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Moose
GP: 24 | W: 15 | L: 9 | OTL: 0 | P: 30
GF: 88 | GA: 69 | PP%: 13.24% | PK%: 71.43%
DG: Eric Pilon | Morale : 58 | Moyenne d’équipe : 64
Prochains matchs #380 vs Phantoms

Centre de jeu
Moose
15-9-0, 30pts
7
2 Phantoms
11-10-2, 24pts
Team Stats
L1SéquenceSOL1
7-5-0Fiche domicile9-3-0
8-4-0Fiche domicile2-7-2
7-3-0Derniers 10 matchs5-4-1
3.67Buts par match 3.17
2.88Buts contre par match 3.48
13.24%Pourcentage en avantage numérique23.73%
71.43%Pourcentage en désavantage numérique76.92%
Silver Knights
12-7-3, 27pts
7
3 Moose
15-9-0, 30pts
Team Stats
W3SéquenceL1
7-3-1Fiche domicile7-5-0
5-4-2Fiche domicile8-4-0
7-3-0Derniers 10 matchs7-3-0
3.73Buts par match 3.67
3.41Buts contre par match 2.88
32.43%Pourcentage en avantage numérique13.24%
73.68%Pourcentage en désavantage numérique71.43%
Moose
15-9-0, 30pts
2025-10-17
Phantoms
11-10-2, 24pts
Statistiques d’équipe
L1SéquenceSOL1
7-5-0Fiche domicile9-3-0
8-4-0Fiche visiteur2-7-2
7-3-010 derniers matchs5-4-1
3.67Buts par match 3.17
2.88Buts contre par match 3.17
13.24%Pourcentage en avantage numérique23.73%
71.43%Pourcentage en désavantage numérique76.92%
Moose
15-9-0, 30pts
2025-10-19
Wranglers
15-9-1, 31pts
Statistiques d’équipe
L1SéquenceW3
7-5-0Fiche domicile7-5-0
8-4-0Fiche visiteur8-4-1
7-3-010 derniers matchs7-2-1
3.67Buts par match 3.48
2.88Buts contre par match 3.48
13.24%Pourcentage en avantage numérique24.36%
71.43%Pourcentage en désavantage numérique75.79%
Eagles
9-9-3, 21pts
2025-10-20
Moose
15-9-0, 30pts
Statistiques d’équipe
W1SéquenceL1
7-4-1Fiche domicile7-5-0
2-5-2Fiche visiteur8-4-0
5-3-210 derniers matchs7-3-0
3.43Buts par match 3.67
3.57Buts contre par match 3.67
35.38%Pourcentage en avantage numérique13.24%
77.61%Pourcentage en désavantage numérique71.43%
Meneurs d'équipe
Buts
Pavel Kraskovsky
11
Passes
Pavel Kraskovsky
11
Points
Pavel Kraskovsky
22
Plus/Moins
Albert Johansson
14
Victoires
Dylan Wells
13
Pourcentage d’arrêts
Dylan Wells
0.902

Statistiques d’équipe
Buts pour
88
3.67 GFG
Tirs pour
706
29.42 Avg
Pourcentage en avantage numérique
13.2%
9 GF
Début de zone offensive
38.7%
Buts contre
69
2.88 GAA
Tirs contre
665
27.71 Avg
Pourcentage en désavantage numérique
71.4%%
20 GA
Début de la zone défensive
39.9%
Informations de l'équipe

Directeur généralEric Pilon
EntraîneurRick Tocchet
DivisionDivision Sud-Est
ConférenceConference 1
CapitaineSami Vatanen
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance3,000
Billets de saison300


Informations de la formation

Équipe Pro32
Équipe Mineure19
Limite Contrat51 / 56
Espoirs41


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
1Daniel Sprong0XX100.0060459774727283716269706868756646646702911,200,000$
2Warren Foegele0XXX100.0066458672708088717072736767805550626703022,500,000$
3Pavel Kraskovsky0X100.0081696772707980707576706669695850646703011,200,000$
4Nils Aman0X100.0068459376697380607572688166644862646602611,300,000$
5Mason Shaw0XXX100.0073678372677489717972717168635354586602711,000,000$
6Michael Amadio0X100.0053459772717992668473677172815150636603011,700,000$
7Maxim Mamin0XXX100.0069459171746976757270747570605038646603111,300,000$
8Frederik Gauthier0X100.0059459771797585727970667063685038596503111,300,000$
9Sergey Tolchinsky0XX100.006746927166737471596971706968593865650311900,000$
10Rasmus Kupari0XXX100.006545918572707770746561705969496264650261900,000$
11Julius Nattinen0X100.0072458472707274687971627359645250446402931,000,000$
12Nikita Grebenkin (R)0X100.007050827472728370507268716250457047630231900,000$
13Sami Vatanen (C)0X100.0060459971697272684568646962816938646603511,500,000$
14Simon Despres0X100.0064459469777076704566657363655326646503531,200,000$
15Albert Johansson (R)0X100.006645917269749071456966756060456064650253900,000$
16Brandon Gormley0X100.0056459570727276694566677062715238646403411,200,000$
17Maxim Groshev (R)0X100.006948837171696967456766706345467064630243750,000$
18Chad Krys0X100.007050867068716659456063705755515426620281800,000$
Rayé
1Anthony Richard0XX98.0477467072677778707468726762685850476602931,300,000$
2Nick Sorensen0XX100.0060468872726068676466666660775846266303111,000,000$
3Sven Andrighetto0XX100.0056429968697479695767706964675430546303321,200,000$
4Lias Andersson0XX100.005945887269697266686767606066475426620282700,000$
5Michal Teply0XX100.006545897270726869607160685647456626620252750,000$
6Valentin Nussbaumer0X100.006445907266707068706865675945457026620262750,000$
7Judd Caulfield (R)0XX100.007048867072707067596667696448497026620253750,000$
8Jeremy Bracco0XX100.006145927268657063666460656062535426610293700,000$
9Brendan Guhle0X92.4367448772707373664568657354625254556502911,100,000$
10Ruben Rafkin0X100.006645737269706867456458695445456626610242750,000$
MOYENNE D’ÉQUIPE99.64654788727072776862686770636352525064
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
1Dylan Wells0100.008487837979808280818483565754556602811,000,000$
2Felix Sandstrom0100.00858371797872777373727757695070630292900,000$
Rayé
1Amir Miftakhov (R)0100.00767169757676767676767659596038620263750,000$
2Keith Petruzzelli0100.00767575797574757675767745457038610272750,000$
MOYENNE D’ÉQUIPE100.0080797578777678767677785458595063
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Rick Tocchet85817865999937CAN612100,000$


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
1Pavel KraskovskyMoose (Win)C2411112213260624159183518.64%042417.70134759000013051.58%53700101.0400000323
2Warren FoegeleMoose (Win)C/LW/RW24101020134091961192716.39%238816.20011728000011156.00%5000001.0300000301
3Daniel SprongMoose (Win)LW/RW2461117124031758174910.34%444518.5801110600001240046.43%2800000.7601000010
4Sergey TolchinskyMoose (Win)LW/RW248917107582448164616.67%437915.80202958000011037.04%2700000.9000001050
5Albert JohanssonMoose (Win)D245111614140222532102615.63%2653422.262241357000149200%000000.6000000012
6Mason ShawMoose (Win)C/LW/RW24410141019534165618527.14%237915.830331057000021062.04%10800000.7400010000
7Michael AmadioMoose (Win)C233111410002374112297.32%234715.11000000001540060.59%43900000.8111000001
8Brandon GormleyMoose (Win)D242111311801116226149.09%3447619.8400029000151000%000000.5500000000
9Simon DespresMoose (Win)D242111376015111631012.50%3543718.2100036000052010%000000.5900000100
10Brendan GuhleMoose (Win)D233912412023182881510.71%3044219.241121353000044010%000000.5400000022
11Maxim GroshevMoose (Win)D244812822037102761514.81%2247119.66213175600003000%000000.5100000101
12Maxim MaminMoose (Win)C/LW/RW247512500162742194516.67%336715.32000120001521048.00%2500100.6500000101
13Nils AmanMoose (Win)C245510180144545173011.11%437515.63000000002502048.39%43400000.5300000101
14Rasmus KupariMoose (Win)C/LW/RW244610-12014185614377.14%131613.191121655000000171.05%3800000.6301000110
15Sami VatanenMoose (Win)D242810146017152613177.69%1449520.640111354000013100%000000.4000000100
16Frederik GauthierMoose (Win)C194375404102852014.29%219110.06000020001310056.34%14200000.7300000100
17Anthony RichardMoose (Win)LW/RW13257200187258188.00%019915.37022930000001025.00%2000000.7000000011
18Nikita GrebenkinMoose (Win)RW1114519512101031210.00%013512.3500000000000040.00%1000000.7400100000
19Sven AndrighettoMoose (Win)LW/RW1914522054143127.14%01528.0500002000000025.00%400000.6500000000
20Julius NattinenMoose (Win)C11325480313116827.27%111210.2600000000001050.00%13200000.8900000100
21Chad KrysMoose (Win)D1011-100101000%01919.130000100001000%000001.0500000000
Statistiques d’équipe totales ou en moyenne432871552421441611533038370622151712.32%186709416.4291625130596000843914453.46%199400200.6813111141313
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
1Dylan WellsMoose (Win)2013600.9022.76110722515210001.0003204200
2Felix SandstromMoose (Win)72300.8813.05335001714300100420000
Statistiques d’équipe totales ou en moyenne2715900.8982.831442226866400132424200


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 Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Albert JohanssonMoose (Win)D252001-01-04SWEYes195 Lbs6 ft0NoNoProspectNoNo32026-05-07FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------Lien
Amir MiftakhovMoose (Win)G262000-04-26RUSYes181 Lbs6 ft1NoNoProspectNoNo32026-05-15FalseFalsePro & Farm750,000$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien
Anthony RichardMoose (Win)LW/RW291996-12-20CANNo176 Lbs5 ft10NoNoN/ANoNo32026-04-29FalseFalsePro & Farm1,300,000$0$0$No1,300,000$1,300,000$-------1,300,000$1,300,000$-------NoNo-------Lien
Brandon GormleyMoose (Win)D341992-02-18CANNo196 Lbs6 ft2NoNoFree AgentNoNo12024-07-24FalseFalsePro & Farm1,200,000$0$0$No---------------------------Lien
Brendan Guhle (sur la masse salariale)Moose (Win)D291997-07-29CANNo197 Lbs6 ft2NoNoN/ANoNo12025-05-28FalseFalsePro & Farm1,100,000$0$0$Yes---------------------------Lien
Chad KrysMoose (Win)D281998-04-10USANo185 Lbs6 ft0NoNoN/ANoNo12025-05-28FalseFalsePro & Farm800,000$0$0$No---------------------------Lien
Daniel SprongMoose (Win)LW/RW291997-03-17NLDNo194 Lbs6 ft0NoNoFree Agent2024-04-29NoNo12026-07-08FalseFalsePro & Farm1,200,000$0$0$No---------------------------Lien
Dylan WellsMoose (Win)G281998-01-03CANNo190 Lbs6 ft2NoNoN/ANoNo12026-04-29FalseFalsePro & Farm1,000,000$0$0$No---------------------------Lien
Felix SandstromMoose (Win)G291997-01-12SWENo191 Lbs6 ft2NoNoN/ANoNo22025-05-28FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------Lien
Frederik GauthierMoose (Win)C311995-04-26CANNo238 Lbs6 ft5NoNoFree AgentNoNo12025-07-03FalseFalsePro & Farm1,300,000$0$0$No---------------------------Lien
Jeremy BraccoMoose (Win)LW/RW291997-03-17USANo185 Lbs5 ft11NoNoN/ANoNo32026-04-29FalseFalsePro & Farm700,000$0$0$No700,000$700,000$-------700,000$700,000$-------NoNo-------Lien
Judd CaulfieldMoose (Win)LW/RW252001-03-19USAYes207 Lbs6 ft3NoNoProspectNoNo32026-05-15FalseFalsePro & Farm750,000$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien
Julius NattinenMoose (Win)C291997-01-14FINNo192 Lbs6 ft2NoNoN/ANoNo32026-04-29FalseFalsePro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------Lien
Keith PetruzzelliMoose (Win)G271999-02-09USANo185 Lbs6 ft5NoNoProspectNoNo22025-05-07FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien
Lias AnderssonMoose (Win)LW/RW281998-10-13SWENo185 Lbs6 ft1NoNoN/ANoNo22026-04-29FalseFalsePro & Farm700,000$0$0$No700,000$--------700,000$--------No--------Lien
Mason ShawMoose (Win)C/LW/RW271998-11-03CANNo184 Lbs5 ft10NoNoN/ANoNo12026-04-29FalseFalsePro & Farm1,000,000$0$0$No---------------------------Lien
Maxim GroshevMoose (Win)D242001-12-14RUSYes198 Lbs6 ft2NoNoProspectNoNo32026-05-15FalseFalsePro & Farm750,000$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien
Maxim MaminMoose (Win)C/LW/RW311995-01-13RUSNo209 Lbs6 ft2NoNoFree AgentNoNo12025-07-03FalseFalsePro & Farm1,300,000$0$0$No---------------------------Lien
Michael AmadioMoose (Win)C301996-05-13CANNo204 Lbs6 ft1NoNoWaiver2024-08-18NoNo12025-05-28FalseFalsePro & Farm1,700,000$0$0$No---------------------------Lien
Michal TeplyMoose (Win)LW/RW252001-05-27CZENo187 Lbs6 ft3NoNoProspectNoNo22025-05-07FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien
Nick SorensenMoose (Win)LW/RW311994-10-23DNKNo182 Lbs6 ft1NoNoN/ANoNo12024-04-29FalseFalsePro & Farm1,000,000$0$0$No---------------------------Lien
Nikita GrebenkinMoose (Win)RW232003-05-02RUSYes210 Lbs6 ft2NoNoFree AgentNoNo12026-05-07FalseFalsePro & Farm900,000$0$0$No---------900,000$900,000$----------------Lien
Nils AmanMoose (Win)C262000-02-07SWENo179 Lbs6 ft2NoNoFree AgentNoNo12025-05-28FalseFalsePro & Farm1,300,000$0$0$No---------------------------Lien
Pavel KraskovskyMoose (Win)C301996-09-11RUSNo185 Lbs6 ft4NoNoN/ANoNo12026-04-29FalseFalsePro & Farm1,200,000$0$0$No---------------------------Lien
Rasmus KupariMoose (Win)C/LW/RW262000-03-15FINNo201 Lbs6 ft2NoNoProspectNoNo12024-04-29FalseFalsePro & Farm900,000$0$0$No---------------------------Lien
Ruben RafkinMoose (Win)D242002-01-08FINNo190 Lbs5 ft11NoNoProspectNoNo22025-05-07FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien
Sami VatanenMoose (Win)D351991-06-03FINNo185 Lbs5 ft10NoNoFree AgentNoNo12024-07-22FalseFalsePro & Farm1,500,000$0$0$No---------------------------Lien
Sergey TolchinskyMoose (Win)LW/RW311995-02-03RUSNo163 Lbs5 ft9NoNoFree Agent2025-10-28NoNo12026-07-08FalseFalsePro & Farm900,000$0$0$No---------------------------Lien
Simon DespresMoose (Win)D351991-07-27CANNo218 Lbs6 ft4NoNoFree AgentNoNo32026-07-06FalseFalsePro & Farm1,200,000$0$0$No1,200,000$1,200,000$-------1,200,000$1,200,000$-------NoNo-------Lien
Sven AndrighettoMoose (Win)LW/RW331993-03-21CHENo187 Lbs5 ft10NoNoFree Agent2024-06-25NoNo22025-07-11FalseFalsePro & Farm1,200,000$0$0$No1,200,000$--------1,200,000$--------No--------Lien
Valentin NussbaumerMoose (Win)C262000-09-25SUINo165 Lbs5 ft11NoNoProspectNoNo22025-05-07FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien
Warren FoegeleMoose (Win)C/LW/RW301996-04-01CANNo198 Lbs6 ft2NoNoWaiver2025-12-10NoNo22025-05-28FalseFalsePro & Farm2,500,000$0$0$No2,500,000$--------2,500,000$--------No--------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3228.53192 Lbs6 ft11.751,060,938$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Sergey TolchinskyPavel KraskovskyWarren Foegele30023
2Mason ShawJulius NattinenDaniel Sprong25023
3Maxim MaminNils AmanRasmus Kupari25023
4Nikita GrebenkinMichael AmadioFrederik Gauthier20032
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Sami VatanenAlbert Johansson35041
2Brandon GormleyMaxim Groshev35041
3Simon DespresChad Krys30041
4Sami VatanenAlbert Johansson0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Daniel SprongPavel KraskovskyWarren Foegele50005
2Rasmus KupariMason ShawSergey Tolchinsky50005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Albert JohanssonMaxim Groshev50014
2Sami VatanenChad Krys50032
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Nils AmanMaxim Mamin50050
2Michael AmadioDaniel Sprong50050
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Albert JohanssonChad Krys50050
2Simon DespresBrandon Gormley50050
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Nils Aman50050Albert JohanssonChad Krys50050
2Maxim Mamin50050Simon DespresBrandon Gormley50050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Pavel KraskovskyDaniel Sprong50023
2Nils AmanRasmus Kupari50023
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Sami VatanenMaxim Groshev50041
2Albert JohanssonSimon Despres50041
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Daniel SprongPavel KraskovskyRasmus KupariAlbert JohanssonMaxim Groshev
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Maxim MaminNils AmanMason ShawAlbert JohanssonSimon Despres
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Daniel Sprong, Nikita Grebenkin, Nils AmanDaniel Sprong, Pavel KraskovskyMaxim Mamin
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Sami Vatanen, Albert Johansson, Simon DespresAlbert JohanssonAlbert Johansson, Simon Despres
Tirs de pénalité
Michael Amadio, Daniel Sprong, Rasmus Kupari, Nikita Grebenkin, Pavel Kraskovsky
Gardien
#1 : Dylan Wells, #2 : Felix Sandstrom


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
1Americans22000000954220000009540000000000041.00091625002633281502542292224561717233133.33%6266.67%039077050.65%45079356.75%22642553.18%560384565180319160
2Bears1010000034-1000000000001010000034-100.000358002633281292542292224264914100.00%220.00%039077050.65%45079356.75%22642553.18%560384565180319160
3BruinsF4220000013121211000006512110000077040.50013233600263328112325422922241133927691200.00%9188.89%039077050.65%45079356.75%22642553.18%560384565180319160
4Comets220000001349110000007161100000063341.000132437002633281652542292224611724279444.44%11281.82%039077050.65%45079356.75%22642553.18%560384565180319160
5Condors11000000422110000004220000000000021.0004812002633281432542292224317018300.00%000%039077050.65%45079356.75%22642553.18%560384565180319160
6Crunch2110000034-1110000003211010000002-220.5003580026332814825422922246216628600.00%3166.67%039077050.65%45079356.75%22642553.18%560384565180319160
7Firebirds2110000078-11010000024-21100000054120.500713201026332816025422922244810821600.00%4175.00%039077050.65%45079356.75%22642553.18%560384565180319160
8Gulls1010000024-21010000024-20000000000000.000235002633281132542292224378121611100.00%6183.33%039077050.65%45079356.75%22642553.18%560384565180319160
9Islanders20100010810-20000000000020100010810-220.5008132100263328171254229222458814319111.11%7357.14%039077050.65%45079356.75%22642553.18%560384565180319160
10Marlies211000006511010000034-11100000031220.5006101600263328154254229222444208275240.00%4250.00%039077050.65%45079356.75%22642553.18%560384565180319160
11PenguinsF22000000826000000000002200000082641.0008132101263328172254229222449201827700.00%9188.89%039077050.65%45079356.75%22642553.18%560384565180319160
12Phantoms11000000725000000000001100000072521.00071320002633281282542292224318612200.00%3166.67%039077050.65%45079356.75%22642553.18%560384565180319160
13Silver Knights1010000037-41010000037-40000000000000.0003580026332812425422922241941010200.00%4325.00%039077050.65%45079356.75%22642553.18%560384565180319160
14Wolf Pack11000000202110000002020000000000021.00024601263328126254229222430847200.00%20100.00%039077050.65%45079356.75%22642553.18%560384565180319160
Total241490001088691912750000041347127400010473512300.62588155243122633281706254229222466518616333068913.24%702071.43%039077050.65%45079356.75%22642553.18%560384565180319160
_Since Last GM Reset241490001088691912750000041347127400010473512300.62588155243122633281706254229222466518616333068913.24%702071.43%039077050.65%45079356.75%22642553.18%560384565180319160
_Vs Conference211370001079562396300000322111127400010473512280.66779139218122633281626254229222457816714128662812.90%601673.33%039077050.65%45079356.75%22642553.18%560384565180319160

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2430L18815524370666518616333012
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
2414900108869
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
127500004134
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
127400104735
Derniers 10 matchs
WLOTWOTL SOWSOL
630010
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
68913.24%702071.43%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
25422922242633281
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
39077050.65%45079356.75%22642553.18%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
560384565180319160


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
1 - 2025-08-285Moose1PenguinsF0WSommaire du match
2 - 2025-08-2917BruinsF3Moose2LSommaire du match
4 - 2025-08-3133Americans2Moose4WSommaire du match
6 - 2025-09-0245Moose0Crunch2LSommaire du match
7 - 2025-09-0362Moose3BruinsF2WSommaire du match
9 - 2025-09-0577Comets1Moose7WSommaire du match
12 - 2025-09-08100Crunch2Moose3WSommaire du match
14 - 2025-09-10115Moose7PenguinsF2WSommaire du match
17 - 2025-09-13131Wolf Pack0Moose2WSommaire du match
19 - 2025-09-15154Firebirds4Moose2LSommaire du match
21 - 2025-09-17161Moose5Firebirds4WSommaire du match
23 - 2025-09-19180Moose3Bears4LSommaire du match
25 - 2025-09-21187Moose4BruinsF5LSommaire du match
27 - 2025-09-23203Marlies4Moose3LSommaire du match
29 - 2025-09-25224Moose2Islanders5LSommaire du match
30 - 2025-09-26233Moose6Comets3WSommaire du match
32 - 2025-09-28243Gulls4Moose2LSommaire du match
35 - 2025-10-01264BruinsF2Moose4WSommaire du match
39 - 2025-10-05292Condors2Moose4WSommaire du match
41 - 2025-10-07306Moose3Marlies1WSommaire du match
43 - 2025-10-09321Americans3Moose5WSommaire du match
45 - 2025-10-11335Moose6Islanders5WXXSommaire du match
47 - 2025-10-13350Moose7Phantoms2WSommaire du match
49 - 2025-10-15363Silver Knights7Moose3LSommaire du match
51 - 2025-10-17380Moose-Phantoms-
53 - 2025-10-19391Moose-Wranglers-
54 - 2025-10-20398Eagles-Moose-
57 - 2025-10-23425Checkers-Moose-
59 - 2025-10-25442Moose-Condors-
61 - 2025-10-27454Moose-Comets-
62 - 2025-10-28461Marlies-Moose-
65 - 2025-10-31480Moose-Admirals-
66 - 2025-11-01492Checkers-Moose-
68 - 2025-11-03509Moose-Icehogs-
70 - 2025-11-05525Crunch-Moose-
73 - 2025-11-08544Moose-Barracuda-
75 - 2025-11-10558Thunderbirds-Moose-
77 - 2025-11-12576Moose-Wolves-
79 - 2025-11-14588Griffins-Moose-
81 - 2025-11-16605Moose-Marlies-
83 - 2025-11-18621Iowa Wild-Moose-
85 - 2025-11-20636Moose-Bears-
87 - 2025-11-22653Comets-Moose-
89 - 2025-11-24665Moose-Checkers-
91 - 2025-11-26679Moose-BruinsF-
92 - 2025-11-27686Monsters-Moose-
94 - 2025-11-29702Moose-Canucks-
97 - 2025-12-02718Wolves-Moose-
99 - 2025-12-04731Moose-Firebirds-
101 - 2025-12-06750Comets-Moose-
103 - 2025-12-08762Moose-Roadrunners-
106 - 2025-12-11781Moose-Rocket-
107 - 2025-12-12787Wolf Pack-Moose-
110 - 2025-12-15810Moose-Rocket-
111 - 2025-12-16817Wolves-Moose-
114 - 2025-12-19843Firebirds-Moose-
116 - 2025-12-21857Moose-Reign-
118 - 2025-12-23871Moose-Americans-
119 - 2025-12-24880SenatorsF-Moose-
122 - 2025-12-27907SenatorsF-Moose-
124 - 2025-12-29917Moose-Crunch-
128 - 2026-01-02944Moose-Wolf Pack-
129 - 2026-01-03950Gulls-Moose-
131 - 2026-01-05973Moose-Wolf Pack-
133 - 2026-01-07982StarsF-Moose-
136 - 2026-01-101007Bears-Moose-
138 - 2026-01-121021Moose-Americans-
140 - 2026-01-141039Bears-Moose-
142 - 2026-01-161050Moose-Eagles-
145 - 2026-01-191071Islanders-Moose-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
148 - 2026-01-221091Moose-Wolves-
149 - 2026-01-231103Phantoms-Moose-
154 - 2026-01-281134Phantoms-Moose-
156 - 2026-01-301148Moose-PenguinsF-
158 - 2026-02-011166PenguinsF-Moose-
160 - 2026-02-031179Moose-PenguinsF-
163 - 2026-02-061198Islanders-Moose-
167 - 2026-02-101226Wolf Pack-Moose-
170 - 2026-02-131243Moose-SenatorsF-
172 - 2026-02-151258Rocket-Moose-
174 - 2026-02-171270Moose-Checkers-
175 - 2026-02-181283Moose-SenatorsF-
178 - 2026-02-211300PenguinsF-Moose-
182 - 2026-02-251328Rocket-Moose-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4530
Assistance24,00012,000
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
30 3000 - 100.00% 178,800$2,145,600$3000125

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
910,907$ 3,285,000$ 3,285,000$ 100,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 884,272$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
5,364,000$ 135 18,397$ 2,483,595$




Moose 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

Moose 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

Moose 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

Moose 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

Moose 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