Soldiers
GP: 82 | W: 43 | L: 36 | OTL: 3 | P: 89
GF: 206 | GA: 184 | PP%: 11.01% | PK%: 87.08%
DG: Louis-Philippe Fraser | Morale : 50 | Moyenne d'Équipe : N/A
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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$
14Jake BeanX100.007369836769788362255951634844446250002221,363,333$
15Kale ClagueX100.00716584716567705725485161484444595000222894,166$
16Maxime Lajoie (R)X100.00736885776869745125444162395151555000223780,000$
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$
3Jack DoughertyX100.00736983636969754825394161394949535000242902,000$
4Teemu Kivihalme (R)X100.00736786666769755025434160394444535000253925,000$
MOYENNE D'ÉQUIPE100.0078658470716875584654546545495061500
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 Miska100.0063567063676758676664304444633600
2Calvin Petersen100.0059779670566450615756304444594800
Rayé
MOYENNE D'ÉQUIPE100.006167836762665464626030444461420
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
1Erik GustafssonSoldiers (VGK)D8275865111160150938447478.33%52196723.9941822653960221406200.00%000000.6612000256
2Joel KellmanSoldiers (VGK)C8224315525280451711513710015.89%20134416.403692119001121647255.59%111000000.8223000563
3Josh AndersonSoldiers (VGK)RW821432466755134169145401089.66%21178821.81310134136301144643146.38%91200000.5139000455
4Eeli TolvanenSoldiers (VGK)LW/RW82221941-14008147125408517.60%4127915.609101950363000053347.56%8200010.6400000333
5Chris WagnerSoldiers (VGK)C/LW/RW82221436710220152178163429513.50%20155518.985274336310163492153.96%142500000.4636022424
6Joseph BlandisiSoldiers (VGK)C/LW8211253692605597105368310.48%15148018.0548123634111252502049.28%69600000.4925000121
7Klim KostinSoldiers (VGK)C/LW/RW72171532-31304010958101347216.83%7111115.4481018363080001222054.17%4800010.5800133232
8Eetu TuulolaSoldiers (VGK)RW821118292012430725688327012.50%10103212.59011315000000042.50%4000000.5600221131
9Anthony BitettoGolden KnightsD7972027816001906462254611.29%58166421.074812453160110333200.00%000000.3201000032
10Yakov TreninSoldiers (VGK)C82918279740938975184712.00%15100612.280002140000242051.89%53000000.5422000311
11Kieffer BellowsSoldiers (VGK)LW8214122621775646990247015.56%6103512.6300004000013246.15%5200000.5000010322
12Jake BeanSoldiers (VGK)D82619252663579571781435.29%48135416.512025560003199300.00%000000.3700100113
13Dmitry SokolovSoldiers (VGK)LW/RW821110218440351644143625.00%64175.0900001000003160.00%1500001.0100000132
14Xavier OuelletSoldiers (VGK)D8221921165585594619384.35%41165220.152911343090001332000.00%000000.2500000100
15Mario FerraroSoldiers (VGK)D826111719001336653184111.32%51149318.21123292150000222000.00%000000.2300000000
16Tanner KeroSoldiers (VGK)C82710176220235355143812.73%105416.6001153700011090059.43%38700000.6300000321
17Brock McGinnGolden KnightsLW/RW366713-214025507014608.57%1175120.873253315710121832041.03%7800000.3534000011
18Cody CeciGolden KnightsD704408012145640.00%1016523.61022333000033000.00%000000.4800000000
19Maxime LajoieSoldiers (VGK)D13044112001254210.00%1321116.2400002000030000.00%000000.3800000011
20Joseph VelenoSoldiers (VGK)C82224220310122916.67%11722.101017631011290164.15%5300000.4600000100
21Kale ClagueSoldiers (VGK)D100111601552030.00%916516.5200014000020000.00%000000.1200000000
22Justin KirklandSoldiers (VGK)LW13000020050000.00%0473.62000090000260060.00%500000.0000000000
23Ty RonningSoldiers (VGK)RW5000-200200000.00%0316.38000000000000100.00%100000.0000000000
Stats d'équipe Total ou en Moyenne14651983495471641288110156914311497472106713.23%4282227015.20498913845935694610273210361152.30%543400020.491632486354338
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
1Hunter MiskaSoldiers (VGK)46222110.8862.09266968938190000.600154610513
2Calvin PetersenSoldiers (VGK)39211520.8682.37212305846350410.762213665320
Stats d'équipe Total ou en Moyenne85433630.8782.22479361317714540410.694368275833


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$7,097$450,000$3,629$0$0$No880,000$Lien
