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

Goons
GP: 44 | W: 14 | L: 23 | OTL: 7 | P: 35
GF: 101 | GA: 133 | PP%: 13.13% | PK%: 87.42%
DG: Stephane Morin | Morale : 90 | Moyenne d’équipe : 57
Prochains matchs #716 vs Spartans

Centre de jeu
Husky
19-21-5, 43pts
0
5 Goons
14-23-7, 35pts
Team Stats
W1SéquenceL1
11-9-3Fiche domicile9-10-4
8-12-2Fiche domicile5-13-3
7-2-1Derniers 10 matchs3-7-0
2.80Buts par match 2.30
3.22Buts contre par match 3.02
17.79%Pourcentage en avantage numérique13.13%
84.10%Pourcentage en désavantage numérique87.42%
Goons
14-23-7, 35pts
2
3 Sags
22-20-5, 49pts
Team Stats
L1SéquenceW1
9-10-4Fiche domicile14-7-1
5-13-3Fiche domicile8-13-4
3-7-0Derniers 10 matchs4-4-2
2.30Buts par match 2.83
3.02Buts contre par match 2.94
13.13%Pourcentage en avantage numérique19.09%
87.42%Pourcentage en désavantage numérique81.44%
Spartans
25-17-2, 52pts
Jour 57
Goons
14-23-7, 35pts
Statistiques d’équipe
L1SéquenceL1
14-7-2Fiche domicile9-10-4
11-10-0Fiche visiteur5-13-3
5-4-110 derniers matchs3-7-0
3.14Buts par match 2.30
3.07Buts contre par match 2.30
10.93%Pourcentage en avantage numérique13.13%
82.57%Pourcentage en désavantage numérique87.42%
Goons
14-23-7, 35pts
Jour 58
Outlaws
28-14-3, 59pts
Statistiques d’équipe
L1SéquenceSOW1
9-10-4Fiche domicile17-3-3
5-13-3Fiche visiteur11-11-0
3-7-010 derniers matchs7-2-1
2.30Buts par match 3.36
3.02Buts contre par match 3.36
13.13%Pourcentage en avantage numérique12.66%
87.42%Pourcentage en désavantage numérique87.01%
Goons
14-23-7, 35pts
Jour 59
Bandits
24-17-5, 53pts
Statistiques d’équipe
L1SéquenceSOL1
9-10-4Fiche domicile13-8-2
5-13-3Fiche visiteur11-9-3
3-7-010 derniers matchs6-3-1
2.30Buts par match 3.13
3.02Buts contre par match 3.13
13.13%Pourcentage en avantage numérique17.16%
87.42%Pourcentage en désavantage numérique86.06%
Meneurs d'équipe
Max SassonButs
Max Sasson
10
Jake BeanPasses
Jake Bean
21
Juuso ValimakiPoints
Juuso Valimaki
29
Juuso ValimakiPlus/Moins
Juuso Valimaki
4
Louis DomingueVictoires
Louis Domingue
11
Magnus ChronaPourcentage d’arrêts
Magnus Chrona
0.902

Statistiques d’équipe
Buts pour
101
2.30 GFG
Tirs pour
995
22.61 Avg
Pourcentage en avantage numérique
13.1%
26 GF
Début de zone offensive
38.4%
Buts contre
133
3.02 GAA
Tirs contre
1322
30.05 Avg
Pourcentage en désavantage numérique
87.4%%
19 GA
Début de la zone défensive
41.9%
Informations de l'équipe

Directeur généralStephane Morin
EntraîneurGreg Cronin
DivisionDivision Est
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,684
Billets de saison1,500


