Please rotate your device to landscape mode for a better experience.
Connexion

Admirals
GP: 26 | W: 5 | L: 20 | OTL: 1 | P: 11
GF: 91 | GA: 151 | PP%: 17.46% | PK%: 69.81%
DG: Keith | Morale : 31 | Moyenne d’équipe : 57
Prochains matchs #303 vs Griffins

Centre de jeu
Admirals
5-20-1, 11pts
4
FINAL
3 Fighting Pandas
14-9-4, 32pts
Team Stats
L1SéquenceOTL1
2-11-1Fiche domicile6-4-4
3-9-0Fiche domicile8-5-0
3-7-0Derniers 10 matchs4-3-3
3.50Buts par match 4.33
5.81Buts contre par match 3.78
17.46%Pourcentage en avantage numérique31.37%
69.81%Pourcentage en désavantage numérique83.13%
Quacken
15-10-1, 31pts
7
FINAL
2 Admirals
5-20-1, 11pts
Team Stats
W2SéquenceL1
10-3-0Fiche domicile2-11-1
5-7-1Fiche domicile3-9-0
7-3-0Derniers 10 matchs3-7-0
3.69Buts par match 3.50
3.15Buts contre par match 5.81
30.19%Pourcentage en avantage numérique17.46%
85.00%Pourcentage en désavantage numérique69.81%
Admirals
5-20-1, 11pts
Jour 61
Griffins
14-13-0, 28pts
Statistiques d’équipe
L1SéquenceW1
2-11-1Fiche domicile7-6-0
3-9-0Fiche visiteur7-7-0
3-7-010 derniers matchs6-4-0
3.50Buts par match 5.63
5.81Buts contre par match 5.63
17.46%Pourcentage en avantage numérique18.75%
69.81%Pourcentage en désavantage numérique68.75%
Admirals
5-20-1, 11pts
Jour 62
Butter Knives
13-10-2, 28pts
Statistiques d’équipe
L1SéquenceSOL1
2-11-1Fiche domicile9-4-1
3-9-0Fiche visiteur4-6-1
3-7-010 derniers matchs6-2-2
3.50Buts par match 4.64
5.81Buts contre par match 4.64
17.46%Pourcentage en avantage numérique15.87%
69.81%Pourcentage en désavantage numérique72.00%
Butter Knives
13-10-2, 28pts
Jour 65
Admirals
5-20-1, 11pts
Statistiques d’équipe
SOL1SéquenceL1
9-4-1Fiche domicile2-11-1
4-6-1Fiche visiteur3-9-0
6-2-210 derniers matchs3-7-0
4.64Buts par match 3.50
5.16Buts contre par match 3.50
15.87%Pourcentage en avantage numérique17.46%
72.00%Pourcentage en désavantage numérique69.81%
Meneurs d'équipe
Brett BerardButs
Brett Berard
8
Jonny BrodzinskiPasses
Jonny Brodzinski
12
Jonny BrodzinskiPoints
Jonny Brodzinski
18
Max SassonPlus/Moins
Max Sasson
-5
Dennis HildebyVictoires
Dennis Hildeby
4
Nikke KokkoPourcentage d’arrêts
Nikke Kokko
0.881

Statistiques d’équipe
Buts pour
91
3.50 GFG
Tirs pour
984
37.85 Avg
Pourcentage en avantage numérique
17.5%
11 GF
Début de zone offensive
40.4%
Buts contre
151
5.81 GAA
Tirs contre
981
37.73 Avg
Pourcentage en désavantage numérique
69.8%%
16 GA
Début de la zone défensive
37.0%
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 Pro23
Équipe Mineure20
Limite contact 43 / 50
Espoirs8


