Admirals

GP: 32 | W: 9 | L: 23 | OTL: 0 | P: 18
GF: 141 | GA: 187 | PP%: 40.74% | PK%: 44.36%
DG: Rock Toussaint | Morale : 42 | Moyenne d'Équipe : 66
Prochain matchs #393 vs Penguins
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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
1Jason DickinsonX100.008143846580748064767062786367667754700
2Curtis LazarX100.005737895975766958625758575667648158650
3Nick PaulX100.007337896292746961656060636167646650640
4Hudson FaschingX100.006936925984928958635655625866645658630
5Dillon HeatheringtonX100.006637885991817258305953575267646950640
6Joe MorrowX100.006950806174765459307054564873676958640
7Chris BigrasX100.006138855776908456305951564667647658630
Rayé
MOYENNE D'ÉQUIPE100.00684087608280745951625661556865715565
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
1Mackenzie Blackwood100.00838482818281838281838265697658780
Rayé
MOYENNE D'ÉQUIPE100.0083848281828183828183826569765878
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Lindy Ruff75707166898357CAN592500,000$


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
1Dillon HeatheringtonAdmirals (NHS)D3212122-108019910738580.93%2249215.380002200001000.00%0217000.8900000252
2Nick PaulAdmirals (NHS)LW3241721-12401816160511072.50%1543613.6300022000000078.79%331716000.9600000233
Stats d'équipe Total ou en Moyenne6453843-221203725267891651.87%3792814.5000044000010078.79%331933000.9300000485
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
Chris BigrasAdmirals (NHS)D221995-02-22No191 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm750,000$0$0$NoLien
Curtis LazarAdmirals (NHS)C221995-02-02No205 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Dillon HeatheringtonAdmirals (NHS)D221995-05-09No225 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Hudson FaschingAdmirals (NHS)RW221995-07-28No204 Lbs6 ft3NoNoNo2Contrat d'EntréePro & Farm750,000$0$0$NoLien
Jason DickinsonAdmirals (NHS)C221995-07-04No200 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm1,500,000$0$0$NoLien
Joe MorrowAdmirals (NHS)D241992-12-09No196 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Mackenzie BlackwoodAdmirals (NHS)G201996-12-09No225 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Nick PaulAdmirals (NHS)LW221995-03-20No230 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
822.00210 Lbs6 ft21.38843,750$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
140122
2Nick Paul30122
320122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
2Dillon Heatherington30122
320122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
160122
2Nick Paul40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Dillon Heatherington40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Dillon Heatherington40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
16012260122
240122Dillon Heatherington40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Dillon Heatherington40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nick Paul, , Nick Paul,
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dillon Heatherington, , Dillon Heatherington,
Tirs de Pénalité
, , , , Nick Paul
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
1Barracuda1010000035-2000000000001010000035-200.0003470023595902626332729901986172150.00%3166.67%119652937.05%19052036.54%27669439.77%675402710293534251
2Bears220000001284110000005411100000074341.0001222340023595904726332729904413121910440.00%6183.33%019652937.05%19052036.54%27669439.77%675402710293534251
3Bruins220000001971211000000133101100000064241.0001938570023595907526332729904314162614964.29%8187.50%119652937.05%19052036.54%27669439.77%675402710293534251
4Gulls11000000514000000000001100000051421.00059140023595903026332729901942136350.00%110.00%019652937.05%19052036.54%27669439.77%675402710293534251
5Heat20200000510-520200000510-50000000000000.000510151023595905926332729904725123110110.00%6433.33%019652937.05%19052036.54%27669439.77%675402710293534251
6Icedogs514000002328-5211000001091303000001319-620.2002340630023595901362633272990114353477181055.56%17852.94%119652937.05%19052036.54%27669439.77%675402710293534251
7Marlies10100000110-90000000000010100000110-900.00012300235959027263327299033112210000.00%11827.27%019652937.05%19052036.54%27669439.77%675402710293534251
8Moose2020000039-61010000027-51010000012-100.00036900235959059263327299068161632200.00%8537.50%019652937.05%19052036.54%27669439.77%675402710293534251
9Phantoms10100000410-610100000410-60000000000000.0004812002359590322633272990291112173133.33%660.00%019652937.05%19052036.54%27669439.77%675402710293534251
10Rampages505000001235-2330300000521-1620200000714-700.000122436002359590143263327299016861426327518.52%211623.81%019652937.05%19052036.54%27669439.77%675402710293534251
11Reigh20200000915-61010000046-21010000059-400.00091827002359590472633272990963518307457.14%9722.22%019652937.05%19052036.54%27669439.77%675402710293534251
12Rocket1010000036-31010000036-30000000000000.0003470023595902126332729903419610200.00%3166.67%119652937.05%19052036.54%27669439.77%675402710293534251
13Stars413000002329-620200000914-5211000001415-120.250234265002359590112263327299018660404820945.00%20860.00%219652937.05%19052036.54%27669439.77%675402710293534251
14Thunderbird11000000541000000000001100000054121.000510150023595903026332729901878106350.00%4250.00%119652937.05%19052036.54%27669439.77%675402710293534251
Total3292300000141187-4616412000007094-2416511000007193-22180.28114126440510235959088926332729909713342664331355540.74%1337444.36%719652937.05%19052036.54%27669439.77%675402710293534251
16Wolves21100000141041100000010461010000046-220.500142741002359590452633272990531520308562.50%10550.00%019652937.05%19052036.54%27669439.77%675402710293534251
_Since Last GM Reset3292300000141187-4616412000007094-2416511000007193-22180.28114126440510235959088926332729909713342664331355540.74%1337444.36%719652937.05%19052036.54%27669439.77%675402710293534251
_Vs Conference244200000097142-4512210000004571-2612210000005271-1980.1679718027710235959065726332729907702591903411003838.00%955542.11%419652937.05%19052036.54%27669439.77%675402710293534251
_Vs Division183150000075111-36927000003655-19918000003956-1760.167751392140023595904952633272990589187152250752938.67%764244.74%319652937.05%19052036.54%27669439.77%675402710293534251

