Connexion

Monsters
GP: 18 | W: 9 | L: 7 | OTL: 2 | P: 20
GF: 68 | GA: 70 | PP%: 18.33% | PK%: 71.93%
DG: Eric Henault | Morale : 50 | Moyenne d’équipe : 68
Prochain matchs #306 vs Wolf Pack
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Centre de jeu
Monsters
9-7-2, 20pts
3
FINAL
5 Wolves
13-5-1, 27pts
Team Stats
W1StreakW3
6-4-0Home Record7-2-0
3-3-2Away Record6-3-1
5-4-1Last 10 Games6-3-1
3.78Buts par match 3.95
3.89Buts contre par match 3.63
18.33%Pourcentage en avantage numérique18.31%
71.93%Pourcentage en désavantage numérique86.96%
Checkers
7-10-2, 16pts
3
FINAL
4 Monsters
9-7-2, 20pts
Team Stats
L2StreakW1
3-5-1Home Record6-4-0
4-5-1Away Record3-3-2
3-7-0Last 10 Games5-4-1
2.84Buts par match 3.78
3.47Buts contre par match 3.89
17.11%Pourcentage en avantage numérique18.33%
78.48%Pourcentage en désavantage numérique71.93%
Monsters
9-7-2, 20pts
2022-11-28
Wolf Pack
11-6-2, 24pts
Statistiques d’équipe
W1SéquenceW2
6-4-0Fiche domicile6-3-0
3-3-2Fiche visiteur5-3-2
5-4-110 derniers matchs5-3-2
3.78Buts par match 4.42
3.89Buts contre par match 3.53
18.33%Pourcentage en avantage numérique24.24%
71.93%Pourcentage en désavantage numérique77.61%
Monsters
9-7-2, 20pts
2022-12-02
Marlies
10-6-2, 22pts
Statistiques d’équipe
W1SéquenceW1
6-4-0Fiche domicile4-4-2
3-3-2Fiche visiteur6-2-0
5-4-110 derniers matchs5-4-1
3.78Buts par match 3.78
3.89Buts contre par match 3.11
18.33%Pourcentage en avantage numérique25.00%
71.93%Pourcentage en désavantage numérique81.71%
Comets
4-13-2, 10pts
2022-12-03
Monsters
9-7-2, 20pts
Statistiques d’équipe
L3SéquenceW1
3-7-0Fiche domicile6-4-0
1-6-2Fiche visiteur3-3-2
2-7-110 derniers matchs5-4-1
3.11Buts par match 3.78
4.21Buts contre par match 3.89
20.31%Pourcentage en avantage numérique18.33%
78.38%Pourcentage en désavantage numérique71.93%
Meneurs d'équipe
Victoires
Sam Montembeault
5
Pourcentage d’arrêts
Sam Montembeault
0.902

Statistiques d’équipe
Buts pour
68
3.78 GFG
Tirs pour
635
35.28 Avg
Pourcentage en avantage numérique
18.3%
11 GF
Début de zone offensive
40.8%
Buts contre
70
3.89 GAA
Tirs contre
637
35.39 Avg
Pourcentage en désavantage numérique
71.9%
16 GA
Début de la zone défensive
40.0%
Information d’équipe

Directeur généralEric Henault
EntraîneurStéphane Richer
DivisionMETROPOLITAINE
ConférenceEST
CapitainePierre-Olivier Joseph
Assistant #1Raphael Lavoie
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,847
Billets de saison300


Information formation

Équipe Pro32
Équipe Mineure20
Limite contact 52 / 55
Espoirs31


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
1Noah Cates0X100.00723483657182756656676963686264050700232925,000$
2Cedric Paquette0X95.008345736075797761746263716472730507002914,332,000$
3Alex Limoges0X97.006638936578808661646266616566670506902531,500,000$
4Marian Studenic0XX100.006339866374807965616465686465670506902411,156,250$
5Rafael Harvey-Pinard0XX100.00763583646682866457626661656469050690235825,000$
6Garrett Pilon0X100.00633793657386796175626761656466050680242989,000$
7Steven Lorentz0XXX100.006538956488778665806261566266670506802641,199,000$
8Adam Mascherin0X100.00634681647277826568616362646567050670241750,000$
9Bokondji Imama0X100.007785645982698060566162585766680506702631,211,000$
10Otto Somppi0X100.006839876379758063706258616364660506702411,049,000$
11Mark Kastelic0X100.00813665588579865375605961566364050670232821,667$
12Raphael Lavoie (A)0XX100.00773487568692835761585960566264050670225925,000$
13Pierre-Olivier Joseph (C)0X98.006938847177868770307160625163650507102351,075,883$
14Joel Hanley0X100.006936846871807566307055645371720506903121,150,000$
15Nick Seeler0X100.007645786081827453306154684769710506702931,278,000$
16Brian Lashoff0X100.00774283578665885630555458467277050660321977,000$
17Brady Keeper0X100.00583595588077736030595662506965050650262954,000$
18Isaak Phillips0X100.00673876578277855930575660486163050650212925,000$
Rayé
1Jack Dugan0X100.006835786177767360666358576264660506602451,562,500$
2Tyler Angle0X100.00583689646788896259635857646265050660222925,000$
3Ivan Chekhovich0XX100.00503595636780746456625960646362050650231903,333$
4Dominic Turgeon0X100.00613988598076855862565761596669050650261999,000$
5Nathan Legare (R)0X100.00663983557583855358555657556163050630213905,000$
6Greg Pateryn0X84.95754579598580736130675874507377050710321750,000$
7Nikolas Brouillard0X100.00574363616474865930625756506769050640271750,000$
8Yanni Kaldis0X100.00613886597074815830625457456769050640271750,000$
9Ole Bjorgvik-Holm0X100.00693483577872775930585356465961050630202917,500$
MOYENNE D’ÉQUIPE99.0468408361777981615262596157656705067
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
1Sam Montembeault100.00779086837675777675777666750507902633,000,000$
2Erik Kallgren100.0074858382737274737274736675050760263750,000$
Rayé
1Vasily Demchenko100.0072787679717072717072717377050740282750,000$
2Jacob Ingham100.0068656684676668676668676367050700222850,000$
3Lukas Parik100.0065666889646365646365646165050680211750,000$
MOYENNE D’ÉQUIPE100.007177768370697170697170667205073
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Stéphane Richer75757575757575Can5650$


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
1Pierre-Olivier JosephMonsters (CLB)D1841620780213839123410.26%3043724.301341851011049100.00%000000.9100000011
2Joel HanleyMonsters (CLB)D1851015-416043343471514.71%3538921.613142050000039000.00%000000.7700000011
3Rafael Harvey-PinardMonsters (CLB)LW/RW176915-860312255145910.91%132118.943031050000041140.00%2000000.9300000101
4Noah CatesMonsters (CLB)LW1810414480182251133219.61%420511.3901113000080047.62%2100111.3700000112
5Cedric PaquetteMonsters (CLB)C186814-1025548556615629.09%938321.3102211511015391053.28%54800100.7300010021
6Alex LimogesMonsters (CLB)LW187613420142564174210.94%335919.9503312470000131037.50%1600000.7200000100
7Brady KeeperMonsters (CLB)D183912-3401521186916.67%1934519.2201126011014100.00%000000.6900000100
8Otto SomppiMonsters (CLB)C18471140061538102610.53%121111.73123937000000048.15%10800001.0400000010
9Nick SeelerMonsters (CLB)D18471118026162582516.00%2334519.18123749000043100.00%000000.6400000200
10Marian StudenicMonsters (CLB)LW/RW18371040019295923315.08%427015.040009250112480061.90%2100000.7400000010
11Greg PaterynMonsters (CLB)D937100601917234813.04%1217219.14112152500000000.00%000001.1600000011
12Garrett PilonMonsters (CLB)C1818942011403015243.33%225214.01000000113501052.92%35900000.7100000010
13Raphael LavoieMonsters (CLB)C/RW18437340232831173212.90%532418.010005290000262049.48%28700000.4300000101
14Isaak PhillipsMonsters (CLB)D1814522022681712.50%1830016.7100000101149000.00%000000.3300000001
15Nathan LegareMonsters (CLB)RW1423544016111861111.11%226819.19112442000000061.11%1800000.3700000000
16Ivan ChekhovichMonsters (CLB)LW/RW10134-200112219164.76%216216.2600000000030038.46%1300000.4900000001
17Mark KastelicMonsters (CLB)C182240601812202910.00%11699.4200000000000051.47%13600000.4700000001
18Bokondji ImamaMonsters (CLB)LW18213240158226149.09%21357.5400000000000025.00%800000.4400000000
19Steven LorentzMonsters (CLB)C/LW/RW4022100574260.00%26015.12011012000000038.46%7800000.6600000000
20Brian LashoffMonsters (CLB)D901152202647050.00%217018.9101121800001000.00%000000.1200000000
21Jack DuganMonsters (CLB)LW5011-100212020.00%0204.040110300000000.00%100000.9900000000
Statistiques d’équipe totales ou en moyenne3206811818617127539942363518746910.71%177530616.58112031125506246113949150.86%163400210.70000107911
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
1Sam MontembeaultMonsters (CLB)105210.9023.4555600323260110.0000810000
2Erik KallgrenMonsters (CLB)104510.8814.2352500373100000.0000108000
Statistiques d’équipe totales ou en moyenne209720.8923.83108200696360110.00001818000


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 Nouveau joueur Poids Taille Non-échange Disponible pour échange Ballotage forcé Contrat Type Salaire actuel Salaire restantSalaire moyenPlafond salarial 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 10Link
Adam MascherinMonsters (CLB)LW241998-06-06No200 Lbs5 ft11NoNoNo1Pro & Farm750,000$576,612$750,000$0$0$NoLien
Alex LimogesMonsters (CLB)LW251997-09-16No201 Lbs6 ft1NoNoNo3Pro & Farm1,500,000$1,153,225$1,500,000$0$0$No1,500,000$1,500,000$Lien
Bokondji ImamaMonsters (CLB)LW261996-08-03No221 Lbs6 ft1NoNoNo3Pro & Farm1,211,000$931,037$883,333$0$0$No925,000$925,000$Lien
Brady KeeperMonsters (CLB)D261996-06-05No197 Lbs6 ft2NoNoNo2Pro & Farm954,000$733,451$650,000$0$0$No954,000$Lien
Brian LashoffMonsters (CLB)D321990-07-16No213 Lbs6 ft3NoNoNo1Pro & Farm977,000$751,134$650,000$0$0$NoLien
Cedric PaquetteMonsters (CLB)C291993-08-13No205 Lbs6 ft0NoNoNo1Pro & Farm4,332,000$3,330,516$0$0$NoLien
Dominic TurgeonMonsters (CLB)C261996-02-25No199 Lbs6 ft2NoNoNo1Pro & Farm999,000$768,048$650,000$0$0$NoLien
Erik KallgrenMonsters (CLB)G261996-10-14No193 Lbs6 ft3NoNoNo3Pro & Farm750,000$576,612$750,000$0$0$No750,000$750,000$Lien
Garrett PilonMonsters (CLB)C241998-04-13No191 Lbs6 ft0NoNoNo2Pro & Farm989,000$760,360$650,000$0$0$No989,000$Lien
Greg PaterynMonsters (CLB)D321990-06-20No221 Lbs6 ft2NoNoNo1Pro & Farm750,000$576,612$750,000$0$0$NoLien
Isaak PhillipsMonsters (CLB)D212001-09-28No193 Lbs6 ft3NoNoNo2Pro & Farm925,000$711,155$600,000$0$0$No925,000$Lien
Ivan ChekhovichMonsters (CLB)LW/RW231999-01-04No185 Lbs5 ft10NoNoNo1Pro & Farm903,333$694,497$0$0$NoLien
Jack DuganMonsters (CLB)LW241998-03-24No185 Lbs6 ft2NoNoNo5Pro & Farm1,562,500$1,201,276$1,562,500$0$0$No1,247,000$1,247,000$1,247,000$1,247,000$Lien
Jacob InghamMonsters (CLB)G222000-06-10No186 Lbs6 ft4NoNoNo2Pro & Farm850,000$653,494$850,000$0$0$No850,000$Lien
Joel HanleyMonsters (CLB)D311991-06-08No190 Lbs5 ft11NoNoNo2Pro & Farm1,150,000$884,139$1,150,000$0$0$No1,150,000$Lien
Lukas ParikMonsters (CLB)G212001-03-15No215 Lbs6 ft4NoNoNo1Pro & Farm750,000$576,612$700,000$0$0$NoLien
Marian StudenicMonsters (CLB)LW/RW241998-10-28No181 Lbs6 ft1NoNoNo1Pro & Farm1,156,250$888,944$650,000$0$0$NoLien
Mark KastelicMonsters (CLB)C231999-03-11No210 Lbs6 ft3NoNoNo2Pro & Farm821,667$631,711$821,667$0$0$No821,667$Lien
Nathan LegareMonsters (CLB)RW212001-01-11Yes205 Lbs6 ft0NoNoNo3Pro & Farm905,000$695,779$700,000$0$0$No905,000$905,000$
Nick SeelerMonsters (CLB)D291993-06-03No201 Lbs6 ft2NoNoNo3Pro & Farm1,278,000$982,548$650,000$0$0$No1,278,000$1,278,000$Lien
Nikolas BrouillardMonsters (CLB)D271995-02-07No168 Lbs5 ft10NoNoNo1Pro & Farm750,000$576,612$750,000$0$0$NoLien
Noah CatesMonsters (CLB)LW231999-02-05No165 Lbs6 ft1NoNoNo2Pro & Farm925,000$711,155$700,000$0$0$No925,000$Lien
Ole Bjorgvik-HolmMonsters (CLB)D202002-05-23No190 Lbs6 ft2NoNoNo2Pro & Farm917,500$705,389$917,500$0$0$No917,500$Lien
Otto SomppiMonsters (CLB)C241998-01-12No192 Lbs6 ft2NoNoNo1Pro & Farm1,049,000$806,489$1,000,000$0$0$NoLien
Pierre-Olivier JosephMonsters (CLB)D231999-07-01No185 Lbs6 ft2NoNoNo5Pro & Farm1,075,883$827,157$650,000$0$0$No1,014,000$1,014,000$1,014,000$1,014,000$Lien
Rafael Harvey-PinardMonsters (CLB)LW/RW231999-01-06No182 Lbs5 ft9NoNoNo5Pro & Farm825,000$634,274$825,000$0$0$No1,262,000$1,262,000$1,262,000$1,262,000$Lien
