Essayer le nouveau site
Veuillez faire pivoter votre appareil en mode paysage pour une meilleure expérience.
Connexion

Admirals
GP: 23 | W: 8 | L: 12 | OTL: 3 | P: 19
GF: 51 | GA: 70 | PP%: 18.33% | PK%: 72.31%
DG: Simon Demèlo | Morale : 41 | Moyenne d’équipe : 63
Prochains matchs #369 vs Crunch

Centre de jeu
Thunderbirds
12-11-1, 25pts
2
4 Admirals
8-12-3, 19pts
Team Stats
W1SéquenceL1
5-5-1Fiche domicile3-8-0
7-6-0Fiche domicile5-4-3
4-6-0Derniers 10 matchs3-6-1
3.08Buts par match 2.22
3.42Buts contre par match 3.04
15.49%Pourcentage en avantage numérique18.33%
70.53%Pourcentage en désavantage numérique72.31%
Griffins
16-6-3, 35pts
4
2 Admirals
8-12-3, 19pts
Team Stats
OTW1SéquenceL1
9-2-0Fiche domicile3-8-0
7-4-3Fiche domicile5-4-3
9-0-1Derniers 10 matchs3-6-1
3.44Buts par match 2.22
2.92Buts contre par match 3.04
21.25%Pourcentage en avantage numérique18.33%
72.13%Pourcentage en désavantage numérique72.31%
Admirals
8-12-3, 19pts
2025-10-16
Crunch
11-10-0, 22pts
Statistiques d’équipe
L1SéquenceL2
3-8-0Fiche domicile7-4-0
5-4-3Fiche visiteur4-6-0
3-6-110 derniers matchs7-3-0
2.22Buts par match 3.86
3.04Buts contre par match 3.86
18.33%Pourcentage en avantage numérique32.14%
72.31%Pourcentage en désavantage numérique81.63%
Reign
5-11-6, 16pts
2025-10-18
Admirals
8-12-3, 19pts
Statistiques d’équipe
L9SéquenceL1
0-7-5Fiche domicile3-8-0
5-4-1Fiche visiteur5-4-3
1-9-010 derniers matchs3-6-1
3.36Buts par match 2.22
4.23Buts contre par match 2.22
18.46%Pourcentage en avantage numérique18.33%
70.13%Pourcentage en désavantage numérique72.31%
Admirals
8-12-3, 19pts
2025-10-20
Silver Knights
12-7-3, 27pts
Statistiques d’équipe
L1SéquenceW3
3-8-0Fiche domicile7-3-1
5-4-3Fiche visiteur5-4-2
3-6-110 derniers matchs7-3-0
2.22Buts par match 3.73
3.04Buts contre par match 3.73
18.33%Pourcentage en avantage numérique32.43%
72.31%Pourcentage en désavantage numérique73.68%
Meneurs d'équipe
Buts
Ostap Safin
8
Passes
Louis Crevier
7
Points
Lane Pederson
11
Plus/Moins
Otto Somppi
3
Victoires
Christopher Gibson
8
Pourcentage d’arrêts
Christopher Gibson
0.911

Statistiques d’équipe
Buts pour
51
2.22 GFG
Tirs pour
653
28.39 Avg
Pourcentage en avantage numérique
18.3%
11 GF
Début de zone offensive
40.7%
Buts contre
70
3.04 GAA
Tirs contre
714
31.04 Avg
Pourcentage en désavantage numérique
72.3%%
18 GA
Début de la zone défensive
41.7%
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 Pro28
Équipe Mineure18
Limite Contrat46 / 56
Espoirs53


