Connexion

Monsters
GP: 4 | W: 1 | L: 1 | OTL: 2 | P: 4
GF: 8 | GA: 12 | PP%: 14.29% | PK%: 60.00%
DG: Trent Zeigler | Morale : 48 | Moyenne d’équipe : 58
Prochains matchs #70 vs Rocket
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Centre de jeu
Wolves
2-1-1, 5pts
3
FINAL
2 Monsters
1-1-2, 4pts
Team Stats
OTL1SéquenceL1
0-1-1Fiche domicile0-0-2
2-0-0Fiche domicile1-1-0
2-1-1Derniers 10 matchs1-1-2
2.25Buts par match 2.00
3.00Buts contre par match 3.00
25.00%Pourcentage en avantage numérique14.29%
66.67%Pourcentage en désavantage numérique60.00%
Monsters
1-1-2, 4pts
4
FINAL
7 Senators
3-0-1, 7pts
Team Stats
L1SéquenceW2
0-0-2Fiche domicile2-0-0
1-1-0Fiche domicile1-0-1
1-1-2Derniers 10 matchs3-0-1
2.00Buts par match 4.50
3.00Buts contre par match 2.50
14.29%Pourcentage en avantage numérique46.67%
60.00%Pourcentage en désavantage numérique84.62%
Rocket
2-1-1, 5pts
Jour 7
Monsters
1-1-2, 4pts
Statistiques d’équipe
W1SéquenceL1
1-0-1Fiche domicile0-0-2
1-1-0Fiche visiteur1-1-0
2-1-110 derniers matchs1-1-2
0.75Buts par match 2.00
0.75Buts contre par match 2.00
16.67%Pourcentage en avantage numérique14.29%
66.67%Pourcentage en désavantage numérique60.00%
IceHogs
2-1-1, 5pts
Jour 9
Monsters
1-1-2, 4pts
Statistiques d’équipe
W1SéquenceL1
0-1-1Fiche domicile0-0-2
2-0-0Fiche visiteur1-1-0
2-1-110 derniers matchs1-1-2
2.00Buts par match 2.00
2.00Buts contre par match 2.00
33.33%Pourcentage en avantage numérique14.29%
87.50%Pourcentage en désavantage numérique60.00%
Monsters
1-1-2, 4pts
Jour 10
Comets
1-2-0, 2pts
Statistiques d’équipe
L1SéquenceW1
0-0-2Fiche domicile1-1-0
1-1-0Fiche visiteur0-1-0
1-1-210 derniers matchs1-2-0
2.00Buts par match 1.67
3.00Buts contre par match 1.67
14.29%Pourcentage en avantage numérique28.57%
60.00%Pourcentage en désavantage numérique40.00%
Meneurs d'équipe
Buts
Isak Rosen
4
Passes
Cole Guttman
3
Points
Isak Rosen
5
Plus/Moins
Isak Rosen
2
Victoires
Jacob Ingham
1
Pourcentage d’arrêts
Jacob Ingham
0.851

Statistiques d’équipe
Buts pour
8
2.00 GFG
Tirs pour
52
13.00 Avg
Pourcentage en avantage numérique
14.3%
1 GF
Début de zone offensive
28.7%
Buts contre
12
3.00 GAA
Tirs contre
74
18.50 Avg
Pourcentage en désavantage numérique
60.0%%
4 GA
Début de la zone défensive
43.4%
Informations de l'équipe

Directeur généralTrent Zeigler
EntraîneurJim Montgomery
DivisionDivision 2
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,064
Billets de saison1,500


