Connexion

Monsters
GP: 26 | W: 18 | L: 5 | OTL: 3 | P: 39
GF: 67 | GA: 42 | PP%: 13.43% | PK%: 84.69%
DG: Paul-André Desrochers | Morale : 50 | Moyenne d’équipe : 60
Prochains matchs #417 vs Phantoms
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Centre de jeu
Admirals
12-11-3, 27pts
2
FINAL
3 Monsters
18-5-3, 39pts
Team Stats
SOL2SéquenceL1
7-6-1Fiche domicile6-4-2
5-5-2Fiche domicile12-1-1
5-3-2Derniers 10 matchs8-2-0
1.81Buts par match 2.58
2.12Buts contre par match 1.62
8.45%Pourcentage en avantage numérique13.43%
90.54%Pourcentage en désavantage numérique84.69%
Oceanics
22-2-1, 45pts
1
FINAL
0 Monsters
18-5-3, 39pts
Team Stats
W3SéquenceL1
11-2-1Fiche domicile6-4-2
11-0-0Fiche domicile12-1-1
9-1-0Derniers 10 matchs8-2-0
3.00Buts par match 2.58
1.36Buts contre par match 1.62
15.49%Pourcentage en avantage numérique13.43%
90.00%Pourcentage en désavantage numérique84.69%
Phantoms
11-11-4, 26pts
2023-12-09
Monsters
18-5-3, 39pts
Statistiques d’équipe
W2SéquenceL1
6-4-3Fiche domicile6-4-2
5-7-1Fiche visiteur12-1-1
4-4-210 derniers matchs8-2-0
1.96Buts par match 2.58
2.00Buts contre par match 2.58
10.53%Pourcentage en avantage numérique13.43%
86.42%Pourcentage en désavantage numérique84.69%
Heat
1-23-2, 4pts
2023-12-11
Monsters
18-5-3, 39pts
Statistiques d’équipe
L1SéquenceL1
0-10-2Fiche domicile6-4-2
1-13-0Fiche visiteur12-1-1
0-9-110 derniers matchs8-2-0
1.85Buts par match 2.58
4.31Buts contre par match 2.58
10.67%Pourcentage en avantage numérique13.43%
83.33%Pourcentage en désavantage numérique84.69%
Crunch
13-12-2, 28pts
2023-12-13
Monsters
18-5-3, 39pts
Statistiques d’équipe
L1SéquenceL1
7-4-1Fiche domicile6-4-2
6-8-1Fiche visiteur12-1-1
4-5-110 derniers matchs8-2-0
2.63Buts par match 2.58
2.81Buts contre par match 2.58
10.00%Pourcentage en avantage numérique13.43%
82.86%Pourcentage en désavantage numérique84.69%
Meneurs d'équipe
Buts
Vasily Podkolzin
12
Passes
Alexander Alexeyev
17
Points
Aliaksei Protas
25
Plus/Moins
Vasily Podkolzin
19
Victoires
Dustin Tokarski
18
Pourcentage d’arrêts
Dustin Tokarski
0.914

Statistiques d’équipe
Buts pour
67
2.58 GFG
Tirs pour
511
19.65 Avg
Pourcentage en avantage numérique
13.4%
9 GF
Début de zone offensive
40.8%
Buts contre
42
1.62 GAA
Tirs contre
454
17.46 Avg
Pourcentage en désavantage numérique
84.7%%
15 GA
Début de la zone défensive
38.4%
Informations de l'équipe

Directeur généralPaul-André Desrochers
DivisionNord
ConférenceOuest
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,889
Billets de saison300


