Toronto Marlies

GP: 82 | W: 38 | L: 39 | OTL: 5 | P: 81
GF: 312 | GA: 323 | PP%: 40.65% | PK%: 62.61%
DG: Guy Rollin | Morale : 48 | Moyenne d'Équipe : 57
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

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 SP
1Michael MerschX100.008078846878788262505764676144446693620
2Michael McCarronXX100.008088617288636463796258685549496487620
3Matthew HighmoreXX100.007166847066626265506562635944446557600
4Jonathan Dahlen (R)XX100.007466926366676961505761635844446365590
5Nathan Walker (C)X100.006562726462717462505962595944456368580
6Emile PoirierXX100.007573806873616354505051644852525875570
7Mason MarchmentX100.007377625977616260505660635744446150570
8Trent FredericX100.007787726577547560705055632545455983570
9Nolan Vesey (R)X100.007776796976495049504944624244445322530
10Grant Besse (R)XX100.007062906262586051503860595744445831530
11Ryan HorvatX100.006467566467656950505044564244445225520
12Stephen GiontaXXX100.006960896560515347594445574344445245510
13Andrew MacWilliamX100.007681636881707747253541643956565364600
14Ben Gleason (R)X100.007469856069788554255241623944445668590
15Ryan StantonX100.007273696673677250254241633958585362590
16Nicolas MelocheX100.007576726276707550254343614144445472580
17Rinat Valiev (A)X100.007980756480646851254641633944445480580
18Keegan LoweX100.007373726573707650254539603745455368580
19Dennis RobertsonX100.007978816278606446253243644152525272570
20Timothy LiljegrenX100.007570867270596151254641613944445469570
Rayé
1Zac LeslieX100.007164876664707648254040593844445219560
2Josiah DidierX100.007275666375667148253941593945455220560
3Brandon Hickey (R)X100.007975876575555748254040633844445228560
4Louie BelpedioX100.007269796569707648253941593944445351560
5Vili Saarijarvi (R)X100.007365906465646947253940593844445219550
MOYENNE D'ÉQUIPE100.00747277657264685339474862444646565657
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
1Jonas Johansson100.00645265846864647066663044446466630
2Chris Driedger100.00635873846665576663623044446225620
Rayé
1Eddie Pasquale100.00646885846368616966653044446559640
2Jeremy Helvig (R)100.00475265844345535547483044444920520
MOYENNE D'ÉQUIPE100.0060587284606159656160304444604360
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Bob Woods48614562454651CAN51272,600$


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
1Matthew HighmoreToronto Marlies (TOR)LW/RW7156621181112508814133011624516.97%63171224.1118213945125112141246344.16%1547645051.3823253974
2Jonathan DahlenToronto Marlies (TOR)C/LW82384785-128155801422528116015.08%62156719.129122116750336586341.45%2755452021.0822353557
3Emile PoirierToronto Marlies (TOR)LW/RW823545803109751011312296411915.28%39157419.2071017211092024451142.86%1195646011.0211447344
4Trent FredericToronto Marlies (TOR)C73304575-202911451031321936612915.54%43141919.44111829241110000271154.40%13313544011.060015212330
5Nathan WalkerToronto Marlies (TOR)LW82334073760301191322366611913.98%44152018.541567532028464146.18%2627525000.9601123563
6Michael MerschToronto Marlies (TOR)LW54284068-612785821081835411415.30%59131624.3891019239010141097043.37%5814039021.0312548615
7Stephen GiontaToronto Marlies (TOR)C/LW/RW69143044-434305214181264117.28%33118817.2247118741014132148.10%8961920000.7400231121
8Andrew MacWilliamToronto Marlies (TOR)D7783038-102881909311711943606.72%120179123.26581322155022314920100.00%12164000.420071318003
9Mason MarchmentToronto Marlies (TOR)LW80161733-151045098107112276214.29%35113214.164487300110330036.30%1352127010.5800334121