Informations de la formation

Équipe Pro23
Équipe Mineure18
Limite contact 41 / 100
Espoirs62


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
1Isak Rosen (R)X98.0075679472678185695064736665464668516602211,450,000$
2Glenn GawdinX98.0075747770748287678065676662454566496502821,240,000$
3Cole GuttmanXXX98.007165857065818666806466636045456550640261950,000$
4Brian Halonen (R)X100.007574787174778163505271646545456549630261996,000$
5Egor Sokolov (R)X100.0084809268808187615056616858444466516302531,495,000$
6Owen Beck (R)X99.0084459981715591596558555825454562486102131,333,000$
7Tristan Broz (R)X100.0077748566745352617655636560444463495902331,350,000$
8Givani SmithX100.0080996375814546612550556825616260495902721,136,000$
9Martin ChromiakX100.007870956770565561505662655944446449590231820,000$
10Trevor Connelly (R)X100.0062636080633832635062615858444460485701931,300,000$
11Jacob PerreaultX100.0072717464716164525053466044444454485502331,106,000$
12Adam RaskaXX100.0064666064666772505047475645444453485402431,315,000$
13Tucker RobertsonX100.0074678963675658506347486146444454495402231,256,000$
14Valtteri PulliX98.008680998080353156255642683745455449600242800,000$
15Billy SweezeyX100.0073747163747381462537395937444452455702911,000,000$
16Ethan FrischX99.007569886369515348253942613945455048550252800,000$
17Ben ZlotyX100.0073688580683532492543396037444452485502311,000,000$
18Tyson FeistX100.006969688069353346253739573744444949530242800,000$
19Leon Muggli (R)X100.0075659980653230412528395937444448385201931,261,000$
Rayé
1Connor Clattenburg (R)X100.0083769980763230445538446442444452465202031,265,000$
2Kyle Jackson (R)XXX100.0058722580723331445538445142444446464902331,467,000$
MOYENNE D’ÉQUIPE99.52747180727155585548505362474545574858
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
1Jacob Ingham98.004440508645904649918145444460536102531,250,000$
2Connor Hughes100.005240509355545659585830444454505702911,000,000$
Rayé
MOYENNE D’ÉQUIPE99.0048405090507251547570384444575259
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jim Montgomery80808080808080CAN5111,600,000$


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’équipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Isak RosenMonsters (CBJ)RW441522017132330.77%19523.8000025000070161.90%2140011.0511000010
2Cole GuttmanMonsters (CBJ)C/LW/RW41342406511249.09%29423.7000005000140065.63%3220000.8412000100
3Glenn GawdinMonsters (CBJ)C42131007593422.22%29223.1510145000080066.67%920000.6502000001
4Valtteri PulliMonsters (CBJ)D40222003104220%810225.670110500008000%036000.3900000000
5Owen BeckMonsters (CBJ)C4011-300472010%08020.2001115000030066.67%630000.2500000000
6Brian HalonenMonsters (CBJ)LW40110408131120%18621.6400005000030075.00%3201000.2322000000
7Egor SokolovMonsters (CBJ)LW4011-3175661100%07819.5200004000000051.52%3300000.2602100000
8Tyson FeistMonsters (CBJ)D4011120340000%16416.240000200000000%000000.3100000000
9Ethan FrischMonsters (CBJ)D4011-220283010%210325.830000400007000%020000.1900000000
10Adam RaskaMonsters (CBJ)LW/RW4000-120920000%26516.28000010000300100.00%10300000000001
11Jacob PerreaultMonsters (CBJ)RW4000-100361000%04812.140000000000000%00000000000000
12Tristan BrozMonsters (CBJ)C4000000534010%14210.5100000000100061.54%130200011000000
13Tucker RobertsonMonsters (CBJ)C4000000000000%061.510000000000000%00000001000000
14Givani SmithMonsters (CBJ)RW4000020300000%0133.430000000000000%00100000000000
15Martin ChromiakMonsters (CBJ)RW4000000000000%000.060000000000000%00000011000000
16Billy SweezeyMonsters (CBJ)D4000-100141110%39724.310000600009000%00100000000000
17Leon MuggliMonsters (CBJ)D4000000020000%0358.770000000001000%00000000000000
18Trevor ConnellyMonsters (CBJ)LW4000-100120010%0256.320000000000000%00000001000000
19Ben ZlotyMonsters (CBJ)D4000-100152100%38220.640001400004000%02000000000000
Statistiques d’équipe totales ou en moyenne7671219-5355638952132013.46%26121415.991238550002630163.95%1471814010.31613100112
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
1Jacob InghamMonsters (CBJ)41120.8512.6425001117434000.5381340010
Statistiques d’équipe totales ou en moyenne41120.8512.6425001117434001340010


