Condors

GP: 4 | W: 1 | L: 3 | OTL: 0 | P: 2
GF: 8 | GA: 16 | PP%: 18.75% | PK%: 80.00%
DG: Jonathan Legault | Morale : 48 | Moyenne d'Équipe : 61
Prochain matchs #94 vs Gulls
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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
1Mitchell StephensX100.005935936273807461656059586063626351600
2Ryan GroppX100.006436916081928858595654575565636249600
3Alexandre AlainX100.005937885876949357615652555463626351590
4Nicholas Caamano (R)X100.006441775579949354565353565461636451590
5Carter BancksX100.005338855469939153565351524878795549580
6Matthew Phillips (R)X100.005035955957928958655954515661636451580
7Matheson IacopelliX100.006838855582787254535151555269656049570
8Brian Pinho (R)X100.005635945469949353605251544867646151570
9Hudson Elynuik (R)X100.006339775685716254655653575261636651570
10Drake Rymsha (R)X100.005742755572787254625351545261636451560
11Martin MarincinX100.006937896392745962306857674873676251650
12Chris BigrasX100.006138855776908456305951564667647649610
13Mitchell Vande SompelX100.006436776070787359306257615563587351610
14Jake CheliosX100.005936925877897057305553604575684749610
15Trevor CarrickX100.005847746180827260305954584669655751610
16Parker WotherspoonX100.005339835669928955305652534663626349590
Rayé
MOYENNE D'ÉQUIPE100.00603885587586805749575357516664635059
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
1John Muse100.00786664697776787776787779854251730
2Mike Condon100.00746563797373747373747377834451710
Rayé
1Joey Daccord (R)100.00636361806261636261636265695948630
MOYENNE D'ÉQUIPE100.0072656376717072717072717479485069
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
John Stevens78777179787371CAN5252,100,000$


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
1Chris BigrasCondors (Edm)D4314-680216152320.00%99423.55202101400005100.00%000000.8500000100
2Ryan GroppCondors (Edm)LW43033205593733.33%0358.8100000000000050.00%400001.7000000001
3Parker WotherspoonCondors (Edm)D40221801063120.00%75413.580000000000000.00%000000.7400000000
4Jake CheliosCondors (Edm)D4112-36016483512.50%57819.5510121000005010.00%000000.5100000000
5Carter BancksCondors (Edm)RW4011-220637450.00%27017.5400000000000041.67%1200000.2900000000
6Matheson IacopelliCondors (Edm)LW4101-2409511259.09%25614.2200000000000041.51%5300000.3500000000
Stats d'équipe Total ou en Moyenne248513-9300672953152715.09%2538916.2130312250000101142.03%6900000.6700000101
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
Stats d'équipe Total ou en Moyenne0.0000.0000.000


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 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
Alexandre AlainCondors (Edm)C221997-03-03No180 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Brian PinhoCondors (Edm)C241995-05-11Yes173 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Carter BancksCondors (Edm)RW291989-08-09No181 Lbs5 ft11NoNoNo2Sans RestrictionPro & Farm300,000$0$0$NoLien
Chris BigrasCondors (Edm)D241995-02-22No191 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm500,000$0$0$NoLien
Drake RymshaCondors (Edm)C201998-08-18Yes187 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Hudson ElynuikCondors (Edm)C211997-10-12Yes194 Lbs6 ft5NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Jake CheliosCondors (Edm)D281991-03-08No185 Lbs6 ft2NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Joey DaccordCondors (Edm)G221996-08-19Yes197 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
John MuseCondors (Edm)G301988-08-01No185 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm750,000$0$0$NoLien
Martin MarincinCondors (Edm)D271992-02-18No213 Lbs6 ft5NoNoNo2Avec RestrictionPro & Farm500,000$0$0$NoLien
Matheson IacopelliCondors (Edm)LW251994-05-15No207 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Matthew PhillipsCondors (Edm)RW211998-04-06Yes140 Lbs5 ft7NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Mike CondonCondors (Edm)G291990-04-27No195 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm750,000$0$0$NoLien
Mitchell StephensCondors (Edm)C221997-02-05No191 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Mitchell Vande SompelCondors (Edm)D221997-02-11No194 Lbs5 ft10NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Nicholas CaamanoCondors (Edm)RW201998-09-07Yes195 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Parker WotherspoonCondors (Edm)D211997-08-24No171 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Ryan GroppCondors (Edm)LW221996-09-16No187 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Trevor CarrickCondors (Edm)D241994-07-04No196 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1923.84187 Lbs6 ft12.95452,632$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
140122
2Carter BancksMatheson Iacopelli30122
3Ryan Gropp20122
4Carter Bancks10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris Bigras40122
2Jake Chelios30122
3Parker Wotherspoon20122
4Chris Bigras10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
160122
2Carter BancksMatheson Iacopelli40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris Bigras60122
2Jake Chelios40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
2Carter Bancks40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris Bigras60122
2Jake Chelios40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Chris Bigras60122
240122Jake Chelios40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
2Carter Bancks40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris Bigras60122
2Jake Chelios40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris Bigras
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris Bigras
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Ryan Gropp, , Matheson IacopelliRyan Gropp, Matheson Iacopelli
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Parker Wotherspoon, , Parker Wotherspoon,
Tirs de Pénalité
, , , Carter Bancks, Matheson Iacopelli
Gardien
#1 : , #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
1Barracuda2020000029-71010000015-41010000014-300.00023500323039263023098252044700.00%9188.89%02510424.04%3514324.48%155328.30%7248122294419
2Heat11000000431110000004310000000000021.00048120032302326302302958246350.00%4175.00%02510424.04%3514324.48%155328.30%7248122294419
3Roadrunners1010000024-21010000024-20000000000000.0002460032301726302304414420300.00%2150.00%02510424.04%3514324.48%155328.30%7248122294419
Total41300000816-831200000712-51010000014-320.2508152300323079263023017144328816318.75%15380.00%02510424.04%3514324.48%155328.30%7248122294419
_Since Last GM Reset41300000816-831200000712-51010000014-320.2508152300323079263023017144328816318.75%15380.00%02510424.04%3514324.48%155328.30%7248122294419
_Vs Conference11000000431110000004310000000000021.00048120032302326302302958246350.00%4175.00%02510424.04%3514324.48%155328.30%7248122294419

