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Admirals
GP: 29 | W: 9 | L: 17 | OTL: 3 | P: 21
GF: 66 | GA: 98 | PP%: 18.42% | PK%: 72.73%
DG: Simon Demèlo | Morale : 37 | Moyenne d’équipe : 63
Prochains matchs #457 vs BruinsF

Centre de jeu
Admirals
9-17-3, 21pts
0
3 Marlies
16-8-3, 35pts
Team Stats
L2SéquenceL1
4-9-0Fiche domicile9-3-3
5-8-3Fiche domicile7-5-0
3-7-0Derniers 10 matchs3-6-1
2.28Buts par match 3.11
3.38Buts contre par match 2.78
18.42%Pourcentage en avantage numérique25.32%
72.73%Pourcentage en désavantage numérique80.00%
Admirals
9-17-3, 21pts
1
2 Wranglers
17-11-1, 35pts
Team Stats
L2SéquenceW2
4-9-0Fiche domicile8-7-0
5-8-3Fiche domicile9-4-1
3-7-0Derniers 10 matchs6-4-0
2.28Buts par match 3.41
3.38Buts contre par match 3.03
18.42%Pourcentage en avantage numérique24.72%
72.73%Pourcentage en désavantage numérique77.27%
BruinsF
16-11-1, 33pts
2025-10-28
Admirals
9-17-3, 21pts
Statistiques d’équipe
SOW1SéquenceL2
11-3-0Fiche domicile4-9-0
5-8-1Fiche visiteur5-8-3
7-3-010 derniers matchs3-7-0
3.29Buts par match 2.28
3.11Buts contre par match 2.28
23.53%Pourcentage en avantage numérique18.42%
76.81%Pourcentage en désavantage numérique72.73%
Moose
19-9-1, 39pts
2025-10-31
Admirals
9-17-3, 21pts
Statistiques d’équipe
OTW1SéquenceL2
8-5-1Fiche domicile4-9-0
11-4-0Fiche visiteur5-8-3
8-1-110 derniers matchs3-7-0
3.66Buts par match 2.28
2.83Buts contre par match 2.28
13.25%Pourcentage en avantage numérique18.42%
72.73%Pourcentage en désavantage numérique72.73%
Admirals
9-17-3, 21pts
2025-11-02
Islanders
16-10-3, 35pts
Statistiques d’équipe
L2SéquenceOTW1
4-9-0Fiche domicile10-2-2
5-8-3Fiche visiteur6-8-1
3-7-010 derniers matchs5-4-1
2.28Buts par match 3.52
3.38Buts contre par match 3.52
18.42%Pourcentage en avantage numérique16.25%
72.73%Pourcentage en désavantage numérique84.78%
Meneurs d'équipe
Buts
Ostap Safin
8
Passes
Louis Crevier
15
Points
Louis Crevier
18
Plus/Moins
Tobias Rieder
1
Victoires
Christopher Gibson
9
Pourcentage d’arrêts
Christopher Gibson
0.9

Statistiques d’équipe
Buts pour
66
2.28 GFG
Tirs pour
800
27.59 Avg
Pourcentage en avantage numérique
18.4%
14 GF
Début de zone offensive
39.3%
Buts contre
98
3.38 GAA
Tirs contre
920
31.72 Avg
Pourcentage en désavantage numérique
72.7%%
24 GA
Début de la zone défensive
42.6%
Informations de l'équipe

Directeur généralSimon Demèlo
EntraîneurDon Hay
DivisionDivision Centrale
ConférenceConference 2
Capitaine
Assistant #1
Assistant #2Matthew Phillips