10Ryan StantonToronto Marlies (TOR)D6722830-5996576907239292.78%96144021.4927971040001123100.00%12351000.4200526010
11Rinat ValievToronto Marlies (TOR)D8232225-21167068696123264.92%82139717.05123485022089200.00%01037000.3600329000
12Ben GleasonToronto Marlies (TOR)D7641822-3806046818643534.65%96150019.753912121040002115000.00%1869000.2900354012
13Michael McCarronToronto Marlies (TOR)C/RW841216624101919466278.70%919224.051342190000191057.74%23984001.6600200111
14Alex IafalloMaple LeafsC/LW686145009730162226.67%1115926.632244130000110029.31%5875001.7500000113
15Nicolas MelocheToronto Marlies (TOR)D82099-9483041693524140.00%51108113.190113230000410022.22%9644000.1700114000
16Travis DermottMaple LeafsD825710086183511.11%1218923.72112214000214000.00%043100.7400000110
17Louie BelpedioToronto Marlies (TOR)D70246-8601614140614.29%133945.641121170111230030.00%2066000.3000000000
18Grant BesseToronto Marlies (TOR)LW/RW32354553531266.67%34013.360000000000010.00%114002.4900010001
19Dennis RobertsonToronto Marlies (TOR)D82044-8262042523511140.00%6192111.230110160000200014.29%7231000.0900004000
20Timothy LiljegrenToronto Marlies (TOR)D82134-575182886512.50%185747.000000300001000.00%2214000.1400001000
21Keegan LoweToronto Marlies (TOR)D82033-5221023368290.00%146407.8200003000030050.00%4220000.0900110000
22Brandon HickeyToronto Marlies (TOR)D35022-315156135020.00%121775.08011090000100050.00%619000.2300111000
23Ryan HorvatToronto Marlies (TOR)LW101013554322250.00%2636.3500003000000050.00%800000.3100001000
24Nolan VeseyToronto Marlies (TOR)LW10011-21010644150.00%1959.5300015000180038.10%2102000.2100110000
25Zac LeslieToronto Marlies (TOR)D15000-200253210.00%4946.3300003000050033.33%1803000.0000000000
26Josiah DidierToronto Marlies (TOR)D32000-5201242000.00%61434.50000020000130035.00%2014000.0000000000
Stats d'équipe Total ou en Moyenne1420287476763-9416711015121516562167722127113.24%9892233015.7379123202209125671017501114331148.09%41694786681120.6869595589363535
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
1Eddie PasqualeToronto Marlies (TOR)58272640.8973.6234198020620071091510.364115717524
2Jonas JohanssonToronto Marlies (TOR)1710510.9123.1610050053603328000.00001654211
3Chris DriedgerToronto Marlies (TOR)30300.8935.03167001413179000.000034100
Stats d'équipe Total ou en Moyenne78373450.9003.5745928027327411498510.364117675835


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
Andrew MacWilliamToronto Marlies (TOR)D281990-03-25No223 Lbs6 ft2NoNoNo1Pro & Farm632,500$0$0$NoLien
Ben GleasonToronto Marlies (TOR)D201998-03-25Yes185 Lbs6 ft1NoNoNo3Pro & Farm761,666$0$0$No761,666$761,666$Lien
Brandon HickeyToronto Marlies (TOR)D221996-04-13Yes201 Lbs6 ft2NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Chris DriedgerToronto Marlies (TOR)G241994-05-18No205 Lbs6 ft4NoNoNo2Pro & Farm850,000$0$0$No850,000$Lien
Dennis RobertsonToronto Marlies (TOR)D271991-05-24No215 Lbs6 ft1NoNoNo1Pro & Farm700,000$0$0$NoLien
Eddie PasqualeToronto Marlies (TOR)G271990-11-19No215 Lbs6 ft3NoNoNo1Pro & Farm900,000$0$0$NoLien
Emile PoirierToronto Marlies (TOR)LW/RW231994-12-14No196 Lbs6 ft2NoNoNo1Pro & Farm650,000$0$0$NoLien
Grant BesseToronto Marlies (TOR)LW/RW231994-07-14Yes174 Lbs5 ft10NoNoNo1Pro & Farm575,000$0$0$NoLien
Jeremy HelvigToronto Marlies (TOR)G211997-05-24Yes207 Lbs6 ft4NoNoNo3Pro & Farm761,666$0$0$No761,666$761,666$Lien
Jonas JohanssonToronto Marlies (TOR)G221995-09-18No206 Lbs6 ft4NoNoNo1Pro & Farm759,167$0$0$NoLien
