Little Stars
GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: Francois Cloutier | Morale : 40 | Moyenne d'Équipe : 63
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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
1Scott Kosmachuck (R)X100.007434777574657974597973666355504340700221550,000$
2Ilya Mikheyev (R)X100.007549806869767476767067616953494740690221500,000$
3Adam Tambellini (R)X100.006229756882756764687482486451454240670223600,000$
4Daniel O'regan (R)X100.006528786865767371727872565950454340670221400,000$
5Joakim Nygard (R)X100.005740807471625981727062618349524840670231500,000$
6Michael Mersch (R)X100.006735747273656370655875537055563840650241500,000$
7Sebastian Wannstrom (R)X100.006429707071676666717268506155563040650251700,000$
8Zach Budish (R)X100.007132776566646563677272566449493140650251725,000$
9Henrik Borgstrom (R)X100.006940746973687166717066606343417740650192500,000$
10Emile Poirier (R)X100.005430806974646662626380507146444340640222550,000$
11Jason Dickinson (R)X100.006632746863636971726669547344445840640213500,000$
12Shane Gersich (R)X100.006136776856667374767564405242426540630204600,000$
13Daniil Tarasov (R)X100.006232676168626066706566546055552840620251650,000$
14Roman Horak (R)X100.006139746758686669716762495348492640620252300,000$
15Matt Luff (R)X100.006335685871585857566981396543436426610192500,000$
16Justin Auger (R)X100.005727745665696559607072416846454440600222500,000$
17Radel Fazleev (R)X100.004933716453666361737465445142424940600203550,000$
18Tyler Wotherspoon (R)X100.007326857576767574537663786666474640730231975,000$
19Anton Cederholm (R)X100.006727846675707060487762804955445140700213750,000$
20Eric Knodel (R)X100.007434707167786567457260715562562940690261500,000$
21Reece Willcox (R)X100.006229757464647267496957746348464640660221375,000$
22Tucker Poolman (R)X100.006933707567625965606851645748484340640233600,000$
23Ville Pokka (R)X100.006437706360656366356662595444444540610221500,000$
Rayé
1Jonathan Dahlen (R)X100.005223646845504670625763536342416040580192500,000$
2Joey Anderson (R)X100.005741666462535953615460555440407740560182500,000$
3Givani Smith (R)X100.006544575865487658496155504840407640560182500,000$
4Rudolfs Balcers (R)X100.005735675550625351595465475841416140550191500,000$
5Jean-Christophe Beaudin (R)X100.004923615346526062606857385141416840540191500,000$
6Yakov Trenin (R)X100.006231625561585062505352395641415340530191500,000$
7Frederic Allard (R)X100.006247676355656166356044645341426540600192500,000$
8Lawrence Pilut (R)X100.006035685459586563416457545246435740580211500,000$
MOYENNE D'ÉQUIPE100.00633472666564656660676555604846504063
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
1Connor Knapp100.00705766757670646574677357532740690
2Dustin Tokarski100.00716781666675746764736768593040690
Rayé
MOYENNE D'ÉQUIPE100.0071627471717369666970706356294069
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Claude Julien82837474596155CAN5211,000,000$


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
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 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
Adam TambelliniLittle Stars (Dal)LW221994-01-01Yes185 Lbs6 ft4NoNoNo3Pro & Farm600,000$600,000$0$0$No600,000$600,000$
Anton CederholmLittle Stars (Dal)D211995-01-01Yes185 Lbs6 ft2NoNoNo3Pro & Farm750,000$750,000$0$0$No750,000$750,000$
Connor KnappLittle Stars (Dal)G261990-01-01No206 Lbs6 ft6NoNoNo1Pro & Farm900,000$900,000$0$0$No
Daniel O'reganLittle Stars (Dal)C221994-01-01Yes169 Lbs5 ft9NoNoNo1Pro & Farm400,000$400,000$0$0$No
Daniil TarasovLittle Stars (Dal)RW251991-01-01Yes185 Lbs6 ft0NoNoNo1Pro & Farm650,000$650,000$0$0$No
