WILKIES-BARRIE Penguins

GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: RS Guerin | Morale : 99 | Moyenne d'Équipe : 65
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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
1Buddy Robinson (A)83X100.007254856199787359526060635877675399690282750,000$
2Taylor Raddysh65X100.007249896287908660565859616063627199690222750,000$
3Markus Granlund (A)10X100.0058398563707981647561626864736863996802711,300,000$
4Stefan Noesen79X100.0076486765787269645862666365736871996802741,000,000$
5Riley Tufte (R)74X100.008455855899858756525553625863628199680223950,000$
6Steven Fogarty57X100.006548886385747562706159646273655699670273750,000$
7Nic Petan91X100.005439876864747367786662616769657199660253750,000$
8Gabriel Gagne85X100.006845826087798058545756596067647499660231750,000$
9Ryan Gropp93X100.006445865981848258545755565867647299660235900,000$
10Chase De Leo84X100.005640846167817459566059586169645399640241750,000$
11Manuel Wiederer89X100.005643895872777657535556595867645699630233750,000$
12Nick Henry (R)75X100.005242875659797854515353525461626499600212800,000$
13Nikita Soshnikov48X100.005335736169565261505858535953514298580261750,000$
14Gabriel Carlsson33X100.006545846188827859305857605165637999670232750,000$
15Brett Lernout55X100.007451875489858653305152574569656399660244750,000$
16Brandon Davidson6X100.006445876182767259305858605377695599660291750,000$
17Andreas Englund52X100.006351825881807757305656595167647399650242750,000$
18Josh Wesley62X100.006646855682737254305352554567646299620242750,000$
19Anton Cederholm (R)76X100.005940795080462950304444605050504499510252750,000$
Rayé
1Tim Schaller77X100.0072428363836572615359626761786846996702900$
MOYENNE D'ÉQUIPE100.00654584608076745950575760576763629965
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
1Anton Forsberg100.00756664827473757473757475815799680
2Mike Condon100.0076535180757476757476757884569968X0
Rayé
MOYENNE D'ÉQUIPE100.0076605881757476757476757783579968
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dave Hakstol75747574787866CAN539900,000$


