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Milwaukee Admirals
GP: 34 | W: 17 | L: 15 | OTL: 2 | P: 52
GF: 97 | GA: 109 | PP%: 27.72% | PK%: 72.85%
DG: Jaryn | Morale : 40 | Moyenne d’équipe : 67
Prochains matchs #488 vs Pee Dee Pride

Centre de jeu
Greenville Swamp Rabbits
11-18-5, 36pts
2
3 Milwaukee Admirals
17-15-2, 52pts
Team Stats
L4SéquenceSOL1
8-7-2Fiche domicile9-5-2
3-11-3Fiche domicile8-10-0
2-5-3Derniers 10 matchs6-3-1
2.65Buts par match 2.85
3.21Buts contre par match 3.21
21.30%Pourcentage en avantage numérique27.72%
71.43%Pourcentage en désavantage numérique72.85%
Cleveland Monsters
19-9-6, 58pts
6
5 Milwaukee Admirals
17-15-2, 52pts
Team Stats
W4SéquenceSOL1
11-4-2Fiche domicile9-5-2
8-5-4Fiche domicile8-10-0
8-1-1Derniers 10 matchs6-3-1
3.47Buts par match 2.85
3.21Buts contre par match 3.21
25.55%Pourcentage en avantage numérique27.72%
81.67%Pourcentage en désavantage numérique72.85%
Milwaukee Admirals
17-15-2, 52pts
Jour 87
Pee Dee Pride
18-9-7, 56pts
Statistiques d’équipe
SOL1SéquenceW3
9-5-2Fiche domicile6-6-5
8-10-0Fiche visiteur12-3-2
6-3-110 derniers matchs5-3-2
2.85Buts par match 3.26
3.21Buts contre par match 3.26
27.72%Pourcentage en avantage numérique21.05%
72.85%Pourcentage en désavantage numérique79.34%
Milwaukee Admirals
17-15-2, 52pts
Jour 89
Rockford IceHogs
17-12-5, 52pts
Statistiques d’équipe
SOL1SéquenceW4
9-5-2Fiche domicile8-5-1
8-10-0Fiche visiteur9-7-4
6-3-110 derniers matchs6-4-0
2.85Buts par match 3.06
3.21Buts contre par match 3.06
27.72%Pourcentage en avantage numérique18.66%
72.85%Pourcentage en désavantage numérique76.40%
Laval Rocket
15-16-4, 45pts
Jour 92
Milwaukee Admirals
17-15-2, 52pts
Statistiques d’équipe
L1SéquenceSOL1
7-8-2Fiche domicile9-5-2
8-8-2Fiche visiteur8-10-0
3-7-010 derniers matchs6-3-1
3.23Buts par match 2.85
3.63Buts contre par match 2.85
19.42%Pourcentage en avantage numérique27.72%
75.78%Pourcentage en désavantage numérique72.85%
Meneurs d'équipe
Buts
Reilly Smith
20
Passes
Adam Henrique
28
Points
Adam Henrique
43
Plus/Moins
Parker Wotherspoon
14
Victoires
KARI PIIROINEN
12
Pourcentage d’arrêts
KARI PIIROINEN
0.918

Statistiques d’équipe
Buts pour
97
2.85 GFG
Tirs pour
932
27.41 Avg
Pourcentage en avantage numérique
27.7%
28 GF
Début de zone offensive
32.5%
Buts contre
109
3.21 GAA
Tirs contre
1170
34.41 Avg
Pourcentage en désavantage numérique
72.8%%
41 GA
Début de la zone défensive
42.5%
Informations de l'équipe

Directeur généralJaryn
DivisionPacific Division
ConférenceWestern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,513
Billets de saison1,200


