Association Québécoise de Hockey Simulé - Goons 

Goons

GP: 20 | W: 7 | L: 10 | OTL: 3 | P: 17
GF: 65 | GA: 83 | PP%: 16.39% | PK%: 69.74%
DG: Stephane Morin | Morale : 90 | Moyenne d'Équipe : 59
Prochain matchs #315 vs Igloos
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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
1Reese Johnson (R)X100.00995177786455694983435670508472090630
2Ryan ReavesX100.00996679758250885330515655669683090620
3Pavol Regenda (R)X100.00544590768053405130485467658371090580
4Darren HelmX100.00644590776250404530405070509683090560
5Mike HardmanX100.00744595757251404530405064508471090560
6Joel Teasdale (R)X100.00504595747254404730445060508472090550
7John HaydenX100.00504885748350404930405855508875090550
8Kyle CriscuoloX100.00504595794766404730405461509080090550
9Aidan McDonough (R)X100.00534592776750404730405457508370090540
10Linus Sandin (R)X100.00504595747350404530405055508774090530
11James Hamblin (R)X100.00504592794850404530405061508370090530
12Marco ScandellaX100.00774587757374405030445688659385090680
13Marcus Bjork (R)X100.00774560827476406130606171688577090670
14Justin BraunX100.00674885756762624730435079509685090650
15Filip Roos (R)X100.00614590806468405230485670668474090630
16Simon Edvinsson (R)X100.00584579757771405130406263658071090620
17Parker Wotherspoon (R)X100.00544590775856404730445064508573090590
Rayé
1Ross JohnstonX78.90855444739150404930485055508976090570
2Jeff Malott (R)X100.00504595767350404530405055508774090540
3Joseph CramarossaX100.00544590776350404730405458509077090540
4Cole McWard (R)X100.00514595775959404830405660508169090580
5Matthew Kessel (R)X100.00504595756763404530405062508271090580
6Brandon GormleyX100.00504595766350404530405055509178090570
7Santeri Hatakka (R)X100.00504595775850404530405055508269090560
MOYENNE D'ÉQUIPE99.0862478776685744483243536354877509058
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
1Joey Daccord (R)100.0070506086707070707070708674090620
2Eetu Makiniemi (R)100.0070506083707070707070708370090610
Rayé
1Christopher Gibson100.0070404091656565656565658875090590
MOYENNE D'ÉQUIPE100.007047538768686868686868867309061
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Martin St-Louis72717472827976CAN4822,000,000$


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'ÉquipePOS GP 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
1Reese JohnsonGoons (QUE)C1810122202515393455252818.18%940822.710338481011412265.94%4581118001.0800003411
2Nicolas Aube-KubelQuebec NordiquesLW171081833410371978175512.82%632319.0023515490003310044.74%38244001.1100011101
3Pavol RegendaGoons (QUE)C208715160223759173413.56%636018.042132410001362049.39%2471612000.8300000110
4Mike HardmanGoons (QUE)LW2041014-52025242873014.29%534817.422133420000160050.00%16512000.8000000002
5Marcus BjorkGoons (QUE)D1711112-852031236529241.54%2343225.420111754011235000.00%01925000.5611000002
6Joel TeasdaleGoons (QUE)RW205611-800161535162314.29%1032316.16112343000001050.00%16910000.6800000011
7Ross JohnstonGoons (QUE)C183710516034203516228.57%528315.75000170000150041.48%176713000.7100000300
8Ryan ReavesGoons (QUE)RW17639-31410201659194310.17%132919.403149480000290045.95%371611000.5500101001
9Justin BraunGoons (QUE)D2017821402226331073.03%2641520.7901114000014000100.00%1321000.3800000000
10John HaydenGoons (QUE)LW20527-240231341132312.20%731515.77000020001250044.83%2998000.4400000021
11Simon EdvinssonGoons (QUE)D20134280132024764.17%831515.7700009000011000.00%0714000.2500000100
12Jeff MalottGoons (QUE)RW51233002253520.00%26913.870000000000000.00%022000.8600000000
13Aidan McDonoughGoons (QUE)RW18303-2001462892110.71%624113.4300002000000040.00%568000.2500000001
14Filip RoosGoons (QUE)D17033220418239140.00%1931718.66000126000032000.00%01021000.1900000000
15Matthew KesselGoons (QUE)D11033000292110.00%1016414.9500000000011000.00%043000.3600000000
16Marco ScandellaGoons (QUE)D17033-107527272810140.00%1444326.10011451000150000.00%0427000.1400001000
17Kyle CriscuoloGoons (QUE)C101231004844125.00%0949.4001102000141045.45%3318000.6400000010
18Linus SandinGoons (QUE)RW320220012232100.00%1227.440000000000000.00%121001.7900000000
19James HamblinGoons (QUE)LW13202-20037133215.38%01189.0900000000040036.36%1151000.3400000000
20Darren HelmGoons (QUE)C12011-7209144370.00%012110.1600002000040053.45%5839000.1600000001
21Parker WotherspoonGoons (QUE)D110111755123130.00%616414.9100002000012000.00%016000.1200001000
22Santeri HatakkaGoons (QUE)D1000000010000.00%01212.770000100001000.00%000000.0000000000
23Cole McWardGoons (QUE)D1000-200001000.00%01111.620000000000000.00%001000.0000000000
24Joseph CramarossaGoons (QUE)LW7000-100521020.00%0497.130000000000000.00%001000.0000000000
Stats d'équipe Total ou en Moyenne3336391154-281934535835562622236710.06%164568717.0810142464479112114056254.44%1126164236000.541111710611
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
1Joey DaccordGoons (QUE)155910.8644.248490060442222100.0000146010
2Eetu MakiniemiGoons (QUE)72120.8403.92352002314472000.0000614010
Stats d'équipe Total ou en Moyenne2271030.8584.1412020083586294100.00002020020


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Aidan McDonoughGoons (QUE)RW231999-11-06Yes190 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm900,000$0$0$No
Brandon GormleyGoons (QUE)D301992-10-12No196 Lbs6 ft2NoNoNo4Sans RestrictionPro & Farm775,000$0$0$No
Christopher GibsonGoons (QUE)G291993-10-12No217 Lbs6 ft2NoNoNo2Sans RestrictionPro & Farm750,000$0$0$No
Cole McWardGoons (QUE)D222001-06-09Yes192 Lbs6 ft1NoNoNo4Avec RestrictionPro & Farm775,000$0$0$No
Darren HelmGoons (QUE)C361987-01-21No192 Lbs6 ft0NoNoNo1Sans RestrictionPro & Farm750,000$0$0$No
Eetu MakiniemiGoons (QUE)G241999-04-19Yes184 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm775,000$0$0$No
Filip RoosGoons (QUE)D241999-01-05Yes190 Lbs6 ft4NoNoNo4Avec RestrictionPro & Farm825,000$0$0$No
James HamblinGoons (QUE)LW241999-04-27Yes176 Lbs5 ft9NoNoNo4Avec RestrictionPro & Farm775,000$0$0$No
Jeff MalottGoons (QUE)RW271996-08-07Yes201 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm1,333,000$0$0$No
Joel TeasdaleGoons (QUE)RW241999-03-11Yes212 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm775,000$0$0$No
Joey DaccordGoons (QUE)G271996-08-19Yes201 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm750,000$0$0$No
John HaydenGoons (QUE)LW281995-02-14No223 Lbs6 ft3NoNoNo4Sans RestrictionPro & Farm750,000$0$0$No
Joseph CramarossaGoons (QUE)LW301992-10-26No190 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm750,000$0$0$No
Justin BraunGoons (QUE)D361987-02-10No205 Lbs6 ft2NoNoNo2Sans RestrictionPro & Farm2,000,000$0$0$No
Kyle CriscuoloGoons (QUE)C311992-05-05No175 Lbs5 ft9NoNoNo1Sans RestrictionPro & Farm775,000$0$0$No
Linus SandinGoons (QUE)RW271996-05-19Yes209 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm750,000$0$0$No
Marco ScandellaGoons (QUE)D331990-02-23No212 Lbs6 ft3NoNoNo2Sans RestrictionPro & Farm3,750,000$0$0$No
Marcus BjorkGoons (QUE)D251997-11-24Yes211 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm900,000$0$0$No
Matthew KesselGoons (QUE)D232000-06-23Yes205 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm775,000$0$0$No
Mike HardmanGoons (QUE)LW241999-02-05No205 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm875,000$0$0$No
Parker WotherspoonGoons (QUE)D261997-08-24Yes190 Lbs6 ft1NoNoNo4Avec RestrictionPro & Farm775,000$0$0$No
Pavol RegendaGoons (QUE)C231999-12-07Yes212 Lbs6 ft4NoNoNo4Avec RestrictionPro & Farm775,000$0$0$No
Reese JohnsonGoons (QUE)C251998-07-10Yes193 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm950,000$0$0$No
Ross Johnston (Sur la Masse Salariale)Goons (QUE)C291994-02-18No230 Lbs6 ft5NoNoNo3Sans RestrictionPro & Farm1,279,550$0$0$Yes
Ryan ReavesGoons (QUE)RW361987-01-20No225 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm5,000,000$0$0$No
Santeri HatakkaGoons (QUE)D222001-01-15Yes191 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm800,000$0$0$No
Simon EdvinssonGoons (QUE)D202003-02-05Yes209 Lbs6 ft6NoNoNo4Avec RestrictionPro & Farm1,200,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2726.96201 Lbs6 ft22.931,158,798$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Mike HardmanReese JohnsonRyan Reaves35122
2John HaydenPavol RegendaJoel Teasdale30122
3James HamblinDarren HelmAidan McDonough25122
4Reese JohnsonKyle CriscuoloLinus Sandin10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marco ScandellaMarcus Bjork35122
2Justin BraunFilip Roos30122
3Simon EdvinssonParker Wotherspoon25122
4Marco ScandellaMarcus Bjork10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Mike HardmanReese JohnsonRyan Reaves55122
2John HaydenPavol RegendaJoel Teasdale45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marco ScandellaMarcus Bjork55122
2Justin BraunFilip Roos45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Reese JohnsonRyan Reaves55122
2Pavol RegendaMike Hardman45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marco ScandellaMarcus Bjork55122
2Justin BraunFilip Roos45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Reese Johnson55122Marco ScandellaMarcus Bjork55122
2Ryan Reaves45122Justin BraunFilip Roos45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Reese JohnsonRyan Reaves55122
2Pavol RegendaMike Hardman45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marco ScandellaMarcus Bjork55122
2Justin BraunFilip Roos45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Mike HardmanReese JohnsonRyan ReavesMarco ScandellaMarcus Bjork
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Mike HardmanReese JohnsonRyan ReavesMarco ScandellaMarcus Bjork
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Darren Helm, Kyle Criscuolo, Aidan McDonoughDarren Helm, Kyle CriscuoloAidan McDonough
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Simon Edvinsson, Parker Wotherspoon, Justin BraunSimon EdvinssonParker Wotherspoon, Justin Braun
Tirs de Pénalité
Reese Johnson, Ryan Reaves, Pavol Regenda, Mike Hardman, Darren Helm
Gardien
#1 : Eetu Makiniemi, #2 : Joey Daccord


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
1Bandits1000010023-1000000000001000010023-110.5002350014212823616123123932618922300.00%20100.00%022241653.37%22640356.08%18132555.69%355175481184366180
2Bayou10001000431100010004310000000000021.000459001421282271612312393265824100.00%4175.00%022241653.37%22640356.08%18132555.69%355175481184366180
3CoolFm4220000014113211000007522110000076140.50014223600142128213316123123931333936814125.00%18761.11%022241653.37%22640356.08%18132555.69%355175481184366180
