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Monsters

GP: 53 | W: 24 | L: 26 | OTL: 3 | P: 51
GF: 167 | GA: 184 | PP%: 22.14% | PK%: 76.64%
DG: Martin Pomminville | Morale : 50 | Moyenne d'Équipe : 61
Prochain matchs #811 vs Eagles
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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
1Jayce HawrylukXX100.00714279647277716359625860636764050620231874,125$
2Rudolfs BalcersX100.00573983656875726458636361646563050620221925,000$
3Noah GregorX100.00684188647173666270615963646362050620212850,000$
4Rodrigo AbolsX100.00714688608877765872615663606764050620232925,000$
5Adam BrooksX100.00574189626776756157606058636764050610231925,000$
6Dmitry SokolovX100.00533787616683855953556056616362050600212830,000$
7Isaac RatcliffeX100.00745283569285875551545459536162050600203863,333$
8Gabriel FontaineX100.00644387587879815753565459606563050600221736,667$
9Jack KopackaX100.00654285588083815754565659586362050600212910,833$
10Kody ClarkX100.00634686588075745753565459536162050590193894,167$
11Jon MerrillX100.007643696582837963307158785275680506602711,375,000$
12Carson Soucy (A)X100.00644389659180716430636372537167050650251750,000$
13Cale FleuryX100.00724388637883776230615864536261050630202883,333$
14Gustav OlofssonX100.00634187598076745730585659457166050610241700,000$
15Kale ClagueX100.00574389637081726130605862546361050610212894,166$
16Andreas BorgmanX100.00625183597483845830575355466965050600241700,000$
17Pierre-Olivier JosephX100.006148855977858457305653584661630506002031,075,833$
Rayé
1Bokondji ImamaX100.00706765568280795551535457536764050590231706,667$
2Maksim SushkoX100.00584785597185875652545753596163050590203879,167$
3Otto SomppiX100.00634589567977765862545457566362050590212800,000$
4Ivan ChekhovichX100.00523888586079785751565455536162050580203903,333$
5Skyler McKenzieX100.00514389585984825753555654586362050580212741,666$
6Drake RymshaX100.00574579547278755359525156546362050570212733,333$
7Ty RonningX100.00533887536373725550515452536563050570212750,833$
MOYENNE D'ÉQUIPE100.0063448460758077594958566056656305060
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 SP
1Mikhail Berdin100.0075828073747375747375746367050640
2Dylan Ferguson100.0074525075737274737274736367050630
Rayé
1Adam Huska100.0070686689696870696870696569050630
2Antoine Bibeau100.0070605886696870696870697175050630
3Jeremy Helvig100.0060525084595860595860596569050570
MOYENNE D'ÉQUIPE100.007063618169687069687069656905062
Nom du Coach 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
1Carson SoucyMonsters (CLB)D53132942-51405670121336510.74%66110820.9177145798000199100.00%000000.7600000023
2Jon MerrillMonsters (CLB)D5363440-203601719112926694.65%78120722.773111461116022194110.00%000000.6600000130
3Rodrigo AbolsMonsters (CLB)C53152035-7300105107155401099.68%10101819.210227570000710157.23%113400000.6936000122
4Otto KoivulaBlue JacketsC/LW3814203481958558110318012.73%785222.4334717860002963052.49%72400010.8018001540
5Cale FleuryMonsters (CLB)D539243303801075068254913.24%4694517.834371949000039200.00%000010.7000000310
6Carl GunnarssonBlue JacketsD5162531-1240188410546655.71%75113522.27268481160112116010.00%000000.5500000013
7Jayce HawrylukMonsters (CLB)C/RW53141731-20260124771305111610.77%4103219.49156161081012350153.12%43300010.6001000310
8Rudolfs BalcersMonsters (CLB)LW53171229-41404966181401379.39%593217.59325251050002212158.33%6000000.6224000121
9Dmitry SokolovMonsters (CLB)RW53161228-7202660111336914.41%195117.961017561011261143.82%8900000.5900000111