Informations de la formation

Équipe Pro26
Équipe Mineure20
Limite contact 46 / 250
Espoirs10


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
1Reilly Smith0X96.0067408177618078716275696871817855407003411,700,000$
2Walker Duehr0X96.008451796685747562556766726476825540680272500,000$
3Corey Perry0X100.005555696180797162696568696499995540670401500,000$
4Mark Kastelic0X100.008655616587707560786463726275715540670262800,000$
5Pontus Holmberg0X100.006145767573777564696865726675665540670261500,000$
6Tyler Pitlick0X100.0087497764727569666468656563817755406603311,500,000$
7Cole Bardreau0X100.007540707561686762656463706577585540650312665,000$
8Kiefer Sherwood0X100.0076477769587574606964637062797055406503032,184,000$
9Alex Belzile0X100.007044766772707162655861706279695540640332500,000$
10Jonathan Gruden0X100.008145717960657360605661706573665540640251500,000$
11Jere Innala0X100.005240777261636360605659676276765540620271500,000$
12Parker Wotherspoon0X99.0055447976926977645065617661766955407002721,525,000$
13Ben Thomas0X100.005342827980687062506061686175675540660291500,000$
14John Gilmour0X100.005148796978707662506260685779785540660321625,000$
15Mike Reilly0X98.006144827461727765506863646177805540660313500,000$
16Julius Honka0X100.005440768347656862506461636275585840630294625,000$
17Michael Kapla0X100.005820797655727260505659665863588540630301500,000$
Rayé
1Adam Henrique0X94.0069428072658086728773706168827555406903511,500,000$
2EMIL PETTERSSON0XXX100.00563367776760606870716462687676524066N0311250,000$
3MARKUS LJUNGH0X100.00523868746060606870726563688291524066N0341250,000$
4PER ASLUND0XX100.00483859726960606748686566679194524066N0381250,000$
5LASSE LAPPALAINEN0X100.00544575708160606348726374608694524068N0361250,000$
6VILLE LAJUNEN0X100.00544071727860607148726763658894524068N0371250,000$
MOYENNE D’ÉQUIPE99.26634374727069706460666468647976564066
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
1MARKUS RUUSU0100.00816060787472737373727172615240700271250,000$
2SAMI RAJANIEMI098.00766060747373747272737078655240700321250,000$
Rayé
1KARI PIIROINEN0100.00816060767774757777747567565240710241250,000$
MOYENNE D’ÉQUIPE99.3379606076757374747473727261524070
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Adam HenriqueMilwaukee Admirals (SJS)C3215284323157373115387813.04%2079124.7371219207203361135056.14%7981722001.0901100630
2Reilly SmithMilwaukee Admirals (SJS)RW31201939356305491135457214.81%2280626.0241216156502221051145.23%3252613010.9701114250
3Walker DuehrMilwaukee Admirals (SJS)RW34131427-535158586105284212.38%2275122.1154913630005571044.87%781514100.7200102223
4Mark KastelicMilwaukee Admirals (SJS)C3291423-74620897062154014.52%1856417.633369550002281050.88%39797000.8200202022
5Cole BardreauMilwaukee Admirals (SJS)LW285152012371564455421429.26%847116.852025330003920044.52%146169100.8500210020
6Pontus HolmbergMilwaukee Admirals (SJS)RW341010208295444792344710.87%1650814.94000192028463141.30%46148000.7900001311
7Jonathan GrudenMilwaukee Admirals (SJS)LW3461218-9803059528122507.41%2058217.124591669000031036.36%331510000.6200213002
8Jere InnalaMilwaukee Admirals (SJS)LW3451015-515539627010297.14%1855716.391236390001260132.00%25145000.5400100102
9Parker WotherspoonMilwaukee Admirals (SJS)D342121414502039705222203.85%6587825.821453831011119100%02232000.3200112001
10Mike ReillyMilwaukee Admirals (SJS)D34012129342043534921140%4276622.550113640002113000%01023000.3100013011
11Tyler PitlickMilwaukee Admirals (SJS)RW3473104121034292871525.00%83309.72000114000133134.21%7654010.6000002101
12Ben ThomasMilwaukee Admirals (SJS)D340772100134621590%3461818.19000349011265000%01225000.2300000000
13Corey PerryMilwaukee Admirals (SJS)RW332240160173023658.70%82808.49000020000210140.00%3036000.2900000000
14John GilmourMilwaukee Admirals (SJS)D34044-6115165111880%4564819.08000153000178000%0819000.1200010000
15Garrett PilonSan Jose SharksC212134161015321551313.33%426312.54000020000100140.44%13632000.2300110001
16Ian ColeSan Jose SharksD14123-77735264716666.25%2234024.31022535000133100%017000.1800205000
17Michael KaplaMilwaukee Admirals (SJS)D34033-4120132613430%3441712.2900003000015000%0015000.1401000000
18Alex BelzileMilwaukee Admirals (SJS)RW34022-26013182050%01634.82000060000150050.00%3013000.2400000000
19Anton LindholmSan Jose SharksD17011140182300%1945.540000000014000%002000.2100000000
20Julius HonkaMilwaukee Admirals (SJS)D33000-5604229530%1833310.1100001000021000%03700000000000
21Kiefer SherwoodMilwaukee Admirals (SJS)RW12000-140741000%0504.1800013000000062.50%81100000000000
Statistiques d’équipe totales ou en moyenne62797171268858722574896295630550110.15%4251021816.302745721027303693697617649.30%2128195234220.520314724151614
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
1KARI PIIROINENMilwaukee Admirals (SJS)24121000.9182.81130101617463930000209223
2SAMI RAJANIEMIMilwaukee Admirals (SJS)165520.8893.807430047424217000.33331420210
Statistiques d’équipe totales ou en moyenne40171520.9083.1720440110811706100033429433


