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Connexion

Admirals
GP: 9 | W: 3 | L: 4 | OTL: 2 | P: 8
GF: 20 | GA: 27 | PP%: 10.00% | PK%: 60.00%
DG: Simon Demèlo | Morale : 45 | Moyenne d’équipe : 64
Prochains matchs #151 vs Reign

Centre de jeu
Silver Knights
4-4-1, 9pts
1
3 Admirals
3-4-2, 8pts
Team Stats
L2SéquenceW2
2-2-0Fiche domicile1-3-0
2-2-1Fiche domicile2-1-2
4-4-1Derniers 10 matchs3-4-2
3.11Buts par match 2.22
2.89Buts contre par match 3.00
11.11%Pourcentage en avantage numérique10.00%
78.95%Pourcentage en désavantage numérique60.00%
Admirals
3-4-2, 8pts
5
1 Barracuda
3-6-1, 7pts
Team Stats
W2SéquenceL1
1-3-0Fiche domicile1-4-0
2-1-2Fiche domicile2-2-1
3-4-2Derniers 10 matchs3-6-1
2.22Buts par match 3.10
3.00Buts contre par match 3.30
10.00%Pourcentage en avantage numérique29.41%
60.00%Pourcentage en désavantage numérique74.07%
Admirals
3-4-2, 8pts
2025-09-12
Reign
3-2-4, 10pts
Statistiques d’équipe
W2SéquenceW1
1-3-0Fiche domicile0-2-3
2-1-2Fiche visiteur3-0-1
3-4-210 derniers matchs3-2-4
2.22Buts par match 3.56
3.00Buts contre par match 3.56
10.00%Pourcentage en avantage numérique23.33%
60.00%Pourcentage en désavantage numérique62.96%
Admirals
3-4-2, 8pts
2025-09-14
Canucks
3-6-0, 6pts
Statistiques d’équipe
W2SéquenceL2
1-3-0Fiche domicile2-3-0
2-1-2Fiche visiteur1-3-0
3-4-210 derniers matchs3-6-0
2.22Buts par match 2.44
3.00Buts contre par match 2.44
10.00%Pourcentage en avantage numérique28.00%
60.00%Pourcentage en désavantage numérique78.79%
Condors
6-3-0, 12pts
2025-09-15
Admirals
3-4-2, 8pts
Statistiques d’équipe
SOW1SéquenceW2
1-3-0Fiche domicile1-3-0
5-0-0Fiche visiteur2-1-2
6-3-010 derniers matchs3-4-2
3.56Buts par match 2.22
2.56Buts contre par match 2.22
28.13%Pourcentage en avantage numérique10.00%
74.07%Pourcentage en désavantage numérique60.00%
Meneurs d'équipe
Buts
Lane Pederson
3
Passes
Otto Somppi
4
Points
Otto Somppi
6
Plus/Moins
Lane Pederson
4
Victoires
Christopher Gibson
3
Pourcentage d’arrêts
Christopher Gibson
0.899