10Logan ShawBlue JacketsC/RW38917261340675912935916.98%991624.1213420850001981049.20%43900000.5728000111
11Noah GregorMonsters (CLB)C53151126-1610082123188591177.98%1598318.561237540002534154.31%111400000.5327000201
12Gabriel FontaineMonsters (CLB)LW5381119-14135624176277610.53%393317.611344710001150154.29%7000000.4100001001
13Robert BortuzzoBlue JacketsD24314174320102425112365.88%5158824.531232051000055100.00%000000.5800000222
14Adam BrooksMonsters (CLB)C5351015-54021428629725.81%572113.61112525000040144.71%37800000.4222000100
15Gustav OlofssonMonsters (CLB)D5301515-318072343516290.00%5182715.6200011011129000.00%000000.3600000000
16Kale ClagueMonsters (CLB)D5331215-2140323130122210.00%3761011.5200014000021010.00%000000.4900000010
17Isaac RatcliffeMonsters (CLB)LW5368141195102327415508.11%373813.94000010000161056.82%4400000.3800001020
18Jack KopackaMonsters (CLB)LW15156-6801910278213.70%226317.5600024000080078.57%1400000.4600000000
19Pierre-Olivier JosephMonsters (CLB)D2022000314110.00%03316.510000000000000.00%000001.2100000000
20Otto SomppiMonsters (CLB)C14000-300312110.00%0292.1300002000050038.89%1800000.0000000000
Stats d'équipe Total ou en Moyenne871160298458-983051513061079181254012758.83%4681583018.17295180317109924616910171053.22%451700030.581236003212315
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
1Mikhail BerdinMonsters (CLB)48242130.9023.0528142114314600210.81137480201
2Antoine BibeauMonsters (CLB)20000.9252.6169003400000.0000024000
3Dylan FergusonMonsters (CLB)20000.8463.0040002130000.0000024000
Stats d'équipe Total ou en Moyenne52242130.9023.0429242114815130210.811374848201


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 Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Adam BrooksMonsters (CLB)C231996-05-06No185 Lbs5 ft10NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Adam HuskaMonsters (CLB)G221997-05-12No227 Lbs6 ft3NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien / Lien NHL
Andreas BorgmanMonsters (CLB)D241995-06-18No199 Lbs6 ft0NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Antoine BibeauMonsters (CLB)G251994-05-01No213 Lbs6 ft3NoNoNo1Pro & Farm675,000$0$0$NoLien / Lien NHL
Bokondji ImamaMonsters (CLB)LW231996-08-03No221 Lbs6 ft1NoNoNo1Pro & Farm706,667$0$0$NoLien / Lien NHL
Cale FleuryMonsters (CLB)D201998-11-19No205 Lbs6 ft1NoNoNo2Pro & Farm883,333$0$0$No883,333$Lien / Lien NHL
Carson SoucyMonsters (CLB)D251994-07-27No210 Lbs6 ft5NoNoNo1Pro & Farm750,000$0$0$NoLien / Lien NHL
Dmitry SokolovMonsters (CLB)RW211998-04-14No221 Lbs5 ft1NoNoNo2Pro & Farm830,000$0$0$No830,000$Lien / Lien NHL
Drake RymshaMonsters (CLB)C211998-08-18No187 Lbs6 ft0NoNoNo2Pro & Farm733,333$0$0$No733,333$Lien / Lien NHL
Dylan FergusonMonsters (CLB)G211998-09-20No189 Lbs6 ft1NoNoNo3Pro & Farm733,333$0$0$No733,333$733,333$Lien
Gabriel FontaineMonsters (CLB)LW221997-04-30No201 Lbs6 ft1NoNoNo1Pro & Farm736,667$0$0$NoLien / Lien NHL
Gustav OlofssonMonsters (CLB)D241994-12-01No200 Lbs6 ft2NoNoNo1Pro & Farm700,000$0$0$NoLien
Isaac RatcliffeMonsters (CLB)LW201999-02-15No200 Lbs6 ft6NoNoNo3Pro & Farm863,333$0$0$No863,333$863,333$Lien
Ivan ChekhovichMonsters (CLB)LW201999-01-04No185 Lbs5 ft1NoNoNo3Pro & Farm903,333$0$0$No903,333$903,333$Lien
Jack KopackaMonsters (CLB)LW211998-03-05No197 Lbs6 ft2NoNoNo2Pro & Farm910,833$0$0$No910,833$Lien / Lien NHL
Jayce HawrylukMonsters (CLB)C/RW231996-01-01No196 Lbs5 ft11NoNoNo1Pro & Farm874,125$0$0$NoLien / Lien NHL
Jeremy HelvigMonsters (CLB)G221997-05-25No188 Lbs6 ft4NoNoNo2Pro & Farm785,000$0$0$No785,000$Lien / Lien NHL
