Connexion

Monsters
GP: 72 | W: 49 | L: 17 | OTL: 6 | P: 104
GF: 186 | GA: 119 | PP%: 15.15% | PK%: 85.08%
DG: Paul-André Desrochers | Morale : 50 | Moyenne d’équipe : 59
Prochains matchs #1159 vs Wolf Pack
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Centre de jeu
Manchots
38-26-7, 83pts
3
FINAL
1 Monsters
49-17-6, 104pts
Team Stats
W2SéquenceSOL1
18-15-3Fiche domicile23-9-3
20-11-4Fiche domicile26-8-3
6-3-1Derniers 10 matchs6-3-1
2.23Buts par match 2.58
1.79Buts contre par match 1.65
14.23%Pourcentage en avantage numérique15.15%
83.49%Pourcentage en désavantage numérique85.08%
Rocket
32-31-8, 72pts
3
FINAL
2 Monsters
49-17-6, 104pts
Team Stats
W1SéquenceSOL1
16-16-2Fiche domicile23-9-3
16-15-6Fiche domicile26-8-3
4-5-1Derniers 10 matchs6-3-1
2.04Buts par match 2.58
2.55Buts contre par match 1.65
12.50%Pourcentage en avantage numérique15.15%
85.71%Pourcentage en désavantage numérique85.08%
Wolf Pack
38-28-6, 82pts
2024-03-28
Monsters
49-17-6, 104pts
Statistiques d’équipe
W1SéquenceSOL1
19-14-2Fiche domicile23-9-3
19-14-4Fiche visiteur26-8-3
6-2-210 derniers matchs6-3-1
2.56Buts par match 2.58
2.15Buts contre par match 2.58
16.53%Pourcentage en avantage numérique15.15%
86.47%Pourcentage en désavantage numérique85.08%
Chill
34-31-7, 75pts
2024-03-30
Monsters
49-17-6, 104pts
Statistiques d’équipe
W2SéquenceSOL1
19-15-3Fiche domicile23-9-3
15-16-4Fiche visiteur26-8-3
5-4-110 derniers matchs6-3-1
2.22Buts par match 2.58
2.28Buts contre par match 2.58
18.56%Pourcentage en avantage numérique15.15%
86.63%Pourcentage en désavantage numérique85.08%
Monsters
49-17-6, 104pts
2024-04-01
Monsters
41-26-5, 87pts
Statistiques d’équipe
SOL1SéquenceW2
23-9-3Fiche domicile19-15-2
26-8-3Fiche visiteur22-11-3
6-3-110 derniers matchs5-4-1
2.58Buts par match 2.26
1.65Buts contre par match 2.26
15.15%Pourcentage en avantage numérique17.35%
85.08%Pourcentage en désavantage numérique84.30%
Meneurs d'équipe
Buts
Marian Studenic
27
Passes
Alexander Alexeyev
42
Points
Vasily Podkolzin
55
Plus/Moins
Vasily Podkolzin
40
Victoires
Dustin Tokarski
48
Pourcentage d’arrêts
Dustin Tokarski
0.914

Statistiques d’équipe
Buts pour
186
2.58 GFG
Tirs pour
1431
19.88 Avg
Pourcentage en avantage numérique
15.2%
30 GF
Début de zone offensive
40.1%
Buts contre
119
1.65 GAA
Tirs contre
1317
18.29 Avg
Pourcentage en désavantage numérique
85.1%%
44 GA
Début de la zone défensive
39.0%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,866
Billets de saison300


Informations de la formation

Équipe Pro27
Équipe Mineure19
Limite contact 46 / 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
1Paul CotterXX100.00795880738277727248646966715650050680224900,000$
2Vasily PodkolzinXX100.00715479778182707250666766725750050680213925,000$
3Marian StudenicXX100.00654371726768656642636167675450050640231750,000$
4Carl HagelinX100.005743656563727463436154636086730506303411,250,000$
5Ben JonesX100.00655262716266656661646067665250050630232760,000$
6Oskar SteenXX100.00594467706165646458615759645350050610241809,168$
7Otto KoivulaXXX100.00685066607364636257605661605250050600241700,000$
8Olle Lycksell (R)X100.00564070695762626342645857635150050600232837,000$
9Daniel Torgersson (R)XX100.00614071626560616241565754605050050580203867,500$
10Justin Sourdif (R)X100.00574066665960606141615556615050050580203847,500$
11Alexander Pashin (R)XXX100.00554470685560605940545453605050050570203826,667$
12Aleksandr Kisakov (R)X100.00564069685557575840545554605050050560193859,167$
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$
3Grant MismashX100.00594470646262605340515153565250050550231825,000$
4Steven KampferX100.00544066646168696440625760626660050610341750,000$
