TORONTO Marlies

GP: 75 | W: 38 | L: 37 | OTL: 0 | P: 76
GF: 341 | GA: 242 | PP%: 17.09% | PK%: 78.74%
DG: Maxime Joseph | Morale : 89 | Moyenne d'Équipe : 60
Prochain matchs #981 vs HERSEY Bears
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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 SP
1Josh Archibald0X100.008341756866828167606667726755514276690
2Zach Sanford0X100.006441736688778065696663636454516567680
3David Kampf (R)0X100.006235756778827666817063726554514380680
4Joel L'Esperance0X100.005935716982585969716869536951504379640
5Zack MacEwen0X100.005889576984515269696363506450504479610
6Jordan Szwarz0X100.005089607072505070706464526452515279600
7Lane Pederson0X100.005089647072505070706464506450504479590
8Phil Lane (R)0X100.005540656581484052304649505160437179530
9Troy Bourke (R)0XX100.005089725862485058505151505150506379530
10Alex Schoenborn (R)0X100.005135737272454048304544505056518789520
11Mirco Mueller0X100.007241786585816665306457776655528176680
12Chris Butler0X100.005435666677555666304945555666553779580
13Jamie McBain0X100.005943725072617757304636605364575479570
14Dylan Coghlan0X100.005289687078505070305449515950504479570
15Julian Melchiori0X100.006489625992495059305045505551505379560
16Nelson Nogier (R)0X100.005335625579505055304641505150506183520
Rayé
MOYENNE D'ÉQUIPE100.00595768657859586349575457595451557960
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
1Vitek Vanecek100.00776683747675777675767150644478660
2Al Montoya100.00705868816969706969696563674779630
Rayé
MOYENNE D'ÉQUIPE100.0074627678737274737273685766467965
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Bob Hartley71717474797954CAN5931,267,000$


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
1Chris ButlerTORONTO Marlies (TOR)D7529709931420172802306716512.61%184160521.405510511250114111600.00%000001.2300000238
2Jordan SzwarzTORONTO Marlies (TOR)RW75673198462601748149512836313.54%44102513.68011817000005049.15%59000121.9100000742
3Zack MacEwenTORONTO Marlies (TOR)RW645440945470102286541310527713.08%20100815.764592377000055067.65%6800061.8600101465
4Zach SanfordTORONTO Marlies (TOR)LW6043499248240577341211528710.44%2689014.8443718531123353079.45%7300042.0700000343
5Julian MelchioriTORONTO Marlies (TOR)D7516547028961027370162521029.88%166133517.80033523000061300.00%000001.0500101213
6Troy BourkeTORONTO Marlies (TOR)C/LW642545705527571462476116410.12%19111217.38246167820271033057.47%8700001.2600100054
7Dylan CoghlanTORONTO Marlies (TOR)D6412566848380974315449937.79%71126419.7534738980003111100.00%000001.0800000322
8Josh ArchibaldTORONTO Marlies (TOR)RW363034646156096652477817712.15%1180522.3723516460002623065.12%17200031.5900000641
9Jamie McBainTORONTO Marlies (TOR)D751449635664018080183511037.65%135155720.77224361060110108200.00%000000.8100000121
10Joel L'EsperanceTORONTO Marlies (TOR)C64362056464060552187416116.51%2364510.091129170001412071.31%47400041.7300000123
11Phil LaneTORONTO Marlies (TOR)RW6412284043603322117469810.26%84256.6600000000000044.12%3400001.8800000011
12Ben HarpurTORONTO Maple LeafsD9134614010412298.33%815216.8900001000131000.00%000000.5300000000
13David KampfTORONTO Marlies (TOR)C1033400022130.00%02121.9500002000050063.64%3300002.7300000001
14Lane PedersonTORONTO Marlies (TOR)C64000000100000.00%000.010000000000000.00%100000.0000000000
Stats d'équipe Total ou en Moyenne7903394828215264672514526862892829200211.72%7151185115.002331542206493362167733066.83%1001000291.3900302293434
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
1Vitek VanecekTORONTO Marlies (TOR)64343000.9292.35380181114921060421.00036401161
2Al MontoyaTORONTO Marlies (TOR)10000.9094.2942003330000.0000064000
Stats d'équipe Total ou en Moyenne65343000.9292.37384381115221390421.000364641161


