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Monsters
GP: 7 | W: 2 | L: 3 | OTL: 2 | P: 6
GF: 21 | GA: 29 | PP%: 20.00% | PK%: 64.71%
DG: Jean Francois Langelier | Morale : 46 | Moyenne d’équipe : 64
Prochains matchs #134 vs Icehogs
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Centre de jeu
Wranglers
6-1-0, 12pts
2
FINAL
1 Monsters
2-3-2, 6pts
Team Stats
W1SéquenceW1
3-1-0Fiche domicile1-1-2
3-0-0Fiche domicile1-2-0
6-1-0Derniers 10 matchs2-3-2
4.14Buts par match 3.00
3.14Buts contre par match 4.14
18.18%Pourcentage en avantage numérique20.00%
94.44%Pourcentage en désavantage numérique64.71%
Monsters
2-3-2, 6pts
5
FINAL
3 Roadrunners
3-4-2, 8pts
Team Stats
W1SéquenceL1
1-1-2Fiche domicile2-2-0
1-2-0Fiche domicile1-2-2
2-3-2Derniers 10 matchs3-4-2
3.00Buts par match 2.89
4.14Buts contre par match 3.33
20.00%Pourcentage en avantage numérique25.00%
64.71%Pourcentage en désavantage numérique75.00%
Icehogs
4-2-2, 10pts
2024-09-19
Monsters
2-3-2, 6pts
Statistiques d’équipe
SOL1SéquenceW1
2-1-1Fiche domicile1-1-2
2-1-1Fiche visiteur1-2-0
4-2-210 derniers matchs2-3-2
3.75Buts par match 3.00
3.13Buts contre par match 3.00
18.52%Pourcentage en avantage numérique20.00%
88.00%Pourcentage en désavantage numérique64.71%
Monsters
2-3-2, 6pts
2024-09-22
Gulls
3-4-1, 7pts
Statistiques d’équipe
W1SéquenceL1
1-1-2Fiche domicile2-1-1
1-2-0Fiche visiteur1-3-0
2-3-210 derniers matchs3-4-1
3.00Buts par match 3.00
4.14Buts contre par match 3.00
20.00%Pourcentage en avantage numérique13.33%
64.71%Pourcentage en désavantage numérique69.57%
Griffins
6-1-1, 13pts
2024-09-24
Monsters
2-3-2, 6pts
Statistiques d’équipe
W6SéquenceW1
3-1-0Fiche domicile1-1-2
3-0-1Fiche visiteur1-2-0
6-1-110 derniers matchs2-3-2
3.63Buts par match 3.00
2.25Buts contre par match 3.00
25.00%Pourcentage en avantage numérique20.00%
84.38%Pourcentage en désavantage numérique64.71%
Meneurs d'équipe
Buts
Sergey Tolchinsky
6
Passes
Joseph Veleno
6
Points
Joseph Veleno
8
Plus/Moins
Vyacheslav Leshchenko
4
Victoires
Malcolm Subban
1
Pourcentage d’arrêts
Jaroslav Janus
0.86

Statistiques d’équipe
Buts pour
21
3.00 GFG
Tirs pour
234
33.43 Avg
Pourcentage en avantage numérique
20.0%
4 GF
Début de zone offensive
45.1%
Buts contre
29
4.14 GAA
Tirs contre
171
24.43 Avg
Pourcentage en désavantage numérique
64.7%%
6 GA
Début de la zone défensive
32.5%
Informations de l'équipe

Directeur généralJean Francois Langelier
EntraîneurKen Hitchcock
DivisionDivision Centrale
ConférenceConference 2
CapitaineVictor Mete
Assistant #1Joseph Veleno
Assistant #2Jack Mcbain


Informations de l’aréna

Capacité3,000
Assistance2,041
Billets de saison300


Informations de la formation

Équipe Pro33
Équipe Mineure18
Limite contact 51 / 56
Espoirs16


Historique d'équipe

Saison actuelle2-3-2 (6PTS)
Historique49-35-11 (0.516%)
Apparitions en séries éliminatoires 1
Historique en séries éliminatoires (W-L)1-4
Coupe Stanley0


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
1Jack Mcbain (A)X100.007966877373789174737272766859486848670242900,000$
2Jacob PetersonXX100.0060459376718087747671727271625268486702511,700,000$
3Joseph Veleno (A)X100.007445877372769274737373776564486848670242900,000$
4Sergey TolchinskyXX100.0071478372657375756072757167686254486702922,000,000$
5Steven LorentzXX100.0064459474737987727170707068665358486702811,700,000$
6Sam LaffertyXX100.0074468372707486727374727270645256486702922,000,000$
7Dominic ToninatoXX100.0071458772737479726975687166604853486603021,725,000$
8Vyacheslav LeshchenkoXX100.0072458375677576716770716662645754486602921,700,000$
9Lukas SedlakXX100.0075588169726778766871717169645750486603121,700,000$
10Tomas NosekX100.0063509172737477717868687266715550486603221,700,000$
11Phillip DigiuseppeXX100.0062459470717484706169696967675253486503021,300,000$
12Andrew DesjardinsX100.0069598567706877677966666862715625486303821,100,000$
13Victor Mete (C)X100.006245937667768673457662765673496048670261900,000$
14Sam Malinski (R)X100.006645898169727376457471726545456048660261900,000$
15Kaedan Korczak (R)X100.007145897672767376457466736045457048660233900,000$
16Sebastian Aho (DEF)X100.0066458275677490744573677459595254386602811,700,000$
17Victor AntipinX100.0061469472686981704571677265654850486503131,500,000$
18Alexis BinnerX100.0063488476766873714566666957605264486402521,000,000$
Rayé
1Linden VeyXX100.0063458971697481696369686665615247436403321,250,000$
2Teemu PulkkinenXX100.0057449671697173726069717166574947436303221,100,000$
3Seth GriffithXX100.0060449170697177696368687066574750436303121,100,000$
4Michal RepikXX100.0060439370706576686666676665564734436203521,100,000$
5Dan SextonXX100.0061439770667169676466666865544925436203721,100,000$
6Jordan SchroederX100.005543976967696867656665686459504243610331900,000$
7Danick PaquetteX100.0062488868736965646361606260454542435903421,000,000$
8Kevin GravelX100.006045957074677069456664716257464643630321800,000$
9Tyler CumaX100.0061458773716764704571627362515138436303411,250,000$
10Matt BartkowskiX100.0063499268706866674565627262645230436303611,250,000$
11Nico Gross (R)X100.006945807269707069456362735645457043620243750,000$
12Mark KaticX100.0059439670697177694568656862484634436203521,000,000$
MOYENNE D’ÉQUIPE100.00654789727072777160696871645950514665
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
1Malcolm Subban100.008079778081758379808282677053446703011,600,000$
2Jaroslav Janus100.007678777677788280818177465138496303421,050,000$
Rayé
1Brent Moran100.00798468817667857070777546475746600281750,000$
MOYENNE D’ÉQUIPE100.0078807479787383767780785356494663
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ken Hitchcock70778461999911CAN744100,000$