Informations de la formation

Équipe Pro29
Équipe Mineure18
Limite contact 47 / 50
Espoirs15


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 moyen
1Aliaksei Protas (R)XX100.00694787719382737356706467695650050680212795,000$
2Paul CotterXX100.00795880738277727248646966715650050680224900,000$
3Vasily PodkolzinXX100.00715479778182707250666766725750050680213925,000$
4Marian StudenicXX100.00654371726768656642636167675450050640231750,000$
5Carl HagelinX100.005743656563727463436154636086730506303411,250,000$
6Ben JonesX100.00655262716266656661646067665250050630232760,000$
7Oskar SteenXX100.00594467706165646458615759645350050610241809,168$
8Otto KoivulaXXX100.00685066607364636257605661605250050600241700,000$
9Olle Lycksell (R)X100.00564070695762626342645857635150050600232837,000$
10Daniel Torgersson (R)XX100.00614071626560616241565754605050050580203867,500$
11Justin Sourdif (R)X100.00574066665960606141615556615050050580203847,500$
12Alexander Pashin (R)XXX100.00554470685560605940545453605050050570203826,667$
13Alexander AlexeyevX100.00634776718379666740645870655650050670222863,333$
14Mark BorowieckiX100.009399347379576054254243856069690506603321,411,111$
15Lucas CarlssonX100.00654370736870677040656569695550050660251800,000$
16Vladislav Kolyachonok (R)X100.00645170727069646540615668655150050640212795,000$
17Brayden PachalX100.00646255676664636240565366605152050610232900,000$
18Matthew Robertson (R)X100.00625366666862626340595464615050050610213797,500$
Rayé
1Ty RonningX100.00524371695364626141545651625350050570242750,833$
2Curtis Hall (R)X100.00634571606762605650515154565150050560222925,000$
3Aleksandr Kisakov (R)X100.00564069685557575840545554605050050560193859,167$
4Grant MismashX100.00594470646262605340515153565250050550231825,000$
5Steven KampferX100.00544066646168696440625760626660050610341750,000$
6Daniil Zhuravlyov (R)X100.00564068685759585640545360595150050580223600,000$
7Hardy Haman Aktell (R)X100.0030403939652929303929293935323005038N0243900,000$
MOYENNE D’ÉQUIPE100.0062486767676563624458566162545105061
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 moyen
1Dustin Tokarski100.007476786975747572737674756805068N0332620,000$
2Jon Gillies100.0070696579696665626768706558050630282700,000$
Rayé
1Filip Larsson (R)100.0039485671424246433839254438050440241750,000$
2Tyler Parsons100.0041475670373948453940274438050430251620,000$
MOYENNE D’ÉQUIPE100.005660647256555956545649575105055
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
1Aliaksei ProtasMonsters (Col)LW/RW261114251920133555205320.00%658822.650335590112975152.63%3800010.8504000322
2Vasily PodkolzinMonsters (Col)LW/RW261213251980254369275217.39%458322.4530310592024982250.83%24200010.8614000431
3Alexander AlexeyevMonsters (Col)D26217191812026231561213.33%2561523.68033758011082000%000000.6200000111
4Marian StudenicMonsters (Col)LW/RW261081810160272453113618.87%045717.582249510002382163.33%3000000.7901000341
5Ben JonesMonsters (Col)C264131710803959486248.33%341515.96033551000061153.97%36500000.8200000301
6Lucas CarlssonMonsters (Col)D2631215192204727286810.71%2260123.142131155011172100%000000.5000000120
7Paul CotterMonsters (Col)C/LW26591416255434141183612.20%151119.670117580000380150.79%50800000.5513001112
8Matthew RobertsonMonsters (Col)D26561110403423112445.45%1844617.1710112000038100%000000.4900000212
9Vladislav KolyachonokMonsters (Col)D2601111400123157120%1453020.41011651000072000%000000.4100000001
10Brayden PachalMonsters (Col)D263581125553241711017.65%1743416.690000601108100%000000.3700001031
11Oskar SteenMonsters (Col)C/RW26257106015183011186.67%240815.71101451000001168.18%2200000.3400000000
12Carl HagelinMonsters (Col)LW261563601117277243.70%132812.64011040000170073.91%2300000.3700000000
13Olle LycksellMonsters (Col)RW2631422010232451512.50%331912.29000020000251034.62%2600000.2500000011
14Justin SourdifMonsters (Col)C2631428013261541020.00%22118.1500000000002046.15%18200000.3800000002
15Mark BorowieckiMonsters (Col)D260333480891515670%2251019.62000551000055000%000000.1200000001
16Otto KoivulaMonsters (Col)C/LW/RW2602221203132226100%330111.5800003000020063.20%25000000.1300000001
17Alexander PashinMonsters (Col)C/LW/RW2620228088112818.18%02128.1600000000000036.36%1100000.1900000010
18Daniel TorgerssonMonsters (Col)LW/RW2600021001711152110%02118.1500000000000054.55%110000000000000
Statistiques d’équipe totales ou en moyenne468661251911622221050247251114735012.92%143768816.439152470567246965617753.28%170800020.50212002181917
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
1Dustin TokarskiMonsters (Col)2618530.9141.48157804394540000.54511260210
Statistiques d’équipe totales ou en moyenne2618530.9141.481578043945400011260210