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Al MontoyaTORONTO Marlies (TOR)G341985-02-13No91 Kg188 CMNoNoNo2Sans RestrictionPro & Farm600,000$0$0$NoLien
Alex SchoenbornTORONTO Marlies (TOR)RW231995-12-12Yes91 Kg185 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$No
Chris ButlerTORONTO Marlies (TOR)D321986-10-27No89 Kg185 CMNoNoNo1Sans RestrictionPro & Farm650,000$0$0$NoLien
David KampfTORONTO Marlies (TOR)C241995-01-12Yes85 Kg188 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Dylan CoghlanTORONTO Marlies (TOR)D211998-02-19No86 Kg188 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Jamie McBainTORONTO Marlies (TOR)D311988-02-25No82 Kg185 CMNoNoNo1Sans RestrictionPro & Farm650,000$0$0$NoLien
Joel L'EsperanceTORONTO Marlies (TOR)C241995-08-18No95 Kg188 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Jordan SzwarzTORONTO Marlies (TOR)RW281991-05-14No91 Kg180 CMNoNoNo2Sans RestrictionPro & Farm750,000$0$0$NoLien
Josh ArchibaldTORONTO Marlies (TOR)RW261992-10-06No80 Kg178 CMNoNoNo6Avec RestrictionPro & Farm1,000,000$0$0$NoLien
Julian MelchioriTORONTO Marlies (TOR)D271991-12-06No97 Kg196 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Lane PedersonTORONTO Marlies (TOR)C221997-08-04No86 Kg183 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Mirco MuellerTORONTO Marlies (TOR)D241995-03-21No95 Kg191 CMNoNoNo4Avec RestrictionPro & Farm900,000$0$0$NoLien
Nelson NogierTORONTO Marlies (TOR)D231996-05-27Yes87 Kg188 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Phil LaneTORONTO Marlies (TOR)RW271992-05-29Yes99 Kg191 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$No
Troy BourkeTORONTO Marlies (TOR)C/LW251994-03-30Yes71 Kg178 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Vitek VanecekTORONTO Marlies (TOR)G231996-01-09No82 Kg185 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Zach SanfordTORONTO Marlies (TOR)LW241994-11-09No94 Kg193 CMNoNoNo6Avec RestrictionPro & Farm1,000,000$0$0$NoLien
Zack MacEwenTORONTO Marlies (TOR)RW231996-07-08No93 Kg191 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1825.6189 Kg188 CM2.89766,667$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
133023
2Troy BourkeZack MacEwen30023
3Jordan Szwarz27023
4Joel L'EsperancePhil Lane10032
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris Butler36023
2Jamie McBainDylan Coghlan31023
3Julian Melchiori28023
4Chris ButlerJamie McBain5032
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
150005
2Troy BourkeZack MacEwen50005
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris Butler50014
2Jamie McBainDylan Coghlan50014
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
150041
2Troy Bourke50041
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris Butler50050
2Jamie McBainDylan Coghlan50050
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
150050Chris Butler50050
250050Jamie McBainDylan Coghlan50050
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
150014
2Troy Bourke50014
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris Butler50023
2Jamie McBainDylan Coghlan50023
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris Butler
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris Butler
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Joel L'Esperance, Zack MacEwen, Joel L'Esperance, Zack MacEwenJoel L'Esperance
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jamie McBain, Dylan Coghlan, Julian MelchioriJamie McBainJamie McBain, Dylan Coghlan
Tirs de Pénalité
, , , , Joel L'Esperance
Gardien
#1 : Vitek Vanecek, #2 : Al Montoya
Lignes d'Attaque Perso. en Prol.
, , , , Joel L'Esperance, Zack MacEwen, Zack MacEwen, , Jordan Szwarz, , Lane Pederson
Lignes de Défense Perso. en Prol.
