Connexion

Marlies
GP: 12 | W: 7 | L: 5 | OTL: 0 | P: 14
GF: 38 | GA: 26 | PP%: 16.33% | PK%: 85.00%
DG: Jonathan Prevost | Morale : 40 | Moyenne d’équipe : 62
Prochains matchs #153 vs Condors
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Centre de jeu
Marlies
7-5-0, 14pts
1
FINAL
3 Penguins
4-7-1, 9pts
Team Stats
W1SéquenceL1
4-2-0Fiche domicile4-3-0
3-3-0Fiche domicile0-4-1
6-4-0Derniers 10 matchs3-6-1
3.17Buts par match 2.17
2.17Buts contre par match 2.92
16.33%Pourcentage en avantage numérique10.71%
85.00%Pourcentage en désavantage numérique80.43%
Firebirds
4-5-3, 11pts
2
FINAL
4 Marlies
7-5-0, 14pts
Team Stats
L2SéquenceW1
1-2-3Fiche domicile4-2-0
3-3-0Fiche domicile3-3-0
3-5-2Derniers 10 matchs6-4-0
2.42Buts par match 3.17
2.92Buts contre par match 2.17
20.59%Pourcentage en avantage numérique16.33%
83.33%Pourcentage en désavantage numérique85.00%
Marlies
7-5-0, 14pts
2025-01-15
Condors
6-6-0, 12pts
Statistiques d’équipe
W1SéquenceW1
4-2-0Fiche domicile3-3-0
3-3-0Fiche visiteur3-3-0
6-4-010 derniers matchs4-6-0
3.17Buts par match 3.00
2.17Buts contre par match 3.00
16.33%Pourcentage en avantage numérique23.53%
85.00%Pourcentage en désavantage numérique74.00%
Checkers
7-3-2, 16pts
2025-01-17
Marlies
7-5-0, 14pts
Statistiques d’équipe
W1SéquenceW1
4-2-0Fiche domicile4-2-0
3-1-2Fiche visiteur3-3-0
7-2-110 derniers matchs6-4-0
2.83Buts par match 3.17
1.75Buts contre par match 3.17
23.26%Pourcentage en avantage numérique16.33%
83.33%Pourcentage en désavantage numérique85.00%
Penguins
4-7-1, 9pts
2025-01-19
Marlies
7-5-0, 14pts
Statistiques d’équipe
L1SéquenceW1
4-3-0Fiche domicile4-2-0
0-4-1Fiche visiteur3-3-0
3-6-110 derniers matchs6-4-0
2.17Buts par match 3.17
2.92Buts contre par match 3.17
10.71%Pourcentage en avantage numérique16.33%
80.43%Pourcentage en désavantage numérique85.00%
Meneurs d'équipe
Brett KulakButs
Brett Kulak
5
Brett KulakPasses
Brett Kulak
8
Brett KulakPoints
Brett Kulak
13
Plus/Moins
Lukas Reichel
9
Victoires
Devon Levi
7
Pourcentage d’arrêts
Devon Levi
0.914

Statistiques d’équipe
Buts pour
38
3.17 GFG
Tirs pour
354
29.50 Avg
Pourcentage en avantage numérique
16.3%
8 GF
Début de zone offensive
42.0%
Buts contre
26
2.17 GAA
Tirs contre
301
25.08 Avg
Pourcentage en désavantage numérique
85.0%%
6 GA
Début de la zone défensive
39.9%
Informations de l'équipe

Directeur généralJonathan Prevost
EntraîneurEric Veilleux
DivisionAtlantic Division
ConférenceConférence EST
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison0


