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Gulls
GP: 80 | W: 36 | L: 33 | OTL: 11 | P: 83
GF: 324 | GA: 339 | PP%: 19.00% | PK%: 74.38%
DG: Pierre-Olivier Lévesque | Morale : 26 | Moyenne d’équipe : 63

Centre de jeu
Americans
39-32-9, 87pts
3
FINAL
7 Gulls
36-33-11, 83pts
Team Stats
W3SéquenceL1
18-17-5Fiche domicile20-17-3
21-15-4Fiche domicile16-16-8
4-3-3Derniers 10 matchs5-5-0
4.00Buts par match 4.05
4.25Buts contre par match 4.24
25.09%Pourcentage en avantage numérique19.00%
79.01%Pourcentage en désavantage numérique74.38%
Americans
39-32-9, 87pts
5
FINAL
4 Gulls
36-33-11, 83pts
Team Stats
W3SéquenceL1
18-17-5Fiche domicile20-17-3
21-15-4Fiche domicile16-16-8
4-3-3Derniers 10 matchs5-5-0
4.00Buts par match 4.05
4.25Buts contre par match 4.24
25.09%Pourcentage en avantage numérique19.00%
79.01%Pourcentage en désavantage numérique74.38%
Meneurs d'équipe
Buts
Anton Blidh
48
Passes
Anton Blidh
61
Points
Anton Blidh
109
Plus/Moins
Dominic Turgeon
21
Victoires
Louis Domingue
27
Pourcentage d’arrêts
Louis Domingue
0.879

Statistiques d’équipe
Buts pour
324
4.05 GFG
Tirs pour
2625
32.81 Avg
Pourcentage en avantage numérique
19.0%
57 GF
Début de zone offensive
36.1%
Buts contre
339
4.24 GAA
Tirs contre
2607
32.59 Avg
Pourcentage en désavantage numérique
74.4%%
82 GA
Début de la zone défensive
37.0%
Informations de l'équipe

Directeur généralPierre-Olivier Lévesque
EntraîneurJean-Sebastien Giguere
DivisionThayer-Tutt
ConférenceRobert-Lebel
Capitaine
Assistant #1
Assistant #2Anton Blidh


Informations de l’aréna

Capacité3,000
Assistance2,749
Billets de saison300


Informations de la formation

Équipe Pro33
Équipe Mineure22
Limite contact 55 / 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
1Dominic Turgeon (R)X100.006636897074807070787968786861504261720232900,000$
2Jakub Vrana (R)X100.006938767572777475767077737857494446720232850,000$
3Anton Blidh (A)X100.008133777972717776677676606358513636710242800,000$
4Scott WilsonX100.007727767675797478696481607266612742710271900,000$
5Sergey TolchinskyX100.007821767474726980667169717254504046700241700,000$
6Troy Terry (R)X100.007032827969736478676670677647475046690222800,000$
7Henri IkonenX100.007445707067577466647367665048493221660242700,000$
8Nick Merkley (R)X100.006135836164736876827568456546464721660222650,000$
9Calvin Thurkauf (R)X100.007955706871548371626967595844464421660223750,000$
10Luke Kunin (R)X100.007537757374547376566372566045464246660221500,000$
11Mikhail Maltsev (R)X100.007146727080557076556767645645455849660211500,000$
12Massimo Rizzo (R)X100.004932574846574758615758335040406822510182500,000$
13Andrei MironovX100.006945877468717167627968776771543849720251950,000$
14Dylan DeMeloX100.006624818169717278537262696360543336700261900,000$
15Jack Glover (R)X100.006941827472727374626376696553504829700232900,000$
16Tarmo Reunanen (R)X100.006541807370596565477160766150464746680213750,000$
17Ryan Collins (R)X100.005635676867616560487158665447473821620231500,000$
18Markus Niemelainen (R)X100.006046666571676660456457615145436212620212500,000$
Rayé
1Branden TroockX100.006245787165616667676567576447472519640251600,000$
2Francis Perron (R)X100.006137726752567171737970436445484120640232600,000$
3Taylor LeierX100.005431825963645968565872556947472819620251450,000$
4Zack MacEwen (R)X100.006849656375637262586267575846473019620232600,000$
5Pavel Dorofeyev (R)X100.006337755080656368606673476641437324620192500,000$
6MacKenzie Entwistle (R)X100.007638695770587957597061524642425519600202500,000$
7Damien Giroux (R)X100.006435746160546556645661496541415821570191500,000$
8Niklas Nordgren (R)X100.004625714357514449624961404141415120500191400,000$
9Jake Pivonka (R)X100.004931635441554443524848334241415520460191500,000$
10Drew Helleson (R)X100.005624806160626352315835623840406320570182500,000$
MOYENNE D’ÉQUIPE100.00663675676764676761666659604947463064
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
1Louis Domingue100.00797074787178698272757169573062730271900,000$
2Eamon McAdam100.00677167616376796261836651503966680251500,000$
Rayé
1Mads Sogaard (R)100.00665568575271735350806842416120610192500,000$
2Connor Ingram100.00565545475055545547454243434120500221250,000$
3Alexis Gravel100.00554258584648584347465341415420490191500,000$
MOYENNE D’ÉQUIPE100.0065596260566667595566604946453860
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jean-Sebastien Giguere73796671916353CAN563800,000$