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
3218W214126440588997133426643310
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
329230000141187
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
1641200007094
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
1651100007193
Derniers 10 Matchs
WLOTWOTL SOWSOL
280000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1355540.74%1337444.36%7
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
26332729902359590
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
19652937.05%19052036.54%27669439.77%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
675402710293534251


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
1 - 2019-10-041Icedogs5Admirals9WSommaire du Match
3 - 2019-10-0614Admirals5Icedogs6LSommaire du Match
5 - 2019-10-0825Admirals5Stars8LSommaire du Match
7 - 2019-10-1037Icedogs4Admirals1LSommaire du Match
11 - 2019-10-1455Rampages11Admirals1LSommaire du Match
13 - 2019-10-1664Admirals4Wolves6LSommaire du Match
14 - 2019-10-1774Admirals1Moose2LSommaire du Match
16 - 2019-10-1987Moose7Admirals2LSommaire du Match
19 - 2019-10-22103Wolves4Admirals10WSommaire du Match
20 - 2019-10-23111Admirals2Rampages3LSommaire du Match
23 - 2019-10-26128Rampages4Admirals2LSommaire du Match
24 - 2019-10-27134Admirals5Thunderbird4WSommaire du Match
27 - 2019-10-30151Admirals9Stars7WSommaire du Match
29 - 2019-11-01160Stars6Admirals3LSommaire du Match
32 - 2019-11-04176Heat4Admirals2LSommaire du Match
35 - 2019-11-07188Admirals3Icedogs5LSommaire du Match
37 - 2019-11-09200Reigh6Admirals4LSommaire du Match
39 - 2019-11-11210Admirals5Rampages11LSommaire du Match
41 - 2019-11-13223Bears4Admirals5WSommaire du Match
43 - 2019-11-15232Admirals5Gulls1WSommaire du Match
46 - 2019-11-18245Admirals5Reigh9LSommaire du Match
48 - 2019-11-20255Admirals7Bears4WSommaire du Match
49 - 2019-11-21262Rampages6Admirals2LSommaire du Match
52 - 2019-11-24277Heat6Admirals3LSommaire du Match
55 - 2019-11-27294Admirals1Marlies10LSommaire du Match
56 - 2019-11-28304Stars8Admirals6LSommaire du Match
59 - 2019-12-01318Phantoms10Admirals4LSommaire du Match
61 - 2019-12-03331Admirals5Icedogs8LSommaire du Match
64 - 2019-12-06342Admirals3Barracuda5LSommaire du Match
65 - 2019-12-07354Rocket6Admirals3LSommaire du Match
68 - 2019-12-10368Bruins3Admirals13WSommaire du Match
70 - 2019-12-12377Admirals6Bruins4WSommaire du Match
74 - 2019-12-16393Penguins-Admirals-
76 - 2019-12-18406Admirals-Sound Tigers-
78 - 2019-12-20414Admirals-Crunch-
79 - 2019-12-21422Marlies-Admirals-
81 - 2019-12-23439Admirals-Rampages-
83 - 2019-12-25449Stars-Admirals-
86 - 2019-12-28466Sound Tigers-Admirals-
