PV Sharapovas

GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: Justin Guitard | Morale : 99 | Moyenne d'Équipe : 67
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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 SPÂgeContratSalaire
1Marcus Sorensen0X100.0072428468677987675364667269756854997102841,600,000$
2Tomas Nosek0XXX100.0079398665817283647661637465756936997102841,250,000$
3Charles Hudon0X100.007145866668817964536265696771725899700261850,000$
4Kenny Agostino0XX100.007246856475807863596562666375685799690285750,000$
5Michael Chaput0X100.006545886380757362766061656275735299680283800,000$
6Justin Kirkland0XX100.006254846180879160565954586167646699670245850,000$
7Ryan MacInnis0XXX100.006446896186757362686159636167647299670243850,000$
8Trevor Moore0X100.006339876667757265716264636669654299670256900,000$
9Miikka Salomaki0XX100.006443886173787562555959636073686199660272950,000$
10T.J. Tynan0XXX100.005639846462777563766558616475685499660285750,000$
11Keegan Kolesar0X100.006749886186777360575958625865636698660235900,000$
12Nate Schnarr (R)0X100.006249845879807657635853565961636698640213750,000$
13Victor Mete0X100.0054388968678284673071596850636568996902241,000,000$
14Christian Folin0X100.007846856087756958305957645377695199670295800,000$
15Yannick Weber0X100.007139856472737862306356615280734199670313750,000$
16Jeremy Lauzon0X100.006349796178807659305856645365627299650234850,000$
17Guillaume Brisebois0X100.005943895975777258305756605265636699640235900,000$
Rayé
1Chase Pearson (R)0X100.006243885778818255505356585765635698640233750,000$
MOYENNE D'ÉQUIPE100.00664486637678786254615964607067589967
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
1Christopher Gibson100.00756765827473757473757475816099680
2Garret Sparks100.00757371847473757473757473775899680
Rayé
1J-F Berube100.00718987737069717069717077835197670
MOYENNE D'ÉQUIPE100.0074767480737274737274737580569868
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Steve Yzerman62626262696960CAN562300,000$


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
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


