beholdershellpepitosKingspatriots

 

 


Hooligans

GP: 5 | W: 1 | L: 4 | OTL: 0 | P: 2
GF: 14 | GA: 26 | PP%: 4.55% | PK%: 54.55%
DG: Maxime Lord | Morale : 50 | Moyenne d'Équipe : 75
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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
1Adrian Kempe0XX100.00663761305361847173838172744843049810
2Alex Iafallo (R)0XX100.00503483274170836843828176634034050800
3Tim Schaller0X100.00784158437559816761808268674846050800
4Matt Moulson0XX100.00453579367351817132808259807057050780
5Mike Ribeiro0X100.00493665435675776174796848848370050770
6Jonny Brodzinski0X100.00693372397444856936798662684234050770
7Drake Caggiula0X100.00834062343763736958798363624134052770
8Marcus Sorensen0X100.00593966493447866436798066634838050740
9Michael Amadio (R)0X100.00462679406142766569807855654543050730
10Zach Aston-Reese (R)0X100.00924159546449656136737671644245050730
11John Quenneville0X100.00663863575263675831707765714238050720
12Ales Hemsky0X100.00313463454856295931717864847968050710
13Dryden Hunt (R)0X100.00853465645148775833707658644239050700
14Frederick Gaudreau0X100.00443389593542756075757654634638050690
15Erik Gustafsson0X100.00493769423567848931857570615042050840
16Tim Heed0X100.00342274424558718330807357725141023780
17Nick Schultz0X100.00643773597655797030726765408174050780
18Brett Kulak0X100.00473863495048848127797161624437052760
19Paul LaDue0X100.00573265456254737930767162644235050760
20Christian Wolanin (R)0X100.00413386524553787330736862653533050730
21Evan McEneny0X100.00263283596555776931726554654136050720
Rayé
1Connor Brown0X100.00393480364072927557828273674946050820
2Ryan Carpenter0X100.00773869416359886876808268634644050800
3Sean Malone0X100.00263285615256795631677353653531050670
4Griffen Molino0X100.00323382683148775631677254653529050650
5Justin Kloos0X100.00512863643238775631677051654040050630
6TJ Tynan0X100.00373290702732735631677049654742050620
7Sami Niku (R)0X100.00263084583355766931726655654437050710
MOYENNE D'ÉQUIPE100.0052347349505477674276756166484304974
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 Campbell100.0081856579838291858567725974050840
2Ken Appleby100.0080886381828191848568712954050810
Rayé
MOYENNE D'ÉQUIPE100.008187648083829185856872446405083
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Marcus SorensenHooligans (HOO)RW5156520541091010.00%2499.9600000000000033.33%351002.4100000000
2Tim SchallerHooligans (HOO)C5505417564155433.33%3418.2600000000000057.78%4513002.4200000000
3Matt MoulsonHooligans (HOO)LW/RW5314-70011163113199.68%1210320.63101524000000050.00%448000.7800000000
4Nick SchultzHooligans (HOO)D5123-240820251274.00%128116.230000200022000.00%067000.7400000100
5Paul LaDueHooligans (HOO)D5303320111105530.00%4469.330000000000100.00%002001.2900000000
6Dryden HuntHooligans (HOO)LW5112-200917258174.00%128617.250003170000000100.00%1177000.4600000000
7Evan McEnenyHooligans (HOO)D5011-200015310.00%7183.600000000000000.00%000001.1100000000
8Christian WolaninHooligans (HOO)D5011300136440.00%2469.320000000000000.00%024000.4300000000
9Mike RibeiroHooligans (HOO)C5011120313000.00%071.5400000000000088.89%920002.6000000000
10Zach Aston-ReeseHooligans (HOO)C5000000000010.00%220.520000000001000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne5014122632755467130596810.77%564839.66101844000241061.29%623732001.0800000100
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 CampbellHooligans (HOO)51400.8965.033102026249143100.000050011
Stats d'équipe Total ou en Moyenne51400.8965.033102026249143100.000050011