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
Adam RaskaMonsters (CBJ)LW/RW242001-09-25CZENo185 Lbs5 ft10NoNoN/ANoNo32025-10-22FalseFalsePro & Farm1,315,000$1,256,295$0$0$No1,315,000$1,315,000$-------1,315,000$1,315,000$-------NoNo-------Lien
Ben ZlotyMonsters (CBJ)D232002-02-24ABNo187 Lbs6 ft0NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm1,000,000$955,357$0$0$No---------------------------Lien
Billy SweezeyMonsters (CBJ)D291996-02-06USANo204 Lbs6 ft1NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm1,000,000$955,357$0$0$No---------------------------Lien
Brian HalonenMonsters (CBJ)LW261999-01-11USAYes207 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm996,000$951,536$0$0$No---------------------------Lien
Cole GuttmanMonsters (CBJ)C/LW/RW261999-04-06USANo181 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm950,000$907,589$0$0$No---------------------------Lien
Connor ClattenburgMonsters (CBJ)C202005-05-02ONYes205 Lbs6 ft2NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,265,000$1,208,527$0$0$No1,265,000$1,265,000$-------1,265,000$1,265,000$-------NoNo-------Lien
Connor HughesMonsters (CBJ)G291996-09-10SWINo231 Lbs6 ft4NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm1,000,000$955,357$0$0$No---------------------------Lien
Egor SokolovMonsters (CBJ)LW252000-06-07RUSYes217 Lbs6 ft3NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,495,000$1,428,259$0$0$No1,495,000$1,495,000$-------1,495,000$1,495,000$-------NoNo-------Lien
Ethan FrischMonsters (CBJ)D252000-10-29USANo192 Lbs5 ft11NoNoFree AgentNoNo22024-10-16FalseFalsePro & Farm800,000$764,286$0$0$No800,000$--------800,000$--------No--------Lien
Givani SmithMonsters (CBJ)RW271998-02-27CANNo214 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm1,136,000$1,085,286$0$0$No1,136,000$--------1,136,000$--------No--------Lien / Lien NHL
Glenn GawdinMonsters (CBJ)C281997-03-25CANNo201 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm1,240,000$1,184,643$0$0$No1,240,000$--------1,240,000$--------No--------Lien / Lien NHL
Isak RosenMonsters (CBJ)RW222003-03-15SWEYes180 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm1,450,000$1,385,268$0$0$No---------------------------Lien
Jacob InghamMonsters (CBJ)G252000-06-10ONTNo205 Lbs6 ft5NoNoN/ANoNo32025-12-08FalseFalsePro & Farm1,250,000$1,194,196$0$0$No1,250,000$1,250,000$-------1,250,000$1,250,000$-------NoNo-------Lien
Jacob PerreaultMonsters (CBJ)RW232002-04-15CANNo196 Lbs6 ft0NoNoN/ANoNo32025-10-17FalseFalsePro & Farm1,106,000$1,056,625$0$0$No1,106,000$1,106,000$-------1,106,000$1,106,000$-------NoNo-------Lien
Kyle JacksonMonsters (CBJ)C/LW/RW232002-10-17CANYes192 Lbs6 ft2NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,467,000$1,401,509$0$0$No1,467,000$1,467,000$-------1,467,000$1,467,000$-------NoNo-------Lien
Leon MuggliMonsters (CBJ)D192006-07-09SWIYes173 Lbs6 ft1NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,261,000$1,204,705$0$0$No1,261,000$1,261,000$-------1,261,000$1,261,000$-------NoNo-------Lien
Martin ChromiakMonsters (CBJ)RW232002-08-20SVKNo190 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm820,000$783,393$0$0$No---------------------------Lien