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
1Anton BlidhGulls (Ana)LW804861109-3520176922948518816.33%34164620.581322354524912381233457.89%1336922131.3202000696
2Dominic TurgeonGulls (Ana)C793647832180100147200699618.00%37142118.0089171795112112654152.27%14962231111.1700000553
3Jakub VranaGulls (Ana)RW80384482-57401111062198115017.35%41153919.2541822222361012515156.29%1674137211.0747000245
4Sergey TolchinskyGulls (Ana)LW8029346315601311052307613612.61%33143617.965492220002231793249.45%915123000.8811000423
5Troy TerryGulls (Ana)RW80242852822091591756110613.71%29104213.030444880001121252.78%363323001.0001000513
6Scott WilsonGulls (Ana)RW792723505515104802095411112.92%26104413.222243751017682047.37%385314100.9606000253
7Luke KuninGulls (Ana)C80232043426010385142327516.20%40110413.8112313540481665141.64%8192019010.7800000211
8Dean KukanDucksD7143438-342107112512050333.33%116192627.13347202080221258000%02771000.3900001012
9Andrei MironovGulls (Ana)D80333367241010716512252602.46%129204925.62145172600112164000%03776000.3501100033
10Mikhail MaltsevGulls (Ana)LW8017183543759366120396714.17%2386710.84000060111405058.82%17179000.8100100102
11Tarmo ReunanenGulls (Ana)D80719264120529969151210.14%79126515.822354740001153000%0551000.4100000010
12Jack GloverGulls (Ana)D68419231412059878029295.00%60124818.361014113000197000%02937000.3700000012
13Dylan DeMeloGulls (Ana)D8022022143007711610037392.00%91163420.43033131920001163000%02358000.2700000001
14Nick MerkleyGulls (Ana)RW61101020-220312274265313.51%55288.67000181011192050.00%1493000.7600000100
15Calvin ThurkaufGulls (Ana)C3712820-6280493357213621.05%544412.010110190003213147.01%23479000.9000000211
16Henri IkonenGulls (Ana)LW4047116120493038113010.53%1240310.08000040000150033.33%121013000.5500000001
17Markus NiemelainenGulls (Ana)D35279220016261211116.67%2546213.2100002000048010%026000.3911000000
18Pavel DorofeyevGulls (Ana)LW401343401611131127.69%42776.9400000000011071.43%760000.2901000000
19Branden TroockGulls (Ana)RW8033300423230%0496.2300002000000050.00%201001.2000000000
20Damien GirouxGulls (Ana)C1612314011990211.11%01489.27000010000150068.75%3212000.4000000000
21Ryan CollinsGulls (Ana)D9022-5204110100%49010.050000000001000%013000.4400000000
22Francis PerronGulls (Ana)LW8011000535040%0374.7400001000010066.67%301000.5300000000
23Taylor LeierGulls (Ana)LW4000000000000%051.2500000000040050.00%20100000000000
24Massimo RizzoGulls (Ana)C6000-120321000%0305.1300000000000037.50%160000000000000
25Drew HellesonGulls (Ana)D6000-640212100%710016.8100001300004000%00500000000000
Statistiques d’équipe totales ou en moyenne12872924437356652430146514822294754124312.73%8002080616.17407611617318919918511878341349.50%3119463515560.71620201303436
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
1Louis DomingueGulls (Ana)67272190.8794.003482202321920907510.706176019112
2Eamon McAdamGulls (Ana)3191220.8554.3813552099684329320.57172060001
Statistiques d’équipe totales ou en moyenne983633110.8734.114838403312604123683248079113