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
Adrian KempeHooligans (HOO)C/LW221996-09-13No195 Lbs188 CMNoNoNo1Contrat d'EntréePro & Farm894,167$0$0$NoLien / Lien NHL
Ales HemskyHooligans (HOO)RW351983-08-13No177 Lbs183 CMNoNoNo1Sans RestrictionPro & Farm760,001$0$0$NoLien / Lien NHL
Alex IafalloHooligans (HOO)C/LW241993-12-21Yes185 Lbs183 CMNoNoNo2Avec RestrictionPro & Farm925,000$0$0$NoLien
Brett KulakHooligans (HOO)D241994-01-06No187 Lbs188 CMNoNoNo1Avec RestrictionPro & Farm817,000$0$0$NoLien
Christian WolaninHooligans (HOO)D231995-03-17Yes185 Lbs188 CMNoNoNo2Avec RestrictionPro & Farm925,000$0$0$NoLien
Connor BrownHooligans (HOO)RW241994-01-14No185 Lbs183 CMNoNoNo3Avec RestrictionPro & Farm2,100,000$0$0$NoLien / Lien NHL
Drake CaggiulaHooligans (HOO)RW241994-06-20No185 Lbs178 CMNoNoNo1Avec RestrictionPro & Farm1,350,000$0$0$NoLien / Lien NHL
Dryden HuntHooligans (HOO)LW221995-11-24Yes197 Lbs183 CMNoNoNo2Contrat d'EntréePro & Farm925,000$0$0$NoLien
Erik GustafssonHooligans (HOO)D261992-03-14No176 Lbs183 CMNoNoNo1Avec RestrictionPro & Farm925,000$0$0$NoLien / Lien NHL
Evan McEnenyHooligans (HOO)D241994-05-22No203 Lbs188 CMNoNoNo1Avec RestrictionPro & Farm450,001$0$0$NoLien
Frederick GaudreauHooligans (HOO)C251993-05-01No179 Lbs183 CMNoNoNo1Avec RestrictionPro & Farm595,000$0$0$NoLien / Lien NHL
Griffen MolinoHooligans (HOO)C241994-01-21No171 Lbs180 CMNoNoNo1Avec RestrictionPro & Farm450,000$0$0$NoLien / Lien NHL
Jack CampbellHooligans (HOO)G261992-01-09No197 Lbs188 CMNoNoNo1Avec RestrictionPro & Farm612,500$0$0$NoLien / Lien NHL
John QuennevilleHooligans (HOO)C221996-04-16No195 Lbs185 CMNoNoNo1Contrat d'EntréePro & Farm894,167$0$0$NoLien
Jonny BrodzinskiHooligans (HOO)C251993-06-19No217 Lbs185 CMNoNoNo1Avec RestrictionPro & Farm925,000$0$0$NoLien / Lien NHL
Justin KloosHooligans (HOO)C241993-11-30No180 Lbs175 CMNoNoNo2Avec RestrictionPro & Farm925,000$0$0$NoLien
Ken ApplebyHooligans (HOO)G231995-04-10No210 Lbs193 CMNoNoNo2Avec RestrictionPro & Farm635,000$0$0$NoLien
Marcus SorensenHooligans (HOO)RW261992-04-07No175 Lbs180 CMNoNoNo1Avec RestrictionPro & Farm1,350,000$0$0$NoLien
Matt MoulsonHooligans (HOO)LW/RW341983-11-01No203 Lbs185 CMNoNoNo1Sans RestrictionPro & Farm750,000$0$0$NoLien / Lien NHL
Michael AmadioHooligans (HOO)C221996-05-13Yes204 Lbs185 CMNoNoNo2Contrat d'EntréePro & Farm925,000$0$0$NoLien
Mike RibeiroHooligans (HOO)C381980-02-10No179 Lbs183 CMNoNoNo1Sans RestrictionPro & Farm450,000$0$0$NoLien / Lien NHL
Nick SchultzHooligans (HOO)D361982-08-25No203 Lbs185 CMNoNoNo1Sans RestrictionPro & Farm450,000$0$0$NoLien / Lien NHL
Paul LaDueHooligans (HOO)D261992-09-06No198 Lbs188 CMNoNoNo1Avec RestrictionPro & Farm925,000$0$0$NoLien / Lien NHL
Ryan CarpenterHooligans (HOO)C271991-01-18No200 Lbs183 CMNoNoNo1Avec RestrictionPro & Farm650,000$0$0$NoLien / Lien NHL
Sami NikuHooligans (HOO)D211996-10-10Yes176 Lbs185 CMNoNoNo2Contrat d'EntréePro & Farm916,667$0$0$NoLien
Sean MaloneHooligans (HOO)C231995-04-30No197 Lbs183 CMNoNoNo1Avec RestrictionPro & Farm925,000$0$0$NoLien / Lien NHL
TJ TynanHooligans (HOO)C261992-02-25No165 Lbs173 CMNoNoNo1Avec RestrictionPro & Farm600,000$0$0$NoLien / Lien NHL
Tim HeedHooligans (HOO)D271991-01-27No185 Lbs183 CMNoNoNo1Avec RestrictionPro & Farm775,000$0$0$NoLien
Tim SchallerHooligans (HOO)C271990-11-16No210 Lbs188 CMNoNoNo1Avec RestrictionPro & Farm600,000$0$0$NoLien
Zach Aston-ReeseHooligans (HOO)C241994-08-10Yes204 Lbs183 CMNoNoNo2Avec RestrictionPro & Farm925,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3025.80191 Lbs183 CM1.33844,983$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matt Moulson40122
2Dryden Hunt30122
3Tim SchallerMarcus Sorensen20122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
2Nick Schultz30122
3Paul LaDueChristian Wolanin20122
4Evan McEneny10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matt Moulson60122
2Dryden Hunt40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Nick Schultz40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
2Tim Schaller40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Nick Schultz40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
16012260122
240122Nick Schultz40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
2Tim Schaller40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Nick Schultz40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matt Moulson
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matt Moulson
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Mike Ribeiro, Jonny Brodzinski, Zach Aston-ReeseMike Ribeiro, Jonny BrodzinskiZach Aston-Reese
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Paul LaDue, Christian Wolanin, Evan McEnenyPaul LaDueChristian Wolanin, Evan McEneny
Tirs de Pénalité
, , , Tim Schaller, Matt Moulson
Gardien
#1 : Jack Campbell, #2 : Ken Appleby