Informations de l’aréna

Capacité3,000
Assistance3,000
Billets de saison300


Informations de la formation

Équipe Pro27
Équipe Mineure19
Limite Contrat46 / 56
Espoirs55


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
1Liam O'Brien0X98.0083457375747076717566687166715238406503231,325,000$
2Nikolay Goldobin87XX98.0057439672716969686665666564735442416403131,000,000$
3Nikolai Prokhorkin0XX96.0077498369737275696465666864715934476403331,000,000$
4Phillip Digiuseppe0XX99.0060459870717282695966676865735834416403331,000,000$
5Jonathan Ang0X96.006147897266747071766869686056505441640282900,000$
6Tobias Rieder0XX99.0058459970707575696066666964686430416403331,000,000$
7Brendan Perlini0XX100.005945957075716869596665666371604241630303900,000$
8Simon Stransky0XX100.006644897268697764646568695360515442620281800,000$
9Matthew Phillips (A)0XXX100.006245887264727860757165636760505444620282900,000$
10Max Zimmer0XX100.005945937268737865636467656060495431620282700,000$
11Jere Innala0X100.006845937267687466616366696349474223610282900,000$
12Louis Crevier0X99.0070459173777876744573647755524866446702522,000,000$
13Corey Schueneman0X100.0059469973718074724571667666564742446603111,800,000$
14Joel Nystrom (R)0X99.006445927567747774457365735945457032650241900,000$
15Marc Del Gaizo0X100.006347887369777872457167705952476246650271750,000$
16Tobias Bjornfot0X100.006245917270777570456963745664476644650252750,000$
17Stepan Falkovsky0X100.0071458372767677674569666855675450446502911,200,000$
Rayé
1Otto Somppi0X89.0865458872707378757672707666595154346602821,200,000$
2Ostap Safin0XX93.007658697273767668696869646055505445640272900,000$
3Adam Marsh0XX100.007658598070646161615960596062566221600292500,000$
4Patrick Harper0X100.005945867262667160706666636651465421600282500,000$
5Casey Fitzgerald0X100.007545787265716765456961686055505445630291900,000$
6Nathan Knoepke0X100.006445907272696959455953645149465821590272500,000$
7Cole Candella0X100.005342887070676559455656665946455421580282500,000$
MOYENNE D’ÉQUIPE98.58654687727072746758676568615951513763
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 SPÂgeContratSalaire
1Christopher Gibson098.007876758079808482838383525646226503311,000,500$
2Antoine Bibeau0100.007581808178788279808179515646516403211,200,500$
Rayé
1Brandon Halverson0100.00797876858068767273769146504232610303725,000$
MOYENNE D’ÉQUIPE99.3377787782797581787980845054453563
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Don Hay7979789499995CAN712100,000$


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
1Louis CrevierAdmirals (Nas)D2931518-1034031344214287.14%3668823.732682058000156000%000000.5200000000
2Tobias BjornfotAdmirals (Nas)D295813-714021294191812.20%3355519.174262256000014000%000010.4700000100
3Lane PedersonPredatorsC216612-240134755143710.91%538418.330333140000381053.94%41900000.6201000012
4Liam O'BrienAdmirals (Nas)C296612-14220614956224510.71%351817.871129500001222054.22%50900000.4601000100
5Ostap SafinAdmirals (Nas)LW/RW298412-1195421851153315.69%048816.842026631011370147.62%4200000.4900001201
6Otto SomppiAdmirals (Nas)C236612040174460184610.00%237616.39011837000051153.08%42200000.6401000101
7Joel NystromAdmirals (Nas)D1811011-91001672811163.57%2639321.861121032011141100%000000.5600000000
8Jonathan AngAdmirals (Nas)C295611-1311532466119488.20%846816.160226140001370047.97%54200000.4700010001
9Phillip DigiuseppeAdmirals (Nas)LW/RW294610-7207196313516.35%145315.64022863000000060.61%3300000.4400000010
10Corey SchuenemanAdmirals (Nas)D22189-3601126309163.33%2245020.470111326000034000%000000.4000000010
11Marc Del GaizoAdmirals (Nas)D29279-418103224257228.00%3051317.71011714000041000%000000.3500002100
12Matthew PhillipsAdmirals (Nas)C/LW/RW29369-900625318239.68%235112.1300000000021058.42%19000000.5100000000
13Nikolay GoldobinAdmirals (Nas)LW/RW29358-80010254920336.12%452918.252029460003670054.39%11400000.3011000100
14Nikolai ProkhorkinAdmirals (Nas)LW/RW29268-4291538193616265.56%249317.031349640000621048.54%10300000.3212200101
15Stepan FalkovskyAdmirals (Nas)D29167-722040222013225.00%3053118.34101731011162000%000000.2600000000
16Tobias RiederAdmirals (Nas)LW/RW293361206155810395.17%241314.26000829000000037.14%3500000.2900000012
17Brendan PerliniAdmirals (Nas)LW/RW29235-116018154011295.00%240213.8800012000091041.94%3100000.2500000010
18Max ZimmerAdmirals (Nas)LW/RW162021000061233.33%0694.3200000000000033.33%600000.5800000000
19Simon StranskyAdmirals (Nas)LW/RW22011-240154205110%31496.8000000000020062.50%800000.1300000000
20Jere InnalaAdmirals (Nas)C5000000010000%040.990000100000000%30000000000000
21Casey FitzgeraldAdmirals (Nas)D6000-2601212010%510918.2600000000015000%00000000000000
Statistiques d’équipe totales ou en moyenne51063112175-111213354284707742355468.14%216834716.3714233714660812395528252.18%245700010.4226213858
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
1Christopher GibsonAdmirals (Nas)2691330.9003.12138521727170120.7504260240
2Antoine BibeauAdmirals (Nas)90400.8863.73370002320100000326000
Statistiques d’équipe totales ou en moyenne3591730.8973.251756219591801242926240