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
Alexis GravelGulls (Ana)G192000-01-01CANNo219 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Andrei MironovGulls (Ana)D251994-01-01RUSNo185 Lbs6 ft2NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm950,000$0$0$No---------------------------
Anton BlidhGulls (Ana)LW241995-01-01SWENo185 Lbs6 ft0NoNoTrade2024-08-06NoNo2FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------
Branden TroockGulls (Ana)RW251994-01-01CANNo194 Lbs6 ft2NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm600,000$0$0$No---------------------------
Calvin ThurkaufGulls (Ana)C221997-01-01CHEYes205 Lbs6 ft2NoNoTrade2025-03-19NoNo3FalseFalsePro & Farm750,000$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------
Connor IngramGulls (Ana)G221997-01-01CANNo196 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm250,000$0$0$No---------------------------
Damien GirouxGulls (Ana)C192000-01-01CANYes179 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Dominic TurgeonGulls (Ana)C231996-01-01CANYes200 Lbs6 ft2NoNoTrade2025-04-15NoNo2FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Drew HellesonGulls (Ana)D182001-01-01USAYes190 Lbs6 ft3NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Dylan DeMeloGulls (Ana)D261993-01-01CANNo195 Lbs6 ft1NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm900,000$0$0$No---------------------------
Eamon McAdamGulls (Ana)G251994-01-01USANo185 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Francis PerronGulls (Ana)LW231996-01-01CANYes178 Lbs6 ft2NoNoFree AgentNoNo22024-08-20FalseFalsePro & Farm600,000$0$0$No600,000$--------600,000$--------No--------
Henri IkonenGulls (Ana)LW241995-01-01FINNo185 Lbs6 ft0NoNoFree AgentNoNo22024-10-07FalseFalsePro & Farm700,000$0$0$No700,000$--------700,000$--------No--------
Jack GloverGulls (Ana)D231996-01-01USAYes198 Lbs6 ft3NoNoFree AgentNoNo22024-08-20FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Jake PivonkaGulls (Ana)C192000-01-01USAYes198 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Jakub VranaGulls (Ana)RW231996-01-01CZEYes197 Lbs6 ft0NoNoFree Agent2024-07-10NoNo22024-08-20FalseFalsePro & Farm850,000$0$0$No950,000$--------850,000$--------No--------
Louis DomingueGulls (Ana)G271992-01-01CANNo210 Lbs6 ft3NoNoFree AgentNoNo12024-10-22FalseFalsePro & Farm900,000$0$0$No---------------------------
Luke KuninGulls (Ana)C221997-01-01USAYes192 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
MacKenzie EntwistleGulls (Ana)RW201999-01-01CANYes184 Lbs6 ft3NoNoFree AgentNoNo22024-08-20FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------
Mads SogaardGulls (Ana)G192000-01-01DNKYes196 Lbs6 ft7NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Markus NiemelainenGulls (Ana)D211998-01-01FINYes201 Lbs6 ft5NoNoTrade2024-08-03NoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Massimo RizzoGulls (Ana)C182001-01-01CANYes181 Lbs5 ft11NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Mikhail MaltsevGulls (Ana)LW211998-01-01RUSYes220 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Nick MerkleyGulls (Ana)RW221997-01-01CANYes194 Lbs5 ft10NoNoTrade2024-09-01NoNo2FalseFalsePro & Farm650,000$0$0$No650,000$--------550,000$--------No--------
Niklas NordgrenGulls (Ana)RW192000-01-01FINYes182 Lbs5 ft8NoNoN/ANoNo1FalseFalsePro & Farm400,000$0$0$No---------------------------
