,000$185,081$0$0$No1,106,666$Lien
Klim KostinSoldiers (VGK)C/LW/RW211999-05-05No196 Lbs6 ft3NoNoNo2Pro & Farm1,075,833$442,480$450,000$185,081$0$0$No1,075,833$Lien
Mario FerraroSoldiers (VGK)D211998-09-17Yes185 Lbs5 ft11NoNoNo3Pro & Farm1,137,500$467,843$1,137,500$467,843$0$0$No1,137,500$1,137,500$
Maxime LajoieSoldiers (VGK)D221997-11-05Yes183 Lbs6 ft1NoNoNo3Pro & Farm780,000$320,806$780,000$320,806$0$0$No780,000$780,000$
Tanner KeroSoldiers (VGK)C271992-07-24No185 Lbs6 ft0NoNoNo1Pro & Farm750,000$308,468$750,000$308,468$0$0$NoLien
Teemu KivihalmeSoldiers (VGK)D251995-06-14Yes181 Lbs6 ft0NoNoNo3Pro & Farm925,000$380,444$925,000$380,444$0$0$No925,000$925,000$
Ty RonningSoldiers (VGK)RW221997-10-20No172 Lbs5 ft9NoNoNo2Pro & Farm750,833$308,810$450,000$185,081$0$0$No750,833$Lien
Xavier OuelletSoldiers (VGK)D261993-07-28No185 Lbs6 ft1NoNoNo1Pro & Farm1,250,000$514,113$1,250,000$514,113$0$0$NoLien
Yakov TreninSoldiers (VGK)C231997-01-13Yes201 Lbs6 ft2NoNoNo3Pro & Farm863,333$355,081$863,333$355,081$0$0$No863,333$863,333$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2623.81192 Lbs6 ft02.041,038,195$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Joseph BlandisiChris WagnerJosh Anderson35122
2Klim KostinJoel KellmanEeli Tolvanen30122
3Kieffer BellowsYakov TreninEetu Tuulola25122
4Dmitry SokolovTanner Kero10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Erik Gustafsson35122
2Anthony BitettoXavier Ouellet30122
3Mario FerraroJake Bean25122
4Erik Gustafsson10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Joseph BlandisiChris WagnerJosh Anderson60122
2Klim KostinJoel KellmanEeli Tolvanen40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Erik Gustafsson60122
2Anthony BitettoXavier Ouellet40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Josh AndersonChris Wagner60122
2Joseph BlandisiJoel Kellman40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Erik Gustafsson60122
2Anthony BitettoXavier Ouellet40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Josh Anderson60122Erik Gustafsson60122
2Chris Wagner40122Anthony BitettoXavier Ouellet40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Josh AndersonChris Wagner60122
2Joseph BlandisiJoel Kellman40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Erik Gustafsson60122
2Anthony BitettoXavier Ouellet40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Joseph BlandisiChris WagnerJosh AndersonErik Gustafsson
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Joseph BlandisiChris WagnerJosh AndersonErik Gustafsson
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Joseph Veleno, Yakov Trenin, Tanner KeroJoseph Veleno, Yakov TreninTanner Kero
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Mario Ferraro, Jake Bean, Anthony BitettoMario FerraroJake Bean, Anthony Bitetto
Tirs de Pénalité
Josh Anderson, Chris Wagner, Joseph Blandisi, Joel Kellman, Yakov Trenin
Gardien
#1 : Hunter Miska, #2 : Calvin Petersen


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
1Bruins21100000651110000003031010000035-220.5006111701413442113728428130221441533319222.22%13376.92%0673126453.24%629126249.84%32063850.16%11718091040341573292
2Condors42200000131211010000045-13210000097240.500132134004134421161284281302217815639421419.05%29582.76%0673126453.24%629126249.84%32063850.16%11718091040341573292
3Flames2010001078-12010001078-10000000000020.500791600413442113828428130221419323212433.33%16287.50%1673126453.24%629126249.84%32063850.16%11718091040341573292
4Griffins1010000012-11010000012-10000000000000.0001230041344211242842813022118312154125.00%6183.33%0673126453.24%629126249.84%32063850.16%11718091040341573292
5IceHogs4220000089-13120000068-21100000021140.5008111901413442115928428130221701977892229.09%31583.87%0673126453.24%629126249.84%32063850.16%11718091040341573292