4Hunters42200000111101100000031231200000810-240.50011152600142128211416123123939026415019210.53%13192.31%022241653.37%22640356.08%18132555.69%355175481184366180
5Husky20100100512-71000010034-11010000028-610.250591400142128276161231239356712529222.22%6350.00%022241653.37%22640356.08%18132555.69%355175481184366180
6Igloos20200000611-51010000057-21010000014-300.0006915001421282541612312393682424245120.00%12466.67%022241653.37%22640356.08%18132555.69%355175481184366180
7Spartans1010000036-31010000036-30000000000000.000358001421282231612312393345410100.00%20100.00%022241653.37%22640356.08%18132555.69%355175481184366180
8TigersCats11000000312110000003120000000000021.00033600142128232161231239325114274125.00%20100.00%022241653.37%22640356.08%18132555.69%355175481184366180
Total20510023006583-18103302200363511027001002948-19170.42565961610014212826341612312393586170197364611016.39%762369.74%122241653.37%22640356.08%18132555.69%355175481184366180
10Vipers10100000510-50000000000010100000510-500.000581300142128246161231239338828127228.57%4250.00%022241653.37%22640356.08%18132555.69%355175481184366180
11Xpress301011001215-3200011008801010000047-330.500121729001421282931612312393902731628112.50%13561.54%122241653.37%22640356.08%18132555.69%355175481184366180
_Since Last GM Reset20510023006583-18103302200363511027001002948-19170.42565961610014212826341612312393586170197364611016.39%762369.74%122241653.37%22640356.08%18132555.69%355175481184366180
_Vs Conference1758013005364-118320120029263926001002438-14150.4415378131001421282538161231239348815215731852815.38%662069.70%122241653.37%22640356.08%18132555.69%355175481184366180
_Vs Division1648013005063-137220120026251926001002438-14130.4065075125001421282506161231239346314115329148714.58%642068.75%122241653.37%22640356.08%18132555.69%355175481184366180

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2017L1659616163458617019736400
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
2051023006583
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
103322003635
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
102701002948
Derniers 10 Matchs
WLOTWOTL SOWSOL
251200
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
611016.39%762369.74%1
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
16123123931421282
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
22241653.37%22640356.08%18132555.69%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
355175481184366180


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 - 2024-04-061Goons1CoolFm3LSommaire du Match
2 - 2024-04-0720CoolFm3Goons1LSommaire du Match
4 - 2024-04-0938TigersCats1Goons3WSommaire du Match
6 - 2024-04-1150Goons2Hunters3LSommaire du Match
7 - 2024-04-1268Goons1Igloos4LSommaire du Match
8 - 2024-04-1381Goons4Hunters3WSommaire du Match
9 - 2024-04-1491Igloos7Goons5LSommaire du Match
11 - 2024-04-16111Xpress4Goons5WXSommaire du Match
12 - 2024-04-17129Goons2Bandits3LXSommaire du Match
14 - 2024-04-19142Hunters1Goons3WSommaire du Match
16 - 2024-04-21162Husky4Goons3LXSommaire du Match
17 - 2024-04-22171Goons2Husky8LSommaire du Match
18 - 2024-04-23190Goons6CoolFm3WSommaire du Match
19 - 2024-04-24202Goons4Xpress7LSommaire du Match
20 - 2024-04-25215Spartans6Goons3LSommaire du Match
22 - 2024-04-27233CoolFm2Goons6WSommaire du Match
23 - 2024-04-28247Goons5Vipers10LSommaire du Match
25 - 2024-04-30267Xpress4Goons3LXSommaire du Match
27 - 2024-05-02285Bayou3Goons4WXSommaire du Match
28 - 2024-05-03297Goons2Hunters4LSommaire du Match
30 - 2024-05-05315Goons-Igloos-