5Daniil Zhuravlyov (R)X100.00564068685759585640545360595150050580223600,000$
6Hardy Haman Aktell (R)X100.0030403939652929303929293935323005038N0243900,000$
MOYENNE D’ÉQUIPE100.0061486667666462614357556161545105060
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
1Jon Gillies100.0070696579696665626768706558050630282700,000$
2Filip Larsson (R)100.0039485671424246433839254438050440241750,000$
Rayé
1Tyler Parsons100.0041475670373948453940274438050430251620,000$
MOYENNE D’ÉQUIPE100.005055597349495350484941514505050
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
1Vasily PodkolzinMonsters (Col)LW/RW7226295540280771351706112115.29%5161422.425382617421363036452.93%71600010.68280005103
2Paul CotterMonsters (Col)C/LW72232750356351251311504512315.33%6144720.1156112517210131584154.07%140000000.6937001743
3Alexander AlexeyevMonsters (Col)D72542473234075605918398.47%67170223.6421012331690220251100%000000.5500000413
4Marian StudenicMonsters (Col)LW/RW72271946333007987138329319.57%3128717.884592215700051347545.83%9600000.7115000594
5Ben JonesMonsters (Col)C72123143233209512013635788.82%6116316.162810191550000503155.28%107100000.7400000514
6Aliaksei ProtasColoradoLW/RW59152439284037711264011811.90%11133322.591672013101152426156.47%8500010.5906000333
7Lucas CarlssonMonsters (Col)D72102535296201386775334913.33%67163922.766410381590111219300%000000.4300000334
8Matthew RobertsonMonsters (Col)D72622283124092532772022.22%40121216.841013160000101100%000000.4600000213
9Vladislav KolyachonokMonsters (Col)D72324271812027594515336.67%47148220.60134211520001217100%000000.3600000113
10Olle LycksellMonsters (Col)RW72169251440356081196219.75%688412.29000090000534035.14%7400100.5700000413
11Mark BorowieckiMonsters (Col)D72618242315553015555192910.91%65143919.99224251500000165120%000000.3300001226
12Brayden PachalMonsters (Col)D725172232635125523672513.89%42119016.53000226011154100%000000.3700001041
13Oskar SteenMonsters (Col)C/RW72614202418043527622667.89%3110615.3715612156000021158.57%7000000.3600000101
14Carl HagelinMonsters (Col)LW72313161118029487018594.29%395313.240114490000461058.06%6200000.3400000110
15Otto KoivulaMonsters (Col)C/LW/RW7248121632086746122336.56%583811.6400018000040161.88%66100000.2900000112
16Justin SourdifMonsters (Col)C7275126180415843122916.28%45828.0900000000004148.40%46900000.4100000003
17Alexander PashinMonsters (Col)C/LW/RW724610618026223183212.90%35848.1100001000001158.62%2900000.3400000020
18Daniel TorgerssonMonsters (Col)LW/RW725169220362644113011.36%36378.85000000001151045.71%3500000.1900000021
19Aleksandr KisakovMonsters (Col)RW13022140928030%01078.2800000000000037.50%800000.3700000000
Statistiques d’équipe totales ou en moyenne129618333651941164115147612321431424104212.79%3862120816.363053832511693369232023461854.33%477600120.49626003444647
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 TokarskiColorado69481650.9141.55414621210712390000.63622690832
2Jon GilliesMonsters (Col)41110.9101.95215007780000.6673369000
Statistiques d’équipe totales ou en moyenne73491760.9131.5743612121141317000257269832


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$98,446$0$0$No859,167$859,167$
Alexander AlexeyevMonsters (Col)D221999-11-15No213 Lbs6 ft4NoNoNoNo2Pro & Farm863,333$98,924$0$0$No863,333$Lien
Alexander PashinMonsters (Col)C/LW/RW202002-01-28Yes154 Lbs5 ft8NoNoNoNo3Pro & Farm826,667$94,722$0$0$No826,667$826,667$
Ben JonesMonsters (Col)C231999-02-26No187 Lbs6 ft0NoNoNoNo2Pro & Farm760,000$87,083$0$0$No760,000$Lien
Brayden PachalMonsters (Col)D231999-08-23No205 Lbs6 ft1NoNoNoNo2Pro & Farm900,000$103,125$0$0$No900,000$Lien