Raphael LavoieMonsters (CLB)C/RW222000-09-25No196 Lbs6 ft4NoNoNo5Pro & Farm925,000$711,155$925,000$0$0$No844,000$844,000$844,000$844,000$Lien
Sam MontembeaultMonsters (CLB)G261996-10-30No199 Lbs6 ft3NoNoNo3Pro & Farm3,000,000$2,306,451$708,750$0$0$No1,662,000$1,662,000$Lien
Steven LorentzMonsters (CLB)C/LW/RW261996-04-13No206 Lbs6 ft4NoNoNo4Pro & Farm1,199,000$921,811$650,000$0$0$No1,199,000$1,199,000$1,199,000$Lien
Tyler AngleMonsters (CLB)LW222000-09-30No172 Lbs5 ft11NoNoNo2Pro & Farm925,000$711,155$925,000$0$0$No925,000$Lien
Vasily DemchenkoMonsters (CLB)G281994-03-16No193 Lbs6 ft2NoNoNo2Pro & Farm750,000$576,612$750,000$0$0$No750,000$Lien
Yanni KaldisMonsters (CLB)D271995-09-30No187 Lbs5 ft11NoNoNo1Pro & Farm750,000$576,612$750,000$0$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3225.00195 Lbs6 ft12.281,143,910$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Alex LimogesCedric PaquetteSteven Lorentz37122
2Rafael Harvey-PinardRaphael LavoieOtto Somppi33122
3Noah CatesGarrett PilonMarian Studenic20122
4Bokondji ImamaMark KastelicOtto Somppi10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Pierre-Olivier JosephBrian Lashoff38122
2Joel HanleyBrady Keeper34122
3Isaak PhillipsNick Seeler28122
4Pierre-Olivier JosephBrady Keeper0122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Rafael Harvey-PinardRaphael LavoieMarian Studenic60122
2Alex LimogesOtto SomppiCedric Paquette40122
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Pierre-Olivier JosephBrian Lashoff60122
2Nick SeelerJoel Hanley40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Garrett PilonMarian Studenic50122
2Rafael Harvey-PinardOtto Somppi50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Pierre-Olivier JosephNick Seeler50122
2Joel HanleyIsaak Phillips50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Garrett Pilon50122Nick SeelerJoel Hanley50122
2Raphael Lavoie50122Brady KeeperIsaak Phillips50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Raphael LavoieMarian Studenic50122
2Alex LimogesRafael Harvey-Pinard50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Pierre-Olivier JosephIsaak Phillips50122
2Nick SeelerBrady Keeper50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Rafael Harvey-PinardCedric PaquetteRaphael LavoiePierre-Olivier JosephNick Seeler
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Noah CatesCedric PaquetteMarian StudenicPierre-Olivier JosephNick Seeler
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Rafael Harvey-Pinard, Alex Limoges, Marian StudenicOtto Somppi, Rafael Harvey-PinardNoah Cates
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Brady Keeper, Pierre-Olivier Joseph, Brian LashoffJoel HanleyPierre-Olivier Joseph, Brady Keeper
Tirs de pénalité
Rafael Harvey-Pinard, Raphael Lavoie, Marian Studenic, Alex Limoges, Pierre-Olivier Joseph
Gardien
#1 : Sam Montembeault, #2 : Erik Kallgren
Lignes d’attaque personnalisées en prolongation
Noah Cates, Raphael Lavoie, Garrett Pilon, Rafael Harvey-Pinard, Mark Kastelic, Cedric Paquette, Cedric Paquette, Otto Somppi, Marian Studenic, Alex Limoges, Steven Lorentz
Lignes de défense personnalisées en prolongation
Pierre-Olivier Joseph, Nick Seeler, Joel Hanley, Brady Keeper, Isaak Phillips