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
1Joseph VelenoMonsters (Clb)C7268-10069226119.09%013819.81022215000191058.66%17900001.1500000001
2Sergey TolchinskyMonsters (Clb)LW/RW7628-24011103131719.35%112517.89213815000000075.00%800011.2800000100
3Jacob PetersonMonsters (Clb)LW/RW7257-20048255138.00%112918.56134515000001058.33%1200001.0800000001
4Dominic ToninatoMonsters (Clb)LW/RW7134-420671031410.00%211816.89000012000010062.50%800000.6800000100
5Vyacheslav LeshchenkoMonsters (Clb)LW/RW7224420154164812.50%09213.1900000000000050.00%400000.8700000010
6Victor MeteMonsters (Clb)D70440202913120%415422.11011716000012000%000000.5200000010
7Kaedan KorczakMonsters (Clb)D7134-5609592311.11%815221.7411241600008000%000000.5300000000
8Phillip DigiuseppeMonsters (Clb)LW/RW722410053931322.22%110014.4200004000000171.43%700000.7900000100
9Sam MalinskiMonsters (Clb)D7033-500767580%615321.99000514000012000%000000.3900000000
10Tomas NosekMonsters (Clb)C72134206162021310.00%110314.81000000000120051.56%12800000.5800000000
11Victor AntipinMonsters (Clb)D7033040428050%612517.910003200000000%000000.4800000000
12Jack McbainMonsters (Clb)C7022-7201216137100%213819.800003160000100050.89%16900000.2900000000
13Alexis BinnerMonsters (Clb)D7022-1206104120%1012718.200000100017000%000000.3100000000
14Sam LaffertyMonsters (Clb)LW/RW7202-6201121661712.50%212417.84000316000000150.00%600000.3200000000
15Steven LorentzMonsters (Clb)LW/RW7101-1001470914.29%1669.48000000001120025.00%400000.3000000000
16Sebastian Aho (DEF)Monsters (Clb)D70110607711470%813218.9600071200007000%000000.1500000000
17Lukas SedlakMonsters (Clb)LW/RW7000-100549320%0547.7100000000000060.00%50000000000000
18Andrew DesjardinsMonsters (Clb)C7000-220454110%0557.8800000000000060.00%650000000000000
Statistiques d’équipe totales ou en moyenne126213960-28360121127234561558.97%53209416.624812471640003952255.13%59500010.5700000322
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
1Jaroslav JanusMonsters (Clb)31010.8603.22149008570000025000
2Malcolm SubbanMonsters (Clb)51310.8164.5527700211140000052000
Statistiques d’équipe totales ou en moyenne82320.8304.084270029171000077000