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 Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis ParDate de la Dernière TransactionBallotage forcé Waiver Possible Contrat Date du Signature du ContratForcer UFA Rappel d'urgence Type Salaire actuel Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Adam MarshAdmirals (Nas)LW/RW291997-08-22USANo160 Lbs6 ft0NoNoN/ANoNo22026-04-29FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Antoine BibeauAdmirals (Nas)G321994-05-01CANNo216 Lbs6 ft3NoNoFree AgentNoNo12024-07-07FalseFalsePro & Farm1,200,500$0$0$No---------------------------Lien
Brandon HalversonAdmirals (Nas)G301996-03-29USANo235 Lbs6 ft5NoNoFree AgentNoNo32026-07-03FalseFalsePro & Farm725,000$0$0$No725,000$725,000$-------725,000$725,000$-------NoNo-------Lien
Brendan PerliniAdmirals (Nas)LW/RW301996-04-27ENGNo211 Lbs6 ft3NoNoFree AgentNoNo32026-07-17FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------Lien
Casey FitzgeraldAdmirals (Nas)D291997-02-25USANo178 Lbs5 ft11NoNoTrade2026-09-28NoNo12024-04-29FalseFalsePro & Farm900,000$0$0$No---------------------------Lien
Christopher GibsonAdmirals (Nas)G331992-12-27FINNo217 Lbs6 ft2NoNoFree AgentNoNo12024-07-07FalseFalsePro & Farm1,000,500$0$0$No---------------------------Lien
Cole CandellaAdmirals (Nas)D281998-02-13CANNo195 Lbs6 ft2NoNoN/ANoNo22025-05-28FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Corey SchuenemanAdmirals (Nas)D311995-09-02USANo197 Lbs5 ft11NoNoFree Agent2025-02-01NoNo12025-07-03FalseFalsePro & Farm1,800,000$0$0$No---------------------------Lien
Jere InnalaAdmirals (Nas)C281998-03-17FINNo183 Lbs5 ft9NoNoProspectNoNo22025-06-02FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------Lien
Joel NystromAdmirals (Nas)D242002-05-14SWEYes178 Lbs5 ft11NoNoFree AgentNoNo12026-05-07FalseFalsePro & Farm900,000$0$0$No---------900,000$900,000$----------------Lien
Jonathan AngAdmirals (Nas)C281998-01-31CANNo165 Lbs5 ft11NoNoN/ANoNo22026-04-29FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------Lien
Liam O'BrienAdmirals (Nas)C321994-07-29CANNo215 Lbs6 ft1NoNoFree Agent2024-08-18NoNo32026-07-03FalseFalsePro & Farm1,325,000$0$0$No1,325,000$1,325,000$-------1,325,000$1,325,000$-------NoNo-------Lien
Louis CrevierAdmirals (Nas)D252001-05-04CANNo228 Lbs6 ft8NoNoFree AgentNoNo22025-05-28FalseFalsePro & Farm2,000,000$0$0$No2,000,000$--------2,000,000$--------No--------Lien
Marc Del GaizoAdmirals (Nas)D271999-10-11USANo188 Lbs5 ft11NoNoProspectNoNo12024-06-18FalseFalsePro & Farm750,000$0$0$No---------------------------Lien
Matthew PhillipsAdmirals (Nas)C/LW/RW281998-04-06CANNo165 Lbs5 ft8NoNoN/ANoNo22025-05-28FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------Lien
Max ZimmerAdmirals (Nas)LW/RW281997-10-29USANo187 Lbs6 ft0NoNoN/ANoNo22026-04-29FalseFalsePro & Farm700,000$0$0$No700,000$--------700,000$--------No--------Lien
Nathan KnoepkeAdmirals (Nas)D271999-04-08USANo202 Lbs6 ft3NoNoN/ANoNo22026-04-29FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Nikolai ProkhorkinAdmirals (Nas)LW/RW331993-09-17RUSNo200 Lbs6 ft3NoNoFree AgentNoNo32026-07-17FalseFalsePro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------Lien
Nikolay GoldobinAdmirals (Nas)LW/RW311995-10-07RUSNo191 Lbs6 ft0NoNoFree AgentNoNo32026-07-22FalseFalsePro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------Lien