31 - 2024-05-06326Rockets-Goons-
32 - 2024-05-07345Goons-Vandals-
34 - 2024-05-09357Grizzlies-Goons-
35 - 2024-05-10371Goons-Grizzlies-
37 - 2024-05-12389Goons-Rockets-
38 - 2024-05-13401Snowbirds-Goons-
40 - 2024-05-15419Marmots-Goons-
42 - 2024-05-17438Goons-CoolFm-
43 - 2024-05-18451TigersCats-Goons-
44 - 2024-05-19472Thugs-Goons-
45 - 2024-05-20484Goons-TigersCats-
47 - 2024-05-22501Goons-Supreme-
48 - 2024-05-23514Goons-Bayou-
49 - 2024-05-24524Supreme-Goons-
51 - 2024-05-26541Goons-Outlaws-
52 - 2024-05-27556Vipers-Goons-
53 - 2024-05-28569Goons-Xpress-
55 - 2024-05-30586Predateurs-Goons-
56 - 2024-05-31599Goons-Predateurs-
58 - 2024-06-02615Warriors-Goons-
59 - 2024-06-03631Goons-Raptors-
61 - 2024-06-05646Barracudas-Goons-
62 - 2024-06-06661Goons-Scorpions-
63 - 2024-06-07674Goons-Thugs-
64 - 2024-06-08681Wolves-Goons-
67 - 2024-06-11708Chiwawa-Goons-
68 - 2024-06-12729Marlies-Goons-
69 - 2024-06-13742Goons-Marlies-
71 - 2024-06-15763Saguenéens-Goons-
72 - 2024-06-16774Goons-Smirnoff Ice-
73 - 2024-06-17788Goons-Bandits-
74 - 2024-06-18800Goons-Marmots-
75 - 2024-06-19810Vandals-Goons-
77 - 2024-06-21833Smirnoff Ice-Goons-
79 - 2024-06-23855Hunters-Goons-
80 - 2024-06-24871Goons-Wolves-
82 - 2024-06-26886Raptors-Goons-
83 - 2024-06-27899Goons-Farmers-
84 - 2024-06-28910Goons-Saguenéens-
86 - 2024-06-30926Scorpions-Goons-
88 - 2024-07-02949Outlaws-Goons-
89 - 2024-07-03962Goons-Warriors-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
90 - 2024-07-04975Goons-Barracudas-
91 - 2024-07-05987Farmers-Goons-
92 - 2024-07-06998Goons-Chiwawa-
95 - 2024-07-091021Twins-Goons-
96 - 2024-07-101041Husky-Goons-
99 - 2024-07-131068Igloos-Goons-
100 - 2024-07-141076Goons-Twins-
102 - 2024-07-161090Goons-Snowbirds-
105 - 2024-07-191110CoolFm-Goons-
106 - 2024-07-201129Goons-Spartans-
107 - 2024-07-211137Bandits-Goons-
110 - 2024-07-241156Bandits-Goons-
111 - 2024-07-251168Goons-Husky-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets5025
Assistance14,7096,354
Assistance PCT73.55%63.54%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
28 2106 - 70.21% 107,316$1,073,160$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,332,139$ 3,128,755$ 3,053,755$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 817,736$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
3,004,848$ 84 45,387$ 3,812,508$




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
4582333004564309311-241141703223135153-18411913013411741581695309490799106212211513245463095085557249880855914852527429.37%2095872.25%9867157954.91%861161353.38%759134256.56%144375021277141411695
4682293307634326333-741141306422171165641152001212155168-1388326526852316612712316261164697897340244981872515662777828.16%2706974.44%51000172158.11%910163755.59%728130555.79%150579920607131412704
4720510023006583-18103302200363511027001002948-191765961610014212826341612312393586170197364611016.39%762369.74%122241653.37%22640356.08%18132555.69%355175481184366180
Total Saison Régulière18467730131498700727-27923133011845342353-1192364002653358374-162007001112181241142270266315699143721592067100553317961481341559016227.46%55515072.97%152089371656.22%1997365354.67%1668297256.12%330417254669161131891580
Séries
45624000002733-6312000001618-2312000001115-4427467320217711893494601212775312017952.94%24866.67%05311844.92%7014448.61%5810853.70%115581275911857
Total Séries624000002733-6312000001618-2312000001115-4427467320217711893494601212775312017952.94%24866.67%05311844.92%7014448.61%5810853.70%115581275911857