Jon MerrillMonsters (CLB)D271992-02-03No195 Lbs6 ft3NoNoNo1Pro & Farm1,375,000$0$0$NoLien / Lien NHL
Kale ClagueMonsters (CLB)D211998-06-05No177 Lbs6 ft0NoNoNo2Pro & Farm894,166$0$0$No894,166$Lien / Lien NHL
Kody ClarkMonsters (CLB)RW191999-10-13No185 Lbs6 ft3NoNoNo3Pro & Farm894,167$0$0$No894,167$894,167$Lien
Maksim SushkoMonsters (CLB)RW201999-02-10No181 Lbs6 ft0NoNoNo3Pro & Farm879,167$0$0$No879,167$879,167$Lien
Mikhail BerdinMonsters (CLB)G211998-03-01No163 Lbs6 ft2NoNoNo2Pro & Farm766,666$0$0$No766,666$Lien / Lien NHL
Noah GregorMonsters (CLB)C211998-07-28No185 Lbs6 ft0NoNoNo2Pro & Farm850,000$0$0$No850,000$Lien
Otto SomppiMonsters (CLB)C211998-01-12No192 Lbs6 ft2NoNoNo2Pro & Farm800,000$0$0$No800,000$Lien / Lien NHL
Pierre-Olivier JosephMonsters (CLB)D201999-07-01No185 Lbs6 ft2NoNoNo3Pro & Farm1,075,833$0$0$No1,075,833$1,075,833$Lien
Rodrigo AbolsMonsters (CLB)C231996-01-05No206 Lbs6 ft4NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Rudolfs BalcersMonsters (CLB)LW221997-04-08No180 Lbs5 ft11NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Skyler McKenzieMonsters (CLB)LW211998-01-20No154 Lbs5 ft8NoNoNo2Pro & Farm741,666$0$0$No741,666$Lien / Lien NHL
Ty RonningMonsters (CLB)RW211997-10-20No167 Lbs5 ft9NoNoNo2Pro & Farm750,833$0$0$No750,833$Lien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2921.86193 Lbs6 ft01.86845,257$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Rudolfs BalcersRodrigo AbolsJayce Hawryluk30122
2Jack KopackaNoah GregorDmitry Sokolov30122
3Gabriel FontaineAdam BrooksIsaac Ratcliffe25122
4Isaac RatcliffeRodrigo Abols15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jon MerrillCarson Soucy30122
2Cale FleuryKale Clague30122
3Gustav OlofssonPierre-Olivier Joseph25122
4Jon MerrillCarson Soucy15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Rudolfs BalcersRodrigo AbolsJayce Hawryluk60122
2Jack KopackaNoah GregorDmitry Sokolov40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jon MerrillCarson Soucy60122
2Cale FleuryKale Clague40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Rodrigo AbolsNoah Gregor60122
2Rudolfs BalcersJayce Hawryluk40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jon MerrillCarson Soucy60122
2Cale FleuryKale Clague40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Rodrigo Abols60122Jon MerrillCarson Soucy60122
2Noah Gregor40122Cale FleuryKale Clague40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Rodrigo AbolsNoah Gregor60122
2Rudolfs BalcersJayce Hawryluk40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jon MerrillCarson Soucy60122
2Cale FleuryKale Clague40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Rudolfs BalcersRodrigo AbolsJayce HawrylukJon MerrillCarson Soucy
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Rudolfs BalcersRodrigo AbolsJayce HawrylukJon MerrillCarson Soucy
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Adam Brooks, Gabriel Fontaine, Adam Brooks, Gabriel Fontaine
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Gustav Olofsson, Pierre-Olivier Joseph, Cale FleuryGustav OlofssonPierre-Olivier Joseph, Cale Fleury
Tirs de Pénalité
Rodrigo Abols, Noah Gregor, Rudolfs Balcers, Jayce Hawryluk, Adam Brooks
Gardien
#1 : , #2 :


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
LigueDomicileVisiteur
# 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
1Admirals2110000089-11010000047-31100000042220.5008162400634352146962658058161551612493133.33%5180.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