Carl Hagelin (contrat à 1 volet)Monsters (Col)LW341988-08-23No185 Lbs6 ft0NoNoYesYes1Pro & Farm1,250,000$143,229$350,000$40,104$NoLien
Curtis HallMonsters (Col)C222000-04-26Yes196 Lbs6 ft3NoNoNoNo2Pro & Farm925,000$105,990$0$0$No925,000$Lien
Daniel TorgerssonMonsters (Col)LW/RW202002-01-26Yes198 Lbs6 ft3NoNoNoNo3Pro & Farm867,500$99,401$0$0$No867,500$867,500$
Daniil ZhuravlyovMonsters (Col)D222000-04-08Yes163 Lbs6 ft0NoNoNoNo3Pro & Farm600,000$68,750$0$0$No600,000$600,000$Lien
Filip LarssonMonsters (Col)G241998-08-17Yes181 Lbs6 ft2NoNoYesYes1Pro & Farm750,000$85,938$0$0$NoLien
Grant MismashMonsters (Col)LW231999-02-19No185 Lbs6 ft0NoNoNoNo1Pro & Farm825,000$94,531$0$0$NoLien
Hardy Haman Aktell (contrat à 1 volet)Monsters (Col)D241998-07-04Yes198 Lbs6 ft3YesNoYesYes3Pro & Farm900,000$103,125$0$0$No900,000$900,000$Lien
Jon Gillies (contrat à 1 volet)Monsters (Col)G281994-01-22No223 Lbs6 ft6NoNoYesYes2Pro & Farm700,000$80,208$0$0$No700,000$Lien
Justin SourdifMonsters (Col)C202002-03-24Yes172 Lbs5 ft11NoNoNoNo3Pro & Farm847,500$97,109$0$0$No847,500$847,500$
Lucas CarlssonMonsters (Col)D251997-07-05No190 Lbs6 ft0NoNoYesYes1Pro & Farm800,000$91,667$0$0$NoLien
Marian StudenicMonsters (Col)LW/RW231998-10-28No181 Lbs6 ft1NoNoNoNo1Pro & Farm750,000$85,938$0$0$NoLien
Mark Borowiecki (contrat à 1 volet)Monsters (Col)D331989-07-12No207 Lbs6 ft1NoNoYesYes2Pro & Farm1,411,111$161,690$511,111$58,565$No1,411,111$Lien
Matthew RobertsonMonsters (Col)D212001-03-09Yes201 Lbs6 ft4NoNoNoNo3Pro & Farm797,500$91,380$0$0$No797,500$797,500$Lien
Olle LycksellMonsters (Col)RW231999-08-24Yes163 Lbs5 ft10NoNoNoNo2Pro & Farm837,000$95,906$0$0$No837,000$Lien
Oskar SteenMonsters (Col)C/RW241998-03-09No187 Lbs5 ft9NoNoYesYes1Pro & Farm809,168$92,717$0$0$NoLien
Otto KoivulaMonsters (Col)C/LW/RW241998-09-01No225 Lbs6 ft5NoNoYesYes1Pro & Farm700,000$80,208$0$0$NoLien
Paul CotterMonsters (Col)C/LW221999-11-16No212 Lbs6 ft2NoNoNoNo4Pro & Farm900,000$103,125$0$0$No900,000$900,000$900,000$Lien
Steven Kampfer (contrat à 1 volet)Monsters (Col)D341988-09-24No198 Lbs5 ft11NoNoYesYes1Pro & Farm750,000$85,938$0$0$NoLien
Ty RonningMonsters (Col)RW241997-10-20No163 Lbs5 ft9NoNoYesYes2Pro & Farm750,833$86,033$0$0$No750,833$Lien
Tyler ParsonsMonsters (Col)G251997-09-17No185 Lbs6 ft1NoNoYesYes1Pro & Farm620,000$71,042$0$0$NoLien
Vasily PodkolzinMonsters (Col)LW/RW212001-06-24No190 Lbs6 ft1NoNoNoNo3Pro & Farm925,000$105,990$0$0$No925,000$925,000$Lien
Vladislav KolyachonokMonsters (Col)D212001-05-26Yes194 Lbs6 ft1NoNoNoNo2Pro & Farm795,000$91,094$0$0$No795,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2723.85189 Lbs6 ft12.04841,473$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Vasily PodkolzinPaul CotterMarian Studenic40122
2Carl HagelinBen JonesOskar Steen30122
3Daniel TorgerssonOtto KoivulaOlle Lycksell20122
4Alexander PashinJustin SourdifAleksandr Kisakov10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alexander AlexeyevMark Borowiecki40122
2Lucas CarlssonVladislav Kolyachonok30122
3Matthew RobertsonBrayden Pachal20122
4Alexander AlexeyevMark Borowiecki10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Vasily PodkolzinPaul CotterMarian Studenic60122
2Carl HagelinBen JonesOskar Steen40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alexander AlexeyevMark Borowiecki60122
2Lucas CarlssonVladislav Kolyachonok40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Vasily PodkolzinPaul Cotter60122
2Marian StudenicBen Jones40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alexander AlexeyevMark Borowiecki60122
2Lucas CarlssonVladislav Kolyachonok40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Vasily Podkolzin60122Alexander AlexeyevMark Borowiecki60122
