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Monsters
GP: 14 | W: 7 | L: 7
GF: 44 | GA: 44 | PP%: 23.26% | PK%: 77.08%
DG: Vincent Attic | Morale : 40 | Moyenne d’équipe : 63

Centre de jeu
Senators
16-11-0, 32pts
3
1 Monsters
7-7-0, 14pts
Team Stats
W3SéquenceL3
10-4-0Fiche domicile4-3-0
6-7-0Fiche domicile3-4-0
8-1-1Derniers 10 matchs6-4-0
3.26Buts par match 3.14
3.19Buts contre par match 3.14
25.00%Pourcentage en avantage numérique23.26%
79.07%Pourcentage en désavantage numérique77.08%
Monsters
7-7-0, 14pts
3
5 Senators
16-11-0, 32pts
Team Stats
L3SéquenceW3
4-3-0Fiche domicile10-4-0
3-4-0Fiche domicile6-7-0
6-4-0Derniers 10 matchs8-1-1
3.14Buts par match 3.26
3.14Buts contre par match 3.19
23.26%Pourcentage en avantage numérique25.00%
77.08%Pourcentage en désavantage numérique79.07%
Meneurs d'équipe
Adam EdstromButs
Adam Edstrom
6
Carl GrundstromPasses
Carl Grundstrom
12
Carl GrundstromPoints
Carl Grundstrom
17
Ville OttavainenPlus/Moins
Ville Ottavainen
4
Nikita TolopiloVictoires
Nikita Tolopilo
7
Nikita TolopiloPourcentage d’arrêts
Nikita Tolopilo
0.904

Statistiques d’équipe
Buts pour
44
3.14 GFG
Tirs pour
606
43.29 Avg
Pourcentage en avantage numérique
23.3%
10 GF
Début de zone offensive
46.0%
Buts contre
44
3.14 GAA
Tirs contre
484
34.57 Avg
Pourcentage en désavantage numérique
77.1%%
11 GA
Début de la zone défensive
38.2%
Informations de l'équipe

Directeur généralVincent Attic
EntraîneurMike Vellucci
DivisionMetropolitan Division
ConférenceEastern Conference
Capitaine
Assistant #1Pierre Engvall
Assistant #2Carl Grundstrom


Informations de l’aréna

Capacité5,000
Assistance4,973
Billets de saison3,750


Informations de la formation

Équipe Pro24
Équipe Mineure20
Limite contact 44 / 70
Espoirs27


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
1Pierre Engvall (A)XX100.006438927291828667586663656471730406703011,250,000$
2Emil BemstromXX100.00653986697284856872666761686769040660271925,000$
3Adam EdstromX100.00865386629979806365606164626567040650252925,000$
4Carl Grundstrom (A)XX100.008435906674768064566062636169710406502841,499,999$
5Kyle MacLeanX100.00724089647677906373626065616668040640271925,000$
6Axel Jonsson-FjallbyX100.007037936475798562586059616367690406302821,100,000$
7Carson MeyerX100.007139736470847863566261606368700406302941,499,999$
8Brennan OthmannX100.00694073657384826458626163656264040630232925,000$
9Carl BerglundX100.00733894588276705664575359546567040610262925,000$
10Michael MilneX100.00723875596982795653585755596364040600233925,000$
11Sam Lipkin (R)X100.00704083577971725654555558566264040600233925,000$
12Parker WotherspoonX100.007354836576868163306858715068700406502941,499,999$
13Ville OttavainenX100.00814184649182866330665761496365040650242925,000$
14Albert JohanssonX100.00663881656883846430635665516466040630251925,000$
15Matthew RobertsonX100.007642746189858459306056624964660406302531,499,999$
16Riley StillmanX100.007562666082697659306057655167690406202821,100,000$
17Ville HeinolaX100.006139846371827164306358605064660406202531,499,999$
Rayé
1Gavin Hayes (R)X100.00643794577381685458565557536163040590223925,000$
2Josh DaviesX100.005943635369656252555150545061630405502231,499,999$
3Travis DermottX100.006835886574837363306255795271690406402931,499,999$
4Tobias BjornfotX100.006838876074797559305855615064660406102531,499,999$
5Charlie Wright (R)X100.00643695577361635530565054456264040580223925,000$
MOYENNE D’ÉQUIPE100.0071418362777978614861586256656704062
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
1Nikita Tolopilo100.00778581987675777675777665730406702641,499,999$
2Cal Petersen100.0075837877747375747375747285040660311925,000$
Rayé
MOYENNE D’ÉQUIPE100.007684808875747675747675697904067
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mike Vellucci64656970888258USA594500,000$