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 Salaire restantPlafond 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 HenriqueMilwaukee Admirals (SJS)C351990-02-06CANNo194 Lbs6 ft0NoNoTrade2025-11-13NoNo12025-09-30FalseFalsePro & Farm1,500,000$821,809$0$0$No---------------------------Lien
Alex BelzileMilwaukee Admirals (SJS)RW331991-08-31CANNo196 Lbs6 ft0NoNoFree AgentNoNo22025-10-20FalseFalsePro & Farm500,000$273,936$0$0$No500,000$--------500,000$--------No--------Lien
Ben ThomasMilwaukee Admirals (SJS)D291996-05-28CANNo187 Lbs6 ft1NoNoTrade2025-11-13NoNo12025-10-27FalseFalsePro & Farm500,000$273,936$0$0$No---------------------------Lien
Cole BardreauMilwaukee Admirals (SJS)LW311993-07-22USANo185 Lbs5 ft10NoNoTrade2026-03-27NoNo22025-09-30FalseFalsePro & Farm665,000$364,335$0$0$No665,000$--------665,000$--------No--------Lien
Corey Perry (contrat à 1 volet)Milwaukee Admirals (SJS)RW401985-05-16CANNo208 Lbs6 ft3NoNoFree AgentNoNo12025-10-20FalseFalsePro & Farm500,000$273,936$0$0$No---------------------------Lien
EMIL PETTERSSON (contrat à 1 volet)Milwaukee Admirals (SJS)C/LW/RW311994-01-14SWENo176 Lbs6 ft2YesNoFree AgentNoNo12026-04-20FalseFalseFarm Only250,000$136,968$0$0$No---------------------------Lien
Jere InnalaMilwaukee Admirals (SJS)LW271998-03-17FINNo183 Lbs5 ft9NoNoFree AgentNoNo12025-11-24FalseFalsePro & Farm500,000$273,936$0$0$No---------------------------Lien
John GilmourMilwaukee Admirals (SJS)D321993-05-17CANNo207 Lbs6 ft0NoNoTrade2025-11-13NoNo12025-09-30FalseFalsePro & Farm625,000$342,420$0$0$No---------------------------
Jonathan GrudenMilwaukee Admirals (SJS)LW252000-05-04USANo172 Lbs6 ft0NoNoTrade2025-11-13NoNo12025-10-20FalseFalsePro & Farm500,000$273,936$0$0$No---------------------------Lien
Julius HonkaMilwaukee Admirals (SJS)D291995-12-03FINNo180 Lbs5 ft11NoNoTrade2025-11-13NoNo42025-10-24FalseFalsePro & Farm625,000$342,420$0$0$No625,000$625,000$625,000$------625,000$625,000$625,000$------NoNoNo------
KARI PIIROINEN (contrat à 1 volet)Milwaukee Admirals (SJS)G242001-07-01FINNo176 Lbs6 ft1NoNoFree AgentNoNo12025-11-24FalseFalseFarm Only250,000$136,968$0$0$No---------------------------Lien
Kiefer SherwoodMilwaukee Admirals (SJS)RW301995-03-31USANo194 Lbs6 ft0NoNoFree AgentNoNo32025-10-20FalseFalsePro & Farm2,184,000$1,196,553$0$0$No2,184,000$2,184,000$-------2,184,000$2,184,000$-------NoNo-------Lien
LASSE LAPPALAINEN (contrat à 1 volet)Milwaukee Admirals (SJS)D361989-06-07FINNo198 Lbs6 ft2YesNoFree AgentNoNo12026-04-20FalseFalseFarm Only250,000$136,968$0$0$No---------------------------Lien
MARKUS LJUNGH (contrat à 1 volet)Milwaukee Admirals (SJS)C341991-01-11SWENo181 Lbs5 ft9YesNoFree AgentNoNo12026-04-20FalseFalseFarm Only250,000$136,968$0$0$No---------------------------Lien
MARKUS RUUSU (contrat à 1 volet)Milwaukee Admirals (SJS)G271997-08-23FINNo176 Lbs6 ft2NoNoFree AgentNoNo12025-11-24FalseFalseFarm Only250,000$136,968$0$0$No---------------------------Lien
Mark KastelicMilwaukee Admirals (SJS)C261999-03-11USANo209 Lbs6 ft4NoNoAssign ManuallyNoNo22025-09-30FalseFalsePro & Farm800,000$438,298$0$0$No800,000$--------800,000$--------No--------Lien
Michael KaplaMilwaukee Admirals (SJS)D301994-09-19USANo201 Lbs6 ft0NoNoFree AgentNoNo12025-11-24FalseFalsePro & Farm500,000$273,936$0$0$No---------------------------Lien
Mike ReillyMilwaukee Admirals (SJS)D311993-07-13USANo196 Lbs6 ft1NoNoFree AgentNoNo32025-10-27FalseFalsePro & Farm500,000$273,936$0$0$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien
PER ASLUND (contrat à 1 volet)Milwaukee Admirals (SJS)LW/RW381986-08-21SWENo183 Lbs6 ft2YesNoFree AgentNoNo12026-04-20FalseFalseFarm Only250,000$136,968$0$0$No---------------------------Lien
Parker WotherspoonMilwaukee Admirals (SJS)D271997-08-24CANNo190 Lbs6 ft1NoNoAssign ManuallyNoNo22025-09-30FalseFalsePro & Farm1,525,000$835,505$0$0$No1,525,000$--------1,525,000$--------No--------Lien
Pontus HolmbergMilwaukee Admirals (SJS)RW261999-03-09SWENo187 Lbs6 ft0NoNoAssign ManuallyNoNo12025-09-30FalseFalsePro & Farm500,000$273,936$0$0$No---------------------------Lien
Reilly SmithMilwaukee Admirals (SJS)RW341991-04-01CANNo185 Lbs6 ft0NoNoAssign ManuallyNoNo12025-09-30FalseFalsePro & Farm1,700,000$931,383$0$0$No---------------------------Lien
SAMI RAJANIEMI (contrat à 1 volet)Milwaukee Admirals (SJS)G321992-08-20FINNo183 Lbs6 ft0NoNoFree AgentNoNo12025-11-24FalseFalseFarm Only250,000$136,968$0$0$No---------------------------Lien
Tyler PitlickMilwaukee Admirals (SJS)RW331991-11-01USANo201 Lbs6 ft2NoNoTrade2025-11-13NoNo12025-09-30FalseFalsePro & Farm1,500,000$821,809$0$0$No---------------------------Lien
VILLE LAJUNEN (contrat à 1 volet)Milwaukee Admirals (SJS)D371988-03-08FINNo194 Lbs6 ft1YesNoFree AgentNoNo12026-04-20FalseFalseFarm Only250,000$136,968$0$0$No---------------------------Lien
Walker DuehrMilwaukee Admirals (SJS)RW271997-11-23USANo209 Lbs6 ft2NoNoAssign ManuallyNoNo22025-09-30FalseFalsePro & Farm500,000$273,936$0$0$No500,000$--------500,000$--------No--------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2630.92190 Lbs6 ft11.46677,846$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Cole BardreauReilly Smith40122
2Jonathan GrudenMark KastelicWalker Duehr30122
3Jere InnalaReilly SmithPontus Holmberg20122
4Walker DuehrCorey Perry10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Parker WotherspoonMike Reilly40122
2John GilmourBen Thomas30122
3Michael KaplaJulius Honka20122
4Parker WotherspoonMike Reilly10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Cole BardreauReilly Smith60122
2Jonathan GrudenMark KastelicWalker Duehr40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Parker WotherspoonMike Reilly60122
2John GilmourBen Thomas40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Reilly Smith60122
2Walker DuehrPontus Holmberg40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Parker WotherspoonMike Reilly60122
2John GilmourBen Thomas40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Reilly Smith60122Parker WotherspoonMike Reilly60122
240122John GilmourBen Thomas40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Reilly Smith60122
2Walker DuehrPontus Holmberg40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Parker WotherspoonMike Reilly60122
2John GilmourBen Thomas40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Cole BardreauReilly SmithParker WotherspoonMike Reilly
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Cole BardreauReilly SmithParker WotherspoonMike Reilly
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Tyler Pitlick, Kiefer Sherwood, Alex BelzileTyler Pitlick, Kiefer SherwoodAlex Belzile
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Michael Kapla, Julius Honka, John GilmourMichael KaplaJulius Honka, John Gilmour
Tirs de pénalité
Reilly Smith, , Walker Duehr, Pontus Holmberg, Mark Kastelic
Gardien
#1 : SAMI RAJANIEMI, #2 : MARKUS RUUSU
Lignes d’attaque personnalisées en prolongation
Reilly Smith, , Walker Duehr, Pontus Holmberg, Mark Kastelic, Corey Perry, Tyler Pitlick, Kiefer Sherwood, Cole Bardreau, Jonathan Gruden
Lignes de défense personnalisées en prolongation
Parker Wotherspoon, Mike Reilly, John Gilmour, Ben Thomas, Michael Kapla