6Marlies220000001138110000007251100000041341.0001120310041344211542842813022126423401000.00%9188.89%1673126453.24%629126249.84%32063850.16%11718091040341573292
7Monarchs211000002201010000012-11100000010120.5002460141344211202842813022132152636800.00%120100.00%0673126453.24%629126249.84%32063850.16%11718091040341573292
8Moose20200000012-120000000000020200000012-1200.00000000413442112628428130221481133301000.00%14378.57%0673126453.24%629126249.84%32063850.16%11718091040341573292
9Penguins2110000067-1110000005321010000014-320.5006111700413442115128428130221269302815320.00%13469.23%0673126453.24%629126249.84%32063850.16%11718091040341573292
10Phantoms1010000012-11010000012-10000000000000.0001230041344211212842813022124712159111.11%50100.00%0673126453.24%629126249.84%32063850.16%11718091040341573292
11Rampage3200001012482100001010461100000020261.000122032014134421166284281302216220306312216.67%14285.71%0673126453.24%629126249.84%32063850.16%11718091040341573292
12Senators1000010023-1000000000001000010023-110.500246004134421115284281302212071815400.00%80100.00%0673126453.24%629126249.84%32063850.16%11718091040341573292
13Sharks21100000431110000002021010000023-120.5004711014134421125284281302212812183412216.67%9188.89%0673126453.24%629126249.84%32063850.16%11718091040341573292
14Sound Tigers1010000023-1000000000001010000023-100.000235004134421117284281302211761414500.00%7271.43%0673126453.24%629126249.84%32063850.16%11718091040341573292
15Stars116300020302286420000020155521000201073160.727305080114134421123628428130221219632122015359.43%73889.04%0673126453.24%629126249.84%32063850.16%11718091040341573292
Total46221800150122106162411100003076562022118001204650-4550.5981222043261741344211870284281302218592457338442493313.25%3004086.67%2673126453.24%629126249.84%32063850.16%11718091040341573292
16Wolves6410001017983110001095433000000844100.8331729460141344211120284281302211063010010743716.28%41392.68%0673126453.24%629126249.84%32063850.16%11718091040341573292
_Since Last GM Reset46221800150122106162411100003076562022118001204650-4550.5981222043261741344211870284281302218592457338442493313.25%3004086.67%2673126453.24%629126249.84%32063850.16%11718091040341573292
_Vs Conference3618140004089781118880002053411218106000203637-1440.611891472361641344211654284281302216781945856831902312.11%2363087.29%0673126453.24%629126249.84%32063850.16%11718091040341573292
_Vs Division2414700040674423147600020453213107100020221210360.750671101771441344211481284281302214571324194601301612.31%1591888.68%0673126453.24%629126249.84%32063850.16%11718091040341573292

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4655W312220432687085924573384417
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4622180150122106
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
24111000307656
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2211801204650
Derniers 10 Matchs
WLOTWOTL SOWSOL
550000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2493313.25%3004086.67%2
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
2842813022141344211
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
673126453.24%629126249.84%32063850.16%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
11718091040341573292


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 - 2020-09-273Soldiers1Stars0WSommaire du Match
2 - 2020-09-2815Stars2Soldiers5WSommaire du Match
4 - 2020-09-3026Stars2Soldiers3WSommaire du Match
5 - 2020-10-0139Soldiers3Stars1WSommaire du Match
7 - 2020-10-0353Bruins0Soldiers3WSommaire du Match
9 - 2020-10-0566Soldiers2Stars1WXXSommaire du Match
10 - 2020-10-0670Stars4Soldiers3LSommaire du Match
12 - 2020-10-0881Soldiers4Wolves3WSommaire du Match
14 - 2020-10-1097Soldiers2Sharks3LSommaire du Match
16 - 2020-10-12102Stars1Soldiers4WSommaire du Match
18 - 2020-10-14113Soldiers2Wolves1WSommaire du Match
20 - 2020-10-16125Wolves1Soldiers5WSommaire du Match
21 - 2020-10-17132Soldiers3Condors1WSommaire du Match
23 - 2020-10-19145Rampage1Soldiers6WSommaire du Match
24 - 2020-10-20155Soldiers2IceHogs1WSommaire du Match
25 - 2020-10-21170IceHogs5Soldiers2LSommaire du Match
27 - 2020-10-23185Griffins2Soldiers1LSommaire du Match
28 - 2020-10-24187Soldiers0Moose5LSommaire du Match
30 - 2020-10-26201Flames5Soldiers3LSommaire du Match
32 - 2020-10-28214Soldiers4Marlies1WSommaire du Match
34 - 2020-10-30226Stars4Soldiers2LSommaire du Match
37 - 2020-11-02241Monarchs2Soldiers1LSommaire du Match
38 - 2020-11-03245Soldiers2Senators3LXSommaire du Match
40 - 2020-11-05261Phantoms2Soldiers1LSommaire du Match
42 - 2020-11-07270Soldiers2Wolves0WSommaire du Match
45 - 2020-11-10288Condors5Soldiers4LSommaire du Match
47 - 2020-11-12303Soldiers3Bruins5LSommaire du Match
48 - 2020-11-13311Wolves2Soldiers3WXXSommaire du Match
50 - 2020-11-15331Sharks0Soldiers2WSommaire du Match
51 - 2020-11-16340Soldiers0Stars2LSommaire du Match
52 - 2020-11-17351Flames3Soldiers4WXXSommaire du Match
53 - 2020-11-18359Soldiers4Condors3WSommaire du Match
55 - 2020-11-20369Soldiers4Stars3WXXSommaire du Match
56 - 2020-11-21380Stars2Soldiers3WSommaire du Match
57 - 2020-11-22396Penguins3Soldiers5WSommaire du Match
58 - 2020-11-23402Soldiers1Penguins4LSommaire du Match
59 - 2020-11-24412Soldiers2Condors3LSommaire du Match
61 - 2020-11-26424Wolves2Soldiers1LSommaire du Match
63 - 2020-11-28440IceHogs0Soldiers3WSommaire du Match
65 - 2020-11-30452Soldiers0Moose7LSommaire du Match
66 - 2020-12-01459Soldiers2Rampage0WSommaire du Match
67 - 2020-12-02469IceHogs3Soldiers1LSommaire du Match
68 - 2020-12-03482Soldiers2Sound Tigers3LSommaire du Match
70 - 2020-12-05489Rampage3Soldiers4WXXSommaire du Match
71 - 2020-12-06505Marlies2Soldiers7WSommaire du Match
73 - 2020-12-08517Soldiers1Monarchs0WSommaire du Match
74 - 2020-12-09522Soldiers-IceHogs-
75 - 2020-12-10533Condors-Soldiers-
76 - 2020-12-11542Soldiers-Rampage-
78 - 2020-12-13554Admirals-Soldiers-
79 - 2020-12-14566Soldiers-Admirals-
80 - 2020-12-15575Rampage-Soldiers-
82 - 2020-12-17590Rocket-Soldiers-
85 - 2020-12-20603Soldiers-Rampage-
86 - 2020-12-21615Soldiers-Rampage-
87 - 2020-12-22623Senators-Soldiers-
88 - 2020-12-23636Admirals-Soldiers-
90 - 2020-12-25646Soldiers-Griffins-
92 - 2020-12-27656Soldiers-Flames-
93 - 2020-12-28664Crunch-Soldiers-
95 - 2020-12-30683IceHogs-Soldiers-
96 - 2020-12-31692Soldiers-Wolves-
97 - 2021-01-01706Stars-Soldiers-
98 - 2021-01-02715Soldiers-Bruins-
99 - 2021-01-03725Soldiers-Phantoms-
101 - 2021-01-05733Sound Tigers-Soldiers-
102 - 2021-01-06749Rampage-Soldiers-
103 - 2021-01-07757Soldiers-Rocket-
105 - 2021-01-09771Bruins-Soldiers-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
106 - 2021-01-10781Soldiers-IceHogs-
107 - 2021-01-11792Soldiers-Condors-
108 - 2021-01-12795Moose-Soldiers-
110 - 2021-01-14811Soldiers-Stars-
111 - 2021-01-15818Monsters-Soldiers-
113 - 2021-01-17838Wolf Pack-Soldiers-
115 - 2021-01-19852Soldiers-Sharks-
116 - 2021-01-20858Soldiers-Monsters-
117 - 2021-01-21861Wolves-Soldiers-
119 - 2021-01-23881Monarchs-Soldiers-
120 - 2021-01-24886Soldiers-Crunch-
121 - 2021-01-25889Soldiers-IceHogs-
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
17 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,520,293$ 2,699,307$ 2,180,274$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,722,017$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 51 32,704$ 1,667,904$




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