2Americans2110000025-31010000004-41100000021120.5002460063435214566265805816158181252800.00%6266.67%01046195253.59%881169152.10%47888254.20%14129991123365692363
3Barracuda1010000023-1000000000001010000023-100.000246006343521427626580581613180275240.00%000.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
4Bears1010000012-11010000012-10000000000000.000123006343521435626580581612711418000.00%20100.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
5Bruins21001000963100010004311100000053241.0009172600634352146762658058161501814553266.67%70100.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
6Checkers2010000158-31010000024-21000000134-110.250591400634352146362658058161631010484375.00%40100.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
7Condors22000000185131100000072511000000113841.00018345200634352141326265805816147111443000.00%7185.71%01046195253.59%881169152.10%47888254.20%14129991123365692363
8Crunch31200000710-32020000037-41100000043120.33371421106343521483626580581619524147710330.00%6266.67%01046195253.59%881169152.10%47888254.20%14129991123365692363
9Devils22000000862000000000002200000086241.0008162400634352146762658058161521714516116.67%6266.67%01046195253.59%881169152.10%47888254.20%14129991123365692363
10Eagles11000000312110000003120000000000021.000358006343521432626580581611892184250.00%10100.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
11Griffins30200010710-32010001045-11010000035-220.333712190063435214129626580581611033014818112.50%60100.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
12Gulls2010010028-6000000000002010010028-610.250235006343521474626580581616217440600.00%2150.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
13Heat2110000079-21010000036-31100000043120.5007132000634352148662658058161661712544125.00%6266.67%01046195253.59%881169152.10%47888254.20%14129991123365692363
14IceHogs10000010431000000000001000001043121.0004610006343521436626580581613011733100.00%10100.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
15Marlies40400000613-71010000013-230300000510-500.000611170063435214101626580581611212420889111.11%10370.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
16Moose110000001001000000000000110000001001021.00010203001634352147462658058161205219000.00%10100.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
17Penguins11000000624000000000001100000062421.0006111700634352142862658058161491182222100.00%40100.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
18Phantoms21100000761110000004221010000034-120.5007132000634352146762658058161651912599222.22%6183.33%01046195253.59%881169152.10%47888254.20%14129991123365692363
19Rampage20200000214-121010000025-31010000009-900.000246006343521479626580581617515859800.00%4250.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
20Reign211000009631010000023-11100000073420.5009142300634352145162658058161681510489333.33%5260.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
21Roadrunners1010000024-2000000000001010000024-200.00024600634352144062658058161246428500.00%20100.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
22Rocket20000020752200000207520000000000041.000710170063435214636265805816175222352500.00%8275.00%11046195253.59%881169152.10%47888254.20%14129991123365692363
23Senators302000101217-520100010812-41010000045-120.333121931006343521486626580581611394028807228.57%12650.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