Owen BeckMonsters (CBJ)C212004-02-03CANYes199 Lbs6 ft0NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,333,000$1,273,491$0$0$No1,333,000$1,333,000$-------1,333,000$1,333,000$-------NoNo-------Lien
Trevor ConnellyMonsters (CBJ)LW192006-02-28USAYes165 Lbs6 ft1NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,300,000$1,241,964$0$0$No1,300,000$1,300,000$-------1,300,000$1,300,000$-------NoNo-------Lien
Tristan BrozMonsters (CBJ)C232002-10-10USAYes205 Lbs6 ft0NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,350,000$1,289,732$0$0$No1,350,000$1,350,000$-------1,350,000$1,350,000$-------NoNo-------Lien
Tucker RobertsonMonsters (CBJ)C222003-06-22CANNo189 Lbs5 ft11NoNoN/ANoNo32025-10-22FalseFalsePro & Farm1,256,000$1,199,929$0$0$No1,256,000$1,256,000$-------1,256,000$1,256,000$-------NoNo-------Lien
Tyson FeistMonsters (CBJ)D242001-01-14BCNo181 Lbs6 ft2NoNoFree AgentNoNo22024-10-16FalseFalsePro & Farm800,000$764,286$0$0$No800,000$--------800,000$--------No--------Lien
Valtteri PulliMonsters (CBJ)D242001-03-13FINNo209 Lbs6 ft6NoNoFree AgentNoNo22024-10-16FalseFalsePro & Farm800,000$764,286$0$0$No800,000$--------800,000$--------No--------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2323.91196 Lbs6 ft12.171,147,391$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Cole GuttmanEgor SokolovIsak Rosen40122
2Owen BeckBrian HalonenGlenn Gawdin30122
3Glenn GawdinCole GuttmanIsak Rosen20122
4Glenn GawdinBrian HalonenIsak Rosen10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Billy SweezeyEthan Frisch40122
2Ben ZlotyValtteri Pulli30122
3Valtteri PulliEthan Frisch20122
4Ethan FrischValtteri Pulli10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Isak RosenCole GuttmanBrian Halonen60122
2Glenn GawdinEgor SokolovOwen Beck40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Valtteri PulliBilly Sweezey60122
2Ben ZlotyEthan Frisch40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Isak RosenGlenn Gawdin60122
2Cole GuttmanBrian Halonen40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Billy SweezeyValtteri Pulli60122
2Ethan FrischBen Zloty40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Glenn Gawdin60122Valtteri PulliEthan Frisch60122
2Isak Rosen40122Billy SweezeyTyson Feist40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Isak RosenGlenn Gawdin60122
2Brian HalonenCole Guttman40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Billy SweezeyBen Zloty60122
2Valtteri PulliEthan Frisch40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Glenn GawdinIsak RosenCole GuttmanBilly SweezeyValtteri Pulli
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Glenn GawdinIsak RosenCole GuttmanBilly SweezeyValtteri Pulli
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Glenn Gawdin, Isak Rosen, Brian HalonenGlenn Gawdin, Isak RosenGlenn Gawdin
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Valtteri Pulli, Ethan Frisch, Billy SweezeyValtteri PulliEthan Frisch, Valtteri Pulli
Tirs de pénalité
Cole Guttman, Glenn Gawdin, Egor Sokolov, Brian Halonen, Isak Rosen
Gardien
#1 : Jacob Ingham, #2 : Connor Hughes


