beholdershellpepitosKingspatriots

 

 


Evil Saints

GP: 35 | W: 18 | L: 12 | OTL: 5 | P: 41
GF: 204 | GA: 117 | PP%: 18.88% | PK%: 77.92%
DG: Michael Pion | Morale : 50 | Moyenne d'Équipe : 78
Prochain matchs #362 vs Giants
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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
1Alex Tuch0X100.00694066278171897261848468764134045840
2Nick Schmaltz0X100.00333473283379817571877972724035050820
3J.T. Compher0X100.00453767354973787074808464634237050800
4Dale Weise0X100.00845061427952776935798062506160047790
5Miles Wood0X100.00614940336257797435818663623432050790
6Eric Fehr0X100.00723562488051436673798168757972047780
7Tage Thompson (R)0X100.00603172416955836634808262643532050760
8Kasperi Kapanen0X100.00782780484251876736778455684537050740
9Victor Ejdsell (R)0X100.00533090597862785748697661643935050730
10Daniel Sprong0XX100.00573082543365605930707963643933050710
11Eric Robinson0X100.00263188626152805631677355653230050670
12Brady Skjei0X100.00723467447471848631867364614739040850
13Jake Dotchin0X100.00825145468061808429837277624544050830
14Jakob Chychrun0X100.00683768426768718527837367683432039820
15Eric Gryba0X100.00885144499056778129807065575455047810
16Blake Hillman0X100.00533093593565807031726660653330050730
17Daniel Brickley (R)0X100.00513087586640816931726652653230050680
Rayé
MOYENNE D'ÉQUIPE100.0062377046636177714278776365433904877
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
1Malcolm Subban100.0084757279878790879058844266050840
2Alexandar Georgiev (R)100.0082916876848391868765702041050800
Rayé
MOYENNE D'ÉQUIPE100.008383707886859187896277315405082
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Paul Maurice70707070707070CAN515450,000$


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
1J.T. CompherEvil Saints (PIO)LW353249815437526611645010219.51%3477222.085611301020000112062.07%2323239032.1016000613
2Kasperi KapanenEvil Saints (PIO)RW354230723310065251545010527.27%1462217.77761335107000004363.64%33499042.3112000434
3Nick SchmaltzEvil Saints (PIO)RW35234871234023871766511113.07%6388825.394711391220004760055.15%3792532021.6016000213
4Miles WoodEvil Saints (PIO)LW353827654034086541844612820.65%3160117.1900000101292158.33%243422032.1614000152
5Jake DotchinEvil Saints (PIO)D3585058294001309215260795.26%8791326.100121248144000257100.00%01949021.2700000032
6Tage ThompsonEvil Saints (PIO)C35371956810059661686011422.02%3674521.3010515411270004363345.60%614397031.5000000200
7Victor EjdsellEvil Saints (PIO)C351039493340204883234712.05%2263018.0104414107000073055.70%605307011.5500000030
8Blake HillmanEvil Saints (PIO)D3512223290027586129271.64%6076021.730228100000364000.00%01026000.6000000000
9Daniel BrickleyEvil Saints (PIO)D3511011234023294714112.13%3147113.470000000015000.00%0917000.4700000000
10Eric RobinsonEvil Saints (PIO)LW352911-1003294018355.00%73239.23011426000040048.57%35182100.6800000001
11Brady SkjeiEvil Saints (PIO)D91910-22026203024183.33%1327330.41033839000226000.00%036000.7300000002
12Robert HaggPioneersD11268201203113164812.50%1620919.0400000000049000.00%009000.7600000100
13Jakob ChychrunEvil Saints (PIO)D1026824160121722669.09%1423923.91011833011243000.00%017000.6700000000
Stats d'équipe Total ou en Moyenne3801993245233131735531599129744979115.34%428745119.612647732359121122039215753.17%19222692321181.40418000161617
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
1Alexandar GeorgievEvil Saints (PIO)35181250.9113.052122201081217689400.76025350430
Stats d'équipe Total ou en Moyenne35181250.9113.052122201081217689400.76025350430