Jonathan DahlenToronto Marlies (TOR)C/LW201997-12-20Yes183 Lbs5 ft11NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Josiah DidierToronto Marlies (TOR)D251993-04-08No202 Lbs6 ft2NoNoNo1Pro & Farm700,000$0$0$NoLien
Keegan LoweToronto Marlies (TOR)D251993-03-29No195 Lbs6 ft2NoNoNo1Pro & Farm675,000$0$0$NoLien
Louie BelpedioToronto Marlies (TOR)D221996-05-14No193 Lbs5 ft11NoNoNo1Pro & Farm925,000$0$0$NoLien
Mason MarchmentToronto Marlies (TOR)LW231995-03-06No204 Lbs6 ft4NoNoNo1Pro & Farm767,500$0$0$NoLien
Matthew HighmoreToronto Marlies (TOR)LW/RW221996-02-27No181 Lbs5 ft11NoNoNo2Pro & Farm775,833$0$0$No775,833$Lien
Michael McCarronToronto Marlies (TOR)C/RW231995-03-06No231 Lbs6 ft6NoNoNo1Pro & Farm700,000$0$0$NoLien
Michael MerschToronto Marlies (TOR)LW251992-10-02No213 Lbs6 ft2NoNoNo1Pro & Farm675,000$0$0$NoLien
Nathan WalkerToronto Marlies (TOR)LW241994-02-06No175 Lbs5 ft9NoNoNo1Pro & Farm650,000$0$0$NoLien
Nicolas MelocheToronto Marlies (TOR)D201997-07-18No204 Lbs6 ft3NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Nolan VeseyToronto Marlies (TOR)LW231995-03-28Yes212 Lbs6 ft0NoNoNo2Pro & Farm817,500$0$0$No817,500$Lien
Rinat ValievToronto Marlies (TOR)D231995-05-11No215 Lbs6 ft3NoNoNo1Pro & Farm700,000$0$0$NoLien
Ryan HorvatToronto Marlies (TOR)LW251993-02-09No185 Lbs5 ft11NoNoNo1Pro & Farm650,000$0$0$NoLien
Ryan StantonToronto Marlies (TOR)D281989-07-20No196 Lbs6 ft2NoNoNo1Pro & Farm770,000$0$0$NoLien
Stephen GiontaToronto Marlies (TOR)C/LW/RW341983-10-09No175 Lbs5 ft7YesNoNo1Pro & Farm700,000$0$0$NoLien
Timothy LiljegrenToronto Marlies (TOR)D191999-04-30No192 Lbs6 ft0NoNoNo2Pro & Farm894,166$0$0$No894,166$Lien
Trent FredericToronto Marlies (TOR)C201998-02-11No203 Lbs6 ft2NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Vili SaarijarviToronto Marlies (TOR)D211997-05-15Yes183 Lbs5 ft10NoNoNo1Pro & Farm894,000$0$0$NoLien
Zac LeslieToronto Marlies (TOR)D241994-01-31No174 Lbs6 ft0YesNoNo1Pro & Farm742,500$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2923.55198 Lbs6 ft11.41769,879$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Michael MerschMichael McCarronMatthew Highmore40122
2Nathan WalkerJonathan DahlenEmile Poirier30122
3Mason MarchmentTrent FredericGrant Besse20122
4Nolan VeseyStephen GiontaRyan Horvat10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Andrew MacWilliamBen Gleason40122
2Ryan StantonRinat Valiev30122
3Nicolas MelocheKeegan Lowe20122
4Dennis RobertsonTimothy Liljegren10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Michael MerschMichael McCarronMatthew Highmore60122
2Nathan WalkerJonathan DahlenEmile Poirier40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Andrew MacWilliamBen Gleason60122
2Ryan StantonRinat Valiev40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Michael McCarronMichael Mersch60122
2Matthew HighmoreNathan Walker40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Andrew MacWilliamBen Gleason60122
2Ryan StantonRinat Valiev40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Michael McCarron60122Andrew MacWilliamBen Gleason60122
2Michael Mersch40122Ryan StantonRinat Valiev40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Michael McCarronMichael Mersch60122
2Matthew HighmoreNathan Walker40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Andrew MacWilliamBen Gleason60122
2Ryan StantonRinat Valiev40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Michael MerschMichael McCarronMatthew HighmoreAndrew MacWilliamBen Gleason