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
1Carl GrundstromMonsters (CBJ)LW/RW1451217060481749193210.20%433223.7724610360001500033.33%2700001.0200000010
2Albert JohanssonMonsters (CBJ)D145813-16033233282115.63%3132823.442241835000140100%000000.7900000011
3Emil BemstromMonsters (CBJ)C/RW14391202014528220473.66%733724.1114520370004531059.26%54000000.7100000011
4Parker WotherspoonMonsters (CBJ)D142911315527213411255.88%2539728.380331132000037000%000000.5500100100
5Adam EdstromMonsters (CBJ)C146410010049438119387.41%328720.5131413320000233057.18%38300000.7000000201
6Pierre EngvallMonsters (CBJ)LW/RW143710-1203355525485.45%834824.870001235000031055.56%1800000.5700000100
7Ville OttavainenMonsters (CBJ)D1418942002315196175.26%1431622.601121133000028000%100000.5700000000
8Axel Jonsson-FjallbyMonsters (CBJ)LW144480006235914466.78%529020.760117320002250060.00%3000000.5500000010
9Ville HeinolaMonsters (CBJ)D14358-2801625216414.29%1731022.1910112000016000%000000.5100000100
10Carson MeyerMonsters (CBJ)RW14437-112021255418467.41%632223.020111034000000052.17%2300000.4300000000
11Kyle MacLeanMonsters (CBJ)C1443726015314115359.76%424317.3900013000091056.32%27700000.5800000010
12Brennan OthmannMonsters (CBJ)LW1434722011244315336.98%219914.2400000000000047.37%1900000.7000000010
13Michael MilneMonsters (CBJ)LW1402211602552611200%125718.3800000000000055.56%900000.1600000000
14Carl BerglundMonsters (CBJ)C14112-240251092611.11%1319614.0200000000000045.65%4600000.2000000000
Statistiques d’équipe totales ou en moyenne1964479123510953163496051894187.27%140416721.2610172711431700082887056.74%137300000.5900100563
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
1Nikita TolopiloMonsters (CBJ)147700.9043.13844004445600000140201
2Cal PetersenMonsters (CBJ)10001.0000400002800000014000
Statistiques d’équipe totales ou en moyenne157700.9092.98885004448400001414201


