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Admirals
GP: 35 | W: 6 | L: 28 | OTL: 1 | P: 13
GF: 124 | GA: 211 | PP%: 24.21% | PK%: 67.61%
DG: Keith | Morale : 23 | Moyenne d’équipe : 57
Prochains matchs #389 vs Broncos

Centre de jeu
Admirals
6-28-1, 13pts
4
FINAL
5 Marlies
21-12-3, 45pts
Team Stats
L3SéquenceW2
2-14-1Fiche domicile9-6-2
4-14-0Fiche domicile12-6-1
1-9-0Derniers 10 matchs7-3-0
3.54Buts par match 4.31
6.03Buts contre par match 3.47
24.21%Pourcentage en avantage numérique26.80%
67.61%Pourcentage en désavantage numérique78.02%
Admirals
6-28-1, 13pts
1
FINAL
5 Broncos
13-16-5, 31pts
Team Stats
L3SéquenceW1
2-14-1Fiche domicile8-10-0
4-14-0Fiche domicile5-6-5
1-9-0Derniers 10 matchs3-5-2
3.54Buts par match 3.53
6.03Buts contre par match 4.21
24.21%Pourcentage en avantage numérique20.55%
67.61%Pourcentage en désavantage numérique61.76%
Broncos
13-16-5, 31pts
Jour 78
Admirals
6-28-1, 13pts
Statistiques d’équipe
W1SéquenceL3
8-10-0Fiche domicile2-14-1
5-6-5Fiche visiteur4-14-0
3-5-210 derniers matchs1-9-0
3.53Buts par match 3.54
4.21Buts contre par match 3.54
20.55%Pourcentage en avantage numérique24.21%
61.76%Pourcentage en désavantage numérique67.61%
Admirals
6-28-1, 13pts
Jour 81
Bruins
10-20-5, 25pts
Statistiques d’équipe
L3SéquenceL3
2-14-1Fiche domicile4-11-3
4-14-0Fiche visiteur6-9-2
1-9-010 derniers matchs2-8-0
3.54Buts par match 3.31
6.03Buts contre par match 3.31
24.21%Pourcentage en avantage numérique23.29%
67.61%Pourcentage en désavantage numérique69.00%
Broncos
13-16-5, 31pts
Jour 82
Admirals
6-28-1, 13pts
Statistiques d’équipe
W1SéquenceL3
8-10-0Fiche domicile2-14-1
5-6-5Fiche visiteur4-14-0
3-5-210 derniers matchs1-9-0
3.53Buts par match 3.54
4.21Buts contre par match 3.54
20.55%Pourcentage en avantage numérique24.21%
61.76%Pourcentage en désavantage numérique67.61%
Meneurs d'équipe
Jonny BrodzinskiButs
Jonny Brodzinski
12
Alexey ToropchenkoPasses
Alexey Toropchenko
22
Alexey ToropchenkoPoints
Alexey Toropchenko
30
Max SassonPlus/Moins
Max Sasson
-2
Dennis HildebyVictoires
Dennis Hildeby
5
Nikke KokkoPourcentage d’arrêts
Nikke Kokko
0.884

Statistiques d’équipe
Buts pour
124
3.54 GFG
Tirs pour
1247
35.63 Avg
Pourcentage en avantage numérique
24.2%
23 GF
Début de zone offensive
39.5%
Buts contre
211
6.03 GAA
Tirs contre
1349
38.54 Avg
Pourcentage en désavantage numérique
67.6%%
23 GA
Début de la zone défensive
37.3%
Informations de l'équipe

Directeur généralKeith
EntraîneurJacques Martin
DivisionMetropolitan
ConférenceEastern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro25
Équipe Mineure19
Limite contact 44 / 50
Espoirs9


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
1Frank Nazar (R)X100.00635686706878716962687065645560041640212500,000$
2Alexey ToropchenkoX100.00846186668171907050655169506366039640262500,000$
3Jonny BrodzinskiX100.00645595687569687362637160517574039640322500,000$
4Elmer Soderblom (R)X100.00775887658971576650676159515861053620244500,000$
5Oskar Bäck (R)X100.00605593647369845966645072506266037610252600,000$
6Max SassonX100.00605099646465576558605759506262040580251500,000$
7Carl GrundstromX100.00855880637165715850615056506564036580282500,000$
8John HaydenX100.00736184588057545568525057507168059560302500,000$
9Justin Robidas (R)X100.00503589576150515550505450515664026520223500,000$
10Nikita GrebenkinX100.00595785587650515050505048506262023510222500,000$
11Danil GushchinX100.00505776515753535250495048506363022500233500,000$