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Michael MerschMichael McCarronMatthew HighmoreAndrew MacWilliamBen Gleason
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Ryan Horvat, Trent Frederic, Mason MarchmentRyan Horvat, Trent FredericMason Marchment
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nicolas Meloche, Keegan Lowe, Dennis RobertsonNicolas MelocheKeegan Lowe, Dennis Robertson
Tirs de Pénalité
Michael McCarron, Michael Mersch, Matthew Highmore, Nathan Walker, Jonathan Dahlen
Gardien
#1 : Jonas Johansson, #2 : Chris Driedger


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
1Binghampton Senators412010001517-22010100077021100000810-240.500152540006911711416128603807823721474165678450.00%15566.67%0685147446.47%830186944.41%626135646.17%147168318078081679856
2Boisbriand Armada411020001073210010005232010100055060.750101525006911711416776038078237210637786010550.00%4175.00%0685147446.47%830186944.41%626135646.17%147168318078081679856
3Brampton Battalion3100100117161200010018801100000098150.833172744006911711416114603807823721133795678450.00%10460.00%1685147446.47%830186944.41%626135646.17%147168318078081679856
4Bridgeport Sound Tigers2020000079-21010000034-11010000045-100.000711180069117114165160380782372722727368337.50%110.00%0685147446.47%830186944.41%626135646.17%147168318078081679856
5Calgary Hitman32100000191272110000012841100000074340.6671928470069117114168060380782372105281186411654.55%9544.44%0685147446.47%830186944.41%626135646.17%147168318078081679856
6Chicago Wolves2010100068-21010000025-31000100043120.50069150069117114164360380782372862127174250.00%6183.33%1685147446.47%830186944.41%626135646.17%147168318078081679856
7Chicoutimi Sagueneens412010001516-110001000321312000001214-240.50015254000691171141611360380782372163461107016531.25%20575.00%1685147446.47%830186944.41%626135646.17%147168318078081679856
8Drummondville Voltigeurs32100000161511100000075221100000910-140.66716294500691171141610260380782372963153437342.86%9455.56%1685147446.47%830186944.41%626135646.17%147168318078081679856
9Grand Rapids Griffins202000001319-61010000038-5101000001011-100.0001320330069117114165460380782372934024255480.00%7528.57%1685147446.47%830186944.41%626135646.17%147168318078081679856
10Hartford Wolf Pack20200000716-91010000058-31010000028-600.000713200069117114163460380782372813660293266.67%10370.00%0685147446.47%830186944.41%626135646.17%147168318078081679856
11Hershey Bears20100010440100000104311010000001-120.5004590069117114164560380782372651959354125.00%20100.00%0685147446.47%830186944.41%626135646.17%147168318078081679856
12Lake Erie Monsters3020010029-71000010023-12020000006-610.1672351069117114164260380782372105435344700.00%9277.78%0685147446.47%830186944.41%626135646.17%147168318078081679856
13Las Vegas Wranglers42200000211382110000097221100000126640.500213859006911711416116603807823721666475599444.44%10370.00%0685147446.47%830186944.41%626135646.17%147168318078081679856
14Laval Rockets211000007521010000013-21100000062420.500712190069117114163960380782372702917204250.00%10100.00%0685147446.47%830186944.41%626135646.17%147168318078081679856
15London Knights30300000516-111010000024-220200000312-900.0005101500691171141650603807823721074698386233.33%9544.44%1685147446.47%830186944.41%626135646.17%147168318078081679856
16Lowell Devils413000001119-821100000811-32020000038-520.2501120310069117114161206038078237217373745910220.00%18477.78%0685147446.47%830186944.41%626135646.17%147168318078081679856