Pavel DorofeyevGulls (Ana)LW192000-01-01RUSYes194 Lbs6 ft1NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Ryan CollinsGulls (Ana)D231996-01-01USAYes204 Lbs6 ft5NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm500,000$0$0$No---------------------------
Scott WilsonGulls (Ana)RW271992-01-01CANNo183 Lbs5 ft11NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm900,000$0$0$No---------------------------
Sergey TolchinskyGulls (Ana)LW241995-01-01RUSNo185 Lbs5 ft7NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm700,000$0$0$No---------------------------
Tarmo ReunanenGulls (Ana)D211998-01-01FINYes179 Lbs6 ft0NoNoTrade2024-07-10NoNo3FalseFalsePro & Farm750,000$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------
Taylor LeierGulls (Ana)LW251994-01-01CANNo174 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm450,000$0$0$No---------------------------
Troy TerryGulls (Ana)RW221997-01-01USAYes180 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm800,000$0$0$No900,000$--------600,000$--------No--------
Zack MacEwenGulls (Ana)RW231996-01-01CANYes205 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm600,000$0$0$No600,000$--------600,000$--------No--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3322.21193 Lbs6 ft11.58631,818$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Anton BlidhDominic TurgeonJakub Vrana40023
2Sergey TolchinskyLuke KuninScott Wilson30023
3Henri IkonenCalvin ThurkaufTroy Terry20023
4Mikhail MaltsevMassimo RizzoNick Merkley10023
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Andrei MironovDylan DeMelo40122
2Jack GloverTarmo Reunanen30122
3Ryan CollinsMarkus Niemelainen20122
4Andrei MironovDylan DeMelo10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Anton BlidhDominic TurgeonJakub Vrana60014
2Sergey TolchinskyLuke KuninScott Wilson40014
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Andrei MironovDylan DeMelo60014
2Jack GloverTarmo Reunanen40014
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jakub VranaDominic Turgeon60122
2Anton BlidhScott Wilson40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Andrei MironovDylan DeMelo60122
2Jack GloverTarmo Reunanen40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Jakub Vrana60122Andrei MironovDylan DeMelo60122
2Dominic Turgeon40122Jack GloverTarmo Reunanen40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jakub VranaDominic Turgeon60122
2Anton BlidhScott Wilson40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Andrei MironovDylan DeMelo60122
2Jack GloverTarmo Reunanen40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Anton BlidhDominic TurgeonJakub VranaAndrei MironovDylan DeMelo
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Anton BlidhDominic TurgeonJakub VranaAndrei MironovDylan DeMelo
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Anton Blidh, Dominic Turgeon, Jakub VranaAnton Blidh, Jakub VranaNick Merkley
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Ryan Collins, Markus Niemelainen, Jack GloverRyan CollinsMarkus Niemelainen, Jack Glover
Tirs de pénalité
Jakub Vrana, Dominic Turgeon, Anton Blidh, Scott Wilson, Sergey Tolchinsky
Gardien
#1 : Louis Domingue, #2 : Eamon McAdam
Lignes d’attaque personnalisées en prolongation
Jakub Vrana, Dominic Turgeon, Anton Blidh, Scott Wilson, Sergey Tolchinsky, Troy Terry, Luke Kunin, Nick Merkley, Henri Ikonen, Calvin Thurkauf
Lignes de défense personnalisées en prolongation
Andrei Mironov, Dylan DeMelo, Jack Glover, Tarmo Reunanen, Ryan Collins