Informations de la formation

Équipe Pro30
Équipe Mineure18
Limite Contrat48 / 50
Espoirs26


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
1Jonny BrodzinskiX100.00574593807058626078516966689180090640321950,000$
2Tyler MotteX95.007645927957576652714756806690780906403051,239,876$
3Max Sasson (R)X95.006045958157524055735158676684710906002543,000,000$
4Christian FischerX97.00924888767456565130515261658876090590284995,995$
5Marc McLaughlin (R)X99.00784595786550405130445858658572090570265800,000$
6Nicolas Aube-KubelX100.00884871747150404930445459508875090560295850,000$
7James Hamblin (R)X100.00504595785450404581405055508471090540264800,000$
8Pavol Regenda (R)X100.005045927479504045304050555084730905302531,100,000$
9Sammy BlaisX100.005045797672504045304050555087740905302921,000,000$
10Zach Dean (R)X100.00504587795350404530405055508169090520224800,000$
11Haydn FleuryX100.007445917871664752305550666688780906402952,600,000$
12Marc-Edouard VlasicX100.005045937764614050304655756598870906303812,500,000$
13Jake BeanX100.005345927857637750304654756586750906302721,800,000$
14Grant HuttonX100.00604590757056404930485072508977090610304925,225$
15Matthew Kessel (R)X100.00634586766655404930485059508472090590254800,000$
Rayé
1Bokondji ImamaX94.00985154737750404730405462508875090570292775,000$
2Jacob LucchiniX100.00504592785457404530405079508977090560302999,999$
3Mike HardmanX100.00504595757150404730445057508673090540264775,000$
4James Malatesta (R)X100.005245957755534045304050555081690905202211,025,000$
5Isaac Ratcliffe (R)X100.00504595766050404530405055508471090520263775,000$
6Tye Felhaber (R)X100.00534595785550404530405055508673090520272800,000$
7Conor ShearyX100.00504590784757404530405055509280090520334900,000$
8Juuso ValimakiX93.785845867864695251304656716586770906302631,500,000$
9William LagessonX100.00524590746961404730445063508978090590292775,000$
10Declan Carlile (R)X100.00504595776154404830405655508472090560254800,000$
11Lucas Johansen (R)X100.00504590795250404530405055508674090560273995,000$
12Santeri Hatakka (R)X100.00504590785850404530405055508372090560243800,000$
MOYENNE D’ÉQUIPE99.0060458977635544483744536255877509057
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 Domingue100.0070506089707070707070709279090620334925,225$
2Magnus Chrona (R)100.00704040906565656565656583720905802521,200,000$
Rayé
1Eetu Makiniemi (R)100.0070404083656565656565658370090570264800,000$
MOYENNE D’ÉQUIPE100.007043478767676767676767867409059
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Greg Cronin88787077967248USA632900,000$


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
1Juuso ValimakiGoons (QUE)D44920294280645358245315.52%5592020.924913331570001115100%000100.6300000430
2Jonny BrodzinskiGoons (QUE)C41101727-2401511010135799.90%777919.0238113315200031252063.51%102500000.6901000172
3Max SassonGoons (QUE)C37101525-320810393256010.75%1070319.01347211280002881062.38%82400000.7101000321
4Christian FischerGoons (QUE)RW441015250275805670225114.29%476617.4212312159000093246.00%5000000.6502100422
5Jake BeanGoons (QUE)D4432124-437557585822395.17%4094921.59077351590003113100%000000.5100100114
6Tyler MotteGoons (QUE)RW41101020-44515689111728858.55%1375918.5132533148000052149.15%5900000.5301210304
7Haydn FleuryGoons (QUE)D4661420-12400116486319299.52%6499721.6946103615500001171035.90%3900000.4000000224
8Marc McLaughlinGoons (QUE)LW406915-8260513059163710.17%575818.95213161330001900043.06%7200100.4011000032
9Marc-Edouard VlasicGoons (QUE)D4331013-1614040486417374.69%3795622.23235361560000116000%000000.2700000022
10Grant HuttonGoons (QUE)D4411011-1625556353312233.03%4285319.3902219103000181000%200000.2600100011
11Jacob LucchiniGoons (QUE)RW347411-204095659194011.86%1151215.07101233000041036.36%2200000.4300000211
12Matthew KesselGoons (QUE)D441910-212958923139137.69%3570916.12011119000017000%000000.2800001000
13William LagessonGoons (QUE)D23189-1280151716386.25%2039016.98000017000030000%000000.4600000012
14Bokondji ImamaGoons (QUE)LW3027935610105262810287.14%354618.211122890001591130.23%4300000.3300002202
15James HamblinGoons (QUE)C44347-9007603113259.68%04379.940001160000110060.36%38600000.3200000003
16Isaac RatcliffeGoons (QUE)LW54041202380550.00%07815.7300007000070040.00%500011.0200000101
17Sammy BlaisGoons (QUE)RW39224-100015162110169.52%33619.28000210000000056.25%1600000.2200000101
18James MalatestaGoons (QUE)RW14303-50057161618.75%418513.28000111000040026.92%2600000.3200000020
19Mike HardmanGoons (QUE)LW27213-10205182052010.00%146017.071013530001380044.00%2500000.1300000010
20Nicolas Aube-KubelGoons (QUE)LW21112-82755214255154.00%736117.200112410001231040.00%3500000.1100001000
21Zach DeanGoons (QUE)C6011-100275230%07412.3900000000000039.66%5800000.2700000000
22Pavol RegendaGoons (QUE)LW14101-900510153116.67%419914.2300014000030041.67%1200000.1000000100
23Declan CarlileGoons (QUE)D2000-100102000%03316.990000100001000%00000000000000
24Tye FelhaberGoons (QUE)C11000-1220588360%016915.430000500006000%40000000000000
25Conor ShearyGoons (QUE)RW3000100001120%0268.710000000000000%10000000000000
Statistiques d’équipe totales ou en moyenne74195178273-174378508728979843046919.65%3651299117.53254772289176700014107214458.69%270400210.4216514252832
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 DomingueGoons (QUE)32111830.9012.9518532191920022023212462
2Magnus ChronaGoons (QUE)143540.9022.8980901394000001.00051232312
Statistiques d’équipe totales ou en moyenne46142370.9022.93266222130132002274444774