87 - 2019-12-29472Admirals-Senateurs-
90 - 2020-01-01488Admirals-Penguins-
93 - 2020-01-04497Devils-Admirals-
95 - 2020-01-06511Monsters-Admirals-
97 - 2020-01-08519Admirals-Reigh-
100 - 2020-01-11534Admirals-Stars-
102 - 2020-01-13543Icedogs-Admirals-
104 - 2020-01-15555Admirals-Rocket-
106 - 2020-01-17566Moose-Admirals-
107 - 2020-01-18575Admirals-Phantoms-
110 - 2020-01-21588Thunderbird-Admirals-
112 - 2020-01-23598Admirals-Monsters-
115 - 2020-01-26612Admirals-Gulls-
117 - 2020-01-28619Barracuda-Admirals-
119 - 2020-01-30628Admirals-Blacknight-
121 - 2020-02-01641Barracuda-Admirals-
123 - 2020-02-03654Admirals-Blacknight-
125 - 2020-02-05667Thunderbird-Admirals-
127 - 2020-02-07680Admirals-Moose-
128 - 2020-02-08686Admirals-Condors-
130 - 2020-02-10694Crunch-Admirals-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
133 - 2020-02-13709Admirals-Devils-
134 - 2020-02-14718Condors-Admirals-
137 - 2020-02-17732Admirals-Icedogs-
138 - 2020-02-18741Senateurs-Admirals-
143 - 2020-02-23755Admirals-Moose-
144 - 2020-02-24766Blacknight-Admirals-
147 - 2020-02-27781Admirals-Condors-
148 - 2020-02-28788Moose-Admirals-
153 - 2020-03-04809Condors-Admirals-
157 - 2020-03-08830Reigh-Admirals-
161 - 2020-03-12848Admirals-Barracuda-
163 - 2020-03-14856Gulls-Admirals-
167 - 2020-03-18875Wolves-Admirals-
168 - 2020-03-19882Admirals-Heat-
171 - 2020-03-22898Blacknight-Admirals-
173 - 2020-03-24909Admirals-Thunderbird-
175 - 2020-03-26921Wolves-Admirals-
176 - 2020-03-27929Admirals-Heat-
177 - 2020-03-28933Admirals-Wolves-
181 - 2020-04-01949Icedogs-Admirals-
187 - 2020-04-07970Gulls-Admirals-
189 - 2020-04-09979Admirals-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
25 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
499,229$ 675,000$ 675,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 313,351$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 120 6,152$ 738,240$




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
33292300000141187-4616412000007094-2416511000007193-221814126440510235959088926332729909713342664331355540.74%1337444.36%719652937.05%19052036.54%27669439.77%675402710293534251
Total Saison Régulière3292300000141187-4616412000007094-2416511000007193-221814126440510235959088926332729909713342664331355540.74%1337444.36%719652937.05%19052036.54%27669439.77%675402710293534251
Séries
21046000005774-17514000002945-16532000002829-18571021590092521241311313116543511398091462452.17%402635.00%06519633.16%5417131.58%5422723.79%2121372289416168
Total Séries1046000005774-17514000002945-16532000002829-18571021590092521241311313116543511398091462452.17%402635.00%06519633.16%5417131.58%5422723.79%2121372289416168