Calvin PetersenSoldiers (VGK)G251994-10-19No185 Lbs6 ft1NoNoNo3Pro & Farm1,108,333$8,938$858,333$6,922$0$0$No858,333$858,333$Lien
Chris WagnerSoldiers (VGK)C/LW/RW291991-05-27No198 Lbs6 ft0NoNoNo2Pro & Farm1,600,000$12,903$1,350,000$10,887$0$0$No1,350,000$Lien
Dmitry SokolovSoldiers (VGK)LW/RW221998-04-13No221 Lbs5 ft11NoNoNo2Pro & Farm830,000$6,694$450,000$3,629$0$0$No830,000$Lien
Eeli TolvanenSoldiers (VGK)LW/RW211999-04-22Yes191 Lbs5 ft10NoNoNo3Pro & Farm3,115,000$25,121$3,115,000$25,121$0$0$No3,115,000$3,115,000$
Eetu TuulolaSoldiers (VGK)RW221998-03-17Yes225 Lbs6 ft2NoNoNo3Pro & Farm925,000$7,460$925,000$7,460$0$0$No925,000$925,000$
Erik GustafssonSoldiers (VGK)D281992-03-14No176 Lbs6 ft0NoNoNo1Pro & Farm650,000$5,242$650,000$5,242$0$0$NoLien
Hunter MiskaSoldiers (VGK)G241995-07-06No170 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$8,065$1,000,000$8,065$0$0$NoLien
Jack DoughertySoldiers (VGK)D241996-05-24No186 Lbs6 ft1NoNoNo2Pro & Farm902,000$7,274$450,000$3,629$0$0$No902,000$Lien
Jake BeanSoldiers (VGK)D221998-06-09No187 Lbs6 ft1NoNoNo2Pro & Farm1,363,333$10,995$450,000$3,629$0$0$No1,363,333$Lien
Joel KellmanSoldiers (VGK)C261994-05-25Yes192 Lbs5 ft11NoNoNo2Pro & Farm937,500$7,560$925,000$7,460$0$0$No925,000$Lien
Joseph BlandisiSoldiers (VGK)C/LW251994-07-18No182 Lbs5 ft11NoNoNo1Pro & Farm680,000$5,484$680,000$5,484$0$0$NoLien
Joseph VelenoSoldiers (VGK)C202000-01-13Yes194 Lbs6 ft1NoNoNo3Pro & Farm1,243,750$10,030$1,243,750$10,030$0$0$No1,243,750$1,243,750$
Josh AndersonSoldiers (VGK)RW261994-05-06No221 Lbs6 ft3NoNoNo1Pro & Farm678,333$5,470$678,333$5,470$0$0$NoLien
Justin KirklandSoldiers (VGK)LW231996-08-02No183 Lbs6 ft3NoNoNo2Pro & Farm925,000$7,460$450,000$3,629$0$0$No925,000$Lien
Kale ClagueSoldiers (VGK)D221998-06-05No177 Lbs6 ft0NoNoNo2Pro & Farm894,166$7,211$450,000$3,629$0$0$No894,166$Lien
Kieffer BellowsSoldiers (VGK)LW221998-06-10No196 Lbs6 ft0NoNoNo2Pro & Farm1,106,666$8,925$450,000$3,629$0$0$No1,106,666$Lien
Klim KostinSoldiers (VGK)C/LW/RW211999-05-05No196 Lbs6 ft3NoNoNo2Pro & Farm1,075,833$8,676$450,000$3,629$0$0$No1,075,833$Lien
Mario FerraroSoldiers (VGK)D211998-09-17Yes185 Lbs5 ft11NoNoNo3Pro & Farm1,137,500$9,173$1,137,500$9,173$0$0$No1,137,500$1,137,500$
Maxime LajoieSoldiers (VGK)D221997-11-05Yes183 Lbs6 ft1NoNoNo3Pro & Farm780,000$6,290$780,000$6,290$0$0$No780,000$780,000$
Tanner KeroSoldiers (VGK)C271992-07-24No185 Lbs6 ft0NoNoNo1Pro & Farm750,000$6,048$750,000$6,048$0$0$NoLien
Teemu KivihalmeSoldiers (VGK)D251995-06-14Yes181 Lbs6 ft0NoNoNo3Pro & Farm925,000$7,460$925,000$7,460$0$0$No925,000$925,000$
Ty RonningSoldiers (VGK)RW221997-10-20No172 Lbs5 ft9NoNoNo2Pro & Farm750,833$6,055$450,000$3,629$0$0$No750,833$Lien
Xavier OuelletSoldiers (VGK)D261993-07-28No185 Lbs6 ft1NoNoNo1Pro & Farm1,250,000$10,081$1,250,000$10,081$0$0$NoLien
Yakov TreninSoldiers (VGK)C231997-01-13Yes201 Lbs6 ft2NoNoNo3Pro & Farm863,333$6,962$863,333$6,962$0$0$No863,333$863,333$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2523.60191 Lbs6 ft02.081,054,863$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Joseph BlandisiChris WagnerJosh Anderson35122
2Klim KostinJoel KellmanEeli Tolvanen30122
3Kieffer BellowsYakov TreninEetu Tuulola25122
4Dmitry SokolovTanner KeroJosh Anderson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Erik GustafssonMario Ferraro35122
2Xavier OuelletJake Bean30122
3Kale ClagueMaxime Lajoie25122
4Erik GustafssonMario Ferraro10122
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 GustafssonMario Ferraro60122
2Xavier OuelletJake Bean40122
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 GustafssonMario Ferraro60122
2Xavier OuelletJake Bean40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Josh Anderson60122Erik GustafssonMario Ferraro60122
2Chris Wagner40122Xavier OuelletJake Bean40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Josh AndersonChris Wagner60122