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
1Bears21000100972110000005231000010045-130.7509162500252023094212203213762154341218.33%20100.00%034766252.42%31665048.62%16831253.85%435299416132233115
2Checkers22000000853110000004311100000042241.00081321002520230802122032137601313428112.50%4250.00%034766252.42%31665048.62%16831253.85%435299416132233115
3Comets11000000532110000005320000000000021.0005813002520230302122032137401312162150.00%6266.67%034766252.42%31665048.62%16831253.85%435299416132233115
4Griffins1000010045-1000000000001000010045-110.50044800252023039212203213749121428000.00%7271.43%034766252.42%31665048.62%16831253.85%435299416132233115
5Phantoms220000001073110000005321100000054141.000101727002520230752122032137691714554125.00%7185.71%134766252.42%31665048.62%16831253.85%435299416132233115
6Roadrunners1010000023-1000000000001010000023-100.0002460025202302821220321372913623200.00%20100.00%034766252.42%31665048.62%16831253.85%435299416132233115
7W-B/Scranton Penguins2110000079-22110000079-20000000000020.50071421002520230692122032137592326517228.57%12558.33%034766252.42%31665048.62%16831253.85%435299416132233115
8Wolf Pack2110000089-11010000035-21100000054120.50081523102520230522122032137882516415240.00%8275.00%134766252.42%31665048.62%16831253.85%435299416132233115
9Wolves3120000011110211000008621010000035-220.33311203100252023010321220321379021147013215.38%6183.33%034766252.42%31665048.62%16831253.85%435299416132233115
10islanders20200000411-71010000026-41010000025-300.000471100252023065212203213791258397114.29%3166.67%034766252.42%31665048.62%16831253.85%435299416132233115
Total1897002006870-210640000039372833002002933-4200.556681181861025202306352122032137637177127399601118.33%571671.93%234766252.42%31665048.62%16831253.85%435299416132233115
_Since Last GM Reset1897002006870-210640000039372833002002933-4200.556681181861025202306352122032137637177127399601118.33%571671.93%234766252.42%31665048.62%16831253.85%435299416132233115
_Vs Conference1796002006667-110640000039372732002002730-3200.588661141801025202306072122032137608164121376581118.97%551670.91%234766252.42%31665048.62%16831253.85%435299416132233115
_Vs Division1476001005457-39540000035341522001001923-4150.5365497151102520230488212203213749913994306501020.00%441272.73%234766252.42%31665048.62%16831253.85%435299416132233115