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 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 Type Salaire actuel Plafond salarial Non Activé Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Non-échange Année 2Non-échange Année 3Non-échange Année 4Non-échange Année 5Non-échange Année 6Non-échange Année 7Non-échange Année 8Non-échange Année 9Non-échange Année 10Lien
Alexis BinnerMonsters (Clb)D251998-12-03No212 Lbs6 ft3NoNoN/ANoNo2Pro & Farm1,000,000$0$0$No1,000,000$--------No--------Lien
Andrew DesjardinsMonsters (Clb)C381986-07-27No196 Lbs6 ft0NoNoN/ANoNo2Pro & Farm1,100,000$0$0$No1,100,000$--------No--------Lien
Brent MoranMonsters (Clb)G281996-07-05No195 Lbs6 ft4NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Dan SextonMonsters (Clb)LW/RW371987-04-29No156 Lbs5 ft10NoNoN/ANoNo2Pro & Farm1,100,000$0$0$No1,100,000$--------No--------Lien
Danick PaquetteMonsters (Clb)C341990-07-17No217 Lbs6 ft0NoNoN/ANoNo2Pro & Farm1,000,000$0$0$No1,000,000$--------No--------Lien
Dominic ToninatoMonsters (Clb)LW/RW301994-03-09No201 Lbs6 ft2NoNoFree AgentNoNo22024-07-10Pro & Farm1,725,000$0$0$No1,725,000$--------No--------Lien
Jack McbainMonsters (Clb)C242000-01-06No201 Lbs6 ft3NoNoN/ANoNo2Pro & Farm900,000$0$0$No900,000$--------No--------Lien
Jacob PetersonMonsters (Clb)LW/RW251999-07-19No170 Lbs6 ft1NoNoN/ANoNo1Pro & Farm1,700,000$0$0$No------------------Lien
Jaroslav JanusMonsters (Clb)G341989-09-21No191 Lbs6 ft0NoNoN/ANoNo2Pro & Farm1,050,000$0$0$No1,050,000$--------No--------Lien
Jordan SchroederMonsters (Clb)C331990-09-29No174 Lbs5 ft8NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------Lien
Joseph VelenoMonsters (Clb)C242000-01-13No203 Lbs6 ft1NoNoN/ANoNo2Pro & Farm900,000$0$0$No900,000$--------No--------Lien
Kaedan KorczakMonsters (Clb)D232001-01-29Yes201 Lbs6 ft3NoNoTrade (Prospect)NoNo32024-04-29Pro & Farm900,000$0$0$No900,000$900,000$-------NoNo-------Lien
Kevin GravelMonsters (Clb)D321992-03-06No205 Lbs6 ft4NoNoFree AgentNoNo12024-07-22Pro & Farm800,000$0$0$No------------------Lien
Linden VeyMonsters (Clb)LW/RW331991-07-17No194 Lbs5 ft8NoNoN/ANoNo2Pro & Farm1,250,000$0$0$No1,250,000$--------No--------Lien
Lukas SedlakMonsters (Clb)LW/RW311993-02-25No205 Lbs6 ft0NoNoFree AgentNoNo22024-07-10Pro & Farm1,700,000$0$0$No1,700,000$--------No--------Lien
Malcolm SubbanMonsters (Clb)G301993-12-21No215 Lbs6 ft2NoNoTrade2024-01-13NoNo1Pro & Farm1,600,000$0$0$No------------------Lien
Mark KaticMonsters (Clb)D351989-05-09No180 Lbs5 ft10NoNoTrade2024-01-27NoNo2Pro & Farm1,000,000$0$0$No1,000,000$--------No--------Lien
Matt BartkowskiMonsters (Clb)D361988-06-04No192 Lbs6 ft1NoNoN/ANoNo1Pro & Farm1,250,000$0$0$No------------------Lien
Michal RepikMonsters (Clb)LW/RW351988-12-31No191 Lbs5 ft10NoNoN/ANoNo2Pro & Farm1,100,000$0$0$No1,100,000$--------No--------Lien
Nico GrossMonsters (Clb)D242000-01-26Yes183 Lbs6 ft1NoNoTrade (Prospect)NoNo32024-06-18Pro & Farm750,000$0$0$No750,000$750,000$-------NoNo-------
Phillip DigiuseppeMonsters (Clb)LW/RW301993-10-09No193 Lbs6 ft0NoNoFree AgentNoNo22024-07-12Pro & Farm1,300,000$0$0$No1,300,000$--------No--------Lien
Sam LaffertyMonsters (Clb)LW/RW291995-03-06No195 Lbs6 ft2NoNoN/ANoNo22024-04-29Pro & Farm2,000,000$0$0$No2,000,000$--------No--------Lien
Sam MalinskiMonsters (Clb)D261998-07-27Yes190 Lbs5 ft11NoNoTrade2024-06-20NoNo12024-06-20Pro & Farm900,000$0$0$No------------------Lien
Sebastian Aho (DEF)Monsters (Clb)D281996-02-17No177 Lbs5 ft11NoNoTrade2024-01-27NoNo1Pro & Farm1,700,000$0$0$No------------------Lien
Sergey TolchinskyMonsters (Clb)LW/RW291995-02-03No156 Lbs5 ft8NoNoN/ANoNo22024-04-29Pro & Farm2,000,000$0$0$No2,000,000$--------No--------Lien
Seth GriffithMonsters (Clb)LW/RW311993-01-04No190 Lbs5 ft9NoNoN/ANoNo2Pro & Farm1,100,000$0$0$No1,100,000$--------No--------Lien
Steven LorentzMonsters (Clb)LW/RW281996-04-13No192 Lbs6 ft3NoNoN/ANoNo1Pro & Farm1,700,000$0$0$No------------------Lien
Teemu PulkkinenMonsters (Clb)LW/RW321992-01-02No187 Lbs5 ft10NoNoN/ANoNo2Pro & Farm1,100,000$0$0$No1,100,000$--------No--------Lien
Tomas NosekMonsters (Clb)C321992-09-01No205 Lbs6 ft3NoNoFree AgentNoNo22024-07-07Pro & Farm1,700,000$0$0$No1,700,000$--------No--------Lien
Tyler CumaMonsters (Clb)D341990-01-19 00:01:24No187 Lbs6 ft2NoNoN/ANoNo1Pro & Farm1,250,000$0$0$No------------------Lien
Victor AntipinMonsters (Clb)D311992-12-06No171 Lbs5 ft10NoNoFree AgentNoNo32024-07-12Pro & Farm1,500,000$0$0$No1,500,000$1,500,000$-------NoNo-------Lien
Victor MeteMonsters (Clb)D261998-06-07No187 Lbs5 ft9NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------Lien
Vyacheslav LeshchenkoMonsters (Clb)LW/RW291995-04-24No160 Lbs6 ft0NoNoN/ANoNo22024-04-29Pro & Farm1,700,000$0$0$No1,700,000$--------No--------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3330.18190 Lbs6 ft01.761,252,273$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Phillip DigiuseppeJack McbainSam Lafferty30014
2Jacob PetersonJoseph VelenoSergey Tolchinsky30014
3Vyacheslav LeshchenkoTomas NosekDominic Toninato25023
4Lukas SedlakAndrew DesjardinsSteven Lorentz15023
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kaedan KorczakSam Malinski35023
2Victor MeteSebastian Aho (DEF)33023
3Victor AntipinAlexis Binner32032
4Victor MeteSam Malinski0032
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Phillip DigiuseppeJack McbainSam Lafferty50005
2Jacob PetersonJoseph VelenoSergey Tolchinsky50005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Victor MeteKaedan Korczak50005
2Sam MalinskiSebastian Aho (DEF)50005
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Tomas NosekSteven Lorentz50050
2Joseph VelenoJack Mcbain50050
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Victor MeteKaedan Korczak50050
2Sam MalinskiSebastian Aho (DEF)50050
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Tomas Nosek50050Victor MeteKaedan Korczak50050
2Steven Lorentz50050Sam MalinskiSebastian Aho (DEF)50050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jack McbainSam Lafferty50023
2Joseph VelenoJacob Peterson50023
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kaedan KorczakSam Malinski50032
2Victor MeteSebastian Aho (DEF)50032
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Joseph VelenoJack McbainSam LaffertyVictor MeteKaedan Korczak
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Joseph VelenoJack McbainSam LaffertyVictor MeteKaedan Korczak
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Vyacheslav Leshchenko, Dominic Toninato, Tomas NosekVyacheslav Leshchenko, Dominic ToninatoTomas Nosek
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Victor Antipin, Alexis Binner, Kaedan KorczakVictor AntipinAlexis Binner, Kaedan Korczak
Tirs de pénalité
Steven Lorentz, Jack Mcbain, Sam Lafferty, Jacob Peterson, Joseph Veleno
Gardien
#1 : Malcolm Subban, #2 : Jaroslav Janus, #3 : 0


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
1Gulls1010000037-4000000000001010000037-400.0003580085712486796723611415000%2150.00%014826555.85%10619155.50%7413256.06%175123160509146
2Icehogs1010000024-2000000000001010000024-200.000246008571398679672276614300.00%3166.67%014826555.85%10619155.50%7413256.06%175123160509146
3Iowa Wild1010000025-31010000025-30000000000000.000235008571378679672247424400.00%2150.00%014826555.85%10619155.50%7413256.06%175123160509146
4Roadrunners11000000532000000000001100000053221.0005101500857132867967219142162150.00%10100.00%014826555.85%10619155.50%7413256.06%175123160509146
5Silver Knights1000010045-11000010045-10000000000010.50048120085713286796722240155240.00%000%014826555.85%10619155.50%7413256.06%175123160509146
6StarsF10001000431100010004310000000000021.00047110085713386796722510142011100.00%6266.67%014826555.85%10619155.50%7413256.06%175123160509146
7Wranglers1000010012-11000010012-10000000000010.500123008571378679672181617500.00%3166.67%014826555.85%10619155.50%7413256.06%175123160509146
Total713012002129-8401012001115-4312000001014-460.4292139600085712348679672171533612120420.00%17664.71%014826555.85%10619155.50%7413256.06%175123160509146
_Since Last GM Reset713012002129-8401012001115-4312000001014-460.4292139600085712348679672171533612120420.00%17664.71%014826555.85%10619155.50%7413256.06%175123160509146
_Vs Conference713012002129-8401012001115-4312000001014-460.4292139600085712348679672171533612120420.00%17664.71%014826555.85%10619155.50%7413256.06%175123160509146
_Vs Division401000001315-22000000068-22010000077000.00013243700857114186796729537267410220.00%12466.67%014826555.85%10619155.50%7413256.06%175123160509146

