Moose

GP: 4 | W: 0 | L: 4 | OTL: 0 | P: 0
GF: 6 | GA: 22 | PP%: 5.00% | PK%: 70.00%
DG: Luc Forget | Morale : 46 | Moyenne d'Équipe : N/A
Prochain matchs #77 vs Rampage
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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
1Antoine LaganiereX100.0056555555585959555055555555707215100
2Filip Chlapik (R)X100.0068555575665757677163626255727415100
3Vinni Lettieri (R)XX100.0076558170656674656164616155505015100
4Corban KnightX100.0080556762777069605059606055757115100
5Garrett MitchellX100.0056555861726469555055555655745015100
6Graham BlackX100.0065556761726365555055555655695015100
7Justin Kirkland (R)X100.0065556764706469555055555555505014700
8Nathan Walker (R)X100.0056555955546068555055555555505015100
9Troy BourkeX100.0060556667636074555055555655505015100
10Ryan OlsenX100.0060556961686669559955555955737415100
11Josh GorgesX100.0083557974897682652562607555918615100
12Dalton ProutX100.0065556077937471642560606355787315100
13Jarred TinordiX100.0055555560555558552555555555535315100
14Chris ButlerX100.0055555660565676562556565655707115100
15Morgan Ellis (A)X100.0058555560555568552555555555535315100
16John RamageX100.0056555660565669562556565655535315100
17T.J. BrennanX100.0060556564796579602560605855535314700
18Mac BennettX100.0056555560555558552555555555535315100
19Yannick WeberX100.0079558283807158732563637455817915100
Rayé
1Jeff HogganX100.0056555555555756555055555555575713300
2Trent Frederic (R)X100.0056555555555555555055555555505014600
3Travis MorinX100.0056555555555555555055555555505014600
MOYENNE D'ÉQUIPE100.006355626366626658435757595563601490
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
1Matej Machovsky (R)100.005747597460576064606055505514800
2Matiss Kivlenieks (R)100.005374937247555058494955505514800
Rayé
MOYENNE D'ÉQUIPE100.00556176735456556155555550551480
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Bryan Trottier57476162787363CAN5951,000,000$


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
1Justin KirklandMoose (Wpg)LW4213-2601114130815.38%15112.97000220000000100.00%300001.1600000000
2T.J. BrennanMoose (Wpg)D402201401552020.00%85513.820001300000000.00%000000.7200000000
Stats d'équipe Total ou en Moyenne8235-220026191501013.33%910713.39000350000000100.00%300000.9300000000
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 Salaire Année 2 Salaire Année 3 Salaire Année 4 Salaire Année 5 Salaire Année 6 Salaire Année 7 Salaire Année 8 Salaire Année 9 Salaire Année 10 Link
Antoine LaganiereMoose (Wpg)C261990-07-04No196 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Chris ButlerMoose (Wpg)D301986-10-27No196 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Corban KnightMoose (Wpg)C261990-09-10No195 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Dalton ProutMoose (Wpg)D261990-03-13No222 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm500,000$0$0$No500,000$500,000$500,000$
Filip ChlapikMoose (Wpg)C191997-06-03Yes196 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$500,000$
Garrett MitchellMoose (Wpg)RW251991-02-09No183 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm900,000$0$0$No
Graham BlackMoose (Wpg)C241993-01-13No180 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Jarred TinordiMoose (Wpg)D241992-02-20No225 Lbs6 ft6NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Jeff HogganMoose (Wpg)LW381978-02-01No193 Lbs5 ft11NoNoYes1Sans RestrictionPro & Farm500,000$0$0$No
John RamageMoose (Wpg)D251991-02-07No200 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Josh GorgesMoose (Wpg)D321984-08-14No201 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Justin KirklandMoose (Wpg)LW201996-08-02Yes183 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Mac BennettMoose (Wpg)D251991-03-25No182 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Matej MachovskyMoose (Wpg)G231993-07-25Yes187 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Matiss KivlenieksMoose (Wpg)G201996-08-26Yes183 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Morgan EllisMoose (Wpg)D241992-04-29No204 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Nathan WalkerMoose (Wpg)LW221994-02-06Yes186 Lbs5 ft8NoNoNo1Contrat d'EntréePro & Farm500,000$0$0$No
Ryan OlsenMoose (Wpg)C221994-03-24No187 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm300,000$0$0$No
T.J. BrennanMoose (Wpg)D271989-04-02No216 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm900,000$0$0$No
Travis MorinMoose (Wpg)C331984-01-08No190 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Trent FredericMoose (Wpg)C181998-02-11Yes216 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$500,000$
Troy BourkeMoose (Wpg)LW221994-03-29No170 Lbs5 ft10NoNoNo1Contrat d'EntréePro & Farm300,000$0$0$No
Vinni LettieriMoose (Wpg)C/RW211995-02-06Yes181 Lbs5 ft10NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Yannick WeberMoose (Wpg)D281988-09-22No200 Lbs5 ft11NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2425.00195 Lbs6 ft12.29441,667$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
140122
2Justin Kirkland30122
320122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
2T.J. Brennan30122
320122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
160122
2Justin Kirkland40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2T.J. Brennan40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2T.J. Brennan40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
16012260122
240122T.J. Brennan40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2T.J. Brennan40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Tirs de Pénalité
, , , ,
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
1Senators2020000038-52020000038-50000000000000.000358002310422923280711616311317.69%8187.50%0178719.54%3112524.80%95715.79%5535141294215
Total40400000622-162020000038-520200000314-1100.000610160023108029232801554644592015.00%20670.00%0178719.54%3112524.80%95715.79%5535141294215
3Wild20200000314-110000000000020200000314-1100.00035800231038292328084302828700.00%12558.33%0178719.54%3112524.80%95715.79%5535141294215
_Since Last GM Reset40400000622-162020000038-520200000314-1100.000610160023108029232801554644592015.00%20670.00%0178719.54%3112524.80%95715.79%5535141294215
_Vs Conference2020000038-52020000038-50000000000000.000358002310422923280711616311317.69%8187.50%0178719.54%3112524.80%95715.79%5535141294215