Statistiques d’équipe
Buts pour
20
2.22 GFG
Tirs pour
255
28.33 Avg
Pourcentage en avantage numérique
10.0%
2 GF
Début de zone offensive
41.9%
Buts contre
27
3.00 GAA
Tirs contre
269
29.89 Avg
Pourcentage en désavantage numérique
60.0%%
8 GA
Début de la zone défensive
40.0%
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 contact 46 / 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 Pederson0X100.0073469075728279747372667566665258486702921,350,000$
2Otto Somppi0X100.0065458872707378757672707666595154446602821,200,000$
3Liam O'Brien0X100.0083457375747076717566687166715238456503231,325,000$
4Nikolay Goldobin87XX100.0057439672716969686665666564735442456403031,000,000$
5Nikolai Prokhorkin0XX100.0077498369737275696465666864715934516403231,000,000$
6Ostap Safin0XX100.007658697273767668696869646055505449640272900,000$
7Phillip Digiuseppe0XX100.0060459870717282695966676865735834456403231,000,000$
8Jonathan Ang0X100.006147897266747071766869686056505448640282900,000$
9Tobias Rieder0XX100.0058459970707575696066666964686430456403331,000,000$
10Brendan Perlini0XX100.005945957075716869596665666371604245630303900,000$
11Simon Stransky0XX100.006644897268697764646568695360515448620281800,000$
12Matthew Phillips (A)0XXX100.006245887264727860757165636760505448620282900,000$
13Louis Crevier0X100.0070459173777876744573647755524866486702522,000,000$
14Corey Schueneman0X100.0059469973718074724571667666564742486603111,800,000$
15Emil Johansson0X100.0065458572687879764570657357665254486603031,300,000$
16Marc Del Gaizo0X100.006347887369777872457167705952476249650261750,000$
17Tobias Bjornfot0X100.006245917270777570456963745664476648650252750,000$
18Stepan Falkovsky0X100.0071458372767677674569666855675450486502911,200,000$
Rayé
1Max Zimmer0XX100.005945937268737865636467656060495441620282700,000$
2Jere Innala0X100.006845937267687466616366696349474241610282900,000$
3Adam Marsh0XX100.007658598070646161615960596062566241600292500,000$
4Patrick Harper0X100.005945867262667160706666636651465441600282500,000$
5Joel Nystrom (R)0X100.006445927567747774457365735945457041650241900,000$
6Nathan Knoepke0X100.006445907272696959455953645149465841590272500,000$
7Cole Candella0X100.005342887070676559455656665946455441580282500,000$
MOYENNE D’ÉQUIPE100.00654688727073746859676569616051514564
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 Gibson099.007876758079808482838383525646406503311,000,500$
2Antoine Bibeau0100.007581808178788279808179515646506403211,200,500$
Rayé
1Brandon Halverson0100.00797876858068767273769146504242610303725,000$
MOYENNE D’ÉQUIPE99.6777787782797581787980845054454463
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
1Otto SomppiAdmirals (Nas)C92463006202112149.52%013414.99011517000001056.82%17600000.8900000101
2Corey SchuenemanAdmirals (Nas)D9145020411187105.56%1222224.70000918000015000%000000.4500000010
3Lane PedersonAdmirals (Nas)C93254208112141114.29%313414.97000000000130052.98%16800000.7400000001
4Tobias BjornfotAdmirals (Nas)D9145-1203915276.67%1217519.5110171700001000%000000.5700000000
5Emil JohanssonAdmirals (Nas)D90441409445100%716418.29011318000014000%000000.4900000000
6Louis CrevierAdmirals (Nas)D9044140111015460%1421824.26011618000116000%000000.3700000000
7Marc Del GaizoAdmirals (Nas)D9134-17510662716.67%713715.290000200003000%000000.5800001100
8Nikolai ProkhorkinAdmirals (Nas)LW/RW913441010146851212.50%014916.610112180000141075.00%1200000.5400200100
9Brendan PerliniAdmirals (Nas)LW/RW9224-320611331215.38%012413.8300001000001033.33%1200000.6400000010
10Ostap SafinAdmirals (Nas)LW/RW9314395134165718.75%013515.01000019000000028.57%700000.5900001000
11Jonathan AngAdmirals (Nas)C9224-200913238228.70%213515.04000000001130050.00%16200000.5900000001
12Nikolay GoldobinAdmirals (Nas)LW/RW91124000715576.67%115317.001014170001130025.00%1200000.2600000000
13Phillip DigiuseppeAdmirals (Nas)LW/RW9112-50005161116.25%013715.28000118000000035.71%1400000.2900000000
14Stepan FalkovskyAdmirals (Nas)D9022-11001274360%816518.370000000007000%000000.2400000000
15Liam O'BrienAdmirals (Nas)C9101-5402412158146.67%013915.50000218000000058.50%14700000.1400000000
16Simon StranskyAdmirals (Nas)LW/RW9011-22011418470%212313.7300000000010071.43%700000.1600000000
17Matthew PhillipsAdmirals (Nas)C/LW/RW9011-6001311380%111713.0300000000000060.00%1000000.1700000000
18Tobias RiederAdmirals (Nas)LW/RW910132013161106.25%211612.9900000000000025.00%1200000.1700000001
Statistiques d’équipe totales ou en moyenne162203959-36020142136255821817.84%71268516.582463918700031163053.18%73900000.4400202324
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)93420.8992.9648600242380000090010
2Antoine BibeauAdmirals (Nas)20000.9033.1058003310000009000
Statistiques d’équipe totales ou en moyenne113420.9002.985440027269000099010