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
76W1213960234171533612100
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
71312002129
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
40112001115
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
31200001014
Derniers 10 matchs
WLOTWOTL SOWSOL
131200
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
20420.00%17664.71%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
86796728571
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
14826555.85%10619155.50%7413256.06%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
175123160509146


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 - 2024-09-021Iowa Wild5Monsters2BLSommaire du match
5 - 2024-09-0630Monsters3Gulls7ALSommaire du match
7 - 2024-09-0844StarsF3Monsters4BWXSommaire du match
10 - 2024-09-1167Silver Knights5Monsters4BLXSommaire du match
12 - 2024-09-1386Monsters2Icehogs4ALSommaire du match
13 - 2024-09-1497Wranglers2Monsters1BLXSommaire du match
17 - 2024-09-18123Monsters5Roadrunners3AWSommaire du match
18 - 2024-09-19134Icehogs-Monsters-
21 - 2024-09-22153Monsters-Gulls-
23 - 2024-09-24164Griffins-Monsters-
25 - 2024-09-26182Monsters-Canucks-
27 - 2024-09-28196Thunderbirds-Monsters-
29 - 2024-09-30211Monsters-Thunderbirds-
31 - 2024-10-02227Monsters-Wolves-
33 - 2024-10-04236Monsters-Barracuda-
35 - 2024-10-06248Iowa Wild-Monsters-
38 - 2024-10-09269Thunderbirds-Monsters-
40 - 2024-10-11285Monsters-Eagles-
42 - 2024-10-13301Wolf Pack-Monsters-
45 - 2024-10-16319Monsters-Roadrunners-
47 - 2024-10-18333Checkers-Monsters-
50 - 2024-10-21356Comets-Monsters-
53 - 2024-10-24377Monsters-Condors-
55 - 2024-10-26392Phantoms-Monsters-
57 - 2024-10-28404Monsters-Thunderbirds-
59 - 2024-10-30419Monsters-StarsF-
61 - 2024-11-01430Condors-Monsters-
64 - 2024-11-04455BruinsF-Monsters-
66 - 2024-11-06463Monsters-Eagles-
68 - 2024-11-08485Admirals-Monsters-
71 - 2024-11-11505Monsters-Condors-
73 - 2024-11-13517Monsters-Islanders-
75 - 2024-11-15527Icehogs-Monsters-
77 - 2024-11-17548Reign-Monsters-
78 - 2024-11-18555Monsters-StarsF-
80 - 2024-11-20572Monsters-Americans-
83 - 2024-11-23589Crunch-Monsters-
85 - 2024-11-25608Monsters-Rocket-
86 - 2024-11-26619Monsters-Griffins-
88 - 2024-11-28630Iowa Wild-Monsters-
90 - 2024-11-30652Gulls-Monsters-
93 - 2024-12-03669Monsters-Icehogs-
95 - 2024-12-05684Condors-Monsters-
98 - 2024-12-08705Monsters-Wolves-
100 - 2024-12-10717Wranglers-Monsters-
102 - 2024-12-12739Monsters-Silver Knights-
104 - 2024-12-14747Admirals-Monsters-
106 - 2024-12-16763Monsters-Canucks-
108 - 2024-12-18779StarsF-Monsters-
111 - 2024-12-21796Monsters-Marlies-
114 - 2024-12-24815Eagles-Monsters-
117 - 2024-12-27840Barracuda-Monsters-
120 - 2024-12-30864Monsters-Silver Knights-
121 - 2024-12-31874PenguinsF-Monsters-
125 - 2025-01-04902Eagles-Monsters-
128 - 2025-01-07923Monsters-Barracuda-
129 - 2025-01-08933Silver Knights-Monsters-
131 - 2025-01-10948Monsters-Iowa Wild-
133 - 2025-01-12966Barracuda-Monsters-
136 - 2025-01-15978Monsters-Iowa Wild-
138 - 2025-01-17996Gulls-Monsters-
141 - 2025-01-201025Griffins-Monsters-
145 - 2025-01-241054Monsters-Admirals-
146 - 2025-01-251058Roadrunners-Monsters-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2025-01-281084Monsters-Admirals-
150 - 2025-01-291089SenatorsF-Monsters-
153 - 2025-02-011114Monsters-Moose-
155 - 2025-02-031123Reign-Monsters-
156 - 2025-02-041134Monsters-SenatorsF-
159 - 2025-02-071154Monsters-Firebirds-
160 - 2025-02-081156Bears-Monsters-
164 - 2025-02-121186StarsF-Monsters-
165 - 2025-02-131190Monsters-Griffins-
168 - 2025-02-161218Roadrunners-Monsters-
169 - 2025-02-171220Monsters-Firebirds-
171 - 2025-02-191225Monsters-Gulls-
173 - 2025-02-211239Monsters-Reign-
175 - 2025-02-231255Canucks-Monsters-
176 - 2025-02-241257Monsters-Wranglers-
177 - 2025-02-251263Monsters-Reign-
180 - 2025-02-281287Monsters-Wranglers-
183 - 2025-03-031303Canucks-Monsters-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4020
Assistance5,6232,540
Assistance PCT70.29%63.50%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
37 2041 - 68.03% 102,706$410,823$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
388,926$ 4,132,500$ 4,132,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 379,746$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
3,800,113$ 168 22,878$ 3,843,504$