17Manitoba Moose210001006601000010023-11100000043130.750691500691171141675603807823728732434010330.00%40100.00%0685147446.47%830186944.41%626135646.17%147168318078081679856
18Milwaukee Admirals52101100181262200000011383010110079-270.7001826440069117114161616038078237215963988410550.00%14378.57%0685147446.47%830186944.41%626135646.17%147168318078081679856
19Peoria Riverman3110100015150211000001011-11000100054140.66715243900691171141685603807823721574619396350.00%7528.57%0685147446.47%830186944.41%626135646.17%147168318078081679856
20Philadelphia Phantoms20200000516-111010000039-61010000027-500.00056110069117114165260380782372822742423133.33%6266.67%0685147446.47%830186944.41%626135646.17%147168318078081679856
21Portland Pirates2100001015781100000010371000001054141.0001526410069117114166960380782372702330409333.33%5260.00%0685147446.47%830186944.41%626135646.17%147168318078081679856
22Quebec Rempart3110100012102211000007611000100054140.6671222340069117114161106038078237210638645213430.77%7442.86%0685147446.47%830186944.41%626135646.17%147168318078081679856
23Rimouski Oceanic21001000835110000005141000100032141.000814220069117114164160380782372381228365240.00%4175.00%0685147446.47%830186944.41%626135646.17%147168318078081679856
24Rochester Americans312000001112-11010000013-221100000109120.3331117280069117114161036038078237210039985311436.36%9366.67%0685147446.47%830186944.41%626135646.17%147168318078081679856
25Seattle Thunderbirds210001005321000010012-11100000041330.75058130069117114165660380782372481856274250.00%3166.67%0685147446.47%830186944.41%626135646.17%147168318078081679856
26Sherbrooke Phoenix41300000912-331200000810-21010000012-120.25091524006911711416104603807823721366297558337.50%10550.00%0685147446.47%830186944.41%626135646.17%147168318078081679856
27Texas Stars2020000058-31010000034-11010000024-200.00059140069117114165760380782372782846345360.00%8537.50%0685147446.47%830186944.41%626135646.17%147168318078081679856
Total822639010421312323-1141141804311157155241122106110155168-13810.49431251582710691171141622956038078237229961065171513232148740.65%2308662.61%7685147446.47%830186944.41%626135646.17%147168318078081679856
29Victoriaville Tigres330000002311122200000014771100000094561.000234063006911711416108603807823721143151588450.00%8537.50%1685147446.47%830186944.41%626135646.17%147168318078081679856
30Worcester Sharks2110000057-21010000015-41100000042220.50059140069117114166660380782372732810302150.00%5260.00%0685147446.47%830186944.41%626135646.17%147168318078081679856
_Since Last GM Reset822639010421312323-1141141804311157155241122106110155168-13810.49431251582710691171141622956038078237229961065171513232148740.65%2308662.61%7685147446.47%830186944.41%626135646.17%147168318078081679856
_Vs Conference4918220620118918182511903101101841724713031008897-9510.520189315504106911711416141560380782372173363311178031265039.68%1415362.41%4685147446.47%830186944.41%626135646.17%147168318078081679856

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8281OTW13125158272295299610651715132310
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
82263910421312323
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4114184311157155
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4112216110155168
Derniers 10 Matchs
WLOTWOTL SOWSOL
333001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2148740.65%2308662.61%7
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
603807823726911711416
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