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
Alex TuchEvil Saints (PIO)RW221996-05-10No222 Lbs193 CMNoNoNo1Contrat d'EntréePro & Farm1,350,000$0$0$NoLien / Lien NHL
Alexandar GeorgievEvil Saints (PIO)G221996-02-10Yes180 Lbs185 CMNoNoNo2Contrat d'EntréePro & Farm925,000$0$0$NoLien
Blake HillmanEvil Saints (PIO)D221996-01-26No180 Lbs185 CMNoNoNo2Contrat d'EntréePro & Farm925,000$0$0$NoLien
Brady SkjeiEvil Saints (PIO)D241994-03-26No211 Lbs191 CMNoNoNo2Avec RestrictionPro & Farm925,000$0$0$NoLien / Lien NHL
Dale WeiseEvil Saints (PIO)RW301988-08-05No206 Lbs188 CMNoNoNo2Sans RestrictionPro & Farm650,000$0$0$NoLien / Lien NHL
Daniel BrickleyEvil Saints (PIO)D231995-03-30Yes203 Lbs191 CMNoNoNo2Avec RestrictionPro & Farm1,350,000$0$0$NoLien
Daniel SprongEvil Saints (PIO)LW/RW211997-03-17No180 Lbs183 CMNoNoNo2Contrat d'EntréePro & Farm925,000$0$0$NoLien / Lien NHL
Eric FehrEvil Saints (PIO)RW331985-09-07No208 Lbs193 CMNoNoNo2Sans RestrictionPro & Farm650,000$0$0$NoLien / Lien NHL
Eric GrybaEvil Saints (PIO)D301988-04-14No222 Lbs193 CMNoNoNo2Sans RestrictionPro & Farm650,000$0$0$NoLien / Lien NHL
Eric RobinsonEvil Saints (PIO)LW231995-06-14No200 Lbs188 CMNoNoNo2Avec RestrictionPro & Farm925,000$0$0$NoLien
J.T. CompherEvil Saints (PIO)LW231995-04-08No193 Lbs183 CMNoNoNo1Avec RestrictionPro & Farm1,000,000$0$0$NoLien / Lien NHL
Jake DotchinEvil Saints (PIO)D241994-03-24No210 Lbs191 CMNoNoNo1Avec RestrictionPro & Farm616,667$0$0$NoLien / Lien NHL
Jakob ChychrunEvil Saints (PIO)D201998-03-31No210 Lbs188 CMNoNoNo1Contrat d'EntréePro & Farm1,350,000$0$0$NoLien / Lien NHL
Kasperi KapanenEvil Saints (PIO)RW221996-07-23No187 Lbs185 CMNoNoNo2Contrat d'EntréePro & Farm925,000$0$0$NoLien
Malcolm SubbanEvil Saints (PIO)G241993-12-21No200 Lbs188 CMNoNoNo2Avec RestrictionPro & Farm650,000$0$0$NoLien
Miles WoodEvil Saints (PIO)LW231995-09-13No195 Lbs188 CMNoNoNo2Avec RestrictionPro & Farm925,000$0$0$NoLien / Lien NHL
Nick SchmaltzEvil Saints (PIO)RW221996-02-23No177 Lbs183 CMNoNoNo1Contrat d'EntréePro & Farm1,541,667$0$0$NoLien / Lien NHL
Tage ThompsonEvil Saints (PIO)C201997-10-30Yes205 Lbs196 CMNoNoNo2Contrat d'EntréePro & Farm1,137,500$0$0$NoLien
Victor EjdsellEvil Saints (PIO)C231995-06-06Yes214 Lbs196 CMNoNoNo2Avec RestrictionPro & Farm925,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1923.74200 Lbs188 CM1.74965,570$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tage ThompsonNick Schmaltz40122
2J.T. CompherVictor EjdsellKasperi Kapanen30122
3Miles WoodNick Schmaltz20122
4J.T. CompherMiles Wood10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jake Dotchin40122
2Blake Hillman30122
3Daniel Brickley20122
4Jake Dotchin10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tage ThompsonNick Schmaltz60122
2J.T. CompherVictor EjdsellKasperi Kapanen40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jake Dotchin60122
2Blake Hillman40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Nick Schmaltz60122
2J.T. CompherMiles Wood40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jake Dotchin60122
2Blake Hillman40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Nick Schmaltz60122Jake Dotchin60122
240122Blake Hillman40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Nick Schmaltz60122
2J.T. CompherMiles Wood40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jake Dotchin60122
2Blake Hillman40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tage ThompsonNick SchmaltzJake Dotchin
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tage ThompsonNick SchmaltzJake Dotchin
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Eric Robinson, , Tage ThompsonEric Robinson, Tage Thompson
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Daniel Brickley, Blake Hillman, Daniel BrickleyBlake Hillman,
Tirs de Pénalité
Nick Schmaltz, , J.T. Compher, Miles Wood,
Gardien
#1 : Alexandar Georgiev, #2 :


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
1Barbarians11000000532110000005320000000000021.000581300896053433502416388332510216300.00%10100.00%042679653.52%33966850.75%28154651.47%824545770273536275
2Barracuda2200000011652200000011650000000000041.0001116270089605348450241638833631310268225.00%5180.00%042679653.52%33966850.75%28154651.47%824545770273536275
3Caribou412000101214-231100010111011010000014-340.5001222340089605341585024163883312235105317423.53%5180.00%042679653.52%33966850.75%28154651.47%824545770273536275
4Casse-Tete1010000015-4000000000001010000015-400.0001230089605344250241638833331447400.00%2150.00%042679653.52%33966850.75%28154651.47%824545770273536275
5Chevalier21000001642110000004131000000123-130.750612180089605347150241638833653014556116.67%7185.71%042679653.52%33966850.75%28154651.47%824545770273536275
6Diabotins2200000013672200000013670000000000041.000132134008960534875024163883362261922600.00%3166.67%042679653.52%33966850.75%28154651.47%824545770273536275
7Giants1010000023-11010000023-10000000000000.0002460089605343650241638833421787200.00%4175.00%042679653.52%33966850.75%28154651.47%824545770273536275
8Hooligans201000101010000000000000201000101010020.500101525008960534735024163883390268314250.00%4175.00%042679653.52%33966850.75%28154651.47%824545770273536275
9Hybrides403000011017-700000000000403000011017-710.1251017270089605341105024163883314054227319315.79%11281.82%042679653.52%33966850.75%28154651.47%824545770273536275
10Jardiniers2200000012392200000012390000000000041.0001219310089605346450241638833661984016425.00%4175.00%042679653.52%33966850.75%28154651.47%824545770273536275
11Remparts22000000822801100000046145110000003613541.00082128210008960534113502416388334316635000.00%3166.67%142679653.52%33966850.75%28154651.47%824545770273536275
12Requins21000100770000000000002100010077030.7507101700896053471502416388338327122213323.08%6183.33%042679653.52%33966850.75%28154651.47%824545770273536275
13Royaux11000000523110000005230000000000021.0005101500896053438502416388333312825500.00%4175.00%042679653.52%33966850.75%28154651.47%824545770273536275
14St Johns422000001619-3211000001114-32110000055040.5001625410089605341465024163883317870225812216.67%11281.82%042679653.52%33966850.75%28154651.47%824545770273536275
Total351612001242041178718134000101255471173800114796316410.58620432552900896053413135024163883312224271675441432718.88%771777.92%142679653.52%33966850.75%28154651.47%824545770273536275
16Werewolves2010000169-3000000000002010000169-310.25068140089605347450241638833762783912325.00%40100.00%042679653.52%33966850.75%28154651.47%824545770273536275
17Zombie3110000167-1211000005501000000112-130.5006814008960534113502416388331013163516318.75%3233.33%042679653.52%33966850.75%28154651.47%824545770273536275
_Since Last GM Reset351612001242041178718134000101255471173800114796316410.58620432552900896053413135024163883312224271675441432718.88%771777.92%142679653.52%33966850.75%28154651.47%824545770273536275
_Vs Conference2078000146267-51072000104127141006000042140-19200.500621031650089605347235024163883365822684329901617.78%42978.57%042679653.52%33966850.75%28154651.47%824545770273536275
_Vs Division1035000123843-5531000102224-2504000021619-3100.5003862100008960534377502416388333901314014233824.24%20480.00%042679653.52%33966850.75%28154651.47%824545770273536275

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
3541L22043255291313122242716754400
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
3516120124204117
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
18134001012554
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
173801147963
Derniers 10 Matchs
WLOTWOTL SOWSOL
640000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1432718.88%771777.92%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
502416388338960534
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
42679653.52%33966850.75%28154651.47%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
824545770273536275


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 - 2018-10-013Jardiniers1Evil Saints6WSommaire du Match
3 - 2018-10-0314Evil Saints1Hybrides2LXXSommaire du Match
5 - 2018-10-0523Royaux2Evil Saints5WSommaire du Match
7 - 2018-10-0733Evil Saints4Hybrides6LSommaire du Match
10 - 2018-10-1046Caribou2Evil Saints1LSommaire du Match
11 - 2018-10-1153Evil Saints2Chevalier3LXXSommaire du Match
15 - 2018-10-1568St Johns11Evil Saints4LSommaire du Match
17 - 2018-10-1780Evil Saints2Werewolves3LXXSommaire du Match
18 - 2018-10-1887Chevalier1Evil Saints4WSommaire du Match
21 - 2018-10-21102Barbarians3Evil Saints5WSommaire du Match
22 - 2018-10-22110Evil Saints36Remparts1WSommaire du Match
23 - 2018-10-23116Evil Saints1Zombie2LXXSommaire du Match
25 - 2018-10-25127Evil Saints1Caribou4LSommaire du Match
26 - 2018-10-26135Jardiniers2Evil Saints6WSommaire du Match
29 - 2018-10-29147Zombie4Evil Saints2LSommaire du Match
31 - 2018-10-31159Evil Saints2St Johns4LSommaire du Match
33 - 2018-11-02168Barracuda5Evil Saints6WSommaire du Match
35 - 2018-11-04182Remparts1Evil Saints46WSommaire du Match
39 - 2018-11-08198Evil Saints2Requins3LXSommaire du Match
40 - 2018-11-09205Caribou3Evil Saints4WSommaire du Match
43 - 2018-11-12218Evil Saints3Hybrides5LSommaire du Match
45 - 2018-11-14226Barracuda1Evil Saints5WSommaire du Match
47 - 2018-11-16237Evil Saints5Requins4WSommaire du Match
49 - 2018-11-18243Evil Saints1Casse-Tete5LSommaire du Match
50 - 2018-11-19249Zombie1Evil Saints3WSommaire du Match
52 - 2018-11-21264Caribou5Evil Saints6WXXSommaire du Match
54 - 2018-11-23277Evil Saints6Hooligans7LSommaire du Match
56 - 2018-11-25285St Johns3Evil Saints7WSommaire du Match
58 - 2018-11-27295Evil Saints3St Johns1WSommaire du Match
60 - 2018-11-29303Diabotins3Evil Saints6WSommaire du Match
62 - 2018-12-01315Evil Saints4Werewolves6LSommaire du Match
63 - 2018-12-02323Diabotins3Evil Saints7WSommaire du Match
66 - 2018-12-05335Evil Saints4Hooligans3WXXSommaire du Match
68 - 2018-12-07343Giants3Evil Saints2LSommaire du Match
70 - 2018-12-09355Evil Saints2Hybrides4LSommaire du Match
72 - 2018-12-11362Giants-Evil Saints-
74 - 2018-12-13376Evil Saints-Zombie-
75 - 2018-12-14384Royaux-Evil Saints-
79 - 2018-12-18399Evil Saints-Chevalier-
80 - 2018-12-19404Royaux-Evil Saints-
82 - 2018-12-21416Evil Saints-Chevalier-
84 - 2018-12-23424Remparts-Evil Saints-
87 - 2018-12-26441Hybrides-Evil Saints-
88 - 2018-12-27446Evil Saints-Leftovers-
91 - 2018-12-30461Pirates-Evil Saints-
92 - 2018-12-31468Evil Saints-Diabotins-
94 - 2019-01-02480Pirates-Evil Saints-
96 - 2019-01-04490Evil Saints-Jardiniers-
98 - 2019-01-06501Casse-Tete-Evil Saints-
99 - 2019-01-07507Evil Saints-Casse-Tete-
101 - 2019-01-09519Leftovers-Evil Saints-
103 - 2019-01-11532Evil Saints-Remparts-
105 - 2019-01-13541Requins-Evil Saints-
107 - 2019-01-15551Evil Saints-Benchwarmers-
109 - 2019-01-17562Benchwarmers-Evil Saints-
111 - 2019-01-19572Evil Saints-Giants-
112 - 2019-01-20580Casse-Tete-Evil Saints-
114 - 2019-01-22586Evil Saints-Benchwarmers-
116 - 2019-01-24600Hybrides-Evil Saints-
119 - 2019-01-27609Evil Saints-Diabotins-
120 - 2019-01-28619Evil Saints-Barracuda-
122 - 2019-01-30626Werewolves-Evil Saints-
123 - 2019-01-31634Evil Saints-Barracuda-
125 - 2019-02-02646Leftovers-Evil Saints-
128 - 2019-02-05662Jardiniers-Evil Saints-
130 - 2019-02-07672Evil Saints-Pirates-
132 - 2019-02-09682Evil Saints-Barbarians-
133 - 2019-02-10685Benchwarmers-Evil Saints-
135 - 2019-02-12699Evil Saints-Pirates-
137 - 2019-02-14706Chevalier-Evil Saints-
141 - 2019-02-18721Evil Saints-Leftovers-
142 - 2019-02-19727Requins-Evil Saints-
145 - 2019-02-22741Evil Saints-Giants-
146 - 2019-02-23746Werewolves-Evil Saints-
147 - 2019-02-24753Evil Saints-Royaux-
150 - 2019-02-27763Hooligans-Evil Saints-
151 - 2019-02-28769Evil Saints-Royaux-
153 - 2019-03-02782Evil Saints-Jardiniers-
154 - 2019-03-03786Hooligans-Evil Saints-
155 - 2019-03-04792Evil Saints-Barbarians-
157 - 2019-03-06801Evil Saints-Caribou-
160 - 2019-03-09813Barbarians-Evil Saints-