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
1Rocket200001102201000010012-11000001010130.7502240101662361927131794292150.00%2150.00%0314175.61%336253.23%304075.00%6419784710753
2Senators1010000047-3000000000001010000047-300.00046100001661461927134212419400.00%220.00%0314175.61%336253.23%304075.00%6419784710753
3Wolves1000000123-11000000123-10000000000010.5002460001661561927131552715100.00%6183.33%0314175.61%336253.23%304075.00%6419784710753
Total40100111812-42000010135-22010001057-240.50081220010166526192713742635637114.29%10460.00%0314175.61%336253.23%304075.00%6419784710753
_Since Last GM Reset40100111812-42000010135-22010001057-240.50081220010166526192713742635637114.29%10460.00%0314175.61%336253.23%304075.00%6419784710753
_Vs Conference40100111812-42000010135-22010001057-240.50081220010166526192713742635637114.29%10460.00%0314175.61%336253.23%304075.00%6419784710753

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
44L181220527426356301
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
4010111812
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
200010135
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
201001057
Derniers 10 matchs
WLOTWOTL SOWSOL
110101
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
7114.29%10460.00%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
61927130166
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
314175.61%336253.23%304075.00%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
6419784710753


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
16Rocket2Monsters1LXSommaire du match
221Monsters1Rocket0WXXSommaire du match
443Wolves3Monsters2LXXSommaire du match
551Monsters4Senators7LSommaire du match
770Rocket-Monsters-
997IceHogs-Monsters-
10103Monsters-Comets-
11126Monsters-Wolves-
12136Barracuda-Monsters-
13148Monsters-Barracuda-
15170Rocket-Monsters-
16184Monsters-Stars-
17197Monsters-Senators-
18213Thunderbirds-Monsters-
19231IceHogs-Monsters-
20245Monsters-Islanders-
22258Monsters-Comets-
23271Canucks-Monsters-
24289Moose-Monsters-
26305Monsters-Silver Knights-
27320Wild-Monsters-
29335Monsters-Canucks-
30352Heat-Monsters-
31375Wolves-Monsters-
32384Monsters-Griffins-
33398Monsters-Condors-
34413Reign-Monsters-
35433Monsters-Bears-
36442Monsters-Crunch-
37458Rocket-Monsters-
39475Senators-Monsters-
40494Monsters-Checkers-
41507Condors-Monsters-
42526Monsters-Senators-
43537Monsters-Thunderbirds-
44550Admirals-Monsters-
45566Wolf Pack-Monsters-
46584Monsters-Islanders-
47598Monsters-Moose-
48611Penguins-Monsters-
49628Bruins-Monsters-
51657Islanders-Monsters-
53674Monsters-Bruins-
54689Silver Knights-Monsters-
55708Monsters-Stars-
56719Checkers-Monsters-
57735Monsters-Reign-
59751Americans-Monsters-
60769Monsters-Penguins-
61780Gulls-Monsters-
63803Monsters-Heat-
64812IceHogs-Monsters-
65824Monsters-Barracuda-
67844Comets-Monsters-
68856Monsters-Americans-
69871Monsters-Marlies-
70884Crunch-Monsters-
72905Barracuda-Monsters-
73915Monsters-Rocket-
74927Monsters-Barracuda-
75942Marlies-Monsters-
77964Griffins-Monsters-
79975Monsters-Wolf Pack-
80997Bears-Monsters-
811003Monsters-Phantoms-
821021Monsters-Roadrunners-
831036Bears-Monsters-
851056Griffins-Monsters-
861065Monsters-Gulls-
881083Monsters-Admirals-
891098Roadrunners-Monsters-
901116Monsters-Wolves-
911126Monsters-Americans-
921139Phantoms-Monsters-
941158Wolves-Monsters-
961180Monsters-Eagles-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
971194Comets-Monsters-
981201Monsters-IceHogs-
991220Eagles-Monsters-
1001231Monsters-Wild-
1011239Monsters-IceHogs-
1021246Monsters-Wolf Pack-
1041264Thunderbirds-Monsters-
1061290Senators-Monsters-
1081311Stars-Monsters-
1101321Monsters-Comets-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance2,6291,498
Assistance PCT65.73%74.90%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
41 2064 - 68.78% 85,292$170,583$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
189,240$ 2,639,000$ 2,639,000$ 1,600,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
23,562$ 117,810$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
3,496,952$ 107 37,848$ 4,049,736$




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