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 Plafond 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 EdstromMonsters (CBJ)C252000-10-12SWENo241 Lbs201 CMNoNoProspectNoNo22024-05-23FalseFalsePro & Farm925,000$0$0$No925,000$--------925,000$--------No--------Lien / Lien NHL
Albert JohanssonMonsters (CBJ)D252001-01-04SWENo168 Lbs183 CMNoNoN/ANoNo1FalseFalsePro & Farm925,000$0$0$No---------------------------Lien / Lien NHL
Axel Jonsson-FjallbyMonsters (CBJ)LW281998-02-10SWENo189 Lbs185 CMNoNoN/AYesNo2FalseFalsePro & Farm1,100,000$0$0$No1,100,000$--------1,100,000$--------No--------Lien / Lien NHL
Brennan OthmannMonsters (CBJ)LW232003-01-05CANNo192 Lbs183 CMNoNoProspectNoNo22024-05-23FalseFalsePro & Farm925,000$0$0$No925,000$--------925,000$--------No--------Lien / Lien NHL
Cal PetersenMonsters (CBJ)G311994-10-19USANo185 Lbs188 CMNoNoTrade2024-10-03YesNo1FalseFalsePro & Farm925,000$0$0$No---------------------------Lien / Lien NHL
Carl BerglundMonsters (CBJ)C262000-01-16SWENo207 Lbs188 CMNoNoProspectNoNo22024-05-23FalseFalsePro & Farm925,000$0$0$No925,000$--------925,000$--------No--------Lien / Lien NHL
Carl GrundstromMonsters (CBJ)LW/RW281997-12-01SWENo200 Lbs183 CMNoNoAssign ManuallyYesNo42024-07-17FalseFalsePro & Farm1,499,999$0$0$No1,499,999$1,499,999$1,499,999$------1,499,999$1,499,999$1,499,999$------NoNoNo------Lien / Lien NHL
Carson MeyerMonsters (CBJ)RW291997-08-18USANo184 Lbs180 CMNoNoAssign ManuallyYesNo42024-07-22FalseFalsePro & Farm1,499,999$0$0$No1,499,999$1,499,999$1,499,999$------1,499,999$1,499,999$1,499,999$------NoNoNo------Lien / Lien NHL
Charlie WrightMonsters (CBJ)D222003-10-22CANYes179 Lbs185 CMNoNoProspectNoNo32025-06-01FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien / Lien NHL
Emil BemstromMonsters (CBJ)C/RW271999-06-01SWENo190 Lbs183 CMNoNoN/ANoNo1FalseFalsePro & Farm925,000$0$0$No---------------------------Lien / Lien NHL
Gavin HayesMonsters (CBJ)LW222004-05-14USAYes177 Lbs185 CMNoNoProspectNoNo32025-06-01FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien / Lien NHL
Josh DaviesMonsters (CBJ)LW222004-03-24CANNo197 Lbs175 CMNoNoFree AgentNoNo32025-07-19FalseFalsePro & Farm1,499,999$0$0$No1,499,999$1,499,999$-------1,499,999$1,499,999$-------NoNo-------Lien / Lien NHL
Kyle MacLeanMonsters (CBJ)C271999-04-29USANo194 Lbs185 CMNoNoN/ANoNo1FalseFalsePro & Farm925,000$0$0$No---------------------------Lien / Lien NHL
Matthew RobertsonMonsters (CBJ)D252001-03-09CANNo211 Lbs193 CMNoNoFree AgentNoNo32025-07-19FalseFalsePro & Farm1,499,999$0$0$No1,499,999$1,499,999$-------1,499,999$1,499,999$-------NoNo-------Lien / Lien NHL
Michael MilneMonsters (CBJ)LW232002-09-21CANNo185 Lbs180 CMNoNoN/ANoNo3FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien / Lien NHL
Nikita TolopiloMonsters (CBJ)G262000-04-06BLRNo229 Lbs198 CMNoNoAssign ManuallyNoNo42024-07-17FalseFalsePro & Farm1,499,999$0$0$No1,499,999$1,499,999$1,499,999$------1,499,999$1,499,999$1,499,999$------NoNoNo------Lien / Lien NHL
Parker WotherspoonMonsters (CBJ)D291997-08-24CANNo192 Lbs185 CMNoNoAssign ManuallyYesNo42024-07-22FalseFalsePro & Farm1,499,999$0$0$No1,499,999$1,499,999$1,499,999$------1,499,999$1,499,999$1,499,999$------NoNoNo------Lien / Lien NHL
Pierre EngvallMonsters (CBJ)LW/RW301996-05-31SWENo215 Lbs196 CMNoNoN/AYesNo1FalseFalsePro & Farm1,250,000$0$0$No---------------------------Lien / Lien NHL
Riley StillmanMonsters (CBJ)D281998-03-09CANNo207 Lbs188 CMNoNoN/AYesNo2FalseFalsePro & Farm1,100,000$0$0$No1,100,000$--------1,100,000$--------No--------Lien / Lien NHL
Sam LipkinMonsters (CBJ)LW232003-01-03USAYes192 Lbs188 CMNoNoProspectNoNo32025-06-01FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien / Lien NHL
Tobias BjornfotMonsters (CBJ)D252001-04-06SWENo200 Lbs183 CMNoNoFree AgentNoNo32025-07-19FalseFalsePro & Farm1,499,999$0$0$No1,499,999$1,499,999$-------1,499,999$1,499,999$-------NoNo-------Lien / Lien NHL
Travis DermottMonsters (CBJ)D291996-12-22CANNo200 Lbs183 CMNoNoFree Agent2025-01-03YesNo32025-07-19FalseFalsePro & Farm1,499,999$0$0$No1,499,999$1,499,999$-------1,499,999$1,499,999$-------NoNo-------Lien / Lien NHL
Ville HeinolaMonsters (CBJ)D252001-03-02FINNo181 Lbs183 CMNoNoFree AgentNoNo32025-07-19FalseFalsePro & Farm1,499,999$0$0$No1,499,999$1,499,999$-------1,499,999$1,499,999$-------NoNo-------Lien / Lien NHL
Ville OttavainenMonsters (CBJ)D242002-08-12FINNo210 Lbs196 CMNoNoProspectNoNo22024-05-23FalseFalsePro & Farm925,000$0$0$No925,000$--------925,000$--------No--------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2425.92197 Lbs185 CM2.501,168,750$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Carl GrundstromEmil BemstromPierre Engvall40014
2Axel Jonsson-FjallbyAdam EdstromCarson Meyer30122
3Brennan OthmannKyle MacLeanMichael Milne20122
4Michael MilneCarl BerglundCarson Meyer10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Parker WotherspoonVille Ottavainen40122
2Albert Johansson30122
3Ville Heinola20122
4Parker Wotherspoon10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Carl GrundstromEmil BemstromPierre Engvall60005
2Axel Jonsson-FjallbyAdam EdstromCarson Meyer40005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Parker WotherspoonVille Ottavainen60113
2Albert Johansson40113
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Emil BemstromCarl Grundstrom60140
2Adam EdstromAxel Jonsson-Fjallby40140
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Parker WotherspoonVille Ottavainen60140
2Albert Johansson40140
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Emil Bemstrom60050Parker WotherspoonVille Ottavainen60140
2Adam Edstrom40050Albert Johansson40140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Emil BemstromCarl Grundstrom60122
2Adam EdstromAxel Jonsson-Fjallby40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Parker WotherspoonVille Ottavainen60122
2Albert Johansson40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Carl GrundstromEmil BemstromPierre EngvallParker WotherspoonVille Ottavainen
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Carl GrundstromEmil BemstromPierre EngvallParker WotherspoonVille Ottavainen
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Kyle MacLean, Carson Meyer, Axel Jonsson-FjallbyKyle MacLean, Carson MeyerKyle MacLean
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
, Ville Heinola, , Ville Heinola
Tirs de pénalité
Pierre Engvall, Emil Bemstrom, Carl Grundstrom, Adam Edstrom, Kyle MacLean
Gardien
#1 : Nikita Tolopilo, #2 : Cal Petersen


