Marlies de Toronto

GP: 38 | W: 16 | L: 17 | OTL: 5 | P: 37
GF: 107 | GA: 115 | PP%: 17.78% | PK%: 82.24%
DG: Benoit Paulin | Morale : 98 | Moyenne d'Équipe : 65
Prochain matchs #511 vs IOWA Wild
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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
1Casey Mittelstadt0X100.006239886677818364716362656663658798690
2Adam Erne0X100.008947776380748762586159576368657498680
3Henrik Borgstrom0X100.006443866483807766736159636665628198680
4Brett Ritchie0X100.008450786189737559525758605973686298670
5John Quenneville (R)0X100.006145866376838061736062646367647698670
6Paul Bittner (R)0XX100.007351875990858258555756605967647398670
7Dominic Toninato (R)0X100.006347826179807859655860625971665798670
8Jordan Kyrou (R)0X100.005739896769777666586364656863647698670
9Lukas Vejdemo (R)0X100.006245906279788363746158646567646298670
10Rasmus Asplund (R)0X100.005839826670817863726461656365667799670
11Isaac Ratcliffe (R)0X100.007452835692858755515454595361627698660
12Nicholas Merkley (R)0X100.005842896069777362576159586265637898640
13Matthew Phillips (R)0X100.005339876157837862586059576263616498640
14Spencer Smallman (R)0X100.006345846077757361555952586167635298640
15Daniel O'Regan (R)0X100.004435827658474161485858585858497998570
16Ryan Collins (R)0X100.007749875593767856305354604567647098650
17Martin Fehervary (R)0X100.006445876081847458305757594661637498650
18Nick Ebert0X100.006247865774828156305554584671665998640
19Jesper Lindgren (R)0X100.005341835867757457305652545165636698610
20Andrew Welinski (R)0X100.004835816575474350304140564960507198520
Rayé
MOYENNE D'ÉQUIPE100.00634485627776756054585760586563719865
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
1Ville Husso (R)100.00748482847372747372747369736198680
2Marcus Hogberg (R)100.00737573917271737271737271756298670
3Veini Vehvilainen (R)100.00718280717069717069717065696298640
Rayé
1Brandon Halverson (R)100.00605856885958605958605967716798570
MOYENNE D'ÉQUIPE100.0070757384696870696870696872639864
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Eric Veilleux66666666707074CAN483300,000$


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
1Ryan CollinsMarlies de Toronto (TOR)D3882836-12560117589328678.60%10792724.4235843116000070000.00%000000.7800000320
2Casey MittelstadtMarlies de Toronto (TOR)C38191635-22042881734810510.98%2971918.9368143611300051162256.87%77900010.9713000114
3Brett RitchieMarlies de Toronto (TOR)RW38121729-2100644115234957.89%1868418.0235835113000001047.83%4600000.8511000130
4Adam ErneMarlies de Toronto (TOR)LW38111728-233510851135421108.15%2173419.34246201130003470059.52%4200010.7601000111
5Paul BittnerMarlies de Toronto (TOR)C/LW38111627-3140703914335817.69%1559315.61481237113000023151.28%3900000.9100000122
6Martin FehervaryMarlies de Toronto (TOR)D3851621-938045275217469.62%4976520.1526825106000075000.00%000000.5500000001
7Henrik BorgstromMarlies de Toronto (TOR)C38128206120227090176013.33%947212.45000000004503056.46%60400110.8533000031
8Nick EbertMarlies de Toronto (TOR)D3871118-8315481758202612.07%3774419.5942632105000061110.00%000000.4800001102
9Isaac RatcliffeMarlies de Toronto (TOR)LW3877146140442339113917.95%941610.9700000000001152.50%4000000.6700000201
10Jesper LindgrenMarlies de Toronto (TOR)D381111291604323299103.45%3854714.400003800029000.00%000000.4400000011
11Andrew WelinskiMarlies de Toronto (TOR)D38291191404017166712.50%4155814.7100000000039000.00%000000.3900000010
12John QuennevilleMarlies de Toronto (TOR)C385510-1460315010537924.76%103779.9300000000001057.86%33700000.5300000011
13Matthew PhillipsMarlies de Toronto (TOR)RW3837106007427717513.90%441710.9700000000000048.65%3700000.4800000000
14Dominic ToninatoMarlies de Toronto (TOR)C38000000203010.00%170.20000120000000100.00%100000.0000000000
15Jordan KyrouMarlies de Toronto (TOR)C38000000000000.00%020.060000200000000.00%000000.0000000000
16Lukas VejdemoMarlies de Toronto (TOR)C38000000401000.00%2330.89000000001260020.00%500000.0000000000
Stats d'équipe Total ou en Moyenne608103168271-162461068754611663217908.83%390800413.162438622327940001550112556.32%193000130.6858001101514
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
1Ville HussoMarlies de Toronto (TOR)38161750.9182.9623084111413880410.81811380810
Stats d'équipe Total ou en Moyenne38161750.9182.9623084111413880410.81811380810


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 Salaire RestantSalaire MoyenSalaire Moyen RestantCap 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 ErneMarlies de Toronto (TOR)LW251995-04-20No96 Kg185 CMNoNoNo4Pro & Farm800,000$418,348$800,000$418,348$0$0$No800,000$800,000$800,000$Lien