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
1Admirals311001001418-420100100814-61100000064230.500142539001051041108103898853858419732206610440.00%11463.64%0875176949.46%892181249.23%678132151.32%172597816897371429715
2Americans421010002216621100000118321001000118360.7502239610010510411081508988538584114256207614428.57%10370.00%0875176949.46%892181249.23%678132151.32%172597816897371429715
3Barracuda733001002931-2413000001621-5320001001310370.5002949780010510411082298988538584121764771772713.70%32681.25%1875176949.46%892181249.23%678132151.32%172597816897371429715
4Bears21100000911-21010000015-41100000086220.500915240010510411087389885385841673023484125.00%9277.78%1875176949.46%892181249.23%678132151.32%172597816897371429715
5Canucks2110000068-2110000004311010000025-320.500610160010510411086889885385841731716431317.69%8537.50%0875176949.46%892181249.23%678132151.32%172597816897371429715
6Checkers22000000743110000003121100000043141.000712190010510411087289885385841501810449111.11%5180.00%0875176949.46%892181249.23%678132151.32%172597816897371429715
7Comets2110000010100110000005321010000057-220.5001014240010510411087889885385841711614404125.00%7357.14%0875176949.46%892181249.23%678132151.32%172597816897371429715
8Condors7330000128280431000001915430200001913-470.50028467410105104110822889885385841203805014731516.13%25676.00%0875176949.46%892181249.23%678132151.32%172597816897371429715
9Crunch210001001165110000008261000010034-130.7501120310010510411086089885385841672110372150.00%5180.00%0875176949.46%892181249.23%678132151.32%172597816897371429715
10Eagles2010100068-21010000025-31000100043120.500612180010510411086489885385841702114385120.00%70100.00%1875176949.46%892181249.23%678132151.32%172597816897371429715
11Firebirds211000001091110000006331010000046-220.50010162610105104110865898853858415120103710220.00%5260.00%0875176949.46%892181249.23%678132151.32%172597816897371429715
12Griffins606000001327-1430300000918-93030000049-500.00013233600105104110817889885385841201627610726415.38%31487.10%1875176949.46%892181249.23%678132151.32%172597816897371429715
13Icehogs311010001917210001000761211000001211140.667192746001051041108112898853858411023022696116.67%11554.55%1875176949.46%892181249.23%678132151.32%172597816897371429715
14Islander2100000111101110000007521000000145-130.7501118290010510411086089885385841751514365240.00%7442.86%0875176949.46%892181249.23%678132151.32%172597816897371429715
15Little Stars2010010039-61000010023-11010000016-510.250369001051041108678988538584169201651600.00%8275.00%0875176949.46%892181249.23%678132151.32%172597816897371429715
16Marlies30300000616-101010000036-320200000310-700.000691500105104110810589885385841923628511119.09%14471.43%0875176949.46%892181249.23%678132151.32%172597816897371429715
17Moose62200110302643210000017125301001101314-170.583303969001051041108192898853858412045476128371232.43%33972.73%3875176949.46%892181249.23%678132151.32%172597816897371429715
18Penguins312000001114-31100000062420200000512-720.33311203100105104110890898853858418930267413323.08%13192.31%0875176949.46%892181249.23%678132151.32%172597816897371429715
19Phantoms330000001486110000006422200000084461.0001424380010510411089289885385841100403265400.00%16475.00%0875176949.46%892181249.23%678132151.32%172597816897371429715
20Punishers2010000158-31010000024-21000000134-110.2505914101051041108758988538584161351641700.00%8187.50%0875176949.46%892181249.23%678132151.32%172597816897371429715
21Rockets311000101513220100010111101100000042240.66715223700105104110893898853858418238305614535.71%16568.75%0875176949.46%892181249.23%678132151.32%172597816897371429715
22Senators531001001915431100100111012200000085370.700193352001051041108161898853858411756036887114.29%18383.33%0875176949.46%892181249.23%678132151.32%172597816897371429715
23Thunderbirds2010000168-21010000045-11000000123-110.25069150010510411085989885385841703112469111.11%6183.33%0875176949.46%892181249.23%678132151.32%172597816897371429715
24Wolfpack2110000089-1110000006421010000025-320.500813210010510411085889885385841641684611436.36%4325.00%0875176949.46%892181249.23%678132151.32%172597816897371429715
25Wranglers3200000112102110000004312100000187150.83312213300105104110893898853858411153823581516.67%11372.73%0875176949.46%892181249.23%678132151.32%172597816897371429715
Total80313303625324339-1540181701310178173540131602315146166-20830.519324531855301051041108262589885385841260788067916693005719.00%3208274.38%8875176949.46%892181249.23%678132151.32%172597816897371429715
_Since Last GM Reset80313303625324339-1540181701310178173540131602315146166-20830.519324531855301051041108262589885385841260788067916693005719.00%3208274.38%8875176949.46%892181249.23%678132151.32%172597816897371429715
_Vs Conference53212202422221225-427101301210122128-6261190121299972560.528221357578101051041108173689885385841173059049010882023919.31%2285675.44%6875176949.46%892181249.23%678132151.32%172597816897371429715
_Vs Division2681400211100112-121468000006166-51226002113946-7210.404100157257101051041108827898853858418252602795591212218.18%1212579.34%5875176949.46%892181249.23%678132151.32%172597816897371429715

