hellpepitosKingspatriots

 

 


Leftovers

GP: 37 | W: 11 | L: 23 | OTL: 3 | P: 25
GF: 144 | GA: 148 | PP%: 28.23% | PK%: 73.17%
DG: Francois Bedard | Morale : 50 | Moyenne d'Équipe : 67
Prochain matchs #282 vs Requins
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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
1Scott Laughton0XX100.00793653416163777077798172725561044710
2Jamie McGinn0XX100.00793963357857557337798353687460050700
3Jujhar Khaira0X100.00814254438358676762798166714555050690
4Filip Chytil0XXX100.00422174366765787053788156723637050690
5Oscar Lindberg0XX100.00792356386856777164778154716446050690
6Matt Martin0XX100.00924949509149716352778052697067050680
7Tobias Rieder0XXX100.00682475455262766438787971736751050680
8Joakim Nordstrom0X100.00782773476358726447767961696048050670
9Boo Nieves0X100.00692163467645786570788253663740050660
10Phillip Di Giuseppe0X100.00832859425847766757777948764545050650
11Filip Zadina (R)0X100.00352083525372825833667467683738050640
12Vinni Lettieri0X100.00792654455449846352757851663942050640
13Brett Pesce0X100.00531870447274708463867875604437050730
14Alex Biega0X100.00852754446560808528857649645662050720
15Mike Reilly0X100.00551466446263808229827550654534050700
16Kevin Gravel0X100.00622975498154887929807361654748050690
17Mark Borowiecki0XX100.00964835498355448031807465595565050690
18Robert Bortuzzo0X100.00824246488754618026817556586259050680
Rayé
1Austin Czarnik0X100.00392372383751787057808152705151050670
2Scott Wilson0X100.00813272445555606548777963634447050650
3Nail Yakupov0XX100.00652457395849716531727954755345050640
4Markus Hannikainen0X100.00801275486641716536737947705239050630
5Kalle Kossila0XXX100.00401773604945815936667559674441050600
6Nic Petan0XX100.00362967544235796139687747655059050600
7Steven Fogarty0X100.00402380677835825733657161684151050590
8Jaycob Megna0X100.00622463508654847830787461664451050680
9Chris Wideman0X100.00773147445346648328827746705357050680
10Dean Kukan0X100.00562367475850778030827639665744050680
11Yannick Weber0X100.00732462476641608025797535757052050670
12Libor Hajek (R)0X100.00392574596660736831726961684447050650
13Ryan Sproul0X100.00372678567659786830727054664947050650
14Chris Bigras0X100.00402581595850786830726954664550050630
MOYENNE D'ÉQUIPE100.0064276547665474704277775668514905067
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
1Michael Hutchinson100.0083928280828985868879757372050800
2Christopher Gibson100.0082888278828587859053616467050790
Rayé
MOYENNE D'ÉQUIPE100.008390827982878686896668697005080
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
David Quinn94867957717650USA534450,000$


