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Admirals
GP: 80 | W: 39 | L: 33 | OTL: 8 | P: 86
GF: 354 | GA: 342 | PP%: 24.13% | PK%: 83.50%
DG: Dany Potvin | Morale : 35 | Moyenne d’équipe : 64

Centre de jeu
Griffins
48-27-5, 101pts
3
FINAL
5 Admirals
39-33-8, 86pts
Team Stats
L2SéquenceL1
26-13-1Fiche domicile21-16-3
22-14-4Fiche domicile18-17-5
5-5-0Derniers 10 matchs5-3-2
4.38Buts par match 4.43
3.76Buts contre par match 4.28
22.26%Pourcentage en avantage numérique24.13%
81.35%Pourcentage en désavantage numérique83.50%
Admirals
39-33-8, 86pts
3
FINAL
4 Barracuda
38-37-5, 81pts
Team Stats
L1SéquenceW1
21-16-3Fiche domicile18-19-3
18-17-5Fiche domicile20-18-2
5-3-2Derniers 10 matchs5-5-0
4.43Buts par match 3.91
4.28Buts contre par match 4.34
24.13%Pourcentage en avantage numérique18.21%
83.50%Pourcentage en désavantage numérique74.83%
Meneurs d'équipe
Buts
Mark McNeill
57
Passes
Mathieu Joseph
62
Points
Mathieu Joseph
110
Plus/Moins
Mark McNeill
16
Victoires
Felix Sanstrom
33
Pourcentage d’arrêts
Felix Sanstrom
0.878

Statistiques d’équipe
Buts pour
354
4.43 GFG
Tirs pour
2554
31.93 Avg
Pourcentage en avantage numérique
24.1%
69 GF
Début de zone offensive
34.3%
Buts contre
342
4.28 GAA
Tirs contre
2675
33.44 Avg
Pourcentage en désavantage numérique
83.5%%
50 GA
Début de la zone défensive
37.3%
Informations de l'équipe

Directeur généralDany Potvin
EntraîneurWayne Gretzky
DivisionJohn-Ahearne
ConférenceRobert-Lebel
CapitaineMark McNeill
Assistant #1
Assistant #2Josh Norris


