Admirals

GP: 6 | W: 2 | L: 3 | OTL: 1 | P: 5
GF: 20 | GA: 16 | PP%: 22.22% | PK%: 86.36%
DG: Stéphane Fournier | Morale : 47 | Moyenne d'Équipe : 62
Prochain matchs #98 vs Wolves
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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
1Jason PominvilleX100.005635936770738666546870636987803229660
2Jordan SzwarzXX100.005939836172939160635859576075685244620
3Austin Poganski (R)XX100.006335935877918757625953585565636247600
4Sam AnasXX100.005135935961918758655955535771665948590
5Jansen HarkinsXX100.005837885774939156595556575663626348590
6Chase Balisy (A)X100.005337885568959654585352555173675848580
7Samuel KurkerX100.006638855881777156525353565469656749580
8Brandon GignacXX100.005436925766797156635854575263626548570
9Tanner Kaspick (R)X100.006137885474878153555252545061636448570
10Joseph GambardellaXX100.005935945670615854555753555671664248560
11Otto Somppi (R)X100.006336905479787253585252545361636448560
12Jacob MiddletonX100.006238855985796958306054635865635648620
13Ben ThomasX100.005936905576939054305551574565636548610
14Ethan BearX100.005838865972908458306252564763625945610
15Dominik MasinX100.006740795483939153305251565465637249610
16Dysin MayoX100.006238855476939053305251544865636248600
17Brandon Hickey (R)X100.006637885581837754305552584565636248600
18Emil JohanssonX100.005238855459928953305251554765626344580
Rayé
MOYENNE D'ÉQUIPE100.00593788577486825647565457536765594660
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
1Louis Domingue100.00797775857877797877797873774845760
2Garret Sparks100.00777472847675777675777671754742740
Rayé
1Jake Oettinger (R)100.00726563937170727170727161658346690
2Jeremy Helvig (R)100.00736361847271737271737263675747690
MOYENNE D'ÉQUIPE100.0075706887747375747375746771594572
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Pascal Vincent72686671736878CAN4741,500,000$


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'ÉquipePOS GP 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
1Jordan SzwarzAdmirals (Nas)C/RW226830063152513.33%05326.84123250000111175.00%5200002.9800000110
2Jacob MiddletonAdmirals (Nas)D6088440576740.00%514323.99033222000018000.00%000001.1101000001
3Austin PoganskiAdmirals (Nas)LW/RW56280801392631223.08%112324.612249190000151063.16%1900011.3000000201
4Brandon GignacAdmirals (Nas)C/LW61453202920375.00%012020.090116210000000100.00%700000.8300000000
5Sam AnasAdmirals (Nas)LW/RW6235-20048246118.33%014123.511123210000140070.59%1700000.7101000001
6Ethan BearAdmirals (Nas)D614511153646525.00%112921.56011223000015000.00%000000.7700010000
7Jansen HarkinsAdmirals (Nas)C/LW622422088146914.29%014323.921013210000140057.14%10500000.5601000000
8Chase BalisyAdmirals (Nas)C603322021015670.00%18113.6400002000000055.56%9000000.7311000000
9Samuel KurkerAdmirals (Nas)RW6213355136182711.11%112020.14000720000010057.14%700000.5001001000
10Dominik MasinAdmirals (Nas)D611259511361516.67%313322.25000519000016000.00%000000.3000001000
11Joseph GambardellaAdmirals (Nas)C/LW62021403293422.22%17612.690000000000000.00%400000.5300000010
12Tanner KaspickAdmirals (Nas)C6022-120459040.00%16110.3100010000080059.32%5900000.6500000000
13Yakov TreninNashville PredatorsC/LW3011-300787240.00%18528.42011210000050047.22%7200000.2301000000
14Ben ThomasAdmirals (Nas)D6101-5408345125.00%212921.53101320000014010.00%000000.1500000010
15Dysin MayoAdmirals (Nas)D6011020534210.00%28714.570000100002000.00%000000.2300000000
16Lukas SedlakNashville PredatorsC/LW/RW1000-100373020.00%02020.1300025000010052.94%1700000.0000000000
17Emil JohanssonAdmirals (Nas)D4000-100100000.00%0143.620000000001000.00%000000.0000000000
18Brandon HickeyAdmirals (Nas)D6000060454020.00%48814.690000000006000.00%000000.0000000000
19Otto SomppiAdmirals (Nas)C6000-100422000.00%0203.4700001000000058.33%1200000.0000000000
Stats d'équipe Total ou en Moyenne99203858106115106104190549010.53%23177417.93611174721800001492258.35%46100010.6516012333
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
1Jeremy HelvigAdmirals (Nas)11000.9371.0060001160000.000010000
2Louis DomingueAdmirals (Nas)40310.8912.472430010920000.667640000
Stats d'équipe Total ou en Moyenne51310.8982.1830300111080000.667650000