, Chris Butler, Jamie McBain, Dylan Coghlan, Julian Melchiori


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
1BELLEVILLE Senators523000001822-4312000001317-42110000055040.400182745001759568325510011057107891895116123400.00%8275.00%0706195336.15%608235925.77%429118136.33%195415241776408774394
2BRIDGEPORT Sound Tigers22000000312110000002111100000010141.000369011759568332100110571078989301840200.00%90100.00%0706195336.15%608235925.77%429118136.33%195415241776408774394
3BROOKLYN Wolfpack33000000372352200000024222110000001301361.00037609702175956832681001105710789309473000.00%20100.00%0706195336.15%608235925.77%429118136.33%195415241776408774394
4CHICAGO Wolves22000000250251100000011011110000001401441.0002545700217595683199100110571078992029000.00%000.00%0706195336.15%608235925.77%429118136.33%195415241776408774394
5CLEVELAND Monsters22000000191181100000010731100000094541.0001928470017595683128100110571078943161040000.00%5260.00%0706195336.15%608235925.77%429118136.33%195415241776408774394
6COLORADO Eagles20200000313-101010000028-61010000015-400.00034700175956833610011057107899124837700.00%4250.00%0706195336.15%608235925.77%429118136.33%195415241776408774394
7CORNWALL Aces44000000375322200000022022220000001551081.00037599602175956833231001105710789731512129300.00%6183.33%1706195336.15%608235925.77%429118136.33%195415241776408774394
8HERSEY Bears1010000006-6000000000001010000006-600.00000000175956831710011057107894516621500.00%3233.33%0706195336.15%608235925.77%429118136.33%195415241776408774394
9HOLLYWOOD Oscar44000000392372200000020119220000001911881.000396710602175956833811001105710789264483000.00%20100.00%0706195336.15%608235925.77%429118136.33%195415241776408774394
10IOWA Wild3120000012841100000010192020000027-520.33312223400175956839910011057107891072412708225.00%6183.33%0706195336.15%608235925.77%429118136.33%195415241776408774394
11LAVAL Rockets21100000440110000003211010000012-120.50047110017595683291001105710789953612289333.33%6183.33%0706195336.15%608235925.77%429118136.33%195415241776408774394
12LEHIGH VALLEY Phantoms4310000012842110000045-12200000083560.750121628001759568395100110571078915245246322522.73%110100.00%0706195336.15%608235925.77%429118136.33%195415241776408774394
13MANITOBA Moose40400000425-2120200000216-142020000029-700.00044800175956838510011057107892226522721317.69%9277.78%0706195336.15%608235925.77%429118136.33%195415241776408774394
14MILWAUKEE Admirals2110000045-11010000024-21100000021120.5004711001759568358100110571078976248331119.09%2150.00%0706195336.15%608235925.77%429118136.33%195415241776408774394
15MONT-LAURIER Sommet514000001124-132110000065130300000519-1420.2001121320017595683135100110571078922977237910440.00%8362.50%0706195336.15%608235925.77%429118136.33%195415241776408774394
16PROVIDENCE Bruins2020000003-31010000002-21010000001-100.0000000017595683321001105710789121411827200.00%70100.00%0706195336.15%608235925.77%429118136.33%195415241776408774394
17PV Sharapovas40400000916-72020000069-32020000037-400.00091423101759568385100110571078915158316613538.46%11372.73%0706195336.15%608235925.77%429118136.33%195415241776408774394
18ROCKFORD IceHogs20200000111-101010000005-51010000016-500.000123001759568318100110571078995202029100.00%10190.00%0706195336.15%608235925.77%429118136.33%195415241776408774394
19SAN DIEGO Gulls2200000014113110000009091100000051441.00014264001175956831591001105710789132954000.00%20100.00%0706195336.15%608235925.77%429118136.33%195415241776408774394
20STOCKTON Flames412000101924-521100000149520100010515-1040.500192443001759568314710011057107891805220809111.11%10460.00%0706195336.15%608235925.77%429118136.33%195415241776408774394
21SYRACUSE Crunch4030100039-62010100024-22020000015-420.25035800175956836910011057107891586062991800.00%18383.33%0706195336.15%608235925.77%429118136.33%195415241776408774394
22TUSCON Roadrunners211000001046110000009181010000013-220.500101525001759568372100110571078972276364125.00%3166.67%0706195336.15%608235925.77%429118136.33%195415241776408774394
Total75353702010341242993721150100020411094381422010101371325760.5073415538942111759568331421001105710789260379441314791582717.09%1743778.74%2706195336.15%608235925.77%429118136.33%195415241776408774394