Ostap Safin (sur la masse salariale)Admirals (Nas)LW/RW271999-02-11CZENo204 Lbs6 ft5NoNoN/ANoNo22026-04-29FalseFalsePro & Farm900,000$0$0$Yes900,000$--------900,000$--------No--------Lien
Otto Somppi (sur la masse salariale)Admirals (Nas)C281998-01-12FINNo190 Lbs6 ft1NoNoN/ANoNo22026-04-29FalseFalsePro & Farm1,200,000$0$0$Yes1,200,000$--------1,200,000$--------No--------Lien
Patrick HarperAdmirals (Nas)C281998-07-29USANo150 Lbs5 ft7NoNoN/ANoNo22026-04-29FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Phillip DigiuseppeAdmirals (Nas)LW/RW331993-10-09CANNo193 Lbs6 ft0NoNoFree Agent2024-11-12NoNo32026-07-22FalseFalsePro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------Lien
Simon StranskyAdmirals (Nas)LW/RW281997-12-21CZENo189 Lbs5 ft11NoNoN/ANoNo12025-05-28FalseFalsePro & Farm800,000$0$0$No---------------------------Lien
Stepan FalkovskyAdmirals (Nas)D291996-12-18BLRNo225 Lbs6 ft7NoNoN/ANoNo12024-04-29FalseFalsePro & Farm1,200,000$0$0$No---------------------------Lien
Tobias BjornfotAdmirals (Nas)D252001-04-06SWENo200 Lbs6 ft0NoNoProspectNoNo22025-06-02FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien
Tobias RiederAdmirals (Nas)LW/RW331993-01-10DEUNo189 Lbs5 ft10NoNoFree AgentNoNo32026-07-17FalseFalsePro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2729.04194 Lbs6 ft11.96953,741$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nikolai ProkhorkinLiam O'Brien25122
2Tobias RiederMatthew PhillipsPhillip Digiuseppe25122
3Nikolay GoldobinJonathan AngBrendan Perlini25122
4Liam O'BrienMatthew PhillipsJonathan Ang25122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Louis CrevierCorey Schueneman25122
2Stepan FalkovskyJoel Nystrom25122
3Tobias BjornfotMarc Del Gaizo25122
4Louis CrevierJoel Nystrom25122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nikolai ProkhorkinNikolay Goldobin50122
2Tobias RiederJonathan AngPhillip Digiuseppe50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Louis CrevierTobias Bjornfot50122
2Stepan FalkovskyJoel Nystrom50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Nikolay GoldobinJonathan Ang50122
2Nikolai Prokhorkin50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Louis CrevierMarc Del Gaizo50122
2Stepan FalkovskyJoel Nystrom50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
150122Louis CrevierTobias Bjornfot50122
2Nikolai Prokhorkin50122Stepan FalkovskyJoel Nystrom50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jonathan AngNikolay Goldobin50122
2Nikolai Prokhorkin50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Louis CrevierMarc Del Gaizo50122
2Stepan FalkovskyJoel Nystrom50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nikolai ProkhorkinLiam O'BrienLouis CrevierJoel Nystrom
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nikolai ProkhorkinLiam O'BrienLouis CrevierJoel Nystrom
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, Jonathan Ang, Nikolay GoldobinNikolai Prokhorkin, Jonathan AngNikolay Goldobin
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Tobias Bjornfot, Marc Del Gaizo, Stepan FalkovskyTobias BjornfotMarc Del Gaizo, Stepan Falkovsky
Tirs de pénalité
Jonathan Ang, Nikolay Goldobin, Nikolai Prokhorkin, , Tobias Rieder
Gardien
#1 : Christopher Gibson, #2 : Antoine Bibeau