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis ParDate de la Dernière TransactionBallotage forcé Waiver Possible Contrat Date du Signature du ContratForcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Bokondji ImamaGoons (QUE)LW291996-08-03CANNo221 Lbs6 ft1NoNoAssign ManuallyNoNo22026-03-08FalseFalsePro & Farm775,000$380,324$0$0$No775,000$--------775,000$--------No--------Lien NHL
Christian FischerGoons (QUE)RW281997-04-15USANo212 Lbs6 ft2NoNoAssign Manually2025-04-14NoNo42026-03-08FalseFalsePro & Farm995,995$488,775$0$0$No995,995$995,995$995,995$------995,995$995,995$995,995$------NoNoNo------Lien NHL
Conor ShearyGoons (QUE)RW331992-06-08USANo179 Lbs5 ft8NoNoTrade2026-03-12NoNo42026-03-08FalseFalsePro & Farm900,000$441,667$0$0$No900,000$900,000$900,000$------900,000$900,000$900,000$------NoNoNo------Lien NHL
Declan CarlileGoons (QUE)D252000-05-18USAYes185 Lbs6 ft1NoNoN/ANoNo42026-03-08FalseFalsePro & Farm800,000$392,593$0$0$No800,000$800,000$800,000$------800,000$800,000$800,000$------NoNoNo------Lien NHL
Eetu MakiniemiGoons (QUE)G261999-04-19FINYes184 Lbs6 ft2NoNoN/ANoNo42026-03-08FalseFalsePro & Farm800,000$392,593$0$0$No800,000$800,000$800,000$------800,000$800,000$800,000$------NoNoNo------Lien NHL
Grant HuttonGoons (QUE)D301995-07-25USANo206 Lbs6 ft3NoNoAssign ManuallyNoNo42026-03-08FalseFalsePro & Farm925,225$454,046$0$0$No925,225$925,225$925,225$------925,225$925,225$925,225$------NoNoNo------Lien NHL
Haydn FleuryGoons (QUE)D291996-07-08CANNo207 Lbs6 ft4NoNoTrade2026-05-13NoNo52026-03-20FalseFalsePro & Farm2,600,000$1,275,926$0$0$No2,600,000$2,600,000$2,600,000$2,600,000$-----2,600,000$2,600,000$2,600,000$2,600,000$-----NoNoNoNo-----Lien NHL
Isaac RatcliffeGoons (QUE)LW261999-02-15CANYes200 Lbs6 ft6NoNoTrade2026-01-11NoNo32026-03-08FalseFalsePro & Farm775,000$380,324$0$0$No775,000$775,000$-------775,000$775,000$-------NoNo-------Lien NHL
Jacob LucchiniGoons (QUE)RW301995-05-09CANNo180 Lbs6 ft0NoNoN/ANoNo22026-03-08FalseFalsePro & Farm999,999$490,740$0$0$No999,999$--------999,999$--------No--------
Jake BeanGoons (QUE)D271998-06-09CANNo191 Lbs6 ft1NoNoTrade2025-09-13NoNo22026-03-08FalseFalsePro & Farm1,800,000$883,333$0$0$No1,800,000$--------1,800,000$--------No--------Lien NHL
James HamblinGoons (QUE)C261999-04-27CANYes185 Lbs5 ft10NoNoN/ANoNo42026-03-08FalseFalsePro & Farm800,000$392,593$0$0$No800,000$800,000$800,000$------800,000$800,000$800,000$------NoNoNo------Lien NHL
James MalatestaGoons (QUE)RW222003-05-31CANYes191 Lbs5 ft9NoNoTrade2026-05-28NoNo12026-03-08FalseFalsePro & Farm1,025,000$503,009$0$0$No---------------------------Lien NHL
Jonny BrodzinskiGoons (QUE)C321993-06-19USANo204 Lbs6 ft0NoNoTrade2026-03-12NoNo12026-03-08FalseFalsePro & Farm950,000$466,204$0$0$No---------------------------Lien NHL
