hellpepitosKingspatriots

 

 


Leftovers

GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: Francois Bedard | Morale : 50 | Moyenne d'Équipe : 62
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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
1Jujhar Khaira0X100.00866182788163796847484673256161050670
2Vinni Lettieri0X100.00756081677073856362434272634747050670
3Steven Fogarty0X100.00756588627770867461434364574545050660
4Joakim Nordstrom0X100.00825190747063765728474675256870050650
5Anthony Angello0X100.00767969667974785873383864604444050650
6Boo Nieves0X100.00786690767963705859454472485959050650
7Pontus Aberg0XX100.00726084767073786242454461625455050650
8Filip Chytil0XXX100.00604095826667896456494957255959050640
9Austin Czarnik0X100.00635785805863646762454468676263050640
10Tobias Rieder0XXX100.00684196846760785931484672256768050640
11Greg McKegg0X100.00755190717055805951474768256364047630
12Mark Borowiecki0XX100.00996065687672706644423982256667047640
13Mike Reilly0X100.00724286787375686725443861256060050620
14Adam Boqvist (R)0X100.00714294806469727425434060254747050610
15Alex Biega0X100.00894485706871646139423870536565050610
16Joe Hicketts0X100.00736692666175815729373766384949050590
17Dean Kukan0X100.00684689687066546325423862255960050590
18Robert Bortuzzo0X100.00815382708263685425413966256668050590
Rayé
1Markus Hannikainen0X100.00796795647257596153424268574950050620
2Nic Petan0XX100.00614693796255576553494575255959050620
3Scott Wilson0X100.00757086736658586242434269585859050620
4Phillip Di Giuseppe0X100.00815288797354745633464465255757050610
5Kalle Kossila0XXX100.00746589536461545569404063584646050600
6Joakim Nygard (R)0X100.00654191906557616144494661254747050590
7Libor Hajek0X100.00734387677568745725423882254747050600
8Jaycob Megna0X100.00827383608670805128343371395252050570
9Kevin Gravel0X100.00806991708056555025333267385657050530
MOYENNE D'ÉQUIPE100.0075568772716571614343416839565605062
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
1Ilya Samsonov (R)100.0077636080827275768277754646044730
2Christopher Gibson100.0058638372586252615856304545050610
Rayé
1Michael Hutchinson100.0050616781584751525257785959050570
2Antoine Bibeau (R)100.0049527282444850565045304444050550
MOYENNE D'ÉQUIPE100.005960717961575761615953494904962
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
David Quinn94867957717650USA543450,000$


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
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