2Joseph BlandisiJoel Kellman40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Erik GustafssonMario Ferraro60122
2Xavier OuelletJake Bean40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Joseph BlandisiChris WagnerJosh AndersonErik GustafssonMario Ferraro
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Joseph BlandisiChris WagnerJosh AndersonErik GustafssonMario Ferraro
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Joseph Veleno, Justin Kirkland, Yakov TreninJoseph Veleno, Justin KirklandYakov Trenin
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Kale Clague, Maxime Lajoie, Xavier OuelletKale ClagueMaxime Lajoie, Xavier Ouellet
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
1Admirals31100010111012010001078-11100000042240.667111930007162651749520510488495517386617317.65%18477.78%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
2Bruins431000001486220000008352110000065160.750142539027162651768520510488497228596518316.67%26484.62%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
3Condors633000001716121100000550422000001211160.500172946017162651793520510488491112710312037616.22%48687.50%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
4Crunch21000010642100000103211100000032141.00069150071626517365205104884949826481000.00%13284.62%11181222952.98%1135223350.83%583114650.87%2085144118626091018519
5Flames30200010911-22010001078-11010000023-120.33391322007162651756520510488496617546014428.57%27485.19%21181222952.98%1135223350.83%583114650.87%2085144118626091018519
6Griffins2010000157-21010000012-11000000145-110.2505101500716265175152051048849381228289111.11%14285.71%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
7IceHogs826000001221-941300000811-341300000410-640.250121830017162651711652051048849135391441594948.16%571180.70%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
8Marlies220000001138110000007251100000041341.0001120310071626517545205104884926423401000.00%9188.89%11181222952.98%1135223350.83%583114650.87%2085144118626091018519
9Monarchs3120000023-12020000013-21100000010120.33324601716265173352051048849512036611200.00%17194.12%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
10Monsters21100000321110000002021010000012-120.5003690171626517205205104884935822421417.14%11281.82%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
11Moose30300000114-131010000012-120200000012-1200.00012300716265174152051048849641747461915.26%21385.71%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
12Penguins2110000067-1110000005321010000014-320.5006111700716265175152051048849269302815320.00%13469.23%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
13Phantoms2020000014-31010000012-11010000002-200.00012300716265173252051048849391636461317.69%16193.75%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
14Rampage8600101036102642001010175124400000019514161.0003664100027162651722652051048849163489816639717.95%39489.74%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
15Rocket2020000004-41010000002-21010000002-200.0000000071626517305205104884932829411000.00%10190.00%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
16Senators21000100330110000001011000010023-130.750369017162651740520510488492492229800.00%100100.00%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
17Sharks3120000045-1110000002022020000025-320.3334711017162651741520510488494219315619210.53%13284.62%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
18Sound Tigers2020000046-21010000023-11010000023-100.000471100716265173552051048849451658341100.00%19289.47%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
19Stars137400020352787430000023194631000201284180.692356095117162651728352051048849249752332486669.09%811087.65%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
20Wolf Pack211000004311010000013-21100000030320.50048120171626517375205104884941732401516.67%16193.75%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
21Wolves8420001122166411000111293431000001073110.6882238600171626517142520510488491514115115249714.29%64592.19%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