Juuso ValimakiGoons (QUE)D261998-10-06FINNo205 Lbs6 ft2NoNoTrade2025-11-14NoNo32026-03-08FalseFalsePro & Farm1,500,000$736,111$0$0$No1,500,000$1,500,000$-------1,500,000$1,500,000$-------NoNo-------Lien NHL
Louis DomingueGoons (QUE)G331992-03-06CANNo208 Lbs6 ft3NoNoAssign ManuallyNoNo42026-03-08FalseFalsePro & Farm925,225$454,046$0$0$No925,225$925,225$925,225$------925,225$925,225$925,225$------NoNoNo------Lien NHL
Lucas JohansenGoons (QUE)D271997-11-16CANYes176 Lbs6 ft2NoNoAssign ManuallyNoNo32026-03-08FalseFalsePro & Farm995,000$488,287$0$0$No995,000$995,000$-------995,000$995,000$-------NoNo-------Lien NHL
Magnus ChronaGoons (QUE)G252000-08-28SWEYes207 Lbs6 ft5NoNoTrade2025-03-20NoNo22026-03-08FalseFalsePro & Farm1,200,000$588,889$0$0$No1,200,000$--------1,200,000$--------No--------Lien NHL
Marc McLaughlinGoons (QUE)LW261999-07-26USAYes199 Lbs6 ft0NoNoAssign ManuallyNoNo52026-04-05FalseFalsePro & Farm800,000$392,593$0$0$No800,000$800,000$800,000$800,000$-----800,000$800,000$800,000$800,000$-----NoNoNoNo-----Lien NHL
Marc-Edouard VlasicGoons (QUE)D381987-03-30CANNo205 Lbs6 ft1NoNoTrade2025-09-28NoNo12026-03-08FalseFalsePro & Farm2,500,000$1,226,852$0$0$No---------------------------Lien NHL
Matthew KesselGoons (QUE)D252000-06-23USAYes205 Lbs6 ft2NoNoN/ANoNo42026-03-08FalseFalsePro & Farm800,000$392,593$0$0$No800,000$800,000$800,000$------800,000$800,000$800,000$------NoNoNo------Lien NHL
Max SassonGoons (QUE)C252000-09-05CANYes181 Lbs6 ft1NoNoTrade2025-12-13NoNo42026-03-08FalseFalsePro & Farm3,000,000$1,472,222$0$0$No3,000,000$3,000,000$3,000,000$------3,000,000$3,000,000$3,000,000$------NoNoNo------Lien NHL
Mike HardmanGoons (QUE)LW261999-02-05USANo205 Lbs6 ft2NoNoN/ANoNo42026-03-08FalseFalsePro & Farm775,000$380,324$0$0$No775,000$775,000$775,000$------775,000$775,000$775,000$------NoNoNo------Lien NHL
Nicolas Aube-KubelGoons (QUE)LW291996-05-10CANNo207 Lbs6 ft0NoNoTrade2026-06-04NoNo52026-04-14FalseFalsePro & Farm850,000$417,130$0$0$No850,000$850,000$850,000$850,000$-----850,000$850,000$850,000$850,000$-----NoNoNoNo-----Lien NHL
Pavol RegendaGoons (QUE)LW251999-12-07SLKYes211 Lbs6 ft4NoNoN/ANoNo32026-03-08FalseFalsePro & Farm1,100,000$539,815$0$0$No1,100,000$1,100,000$-------1,100,000$1,100,000$-------NoNo-------Lien NHL
Sammy BlaisGoons (QUE)RW291996-06-17CANNo206 Lbs6 ft2NoNoTrade2025-04-07NoNo22026-03-08FalseFalsePro & Farm1,000,000$490,741$0$0$No1,000,000$--------1,000,000$--------No--------Lien NHL
Santeri HatakkaGoons (QUE)D242001-01-15FINYes191 Lbs6 ft1NoNoN/ANoNo32026-03-08FalseFalsePro & Farm800,000$392,593$0$0$No800,000$800,000$-------800,000$800,000$-------NoNo-------Lien NHL