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Austin PoganskiAdmirals (Nas)LW/RW231996-02-16Yes198 Lbs6 ft1NoNoNo4Avec RestrictionPro & Farm500,000$0$0$NoLien
Ben ThomasAdmirals (Nas)D231996-05-28No180 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Brandon GignacAdmirals (Nas)C/LW211997-11-07No170 Lbs5 ft11NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$NoLien
Brandon HickeyAdmirals (Nas)D231996-04-13Yes201 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm500,000$0$0$NoLien
Chase BalisyAdmirals (Nas)C271992-02-02No179 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Dominik MasinAdmirals (Nas)D231996-02-01No198 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm500,000$0$0$NoLien
Dysin MayoAdmirals (Nas)D221996-08-17No194 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm500,000$0$0$NoLien
Emil JohanssonAdmirals (Nas)D231996-05-06No189 Lbs5 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Ethan BearAdmirals (Nas)D221997-06-26No197 Lbs5 ft11NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Garret SparksAdmirals (Nas)G261993-06-28No201 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm500,000$0$0$NoLien
Jacob MiddletonAdmirals (Nas)D231996-01-02No210 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Jake OettingerAdmirals (Nas)G201998-12-18Yes220 Lbs6 ft5NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$NoLien
Jansen HarkinsAdmirals (Nas)C/LW221997-05-23No182 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Jason PominvilleAdmirals (Nas)RW361982-11-30No180 Lbs5 ft11NoNoNo3Sans RestrictionPro & Farm5,666,000$0$0$NoLien
Jeremy HelvigAdmirals (Nas)G221997-05-25Yes188 Lbs6 ft4NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Jordan SzwarzAdmirals (Nas)C/RW281991-05-14No200 Lbs5 ft11NoNoNo2Sans RestrictionPro & Farm400,000$0$0$NoLien
Joseph GambardellaAdmirals (Nas)C/LW251993-12-01No196 Lbs5 ft10NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Louis DomingueAdmirals (Nas)G271992-03-06No210 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm2,500,000$0$0$NoLien
Otto SomppiAdmirals (Nas)C211998-01-12Yes192 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Sam AnasAdmirals (Nas)LW/RW261993-06-01No163 Lbs5 ft8NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Samuel KurkerAdmirals (Nas)RW251994-04-08No202 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm500,000$0$0$NoLien
Tanner KaspickAdmirals (Nas)C211998-01-28Yes200 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2224.05193 Lbs6 ft02.95748,455$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Austin PoganskiJordan SzwarzSam Anas40122
2Brandon GignacJansen HarkinsSamuel Kurker30122
3Joseph GambardellaChase BalisyJordan Szwarz20122
4Austin PoganskiTanner KaspickSam Anas10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jacob MiddletonDominik Masin40122
2Ethan BearBen Thomas30122
3Dysin MayoBrandon Hickey20122
4Jacob MiddletonDominik Masin10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Austin PoganskiJordan SzwarzSam Anas60122
2Brandon GignacJansen HarkinsSamuel Kurker40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jacob MiddletonDominik Masin60122
2Ethan BearBen Thomas40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Jordan SzwarzAustin Poganski60122
2Sam AnasJansen Harkins40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jacob MiddletonDominik Masin60122
2Ethan BearBen Thomas40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Jordan Szwarz60122Jacob MiddletonDominik Masin60122
2Austin Poganski40122Ethan BearBen Thomas40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Jordan SzwarzAustin Poganski60122
2Sam AnasJansen Harkins40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jacob MiddletonDominik Masin60122
2Ethan BearBen Thomas40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Austin PoganskiJordan SzwarzSam AnasJacob MiddletonDominik Masin
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Austin PoganskiJordan SzwarzSam AnasJacob MiddletonDominik Masin
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Otto Somppi, Chase Balisy, Tanner KaspickOtto Somppi, Chase BalisyTanner Kaspick
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dysin Mayo, Brandon Hickey, Ethan BearDysin MayoBrandon Hickey, Ethan Bear
Tirs de Pénalité
Jordan Szwarz, Austin Poganski, Sam Anas, Jansen Harkins, Samuel Kurker
Gardien
#1 : , #2 :


