Association Québécoise de Hockey Simulé - Goons 

Goons

GP: 18 | W: 6 | L: 9 | OTL: 3 | P: 15
GF: 59 | GA: 76 | PP%: 15.79% | PK%: 67.65%
DG: Stephane Morin | Morale : 90 | Moyenne d'Équipe : 59
Prochain matchs #285 vs Bayou
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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)X98.00995177786455694983435670508472090630
2Ryan ReavesX99.00996679758250885330515655669683090620
3Nicolas Aube-Kubel (R)X99.00974869786957645430525665668674090620
4Pavol Regenda (R)X99.00544590768053405130485467658371090580
5Darren HelmX100.00644590776250404530405070509683090560
6Mike HardmanX100.00744595757251404530405064508471090560
7Joel Teasdale (R)X100.00504595747254404730445060508472090550
8John HaydenX100.00504885748350404930405855508875090550
9Jeff Malott (R)X100.00504595767350404530405055508774090540
10James Hamblin (R)X100.00504592794850404530405061508370090530
11Marco ScandellaX99.00774587757374405030445688659385090680
12Marcus Bjork (R)X99.00774560827476406130606171688577090670
13Justin BraunX100.00674885756762624730435079509685090650
14Filip Roos (R)X100.00614590806468405230485670668474090630
15Simon Edvinsson (R)X100.00584579757771405130406263658071090620
16Parker Wotherspoon (R)X100.00544590775856404730445064508573090590
Rayé
1Ross JohnstonX58.90855444739150404930485055508976090570
2Kyle CriscuoloX100.00504595794766404730405461509080090550
3Aidan McDonough (R)X100.00534592776750404730405457508370090540
4Joseph CramarossaX100.00544590776350404730405458509077090540
5Linus Sandin (R)X100.00504595747350404530405055508774090530
6Cole McWard (R)X100.00514595775959404830405660508169090580
7Matthew Kessel (R)X100.00504595756763404530405062508271090580
8Brandon GormleyX100.00504595766350404530405055509178090570
9Santeri Hatakka (R)X100.00504595775850404530405055508269090560
MOYENNE D'ÉQUIPE98.0463478676685745483243536354877509058
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)99.0070506083707070707070708370090610
Rayé
1Christopher Gibson100.0070404091656565656565658875090590
MOYENNE D'ÉQUIPE99.677047538768686868686868867309061
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)C169122101915343052222617.31%935922.490338431011372265.30%4151115001.1700003311
2Nicolas Aube-KubelGoons (QUE)LW15107174295321971175114.08%628619.1223515450003260044.74%38234001.1900010101
3Pavol RegendaGoons (QUE)C188715360192950172916.00%631817.692132390001312048.88%2231310000.9400000110
4Mike HardmanGoons (QUE)LW184913-42022232362817.39%531517.522132400000140046.67%15411000.8200000002
5Marcus BjorkGoons (QUE)D1511112-548029186128201.64%2238125.460111651011229000.00%01619000.6311000002
6Ross JohnstonGoons (QUE)C183710516034203516228.57%528315.75000170000150041.48%176713000.7100000300
7Joel TeasdaleGoons (QUE)RW18369-60014123116209.68%929116.21011241000001046.67%1599000.6200000010
8Ryan ReavesGoons (QUE)RW15628-21210161354144111.11%128619.133149440000250045.71%35139000.5600101001
9Justin BraunGoons (QUE)D181560120212532973.12%2537020.5701113600013400100.00%1319000.3200000000
10John HaydenGoons (QUE)LW18426-240221335112011.43%728515.84000020001210046.15%2678000.4200000011
11Simon EdvinssonGoons (QUE)D18134280131923764.35%829116.1800009000011000.00%0614000.2700000100
12Jeff MalottGoons (QUE)RW51233002253520.00%26913.870000000000000.00%022000.8600000000
13Filip RoosGoons (QUE)D15033020417218140.00%1727318.25000123000026000.00%0914000.2200000000
14Matthew KesselGoons (QUE)D11033000292110.00%1016414.9500000000011000.00%043000.3600000000
15Marco ScandellaGoons (QUE)D15033-7752124269130.00%1339126.07011448000141000.00%0323000.1500001000
16Linus SandinGoons (QUE)RW320220012232100.00%1227.440000000000000.00%121001.7900000000
17Aidan McDonoughGoons (QUE)RW16202-200145248188.33%621713.5700002000000040.00%556000.1800000001
18James HamblinGoons (QUE)LW11202-30026133215.38%01069.7100000000040036.36%1141000.3700000000
19Parker WotherspoonGoons (QUE)D90112004123130.00%613715.2800002000010000.00%015000.1500000000
20Kyle CriscuoloGoons (QUE)C8011-100473410.00%0789.8600001000130042.31%2616000.2500000000
21Darren HelmGoons (QUE)C10000-7204113230.00%0909.0900001000020056.76%3728000.0000000000
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 Moyenne2995784141-21167353193195712053349.98%158509717.059132261447112113505253.81%1024145202000.5511115949
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)134810.8644.377280053390196000.0000126010
2Eetu MakiniemiGoons (QUE)72120.8403.92352002314472000.0000612010
Stats d'équipe Total ou en Moyenne206930.8584.2210800076534268000.00001818020