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
42L3815237917144328800
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4130000816
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3120000712
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
101000014
Derniers 10 Matchs
WLOTWOTL SOWSOL
130000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
16318.75%15380.00%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
26302303230
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
2510424.04%3514324.48%155328.30%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
7248122294419


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
3 - 2019-09-048Heat3Condors4WSommaire du Match
4 - 2019-09-0522Barracuda5Condors1LSommaire du Match
8 - 2019-09-0931Condors1Barracuda4LSommaire du Match
11 - 2019-09-1257Roadrunners4Condors2LSommaire du Match
18 - 2019-09-1994Condors-Gulls-
25 - 2019-09-26129Heat-Condors-
29 - 2019-09-30138Condors-Heat-
32 - 2019-10-03166Stars-Condors-
33 - 2019-10-04171Rampage-Condors-
37 - 2019-10-08179Condors-Wild-
39 - 2019-10-10202Condors-Wild-
45 - 2019-10-16233Condors-Gulls-
46 - 2019-10-17248Eagles-Condors-
49 - 2019-10-20256Eagles-Condors-
52 - 2019-10-23275Condors-Reign-
53 - 2019-10-24289Roadrunners-Condors-
58 - 2019-10-29307Reign-Condors-
60 - 2019-10-31331Moose-Condors-
64 - 2019-11-04347Moose-Condors-
67 - 2019-11-07376Barracuda-Condors-
68 - 2019-11-08380Condors-Barracuda-
73 - 2019-11-13400Gulls-Condors-
74 - 2019-11-14413Condors-Heat-
78 - 2019-11-18433Condors-Heat-
80 - 2019-11-20446Condors-Eagles-
81 - 2019-11-21463Condors-Eagles-
86 - 2019-11-26475Condors-Gulls-
88 - 2019-11-28498Gulls-Condors-
90 - 2019-11-30510Condors-Reign-
92 - 2019-12-02517Gulls-Condors-
94 - 2019-12-04528Eagles-Condors-
95 - 2019-12-05544Roadrunners-Condors-
99 - 2019-12-09557Condors-Stars-
101 - 2019-12-11572Condors-Eagles-
102 - 2019-12-12587Condors-Eagles-
106 - 2019-12-16603Heat-Condors-
108 - 2019-12-18615Heat-Condors-
109 - 2019-12-19630Condors-Gulls-
111 - 2019-12-21643Condors-Barracuda-
113 - 2019-12-23652Eagles-Condors-
115 - 2019-12-25666Condors-Roadrunners-
116 - 2019-12-26669Condors-Roadrunners-
122 - 2020-01-01694Wild-Condors-
123 - 2020-01-02708Condors-Reign-
129 - 2020-01-08732Barracuda-Condors-
130 - 2020-01-09747Gulls-Condors-
134 - 2020-01-13768Heat-Condors-
136 - 2020-01-15778Condors-Reign-
137 - 2020-01-16792Reign-Condors-
144 - 2020-01-23838Condors-Roadrunners-
146 - 2020-01-25846Condors-Roadrunners-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29865Wild-Condors-
151 - 2020-01-30881Barracuda-Condors-
155 - 2020-02-03895Condors-Barracuda-
157 - 2020-02-05909Condors-Heat-
158 - 2020-02-06920Condors-Barracuda-
162 - 2020-02-10942Gulls-Condors-
165 - 2020-02-13966Reign-Condors-
171 - 2020-02-19993Condors-Reign-
176 - 2020-02-241025Reign-Condors-
178 - 2020-02-261036Condors-Gulls-
179 - 2020-02-271051Barracuda-Condors-
182 - 2020-03-011061Condors-Moose-
183 - 2020-03-021068Condors-Moose-
186 - 2020-03-051096Condors-Rampage-
190 - 2020-03-091111Roadrunners-Condors-
193 - 2020-03-121140Reign-Condors-
194 - 2020-03-131150Condors-Heat-



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
31 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
146,484$ 86,000$ 11,630$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 5,759$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 181 11,268$ 2,039,508$




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
1441300000816-831200000712-51010000014-328152300323079263023017144328816318.75%15380.00%02510424.04%3514324.48%155328.30%7248122294419
Total Saison Régulière41300000816-831200000712-51010000014-328152300323079263023017144328816318.75%15380.00%02510424.04%3514324.48%155328.30%7248122294419