Andrew WelinskiMarlies de Toronto (TOR)D271993-04-27Yes91 Kg188 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Brandon HalversonMarlies de Toronto (TOR)G241996-03-29Yes95 Kg193 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Brett RitchieMarlies de Toronto (TOR)RW271993-07-01No100 Kg193 CMNoNoNo2Pro & Farm1,750,000$915,137$1,750,000$915,137$0$0$No1,750,000$Lien
Casey MittelstadtMarlies de Toronto (TOR)C211998-11-22No90 Kg185 CMNoNoNo1Pro & Farm750,000$392,201$750,000$392,201$0$0$NoLien
Daniel O'ReganMarlies de Toronto (TOR)C261994-01-30Yes82 Kg175 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Dominic ToninatoMarlies de Toronto (TOR)C261994-03-09Yes87 Kg188 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Henrik BorgstromMarlies de Toronto (TOR)C231997-08-06No90 Kg191 CMNoNoNo1Pro & Farm750,000$392,201$750,000$392,201$0$0$NoLien
Isaac RatcliffeMarlies de Toronto (TOR)LW211999-02-15Yes91 Kg198 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Jesper LindgrenMarlies de Toronto (TOR)D231997-05-19Yes75 Kg183 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
John QuennevilleMarlies de Toronto (TOR)C241996-04-16Yes89 Kg185 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Jordan KyrouMarlies de Toronto (TOR)C221998-05-05Yes80 Kg183 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Lukas VejdemoMarlies de Toronto (TOR)C241996-01-25Yes88 Kg188 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Marcus HogbergMarlies de Toronto (TOR)G251994-11-25Yes95 Kg196 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Martin FehervaryMarlies de Toronto (TOR)D201999-10-06Yes91 Kg188 CMNoNoNo1Pro & Farm750,000$392,201$750,000$392,201$0$0$No
Matthew PhillipsMarlies de Toronto (TOR)RW221998-04-06Yes64 Kg170 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Nicholas MerkleyMarlies de Toronto (TOR)RW231997-05-23Yes88 Kg178 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Nick EbertMarlies de Toronto (TOR)D261994-05-11No91 Kg183 CMNoNoNo1Pro & Farm750,000$392,201$750,000$392,201$0$0$NoLien
Paul BittnerMarlies de Toronto (TOR)C/LW231996-11-04Yes93 Kg196 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Rasmus AsplundMarlies de Toronto (TOR)C221997-12-03Yes86 Kg180 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Ryan CollinsMarlies de Toronto (TOR)D241996-05-06Yes98 Kg196 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Spencer SmallmanMarlies de Toronto (TOR)RW231996-09-09Yes90 Kg185 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Veini VehvilainenMarlies de Toronto (TOR)G231997-02-13Yes82 Kg183 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Ville HussoMarlies de Toronto (TOR)G251995-02-06Yes93 Kg191 CMNoNoNo4Pro & Farm750,000$392,201$750,000$392,201$0$0$No750,000$750,000$750,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2423.7189 Kg188 CM3.42793,750$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Adam ErneBrett Ritchie31122
2Paul BittnerCasey Mittelstadt26122
3Isaac RatcliffeHenrik BorgstromMatthew Phillips23122
4John Quenneville20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan Collins31122
2Martin FehervaryNick Ebert26122
3Jesper LindgrenAndrew Welinski23122
4Ryan Collins20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Adam ErneBrett Ritchie55122
2Paul BittnerCasey Mittelstadt45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan Collins55122
2Martin FehervaryNick Ebert45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Casey Mittelstadt55122
2Henrik BorgstromAdam Erne45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan Collins55122
2Martin FehervaryNick Ebert45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
155122Ryan Collins55122
2Casey Mittelstadt45122Martin FehervaryNick Ebert45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Casey Mittelstadt55122
2Henrik BorgstromAdam Erne45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan Collins55122
2Martin FehervaryNick Ebert45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Adam ErneBrett RitchieRyan Collins
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Adam ErneBrett RitchieRyan Collins
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dominic Toninato, Jordan Kyrou, Lukas VejdemoDominic Toninato, Jordan KyrouLukas Vejdemo
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jesper Lindgren, Andrew Welinski, Martin FehervaryJesper LindgrenAndrew Welinski, Martin Fehervary
Tirs de Pénalité
, Casey Mittelstadt, Henrik Borgstrom, Adam Erne, Brett Ritchie
Gardien
#1 : Ville Husso, #2 : Marcus Hogberg
Lignes d'Attaque Perso. en Prol.