24Sound Tigers1010000047-3000000000001010000047-300.0004610006343521432626580581614519626200.00%20100.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
25Stars1010000012-11010000012-10000000000000.000123006343521427626580581612265252150.00%000.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
26Thunderbirds311000108802110000045-11000001043140.6678132100634352149162658058161101342263400.00%11281.82%11046195253.59%881169152.10%47888254.20%14129991123365692363
Total53152602172167184-1726414020517087-172711120012197970510.4811672984651163435214181262658058161169246830713061312922.14%1373276.64%21046195253.59%881169152.10%47888254.20%14129991123365692363
27Wild20000011660200000116600000000000030.750691500634352145762658058161712112445120.00%60100.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
28Wolf Pack10001000431100010004310000000000021.000471100634352143862658058161308123211100.00%6350.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
29Wolves1010000006-6000000000001010000006-600.00000000634352142262658058161306215100.00%10100.00%01046195253.59%881169152.10%47888254.20%14129991123365692363
_Since Last GM Reset53152602172167184-1726414020517087-172711120012197970510.4811672984651163435214181262658058161169246830713061312922.14%1373276.64%21046195253.59%881169152.10%47888254.20%14129991123365692363
_Vs Conference24712001318186-51126000213237-513560011049490220.45881146227016343521493562658058161722193108583611219.67%47980.85%01046195253.59%881169152.10%47888254.20%14129991123365692363
_Vs Division1126000314041-13030002112111823000102830-2110.5004072112006343521443262658058161328804625530620.00%23673.91%01046195253.59%881169152.10%47888254.20%14129991123365692363

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
5351L316729846518121692468307130611
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
5315262172167184
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2641420517087
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
27111201219797
Derniers 10 Matchs
WLOTWOTL SOWSOL
270010
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1312922.14%1373276.64%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
6265805816163435214
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
1046195253.59%881169152.10%47888254.20%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
14129991123365692363


Derniers Match 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
3 - 2020-10-0715Bruins3Monsters4WXSommaire du Match
4 - 2020-10-0829Monsters5Devils4WSommaire du Match
7 - 2020-10-1146Wolf Pack3Monsters4WXSommaire du Match
9 - 2020-10-1363Americans4Monsters0LSommaire du Match
10 - 2020-10-1470Monsters3Checkers4LXXSommaire du Match
13 - 2020-10-1793Monsters6Penguins2WSommaire du Match
14 - 2020-10-1896Monsters1Marlies3LSommaire du Match
16 - 2020-10-20117Monsters1Gulls6LSommaire du Match
18 - 2020-10-22125Wild3Monsters4WXXSommaire du Match
21 - 2020-10-25149Rocket3Monsters4WXXSommaire du Match
22 - 2020-10-26158Monsters2Marlies3LSommaire du Match
24 - 2020-10-28174Crunch3Monsters1LSommaire du Match
27 - 2020-10-31194Griffins2Monsters3WXXSommaire du Match
29 - 2020-11-02208Monsters2Americans1WSommaire du Match
31 - 2020-11-04224Marlies3Monsters1LSommaire du Match
32 - 2020-11-05230Monsters3Phantoms4LSommaire du Match
35 - 2020-11-08254Senators4Monsters5WXXSommaire du Match
37 - 2020-11-10262Monsters4IceHogs3WXXSommaire du Match
39 - 2020-11-12279Monsters4Admirals2WSommaire du Match
41 - 2020-11-14295Checkers4Monsters2LSommaire du Match
43 - 2020-11-16312Monsters11Condors3WSommaire du Match
