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IceHogs

GP: 1 | W: 1 | L: 0
GF: 7 | GA: 2 | PP%: 0.00% | PK%: 100.00%
DG: Laurent Laporte | Morale : 50 | Moyenne d'Équipe : 62
Prochain matchs #14 vs Wolves
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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
1Nolan PatrickXX100.00674483748078857380706759726164055670
2Nick RitchieX100.00894764688778736753726463666766073670
3Jesperi Kotkaniemi (R)XX100.00673885697775927178726659705962045660
4Jakob Forsbacka KarlssonXX100.00593593677475626573666264636564050640
5Adam CracknellXXX100.00703691598578665862595860548474050630
6Chris TerryXX100.00543787646993916368616258637870050630
7Curtis McKenzieX100.00674372618194926068615760597568050630
8Michael SgarbossaX100.00574177637294956268616158627367050630
9C.J. SmithX100.00523692636981706259616459626966050620
10Michael AmadioXX100.00563690627873656173626357636563050620
11Adam TambelliniXX100.00653692578294935660565458556965050610
12Nicolas RoyXX100.00633691598777715865565660546362050610
13Madison BoweyX100.00775473628079636130735466526765069630
14Chris BigrasX100.00613885577690845630595156466764050590
15Sergei BoikovX100.00643676577877735630545253516364050580
16Tobias Geisser (R)X100.00643676578277735630545253516364050580
Rayé
1Axel HolmstromXX100.00613594587492895663555457596563050600
2Jansen HarkinsXX100.00583788577493915659555657566362050600
3Kristian Vesalainen (R)XX100.00633692598569615854595657596062050600
4Nic PetanXXX100.00503593546560505458555451546765050560
MOYENNE D'ÉQUIPE100.0063398561788177605861585859676505262
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
1Mike Condon100.0074656379737374737374737783050650
Rayé
MOYENNE D'ÉQUIPE100.007465637973737473737473778305065
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'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
1Madison BoweyIceHogs (CHI)D1033400431000.00%12424.970000200003000.00%000002.4000000010
2Curtis McKenzieIceHogs (CHI)LW12133004350040.00%01616.87000000000000100.00%100003.5600000100
3Jakob Forsbacka KarlssonIceHogs (CHI)C/RW11121000042125.00%12020.130001300001000.00%100001.9900000000
4Michael AmadioIceHogs (CHI)C/RW1022300021100.00%01515.3500000000020050.00%600002.6100000000
5Michael SgarbossaIceHogs (CHI)C11123000241025.00%01616.5300000000000044.00%2500002.4200000001
6Adam CracknellIceHogs (CHI)C/LW/RW11010202340325.00%01616.38000310000000100.00%300001.2200000000
7C.J. SmithIceHogs (CHI)LW110110010101100.00%21717.630000000000000.00%000001.1300000000
8Chris BigrasIceHogs (CHI)D1011400000000.00%12424.970000200003000.00%000000.8000000000
9Jesperi KotkaniemiIceHogs (CHI)C/LW1011020351110.00%01717.6200001000010045.45%2200001.1400000000
10Chris TerryIceHogs (CHI)LW/RW1011000114120.00%01717.150001200000000.00%000001.1700000000
11Nicolas RoyIceHogs (CHI)C/RW1011100303110.00%066.670000000000000.00%000003.0000000000
12Nolan PatrickIceHogs (CHI)C/RW11011000222250.00%02121.8200003000031057.14%2800000.9200000000
13Tobias GeisserIceHogs (CHI)D1011100112100.00%02020.330000100002000.00%000000.9800000000
14Adam TambelliniIceHogs (CHI)C/LW1000100222010.00%11616.8800000000000050.00%400000.0000000000
15Nick RitchieIceHogs (CHI)LW1000120822010.00%02020.3700003000020033.33%600000.0000000000
16Sergei BoikovIceHogs (CHI)D1000100200210.00%22020.330000100002000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne16713202560312636121419.44%829418.370005270000231050.00%9600001.3600000111
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
1Mike CondonIceHogs (CHI)11000.9432.0060002350000.000010000
Stats d'équipe Total ou en Moyenne11000.9432.0060002350000.000010000


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 Cap 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 CracknellIceHogs (CHI)C/LW/RW331985-07-15No209 Lbs6 ft3NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Adam TambelliniIceHogs (CHI)C/LW231994-11-01No191 Lbs6 ft3NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Axel HolmstromIceHogs (CHI)C/LW221996-06-29No198 Lbs6 ft0NoNoNo1Pro & Farm894,167$0$0$NoLien / Lien NHL
C.J. SmithIceHogs (CHI)LW231994-12-01No181 Lbs5 ft11NoNoNo1Pro & Farm874,125$0$0$NoLien / Lien NHL
Chris BigrasIceHogs (CHI)D231995-02-22No191 Lbs6 ft1NoNoNo1Pro & Farm874,125$0$0$NoLien / Lien NHL
Chris TerryIceHogs (CHI)LW/RW291989-04-07No191 Lbs5 ft10NoNoNo2Pro & Farm675,000$0$0$No675,000$Lien / Lien NHL
Curtis McKenzieIceHogs (CHI)LW271991-02-22No205 Lbs6 ft2NoNoNo2Pro & Farm750,000$0$0$No750,000$Lien / Lien NHL
Jakob Forsbacka KarlssonIceHogs (CHI)C/RW211996-10-31No184 Lbs6 ft1NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Jansen HarkinsIceHogs (CHI)C/LW211997-05-23No182 Lbs6 ft1NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien / Lien NHL
Jesperi KotkaniemiIceHogs (CHI)C/LW182000-07-06Yes184 Lbs6 ft2NoNoNo3Pro & Farm3,425,000$0$0$No3,425,000$3,425,000$Lien / Lien NHL
Kristian VesalainenIceHogs (CHI)LW/RW191999-06-01Yes207 Lbs6 ft3NoNoNo4Pro & Farm1,491,667$0$0$No1,460,833$1,460,833$1,460,833$Lien / Lien NHL
Madison BoweyIceHogs (CHI)D231995-04-22No198 Lbs6 ft2NoNoNo2Pro & Farm1,000,000$0$0$No1,000,000$Lien / Lien NHL
Michael AmadioIceHogs (CHI)C/RW221996-05-13No204 Lbs6 ft1NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Michael SgarbossaIceHogs (CHI)C261992-07-25No186 Lbs6 ft0NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Mike CondonIceHogs (CHI)G281990-04-27No195 Lbs6 ft2NoNoNo2Pro & Farm2,400,000$0$0$No2,400,000$Lien / Lien NHL
Nic PetanIceHogs (CHI)C/LW/RW231995-03-22No179 Lbs5 ft9NoNoNo3Pro & Farm874,125$0$0$No775,000$775,000$Lien / Lien NHL
Nick RitchieIceHogs (CHI)LW221995-12-05No234 Lbs6 ft2NoNoNo3Pro & Farm1,640,000$0$0$No1,498,925$1,498,925$Lien / Lien NHL
Nicolas RoyIceHogs (CHI)C/RW211997-02-05No205 Lbs6 ft4NoNoNo2Pro & Farm815,000$0$0$No815,000$Lien / Lien NHL
Nolan PatrickIceHogs (CHI)C/RW201998-09-19No198 Lbs6 ft2NoNoNo2Pro & Farm3,575,000$0$0$No3,575,000$Lien / Lien NHL
Sergei BoikovIceHogs (CHI)D221996-01-24No195 Lbs6 ft2NoNoNo1Pro & Farm681,667$0$0$NoLien / Lien NHL
Tobias GeisserIceHogs (CHI)D191999-02-13Yes201 Lbs6 ft4NoNoNo4Pro & Farm866,667$0$0$No837,778$837,778$837,778$Lien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2123.10196 Lbs6 ft11.901,217,216$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Nick RitchieNolan PatrickJakob Forsbacka Karlsson30122
2Chris TerryJesperi KotkaniemiAdam Cracknell30122
3Curtis McKenzieMichael SgarbossaMichael Amadio25122
4C.J. SmithAdam TambelliniNicolas Roy15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison BoweyChris Bigras30122
2Tobias GeisserSergei Boikov30122
3C.J. SmithAdam Tambellini25122
4Madison BoweyChris Bigras15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Nick RitchieNolan PatrickJakob Forsbacka Karlsson60122
2Chris TerryJesperi KotkaniemiAdam Cracknell40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison BoweyChris Bigras60122
2Tobias GeisserSergei Boikov40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Nick RitchieNolan Patrick60122
2Jesperi KotkaniemiJakob Forsbacka Karlsson40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison BoweyChris Bigras60122
2Tobias GeisserSergei Boikov40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Nick Ritchie60122Madison BoweyChris Bigras60122
2Nolan Patrick40122Tobias GeisserSergei Boikov40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Nick RitchieNolan Patrick60122
2Jesperi KotkaniemiJakob Forsbacka Karlsson40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison BoweyChris Bigras60122
2Tobias GeisserSergei Boikov40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nick RitchieNolan PatrickJakob Forsbacka KarlssonMadison BoweyChris Bigras
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nick RitchieNolan PatrickJakob Forsbacka KarlssonMadison BoweyChris Bigras
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Michael Sgarbossa, Curtis McKenzie, Michael AmadioMichael Sgarbossa, Curtis McKenzieMichael Amadio
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Tobias Geisser, Sergei Boikov, Madison BoweyTobias GeisserSergei Boikov, Madison Bowey
Tirs de Pénalité
Nick Ritchie, Nolan Patrick, Jesperi Kotkaniemi, Jakob Forsbacka Karlsson, Chris Terry
Gardien
#1 : Mike Condon, #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
Total11000000725110000007250000000000021.00071320002320361013130358631300.00%30100.00%0163250.00%224647.83%101855.56%2315228136
2Wolves11000000725110000007250000000000021.00071320002320361013130358631300.00%30100.00%0163250.00%224647.83%101855.56%2315228136
_Since Last GM Reset11000000725110000007250000000000021.00071320002320361013130358631300.00%30100.00%0163250.00%224647.83%101855.56%2315228136
_Vs Conference11000000725110000007250000000000021.00071320002320361013130358631300.00%30100.00%0163250.00%224647.83%101855.56%2315228136
_Vs Division11000000725110000007250000000000021.00071320002320361013130358631300.00%30100.00%0163250.00%224647.83%101855.56%2315228136

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
12W1713203635863100
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
110000072
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
110000072
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
000000000
Derniers 10 Matchs
WLOTWOTL SOWSOL
100000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
300.00%30100.00%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
10131302320
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
163250.00%224647.83%101855.56%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
2315228136


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
2 - 2020-04-066Wolves2IceHogs7WSommaire du Match
4 - 2020-04-0814Wolves-IceHogs-
6 - 2020-04-1022IceHogs-Wolves-
8 - 2020-04-1230IceHogs-Wolves-
10 - 2020-04-1438Wolves-IceHogs-
12 - 2020-04-1646IceHogs-Wolves-
14 - 2020-04-1854Wolves-IceHogs-



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
40 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 2,556,156$ 2,526,163$ 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$ 12 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
282254501218290366-7641181401116172162104173100102118204-86502905108003012576875295099794399441253774281513843325917.77%3327278.31%21564288554.21%1072216849.45%738148849.60%2009140119075981050523
382204901525247348-10141122200313125167-424182701212122181-5940247410657029381706314810051016108068286676172013653625715.75%2968072.97%21726306456.33%1283231255.49%788137457.35%2021143319185871029510
4825218002372661808641279000231398752412590021412793341042664817472111147277629461010952964682432678122018835779716.81%5157286.02%51674316452.91%1475295149.98%637124051.37%2051139318906391035530
58259120334132014717341305021211666610041297012201548173118320587907010133102789332410241156111443215661455520322234921.97%2403187.08%81933304363.52%1501251959.59%767125860.97%2258165616895411009533
6825714030443841901944130601022196901064127802022188100881143846871071011163122929398913631270133351252372758720842193515.98%2454282.86%72164349561.92%1646276759.49%798132660.18%233717341628534999530
782541701253366202164412880004120697109412690121216010555108366659102505152124849394412841257137653235472748118822105325.24%2184479.82%32246351963.82%1614263661.23%884136764.67%233917391629527999534
882512103034474255219412860201426211914341231501020212136761024748611335021871581238432313931441146644254174056918751814725.97%2416075.10%52166332965.06%1613258662.37%968152663.43%241918371565490972531
882512103034474255219412860201426211914341231501020212136761024748611335021871581238432313931441146644254174056918751814725.97%2416075.10%52166332965.06%1613258662.37%968152663.43%241918371565490972531
Total Saison Régulière65636919701514253628211943878328201760851424152890762132816812107911121293103625773828215056787754311548937346028947946994769793412199505729551614380228544419.43%232846180.20%37156392582860.55%118172052557.57%65481110558.96%178561303413793441080684226
Séries
4136700000363427430000021165624000001518-3123668104029179143513915813623671231863081031413.59%841285.71%123149746.48%21245446.70%8620242.57%30519930510817085
51610600000453312853000002417785300000211652045791240124910261120217618845513155149395551018.18%62985.48%039865560.76%34559757.79%12424650.41%451319384123214109
62316700000805921131030000046291710640000034304328014322301262527292931327930136744216176566711115.49%76692.11%049593852.77%44286850.92%18737549.87%593415530171305152
762400000161603120000078-131200000981416294500483123062777714179523216123313.04%16475.00%016126061.92%12120758.45%429046.67%165116135468443
8110000007251100000072500000000000271320002320361013130358631300.00%30100.00%0163250.00%224647.83%101855.56%2315228136
Total Séries5935240000018414440322111000001057233271413000007972770184332516046562516224172670371597183855454914612553814.90%2413187.14%11301238254.62%1142217252.58%44993148.23%154010651378458787397