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
1Abbotsford Canucks11000000532000000000001100000053231.000561100213936126223326372133014111622100.00%30100.00%030964547.91%40884348.40%27349555.15%622295763335659331
2Athens Rock Lobsters1000010034-11000010034-10000000000010.33335800213936131223326372133916112622100.00%30100.00%030964547.91%40884348.40%27349555.15%622295763335659331
3Bakersfield Condors22000000743110000004311100000031261.000712190021393615322332637213682933447228.57%14285.71%130964547.91%40884348.40%27349555.15%622295763335659331
4Bloomington Bison11000000312110000003120000000000031.000347002139361262233263721319321198337.50%30100.00%030964547.91%40884348.40%27349555.15%622295763335659331
5Bridgeport Islanders1010000026-4000000000001010000026-400.000246002139361282233263721333101423500.00%7357.14%030964547.91%40884348.40%27349555.15%622295763335659331
6Cleveland Monsters30200001612-62010000159-41010000013-210.111611170021393618022332637213109474856400.00%19763.16%030964547.91%40884348.40%27349555.15%622295763335659331
7Coachella Valley Firebirds11000000312110000003120000000000031.0003470021393612022332637213331213215240.00%40100.00%030964547.91%40884348.40%27349555.15%622295763335659331
8Colorado Eagles2020000015-41010000003-31010000012-100.000112002139361432233263721378282640700.00%8275.00%030964547.91%40884348.40%27349555.15%622295763335659331
9Grand Rapids Griffins2010100056-11010000024-21000100032120.33358130021393615222332637213792020384125.00%5260.00%030964547.91%40884348.40%27349555.15%622295763335659331
10Greensboro Gargoyles1010000012-11010000012-10000000000000.000123002139361202233263721337141514000%50100.00%030964547.91%40884348.40%27349555.15%622295763335659331
11Greenville Swamp Rabbits11000000321110000003210000000000031.000347002139361272233263721342158153266.67%4175.00%030964547.91%40884348.40%27349555.15%622295763335659331
12Henderson Silver Knights20200000714-71010000048-41010000036-300.000712190021393615822332637213611861508337.50%13746.15%030964547.91%40884348.40%27349555.15%622295763335659331
13Iowa Heartlanders11000000523110000005230000000000031.000510150021393614422332637213291613294125.00%4175.00%130964547.91%40884348.40%27349555.15%622295763335659331
14Macon Whoopee2110000078-1000000000002110000078-130.50071118002139361612233263721386271351400.00%4175.00%030964547.91%40884348.40%27349555.15%622295763335659331
15Orlando Solar Bears1010000013-2000000000001010000013-200.000112002139361212233263721334104123200.00%3166.67%030964547.91%40884348.40%27349555.15%622295763335659331
16Pee Dee Pride22000000725110000005231100000020261.000713200121393615422332637213432724445360.00%12191.67%130964547.91%40884348.40%27349555.15%622295763335659331
17Providence Bruins1010000013-2000000000001010000013-200.00012300213936128223326372134115914100.00%20100.00%030964547.91%40884348.40%27349555.15%622295763335659331
18Reading Royals22000000853110000004311100000042261.000815230021393615522332637213581855438450.00%10370.00%030964547.91%40884348.40%27349555.15%622295763335659331
19Rockford IceHogs2110000068-2110000004311010000025-330.50061117002139361712233263721367292545500.00%10460.00%030964547.91%40884348.40%27349555.15%622295763335659331
20San Diego Gulls2110000089-1000000000002110000089-130.500814220021393615022332637213731561518112.50%8450.00%030964547.91%40884348.40%27349555.15%622295763335659331
21Trois Rivieres Lions11000000211110000002110000000000031.00023500213936118223326372132513619300.00%30100.00%030964547.91%40884348.40%27349555.15%622295763335659331
22Utica Devils1010000016-5000000000001010000016-500.00011200213936128223326372134583611100.00%4175.00%030964547.91%40884348.40%27349555.15%622295763335659331
23Wheeling Nailers11000000523000000000001100000052331.00059140021393613822332637213411511215240.00%3166.67%030964547.91%40884348.40%27349555.15%622295763335659331
Total3416150110197109-121695001014848018710010004961-12520.510971632600121393619322233263721311704195757131012827.72%1514172.85%330964547.91%40884348.40%27349555.15%622295763335659331
_Since Last GM Reset3416150110197109-121695001014848018710010004961-12520.510971632600121393619322233263721311704195757131012827.72%1514172.85%330964547.91%40884348.40%27349555.15%622295763335659331
_Vs Conference241210010017378-51164000013437-31366010003941-2390.5427312219501213936164922332637213804287411518752128.00%1133370.80%230964547.91%40884348.40%27349555.15%622295763335659331
_Vs Division963000003433143100000141315320000020200180.6673455890021393612352233263721327480222200391538.46%411465.85%030964547.91%40884348.40%27349555.15%622295763335659331