, Casey Mittelstadt, Henrik Borgstrom, Adam Erne, Brett Ritchie, John Quenneville, John Quenneville, Paul Bittner, Dominic Toninato, Jordan Kyrou, Lukas Vejdemo
Lignes de Défense Perso. en Prol.
, Ryan Collins, Martin Fehervary, Nick Ebert, Jesper Lindgren


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
1BRIDGEPORT Sound Tigers2010100056-11010000024-21000100032120.50059140035392874337739240614852514333133.33%5340.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
2BROOKLYN Wolfpack10000010431100000104310000000000021.00045900353928730377392406142851718500.00%20100.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
3Binghampton Devils2010010036-32010010036-30000000000010.2503690035392876737739240614901311474125.00%30100.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
4CHICAGO Wolves11000000321110000003210000000000021.000358003539287353773924061433104223133.33%20100.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
5COLORADO Eagles1010000035-21010000035-20000000000000.0003691035392871637739240614411510204125.00%5260.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
6HERSEY Bears22000000844000000000002200000084441.00081422013539287443773924061460136266350.00%30100.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
7HOLLYWOOD Oscar1010000003-31010000003-30000000000000.000000003539287243773924061443141014700.00%5180.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
8IOWA Wild2020000038-51010000024-21010000014-300.0003690035392876637739240614702912428112.50%6266.67%0502120641.63%520140137.12%21755838.89%8626141002264446214
9LAVAL Rockets20200000011-110000000000020200000011-1100.000000003539287423773924061480211828600.00%7185.71%0502120641.63%520140137.12%21755838.89%8626141002264446214
10LEHIGH VALLEY Phantoms11000000422000000000001100000042221.000461000353928736377392406143164114250.00%20100.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
11MONT-LAURIER Sommet11000000532000000000001100000053221.000571200353928739377392406141984174125.00%20100.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
12Manitoba Moose2020000037-4000000000002020000037-400.0003690035392874637739240614722514396116.67%7271.43%0502120641.63%520140137.12%21755838.89%8626141002264446214
13PROVIDENCE Bruins1010000034-1000000000001010000034-100.000369003539287183773924061453174185240.00%20100.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
14PV Sharapovas2020000048-41010000025-31010000023-100.0004610003539287573773924061498281438500.00%7185.71%0502120641.63%520140137.12%21755838.89%8626141002264446214
15Quebec Nordiques21000010743210000107430000000000041.000710170035392877337739240614521020424125.00%9188.89%0502120641.63%520140137.12%21755838.89%8626141002264446214
16ROCKFORD IceHogs11000000321000000000001100000032121.00034700353928733377392406142912412400.00%20100.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
17SAN DIEGO Gulls22000000194151100000092711000000102841.00019325100353928713537739240614381310442150.00%5180.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
18STOCKTON Flames2010001045-1100000103211010000013-220.50044800353928759377392406147721103612216.67%5180.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
19Syracruse Crunch311010001055201010004401100000061540.667101727003539287983773924061411021224810110.00%8187.50%0502120641.63%520140137.12%21755838.89%8626141002264446214
20TUSCON Roadrunners1000010023-1000000000001000010023-110.5002350035392872337739240614267618400.00%3166.67%0502120641.63%520140137.12%21755838.89%8626141002264446214
Total38111702530107115-82048014305359-61879011005456-2370.48710717428111353928711783773924061413894052506871352417.78%1071982.24%0502120641.63%520140137.12%21755838.89%8626141002264446214
22UTICA Comets1010000035-2000000000001010000035-200.000347003539287313773924061439168265120.00%40100.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
