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 : 67
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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
1Jamie McGinn0XX100.00793963357857557337798353687460047700
2Pontus Aberg0XX100.00521065345865777233808256745534043700
3Jujhar Khaira0X100.00814254438358676762798166714555052690
4Filip Chytil0XXX100.00422174366765787053788156723637047690
5Oscar Lindberg0XX100.00792356386856777164778154716446050690
6Tobias Rieder0XXX100.00682475455262766438787971736751047680
7Joakim Nordstrom0X100.00782773476358726447767961696048047670
8Boo Nieves0X100.00692163467645786570788253663740047660
9Phillip Di Giuseppe0X100.00832859425847766757777948764545047650
10Vinni Lettieri0X100.00792654455449846352757851663942047640
11Markus Hannikainen0X100.00801275486641716536737947705239047630
12Alex Biega0X100.00852754446560808528857649645662047720
13Mike Reilly0X100.00551466446263808229827550654534047700
14Mark Borowiecki0XX100.00964835498355448031807465595565054690
15Dean Kukan0X100.00562367475850778030827639665744047680
16Robert Bortuzzo0X100.00824246488754618026817556586259050680
17Libor Hajek (R)0X100.00392574596660736831726961684447050650
Rayé
1Matt Martin0XX100.00924949509149716352778052697067055680
2Austin Czarnik0X100.00392372383751787057808152705151050670
3Scott Wilson0X100.00813272445555606548777963634447050650
4Nail Yakupov0XX100.00652457395849716531727954755345050640
5Kalle Kossila0XXX100.00401773604945815936667559674441050600
6Nic Petan0XX100.00362967544235796139687747655059047600
7Steven Fogarty0X100.00402380677835825733657161684151047590
8Kevin Gravel0X100.00622975498154887929807361654748047690
9Jaycob Megna0X100.00622463508654847830787461664451050680
10Chris Wideman0X100.00773147445346648328827746705357050680
11Joe Hicketts0X100.00492982584067816931737064674663050670
12Yannick Weber0X100.00732462476641608025797535757052050670
13Ryan Sproul0X100.00372678567659786830727054664947050650
14Chris Bigras0X100.00402581595850786830726954664550050630
MOYENNE D'ÉQUIPE100.0064276547655374703977775568525004967
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
1Michael Hutchinson100.0083928280828985868879757372047800
2Christopher Gibson100.0082888278828587859053616467050790
Rayé
MOYENNE D'ÉQUIPE100.008390827982878686896668697004980
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
Alex BiegaLeftovers (Tru)D311988-04-04No199 Lbs178 CMNoNoNo2Pro & Farm990,000$990,000$0$0$No990,000$Lien / Lien NHL
Austin CzarnikLeftovers (Tru)C261992-12-12No170 Lbs175 CMNoNoNo1Pro & Farm1,250,000$1,250,000$0$0$NoLien
Boo NievesLeftovers (Tru)C251994-01-23No210 Lbs191 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien
Chris BigrasLeftovers (Tru)D241995-02-22No191 Lbs185 CMNoNoNo1Pro & Farm874,125$874,125$0$0$NoLien / Lien NHL
Chris WidemanLeftovers (Tru)D291990-01-07No183 Lbs178 CMNoNoNo0Pro & Farm0$0$NoLien / Lien NHL
Christopher GibsonLeftovers (Tru)G261992-12-27No207 Lbs188 CMNoNoNo1Pro & Farm675,000$675,000$0$0$NoLien / Lien NHL
Dean KukanLeftovers (Tru)D261993-07-08No186 Lbs188 CMNoNoNo2Pro & Farm725,000$725,000$0$0$No725,000$Lien
Filip ChytilLeftovers (Tru)C/LW/RW201999-09-05No208 Lbs188 CMNoNoNo2Pro & Farm1,244,166$1,244,166$0$0$No1,244,166$Lien
Jamie McGinnLeftovers (Tru)LW/RW311988-08-05No205 Lbs185 CMNoNoNo2Pro & Farm780,000$780,000$0$0$No780,000$Lien / Lien NHL
Jaycob MegnaLeftovers (Tru)D261992-12-10No221 Lbs198 CMNoNoNo1Pro & Farm650,000$650,000$0$0$NoLien
Joakim NordstromLeftovers (Tru)C271992-02-25No194 Lbs185 CMNoNoNo2Pro & Farm1,000,000$1,000,000$0$0$No1,000,000$Lien / Lien NHL
Joe HickettsLeftovers (Tru)D231996-05-04No180 Lbs173 CMNoNoNo0Pro & Farm0$0$NoLien
Jujhar KhairaLeftovers (Tru)LW251994-08-13No212 Lbs193 CMNoNoNo2Pro & Farm1,200,000$1,200,000$0$0$No1,200,000$Lien / Lien NHL
Kalle KossilaLeftovers (Tru)C/LW/RW261993-04-14No185 Lbs178 CMNoNoNo1Pro & Farm650,000$650,000$0$0$NoLien
Kevin GravelLeftovers (Tru)D271992-03-06No211 Lbs193 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien / Lien NHL
Libor HajekLeftovers (Tru)D211998-02-04Yes204 Lbs188 CMNoNoNo1Pro & Farm894,166$894,166$0$0$NoLien
Mark BorowieckiLeftovers (Tru)LW/D301989-07-12No207 Lbs185 CMNoNoNo1Pro & Farm1,440,000$1,440,000$0$0$NoLien / Lien NHL
Markus HannikainenLeftovers (Tru)LW261993-03-26No200 Lbs185 CMNoNoNo2Pro & Farm750,000$750,000$0$0$No750,000$Lien / Lien NHL
Matt MartinLeftovers (Tru)LW/RW301989-05-08No220 Lbs191 CMNoNoNo0Pro & Farm0$0$NoLien / Lien NHL
Michael HutchinsonLeftovers (Tru)G291990-03-02No200 Lbs191 CMNoNoNo2Pro & Farm840,000$840,000$0$0$No840,000$Lien / Lien NHL
Mike ReillyLeftovers (Tru)D261993-07-13No195 Lbs185 CMNoNoNo2Pro & Farm1,500,000$1,500,000$0$0$No1,500,000$Lien / Lien NHL
Nail YakupovLeftovers (Tru)LW/RW251993-10-06No195 Lbs180 CMNoNoNo1Pro & Farm962,500$962,500$0$0$NoLien / Lien NHL
Nic PetanLeftovers (Tru)C/LW241995-03-22No179 Lbs175 CMNoNoNo2Pro & Farm775,000$775,000$0$0$No775,000$Lien / Lien NHL
Oscar LindbergLeftovers (Tru)C/RW271991-10-29No202 Lbs185 CMNoNoNo1Pro & Farm1,700,000$1,700,000$0$0$NoLien / Lien NHL
Phillip Di GiuseppeLeftovers (Tru)RW251993-10-09No192 Lbs183 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien / Lien NHL
Pontus AbergLeftovers (Tru)LW/RW261993-09-23No196 Lbs180 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien / Lien NHL
Robert BortuzzoLeftovers (Tru)D301989-03-18No216 Lbs193 CMNoNoNo1Pro & Farm1,656,000$1,656,000$0$0$NoLien / Lien NHL
Ryan SproulLeftovers (Tru)D261993-01-13No205 Lbs193 CMNoNoNo1Pro & Farm687,500$687,500$0$0$NoLien / Lien NHL
Scott WilsonLeftovers (Tru)RW271992-04-24No186 Lbs180 CMNoNoNo1Pro & Farm1,050,000$1,050,000$0$0$NoLien / Lien NHL
Steven FogartyLeftovers (Tru)C261993-04-19No210 Lbs191 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien
Tobias RiederLeftovers (Tru)C/LW/RW261993-01-10No186 Lbs180 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien / Lien NHL
Vinni LettieriLeftovers (Tru)C241995-02-06No191 Lbs180 CMNoNoNo2Pro & Farm700,000$700,000$0$0$No700,000$Lien
Yannick WeberLeftovers (Tru)D311988-09-23No200 Lbs180 CMNoNoNo0Pro & Farm0$0$NoLien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3326.39198 Lbs185 CM1.39824,044$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
132113
2Oscar Lindberg28113
322122
418140
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
135131
234131
3Robert Bortuzzo31131
40122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
160113
2Oscar Lindberg40113
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
16012260122
24012240122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Oscar Lindberg
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Robert Bortuzzo, Robert Bortuzzo,
Tirs de Pénalité
, , , ,
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$ 2,719,346$ 2,674,929$ 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