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Salaire RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Adam BoqvistLeftovers (Tru)D202000-08-14Yes179 Lbs180 CMNoNoNo2Pro & Farm1,744,167$1,744,167$0$0$No1,744,167$Lien
Alex BiegaLeftovers (Tru)D321988-04-04No193 Lbs178 CMNoNoNo2Pro & Farm990,000$990,000$0$0$No990,000$Lien / Lien NHL
Anthony AngelloLeftovers (Tru)C241996-03-06No209 Lbs196 CMNoNoNo2Pro & Farm925,000$925,000$0$0$No925,000$Lien
Antoine BibeauLeftovers (Tru)G261994-05-01Yes207 Lbs191 CMNoNoNo2Pro & Farm675,000$675,000$0$0$No675,000$
Austin CzarnikLeftovers (Tru)C271992-12-12No160 Lbs175 CMNoNoNo1Pro & Farm1,250,000$1,250,000$0$0$NoLien
Boo NievesLeftovers (Tru)C261994-01-23No212 Lbs191 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien
Christopher GibsonLeftovers (Tru)G271992-12-27No188 Lbs185 CMNoNoNo1Pro & Farm675,000$675,000$0$0$NoLien / Lien NHL
Dean KukanLeftovers (Tru)D271993-07-08No186 Lbs188 CMNoNoNo2Pro & Farm725,000$725,000$0$0$No725,000$Lien
Filip ChytilLeftovers (Tru)C/LW/RW211999-09-05No178 Lbs185 CMNoNoNo2Pro & Farm1,244,166$1,244,166$0$0$No1,244,166$Lien
Greg McKeggLeftovers (Tru)C281992-06-17No191 Lbs183 CMNoNoNo2Pro & Farm750,000$750,000$0$0$No750,000$Lien / Lien NHL
Ilya SamsonovTruitesG231997-02-21Yes200 Lbs191 CMNoNoNo2Pro & Farm1,475,000$1,475,000$1,475,000$1,475,000$No1,475,000$Lien
Jaycob MegnaLeftovers (Tru)D271992-12-10No225 Lbs198 CMNoNoNo1Pro & Farm650,000$650,000$0$0$NoLien
Joakim NordstromLeftovers (Tru)C281992-02-25No189 Lbs185 CMNoNoNo2Pro & Farm1,000,000$1,000,000$0$0$No1,000,000$Lien / Lien NHL
Joakim NygardLeftovers (Tru)LW271993-01-08Yes179 Lbs183 CMNoNoNo2Pro & Farm925,000$925,000$0$0$No925,000$Lien
Joe HickettsLeftovers (Tru)D241996-05-04No175 Lbs173 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien
Jujhar KhairaLeftovers (Tru)LW261994-08-13No214 Lbs193 CMNoNoNo2Pro & Farm1,200,000$1,200,000$0$0$No1,200,000$Lien / Lien NHL
Kalle KossilaLeftovers (Tru)C/LW/RW271993-04-14No175 Lbs180 CMNoNoNo1Pro & Farm650,000$650,000$0$0$NoLien
Kevin GravelLeftovers (Tru)D281992-03-06No212 Lbs193 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien / Lien NHL
Libor HajekLeftovers (Tru)D221998-02-03No202 Lbs188 CMNoNoNo1Pro & Farm894,166$894,166$0$0$NoLien
Mark BorowieckiTruitesLW/D311989-07-12No207 Lbs185 CMNoNoNo1Pro & Farm1,440,000$1,440,000$1,440,000$1,440,000$NoLien / Lien NHL
Markus HannikainenLeftovers (Tru)LW271993-03-25No190 Lbs188 CMNoNoNo2Pro & Farm750,000$750,000$0$0$No750,000$Lien / Lien NHL
Michael HutchinsonLeftovers (Tru)G301990-03-01No202 Lbs191 CMNoNoNo2Pro & Farm840,000$840,000$0$0$No840,000$Lien / Lien NHL
Mike ReillyLeftovers (Tru)D271993-07-12No195 Lbs188 CMNoNoNo2Pro & Farm1,500,000$1,500,000$0$0$No1,500,000$Lien / Lien NHL
Nic PetanLeftovers (Tru)C/LW251995-03-21No179 Lbs175 CMNoNoNo2Pro & Farm775,000$775,000$0$0$No775,000$Lien / Lien NHL
Phillip Di GiuseppeLeftovers (Tru)RW261993-10-09No201 Lbs183 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien / Lien NHL
Pontus AbergLeftovers (Tru)LW/RW271993-09-22No196 Lbs180 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien / Lien NHL
Robert BortuzzoLeftovers (Tru)D311989-03-18No216 Lbs193 CMNoNoNo1Pro & Farm1,656,000$1,656,000$0$0$NoLien / Lien NHL
Scott WilsonLeftovers (Tru)RW281992-04-24No183 Lbs180 CMNoNoNo1Pro & Farm1,050,000$1,050,000$0$0$NoLien / Lien NHL
Steven FogartyLeftovers (Tru)C271993-04-18No206 Lbs191 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien
Tobias RiederLeftovers (Tru)C/LW/RW271993-01-09No186 Lbs180 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien / Lien NHL
Vinni LettieriLeftovers (Tru)C251995-02-06No195 Lbs180 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3126.48195 Lbs185 CM1.74947,855$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jujhar KhairaAnthony AngelloPontus Aberg32113
2Vinni LettieriFilip Chytil28113
3Tobias RiederJoakim NordstromAustin Czarnik22122
4Greg McKeggBoo NievesSteven Fogarty18140
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Joe HickettsMike Reilly35131
2Adam BoqvistAlex Biega34131
3Robert BortuzzoDean Kukan31131
4Robert Bortuzzo0122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jujhar KhairaSteven FogartyPontus Aberg60113
2Tobias RiederVinni LettieriFilip Chytil40113
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dean KukanMike Reilly60122
2Adam BoqvistAlex Biega40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Joakim NordstromJujhar Khaira60122
2Vinni LettieriTobias Rieder40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Robert BortuzzoMike Reilly60122
2Adam BoqvistAlex Biega40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Tobias Rieder60122Mike Reilly60122
2Vinni Lettieri40122Adam BoqvistAlex Biega40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Boo NievesJujhar Khaira60122
2Vinni LettieriPontus Aberg40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Robert BortuzzoMike Reilly60122
2Adam BoqvistAlex Biega40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jujhar KhairaTobias RiederPontus AbergDean KukanMike Reilly
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jujhar KhairaAnthony AngelloPontus AbergDean KukanMike Reilly
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Austin Czarnik, Tobias Rieder, Joakim NordstromJoakim Nordstrom, Tobias RiederJoakim Nordstrom
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Joe Hicketts, Dean Kukan, Robert BortuzzoJoe HickettsJoe Hicketts, Dean Kukan
Tirs de Pénalité
Tobias Rieder, Jujhar Khaira, Vinni Lettieri, Pontus Aberg, Joakim Nordstrom
Gardien
#1 : , #2 : Christopher Gibson