Tye FelhaberGoons (QUE)C271998-08-05CANYes185 Lbs5 ft11NoNoProspectNoNo22026-03-08FalseFalsePro & Farm800,000$392,593$0$0$No800,000$--------800,000$--------No--------Lien NHL
Tyler MotteGoons (QUE)RW301995-03-10USANo194 Lbs5 ft10NoNoAssign Manually2026-01-16NoNo52026-03-20FalseFalsePro & Farm1,239,876$608,458$0$0$No1,239,876$1,239,876$1,239,876$1,239,876$-----1,239,876$1,239,876$1,239,876$1,239,876$-----NoNoNoNo-----Lien NHL
William LagessonGoons (QUE)D291996-02-22SWENo211 Lbs6 ft2NoNoTrade2026-01-11NoNo22026-03-08FalseFalsePro & Farm775,000$380,324$0$0$No775,000$--------750,000$--------No--------Lien NHL
Zach DeanGoons (QUE)C222003-01-04CANYes176 Lbs6 ft0NoNoTrade2025-06-14NoNo42026-03-08FalseFalsePro & Farm800,000$392,593$0$0$No800,000$800,000$800,000$------800,000$800,000$800,000$------NoNoNo------Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3027.63197 Lbs6 ft13.201,133,544$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Marc McLaughlinJonny BrodzinskiTyler Motte35122
2Max SassonChristian Fischer30122
3Nicolas Aube-KubelJames HamblinSammy Blais25122
4Pavol RegendaZach DeanTyler Motte10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Haydn FleuryMarc-Edouard Vlasic35122
2Jake Bean30122
3Grant HuttonMatthew Kessel25122
4Haydn FleuryMarc-Edouard Vlasic10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Marc McLaughlinJonny BrodzinskiTyler Motte55122
2Max SassonChristian Fischer45122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Haydn FleuryMarc-Edouard Vlasic55122
2Jake Bean45122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jonny BrodzinskiMarc McLaughlin55122
2Max Sasson45122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Haydn FleuryMarc-Edouard Vlasic55122
2Jake Bean45122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Jonny Brodzinski55122Haydn FleuryMarc-Edouard Vlasic55122
2Max Sasson45122Jake Bean45122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jonny BrodzinskiMarc McLaughlin55122
2Max Sasson45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Haydn FleuryMarc-Edouard Vlasic55122
2Jake Bean45122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Marc McLaughlinJonny BrodzinskiTyler MotteHaydn FleuryMarc-Edouard Vlasic
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Max SassonChristian FischerJake Bean
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Marc McLaughlin, , Nicolas Aube-KubelMarc McLaughlin, Marc McLaughlin
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
, Grant Hutton, Matthew Kessel, Grant Hutton
Tirs de pénalité
Tyler Motte, Jonny Brodzinski, Max Sasson, Christian Fischer, Marc McLaughlin
Gardien
#1 : Louis Domingue, #2 : Magnus Chrona