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)X100.00635686706878716862676966645559047640212500,000$
2Alexey ToropchenkoX100.00846186668171906950645070506365046640262500,000$
3Jonny BrodzinskiX100.00645595687569687362637061517573046640322500,000$
4Oskar Bäck (R)X100.00605593647369845966635073506265045610252600,000$
5Brett Berard (R)X100.00705587646065606650596458515859046590233500,000$
6Max SassonX100.00615099646465576558605659506261045580251500,000$
7Carl GrundstromX100.00845880637165715850605057506563044580282500,000$
8John HaydenX100.00736184588057545568525057507168056560302500,000$
9Justin Robidas (R)X100.00503589576150515550505450515664024520223500,000$
10Nikita GrebenkinX100.00595785577550515050505049506261031510222500,000$
11Danil GushchinX100.00505775505653535350505049506362031500233500,000$
12Joel HanleyX100.00696484626674726650595175558077045650341500,000$
13Henry ThrunX100.00676783627572766750615166556162044630241500,000$
14Ryan SheaX100.00625984627968646250545071556969045620282500,000$
15Isaiah George (R)X100.00595790607067616450565165555558044590213500,000$
16Ville Ottavainen (R)X100.00553594577650525050605050555969044540233500,000$
Rayé
1Devin KaplanX100.00503589577150515050505050505355024510213500,000$
2Jack FinleyX100.00503589578050505050505050505959024510232700,000$
3Alex Barré-BouletX100.00504353576250515050505050506564024510282500,000$
4Nikita PrishchepovX100.00525089576950505050505050505355024510212500,000$
5Isak RosenX100.00505089576350514950505049505657032500222500,000$
MOYENNE D’ÉQUIPE100.0061528660706161595356535852626303957
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)100.0050636083514646464650505958010530243500,000$
2Nikke Kokko (R)100.0050605971525350505050505252041530213500,000$
Rayé
MOYENNE D’ÉQUIPE100.005062607752504848485050565502653
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
1Jonny BrodzinskiAdmirals (NYI)C1761218-13004317329408.22%431118.3021314340001110056.70%38800001.1600000011
2Cole SillingerNew York IslandersC/LW1510717-1220182676234613.16%436824.592028320110231041.67%2400010.9200000222
3Joel HanleyAdmirals (NYI)D1731114-1412039232492312.50%3043825.79123631000020000%000000.6400000410
4Alexey ToropchenkoAdmirals (NYI)RW1731114-810029233512338.57%432218.99022635000030061.90%2100000.8700000011
5Brett BerardAdmirals (NYI)LW178513-1400151646112617.39%433219.590228360003171040.91%2200000.7800000111
6Frank NazarAdmirals (NYI)C174812-6008364412369.09%434120.091124361011291054.93%42600000.7000000101
7Henry ThrunAdmirals (NYI)D1721012-196036211831211.11%2842224.84112831000019000%000000.5700000001
8Carl GrundstromAdmirals (NYI)RW174711-1410038102692115.38%430918.18022435000000064.71%1700000.7100000012
9Isaiah GeorgeAdmirals (NYI)D173811-214013192821410.71%2838122.451011636000019000%000000.5800000000
10Oskar BäckAdmirals (NYI)C173710-15201643333339.09%530618.02022350000141058.88%30400000.6500000100
11Ryan SheaAdmirals (NYI)D17189-12801321195115.26%2840924.09011833000020000%000000.4400000010
12Max SassonAdmirals (NYI)C17426-52059156826.67%31146.7110111000010050.98%10200001.0500000001
13Nikita GrebenkinAdmirals (NYI)RW17134-162017615796.67%126515.6000002000000047.06%1700000.3000000000
14Ville OttavainenAdmirals (NYI)D17123-7208721250.00%1628716.8900019000011000%000000.2100000100
15Erik HaulaNew York IslandersLW2202-24027131315.38%74723.93000020000300100.00%200000.8400000000
16Danil GushchinAdmirals (NYI)LW17112-1500129144127.14%427416.1200001000050033.33%1500000.1500000000
17Isak RosenAdmirals (NYI)RW17000-600326330%11036.0600000000000050.00%20000000000000
Statistiques d’équipe totales ou en moyenne27256102158-19964027630948714033211.50%175503518.51914238736611252034055.52%134000010.630000010810
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)1741110.8175.51751006937800100161010
2Nikke KokkoAdmirals (NYI)70100.8815.21242002117700000015000
3Spencer MartinNew York Islanders10000.76510.0024004170000011000
Statistiques d’équipe totales ou en moyenne2541210.8365.541018009457200101717010