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
Andreas EnglundWILKIES-BARRIE Penguins (PIT)D241/21/1996No86 Kg191 CMNoNoNo2Pro & Farm750,000$750,000$500,000$500,000$0$0$No750,000$Lien
Anton CederholmWILKIES-BARRIE Penguins (PIT)D252/21/1995Yes93 Kg188 CMNoNoNo2Pro & Farm750,000$750,000$500,000$500,000$0$0$No750,000$
Anton ForsbergWILKIES-BARRIE Penguins (PIT)G2711/27/1992No87 Kg191 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$Lien
Brandon DavidsonWILKIES-BARRIE Penguins (PIT)D298/21/1991No95 Kg188 CMNoNoNo1Pro & Farm750,000$750,000$750,000$750,000$0$0$NoLien
Brett LernoutWILKIES-BARRIE Penguins (PIT)D249/24/1995No97 Kg193 CMNoNoNo4Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$750,000$Lien
Buddy RobinsonWILKIES-BARRIE Penguins (PIT)RW289/30/1991No105 Kg198 CMNoNoNo2Pro & Farm750,000$750,000$500,000$500,000$0$0$No750,000$Lien
Chase De LeoWILKIES-BARRIE Penguins (PIT)C2410/25/1995No85 Kg175 CMNoNoNo1Pro & Farm750,000$750,000$750,000$750,000$0$0$NoLien
Gabriel CarlssonWILKIES-BARRIE Penguins (PIT)D231/2/1997No87 Kg196 CMNoNoNo2Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$Lien
Gabriel GagneWILKIES-BARRIE Penguins (PIT)RW2311/11/1996No85 Kg196 CMNoNoNo1Pro & Farm750,000$750,000$750,000$750,000$0$0$NoLien
Josh WesleyWILKIES-BARRIE Penguins (PIT)D244/9/1996No89 Kg191 CMNoNoNo2Pro & Farm750,000$750,000$500,000$500,000$0$0$No750,000$Lien
Manuel WiedererWILKIES-BARRIE Penguins (PIT)RW2311/21/1996No80 Kg185 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$Lien
Markus GranlundWILKIES-BARRIE Penguins (PIT)C274/16/1993No82 Kg183 CMNoNoNo1Pro & Farm1,300,000$1,300,000$1,300,000$1,300,000$0$0$NoLien
Mike CondonWILKIES-BARRIE Penguins (PIT)G304/27/1990No89 Kg188 CMNoYesNo3Pro & Farm2,400,000$2,400,000$2,400,000$2,400,000$0$0$No2,400,000$2,400,000$Lien
Nic PetanWILKIES-BARRIE Penguins (PIT)LW253/22/1995No80 Kg175 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$Lien
Nick HenryWILKIES-BARRIE Penguins (PIT)RW217/4/1999Yes86 Kg155 CMNoNoNo2Pro & Farm800,000$800,000$750,000$750,000$0$0$No800,000$
Nikita SoshnikovWILKIES-BARRIE Penguins (PIT)LW2610/14/1993No84 Kg180 CMNoNoNo1Pro & Farm750,000$750,000$750,000$750,000$0$0$NoLien
Riley TufteWILKIES-BARRIE Penguins (PIT)LW224/10/1998Yes107 Kg198 CMNoNoNo3Pro & Farm950,000$950,000$750,000$750,000$0$0$No950,000$950,000$
Ryan GroppWILKIES-BARRIE Penguins (PIT)LW239/16/1996No85 Kg191 CMNoNoNo5Pro & Farm900,000$900,000$900,000$900,000$0$0$No900,000$900,000$900,000$900,000$Lien
Stefan NoesenWILKIES-BARRIE Penguins (PIT)RW272/12/1993No93 Kg185 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
Steven FogartyWILKIES-BARRIE Penguins (PIT)C274/19/1993No95 Kg191 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$Lien
Taylor RaddyshWILKIES-BARRIE Penguins (PIT)RW222/18/1998No98 Kg191 CMNoNoNo2Pro & Farm750,000$750,000$500,000$500,000$0$0$No750,000$Lien
Tim SchallerWILKIES-BARRIE Penguins (PIT)C2911/16/1990No93 Kg188 CMNoNoNo0Pro & Farm0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2225.1490 Kg188 CM2.27845,455$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Stefan NoesenNic PetanBuddy Robinson31122
2Riley TufteMarkus GranlundTaylor Raddysh26122
3Ryan GroppSteven FogartyGabriel Gagne23122
4Nikita SoshnikovChase De LeoNick Henry20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Gabriel CarlssonBrandon Davidson35122
2Brett LernoutAndreas Englund34122
3Josh WesleyAnton Cederholm21122
4Gabriel CarlssonBuddy Robinson10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Stefan NoesenNic PetanBuddy Robinson55122
2Riley TufteMarkus GranlundSteven Fogarty45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Gabriel CarlssonBrandon Davidson55122
2Brett LernoutAndreas Englund45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Steven FogartyManuel Wiederer55122
2Chase De LeoGabriel Gagne45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Gabriel CarlssonBrandon Davidson55122
2Brett LernoutAndreas Englund45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Chase De Leo55122Josh WesleyAnton Cederholm55122
2Nick Henry45122Brett LernoutAndreas Englund45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Nic PetanStefan Noesen55122
2Markus GranlundBuddy Robinson45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Gabriel CarlssonBrandon Davidson55122
2Brett LernoutAndreas Englund45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Stefan NoesenNic PetanBuddy RobinsonRiley TufteBrandon Davidson
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Steven FogartyMarkus GranlundTaylor RaddyshJosh WesleyAnton Cederholm
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nic Petan, Buddy Robinson, Steven FogartyStefan Noesen, Riley TufteSteven Fogarty
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Josh Wesley, Anton Cederholm, Brett LernoutJosh WesleyAnton Cederholm, Brett Lernout
Tirs de Pénalité
Taylor Raddysh, Buddy Robinson, Nic Petan, Markus Granlund, Stefan Noesen
Gardien
#1 : Mike Condon, #2 : Anton Forsberg
Lignes d'Attaque Perso. en Prol.
Nic Petan, Stefan Noesen, Markus Granlund, Taylor Raddysh, Steven Fogarty, Riley Tufte, Riley Tufte, Chase De Leo, Gabriel Gagne, Nick Henry, Ryan Gropp
Lignes de Défense Perso. en Prol.
Gabriel Carlsson, Brandon Davidson, Brett Lernout, Andreas Englund, Josh Wesley


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$ 1,860,000$ 1,710,000$ 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
3480372701203126418777401517060111161011540221006020148866210526446472816106845916286099391089575216464372314922664818.05%3155383.17%41663280759.24%1424253556.17%682114459.62%202514431844572987496
3480372701203126418777401517060111161011540221006020148866210526446472816106845916286099391089575216464372314922664818.05%3155383.17%41663280759.24%1424253556.17%682114459.62%202514431844572987496
Total Saison Régulière160745402406252837415480303401202223220230804420012040296172124210528928145621221216811832572019861820179015043281286144629845329618.05%63010683.17%83326561459.24%2848507056.17%1364228859.62%40502886368911451974993
Séries
34734000001214-241300000610-432100000642612223401354021954816222227607414418211.11%34488.24%014224358.44%14627054.07%478455.95%183130176528743
Total Séries734000001214-241300000610-432100000642612223401354021954816222227607414418211.11%34488.24%014224358.44%14627054.07%478455.95%183130176528743