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
TotalDomicile Visiteur
# 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 RI
1Barracuda2110000057-21010000006-61100000051420.50051015002514253422752602502158131234200.00%6350.00%051195753.40%536103751.69%23544153.29%694476687214377189
2Canucks10001000321000000000001000100032121.000358002514253332752602502134910135120.00%5180.00%051195753.40%536103751.69%23544153.29%694476687214377189
3Condors1010000035-21010000035-20000000000000.000369102514253232752602502128122163133.33%10100.00%051195753.40%536103751.69%23544153.29%694476687214377189
4Crunch1010000026-4000000000001010000026-400.000246002514253182752602502144101012200.00%50100.00%051195753.40%536103751.69%23544153.29%694476687214377189
5Griffins3110000179-22110000078-11000000101-130.500713201025142539127526025021723023565120.00%8187.50%051195753.40%536103751.69%23544153.29%694476687214377189
6Icehogs1000010023-1000000000001000010023-110.50024600251425342275260250213062144125.00%10100.00%051195753.40%536103751.69%23544153.29%694476687214377189
7Iowa Wild1000010023-1000000000001000010023-110.50024600251425320275260250213791118300.00%3166.67%051195753.40%536103751.69%23544153.29%694476687214377189
8Marlies1010000003-3000000000001010000003-300.0000000025142533327526025021286810200.00%4175.00%051195753.40%536103751.69%23544153.29%694476687214377189
9Reign201000101011-11010000068-21000001043120.5001015250025142537027526025021811617227457.14%5340.00%051195753.40%536103751.69%23544153.29%694476687214377189
10Roadrunners41300000915-62020000049-52110000056-120.250917260025142531232752602502113032366310220.00%12558.33%051195753.40%536103751.69%23544153.29%694476687214377189
11Rocket1010000014-3000000000001010000014-300.000123002514253182752602502135661011100.00%30100.00%051195753.40%536103751.69%23544153.29%694476687214377189
12Silver Knights31200000710-3211000006511010000015-420.33371320002514253732752602502186242943600.00%13653.85%051195753.40%536103751.69%23544153.29%694476687214377189
13StarsF1010000003-31010000003-30000000000000.0000000025142532827526025021288714100.00%10100.00%051195753.40%536103751.69%23544153.29%694476687214377189
14Thunderbirds4310000014104220000007342110000077060.7501423370025142531002752602502113734226615320.00%11281.82%151195753.40%536103751.69%23544153.29%694476687214377189
15Wolf Pack1010000002-21010000002-20000000000000.00000000251425326275260250213051017100.00%5180.00%051195753.40%536103751.69%23544153.29%694476687214377189
16Wranglers2020000015-4000000000002020000015-400.000123002514253602752602502162121029900.00%50100.00%051195753.40%536103751.69%23544153.29%694476687214377189
Total29717012116698-321349000003349-161638012113349-16210.3626611818420251425380027526025021920232215437761418.42%882472.73%151195753.40%536103751.69%23544153.29%694476687214377189
_Since Last GM Reset29717012116698-321349000003349-161638012113349-16210.3626611818420251425380027526025021920232215437761418.42%882472.73%151195753.40%536103751.69%23544153.29%694476687214377189
_Vs Conference25713012116383-201248000003347-141335012113036-6210.4206311217520251425370527526025021783205181388701318.57%712269.01%151195753.40%536103751.69%23544153.29%694476687214377189
_Vs Division1142001012734-7531000001115-4611001011619-3100.45527487500251425331327526025021362897817533618.18%28871.43%151195753.40%536103751.69%23544153.29%694476687214377189

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2921L26611818480092023221543720
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
2971712116698
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
134900003349
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
163812113349
Derniers 10 matchs
WLOTWOTL SOWSOL
370000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
761418.42%882472.73%1
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
275260250212514253
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
51195753.40%536103751.69%23544153.29%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
694476687214377189


Derniers matchs 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 - 2025-08-3025Roadrunners4Admirals3LSommaire du match
5 - 2025-09-0138Admirals1Roadrunners5LSommaire du match
6 - 2025-09-0250Barracuda6Admirals0LSommaire du match
7 - 2025-09-0359Admirals2Iowa Wild3LXSommaire du match
9 - 2025-09-0575Admirals4Roadrunners1WSommaire du match
11 - 2025-09-0788Admirals2Icehogs3LXSommaire du match
13 - 2025-09-09104StarsF3Admirals0LSommaire du match
15 - 2025-09-11123Silver Knights1Admirals3WSommaire du match
17 - 2025-09-13137Admirals5Barracuda1WSommaire du match
19 - 2025-09-15151Admirals4Reign3WXXSommaire du match
21 - 2025-09-17162Admirals3Canucks2WXSommaire du match
22 - 2025-09-18172Condors5Admirals3LSommaire du match
26 - 2025-09-22195Silver Knights4Admirals3LSommaire du match
28 - 2025-09-24218Roadrunners5Admirals1LSommaire du match
30 - 2025-09-26229Admirals0Wranglers3LSommaire du match
32 - 2025-09-28244Admirals0Griffins1LXXSommaire du match
34 - 2025-09-30260Thunderbirds1Admirals3WSommaire du match
36 - 2025-10-02270Admirals3Thunderbirds6LSommaire du match
38 - 2025-10-04290Admirals1Rocket4LSommaire du match
40 - 2025-10-06298Wolf Pack2Admirals0LSommaire du match
43 - 2025-10-09322Admirals4Thunderbirds1WSommaire du match
45 - 2025-10-11331Thunderbirds2Admirals4WSommaire du match
48 - 2025-10-14354Griffins4Admirals2LSommaire du match
50 - 2025-10-16369Admirals2Crunch6LSommaire du match
52 - 2025-10-18385Reign8Admirals6LSommaire du match
54 - 2025-10-20403Admirals1Silver Knights5LSommaire du match
56 - 2025-10-22416Griffins4Admirals5WSommaire du match
58 - 2025-10-24433Admirals0Marlies3LSommaire du match
60 - 2025-10-26449Admirals1Wranglers2LSommaire du match
62 - 2025-10-28457BruinsF-Admirals-
65 - 2025-10-31480Moose-Admirals-
67 - 2025-11-02494Admirals-Islanders-
69 - 2025-11-04514Iowa Wild-Admirals-
71 - 2025-11-06526Admirals-Wolves-
72 - 2025-11-07541Admirals-Canucks-
74 - 2025-11-09554Monsters-Admirals-
77 - 2025-11-12574Comets-Admirals-
79 - 2025-11-14589Admirals-Islanders-
81 - 2025-11-16607Barracuda-Admirals-
84 - 2025-11-19628Admirals-Roadrunners-
86 - 2025-11-21641Admirals-Gulls-
87 - 2025-11-22651Bears-Admirals-
90 - 2025-11-25669Admirals-SenatorsF-
91 - 2025-11-26680Reign-Admirals-
94 - 2025-11-29696Admirals-Eagles-
96 - 2025-12-01710SenatorsF-Admirals-
98 - 2025-12-03730Admirals-Roadrunners-
100 - 2025-12-05738Admirals-Barracuda-
101 - 2025-12-06749Icehogs-Admirals-
104 - 2025-12-09772Silver Knights-Admirals-
106 - 2025-12-11782Admirals-StarsF-
109 - 2025-12-14803Admirals-Phantoms-
110 - 2025-12-15812Roadrunners-Admirals-
113 - 2025-12-18835Eagles-Admirals-
115 - 2025-12-20853Admirals-Checkers-
118 - 2025-12-23869Condors-Admirals-
120 - 2025-12-25884Admirals-Silver Knights-
122 - 2025-12-27902Americans-Admirals-
124 - 2025-12-29918Admirals-Eagles-
126 - 2025-12-31934Wranglers-Admirals-
129 - 2026-01-03952Admirals-Firebirds-
131 - 2026-01-05970Admirals-Gulls-
132 - 2026-01-06974Icehogs-Admirals-
135 - 2026-01-09999PenguinsF-Admirals-
137 - 2026-01-111015Admirals-Icehogs-
140 - 2026-01-141034Admirals-Griffins-
141 - 2026-01-151041Iowa Wild-Admirals-
144 - 2026-01-181063Eagles-Admirals-
146 - 2026-01-201076Admirals-Monsters-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2026-01-231098Wranglers-Admirals-
152 - 2026-01-261124Gulls-Admirals-
155 - 2026-01-291139Admirals-Monsters-
157 - 2026-01-311156Monsters-Admirals-
159 - 2026-02-021172Admirals-Reign-
161 - 2026-02-041186StarsF-Admirals-
165 - 2026-02-081213StarsF-Admirals-
167 - 2026-02-101222Admirals-StarsF-
171 - 2026-02-141247Canucks-Admirals-
174 - 2026-02-171273Canucks-Admirals-
176 - 2026-02-191289Admirals-Iowa Wild-
177 - 2026-02-201295Admirals-Condors-
179 - 2026-02-221311Gulls-Admirals-
182 - 2026-02-251325Admirals-Condors-
183 - 2026-02-261343Phantoms-Admirals-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4530
Assistance26,00013,000
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
29 3000 - 100.00% 178,800$2,324,400$3000125

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
906,274$ 2,365,100$ 2,365,100$ 100,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 873,659$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
5,185,200$ 124 13,397$ 1,661,228$




Admirals Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Admirals Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Admirals Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
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

Admirals Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Admirals Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA