Trashers

GP: 82 | W: 49 | L: 24 | OTL: 9 | P: 107
GF: 259 | GA: 205 | PP%: 39.38% | PK%: 57.63%
DG: Guillaume Diamond | Morale : 50 | Moyenne d'Équipe : 64
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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
1Miles Wood (A)X100.00854270866675946048556461605773050740
2Teddy BluegerX100.00743989866079835670526082626075050730
3Blake Lizotte (R)X100.00633687874676936072615880565169046730
4Kirby Dach (R)X100.00583686867177925950586064633960040720
5Vladimir Sobotka (C)X100.00863588845968545468515683548186050720
6Michael AmadioX100.00523693836773855461515764555464050680
7Max JonesX100.00723688807272735148455772554865050680
8Dmytro Timashov (R)X100.00843691835764665148465564535469050660
9Drake Batherson (R)X100.00703992847166415247505457534863050650
10Martin FrkX100.00593694836764475348475959566369050650
11Mitchell Stephens (R)X100.00613692846066604964445456535161050630
12Nico Sturm (R)X100.00513695837160254853465064505764050620
13Madison BoweyX100.00683686856472735948615766555770050710
14Dennis CholowskiX100.00523293856369605747546056574861050670
15Martin MarincinX100.00553493837562435149495270516671050670
16Oliver KylingtonX100.00583292865564665448515661545163050660
17Andrew Peeke (R)X100.00633293856459415247495463534862050640
Rayé
1Alexander True (R)X100.00603695857360294951485063505162050630
2Isac Lundestrom (R)X100.00483695856062314953475063504557050610
3Ryan MacInnis (R)X100.00513695847159274648425060505461050600
4Mikhail GrigorenkoX100.00463195827253334742425157516063050600
5Klim Kostin (R)X100.00533695827358254746405455534556050590
6Jason Robertson (R)X100.00473695827359254846455056504556050590
7Joachim Blichfeld (R)X100.00503694866259254547405060504857050590
8Jonathan Davidsson (R)X100.00503595855857254747435061505160050590
9Calvin Thurkauf (R)X100.00533695836958254548405056505159050590
10Blake Speers (R)X100.00453095845850254540405055505157050560
11Daniel O'Regan (R)X100.00453095845250254540405055506062050560
12Riley Stillman (R)X100.00734191846168575148525076504866050690
13Niko Mikkola (R)X100.00503195876455254948485063505462050620
14Joe Hicketts (R)X100.00583095854756255148515060505464050610
15Calle Rosen (R)X100.00473194865857295148515057506064050610
16Gabriel Carlsson (R)X100.00503295866854254847455057505159050600
17Jimmy SchuldtX100.00453295827750254648455055505761050600
18Sebastian Aho D (R)X100.00453295867350254548455055505460050590
19Jakub Zboril (R)X100.00453395827750254547455055505158050590
20Ben Gleason (R)X100.00453295857550254547455055504857050590
21Gustav OlofssonX100.00473295836452254748455055586063050590
22Nikolai Knyzhov (R)X100.00523294856253254847455056504858050590
MOYENNE D'ÉQUIPE100.0057349284656144505048536253536305063
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
1Jack Campbell100.0078447374797981787867576569049750
Rayé
1Alex Nedeljkovic (R)100.0072256471767174727465574952050670
2Harri Sateri100.0063257176636364636365557762050610
3Christopher Gibson (R)100.0060257477586060606065556555050580
MOYENNE D'ÉQUIPE100.006830717569687068696656646005065
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Benoit Groulx68657179707273CAN503900,000$


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
1Blake LizotteTrashers (NAS)C73316899143001101502608915011.92%44158121.661842603820811271843160.75%18429953111.252150001165
2Kirby DachTrashers (NAS)RW793250821731581652548915212.60%33145818.4619304933224000036641.30%929249101.1201010495
3Miles WoodTrashers (NAS)LW63383977141040138922627312314.50%39135521.522320433918111281389449.61%3818643031.14513000679
4Madison BoweyTrashers (NAS)D801434481365515411718668707.53%129213726.72142034212440113197100.00%079124000.4500100253
5Vladimir SobotkaTrashers (NAS)LW8223194216320154811845710512.50%31132116.11101020191800111142255.17%586652000.6413000444
6Michael AmadioTrashers (NAS)RW82182240231005566188611119.57%26123515.076101614158000016052.24%675533000.6500000332
7Teddy BluegerTrashers (NAS)C75171027838011090207521248.21%25105914.133363381238843460.81%6206852000.5115000124
8Riley StillmanTrashers (NAS)D74619252454201301119034446.67%85177323.976814101870001176200.00%035102000.2800130010
9Max JonesTrashers (NAS)LW801211231433512583105396211.43%24108813.6155108470000421047.27%553755100.4202000103
10Martin MarincinTrashers (NAS)D754172113120401019333294.30%77151420.1944861350003128000.00%02777000.2800000000
11Martin FrkTrashers (NAS)RW5581018660423010227807.84%1669012.56336471015411150.00%524122100.5200000102
12Dmytro TimashovTrashers (NAS)LW82810183801175112942726.20%2682710.092353140002232241.38%293724000.4400000020
13Drake BathersonTrashers (NAS)RW8237107160622311044682.73%197989.74011040000140043.75%324925000.2500000010
14Dennis CholowskiTrashers (NAS)D71010101110033525532300.00%41107715.17022047000235000.00%03255000.1901000000
15Mitchell StephensTrashers (NAS)C70516312048447618386.58%186349.0700000000071155.04%2583019000.1900000010
16Oliver KylingtonTrashers (NAS)D820661334029575222150.00%47113013.79011010000138000.00%01950000.1100000000
17Andrew PeekeTrashers (NAS)D27011320191214750.00%1337914.0400000000023000.00%0329000.0500000000
18Alexander TrueTrashers (NAS)RW20101-100118185135.56%71587.9100001000000050.00%673000.1300000001
19Trevor MoorePredateursRW6101-10017318895.56%19916.60101214000020033.33%333000.2000000100
20Nico SturmTrashers (NAS)C14011-1008911250.00%61188.4300000000000059.26%2711000.1700000000
21Isac LundestromTrashers (NAS)LW9000100155060.00%1738.120000000000000.00%102000.0000000000
Stats d'équipe Total ou en Moyenne12812213355562004973514841250241980213119.14%7082051216.0111416227620017074610411159372157.62%3523866873440.54940240344138
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
1Jack CampbellTrashers (NAS)65371790.9202.343848431501866929510.7674363181065
2Alex NedeljkovicTrashers (NAS)148500.9072.597870034367183201.00061357002
3Harri SateriTrashers (NAS)64200.9211.97365001215189100.667361100
Stats d'équipe Total ou en Moyenne85492490.9182.3550014319623841201810.7885282761167


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 NedeljkovicTrashers (NAS)G241996-01-01Yes189 Lbs6 ft0NoNoNo3Pro & Farm1,300,000$10,655$0$0$No1,300,000$1,300,000$
Alexander TrueTrashers (NAS)RW231997-01-01Yes200 Lbs6 ft5NoNoNo2Pro & Farm700,000$5,737$0$0$No700,000$
Andrew PeekeTrashers (NAS)D221998-01-01Yes194 Lbs6 ft3NoNoNo2Pro & Farm750,000$6,147$0$0$No750,000$Lien
Ben GleasonTrashers (NAS)D221998-01-01Yes185 Lbs6 ft1NoNoNo4Pro & Farm800,000$6,557$0$0$No800,000$800,000$800,000$Lien
Blake LizotteTrashers (NAS)C231997-01-01Yes172 Lbs5 ft7NoNoNo3Pro & Farm1,000,000$8,196$0$0$No1,000,000$1,000,000$
Blake SpeersTrashers (NAS)C231997-01-01Yes185 Lbs5 ft11NoNoNo4Pro & Farm850,000$6,967$0$0$No850,000$850,000$850,000$
Calle RosenTrashers (NAS)D261994-01-01Yes186 Lbs6 ft1NoNoNo2Pro & Farm725,000$5,942$0$0$No725,000$Lien / Lien NHL
Calvin ThurkaufTrashers (NAS)RW231997-01-01Yes204 Lbs6 ft2NoNoNo3Pro & Farm625,000$5,122$0$0$No625,000$625,000$
Christopher GibsonTrashers (NAS)G281992-01-01Yes207 Lbs6 ft2NoNoNo2Pro & Farm725,000$5,942$0$0$No725,000$Lien NHL
Daniel O'ReganTrashers (NAS)LW261994-01-01Yes180 Lbs5 ft9NoNoNo2Pro & Farm550,000$4,508$0$0$No550,000$
Dennis CholowskiTrashers (NAS)D221998-01-01No197 Lbs6 ft2NoNoNo1Pro & Farm825,000$6,762$0$0$NoLien
Dmytro TimashovTrashers (NAS)LW241996-01-01Yes192 Lbs5 ft10NoNoNo2Pro & Farm700,000$5,737$0$0$No700,000$
Drake BathersonTrashers (NAS)RW221998-01-01Yes206 Lbs6 ft3NoNoNo3Pro & Farm900,000$7,377$0$0$No900,000$900,000$
Gabriel CarlssonTrashers (NAS)D231997-01-01Yes192 Lbs6 ft5NoNoNo1Pro & Farm900,000$7,377$0$0$NoLien / Lien NHL
Gustav OlofssonTrashers (NAS)D261994-01-01No200 Lbs6 ft2NoNoNo2Pro & Farm600,000$4,918$0$0$No600,000$Lien / Lien NHL
Harri SateriTrashers (NAS)G311989-01-01No205 Lbs6 ft1NoNoNo1Pro & Farm500,000$4,098$0$0$NoLien NHL
Isac LundestromTrashers (NAS)LW211999-01-01Yes187 Lbs6 ft0NoNoNo1Pro & Farm800,000$6,557$0$0$No
Jack CampbellTrashers (NAS)G281992-01-01No197 Lbs6 ft2NoNoNo2Pro & Farm975,000$7,991$0$0$No975,000$Lien NHL
Jakub ZborilTrashers (NAS)D231997-01-01Yes200 Lbs6 ft0NoNoNo3Pro & Farm800,000$6,557$0$0$No800,000$800,000$Lien
Jason RobertsonTrashers (NAS)LW211999-01-01Yes210 Lbs6 ft3NoNoNo2Pro & Farm750,000$6,147$0$0$No750,000$
Jimmy SchuldtTrashers (NAS)D251995-01-01No205 Lbs6 ft1NoNoNo2Pro & Farm750,000$6,147$0$0$No750,000$Lien
Joachim BlichfeldTrashers (NAS)RW221998-01-01Yes180 Lbs6 ft2NoNoNo2Pro & Farm550,000$4,508$0$0$No550,000$
Joe HickettsTrashers (NAS)D241996-01-01Yes180 Lbs5 ft8NoNoNo2Pro & Farm750,000$6,147$0$0$No750,000$Lien / Lien NHL
Jonathan DavidssonTrashers (NAS)RW231997-01-01Yes185 Lbs5 ft11NoNoNo2Pro & Farm550,000$4,508$0$0$No550,000$
Kirby DachTrashers (NAS)RW192001-01-01Yes197 Lbs6 ft4NoNoNo3Pro & Farm850,000$6,967$0$0$No850,000$850,000$
Klim KostinTrashers (NAS)LW211999-01-01Yes212 Lbs6 ft3NoNoNo2Pro & Farm750,000$6,147$0$0$No750,000$
Madison BoweyTrashers (NAS)D251995-01-01No202 Lbs6 ft2NoNoNo1Pro & Farm750,000$6,147$0$0$NoLien / Lien NHL
Martin FrkTrashers (NAS)RW271993-01-01No205 Lbs6 ft1NoNoNo1Pro & Farm900,000$7,377$0$0$NoLien NHL
Martin MarincinTrashers (NAS)D281992-01-01No217 Lbs6 ft5NoNoNo3Pro & Farm1,000,000$8,196$0$0$No1,000,000$1,000,000$Lien / Lien NHL
Max JonesTrashers (NAS)LW221998-01-01No220 Lbs6 ft1NoNoNo3Pro & Farm900,000$7,377$0$0$No900,000$900,000$
Michael AmadioTrashers (NAS)RW241996-01-01No204 Lbs6 ft1NoNoNo2Pro & Farm700,000$5,737$0$0$No700,000$Lien NHL
Mikhail GrigorenkoTrashers (NAS)C261994-01-01No209 Lbs6 ft3NoNoNo1Pro & Farm1,000,000$8,196$0$0$No
Miles WoodTrashers (NAS)LW251995-01-01No195 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$8,196$0$0$NoLien NHL
Mitchell StephensTrashers (NAS)C231997-01-01Yes193 Lbs5 ft11NoNoNo2Pro & Farm750,000$6,147$0$0$No750,000$
Nico SturmTrashers (NAS)C251995-01-01Yes206 Lbs6 ft3NoNoNo2Pro & Farm800,000$6,557$0$0$No800,000$
Niko MikkolaTrashers (NAS)D241996-01-01Yes185 Lbs6 ft4NoNoNo3Pro & Farm750,000$6,147$0$0$No750,000$750,000$