Informations de l’aréna

Capacité3,000
Assistance2,784
Billets de saison300


Informations de la formation

Équipe Pro38
Équipe Mineure19
Limite contact 57 / 250
Espoirs0


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
1Mathieu Joseph (R)X100.0079387579797380756675807671604948617402211,000,000$
2Mark McNeill (C)X100.007338787578767377787374757564553653730261900,000$
3Antti Suomela (R)X100.007839747984698067717875627461534523720251700,000$
4Hunter ShinkarukX100.006939807572757672697384597760553654720251950,000$
5Lucas WallmarkX100.006532807778767671837767716655494041710242900,000$
6Kasper BjorkqvistX100.006839777666777378808971526655494140710251900,000$
7Nolan VeseyX100.007937727670587777647367596147503654680241800,000$
8Riley BarberX100.007334817166686469687568667650493424680251650,000$
9Josh Norris (R) (A)X100.006530797071767271665885517451445845670201750,000$
10Pavol Regenda (R)X100.006947766363686070676466566347446115640201500,000$
11Milos Kelemen (R)X100.006023655481636768706070436344446455600201500,000$
12Ruslan Iskhakov (R)X100.005740616666625362536161435642426818570191500,000$
13Olli Juolevi (R)X100.007132778468596783447659735653465344710212700,000$
14Christian DjoosX100.007332837069626669506852785851533055690251650,000$
15Reilly Walsh (R)X100.006433837268686763477757835451445455690201750,000$
16Carl DahlstromX100.007118826860627261456863795649513732670241600,000$
17Ian Mitchell (R)X100.005534797764586277468063724748446110670201750,000$
18Sean Durzi (R)X100.005940817554636481327460634345445940650211500,000$
19Josh Wesley (R)X100.005839846368686958446957724646483838650231600,000$
20Tobias Bjornfot (R)X100.004730697549576768378051634040407549600182500,000$
Rayé
1Gerald MayhewX100.005842796766698375736476597362573619680272750,000$
2Ryan OlsenX100.005433797571667368636568487047472622640251600,000$
3Drew O'Connor (R)X100.007640686777567868637165565446455321640212999,999$
4Carsen Twarynski (R)X100.004636866361796252597362685544464019620221500,000$
5Troy BourkeX100.005041677158586667657068425347472619610251600,000$
6Filip Chlapik (R)X100.006336705667566062735868535444444319600221600,000$
7Bokondji Imama (R)X100.007853674676506861596063426145453420580231750,000$
8Mark Kastelic (R)X100.007138595677496861555364525742425419580202500,000$
9Joni Ikonen (R)X100.004721755743504173586150455842424920540201550,000$
10Jack Malone (R)X100.004636594953555542585857475342425820510192500,000$
11Patrick Moynihan (R)X100.004933594752444650494647386040407319470182500,000$
12Grant HuttonX100.008150556663635550397056593954553819630241750,000$
13Sergei Zborovskiy (R)X100.00543179676862635430553874514646459610221500,000$
14Libor Hajek (R)X100.006443746263576059365445635143434220600211500,000$
15Henry Thrun (R)X100.006635645251635555335953594440407519560182500,000$
MOYENNE D’ÉQUIPE100.00643674676663666657686360594947483164
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
1Felix Sanstrom100.00697671727371707168687351475574690221700,000$
2Tristan Jarry100.00757676716978736459776961503875690241700,000$
Rayé
1Sean Maguire100.00677161626367636565657154572720640261500,000$
MOYENNE D’ÉQUIPE100.0070746968687269676470715551405667
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Wayne Gretzky70628291526855Can6611,000,000$