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 Salaire RestantSalaire MoyenSalaire Moyen RestantCap 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
Charles HudonPV Sharapovas (DET)LW266/23/1994No86 Kg178 CMNoNoNo1Pro & Farm850,000$850,000$850,000$850,000$0$0$NoLien
Chase PearsonPV Sharapovas (DET)C238/23/1997Yes86 Kg188 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Christian FolinPV Sharapovas (DET)D292/9/1991No93 Kg193 CMNoNoNo5Pro & Farm800,000$800,000$800,000$800,000$0$0$No800,000$800,000$800,000$800,000$Lien
Christopher GibsonPV Sharapovas (DET)G2712/27/1992No94 Kg188 CMNoNoNo6Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$750,000$750,000$750,000$Lien
Garret SparksPV Sharapovas (DET)G276/28/1993No91 Kg191 CMNoNoNo5Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$750,000$750,000$Lien
Guillaume BriseboisPV Sharapovas (DET)D237/21/1997No80 Kg188 CMNoNoNo5Pro & Farm900,000$900,000$900,000$900,000$0$0$No900,000$900,000$900,000$900,000$Lien
J-F BerubePV Sharapovas (DET)G297/13/1991No80 Kg185 CMNoNoNo6Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$750,000$750,000$750,000$Lien
Jeremy LauzonPV Sharapovas (DET)D234/28/1997No93 Kg185 CMNoNoNo4Pro & Farm850,000$850,000$850,000$850,000$0$0$No850,000$850,000$850,000$Lien
Justin KirklandPV Sharapovas (DET)C/LW248/2/1996No83 Kg191 CMNoNoNo5Pro & Farm850,000$850,000$850,000$850,000$0$0$No850,000$850,000$850,000$850,000$Lien
Keegan KolesarPV Sharapovas (DET)RW234/8/1997No103 Kg188 CMNoNoNo5Pro & Farm900,000$900,000$900,000$900,000$0$0$No900,000$900,000$900,000$900,000$Lien
Kenny AgostinoPV Sharapovas (DET)LW/RW284/30/1992No93 Kg183 CMNoNoNo5Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$750,000$750,000$Lien
Marcus SorensenPV Sharapovas (DET)RW284/7/1992No80 Kg180 CMNoNoNo4Pro & Farm1,600,000$1,600,000$1,600,000$1,600,000$0$0$No1,600,000$1,600,000$1,600,000$Lien
Michael ChaputPV Sharapovas (DET)C284/9/1992No90 Kg188 CMNoNoNo3Pro & Farm800,000$800,000$800,000$800,000$0$0$No800,000$800,000$Lien
Miikka SalomakiPV Sharapovas (DET)LW/RW273/9/1993No92 Kg180 CMNoNoNo2Pro & Farm950,000$950,000$950,000$950,000$0$0$No950,000$Lien
Nate SchnarrPV Sharapovas (DET)C212/25/1999Yes82 Kg191 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Ryan MacInnisPV Sharapovas (DET)C/LW/RW242/14/1996No87 Kg193 CMNoNoNo3Pro & Farm850,000$850,000$850,000$850,000$0$0$No850,000$850,000$Lien
T.J. TynanPV Sharapovas (DET)C/LW/RW282/25/1992No75 Kg173 CMNoNoNo5Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$750,000$750,000$Lien
Tomas NosekPV Sharapovas (DET)C/LW/RW289/1/1992No93 Kg188 CMNoNoNo4Pro & Farm1,250,000$1,250,000$1,250,000$1,250,000$0$0$No1,250,000$1,250,000$1,250,000$Lien
Trevor MoorePV Sharapovas (DET)LW253/21/1995No84 Kg178 CMNoNoNo6Pro & Farm900,000$900,000$750,000$750,000$0$0$No900,000$900,000$900,000$900,000$900,000$Lien
Victor MetePV Sharapovas (DET)D226/7/1998No85 Kg175 CMNoNoNo4Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$No1,000,000$1,000,000$1,000,000$Lien
Yannick WeberPV Sharapovas (DET)D319/23/1988No91 Kg180 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2125.9088 Kg185 CM4.14880,952$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Charles HudonTomas NosekMarcus Sorensen31122
2Kenny AgostinoMichael ChaputRyan MacInnis26122
3Trevor MooreJustin KirklandMiikka Salomaki23122
4Tomas NosekT.J. TynanKeegan Kolesar20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Victor MeteChristian Folin31122
2Yannick WeberJeremy Lauzon26122
3Guillaume BriseboisVictor Mete23122
4Christian FolinYannick Weber20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Charles HudonTomas NosekMarcus Sorensen55122
2Kenny AgostinoMichael ChaputRyan MacInnis45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Victor MeteChristian Folin55122
2Yannick WeberJeremy Lauzon45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Tomas NosekMarcus Sorensen55122
2Charles HudonKenny Agostino45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Victor MeteChristian Folin55122
2Yannick WeberJeremy Lauzon45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Tomas Nosek55122Victor MeteChristian Folin55122
2Marcus Sorensen45122Yannick WeberJeremy Lauzon45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Tomas NosekMarcus Sorensen55122
2Charles HudonKenny Agostino45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Victor MeteChristian Folin55122
2Yannick WeberJeremy Lauzon45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Charles HudonTomas NosekMarcus SorensenVictor MeteChristian Folin
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Charles HudonTomas NosekMarcus SorensenVictor MeteChristian Folin
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nate Schnarr, Justin Kirkland, Trevor MooreNate Schnarr, Justin KirklandTrevor Moore
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Guillaume Brisebois, Jeremy Lauzon, Victor MeteGuillaume BriseboisJeremy Lauzon, Victor Mete
Tirs de Pénalité
Tomas Nosek, Marcus Sorensen, Charles Hudon, Kenny Agostino, Michael Chaput
Gardien
#1 : Garret Sparks, #2 : Christopher Gibson
Lignes d'Attaque Perso. en Prol.
Tomas Nosek, Marcus Sorensen, Charles Hudon, Kenny Agostino, Michael Chaput, Justin Kirkland, Justin Kirkland, Trevor Moore, Ryan MacInnis, Miikka Salomaki, T.J. Tynan
Lignes de Défense Perso. en Prol.
Victor Mete, Christian Folin, Yannick Weber, Jeremy Lauzon, Guillaume Brisebois


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
Total00000000000000000000000000000000000.000000000000000000000000.00%000.00%0000.00%000.00%000.00%000000

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
00N/A0000000000
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
000000000
Derniers 10 Matchs
WLOTWOTL SOWSOL
000000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
000.00%000.00%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
00000000
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
000.00%000.00%000.00%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
000000


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



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance0.00%0.00%
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$ 1,850,000$ 1,835,000$ 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$ 0 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
34804321083322641641004022110321113478564021100512113086441132644947581896827513256782584986249195357471114592485020.16%3233888.24%11609273958.74%1306236055.34%661116256.88%213915401711553995516
34804321083322641641004022110321113478564021100512113086441132644947581896827513256782584986249195357471114592485020.16%3233888.24%11609273958.74%1306236055.34%661116256.88%213915401711553995516
Total Saison Régulière16086420166645283282008044220642226815611280422001024226017288226528988151621619216415026513416501698172498390611481422291849610020.16%6467688.24%23218547858.74%2612472055.34%1322232456.88%427930813423110719901032
Séries
342114700000564971165000002323010820000033267285610215801171816562319618820039619167249384741114.86%1001585.00%037473650.82%35672249.31%16832252.17%570401489155275140
Total Séries2114700000564971165000002323010820000033267285610215801171816562319618820039619167249384741114.86%1001585.00%037473650.82%35672249.31%16832252.17%570401489155275140