Nikolai KnyzhovTrashers (NAS)D221998-01-01Yes194 Lbs6 ft2NoNoNo4Pro & Farm1,000,000$8,196$0$0$No1,000,000$1,000,000$1,000,000$Lien
Oliver KylingtonTrashers (NAS)D231997-01-01No183 Lbs6 ft0NoNoNo2Pro & Farm975,000$7,991$0$0$No975,000$Lien
Riley StillmanTrashers (NAS)D221998-01-01Yes196 Lbs6 ft1NoNoNo3Pro & Farm850,000$6,967$0$0$No850,000$850,000$Lien
Ryan MacInnisTrashers (NAS)C241996-01-01Yes200 Lbs6 ft4NoNoNo3Pro & Farm750,000$6,147$0$0$No750,000$750,000$
Sebastian Aho DTrashers (NAS)D241996-01-01Yes170 Lbs5 ft10NoNoNo2Pro & Farm600,000$4,918$0$0$No600,000$Lien
Teddy BluegerTrashers (NAS)C261994-01-01No185 Lbs6 ft0NoNoNo3Pro & Farm1,000,000$8,196$0$0$No1,000,000$1,000,000$
Vladimir SobotkaTrashers (NAS)LW331987-01-01No191 Lbs5 ft11NoNoNo3Pro & Farm900,000$7,377$0$0$No900,000$900,000$Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
4324.14195 Lbs6 ft12.26804,651$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Miles WoodBlake LizotteKirby Dach40122
2Vladimir SobotkaTeddy BluegerMichael Amadio30122
3Max JonesMitchell StephensMartin Frk20122
4Dmytro TimashovNico SturmDrake Batherson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison Bowey40122
2Martin MarincinDennis Cholowski30122
3Oliver KylingtonAndrew Peeke20122
4Madison Bowey10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Miles WoodBlake LizotteKirby Dach60122
2Vladimir SobotkaTeddy BluegerMichael Amadio40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison Bowey60122
2Martin MarincinDennis Cholowski40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Miles WoodBlake Lizotte60122
2Teddy BluegerMax Jones40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison Bowey60122
2Martin MarincinDennis Cholowski40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Miles Wood60122Madison Bowey60122
2Blake Lizotte40122Martin MarincinDennis Cholowski40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Miles WoodBlake Lizotte60122
2Teddy BluegerMax Jones40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison Bowey60122
2Martin MarincinDennis Cholowski40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Miles WoodBlake LizotteKirby DachMadison Bowey
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Miles WoodBlake LizotteKirby DachMadison Bowey
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Max Jones, Dmytro Timashov, Martin FrkMax Jones, Dmytro TimashovMartin Frk
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Oliver Kylington, Andrew Peeke, Martin MarincinOliver KylingtonAndrew Peeke, Martin Marincin
Tirs de Pénalité
Miles Wood, Blake Lizotte, Max Jones, Teddy Blueger, Vladimir Sobotka
Gardien
#1 : , #2 : Jack Campbell


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
13L2200000013310110000006151100000072541.000132033003011110715656999801058945924193511872.73%7185.71%11048179458.42%998180755.23%712119159.78%1855105716777281472771
2Armada521001101615130100110711-42200000094570.70016254100301111071515569998010589415962409219631.58%19857.89%01048179458.42%998180755.23%712119159.78%1855105716777281472771
3Chops2010000169-31000000134-11010000035-210.2506111700301111071569699980105894773024248337.50%12650.00%11048179458.42%998180755.23%712119159.78%1855105716777281472771
4Draveurs201010005501010000023-11000100032120.500591400301111071566699980105894482512455240.00%6350.00%11048179458.42%998180755.23%712119159.78%1855105716777281472771
5Griffins21000001541110000003121000000123-130.7505813003011110715636999801058947021105710440.00%5260.00%01048179458.42%998180755.23%712119159.78%1855105716777281472771
6Heat 431000001587211000006512200000093660.7501526410130111107151616999801058949854228615746.67%11645.45%01048179458.42%998180755.23%712119159.78%1855105716777281472771
7Jarrets Noirs43001000187112200000012482100100063381.000183048003011110715132699980105894127372682191368.42%13653.85%01048179458.42%998180755.23%712119159.78%1855105716777281472771
8Monarchs44000000198112200000095422000000103781.00019274600301111071512869998010589490234376231460.87%14471.43%01048179458.42%998180755.23%712119159.78%1855105716777281472771
9Monster210000014311000000112-11100000031230.75047110030111107156669998010589465208398112.50%40100.00%01048179458.42%998180755.23%712119159.78%1855105716777281472771
10Mosquitos650000103110213200001012663300000019415121.0003145760030111107151916999801058941303953121382155.26%19668.42%01048179458.42%998180755.23%712119159.78%1855105716777281472771
11National22000000413110000001011100000031241.000471101301111071555699980105894542912428112.50%60100.00%01048179458.42%998180755.23%712119159.78%1855105716777281472771
12Pantheres21000010523110000002021000001032141.00056110130111107157369998010589458191441300.00%7271.43%01048179458.42%998180755.23%712119159.78%1855105716777281472771
13Phantoms 2020000036-31010000024-21010000012-100.00035800301111071561699980105894611610397228.57%5340.00%01048179458.42%998180755.23%712119159.78%1855105716777281472771
14Rambo41300000812-4211000006602020000026-420.2508132100301111071513669998010589412238388111436.36%191047.37%01048179458.42%998180755.23%712119159.78%1855105716777281472771
15Rapido201000104401010000012-11000001032120.500461000301111071572699980105894501914605120.00%7357.14%01048179458.42%998180755.23%712119159.78%1855105716777281472771
16Red Bull602000401918130100020111013010002088080.667192140103011110715177699980105894148444216618738.89%211052.38%01048179458.42%998180755.23%712119159.78%1855105716777281472771
17Rivermen623000011120-93110000146-231200000714-750.417111627003011110715206699980105894210655214025624.00%261350.00%01048179458.42%998180755.23%712119159.78%1855105716777281472771
18Rocket7320000218180412000011114-33200000174380.5711829470030111107152296999801058941535478182291034.48%301163.33%11048179458.42%998180755.23%712119159.78%1855105716777281472771
19Rockets722010021819-13100100197241200001912-380.571183250003011110715268699980105894235983813919315.79%19857.89%01048179458.42%998180755.23%712119159.78%1855105716777281472771
20Sea Dogs2020000036-31010000024-21010000012-100.0003690030111107158669998010589480201844200.00%9544.44%01048179458.42%998180755.23%712119159.78%1855105716777281472771
21Spartans220000001266110000004221100000084441.000121729003011110715706999801058946530122911545.45%6516.67%01048179458.42%998180755.23%712119159.78%1855105716777281472771
Total823824031882592055441171301145123109144121110204313696401070.65225940366213301111071527786999801058942385839645174432012639.38%29512557.63%51048179458.42%998180755.23%712119159.78%1855105716777281472771
23Walleye523000001317-42020000059-43210000088040.40013213400301111071517069998010589416254489318422.22%241154.17%11048179458.42%998180755.23%712119159.78%1855105716777281472771
24Wolf Pack22000000945110000004311100000051441.0009162500301111071579699980105894641812318450.00%6266.67%01048179458.42%998180755.23%712119159.78%1855105716777281472771
_Since Last GM Reset823824031882592055441171301145123109144121110204313696401070.65225940366213301111071527786999801058942385839645174432012639.38%29512557.63%51048179458.42%998180755.23%712119159.78%1855105716777281472771
_Vs Conference3221802010125685716114000106038221610402000653035480.75012519532001301111071510696999801058949002992556251437451.75%1104559.09%21048179458.42%998180755.23%712119159.78%1855105716777281472771
_Vs Division128400000382018642000001610664200000221012160.66738609802301111071540569998010589434612581248421638.10%381171.05%11048179458.42%998180755.23%712119159.78%1855105716777281472771

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
82107SOL125940366227782385839645174413
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8238243188259205
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4117131145123109
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
412111204313696
Derniers 10 Matchs
WLOTWOTL SOWSOL
440002
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
32012639.38%29512557.63%5
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
6999801058943011110715
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
1048179458.42%998180755.23%712119159.78%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1855105716777281472771


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 - 2020-09-259Rocket3Trashers1LSommaire du Match
2 - 2020-09-2618Trashers2Rockets3LSommaire du Match
4 - 2020-09-2830Trashers3Red Bull2WXXSommaire du Match
5 - 2020-09-2939Rivermen1Trashers2WSommaire du Match
6 - 2020-09-3048Trashers4Rocket1WSommaire du Match
7 - 2020-10-0159Trashers3Walleye2WSommaire du Match
8 - 2020-10-0270Red Bull3Trashers4WXXSommaire du Match
9 - 2020-10-0381Trashers3Rockets2WSommaire du Match
11 - 2020-10-0594Mosquitos2Trashers3WXXSommaire du Match
12 - 2020-10-06105Trashers2Rivermen4LSommaire du Match
13 - 2020-10-07118Armada3Trashers2LXSommaire du Match
15 - 2020-10-09133Red Bull3Trashers2LSommaire du Match
17 - 2020-10-11145Trashers7Mosquitos2WSommaire du Match
19 - 2020-10-13152Trashers2Walleye4LSommaire du Match
21 - 2020-10-15165Walleye5Trashers2LSommaire du Match
23 - 2020-10-17180Trashers2Rocket1WSommaire du Match
25 - 2020-10-19190Rocket2Trashers4WSommaire du Match
27 - 2020-10-21205National0Trashers1WSommaire du Match
29 - 2020-10-23219Phantoms 4Trashers2LSommaire du Match
31 - 2020-10-25232Trashers3Chops5LSommaire du Match
33 - 2020-10-27236Trashers2Red Bull4LSommaire du Match
35 - 2020-10-29255Chops4Trashers3LXXSommaire du Match
37 - 2020-10-31268Monarchs3Trashers5WSommaire du Match
39 - 2020-11-02274Trashers2Rivermen9LSommaire du Match
40 - 2020-11-03290Trashers3National1WSommaire du Match
42 - 2020-11-05301Griffins1Trashers3WSommaire du Match
43 - 2020-11-06312Trashers9Mosquitos1WSommaire du Match
44 - 2020-11-07319Trashers6Heat 2WSommaire du Match
46 - 2020-11-09332Rivermen2Trashers1LXXSommaire du Match
47 - 2020-11-10345Trashers1Rambo3LSommaire du Match
49 - 2020-11-123583L1Trashers6WSommaire du Match