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 Ballotage forcé Waiver Possible Contrat Type Salaire actuel Salaire moyen restantPlafond 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 10Lien
Aleksandr KisakovMonsters (Col)RW192002-11-01Yes150 Lbs5 ft10NoNoNoNo3Pro & Farm859,167$595,152$0$0$No859,167$859,167$
Alexander AlexeyevMonsters (Col)D221999-11-15No213 Lbs6 ft4NoNoNoNo2Pro & Farm863,333$598,038$0$0$No863,333$Lien
Alexander PashinMonsters (Col)C/LW/RW202002-01-28Yes154 Lbs5 ft8NoNoNoNo3Pro & Farm826,667$572,639$0$0$No826,667$826,667$
Aliaksei ProtasMonsters (Col)LW/RW212001-01-06Yes225 Lbs6 ft6NoNoNoNo2Pro & Farm795,000$550,703$0$0$No795,000$Lien
Ben JonesMonsters (Col)C231999-02-26No187 Lbs6 ft0NoNoNoNo2Pro & Farm760,000$526,458$0$0$No760,000$Lien
Brayden PachalMonsters (Col)D231999-08-23No205 Lbs6 ft1NoNoNoNo2Pro & Farm900,000$623,438$0$0$No900,000$Lien
Carl Hagelin (contrat à 1 volet)Monsters (Col)LW341988-08-23No185 Lbs6 ft0NoNoYesYes1Pro & Farm1,250,000$865,885$350,000$242,448$NoLien
Curtis HallMonsters (Col)C222000-04-26Yes196 Lbs6 ft3NoNoNoNo2Pro & Farm925,000$640,755$0$0$No925,000$Lien
Daniel TorgerssonMonsters (Col)LW/RW202002-01-26Yes198 Lbs6 ft3NoNoNoNo3Pro & Farm867,500$600,924$0$0$No867,500$867,500$
Daniil ZhuravlyovMonsters (Col)D222000-04-08Yes163 Lbs6 ft0NoNoNoNo3Pro & Farm600,000$415,625$0$0$No600,000$600,000$Lien
Dustin Tokarski (contrat à 1 volet)Monsters (Col)G331989-09-16No198 Lbs6 ft0YesNoYesYes2Pro & Farm620,000$429,479$0$0$No620,000$Lien
Filip LarssonMonsters (Col)G241998-08-17Yes181 Lbs6 ft2NoNoYesYes1Pro & Farm750,000$519,531$0$0$NoLien
Grant MismashMonsters (Col)LW231999-02-19No185 Lbs6 ft0NoNoNoNo1Pro & Farm825,000$571,484$0$0$NoLien
Hardy Haman Aktell (contrat à 1 volet)Monsters (Col)D241998-07-04Yes198 Lbs6 ft3YesNoYesYes3Pro & Farm900,000$623,438$0$0$No900,000$900,000$Lien
Jon Gillies (contrat à 1 volet)Monsters (Col)G281994-01-22No223 Lbs6 ft6NoNoYesYes2Pro & Farm700,000$484,896$0$0$No700,000$Lien
Justin SourdifMonsters (Col)C202002-03-24Yes172 Lbs5 ft11NoNoNoNo3Pro & Farm847,500$587,070$0$0$No847,500$847,500$
Lucas CarlssonMonsters (Col)D251997-07-05No190 Lbs6 ft0NoNoYesYes1Pro & Farm800,000$554,167$0$0$NoLien
Marian StudenicMonsters (Col)LW/RW231998-10-28No181 Lbs6 ft1NoNoNoNo1Pro & Farm750,000$519,531$0$0$NoLien
Mark Borowiecki (contrat à 1 volet)Monsters (Col)D331989-07-12No207 Lbs6 ft1NoNoYesYes2Pro & Farm1,411,111$977,488$511,111$354,051$No1,411,111$Lien
Matthew RobertsonMonsters (Col)D212001-03-09Yes201 Lbs6 ft4NoNoNoNo3Pro & Farm797,500$552,435$0$0$No797,500$797,500$Lien
Olle LycksellMonsters (Col)RW231999-08-24Yes163 Lbs5 ft10NoNoNoNo2Pro & Farm837,000$579,797$0$0$No837,000$Lien
Oskar SteenMonsters (Col)C/RW241998-03-09No187 Lbs5 ft9NoNoYesYes1Pro & Farm809,168$560,517$0$0$NoLien
Otto KoivulaMonsters (Col)C/LW/RW241998-09-01No225 Lbs6 ft5NoNoYesYes1Pro & Farm700,000$484,896$0$0$NoLien