24UTICA Comets2020000029-71010000024-21010000005-500.0002351017595683231001105710789115311833500.00%9544.44%0706195336.15%608235925.77%429118136.33%195415241776408774394
25VICTORIAVILLE Tigres422000001419-52200000093620200000516-1140.50014253900175956838610011057107891594836569222.22%17382.35%0706195336.15%608235925.77%429118136.33%195415241776408774394
26WILKIES-BARRIE Penguins430010004110312200000022418210010001961381.000416610701175956833111001105710789631714793266.67%60100.00%1706195336.15%608235925.77%429118136.33%195415241776408774394
_Since Last GM Reset75353702010341242993721150100020411094381422010101371325760.5073415538942111759568331421001105710789260379441314791582717.09%1743778.74%2706195336.15%608235925.77%429118136.33%195415241776408774394
_Vs Conference492125020102191724724131001000130745625815010108998-9480.49021935056915175956832071100110571078917095162769991122219.64%1122280.36%2706195336.15%608235925.77%429118136.33%195415241776408774394
_Vs Division169100200011238748550100062194384501000501931220.688112176288041759568385110011057107894221337631632721.88%36488.89%1706195336.15%608235925.77%429118136.33%195415241776408774394

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7576L2341553894314226037944131479211
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7535372010341242
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3721151000204110
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3814221010137132
Derniers 10 Matchs
WLOTWOTL SOWSOL
370000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1582717.09%1743778.74%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
100110571078917595683
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
706195336.15%608235925.77%429118136.33%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
195415241776408774394


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 - 2019-07-3012CLEVELAND Monsters7TORONTO Marlies10WSommaire du Match
2 - 2019-07-3118TORONTO Marlies10CORNWALL Aces4WSommaire du Match
3 - 2019-08-0128TORONTO Marlies0MONT-LAURIER Sommet9LSommaire du Match
4 - 2019-08-0241BELLEVILLE Senators11TORONTO Marlies5LSommaire du Match
6 - 2019-08-0460MANITOBA Moose10TORONTO Marlies2LSommaire du Match
8 - 2019-08-0680BELLEVILLE Senators5TORONTO Marlies3LSommaire du Match
9 - 2019-08-0785TORONTO Marlies7WILKIES-BARRIE Penguins6WXSommaire du Match
10 - 2019-08-08103STOCKTON Flames6TORONTO Marlies13WSommaire du Match
11 - 2019-08-09108TORONTO Marlies1MANITOBA Moose7LSommaire du Match
12 - 2019-08-10118TORONTO Marlies5VICTORIAVILLE Tigres11LSommaire du Match
14 - 2019-08-12134TORONTO Marlies1STOCKTON Flames12LSommaire du Match
15 - 2019-08-13144VICTORIAVILLE Tigres2TORONTO Marlies7WSommaire du Match
17 - 2019-08-15166TORONTO Marlies6LEHIGH VALLEY Phantoms2WSommaire du Match
18 - 2019-08-16170HOLLYWOOD Oscar1TORONTO Marlies12WSommaire du Match
20 - 2019-08-18191MONT-LAURIER Sommet2TORONTO Marlies4WSommaire du Match
22 - 2019-08-20210IOWA Wild1TORONTO Marlies10WSommaire du Match
23 - 2019-08-21220TORONTO Marlies14CHICAGO Wolves0WSommaire du Match
24 - 2019-08-22232TORONTO Marlies13BROOKLYN Wolfpack0WSommaire du Match
25 - 2019-08-23246CHICAGO Wolves0TORONTO Marlies11WSommaire du Match
26 - 2019-08-24260SAN DIEGO Gulls0TORONTO Marlies9WSommaire du Match
28 - 2019-08-26274TORONTO Marlies2MILWAUKEE Admirals1WSommaire du Match
29 - 2019-08-27288TORONTO Marlies12WILKIES-BARRIE Penguins0WSommaire du Match
30 - 2019-08-28298VICTORIAVILLE Tigres1TORONTO Marlies2WSommaire du Match
31 - 2019-08-29311TORONTO Marlies0VICTORIAVILLE Tigres5LSommaire du Match
32 - 2019-08-30323TORONTO Marlies5SAN DIEGO Gulls1WSommaire du Match
33 - 2019-08-31334BRIDGEPORT Sound Tigers1TORONTO Marlies2WSommaire du Match
34 - 2019-09-01350SYRACUSE Crunch1TORONTO Marlies2WXR3Sommaire du Match
36 - 2019-09-03364TORONTO Marlies4STOCKTON Flames3WXXSommaire du Match
37 - 2019-09-04375PV Sharapovas3TORONTO Marlies2LSommaire du Match
38 - 2019-09-05393BELLEVILLE Senators1TORONTO Marlies5WSommaire du Match