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
1Marlies7430000021210422000001112-132100000109180.57121375800171311330818619519431277706315519421.05%27581.48%036763158.16%29352455.92%11921854.59%39628530710118394
2Senators7340000023230321000001082413000001315-260.42923426500171311329818619519431207714616124625.00%21671.43%036763158.16%29352455.92%11921854.59%39628530710118394
Total147700000444407430000021201734000002324-1140.500447912300171311360618619519431484141109316431023.26%481177.08%036763158.16%29352455.92%11921854.59%39628530710118394
_Since Last GM Reset147700000444407430000021201734000002324-1140.500447912300171311360618619519431484141109316431023.26%481177.08%036763158.16%29352455.92%11921854.59%39628530710118394
_Vs Conference147700000444407430000021201734000002324-1140.500447912300171311360618619519431484141109316431023.26%481177.08%036763158.16%29352455.92%11921854.59%39628530710118394

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1414L3447912360648414110931600
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
147700004444
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
74300002120
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
73400002324
Derniers 10 matchs
WLOTWOTL SOWSOL
640000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
431023.26%481177.08%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
186195194311713113
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
36763158.16%29352455.92%11921854.59%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
39628530710118394


Derniers matchs joués
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe visiteuse Score Équipe locale Score ST OT SO RI Lien
1 - 2026-04-203Marlies4Monsters2LSommaire du match
3 - 2026-04-2211Marlies3Monsters2LSommaire du match
5 - 2026-04-2419Monsters3Marlies5LSommaire du match
7 - 2026-04-2627Monsters5Marlies3WSommaire du match
9 - 2026-04-2835Marlies3Monsters4WXSommaire du match
11 - 2026-04-3043Monsters2Marlies1WXSommaire du match
13 - 2026-05-0251Marlies2Monsters3WSommaire du match
15 - 2026-05-0458Monsters5Senators3WSommaire du match
16 - 2026-05-0562Monsters2Senators3LSommaire du match
17 - 2026-05-0666Senators2Monsters5WSommaire du match
19 - 2026-05-0870Senators3Monsters4WXSommaire du match
20 - 2026-05-0974Monsters3Senators4LSommaire du match
21 - 2026-05-1078Senators3Monsters1LSommaire du match
22 - 2026-05-1182Monsters3Senators5LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité30002000
Prix des billets2515
Assistance21,00013,814
Assistance PCT100.00%98.67%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
34 4973 - 99.47% 152,718$1,069,027$5000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
0$ 2,805,000$ 2,805,000$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

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




Monsters Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Monsters Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Monsters Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT

Monsters Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Monsters Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA