Moose

GP: 41 | W: 6 | L: 34 | OTL: 1 | P: 13
GF: 91 | GA: 183 | PP%: 14.18% | PK%: 76.74%
DG: Luc Forget | Morale : 28 | Moyenne d'Équipe : 60
Prochain matchs #663 vs IceHogs
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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
1Ryan OlsenX100.005939835875939157595656585769656060600
2Justin KirklandXX100.006238845680949555615652565465636241590
3Trent FredericX100.006245795681786855635456575361637960580
4Patrick BajkovX100.005736915572777154515254535463626360560
5Troy BourkeX100.005336925462787253585451524869656360550
6Dalton ProutX100.007340786286705961306258694977694837640
7Chris ButlerX100.006237896177846859306156654782764544640
8TJ BrennanX100.006840806081928959306353585178706260640
9John RamageX100.005839835772949556305653544675685160620
Rayé
MOYENNE D'ÉQUIPE100.00623984587684795746575458517167595460
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
Rayé
MOYENNE D'ÉQUIPE0.000000000000000000
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Bryan Trottier57476162787363CAN6041,000,000$


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'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
1Dalton ProutMoose (Wpg)D4182432-2913810176718638659.30%9583020.2654954103000076010.00%000000.7700100510
2Chris ButlerMoose (Wpg)D41112132-1256107875110377110.00%7877118.81651158110000081100.00%000010.8300200314
3Justin KirklandMoose (Wpg)LW/RW411552012955048101225314.85%133518.5700000000001062.96%2700001.1400100330
4Filip ChlapikWinnipeg JetsC2303000411931133.33%04723.6410111000150144.68%4700011.2701000100
Stats d'équipe Total ou en Moyenne125375087-402232530820530610020012.09%186200016.001292111321600011632251.35%7400020.87014001254
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
1Matiss KivlenieksWinnipeg Jets42200.8933.5322100131210001.000344100
Stats d'équipe Total ou en Moyenne42200.8933.5322100131210001.000344100