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
1Benchwarmers514000001426-122110000079-230300000717-1020.20014193300526114047444542497933632214.55%11554.55%0188720.69%3412028.33%147418.92%8555158406628
Total514000001426-122110000079-230300000717-1020.20014193300526114047444542497933632214.55%11554.55%0188720.69%3412028.33%147418.92%8555158406628
_Since Last GM Reset514000001426-122110000079-230300000717-1020.20014193300526114047444542497933632214.55%11554.55%0188720.69%3412028.33%147418.92%8555158406628
_Vs Conference514000001426-122110000079-230300000717-1020.20014193300526114047444542497933632214.55%11554.55%0188720.69%3412028.33%147418.92%8555158406628

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
52L114193314024979336300
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
51400001426
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
211000079
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3030000717
Derniers 10 Matchs
WLOTWOTL SOWSOL
140000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2214.55%11554.55%0
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
47444545261
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
188720.69%3412028.33%147418.92%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
8555158406628


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
1 - 2019-04-038Hooligans2Benchwarmers6LSommaire du Match
2 - 2019-04-0416Hooligans4Benchwarmers8LSommaire du Match
3 - 2019-04-0524Benchwarmers6Hooligans3LSommaire du Match
4 - 2019-04-0632Benchwarmers3Hooligans4WXSommaire du Match
5 - 2019-04-0740Hooligans1Benchwarmers3LSommaire du Match



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
39 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 2,534,951$ 2,035,784$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 0$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 3 0$ 0$




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
201684195301326255252342132101124116102144263200202139150-11382554146694379888552460777797880393014111283716192494819.28%3117476.21%9497162630.57%512204725.01%294104028.27%1673110523006461113502
20178438310453333031317422312012221631333042151903311167180-137633053886822118110957276992293689537246191241915103078126.38%2094677.99%18814178345.65%606148340.86%566121646.55%1942131219356381205591
201784313703661242224184217180123110610514214190243013611917622424216632482698210246081880080959243684160121382894716.26%2857175.09%4957167957.00%854166051.45%51299851.30%1925119718476881322675
201882393500422503298205412612000122821181644113230041022118041785038281331232181781052326612211076961243033111553812463238024.77%2495478.31%7833189843.89%734174542.06%616137144.93%1904131519006101144558
Total Saison Régulière33412715608181312133010872431677963035896674582091674893051353663629342541330220135311012497445367241095537383609354515910944398023956513116825621.92%105424576.76%383101698644.39%2706693539.02%1988462542.98%744649307982258447852329
Séries
201640400000510-52020000025-32020000035-2058130001409420472341505715702129.52%50100.00%06876.90%189119.78%64613.04%6639129335123
2016624000001419-53120000078-131200000711-4414243800445120059636315185526312427311.11%241058.33%010013772.99%8312466.94%497169.01%1661071335710856
20171697000004754-78620000028208835000001934-151847801270019121335461821891631257421386238862427.91%43881.40%016139840.45%12636134.90%8322437.05%359243411130223105
2017954000001919043100000103752300000916-71019264504477128689831068199756822819315.79%34488.24%012818170.72%8213162.60%599661.46%2471671726213273
2018514000001426-122110000079-230300000717-10214193300526114047444542497933632214.55%11554.55%0188720.69%3412028.33%147418.92%8555158406628
Total Séries4017230000099128-2919118000005445921615000004583-38349915725604322635612663974264004313574762657231753318.86%1172776.92%041389046.40%34382741.48%21151141.29%9266141005323581287