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$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Alexey ToropchenkoAdmirals (NYI)RW261999-06-25RUSNo222 Lbs6 ft6NoNoTrade2025-07-11NoNo2FalseFalsePro & Farm500,000$50,000$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Brett BerardAdmirals (NYI)LW232002-09-09USAYes175 Lbs5 ft9NoNoFree AgentNoNo32025-08-07FalseFalsePro & Farm500,000$50,000$33,611$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$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Danil GushchinAdmirals (NYI)LW232002-02-06RUSNo165 Lbs5 ft8NoNoTrade2024-12-31NoNo32024-08-13FalseFalsePro & Farm500,000$50,000$33,611$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$33,611$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$33,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Frank NazarAdmirals (NYI)C212004-01-14USAYes190 Lbs5 ft10NoNoTrade2024-12-31NoNo2FalseFalsePro & Farm500,000$50,000$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Henry ThrunAdmirals (NYI)D242001-03-12USANo210 Lbs6 ft2NoNoTrade2024-12-31NoNo1FalseFalsePro & Farm500,000$50,000$33,611$No---------------------------Lien / Lien NHL
Isaiah GeorgeAdmirals (NYI)D212004-02-15CANYes196 Lbs6 ft1NoNoFree AgentNoNo32025-08-07FalseFalsePro & Farm500,000$50,000$33,611$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$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Jack FinleyAdmirals (NYI)C232002-09-02USANo220 Lbs6 ft6NoNoFree AgentNoNo22025-08-10FalseFalsePro & Farm700,000$70,000$47,056$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$33,611$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$33,611$No---------------------------Lien / Lien NHL
Nikita GrebenkinAdmirals (NYI)RW222003-05-02RUSNo210 Lbs6 ft2NoNoFree AgentNoNo22025-08-07FalseFalsePro & Farm500,000$50,000$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Nikita PrishchepovAdmirals (NYI)C212004-02-20RUSNo194 Lbs6 ft1NoNoFree AgentNoNo22025-08-07FalseFalsePro & Farm500,000$50,000$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Nikke KokkoAdmirals (NYI)G212004-03-14FINYes184 Lbs6 ft3NoNoFree AgentNoNo32025-08-07FalseFalsePro & Farm500,000$50,000$33,611$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$40,333$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
Ville OttavainenAdmirals (NYI)D232002-08-12FINYes210 Lbs6 ft5NoNoFree AgentNoNo32025-08-07FalseFalsePro & Farm500,000$50,000$33,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2324.65198 Lbs6 ft12.22513,043$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Frank NazarAlexey Toropchenko40122
2Brett BerardJonny BrodzinskiCarl Grundstrom30122
3Danil GushchinOskar BäckNikita Grebenkin30122
4Max Sasson0122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joel HanleyRyan Shea40122
2Henry ThrunIsaiah George30122
3Ville OttavainenJoel Hanley20122
4Ryan SheaHenry Thrun10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Frank NazarAlexey Toropchenko60122
2Brett BerardJonny BrodzinskiCarl Grundstrom40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joel HanleyRyan Shea60122
2Henry ThrunIsaiah George40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Frank Nazar60122
2Jonny BrodzinskiBrett Berard40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joel HanleyRyan Shea60122
2Henry ThrunIsaiah George40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Frank Nazar60122Joel HanleyRyan Shea60122
2Jonny Brodzinski40122Henry ThrunIsaiah George40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Frank Nazar60122
2Jonny BrodzinskiBrett Berard40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joel HanleyRyan Shea60122
2Henry ThrunIsaiah George40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Frank NazarAlexey ToropchenkoJoel HanleyRyan Shea
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Frank NazarAlexey ToropchenkoJoel HanleyRyan Shea
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Oskar Bäck, Brett Berard, Carl GrundstromOskar Bäck, Brett BerardOskar Bäck
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Henry Thrun, Isaiah George, Ville OttavainenHenry ThrunHenry Thrun, Isaiah George
Tirs de pénalité
, Alexey Toropchenko, Frank Nazar, Jonny Brodzinski, 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