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
3452SOL197163260932117041957571301
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
341615110197109
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
169501014848
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
1871010004961
Derniers 10 matchs
WLOTWOTL SOWSOL
630001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1012827.72%1514172.85%3
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
223326372132139361
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
30964547.91%40884348.40%27349555.15%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
622295763335659331


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
212Milwaukee Admirals5Abbotsford Canucks3WSommaire du match
425Coachella Valley Firebirds1Milwaukee Admirals3WSommaire du match
641Henderson Silver Knights8Milwaukee Admirals4LSommaire du match
855Milwaukee Admirals4Reading Royals2WSommaire du match
1069Milwaukee Admirals4San Diego Gulls3WSommaire du match
1284Milwaukee Admirals1Macon Whoopee4LSommaire du match
1497Bloomington Bison1Milwaukee Admirals3WSommaire du match
15107Milwaukee Admirals1Utica Devils6LSommaire du match
17120Athens Rock Lobsters4Milwaukee Admirals3LXSommaire du match
20140Milwaukee Admirals1Providence Bruins3LSommaire du match
24154Milwaukee Admirals1Colorado Eagles2LSommaire du match
27168Milwaukee Admirals3Bakersfield Condors1WSommaire du match
29175Grand Rapids Griffins4Milwaukee Admirals2LSommaire du match
33196Cleveland Monsters3Milwaukee Admirals0LSommaire du match
35206Pee Dee Pride2Milwaukee Admirals5WSommaire du match
38220Milwaukee Admirals2Rockford IceHogs5LSommaire du match
41234Rockford IceHogs3Milwaukee Admirals4WSommaire du match
45251Milwaukee Admirals2Pee Dee Pride0WSommaire du match
48263Milwaukee Admirals1Cleveland Monsters3LSommaire du match
51275Milwaukee Admirals3Grand Rapids Griffins2WXSommaire du match
54294Bakersfield Condors3Milwaukee Admirals4WSommaire du match
57303Colorado Eagles3Milwaukee Admirals0LSommaire du match
60317Milwaukee Admirals1Orlando Solar Bears3LSommaire du match
62329Greensboro Gargoyles2Milwaukee Admirals1LSommaire du match
64349Trois Rivieres Lions1Milwaukee Admirals2WSommaire du match
66364Milwaukee Admirals5Wheeling Nailers2WSommaire du match
68378Milwaukee Admirals6Macon Whoopee4WSommaire du match
70391Milwaukee Admirals4San Diego Gulls6LSommaire du match
72405Reading Royals3Milwaukee Admirals4WSommaire du match
74419Milwaukee Admirals3Henderson Silver Knights6LSommaire du match
76423Milwaukee Admirals2Bridgeport Islanders6LSommaire du match
78439Iowa Heartlanders2Milwaukee Admirals5WSommaire du match
80450Greenville Swamp Rabbits2Milwaukee Admirals3WSommaire du match
84472Cleveland Monsters6Milwaukee Admirals5LXXSommaire du match
87488Milwaukee Admirals-Pee Dee Pride-