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
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
Emil JohanssonAdmirals (Nas)D301996-05-06SWENo189 Lbs5 ft11NoNoN/ANoNo32026-04-29FalseFalsePro & Farm1,300,000$0$0$No1,300,000$1,300,000$-------1,300,000$1,300,000$-------NoNo-------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)D261999-10-11USANo188 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/RW321993-09-17RUSNo200 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/RW301995-10-07RUSNo191 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/RW321993-10-09CANNo193 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
2828.93195 Lbs6 ft12.04982,179$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tobias RiederOtto SomppiOstap Safin25014
2Nikolay GoldobinLane PedersonNikolai Prokhorkin25014
3Matthew PhillipsLiam O'BrienPhillip Digiuseppe25014
4Brendan PerliniJonathan AngSimon Stransky25014
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Emil JohanssonLouis Crevier25023
2Corey SchuenemanMarc Del Gaizo25023
3Tobias BjornfotStepan Falkovsky25122
4Louis CrevierCorey Schueneman25122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nikolai ProkhorkinOtto SomppiNikolay Goldobin50005
2Phillip DigiuseppeLiam O'BrienOstap Safin50005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Corey SchuenemanLouis Crevier50023
2Emil JohanssonTobias Bjornfot50023
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Lane PedersonNikolai Prokhorkin50122
2Jonathan AngNikolay Goldobin50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Louis CrevierEmil Johansson50122
2Corey SchuenemanStepan Falkovsky50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Lane Pederson50122Emil JohanssonMarc Del Gaizo50122
2Liam O'Brien50122Corey SchuenemanTobias Bjornfot50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Lane PedersonOstap Safin50122
2Liam O'BrienTobias Rieder50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Corey SchuenemanEmil Johansson50122
2Tobias BjornfotLouis Crevier50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nikolay GoldobinLane PedersonOstap SafinEmil JohanssonStepan Falkovsky
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Phillip DigiuseppeLiam O'BrienBrendan PerliniLouis CrevierCorey Schueneman
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Liam O'Brien, Nikolay Goldobin, Phillip DigiuseppeOstap Safin, Brendan PerliniSimon Stransky
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Marc Del Gaizo, Tobias Bjornfot, Louis CrevierMarc Del GaizoLouis Crevier, Emil Johansson
Tirs de pénalité
Lane Pederson, Nikolay Goldobin, Nikolai Prokhorkin, Phillip Digiuseppe, 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
TotalDomicileVisiteur
# 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
1Barracuda2110000057-21010000006-61100000051420.5005101500956042857984758131234200.00%6350.00%017130755.70%14529349.49%7713357.89%2261562026211560
2Icehogs1000010023-1000000000001000010023-110.5002460095604285798473062144125.00%10100.00%017130755.70%14529349.49%7713357.89%2261562026211560
3Iowa Wild1000010023-1000000000001000010023-110.5002460095602085798473791118300.00%3166.67%017130755.70%14529349.49%7713357.89%2261562026211560
4Roadrunners31200000810-21010000034-12110000056-120.333815230095609185798471012826505120.00%8362.50%017130755.70%14529349.49%7713357.89%2261562026211560
5Silver Knights11000000312110000003120000000000021.000369009560328579847157212500.00%110.00%017130755.70%14529349.49%7713357.89%2261562026211560
6StarsF1010000003-31010000003-30000000000000.000000009560288579847288714100.00%10100.00%017130755.70%14529349.49%7713357.89%2261562026211560
Total934002002027-741300000614-8521002001413180.4442039590095602558579847269716014220210.00%20860.00%017130755.70%14529349.49%7713357.89%2261562026211560
_Since Last GM Reset934002002027-741300000614-8521002001413180.4442039590095602558579847269716014220210.00%20860.00%017130755.70%14529349.49%7713357.89%2261562026211560
_Vs Conference934002002027-741300000614-8521002001413180.4442039590095602558579847269716014220210.00%20860.00%017130755.70%14529349.49%7713357.89%2261562026211560
_Vs Division600001001219-72000000037-440000100912-310.083122335009560181857984719651469613215.38%13469.23%017130755.70%14529349.49%7713357.89%2261562026211560

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
98W2203959255269716014200
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
93402002027
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4130000614
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
52102001413
Derniers 10 matchs
WLOTWOTL SOWSOL
340200
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
20210.00%20860.00%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
85798479560
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
17130755.70%14529349.49%7713357.89%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2261562026211560