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
1Bears1010000023-11010000023-10000000000000.000246008751396968527166917600.00%10100.00%011920059.50%9416357.67%569260.87%164119125407439
2Gulls11000000642000000000001100000064221.0006111700875130696852722619185360.00%7185.71%011920059.50%9416357.67%569260.87%164119125407439
3Rampage1000000123-1000000000001000000123-110.5002350087512669685273048153133.33%4175.00%011920059.50%9416357.67%569260.87%164119125407439
4Reign11000000716000000000001100000071621.0007142100875152696852716213204125.00%40100.00%011920059.50%9416357.67%569260.87%164119125407439
5Stars1010000023-1000000000001010000023-100.00024600875122696852728310176116.67%5180.00%011920059.50%9416357.67%569260.87%164119125407439
Total62300001201641010000023-1522000011813550.4172038580087511906968527130236110627622.22%22386.36%011920059.50%9416357.67%569260.87%164119125407439
7Wolves1010000012-1000000000001010000012-100.000123008751216968527182219300.00%10100.00%011920059.50%9416357.67%569260.87%164119125407439
_Since Last GM Reset62300001201641010000023-1522000011813550.4172038580087511906968527130236110627622.22%22386.36%011920059.50%9416357.67%569260.87%164119125407439
_Vs Conference3020000158-3000000000003020000158-310.1675914008751696968527769205112216.67%10280.00%011920059.50%9416357.67%569260.87%164119125407439
_Vs Division3010000114770000000000030100001147710.16714274100875110369685275610345712433.33%12191.67%011920059.50%9416357.67%569260.87%164119125407439

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
65W2203858190130236110600
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
62300012016
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
101000023
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
52200011813
Derniers 10 Matchs
WLOTWOTL SOWSOL
230001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
27622.22%22386.36%0
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
69685278751
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
11920059.50%9416357.67%569260.87%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
164119125407439