2Paul Cotter40122Lucas CarlssonVladislav Kolyachonok40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Vasily PodkolzinPaul Cotter60122
2Marian StudenicBen Jones40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alexander AlexeyevMark Borowiecki60122
2Lucas CarlssonVladislav Kolyachonok40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Vasily PodkolzinPaul CotterMarian StudenicAlexander AlexeyevMark Borowiecki
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Vasily PodkolzinPaul CotterMarian StudenicAlexander AlexeyevMark Borowiecki
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Olle Lycksell, Otto Koivula, Daniel TorgerssonOlle Lycksell, Otto KoivulaDaniel Torgersson
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Matthew Robertson, Brayden Pachal, Lucas CarlssonMatthew RobertsonBrayden Pachal, Lucas Carlsson
Tirs de pénalité
Vasily Podkolzin, Paul Cotter, Marian Studenic, Ben Jones, Carl Hagelin
Gardien
#1 : Jon Gillies, #2 : Filip Larsson


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
1Admirals32000010734210000106331100000010161.00071219017445628465154224784259203654400.00%16287.50%01055191455.12%1010186554.16%53099753.16%186113211600504903464
2Baby Hawks402010011013-32010000146-22010100067-130.3751020300074456286551542247842791551841218.33%20575.00%01055191455.12%1010186554.16%53099753.16%186113211600504903464
3Bears21000010853110000004221000001043141.00081321007445628335154224784238818388112.50%9277.78%11055191455.12%1010186554.16%53099753.16%186113211600504903464
4Bruins21100000541110000003121010000023-120.500581300744562833515422478422571037900.00%50100.00%01055191455.12%1010186554.16%53099753.16%186113211600504903464
5Cabaret Lady Mary Ann2110000034-1110000002111010000013-220.5003690074456284251542247842381616339111.11%7185.71%01055191455.12%1010186554.16%53099753.16%186113211600504903464
6Caroline2010010024-21010000001-11000010023-110.25024600744562833515422478423392433900.00%10190.00%01055191455.12%1010186554.16%53099753.16%186113211600504903464
7Chiefs40200011710-32010000135-22010001045-130.375710170174456287151542247842782842831715.88%19478.95%11055191455.12%1010186554.16%53099753.16%186113211600504903464
8Chill2200000010460000000000022000000104641.000101929017445628495154224784245818333133.33%9277.78%01055191455.12%1010186554.16%53099753.16%186113211600504903464
9Comets32100000532211000002201100000031240.667510150074456286651542247842371321691218.33%8187.50%01055191455.12%1010186554.16%53099753.16%186113211600504903464
10Cougars22000000413110000002111100000020241.00047110174456282751542247842501216474125.00%7185.71%01055191455.12%1010186554.16%53099753.16%186113211600504903464
11Crunch22000000624110000002021100000042241.000612180174456285751542247842331214364125.00%70100.00%01055191455.12%1010186554.16%53099753.16%186113211600504903464
12Heat33000000945220000007341100000021161.00091524007445628775154224784263152467400.00%12191.67%01055191455.12%1010186554.16%53099753.16%186113211600504903464
13Jayhawks43100000177102110000063322000000114760.7501732490074456281385154224784269172410611436.36%12191.67%01055191455.12%1010186554.16%53099753.16%186113211600504903464
14Las Vegas21000001550110000004311000000112-130.750591400744562846515422478422781238400.00%6350.00%01055191455.12%1010186554.16%53099753.16%186113211600504903464
15Manchots2110000045-11010000013-21100000032120.5004812007445628335154224784243123047100.00%14471.43%01055191455.12%1010186554.16%53099753.16%186113211600504903464