12Joel HanleyX100.00706484626674726750605175558078037650341500,000$
13Henry ThrunX100.00686783637672766750615265556163036630241500,000$
14Ryan SheaX100.00625984627968646250545070556970035620282500,000$
15Isaiah George (R)X100.00595790617167616450565265555559038590213500,000$
16Ville Ottavainen (R)X100.00553594587750525050605049555970037540233500,000$
Rayé
1Brett Berard (R)X97.08705587656165606650596457515860030590233500,000$
2Devin KaplanX100.00503589577150515050505050505355020510213500,000$
3Jack FinleyX100.00503589578050505050505050505959020510232700,000$
4Alex Barré-BouletX100.00504353576250515050505050506564020510282500,000$
5Nikita PrishchepovX100.00525089576950505050505050505355020510212500,000$
6Isak RosenX100.00505089576350514950505049505657023500222500,000$
MOYENNE D’ÉQUIPE99.8762528661716161595357545852626403357
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
1Dennis Hildeby (R)100.005163608352464646465050595902530243500,000$
2Nikke Kokko (R)100.0050605971525249494950505252034530213500,000$
Rayé
1Spencer Martin100.0050646073505050505050596969033550301500,000$
MOYENNE D’ÉQUIPE100.005062607651494848485053606002354
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jacques Martin5050505050501CAN715500,000$


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
1Alexey ToropchenkoAdmirals (NYI)RW2682230-23140583969216011.59%752220.093581059000050061.54%3900001.1500000032
2Jonny BrodzinskiAdmirals (NYI)C26121628-2420950112437310.71%1048718.7534722570001190056.92%57800011.1500000212
3Frank NazarAdmirals (NYI)C26101626-2000156581197012.35%653920.743699601014452055.07%67000000.9600000111
4Joel HanleyAdmirals (NYI)D2631922-2316061324313296.98%5467425.941451252000030000%000000.6500000510
5Brett BerardAdmirals (NYI)LW2511819-2100212975204314.67%649719.9122413570003241042.11%3800000.7600000211
6Carl GrundstromAdmirals (NYI)RW2661117-26160611746153113.04%548418.640441059000010054.84%3100000.7000000122
7Cole SillingerNew York IslandersC/LW1510717-1220182676234613.16%436824.592028320110231041.67%2400010.9200000222
8Henry ThrunAdmirals (NYI)D2641317-3710055353082413.33%4164324.733361553000030000%000000.5300000001
9Isaiah GeorgeAdmirals (NYI)D2651116-304019294061812.50%4758722.593252359000031000%000000.5400000001
10Oskar BäckAdmirals (NYI)C2651015-262020715213549.62%846818.03022490000181058.07%47700000.6400000100
11Ryan SheaAdmirals (NYI)D2611112-3014032232311254.35%4362624.110221055000031000%000000.3800000020
12Max SassonAdmirals (NYI)C267310-2206152281531.82%31786.8510112000020058.90%14600001.1200000003
13Elmer SoderblomAdmirals (NYI)LW7268-900851971510.53%116623.73011118000090053.33%1500000.9600000010
14Nikita GrebenkinAdmirals (NYI)RW26145-246024111910185.26%241215.8700004000010050.00%2600000.2400000000
15Ville OttavainenAdmirals (NYI)D26134-138014932333.33%2143416.73000115000014000%000000.1800000100
16Erik HaulaNew York IslandersLW2202-24027131315.38%74723.93000020000300100.00%200000.8400000000
17Danil GushchinAdmirals (NYI)LW26112-29001911208155.00%543616.81000080000110048.28%2900000.0900000000
18Isak RosenAdmirals (NYI)RW17000-600326330%11036.0600000000000050.00%20000000000000
Statistiques d’équipe totales ou en moyenne40489161250-357100044547674923154511.88%271768019.0121355613960911283065056.14%207700020.6500000151415
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
1Dennis HildebyAdmirals (NYI)2651910.8166.1411342011663000100251011
2Nikke KokkoAdmirals (NYI)120100.8845.13398003429300000024110