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
1Brett PesceLeftovers (Tru)D3711304112120238111738459.40%8497326.326814331040225210000.00%02840000.8400000021
2Jujhar KhairaLeftovers (Tru)LW37261440-24209252124366420.97%1666718.03871522850002763245.16%313212021.2000000211
3Pontus AbergTruitesLW/RW3613253824260243689295214.61%2277921.67210122392213142340150.00%64168010.9714000111
4Oscar LindbergLeftovers (Tru)C/RW36825333280673865225912.31%1156615.74312151286000000059.12%499165001.1600000102
5Jamie McGinnLeftovers (Tru)LW/RW361317308160583098295313.27%961917.2054922920000792144.74%76204000.9724000032
6Scott LaughtonLeftovers (Tru)C/LW2012172911280424869225417.39%2445622.831459491124991065.09%424128011.2700000121
7Tobias RiederLeftovers (Tru)C/LW/RW371217291080194693233212.90%2045112.19551014412242120047.87%2821520011.2900000110
8Phillip Di GiuseppeLeftovers (Tru)RW3713112410240441859153022.03%344512.0300000303311045.00%20105011.0800000101
9Filip ChytilLeftovers (Tru)C/LW/RW3622022-11209318322422.41%1056015.572791586000130061.90%21125000.7904000000
10Mike ReillyLeftovers (Tru)D37417218160112237162710.81%3479721.552359760225157000.00%01016000.5301000100
11Alex BiegaLeftovers (Tru)D3621719258091247117302.82%2591725.48156111030116189000.00%02011000.4100000100
12Boo NievesLeftovers (Tru)C3710919980172947182521.28%32877.78000040221270066.46%158155011.3200000001
13Robert BortuzzoLeftovers (Tru)D3621012248049273510155.71%2152614.6200000000266000.00%0915000.4601000001
14Matt MartinLeftovers (Tru)LW/RW362810-748053236132403.28%652114.49000000222670049.09%55234000.3800000000
15Joakim NordstromLeftovers (Tru)C36448-48018354210279.52%1136710.200000010141280056.33%316105000.4400000000
16Filip ZadinaLeftovers (Tru)RW37538420314187727.78%92426.5600000000001044.44%956010.6600000000
17Kevin GravelLeftovers (Tru)D363472809413317109.09%3045612.670000001112100.00%046000.3100000000
18Mark BorowieckiLeftovers (Tru)LW/D36055-1399584544417210.00%5073520.4400011760221121000.00%0628000.1400100000
19Vinni LettieriLeftovers (Tru)C17033-61201713206130.00%520712.2000000000000054.14%18141000.2900000000
Stats d'équipe Total ou en Moyenne656142256398624935730662120538664611.78%3931057916.133565100181900916255314799457.12%2136267204080.7531410091011
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
1Michael HutchinsonLeftovers (Tru)36102220.8843.962063201361170605000.72711360212
2Christopher GibsonLeftovers (Tru)61110.8773.3517900108149000.0000137000
Stats d'équipe Total ou en Moyenne42112330.8833.912243201461251654000.727113737212


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 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
Alex BiegaLeftovers (Tru)D311988-04-04No199 Lbs178 CMNoNoNo1Pro & Farm650,000$378,834$0$0$NoLien / Lien NHL
Austin CzarnikLeftovers (Tru)C261992-12-12No170 Lbs175 CMNoNoNo2Pro & Farm1,250,000$728,527$0$0$No1,250,000$Lien
Boo NievesLeftovers (Tru)C251994-01-23No210 Lbs191 CMNoNoNo1Pro & Farm925,000$539,110$0$0$NoLien
Brett PesceLeftovers (Tru)D241994-11-15No206 Lbs191 CMNoNoNo1Pro & Farm809,167$471,600$0$0$NoLien / Lien NHL
Chris BigrasLeftovers (Tru)D241995-02-22No191 Lbs185 CMNoNoNo2Pro & Farm874,125$509,459$0$0$No874,125$Lien / Lien NHL
Chris WidemanLeftovers (Tru)D291990-01-07No183 Lbs178 CMNoNoNo1Pro & Farm800,000$466,257$0$0$NoLien / Lien NHL
Christopher GibsonLeftovers (Tru)G261992-12-27No207 Lbs188 CMNoNoNo2Pro & Farm675,000$393,404$0$0$No675,000$Lien / Lien NHL
Dean KukanLeftovers (Tru)D261993-07-08No186 Lbs188 CMNoNoNo1Pro & Farm700,000$407,975$0$0$NoLien
Filip ChytilLeftovers (Tru)C/LW/RW201999-09-05No208 Lbs188 CMNoNoNo1Pro & Farm1,275,000$743,098$0$0$NoLien
Filip ZadinaLeftovers (Tru)RW191999-11-27Yes195 Lbs183 CMNoNoNo2Pro & Farm1,744,167$1,016,539$0$0$No1,744,167$Lien
Jamie McGinnLeftovers (Tru)LW/RW311988-08-05No205 Lbs185 CMNoNoNo1Pro & Farm650,000$378,834$0$0$NoLien / Lien NHL
Jaycob MegnaLeftovers (Tru)D261992-12-10No221 Lbs198 CMNoNoNo2Pro & Farm650,000$378,834$0$0$No650,000$Lien
Joakim NordstromLeftovers (Tru)C271992-02-25No194 Lbs185 CMNoNoNo1Pro & Farm1,275,000$743,098$0$0$NoLien / Lien NHL
Jujhar KhairaLeftovers (Tru)LW251994-08-13No212 Lbs193 CMNoNoNo1Pro & Farm675,000$393,404$0$0$NoLien / Lien NHL
Kalle KossilaLeftovers (Tru)C/LW/RW261993-04-14No185 Lbs178 CMNoNoNo2Pro & Farm650,000$378,834$0$0$No650,000$Lien
Kevin GravelLeftovers (Tru)D271992-03-06No211 Lbs193 CMNoNoNo1Pro & Farm650,000$378,834$0$0$NoLien / Lien NHL
Libor HajekLeftovers (Tru)D211998-02-04Yes204 Lbs188 CMNoNoNo2Pro & Farm894,166$521,139$0$0$No894,166$Lien
Mark BorowieckiLeftovers (Tru)LW/D301989-07-12No207 Lbs185 CMNoNoNo2Pro & Farm1,440,000$839,263$0$0$No1,440,000$Lien / Lien NHL
Markus HannikainenLeftovers (Tru)LW261993-03-26No200 Lbs185 CMNoNoNo1Pro & Farm675,000$393,404$0$0$NoLien / Lien NHL
Matt MartinLeftovers (Tru)LW/RW301989-05-08No220 Lbs191 CMNoNoNo1Pro & Farm650,000$378,834$0$0$NoLien / Lien NHL
Michael HutchinsonLeftovers (Tru)G291990-03-02No200 Lbs191 CMNoNoNo1Pro & Farm650,000$378,834$0$0$NoLien / Lien NHL
Mike ReillyLeftovers (Tru)D261993-07-13No195 Lbs185 CMNoNoNo1Pro & Farm725,000$422,546$0$0$NoLien / Lien NHL
Nail YakupovLeftovers (Tru)LW/RW251993-10-06No195 Lbs180 CMNoNoNo2Pro & Farm962,500$560,966$0$0$No962,500$Lien / Lien NHL
Nic PetanLeftovers (Tru)C/LW241995-03-22No179 Lbs175 CMNoNoNo1Pro & Farm925,000$539,110$0$0$NoLien / Lien NHL
Oscar LindbergLeftovers (Tru)C/RW271991-10-29No202 Lbs185 CMNoNoNo2Pro & Farm1,700,000$990,797$0$0$No1,700,000$Lien / Lien NHL
Phillip Di GiuseppeLeftovers (Tru)RW251993-10-09No192 Lbs183 CMNoNoNo1Pro & Farm725,000$422,546$0$0$NoLien / Lien NHL
Robert BortuzzoLeftovers (Tru)D301989-03-18No216 Lbs193 CMNoNoNo2Pro & Farm1,656,000$965,153$0$0$No1,656,000$Lien / Lien NHL
Ryan SproulLeftovers (Tru)D261993-01-13No205 Lbs193 CMNoNoNo2Pro & Farm687,500$400,690$0$0$No687,500$Lien / Lien NHL
Scott LaughtonLeftovers (Tru)C/LW251994-05-30No190 Lbs185 CMNoNoNo1Pro & Farm962,500$560,966$0$0$NoLien / Lien NHL
Scott WilsonLeftovers (Tru)RW271992-04-24No186 Lbs180 CMNoNoNo2Pro & Farm1,050,000$611,963$0$0$No1,050,000$Lien / Lien NHL
Steven FogartyLeftovers (Tru)C261993-04-19No210 Lbs191 CMNoNoNo1Pro & Farm750,000$437,116$0$0$NoLien
Tobias RiederLeftovers (Tru)C/LW/RW261993-01-10No186 Lbs180 CMNoNoNo1Pro & Farm2,225,000$1,296,779$0$0$NoLien / Lien NHL
Vinni LettieriLeftovers (Tru)C241995-02-06No191 Lbs180 CMNoNoNo1Pro & Farm925,000$539,110$0$0$NoLien
Yannick WeberLeftovers (Tru)D311988-09-23No200 Lbs180 CMNoNoNo1Pro & Farm1,224,000$713,374$0$0$NoLien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3426.18199 Lbs185 CM1.38972,915$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Oscar LindbergJamie McGinn40122
2Jujhar KhairaVinni LettieriFilip Chytil30122
3Matt MartinBoo NievesPhillip Di Giuseppe20122
4Tobias RiederJoakim NordstromFilip Zadina10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Brett PesceAlex Biega40122
2Mike ReillyMark Borowiecki30122
3Kevin GravelRobert Bortuzzo20122
4Brett PesceAlex Biega10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tobias RiederJamie McGinn60122
2Jujhar KhairaOscar LindbergFilip Chytil40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Brett PesceAlex Biega60122
2Mike ReillyMark Borowiecki40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Joakim Nordstrom60122
2Jamie McGinnJujhar Khaira40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Brett PesceAlex Biega60122
2Mike ReillyMark Borowiecki40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Joakim Nordstrom60122Brett PesceAlex Biega60122
240122Mike ReillyMark Borowiecki40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Tobias Rieder60122
2Jamie McGinnJujhar Khaira40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Brett PesceAlex Biega60122
2Mike ReillyMark Borowiecki40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Filip ChytilJamie McGinnBrett PesceAlex Biega
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Oscar LindbergJamie McGinnBrett PesceAlex Biega
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Boo Nieves, Tobias Rieder, Matt MartinBoo Nieves, Tobias RiederMatt Martin
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Kevin Gravel, Robert Bortuzzo, Mike ReillyKevin GravelRobert Bortuzzo, Mike Reilly
Tirs de Pénalité
Filip Chytil, , Jamie McGinn, Mark Borowiecki, Jujhar Khaira
Gardien
#1 : Michael Hutchinson, #2 : Christopher Gibson