40 - 2019-09-07404TORONTO Marlies1IOWA Wild3LSommaire du Match
41 - 2019-09-08417PV Sharapovas6TORONTO Marlies4LSommaire du Match
43 - 2019-09-10431TORONTO Marlies1IOWA Wild4LSommaire du Match
44 - 2019-09-11443SYRACUSE Crunch3TORONTO Marlies0LR3Sommaire du Match
45 - 2019-09-12453TORONTO Marlies2BELLEVILLE Senators1WSommaire du Match
47 - 2019-09-14470TORONTO Marlies2LEHIGH VALLEY Phantoms1WSommaire du Match
48 - 2019-09-15481TUSCON Roadrunners1TORONTO Marlies9WSommaire du Match
49 - 2019-09-16493TORONTO Marlies2PV Sharapovas4LSommaire du Match
50 - 2019-09-17506LEHIGH VALLEY Phantoms1TORONTO Marlies2WSommaire du Match
51 - 2019-09-18522ROCKFORD IceHogs5TORONTO Marlies0LSommaire du Match
52 - 2019-09-19533TORONTO Marlies1PV Sharapovas3LSommaire du Match
54 - 2019-09-21548HOLLYWOOD Oscar0TORONTO Marlies8WSommaire du Match
55 - 2019-09-22558TORONTO Marlies0SYRACUSE Crunch1LR3Sommaire du Match
57 - 2019-09-24573LAVAL Rockets2TORONTO Marlies3WSommaire du Match
58 - 2019-09-25583TORONTO Marlies1BRIDGEPORT Sound Tigers0WSommaire du Match
60 - 2019-09-27597TORONTO Marlies0PROVIDENCE Bruins1LSommaire du Match
61 - 2019-09-28609STOCKTON Flames3TORONTO Marlies1LSommaire du Match
64 - 2019-10-01628PROVIDENCE Bruins2TORONTO Marlies0LSommaire du Match
65 - 2019-10-02636TORONTO Marlies10HOLLYWOOD Oscar0WSommaire du Match
67 - 2019-10-04648TORONTO Marlies9CLEVELAND Monsters4WSommaire du Match
68 - 2019-10-05661CORNWALL Aces0TORONTO Marlies12WSommaire du Match
70 - 2019-10-07681TORONTO Marlies0HERSEY Bears6LR3Sommaire du Match
71 - 2019-10-08687LEHIGH VALLEY Phantoms4TORONTO Marlies2LSommaire du Match
73 - 2019-10-10703TORONTO Marlies1SYRACUSE Crunch4LR3Sommaire du Match
74 - 2019-10-11714MONT-LAURIER Sommet3TORONTO Marlies2LSommaire du Match
75 - 2019-10-12727TORONTO Marlies1COLORADO Eagles5LSommaire du Match
76 - 2019-10-13737CORNWALL Aces0TORONTO Marlies10WSommaire du Match
77 - 2019-10-14752TORONTO Marlies1LAVAL Rockets2LSommaire du Match
79 - 2019-10-16764MILWAUKEE Admirals4TORONTO Marlies2LSommaire du Match
80 - 2019-10-17782BROOKLYN Wolfpack0TORONTO Marlies11WSommaire du Match
83 - 2019-10-20806COLORADO Eagles8TORONTO Marlies2LSommaire du Match
84 - 2019-10-21816TORONTO Marlies5CORNWALL Aces1WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
85 - 2019-10-22831BROOKLYN Wolfpack2TORONTO Marlies13WSommaire du Match
86 - 2019-10-23837TORONTO Marlies0UTICA Comets5LSommaire du Match
87 - 2019-10-24852TORONTO Marlies3BELLEVILLE Senators4LSommaire du Match
88 - 2019-10-25863WILKIES-BARRIE Penguins2TORONTO Marlies11WSommaire du Match
89 - 2019-10-26870TORONTO Marlies2MONT-LAURIER Sommet5LSommaire du Match
90 - 2019-10-27883TORONTO Marlies3MONT-LAURIER Sommet5LSommaire du Match
92 - 2019-10-29896MANITOBA Moose6TORONTO Marlies0LSommaire du Match
94 - 2019-10-31916WILKIES-BARRIE Penguins2TORONTO Marlies11WSommaire du Match
95 - 2019-11-01928TORONTO Marlies1ROCKFORD IceHogs6LSommaire du Match
97 - 2019-11-03939UTICA Comets4TORONTO Marlies2LSommaire du Match
98 - 2019-11-04943TORONTO Marlies9HOLLYWOOD Oscar1WSommaire du Match
100 - 2019-11-06964TORONTO Marlies1MANITOBA Moose2LSommaire du Match
101 - 2019-11-07972TORONTO Marlies1TUSCON Roadrunners3LSommaire du Match
102 - 2019-11-08981HERSEY Bears-TORONTO Marlies-
104 - 2019-11-10994TORONTO Marlies-TUSCON Roadrunners-
106 - 2019-11-121012IOWA Wild-TORONTO Marlies-



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
2 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,480,335$ 1,380,000$ 1,380,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,284,380$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 6 24,738$ 148,428$




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
3275353702010341242993721150100020411094381422010101371325763415538942111759568331421001105710789260379441314791582717.09%1743778.74%2706195336.15%608235925.77%429118136.33%195415241776408774394
Total Saison Régulière75353702010341242993721150100020411094381422010101371325763415538942111759568331421001105710789260379441314791582717.09%1743778.74%2706195336.15%608235925.77%429118136.33%195415241776408774394