16Marlies2020000004-41010000001-11010000003-300.000000007445628335154224784235101641200.00%70100.00%01055191455.12%1010186554.16%53099753.16%186113211600504903464
17Minnesota22000000716110000005051100000021141.00071320017445628415154224784232416338225.00%8187.50%01055191455.12%1010186554.16%53099753.16%186113211600504903464
18Monarchs33000000725110000003032200000042261.000714210174456285751542247842561534721000.00%17194.12%11055191455.12%1010186554.16%53099753.16%186113211600504903464
19Monsters11000000312110000003120000000000021.00036900744562817515422478421971227400.00%50100.00%01055191455.12%1010186554.16%53099753.16%186113211600504903464
20Oceanics211000003301010000001-11100000032120.5003690074456284251542247842411514404125.00%7185.71%01055191455.12%1010186554.16%53099753.16%186113211600504903464
21Oil Kings11000000312000000000001100000031221.000358007445628185154224784217512282150.00%50100.00%01055191455.12%1010186554.16%53099753.16%186113211600504903464
22Phantoms22000000624110000004131100000021141.000610160074456283251542247842431314427228.57%7185.71%01055191455.12%1010186554.16%53099753.16%186113211600504903464
23Rocket2000000246-21000000123-11000000123-120.5004711007445628365154224784247142436600.00%11190.91%01055191455.12%1010186554.16%53099753.16%186113211600504903464
24Sags32100000844211000004401100000040440.667815230174456286551542247842461022474250.00%11463.64%01055191455.12%1010186554.16%53099753.16%186113211600504903464
25Seattle31101000642110000003122010100033040.667612180174456284851542247842451326509222.22%13284.62%01055191455.12%1010186554.16%53099753.16%186113211600504903464
26Senators2110000034-1110000002111010000013-220.5003580074456282951542247842331114495120.00%7357.14%01055191455.12%1010186554.16%53099753.16%186113211600504903464
27Sound Tigers22000000734110000004131100000032141.000713200074456283451542247842441226443133.33%10190.00%01055191455.12%1010186554.16%53099753.16%186113211600504903464
28Spiders21100000541110000004221010000012-120.5005914007445628315154224784228158346116.67%40100.00%01055191455.12%1010186554.16%53099753.16%186113211600504903464
29Stars330000001129110000004222200000070761.00011193002744562863515422478424919145611436.36%70100.00%01055191455.12%1010186554.16%53099753.16%186113211600504903464
30Thunder22000000835110000006331100000020241.000813210174456285651542247842401319574125.00%7185.71%01055191455.12%1010186554.16%53099753.16%186113211600504903464
31Wolf Pack11000000312000000000001100000031221.000347007445628135154224784225101615200.00%80100.00%01055191455.12%1010186554.16%53099753.16%186113211600504903464
Total7244170213518611967352290001390553537228021229664321040.7221863365220127445628143151542247842131738664314761983015.15%2954485.08%31055191455.12%1010186554.16%53099753.16%186113211600504903464
_Since Last GM Reset7244170213518611967352290001390553537228021229664321040.7221863365220127445628143151542247842131738664314761983015.15%2954485.08%31055191455.12%1010186554.16%53099753.16%186113211600504903464
_Vs Conference392190211599673219115000034631152010402112533617540.69299181280077445628828515422478426972003367991221915.57%1522285.53%11055191455.12%1010186554.16%53099753.16%186113211600504903464
_Vs Division2171000026540259310000122175124000001432320160.3816511918405744562846951542247842393106179435661421.21%821482.93%11055191455.12%1010186554.16%53099753.16%186113211600504903464

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
72104SOL1186336522143113173866431476012
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
7244172135186119
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3522900139055
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3722821229664