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
1Barracuda512001102021-1311000101082201001001013-350.5002036560051385241764213564202015256649420420.00%321165.63%241874755.96%50685659.11%30755455.42%835535858302550269
2Benchwarmers1010000013-21010000013-20000000000000.00012300513852430421356420203519818200.00%40100.00%041874755.96%50685659.11%30755455.42%835535858302550269
3Caribou30300000511-62020000047-31010000014-300.0005101500513852497421356420209836545915426.67%26869.23%041874755.96%50685659.11%30755455.42%835535858302550269
4Casse-Tete30300000919-101010000047-320200000512-700.0009162500513852481421356420201062848667228.57%24866.67%041874755.96%50685659.11%30755455.42%835535858302550269
5Chevalier2010000128-6000000000002010000128-610.2502350051385246942135642020781630396116.67%15380.00%041874755.96%50685659.11%30755455.42%835535858302550269
6Diabotins1010000023-1000000000001010000023-100.00024600513852437421356420202210122411100.00%6266.67%041874755.96%50685659.11%30755455.42%835535858302550269
7Hooligans11000000541110000005410000000000021.000591400513852432421356420203514142122100.00%7357.14%041874755.96%50685659.11%30755455.42%835535858302550269
8Hybrides11000000413110000004130000000000021.00048120051385243842135642020301810206233.33%50100.00%041874755.96%50685659.11%30755455.42%835535858302550269
9Jardiniers303000001019-91010000056-120200000513-800.000101929005138524964213564202010927386215533.33%19857.89%141874755.96%50685659.11%30755455.42%835535858302550269
10Pirates714010102324-121000010945504010001420-660.429234063005138524246421356420202618410311917635.29%501080.00%141874755.96%50685659.11%30755455.42%835535858302550269
11Requins110000003823611000000382360000000000021.0003865103005138524384213564202020669000.00%30100.00%441874755.96%50685659.11%30755455.42%835535858302550269
12Royaux422000001214-21100000043131200000811-340.5001224360051385241234213564202015039449813430.77%23386.96%141874755.96%50685659.11%30755455.42%835535858302550269
Total3782301122144148-418780002194603419115011015088-38250.33814426040400513852412054213564202012513954957331243528.23%2466673.17%941874755.96%50685659.11%30755455.42%835535858302550269
14Werewolves513000011319-6412000011015-51010000034-130.30013243700513852414242135642020155426410420420.00%321068.75%041874755.96%50685659.11%30755455.42%835535858302550269
_Since Last GM Reset3782301122144148-418780002194603419115011015088-38250.33814426040400513852412054213564202012513954957331243528.23%2466673.17%941874755.96%50685659.11%30755455.42%835535858302550269
_Vs Conference14390101079552463200010581939807010002136-15100.3577913921800513852447942135642020482160181253371437.84%892374.16%641874755.96%50685659.11%30755455.42%835535858302550269
_Vs Division910000003235-34100000014113500000001824-620.111326092005138524299421356420203029510819233824.24%551474.55%341874755.96%50685659.11%30755455.42%835535858302550269

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
3725L21442604041205125139549573300
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
378231122144148
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
187800219460
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
1911511015088
Derniers 10 Matchs
WLOTWOTL SOWSOL
440101
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1243528.23%2466673.17%9
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
421356420205138524
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
41874755.96%50685659.11%30755455.42%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
835535858302550269