3Spencer MartinAdmirals (NYI)10000.76510.0024004170000011000
Statistiques d’équipe totales ou en moyenne3952010.8365.9315572015494000102626121


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 Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer 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
Alex Barré-BouletAdmirals (NYI)C281997-05-21CANNo178 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$28,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Alexey ToropchenkoAdmirals (NYI)RW261999-06-25RUSNo222 Lbs6 ft6NoNoTrade2025-07-11NoNo2FalseFalsePro & Farm500,000$50,000$28,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Brett BerardAdmirals (NYI)LW232002-09-09USAYes175 Lbs5 ft9NoNoFree AgentNoNo32025-08-07FalseFalsePro & Farm500,000$50,000$28,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Carl GrundstromAdmirals (NYI)RW281997-12-01SWENo200 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$28,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Danil GushchinAdmirals (NYI)LW232002-02-06RUSNo165 Lbs5 ft8NoNoTrade2024-12-31NoNo32024-08-13FalseFalsePro & Farm500,000$50,000$28,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Dennis HildebyAdmirals (NYI)G242001-08-19SWEYes224 Lbs6 ft7NoNoFree AgentNoNo32025-08-07FalseFalsePro & Farm500,000$50,000$28,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Devin KaplanAdmirals (NYI)RW212004-01-10USANo199 Lbs6 ft2NoNoFree AgentNoNo32025-08-09FalseFalsePro & Farm500,000$50,000$28,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Elmer SoderblomAdmirals (NYI)LW242001-07-05SWEYes246 Lbs6 ft8NoNoTrade2025-12-07NoNo42025-07-27FalseFalsePro & Farm500,000$50,000$28,611$No500,000$500,000$500,000$------500,000$500,000$500,000$------NoNoNo------Lien / Lien NHL
Frank NazarAdmirals (NYI)C212004-01-14USAYes190 Lbs5 ft10NoNoTrade2024-12-31NoNo2FalseFalsePro & Farm500,000$50,000$28,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Henry ThrunAdmirals (NYI)D242001-03-12USANo210 Lbs6 ft2NoNoTrade2024-12-31NoNo1FalseFalsePro & Farm500,000$50,000$28,611$No---------------------------Lien / Lien NHL
Isaiah GeorgeAdmirals (NYI)D212004-02-15CANYes196 Lbs6 ft1NoNoFree AgentNoNo32025-08-07FalseFalsePro & Farm500,000$50,000$28,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Isak RosenAdmirals (NYI)RW222003-03-15SWENo180 Lbs6 ft0NoNoTrade2025-06-22NoNo2FalseFalsePro & Farm500,000$50,000$28,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Jack FinleyAdmirals (NYI)C232002-09-02USANo220 Lbs6 ft6NoNoFree AgentNoNo22025-08-10FalseFalsePro & Farm700,000$70,000$40,056$No700,000$--------700,000$--------No--------Lien / Lien NHL
Joel HanleyAdmirals (NYI)D341991-06-08CANNo186 Lbs5 ft11NoNoAssign ManuallyNoNo12025-04-13FalseFalsePro & Farm500,000$0$0$No---------------------------Lien / Lien NHL
John HaydenAdmirals (NYI)C301995-02-14USANo223 Lbs6 ft3NoNoAssign ManuallyNoNo22025-06-14FalseFalsePro & Farm500,000$0$0$No500,000$-----------------No--------Lien / Lien NHL
Jonny BrodzinskiAdmirals (NYI)C321993-06-19USANo211 Lbs6 ft0NoNoAssign ManuallyNoNo22025-03-28FalseFalsePro & Farm500,000$0$0$No500,000$-----------------No--------Lien / Lien NHL
Justin RobidasAdmirals (NYI)C222003-03-13USAYes176 Lbs5 ft8NoNoFree AgentNoNo32025-08-07FalseFalsePro & Farm500,000$50,000$28,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Max SassonAdmirals (NYI)C252000-09-05USANo181 Lbs6 ft1NoNoFree AgentNoNo12025-08-19FalseFalsePro & Farm500,000$50,000$28,611$No---------------------------Lien / Lien NHL