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
TotalDomicile Visiteur
# 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 RI
1Bandits1010000025-31010000025-30000000000000.00024600392734121332308345173912221300.00%10100.00%0737130556.48%798142556.00%39167058.36%11007601009316556286
2Barracudas2020000018-71010000013-21010000005-500.00012310392734152332308345178820834800.00%40100.00%0737130556.48%798142556.00%39167058.36%11007601009316556286
3Bayou1010000024-2000000000001010000024-200.00023500392734124332308345173417225400.00%10100.00%0737130556.48%798142556.00%39167058.36%11007601009316556286
4Chiwawa11000000404110000004040000000000021.0004711013927341263323083451796621500.00%30100.00%0737130556.48%798142556.00%39167058.36%11007601009316556286
5CoolFm2020000036-31010000024-21010000012-100.00036900392734139332308345176615202310110.00%100100.00%0737130556.48%798142556.00%39167058.36%11007601009316556286
6Farmers1010000034-11010000034-10000000000000.00035800392734128332308345172764215120.00%20100.00%0737130556.48%798142556.00%39167058.36%11007601009316556286
7Hunters210000017521000000134-11100000041330.750711180039273415833230834517712614358450.00%60100.00%0737130556.48%798142556.00%39167058.36%11007601009316556286
8Husky11000000505110000005050000000000021.0005101501392734132332308345173034197114.29%20100.00%0737130556.48%798142556.00%39167058.36%11007601009316556286
9Igloos1000010045-11000010045-10000000000010.500471100392734128332308345173046217114.29%3166.67%0737130556.48%798142556.00%39167058.36%11007601009316556286
10Marlies30200100310-72010010026-41010000014-310.16736900392734160332308345171022354561300.00%14378.57%0737130556.48%798142556.00%39167058.36%11007601009316556286
11Marmots3120000038-5110000002112020000017-620.333369003927341463323083451767131657600.00%8187.50%0737130556.48%798142556.00%39167058.36%11007601009316556286
12Outlaws1000010034-11000010034-10000000000010.50036900392734121332308345173496223133.33%30100.00%0737130556.48%798142556.00%39167058.36%11007601009316556286
13Predateurs21100000761000000000002110000076120.5007121910392734156332308345174510253013215.38%40100.00%0737130556.48%798142556.00%39167058.36%11007601009316556286
14Raptors32100000880220000007431010000014-340.6678152300392734168332308345178225244913215.38%12191.67%0737130556.48%798142556.00%39167058.36%11007601009316556286
15Sags21100000743110000005141010000023-120.5007132000392734131332308345175166397114.29%30100.00%0737130556.48%798142556.00%39167058.36%11007601009316556286
16Smirnoff Ice211000004401010000023-11100000021120.5004812003927341293323083451733817332150.00%6183.33%0737130556.48%798142556.00%39167058.36%11007601009316556286
17Snowbirds21000100550110000003211000010023-130.75059140039273415033230834517641514508225.00%70100.00%0737130556.48%798142556.00%39167058.36%11007601009316556286
18Thugs2010010069-31010000035-21000010034-110.25069150039273415333230834517679204116212.50%9366.67%0737130556.48%798142556.00%39167058.36%11007601009316556286
19Twins31100010871100000102112110000066040.66781018003927341743323083451710422395613215.38%160100.00%0737130556.48%798142556.00%39167058.36%11007601009316556286
20Vandals2110000023-11010000002-21100000021120.50024600392734138332308345172716163710110.00%7271.43%0737130556.48%798142556.00%39167058.36%11007601009316556286
21Vipers2010010026-4000000000002010010026-410.2502350039273414633230834517641818401300.00%9188.89%0737130556.48%798142556.00%39167058.36%11007601009316556286
22Wolves31200000811-3211000007701010000014-320.33381422003927341753323083451711022316615320.00%12558.33%0737130556.48%798142556.00%39167058.36%11007601009316556286
23Xpress20200000411-71010000004-41010000047-300.00047110039273414033230834517782318479111.11%9188.89%0737130556.48%798142556.00%39167058.36%11007601009316556286
Total44132300611101133-3223810003116065-521513003004168-27350.3981011772782239273419953323083451713223283708431982613.13%1511987.42%0737130556.48%798142556.00%39167058.36%11007601009316556286
_Since Last GM Reset44132300611101133-3223810003116065-521513003004168-27350.3981011772782239273419953323083451713223283708431982613.13%1511987.42%0737130556.48%798142556.00%39167058.36%11007601009316556286
_Vs Conference18411002013858-201126002012536-11725000001322-9110.306387010801392734138133230834517543133155333701014.29%61788.52%0737130556.48%798142556.00%39167058.36%11007601009316556286
_Vs Division925001012532-7613001011622-631200000910-160.33325457001392734121833230834517314836416644818.18%31293.55%0737130556.48%798142556.00%39167058.36%11007601009316556286

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
4435L1101177278995132232837084322
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
4413230611101133
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2381003116065
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2151303004168
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
1982613.13%1511987.42%0
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
332308345173927341
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
737130556.48%798142556.00%39167058.36%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
11007601009316556286


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
110Goons0Vipers3LSommaire du match
224Barracudas3Goons1LSommaire du match
439Chiwawa0Goons4WSommaire du match
559Goons0Marmots1LSommaire du match
671Sags1Goons5WSommaire du match
786Goons2Twins5LSommaire du match
999Marlies3Goons2LXSommaire du match
11126Goons2Bayou4LSommaire du match
12136Outlaws4Goons3LXSommaire du match
14159Igloos5Goons4LXSommaire du match
16180Goons6Predateurs3WSommaire du match
17190Thugs5Goons3LSommaire du match
18210Goons2Snowbirds3LXSommaire du match
19221Wolves6Goons4LSommaire du match
20242Goons0Barracudas5LSommaire du match
21251Goons2Vandals1WSommaire du match
22263Hunters4Goons3LXXSommaire du match
24283Goons1Predateurs3LSommaire du match
25293Marlies3Goons0LSommaire du match
26314Twins1Goons2WXXSommaire du match
28338Goons4Twins1WSommaire du match
29349Vandals2Goons0LSommaire du match
31369Goons1Marmots6LSommaire du match
32383Raptors1Goons2WSommaire du match
34402Goons4Hunters1WSommaire du match
35417Raptors3Goons5WSommaire du match
36435CoolFm4Goons2LSommaire du match
37448Goons3Thugs4LXSommaire du match
38464Goons4Xpress7LSommaire du match
39473Bandits5Goons2LSommaire du match
41497Snowbirds2Goons3WSommaire du match
42514Goons1Wolves4LSommaire du match
43527Goons2Vipers3LXSommaire du match
44537Marmots1Goons2WSommaire du match
45552Goons2Smirnoff Ice1WSommaire du match
46566Farmers4Goons3LSommaire du match
47589Xpress4Goons0LSommaire du match
48601Goons1Raptors4LSommaire du match
49621Smirnoff Ice3Goons2LSommaire du match
51637Goons1CoolFm2LSommaire du match
52646Goons1Marlies4LSommaire du match
53659Wolves1Goons3WSommaire du match
54681Husky0Goons5WSommaire du match
55689Goons2Sags3LSommaire du match
57716Spartans-Goons-
58728Goons-Outlaws-
59742Goons-Bandits-
60757Barracudas-Goons-
61773Goons-Bandits-
62784Warriors-Goons-
64808Outlaws-Goons-
65817Goons-TigersCats-
66839Scorpions-Goons-
68860Goons-Grizzlies-
69861Goons-Farmers-
70877Grizzlies-Goons-
71899Igloos-Goons-
74928Supreme-Goons-
75937Goons-Bayou-
77962Bayou-Goons-
78970Goons-Rockets-
80994Scorpions-Goons-
811015Goons-Vandals-
821025Chiwawa-Goons-
831041Goons-Spartans-
841055Rockets-Goons-
861072Goons-Warriors-
881087TigersCats-Goons-
901109Goons-Husky-
911120Goons-Spartans-
921131Sags-Goons-
941149Twins-Goons-
951169Goons-Chiwawa-
961179Thugs-Goons-
971185Goons-Scorpions-
981201Goons-Husky-
1001211Predateurs-Goons-
1011212Goons-Supreme-
1051242Vipers-Goons-
1061249Goons-Snowbirds-
1071258Goons-Supreme-
1081265Goons-Igloos-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4525
Assistance45,67116,061
Assistance PCT99.28%69.83%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
18 2684 - 89.47% 128,177$2,948,064$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,112,828$ 3,400,632$ 3,400,632$ 900,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 1,650,798$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
2,307,181$ 53 39,821$ 2,110,513$




Goons 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

Goons 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

Goons 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

Goons 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

Goons 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