89503Milwaukee Admirals-Rockford IceHogs-
92515Laval Rocket-Milwaukee Admirals-
93522Milwaukee Admirals-Laval Rocket-
95533Milwaukee Admirals-Savannah Ghost Pirates-
98554Savannah Ghost Pirates-Milwaukee Admirals-
100573Rochester Americans-Milwaukee Admirals-
102583Milwaukee Admirals-Lehigh Valley Phantoms-
105602Milwaukee Admirals-Coachella Valley Firebirds-
107613Abbotsford Canucks-Milwaukee Admirals-
110625Milwaukee Admirals-Bloomington Bison-
113635Colorado Eagles-Milwaukee Admirals-
115649Milwaukee Admirals-Bakersfield Condors-
118659Grand Rapids Griffins-Milwaukee Admirals-
121675Milwaukee Admirals-Trois Rivieres Lions-
123689Milwaukee Admirals-Greensboro Gargoyles-
125703Orlando Solar Bears-Milwaukee Admirals-
128727Providence Bruins-Milwaukee Admirals-
130742Milwaukee Admirals-Athens Rock Lobsters-
132752Utica Devils-Milwaukee Admirals-
135770Macon Whoopee-Milwaukee Admirals-
137783San Diego Gulls-Milwaukee Admirals-
139797Milwaukee Admirals-Reading Royals-
142811Henderson Silver Knights-Milwaukee Admirals-
144823Wheeling Nailers-Milwaukee Admirals-
146830Bridgeport Islanders-Milwaukee Admirals-
148844Milwaukee Admirals-Iowa Heartlanders-
152868Milwaukee Admirals-Greenville Swamp Rabbits-
154881Milwaukee Admirals-Rochester Americans-
156892Lehigh Valley Phantoms-Milwaukee Admirals-
158899Milwaukee Admirals-Cleveland Monsters-
160915Pee Dee Pride-Milwaukee Admirals-
162930Rockford IceHogs-Milwaukee Admirals-
164939Milwaukee Admirals-Grand Rapids Griffins-
166959Bakersfield Condors-Milwaukee Admirals-
168968Milwaukee Admirals-Colorado Eagles-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
171987Macon Whoopee-Milwaukee Admirals-
1731000San Diego Gulls-Milwaukee Admirals-
1751014Reading Royals-Milwaukee Admirals-
1771028Milwaukee Admirals-Henderson Silver Knights-
1801047Coachella Valley Firebirds-Milwaukee Admirals-
1811061Milwaukee Admirals-Coachella Valley Firebirds-
1831076Abbotsford Canucks-Milwaukee Admirals-
1841090Milwaukee Admirals-Abbotsford Canucks-
1861105Bloomington Bison-Milwaukee Admirals-
1871119Milwaukee Admirals-Bloomington Bison-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3111
Assistance25,63814,577
Assistance PCT80.12%91.11%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
24 2513 - 83.78% 59,695$955,125$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
646,865$ 1,512,400$ 0$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 646,865$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,432,688$ 103 8,045$ 828,635$




Milwaukee 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

Milwaukee 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

Milwaukee 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

Milwaukee 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

Milwaukee 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