Paul CotterMonsters (Col)C/LW221999-11-16No212 Lbs6 ft2NoNoNoNo4Pro & Farm900,000$623,438$0$0$No900,000$900,000$900,000$Lien
Steven Kampfer (contrat à 1 volet)Monsters (Col)D341988-09-24No198 Lbs5 ft11NoNoYesYes1Pro & Farm750,000$519,531$0$0$NoLien
Ty RonningMonsters (Col)RW241997-10-20No163 Lbs5 ft9NoNoYesYes2Pro & Farm750,833$520,108$0$0$No750,833$Lien
Tyler ParsonsMonsters (Col)G251997-09-17No185 Lbs6 ft1NoNoYesYes1Pro & Farm620,000$429,479$0$0$NoLien
Vasily PodkolzinMonsters (Col)LW/RW212001-06-24No190 Lbs6 ft1NoNoNoNo3Pro & Farm925,000$640,755$0$0$No925,000$925,000$Lien
Vladislav KolyachonokMonsters (Col)D212001-05-26Yes194 Lbs6 ft1NoNoNoNo2Pro & Farm795,000$550,703$0$0$No795,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2924.07191 Lbs6 ft12.03832,234$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Vasily PodkolzinPaul CotterAliaksei Protas40122
2Marian StudenicBen JonesOskar Steen30122
3Carl HagelinOtto KoivulaOlle Lycksell20122
4Daniel TorgerssonJustin SourdifAlexander Pashin10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alexander AlexeyevLucas Carlsson40122
2Mark BorowieckiVladislav Kolyachonok30122
3Brayden PachalMatthew Robertson20122
4Alexander AlexeyevLucas Carlsson10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Vasily PodkolzinPaul CotterAliaksei Protas60122
2Marian StudenicBen JonesOskar Steen40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alexander AlexeyevLucas Carlsson60122
2Mark BorowieckiVladislav Kolyachonok40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Vasily PodkolzinAliaksei Protas60122
2Paul CotterMarian Studenic40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alexander AlexeyevLucas Carlsson60122
2Mark BorowieckiVladislav Kolyachonok40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Vasily Podkolzin60122Alexander AlexeyevLucas Carlsson60122
2Aliaksei Protas40122Mark BorowieckiVladislav Kolyachonok40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Vasily PodkolzinAliaksei Protas60122
2Paul CotterMarian Studenic40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alexander AlexeyevLucas Carlsson60122
2Mark BorowieckiVladislav Kolyachonok40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Vasily PodkolzinPaul CotterAliaksei ProtasAlexander AlexeyevLucas Carlsson
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Vasily PodkolzinPaul CotterAliaksei ProtasAlexander AlexeyevLucas Carlsson
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Carl Hagelin, Otto Koivula, Olle LycksellCarl Hagelin, Otto KoivulaOlle Lycksell
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Brayden Pachal, Matthew Robertson, Mark BorowieckiBrayden PachalMatthew Robertson, Mark Borowiecki
Tirs de pénalité
Vasily Podkolzin, Aliaksei Protas, Paul Cotter, Marian Studenic, Carl Hagelin
Gardien
#1 : Dustin Tokarski, #2 : Jon Gillies


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
1Admirals32000010734210000106331100000010161.00071219012718203461761511752159203654400.00%16287.50%038369754.95%34465652.44%18335551.55%682486574181324168
2Baby Hawks1000000123-11000000123-10000000000010.5002460027182035176151175212641916200.00%5180.00%038369754.95%34465652.44%18335551.55%682486574181324168
3Caroline1010000001-11010000001-10000000000000.0000000027182031217615117521134618100.00%30100.00%038369754.95%34465652.44%18335551.55%682486574181324168
4Chiefs2010000135-22010000135-20000000000010.2503580027182033917615117521291116331218.33%6266.67%138369754.95%34465652.44%18335551.55%682486574181324168
5Chill11000000541000000000001100000054121.000591400271820330176151175212451217200.00%6266.67%038369754.95%34465652.44%18335551.55%682486574181324168
6Comets1010000001-11010000001-10000000000000.000000002718203221761511752173714300.00%10100.00%038369754.95%34465652.44%18335551.55%682486574181324168
7Crunch11000000422000000000001100000042221.00048120027182032317615117521197617200.00%30100.00%038369754.95%34465652.44%18335551.55%682486574181324168
8Heat11000000321110000003210000000000021.0003580027182033317615117521236431100.00%2150.00%038369754.95%34465652.44%18335551.55%682486574181324168
9Jayhawks11000000624000000000001100000062421.0006121800271820339176151175211730295240.00%000%038369754.95%34465652.44%18335551.55%682486574181324168
10Las Vegas1000000112-1000000000001000000112-110.5001230027182032517615117521165615200.00%30100.00%038369754.95%34465652.44%18335551.55%682486574181324168
11Manchots11000000321000000000001100000032121.00036900271820320176151175212071627000%7185.71%038369754.95%34465652.44%18335551.55%682486574181324168
12Minnesota11000000211000000000001100000021121.000246002718203151761511752118312155120.00%6183.33%038369754.95%34465652.44%18335551.55%682486574181324168
13Monarchs22000000422000000000002200000042241.0004812002718203301761511752136112440700.00%12191.67%138369754.95%34465652.44%18335551.55%682486574181324168
14Oceanics1010000001-11010000001-10000000000000.0000000027182032017615117521134415300.00%20100.00%038369754.95%34465652.44%18335551.55%682486574181324168
15Seattle31101000642110000003122010100033040.667612180127182034817615117521451326509222.22%13284.62%038369754.95%34465652.44%18335551.55%682486574181324168
16Sharks11000000404000000000001100000040421.00048120127182032317615117521154425000%20100.00%038369754.95%34465652.44%18335551.55%682486574181324168
17Sound Tigers11000000321000000000001100000032121.00036900271820314176151175212171226100.00%5180.00%038369754.95%34465652.44%18335551.55%682486574181324168
18Spiders11000000422110000004220000000000021.000471100271820317176151175211682192150.00%10100.00%038369754.95%34465652.44%18335551.55%682486574181324168
19Stars11000000404000000000001100000040421.000471101271820327176151175211770125240.00%000%038369754.95%34465652.44%18335551.55%682486574181324168
20Thunder11000000633110000006330000000000021.00061016002718203231761511752120111029100.00%5180.00%038369754.95%34465652.44%18335551.55%682486574181324168
Total2616501013674225125400012272251411101001402020390.750671251920427182035111761511752145414322250267913.43%981584.69%238369754.95%34465652.44%18335551.55%682486574181324168
_Since Last GM Reset2616501013674225125400012272251411101001402020390.750671251920427182035111761511752145414322250267913.43%981584.69%238369754.95%34465652.44%18335551.55%682486574181324168
_Vs Conference14640100331238723000021113-274101001201010170.607315990022718203288176151175212306610225047817.02%42783.33%138369754.95%34465652.44%18335551.55%682486574181324168
_Vs Division82100000221664010000059-4420000001771040.25022416301271820317517615117521144376313734617.65%25676.00%138369754.95%34465652.44%18335551.55%682486574181324168