23VICTORIAVILLE Tigres2010010025-32010010025-30000000000010.2502460035392876237739240614781810318112.50%50100.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
24WILKIES-BARRIE Penguins31000200910-131000200910-10000000000040.667914230035392871013773924061413758185716318.75%8275.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
_Since Last GM Reset38111702530107115-82048014305359-61879011005456-2370.48710717428111353928711783773924061413894052506871352417.78%1071982.24%0502120641.63%520140137.12%21755838.89%8626141002264446214
_Vs Conference1566011105349452200010211651044011003233-1170.567538814111353928745037739240614512154101265471021.28%40880.00%0502120641.63%520140137.12%21755838.89%8626141002264446214
_Vs Division82200110332310300000101275522001002116570.43833508300353928731137739240614242794815534514.71%24483.33%0502120641.63%520140137.12%21755838.89%8626141002264446214

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
3837L11071742811178138940525068711
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
3811172530107115
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
204814305359
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
187911005456
Derniers 10 Matchs
WLOTWOTL SOWSOL
550000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1352417.78%1071982.24%0
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
377392406143539287
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
502120641.63%520140137.12%21755838.89%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
8626141002264446214


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 - 2020-08-024Marlies de Toronto1IOWA Wild4LSommaire du Match
2 - 2020-08-0319Quebec Nordiques1Marlies de Toronto3WSommaire du Match
4 - 2020-08-0533VICTORIAVILLE Tigres2Marlies de Toronto1LXSommaire du Match
6 - 2020-08-0756WILKIES-BARRIE Penguins4Marlies de Toronto3LXSommaire du Match
7 - 2020-08-0866Marlies de Toronto3BRIDGEPORT Sound Tigers2WXSommaire du Match
9 - 2020-08-1083WILKIES-BARRIE Penguins3Marlies de Toronto2LXSommaire du Match
11 - 2020-08-1299Marlies de Toronto5MONT-LAURIER Sommet3WSommaire du Match
12 - 2020-08-13112Marlies de Toronto3PROVIDENCE Bruins4LSommaire du Match
13 - 2020-08-14125Binghampton Devils2Marlies de Toronto1LXSommaire du Match
14 - 2020-08-15135Syracruse Crunch2Marlies de Toronto1LSommaire du Match
16 - 2020-08-17150Marlies de Toronto3HERSEY Bears0WSommaire du Match
17 - 2020-08-18162Quebec Nordiques3Marlies de Toronto4WXXSommaire du Match
18 - 2020-08-19175Marlies de Toronto2TUSCON Roadrunners3LXSommaire du Match
19 - 2020-08-20180Marlies de Toronto2Manitoba Moose4LSommaire du Match
20 - 2020-08-21193PV Sharapovas5Marlies de Toronto2LSommaire du Match
22 - 2020-08-23212STOCKTON Flames2Marlies de Toronto3WXXSommaire du Match
24 - 2020-08-25235VICTORIAVILLE Tigres3Marlies de Toronto1LSommaire du Match
25 - 2020-08-26250Marlies de Toronto3ROCKFORD IceHogs2WSommaire du Match
26 - 2020-08-27261COLORADO Eagles5Marlies de Toronto3LSommaire du Match
28 - 2020-08-29277Marlies de Toronto6Syracruse Crunch1WSommaire du Match
29 - 2020-08-30285Marlies de Toronto0LAVAL Rockets7LSommaire du Match
30 - 2020-08-31292SAN DIEGO Gulls2Marlies de Toronto9WSommaire du Match
32 - 2020-09-02313CHICAGO Wolves2Marlies de Toronto3WSommaire du Match
33 - 2020-09-03324Marlies de Toronto0LAVAL Rockets4LSommaire du Match
34 - 2020-09-04332Marlies de Toronto1Manitoba Moose3LSommaire du Match
35 - 2020-09-05345IOWA Wild4Marlies de Toronto2LSommaire du Match
37 - 2020-09-07364WILKIES-BARRIE Penguins3Marlies de Toronto4WSommaire du Match
38 - 2020-09-08373Marlies de Toronto3UTICA Comets5LR3Sommaire du Match
40 - 2020-09-10389BROOKLYN Wolfpack3Marlies de Toronto4WXXSommaire du Match
41 - 2020-09-11402Marlies de Toronto4LEHIGH VALLEY Phantoms2WSommaire du Match
43 - 2020-09-13418Marlies de Toronto1STOCKTON Flames3LSommaire du Match