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 - 2019-10-065Requins2Leftovers38WSommaire du Match
2 - 2019-10-0710Leftovers1Chevalier6LSommaire du Match
5 - 2019-10-1019Leftovers1Caribou4LSommaire du Match
6 - 2019-10-1121Leftovers1Barracuda3LSommaire du Match
8 - 2019-10-1330Werewolves4Leftovers5WSommaire du Match
10 - 2019-10-1539Werewolves3Leftovers0LSommaire du Match
13 - 2019-10-1849Barracuda4Leftovers3LSommaire du Match
16 - 2019-10-2160Leftovers3Pirates4LSommaire du Match
17 - 2019-10-2267Caribou4Leftovers2LSommaire du Match
20 - 2019-10-2576Pirates1Leftovers5WSommaire du Match
21 - 2019-10-2684Leftovers3Casse-Tete5LSommaire du Match
23 - 2019-10-2889Leftovers4Pirates3WXSommaire du Match
25 - 2019-10-3097Werewolves4Leftovers2LSommaire du Match
26 - 2019-10-31102Leftovers2Royaux5LSommaire du Match
28 - 2019-11-02110Leftovers3Royaux5LSommaire du Match
30 - 2019-11-04117Royaux3Leftovers4WSommaire du Match
32 - 2019-11-06126Leftovers2Pirates3LSommaire du Match
33 - 2019-11-07131Benchwarmers3Leftovers1LSommaire du Match
36 - 2019-11-10143Hybrides1Leftovers4WSommaire du Match
37 - 2019-11-11149Leftovers3Jardiniers7LSommaire du Match
40 - 2019-11-14157Caribou3Leftovers2LSommaire du Match
42 - 2019-11-16167Leftovers1Chevalier2LXXSommaire du Match
43 - 2019-11-17170Jardiniers6Leftovers5LSommaire du Match
45 - 2019-11-19182Hooligans4Leftovers5WSommaire du Match
46 - 2019-11-20185Leftovers3Werewolves4LSommaire du Match
49 - 2019-11-23197Leftovers2Casse-Tete7LSommaire du Match
50 - 2019-11-24201Casse-Tete7Leftovers4LSommaire du Match
52 - 2019-11-26212Leftovers9Barracuda10LXSommaire du Match
54 - 2019-11-28215Leftovers3Pirates6LSommaire du Match
55 - 2019-11-29222Pirates3Leftovers4WXXSommaire du Match
57 - 2019-12-01230Leftovers2Pirates4LSommaire du Match
59 - 2019-12-03237Barracuda2Leftovers4WSommaire du Match
61 - 2019-12-05244Leftovers3Royaux1WSommaire du Match
62 - 2019-12-06251Barracuda2Leftovers3WXXSommaire du Match
64 - 2019-12-08260Werewolves4Leftovers3LXXSommaire du Match
65 - 2019-12-09264Leftovers2Jardiniers6LSommaire du Match
67 - 2019-12-11273Leftovers2Diabotins3LSommaire du Match
70 - 2019-12-14282Requins-Leftovers-
71 - 2019-12-15291Hybrides-Leftovers-
73 - 2019-12-17297Leftovers-Requins-
75 - 2019-12-19303Leftovers-Barracuda-
77 - 2019-12-21310Leftovers-Caribou-
78 - 2019-12-22315Vagabond-Leftovers-
80 - 2019-12-24325Hooligans-Leftovers-
84 - 2019-12-28336Vagabond-Leftovers-
85 - 2019-12-29342Leftovers-Vagabond-
88 - 2020-01-01352Royaux-Leftovers-
89 - 2020-01-02361Jardiniers-Leftovers-
90 - 2020-01-03367Pirates-Leftovers-
92 - 2020-01-05371Leftovers-Benchwarmers-
94 - 2020-01-07378Leftovers-Caribou-
96 - 2020-01-09384Leftovers-Hooligans-
97 - 2020-01-10391Leftovers-Chevalier-
99 - 2020-01-12398Casse-Tete-Leftovers-
102 - 2020-01-15409Leftovers-Diabotins-
104 - 2020-01-17415Requins-Leftovers-
106 - 2020-01-19423Leftovers-Casse-Tete-
107 - 2020-01-20428Chevalier-Leftovers-
108 - 2020-01-21436Leftovers-Caribou-
111 - 2020-01-24444Leftovers-Requins-
112 - 2020-01-25448Werewolves-Leftovers-
115 - 2020-01-28459Benchwarmers-Leftovers-
116 - 2020-01-29463Leftovers-Vagabond-
118 - 2020-01-31472Leftovers-Benchwarmers-
119 - 2020-02-01477Diabotins-Leftovers-
122 - 2020-02-04489Leftovers-Vagabond-
123 - 2020-02-05493Requins-Leftovers-
127 - 2020-02-09505Diabotins-Leftovers-
130 - 2020-02-12514Leftovers-Royaux-
131 - 2020-02-13521Werewolves-Leftovers-
134 - 2020-02-16527Leftovers-Werewolves-
135 - 2020-02-17535Diabotins-Leftovers-
139 - 2020-02-21546Pirates-Leftovers-
140 - 2020-02-22550Leftovers-Hooligans-
141 - 2020-02-23556Leftovers-Barracuda-
143 - 2020-02-25566Jardiniers-Leftovers-
145 - 2020-02-27573Leftovers-Hybrides-
146 - 2020-02-28580Chevalier-Leftovers-
148 - 2020-03-01586Leftovers-Hybrides-
150 - 2020-03-03594Barracuda-Leftovers-
152 - 2020-03-05600Leftovers-Jardiniers-
154 - 2020-03-07606Leftovers-Benchwarmers-
156 - 2020-03-09613Caribou-Leftovers-
160 - 2020-03-13624Chevalier-Leftovers-