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
Chris ButlerMoose (Wpg)D321986-10-27No196 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Dalton ProutMoose (Wpg)D291990-03-13No215 Lbs6 ft3NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
John RamageMoose (Wpg)D281991-02-07No190 Lbs6 ft0NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Justin KirklandMoose (Wpg)LW/RW221996-08-02No183 Lbs6 ft3NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Patrick BajkovMoose (Wpg)RW211997-11-27No186 Lbs6 ft0NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Ryan OlsenMoose (Wpg)C251994-03-25No187 Lbs6 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
TJ BrennanMoose (Wpg)D301989-04-03No216 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$NoLien
Trent FredericMoose (Wpg)C211998-02-11No203 Lbs6 ft2NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Troy BourkeMoose (Wpg)LW251994-03-30No156 Lbs5 ft10NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
925.89192 Lbs6 ft12.67433,333$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
140122
230122
3Justin Kirkland20122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dalton Prout40122
2Chris Butler30122
320122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
160122
240122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dalton Prout60122
2Chris Butler40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dalton Prout60122
2Chris Butler40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Dalton Prout60122
240122Chris Butler40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dalton Prout60122
2Chris Butler40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Dalton Prout
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Dalton Prout
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
1Admirals40400000324-2120200000112-1120200000212-1000.00036900363320265341348352101515234641715.88%18761.11%0320101531.53%382127629.94%19663830.72%7635241246295463202
2Condors20200000412-80000000000020200000412-800.00047110036332024634134835210791822276116.67%10280.00%0320101531.53%382127629.94%19663830.72%7635241246295463202
3Eagles2110000011832110000011830000000000020.5001121320036332021103413483521058121039700.00%5180.00%0320101531.53%382127629.94%19663830.72%7635241246295463202
4Griffins624000001920-1413000001113-22110000087140.3331933520036332021723413483521018852501031815.56%24866.67%0320101531.53%382127629.94%19663830.72%7635241246295463202
5Gulls2020000059-4000000000002020000059-400.000581300363320283341348352108723144610110.00%7271.43%0320101531.53%382127629.94%19663830.72%7635241246295463202
6Heat20200000412-80000000000020200000412-800.000461000363320256341348352101142422544125.00%90100.00%0320101531.53%382127629.94%19663830.72%7635241246295463202
7IceHogs1010000023-1000000000001010000023-100.00024600363320234341348352103781725200.00%50100.00%0320101531.53%382127629.94%19663830.72%7635241246295463202
8Marlies2110000058-32110000058-30000000000020.500510150036332028634134835210903127514250.00%11190.91%0320101531.53%382127629.94%19663830.72%7635241246295463202
9Rampage605000011126-1540400000717-102010000149-510.08311223300363320211834134835210234714610820525.00%23578.26%0320101531.53%382127629.94%19663830.72%7635241246295463202
10Rocket20200000310-720200000310-70000000000000.0003690036332023934134835210722418321119.09%8187.50%0320101531.53%382127629.94%19663830.72%7635241246295463202
11Senators20101000550201010005500000000000020.500581300363320238341348352107812212610330.00%8275.00%0320101531.53%382127629.94%19663830.72%7635241246295463202
12Stars30300000314-110000000000030300000314-1100.00035800363320270341348352101003320431300.00%10280.00%0320101531.53%382127629.94%19663830.72%7635241246295463202
Total414340101191183-9222318010005090-4019116000114193-52130.1599116125210363320210453413483521015314293837241412014.18%1724076.74%0320101531.53%382127629.94%19663830.72%7635241246295463202
14Wild40300010719-122020000029-720100010510-520.2507815003633202703413483521013348496310110.00%20955.00%0320101531.53%382127629.94%19663830.72%7635241246295463202
15Wolves30300000913-42020000058-31010000045-100.0009172610363320258341348352101102133439333.33%140100.00%0320101531.53%382127629.94%19663830.72%7635241246295463202
_Since Last GM Reset414340101191183-9222318010005090-4019116000114193-52130.1599116125210363320210453413483521015314293837241412014.18%1724076.74%0320101531.53%382127629.94%19663830.72%7635241246295463202
_Vs Conference403010001014-4201010005502020000059-420.2501016260036332021213413483521016535357220420.00%15473.33%0320101531.53%382127629.94%19663830.72%7635241246295463202

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4113W1911612521045153142938372410
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
41434101191183
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2231810005090
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
1911600114193
Derniers 10 Matchs
WLOTWOTL SOWSOL
190000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1412014.18%1724076.74%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
341348352103633202
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
320101531.53%382127629.94%19663830.72%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
7635241246295463202