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
Nicolas Aube-KubelGoons (QUE)LW271996-05-10Yes207 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm1,000,000$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
2826.96202 Lbs6 ft22.961,153,127$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Nicolas Aube-KubelReese JohnsonRyan Reaves35122
2Mike HardmanPavol RegendaJoel Teasdale30122
3John HaydenJeff Malott25122
4James HamblinDarren HelmReese Johnson10122
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
1Nicolas Aube-KubelReese JohnsonRyan Reaves55122
2Mike HardmanPavol 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 JohnsonNicolas Aube-Kubel55122
2Ryan ReavesPavol Regenda45122
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
2Nicolas Aube-Kubel45122Justin BraunFilip Roos45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Reese JohnsonNicolas Aube-Kubel55122
2Ryan ReavesPavol Regenda45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marco ScandellaMarcus Bjork55122
2Justin BraunFilip Roos45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nicolas Aube-KubelReese JohnsonRyan ReavesMarco ScandellaMarcus Bjork
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nicolas Aube-KubelReese JohnsonRyan ReavesMarco ScandellaMarcus Bjork
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Darren Helm, John Hayden, Darren HelmJohn Hayden
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Simon Edvinsson, Parker Wotherspoon, Justin BraunSimon EdvinssonParker Wotherspoon, Justin Braun
Tirs de Pénalité
Reese Johnson, Nicolas Aube-Kubel, Ryan Reaves, Pavol Regenda,
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
1Bandits1000010023-1000000000001000010023-110.5002350010202813614221022522618922300.00%20100.00%020538453.39%20036554.79%16229455.10%322160429165329163
2CoolFm4220000014113211000007522110000076140.50014223600102028113314221022521333936814125.00%18761.11%020538453.39%20036554.79%16229455.10%322160429165329163
3Hunters32100000972110000003122110000066040.66791322001020281861422102252642523351616.25%9188.89%020538453.39%20036554.79%16229455.10%322160429165329163
4Husky20100100512-71000010034-11010000028-610.250591400102028176142210225256712529222.22%6350.00%020538453.39%20036554.79%16229455.10%322160429165329163
5Igloos20200000611-51010000057-21010000014-300.0006915001020281541422102252682424245120.00%12466.67%020538453.39%20036554.79%16229455.10%322160429165329163
6Spartans1010000036-31010000036-30000000000000.000358001020281231422102252345410100.00%20100.00%020538453.39%20036554.79%16229455.10%322160429165329163
7TigersCats11000000312110000003120000000000021.00033600102028132142210225225114274125.00%20100.00%020538453.39%20036554.79%16229455.10%322160429165329163
Total1859013005976-179330120032320926001002744-17150.4175989148001020281579142210225253416417132557915.79%682267.65%120538453.39%20036554.79%16229455.10%322160429165329163
9Vipers10100000510-50000000000010100000510-500.000581300102028146142210225238828127228.57%4250.00%020538453.39%20036554.79%16229455.10%322160429165329163
10Xpress301011001215-3200011008801010000047-330.500121729001020281931422102252902731628112.50%13561.54%120538453.39%20036554.79%16229455.10%322160429165329163
_Since Last GM Reset1859013005976-179330120032320926001002744-17150.4175989148001020281579142210225253416417132557915.79%682267.65%120538453.39%20036554.79%16229455.10%322160429165329163
_Vs Conference1657013005160-98320120029263825001002234-12150.4695176127001020281510142210225246215113930349714.29%622067.74%120538453.39%20036554.79%16229455.10%322160429165329163
_Vs Division1547013004859-117220120026251825001002234-12130.4334873121001020281478142210225243714013527645613.33%602066.67%120538453.39%20036554.79%16229455.10%322160429165329163

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
1815OTL1598914857953416417132500
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
185913005976
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
93312003232
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
92601002744
Derniers 10 Matchs
WLOTWOTL SOWSOL
340300
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
57915.79%682267.65%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
14221022521020281
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
20538453.39%20036554.79%16229455.10%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
322160429165329163


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 - 2024-05-02285Bayou-Goons-
28 - 2024-05-03297Goons-Hunters-
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
Assistance13,1065,663
Assistance PCT72.81%62.92%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
29 2085 - 69.51% 106,250$956,250$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,151,332$ 3,100,800$ 3,025,800$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 708,857$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
3,081,250$ 88 45,140$ 3,972,320$




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
471859013005976-179330120032320926001002744-17155989148001020281579142210225253416417132557915.79%682267.65%120538453.39%20036554.79%16229455.10%322160429165329163
Total Saison Régulière18267720121498694720-26913133010845338350-1291363902653356370-14198694110517994113826926630564414182138205399548117901455337658616127.47%54714972.76%152072368456.24%1971361554.52%1649294156.07%327117094617159231531563
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