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 - 2025-08-2725Roadrunners4Admirals3LSommaire du match
5 - 2025-08-2938Admirals1Roadrunners5LSommaire du match
6 - 2025-08-3050Barracuda6Admirals0LSommaire du match
7 - 2025-08-3159Admirals2Iowa Wild3LXSommaire du match
9 - 2025-09-0275Admirals4Roadrunners1WSommaire du match
11 - 2025-09-0488Admirals2Icehogs3LXSommaire du match
13 - 2025-09-06104StarsF3Admirals0LSommaire du match
15 - 2025-09-08123Silver Knights1Admirals3WSommaire du match
17 - 2025-09-10137Admirals5Barracuda1WSommaire du match
19 - 2025-09-12151Admirals-Reign-
21 - 2025-09-14162Admirals-Canucks-
22 - 2025-09-15172Condors-Admirals-
26 - 2025-09-19195Silver Knights-Admirals-
28 - 2025-09-21218Roadrunners-Admirals-
30 - 2025-09-23229Admirals-Wranglers-
32 - 2025-09-25244Admirals-Griffins-
34 - 2025-09-27260Thunderbirds-Admirals-
36 - 2025-09-29270Admirals-Thunderbirds-
38 - 2025-10-01290Admirals-Rocket-
40 - 2025-10-03298Wolf Pack-Admirals-
43 - 2025-10-06322Admirals-Thunderbirds-
45 - 2025-10-08331Thunderbirds-Admirals-
48 - 2025-10-11354Griffins-Admirals-
50 - 2025-10-13369Admirals-Crunch-
52 - 2025-10-15385Reign-Admirals-
54 - 2025-10-17403Admirals-Silver Knights-
56 - 2025-10-19416Griffins-Admirals-
58 - 2025-10-21433Admirals-Marlies-
60 - 2025-10-23449Admirals-Wranglers-
62 - 2025-10-25457BruinsF-Admirals-
65 - 2025-10-28480Moose-Admirals-
67 - 2025-10-30494Admirals-Islanders-
69 - 2025-11-01514Iowa Wild-Admirals-
71 - 2025-11-03526Admirals-Wolves-
72 - 2025-11-04541Admirals-Canucks-
74 - 2025-11-06554Monsters-Admirals-
77 - 2025-11-09574Comets-Admirals-
79 - 2025-11-11589Admirals-Islanders-
81 - 2025-11-13607Barracuda-Admirals-
84 - 2025-11-16628Admirals-Roadrunners-
86 - 2025-11-18641Admirals-Gulls-
87 - 2025-11-19651Bears-Admirals-
90 - 2025-11-22669Admirals-SenatorsF-
91 - 2025-11-23680Reign-Admirals-
94 - 2025-11-26696Admirals-Eagles-
96 - 2025-11-28710SenatorsF-Admirals-
98 - 2025-11-30730Admirals-Roadrunners-
100 - 2025-12-02738Admirals-Barracuda-
101 - 2025-12-03749Icehogs-Admirals-
104 - 2025-12-06772Silver Knights-Admirals-
106 - 2025-12-08782Admirals-StarsF-
109 - 2025-12-11803Admirals-Phantoms-
110 - 2025-12-12812Roadrunners-Admirals-
113 - 2025-12-15835Eagles-Admirals-
115 - 2025-12-17853Admirals-Checkers-
118 - 2025-12-20869Condors-Admirals-
120 - 2025-12-22884Admirals-Silver Knights-
122 - 2025-12-24902Americans-Admirals-
124 - 2025-12-26918Admirals-Eagles-
126 - 2025-12-28934Wranglers-Admirals-
129 - 2025-12-31952Admirals-Firebirds-
131 - 2026-01-02970Admirals-Gulls-
132 - 2026-01-03974Icehogs-Admirals-
135 - 2026-01-06999PenguinsF-Admirals-
137 - 2026-01-081015Admirals-Icehogs-
140 - 2026-01-111034Admirals-Griffins-
141 - 2026-01-121041Iowa Wild-Admirals-
144 - 2026-01-151063Eagles-Admirals-
146 - 2026-01-171076Admirals-Monsters-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2026-01-201098Wranglers-Admirals-
152 - 2026-01-231124Gulls-Admirals-
155 - 2026-01-261139Admirals-Monsters-
157 - 2026-01-281156Monsters-Admirals-
159 - 2026-01-301172Admirals-Reign-
161 - 2026-02-011186StarsF-Admirals-
165 - 2026-02-051213StarsF-Admirals-
167 - 2026-02-071222Admirals-StarsF-
171 - 2026-02-111247Canucks-Admirals-
174 - 2026-02-141273Canucks-Admirals-
176 - 2026-02-161289Admirals-Iowa Wild-
177 - 2026-02-171295Admirals-Condors-
179 - 2026-02-191311Gulls-Admirals-
182 - 2026-02-221325Admirals-Condors-
183 - 2026-02-231343Phantoms-Admirals-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4530
Assistance8,0004,000
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
38 3000 - 100.00% 178,800$715,200$3000125

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
277,516$ 2,750,100$ 2,750,100$ 100,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 267,724$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
6,794,400$ 166 15,490$ 2,571,340$




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