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
40L4610168015546445900
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4040000622
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
202000038
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2020000314
Derniers 10 Matchs
WLOTWOTL SOWSOL
040000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2015.00%20670.00%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
29232802310
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
178719.54%3112524.80%95715.79%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
5535141294215


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 - 2018-09-076Moose2Wild7LSommaire du Match
5 - 2018-09-0925Moose1Wild7LSommaire du Match
10 - 2018-09-1438Senators4Moose2LSommaire du Match
11 - 2018-09-1549Senators4Moose1LSommaire du Match
17 - 2018-09-2177Rampage-Moose-
19 - 2018-09-2397Rampage-Moose-
25 - 2018-09-29122Moose-Admirals-
26 - 2018-09-30135Moose-IceHogs-
28 - 2018-10-02136Moose-Admirals-
31 - 2018-10-05148Wolves-Moose-
32 - 2018-10-06158Wolves-Moose-
37 - 2018-10-11180Griffins-Moose-
39 - 2018-10-13197Griffins-Moose-
42 - 2018-10-16211Moose-Rampage-
43 - 2018-10-17220Moose-Stars-
46 - 2018-10-20241Moose-Griffins-
47 - 2018-10-21251Moose-Wolves-
52 - 2018-10-26271Wild-Moose-
53 - 2018-10-27277Wild-Moose-
57 - 2018-10-31306Moose-Gulls-
59 - 2018-11-02316Moose-Gulls-
60 - 2018-11-03331Moose-Condors-
64 - 2018-11-07347Moose-Condors-
66 - 2018-11-09361Moose-Heat-
67 - 2018-11-10373Moose-Heat-
73 - 2018-11-16397Marlies-Moose-
74 - 2018-11-17405Marlies-Moose-
80 - 2018-11-23442Griffins-Moose-
81 - 2018-11-24451Griffins-Moose-
89 - 2018-12-02500Eagles-Moose-
90 - 2018-12-03506Eagles-Moose-
92 - 2018-12-05515Moose-Rampage-
94 - 2018-12-07526Moose-Stars-
95 - 2018-12-08541Moose-Stars-
100 - 2018-12-13560Rocket-Moose-
102 - 2018-12-15578Rocket-Moose-
104 - 2018-12-17592Admirals-Moose-
106 - 2018-12-19600Admirals-Moose-
109 - 2018-12-22617Rampage-Moose-
110 - 2018-12-23633Rampage-Moose-
113 - 2018-12-26648Moose-Griffins-
115 - 2018-12-28663Moose-IceHogs-
116 - 2018-12-29668Moose-Admirals-
122 - 2019-01-04690Moose-Admirals-
123 - 2019-01-05707Moose-Wolves-
127 - 2019-01-09717Moose-Griffins-
130 - 2019-01-12742Stars-Moose-
131 - 2019-01-13750Stars-Moose-
134 - 2019-01-16766Wolves-Moose-
136 - 2019-01-18776Wolves-Moose-
138 - 2019-01-20795Admirals-Moose-
139 - 2019-01-21806Admirals-Moose-
141 - 2019-01-23808Moose-Marlies-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25825Moose-Rocket-
144 - 2019-01-26828Moose-Rocket-
148 - 2019-01-30850Moose-Marlies-
150 - 2019-02-01860Moose-Senators-
151 - 2019-02-02872Moose-Senators-
158 - 2019-02-09911IceHogs-Moose-
159 - 2019-02-10924IceHogs-Moose-
162 - 2019-02-13940Stars-Moose-
164 - 2019-02-15951Stars-Moose-
166 - 2019-02-17967Gulls-Moose-
168 - 2019-02-19975Gulls-Moose-
171 - 2019-02-22991Moose-Eagles-
172 - 2019-02-231005Moose-Eagles-
176 - 2019-02-271024Moose-Stars-
178 - 2019-03-011035Moose-Rampage-
179 - 2019-03-021050Moose-Rampage-
182 - 2019-03-051061Condors-Moose-
183 - 2019-03-061068Condors-Moose-
186 - 2019-03-091084Heat-Moose-
187 - 2019-03-101099Heat-Moose-
192 - 2019-03-151118Moose-Griffins-
193 - 2019-03-161137Moose-Wolves-
194 - 2019-03-171148Moose-Wolves-



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
36 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
74,087$ 106,000$ 75,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 7,073$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 181 5,701$ 1,031,881$




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
1340400000622-162020000038-520200000314-110610160023108029232801554644592015.00%20670.00%0178719.54%3112524.80%95715.79%5535141294215
Total Saison Régulière40400000622-162020000038-520200000314-110610160023108029232801554644592015.00%20670.00%0178719.54%3112524.80%95715.79%5535141294215