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
24 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,453,341$ 3,307,914$ 2,509,729$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
20,294$ 1,453,341$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 95 20,294$ 1,927,930$




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
201684280010013142066-17524204101000149998-84942239000011651068-9034314560874001071041021249283185879982120772202215863286921.04%41227932.28%81071168463.60%52784662.29%1796302759.33%2002129416996261346666
20168446220732444219225042297021122548616842171505212188106829244277412160413813416111260683388985451221481993918532756222.55%3235682.66%141033165662.38%987159162.04%783121764.34%2097138617146651277661
201784293905146245378-13342161702034119191-7242132203112126187-61582454186631481758013220069775471666259688666715682855619.65%3246978.70%11654154842.25%735165644.38%499120441.45%1809112019826971313650
2017842439073653042455942161405313169104654282502052135141-648304530834231121017818256282685183191231275771418812814415.66%3486780.75%141029172959.51%997159862.39%701112562.31%2049133717766711298660
201882432404245465289176412710000312401241164116140421422516560864658311296021901581091032211166105197556263393487718143388525.15%4168380.05%241110191957.84%1022176357.97%788130660.34%2023132416996551250644
201882244803421473374994115200222026117388419280120121220111484738241297222001451238302911659109402529221056130115222716122.51%54914573.59%251112178462.33%1211197461.35%880141562.19%1895123318526531204603
20193782301122144148-418780002194603419115011015088-382514426040400513852412054213564202012513954957331243528.23%2466673.17%941874755.96%50685659.11%30755455.42%835535858302550269
Total Saison Régulière53717627502814202423873692-13052681101170126121112861736-45026966158016881311011956-8553612387419765845158797557056517315593956695535317160485619701510957190241221.66%261876570.78%10564271106758.07%59851028458.20%5754984858.43%12713823211581427282414155
Séries
2016161150000055352076100000321220954000002323022551021570221211125561691891899431144165310601931.67%55983.64%119935755.74%16330653.27%11121052.86%410278331124233120
2016954000001918153200000101004220000098110193251009361293113701064247941141932328.70%43783.72%212118665.05%13519369.95%7510273.53%2451711776712565
2017514000001318-52110000087130300000511-62132336007420143434455118852548623521.74%27388.89%1549954.55%4912937.98%226036.67%10768128407034
2017514000001119-82110000076130300000413-92111829004250191654776317473569311327.27%29968.97%17710573.33%8212864.06%446765.67%12484111376734
20181156000003539-45230000019181633000001621-510355792102067241615112612910399148138268581322.41%641871.88%314329348.81%13826152.87%6714845.27%25815526010118189
2018514000001827-9211000001210230300000617-112183452009630154674339521871948426311.54%371267.57%04510742.06%8314955.70%447757.14%10361132457435
Total Séries51242700000151156-52314900000886325281018000006393-3048151266417127042345175360851959432165758262110342014522.39%2555877.25%8639114755.71%650116655.75%36366454.67%12498191143416753380