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
Total00000000000000000000000000000000000.000000000000000000000000.00%000.00%0000.00%000.00%000.00%000000

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
00N/A0000000000
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
000000000
Derniers 10 Matchs
WLOTWOTL SOWSOL
000000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
000.00%000.00%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
00000000
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
000.00%000.00%000.00%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
000000


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



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance0.00%0.00%
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
42 0 - 0.00%0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 3,009,351$ 2,877,434$ 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$ 0 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
201684280010013142066-17524204101000149998-84942239000011651068-9034314560874001071041021249283185879982120772202215863286921.04%41227932.28%81071168463.60%52784662.29%1796302759.33%2002129416996261346666
20168446220732444219225042297021122548616842171505212188106829244277412160413813416111260683388985451221481993918532756222.55%3235682.66%141033165662.38%987159162.04%783121764.34%2097138617146651277661
201784293905146245378-13342161702034119191-7242132203112126187-61582454186631481758013220069775471666259688666715682855619.65%3246978.70%11654154842.25%735165644.38%499120441.45%1809112019826971313650
2017842439073653042455942161405313169104654282502052135141-648304530834231121017818256282685183191231275771418812814415.66%3486780.75%141029172959.51%997159862.39%701112562.31%2049133717766711298660
201882432404245465289176412710000312401241164116140421422516560864658311296021901581091032211166105197556263393487718143388525.15%4168380.05%241110191957.84%1022176357.97%788130660.34%2023132416996551250644
201882244803421473374994115200222026117388419280120121220111484738241297222001451238302911659109402529221056130115222716122.51%54914573.59%251112178462.33%1211197461.35%880141562.19%1895123318526531204603
Total Saison Régulière50016825202713182222433544-13012501031090126101011921676-48425065143015781210511868-8173362243393761805158287176536116110551853135115297147975224652010224177837721.20%237269970.53%9660091032058.23%5479942858.11%5447929458.61%11877769710723397076913886
Séries
2016161150000055352076100000321220954000002323022551021570221211125561691891899431144165310601931.67%55983.64%119935755.74%16330653.27%11121052.86%410278331124233120
2016954000001918153200000101004220000098110193251009361293113701064247941141932328.70%43783.72%212118665.05%13519369.95%7510273.53%2451711776712565
2017514000001318-52110000087130300000511-62132336007420143434455118852548623521.74%27388.89%1549954.55%4912937.98%226036.67%10768128407034
2017514000001119-82110000076130300000413-92111829004250191654776317473569311327.27%29968.97%17710573.33%8212864.06%446765.67%12484111376734
20181156000003539-45230000019181633000001621-510355792102067241615112612910399148138268581322.41%641871.88%314329348.81%13826152.87%6714845.27%25815526010118189
2018514000001827-9211000001210230300000617-112183452009630154674339521871948426311.54%371267.57%04510742.06%8314955.70%447757.14%10361132457435
Total Séries51242700000151156-52314900000886325281018000006393-3048151266417127042345175360851959432165758262110342014522.39%2555877.25%8639114755.71%650116655.75%36366454.67%12498191143416753380