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 - 2019-09-046Moose5Wild4WXXSommaire du Match
5 - 2019-09-0625Moose0Wild6LSommaire du Match
10 - 2019-09-1138Senators2Moose1LSommaire du Match
11 - 2019-09-1249Senators3Moose4WXSommaire du Match
17 - 2019-09-1877Rampage7Moose3LSommaire du Match
19 - 2019-09-2097Rampage3Moose1LSommaire du Match
25 - 2019-09-26122Moose2Admirals8LSommaire du Match
26 - 2019-09-27135Moose2IceHogs3LSommaire du Match
28 - 2019-09-29136Moose0Admirals4LSommaire du Match
31 - 2019-10-02148Wolves2Moose1LSommaire du Match
32 - 2019-10-03158Wolves6Moose4LSommaire du Match
37 - 2019-10-08180Griffins3Moose2LSommaire du Match
39 - 2019-10-10197Griffins5Moose3LSommaire du Match
42 - 2019-10-13211Moose3Rampage4LXXSommaire du Match
43 - 2019-10-14220Moose1Stars4LSommaire du Match
46 - 2019-10-17241Moose3Griffins4LSommaire du Match
47 - 2019-10-18251Moose4Wolves5LSommaire du Match
52 - 2019-10-23271Wild5Moose1LSommaire du Match
53 - 2019-10-24277Wild4Moose1LSommaire du Match
57 - 2019-10-28306Moose1Gulls3LSommaire du Match
59 - 2019-10-30316Moose4Gulls6LSommaire du Match
60 - 2019-10-31331Moose2Condors5LSommaire du Match
64 - 2019-11-04347Moose2Condors7LSommaire du Match
66 - 2019-11-06361Moose2Heat6LSommaire du Match
67 - 2019-11-07373Moose2Heat6LSommaire du Match
73 - 2019-11-13397Marlies3Moose4WSommaire du Match
74 - 2019-11-14405Marlies5Moose1LSommaire du Match
80 - 2019-11-20442Griffins4Moose3LSommaire du Match
81 - 2019-11-21451Griffins1Moose3WSommaire du Match
89 - 2019-11-29500Eagles3Moose7WSommaire du Match
90 - 2019-11-30506Eagles5Moose4LSommaire du Match
92 - 2019-12-02515Moose1Rampage5LSommaire du Match
94 - 2019-12-04526Moose1Stars5LSommaire du Match
95 - 2019-12-05541Moose1Stars5LSommaire du Match
100 - 2019-12-10560Rocket6Moose3LSommaire du Match
102 - 2019-12-12578Rocket4Moose0LSommaire du Match
104 - 2019-12-14592Admirals6Moose0LSommaire du Match
106 - 2019-12-16600Admirals6Moose1LSommaire du Match
109 - 2019-12-19617Rampage5Moose2LSommaire du Match
110 - 2019-12-20633Rampage2Moose1LSommaire du Match
113 - 2019-12-23648Moose5Griffins3WSommaire du Match
115 - 2019-12-25663Moose-IceHogs-
116 - 2019-12-26668Moose-Admirals-
122 - 2020-01-01690Moose-Admirals-
123 - 2020-01-02707Moose-Wolves-
127 - 2020-01-06717Moose-Griffins-
130 - 2020-01-09742Stars-Moose-
131 - 2020-01-10750Stars-Moose-
134 - 2020-01-13766Wolves-Moose-
136 - 2020-01-15776Wolves-Moose-
138 - 2020-01-17795Admirals-Moose-
139 - 2020-01-18806Admirals-Moose-
141 - 2020-01-20808Moose-Marlies-
143 - 2020-01-22825Moose-Rocket-
144 - 2020-01-23828Moose-Rocket-
148 - 2020-01-27850Moose-Marlies-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29860Moose-Senators-
151 - 2020-01-30872Moose-Senators-
158 - 2020-02-06911IceHogs-Moose-
159 - 2020-02-07924IceHogs-Moose-
162 - 2020-02-10940Stars-Moose-
164 - 2020-02-12951Stars-Moose-
166 - 2020-02-14967Gulls-Moose-
168 - 2020-02-16975Gulls-Moose-
171 - 2020-02-19991Moose-Eagles-
172 - 2020-02-201005Moose-Eagles-
176 - 2020-02-241024Moose-Stars-
178 - 2020-02-261035Moose-Rampage-
179 - 2020-02-271050Moose-Rampage-
182 - 2020-03-011061Condors-Moose-
183 - 2020-03-021068Condors-Moose-
186 - 2020-03-051084Heat-Moose-
187 - 2020-03-061099Heat-Moose-
192 - 2020-03-111118Moose-Griffins-
193 - 2020-03-121137Moose-Wolves-
194 - 2020-03-131148Moose-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
16 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
613,054$ 39,000$ 5,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 25,385$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 80 5,356$ 428,480$




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
14414340101191183-9222318010005090-4019116000114193-52139116125210363320210453413483521015314293837241412014.18%1724076.74%0320101531.53%382127629.94%19663830.72%7635241246295463202
Total Saison Régulière414340101191183-9222318010005090-4019116000114193-52139116125210363320210453413483521015314293837241412014.18%1724076.74%0320101531.53%382127629.94%19663830.72%7635241246295463202