Dustin TokarskiLittle Stars (Dal)G271989-01-01No198 Lbs5 ft11NoNoNo1Pro & Farm900,000$900,000$0$0$No
Emile PoirierLittle Stars (Dal)LW221994-01-01Yes185 Lbs6 ft1NoNoNo2Pro & Farm550,000$550,000$0$0$No550,000$
Eric KnodelLittle Stars (Dal)D261990-01-01Yes216 Lbs6 ft6NoNoNo1Pro & Farm500,000$500,000$0$0$No
Frederic AllardLittle Stars (Dal)D191997-01-01Yes179 Lbs6 ft1NoNoNo2Pro & Farm500,000$500,000$0$0$No500,000$
Givani SmithLittle Stars (Dal)RW181998-01-01Yes205 Lbs6 ft2NoNoNo2Pro & Farm500,000$500,000$0$0$No500,000$
Henrik BorgstromLittle Stars (Dal)C191997-01-01Yes198 Lbs6 ft3NoNoNo2Pro & Farm500,000$500,000$0$0$No500,000$
Ilya MikheyevLittle Stars (Dal)RW221994-01-01Yes195 Lbs6 ft3NoNoNo1Pro & Farm500,000$500,000$0$0$No
Jason DickinsonLittle Stars (Dal)C211995-01-01Yes185 Lbs6 ft2NoNoNo3Pro & Farm500,000$500,000$0$0$No500,000$500,000$
Jean-Christophe BeaudinLittle Stars (Dal)C191997-01-01Yes196 Lbs6 ft1NoNoNo1Pro & Farm500,000$500,000$0$0$No
Joakim NygardLittle Stars (Dal)LW231993-01-01Yes179 Lbs6 ft0NoNoNo1Pro & Farm500,000$500,000$0$0$No
Joey AndersonLittle Stars (Dal)RW181998-01-01Yes190 Lbs5 ft11NoNoNo2Pro & Farm500,000$500,000$0$0$No500,000$
Jonathan DahlenLittle Stars (Dal)LW191997-01-01Yes181 Lbs5 ft11NoNoNo2Pro & Farm500,000$500,000$0$0$No500,000$
Justin AugerLittle Stars (Dal)RW221994-01-01Yes185 Lbs6 ft7NoNoNo2Pro & Farm500,000$500,000$0$0$No500,000$
Lawrence PilutLittle Stars (Dal)D211995-01-01Yes194 Lbs5 ft11NoNoNo1Pro & Farm500,000$500,000$0$0$No
Matt LuffLittle Stars (Dal)RW191997-01-01Yes190 Lbs6 ft2NoNoNo2Pro & Farm500,000$500,000$0$0$No500,000$
Michael MerschLittle Stars (Dal)LW241992-01-01Yes218 Lbs6 ft2NoNoNo1Pro & Farm500,000$500,000$0$0$No
Radel FazleevLittle Stars (Dal)C201996-01-01Yes192 Lbs5 ft11NoNoNo3Pro & Farm550,000$550,000$0$0$No550,000$550,000$
Reece WillcoxLittle Stars (Dal)D221994-01-01Yes184 Lbs6 ft3NoNoNo1Pro & Farm375,000$375,000$0$0$No
Roman HorakLittle Stars (Dal)C251991-01-01Yes170 Lbs6 ft0NoNoNo2Pro & Farm300,000$300,000$0$0$No300,000$
Rudolfs BalcersLittle Stars (Dal)LW191997-01-01Yes180 Lbs5 ft11NoNoNo1Pro & Farm500,000$500,000$0$0$No
Scott KosmachuckLittle Stars (Dal)RW221994-01-01Yes185 Lbs5 ft11NoNoNo1Pro & Farm550,000$550,000$0$0$No
Sebastian WannstromLittle Stars (Dal)RW251991-01-01Yes180 Lbs6 ft1NoNoNo1Pro & Farm700,000$700,000$0$0$No
Shane GersichLittle Stars (Dal)LW201996-01-01Yes175 Lbs5 ft11NoNoNo4Pro & Farm600,000$600,000$0$0$No700,000$800,000$900,000$
Tucker PoolmanLittle Stars (Dal)D231993-01-01Yes185 Lbs6 ft2NoNoNo3Pro & Farm600,000$600,000$0$0$No600,000$600,000$
Tyler WotherspoonLittle Stars (Dal)D231993-01-01Yes210 Lbs6 ft2NoNoNo1Pro & Farm975,000$975,000$0$0$No
Ville PokkaLittle Stars (Dal)D221994-01-01Yes205 Lbs5 ft11NoNoNo1Pro & Farm500,000$500,000$0$0$No
Yakov TreninLittle Stars (Dal)C191997-01-01Yes201 Lbs6 ft2NoNoNo1Pro & Farm500,000$500,000$0$0$No
Zach BudishLittle Stars (Dal)RW251991-01-01Yes223 Lbs6 ft3NoNoNo1Pro & Farm725,000$725,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3321.82191 Lbs6 ft11.67564,394$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
140122
230122
320122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
230122
320122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
160122
240122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
16012260122
24012240122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
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
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
Capacité20001000
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 JourCapacitéPopularité de l'Équipe
0 0 - 0.00%0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 1,862,500$ 1,510,000$ 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