45 - 2020-11-18325Monsters3Devils2WSommaire du Match
47 - 2020-11-20335Phantoms2Monsters4WSommaire du Match
49 - 2020-11-22355Rocket2Monsters3WXXSommaire du Match
51 - 2020-11-24369Monsters10Moose0WSommaire du Match
53 - 2020-11-26388Rampage5Monsters2LSommaire du Match
54 - 2020-11-27397Monsters2Barracuda3LSommaire du Match
57 - 2020-11-30413Monsters0Wolves6LSommaire du Match
58 - 2020-12-01426Monsters5Bruins3WSommaire du Match
60 - 2020-12-03438Crunch4Monsters2LSommaire du Match
62 - 2020-12-05458Monsters4Senators5LSommaire du Match
64 - 2020-12-07465Stars2Monsters1LSommaire du Match
67 - 2020-12-10486Monsters1Gulls2LXSommaire du Match
68 - 2020-12-11495Thunderbirds2Monsters3WSommaire du Match
71 - 2020-12-14518Eagles1Monsters3WSommaire du Match
72 - 2020-12-15528Monsters4Heat3WSommaire du Match
75 - 2020-12-18545Monsters7Reign3WSommaire du Match
76 - 2020-12-19556Wild3Monsters2LXXSommaire du Match
79 - 2020-12-22574Monsters2Roadrunners4LSommaire du Match
81 - 2020-12-24587Senators8Monsters3LSommaire du Match
83 - 2020-12-26605Monsters0Rampage9LSommaire du Match
85 - 2020-12-28616Thunderbirds3Monsters1LSommaire du Match
87 - 2020-12-30635Monsters4Sound Tigers7LSommaire du Match
89 - 2021-01-01646Reign3Monsters2LSommaire du Match
91 - 2021-01-03662Monsters2Marlies4LSommaire du Match
93 - 2021-01-05676Heat6Monsters3LSommaire du Match
96 - 2021-01-08701Monsters4Crunch3WSommaire du Match
98 - 2021-01-10709Bears2Monsters1LSommaire du Match
101 - 2021-01-13734Condors2Monsters7WSommaire du Match
103 - 2021-01-15751Monsters4Thunderbirds3WXXSommaire du Match
105 - 2021-01-17766Griffins3Monsters1LSommaire du Match
107 - 2021-01-19774Monsters3Griffins5LSommaire du Match
110 - 2021-01-22798Admirals7Monsters4LSommaire du Match
112 - 2021-01-24811Monsters-Eagles-
114 - 2021-01-26828Devils-Monsters-
119 - 2021-01-31853Marlies-Monsters-
122 - 2021-02-03879Monsters-Stars-
124 - 2021-02-05888Condors-Monsters-
126 - 2021-02-07899Monsters-Rocket-
128 - 2021-02-09914Americans-Monsters-
129 - 2021-02-10928Monsters-Checkers-
132 - 2021-02-13946Wolf Pack-Monsters-
134 - 2021-02-15956Monsters-Americans-
136 - 2021-02-17977Moose-Monsters-
138 - 2021-02-19987Monsters-Wolf Pack-
140 - 2021-02-211005Monsters-Phantoms-
141 - 2021-02-221016Roadrunners-Monsters-
142 - 2021-02-231027Monsters-Bears-
145 - 2021-02-261045Bruins-Monsters-
146 - 2021-02-271051Monsters-Checkers-
149 - 2021-03-021072Monsters-Comets-
151 - 2021-03-041084Gulls-Monsters-
154 - 2021-03-071107Monsters-Penguins-
155 - 2021-03-081116Wolves-Monsters-
157 - 2021-03-101129Monsters-Sound Tigers-
159 - 2021-03-121146Sound Tigers-Monsters-
162 - 2021-03-151171Comets-Monsters-
165 - 2021-03-181182Monsters-Bears-
169 - 2021-03-221204Penguins-Monsters-
173 - 2021-03-261229IceHogs-Monsters-
175 - 2021-03-281240Monsters-Wild-
179 - 2021-04-011263Barracuda-Monsters-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
15 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,745,506$ 2,451,246$ 1,433,917$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,745,506$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 72 13,468$ 969,696$




LigueDomicileVisiteur
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
Saison Régulière
282452602252289234554125120002215311934412014022301361152190289511800141059978929981028994953412275685113916284058120.00%4448979.95%51671302955.17%1414274651.49%692128353.94%2082144018386171046534
282303805423269271-241181701212143136741122104211126135-9602694677363510393667254085884281835265880357812703467621.97%2314680.09%31266257949.09%1195266044.92%656136048.24%1924131919736101064531