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
1Mathieu JosephAdmirals (Nas)RW694862110-37551401073109917915.48%45153022.181620365320902261955346.07%1916923101.4401010678
2Mark McNeillAdmirals (Nas)RW775746103164351201062788217520.50%42139818.1699182518513481548252.22%905820131.47010011056
3Lucas WallmarkAdmirals (Nas)C744753100133201281582395712819.67%42144219.49618242117811292125054.50%16793327011.3911000674
4Hunter ShinkarukAdmirals (Nas)LW80324577-19240117842418015513.28%39154019.261015253322011231202045.67%1276125011.0001000414
5Olli JuoleviAdmirals (Nas)D71124961-22608611114843588.11%99157622.214812181980113198210%03862000.7700000214
6Nolan VeseyAdmirals (Nas)LW73243357236097581645810714.63%1298613.51661214910112461060.00%452315001.1600000132
7Josh NorrisAdmirals (Nas)C66193756-152759295118376716.10%17121818.4671522151672024763147.45%14902813000.9200100321
8Ian MitchellAdmirals (Nas)D71639457300609311347335.31%79150921.272911141810112173110%02442000.6000000000
9Antti SuomelaAdmirals (Nas)C421823414260726397285718.56%1966115.762247811011311248.91%5053112001.2400000232
10Reilly WalshAdmirals (Nas)D8063440-172008517010943515.50%134200925.123710202530000276100%02280000.4000000103
11Riley BarberAdmirals (Nas)RW552119406405550106305719.81%1760210.950110133037953125.00%242011011.3300000161
12Kasper BjorkqvistAdmirals (Nas)RW74202040-520084541515210513.25%2085211.52101131000042052.63%38473000.9400000213
13Tobias BjornfotAdmirals (Nas)D6832427248029693821277.89%57112516.561342135011075100%0932000.4800000001
14Ryan OlsenAdmirals (Nas)C39101121-280212754183318.52%63819.77000000000222042.06%126113001.1000000100
15Pavol RegendaAdmirals (Nas)LW66912214440835465192713.85%1289713.60112497000062054.55%44814000.4700000102
16Carl DahlstromAdmirals (Nas)D6202020514037713510180%4981813.210001520110116000%0618000.4900000000
17Gerald MayhewAdmirals (Nas)RW3710919-1060232780244412.50%1037910.25000224000051052.94%17179001.0000000011
18Christian DjoosAdmirals (Nas)D77114158804377281663.57%5595512.410111460000148000%0343000.3100000000
19Milos KelemenAdmirals (Nas)LW80459-24005624419249.76%147689.60000115000060045.83%24414000.2300000000
20Sean DurziAdmirals (Nas)D74066-123522382511150%3379210.7101123100008000%0415000.1500010000
21Drew O'ConnorAdmirals (Nas)LW23336-56027162571012.00%824910.86000217000190050.00%443000.4800000000
22Ruslan IskhakovAdmirals (Nas)C59235-102952928257108.00%75038.53000000000100141.78%21307000.2000000000
23Josh WesleyAdmirals (Nas)D61055440112516460%194507.3800004000021000%0210000.2200000000
24Filip ChlapikAdmirals (Nas)C12134-140101463216.67%612810.7000000000000056.52%6904000.6200000000
25Mark KastelicAdmirals (Nas)C23112-620022816136.25%31848.0100000000010049.44%8902000.2200000000
26Sergei ZborovskiyAdmirals (Nas)D27011-8405163120%222047.580000000002000%005000.1000000000
27Henry ThrunAdmirals (Nas)D39011260393020%31784.580000000000000%004000.1100000000
28Grant HuttonAdmirals (Nas)D4000-500450000%0348.730000000000000%00000000000000
29Troy BourkeAdmirals (Nas)LW1000000000000%011.020000000000000%00000000000000
30Carsen TwarynskiAdmirals (Nas)LW1000000000000%022.980000000000000%00000000000000
31Patrick MoynihanAdmirals (Nas)RW5000-360201000%3438.65000000000000100.00%10100000000000
Statistiques d’équipe totales ou en moyenne1590354578932-4163325156316572535807140113.96%8722342914.7468116184236223991221462021401249.98%4776522517260.8014121403742
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
1Felix SanstromAdmirals (Nas)62332160.8784.043563402401966979710.50025819232
2Tristan JarryAdmirals (Nas)2561220.8654.521248009469732402002258110
3Sean MaguireAdmirals (Nas)10000.55634.29700494000003000
Statistiques d’équipe totales ou en moyenne88393380.8744.21481940338267213077328080342


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 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
Antti SuomelaAdmirals (Nas)C251994-01-01FINYes180 Lbs6 ft0NoNoFree Agent2024-11-07NoNo12025-02-15FalseFalsePro & Farm700,000$0$0$No---------------------------
Bokondji ImamaAdmirals (Nas)LW231996-01-01CANYes221 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm750,000$0$0$No---------------------------
Carl DahlstromAdmirals (Nas)D241995-01-01SWENo185 Lbs6 ft4NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm600,000$0$0$No---------------------------
Carsen TwarynskiAdmirals (Nas)LW221997-01-01CANYes198 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Christian DjoosAdmirals (Nas)D251994-01-01SWENo158 Lbs5 ft11NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm650,000$0$0$No---------------------------
Drew O'ConnorAdmirals (Nas)LW211998-01-01USAYes190 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm999,999$0$0$No1,000,000$--------999,999$--------No--------
Felix SanstromAdmirals (Nas)G221997-01-01SWENo191 Lbs6 ft2NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm700,000$0$0$No---------------------------
Filip ChlapikAdmirals (Nas)C221997-01-01CZEYes194 Lbs6 ft2NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm600,000$0$0$No---------------------------
Gerald MayhewAdmirals (Nas)RW271992-01-01USANo161 Lbs6 ft4NoNoN/ANoNo2FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------
Grant HuttonAdmirals (Nas)D241995-01-01USANo207 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm750,000$0$0$No---------------------------
Henry ThrunAdmirals (Nas)D182001-01-01CANYes190 Lbs6 ft2NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Hunter ShinkarukAdmirals (Nas)LW251994-01-01CANNo185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm950,000$0$0$No---------------------------
Ian MitchellAdmirals (Nas)D201999-01-01CANYes173 Lbs5 ft11NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm750,000$0$0$No---------------------------
Jack MaloneAdmirals (Nas)RW192000-01-01USAYes190 Lbs6 ft1NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Joni IkonenAdmirals (Nas)C201999-01-01FINYes171 Lbs5 ft10NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm550,000$0$0$No---------------------------
Josh NorrisAdmirals (Nas)C201999-01-01USAYes199 Lbs6 ft1NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm750,000$0$0$No---------------------------
Josh WesleyAdmirals (Nas)D231996-01-01USAYes201 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm600,000$0$0$No---------------------------
Kasper BjorkqvistAdmirals (Nas)RW251994-01-01FINNo194 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm900,000$0$0$No---------------------------
Libor HajekAdmirals (Nas)D211998-01-01CZEYes205 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Lucas WallmarkAdmirals (Nas)C241995-01-01SWENo185 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Mark KastelicAdmirals (Nas)C201999-01-01USAYes227 Lbs6 ft4NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Mark McNeillAdmirals (Nas)RW261993-01-01CANNo212 Lbs6 ft2NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm900,000$0$0$No---------------------------
Mathieu JosephAdmirals (Nas)RW221997-01-01CANYes190 Lbs6 ft1NoNoTrade2024-08-03NoNo1FalseFalsePro & Farm1,000,000$0$0$No---------------------------
Milos KelemenAdmirals (Nas)LW201999-01-01SVKYes210 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Nolan VeseyAdmirals (Nas)LW241995-01-01USANo210 Lbs6 ft2NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm800,000$0$0$No---------------------------
Olli JuoleviAdmirals (Nas)D211998-01-01FINYes183 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm700,000$0$0$No700,000$--------700,000$--------No--------
Patrick MoynihanAdmirals (Nas)RW182001-01-01CANYes185 Lbs5 ft11NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Pavol RegendaAdmirals (Nas)LW201999-01-01SVKYes212 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Reilly WalshAdmirals (Nas)D201999-01-01CANYes185 Lbs6 ft0NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm750,000$0$0$No---------------------------
Riley BarberAdmirals (Nas)RW251994-01-01USANo194 Lbs5 ft11NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm650,000$0$0$No---------------------------
Ruslan IskhakovAdmirals (Nas)C192000-01-01RUSYes165 Lbs5 ft9NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Ryan OlsenAdmirals (Nas)C251994-01-01CANNo187 Lbs6 ft1NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm600,000$0$0$No---------------------------
Sean DurziAdmirals (Nas)D211998-01-01CANYes195 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Sean MaguireAdmirals (Nas)G261993-01-01CANNo193 Lbs6 ft1NoNoFree AgentNoNo12025-01-18FalseFalsePro & Farm500,000$0$0$No---------------------------
Sergei ZborovskiyAdmirals (Nas)D221997-01-01RUSYes194 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Tobias BjornfotAdmirals (Nas)D182001-01-01SWEYes201 Lbs6 ft1NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Tristan JarryAdmirals (Nas)G241995-01-01CANNo185 Lbs6 ft2NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm700,000$0$0$No---------------------------
Troy BourkeAdmirals (Nas)LW251994-01-01CANNo156 Lbs5 ft10NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm600,000$0$0$No---------------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3822.26191 Lbs6 ft11.24660,526$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nolan VeseyJosh NorrisMathieu Joseph40122
2Hunter ShinkarukLucas WallmarkMark McNeill30122
3Pavol RegendaAntti SuomelaKasper Bjorkqvist20122
4Milos KelemenRuslan IskhakovRiley Barber10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Reilly WalshIan Mitchell40122
2Olli JuoleviTobias Bjornfot30122
3Christian DjoosSean Durzi20122
4Carl DahlstromJosh Wesley10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nolan VeseyJosh NorrisMathieu Joseph60113
2Hunter ShinkarukLucas WallmarkMark McNeill40113
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Reilly WalshIan Mitchell60122
2Olli JuoleviTobias Bjornfot40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Lucas WallmarkMathieu Joseph60122
2Mark McNeillRiley Barber40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Reilly WalshIan Mitchell60131
2Olli JuoleviChristian Djoos40131
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Mathieu Joseph60131Reilly WalshIan Mitchell60131
2Mark McNeill40131Olli JuoleviCarl Dahlstrom40131
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Lucas WallmarkMathieu Joseph60122
2Mark McNeillHunter Shinkaruk40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Reilly WalshIan Mitchell60122
2Carl DahlstromTobias Bjornfot40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Hunter ShinkarukJosh NorrisMathieu JosephReilly WalshIan Mitchell
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Hunter ShinkarukLucas WallmarkMathieu JosephReilly WalshOlli Juolevi
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Antti Suomela, Riley Barber, Pavol RegendaAntti Suomela, Pavol RegendaRiley Barber
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Olli Juolevi, Christian Djoos, Tobias BjornfotSean DurziOlli Juolevi, Josh Wesley
Tirs de pénalité
Mathieu Joseph, Mark McNeill, Hunter Shinkaruk, Lucas Wallmark, Kasper Bjorkqvist
Gardien
#1 : Felix Sanstrom, #2 : Tristan Jarry
Lignes d’attaque personnalisées en prolongation
Mathieu Joseph, Mark McNeill, Hunter Shinkaruk, Lucas Wallmark, Josh Norris, Antti Suomela, Riley Barber, Kasper Bjorkqvist, Nolan Vesey, Milos Kelemen
Lignes de défense personnalisées en prolongation
Olli Juolevi, Reilly Walsh, Ian Mitchell, Tobias Bjornfot, Josh Wesley


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
1Americans6320010027243320001001495312000001315-270.58327477400106123121418579490784016196736212732928.13%31390.32%1834166550.09%939181451.76%693138150.18%168293917107491437713
2Barracuda43100000221572200000014862110000087160.7502238600010612312141377949078401612138328613538.46%16287.50%2834166550.09%939181451.76%693138150.18%168293917107491437713
3Bears20200000810-21010000045-11010000045-100.00081119001061231214787949078401661171040500.00%5180.00%0834166550.09%939181451.76%693138150.18%168293917107491437713
4Canucks20200000613-71010000046-21010000027-500.00069150010612312145579490784016713722387228.57%11463.64%0834166550.09%939181451.76%693138150.18%168293917107491437713
5Checkers32100000171431100000083521100000911-240.66717294600106123121490794907840161042330506233.33%15286.67%1834166550.09%939181451.76%693138150.18%168293917107491437713
6Comets512011001620-421100000810-230101100810-250.5001627430010612312141607949078401617853428315213.33%21290.48%1834166550.09%939181451.76%693138150.18%168293917107491437713
7Condors431000002214811000000532321000001711660.7502237590010612312141397949078401611941267716425.00%13192.31%0834166550.09%939181451.76%693138150.18%168293917107491437713
8Crunch31100100151502100010011921010000046-230.500152540101061231214101794907840161093222559333.33%110100.00%0834166550.09%939181451.76%693138150.18%168293917107491437713
9Eagles202000001012-21010000078-11010000034-100.0001018280010612312147679490784016591122711218.18%10100.00%0834166550.09%939181451.76%693138150.18%168293917107491437713
10Firebirds312000001513220200000811-31100000072520.33315233800106123121489794907840161153916595240.00%9188.89%1834166550.09%939181451.76%693138150.18%168293917107491437713
11Griffins3200000113112220000008531000000156-150.83313193200106123121498794907840161022622605120.00%11281.82%0834166550.09%939181451.76%693138150.18%168293917107491437713
12Gulls31101000181441010000046-221001000148640.667182947001061231214977949078401610332205111436.36%10460.00%0834166550.09%939181451.76%693138150.18%168293917107491437713
13Icehogs622011002226-432100000139430101100917-870.58322365800106123121419179490784016197555613827518.52%28485.71%0834166550.09%939181451.76%693138150.18%168293917107491437713
14Islander220000001293110000007521100000054141.0001222340010612312146679490784016582822315120.00%11190.91%1834166550.09%939181451.76%693138150.18%168293917107491437713
15Little Stars22000000826110000004131100000041341.00081422001061231214637949078401654232236200.00%11190.91%1834166550.09%939181451.76%693138150.18%168293917107491437713
16Marlies3210000011561010000012-122000000103740.667111627001061231214887949078401611638187313215.38%90100.00%1834166550.09%939181451.76%693138150.18%168293917107491437713
17Moose32100000853220000008261010000003-340.6678132100106123121477794907840169027186712325.00%9188.89%0834166550.09%939181451.76%693138150.18%168293917107491437713
18Penguins2110000068-2110000003121010000037-420.50061117001061231214647949078401660172726700.00%7185.71%0834166550.09%939181451.76%693138150.18%168293917107491437713
19Phantoms311001001420-620100100714-71100000076130.500142438001061231214967949078401611137286713430.77%9366.67%0834166550.09%939181451.76%693138150.18%168293917107491437713
20Punishers210010001073100010006511100000042241.0001018280010612312146979490784016661712337342.86%6266.67%0834166550.09%939181451.76%693138150.18%168293917107491437713
21Rockets31100100171611100000096320100100810-230.500173148001061231214107794907840161093416619222.22%8187.50%0834166550.09%939181451.76%693138150.18%168293917107491437713
22Senators624000002631-5312000001415-1312000001216-440.33326426810106123121418279490784016215817012119315.79%30970.00%0834166550.09%939181451.76%693138150.18%168293917107491437713
23Thunderbirds21100000121111010000035-21100000096320.5001220320010612312145179490784016613210377457.14%5180.00%0834166550.09%939181451.76%693138150.18%168293917107491437713
24Wolfpack21100000761110000005321010000023-120.500710170010612312147579490784016652463712216.67%30100.00%0834166550.09%939181451.76%693138150.18%168293917107491437713
25Wranglers403001001221-930300000816-81000010045-110.1251221331010612312141207949078401613540268518422.22%13469.23%0834166550.09%939181451.76%693138150.18%168293917107491437713
Total8035330470135434212402016013001831671640151703401171175-4860.538354590944301061231214255479490784016267587563715652866924.13%3035083.50%9834166550.09%939181451.76%693138150.18%168293917107491437713
_Since Last GM Reset8035330470135434212402016013001831671640151703401171175-4860.538354590944301061231214255479490784016267587563715652866924.13%3035083.50%9834166550.09%939181451.76%693138150.18%168293917107491437713
_Vs Conference4822180250121220210241390020010595102499023011071070540.563212353565201061231214151779490784016161452239410131884624.47%1873481.82%4834166550.09%939181451.76%693138150.18%168293917107491437713
_Vs Division1878012007581-69530010041338925011003448-14180.5007512520010106123121455879490784016608209188386781721.79%891682.02%1834166550.09%939181451.76%693138150.18%168293917107491437713

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8086L135459094425542675875637156530
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8035334701354342
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4020161300183167
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4015173401171175
Derniers 10 matchs
WLOTWOTL SOWSOL
530200
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2866924.13%3035083.50%9
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
794907840161061231214
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
834166550.09%939181451.76%693138150.18%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
168293917107491437713


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
13Admirals3Senators7LSommaire du match
312Admirals3Americans4LR1Sommaire du match
518Admirals9Condors2WSommaire du match
625Senators6Admirals4LSommaire du match
944Admirals1Icehogs9LR1Sommaire du match
1052Icehogs3Admirals2LSommaire du match
1572Admirals2Icehogs3LXR1Sommaire du match
1777Americans4Admirals3LXR1Sommaire du match
2099Wranglers6Admirals3LSommaire du match
21107Admirals3Comets2WXSommaire du match
24124Admirals6Senators4WSommaire du match
26130Phantoms6Admirals5LXSommaire du match
29147Admirals5Barracuda3WSommaire du match
30155Senators8Admirals7LSommaire du match
33174Admirals6Checkers4WSommaire du match
35180Barracuda5Admirals9WSommaire du match
40206Icehogs3Admirals5WR1Sommaire du match
43221Thunderbirds5Admirals3LSommaire du match
47238Admirals6Gulls5WXSommaire du match
49249Gulls6Admirals4LSommaire du match
53268Wolfpack3Admirals5WSommaire du match
55282Admirals4Crunch6LSommaire du match
58293Admirals5Griffins6LXXSommaire du match
60302Penguins1Admirals3WSommaire du match
64323Canucks6Admirals4LSommaire du match
66337Admirals5Islander4WSommaire du match
68348Admirals3Senators5LSommaire du match
70355Punishers5Admirals6WXSommaire du match
72371Admirals4Punishers2WSommaire du match
73380Admirals6Marlies1WSommaire du match
75386Wranglers5Admirals2LSommaire du match
78400Admirals4Condors2WSommaire du match
80410Admirals9Thunderbirds6WSommaire du match
81415Phantoms8Admirals2LSommaire du match
85437Griffins2Admirals3WSommaire du match
89456Admirals4Marlies2WSommaire du match
90463Comets2Admirals5WSommaire du match
94482Admirals4Little Stars1WSommaire du match
95490Eagles8Admirals7LSommaire du match
99506Admirals7Phantoms6WSommaire du match
101515Crunch2Admirals5WSommaire du match
105535Barracuda3Admirals5WSommaire du match
108552Admirals3Penguins7LSommaire du match
110560Checkers3Admirals8WSommaire du match
111572Admirals3Eagles4LSommaire du match
115588Senators1Admirals3WSommaire du match
117597Admirals2Wolfpack3LSommaire du match
119608Admirals6Icehogs5WXR1Sommaire du match
121618Bears5Admirals4LSommaire du match
124635Admirals4Condors7LSommaire du match
126642Admirals3Comets5LSommaire du match
127649Moose1Admirals3WSommaire du match
130665Admirals2Canucks7LSommaire du match
131675Little Stars1Admirals4WSommaire du match
134693Islander5Admirals7WSommaire du match
136704Admirals3Americans5LR1Sommaire du match
137712Admirals2Comets3LXSommaire du match
140726Condors3Admirals5WSommaire du match
143746Admirals4Rockets5LSommaire du match
144753Firebirds6Admirals5LSommaire du match
147767Admirals0Moose3LSommaire du match
148775Comets8Admirals3LSommaire du match
153798Moose1Admirals5WSommaire du match
155810Admirals8Gulls3WSommaire du match
157819Admirals7Firebirds2WSommaire du match
159830Rockets6Admirals9WSommaire du match
162849Firebirds5Admirals3LSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
165861Admirals4Bears5LSommaire du match
167873Admirals4Rockets5LXSommaire du match
169882Wranglers5Admirals3LSommaire du match
172896Admirals4Wranglers5LXSommaire du match
174908Marlies2Admirals1LSommaire du match
178931Americans2Admirals4WR1Sommaire du match
181950Icehogs3Admirals6WSommaire du match
183956Admirals3Checkers7LSommaire du match
184963Admirals7Americans6WR1Sommaire du match
188983Americans3Admirals7WSommaire du match
1921004Crunch7Admirals6LXSommaire du match
1961025Griffins3Admirals5WSommaire du match
1991034Admirals3Barracuda4LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance74,12237,237
Assistance PCT92.65%93.09%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2784 - 92.80% 175,298$7,011,918$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
3,430,318$ 2,510,000$ 2,510,000$ 1,000,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
12,426$ 2,410,181$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 17,376$ 0$




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