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
4 - 2019-09-0519Admirals2Stars3LSommaire du Match
7 - 2019-09-0828Admirals2Rampage3LXXSommaire du Match
11 - 2019-09-1248Bears3Admirals2LSommaire du Match
12 - 2019-09-1361Admirals1Wolves2LSommaire du Match
15 - 2019-09-1668Admirals7Reign1WSommaire du Match
17 - 2019-09-1880Admirals6Gulls4WSommaire du Match
19 - 2019-09-2098Admirals-Wolves-
21 - 2019-09-22101Rampage-Admirals-
24 - 2019-09-25112Monsters-Admirals-
25 - 2019-09-26122Moose-Admirals-
28 - 2019-09-29136Moose-Admirals-
31 - 2019-10-02149IceHogs-Admirals-
32 - 2019-10-03159Admirals-Griffins-
36 - 2019-10-07174Wolves-Admirals-
38 - 2019-10-09188IceHogs-Admirals-
40 - 2019-10-11207Admirals-Wolves-
43 - 2019-10-14221Admirals-Wild-
45 - 2019-10-16232Admirals-Wild-
46 - 2019-10-17242Reign-Admirals-
50 - 2019-10-21261Wild-Admirals-
52 - 2019-10-23267Admirals-Griffins-
53 - 2019-10-24280IceHogs-Admirals-
59 - 2019-10-30314Stars-Admirals-
60 - 2019-10-31326Admirals-IceHogs-
64 - 2019-11-04345Admirals-Stars-
66 - 2019-11-06357Admirals-Stars-
67 - 2019-11-07371Admirals-Rampage-
70 - 2019-11-10381Griffins-Admirals-
73 - 2019-11-13398Stars-Admirals-
74 - 2019-11-14406Admirals-Griffins-
78 - 2019-11-18431Admirals-IceHogs-
81 - 2019-11-21452Wolves-Admirals-
85 - 2019-11-25469Wolves-Admirals-
88 - 2019-11-28493Admirals-Wild-
92 - 2019-12-02516Admirals-IceHogs-
95 - 2019-12-05539Admirals-Penguins-
96 - 2019-12-06549Admirals-Bears-
99 - 2019-12-09555Griffins-Admirals-
102 - 2019-12-12584Gulls-Admirals-
104 - 2019-12-14592Admirals-Moose-
106 - 2019-12-16600Admirals-Moose-
109 - 2019-12-19622Admirals-Griffins-
110 - 2019-12-20635Admirals-Wolves-
112 - 2019-12-22644Rampage-Admirals-
115 - 2019-12-25662Wild-Admirals-
116 - 2019-12-26668Moose-Admirals-
122 - 2020-01-01690Moose-Admirals-
123 - 2020-01-02706IceHogs-Admirals-
127 - 2020-01-06721Stars-Admirals-
129 - 2020-01-08728Penguins-Admirals-
130 - 2020-01-09734Wolves-Admirals-
133 - 2020-01-12758Rampage-Admirals-
138 - 2020-01-17795Admirals-Moose-
139 - 2020-01-18806Admirals-Moose-
143 - 2020-01-22819Admirals-Monsters-
145 - 2020-01-24841Admirals-Monsters-
148 - 2020-01-27853Admirals-Stars-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29864Admirals-Rampage-
152 - 2020-01-31885Admirals-Rampage-
154 - 2020-02-02889Stars-Admirals-
157 - 2020-02-05906Wolves-Admirals-
158 - 2020-02-06917Griffins-Admirals-
159 - 2020-02-07928Admirals-Wolves-
162 - 2020-02-10934Monsters-Admirals-
165 - 2020-02-13961Griffins-Admirals-
171 - 2020-02-19989IceHogs-Admirals-
172 - 2020-02-20998Admirals-IceHogs-
176 - 2020-02-241023Admirals-IceHogs-
179 - 2020-02-271049Admirals-Wolves-
180 - 2020-02-281055Admirals-Griffins-
183 - 2020-03-021067Rampage-Admirals-
185 - 2020-03-041079Wolves-Admirals-
186 - 2020-03-051091Wild-Admirals-
189 - 2020-03-081106IceHogs-Admirals-
193 - 2020-03-121131Griffins-Admirals-
194 - 2020-03-131149Admirals-IceHogs-



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
37 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
141,643$ 164,660$ 42,700$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 10,199$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 177 8,581$ 1,518,837$




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
1462300001201641010000023-1522000011813552038580087511906968527130236110627622.22%22386.36%011920059.50%9416357.67%569260.87%164119125407439
Total Saison Régulière62300001201641010000023-1522000011813552038580087511906968527130236110627622.22%22386.36%011920059.50%9416357.67%569260.87%164119125407439