44 - 2020-09-14421Binghampton Devils4Marlies de Toronto2LSommaire du Match
45 - 2020-09-15438Marlies de Toronto2PV Sharapovas3LSommaire du Match
46 - 2020-09-16447Syracruse Crunch2Marlies de Toronto3WXSommaire du Match
48 - 2020-09-18462Marlies de Toronto10SAN DIEGO Gulls2WSommaire du Match
49 - 2020-09-19474HOLLYWOOD Oscar3Marlies de Toronto0LSommaire du Match
50 - 2020-09-20488Marlies de Toronto5HERSEY Bears4WSommaire du Match
51 - 2020-09-21497BRIDGEPORT Sound Tigers4Marlies de Toronto2LSommaire du Match
53 - 2020-09-23511Marlies de Toronto-IOWA Wild-
54 - 2020-09-24525BELLEVILLE Senators-Marlies de Toronto-
56 - 2020-09-26541Marlies de Toronto-Quebec Nordiques-
57 - 2020-09-27551Quebec Nordiques-Marlies de Toronto-
58 - 2020-09-28560Marlies de Toronto-WILKIES-BARRIE Penguins-
59 - 2020-09-29579PV Sharapovas-Marlies de Toronto-
60 - 2020-09-30586Marlies de Toronto-BRIDGEPORT Sound Tigers-
61 - 2020-10-01602LAVAL Rockets-Marlies de Toronto-
63 - 2020-10-03616Marlies de Toronto-Manitoba Moose-
64 - 2020-10-04629HERSEY Bears-Marlies de Toronto-
65 - 2020-10-05644Marlies de Toronto-STOCKTON Flames-
66 - 2020-10-06653Marlies de Toronto-Binghampton Devils-
67 - 2020-10-07660MONT-LAURIER Sommet-Marlies de Toronto-
69 - 2020-10-09677Marlies de Toronto-MILWAUKEE Admirals-
70 - 2020-10-10688TUSCON Roadrunners-Marlies de Toronto-
71 - 2020-10-11704Marlies de Toronto-PROVIDENCE Bruins-
72 - 2020-10-12713ROCKFORD IceHogs-Marlies de Toronto-
74 - 2020-10-14728Marlies de Toronto-SAN DIEGO Gulls-
75 - 2020-10-15738Manitoba Moose-Marlies de Toronto-
77 - 2020-10-17757VICTORIAVILLE Tigres-Marlies de Toronto-
78 - 2020-10-18766Marlies de Toronto-CHICAGO Wolves-
79 - 2020-10-19782UTICA Comets-Marlies de Toronto-
81 - 2020-10-21796Marlies de Toronto-TUSCON Roadrunners-
82 - 2020-10-22811CHICAGO Wolves-Marlies de Toronto-
83 - 2020-10-23823Marlies de Toronto-COLORADO Eagles-
84 - 2020-10-24829Marlies de Toronto-VICTORIAVILLE Tigres-
85 - 2020-10-25843ROCKFORD IceHogs-Marlies de Toronto-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
87 - 2020-10-27856Marlies de Toronto-HOLLYWOOD Oscar-
88 - 2020-10-28866Marlies de Toronto-BROOKLYN Wolfpack-
89 - 2020-10-29874LEHIGH VALLEY Phantoms-Marlies de Toronto-
90 - 2020-10-30891Marlies de Toronto-BELLEVILLE Senators-
91 - 2020-10-31899Marlies de Toronto-MONT-LAURIER Sommet-
92 - 2020-11-01908LEHIGH VALLEY Phantoms-Marlies de Toronto-
93 - 2020-11-02922Marlies de Toronto-BELLEVILLE Senators-
94 - 2020-11-03933PROVIDENCE Bruins-Marlies de Toronto-
95 - 2020-11-04947Marlies de Toronto-BROOKLYN Wolfpack-
97 - 2020-11-06959LAVAL Rockets-Marlies de Toronto-
99 - 2020-11-08977COLORADO Eagles-Marlies de Toronto-
102 - 2020-11-11997MILWAUKEE Admirals-Marlies de Toronto-
103 - 2020-11-121007Marlies de Toronto-UTICA Comets-
106 - 2020-11-151027MILWAUKEE Admirals-Marlies de Toronto-
107 - 2020-11-161032Marlies de Toronto-HOLLYWOOD Oscar-



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
20 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
911,556$ 1,905,000$ 1,905,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 908,804$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 57 17,477$ 996,189$




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
338297300000136849-713415360000073422-349414370000063427-3641813623737300733528015145715064370661919657611039955.05%311067.74%0363119630.35%342222915.34%310160019.38%7174593438496764249
3438111702530107115-82048014305359-61879011005456-23710717428111353928711783773924061413894052506871352417.78%1071982.24%0502120641.63%520140137.12%21755838.89%8626141002264446214
Total Saison Régulière120209002530243964-7216194401430126481-35559114601100117483-3665524341165411108745672692948898843148008237032617902342912.39%1382978.99%0865240236.01%862363023.75%527215824.42%1579107444407601210464