38246170517627819286412290404214399444124801134135934292278488766051048577202852931890990982285661104016383577019.61%4316185.85%71699299956.65%1394266152.39%663125952.66%2131148118066031064547
3824024011610258226324125110003213811028411513011381201164802584457032210873701329901023965956114251371172113953516217.66%2595678.38%21643301354.53%1266252450.16%667126952.56%2153152217985841053548
482392804047246239741279010221341003441121903025112139-2778246443689328985641225968518688507524537571318190959511419.16%5339681.99%41543303650.82%1304275747.30%612128347.70%2109145918506251024523
582541302265298169129412790001414784634127402251151856610829851881609113104731530309541007103387212065259720252334218.03%2584482.95%21855289364.12%1467240561.00%825129263.85%2273165516805481030548
682481606354373237136412080333418612561412880302018711275963736651038191411259614386211641295135885264675565521342175525.35%2855281.75%42111346660.91%1597279157.22%829140958.84%2288167316855401010534
782551800243329214115412690013217211557412990011115799581103295819100713596949343811371182110349241173752720872225424.32%2335476.82%41971325160.63%1497255558.59%801138757.75%2305168116145361035560
8824624020463832371464122902026205119864124150002017811860923837131096061691099914366312061201123162255673045220611724526.16%2004279.00%11892312460.56%1378249255.30%848143858.97%240418061574498997547
8824624020463832371464122902026205119864124150002017811860923837131096061691099914366312061201123162255673045220611724526.16%2004279.00%11892312460.56%1378249255.30%848143858.97%240418061574498997547
953152602172167184-1726414020517087-172711120012197970511672984651163435214181262658058161169246830713061312922.14%1373276.64%21046195253.59%881169152.10%47888254.20%14129991123365692363
Total Saison Régulière8734642540311654543273244083343623811601562833169612134834372261380161026211577122735094932735842911511561299102186814133444109841102511104769261657689778619514320167321.02%321161480.88%35185893246657.26%147712777453.18%79191430055.38%2349016846185216028110175785
Séries
223167000008450341284000004225171183000004225173284149233013225261838268279275165881943644111292620.16%1241786.29%253888760.65%44874460.22%20635757.70%601414495175301156
2624000001522-73120000089-131200000713-641528430053612076072732218669511218527.78%33875.76%011722053.18%10020947.85%5110150.50%147100143437437
31046000002537-12514000001022-1253200000151508254772001158131712291995399106140239521019.23%54885.19%111733035.45%13343030.93%4614232.39%2211512657312158
340400000715-82020000027-52020000058-307132000223012335493901343748732314.35%22768.18%07013651.47%6413647.06%286543.08%946395315025
440400000713-62020000058-32020000025-3071320001330117543231013254951072229.09%40977.50%07514751.02%6715842.41%346353.97%9059100314823
58440000020200422000009904220000011110820375700411412808999848259636321436616.67%28775.00%014531645.89%12226046.92%6714047.86%2011371916210653
612570000035341624000001315-26330000022193103565100001411100426145153127144511310030343511.63%45686.67%022944251.81%24947951.98%11019057.89%2751912988915073
7514000001120-931200000912-32020000028-6211193000326015835674610207504415717529.41%20670.00%08818348.09%9621544.65%378245.12%12788126386834
Total Séries72324000000204211-73715220000098107-935171800000106104264204371575017262664246680884277442238268394916163406017.65%3666881.42%31379266151.82%1279263148.61%579114050.79%175912061716547922462