Nikita GrebenkinAdmirals (NYI)RW222003-05-02RUSNo210 Lbs6 ft2NoNoFree AgentNoNo22025-08-07FalseFalsePro & Farm500,000$50,000$28,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Nikita PrishchepovAdmirals (NYI)C212004-02-20RUSNo194 Lbs6 ft1NoNoFree AgentNoNo22025-08-07FalseFalsePro & Farm500,000$50,000$28,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Nikke KokkoAdmirals (NYI)G212004-03-14FINYes184 Lbs6 ft3NoNoFree AgentNoNo32025-08-07FalseFalsePro & Farm500,000$50,000$28,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Oskar BäckAdmirals (NYI)C252000-03-12SWEYes202 Lbs6 ft4NoNoFree AgentNoNo22025-08-07FalseFalsePro & Farm600,000$60,000$34,333$No600,000$--------600,000$--------No--------Lien
Ryan SheaAdmirals (NYI)D281997-02-11USANo220 Lbs6 ft1NoNoAssign ManuallyNoNo22025-06-14FalseFalsePro & Farm500,000$0$0$No500,000$-----------------No--------Lien / Lien NHL
Spencer MartinAdmirals (NYI)G301995-06-08CANNo191 Lbs6 ft3NoNoFree AgentNoNo12025-07-23FalseFalsePro & Farm500,000$50,000$28,611$No---------------------------Lien / Lien NHL
Ville OttavainenAdmirals (NYI)D232002-08-12FINYes210 Lbs6 ft5NoNoFree AgentNoNo32025-08-07FalseFalsePro & Farm500,000$50,000$28,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2524.84200 Lbs6 ft22.24512,000$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Elmer SoderblomFrank NazarAlexey Toropchenko40122
2Jonny BrodzinskiCarl Grundstrom30122
3Danil GushchinOskar BäckNikita Grebenkin30122
4Elmer SoderblomMax SassonAlexey Toropchenko0122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joel HanleyHenry Thrun40122
2Ryan SheaIsaiah George30122
3Ville OttavainenJoel Hanley20122
4Henry ThrunRyan Shea10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Elmer SoderblomFrank NazarAlexey Toropchenko60122
2Jonny BrodzinskiCarl Grundstrom40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joel HanleyHenry Thrun60122
2Ryan SheaIsaiah George40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Frank NazarElmer Soderblom60122
2Jonny Brodzinski40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joel HanleyHenry Thrun60122
2Ryan SheaIsaiah George40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Frank Nazar60122Joel HanleyHenry Thrun60122
2Jonny Brodzinski40122Ryan SheaIsaiah George40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Frank NazarElmer Soderblom60122
2Jonny Brodzinski40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joel HanleyHenry Thrun60122
2Ryan SheaIsaiah George40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Elmer SoderblomFrank NazarAlexey ToropchenkoJoel HanleyHenry Thrun
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Elmer SoderblomFrank NazarAlexey ToropchenkoJoel HanleyHenry Thrun
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Oskar Bäck, , Carl GrundstromOskar Bäck, Oskar Bäck
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Ryan Shea, Isaiah George, Ville OttavainenRyan SheaRyan Shea, Isaiah George
Tirs de pénalité
Alexey Toropchenko, Frank Nazar, Jonny Brodzinski, Elmer Soderblom, Oskar Bäck
Gardien
#1 : Dennis Hildeby, #2 : Nikke Kokko


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
1Americiens11000000871000000000001100000087121.0008132100534328047411434402041202267457.14%110.00%0614120550.95%580113751.01%36870552.20%868617787237444224
2Barons2110000049-51010000017-61100000032120.50048120053432804241143440205612026200.00%000%0614120550.95%580113751.01%36870552.20%868617787237444224
3Broncos2020000038-51010000023-11010000015-400.000358005343280434114344020481614213133.33%7271.43%0614120550.95%580113751.01%36870552.20%868617787237444224
4Bruins1010000024-2000000000001010000024-200.0002460053432802941143440202916815100.00%30100.00%0614120550.95%580113751.01%36870552.20%868617787237444224
5Butter Knives302001001021-1120100100712-51010000039-610.1671017270053432809341143440201463618579444.44%8275.00%1614120550.95%580113751.01%36870552.20%868617787237444224
6Fighting Pandas11000000431000000000001100000043121.0004812005343280254114344020226015500.00%000%0614120550.95%580113751.01%36870552.20%868617787237444224
7Firebirds312000001724-7211000001316-31010000048-420.33317324900534328013341143440201234112687228.57%6266.67%0614120550.95%580113751.01%36870552.20%868617787237444224
8Griffins606000002341-18505000002034-141010000037-400.0002344671053432802534114344020302792613415320.00%13469.23%1614120550.95%580113751.01%36870552.20%868617787237444224
9Ice Bats1010000057-2000000000001010000057-200.00059140053432803041143440204680173133.33%000%0614120550.95%580113751.01%36870552.20%868617787237444224
10Lynx20200000713-61010000056-11010000027-500.000713200053432808941143440208329841400.00%4325.00%0614120550.95%580113751.01%36870552.20%868617787237444224
11Marlies21100000880110000004311010000045-120.500814220053432805141143440204718163112541.67%7185.71%0614120550.95%580113751.01%36870552.20%868617787237444224
12Nordiks1010000028-6000000000001010000028-600.00023500534328022411434402045202193133.33%10100.00%0614120550.95%580113751.01%36870552.20%868617787237444224
13Quacken20200000313-101010000027-51010000016-500.00036900534328046411434402063181234100.00%6433.33%0614120550.95%580113751.01%36870552.20%868617787237444224
14Roadrunners30300000813-51010000035-22020000058-300.00081422005343280984114344020892914479222.22%7185.71%0614120550.95%580113751.01%36870552.20%868617787237444224
15Tomahawks1010000037-41010000037-40000000000000.0003690053432804941143440204712023300.00%000%0614120550.95%580113751.01%36870552.20%868617787237444224
16Wombats312000001216-41010000036-321100000910-120.3331223350053432801564114344020111241473800.00%7357.14%0614120550.95%580113751.01%36870552.20%868617787237444224
17Wranglers1010000059-4000000000001010000059-400.0005914005343280414114344020518219300.00%10100.00%0614120550.95%580113751.01%36870552.20%868617787237444224
Total3562800100124211-87172140010063106-43184140000061105-44130.186124228352105343280124741143440201349392148666952324.21%712367.61%2614120550.95%580113751.01%36870552.20%868617787237444224
_Since Last GM Reset3562800100124211-87172140010063106-43184140000061105-44130.186124228352105343280124741143440201349392148666952324.21%712367.61%2614120550.95%580113751.01%36870552.20%868617787237444224
_Vs Conference215150010079117-38926001003751-141239000004266-24110.262791432220053432807644114344020739235106394651827.69%501570.00%1614120550.95%580113751.01%36870552.20%868617787237444224
_Vs Division1429000005589-34914000003859-21515000001730-1340.1435510415910534328058541143440205841606629633618.18%331166.67%1614120550.95%580113751.01%36870552.20%868617787237444224

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
3513L31242283521247134939214866610
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
356280100124211
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
17214010063106