685147446.47%830186944.41%626135646.17%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
147168318078081679856


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
1 - 2019-10-048Toronto Marlies9Rochester Americans4WSommaire du Match
3 - 2019-10-0619Victoriaville Tigres5Toronto Marlies8WSommaire du Match
5 - 2019-10-0839Sherbrooke Phoenix4Toronto Marlies2LSommaire du Match
7 - 2019-10-1059Toronto Marlies1Boisbriand Armada2LSommaire du Match
8 - 2019-10-1169Toronto Marlies2London Knights7LSommaire du Match
9 - 2019-10-1283Boisbriand Armada1Toronto Marlies3WSommaire du Match
11 - 2019-10-1499Toronto Marlies1Milwaukee Admirals3LSommaire du Match
12 - 2019-10-15103Toronto Marlies4Chicoutimi Sagueneens8LSommaire du Match
14 - 2019-10-17121Quebec Rempart4Toronto Marlies1LSommaire du Match
16 - 2019-10-19142Calgary Hitman4Toronto Marlies3LSommaire du Match
18 - 2019-10-21161Peoria Riverman6Toronto Marlies1LSommaire du Match
19 - 2019-10-22172Toronto Marlies3Las Vegas Wranglers5LSommaire du Match
20 - 2019-10-23186Toronto Marlies2Lowell Devils4LSommaire du Match
22 - 2019-10-25202Toronto Marlies3Drummondville Voltigeurs5LSommaire du Match
23 - 2019-10-26210Milwaukee Admirals1Toronto Marlies2WSommaire du Match
26 - 2019-10-29235Las Vegas Wranglers5Toronto Marlies2LSommaire du Match
27 - 2019-10-30246Toronto Marlies2Binghampton Senators6LSommaire du Match
28 - 2019-10-31258Drummondville Voltigeurs5Toronto Marlies7WSommaire du Match
30 - 2019-11-02277Toronto Marlies9Victoriaville Tigres4WSommaire du Match
31 - 2019-11-03283Toronto Marlies5Portland Pirates4WXXSommaire du Match
33 - 2019-11-05298Sherbrooke Phoenix2Toronto Marlies6WSommaire du Match
34 - 2019-11-06311Toronto Marlies6Binghampton Senators4WSommaire du Match
36 - 2019-11-08324Chicoutimi Sagueneens2Toronto Marlies3WXSommaire du Match
38 - 2019-11-10349Rochester Americans3Toronto Marlies1LSommaire du Match
40 - 2019-11-12364Toronto Marlies4Boisbriand Armada3WXSommaire du Match
41 - 2019-11-13378Lake Erie Monsters3Toronto Marlies2LXSommaire du Match
43 - 2019-11-15399Peoria Riverman5Toronto Marlies9WSommaire du Match
44 - 2019-11-16409Toronto Marlies4Chicago Wolves3WXSommaire du Match
46 - 2019-11-18423Toronto Marlies5Peoria Riverman4WXSommaire du Match
47 - 2019-11-19438Hershey Bears3Toronto Marlies4WXXSommaire du Match
49 - 2019-11-21455Toronto Marlies2Hartford Wolf Pack8LSommaire du Match
50 - 2019-11-22470Milwaukee Admirals2Toronto Marlies9WSommaire du Match
52 - 2019-11-24484Toronto Marlies4Milwaukee Admirals5LXSommaire du Match
53 - 2019-11-25501Bridgeport Sound Tigers4Toronto Marlies3LSommaire du Match
55 - 2019-11-27518Chicago Wolves5Toronto Marlies2LSommaire du Match
56 - 2019-11-28530Toronto Marlies0Hershey Bears1LSommaire du Match
58 - 2019-11-30546Toronto Marlies1London Knights5LSommaire du Match
59 - 2019-12-01558Toronto Marlies0Lake Erie Monsters2LSommaire du Match
61 - 2019-12-03569Rimouski Oceanic1Toronto Marlies5WSommaire du Match
62 - 2019-12-04587Toronto Marlies4Worcester Sharks2WSommaire du Match
64 - 2019-12-06597Sherbrooke Phoenix4Toronto Marlies0LSommaire du Match
66 - 2019-12-08619Boisbriand Armada1Toronto Marlies2WXSommaire du Match
68 - 2019-12-10634Toronto Marlies1Lowell Devils4LSommaire du Match
69 - 2019-12-11647Toronto Marlies2Philadelphia Phantoms7LSommaire du Match
70 - 2019-12-12659Laval Rockets3Toronto Marlies1LSommaire du Match
72 - 2019-12-14678London Knights4Toronto Marlies2LSommaire du Match
