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Connexion

Monsters
GP: 40 | W: 27 | L: 11 | OTL: 2 | P: 56
GF: 88 | GA: 65 | PP%: 30.51% | PK%: 80.15%
DG: Stéphane Drolet | Morale : 94 | Moyenne d’équipe : 68

Centre de jeu
Wolves
20-16-4, 44pts
1
2 Monsters
27-11-2, 56pts
Team Stats
W1SéquenceW4
13-6-1Fiche domicile11-8-1
7-10-3Fiche domicile16-3-1
5-4-1Derniers 10 matchs8-2-0
1.88Buts par match 2.20
1.85Buts contre par match 1.63
21.74%Pourcentage en avantage numérique30.51%
73.80%Pourcentage en désavantage numérique80.15%
Monsters
27-11-2, 56pts
4
3 Rampage
32-4-4, 68pts
Team Stats
W4SéquenceOTL1
11-8-1Fiche domicile15-2-3
16-3-1Fiche domicile17-2-1
8-2-0Derniers 10 matchs9-0-1
2.20Buts par match 3.83
1.63Buts contre par match 1.93
30.51%Pourcentage en avantage numérique50.76%
80.15%Pourcentage en désavantage numérique78.24%
Meneurs d'équipe
Buts
Scott Morrow
17
Passes
Scott Morrow
19
Points
Scott Morrow
36
Jacob Bernard-DockerPlus/Moins
Jacob Bernard-Docker
-2

Statistiques d’équipe
Buts pour
88
2.20 GFG
Tirs pour
792
19.80 Avg
Pourcentage en avantage numérique
30.5%
54 GF
Début de zone offensive
33.9%
Buts contre
65
1.63 GAA
Tirs contre
669
16.73 Avg
Pourcentage en désavantage numérique
80.1%%
27 GA
Début de la zone défensive
34.1%
Informations de l'équipe

Directeur généralStéphane Drolet
DivisionNord
ConférenceConference Est
Capitaine
Assistant #1Timo Meier
Assistant #2


Informations de l’aréna

Capacité8,000
Assistance0
Billets de saison1,600


Informations de la formation

Équipe Pro3
Équipe Mineure19
Limite contact 22 / 250
Espoirs42


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
1Ethan Del Mastro (R)0X100.008245917280758661255249712546466382710212856,000$
2Scott Morrow (R)0X100.005942997278688260256749672545456284680212916,667$
3Jacob Bernard-Docker0X100.007156877173626060255148692559595978640241805,000$
Rayé
MOYENNE D’ÉQUIPE100.00714892727768766025574969255050618168
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
Rayé
MOYENNE D’ÉQUIPE0.000000000000000000
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Scott MorrowMonsters (CBJ)D40171936-6201730124575813.71%26104526.151416303111800010108830%01173000.691200017176
2Ethan Del MastroMonsters (CBJ)D4061622-4211541306730268.96%40105226.316814211200001108220%0882000.420102115149
3Jacob Bernard-DockerMonsters (CBJ)D40189-2252516143919282.56%2997524.391345112000181010%0951000.18020417522
Statistiques d’équipe totales ou en moyenne120244367-124840747423010611210.43%95307325.6121274857350000122971060.00%028206000.4415062393637
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


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 Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Ethan Del MastroMonsters (CBJ)D212003-01-15CANYes210 Lbs6 ft4NoNoN/ANoNo2FalseFalsePro & Farm856,000$0$0$No856,000$--------856,000$--------No--------Lien
Jacob Bernard-DockerMonsters (CBJ)D242000-06-30CANNo198 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm805,000$0$0$No---------------------------Lien / Lien NHL
Scott MorrowMonsters (CBJ)D212002-11-01USAYes210 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm916,667$0$0$No916,667$--------916,667$--------No--------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
322.00206 Lbs6 ft21.67859,222$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
140122
230122
320122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ethan Del MastroScott Morrow40122
2Jacob Bernard-Docker30122
3Ethan Del MastroScott Morrow20122
4Jacob Bernard-Docker10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
160122
240122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ethan Del MastroScott Morrow60122
2Jacob Bernard-Docker40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
160122
240122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ethan Del MastroScott Morrow60122
2Jacob Bernard-Docker40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
160122Ethan Del MastroScott Morrow60122
240122Jacob Bernard-Docker40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
160122
240122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ethan Del MastroScott Morrow60122
2Jacob Bernard-Docker40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ethan Del MastroScott Morrow
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ethan Del MastroScott Morrow
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, , ,
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Ethan Del Mastro, Scott Morrow, Jacob Bernard-DockerEthan Del MastroScott Morrow, Jacob Bernard-Docker
Tirs de pénalité
, , , ,
Gardien
#1 : , #2 :
Lignes d’attaque personnalisées en prolongation
, , , , , , , , ,
Lignes de défense personnalisées en prolongation
Ethan Del Mastro, Scott Morrow, Jacob Bernard-Docker, ,


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
1Admirals11000000211000000000001100000021121.00024600132445716141264361342048125240.00%40100.00%029256751.50%28356949.74%28553553.27%9326591013272479233
2Americans22000000514110000002111100000030341.0005101501132445748141264361342411152213323.08%5180.00%029256751.50%28356949.74%28553553.27%9326591013272479233
3Barracuda21001000633110000004221000100021141.00069150013244574514126436134461647208450.00%6266.67%029256751.50%28356949.74%28553553.27%9326591013272479233
4Bears1010000002-21010000002-20000000000000.0000000013244571414126436134226614400.00%3233.33%029256751.50%28356949.74%28553553.27%9326591013272479233
5Bruins1010000001-11010000001-10000000000000.00000000132445710141264361342331910300.00%7185.71%029256751.50%28356949.74%28553553.27%9326591013272479233
6Checkers1010000012-1000000000001010000012-100.000123001324457181412643613411495400.00%2150.00%029256751.50%28356949.74%28553553.27%9326591013272479233
7Comets201010005501010000023-11000100032120.50059140013244574214126436134351189218225.00%7357.14%029256751.50%28356949.74%28553553.27%9326591013272479233
8Condors11000000211110000002110000000000021.00023500132445713141264361341610109300.00%5180.00%029256751.50%28356949.74%28553553.27%9326591013272479233
9Crunch211000001101010000001-11100000010120.500123011324457351412643613423121330600.00%40100.00%029256751.50%28356949.74%28553553.27%9326591013272479233
10Devils22000000633110000004221100000021141.00061117001324457361412643613433743214535.71%20100.00%029256751.50%28356949.74%28553553.27%9326591013272479233
11Eagles10001000211000000000001000100021121.00024600132445722141264361341456116116.67%30100.00%029256751.50%28356949.74%28553553.27%9326591013272479233
12Griffins1000000112-1000000000001000000112-110.500123001324457151412643613413413104125.00%4175.00%029256751.50%28356949.74%28553553.27%9326591013272479233
13Gulls11000000422000000000001100000042221.000481200132445720141264361341776922100.00%30100.00%029256751.50%28356949.74%28553553.27%9326591013272479233
14Heat11000000413000000000001100000041321.0004711001324457271412643613421153013200.00%50100.00%029256751.50%28356949.74%28553553.27%9326591013272479233
15Hockey Club 11000000101110000001010000000000021.00011201132445717141264361341334114125.00%20100.00%029256751.50%28356949.74%28553553.27%9326591013272479233
16IceHogs11000000422000000000001100000042221.0004812001324457201412643613421913125360.00%4175.00%029256751.50%28356949.74%28553553.27%9326591013272479233
17Marlies2110000047-31010000004-41100000043120.50046100013244573414126436134391024298225.00%8187.50%029256751.50%28356949.74%28553553.27%9326591013272479233
18Moose1010000012-11010000012-10000000000000.00012300132445716141264361341467175120.00%10100.00%029256751.50%28356949.74%28553553.27%9326591013272479233
19Penguins1010000023-11010000023-10000000000000.00024600132445723141264361341966143133.33%3166.67%029256751.50%28356949.74%28553553.27%9326591013272479233
20Phantoms11000000321000000000001100000032121.000369001324457151412643613417311195240.00%3166.67%029256751.50%28356949.74%28553553.27%9326591013272479233
21Rampage10001000431000000000001000100043121.00048120013244573314126436134301020176233.33%6350.00%029256751.50%28356949.74%28553553.27%9326591013272479233
22Reign11000000312110000003120000000000021.00036900132445720141264361342281485360.00%7185.71%029256751.50%28356949.74%28553553.27%9326591013272479233
23Rocket2010010025-31000010012-11010000013-210.2502240013244574114126436134389143111218.18%70100.00%029256751.50%28356949.74%28553553.27%9326591013272479233
24Sagnéens11000000303110000003030000000000021.000369011324457211412643613413213134250.00%40100.00%029256751.50%28356949.74%28553553.27%9326591013272479233
25Senators21100000743110000005141010000023-120.500713200013244573814126436134266232311654.55%9366.67%029256751.50%28356949.74%28553553.27%9326591013272479233
26Sound Tigers11000000211110000002110000000000021.00024600132445719141264361341077116233.33%10100.00%029256751.50%28356949.74%28553553.27%9326591013272479233
27Stars10000010211000000000001000001021121.00022400132445727141264361341751192150.00%3166.67%029256751.50%28356949.74%28553553.27%9326591013272479233
28Thunderbirds1010000003-31010000003-30000000000000.00000000132445714141264361341531311400.00%4175.00%029256751.50%28356949.74%28553553.27%9326591013272479233
29Wild11000000202000000000001100000020221.000246011324457201412643613485118200.00%30100.00%029256751.50%28356949.74%28553553.27%9326591013272479233
30Wolf Pack21001000743100010003211100000042241.000713200013244575014126436134311729289444.44%7271.43%029256751.50%28356949.74%28553553.27%9326591013272479233
31Wolves11000000211110000002110000000000021.00024600132445723141264361341871875240.00%40100.00%029256751.50%28356949.74%28553553.27%9326591013272479233
Total402111051118865232010801100373342011304011513219560.70088160248051324457792141264361346692315134861775430.51%1362780.15%029256751.50%28356949.74%28553553.27%9326591013272479233
_Since Last GM Reset402111051118865232010801100373342011304011513219560.70088160248051324457792141264361346692315134861775430.51%1362780.15%029256751.50%28356949.74%28553553.27%9326591013272479233
_Vs Conference23101002100454411347011002126-510630100024186250.5434582127021324457437141264361343661152823001092926.61%721776.39%029256751.50%28356949.74%28553553.27%9326591013272479233
_Vs Division97501100211745330010011101442010001073170.944214061001324457175141264361341435072123451431.11%21766.67%029256751.50%28356949.74%28553553.27%9326591013272479233