51 - 2020-11-14373Heat 0Trashers3WSommaire du Match
53 - 2020-11-16388Trashers3Red Bull2WXXSommaire du Match
54 - 2020-11-17397Rambo2Trashers3WSommaire du Match
55 - 2020-11-18411Trashers3Walleye2WSommaire du Match
56 - 2020-11-19418Trashers1Rambo3LSommaire du Match
58 - 2020-11-21431Trashers1Sea Dogs2LSommaire du Match
59 - 2020-11-22438Jarrets Noirs3Trashers6WSommaire du Match
60 - 2020-11-23451Trashers3Jarrets Noirs2WXSommaire du Match
61 - 2020-11-24456Walleye4Trashers3LSommaire du Match
63 - 2020-11-26478Mosquitos3Trashers5WSommaire du Match
64 - 2020-11-27488Trashers2Rockets3LXXSommaire du Match
66 - 2020-11-29503Sea Dogs4Trashers2LSommaire du Match
68 - 2020-12-01516Trashers3Rapido2WXXSommaire du Match
69 - 2020-12-02525Heat 5Trashers3LSommaire du Match
71 - 2020-12-04544Armada3Trashers4WXXSommaire du Match
72 - 2020-12-05556Rocket4Trashers3LXXSommaire du Match
73 - 2020-12-06566Trashers8Spartans4WSommaire du Match
75 - 2020-12-08579Trashers5Wolf Pack1WSommaire du Match
76 - 2020-12-09590Trashers7Monarchs1WSommaire du Match
77 - 2020-12-10599Wolf Pack3Trashers4WSommaire du Match
78 - 2020-12-11609Trashers3Rivermen1WSommaire du Match
79 - 2020-12-12623Monarchs2Trashers4WSommaire du Match
81 - 2020-12-14639Trashers2Griffins3LXXSommaire du Match
82 - 2020-12-15646Rapido2Trashers1LSommaire du Match
83 - 2020-12-16656Trashers2Rockets4LSommaire du Match
85 - 2020-12-18669Rockets3Trashers2LXXSommaire du Match
86 - 2020-12-19686Pantheres0Trashers2WSommaire du Match
88 - 2020-12-21699Trashers3Monster1WSommaire du Match
89 - 2020-12-22711Trashers3Draveurs2WXSommaire du Match
90 - 2020-12-23718Rivermen3Trashers1LSommaire du Match
91 - 2020-12-24734Spartans2Trashers4WSommaire du Match
93 - 2020-12-26750Rockets2Trashers3WXSommaire du Match
94 - 2020-12-27760Trashers4Armada1WSommaire du Match
95 - 2020-12-28772Jarrets Noirs1Trashers6WSommaire du Match
96 - 2020-12-29777Trashers5Armada3WSommaire du Match
97 - 2020-12-30787Trashers3Pantheres2WXXSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
99 - 2021-01-01808Armada5Trashers1LSommaire du Match
100 - 2021-01-02816Trashers3Heat 1WSommaire du Match
101 - 2021-01-03826Trashers73L2WSommaire du Match
102 - 2021-01-04834Trashers3Jarrets Noirs1WSommaire du Match
103 - 2021-01-05840Red Bull4Trashers5WXXSommaire du Match
105 - 2021-01-07863Rambo4Trashers3LSommaire du Match
107 - 2021-01-09878Rocket5Trashers3LSommaire du Match
108 - 2021-01-10888Trashers1Phantoms 2LSommaire du Match
109 - 2021-01-11896Trashers3Monarchs2WSommaire du Match
111 - 2021-01-13908Draveurs3Trashers2LSommaire du Match
113 - 2021-01-15926Rockets2Trashers4WSommaire du Match
114 - 2021-01-16936Trashers1Rocket2LXXSommaire du Match
115 - 2021-01-17944Trashers3Mosquitos1WSommaire du Match
117 - 2021-01-19959Mosquitos1Trashers4WSommaire du Match
120 - 2021-01-22973Monster2Trashers1LXXSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance79,15039,790
Assistance PCT96.52%97.05%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
-40 2901 - 96.70% 94,443$3,872,164$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
3,579,985$ 3,460,000$ 3,430,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
28,115$ 3,545,731$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
-3,777,721$ 1 28,361$ 28,361$




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