Informations de la formation

Équipe Pro30
Équipe Mineure18
Limite contact 48 / 70
Espoirs6


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
1Mason McTavish0XX100.007243607987867884787777718060500407502223,394,167$
2Jimmy Vesey0XX100.00794590758083888050737373768070040740322750,000$
3Aliaksei Protas0XXX96.00714095739384807960776674736050040730253888,333$
4Sonny Milano0XX100.00664087757782847540687567758373040720292750,000$
5Noah Cates0XX100.007340947581847874697266747260500407202611,137,500$
6Mattias Janmark0XX100.007363727381828971536864726983730407103331,000,000$
7Mark Jankowski0XX100.00584082728584787175686770708070040700311775,000$
8Lukas Reichel0XX100.006945917775847873687165657260500407002311,337,500$
9Ben Meyers0XX100.006940827379807066536261656760500406602721,031,250$
10Kristian Reichel0X100.00624368716370686544616264665450040630271775,000$
11Riley Sutter0X100.00674663647066646159595464605250040610261775,000$
12Cole Reinhardt0X100.00645059636866646142605460595250040600251813,333$
13Brett Kulak0X99.007140807578849076407365777285750407403211,850,000$
14Ben Hutton0X99.00574579738184797140686472698373040710321750,000$
15Ville Ottavainen0X100.00704370657265636640635970635050040650231925,000$
16Alec Regula0X98.97704466657265636340625570615150040640251775,000$
17Calle Rosen0X100.00534174656272706540655366616555040630311750,000$
18Jack Thompson0X100.00554173716464626640655766655050040630232902,500$
Rayé
1Riley Damiani0X100.00544367656066646159585651615250040580252891,667$
2Shane Bowers0X100.00544073656265636041515551605250040570262750,000$
3Oskar Olausson0X100.00604270656360576143545652615050040570232894,167$
4Sam Morton0XX100.00604070656361585650515257585250040570261750,000$
5Justin Hryckowian0XX100.00604169646460575440515153565150040550241750,000$
6Gabriel Landeskog0XX100.00111111111111111040603227,000,000$
7Tyler Tucker0X51.99747160748382686840616270685850040690252808,333$
8Cameron Crotty0X100.00654270656967656240555467605350040620261775,000$
9Luke Krys0X100.00614170656560575440515261575150040580251750,000$
10Gabriel Carlsson0X100.0011111111111111104060281725,000$
MOYENNE D’ÉQUIPE97.9660416965686866624659566161575104061
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
1Devon Levi0100.00827878788079777979807658510407602421,566,667$
2Felix Sandstrom0100.0073666665686668656669625550040660291775,000$
Rayé
MOYENNE D’ÉQUIPE100.007872727274737372737569575104071
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Eric Veilleux4349584661621CAN521525,000$


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
1Brett KulakMarlies (TOR)D125813510020202641219.23%2331526.263141344000029210%000000.8300000201
2Aliaksei ProtasMarlies (TOR)C/LW/RW12471132082936172011.11%125921.631344420000150041.18%3400000.8500000011
3Lukas ReichelMarlies (TOR)C/LW1256119009262541720.00%015312.80011215000091054.41%13600001.4300000101
4Jimmy VeseyMarlies (TOR)LW/RW12461056017354042810.00%226121.820444290000311038.10%2100000.7600000020
5Mason McTavishMarlies (TOR)C/LW1245958042393182912.90%426321.981016290003331051.60%37400000.6800000110
6Mark JankowskiMarlies (TOR)C/LW124489004192591916.00%214712.32000014000040056.25%1600001.0800000010
7Ben HuttonMarlies (TOR)D12257680991821011.11%1031926.59112741000030100%000000.4400000110
8Noah CatesMarlies (TOR)C/LW12167-34011333618222.78%522418.7312312410000160050.00%26000000.6200000000
9Alec RegulaMarlies (TOR)D120661160171181120%1824320.31000322000013000%000000.4900000011
10Sonny MilanoMarlies (TOR)LW/RW12415-3007142882314.29%221417.84011440000081026.92%2600000.4700000000
11Jack ThompsonMarlies (TOR)D1222406012961833.33%718615.5300003000015000%000000.4300000010
12Ville OttavainenMarlies (TOR)D121340403311104910.00%824020.06011537000029000%000000.3300000000
13Calle RosenMarlies (TOR)D9022400311220%0778.6000001000005000%000000.5200000000
14Kristian ReichelMarlies (TOR)RW1211290011791911.11%012810.7000000000000025.00%400000.3100000001
15Tyler TuckerMarlies (TOR)D31121806250120.00%15317.8610141000006000%000000.7500000000
16Mattias JanmarkMarlies (TOR)LW/RW12011-2603315299230%020717.25011441000000025.00%400000.1000000000
17Riley SutterMarlies (TOR)RW12011-100945120%1736.1500000000000042.86%700000.2700000000
18Ben MeyersMarlies (TOR)C/LW12011-10071210860%0847.0300000000190038.27%8100000.2400000000
19Cole ReinhardtMarlies (TOR)LW12000-160426140%1736.120000000000000%20000000000000
Statistiques d’équipe totales ou en moyenne21638661044684026229835410225610.73%85352816.34815236842500042597148.81%96500000.5900000585
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
1Devon LeviMarlies (TOR)127500.9142.15698212529000100120100
2Felix SandstromMarlies (TOR)10001.0000190001000000012000
Statistiques d’équipe totales ou en moyenne137500.9172.09717212530000101212100


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Alec RegulaMarlies (TOR)D251999-08-06USANo218 Lbs6 ft4NoNoAssign ManuallyNoNo12024-11-11FalseFalsePro & Farm775,000$0$0$No---------------------------
Aliaksei ProtasMarlies (TOR)C/LW/RW252000-01-06BLRNo225 Lbs6 ft6NoNoTrade2024-07-04NoNo32024-08-25FalseFalsePro & Farm888,333$0$0$No888,333$888,333$-------888,333$888,333$-------NoNo-------
Ben HuttonMarlies (TOR)D321992-04-20CANNo201 Lbs6 ft3NoNoN/AYesYes1FalseFalsePro & Farm750,000$0$0$No---------------------------Lien NHL
Ben MeyersMarlies (TOR)C/LW271997-11-15USANo194 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm1,031,250$0$0$No1,031,250$--------1,031,250$--------No--------
Brett KulakMarlies (TOR)D321993-01-06CANNo192 Lbs6 ft2NoNoN/AYesYes1FalseFalsePro & Farm1,850,000$0$0$No---------------------------Lien NHL
Calle RosenMarlies (TOR)D311993-02-02SWENo186 Lbs6 ft1NoNoN/AYesYes1FalseFalsePro & Farm750,000$0$0$No---------------------------Lien NHL
Cameron CrottyMarlies (TOR)D261998-05-05CANNo211 Lbs6 ft3NoNoN/ANoNo12024-08-25FalseFalsePro & Farm775,000$0$0$No---------------------------
Cole ReinhardtMarlies (TOR)LW251999-02-01CANNo215 Lbs6 ft1NoNoN/ANoNo12024-08-25FalseFalsePro & Farm813,333$0$0$No---------------------------
Devon LeviMarlies (TOR)G242000-12-27CANNo192 Lbs6 ft0NoNoTrade2024-07-04NoNo2FalseFalsePro & Farm1,566,667$0$0$No1,566,667$--------1,566,667$--------No--------
Felix SandstromMarlies (TOR)G291996-01-12SWENo196 Lbs6 ft2NoNoN/ANoNo12024-08-25FalseFalsePro & Farm775,000$0$0$No---------------------------
Gabriel CarlssonMarlies (TOR)D281997-01-02SWENo195 Lbs6 ft5NoNoN/ANoNo1FalseFalsePro & Farm725,000$0$0$No---------------------------Lien / Lien NHL
Gabriel LandeskogMarlies (TOR)LW/RW321992-11-23SWENo215 Lbs6 ft1NoNoTrade2024-07-04YesYes2FalseFalsePro & Farm7,000,000$0$0$No7,000,000$--------7,000,000$--------No--------Lien / Lien NHL
Jack ThompsonMarlies (TOR)D232001-03-19CANNo189 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm902,500$0$0$No902,500$--------902,500$--------No--------
Jimmy VeseyMarlies (TOR)LW/RW321992-05-26USANo200 Lbs6 ft2NoNoN/AYesYes2FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien NHL
Justin HryckowianMarlies (TOR)C/LW242000-02-23CANNo195 Lbs5 ft10NoNoAssign ManuallyNoNo12024-11-11FalseFalsePro & Farm750,000$0$0$No---------------------------
Kristian ReichelMarlies (TOR)RW271997-06-11CZENo188 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm775,000$0$0$No---------------------------Lien NHL
Lukas ReichelMarlies (TOR)C/LW232001-05-17DEUNo170 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm1,337,500$0$0$No---------------------------
Luke KrysMarlies (TOR)D251999-09-27USANo195 Lbs6 ft2NoNoAssign ManuallyNoNo12024-11-11FalseFalsePro & Farm750,000$0$0$No---------------------------
Mark JankowskiMarlies (TOR)C/LW311993-09-13CANNo212 Lbs6 ft4NoNoN/AYesYes12024-08-25FalseFalsePro & Farm775,000$0$0$No---------------------------Lien NHL
Mason McTavishMarlies (TOR)C/LW222002-01-30CHENo213 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm3,394,167$0$0$No3,394,167$--------3,394,167$--------No--------
Mattias JanmarkMarlies (TOR)LW/RW331991-12-08SWENo205 Lbs6 ft2NoNoN/AYesYes32024-08-25FalseFalsePro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------Lien NHL
Noah CatesMarlies (TOR)C/LW261998-02-05USANo194 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm1,137,500$0$0$No---------------------------
Oskar OlaussonMarlies (TOR)RW232001-11-10SWENo181 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm894,167$0$0$No894,167$--------894,167$--------No--------
Riley DamianiMarlies (TOR)C251999-03-20CANNo180 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm891,667$0$0$No891,667$--------891,667$--------No--------
Riley SutterMarlies (TOR)RW261998-10-25USANo211 Lbs6 ft4NoNoN/ANoNo12024-08-25FalseFalsePro & Farm775,000$0$0$No---------------------------Lien NHL
Sam MortonMarlies (TOR)C/LW261998-07-28USANo186 Lbs6 ft1NoNoAssign ManuallyNoNo12024-11-11FalseFalsePro & Farm750,000$0$0$No---------------------------
Shane BowersMarlies (TOR)C261998-07-30CANNo180 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien NHL
Sonny MilanoMarlies (TOR)LW/RW291995-05-12USANo194 Lbs6 ft0NoNoTrade2024-07-04YesYes2FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien NHL
Tyler Tucker (sur la masse salariale)Marlies (TOR)D251999-03-01CANNo204 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm808,333$0$0$No808,333$--------808,333$--------No--------
Ville OttavainenMarlies (TOR)D232001-08-12FINNo216 Lbs6 ft5NoNoAssign ManuallyNoNo12024-11-11FalseFalsePro & Farm925,000$0$0$No---------------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3026.83198 Lbs6 ft21.501,193,847$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jimmy VeseyMason McTavishAliaksei Protas40122
2Sonny MilanoNoah CatesMattias Janmark30122
3Mark JankowskiLukas ReichelKristian Reichel20122
4Cole ReinhardtBen MeyersRiley Sutter10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brett KulakBen Hutton40122
2Alec RegulaVille Ottavainen30122
3Alec RegulaJack Thompson20122
4Brett KulakBen Hutton10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Mark JankowskiLukas ReichelAliaksei Protas60122
2Sonny MilanoNoah CatesMattias Janmark40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brett KulakBen Hutton60122
2Alec RegulaVille Ottavainen40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Sonny MilanoLukas Reichel60122
2Aliaksei ProtasNoah Cates40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brett KulakBen Hutton60122
2Alec RegulaVille Ottavainen40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Aliaksei Protas60122Brett KulakBen Hutton60122
2Noah Cates40122Alec RegulaVille Ottavainen40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Mark JankowskiBen Meyers60122
2Aliaksei ProtasNoah Cates40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brett KulakBen Hutton60122
2Jack ThompsonVille Ottavainen40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jimmy VeseyMason McTavishAliaksei ProtasBrett KulakBen Hutton
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jimmy VeseyMason McTavishAliaksei ProtasBrett KulakBen Hutton
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Lukas Reichel, Mark Jankowski, Ben MeyersLukas Reichel, Mark JankowskiBen Meyers
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Alec Regula, Jack Thompson, Ben HuttonAlec RegulaJack Thompson, Brett Kulak
Tirs de pénalité
Ben Meyers, Mason McTavish, Aliaksei Protas, Noah Cates, Sonny Milano
Gardien
#1 : Devon Levi, #2 : Felix Sandstrom
Lignes d’attaque personnalisées en prolongation
Mason McTavish, Jimmy Vesey, Aliaksei Protas, Noah Cates, Sonny Milano, Mattias Janmark, Mattias Janmark, Lukas Reichel, Mark Jankowski, Ben Meyers, Kristian Reichel
Lignes de défense personnalisées en prolongation
Brett Kulak, Ben Hutton, Jack Thompson, Ville Ottavainen, Alec Regula


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
1Americans21100000532110000005231010000001-120.5005712001512926312410612043751243600.00%5260.00%019040347.15%19438350.65%8717450.00%2982062708915277
2Checkers1010000023-11010000023-10000000000000.000235001512922012410612042711422400.00%20100.00%019040347.15%19438350.65%8717450.00%2982062708915277
3Firebirds21001000853110000004221000100043141.000815230015129260124106120449168377114.29%40100.00%019040347.15%19438350.65%8717450.00%2982062708915277
4Monsters10001000431000000000001000100043121.00046100015129226124106120424410263133.33%5180.00%019040347.15%19438350.65%8717450.00%2982062708915277
5Penguins422000001293110000004043120000089-140.500122234111512921171241061204107362810118422.22%14285.71%019040347.15%19438350.65%8717450.00%2982062708915277
6Reign1010000012-11010000012-10000000000000.000123001512923612410612042661018200.00%5180.00%019040347.15%19438350.65%8717450.00%2982062708915277
7Rocket11000000615110000006150000000000021.000611170015129232124106120431714159222.22%50100.00%019040347.15%19438350.65%8717450.00%2982062708915277
Total125502000382612642000002210126130200016160140.5833866104111512923541241061204301858626249816.33%40685.00%019040347.15%19438350.65%8717450.00%2982062708915277
_Since Last GM Reset125502000382612642000002210126130200016160140.5833866104111512923541241061204301858626249816.33%40685.00%019040347.15%19438350.65%8717450.00%2982062708915277
_Vs Conference8440000025169431000001761141300000810-280.500254368111512922321241061204202595818137616.22%26484.62%019040347.15%19438350.65%8717450.00%2982062708915277
_Vs Division422000001293110000004043120000089-140.500122234111512921171241061204107362810118422.22%14285.71%019040347.15%19438350.65%8717450.00%2982062708915277

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1214W13866104354301858626211
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
125520003826
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
64200002210
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
61320001616
Derniers 10 matchs
WLOTWOTL SOWSOL
442000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
49816.33%40685.00%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
1241061204151292
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
19040347.15%19438350.65%8717450.00%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2982062708915277


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
4 - 2024-12-2311Rocket1Marlies6WSommaire du match
5 - 2024-12-2423Reign2Marlies1LSommaire du match
7 - 2024-12-2633Marlies4Monsters3WXSommaire du match
9 - 2024-12-2847Penguins0Marlies4WSommaire du match
11 - 2024-12-3059Marlies3Penguins4LSommaire du match
13 - 2025-01-0170Marlies4Firebirds3WXSommaire du match
15 - 2025-01-0383Checkers3Marlies2LSommaire du match
17 - 2025-01-0595Americans2Marlies5WSommaire du match
19 - 2025-01-07108Marlies0Americans1LSommaire du match
21 - 2025-01-09118Marlies4Penguins2WSommaire du match
23 - 2025-01-11131Marlies1Penguins3LSommaire du match
25 - 2025-01-13142Firebirds2Marlies4WSommaire du match
27 - 2025-01-15153Marlies-Condors-
29 - 2025-01-17166Checkers-Marlies-
31 - 2025-01-19179Penguins-Marlies-
32 - 2025-01-20184Marlies-Manitoba Moose-
34 - 2025-01-22201Eagles-Marlies-
36 - 2025-01-24211Marlies-Eagles-
38 - 2025-01-26225IceHogs-Marlies-
40 - 2025-01-28235Marlies-Comets-
42 - 2025-01-30249Stars-Marlies-
44 - 2025-02-01261Marlies-Wolves-
46 - 2025-02-03274Marlies-IceHogs-
48 - 2025-02-05282Marlies-Stars-
49 - 2025-02-06288Rocket-Marlies-
51 - 2025-02-08304Gulls-Marlies-
53 - 2025-02-10317Admirals-Marlies-
55 - 2025-02-12332Marlies-IceHogs-
56 - 2025-02-13342Marlies-Wranglers-
58 - 2025-02-15352Comets-Marlies-
60 - 2025-02-17369Wolves-Marlies-
62 - 2025-02-19378Marlies-Gulls-
64 - 2025-02-21391Marlies-Wolves-
66 - 2025-02-23400Bruins-Marlies-
67 - 2025-02-24415Gulls-Marlies-
69 - 2025-02-26428Marlies-Checkers-
71 - 2025-02-28439Marlies-Bruins-
73 - 2025-03-02446Marlies-Wranglers-
74 - 2025-03-03456Reign-Marlies-
76 - 2025-03-05471Griffins-Marlies-
79 - 2025-03-08490Americans-Marlies-
81 - 2025-03-10506Wranglers-Marlies-
82 - 2025-03-11517Marlies-Rocket-
84 - 2025-03-13527Marlies-Griffins-
85 - 2025-03-14538Silver Knights-Marlies-
87 - 2025-03-16551Monsters-Marlies-
89 - 2025-03-18563Marlies-Monsters-
91 - 2025-03-20577Marlies-Admirals-
92 - 2025-03-21586Silver Knights-Marlies-
93 - 2025-03-22596Marlies-Silver Knights-
95 - 2025-03-24609Senators-Marlies-
98 - 2025-03-27626Wolves-Marlies-
100 - 2025-03-29643Marlies-Manitoba Moose-
101 - 2025-03-30649Marlies-Wolf Pack-
102 - 2025-03-31658Rocket-Marlies-
104 - 2025-04-02669Marlies-Stars-
105 - 2025-04-03684Wolves-Marlies-
107 - 2025-04-05697Marlies-Admirals-
109 - 2025-04-07708Crunch-Marlies-
110 - 2025-04-08714Marlies-Reign-
112 - 2025-04-10728Comets-Marlies-
113 - 2025-04-11744Marlies-Americans-
115 - 2025-04-13755Wolf Pack-Marlies-
116 - 2025-04-14766Marlies-Firebirds-
118 - 2025-04-16778Marlies-Manitoba Moose-
119 - 2025-04-17787Manitoba Moose-Marlies-
121 - 2025-04-19797Marlies-Condors-
122 - 2025-04-20810Wolf Pack-Marlies-
124 - 2025-04-22825Bruins-Marlies-
126 - 2025-04-24837Marlies-Griffins-
128 - 2025-04-26849Admirals-Marlies-
130 - 2025-04-28863Marlies-Senators-
132 - 2025-04-30875Manitoba Moose-Marlies-
133 - 2025-05-01883Marlies-Senators-
134 - 2025-05-02897Condors-Marlies-
136 - 2025-05-04908Marlies-Eagles-
138 - 2025-05-06921Senators-Marlies-
140 - 2025-05-08938Marlies-Condors-
141 - 2025-05-09946Senators-Marlies-
143 - 2025-05-11957Marlies-Crunch-
144 - 2025-05-12966Admirals-Marlies-
146 - 2025-05-14976Marlies-Crunch-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
35 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
0$ 35,007,084$ 35,007,084$ 525,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 123 240,082$ 29,530,086$




Marlies 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

Marlies 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

Marlies 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

Marlies 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

Marlies 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