Total82353601172206184224116180105111492224119180012192920890.543206358564113716265171534520510488491514445130015754545011.01%5427087.08%41181222952.98%1135223350.83%583114650.87%2085144118626091018519
_Since Last GM Reset82353601172206184224116180105111492224119180012192920890.543206358564113716265171534520510488491514445130015754545011.01%5427087.08%41181222952.98%1135223350.83%583114650.87%2085144118626091018519
_Vs Conference5925260105214913514291014010317967123015120002170682640.5421492584071871626517111052051048849110433196711363273711.31%3915087.21%01181222952.98%1135223350.83%583114650.87%2085144118626091018519
_Vs Division3719130104210574311988010216044161811500021453015500.6761051802851571626517767520510488496982036267252032411.82%2413087.55%01181222952.98%1135223350.83%583114650.87%2085144118626091018519

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8289W12063585641534151444513001575113
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8235361172206184
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
411618105111492
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
41191801219292
Derniers 10 Matchs
WLOTWOTL SOWSOL
450001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
4545011.01%5427087.08%4
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
5205104884971626517
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
1181222952.98%1135223350.83%583114650.87%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
2085144118626091018519


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 - 2020-12-09522Soldiers0IceHogs2LSommaire du Match
75 - 2020-12-10533Condors0Soldiers1WSommaire du Match
76 - 2020-12-11542Soldiers3Rampage1WSommaire du Match
78 - 2020-12-13554Admirals4Soldiers2LSommaire du Match
79 - 2020-12-14566Soldiers4Admirals2WSommaire du Match
80 - 2020-12-15575Rampage1Soldiers2WXSommaire du Match
82 - 2020-12-17590Rocket2Soldiers0LSommaire du Match
85 - 2020-12-20603Soldiers7Rampage2WSommaire du Match
86 - 2020-12-21615Soldiers7Rampage2WSommaire du Match
87 - 2020-12-22623Senators0Soldiers1WSommaire du Match
88 - 2020-12-23636Admirals4Soldiers5WXXSommaire du Match
90 - 2020-12-25646Soldiers4Griffins5LXXSommaire du Match
92 - 2020-12-27656Soldiers2Flames3LSommaire du Match
93 - 2020-12-28664Crunch2Soldiers3WXXSommaire du Match
95 - 2020-12-30683IceHogs3Soldiers2LSommaire du Match
96 - 2020-12-31692Soldiers2Wolves3LSommaire du Match
97 - 2021-01-01706Stars4Soldiers3LSommaire du Match
98 - 2021-01-02715Soldiers3Bruins0WSommaire du Match
99 - 2021-01-03725Soldiers0Phantoms2LSommaire du Match
101 - 2021-01-05733Sound Tigers3Soldiers2LSommaire du Match
102 - 2021-01-06749Rampage0Soldiers5WSommaire du Match
103 - 2021-01-07757Soldiers0Rocket2LSommaire du Match
105 - 2021-01-09771Bruins3Soldiers5WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
106 - 2021-01-10781Soldiers1IceHogs3LSommaire du Match
107 - 2021-01-11792Soldiers3Condors4LSommaire du Match
108 - 2021-01-12795Moose2Soldiers1LSommaire du Match
110 - 2021-01-14811Soldiers2Stars1WSommaire du Match
111 - 2021-01-15818Monsters0Soldiers2WSommaire du Match
113 - 2021-01-17838Wolf Pack3Soldiers1LSommaire du Match
115 - 2021-01-19852Soldiers0Sharks2LSommaire du Match
116 - 2021-01-20858Soldiers1Monsters2LSommaire du Match
117 - 2021-01-21861Wolves4Soldiers3LXXSommaire du Match
119 - 2021-01-23881Monarchs1Soldiers0LSommaire du Match
120 - 2021-01-24886Soldiers3Crunch2WSommaire du Match
121 - 2021-01-25889Soldiers1IceHogs4LSommaire du Match
122 - 2021-01-26894Soldiers3Wolf Pack0WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacitéPopularité de l'Équipe
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
4,151,701$ 2,637,157$ 2,118,124$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 2,806,671$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 1 32,203$ 32,203$




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