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8083L132453185526252607880679166930
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8031333625324339
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4018171310178173
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4013162315146166
Derniers 10 matchs
WLOTWOTL SOWSOL
451000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3005719.00%3208274.38%8
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
898853858411051041108
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
875176949.46%892181249.23%678132151.32%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
172597816897371429715


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
14Barracuda6Gulls4LR1Sommaire du match
519Gulls4Barracuda5LXSommaire du match
836Gulls1Condors2LR1Sommaire du match
946Condors6Gulls2LSommaire du match
1259Moose4Gulls9WSommaire du match
1779Gulls2Griffins3LR1Sommaire du match
1993Griffins3Gulls1LSommaire du match
21106Barracuda4Gulls2LR1Sommaire du match
22112Gulls4Moose3WXXSommaire du match
26134Senators2Gulls1LXSommaire du match
30152Gulls5Wranglers3WSommaire du match
31164Rockets4Gulls5WXXSommaire du match
35183Condors4Gulls7WR1Sommaire du match
37193Gulls3Condors4LXXSommaire du match
39203Gulls2Marlies7LSommaire du match
41212Penguins2Gulls6WSommaire du match
43218Gulls3Penguins5LSommaire du match
47238Admirals6Gulls5LXSommaire du match
49249Gulls6Admirals4WSommaire du match
51262Gulls5Comets7LSommaire du match
53270Gulls5Icehogs3WSommaire du match
55278Comets3Gulls5WSommaire du match
57291Gulls4Eagles3WXSommaire du match
59296Gulls3Senators2WSommaire du match
61307Senators6Gulls4LSommaire du match
64325Gulls3Punishers4LXXSommaire du match
66334Wranglers3Gulls4WSommaire du match
69353Gulls5Condors7LR1Sommaire du match
70359Firebirds3Gulls6WSommaire du match
73375Gulls3Wranglers4LXXSommaire du match
75385Griffins8Gulls4LR1Sommaire du match
79406Eagles5Gulls2LSommaire du match
82425Condors2Gulls4WR1Sommaire du match
84434Gulls2Thunderbirds3LXXSommaire du match
87450Senators2Gulls6WSommaire du match
91468Gulls4Islander5LXXSommaire du match
93478Wolfpack4Gulls6WSommaire du match
95489Gulls2Canucks5LSommaire du match
99505Punishers4Gulls2LSommaire du match
104526Phantoms4Gulls6WSommaire du match
106542Gulls4Checkers3WSommaire du match
108549Moose3Gulls6WSommaire du match
111571Gulls2Wolfpack5LSommaire du match
113579Little Stars3Gulls2LXSommaire du match
118601Moose5Gulls2LSommaire du match
121623Gulls5Barracuda3WR1Sommaire du match
123628Marlies6Gulls3LSommaire du match
126647Gulls4Barracuda2WR1Sommaire du match
127654Checkers1Gulls3WSommaire du match
130668Gulls4Rockets2WSommaire du match
132679Crunch2Gulls8WSommaire du match
134695Gulls4Moose5LXSommaire du match
135699Gulls3Crunch4LXSommaire du match
137710Thunderbirds5Gulls4LSommaire du match
140729Gulls6Americans5WXSommaire du match
142736Barracuda8Gulls5LR1Sommaire du match
145756Gulls5Americans3WSommaire du match
146762Canucks3Gulls4WSommaire du match
149782Bears5Gulls1LSommaire du match
151791Gulls1Marlies3LSommaire du match
153799Gulls1Little Stars6LSommaire du match
155810Admirals8Gulls3LSommaire du match
157824Gulls7Icehogs8LSommaire du match
160837Gulls5Senators3WSommaire du match
161844Rockets7Gulls6LSommaire du match
164858Gulls3Phantoms1WSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
166868Islander5Gulls7WSommaire du match
170886Gulls8Bears6WSommaire du match
171891Gulls1Griffins4LR1Sommaire du match
173903Griffins7Gulls4LSommaire du match
175918Icehogs6Gulls7WXSommaire du match
178936Gulls2Penguins7LSommaire du match
180944Condors3Gulls6WR1Sommaire du match
181947Gulls1Griffins2LR1Sommaire du match
185972Barracuda3Gulls5WSommaire du match
186973Gulls5Phantoms3WSommaire du match
189986Gulls4Firebirds6LSommaire du match
191995Gulls5Moose6LSommaire du match
1941011Americans3Gulls7WSommaire du match
2001037Americans5Gulls4LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance73,39836,560
Assistance PCT91.75%91.40%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2749 - 91.63% 173,257$6,930,271$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
3,099,030$ 2,085,000$ 2,085,000$ 800,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
10,322$ 2,290,159$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 14,282$ 0$




Gulls 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

Gulls 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

Gulls 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

Gulls 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

Gulls 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