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
4056W48816024879266923151348605
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
40211151118865
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2010811003733
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2011340115132
Derniers 10 matchs
WLOTWOTL SOWSOL
820000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1775430.51%1362780.15%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
141264361341324457
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
29256751.50%28356949.74%28553553.27%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
9326591013272479233


Derniers matchs joués
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe visiteuse Score Équipe locale Score ST OT SO RI Lien
1 - 2025-10-052Monsters2Eagles1WXSommaire du match
2 - 2025-10-0621Wolf Pack2Monsters3WXSommaire du match
4 - 2025-10-0840Monsters1Griffins2LXXSommaire du match
5 - 2025-10-0951Monsters4Marlies3WSommaire du match
6 - 2025-10-1068Reign1Monsters3WSommaire du match
7 - 2025-10-1191Rocket2Monsters1LXSommaire du match
9 - 2025-10-13109Monsters3Americans0WSommaire du match
11 - 2025-10-15118Monsters1Checkers2LSommaire du match
12 - 2025-10-16130Sagnéens0Monsters3WSommaire du match
14 - 2025-10-18150Monsters2Admirals1WSommaire du match
15 - 2025-10-19160Sound Tigers1Monsters2WSommaire du match
17 - 2025-10-21184Barracuda2Monsters4WSommaire du match
18 - 2025-10-22192Monsters4Gulls2WSommaire du match
19 - 2025-10-23212Moose2Monsters1LSommaire du match
20 - 2025-10-24236Penguins3Monsters2LSommaire du match
21 - 2025-10-25244Monsters2Wild0WSommaire du match
23 - 2025-10-27266Bears2Monsters0LSommaire du match
25 - 2025-10-29278Monsters2Barracuda1WXSommaire du match
26 - 2025-10-30296Marlies4Monsters0LSommaire du match
27 - 2025-10-31314Monsters2Stars1WXXSommaire du match
28 - 2025-11-01327Americans1Monsters2WSommaire du match
30 - 2025-11-03349Monsters1Rocket3LSommaire du match
31 - 2025-11-04363Monsters4Heat1WSommaire du match
32 - 2025-11-05376Senators1Monsters5WSommaire du match
33 - 2025-11-06396Thunderbirds3Monsters0LSommaire du match
35 - 2025-11-08419Bruins1Monsters0LSommaire du match
36 - 2025-11-09430Monsters1Crunch0WSommaire du match
37 - 2025-11-10449Devils2Monsters4WSommaire du match
38 - 2025-11-11459Monsters2Devils1WSommaire du match
40 - 2025-11-13485Comets3Monsters2LSommaire du match
41 - 2025-11-14501Monsters4IceHogs2WSommaire du match
42 - 2025-11-15506Monsters4Wolf Pack2WSommaire du match
43 - 2025-11-16522Condors1Monsters2WSommaire du match
44 - 2025-11-17541Monsters3Comets2WXSommaire du match
46 - 2025-11-19557Crunch1Monsters0LSommaire du match
47 - 2025-11-20566Monsters2Senators3LSommaire du match
49 - 2025-11-22589Hockey Club 0Monsters1WSommaire du match
50 - 2025-11-23595Monsters3Phantoms2WSommaire du match
52 - 2025-11-25619Wolves1Monsters2WSommaire du match
53 - 2025-11-26628Monsters4Rampage3WXSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité50003000
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
0 0 - 0.00% 0$0$8000110

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,785,905$ 2,577,667$ 2,577,667$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 2,785,905$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 46,867$ 0$




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

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 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

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