Derniers 10 matchs
WLOTWOTL SOWSOL
630001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1983015.15%2954485.08%3
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
515422478427445628
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
1055191455.12%1010186554.16%53099753.16%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
186113211600504903464


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 - 2023-10-1429Monsters4Sags0AWSommaire 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 - 2023-12-09417Phantoms1Monsters4BWSommaire du match
63 - 2023-12-11431Heat1Monsters4BWSommaire du match
65 - 2023-12-13445Crunch0Monsters2BWSommaire du match
68 - 2023-12-16462Monsters3Oceanics2AWSommaire du match
69 - 2023-12-17478Sags3Monsters1BLSommaire du match
71 - 2023-12-19492Monsters5Baby Hawks4AWXSommaire du match
73 - 2023-12-21507Senators1Monsters2BWSommaire du match
75 - 2023-12-23525Jayhawks2Monsters1BLSommaire du match
79 - 2023-12-27537Monsters5Jayhawks2AWSommaire du match
81 - 2023-12-29552Monsters1Chiefs0AWXXSommaire du match
83 - 2023-12-31571Sags1Monsters3BWSommaire du match
85 - 2024-01-02582Sound Tigers1Monsters4BWSommaire du match
87 - 2024-01-04593Monsters3Stars0AWSommaire du match
89 - 2024-01-06606Cabaret Lady Mary Ann1Monsters2BWSommaire du match
91 - 2024-01-08624Bruins1Monsters3BWSommaire du match
93 - 2024-01-10637Las Vegas3Monsters4BWSommaire du match
96 - 2024-01-13663Monsters0Marlies3ALSommaire du match
98 - 2024-01-15678Monsters2Rocket3ALXXSommaire du match
99 - 2024-01-16682Monsters1Senators3ALSommaire du match
101 - 2024-01-18692Monsters2Bruins3ALSommaire du match
103 - 2024-01-20707Monsters2Phantoms1AWSommaire du match
107 - 2024-01-24742Bears2Monsters4BWSommaire du match
109 - 2024-01-26757Monarchs0Monsters3BWSommaire du match
119 - 2024-02-05781Monsters3Wolf Pack1AWSommaire du match
120 - 2024-02-06787Monsters1Spiders2ALSommaire du match
122 - 2024-02-08799Monsters2Caroline3ALXSommaire du match
124 - 2024-02-10809Monsters1Cabaret Lady Mary Ann3ALSommaire du match
127 - 2024-02-13828Monsters4Bears3AWXXSommaire du match
129 - 2024-02-15842Monsters2Thunder0AWSommaire du match
132 - 2024-02-18864Jayhawks1Monsters5BWSommaire du match
134 - 2024-02-20881Comets1Monsters2BWSommaire du match
136 - 2024-02-22890Monsters2Cougars0AWSommaire du match
138 - 2024-02-24908Marlies1Monsters0BLSommaire du match
141 - 2024-02-27936Stars2Monsters4BWSommaire du match
143 - 2024-02-29949Monsters1Baby Hawks3ALSommaire du match
145 - 2024-03-02959Monsters5Chill0AWSommaire du match
147 - 2024-03-04979Baby Hawks3Monsters2BLSommaire du match
149 - 2024-03-06991Cougars1Monsters2BWSommaire du match
151 - 2024-03-081006Minnesota0Monsters5BWSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
155 - 2024-03-121039Monsters2Heat1AWSommaire du match
156 - 2024-03-131044Monsters3Comets1AWSommaire du match
159 - 2024-03-161072Monsters3Oil Kings1AWSommaire du match
162 - 2024-03-191089Monsters3Chiefs5ALSommaire du match
165 - 2024-03-221111Monsters1Monsters3BWSommaire du match
167 - 2024-03-241125Manchots3Monsters1BLSommaire du match
169 - 2024-03-261144Rocket3Monsters2BLXXSommaire du match
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
Assistance67,00433,291
Assistance PCT95.72%95.12%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
6 2866 - 95.52% 97,526$3,413,406$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,622,972$ 1,770,867$ 1,770,867$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,223$ 1,622,972$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
585,155$ 22 9,223$ 202,906$




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