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
23 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,064,713$ 3,049,584$ 2,578,334$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
18,825$ 1,064,713$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 92 18,825$ 1,731,900$




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
20168425520040338931079421324003022241457942122800101165165050389596985111331271290259786286487082941105745913473303610.91%1694672.78%1509175029.09%461173126.63%391124831.33%1749118621936371120523
201784224904252187286-9942142301130107131-24428260312280155-75441873155023247805115211260375372757269895035016803195115.99%1764276.14%2627144943.27%629161139.04%414103440.04%164496321097081334658
2017843032066462662343242151404414139115244215180223212711986026644170702898384112429811784783832635948101615872615019.16%4608082.61%11738158746.50%898197545.47%454107642.19%1785112820747081255592
20183516120012420411787181340001012554711738001147963164120432552900896053413135024163883312224271675441432718.88%771777.92%142679653.52%33966850.75%28154651.47%824545770273536275
Total Saison Régulière28793145010131115104694799144556505856595445150143388005569451502-51195104616772723453583503173084512778281727681819496338219925158105316415.57%88218579.02%152300558241.20%2327598538.88%1540390439.45%600438247147232842462049
Séries
201640400000426-222020000028-620200000218-1604711001210933135270172392270800.00%11190.91%0106714.93%159216.30%95316.98%6341127284819
20161046000002527-25230000014122523000001115-482545700071152291816810438351126102228371232.43%42685.71%07320236.14%7524131.12%3911833.05%2121202859817785
201740400000822-142020000058-320200000314-11081321001520100353232114358186615320.00%9455.56%0447657.89%418846.59%205834.48%7343108336029
201740400000714-72020000047-32020000037-407111800043011736453601344863611417.14%24866.67%0278830.68%5010249.02%174240.48%855498345626
Total Séries22418000004489-451129000002535-101129000001954-35844761200092211260118318019939800271205425741621.62%861977.91%015443335.57%18152334.61%8527131.37%435259620195344160