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
18414000061105
Derniers 10 matchs
WLOTWOTL SOWSOL
190000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
952324.21%712367.61%2
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
41143440205343280
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
614120550.95%580113751.01%36870552.20%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
868617787237444224


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
312Lynx6Admirals5LSommaire du match
625Griffins6Admirals4LSommaire du match
835Admirals5Wombats4WSommaire du match
1044Admirals2Lynx7LSommaire du match
1255Griffins8Admirals5LSommaire du match
1467Wombats6Admirals3LSommaire du match
1675Admirals4Firebirds8LSommaire du match
1782Admirals4Wombats6LSommaire du match
2099Roadrunners5Admirals3LSommaire du match
21103Admirals2Bruins4LSommaire du match
24116Griffins8Admirals6LSommaire du match
26127Admirals2Roadrunners3LSommaire du match
29139Firebirds7Admirals8WSommaire du match
33159Broncos3Admirals2LSommaire du match
35170Admirals3Roadrunners5LSommaire du match
38179Butter Knives4Admirals3LXSommaire du match
41195Admirals2Nordiks8LSommaire du match
43204Firebirds9Admirals5LSommaire du match
45209Admirals1Quacken6LSommaire du match
47223Tomahawks7Admirals3LSommaire du match
49233Admirals5Wranglers9LSommaire du match
50244Barons7Admirals1LSommaire du match
52254Admirals3Barons2WSommaire du match
54268Marlies3Admirals4WSommaire du match
56278Admirals4Fighting Pandas3WSommaire du match
58289Quacken7Admirals2LSommaire du match
61303Admirals3Griffins7LSommaire du match
62310Admirals3Butter Knives9LSommaire du match
65320Butter Knives8Admirals4LSommaire du match
67334Griffins7Admirals4LSommaire du match
69340Admirals5Ice Bats7LSommaire du match
71354Admirals8Americiens7WSommaire du match
73363Griffins5Admirals1LSommaire du match
75373Admirals4Marlies5LSommaire du match
76378Admirals1Broncos5LSommaire du match
78389Broncos-Admirals-
81403Admirals-Bruins-
82413Broncos-Admirals-
84425Roadrunners-Admirals-
89445Ice Bats-Admirals-
93464Admirals-Americiens-
94468Ice Bats-Admirals-
98485Admirals-Roadrunners-
99492Fighting Pandas-Admirals-
102509Lions-Admirals-
104518Admirals-Tomahawks-
106531Admirals-Butter Knives-
107535Fighting Pandas-Admirals-
110553Aces-Admirals-
112565Admirals-Firebirds-
113576Barracuda-Admirals-
116586Admirals-Marlies-
119597Admirals-Firebirds-
120604Canucks-Admirals-
122620Wranglers-Admirals-
124628Admirals-Tomahawks-
126641Roadrunners-Admirals-
131662Firebirds-Admirals-
133679Admirals-Canucks-
134684Americiens-Admirals-
137696Admirals-Canucks-
139705Admirals-Lions-
140711Bruins-Admirals-
143727Lynx-Admirals-
145736Admirals-Broncos-
147744Admirals-Barracuda-
148753Americiens-Admirals-
150765Admirals-Fighting Pandas-
152776Lynx-Admirals-
155789Admirals-Bruins-
156794Admirals-Wombats-
157799Admirals-Broncos-
158803Marlies-Admirals-
161820Admirals-Aces-
162824Nordiks-Admirals-
164837Admirals-Wombats-
166842Admirals-Aces-
167847Admirals-Lynx-
169855Wombats-Admirals-
172871Admirals-Lynx-
174879Wombats-Admirals-
178895Bruins-Admirals-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
24 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
743,661$ 1,280,000$ 1,080,000$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
1,080,000$ 444,208$ 25 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 103 9,889$ 1,018,567$




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