Monsters 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
1Joseph Veleno89315283233815016527911.11%34175519.7239124311236152.56%10.9500
2Juuso Valimaki82136174136011410012010.83%101189023.058917650221030%00.7800
3Jacob Peterson892542671212341042808.93%19162818.29511163900015252.94%00.8216
4Victor Mete8475966132257751146.14%99190922.7331114610220100%00.6900
5Jack Mcbain872535606441521912609.62%21175420.164594510122149.89%00.6824

Monsters 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
1Malcolm Subban48231460.8923.3326340214613510000.80826
2Jaroslav Janus36191020.8952.83190702908550100.3333
3Brent Moran11000.9382.00600023200000

Monsters 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
Saison régulière
158236320704328525530411716020331451341141191605010140121199728551980415931027912257582784787248234569952813072584316.67%2245276.79%31509290551.94%1370263352.03%701136251.47%2017140218735941074544
16713012002129-8401012001115-4312000001014-462139600085712348679672171533612120420.00%17664.71%014826555.85%10619155.50%7413256.06%175123160509146
Total Saison régulière89373508243306284224517170323315614974420180501015013515103306558864151011078613280991392693950251675256414282784716.91%2415875.93%31657317052.27%1476282452.27%775149451.87%2193152620336451165590
Séries éliminatoires
15514000001418-42020000046-2312000001012-22142438004640134553544015043439015320.00%18666.67%06515541.94%8516850.60%437954.43%11073124396633
Total Séries éliminatoires514000001418-42020000046-2312000001012-22142438004640134553544015043439015320.00%18666.67%06515541.94%8516850.60%437954.43%11073124396633

Monsters 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
1Vyacheslav Leshchenko5235141041315.38%08016.06011200000025.00%01.2500
2Victor Mete5044104480%1111322.6301110000000%00.7100
3Jack Mcbain5314147111520.00%09619.23101200000049.59%00.8300
4Michal Repik51232004714.29%0428.5100000000000%01.4100
5Jonathan Racine5033-248570%510521.1801130000000%00.5700

Monsters 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
1Jaroslav Janus21000.8892.86840043600000
2Malcolm Subban40220.8773.89216001411400000