1Barons2110000049-51010000017-61100000032120.50048120034342304231334133005612026200.00%000%045793348.98%41385348.42%26952251.53%626441602181330165
2Broncos1010000023-11010000023-10000000000000.0002350034342302831334133002366113133.33%3166.67%045793348.98%41385348.42%26952251.53%626441602181330165
3Bruins1010000024-2000000000001010000024-200.0002460034342302931334133002916815100.00%30100.00%045793348.98%41385348.42%26952251.53%626441602181330165
4Butter Knives1000010034-11000010034-10000000000010.50033600343423031313341330054121018200.00%50100.00%145793348.98%41385348.42%26952251.53%626441602181330165
5Fighting Pandas11000000431000000000001100000043121.0004812003434230253133413300226015500.00%000%045793348.98%41385348.42%26952251.53%626441602181330165
6Firebirds312000001724-7211000001316-31010000048-420.33317324900343423013331334133001234112687228.57%6266.67%045793348.98%41385348.42%26952251.53%626441602181330165
7Griffins303000001522-7303000001522-70000000000000.00015294410343423016831334133001634816755360.00%8275.00%145793348.98%41385348.42%26952251.53%626441602181330165
8Lynx20200000713-61010000056-11010000027-500.000713200034342308931334133008329841400.00%4325.00%045793348.98%41385348.42%26952251.53%626441602181330165
9Marlies11000000431110000004310000000000021.000481200343423027313341330022136127228.57%20100.00%045793348.98%41385348.42%26952251.53%626441602181330165
10Nordiks1010000028-6000000000001010000028-600.00023500343423022313341330045202193133.33%10100.00%045793348.98%41385348.42%26952251.53%626441602181330165
11Quacken20200000313-101010000027-51010000016-500.00036900343423046313341330063181234100.00%6433.33%045793348.98%41385348.42%26952251.53%626441602181330165
12Roadrunners30300000813-51010000035-22020000058-300.00081422003434230983133413300892914479222.22%7185.71%045793348.98%41385348.42%26952251.53%626441602181330165
13Tomahawks1010000037-41010000037-40000000000000.0003690034342304931334133004712023300.00%000%045793348.98%41385348.42%26952251.53%626441602181330165
14Wombats312000001216-41010000036-321100000910-120.3331223350034342301563133413300111241473800.00%7357.14%045793348.98%41385348.42%26952251.53%626441602181330165
15Wranglers1010000059-4000000000001010000059-400.0005914003434230413133413300518219300.00%10100.00%045793348.98%41385348.42%26952251.53%626441602181330165
Total265200010091151-6014211001005486-321239000003765-28110.212911692601034342309843133413300981294110496631117.46%531669.81%245793348.98%41385348.42%26952251.53%626441602181330165
_Since Last GM Reset265200010091151-6014211001005486-321239000003765-28110.212911692601034342309843133413300981294110496631117.46%531669.81%245793348.98%41385348.42%26952251.53%626441602181330165
_Vs Conference16411001005983-24825001003343-10826000002640-1490.2815910816700343423061631334133005561767830046715.22%371072.97%145793348.98%41385348.42%26952251.53%626441602181330165
_Vs Division1028000004665-19714000003347-14314000001318-540.200468713310343423048531334133004201194822723626.09%24866.67%145793348.98%41385348.42%26952251.53%626441602181330165

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2611L19116926098498129411049610
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
26520010091151
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
1421101005486
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
123900003765
Derniers 10 matchs
WLOTWOTL SOWSOL
370000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
631117.46%531669.81%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
31334133003434230
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
45793348.98%41385348.42%26952251.53%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
626441602181330165


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
61303Admirals-Griffins-
62310Admirals-Butter Knives-
65320Butter Knives-Admirals-
67334Griffins-Admirals-
69340Admirals-Ice Bats-
71354Admirals-Americiens-
73363Griffins-Admirals-
75373Admirals-Marlies-
76378Admirals-Broncos-
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
27 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
567,883$ 1,180,000$ 980,000$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
980,000$ 338,432$ 23 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 121 9,333$ 1,129,293$




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