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2639L16712519251145414322250204
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
2616510136742
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
125400122722
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
1411110014020
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
67913.43%981584.69%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
176151175212718203
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
38369754.95%34465652.44%18335551.55%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
682486574181324168


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
2 - 2023-10-117Monsters2Monarchs1AWSommaire du match
5 - 2023-10-1429Monsters4Sharks0AWSommaire du match
8 - 2023-10-1746Monsters2Seattle3ALSommaire du match
10 - 2023-10-1962Baby Hawks3Monsters2BLXXSommaire du match
12 - 2023-10-2176Caroline1Monsters0BLSommaire du match
15 - 2023-10-2490Monsters3Sound Tigers2AWSommaire du match
17 - 2023-10-26105Monsters3Manchots2AWSommaire du match
20 - 2023-10-29126Monsters4Crunch2AWSommaire du match
23 - 2023-11-01143Chiefs3Monsters2BLSommaire du match
26 - 2023-11-04173Monsters1Las Vegas2ALXXSommaire du match
29 - 2023-11-07188Spiders2Monsters4BWSommaire du match
31 - 2023-11-09201Seattle1Monsters3BWSommaire du match
33 - 2023-11-11219Chiefs2Monsters1BLXXSommaire du match
35 - 2023-11-13228Monsters1Seattle0AWXSommaire du match
37 - 2023-11-15240Admirals1Monsters3BWSommaire du match
40 - 2023-11-18264Monsters4Stars0AWSommaire du match
42 - 2023-11-20275Monsters5Chill4AWSommaire du match
44 - 2023-11-22292Comets1Monsters0BLSommaire du match
46 - 2023-11-24306Monsters2Minnesota1AWSommaire du match
47 - 2023-11-25315Heat2Monsters3BWSommaire du match
49 - 2023-11-27324Thunder3Monsters6BWSommaire du match
52 - 2023-11-30350Monsters6Jayhawks2AWSommaire du match
54 - 2023-12-02366Monsters1Admirals0AWSommaire du match
55 - 2023-12-03373Monsters2Monarchs1AWSommaire du match
57 - 2023-12-05386Admirals2Monsters3BWXXSommaire du match
59 - 2023-12-07402Oceanics1Monsters0BLSommaire du match
61 - 2023-12-09417Phantoms-Monsters-
63 - 2023-12-11431Heat-Monsters-
65 - 2023-12-13445Crunch-Monsters-
68 - 2023-12-16462Monsters-Oceanics-
69 - 2023-12-17478Sharks-Monsters-
71 - 2023-12-19492Monsters-Baby Hawks-
73 - 2023-12-21507Senators-Monsters-
75 - 2023-12-23525Jayhawks-Monsters-
79 - 2023-12-27537Monsters-Jayhawks-
81 - 2023-12-29552Monsters-Chiefs-
83 - 2023-12-31571Sharks-Monsters-
85 - 2024-01-02582Sound Tigers-Monsters-
87 - 2024-01-04593Monsters-Stars-
89 - 2024-01-06606Cabaret Lady Mary Ann-Monsters-
91 - 2024-01-08624Bruins-Monsters-
93 - 2024-01-10637Las Vegas-Monsters-
96 - 2024-01-13663Monsters-Marlies-
98 - 2024-01-15678Monsters-Rocket-
99 - 2024-01-16682Monsters-Senators-
101 - 2024-01-18692Monsters-Bruins-
103 - 2024-01-20707Monsters-Phantoms-
107 - 2024-01-24742Bears-Monsters-
109 - 2024-01-26757Monarchs-Monsters-
119 - 2024-02-05781Monsters-Wolf Pack-
120 - 2024-02-06787Monsters-Spiders-
122 - 2024-02-08799Monsters-Caroline-
124 - 2024-02-10809Monsters-Cabaret Lady Mary Ann-
127 - 2024-02-13828Monsters-Bears-
129 - 2024-02-15842Monsters-Thunder-
132 - 2024-02-18864Jayhawks-Monsters-
134 - 2024-02-20881Comets-Monsters-
136 - 2024-02-22890Monsters-Cougars-
138 - 2024-02-24908Marlies-Monsters-
141 - 2024-02-27936Stars-Monsters-
143 - 2024-02-29949Monsters-Baby Hawks-
145 - 2024-03-02959Monsters-Chill-
147 - 2024-03-04979Baby Hawks-Monsters-
149 - 2024-03-06991Cougars-Monsters-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
151 - 2024-03-081006Minnesota-Monsters-
155 - 2024-03-121039Monsters-Heat-
156 - 2024-03-131044Monsters-Comets-
159 - 2024-03-161072Monsters-Oil Kings-
162 - 2024-03-191089Monsters-Chiefs-
165 - 2024-03-221111Monsters-Monsters-
167 - 2024-03-241125Manchots-Monsters-
169 - 2024-03-261144Rocket-Monsters-
171 - 2024-03-281159Wolf Pack-Monsters-
173 - 2024-03-301169Chill-Monsters-
175 - 2024-04-011181Monsters-Monsters-
178 - 2024-04-041207Monsters-Minnesota-
179 - 2024-04-051214Monsters-Oil Kings-
181 - 2024-04-071236Stars-Monsters-
183 - 2024-04-091248Minnesota-Monsters-
187 - 2024-04-131272Oceanics-Monsters-
188 - 2024-04-141284Monsters-Las Vegas-
192 - 2024-04-181310Oil Kings-Monsters-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance23,19511,476
Assistance PCT96.65%95.63%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
29 2889 - 96.31% 98,397$1,180,758$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
568,583$ 1,850,367$ 1,850,367$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,637$ 568,583$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
2,853,498$ 133 9,637$ 1,281,721$




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