74 - 2019-12-16698Toronto Marlies0Lake Erie Monsters4LSommaire du Match
76 - 2019-12-18710Grand Rapids Griffins8Toronto Marlies3LSommaire du Match
77 - 2019-12-19722Toronto Marlies10Grand Rapids Griffins11LSommaire du Match
78 - 2019-12-20739Hartford Wolf Pack8Toronto Marlies5LSommaire du Match
80 - 2019-12-22754Toronto Marlies9Brampton Battalion8WSommaire du Match
81 - 2019-12-23768Philadelphia Phantoms9Toronto Marlies3LSommaire du Match
83 - 2019-12-25782Toronto Marlies4Bridgeport Sound Tigers5LSommaire du Match
84 - 2019-12-26799Las Vegas Wranglers2Toronto Marlies7WSommaire du Match
85 - 2019-12-27811Toronto Marlies4Manitoba Moose3WSommaire du Match
87 - 2019-12-29827Lowell Devils10Toronto Marlies3LSommaire du Match
89 - 2019-12-31845Toronto Marlies2Milwaukee Admirals1WXSommaire du Match
91 - 2020-01-02859Lowell Devils1Toronto Marlies5WSommaire du Match
92 - 2020-01-03876Toronto Marlies2Texas Stars4LSommaire du Match
94 - 2020-01-05888Texas Stars4Toronto Marlies3LSommaire du Match
95 - 2020-01-06901Toronto Marlies5Quebec Rempart4WXSommaire du Match
97 - 2020-01-08917Toronto Marlies4Seattle Thunderbirds1WSommaire du Match
98 - 2020-01-09928Quebec Rempart2Toronto Marlies6WSommaire du Match
100 - 2020-01-11947Worcester Sharks5Toronto Marlies1LSommaire du Match
102 - 2020-01-13971Portland Pirates3Toronto Marlies10WSommaire du Match
104 - 2020-01-15985Toronto Marlies9Las Vegas Wranglers1WSommaire du Match
106 - 2020-01-171002Toronto Marlies6Drummondville Voltigeurs5WSommaire du Match
107 - 2020-01-181011Toronto Marlies7Calgary Hitman4WSommaire du Match
108 - 2020-01-191016Calgary Hitman4Toronto Marlies9WSommaire du Match
110 - 2020-01-211036Toronto Marlies1Sherbrooke Phoenix2LSommaire du Match
111 - 2020-01-221048Seattle Thunderbirds2Toronto Marlies1LXSommaire du Match
113 - 2020-01-241070Manitoba Moose3Toronto Marlies2LXSommaire du Match
114 - 2020-01-251078Toronto Marlies1Chicoutimi Sagueneens3LSommaire du Match
117 - 2020-01-281099Victoriaville Tigres2Toronto Marlies6WSommaire du Match
119 - 2020-01-301122Binghampton Senators5Toronto Marlies4LSommaire du Match
120 - 2020-01-311132Toronto Marlies7Chicoutimi Sagueneens3WSommaire du Match
122 - 2020-02-021139Toronto Marlies3Rimouski Oceanic2WXSommaire du Match
123 - 2020-02-031153Toronto Marlies1Rochester Americans5LSommaire du Match
124 - 2020-02-041165Brampton Battalion4Toronto Marlies3LXXSommaire du Match
128 - 2020-02-081189Brampton Battalion4Toronto Marlies5WXSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
129 - 2020-02-091197Toronto Marlies6Laval Rockets2WSommaire du Match
132 - 2020-02-121217Binghampton Senators2Toronto Marlies3WXSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets2512
Assistance80,27439,631
Assistance PCT97.90%96.66%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2925 - 97.48% 90,215$3,698,811$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,165,314$ 2,232,651$ 2,172,651$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 2,165,314$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 17,203$ 0$




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
2019822639010421312323-1141141804311157155241122106110155168-138131251582710691171141622956038078237229961065171513232148740.65%2308662.61%7685147446.47%830186944.41%626135646.17%147168318078081679856
Total Saison Régulière822639010421312323-1141141804311157155241122106110155168-138131251582710691171141622956038078237229961065171513232148740.65%2308662.61%7685147446.47%830186944.41%626135646.17%147168318078081679856