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
1Lane Pederson0X97.0073469075728279747372667566665258486702921,350,000$
2Otto Somppi0X100.0065458872707378757672707666595154476602821,200,000$
3Liam O'Brien0X97.0083457375747076717566687166715238446503231,325,000$
4Nikolay Goldobin87XX100.0057439672716969686665666564735442446403131,000,000$
5Nikolai Prokhorkin0XX100.0077498369737275696465666864715934506403331,000,000$
6Ostap Safin0XX100.007658697273767668696869646055505448640272900,000$
7Phillip Digiuseppe0XX100.0060459870717282695966676865735834446403331,000,000$
8Jonathan Ang0X100.006147897266747071766869686056505444640282900,000$
9Tobias Rieder0XX100.0058459970707575696066666964686430446403331,000,000$
10Brendan Perlini0XX100.005945957075716869596665666371604244630303900,000$
11Simon Stransky0XX100.006644897268697764646568695360515445620281800,000$
12Matthew Phillips (A)0XXX100.006245887264727860757165636760505447620282900,000$
13Louis Crevier0X100.0070459173777876744573647755524866476702522,000,000$
14Corey Schueneman0X100.0059469973718074724571667666564742476603111,800,000$
15Joel Nystrom (R)0X100.006445927567747774457365735945457035650241900,000$
16Marc Del Gaizo0X100.006347887369777872457167705952476249650271750,000$
17Tobias Bjornfot0X100.006245917270777570456963745664476647650252750,000$
18Stepan Falkovsky0X100.0071458372767677674569666855675450476502911,200,000$
Rayé
1Max Zimmer0XX100.005945937268737865636467656060495435620282700,000$
2Jere Innala0X100.006845937267687466616366696349474229610282900,000$
3Adam Marsh0XX100.007658598070646161615960596062566227600292500,000$
4Patrick Harper0X100.005945867262667160706666636651465427600282500,000$
5Casey Fitzgerald0X100.007545787265716765456961686055505451630291900,000$
6Nathan Knoepke0X100.006445907272696959455953645149465827590272500,000$
7Cole Candella0X100.005342887070676559455656665946455427580282500,000$
MOYENNE D’ÉQUIPE99.76664688727073746859676569616051514263
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 Gibson099.007876758079808482838383525646336503311,000,500$
2Antoine Bibeau0100.007581808178788279808179515646536403211,200,500$
Rayé
1Brandon Halverson0100.00797876858068767273769146504235610303725,000$
MOYENNE D’ÉQUIPE99.6777787782797581787980845054454063
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
1Lane PedersonAdmirals (Nas)C20561104011455114369.80%536018.030332120000331054.46%40400000.6101000012
2Liam O'BrienAdmirals (Nas)C235611-8220594146214210.87%340717.711129490001172054.07%41800000.5401000100
3Ostap SafinAdmirals (Nas)LW/RW2383110175331240132820.00%036916.062025511011200157.14%2100000.6000001201
4Louis CrevierAdmirals (Nas)D233710-522025303710248.11%3054623.752351846000142000%000000.3700000000
5Otto SomppiAdmirals (Nas)C18551032010365217359.62%129716.51011837000051153.71%35000000.6701000101
6Joel NystromAdmirals (Nas)D12178-580105217104.76%1725321.11112718011024100%000000.6300000000
7Matthew PhillipsAdmirals (Nas)C/LW/RW23268-600318256208.00%228312.3400000000010059.46%11100000.5600000000
8Tobias BjornfotAdmirals (Nas)D23178-51001622265143.85%2544519.351231544000013000%000000.3600000000
9Corey SchuenemanAdmirals (Nas)D16167240815299153.45%1735522.230111325000028000%000000.3900000010
10Marc Del GaizoAdmirals (Nas)D23167-314102919196165.26%2739617.26011714000022000%000000.3500002100
11Nikolai ProkhorkinAdmirals (Nas)LW/RW23257-1201034173113246.45%239016.971238510000461050.00%7200000.3612200101
12Phillip DigiuseppeAdmirals (Nas)LW/RW23347-820514508326.00%135115.28022651000000047.62%2100000.4000000010
13Stepan FalkovskyAdmirals (Nas)D23167-418033181511146.67%2241718.16101517011043000%000000.3400000000
14Jonathan AngAdmirals (Nas)C23246-87527374515314.44%634715.13011120001270047.12%41600000.3400010001
15Nikolay GoldobinAdmirals (Nas)LW/RW23235-3006163915275.13%340817.762026350003480050.91%5500000.2411000000
16Brendan PerliniAdmirals (Nas)LW/RW23224-7401310277257.41%131613.7500001000061040.74%2700000.2500000010
17Tobias RiederAdmirals (Nas)LW/RW23213020210465314.35%231113.53000616000000032.00%2500000.1900000002
18Max ZimmerAdmirals (Nas)LW/RW112021000061233.33%0686.2200000000000033.33%600000.5800000000
19Simon StranskyAdmirals (Nas)LW/RW16011-240144205110%21489.2600000000020062.50%800000.1300000000
20Jere InnalaAdmirals (Nas)C4000000010000%041.230000100000000%30000000000000
21Casey FitzgeraldAdmirals (Nas)D6000-2601212010%510918.2600000000015000%00000000000000
Statistiques d’équipe totales ou en moyenne4024885133-61166303503716271884387.66%171659016.3911182911647912373997252.04%193700000.4026213648
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)208930.9112.71110721505620120.7504200240
2Antoine BibeauAdmirals (Nas)70300.8873.53289001715000000320000
Statistiques d’équipe totales ou en moyenne2781230.9062.881396216771201242320240


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
Lane PedersonAdmirals (Nas)C291997-08-04CANNo190 Lbs6 ft0NoNoN/ANoNo22026-04-29FalseFalsePro & Farm1,350,000$0$0$No1,350,000$--------1,350,000$--------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 SafinAdmirals (Nas)LW/RW271999-02-11CZENo204 Lbs6 ft5NoNoN/ANoNo22026-04-29FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------Lien
Otto SomppiAdmirals (Nas)C281998-01-12FINNo190 Lbs6 ft1NoNoN/ANoNo22026-04-29FalseFalsePro & Farm1,200,000$0$0$No1,200,000$--------1,200,000$--------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
2829.04194 Lbs6 ft11.96967,893$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nikolai ProkhorkinLane PedersonOstap Safin25122
2Tobias RiederOtto SomppiPhillip Digiuseppe25122
3Nikolay GoldobinJonathan AngBrendan Perlini25122
4Lane PedersonMatthew PhillipsLiam O'Brien25122
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 ProkhorkinLane PedersonOstap Safin50122
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 GoldobinLane Pederson50122
2Nikolai ProkhorkinOstap Safin50122
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
1Ostap Safin50122Louis CrevierTobias Bjornfot50122
2Nikolai Prokhorkin50122Stepan FalkovskyJoel Nystrom50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jonathan AngLane Pederson50122
2Nikolai ProkhorkinOstap Safin50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Louis CrevierMarc Del Gaizo50122
2Stepan FalkovskyJoel Nystrom50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nikolai ProkhorkinLane PedersonOstap SafinLouis CrevierJoel Nystrom
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nikolai ProkhorkinLane PedersonOstap SafinLouis CrevierJoel Nystrom
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Ostap Safin, 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
Lane Pederson, Nikolay Goldobin, Nikolai Prokhorkin, Ostap Safin, 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
1Barracuda2110000057-21010000006-61100000051420.50051015001910203422232042112158131234200.00%6350.00%040678052.05%41679952.07%18633655.36%560385538168300152
2Canucks10001000321000000000001000100032121.000358001910203332232042112134910135120.00%5180.00%040678052.05%41679952.07%18633655.36%560385538168300152
3Condors1010000035-21010000035-20000000000000.000369101910203232232042112128122163133.33%10100.00%040678052.05%41679952.07%18633655.36%560385538168300152
4Griffins2010000125-31010000024-21000000101-110.2502351019102035522320421121532623353133.33%8187.50%040678052.05%41679952.07%18633655.36%560385538168300152
5Icehogs1000010023-1000000000001000010023-110.50024600191020342223204211213062144125.00%10100.00%040678052.05%41679952.07%18633655.36%560385538168300152
6Iowa Wild1000010023-1000000000001000010023-110.50024600191020320223204211213791118300.00%3166.67%040678052.05%41679952.07%18633655.36%560385538168300152
7Reign10000010431000000000001000001043121.0004610001910203512232042112142511123133.33%3233.33%040678052.05%41679952.07%18633655.36%560385538168300152
8Roadrunners41300000915-62020000049-52110000056-120.250917260019102031232232042112113032366310220.00%12558.33%040678052.05%41679952.07%18633655.36%560385538168300152
9Rocket1010000014-3000000000001010000014-300.000123001910203182232042112135661011100.00%30100.00%040678052.05%41679952.07%18633655.36%560385538168300152
10Silver Knights21100000651211000006510000000000020.50061117001910203592232042112141171231600.00%4250.00%040678052.05%41679952.07%18633655.36%560385538168300152
11StarsF1010000003-31010000003-30000000000000.0000000019102032822320421121288714100.00%10100.00%040678052.05%41679952.07%18633655.36%560385538168300152
12Thunderbirds4310000014104220000007342110000077060.7501423370019102031002232042112113734226615320.00%11281.82%140678052.05%41679952.07%18633655.36%560385538168300152
13Wolf Pack1010000002-21010000002-20000000000000.00000000191020326223204211213051017100.00%5180.00%040678052.05%41679952.07%18633655.36%560385538168300152
14Wranglers1010000003-3000000000001010000003-300.0000000019102033322320421121315416300.00%20100.00%040678052.05%41679952.07%18633655.36%560385538168300152
Total23612012115170-191138000002237-151234012112933-4190.413519114220191020365322320421121714187168359601118.33%651872.31%140678052.05%41679952.07%18633655.36%560385538168300152
_Since Last GM Reset23612012115170-191138000002237-151234012112933-4190.413519114220191020365322320421121714187168359601118.33%651872.31%140678052.05%41679952.07%18633655.36%560385538168300152
_Vs Conference21610012115064-141037000002235-131133012112829-1190.452508913920191020360922320421121649176152332581017.24%571770.18%140678052.05%41679952.07%18633655.36%560385538168300152
_Vs Division1132001012734-7521000001115-4611001011619-380.36427487500191020331322320421121362897817533618.18%28871.43%140678052.05%41679952.07%18633655.36%560385538168300152

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2319L1519114265371418716835920
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
2361212115170
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
113800002237
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
123412112933
Derniers 10 matchs
WLOTWOTL SOWSOL
360001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
601118.33%651872.31%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
223204211211910203
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
40678052.05%41679952.07%18633655.36%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
560385538168300152


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 - 2025-10-16369Admirals-Crunch-
52 - 2025-10-18385Reign-Admirals-
54 - 2025-10-20403Admirals-Silver Knights-
56 - 2025-10-22416Griffins-Admirals-
58 - 2025-10-24433Admirals-Marlies-
60 - 2025-10-26449Admirals-Wranglers-
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
Assistance22,00011,000
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
31 3000 - 100.00% 178,800$1,966,800$3000125

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
745,115$ 2,710,100$ 2,710,100$ 100,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 718,475$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
5,542,800$ 135 15,272$ 2,061,720$




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