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1820W16811818663563717712739910
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
189702006870
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
106400003937
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
83302002933
Derniers 10 matchs
WLOTWOTL SOWSOL
540100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
601118.33%571671.93%2
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
21220321372520230
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
34766252.42%31665048.62%16831253.85%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
435299416132233115


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
3 - 2022-10-1816Bears2Monsters5BWSommaire du match
4 - 2022-10-1931Monsters2islanders5ALSommaire du match
6 - 2022-10-2146Wolf Pack5Monsters3BLSommaire du match
9 - 2022-10-2465Comets3Monsters5BWSommaire du match
11 - 2022-10-2674Monsters5Phantoms4AWSommaire du match
13 - 2022-10-2893Monsters4Bears5ALXSommaire du match
16 - 2022-10-31113Wolves1Monsters5BWSommaire du match
20 - 2022-11-04134Wolves5Monsters3BLSommaire du match
21 - 2022-11-05140Monsters5Wolf Pack4AWSommaire du match
24 - 2022-11-08167Phantoms3Monsters5BWSommaire du match
25 - 2022-11-09180Monsters4Griffins5ALXSommaire du match
29 - 2022-11-13193Monsters2Roadrunners3ALSommaire du match
31 - 2022-11-15205islanders6Monsters2BLSommaire du match
33 - 2022-11-17227Monsters4Checkers2AWSommaire du match
36 - 2022-11-20237W-B/Scranton Penguins2Monsters5BWSommaire du match
38 - 2022-11-22257W-B/Scranton Penguins7Monsters2BLSommaire du match
39 - 2022-11-23267Monsters3Wolves5ALSommaire du match
42 - 2022-11-26290Checkers3Monsters4BWSommaire du match
44 - 2022-11-28306Monsters-Wolf Pack-
48 - 2022-12-02324Monsters-Marlies-
49 - 2022-12-03334Comets-Monsters-
52 - 2022-12-06356Monsters-Roadrunners-
53 - 2022-12-07369Binghamton Senateurs-Monsters-
58 - 2022-12-12394islanders-Monsters-
59 - 2022-12-13408Monsters-Comets-
62 - 2022-12-16423Comets-Monsters-
63 - 2022-12-17436Monsters-Comets-
65 - 2022-12-19454Monsters-Barracuda-
67 - 2022-12-21469Gulls-Monsters-
72 - 2022-12-26488Texas Stars-Monsters-
76 - 2022-12-30515Thunderbirds-Monsters-
78 - 2023-01-01533Monsters-islanders-
80 - 2023-01-03546Wolves-Monsters-
84 - 2023-01-07560Monsters-W-B/Scranton Penguins-
86 - 2023-01-09578Iowa Wild-Monsters-
88 - 2023-01-11600Monsters-Canucks-
90 - 2023-01-13612Americans-Monsters-
92 - 2023-01-15632Monsters-Bears-
93 - 2023-01-16644Providence Bruins-Monsters-
96 - 2023-01-19664Monsters-Comets-
99 - 2023-01-22677Rockets-Monsters-
101 - 2023-01-24698Monsters-islanders-
102 - 2023-01-25710Rockets-Monsters-
104 - 2023-01-27731Monsters-Rockets-
105 - 2023-01-28739Eagles-Monsters-
108 - 2023-01-31766Monsters-islanders-
109 - 2023-02-01772Crunch-Monsters-
111 - 2023-02-03786Monsters-Checkers-
112 - 2023-02-04802Admirals-Monsters-
115 - 2023-02-07819Monsters-Wolves-
119 - 2023-02-11837Monsters-Firebirds-
120 - 2023-02-12844Wranglers-Monsters-
122 - 2023-02-14867Phantoms-Monsters-
126 - 2023-02-18882Monsters-IceHogs-
128 - 2023-02-20898Thunderbirds-Monsters-
130 - 2023-02-22920Monsters-Wolves-
131 - 2023-02-23930islanders-Monsters-
133 - 2023-02-25946Monsters-Americans-
136 - 2023-02-28963Griffins-Monsters-
137 - 2023-03-01970Monsters-Silver Knights-
140 - 2023-03-04994Monsters-Reign-
142 - 2023-03-06999Condors-Monsters-
144 - 2023-03-081009Monsters-Bears-
146 - 2023-03-101030Bears-Monsters-
148 - 2023-03-121044Monsters-Providence Bruins-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
150 - 2023-03-141062Phantoms-Monsters-
152 - 2023-03-161073Monsters-Moose-
155 - 2023-03-191096Griffins-Monsters-
157 - 2023-03-211112Monsters-Binghamton Senateurs-
158 - 2023-03-221124Wolf Pack-Monsters-
160 - 2023-03-241131Monsters-Roadrunners-
162 - 2023-03-261141Monsters-Wolf Pack-
164 - 2023-03-281165Bears-Monsters-
169 - 2023-04-021191W-B/Scranton Penguins-Monsters-
171 - 2023-04-041216Marlies-Monsters-
173 - 2023-04-061222Monsters-Crunch-
175 - 2023-04-081234Monsters-W-B/Scranton Penguins-
176 - 2023-04-091251Marlies-Monsters-
179 - 2023-04-121264Monsters-W-B/Scranton Penguins-
181 - 2023-04-141279Monsters-Phantoms-
182 - 2023-04-151292Wolf Pack-Monsters-
184 - 2023-04-171301Monsters-Phantoms-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets2716
Assistance19,0559,412
Assistance PCT95.28%94.12%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
31 2847 - 94.89% 99,097$990,966$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 3,660,513$ 2,446,875$ 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
3,071,995$ 143 19,680$ 2,814,240$




Monsters Leaders statistiques (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

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

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

Monsters Leaders statistiques (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

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